Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian Approach to Inference and Prediction for Spatially Correlated Count Data Based on Gaussian Copula Model

Gaussian Copula has been successfully applied in spatially correlated count data due to its ability to completely model the high-dimensional dependence. In this article, we develop a Bayesian method to fulfill both parameter estimation and spatial prediction for spatially correlated count data set. A MCMC scheme (MetropolisCHastings Algorithm plus rejection sampling) is adopted to iteratively update parameter estimates; upon convergence the parameters are then used for spatial (missing count data) prediction. In terms of parameter estimation, we show that our approach yields better and more consistent results than the existing method and that our approach can significantly decrease computational burden, in the same real-life data set. Moreover, we compare the spatial prediction performance to the common Generalized Additive Models (GAM). The results in the real-life dataset as well as a well-designed simulated data set both demonstrate that our approach outperforms GAMs, especially when the missing data is small.
Neural Network Reinforcement Learning for Walking Control of a 3-Link Biped Robot

In recent years, researches on adaptive control have focused on bio-inspired learning techniques to deal with real-life applications. Reinforcement Learning (RL) is one of these major techniques, which has been widely used in robot control approaches. The implementation of artificial neural networks in RL algorithms enables more efficient optimal control strategies. This article proposes a field application of neural network reinforcement learning (NNRL) for walking control of an active simulated 3-link biped robot. The adaptive control agent consists of two neural network units, known as actor and critic for learning prediction and learning control tasks. Results of the presented control method reveal its efficiency in stable walking control of the biped robot model as a nonlinear complex dynamic task.
Face Verification by Using Sparse Representation Algorithm in Compressive Sensing

 Abstract— Face verification, a part of security systems, is widely used in many applications. This biometric application is more hygienic comparing with other biometric systems since there is no direct contact between face and camera. Moreover, it is a low cost setup. A sparse representation algorithm as a part of compressive sensing was used in this paper with the accuracy achieved up to 88% during non-optimized sensing matrix and with the average time process of 4.37 seconds. The accuracy achieved was 94% during optimized sensing matrix but the average time process was slower at 8.73 seconds. Encryption process also happened during the image compression which not only reduced the size of the image but also increased the data security.
Non-causal non-parametric multi-scale Markov Random Field synthesis of volumetric textures from a unique 2D sample

We propose a genuine 3D texture synthesis algorithm based on a probabilistic 2D Markov Random Field conceptualization. We intend to reproduce, in the volumetric texture, the interactions between pixels learned non-parametrically in an input 2D image. Optimization is handled voxel by voxel by a deterministic algorithm, deciding for each voxel the most probable grey level. Variants are proposed regarding the heuristic strategies used for the simultaneous handling of the orthogonal slices containing the voxel. Voxel relaxation and scale handling policies are al so investigated. The procedures are materialized on various textures to identify their strengths and weaknesses.
Privacy and Secrecy: A Conceptual Comparison

Privacy and secrecy both involve boundaries and the denial of access to others; however, they differ in the moral content of the behavior which is concealed. Privacy is consensual where secrecy is not; that is, there is a “right to privacy” but no equivalent “right to secrecy. ” Those stigmatized or disadvantaged social groups who have little or no access to privacy utilize secrecy to conceal their behavior. The private family and the secret homosexual world are examples of groups which utilize privacy and secrecy, respectively.
Add Cartesian Differential Invariants to Minimum Description Length Shape Models

The minimum description length approach can automatic solve the point correspondence problem and give the better statistical shape models than those built by hand or equally spaced way. The current mdl approaches build the models only based on the segmented shapes without considering the local image structure and may place the markers at wrong places. This paper adds Cartesian differential invariants to the Minimum Description Length Shape Models and uses it to get better models.
Near-field measurements and dual-tuned matching of two CDRA versions for combined 1H/23Na 7T-MRI

First near-field measurement results of two different congeneric dual resonant antennas (CDRAs) are presented in this paper. Each CDRA generates a half-wavelength current distribution at two desired resonance frequencies tailored to the magnetic resonance frequency of 1H- and 23Na-nuclei for 7 Tesla magnetic resonance imaging (MRI). Furthermore, the dual-tuned matching and feeding networks for these antenna types are discussed and shown in this paper as well. The presented CDRAs are based on composite right/left-handed (CRLH) transmission lines terminated with open or short circuits providing two different current and field distributions between both CDRA versions.
Security and Trust in Electronic Commerce - Finding the Safe Side

E-commerce is a new world generated from economy it makes the life easier for bidders and buyers. Both can sign in giant projects or transactions without making any kind of effort (you control everything from your home); However, there is another side making the best of efforts to frustrate, handle or hack the e-commerce transaction. So how can we protect it? If we succeed in the protection, what are ways that could help the organization to gain the consumer's trust? This paper will discuss the security of e- commerce, after that it will cover trust between consumers and the other side; to make the consumers sail smoothly in the sea of E-commerce without any constraints.
Approaching a topological phase transition in Majorana nanowires

Recent experiments have produced mounting evidence of Majorana zero modes in nanowire-superconductor hybrids. Signatures of an expected topological phase transition accompanying the onset of these modes nevertheless remain elusive. We investigate a fundamental question concerning this issue: Do well-formed Majorana modes necessarily entail a sharp phase transition in these setups? Assuming reasonable parameters, we argue that finite-size effects can dramatically smooth this putative transition into a crossover, even in systems large enough to support well-localized Majorana modes. We propose overcoming such finite-size effects by examining the behavior of low-lying excited states through tunneling spectroscopy. In particular, the excited-state energies exhibit characteristic field and density dependence, and scaling with system size, that expose an approaching topological phase transition. We suggest several experiments for extracting the predicted behavior. As a useful byproduct, the protocols also allow one to measure the wire's spin-orbit coupling directly in its superconducting environment.
2 GHz low power double edge triggered flip-flop in 65nm CMOS technology

This paper proposed a low power, Double-edge-triggered flip-flop design in 65nm CMOS technology. The proposed DETFF is having fewer clocked transistors than earlier conventional designs. The DETFF is simulated with different clock frequencies ranging from 400MHz to 2GHz. Simulation results show least delay, lowest power dissipation than older designs. Further, at scaled voltages the average power dissipation is improved by 46.85% and 96.60% when compared with DETFF1 and DETFF2 respectively and improvement in PDP is 58% and 97.54% as compared to DETFF1 and DETFF2 respectively, which claims that proposed design is suitable for low power, low voltage and high speed applications.
Acetazolamide for the prevention of acute mountain sickness--a systematic review and meta-analysis.

BACKGROUND Acetazolamide has been reported to be effective in the prevention of acute mountain sickness (AMS). Our aim was to conduct a systematic review of randomized, placebo-controlled trials of acetazolamide in the prevention of AMS. METHODS Studies were identified by searching the MEDLINE, Embase, Cochrane Clinical Trials Register, and ClinicalTrials.gov databases. Primary end point was difference in incidence of AMS between acetazolamide and placebo groups. RESULTS Acetazolamide prophylaxis was associated with a 48% relative-risk reduction compared to placebo. There was no evidence of an association between efficacy and dose of acetazolamide. Adverse effects were often not systematically reported but appeared to be common but generally mild. One study found that adverse effects of acetazolamide were dose related. CONCLUSIONS Acetazolamide is effective prophylaxis for the prevention of symptoms of AMS in those going to high altitude. A dose of 250 mg/day has similar efficacy to higher doses and may have a favorable side-effect profile.
Effect of Icon Styles on Cognitive Absorption and Behavioral Intention of Low Literate Users

Information and communication technologies (ICT) are being considered as one of the most potential medium for bringing more efficient and sustainable solution for many problems faced by different communities belong to the middle of economic pyramid of developing countries. Mobile phone based applications can offer many potential solutions for such problems. Existing solutions which are quite successful at the top of the pyramid user population often prove itself ineffective at the middle of the pyramid naive low-literate users. In this context interface designers also face considerable challenges due to lack of consolidate icon design methodology which can be adapted for the target user sections. Therefore we propose an empirical study to address the requirement of concrete icon design methodology. Grounded in ‘Cognitive Absorption’ and ‘Theory of Metaphor’ we propose a concrete design guidelines specifically for designing icons to ensure instant learning, usage and adaptation of the system for daily usage. A mobile pest management system is developed to bring the real context on which design methodologies and the role of cognitive absorption and metaphor can be examined to identify the most appropriate one. Our preliminary study suggests a comprehensive icon design methodology and its effect on cognitive absorption as well as behavioral intention for low literate
Evolutionary deployment optimization for service‐oriented clouds

This paper focuses on service deployment optimization in cloud computing environments. In a cloud, an application is assumed to consist of multiple services. Each service in an application can be deployed as one or more service instances. Different service instances operate at different quality of service (QoS) levels depending on the amount of computing resources assigned to them. In order to satisfy given performance requirements, i.e. service level agreements (SLAs), each application is required to optimize its deployment configuration such as the number of service instances, the amount of computing resources to assign and the locations of service instances. Since this problem is NP‐hard and often faces trade‐offs among conflicting QoS objectives in SLAs, existing optimization methods often fail to solve it. mathrmE3‐R is a multiobjective genetic algorithm that seeks a set of Pareto‐optimal deployment configurations that satisfy SLAs and exhibit the trade‐offs among conflicting QoS objectives. By leveraging queueing theory, E3‐R estimates the performance of an application and aids defining SLAs in a probabilistic manner. Moreover, E3‐R automatically reduces the number of QoS objectives and improves the quality of solutions further. Experimental studies demonstrate that E3‐R efficiently obtains quality deployment configurations that satisfy given SLAs. Copyright © 2011 John Wiley & Sons, Ltd.
Welfare Magnet Hypothesis, Fiscal Burden and Immigration Skill Selectivity

In this paper, we investigate the effect of welfare state generosity on the difference between skilled and unskilled migration rates, and the role of mobility restriction in shaping this effect. We utilize the free labor movement within the European Union plus Norway and Switzerland (EUR) and the restricted movement from outside the EUR in order to compare the free-migration regime to the restricted-migration regime. We find strong support for the magnet hypothesis under the free-migration regime, and the fiscal burden hypothesis under the restricted-migration regime, even after controlling for differences in educational quality and returns to skills in source and host countries.
Lipopolysaccharide (LPS)-binding protein accelerates the binding of LPS to CD14

CD14 is a 55-kD protein found as a glycosylphosphatidylinositol (GPI)- anchored protein on the surface of monocytes, macrophages, and polymorphonuclear leukocytes, and as a soluble protein in the blood. Both forms of CD14 participate in the serum-dependent responses of cells to bacterial lipopolysaccharide (LPS). While CD14 has been described as a receptor for complexes of LPS with LPS-binding protein (LBP), there has been no direct evidence showing whether a ternary complex of LPS, LBP, and CD14 is formed, or whether CD14 binds LPS directly. Using nondenaturing polyacrylamide gel electrophoresis (native PAGE), we show that recombinant soluble CD14 (rsCD14) binds LPS in the absence of LBP or other proteins. Binding of LPS to CD14 is stable and of low stoichiometry (one or two molecules of LPS per rsCD14). Recombinant LBP (rLBP) does not form detectable ternary complexes with rsCD14 and LPS, but it does accelerate the binding of LPS to rsCD14. rLBP facilitates the interaction of LPS with rsCD14 at substoichiometric concentrations, suggesting that LBP functions catalytically, as a lipid transfer protein. Complexes of LPS and rsCD14 formed in the absence of LBP or other serum proteins strongly stimulate integrin function on PMN and expression of E-selectin on endothelial cells, demonstrating that LBP is not necessary for CD14-dependent stimulation of cells. These results suggest that CD14 acts as a soluble and cell surface receptor for LPS, and that LBP may function primarily to accelerate the binding of LPS to CD14.
Modulation of the Fusiform Face Area following Minimal Exposure to Motivationally Relevant Faces: Evidence of In-group Enhancement (Not Out-group Disregard)

Studies have shown that fusiform face area (FFA) activity increases with visual expertise. We present an fMRI study showing that faces from a social category made relevant by an experimental manipulation (members of an experimentally created in-group) preferentially recruited the FFA even when they were matched in exposure to face stimuli from a less significant social category (members of an experimentally created out-group). Faces were randomly assigned to groups and fully counterbalanced so that no perceptual cues allowed participants to visually distinguish category membership. The results revealed a pattern of in-group enhancement (not out-group disregard), such that the FFA was selectively engaged following the presentation of in-group compared with out-group or unaffiliated control faces even when the intergroup distinction was arbitrary, and exposure to in-group and out-group faces was equivalent and brief. In addition, individual differences in FFA activity for in-group versus out-group faces were correlated with recognition memory differences for in-group and out-group faces. The effects of group membership on the FFA were not affected by task instruction to respond to in-group or out-group members and were functionally dissociated from early visual processing in the primary visual cortex. This study provides evidence that the FFA is sensitive to top–down influences and may be involved in subordinate level (vs. superordinate level) encoding of stimuli in the absence of long-term exposure or explicit task instructions.
A research for intelligent cotton picking robot based on machine vision

Analysing the cotton picker in current situation of China, this paper proposed a new design of Intelligent Cotton Picking Robot (ICPR) based on machine vision including the motion control subsystem and machine vision subsystem. The former adopts the YASKAWA MP2100 as the core, which can control the robot of 4-DOF and X-axis. The latter based on the interface module of SEED-VPM642 with 2-CCD cameras, can get an efficient and precise recognition. The identification of mature cotton is one of the critical tasks in this robotic application. According to the statistic experiments and analysis, an optimized segmentation algorithm based on chromatic aberration is studied. The results demonstrate that the method for cotton recognition is well done and the increased pace helps improve the speed of the processing.
Greedy or Not? Best Improving versus First Improving Stochastic Local Search for MAXSAT

Stochastic local search (SLS) is the dominant paradigm for incomplete SAT and MAXSAT solvers. Early studies on small 3SAT instances found that the use of “best improving” moves did not improve search compared to using an arbitrary “first improving” move. Yet SLS algorithms continue to use best improving moves. We revisit this issue by studying very large random and industrial MAXSAT problems. Because locating best improving moves is more expensive than first improving moves, we designed an “approximate best” improving move algorithm and prove that it is as efficient as first improving move SLS. For industrial problems the first local optima found using best improving moves are statistically significantly better than local optima found using first improving moves. However, this advantage reverses as search continues and algorithms must explore equal moves on plateaus. This reversal appears to be associated with critical variables that are in many clauses and that also yield large improving moves.
Applications of wavelet transforms in electric power quality: Harmonic distortion

Wavelet transform is, at present, one of the most useful digital signal processing tools for time-frequency analysis of power quality disturbances in power systems. This paper presents a review of the applications of wavelet transforms in the measurement and analysis of harmonic distortion in power systems, discussing the performance, advantages and limitations of the different methods proposed in the technical literature.
The role of the neutrophil and phagocytosis in infection caused by Helicobacter pylori

Recent advances in our understanding of Helicobacter pylori-phagocyte interactions indicate that these organisms actively modulate phagocyte function in order to retard phagocytosis, while simultaneously inducing a strong respiratory burst. The central players in this dynamic include H. pylori neutrophil activating protein and factors that are associated with the cag pathogenicity island type IV secretion apparatus. Additionally, catalase, alkyl hydroperoxide reductase, and factors that are unique to type I strains allow bacteria to resist phagocytic killing.
Nitric oxide and salicylic acid signaling in plant defense.

Salicylic acid (SA) plays a critical signaling role in the activation of plant defense responses after pathogen attack. We have identified several potential components of the SA signaling pathway, including (i) the H(2)O(2)-scavenging enzymes catalase and ascorbate peroxidase, (ii) a high affinity SA-binding protein (SABP2), (iii) a SA-inducible protein kinase (SIPK), (iv) NPR1, an ankyrin repeat-containing protein that exhibits limited homology to IkappaBalpha and is required for SA signaling, and (v) members of the TGA/OBF family of bZIP transcription factors. These bZIP factors physically interact with NPR1 and bind the SA-responsive element in promoters of several defense genes, such as the pathogenesis-related 1 gene (PR-1). Recent studies have demonstrated that nitric oxide (NO) is another signal that activates defense responses after pathogen attack. NO has been shown to play a critical role in the activation of innate immune and inflammatory responses in animals. Increases in NO synthase (NOS)-like activity occurred in resistant but not susceptible tobacco after infection with tobacco mosaic virus. Here we demonstrate that this increase in activity participates in PR-1 gene induction. Two signaling molecules, cGMP and cyclic ADP ribose (cADPR), which function downstream of NO in animals, also appear to mediate plant defense gene activation (e.g., PR-1). Additionally, NO may activate PR-1 expression via an NO-dependent, cADPR-independent pathway. Several targets of NO in animals, including guanylate cyclase, aconitase, and mitogen-activated protein kinases (e.g., SIPK), are also modulated by NO in plants. Thus, at least portions of NO signaling pathways appear to be shared between plants and animals.
Unification of dynamic gait generation methods via variable virtual gravity and its control performance analysis

The authors have clarified the mechanism of passive dynamic walking from the mechanical energy point of view, and reported its basic results. This paper then considers the generalization and unification of dynamic gait generation methods by introducing variable virtual gravity concept and some solution formulas as well as essential mechanical energy orbits. As two leading methods, energy tracking control and virtual passive dynamic walking are considered, and we analyze the control performances of robust stability and energy-efficiency criterions by numerical simulations. Finally we discuss the application possibility of the methods to actual walking machines from the ZMP point of view.
Robust synthetic biology design: stochastic game theory approach

Motivation: Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. Results: A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi–Sugeno (T–S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. Availability: http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement. pdf Contact: bschen@ee.nthu.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online.