Miracle-dz/UniFAR-FTUs huggingface dataset:
ALGORITHM FOR TUNING THE CMAC REGULATOR SCALIN GAINS VIA AUTOMATIC SYSTEM STEP RESPONSE

The paper presents the tuning of a CMAC (Cerebellar Model Articulation Controller) regulator, with B-spline basis functions of order 3, implemented in an automatic daylight control system. After the tuning process of the regulator scaling gains, a set of ranges for scaling gains resulted. For these ranges of scaling gains the automatic lighting control system (ALCS) satisfied the desired performances. After the tuning process, the behavior of the ALCS in the presence of the illuminance disturbances was studied. At the final of the paper, an experimental tuning algorithm of the regulator scaling gains via ALCS step responses analysis is proposed. Even if the used experimental model of the process is a gross approximation of the real model of the process, using this experimental tuning algorithm, the designer can find a set of ranges of the regulator scaling gains for which the ALCS is stable and satisfy the desired performances.
New Bounds for Restricted Isometry Constants T

This paper discusses new bounds for restricted isometry constants in compressed sensing. Let be an real matrix and be a positive integer with . One of the main results of this paper shows that if the restricted isometry constant of satisfies then -sparse signals are guaranteed to be recovered exactly via minimization when no noise is present and -sparse signals can be estimated stably in the noisy case. It is also shown that the bound cannot be substantially improved. An explicit example is constructed in which , but it is impossible to recover certain -sparse signals.
Diffusion of innovation - the adoption of electronic commerce by small and medium enterprises (SMEs) in regional Australia

Many variables can influence the likelihood of innovation adoption. Analysis of these variables suggests that further research needs to be conducted to better understand the process of adoption. This paper explores the issues that influence the diffusion of innovation as it relates to the adoption of e-commerce by Small and Medium Enterprises (SMEs) particularly in regional areas. While it is generally accepted that the strategic use of Information Technology (IT) is vital in the marketplace, SMEs, especially those in regional Australia, are lagging behind. The paper examines existing theory as it pertains to the diffusion of innovation from the perspective of regional SMEs. A research study is outlined to identify the causal factors responsible for this lack of uptake of IT. It is critical to understand such factors so that steps can be taken to redress this inequity and positively influence the acceptance and use of IT innovations in SMEs in regional Australia. An empirical investigation is planned to explore this diffusion and the slow rate of uptake by SMEs. This investigation will use a survey, preceded by focus groups, to uncover factors influencing the adoption or non adoption of IT innovations by SMEs.
From Diffusion to Reaction via Γ-Convergence

We study the limit of high activation energy of a special Fokker-Planck equation, known as Kramers-Smoluchowski (K-S) equation. This equation governs the time evolution of the probability density of a particle performing a Brownian motion under the influence of a chemical potential H/ε. We choose H having two wells corresponding to two chemical states A and B. We prove that after a suitable rescaling the solution to (K-S) converges, in the limit of high activation energy (ε → 0), to the solution of a simple system modeling the diffusion of A and B, and the reaction A B. The aim of this paper is to give a rigorous proof of Kramer’s formal derivation and to embed chemical reactions and diffusion processes in a common variational framework which allows to derive the former as a singular limit of the latter, thus establishing a connection between two worlds often regarded as separate. The singular limit is analysed by means of Gamma-convergence in the space of finite Borel measures endowed with the weak-∗ topology.
Reverse architecting approach for complex systems

Philips is an electronics company which operates world wide and participates in professional as well as consumer markets. The architecture of many software intensive systems are currently not optimally prepared for the changing market. For example, the variety of systems is increasing because different users or user groups demand slightly different variants of a system. Good understanding of systems is required to be able to follow these changes. During the last years we have analysed a number of systems from which we have derived a general approach for reverse architecting (RA). Our approach has proved to be applicable for various complex systems in different domains. It consists of a number of RA steps. We describe three RA steps and indicate some aspects of other RA steps. The description is supplemented with three case studies of complex systems. The complete set of RA steps is not fully independent, however it is not necessary to perform all RA steps for each case
A NEW SYSTOLIC ALGORITHM OF 2-D DCT TRANSFORM BASED ON PSEUDO-CORRELATION STRUCTURES FOR A UNIFIED VLSI ARCHITECTURE

Using a new input sequence restructuring a new VLSI algorithm for 2-D discrete cosine transform (DCT) for an efficient unified VLSI architecture, with appealing topological features and high performances has been obtained. The new algorithm has a modular and regular computational structure and can be computed in parallel using two pseudo-correlation structures, resulting in a high throughput VLSI implementation. Using the proposed algorithm we can obtain an efficient VLSI architecture for 2-D DCT having a high speed at a low hardware complexity. The architecture that can be obtained has good topological properties as a regular and modular structure and local connections and can be used to obtain a unified implementation for 2-D DCT and DST.
Fast Inference in Non-Conjugate Gaussian Process Models via Data Augmentation

We present AugmentedGaussianProcesses.jl, a software package for augmented stochastic variational inference (ASVI) for Gaussian process models with non-conjugate likelihood functions. The idea of ASVI is to find an augmentation of the original GP model which renders the model conditionally conjugate and perform inference in the augmented model. We evaluate our method for three GP models (GP classification, robust GP regression and a Bayesian SVM model) and demonstrate that it is up to two orders of magnitude faster than the state-of-the-art.
Using big data to support automatic Word Sense Disambiguation

Word Sense Disambiguation (WSD) usually relies on data structures built upon the words to be disambiguated. This is a time-consuming process that requires a huge computational effort. In this paper, we propose an approach to automatically build a generic sense inventory (called iSC) to be used as a reference for disambiguation. The sense inventory is built extracting insight from Big Data exploiting a community detection algorithm. Since generate taking into account large corpora of data, the iSC is independent of the domain of application and of predefined target words.
VISION SIMULATOR OF HSR-VII FOR OBSTACLERUN IN HUROCUP

This paper presents the vision simulator, which is designed for simulating vision processing and task planning for smallsize humanoid, HSR-VII. Vision simulator under 3D environment is essential for developing motion planning and vision processing algorithm including foot step planning. In order to simulate gate generation and vision processing concurrently, the essential components such as walking pattern generator, vision module, visualizer and task planner are included in this simulator. Detailed program architecture is explained along with its function descriptions. For the understanding of whole architecture, brief description on HSR-VII and modifiable walking pattern generation algorithm are introduced. To verify the effectiveness of the SW system, the simulation designed for ObstacleRun in FIRA HuroCup league is carried out using the designed simulator.
Cutting Words

We examined whether subtle exposure to sexually objectifying cues increases women’s intentions to have cosmetic surgery. Undergraduate women (N = 116) were randomly assigned to a condition in which they unscrambled sentences containing words associated with sexual objectification, non-self-objectifying physicality, or neutral content. Following a manipulation check of these primes, participants reported their body shame and intentions to have cosmetic surgery in the future. Results revealed that priming a state of self-objectification, compared to the two non-self-objectifying conditions, increased both body shame and intentions to have cosmetic surgery. In a mediational model, the link between self-objectification and intentions to have cosmetic surgery was partially mediated by body shame. Controlling for other key intrapersonal and social motives linked to interest in cosmetic surgery did not alter these patterns. These findings highlight the potential for the consumption of cosmetic surgery to stand as another harmful micro-level consequence of self-objectification that may be perpetuated via subtle exposure to sexually objectifying words, even in the absence of visual depictions or more explicit encounters of sexual objectification.
Dual Stewart platform mobility simulator

The paper presents the simulation and modeling of gait on a system using two prototype compact Stewart platforms. Control issues raised by the reduced size of the robots and hence their lower power output are discussed. The flexible haptic material concept is introduced and used to realistically model heterogeneous haptic surfaces simulating the virtual ground. An algorithm for virtual foot/virtual surface contact modeling and transforming the platform motion into walking in VEs is also presented.
Traffic Analysis & Modeling in Wireless Sensor Networks and Their Applications on Network Optimization and Anomaly Detection

Wireless sensor network (WSN) has emerged as a promising technology thanks to the recent advances in electronics, networking, and information technologies. However, there is still a great deal of additional research required before it finally becomes a mature technology. This article concentrates on three factors which are holding back the development of WSNs. Firstly, there is a lack of traffic analysis & modeling for WSNs. Secondly, network optimization for WSNs needs more investigation. Thirdly, the development of anomaly detection techniques for WSNs remains a seldom touched area. Among these three factors, the understanding regarding the traffic dynamics within WSNs provide a basis for further works on network optimization and anomaly detection for WSNs.
Understanding security mistakes developers make: Qualitative analysis from Build It, Break It, Fix It

Secure software development is a challenging task requiring consideration of many possible threats and mitigations. This paper investigates how and why programmers, despite a baseline of security experience, make security-relevant errors. To do this, we conducted an in-depth analysis of 94 submissions to a secure-programming contest designed to mimic real-world constraints: correctness, performance, and security. In addition to writing secure code, participants were asked to search for vulnerabilities in other teams’ programs; in total, teams submitted 866 exploits against the submissions we considered. Over an intensive six-month period, we used iterative open coding to manually, but systematically, characterize each submitted project and vulnerability (including vulnerabilities we identiﬁed ourselves). We labeled vulnerabilities by type, attacker control allowed, and ease of exploitation, and projects according to security implementation strategy. Several patterns emerged. For example, simple mistakes were least common: only 21% of projects introduced such an error. Conversely, vulnerabilities arising from a misunderstanding of security concepts were signiﬁcantly more common, appearing in 78% of projects. Our results have implications for improving secure-programming APIs, API documentation, vulnerability-ﬁnding tools, and security education.
Short-term load forecasting based on Bayesian neural networks learned by Hybrid Monte Carlo method

This paper reports on Bayesian technique to design an optimal neural networks based model for short term load forecasting. Usually, The weight vector has Normal prior distribution, and the posterior distribution is approximated by Gaussian approximation. In order to avoid Gaussian approximation, we used Hybrid Monte Carlo algorithm to learn the weight vector, such that the Hamilton energy function has minimal value. In Hybrid Monte Carlo algorithm, the Hamilton function is the regularized error function, and the position variables is weights. In simulation experiments, two types Bayesian neural networks with Normal weight and Cauchy weight are used to hour load forecasting. Experiment result show that these two approaches have good performance (evaluated by MAPE and RMSE)
Success Factors for Peace Treaties: A Review of Theory and Evidence

Wars impose tremendous costs on societies and the question of how to end them is of foremost importance. Several hundred books and scientific articles have been written on mediation and peace agreements. In this policy paper I shall provide a critical literature survey on the effects of peace agreements, with a special emphasis on mediation. One of the major conclusions of this review of existing work is that many findings in the literature need to be interpreted with much care, as they are merely correlations that could well be driven by selection bias or confounding factors, and that interpreting them as causal evidence would be dangerous. This survey does however not limit itself to discussing the potential fragility of various findings, but also highlights some results that are supported by a substantial body of suggestive evidence, focusing in particular on the sharing of political and military power, on security guarantees, on trust-building measures and on the role of economic opportunities.
[The influence of pain aliments and vertebral mobility in patients after whole body cryotherapy].

INTRODUCTION The motive efficiency depends from many factors, in this currently also form the state of health. The change in grounds of vertebral column causing the limitations of mobility and pain can significance worsen the functional state, motive efficiency and quality of patient's life. The leadership of active mode of life complying to recommendations the preventive style of life as well as the using with interventions of physical medicine influences on improvement significance the state of health. MATERIAL AND METHODS It the examination groups were 42 patients (21 women and 21 men) in age from 45-65 years with low back pain about different etiology. All studied were thirty interventions of whole body cryotherapy and then practices kinesitherapy exercises by 30 minutes subjected on gymnastic room. To evaluation of stepping pain ailments was the scale VAS executed, mobility of lumbar spine with help of Schober test as well as was executed. All results were statistical analysis subjected. RESULTS After whole body cryotherapy the pain ailments in scale VAS were statistical significant in men group. The decrease of pain ailments influenced on improvement column mobility vertebral spine with use a Schober test (p<0,05). The statistical analysis were not significant in women group of pain ailments and the opinion of mobility of vertebral column spine (p > 0,05). CONCLUSIONS Whole body cryotherapy reduced significance pain ailments and mobility of lumbar spine in men group. In women group the got results were not statistical significant.
Positive Natural Selection in the Human Lineage

Positive natural selection is the force that drives the increase in prevalence of advantageous traits, and it has played a central role in our development as a species. Until recently, the study of natural selection in humans has largely been restricted to comparing individual candidate genes to theoretical expectations. The advent of genome-wide sequence and polymorphism data brings fundamental new tools to the study of natural selection. It is now possible to identify new candidates for selection and to reevaluate previous claims by comparison with empirical distributions of DNA sequence variation across the human genome and among populations. The flood of data and analytical methods, however, raises many new challenges. Here, we review approaches to detect positive natural selection, describe results from recent analyses of genome-wide data, and discuss the prospects and challenges ahead as we expand our understanding of the role of natural selection in shaping the human genome.
GlossBoot: Bootstrapping Multilingual Domain Glossaries from the Web

We present GlossBoot, an effective minimally-supervised approach to acquiring wide-coverage domain glossaries for many languages. For each language of interest, given a small number of hypernymy relation seeds concerning a target domain, we bootstrap a glossary from the Web for that domain by means of iteratively acquired term/gloss extraction patterns. Our experiments show high performance in the acquisition of domain terminologies and glossaries for three different languages.
Improper Gaussian Signaling Scheme for the Z-Interference Channel

This paper studies improper Gaussian signaling in the Z-Interference-Channel (ZIC) for the case when the interference is treated as noise. The extra degree of freedom from improper signaling provides better interference management, which balances the trade-off between maximizing the direct link throughput and controlling the effect of interference, hence giving better achievable rate than the proper signaling counterpart. In this work, a closed form solution to the sum-rate maximizing real-composite transmit covariance matrix is derived for the ZIC. The structure of the real-composite covariance matrix reveals some interesting insights, such as the optimality of binary power control, the channel condition when improper signaling is strictly better than the proper signaling strategy, as well as the relationship between the choice of the real-composite transmit covariance matrix and the system parameters. The connection between the results obtained in this work and those available in the literature are also pointed out.
Rapid Publication Three Alternative Promoters of the Rat g-Glutamyl Transferase Gene Are Active in Developing Lung and Are Differentially Regulated by Oxygen after Birth

The rat gamma-glutamyl transferase mRNA transcripts I, II, and III are derived from three alternative promoters, P(I), P(II), and P(III). In the adult only mRNA III is expressed in the lung. We show that mRNA III gene expression is developmentally regulated in the fetal lung; it is first expressed in gestation. In contrast to the adult lung, the fetal lung expresses mRNA I, II, and III. The switch from the fetal to the adult pattern of gammaGT mRNA expression begins within the first 24 h of birth and is complete by 10 d of age. gammaGT mRNA II disappears within 24 h, mRNA I disappears by 10 d leaving mRNA III as the sole transcript. Alveolar epithelial type 2 cells (AT2) isolated from the adult lung express only mRNA III. When cultured in 21% O2 mRNA III is maintained, but when cultured in 3% O2 the fetal pattern of mRNA I, II and III expression is induced. When AT2 cells in hypoxia are exposed to carbon monoxide, mRNA II is suppressed suggesting that a heme-binding protein (responsive to oxygen) may suppress mRNA II expression and may be responsible for the decrease in lung mRNA II seen after birth. A reporter gene under the control of DNA sequences from the gammaGT P(III) promoter is activated in transient transfection studies in response [. ] Research Article
Consumer choice and optimal locations models: Formulations and heuristics

Abstract. A new direction of research in competitive location theory incorporates theories of consumer choice behavior in its models. Following this direction, the present article studies the importance of consumer behavior with respect to distance or transportation costs in the optimality of locations obtained by traditional competitive location models. We consider various ways of defining a key parameter in the basic maximum capture model (MAXCAP). This parameter will indicate a number of ways to take distance into account based on several consumer choice behavior theories. The optimal locations and the deviation in demand – captured when the optimal locations of the other models are used instead of the true ones – are computed for each model. We present a metaheuristic based on GRASP and the tabu search procedure to solve all the models. Computational experience and an application to a 55-node network are also presented.
Pubertal Bisphenol A Exposure Alters Murine Mammary Stem Cell Function Leading to Early Neoplasia in Regenerated Glands

Perinatal exposure to bisphenol A (BPA) has been shown to cause aberrant mammary gland morphogenesis and mammary neoplastic transformation. Yet, the underlying mechanism is poorly understood. We tested the hypothesis that mammary glands exposed to BPA during a susceptible window may lead to its susceptibility to tumorigenesis through a stem cell–mediated mechanism. We exposed 21-day-old Balb/c mice to BPA by gavage (25 μg/kg/d) during puberty for 3 weeks, and a subset of animals were further challenged with one oral dose (30 mg/kg) of 7,12-dimethylbenz(a)anthracene (DMBA) at 2 months of age. Primary mammary cells were isolated at 6 weeks, and 2 and 4 months of age for murine mammary stem cell (MaSC) quantification and function analysis. Pubertal exposure to the low-dose BPA increased lateral branches and hyperplasia in adult mammary glands and caused an acute increase of MaSC in 6-week-old glands and a delayed increase of luminal progenitors in 4-month-old adult gland. Most importantly, pubertal BPA exposure altered the function of MaSC from different age groups, causing early neoplastic lesions in their regenerated glands similar to those induced by DMBA exposure, which indicates that MaSCs are susceptible to BPA-induced transformation. Deep sequencing analysis on MaSC-enriched mammospheres identified a set of aberrantly expressed genes associated with early neoplastic lesions in patients with human breast cancer. Thus, our study for the first time shows that pubertal BPA exposure altered MaSC gene expression and function such that they induced early neoplastic transformation. Cancer Prev Res; 7(4); 445–55. ©2014 AACR.
Three necessary conditions for establishing effective Sustainable Development Goals in the Anthropocene

The purpose of the United Nations-guided process to establish Sustainable Development Goals is to galvanize governments and civil society to rise to the interlinked environmental, societal, and economic challenges we face in the Anthropocene. We argue that the process of setting Sustainable Development Goals should take three key aspects into consideration. First, it should embrace an integrated social-ecological system perspective and acknowledge the key dynamics that such systems entail, including the role of ecosystems in sustaining human wellbeing, multiple cross-scale interactions, and uncertain thresholds. Second, the process needs to address trade-offs between the ambition of goals and the feasibility in reaching them, recognizing biophysical, social, and political constraints. Third, the goal-setting exercise and the management of goal implementation need to be guided by existing knowledge about the principles, dynamics, and constraints of social change processes at all scales, from the individual to the global. Combining these three aspects will increase the chances of establishing and achieving effective Sustainable Development Goals.