Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis of underspecified composite e-services based on automated reasoning

In this paper we study automatic composition synthesis of <i>e</i>-Services, based on automated reasoning. We represent the behavior of an <i>e</i>-Service in terms of a deterministic transition syst (or a finite state machine), in which for each action the role of the <i>e</i>-Service, either as initiator or as servant, is highlighted. In this setting we present an algorithm based on satisfiability in a variant of Propositional Dynamic Logic that solves the automatic composition probl. Specifically, given (<i>i</i>) a possibly incomplete specification of the sequences of actions that a client would like to realize, and (<i>ii</i>) a set of available <i>e</i>-Services, our technique synthesizes a composite <i>e</i>-Service that (<i>i</i>) uses only the available <i>e</i>-Services and (<i>ii</i>) interacts with the client "in accordance" to the given specification. We also study the computational complexity of the proposed algorithm.
Design and implementation of a built-in camera based user interface for mobile games

In this paper, we present a novel user interface design for mobile games using its built-in camera. It is motivated by the problem of limited number of keys on the small keypad of mobile devices. We implement two different ways, with and without the use of markers, to study the effectiveness of the design in a 2-dimensional and 3-dimensional game respectively. The algorithms implemented in the design are lightweight enough so that they are executable in real-time and at the same time, able to produce realism for the games.
A repeat request strategy based on sliding window decoding of unit-memory convolutional codes

In this correspondence, we investigate a decision feedback strategy for convolutional codes which is based on a sliding window decoding procedure and a threshold test as decision rule. For this purpose, we introduce the burst distance spectrum of a convolutional code and derive asymptotic bounds for the ensemble of periodically time-varying convolutional codes. These results are helpful for the asymptotic analysis of the decision feedback scheme. We show that unit memory codes are particularly suited for such a transmission scheme. For these codes, the decoding procedure is reduced to the decoding of block codes with lengths in the order of the overall constraint length of the convolutional code. This leads to a significantly smaller decoding complexity compared with other known decoding and decision rules. Whereas the achievable asymptotic performance is close to the best known bounds. For low rates, our results even improve these bounds.
Reduction of FPGA resources for regular expression matching by relation similarity

Intrusion Detection Systems have to match large sets of regular expressions to detect malicious traffic on multi-gigabit networks. Many algorithms and architectures have been proposed to accelerate pattern matching, but formal methods for reduction of Nondeterministic finite automata have not been used yet. We propose to use reduction of automata by similarity to match larger set of regular expressions in FPGA. Proposed reduction is able to decrease the number of states by more than 32% and the amount of transitions by more than 31%. The amount of look-up tables is reduced by more than 15% and the amount of flip-flops by more than 34%.
Reversing autism by targeting downstream mTOR signaling

Autism spectrum disorders (ASDs) are a group of clinically and genetically heterogeneous neurodevelopmental disorders characterized by impaired social interactions, repetitive behaviors and restricted interests (Baird et al., 2006; Zoghbi and Bear, 2012). The genetic defects in ASDs may interfere with synaptic protein synthesis. Synaptic dysfunction caused by aberrant protein synthesis is a key pathogenic mechanism for ASDs (Kelleher and Bear, 2008; Richter and Klann, 2009; Ebert and Greenberg, 2013). Understanding the details about aberrant synaptic protein synthesis is important to formulate potential treatment for ASDs. The mammalian target of the rapamycin (mTOR) pathway plays central roles in synaptic protein synthesis (Hay and Sonenberg, 2004; Hoeffer and Klann, 2010; Hershey et al., 2012). Recently, Gkogkas and colleagues published exciting data on the role of downstream mTOR pathway in autism (Gkogkas et al., 2013) (Figure ​(Figure11).
Automatically configuring the network layer of data centers for cloud computing

With the requirement of very large data centers for cloud computing, the challenge lies in how to produce a scalable and inexpensive design to interconnect a large number of servers in data centers while providing fault tolerance and high network capacity. Internet Protocol (IP)-based data center networks (DCNs) can support a sufficiently large number of machines and dynamic multi-path routing. However, the complex and error-prone manual configuration of IP-based DCNs hinders its deployment. In this paper, we propose DCZeroconf, a fully automatic IP address configuration mechanism, to eliminate the burden of manual configurations of the IP addresses of servers and switches in data centers. We have implemented a prototype system to validate the effectiveness of DCZeroconf via extensive experiments and simulations. The evaluation results demonstrate that DCZeroconf supports different topologies, and the assigned IP addresses can be automatically adjusted upon dynamic topology changes. In addition, the entire automatic process can be completed in seconds or less.
Population genetic analysis of Arapaima gigas, one of the largest freshwater fishes of the Amazon basin: implications for its conservation

The present study reports the first population genetic analysis of Arapaima gigas, an important but critically over‐exploited fish species of the Amazon basin. We sequenced two discontinuous mitochondrial DNA regions of 1204 base‐pairs (bp) (NADH1 segment) and 1143bp (ATPase segment) from 139 individuals of A. gigas representing eight localities spanning the Amazon basin from Iquitos, Peru to Macapá, Brazil. We discovered 34 haplotypes separated by 44 segregating sites. The two most common haplotypes are shared among all populations and isolation‐by‐distance appears to be the most important population dynamic, although there is no significant association between geographical distance and genetic differentiation. Observed patterns of differentiation appear to be attributable largely to anthropogenic factors associated with over‐exploitation. Greatest haplotypic diversity exists upstream of Manaus and in areas away from large centres of population. The female variance and inbreeding effective population sizes are approximately 150000 individuals and localities in the Amazon basin are connected by gene flow. Naturally low levels of population differentiation and relatively high between‐population connectivity is encouraging for the conservation and management of A. gigas. If strategically placed biological reserves were created throughout the Amazon basin to act as sources of emigrants within a source–sink metapopulation model, we believe locally depleted populations can be re‐populated and maintained by individuals immigrating from these reserves.
Constraints on leptonically annihilating Dark Matter from reionization and extragalactic gamma background

The PAMELA, Fermi and HESS experiments (PFH) have shown anomalous excesses in the cosmic positron and electron fluxes. A very exciting possibility is that those excesses are due to annihilating dark matter (DM). In this paper we calculate constraints on leptonically annihilating DM using observational data on diffuse extragalactic gamma-ray background and measurements of the optical depth to the last-scattering surface, and compare those with the PFH favored region in the m_{DM} - plane. Having specified the detailed form of the energy input with PYTHIA Monte Carlo tools we solve the radiative transfer equation which allows us to determine the amount of energy being absorbed by the cosmic medium and also the amount left over for the diffuse gamma background. We find that the constraints from the optical depth measurements are able to rule out the PFH favored region fully for the \tau^{-}+\tau^{+} annihilation channel and almost fully for the \mu^{-}+\mu^{+} annihilation channel. It turns out that those constraints are quite robust with almost no dependence on low redshift clustering boost. The constraints from the gamma-ray background are sensitive to the assumed halo concentration model and, for the power law model, rule out the PFH favored region for all leptonic annihilation channels. We also find that it is possible to have models that fully ionize the Universe at low redshifts. However, those models produce too large free electron fractions at z > ~100 and are in conflict with the optical depth measurements. Also, the magnitude of the annihilation cross-section in those cases is larger than suggested by the PFH data.
Phylogenetic Analysis of Pasteuria penetrans by 16S rRNA Gene Cloning and Sequencing.

Pasteuria penetrans is an endospore-forming bacterial parasite of Meloidogyne spp. This organism is among the most promising agents for the biological control of root-knot nematodes. In order to establish the phylogenetic position of this species relative to other endospore-forming bacteria, the 16S ribosomal genes from two isolates of P. penetrans, P-20, which preferentially infects M. arenaria race 1, and P-100, which preferentially infects M. incognita and M. javanica, were PCR-amplified from a purified endospore extraction. Universal primers for the 16S rRNA gene were used to amplify DNA which was cloned, and a nucleotide sequence was obtained for 92% of the gene (1,390 base pairs) encoding the 16S rDNA from each isolate. Comparison of both isolates showed identical sequences that were compared to 16S rDNA sequences of 30 other endospore-forming bacteria obtained from GenBank. Parsimony analyses indicated that P. penetrans is a species within a clade that includes Alicyclobacillus acidocaldarius, A. cycloheptanicus, Sulfobacillus sp. , Bacillus tusciae, B. schlegelii, and P. ramosa. Its closest neighbor is P. ramosa, a parasite of Daphnia spp. (water fleas). This study provided a genomic basis for the relationship of species assigned to the genus Pasteuria, and for comparison of species that are parasites of different phytopathogenic nematodes.
Dynamic force/torque measurement using a 12DOF sensor

This article presents an algorithm for dynamic force/torque measurement and robot load identification using the so called 12DOF sensor to measure forces/torques and linear/angular accelerations. The basic equations of dynamic forces and torques arising during robot motion and acting on the end-effector were worked out. To be able to perform the experiments suitable robot system based on a six axes articulated manipulator was constituted. For this system also the appropriate software was developed. The load parameters of the tool were determined during particular motion sequence of the robot and the values were compared with values from CAD software. The compensation of dynamic forces and torques is verified using the experimental robot system and the results are presented.
A sort-based deferred shading architecture for decoupled sampling

Stochastic sampling in time and over the lens is essential to produce photo-realistic images, and it has the potential to revolutionize real-time graphics. In this paper, we take an architectural view of the problem and propose a novel hardware architecture for efficient shading in the context of stochastic rendering. We replace previous caching mechanisms by a sorting step to extract coherence, thereby ensuring that only non-occluded samples are shaded. The memory bandwidth is kept at a minimum by operating on tiles and using new buffer compression methods. Our architecture has several unique benefits not traditionally associated with deferred shading. First, shading is performed in primitive order, which enables late shading of vertex attributes and avoids the need to generate a G-buffer of pre-interpolated vertex attributes. Second, we support state changes, e.g., change of shaders and resources in the deferred shading pass, avoiding the need for a single über-shader. We perform an extensive architectural simulation to quantify the benefits of our algorithm on real workloads.
Effects of Probiotic on Comfort and Body Care Behaviors of Broilers Reared at Different Stocking Densities

This study was conducted to investigate the effect of probiotic on comfort and body care behaviors of broilers reared at two different densities. Two hundred and forty chicks were subdivided into four groups, two groups were reared under low stocking density (LSD); 10 bird/m2 and another 2 groups were reared under high stocking density (HSD); 15 bird/m2. In each density, one group was supplemented with probiotic in the drinking water and the other was not supplemented. Normal behavior of birds was recorded throughout the growing cycle twice a week, using video camera (Sony, Japan). Then after, comfort (standing, lying and sleeping), body care (preening, dust bathing, wing/leg stretching and head scratching) and aggressive behaviors of birds were analyzed. HSD reduced comfort behavior compared to low density without probiotic group. Standing frequency was significantly increased at the 6th week of the growing cycle. In addition, interrupted lying bouts frequency was increased and the non-interrupted lying bouts (frequency and duration) were decreased significantly. Moreover, preening frequency was decreased. However, aggressive behavior was not observed in all groups. Probiotic supplementation didn’t alter comfort, aggressive and body care behaviors of broilers at both densities in comparison to low density without probiotic group. However, birds stocked at high stocking density and supplemented with probiotic showed no alterations in all behavioral patterns compared to HSD group without probiotic supplementation. Data suggested that the used probiotic in this study was unable to improve comfort and body care behaviors of broilers reared at low stocking density and failed to alleviate impacts of high density stress on these behaviors.
CGAP-Align: A High Performance DNA Short Read Alignment Tool

Background Next generation sequencing platforms have greatly reduced sequencing costs, leading to the production of unprecedented amounts of sequence data. BWA is one of the most popular alignment tools due to its relatively high accuracy. However, mapping reads using BWA is still the most time consuming step in sequence analysis. Increasing mapping efficiency would allow the community to better cope with ever expanding volumes of sequence data. Results We designed a new program, CGAP-align, that achieves a performance improvement over BWA without sacrificing recall or precision. This is accomplished through the use of Suffix Tarray, a novel data structure combining elements of Suffix Array and Suffix Tree. We also utilize a tighter lower bound estimation for the number of mismatches in a read, allowing for more effective pruning during inexact mapping. Evaluation of both simulated and real data suggests that CGAP-align consistently outperforms the current version of BWA and can achieve over twice its speed under certain conditions, all while obtaining nearly identical results. Conclusion CGAP-align is a new time efficient read alignment tool that extends and improves BWA. The increase in alignment speed will be of critical assistance to all sequence-based research and medicine. CGAP-align is freely available to the academic community at http://sourceforge.net/p/cgap-align under the GNU General Public License (GPL).
Is Somebody Watching Your Facebook Newsfeed?

With the popularity of Social Networking Services (SNS), more and more sensitive information are stored online and associated with SNS accounts. The obvious value of SNS accounts motivates the usage stealing problem -- unauthorized, stealthy use of SNS accounts on the devices owned/used by account owners without any technology hacks. For example, anxious parents may use their kids' SNS accounts to inspect the kids' social status; husbands/wives may use their spouses' SNS accounts to spot possible affairs. Usage stealing could happen anywhere in any form, and seriously invades the privacy of account owners. However, there is no any currently known defense against such usage stealing. To an SNS operator (e.g., Facebook Inc.), usage stealing is hard to detect using traditional methods because such attackers come from the same IP addresses/devices, use the same credentials, and share the same accounts as the owners do. In this paper, we propose a novel continuous authentication approach that analyzes user browsing behavior to detect SNS usage stealing incidents. We use Facebook as a case study and show that it is possible to detect such incidents by analyzing SNS browsing behavior. Our experiment results show that our proposal can achieve higher than 80% detection accuracy within 2 minutes, and higher than 90% detection accuracy after 7 minutes of observation time.
Quantifying Synergy: A Systematic Review of Mixture Toxicity Studies within Environmental Toxicology

Cocktail effects and synergistic interactions of chemicals in mixtures are an area of great concern to both the public and regulatory authorities. The main concern is whether some chemicals can enhance the effect of other chemicals, so that they jointly exert a larger effect than predicted. This phenomenon is called synergy. Here we present a review of the scientific literature on three main groups of environmentally relevant chemical toxicants: pesticides, metal ions and antifouling compounds. The aim of the review is to determine 1) the frequency of synergy, 2) the extent of synergy, 3) whether any particular groups or classes of chemicals tend to induce synergy, and 4) which physiological mechanisms might be responsible for this synergy. Synergy is here defined as mixtures with minimum two-fold difference between observed and predicted effect concentrations using Concentration Addition (CA) as a reference model and including both lethal and sub-lethal endpoints. The results showed that synergy occurred in 7%, 3% and 26% of the 194, 21 and 136 binary pesticide, metal and antifoulants mixtures included in the data compilation on frequency. The difference between observed and predicted effect concentrations was rarely more than 10-fold. For pesticides, synergistic mixtures included cholinesterase inhibitors or azole fungicides in 95% of 69 described cases. Both groups of pesticides are known to interfere with metabolic degradation of other xenobiotics. For the four synergistic metal and 47 synergistic antifoulant mixtures the pattern in terms of chemical groups inducing synergy was less clear. Hypotheses in terms of mechanisms governing these interactions are discussed. It was concluded that true synergistic interactions between chemicals are rare and often occur at high concentrations. Addressing the cumulative rather than synergistic effect of co-occurring chemicals, using standard models as CA, is therefore regarded as the most important step in the risk assessment of chemical cocktails.
A Social Work Perspective on Seclusion and Restraint in Australia’s Public Mental Health System

ABSTRACT A social work perspective of the nature of seclusion and restraint in Australia’s public mental health systems is presented. The article suggests a theme of seclusion and restraint as a regulatory mechanism despite evidence of harm and even death. The case that the use of seclusion and restraint constitutes a social justice issue as it can be understood as an abuse of human rights and form of torture is established. An incident of a person dying in an Australian mental health facility after being secluded is presented to substantiate this claim. An over focus on individual expressions of violence or risk can be at the expense of understanding the systemic and cultural nature of violence in mental health systems. It is important to understand the nature of, and perhaps to question the presumed necessity of, seclusion and restraint practices to ensure that social workers are not breaching their professional obligations to people who are mental health clients.
Association of the Porcine Cluster of Differentiation 4 Gene with T Lymphocyte Subpopulations and Its Expression in Immune Tissues

Cluster of differentiation 4 (CD4) is mainly expressed on CD4+ T cells, which plays an important role in immune response. The aim of this study was to detect the association between polymorphisms of the CD4 gene and T lymphocyte subpopulations in pigs, and to investigate the effects of genetic variation on the CD4 gene expression level in immune tissues. Five missense mutations in the CD4 gene were identified using DNA pooling sequencing assays, and two main haplotypes (CCTCC and AGCTG) in strong linkage disequilibrium (with frequencies of 50.26% and 46.34%, respectively) were detected in the population of Large White pigs. Our results indicated that the five SNPs and the two haplotypes were significantly associated with the proportions of CD4−CD8−, CD4+CD8+, CD4+CD8−, CD4+ and CD4+/CD8+ in peripheral blood (p<0.05). Gene expression analysis showed the mRNA level of the CD4 gene in thymus was significantly higher than that in lymph node and spleen (p<0.05). However, no significant difference was observed between animals with CCTCC/CCTCC genotype and animals with AGCTG/AGCTG genotype in the three immune tissues (p>0.05). These results indicate that the CD4 gene may influence T lymphocyte subpopulations and can be considered as a candidate gene affecting immunity in pigs.
An FPGA Based Implementation for 2-D Discrete Wavelet transform

A 2-D discrete wavelet transform hardware design based on multiplier design based architecture is presented in this paper. We have proposed based on arithmetic for low complexity and efficient implementation of 2-D discrete wavelet transform. The multiplier design based technique has been applied to reduce the number of delay. This paper provides the clearcut idea in about the application of 8-multiplier and 6- adder in one, two & three level of architecture This architecture is suitable for high speed on-line applications, the most important one being image processing, reduced the area and power in the discrete wavelet transform. With this architecture the speed of the 2-D discrete wavelet transform is increased. It has 100% hardware utilization efficiency
Identifying Mubasher software products through sentiment analysis of Arabic tweets

Social media has recently become a rich resource in mining user sentiments. In this paper, Twitter has been chosen as a platform for opinion mining in trading strategy with Mubasher products, which is a leading stock analysis software provider in the Gulf region. This experiment proposes a model for sentiment analysis of Saudi Arabic (standard and Arabian Gulf dialect) tweets to extract feedback from Mubasher products. A hybrid of natural language processing and machine learning approaches on building models are used to classify tweets according to their sentiment polarity into one of the classes positive, negative and neutral. Firstly, document's Pre-processing are explored on the dataset. Secondly, Naive Bayes and Support Vector Machines (SVMs) are applied with different feature selection schemes like TF-IDF (Term Frequency-Inverse Document Frequency) and BTO (Binary-Term Occurrence). Thirdly, the proposed model for sentiment analysis is expanded to obtain the results for N-Grams term of tokens. Finally, human has labelled the data and this may involve some mistakes in the labelling process. At this moment, neutral class with generalisation of our classification will take results to different classification accuracy.