Miracle-dz/UniFAR-FTUs huggingface dataset:
ML performance bounds of turbo and LDPC codes

To date there is no practical means to evaluate the true word error probability (WEP) of a given turbo or LDPC code because typical decoders cannot achieve the performance of ML decoding. In this paper, we propose a viable methodology to establish tight bounds on the ML-decoding WEP for these codes through empirical simulation. Our framework centers on the efficient use of multiple-output decoding induced by receiver-generated side information, or gift. At low WEP regime, perturbed decoding can give tight bounds. In high WEP regime, due to the prohibitive complexity of perturbed decoding, we instead pursue other type of gifts. The effectiveness of various types of gifts is investigated in detail. We observe that the complexity of gift-assisted decoding is dominated by the effort to identify partial gifts that can then be further extended. Using bit values as gifts and an algorithm that maximizes the efficiency of identifying valid partial gifts, the ML bounds of turbo and LDPC codes are evaluated. At low WEP regime, our approach successfully yields the ML performance for these codes. Their WEP are shown to be very far from the sphere packing bound. At higher WEP regime, our results indicate that best-performing message-passing decoders underperform an ML decoder by at least 0.2 dB.
Influence of Parent–Child Interaction on Socio-emotional Development of Children With Perinatal Risks

The article is devoted to the study of the influence of peculiarities of child–parent interaction on the early socio-emotional development of children with perinatal risks. This is a relevant area since, first of all, there is an increasing number of children with such risks (especially, with the risk of autism spectrum disorders (ASD) andattention deficit hyperactivity disorder (ADHD)). Moreover, it is parents who can be most instrumental in the successful development, adaptation and socialization of children. The article examines Russian and foreign approaches to the definition of socio-emotional development, stages, and levels of its development. It also analyses the data obtained in the course of research of peculiarities of parent–child interaction with the help of video observation (PCI) that was conducted using the coding scales (SocialinteractionratingScale). In order to assess cognitive, speech, socio-emotional development, and adaptive behavior, «Bayley Scales of Infant Development Third Edition» were used. The data of eight children of the control group (average age 5–8months) and eight children of the experimental group with family risk of atypical development (older sibling or parent have a confirmed diagnosis of ASD and/or ADHD) (average age 2–66 months) were analyzed. Two-way analysis of variance showed that nondirective behavior of parents can lead to a more successful developmentof socio-emotional skills of children with the family risk of ASD and ADHD, namely, the skill ‘social setting’. The study is a pilot but demonstrates a potential for further research in this area. Keywords: child–parent interaction, video observation, young children, family risk, socio-emotional development
NEW RESULTS ON THE IDENTIFICATION OF INTERVAL PREDICTOR MODELS

In this paper, the problem of identifying a predictor model for an unknown system is studied. Instead of standard models returning a prediction value as output, we consider models returning prediction intervals. Identification is performed according to some optimality criteria, and, thanks to this approach, we are able to provide, independently of the data generation mechanism, an exact evaluation of the reliability (i.e. the probability of containing the actual true system output value) of the prediction intervals returned by the identified models. This is in contrast to standard identification where strong assumptions on the system generating data are usually required.
Assimilation of T‐TREC‐retrieved wind data with WRF 3DVAR for the short‐term forecasting of typhoon Meranti (2010) near landfall

An extended Tracking Radar Echo by Correlation (TREC) technique, called T‐TREC technique, has been developed recently to retrieve horizontal circulations within tropical cyclones (TCs) from single Doppler radar reflectivity (Z) and radial velocity (Vr, when available) data. This study explores, for the first time, the assimilation of T‐TREC‐retrieved winds for a landfalling typhoon, Meranti (2010), into a convection‐resolving model, the WRF (Weather Research and Forecasting). The T‐TREC winds or the original Vr data from a single coastal Doppler radar are assimilated at the single time using the WRF three‐dimensional variational (3DVAR), at 8, 6, 4, and 2 h before the landfall of typhoon Meranti. In general, assimilating T‐TREC winds results in better structure and intensity analysis of Meranti than directly assimilating Vr data. The subsequent forecasts for the track, intensity, structure and precipitation are also better, although the differences becomes smaller as the Vr data coverage improves when the typhoon gets closer to the radar. The ability of the T‐TREC retrieval in capturing more accurate and complete vortex circulations in the inner‐core region of TC is believed to be the primary reason for its superior performance over direct assimilation of Vr data; for the latter, the data coverage is much smaller when the TC is far away and the cross‐beam wind component is difficult to analyze accurately with 3DVAR method.
Five-level inverter scheme for an induction motor drive with simultaneous elimination of common-mode voltage and DC-link capacitor voltage imbalance

The simultaneous elimination of common-mode voltage and DC-link capacitor voltage imbalance is achieved in a five-level inverter scheme for an induction motor drive throughout its operating range. A dual five-level inverter-fed open-end-winding induction motor structure is used for the proposed drive. Initially, the operating limitations of achieving this dual task for the five-level inverter configuration are investigated for a single DC power supply. Subsequently, a switching strategy for a five-level inverter topology with two DC power supplies is proposed to achieve the dual task over the entire speed range of the drive. The proposed drive offers a simple power-bus structure with more redundant switching combinations for inverter voltage vectors, and requires a lower voltage-blocking capacity of the power devices as compared with the conventional single five-level inverter-fed drive. As only the availability of redundant switching combinations for inverter voltage vectors is exploited, the dual task is achieved without disturbing the fundamental component of the inverter output voltage and the scheme does not need any extra control circuit hardware. Experimental verification of the proposed scheme is done on a 1.5 kW induction motor drive in the linear as well as overmodulation range.
Framing curriculum development in social work education about social enterprises: a scoping literature review

ABSTRACT Social enterprises are emerging globally as an organizational form that can support social service nonprofits to meet sustainability and financial resource goals, along with supporting vulnerable and marginalized social groups. This scoping literature review provides a broad content and thematic analysis of current literature on social enterprises with the intention of highlighting areas for curriculum development related to this subject matter. Based on a review of 641 academic journal abstracts, it is apparent that social enterprises are emerging as a dominant organizational entity for addressing persistent social, economic, and environmental challenges in many different countries. Key themes for curriculum development relate to content associated with the political-economic environment for which social enterprises have emerged, business and marketing strategies, internal organizational dynamics (such as leadership strategies), along with an assessment of the general possible impact that social enterprises can have on vulnerable social groups. Advancement of curriculum related to social enterprises—with emphasis on business development and leadership—is an important and necessary component to effectively prepare social work students for contemporary social work practice and leadership.
Direction Sensing RFID Reader for Mobile Robot Navigation

A self-contained direction sensing radio frequency identification (RFID) reader is developed employing a dual-directional antenna for automated target acquisition and docking of a mobile robot in indoor environments. The dual-directional antenna estimates the direction of arrival (DOA) of signals from a transponder by using the ratio of the received signal strengths between two adjacent antennas. This enables the robot to continuously monitor the changes in transponder directions and ensures reliable docking guidance to the target transponder. One of the technical challenges associated with this RFID direction finding is to sustain the accuracy of the estimated DOA that varies according to environmental conditions. It is often the case that the robot loses its way to the target in a cluttered environment. To cope with this problem, the direction correction algorithm is proposed to triangulate the location of the transponder with the most recent three DOA estimates. Theoretical simulation results verify the reliability of the proposed algorithm that quantifies the potential error in the DOA estimation. Using the algorithm, we validate mobile robot docking to an RFID transponder in an office environment occupied by obstacles.
Glycated Hemoglobin Value for Fasting Plasma Glucose of 126 mg/dL in Korean: The 2011 Korea National Health and Nutrition Examination Survey

We aimed to estimate the cutoff value of glycated hemoglobin (HbA1c, A1c) for fasting plasma glucose (FPG) of 126 mg/dL in the Korean adult population, using the 2011 Korea National Health and Nutrition Examination Survey. A total of 5,421 participants without a history of diabetes and over 19 years of age were included in the analysis. A point-wise area under the receiver operating characteristic curve was used to estimate the optimal A1c cutoff value. A1c threshold of 6.1% produced the highest sum of sensitivity (85.2%) and specificity (90.5%) for FPG of 126 mg/dL (area under the curve, 0.941, P<0.001). A1c of 6.5% produced a sensitivity of 67.7% and specificity of 98.0% for FPG of 126 mg/dL. Considering A1c as one of three criteria for the diagnosis of diabetes and the specificity of an A1c cutoff of 6.5%, the current diagnostic criteria of A1c≥6.5% might be acceptable in the Korean adult population.
is a senior economist at the Economic Development Institute of the World Bank and Sanjay Pradhan is a Manager of the Public Sector Board of the Eastern Europe and Central Asia Region of the World Bank

Introduction In recent years, there has been heightened concern about poor fiscal outcomes in both developed and developing countries. Governments have had to reduce aggregate public spending and deficits due to serious macroeconomic imbalances. At the same time, governments have had to focus attention on the composition of spending in deciding where to cut expenditures, i.e. allocative efficiency. Moreover, many have recognized the need to address often serious problems with technical inefficiency in the use of budgeted resources (World Bank 1992). But while policy makers and researchers have recognized these three basic problems, for the most part they have not addressed them in an integrated manner. In particular, the interrelationships among these problems have not been systematically examined. Macroeconomists have focussed the control of aggregate spending and the deficit. Experts in public administration have worked predominantly on improving technical efficiency. And, fiscal economists have concentrated on issues of allocative efficiency. 1 Further, much of the work on these issues has not dealt with the underlying institutional arrangements which affect the outcomes. Indeed recently, there has been a flurry of work on the role of institutions in influencing aggregate fiscal discipline (Alesina et al, 1996; Von Hagen, 1992). But this work has not addressed the implications of these and other institutional arrangements on allocative and technical efficiency. The relative lack of attention to coherence and institutional underpinnings stems in part from the absence of an analytical framework within which to evaluate a public expenditure management system. In this paper, we present such a framework. Specifically, we examine how institutional arrangements (i.e., the rules, norms, procedures) governing the budget process affect incentives governing the allocation and use of resources. Using theories from the new institutional economics to guide us, we identify key theoretical problems that underpin any public expenditure management system. We then construct a set of generic institutional arrangements each of which can potentially address one or more of the problems and link with each arrangement relevant accountability and/or transparency enhancing mechanisms. We categorize these arrangements and mechanisms according to their relative impact on three levels or categories of expenditure outcomes—the 3 aggregate level of spending and the deficit, the composition of expenditures, and the technical efficiency in the use of budgeted resources. On the basis of this categorization, we are able to develop a parsimonious measure of the potential effectiveness of a system with respect to each of the three …
Cnidarians as a Source of New Marine Bioactive Compounds—An Overview of the Last Decade and Future Steps for Bioprospecting

Marine invertebrates are rich sources of bioactive compounds and their biotechnological potential attracts scientific and economic interest worldwide. Although sponges are the foremost providers of marine bioactive compounds, cnidarians are also being studied with promising results. This diverse group of marine invertebrates includes over 11,000 species, 7500 of them belonging to the class Anthozoa. We present an overview of some of the most promising marine bioactive compounds from a therapeutic point of view isolated from cnidarians in the first decade of the 21st century. Anthozoan orders Alcyonacea and Gorgonacea exhibit by far the highest number of species yielding promising compounds. Antitumor activity has been the major area of interest in the screening of cnidarian compounds, the most promising ones being terpenoids (monoterpenoids, diterpenoids, sesquiterpenoids). We also discuss the future of bioprospecting for new marine bioactive compounds produced by cnidarians.
Maximal compact tori in the Hamiltonian group of 4-dimensional symplectic manifolds

We prove that the group of Hamiltonian automorphisms of a symplectic $4$-manifold $(M,\omega)$, Ham$(M,\omega)$, contains only finitely many conjugacy classes of maximal compact tori with respect to the action of the full symplectomorphism group Symp$(M,\omega)$. We also consider the set of conjugacy classes of\/ $2$-tori in Ham$(M,\omega)$ with respect to Hamiltonian conjugation and show that its finiteness is equivalent to the finiteness of the symplectic mapping class group $\pi_{0}$(Symp$(M,\omega)$). Finally, we extend to rational and ruled manifolds a result of Kedra which asserts that if $(M,\omega)$ is a simply connected symplectic $4$-manifold with $b_{2}\geq 3$, and if $(\widetilde{M},\widetilde{\omega}_{\delta})$ denotes a symplectic blow-up of $(M,\omega)$ of small enough capacity $\delta$, then the rational cohomology algebra of the Hamiltonian group Ham($\widetilde{M},\widetilde{\omega}_{\delta})$ is not finitely generated. Our results are based on the fact that in a symplectic $4$-manifold endowed with any tamed almost structure $J$, exceptional classes of minimal symplectic area are $J$-indecomposable.
Bayesian inference of exponential random graph models under measurement errors

While the impact of measurement errors inherent in network data has been widely recognized, relatively little work has been done to solve the problem mainly due to the complex dependence nature of network data. In this paper, we propose a Bayesian inference framework for summary statistics of the true underlying network, based on the network observed with measurement errors. To the best of our knowledge, this paper is the first to deal with measurement errors in the network data analysis in a Bayesian framework. We construct a Gibbs sampler to iteratively draw underlying true networks and model parameters. We incorporate the exponential random graph model to serve as the likelihood function, and use the exchange algorithm to draw model parameters. Simulation results show that using our inference framework, the impact of measurement errors has been reduced significantly.
Learning on the Job: Optimal Instruction for Crowdsourcing

A large body of crowdsourcing research focuses on using techniques from artificial intelligence to improve estimates of latent answers to questions, assuming fixed (latent) worker quality. Recently, researchers have begun to investigate how best to actively improve worker quality through instruction (Basu & Christensen, 2013; Singla et al., 2014). However, none of the existing work considers the fundamental tradeoff between providing instruction and getting actual work done. In this work, we present a reinforcement learning agent capable of optimizing the instruction it provides, by learning the effectiveness of its teaching actions, the quality of the worker population, and the amount of work output it can expect from individual workers. Evaluations on synthetic data show that our agent learns adaptive instruction policies that significantly outperform common baseline strategies such as providing a tutorial of fixed length.
Simple Landmark Localization on a Three-Layer Mobile Robot Architecture

This paper describes a mobile robot system designed to explore and map an area such as is encountered in urban search and rescue simulations. The robot uses homogeneous artificial landmarks for localization as it builds metric and topological maps, determining landmark distance and bearing with groundplane calculations from a single camera and using Kalman filtering techniques to perform localization. A three-layer robot control architecture is discussed which combines the features of a reactive navigation system and a symbolic planner as well as a middle layer which consists of a set of informationgathering and motor schema. When implemented on a Magellan II mobile robot, the localization technique and the three-layer architecture correctly localized the robot while exploring and mapping.
A Tool Based on DL for UML Model Consistency Checking

Automated consistency checking of UML models becomes necessary as models grow in size and complexity. Since the UML metamodel does not enforce model consistency, there are no fixed guidelines on how to approach the consistency problem. Current solutions are generally partial. The translation of the metamodel and the user designed model into Description Logics has proved to provide a solution in detecting a large set of inconsistencies. In order to make this solution available to system designers, we have implemented MCC+, a UML model consistency checker, built as a plug-in for Poseidon for UML, and relying on Jena as a reasoning engine. Compared to other approaches, we propose a usable and scalable solution, interoperable with a known modeling tool. We show the application of MCC+ to a real world large example of a meshing tool.
Synthesis and in vivo magnetic resonance imaging evaluation of biocompatible branched copolymer nanocontrast agents

Branched copolymer nanoparticles (Dh =20–35 nm) possessing 1,4,7, 10-tetraazacyclododecane-N,N′,N″,N‴-tetraacetic acid macrocycles within their cores have been synthesized and applied as magnetic resonance imaging (MRI) nanosized contrast agents in vivo. These nanoparticles have been generated from novel functional monomers via reversible addition–fragmentation chain transfer polymerization. The process is very robust and synthetically straightforward. Chelation with gadolinium and preliminary in vivo experiments have demonstrated promising characteristics as MRI contrast agents with prolonged blood retention time, good biocompatibility, and an intravascular distribution. The ability of these nanoparticles to perfuse and passively target tumor cells through the enhanced permeability and retention effect is also demonstrated. These novel highly functional nanoparticle platforms have succinimidyl ester-activated benzoate functionalities within their corona, which make them suitable for future peptide conjugation and subsequent active cell-targeted MRI or the conjugation of fluorophores for bimodal imaging. We have also demonstrated that these branched copolymer nanoparticles are able to noncovalently encapsulate hydrophobic guest molecules, which could allow simultaneous bioimaging and drug delivery.
WOODFIBER-PLASTIC COMPOSITES IN THE UNITED STATES-HISTORY AND CURRENT AND FUTURE MARKETS

Research on wood and natural fiber-plasticcomposites has spanned several decades. However, there was relatively little market activity in the United States outside of the automotive industry prior to the last 5 years. Recently, however, the U.S. wood-plasticcomposites industry has grown tremendously. Although its total marketsize is small relativetothe traditional wood composites industry, the U.S. wood-plasticcomposites industry isgrowingquicklyand hasattracted the interestof both the plastics and the forest products industries. Researchers, raw material suppliers, equipment manufacturers, and end product manufacturers often worktogetherto develop, produce, and market thesecomposites.
Polar fusion technique analysis for evaluating the performances of image fusion of thermal and visual images for human face recognition

This paper presents a comparative study of two different methods, which are based on fusion and polar transformation of visual and thermal images. Here, investigation is done to handle the challenges of face recognition, which include pose variations, changes in facial expression, partial occlusions, variations in illumination, rotation through different angles, change in scale etc. To overcome these obstacles we have implemented and thoroughly examined two different fusion techniques through rigorous experimentation. In the first method log-polar transformation is applied to the fused images obtained after fusion of visual and thermal images whereas in second method fusion is applied on log-polar transformed individual visual and thermal images. After this step, which is thus obtained in one form or another, Principal Component Analysis (PCA) is applied to reduce dimension of the fused images. Log-polar transformed images are capable of handling complicacies introduced by scaling and rotation. The main objective of employing fusion is to produce a fused image that provides more detailed and reliable information, which is capable to overcome the drawbacks present in the individual visual and thermal face images. Finally, those reduced fused images are classified using a multilayer perceptron neural network. The database used for the experiments conducted here is Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal and visual face images. The second method has shown better performance, which is 95.71% (maximum) and on an average 93.81% as correct recognition rate.