dataesr/scientific-paragraphs-categorization huggingface dataset:
We are not able to causally attribute changes in the child well-being scores between these two data points to lockdown. Second, due to social distancing measures, the Elfe-SAPRIS survey was implemented online, which have led to response bias. Families who had enough time to complete the questionnaire may have had the best experience of lockdown. Moreover, the poorest families, without access to the Internet or being less reachable by email (which was the way used for contacting parents), were not covered by our survey. However, these families have been the hardest hit by the economic consequences of the pandemic and have the poorest living conditions. In addition, the child's experience of confinement and well-being was reported from the perspective of the parent responding to the survey, in most cases the mother, and not from the perspective of the children themselves, which can positively bias the results if parents do not perceive their children's difficulties.
, 2021). To re-signify and validate the perception of social vulnerability by the distribution of census data, SWISVI was aggregated with the population density variables and occupation patterns by region. This is because social vulnerability is not a directly observable phenomenon, and since there is no device to measure it, its validation requires proxies  (DE SHERBININ et al. , 2019; TATE, 2012). SUWSVI shows significant differences between ranges and their regions of predominance. We sought to better understand this relation in the most affected census sectors by associating results with testimonies on the Facebook social network (PREFEITURA DE SÃO JOSÉ DOS CAMPOS, 2016). Quintslr (2018) also used media data to observe the social construction of the hydric crisis and demonstrate how the hegemonic discourse on the risk of shortages has contributed to keeping the issue of inequality out of decision-making spheres.
(DAEE, 2017) databases of the municipality used for this work were obtained from the 2010 Brazilian Institute of Geography and Statistics Census data(IBGE, 2017). The location of public water supply connections was obtained from the Department of Water and Electricity(DAEE, 2017). The socioeconomic indicators were prepared from information in 871 census sectors in São José dos Campos provided by the 2010 Census(IBGE, 2017). We also supplementarily analyzed over 1,300 citizen comments made on the Facebook profile of the Municipality of São José dos Campos (PREFEITURA DE SÃO JOSÉ DOS CAMPOS.
(DAEE, 2017) databases of the municipality used for this work were obtained from the 2010 Brazilian Institute of Geography and Statistics Census data(IBGE, 2017). The location of public water supply connections was obtained from the Department of Water and Electricity(DAEE, 2017). The socioeconomic indicators were prepared from information in 871 census sectors in São José dos Campos provided by the 2010 Census(IBGE, 2017). We also supplementarily analyzed over 1,300 citizen comments made on the Facebook profile of the Municipality of São José dos Campos (PREFEITURA DE SÃO JOSÉ DOS CAMPOS Composition of the social urban water shortage vulnerability index (SUWSVI) applied to São José dos Campos, SP, Brazil 178Sustainability inDebate -Brasília, v. 13, n. 3, p. 173-188, dec/2022ISSN-e 2179-90672.
FUNDING PS is supported by the  Agence Nationale de la Recherche  ( ANR-11-LABX-0021  to  Labex LipSTIC) , the the  Conseil Reǵional de Franche-Comté (" Soutien au LabEX LipSTIC "), and by the  MiMedI  project funded by  BPI France  (grant No. DOS0060162/00 ), and the  European Union  through the  European Regional Development Fund of the Region Bourgogne-Franche-Comte  (grant No. FC0013440 ). ET is supported by  Programme Hospitalier de Recherche clinique PHRC-I|_   GIRCI_ EST_B02 2015. KB-K was supported by the  National Science Centre, Poland  (grant No. 2016/21/B/ NZ5/01901 ).
Finally, two noteworthy posters were presented by companies developing FSHD-focused technologies. Fulcrum Therapeutics presented a poster on the evaluation of p38α/β target engagement biomarkers in skeletal muscle in trials of losmapimod, which is a DUX4-reducing small molecule currently being tested in a Phase 2b (NCT04003974) study in FSHD patients. The microRNA therapeutics company miRecule presented the development of an anti-DUX4 modified RNA oligonucleotide conjugated to miRecule's antibody delivery technology for the treatment of FSHD. The goal of this strategy is to improve oligonucleotide delivery to muscle when delivered systemically.
Sixteen subjects who met inclusion criteria similar to the ReDUX4 study were enrolled and underwent needle muscle biopsies of a STIR+ muscle 6 weeks apart. Using RNA-seq data from this and published studies, a panel of DUX4-related transcripts was identified. Jeffrey Statland described the results of a phase 2 trial of ACE-083 in FSHD sponsored by Acceleron Pharma. ACE-083 is a locally delivered nonspecific myostatin inhibitor which induces increased muscle growth. This was a two part study: part 1 was dose-ranging (N = 37); part 2 was RDBPC for 6 months followed by a 6-month open-label period. Patients were treated with ACE-083 240 mg/muscle or placebo (1:1) injected into the tibialis anterior (TA) or biceps brachii (BB) muscles bilaterally q3 weeks (N = 58). The primary endpoint was increased in muscle mass of the TA or BB.
Acknowledgements We thank the following sponsors for supporting the 2020  FSHD International Research Congress: AFM Telethon, Avidity Biosciences ,  Bionano Genomics ,  Dyne Therapeutics ,  Fulcrum Therapeutics, Genomic Vision, Muscular Dystrophy Association, MiRecule ,  PerkinElmer Genomics, University of Massachusetts Medical School/NIH/Wellstone Center, University of Nevada School of Medicine.
Both patients' characteristics are presented in Tables  E1  and E2 , respectively, in this article's Online Repository at www. jacionline. org. For these 3 types of analyses, we paid a special attention to recruit patients with asthma with similar clinical and functional characteristics. Indeed, there was no significant difference in either age, body mass index, FEV 1 , or FEV 1 /forced vital capacity ratio in the 3 groups of patients using 1-way ANOVA (data not shown).
*Co-last author. This study was supported by the '' Agence Nationale pour la Recherche'' (ANR ,  ROSAE  Project  CE14-0015-01 ), the  ''Fondation de l'Universit e de Bordeaux'' ('' Fonds FGLMR/AVAD pour les maladies chroniques ''), and an unrestricted grant from  Astra-Zeneca , France. Disclosure of potential conflict of interest: F. Beaufils reports personal fees and nonfinancial support from  Novartis ,  Chiesi , and  AstraZeneca  outside the submitted work. I. submitted work; grants and personal fees from  Novartis ; grants, personal fees, and nonfinancial support from  Boehringer Ingelheim ; personal fees and nonfinancial support from  Chiesi , As-traZeneca, and  Sanofi ; and  Hospital of Bordeaux , as well as  Isabelle Goasdoue ,  Virginie Niel , and  Marine Servat  from the  Clinical Investigation Center  for technical assistance and all the team members of the  Bordeaux Imaging Center (BIC, Bordeaux University ).
The international business literature, while extensive by now, has given scant attention to the direct comparison of the performance of advanced economy multinational enterprises (AMNEs) and emerging market multinational enterprises (EMNEs) in international markets. In particular, the question of how well these firms perform in each other's home markets is an intriguing one. In this study, we examine "market share" performance of AMNEs and EMNEs in each other's countries using a comprehensive, longitudinal dataset. Drawing from the eclectic paradigm, we contend that, in comparison, EMNEs perform better as they: i) develop non-traditional ownership advantages based on their learnings in their home markets, and ii) expand into advanced economy markets relying on non-traditional ownership advantages.
S. , and Europe  (Ramamurti & Williamson, 2019). The present study is based on actual performance metrics while examining longitudinal data in several countries and industries. Importantly, we provide a direct comparison of performance of AMNEs and EMNEs in each other's markets. Another key contribution of this study is the application of the eclectic paradigm to explain the superiority (market share gain performance) of EMNEs compared to AMNEs. We argue that the eclectic paradigm, initially developed for AMNEs, can be extended for EMNEs. Finally, our study reveals how the performance of AMNEs and EMNEs is evolving over time, considering specific country-industry dyads. The data employed in the present investigation is drawn from the Euromonitor Passport, a rich, proprietary database that enables us to carry out our investigation at a granular level.
EMNEs as family conglomerates About a third of the EMNEs in our dataset are family-owned. Familyowned conglomerates played an important role in the long-term performance of emerging markets  (Cavusgil et al. , 2021; Kim, Kandemir, & Cavusgil, 2004). Family-owned MNEs are common and dominant in such emerging markets as Brazil, Mexico, South Korea, Thailand, and Turkey. Accustomed to managing well in highly volatile home country conditions, they have gained resilience and can make timely decisions, benefiting from favorable demand conditions. They can also make longterm decisions effectively and be persistent in their strategies  (Andrade, Mitchell, & Stafford, 2001). Therefore, it is plausible to argue that family-owned firms play a role in developing firm-specific advantages in emerging markets.
Data To examine respective market performance of AMNEs and EMNEs operating in each other's markets, we draw data from the Euromonitor Passport, a proprietary database which enables us to carry out our investigation at a granular (industry and country specific) level. This database affords us several important advantages. First, the Euromonitor database allows us to examine annual performance with a wellestablished objective measuremarket share datafor each firm that operates in each country. The literature on the measurement of performance supports the use of market share as a robust indicator of firm performance  (Guo, 2013; Iversen & Hem, 2011; Katsikeas, Morgan, Leonidou, & Hult, 2016; Talay, Townsend, & Yeniyurt, 2015). It is also regarded as one of the principal determinants of business profitability  (Faria & Wellington, 2005; Farris et al.
, 2006; Szymanski, Bharadwaj, & Varadarajan, 1993). Second, the Passport database provides annual market share data in percentage points for each firm operating in each country-industry combination or dyad. Compared to the extant work that considers performance at the industry or country level, this feature affords us an important advantagethe ability to compare the market share performance of defenders and challengers. Third, apart from identifying overall trends in firm market share, we can explore the contingent nature of market share performance of a group of MNEs based on numerous country-industry combinations. In addition to including a representative set of advanced economies and emerging markets, we consider a set of consumer industries (retail, ready meal, apparel, soft drinks, beauty and personal care, small home appliances, and electronics), providing robust comparisons.
Context of the study For our analyses, we selected a sample of advanced economies and emerging markets and a sample of service and manufacturing industry sectors that are available in the Euromonitor Passport database. For country selection, we considered the following two criteria. First, we ensured sufficient geographic and cultural representation. Second, we selected a representative set of advanced economies and emerging markets from the Group of Twenty (G20) countries as these are some of the world's major economies with abundant market potential. As a group, G20 countries account for more than 75 percent of the world GDP, 75 percent of the global trade, and 60 percent of the world population (Statisa Research Department, 2020; The G20, 2021). Consequently, the following six advanced economies were included in the preliminary analysis: Canada, France, Germany, Japan, the U.
K. , and the United States. Similarly, we selected six countries that are representative of emerging markets: Brazil, China, India, South Africa, South Korea, and Turkey. Cumulatively, the selected countries account for major proportion in terms of their contribution to GDP. Industry selection is based on accessibility of data as well as generalizability. Industry sectors selected for this analysis are retail, ready meal, apparel, soft drinks, beauty and personal care, small home appliance, and electronics. These are the target consumer markets for the AMNEs more than a decade and they are open to foreign competitions. Thus, a focus on these industries allows for cross-country comparisons. Our data includes actual leading multinational firms operating in these seven industries in the six advanced economies and six emerging markets.
Analyses and measures Our focus in this study is foreign market performance of MNEs. However, we differentiate between AMNEs and EMNEs and explore the performance of AMNEs in emerging markets and EMNEs in advanced economies to respond to our research questions. Therefore, for each AMNE case, the dependent variable is the market share performance in emerging markets only. In contrast, for each EMNE case, the dependent variable is the market share performance in advanced economies. We analyzed the data in two steps to respond to our research questions. First, to gain some preliminary insights on the market share gain performance phenomenon, we examined the overall behavior of market share gain performance of both AMNEs and EMNEs as a group. Next, to provide deeper insights, we carried out a statistical analysis of market share gain performance comparing individual AMNEs and EMNEs across industries and country markets, utilizing a panel time series analysis.
For this analysis, we adopted the random effects model using generalized least squares. The generalized least squares estimation method for random effects  (Wooldridge, 2002 ) is often used to analyze datasets that are cross-sectional time series panels  (Aaker & Jacobson, 1994; Dewan & Kraemer, 2000; Prabhu et al. , 2005). Further, a fixed effects estimation is not viable for models that include dummy variables such as the EMNE/AMNE and country dummies that overlap with the fixed effects  (Wooldridge, 2002). In parallel, we operationalize foreign market performance in select country-industry combinations in two ways: i) collective (aggregate) market share gain of leading AMNEs or EMNEs over a ten-year period as a first step, preliminary analysis; and ii) annual individual market share of each AMNE or EMNE through a multivariate, random effects analysis.
Econometric analysisrandom effects model In contrast to the preliminary analysis where we examined the market share gain performance of MNEs as a group, we next engaged in a more definitive analysis by using firm-level, individual MNE market share data for the firms under study. To provide more definitive insights into the market share performance of AMNEs and EMNEs operating in emerging markets and advanced economies, respectively, we carried out an econometric analysis. We analyzed AMNE and EMNE market shares across industries and country markets utilizing a panel times series approach. The dataset was organized by country-company dyads on a yearly basis, from 2010 to 2019. To investigate AMNE and EMNE market share differences among industries and countries, we estimated the following random effects model using generalized least squares: Market Share ijt = β 0 + β 1 Country j + β 2 Industry i + β 3 Age it + β 4 Year t + β 5 EMNE i + β 6 Year t × EMNE i + ε ijt Where, I denotes the focal company studied, j denotes the country in which the company is operating, and t denotes the time period.
Predicting future extinction: direct drivers of loss Identifying direct threats is part of the IUCN Red List Assessment process, and even species that are not explicitly threatened (i. e. , those that are Least Concern [LC], Near Threatened [NT], or Data Deficient [DD]) can still have threats listed. Here we discuss these threats and how they apply to all species. Our analysis of IUCN assessments indicates that overexploitation and agriculture are the most frequently listed threats to Malagasy fauna (excluding invertebrates) and flora (Fig. 2 ), mirroring global findings  (36). Overexploitation is unsustainable biological resource use as defined by the IUCN  (37) , including hunting and collecting for subsistence use or national/international trade. Overexploitation is linked in some cases to illegal harvestingfor example, the illegal logging of rosewood for trade (Dalbergia spp.
As in many low-income countries, insufficient public funding means that the number of Malagasy professionals is still insufficient to serve the country's needs, there are relatively few PhD positions available to students, and those that are trained at higher levels often move away from academia and into the private sector. Access to up-to-date biodiversity data has also been a limiting factor  (15). A further challenge is how to successfully engage multiple parts of society in conservation. Efforts that are genuinely socially integrated have been shown to produce more effective and resilient practices, policies, and decision-making, especially in the face of unstable environmental, political, and health situations  (114). The Madagascar Fauna and Flora Group, the Lemur Conservation Foundation, Durrell Wildlife Conservation Trust, The Peregrine Fund Madagascar, Madagascar Biodiversity Center, and Madagasikara Voakajy, as well as the work of the Royal Botanic Gardens, Kew, and Missouri Botanical Garden, are all examples of successful collaborations involving researchers, conservation partners and local communities to protect biodiversity and empower local people.
Acknowledgments: Carly Cowell (RBG Kew) provided information on METT assessments and monitoring and  Karen Freeman  ( Madagascar Fauna  and  Flora Group ) provided information on invasive vertebrates. Anna Rauhaus  ( Cologne Zoo ),  Joel Kamphausen , and  Laura Leiss  (both of  University of Cologne ) supported the zoo database analyses. Inessa Voet  illustrated the graphical abstract. Julia P. G. Jones  ( Bangor University ) contributed to discussions that shaped and improved the analyses and text. We thank  James Aronson  ( Missouri Botanical Garden ),  David Ashley  ( UK Ambassador  to Madagascar and Comoros),  Adolphe Lehavana  ( Missouri Botanical Garden ),  Jonah Ratsimbazafy  ( Houston Zoo  and the  Groupe d'Etude et de Recherche sur les Primates de Madagascar) ,  Serge Ratsirahonana  ( Fondation pour les Aires Protégées et la Biodiversité de Madagascar ), and  George E.
Charcoal Briquettes Kingsford charcoal briquettes are the leading seller in the USA, according to several sources, accounting for well over 50% of total physical volume. Therefore, this has been used as proxy for all charcoal briquettes. Their composition (Table  1 ) has been estimated from several sources: a video from 2001 of a Kingsford factory (https://bit. ly/3bInhVO (accessed on 20 May 2022)) that appears to be located on or next to an open-pit coal mine; correspondence of Kingsford with members of the California BBQ Association from around 2001 (https://www. virtualweberbullet. com/all-about-charcoal/ (accessed on 20 May 2022)) reproduces the information, which was originally posted by Kingsford. This original was verified by the authors at https://archive. org/web/ (accessed on 20 May 2022)); a Kingsford safety data sheet from 2016 (https://bit.
Wood Pellets and Wood Logs Wood comes from countless species of trees. Therefore, do wood pellets, which can also come from 'woody biomass'. Those used in grilling come from waste/residue wood, not from stem wood. Lower heating values of 19. 6 and 20 MJ/kg are used for pellets and air-dried wood  [6]. Combustion emissions are 202 lb CO 2 e/mmBTU  [1]. Pre-combustion footprints are taken from ecoinvent: pellets from the process 'Wood pellets, u = 10%, at storehouse/RER U'; and logs from 'Logs, hardwood, at forest/RER U'. European datasets were used, because no equivalent US datasets are readily available. From inspection of the data, it is believed that European and US figures would be very similar.
Of note, only the asymptotic test from dearseq works on nonnormalized data, while its permutation test fails because of this same issue: observations across samples are not exchangeable and therefore the null distribution is not well estimated by permutations. show in the middle panel of Figure  1B  that both dearseq and the Wilcoxon test attained the nominal FDR as sample size increased. We also show in Figure  1B  bottom panel an alternative permutation scheme which fixes the issues with the scheme in Li et al : when counts are first normalized before being permuted under H 0 , we demonstrate that all three tests adequately controlled the FDR for the full dataset. Figure  2  shows that once convergence was reached, the dearseq asymptotic test achieved slightly higher statistical power than Wilcoxon test, while the Wilcoxon test had superior power to dearseq permutation test.
Toy example Here we present a toy example to illustrate the impact of post-permutation normalization due to library size imbalance. Consider three genes: Gene 1 and Gene 3 are truly associated with the condition of interest A, while Gene 2 is independent of this condition. These three genes are measured across 10 samples with a library size that varies from 80 to 15,000. Table  S1  presents the raw data while Tables  S2, S3 , and S4 display the normalized, permuted and normalized permuted data respectively. We observe that 0. 0e+00  shows that most of the total library size is accounted for by the subset of the 5,778 true DE genes, and even more so for the left ventricle heart condition in this example there is confusion between the condition and the library size (i. e. not normalizing the data leads to Gene 2 being significantly associated with condition A, while normalizing by y ij = log 2( y ij 10 i=1 y ij ) removes the spurious association).
[1]irical statistical power for the Wilcoxon test and dearseq asymptotic and permutation tests. Average over 50 semi-synthetic dataset generated from the GTEx Heart atrial appendage VS Heart left ventricle data. 50% of the true Differentially Expressed (DE) genes are randomly sampled in each semi-synthetic dataset (i. e. 2,889 genes remains unpermuted as true positives) and considered as gold-standard DE genes used as true positives. Panel A reproduces the results from Li et al[1]Figure2Bas a function of sample size for both 1% and 10% nominal FDR levels, when.
[1]irical statistical power for the Wilcoxon test and dearseq asymptotic and permutation tests. Average over 50 semi-synthetic dataset generated from the GTEx Heart atrial appendage VS Heart left ventricle data. 50% of the true Differentially Expressed (DE) genes are randomly sampled in each semi-synthetic dataset (i. e. 2,889 genes remains unpermuted as true positives) and considered as gold-standard DE genes used as true positives. Panel A reproduces the results from Li et al[1]Figure2Bas a function of sample size for both 1% and 10% nominal FDR levels, when Nominal Rate: 1% 9 10 12 15 20 Sample size: 372/386 (total) 40 60 80 100 372/386 (total) Sample size (per group) 4 5 6 7 No normalization Normalization first 0. 01% 8 0. 1% 1% 5% 10% 20% 100% Nominal ('claimed') FDR S1 Supplementary figures of performance evaluation Nominal Rate: 10% 4 5 6 7 8 9 10 12 15 20 0.