Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Spectrum Sharing Based on Two-Path Successive Relaying

A spectrum sharing scheme is proposed for overlaid wireless networks based on the decode-and-forward two-path successive relaying technique. In this scheme, two secondary transmitters are used to transmit secondary information alternately to their respective receivers while relaying the primary signal at the same time. The transmission of the primary system is continuous, and the secondary system can opportunistically help the primary transmission in exchange for the spectrum sharing. Superposition coding is used at the secondary transmitters, where the primary signal and secondary signal are linearly combined. Successive interference decoding and cancelation is performed by secondary users to extract their desired signals. For the primary system, joint decoding is performed by treating the secondary signal as noise at the receiver side. The optimal power allocation is determined to maximize the success probability of the secondary system without violating the outage performance of the primary system. Numerical and simulation results show that the proposed scheme can conservatively protect the primary performance while realizing the secondary transmission requirement.
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A Multi-Bit Fully Homomorphic Encryption with Shorter Public Key from LWE

The efficiency of fully homomorphic encryption is a big question at present. To improve efficiency of fully homomorphic encryption, we use the technique of packed ciphertext to construct a multi-bit fully homomorphic encryption based on Learning with Errors problem. Our scheme has a short public key. Since our fully homomorphic encryption scheme builds on the basic encryption scheme that choose Learning with Errors samples from Gaussian distribution and add Gaussian error to it, which result in that the number of Learning with Errors samples decrease from 2nlogq to n+1. We prove that our fully homomorphic encryption scheme is feasible and its security relies on the hardness of Learning with Errors problem. In addition we adapt the optimization for the process of key switching from GHS13 and formal this new process of key switching for multi-bit fully homomorphic encryption. At last, we analyze the concert parameters and compare these parameters between our scheme and GHS13 scheme. The data show that our scheme has public key smaller by a factor of about logq than it in GHS13 scheme.
Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms.
Anthropomorphic finger antagonistically actuated by SMA plates

Most robotic applications that contain shape memory alloy (SMA) actuators use the SMA in a linear or spring shape. In contrast, a novel robotic finger was designed in this paper using SMA plates that were thermomechanically trained to take the shape of a flexed human finger when Joule heated. This flexor actuator was placed in parallel with an extensor actuator that was designed to straighten when Joule heated. Thus, alternately heating and cooling the flexor and extensor actuators caused the finger to flex and extend. Three different NiTi based SMA plates were evaluated for their ability to apply forces to a rigid and compliant object. The best of these three SMAs was able to apply a maximum fingertip force of 9.01N on average. A 3D CAD model of a human finger was used to create a solid model for the mold of the finger covering skin. Using a 3D printer, inner and outer molds were fabricated to house the actuators and a position sensor, which were assembled using a multi-stage casting process. Next, a nonlinear antagonistic controller was developed using an outer position control loop with two inner MOSFET current control loops. Sine and square wave tracking experiments demonstrated minimal errors within the operational bounds of the finger. The ability of the finger to recover from unexpected disturbances was also shown along with the frequency response up to 7 rad s−1. The closed loop bandwidth of the system was 6.4 rad s−1 when operated intermittently and 1.8 rad s−1 when operated continuously.
Multilingual Dependency Learning: Exploiting Rich Features for Tagging Syntactic and Semantic Dependencies

This paper describes our system about multilingual syntactic and semantic dependency parsing for our participation in the joint task of CoNLL-2009 shared tasks. Our system uses rich features and incorporates various integration technologies. The system is evaluated on in-domain and out-of-domain evaluation data of closed challenge of joint task. For in-domain evaluation, our system ranks the second for the average macro labeled F1 of all seven languages, 82.52% (only about 0.1% worse than the best system), and the first for English with macro labeled F1 87.69%. And for out-of-domain evaluation, our system also achieves the second for average score of all three languages.
Hierarchical constraint-based singularity avoidance

A reflexive approach for the hierarchical constraint-based singularity avoidance is proposed and demonstrated on the example of a two-link planar robot. The method is based on the concept of lower level constraint adaptation by introducing virtual velocity constraints in relation to higher level system states and on the concept of anisotropic reflexive trajectory deflection. Constraints adaptation utilizes a metaphor of virtual damping the end effector in task space. Clipping errors in joint space are transferred to the task space using the robot's Jacobi matrix and a deviation parameter-matrix. Thus the position and velocity control behavior in the vicinity of a singular configuration is influenced in a way that this singularity can be safely avoided and constraints in the task and joint space can be hold. Furthermore, redundant degrees of freedom can be used to minimize the position error reflexively without calculating new trajectories.
Characterological and behavioral self-blame in children: Assessment and development considerations

Abstract A new instrument, the Why It Happened questionnaire, was developed for assessing characterological and behavior self-blame in two samples of third- through ninth-grade children (Sample 1: n = 121; sample 2: n = 322). Children's responses were very consistent within specific classes of negative events but only moderately consistent across time. Exploratory and confirmatory factor analyses of open-ended and self-rating responses, respectively, revealed that children's self-blame attributions were only moderately consistent across different classes of negative events, and that children's tendency to make characterological and behavioral attributions were unrelated for academic events and moderately correlated for social events. Multiple regression revealed that characterological self-blame about academic and social events were not significantly related to self-reported depression until ninth grade. Implications for cognitive diathesis-stress models of depression for children are discussed.
Learning Hawkes Processes from Short Doubly-Censored Event Sequences

Many real-world applications require robust algorithms to learn point processes based on a type of incomplete data — the so-called short doubly-censored (SDC) event sequences. We study this critical problem of quantitative asynchronous event sequence analysis under the framework of Hawkes processes by leveraging the idea of data synthesis. Given SDC event sequences observed in a variety of time intervals, we propose a sampling-stitching data synthesis method, sampling predecessors and successors for each SDC event sequence from potential candidates and stitching them together to synthesize long training sequences. The rationality and the feasibility of our method are discussed in terms of arguments based on likelihood. Experiments on both synthetic and real-world data demonstrate that the proposed data synthesis method improves learning results indeed for both time-invariant and time-varying Hawkes processes.
Combustible gases and early fire detection: an autonomous system for wireless sensor networks

Fires or toxic gas leakages may have grave consequences like significant pecuniary loss or even lead to human victims. In this paper we present an autonomous wireless sensor system for early fire and gas leak detection. The system consists of two modules: a gas sensor module and a power management module. The operation of the gas sensor module is based on the pyrolysis product detection which makes it possible to detect fire before inflammation. In addition, the on board gas sensor can identify the type of leaking gas. A generic energy scavenging module, able to handle both alternating current and direct current based ambient energy sources, provides the power supply for the gas sensor module. The harvested energy is stored in two energy buffers of different kind, and is delivered to the sensor node in accordance to an efficient energy supply switching algorithm. At the end of the paper we demonstrate the experimental results on gas detection, energy consumption evaluation, and show how to ensure the system autonomous operation.
Family Environment and Social Development in Gifted Students

Involving more than 1,500 academically gifted students and their parents, this study examined relationships between family environment and social competence of gifted students. Results from an online survey revealed that our gifted students rated their families as cohesive and flexible with high levels of satisfaction and communication among family members. Compared with students, parents identified their families as more intimate, cohesive, and flexible and felt more positively about communication among their family members. Students’ ratings of their family were found to be good predictors of their interpersonal ability and peer relationships, and positive correlations were found between the students’ social competence and their ratings of functional aspects of the family. Differences were also found by students’ level of social competence, with students with higher levels of social competence rating their families more positively. Unlike the norming sample, rigidity was not endorsed as a negative family variable. The results of this study are consistent with previous research in that affectionate, supportive, and respectful family environments appear to be important to the development of interpersonal skills and competency and peer relationships for gifted individuals.
ChromatinDB: a database of genome-wide histone modification patterns for Saccharomyces cerevisiae

UNLABELLED Covalent modifications to histone proteins play a critical role in regulating gene transcription. Previous studies have used chromatin immunoprecipitation (ChIP) based microarray assays to profile genomic regions that are enriched or depleted for a particular histone modification. Such studies have been conducted extensively in the yeast Saccharomyces cerevisiae, but currently no comprehensive data repositories or analysis tools are available for these data sets. For this reason, we have developed the ChromatinDB database, which contains genome-wide ChIP data for 22 different histones or histone modifications in S. cerevisiae. ChromatinDB provides novel tools to facilitate the visualization and statistical analysis of chromatin features for user-selected gene sets. AVAILABILITY http://www.bioinformatics2. wsu.edu/ChromatinDB. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
School Discipline, Educational Interest and Pupil Wisdom☆

Abstract In this article, the concept of school discipline will be explored in relation to that of educational interest. Initially, Clark’s account of two different kinds of school order (discipline and control) will be explained. The interest-based theory of school discipline advanced by Pat Wilson will thereafter be analysed. It will be argued that both these scholars persuasively explain how school discipline may follow when learning activities are successfully married to pupil interests and experiences. However, it will be maintained that the epistemic position adopted by Wilson is problematic. Although Wilson suggests that Richard Peters placed too great an educational emphasis on initiating pupils into public traditions of knowledge, it is here claimed that Wilson did not value that development enough. With reference to Whitehead, it is concluded that discipline in schools ought to be arranged so as to help pupils foster wisdom for life, as this concept integrates liberal knowledge and educational interest.
Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging

The statistical analysis of covariance matrices occurs in m any important applications, e.g. in diffusion tensor imaging or longitudinal data analysis. We consider the situation where it is of interest to estimate an average covariance matrix, describe its anisotropy and to carry out principal geodesic analysis of covariance matrices. In medical image analysis a particular type of covariance matrix arises in diffusion weighted imaging called a diffusion tensor. The diffusion tensor is a 3 × 3 covariance matrix which is estimated at each voxel in the brain, and is obtained by fittin g a physically-motivated model on measurements from the Fourier transform of the molecule displacement density (Basser et al., 1994). A strongly anisotropic diffusion tensor indicates a strong direction of white matter fibre tracts, and plots of measures of anisotropy are very useful t o neurologists. A measure that is very commonly used in diffusion tensor imaging is Fractional Anisotropy
Electroencephalography: Basic Principles, Clinical Applications and Related Fields

This book has 44 chapters written by 23 authors from Europe and the United States. It represents a commendable attempt at producing a one-volume, comprehensive textbook on EEG. Many chapters are good, but some are especially clear and didactic. "Biophysical Aspects of EEG and MEG Generation" deals with its subject in a clear and well-organized fashion understandable to all readers, leaving the mathematical foundations in an appendix for those whose interests are more basic. The chapter on the EEG laboratory goes into a discussion of laboratory design and organization, including comments on reporting EEGs and handling the reports. This is a useful feature that is not commonly seen in texts on EEG. The contingent negative variation is amply discussed in a review that includes techniques and physiologic and psychological correlates, updating previous reviews by the authors of the chapters. Some of the chapters are outstanding. The one on psychiatric disorders
Person Recall in Field Settings1

Men and women were stopped in public places by a target, who approached them either in an open and friendly demeanor or with a closed and hesitant demeanor. Witnesses interacted with the target for either 5 s or 30 s, and were tested for cued recall 2 min after the encounter. Demeanor did not influence overall recall, but did affect recall of specific characteristics. Men were superior to women in recall of physical characteristics, but gender differences were not found in recall of clothing characteristics. Witnesses were superior with longer observation periods, especially for recall of clothing. Significant but low confidence-accuracy correlations were found for recall of 8 of 14 person characteristics. Men were superior to women in their accuracy of duration estimations, but men and women both consistently overestimated durations.
Clinical usefulness of bone age determination in the management of tall stature

Measurements of skeletal maturation are used in the study and management of growth and growth disorders because of the correlation between the degree of skeletal maturation and the potential for further growth. In a study of 147 tall girls, final height was overpredicted by 0.7 ± 2.5 cm (mean ± SD) when based on the Bayley—Pinneau method. The radius—ulna—short bones (Tanner—Whitehouse 2) mark II method of assessment produced an underprediction of final height by 0.8 ± 2.9 cm and 1.0 ± 2.8 cm when the rating was performed by a skilled human or by a computer‐aided system, respectively. These errors in prediction were considered acceptable, although when predictions were made on five girls below 11 years of age, they were less accurate. □ Skeletal maturation, growth disorders, bone age, height prediction, tall girls
Couple Checkup: Tuning Up Relationships

There is considerable evidence that marriage is good for both adults and children and marriage education programs are designed to help build stronger marriages. However, these programs have a variety of problems that limit their effectiveness and impact and the Couple Checkup overcomes some of those limitations. The Couple Checkup can also be used by a couple on their own or used with marriage education programs to improve its impact. The Couple Checkup is based on the PREPARE/ENRICH Program, and it customizes the assessment for each couple. The couple can view and print their Checkup Report and a Couple Discussion Guide. The goal is for the Couple Checkup to reach a more diverse group of couples, to empower couples to deal with issues on their own, and to emphasize prevention over remediation. The Couple Checkup can also be used in a group setting and group leaders can create a Group Summary to help them better understand and work with the couples in a group.
Comparison of Broth Microdilution, E Test, and Agar Dilution Methods for Antibiotic Susceptibility Testing of Campylobacter jejuni and Campylobacter coli

ABSTRACT A standardized broth microdilution method was compared to the E test and an agar dilution method for the antimicrobial susceptibility testing of Campylobacter jejuni and C. coli isolates. A group of 47 human clinical isolates, 37 isolates from retail poultry, and 29 isolates from living turkeys (total, 113 isolates) was included in the study. These encompassed 92 C. jejuni and 21 C. coli strains. The MICs of six antimicrobial agents were determined by the broth microdilution and E test methods, and the strains of human origin were additionally tested by the agar dilution method. In general, broth microdilution MICs agreed within 1 log2 MIC increment with 90.0% of E test results and 78.7% of agar dilution test results. The agar dilution method gave much lower gentamicin MICs than the broth microdilution method, but the data were significantly (P < 0.01) correlated and there was 100% agreement in the sensitivities and specificities in the comparison of the tests. The broth microdilution method had the highest sensitivity for analysis of the susceptibilities of Campylobacter to nalidixic acid and trimethoprim-sulfamethoxazole. The MICs of ciprofloxacin and erythromycin complied numerically by all three methods. The classification of the results and the correlation of the data demonstrated a high degree of agreement. All methods were equally suitable for the testing of the sensitivity of Campylobacter to tetracycline. Thus, the broth microdilution method appears to be an easy and reliable method for determination of the MICs of antibiotics for C. jejuni and C. coli, and it may offer an interesting alternative to MIC determination by the agar dilution technique or the E test.
A heteroscedastic extension of LDA based on multi-class matusita affinity

Linear discriminant analysis (LDA), a conventional feature extraction technique, is a homoscedastic solution and ignores the second order information of the data. A heteroscedastic extension of LDA has been previously proposed which relies on the average pairwise Chernoff distances of the classes. However, in a multi-class scenario with number of classesC >; 2, the average of pairwise distances is not directly related to the classification error rate. Furthermore, the corresponding method imposes a high computational complexity of order O(C(C - 1)). This paper proposes an inherently multi-class heteroscedastic extension of LDA based on Matusita's separability measure, a multi-class generalization of the Chernoff distance which is related to multi-class error bounds. The proposed feature extractor can be trained non-iteratively with computational complexity of O(C). Experimental comparisons with the Chernoffmethod demonstrate both a performance improvement when estimated parameters are used, and a reduction of factor C - 1 in the computational load as predicted.
Using SVM and Clustering Algorithmsin IDS Systems

Intrusion Detection System (IDS) is a system, that monitors network traffic and tries to detect suspicious activity. In this paper we discuss the possibilities of application of clustering algorithms and Support Vector Machines (SVM) for use in the IDS. There we used K-means, FarthestFirst and COBWEB algorithms as clustering algorithms and SVM as classification SVM of type 1, known too as C-SVM. By appropriate choosing of kernel and SVM parameters we achieved improvements in detection of intrusion to system. Finally, we experimentally verified the efficiency of applied algorithms in IDS.
Chlamydia trachomatis pneumonia induces in vivo production of interleukin-1 and -6

Cytokine induction during Chlamydia trachomatis pneumonia may alter the pathogenesis or course of disease. We examined interleukin-1 (IL-1) and IL-6 production by measuring mRNA and bioactivity in murine lungs. mRNA and bioactivity for IL-1 alpha, IL-1 beta, and IL-6 increased after Chlamydia infection. These cytokines may be important in regulating host defenses against C. trachomatis.
Using unfoldings in automated testing of multithreaded programs

In multithreaded programs both environment input data and the nondeterministic interleavings of concurrent events can affect the behavior of the program. One approach to systematically explore the nondeterminism caused by input data is dynamic symbolic execution. For testing multithreaded programs we present a new approach that combines dynamic symbolic execution with unfoldings, a method originally developed for Petri nets but also applied to many other models of concurrency. We provide an experimental comparison of our new approach with existing algorithms combining dynamic symbolic execution and partial-order reductions and show that the new algorithm can explore the reachable control states of each thread with a significantly smaller number of test runs. In some cases the reduction to the number of test runs can be even exponential allowing programs with long test executions or hard-to-solve constrains generated by symbolic execution to be tested more efficiently.