Miracle-dz/UniFAR-FTUs huggingface dataset:
Tauopathy‐associated PERK alleles are functional hypomorphs that increase neuronal vulnerability to ER stress

&NA; Tauopathies are neurodegenerative diseases characterized by tau protein pathology in the nervous system. EIF2AK3 (eukaryotic translation initiation factor 2 alpha kinase 3), also known as PERK (protein kinase R‐like endoplasmic reticulum kinase), was identified by genome‐wide association study as a genetic risk factor in several tauopathies. PERK is a key regulator of the Unfolded Protein Response (UPR), an intracellular signal transduction mechanism that protects cells from endoplasmic reticulum (ER) stress. PERK variants had previously been identified in Wolcott‐Rallison Syndrome, a rare autosomal recessive metabolic disorder, and these variants completely abrogated the function of PERK's kinase domain or prevented PERK expression. In contrast, the PERK tauopathy risk variants were distinct from the Wolcott‐Rallison variants and introduced missense alterations throughout the PERK protein. The function of PERK tauopathy variants and their effects on neurodegeneration are unknown. Here, we discovered that tauopathy‐associated PERK alleles showed reduced signaling activity and increased PERK protein turnover compared to protective PERK alleles. We found that iPSC‐derived neurons carrying PERK risk alleles were highly vulnerable to ER stress‐induced injury with increased tau pathology. We found that chemical inhibition of PERK in human iPSC‐derived neurons also increased neuronal cell death in response to ER stress. Our results indicate that tauopathy‐associated PERK alleles are functional hypomorphs during the UPR. We propose that reduced PERK function leads to neurodegeneration by increasing neuronal vulnerability to ER stress‐associated damage. In this view, therapies to enhance PERK signaling would benefit at‐risk carriers of hypomorphic alleles.
TDroid: Exposing App Switching Attacks in Android with Control Flow Specialization

The Android multitasking mechanism can be plagued with app switching attacks, in which a malicious app replaces the legitimate top activity of the focused app with one of its own, thus mounting, e.g., phishing and denial-of-service attacks. Existing market-level defenses are still ineffective, as static analysis is fundamentally unable to reason about the intention of an app and dynamic analysis has low coverage. We introduce TDroid, a new market-level approach to detecting app switching attacks. The challenge lies in how to handle a plethora of input-dependent branch predicates (forming an exponential number of paths) that control the execution of the code responsible for launching such attacks. TDroid tackles this challenge by combining static and dynamic analysis to analyze an app without producing any false positives. In its static analysis, TDroid transforms the app into runnable slices containing potentially app switching attacks, one slice per attack. In its dynamic analysis, TDroid executes these slices on an Android phone or emulator to expose their malicious GUIs. The novelty lies in the use of a new trigger-oriented slicing technique in producing runnable slices so that certain input-dependent branch predicates are specialized to execute always some fixed branches. Evaluated with a large set of malware apps, TDroid is shown to outperform the state of the art, by detecting substantially more app switching attacks, in a few minutes per app, on average.
A Multilevel Scheduling MAC Protocol for Underwater Acoustic Sensor Networks(UASN)

Underwater acoustic sensor networks (UASNs) have attracted great attention in recent years and utilizes as a part of oceanic applications. This network has to deal with propagation delay, energy constraints and limited bandwidth which are strenuous for designing a Medium Access Control (MAC) protocol for underwater communication. There also exists an idle channel listening and overhearing problem which sets down the energy into starvation in the contention-based MAC protocols. Alternatively, lengthy time slots and time synchronization equated by schedule-based MAC protocols, outcomes the variable transmission delay and degrades the network performances. To iron out these problems, we propose a cluster-based MAC protocol, tagged as Multilevel Scheduling MAC (MLS-MAC) protocol for UASN in the paper. The cluster head is a decision maker for packet transmission and aids to inflate the lifetime of sensor nodes. To reinforce the channel efficiency, the multilevel scheduling in data phase is initiated with two queues depending on the applications fixed by the cluster head. The simulation result shows that the MLS-MAC has increased the network throughput and has decreased energy consumption.
Tell Them Apart: Distilling Technology Differences from Crowd-Scale Comparison Discussions

Developers can use different technologies for many software development tasks in their work. However, when faced with several technologies with comparable functionalities, it is not easy for developers to select the most appropriate one, as comparisons among technologies are time-consuming by trial and error. Instead, developers can resort to expert articles, read official documents or ask questions in Q&A sites for technology comparison, but it is opportunistic to get a comprehensive comparison as online information is often fragmented or contradictory. To overcome these limitations, we propose the diffTech system that exploits the crowdsourced discussions from Stack Overflow, and assists technology comparison with an informative summary of different comparison aspects. We first build a large database of comparable software technologies by mining tags in Stack Overflow, and locate comparative sentences about comparable technologies with NLP methods. We further mine prominent comparison aspects by clustering similar comparative sentences and represent each cluster with its keywords. The evaluation demonstrates both the accuracy and usefulness of our model and we implement a practical website for public use.
Deep Transfer Learning for Image‐Based Structural Damage Recognition

This article implements the state‐of‐the‐art deep learning technologies for a civil engineering application, namely recognition of structural damage from images. Inspired by ImageNet Challenge and the development of computer hardware, the concept of Structural ImageNet is proposed herein with four naïve baseline recognition tasks: component type identification, spalling condition check, damage level evaluation, and damage type determination. A relatively small number of images (2,000) are selected from the Structural ImageNet and manually labeled according to the four recognition tasks. In order to avoid overfitting, Transfer Learning (TL) based on VGGNet (Visual Geometry Group) is introduced and applied using two different strategies, namely feature extractor and fine‐tuning. Two experiments are designed based on properties of these two strategies to find the relative optimal model parameters and scope of application. Models obtained by both strategies indicate the promising recognition results and different application potentials where feature extractor and fine‐tuning can be respectively used for preliminary analysis and for further improvement. These results also reveal the potential uses of deep TL in image‐based structural damage recognition.
Identifying High-Quality Chinese News Comments Based on Multi-Target Text Matching Model

With the development of information technology, there is an explosive growth in the number of online comment concerning news, blogs and so on. The massive comments are overloaded, and often contain some misleading and unwelcome information. Therefore, it is necessary to identify high-quality comments and filter out low-quality comments. In this work, we introduce a novel task: high-quality comment identification (HQCI), which aims to automatically assess the quality of online comments. First, we construct a news comment corpus, which consists of news, comments, and the corresponding quality label. Second, we analyze the dataset, and find the quality of comments can be measured in three aspects: informativeness, consistency, and novelty. Finally, we propose a novel multi-target text matching model, which can measure three aspects by referring to the news and surrounding comments. Experimental results show that our method can outperform various baselines by a large margin on the news dataset.
Alcohol and the risk of pneumonia: a systematic review and meta-analysis

Objective A systematic review and meta-analysis to estimate the magnitude of the association between alcohol consumption and the risk of community-acquired pneumonia (CAP) in adults was undertaken. Design Systematic review and meta-analysis. Methods Comprehensive searches of Medline, Embase and Web of Science were carried out to identify comparative studies of the association between alcohol intake and CAP between 1985 and 2017. Reference lists were also screened. A random-effects meta-analysis was used to estimate pooled effect sizes. A dose–response meta-analysis was also performed. Results We found 17 papers eligible for inclusion in the review, of which 14 provided results which could be pooled. Meta-analysis of these 14 studies identified an 83% increased risk of CAP among people who consumed alcohol or in higher amounts, relative to those who consumed no or lower amounts of alcohol, respectively (relative risk=1.83, 95% CI 1.30 to 2.57). There was substantial between-study heterogeneity, which was attributable in part to differences in study continent, adjustment for confounders and pneumonia diagnosis (clinical vs death). Dose–response analysis found that for every 10–20 g higher alcohol intake per day, there was an 8% increase in the risk of CAP. Conclusions The findings suggest that alcohol consumption increases the risk of CAP. Therefore, strengthening policies to reduce alcohol intake would be likely to reduce the incidence of CAP.
Removal of mercury(II) from contaminated water by gold-functionalised Fe3O4 magnetic nanoparticles

ABSTRACT Fe3O4 nanoparticles were prepared by co-precipitation of Fe2+ and Fe3+ and then modified with Au to produce an effective adsorbent (Fe3O4/Au) for aqueous Hg(II) in contaminated water. Rietveld refinement on the XRD pattern confirmed that the Fe3O4/Au was synthesised. Mössbauer spectra exhibited broad and asymmetric resonance lines with two sextets which can be assigned to tetrahedral Fe3+; and octahedral Fe3+/Fe2+. The quantitative analysis of magnetite confirms that the sample shows around 3 wt. % Au and 97 wt. % partially oxidised Fe3O4. High surface area: 121 m2 g−1, average pore sizes: 6.3 nm and pore volume: 1.64 cm3 g−1. The kinetics data were better fitted with a pseudo-second-order and Dubinin–Radushkevich isotherm suggests the Hg(II) adsorption onto Fe3O4/Au nanoparticles was mainly by chemical adsorption forming complex with the Au metal immobilised on Fe3O4 surfaces. Adsorption capacity of 79.59 mg g−1. Ionic strength and co-existing ions had a slight influence on the adsorption capacity. GRAPHICAL ABSTRACT
Deletion of GIT1 Impacts eNOS Activity To Aggravate sFlt-1–Induced Preeclampsia Phenotype in Mice

Preeclampsia, a serious multisystem disorder specific to human pregnancy, remains a considerable burden of disease worldwide. Reduced nitric oxide bioavailability is proved to be crucial in the maternal and fetal pathophysiology of preeclampsia. G-protein-coupled Receptor Kinase Interactor-1 (GIT1) is a novel endothelial nitric oxide synthases (eNOS) interactor mediator. The aim of this paper is to investigate the effect of GIT1 on preeclampsia. Blood pressure (BP) was measured using a carotid catheter-calibrated eight-chamber tail-cuff system (CODA) at the same time daily. Urinary albumin excretion (UAE) was determined using Albuwell-M kits (Exocell Inc) and creatinine clearance (CCr) was determined by measuring urinary creatinine concentration with tandem liquid chromatography–mass spectrometry. The release of nitrite was analyzed to detect nitric oxide (NO) production using a Sievers Chemiluminescence NO Analyzer. NOS activity was examined by measuring the conversion of 3H-labeled l-arginine to 3H-labeled l-citrulline. BP was significantly increased in GIT1−/− mice with or without sFIT-1 treatment. In addition, GIT1−/− mice possessed higher UAE and lower CCr. Depletion of GIT1 impedes the NO production and placenta eNOS activity. Additional GIT1 attenuates sFlt-1-induced preeclampsia phenotypes. Our findings suggest that GIT1 significantly extenuates the sFlt-1-induced preeclampsia phenotypes by inhibiting eNOS activity, indicating a crucial role of GIT1 in the progression of preeclampsia.
Language Identification in Code-Mixed Data using Multichannel Neural Networks and Context Capture

An accurate language identification tool is an absolute necessity for building complex NLP systems to be used on code-mixed data. Lot of work has been recently done on the same, but there’s still room for improvement. Inspired from the recent advancements in neural network architectures for computer vision tasks, we have implemented multichannel neural networks combining CNN and LSTM for word level language identification of code-mixed data. Combining this with a Bi-LSTM-CRF context capture module, accuracies of 93.28% and 93.32% is achieved on our two testing sets.
Automated Model Repair for Alloy

Automated program repair is an active research area. However, existing research focuses mostly on imperative code, e.g. in Java. In this paper, we study the problem of repairing declarative models in Alloy - a first order relational logic with transitive closure. We introduce ARepair, the first technique for repairing Alloy models. ARepair follows the spirit of traditional automated program repair techniques. Specifically, ARepair takes as input a faulty Alloy model and a test suite that contains some failing test, and outputs a repaired model that is correct with respect to the given tests. ARepair integrates ideas from mutation testing and program synthesis to provide an effective solution for repairing Alloy models. The experimental results show that ARepair can fix 28 out of 38 real-world faulty models we collected.
Phenotypic Plasticity Promotes Overwintering Survival in A Globally Invasive Crop Pest, Drosophila suzukii

Spotted wing drosophila, Drosophila suzukii Matsumura, is a major pest of small fruit worldwide in temperate and subtropical growing regions. In Northern climates, D. suzukii likely overwinters locally under leaf litter and snow pack, but our understanding of the factors affecting thermal susceptibility is limited. While previous investigations of thermal susceptibility in this species have employed conventional static acclimation protocols, we aimed to determine whether gradual cooling, or dynamic acclimation, may extend the limits of known thermal tolerance by more closely approximating naturally occurring shifts in temperature. First, we assessed survival among adult and pupal D. suzukii using static acclimation. Then, we re-assessed survival using a novel dynamic acclimation method. We found that while static acclimation was sufficient to induce cold tolerance, dynamic acclimation significantly improved survival at temperatures as low as −7.5 °C. Following static acclimation, the lower lethal limit of adult D. suzukii was −1.1 °C in winter morphotype (WM) adults compared to 1.7 °C in non-acclimated summer morphotype (SM) adults. Dynamic acclimation reduced the lower limit to −5 °C in SM flies. At the end of our study 50% of WM flies survived 72 h at −7.5 °C. Below 0 °C pupal survival declined significantly regardless of acclimation procedure. However, pupal acclimation improved survival outcomes significantly compared to non-acclimated pupae, suggesting that while juvenile diapause is unlikely, cold hardening likely benefits those flies which may develop into the overwintering WM population. These data suggest that the degree of cold hardening is proportional to the thermal environment, a finding previously unrecognized in this species. Given the economic impact of this pest, these data may have important implications for offseason population monitoring and management. We discuss how phenotypic plasticity may drive geographical range expansion, and the impact of climate change on the spread of this species.
Automatic Segmentation of MRI Human Thigh Muscles: Combination of Reliable and Fast Framework Methods for Quadriceps, Femur and Marrow Segmentation

This paper outlines the procedure for automated segmentation of human thigh magnetic resonance images. Datasets that included sequential transverse-plane images (approximately 20 sequential images) were used to develop the framework and the images of mid-thigh were selected to establish the segmentation algorithm because these images contain essential parametric and geometric information that represents the subsequent images of the same dataset. Hence, if the mid-thigh can be decomposed accurately, it would significantly improve the prospects of decomposing all remaining transverse images within the dataset. The segmentation framework was designed based on the integration of statistical signal processing and medical imaging algorithms. The results showed good segmentation accuracy and fast processing time.
Automatic Mining of Constraints for Monitoring Systems of Systems

The behavior of complex software-intensive systems of systems often only fully emerges during operation, when all systems interact with each other and with their environment. Runtime monitoring approaches are thus used to detect deviations from the expected behavior, which is commonly defined by engineers, e.g., using temporal logic or domain-specific languages. However, the deep domain knowledge required to specify constraints is often not available during the development of systems of systems with multiple teams independently working on heterogeneous components. In this paper, we thus describe our ongoing PhD research to automatically mine constraints for runtime monitoring from recorded events. Our approach mines constraints on event occurrence, timing, data, and combinations of these properties. The approach further presents the mined constraints to users offering multiple ranking strategies and can also be used to support users in system evolution scenarios.
Kelembagaan Agribisnis pada Desa Berbasis Komoditas Perkebunan

Kelembagaan merupakan organisasi atau kaidah baik formal maupun informal yang mengatur perilaku dan tindakan masyarakat untuk mencapai tujuan tertentu. Dari beberapa hasil kajian, Syahyuti (2006) menyimpulkan bahwa kelembagaan memiliki perhatian utama pada perilaku yang berpola, yang sebagian besar berasal dari norma-norma yang dianut. Kelembagaan berpusat pada tujuan, nilai atau kebutuhan sosial utama. Lebih jauh dikatakan bahwa kelembagaan mengacu kepada suatu prosedur, kepastian, dan panduan untuk melakukan sesuatu. Handayani (2013) menyebutkan bahwa kelembagaan mengandung dua pengertian, yaitu institusi dan nilai/norma: sebuah institusi yang di dalamnya terkandung nilai/norma. Nilai dan norma yang ada dalam institusi inilah yang mengatur jalannya institusi tersebut. Sementara, agribisnis merupakan bisnis dalam sektor pertanian baik dari hulu hingga hilir yang mencakup seluruh aktivitas yang meliputi produksi, penyimpanan, pemasaran, prosesing bahan dasar dari usaha tani, serta suplai input dan penyediaan pelayanan penyuluhan, penelitian, dan kebijakan. Jadi kelembagaan agribisnis adalah institusi yang terkait dengan agribisnis atau bisnis pertanian yang di dalam institusi tersebut terdapat nilai-nilai dan norma yang mengaturnya. Dalam agribisnis lahan kering berbasiskan perkebunan terdapat berbagai kelembagaan di antaranya kelembagaan sarana produksi, kelembagaan pemasaran, dan kelembagaan penyuluhan. Peran kelembagaan petani dalam mendukung keberlanjutan pertanian sangat diperlukan untuk memberikan masukan dan pertimbangan bagi pelaku pembangunan dalam rangka pengembangan ekonomi lokal (Noviatirida, 2011). Dalam melakukan usaha taninya petani mempunyai hubungan kerja dengan lembaga-lembaga pendukungnya, seperti kelompok tani, pedagang saprodi, pedagang hasil pertanian, penyuluh, koperasi, bank, dan pemerintah daerah (Cahyono dan Tjokropandojo, 2012). Lembaga pemasaran dalam distribusi hasil pertanian dalam usaha tani merupakan badan usaha atau individu yang menyelenggarakan pemasaran, menyalurkan jasa dan komoditas pertanian dari produsen kepada konsumen akhir serta memiliki hubungan dengan badan usaha atau individu lainnya. Keberadaan lembaga pemasaran dikarenakan oleh dorongan atau keinginan konsumen untuk mendapatkan komoditas yang sesuai dengan waktu, tempat, dan bentuk yang diinginkan. Timbal Balik dari konsumen adalah memberikan balas jasa kepada lembaga pemasaran berupa margin pemasaran (Zulfahmi, 2012). Makalah ini bertujuan untuk melihat dinamika kelembagaan agribisnis tanaman perkebunan di agroekosistem lahan kering. Kelembagaan agribisnis yang dikaji meliputi kelembagaan sarana produksi, kelembagaan pemasaran, dan kelembagaan kelompok tani dan penyuluhan.
Isoform-specific AMPK association with TBC1D1 is reduced by a mutation associated with severe obesity

AMP-activated protein kinase (AMPK) is a key regulator of cellular and systemic energy homeostasis which achieves this through the phosphorylation of a myriad of downstream targets. One target is TBC1D1 a Rab-GTPase-activating protein that regulates glucose uptake in muscle cells by integrating insulin signalling with that promoted by muscle contraction. Ser237 in TBC1D1 is a target for phosphorylation by AMPK, an event which may be important in regulating glucose uptake. Here, we show AMPK heterotrimers containing the α1, but not the α2, isoform of the catalytic subunit form an unusual and stable association with TBC1D1, but not its paralogue AS160. The interaction between the two proteins is direct, involves a dual interaction mechanism employing both phosphotyrosine-binding (PTB) domains of TBC1D1 and is increased by two different pharmacological activators of AMPK (AICAR and A769962). The interaction enhances the efficiency by which AMPK phosphorylates TBC1D1 on its key regulatory site, Ser237. Furthermore, the interaction is reduced by a naturally occurring R125W mutation in the PTB1 domain of TBC1D1, previously found to be associated with severe familial obesity in females, with a concomitant reduction in Ser237 phosphorylation. Our observations provide evidence for a functional difference between AMPK α-subunits and extend the repertoire of protein kinases that interact with substrates via stabilisation mechanisms that modify the efficacy of substrate phosphorylation.
Cable-Driven Parallel Robot with Reconfigurable End Effector Controlled with a Compliant Actuator

Redundancy in cable-driven parallel robots provides additional degrees of freedom that can be used to achieve different objectives. In this robot, this degree of freedom is used to act on a reconfigurable end effector with one degree of freedom. A compliant actuator actuated by one motor exerts force on both bodies of the platform. Due to the high tension that appears in this cable in comparison with the rest of the cables, an elastic model was developed for solving the kinestostatic and wrench analysis. A linear sensor was used in one branch of this cable mechanism to provide the needed intermediate values. The position of one link of the platform was fixed in order to focus this analysis on the relationship between the cables and the platform’s internal movement. Position values of the reconfigurable end effector were calculated and measured as well as the tension at different regions of the compliant actuator. The theoretical values were compared with dynamic simulations and real prototype results.