Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning ODE Models with Qualitative Structure Using Gaussian Processes

Recently there has been increasing interest in the use of learning techniques to model dynamical systems directly from data for scientific and engineering applications. However, in many contexts explicit data collection is expensive and learning algorithms must be data-efficient to be practicable. This suggests using additional qualitative information about the system, which is often available from prior experiments or domain-specific knowledge. We propose an approach to learning a vector field of differential equations using sparse Gaussian Processes that allows us to combine data and additional structural information, like Lie Group symmetries and fixed points. We show that this combination improves extrapolation and long-term behaviour, and reduces computational cost.
Intentonomy: a Dataset and Study towards Human Intent Understanding

An image is worth a thousand words, conveying information that goes beyond the mere visual content therein. In this paper, we study the intent behind social media images with an aim to analyze how visual information can facilitate recognition of human intent. Towards this goal, we introduce an intent dataset, Intentonomy, comprising 14K images covering a wide range of everyday scenes. These images are manually annotated with 28 intent categories derived from a social psychology taxonomy. We then systematically study whether, and to what extent, commonly used visual information, i.e., object and context, contribute to human motive understanding. Based on our findings, we conduct further study to quantify the effect of attending to object and context classes as well as textual information in the form of hashtags when training an intent classifier. Our results quantitatively and qualitatively shed light on how visual and textual information can produce observable effects when predicting intent.1
A Distributed Algorithm for Overlapped Community Detection in Large-Scale Networks

Overlapped community detection in social networks has become an important research area with the increasing popularity and complexity of the networks. Most of the existing solutions are either centralized or parallel algorithms, which are computationally intensive - require complete knowledge of the entire network. But it isn’t easy to collect entire network data because the size of the actual network may be prohibitively large. It may result from either privacy concerns (users of a social network may be unwilling to reveal their social links) or technological impediments (implementation of an efficient web crawler). Performing in-network computation solves both problems utilizing the computational capability of the individual nodes of the network. Simultaneously, nodes communicate and share data with their neighbours via message passing, which may go a long way toward mitigating individual nodes’ privacy concerns in the network.All the concerns mentioned above motivated us to design a decentralized or distributed technique to detect overlapped communities in a large-scale network. It is desirable because this technique does not offer a single point of failure, and the system as a whole can continue to function even when many of the nodes fail. To overcome the disadvantages of the existing solutions, in this paper, we address the overlapped community detection problem for large-scale networks. We present an efficient distributed algorithm, named DOCD, to identify the overlapped communities in the network. The efficiency of DOCD algorithm is verified with extensive simulation study on some networks such as, Dolphin, Zachary karate club, Football club, and Facebook ego networks. We show that DOCD algorithm is capable of keeping the asymptotically same results with the existing classical centralized algorithms [1]–[5] in terms of community modularity and the number of identified communities. The DOCD algorithm can also efficiently identify the overlapped nodes and overlapped communities with a small number of rounds of communication and computation.
Organizational Ambidexterity in Family-Managed Firms: The Role of Family Involvement in Top Management

Organizational ambidexterity is vital for family firms’ long-term success, yet we still lack sufficient insights into the role of family involvement in top management in this context. Building on research on family firm innovation and diversity, we argue there are curvilinear relationships between family involvement in top management and exploration, exploitation, and organizational ambidexterity. We further propose that these (inverse) U-shaped relationships are affected by family CEOs’ family-centered noneconomic goals. Multisource data on 109 family-managed firms support most of our hypotheses and provide a nuanced understanding of how diversity within top management affects family firms’ innovative behavior.
Plasma neurofilament light predicts mortality in patients with stroke

Plasma neurofilament light is a reliable, uniform marker to estimate neuroaxonal injury and forecast all-cause mortality across major stroke types. Circulating marker of brain damage The outcome of a stroke varies greatly between patients from temporary mild symptoms to permanent disability and death. Clinical scale for measuring disease severity shows poor correlation with brain tissue damage. Identification of better markers of tissue damage could improve the ability to predict outcome and promote the development of better therapies. Now, Gendron et al. showed that the expression of circulating neurofilament light (NFL) was increased in multiple cohorts of patients with stroke compared to controls and correlated with brain tissue damage. In addition, blood concentration of NFL correlated with functional outcome and mortality. The results suggest that blood NFL might be used as prognostic marker after stroke. Given the heterogeneity of stroke brain injury, there is a clear need for a biomarker that determines the degree of neuroaxonal injury across stroke types. We evaluated whether blood neurofilament light (NFL) would fulfill this purpose for patients with acute cerebral infarction (ACI; N = 227), aneurysmal subarachnoid hemorrhage (aSAH; N = 58), or nontraumatic intracerebral hemorrhage (ICH; N = 29). We additionally validated our findings in two independent cohorts of patients with ICH (N = 96 and N = 54) given the scarcity of blood biomarker studies for this deadliest stroke type. Compared to healthy individuals (N = 79 and N = 48 for the discovery and validation cohorts, respectively), NFL was higher for all stroke types. NFL associated with radiographic markers of brain tissue damage. It correlated with the extent of early ischemic injury in patients with ACI, hemorrhage severity in patients with aSAH, and intracranial hemorrhage volume in patients with ICH. In all patients, NFL independently correlated with scores from the NIH Stroke Scale, the modified Rankin Scale, and the Mini-Mental State Examination at blood draw, which respectively assess neurological, functional, and cognitive status. Furthermore, higher NFL concentrations independently associated with 3- or 6-month functional disability and higher all-cause mortality. These data support NFL as a uniform method to estimate neuroaxonal injury and forecast mortality regardless of stroke mechanism. As a prognostic biomarker, blood NFL has the potential to assist with planning supportive and rehabilitation services and improving clinical trial efficiency for stroke therapeutics and devices.
Protocol for the Prognostication of Consciousness Recovery Following a Brain Injury

Individuals who have suffered a severe brain injury typically require extensive hospitalization in intensive care units (ICUs), where critical treatment decisions are made to maximize their likelihood of recovering consciousness and cognitive function. These treatment decisions can be difficult when the neurological assessment of the patient is limited by unreliable behavioral responses. Reliable objective and quantifiable markers are lacking and there is both (1) a poor understanding of the mechanisms underlying the brain’s ability to reconstitute consciousness and cognition after an injury and (2) the absence of a reliable and clinically feasible method of tracking cognitive recovery in ICU survivors. Our goal is to develop and validate a clinically relevant EEG paradigm that can inform the prognosis of unresponsive, brain-injured patients in the ICU. This protocol describes a study to develop a point-of-care system intended to accurately predict outcomes of unresponsive, brain-injured patients in the ICU. We will recruit 200 continuously-sedated brain-injured patients across five ICUs. Between 24 h and 7 days post-ICU admission, high-density EEG will be recorded from behaviorally unresponsive patients before, during and after a brief cessation of pharmacological sedation. Once patients have reached the waking stage, they will be asked to complete an abridged Cambridge Brain Sciences battery, a web-based series of neurocognitive tests. The test series will be repeated every day during acute admission (ICU, ward), or as often as possible given the constraints of ICU and ward care. Following discharge, patients will continue to complete the same test series on weekly, and then monthly basis, for up to 12 months following injury. Functional outcomes will also be assessed up to 12 months post-injury. We anticipate our findings will lead to an increased ability to identify patients, as soon as possible after their brain injury, who are most likely to survive, and to make accurate predictions about their long-term cognitive and functional outcome. In addition to providing critically needed support for clinical decision-making, this study has the potential to transform our understanding of key functional EEG networks associated with consciousness and cognition.
Senescence in Pulmonary Fibrosis: Between Aging and Exposure

To date, chronic pulmonary pathologies represent the third leading cause of death in the elderly population. Evidence-based projections suggest that >65 (years old) individuals will account for approximately a quarter of the world population before the turn of the century. Genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication, are described as the nine “hallmarks” that govern cellular fitness. Any deviation from the normal pattern initiates a complex cascade of events culminating to a disease state. This blueprint, originally employed to describe aberrant changes in cancer cells, can be also used to describe aging and fibrosis. Pulmonary fibrosis (PF) is the result of a progressive decline in injury resolution processes stemming from endogenous (physiological decline or somatic mutations) or exogenous stress. Environmental, dietary or occupational exposure accelerates the pathogenesis of a senescent phenotype based on (1) window of exposure; (2) dose, duration, recurrence; and (3) cells type being targeted. As the lung ages, the threshold to generate an irreversibly senescent phenotype is lowered. However, we do not have sufficient knowledge to make accurate predictions. In this review, we provide an assessment of the literature that interrogates lung epithelial, mesenchymal, and immune senescence at the intersection of aging, environmental exposure and pulmonary fibrosis.
How the Pacific Oyster Responds to Ocean Acidification: Development and Application of a Meta-Analysis Based Adverse Outcome Pathway

Biological fitness relies on processes acting at various levels of organization, all of which can be modified by environmental change. Application of synthesis frameworks, such as the Adverse Outcome Pathway (AOP), can enhance our understanding of the responses to stressors identified in studies at each level, as well as the links among them. However, the use of such frameworks is often limited by a lack of data. In order to identify contexts with sufficient understanding to apply the AOP framework, we conducted a meta-analysis of studies considering ocean acidification effects on calcifying mollusks. Our meta-analysis identified that most studies considered the adult life history stage, bivalve taxonomic group, individual-level changes, and growth- and metabolism-related responses. Given the characteristics of the published literature, we constructed an AOP for the effects of ocean acidification on calcification in an adult bivalve, specifically the Pacific oyster (Magallana gigas). By structuring results within the AOP framework, we identify that, at present, the supported pathways by which ocean acidification affects oyster calcification are via the downregulation of cavortin and arginine kinase transcription. Such changes at the molecular level can prompt changes in cellular and organ responses, including altered enzyme activities, lipid peroxidation, and regulation of acid–base status, which have impacts on organism level metabolic rate and, therefore, calcification. Altered calcification may then impact organism mortality and population sizes. We propose that when developed and incorporated in future studies, the AOP framework could be used to investigate sources of complexity including varying susceptibility within and among species, feedback mechanisms, exposure duration and magnitude, and species interactions. Such applications of the AOP framework will allow more effective reflections of the consequences of environmental change, such as ocean acidification, on all levels of biological organization.
The Target MicroRNAs and Potential Underlying Mechanisms of Yiqi-Bushen-Tiaozhi Recipe against‐Non-Alcoholic Steatohepatitis

MicroRNAs (miRNAs) have emerged as potential therapeutic targets for non-alcoholic fatty liver disease/non-alcoholic steatohepatitis (NAFLD/NASH). Traditional Chineses Medicine (TCM) plays an important role in the prevention or treatment of NAFLD/NASH. However, miRNA targets of TCM against NASH still remain largely unknown. Here, we showed that Yiqi-Bushen-Tiaozhi (YBT) recipe effectively attenuated diet-induced NASH in C57BL/6 mice. To identify the miRNA targets of YBT and understand the potential underlying mechanisms, we performed network pharmacology using miRNA and mRNA deep sequencing data combined with Ingenuity Pathway Analysis (IPA). Mmu-let-7a-5p, mmu-let-7b-5p, mmu-let-7g-3p and mmu-miR-106b-3p were screened as the main targets of YBT. Our results suggested that YBT might alleviate NASH by regulating the expression of these miRNAs that potentially modulate inflammation/immunity and oxidative stress. This study provides useful information for guiding future studies on the mechanism of YBT against NASH by regulating miRNAs.
Back to the Basics of Mate Choice: The Evolutionary Importance of Darwin’s Sense of Beauty

There is a simple and general explanation for the evolution of mate choice that does not rely on benefits to be gained from favoring some potential mates over others, nor on ornament-preference genetic correlations (but that can help establish such benefits and correlations). Mate choice necessarily arises from competition to engage the powerful but discriminating reward mechanisms that regulate sexual interactions. Progress in understanding the evolution of mate choice will come from analyzing the subjective nature of the cognitive-emotional mechanisms that regulate its expression. A key mechanism may be the sense of beauty—the feeling whose function it is to reward attention to, and engagement with, attractive objects. Any animal whose behavior and decision-making are regulated by mechanisms of emotion and feeling may possess the sense of beauty. Competition to be perceived as beautiful engages brain-generated, top-down influences on perception and subjective experience, adding manifold ways to improve ornament attractiveness. In this paper, I discuss the evolutionary consequences of mate choice involving the sense of beauty and how to test for it.
Blind deconvolution via complementarily structure-aware image smoothing

Abstract. Blind deconvolution is known as a challenging low-level vision problem due to the diverse blur scenarios in real-world imaging. Another attempt is made with critical thoughts on existing image priors for nonparametric blur kernel estimation, proposing an alternative approach to blind deconvolution via complementarily structure-aware image smoothing (CSIS). Similar to most state-of-the-art blind deblurring methods, the proposed approach partly builds on the naïve L0-based sparse model, but the core contribution here is to additionally advocate a type of redescending potential (RDP) functions as a more elegant way for boosting blind deblurring. With the RDP element, the new approach is capable of easily achieving the discrimination between clear and blurred images. Meanwhile, the performance of the proposed method can be better ensured due to the complementary smoothing behavior induced by the RDP functions. Specifically speaking, it is known that L0-based smoothing plays a critical role in pursuing salient step-edges from blurry images especially in the early period of blur kernel estimation, whereas the RDP-based smoothing is found particularly significant in the later stage when the fine pursuit of salient roof-edges or ramp-edges are dominantly critical for more precise and robust kernel estimation. In this sense, the proposed CSIS-based blind deblurring algorithm is more intuitive than previous L0-based methods. Not only that, numerous experimental results on benchmark blurred images, no matter synthetic or realistic, also demonstrate the comparable or even better performance of the proposed approach in terms of both effectiveness and robustness.
Effects of Compression Garments on Balance Control in Young Healthy Active Subjects: A Hierarchical Cluster Analysis

There is controversy about the influence of compression garments on balance control. A positive influence was reported in elderly and injured individuals, whereas no beneficial effects were observed in young healthy active subjects, which is likely due to the large inter-individual differences in these subjects. Hence, this study investigated the acute effects of compression garments on balance control in young healthy active subjects by addressing the issue of heterogeneity of individuals’ responses to the wearing of compression garments. Thirteen young, healthy, active subjects were recruited. They stood on a force plate which recorded the center of foot pressure displacements in a monopedal stance with the eyes closed and on a wobble board with the eyes open, while wearing compression garments or not. Statistics were first calculated with the data from the whole sample. A hierarchical cluster analysis was also performed in order to categorize the participants’ behaviors into subgroups with similar characteristics. The whole group analysis showed that there were no significant effects attributed to compression garments. The clustering analysis identified distinct and homogeneous subgroups of participants. Only participants who swayed the more at baseline benefited from the wearing of compression garments to improve their balance control. These participants might have either a gravity-dependent preferred sensorimotor strategy with an exploratory postural behavior or poorer balance/proprioceptive abilities. Since poor balance control is a predictor of sports injury risk, wearing compression garments during sports practice could be viewed as a potential prevention strategy for individuals at risk.
Predictive Value of Temporal Muscle Thickness Measurements on Cranial Magnetic Resonance Images in the Prognosis of Patients With Primary Glioblastoma

Objective: To investigate the predictive value of prognosis of primary GBM patients using TMT on three-dimensional (3D) MR images of the brain. Methods: Data of 130 patients with primary GBM from the TCGA-GBM database were analyzed retrospectively. TMT was measured on the axial plane by multi-planar reformation (MPR) of T1WI MR images perpendicular to the long axis of the temporal muscle at the level of the orbital roof. The axial MR plane was oriented parallel to the anterior commissure-posterior commissure line. Student's t-test or Mann–Whitney U-test was utilized to determine whether there were significant differences in the TMT and OS between male and female patients. The Pearson correlation analysis was adopted to evaluate the correlation between the age at GBM diagnosis and TMT. All patients were divided into two groups based on their median TMT, and the Kaplan–Meier curve was used to calculate the OS curve. The association between TMT and OS of GBM patients, as well as the multivariate analysis of TMT and other clinical factors affecting the survival time, was evaluated with Cox regression model. Results: TMT was a risk factor for the prognosis of GBM with its hazard ratio (HR) of 0.802 (95% CI 0.698–0.922; P = 0.002; Cox regression model). Grouped by median TMT, the group with above-median TMT demonstrated a significant increase in survival time (15.6 months) compared with the one with below-median TMT (11.2 months) (P < 0.001; log-rank test). In the multivariate survival analysis using a Cox regression model, TMT (HR 0.863; 95% CI 0.748–0.996; P = 0.044), age at the diagnosis of GBM (HR 1.042; 95% CI 1.024–1.060; P < 0.001), and concurrent chemoradiotherapy (HR 0.510; 95% CI 0.336–0.775; P = 0.002) were significantly associated with survival time. Conclusion: TMT as an independent predictor is sensitive to the survival prognosis of primary GBM patients, which has potential to predict the survival time.
CNS-Targeting Therapies for Lysosomal Storage Diseases: Current Advances and Challenges

During the past decades, several therapeutic approaches have been developed and made rapidly available for many patients afflicted with lysosomal storage disorders (LSDs), inborn organelle disorders with broad clinical manifestations secondary to the progressive accumulation of undegraded macromolecules within lysosomes. These conditions are individually rare, but, collectively, their incidence ranges from 1 in 2,315 to 7,700 live-births. Most LSDs are manifested by neurological symptoms or signs, including developmental delay, seizures, acroparesthesia, motor weakness, and extrapyramidal signs. The chronic and later-onset clinical forms are at one end of the continuum spectrum and are characterized by a subtle and slow progression of neurological symptoms. Due to its inherent physiological properties, unfortunately, the blood-brain barrier (BBB) constitutes a significant obstacle for current and upcoming therapies to achieve the central nervous system (CNS) and treat neurological problems so prevalent in these conditions. To circumvent this limitation, several strategies have been developed to make the therapeutic agent achieve the CNS. This narrative will provide an overview of current therapeutic strategies under development to permeate the BBB, and address and unmet need for treatment of the progressive neurological manifestations, which are so prevalent in these inherited lysosomal disorders.