Miracle-dz/UniFAR-FTUs huggingface dataset:
Tchebycheff Procedure for Multi-task Text Classification

Multi-task Learning methods have achieved great progress in text classification. However, existing methods assume that multi-task text classification problems are convex multiobjective optimization problems, which is unrealistic in real-world applications. To address this issue, this paper presents a novel Tchebycheff procedure to optimize the multi-task classification problems without convex assumption. The extensive experiments back up our theoretical analysis and validate the superiority of our proposals.
Gene therapy targeting the inner retina rescues the retinal phenotype in a mouse model of CLN3 Batten disease.

The neuronal ceroid lipofuscinoses (NCLs), often referred to as Batten disease, are inherited lysosomal storage disorders that represent the most common neurodegeneration during childhood. Symptoms include seizures, vision loss, motor and cognitive decline and premature death. The development of brain-directed treatments for NCLs has made noteworthy progress in recent years. Clinical trials are currently ongoing or planned for different forms of the disease. Despite these promising advances, it is unlikely that therapeutic interventions targeting the brain will prevent loss of vision in patients as retinal cells remain untreated and will continue to degenerate. Here, we demonstrate that Cln3Δex7/8 mice, a mouse model of CLN3 Batten disease with juvenile onset, suffer from a decline in inner retinal function resulting from the death of rod bipolar cells, interneurons vital for signal transmission from photoreceptors to ganglion cells in the retina. We also show that this ocular phenotype can be treated by adeno-associated virus (AAV)-mediated expression of CLN3 in cells of the inner retina, leading to significant survival of bipolar cells and preserved retinal function. In contrast, the treatment of photoreceptors, which are lost in patients at late disease stages, was not therapeutic in Cln3Δex7/8 mice, underlining the notion that CLN3 disease is primarily a disease of the inner retina with secondary changes in the outer retina. These data indicate that bipolar cells play a central role in this disease and identify this cell type as an important target for ocular AAV-based gene therapies for CLN3 disease.
Learning Source Phrase Representations for Neural Machine Translation

The Transformer translation model (Vaswani et al., 2017) based on a multi-head attention mechanism can be computed effectively in parallel and has significantly pushed forward the performance of Neural Machine Translation (NMT). Though intuitively the attentional network can connect distant words via shorter network paths than RNNs, empirical analysis demonstrates that it still has difficulty in fully capturing long-distance dependencies (Tang et al., 2018). Considering that modeling phrases instead of words has significantly improved the Statistical Machine Translation (SMT) approach through the use of larger translation blocks (“phrases”) and its reordering ability, modeling NMT at phrase level is an intuitive proposal to help the model capture long-distance relationships. In this paper, we first propose an attentive phrase representation generation mechanism which is able to generate phrase representations from corresponding token representations. In addition, we incorporate the generated phrase representations into the Transformer translation model to enhance its ability to capture long-distance relationships. In our experiments, we obtain significant improvements on the WMT 14 English-German and English-French tasks on top of the strong Transformer baseline, which shows the effectiveness of our approach. Our approach helps Transformer Base models perform at the level of Transformer Big models, and even significantly better for long sentences, but with substantially fewer parameters and training steps. The fact that phrase representations help even in the big setting further supports our conjecture that they make a valuable contribution to long-distance relations.
HyperCore: Hyperbolic and Co-graph Representation for Automatic ICD Coding

The International Classification of Diseases (ICD) provides a standardized way for classifying diseases, which endows each disease with a unique code. ICD coding aims to assign proper ICD codes to a medical record. Since manual coding is very laborious and prone to errors, many methods have been proposed for the automatic ICD coding task. However, most of existing methods independently predict each code, ignoring two important characteristics: Code Hierarchy and Code Co-occurrence. In this paper, we propose a Hyperbolic and Co-graph Representation method (HyperCore) to address the above problem. Specifically, we propose a hyperbolic representation method to leverage the code hierarchy. Moreover, we propose a graph convolutional network to utilize the code co-occurrence. Experimental results on two widely used datasets demonstrate that our proposed model outperforms previous state-of-the-art methods.
Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks

Efficient structure encoding for graphs with labeled edges is an important yet challenging point in many graph-based models. This work focuses on AMR-to-text generation – A graph-to-sequence task aiming to recover natural language from Abstract Meaning Representations (AMR). Existing graph-to-sequence approaches generally utilize graph neural networks as their encoders, which have two limitations: 1) The message propagation process in AMR graphs is only guided by the first-order adjacency information. 2) The relationships between labeled edges are not fully considered. In this work, we propose a novel graph encoding framework which can effectively explore the edge relations. We also adopt graph attention networks with higher-order neighborhood information to encode the rich structure in AMR graphs. Experiment results show that our approach obtains new state-of-the-art performance on English AMR benchmark datasets. The ablation analyses also demonstrate that both edge relations and higher-order information are beneficial to graph-to-sequence modeling.
Validation and implications of a growth model for brown trout, Salmo trutta, using long‐term data from a small stream in north‐west England

Summary 1. The objectives were: (i) to check the validity of a new growth model; (ii) to examine the relationship between population density and both mean mass and mean growth rate and (iii) to discover if compensatory growth occurred. First (0+) and second (1+) year-old juvenile sea-trout were sampled by electrofishing at the beginning and end of the summer from 1967 to 2000. Additional samples were taken in some years in winter and in the critical period for survival when the fry first emerge from the gravel. The trout left the stream as pre-smolts in May, soon after their second birthday. 2. A growth model (Elliott, Hurley & Fryer, 1995) estimated the mean mass of the trout over the 2 years spent in fresh water. The date and mean mass at the start of the growth period were defined as the median date for fry emerging from the gravel and their mean mass at emergence, both being estimated from individual-based models (Elliott & Hurley, 1998a, b). 3. The variation in mean mass among year-classes was small for newly-emerged fry (CV = 6.2%), maximum at the start of the first summer of the life cycle (CV = 38.1%), and then decreased gradually for successive life-stages to a low value for pre-smolts (CV = 10.8%). Mean mass was not related to population density and, therefore, mean growth rate was density-independent. Growth in the first, but not the second, winter of the life cycle was lower than model prediction, but when it was assumed in the model that there was no first-winter growth, there was good agreement in most year-classes between model estimated values and observed mean mass. Exceptions were that mean masses and growth rates for 0+ trout after four summer droughts were lower than expected, but compensatory growth followed, so that observed and expected masses were similar for 1+ trout. 4. Pre-smolt mean mass on 30 April measured total growth achieved in the freshwater phase of the life cycle. This was significantly related to mean mass at the end of the first and second summers of the life cycle, but not to the emergence date and mean mass of emerging fry. 5. These juvenile sea-trout were growing at their maximum potential in most year-classes but when this was not achieved, compensatory growth soon restored their mass to values expected from the model. This ensured a low variation in the mean mass of pre-smolts just before they migrated to the sea. However, the latter mass was higher in more recent year-classes (1987–98) than in previous ones (1967–86), demonstrating the effect of slightly higher stream temperature. This study has shown the importance of developing realistic growth models in order to detect departure from maximum potential growth, and the more subtle effects of temperature change, possibly due to the effects of climate change.
Statistical Mechanics of Non-Muscle Myosin IIA in Human Bone Marrow-Derived Mesenchymal Stromal Cells Seeded in a Collagen Scaffold: A Thermodynamic Near-Equilibrium Linear System Modified by the Tripeptide Arg-Gly-Asp (RGD)

Mesenchymal stromal cells (MSCs) were obtained from human bone marrow and amplified in cultures supplemented with human platelet lysate. Once semi-confluent, cells were seeded in solid collagen scaffolds that were rapidly colonized by the cells generating a 3D cell scaffold. Here, they acquired a myofibroblast phenotype and when exposed to appropriate chemical stimulus, developed tension and cell shortening, similar to those of striated and smooth muscle cells. Myofibroblasts contained a molecular motor—the non-muscle myosin type IIA (NMMIIA) whose crossbridge (CB) kinetics are dramatically slow compared with striated and smooth muscle myosins. Huxley’s equations were used to determine the molecular mechanical properties of NMMIIA. Thank to the great number of NMMIIA molecules, we determined the statistical mechanics (SM) of MSCs, using the grand canonical ensemble which made it possible to calculate various thermodynamic entities such as the chemical affinity, statistical entropy, internal energy, thermodynamic flow, thermodynamic force, and entropy production rate. The linear relationship observed between the thermodynamic force and the thermodynamic flow allowed to establish that MSC-laden in collagen scaffolds were in a near-equilibrium stationary state (affinity ≪ RT), MSCs were also seeded in solid collagen scaffolds functionalized with the tripeptide Arg-Gly-Asp (RGD). This induced major changes in NMMIIA SM particularly by increasing the rate of entropy production. In conclusion, collagen scaffolds laden with MSCs can be viewed as a non-muscle contractile bioengineered tissue operating in a near-equilibrium linear regime, whose SM could be substantially modified by the RGD peptide.
Breath tests for gastrointestinal diseases - will it be safe to conduct breath tests after the COVID-19 pandemic?

Breath tests are simple, noninvasive alternatives, which are considered harmless for the diagnosis of Helicobacter pylori (H. pylori) infection, small intestinal bacterial overgrowth (SIBO), lactose intolerance (), and inflammatory bowel disease (). In Brazil, the acquisition of 13C-urea from abroad is challenging; however, with the support of the Division of Pharmacy, 13C-urea breath tests were routinely performed in clinical practice (). Patients using anticoagulant drugs, with low platelets count, cardiac impairment that contraindicates endoscopy, or those who did not want [. ]
Merit of an Ursodeoxycholic Acid Clinical Trial in COVID-19 Patients

Corona Virus Disease 2019 (COVID-19) has affected over 8 million people worldwide. We underscore the potential benefits of conducting a randomized open-label unblinded clinical trial to evaluate the role of ursodeoxycholic acid (UDCA) in the treatment of COVID-19. Some COVID-19 patients are characterized with cytokine storm syndrome that can cause severe and irreversible damage to organs leading to multi-organ failure and death. Therefore, it is critical to control both programmed cell death (apoptosis) and the hyper-immune inflammatory response in COVID-19 patients to reduce the rising morbidity and mortality. UDCA is an existing drug with proven safety profiles that can reduce inflammation and prevent cell death. National Geographic reported that, “China Promotes Bear Bile as Coronavirus Treatment”. Bear bile is rich in UDCA, comprising up to 40–50% of the total bile acid. UDCA is a logical and attainable replacement for bear bile that is available in pill form and merits clinical trial consideration.
Sub-Daily Exposure to Fine Particulate Matter and Ambulance Dispatches during Wildfire Seasons: A Case-Crossover Study in British Columbia, Canada

Background: Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d. Objectives: We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia. Methods: We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD). Results: Increased respiratory health outcomes were observed within 1 h of exposure to a 10-μg/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively. Conclusions: We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792
Turning Spent Coffee Grounds into Sustainable Precursors for the Fabrication of Carbon Dots

Spent coffee grounds (SCGs) are known for containing many organic compounds of interest, including carbohydrates, lipids, phenolic compounds and proteins. Therefore, we investigated them as a potential source to obtain carbon dots (CDs) via a nanotechnology approach. Herein, a comparison was performed between CDs produced by SCGs and classic precursors (e.g., citric acid and urea). The SCG-based CDs were obtained via the one-pot and solvent-free carbonization of solid samples, generating nanosized particles (2.1–3.9 nm). These nanoparticles exhibited a blue fluorescence with moderate quantum yields (2.9–5.8%) and an excitation-dependent emission characteristic of carbon dots. SCG-based CDs showed potential as environmentally relevant fluorescent probes for Fe3+ in water. More importantly, life cycle assessment studies validated the production of CDs from SCG samples as a more environmentally sustainable route, as compared to those using classic reported precursors, when considering either a weight- or a function-based functional unit.
Genetic analysis of uniparental and autosomal markers in human populations

The main objectives of this thesis are to describe the distribution of genetic diversity in modern human populations and the distribution across subpopulations, with emphasis on the populations of Africa and Europe, with a special focus on Cameroon, West and Central Africa, and Italy, respectively, and also, of. inferring prehistoric and historical events that determined the observed diversity and structure in contemporary populations. Most of the genome is biparentally inherited and recombines. However, two particular segments of the DNA are inherited from one parent only and do not recombine: the mtDNA and, for the most of its length, the Y chromosome.In this work, samples from Europe and Africa have been analyzed for Y chromosome, mtDNA and autosomal markers. The characterization of the distribution of genetic variation within different populations in different regions of the world, allows us to investigate the genetic affinities, or even phylogenetic proximity, within and between populations. The study of how genetic variability distributes among and within populations is a key aspect for association studies in disease studies, as well as for forensic genetic purposes. In this latter case, the study of genetic variability is essential for individual identification through a genetic 'fingerprint', i.e. a set of markers can be so variable that the observed allelic combination are nearly individual specific. The process of inference, based on models of population genetics, is strongly motivated by anthropological interest in the history of our species, their origins, movements and population development. Also forensic genetics, the science that combines population genetics and forensic medicine, is using the genetic variability of humans. In this case we have two main applications: 1) the individual identification in criminal cases and 2) the identification of two close relatives. The genetic makeup of an individual cannot be considered in isolation, but has to be related to the degree and structure of genetic variation present in the population to which that individual belongs. The employed methods of DNA typing, in fact, cannot guarantee that the given genotype is unique and that there is no other person carrying the same markers. Because of this, probabilities are computed: e.g., the probability that a person has left a biological sample in the criminal scene, or the probability that the presumed father is the biological father of a child. Estimating the probabilities is based on knowing the genotype frequencies of the population, to which the people involved in the case, belong.
Racial Inequality in Psychological Research: Trends of the Past and Recommendations for the Future

Race plays an important role in how people think, develop, and behave. In the current article, we queried more than 26,000 empirical articles published between 1974 and 2018 in top-tier cognitive, developmental, and social psychology journals to document how often psychological research acknowledges this reality and to examine whether people who edit, write, and participate in the research are systematically connected. We note several findings. First, across the past five decades, psychological publications that highlight race have been rare, and although they have increased in developmental and social psychology, they have remained virtually nonexistent in cognitive psychology. Second, most publications have been edited by White editors, under which there have been significantly fewer publications that highlight race. Third, many of the publications that highlight race have been written by White authors who employed significantly fewer participants of color. In many cases, we document variation as a function of area and decade. We argue that systemic inequality exists within psychological research and that systemic changes are needed to ensure that psychological research benefits from diversity in editing, writing, and participation. To this end, and in the spirit of the field’s recent emphasis on metascience, we offer recommendations for journals and authors.
Visualization strategies for regression estimates with randomization inference

Coefficient plots are a popular tool for visualizing regression estimates. The appeal of these plots is that they visualize confidence intervals around the estimates and generally center the plot around zero, meaning that any estimate that crosses zero is statistically nonsignificant at least at the alpha level around which the confidence intervals are constructed. For models with statistical significance levels determined via randomization models of inference and for which there is no standard error or confidence intervals for the estimate itself, these plots appear less useful. In this article, I illustrate a variant of the coefficient plot for regression models with p-values constructed using permutation tests. These visualizations plot each estimate’s p-value and its associated confidence interval in relation to a specified alpha level. These plots can help the analyst interpret and report the statistical and substantive significances of their models. I illustrate using a nonprobability sample of activists and participants at a 1962 anticommunism school.
Innovations, challenges, and minimal information for standardization of humanized mice

Mice xenotransplanted with human cells and/or expressing human gene products (also known as “humanized mice”) recapitulate the human evolutionary specialization and diversity of genotypic and phenotypic traits. These models can provide a relevant in vivo context for understanding of human‐specific physiology and pathologies. Humanized mice have advanced toward mainstream preclinical models and are now at the forefront of biomedical research. Here, we considered innovations and challenges regarding the reconstitution of human immunity and human tissues, modeling of human infections and cancer, and the use of humanized mice for testing drugs or regenerative therapy products. As the number of publications exploring different facets of humanized mouse models has steadily increased in past years, it is becoming evident that standardized reporting is needed in the field. Therefore, an international community‐driven resource called “Minimal Information for Standardization of Humanized Mice” (MISHUM) has been created for the purpose of enhancing rigor and reproducibility of studies in the field. Within MISHUM, we propose comprehensive guidelines for reporting critical information generated using humanized mice.