Miracle-dz/UniFAR-FTUs huggingface dataset:
NGOs, human capital, and women's empowerment: Evidence from Bangladesh.

This thesis studies the effects of non-governmental organizations (NGOs) on human capital investment and women's empowerment in Bangladesh. Chapter Two studies how the entry of NGOs in primary education has affected educational outcomes of girls and examines the mechanisms which account for the relative performance of NGO versus state schools in improving female educational outcomes. The results show that the entry of NGO schools has significantly increased girls' enrollment as compared to boys. The two most prominent characteristics of NGO schools that encourage girls' enrollment are the high percentage of female teachers and having Parent-Teacher Associations. NGO schools show strong effects in improving children's test scores. Chapter Three analyzes the factors which affect teacher presence, student attendance, and community participation in primary schools in Bangladesh. The results show that, after controlling for other factors, NGO school teachers are more likely to be present in school, NGO schools are associated with higher student attendance rates, and guardians of NGO school students, in particular mothers, are more likely to participate in school meetings. Motivation appears the most important factor explaining teacher presence among NGO school teachers. Teacher attendance rate and other factors relating to curriculum and school facility explain student attendance in NGO schools. Chapter Four investigates the effects of having the Grameen Bank in the village of residence on fertility decisions and women's empowerment. The results suggest that the Grameen Bank affects fertility decisions in the direction towards lower fertility. The changes include a reduction in women's ideal number of children and the number of births in the year prior to the survey, and an increase in husband's approval rate, and actual use, of family planning methods. Having the Grameen Bank in the village shows positive relationship with women's empowerment as measured by contribution to family support and mobility.
Fast Bidimensional Empirical Mode Decomposition Based on an Adaptive Block Partitioning

†† Summary The decomposition of images with great size using the Bidimensional Empirical Mode Decomposition (BEMD) necessitates an important calculation time. To overcome this problem we first proposed in [1] a new approach using Blockbased BEMD method (BBEMD) where an input image is subdivided into four subblocks, and then the BEMD is applied on each of the four blocks separately. This method offered a good solution to the calculation time, unfortunately blocking artefact is noticeable in the resulting modes, this is a result of ignoring the interblock correlation during the BEMD process and every block was taken as an independent entity when interpolating the blocks borders in the sifting process. The Lapped Block-based BEMD (LBBEMD) is then proposed to whelm the artefact problem using for every block the neighbouring information by enlarging the block neighbourhood related to the two adjacent blocks inside the image during the blocks decomposition. Enlarging neighbourhood blocks necessitate intensive simulations to have for each block the corresponding enlargement size, thing that affects remarkably on the calculation time. Experimentation shows that the LBBEMD can not handle correctly the artefact problems, because the enlargement size can not be enough “or too big” to surround all the concerned pixels for each block in the image. The problem with the LBBEMD is to exactly define, a priori, for each block the size of the neighbouring enlargement size. In this paper, we will present an adaptive and fast Block Empirical mode decomposition to eliminate definitively the artefacts problems when subdividing an image into lapped blocks and we will prove, by simulations, that our method offers a good trade-off between computational time and decomposition quality.
A biophysical approach to transcription factor binding site discovery.

Identification of transcription factor binding sites within regulatory segments of genomic DNA is an important step toward understanding of the regulatory circuits that control expression of genes. Here, we describe a novel bioinformatics method that bases classification of potential binding sites explicitly on the estimate of sequence-specific binding energy of a given transcription factor. The method also estimates the chemical potential of the factor that defines the threshold of binding. In contrast with the widely used information-theoretic weight matrix method, the new approach correctly describes saturation in the transcription factor/DNA binding probability. This results in a significant improvement in the number of expected false positives, particularly in the ubiquitous case of low-specificity factors. In the strong binding limit, the algorithm is related to the "support vector machine" approach to pattern recognition. The new method is used to identify likely genomic binding sites for the E. coli transcription factors collected in the DPInteract database. In addition, for CRP (a global regulatory factor), the likely regulatory modality (i.e., repressor or activator) of predicted binding sites is determined.
Structural Approach to the Designing of the Complementary Graphs in the GRADIS Agent Framework

The parallel execution of the programs increases their effectiveness, but designing such the algorithms is more difficult compared to the sequential ones. Thus any form of automatic translation of a sequential program structure into a distributed hardware environment is desired. In the paper the problem of an effective implementation of the complementary graphs concept performed by an agent environment is considered. An inter-agent cooperation leading to removing from the partial graphs the undesired substructures making the parallel graph transformations ineffective is presented.
Computing optimal data collection rate for energy harvesting sensor networks

Environmental energy is an attractive power source for low power wireless sensor networks (WSNs). Renewable energy sources such as solar, wind, thermal, and vibrant energy provides services without interruptions for environmental applications. Environment monitoring applications require data collection from each node but time-varying and dissimilar recharging rates of sensor nodes poses challenges. The aim is to design a sensor network which gives fair and high data extraction from all nodes in presence of renewable energy source by computing lexicographic data collection rate and routing paths for each node. We propose a distributed algorithm for computing lexicographic rate assignment. We compare distributed algorithm with other routing techniques using different scenarios.
Pharmacokinetics and Bioavailability of Plant Lignan 7-Hydroxymatairesinol and Effects on Serum Enterolactone and Clinical Symptoms in Postmenopausal Women: A Single-Blinded, Parallel, Dose-Comparison Study

Objective: 7-Hydroxymaitairesinol (7-HMR) is a naturally occurring plant lignan found in whole grains and the Norway spruce (Piciea abies). The purpose of this study was to evaluate the bioavailability of a proprietary 7-HMR product (HMRlignan, Linnea SA, Locarno, Switzerland) through measurement of lignan metabolites and metabolic precursors. Methods: A single-blind, parallel, pharmacokinetic and dose-comparison study was conducted on 22 postmenopausal females not receiving hormone replacement therapy. Subjects were enrolled in either a 36 mg/d (low-dose) or 72 mg/d dose (high-dose) regimen for 8 weeks. Primary measured outcomes included plasma levels of 7-HMR and enterolactone (ENL), and single-dose pharmacokinetic analysis was performed on a subset of subjects in the low-dose group. Safety data and adverse event reports were collected as well as data on hot flash frequency and severity. Results: Pharmacokinetic studies demonstrated 7-HMR C max = 757.08 ng/ml at 1 hour and ENL C max = 4.8 ng/ml at 24 hours. From baseline to week 8, plasma 7-HMR levels increased by 191% in the low-dose group (p < 0.01) and by 1238% in the high-dose group (p < 0.05). Plasma ENL levels consistently increased as much as 157% from baseline in the low-dose group and 137% in the high-dose group. Additionally, the mean number of weekly hot flashes decreased by 50%, from 28.0/week to 14.3/week (p < 0.05) in the high-dose group. No significant safety issues were identified in this study. Conclusion: The results demonstrate that HMRlignan is quickly absorbed into the plasma and is metabolized to ENL in healthy postmenopausal women. Clinically, the data demonstrate a statistically significant improvement in hot flash frequency. Doses up to 72 mg/d HMRlignan for 8 weeks were safe and well tolerated in this population.
Analysis of the Evolutionary Relationships of the PDZ Domains

The PDZ domains are well-known globular fold module of many scaffolding proteins. The domains are involved in protein-protein interaction and play a central role in organizing diverse cell signaling assemblies [2]. Recently the motifs of their binding sites have been researched in biochemical and structural studies [1, 3], but it was pointed out the difficulty to classify the PDZ domains on the basis of the chemical characteristics of binding sites residues [4]. Another one of the specific known features is that the domain appears several times in a mature protein. The result of sequence analysis of the PDZ domain strongly suggested that the PDZ domains were derived from the domain duplication rather than the vertical conservation or the gene duplication.
Normal Sorting but Defective Endocytosis of the Low Density Lipoprotein Receptor in Mice with Autosomal Recessive Hypercholesterolemia*

Autosomal recessive hypercholesterolemia (ARH) is a genetic form of hypercholesterolemia that clinically resembles familial hypercholesterolemia (FH). As in FH, the rate of clearance of circulating low density lipoprotein (LDL) by the LDL receptor (LDLR) in the liver is markedly reduced in ARH. Unlike FH, LDL uptake in cultured fibroblasts from ARH patients is normal or only slightly impaired. The gene defective in ARH encodes a putative adaptor protein that has been implicated in linking the LDLR to the endocytic machinery. To determine the role of ARH in the liver, ARH-deficient mice were developed. Plasma levels of LDL-cholesterol were elevated in the chow-fed Arh–/– mice (83 ± 8 mg/dl versus 68 ± 8 mg/dl) but were lower than those of mice expressing no LDLR (Ldlr–/–) (197 ± 8 mg/dl). Cholesterol feeding elevated plasma cholesterol levels in both strains. The fractional clearance rate of radiolabeled LDL was reduced to similar levels in the Arh–/– and Ldlr–/– mice, whereas the rate of removal of α2-macroglobulin by the LDLR-related protein, which also interacts with ARH, was unchanged. Immunolocalization studies revealed that a much greater proportion of immunodetectable LDLR, but not LDLR-related protein, was present on the sinusoidal surface of hepatocytes in the Arh–/– mice. Taken together, these results are consistent with ARH playing a critical and specific role in LDLR endocytosis in the liver.
Innovation and Legal Enforcement for Competition Policy: Theory and international evidence from overseas subsidiaries of the Japanese auto-parts suppliers

Do legal enforcements for competition policy have differential effects on innovative research and development (RD Schwartzstein and Shleifer, 2013; Segal and Whinston, 2007). The model suggests that there are in subgame-perfect equilibria some relations concerning average treatment effects of legal enforcement on entrant's R&D or incumbent's deterrence activities, conditional on law and order degree in host countries (World Bank Worldwide Governance Indicators). Second, focusing on overseas subsidiaries of the Japanese auto-parts suppliers that have international deployments with different legal origins in locations, we use a pooled data set of the Basic Survey of Overseas Business Activities and the Basic Survey of Japanese Business Structure and Activities. The average multi-valued treatment effect estimation shows positive results for the model. It suggests that under regulation as a legal enforcement scheme instead of strict liability or negligence, even in countries with low degree of law and order, R&D activities would be more enhanced and R&D-deterrent ones be further suppressed on average. Legal enforcement for competition policy does matter for innovation.
Alterations in Intrinsic Membrane Properties and the Axon Initial Segment in a Mouse Model of Angelman Syndrome

The axon initial segment (AIS) is the site of action potential initiation in neurons. Recent studies have demonstrated activity-dependent regulation of the AIS, including homeostatic changes in AIS length, membrane excitability, and the localization of voltage-gated Na+ channels. The neurodevelopmental disorder Angelman syndrome (AS) is usually caused by the deletion of small portions of the maternal copy of chromosome 15, which includes the UBE3A gene. A mouse model of AS has been generated and these mice exhibit multiple neurological abnormalities similar to those observed in humans. We examined intrinsic properties of pyramidal neurons in hippocampal area CA1 from AS model mice and observed alterations in resting membrane potential, threshold potential, and action potential amplitude. The altered intrinsic properties in the AS mice were correlated with significant increases in the expression of the α1 subunit of Na/K-ATPase (α1-NaKA), the Na+ channel NaV1.6, and the AIS anchoring protein ankyrin-G, as well as an increase in length of the AIS. These findings are the first evidence for pathology of intrinsic membrane properties and AIS-specific changes in AS, a neurodevelopmental disorder associated with autism.
X-inactivation patch size in human female tissue confounds the assessment of tumor clonality

Most models of tumorigenesis assume that tumors are monoclonal in origin. This conclusion is based largely on studies using X chromosome-linked markers in females. One important factor, often ignored in such studies, is the distribution of X-inactivated cells in tissues. Because lyonization occurs early in development, many of the progeny of a single embryonic stem cell are grouped together in the adult, forming patches. As polyclonality can be demonstrated only at the borders of X-inactivation patches, the patch size is crucial in determining the chance of demonstrating polyclonality and hence the number of tumors that need to be examined to exclude polyclonality. Previously studies using X-linked genes such as glucose-6-phosphate dehydrogenase have been handicapped by the need to destroy the tissues to study the haplotypes of glucose-6-phosphate dehydrogenase [Fialkow, P.-J. (1976) Biochim. Biophys. Acta 458, 283–321] or to determine the restriction fragment length polymorphisms of X chromosome-linked genes [Vogelstein, B. , Fearon, E. R. , Hamilton, S. R. & Feinberg, A. P. (1985) Science 227, 642–645]. Here we visualize X-inactivation patches in human females directly. Results show that the patch size is relatively large in both the human colon and breast, confounding assessment of tumor clonality with traditional X-inactivation studies.
The Effect Of Earnings Management And Disclosure On Information Asymmetry

This research aims to provide empirical evidence about the effect of earnings management and disclosure on information asymmetry. This research was conducted using a population of public sector property companies, real estate and building construction in Indonesia Stock Exchange. Samples were selected based on the following criteria: (1) registered as property companies, real estate and building construction, (2) has a complete financial statement information, (3) the financial statements are expressed in dollars, and (4) have publish financial statements. Data analysis was conducted using data polled cross-section that includes 37 property companies, real estate and building construction and financial statement. Earnings management is measured by working capital accruals, measured by an index voluntary disclosure, and information asymmetry measured by abnormal returns. Hypothesis testing is done using path analysis. The result provide empirical evidence that: (1) earnings management does not affect the information asymmetry, (2) disclosure and significant negative effect of the informationasymmetry, (3) the total effect of earnings management and disclosure of the information asymmetry is at 78%.
Diagnoser with Hybrid Structure for Fault Diagnosis of a Class of Hybrid Dynamic Systems

In this paper, we propose a new model-based approach for the fault diagnosis of hybrid dynamic systems (HDS), in particular discretely controlled continuous system (DCCS). The goal is to construct a diagnosis module (called diagnoser) able to diagnose parametric and discrete faults. Parametric faults are characterized by abnormal changes in some system parameters whereas discrete faults are attributed to undesired changes in the system configuration. This approach is based on a diagnoser with hybrid structure composed of three parts: discrete diagnoser, continuous diagnoser and coordinator. The discrete diagnoser is modelled as a discrete time hybrid automata model. It is used to detect and to isolate the discrete faults. The continuous diagnoser is based on a set of residuals comparing the measured and estimated values of each continuous variable in order to diagnose the parametric faults. The coordinator combines the discrete and continuous decisions of the two diagnoser sin order to diagnose faults requiring the interaction between both diagnosers.
The study of the generate and screening of vehicle license plate's potential region queue based on image

With the microprocessor as its core, the license plate automatic recognition system is a highly intelligent electronic system based on technologies such as image processing and pattern recognition. The goal of license location algorithm is to accurately identify the position of the license on a motor vehicle license image. The license can appear anywhere on the image with different degrees of tilt and distortion, or it may be stained. Therefore, the algorithm has to take these situations into consideration.
Using an Ant Colony approach for Solving capacitated Vehicle Routing Problem with time Windows

In this paper, a capacitated vehicle routing problem with time windows (CVRPTW) is presented. In this work, a new idea for calculating the heuristic value to improve the performance of ant colony algorithms when solving capacitated vehicle routing problems with hard time windows is proposed. The performance of the model and the heuristic approach are evaluated by Solomon’s VRPTW benchmark problems. The results show that in 14 problem instances, our solutions are better than the best solutions reported for the VRPTW by other researchers in both total traveling distance and number of used vehicles. Our solutions superiority over the best solutions published in the literature are in instances R1, R2 and Particularly RC2 such a way that the average number of used vehicles are considerably less.
Joint Signal Detection and Classification Based on First-Order Cyclostationarity For Cognitive Radios

The sensing of the radio frequency environment has important commercial and military applications and is fundamental to the concept of cognitive radio. The detection and classification of low signal-to-noise ratio signals with relaxed a priori information on their parameters are essential prerequisites to the demodulation of an intercepted signal. This paper proposes an algorithm based on first-order cyclostationarity for the joint detection and classification of frequency shift keying (FSK) and amplitude-modulated (AM) signals. A theoretical analysis of the algorithm performance is also presented and the results compared against a performance benchmark based on the use of limited assumed a priori information on signal parameters at the receive-side. The proposed algorithm has the advantage that it avoids the need for carrier and timing recovery and the estimation of signal and noise powers.
Guidelines for revascularization: The evidence base matures

[first paragraph of article] Myocardial revascularization procedures continue to represent important treatment options for patients with acute and chronic coronary artery disease (CAD) and also represent a major source of health care expenditures . For the past decade, the indications for revascularization in patients with chronic CAD, and the indications for surgical versus percutaneous revascularization, have been the subject of considerable discussion, debate, and controversy. The guidelines from the American College of Cardiology Foundation/American Heart Association (ACCF/AHA) and the European Society of Cardiology / European Association for Cardiothoracic S (ESC/EACTS) have made major inroads in resolving these issues and have provided the standards for care for interventional cardiologists, surgeons, and the physicians who refer patients for these procedures. The transatlantic guidelines have also been remarkably concordant in their overall recommendations.
Capturing Complementary Information via Reversed Filter Bank and Parallel Implementation with MFCC for Improved Text-Independent Speaker Identification

A state of the art speaker identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, mel-frequency cepstral coefficients (MFCC) modeled on the human auditory system have been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This work proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature improves performance baseline of MFCC based system. The proposition is validated by experiments conducted on two different kinds of databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with two different classifier paradigms, namely Gaussian Mixture Models (GMM) and Polynomial Classifier (PC) and for various model orders
The Star Formation Histories of Galaxies in Distant Clusters

We present a detailed analysis of the spectroscopic catalog of galaxies in 10 distant clusters from Dressler et al. We investigate the nature of the different spectral classes defined by Dressler et al., including star-forming, poststarburst, and passive galaxy populations, and reproduce their basic properties using our spectral synthesis model. We attempt to identify the evolutionary pathways between the various spectral classes in order to search for the progenitors of the numerous poststarburst galaxies. The comparison of the spectra of the distant galaxy populations with samples drawn from the local universe leads us to identify a significant population of dust-enshrouded starburst galaxies, showing both strong Balmer absorption and relatively modest [O II] emission, that we believe are the most likely progenitors of the poststarburst population. We present the differences between the field and cluster galaxies at z=0.4-0.5. We then compare the spectral and morphological properties of the distant cluster galaxies, exploring the connection between the quenching of star formation inferred from the spectra and the strong evolution of the S0 population discussed by Dressler et al. We conclude that either two different timescales and/or two different physical processes are responsible for the spectral and morphological transformation.