Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: These intensity differences are larger for the Weser/Ems, Oder and Danube catchments and even statistically significant for the former two, compared to the Rhine and Elbe. This is consistent with the result from the composite analysis that dynamical factors distinguish MEPEs from LEPEs in the former three catchments (see Sect. 4. 2. 2). In addition to the cyclone pathway and intensity, its velocity may be an important factor for extreme precipitation, as slower-moving systems can lead to a larger precipitation accumulation at a specific location. In order to analyse cyclone velocities, Fig. 10 shows the travelled distances of tracked cyclones in 6-hourly intervals for MEPEs (in red) and LEPEs (in blue). Only on the day of the events and the previous day can reasonable distributions be produced, as the number of identified cyclones is too low during earlier periods (see grey bars in Fig. 10). In general, cyclones tend to decelerate on the day of the event compared to the previous day, which is consistent with the hypothesis that slower-moving cyclones can enhance the precipitation amounts in the river catchments. However, comparing cyclone velocities between MEPEs and LEPEs during the day of the extreme events shows that there is a large scatter and no clear difference in the median velocities. Similar results are found for the other river catchments (not shown). Only for the Elbe and Oder catchments is there a slight tendency towards slower cyclones for MEPEs compared to LEPEs. Figure 10Distributions of travelled distances during 6-hourly time intervals of tracked cyclones during (red) MEPEs and (blue) LEPEs over the Danube catchment. The grey bars show the absolute cyclone counts at each time step for (dark grey) MEPEs and (light grey) LEPEs. The time on the x axis is specified relative to the occurrence of the extreme event, and 0 h corresponds to the end of the daily event. summary, the results of the cyclone tracking analysis show that extreme precipitation events in the selected river catchments are associated with typical cyclone tracks from the south towards the east of the respective catchment and with a deceleration of the cyclones during the day of the event.

Output: corroborate


Input: Claim: All high-paying jobs require a college degree. [SEP] Text: In the second stage of our analysis, we used a meta-analytic approach to summarize findings across institutions (Cooper & Hedges, 1994; Lipsey & Wilson, 2001). Although the impact studies for each institution followed a generally consistent approach, there was some variation among the OER initiatives and the institutions rolling them out as described (see the “Research context and procedure” section). Using meta-analysis offered more flexibility to combine the results across individual studies with variation as compared to combining the data into a single analysis. Though it was not possible to test for interactions between student- and institutional-level characteristics, our meta-analytic approach allowed us to explore implementation and study design features that are associated with the size of the impact in different institutions. ResultsDescriptive statisticsTable 3 presents the characteristics of the final analysis samples for each site in terms of size and student demographics. These data are for the matched samples, after propensity score matching was used to establish baseline equivalence between the treatment and comparison conditions. The sample size available for analysis ranged considerably across the 11 colleges, with some having samples in the low hundreds and others approaching 5,000. With the exception of one site, the average student age was around 20 years old. At least a third or more of the sample at each college consisted of students eligible for or who had received Pell grants. The proportion of students from historically underrepresented ethnic minority groups ranged considerably across colleges from 25 to 88%. Table 3 Demographic characteristics of the final analysis samples, by collegeFull size tableRQ1 main impact analysisCredit accumulationIn 6 of the 11 colleges, treatment students taking OER courses accumulated significantly more course credits than those who had not taken any OER courses (see Table 4). The number of additional credits accumulated by treatment students ranged from 2 to 8 across these six schools. In the remaining 5 colleges, students’ credit accumulation in the two conditions was not statistically different after controlling for differences in student characteristics. Table 4 Credit accumulation results, by collegeFull size tableTable 4 also shows the estimated effect size for each of the research partner colleges on credit accumulation. An effect size is a standardized measure of the magnitude of an effect and is calculated as the standardized mean difference between two groups. The effect size increases in magnitude as the difference between the groups on the outcome measure gets larger. The U. S. Department of Education’s Clearinghouse (2017) defines effect sizes equal or greater than 0.

Output: pass


Input: Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: Neuroimage 2002;15:273–89. ↵Differential fractional anisotropy abnormalities in adolescents with ADHD or schizophrenia. 2010;181:193–8. ↵White-matter abnormalities in attention deficit hyperactivity disorder: a diffusion tensor imaging study. Mapp 2009;30:2757–65. ↵Development of cortical asymmetry in typically developing children and its disruption in attention-deficit/hyperactivity disorder. Psychiatry 2009;66:888–96. ↵Smaller prefrontal and premotor volumes in boys with attention-deficit/hyperactivity disorder. 2002;52:785–94. ↵Ten years of Neuroscience: insights from the highly cited. Neurosci 2010;11:718–26. ↵White matter microstructure in superior longitudinal fasciculus associated with spatial working memory performance in children. J 2011;23:2135–46. ↵Fassbender C, Schweitzer JB. Is there evidence for neural compensation in attention deficit hyperactivity disorder? A review of the functional neuroimaging literature. Rev 2006;26:445–65. ↵Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. 2005;57:1336–46. ↵Multimodal imaging of the self-regulating developing brain. 2012;109:19620–5. OpenUrlAbstract/↵Veazie PJ. When to combine hypotheses and adjust for multiple tests. Res 2006;41:804–18.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: MEPEs are linked to higher cyclone frequencies and also to more intense cyclones compared to LEPEs, in particular in the Oder, Danube and Weser/Ems catchments. However, the cyclones' translation velocities are similar for MEPEs and LEPEs and thus do not allow for distinguishing 100-year events from less extreme precipitation events. 5 Discussion and conclusion The aim of this study has been to robustly investigate the atmospheric processes during 100-year precipitation events in large central European river catchments and their differences compared to less extreme events. A better understanding of these high-impact events may be instrumental to provide more accurate forecasts of river floods and reduce uncertainties in projections of their potential future changes. To perform such a robust process analysis, we use a large dataset of model-generated daily precipitation fields obtained from the ECMWF operational ensemble weather prediction system following a method introduced by Breivik et al. (2013). Statistical analyses show that the 10th forecast days from these simulations produce quasi-independent precipitation events, in particular with regard to extremes such as annual maxima, and that the intensity distribution of these simulated events lies within the uncertainties obtained from different observational datasets. With the help of extreme value theory, return levels of 100-year and more moderate, 20- to 50-year extreme precipitation events are determined for each selected river catchment, and the events surpassing these return levels are investigated with regard to the underlying atmospheric conditions. An analysis of the temporal and spatial characteristics of the extreme precipitation events shows that most 100-year events occur during the extended summer June–September, with only a few exceptions in May or October. This corresponds well with historical precipitation extremes (e. g. Grams et al. , 2014; Ulbrich et al. , 2003) and statistical analyses of rain gauge data (Fischer et al. , 2018). More moderate precipitation extremes also peak during the summer season but may occur during winter in the Rhine and Weser/Ems catchments as well. The spatial distribution of precipitation during the extreme events is influenced by the topography of the catchments, in particular by the orographic effect of the Alps in the Danube and Rhine catchments. In order to determine the characteristic atmospheric conditions associated with the 100-year precipitation events, a composite analysis is used in combination with a cyclone tracking algorithm.

Output: corroborate


Input: Claim: Climate change has contributed to more frequent and intense heatwaves. [SEP] Text: Meanwhile, the two ensembles agree with the two reanalyses in terms of negative heat flux anomalies at remote locations along the eastern and southern flanks of the blocking regions. The negative heat flux anomaly is spatially coincident with below-normal heatwave frequency for each ensemble and reanalysis, implying that the negative anomalies can, along with cold air advection, contribute to below-normal heatwave frequency. Fig. 5a Net surface heat flux anomaly and c temperature advection anomaly (850 hPa) with wind vector anomaly (arrows over grid points) of ERA-Interim, NCEP-DOE-R2, and CanESM2 and CanESM5 ensemble averages (EAs) when blocking occurs in BR2 and BR3 for 1981–2010 baseline, and b, d those of CanESM2 and CanESM5 EAs for 2071–2100 future period. Black dots over grid points in (a) and (c) of ERA-Interim and NCEP-DOE-R2 represent statistical significance at the 10% significant level tested by bootstrap approach. Larger dot size of CanESM2 and CanESM5 ensembles represents larger number of ensemble members yield statistical significance (percentages of the number are defined in the legend)Full size imageThe two models simulate similar spatial patterns of 850 hPa temperature advection anomalies as the two reanalyses over (Fig. 5c). In particular, strong negative temperature advection anomalies are found on the eastern and southern flanks of the blocking cores, due to northerly and/or north-easterly wind anomalies that result from anomalous clockwise anti-cyclonic circulation. This spatial pattern of negative temperature advection anomalies over during blocking is in line with findings over Europe (e. g. , Trigo et al. 2004; Sousa et al. 2018). Below-normal heatwave frequency at remote eastern and southern regions away from blocking cores (Fig. 3a) can be explained by the negative temperature advection anomalies. Meanwhile, the two climate models and the reanalyses display positive temperature advection anomalies on the southwestern and western regions away from the blocking cores. These are driven by southerly wind anomalies associated with anomalous anti-cyclonic circulation during blocking and they result in above-normal heatwave frequency in those regions.

Output: contrast


Input: Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: / 2003 Emotion and intuition : Effects of positive and negative mood on implicit judgments of semantic coherence 14 (5) : 416 ~ 5 4. [학술지] Botvinick, M. M. / 2001 Conflict monitoring and cognitive control 108 (3) : 624 ~ 3 5. [기타] Bradley, M. M. / 2007 Sounds (2nd Edition; IADS‐2): of Sounds and NIMH Center for the Study of Emotion and Attention 6. [학술지] Choi, Y. / 2015 International affective digitized sounds in Korea : a cross-cultural adaptation and validation study united with Acustica 101 (1) : 134 ~ 1 7. [학술지] Dreisbach, G. / 2004 How positive affect modulates cognitive control : Reduced perseveration at the cost of increased distractibility Journal of : and Cognition 30 (2) : 343 ~ 2 8. [학술지] Egner, T. / 2007 Congruency sequence effects and cognitive control & 7 (4) : 380 ~ 4 9. [학술지] Fan, J. / 2002 Testing the efficiency and independence of attentional networks Journal of 14 (3) : 340 ~ 3 10. [학술지] Fredrickson, B. L. / 2005 Positive emotions broaden the scope of attention and thought‐action repertoires Cognition & Emotion 19 (3) : 313 ~ 3 11. [학술지] Glickman, M. / 2018 Attentional capture by irrelevant emotional distractor faces is contingent on implicit attentional settings Cognition & Emotion 32 (2) : 303 ~ 2 12. [학술지] Gratton, G. / 1992 Optimizing the Use of Information-of Activation of Responses Journal of : General 121 (4) : 480 ~ 4 13. [학술지] Gray, J. R. / 2004 Integration of emotion and cognitive control in 13 (2) : 46 ~ 2 14. [학술지] Hodsoll, S. / 2011 by Emotion 11 (2) : 346 ~ 2 15.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: This is especially relevant for the Danube and Rhine catchments, as a northerly flow towards the Alps enforces orographic precipitation enhancement. Previous case studies have shown that, during such situations, typically various moisture sources contribute to the precipitation, with evapotranspiration from the land surface often playing a dominant role (Krug et al. , 2022; Grams et al. , 2014; Winschall et al. , 2014). The important role of moisture transport in particular for orographic precipitation associated with European floods has already been recognised in previous studies (Gvoždíková and Müller, 2021; Froidevaux and Martius, 2016). To identify the mechanisms that distinguish the very extreme, 100-year precipitation events (MEPEs), they are compared to a sample of less extreme events with return periods between 20 and 50 years (LEPEs). The general synoptic-scale patterns associated with LEPEs are similar to MEPEs, with an upper-level trough over western Europe on the day before the event that often develops into a cutoff low, going along with surface cyclogenesis slightly downstream. The specific differences between MEPEs and LEPEs depend on the river catchment. On the one hand, differences in dynamical processes are the most important for the Danube and Oder catchments. In particular, the cutoff low is intensified, surface cyclogenesis occurs more regularly and the surface cyclones are also more intense during MEPEs compared to LEPEs. This is expected to enhance moisture transport towards the catchments and dynamical forcing for ascent in the catchments, resulting in stronger precipitation. These results are in slight contrast to the findings of Pfahl and Wernli (2012), who did not detect differences in the intensity of cyclones associated with extreme precipitation in central Europe. This is likely due to the fact that they analysed less extreme events than those studied here. The difference in cyclone intensity thus appears to be a specific characteristic of very extreme, 100-year events. However, there are no clear differences between the translation velocities of cyclones associated with MEPEs and LEPEs. On the other hand, MEPEs in the Elbe and Rhine catchments differ from LEPEs mainly due to significantly higher temperature and lower-tropospheric moisture content over large areas east and northeast of the river catchments.

Output: corroborate


Input: Claim: Climate change has contributed to more frequent and intense heatwaves. [SEP] Text: Cat 4–5 proportions are lower than those for the global hurricane data, an expected result since high intensities are only maintained for a relatively short period of the overall cyclone lifetime and could easily be missed by the similarly short period spent within landfall range. The slope of the Cat 4–5 trend for this land-proximity subset is ~27 % per °C, essentially the same as the ~29 % per °C from the Kossin (2012) homogenized satellite data in Fig. 6a. Fig. 7Relationship of anthropogenic change to annual proportions of Cat 1–2 and Cat 4–5 hurricanes in proximity to land. A 5-year running mean smoothing has been used, thin solid lines indicate linear trends, and all variances have p < 0. 01 (using unsmoothed data)Full size image General agreement with Fig. 7 is found for landfall in each ocean basin except the Ocean and the western North Pacific. The landfall rarity of intense Ocean hurricanes means the data are too noisy for analysis. For the western the trend is very weak and slightly negative, which we attribute to a general eastward and equatorward movement of the main genesis location in recent decades (Wu and Zhao 2012). This promotes the development of a higher proportion of intense hurricanes, but also means that fewer of them will make landfall. Weinkle et al. (2012) examined the global number of hurricanes that actually make landfall in each of the Saffir–Simpson categories. The proportion of Cat 4–5 at landfall to all landfall hurricanes in their data set has increased with ACCI at a rate of ~21 % per °C (p < 0. 01) since 1975. This study leads us to the following observational conclusions. Over the past few decades there has been an observed ~40 % per °C trend relative to the ACCI in the proportion of 4–5 hurricanes (p < 0. 01) and a compensating decrease in Cat 1–2 proportions. Comparison with the Kossin (2012) homogenized satellite data and with global sets of tropical cyclones in proximity to land indicates that changing analysis and observing practices may have contributed 10–15 % of the trend. This leaves a real trend in the proportion of Cat 4–5 hurricanes of 25–30 % per °C that is directly attributed to anthropogenic warming as defined by the ACCI.

Output: pass


Input: Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: [학술대회] Hristova, P. / 2011 Anxiety fosters relational encoding Proceedings of the on cognitive Science: on 16. [학술지] Isen, A. M. / 1992 An influence of positive affect on social categorization Motivation and Emotion 16 (1) : 65 ~ 1 17. [학술지] Kazen, M. / 2005 Intention memory and achievement motivation : Volitional facilitation and inhibition as a function of affective contents of need-related stimuli Journal of Personality and 89 (3) : 426 ~ 3 18. [학술지] Kim, C. / 2016 of the Running- Location on Choice Psychology 30 (6) : 1014 ~ 6 19. [학술지] Kuhl, J. / 1999 Volitional facilitation of difficult intentions : joint activation of intention memory and positive affect removes stroop interference Journal of : General 128 (3) : 382 20. [학술지] Lang, P. J. / 1997 Picture System(IAPS) : NIMH Center for the Study of Emotion and Attention 1 : 39 ~ 21. [학술지] Lindsay, D. S. / 1994 Dissociations-the Relationship between Facilitation and Interference Journal of : and Performance 20 (2) : 219 ~ 2 22. [학술지] Lu, C. H. / 1995 of Information on Performance-a Review of the Simon and Effects &Review 2 (2) : 174 ~ 2 23. [학술지] MacLeod, C. M. / 1991 Half a century of research on the Stroop effect : an integrative review 109 (2) : 163 ~ 2 24. [학술지] Mayr, U. / 2003 Conflict adaptation effects in the absence of executive control 6 (5) : 450 ~ 5 25. [학술지] Miller, E. K. / 2001 An integrative theory of prefrontal cortex function Neuroscience 24 : 167 ~ 26. [학술지] Padmala, S. / 2011 Negative emotion impairs conflict-driven executive control Frontiers in Psychology 2 : 192 27.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: September 01 2023 Connecting extreme weather events to climate change Advances in attribution science are improving understanding of human influence on our planet. Search for other works by this author on: PubMed 10. 1063/PT. 3. 5309 Open the PDF for in another window and Connecting extreme weather events to climate change. 1 September 2023; 76 (9): 40–46. Download citation file: Ris (Zotero) toolbar search Menu toolbar search search input Search input auto suggest filter your search his house in Oxford, UK, was flooded by an exceptionally rainy storm in January 2003, proposed that the anthropogenic influence on severe weather events could be quantified. 1 Before that, most climate scientists avoided discussing how human activity affected individual extreme weather events. Rather, they would deflect, saying, for example, “While no individual event can be tied to climate change, whatever happened is consistent with expectations. ” That statement is no longer true. Using extreme-event attribution techniques, it is now possible to make quantitative statements about the human influence on many classes of individual weather and climate events. View largeDownload slide. COM/E4CView largeDownload slide. COM/E4C Close modal In 2003, shortly after Allen’s proposal, central Europe experienced a disastrous heat wave that caused more than 70 000 excess deaths. At the time, using a high-quality record of European temperatures and a single climate model, Allen and colleagues estimated that climate change at least doubled the chances of the measured high daytime temperatures. 2 Since then, the field of extreme-weather-event attribution has expanded to include not just heat waves but also floods, droughts, heavy precipitation, and certain extreme storms, such as hurricanes (reference 3, 2017. (Courtesy of US Guard/Staff Sgt. Daniel J. Martinez. )View largeDownload slidePort Arthur, Texas, was devastated by the overwhelming amount of precipitation from in 2017. (Courtesy of US Guard/Staff Sgt. Daniel J. Martinez. ) Close modal A second technique, known as Granger causality, after the econometrician Clive Granger, can be useful when direct interference in the experiment is undesirable or impossible. In epidemiology, for instance, a study of heart disease in a selected population might consider obesity, smoking habits, family history, and other relevant causal factors. A statistical model that involves those factors as variables can provide information on their possible influence.

Output: corroborate


Input: Claim: Climate change has contributed to more frequent and intense heatwaves. [SEP] Text: Each set of experiments consists of three ensemble members forced by three GCMs. The historical baseline period consists of 31 years from 1975 to 2005 and the projected future period covers 31 years from 2070 to 2100. Selection of the used for specifying the boundary conditions for MRCM are selected from among the many participant models in CMIP5 by applying the following criteria:We adopt the 19 GCMs evaluated favorably by McSweeney et al. 48 based on their performance over Southeast Asia. And then we select 6 GCMs out of the 19 by requiring an oceanic horizontal resolution of 1. 11° or higher, capable of simulating complex ocean processes over this region. Over land, the surface temperature, TW, relative humidity, and precipitation from GCMs are objectively analyzed and compared to CRU43, ERA-Interim41, and TRMM49 datasets. To assess the performance of each GCM, the and annual cycle for each variable are compared separately over two regions (). As a result of applying the above criteria, three GCMs are selected: CCSM445, 1. 0 46, and MPI-ESM-MR47. More detailed information about the GCMs is presented in 1. Bias correctionSimulations by a regional climate model may contain a systematic bias arising from inadequate physics, and/or bias in the global climate model simulations used as lateral boundary conditions50,51. These model biases impact historical as well as future climate change projections. To reduce the impact of this bias, we applied the same bias correction procedure developed by Pal and Eltahir16 for correcting future projections in southwest Asia. This methodology allows correction of daily TWmax. TW is computed by the formulation developed by Davis-Jones52. Reliable reanalysis data at high spatial and temporal resolution is the key to correct bias in simulated daily variables. ERA-Interim reanalysis represents spatially complete and dynamically consistent estimates of the state of the climate system41 and is therefore used for the following bias correction procedure. In the first step, TW is computed by the formulation developed by Davies-Jones52for both the MRCM hourly output and the ERA-Interim reanalysis 3-hourly 0. 75° × 0. 75° data.

Output: pass


Input: Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: 009 김초복 and 이윤지 “of an on Choice by Attention“ 한국심리학회지: 인지 및 생물 31. 2 190. (2019): 181. 김초복 이윤지. of an on Choice by Attention 한국심리학회지: 인지 및 생물 [Internet]. 2019; 31(2), : 181 - 190. Available from: doi:10. 22172/cogbio. 2019. 31. 2. 009 김초복 이윤지. “of an on Choice by Attention“ 한국심리학회지: 인지 및 생물 31, no. 2, (2019): 181 - 190. doi: :10. 22172/cogbio. 2019. 31. 2. 009 텍스트 파일로 저장 피인용 논문 (우)305-754 대전광역시 유성구 가정로 201 한국연구재단 TEL: 042-869-6674, 1544-6118 E-mail: kciadmin@nrf. re. kr 2024 NRF. .

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: For climate, scientists have developed extreme-value statistical models using greenhouse gas concentrations, air pollution, urbanization, El Niño, and other natural modes of variability as covariates to isolate their relative influence on extreme weather. and Granger causal-inference techniques have their strengths and limitations. Granger causal inference may lead to the post hoc, ergo propter hoc fallacy—that correlation does not necessarily imply causality. Additionally, the influence of unspecified covariates must be considered. causal inference relies on models, one must first ascertain whether the model is fit for the purpose at hand. Many extreme weather events are poorly simulated when available public climate model data sets are used, and thus those data sets are unsuitable for attribution studies. Confidence in attribution statements is increased when both Granger and Pearl causal-inference techniques can be invoked and produce similar results. Confidence is further increased when multiple independent research groups use different models, observations, and methods and arrive at similar conclusions. One motivation for performing extreme-event attribution studies is to satisfy the public’s curiosity about how climate change affects them. But an equally important motivation is gaining insight into the physical mechanisms behind the changes in extreme weather events. Borrowing concepts from epidemiology, scientists hope to untangle and quantify the different causal factors. The ongoing work focuses on answering two questions: “Did climate change affect the magnitude of an event of a given estimated rarity? ” and “Did climate change cause the chances of an event of an observed high magnitude to change? ” Extreme heat Those two questions are two sides of the same coin, as illustrated by the abnormally hot temperatures in Texas during the summer of 2011. Figure 1a shows observed Texas summer temperature departures (purple) from the average of the 1961–90 temperatures. Two simulations are shown, one with realistic human changes to the atmospheric composition (orange)—mainly well-mixed greenhouse gas increases, stratospheric ozone decreases, and aerosol pollution—and the other counterfactual (green), in which temperatures are cooler because it doesn’t include the effect of human changes. Both the observations and the predicted data in the realistic model trend upward. The absence of such a trend in the counterfactual simulation reveals that there is an attributable human influence on Texas summer temperatures. Increasingly hot summers are expected. Yet the 2011 temperature, shown by the black dot, was about 2.

Output: corroborate


Input: Claim: Climate change has contributed to more frequent and intense heatwaves. [SEP] Text: By contrast, significant precipitation decreases are mainly seen over South Asia, the tropical western Pacific, the Yellow Sea, the central North Pacific, central NA, and parts of the tropical and central (Fig. 3, top). The reduced precipitation and convection in South Asia—western Pacific indicates weakened summer monsoon activity. This represents an anomalously negative diabatic heating in the tropical region. The TCWV anomaly is broadly similar to the precipitation anomaly over the northern Pacific (Fig. 3, bottom). The area-weighted pattern correlation between the two anomalous fields is 0. 61 over the northern (0-90oN) Pacific. In addition, it is interesting to see an anomalous TCWV path across the mid-latitude North Pacific, indicating a northeastward injection of moisture from the subtropical western Pacific towards western NA. By contrast, the TCWV anomalies are mostly positive over western NA and negative over eastern NA, which differs from the precipitation anomalies over NA. In particular, many areas of increased (reduced) TCWV collocate with reduced (increased) precipitation over the NA continent (Fig. 3). This suggests that the anomalous precipitation is not only related to the water vapor anomaly, but also to other mechanisms such as those responsible for inducing adiabatic vertical motions and moisture convergence (e. g. , Zhang et al. 2011; Mo et al. 2021). Previous observations and climate model results also suggested that deficits in soil moisture would lead to more frequent and severe hot temperatures in summer, and vice versa. The above-normal (below-normal) precipitation often increases (decreases) the soil moisture, which in turn favors less (more) heatwaves (e. g. , Dai et al. 1998; Alexander 2010; Wu et al. 2012). In addition, both precipitation and TCWV anomalies are weak upstream over most of the Eurasian continent. Fig. 3As in Fig. 2, but for precipitation (mmday−1) and TCWV (Kgm−2) anomalies. Contour interval is 0. 2 (…, − 0. 3, − 0. 1, 0. 1, 0. 3, …)Full size imageThe strongest water vapour transport (AR-like feature) often penetrates through a cyclone-anticyclone couplet.

Output: contrast


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: Full text Figures and data Peer review Side by side Peer review process Decision letter Author response Peer review process This 330. This would enable more rapid sgRNA insertion (due to two unique restriction digest sites) instead of sequential amplification, gel purification, and ligation. 5) Regarding the FRAP experiments, could the authors expand their discussion on the difference between their measurements obtained on endogenous levels of receptors and those previously obtained on overexpressed receptors. 6) In the cell specific approach, could the author provide feedback on Cas9 cell expression versus viral Cas9 expression. Author response Essential revisions: 1) The finding that a small fraction of neurons undergo GluA2 KO is puzzling, since no KO alleles were detected in genomic PCR (Figure 4—figure supplement 2). Is it more likely that the same fraction of neurons would lack GluA2 expression in non-transfected controls? Or controls that only receive mCherry plasmid transfections? Complete KO would require successful targeting at both alleles, without donor insertion at either one. Either way, if complete KO in some cells is a possibility, this could be investigated more systematically (or at least discussed more thoroughly) since it may influence potential results. To address the possibility of there being GluA2-lacking cells in non-transfected neurons, we have performed immunofluorescence on cultured mouse cortical neurons. We found that 1. 2% of neurons analyzed had no detectable levels of GluA2. Therefore, we can confirm the reviewers suspicious that a small fraction of neurons is, indeed, naturally GluA2-lacking. In comparison, we identified around 12. 4% of cell with undetectable GluA2 (i. e. , KO) with transfection of TKIT constructs for SEP-GluA2 KI (Figure 4—figure supplement 2D). Therefore, we think that undetectable GluA2 observed in some cells transfected with TKIT plasmids is an unfortunate, but not completely unexpected, result of gene knockout through double strand break generation without donor insertion. A possible explanation for the creation of these GluA2-KO neurons could also be incomplete co-transfection of all three plasmids (gRNAs/spCas9, donor DNA, mCherry). Cells lacking the donor DNA plasmid will be biased towards gene knockout.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: 5 °C warmer than the average summer and was considered a rare, 1-in-30-year event at the time. Figure 1. View largeDownload slideDeparture from average summer temperatures in Texas. (a) A realistic historical simulation (orange) and a cooler counterfactual climate without anthropogenic climate change (green) are compared with the observations (purple). The black dot represents the observed value of 2. 467 °C for 2011. The solid lines represent the smoothed temperature anomalies. (Adapted from ref. 6. ) (b) Simulations show the likelihood of Texas summer surface air temperature in a realistic climate (orange) and the cooler counterfactual climate (green). A return value (maximum temperature) has a 1/(return time) chance of being met or exceeded in a given year. The dashed line indicates that the observed temperature was a 1-in-30-year event in 2011, and it was 1. 5 °C warmer than it would’ve been without climate change. Figure 1. View largeDownload slideDeparture from average summer temperatures in Texas. (a) A realistic historical simulation (orange) and a cooler counterfactual climate without anthropogenic climate change (green) are compared with the observations (purple). The black dot represents the observed value of 2. 467 °C for 2011. The solid lines represent the smoothed temperature anomalies. (Adapted from ref. 6. ) (b) Simulations show the likelihood of Texas summer surface air temperature in a realistic climate (orange) and the cooler counterfactual climate (green). A return value (maximum temperature) has a 1/(return time) chance of being met or exceeded in a given year. The dashed line indicates that the observed temperature was a 1-in-30-year event in 2011, and it was 1. 5 °C warmer than it would’ve been without climate change. Close modal To answer the two event-attribution questions about changes in event magnitude and frequency, one needs to turn to the climate-model data. Figure 1b shows the return values of average summer temperatures in Texas as a function of time. The return value is the highest average temperature expected to be reached once in a given period of time, known as the return time. The solid orange line, representing the realistic simulation, reveals that an average temperature of 34 °C would occur once in 30 years.

Output: corroborate


Input: Claim: Climate change has contributed to more frequent and intense heatwaves. [SEP] Text: polymictic lakes), which according to Hutchinson's (1957) mixing classification are among the most abundant at mid-latitudes, it is unlikely that the spatial extent of heatwaves will increase within a warming world, as vertical mixing will likely destroy any spatiotemporally connected heatwaves that develop. In lakes that are semi-permanently/permanently stratified (oligomictic/meromictic), such as the deep lakes south of the or those located at low latitudes (e. g. Lake Tanganyika), it is possible that lake heatwaves could respond sensitively to a warming world, with lake heatwaves extending across multiple years, as has previously been observed in the marine environment (Bond et al 2015, and Mantua 2016, Oliver et al 2021). Moreover, as lakes transition to a more stable mixing regime in the future (e. g. from polymictic to monomictic or monomictic to oligomictic; Woolway and Merchant 2019), more lakes will likely experience an expansion in the spatial extent of heatwaves. This is an area for further study. We anticipate the spatial extent of lake heatwaves to increase at a faster rate than observed here in the Great Lakes. This is particularly true in lakes that will lose their ice cover this century (Sharma et al 2019), as lake heatwaves could then extend throughout the winter season and continue to expand. Based on our results, one might also expect that, in the near future, lake heatwaves may occupy the entire surface area of lakes on an annual basis, potentially resulting in the emergence of a permanent heatwave state (Woolway et al 2021a). The continued spatial expansion of lake heatwaves will likely expose aquatic organisms to thermal extremes that have not been experienced before, and there will likely be a substantial departure from the 'normal' thermal conditions that have shaped the aquatic environment in the past. Aquatic organisms that live in regions close to their maximum thermal limit are likely to be most susceptible to the rapid expansion of lake heatwaves, as temperature anomalies there are more likely to exceed organismal physiological thresholds and hence increase mortality rates (Till et al 2019). Specifically, with the spatial expansion of lake heatwaves, one could expect dramatic losses of marginal populations at thermal range edges in the Great Lakes, as has already been documented in the marine environment (Hobday et al 2016).

Output: contrast


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: We further speculate that the discrepancy between the genomic PCR and immunofluorescence could result from a more complete co-transfection using electroporation and a bias towards easier detection of larger PCR products (i. e. , the KI and WT fragments) using ethidium bromide integration for detection. We have now included these data in the manuscript as Figure 4—figure supplement 3 and discussed this in the context of the GluA2 KO seen with TKIT (Results). Also see the Discussion. We also added a description of this methodology to the Materials and methods section of the manuscript. 2) Recent reports suggest that AAV vector genomes can integrate at DSBs created by Cas9 (PMIDs: 33087932, 31570731), and Cas9 can often create an opportunity for unintended insertions. Although PCR of genomic DNA (shown in Figure 4—figure supplement 2) detected both WT and KI alleles, it is not clear how often insertion of other sequences (with variable length) occurs, and no data at the level of DNA sequence is provided following AAV delivery methods. The fidelity of clean donor insertion could be examined by Sanger sequencing of genomic DNA clones to more completely define the results of insertion and genomic sequence changes around cut sites. This would also help to identify potential issues that may affect non-coding sequences (which, at the locations targeted here, are likely to be important regulatory elements). We are grateful to the reviewers for raising this important point. We agree that this is a necessary consideration when coupling AAVs withCas9 methods for genome editing (which is being widely adopted in the field). In fact, we now also speculate that 5’UTR integration of fragments of AAV could explain the lower efficiency in vivo with AAVs compared to in vitro with transfections. We have updated the text in the Results section to account for this possibility and include the recommended 2. The hippocampus will then be dissected, and genomic DNA amplify using a high-fidelity polymerase and a very long extension time (to account for variable sized insertions) flanking the KI sites. The PCR products will be sent for deep sequencing (as in Hanlon et al. , 2019). This will enable us to calculate the percentage of reads that have AAV insertions.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: In the counterfactual simulation, shown by the green line, the average temperature occurring once every 30 years would be just over 32 °C. Thus the answer to the first question is that climate change increased the average temperature of a 1-in-30-year event by about 2 °C. To answer the second question about the change in rarity, one needs to estimate chances of an average temperature of 34. 2 °C without any climate change. The observed temperature is near the upper bound of the counterfactual distribution, and the return time is estimated to be 66 million years. Publishing an attribution statement based on that estimate would be unwise, however, because the uncertainties from extrapolating out that far are extreme. Best practice is to put uncertainty bounds on the ratio of those return times. Using a likelihood ratio test, scientists can place a 95% confidence interval of 16 to infinity on the ratio of counterfactual to observed return times. In plain language, climate change increased the chances of the observed 2011 Texas summer temperature by at least a factor of 16. The current global warming level of about 1. 2 °C above preindustrial levels means that any rare heat wave that now occurs has an attributable human influence (reference 3, 34. 2 °C in Texas—is more uncertain because of both the statistical model and event characterization, although the lower bound on probability changes has been found to be independent of estimates of event magnitude. 7,8 the human influence on heavy precipitation events is more complicated than for heat waves for several reasons. The first is that precipitation is a sporadic event, and extreme precipitation even more so. (To learn about human influences on monsoons, see page 32 in this issue. ) Well-established theory (the Clausius–Clapeyron relation) and traditional trend analysis reveal that saturation specific humidity increases by about 7% per 1 °C of local warming. Because extreme precipitation usually occurs in fully saturated atmospheric conditions, one might expect the likelihood of such an event to also increase at the same rate. The more likely a local area is to be fully saturated, the more likely it is to rain. Analyses that used the 100 km climate models on extreme precipitation trends confirm that rate of increase (reference 3, 2017. 8,11,12 A best estimate distilled from those papers is that climate change increased Harvey’s rainfall by 19%, or about 2.

Output: corroborate


Input: Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: From natural threats such as wild destructive fires and outbreaks of insect pests and diseases are the integral part of forests dynamics, however they disrupt the yields of forests goods and services, affecting growth of trees and their survival, as well as water quality and biodiversity. Among the major challenges of forest threats in many countries are outbreaks of insect pests and diseases resulting in economic and environmental resources lost. When insect outbreaks reach epidemic, covering large territories and lasting for months, aerial resources of fight remain the only way to treat the infestation effectively and protect valuable forests. 3-5 are given the materials of damage from insects and diseases according to forest species from 25 countries, forests areas affected by continents and forest areas affected by insect pests and diseases by climatic zones [8,9]. Planted forests are more affected by insect pests and diseases than naturally regenerated forests. As to the plant species, broadleaves are affected more than coniferous (Table 3). According to the continents the most affected are: Europe-941,992ha. , Followed by North and Central America- 738,287ha and South America-612,358 ha. (Table 4). By climate zones the most affected is temperate zone- 72, 616ha. Then come tropical zone- 10,676ha. and subtropical-7,814ha (Table 5). Table 4: Forest area affected by insect pests and diseases by continents (ha). Source: 2015. Table 5: Forest area affected by insect pests and diseases by climatic zones (ha). Source: 2015. Table 6: Average area of forest annually affected by fire by regions and sub-regions, 2005. Source: FAO Meeting on Fires. FAO, 138. Rome [20]. Potential costs of US $ 540 billion economic damage to the world agriculture is predicted per year if spread of invasive pests and pathogens won’t be stopped. Wildfires are among the most destructive threats to forests. Fires do not respect national boarders among countries. Fast and effective detection is a key factor in wildfire fighting. The four major natural causes of wildfire ignitions are: lightning, volcanic eruption, sparks from rock-falls and spontaneous combustion [10-12]. Wildfires occur on all continents of the world except Antarctica. Destructive wildfires are common events in and other countries.

Output: contrast


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: 3) I agree with the authors that tagging endogenous proteins is likely to preserve the normal physiological processes of transcription, mRNA processing, and protein localization, all of which will be specific to the target in question. Thus, the ability to use this system with proximity labeling proteomics approaches is a promising future direction. However, the author's claims about the superiority of this combination in the Discussion section should likely be tempered given that the tags used by these approaches were not incorporated or tested here. We agree with the reviewers and have tempered this claim for future utility accordingly in our Discussion by adding the following sentence: “However, the feasibility of coupling TKIT with proximity labelling remains to be tested and will likely depend upon the transfection or transduction efficiency, the KI efficiency for the target protein, as well as the absolute abundance of the target protein being tagged. ” 4) Was the sequential sgRNA cloning and ligation process used for all genes targeted here? While it clearly works, this is somewhat laborious and may discourage others from adopting this technology. Since all TKIT targets will require two sgRNAs, the authors might consider using pX333 (PMID: 25337876; Addgene plasmid 64073) instead of pX330. This would enable more rapid sgRNA insertion (due to two unique restriction digest sites) instead of sequential amplification, gel purification, and ligation. We agree with the reviewers and want to make this method as accessible to the community as possible. In fact, to simplify cloning of plasmids containing Two U6 + guides + cas9 we have designed a strategy using HiFi assembly to make these plasmids in a single cloning step. We have added this methodology to the Materials and methods section of the manuscript, which we hope will make it easier for investigators to use TKIT for their own projects. We also include the reviewer’s suggestion of using PX333. However, for transparency, we will leave the details of how we originally made these constructs. 5) Regarding the FRAP experiments, could the authors expand their discussion on the difference between their measurements obtained on endogenous levels of receptors and those previously obtained on overexpressed receptors. We thank the reviewers for this useful suggestion, which is at the core of why we think such knock-in approaches are of such value to the field. Comparisons and 1.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: 5 times as much as what might be expected from Clausius–Clapeyron scaling of the increased available moisture from the 1 °C of attributable warming in the Gulf of Mexico. Since Harvey, numerous other tropical storms have been analyzed and have revealed similar scaling of precipitation statistics. 10,13 The mechanism for the super Clausius–Clapeyron scaling is simple. Figure 2a shows the composite simulated precipitation from Hurricane Maria, which devastated in 2017. Figure 2b shows the attributable precipitation changes at the time it occurred, and figure 2c shows the hypothetical precipitation changes in a much warmer world. The first thing to notice is that the increases, either in an absolute or relative sense, are the largest in the rainiest parts of the storm. The second is that there are decreases in the outer precipitation bands. What is happening is that warmer conditions are likely increasing the storm’s wind speeds. While the changes in instantaneous maximum wind speeds are thought to be slight at present, they will become more robust in a much warmer world. That increase in tropical cyclone intensity causes the storm structure to change and become more efficient at precipitating available moisture. Figure 2. View largeDownload slideChanges in precipitation during in 2017 relative to the cyclone center throughout its lifetime. (a) Composite simulated precipitation across multiple simulations under realistic climate conditions. (b) Attributable change in precipitation calculated from realistic simulations and a cooler, counterfactual simulation approximating preindustrial conditions. (c) Projected change in precipitation calculated from realistic simulations and counterfactual conditions at 3. 5 °C warmer than preindustrial conditions, or how much worse it could’ve been. Contours indicate the rainfall rate from the historical simulation. The plots are in units of the grid resolution, 4. 5 km. (Adapted from ref. 13. )Figure 2. View largeDownload slideChanges in precipitation during in 2017 relative to the cyclone center throughout its lifetime. (a) Composite simulated precipitation across multiple simulations under realistic climate conditions. (b) Attributable change in precipitation calculated from realistic simulations and a cooler, counterfactual simulation approximating preindustrial conditions. (c) Projected change in precipitation calculated from realistic simulations and counterfactual conditions at 3. 5 °C warmer than preindustrial conditions, or how much worse it could’ve been. Contours indicate the rainfall rate from the historical simulation. The plots are in units of the grid resolution, 4. 5 km.

Output: corroborate


Input: Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: 3 Relative frequency, relative density and relative dominance were determined following Phillips4 while importance value index (IVI) was calculated following Mishra. 5 Species diversity was determined following Shannon and Wiener information function6 and species similarity index. 7 The study was to see the present state of vegetation in each forest type and a change matrix was prepared to compare the present status of the forests with the original vegetation as described by Champion et al. 1,8 Quality of forest cover The forest cover is being monitored in India since 1985 when the first State of was published by the FSI. Though the forest and tree cover has been increasing marginally after every assessment report which is due apart from steps taken for afforestation and expansion of tree cover on private and common lands is also the result of changes in technology of assessment over the year. Nevertheless, it is credible for the country of such a huge population that the forest cover is increasing as also its flagship wild life species like Lions and Tigers. There is a total of 7082 million tonnes of carbon in India’s forests indicating an increase of 38 million tonnes over the last assessments of 2015. The question from the point of view of ecological stability and sustainability of forests wealth, however, is whether the forests of the country are in good shape quality wise and able to meet the ecological needs of the country. The answer is a firm no despite some remarkable but fragmentary achievements. The degraded forests of less than 40% crown density as per the latest estimation is 30 million ha which has increased from 24 million ha as estimated in 1985 report of the FSI. The moderately dense forests with crown density of more than 40% now stand to 39 million ha which is an addition of around 2 million ha over the 37 million ha reported previously in 1985. This also includes around 9 million ha area of dense forests of more than 70 % crown density. It is these areas which also have most of the wild life and Sanctuaries covering around 15 million ha of the forests. This meagre addition of 2 million ha seems more to be the result of technology rather than improvements in the forest stands. There are 170,000 villages in the country in and around 32 million ha of forests. It is the pressure exerted by the people y these villages for fuel wood, fodder and (NTFPs) living in and around forest areas that the degradation of the forest resources is continuing.

Output: contrast


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: Skip to Content eLife home page your research Search by keyword or author Reset form my search to Research 10. 7554/eLife. 44452 Open access Copyright information Version of RecordJuly 9, 2019 Open annotations (there are currently 0 annotations on this page). 4,597 views 705 downloads 82 4452. Copy to clipboard Download BibTeX Download. RIS Full text Figures and data Peer review Side by side Additional files 8 figures, 1 table and 3 additional files 1 with 2 supplements Download asset Open asset Defective autophagy enhances RIPK1-dependent and independent necroptosis. (A, B) Cell death assayed by (PI) staining and live-cell imaging for 12–16 hr (n = 5). BMDMs from mice of the indicated genotypes were treated with combinations of TNF/zVAD/Nec-1 (A) or PolyI:C/zVAD/Nec-1 and LPS/zVAD/Nec-1 (B). (C) Immunoblots confirming deletion of autophagy genes in BMDMs of indicated genotypes using RNP electroporation. NTC = non targeting control gRNA. (D, E) Cell death assayed under combinations of PolyI:C/zVAD/Nec-1 (D) or LPS/zVAD/Nec-1 (E) treatment (n = 4). Data in (A, B) are representative of four independent experiments; (C–E) are representative of two independent experiments. *p<0. 05, **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. Figure 1—source data 1 Defective autophagy enhances RIPK1-dependent and independent necroptosis. Download elife-44452-fig1-data1-v1. xlsx Figure 1—figure supplement 1 Download asset Open asset Elevated cell death and cytokine production by Atg16l1-c. (A) Cell death assayed by PI staining and live-cell imaging for 12–16 hr following with combinations of Pam3CSK4/zVAD/Nec-1, R848/zVAD/Nec-1 or CpG-ODN 1826/zVAD/Nec-1 (n = 5).

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: (Adapted from ref. 13. ) Close modal Hurricanes receive much of the attention in the attribution community, but other storm types are worth studying. A recent storyline analysis found that precipitation from a selected group of strong atmospheric-river storms affecting the coincidentally also increased at about twice the Clausius–Clapeyron rate. 9 Analysis suggests that those physical mechanisms of change are very different than inferred for tropical cyclones. Although few additional studies have been made of atmospheric rivers that impact coastal zones, the information has been alarming enough for decision makers to act on it. Although interest is high, little is known with confidence about anthropogenic increases in the intense summer mesoscale convective systems that can occur in continental interiors, partly because of computational constraints. Limited studies have analyzed the human influence on environmental conditions that support tornadoes, but there is no consensus regarding how climate change has influenced tornados. 14 the impact of climate change on drought can be complicated. One must consider the different types of droughts. NOAA classifies drought as a hierarchy of four related conditions. Meteorological drought is characterized by a deficit of precipitation; agricultural or ecological drought, of soil moisture; and hydrological drought, of water supply. Socioeconomic drought occurs when demand for water exceeds the supply. Agricultural drought depends on both the precipitation that falls on the ground and the evapotranspiration of moisture from plants and soils. Evaporation from bare ground depends strongly on air temperature. As the temperature increases from climate change, evaporation increases lead to drier soils. Transpiration from plants depends even more strongly on air temperature. Plants cool themselves by opening their stomata and evaporating water. In hot conditions, they can draw moisture from their root system until little soil moisture is left. Decreased soil moisture may in turn limit evapotranspiration, which means the relationship between temperature and soil moisture isn’t linear. Recent literature shows that human-induced climate change has contributed to increases in agricultural droughts in some regions because of evapotranspiration increases (reference 3, 2017. A counterfactual “flood that might have been” was constructed by decreasing Harvey’s observed precipitation uniformly according to published precipitation-attribution statements and using that as the input to a credible flood model.

Output: corroborate


Input: Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: 5 and RCP8. 5 scenarios, assessed by the Maxent simulations. We assigned rankings to species based on IUCN threat categories, taking into account also the future habitat loss. For the calculations, the core-area zonation (CAZ) approach was employed to determine the high-priority areas. This complementarity-based prioritization algorithm assigns conservation values by maximizing regional diversity and its complementarity. Essentially, CAZ emphasizes the selection of areas of high-quality habitats for the rarest or high-weighted species, and the prioritization aims to retain core areas for all species. To ensure that climatic refugia would be identified outside the urbanized and agricultural landscape, we excluded spatial surfaces of land use (cites and cropland) as a conditions mask layer. Moreover, the land cover classes (barren lands, lakes, grasslands, forests, and shrublands) were used as condition layers. These raster layers were derived from the global land cover change maps of the Agency (EEA 2023). We included in the analyses the already existing protected areas (PA), sourced by the Protected Planet: on (UNEP-WCMC and IUCN 2023). As conservation planning due to resource limitations rarely allows all potential habitats’ protection, the threshold used to select the highest priority areas was set to 20% of land as climatic stabilization areas based on the recommendation proposed by the for Nature (Dinerstein et al. 2019). To determine each species’ climatic niche’s representation within its associated PA climate space, we calculated the proportion of its bivariate density grid covered by the PA density grid in QGIS. ResultsCurrent distributional patternsThe predictive accuracies of all models under current conditions were relatively high (AUC > 0. 961), indicating the high reliability of the predictions (Table 1). The predictions properly described the current range for most of the taxa; however, potential distribution appeared slightly broader than their geographic range in the Hyrcanian ecoregion (Fig. 1 and Fig. 2 1). Some of them exceeded their potential niches by areas with at least 25–50% habitat suitability outside the main center of distribution (Fig. 1 1).

Output: pass


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: (B, C) ELISA measurements of IL-1β (B) and TNFα (C) in cell culture supernatants following treatment with combinations of LPS/zVAD/Nec-1 for 18 hr (n = 5). Data in (A) are representative of four independent experiments; (B, C) are representative of two independent experiments. *p<0. 05, **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. Figure 1—figure supplement 1—source data 1 Elevated cell death and cytokine production by Atg16l1-c. Download elife-44452-fig1-figsupp1-data1-v1. xlsx Figure 1—figure supplement 2 Download asset Open asset -mediated deletion of genes in primary BMDMs. (A) Schematic of screening protocol to identify conditions for high efficiency eGFP deletion in monocytes and BMDMs using electroporation ofCas9-guide RNA(gRNA) ribonucleoprotein (RNP) complexes. (B) Flow cytometry plot demonstrating condition resulting in highly efficient eGFP loss. (C) Schematic illustrating -mediated deletion of Ptprc/CD45. (D) Flow cytometry plots depicting Ptprc deletion and associated quantification of CD45 knockdown pooled from two independent experiments. Selected electroporation conditions were repeated at least three times with consistent results. Bar graphs depict mean. NTC = non targeting control gRNA. Figure 1—figure supplement 2—source data 2 -mediated deletion of genes in primary BMDMs. Download elife-44452-fig1-figsupp2-data2-v1. xlsx Figure 2 with 2 supplements Download asset Open asset RIPK3, MLKL and TRIF are required for RIPK1-independent necroptosis in Atg16l1-deficient BMDMs. (A-E) Immunoblot (A, C) and cell death assays (B, D, E) of BMDMs from mice of indicated genotypes treated with combinations of LPS/zVAD/Nec-1 following -mediated deletion of RIPK3, MLKL or GSDMD (A, B) (n = 4) or TRIF (C–E) (n = 6).

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: 15 Figure 3 compares the actual flood depth and the best estimate of the counterfactual one in two Houston neighborhoods, where almost 9 000 homes were flooded. The 19% precipitation increase attributable to human-influenced climate change translated to an additional 1 m of flood waters and a 14% increase in flood area. Equivalently, as a best estimate, the probability of a $90 billion hurricane loss (the amount of estimated insured losses) in Texas was quadrupled because of climate change. Figure 3. View largeDownload slideActual and counterfactual flood simulations in Texas’s and Pasadena neighborhoods during Hurricane Harvey. (a) The flood that was. (Adapted from ref. 15. ) (b) The flood that might have been in the absence of anthropogenic climate change. The difference between the models is the assumption that human activities increased Harvey storm total precipitation by 19%. Colors denote the depth of flood water in meters. Figure 3. View largeDownload slideActual and counterfactual flood simulations in Texas’s and Pasadena neighborhoods during Hurricane Harvey. (a) The flood that was. (Adapted from ref. 15. ) (b) The flood that might have been in the absence of anthropogenic climate change. The difference between the models is the assumption that human activities increased Harvey storm total precipitation by 19%. Colors denote the depth of flood water in meters. Close modal flood model has a resolution of 30 m—about the size of a suburban property—and its results have been made publicly available at The maps permit individuals to understand whether their home would have flooded without human-influenced climate change. Individuals can select different estimates of the human influence on precipitation and locate their home on both the realistic and counterfactual flood maps. That level of detail also permits a more refined damage estimate by combining it with socioeconomic data sets. Projecting real-estate maps onto the flood maps results in a best estimate that approximately 32% of flooded homes in Harris County, where Houston is located, would not have been flooded without climate change. Furthermore, in the actual flood, 75% of the county’s flooded homes were outside the federal 100-year flood plain—likely uninsured against flood damage—adding to the $90 billion insured loss. 16 Figure 4 shows an upper bound on the distribution of homes that were flooded in because of climate change. Figure 4. View largeDownload slideAdditional anthropogenic flooding.

Output: corroborate


Input: Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: Similarly, the potential niches of sub-endemic species, Euonymus velutinus, Lonicera floribunda, and Quercus castaneifolia, were much broader than the realized ones (Fig. 1 1). Table 1 Predictive performance of the species distribution models (SDMs) evidenced by the area under the curve (AUC) values and altitude changes for the Hyrcanian endemic and sub-endemic species at future climatic scenarios (RCP; ca. 2071–2100); (“ − ” decreasing of elevation) Full size tableThe climatic factors were more important in determining taxa distribution than topography and soil (Table S3). At the regional level, the most limiting factors were the precipitation of the driest month (bio14), the precipitation of the coldest quarter (bio19), and temperature seasonality (bio4). Specifically, the precipitation of the driest month (bio14) had a relatively highest contribution, ranging from 18% to 33% in all tested taxa, except for lowland species. julibrissin and Gleditsia caspica, the potential niches were determined mostly by the temperature seasonality (bio4), reaching nearly 27% of contribution in the simulations, and the precipitation of the coldest quarter (bio17; 17% and 28%, respectively), while for Parrotia persica, only bio17 was more significant with a contribution of ca. 34%. In most of the montane taxa except for Hedera pastuchovii and Ruscus hyrcanus and in lowland Populus caspica, the precipitation of the coldest quarter (bio19) was defined also as the most important variable limiting the distributional patterns. The sum of monthly mean temperatures greater than 0 °C had relatively moderate effects on the distributional patterns with a contribution of > 10% in Acer velutinum, Populus persica, and Ruscus hyrcanus (Table 3 2). The synthetic Emberger’s pluviothermic quotient, evapotranspiration (annualPET), and drought indicators (aridity index “aridityIndex” and relative wetness to aridity “climaticMoistureIndex”) had a negligible contribution in all models.

Output: pass


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: Cell death assayed by PI staining and live-cell imaging for 12–16 hr. Data in (A, B) are representative of three independent experiments; (C, D, E) are representative of four independent experiments. **p<0. 01, ***p<0. 001, ****p<0. 0001. Bar graphs depict mean. NTC = non targeting gRNA. Figure 2—source data 1 RIPK3, MLKL and TRIF are required for RIPK1-independent necroptosis in Atg16l1-deficient BMDMs. Download elife-44452-fig2-data1-v1. xlsx Figure 2—figure supplement 1 Download asset Open asset RIPK3 and MLKL drive RIPK1-dependent, TNF-mediated necroptosis; TRIF drives RIPK1-independent, PolyI:C-mediated necroptosis in Atg16l1-c. (A) Cell death assayed by PI staining and live-cell imaging for 12–16 hr of BMDMs treated with combinations of TNFα/zVAD/Nec-1 following -mediated deletion of Ripk3, Mlkl or Gsdmd (n = 4). Gene deletion confirmed by immunoblots in Figure 2A. (B) Immunoblots confirming -mediated deletion of Nlrp3 or Pycard in wild-type or Atg16l1-c. (C) Cell death assayed by PI staining and live-cell imaging for 12–16 hr following -mediated deletion of Nlrp3 or Pycard and treatment with PolyI:C/zVAD/Nec-1 or LPS/zVAD/Nec-1 (n = 5). Data in(A) are representative of three independent experiments; (B, C) are representative of two independent experiments. Bar graphs depict mean. *p<0. 05, **p<0. 01, ****p<0. 0001. NTC = non targeting gRNA. Figure 2—figure supplement 1—source data 1 RIPK3 and MLKL drive RIPK1-dependent, TNF-mediated necroptosis; TRIF drives RIPK1-independent, PolyI:C mediated necroptosis in Atg16l1-c.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: Each hexagonal bin symbolizes the upper limit of the number of residential buildings that would not have flooded without the added impact of climate change in Harris County, Texas, during in 2017. (Adapted from ref. 16. )Figure 4. View largeDownload slideAdditional anthropogenic flooding. Each hexagonal bin symbolizes the upper limit of the number of residential buildings that would not have flooded without the added impact of climate change in Harris County, Texas, during in 2017. (Adapted from ref. 16. ) Close modal Census data further reveal that Hurricane Harvey’s flood damages were not equally distributed across socioeconomic groups. Hispanic households are about 36% of the population of Harris County, but they owned or rented roughly 50% of the flooded homes. Additional analysis reveals that in wealthy neighborhoods, damages increased for households with more wealth. In low-income neighborhoods, the opposite trend was found: that damages increased for households with less wealth. Given the relative contribution to increases in greenhouse gases from people who are wealthy compared with people who are economically marginalized, such analyses quantify environmental and other social injustices. 16 More than just a weather forecast Other human impacts of extreme weather can also be quantified. Of particular interest is whether climate change increases the number of deaths from heat waves. They are among the deadliest of all extreme weather events, and epidemiology studies have developed relationships between mortality risk and temperature. 17 At high temperatures, the relationship becomes more sensitive: In already hot weather, a small increase in temperature can cause large increases in mortality. Scientists can use the relationship when estimating the attributable human temperature increase to understand the change in mortality risk during a heat wave. Another method maps mortality and temperature curves onto temperature-change plots, like those in figure 1, to estimate the number of people who have died because of the influence of climate change on a heat wave and to determine how the probability of death has changed. 18 The models are not perfect. Incorporating adaptive measures—for example, cooling centers and other outreach that can reduce the heat wave mortality risk—into attribution statements is currently challenging. There are many additional factors to consider when extending attribution statements about the human influence on extreme weather events to attribution statements about the human influence on the events’ outcomes. The sixth assessment report of the on declares that “human-induced climate change is already affecting many weather and climate extremes in every region across the globe” (reference 3, page 8).

Output: corroborate


Input: Claim: Deforestation contributes to habitat loss and climate change. [SEP] Text: However, because contemporary climate change has a different trajectory, past performance as refugia does not necessarily guarantee that these areas will offer suitable habitats in the future (Barrows et al. 2020; Keppel et al. 2015; Sandel et al. 2011). The palaeoenvironmental and palynology data concurrently point to the Hyrcanian ecoregion as a long-time glacial refugial area (Connor and Kvavadze 2009; Leroy and Arpe 2007), acting as a sanctuary for the Neogene flora. Currently, the region is relatively buffered from contemporary climate change that enables the persistence of the unique relict ecosystems with high species richness and endemism. Nevertheless, our projections suggest that the climatically suitable habitats for endemic and sub-endemic woody taxa in the Hyrcanian forests are expected to contract by 2100, with a mean projected loss of up to 45%, as generally predicted for other major temperate forest trees in the ecoregion (Dering et al. 2021; Naqinezhad et al. 2022; Sękiewicz et al. 2022; Taleshi et al. 2019). Notably, according to our SDMs, a range shift to the western part of the region is predicted for most species. Specifically, we found that a considerable loss of suitable habitats for endemic woody taxa would be expected in the eastern parts of the region (Golestan) and in the (northwestern Hyrcania) with over 85% and 34%, where the highest species richness is currently observed (Fig. 3A). Although most of the mountainous areas of Gilan are likely to be lost with habitat shifts eastward were predicted in this subregion. The eastern Hyrcanian ecoregion is currently quite different in terms of climatic regimes, with the highest mean temperature and lowest precipitations (Fig. 1B), and the mean annual temperature would be more adversely impacted in the region in the coming decades with increases of even 4 °C. Consequently, these changes may put the local stands beyond the species’ ecological optimum. At the same time, in Gilan, higher precipitation is expected compared to the remaining part of the region which leads to probable range expansion of species occurring in alluvial and lowland sites, such Populus caspica and Alnus glutinosa.

Output: contrast


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: Download elife-44452-fig2-figsupp1-data1-v1. xlsx Figure 2—figure supplement 2 Download asset Open asset TNF and interferon license necroptosis in BMDMs. (A-F) Cell death assayed by PI staining and live-cell imaging for 12–16 hr of Atg16l1-WT and Atg16l1-cpre-treated with TNFR2-Fc or α-IFNAR1 followed by TLR ligand or TNF mediated necroptosis (n = 5). Cells were pre-treated for 36 hr with 20 μg/mL α-Ragweed, TNFR2-Fc or α-IFNAR1 prior to addition of TLR ligands or TNF. (G) Immunoblots for phosphorylated STAT1 in BMDMs following LPS/zVAD treatment over 6 hr. Data in (A–F) are representative of four independent experiments; (G) are representative of two independent experiments. **p<0. 01, ****p<0. 0001. Bar graphs depict mean. Figure 2—figure supplement 2—source data 2 TNF and interferon license necroptosis in BMDMs. Download elife-44452-fig2-figsupp2-data2-v1. xlsx Figure 3 Download asset Open asset Loss of Atg16l1 drives accumulation of detergent insoluble, high molecular weight 1, RIPK3 and enhances RIPK1/RIPK3 phosphorylation. (A, B) Immunoblots of TRIF in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations of LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (A) or insoluble (B) fractions. (C, D) immunoblots for autophosphorylated RIPK1 (Ser166/Thr169, p-RIPK1) and total RIPK1 in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (C) or insoluble (D) fractions.

Output: pass


Input: Claim: Climate change is causing more extreme weather events worldwide. [SEP] Text: Developments in attribution science over the past two decades reinforce that statement by extending attribution statements about observed long-term climate change to encompass robust statements about the human influence on many types of individual extreme weather events. That includes heat waves, heavy precipitation events, and floods. Attribution methods for some classes of events have matured to the point where they could be operationalized to regularly inform the public about the current dangers of climate change. That would also greatly increase the number of events analyzed in that way and further understanding. Extreme weather happens everywhere, but most event-attribution studies have focused on events in nations that have the requisite human and computational resources. Groups like Attribution ( have begun to apply attribution science to significant weather events in low-income countries. Such organizations’ credibility is increased when they involve experts from those nations who better understand the details of local climate and associated impacts. The extension of attribution science to connect human increases to the socioeconomic damages and inequalities of extreme weather events is now underway. That work has the potential to inform low-income nations about their loss and damages, giving them the knowledge to negotiate for more assistance from recovery funds. 1. M. Allen, Nature 421, 891 (2003). Stott, D. Stone, M. Allen, Nature 432, 610 (2004). Masson-Delmotte et al. , eds. , 2021: Science Basis—I Contribution to the Report of the on Climate Change, Cambridge U. Press (2021). 4. G. J. van Oldenborgh et al. , Earth’s Future 10, e2021EF002271 (2022). Y. Philip et al. , Earth Syst. Dyn. 13, 1689 (2022). Bercos-Hickey, C. M. Patricola, W. A. Gallus Jr, J. Clim. 34, 8989 (2021). Clim. Extrem. 12, 24 (2016). D. Risser, M. F. Wehner, Geophys. Res. Lett. 44, 12457 (2017). M. Patricola et al. , Weather Clim. Extrem. 36, 100440 (2022). Commun. 13, 1905 (2022). J. van Oldenborgh et al. , Environ. Res. Lett. 12, 124009 (2017). S. Wang et al.

Output: corroborate


Input: Claim: Renewable energy sources can reduce reliance on fossil fuels. [SEP] Text: Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : on Investment (EROI), fosszilis energiahordozók, megújuló energiaforrások, fenntarthatóság Jegyzet elhelyezéséhez, kérjük, lépj be. ! HivatkozásokVálaszd ki a számodra megfelelő hivatkozásformátumot:Harvard (2024): Magyar Tudomány 2024/04. : Akadémiai Kiadó. Letöltve: (2024. 11. 04. )Chicago. 2024. Magyar Tudomány 2024/04. : Akadémiai Kiadó. (Letöltve: 2024. 11. 04. (2024). Magyar Tudomány 2024/04. Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : on Investment (EROI), fossil fuels, renewable energy sources, sustainability Jegyzet elhelyezéséhez, kérjük, lépj be. ! HivatkozásokVálaszd ki a számodra megfelelő hivatkozásformátumot:Harvard (2024): Magyar Tudomány 2024/04. : Akadémiai Kiadó. Letöltve: (2024. 11. 04. )Chicago. 2024. Magyar Tudomány 2024/04. : Akadémiai Kiadó. (Letöltve: 2024. 11. 04. (2024). Magyar Tudomány 2024/04. Akadémiai Kiadó. (Letöltve: 2024. 11. 04. : 10. 1556/2065. 185. 2024. 4. 8 Jegyzet elhelyezéséhez, kérjük, lépj be. !

Output: pass


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: (E, F) immunoblot assay for autophosphorylated RIPK3 (Thr231/Ser232, p-RIPK3) and total RIPK3 in Atg16l1-WT and Atg16l1-clysates following 4 hr of treatment with indicated combinations of LPS/zVAD/Nec-1 and enrichment of NP-40 soluble (E) or insoluble (F) fractions. Representative data shown from three independent experiments. In all immunoblots, -mediated TRIF deletion was performed in Atg16l1-cfollowed by LPS/zVAD treatment as a negative control. *=non specific bands (n. s. ). Figure 4 with 2 supplements Download asset Open asset Overabundance of TRIF, phosphorylated and ubiquitinated RIPK1 and RIPK3 coincides with accelerated necroptosis of Atg16l1 deficient BMDMs. (A) Kinetic measurement of cell death over 18 hr of LPS/zVAD treatment (n = 5). (B) Immunoblot of TRIF in NP-40 insoluble fractions of BMDM lysates over 6 hr of LPS/zVAD treatment. (C, D) Immunoblots of autophosphorylated and total RIPK1 (C), RIPK3 (D) in NP-40 insoluble fractions of BMDM lysates treated as in (B). (E) Immunoblots of autophosphorylated RIPK1, RIPK3 and ubiquitin in BMDM lysates following immunoprecipitation of M1 or K63-ubiquitinated proteins after 4 hr of LPS/zVAD treatment. Data in (A) are representative of four independent experiments; (B–D) are representative of three independent experiments; (E) are representative of three independent experiments. *=P < 0. 05. Figure 4—source data 1 Overabundance of TRIF, phosphorylated and ubiquitinated RIPK1 and RIPK3 coincides with accelerated necroptosis of ATG16L deficient BMDMs. Download elife-44452-fig4-data1-v1.

Output: pass


Input: Claim: Deforestation contributes to increased atmospheric CO2 levels. [SEP] Text: 4) Most of the emitted IR radiation is leaving the atmosphere, but a part of it (back radiation or backscatter) from greenhouse gases returns to the Earth’s surface and is absorbed. 5) The absorbed backscatter leads to increased surface temperature that heats the air. 6) Humans’ increased emission of greenhouse gases, mainly CO2, leads to an enhanced Greenhouse Effect. This explanation is used by IPCC (on Climate Change) [3] and other research [4] [5] [6]. Points 1 to 4 have been verified by several types of measurements, both by satellites and at ground level [7] [8]. However, no direct measurement was made of the resulting heating of Earth’s surface. IPCC admits that the amount of heating is still discussed and that the enhanced greenhouse effect from increased amount of CO2 has, until recently, only been confirmed by empirical evidence [9]. But one experiment, clearly showing that CO2 can heat a black-body, was performed by Harde and Schnell in 2020 [10]. This experiment was the basis for the experiments presented here. 2. The Harde/Harde and Schnell [10] have presented an experiment that should explain how added amounts of greenhouse gases (like CO2) heat the surface of the Earth. Their experimental setup is shown in Figure 1, consisting of a cylinder-shaped tank, which on the inside consists of polished aluminum. Internal height/diameter is 111 cm/36cm. The doom shaped top part is heated to 30˚C while a cooled (−11. 4˚C), black plate is placed at the bottom. Compared to the earth/atmosphere situation this setup is mounted upside-down. Close to the top of the tank is a small black-painted aluminum plate placed, representing the Earth’s surface (the EP). This setup leads to a vertically stable temperature gradient, similar to the lapse rate gradient of the troposphere. The cold plate represents the top of the troposphere. The cylinder was first filled with dry air and left to stabilize thermally. When CO2 was added to the air in the tank the temperature of the increases. This is seen in their Figure 10(a). The highest concentration of CO2 used Figure 1. The experimental setup used by Harde and Schnell [10]. was 20%, leading to an increase of the temperature of 1. 18˚C.

Output: corroborate


Input: Claim: Renewable energy sources can reduce reliance on fossil fuels. [SEP] Text: , 2022). Az energiaszektor átalakítása során az egyik fontos mutatószám az EROI, azaz az energiabefektetés-energiahozam arány, amely lehetővé teszi a különböző energiaforrások és technológiák összehasonlítását, és segíti a döntéshozókat abban, hogy optimális energiastratégiákat alakítsanak ki a jövőbeli energiabiztonság és fenntarthatóság biztosítása érdekében. Az EROI egy dimenzió nélküli mutató. Értéke azt mutatja, hogy az adott energiaforrás vagy technológia mennyi többletenergiát hoz létre a befektetett energiához képest. Amikor ez az érték 1 feletti, az azt jelenti, hogy az energiatermelés hatékonyabb és eredményesebb, mivel több hasznosítható energia jön létre az adott befektetett energiához képest. Amennyiben viszont az értéke kisebb mint 1, akkor az energiaforrás vagy technológia nem hatékony, mert kevesebb hasznosítható energia keletkezik, mint amennyit annak előállításához felhasználtak (Hall et al. , 2014; Court–Fizaine, 2017; Brockway et al. , 2019; de Castro–Capellán-Perez, 2020; Diesendorf–Wiedmann, 2020).

Output: pass


Input: Claim: CRISPR technology enables precise gene editing. [SEP] Text: xlsx Figure 4—figure supplement 1 Download asset Open asset Enhanced MLKL activation and accelerated cell death in Atg16l1 deficient BMDMs following LPS- or PolyI:C-mediated necroptosis. (A) Immunoblots depicting p-MLKL Ser345 in NP-40 soluble and insoluble fractions of BMDM lysates 4 hr after indicated treatments. (B, C) Death of wild-type and Atg16l1-cassayed by PI staining and live-cell imaging over 18 hr of LPS- (B) or PolyI:C- (C) mediated necroptosis. LPS +zVAD time-course is same as in Figure 4A. Data in (A) are representative of three independent experiments; (B, C) are representative of four independent experiments. Dots represent mean (n = 5)±S. D. *p<0. 05, **p<0. 01, ****p<0. 0001. Figure 4—figure supplement 1—source data 1 Enhanced MLKL activation and accelerated cell death in ATG16L1 deficient BMDMs following LPS- or PolyI:C-mediated necroptosis. Download elife-44452-fig4-figsupp1-data1-v1. xlsx Figure 4—figure supplement 2 Download asset Open asset Lysosomal function and autophagic flux drive turnover of active 1 and RIPK3 during necroptosis. (A-C) Immunoblots assaying levels of TRIF (A), RIPK1 (B) or RIPK3 (C) in total lysatse (bottom) and detergent- insoluble fractions (top) of BMDM lysates over 6 hr of LPS/zVAD treatment in the presence of Bafilomycin A1. (D–F) Immunoblots assaying basal turnover of TRIF (D), RIPK1 (E) or RIPK3 (F) by perturbation of proteasomal (MG132, 2 μM) or lysosomal (Bafilomycin A1, BafA1 100 nM) activity. Dot plots in (D–F) summarize protein abundance measured by immunoblot intensity normalized to 0 hr time point. Lines depict mean (n = 4).

Output: pass