Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian networks and complex survey sampling from finite populations

We propose a novel methodology based on the concept of Bayesian network (BN, see Cowell et al., 1999) for the estimation of a joint probability distribution of a set of categorical variables when samples are drawn according to complex survey designs. Note that, restricting ourselves to categorical variables, the previous aim corresponds to estimation of a contingency table, a very frequent problem in Offc ial Statistics. BNs are graphical devices largely used in many different scientifc contexts, such as artifcial intelligence and multivariate statistics (Neapolitan, 2004). However, when estimating and using BNs, observations have always been considered as i.i. d. generations from a suitable joint distribution function. Up to now, BNs have never been defned and applied when sampling from fnite populations. This paper shows that BNs can be easily adapted to the context of fnite survey sampling via the defnition of a suitable additional variable, in the following denoted with SD, representing the survey design. Hence, SD will be a categorical variable with as many states as the different inclusion probabilities of frst order. The BN representation allows the def nition of a much larger class of estimators, of the model assisted type (see Sarndal ̈ et al., 1992). Also, the possibility to use poststratifcation methods and, in general, integration of different surveys is illustrated.
Introduction to the special issue on eye gaze in intelligent human-machine interaction

Given the recent advances in eye tracking technology and the availability of nonintrusive and high-performance eye tracking devices, there has never been a better time to explore new opportunities to incorporate eye gaze in intelligent and natural human-machine communication. In this special issue, we present six articles that cover various aspects of eye gaze in human-machine interaction, including applications of gaze tracking in human-machine interaction, techniques that recognize gaze gestures and render gaze behaviors, and the analysis of gaze behaviors in social interactions.
Quantitative Proteomic and Genetic Analyses of the Schizophrenia Susceptibility Factor Dysbindin Identify Novel Roles of the Biogenesis of Lysosome-Related Organelles Complex 1

The Biogenesis of Lysosome-Related Organelles Complex 1 (BLOC-1) is a protein complex containing the schizophrenia susceptibility factor dysbindin, which is encoded by the gene DTNBP1. However, mechanisms engaged by dysbindin defining schizophrenia susceptibility pathways have not been quantitatively elucidated. Here, we discovered prevalent and novel cellular roles of the BLOC-1 complex in neuronal cells by performing large-scale Stable Isotopic Labeling of Cells in Culture (SILAC) quantitative proteomics combined with genetic analyses in dysbindin-null mice (Mus musculus) and the genome of schizophrenia patients. We identified 24 proteins that associate with the BLOC-1 complex, many of which were altered in content/distribution in cells or tissues deficient in BLOC-1. New findings include BLOC-1 interactions with the COG complex, a Golgi apparatus tether, and antioxidant enzymes peroxiredoxins 1–2. Importantly, loci encoding eight of the 24 proteins are affected by genomic copy number variation in schizophrenia patients. Thus, our quantitative proteomic studies expand the functional repertoire of the BLOC-1 complex and provide insight into putative molecular pathways of schizophrenia susceptibility.
An Updated Strategy for Designing Non-Fullerene Acceptors by the Lowest Singlet and Triplet States Excitation: Influence of Periodical Substitution from O, S, and Se to Te for BAE Derivatives

When one is trying to maintain original advantageous properties of molecule without increasing the difficulty of synthesis and processing, simultaneously, adding more predictable properties is a preferred choice for designing promising molecules. Here, we report the photovoltaic performance of bistricyclic aromatic enes (BAE) derivative acceptors as a function of heteroatom substitutions (O, S, Se, Te), and the range they can maintain. Beyond that, by combining singlet–triplet exciton conversion with singlet fission (SF), an additional perspective to characterize molecules performance is predicted by employing T1-excitation. Theoretical calculation results showed that for small molecules (BAEs), heavy atom substitution of the same group could increase conformation stability, electron acceptability, and spin–orbit coupling. After expansion of the molecular size (DPP-BAE-DPP), the difference in molecular properties is mainly due to the conformation type for singlet states excitation. For triplet states exci.
Role Recognition in Radio Programs using Social Affiliation Networks and Mixtures of Discrete Distributions: an Approach Inspired by Social Cognition

This paper presents an approach for the recognition of the roles played by speakers participating in radio programs. The approach is inspired by social cognition, i.e. by the way humans make sense of people they do not know, and it includes unsupervised speaker clustering performed with Hidden Markov Models, Social Network Analysis and Mixtures of Bernoulli and Multinomial Distributions. The experiments are performed over two corpora of radio programs for a total of around 45 hours of material. The results show that more than 80 percent of the data time can be labeled correctly in terms of role.
Metagenomic Analysis of Antibiotic Resistance Genes in Dairy Cow Feces following Therapeutic Administration of Third Generation Cephalosporin

Although dairy manure is widely applied to land, it is relatively understudied compared to other livestock as a potential source of antibiotic resistance genes (ARGs) to the environment and ultimately to human pathogens. Ceftiofur, the most widely used antibiotic used in U.S. dairy cows, is a 3rd generation cephalosporin, a critically important class of antibiotics to human health. The objective of this study was to evaluate the effect of typical ceftiofur antibiotic treatment on the prevalence of ARGs in the fecal microbiome of dairy cows using a metagenomics approach. β-lactam ARGs were found to be elevated in feces from Holstein cows administered ceftiofur (n = 3) relative to control cows (n = 3). However, total numbers of ARGs across all classes were not measurably affected by ceftiofur treatment, likely because of dominance of unaffected tetracycline ARGs in the metagenomics libraries. Functional analysis via MG-RAST further revealed that ceftiofur treatment resulted in increases in gene sequences associated with “phages, prophages, transposable elements, and plasmids”, suggesting that this treatment also enriched the ability to horizontally transfer ARGs. Additional functional shifts were noted with ceftiofur treatment (e.g., increase in genes associated with stress, chemotaxis, and resistance to toxic compounds; decrease in genes associated with metabolism of aromatic compounds and cell division and cell cycle), along with measureable taxonomic shifts (increase in Bacterioidia and decrease in Actinobacteria). This study demonstrates that ceftiofur has a broad, measureable and immediate effect on the cow fecal metagenome. Given the importance of 3rd generation cephalospirins to human medicine, their continued use in dairy cattle should be carefully considered and waste treatment strategies to slow ARG dissemination from dairy cattle manure should be explored.
Discrete time domain analysis and optimal design of stationary frame AC current controllers with active damped LCL Filter for high power applications

Due to the large variety of renewable power sources, power electronics play an important role in energy conversion. Different power converter topologies are used to interface distributed power generation systems (DPGS) with the utility network. Introduction of power electronics for DPGS provide several advantages such as energy optimal operation by employing a control algorithm to extract the maximum available power. In addition, load control, reduced noise, controllable active and reactive power and improved power quality. These achievements are further improved by digital control systems. The analysis presented in this paper shows the relations of how the stability margins and the transient response criteria are related to the sampling frequency, computational delay and controller gains. The procedure followed can be applied to any filter order with any number of samples of control delay at any sampling frequency. This gives a straightforward method for optimal tuning of the stationary frame AC current controllers with the required stability margins and transient response characteristics. The concluded assumptions were simulated & verified through Matlab/Simulink.
The polynomial solvability of selected bicriteria scheduling problems on parallel machines with equal length jobs and release dates

We consider bicriteria scheduling problems involving several classical well-known scheduling objectives on parallel, identical machines with job release dates. The jobs are assumed to have equal processing times. Our bicriteria treatment of these problems includes lexicographic optimization, minimization of a composite linear function, generation of schedules on the efficient frontier and the generation of all Pareto optimal solutions. Using the framework provided by the dynamic program of Baptiste (2000), we show the polynomial solvability for several bicriteria problems when the number of machines is given. We also present algorithms that extend the linear programming approach of Brucker and Kravchenko (2008) and whose complexities are polynomial in the number of jobs and independent of the number of machines. The complexity status of the bicriteria problems considered in this paper was previously unknown.
Oral administration of Aloe vera gel, anti-microbial and anti-inflammatory herbal remedy, stimulates cell-mediated immunity and antibody production in a mouse model

Introduction Aloe vera (L.) Burm. f. (Aloe barbadensis Mill) Liliaceae, succulent plant native to northern Africa, is presently cultivated in many regions of the world. Traditionally, its inner part of parenchyma, which contains aloe gel, was used for the treatment of minor wounds, inflammatory skin disorders, thermal and radiation burns and to alleviate chronic osteoarthritis pain. It also possesses some antimicrobial activity. Now, aloe gel is also increasingly consumed as a dietary supplement. Some data suggest its immunomodulatory properties. The aim of the study The aim of the study was to evaluate the influence of orally administered aloe gel on some parameters of cellular and humoral immunity viz. mitogen-induced proliferation of splenic lymphocytes and their chemokinetic activity, and anti-sheep red blood cells (SRBC) antibody production in Balb/c mice. Results Daily treatment of mice for 14 and 21 days with 50 µl or 150 µl of aloe gel dose resulted in enhanced chemokinetic activity and stronger response of their splenic lymphocytes to mitogen PHA and enhancement of anti-SRBC antibody production.
Opportunistic relaying vs. selective cooperation: analyzing the occurrence-conditioned outage capacity

Opportunistic Relaying (OR) and Selection Decode-and-Forward (SDF) cooperation protocols can both substantially improve the performance of wireless networks but fundamentally differ in utilized redundancy, relays, and channel knowledge. To analyze when SDF or OR improves error and data rate, we (1) derive their general outage probability and capacity for arbitrary relay configurations, (2) systematically benchmark both approaches in two-hop configurations, (3) study how often beneficial configurations occur in large networks, and, finally, condition our capacity results by this occurrence probability. Our results clearly show that OR maximizes the outage capacity at high acceptable error rate while SDF succeeds if a low error rate is required. SDF performs best if even the relays can cooperate among themselves, supported frequently in networks with more than three neighbors. Consequently, cooperating relays, adapting between OR and SDF, and joining these two approaches should be the focus of future protocol design. To this end, our paper provides a theoretical basis, adaptation rules, and design guidelines.
A model of knowledge‐sharing motivation

In this article, I present a model of knowledge-sharing motivation based on a combination of the theory of planned behavior (TPB) and self-determination theory (SDT), along with a review of research supporting the model and suggestions for future research and methodologies to study knowledgesharing behavior. I also give suggestions for designing five important human resource management (HRM) practices, including staffing, job design, performance and compensation systems, managerial styles, and training. © 2009 Wiley Periodicals, Inc.
Image Distribution Model Based Iterative Learning Control for Combustion Processes

In combustion processes, the goals of the operation are to keep the combustor in the optimal condition and alleviate instabilities and its severe consequence. The conventional control systems based on the oxygen content usually have responses with certain delay. Most flames are turbulent and are affected by several unmeasured disturbances and continuous variation due to several types of fuels burnt simultaneously. This paper presents a closed-loop combustion control algorithm for a combustor using the distribution control theory developed recently. Using the distribution data obtained by a pilot-scale experiment, the equivalent selective B-spline wavelet approximation is proposed to construct a probability distribution function model so that the resulting output density distribution curve matches the desired distribution. In the distribution control design, an iterative learning PDF control strategy is developed. It ensures the output PDF to follow the desired distribution. The proposed method is applied to a pilot scaled combustion control system to demonstrate its effectiveness.
A high efficiency transformerless PV grid-connected inverter with leakage current suppression

This paper presents a new diode free freewheeling and common-mode voltage (CMV) clamping branches for single phase transformerless grid connected photovoltaic (PV) inverter for complete leakage current elimination and low conduction losses. In the past, various isolation techniques have been proposed for leakage current elimination in transformerless PV inverters. However, galvanic isolation only cannot completely eliminate leakage current due to that a resonant path is created by the switch junction capacitors, which also generate leakage current. The proposed freewheeling branch consists of four MOSFETs along with a clamping branch, which consists of two MOSFETs and a capacitor divider. The divider is connected to the DC side of the converter to keep constant CMV in the freewheeling path. As a result, the improved CMV clamping has been achieved for complete leakage current elimination. The unipolar sinusoidal pulse width modulation (SPWM) technique and modified HERIC topology with AC-decoupling for galvanic isolation is adopted for lower conduction losses. The proposed topology consists of only MOSFET in the freewheeling and clamping path which provides lower conduction losses compared with diode based topologies. The performances of the proposed topology in terms of common mode characteristics, leakage current, total harmonic distortion and conversion efficiency are analyzed and compared with H5, H6, HERIC and HBZBR topologies. The detail analyses are performed using MATLAB/Simulink and PSIM.
Image Contrast Enhancement Using Discrete Dual Hahn Moments

The main objective of this paper is to develop a simple technique for contrast enhancement of monochrome and color images using Discrete Dual Hahn (DDH) moments. The basic idea of our approach is to measure a local contrast at each band of a DDH moment matrix and use it to modify them. These modified moments are used to construct the enhanced image by taking the inverse DDH moment transform. For color images only luminance image was enhanced using the above procedure. Hence, other components are not changed. We compute image entropy, coefficient of information content and universal quality index for verifying the results with alpha rooting, Kratchouk moment and Tchebichef moment based approaches.
Trust in PRIME

The PRIME project develops privacy enhancing identity management systems that allow users in various application areas such as e-commerce to regain control over their personal spheres. This paper introduces the PRIME technical architecture that also includes special trust-enhancing mechanisms, and shows how PRIME technologies can enhance privacy and trust of e-shopping customers. It also discusses the socio-psychological factors and HCI aspects influencing the end user's trust in privacy enhancing identity management, and shows why HCI research, user studies, and socio-psychological research, are necessary efforts to accompany system design
A Comparative Study of Discourse Markers: The Case of three English Applied Linguistic Texts with their Farsi Translations

This research was an attempt to find the relationship between English discourse markers and their Farsi translations. It was conducted in order to find out whether DMs translations completely demonstrate source texts orientation and to what extent DMs translations are functionally appropriate compared to the original text? Six instruments were used. Three of them were the original English books and the other three were their translations. Ten pages from each original book were randomly selected. Then they were compared to their translations by the researcher and two translation teachers according to Farahzad's (1992) scale. The results of the study showed that there is a high degree of relationship between English DMs and their Persian counterparts; however, there is not a 1:1 translation about DMs. It can be also said that Persian translations are, functionally and almost totally, appropriate, compared to the original texts.
Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers

Despite the dramatic improvements achieved in building energy-efficient electronic devices, the amount of electricity consumed worldwide to power the global information technology infrastructure has grown tremendously in the past decade. In this paper, we propose algorithms to reduce energy consumption by data centers by considering the placement of virtual machines onto the servers in the data center intelligently. We formulate this problem as an integer programming problem, prove it is NP-hard, then explore two greedy approximation algorithms, minimum energy virtual machine (VM) scheduling algorithm (MinES) and minimum communication virtual machine scheduling algorithm (MinCS), to reduce the energy while satisfying the tenants' service level agreements. We examine the performance of these two algorithms in both small and large clusters using real data traces and synthetic workloads, and compare them to other alternatives. Our results demonstrate that MinES and MinCS yield scheduling that are within 4.3 to 6.1 percent energy consumption of the optimal solution while being computationally efficient.
Troubles with Bayesianism: An introduction to the psychological immune system

Correspondence Eric Mandelbaum, Philosophy Program, CUNY Graduate Center and Baruch College, 365 Fifth Avenue, Room 7113, New York, NY 10016. Email: emandelbaum@gc.cuny. edu A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and explain mental processes that best exemplify our ability to be rational. However, evidence from belief acquisition and change appears to show that we do not acquire and update information in a Bayesian way. Instead, the principles of belief acquisition and updating seem grounded in maintaining a psychological immune system rather than in approximating a Bayesian processor.
Roles of Tropical Indian-Pacific Oceans SSTs in the Interdecadal Variability of East Asian Summer Monsoon: A Modeling Study

This study investigates the roles of tropical Indian-Pacific oceans SSTs in the interdecadal variability of East Asian Summer Monsoon (EASM) during the second half of the twentieth century based on simulations from an atmospheric general circulation model, NCAR CAM3 (Community Atmospheric Model). These simulations are conducted by the observed 1950-2000 monthly SSTs in the tropical Indian-Pacific oceans, tropical Indian Ocean and tropical Pacific, independently. Results show that CAM3 is able to simulate the observed interdecadal weakening of EASM occurred in the mid-late 1970s when SSTs in tropical Indian-Pacific Oceans and tropical Pacific SSTs are determined, but to simulate the interdecadal strengthening of EASM when SSTs in the tropical Indian Ocean are determined. These results indicate that SST anomaly in the tropical Pacific plays a central role in the interdecadal weakening of EASM occurred in the mid-late of 1970s, while SST anomaly in the tropical Indian Ocean plays a converse role in it. As a background, the interdecadal variation of tropical Pacific SSTs has an important effect upon the interdecadal weakening of EASM.
A Global Survey of Software Development Practices

The worldwide boom in the use of information technology has spurred software development efforts around the globe. Our ongoing research program focuses on three aspects of the global development of software: (1) collection of quantitative data regarding current practice and performance in a variety of countries; (2) determination of the adoption of competing models of software development across countries, and (3) analysis of the impact of different development practices on performance. This paper presents the results of a survey of 104 software development projects primarily centered in India, Japan, Europe and the United States. Practice and performance are contrasted by region. Among other findings it appears from the data that Indian organizations are doing an admirable job of combining conventional best practices, such as specification and review, with more flexible techniques that should enable them to respond more effectively to customer demands. If such a trend is replicated across the broader population, it suggests the Indian software industry is likely to experience continued growth and success in future.
Low cost DOA estimation for wideband sources

This paper presents a temporal method for direction of arrival (DOA) estimation for wideband sources by using an antenna array. Existing DOA estimation algorithms treat the problem in frequency domain by decomposing the wide spectrum of these signals in several narrowband signals, and use a narrowband DOA estimation methods to solve the problem. These methods suffer from high computational complexity. This paper introduces a temporal method based on cross-correlation functions between sensors outputs. The estimation of the propagation delays is the key to find directions of arrival of wideband sources. The method has low cost complexity in terms of computations and sensors number. In this paper we describe the method and we do some comparative simulations to show the performance of the suggested method.