Miracle-dz/UniFAR-FTUs huggingface dataset:
Age, Growth, and Fecundity of Alabama Shad ( Alosa alabamae ) in the Apalachicola River, Florida

Age and growth of Alabama shad Alosa alabamae were estimated by examining scales and otoliths from 203 adult fish collected on their spawning run in the upper Apalachicola River from 2005 and 2006. Ages of Alabama shad ranged from 1  4 years. All sampled spawning males were between 1 and 3 years old, whereas females were 2 4 years of age. Scales and otoliths both gave similar age estimates. Although otoliths are the preferred aging structure, scales can be removed in the field without sacrificing the specimen. Age distributions from this study differed from those of previous studies for both males and females. Female Alabama shad, on average, were found to be larger than males at age 2 and age 3. Growth of male and female Alabama shad is best described by the equations: Lt = 359.6 [1 ℮ ] and Lt = 389.5 [1 ℮ ]. Mean back-calculated lengths were similar to those of observed values for males and females. Alabama shad demonstrated a positive correlation of length to fecundity, with fecundity estimates ranging from 26,095 to 208,494 eggs per female. Fecundity estimates appeared similar to other studies from the Apalachicola River. Variations in fecundity estimates may be contributed to partial spawning. Gonosomatic indices of female shad ranged from 3.6  24.0. In contrast to earlier studies, no spawning marks were found on scales.
A Di erential Geometric Approachto Nonlinear Filtering : the Projection Filter

We present a new and systematic method of approximating exact nonlinear lters with nite dimensional lters, using the diierential geometric approach to statistics. We deene rigorously the projection lter in the case of exponential families. We propose a convenient exponential family, which allows to simplify the projection lter equation, and to deene an a posteriori measure of the performance of the projection lter.
The role of hypoxia-inducible factor stabilizers in the treatment of anemia in patients with chronic kidney disease

Introduction: The purpose of this study was to analyze the effects of hypoxia-inducible factor (HIF) stabilizers on anemia in non-dialysis-dependent (NDD) and dialysis-dependent (DD) chronic kidney disease (CKD) patients. Methods: Published studies were extracted from PubMed, China Biological Medicine Database (CBM), Wanfang database, and Cochrane Library on March 10, 2018, and relevant studies were pooled and included in a meta-analysis. Data on hemoglobin (Hb), ferritin, and hepcidin levels, total iron-binding capacity (TIBC), and incidence of adverse events (AEs) were extracted and pooled using Review Manager Version 5.3. Results: Data from nine selected studies were extracted. Meta-analysis of the included studies showed that HIF stabilizers reduced ferritin and hepcidin levels and increased Hb level and TIBC in NDD-CKD patients. However, HIF stabilizers only increased TIBC, and did not affect ferritin, hepcidin, and Hb levels in DD-CKD patients. Furthermore, no notable differences in AEs and severe AEs between NDD-CKD and DD-CKD patients were detected. Conclusion: HIF stabilizers are effective for the treatment of anemia in NDD-CKD patients and safe for short-term use.
Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms

This paper presents exact solution methods for analyzing vulnerability of electric power networks to a certain kind of undetectable attacks known as false data injection attacks. We show that the problems of finding the minimum number of measurement points to be attacked undetectably reduce to minimum cut problems on hypergraphs, which admit efficient combinatorial algorithms. Experimental results indicate that our exact solution methods run as fast as the previous methods, most of which provide only approximate solutions. We also present an algorithm for enumerating all small cuts in a hypergraph, which can be used for finding vulnerable sets of measurement points.
eR- α 36: a novel biomarker and potential therapeutic target in breast cancer

: Estrogen receptor-alpha36 (ER- α 36) is a 36-kDa variant of estrogen receptor-alpha (ER- α ) firstly identified and cloned by Wang et al in 2005. It lacks both transactivation domains (activation function 1 and activation function 2) and has different biological characteristics compared to traditional ER- α (ER- α 66). ER- α 36 primarily locates on plasma membrane and cytoplasm and functions as a mediator in the rapid membrane-initiated non-genomic signaling pathway. Additionally, it inhibits the traditional genomic signaling pathway mediated by ER- α 66 in a dominant-negative pattern. Accumulating evidence has demonstrated that ER- α 36 regulates the physiological function of various tissues. Thus, dysregulation of ER- α 36 is closely associated with plenty of diseases including cancers. ER- α 36 is recognized as a molecular abnormality which solidly correlates to carcinogenesis, aggressiveness, and therapeutic response of breast cancer. Additionally, special attention has been paid to the role of ER- α 36 in endocrine therapy resistance. Therefore, ER- α 36 provides a novel biomarker of great value for diagnosis, prognosis, and treatment of breast cancer. It may also be a potential therapeutic target for breast cancer patients, especially for those who are resistant to endocrine therapy. In this review, we will overview and update the biological characteristics, underlying mechanism, and function of ER- α 36, focusing on its biological function in breast cancer and endocrine therapy resistance. We will evaluate its application value in clinical practice.
Patients with systemic lupus erythematosus, myositis, rheumatoid arthritis and scleroderma share activation of a common type I interferon pathway

Objective To characterise activation of the type I interferon (IFN) pathway in patients with systemic lupus erythematosus (SLE), dermatomyositis (DM), polymyositis (PM), rheumatoid arthritis (RA) and systemic scleroderma (SSc) and to evaluate the potential to develop a molecular diagnostic tool from the peripheral blood that reflects this activation in disease-affected tissues. Methods Overexpressed transcripts were identified in the whole blood (WB) of 262 patients with SLE, 44 with DM, 33 with PM, 28 with SSc and 89 with RA and compared with 24 healthy subjects using Affymetrix microarrays. A five gene type I IFN signature was assessed in these subjects to identify subpopulations showing both activation and concordance of the type I IFN pathway in the peripheral blood and disease-affected tissues of each disease and to correlate activation of this pathway in the WB with clinical measurements. Results A common set of 36 type I IFN inducible transcripts were identified among the most overexpressed in the WB of all subjects. Significant activation of the type I IFN pathway in subgroups of each of the five diseases studied was observed. Baseline disease activity measurements correlated with a type I IFN gene signature in the WB of subjects with SLE, PM and SSc, as did various serum autoantibody levels in subjects with SLE and DM. This signature was also well correlated between disease-affected tissue and WB in subjects with SLE, DM, PM and SSc. Conclusions The results indicate that the type I IFN pathway is activated in patient subsets of five rheumatic diseases and suggest that these subsets may benefit from anti-IFN therapy.
Defeasibility in Answer Set Programs via Argumentation Theories 1

Defeasible reasoning has been studied extensively in the last two decades and many different and dissimilar approaches are currently on the table. This multitude of ideas has made the field hard to navigate and the different techniques hard to compare. Our earlier work on Logic Programming with Defaults and Argumentation Theories (LPDA) introduced a degree of unification into the approaches that rely on the well-founded semantics. The present work takes this idea further and introduces ASPDA (Answer Set Programs via Argumentation Theories) — a unifying framework for defeasibility of disjunctive logic programs under the Answer Set Programming (ASP). Since the well-founded and the answer set semantics underlie almost all existing approaches to defeasible reasoning in Logic Programming, LPDA and ASPDA together capture most of those approaches. In addition to ASPDA, we obtained a number of interesting and non-trivial results. First, we show that ASPDA is reducible to ordinary ASP programs. Second, we study reducibility of ASPDA to the non-disjunctive case and show that head-cycle-free ASPDA programs reduce to the non-disjunctive case—similarly to head-cycle-free ASP programs, but through a more complex transformation. We also shed light on the relationship between ASPDA and some of the earlier theories such as Defeasible Logic and LPDA.
Computers in Biology and Medicine

Background: COVID-19 infected millions of people and increased mortality worldwide. Patients with suspected COVID-19 utilised emergency medical services (EMS) and attended emergency departments, resulting in increased pressures and waiting times. Rapid and accurate decision-making is required to identify patients at high-risk of clinical deterioration following COVID-19 infection, whilst also avoiding unnecessary hospital admissions. Our study aimed to develop artificial intelligence models to predict adverse outcomes in suspected COVID-19 patients attended by EMS clinicians. Method: Linked ambulance service data were obtained for 7,549 adult patients with suspected COVID-19 infection attended by EMS clinicians in the Yorkshire and Humber region (England) from 18-03-2020 to 29-06-2020. We used support vector machines (SVM), extreme gradient boosting, artificial neural network (ANN) models, ensemble learning methods and logistic regression to predict the primary outcome (death or need for organ support within 30 days). Models were compared with two baselines: the decision made by EMS clinicians to convey patients to hospital, and the PRIEST clinical severity score. Results: Of the 7,549 patients attended by EMS clinicians, 1,330 (17.6%) experienced the primary outcome. Machine Learning methods showed slight improvements in sensitivity over baseline results. Further improvements were obtained using stacking ensemble methods, the best geometric mean (GM) results were obtained using SVM and ANN as base learners when maximising sensitivity and specificity. Conclusions: These methods could potentially reduce the numbers of patients conveyed to hospital without a concomitant increase in adverse outcomes. Further work is required to test the models externally and develop an automated system for use in clinical settings.
Theory-based Habit Modeling for Enhancing Behavior Prediction

Psychological theories of habit posit that when a strong habit is formed through behavioral repetition, it can trigger behavior automatically in the same environment. Given the reciprocal relationship between habit and behavior, changing lifestyle behaviors (e.g., toothbrushing) is largely a task of breaking old habits and creating new and healthy ones. Thus, representing users' habit strengths can be very useful for behavior change support systems (BCSS), for example, to predict behavior or to decide when an intervention reaches its intended effect. However, habit strength is not directly observable and existing self-report measures are taxing for users. In this paper, built on recent computational models of habit formation, we propose a method to enable intelligent systems to compute habit strength based on observable behavior. The hypothesized advantage of using computed habit strength for behavior prediction was tested using data from two intervention studies, where we trained participants to brush their teeth twice a day for three weeks and monitored their behaviors using accelerometers. Through hierarchical cross-validation, we found that for the task of predicting future brushing behavior, computed habit strength clearly outperformed self-reported habit strength (in both studies) and was also superior to models based on past behavior frequency (in the larger second study). Our findings provide initial support for our theory-based approach of modeling user habits and encourages the use of habit computation to deliver personalized and adaptive interventions.
Non-binary and linear precoded faster-than-Nyquist signaling

—Faster than Nyquist (FTN) signaling is an important method of narrowband coding. The concept is extended here to non binary signal constellations; these are much more bandwidth efﬁcient than binary ones. A powerful method of ﬁnding the minimum distance for binary and non binary FTN is presented. Precoding FTN transmissions with short linear ﬁlters proves to be an effective way to gain distance. A Shannon limit to bit error rate is derived that applies for FTN. Tests of an M-algorithm receiver are performed and compared to this limit.
Hierarchical 2-D mesh representation, tracking, and compression for object-based video

This paper proposes methods for designing, tracking and coding hierarchical two-dimensional (2-D) content-based mesh representations. The design procedure consists of constructing a fine-to-coarse hierarchy of Delaunay meshes, using image- and shape-based criteria for mesh geometry simplification. Hierarchical tracking employs a coarse-to-fine strategy with mesh-based motion vector optimization. We introduce new techniques to maintain the initial mesh hierarchy and topology during tracking by imposing certain constraints at each stage of the procedure. The hierarchical compression technique is based on a nearest neighbor ordering of mesh node points. This ordering serves to identify the mesh boundary nodes as well as establish spatial predictors for differential coding of node coordinates and motion vectors. The proposed hierarchical mesh representation, which has applications in object-based video manipulation, investing, and compression, provides improved tracking performance (compared to a nonhierarchical representation) and allows progressive (scalable) transmission of the object geometry (including shape) and motion information, as well as variable level-of-detail rendering. Experimental results are presented to compare the tracking and compression performance of hierarchical versus nonhierarchical mesh representations and to demonstrate the tradeoff between image quality and mesh bit rate for 2-D mesh-based video object rendering.
Widespread selection and gene flow shape the genomic landscape during a radiation of monkeyflowers

Speciation genomic studies aim to interpret patterns of genome-wide variation in light of the processes that give rise to new species. However, interpreting the genomic “landscape” of speciation is difficult, because many evolutionary processes can impact levels of variation. Facilitated by the first chromosome-level assembly for the group, we use whole-genome sequencing and simulations to shed light on the processes that have shaped the genomic landscape during a radiation of monkeyflowers. After inferring the phylogenetic relationships among the 9 taxa in this radiation, we show that highly similar diversity (π) and differentiation (FST) landscapes have emerged across the group. Variation in these landscapes was strongly predicted by the local density of functional elements and the recombination rate, suggesting that the landscapes have been shaped by widespread natural selection. Using the varying divergence times between pairs of taxa, we show that the correlations between FST and genome features arose almost immediately after a population split and have become stronger over time. Simulations of genomic landscape evolution suggest that background selection (BGS; i.e., selection against deleterious mutations) alone is too subtle to generate the observed patterns, but scenarios that involve positive selection and genetic incompatibilities are plausible alternative explanations. Finally, tests for introgression among these taxa reveal widespread evidence of heterogeneous selection against gene flow during this radiation. Combined with previous evidence for adaptation in this system, we conclude that the correlation in FST among these taxa informs us about the processes contributing to adaptation and speciation during a rapid radiation.
Rubella Virus: First Calcium-Requiring Viral Fusion Protein

Rubella virus (RuV) infection of pregnant women can cause fetal death, miscarriage, or severe fetal malformations, and remains a significant health problem in much of the underdeveloped world. RuV is a small enveloped RNA virus that infects target cells by receptor-mediated endocytosis and low pH-dependent membrane fusion. The structure of the RuV E1 fusion protein was recently solved in its postfusion conformation. RuV E1 is a member of the class II fusion proteins and is structurally related to the alphavirus and flavivirus fusion proteins. Unlike the other known class II fusion proteins, however, RuV E1 contains two fusion loops, with a metal ion complexed between them by the polar residues N88 and D136. Here we demonstrated that RuV infection specifically requires Ca2+ during virus entry. Other tested cations did not substitute. Ca2+ was not required for virus binding to cell surface receptors, endocytic uptake, or formation of the low pH-dependent E1 homotrimer. However, Ca2+ was required for low pH-triggered E1 liposome insertion, virus fusion and infection. Alanine substitution of N88 or D136 was lethal. While the mutant viruses were efficiently assembled and endocytosed by host cells, E1-membrane insertion and fusion were specifically blocked. Together our data indicate that RuV E1 is the first example of a Ca2+-dependent viral fusion protein and has a unique membrane interaction mechanism.
Quantifying within-host diversity of H5N1 influenza viruses in humans and poultry in Cambodia

Avian influenza viruses (AIVs) periodically cross species barriers and infect humans. The likelihood that an AIV will evolve mammalian transmissibility depends on acquiring and selecting mutations during spillover, but data from natural infection is limited. We analyze deep sequencing data from infected humans and domestic ducks in Cambodia to examine how H5N1 viruses evolve during spillover. Overall, viral populations in both species are predominated by low-frequency (<10%) variation shaped by purifying selection and genetic drift, and half of the variants detected within-host are never detected on the H5N1 virus phylogeny. However, we do detect a subset of mutations linked to human receptor binding and replication (PB2 E627K, HA A150V, and HA Q238L) that arose in multiple, independent humans. PB2 E627K and HA A150V were also enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adaptive. Our data show that H5N1 viruses generate putative human-adapting mutations during natural spillover infection, many of which are detected at >5% frequency within-host. However, short infection times, genetic drift, and purifying selection likely restrict their ability to evolve extensively during a single infection. Applying evolutionary methods to sequence data, we reveal a detailed view of H5N1 virus adaptive potential, and develop a foundation for studying host-adaptation in other zoonotic viruses. Author summary H5N1 avian influenza viruses can cross species barriers and cause severe disease in humans. H5N1 viruses currently cannot replicate and transmit efficiently among humans, but animal infection studies and modeling experiments have suggested that human adaptation may require only a few mutations. However, data from natural spillover infection has been limited, posing a challenge for risk assessment. Here, we analyze a unique dataset of deep sequence data from H5N1 virus-infected humans and domestic ducks in Cambodia. We find that well-known markers of human receptor binding and replication arise in multiple, independent humans. We also find that 3 mutations detected within-host are enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adapting. However, we also show that within-host evolution in both humans and ducks are shaped heavily by purifying selection and genetic drift, and that a large fraction of within-host variation is never detected on the H5N1 phylogeny. Taken together, our data show that H5N1 viruses do generate human-adapting mutations during natural infection. However, short infection times, purifying selection, and genetic drift may severely limit how much H5N1 viruses can evolve during the course of a single infection.
Use of care and the oral health status of people aged 60 years and older in France: results from the national health and Disability survey

Objective: We aimed to analyze, from the data in a national survey, the use of oral care and the oral health status of patients living at home or in an institution. Background: Patients aged 60 years and older have important oral health needs, but their oral management may differ according to their immediate environment. The fact of living at home or in an institution can influence the use of care and alter the patients’ perception of their oral health status. Methods: The data analyzed were taken from a survey on disability and health carried out in 2008–2009, which is representative of the population living in France. It consists of two sections, one centered on disability and health among home-dwellers and the other on patients living in an institution. In each of these two populations, we carried out descriptive analysis of three themes: use of care, forgoing of care, and oral health. Results: Although visits to physicians and specialists were frequent, visits to dentists were lower in both populations. While a minority of patients forwent care, it was dental care that was mainly forgone by both home-dwellers and institutionalized patients. The cost factor remained the principal reason, but other factors such as fear or accessibility problems were cited. Use of a dental appliance was considerably more frequent among institutionalized patients than among home-dwellers, with just over half the institutionalized population wearing a dental appliance. Perceived state of oral health remained difficult to interpret. Conclusion: To improve access to oral care for the elderly, the patients, their entourage and health providers need increased awareness and information on the importance of good oral health. Better information must be associated with regular clinical examination.
Exogenous Lipoid Pneumonia in Children: A Systematic Review and Case Series from South Africa

6 CHAPTER 1: INTRODUCTION . 7 1.1 Context . 7 1.1.1 Methodological aspects . 7 1.1.2 Summary . 10 1.2 Ethical Considerations . 13 1.3 Author guidelines for Pediatric Pulmonology. 14 References . 21 CHAPTER 2: PUBLICATION-READY MANUSCRIPT . 23 APPENDICES . 24 Appendix 1: Data Capture Instruments . 24 Appendix 2: Consent and Confidentiality Agreements . 25 Appendix 3: Technical Appendix . 26 Appendix 4: Ethical Approval and Confidentiality Agreements . 27
The impacts of new A8 migration in Leeds

New arrivals from Eastern Europe have made regular headlines in the popular press in recent times, not only for the unprecedented magnitude of the flows involved, but also for their impacts – positive and negative – on regions and localities up and down the country. This paper reports on a recently completed research project aimed at finding out more about A8 migrants in Leeds.