Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: If the building stock can be shown to cause health problems that can be traced to inadequate ventilation, then the government agencies will try to improve the situation by requiring higher ventilation rates. On the other hand, if air leakages through the building envelopes provide ample contributions to the ventilation of the building stock, in addition to the controllable ventilation rates, then the required ventilation rates need not be as stringent because the total ventilation rate will be sufficient anyway. The point here is to highlight plausible dependencies on average, even though there may be a wide spectrum of properties in the building stock. Thus, changes in the properties of the building stock will lead to changes in the ventilation requirements recommended by government agencies. The EPBD objective to transform the building stock to NZE- buildings with tighter building envelopes should, with the above logic, lead to a more stringent requirements for ventilation rates [8]. However, as mentioned in the Introduction, the “energy efficiency first” principle in EPBD [12] pushes other incentives towards their minimum legal limits when they are in conflict with the efforts to improve the energy performance of buildings. Maintaining a good indoor air quality by ventilation is such an incentive, and therefore ventilation rates will be pushed towards their minimum legal limits. As a consequence, in the coming EPBD transformation of the building stock, the minimum legally required ventilation rates play a critical role as counterbalances to prevent a decline in indoor air quality. The required ventilation rates will probably need to be increased to maintain the present levels of indoor air quality in the building stock. It is therefore doubly worrying that the ventilation requirements in the standards on the European level recently have been lowered as shown in Table 2. For example, in a standard 10 m2 office for one person, the required ventilation rate (qtot) is lowered by 43% from 10. 5 L⋅s−1 in the old guideline CEN-EN15251:2006 [61] to 6 L⋅s−1 in the new guideline CEN-EN16798:2019 [62]. The change corresponds to recommending 30% dissatisfied un-adapted judges in the new guidelines as compared to 20% in the old guidelines. The guidelines in the provide the “floor” upon which the legal requirements of the member countries rests. Lowering the required ventilation rates in the opens for a corresponding lowering in the legislation of the member states. [SEP] Justify:

Output: The text contrasts the claim by highlighting that changes in ventilation requirements and standards may lead to a decline in indoor air quality. It mentions that the required ventilation rates could be lowered, which could compromise the efforts to maintain good indoor air quality. Consequently, the assertion in the claim that ventilation systems improve air quality by circulating fresh air is contradicted by the implications of reduced legal ventilation standards.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: These compounds can be further developed and assessed as phytoformulations against SARS-CoV-2 infection [8]. 2. 4 Siddha medicineDuring molecular docking and simulation analysis for the prevention and cure of COVID-19 infection on some phytoconstituents of Siddha medicine were determined as potential candidates. Among them orientin, bis-andrographolide, cucurbitacin B, cucurbitacin E, isocucurbitacin B, vitexin, berberine, bryonolic acid, piperine and magnoflorine were identified as potential lead molecules that have been shown to possess the ability to interact with the components that block the viral replication in SARS-CoV-2. Moreover, the immune-enhancing properties of these compounds without any adverse side effects could provide natural immune power to resist COVID-19 infections [14]. Several plants have been found to act on the ACE-2 receptor, which could become promising antiviral agents and can help in combatting COVID-19 pandemic. Rheum palmatum, Polygonum multiflorum, Cerasus avium, Alcea digitata, Rubia tinctorum, Citrus aurantium, Berberis integerrima, Peganum harmala and Allium sativum have the potential to act on the ACE-2 receptor and are well-known for blocking the transmission or entry of Coronoviruses. These plants can possibly be used for the combinational therapeutic management of COVID-19 by inhibiting various protein targets of SARS-CoV-2 (Table 1) [15]. Traditional medicinesMedicinal plantsAntiviral compoundsVirus1. The list of traditional medicines for antiviral activities. 2. 5 Thai traditional medicineAmong 122 Thai traditional medicines, Boesenbergia rotunda extract and its compound, known as panduratin A exhibited the potent anti-SARS-CoV-2 activity by using the high-content imaging system coupled with the plaque reduction assay. Treatment with Boesenbergia rotunda extract and panduratin A after viral infection drastically suppressed SARS-CoV-2 infectivity in Vero E6 cells with IC50 of 3. 62 μg/mL (CC50 = 28. 06 μg/mL) and 0. 81 μΜ (CC50 = 14. [SEP] Justify:

Output: The text does not directly address the claim regarding the derivation of traditional medicines from plants used by indigenous cultures. Instead, it focuses on the antiviral properties of certain medicinal plants and their potential applications in combating COVID-19, which does not specifically relate to indigenous practices or the origins of these medicines.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Next, we decoded the series of the hidden states globally by maximizing the conditional probability of the whole sequence P(ZT | XT). The optimal path was found using the Viterbi algorithm with estimated parameters. The hidden states were matched with sleep and wake states. The state with higher estimated mean heart rate, µHR, and mean activity level, µACT, represented the active status of the participants, and related to a waking state. On the other hand, the state with lower estimated mean heart rate and mean activity level represented the resting status, which was related to a sleeping state (heart rate variance, σ2HR, and activity level variance, σ2ACT). Implementation of the ModelsAfter preprocessing, the data were ready for implementation of the HMMs. For each participant, we plotted the kernel density estimates of heart rate and of log-transformed step count (Figure 2) to explore suitable prior joint emission distributions. From the kernel density plot of heart rate, the overdispersed and nonsymmetric observations suggested a bimodal distribution, which may be modeled by a mixture model, and very likely a two-component Gaussian mixture; however, mixture models do not take temporal dependency into account, which prompted us to adopt the hidden Markov model. A Poisson distribution is a natural choice for modeling count data; however, the step count ranged from 0 to 160. Since it would have been computationally expensive to estimate, especially for our long sequence, we took the log transformation of step count and found that they were also distributed marginally as a two-component Gaussian mixture. Based on the marginal density plots, we proposed two schemes for fitting multivariate HMM. For model scheme M1, we specified bivariate Gaussian distribution for heart rate and log(XSTEP+1) for both states; for model scheme M2, we assumed univariate Gaussian distribution for heart rate for both states and univariate Gaussian distribution for log-transformed step count for both states. Two HMMs were fitted for each participant, one HMM modeled using model scheme M1 and another using model scheme M2. The best model was chosen based on Akaike information criterion (AIC) and Bayesian information criterion (BIC). Moreover, the goodness of fit of the best model was further assessed by ordinary normal pseudo-residuals [27]: (10)If the observations x1,. . . [SEP] Justify:

Output: The text corroborates the claim by discussing the use of heart rate and movement data in modeling sleep and wake states through the hidden Markov model (HMM). It mentions that the states with higher estimated mean heart rate and activity level correspond to waking states, while states with lower mean values represent resting or sleeping states. This directly supports the idea that wearable devices leverage such physiological and movement data to estimate different sleep stages.


Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: While it is slightly encouraging that the Swedish legislation is unchanged at the moment, as seen in Table 1, it is obvious that the risk of EPBD creating unhealthy indoor environments will be augmented. The present levels of indoor air quality in the building stock risk being lowered by the combined effect of tighter building envelopes and the prospect of lower required ventilation rates. 15251:2006CEN EN 16278. 1:2019Dissatisfied [%]Airflow per person [L⋅s−1/person]DissatisfiedAirflow per person L⋅s−1/personI10101010II207207III30304IV< 30< 4402. 5Dissatisfied [%]Very low polluting building [L⋅s−1/m2]DissatisfiedVery low polluting building [L⋅s−1/m2]I100. 5100. 5II200. 35200. 35III30300. 2IV< 30<0. 2400. 15Table 2. Values are extracted from the official European guidelines for ventilation requirements and air quality. CEN EN 15251:2006 are the old guidelines from 2006 [61] and CEN EN 16278. 1:2019 are the new guidelines (valid from 8 May, 2019) [62] issued by for Standardization. The bold figures are the recommended values. As concluded in the previous section, simply specifying required ventilation rates cannot guarantee an adequately low exposure to indoor pollutants [63]. Legislation also need to address the air distribution. In the [62] and in the [56], the given ventilation rates assume complete mixing in the room. Thus, they presuppose a mixing mechanical ventilation system. Other ventilation systems are accommodated by dividing with a correction factor. [26] proposes a correction factor called the air change effectiveness defined as εI=τn/τ¯ evaluated in the breathing zone [56]. For mixing ventilation this gives εI,mixed=1 and for plug flow εI,plugflow=2. The correction factor in the is similarly defined, but evaluated as a room average, and is called ventilation effectiveness εv. (The nomenclature for the correction factors is a bit confusing and may be easily mixed-up with the air change efficiency defined in Eq. (12). [SEP] Justify:

Output: The text contrasts the claim by indicating that simply specifying required ventilation rates does not guarantee adequate exposure to indoor pollutants, implying that the effectiveness of ventilation systems in improving air quality is contingent on additional factors. It states that needed legislation must address air distribution and that the assumed complete mixing of air, central to many ventilation guidelines, may not always provide the expected improvement in air quality.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: 71 μM), respectively. Also, the treatment of panduratin A at the pre-entry phase inhibited SARS-CoV-2 infection with IC50 of 5. 30 μM (CC50 = 43. 47 μM). Therefore, exerted the inhibitory effect against -2 infection at both pre-entry and post-infection phases as the novel natural candidate [16]. 2. 6 African traditional medicineethnomedicinal herbs (Abrus precatorius L. Gaertn, Achyranthes aspera L. , Allium sativum L. , Annona muricata L. , Artemisia afra Jacq. ex Willd, Azadirachta indica A. Juss. , Cryptolepis sanguinolenta (Lindl. ) Schltr. , Curcuma longa L. , Euphorbia hirta L. , Garcinia kola Heckel, Glycyrrhiza glabra L. , Moringa oleifera Lam. , Nigella sativa L. , Psidium guajava L. , Zingiber officinale Roscoe) used in African traditional medicine from different countries in Africa were investigated in the prevention, treatment and management of COVID-19 infection [17]. From them, Glycyrrhiza glabra was reported to be successful inhibitor for SARS-CoV replication and was recommended for the management COVID-19. Due to the complex nature of SARS-CoV-2 and clinical presentation of COVID-19 disease, combining two or more extracts with various pharmacological activity from these herbs in a standard dosage form such as capsule, tablets, syrups, and injections is necessary in the management of the disease. This combination would improve adherence but care must be taken to ensure that all ingredients in the formulation are compatible otherwise it may lead to therapeutic failure or toxicity. These findings will serve as a source of information for future research in the selection of herbs which could be used in the management of COVID-19 [17]. 2. 6. 1 African medicinal plantsSixty-two alkaloids and hundred terpenoids isolated from some African medicinal plants were docked to the 3-Chymotrypsin-Like protease (3CLpro) controled coronavirus replication as a promising drug target for combating the coronavirus infection. [SEP] Justify:

Output: The text discusses the use of various African traditional medicinal herbs in the prevention and treatment of COVID-19. However, it does not specifically mention the relationship between these plants and indigenous cultures, nor does it provide information about their traditional use outside of the context of modern medicine. Thus, the text is not directly relevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: S/W: sleep/wake. View this figureComparison of Scoring Algorithmsautomatically detects sleep based on activity—“When your body is completely at rest and you haven’t moved for about an hour, your Fitbit device records that you’re asleep” [41];—however, the exact scoring algorithm is proprietary. Only the sleep/wake scoring results can be compared with Fitbit’s output (7 sleep-related states). For comparison, asleep, deep, light, and REM were reclassified as sleep, while restless, awake, and wake were reclassified as wake. ModelIn addition to applying the proposed model to 3-month time periods for each participant, as a pilot experiment, we applied the personalized algorithms on a daily basis for each person. To investigate whether there was any difference in estimated parameters between weekdays (Monday to Friday) and weekends (Saturday and Sunday), we used two-tailed independent t tests to compare the parameters of the two for each participant (P<. 05 was deemed significant). ResultsOverviewAfter nonwear exclusion, there were 14 participants whose data qualified for analysis (aged from 61 to 91 years old; 12 women and 2 men); 6 participants had hypertension, 5 had high cholesterol, 2 had diabetes mellitus, 3 had cancer, and 1 had a stroke. The percentage of missing heart rate data ranged from 0. 31% to 0. 96% (mean 0. 64%). Examples of 24 hours of step count and heart rate data are shown in Figure 4 in which the circadian cycle was quite clearly evident, and the segmentation of activity and heart rate over the 24 hours was visible. Figure 4. A 24-hour example plot of step count every 15 minutes and heart rate every 1 minute for participant EL01 from 8 AM to 7:59 AM the following morning. Note: Times are in 24-hour format. View this figure ResultsIn order to illustrate our proposed approach, we used the sleep and wake identification of two typical examples, participants EL02 and EL21, for demonstration. We first examined the recordings to eliminate nonwear days. There were 16 days were eliminated from analysis for EL02 and 9 days were eliminated from analysis for EL21. To compare two schemes of modeling multivariate time series, we present model selection results, including log likelihoods, AIC, and BIC in Table 1. [SEP] Justify:

Output: The text corroborates the claim by explaining that a device like Fitbit uses activity and heart rate data to detect sleep stages. It states that the device records sleep when there is no movement for about an hour, indicating that heart rate and movement data are indeed utilized in assessing sleep states.


Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: ) If the system is not fully mixed, the correction factor is less than unity and the required ventilation rate should be correspondingly increased. If displacement or plug flow ventilation systems are used, that are more efficient than mixing ventilation, the correction factor is larger than unity and the required ventilation rates may be correspondingly decreased. Legal ventilation requirements also address air distribution, but rephrased into requirements that newly installed ventilation should be shown to function as designed, that the ventilation rate should be sufficient, or by requiring a specified air change efficiency as in Table 1. I have the impression that air change efficiency is seldom tested in the field. The control of newly installed ventilation systems mostly consist of ensuring that the design ventilation flows are obtained, otherwise the ventilation system components are assumed to function with the same efficiency as in laboratory tests. However, there are a number of factors that may lower the ventilation system efficiency in a real building. Some of these factors were mentioned in connection with ventilation short-circuiting in previous section (see also Figure 5); ventilation systems may be very complex and design choices may have unforeseeable consequences; a ventilation designer may enter late in the planning process and may be forced to make suboptimal choices, e. g. inlets vents may end up too close to outlet vents; or occupants may tamper with the intended function of the ventilation components to minimize perceived draft. It may be prudent to verify that air is distributed with the intended efficiency in new and old ventilation installations. The above standards clearly favor mechanical ventilation systems where ventilation rate is an easy parameter to measure. It is not that easy to measure ventilation rate for natural ventilation systems. It is more difficult to demonstrate that natural ventilation systems are in compliance with the legal requirements than it is for mechanical ventilation systems. In addition, rooms with natural ventilation systems typically have higher room heights, than rooms with mechanical ventilation systems. Naturally ventilated rooms require larger room volumes to prevent concentration build-up of transient pollution sources to offset the natural fluctuations in the ventilation rate. Historically, the introduction of mechanical ventilation systems allowed building entrepreneurs to squeeze in three floors in the same volume where previously there would be two floors in older naturally ventilated buildings [30]. Using this observation, rooms with natural ventilation are roughly estimated to be 50% larger than rooms with mechanical ventilation. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and inefficiencies of ventilation systems. It suggests that factors such as system design, occupants tampering, and the challenges of measuring efficiency can lead to reduced effectiveness in improving air quality. The mention of needing to verify intended efficiency and that air change efficiency is seldom tested implies that simply having a ventilation system does not guarantee improved air quality as claimed.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: The twenty alkaloids and terpenoids with high binding affinities to the SARS-CoV-2 3CLpro were further docked to the 3CLpro of SARS-CoV by comparing with the reference inhibitors (Lopinavir and Ritonavir). From them, 10-hydroxyusambarensine, cryptoquindoline, 6-oxoisoiguesterin and 22-hydroxyhopan-3-one showed potent activity against SARS-CoV-2 3CLpro [31]. 2. 6. 2 Nigerian medicinal plantsmedicinal plants and their 9 phytoconstituents were investigated against symptoms related to COVID-19. Their specific therapeutic actions are administered to combat the key players in the pathogenesis of the disease [32]. 2. 6. 3 Moroccan medicinal plantsThe molecular docking studies on sixtyseven phytoconstituents from Moroccan medicinal plants were evaluated for their in vitro and in vivo antiviral activity against SARS-COV-2 Main protease before clinical trial. The results of molecular docking studies showed that three compounds (crocin, digitoxigenin, and β-eudesmol) were proposed as inhibitors against the coronavirus based on the energy types of interaction between these compounds and studied protein [33]. 2. 6. 4 medicinal plantsTwentynine phytoconstituents isolated from commonly used traditional medicinal plants were examined against SARS-CoV-2 using molecular docking and molecular dynamics. Molecular docking identified arabic acid from Acacia senegal and L-canavanine found in Sutherlandia frutescens were determined as a potential inhibitor 3C-Like main protease (3CLpro) of SARS-CoV-2. Similarly, hypoxoside isolated from Hypoxis hemerocallidea and uzarin from Xysmalobium undulatum were also identified as a potential inhibitor of SARS-CoV-2 receptor binding domain and SARS-CoV-2 RNA-dependent polymerase (SARS-CoV-2 RdRp). In addition, these compounds exhibited favorable binding orientations characterized by strong molecular interactions within respective inhibitors binding pockets of the target enzymes [34]. 2. 7 Traditional medicinal plants of countriesUncaria tomentosa (cat’s claw) is traditionally used medicinal plant in countries. [SEP] Justify:

Output: The text provides a detailed examination of various medicinal plants, their phytoconstituents, and their potential antiviral activity against SARS-CoV-2. However, it does not specifically address the use of traditional medicines derived from plants by indigenous cultures. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: 04)Heart rateµHR87. 18 (12. 52)66. 37 (7. 82)σ2HR241. 16 (110. 75)47. 18 (36. 91)Correlation, ρ0. 54 (0. 07)0. 01 (0. 01)TransitionWake state0. 989 (0. 003)0. 011 (0. 003)Sleep state0. 017 (0. 002)0. 983 (0. 002)Investigating the Effect of the Fusion of and Activity in the ModelWe compared the final scoring results from approaches based on the heart rate HMM, the activity HMM and our fusion approach minute-by-minute for each participant. Table 4 presents duration, heart rate, and activity level in different combinations of possible results for EL02 as an example. For EL02, 49. 30% (42,599/86,400 minutes) of the recordings were scored as wake, and 33. 87% (29,264/86,400 minutes) were scored as sleep by all three methods, which indicated the monotonic relationship between heart rate and activity level for most of the time, whether sleep or wake. There were 13. 42% (11,593/86,400) that changed states by our fusion approach compared to that indicated using only one data-source type. Our approach rarely (2/86,400, <0. 001%) scored one minute as sleep state if either the heart rate HMM or the activity HMM had classified the minute as wake state. The determination of sleep state in our approach was a combination of activity and heart rate for EL02. Table 4. Comparison between the activity HMM, the heart rate HMM, and our fusion approach for participant EL02. HMMComparisonActivity onlyHeart rate onlyFusionDuration(total minutes=86,400), n (%)Heart rate, mean (SD)Activity level, mean (SD)wakewakewake42,599 (49. 30)113. 37 (11. 28)3. 13 (0. 91)wakewakesleep0 (0)——wakesleepwake2825 (3. 27)76. 12 (8. 94)2. 14 (0. 96)wakesleepsleep1 (0. 00)74 (—)0. 76 (—)sleepwakewake8768 (10. 15)101. [SEP] Justify:

Output: The text corroborates the claim by explaining how the determination of sleep states utilizes both heart rate and activity data in their model. It specifically states that the approach analyzed heart rate and activity levels, showing a 'monotonic relationship between heart rate and activity level for most of the time' and emphasizing the role of both data sources in estimating sleep stages.


Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: If there is a legally required air change rate or a required ventilation rate per floor area (as exemplified in Table 1), the prescribed ventilation rates will also be 50% larger for naturally ventilated rooms, as compared to a mechanically ventilated room. This increase is probably unnecessary and it arises because the legal requirements does not consider the different ventilation strategies used in natural ventilation systems. It would be desirable that all ventilation strategies should be treated equally in the eyes of the law, with the same objective requirements for adequate indoor air quality. If the objective of the legal regulations is to ensure that 80% of the occupants find the perceived air quality to be acceptable, as it appears to be, then it would be more fitting to simply require that less than 20% of the occupants are feeling uncomfortable. This could be tested in a questionnaire. Note that this approach is suggested in some environmental certification systems for buildings, e. g. the level GULD in Miljöbyggnad 3. 1 [64]. The problem with such an approach is that other factors, than the actual air quality, may affect the outcome [27]. Alternatively, the regulations should apply specifically to the occupied zone of a room. This would lead to more balanced demands on natural ventilation systems as compared to the demands on mechanical ventilation systems. To specify concentration limits in the occupied zone would be preferable because of the direct link to exposure, but the challenge is that the human nose is very sensitive so some substances and there may be difficulties to measure such low concentrations at the present time. An indirect approach would be to specify some local ventilation parameter, such as the local mean age of air, in the occupied zone. The fact that ventilation requirements primarily targets occupant comfort, does not mean that ventilation is irrelevant for the health of the occupants. Adverse health effects caused by exposure to indoor air pollution have been estimated to cause that approximately two million disability-adjusted lifetime years (DALYs) are lost annually, based on the population in 26 European countries. In economic terms this corresponds to a societal cost exceeding €200 billion [60]. It is very likely that the combined effect of the lower ventilation requirements and tighter building envelopes due to EPBD will increase this societal cost considerably. The prospect of turning buildings into unhealthy containers for the occupants certainly tempers my enthusiasm for the projected EPBD energy savings. Advertisement 3. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and legal requirements surrounding ventilation systems, suggesting that merely increasing air change rates does not necessarily lead to improved air quality. It highlights that adverse health effects due to indoor air pollution can persist even with ventilation systems in place, indicating that the effectiveness of these systems in truly improving air quality may be compromised if they do not address specific issues such as occupant comfort and measurement challenges. Therefore, while ventilation systems are intended to improve air quality, the text underscores that they may fail to meet this objective adequately.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Twentysix phytoconstituents of Uncaria tomentosa were docked on the binding interface of the ACE-2 and SARS-CoV-2 spike protein of novel corona virus. From these compounds namely Proanthocyanidin C1, 3-isodihydrocadambine, and Uncaric acid had a good predicted binding affinity for interface of the ACE-2 as compared to the sulfated Heparin OctaSaccharide (HepOS). Likewise, 3-dihydrocadambine, Proanthocyanidin B4, Proanthocyanidin B2 and Proanthocyanidin C1 had the highest docking score on SARS-CoV-2 spike glycoprotein in their open state. Virtual prediction ADME revealed that Speciophylline, and Uncaric acid presented values of drug ability according to Lipinski rule, demonstrating their potential bioavailability as likely orally active antiviral. Uncaria tomentosa can be performed as an herbal supplement with the safety and efficacy parameters at both preclinical and clinical stages to evaluate its effectiveness in the treatment of novel coronavirus disease (COVID-19) [18]. Thirty-nine herbal medicinal plants known in the America and Europe for the management of respiratory conditions, mainly regarding the symptoms cough, pain and fever were studied for their therapeutic potential alongwith the limitations for their use and possible risks. For five out of the 39 herbal drugs a positive benefit/risk assessment was determined. The level of evidence for Althaea officinalis, Commiphora molmol, Glycyrrhiza glabra, Hedera helix and Sambucus nigra are suggested a potential clinical use as adjuvants in the treatment of early/mild cases of COVID-19. Another twelve herbal medicines were classified as promising plant species [19]. Advertisement 3. Various phytoconstituentsVarious phytoconstituents occured in living organisms in a high structural diversity have antiviral activities by inhibiting different stages in the replication of various viruses. Their different antiviral mechanisms like virus adsorption, virus-cell fusion, reverse transcription, protease and integrase inhibition have been reported in recent studies [20, 21]. [SEP] Justify:

Output: The text does not provide information about the derivation of traditional medicines from plants used by indigenous cultures. Instead, it focuses on the potential antiviral properties of specific phytoconstituents and herbal medicines in relation to COVID-19 treatment. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: 21 (13. 74)0. 82 (0. 67)sleepwakesleep1 (0. 00)96 (—)0. 38 (—)sleepsleepwake2942 (3. 41)80. 72 (8. 37)0. 97 (0. 68)sleepsleepsleep29,264 (33. 87)69. 62 (5. 10)0. 28 (4. 24)For recordings that the activity HMM scored as wake, the heart rate HMM scored as sleep, and our approach scored as wake, the mean heart rate was 76. 12, and the mean activity level was 2. 14 (equivalent to 7. 5 steps per minute). The nontrivial activity level led our approach to score that minute as wake. For recordings that the activity HMM scored sleep, the heart rate HMM scored wake, and our approach scored as wake, the mean heart rate was 101. 21, and the mean activity level was 0. 82. Furthermore, we present an example of 24 hours of scoring results from the three model types along with observational data for EL02 in Figure 6. The bars below the observations indicated the scored sleep or wake states in three models. From the highlighted period in Figure 6, we can see that if we used activity data alone, it was very likely to be classified as sleep due to the extremely low activity level. However, the high and fluctuating heart rate might suggest the person was awake. Figure 6. An example plot of observations and scoring results from and our approach for EL02. HMM: hidden Markov model. View this figureExcept for epoch-by-epoch comparison, we also evaluated the performance on a crucial sleep metric, the total amount of sleeping time in the recording period [42]. For all participants, we calculated daily total sleep time at night for all available days. The nighttime sleep period of each participant was collected with the indicating when they usually went to bed at night and got up in the morning [43]. Figure 7 displays the boxplot of estimated total sleep time during their bedtime for all participants. We could see that the median estimated total sleep time at bedtime varied a lot from person-to-person. For EL01, EL02, EL06, EL24, and EL25, the median total sleep time estimated by our approach was less than those from the heart rate HMM and the activity HMM. [SEP] Justify:

Output: The text supports the claim by discussing how different models use heart rate and movement data to classify sleep and wake states. It mentions the use of 'activity data alone' leading to a likely classification of sleep, while the 'high and fluctuating heart rate might suggest the person was awake', which illustrates the integration of heart rate and movement data in estimating sleep stages.


Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: This low number of release points was selected based on the fact that the greater the presence of gas release points within the domain, the more wind flow characteristics are affected. The behaviour of the plumes from the four point sources was totally different from those which were emitted from the whole volume. In addition, the measured data showed that the averaged domain concentration is quite sensitive to the source location. This led to inaccurate results. There are different indices such as the age theory (Sandberg, 1983), purging flow rate, visitation frequency (Kato et al. , 2003) and the six indices SVE1-6 (Kato et al. , 1992) that are used to assess the air quality of a room or a domain located within an enclosed environment. Among these indices, three indices were adopted to implement the present study, i. e. purging flow rate (PFR), visitation frequency (VF), and pollutant residence time (TP). Values of VE indices for a domain are of practical importance in reflecting the effect of the geometrical characteristics of such domain, i. e. the PFR value for a domain represents the local ventilation effectiveness of such domain. A small purging flow rate means that this domain is weakly ventilated. Also, higher values for the visitation frequency and residence time of pollutants are indications of poor removal efficiency of the pollutants by the applied wind. In the following section, definitions of the three indices will be explained in details. 2. 1. Purging flow rate The purging flow rate is the most important index for defining the ventilation efficiency of a local domain. It can be considered as the local ventilation efficiency. For a domain, PFR is defined as the effective airflow rate required to remove/purge the air pollutants from that domain (Kato et al. , 2003). In other words, the purging flow rate can be considered as the net rate by which the pollutants are flushed out of the domain. It reflects the capacity at which the wind removes the pollutant from the domain. The following equation is used to calculate PFR: E1 where: qp denotes pollutant generation rate (kg/s). cP is the domain-averaged concentration (= c×ρ) (kg/m3). ρ is the air density (kg/m3). c is the mass concentration (kg/kg). [SEP] Justify:

Output: The text contrasts the claim by discussing various factors that influence air quality within an enclosed domain, specifically focusing on purging flow rate (PFR) and its implications for ventilation efficiency. It states that a low purging flow rate indicates weak ventilation, which contradicts the notion that ventilation systems effectively improve air quality by facilitating the circulation of fresh air indoors. The mention of indices and their measurements highlights that insufficient ventilation can lead to poor pollutant removal, suggesting that ventilation might not always achieve improved air quality as per the claim.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Lycorine, hypericin, emodin, tylophorine, ouabain, mycophenolate mofetil, silvestrol, myricetin and scutellarein were also reported for their inhibitory effects against SARS-CoV-2 and other human coronaviruses [22]. Some phytoconstituents such as myricitrin, methyl rosmarinate, 5,7,3′,4′-tetrahydroxy-2′-(3,3-dimethylallyl) isoflavone, 3,5,7,3′,4′,5′-hexahydroxy flavanone-3-β-D-glucopyranoside, (2S)-eriodictyol 7-O-(6′′-O-galloyl)-β-D-glucopyranoside, calceolarioside B, myricetin, 3-O-β-D-glucopyranoside, licoleafol, and amaranthin were reported as potential lead candidates to develop novel anti-SARS-CoV-2 drugs [23]. Moreover, anthraquinone derivatives were screened on the basis of binding energy against N-(NTD) of SARS-CoV-2. Emodin, Anthrarufin, Alizarine, Aloe- emodin, and Dantron showed the good binding affinity at three different active sites of N-of SARS-CoV-2 nucleocapsid phosphoprotein. These compounds prevent the assembly of virus p4. ConclusionPlants and their secondary metabolites provide valuable leads for the development into drugs for the novel antiviral activities. Ivermectin is the FDA approved drug and inhibited the replication of SARS-CoV-2 [35]. Although there is an increase in the use of traditional medicine worldwide, researches in traditional medicines are insufficient. Assessments of the quality, safety, and efficacy of traditional medicines are needed to provide scientific information that regulations need. In the present review, antiviral activity mainly against coronaviruses of traditional medicines along with their phytoconstituents through the literature data relevant to their enzyme and receptor interactions given by different assays. [SEP] Justify:

Output: The text does not directly address the claim regarding the derivation of traditional medicines from plants used by indigenous cultures. Instead, it discusses antiviral properties of various phytoconstituents found in plants and notes an increase in the use of traditional medicine but acknowledges insufficient research in this area. Therefore, it does not corroborate or contrast the claim, making it irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: For the other participant, they were nearly the same as the activity HMM. Figure 7. Boxplot of estimated daily total sleep time during bedtime at night from heart rate HMM, activity HMM, and fusion HMM (our approach) for all participants. HMM: hidden Markov model; TST: total sleep time. View this figureFitbit’s Sleep-ResultsWe compared results from our approach with those from Fitbit’s scoring algorithm minute-by-minute. We treated Fitbit’s sleep/wake scoring algorithm as representative of existing methods. The mean agreement between our approach and Fitbit’s scoring was 87. 31%, (range 82. 90% to 91. 04%). As for total sleep time, the boxplot of the estimated total sleep time at night using our approach and Fitbit’s algorithm are displayed in Figure 8. There were several days where Fitbit’s had no sleep/wake records but had continuous regular heart rate recordings. The median estimates of total sleep time from our approach were lower than those from Fitbit in 12 of 14 participants, which indicated our approach tended to score more wake epochs. The dispersion of estimated sleep duration using our approach was relatively narrower than that of Fitbit’s algorithm, which may suggest a stable indicator of participants’ habitual nighttime sleep duration. Figure 8. Boxplot of estimated daily total sleep time during bedtime at night from our approach and Fitbit’s approach for all participants. HMM: hidden Markov model; TST: total sleep time. View this figurevalues for independent two-tailed t tests comparing estimated parameter values between weekdays and weekends for each person are shown in Table 5. There was no significant difference for γ21, σ2HR for wake state, and µACT for sleep state between weekends and weekdays for any participant. As shown in Table 5, 5 of 14 participants had no significant difference in any of the estimated parameters between weekday models and weekend models, while 9 participants had differences in at least one parameter. For example, EL04 had a significantly lower transition probability from wake to sleep (0. 015 for weekdays; 0. 018 for weekends). EL11 had a higher mean estimated variance of activity level in wake state on weekdays (1. 49 for weekdays; 1. 29 for weekends). Table 5. [SEP] Justify:

Output: The text corroborates the claim by discussing methods that utilize heart rate data alongside activity data (implied as movement data) to estimate sleep metrics. It mentions the comparison of results from a proposed approach and Fitbit’s algorithm, which is representative of wearable devices that estimate sleep stages based on similar data types. The reference to heart rate recordings and their role in scoring sleep/wake cycles supports the assertion that such devices leverage heart rate and movement for sleep analysis.


Input: Task: contrast the claim using the given text. Claim: Ventilation systems improve air quality by circulating fresh air indoors. [SEP] Text: To compare the wind ventilation performance for the two building patterns, seven domains were considered within these arrays, domain (1 ~ 7), as shown in Figure 16. Wind flow fields were calculated for two directions of 0o and 45o. Figure 17 shows the flow fields around the building patterns for the two directions. Figure 16. Schematic of two different building arrays showing the selected domains; (a) aligned, (b) staggered. The calculated VE indices for the seven domains are shown in Figure 18. The figure show large variation in the air quality parameters. In the case of θ = 0o, the staggered array shows undesirable air quality conditions within the selected domains compared with the case of aligned blocks except for domains 3 and 4. High pollutant concentrations and low air exchange rates are observed in this case. Additionally, the purging capability of the natural wind for the staggered distribution was lower than that of the aligned one, reflected by high values for VF and TP. This can be referred to the fact that the staggered distribution of blocks prevents the direct flow between the blocks, which decreases the wind capability in removing the pollutants. On the other hand, the smooth flow of the wind within the aligned array at such wind direction dilutes the pollutant concentrations, and hence improves the air Figure 17. Wind flow fields around the two building arrays for the two directions (z/H = 0); (a) aligned 0o, (a) staggered 0o, (a) aligned 45o, (a) staggered 0o. quality of the considered domains. With respect to domains 3 and 4, the locations of such domains within the aligned array are worse than their locations within the staggered one. The geometry of the aligned blocks allows such domains to have three open boundaries, while in the staggered distribution they have four boundaries. Such geometry decreases the ventilation performance of the applied wind of these domains due to the lower inlet flux compared with the other five domains. In the case of θ = 45o, the situation is reversed, where the staggered array show good removal efficiency compared with the aligned array for almost all domains. Such behavior can be attributed to the circulatory vortices that were established around the aligned blocks at such wind direction. These circulatory flows decrease the wind ventilation performance since it reduces the wind velocity within the array domains. [SEP] Justify:

Output: The text contrasts the claim by discussing the performance of different building patterns on air quality, indicating that the staggered array has inferior wind ventilation capabilities compared to the aligned array. It explains how the staggered distribution prevents direct wind flow, leading to higher pollutant concentrations and lower air exchange rates, which contradicts the claim that ventilation systems improve air quality.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Pre-clinical studies would provide deep insight into mechanism of actions and also drug ability of the antiviral candidates for the treatment of COVID-19 infection. Besides, vast range of double-blinded clinical studies with strict protocols is required to estimate the accurate potential of antiviral phytochemicals against COVID-19 with the aim of ensuring the fulfillment of international acceptable standards. Therefore, phytoconstituents will play an important role and continue to support in developing potential drugs against SARS-CoV-2. of interestThe authors declare no conflict of interest. 1. -Rad M, Kılıc -Rad J. Medicinal plants used in the treatment of human immunodeficiency virus. Int. J. Mol. Sci. 2018;19(5):1459-1519. DOI: 10. 3390/ijms190514592. . Antiviral activities in extracts of Turkish medicinal plants. Pharm. Biol. 2000;38:171-175. DOI: 10. 1076/1388-0209(200007)3831-SFT1713. Sener B. Antiviral activity of natural products and herbal extracts. J. 2020;31:474-477. 4. . herbal medicine at the forefront battle against COVID-19: Clinical experience and scientific basis. Phytomedicine 2020;80:153337. DOI: 0. 1016/j. phymed. 2020. 1533375. -L. Structural basis of SARS-CoV-2 3CLpro and anti-COVID-19 drug discovery from medicinal plants. J. Pharm. Anal. 2020;10:313e319. DOI: 10. 1016/j. jpha. 2020. 03. 0096. . Saxifraga spinulosa-derived components rapidly inactivate multiple viruses including SARS-CoV-2. Viruses. 2020;12:699. DOI: 10. 3390/v120706997. Bahramsoltani R, Rahimi R. An evaluation of traditional Persian medicine for the management of SARS-CoV-2. Front. Pharmacol. 2020;11:571434. DOI: 10. 3389/fphar. 2020. 5714348. . [SEP] Justify:

Output: The text discusses various studies related to the antiviral properties of phytochemicals and medicinal plants, particularly in the context of COVID-19. However, it does not address or mention the derivation of traditional medicines from plants used by indigenous cultures, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: DiscussionPrincipal FindingsLongitudinal monitoring of sleep duration can objectively help detect sleep disorders and reduce the risk of related diseases. In order to facilitate personalized home-based monitoring, it is essential to record sleep and wake states using wearable devices efficiently and nonintrusively. In this study, we proposed a novel personalized and unsupervised approach for sleep/wake identification using both heart rate and activity data from a commercial wearable device. The approach was successfully implemented in case studies of community-dwelling older adults. Our proposed approach is the first unsupervised and personalized sleep/wake classification approach, to our knowledge. It does not require any time-consuming and costly PSG annotation, which is hard to obtain simultaneously with wearable device data [15,36]. Furthermore, our approach was efficient enough to be adaptive to a different participant without requiring PSG annotations. In our case study, the variance in estimated parameters in HMM between participants also proved the necessity of a personalized model. The data-level fusion of activity and heart rate data for sleep/wake scoring in wearable device was explored. Based on comparison among scoring results from HMMs using heart rate only, activity data only, and both data sources, we concluded that our approach could potentially help identify more wake epochs for people who have distinguishable heart rate patterns between sleep and wake. This coincided with the findings of significant different heart rate during sleep and wake states [32] and its classification power in sleep/wake identification algorithms [33,44]. Our approach had results that were mostly consistent with those of Fitbit, a commonly used commercial device. For most of the participants, our approach tended to score more wake epochs during bedtime, which may be potentially useful as it has been shown by Montgomery-Downs et al [45] that many commercial wearable devices, when compared to PSG, tend to overestimate sleep epochs. This should be further investigated with PSG annotations. StrengthsIn addition to sleep and wake identification and total sleep time estimation results, this paper proposed an approach that provides a new probabilistic way to characterize and quantify activity patterns and cardiac patterns during sleep and wake for each participant with estimated HMM parameters. A low estimated mean activity in wake states suggest a sedentary behavior style when the participant is wake, which should be of concern to the participant or their health care provider [46]. [SEP] Justify:

Output: The text corroborates the claim by discussing a proposed method for sleep/wake identification that utilizes both heart rate and activity data from a wearable device. It explains that this approach effectively aids in recording sleep and wake states nonintrusively, supporting the idea that wearable devices can use heart rate and movement data for estimating sleep stages.


Input: Task: pass the claim using the given text. Claim: Smart air quality devices provide real-time monitoring of pollutants. [SEP] Text: For POP determination, SPMDs are dialysed with the appropriate solvent and the extract, after clean up, is analysed by GC-MS (Ockenden et al. , 2001a). SPMDs are deployed over weeks/months/years in the chosen site. Deployment time of the SPMD is analyte-dependent; in addition, it depends on instrument limit of detection, SPMD blank level, uptake rates and typical atmospheric concentration of the POP. The capacity of the SPMD depends on the quantity of lipid in the sampler and uptake rates by SPMDs depend on permeability of the membrane. Uptake rates are influenced by ambient temperature and wind speed; performance reference compounds can be used to “correct” for site-specific differences in uptake rates. SPMDs are easily contaminated, thus SPMD field blanks have to be taken to the field in sealed containers but not exposed, in order to evaluate the degree of contamination. Despite cited drawbacks, SPMDs are ideal samplers for studies into spatial differences in concentrations and profiles of POPs in the atmosphere, to identify sites where further investigations are required and for producing time-integrated data (Ockenden et al. , 2001a). 4. 2. Quality controlQuality control of the analytical procedure for POP determination in samples from remote zones is a very critical step in consideration of low atmospheric POP levels and the time lag between sampling and analysis. The risk of contamination is higher in particular for Antarctic air samples due to the much longer transport and storage time. Suitable analytical quality control and quality assurance programs have to be run in the sampling site and in the laboratory, during sample gathering and analysis in order to guarantee data reliability. With the purpose of assuring the overall quality and validity of experimental data, a systematic and detailed sampling strategy and blank choice have to be carried out. In order to prevent any contamination during sampling operations, clean room protocols should be attended. All the samplings should be performed downwind and away from local contamination sources, e. g. scientific stations. The operators should wear special clean room clothing and polyethylene gloves even during sampling, over their warm clothing. Immediately after the gathering, an opportune storage procedure (different according to the sampling method and sampling device) is applied in order to maintain unaltered the sample characteristics. [SEP] Justify:

Output: The text does not address the use of smart air quality devices or their capabilities in monitoring pollutants in real-time. It focuses on the methodology of using Semi-Permeable Membrane Devices (SPMDs) for determining persistent organic pollutants (POPs) over extended periods, which does not corroborate or contrast the claim regarding smart air quality devices.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Traditional medicinal plants against replication, maturation and transmission targets of SARS-CoV-2: Computational investigation. J. Biomol. Struc. Dyn. 2020;5:1-18. DOI: 10. 1080/07391102. 2020. 18422469. . Structural basis for the inhibition of SARS-CoV2 main protease by Indian medicinal plant-derived antiviral compounds. J. Biomol. Struc. Dyn. 2020;1-9. DOI: 10. 1080/07391102. 2020. 183445710. . Antiviral activity of traditional medicinal plants from Ayurveda against SARS-CoV-2 infection. J. Biomol. Struc. Dyn. 2020;19:1-17. DOI: 10. 1080/07391102. 2020. 18327711. . Natural compounds as potential inhibitors of novel coronavirus (COVID-19) main protease: An in silico study. Research Square. DOI: 21203/rs. 3. rs-22839/v112. Sharma K, Zafar, R. Occurrence of taraxerol and taraxasterol in medicinal plants. Pharmacog. Rev. 2015;9:19-23. DOI: 10. 4103/0973-7847. 15631713. . Promising anti-influenza properties of active constituent of Withania somnifera Ayurvedic herb in targeting neuraminidase of H1N1 influenza: Computational study. Biophys. 2015;72(3):727-739. DOI: 10. 1007/s12013-015-0524-914. . Ethnomedicines of Indian origin for combating COVID-19 infection by hampering the viral replication: Using structure-based drug discovery approach. J. Biomol. Struc. Dyn. 2020;1-16. DOI: 10. 1080/07391102. 2020. 177853715. . Plants-derived biomolecules as potent antiviral phytomedicines: New insights on ethnobotanical evidences against coronaviruses. Plants. 2020;9:1244. DOI: 10. 3390/plants909124416. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various studies and findings related to the antiviral properties of traditional medicinal plants, particularly in the context of diseases like COVID-19 and influenza. It does not mention the relationship between traditional medicines and indigenous cultures or how traditional practices derive from them.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Abnormally high estimated mean heart rate in sleep states can be an indicator of autonomic nervous system dysfunction or of the development of chronic fatigue syndrome [47]. A high estimated probability of transitioning from sleep to wake might suggest disturbed sleep. Monitoring these parameters for clinical use is promising and remains to be explored in specific tasks. In addition, we demonstrated how to characterize cardiac and behavior patterns on a daily basis. During our 3-month study, some participants exhibited significantly different patterns between weekdays and weekends. On weekdays, participants had regular visits to older adult centers in their community, which provided various activities. This could explain why some participants tended to have higher estimated mean and variance of activity level for wake state and were less likely to transition from wake to sleep on weekdays. There exists not only interindividual variability in sleep patterns but also intraindividual variability [34]. This analysis can also provide a reference to improve the accuracy of the personalized model to infer sleep/wake states by including covariates (eg, weekday or weekend) in the transition matrix or emission distributions in HMM. LimitationsWe acknowledge that there are also some limitations to our work. First, direct conclusions about our approach’s accuracy cannot be drawn because of the lack of PSG recordings in this study and the small sample size. The estimated sleep/wake states might also be better interpreted as resting-active states at this stage. Second, the comparison with Fitbit’s scoring may not be very fair since the exact algorithm is not publicly known and the data type used for sleep/wake scoring was unknown as well. We also cannot reasonably compare the proposed approach with existing methods on the same data set because of the lack of personalized and unsupervised approaches in sleep/wake scoring (to our knowledge). Third, we collected heart rate and step count data using Fitbit, which were reported in different granularities. In order to achieve data-level fusion and prepare it for modeling, we simulated 1-minute step data from 15-minute step data which might have resulted in some imprecision. We strongly call for different reporting granularity options in commercial wearable devices to further facilitate research and their use in health care monitoring systems. Future WorkIn the future, we plan to compare the proposed approach with PSG to further validate the accuracy of the scoring. [SEP] Justify:

Output: The text corroborates the claim by discussing how heart rate and movement data collected from devices like Fitbit can be analyzed to infer sleep/wake states. It mentions the monitoring of these parameters for clinical use and suggests that such wearable device data could improve the accuracy of personalized models for estimating sleep stages, thereby aligning with the claim about the use of such data.


Input: Task: pass the claim using the given text. Claim: Smart air quality devices provide real-time monitoring of pollutants. [SEP] Text: Recent studiesRecent studies carried out in Antarctica, increased the limited atmospheric database on POPs in remote areas by reporting POP concentrations during the austral summer and hypothesizing their possible sources. Montone et al. (2003) reported atmospheric levels of PCBs near the Research Station, at Island, during a sampling survey undertaken in the austral summer of 1995-1996. Single PCB congeners ranged from below detection limit to 33. 2 pg m-3. The lower chlorinated congeners (PCB-101 and below) predominated in the air samples and represented 66. 7% of the total PCB concentrations. Atmospheric levels of PCBs were correlated with meteorological conditions (as well as to the general synoptic atmospheric circulation of the region) and the higher levels were associated with the passage of the frontal system coming from over the causing a local increase in air temperature and surface winds from northwest, north and northeast (Montone et al. , 2003). Gambaro et al. (2005) monitored the air near Research Station. Gas-phase concentration of individual PCB congeners in the air of Bay ranged from below detection limit 0. 25 pg m-3. The gas-phase ΣPCB concentrations ranged from 0. 61 to 1. 78 pg m-3 with a mean concentration of 1. 06 pg m-3. Over 90% of the total PCB content was due to congener with one to four chlorine atoms and only about 10% with five to seven chlorines, whereas higher chlorinated PCBs were below detection limits. In agreement with other studies, the results emphasized that the PCB profile was dominated by tri-CB and tetra-CB with relatively high contributions from mono-CB and di-CB (Gambaro et al. , 2005). In addition, investigations on POP distribution in Antarctica were made by Ockenden at al. (2001b) which monitored the air for PCBs at two sites in the southern hemisphere, one over land and the other over water. They found that the highest concentrations were observed when temperatures were greater and the air concentrations were higher over water than over land. POP concentrations were found to be higher in air samples from the and sub-Antarctic islands than in those from continental sites (Bargagli, 2005). 5. 6. [SEP] Justify:

Output: The text does not address the claim regarding smart air quality devices and their real-time monitoring capabilities. Instead, it focuses on studies conducted in Antarctica that report atmospheric levels of pollutants like PCBs. As such, it does not provide information that supports, contrasts, or relates to the claim directly.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: 1. High-content screening of Thai medicinal plants reveals Boesenbergia rotunda extract and its component Panduratin a as anti-SARS-CoV-2 agents. Scientifc Reports. 2020;10:19963. DOI: 10. 1038/s41598-020-77003-317. Adeleye OA, Femi--. Ethnomedicinal herbs in African traditional medicine with potential activity for the prevention, treatment, and management of coronavirus disease 2019. Future J. Pharm. Sci. 2021;7:72. DOI: 10. 1186/s43094-021-00223-5. 18. Yepes-Pereza AF, Herrera-Calderonb O, Quintero-Saumeth J. Uncaria tomentosa (cat’s claw): A promising herbal medicine against SARS-CoV2/ACE-2 junction and SARS-CoV-2 spike protein based on molecular modeling. J. Biomol. Struc. Dyn. 2020;29:1-17. DOI: 10. 1080/07391102. 2020. 183767619. Silveira D, Prieto--ães. COVID-19: Is there evidence for the use of herbal medicines as adjuvant symptomatic therapy? Front. Pharmacol. 2020;11:581840. DOI: 10. 3389/fphar. 2020. 58184020. Taban Akça K, Suntar I. An overview on flavonoids as potential antiviral strategies against coronavirus infections. J. 2020;31:478-484. 21. KA. Natural products as antiviral agents. Stud. Nat. Prod. Chem. 2000;24:473-572. DOI: 10. 1016/S1572-5995(00)80051-422. Jahan I, Onay A. Potentials of plant-based substance to inhabit and probable cure for the COVID-19. Turk. J. Biol. 2020;44:228-241. DOI: 10. 3906/biy-2005-11423. . Natural products as potential leads against coronaviruses: Could they be encouraging structural models against SARS-CoV-2? Nat. Prod. [SEP] Justify:

Output: The text discusses various studies on the anti-viral properties of certain plants and herbal medicines in relation to COVID-19. However, it does not mention the concept of traditional medicines being derived from plants used by indigenous cultures, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: NPJ 2019;2:50 [FREE Full text] [CrossRef] [Medline]. Automatic sleep/wake identification from wrist activity. Sleep 1992 Oct;15(5):461-469. [Medline]. Activity-based sleep-wake identification: an empirical test of methodological issues. Sleep 1994;17(3):201-207. [Medline]. Algorithms for sleep-wake identification using actigraphy: a comparative study and new results. J 2009 Mar;18(1):85-98 [FREE Full text] [CrossRef] [Medline]CamNtech. user manual. Salusa. 2008 Jul 10. URL: [accessed 2020-07-16]. A novel machine learning unsupervised algorithm for sleep/wake identification using actigraphy. 2020 Apr 28:1-14. [CrossRef] [Medline]. Models for Time Series:. : CRC Press; 2016. évi F, et al. models for monitoring circadian rhythmicity in telemetric activity data. J R 2018 Feb;15(139) [FREE Full text] [CrossRef] [Medline]. A transition-constrained discrete hidden Markov model for automatic sleep staging. Online 2012 Aug 21;11:52 [FREE Full text] [CrossRef] [Medline]. Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms. 2013 Aug 30;32(19):3342-3356 [FREE Full text] [CrossRef] [Medline]. Accuracy of consumer wearable heart rate measurement during an ecologically valid 24-hour period: intraindividual validation study. 2019 Mar 11;7(3):e10828 [FREE Full text] [CrossRef] [Medline] Continuous 24-hour assessment of the neural regulation of systemic arterial pressure and RR variabilities in ambulant subjects. Circulation 1990 Feb;81(2):537-547. [CrossRef] [Medline] An evaluation of cardiorespiratory and movement features with respect to sleep-stage classification. 2014 Mar;18(2):661-669. [CrossRef] [Medline]. Effects of between- and within-subject variability on autonomic cardiorespiratory activity during sleep and their limitations on sleep staging: a multilevel analysis. [SEP] Justify:

Output: The text corroborates the claim by referencing multiple studies that discuss methodologies for sleep-wake identification using actigraphy, which incorporates movement and physiological data, such as heart rate, to classify sleep stages. For example, it mentions 'A transition-constrained discrete hidden Markov model for automatic sleep staging' and 'An evaluation of cardiorespiratory and movement features with respect to sleep-stage classification,' indicating that wearable devices utilize these kinds of data for sleep estimation.


Input: Task: contrast the claim using the given text. Claim: All indoor plants can purify the air as effectively as air purifiers. [SEP] Text: Research 1018. Development of Step-for as ¹ and Gopinath R²* ¹Department of ²Department of &M, India *Corresponding author: Rajesh Gopinath, Department of &M, India Received: November 25, 2016; Accepted: March 22, 2017; Published: March 30, 2017 compared to the outdoor air environment, it is indoors which is more polluted owing to various influences. This anthropogenic forced situation hence warrants inception of natural purifiers/filters such as the indoor plants. However literatures available are ambiguous on the ability of all indoor plants and focuses only on a few, and even those are restricted to random pollutants. Since indoor plants do not remove all pollutants, and also all are not known to perform the natural purification act; it can be quite cumbersome to decide which plant is best suited for any generic toxic indoor air environment. While the ranking of indoor plants is very much needed to strategize the indoor air environment pollution abatement measures; unfortunately at present there is no system available to-date to rank the indoor plants or even a methodology to develop it. The present research focuses on developing a mechanism of ranking in terms of maximum pollutant (s) removal efficiency. To achieve this, initially all indoor plants from the existing literatures were identified, and eventually the weighted ‘ranking’ was arrived at by studying several parameters such as ‘number of indoor air pollutants removed’ and ‘removal efficiency in terms of their frequency & magnitude’; based on their relative ‘severity’ ranking. The research arrived at the conclusion that indoor flora namely and ranked as 1st, 2nd, 3rd and 4th respectively are relatively the best in terms of indoor air purification. Keywords: Indoor air quality; Pollutants; Ranking; Indoor plants individuals spend more than 90% of their time indoors. Compared to outdoor environment, it is indoors which is more polluted on account of various reasons ranging from bad ventilation & housekeeping practices to modern & tight constructions [1]. Hence this warrants ergonomic corrective measures such as inception of indoor plants, however all indoor plants do not remove any or all pollutants. Agency (US-EPA) has listed about 50 indoor plants that reduce upto 90-95% of toxic chemical present in indoor environment, with NASA supporting this claim [2,3]. [SEP] Justify:

Output: The text contrasts the claim by stating that 'not all indoor plants do not remove any or all pollutants' and that existing literature is ambiguous about the ability of all indoor plants to purify the air. It emphasizes the necessity of distinguishing which indoor plants are effective and notes that the US-EPA has listed about 50 indoor plants that can reduce up to 90-95% of indoor air pollutants, but does not support the universality of all indoor plants being equally effective as air purifiers.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Bioprospect. 2020;10:171-186. DOI: 10. 1007/s13659-020-00250-424. . In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: An approach to prevent virus assembly. J. Biomol. Struct. Dyn. 2020;27:1-18. DOI: 10. 1080/07391102. 2020. 180445725. . Golden pigment curcumin: An inspiring antiviral molecular model for COVID-19 drug design. J. 2020;31:469-473. 26. . Antiviral activities of resveratrol against rotavirus in vitro and in vivo. Phytomedicine. 2020;77:153230. DOI: 10. 1016/j. phymed. 2020. 15323027. Mohammad-. In vitro antiviral effects of Peganum harmala seed extract and its total alkaloids against influenza virus. Micropath. 2017;110:42-49. DOI: 10. 1016/j. micpath. 2017. 06. 01428. . COVID-19 and therapy with essential oils having antiviral, anti-infammatory, and immunomodulatory properties. Infammopharmacology. 2020;28(5):1153-1161. DOI: 10. 1007/s10787-020-00744-029. . Biological effects of essential oils. Food and Chem Tox. 2008;46:446-475. DOI: 10. 1016/j. fct. 2007. 09. 10630. . Aromatic herbs, medicinal plant-derived essential oils and phytochemical extracts as potential therapies for coronaviruses: Future perspectives. Plants. 2020;9:800. DOI: 10. 3390/plants906080031. . Potential inhibitors of coronavirus 3-chymotrypsin-like protease (3CLpro): An in silico screening of alkaloids and terpenoids from African medicinal plants. J. Biomol. Struc. Dyn. 2020;18:1-1813. DOI: 10. 1080/07391102. 2020. 176486832. . [SEP] Justify:

Output: The text provides a series of references and studies related to various phytocompounds and their antiviral properties, but does not address the claim about the origins of traditional medicines in indigenous cultures. Thus, it is irrelevant to the claim being analyzed.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Neurosci 2015;2015:583620 [FREE Full text] [CrossRef] [Medline]. Interindividual differences in the dynamics of the homeostatic process are trait-like and distinct for sleep versus wakefulness. J 2017 Apr;26(2):171-178 [FREE Full text] [CrossRef] [Medline]Khademi A, El-. Personalized sleep parameters estimation from actigraphy: a machine learning approach. Sleep 2019;11:387-399 [FREE Full text] [CrossRef] [Medline]Karlen W, Floreano D. Adaptive sleep-wake discrimination for wearable devices. 2011 Apr;58(4):920-926. [CrossRef] [Medline]Deliang C, Inger H. Empirical-statistical downscaling. : Publishing Company; 2008. Visser I, Speekenbrink M. depmixS4: an R Package for Models. J 2010;36(7). [CrossRef]. An activity-based sleep monitor system for ambulatory use. Sleep 1982;5(4):389-399. [CrossRef] [Medline]How do I track my sleep with my Fitbit device? Fitbit. URL: [accessed 2020-07-16]. How to interpret the results of a sleep study. 2014;4(5):24983 [FREE Full text] [CrossRef] [Medline]. Index: a new instrument for psychiatric practice and research. 1989 May;28(2):193-213. [Medline]. Automatic sleep and wake classifier with heart rate and pulse oximetry: derived dynamic time warping features and logistic model. 2016 Presented at: (SysCon); 2016; p. 1-6. [CrossRef]Montgomery-. Movement toward a novel activity monitoring device. 2012 Sep;16(3):913-917. [CrossRef] [Medline]. Associations between multiple indicators of objectively-measured and self-reported sedentary behaviour and cardiometabolic risk in older adults. 2012 Jan;54(1):82-87. [CrossRef] [Medline] Higher heart rate and reduced heart rate variability persist during sleep in chronic fatigue syndrome: a population-based study. 2007 Dec 30;137(1-2):94-101. [SEP] Justify:

Output: The text corroborates the claim by referencing various studies and inventions related to wearable devices that utilize heart rate data and movement for sleep tracking. For instance, it mentions 'Automatic sleep and wake classifier with heart rate and pulse oximetry,' highlighting the use of heart rate data to differentiate between sleep states, which aligns with the claim regarding the use of heart rate data to estimate sleep stages.


Input: Task: contrast the claim using the given text. Claim: All indoor plants can purify the air as effectively as air purifiers. [SEP] Text: These include (Figure 1), Areca Palm, (Figure 2), Fern, (Figure 3), -- etc [4]. Their efficiency was confirmed by carrying out studies in controlled conditions simulating the natural environment, over a 24- hour period. The process mechanism involves toxic chemicals being absorbed by the plant through stomata and then transferred to the roots where the microbes break down the wide varieties of unhealthy compounds into simpler molecules which could be reabsorbed by plants [5]. Figure 1: Aloe Vera. Figure 1: Aloe Vera. 2: Arrowhead Vine. Figure 2: Arrowhead Vine. 3: Bamboo Palm. Figure 3: Bamboo Palm. of there are no ranking system or ranks available w. r. t indoor plants due to various reasons such as lack of awareness, dearth of research on indoor air pollution owing to high cost etc. To overcome the resultant gap in literature, the present study advents a new technique with sequential weightage analysis to rank the indoor plants. ideal ranking approach for indoor plants was developed in this study by a sequence of simple steps. Firstly, all the major indoor plants (available in the literature till date) which purify the polluted indoor environment were compiled, and then screened for obtaining clarity on which all pollutant or pollutants they were able to remove as cited in available literatures. Further weightage analysis was carried out in two stages. Firstly, 30% weightage was decided based on the number of indoor air pollutants. Secondly 70% weightage was affirmed based on the frequency & magnitude of the pollutants removed i. e. , removal efficiency based on the removal rate & initial concentration. This part of the computation was majorly based on severity of the indoor air pollutant removed; hence it was ascertained according to the ranking of indoor air pollutants. Presumably, an ideal ranking technique would rank highest those pollutants whose abatement would produce the greatest benefit. For this five sequential criterions focusing on priority wise classification to develop the final ranking. Primarily, from an exhaustive literature survey, all the potential sources contributing to indoor air pollution were identified. Secondly, all the toxic indoor air pollutants were extracted from databases of E. P. A. and W. H. O. In the next step, frequency assessment was carried out for sources and pollutants based on emission and occurrence. The list was then prepared for subsequent stages of assessment. [SEP] Justify:

Output: The text contrasts the claim by discussing research on indoor plants' air purification efficiency and indicates that there are no existing rankings or conclusive evidence categorizing their effectiveness relative to air purifiers. It mentions the development of a ranking technique based on removal efficiency and highlights that various factors influence the ability of indoor plants to purify the air, suggesting variability in their effectiveness compared to air purifiers.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: 56 hectares located within the town of Mitú, the Capital of the Department of Vaupés Medio, in the Vaupés Medio zone, was chosen as the study area (Figure 1). This area includes 10 indigenous communities with 1260 inhabitants distributed as demonstrated in Table 1. According to the Holdridge classification, this region is located within the Forest life system zone, between 185 to 205 meters above sea level, with an average temperature of 25. 7°C, 3000mm maximum annual rain fall, relative humidity is always above 80%, and the sun shines on average 1,255 hours annually. 15 Figure 1 Geographical location of the study area. of Inhabitants* Number and % of Vista del Tuy 85 0°43'25. 29'' N and 70°54'50" O 2 (6. 06) 2 57 0°50'24. 86" N and 70°56'47. 98" O 4 (12. 12) 6 105 0°48'11. 09'' N and 70°57'. 16. 20' O 9 (27. 27) 19 San José de Ñamú 186 0°55'44. 89'' N and 70°33'. 24. 80' O 2 (6. 06) 6 Yuruparí 240 0°51'56. 68'' N and 70°59'. 56. 68'' O 6 (18. 18) 13 de los Cerros 84 0°52'46. 24'' N and 70°43'18. 19'' O 2 (6. 06) 4 de Mandí 171 1°05'59. 17'' N and 70°43'10. 31'' O 2 (6. 06) 4 del Ti 127 0°48'05. 68'' N and 70°42'01. 97'' O 1 (3. 03) 0 de Lima 84 0°57'35. 61'' N and 70°4345,55'' O 1(3. 03) 1 Nazaret del Ti 121 0°51'24. 50'' N and 70°41'31. 46'' O 3 (9. 09) 2 Total 33(100) 57 Table 1 Geographical characteristics of the ten communities in the Middle Vaupes. *Data reported by Felipe Rodriguez, the indigenous president of the Association of () in 2010. Altitude (m. s. n. m): 180. [SEP] Justify:

Output: The text discusses geographical and demographic information about indigenous communities in the Vaupés Medio zone, including data about their inhabitants and environmental conditions. However, it does not provide any information regarding traditional medicines or their derivation from plants used by these cultures. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some wearable devices use heart rate and movement data to estimate sleep stages. [SEP] Text: Wearable and app-based resilience modelling in employees: exploring the possibilities to model psychological resilience using wearable-measured heart rate variability and sleep Herman de output: Thesis › Thesis fully internal (DIV) 332 Downloads (Pure) has a major impact on both an individual and a societal level. Early recognition of the negative impact of stress or reduced resilience can be used in personalized interventions that enable the user to break the identified pattern through timely feedback, and thus limit the emergence of stress-related problems. The emergence of wearable sensor technology makes it possible to continuously monitor relevant behavioral and physical parameters such as sleep and heart rate variability (HRV). Sleep and HRV have been linked to stress and resilience in population studies, but knowledge on whether these relationships also apply within individuals, which is necessary for the aforementioned personalization, is lacking. This thesis introduces a cyclical conceptual model for resilience and four observational studies that test relationships between sleep, HRV and subjective resilience-related outcomes within participants using different types of data analysis at different timeframes. The relationships from the conceptual model and the related hypotheses are broadly confirmed in these studies. Participants tended to have more favorable subjective stress- and resilience-related outcomes on days with a relatively high resting HRV or long total sleep duration. Also, having a resting HRV that fluctuates relatively little from day to day was related to less stress and somatization. However, the strength of the relationships found was modest. The current findings can therefore not yet be directly implemented to initiate meaningful feedback, but they do provide starting points for future research and take a relevant step towards the possible future development of automated resilience interventions. Original languageEnglishQualificationDoctor of PhilosophyAwarding InstitutionUniversity of GroningenSupervisors/AdvisorsSanderman, Robbert, Supervisorvan der -supervisorKamphuis, W. , Co-supervisor, External personAward date15-Mar-2023Place of Publication[Groningen]PublisherUniversity of 978-94-6473-039-5DOstatusPublished - 2023 Access to Document 10. 33612/diss. 572706492Complete thesisFinal publisher's version, 23 MBPropositionsFinal publisher's version, 113 KB Handle. netPersistent link into the research topics of 'Wearable and app-based resilience modelling in employees: exploring the possibilities to model psychological resilience using wearable-measured heart rate variability and sleep'. Together they form a unique fingerprint. [SEP] Justify:

Output: The text corroborates the claim by discussing the emergence of wearable sensor technology that enables continuous monitoring of behavioral and physical parameters, specifically mentioning sleep and heart rate variability (HRV). This relates directly to the claim about wearable devices utilizing heart rate data to estimate sleep stages, since HRV is often linked to sleep quality and potentially used in sleep analysis.


Input: Task: contrast the claim using the given text. Claim: All indoor plants can purify the air as effectively as air purifiers. [SEP] Text: Herein it may be observed that (ranking-1), (ranking-1), (ranking-2) and (ranking-2) are the top 4 plants in naturally purifying the indoor air. Nevertheless it is not merely the number of pollutants removed that matter, but the severity of each of these pollutants which can reveal the true potential of each plant species in purification of indoor air. chart 2: Count of removal by Indoor Plants. chart 2: Count of removal by Indoor Plants. applying 70% weightage analysis, the Revised-Final ranking was arrived at wherein it may be inferred that (ranking-1), (ranking-2), (ranking-3) and (ranking-4) are the top 4 natural purifiers of indoor air. The deviation from initial to and revised final ranking for all indoor plants is presented under Table 1. As a credibility check; the plants securing final top rankings were also found to be mentioned in EPA’s list of best [2] and in NASA’s list of best [3]. While EPA list was generic, NASA listed the indoor plants on their merit basis in terms of their for by studying only limited Pollutants. As the studies by EPA and NASA were inadequate in terms of the range of indoor plants and indoor air pollutants addressed; the present result need not necessarily satisfy the hierarchy developed by them. As can be observed from (Table 1); plants ranked within top ten as per present research (such as and ranked 7, 6, 9, 1, 4, 9 and 5 respectively) was not even rated by NASA. Lily which was ranked 2nd in present study was rated only 7. 5 by Table 1: Step-wise Development of of Indoor Plants. Name of the Plant/ 04 21 7. 5 04 20 -- 03 10 -- Palm 05 25 7. 8 03 12 7. 8 04 11 8. 4 Fern 05 25 -- 03 08 8. 0 01 03 7. 8 05 24 -- 02 02 7. 5 03 16 8. 5 03 07 -- 05 25 8. [SEP] Justify:

Output: The text contrasts the claim by indicating that while certain plants rank highly as air purifiers, the effectiveness of indoor plants varies and is not on par with air purifiers. It notes that not merely the number of pollutants removed matters, but also the severity of each pollutant and acknowledges that the studies by the EPA and NASA were inadequate in addressing the full range of indoor plants and pollutants. Furthermore, it suggests that the results from the current study challenge the rankings established by EPA and NASA, implying that the purification ability of many indoor plants may not meet the standard of effectiveness claimed in the statement.


Input: Task: pass the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: The rainy season is between March and July, with monthly precipitations that oscillate between 250 and 300 mm. The least rainy period occurs between August and October and is called “Indian summer or time of the worm”. The dry period occurs between November and February. The indigenous communities studied can be found between tributaries of the creeks Ti and Tui on the shores of the Vaupés river, known specifically as the Vaupés Medio. In this region located between Pucarón and Yacayacá, there are 22 indigenous communities with approximately 2684 inhabitants, belonging mostly to the ethnic groups: and Tukano. Additionally, there are small populations of ethnic groups representing the Siriano, Yurutí, Barazano, Makuna, Pisamira, Taiwano, and Desanos peoples, as well as non-indigenous people, all members of the Association of Vaupés Medio (). The majority of these ethnic groups are not found within their ancestral territories, displaced from other Amazonian territories due to the phenomenon of rubber harvesting (Felipe Rodriguez, Personal communication, 2006. ). The indigenous economy in this zone is subsistence, coming from agricultural activities known as “chagras” or small plantations, fishing, hunting and collection of wild species. 16 Ethics Initially, the researchers informed the community of the objectives and expectations of the study and invited the traditional healers to participate. The key informants who offered to participate read the informed consent, if they could not read; it was translated to Cubeo and read to them. The translator is the first author of this work, is indigenous Cubeo and is knowledgeable of some dialects spoken in the zone. Subsequently, the informed consent was signed and in the case of those who did not know how to sign, their finger print was used. The informed consent had the approval of the from the Institute within the of the University of Antioquia. Coordination with the community At the 2007 congress of the indigenous organization of Vaupés Medio, the first contact with the communities in this zone was made. Attending were approximately 70 people, among them leaders and inhabitants from the community, permitting a space for discussion and knowledge sharing. Additionally, consent for the collection of information for the study was obtained. During this event the study design and proposal was presented to traditional authorities. [SEP] Justify:

Output: The text does not address the claim about traditional medicines derived from plants used by indigenous cultures. Instead, it provides information about the indigenous communities' geographical location, economic activities, and the process of informed consent for a study on these communities. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Wearable sleep monitors can help users identify habits affecting their sleep. [SEP] Text: Consistent with the assessment of sleep quality using the PSQI, questions were asked if participants were experiencing sleep disturbances at the time they download Calm (i. e. , difficulty with falling asleep, staying asleep, waking too early, or getting restful sleep. App usage patterns were evaluated with questions about how often participants used Calm in general (i. e. , number of times per week) and how often they used specific Calm components at night for sleep (i. e. , Sleep Stories, sleep meditations, non-sleep meditations, and music/soundscapes). Perceived benefit of using Calm was explored by asking participants about the extent to which they believed Calm usage had helped to improve their sleep disturbance. Specifically, participants were asked whether using Calm very much improved (= 3), somewhat improved (= 2), or caused no noticeable improvement (= 1) in their sleep. The questions for mental health conditions (i. e. , anxiety, depression, PTSD) followed the same format (i. e. , diagnosis and then perceptions of improvement). Statistical analysis Analyses were conducted using 26. 0. Frequencies and descriptive statistics were used to characterize the sample and to examine app usage patterns. Correlations were used to examine within-participant associations between sleep quality and app usage. Associations between app usage and improvements in sleep and mental health were assessed in stepwise models using the PLUM ordinal regression procedure. At step 1, models regressed self-reported improvements in sleep and mental health outcomes onto app usage frequency. To examine whether severity of sleep disturbance moderated the relationship between usage and perceived improvements, PSQI score usage × PSQI were added as predictors in Step 2. Goodness of fit was evaluated via -2 log-likelihoods, Pearson’s chi-square, and pseudo R2 statistics. To correct for multiple testing, Bonferroni-adjusted p-values were used to determine significance. Given the likely correlations between use of different Calm components, individual-component models were followed up with multivariate models that included all components as simultaneous predictors. To reduce risk of over-fitting, only significant PSQI score usage × PSQI interactions were retained in multivariate models. ResultsThere were 366,173 subscribers who received an invitation to participate. Of those, 5. 6% (n = 19,341) accessed the survey, 4. [SEP] Justify:

Output: The text discusses how participants were asked about their sleep disturbances and the perceived benefits of using the Calm app, which is relevant to identifying habits that affect sleep. The assessments included evaluating app usage patterns and self-reported improvements in sleep quality, indicating that tools like Calm can help users recognize how their behaviors impact sleep.


Input: Task: contrast the claim using the given text. Claim: All indoor plants can purify the air as effectively as air purifiers. [SEP] Text: 5 Schefflera 03 06 -- 03 09 -- 05 24 -- Azalea 06 27 -- 04 12 -- 01 01 -- Philodendron 06 27 -- 02 04 -- Ivy 05 23 -- Philodendron 06 27 -- Philodendron 03 09 -- 05 25 -- 06 28 -- 03 05 -- 05 22 -- Warneckei 04 14 -- Chrysanthemum 04 13 -- Mother-in-law's tongue 04 15 -- Plant 06 27 -- Dracaena "Janet Craig" 05 28 7. 8 04 18 -- 04 17 -- 04 19 7. 7 Marginata 05 26 -- Table 1: Step-wise Development of of Indoor Plants. Close NASA, much below to other lower ranked plants such as (NASA rating 8. 5 & ranked 16 by present study), (NASA rating 8. 5 & ranked 25 by present study), (NASA rating 8. 4 & ranked 11 by present study), (NASA rating 8. 0 & ranked 08 by present study), Palm (NASA rating 7. 8 & ranked No. 25 by present study), (NASA rating 7. 7 & ranked No. 19 by present study) and Craig (NASA rating 7. 8 & ranked No. 12 by present study). Ironically, which shares same rating by NASA of 7. 5 is ranked a far low at 21 by present study). However, with a NASA rating of 7. 8 has been ranked 3rd. These discrepancies are due to the fact that the NASA studies did not consider the severity of each indoor air pollutant or encompass the entire range of indoor plants as undertaken in present study. The present study was entirely dependent on secondary data, which also was sparse owing to factors such as limited research and cost of pollution analysis. is highly recommended to have indoor plants that perform natural detoxification of indoor air environment. However not all the indoor plants available have this ability and those having present varied capacity, and neither does the literatures confirm specifically which indoor plants are better than the rest. To overcome this lacuna, the present study advents a new technique with sequential weightage analysis to rank the indoor plants. The study arrived at the conclusion that and are relatively the best in terms of pollutants removal efficiency. Ranking of the indoor plants thus also gives an economic edge in the selection of the finest plants for variable toxic indoor environment. [SEP] Justify:

Output: The text contrasts the claim by stating that 'not all the indoor plants available have this ability' to purify the air. It emphasizes that there is variability in the capacity of indoor plants to perform air purification, and the literature does not confirm which indoor plants are superior to others. This counters the claim that all indoor plants can purify air as effectively as air purifiers.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: 30 this study, most of the respondents are male. Men seem to possess more traditional knowledge of medicinal plants compared to women, possibly due to their increased access to the forest to hunt, collect wild fruits and plants, and obtain material for housing construction and development of tools. These activities allow them to acquire forest-related knowledge, while on the other hand, women are dedicated to the care of charges and care of the house. In the communities represented in this study, women have more access to plants grown in home gardens. The number of woman participants in this study is low because most plants used for malaria are found in the forest. This finding is consistent with research conducted by Boster101 and Garro102 who mentioned that the knowledge of any given person is determined by their role in society (gender, age, division of labor, individual experience), creating differences in access to knowledge. The largest number of species reported, is observed in the community of Puerto Laguna. This result could be due to the presence of the only Paye who participated in the study. is the most influential community member who passes on their knowledge to the younger generations. Yurupari, is a community that also reported a large number of species. This could be due to their proximity to and the observed relationship between the inhabitants of these communities, allowing transmission of knowledge between traditional healers. The families with more genera and species reported are Bignoniaceae (8 species/6 genera) and Fabaceae (4 species/4 genera). According to Gentry103 the Bignoniaceae family predominates among the plants with medicinal use. Gentry identified 27 genera of lianas and nine genera of trees, all with therapeutic properties. The finding in this study of several species belonging to the Bignoniaceae family with antimalarial use may be due to the wide geographic distribution of this family and the presence of secondary metabolites of naphthoquinone, such as lapachol. 104 On the other hand, the Fabaceae family is also often used for medicinal purposes. According Leonti, this is probably due to its abundance and high diversity of active constituent chemicals with organoleptic properties. 97 Alkaloids, flavonoids and polyphenols have been isolated from this family. The activity of these metabolites is associated with antidiabetic106 anti-inflammatory106 and antimicrobial effects. [SEP] Justify:

Output: The text corroborates the claim by discussing the knowledge of medicinal plants related to traditional medicine and indigenous cultures. It highlights the role of community members in passing on knowledge about medicinal plant species, specifically referencing families of plants like Bignoniaceae and Fabaceae, which are used for medicinal purposes. The mention of specific species and their therapeutic properties further supports the idea that traditional medicines are indeed derived from plants used by indigenous cultures.


Input: Task: corroborate the claim using the given text. Claim: Wearable sleep monitors can help users identify habits affecting their sleep. [SEP] Text: PSQI total and component scores. half of participants reported having been diagnosed with at least one mental health condition when they initially downloaded Calm (44. 3%, n = 4,386), the most common being anxiety disorders (29. 6%, n = 2,930) and depression (26. 8%, n = 2,657). Additionally, 8. 0% (n = 790) reported a diagnosis of PTSD. App and component engagement On average, participants used Calm five times per week (see Table 3). were the most commonly used component at night for sleep. There were significant moderate correlations between reported usage frequencies across almost all individual components, except that frequency of using was not related to the frequency of using general (i. e. , not sleep-specific) meditations at night. PSQI scores were also correlated with app usage, but these effects were small. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 3. Correlations between frequencies of using individual Calm components. Improvements in sleep The majority of participants reported that using Calm helped them fall asleep (90. 0% reported somewhat or very much improved), stay asleep (69. 7%), and get restful sleep (79. 2%), but the small proportion of individuals who reported problems waking up too early did not notice improvement in this area (39. 6%; see Table 4). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 4. Frequencies of reported improvements in sleep disturbance. Step 1, frequency of using Calm at night was positively associated with perceived improvements in all aspects of sleep (i. e. , falling asleep, staying asleep, getting restful sleep, and not waking too early; see Table 5). 2, there were no significant main effects of PSQI, but there were significant interactions in which PSQI scores moderated the relationship between the frequency of using Calm and improvements in staying asleep and getting restful sleep, such that participants who reported more severe sleep disturbance benefitted more from using Calm with regard to improvements in staying asleep and getting restful sleep (see Table 6). Although using Calm was also associated with improvements in falling asleep and waking too early, these improvements did not differ based on severity of sleep disturbance. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 5. [SEP] Justify:

Output: The text corroborates the claim by indicating that participants reported improvements in various aspects of sleep after using the Calm app, which suggests that such digital tools can assist users in identifying and managing their sleep habits. Specifically, it mentions that '90.0% reported somewhat or very much improved' sleep outcomes, which aligns with the idea that wearable sleep monitors can help users identify habits affecting their sleep.