Miracle-dz/UniFAR-FTUs huggingface dataset:
Polymorphisms on SSC15q21-q26 Containing QTL for reproduction in Swine and its association with litter size

Several quantitative trait loci (QTL) for important reproductive traits (ovulation rate) have been identified on the porcine chromosome 15 (SSC15). To assist in the selection of positional candidate swine genes for these QTL on SSC15, twenty-one genes had already been assigned to SSC15 in a previous study in our lab, by using the radiation hybrid panel IMpRH. Further polymorphism studies were carried out on these positional candidate genes with four breeds of pigs (Duroc, Erhualian, Dahuabai and Landrace) harboring significant differences in reproduction traits. A total of nineteen polymorphisms were found in 21 genes. Among these, seven in six genes were used for association studies, whereby NRP2 polymorphism was found to be significantly (p < 0.05) associated with litter-size traits. NRP2 might be a candidate gene for pig-litter size based on its chromosome location (Du et al., 2006), significant association with litter-size traits and relationships with Sema and the VEGF super families.
New approach to cogging torque simulation using numerical functions

The paper presents a new method for simulation of the cogging torque in a PM machine. The method benefits the numerical functions for modeling the magnetic system of the electrical machine. To compute the cogging torque by the numerical functions, it is necessary to model the permanent magnets and permeance of the machine. In this paper, we introduce two improved numerical functions to model them. The first one is capable of modeling the permanent magnet and it is called the MMF function. This function numerically states the MMF drop on the machine air gap respect to the angular location. The other function models the air gap accurately while the stator saliency due to the teeth is also considered. This function is called the permeance function. The described procedure has been tested on a constructed PM machine. Then the model is simulated and verified by FEM and experiment results.
Reinforcement Learning in Perfect-Information Games ⁄

This paper studies action-based reinforcement learning in finite perfectioninformation games. Restrictions on the valuation updating rule that guarantee that the play eventually converges to a subgame-perfect Nash equilibrium (SPNE) are identified. These conditions are mild enough to contain interesting and plausible learning behavior. We provide two examples of such updating rule that suggest that the extent of knowledge and rationality assumptions needed to support a SPNE outcome in finite perfect-information games may be minimal.
DFT Assisted Techniques for Peak Launch-to-Capture Power Reduction during Launch-On-Shift At-Speed Testing

Scan-based testing is crucial to ensuring correct functioning of chips. In this scheme, the scan and capture phases are interleaved. It is well known that for large designs, excessive switching activity during the launch-to-capture window leads to high voltage droop on the power grid, ultimately resulting in false delay failures during at-speed test. This article proposes a new design-for-testability (DFT) scheme for launch-on-shift (LOS) testing, which ensures that the combinational logic remains undisturbed between the interleaved capture phases, providing computer-aided-design (CAD) tools with extra search space for minimizing launch-to-capture switching activity through test pattern ordering (TPO). We further propose a new TPO algorithm that keeps track of the don't cares during the ordering process, so that the don't care filling step after the ordering process yields a better reduction in launch-to-capture switching activity compared to any other technique in the literature. The proposed DFT-assisted technique, when applied to circuits in ITC99 benchmark suite, produces an average reduction of 17.68% in peak launch-to-capture switching activity (CSA) compared to the best known lowpower TPO technique. Even for circuits whose test cubes are not rich in don't care bits, the proposed technique produces an average reduction of 15% in peak CSA, while for the circuits with test cubes rich in don't care bits (≥75%), the average reduction is 24%. The proposed technique also reduces the average power dissipation (considering both scan cells and combinational logic) during the scan phase by about 43.5% on an average, compared to the adjacent filling technique.
Calibration-free robotic eye-hand coordination based on an auto disturbance-rejection controller

This paper addresses the calibration-free robotic eye-hand coordination in a way other than the conventional image Jacobian matrix approach that has been studied extensively in literature. A nonlinear mapping rather than the linear mapping used in the image Jacobian matrix between the image space and the robotic control space is proposed. This mapping is regarded as the system's unmodeled dynamics expressed in system state equations. An extended state observer is designed first to estimate the unmodeled dynamics as well as the external disturbance of the system. With the estimation results as the compensation, a system controller is designed based on the nonlinear state-error feedback control strategy. Convergence of the extended state observer as well as the overall controller for a typical eye-hand coordination system is proved. Compared with the conventional calibration-free robotic eye-hand coordination with a Jacobian matrix, the proposed controller is independent of specific tasks and system configurations. Thus, a general design procedure is proposed for the calibration-free robotic eye-hand coordination. Simulation and experiment results demonstrate the satisfactory performance and effectiveness of the proposed approach.
Streaming Video over TFRC with Linear Throughput Equation

The TCP-Friendly Rate Control (TFRC) protocol manifests strong equality towards competing TCP or TCPfriendly flows. Although the RFC 3448 suggests that TFRC is suitable for multimedia, this equality is a great disadvantage in the case of transmitting multimedia over the TFRC. The TFRC emulates TCP-like congestion control using the TCP throughput equation. In the paper, we substitute the TCP throughput equation recommended for the TFRC with a linear throughput equation. Simulation results show that the proposed solution is more suitable for multimedia than the equation proposed in RFC 3448. Experiments were carried out using an event-driven ns-2 simulator, developed in U. C. Berkeley.
Applying Ontology-Based Personal Profile for Product Search System

Personal profile can be directly derived from personal registration before user uses product search system. However, this personal profile is not used in general product search system although the search product system is to require to present product user's needs. This paper proposes an approach of semantic product search system through ontological personal profiles. Using ontological personal profile is considered and helps filter of search results by semantic relationship and ontology mapping between personal profile and product details. Our experiments of the product search system show search results based on semantic mapping creation from ontological personal profile to relevant product. The evaluation of the system is measured by average precision, recall and F-measure that give a set of information retrieval by difference personal profiles.
Measuring economic uncertainty using news-media textual data

We develop a news-media textual measure of aggregate economic uncertainty, defined as the fraction of Financial Times articles that contain uncertainty-related keyphrases, at frequencies from daily to annual, from January 1982 to April 2014. We improve on existing similar measures in several ways. First, we reveal extensive and irregular duplication of articles in the news database most widely used in the literature, and provide a simple but effective de-duplication algorithm. Second, we boost the uncertainty ‘signal strength’ by 14% through the simple addition of the word “uncertainties” to the conventional keyword list of “uncertain” and “uncertainty”, and show that adding further uncertainty-related keyphrases would likely constitute only a second-order adjustment. Third, we demonstrate the importance of normalising article counts by total news volume and provide the first textual uncertainty measure to do so for the UK. We empirically establish the plausibility of our measure as an uncertainty proxy through a detailed narrative analysis and a detailed comparative analysis with another popular uncertainty proxy, stock returns volatility. We show the relationship between these proxies is strong and significant on average, but breaks down periodically. We offer plausible explanations for this behaviour. We also establish the absence of Granger causation between the measures, even down to daily (publication) frequency.
Are Friendly Farmers Environmentally Friendly? Effect of Community Involvement on Environmental Awareness

We study if community involvement makes an individual more environmentally friendly. An individual with greater attachment to the community is likely to be more socially responsible. They are also more likely to have better exposure and access to information about the importance of the environment and environmentally friendly practices. Using associational memberships as a measure of community involvement we study its effects on agricultural practices among Georgia farmers. Our findings showed that, first, community involvement had a positive effect on the decision to adopt environmentally friendly agricultural practices, and, secondly, it also had a positive effect on the extent to which farmers adopt these practices. These findings establish an additional dimension to the benefits that would accrue to policies that promote social interaction and civic engagement in rural areas associated with farming.
On the spurious solutions of the Fastica algorithm

The present contribution deals with the statistical tool of Independent Component Analysis (ICA). The focus is on Fas-tICA, arguably the most popular algorithm in the domain of ICA. Despite its success, it is observed that FastICA occasionally yields outcomes that do not correspond to any solutions of ICA. These outcomes are called spurious solutions. In this work, we give a thorough and rigorous investigation of the spurious solutions of FastICA. We characterize various sets of interest and show that the kurtosis-based FastICA is theoretically free of spurious solutions. Examples are given, showing that in certain scenarios, popular nonlinearities such as “Gauss” or “tanh” systematically yield spurious solutions, whereas only “kurtosis” may give reliable results.
Content-based Multimedia Indexing and Retrieval Integrating Keywords and Contents Unifying Keywords and Visual Contents in Image Retrieval the Proposed Method Joint Querying and Relevance Feedback Texture Features Structure Features Text Annotations Color Features Figure 1. an Image Object with Both

We're interested in using keywords and visual content together in image retrieval. We used a seamless joint querying and relevance feedback scheme based on keywords and low-level visual content, incorporating keyword similarities. We developed an algorithm for a learned word similarity matrix and conducted experiments that validated our approach. A s an interdisciplinary research field, multimedia information retrieval addresses and explores both text-based indexing and processing issues and multidimensional signal/information processing techniques. The performance of a content-based image retrieval (CBIR) system is inherently constrained by low-level features, and it can't give satisfactory retrieval results in many cases, especially when users' high-level concepts aren't easily expressed by low-level features. (Please see some of the other resources 1,2 we've cited for state-of-the-art attempts in associating low-level features with high-level semantic concepts and their limits.) Therefore, for real-world applications, CBIR systems should feature textual annotations to improve the retrieval performance. In this article we explore the unification of keywords and feature contents for image retrieval. We propose a seamless joint querying and relevance feedback scheme based on both keywords and low-level visual contents incorporating keyword similarities. We propose an algorithm for the learning of the word similarity matrix (we use word, term, or concept similarity matrix interchangeably throughout this article) during user interaction, namely word association via relevance feedback (WARF). We can apply this learned similarity matrix, specific to the data set and the users, for keyword semantic grouping, thesaurus construction, and soft query expansion during intelligent image retrieval. In the area of CBIR, despite advances in feature selection algorithms and matching and retrieval techniques, current systems still have major difficulties relating low-level features to high-level semantics. From our extensive experiments on CBIR systems using features such as color, texture, structure, spatial layout, and relevance feedback from users, it's apparent that low-level contents often don't describe the high-level semantic concepts in users' minds. This is one of the major burdens in implementing a CBIR system for practical image retrieval applications. To overcome this burden, we should unify text-based retrieval with content-based retrieval. Actually, most of the online commercial image databases are annotated with keywords and descriptions or organized into categories. Some researchers have addressed this problem from various standpoints, 3–5 but no one has focused on the issues of online learning of term similarity matrix and word grouping for intelligent query expansion, which we emphasize in this article. Keywords have more direct mapping …
Distributed Source Coding for Multimedia Multicast Over Heterogeneous Networks

Real-time multimedia multicast over wireless networks is an exciting application that has generated a lot of interest recently. Its main challenge lies in the stringent bandwidth and time-delay requirements of real-time multimedia and severe impairments of the wireless channels. We develop a network-aware cross-layer design for multimedia multicast over heterogeneous wireless-wireline networks, that leverages the knowledge on network information theory, multimedia processing, error control, and networking. In particular, the encoded multimedia data are broadcast to multiple Internet servers over a wireless radio link. Each server merely compresses the signal it has received using distributed source coding by exploiting mutual correlation among signals received at different servers. The receiver collects bitstreams from the servers before performing joint decoding. We provide an algorithm for optimal nonuniform scalar quantizer design at the server side that minimizes the required rate under the decoder bit error rate constraint. For scalable multimedia codes, we develop a joint source-channel coding scheme which combines error-protection at the base station and distributed source coding at the servers. Our experimental results show significant performance improvements over conventional solutions due to spatial diversity and distributed source coding gains.
Identification of cis-Regulatory Elements in the Mammalian Genome: The cREMaG Database

Background A growing number of gene expression-profiling datasets provides a reliable source of information about gene co-expression. In silico analyses of the properties shared among the promoters of co-expressed genes facilitates the identification of transcription factors (TFs) involved in the co-regulation of those genes. Our previous experience with microarray data led to the development of a database suitable for the examination of regulatory motifs in the promoters of co-expressed genes. Methodology We introduce the cREMaG (cis-Regulatory Elements in the Mammalian Genome) system designed for in silico studies of the promoter properties of co-regulated mammalian genes. The cREMaG system offers an analysis of data obtained from human, mouse, rat, bovine and canine gene expression-profiling studies. More than eight analysis parameters can be utilized in user-defined combinations. The selection of alternative transcription start sites and information about CpG islands are also available. Conclusions Using the cREMaG system, we successfully identified TFs mediating transcriptional responses in reference gene sets. The cREMaG system facilitates in silico studies of mammalian transcriptional gene regulation. The resource is freely available at http://www.cremag. org.
3D path following with no bounds on the path curvature through surface intersection

The article proposes a new feedback control model which is suited for path following in a 3 Dimensional Cartesian space. Differently from other methods in literature, the method proposed neither requires to compute a projection of the robot's position on the path, nor it needs considering a moving virtual target. In spite of this: i) it guarantees asymptotic stability for every 3D curve which can be represented through a couple of intersecting surfaces f1(X, Y,Z) = 0, f2(X, Y,Z) = 0; ii) it does not put any bounds on the initial position of the vehicle depending on the path's curvature.
A Symbol Based Watermarking Approach for Spread Spectrum Audio Watermarking Methods

This paper proposes an high embedding capacity symbol based audio watermarking process. The traditional watermark embedding processes require longer duration audio sequence in order to accommodate all the input watermark bits. Shorter duration audio sequences which are like advertisements in Television &amp; Radio should allow the embedding of a complete watermark at least once to be able to correctly identify the owner or content. A symbol based approach for spread spectrum based audio watermark methods has been proposed in order to reduce the required size of the audio sequences for watermarking. Each group of watermark bits called as a symbol are mapped to a unique pseudo-random sequence. These PN sequence are used for actual embedding in Spread Spectrum based watermarking technique. This process while reducing the size of the audio sequence required, it also helps in reducing the errors in longer duration audio as it can allow redundant addition of watermark. An error correction method is also added to further reduce the symbol errors that are caused due to the intentional and unintentional watermark removal attacks.
PAPA: Physiology and Purpose-Aware Automatic Playlist Generation

In this paper we present PAPA, a novel approach for automatically generating playlists. The proposed framework utilizes the user’s physiological response to music, together with traditional song meta-data to generate a playlist the user will not only enjoy, but which will assist him or her in achieving various user-defined goals (“purpose”). In addition to outlining the generic framework, we present an exemplary application named MPTrain that (1) creates a playlist in real-time to assist users in achieving specific exercise goals; and (2) incorporates the user’s physiological response to the music to determine the next song to play.
Challenges in Designing Low-Power CMOS Wireless Systems-on-a-Chip

This paper describes the challenges in designing low-power CMOS systems-on-a-chip for wireless communications. RF transceiver building blocks for signal amplification, frequency translation, and frequency selectivity are examined with special emphasis on low noise amplifier, power amplifier, mixer, and frequency synthesizer. System-on-a-chip integration issues to relevant to a low-power CMOS design are also discussed
A Link between the Increase in Electroencephalographic Coherence and Performance Improvement in Operating a Brain-Computer Interface

We study the relationship between electroencephalographic (EEG) coherence and accuracy in operating a brain-computer interface (BCI). In our case, the BCI is controlled through motor imagery. Hence, a number of volunteers were trained using different training paradigms: classical visual feedback, auditory stimulation, and functional electrical stimulation (FES). After each training session, the volunteers' accuracy in operating the BCI was assessed, and the event-related coherence (ErCoh) was calculated for all possible combinations of pairs of EEG sensors. After at least four training sessions, we searched for significant differences in accuracy and ErCoh using one-way analysis of variance (ANOVA) and multiple comparison tests. Our results show that there exists a high correlation between an increase in ErCoh and performance improvement, and this effect is mainly localized in the centrofrontal and centroparietal brain regions for the case of our motor imagery task. This result has a direct implication with the development of new techniques to evaluate BCI performance and the process of selecting a feedback modality that better enhances the volunteer's capacity to operate a BCI system.
Red fish, blue fish: trade-offs between pigmentation and immunity in Betta splendens

Carotenoid pigments are responsible for many examples of sexually attractive red, orange, and yellow coloration in animals and play an important role in antioxidant and immune defenses. Because vertebrates cannot synthesize carotenoids, limited dietary availability may impose a trade-off between maintaining ornamental coloration and health. We used an experimental approach to test the carotenoid trade-off hypothesis in the fighting fish Betta splendens, by examining whether carotenoid allocation strategies differ among conspecifics that exhibit a gradient of body coloration from blue to red. We found that male redness is underlain by carotenoids and that females preferred to associate with red males over blue males, suggesting a sexually-selected advantage to being red. Moreover, we found strong experimental support for the carotenoid trade-off hypothesis, as individuals that varied in color did not appear to allocate carotenoids equally to both immune response and coloration. Redder fish given supplemental carotenoids increased in both immune response (to a phytohemagglutination challenge) and redness compared with controls. In contrast, bluer fish given supplemental carotenoids did not become more red but instead benefited immunologically more so than either control or redder supplemented fish. These results enhance our understanding of the evolution and plasticity of carotenoid mobilization and utilization pathways in animals. Copyright 2007, Oxford University Press.
A Survey on Enhanced Human Identification Using Gait Recognition based on Neural Network And Support Vector Machine

Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation. Controlled environments such as banks, military installations and even airports need to be able to quickly detect threats and provide differing levels of access to different user groups. Gait shows a particular way or manner of moving on foot and gait recognition is the process of identifying an individual by the manner in which they walk. Gait is less unobtrusive biometric, which offers the possibility to identify people at a distance, without any interaction or co-operation from the subject; this is the property which makes it so attractive. This paper proposed new method for gait recognition. In this thesis I will present the review of gait recognition system, different approaches and classification categories of Gait recognition like Model Free Approach, GMM for background substraction, Silhouette Segmentation. We combinedly used SVM(Support vector Machine) with NN(Neural Network) then compare it with BPNN