Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: One channel of the chamber received the prey damaged-skin-extracts from juvenile Pomacentrus moluccensis. The other compartment received an equal quantity of seawater control with no additional chemical cues (i. e. a control). Dye trials indicated stimulus flow was even in the chamber compartments, flowing through the chambers and exiting at the front. The stimulus moved through the compartment at 23±2. 5 mm. sec−1 and the chamber had been flushed after 4. 5 min. All trials were undertaken at a constant temperature of 27°C. Fish were not fed for two days prior to trials to standardize for satiation. Control trials, where untreated seawater only was injected into both channels were randomly interspersed among trials with skin extracts. These trials confirmed that the fish used each compartment in approximately equal frequency when no additional cue was present. At to the start of each trial, a fish was placed in the barricaded area at the front of the chamber and allowed to acclimate for a minimum of four hours. Before the removal of the barrier, 60 ml of seawater was drawn through each of the tubes and discarded to remove stagnant water. Another 60 ml of seawater was drawn through the injection tubes and retained. 15 ml of the stimulus was then injected into each tube simultaneously, followed by the 60 ml of seawater previously removed, to flush the stimuli into the respective chamber compartments. The barrier was slowly removed and the behavioral observations commenced. Trials occurred over eight min and stimuli were re-injected at four min intervals. After the trial ceased, fish were once again retained in the acclimation area, and chambers were left to flush for approximately one hour. The compartments into which the stimuli were injected were swapped and the trial was repeated. Following the injection of the stimuli and the removal of the barrier, the location of the fish within the chamber was recorded every five seconds. Only the time spent in the channels of the chamber were included in the analysis as fish from all treatment groups within the control trials (SW vs SW) and treatment (prey skin extract vs SW) trials spent on average, less than 0. 25 of their time in the acclimation area. As this time was minimal in the total time of the trial, removal of this period from the analysis was deemed to be acceptable. [SEP] Justify:

Output: The text contrasts the claim by discussing a study involving the behavioral response of juvenile fish (Pomacentrus moluccensis) to chemical stimuli, which suggests that fish can be affected by environmental changes, such as the introduction of skin extracts. This implies that fish may not be immune to impacts related to ocean conditions, directly opposing the claim that ocean acidification does not affect them.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: M4500, Iran) was used to measure the pedal volume of the rat up to the ankle joint before (volume A (VA), baseline) and 1, 2, and 3 h after (volume B (VB)) the sub-plantar administration of carrageenan, as explained formerly (25). Paw edema inhibition was calculated by (VB-VA)/VA formula, where VA stands for the volume of the right hind paw before injection of carrageenan, and VB stands for the volume of the right hind paw after injection of carrageenan. Ultimately, rats were euthanized and right hind paws were separated for biochemical tests (4). Biochemical tests Myeloperoxidase test Migration of neutrophils to the hind paws of rats was appraised by myeloperoxidase (MPO) kinetic-colorimetric assay (26). The measurement was performed by collecting paw tissue in ice-cold phosphate buffer saline (PBS; pH = 6) containing 0. 6% hexadecyltrimethylammonium bromide. After homogenization and centrifugation (10000 rpm, 30 min, 4 °C), the resulting supernatant of samples was evaluated for MPO activity spectrophotometrically at 400 nm (UV Spectrophotometer, Analytikjena, Germany). The results were presented as MPO activity. Lipid peroxidation assay Lipid peroxidation was measured by evaluating malondialdehyde (MDA) (27). Based on the kit protocol, after tissue homogenizing, 50 μL of supernatant or standard solutions were mixed with 300 μL reagent and heated at 90 °C for 30 min. Following cooling the mixture, the absorbance was evaluated at 532 nm using an Elisa reader (Multi -mode Reader, Botek, USA). The lipid peroxidation was articulated in terms of nmol MDA/mg protein. Statistical analysis The data were presented as mean ± SEM. Analysis of variance (ANOVA) followed by the Tukey post-hoc test was used. After obtaining the data from different experimental groups, they were analyzed using Graph8 software, and P values < 0. 05 were considered significantly different. [SEP] Justify:

Output: The text describes experimental procedures used to measure paw edema and neutrophil migration in rats, but it does not mention curcumin or turmeric, nor does it provide any information on anti-inflammatory properties. Therefore, it is irrelevant to the claim about curcumin.


Input: Task: pass the claim using the given text. Claim: The majority of space debris is made up of defunct satellites and fragments from past collisions or explosions in orbit. [SEP] Text: comments noted that critical components inducing break-ups are sometimes identified only years after the satellite has been operational, which could result in a large problem with large numbers of satellites, particularly with short production times involved. at 3. 102. This type of proposal was suggested by ESA in its comments to the proceeding, with respect to large constellations. comments at 3. 103. 104. 105. U. S. Practices at 4-1. 106. IADC Guidelines at § 5. 3. 2. 107. at 3 (noting that disposal of satellites in large LEO constellations by orbit raising should be avoided). 108. Order, 19 FCC Rcd at 11591, para. 60. 109. Direct retrieval of satellites implicates the need to assess rendezvous and proximity operations, and any risk of debris generation from those operations. 110. Order, 19 FCC Rcd at 11603-04, para 87. 111. . ,. SAT-MOD-20091119-00123, at 3-7; O3b. SES-LIC-20100723-00952, to S at 37-40;. SAT-LOA-20161115-00113, Letter from to Jose P. (April 11, 2017) at 7-8. The geostationary disposal requirement in our rules, intended for satellites orbiting at inclinations of approximately 15 degrees or less, can be viewed as an example of this type of disposal. 112. . SAT-PDR-20161115-00111, to S at 15-18. This approach appears to be more readily available for satellites operating at higher inclinations. 113. End-of-life Disposal in Orbits, & Carmen Pardini, Proceedings of the 9th for the Advancement of Space Safety, 2017, 114. See, e. g. , Inc. , Application for Launch and. SAT-LOA-20130626-00087, Exh. 43 at 2 (describing the nominal lifetime of its Flock 1 satellites as 11 months, with maximum lifetime of 18 months); Inc. ,. SAT-MOD-20150802-00053, Exh. 43 at 1 (describing expected operational lifetime of a series of additional satellites as approximately two years); Spire Global, Inc. , Application for Launch and. [SEP] Justify:

Output: The text does not address the composition of space debris directly. Instead, it discusses various regulations and practices regarding the disposal of satellites, the implications of operational lifetimes, and how certain guidelines relate to satellite behavior and debris generation. As such, it does not corroborate or contrast the claim but rather provides unrelated information.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: This exclusion was also due to fact that mixing of the cues could not be ruled out, as the water flowed out of the chamber. Dye trials indicated that some mixing could have been occurring in this small rear section of the chamber as the water moves out of the draining holes. Therefore, the time the fish were spending in this area was not necessarily indicative of a choice of cue, as fish could have been exposed to both the untreated seawater and the prey skin extract. The sequence of the olfactory preference tests for the control and CO2 treated fish were randomised throughout the duration of the experiment. Previous investigations, on different species, have indicated that testing in control water did not yield any differences to testing in CO2 treated water [15]–[16] and thus all olfactory trials were conducted using control water. Observations were undertaken from behind a black barrier to minimise disturbance to fish. Preparation of experimental stimuli. Prey cues were prepared using skin extracts from juvenile Pomacentrus moluccensis. Fish were euthanised by a quick blow to the head and placed in a clean petri dish. Vertical incisions were made along the flank of each fish using a scapel blade, and the specimen was rinsed in 15 ml of seawater. Two damselfish (TL; 22. 04±0. 65 mm; mean ± SE) were used for each skin extract solution, with eight superficial cuts of similar size, made along each side of the flank to standardize for size. Experiment 2 – Activity levels and feeding behaviour of Pseudochromis fuscus. Baseline activity levels of P. fuscus were recorded to discern potential differences between behaviours of fish treated with control seawater (current-day CO2 levels) and those treated with elevated levels of CO2 (mid and high CO2 treatments). Trials were carried out in 35 L aquaria (390×300×290 mm) and behaviour was recorded by video cameras to prevent observer-induced behavioural responses. A 50×50 mm grid was laid at the bottom of the aquarium and was submerged by a 10 cm hollow PVC pipe shelter placed at the centre of one end. This shelter had two exit holes which were facing the tank walls, with the curved edge of the pipe against the tank wall furthest from the video camera, which was placed on a tripod above the aquarium. [SEP] Justify:

Output: The text contrasts the claim by describing experiments on fish, specifically mentioning the activity levels and feeding behavior of the fish under different CO2 treatments. This suggests that fish are indeed affected by changes in CO2 levels associated with ocean acidification, which directly counters the claim that fish are immune to its effects.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Pulido-Moran M, Moreno-Fernandez J, Ramirez-Tortosa C, Ramirez-Tortosa M. Curcumin and health. Molecules. 2016;21(3):264,1-22. DOI: 10. 3390/molecules21030264. | PubMed | CrossRef | 6. . Bioavailability of curcumin and curcumin glucuronide in the central nervous system of mice after oral delivery of nano-curcumin. Pharm. 2016;511(1):415-423. DOI: 10. 1016/j. ijpharm. 2016. 07. 027. | Text | PubMed | CrossRef | 7. Sharma OP. Antioxidant activity of curcumin and related compounds. Biochem Pharmacol. 1976;25(15):1811-1812. DOI: 10. 1016/0006-2952(76)90421-4. | PubMed | CrossRef | 8. . Antioxidative effects of plant polyphenols: from protection of g protein signaling to prevention of age-related pathologies. Y Acad Sci. 2007;1095(1):449-457. DOI: 10. 1196/annals. 1397. 048. | Text | PubMed | CrossRef | 9. . Curcumin for malaria therapy. Res Commun. 2005;326(2):472-474. DOI: 10. 1016/j. bbrc. 2004. 11. 051. | PubMed | CrossRef | 10. Vera-Ramirez L, Pérez-Lopez P, Varela-Lopez A, Ramirez-. Curcumin and liver disease. Biofactors. 2013;39(1):88-100. DOI: 10. 1002/biof. 1057. | Text | PubMed | CrossRef | 11. Curcumin as a therapeutic agent in dementia: a mini systematic review of human studies. J. 2014;2014:174282,1-1. DOI:DOI: 10. 1155/2014/174282. | 12. . Neuroprotective properties of curcumin in Alzheimer's disease-merits and limitations. Chem. 2013;20(32):3955-3985. DOI: 10. 2174/09298673113209990210. | PubMed | CrossRef | 13. editors. [SEP] Justify:

Output: The text provides multiple references and studies related to curcumin but does not specifically address or provide evidence for the claim regarding anti-inflammatory properties. Therefore, it is considered irrelevant to the claim.


Input: Task: pass the claim using the given text. Claim: Mars rovers have provided invaluable data about the planet’s surface and potential for past life. [SEP] Text: Introduction 2. Consent in a digital environment 3. Addressing the power imbalance II. Legislative history III. Obligation to demonstrate consent (Art. 7 para. 1) 1. Scope of obligation a) Controller accountability b) Timing c) Inability to demonstrate consent 2. Obligation to demonstrate consent where there are multiple controllers 3. Proxy consent through automated tools IV. Formal requirements for consent requests (Art. 7 para. 2) 1. Separation of consent information from information on other matters a) Consent as approval of pre-formulated statement b) Clear and distinguishable information c) Invalidity of declaration d) Infringement of the GDPR through a faulty declaration 2. Clear and plain language 3. Intelligible and easily accessible form a) Practical ways to meet consent information requirements b) Consent information in an online context V. Withdrawal of consent (Art. 7 para. 3) 1. Right to withdraw consent 2. Effect of withdrawal 3. Withdrawal where processing is based on more than one legal ground 4. Form of withdrawal VI. Restrictions on “bundling” (Art. 7 para. 4) 1. “Bundling” in the context of consumer contracts a) Distinction between necessary and unnecessary data b) Conditionality c) Data as counter-performance d) Application of Art. 7 para. 4 in non-commercial contexts 2. Controller obligations 3. Genuine choice 4. Burden of proof 391–399 Art. 8 Conditions applicable to child's consent in relation to information society servicesThe authors would like to thank Ayça Atabey for her assistance in conducting the research for this 1. Art. 8 para. 1 a) Consent by a child b) Parental consent c) Information society services d) Remuneration e) Information society services offered directly to a child 2. Art. 8 para. 2: Parental consent verification requirements 3. Art. 8 para. 3: Enforcement 400–419 Art. 9 Processing of special categories of personal data András Jóri 400–419 Details I. Preliminary remarks II. Legislative history III. Analysis 1. “Special categories of personal data” (para. 1) 2. “Revealing” (para. 1) 3. “Shall be prohibited” (para. 1) 4. [SEP] Justify:

Output: The text provided is irrelevant to the claim as it discusses topics related to digital consent and data processing, with no mention of Mars, rovers, planetary data, or the potential for past life on Mars. Thus, it does not corroborate or contrast the claim in any meaningful way.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: To determine if predators exhibited a preference for prey skin extract, the mean proportion of time spent in the stream of water containing prey skin extract was compared against the null-expectation of 0. 5 for no preference. The mean time that individuals spent in the chamber channel with the prey skin extract was then compared among the control seawater and the two CO2 treatments, using a one-factor analysis of variance (ANOVA) and a post-hoc Tukey's HSD means comparison tests. Assumptions of normality and homogeneity of variance were explored using residual analysis and deemed to be satisfied. Movement and feeding behaviour were first compared among the three treatments with a multivariate ANOVA (). One-factor ANOVAs with planned comparisons were then used to further explore any significant differences in behaviours between the CO2 treated fish and non-treated fish. Residual analysis was used to determine whether data were normally distributed and homogenous in variance. A square-root transformation was applied in cases where data did not meet the assumptions of. of Pseudochromis fuscus to prey skin extracts Predators spent approximately equal proportions of time in both channels of the chamber when no additional odour was present (average proportions; Control = 0. 47±0. 08, Mid = 0. 47±0. 10, High = 0. 50±0. 10); Fig. 1). P. fuscus treated in control seawater exhibited an attraction to the prey skin extract, spending significantly more than half their time in the compartment containing this cue (t = 2. 621, df = 9, p = 0. 028). In contrast, P. fuscus treated in CO2 enriched water spent significantly less than half their time in the channels containing prey skin extract (Mid = 2. 577, df = 9, p = 0. 030; High = 2. 296, df = 13, p = 0. 039). P. fuscus exposed to CO2 enriched water spent approximately 20% less time in the water stream containing prey odor compared with control fish (F2,31 = 6. 854, p = 0. 003; Fig. 1). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 1. Response of Pseudochromis fuscus to prey skin extracts. Proportion of time (mean ± SE) spent in the channel receiving the prey skin extracts for P. [SEP] Justify:

Output: The text contrasts the claim by demonstrating that ocean acidification (as indicated by the CO2 treatments) impacts fish behavior. Specifically, the study shows that the fish species Pseudochromis fuscus exhibited significant behavioral changes when exposed to CO2 enriched water compared to control seawater. The fish spent less time in the presence of prey skin extracts when treated with higher CO2 levels, indicating that fish are not immune but rather affected by changes in ocean acidity.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: The molecular targets and therapeutic uses of curcumin in health and disease. New York: & Business Media; 2007. pp? ? ? DOI: 10. 1007/978-0-387-46401-5. 14. . The effect of the water on the curcumin tautomerism: a quantitative approach. . 2014;132:815-820. DOI: 10. 1016/j. saa. 2014. 05. 096. | PubMed | CrossRef | 15. -. Recent advances in the investigation of curcuminoids. Chin Med. 2008;3(1):11,1-13. DOI: 10. 1186/1749-8546-3-11. | PubMed | CrossRef | 16. Tapal A, Tiku PK. Complexation of curcumin with soy protein isolate and its implications on solubility and stability of curcumin. Food Chem. 2012;130(4):960-965. DOI: 10. 1016/j. foodchem. 2011. 08. 025. | PubMed | CrossRef | 17. . Validated LC/MS/MS assay for curcumin and tetrahydrocurcumin in rat plasma and application to pharmacokinetic study of phospholipid complex of curcumin. J Anal. 2006;40(3):720-727. DOI: 10. 1016/j. jpba. 2005. 09. 032. | Text | PubMed | CrossRef | 18. . Therapeutic and chemopreventive effects of nano curcumin against diethylnitrosamine induced hepatocellular carcinoma in rats. Sci. 2014;6(3):54-62. | 19. . New nanomicelle curcumin formulation for ocular delivery: improved stability, solubility, and ocular anti-inflammatory treatment. Ind Pharm. 2017;43(11):1846-1857. DOI: 10. 1080/03639045. 2017. 1349787. | PubMed | CrossRef | 20. Hunskaar S, Hole K. The formalin test in mice: dissociation between inflammatory and non-inflammatory pain. Pain. 1987;30(1):103-114. DOI: 10. 1016/0304-3959(87)90088-1. | Text | PubMed | CrossRef | 21. [SEP] Justify:

Output: The text does not provide specific information about curcumin's anti-inflammatory properties; rather, it cites various sources related to curcumin without directly supporting or contradicting the claim. Therefore, it is considered irrelevant.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: . org 2024 in to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using main navigation't sign in? Forgot your username? Enter your email address below and we will send you your username If the address matches an existing account you will receive an email with instructions to retrieve your username Login to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using 9, 2018 in The amazing analytics journey The three-stage process going from descriptive to predictive to prescriptive/pre-emptive analytics … and three final steps for implementation. : Share onShare on PRINT 10. 1287/LYTX. 2018. 04. 12 The future looks bright for companies that complete the analytics journey. The evolution of analytics integration in day-to-day business is widely considered a three-stage process, from descriptive analytics to predictive analytics to prescriptive analytics/pre-emptive analytics. Let’s review each stage. Descriptive analytics is the science and art of summarizing data that is logically grouped and structured in layers to create a seamless flow of insights that can be drilled down into, as well as be presented in a visually appealing way. It involves creating aggregates by establishing data linkages that provide a visual presentation to make it intuitive and easy to understand and use. The objective of descriptive analytics is to allow a business user to see the status of business as it really is, in the simplest manner possible, and then do a post-mortem to determine what drove the business to its current state. Most companies are already deploying this type of analytics across their business functions. There is still a long way to go before the job is complete, but the importance of implementation is clearly understood and there are no debates on its necessity and urgency. Predictive analytics is the next stage of this evolution. Simply put, this is all about saying what is going to happen in the future. Based on data from the past present, this field of analytics deals with making predictions about future events, as well as specifies the probability of the prediction turning out true. It involves statistical modeling and advanced analytical methods such as machine learning and artificial intelligence. [SEP] Justify:

Output: The text corroborates the claim by discussing predictive analytics, a domain where artificial intelligence (AI) and advanced analytical methods are utilized. It emphasizes how predictive analytics uses past and present data to forecast future events, specifically mentioning that it involves statistical modeling and machine learning, both of which are integral to AI applications in various fields.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: fuscus exposed to control (n = 10), mid CO2 (n = 10) and high CO2 (n = 14) water treatments. Letters above bars indicate post-hoc Tukey's HSD groupings of means at p<0. 05. Effects on activity levels and feeding behaviour of Pseudochromis fuscus Treatment in CO2 enriched water had a significant effect on movement patterns of P. fuscus (Pillai's trace4,44 = 0. 412, p = 0. 035; Fig. 2). P. fuscus in the high CO2 treatment displayed activity levels double that of fish kept in control seawater, crossing 269. 14±55. 76 (mean ± SE) lines compared to 139±16. 54 for the control fish (F2,22 = 3. 459, p = 0. 049 Fig. 2a). P. fuscus in the mid CO2 treatment showed activity levels (143. 50±43. 97 lines) similar to that of the control fishes. The cumulative distance moved away from shelter by P. fuscus in all treatments was not significantly affected by CO2 treatment (F2,22 = 0. 979, p = 0. 39). However there was a trend for P. fuscus exposed to the elevated CO2 treatments to move a greater cumulative distance than P. fuscus in kept in control seawater (Fig. 2b). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 2. Movement behaviour of Pseudochromis fuscus. A. Mean (± SE) activity levels (denoted by line crosses) and B. mean cumulative distance moved from shelter for P. fuscus following exposure to control (n = 10), mid CO2 (n = 8) and high CO2 (n = 7) water treatments. Significance from planned comparisons (control vs. high) at p<0. 05 = *. feeding behaviour of P. fuscus, was significantly affected by treatment in CO2 enriched water (Pillai's trace4,44 = 0. 402, p = 0. 047; Fig. 3). Time taken to respond to the introduction of food to the tank was significantly greater for the mid CO2 treated fish (172. 43±38. 52 sec) when compared to the controls (41. [SEP] Justify:

Output: The text contrasts the claim by demonstrating that the activity levels and feeding behavior of Pseudochromis fuscus, a fish species, were significantly affected by exposure to CO2 enriched water. This suggests that fish are not immune to the effects of ocean acidification, as indicated by the substantial differences in movement patterns and response times based on CO2 treatment levels.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Plant material, processing and extraction processturmeric (LKD) rhizomes were collected from the Lakadong region in Meghalaya, India (Location: 25° 11′ 0" North, 92° 17′ 0" East). The plant material was authenticated at the of India, Shillong, Meghalaya (India) and a voucher specimen (Specimen number. GIPS/2018/003) was preserved for future reference at the of. The rhizomes were cleaned, dried, and ground into coarse powder. The homogeneous powdered material (1 kg) was subjected to successive extraction for 72 h using solvents (2. 5 L) of increasing polarity (hexane, chloroform, ethyl acetate, and methanol) in a Soxhlet apparatus. The extracts obtained were filtered, concentrated using reduced pressure and labeled as hexane extract (LKDHE), chloroform extract (LKDCH), ethyl acetate extract (LKDEA), and methanol extract (LKDME). Residual solvents in extracts by gas chromatographyThe collected extracts were analyzed for residual solvent content using (GC) with a Headspace system (Clarus 690 Perkin Elmer). The injection Volume sampling rate was maintained at 12,50000pts/s with initial oven temperature at 40̊ C for 2 min followed by GC run (Ramp 1 at 5. 0 deg/min to 100 deg/min hold for 1 min and Ramp 2 10. 0 deg/min to 150 deg/min with hold time of 0. 00 min), offset at 100 µV. Extract samples were placed in vials, and the GC run was executed following the specified procedure (Fig. 1). The outcomes are displayed in Additional file 1: Fig. S1. Fig. 1Phytochemical evaluation of LKD extracts and characterization of curcumin. [SEP] Justify:

Output: The text is irrelevant to the claim because it describes the method of extracting various compounds from turmeric rhizomes without mentioning curcumin or its anti-inflammatory properties. It focuses on the extraction process and analysis of residual solvent content rather than providing information related to curcumin's effects.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: It relies on data to determine the causality of past events and uses these underlying factors to determine where the future is headed. This is where data scientists revel in using applied mathematics and technology to provide prophecies that can be logically constructed and debated. Businesses, however, need more than just insights. It is not enough to know why the past turned out as it did or to know what is likely to happen in the future based on the present. Businesses need more actionability, an urge to shape the future by knowing what factors are driving it, by being able to determine the effort in influencing these driving factors and the risks that lie underneath. Decision-makers want to simulate the future by playing out scenarios and then choosing a course of action that looks the most desirable to them. Welcome to what I call pre-emptive analytics, more widely known as prescriptive analytics. Tale of To better understand the three concepts, consider an illustrative scenario: A hotel chain wants to understand the state of its business and what factors are driving its business for better or worse. The hotel chain will need answers to the following questions: What is the revenue by hotel type, by customer category, by season and by a dozen other groupings? What is the composition of revenue from existing versus new customers? Why did a new customer come to my hotel? What made an old customer churn? These and more are answered by providing a structured grouping of past and present data through graphs and charts. That is descriptive analytics, often called basic business intelligence. As time passes, the hotel chain wants to determine answers regarding the future, such as: Given the customer demographics and trends affecting the business, what are the likely revenues in the next five years? How many new customers are likely to stay in our hotels in the next holiday season? What might be the occupancy rates at various price points? Such questions are answered by having the ability to see the patterns that have determined the past and present, and are likely to have a similar effect in the future. The process involves determining possible factors influencing business outcomes based on hypothesis and intuition first, and then testing these hypotheses through available data to determine which input affects what output and by how much. This requires people with advanced skill sets in statistics, creation of algorithms and using technology on large data sets to find answers faster and more accurately. This is what we call the field of predictive analytics. The story only gets better from here. [SEP] Justify:

Output: The text corroborates the claim by discussing predictive analytics, which is a significant application of AI. It describes how businesses use data and analytics to understand past events, predict future trends, and make informed decisions, aligning with AI's use in predictive analytics, a key area mentioned in the claim. Additionally, it emphasizes the need for advanced statistical skills and algorithms that are integral to AI-driven applications.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: 10±14. 70 sec; F2,21 = 4. 616, p = 0. 022; Fig. 3a), resulting in a delay in reaction by an average of two minutes. The effect of the high CO2 treatment on time to respond to food was less severe, with reaction times of just over one minute (65. 9 seconds) slower than control fish. The feeding strikes followed similar patterns; P. fuscus in the mid CO2 treatment exhibited significantly fewer (8. 14±2. 91) feeding strikes compared to control (21. 1±3. 96) and high CO2 treated fish (21. 43±5. 80; F2,21 = 3. 504, p = 0. 05; Fig. 3b). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 3. Feeding behaviour of Pseudochromis fuscus. A. Time to respond (seconds; mean ± SE) and B. feeding strikes (mean ± SE) of P. fuscus following exposure to control (n = 9), mid CO2 (n = 7) and high CO2 (n = 7) water treatments. Significance from planned comparisons (control vs. mid CO2) at p<0. 01 = *, p<0. 001 = **. DiscussionIn this study, the first to investigate the effects of ocean acidification on the behaviour of a predatory fish, we show that the ability of a common meso-predator to detect chemical cues produced by it's prey is hindered and activity levels are elevated by exposure to elevated CO2. P. fuscus naturally exhibited a preference for the olfactory cues of injured prey, however, following exposure to dissolved CO2 concentrations that could be widespread in the ocean by the end of the century [7], they displayed a slight avoidance to these cues. Predators treated in control water spent approximately 60% of their time in the chamber channel containing prey skin extracts, but this value fell to around 40% in CO2 treated fish. A change in reaction to olfactory cues is consistent with previous studies that have found that larval fish exposed to elevated CO2 were unable to discriminate between ecologically important cues, becoming attracted to cues they normally avoided [15], [18] and exhibiting reduced preference for favourable cues [14]. [SEP] Justify:

Output: The text contrasts the claim by providing evidence that ocean acidification negatively affects fish behavior, specifically stating that exposure to elevated CO2 alters the ability of a common predatory fish, P. fuscus, to detect chemical cues from its prey. It highlights that fish are not immune to the effects of ocean acidification, as their feeding behavior and reaction to olfactory cues are significantly impacted by increased CO2 levels.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: A: TLC chromatogram of LKD successive extracts; B, C, D: HPTLC fingerprinting of isolated curcumin from fingerprinting of purified LKD curcumin F MS spectra G 1H NMR of purified LKD curcumin H 13C NMR of purified LKD curcuminFull size imagePhysical evaluations and phytochemical studies of the LKD successive extractsPhysical properties of the LKD successive extractsVarious physical parameters were evaluated on the extracts including testing for organoleptic characters, nature of the extract, percentage yield; pH and solubility testing were determined [13]. Phytochemical evaluations and analytical process of curcumin from LKDPreliminary phytochemical screening, thin layer chromatography and quantification of total phenolic contentPhytochemical screening of the LKD successive extracts was conducted to identify various classes of phytochemicals [14]. Prominent phytochemical classes that produced positive test results underwent further verification using Thin-(TLC) methods. For extracts abundant in curcuminoids, TLC analysis was executed following established protocols [15]. The procedure encompassed preparing sample extracts for analysis, selecting the stationary phase, optimizing the mobile phase, developing the chromatogram, and spotting detection, all in accordance with established guidelines. The stationary phase for TLC employed pre-coated silica gel 60 F254 aluminum sheets (Merck Ltd. ), while the mobile phase was composed of a mixture of chloroform and methanol in a 9:1 ratio. Subsequently, the TLC plates were observed using short UV light (264 nm), long UV light (366 nm), and visible light, both before and after applying the detecting reagent. Furthermore, the optimization of High-Performance Thin-(HPTLC) fingerprinting and the analysis of the curcumin-rich crude fraction after isolation via column chromatography were performed using equipment, which included the sample applicator, visualizer, and 4 software. Furthermore, based on the results of the preliminary phytochemical screening and TLC analysis, further studies were conducted for the total phenolic and tannin content estimation using a UV–Visible spectrophotometer (Shimadzu-AA6300). The total phenolic content and total tannin content were determined using the Folin-Ciocalteu method with certain modifications [16]. [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily discusses analytical methods and physical evaluations of LKD successive extracts, including curcumin, without addressing or providing evidence related to curcumin's anti-inflammatory properties.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: Now that the hotel chain knows the past and the present, as well as how the future may turn out if things grow in an organic manner, it wants answers to more nuanced questions: Given an investment capability of $1 million, where should we deploy it to get the best return on investment? Which customers should be sent discount coupons to most improve those customers’ lifetime value to the hotel chain? Which promotions should the hotel chain run for the next holiday season? These questions are more open-ended. The managers are seeking options to determine the future, as well as recommendations regarding which options may work better than others. The answers involve optimizing under business constraints such as investments, time availability, irreversible choices or, in some cases, the need to make only a set of reversible choices under risk. In this instance, the development of a solution requires an analyst to understand the business scenario in great depth and codify its DNA to link inputs to potential outputs. The next step is to simulate output scenarios and place the power of an informed, data-driven choice in the hands of the decision-maker. Furthermore, it may be necessary to optimize by automating the process of choice itself so that human fallacies are removed from the decision-making. This is where the world of business analytics is headed. Maps tells us which route to take among the seemingly infinite choices to reach the airport on time, or, when Amazon makes the product recommendations when you login to your home page, or when your bank calls you to offer you a customized loan term, it is pre-emptive/prescriptive analytics at play. Every industry needs to exploit the power of pre-emptive analytics to improve decision-making, make fewer mistakes and grow faster. to does a company implement prescriptive analytics in real-world practice? The first and most crucial step is to determine what the business truly needs – what are the key performance indicators (KPIs) that the decision-makers want to improve? This process is not as simple as it sounds. Many businesses struggle to define the set of KPIs that matter the most to them. While every company wants to make more money and wants to do so faster and with less investment, the process of choosing KPIs requires a deeper look to determine what is truly needed and what is just “nice to have. [SEP] Justify:

Output: The text corroborates the claim by discussing the utilization of analytics—specifically pre-emptive and prescriptive analytics—in decision-making processes across industries. The mention of automated decision-making and the need for business analytics aligns with the idea that AI technologies are applied to enhance decision-making and predictive capabilities, which are critical aspects of predictive analytics.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: This diminished preference could indicate a reduced ability to recognise the olfactory cues presented and is supported by the observation that CO2 treated P. fuscus were more inquisitive and explored the entire chamber, compared to the more directional response towards the cue exhibited by control fish. P. fuscus inhabit topographically complex reef habitats, potentially limiting the effectiveness of locating prey via visual information over long distances [42]. Olfactory cues are suggested to be important in initiating a foraging response in predators, with the release of the prey skin extract resulting in a directional movement of predators towards prey [37]–[38]. A shift from attraction to repulsion of favourable prey cues due to ocean acidification could result in a decrease in the predatory activity of meso-predators and a reduced ability to respond to fluctuations in food availability. The potential exists for effects of elevated CO2 on predator behaviour to counteract the increased risk of mortality posed to prey species. It is possible that reduced attraction of predators to damage-released skin extracts of prey, or even slight avoidance of the cue, could enhance the survival of prey. However, previous research addressing the effects of elevated CO2 on newly-settled prey fishes indicates a dramatic switch from complete avoidance to strong preference for predator odour following exposure to CO2 enriched water [15]. In contrast, the present study found that following CO2 treatment predators spent 20% less time in a water stream containing the smell of injured prey. Although both predator and prey are affected by the elevated CO2, the repercussions of the loss of predator avoidance by the settling fish is likely to be more detrimental for prey survival than can be offset by a small reduction in predator response to prey olfactory cues. This supports earlier suggestions that ocean acidification is a potential threat to replenishment of reef fish populations [14]. Further investigations addressing the loss of olfactory information coupled with other traits that are important in the outcome of predator-prey interactions, such as other sensory modalities, boldness and locomotor performance, would provide a more detailed indication of the likely impacts to future reef fish populations. Avoidance of the beneficial olfactory cue of injured prey may be attributed to an alteration of neuro-sensory functioning following exposure to elevated CO2 [14], [17]–[18]. [SEP] Justify:

Output: The text contrasts the claim by demonstrating that ocean acidification has significant effects on fish behavior. It discusses how predators like P. fuscus exhibit changes in their response to olfactory cues after exposure to CO2, indicating that fish are not immune to the impacts of ocean acidification. Specifically, it highlights a reduction in time spent in the presence of injured prey cues due to changes in sensory functioning, suggesting that fish populations are affected by elevated CO2 levels.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Sampling was done by preparing all the successive extracts at concentration of 1 mg/mL. A series of dilution in the concentration range of 0. 02–0. 10 mg/mL was prepared for tannic acid (1 mg/mL stock solution) taken as reference standard. The total phenolics (TP), total simple phenolics (TSP) and total tannin content (TC) were estimated using the reported methods. All estimations were performed in triplicates and were statistically expressed as Mean ± S. E. M using linear regression equation. Isolation and characterization of curcumin from LKDThe analysis of the chloroform extract (LKDCH) through TLC and HPTLC confirmed a notable presence of curcumin. Consequently, an attempt was undertaken to isolate curcumin from this extract, employing a column chromatography approach. The wet packing method was adopted, wherein the column was packed with silica gel (#60–120 mesh, column grade, Merck Ltd. ), combined with exceptionally pure chloroform. LKDCH (50 g) was absorbed in chloroform and introduced into the column. The elution process was executed by employing a gradient mixture of methanol (MeOH) and chloroform (CHCl3), with a progressively increasing proportion of MeOH within CHCl3. The gradient levels were as follows: 1%, 2. 5%, 5%, 7. 5%, 10%, 15%, 20%, 40%, 60%, 80%, and finally, 100%. The eluates were collected in 25 mL fractions. values led to the pooling of corresponding eluates, which were subsequently concentrated using a rotary evaporator. The procedure yielded 105 fractions. Notably, fractions 50–55 exhibited distinct yellow single spots of curcumin, which were then combined and subjected to concentration. To enhance its purity, curcumin was purified through recrystallization in 100% acetone and stored at room temperature. The characterization and interpretation of the structure of the isolated curcumin was analyzed by sophisticated spectrometric techniques including FTIR (Bruker Alpha), 1HNMR and 13CNMR (Neo 500 MHz FT-NMR spectrometer), Mass spectrometer (-spectrometer) [17]. [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily discusses the methods for isolating and characterizing curcumin, rather than addressing its potential anti-inflammatory properties. It includes technical details about the extraction and purification of curcumin without providing any information or evidence related to its pharmacological effects, particularly anti-inflammatory properties.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: Computer vision techniques, including image processing and pattern recognition methods, play a vital role in analyzing the captured images or point cloud data and extracting relevant crack features [2, 3]. Machine learning algorithms, such as deep neural networks, can be trained on large datasets of annotated crack images to learn the characteristic patterns and textures associated with cracks. These models can then be deployed to accurately and efficiently detect cracks in real time or during post-processing. Furthermore, advancements in data processing and computing capabilities have facilitated the development of efficient algorithms for crack quantification. Once cracks are detected, various parameters such as crack length, width, orientation, and depth can be measured to assess the severity and extent of the damage. These quantitative measurements are crucial for making informed decisions regarding maintenance, repair, or rehabilitation strategies. The integration of remote sensing techniques, such as aerial or satellite imagery, with ground-based data acquisition systems has further enhanced the capabilities of crack detection and monitoring. By combining data from multiple sources, it becomes possible to obtain a comprehensive understanding of the structural health and performance of civil infrastructure over large areas. In this study, we propose an automatic pixel-level crack segmentation method to extract cracks at critical moments within the fracture videos. This method leverages image processing techniques and deep learning models to identify crack regions accurately. By segmenting cracks at the pixel level, we can obtain detailed information about crack geometry, size, and orientation, which are essential for subsequent analysis and prediction. Furthermore, we employ a Long Short-(LSTM) network, a type of recurrent neural network (RNN), to learn temporal patterns and dependencies within the crack segmentation masks across consecutive frames. The LSTM network is capable of capturing long-term dependencies and sequential information, making it suitable for modeling crack evolution over time. By leveraging the learned temporal patterns, the network can estimate how cracks will evolve and propagate in subsequent frames, enabling us to predict crack trajectories accurately. The paper is structured as follows. Section 2 provides an overview of the related work on automatic crack detection and segmentation algorithms. Section 3 outlines the methodology employed in this study. Details regarding the experiments, specimens, and dataset preparation are presented in Section 4. Section 5 presents the results and discussions. Finally, Section 6 concludes the paper and discusses potential extensions of the work. Advertisement 2. Related worksIn the field of crack visual detection, significant research efforts have been devoted to developing effective methods for crack segmentation and analysis. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of machine learning algorithms, such as deep neural networks, for image processing tasks, specifically in the area of crack detection and segmentation. The discussion of computer vision techniques, pattern recognition methods, and the leveraging of advanced neural networks indicates a direct application of AI in image recognition. Additionally, the mention of LSTM networks for modeling crack evolution over time aligns with the broader applications of AI in predictive analytics.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: The inability to distinguish between important olfactory cues, such as predator and non-predator odour [15], and reduced attraction to prey skin extract shown in this study, could be caused by impaired transfer of chemosensory signals across the olfactory epithelium or some other disruption to the olfactory nervous system. Changes in activity levels and feeding behaviour, which are not necessarily associated with olfactory sensitivity, suggest that the physiological mechanisms responsible occur at a cellular level within the nervous system. For example, cellular changes caused by acid-base regulation in CO2 exposed fish might affect neuronal pathways that mediate a range of functions, including olfactory discrimination and activity levels [17]. Detailed physiological studies would be required to test the possible mechanisms responsible for changes in olfactory responses and behaviour observed here and in previous studies. A similar reduction in response to alarm cues has been described in freshwater fishes exposed to weakly acidic conditions [43]–[45]. However, the mechanisms involved are different to those responsible for the changes in behaviour observed here for P. fuscus and in larval fish exposed to elevated CO2. In the freshwater examples, exposure of the alarm cue to mineral acid (e. g. H2SO4) causes a non-reversible structural change in the alarm cue molecule, rendering it unrecognizable to the olfactory system [43]. In contrast, we presented the alarm cue in control water and it elicited a response in control fish as expected. Consequently, the changed behaviour of CO2 treated P. fuscus was due to their exposure to CO2, not a change in the alarm cue itself. Furthermore, trials associated with another study [46] demonstrated that presenting the same prey skin extracts used here in either control or CO2-enriched water elicited the same strong avoidance behavior in larval damselfishes (DM Dixson, unpublished data] indicating that elevated CO2 does not cause a chemical change in the cue in saltwater. However, it should be noted that this particular experiment does not address the possibility that in acidified water the prey alarm cues utilized could be subject to structural changes. Hearing is also affected by elevated CO2, indicating responses to CO2 are not confined to the olfactory system [17]. This is further evidence that the various behavioural effects observed are not simply due to a change in the structure of chemical cues. [SEP] Justify:

Output: The text contrasts the claim by explaining how ocean acidification affects fish, particularly regarding their ability to process olfactory cues and reactions to alarm signals. It states that physiological changes in fish, specifically those exposed to elevated CO2, affect their chemosensory functions and behaviour. This directly counters the claim that fish are immune to the effects of ocean acidification, as it highlights the vulnerability of fish to changes in their environment.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Differential scanning calorimetry (DSC)The DSC 3 instrument (Mettler Toledo; Model no-ME-5140313) was employed to examine the melting point behavior of both the isolated and purified curcumin, as well as the standard curcumin. Samples were positioned in aluminum pans and subjected to scanning at a rate of 10 °C per minute within the temperature range of 20 °C to 300 °C under an inert nitrogen gas environment. For confirming the identity and purity of the isolated curcumin, a comparison was made between the endothermic peak of the isolated curcumin and that of the standard curcumin [18]. HPLC analysis for determination of the purity of isolated curcuminThe purity of isolated Curcumin from extracts was determined by HPLC (). consisted of a chromatographic pump, Injector, and UV detector. For HPLC separation, a reversed-phase C-18 column was used. The mobile phase was composed of acetonitrile-acidic Water (pH 3 adjusted by acetic acid) (80:20v/v) at a flow rate of 1 m/min. The run time was 10 min and the detection wavelength was set at 425 nm. The mobile phase was filtered using a 0. 2 nm millipore membrane filter. The sample injection volume was set at 20 μl. The purity was determined by comparing it with a chromatogram of the standard curcumin from SRL, India (95% Purity) [8]. The result is shown in Fig. 2. Fig. 2HPLC chromatogram of curcumin. A: Curcumin standard; B: Curcumin in LKDCH and purity of isolated curcumin from LKDCH; C: Curcumin standard; D Curcumin isolated from size imageNuclear magnetic resonance (NMR)The chemical identity of the LKCH isolated curcumin was further confirmed by proton NMR spectrum usingMultinuclear FT-NMR Spectrometer (ECX400 -Jeol 400 MHz, Japan). The samples were dissolved in dimethyl sulfoxide d6 (DMSO d6) as solvent. 20 µl of tetramethylsilane (TMS) was added to the sample solution as the internal reference. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses techniques for analyzing curcumin's purity and identity through differential scanning calorimetry (DSC) and high-performance liquid chromatography (HPLC), along with nuclear magnetic resonance (NMR) spectroscopy. It does not mention any anti-inflammatory properties of curcumin.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: An example of employing a pavement crack detection framework based on random forests (RF) is presented in the work by Shi et al. [9]. They proposed a framework called CrackForest, specifically designed to identify complex cracks in pavement images. The CrackForest framework utilized random structured forests along with integral channel features to define crack tokens that incorporate structural information. These crack tokens represented crack regions within image patches, with each patch measuring 16x16 pixels and containing labeled crack edges. The CrackForest method demonstrated its capability to extract complex cracks with arbitrary topologies, including corners, curves, and lines, on the road crack dataset known as CFD. By leveraging the RF technique and incorporating integral channel features, the framework exhibited robust crack detection performance. It provided an effective approach for automated identification of complex cracks in pavement images, offering potential benefits in road inspection and maintenance. Kim et al. [10] proposed a machine learning-based method for concrete crack recognition, which aids in identifying the presence and location of cracks from surface images. In recent years, with the increase in hardware computing power and data scale, deep learning algorithms have been widely applied to high-level feature learning in crack defect images. They have achieved remarkable results in the precise identification of complex crack defects in scenarios with complex background noise. Deep learning techniques, particularly convolutional neural networks (CNNs), have revolutionized crack detection and segmentation. These methods leverage the hierarchical representation learning capabilities of CNNs to automatically extract discriminative crack features. For instance, Zhang et al. [11] introduced a novel approach called CrackNet, which is based on Networks (CNN), for 3D asphalt pavement crack detection. In their studies, Zhang et al. compared the performance of CNN with other methods, including SVM and a 3D shadow modeling method. The results demonstrated the superiority of CNN over these alternative approaches. CNNs have the advantage of automatically learning discriminative features from raw data, allowing for more accurate and efficient crack detection in pavement images. Dung et al. [12] presented an algorithm for crack detection on concrete materials utilizing Networks (FCN). Their approach involved employing various CNN architectures, including VGG16, Inception-V3, and ResNet, as encoders to extract features. To evaluate the performance of the algorithm, Dung et al. conducted experiments on the Concrete-Crack-Ozgene dataset, which is a publicly available dataset commonly used for concrete crack analysis. [SEP] Justify:

Output: The text corroborates the claim by providing detailed examples of AI's application in image recognition, specifically in the context of crack detection and segmentation in pavement images. The discussion of using machine learning methods, particularly convolutional neural networks (CNNs), emphasizes the role of AI in recognizing complex patterns within images, which aligns with the claim about AI's extensive usage in applications like image recognition.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: Nevertheless, it is intriguing that two different acidification processes both affect behavioral responses of fish to alarm cues, with potentially important consequences in freshwater and marine ecosystems. Enhanced activity levels and altered feeding responses of P. fuscus are similar to the findings of the effects of elevated CO2 on newly settled fish. Munday and colleagues [14] found that following exposure to elevated CO2 Pomacentrus wardi were bolder, move further from shelter, were more active and less responsive to threats when compared to control individuals. Given that Pseudochromis fuscus themselves may be prey to larger predators, incidental movement further from shelter due to altered behaviour could increase their vulnerability. This effect however, remains to be assessed in the field to determine if changes to activity levels influence exposure of P. fuscus to larger predators. The olfactory abilities and activity levels of fishes have previously been investigated, however this is the first demonstration of the direct influence of elevated CO2 on a predator's response to food. Delayed feeding response of P. fuscus in mid CO2 could be attributed to their inability to detect the presence of food due to the disruption of their olfactory capabilities. For P. fuscus in the high CO2 treatment, a faster response than the mid CO2 treated fish and a similar number of feeding strikes to the control fishes might have occurred as a result of higher activity levels and greater behavioural boldness, which would facilitate food detection. Predatory fish use a variety of sensory cues to detect and locate prey, and although olfaction is often important [31], vision can also play an important role in prey detection and capture [47]. Increased activity in the high CO2 treatment could have resulted in the fish relying more on vision than olfaction to detect food. Consequently, a consideration of all sensory abilities and behaviour, not just olfaction, will be important in determining the outcome of predator-prey interactions under acidified conditions. In one of the only other studies to investigate the potential effects of ocean acidification on predator-prey interactions, Bibby and colleagues [16] found that reduced shell thickness in the intertidal gastropod Littorina littorea at low seawater pH was associated with increased predator evasion behavior, which might help offset the increased risk of mortality in thin-shelled individuals. [SEP] Justify:

Output: The text contrasts the claim by highlighting that fish are affected by ocean acidification, specifically in their behavioral responses to alarm cues. The text mentions that changes in activity levels and feeding responses of fish like P. fuscus and Pomacentrus wardi are observed due to elevated CO2, which indicates that fish behavior is influenced by acidification processes. This directly challenges the claim that fish are immune to the effects of ocean acidification.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: These precipitated nanosuspensions were then kept overnight under stirring to evaporate out the organic solvent. Characterisation and optimisation of Curcumin nanosuspensions (Cur-NS)Measurement of p4. Fig. 4TEM photomicrograph of Curcumin NanosuspensionFull size imageDrug entrapment efficiencyThe percentage drug entrapment was determined by the developed HPLC method. The Cur-NS were centrifuged at 11,000 rpm () for 15 min. After centrifuging, the supernatant was taken out and 1 ml of acetonitrile was added to the nanop7. 4 + 0. 5 percent Tween 80) at 37 °C under continuous magnetic stirring using IKA HS 7. At regular intervals, 2 ml of samples were collected and replaced with fresh media. The drug concentrations in the collected samples were then determined by the developed analytical HPLC method using the calibration equation y = 18,005. 5574x− 64979. 1884 R2 = 0. 991. [22]Formulation and optimisation of Cur-NS loaded gel (Cur-NS-nanogel)Preparation of plain gelCarbopol 940 was dissolved in water and stirred continuously untill it dissolves completely. The polymeric solution was then cross-linked chemically by drop-wise addition of triethanolamineoleate with continous stirring at constant rate until a clear homogeneous gel was obtained [26]. Optimization and evaluation of the topical gelThe prepared gels were then optimized based on varying concentration (0. 2–0. 5%) of the polymer, the alkali (triethanolamine) and its effect on the physicochemical properties e. g. pH, Viscosity, Gel strength and Spreadability [27]. pH: pH of the gel was measured using a digital pH meter (μ pH system 361, Systonics). The pH meter was first calibrated with three standard buffers (pH 4, 7 and 9). After calibrating the apparatus, the pH of freshly prepared Carbopol 940 gels were measured by dissolving and equilibrating the required amount of gel in distilled water. Viscosity: Viscosity of the prepared Gels were determined using Brookfield viscometer (DV-E Viscometer; Model No-) at 30 rpm/min using spindle No 64. [SEP] Justify:

Output: The text is irrelevant to the claim because it discusses the formulation and optimization of Curcumin nanosuspensions and the preparation of gel without providing any information about the anti-inflammatory properties of curcumin itself.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: The results of their study revealed that VGG16 outperformed Inception-V3 and ResNet in terms of crack image classification. Zhang et al. [13] proposed a novel context-aware deep convolutional semantic segmentation network for the effective detection of concrete surface cracks under various conditions. Advertisement 3. Methodology3. 1 OverviewFigure 1 illustrates the framework overview of the visual recognition and prediction of crack propagation trajectories in this study. Firstly, we established static and dynamic loading experimental systems using a hydraulic machine and SHPB (Pressure Bar), respectively. Concrete, rock, and coal standard specimens were subjected to destructive tests at different loading rates. The crack propagation process of different materials under various loading conditions was recorded using a high-speed camera. Subsequently, the FPN (Network) was employed to identify and extract cracks, while ConvLSTM (Short-Term Memory) was used for spatiotemporal modeling and analysis of the extracted cracks. Ultimately, predictive analysis of crack propagation in building materials was conducted. Figure 1. An overview of this work. 3. 2 FPN for crack segmentationPixel-level crack segmentation plays a crucial role in accurately identifying and delineating crack regions within construction materials. To tackle this task, we used the Network (FPN), a popular architecture that has shown remarkable performance in various semantic segmentation tasks, including crack detection [14]. The FPN architecture is designed to address the challenge of effectively utilizing multi-scale features for pixel-level segmentation. It leverages a top-down pathway and lateral connections to create a feature pyramid with multiple levels of abstraction. This allows the network to capture both local and global contextual information, enabling accurate and precise segmentation. The FPN module consists of two main components: the top-down pathway and the lateral connections. The top-down pathway involves upsampling the higher-resolution feature maps to match the dimensions of the lower-resolution feature maps. This process allows the network to propagate fine-grained details from higher levels to lower levels, enhancing the ability to capture small-scale crack features. The lateral connections, on the other hand, involve the fusion of feature maps from different levels of the pyramid. This fusion operation helps to preserve both local and global contextual information by combining features at different scales. By integrating multi-scale features, the FPN can effectively handle cracks of varying sizes and complexities, improving the accuracy of pixel-level segmentation. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of AI methodologies, specifically referencing architectures like FPN for image segmentation and predictive analysis of crack propagation. It highlights the application of these advanced techniques in recognizing and analyzing images of construction materials, thereby supporting the assertion that AI is utilized in image recognition and predictive analytics.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: Therefore, the outcome of predator-prey interactions under changed environmental conditions can be complex and difficult to predict. This study was carried out in laboratory conditions and thus, does not allow for a full evaluation of the potential effects of ocean acidification on the predatory ability and vulnerability of P. fuscus in their natural environment. Nevertheless, the effects observed suggest that the outcome of predator-prey interactions could be influenced by elevated pCO2 in nature. Furthermore, as these were short-term experiments involving acute exposure to elevated CO2, the potential for fish to acclimate or adapt to rapid ocean acidification was not tested. Munday and others [14] found that the settlement-stage fish exposed to elevated CO2 for four days exhibited almost identical impairment of their olfactory-mediated behavior as fish reared from birth at elevated CO2. Consequently, it does not seem likely that further increasing the duration of the CO2 treatments by days to weeks would have affected the results of this experiment. Long-term rearing experiments over months to years will be required to determine if either predators or prey can acclimate to elevated CO2 in the longer term. Munday and colleagues [14] also found that larval fish exhibited considerable variation in responses to acidification at approximately 700 ppm CO2, which suggests some capacity for selection of tolerant phenotypes. In contrast, P. fuscus did not exhibit an increase in individual variation in sensitivity at intermediate CO2 levels, even though the CO2 concentration (∼650 µatm) was similar to that at which variation in responses was observed in larval fishes. This study is the first to demonstrate the potential impacts of ocean acidification on a predatory fish, beyond the early life history stages. Combined effects of elevated CO2 on attraction to prey odour and changes in general activity levels suggest that even moderate increases in atmospheric CO2 affect the behaviour of meso-predators and the outcome of interactions between P. fuscus and their prey. Further investigations are required to determine and test the effects of changed behaviour on predator success in the field and the impact this has on prey populations. [SEP] Justify:

Output: The text contrasts the claim by discussing the effects of ocean acidification on predatory fish, specifically mentioning that elevated CO2 levels can influence their behavior and interaction with prey. It highlights that even moderate increases in atmospheric CO2 affect meso-predators like P. fuscus, indicating that fish are not immune to ocean acidification. The study suggests potential impacts on predator-prey dynamics due to the behavior changes in fish, which directly contradicts the assertion that fish are unaffected.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: The viscometer was calibrated using a standard solution of glycerine before all measurements. SpreadabilityTwo sets of glass slides with uniform dimensions were used to test the spreadability of the produced gels. One of the slides was covered with the gel formulation. The gel was sandwiched between the two slides in an area that was occupied by a distance of 7. 5 cm along with the slides when the other slide was positioned on top of the gel. The upper slides were given a 100-g weight to press the gel between them into a thin layer in a uniform manner. The excess gel that was sticking to the slides was scraped off after the weight was taken off. The two slides in place were securely fastened to a stand so that only upper slides could slip off freely under the force of weight tied on them. A 20 g weight was tied to the upper slide. The time taken for the upper slide to cover a distance of 7. 5 cm and get separated from the lower slide under the force of the weight, was noted. The experiment was performed in triplicates and the meantime was taken for calculation [27, 28]. The following formula was used to determine spreadability:$$S = \, m \, \times \, l/t$$where, S = spreadability, m-weight tied to upper slides, l- length of the glass slide and t- time taken in sec. Gel strengthThe strength of the gel formulations was determined using a (System, FD/1–077). The "gelling strength test" or compression mode of the was selected, and the test speed was set to 1. 0 mm/s. 50 points per second for the acquisition rate and 5 g for the trigger force were chosen. An aluminum probe of 7. 6 cm diameter was used for all the samples. The immersion probe was inserted into the gel during the test at room temperature. Gel strength, expressed in grams, was used to determine the force necessary to penetrate the gel [28]. Preparation of Cur-NS-nanogelwas prepared by adding the Carbopol 940 in the Cur-NS followed by cross linking with triethanolamine. The nanosuspensions were then continuously stirred until homogenous nanogels were formed. [SEP] Justify:

Output: The text does not address the claim about the anti-inflammatory properties of curcumin found in turmeric. Instead, it describes experimental procedures related to gel formulations and measurements of spreadability and gel strength without mentioning curcumin, turmeric, or any inflammatory response.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: In this work, we employ ResNet as a pre-trained backbone network to extract high-level features from the input crack images. These features are then fed into the FPN module, which generates a set of feature maps at different resolutions, each corresponding to a specific scale of the input image. To perform pixel-level crack segmentation, we employ a segmentation head on top of the FPN module. This head typically consists of convolutional layers followed by upsampling and downsampling operations. The convolutional layers further refine the features obtained from the FPN, while the upsampling and downsampling operations adjust the resolution of the features to match the input image size and the desired output segmentation map. During the training phase, we optimize the FPN network by minimizing the binary the Dice loss, and Intersection over Union (IoU) score. This loss function measures the discrepancy between the predicted crack segmentation map and the ground truth map at each pixel location. By backpropagating the error through the network, the FPN adjusts its parameters to improve the accuracy of crack segmentation. The FPN-based pixel-level crack segmentation method offers several advantages. Firstly, the multi-scale feature fusion enables the network to capture crack details at different resolutions, improving the segmentation accuracy for cracks of varying sizes. Secondly, the top-down pathway facilitates the propagation of fine-grained details, enhancing the network’s ability to capture small-scale crack features. Lastly, the FPN architecture is flexible and can be easily integrated with different backbone networks, making it adaptable to various crack detection scenarios. 3. 3 ConvLSTM for crack propagation prediction[15] architecture extends the traditional LSTM by replacing fully connected layers with convolutional layers. This modification enables the network to process spatially structured data, such as images or video frames, directly. By integrating convolutional operations into the LSTM framework, the ConvLSTM can learn spatial patterns and temporal dependencies simultaneously. layer consists of a grid of LSTM cells, where each cell maintains a hidden state and a cell state. The hidden state captures the learned representation of the crack segmentation masks, while the cell state retains the long-term memory of the temporal sequence. By processing each input frame sequentially, the ConvLSTM network can learn and update its hidden and cell states, capturing the evolution of cracks over time. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of convolutional neural networks (specifically ResNet and FPN) and ConvLSTM for tasks like pixel-level crack segmentation and crack propagation prediction. The mention of ‘processing spatially structured data, such as images’ indicates the application of AI in image recognition, supporting the claim that AI is widely utilized in such applications.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: However, the extreme attraction to predator odour by larval fishes under acidified conditions, compared to the relatively small avoidance of prey cues by meso-predators detected in this study suggest that it is unlikely that negative effects on predators will fully compensate for the increase in mortality rates of larval fish returning to the reef in an acidified ocean. 1. (2009) Ocean acidification: present conditions and future changes in a high CO2 world. Oceanography 22: 36–47. View 2. Hoegh-Guldberg O, Bruno JF (2010) The impact of climate change on the world's marine ecosystems. Science 328: 1523–1528. View 3. (2010) Ocean acidification, unprecedented, unsettling. Science 328: 1500–1501. View 4. , editors. 2007: the Basis. 996 p. Contribution of I to the Report of the on and. 5. Caldeira K, Wickett ME (2005) Ocean model predictions of chemistry changes from carbon dioxide emissions to the atmosphere and ocean. J 110: C09S04. View 6. -(2005) Ocean acidification due to increasing atmospheric carbon dioxide policy document 12/0. 1–68. View 7. Pelejero C, Calvo E, Hoegh-(2010) Paleo-perspectives on ocean acidification. Evol 25: 332–344. View 8. (2005) Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437: 681–686. View 9. -P, Middelburg JJ, et al. (2007) Impact of elevated CO2 on shellfish calcification. Lett 34: L07603. View 10. (2008) Impacts of ocean acidification on marine fauna and ecosystem processes. ICES J of 65: 414–432. View 11. Havenhand JN, Buttler F-(2008) Near-future levels of ocean acidification reduce fertilization success in a sea urchin. 18: R651–R652. View 12. (2009) Ocean acidification: the other CO2 problem. 1: 169–192. View 13. (2009) Coral reefs and ocean acidification. Oceanogr 22: 108–117. View 14. (2009) Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. [SEP] Justify:

Output: The text contrasts the claim by indicating that larval fishes are negatively affected under acidified conditions, as evidenced by their extreme attraction to predator odour and increased mortality rates. This suggests that fish, contrary to the claim, are not immune to the effects of ocean acidification.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Evaluation of Cur-NS-nanogelThe nanogels were evaluated in terms of appearance, homogeneity, pH, viscosity, and spreadability as mentioned in the earlier sections. Drug content in Cur-NS-nanogelThe drug content was measured by dissolving the measured amount of gel in acetonitrile. The dispersion obtained was filtered and analyzed at 425 nm using the developed HPLC method [29]. Drug loading efficiency (%) = (Experimental drug content/ Theoretical drug content) 100%Stability studiesThe accelerated stability studies were conducted in accordance to the ICH guidelines. The Cur-NS-Nanogel were kept at 4 °C, 25 °C and 40 °C and stability was observed for 30 days. The stability was observed in terms of change in color, appearance, pH, viscosity, and gel strength [30]Ex vivo skin permeation studyProcessing of rat skinThe albino Wistar rats were received from the animal house facility of Veterinary College, Khanapara. The animal study was conducted as per the guidelines after getting approval from the (Ref no: GIPS/IAEC/M. PH/PRO/10/2022). Experimental animals were feed with standard commercial pellets with free access to water ad libitum and housed according to standard laboratory environment by maintaining a 12 h day and night cycle at normal room temperature of 25 ± 1°C and 45–55% relative humidity. The rats (200–250 gm) were anesthetized using ketamine (30 mg/kg) [IP] anesthesia prior to excision of the skin and hairs were removed using hair clips. Excised skin were rinsed with 0. 9% saline water [31]. Permeation studyThe permeation through skin was studied using 20 ml modified franz diffusion cell assembly. The prepared rat skins were tied to the donor compartment such that the dermis faces the receiver compartment. The receptor compartment was filled with receptor media (PBS 7. 4 + 0. 5%Tween 80) and the donor compartment was loaded with 200 mg of Cur-NS Nanogel. The assembly was placed in a temperature controlled magnetic stirrer (IKA HS7) with temperature maintained at 37 ̊C. Drug permeation study was conducted for 24 h under continuous magnetic stirring. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the evaluation, formulation, and permeation studies of a Cur-NS-nanogel, without mentioning any anti-inflammatory properties of curcumin or turmeric.


Input: Task: corroborate the claim using the given text. Claim: AI is widely used in applications like image recognition, natural language processing, and predictive analytics. [SEP] Text: 2022;356:1292384. . Real-time image thresholding based on sample space reduction and interpolation approach. Journal of Computing in Civil Engineering. 2003;17(4):264-2725. Abdel-. Analysis of edge-detection techniques for crack identification in bridges. Journal of Computing in Civil Engineering. 2003;17(4):255-2636. Automatic bridge crack detection–a texture analysis-based approach. In: Networks in Pattern Recognition: 6th 3 2014, Montreal, QC, Canada, October 6-8, 2014. Proceedings 6. Midtown Manhattan, City: Publishing; 2014. 2037. Zalama E, Gómez-García-Bermejo J, Medina R, et al. Road crack detection using visual features extracted by Gabor filters. Computer-. 2014;29(5):342-3588. . An algorithm for concrete crack extraction and identification based on machine vision. IEEE Access. 2018;6:28993-290029. Automatic road crack detection using random structured forests. IEEE Transactions on Systems. 2016;17(12):3434-344510. Kim H. Crack and noncrack classification from concrete surface images using machine learning. Monitoring. 2018;18(3):725-73811. Automated pixel-level pavement crack detection on 3D asphalt surfaces using a deep-learning network. Computer-. 2017;32(10):805-81912. Dung CV. Autonomous concrete crack detection using deep fully convolutional neural network. Automation in Construction. 2019;99:52-5813. Zhang X. Concrete crack detection using context-aware deep semantic segmentation network. Computer-. 2019;34(11):951-97114. Lin TY, Dollár P, Girshick R, et al. Feature pyramid networks for object detection. In: Proceedings of the IEEE Conference on. City, United States: Institute for Electrical and (IEEE). 2017. 2515. Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in Processing Systems. 2015;28:802-81016. Khosravani MR, Weinberg K. A review on split Hopkinson bar experiments on the dynamic characterisation of concrete. Construction and Building Materials. 2018;190:1264-1283 information 1. [SEP] Justify:

Output: The text corroborates the claim by providing various examples of applications of AI in the context of image recognition and analysis, particularly in the detection of cracks in bridges and pavements. Specific references to 'automatic bridge crack detection' and the use of 'deep-learning networks' imply that AI techniques are indeed used for visual recognition tasks, aligning with the claim that AI is widely used in image recognition.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: 106: 1848–1852. View 15. (2010) Ocean acidification disrupts the innate ability of fish to detect predator olfactory cues. 13: 68–75. View 16. Bibby R, Cleall-(2007) Ocean acidification disrupts induced defences in the intertidal gastropod Littorina littorea. 3: 699–701. View 17. (2011) Ocean acidification erodes crucial auditory behaviour in a marine fish. Biol Lett. View 18. (2010) Replenishment of fish populations is threatened by ocean acidification. 107: 12930–12934. View 19. Paine RT (1966) Food web complexity and species diversity. 65–75. View 20. Hixon MA (1991) Predation as a process structuring coral reef fish communities. In: Sale PF, editor. The ecology of fishes on coral reefs. 507. Inc. , San Diego. 21. (2010) Comparative analysis of marine ecosystems: workshop on predator-prey interactions. Biol Lett. View 22. Beukers-(2004) The influence of prey abundance on the feeding ecology of two piscivorous species of coral reef fish. J 299: 155–184. View 23. (2010) Predators reduce abundance and species richness of coral reef fish recruits via non-selective predation. 29: 527–532. View 24. (1997) Effects of a predatory fish on the recruitment and abundance of Caribbean coral reef fishes. 148: 11–21. View 25. (2004) Odd species out as predators reduce diversity of coral-reef fishes. Ecology 85: 2933–2937. View 26. (2006) The predation gauntlet: early post-settlement mortality in reef fishes. 25: 19–22. View 27. Carr M, (1995) Predation effects on early post-settlement survivorship of coral-reef fishes. 124: 31–42. View 28. (2002) Competition for shelter space causes density-dependent predation mortality in damselfishes. Ecology 83: 2855–2868. View 29. (2010) Size-selectivity of predatory reef fish on juvenile prey. 399: 273–283. View 30. Hara TJ (2006) Feeding behaviour in some teleosts is triggered by single amino acids primarily through olfaction. [SEP] Justify:

Output: The text contrasts the claim by providing multiple pieces of evidence that show ocean acidification negatively impacts fish. It specifically mentions that ocean acidification disrupts fish's innate abilities to detect predator cues and erodes auditory behavior crucial for their survival. Furthermore, it states that replenishment of fish populations is threatened by ocean acidification, indicating that fish are indeed affected, contrary to the claim that they are immune.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: The purified curcumin was lyophilized and characterized by NMR, FT-IR, Mass and UV–Visible spectrophotometer. The melting point of the compound was observed at 181 °C and the UV–visible spectrum with λmax was recorded at 425 nm. IR bands (υ cm−1) showed the presence of prominent functional groups of curcumin at 3653 (–OH), 2979 (C–H), 1625 (C = C), 1264 (C–O–C), 1026 (C-O–H). 1HNMR spectrum (400 -d6) produces prominent proton peaks (δ ppm) at 3. 837 (s, 6H, OCH3), 6. 056 [s, 1H, C(OH) = CH], 6. 777 (d, 2H, 2,6-H), 6. 833 (d, 2H), 7. 160 (d, 2H), 7. 325 (s, 2H), 7. 567 (d, 2H, 1,7–H), 9. 667 (br s, 2H, phenolic –OH). Chemical shift with δ value at 3. 837 depicted a singlet peak which corresponds to the existing of two methoxy groups; whereas, a sharp δ value at 9. 667 represent the presence of phenolic hydroxy group. The two aromatic proton signals at δ value region of 6. 833 and 7. 160 each of them integrated for four protons diagnostic for two identical para-substituted benzene rings. 13C NMR spectrum (125 ) represents distinct carbon peaks (δ ppm) at 55. 60, 100. 79, 111. 29, 115. 64, 121. 00, 123. 02, 126. 26, 140. 63, 147. 91, 149. 27, 183. 12. 13C NMR chemical shift with δ value at 55. 60 clearly signify the carbon atom corresponding to methoxy group; whereas, δ value at 183. 12 depicted the carbon atom corresponding to enol and keto group. Furthermore, the mass spectra (TOF–MS-ES+) depicted that the base peak at m/z 177. 056 and a molecular ion peak [M + H]+ at 369. 135 was detected. [SEP] Justify:

Output: The text provides a detailed characterization of purified curcumin using various analytical techniques such as NMR, FT-IR, and mass spectrometry. However, it does not mention any information about the anti-inflammatory properties of curcumin, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Most current AI technologies are specialized and focused on specific tasks, rather than general intelligence. [SEP] Text: . org 2024 in to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using main navigation't sign in? Forgot your username? Enter your email address below and we will send you your username If the address matches an existing account you will receive an email with instructions to retrieve your username Login to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using 19, 2020 in AI Artificial general intelligence: What to expect and when : Share onShare on PRINT 10. 1287/LYTX. 2020. 05. 05 Many experts expect that today’s artificial intelligence will eventually evolve into artificial general intelligence (AGI), a point at which computers meet or even exceed human intelligence. totally agree, I would also contend that this evolution will happen sooner rather than later. Why? To answer that question requires a bit of background on AGI, beginning with defining what AGI is (and isn’t). Artificial general intelligence seeks to solve a broad spectrum of problems that intelligent human beings can solve. This is in direct contrast to narrow AI, which is what is represented by most of today’s AI. Narrow AI uses AI techniques to exceed human abilities in a specific problem area. Put another way, AGI is all the expectations of AI come true. Unfortunately, we don’t really know what intelligence is. We can’t even say for sure whether there are types of intelligence that are different from human intelligence. While AI encompasses many techniques that have been used with great success on specific problems, AGI is more nebulous. This makes it incredibly difficult to develop software that solves a problem where the techniques are not known, and no concrete problem statement exists. AGI are several approaches to creating AGI. It might be developed by combining today’s narrow AI capabilities and amassing huge computational power. It might be generated by replicating the human brain, either by simulating the neocortex’s 16 billion neurons or by uploading content from scanned human minds. It might be produced by analyzing human intelligence, defining a “cognitive model” and implementing it with procedural language techniques. [SEP] Justify:

Output: The text corroborates the claim by discussing the distinction between narrow AI and artificial general intelligence (AGI). It states that 'narrow AI uses AI techniques to exceed human abilities in a specific problem area,' which supports the idea that current AI technologies are indeed specialized and focused on specific tasks rather than possessing general intelligence.


Input: Task: contrast the claim using the given text. Claim: Ocean acidification only affects animals with hard shells, and fish are immune. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-4512535/v1This work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this latest preprint versionAbstractsplicing is a fundamental mechanism of gene expression regulation that increases the mRNA diversity expressed from the genome and can be partially regulated by the circadian clock. The time-dependent production of transcript isoforms from the same gene facilitates coordination of biological processes with the time of day and is a crucial mechanism enabling organisms to cope with environmental changes. In this study, we aim to determine the impact of future ocean acidification conditions on circadian splicing patterns in the brain of fish, while also accounting for diel CO2 fluctuations that naturally occur on coral reefs. in the control group exhibited a temporal splicing pattern across the 24-hour period, however, these splicing events were largely absent in fish exposed to either stable or fluctuating elevated CO2 conditions. Furthermore, the molecular responses were influenced not only by an overall increase in CO2 concentration but also by its stability, with 6am and 6pm being key timepoints when the majority of the aberrant splicing events were identified. We found that fish in fluctuating CO2 conditions exhibited increased plasticity in transcriptional regulation by varying the proportion of transcript isoforms depending on the time-of-day. This was especially notable for genes associated with neural functioning. findings suggest that fish rely on different molecular mechanisms to respond to elevated CO2 exposure in stable and fluctuating conditions. Periodic variation in CO2 levels in the fluctuating CO2 treatment might enable fish to rely on feed-forward mechanisms to synchronize neural functions with external environmental conditions. Such interconnectedness between external pH changes and transcriptional regulation via alternative splicing may provide fish in fluctuating CO2 environments with greater flexibility in biological responses, which may alleviate sensory and behavioural impairments enabling them to better cope with future ocean acidification conditions. Diel CO2 fluctuationscircadian rhythmalternative splicingtranscriptomicsspiny damselfishcoral reefFiguresFigure 1Figure 2Figure 3Figure 4Figure 5BackgroundOcean acidification (OA), one of the aspects of global change, has been shown to have adverse effects on numerous marine organisms due to its impact on diverse biological processes [1, 2, 3]. [SEP] Justify:

Output: The text contrasts the claim by discussing the impact of ocean acidification on fish, indicating that they are affected by fluctuating CO2 conditions. It explains that fish exhibit changes in their molecular responses, highlighting that even fish are influenced by elevated CO2 levels, and their transcriptional regulation is altered in response to these conditions. This directly contradicts the claim that fish are immune to the effects of ocean acidification.


Input: Task: pass the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: All these analytical spectroscopic features are in line with the data reported in the literature thus signifying the identity of curcumin isolated from Lakadong rhizome [17, 40, 41]. The results are shown in Fig. 1. Formulation of Curcumin loaded nanosuspensionHomogenous nanosuspensions were obtained by the precipitation-sonication method. The precipitation method of nanosuspensions preparation is instantaneous, straightforward and easy [42]. Characterization of curcumin NSP0. 2 ± 0. 1, indicating suitable size and distribution. From the study, the of the formulations was found to be − 2. 92 ± 0. 2 mV. Optimization of the Cur-NSThe nanosuspensions were optimized by using drug concentration, ratio of organic phase to aqueous phase, Polymer (PLGA) concentration, and stabilizer (Poly vinyl alcohol) concentration as the variables. The effects of these independent variables on the dependent variables (p0. 25% and PVA concentration of 0. 6% were considered as optimized variable conditions as shown in Table 3. F3, which was the optimized NS, was found to have p157. 1 ± 2. 4 and polydispersity index 0. 132 ± 0. 052. Table 3 Formulation table for optimized (Cur-NS)Full size tableTransmission electron microscopy (TEM)The morphology and size of the formulations were observed by TEM studies. The nanop98. 52% ± 0. 2 which can be considered sufficient. In vitro drug releaseIn vitro release behavior of Curcumin from the optimized Cur-NS was observed for 24 h. A sustained drug release rate was observed with almost 80% drug being released in initial 4 h indicating an initial burst release followed by sustained release upto to 90. 0 ± 1. 6% in 24 h. Preparation of Cur-NS based topical gelHomogenous nanogels were obtained by adding the Carbopol as the gelling agent in the optimized Cur-NS, followed by cross linking by addition of triethanolamine as the alkali. Optimization and evaluation of the topical gelEvaluation of the Cur-nanogelsThe Cur-Nanogel was optimized by observing the effect of varying concentration (0. 2–0. 5%) of the Carbopol and alkali (triethanolamine) and its effect on the physicochemical properties e. [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily discusses the analytical and characterization aspects of curcumin and its formulation into nanosuspensions and gels. There is no mention of anti-inflammatory properties or any related effects of curcumin.


Input: Task: corroborate the claim using the given text. Claim: Most current AI technologies are specialized and focused on specific tasks, rather than general intelligence. [SEP] Text: To provide an example that combines today’s narrow AI capabilities and amasses huge computational power, look no further than generative pre-trained transformer 3 (GPT-3). A monumental achievement from OpenAI that generates text, GPT-3 possesses a library that contains many billions of words and phrases, as well as their relationships to other words and phrases. GPT-3 has been so successful that OpenAI, concerned about the potential for its misuse, has not made it public. But while GPT-3 seems smart, few contend that it understands the words it is using. Still, GPT-3 does demonstrate that you can fool a lot of people a lot of the time if you have enough data and computer power. Similarly, while replicating the human brain by simulating the neocortex’s neurons can generate AGI, the algorithms of today’s artificial neural networks have very little to do with the way in which biological neurons actually work. Despite these limitations, numerous massive AGI projects are currently underway. These include DeepMind, an Alphabet (Google) subsidiary; OpenAI, where Microsoft has invested $1 billion; and Google Brain, with its open source project TensorFlow. and virtually all large companies also have some sort of AGI research, and smaller projects abound. Difficulties and home in on an AGI solution, I contend most narrow AI falls short of the capabilities common to any three-year-old. The average three-year-old playing with blocks understands that objects exist in a real world, time moves forward, and blocks have to be stacked up before they can fall down. The basic limitation of all AI is that these systems are unable to comprehend that words and images represent physical things that exist and interact in a physical universe, and that causes have effects with the comprehension of time. These basic underlying problems have yet to be solved, perhaps because it is difficult to get major funding to solve problems that any three-year-old can solve. I have written extensively that the risks from AGI superminds is very real, but calamity is not inevitable. AGIs are necessarily goal-directed systems and will exceed whatever objectives we set for them. At least initially, we can set those goals for the benefit of humanity, and AGIs will provide tremendous benefit. If AGIs are weaponized, on the other hand, they will likely be efficient in that realm, too. [SEP] Justify:

Output: The text corroborates the claim by discussing the limitations of today's AI, particularly in relation to general intelligence. It emphasizes that systems like GPT-3, while impressive, do not understand the words they generate, indicating a specialization in specific tasks rather than the broader understanding associated with general intelligence. The author also notes that current AI falls short of cognitive capabilities as basic as those of a three-year-old, reinforcing the notion that most AI technologies today are narrowly focused.