dataesr/scientific-paragraphs-categorization huggingface dataset:
Determination of molecular weight distribution of hemicellulose by SEC The molecular weight distribution of hemicellulose was determined by SEC. The analysis was performed using a Hewlett-Packard 1090 series HPLC system consisting of an autosampler, a UV detector, and 3 columns of Styragel HR1, HR3, and HR4 (Waters Inc. ) linked in series using tetrahydrofuran (THF) as the eluent. The hemicellulose was dissolved in 1 mg/mL of THF, and the solution was filtered through a 0. 45 mm filter. Then, 20 mL of the filtered solution was injected into the system and was detected using a UV detector at 280 nm. Data were collected using Agilent ChemStation rev. A. 10. 01 and analyzed using Agilent GPC Addon rev. A. 02. 02 software.
Acknowledgements The authors thank  Dr. Isabelle Ziegler-Devin  from  LERMAB, University of Lorraine, France , in aiding with the HPAEC-PAD and SEC analysis. as well as Biolie, France, in assisting with the AEE and GC-MS analysis. The authors also thank the  Malaysian Government, French Embassy Malaysia ,  Université de Lorraine , and  Universiti Sains Malaysia  for the financial support of this study through the  Research University Grant  RUI:  1001/PKIMIA/8011072.
Introduction The seventh United Nations Sustainable D evelopment G oal (SDG7) is: Ensure access to affordable, reliable, sustainable and modern energy. In short, Affordable and clean energy is one of our overarching civilization goals this millennium. Statisticians usually measure progress towards SDG7 using objective indicators based on electricity distribution and consumption data. This text argues that objective indicators are not enough. Human development is an issue of subjective feeling as much as a question of technology or economics. Based on national household surveys, self-reported satisfaction indicators offer a complementary perspective to understand society's energy poverty situation more fully. Vietnam is a Southeast Asia country comprising almost a hundred million people. Its GDP per capita, purchasing power parity, was 8 397 USD in 2019 (World Bank database, accessed 2021-05-22).
We will look at the residential demand from a different perspective -energy poverty-using different data: the Vietnam Households Living Standard Surveys (VHLSS) from 2008 to 2018. Son and Yoon (2020)  examined the determinants of inequality in Vietnamese households electricity consumption, using VHLSS data from 1993 to 2004. Inequality can be defined, at the population level, by how much the statistical distribution of consumption deviates from the uniform distribution. They found that a) electricity consumption increased more than proportionally with income, and b) the inequality of electricity consumption was larger than income inequality. The grid expanded continuously from 1993 to 2004, increasing electricity access. Son and Yoon warned that increasing access could increase inequality as the wealthier households benefited more from the opportunity.
Acknowledgements NHS provided the initial idea and the data, HDM directed the research. The two authors contributed to statistical analysis and writing. This work was started while the first author was visiting professor at the Clean Energy and Sustainable Development Lab (CleanED/USTH). We gratefully acknowledge comments from our colleagues Audrey Berry, Franck Nadaud, Nguyễn The first block is split into two blocks. The first 50 kWh is priced at 35 -40% of the average electricity supply cost. The second 50 kWh is priced at the average supply cost. 2011 The first two blocks are amended. The first block is 0 -50 kWh and priced at the average supply cost. This price is only for low-income households registered with EVN, which consume less than 50 kWh per month. All other households pay the second block price from 0 to 100 kWh.
Statistical Analysis Data were analyzed using a mixed effects model in Minitab 18. In the model, diet, experimental week, and their interaction were used as fixed factors, while cow was set as the random factor  [50]. Measurements from the week before the 6-week measurement period, when all cows were fed the same basal diet, were used as a covariate in the model. Normality of residuals were evaluated visually and, while most data showed no deviation from normality, SCC, milk I content, and I intake were log10 transformed prior to analysis so that their residuals were normalized. Fischer's least significance difference test (p < 0. 05) was used for pairwise comparison of the means, where the mixed effect model showed a significant effect of diet, experimental week, or their interaction.
Acknowledgments: The farmers  Höskuldur Gunnarsson  and  Hilda Pálmadóttir  at the experimental farm  Stóra-Ármót, Iceland , are thanked for their efforts and work. Helga Gunnlaugsdóttir  (Orkidea) and  Jóhannes Sveinbjörnsson  ( Agricultural University of Iceland ) are acknowledged for their muchappreciated advice on the experimental design. Sveinn Sigurmundsson  ( Agricultural Society of South Iceland ) is thanked for his effort in getting the project started. The authors would like to thank  Christopher Humphrey  for his guidance on milk and feed analysis for iodine.
64 × 10 6 g/mol in an atypical area, Échemines (France) in the 2015 crop season, to 30. 51 × 10 6 g/mol at Navarre (Spain) in the same crop season. To verify our choice of locations used in our study and to detect possible effects exerted by groups of locations, we processed the data according to the characteristics of the locations. Thus, we have formed three groups of places as indicated in the materials and methods section. The means and the results of the Duncan analysis are shown in Table  4. The results showed that there were significant differences between location groups for all parameters except for the percentage of AML and AMP. We noted that "typical" locations in France and European areas were often distinguished from the "atypical" group in France. This really indicated significant differences in growing conditions (abiotic stress).
Acknowledgments: The authors thank the majority of European private breeding companies operating in France (Caussades semences. Florimond Desprez. Agri Obtentions. Secobra. Limagrain. Lemaire. Momont-Hennette. Asur Plant breeding. Syngenta Seeds. RAGT) for the provision of their wheat cultivars and their logistical support. The authors thank also all engineers, technicians and trainees who participated in the FSOV, particularly  Camille Boroch ,  Lucie Lequeux ,  Zineb Kadri  and  Marwa Ben Salah.
Statistical Analysis Normality of the data was tested using Kolmogorov-Smirnov test. All analysis (Chi-square test, two-samples t-test, Mann-Whitney U, Kruskal-Wallis, Spearman correlation, linear regression, and Receiver Operating Characteristics "ROC") were performed using IBM SPSS Statistic software version 23 (IBM Corporation, USA). The results of continuous variables are provided in mean (95% K & Sr peaks CI) and median (IQR) and of categorical variables in percentages (%). When the P-value was < 0. 05 the result was considered as statistically significant, and the degree of the differences are marked as: * p < 0. 05, * * p < 0. 01, * * * p < 0. 001, and * * * * p < 0. 0001. All figures were created with GraphPad Prism 9. 0. 1.
Especially, the in vivo therapeutic efficacy of SPMs and associated dampening of effector T-cell responses can benefit from both a direct effect on T cells and an indirect action through antigen-presenting cells (APCs: DCs, macrophages), expressing SPM receptors, as SPMs downregulate APC activation, expression of costimulatory molecules, and secretion of inflammatory cytokines, which subsequently prime effector T cells  (72). In terms of clinical application, a pilot study has been launched in patients undergoing total knee arthroplasty to investigate the impact of preoperative supplementation with Lipinova ® (Solutex), described as a concentrate of EPA, DHA, and SPMs (NCT03434236). However, the clinical use of SPMs as therapeutic agents is impeded by their metabolically labile and unstable state, restricted bioavailability, and rapid clearance, and thus calls for the development of SPM synthetic analogs displaying pharmacokinetic properties in compliance with in vivo usage  (92, 93).
In this line, a RvE1 mimetic, RX-10045, has been tested as an ophthalmic solution for dry eye symptoms (NCT00799552), allergic conjunctivitis (NCT01639846), and in patients undergoing cataract surgery (NCT02329743). Promising results were recently reported in a phase 1 trial evaluating the safety and efficacy of BLXA4, a LXA4 analog, to treat periodontitis (NCT02342691): daily rinsing with mouthwash containing BLXA4 reduced gingival inflammation, and this was associated with a shift in serum lipid mediators toward a pro-resolving profile  (94). The development of SPM receptor agonists is also in the pipeline, as recently documented by the study of Trilleaud et al. who tested a new anti-ChemR23 agonist antibody in models of acute and chronic colitis (induced by DSS or adoptive transfer of CD4 + CD45RB high T cells, respectively) and inflammation-driven cancers  (95).
SPM lipidomic analyses are indeed performed in the frame of several clinical studies as a read-out of disease diagnosis and progression, inflammatory profile [for instance in COVID19 patients (100)], as well as response to therapeutic interventions (NCT04698291, NCT04452942, NCT04697719, NCT01865448, NCT04308889, NCT04377334, and NCT02719665)  (101). In addition, the pathways governing immune regulation and resolution programs are interrelated and provide the mechanistic rationale for developing SPM-based therapeutic strategies that can be beneficial for the treatment of chronic inflammatory disorders, autoimmune diseases, and organ transplantation, notably through the control of effector T cells and boost of Tregs. This is reinforced by the positive outcomes observed in various pathological settings after dietary intervention using SPM precursors, DHA and EPA, or omega-3 lipids, which enhance SPM levels and help in controlling excessive inflammation and autoimmunity in both humans and mice  (102) (103) (104).
FUNDING The laboratory of SY and JP-H is supported by grants from the  EFSD/JDRF/Lilly European Programme in Type 1 Diabetes Research 2019 , the  Agence Nationale de la Recherche  ( ANR-17-CE17-0004 ,  ANR-18-IDEX-0001 ), the  Fondation pour la Recherche Medicale  ( EQU20193007831 ), the  Association des Jeunes Diabetiques , and the  Innovative Medicines Initiative 2 Joint Undertaking  under grant agreements  115797  and  945268  (INNODIA and  INNODIA HARVEST) , which receive support from the  EU   Horizon 2020 program , the  European Federation of Pharmaceutical Industries and Associations, JDRF , and  The Leona M. and Harry B. Helmsley Charitable Trust. VC is funded by the  Italian Ministry of Health  (grant  GR-2016-02362380 ), the  Italian Foundation of Multiple Sclerosis  ( FISM 2017/R/08 ), and the  MAI Award Grant  ( MAI-VC-2021 ).
SP is funded by the  Conseil Reǵional de Franche-Comté ( AAP 2019 ), the  Agence Nationale de la Recherche  ( ANR-11-LABX-0021  and  ANR-17-CE17-0004 ),  BPI France  (grant No. DOS0060162/00 ), and the  European Union  through the  European Regional Development Fund of the Reǵion Bourgogne-Franche-Comte  ( FC0013440 ).
Procedure The images are analyzed using the free software "ImageJ". This software allows to filter the images according to the characteristics of the color. The thresholds were set to measure the areas corresponding to the hulls. When the cutoff was set, the software calculates the area occupied by the selected pixels. Although the samples are slightly flattened by the scanner cover, there are still shadows in the image that may cause us to underestimate the kernel content. Since it is not possible to set thresholds that would identify these shaded areas to remove them from the analysis, we considered that this bias would be constant and would not affect our purity assessments.
Wenlin and Fenghong (2007)  using a process based on percussion of the seeds followed by separation in an air stream claim to be able to obtain a residual kernel content of less than 1% in the hull fraction. However, the best source of information appears to be the Feedipedia database, which contains a compositional table based on 32 samples indicating an average oil content of 13. 2% on dry matter (11. 5% at 12. 5% water,  Heuzé et al. , 2019). The database collects analyses from industrial and experimental samples. Interestingly, the values are highly variable (7. 4-24. 4% on DM, standard deviation 4. 5%). This variability may be partly due to the difficulty of extracting the oil present in the endosperm cells, which requires vigorous grinding to be made extractable and which not all laboratories perform  (Quinsac et al.
, 2013). In conclusion, compared to the literature data, our results support the best performance comparison. The system requires a precise adjustment of the roll gap and works perfectly with hulls at natural water content. We have seen that the good functioning of the system requires a homogeneous distribution of the particles on the working surface. The feeding of the rollers requires a device which must be thought to ensure an arrival in monolayer of the particles to be separated. The process, apart from the cylinders, does not require any additional equipment. The simplicity of the principle, and the few parameters to be controlled, should allow a regular operation with few malfunctions and simple maintenance. The energy consumption and maintenance costs of this process should be low. A search in the scientific literature and in patent databases suggests that this sorting principle is new in the field of oilseed material sorting.
Acknowledgements. This work was performed in partnership with SAS PIVERT within the framework of the ( French) Institute for Energy Transition (Institut pour la Transition Énergétique (ITE) PIVERT  (www. institut-pivert. com)program selected as an  Investment for the Future ("Investissements d'Avenir") project. This work was supported by the  French Government  as part of the  Investissements d'Avenir programme , under reference  ANR-001.
Data analysis Annual schistosomiasis prevalence was presented as a percentage of the number of children infected in an age group out of the total number of children in the same age group. Linear regression was used to examine the trend in the annual schistosomiasis prevalence from the beginning of the study to 2020. A two-sided of Chi-squared test was used to compare prevalence between the different age groups of PSAC. Results were considered statistically different if P < 0. 05 (*); P < 0. 01 (**); P < 0. 001 (***). Data were entered using Microsoft Excel ® spreadsheet software. Statistical analyses were conducted using R studio software [R Core Team (2019). R: A language and.
In consequence, children who do not go to school are not offered treatment and their mobility could promote the spread of the disease. Indeed, studies have shown that non-school-attending SAC have similar or higher prevalence rates of infections compared to school-attending children  [38, 48]. These data encourage us to continue to work in parallel with the PNLB in order to track nonschool-attending infected children and to better control the disease. Moreover, as praziquantel is now administered by a teacher and not by a healthcare worker who is more aware of the serious risks of schistosomiasis, this could lead to a lack of compliance from the children so praziquantel administration should be careful monitored, as also suggested in previous studies  [27, 37]. To counter the potential bias due to the treatment provided by the PNLB, we evaluated the prevalence of schistosomiasis before their arrival in the village to evaluate the eventual re-infestations in SAC.
Funding: This work has been supported by the  French government's "Investissements d'Avenir" programme , which is managed by the  Agence Nationale de la Recherche (ANR) , under the reference PsyCARE  ANR-18-RHUS-0014. Ariel Frajerman  is funded by the  Agence Régionale de Santé Ile de France. Boris Chaumette  receives a grant from the  Fondation Bettencourt Schueller.
(Lys205del) mutation in PROKR2, both in a male patient with normosmic idiopathic IHH (HH12) and his asymptomatic mother. Whole-exome sequencing in the three HH1 family members allowed the identification of additional variants in the prioritized genes. We then carried out digenic combination predictions using the oligogenic resource for variant analysis (ORVAL) software. For HH1, we found the highest number of disease-causing variant pairs. Notably, a CCDC141 variant (c. 2803C > T) was involved in 18 pathogenic digenic combinations. The CCDC141 variant acts in an autosomal recessive inheritance mode, based on the digenic effect prediction data. For the second patient (HH12), prediction by ORVAL allowed the identification of an interesting pathogenic digenic combination between DUSP6 and SEMA7A genes, predicted as "dual molecular diagnosis.
In-silico Analysis To gain insight into the effect of the newly identified genetic variation p. (Lys205del), we carried out an in silico analysis. We first tested the impact of genetic variation on splicing by creating or abolishing a splice site. This analysis was performed using the Human Splicing Finder program  (Desmet et al. , 2009)   1. We then carried out an in silico 3D structure prediction using Phre2 tool  (Kelley et al. , 2009)   2  in order to predict the effect of genetic variation on protein folding.
Exome Analysis An in-house pipeline analysis was used to generate VCF files. Then, the annotation and the prioritization of variants were carried out using VarAFT tool, version 2. 04 3. A disease-causing gene approach was used to extract variants located in 46 CHHrelated genes extracted from the Online Mendelian Inheritance in Men database and recent literature (Supplementary Table  1 ). Functionally relevant variants located in exonic genomic regions and splice sites were then selected from the list of variants contained in the VCF file. Variants located in the regulatory regions (UTR, promoters, enhancers, and miRNA binding sites, etc. ) flanking the PROKR2 gene were also screened. Regulatory regions were retrieved using the Genome Browser tool provided by the University of California Santa Cruz database 4  as well as the GeneCards Human Gene database 5.
The functional effects of the genetic sequence variants were evaluated by in silico prediction tools including SIFT 6  , PolyPhen 7  , FATHMM 8  , MutationTaster 9  , MutationAssessor 1. 0 10  , PROVEAN v1. 1 11  , and Varsome 12. Furthermore, in order to pinpoint the variants that could potentially be associated with disease expression in the index cases (HH1 and HH12), each selected variant of interest was compared to the exome data of 92 unrelated Tunisian individuals stored in the local database. This approach allowed us to avoid bias especially that public databases, such as ESP6500, GnomAD, or 1000Genomes, do not contain relevant information regarding the genetic background of individuals from the Middle East, North Africa populations.
Digenic Effect Prediction The Oligogenic Resource for Variant Analysis (ORVAL) online software 13  was used to predict the effect of variant combinations in disease-causing genes. This tool is based on variant annotation and effect prediction of two predictive methods named VarCOPP and Digenic Effect predictor. The evaluation scores of digenic combinations include the support score (SS) and the classification score (CS). SS informs about the percentage of algorithms integrated in VarCOPP and Digenic Effect predictor that support the pathogenicity of a given bi-locus combination. Its value ranges from 0 to 100. For candidate disease-causing combinations, SS should be equal or greater than 50%. The CS should correspond to the median probability of a digenic combination to be disease-causing.
To confirm these molecular findings, blood sampling, PCR, and sequencing reactions were performed twice. To exclude contamination and paternity problems, all members of this family were genotyped using the identifier kit (Applied Biosystems). The analysis of allele segregation was in favor of paternity inclusion. For HH12, the molecular analysis allowed the identification of a novel variation, c. 614_616del; p. (Lys205del), in the PROKR2 gene at a heterozygous state. Bioinformatics analysis using the Uniprot database showed that the lysine amino acid at position 205 is buried amid the second extracellular loop and that this residue is highly conserved in Prokr2 from mouse, rat, chimp, dog, cow, Xenopus tropicalis, and zebrafish and in the human PROKR1 protein. The deleterious effect of this genetic variation could be explained by the creation of a new acceptor splice site as illustrated by the results of the Human Splicing Finder and Genetic Variation Taster tools (donor gained, score = 0.
Exome Analysis and Digenic Effect Prediction for the HH1 Family In total, 43, 39, and 33 genetic variants were identified in HH1, her brother, and her father, respectively. For HH1, seven rare variants were identified with a minor allele frequency (MAF) < 0. 1 according to the 1000Genomes and GnomAD databases. Four rare variants were harbored by the brother and the father. Besides the p. (Pro290Ser) in the PROKR2 gene, the remaining rare variants in each case were predicted as benign or as VUS by Varsome search engine as well as 10 in silico prediction programs (Supplementary Tables  2 3 4 ). For each set of variants identified in the three family members, we proceeded to the digenic effect prediction of variant pairs using the ORVAL software. A total of 940, 828, and 668 digenic combinations were, respectively, obtained in the index case HH1, the asymptomatic brother HH1F, and the father HH1P.
These specific variants included four exonic missense variants in PCSK1 (NM_000439), IL17RD (NM_017563), and CCDC141 (NM_173648) genes, which were homozygous in the proband and heterozygous in the unaffected family members. Another exonic variant in the FLRT3 gene (NM_013281), as well as two splice site variants in WDR11 (NM_018117) and SMCHD1 (NM_015295) genes, was only present in the index case HH1 (Table  2 ). All these variants were frequent, with a MAF ranging from 0. 2 to 0. 6 according to the GnomAD database, except for the missense variant [c. 2803C > T; p. (Arg935Trp)] in the CCDC141 gene (MAF = 0. 06) (Supplementary Table  2 ). This variant was absent in the in-house control database. Despite being predicted as benign by Varsome, this variant [p. (Arg935Trp)] was involved in the second most important pathogenic combinations (15%; 13 genes) in HH1, after the PROKR2 gene variant [p.
The two other genetic variations identified in FLRT3 (NM_013281) and WDR11 (NM_018117) genes, present only in HH1 case, represented only 2% of the overall diseasecausing variant pairs. We also evaluated the involvement of other variants located in the flanking regulatory regions of the PROKR2 gene, which could be responsible for the incomplete penetrance in the family members of HH1. On the basis of predictions provided by the Encyclopedia of DNA Elements and the GeneHancer database, we focused on regulatory regions adjacent to the PROKR2 gene, likely covered by whole-exome sequencing (WES). The closest promoter and enhancer regions are located in the exon 1-intron 1 junction of PROKR2. This region is rich with CpG islands and overlaps with the AX746654 gene. Two transcription factors, namely, HDAC2 and CTCF, are known to bind to this region.
The WES analysis did not reveal any variants in the regulatory region of PROKR2 nor in the genes encoding its transcription factors. (NM_001146029), as well as a splice site variation in the PLXNA1 gene (NM_032242; MAF = 0. 03 in GnomAD). The SEMA7A gene variant was predicted as a VUS according to Varsome, whereas the PLXNA1 gene variation was classified as benign. The SEMA7A variant [p. (Glu436Lys)] was absent in the 92 exomes of our local database (Supplementary Table  8 ).