Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of size of DG on voltage flicker and voltage sag in closed-loop distribution system

Application of distributed generation (DG) in distribution system is expected to increase in the near future due to its positive impacts such as voltage support, improved reliability, small size and losses reduction. However DGs may have negative impacts on power quality, such as voltage regulation, harmonic distortion, islanding and confliction with relaying and reclosing. This paper investigates the effect of the Distributed Generation (DG) and its size on voltage flicker and voltage sag which is considered recently as an urgent power quality problem that can affect motor starting, temperature rise, overloading of generators, motors and may cause health risk problems due to the annoying light flicker which is consequence of voltage fluctuation. The effect of different sizes of DG on the voltage flicker and voltage sag in different buses of IEEE 34 buses meshed distribution system has been investigated. To support this argument, simulations are achieved on MATLAB/SIMULINK, where the results reveal the amount of effect of DG on voltage flicker and voltage sag for different types of buses of meshed distribution system.
Medical Computer Vision, Virtual Reality and Robotics: Promising Research Tracks

The automated analysis of 3D medical images can improve significantly both diagnosis and therapy. This automation raises a number of new fascinating research problems in the fields of computer vision, graphics and robotics. In this article, (a complete version is published by the Int. Journal of Image and Vision Computing [4]) I propose a list of such problems after a review of the current major 3D imaging modalities, and a description of the related medical needs. I then present some of past and current work done in our research group EPIDAURE at INRIA, on the following topics: segmentation of 3D images, 3D shape modeling, 3D rigid and nonrigid registration, 3D motion analysis and 3D simulation of therapy.
Efficient myoblast expansion for regenerative medicine use

Cellular therapy using expanded autologous myoblasts is a treatment modality for a variety of diseases. In the present study, we compared the commercial skeletal muscle cell growth medium-2 (SKGM-2) with a medium designed by our group for the expansion of skeletal myoblasts. The use of an in-house medium [DMEM/F12 medium supplemented with EGF, bFGF, HGF, insulin and dexamethasone (DFEFH)] resulted in a greater number of myoblast colonies (>50%) and a 3-, 4- and 9-fold higher proliferation rate, eventually resulting in a 3-, 7- and 87-fold greater number of cells at the 1st, 2nd and 3rd passage, respectively, compared with the cells grown in SKGM-2 medium. The average CD56 expression level was higher in the myoblasts cultured in DFEFH than in those culturd in SKGM-2 medium. At the 3rd passage, lower expression levels of myostatin and considerably higher expression levels of myogenin were observed in the cells that were grown in DFEFH medium. The results of our study indicated that myoblasts cultured in both medium types displayed fusogenic potential at the 3rd passage. Furthermore, it was shown that cells cultured in DFEFH medium created myotubes with a considerably higher number of nuclei. Additionally, we observed that the fusion potential of the cells markedly decreased with the subsequent passages and that the morphology of the myoblasts differed between the 2 cultured media. Our data demonstrate that culture in the DFEFH medium leads to an approximately 90-fold greater number of myoblasts, with improved morphology and greater fusion potential, compared with culture in the commercial SKGM-2 medium.
Author Manuscript, Published in "international Association for Statistical Computing (iasc), Statistics for Data Mining, Learning and Knowledge Extraction, Aveiro : Portugal Adaptive Clustering of Time Series

abstract This paper focuses on the cell division cycle insuring the proliferation of cells and which is drastically aberrant in cancer cells. The aim of this biological problem is the identification of genes characterizing each cell cycle phase. The identification process is commonly based on a prior set of well-characterized cell cycle genes, called reference genes. The expression levels of the studied genes are measured during the cell division cycle. Each studied gene is assigned a cell cycle phase by it's peak similarity to the reference genes. This classical approach suffers of two limitations. On the one hand, the most widely used proximity measures between gene expression profiles are based on the closeness of the values regardless to the similarity with respect to (w.r.t.) the genes expression behavior. On the other hand, many different ill-founded sets of reference genes are proposed in the literature, and biologists are not agree about those of genes best characterizing the observed cell cycle phases. Our aim in this paper is twice. We propose a new dissimilarity index for gene expression profiles to include both proximity measures w.r. t. values and w.r. t. behavior. An adaptive unsupervised classification, based on the proposed dissimilarity index, is then performed to identify the cell cycle phases of the studied genes. Finally, we propose a new set of reference genes, well-assessed by a biological knowledge.
A new shape-based method for object localization and characterization from scattered field data

The problem of characterizing the geometric structure of an object buried in an inhomogeneous halfspace of unknown composition is considered. The authors develop a nonlinear inverse scattering algorithm based on a low-dimensional parameterization of the unknown object and the background. In particular, they use a low-order polynomial expansion to represent the spatial variations in the real and imaginary parts of the object and background complex permittivities. The boundary separating the target from the unknown background is described using a periodic, quadratic B-spline curve whose control points can be individually manipulated. They determine the unknown control point locations and contrast expansion coefficients using a greedy-type approach to minimize a regularized least-squares cost function. The regularizer used here is designed to constrain the geometric structure of the boundary of the object and is closely related to snake methods employed in the image processing community. They demonstrate the performance of their approach via extensive numerical simulation involving two-dimensional (2D), TM/sub z/ scattering geometries. Their results indicate a strong ability to localize and estimate the shape of the object even in the presence of an unknown and inhomogeneous background.
Decoupled random modulation technique for an open-end winding induction motor based 3-level inverter

This paper presents a random pulse width modulation (RPWM) technique for 3-level inverter based on open-end winding induction motor. A 3-level inverter can be realized by feeding an induction motor in open-end winding configuration with two 2-level inverters from both sides. A decoupled random PWM strategy for an open-end winding induction motor drive is proposed in this paper, in which, the switching signals for the individual inverters are derived separately. In the proposed scheme, the instantaneous switching states for the inverters are independently generated by comparing the decoupled reference voltage of the individual inverters with a random carrier wave. The proposed scheme is implemented for 2hp induction motor drive and experimental results are presented. Experimental results showing the comparison of the performance of the proposed scheme with that of the sine-triangle PWM is also presented.
Indonesian Adaptation and Psychometric Properties Evaluation of the Big Five Personality Inventory: IPIP-BFM-50

The big five personality traits are the best acknowledged and most commonly used model in psychology. Therefore, many personality scales are developed based on this personality model. IPIP-BFM-50 is one of the open-source scales measuring big five personality that is widely used by the world researchers. This study aimed to adapt IPIP-BFM-50 into Indonesian and evaluate its psychometric properties. Adaptation was done by following the guidelines of the International Test Commission (ITC). The result shows that IPIP-BFM-50 Indonesia has Aiken's V index ranging from 0.71 - 0.98. Alpha reliability with n = 502 ranges from 0.762 (agreeableness) to 0.862 (emotional stability). Factor analysis shows that the items are well-grouped according to their dimensions with loading factor ranging from 0.34 to 0.75 on the factors measured. Thus, IPIP-BFM-50 Indonesia has satisfactory psychometric properties and can be used to measure Big five personality.
Activation of the Jasmonic Acid Pathway by Depletion of the Hydroperoxide Lyase OsHPL3 Reveals Crosstalk between the HPL and AOS Branches of the Oxylipin Pathway in Rice

The allene oxide synthase (AOS) and hydroperoxide lyase (HPL) branches of the oxylipin pathway, which underlie the production of jasmonates and aldehydes, respectively, function in plant responses to a range of stresses. Regulatory crosstalk has been proposed to exist between these two signaling branches; however, there is no direct evidence of this. Here, we identified and characterized a jasmonic acid (JA) overproduction mutant, cea62, by screening a rice T-DNA insertion mutant library for lineages that constitutively express the AOS gene. Map-based cloning was used to identify the underlying gene as hydroperoxide lyase OsHPL3. HPL3 expression and the enzyme activity of its product, (E)-2-hexenal, were depleted in the cea62 mutant, which resulted in the dramatic overproduction of JA, the activation of JA signaling, and the emergence of the lesion mimic phenotype. A time-course analysis of lesion formation and of the induction of defense responsive genes in the cea62 mutant revealed that the activation of JA biosynthesis and signaling in cea62 was regulated in a developmental manner, as was OsHPL3 activity in the wild-type plant. Microarray analysis showed that the JA-governed defense response was greatly activated in cea62 and this plant exhibited enhanced resistance to the T1 strain of the bacterial blight pathogen Xanthomonasoryzaepvoryzae (Xoo). The wounding response was attenuated in cea62 plants during the early stages of development, but partially recovered when JA levels were elevated during the later stages. In contrast, the wounding response was not altered during the different developmental stages of wild-type plants. These findings suggest that these two branches of the oxylipin pathway exhibit crosstalk with regards to biosynthesis and signaling and cooperate with each other to function in diverse stress responses.
Development of Highly Organized Lymphoid Structures in Buruli Ulcer Lesions after Treatment with Rifampicin and Streptomycin

Background Buruli ulcer caused by Mycobacterium ulcerans is an infection of the subcutaneous tissue leading to chronic necrotising skin ulcers. The pathogenesis is associated with the cytocidal and immunosuppressive activities of a macrolide toxin. Histopathological hallmark of progressing disease is a poor inflammatory response despite of clusters of extracellular bacilli. While traditionally wide excision of the infected tissue was the standard treatment, provisional WHO guidelines now recommend an eight week pre-treatment with streptomycin and rifampicin. Methodology/Principal Findings We conducted a detailed immunohistochemical analysis of tissue samples from Buruli patients who received antibiotic treatment. Cellular immune response along with bacterial load and distribution were monitored. We demonstrate that this treatment leads to the development of highly organized cellular infiltration surrounding areas of coagulative necrosis. Diffuse infiltrates, granulomas and dense lymphocyte aggregation close to vessels were observed. Mycobacterial material was primarily located inside mononuclear phagocytes and microcolonies consisting of extracellular rod-shaped mycobacteria were no longer found. In observational studies some patients showed no clinical response to antibiotic treatment. Corresponding to that, one of five lesions analysed presented with huge clusters of rod-shaped bacilli but no signs of infiltration. Conclusions/Significance Results signify that eight weeks of antibiotic treatment reverses local immunosuppression and leads to an active inflammatory process in different compartments of the skin. Structured leukocyte infiltrates with unique signatures indicative for healing processes developed at the margins of the lesions. It remains to be analysed whether antibiotic resistance of certain strains of M. ulcerans, lacking patient compliance or poor drug quality are responsible for the absent clinical responses in some patients. In future, analysis of local immune responses could serve as a suitable surrogate marker for the efficacy of alternative treatment strategies.
Optimal Martingale measures and hedging in models driven by Levy processes

Our research falls into a broad area of pricing and hedging of contingent claims in incomplete markets. In the first part we introduce the Levy processes as a suitable class of processes for financial modelling purposes. This in turn causes the market to become incomplete in general and therefore the martingale measure for the pricing/hedging purposes has to be chosen by introducing some subjective criteria. We study several such criteria in the second section for a general stochastic volatility model driven by Levy process, leading to minimal martingale measure, variance-optimal, or the more general q-optimal martingale measure, for which we show the convergence to the minimal entropy martingale measure for q ↓ 1. The martingale measures studied in the second section are put to use in the third section, where we consider various hedging problems in both martingale and semimartingale setting. We study locally risk-minimization hedging problem, meanvariance hedging and the more general p-optimal hedging, of which the meanvariance hedging is a special case for p = 2. Our model allows us to explicitly determine the variance-optimal martingale measure and the mean-variance hedging strategy using the structural results of Gourieroux, Laurent and Pham (1998) extended to discontinuous case by Arai (2005a). Assuming a Markovian framework and appealing to the Feynman-Kac theorem, the optimal hedge can be found by solving a three-dimensional partial integrodifferential equation. We illustrate this in the last section by considering the variance-optimal hedge of the European put option, and find the solution numerically by applying finite difference method.
Development of self-regulation in context

In this articIe, we aim to contribute to an understanding of the limits of intentionality from a child development perspective. Here, we define intentionality as goal-directed agentie behavior. Intentions encompass cognitive representations of goals and of means that organize behavior and that are directed to a particular goal (i.e., action plan; see Gollwitzer, 2012; Wieber, Thürmer and Gollwitzer, this volume). Intentions also incIude the motivation to pursue a goal in order to achieve a desired outcome (Bratman, 1999; Malle, Moses and Baldwin, 2001; Iomasello, Carpenter, Call, Behne and Moll, 2005). More precisely, we focus on self-regulation as intentional behavior that is constitutive for human agency. We conceive of self-regulation as the motivation and ability to guide goal-directed behavior over time and across different situational contexts in the process of goal attainment in order to transfer intentions into behavior and to achieve a desired result (Karoly, 1993). Self-regulation as intentional behavior can be limited by internal (e.g., temperament) and extern al factors (e.g., parenting) throughout development. In this regard, limits of intentionality may induce incomplete goal attainment (Suchodoletz and Achtziger, 2011; Wieber, Gollwitzer and Seebaß, 2011). Contextual conditions can have positive and negative influences on the development of self-regulation. Interactionist perspectives point to the active role of the agentie individual within adynamie person-environment system (developmental contextualism; Lerner and Walls, 1999; Magnusson and Stattin, 2006). Cognitive, emotional, and motivational variables (e.g., self-representations) and underlying biological processes are assumed to shape individuals' interactions with their environments, and vice versa (see also Blair and McKinnon, this volume). Self-regulation develops through individuals' intentional activities in different contexts during development throughout the life-span. Referring to Bronfenbrenner's bioecological approach (Bronfenbrenner and Ceci, 1994), the child's mierosystem interacts reciprocally with the immediate environment, for instance in the family or the school context. Ihis incIudes bidirectional effects
SoC-based Software-Hardware codesign of intelligent diagnosis

This study develops and implements a SoC-based HW/SW (Hardware-Software) codesign for an intelligent diagnostic system. To improve the efficiency of the VLSI (Very Large Scale Integration) design process, the components of the intelligent diagnostic system are designed in the form of SIP (Silicon Intellectual Property) modules. The SIP modules, including the CPU module, the GPIO (General Purpose I/O) module and the NN (Neural Network) module, are then integrated to form the complete intelligent diagnostic system. In constructing the system, an embedded processor is employed to run software programs. In addition to integrating the hardware architecture, this study also develops application software, comprising a bootloader, a UARTcomm module and a main program for human-machine interface, to drive the embedded processor. The SoC-based HW/SW codesign method employed in this study increases the efficiency of the system design process and reduces the rebuild time. The results of the experimental trials verify the successful performance of the developed intelligent diagnostic system.
Applying a Hybrid Genetic Algorithm in the Design of a Self-Paced Brain Interface with a Low False Positive Rate

A new hybrid genetic algorithm (HGA) for optimization of a self-paced brain interface (SBI) is proposed. To identify intentional control (IC) commands in the noisy background EEG signal, the proposed SBI uses features extracted from three neurological phenomena - movement-related potentials as well as changes in the power of Mu and Beta rhythms. To identify the IC commands, for each neurological phenomenon, a multiple classifier system (MCS) is designed. Then a 2nd-stage MCS combines the outputs of the individual MCSs and generates the final decision. The HGA selects the optimal subset of features, the optimal parameter values of the classifiers, as well as the best configuration for combining the MCSs. Analysis of the data of four subjects shows an average TP = 56.18%, and an average FP = 0.14%, a significant improvement over our previous SBI design.
Generation of tests for programming challenge tasks using evolution algorithms

In this paper, an automated method for generation of tests in order to detect inefficient (slow) solutions for programming challenge tasks is proposed. The method is based on genetic algorithms. The proposed method was applied to a task from the Internet problem archive - the Timus Online Judge. For this problem, none of the existed solutions passed the generated set of tests.
Towards Automatic Generation of Gene Summary

In this paper we present an extractive system that automatically generates gene summaries from the biomedical literature. The proposed text summarization system selects and ranks sentences from multiple MEDLINE abstracts by exploiting gene-specific information and similarity relationships between sentences. We evaluate our system on a large dataset of 7,294 human genes and 187,628 MEDLINE abstracts using Recall-Oriented Understudy for Gisting Evaluation (ROUGE), a widely used automatic evaluation metric in the text summarization community. Two baseline methods are used for comparison. Experimental results show that our system significantly outperforms the other two methods with regard to all ROUGE metrics. A demo website of our system is freely accessible at http://60.195. 250.72/onbires/summary.jsp.
A Compromise-Resilient Group Rekeying Scheme for Hierarchical Wireless Sensor Networks

The wireless sensor networks (WSNs) are normally operated in unattended, harsh, or hostile environment. The adversaries may easily compromise some sensor nodes and abuse their shared keys to inject false sensing reports or modify the reports sent by other nodes. Many applications in WSNs require secure group communications, which are supported by group keys. Once a malicious node is detected in the group, the group key should be renewed immediately for the network security. Some strategies have been proposed to develop the group rekeying protocol, but most existing schemes suffer the node capture attack. To conquer this problem, we propose a new compromise-resilient group rekeying scheme for hierarchical WSNs in this paper. Compared with existing schemes, our rekeying method possesses the following features: (1) it is robust to the node capture attack, (2) it supports both forward secrecy and backward secrecy, and (3) it has low communication and storage overhead, which are particularly beneficial to the resource-constrained large-scale sensor networks.
An oriented-application adaptive mobile cloud computing middleware

This paper presents the cloud virtual machine resources allocation strategy based on virtual machine implementation, deployment structures in virtual machine management. By consulting a large number of literature, thought resources management not only confined to the system level, application level actually need more resources to cooperate, therefore this paper proposes adaptive cloud computing middleware AMCCM (Adaptive Mobile Cloud Computing Middleware) this concept, and gives the structure of the AMCCM and process, finally through the implementation of a XX's mobile office system to verify this method, and the original office system were compared, the cloud platform of mobile office system efficiency more efficient.
The Value of Online Users: Empirical Evaluation of the Price of Personalized Ads

Ad networks use the behaviors of online users to associate them with preferences (features), and market these features to enable advertisers to target online users. Typical features associated with users include location, interests, gender, age, and etc. Furthemore, ad networks provide their clients with campaing creation tools to help to them to configure and run campains. In this paper, we study the pricing of ads using the ad campaing planning tools of ad networks. We develop tools to collect the suggested bid prices from two platforms: YouTube and Facebook. Analyzing these prices we find that United States is the most expensive country in both platforms. We also find that the most expensive preferences are different in YouTube and Facebook. In YouTube, the top preferences are related to Oil & Gas, while in Facebook are devices, ethnics or politics depending on the type of bidding. Finally, we do not find any price difference genders in Facebook.