Miracle-dz/UniFAR-FTUs huggingface dataset:
A Nanobody Targeting Viral Nonstructural Protein 9 Inhibits Porcine Reproductive and Respiratory Syndrome Virus Replication

The pandemic outbreak of PRRS, which is caused by PRRSV, has greatly affected the swine industry. We still lack an efficient vaccine, and it is an immense challenge to control its infection. An intracellularly expressed Nsp9-specific nanobody, Nb6, has been shown to be able to inhibit PRRSV replication in MARC-145 cells. However, its application is limited, because Nb6 cannot physically enter cells. Here, we demonstrated that the cell-penetrating peptide TAT could deliver Nb6 into cultured cells. In addition, TAT-Nb6 fusion protein could suppress the replication of various PRRSV strains in MARC-145 cells and PAMs. These findings may provide a new approach for drug development to control PRRS. ABSTRACT Porcine reproductive and respiratory syndrome (PRRS) is of great concern to the swine industry due to pandemic outbreaks of the disease, current ineffective vaccinations, and a lack of efficient antiviral strategies. In our previous study, a PRRSV Nsp9-specific nanobody, Nb6, was successfully isolated, and the intracellularly expressed Nb6 could dramatically inhibit PRRSV replication in MARC-145 cells. However, despite its small size, the application of Nb6 protein in infected cells is greatly limited, as the protein itself cannot enter the cells physically. In this study, a trans-activating transduction (TAT) peptide was fused with Nb6 to promote protein entry into cells. TAT-Nb6 was expressed as an inclusion body in Escherichia coli, and indirect enzyme-linked immunosorbent assays and pulldown assays showed that E. coli-expressed TAT-Nb6 maintained the binding ability to E. coli-expressed or PRRSV-encoded Nsp9. We demonstrated that TAT delivered Nb6 into MARC-145 cells and porcine alveolar macrophages (PAMs) in a dose- and time-dependent manner, and TAT-Nb6 efficiently inhibited the replication of several PRRSV genotype 2 strains as well as a genotype 1 strain. Using a yeast two-hybrid assay, Nb6 recognition sites were identified in the C-terminal part of Nsp9 and spanned two discontinuous regions (Nsp9aa454–551 and Nsp9aa599–646). Taken together, these results suggest that TAT-Nb6 can be developed as an antiviral drug for the inhibition of PRRSV replication and controlling PRRS disease. IMPORTANCE The pandemic outbreak of PRRS, which is caused by PRRSV, has greatly affected the swine industry. We still lack an efficient vaccine, and it is an immense challenge to control its infection. An intracellularly expressed Nsp9-specific nanobody, Nb6, has been shown to be able to inhibit PRRSV replication in MARC-145 cells. However, its application is limited, because Nb6 cannot physically enter cells. Here, we demonstrated that the cell-penetrating peptide TAT could deliver Nb6 into cultured cells. In addition, TAT-Nb6 fusion protein could suppress the replication of various PRRSV strains in MARC-145 cells and PAMs. These findings may provide a new approach for drug development to control PRRS.
Off-chaining Models and Approaches to Off-chain Computations

Off-chaining has been suggested to enhance scalablity and privacy of blockchains, especially in public networks. However, a systematic classification is missing. In this paper, we propose generic off-chaining models categorizing different types of off-chaining. From our analysis of these models, we conclude that off-chain computations are particularly powerful and subsequently provide a description and comparison of off-chain computation approaches.
Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG

Modelling and exploiting teammates' policies in cooperative multi-agent systems have long been an interest and also a big challenge for the reinforcement learning (RL) community. The interest lies in the fact that if the agent knows the teammates' policies, it can adjust its own policy accordingly to arrive at proper cooperations; while the challenge is that the agents' policies are changing continuously due to they are learning concurrently, which imposes difficulty to model the dynamic policies of teammates accurately. In this paper, we present \emph{ATTention Multi-Agent Deep Deterministic Policy Gradient} (ATT-MADDPG) to address this challenge. ATT-MADDPG extends DDPG, a single-agent actor-critic RL method, with two special designs. First, in order to model the teammates' policies, the agent should get access to the observations and actions of teammates. ATT-MADDPG adopts a centralized critic to collect such information. Second, to model the teammates' policies using the collected information in an effective way, ATT-MADDPG enhances the centralized critic with an attention mechanism. This attention mechanism introduces a special structure to explicitly model the dynamic joint policy of teammates, making sure that the collected information can be processed efficiently. We evaluate ATT-MADDPG on both benchmark tasks and the real-world packet routing tasks. Experimental results show that it not only outperforms the state-of-the-art RL-based methods and rule-based methods by a large margin, but also achieves better performance in terms of scalability and robustness.
DDS: Deadlock Detector and Solver

Deadlock is among the most complex problems that affect the reliability of concurrent programs such as real-time operating systems. Deadlocks occur when multiple processes or threads are mutually blocked while holding a resource required by another process or thread. Current deadlock detection methods are typically based on timeout mechanisms. Recovery from deadlocks frequently involves the rollback of computations, resulting in significant delays. Here we discuss Deadlock Detector and Solver (DDS), which can rapidly detect and resolve circular deadlocks in Java programs. The DDS uses a supervisory controller, which monitors program execution and automatically detects the deadlocks resulting from the hold-and-wait cycles in Java locks. When a deadlock is detected, the DDS uses a preemptive strategy to break it. We use static analysis to assist DDS when selecting the Java thread to be preempted. Our empirical results show that the DDS can monitor program execution and resolve deadlocks without significant runtime overhead.
Improvements on the Interfacial Properties of High-k/Ge MIS Structures by Inserting a La2O3 Passivation Layer

In this paper, the impact of La2O3 passivation layers on the interfacial properties of Ge-based metal-insulator-semiconductor (MIS) structures was investigated. It was proven that the formation of a thermodynamically stable LaGeOx component by incorporating a La2O3 interlayer could effectively suppress desorption of the interfacial layer from GeO2 to volatile GeO. The suppression of GeO desorption contributed to the decrease in oxide trapped charges and interfacial traps in the bulk of the gate insulator, or the nearby interfacial regions in the Al2O3/La2O3/Ge structure. Consequently, the hysteretic behavior of the dual-swept capacitance-voltage (C-V) curves and the frequency dispersion of multi-frequency C-V curves were remarkably weakened. Besides, more than one order of magnitude decrease in the gate leakage current density, and higher insulator breakdown electric field were obtained after inserting a La2O3 passivation layer.
Pervasive allele-specific regulation on RNA decay in hybrid mice

Using a F1 hybrid mouse system, this study globally investigates the effects of cis-regulatory divergence on RNA decay in mammals and reveals the evolutionary roles of RNA decay regulation. Cellular RNA abundance is determined by both RNA transcription and decay. Therefore, change in RNA abundance, which can drive phenotypic diversity between different species, could arise from genetic variants affecting either process. However, previous studies in the evolution of RNA expression have been largely focused on transcription. Here, to globally investigate the effects of cis-regulatory divergence on RNA decay in mammals for the first time, we quantified allele-specific differences in RNA decay rates (ASD) in an F1 hybrid mouse. Out of 8,815 genes with sufficient data, we identified 621 genes exhibiting significant cis-divergence. Systematic analysis of these genes revealed that the genetic variants affecting microRNA binding and RNA secondary structures contribute to the observed divergences. Finally, we demonstrated that although the divergences in RNA abundance were predominantly determined by allelic differences in RNA transcription, most genes with significant ASD did not exhibit significant difference in RNA abundance. For these genes, the apparently compensatory effect between the allelic differences in RNA transcription and ASD suggests that changes in RNA decay could serve as important means to stabilize RNA abundances during mammalian evolution.
Electrocardiogram Fiducial Points Detection for Health Care Systems

Cardiovascular diseases (CVD) are the leading cause of death in the world, representing almost 31\% of global deaths. Therefore, continuous research on early diagnosis methods has been made to achieve more effective treatments of CVDs. Electro-cardiogram (ECG) stands as the most common technique used to monitor cardiac variations. In ECG, five key points (a.k.a. fiducial points) correspond to the wave peaks P, Q, R, S, and T, whereby anomalies in the relative positions of these fiducial points indicate a potential CVD. Thus, a real-time decision support system capable of detecting ECG fiducial points is of paramount importance to early treatment. This paper proposes a real-time method to identify fiducial points in ECGs leveraging for this moving averages and heuristics. The performance comparison between the proposed method applied to the MIT-BIH Arrhythmia Database over other relevant methods found in the literature has been carried out. Results show that the proposed method outperforms the other techniques concerning both accuracy and computational cost impact.
A Feasibility Study of Watchdogs on Opportunistic Mobile Networks

-Detection of selfish behavior is crucial to the proper functioning of opportunistic mobile networks operations. Previous works focused on developing reputation systems or trust models. However, these approaches assume the existence of an efficient model for detecting selfish nodes, such as watchdogs. Moreover, other studies do not present an experimental analysis of the efficiency of the watchdog implementation. This article discusses the design, implementation, and validation of a watchdog, in order to verify the effectiveness of the detection process and to understand the effects of this mechanism for increasing density of messages in the network. We tested the proposed watchdog with two different mobility traces, with a low and a high contact density. The analysis of true positives present a very promising result for watchdog evaluation on real opportunistic mobile networks. However, our results showed that the implementation of watchdog may present some issues related to how false positives were detected during the monitoring and in case that the number of contacts increases. To handle this, we propose an acknowledgement mechanism to increase the reliability of false positive detections and the results improved above 68{\% in both traces. Our results also present a brief study of congestion control and, even with a congestion control of six hours, the results remain virtually unchanged, so that staying with forwarding information for a long time does not affect reliability. The improvement in the number of messages relayed was above 35{\% for both traces.
Identification of New Sources of Resistance to Wheat Stem Rust in Aegilops spp. in the Tertiary Genepool of Wheat

Recent stem rust epidemics in eastern Africa and elsewhere demonstrated that wheat stem rust is a re-emerging disease posing a threat to wheat production worldwide. The cultivated wheat gene pool has a narrow genetic base for resistance to virulent races, such as races in the Ug99 race group. Wild relatives of wheat are a tractable source of stem rust resistance genes. Aegilops species in the tertiary genepool have not been exploited to any great extent as a source of stem rust resistance. We evaluated 1,422 accessions of Aegilops spp. for resistance to three highly virulent races (TTKSK, TRTTF, and TTTTF) of Puccinia graminis f. sp. tritici. Species studied include Ae. biuncialis, Ae. caudata, Ae. comosa, Ae. cylindrica, Ae. geniculata, Ae. neglecta, Ae. peregrina, Ae. triuncialis, and Ae. umbellulata that do not share common genomes with cultivated wheat. High frequencies of resistance were observed as 977 (68.8%), 927 (65.2%), and 850 (59.8%) accessions exhibited low infection types to races TTKSK, TTTTF, and TRTTF, respectively. Contingency table analyses showed strong association for resistance to different races in several Aegilops spp. , indicating that for a given species, the resistance genes effective against multiple races. Inheritance studies in selected accessions showed that resistance to race TTKSK is simply inherited.
Scalability of Real-Time IoT-based Applications for Smart Cities

The Internet of Things (IoT) is getting momentum, which drives us to design solutions able to deal with huge amounts of data coming from different sorts of sensors in order to make decisions to adapt system behavior automatically. While in recent years many IoT-based reasoning systems have already been proposed, there are no comprehensive results reporting their performance, particularly in complex environments. As an answer to that challenge, developers often choose an architecture design based on previous experience that have an impact on the system performance and scalability. This paper shows experimental results of a performance analysis study of different implementations of context-aware management architectures for IoT-based smart cities. Results show that different architectural choices affect system scalability and that automatic real time decision-making is feasible in an environment composed of dozens of thousands of sensors continuously transmitting data.
Enablers and barriers in accessing sexual and reproductive health services among visually impaired women in the Ashanti and Brong Ahafo Regions of Ghana

Abstract The need to improve the sexual and reproductive health (SRH) and rights of women with disabilities is increasingly acknowledged. Unfortunately, women with disabilities in low- and middle-income settings, including Ghana, face several barriers (including structural, financial, physical, social and attitudinal) to accessing SRH services and care. This paper explores the enablers and barriers to accessing SRH services and care among visually impaired women in the Ashanti and Brong Ahafo Regions of Ghana. Qualitative data from in-depth interviews and focus group discussions were collected from 21 visually impaired women, selected through purposive and snowballing sampling techniques. Thematic analysis was used to develop codes, and data were further grouped into emerging themes. The barriers to accessing SRH services and care were financial difficulties and lack of preferential treatment. The enablers which facilitated access to SRH services and care were the support provided by caregivers and friendly relationships with health providers. To address these challenges and promote access, SRH related policies, services and programmes should be inclusive of the needs of visually impaired women, and measures to remove financial challenges to service utilisation and foster positive relationships with health workers, church and community members should be adopted.
GPU Acceleration of the Most Apparent Distortion Image Quality Assessment Algorithm

The primary function of multimedia systems is to seamlessly transform and display content to users while maintaining the perception of acceptable quality. For images and videos, perceptual quality assessment algorithms play an important role in determining what is acceptable quality and what is unacceptable from a human visual perspective. As modern image quality assessment (IQA) algorithms gain widespread adoption, it is important to achieve a balance between their computational efficiency and their quality prediction accuracy. One way to improve computational performance to meet real-time constraints is to use simplistic models of visual perception, but such an approach has a serious drawback in terms of poor-quality predictions and limited robustness to changing distortions and viewing conditions. In this paper, we investigate the advantages and potential bottlenecks of implementing a best-in-class IQA algorithm, Most Apparent Distortion, on graphics processing units (GPUs). Our results suggest that an understanding of the GPU and CPU architectures, combined with detailed knowledge of the IQA algorithm, can lead to non-trivial speedups without compromising prediction accuracy. A single-GPU and a multi-GPU implementation showed a 24× and a 33× speedup, respectively, over the baseline CPU implementation. A bottleneck analysis revealed the kernels with the highest runtimes, and a microarchitectural analysis illustrated the underlying reasons for the high runtimes of these kernels. Programs written with optimizations such as blocking that map well to CPU memory hierarchies do not map well to the GPU’s memory hierarchy. While compute unified device architecture (CUDA) is convenient to use and is powerful in facilitating general purpose GPU (GPGPU) programming, knowledge of how a program interacts with the underlying hardware is essential for understanding performance bottlenecks and resolving them.
Sulfotransferase and Heparanase: Remodeling Engines in Promoting Virus Infection and Disease Development

An extraordinary binding site generated in heparan sulfate (HS) structures, during its biosynthesis, provides a unique opportunity to interact with multiple protein ligands including viral proteins, and therefore adds tremendous value to this master molecule. An example of such a moiety is the sulfation at the C3 position of glucosamine residues in HS chain via 3-O sulfotransferase (3-OST) enzymes, which generates a unique virus-cell fusion receptor during herpes simplex virus (HSV) entry and spread. Emerging evidence now suggests that the unique patterns in HS sulfation assist multiple viruses in invading host cells at various steps of their life cycles. In addition, sulfated-HS structures are known to assist in invading host defense mechanisms and initiating multiple inflammatory processes; a critical event in the disease development. All these processes are detrimental for the host and therefore raise the question of how HS-sulfation is regulated. Epigenetic modulations have been shown to be implicated in these reactions during HSV infection as well as in HS modifying enzyme sulfotransferases, and therefore pose a critical component in answering it. Interestingly, heparanase (HPSE) activity is shown to be upregulated during virus infection and multiple other diseases assisting in virus replication to promote cell and tissue damage. These phenomena suggest that sulfotransferases and HPSE serve as key players in extracellular matrix remodeling and possibly generating unique signatures in a given disease. Therefore, identifying the epigenetic regulation of OST genes, and HPSE resulting in altered yet specific sulfation patterns in HS chain during virus infection, will be a significant a step toward developing potential diagnostic markers and designing novel therapies.
Dynamic Random Testing Strategy for Test Case Optimization in Cloud Environment

Dynamic Random Testing (DRT) strategy employs feedback mechanism to guide the selection of test cases, which has shown to be effective in fault detection process. Cloud testing is the combination of cloud computing and software testing, in which the parallel mechanism is introduced to handle multiple test tasks simultaneously. The efficiency of DRT can be improved by combining it into cloud environment. However, it faces challenges in cloud testing as its test cases are selected sequentially, which does not consist with the characteristic of parallelism underlying cloud testing. In this paper, we present a cloud-based DRT strategy to adapt DRT in cloud testing, in which both the test case prioritization and resource allocation are considered. The results of the experiments show that the cloud-based DRT can improve the efficiency of original DRT and provide stable fault detection performance enhancement over other testing strategies.
Latency Analysis of UAV based Communication Networks

UAV based communication is gaining more and more interest in both research and industry. On top of all benefits gained by using UAVs, we investigate in this paper the effect of using UAV communication on the user experienced latency in cellular systems. In particular, we focus on the queuing delay component of latency, and compare the resulting delay when using a UAV base station as compared to a standard ground base station. Numerical results show the advantage of using UAVs in reducing the delay due to the enhanced LOS in the channel, even at a fraction of the transmit power used. Moreover, the results show the need to optimize the height of the UAV based on the user location.
Characterization of Arginine Catabolism by Lactic Acid Bacteria Isolated from Kimchi

Kimchi fermentation depends on diverse lactic acid bacteria, which convert raw materials into numerous metabolites that contribute to the taste of food. Amino acids and saccharides are important primary metabolites. Arginine is nearly exhausted during kimchi fermentation, whereas the concentrations of other amino acids are reported not to increase or decrease dramatically. These phenomena could imply that arginine is an important nutritional component among the amino acids during kimchi fermentation. In this study, we investigated the arginine-catabolism pathway of seven lactic acid bacteria isolated from kimchi and evaluated the products of arginine catabolism (citrulline and ornithine) associated with the bacteria. The arginine content dramatically decreased in cultures of Lactobacillus brevis and Weissella confusa from 300 μg/mL of arginine to 0.14 ± 0.19 and 1.3 ± 0.01 μg/mL, respectively, after 6 h of cultivation. Citrulline and ornithine production by L. brevis and W. confusa showed a pattern that was consistent with arginine catabolism. Interestingly, Pediococcus pentosaceus, Lactobacillus plantarum, Leuconostoc mesenteroides, and Leuconostoc lactis did not show increased citrulline levels after arginine was added. The ornithine contents were higher in all bacteria except for L. lactis after adding arginine to the culture. These results were consistent with the absence of the arginine deiminase gene among the lactic acid bacteria. Arginine consumption and ornithine production were monitored and compared with lactic acid bacteria by metagenomics analysis, which showed that the increment of ornithine production correlated positively with lactic acid bacteria growth.