Miracle-dz/UniFAR-FTUs huggingface dataset:
Point of Interest Awareness using Indoor Positioning with a Mobile Phone

Although location based applications have been gaining popularity, most positioning devices do not work when in an indoor environment, hindering the development of both mixed and indoor location based applications. In this paper we present a point of interest aware application that shows information to the user that is dependent on his indoor location. To be able to detect the user’s position, we propose a technique, based on the detection of footsteps, and the direction in which they were taken, to be able to calculate the position of the user inside a building. To improve the accuracy of the system, we use information about the buildings floor plan to create a graph that can be used to correct invalid movements.
Transcriptional and Metabolic Changes Associated to the Infection by Fusarium verticillioides in Maize Inbreds with Contrasting Ear Rot Resistance

Fusarium verticillioides causes ear rot and grain mycotoxins in maize (Zea mays L.), which are harmful to human and animal health. Breeding and growing less susceptible plant genotypes is one alternative to reduce these detrimental effects. A better understanding of the resistance mechanisms would facilitate the implementation of strategic molecular agriculture to breeding of resistant germplasm. Our aim was to identify genes and metabolites that may be related to the Fusarium reaction in a resistant (L4637) and a susceptible (L4674) inbred. Gene expression data were obtained from microarray hybridizations in inoculated and non-inoculated kernels from both inbreds. Fungal inoculation did not produce considerable changes in gene expression and metabolites in L4637. Defense-related genes changed in L4674 kernels, responding specifically to the pathogen infection. These results indicate that L4637 resistance may be mainly due to constitutive defense mechanisms preventing fungal infection. These mechanisms seem to be poorly expressed in L4674; and despite the inoculation activate a defense response; this is not enough to prevent the disease progress in this susceptible line. Through this study, a global view of differential genes expressed and metabolites accumulated during resistance and susceptibility to F. verticillioides inoculation has been obtained, giving additional information about the mechanisms and pathways conferring resistance to this important disease in maize.
The Influence of Professionals' Empathy on Parents' Anxiety in Cases of Juvenile Criminology.

In situations of juvenile delinquency, abuse, or neglect, determination of child custody relies on interviews with parents. This study aims to examine the effects of the interviewer's empathy on parents' anxiety, and to explore how parents experience these situations. A measure of anxiety was applied to 41 parents under evaluation for child custody before and after the assessment interview. Professionals' empathy was rated by both parents and professionals after each appointment. Parents participated in semistructured interviews. Data were analyzed through statistical and content analyses. The decrease in anxiety was significantly greater for parents who perceived professionals as "perfect" than for parents who perceived professionals as "less than perfect" in empathy. Parents' and professionals' empathy scores correlated positively, but the association between professionals' self-rated empathy and parents' anxiety was nonsignificant. Reactions to the justice system's intervention emerging in the semistructured interviews were "unjustifiable intrusion," "disconcerting information," and "reality confirmation. " Each associated differently with parents' expectations for the assessment interview (respectively, that the process be over quickly, that it be over successfully, and that help start quickly). Our results support the important effects, from parents' perspectives, of empathy in assessment interviews in the context of juvenile criminology.
Evaluating vendor's performance in outsource software development risks using analytic hierarchy process technique

Outsource software development approach has been recognized as an important practice in government agencies as well as in private sectors. It includes third parties role and involvement in IT implementation and thus this approach has certain level of risks that need to be identified, measured and managed. The benefits and reasons associated with outsourcing implementation are operation and development cost reduction, operational efficiency and improves service quality. Although there are advantages in this approach, but there are also risks that associated with it. In this study, a survey was conducted to recognize key risks involve in outsource software development and to access and classify risk's level and severity in the software project development and implementation. Then, the identified risks were analyzed using AHP technique to evaluate the performance of the vendors in outsourcing data collected in the organization. The evaluation was carried out with officers in The Rubber Industry Smallholders Development Authority or RISDA in Malaysia because this organization has experience in outsourcing for more than 15 years. The results categorize key risks associated with system software development and the method developed helps the organizations to manage risks based on the importance and harshness of the risk towards organisations. The proposed method is developed and established on risk analysis to measure performance of the vendors using multi-criteria selection method.
NEDindex: A new metric for community structure in networks

There are several metrics (Modularity, Mutual Information, Conductance, etc.) to evaluate the strength of graph clustering in large graphs. These metrics have great significance to measure the effectiveness and they are often used to find the strongly connected clusters with respect to the whole graph. In this paper, we propose a new metric to evaluate the strength of graph clustering and also study its applications. We show that our proposed metric has great consistency which is similar to other metrics and easy to calculate. Our proposed metric also shows consistency where other metrics fail in some special cases. We demonstrate that our metric has reasonable strength while extracting strongly connected communities in both simulated (in silico) data and real data networks. We also show some comparative results of our proposed metric with other popular metric(s) for Online Social Networks (OSN) and Gene Regulatory Networks (GRN).
Nonlinear Multiple Kernel Learning via Mixture of Probabilistic Kernel Discriminant Analysis

Multiple kernel learning (MKL) provides a powerful tool for heterogenous data integration. Most existing MKL formulations are based on a linear kernel combination, which, however, restricts the flexibility of the learning model. In this paper, we propose a novel nonlinear multiple kernel learning formulation based on the model combination. The proposed formulation (called MPKDA) is derived from a novel probabilistic model for kernel discriminant analysis (KDA) and its mixture. Experimental results on various real applications demonstrate that the proposed MPKDA model provides competitive performance comparing with the representative approaches. We also analyze the relationship between the proposed model and the existing KDA-based MKL formulations, and show how to use the proposed MPKDA model to handle missing data and perform localized multiple kernel learning (LMKL).
Novel illumination-normalization method based on region information

A region based illumination-normalization method which only uses gray level values in an image as information is proposed in this paper. The general purpose of illumination normalization is to reduce lighting effect when the testing images are captured in different environment and supplies useful and uniform data. We apply the algorithm in our face recognition system. The algorithm first divides the testing face images into two parts using homomorphic filtering method. One is the face feature, F0, and the other one is the illumination information, I0. Next, an illumination reference model is constructed from a set of normal face images. The illumination information of the testing face image is then adjusted according to the illumination reference model. The modified illumination information, Iα, and original face feature, F0, are at last combined to make up the normalized face image. The face recognition result is improved after the algorithm is applied.
Protein synthesis in vivo in rats fed on lipid-rich liquid diets

Changes in tissue composition and protein synthesis ratio were studied in the major tissues of the body in young rats fed on lipid-rich, isonitrogenous purified liquid diets, a convenient method for inducing voluntary overfeeding under controlled nutritional conditions. Overfed rats showed faster growth induced by the energy excess. Analysis of tissue composition (protein, DNA and RNA contents) revealed that growth was due mainly to tissue hyperplasia in which protein and DNA contents increased in parallel. Fractional protein synthesis ratio measured in vivo by the flooding-dose method of phenylalanine showed a marked increase in all tissues. This change could be attributed to an increase in the ribosomal activity for protein synthesis in most tissues. Therefore, our results indicate that addition of a supplementary energy source (as lipids) to a well-balanced diet improves growth and protein synthesis in growing rats.
Circuit Design for Testing Standard Cell Libraries

This work presents the design methodology and the architecture of simple, efficient and easy-to-use test circuits for evaluating and validating any set of library cells (combinational and sequential logic gates), both in the design environment and for on silicon prototyping. Evaluation and validation are accomplished considering functionality, performance, power consumption and impact in operation of nanometer aging effects. Simulation results demonstrate the behavior of the proposed design and the many facilities it provides.
Diversity of Lysophosphatidic Acid Receptor-Mediated Intracellular Calcium Signaling in Early Cortical Neurogenesis

Lysophosphatidic acid (LPA) is a membrane-derived lysophospholipid that can induce pleomorphic effects in neural progenitor cells (NPCs) from the cerebral cortex, including alterations in ionic conductance. LPA-induced, calcium-mediated conductance changes have been reported; however, the underlying molecular mechanisms have not been determined. We show here that activation of specific cognate receptors accounts for nearly all intracellular calcium responses evoked by LPA in acutely cultured nestin-positive NPCs from the developing mouse cerebral cortex. Fast-onset changes in intracellular calcium levels required release from thapsigargin-sensitive stores by a pertussis toxin-insensitive mechanism. The influx of extracellular calcium through Cd2+/Ni2+-insensitive influx pathways, approximately one-half of which were Gd3+ sensitive, contributed to the temporal diversity of responses. Quantitative reverse transcription-PCR revealed the presence of all five known LPA receptors in primary NPCs, with prominent expression of LPA1, LPA2, and LPA4. Combined genetic and pharmacological studies indicated that NPC responses were mediated by LPA1 (∼30% of the cells), LPA2 (∼30%), a combination of receptors on single cells (∼30%), and non-LPA1,2,3 pathways (∼10%). LPA responsivity was significantly reduced in more differentiated TuJ1+ cells within cultures. Calcium transients in a large proportion of LPA-responsive NPCs were also initiated by the closely related signaling lipid S1P (sphingosine-1-phosphate). These data demonstrate for the first time the involvement of LPA receptors in mediating surprisingly diverse NPC calcium responses involving multiple receptor subtypes that function within a single cell. Compared with other known factors, lysophospholipids represent the major activator of calcium signaling identified within NPCs at this early stage in corticogenesis.
An integrated perspective on diabetic, alcoholic, and drug-induced neuropathy, etiology, and treatment in the US

Neuropathic pain (NeuP) is a syndrome that results from damaged nerves and/or aberrant regeneration. Common etiologies of neuropathy include chronic illnesses and medication use. Chronic disorders, such as diabetes and alcoholism, can cause neuronal injury and consequently NeuP. Certain medications with antineoplastic effects also carry an exquisitely high risk for neuropathy. These culprits are a few of many that are fueling the NeuP epidemic, which currently affects 7%–10% of the population. It has been estimated that approximately 10% and 7% of US adults carry a diagnosis of diabetes and alcohol disorder, respectively. Despite its pervasiveness, many physicians are unfamiliar with adequate treatment of NeuP, partly due to the few reviews that are available that have integrated basic science and clinical practice. In light of the recent Centers for Disease Control and Prevention guidelines that advise against the routine use of μ-opioid receptor-selective opioids for chronic pain management, such a review is timely. Here, we provide a succinct overview of the etiology and treatment options of diabetic and alcohol- and drug-induced neuropathy, three different and prevalent neuropathies fusing the combined clinical and preclinical pharmacological expertise in NeuP of the authors. We discuss the anatomy of pain and pain transmission, with special attention to key ion channels, receptors, and neurotransmitters. An understanding of pain neurophysiology will lead to a better understanding of the rationale for the effectiveness of current treatment options, and may lead to better diagnostic tools to help distinguish types of neuropathy. We close with a discussion of ongoing research efforts to develop additional treatments for NeuP.
Cross-core event monitoring for processor failure prediction

A recent trend in the design of commodity processors is the combination of multiple independent execution units on one chip. With the resulting increase of complexity and transistor count, it becomes more and more likely that a single execution unit on a processor gets faulty. In order to tackle this situation, we propose an architecture for dependable process management in chip-multiprocessing machines. In our approach, execution units survey each other to anticipate future hardware failures. The prediction relies on the analysis of processor hardware performance counters by a statistical rank-sum test. Initial experiments with the Intel Core processor platform proved the feasibility of the approach, but also showed the need for further investigation due to a high prediction quality variation in most of the cases.
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution

In this paper, we introduce a new skeleton pruning method based on contour partitioning. Any contour partition can be used, but the partitions obtained by discrete curve evolution (DCE) yield excellent results. The theoretical properties and the experiments presented demonstrate that obtained skeletons are in accord with human visual perception and stable, even in the presence of significant noise and shape variations, and have the same topology as the original skeletons. In particular, we have proven that the proposed approach never produces spurious branches, which are common when using the known skeleton pruning methods. Moreover, the proposed pruning method does not displace the skeleton points. Consequently, all skeleton points are centers of maximal disks. Again, many existing methods displace skeleton points in order to produces pruned skeletons
GASIM: a fast Galois field based simulator for functional model

This paper presents a fast logic simulator based on Galois field. This is designed to act as an underlying tool for all finite field applications considering the fact that simulation plays an important role in all these applications. Three approaches for finite field representation and its evaluation are discussed. In addition an approach for normalizing the finite field based decision diagrams is also presented. The experimental results show the trade-off that can be made by using different design representations between spatial complexity and speed. Also the results show that it can be used in conventional simulation environment to achieve speedup.
Enjeux et controverses autour des études d'impact en microfinance. Comment concilier rigueur scientifique et pertinence opérationnelle ?

Les etudes d'impact en microfinance ne constituent pas un champ stabilise. Elles sont un lieu de rencontre entre trois grands referentiels, animes par differents types d'acteurs, et porteurs de normes propres : le referentiel scientifique, regi par des criteres de rigueur, d'objectivite et de verifiabilite des resultats ; le referentiel developpementaliste, centre (au moins en theorie) sur des principes de demande et de participation des acteurs, d'adaptation aux situations specifiques locales ; le referentiel operationnel enfin, avec ses criteres d'efficacite, de relation cout-benefice, de satisfaction des clients/usagers. Par ailleurs, au sein du referentiel scientifique, les etudes d'impact continuent de poser des defis conceptuels et methodologiques, qui alimentent les controverses. La mise en coherence de ces referentiels par les differentes parties prenantes est par consequent loin d'aller de soi (Bouquet 2006).
Towards red‐edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) simulated data

Several methods for extracting the chlorophyll sensitive red‐edge position (REP) from hyperspectral data are reported in literature. This study is a continuation of a recent paper published as ‘A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method’. The method was validated experimentally for estimation of foliar nitrogen concentrations of rye, maize and mixed grass/herb. The objective of this study was to test the utility of the linear extrapolation method under different conditions including variable canopy biophysical parameters, solar zenith angle, sensor noise and spectral bandwidth. REPs were extracted from synthetic canopy spectra that were simulated using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) radiative transfer models. REPs extracted by the linear extrapolation method involving wavebands at 680, 694, 724 and 760 nm produced the highest correlation (R 2 = 0.75) with leaf chlorophyll content with minimal effects of leaf and canopy biophysical confounders (leaf area index, leaf inclination distribution and leaf dry matter content) compared to traditional techniques including the linear interpolation, inverted Gaussian modelling and polynomial fitting techniques. In addition, the new technique is insensitive to changes in solar zenith angle. However, the advantage of using the linear extrapolation method compared to the various alternative methods diminishes with increasing sensor noise and decreasing spectral resolution. In summary, the linear extrapolation technique confirms its high potential for leaf chlorophyll estimation. The efficacy of the technique under field conditions needs to be established.
Modeling the electric field of weakly electric fish

SUMMARY Weakly electric fish characterize the environment in which they live by sensing distortions in their self-generated electric field. These distortions result in electric images forming across their skin. In order to better understand electric field generation and image formation in one particular species of electric fish, Apteronotus leptorhynchus, we have developed three different numerical models of a two-dimensional cross-section of the fish's body and its surroundings. One of these models mimics the real contour of the fish; two other geometrically simple models allow for an independent study of the effects of the fish's body geometry and conductivity on electric field and image formation. Using these models, we show that the fish's tapered body shape is mainly responsible for the smooth, uniform field in the rostral region, where most electroreceptors are located. The fish's narrowing body geometry is also responsible for the relatively large electric potential in the caudal region. Numerical tests also confirm the previous hypothesis that the electric fish body acts approximately like an ideal voltage divider; this is true especially for the tail region. Next, we calculate electric images produced by simple objects and find they vary according to the current density profile assigned to the fish's electric organ. This explains some of the qualitative differences previously reported for different modeling approaches. The variation of the electric image's shape as a function of different object locations is explained in terms of the fish's geometrical and electrical parameters. Lastly, we discuss novel cues for determining an object's rostro-caudal location and lateral distance using these electric images.
Test Case Generation and Test Data Extraction Techniques

113803-9191 IJECS-IJENS © June 2011 IJENS I J E N S Abstract— the software testing immensely depends on three main phases: test case generation, test execution, and test evaluation. Test case generation is the core of any testing process; however, those generated test cases still require test data to be executed which makes the test data generation not less important than the test case generation. This kept the researchers during the past decade occupied with automating those processes which played a tremendous role in reducing the time and effort spent during the testing process. This paper explores different approaches that had emerged during the past decade regarding the generation of test cases and test data from different models as an emerging type of model based testing. Unified Modeling Language UML models took the greatest share from among those models. Many researchers had paid a great attention to optimizing and reducing the test cases rather than generating them; light is shed on some of those approaches as well.