Miracle-dz/UniFAR-FTUs huggingface dataset:
Aurora Software Product Line

In this paper, an in-house Software Product Line (SPL), so-called Aurora, is introduced as a platform independent multi-tier Web development environment including the core infrastructure based on Rich Internet Application (RIA) and Enterprise Internet Application (EIA) models. Besides Aurora provides a complete roadmap to enterprise scale Web-based applications, it also embodies the SPL within the context of software process management methodology, WYSIWYG (What You See Is What You Get) design and development environments, software lifecycle management techniques and quality management tools. Essential SPL activities – management, core asset development and product development – have been also discussed in addition to the brief descriptions of some real life cases implemented on Aurora.
The Importance of Race in Juvenile Commitment in the New Jersey Family Court

In this study, we examine how important juvenile race and other factors are in juvenile commitment classification in the New Jersey Family Court. Data from the Family Court in New Jersey for the year 2010 comprise the population. Given the class imbalance in the dependent variable, we employ balanced random forest (RF). Variable importance plots and an information gain summary are used to assess the role of the juvenile’s race and other variables for classes of the dependent variable. The results from balanced RF indicate that the juvenile’s delinquency history and the offense seriousness make the most important contributions to commitment to juvenile state incarceration. The juvenile’s race makes a very weak contribution to commitment; in fact, when the balanced RF was rerun with the juvenile’s race omitted, the estimated misclassification error slightly dropped for commitments. Balanced RF is an attractive procedure for handling dependent variables with highly imbalanced classes. The juvenile’s adjudication history and offense seriousness emerged as the most important variables to state incarceration. The race of the juvenile was not an important variable with respect to commitment.
Theoretical properties of Cook’s PFC dimension reduction algorithm for linear regression

We analyse the properties of the Principal Fitted Components (PFC) algorithm proposed by Cook. We derive theoretical properties of the resulting estimators, including sufficient conditions under which they are $\sqrt{n}$-consistent, and explain some of the simulation results given in Cook's paper. We use techniques from random matrix theory and perturbation theory. We argue that, under Cook's model at least, the PFC algorithm should outperform the Principal Components algorithm.
Framework Based on Privacy Policy Hiding for Preventing Unauthorized Face Image Processing

We put forward a framework to address a problem created by the rapidly spreading use of imaging devices and related to involuntarily or unintentionally photographed individuals: their pictures can accumulate additional meta information via face recognition systems and can be manually tagged via social networks and publishing platforms. With this framework a user can express his/her picture privacy policy in a machine readable format and (to some extent) automatically enforce it. An easily understandable flag system is used to define restrictions on picture usage and link ability. This policy is encoded in an unobtrusive way into wardrobe patterns and accessory designs with almost no impact on apparel appearance or social interaction.
Benefits of SOA: Evaluation of an implemented scenario against alternative architectures

Service-oriented architecture (SOA) is based on a design principle for business software systems. The SOA movement has taken up momentum, especially because of widespread middleware vendor support, e.g. by IBM, HP, BEA, Microsoft, Sun, Software AG, TIBCO, Oracle, SAP and others. Still answers to questions of how the target architecture should look like and what the advantages over other architectures are remain open. We have implemented a scenario based on free software, which consists of a well-defined service-oriented target architecture. In this article, we compare the used service-oriented approach with other state-of-theart architectures to show that changeability and efficiency improve compared to alternative architectures.
Spatial Metadata for Remote Sensing Imagery

Mining the petabyte and growing archive of remotely sensed images to obtain the necessary information for land cover change studies becomes more difficult as more imagery is obtained and stored at various locations by government agencies or private companies. The increasing importance of networking with the requirement to move data sets between different servers and clients makes the data volume problem particularly acute. Mitigating this problem requires using data efficiently, that is, using data at the appropriate scale and resolution to adequately characterize phenomena, thus providing accurate answers to the questions being asked. This requires a thorough understanding of the effects of adjusting image resolution to match the resolution of images from other sources or supporting data for biophysical or urban growth models. This paper summarizes a NASA Intelligent Systems-funded project that is examining the use of fractals and geostatistical techniques as aids to image classification and segmentation, as indicators of the effects of image processing techniques such as rectification, rescaling, ratioing and classification, as indicators for change detection, and as metadata for mining and selecting appropriate imagery for global change studies. This project will provide benchmarked indices of image complexity that complement existing metadata schemas and will facilitate image retrieval and analysis. This will streamline global change investigations by quickly identifying the proper source, lineage, general image content, scale, and resolution of imagery suited to an analysis of anthropogenic alterations in land cover, thus allowing researchers to concentrate on the underlying physical processes and potential consequences of these changes.
Self-regulation resources and physical activity participation among adults with type 2 diabetes

Physical activity plays a crucial role in the prevention and treatment of type 2 diabetes. Therefore, it is important to understand why so few adults with type 2 diabetes regularly engage in physical activity. The role of self-regulation in the context of health-related behavior adherence, especially in terms of physical activity engagement and adherence, has largely been reviewed based on the strength energy model. Building on this line of research, the aim of this theoretical work was to highlight how self-regulation and ego depletion can influence the lower rate of physical activity participation among adults with type 2 diabetes, compared to adults from the general population.
Elimination of lexical ambiguities by grammars: The ELAG system

We present a new, INTEX-compatible formalism for the description of distributional constraints, ELAG (Elimination of lexical ambiguity by grammars). The constraints may be checked against text, and the lexical ambiguity of the text may thus be partly resolved. We describe and exemplify the main properties of ELAG with the aid of simple rules, formalizing exploitable constraints. We specify in detail the effect of applying an ELAG rule or grammar to a text. We examine the practical properties of the formalism from the point of view of a rule writer. We describe our evaluation procedure for the lexical disambiguation results.
Interaction of a plant virus-encoded protein with the major nucleolar protein fibrillarin is required for systemic virus infection

The nucleolus and specific nucleolar proteins are involved in the life cycles of some plant and animal viruses, but the functions of these proteins and of nucleolar trafficking in virus infections are largely unknown. The ORF3 protein of the plant virus, groundnut rosette virus (an umbravirus), has been shown to cycle through the nucleus, passing through Cajal bodies to the nucleolus and then exiting back into the cytoplasm. This journey is absolutely required for the formation of viral ribonucleoprotein particles (RNPs) that, themselves, are essential for the spread of the virus to noninoculated leaves of the shoot tip. Here, we show that these processes rely on the interaction of the ORF3 protein with fibrillarin, a major nucleolar protein. Silencing of the fibrillarin gene prevents long-distance movement of groundnut rosette virus but does not affect viral replication or cell-to-cell movement. Repressing fibrillarin production also localizes the ORF3 protein to multiple Cajal body-like aggregates that fail to fuse with the nucleolus. Umbraviral ORF3 protein and fibrillarin interact in vitro and, when mixed with umbravirus RNA, form an RNP complex. This complex has a filamentous structure with some regular helical features, resembling the RNP complex formed in vivo during umbravirus infection. The filaments formed in vitro are infectious when inoculated to plants, and their infectivity is resistant to RNase. These results demonstrate previously undescribed functions for fibrillarin as an essential component of translocatable viral RNPs and may have implications for other plant and animal viruses that interact with the nucleolus.
Understanding Movement as Input for Interaction-a study of Two EyeToy(tm) Games

Interaction between people and computers can now be driven by movements of the human body without the need for mediation by other input devices. We present a way of conceptualising movement-based interaction. Our approach uses two existing frameworks for investigation of the relationship between bodily actions and the corresponding response from technology. The first framework examines characteristics of an interface in terms of “Sensible, Sensable, and Desirable” movement properties. In the second framework movement is seen as a form of “communication” between the user and technology, and the analysis looks at the implications this has for realising the interaction.
Dynamic Differential Evolution for Constrained Real-Parameter Optimization

Differential evolution (DE) has been shown to be a simple and effective evolutionary algorithm for global optimization both in benchmark test functions and many real-world applications. This paper introduces a dynamic differential evolution (D-DE) algorithm to solve constrained optimization problems. In D-DE, a novel mutation operator is firstly designed to prevent premature. Secondly, the scale factor F and the crossover probability CR are dynamic and adaptive to be beneficial for adjusting control parameters during the evolutionary process, especially, when done without any user interaction. Thirdly, D-DE uses orthogonal design method to generate initial population and reinitialize some solutions to replace some worse solutions during the search process. Finally, D-DE is validated on 6 benchmark test functions provided by the CEC 2006 special session on constrained real-parameter optimization. The experimental results obtained by D-DE are explained and discussed, and some conclusions are also drawn.
Functionally Distinct Transmission of Human Immunodeficiency Virus Type 1 Mediated by Immature and Mature Dendritic Cells

ABSTRACT Dendritic cells (DCs) potently stimulate the transmission of human immunodeficiency virus type 1 (HIV-1) to CD4+ T cells. Immature DCs (iDCs) located in submucosal tissues can capture HIV-1 and migrate to lymphoid tissues, where they become mature DCs (mDCs) for effective antigen presentation. DC maturation promotes HIV-1 transmission; however, the underlying mechanisms remain unclear. Here we have compared monocyte-derived iDCs and mDCs for their efficiencies and mechanisms of HIV-1 transmission. We have found that mDCs significantly facilitate HIV-1 endocytosis and efficiently concentrate HIV-1 at virological synapses, which contributes to mDC-enhanced viral transmission, at least in part. mDCs were more efficient than iDCs in transferring HIV-1 to various types of target cells independently of C-type lectins, which partially accounted for iDC-mediated HIV-1 transmission. Efficient HIV-1 trans-infection mediated by iDCs and mDCs required contact between DCs and target cells. Moreover, rapid HIV-1 degradation occurred in both iDCs and mDCs, which correlated with the lack of HIV-1 retention-mediated long-term viral transmission. Our results provide new insights into the mechanisms underlying DC-mediated HIV-1 transmission, suggesting that HIV-1 exploits mDCs to facilitate its dissemination within lymphoid tissues.
Simultaneous characterization of efferent and afferent connectivity, neuroactive substances, and morphology of neurons.

We present a method for establishing in a single experiment four characteristics of individual neurons: the efferent and afferent connectivity, the morphology, and the content of a particular neuroactive substance. The connectivity of the neurons is determined by retrograde fluorescent tracing with Fast Blue and anterograde tracing with the lectin Phaseolus vulgaris leucoagglutinin (PHA-L). After fixation, the brain is cut into 300-micron thick slices. Neurons containing retrogradely transported Fast Blue are intracellularly injected with the fluorescent dye Lucifer Yellow to fill their dendritic trees. The slices are then resectioned at 20-40 microns. One section through the soma of a Lucifer Yellow-filled neuron is selected for the detection of a neuroactive substance contained by this cell [immunofluorescence, secondary antiserum conjugated to tetramethylrhodamine (TRITC)]. Using appropriate filtering, it can be determined in the fluorescence microscope whether a Lucifer Yellow-containing cell body has also been labeled with TRITC, i.e., whether it is immunoreactive for this neuroactive substance. The adjacent sections are subjected to dual peroxidase immunocytochemistry with different chromogens to visualize the PHA-L-labeled afferent fibers (nickel-enhanced diaminobenzidine, blue-black reaction product) and to stabilize the Lucifer Yellow (diaminobenzidine, brown reaction product) in the dendrites of the intracellular injected cells. The other sections are used for electron microscopic visualization of the transported PHA-L. The relationships between the PHA-L-labeled afferent fibers (blue color) and the dendrites of the intracellularly Lucifer Yellow-injected, retrogradely Fast Blue-labeled cells (brown color) are studied by light microscopy. The electron microscope supplies ultrastructural data on the PHA-L-labeled axon terminals.
EVOLUTIONARY LEARNING OF RICH NEURAL NETWORKS IN THE BAYESIAN MODEL SELECTION FRAMEWORK

In this paper we focus on the problem of using a genetic algorithm for model selection within a Bayesian framework. We propose to reduce the model selection problem to a search problem solved using evolutionary computation to explore a posterior distribution over the model space. As a case study, we introduce ELeaRNT (Evolutionary Learning of Rich Neural Network Topologies), a genetic algorithm which evolves a particular class of models, namely, Rich Neural Networks (RNN), in order to find an optimal domain-specific non-linear function approximator with a good generalization capability. In order to evolve this kind of neural networks, ELeaRNT uses a Bayesian fitness function. The experimental results prove that ELeaRNT using a Bayesian fitness function finds, in a completely automated way, networks well-matched to the analysed problem, with acceptable complexity.
Engineering Virtual Cardiac Tissue

The kinetics of proteins involved in ion transfer, sequestration and binding in cardiac cells can be modelled to construct a model of the electrical activity of isolated cardiac cells as a system of ordinary differential equations. These cell models may be incorporated into tissue models, which, when combined with histology and anatomy, form virtual tissues. The effects of changes in specific protein expression, or changes in protein kinetics, produced by mutations or pharmacological agents, can be simulated using these tissue models and used to account for the whole organ effects of changes in specific ion-transport protein activity.
Triangular decomposition of semi-algebraic systems

Regular chains and triangular decompositions are fundamental and well-developed tools for describing the complex solutions of polynomial systems. This paper proposes adaptations of these tools focusing on solutions of the real analogue: semi-algebraic systems. We show that any such system can be decomposed into finitely many regular semi-algebraic systems. We propose two specifications of such a decomposition and present corresponding algorithms. Under some assumptions, one type of decomposition can be computed in singly exponential time w.r. t. the number of variables. We implement our algorithms and the experimental results illustrate their effectiveness.
The design of CMOS cellular neural network (CNN) using the neuron-bipolar junction transistor (/spl nu/BJT)

In this paper, two CMOS implementations of the cellular neural network (CNN) are presented based on the neuron-bipolar junction transistor (/spl nu/BJT) which consists of the parasitic PNP bipolar junction transistor and the spreading base resistor array in the CMOS process. In the first design, the /spl nu/BJT is used to implement the neuron and weights of the cell. In the second design, it is used to implement the current summation and weights of the cell, and a diode structure is proposed to realize the neuron. For programmable capability the resistor in the /spl nu/BJT can be replaced by a tunable MOS resistor. The two kinds of circuits have been designed and fabricated in 0.6 /spl mu/m single-poly-triple-metal n-well CMOS process.
Scenario generation for nancial modelling : Desirable properties and a case study

Investment decisions are made ex ante, that is based on parameters that are not known at the time of decision making. Scenario generators are used not only in the models for (optimum) decision making under uncertainty, they are also used for evaluation of decisions through simulation modelling. In this paper, we review those properties of scenario generators which are regarded as desirable; these are not suf cient to guarantee the goodness of a scenario generator. We also review classical models for scenario generation of asset prices. In particular we consider some recently reported methods which have been proposed for distributions with `heavy tails'.
Enhanced survival of autoepidermal-allodermal composite grafts in allosensitized animals by use of silver-nylon dressings and direct current.

OBJECTIVE Observe the effect of silver-nylon (SN) dressing and direct electric current on healing of meshed autoepidermal/allodermal composite skin grafts (MCSGs) in allosensitized rats. MATERIALS AND METHODS MCSGs were placed on experimental animals 28 to 30 days after placement of sensitizing allografts. MCSGs and control allografts were covered with either Vaseline gauze (VG) or SN; direct current, 40 microA, was applied for 5 days to some of the SN-dressed wounds (SNDCs). MEASUREMENTS AND MAIN RESULTS Second set rejection of MCSG was not observed. SN- and SNDC-treated grafts showed expansion of the meshed autoepidermis with complete epithelialization within 3 weeks. VG-covered wounds developed areas of open granulation and were not completely epithelialized at 3 months. Both SN and SNDC reduced wound contraction when compared to VG (SN versus VG p < 0.02, SNDC versus VG p < 0.008). MCSG was found to be of low alloantigenicity in that it did not induce second set rejection of subsequent skin allograft. CONCLUSIONS SN dressings enhanced survival of meshed composite skin grafts.
Cognitive Behavioral Therapy as an Effort to Improve Self Acceptance of Adolescents in Orphanage

Received: February 22, 2017 Revised: March 29, 2017 Accepted: August 04, 2017 Abstract: Background: The Ministry of Social Affairs found several relevant facts about the condition of child care in orphanages across five cities in Indonesia, among others is the lack of attention to the fulfillment of emotional needs and psychosocial development. This problem persists despite the knowledge that major changes in maturity and psychosocial development, particularly associated with the social function, progressed greatly during adolescence, increasing the need for intensive psychological assistance during self-discovery. The process of self-discovery always begins with self-acceptance.
A REVIEW OF LOW LEVEL VISUAL FEATURES FORA CONTENT BASED MEDICAL IMAGE RETRIEVAL SYSTEM

Medical imaging is a precious and essential tool in healthcare systems, helps the physicians to emanate good quality of treatment. The advancement in medical Technology has resulted in a huge number of medical images which are stored in a database for future purpose. It is very imperative to build an effective retrieval system which browse through entire database in diagnosing the various diseases, helping the therapeutic process and in supporting the medical decision makingprocess. Content based Image Retrieval (CBIR) assists in retrieving the required medical images from a huge database on the basis of their visual features like shape, color and texture. Medical images are generally represented in gray level rather than color. Feature extraction plays an important role in an ever-increasing the performance of the medical image retrieval system. This paper presents a various multiple feature extraction techniques for effective content based medical image retrieval system.
Efficient tracking with the Bounded Hough Transform

The Bounded Hough Transform is introduced to track objects in a sequence of sparse range images. The method is based upon a variation of the General Hough Transform that exploits the coherence across image frames that results from the relationship between known bounds on the object's velocity and the sensor frame rate. It is extremely efficient, running in O(N) for N range data points, and effectively trades off localization precision for runtime efficiency. The method has been implemented and tested on a variety of objects, including freeform surfaces, using both simulated and real data from Lidar and stereovision sensors. The motion bounds allow the inter-frame transformation space to be reduced to a reasonable, and indeed small size, containing only 729 possible states. In a variation, the rotational subspace is projected onto the translational subspace, which further reduces the transformation space to only 54 states. Experimental results confirm that the technique works well with very sparse data, possibly comprising only tens of points per frame, and that it is also robust to measurement error and outliers.
Using Chimeric Mice with Humanized Livers to Predict Human Drug Metabolism and a Drug-Drug Interaction

Interspecies differences in drug metabolism have made it difficult to use preclinical animal testing data to predict the drug metabolites or potential drug-drug interactions (DDIs) that will occur in humans. Although chimeric mice with humanized livers can produce known human metabolites for test substrates, we do not know whether chimeric mice can be used to prospectively predict human drug metabolism or a possible DDI. Therefore, we investigated whether they could provide a more predictive assessment for clemizole, a drug in clinical development for the treatment of hepatitis C virus (HCV) infection. Our results demonstrate, for the first time, that analyses performed in chimeric mice can correctly identify the predominant human drug metabolite before human testing. The differences in the rodent and human pathways for clemizole metabolism were of importance, because the predominant human metabolite was found to have synergistic anti-HCV activity. Moreover, studies in chimeric mice also correctly predicted that a DDI would occur in humans when clemizole was coadministered with a CYP3A4 inhibitor. These results demonstrate that using chimeric mice can improve the quality of preclinical drug assessment.