Miracle-dz/UniFAR-FTUs huggingface dataset:
Cataract-associated connexin 46 mutation alters its interaction with calmodulin and function of hemichannels

Connexin channels help maintain eye lens homeostasis and transparency. The G143R missense substitution in connexin (Cx) 46 is associated with congenital Coppock cataracts; however, the underlying molecular mechanism is largely unknown. Here, we report that compared with WT Cx46, the G143R substitution abolishes hemichannel conductance in Xenopus oocytes and in HeLa cells. Moreover, this substitution is dominant-negative and inhibits conductance of WT Cx46. CD analysis indicated that the substitution greatly reduces the α-helical structure of the intracellular Cx46 loop domain. Protein pulldown assays and isothermal titration calorimetry revealed that this Cx46 domain directly interacts with calmodulin (CaM) in a Ca2+-dependent fashion, an observation confirmed by immunofluorescent co-localization of Cx46 with CaM. Interestingly, the G143R substitution enhanced the Cx46–CaM interaction and attenuated its abolishment by Ca2+ depletion. Moreover, Cx46 increased dye influx, and the G143R substitution augmented this effect. Inhibition of Ca2+-mediated CaM activation blocked hemichannel permeability. The membrane potential plays a crucial role in Cx46 membrane permeability. We found that the activity of hemichannels is detectable under rest and hyperpolarization conditions but is eliminated with depolarization. These results suggested that the G143R substitution impairs voltage-dependent electrical conductance and alters membrane permeability mediated by Cx46 hemichannels. The latter likely is caused by the substitution-induced structural changes of the intracellular loop domain associated with the increased interaction with CaM and reduced Ca2+ sensitivity. The data suggest that the G143R-induced enhancement of the CaM–Cx46 interaction results in altered hemichannel activities and might be related to cataract formation.
On branching rules for convex mixed-integer nonlinear optimization

Branch-and-Bound (B&B) is perhaps the most fundamental algorithm for the global solution of convex Mixed-Integer Nonlinear Programming (MINLP) problems. It is well-known that carrying out branching in a nonsimplistic manner can greatly enhance the practicality of B&B in the context of Mixed-Integer Linear Programming (MILP). No detailed study of branching has heretofore been carried out for MINLP. In this article, we study and identify useful sophisticated branching methods for MINLP, including novel approaches based on approximations of the nonlinear relaxations by linear and quadratic programs.
Characterizing and Measuring Maliciousness for Cybersecurity Risk Assessment

Cyber attacks have been increasingly detrimental to networks, systems, and users, and are increasing in number and severity globally. To better predict system vulnerabilities, cybersecurity researchers are developing new and more holistic approaches to characterizing cybersecurity system risk. The process must include characterizing the human factors that contribute to cyber security vulnerabilities and risk. Rationality, expertise, and maliciousness are key human characteristics influencing cyber risk within this context, yet maliciousness is poorly characterized in the literature. There is a clear absence of literature pertaining to human factor maliciousness as it relates to cybersecurity and only limited literature relating to aspects of maliciousness in other disciplinary literatures, such as psychology, sociology, and law. In an attempt to characterize human factors as a contribution to cybersecurity risk, the Cybersecurity Collaborative Research Alliance (CSec-CRA) has developed a Human Factors risk framework. This framework identifies the characteristics of an attacker, user, or defender, all of whom may be adding to or mitigating against cyber risk. The maliciousness literature and the proposed maliciousness assessment metrics are discussed within the context of the Human Factors Framework and Ontology. Maliciousness is defined as the intent to harm. Most maliciousness cyber research to date has focused on detecting malicious software but fails to analyze an individual’s intent to do harm to others by deploying malware or performing malicious attacks. Recent efforts to identify malicious human behavior as it relates to cybersecurity, include analyzing motives driving insider threats as well as user profiling analyses. However, cyber-related maliciousness is neither well-studied nor is it well understood because individuals are not forced to expose their true selves to others while performing malicious attacks. Given the difficulty of interviewing malicious-behaving individuals and the potential untrustworthy nature of their responses, we aim to explore the maliciousness as a human factor through the observable behaviors and attributes of an individual from their actions and interactions with society and networks, but to do so we will need to develop a set of analyzable metrics. The purpose of this paper is twofold: (1) to review human maliciousness-related literature in diverse disciplines (sociology, economics, law, psychology, philosophy, informatics, terrorism, and cybersecurity); and (2) to identify an initial set of proposed assessment metrics and instruments that might be culled from in a future effort to characterize human maliciousness within the cyber realm. The future goal is to integrate these assessment metrics into holistic cybersecurity risk analyses to determine the risk an individual poses to themselves as well as other networks, systems, and/or users.
Implementation and Operational Research: A Cost-Effective, Clinically Actionable Strategy for Targeting HIV Preexposure Prophylaxis to High-Risk Men Who Have Sex With Men

Background:Preexposure prophylaxis (PrEP) is effective at preventing HIV infection among men who have sex with men (MSM), but there is uncertainty about how to identify high-risk MSM who should receive PrEP. Methods:We used a mathematical model to assess the cost-effectiveness of using the HIV Incidence Risk Index for MSM (HIRI-MSM) questionnaire to target PrEP to high-risk MSM. We simulated strategies of no PrEP, PrEP available to all MSM, and eligibility thresholds set to HIRI-MSM scores between 5 and 45, in increments of 5 (where a higher score predicts greater HIV risk). Based on the iPrEx, IPERGAY, and PROUD trials, we evaluated PrEP efficacies from 44% to 86% and annual costs from $5900 to 8700. We designate strategies with incremental cost-effectiveness ratio (ICER) ⩽$100,000/quality-adjusted life-year (QALY) as “cost-effective. ” Results:Over 20 years, making PrEP available to all MSM is projected to prevent 33.5% of new HIV infections, with an ICER of $1,474,000/QALY. Increasing the HIRI-MSM score threshold reduces the prevented infections, but improves cost-effectiveness. A threshold score of 25 is projected to be optimal (most QALYs gained while still being cost-effective) over a wide range of realistic PrEP efficacies and costs. At low cost and high efficacy (IPERGAY), thresholds of 15 or 20 are optimal across a range of other input assumptions; at high cost and low efficacy (iPrEx), 25 or 30 are generally optimal. Conclusions:The HIRI-MSM provides a clinically actionable means of guiding PrEP use. Using a score of 25 to determine PrEP eligibility could facilitate cost-effective use of PrEP among high-risk MSM who will benefit from it most.
Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks

Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller’s direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20–40% while ensuring feasible data delay.
Photo-Doped Active Electrically Controlled Terahertz Modulator

We demonstrate an electric-controlled terahertz(THz) modulator which can be used to realize amplitude modulation of terahertz waves with slight photo-doping. The THz pulse transmission was efficiently modulated by electrically controlling the monolayer silicon-based device. The modulation depth reached 100% almost when the applied voltage was 7V at an external laser intensity of 0.6W/cm2. The saturation voltage reduced with the increase of the photo-excited intensity. In a THz continuous wave(CW)system, a significant fall in both THz transmission and reflection was also observed with the increase of applied voltage. This reduction in the THz transmission and reflection was induced by the absorption for electron injection. The results show that a high-efficiency and high modulation depth broadband electric-controlled terahertz modulator in a pure Si structure has been realized.
Environmental constraints on the compositional and phylogenetic beta‐diversity of tropical forest snake assemblages

The ongoing biodiversity crisis increases the importance and urgency of studies addressing the role of environmental variation on the composition and evolutionary history of species assemblages, but especially the tropics and ectotherms remain understudied. In regions with rainy summers, coexistence of tropical ectothermic species may be determined by the partitioning of the climatic niche, as ectotherms can rely on water availability and thermoregulatory behaviour to buffer constraints along their climatic niche. Conversely, tropical ectotherms facing dry summers would have fewer opportunities to climatic niche partitioning and other processes rather than environmental filtering would mediate species coexistence. We used 218 snake assemblages to quantify the compositional (CBD) and phylogenetic (PBD) beta-diversity of snakes in the Atlantic Forest (AF) hotspot, South America. We identify two AF regions with distinct climatological regimes: dry summers in the northern-AF and rainy summers in the southern-AF. While accounting for the influence of multiscale spatial processes, we disentangle the relative contribution of thermal, water-related and topographic conditions in structuring the CBD and PBD of snake assemblages, and determine the extent in which snake assemblages under distinct climatological regimes are affected by environmental filtering. Thermal conditions best explain CBD and PBD of snakes for the whole AF, whereas water-related factors best explain the structure of snake assemblages within a same climatological regime. CBD and PBD patterns are similarly explained by spatial factors but snake assemblages facing dry summers are more affected by spatial processes operating at fine to intermediate spatial scale, whereas those assemblages in regions with rainy summers have a stronger signature of coarse-scale processes. As expected, environmental filtering plays a stronger role in southern-AF than northern-AF, and the synergism between thermal and water-related conditions is the key cause behind this difference. Differences in climatological regimes within the tropics affect processes mediating species coexistence. The influence of broad-scale gradients (e.g. temperature and precipitation) in structuring tropical ectothermic assemblages is greater in regions with rainy summers where climatic niche partitioning is more likely. Our findings highlight the potential stronger role of biotic interactions and neutral processes in structuring ectothermic assemblages facing changes towards warmer and dryer climates.
Assembly and ecological function of the root microbiome across angiosperm plant species

Significance Microbial communities living on and within plants and animals contribute to host function. How host evolution shapes associated microbial communities, and in turn, how these microbes affect the ecology of their hosts is relatively unknown. Here, we demonstrate that evolution occurring across plant species affects root microbial diversity and composition. Greater similarity in root microbiota among host plant species leads to reduced plant performance through negative soil feedbacks. Additionally, drought shifts the composition of root microbiomes, where changes in the relative abundance of specific bacterial taxa are associated with increased drought tolerance of plants. Our work highlights the potential role of host-associated microbial communities in mediating interactions between hosts and their biotic and abiotic environment. Across plants and animals, host-associated microbial communities play fundamental roles in host nutrition, development, and immunity. The factors that shape host–microbiome interactions are poorly understood, yet essential for understanding the evolution and ecology of these symbioses. Plant roots assemble two distinct microbial compartments from surrounding soil: the rhizosphere (microbes surrounding roots) and the endosphere (microbes within roots). Root-associated microbes were key for the evolution of land plants and underlie fundamental ecosystem processes. However, it is largely unknown how plant evolution has shaped root microbial communities, and in turn, how these microbes affect plant ecology, such as the ability to mitigate biotic and abiotic stressors. Here we show that variation among 30 angiosperm species, which have diverged for up to 140 million years, affects root bacterial diversity and composition. Greater similarity in root microbiomes between hosts leads to negative effects on plant performance through soil feedback, with specific microbial taxa in the endosphere and rhizosphere potentially affecting competitive interactions among plant species. Drought also shifts the composition of root microbiomes, most notably by increasing the relative abundance of the Actinobacteria. However, this drought response varies across host plant species, and host-specific changes in the relative abundance of endosphere Streptomyces are associated with host drought tolerance. Our results emphasize the causes of variation in root microbiomes and their ecological importance for plant performance in response to biotic and abiotic stressors.
Individual aptitude in Mandarin lexical tone perception predicts effectiveness of high-variability training

Although the high-variability training method can enhance learning of non-native speech categories, this can depend on individuals’ aptitude. The current study asked how general the effects of perceptual aptitude are by testing whether they occur with training materials spoken by native speakers and whether they depend on the nature of the to-be-learned material. Forty-five native Dutch listeners took part in a 5-day training procedure in which they identified bisyllabic Mandarin pseudowords (e.g., asa) pronounced with different lexical tone combinations. The training materials were presented to different groups of listeners at three levels of variability: low (many repetitions of a limited set of words recorded by a single speaker), medium (fewer repetitions of a more variable set of words recorded by three speakers), and high (similar to medium but with five speakers). Overall, variability did not influence learning performance, but this was due to an interaction with individuals’ perceptual aptitude: increasing variability hindered improvements in performance for low-aptitude perceivers while it helped improvements in performance for high-aptitude perceivers. These results show that the previously observed interaction between individuals’ aptitude and effects of degree of variability extends to natural tokens of Mandarin speech. This interaction was not found, however, in a closely matched study in which native Dutch listeners were trained on the Japanese geminate/singleton consonant contrast. This may indicate that the effectiveness of high-variability training depends not only on individuals’ aptitude in speech perception but also on the nature of the categories being acquired.
A Systematic Study on Explicit-State Non-Zenoness Checking for Timed Automata

Zeno runs, where infinitely many actions occur within finite time, may arise in Timed Automata models. Zeno runs are not feasible in reality and must be pruned during system verification. Thus it is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as counterexamples during model checking. Existing approaches on non-Zenoness checking include either introducing an additional clock in the Timed Automata models or additional accepting states in the zone graphs. In addition, there are approaches proposed for alternative timed modeling languages, which could be generalized to Timed Automata. In this work, we investigate the problem of non-Zenoness checking in the context of model checking LTL properties, not only evaluating and comparing existing approaches but also proposing a new method. To have a systematic evaluation, we develop a software toolkit to support multiple non-Zenoness checking algorithms. The experimental results show the effectiveness of our newly proposed algorithm, and demonstrate the strengths and weaknesses of different approaches.
Synthesis of Ag/PANI Core Shell Nanocomposites Using Ionizing Radiation

Silver/polyaniline (Ag/PANI) nanocomposites were prepared by γ-irradiation oxidative polymerization of aniline monomer in the presence of ammonium persulfate. Ultraviolet/visible absorption shows the formation and growth of irradiated Ag nanoparticles within the PANI matrix. The transmission electron microscopic image of irradiated PANI-coated Ag nanoparticles indicated a spherical shape with a particle size of 25–30 nm. The X-ray diffraction patterns indicated that PANI is amorphous and has a broad band centered at 2θ = 25.5o, and the crystalline phase of Ag nanoparticles is face cubic with a crystallite size of 22–26 nm. DC conductivities of pure PANI and Ag/PANI nanocomposites show that the DC electrical conductivity of the irradiated Ag/PANI nanocomposites is higher than that of pure PANI. Catalytic evaluation of Ag/PANI nanocomposites shows that the composite is a successive catalyst for the reduction of 4-nitrophenol.
Controlling the crucible: a novel PvP recommender systems framework for destiny

Compared to conventional retail games, today's Massively Multiplayer Online Games (MMOGs) have become progressively more complex and volatile, living in a highly competitive market. Consumable resources in such games are nearly unlimited, making decisions to improve levels of engagement more challenging. Intelligent information filtering methods here can help players make smarter decisions, thereby improving performance, increasing level of engagement, and reducing the likelihood of early departure. In this paper, a novel approach towards building a hybrid multi-profile based recommender system for player-versus-player (PvP) content in the MMOG Destiny is presented. The framework groups the players based on three distinct traced behavioral aspects: base stats, cooldown stats, and weapon playstyle. Different combinations of these profiles are considered to make behavioral recommendations. An online evaluation was performed to investigate the usefulness of the proposed recommender framework to players of Destiny.
Novel Transcriptional Activity and Extensive Allelic Imbalance in the Human MHC Region

The MHC region encodes HLA genes and is the most complex region in the human genome. The extensively polymorphic nature of the HLA hinders accurate localization and functional assessment of disease risk loci within this region. Using targeted capture sequencing and constructing individualized genomes for transcriptome alignment, we identified 908 novel transcripts within the human MHC region. These include 593 novel isoforms of known genes, 137 antisense strand RNAs, 119 novel long intergenic noncoding RNAs, and 5 transcripts of 3 novel putative protein-coding human endogenous retrovirus genes. We revealed allele-dependent expression imbalance involving 88% of all heterozygous transcribed single nucleotide polymorphisms throughout the MHC transcriptome. Among these variants, the genetic variant associated with Behçet’s disease in the HLA-B/MICA region, which tags HLA-B*51, is within novel long intergenic noncoding RNA transcripts that are exclusively expressed from the haplotype with the protective but not the disease risk allele. Further, the transcriptome within the MHC region can be defined by 14 distinct coexpression clusters, with evidence of coregulation by unique transcription factors in at least 9 of these clusters. Our data suggest a very complex regulatory map of the human MHC, and can help uncover functional consequences of disease risk loci in this region.
Multi-Semi-Couple Super-Resolution Method for Edge Computing

Video analyses based on edge computing typically need high-resolution video images, while, in practice, the resolutions of captured video images may not high enough. Thus, super-resolution techniques are possible solutions for such purpose with input low-resolution images. Sparse-coding-based super-resolution methods are well known for their efficiency. However, the current sparse-coding-based methods suffer from two major problems. First, the sparse coefficient of a low-resolution patch is assumed to be same as the sparse coefficient of its corresponding high-resolution patch, which is too strict to deal with various patterns; and second, the current methods only learn one pair of high-resolution and low-resolution dictionaries, while, since patches in image are of diversity in real world, it is difficult to use only one pair of dictionaries to cover all possible patches. In this paper, to overcome these two issues, we propose a super-resolution method to: 1) relax the assumption by linearizing the sparse coefficient of a low-resolution patch to that of high-resolution patch and 2) minimize super-resolution errors by jointly partitioning training patches into several clusters and learning dictionaries. Experimental results validate that our algorithm achieve more faithful reconstructions.