Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Reducing the Length of the Questionnaire by Multiple Matrix Sampling on the Validity of Structural Equation Modeling for Factors Affecting Job Morale

The research was designed to examine the effects of question setting using different conditions into 10 sets on the validity of structural equation modeling for factors affecting job morale. The data was collected from 690 personnel working in regional Statistical Offices around Thailand by using cluster random sampling. The tool used in collecting data was the questionnaire with 95 items and 5 levels of rating scale. The discrimination value was between 0.244 and 0.860 and the reliability: α was from 0.699 to 0.900. Data analysis was conducted by the use of descriptive statistics and structural equation modeling by Mplus 7.4 program. The findings showed that the structural equation modeling with question setting in 3 sets of sub-questionnaires, cooperated with item sampling without replacement and non-fixing core items, conformed to the empirical data the most and that overall relationship between the structural model parameter and the model parameter from the complete questionnaire was high in a positive way.
Targeted Maximum Likelihood Method for Repeated Measures Semiparametric Regression: Discovery for Transcription Factor Activity

In longitudinal and repeated measures data analysis, often the goal is to determine the effect of a treatment or aspect on a particular outcome (e.g. disease progression). We consider semiparametric repeated measures regression model, where the parametric component models effect of the variable of interest and any modification by other covariates. The expectation of this parametric component over the other covariates is a measure of variable importance. Here we present a targeted maximum likelihood estimator of the finite dimensional regression parameter, which is easily estimated using standard software for generalized estimating equations. The targeted maximum likelihood method provides double robust and locally efficient estimates of the variable importance parameters and inference based on the influence curve. We demonstrate these properties through simulation under correct and incorrect model specification, and apply our method in practice to estimating the activity of transcription factor (TF) over cell cycle in yeast. We specifically target the importance of SWI4, SWI6, MBP1, MCM1, ACE2, FKH2, NDD1, and SWI5. The semiparametric model allows us to determine the importance of a TF at specific time points by specifying time indicators as potential effect modifiers of the TF. Our results are promising, showing significant importance trends during the expected time periods. This methodology can also be used as a variable importance analysis tool to assess the effect of a large number of variables such as gene expressions, or single nucleotide polymorphisms.
Scaling in financial prices: IV. Multifractal concentration

In the Brownian model, even the largest of N successive daily price increments contributes negligibly to the overall sample variance. The resulting 'absent' concentration justifies the role of variance in measuring Brownian volatility. Mandelbrot introduced in 1963 an alternative 'mesofractal model', in which the population variance is infinite. A significant proportion of the overall sample variance comes from an absolutely small number of large contributions, expressing a 'hard' form of concentration. To achieve a prescribed proportion of the overall measured variance, those 1900 and 1963 models require numbers of days of the order of N 1 and N 0, respectively. This paper shows that an intermediate possibility exists: a new and very flexible 'soft' form of concentration is provided by the 'multifractal' model Mandelbrot introduced in 1997. The standard 'extreme values' theory applies to mesofractals but multifractals behave very differently. The single largest contribution to sample variance is asymptotically negligible; however, an arbitrarily high proportion of the overall variance is contributed by a number of days of the order of N D, where 0<D<1. The characteristic exponent D, a fractal dimension, is a consequence of scaling. It allows 'softness' to be modulated between the unrealistic extremes N 1 and N 0. As N increases, so does the absolute number N D, but the relative number N D/N decreases to zero. As a result, the bulk of the significant effects concentrates in a small proportion of cases. (This is a finite approximation of a set of measure zero, but mathematical refinements do not matter in this paper.)
Classification of Cell Death

In 1972 Kerr and colleagues collect the cell death under two headings. Although cell death is known as apoptosis ve necrosis, molecular studies add to morphological studies and according to this, this classification is extended. In 2009 NCCD classifies it entosis, mitotic collapse, necrosis, necropitosis and pyroptosis by using terminological words. In addition to these there are diffirent types of cell death in terms of signal pathway. These are autophagic cell death, carnification cell death, netoz cell death, partanatoz cell death, anoikis cell death. In this article these types of cell death is noticed in detail.
Faster gradient descent via an adaptive learning rate

Any gradient descent requires to choose a learning rate. With deeper and deeper models, tuning that learning rate can easily become tedious and does not necesarily lead to an ideal convergence. We propose a variation of the gradient descent algorithm in the which the learning rate η is not fixed. Instead, we learn η itself, either by another gradient descent (first-order method), or by Newton’s method (second-order). This way, gradient descent for any machine learning algorithm can be optimized.
Sources and accumulation of organic carbon in the Pearl River Estuary surface sediment as indicated by elemental, stable carbon isotopic, and carbohydrate compositions

Abstract. Organic matter in surface sediments from the upper reach of the Pearl River Estuary and Lingdingyang Bay, as well as the adjacent northern South China Sea shelf was characterized using a variety of techniques, including elemental (C and N) ratio, bulk stable organic carbon isotopic composition (δ13C), and carbohydrate composition analyses. Total organic carbon (TOC) content was 1.21±0.45% in the upper reach, down to 1.00±0.22% in Lingdingyang Bay and to 0.80±0.10% on the inner shelf and 0.58±0.06% on the outer shelf. δ13C values ranged from −25.1‰ to −21.3‰ in Lingdingyang Bay and the South China Sea shelf, with a trend of enrichment seawards. The spatial trend in C/N ratios mirrored that of δ13C, with a substantial decrease in C/N ratio offshore. Total carbohydrate yields ranged from 22.1 to 26.7 mg (100 mg OC)−1, and typically followed TOC concentrations in the estuarine and shelf sediments. Total neutral sugars, as detected by the nine major monosaccharides (lyxose, rhamnose, ribose, arabinose, fucose, xylose, galactose, mannose, and glucose), were between 4.0 and 18.6 mg (100 mg OC)−1 in the same sediments, suggesting that significant amounts of carbohydrates were not neutral aldoses. Using a two end-member mixing model based on δ13C values and C/N ratios, we estimated that the terrestrial organic carbon contribution to the surface sediment TOC was ca. 78±11% for Lingdingyang Bay, 34±4% for the inner shelf, and 5.5±1% for the outer shelf. The molecular composition of the carbohydrate in the surface sediments also suggested that the inner estuary was rich in terrestrially derived carbohydrates but that their contribution decreased offshore. A relatively high abundance of deoxyhexoses in the estuary and shelf indicated a considerable bacterial source of these carbohydrates, implying that sediment organic matter had undergone extensive degradation and/or transformation during transport. Sediment budget based on calculated regional accumulation rates showed that only ~50% of the influxes of terrestrial organic carbon were accumulated in the estuary. This relatively low accumulation efficiency of terrestrial organic matter as compared to the total suspended solids (accumulation efficiency ~73%) suggested significant degradation of the terrestrial organic carbon within the estuarine system after its discharge from the river. This study demonstrated that the combination of the bulk organic matter properties together with the isotopic composition and molecular-level carbohydrate compositions can be an efficient way to track down the source and fate of organic matter in highly dynamic estuarine and coastal systems. The predominance of terrestrially originated organic matter in the sediment and its generally low accumulation efficiency within the estuary is not surprising, and yet it may have important implications in light of the heavy anthropogenic discharges into the Pearl River Estuary during the past thirty years.
James D. Meernik, Acting Dean of the Robert B. Toulouse School of Graduate Studies GRAPH-BASED KEYPHRASE EXTRACTION USING WIKIPEDIA Bharath Dandala, B.Tech. Thesis Prepared for the Degree of MASTER OF SCIENCE UNIVERSITY OF NORTH TEXAS

Keyphrases describe a document in a coherent and simple way, giving the prospective reader a way to quickly determine whether the document satisfies their information needs. The pervasion of huge amount of information on Web, with only a small amount of documents have keyphrases extracted, there is a definite need to discover automatic keyphrase extraction systems. Typically, a document written by human develops around one or more general concepts or sub-concepts. These concepts or sub-concepts should be structured and semantically related with each other, so that they can form the meaningful representation of a document. Considering the fact, the phrases or concepts in a document are related to each other, a new approach for keyphrase extraction is introduced that exploits the semantic relations in the document. For measuring the semantic relations between concepts or sub-concepts in the document, I present a comprehensive study aimed at using collaboratively constructed semantic resources like Wikipedia and its link structure. In particular, I introduce a graph-based keyphrase extraction system that exploits the semantic relations in the document and features such as term frequency. I evaluated the proposed system using novel measures and the results obtained compare favorably with previously published results on established benchmarks. BIBLIOGRAPHY 43 v CHAPTER 1 INTRODUCTION 1.1. Keyphrase Extraction Keyphrases are words or phrases that indicate the main topics in a document [12]. Keyphrases describe a document in a coherent and simple way, giving the prospective reader a way to quickly determine whether the document satisfies their information needs. The per-vasion of the huge amount of information on World Wide Web, with only a small amount of documents have keyphrase generated, there is a definite need to build keyphrase generation systems. Manual assignment of keyphrase is a tedious and time-consuming task, especially considering the proliferation of the web. Thus, there is a great need for means of automatic keyphrase generation systems. Keyphrase generation is an approach to collect the main topics of a document into a list of phrases. The task of automatic keyphrase generation is divided into two groups: keyphrase assignment and keyphrase extraction. In keyphrase assignment, all potential keyphrases appear in a predefined vocabulary and the task is to classify documents into different keyphrase classes. In keyphrase extraction, keyphrases are available in the document,although authors occasionally supply keyphrases that they do not appear in the document [9]. Automatic keyphrase extraction is the identification of the most important phrases …
Excessive Cap-dependent Translation as a Molecular Mechanism Underlying ASD

Abstract : We hypothesize that excessive cap-dependent translation is a causative factor in autism spectrum disorder (ASD). To test this hypothesis, we have been studying transgenic mice that overexpress eIF4E have been testing the following specific aims: 1) to determine whether eIF4E transgenic mice display behaviors consistent with ASD, 2) to determine whether ASD-like behaviors displayed by eIF4E transgenic mice can be reversed by novel cap-dependent translation inhibitors, and 3) to determine whether eIF4E transgenic mice display cellular and molecular abnormalities due to excessive cap-dependent translation. mice. Our studies will provide information concerning whether overexpression of eIF4E is a biological risk factor for ASD. Our studies also will provide important information concerning the role of upregulated cap-dependent translation in ASD, and could link ASD mechanistically at the level of cap-dependent translational control to fragile X syndrome (FXS), tuberous sclerosis complex (TSC), and autistic patients with PTEN and EIF4E mutations. Moreover, the results of these studies would provide information for the design and use of compounds to therapeutically target eIF4E-eIF4G interactions and eIF4A for treating patients with ASD.
Chest Imaging Findings in Hospitalized Children with H1N1 Influenza

INTRODUCTION Novel swine-origin influenza A (2009 H1N1) was first reported in Mexico in April 2009 (1). Since then, it has rapidly spread to many countries around the world. The first laboratory-confirmed case in Turkey was seen on June 27, 2009, and the pandemic 2009 H1N1 influenza A virus arrived at Konya in September 2009 (2). The symptoms of H1N1 infection may be similar to seasonal influenza, and hospitalization is not usually required. The virus can infect the lower respiratory tract and cause rapidly progressive pneumonia, especially in children and younger adults. The abnormal thoracic computed tomography (CT) scan findings vary widely among the studies of 2009 H1N1 influenza. Descriptions of the chest imaging manifestations of H1N1 virus infection in children are limited (3-7).
Transparent Electrochemical Detectors to Study Exocytosis

Neurons release neurotransmitters in a process called exocytosis, wherein packets of transmitter molecules are released from the cells upon stimulation. Adrenal chromaffin cells, which also undergo exocytosis, constitute a model system for neuronal release. Quantal release of adrenaline from chromaffin cells can be measured using the electrochemical technique of amperometry, historically employing a carbon fiber electrode [1]. To gain information about the exocytotic mechanism, we have developed a method of electrochemical imaging employing transparent microfabricated devices based on amperometry. We have successfully measured electrochemical events using transparent electrodes simultaneously with fluorescence imaging, yielding more information about the exocytotic process.
ACOUSTIC SCENE CLASSIFICATION USING SPATIAL FEATURES

Due to various factors, the vast majority of the research in the field of Acoustic Scene Classification has used monaural or binaural datasets. This paper introduces EigenScape a new dataset of 4th-order Ambisonic acoustic scene recordings and presents preliminary analysis of this dataset. The data is classified using a standard Mel-Frequency Cepstral Coefficient Gaussian Mixture Model system, and the performance of this system is compared to that of a new system using spatial features extracted using Directional Audio Coding (DirAC) techniques. The DirAC features are shown to perform well in scene classification, with some subsets of these features outperforming the MFCC classification. The differences in label confusion between the two systems are especially interesting, as these suggest that certain scenes that are spectrally similar might not necessarily be spatially similar.
TWO LEVEL SELF -SUPERVISED RELATION EXTRACTION FROM MEDLINE USING UMLS

The biomedical research literature is one among many other domains that hides a precious knowledge, and the biomedical community made an extensive use of this scientific literature to discover the facts of biomedical entities, such as disease, drugs,etc.MEDLINE is a huge database of biomedical research papers which remain a significantly underutilized source of biological information. Discovering the useful knowledge from such huge corpus leads to various problems related to the type of information such as the concepts related to the domain of texts and the semantic relationship associated with them. In this paper, we propose a Two-level model for Self-supervised relation extraction from MEDLINE using Unified Medical Language System (UMLS) Knowledge base. The model uses a Self-supervised Approach for Relation Extraction (RE) by constructing enhanced training examples using information from UMLS. The model shows a better result in comparison with current state of the art and naive approaches.
Inhomogeneous driving in quantum annealers can result in orders-of-magnitude improvements in performance

Quantum annealers are special-purpose quantum computers that primarily target solving Ising optimization problems. Theoretical work has predicted that the probability of a quantum annealer ending in a ground state can be dramatically improved if the spin driving terms, which play a crucial role in the functioning of a quantum annealer, have different strengths for different spins; that is, they are inhomogeneous. In this paper we describe a time-shift-based protocol for inhomogeneous driving and demonstrate, using an experimental quantum annealer, the performance of our protocol on a range of hard Ising problems that have been well-studied in the literature. Compared to the homogeneous-driving case, we find that we are able to improve the probability of finding a ground state by up to 107× for Weak–Strong–Cluster problem instances, and by up to 103× for more general spin-glass problem instances. In addition to being of practical interest as a heuristic speedup method, inhomogeneous driving may also serve as a useful tool for investigations into the physics of experimental quantum annealers.
Triangular road signs detection and recognition algorithm and its embedded system implementation

This paper proposes a low-complex triangular road signs detection and recognition algorithm that can be implemented on an embedded system for real-time applications and maintains decent detection and recognition accuracy under inclement weather conditions. The proposed method is composed of the shape detection to locate triangular road signs followed by the two feature extraction methods to focus on their different contents, and the descriptor construction method to eliminate the noise and make the system robust. This work is implemented on a desktop computer as well on an automotive-grade Freescale i.MX 6 embedded platform. Under a video resolution of 1280x720, the proposed system achieves 161 fps on the desktop computer and 17 fps on the Freescale i.MX6 embedded platform with an overall accuracy of 93.33%.
Switching via quantum activation: A parametrically modulated oscillator (14 pages)

We study switching between period-two states of an underdamped quantum oscillator modulated at nearly twice its natural frequency. For all temperatures and parameter values switching occurs via quantum activation: it is determined by diffusion over oscillator quasienergy, provided the relaxation rate exceeds the rate of interstate tunneling. The diffusion has quantum origin and accompanies relaxation to the stable state. We find the semiclassical distribution over quasienergy. For T=0, where the system has detailed balance, this distribution differs from the distribution for T{yields}0; the T=0 distribution is also destroyed by small dephasing of the oscillator. The characteristic quantum activation energy of switching displays a typical dependence on temperature and scaling behavior near the bifurcation point where period doubling occurs.
HOW ACCURATE IS MOLECULAR DYNAMICS

This thesis consists of the four papers which consider different aspects of stochastic process modeling, error analysis, and minimization of computational cost. In Paper I, we construct a Multipath Fading Channel (MFC) model for wireless channels with noise introduced through scatterers flipping on and off. By coarse graining the MFC model a Gaussian process channel model is developed. Complexity and accuracy comparisons of the models are conducted. In Paper II, we generalize a multilevel Forward Euler Monte Carlo method introduced by Mike Giles for the approximation of expected values depending on solutions of Ito stochastic differential equations. Giles' work proposed and analyzed a Forward Euler Multilevel Monte Carlo (MLMC) method based on realizations on a hierarchy of uniform time discretizations and a coarse graining based control variates idea to reduce the computational cost required by a standard single level Forward Euler Monte Carlo method. This work is an extension of Giles' MLMC method from uniform to adaptive time grids. It has the same improvement in computational cost and is applicable to a larger set of problems. In paper III, we consider the problem to estimate the mean of a random variable by a sequential stopping rule Monte Carlo method. The performance of a typical second moment based sequential stopping rule is shown to be unreliable both by numerical examples and by analytical arguments. Based on analysis and approximation of error bounds we construct a higher moment based stopping rule which performs more reliably. In paper IV, Born-Oppenheimer dynamics is shown to provide an accurate approximation of time-independent Schrodinger observables for a molecular system with an electron spectral gap, in the limit of large ratio of nuclei and electron masses, without assuming that the nuclei are localized to vanishing domains. The derivation, based on a Hamiltonian system interpretation of the Schrodinger equation and stability of the corresponding hitting time Hamilton-Jacobi equation for non ergodic dynamics, bypasses the usual separation of nuclei and electron wave functions, includes caustic states and gives a different perspective on the Born-Oppenheimer approximation, Schrodinger Hamiltonian systems and numerical simulation in molecular dynamics modeling at constant energy.
On the spectral and Frobenius norm of a generalized Fibonacci r-circulant matrix

Abstract Consider the recursion g0 = a, g1 = b, gn = gn−1 + gn−2, n = 2, 3, . We compute the Frobenius norm of the r-circulant matrix corresponding to g0, . , gn−1. We also give three lower bounds (with equality conditions) for the spectral norm of this matrix. For this purpose, we present three ways to estimate the spectral norm from below in general.
Aerobic oxidation of thiols to disulfides by heterogeneous gold catalysts

Thiols are smoothly and efficiently oxidized to disulfides (RSSR) with air in the presence of gold nanoparticles supported on CeO2 in absence of solvent, as well as in aqueous solutions and neutral pH. It is shown that the reaction can occur through the coupling of two sulphur radicals on the metal surface. The sulphur radicals are formed from thiols by one-electron oxidation with the metal. This reaction mechanism strongly resembles that found for sulfhydryl oxidases, a class of enzymes which are involved in the oxidative protein folding through de novo formation of disulfides from thiols.