Miracle-dz/UniFAR-FTUs huggingface dataset:
When Landscape Ecology Meets Physiology: Effects of Habitat Fragmentation on Resource Allocation Trade-Offs

Landscape heterogeneity is a general feature of natural environments, strongly affected by habitat fragmentation. It can affect a population’s dynamics and probability of extinction. Fragmentation increases among-patch isolation and decreases patch size, resulting in a reduction in available resources in smaller patches. To persist, animals must be able to translate the variation imposed by fragmentation into adaptive energy allocation strategies that enable populations to avoid extinction. This means that physiological adaptations are expected to reflect changes in landscape configuration, especially in the size of the natural habitat patches and degree of isolation among them. We propose a novel, integrative conceptual framework in which spatial characteristics of the environment, imposed by fragmentation, lead to specific life-history traits that increase survival (at the individual level) and decrease the likelihood of extinction (as an emergent property at the population level). We predict that a resource allocation trade-off between the life-history traits of reproduction and dispersal along a fragmentation gradient will emerge. Populations occurring in patches of different sizes and isolations along gradients of fragmentation and productivity will exhibit differences in the strength of the dispersal-reproduction trade-off. Emerging from this framework are several explicit and testable hypotheses that predict that the dispersal-reproduction trade-off will be shaped by landscape heterogeneity imposed by fragmentation. Hence, this trade-off serves as the mechanistic link that translates environmental variation created by fragmentation into variation in species abundances and population dynamics by lowering local extinction probability and increasing overall population persistence.
Power Consumption and Energy-Efficiency for In-Band Full-Duplex Wireless Systems

This paper presents an analytical model of power consumption for In-Band Full-Duplex (IBFD) Wireless Local-Area Networks (WLANs). Energy-efficiency is compared for both Half-Duplex (HD) and IBFD networks. The presented analytical model closely matches the results generated by simulation. For a given traffic scenario, IBFD systems exhibit higher power consumption, however at improved energy efficiency when compared to equivalent HD WLANs.
LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds

We present LBS-AE; a self-supervised autoencoding algorithm for fitting articulated mesh models to point clouds. As input, we take a sequence of point clouds to be registered as well as an artist-rigged mesh, i.e. a template mesh equipped with a linear-blend skinning (LBS) deformation space parameterized by a skeleton hierarchy. As output, we learn an LBS-based autoencoder that produces registered meshes from the input point clouds. To bridge the gap between the artist-defined geometry and the captured point clouds, our autoencoder models pose-dependent deviations from the template geometry. During training, instead of us- ing explicit correspondences, such as key points or pose supervision, our method leverages LBS deformations to boot- strap the learning process. To avoid poor local minima from erroneous point-to-point correspondences, we utilize a structured Chamfer distance based on part-segmentations, which are learned concurrently using self-supervision. We demonstrate qualitative results on real captured hands, and report quantitative evaluations on the FAUST benchmark for body registration. Our method achieves performance that is superior to other unsupervised approaches and com- parable to methods using supervised examples.
Microgravity Effect on Microstructural Development of Tri-calcium Silicate (C3S) Paste

For the first time, tricalcium silicate (C3S) and an aqueous solution were mixed and allowed to hydrate in the microgravity environment aboard the International Space Station (ISS). The research hypothesis states that minimizing gravity-driven transport phenomena, such as buoyancy, sedimentation, and thermosolutal convection ensures diffusion-controlled crystal growth and, consequently, lead to unique microstructures. Results from SEM micrographs, image analysis, mercury intrusion porosimetry, thermogravimetry, and x-ray diffraction revealed that the primary differences in g hydrated C3S paste are increased porosity and a lower aspect ratio of portlandite crystals, likely due to a more uniform phase distribution. Relevant observations led by the presence or absence of gravity, including bleeding effect, density, and crystallography are also presented and discussed.
Inhibition of SIRT2 by Targeting GSK3β-Mediated Phosphorylation Alleviates SIRT2 Toxicity in SH-SY5Y Cells

Sirtuin 2 (SIRT2) is thought to be important in the pathogenesis of Parkinson’s disease (PD), and the inhibition of SIRT2 rescues α-synuclein toxicity in a cellular model of PD. Recent studies have focused on identifying inhibitors of SIRT2, but little is known about the processes that directly regulate its function. GSK3β is a serine/threonine protein kinase that affects a wide range of biological functions, and it is localized in Lewy bodies (LBs). Therefore, we investigated whether SIRT2 is regulated by GSK3β and enhances cell death in PD. In the present study, Western blot showed that total SIRT2 levels did not change noticeably in a cellular model of PD but that SIRT2 phosphorylation was increased, and GSK3β activity was elevated. In addition, mass spectrometry (MS) studies indicated that SIRT2 was phosphorylated by GSK3β at three specific sites. Phospho- or dephospho-mimicking studies demonstrated that this postmodification (phosphorylation) increased SIRT2 toxicity in SH-SY5Y cells. Collectively, our findings identify a posttranslational mechanism that controls SIRT2 function in PD and provide evidence for a novel regulatory pathway involving GSK3β, SIRT2, and α-synuclein.
Learning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning

We investigate learning feature-to-feature translator networks by alternating back-propagation as a general-purpose solution to zero-shot learning (ZSL) problems. Our method can be categorized to a generative model-based ZSL one. In contrast to the GAN or VAE that requires auxiliary networks to assist the training, our model consists of a single conditional generator that maps the class feature and a latent vector %accounting for randomness in the output to the image feature, and is trained by maximum likelihood estimation. The training process is a simple yet effective EM-like process that iterates the following two steps: (i) the inferential back-propagation to infer the latent noise vector of each observed data, and (ii) the learning back-propagation to update the parameters of the model. With slight modifications of our model, we also provide a solution to learning from incomplete visual features for ZSL. We conduct extensive comparisons with existing generative ZSL methods on five benchmarks, demonstrating the superiority of our method in not only performance but also convergence speed and computational cost. Specifically, our model outperforms the existing state-of-the-art methods by a remarkable margin up to $3.1\%$ and $4.0\%$ in ZSL and generalized ZSL settings, respectively.
Memory System Designed for Multiply-Accumulate (MAC) Engine Based on Stochastic Computing

Convolutional neural network (CNN) achieves excellent performance on fascinating tasks such as image recognition and natural language processing at the cost of high power consumption. Stochastic computing (SC) is an attractive paradigm implemented in low power applications which performs arithmetic operations with simple logic and low hardware cost. However, conventional memory structure designed and optimized for binary computing leads to extra data conversion costs, which significantly decreases the energy efficiency. Therefore, a new memory system designed for SC-based multiply-accumulate (MAC) engine applied in CNN which is compatible with conventional memory system is proposed in this paper. As a result, the overall energy consumption of our new computing structure is 0.91 pJ, which is reduced by 82.1% compared with the conventional structure, and the energy efficiency achieves 164.8 TOPS/W.
Production of IgG2 Antibodies to Pneumococcal Polysaccharides After Vaccination of Treated HIV Patients May Be Augmented by IL-7Rα Signaling in ICOS+ Circulating T Follicular-Helper Cells

Greater understanding of factors influencing the maturation of antibody responses against pneumococcal polysaccharides (PcPs) may improve pneumococcal vaccination strategies. Although PcPs are type 2 T cell-independent antigens thought not to induce follicular immune responses, we have previously shown that IgG2 antibody responses against antigens in the 23-valent unconjugated PcP vaccine (PPV23) are associated with expansion of ICOS+ circulating T follicular helper (cTFH) cells in HIV seronegative subjects but not HIV patients. As IL-7Rα signaling in CD4+ T cells may affect TFH cell function and is adversely affected by HIV-1 infection, we have examined the relationship of IL-7Rα expression on ICOS+ cTFH cells with PcP-specific IgG2 antibody responses. PPV23 vaccination was undertaken in HIV patients receiving antiretroviral therapy (n = 25) and HIV seronegative subjects (n = 20). IL-7Rα expression on ICOS+ and ICOS− cTFH cells was assessed at day(D) 0, 7, and 28. Fold increase between D0 and D28 in serum IgG1 and IgG2 antibodies to PcP serotypes 4, 6B, 9V, and 14 and the frequency of IgG1+ and IgG2+ antibody secreting cells (ASCs) at D7 were also assessed. Decline in IL-7Rα expression on ICOS+ cTFH cells between D0 and D7 occurred in 75% of HIV seronegative subjects and 60% of HIV patients (Group A), with changes in IL-7Rα expression being more pronounced in HIV patients. Group A patients exhibited abnormally high IL-7Rα expression pre-vaccination, an association of serum IgG2, but not IgG1, antibody responses with a decline of IL-7Rα expression on ICOS+ cTFH cells between D0 and D7, and an association of higher IgG2+ ASCs with lower IL-7Rα expression on ICOS+ cTFH cells at D7. As decline of IL-7Rα expression on CD4+ T cells is an indicator of IL-7Rα signaling, our findings suggest that utilization of IL-7 by cTFH cells affects production of IgG2 antibodies to PPV23 antigens in some HIV patients.
Tax Avoidance and Accounting Conservatism

This study analyzes the relation between accounting conservatism, future tax rate cuts and countries' level of book-tax conformity. Firms have an incentive to increase conservatism in financial reporting when a tax rate cut is imminent to shift taxable income into the lower taxed future. Using a panel of firms across 18 countries from 1995 to 2010 I find that conditional conservatism is positively and significantly associated with future tax rate cuts when book-tax conformity is high. This effect is particularly pronounced for firms that concentrate the majority of their operations in the country in which the tax rate is cut. In contrast, there is no significant relation between future tax rate cuts and unconditional conservatism.
Regulation of Dietary Lipid Sources on Tissue Lipid Classes and Mitochondrial Energy Metabolism of Juvenile Swimming Crab, Portunus trituberculatus

An 8-weeks feeding trial with swimming crab, Portunus trituberculatus, was conducted to investigate the effects of different dietary lipid sources on the lipid classes, lipid metabolism, and mitochondrial energy metabolism relevant genes expression. Six isonitrogenous and isolipidic experimental diets were formulated to contain fish oil (FO), krill oil (KO), palm oil (PO), rapeseed oil (RO), soybean oil (SO), and linseed oil (LO), respectively. A total of 270 swimming crab juveniles (initial weight 5.43 ± 0.03 g) were randomly divided into six diets with three replications, each consisted of 45 juvenile crabs. The results revealed that crabs fed KO had highest lipid content in hepatopancreas and free fatty acids in serum among all diets. The anabolic pathway relevant genes: fas and acc were up-regulated in KO diet. The catabolic pathway relevant genes, hsl, was up-regulated in LO diet, while cpt1 was up-regulated in KO diet. Whereas, the genes involved in the transport and uptake of fatty acids such as fabp1 and fatp4 were down-regulated in crab fed PO and RO diets. Furthermore, the gene expression levels of transcription factors: srebp-1 and hnf4α in KO and SO diets were the highest among all diets. FO and KO diets had significantly higher unsaturation index of mitochondrial membrane than others. The genes related to mitochondrial energy metabolism, such as Atpase6, sirt1, and sirt3 were significantly up-regulated in KO and SO diets. In summary, dietary KO and SO supplementation could improve the lipid metabolism, promote energy production for juvenile swimming crab and improve physiological process and function including molting. These findings could contribute to deepen the understanding of the physiological metabolism of dietary fatty acids for swimming crab.
A Genetic Variant of miR-34a Contributes to Susceptibility of Ischemic Stroke Among Chinese Population

miRNAs are small non-coding RNAs modulating gene expression, and variants in miRNA genes are involved in the pathogenesis of ischemic stroke (IS). However, the effect of miR-34a polymorphisms on IS susceptibility has rarely been reported. In the present study, we investigated the association between rs12128240, rs2666433, and rs6577555 of the miR-34a gene and IS susceptibility. Snapshot assay was used to detect miR-34a polymorphisms in 548 IS patients and 560 controls. Relative expression of miR-34a was measured by quantitative real-time PCR. We found that rs2666433 was associated with a significantly increased risk of IS (AA vs. GG: OR = 1.61, 95% CI = 1.05–2.52, P = 0.031; AA vs. GG+GA: OR = 1.58, 95% CI = 1.05–2.45, P = 0.026). For the IS subtypes, rs2666433 was associated with large artery atherosclerosis (AA vs. GG: OR = 2.09, 95% CI = 1.16–3.51, P = 0.007; AA vs. GG+GA: OR = 2.02, 95% CI = 1.15–3.33, P = 0.007; A vs. G: OR = 1.36, 95% CI = 1.07–1.81, P = 0.021). Additionally, the level of miR-34a was significantly up-regulated in IS patients compared to the controls (P < 0.001), and patients with rs2666433 AA genotype had a higher level of miR-34a than those with GG+GA genotypes (P < 0.001). Furthermore, increased level of homocysteine was observed in IS patients compared to the controls (P < 0.001), especially in patients carrying the rs2666433AA genotype compared to those carrying the rs2666433 GG+GA genotypes (P < 0.001). However, no significant association between rs12128240 or rs6577555 and IS was found. Collectively, our study found the association between miR-34a polymorphisms and the risk of IS among the Chinese population. The results may provide an explanation for etiology of IS and a potential biomarker or therapeutic target for IS. HIGHLIGHTS- MiR-34a rs2666433 polymorphism was associated with an increased risk of ischemic stroke. - The level of miR-34a was significantly up-regulated in ischemic stroke patients compared with controls, and patients with rs2666433 AA genotype had a higher level miR-34a than those with GG+GA genotypes. - Furthermore, increased level of homocysteine was showed in IS patients compared to controls, and in patients carrying the rs2666433AA compared to those carrying the rs2666433 GG+GA.
High-frequency crowd insights for public safety and congestion control

We present results from several projects aimed at enabling the real-time understanding of crowds and their behaviour in the built environment. We make use of CCTV video cameras that are ubiquitous throughout the developed and developing world and as such are able to play the role of a reliable sensing mechanism. We outline the novel methods developed for our crowd insights engine, and illustrate examples of its use in different contexts in the urban landscape. Applications of the technology range from maintaining security in public spaces to quantifying the adequacy of public transport level of service.
An Examination of Whether Mindfulness Can Predict the Relationship Between Objective and Subjective Attitudinal Ambivalence

Ambivalence is a mixed reaction toward an attitudinal object. Ambivalence is often viewed as aversive and people are motivated to reduce it. However, the presence of both strong positive and negative attitudes toward an object (objective ambivalence; OA) does not always lead to consciously experienced conflicted and torn feelings (subjective ambivalence; SA) or psychological discomfort. We hypothesized that the way people think about their inner experience can affect whether ambivalent attitudes lead to increased conflicted feelings. In five studies, we examined whether mindfulness predicts the relationship between objective and subjective ambivalence. We predicted that the acceptance aspect of mindfulness would attenuate the relationship between OA and SA, based on the idea that acceptance makes people more tolerant and less judgmental toward their inner states in general (and OA in particular). Although some findings across five studies were consistent with the prediction showing that acceptance attenuated the OA–SA relationship, other findings were not and even showed that acceptance strengthened the OA–SA relationship. A meta-analysis of the interaction effect across all studies failed to find support for predictions (r = -0.036 and 95% CI [-0.087; 0.022]). We discuss possible reasons for these mixed findings, and the implications of these studies.
Tripartite coincidence-best proximity points in generalized metric spaces

We first introduce a notion of convex structure in generalized metric spaces, then we introduce tripartite contractions, tripartite semi-contractions, tripartite coincidence points, as well as tripartite best proximity points for a given triple $(K;S;T)$ of nonlinear mappings defined on the union $A\cup B\cup C$ of closed subsets of a generalized metric space. We prove theorems on the existence and convergence of tripartite coincidence-best proximity points.
Associated factors for depressive disorder in patients with end-stage renal disease treated with continuous ambulatory peritoneal dialysis

Background The aim of this study was to primarily determine factors associated with the depressive disorders in continuous ambulatory peritoneal dialysis (CAPD). Methods CAPD patients were recruited from the chronic kidney disease and CAPD Clinic of University Hospital. The stable CAPD patients for at least 3 months were included in the study. Sociodemographic data, renal conditions, and depressive disorder were evaluated. In addition to determining prevalence rate of depressive disorders, identification of factors associated with depressive disorders in CAPD patients were analyzed by using the multivariable logistic regression analysis with backward elimination procedure. Results The eligible participants were 108 patients. The study found that 11% of CAPD patients were diagnosed with depressive disorders including, minor depressive, dysthymic, and major depressive disorders. Additionally, the depressive disorders were associated with the duration between the diagnosis date of the end-stage renal disease (ESRD) and the initial treatment date (P=0.043). Accordingly, the ESRD patients diagnosed in <12 months had 3.57-fold higher risk of depressive disorders than the patients diagnosed after a long time. Conclusion The rate of prevalence for depressive disorder is high in the CAPD patients. Additionally, the results of this study have shown the relationship between depressive disorder and time for diagnosis of ESRD. Specifically, the risk of depressive disorder increases when patients have a shorter duration between the dates of ESRD diagnosis and initial treatment. In addition to closed monitoring for those patients, the psychiatrists should be consulted for evaluation and treatment of depressive disorders for the suspected high risk patients.
Attention-Guided Network for Ghost-Free High Dynamic Range Imaging

Ghosting artifacts caused by moving objects or misalignments is a key challenge in high dynamic range (HDR) imaging for dynamic scenes. Previous methods first register the input low dynamic range (LDR) images using optical flow before merging them, which are error-prone and cause ghosts in results. A very recent work tries to bypass optical flows via a deep network with skip-connections, however, which still suffers from ghosting artifacts for severe movement. To avoid the ghosting from the source, we propose a novel attention-guided end-to-end deep neural network (AHDRNet) to produce high-quality ghost-free HDR images. Unlike previous methods directly stacking the LDR images or features for merging, we use attention modules to guide the merging according to the reference image. The attention modules automatically suppress undesired components caused by misalignments and saturation and enhance desirable fine details in the non-reference images. In addition to the attention model, we use dilated residual dense block (DRDB) to make full use of the hierarchical features and increase the receptive field for hallucinating the missing details. The proposed AHDRNet is a non-flow-based method, which can also avoid the artifacts generated by optical-flow estimation error. Experiments on different datasets show that the proposed AHDRNet can achieve state-of-the-art quantitative and qualitative results.
Ability to Suppress TGF-β-Activated Myofibroblast Differentiation Distinguishes the Anti-pulmonary Fibrosis Efficacy of Two Danshen-Containing Chinese Herbal Medicine Prescriptions

Background: Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease with limited treatment options. It also leads to progressive respiratory failure, which subsequently affects the heart functionality, a pathological heart-lung interaction increasingly noticed and defined as pulmonary-heart disease (PHD). Traditional Chinese medicine (TCM) theory for treating “phlegm-stasis cementation syndrome” may suggest a possibility of treating PHD complication with Chinese medicine prescriptions previously used for cardiovascular diseases. Methods: Here, we evaluate the efficacies of two compound Chinese medicine prescriptions, Danlou prescription (DLP) and Danhong prescription (DHP), which share a common herbal component, Salvia miltiorrhiza (Danshen), on pulmonary fibrosis. Severity grades of Bleomycin (BLM)-induced pulmonary fibrosis were assessed by micro-Computerized Tomography (μCT) in accordance with the clinical evaluation standard. Lung pathological changes and collagen deposition were investigated by histopathology. Myofibroblast differentiation was assessed by immunohistochemistry of α-SMA and TGF-β receptor type II expression in situ. Network pharmacology analysis of the drug-target interaction in IPF progression for DLP or DHP was performed using Ingenuity® Pathways Analysis (IPA) system. Results: We show that a non-invasive μCT effectively monitor and quantify BLM-induced pulmonary fibrosis and its treatment efficacy by Chinese medicine prescription in rodents. In addition, although both containing Salvia miltiorrhiza, DLP but not DHP mitigates BLM-induced lung fibrosis by inhibiting the TGF-β signaling-activated myofibroblast differentiation and α-SMA expression in a mouse model. Core analysis by IPA revealed that DLP ingredients regulated not only pulmonary fibrosis related inflammatory genes but also genes associated with myofibroblast activation and collagen deposition. Conclusion: This study suggests that a clinically efficacious cardiovascular Chinese herbal medicine (DLP) can be successfully repurposed to treat a lung disease in pulmonary fibrosis guided by TCM theory. Our comparative study between DLP and DHP demonstrated a critical requirement of suppressing both pro-inflammatory and pro-fibrotic pathways for the treatment of pulmonary fibrosis, supporting that a multi-component prescription capable of “removing both phlegm and blood stasis” will better achieve co-protection of heart and lung in PHD.