Miracle-dz/UniFAR-FTUs huggingface dataset:
The Vibrio H-Ring Facilitates the Outer Membrane Penetration of the Polar Sheathed Flagellum

Flagellum is the major organelle for motility in many bacterial species. While most bacteria possess external flagella, such as the multiple peritrichous flagella found in Escherichia coli and Salmonella enterica or the single polar sheathed flagellum in Vibrio spp. , spirochetes uniquely assemble periplasmic flagella, which are embedded between their inner and outer membranes. Here, we show for the first time that the external flagella in Vibrio alginolyticus can be changed as periplasmic flagella by deleting two flagellar genes. The discovery here may provide new insights into the molecular basis underlying assembly, diversity, and evolution of flagella. ABSTRACT The bacterial flagellum has evolved as one of the most remarkable nanomachines in nature. It provides swimming and swarming motilities that are often essential for the bacterial life cycle and pathogenesis. Many bacteria such as Salmonella and Vibrio species use flagella as an external propeller to move to favorable environments, whereas spirochetes utilize internal periplasmic flagella to drive a serpentine movement of the cell bodies through tissues. Here, we use cryo-electron tomography to visualize the polar sheathed flagellum of Vibrio alginolyticus with particular focus on a Vibrio-specific feature, the H-ring. We characterized the H-ring by identifying its two components FlgT and FlgO. We found that the majority of flagella are located within the periplasmic space in the absence of the H-ring, which are different from those of external flagella in wild-type cells. Our results not only indicate the H-ring has a novel function in facilitating the penetration of the outer membrane and the assembly of the external sheathed flagella but also are consistent with the notion that the flagella have evolved to adapt highly diverse needs by receiving or removing accessary genes. IMPORTANCE Flagellum is the major organelle for motility in many bacterial species. While most bacteria possess external flagella, such as the multiple peritrichous flagella found in Escherichia coli and Salmonella enterica or the single polar sheathed flagellum in Vibrio spp. , spirochetes uniquely assemble periplasmic flagella, which are embedded between their inner and outer membranes. Here, we show for the first time that the external flagella in Vibrio alginolyticus can be changed as periplasmic flagella by deleting two flagellar genes. The discovery here may provide new insights into the molecular basis underlying assembly, diversity, and evolution of flagella.
Envisioning an Endfire Circularly Polarized Antenna: Presenting a Planar Antenna with a Wide Beamwidth and Enhanced Front-to-Back Ratio

We present a design approach to a novel nonturnstile planar endfire circularly polarized (CP) antenna with a widened beamwidth and an enhanced front-to-back ratio. This approach combines a semicircular magnetic dipole and a V-shaped open loop to widen the azimuthal beamwidth at first. Then, to further enhance the front-to-back ratio, the V-shaped loop is appropriately rotated with respect to its feed apex. The tradeoff between the azimuthal beamwidth and the front-to-back ratio is theoretically revealed based on the approximate closed-form radiation pattern functions. Antenna prototypes are simulated accordingly, and they are then designed and measured to validate the design approach. The measured impedance bandwidth for |S<sub>11</sub>| &lt;-10 dB covers a frequency range of 2.25-2.5 GHz (10.5% in fraction), and the axial ratio (AR) bandwidth of &lt;3 dB is 2.3-2.57 GHz (11.1% in fraction). The measured 3-dB AR beamwidths of the proposed antenna are equal to 180&deg; and 115&deg; in the elevational and azimuthal plane, respectively, at 2.35 GHz. In addition, the measured in-band average frontto- back ratio reaches up to 13.7 dB.
Non-Interactive Key Exchange from Identity-Based Encryption

Since the seminal work of Diffie and Hellman [19], Non-Interactive Key Exchange (NIKE) has become one of the fundamental problems of modern cryptography, but additional security requirements have led to elaborated ad-hoc constructions, which often lack simplicity in their design. In particular, Identity-Based NIKE is still a major problem with few available constructions, and those ad-hoc constructions do not give a lot of insight on what is required to be able to achieve such a NIKE scheme only based on the identity (and not relying on the public-key setting). In this work, we focus on the public-key setting and show how to generically build a NIKE scheme using a specific kind of Identity-Based Encryption, while also opening research on a new kind of Identity-Based Key Encapsulation Mechanisms (IBKEM), which we call identity-independent 2-tier IBKEM. As an interesting result, this construction also leads to the first known NIKE construction based on lattices. While most of the instantiations given in this paper lie in the random oracle model, this is not an inherent problem of our generic construction but rather a consequence of the lack of an existing identity-independent 2-tier IBKEM scheme in the standard model. Our proposal thus allows to reduce the problem to the construction of several building blocks, which can be studied independently in order to lead to an instantiation of NIKE in the standard model.
Impact of sharing electronic health records with patients on the quality and safety of care: a systematic review and narrative synthesis protocol

Introduction Providing patients with access to electronic health records (EHRs) has emerged as a promising solution to improve quality of care and safety. As the efforts to develop and implement EHR-based data sharing platforms mature and scale up worldwide, there is a need to evaluate the impact of these interventions and to weigh their relative risks and benefits, in order to inform evidence-based health policies. The aim of this work is to systematically characterise and appraise the demonstrated benefits and risks of sharing EHR with patients, by mapping them across the six domains of quality of care of the Institute of Medicine (IOM) analytical framework (ie, patient-centredness, effectiveness, efficiency, timeliness, equity and safety). Methods and analysis CINAHL, Cochrane, Embase, HMIC, Medline/PubMed and PsycINFO databases will be searched from January 1997 to August 2017. Primary outcomes will include measures related with the six domains of quality of care of the IOM analytical framework. The quality of the studies will be assessed using the Cochrane Risk of Bias Tool, the ROBINS-I Tool and the Drummond’s checklist. A narrative synthesis will be conducted for all included studies. Subgroup analysis will be performed by domain of quality of care domain and by time scale (ie, short-term, medium-term or long-term impact). The body of evidence will be summarised in a Summary of Findings table and its strength assessed according to the GRADE criteria. Ethics and dissemination This review does not require ethical approval as it will summarise published studies with non-identifiable data. This protocol complies with the Preferred Reporting Items for Systematic Review and Meta-Analyses Protocols guidelines. Findings will be disseminated widely through peer-reviewed publication and conference presentations, and patient partners will be included in summarising the research findings into lay summaries and reports. PROSPERO registration number CRD42017070092.
Continuous Moderate-Intensity but Not High-Intensity Interval Training Improves Immune Function Biomarkers in Healthy Young Men.

Khammassi, M, Ouerghi, N, Said, M, Feki, M, Khammassi, Y, Pereira, B, Thivel, D, and Bouassida, A. Continuous moderate-intensity but not high-intensity interval training improves immune function biomarkers in healthy young men. J Strength Cond Res XX(X): 000-000, 2018-Effects of endurance running methods on hematological profile are still poorly known. This study aimed to compare the effects of 2 training regimes; high-intensity interval training (HIIT) and moderate-intensity continuous training (MCT) performed at the same external load on hematological biomarkers in active young men. Sixteen men aged 18-20 years were randomly assigned to HIIT or MCT group. Aerobic capacity and hematological biomarkers were assessed before and after 9 weeks of interventions. At baseline, aerobic and hematological parameters were similar for the 2 groups. After intervention, no significant change was observed in maximal aerobic velocity and estimated V[Combining Dot Above]O2max in both groups. Leukocyte (p < 0.01), lymphocyte (p < 0.05), neutrophil (p < 0.05), and monocyte (p < 0.01) count showed significant improvements in response to the MCT compared with the HIIT intervention. The MCT intervention favored an increase in the number of immune cells, whereas the opposite occurred as a result of the HIIT intervention. These findings suggest that MCT interventions might be superior to HIIT regimes in improving immune function in active young men.
Communication-Aware Module Placement for Power Reduction in Large FPGA Designs

Modern multi-million logic FPGAs allow hardware designers to map increasingly large designs into FPGAs. However, traditional FPGA CAD flows scale poorly for large designs, often producing low quality solutions in terms of performance and power in such cases. To improve the design productivity, modular design methodology partitions a large design into subsystems, compiles them individually and finally collates the individual solutions to complete the mapping process. Existing work has attempted to partition large designs into smaller subsystems, based on the intra-subsystem communication frequencies, to reduce routing power dissipation. However, inter-subsystem communication has not been considered, especially, during the placement stage. In this paper, we first show the adverse effect of ignoring the inter-subsystem communication during the placement stage. Next, we propose an inter-subsystem communication-aware placement technique using a Simulated Annealing based approach to achieve significant power savings. Experimental results show over 7% reduction in routing power when compared to the existing state-of-the-art partitioning flow that does not consider inter-subsystem communication, while the routing power reduction is over 11% when compared to a commercial CAD tool such as Altera Quartus.
Training assistant: strengthen your tactical nous with proficient virtual basketball players

Tactic training plays a crucial role in basketball offensive plays. With the aid of virtual reality, we propose a framework to improve the effectiveness and experience of tactic learning. The framework consists of a tactic input device and a wireless VR interaction system, which allows the user to conveniently input target tactic and practice in a high-fidelity circumstance. By the assistance of our VR training system, the user can vividly experience how the tactics are executed by viewing from the a specific player's viewing direction. Additionally, tactic movement guidance, action hint of how to offense aggressively, and virtual defenders are rendered in our system to make the training more realistic. By using the proposed framework, players can strengthen their tactical nous and improve the efficiency of tactic training.
Stall-Aware Fixed-Point Implementation of LMS Filters

Least-Mean-Square (LMS) is the most popular adaptive filtering algorithm, due to its numerical stability, satisfactory steady-state error and relatively low computational complexity. LMS algorithm is commonly employed in a multitude of tasks such as channel equalization, adaptive noise cancellation, system identification and frequency tracking. Owing to its computational complexity, LMS algorithm is commonly implemented in hardware, in which, due to speed and energy constraints, a fixed-point arithmetic is usually adopted. As shown in the literature, the effects due to fixed-point arithmetic alter the behavior of the algorithm, causing a significant increase in the steady-state error, due to the so-called stall phenomenon. In this paper we propose a novel fixed-point scheme which significantly limits the stalling. This gives increased flexibility to the designer in the choice of the step-size, that controls the tradeoff between convergence rate and steady-state-error. Implementation results in a 40nm CMOS technology are presented in the paper, to assess the impact of the proposed scheme in terms of area, speed and power.
Reinforcement Learning for Build-Order Production in StarCraft II

StarCraft II is one of the most popular real-time strategy games and has become an important benchmark for AI research as it provides a complex environment with numerous challenges. The build order problem is one of the key challenges which concern the order and type of buildings and units to produce based on current game situation. In contrast to existing hand-craft methods, we propose two reinforcement learning based models: Neural Network Fitted Q-Learning (NNFQ) and Convolutional Neural Network Fitted Q-Learning (CNNFQ). NNFQ and CNNFQ have been applied into a simple bot for fighting against the enemy race. Experimental results show that both these two models are capable of finding the most effective production sequence to defeat the opponent.
The Methylation Status of the Epigenome: Its Emerging Role in the Regulation of Tumor Angiogenesis and Tumor Growth, and Potential for Drug Targeting

Approximately 50 years ago, Judah Folkman raised the concept of inhibiting tumor angiogenesis for treating solid tumors. The development of anti-angiogenic drugs would decrease or even arrest tumor growth by restricting the delivery of oxygen and nutrient supplies, while at the same time display minimal toxic side effects to healthy tissues. Bevacizumab (Avastin)—a humanized monoclonal anti VEGF-A antibody—is now used as anti-angiogenic drug in several forms of cancers, yet with variable results. Recent years brought significant progresses in our understanding of the role of chromatin remodeling and epigenetic mechanisms in the regulation of angiogenesis and tumorigenesis. Many inhibitors of DNA methylation as well as of histone methylation, have been successfully tested in preclinical studies and some are currently undergoing evaluation in phase I, II or III clinical trials, either as cytostatic molecules—reducing the proliferation of cancerous cells—or as tumor angiogenesis inhibitors. In this review, we will focus on the methylation status of the vascular epigenome, based on the genomic DNA methylation patterns with DNA methylation being mainly transcriptionally repressive, and lysine/arginine histone post-translational modifications which either promote or repress the chromatin transcriptional state. Finally, we discuss the potential use of “epidrugs” in efficient control of tumor growth and tumor angiogenesis.
The challenge of detecting sophisticated attacks: Insights from SOC Analysts

The ever-increasing rate of sophisticated cyber-attacks and its subsequent impact on networks has remained a menace to the security community. Existing network security solutions, including those applying machine learning algorithms, often centre their detection on the identification of threats in individual network events, which is proven inadequate in detecting sophisticated multi-stage attacks. Similarly, SOC analysts whose roles involve detecting advanced threats are faced with a significant amount of false-positive alerts from the existing tools. Their ability to detect novel attacks or variants of existing ones is limited by the lack of expert input from SOC analysts in their creation of the tools; and the use of features that are closely linked to the structure of specific malware which detection models aim to identify. In this work, we conduct a literature review on malware detection tools, reflect on the features used in these approaches and extend the feature-set with novel ones identified by interviewing experienced SOC analysts. We conduct thematic analysis to the qualitative data obtained from the interviews, and our results indicate not only the presence novel generic malware characteristics based on network and application events (web proxy, firewall, DNS), but identify valuable lessons for developing effective SOCs regarding their structure and processes.
Surface smoothing for enhanced 3D medical visualization

This paper presents four methods for enhancing the visual appearance of surface-rendered anatomical objects while preserving the original geometry and topology of the underlying model. The methods consist of generating normal vectors for each vertex in a surface mesh by image gradient and cross-product operations. THe normal vectors are then modified to alter lighting effects and make the surfaces appear smoother. This is accomplished using various filtering techniques that replace each original vertex normal by a weighted value. Normal vectors affect the visualization of the surface mesh because lighting models utilize the vertex normals when generating an image from a given viewpoint. Our methods alter the normal vectors in order to smooth the surfaces for easier diagnosis using medical images.
Learning Discriminative 3D Shape Representations by View Discerning Networks

In view-based 3D shape recognition, extracting discriminative visual representation of 3D shapes from projected images is considered the core problem. Projections with low discriminative ability can adversely influence the final 3D shape representation. Especially under the real situations with background clutter and object occlusion, the adverse effect is even more severe. To resolve this problem, we propose a novel deep neural network, View Discerning Network, which learns to judge the quality of views and adjust their contributions to the representation of shapes. In this network, a Score Generation Unit is devised to evaluate the quality of each projected image with score vectors. These score vectors are used to weight the image features and the weighted features perform much better than original features in 3D shape recognition task. In particular, we introduce two structures of Score Generation Unit, Channel-wise Score Unit and Part-wise Score Unit, to assess the quality of feature maps from different perspectives. Our network aggregates features and scores in an end-to-end framework, so that final shape descriptors are directly obtained from its output. Our experiments on ModelNet and ShapeNet Core55 show that View Discerning Network outperforms the state-of-the-arts in terms of the retrieval task, with excellent robustness against background clutter and object occlusion.
Fusion of evidential occupancy grids for cooperative perception

In the field of autonomous navigation, perception of the driving scene is one of the essential elements. Existing solutions combine on-board exteroceptive sensors, and are capable of understanding some of the near vehicle’s dynamic surrounding environment. Furthermore, the perception capability of each vehicle can be enhanced by wireless information sharing if vehicles in the neighborhood transmit pertinent information. The primary benefit of such approach is to enable and improve the performance-safety of cooperative autonomous driving. The introduction of such a vehicle-to-vehicle communication leads to think of the global architecture as a system of systems. In this work, we address the task of evidential occupancy grid fusion so that a given vehicle can refine and complete its occupancy grid with the help of grids received from other near vehicles. The communication channel is supposed to be ideal, noiseless with infinite capacity. We focus on the fusion framework itself, using the theory of belief functions for reasoning with uncertainties on the relative poses of the vehicles and on the exchanged sensor measurement data. We evaluate the fusion system with real data acquired on public roads, with two connected vehicles.
Nomenclature of humanized mAbs: Early concepts, current challenges and future perspectives

Nomenclature of monoclonal antibodies traditionally followed a strict scheme indicating target and species information. Because of the rapid advances in this field, emphasized by approval of four humanized and six human antibodies in 2017, the International Nonproprietary Name of new antibodies was updated profoundly by removing the species substem completely. In this review we give an overview about what developments led to the preference of the scientific community towards human-like antibodies. We summarize the major updates in naming schemes that tried to classify antibodies according to their humanization technique or to the final primary sequence and how this led to the erroneous perception to indicate expected immunogenicity. Following the new 2017 nomenclature update, there will not be any information available about the species origin in the names of new antibodies, which emphasizes the need for providing additional supplemental information to the scientific community and develop tools to accurately estimate and control the safety of new monoclonal antibody molecules.
Linking personality and cognition: a meta-analysis

In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the direction of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation among studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship. This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive abilities’.