Miracle-dz/UniFAR-FTUs huggingface dataset:
The Demographics of Minimizing Child Bullying by Maximizing Child Self-esteem: a Study from the Assuit Governorate, Egypt, Using GIS and Structural Equation Modelling.

Background: Low self-esteem originating in childhood often has a negative effect throughout a person’s life. Someone’s self-esteem is primarily a result of how he is treated by his parents, with influences also from school and the workplace. This study gathers information from a group of children in Assuit Governorate provinces in Egypt about their experiences of abuse and their responses with regard to their self-esteem. Methods: The study used a 23-item questionnaire with both open-ended and closed-ended questions, presented in a faceto-face situation with 1,751 children aged 10-12 years. Most of the items were structured as per the Likert scale of 1 to 5. Amos software was used, along with a confirmatory factor analysis (CFA) with path diagram models. A GIS (geographic information system) approach was used for mapping and plotting the outcomes of the research. Results: Punishment, ill-treatment and lack of warmth and praise for children seem to be the main reasons for low selfesteem amongst children in the area of study. The gender of the child has no significant effect as regards the means of discipline, whereas the marital status and education of the parents does have an effect. Conclusions: Educating and disciplining children is not an easy task, and parents need to receive good guidance in this area, with a focus on instilling positive behavior in children and an awareness of what is acceptable and what is unacceptable behavior, in order to prevent them from behaving in unacceptable ways.
Soft-error-immune communication network using unbalanced protection selection

Complexity in digital systems is pushing the system design more and more toward the two almost separate phases, design of computational units and design of communication structures for connecting these units. As technology grows, these communication networks become more complex and require protection for their reliability. On the other hand, by shrinking transistor geometries, the effects of soft errors are expected to become more significant than before. This paper estimates the vulnerability of MPSoC's communication infrastructure in form of silence data corruption failure in time (SDC FIT), and then uses a protection method for transient faults on interconnects that have SDC FIT values higher than a threshold value. Setting the threshold value, which is a tradeoff between reliability of interconnects and protection overheads, depends on of the application's constraints that is its measure of susceptibility to soft errors.
J un 2 00 7 R-trees and laminations for free groups III : Currents and dual R-tree metrics

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. -trees and laminations for free groups III: Currents and dual -tree metrics Thierry Coulbois, Arnaud Hilion, Martin Lustig
Cooperative Adaptive Cruise Control (CACC)

Cooperative Adaptive Cruise Controller is the next generation of Adaptive Cruise Controller(ACC). Through communication of vehicles CACC performs control maneuvers. The most important feature of CACC is its ability to enhance the capability of drivers and on-board devices(e.g.,radar or sensors), and thus, improving road traffic safety and efficiency. Inter-Vehicle Communication(IVC) and Roadside-to-Vehicle Communication(RVC) are the basic requirements of CACC. This reprt aims at describing the implementation of IVC/RVC and its advantages. The implementation of MAC layer protocol and Network layer protocol for IVC/RVC communication is described.
THE EFFECT OF INTERPERSONAL COMMUNICATION AND JOB STRESS ON ORGANIZATIONAL COMMITMENT AT CUSTOMS TRAINING CENTER

The objective of the research is to know the effect of interpersonal communication and job stress on organizational commitment. This research used quantitative approach. The research was conducted of Customs and Excise Training Center by using a survey method with path analysis applied in testing hypothesis. The number of 50 employee as sample was selected by using Slovin formula. The research conclude: (1) There is a direct positive effect of interpersonal communication on organizational commitment (2) There is a direct negative effect of work stress on commitment organization (3) There is a direct negative effect of interpersonal communication on organizational commitment.
Preschooler's Ability to Decide Whether a Photographed Unfamiliar Object Can Move Itself.

Does the preschooler's use of the animate-inanimate distinction reflect knowledge about which category types engage in self-initiated movements? Threeand 4-year-olds viewed photographs of unfamiliar objects, including mammalian animals, nonmammalian animals, statues with animallike forms and parts, wheeled vehicles, and multipart rigid objects, and decided whether each item could go up and down a hill by itself. Four-year-olds were reliably accurate about the movement potentials for each of the five classes of items; 3-year-olds' scores were significantly above chance in all but one category. Analyses of rule use and verbalization data showed that children were concerned about cause of movement and used an animate-inanimate hierarchy. Explanations from both age groups varied, in a consistent manner, the kind of information and criteria used to make inferences as function of the type of item. We discuss how these data bear on a theory of concepts.
Limiting Integral Loop Digital Control for DC–DC Converters Subject to Changes in Load Current and Source Voltage

A new digital control technique is proposed to improve the speed of both load current and source voltage transient responses for dc-dc converters operating in continuous conduction mode (CCM). The key structure of the proposed control technique is a combination of a limiting integral loop and related arithmetic operations to produce the desired switching sequence during transient condition. The limiting integral loop is built as a novel structure for capacitor charge balance operation. In contrast to previous approaches, the proposed control technique is valid for three basic converters: 1) buck; 2) boost; and 3) buck-boost. Moreover, since the transient period is forced to be an integer multiple of the switching cycle, the advantage of fixed switching frequency is inherently provided. Simulation and experimental results from a noninverting synchronous buck-boost converter prototype are given to validate the effectiveness of the proposed solution.
Study of equatorial Kelvin waves using the MST radar and radiosonde observations

Abstract. In this paper an attempt has been made to study equatorial Kelvin waves using a high power coherent VHF radar located at Gadanki (13.5° N, 79.2° E), a tropical station in the Indian sub-continent. Simultaneous radiosonde observations taken from a nearby meteorological station located in Chennai (13.04° N, 80.17° E) were also used to see the coherence in the observed structures. These data sets were analyzed to study the mean winds and equatorial waves in the troposphere and lower stratosphere. Equatorial waves with different periodicities were identified. In the present study, particular attention has been given to the fast Kelvin wave (6.5-day) and slow Kelvin wave (16-day). Mean zonal wind structures were similar at both locations. The fast Kelvin wave amplitudes were somewhat similar in both observations and the maximum amplitude is about 8m/s. The phase profiles indicated a slow downward progression. The slow Kelvin wave (16-day) amplitudes shown by the radiosonde measurements are a little larger than the radar derived amplitudes. The phase profiles showed downward phase progression and it translates into a vertical wavelength of ~10-12km. The radar and radiosonde derived amplitudes of fast and slow Kelvin waves are larger at altitudes near the tropopause (15-17km), where the mean wind attains westward maximum.
Texture Analysis Using GMRF Model for Image Segmentation on Spectral Clustering

Spectral clustering algorithms are newly developing technique in recent years. In this paper, we derive a new pairwise affinity function for spectral clustering based on a measure of texture features represented by Gaussian Markov Random Field (GMRF) model. This model is used to capture the statistical properties of the neighborhood at a pixel, and then pairwise affinities represented by it can cluster the pixels into coherent groups. Having obtained a local similarity measured by regions of coherent texture and brightness, we use the normalized cuts to find partitions of the image. Experimental results demonstrate that the proposed method is effective and robust for image segmentation.
Research on semantic network image retrieval method

As a prominent form of multimedia, image retrieval has become an important project research presently. Nowadays, the development of image search engine mainly bases on two kinds of technique: 1) traditional Text-Based Image Retrieval (TBIR); 2) Content-Based Image Retrieval (CBIR). However, because of the limitation of the “semantic gap” bottleneck, they both have limitations. In the light of this, we present an image retrieval method based on semantic network. We create a mapping from low-level image visual features to high-level semantic, and attempt to identify the semantic concept of visual features. We also introduce user feedback, guide search results to the optimal direction, and make it to fit the natural way for humans to understand image. The technology requires the use of the knowledge library for storing semantic networks and mapping. In this paper, the system model, retrieval method and experiments are given. Experimental results indicate that the method have better retrieval efficiency.
Noise Reduction of cDNA Microarray Images Using Complex Wavelets

Noise reduction is an essential step of cDNA microarray image analysis for obtaining better-quality gene expression measurements. Wavelet-based denoising methods have shown significant success in traditional image processing. The complex wavelet transform (CWT) is preferred to the classical discrete wavelet transform for denoising of microarray images due to its improved directional selectivity for better representation of the circular edges of spots and near shift-invariance property. Existing CWT-based denoising methods are not efficient for microarray image processing because they fail to take into account the signal as well as noise correlations that exist between red and green channel images. In this paper, two bivariate estimators are developed for the CWT-based denoising of microarray images using the standard maximum a posteriori and linear minimum mean squared error estimation criteria. The proposed denoising methods are capable of taking into account both the interchannel signal and noise correlations. Significance of the proposed denoising methods is assessed by examining the effect of noise reduction on the estimation of the log-intensity ratio. Extensive experimentations are carried out to show that the proposed methods provide better noise reduction of microarray images leading to more accurate estimation of the log-intensity ratios as compared to the other CWT-based denoising methods.
Multi-Agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC)

Traffic congestion in Greater Toronto Area costs Canada $ 6 billion /year and is expected to grow up to $ 15 billion /year in the next few decades. Adaptive Traffic Signal Control(ATSC) is a promising technique to alleviate traffic congestion. For medium-large transportation networks, coordinated ATSC is becoming a challenging problem because the number of system states and actions grows exponentially as the number of networked intersections grows. Efficient and robust controllers can be designed using a multi-agent reinforcement learning (MARL) approach in which each controller (agent) is responsible for the control of traffic lights around a single traffic junction. This paper presents a novel, decentralized and coordinated adaptive real-time traffic signal control system using Multi-Agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLINATSC) that aims to minimize the total vehicle delay in the traffic network. The system is tested using microscopic traffic simulation software (PARAMICS) on a network of 5 signalized intersections in Downtown Toronto. The performance of MARLIN-ATSC is compared against two approaches: the conventional pretimed signal control (B1) and independent RL-based control agents (B2), i.e. with no coordination. The results show that network-wide average delay savings range from 32% to 63% relative to B1 and from 7% to 12% relative to B2 under different demand levels and arrival profiles.
Preferences for oral versus intravenous adjuvant chemotherapy among early breast cancer patients

Purpose The purpose of this study was to evaluate preferences for oral versus intravenous adjuvant chemotherapy among early breast cancer patients (UMIN-CTR number UMIN000004696). Patients and methods Eighty-two postmenopausal women with estrogen receptor-positive, human epidermal growth-factor receptor 2-negative breast cancer who had completed adjuvant chemotherapy were asked about their preferred route of administration of chemotherapy and the reason. Women also answered questions about their physical and psychological status and quality of life during chemotherapy. Results Patients who had received oral chemotherapy preferred it more frequently than those who had received intravenous chemotherapy (100% versus 37%, respectively, chi-square =15.5; P<0.001). Patients who preferred the same route of administration of chemotherapy as they had previously received showed a significantly better psychological status during chemotherapy compared with those who preferred a different route. Conclusion Our study showed that preferences for oral and intravenous chemotherapy strongly depended on the actual prior administration of chemotherapy and patients’ own experiences during chemotherapy.
A Survey on Data Mining Algorithms and Future Perspective

-Data mining is a powerful and new method of analyzing data and finding out new patterns from large set of data. The objective of data mining is to pull out knowledge from a data set in an understandable format. Data mining is the process of collecting, extracting and analyzing large data set from different perspectives. There is an enormous amount of data stored in databases and data warehouse due to enormous technological advancements in computing and Internet. It is therefore, required, to develop powerful tools for analysis of such huge data and mining valuable information out of it. One of the main challenges in database mining is developing fast and efficient algorithms that can handle large volumes of data as most of the mining algorithms perform computation over the entire databases, often very large. Data mining is a convenient way of extracting patterns, which represents knowledge implicitly stored in large data sets and focuses on issues relating to their feasibility, usefulness, effectiveness and scalability. It can be viewed as an essential step in the process of knowledge discovery. Data are normally preprocessed through data cleaning, data integration, data selection, and data transformation and prepared for the mining task. Data mining can be performed on various types of databases and information repositories, but the kind of patterns to be found are specified by various data mining functionalities like class description, association, correlation analysis, classification, prediction, cluster analysis etc. This paper gives an overview of the existing data mining algorithms required for the same.
Spectral Profiles, a Novel Representation of Tandem Mass Spectra and Their Applications for de Novo Peptide Sequencing and Identification*

Despite many efforts in the last decade, the progress in de novo peptide sequencing has been slow with only 30–45% of all peptides correctly reconstructed. We argue that accurate full-length peptide sequencing may be an unattainable goal for some spectra and demonstrate how to accurately sequence gapped peptides instead. We further argue that gapped peptides are nearly as useful as full-length peptides for error-tolerant database searches. Gapped peptides occupy a niche between long but inaccurate full-length reconstructions and short but accurate peptide sequence tags. Our MS-Profile tool uses spectral profiles, a new representation of tandem mass spectra, to generate gapped peptides that are longer and more accurate than peptide sequence tags of length 3 traditionally used to speed up database searches in proteomics. In addition, spectral profiles also enable intuitive visualization of all high scoring de novo reconstructions of tandem mass spectra.
ON THE GLOBAL CONVERGENCE OF THE HIGH-ORDER POWER METHOD FOR RANK-ONE TENSOR APPROXIMATION DRAFT AS OF January

Tensor decomposition has consequential applications in va r ous fields of disciplines, but it remains to be an extremely challenging task even to this date. A slightly more manageab le endeavor has been to find a low rank approximation in place o f the decomposition. Even for this less stringent task, it is an es tabli hed fact that tensors beyond matrices can fail to have best low rank approximations, with the notable exception that the best ra nk-one approximation always exists for tensors of any order . Toward the latter, the most popular approach is via the notion of alternating pr ojection. The specific numerical scheme appears as a variant of the power method. The so called proofs of convergence in the literatur e, however, have been only on the limiting behavior of the obj ective values. This is not enough, as the dynamics of the iterates itself sho uld also be analyzed. The purpose of this paper is to fill the ga p by presenting a rigorous convergence analysis of the power method for the r ank-one approximation. Also briefly discussed is a comparis on of the power method with the global optimization.
Representation of individual elements of a complex call sequence in primary auditory cortex

Conspecific communication calls can be rhythmic or contain extended, discontinuous series of either constant or frequency modulated harmonic tones and noise bursts separated by brief periods of silence. In the guinea pig, rhythmic calls can produce isomorphic responses within the primary auditory cortex (AI) where single units respond to every call element. Other calls such as the chutter comprise a series of short irregular syllables that vary in their spectral content and are more like human speech. These calls can also evoke isomorphic responses, but may only do so in fields in the auditory belt and not in AI. Here we present evidence that cells in AI treat the individual elements within a syllable as separate auditory objects and respond selectively to one or a subset of them. We used a single chutter exemplar to compare single/multi-unit responses in the low-frequency portion of AI—AI(LF) and the low-frequency part of the thalamic medial geniculate body—MGB(LF) in urethane anaesthetized guinea pigs. Both thalamic and cortical cells responded with brief increases in firing rate to one, or more, of the 8 main elements present in the chutter call. Almost none of the units responded to all 8 elements. While there were many different combinations of responses to between one and five of the elements, MBG(LF) and AI(LF) neurons exhibited the same specific types of response combinations. Nearby units in the upper layers of the cortex tended to respond to similar combinations of elements while the deep layers were less responsive. Thus, the responses from a number of AI units would need to be combined in order to represent the entire chutter call. Our results don't rule out the possibility of constructive convergence but there was no evidence that a convergence of inputs within AI led to a complete representation of all eight elements.
Biomechanics and visual-motor control: how it has, is, and will be used to reveal the secrets of hitting a cricket ball

Cricket batting is an incredibly complex task which requires the coordination of full-body movements to successfully hit a fast moving ball. Biomechanical studies on batting have helped to shed light on how this intricate skill may be performed, yet the many different techniques exhibited by batters make the systematic examination of batting difficult. This review seeks to critically evaluate the existing literature examining cricket batting, but doing so by exploring the strong but often neglected relationship between biomechanics and visual-motor control. In three separate sections, the paper seeks to address (i) the different theories of motor control which may help to explain how skilled batters can hit a ball, (ii) strategies used by batters to overcome the (at times excessive) temporal constraints, and (iii) an interpretation from a visual-motor perspective of the prevailing biomechanical data on batting.
Characterization of Novel and Uncharacterized p53 SNPs in the Chinese Population – Intron 2 SNP Co-Segregates with the Common Codon 72 Polymorphism

Multiple single nucleotide polymorphisms (SNPs) have been identified in the tumor suppressor gene p53, though the relevance of many of them is unclear. Some of them are also differentially distributed in various ethnic populations, suggesting selective functionality. We have therefore sequenced all exons and flanking regions of p53 from the Singaporean Chinese population and report here the characterization of some novel and uncharacterized SNPs - four in intron 1 (nucleotide positions 8759/10361/10506/11130), three in intron 3 (11968/11969/11974) and two in the 3′UTR (19168/19514). Allelic frequencies were determined for all these and some known SNPs, and were compared in a limited scale to leukemia and lung cancer patient samples. Intron 2 (11827) and 7 (14181/14201) SNPs were found to have a high minor allele frequency of between 26–47%, in contrast to the lower frequencies found in the US population, but similar in trend to the codon 72 polymorphism (SNP12139) that shows a distribution pattern correlative with latitude. Several of the SNPs were linked, such as those in introns 1, 3 and 7. Most interestingly, we noticed the co-segregation of the intron 2 and the codon 72 SNPs, the latter which has been shown to be expressed in an allele-specific manner, suggesting possible regulatory cross-talk. Association analysis indicated that the T/G alleles in both the co-segregating intron 7 SNPs and a 4tagSNP haplotype was strongly associated increased susceptibility to lung cancer in non-smoker females [OR: 1.97 (1.32, 3.394)]. These data together demonstrate high SNP diversity in p53 gene between different populations, highlighting ethnicity-based differences, and their association with cancer risk.