Miracle-dz/UniFAR-FTUs huggingface dataset:
Editorial: recent discoveries in evolutionary and genomic microbiology

According to the current knowledge, the human body can be viewed as a superorganism comprised of human cells and resident microbial communities called microbiota (Ley et al., 2008). Human microbiota has a wide range of physiological functions, playing an important role in digestion, immunity, and production of certain vitamins; however, most of these microorganisms cannot be cultured in laboratory conditions, and until recently it has been the main challenge for clear determination of the composition of human microbiome (Tlaskalova-Hogenova et al., 2011). New discoveries in methods of molecular biology, including the emergence of omics technologies, have provided a possibility for deciphering the qualitative and quantitative composition of the microbiome (Tlaskalova-Hogenova et al., 2011). This breakthrough has also stimulated in-depth investigation of host-microbiota interactions (Tlaskalova-Hogenova et al., 2011). Basic comparative research revealed that each individual has a unique microbiota, which composition is largely determined during the first years of life but can be altered, reversibly or irreversibly, by a number of factors, such as age, environment, diet, drugs, diseases, and others (Zoetendal et al., 2008).
Nucleocytoplasmic shuttling of SOX14A and SOX14B transcription factors

The nucleocytoplasmic shuttling of SOX transcription factors play a crucial role in the regulation of SOX protein functions during development. In this study, we have demonstrated two nuclear localization signals in the HMG box of Eriocheir sinensis SOX14A and SOX14B. These two conserved nuclear localization signals mediate nuclear transport. The N-termini nuclear localization signal mediates the calmodulin-dependent pathway and the C-termini nuclear localization signal interacts with the importin-β pathway. The targeted deletion of nuclear localization signals of SOX14A/B dramatically inhibits the nuclear accumulation. We have first time revealed a non-classic nuclear export signal in the HMG box of E. sinensis SOX14A/B proteins is responds to leptomycin B. E. sinensis SOX14A/B is transported from the nucleus to the cytoplasm via a CRM1-dependent nuclear export pathway. And E. sinensis SOX14A/B are not belong to the subgroup E SOX proteins. Furthermore, these findings could shed a light on the mechanisms involved in the nuclear export of SOX proteins. The imperfect nuclear export signal on other SOX proteins, rather than just those of the SOXE group, may also be functional for nuclear export.
Fuzzy Random Walkers with Second Order Bounds: An Asymmetric Analysis

Edge-fuzzy graphs constitute an essential modeling paradigm across a broad spectrum of domains ranging from artificial intelligence to computational neuroscience and social network analysis. Under this model, fundamental graph properties such as edge length and graph diameter become stochastic and as such they are consequently expressed in probabilistic terms. Thus, algorithms for fuzzy graph analysis must rely on non-deterministic design principles. One such principle is Random Walker, which is based on a virtual entity and selects either edges or, like in this case, vertices of a fuzzy graph to visit. This allows the estimation of global graph properties through a long sequence of local decisions, making it a viable strategy candidate for graph processing software relying on native graph databases such as Neo4j. As a concrete example, Chebyshev Walktrap, a heuristic fuzzy community discovery algorithm relying on second order statistics and on the teleportation of the Random Walker, is proposed and its performance, expressed in terms of community coherence and number of vertex visits, is compared to the previously proposed algorithms of Markov Walktrap, Fuzzy Walktrap, and Fuzzy Newman–Girvan. In order to facilitate this comparison, a metric based on the asymmetric metrics of Tversky index and Kullback–Leibler divergence is used.
Adaptive PID Control of Standalone Wind Energy Conversion Systems

One of the most essential control tasks for standalone Wind Energy Conversion Systems (WECS) is to maximize the power conversion from wind. This task is normally achieved by the Maximum Power Point Tracking (MPPT) algorithms. However, such algorithms are simple and ineffective in satisfying additional complex requirements. Alternatively, the Proportional Integral Derivative (PID) control technique can be used for the optimal power conversion. However, the PID control is not effective in coping with the highly nonlinear, time-varying nature of WECS and stochastic change of wind. To overcome the PID control limitation, this paper presents an adaptive PID control design for standalone WECS, which is shown better than the traditional PID control in dealing with system changing conditions of WECS. The proposed adaptive strategy is validated by computer simulations. Key–Words: PID control, Adaptive PID control, Lyapunov analysis, Standalone wind energy conversion systems, Optimal power conversion, Permanent magnet synchronous generator.
Evaluation of SPC and BSS for indoor pass-by noise contribution analysis

The indoor vehicle pass-by test is a simulation of a field pass-by noise measurement in a controlled environment allowing repeatable measurements independent of weather conditions. During vehicle development modifications can be tested out in a fast manner to see the immediate influence on the overall vehicle noise levels produced during a pass-by acceleration test. Besides performing the standard pass-by noise test, vehicle improvement work requires knowledge about the noise contribution from the different vehicle sources during the pass-by test. A source path contribution (SPC) concept involving modelling the main vehicle noise sources contributing to the pass-by noise will be presented. A special feature of this approach is that it processes entirely in the time-domain to produce source strength estimates for the considered noise sources followed by a synthesis to produce pass-by noise estimates for the vehicle and for individual noise sources based on indicator microphone near-field data and acoustic transfer functions. As a result major pass-by noise contributors are identified at a given vehicle position during the pass-by test. Results produced by this method will be compared to a blind source separation (BSS) methodology applied to the operational dataset only for extracting source signals related to the different noise processes during vehicle operation. Extracted source signals are correlated with far-field measurements to estimate pass-by noise contributions. The BSS methodology is verified using a speaker setup showing excellent separation of tyre and engine noise contributions. Data from indoor pass-by noise measurements with a vehicle on a chassis-dynamometer is finally used to test and evaluate the two methods.
Trait and Marker Associations in Oryza nivara and O. rufipogon Derived Rice Lines under Two Different Heat Stress Conditions

Wild species and derived introgression lines (ILs) are a good source of genes for improving complex traits such as heat tolerance. The effect of heat stress on 18 yield traits was studied in four treatments in two seasons, under field conditions by subjecting 37 ILs and recurrent parents Swarna and KMR3, N22 mutants, and wild type and 2 improved rice cultivars to heat stress using polycover house method in wet season and late sowing method in dry season. Normal grown unstressed plants were controls. Both correlation and path coefficient analysis showed that the major contributing traits for high yield per plant (YPP) under heat stress conditions were tiller number, secondary branches in panicle, filled grain number, and percent spikelet fertility. Three ILs, K-377-24, K-16-3, and S-148 which gave the highest YPP of 12.30–32.52 g under heat stress in both the seasons were considered the most heat tolerant. In contrast, K-363-12, S-75, and Vandana which gave the least YPP of 5.36–10.84 g were considered heat susceptible. These lines are a good genetic resource for basic and applied studies on heat tolerance in rice. Genotyping using 49 SSR markers and single marker analysis (SMA) revealed 613 significant marker- trait associations in all four treatments. Significantly, nine markers (RM243, RM517, RM225, RM518, RM525, RM195, RM282, RM489, and RM570) on chromosomes 1, 2, 3, 4, 6, and 8 showed association with six traits (flag leaf spad, flag leaf thickness, vegetative leaf temperature, plant height, panicle number, and tiller number) under heat stress conditions in both wet and dry seasons. Genes such as heat shock protein binding DnaJ, Hsp70, and temperature-induced lipocalin-2 OsTIL-2 close to these markers are candidates for expression studies and evaluation for use in marker assisted selection for heat tolerance.
Performance analysis of random linear network coding in two-source single-relay networks

This paper considers the multiple-access relay channel in a setting where two source nodes transmit packets to a destination node, both directly and via a relay node, over packet erasure channels. Intra-session network coding is used at the source nodes and inter-session network coding is employed at the relay node to combine the recovered source packets of both source nodes. In this work, we investigate the performance of the network-coded system in terms of the probability that the destination node will successfully recover the source packets of the two source nodes. We build our analysis on fundamental probability expressions for random matrices over finite fields and we derive upper bounds on the system performance for the case of systematic and non-systematic network coding. Simulation results show that the upper bounds are very tight and accurately predict the decoding probability at the destination node. Our analysis also exposes the clear benefits of systematic network coding at the source nodes compared to non-systematic transmission.
LFI: A practical and general library-level fault injector

Fault injection, a critical aspect of testing robust systems, is often overlooked in the development of general-purpose software. We believe this is due to the absence of easy-to-use tools and to the extensive manual labor required to perform fault injection tests. This paper introduces LFI (L ibrary Fault Injector), a tool that automates the preparation of fault scenarios and their injection at the boundary between shared libraries and applications. LFI extends prior work by automatically profiling fault behaviors of libraries via static analysis of their binaries, thus reducing the dependence on human labor and perfect documentation. We present techniques for automatically generating injection scenarios and we describe a simple language for expressing such scenarios. LFI does not require access to libraries' source code and works for Linux, Windows, and Solaris on x86 and SPARC platforms.
O C ] 4 O ct 2 01 4 SOLVING COUPLED COMPOSITE MONOTONE INCLUSIONS BY SUCCESSIVE FEJÉR APPROXIMATIONS

Abstract. We propose a new class of primal-dual Fejér monotone algorithms for solving systems of composite monotone inclusions. Our construction is inspired by a framework used by Eckstein and Svaiter for the basic problem of finding a zero of the sum of two monotone operators. At each iteration, points in the graph of the monotone operators present in the model are used to construct a half-space containing the Kuhn-Tucker set associated with the system. The primal-dual update is then obtained via a relaxed projection of the current iterate onto this half-space. An important feature that distinguishes the resulting splitting algorithms from existing ones is that they do not require prior knowledge of bounds on the linear operators involved or the inversion of linear operators.
Chemotaxonomic Identification of Single Bacteria by Micro-Raman Spectroscopy: Application to Clean-Room-Relevant Biological Contaminations

ABSTRACT Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.
SIRT 3 Deacetylates Ceramide Synthases IMPLICATIONS FOR MITOCHONDRIAL DYSFUNCTION AND BRAIN INJURY *

Sergei A. Novgorodov, Christopher L. Riley, Jarryd A. Keffler, Jin Yu, Mark S. Kindy, Wendy B. Macklin, David B. Lombard , and Tatyana I. Gudz From the Ralph H. Johnson Veterans Affairs Medical Center, Charleston, South Carolina 29401, the Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina 29425, the Department of Cell and Developmental Biology, University of Colorado, Aurora, Colorado 80045, and the Department of Pathology and Institute of Gerontology, University of Michigan, Ann Arbor, Michigan 48109
Title Combined mechanical and circuit nonlinearities in electrostatic vibration energy harvesters

The aim of this paper is to study an electrostatic vibration energy harvester that utilises a nonlinear resonator. A vibration energy harvester represents a system where a mechanical resonator driven by ambient vibrations is coupled with a conditioning electronic circuit, which acts as a damper and converts mechanical energy into electrical. If a nonlinear resonator is embedded into the conditioning circuit, nonlinearity will appear from both mechanical and circuit components of the system. We expand the analytical approach that we developed in our previous works to the case of combined mechanical and circuit nonlinearities. This allow us to analyze steady-state behavior and compare it with the linear case. In addition, we discuss a specific nonlinear phenomena that is introduced by the discontinuity of the system — the sliding bifurcation. We show that the onset of steady-state quasi-harmonic oscillations occur through the disappearance of sliding motion.
Graphical Representations for Analog IC Design in Deep and Ultra-Deep Submicron CMOS

The paper presents a set of simulation experiments for characterization and graphical representation of the performance of deep and ultra-deep submicron CMOS transistors. The aim is to propose a general approach for illustration of the basic capabilities and limitations of tested CMOS technologies. The results are used to determine the bias conditions and the sizes of the transistors in analog integrated circuit design. To this goal the key figures of merit for characterizing of CMOS technologies are discussed and test circuits for their examination by simulation are presented. The test circuits are applied for study of 45nm ultra-deep submicron CMOS technology. The obtained results are analyzed and recommendations and simple rules of thumbs for application of the presented approach in practice are given.
Does the Size-Illusion Effect on Prehensile Movements Depend on Preview Duration for Visuomotor Process?

ABSTRACT Given that visual estimation of an object's size is affected by an illusory figure, the present study investigates the Ebbinghaus size-illusion effect on visuomotor performance within different preview durations for viewing an object (no preview, 300, 700, 1500, and 3000 ms) before initiating the movement. Twenty participants performed the following actions: (a) grasping the object and (b) matching the perceived object size with the finger aperture configuration as in the grasping task. The illusion affected the grasping aperture size only in the no- and 300-ms preview durations, while the matching aperture was affected across all preview conditions. These results suggest that the preview duration influences the size illusion to affect the grasping performance, and subjects adopt different visuomotor processes, depending on preview duration.
Noble Feature Extraction of Malware from Contents of File

— Malware family identification is a critical process involving extraction of distinctive property from a set of malware samples. Now a day several malware authors use various techniques to prevent the identification of unique property of their programs, such as, encryption and obfuscation. In this paper, we present features extraction of malware from contents of the file. First of all we scanning sample dataset or executable file through the virus total online tool[4] then disassemble given file by using IDA pro tool[1]; Convert given file into N-gram sequential pattern by using KfNgram tool[2]; Measurement of used symbols, sections, metadata and finally calculate the entropy. Our goal in this research is to introduce a noble set of features to understood malware features.
Refinement of Partial Behavior Models Under Model Composition and Abstraction

During requirements elicitation and preliminary design, a system’s behavior is typically partially specified: some behavior is defined as either forbidden or required, while other behavior is not yet categorized as either of those. The goal is then to gradually refine the specification and finally arrive at a complete behavioral description. Partial-behavior modeling formalisms, such as Modal Transition Systems, can support such gradual refinement. However, several challenges still remain, particularly in the context of hierarchical architectural specifications where (sub)system models are composed of smaller subsystems and components, and, in turn, abstracted to be made more compact and analyzable. Refinement of a behavior specification can be performed using models of varying scopes (e.g., different subsystems) and levels of abstraction, depending on the stakeholder needs. The primary challenge then becomes ensuring that a refinement of a model is correct when that model is a composition (or abstraction) of other models; this problem has not been addressed in the existing literature. In this paper, we propose a framework that supports reasoning about behavior refinement of composite and abstract models. Our framework assures that (1) a refinement of a composition is realized with refinements of the individual composed models and (2) a refinement of an abstract model is interpreted in terms of a refinement of the detailed model.
Data-driven Human Behavior Models: Opportunities and Challenges

We live in a world of data, of big data, a big part of which has been generated by humans through their interactions with both the physical and digital world. A key element in the exponential growth of human behavioral data is the mobile phone. There are more mobile phones in the world as humans which has turned the mobile phone into the piece of technology with the highest levels of adoption in human history. We carry them with us all through the day (and night, in many cases), leaving digital traces of our physical interactions. Mobile phones have become sensors of human activity both in the large scale and also as the most personal devices. In my talk, I present some of the work that we are doing at Telefonica Research in the area of modeling humans from human behavioral data collected from mobile phones. The data may be data that is automatically collected by the mobile network infrastructure --in particular Call Detail Records or CDRs---or data that is collected by an experimental mobile application through a user study. All projects entail data analytics and machine learning in order to build accurate models of individual or aggregate behavior. In particular, I describe four projects: (1) a project to automatically infer personality from Call Detail Records [1]; (2) MobiScore, a project to automatically assess a credit score from Call Detail Records [2]; Borapp, a mobile app that is able to detect boredom from patterns of phone usage [3] and a project to automatically predict crime hotspots in a city from human dynamics and demographic data [4]. I conclude by highlighting opportunities and challenges associated with building data-driven models of human behavior.
Application of Wireless Power Transmission Systems in Wireless Capsule Endoscopy: An Overview

Wireless capsule endoscopy (WCE) is a promising technology for direct diagnosis of the entire small bowel to detect lethal diseases, including cancer and obscure gastrointestinal bleeding (OGIB). To improve the quality of diagnosis, some vital specifications of WCE such as image resolution, frame rate and working time need to be improved. Additionally, future multi-functioning robotic capsule endoscopy (RCE) units may utilize advanced features such as active system control over capsule motion, drug delivery systems, semi-surgical tools and biopsy. However, the inclusion of the above advanced features demands additional power that make conventional power source methods impractical. In this regards, wireless power transmission (WPT) system has received attention among researchers to overcome this problem. Systematic reviews on techniques of using WPT for WCE are limited, especially when involving the recent technological advancements. This paper aims to fill that gap by providing a systematic review with emphasis on the aspects related to the amount of transmitted power, the power transmission efficiency, the system stability and patient safety. It is noted that, thus far the development of WPT system for this WCE application is still in initial stage and there is room for improvements, especially involving system efficiency, stability, and the patient safety aspects.
Resurgent extrapolation: rebuilding a function from asymptotic data. Painlevé I

Extrapolation is a generic problem in physics and mathematics: how to use asymptotic data in one parametric regime to learn about the behavior of a function in another parametric regime. For example: extending weak coupling expansions to strong coupling, or high temperature expansions to low temperature, or vice versa. Such extrapolations are particularly interesting in systems possessing dualities. Here we study numerical procedures for performing such an extrapolation, combining ideas from resurgent asymptotics with well-known techniques of Borel summation, Padé approximants and conformal mapping. We illustrate the method with the concrete example of the Painlevé I equation, which has applications in many branches of physics and mathematics. Starting solely with a finite number of coefficients from asymptotic data at infinity on the positive real line, we obtain a high precision extrapolation of the function throughout the complex plane, even across the phase transition into the pole region. The precision far exceeds that of state-of-the-art numerical integration methods along the real axis. The methods used are both elementary and general, not relying on Painlevé integrability properties, and so are applicable to a wide class of extrapolation problems.