Miracle-dz/UniFAR-FTUs huggingface dataset:
Usability Issues in Knowledge Representation Systems

The amount of use a knowledge representation system receives depends on more than just the theoretical suitability of the system. Some critical determiners of usage have to do with issues related to the representation formalism of the system, some have to do with non-representational issues of the system itself, and some might be most appropriately labeled public relations. We rely on over eight years of industrial application experiences using a particular family of knowledge representation systems based on description logics to identify and describe usability issues that were mandatory for our application successes.
A Survey of Timing Channels and Countermeasures

A timing channel is a communication channel that can transfer information to a receiver/decoder by modulating the timing behavior of an entity. Examples of this entity include the interpacket delays of a packet stream, the reordering packets in a packet stream, or the resource access time of a cryptographic module. Advances in the information and coding theory and the availability of high-performance computing systems interconnected by high-speed networks have spurred interest in and development of various types of timing channels. With the emergence of complex timing channels, novel detection and prevention techniques are also being developed to counter them. In this article, we provide a detailed survey of timing channels broadly categorized into network timing channel, in which communicating entities are connected by a network, and in-system timing channel, in which the communicating entities are within a computing system. This survey builds on the last comprehensive survey by Zander et al. [2007] and considers all three canonical applications of timing channels, namely, covert communication, timing side channel, and network flow watermarking. We survey the theoretical foundations, the implementation, and the various detection and prevention techniques that have been reported in literature. Based on the analysis of the current literature, we discuss potential future research directions both in the design and application of timing channels and their detection and prevention techniques.
Mechanism of the hydrophobic effect in the biomolecular recognition of arylsulfonamides by carbonic anhydrase

The hydrophobic effect—a rationalization of the insolubility of nonpolar molecules in water—is centrally important to biomolecular recognition. Despite extensive research devoted to the hydrophobic effect, its molecular mechanisms remain controversial, and there are still no reliably predictive models for its role in protein–ligand binding. Here we describe a particularly well-defined system of protein and ligands—carbonic anhydrase and a series of structurally homologous heterocyclic aromatic sulfonamides—that we use to characterize hydrophobic interactions thermodynamically and structurally. In binding to this structurally rigid protein, a set of ligands (also defined to be structurally rigid) shows the expected gain in binding free energy as hydrophobic surface area is added. Isothermal titration calorimetry demonstrates that enthalpy determines these increases in binding affinity, and that changes in the heat capacity of binding are negative. X-ray crystallography and molecular dynamics simulations are compatible with the proposal that the differences in binding between the homologous ligands stem from changes in the number and organization of water molecules localized in the active site in the bound complexes, rather than (or perhaps in addition to) release of structured water from the apposed hydrophobic surfaces. These results support the hypothesis that structured water molecules—including both the molecules of water displaced by the ligands and those reorganized upon ligand binding—determine the thermodynamics of binding of these ligands at the active site of the protein. Hydrophobic effects in various contexts have different structural and thermodynamic origins, although all may be manifestations of the differences in characteristics of bulk water and water close to hydrophobic surfaces.
Metabolism and metabolites of polychlorinated biphenyls

Abstract The metabolism of polychlorinated biphenyls (PCBs) is complex and has an impact on toxicity, and thereby on the assessment of PCB risks. A large number of reactive and stable metabolites are formed in the processes of biotransformation in biota in general, and in humans in particular. The aim of this document is to provide an overview of PCB metabolism, and to identify the metabolites of concern and their occurrence. Emphasis is given to mammalian metabolism of PCBs and their hydroxyl, methylsulfonyl, and sulfated metabolites, especially those that persist in human blood. Potential intracellular targets and health risks are also discussed.
SER for Optimal Combining in Rician Fading with Co-channel Interference

Approximate Symbol error rate (SER) expressions are derived for receive diversity system employing optimum combining, when both the desired and the interfering signals are subjected to Rician fading, for the case of a) equal power uncorrelated interferers b) unequal power interferers c) interferer correlation. The derived expressions are applicable for an arbitrary number of receive antennas and interferers and for any QAM constellation. Furthermore, we derive a simple closed form expression for SER in the interference-limited regime, for the special case of Rayleigh faded interferers. A close match is observed between the SER result obtained through the derived analytical expression and the one obtained from Monte-Carlo simulations, for a variety of QAM constellations.
Conceptualizing School Leadership and Management from a Distributed Perspective: An Exploration of Some Study Operations and Measures

A distributed perspective on school leadership and management has garnered considerable attention from policy makers, practitioners, and researchers in many countries over the past decade. However, we should be skeptical of its appeal as a measure of worth. While optimism is high with respect to taking a distributed perspective, we urge caution by arguing for more attention to research fundamentals in the form of study operations and research measures before seeking causal inferences. The question is not, does distributed leadership work? but rather, how are leadership and management related to school and classroom conditions and school outcomes? To answer this question from a distributed perspective, we need to engage study operations and measures when taking a distributed perspective in school leadership and management research. This article attempts to extend that conversation.
Linguistic Evaluation of Support Verb Constructions by OpenLogos and Google Translate

This paper presents a systematic human evaluation of translations of English support verb constructions produced by a rule-based machine translation (RBMT) system (OpenLogos) and a statistical machine translation (SMT) system (Google Translate) for five languages: French, German, Italian, Portuguese and Spanish. We classify support verb constructions by means of their syntactic structure and semantic behavior and present a qualitative analysis of their translation errors. The study aims to verify how machine translation (MT) systems translate fine-grained linguistic phenomena, and how well-equipped they are to produce high-quality translation. Another goal of the linguistically motivated quality analysis of SVC raw output is to reinforce the need for better system hybridization, which leverages the strengths of RBMT to the benefit of SMT, especially in improving the translation of multiword units. Taking multiword units into account, we propose an effective method to achieve MT hybridization based on the integration of semantico-syntactic knowledge into SMT.
HyRec: leveraging browsers for scalable recommenders

The ever-growing amount of data available on the Internet calls for personalization. Yet, the most effective personalization schemes, such as those based on collaborative filtering (CF), are notoriously resource greedy. This paper presents HyRec, an online cost-effective scalable system for user-based CF personalization. HyRec offloads recommendation tasks onto the web browsers of users, while a server orchestrates the process and manages the relationships between user profiles. HyRec has been fully implemented and extensively evaluated on several workloads from MovieLens and Digg. We convey the ability of HyRec to reduce the operation costs of content providers by nearly 50% and to provide a 100-fold improvement in scalability with respect to a centralized (or cloud-based recommender approach), while preserving the quality of personalization. We also show that HyRec is virtually transparent to users and induces only 3% of the bandwidth consumption of a P2P solution.
CS 596 : Theoretical Machine Learning

Mistake Bound (MB) Model As in the PAC model, we have an instance space X, function class as H, and target function as h∗ ∈ H. In the MB model, learning occurs rounds. In each round t: 1. The learner gets an unlabeled example xt ∈ X. 2. The learner predicts its label yt ∈ {0, 1}. 3. The learner is told the correct label y = h(xt). The goal is to minimize the number of mistakes. For an online learning algorithm A, we denote by MBA(H) the maximal number of mistakes A might make on a sequence of examples which is labeled by some h∗ ∈ H. Define MB(H) as the best mistake bound achievable by a deterministic algorithm for learning H. Let’s look at a simple example.
Optimal Dissemination of Security Patches in Mobile Wireless Networks

The security threat posed by malware in mobile wireless networks can be countered through immunization using security patches. The distribution of patches, however, consumes bandwidth that is scarce in wireless networks, and must, there fore, be judiciously controlled in order to attain desired tradeoffs between security risks and bandwidth consumption. We consider both nonreplicative and replicative dissemination of patches: a predetermined set of dispatcher nodes distribute the patches in the former, whereas the dispatcher set continually grows in the latter as the nodes that receive the patch become dispatchers themselves. In each case, the desired tradeoffs can be attained by activating at any given time only fractions of dispatchers and selecting their packet transmission rates. We formulate the afore said tradeoffs as optimal control problems that seek to minimize the aggregate network costs that depend on security risks and the overall extra bandwidth used in the network for dissemination of the security patches. We prove that the dynamic control strategies have simple structures: when the cost function associated with the bandwidth consumed in patching is concave, the control strategies are bang-bang with at most one jump from the maximum to the minimum value. When the cost function is strictly convex, the aforesaid transition is strict but continuous. We compare the efficacy of different dispatch models and also those of the optimum dynamic and static controls using numerical computations.
Climatological Effects on the Breeding of Terns

The physical circulation in the Western Indian Ocean controls the supply of nutrients, and this, combined with the stability of the surface layer and the availability of sunlight controls the primary production. In this note, we review two papers' findings on how the physical conditions ultimately impact upon the breeding of terns, a marinetop predator in the region. Rather than trace causal links through the food chain, we show empirical connections between avian breeding and the environmental conditions, all of which appear statistically significant.
An ex vivo model to quantitatively analyze cell migration in tissue

Background: Within the developing central nervous system, the ability of cells to migrate throughout the tissue parenchyma to reach their target destination and undergo terminal differentiation is vital to normal central nervous system (CNS) development. To develop novel therapies to treat the injured CNS, it is essential that the migratory behavior of cell populations is understood. Many studies have examined the ability of individual neurons to migrate through the developing CNS, describing specific modes of migration including locomotion and somal translocation. Few studies have investigated the mass migration of large populations of neural progenitors, particularly in the developing the spinal cord. Here, we describe a method to robustly analyze large numbers of migrating cells using a co‐culture assay. Results: The ex vivo tissue model promotes the survival and differentiation of co‐cultured progenitor cells. Using this assay, we demonstrate that migrating neuroepithelial progenitor cells display region specific migration patterns within the dorsal and ventral spinal cord at defined developmental time points. Conclusions: The technique described here is a viable ex vivo model to quantitatively analyze cell migration and differentiation. We demonstrate the ability to detect changes in cell migration within distinct tissue region across tissue samples using the technique described here. Developmental Dynamics 247:201–211, 2018. © 2017 Wiley Periodicals, Inc.
Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data

The problem of rewriting keyword search queries on graph data has been studied recently, where the main goal is to clean user queries by rewriting keywords as valid tokens appearing in the data and grouping them into meaningful segments. The main solution to this problem employs heuristics for ranking query rewrites and a dynamic programming algorithm for computing them. Based on a broader set of queries defined by an existing benchmark, we show that the use of these heuristics does not yield good results. We propose a novel probabilistic framework, which enables the optimality of a query rewrite to be estimated in a more principled way. We show that our approach outperforms existing work in terms of effectiveness and efficiency of query rewriting. More importantly, we provide the first results indicating query rewriting can indeed improve overall keyword search runtime performance and result quality.
Role of Sindbis Virus Capsid Protein Region II in Nucleocapsid Core Assembly and Encapsidation of Genomic RNA

ABSTRACT Sindbis virus is an enveloped positive-sense RNA virus in the alphavirus genus. The nucleocapsid core contains the genomic RNA surrounded by 240 copies of a single capsid protein. The capsid protein is multifunctional, and its roles include acting as a protease, controlling the specificity of RNA that is encapsidated into nucleocapsid cores, and interacting with viral glycoproteins to promote the budding of mature virus and the release of the genomic RNA into the newly infected cell. The region comprising amino acids 81 to 113 was previously implicated in two processes, the encapsidation of the viral genomic RNA and the stable accumulation of nucleocapsid cores in the cytoplasm of infected cells. In the present study, specific amino acids within this region responsible for the encapsidation of the genomic RNA have been identified. The region that is responsible for nucleocapsid core accumulation has considerable overlap with the region that controls encapsidation specificity.
The Possible Mechanism of Idiosyncratic Lapatinib-Induced Liver Injury in Patients Carrying Human Leukocyte Antigen-DRB1*07:01

Idiosyncratic lapatinib-induced liver injury has been reported to be associated with human leukocyte antigen (HLA)-DRB1*07:01. In order to investigate its mechanism, interaction of lapatinib with HLA-DRB1*07:01 and its ligand peptide derived from tetanus toxoid, has been evaluated in vitro. Here we show that lapatinib enhances binding of the ligand peptide to HLA-DRB1*07:01. Furthermore in silico molecular dynamics analysis revealed that lapatinib could change the β chain helix in the HLA-DRB1*07:01 specifically to form a tightly closed binding groove structure and modify a large part of the binding groove. These results indicate that lapatinib affects the ligand binding to HLA-DRB1*07:01 and idiosyncratic lapatinib-induced liver injury might be triggered by this mechanism. This is the first report showing that the clinically available drug can enhance the binding of ligand peptide to HLA class II molecules in vitro and in silico.
An Effective Algorithm to Detect Abnormal Step Counting Based on One-Class SVM

Walking is the most easily achievable way to reduce obesity and to keep fit. Step counting devices are helpful for users to develop regular walking habits, but they may mistake some abnormal situations (SHAKING, SWING, JITTER, PENDULUM, etc.) for walking and thus result in step counting errors. Such errors will inflate the number of steps, and lead to biased inter-user comparisons or competitions. To fix the problem, we developed an effective algorithm to detect abnormal step counting, which extract 13 non-directional features from acceleration data, and feed them into OneClass Support Vector Machine (OCSVM) to check wether it is abnormal. The detection algorithm has been tested on a dataset composed of 500 minutes real world data, which is captured by 10 users. It is shown that the proposed algorithm is capable of detecting most of the abnormal situations while not mistaking normal activity (walking/running) for abnormal. While the false alarm rate is 5.08%, the algorithm detects 90.72% of abnormal situations. The AUC (Area Under the Curve) of the proposed algorithm reaches 0.9252, which shows that the algorithm is very effective for abnormal situation detection. Keywords-abnormal step-counting detection; OCSVM; Nondirectional Feature Extraction;
A Platform-as-a-Service for in-situ development of wireless sensor network applications

In this paper we present a Platform-as-a-Service (PaaS) approach for rapid development of wireless sensor network (WSN) applications based on the dinam-mite concept, i.e. an embedded web-based development environment and run-time platform for WSN systems integrated in a single information appliance. The PaaS is hosted by a cloud of dinam-mite nodes which facilitates the on-demand development, deployment and integration of WSN applications. We introduce the dinam Cloud architecture and focus, in this paper, on the PaaS layer established by the dinam-mite nodes. In addition to the description of this so-called dinam PaaS, a performance analysis of the dinam-mite node towards its applicability to forming a dinam PaaS layer is demonstrated. We then present the MASON mobile vehicular network as an example of such a WSN which delivers spatially and temporally fine-grained environmental measurements within the city of Beijing, and illustrate how to utilize the dinam PaaS for integrating the data from the MASON network into its back-end business system. Finally, we discuss the five essential properties of the Cloud Computing stack, according to the NIST definition, with respect to the dinam PaaS and illustrate the benefits of the dinam PaaS for system integration as well as WSN application development.
Multiphysics computational models for cardiac flow and virtual cardiography

A multiphysics simulation approach is developed for predicting cardiac flows as well as for conducting virtual echocardiography (ECHO) and phonocardiography (PC) of those flows. Intraventricular blood flow in pathological heart conditions is simulated by solving the three‐dimensional incompressible Navier–Stokes equations with an immersed boundary method, and using this computational hemodynamic data, echocardiographic and phonocardiographic signals are synthesized by separate simulations that model the physics of ultrasound wave scattering and flow‐induced sound, respectively. For virtual ECHO, a Doppler ultrasound image is reproduced through Lagrangian particle tracking of blood cell particles and application of sound wave scattering theory. For virtual PC, the generation and propagation of blood flow‐induced sounds (‘hemoacoustics’) is directly simulated by a computational acoustics model. The virtual ECHO is applied to reproduce a color M‐mode Doppler image for the left ventricle as well as continuous Doppler image for the outflow tract of the left ventricle, which can be verified directly against clinically acquired data. The potential of the virtual PC approach for providing new insights between disease and heart sounds is demonstrated by applying it to modeling systolic murmurs caused by hypertrophic cardiomyopathy. Copyright © 2013 John Wiley & Sons, Ltd.
Restricted dead‐end elimination: Protein redesign with a bounded number of residue mutations

Dead‐end elimination (DEE) has emerged as a powerful structure‐based, conformational search technique enabling computational protein redesign. Given a protein with n mutable residues, the DEE criteria guide the search toward identifying the sequence of amino acids with the global minimum energy conformation (GMEC). This approach does not restrict the number of permitted mutations and allows the identified GMEC to differ from the original sequence in up to n residues. In practice, redesigns containing a large number of mutations are often problematic when taken into the wet‐lab for creation via site‐directed mutagenesis. The large number of point mutations required for the redesigns makes the process difficult, and increases the risk of major unpredicted and undesirable conformational changes. Preselecting a limited subset of mutable residues is not a satisfactory solution because it is unclear how to select this set before the search has been performed. Therefore, the ideal approach is what we define as the κ‐restricted redesign problem in which any κ of the n residues are allowed to mutate. We introduce restricted dead‐end elimination (rDEE) as a solution of choice to efficiently identify the GMEC of the restricted redesign (the κGMEC). Whereas existing approaches require n‐choose‐κ individual runs to identify the κGMEC, the rDEE criteria can perform the redesign in a single search. We derive a number of extensions to rDEE and present a restricted form of the A* conformation search. We also demonstrate a 10‐fold speed‐up of rDEE over traditional DEE approaches on three different experimental systems. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010
Research on a dual active bridge based power electronics transformer using nanocrystalline and Silicon Carbide

A power electronics transformer (PET) based on dual active bridge (DAB) with input series and output parallel (ISOP) cascaded topology is studied in this paper. Fe-based nanocrystalline alloys transformer cores and Silicon Carbide (SiC) power MOSFETs are adopted to improve the power density and efficiency. Mathematical derivation of the input voltage distribution is deduced with the conclusion that the voltage equalization cannot be achieved autonomously. A feedback control method is proposed to balance the input voltage. The measurement of the dynamic B-H loops of the nanocrystalline core under the excitation of square wave and sinusoidal wave is conducted. The high frequency isolation transformer (HFIT) is designed based on the loss performance calculated using the dynamic B-H loop and Ohm's law. The optimized operating flux density is around ±0.68 T at 20 kHz, which is much higher than the empirical value around ±0.3 T to take full advantage of the nanocrystalline core. Finally, a 13.2 kVA prototype is built to verify the above analysis and design.