Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Screen in Saccharomyces cerevisiae Identifies Vacuolar Protein Sorting, Autophagy, Biosynthetic, and tRNA Methylation Genes Involved in Life Span Regulation

The study of the chronological life span of Saccharomyces cerevisiae, which measures the survival of populations of non-dividing yeast, has resulted in the identification of homologous genes and pathways that promote aging in organisms ranging from yeast to mammals. Using a competitive genome-wide approach, we performed a screen of a complete set of approximately 4,800 viable deletion mutants to identify genes that either increase or decrease chronological life span. Half of the putative short-/long-lived mutants retested from the primary screen were confirmed, demonstrating the utility of our approach. Deletion of genes involved in vacuolar protein sorting, autophagy, and mitochondrial function shortened life span, confirming that respiration and degradation processes are essential for long-term survival. Among the genes whose deletion significantly extended life span are ACB1, CKA2, and TRM9, implicated in fatty acid transport and biosynthesis, cell signaling, and tRNA methylation, respectively. Deletion of these genes conferred heat-shock resistance, supporting the link between life span extension and cellular protection observed in several model organisms. The high degree of conservation of these novel yeast longevity determinants in other species raises the possibility that their role in senescence might be conserved.
Multiple stopping time POMDPs: Structural results

This paper considers a multiple stopping problem on a Hidden Markov model sample path of infinite horizon; where a reward, dependent on the underlying state, is associated with each stop. The decision maker stops L times to maximize the total expected revenue. The aim is to determine the structure of the optimal multiple stopping policy. The formulation generalizes the classical (single) stopping time Partially Observed Markov Decision (POMDP) problem. Even though the stopping set (in terms of the Bayesian beliefs) is not necessarily convex, we show that is a connected set. The structural results are illustrated using a numerical example.
Dempster-Shafer ’ s Theory of Evidence applied to Documents : modelling Uncertainty

Documents ojlen display a structure determined by the author, e.g., several chapters, each with several sub-chapters and so on. Taking into account the structure of a document allows the retrieval process to focus on those parts of the documents that are most relevant to an information need. Chiaramella et al advanced a model for indexing and retrieving structured documents. Their aim was to express the model within a framework based on formal logics with associated theories. They developed the logical formalism of the model. This paper adds to this model a theory of uncertainty, the Dempster-Shafer theory of evidence. It is shown that the theory provides a rule, the Dempster’s combination rule, that a[lows the expression of the uncertainty with respect to parts of a document, and that is compatible with the iogica{ model developed by Chiaramella et al.
Image Retrieval based on intention with Hybrid Query Model for the Web

The image retrieval applications are designed to collect images based on textual query or image contents. Web-scale image search engines (e.g., Google image search, Bing image search) mostly rely on surrounding text features. It is difficult for them to interpret users’ search intention only by query keywords and this leads to ambiguous and noisy search results which are far from satisfactory. It is important to use visual information in order to solve the ambiguity in text-based image retrieval. Internet image search approach is used to fetch images on the web environment. It only requires the user to click on one query image with minimum effort and images from a pool retrieved by text-based search are reranked based on both visual and textual content. The key contribution is to capture the users’ search intention from this one-click query image. The user intent collection steps are automatic, without extra effort from the user. This is critically important for any commercial web-based image search engine, where the user interface has to be extremely simple. Besides this key contribution, a set of visual features which are both effective and efficient in Internet image search are designed.RankBoost framework algorithm is enhanced to rank images with photographic quality. Content similarity and visual quality factors are used for the re-ranking process. Redundant image filtering process is integrated with the system. Query expansion is upgraded using query patterns and associations. The approach significantly improves the precision of topranked images and also the user experience.
A transition-based strategy for object-oriented software testing

Though time-to-market has become the primary criterion that drives most current software development projects, quality still remains the key concern of critical software development projects, for which the cost of a single bug may involve serious loss or damages. Meeting the higher quality level required for such kinds of systems may be achieved only by using sound and rigorous test practices. We present in this paper an integrated platform that uses a formalized version of UML statechart as the basis for rigorous testing of object-oriented programs. The platform adapts and integrates systematic test data generation strategies and associated tools for object-oriented program testing.
PFC AND SPEED CONTROL OF BLDC MOTOR USING ZETA CONVERTER

A Power Factor Correction (PFC) and sensorless speed control of BLDC (Brushless DC) motor using zeta converter is presented. Zeta converter is a fourth-order DC-DC converter made up of two inductors and two capacitors and capable of operating in either step-up or step- down mode. The PFC is achieved by zeta converter. Sensorless speed control of BLDC motor is achieved and the cost and wiring of sensors are reduced. A MATLAB/ Simulink environment is used to simulate the developed model to achieve a wide range of speed control with high PF (Power Factor) and improved PQ (Power Quality) at the supply.
Accuracy Improvement for Stiffness Modeling of Parallel Manipulators

The paper focuses on the accuracy improvement of stiffness models for parallel manipulators, which are employed in high-speed precision machining. It is based on the integrated methodology that combines analytical and numerical techniques and deals with multidimensional lumped-parameter models of the links. The latter replace the link flexibility by localized 6-dof virtual springs describing both translational/rotational compliance and the coupling between them. There is presented detailed accuracy analysis of the stiffness identification procedures employed in the commercial CAD systems (including statistical analysis of round-off errors, evaluating the confidence intervals for stiffness matrices). The efficiency of the developed technique is confirmed by application examples, which deal with stiffness analysis of translational parallel manipulators.
Specular Surface Recovery via Coded Target Stereopsis

A key challenge facing space-based computer vision systems is the presence of highly specular surfaces. Such surfaces present a challenge to conventional vision systems due to specular re(cid:13)ections, which may mask the true location of objects and lead to incorrect measurements. The problem is complicated by the fact that the use of high-powered illuminants, such as laser beams, can be problematic since the instruments inside space structures are often sensitive to various forms of radiation. This article presents a new approach to reconstructing the local surface structure of highly specular objects. The system utilizes a commercial trinocular stereo vision system and a coded low-power two-dimensional il-luminant to recover surface structure. The local surface structure of an object is obtained by projecting light patterns onto the object’s surface and inferring surface structure by examining the interaction of the illu-minant and the surface. The system recovers both specular and di(cid:11)use surface regions. Experimental results demonstrate the e(cid:11)ectiveness of the approach.
Diffraction Structural Biology Synchrotron Radiation Crystal Structure of Udp-glucose:anthocyanidin 3-o-glucosyltransferase from Clitoria Ternatea

Flowers of the butterfly pea (Clitoria ternatea) accumulate a group of polyacylated anthocyanins, named ternatins, in their petals. The first step in ternatin biosynthesis is the transfer of glucose from UDP-glucose to antho-cyanidins such as delphinidin, a reaction catalyzed in C. ternatea by UDP-glucose:anthocyanidin 3-O-glucosyltransferase (Ct3GT-A; AB185904). To elucidate the structure–function relationship of Ct3GT-A, recombinant Ct3GT-A was expressed in Escherichia coli and its tertiary structure was determined to 1.85 A ˚ resolution by using X-ray crystallography. The structure of Ct3GT-A shows a common folding topology, the GT-B fold, comprised of two Rossmann-like // domains and a cleft located between the N-and C-domains containing two cavities that are used as binding sites for the donor (UDP-Glc) and acceptor substrates. By comparing the structure of Ct3GT-A with that of the flavonoid glycosyltransferase VvGT1 from red grape (Vitis vinifera) in complex with UDP-2-deoxy-2-fluoro glucose and kaempferol, locations of the catalytic His-Asp dyad and the residues involved in recognizing UDP-2-deoxy-2-fluoro glucose were essentially identical in Ct3GT-A, but certain residues of VvGT1 involved in binding kaempferol were found to be substituted in Ct3GT-A. These findings are important for understanding the differentiation of acceptor-substrate recognition in these two enzymes.
A II-HARQ scheme for BEC models with ML decoding of Turbo Codes

In this paper we propose a coding-decoding scheme to be used for II-type hybrid ARQ on a binary erasure channel model, based on rate compatible punctured binary Turbo Codes, DRP interleaver design and ML decoding at the receiver. We carefully design the interleaver and the puncturing mask, and we describe how to achieve low-complexity Maximum Likelihood decoding. We show for the case of an MPEG2 packet size that this scheme overrides random codes upper bounds, providing throughputs within 0.05 bits from capacity at word error rates greater or equal to 10-6.
Efficient data reuse in value function approximation

Off-policy reinforcement learning is aimed at efficiently using data samples gathered from a policy that is different from the currently optimized policy. A common approach is to use importance sampling techniques for compensating for the bias of value function estimators caused by the difference between the data-sampling policy and the target policy. However, existing off-policy methods often do not take the variance of the value function estimators explicitly into account and therefore their performance tends to be unstable. To cope with this problem, we propose using an adaptive importance sampling technique which allows us to actively control the trade-off between bias and variance. We further provide a method for optimally determining the trade-off parameter based on a variant of cross-validation. The usefulness of the proposed approach is demonstrated through simulated swing-up inverted-pendulum problem.
Modified Methods of Estimating Space-Time Spectra from Polar-orbiting Satellite Data: Part II: The Wavenumber Transform Method@@@第2部:波数変換法

In order to estimate space-time spectra correctly from uneven twice-daily data sampled by a polar-orbiting satellite, the wavenumber transform method (Hayashi, 1980) is modified by the use of a nonorthogonal Fourier inversion. The space-time spectra are obtained from the time-Fourier coefficients of the space-Fourier transforms of the asynoptic field with respect to its frequency-shifted wavenumber. Since this method requires the spatial interpolation of asynoptic data, it is effective only for ultralong waves. The wavenumberfrequency aliasing characteristics are examined and the computer code is exemplified.
U-duality between Three and Higher Dimensional Black Holes

We show that the D-brane configurations for the five and four-dimensional black holes give the geometry of two and three-dimensional ones as well. The emergence of these lower dimensional black holes from the D-brane configurations for those of higher dimensions comes from the choice of the integration constant of harmonic functions, which decides the asymptotic behavior of the metric and other fields. We show that they are equivalent, which are connected by U-dual transformations. This means that stringy black holes in various dimensions are effectively in the same universality class and many properties of black holes in the same class can be infered from the study of those of the three-dimensional black holes.
PSEUDOSPECTRAL COLLOCATION METHODS FOR FOURTH ORDER DIFFERENTIAL EQUATIONS

Collocation schemes are presented for solving linear fourth order differential equations in one and two dimensions. The variational formulation of the model fourth order problem is discretized by approximating the integrals by a Gaussian quadrature rule generalized to include the values of the derivative of the integrand at the boundary points. Collocation schemes are derived which are equivalent to this discrete variational problem. An efficient preconditioner based on a low-order finite difference approximation to the same differential operator is presented. The corresponding multi-domain problem is also considered and interface conditions are derived. Pseudospectral approximations which are C^1 continuous at the interfaces are used in each subdomain to approximate the solution. The approximations are also shown to be C^3 continuous at the interfaces asymptotically. A complete analysis of the collocation scheme for the multi-domain problem is provided. The extension of the method to the biharmonic equation in two dimensions is discussed and results are presented for a problem defined in a non-rectangular domain.
Knowledge Sharing for Supply Chain Management Based on Fuzzy Ontology on the Semantic Web

Knowledge sharing is the basic means to improve the efficiency of supply chain management (SCM). Ontology is the basis of sharing and reusing knowledge on the semantic Web. Fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. In order to handle fuzzy phenomenon and uncertainty of knowledge in SCM, this paper proposes a series of fuzzy ontology models using intuitionistic fuzzy set that consists of fuzzy domain ontology and fuzzy linguistic variable ontologies. Then, a fuzzy ontology framework is presented, including three parts: concepts, properties of concepts and values of properties. The application, which uses fuzzy ontology to model customer and product knowledge in supply chain, shows that these models can overcome the localization of other fuzzy ontology models, and this research facilitates the fuzzy knowledge sharing and reuse on the semantic Web.
PROPERTIES OF GRAVITOTURBULENT ACCRETION DISKS

We explore the properties of cold gravitoturbulent accretion disks—non-fragmenting disks hovering on the verge of gravitational instability (GI)—using a realistic prescription for the effective viscosity caused by gravitational torques. This prescription is based on a direct relationship between the angular momentum transport in a thin accretion disk and the disk cooling in a steady state. Assuming that opacity is dominated by dust we are able to self-consistently derive disk properties for a given assuming marginal gravitational stability. We also allow external irradiation of the disk and account for a non-zero background viscosity, which can be due to the magneto-rotational instability. Spatial transitions between different co-existing disk states (e.g., between irradiated and self-luminous or between gravitoturbulent and viscous) are described and the location of the boundary at which the disk must fragment is determined in a variety of situations. We demonstrate in particular that at low enough external irradiation stabilizes the gravitoturbulent disk against fragmentation to very large distances thus providing means of steady mass transport to the central object. Implications of our results for the possibility of planet formation by GI in protoplanetary disks and star formation in the Galactic center and for the problem of feeding supermassive black holes in galactic nuclei are discussed.
Effects of Dietary Additives and Early Feeding on Performance, Gut Development and Immune Status of Broiler Chickens Challenged with Clostridium perfringens

The effects of dietary additives and holding time on resistance and resilience of broiler chickens to Clostridium perfringens challenge were investigated by offering four dietary treatments. These were a negative control (basal), a positive control (Zn-bacitracin) and two dietary additives, mannanoligosaccharides (MOS), and acidifier. Two holding times included (a) immediate access to feed and water post hatch (FED) and (b) access to both feed and water 48 h post hatch (HELD). Chicks fed Zn-bacitracin had no intestinal lesions attributed to necrotic enteritis (NE), whereas chicks fed both MOS or acidifier showed signs of NE related lesions. All dietary treatments were effective in reducing the numbers of C. perfringens in the ileum post challenge. The FED chicks had heavier body weight and numerically lower mortality. The FED chicks also showed stronger immune responses to NE challenge, showing enhanced (p<0.05) proliferation of T-cells. Early feeding of the MOS supplemented diet increased (p<0.05) IL-6 production. The relative bursa weight of the FED chicks was heavier at d 21 (p<0.05). All the additives increased the relative spleen weight of the HELD chicks at d 14 (p<0.05). The FED chicks had increased villus height and reduced crypt depth, and hence an increased villus/crypt ratio, especially in the jejunum at d 14 (p<0.05). The same was true for the HELD chicks given dietary additives (p<0.05). It may be concluded that the chicks with early access to dietary additives showed enhanced immune response and gut development, under C. perfringens challenge. The findings of this study shed light on managerial and nutritional strategies that could be used to prevent NE in the broiler industry without the use of in-feed antibiotics.
Calculation of minimum capacitance of isolated three phase induction generator using adaptive PSO technique

This paper helps to find out the minimum capacitance required for self-excitation of an isolated three-phase self-excited induction generator (SEIG) using Adaptive Particle Swarm Optimization (APSO) technique. APSO technique has been used to solve the non-linear equations and capacitance calculation has been done under various conditions like loading, change in rotor speed. The results obtained using APSO technique has been compared with that obtained from steady-state model.
Automatic Detection of Atrial Fibrillation in Cardiac Vibration Signals

We present a study on the feasibility of the automatic detection of atrial fibrillation (AF) from cardiac vibration signals (ballistocardiograms/BCGs) recorded by unobtrusive bed-mounted sensors. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and not as a replacement for ECG-based methods used in clinical environments. Based on the BCG data recorded in a study with ten AF patients, we evaluate and rank seven popular machine learning algorithms (naive Bayes, linear and quadratic discriminant analysis, support vector machines, random forests as well as bagged and boosted trees) for their performance in separating 30-s long BCG epochs into one of three classes: sinus rhythm, AF, and artifact. For each algorithm, feature subsets of a set of statistical time-frequency-domain and time-domain features were selected based on the mutual information between features and class labels as well as the first- and second-order interactions among features. The classifiers were evaluated on a set of 856 epochs by means of tenfold cross validation. The best algorithm (random forests) achieved a Matthews correlation coefficient, mean sensitivity, and mean specificity of 0.921, 0.938, and 0.982, respectively.
Lessons Learned: Towards Informal Science Education of Human-Robot Interaction at Children's Science Museums

Robots themselves are interesting as museum exhibits and appeal to a wide range of people [9]. However, human-robot interaction (HRI) is more than just robotics. Informal science education about HRI can occur using “hands-on” exhibits deployed at science museums. I discuss some of the lessons learned from the installation of two HRI exhibits: one at the Discovery Museums in Acton, MA, and the other at the Children’s Museum of Atlanta in Atlanta, GA.
Graption : Automated Detection of P 2 P Applications using Traffic Dispersion Graphs ( TDGs )

Monitoring network traffic and detecting emerging P2P applications is an increasingly challenging problem since ne w applications obfuscate their traffic. Despite recent effor ts, the problem is not yet solved and network administrators are still looking for effective and deployable tools. In this pa per, we address this problem using Traffic Dispersion Graphs (TDGs), a novel way to analyze traffic. Given a set of flows, a TDG is a graph with an edge between any two IP addresses that communicate. Thus TDGs capture network-wide interactions. We start by exploring the potential of TDGs for traffic monitoring by focusing on graph metrics instead of features of individual flows. We then use TDGs to develop an application classification tool dubbed Graption ( Graphbased P2P detec tion), which we target specifically for detecting P2P traffic. Graption begins by partitioning traffic flows into clusters based on flow-level features and without the need for application-specific knowledge. It then builds TDGs for these clusters, and uses graph metrics to identify clusters that correspond to P2P applications. Finally, we a utomatically extract a regular expression for a new P2P appli cation, allowing the use of existing IDS devices and routers to block or rate-limit the detected traffic. We describe trac edriven experiments that show more than 90% precision and recall for P2P detection.
Load Balancing of Telecommunication Networks based on Multiple Spanning Trees

In this paper we address the problem of load balancing optimization of telecommunication networks based on multiple spanning tree routing. We focus on two objectives – minimization of the maximum link load and minimization of the network utilization imposing a worst case load value – and we propose two sets of mixed integer programming models defining the optimization problems (where one set is derived from the other). We further propose three decompositions (based on the Dantzig-Wolfe principle) to be applied to the models, as alternative means to solve the same problems. A set of computational results show the efficiency of the different models and decompositions.
Elección de método e intensidad de búsqueda de empleo en los desempleados

En este articulo investigamos la utilizacion de diferentes metodos de busqueda de empleo entre los trabajadores desempleados y la intensidad del proceso de busqueda. Se presenta un modelo de busqueda de empleo que relaciona la eleccion del metodo de busqueda con los costes mone-tarios y de tiempo y la productividad esperada, entre otros factores. El analisis empirico se basa en la Encuesta Sociodemografica de la Comu-nidad Valenciana (1988). (La evidencia econometrica muestra que los metodos de busqueda elegidos y el numero de metodos utilizados (in-tensidad) estan determinados por las caracteristicas personales y socioe-conomicas de los individuos, las cuales reflejan necesidades y costes junto con fuentes de ingresos y productividades esperadas.