Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Social Mobility Effect Poverty

This study attempts to investigate the intergenerational social mobility in Malaysia by focusing on the phenomenon of rural people getting out of the poverty circle. The analysis is based on a survey of the rural households in the northern region of Malaysia, comprising the states of Kedah, Perlis, Pulau Pinang and Perak. The impact of social mobility on poverty is analyzed using logit model where nine independent variables are used. The dependent variable which is the level of education of the son is used as a proxy to determine whether the person is poor or not. Those sons who achieved lower than a diploma is categorised as poor. Meanwhile, social mobility is categorised into four, namely no mobility, low mobility, medium mobility and high mobility. Our findings show that there are only four factors (mobility, asset ownership, the existence of a university in the near vicinity and the respondents’ house being near to town)that significantly affect poverty among the children. We found that the higher the social mobility, the lower the poverty. © 2016 Published by Future Academy www.FutureAcademy. org.uk
Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels

Abstract Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation quality metric (Rsq) overestimated dosage r2 (squared correlation between imputed dosage and true genotype) particularly in marginal-quality bins. Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1 or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θ value) in the hidden Markov model, we revealed that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could be deviated from dosage r2 for a subpopulation in the multi-ancestry panel, and the deviation represents different imputed-dosage distributions. Finally, despite the impact of the θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value substantially impacts the imputed dosage and the imputation quality metric value.
Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China

Background There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden. Methods Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status. Results A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status. Conclusions Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden. Supplementary information The online version contains supplementary material available at https://doi.org/10.1265/ehpm.23-00118.
Neonatal mortality associated with sodium monofluoracetate in kids fed with colostrum from goats ingesting Amorimia septentrionalis

ABSTRACT: Sudden deaths after colostrum ingestion in kids and lambs born to mothers grazing in areas with Amorimia septentrionalis have been reported in the Brazilian northeastern semi-arid region, in Paraíba state. This study aimed to determine whether the sodium monofluoracetate (MF) contained in A. septentrionalis is eliminated in milk, causing the death of kids. After confirming gestation on the 25th day after mating, 26 goats were randomly distributed into three groups. In Group 1, eight goats received fresh leaves of A. septentrionalis in daily doses of 1g/kg body weight, administered at three different periods during gestation: from days 91 to 100, 116 to 125, and from day 140 until delivery day. In Group 2, consisting of 10 females, eight goats received 1g/kg body weight of A. septentrionalis dried and milled leaves, fed daily from the 140th day of gestation until delivery. The other two goats of this group did not ingest the plant during gestation and after delivery the colostrum supplied to their kids was replaced by colostrum of goats from that same group that had ingested the plant. Eight goats from Group 3 (control) did not ingest A. septentrionalis. Seven goats from Group 1 showed signs of poisoning from 2nd to 8th days of plant administration, in all periods, and recovered within 7 to 12 days. Another goat presented severe clinical signs and was submitted to euthanasia in extremis. Two goats aborted. Four kids, from two goats, received colostrum and, after 15 minutes, presented depression, breathing wheezing, lateral recumbence, bleating, and death. Two goats gave birth at night; the two kids were found dead and, at necropsy, it was verified that they were born alive. The last goat in this group gave birth to two kids which showed no signs of poisoning after colostrum ingestion. In Group 2, the eight goats that ingested dry leaves of the plant presented tachycardia and engorgement of the jugular veins; six aborted, and the kids of the other two goats died immediately after delivery without ingesting colostrum. The three kids of the two goats that did not ingest the plant during gestation did not show signs of poisoning after ingesting colostrum from the goats that had ingested the plant. In Group 3, all females kidded normally and the kids showed no signs of poisoning. Ten leaf samples of A. septentrionalis contained 0.00074% ±0.00018 MF. These results demonstrate that the MF of A. septentrionalis is eliminated in colostrum and may cause the death of kids. As in previous reports, the plant also caused abortion.
Evaluation of Peri-Implant Parameters and Functional Outcome of Immediately Placed and Loaded Mandibular Overdentures: A 5-year Follow-up Study.

PURPOSE To evaluate the peri-implant parameters of immediately placed and loaded mandibular overdentures over a 5-year follow-up period. MATERIALS AND METHODS All subjects who had been advised and planned for two-implant mandibular overdenture treatment were included in this study. The peri-implant parameters -including plaque index (PI), bleeding index (BI) and peri-implant pocket depth (PIPD) as well as marginal bone loss (MBL) - were assessed. In addition, prosthodontic parameters including abutment-, implant- and denture-related complications were assessed. Patients were evaluated at follow-up visits, scheduled at 1, 12, 24, 36, 48, and 60 months. The data distribution was analysed with the Shapiro-Wilk test. Data within follow-up categories were compared using ANOVA and the Tukey-Kramer test. A p-value < 0.05 was considered statistically significant. RESULTS Among the 32 participants, 19 were males and 13 were females, with a mean age of 60.5 ± 7.33. The mean plaque index (PI), bleeding index (BI) and peri-implant pocket depth (PIPD) varied over time. However, no statistically significant difference was observed in the plaque index, bleeding index and peri-implant pocket depth over time (p > 0.05). The mean value at baseline was found to be -0.9 ± 0.3. The values increased over time, with the highest value observed at 60 months 2.6 ± 0.7, which was statistically significant (p < 0.001). CONCLUSION Immediately placed and loaded mandibular implant overdentures using two un-splinted implants with locator attachments showed acceptable PI, BI and PIPD at the 5-year follow-up. Statistically significantly greater marginal bone loss was observed from baseline to follow-up, but it was within acceptable limits. A moderate number of restorative and abutment complications were observed during the follow-up of IODs.
Interval estimation method for design flood region composition

The current methods for design flood region composition use some specific situations to summarize all possible combination of the flood at each sub-watershed,which leads to the results lacking in theoretical basis,showing huge difference and hard to assess the errors. In this study,the joint probability density function value of flood volume at each sub-watershed was adopted to measure its occurrence likelihood.Based on Copula function the normalized probability density function of flood volume at sub-watershed was derived. A new methodology for interval estimation of design flood region composition was proposed. The Geheyan reservoir located at Qingjiang basin was selected as a case study. It is demonstrated that the results of typical year method are not within the range of peak discharges estimated by the 95 % confidence intervals,and the results of equivalent frequency regional composition method are within those intervals which indicates that it has some rationality. The proposed method has strong statistical basis and can not only give both point and interval estimates of design flood region composition,but also evaluate the uncertainty of estimate quantitatively,which will provide a new approach for design flood region composition analysis and calculation.
Predicting drug–target binding affinity with cross-scale graph contrastive learning

Abstract Identifying the binding affinity between a drug and its target is essential in drug discovery and repurposing. Numerous computational approaches have been proposed for understanding these interactions. However, most existing methods only utilize either the molecular structure information of drugs and targets or the interaction information of drug–target bipartite networks. They may fail to combine the molecule-scale and network-scale features to obtain high-quality representations. In this study, we propose CSCo-DTA, a novel cross-scale graph contrastive learning approach for drug-target binding affinity prediction. The proposed model combines features learned from the molecular scale and the network scale to capture information from both local and global perspectives. We conducted experiments on two benchmark datasets, and the proposed model outperformed existing state-of-art methods. The ablation experiment demonstrated the significance and efficacy of multi-scale features and cross-scale contrastive learning modules in improving the prediction performance. Moreover, we applied the CSCo-DTA to predict the novel potential targets for Erlotinib and validated the predicted targets with the molecular docking analysis.
COVID-19 in Children with Chronic Kidney Disease; Does it Differ Much?

Abstract Background COVID-19 is known to have a mild course in children, however more data on pediatric chronic kidney disease (CKD) is needed. We aimed to assess the incidence and severity of COVID-19 in pediatric CKD patients. Methods A questionnaire including demographics, COVID-19 history, symptoms, and vaccination status was applied to patients with CKD. We also retrospectively reviewed the presentation and outcomes of SARS-CoV-2 infection in this patient group from March 2020 to December 2021. Results 220 patients were included, 48 were found to have experienced COVID-19. There was no significant difference regarding age, gender, underlying kidney disease, CKD stage, dialysis status, type or number of immunosuppressive medications, and glomerular filtration rate between patients with and without COVID-19. Most were infected by a household member (43.8%) and during outpatient or inpatient care (18.8%). Four (8.3%) were asymptomatic, and 43 (89.6%) had mild infection. Severe COVID-19 was observed in only one patient. Eleven (22.9%) patients with COVID-19 were previously vaccinated. Acute kidney injury was detected in 4 (8.3%); as stage 1 in all. Median follow-up after COVID-19 was 4.6 months. All patients fully recovered, and no renal disease flare or death was observed. Conclusions Although the vaccination rate was low in our cohort, the majority of the children with COVID-19 showed a mild course. Along with the vaccination, general precautions seemed to be successful for this population.
Automatic Classification of Interactive Texts In Design Thinking

This research used natural language processing technology to analyze learners’ interactive texts in the design process, open up the black box of design, and assess learners’ design thinking and information processing level in the design process based on interactive text data. This study proposed a design thinking stage model with reference to the process model of design thinking, and built a text coding framework based on interactive text data. An experiment involving181 students was conducted to collect interactive text data. An automated classification of interactive texts was achieved based on manual and machine coding, and BERT algorithm model performed better, with the accuracy reaching 82%. This automatic classification method has high application value in mastering learners’ knowledge mastery, learning activity maintenance, intervention of learning emotion, and early warning of learning in the design process.
Teaching-Assistant Robot Tutoring Students in the Classroom

This paper describes a teaching-assistant robot that helps teachers conduct programming classes. Programming classes generally include explanations of the basic syntax of programming languages, their applications, and cording exercises. However, the time in these classes teachers spend debugging students’ programs is usually much longer than the actual class time. Such delays can affect the progress of programming classes and student motivation. Against this background, we have been developing a teaching-assistant robot that provides advice and assistance to students with questions to support the efficient flow of programming classes. In this paper, we describe a method in which a teaching-assistant robot locates a student who has a question, moves to the student, responds to the student's question about the assembly of a wheeled robot, and gives advice to the student in a simulated class about assembling a wheeled robot used for learning programming. The teaching-assistant robot is able to answer questions about the assembly of the wheeled robot and give advice. In addition, the effectiveness of the teaching-assistant robot is demonstrated through evaluation experiments.
Design with Simon's Inner and Outer Environments: Theoretical Foundations for Design Science Research Methods for Digital Science

Design science research has traditionally been applied to complex real-world problems to produce an artifact to address such problems. Although design science research efforts have been applied traditionally to business or related problems, there is a large set of problems in the area of digital science that also require important, digital artifacts. The digitalization of science has resulted in the need to develop essential, specialized, devices and software before it is feasible for scientists to carry out their work. This research examines digital science to identify its challenges and demonstrate how it can be possible to progress digital science with design science research, thereby establishing digital science as an important area of transdisciplinary inquiry. These areas of research are examined for their synergies and explained by positioning artifact development challenges with respect to Simon's inner and outer environments, and the interface between them.
Human Brain Mapping of Homotopic Functional Affinity

Spatially corresponding areas in the left and right hemispheres of the human brain, also known as homotopic brain regions, often exhibit functional similarities, i.e., functional homotopy. To understand the principles and mechanisms of functional homotopy in human psychological behavior, this paper proposes a method for studying functional homotopy in the human brain: homotopic functional affinity. This method quantifies the functional affinity of homotopic brain regions by calculating the cosine distance of whole-brain functional connectivity patterns of homotopic regions. Using the whole-brain functional MRI database from the Human Connectome Project in the United States and China, we first mapped the homotopic functional affinity atlas with “700 milliseconds - 2 millimeters” spatiotemporal precision, assessing its test-retest reliability for individual differences. Subsequently, we located three specific areas in the human temporo-parietal junction through systematic analysis of this atlas, discovering their hemispheric lateralization patterns and revealing their functional associations with attention, language, and social cognition. Lastly, through multimodal brain atlas correlation calculations, we further explored the correlation of human brain homotopic functional affinity with genetics, evolution, structural, and functional organizational distribution. In summary, our proposed method of homotopic functional affinity provides a reliable and valid functional measurement atlas for population neuroscience research.
A Checklist of Phytoplanktonic Algae of Nyamuhinga Stream in Lake Kivu Basin (Eastern DR Congo)

Limnology Laboratory, Department of Biology, Centre de Recherche en Sciences Naturelles de Lwiro (CRSN-Lwiro), D.S. Bukavu/DR Congo. Vegetable Physiology and Apply Microbiology Laboratory, Faculty of Sciences and Applied Sciences, Université Officielle de Bukavu (UOB), PO Box. 570 Bukavu, DR Congo. Biology Department, Section of Exact Science, Institut Supérieur Pédagogique de Kinyatsi (ISPKinyatsi), . PO Box.
Global Huntingtin Knockout in Adult Mice Leads to Fatal Neurodegeneration that Spares the Pancreas

Huntington’s disease (HD) is a fatal neurogenerative disorder caused by an expanded glutamine-coding CAG tract in the Huntingtin (Htt) gene. HD is believed to primarily arise via a toxic gain of function, and as a result a wide range of Htt-lowering treatments are in clinical trials. The safety of these trials is contingent on the risks imposed by Htt lowering: Htt is widely conserved, ubiquitously expressed and its complete loss causes severe developmental symptoms in mice and humans. Recently, multiple labs have reported on the consequences of widespread inducible Htt loss in mice. One report describes that early induction of global Htt loss causes fatal pancreatitis, but that later onset lowering is benign. Another study did not report fatal pancreatitis but suggested that postnatal Htt loss was associated with widespread progressive phenotypes, including subcortical calcification and neurodegeneration. To better understand the risks posed by widespread inducible Htt loss we established the phenotypes of mice in which we knocked out Htt with two tamoxifen inducible Cre lines, which we have here extensively characterized. In short, we find that widespread loss of Htt at 2 months of age leads to a wide range of phenotypes, including subcortical calcification, but does not result in acute pancreatitis or histological changes in the pancreas. Additionally, we report here for the first time that Htt loss is followed by robust and sustained increases in the levels of neurofilament light chain (NfL), a peripherally accessible biomarker of neuroaxonal stress. These results confirm that complete loss of Htt in mice is associated with pronounced risks, including progressive subcortical calcification and neurodegeneration.
The inevitability and superfluousness of cell types in spatial cognition

Discoveries of functional cell types, exemplified by the cataloging of spatial cells in the hippocampal formation, are heralded as scientific breakthroughs. We question whether the identification of cell types based on human intuitions has scientific merit and suggest that “spatial cells” may arise in non-spatial computations of sufficient complexity. We show that deep neural networks (DNNs) for object recognition, which lack spatial grounding, contain numerous units resembling place, border, and head-direction cells. Strikingly, even untrained DNNs with randomized weights contained such units and support decoding of spatial information. Moreover, when these “spatial” units are excluded, spatial information can be decoded from the remaining DNN units, which highlights the superfluousness of cell types to spatial cognition. Now that large-scale simulations are feasible, the complexity of the brain should be respected and intuitive notions of cell type, which can be misleading and arise in any complex network, should be relegated to history.
Predictive coding in ASD: inflexible weighting of prediction errors when switching from stable to volatile environments

Individuals with autism spectrum disorder (ASD) have been widely reported to show atypicalities in predictive coding, though there remains a controversy regarding what causes such atypical processing. Suggestions range from overestimation of volatility to rigidity in the reaction to environmental changes. Here, we tested two accounts directly using duration reproduction of volatile and non-volatile interval sequences. Critically, both sequences had the same set of intervals but differed in their stimulus presentation orders. Comparing individuals with ASD vs. their matched controls, we found both groups to respond to the volatility in a similar manner, albeit with a generally reduced prior in the ASD group. Interestingly, though, relative to the control group, the ASD group exhibited a markedly reduced trust in the prior in the volatile trial session when this was performed after the nonvolatile session, while both groups performed comparably in the reverse session order. Our findings suggest that it is not the learning of environmental volatility that is compromised in ASD. Rather, it is their response to a change of the volatility regimen from stable to volatile, which causes a highly inflexible weighting of prediction errors. keywords: autism, predictive coding, prediction errors, adaptability, volatility