Miracle-dz/UniFAR-FTUs huggingface dataset:
An effective feature for crack detection on train wheel surface

Automatic crack detection on train wheel surface is highly crucial for safety and labor-cost efficiency. Algorithms have been explored to cope with the image based crack detection problem, but mostly for concrete structure or pavement surface. It's a tougher problem on train wheel surface because of noise such as scratch, rust, dirt, shadow and son on which are unlikely to be denoised by simple image processing methods or image transform algorithms. In this paper, we treat this mission as an object detection problem. A LoG gradient based method is proposed to weight the pixels within the Haar-like feature mask region. We call it LoG Weighted Haar-like feature (LWH). With this, a more precise description of the crack sample images is achieved. An evaluation is performed to show the effectiveness of our method.
Indirect Recognition of Porcine Swine Leukocyte Ag Class I Molecules Expressed on Islets by Human CD4+ T Lymphocytes1

Xenotransplantation of porcine islets is considered a viable alternative treatment for type 1 diabetes mellitus. Therefore, we characterized human PBL responding to porcine islets both in vitro by coculture and in vivo using SCID mice reconstituted with human PBLs (HuPBL-SCID) and transplanted with porcine islets. T cell lines generated in vitro and graft-infiltrating T cells obtained from HuPBL-SCID mice were CD4+-proliferated specifically to porcine islets cultured with autologous APC. This proliferation was abrogated by an anti-human class II Ab. These T cell lines also proliferated to purified swine leukocyte Ag (SLA) class I molecules in the presence of self-APC, indicating that the primary xenoantigens recognized are peptides derived from SLA. This CD4+ T cell line lysed porcine islets but not splenocytes. CD4+ T cell clones with Th0, Th1, and Th2 cytokine profiles were isolated. The Th0 and Th1 clones lysed porcine islets, whereas the Th2 clone that secreted a large amount of IL-4 was not lytic. These results demonstrate that human T cells responding to porcine islets are primarily CD4+ and recognize porcine xenoantigens by the indirect Ag pathway presentation. These activated T cells produce cytokines that lyse islets. Furthermore, we demonstrate that the major porcine xenoantigens recognized are SLA class I molecules.
FACTORS THAT AFFECT CLOUD COMPUTING ADOPTION BY SMALL AND MEDIUM ENTERPRISES IN KENYA

The number of Small and Medium Enterprises in Kenya have increased tremendously over the last ten years. They have played a profound role in providing employment to the population besides growing the Kenyan economy. Cloud computing is a new entrant to the technology arena which in form of Platform as a Service, Software as a Service and Infrastructure as a Service promises profound reduction in cost of operations in a business. It offers immense benefits as the business enterprise utilizes the pay per use model availed by the cloud service providers as per the needs of the business enterprise. This eliminates the need to purchase expensive software, development platforms and setting up complex ICT infrastructure. This is akin to renting what they need instead of purchasing and owning it. However, the SMEs in Kenya have not taken up the cloud computing benefits to maximise their competitive advantage. This research paper focuses on the factors that affect the adoption of cloud computing by SMEs in Kenya. The research process involves a descriptive research design. The research findings have shown that technological, organisational and environmental factors have affected the adoption of cloud technologies.
Contributions of an integrated genre theory of text and context to teaching LSP

Quelles peuvent etre aujourd’hui les contributions d’une approche de genre a l’enseignement des competences en LSP ? Cet article repond a cette question en suggerant que l’approche de genre y est bien adaptee, surtout si ce que l’on comprend par genre est texte-et-contexte. Afin de mieux comprendre la dualite de genre, la recente reconceptualisation du contexte par des chercheurs en genre sera discutee. Ensuite, s’appuyant sur une vision integree de genre afin de mieux cerner et comprendre les conditions du developpement de la competence langagiere specialisee, une approche pour l’enseignement des LSP, appelee la « modelisation communicative dirigee », sera decrite. Cette approche cherche a developper les multiples competences necessaires en LSP, en integrant les suppositions generees par l’unification du texte et du contexte.
Low Mitochondrial DNA Diversity in an Ancient Population from China: Insight into Social Organization at the Fujia Site

ABSTRACT To gain insight into the social organization of a population associated with the Dawenkou period, we performed ancient DNA analysis of 18 individuals from human remains from the Fujia site in Shandong Province, China. Directly radiocarbon dated to 4800–4500 cal BP, the Fujia site is assumed to be associated with a transitional phase from matrilineal clans to patrilineal monogamous families. Our results reveal a low mitochondrial DNA diversity from the site and population. Combined with Y chromosome data, the pattern observed at the Fujia site is most consistent with a matrilineal community. The patterns also suggest that the bond of marriage was de-emphasized compared with the bonds of descent at Fujia.
Lack of C9orf72 Repeat Expansion in Taiwanese Patients with Mixed Neurodegenerative Disorders

Background: The hexanucleotide repeat expansion in intron 1 of the C9orf72 gene is recognized as the most common genetic cause of frontotemporal dementia (FTD). There are overlapping clinical and pathological characteristics between FTD and Parkinsonism syndrome, and some FTD patients may present with Parkinsonism. The aim of this study was to analyze the hexanucleotide repeat numbers of C9orf72 gene in a mixed Taiwanese cohort with FTD, Parkinsonism syndrome, Parkinson’s disease (PD), and Alzheimer’s dementia (AD). Method: The number of hexanucleotide repeats was estimated in a total of 482 patients with mixed neurodegenerative disorders and 485 control subjects, using a two-step repeat-primed polymerase chain reaction-based genotyping strategy. The individual groups of patients included patients with Parkinsonism syndrome (n = 95), familial PD (n = 109), young-onset PD (n = 201), FTD (n = 9), sporadic AD (n = 61), and early-onset AD (n = 7). Results: We did not identify any pathogenic repeats (>30 repeats) of C9orf72 in either the patients or control subjects. However, we found one young-onset PD patient and one control subject that each had an intermediate number of repeats (25 and 21 repeats, respectively). The clinical phenotype of the young-onset PD in this patient was similar to typical idiopathic PD without additional features, and the patient responded well to levodopa treatment. Conclusion: The repeat expansion in C9orf72 is not a common cause of PD, Parkinsonism syndrome, or dementia in our population. Further studies are needed to investigate the clinical and biological significance of intermediate repeats in C9orf72.
Developmental Origin of the Neuronal Subtypes That Comprise the Amygdalar Fear Circuit in the Mouse

We have taken a genetic-based fate-mapping approach to determine the specific contributions of telencephalic progenitors to the structures that comprise the amygdalar fear circuit including the central (CA), lateral (LA), and basolateral (BLA) amygdala. Our data indicate that progenitors in the ventral pallium (VP) contribute projection neurons to the LA and BLA but not the CA. Rather, the CA appears to derive, at least in part, from progenitors located in the ventral lateral ganglionic eminence (vLGE). Diverse groups of interneurons populate these amygdalar nuclei, and as predicted our data support the notion that they originate from subpallial progenitors. A rather specific population of amygdalar interneurons, the intercalated cells (ITCs), is known to play a fundamental role in fear-related behaviors. However, no information on their specific origin has, as yet, been provided. Our findings suggest that the ITCs arise from the dorsal lateral ganglionic eminence (dLGE) and migrate in the lateral migratory stream to populate the paracapsular regions as well as the main intercalated mass of the amygdala (IA). Germ-line Gsx2 mutants are known to exhibit an expansion of the VP into the LGE and a concomitant reduction in the dLGE and vLGE. Accordingly, Gsx2 conditional mutants display a significantly enlarged LA and a significant reduction in ITCs both within the paracapsular regions and the IA. Additional support for a dLGE origin of the ITCs was obtained in conditional mutants of the dLGE gene Sp8. Thus, our findings indicate diverse origins for the neuronal components that comprise the amygdalar fear circuit.
9 kW SiC MOSFET based DC/DC converter

In this paper a 9 kW DC/DC converter based on SiC MOSFET devices is presented. Precise control of the output voltage is realized with the help of a state feedback controller with an additional integral action. Simulation and experimental test results as well as an efficiency of DC/DC converter are presented. The behavior of the converter was investigated during no-load and variable load operation. Device efficiency was also investigated and it was found that the efficiency exceed 98% in a wide operating range.
Jawi-Malay transliteration

Jawi-Malay transliteration at basis was introduced to get information from old manuscripts that contain important information in various spheres of knowledge. The weakness in reading and understanding from Jawi source rise when new generation less in use Jawi as medium in their daily activities such as spreading and retrieval information. Using the earlier literature reviews, approaches, framework and evaluation result as guideline, we proposed some main method such as character categorise, stemming process, Unicode Mapping, Jawi-Malay Rules and Voice synthesizer. The integration of the above methods will help to quick in transliteration process and well in output. By the way, this transliteration design also have their weakness because not all word can be accurate in transliterate. For the beyond researcher, suggested to improve the rules and develop synthesizer by our own slang.
Behavioral/systems/cognitive Effective Sensory Modality Activating an Escape Triggering Neuron Switches during Early Development in Zebrafish Laser Ablation of the M-cell and Ca 2ϩ Imaging of the M-cell during Escape Demonstrated That M-cell Firing Is Required to Initiate Short-latency Fast Escapes 

Developing nervous systems grow to integrate sensory signals from different modalities and to respond through various behaviors. Here, we examined the development of escape behavior in zebrafish [45–170 h postfertilization (hpf)] to study how developing sensory inputs are integrated into sensorimotor circuits. Mature fish exhibit fast escape upon both auditory/vestibular (AV) and head-tactile stimuli. Newly hatched larvae, however, do not respond to AV stimuli before 75 hpf. Because AV-induced fast escape in mature fish is triggered by a pair of hindbrain neurons known as Mauthner (M) cells, we studied functional development of the M-cell circuit accounting for late acquisition of AV-induced escape. In fast escape elicited by head-directed water jet, minimum onset latency decreased throughout development (5 ms at 45–59 hpf, 3 ms after 75 hpf). After 75 hpf, lesioning the otic vesicle (OV) to eliminate AV input resulted in loss of short-latency (Ͻ5 ms) fast escape, whereas ablation of the sensory trigeminal ganglion (gV) to block head-tactile input did not. Before 75 hpf, however, fast escape persisted after OV lesion but disappeared after gV ablation.
The egg trade--making sense of the market for human oocytes.

In the United States, a woman may receive $20,000 for an egg used for reproduction but nothing for the same egg used for stem-cell research. Debora Spar argues that what we need is a fresh debate on egg donation and a new set of policies. Debora Spar and Emily Galpern debate the appropriateness of financial compensation for women who donate oocytes for in vitro fetrilization and stem-cell research. Spar is a professor of business administration at Harvard Business School, and Galpern is a project director on reproductive health and human rights at the Center for Genetics and Society, Oakland, California.
Interpolation technique for extracting features from ECG signals sampled at low sampling rates

The occurrence of the R peak (t/sub R/), and the area of the QRS complex (A/sub QRS/) are among the features estimated from each ECG wave. To estimate these parameters ECG is traditionally sampled at a high sampling rate (250-500 Hz). However, since t/sub R/ and A/sub QRS/ are identified by the selective analysis of the QRS complex and since the QRS maximal frequency component is about 25 Hz, we propose a new procedure to identify t/sub R/ and A/sub QRS/ from ECG sampled at the relatively low rate dictated by the frequency content of the QRS complex. The procedure identifies each QRS complex from the sampled ECG, and estimates t/sub R/ and A/sub QRS/ after interpolation of the QRS complex. The interpolation is obtained as the inverse discrete Fourier transform (IDFT) of the zero-padded DFT of the QRS. The technique was tested on a public database of ECG. Results showed that by this technique t/sub R/ and A/sub QRS/ can be accurately derived from ECG sampled at frequency as low as 70 Hz.
Robust Visual Tracking via Appearance Modeling and Sparse Representation

When appearance variation of object, partial occlusion or illumination change in object images occurs, most existing tracking approaches fail to track the target effectively. To deal with the problem, this paper proposed a robust visual tracking method based on appearance modeling and sparse representation. The proposed method exploits two-dimensional principal component analysis (2DPCA) with sparse representation theory for constructing appearance model. Then tracking is achieved by Bayesian inference framework, in which a particle filter is applied to evaluate the target state sequentially over time. In addition, to make the observation model more robust, the incremental learning algorithm is used to update the template set. Both qualitative and quantitative evaluations on four publicly available benchmark video sequences demonstrate that the proposed visual tracking algorithm performs better than several state-of-the-art algorithms.
Functional Unification Approach to Automated Visualization Design

A unification-based approach to visualization design provides a uniform way of representing user requirements, design knowledge, and graphic designs as well as algorithms for synthesizing graphic presentations. We demonstrate this approach on two types of requirements – structural in the form of sketches and functional in the form of tasks. With this approach we aim to achieve the following system design goals: expressiveness (the formalism can express the visualization design problem and its problem-solving algorithms), uniformity (the same formalism can be applied to different generation tasks), efficiency (graphics can be designed in a reasonable amount of time), and extensibility (the system can be extended with new types of requirements, design elements and design knowledge).
Genetic Programming: Semantic point mutation operator based on the partial derivative error

There is a great interest in the Genetic Programming (GP) community to develop semantic genetic operators. Most recent approaches includes the genetic programming framework for symbolic regression called Error Space Alignment GP, the geometric semantic operators, and our previous work the semantic crossover based on the partial derivative error. To the best of our knowledge, there has not been a semantic genetic operator similar to the point mutation. In this contribution, we start filling this gap by proposing a semantic point mutation based on the derivative of the error. This novel operator complements our previous semantic crossover and, as the results show, there is an improvement in performance when this novel operator is used, and, furthermore, the best performance in our setting is the system that uses the semantic crossover and the semantic point mutation.
Selection of attribute combinations of ERP's for classification of emotions along arousal axis

Emotions play a key role in our daily interaction with the outside world. The emotions govern our quality of relations within the society. The emotion detection becomes necessary for developing an affective Human-Computer interface. In this paper we have developed a two class emotion classifier based on Electroencephalogram (EEG) signals. The EEG signalshave beenacquired from five subjects on three frontal electrodes namely Fz, F3 and F4. The images provided by International Affective Picture System (IAPS) have been used for evoking emotions. The ERP potentials P100, N100 and the two latencies corresponding to these bio potentials have been extracted for every class of emotion from preprocessed EEG signals. The training and testing has been performed on 11 combinations of the extracted features. The LIBSVM classifier (RBF kernel) with 3 fold cross validation has been used for classification of emotions along arousal axis into two classes. When emotions are classified subject wise, it has been found that the accuracy remains consistently high (above 75%) on the attribute combinations(P100, Nt100), (P100, Pt100) and (P100, Pt100, N100, Nt100). From the 11 combinations processed to classify emotions along arousal domain, it has been found that the attribute combination of(P100,Pt100,N100,Nt100)gives the best results on all three electrodes used followed by (P100,Nt100) and (N100,Nt100). An average accuracy of 66.26% has been achieved for (P100, Pt100, N100, Nt100), 65.59% for (P100, Nt100), 63.89% for attribute combination (N100, Nt100). Keywords: EEG, Emotions, Event related potential (ERP), Feature Extraction
Empirical Analysis of Answering How to Improve People's Happiness in Consideration of Risk Factors: From the Perspective of General Bayesian Network

In the healthcare literature, happiness has been neglected as an important research issue. However, it seems clear that happiness becomes more important in research agenda as societies grow older. It is well known that happiness is related with various kinds of factors. Therefore, managing happiness requires careful handling of a number of related factors in a very systematic and organized way. In this sense, this study proposes General Bayesian Network (GBN) approach in order to extract causal knowledge about happiness from the analysis of the related factors. By using Friends-and-Family dataset, we performed GBN-based scenario analyses to answer sophisticated questions about happiness. The empirical results showed that GBN proved to have huge potentials in handling well-ness problems in the field of health informatics.
Does Changing Corporate Governance Alone Result in Better Firm Performance

An important public policy issue actively debated in the financial economics literature is whether firms can increase their value solely by changing one or more corporate governance mechanisms. In this paper, we directly examine whether changing governance leads to changes in future firm performance. Specifically, we analyze a sample of firms that instituted governance changes and sort them based on the direction of their governance changes for thirteen different governance measures. We focus on firms that make large governance changes to enhance the power of our tests. We find no significant difference in future performance between firms that have a large increase in governance measures and firms that have a large decrease in governance measures. We also find that the governance changes are driven by movement towards mean industry governance levels, merger pressures, as well as changes in the firm’s observable characteristics. We conclude that firms choose their governance structures in equilibrium, and changing governance alone does not result in better future performance. These findings are robust to many different specifications, definitions of large governance changes, samples, and definitions of firm performance.
Correlation matching approach to source separation in the presence of spatially correlated noise

This paper addresses a new method of source separation that is robust in the presence of spatially correlated but temporally white noise. The method exploits the non-vanishing temporal structure of sources to reduce the effect of noise. In the framework of correlation matching, we develop two efficient least squares algorithms. Useful behavior of the proposed algorithms is confirmed by numerical experiments.
Giant Arc Statistics in Concord with a Concordance Lambda Cold Dark Matter Universe

The frequency of giant arcs—highly distorted and strongly gravitationally lensed background galaxies—is a powerful test for cosmological models. Previous comparisons of arc statistics for the currently favored concordance cosmological model (lambda cold dark matter [LCDM]) with observations have shown an apparently large discrepancy in underpredicting cluster arcs. We present new ray-shooting results, based on a high-resolution (10243 particles in a 320 h-1 Mpc box) large-scale structure simulation normalized to the Wilkinson Microwave Anisotropy Probe (WMAP) observations. We follow light rays through a pseudo-three-dimensional matter distribution approximated by up to 38 lens planes and evaluate the occurrence of arcs for various source redshifts. We find that the frequency of strongly lensed background galaxies is a steep function of source redshift: the optical depth for giant arcs increases by a factor of 5 when background sources are moved from redshift zs = 1.0 to 1.5. This is a consequence of a small decrease of the critical surface mass density for lensing, combined with the very steep cluster mass function at the high-mass end plus a modest contribution from secondary lens planes. Our results are consistent with those of Bartelmann et al. if we—as they did—restrict all sources to be at zs = 1. If we allow sources extending to or beyond zs ≥ 1.5, the apparent discrepancy vanishes: the frequency of arcs increases by about a factor of 10 as compared to previous estimates, and results in roughly one arc per 20 deg2 over the sky, in good agreement with the observed frequency of arcs.
Castalia: revealing pitfalls in designing distributed algorithms in WSN

We present Castalia, a simulator for WSN that models many aspects of the WSN system and uses advanced models especially in terms of the channel and radio behaviour. We show the effects of these features in distributed algorithms that work fine with simpler simulators but fail under Castalia. The demo will present the differences, explain the failures and show how to redesign the algorithms to make them work under more realistic conditions.
Silverfish: A Contextual Knowledge Extraction and Aggregation System for Academics

Repositories like arXiv 1 and knowledge bases like CiteSeer 2 are increasingly becoming central to academicians and researchers. However, current systems provide too little semantic support like determining the topic of a paper, modelling the interests of a user, etc. Silversh is a contextual knowledge extraction and aggregation system that adds a signicant amount of semantics to academic repositories. Silversh automatically extracts pertinent key phrases and models semantic content in the form of a back end cooccurrence graph. This is used for \intelligent" operations like recommendations, nding related content and semantics based routing of announcements.