Miracle-dz/UniFAR-FTUs huggingface dataset:
Social Cognition through the Lens of Cognitive and Clinical Neuroscience

Social cognition refers to a set of processes, ranging from perception to decision-making, underlying the ability to decode others' intentions and behaviors to plan actions fitting with social and moral, besides individual and economic considerations. Its centrality in everyday life reflects the neural complexity of social processing and the ubiquity of social cognitive deficits in different pathological conditions. Social cognitive processes can be clustered in three domains associated with (a) perceptual processing of social information such as faces and emotional expressions (social perception), (b) grasping others' cognitive or affective states (social understanding), and (c) planning behaviors taking into consideration others', in addition to one's own, goals (social decision-making). We review these domains from the lens of cognitive neuroscience, i.e., in terms of the brain areas mediating the role of such processes in the ability to make sense of others' behavior and plan socially appropriate actions. The increasing evidence on the “social brain” obtained from healthy young individuals nowadays constitutes the baseline for detecting changes in social cognitive skills associated with physiological aging or pathological conditions. In the latter case, impairments in one or more of the abovementioned domains represent a prominent concern, or even a core facet, of neurological (e.g., acquired brain injury or neurodegenerative diseases), psychiatric (e.g., schizophrenia), and developmental (e.g., autism) disorders. To pave the way for the other papers of this issue, addressing the social cognitive deficits associated with severe acquired brain injury, we will briefly discuss the available evidence on the status of social cognition in normal aging and its breakdown in neurodegenerative disorders. Although the assessment and treatment of such impairments is a relatively novel sector in neurorehabilitation, the evidence summarized here strongly suggests that the development of remediation procedures for social cognitive skills will represent a future field of translational research in clinical neuroscience.
Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells’ ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.
Task-Embedded Control Networks for Few-Shot Imitation Learning

Much like humans, robots should have the ability to leverage knowledge from previously learned tasks in order to learn new tasks quickly in new and unfamiliar environments. Despite this, most robot learning approaches have focused on learning a single task, from scratch, with a limited notion of generalisation, and no way of leveraging the knowledge to learn other tasks more efficiently. One possible solution is meta-learning, but many of the related approaches are limited in their ability to scale to a large number of tasks and to learn further tasks without forgetting previously learned ones. With this in mind, we introduce Task-Embedded Control Networks, which employ ideas from metric learning in order to create a task embedding that can be used by a robot to learn new tasks from one or more demonstrations. In the area of visually-guided manipulation, we present simulation results in which we surpass the performance of a state-of-the-art method when using only visual information from each demonstration. Additionally, we demonstrate that our approach can also be used in conjunction with domain randomisation to train our few-shot learning ability in simulation and then deploy in the real world without any additional training. Once deployed, the robot can learn new tasks from a single real-world demonstration.
Enhanced Pulsatile Growth Hormone Secretion and Altered Metabolic Hormones by in Vivo Hexarelin Treatment in Streptozotocin-Induced Diabetic Rats

Significant growth hormone (GH) reductions have been reported in diabetic animal models with disturbed metabolic balance coinciding with GH deficiency. Therefore, enhanced GH secretion may have beneficial effects in controlling diabetes. Thus, we aim to investigate the effect of hexarelin, a synthetic GH secretagogue (GHS), on GH secretion in streptozotocin (STZ, 65 mg/kg)-induced diabetic rats. Daily hexarelin (100 μg/kg) treatment was performed for two weeks in four-week-long STZ-diabetic and vehicle control rats. Pulsatile GH secretion in STZ-rats was significantly reduced in total, pulsatile, basal, and mass of GH secretion per burst. In addition, impaired GH secretion was followed by an increase in fasting-level free fatty acids (FFAs) and a decrease in insulin-like growth factor 1 (IGF-1) compared to control rats. After hexarelin treatment, pulsatile GH secretion in STZ-rats was significantly increased in total, pulsatile, and basal, but not in the mass GH secretion per burst, compared to STZ-rats without hexarelin treatment. However, there was no significant elevation in GH secretion in the hexarelin-treated control group. In addition, hexarelin-treated STZ-rats showed a significant decrease in fasting level FFAs, whereas suppression of fasting level for IGF-1 was maintained. These results suggest that STZ-induced diabetic rats have impaired pulsatile GH secretion, causing increased FFAs and decreased IGF-1 levels in circulation. Hexarelin injections for two weeks is able to normalize impaired pulsatile GH secretion with normal fasting levels of FFAs, but fails to recover IGF-1 levels.
Is there a "golden" feature set for static warning identification?: an experimental evaluation

Background: The most important challenge regarding the use of static analysis tools (e.g., FindBugs) is that there are a large number of warnings that are not acted on by developers. Many features have been proposed to build classification models for the automatic identification of actionable warnings. Through analyzing these features and related studies, we observe several limitations that make the users lack practical guides to apply these features. Aims: This work aims at conducting a systematic experimental evaluation of all the public available features, and exploring whether there is a golden feature set for actionable warning identification. Method: We first conduct a systematic literature review to collect all public available features for warning identification. We employ 12 projects with totally 60 revisions as our subject projects. We then implement a tool to extract the values of all features for each project revision to prepare the experimental data. Results: Experimental evaluation on 116 collected features demonstrates that there is a common set of features (23 features) which take effect in warning identification for most project revisions. These features can achieve satisfied performance with far less time cost for warning identification. Conclusions: These commonly-selected features can be treated as the golden feature set for identifying actionable warnings. This finding can serve as a practical guideline for facilitating real-world warning identification.
Do the Low WHRs and BMIs Judged Most Attractive Indicate Better Health?

It is widely claimed that in well-nourished populations, very low female waist–hip ratios (WHRs) together with low body mass indices (BMIs) are judged attractive by men because these features reliably indicate superior health and fertility. However, studies show that mortality rates are higher in women with low BMIs than in women with average BMIs and are inversely related to BMI in subsistence populations. Measures of current health in women of reproductive age have not been similarly studied. We analyze large U.S. samples of reproductive-age women and show that controlling for other factors known to affect health, those with low BMIs (<20), WHRs, or waist/stature ratios did not have better health than those with values in the middle range, and there was no relationship between subsequent health outcomes and BMI in early adulthood. Lower self-reported BMIs were linked to poorer health and an increased risk of infection. However, based on recent U.S. natality data, primiparas with lower BMIs had a lower risk of an operative delivery and of gestational hypertension. Beyond these two parity-restricted effects, relevant studies and new tests fail to support the view that women with the very low BMIs and WHRs consistently judged attractive are generally healthier than women with average values; significant correlations were consistently in the opposite direction.
School of Informatics, University of Edinburgh

In this brief technical report we introduce the CINIC-10 dataset as a plug-in extended alternative for CIFAR-10. It was compiled by combining CIFAR-10 with images selected and downsampled from the ImageNet database. We present the approach to compiling the dataset, illustrate the example images for different classes, give pixel distributions for each part of the repository, and give some standard benchmarks for well known models. Details for download, usage, and compilation can be found in the associated github repository. 1 .
Effect of zinc oxide sources and dosages on gut microbiota and integrity of weaned piglets

Zinc oxide (ZnO) supplied at pharmacological dosage in diets of weaned piglets improves growth performance. However, it causes environmental contamination and induces bacterial antibiotic resistance, yet this practice is debated. The effects on gut microbiota and integrity in weaned piglets of conventional ZnO at nutritional and pharmacological dosage (110 and 2,400 mg/kg Zn, respectively) were compared to an alternative ZnO source at 110 and 220 mg/kg Zn. Each of the four treatments was applied to four pens (two piglets/pen; weaning age, 20 days) for 15 days, and piglets were sampled on day 15 to determine indices of gut integrity. Feeding conventional ZnO at 2,400 mg/kg Zn reduced coliforms and Escherichia coli in distal small intestine as compared to conventional ZnO at 110 mg/kg (-1.7 and -1.4 log10 cfu/g, respectively), whereas the alternative ZnO reduced only coliforms, irrespective of dosage (-1.6 to -1.7 log10 cfu/g). Transepithelial electrical resistance of distal small intestinal mucosa was higher for pigs fed the alternative ZnO source as compared with groups fed 110 mg/kg Zn of conventional ZnO, in line with a trend for higher gene expression of claudin-1 and zona occludens-1. Interestingly, the alternative ZnO source at 110 and 220 mg/kg Zn increased intestinal alkaline phosphatase gene transcript as compared to conventional ZnO at 110 mg/kg Zn, whereas the alternative ZnO source at 110 mg/kg Zn exhibited higher Zn concentrations in mucosa (2,520 μg/g) as compared to conventional ZnO at 110 mg/kg Zn (1,211 μg/g). However, assessing alkaline phosphatase activity, no significant effects were found. In conclusion, the alternative ZnO reduced digesta Enterobacteriaceae numbers and improved gut integrity, albeit similar or better, depending on the dosage, to the effects of pharmacological dosage of conventional ZnO.
Quantifying how constraints limit the diversity of viable routes to adaptation

Convergent adaptation can occur at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures. These patterns provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution. A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis. Here, we formulate a novel metric to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution, and then generalize this for simultaneous analysis of multiple lineages. This metric is explicitly based on the probability of observing a given amount of repeatability by chance under an arbitrary null hypothesis, and is readily compared among different species and types of trait. We also formulate a metric to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation. As an example of how these metrics can be used to draw inferences, we assess the amount of repeatability observed in existing datasets on adaptation to antibiotics in yeast and climate in conifers. This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution.
Proximal Online Gradient Is Optimum for Dynamic Regret: A General Lower Bound

In online learning, the dynamic regret metric chooses the reference oracle that may change over time, while the typical (static) regret metric assumes the reference solution to be constant over the whole time horizon. The dynamic regret metric is particularly interesting for applications, such as online recommendation (since the customers’ preference always evolves over time). While the online gradient (OG) method has been shown to be optimal for the static regret metric, the optimal algorithm for the dynamic regret remains unknown. In this article, we show that proximal OG (a general version of OG) is optimum to the dynamic regret by showing that the proved lower bound matches the upper bound. It is highlighted that we provide a new and general lower bound of dynamic regret. It provides new understanding about the difficulty to follow the dynamics in the online setting.
“Neither a wife nor a widow”: an interpretative phenomenological analysis of the experiences of female family caregivers in disorders of consciousness

ABSTRACT Disorders of consciousness (DoC) disrupt close relationships. This study investigated the experience of a DoC in the family. Four main themes were identified from semi-structured interviews with nine females and analysed using Interpretative Phenomenological Analysis (IPA): (1) Loss without a name, (2) Relationship without a title, (3) Symbiotic relating and (4) Frozen futures. Participants’ accounts showed complex losses and relationship transformations that were challenging to cope with. Participants embodied the person and experienced reductions in rehabilitation and social visits as personally abandoning and led to strong advocacy with professionals. The uncertainty created by the DoC meant participants lived in the present moment and struggled to make plans for their future. Psychological support to demonstrate a sensitivity and validation of this unique complex loss, a framework for naming the loss, provision of education about the condition and enhancing coping with a chronic situation are needed.
Transcriptome Sequencing Reveals the Differentially Expressed lncRNAs and mRNAs Involved in Cryoinjuries in Frozen-Thawed Giant Panda (Ailuropoda melanoleuca) Sperm

Sperm cryopreservation and artificial insemination are important methods for giant panda breeding and preservation of extant genetic diversity. Lower conception rates limit the use of artificial insemination with frozen-thawed giant panda sperm, due to the lack of understanding of the cryodamaging or cryoinjuring mechanisms in cryopreservation. Long non-coding RNAs (lncRNAs) are involved in regulating spermatogenesis. However, their roles during cryopreservation remain largely unexplored. Therefore, this study aimed to identify differentially expressed lncRNAs and mRNAs associated with cryodamage or freeze tolerance in frozen-thawed sperm through high throughput sequencing. A total of 61.05 Gb clean reads and 22,774 lncRNA transcripts were obtained. From the sequencing results, 1477 significantly up-regulated and 1,396 significantly down-regulated lncRNA transcripts from fresh and frozen-thawed sperm of giant panda were identified. GO and KEGG showed that the significantly dysregulated lncRNAs and mRNAs were mainly involved in regulating responses to cold stress and apoptosis, such as the integral component of membrane, calcium transport, and various signaling pathways including PI3K-Akt, p53 and cAMP. Our work is the first systematic profiling of lncRNA and mRNA in fresh and frozen-thawed giant panda sperm, and provides valuableinsights into the potential mechanism of cryodamage in sperm.
Low Praziquantel Treatment Coverage for Schistosoma mansoni in Mayuge District, Uganda, Due to the Absence of Treatment Opportunities, Rather Than Systematic Non-Compliance

The World Health Organization (WHO) recommends praziquantel mass drug administration (MDA) to control schistosomiasis in endemic regions. We aimed to quantify recent and lifetime praziquantel coverage, and reasons for non-treatment, at an individual level to guide policy recommendations to help Uganda reach WHO goals. Cross-sectional household surveys (n = 681) encompassing 3208 individuals (adults and children) were conducted in 2017 in Bugoto A and B, Mayuge District, Uganda. Participants were asked if they had received praziquantel during the recent MDA (October 2016) and whether they had ever received praziquantel in their lifetime. A multivariate logistic regression analysis with socio-economic and individual characteristics as covariates was used to determine factors associated with praziquantel uptake. In the MDA eligible population (≥5 years of age), the most recent MDA coverage was 48.8%. Across individuals’ lifetimes, 31.8% of eligible and 49.5% of the entire population reported having never taken praziquantel. Factors that improved individuals’ odds of taking praziquantel included school enrolment, residence in Bugoto B and increasing years of village-residency. Not being offered (49.2%) and being away during treatment (21.4%) were the most frequent reasons for not taking the 2016 praziquantel MDA. Contrary to expectations, chronically-untreated individuals were rarely systematic non-compliers, but more commonly not offered treatment.
Recommending Scientific Papers: The Role of Citation Contexts

This paper addresses the problem of building recommender systems for scientific papers based on the linguistic and contextual analysis of citation contexts. We explain the importance of taking into consideration citation contexts and the different methodologies that exist as well as the ways that citations impact recommender systems. We also discuss the limits of using citation contexts to generate recommendations.
Anytime Stochastic Gradient Descent: A Time to Hear from all the Workers

In this paper, we focus on approaches to parallelizing stochastic gradient descent (SGD) wherein data is farmed out to a set of workers, the results of which, after a number of updates, are then combined at a central master node. Although such synchronized SGD approaches parallelize well in idealized computing environments, they often fail to realize their promised computational acceleration in practical settings. One cause is slow workers, termed stragglers, who can cause the fusion step at the master node to stall, which greatly slowing convergence. In many straggler mitigation approaches work completed by these nodes, while only partial, is discarded completely. In this paper, we propose an approach to parallelizing synchronous SGD that exploits the work completed by all workers. The central idea is to fix the computation time of each worker and then to combine distinct contributions of all workers. We provide a convergence analysis and optimize the combination function. Our numerical results demonstrate an improvement of several factors of magnitude in comparison to existing methods.
Effects of Constructivist and Transmission Instructional Models on Mathematics Achievement in Mainland China: A Meta-Analysis

The innovation of teaching and learning methods has been a common theme among these meta-analyses in the field of mathematics education. However, no published study has reviewed the effects of teaching models on mathematics achievement in mainland China. This review is intended to examine effects of constructivist instructional models and improved transmission instructional models on mathematics performance in mainland China. Using rigorous inclusion criteria, we identified 89 studies for constructivist instruction and 25 studies for improved transmission instruction in grades 1–12. Compared with traditional transmission instruction, the weighted mean effect sizes of constructivist instruction and improved transmission instruction were +0.55 and +0.63, respectively. These two effect sizes were not significantly different. Of the included studies, inquiry-based learning (N = 26, d = +0.52), problem-based learning (N = 21, d = +0.58), cooperative learning (N = 14, d = +0.67), autonomous learning (N = 8, d = +0.43), and script-based learning (N = 12, d = +0.47) were frequently used constructivist models, and grouping teaching (N = 10, d = +0.57) and variation teaching (N = 7, d = +0.49) were frequently used improved transmission models. All seven models had significant effects on improving mathematics achievement. Our findings implicate that the traditional transmission teaching model needs to be changed in mainland China but the constructivist model is not the only promising approach. The impact of study features and the limitations of this review were also discussed.
Comprehensive characterisation of the heterogeneity of adalimumab via charge variant analysis hyphenated on-line to native high resolution Orbitrap mass spectrometry

ABSTRACT Charge variant analysis is a widely used tool to monitor changes in product quality during the manufacturing process of monoclonal antibodies (mAbs). Although it is a powerful technique for revealing mAb heterogeneity, an unexpected outcome, for example the appearance of previously undetected isoforms, requires further, time-consuming analysis. The process of identifying these unknowns can also result in unwanted changes to the molecule that are not attributable to the manufacturing process. To overcome this, we recently reported a method combining highly selective cation exchange chromatography-based charge variant analysis with on-line mass spectrometric (MS) detection. We further explored and adapted the chromatographic buffer system to expand the application range. Moreover, we observed no salt adducts on the native protein, also supported by the optimal choice of MS parameters, resulting in increased data quality and mass accuracy. Here, we demonstrate the utility of this improved method by performing an in-depth analysis of adalimumab before and after forced degradation. By combining molecular mass and retention time information, we were able to identify multiple modifications on adalimumab, including lysine truncation, glycation, deamidation, succinimide formation, isomerisation, N-terminal aspartic acid loss or C-terminal proline amidation and fragmentation along with the N-glycan distribution of each of these identified proteoforms. Host cell protein (HCP) analysis was performed using liquid chromatography-mass spectrometry that verified the presence of the protease Cathepsin L. Based on the presence of trace HCPs with catalytic activity, it can be questioned if fragmentation is solely driven by spontaneous hydrolysis or possibly also by enzymatic degradation.