Miracle-dz/UniFAR-FTUs huggingface dataset:
An embedded handwriting recognizing system of mathematical expression: Embedded-MatheWriter

This paper has contrived an online handwriting recognizing system of mathematical expression based on an embedded equipment, which supports in the use of the languages of the minority, such as Uyghur and Kazakh languages . For the features of mathematical expression recognizing, and from the point of ensuring the system's efficiency , this paper has constructed an embedded platform, on which the capability of the system has been tested, and it has compared the data gained from the test with those in PC , which offers a gist to improve the algorithm and perfect the system.
Neurodegeneration Caused by Polyglutamine Expansion Is Regulated by P-Glycoprotein in Drosophila melanogaster

Trinucleotide CAG repeat disorders are caused by expansion of polyglutamine (polyQ) domains in certain proteins leading to fatal neurodegenerative disorders and are characterized by accumulation of inclusion bodies in the neurons. Clearance of these inclusion bodies holds the key to improve the disease phenotypes, which affects basic cellular processes such as transcription, protein degradation and cell signaling. In the present study, we show that P-glycoprotein (P-gp), originally identified as a causative agent of multidrug-resistant cancer cells, plays an important role in ameliorating the disease phenotype. Using a Drosophila transgenic strain that expresses a stretch of 127 glutamine repeats, we demonstrate that enhancing P-gp levels reduces eye degeneration caused by expression of polyQ, whereas reducing it increases the severity of the disease. Increase in polyQ inclusion bodies represses the expression of mdr genes, suggesting a functional link between P-gp and polyQ. P-gp up-regulation restores the defects in the actin organization and precise array of the neuronal connections caused by inclusion bodies. β-Catenin homolog, Armadillo, also interacts with P-gp and regulates the accumulation of inclusion bodies. These results thus show that P-gp and polyQ interact with each other, and changing P-gp levels can directly affect neurodegeneration.
Exploiting Diversity of Neural Network Ensembles based on Extreme Learning Machine

Extreme learning machine (ELM) is an emergent method for train- ing single hidden layer feedforward neural networks (SLFNs) with extremely fast training speed, easy implementation and good generalization performance. This work presents effective ensemble procedures for combining ELMs by exploiting di- versity. A large number of ELMs are initially trained in three different scenarios: the original feature input space, the obtained feature subset by forward selection and different random subsets of features. The best combination of ELMs is con- structed according to an exact ranking of the trained models and the useless net- works are discarded. The experimental results on several regression problems show that robust ensemble approaches that exploit diversity can effectively improve the performance compared with the standard ELM algorithm and other recent ELM extensions.
Stable Learning in Coding Space for Multi-class Decoding and Its Extension for Multi-class Hypothesis Transfer Learning

Many prevalent multi-class classification approaches can be unified and generalized by the output coding framework which usually consists of three phases: (1) coding, (2) learning binary classifiers, and (3) decoding. Most of these approaches focus on the first two phases and predefined distance function is used for decoding. In this paper, however, we propose to perform learning in coding space for more adaptive decoding, thereby improving overall performance. Ramp loss is exploited for measuring multi-class decoding error. The proposed algorithm has uniform stability. It is insensitive to data noises and scalable with large scale datasets. Generalization error bound and numerical results are given with promising outcomes.
Single Unpurified Breast Tumor-Initiating Cells from Multiple Mouse Models Efficiently Elicit Tumors in Immune-Competent Hosts

The tumor-initiating cell (TIC) frequency of bulk tumor cell populations is one of the criteria used to distinguish malignancies that follow the cancer stem cell model from those that do not. However, tumor-initiating cell frequencies may be influenced by experimental conditions and the extent to which tumors have progressed, parameters that are not always addressed in studies of these cells. We employed limiting dilution cell transplantation of minimally manipulated tumor cells from mammary tumors of several transgenic mouse models to determine their tumor-initiating cell frequency. We determined whether the tumors that formed following tumor cell transplantation phenocopied the primary tumors from which they were isolated and whether they could be serially transplanted. Finally we investigated whether propagating primary tumor cells in different tissue culture conditions affected their resident tumor-initiating cell frequency. We found that tumor-initiating cells comprised between 15% and 50% of the bulk tumor cell population in multiple independent mammary tumors from three different transgenic mouse models of breast cancer. Culture of primary mammary tumor cells in chemically-defined, serum-free medium as non-adherent tumorspheres preserved TIC frequency to levels similar to that of the primary tumors from which they were established. By contrast, propagating the primary tumor cells in serum-containing medium as adherent populations resulted in a several thousand-fold reduction in their tumor-initiating cell fraction. Our findings suggest that experimental conditions, including the sensitivity of the transplantation assay, can dramatically affect estimates of tumor initiating cell frequency. Moreover, conditional on cell culture conditions, the tumor-initiating cell fraction of bulk mouse mammary tumor cell preparations can either be maintained at high or low frequency in vitro thus permitting comparative studies of tumorigenic and non-tumorigenic cancer cells.
Coping with unreliable channels: Efficient link estimation for low-power wireless sensor networks

The dynamic nature of wireless communication and the stringent energy constraints are major challenges for the design of low-power wireless sensor network applications. The link quality of a wireless link is known for its great variability, dependent on the distance between nodes, the antennapsilas radiation characteristic, multipath, diffraction, scattering and many more. Especially for indoor and urban deployments, there are numerous factors impacting the wireless channel. In an extensive experimental study contained in the first part of this paper, we show the magnitude of this problem for current Wireless Sensor Networks (WSNs) and that based on the overall connectivity graph of a typical multihop WSN, a large portion of the links actually exhibit very poor characteristics. We present a pattern based estimation technique that allows assessing the quality of a link at startup and as a result to construct an optimal neighbor table right at the beginning using a minimum of resources only. Our estimation technique is superior compared to other approaches where protocols continue to decide on the fly which links to use expending valuable energy both for unnecessary retransmissions and recursive link estimation.
Using rhythm to teach spelling to a child with autism

Using Rhythm to Teach Spelling to a Child with Autism Celina Marie Cerf, M.A. The University of Texas at Austin, 2015 Supervisor: Li Sheng Co-Supervisor: Jessica Franco The purpose of this study was to develop a multimodal spelling acquisition program (MSAP) for children with autism that capitalizes on sensory perception skills that may be intact with this population to teach early spelling skills. Progress was monitored through seven phases: pre-assessment, baseline probe, acquisition probe, instruction sessions, post-assessment, and maintenance probes of the treatment. MSAP provides for three spelling instructional conditions: (1) instruction with rhythmic auditory feedback in the form of Morse Code presented via speakers at 450 Hz, (2) instruction with rhythmic tactile feedback of Morse Code presented via a bone oscillator, and (3) instruction without feedback. The MSAP program recorded the child’s performance for spelling accuracy and rate for each word during the assessment probes. Although the child acquired spelling knowledge of the target words, the statistical analysis revealed no significant difference in the spelling acquisition between the instruction conditions. The computerized instruction did generalize to untaught words. This study’s limitations and future directions are discussed. Table of
Reachability of consensus and synchronizing automata

We consider the problem of determining the existence of a sequence of matrices driving a discrete-time multi-agent consensus system to consensus. We transform this problem into the problem of the existence of a product of the (stochastic) transition matrices that has a positive column. This allows us to make use of results from automata theory to sets of stochastic matrices. Our main result is a polynomial-time algorithm to decide the existence of a sequence of matrices achieving consensus.
Lectin histochemical characteristics of the epithelial surface of ileal Peyer's patches in 3-week-old pigs.

Distinct glycoconjugate expression between dome enterocytes and villus enterocytes in ileum from twelve 3-week-old conventional pigs was examined by the use of twenty one biotinylated lectins with avidin-biotin-peroxidase complex method. Three patterns of staining were seen. First, lectins bind to dome enterocyte and villus enterocyte to approximately equal staining, i.e. DSL, WGA, s-WGA and ConA. Second, lectins display a markedly higher affinity for villus enterocyte than dome enterocyte, i.e. DBA, SBA, RCA I, SJA, VVA, BSL II, LEL, PNA, Jacalin, and ECL. Third, lectins exhibit negative staining to dome enterocyte only, i.e. PSA, LCA, UEA-I, and STL. Four lectins; PSA, LCA, UEA-I, STL may be useful negative marker to differentiate glycoconjugate expression between dome enterocyte and villus enterocyte. The staining patterns are slightly different among these negative markers. Three lectins, PSA, LCA, and UEA-1, are negative marker to differentiate dome enterocytes and villus enterocytes. But STL is also negative to dome epithelial surface and moderately positive to villus brush border. It is suggested that the present lectin-binding studies provide the marker of dome enterocyte as compared with villus enterocytes.
Nonparametric Density Estimation for Positive Time Series

The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For independent and identically distributed data, several solutions have been put forward to solve this boundary problem. In this paper, we propose the gamma kernel estimator as a density estimator for positive time series data from a stationary @a-mixing process. We derive the mean (integrated) squared error and asymptotic normality. In a Monte Carlo simulation, we generate data from an autoregressive conditional duration model and a stochastic volatility model. We study the local and global behavior of the estimator and we find that the gamma kernel estimator outperforms the local linear density estimator and the Gaussian kernel estimator based on log-transformed data. We also illustrate the good performance of the h-block cross-validation method as a bandwidth selection procedure. An application to data from financial transaction durations and realized volatility is provided.
Destination Prediction by Identifying and Clustering Prominent Features from Public Trajectory Datasets

Destination prediction is an essential task in many location-based services (LBS) such as providing targeted advertisements and route recommendations. Most existing solutions were generative methods that model the problem as a series of probabilistic events that are then used to compute the destination probability using Bayes’ rule. In contrast, we propose a discriminative method that chooses the most prominent features found in a public trajectory dataset, clusters the trajectories into groups based on these features, and performs destination prediction queries accordingly. Our method is more concise and simple than existing methods while achieving better runtime efficiency and prediction accuracy as verified by experimental studies. Received on XXXX; accepted on XXXX; published on XXXX
QTL analysis of photoperiod sensitivity in common buckwheat by using markers for expressed sequence tags and photoperiod-sensitivity candidate genes

Photoperiod sensitivity is an important trait related to crop adaptation and ecological breeding in common buckwheat (Fagopyrum esculentum Moench). Although photoperiod sensitivity in this species is thought to be controlled by quantitative trait loci (QTLs), no genes or regions related to photoperiod sensitivity had been identified until now. Here, we identified QTLs controlling photoperiod sensitivity by QTL analysis in a segregating F4 population (n = 100) derived from a cross of two autogamous lines, 02AL113(Kyukei SC2)LH.self and C0408-0 RP. The F4 progenies were genotyped with three markers for photoperiod-sensitivity candidate genes, which were identified based on homology to photoperiod-sensitivity genes in Arabidopsis and 76 expressed sequence tag markers. Among the three photoperiod-sensitivity candidate genes (FeCCA1, FeELF3 and FeCOL3) identified in common buckwheat, FeELF3 was associated with photoperiod sensitivity. Two EST regions, Fest_L0606_4 and Fest_L0337_6, were associated with photoperiod sensitivity and explained 20.0% and 14.2% of the phenotypic variation, respectively. For both EST regions, the allele from 02AL113(Kyukei SC2)LH.self led to early flowering. An epistatic interaction was also confirmed between Fest_L0606_4 and Fest_L0337_6. These results demonstrate that photoperiod sensitivity in common buckwheat is controlled by a pathway consisting of photoperiod-sensitivity candidate genes as well as multiple gene action.
Reasons for reconsidering quantitative research based on the use of Likert scale and other social science data sets. J. Michell. (1999). Measurement in psychology: Critical history of a methodological concept. United Kingdom: Cambridge University Press. Price: $99.00 (hardback)

A sense of common cause largely motivates my review of this book. Like the author, Joel Michell, I am increasingly inclined to the view that there is "an error in scientific method fundamental to quantitative psychology'' (p. xi), one that generalises across the social sciences (although I hadn't glimpsed the full extent prior to looking through this book). In my current capacity as statistical adviser to a Faculty of Education, I encounter an ocean of research that washes between the shores of qualitative (e.g., case studies) and quantitative (e.g., attitude) research. The latter is largely focused on the use of survey instruments based on the Likert scale. The "rule of thumb'' seems to be that a continuum of response categories such as "strongly disagree, disagree, undecided, agree, strongly agree", can be recoded numerically as 1, 2, 3 , 4, 5. Usually, the resulting set of numbers is analysed as if possessing ratio or at least equal interval properties. That is, participant responses signifying, for example, agreement vs. disagreement typically are analysed by computing central tendency and range (descriptive statistics) and then examining significant differences between conditions by means of quantitative statistical procedures (inferential statistics). To my mind, this approach to the analysis of human data is built on a foundation of sand, the sand being the inability of such numerical scales to amount to more than a numerical representation of an ordinal, at best, set of response categories. At this point, the book under review gets a mention. The author's major assertion is that the unfounded assumptions I've noted in relation to the use of the Likert scale in educational research are present throughout the social sciences. Michell begins by defining quantitative science as seeking to discover Euclidean relationships between changes in the intensity of attributes (e.g., length) that are additive and can be expressed in terms of a ratio (i.e., M2 is twice as long as MI; length x breadth = area). In these terms, the goal of measurement can be restated as the process of discovering ratios. He contrasts the approach of psychological measurement, including scales based on item
Eurosensors XXVI , September 9-12 , 2012 , Kraków , Poland Electromagnetic transduction for wireless passive sensors

Wireless sensors market is growing very fast these last years tanks to the availability of cheap, small and efficient micro-sensors, batteries, analog and RF circuits, and to the presence of standardized communication protocols. Even if these active sensors are very attractive for a lot of applications, they suffer from weak energy autonomy and they are not compatible with harsh environment. In order to overcome these problems, we have developed a new kind of wireless sensors using electromagnetic transducers and radar interrogation. These passive sensors (battery-less and without electronic components) have been studied for pressure, temperature, gas and stress applications © 2012 Published by Elsevier Ltd.
The Characteristics of Implicit Theory of Intelligence of Children in Higher Grader of Primary School and the Effects of Praise On it

With 101 children of 5th-grade students as subjects,the experimental study explored the characteristics of the development of implicit theory of intelligence and the influences of praise on it.The results were:(a) All children in three different conditions endorsed an incremental theory of intelligence,indicating children in higher grader of primary school in our country emphasized the plasticity of intelligence;children in the control condition rated effort more important than ability,indicating children in higher grader of primary school considered effort more important for our achievement;(b) The degree to which the groups endorsed an entity theory of intelligence showed significant differences among the children in the three conditions,children that praised for ability more inclined to consider intelligence as an fixed、uncontrollable trait.
Robust adaptive fuzzy tracking control for a class of nonlinear systems

This paper deals with the design of a robust adaptive fuzzy tracking control for a class of uncertain and disturbed nonlinear systems. In addition to the desired performances and the convergence of the tracking error, the proposed approach guarantees the uniformly ultimately boundedness of the resulting closed-loop system. Furthermore, it allows overcoming many problems related to adaptive fuzzy controllers like singularity problem and constraints on the control gain, and reducing the number of used parameters, which encourage the real-time implementation. Finally two simulation examples are presented to show the effectiveness and the performances of the proposed approach.
Feature Extraction Based on Nonparametric Waveform Estimation and Matching Pursuit

This paper presents a novel method for extracting feature waveforms of the compound signal, which combined the nonparametric waveform estimation based on filter bank with the conventional matching pursuit (MP). At each iteration of the MP, the proposed method expressed the extracted feature waveform that has the best matched with the signal local structure with a series expansion of a set of nonparametric basis functions which generated by filtering the template signal through a bandpass filter bank. A prior signal information is no more require for a template signal owe to apply the adaptive template signal in this method. So, the construction of general described by some parameters is unnecessary and it felicitates the method for a wide variety of applications. Simulated and experimental results verify the practicability and effectiveness of this algorithm, even if the noise frequency band coincides with that of the feature waveform of the signal.
Family with Sequence Similarity 60A (FAM60A) Protein Is a Cell Cycle-fluctuating Regulator of the SIN3-HDAC1 Histone Deacetylase Complex*

Background: The SIN3-HDAC is a multimeric histone deacetylase complex that regulates gene expression. Results: FAM60A, a cell cycle-regulated protein, is a subunit of the SIN3-HDAC complex that influences the expression of certain SIN3-HDAC-regulated genes. Conclusion: FAM60A is a novel subunit of SIN3-HDAC that regulates gene expression. Significance: FAM60A, a novel component of SIN3-HDAC, is required for proper cyclin D1 expression. The SIN3A-HDAC complex deacetylates histones thereby repressing gene transcription. Here we describe family with sequence similarity 60A (FAM60A), a cell cycle-regulated protein that binds to the SIN3-HDAC complex. FAM60A expression peaks during G1 and S phases of the cell cycle in U2OS cells, in a manner similar to the G1 regulator cyclin D1, which is a known target of SIN3-HDAC. In this light we found that FAM60A binds to SIN3-HDAC-regulated promoters such as cyclin D1 in G1 and S phases. Cells depleted of FAM60A show increased histone acetylation at the cyclin D1 promoter and elevated levels of cyclin D1 mRNA and protein. Furthermore, depletion of FAM60A altered the periodic association of HDAC1 with the cyclin D1 promoter, increased cyclin D1 expression at all cell cycle phases, and caused premature S phase entry. The data in this study introduce FAM60A as a novel regulator of SIN3-HDAC function and gene expression.
Improved image quality measure through particle swarm optimization

In this paper we present new approach to the objective image quality evaluation based on discrete wavelet transform (DWT) and particle swarm optimization (PSO). DWT was applied on image difference (difference between original and degraded image) that is decomposed into approximation and detail subbands. DWT coefficients were computed using Coiflet wavelet filter banks. The coefficients were used to compute new image quality measure (IQM) that is defined as perceptual weighted difference between coefficients of original and degraded image. Weighting factors for wavelet subbands have been experimentally determined using PSO optimization algorithm to achieve the best possible correlation with results of subjective (perceptual) image quality evaluation. Experimental results demonstrate that the proposed technique has high correlation with results of subjective test and low computational time important for real-time applications.
Confrontations in “Genethics”: Rationalities, Challenges, and Methodological Responses

It was only a matter of time before the portmanteau term “genethics” would be coined and a whole field within bioethics delineated. The term can be dated back at least to 1984 and the work of James Nagle, who claims credit for inventing the word, which he takes “to incorporate the various ethical implications and dilemmas generated by genetic engineering with the technologies and applications that directly or indirectly affect the human species. ” In Nagle’s phrase, “Genethic issues are instances where medical genetics and biotechnology generate ethical problems that warrant societal deliberation. ” The great promises and terrific threats of developments in scientific understanding of genetics, and the power to enhance, modify, or profit from the knowledge science breeds, naturally offer a huge range of issues to vex moral philosophers and social theorists. Issues as diverse as embryo selection and the quest for immortality continue to tax analysts, who offer reasons as varied as the matters that might be dubbed “genethical” for or against the morality of things that are actually possible, logically possible, and even just tenuously probable science fiction.