Miracle-dz/UniFAR-FTUs huggingface dataset:
The COP9 Signalosome Suppresses Cardiomyocyte Necroptosis

Background Loss of cardiomyocyte (CMs) due to apoptosis and regulated necrosis contributes to heart failure. However, the molecular mechanisms governing regulated CM necrosis remain obscure. The COP9 signalosome (CSN) formed by 8 unique protein subunits (COPS1 through COPS8) functions to deneddylate Cullin-RING ligases (CRLs), thereby regulating the functioning of the CRLs. Mice with CM-restricted knockout of Cops8 (Cops8-cko) die prematurely, following reduced myocardial performance of autophagy and the ubiquitin-proteasome system (UPS) as well as massive CM necrosis. This study was aimed to determine the nature and underlying mechanisms of the CM necrosis in Cops8-cko mice. Methods We examined myocardial expression and activities of key proteins that reflect the status of the RIPK1-RIPK3 pathway, redox, and caspase 8 in Cops8-cko mice. Moreover, we used in vivo CM uptake of Evan’s blue dye (EBD) as an indicator of necrosis and performed Kaplan-Meier survival analyses to test whether treatment with a RIPK1 kinase inhibitor (necrostatin-1) or an antioxidant (N-acetyl-L-cysteine), global knockout of the RIPK3 or the Ppif gene, CM-restricted knockout of the Nrf2 gene, or cardiac HMOX1 overexpression could rescue the Cops8-cko phenotype. Results Compared with littermate control mice, myocardial protein levels of RIPK1, RIPK3, MLKL, the RIPK1-bound RIPK3, protein carbonyls, full-length caspase 8, Nrf2, Ser40-phosphorylated Nrf2 and BCL2, as well as histochemical staining of superoxide anions were significantly increased but the cleaved caspase 8 and the overall caspase 8 activity were markedly decreased in Cops8-cko mice, indicating that the RIPK1-RIPK3 and the Nrf2 pathways are activated and caspase 8 activation is suppressed by Cops8-cko. Continuous necrostatin-1 infusion initiated at 2 weeks of age nearly completely blocked CM necrosis at 3 weeks and markedly delayed premature death of Cops8-cko mice. RIPK3 haploinsufficiency or cardiac-specific Nrf2 heterozygous knockout discernably attenuated CM necrosis and/or delayed mouse premature death; conversely, Ppif knockout, N-acetyl-L-cysteine treatment, and cardiac overexpression of HMOX1 exacerbated CM necrosis and mouse premature death. Conclusions Cardiac Cops8/CSN malfunction causes RIPK1-RIPK3 mediated CM necroptosis in mice; sustained Nrf2 activation and reductive stress pivot cardiomyocytes to necroptosis when autophagy and the UPS are impaired; and the CSN plays an indispensable role in suppressing CM necroptosis.
A Way to Mitigate Force-Fight Oscillation Based on Pressure and Position Compensation for Fly-by-Wire Flight Control Systems

This paper focuses on force-fight oscillation mitigation in fly-by-wire (FBW) flight control systems (FCSs) for civil aircraft. The theory of “force fight” was first introduced after analyzing its impact on active-active actuators system. The architecture of one typical FBW FCS and the layout of an electronic hydraulic servo actuator (EHSA) were described. A force-fight mitigation algorithm applying pressure and position compensation feedback was then presented. To validate algorithm performance, an associated actuator-surface model was created to simulate force fight. Finally, the algorithm was tested using worst-case scenarios by calculating the system latency and tolerance, and verified using special ‘‘Iron Bird’’ tests. The results show an obvious decrease in the difference delta press (DDP) when comparing with/without mitigation, and thereby meeting force fight limitation requirements.
Deep predictive coding accounts for emergence of complex neural response properties along the visual cortical hierarchy

Predictive coding provides a computational paradigm for modelling perceptual processing as the construction of representations accounting for causes of sensory inputs. Here, we develop a scalable, deep predictive coding network that is trained using a Hebbian learning rule. Without a priori constraints that would force model neurons to respond like biological neurons, the model exhibits properties similar to those reported in experimental studies. We analyze low- and high-level properties such as orientation selectivity, object selectivity and sparseness of neuronal populations in the model. As reported experimentally, image selectivity increases systematically across ascending areas in the model hierarchy. A further emergent network property is that representations for different object classes become more distinguishable from lower to higher areas. Thus, deep predictive coding networks can be effectively trained using biologically plausible principles and exhibit emergent properties that have been experimentally identified along the visual cortical hierarchy. Significance Statement Understanding brain mechanisms of perception requires a computational approach based on neurobiological principles. Many deep learning architectures are trained by supervised learning from large sets of labeled data, whereas biological brains must learn from unlabeled sensory inputs. We developed a Predictive Coding methodology for building scalable networks that mimic deep sensory cortical hierarchies, perform inference on the causes of sensory inputs and are trained by unsupervised, Hebbian learning. The network models are well-behaved in that they faithfully reproduce visual images based on high-level, latent representations. When ascending the sensory hierarchy, we find increasing image selectivity, sparseness and generalizability for object classification. These models show how a complex neuronal phenomenology emerges from biologically plausible, deep networks for unsupervised perceptual representation.
Golgi SM protein Sly1 promotes productive trans-SNARE complex assembly through multiple mechanisms

SNARE chaperones of the Sec1/mammalian Unc-18 (SM) family have critical roles in SNARE-mediated membrane fusion. Using SNARE and Sly1 mutants, and a new in vitro assay of fusion, we separate and assess proposed mechanisms through which Sly1 augments fusion: (i) opening the closed conformation of the Qa-SNARE Sed5; (ii) close-range tethering of vesicles to target organelles, mediated by the Sly1-specific regulatory loop; and (iii) preferential nucleation of productive trans-SNARE complexes. We show that all three mechanisms are important and operate in parallel, and we present evidence that close-range tethering is particularly important for trans-complex assembly when cis-SNARE assembly is a competing process. In addition, the autoinhibitory N-terminal Habc domain of Sed5 has at least two positive activities: the Habc domain is needed for correct Sed5 localization, and it directly promotes Sly1-dependent fusion. Remarkably, “split Sed5,” with the Habc domain present only as a soluble fragment, is functional both in vitro and in vivo.
TLR4 signaling in neurons enhances calcium-permeable AMPAR currents 1 and drives post-traumatic epileptogenesis 2

Traumatic brain injury is a major risk factor for acquired epilepsies and understanding the 8 mechanisms underlying the early pathophysiology could yield viable therapeutic targets. 9 Growing evidence indicates a role for inflammatory signaling in modifying neuronal excitability 10 and promoting epileptogenesis. Here, we identify that signaling through an innate immune 11 receptor, toll-like receptor 4 (TLR4), in neurons, augments calcium-permeable AMPA receptor 12 (CP-AMPAR) currents in the hippocampal dentate gyrus after brain injury. Blocking TLR4 13 signaling in vivo shortly after brain injury reduced dentate network excitability and seizure 14 susceptibility. When blocking of TLR4 signaling after injury was delayed, however, this 15 treatment failed to reduce post-injury seizure susceptibility. Further, TLR4 signal blocking was 16 less efficacious in limiting seizure susceptibility when AMPAR currents, downstream targets of 17 TLR4 signaling, were transiently enhanced. Paradoxically, blocking TLR4 signaling augmented 18 both network excitability and seizure susceptibility in uninjured controls. Despite the differential 19 effect on seizure susceptibility, TLR4 antagonism suppressed cellular inflammatory responses 20 after injury without impacting sham controls. These findings demonstrate that independently of 21 glia, the immune receptor TLR4 directly regulates post-traumatic neuronal excitability. 22 Moreover, the TLR4-dependent early increase in dentate excitability is causally associated with 23 epileptogenesis. Identification and selective targeting of the mechanisms underlying the aberrant 24 TLR4-mediated increase in CP-AMPAR signaling after injury may prevent epileptogenesis after 25 traumatic brain injury. 26
A predictive analytics framework as a countermeasure for attrition of students

ABSTRACT Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students’ retention services. Big Data mining and machine learning methods are applied to manipulate, analyze and predict students’ failure, supporting self-directed learning. Despite the extensive application of data mining to education, the imbalance problem in minority classes of students’ attrition is often overlooked in conventional models. This document proposes a large data frame using the Hadoop ecosystem and the application of machine learning techniques to different datasets of an academic year at the Hellenic Open University. Datasets were divided into thirty-five weeks. Thirty-two classifiers were created, compared and statistical analyzed to address the minority classes’ imbalance of student’s failure. The algorithms metacost-SMO, and C4.5 provide the most accurate performance for each target class. Early predictions of timeframes determine a remarkable performance, while the importance of written assignments and specific quizzes is noticeable. The models’ performance in any week is exploited by developing a prediction tool for student attrition, contributing to timely and personalized intervention.
Intermittent pneumatic compression versus multilayer bandages for reducing post mastectomy lymphedema: A randomized controlled trial. -

Background: Lymphoedema is a serious health, psychosocial and economic problem among patients treated for malignant tumors which requested specified physical therapy aiming to reverse further increase of limb size. Purpose: The aim of this study was to compare the efficacy of intermittent pneumatic-compression and multilayer bandages (Mobiderm bandage) in reduction of post mastectomy lymphedema. Methods: Thirty female patients with unilateral post mastectomy secondary lymphedema participated in this study. Patients were randomly assigned into two equal groups of 15, group (A) received intermittent pneumatic compression therapy for 20 min per day, daily for 3 weeks in addition to traditional medical treatment with manual lymphatic drainage and group (B) received multilayer bandages for 20 hours per day, daily for 3 weeks. Results: After one week of treatment (Post 1), between group statistical analysis showed significant increase (p< 0.05) in functional scale measures, slight improvements (p< 0.05) in goniometric measurement at several points despite no improvements (p≥ 0.05) in the other points. Nevertheless, the tape measurement showed no significant changes in most points (p≥ 0.05). This study showed a significant increase (p< 0.05) in goniometric measurement, tape measurement at most points of measures and functional scale measures in both groups after three weeks of treatment (Post 3) in comparing between pre and post 3 treatment within each group but with higher improvement in group B than group A. Conclusions: Mobiderm bandage produced objective improvement in lymphedema more than the usage of intermittent pneumatic compression, however both considered as a gold therapeutic tool in the management of lymphedema post mastectomy.
Large-Area Laying of Soft Textile Power Generators for the Realization of Body Heat Harvesting Clothing

This paper presents the realization of a flexible thermoelectric (TE) generator as a textile fabric that converts human body heat into electrical energy for portable, low-power microelectronic products. In this study, an organic non-toxic conductive coating was used to dip rayon wipes into conductive TE fabrics so that the textile took advantage of the TE currents which were parallel to the temperature gradient. To this end, a dyed conductive cloth was first sewn into a TE unit. The TE unit was then sewn into an array to create a temperature difference between the human body and the environment for TE power harvesting. The prototype of the TE fabric consisted of 48 TE units connected by conductive wire over an area of 275 × 205 mm2, and the TE units were sewn on a T-shirt at the chest area. After fabrication and property tests, a Seebeck coefficient of approximately 20 μV/K was measured from the TE unit, and 0.979 mV voltage was obtained from the T-shirt with TE textile fabric. Since the voltage was generated at a low temperature gradient environment, the proposed energy solution in actual fabric applications is suitable for future portable microelectronic power devices.
scIGANs: single-cell RNA-seq imputation using generative adversarial networks

Single-cell RNA-sequencing (scRNA-seq) enables the characterization of transcriptomic profiles at the single-cell resolution with increasingly high throughput. However, it suffers from many sources of technical noises, including insufficient mRNA molecules that lead to excess false zero values, termed dropouts. Computational approaches have been proposed to recover the biologically meaningful expression by borrowing information from similar cells in the observed dataset. However, these methods suffer from oversmoothing and removal of natural cell-to-cell stochasticity in gene expression. Here, we propose the generative adversarial networks (GANs) for scRNA-seq imputation (scIGANs), which uses generated cells rather than observed cells to avoid these limitations and balances the performance between major and rare cell populations. Evaluations based on a variety of simulated and real scRNA-seq datasets show that scIGANs is effective for dropout imputation and enhances various downstream analysis. ScIGANs is robust to small datasets that have very few genes with low expression and/or cell-to-cell variance. ScIGANs works equally well on datasets from different scRNA-seq protocols and is scalable to datasets with over 100,000 cells. We demonstrated in many ways with compelling evidence that scIGANs is not only an application of GANs in omics data but also represents a competing imputation method for the scRNA-seq data.
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce

With the prosperous of cross-border e-commerce, there is an urgent demand for designing intelligent approaches for assisting e-commerce sellers to offer local products for consumers from all over the world. In this paper, we explore a new task of cross-lingual information retrieval, i.e., cross-lingual set-to-description retrieval in cross-border e-commerce, which involves matching product attribute sets in the source language with persuasive product descriptions in the target language. We manually collect a new and high-quality paired dataset, where each pair contains an unordered product attribute set in the source language and an informative product description in the target language. As the dataset construction process is both time-consuming and costly, the new dataset only comprises of 13.5k pairs, which is a low-resource setting and can be viewed as a challenging testbed for model development and evaluation in cross-border e-commerce. To tackle this cross-lingual set-to-description retrieval task, we propose a novel cross-lingual matching network (CLMN) with the enhancement of context-dependent cross-lingual mapping upon the pre-trained monolingual BERT representations. Experimental results indicate that our proposed CLMN yields impressive results on the challenging task and the context-dependent cross-lingual mapping on BERT yields noticeable improvement over the pre-trained multi-lingual BERT model.
Effect of the biceps Brachii tendon on elbow flexor force steadiness in men and women

ii PREFACE . iii TABLE OF CONTENTS . iv LIST OF TABLES . vi LIST OF FIGURES . vii LIST OF ABBREVIATIONS . viii ACKNOWLEDGEMENTS . ix DEDICATION . x CHAPTER 1: INTRODUCTION . 1 1.1 Neuromuscular Organization of Voluntary Movement . 1 1.2 Structural and Mechanical Properties of Tendon . 4 1.3 Integrated Functional Interaction between Muscle and Tendon . 8 1.4 Contribution of Biceps Brachii Muscle and Its Tendon to Movement . 12 1.5 Isometric Force and Force Steadiness . 13 1.6 Sex difference in force steadiness . 15 1.7 Summary of Literature . 16 CHAPTER 2: PURPOSE AND HYPOTHESES . 17 2.1 Purpose . 17 2.2 Hypotheses . 17 CHAPTER 3: METHODOLOGY . 18 3.1 Participants . 18 3.2 Experimental Protocol . 18 3.3 Experimental Setup . 21 3.4 Assessment . 21 3.4. 1 Resting BB muscle and tendon length and CSA measurement . 21 3.4. 2 Maximal Voluntary contractions (MVC) and Voluntary Activation . 22 3.4. 3 Measurement of tendon elongation and CSA during the steadiness task . 23 3.5 Data Analysis . 25 3.5. 1 Muscle and Tendon Properties at rest . 26
The Environmental Assessment on Chinese Logistics Enterprises Based on Non-Radial DEA

Under the new situation of economic development in China, the logistics industry is facing unbalanced development regarding economic and environmental performance. From the enterprise level, this study investigated the sustainability of Chinese logistics based on the environmental assessment data envelopment analysis (DEA) model, and measured the unified efficiency of a logistics company under two different production arrangement strategies. The empirical measurement provides several findings. First, logistics enterprises give higher priority to operational benefits than environmental performance. Second, under the operational priority of production arrangement, small and medium-sized enterprises’ (SMEs) unified efficiency is better than a large enterprise, and private enterprises’ unified efficiency is better than state-owned enterprises. Moreover, the empirical study has further proved that the sustainability development of Chinese logistics is still at the primary stage; when facing trade-offs in the sustainability context, logistics companies still prioritize operational performance first. Therefore, transforming corporate strategy into an environmental sustainable priority and realizing logistics sustainability still has a long way to go, which is the backbone of realizing balanced development of both the economy and environment.
A review of language regression in autism spectrum disorder and the role of language theories: Towards explanation

Background & aims The purpose of this study is to summarize characteristics of language regression—a phenomenon most commonly associated with autism spectrum disorder, outline language theories of early word learning, and use them to propose theoretical bases to language regression. Method Using a systematic review of the current literature in language regression and a purposive sampling of language theories, hypotheses for the cause of language regression are discussed. Results The following hypotheses were developed based on the reviewed theories of word learning: (a) Initial first words were not true words, but instead were protowords; (b) fast mapped forms never progressed to truly learned words; (c) initial first words were echoed productions of heard words; (d) the described regression is actually a maintenance of previous developmental levels with increasing chronological age. Conclusions It is possible that individuals with autism spectrum disorder are not “losing” words, but instead are not progressing in their ability to learn and use new words. Early word learning in typically developing children is seemingly similar to early development in individuals with autism spectrum disorder; however, the ability to expand from early “intermediate words” to expansive vocabularies, word combinations, and morphological variations is impeded. Clinical implications for evaluation of word “loss” and treatments are discussed.
Reconstructing the complex evolutionary history of the fused Aco2 gene in fission yeast

The Aco2 gene of Schizosaccharomyces pombe was formed by gene fusion between curious partners, namely genes encoding the enzyme aconitase and a mitochondrial ribosomal protein. In addition to a full-length transcript, a truncated mRNA encoding only the N-terminal aconitase domain is produced by polyadenylation at an internal site. Protein products of the gene are found in the nucleus, mitochondria and cytoplasm, consistent with the presence of multiple subcellular targeting signals. To reconstruct the evolution of this complex gene, we studied homologous genes from a range of related species. We find evidence for a dynamic history within Taphrinomycotina, including: early evolution of a nuclear localization signal; creation of a 3’ intron that could be involved in regulating subcellular targeting; evolution of multiple peroxisomal targeting signals in different lineages; and recurrent gene loss. We present a likely stepwise model for the evolution of this remarkable gene and discuss alternative scenarios.
Mapping Obfuscation-Based PHY Security Scheme for Resource-Constrained Wireless Sensor Network

ABSTRACT Wireless sensor network (WSN) physical layer (PHY) uses M-ary spread spectrum (MaSS). This paper explores MaSS and emphasizes that based on the implementation approach; the technology has the potential to provide security at the PHY of wireless devices. The MaSS parameters, namely, spreading sequences and symbol to sequence mapping logic, can be obfuscated for security implementation. In this paper, we have focused our analysis on obfuscating mapping logic, i.e. Mapping Obfuscation (MO). Mathematical analysis reveals that an eavesdropper with processing speed in the order of 1018 operations/sec can intercept and decode short length (maximum 8–10 bytes) packets in <100 s. Simulation exposes that the eavesdropper can achieve a success rate of 50% for short-length packets if its signal-to-noise ratio exceeds −1 dB. An attacker has only one check metric for mapping sequence detection that is correct frame check sequence (FCS) detection. However, FCS detection may be misleading; if packet-embedded FCS and eavesdropper-generated FCS are the same for the wrong mapping sequence. For MO-based MaSS, false FCS detection probability is 30 times more than valid FCS detection probability. To reduce false FCS probability attacker need to analyse multiple radio frequency (RF) packets for detecting a valid mapping key; this increases the computation time. For MO-based PHY security, correct mapping sequence identification by exhaustive search demands cluster-based parallel processing.