Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomised crossover study of the Flutter device and the active cycle of breathing technique in non-cystic fibrosis bronchiectasis

AUTHOR:e-mail address please Background: Airway clearance techniques are an important part of the routine care of patients with bronchiectasis. The use of the Flutter, a hand held pipe-like device causing oscillating positive expiratory pressure within the airways, has been proposed as an alternative to more conventional airway clearance techniques. Methods: A randomised crossover study was performed in 17 stable patients with non-cystic fibrosis bronchiectasis at home, in which 4 weeks of daily active cycle of breathing technique (ACBT) were compared with 4 weeks of daily physiotherapy with the Flutter device. Results: No significant differences between the two techniques were found. Median weekly sputum weights were similar with a median treatment difference of 7.64 g (p=0.77) and there was no evidence of treatment order or order interaction effects (p=0.70). Health status (Chronic Respiratory Disease Questionnaire) and ventilatory function did not change significantly during either treatment period. There was no significant change in peak expiratory flow rate or in breathlessness (Borg score) after individual physiotherapy sessions with either technique. A questionnaire indicated subjectively that patients preferred the Flutter (11/17) to ACBT for routine use. Conclusions: Daily use of the Flutter device in the home is as effective as ACBT in patients with non-cystic fibrosis bronchiectasis and has a high level of patient acceptability.
Blind channel identification and extraction of more sources than sensors

It is often admitted that a static with more inputs than outputs cannot be blindly identified, that is, identified only from the observation of its outputs, and without any a priori knowledge on the source statistics but their independence.By resorting to high-order statistics, it turns out that static MIMO systems with fewer outputs than inputs can be identified, as demonstrated in the present paper. The principle, already described in a recent theoretical paper, had not yet been applied to a concrete blind identification problem. Here, in order to demonstrate its feasibility, the procedure is detailed in the case of a 2-sensor 3-source mixture; a numerical algorithm is devised, that blindly identifies a 3-input 2-output mixture. Computer results show its behavior as a function of the data length when sources are QPSK-modulated signals, widely used in digital communications. Then another algorithm is proposed to extract the 3 sources from the 2 observations, once the mixture has been identified. Contrary to the first algorithm, this one assumes that the sources have a known discrete distribution. Computer experiments are run in the case of three BPSK sources in presence of Gaussian noise.
Fast face detection using boosted eigenfaces

This paper describes a new eigenface based face detection using boosted eigen features. Eigenfaces have long been used for face detection and recognition. The basic detection and recogniton system works by projecting the face images onto a feature space that spans significant variations among the training set. But the distance from the face space is not a reliable measure to classify faces from non-faces as some of the non-faces may also lie close to the face space. We propose to build a better classifier by boosting a set of weak classifiers built from the projections onto the eigen vectors of the face space. The proposed system provides significantly better performance compared to the distance measure. Also, we propose to improve the speed of detection in real images using FFT.
Cellular Nonlinear Network-Based Bio-Inspired Decentralized Control of Locomotion for Hexapod Robots

This article introduces a new approach to locomotion control in six-legged robots. The approach is inspired by the model of decentralized locomotion control in the stick insect introduced by one of the authors and makes use of second-order nonlinear systems to realize the neuron-like dynamics of the sub-units of the whole control system. Each of these sub-units controls the behavior of a leg and is coordinated with the others by means of local influences based on the leg status, revealed by contact sensors. The suitability of the approach has been shown by using cellular nonlinear networks (CNNs) to implement the leg controllers. Simulations of the CNN-based locomotion control demonstrate its robustness with respect to different initial conditions and the property of pattern recovery after the external blocking of a leg.
A Comparison of Fusion Rules for Cooperative Spectrum Sensing in Fading Channels

—This paper presents a simulation comparison of six fusion rules for cooperative spectrum sensing: Likelihood Ratio combining, soft Optimal Linear combining, soft Equal Weight combining, and hard decision combining using the OR, AND, and the Majority counting rules. Simulation results are presented via Receiver Operating Characteristic (ROC) curves for cooperative sensing using the abovementioned fusion rules for a cognitive radio system operating in AWGN, correlated/uncorrelated shadowing, and in channels featuring composite large-scale and small scale fading. Simulations results using a Lab generated DTV signal in frequency selective fading channels are also presented. This work is very relevant in light of the inclusion of cooperative sensing in the FCC rules for unlicensed operation in the TV bands.
Unsupervised Methods for Determining Object and Relation Synonyms on the Web

The task of identifying synonymous relations and objects, or synonym resolution, is critical for high-quality information extraction. This paper investigates synonym resolution in the context of unsupervised information extraction, where neither hand-tagged training examples nor domain knowledge is available. The paper presents a scalable, fully-implemented system that runs in O(KN log N) time in the number of extractions, N, and the maximum number of synonyms per word, K. The system, called RESOLVER, introduces a probabilistic relational model for predicting whether two strings are co-referential based on the similarity of the assertions containing them. On a set of two million assertions extracted from the Web, RESOLVER resolves objects with 78% precision and 68% recall, and resolves relations with 90% precision and 35% recall. Several variations of RESOLVER's probabilistic model are explored, and experiments demonstrate that under appropriate conditions these variations can improve F1 by 5%. An extension to the basic RESOLVER system allows it to handle polysemous names with 97% precision and 95% recall on a data set from the TREC corpus.
Role of Family, Neighbourhood and Peers in Development of Delinquent Behavior in Adolescents

All over the globe juvenile delinquency is a major issue. Even after lots of efforts to minimize it, it is increasing. Therefore, the review paper aims on looking at the basic causes of development of delinquent behavior in adolescents. Objectives of this study are, finding out what role family plays in development of adolescents’ delinquent behavior, what role neighborhood (local neighborhood or extra-local neighborhood) plays in development of delinquent behavior in adolescents, what role do peers play in development of delinquent behavior in adolescents and what role do economic factors and personal factors play in development of adolescents’ delinquent behavior. Researches from past 12 years (from 2004 till 2016), including 39 papers, relevant to the study have been selected on basis of the keywords of the study from different websites PubMed, WileyOnline Library and some other online sociology, criminology and community psychology journal websites. Type of studies included in this paper are quantitative, qualitative, case study, cross-sectional and longitudinal studies. Results indicated family, peers, neighborhood, economic factors and personal factors are the reasons of development of delinquent behavior of adolescents. Interventions in keeping consideration of these issues should be planned for the reduction of juvenile crimes.
Duplication of the SLIT3 Locus on 5q35.1 Predisposes to Major Depressive Disorder

Major depressive disorder (MDD) is a common psychiatric and behavioral disorder. To discover novel variants conferring risk to MDD, we conducted a whole-genome scan of copy number variation (CNV), including 1,693 MDD cases and 4,506 controls genotyped on the Perlegen 600K platform. The most significant locus was observed on 5q35.1, harboring the SLIT3 gene (P = 2×10−3). Extending the controls with 30,000 subjects typed on the Illumina 550 k array, we found the CNV to remain exclusive to MDD cases (P = 3.2×10−9). Duplication was observed in 5 unrelated MDD cases encompassing 646 kb with highly similar breakpoints. SLIT3 is integral to repulsive axon guidance based on binding to Roundabout receptors. Duplication of 5q35.1 is a highly penetrant variation accounting for 0.7% of the subset of 647 cases harboring large CNVs, using a threshold of a minimum of 10 SNPs and 100 kb. This study leverages a large dataset of MDD cases and controls for the analysis of CNVs with matched platform and ethnicity. SLIT3 duplication is a novel association which explains a definitive proportion of the largely unknown etiology of MDD.
Refinement in Fresco

Fresco is an interactive environment for building specified and proven re-usable program components in an object-oriented language. (Or rather, it is a projected one, since only small pieces of a prototype yet exist. The use of the present tense is grammatically simpler, but should not be understood to imply that any more than a design currently exists.) The benefits of re-usability promised by object-oriented programming include greater reliability — because components are tried and tested; and more rapid construction — because new products and components are built largely from archived components with a small amount of product-specific ‘glue’. There are a number of (soluble, I believe) problems connected with the management, accountancy, legal and distribution aspects of this scenario; but under the assumption that these can be overcome, Fresco is an attempt to address its reliability problem. If software is to be constructed from library components obtained from everywhere, then we must be sure that the components will fulfill their functions as advertised. But if this means reading and testing them all for ourselves, then we lose much of the supposed benefit of re-use. This is a good motivation for using formal methods. Clearly, formal specification and proof take more resources: but if a component is to be used in many products, then it is worth the extra effort. The aim in Fresco is therefore to specify object-oriented program components — rather than merely to write specifications in an object-oriented style. This brings practical differences from many of the current OO specification projects:
MILITARY EXPENDITURE AND MIGRATION IN EUROPE

The enlargement of the EU has implications for the national defence requirements and therefore national defence policy of European nations. In light of the freedom of movement of citizens between member states it is appropriate to consider the implications of a country's military expenditure for its macroeconomy and specifically on the flows of migration between member states. Traditionally, income differentials, employment levels and relative standards of living are all factors that influence an individual's decision to migrate. To this list we add the level of military expenditure. Migration from a panel of 16 Central and Eastern European Countries (CEECs) to Germany between 1995 and 2002 is found to be the result of the level of military expenditure of the source country and the host country in conjunction with factors consistent with standard theoretical predictions.
RICE UNIVERSITY SCHOLARS PROGRAM COVER SHEET

OF PROPOSED STUDY The creation of meaningful geometry for architecture or simulations currently takes a considerable amount of time. Traditional geometry generation usually entails the creation of a rough layout of the architecture, the manual addition of geometric detail, and a final application of colors and textures to the geometry. By automating large portions of this process using the parametric generation of largescale geometry and the subsequent addition of detail using techniques borrowed from texture synthesis, geometry generation will be accelerated dramatically. I propose to study algorithms that allow for such automatic geometry synthesis and to create an editing environment that enables the user to automatically generate architecture governed by a set of parameters. In a second phase, the environment will then be used to synthesize meaningful detail into the still bare geometry. The system will display the results 3-dimensionally and let the user export the generated geometry into other programs.
Off-line calibration of a macroscopic Dynamic Traffic Assignment model: Iterative demand-supply parameters estimation

Dynamic Traffic Assignment (DTA) is an increasingly popular and effective tool for analyzing complex transportation networks which integrates both demand and supply variations in time to replicate prevailing traffic conditions and forecast future network states. Application of these models requires meticulous calibration of both demand and supply parameters to generate consistent and reliable results. The aim of this paper is to present a calibration approach for a macroscopic DTA model in an off-line environment. We estimate Time Dependent Origin Destination (TDOD) demand matrices by a bi-level optimization problem and manually adjust supply parameters afterward. The calibration procedure and relative effectiveness of the iterative demand-supply calibration compared with demand-only calibration is investigated via a real network coded in VISUM. Link traffic volumes are used as measures of performance to compare observed and estimated values. The output of this paper is a guideline to calibrate macroscopic DTA models which can be used (i) for deployment of intelligent transportation systems, (ii) as an initial solution in on-line systems to efficiently combine historical and real-time data and provide more accurate anticipatory information, and (iii) appraise subsequent network performance and predict consequences of various traffic management strategies.
Tumor Necrosis Factor (TNF) Receptor Superfamily Member 1b on CD8+ T Cells and TNF Receptor Superfamily Member 1a on Non-CD8+ T Cells Contribute Significantly to Upper Genital Tract Pathology Following Chlamydial Infection.

BACKGROUND We demonstrated previously that tumor necrosis factor α (TNF-α)-producing Chlamydia-specific CD8(+) T cells cause oviduct pathological sequelae. METHODS In the current study, we used wild-type C57BL/6J (WT) mice with a deficiency in genes encoding TNF receptor superfamily member 1a (TNFR1; TNFR1 knockout [KO] mice), TNF receptor superfamily member 1b (TNFR2; TNFR2 KO mice), and both TNFR1 and TNFR2 (TNFR1/2 double KO [DKO] mice) and mix-match adoptive transfers of CD8(+) T cells to study chlamydial pathogenesis. RESULTS TNFR1 KO, TNFR2 KO, and TNFR1/2 DKO mice displayed comparable clearance of primary or secondary genital Chlamydia muridarum infection but significantly reduced oviduct pathology, compared with WT animals. The Chlamydia-specific total cellular cytokine response in splenic and draining lymph nodes and the antibody response in serum were comparable between the WT and KO animals. However, CD8(+) T cells from TNFR2 KO mice displayed significantly reduced activation (CD11a expression and cytokine production), compared with TNFR1 KO or WT animals. Repletion of TNFR2 KO mice with WT CD8(+) T cells but not with TNFR2 KO CD8(+) T cells and repletion of TNFR1 KO mice with either WT or TNFR1 KO CD8(+) T cells restored oviduct pathology to WT levels in both KO groups. CONCLUSIONS Collectively, these results demonstrate that TNFR2-bearing CD8(+) T cells and TNFR1-bearing non-CD8(+) T cells contribute significantly to oviduct pathology following genital chlamydial infection.
Necklace: An efficient cuckoo hashing scheme for cloud storage services

With the rapid growth of data, query performance is an important concern in cloud storage applications. To reduce the query response time, cuckoo hashing via d hash functions has been adopted to achieve O(1) query efficiency. However, in practice the cuckoo hashing consumes a large amount of system resources, since an item insertion may suffer from frequent “kick-out” operations or even endless loops. In order to address this problem, we propose an efficient loop-oblivious scheme, called Necklace, in the cloud. The idea behind Necklace is to minimize data migration among servers and alleviate the collisions in the insertion operation. We identify the shortest path via indexing the auxiliary table, without retrieving the actual storage contents or carrying out the tentative “kick-out” operations. We have implemented Necklace in a real cloud system and examined the performance by using a real-world trace. Extensive experimental results demonstrate the efficiency and efficacy of Necklace.
Internet of Things Virtual Networks: Bringing Network Virtualization to Resource-Constrained Devices

Networks of smart resource-constrained objects, such as sensors and actuators, can support a wide range of application domains. In most cases these networks were proprietary and stand-alone. More recently, many efforts have been undertaken to connect these networks to the Internet using standard protocols. Current solutions that integrate smart resource-constrained objects into the Internet are mostly gateway-based. In these solutions, security, firewalling, protocol translations and intelligence are implemented by gateways at the border of the Internet and the resource-constrained networks. In this paper, we introduce a complementary approach to facilitate the realization of what is called the Internet of Things. Our approach focuses on the objects, both resource-constrained and non-constrained, that need to cooperate by integrating them into a secured virtual network, named an Internet of Things Virtual Network or IoTVN. Inside this IoT-VN full end-to-end communication can take place through the use of protocols that take the limitations of the most resource-constrained devices into account. We describe how this concept maps to several generic use cases and, as such, can constitute a valid alternative approach for supporting selected applications. A first implementation demonstrating the key concepts of this approach is described. It illustrates the feasibility of integrating resource-constrained devices into virtual networks, but also reveals open challenges.
Improved Wavelet-Based Online Signature Verification Scheme Considering Pen Scenario Information

Although signature verification is safer biotypes in terms of criminal, it has more risk on business safety. In this paper we address important challenge of on-line signature verification, which is the high dimensionality of the signature features dataset. This issue can make the verification procedure computationally costly. In this regard, we take advantage of wavelet transform along with a feature selection scheme to introduce a new set of features. The experimental results on SVC 2004 database suggest that using this set of features, we can verify the signature with 3.5% EER while having significantly lower dimension data set in comparison with the state-of-the-art techniques.
Performance Persistence of Indian Fund of Mutual Funds: With Special Reference to Bull and Bear Market

This paper examines the performance persistence of Indian Fund of Mutual Funds (FoFs) during the period from January 2nd 2007 to December 31st 2010. The entire study period classified into three sub-periods based on the movement of BSE 500 index closing value and they are named as First Bull Market Period, Bear Market Period and Second Bull Market Period. The performance of individual FoFs in each sub-period are assessed by employing the performance measures of average excess return, Sharpe ratio and Jensen’s alpha. After testing the performance of the sample funds, contingence table is created by classifying the sample funds as winner or loser. Malkiel Z-test, Brown and Goetzmann Z-test and Khan and Rude Chi-square test is used to test the performance persistence of sample funds and found that the fund excel in the bull market do not expect to do well in the bear market. This study also concluded that the investors cannot earn above average risk adjusted return in the bull market period by hiring the above median performer of earlier bull market period.
Towards energy-aware intrusion detection systems on mobile devices

This paper investigates the correlations between the energy consumption of Android devices and the presence of threats (e.g. battery-drain attacks). In particular, this paper proposes a model for the energy consumption of single hardware components of a mobile device during normal usage and under attack. The model has been implemented in a kernel module and used to build up an energetic signature of both legal and malicious behaviors of WiFi hardware component in different Android devices. Such activity allows us to build a tentative database of signatures that can be used to detect attacks by means of the actual energy consumption of a mobile device. The proposed power consumption model and kernel module can be applied also to other hardware components, so to obtain very precise energetic signatures.
APPROACHES TO HUMAN CAPITAL AND SUSTAINABLE DEVELOPMENT IN CRISIS CONDITIONS

This paper illustrates the relationship formed in the economy between human capital and sustainable development considering that in recent years we are witnessing an expansion of the concept of human development towards sustainable human development. This requires increased performance and social responsibility entity in complete correlation with the wide expression of people's choices and utilization capacity, so that they contribute to meeting the needs of present generations taking into account ecological and social environment to protect future generations.
Board Structure, Executive Compensation and Firm Performance in Emerging Economies: Evidence from India

This paper examines the empirical relationship between board structure, CEO compensation and firm performance in the context of an emerging economy, India. Using panel data on 462 manufacturing firms from the Indian corporate sector for the period 1997 to 2002 I would like to explore two specific issues. First, I have examined how the structure of the corporate board in terms of size and proportion of non-executive directors affect the firm performance. This study also finds that the identity of the Chief Executive Officer matters; if the CEO is related to the promoter(s), the company performs better. Second, I have examined how the level and different components of executive compensation have an effect on the firm performance. The empirical findings indicate that size of the board and proportion of non-executive directors have a non-linear relation with firm performance. There is a threshold level on size of the board at 11 and proportion of non-executive directors at 73 % beyond which the performance of the firm starts decreasing. The relationship between executive compensation and firm performance is also found to be non-linear. There is also a saturation level on board compensation, beyond which the performance does not increase. The result suggests that institutional characteristics of emerging economies may support management structures, which are different from those predicted by earlier studies. JEL classification: G35, J33, C29