Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Renal Histological Changes in Alloxan-Induced Diabetic Rats

Diabetes mellitus is a progressive disease. Most investigators have focused on glomerular changes in diabetic kidney and non-glomerular alterations have been less attended. The present study has been conducted to find early non-glomerular histological changes in diabetic renal tissue. Twenty male Wistar rats weighting 200-250 g were used for the diabetic group. Diabetes mellitus was induced by single injection of Alloxan. After 8 weeks, paraffin embedded blocks of kidneys were prepared for evaluating the histological changes due to diabetes. Histological study showed the deposit of eosinophilic materials in the intermediate substantial of medulla and thickening of renal arterial wall in the kidney of 70% of diabetic rats. The average weight of kidneys increased when compared to non diabetic animals. Furthermore, the amount of blood flow in arteries of all diabetic kidneys has been enhanced. The present study demonstrates some early renal histological changes in diabetes mellitus which were earlier compared to those reported previously. Diabetic nephropathy is a progressive disease and renal care design can help better prognosis achievement.
International Conference on Computational Science , ICCS 2013 n-step FM-Index for faster pattern matching

Fast pattern matching is a requirement for many problems, specially for bioinformatics sequence analysis like short read mapping applications. This work presents a variation of the FM-index method, denoted n-step FM-index, that is applied in exact match genome search. We propose an alternative two-dimensional FM-index structure that allows backward-search navigation giving steps of n symbols at a time. The main advantages of this arrangement are the reduction of the computational work, but most importantly, the reduction by n of the chain of dependent data accesses, and the increase in the temporal locality of the data access pattern. This benefit comes at the expense of increasing the total amount of data required for the index. We present an in-depth performance analysis of a multi-core implementation of the algorithm using large references (up to 1.5G). We identify memory latency as the major performance limiter for single-thread execution and memory bandwidth for multi-thread execution. Our proposal provides speedups ranging from 1.4× to 2.4×, when there is no limitation on DRAM capacity. We also analyse the trade-off of compacting the proposed data structure in order to reduce memory capacity requirements, now at the expense of increasing execution time. An extra 33% of DRAM space allows our proposal to improve performance by 1.2×, while doubling DRAM size enables an additional 1.5×. Our proposal of n-step algorithm provides an alternative for pseudo-random memory access algorithms to be redesigned to scale in current and future computer systems.
Coupled Resonator Diplexer for LTE-Advanced System

This paper presents the design of a microstrip hairpin diplexer. The design is based on coupledresonator structure using U-Shaped resonators. It is designed to meet The Long Term Evolution-Advanced (LTEA) system Band 7, operating at uplink (UL): 2.50–2.57 GHz and downlink (DL): 2.62–2.69 GHz for base transceiver station antenna. The structure has three ports with 10-coupled resonators with direct coupling to produce diplexer with chebyshev filtering response. The diplexer does not involve any external junctions for distribution of energy, so it can be miniaturized in comparison to conventional diplexers.
A Correlational Analysis of Test Anxiety and Response Time on a Computerized Adaptive Math Test among Seventh Grade Students by Gender.

Studies have shown that test anxiety has become more prevalent since the adoption of the No Child Left Behind Act in 2001 and that test anxiety negatively affects student achievement. Early research viewed test anxiety as being a unidimensional construct; however, recent research has purported that test anxiety is a multidimensional construct. Consequently, test anxiety being viewed as multidimensional has changed how test anxiety is measured as evidenced by the development of multidimensional test anxiety measurement scales. Literature indicates that there is a gap in the study of K-12 test anxiety and response time data on assessments. A nonexperimental correlational research design was used for this study. The purpose of this study was to examine the relationships between multidimensional test anxiety measures and the response time of students taking a computerized adaptive math assessment, the ® (MAP) by the Northwest Evaluation Association (NWEA), while controlling for gender. Participants for the study were 215 seventh grade math students at a school in the West. The test anxiety of participants was measured using the Children’s Test Anxiety Scale (CTAS). The response time data was captured by the NWEA MAP math tests. Spearman correlations were used to examine the relationship between test anxiety and response time. No statistically significant relationships were found. Recommendations for future research are to examine relationships between test anxiety and RTE using different normative thresholds (NT) and utilizing other multidimensional test anxiety scales as they become commercially available. : computerized adaptive testing, deficit model, expectancy theory, interference model, response time, test anxiety Measures of Academic Progress
Maximum Entropy Models for Realization Ranking

In this paper we describe and evaluate different statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. Three models are trained and tested; an n-gram language model, a discriminative maximum entropy model using structural features, and a combination of these two. Our realization component forms part of a larger, hybrid MT system.
A Novel Use of Higher Order Information to Detect Inliers of an Implicit Model

The problem we address in this paper is to label datapoints when the information about them is provided primarily in terms of their subsets or groups. The knowledge we have for a group is a likelihood value for each group member to belong to same class. These likelihood values are computed using a model, either explicit or implicit, of the pattern we wish to learn. By deﬁning a Markov Random Field (MRF) over the labels of data, we formulate the problem as an MRF inference problem. A submodular function is deﬁned as clique potential function for this MRF. We identiﬁed a special form of this clique potential function that results in a simple and eﬃcient inference method with linear running time with respect to the number of datapoints and subsets. The formulation allows augmentation of energy functions for data with several diﬀerent size subsets. We present experimental results in applications where the proposed method produces improved performances over other methods.
International Journal of Behavioral Nutrition and Physical Activity Global Positioning System: a New Opportunity in Physical Activity Measurement

Accurate measurement of physical activity is a prerequisite to monitor population physical activity levels and design effective interventions. Global Positioning System (GPS) technology offers potential to improve the measurement of physical activity. This paper 1) reviews the extant literature on the application of GPS to monitor human movement, with a particular emphasis on free-living physical activity, 2) discusses issues associated with GPS use, and 3) provides recommendations for future research. Overall findings show that GPS is a useful tool to augment our understanding of physical activity by providing the context (location) of the activity and used together with Geographical Information Systems can provide some insight into how people interact with the environment. However, no studies have shown that GPS alone is a reliable and valid measure of physical activity.
Teaching Social Communication Skills Through Human-Agent Interaction

There are a large number of computer-based systems that aim to train and improve social skills. However, most of these do not resemble the training regimens used by human instructors. In this article, we propose a computer-based training system that follows the procedure of social skills training (SST), a well-established method to decrease human anxiety and discomfort in social interaction, and acquire social skills. We attempt to automate the process of SST by developing a dialogue system named the automated social skills trainer, which teaches social communication skills through human-agent interaction. The system includes a virtual avatar that recognizes user speech and language information and gives feedback to users. Its design is based on conventional SST performed by human participants, including defining target skills, modeling, role-play, feedback, reinforcement, and homework. We performed a series of three experiments investigating (1) the advantages of using computer-based training systems compared to human-human interaction (HHI) by subjectively evaluating nervousness, ease of talking, and ability to talk well; (2) the relationship between speech language features and human social skills; and (3) the effect of computer-based training using our proposed system. Results of our first experiment show that interaction with an avatar decreases nervousness and increases the user's subjective impression of his or her ability to talk well compared to interaction with an unfamiliar person. The experimental evaluation measuring the relationship between social skill and speech and language features shows that these features have a relationship with social skills. Finally, experiments measuring the effect of performing SST with the proposed application show that participants significantly improve their skill, as assessed by separate evaluators, by using the system for 50 minutes. A user survey also shows that the users thought our system is useful and easy to use, and that interaction with the avatar felt similar to HHI.
How did Homo Heuristicus Become Ecologically Rational?

Gigerenzer and colleagues have proposed the ‘adaptive toolbox of heuristics’ as an account of resource-bounded human decision-making. According to these authors, evolution has endowed such toolboxes with ‘ecological rationality’, defined as the ability to make good quality decisions in their specific environments. Here we explore to what extent the mechanisms of evolution alone can produce ecologically rational toolboxes. We present a formal argument for why evolution is unlikely to produce ecologically rational toolboxes given the astronomically large space of possible toolboxes. The probability of finding one or more ecologically rational toolboxes in this space is negligibly small, even granting an evolutionary time scale of searching for it. We furthermore present artificial evolution simulations results that show that evolution can produce toolboxes of heuristics that are ‘good enough’ to survive, but that those toolboxes are not ecologically rational (in agreement with our formal argument). Our results do not rule out that ontogenetic adaptation processes (development and learning) may yield ecologically rational toolboxes, but it does put into question the idea that phylogenetic processes (evolution) could. We discuss the implications of our findings for future theoretical research on heuristic decision-making.
Bimanual Response Grouping in Dual-Task Paradigms

In three experiments we measured response time (RT) and peak force (PF) to investigate the grouping of left- and right-hand key press responses in a dual-task paradigm involving two independent go/no-go tasks. Within each task, a go stimulus within one of two modalities (i.e., visual versus auditory) required a response by one hand. In Experiment 1 with simultaneous go stimuli in the two tasks, responses appeared to be grouped in approximately 75–80% of trials, compared with nearly 100% grouping in a single-task condition requiring bimanual responses to the onset of any stimulus in either modality. In Experiment 2 with stimulus onset asynchronies (SOAs) of 0–400 ms between the two go stimuli, response grouping clearly declined as SOA increased, although some grouping was still evident even at the longest SOA. The same pattern was observed in Experiment 3 with the same range of SOAs but unpredictable stimulus order, suggesting that grouping is not strongly dependent on prior knowledge of the likely response order. These results emphasize the pervasiveness of response grouping in bimanual dual-task RT paradigms and provide useful clues as to its nature.
RNA-Catalyzed RNA Polymerization: Accurate and General RNA-Templated Primer Extension

The RNA world hypothesis regarding the early evolution of life relies on the premise that some RNA sequences can catalyze RNA replication. In support of this conjecture, we describe here an RNA molecule that catalyzes the type of polymerization needed for RNA replication. The ribozyme uses nucleoside triphosphates and the coding information of an RNA template to extend an RNA primer by the successive addition of up to 14 nucleotides—more than a complete turn of an RNA helix. Its polymerization activity is general in terms of the sequence and the length of the primer and template RNAs, provided that the 3′ terminus of the primer pairs with the template. Its polymerization is also quite accurate: when primers extended by 11 nucleotides were cloned and sequenced, 1088 of 1100 sequenced nucleotides matched the template.
Using dependency graphs to support collaboration over GitHub: The Neo4j graph database approach

Software Configuration Management Systems capture direct conflicts which arise due to concurrent editing of same shared artifact. However, indirect conflicts, arising due to concurrent editing of related artifacts by collaborative developers, might eventually evade the build process employed by the underlying SCM. Additional collaborative software development tools have been developed, that supplement existing SCM systems, by providing change awareness information about potential indirect conflicts. In this paper, we propose the tool named Collaboration Over GitHub (COG), that provides support for collaborative software development over GitHub and also captures indirect conflicts at finer levels of granularity. For this, COG converts project repositories into dependency graphs which are stored as Neo4j Graph Databases. These graphs store structural and dependency information obtained from codebases and are used for identifying conflicts and affected artifacts.
The gendered nature of men's filial care.

OBJECTIVES This paper investigates sociodemographic and family structure factors that predict men's involvement (n = 773) in different gendered dimensions of filial caregiving: traditionally male, gender neutral, and traditionally female care. METHODS The concepts that guide this research relate to family obligations or motivations to provide care, specifically, commitment to care, legitimate excuses, and caring by default. Data for this research come from the Work and Family Survey (1991-1993) conducted by the Work and Eldercare Research Group of CARNET: The Canadian Aging Research Network. RESULTS Although such factors as geographic proximity and sibling network composition predict men's involvement independent of the type of task, the gendered nature of the task is important in how other factors, such as filial obligation, parental status, education, and income influence involvement in care. DISCUSSION The findings suggest that, for traditionally male tasks, legitimate excuses or a commitment to care may play a more minor role in influencing men's involvement than is true for traditionally female tasks. Overall, this research demonstrates the importance of examining the gendered nature of the care tasks and highlights the value of the conceptual framework for explaining variations in men's filial care.
Reliability simulation of TMO RRAM

Combination with the RRAM analytic model with varation and the Monte Carlo simulator based on the microcosmic processes of oxygen vacancies and oxygen ion's generation, transportation and recombination, a TMO RRAM reliability simulation platform is developed to simulate and evaluate the main reliability issues of RRAM including retention, endurance, operation disturb considering the intrinsic variation.
Distributed demand scheduling method to reduce energy cost in smart grid

Smart grid has attracted attentions and expresses a view for the future power systems in the world. Demand Side Management(DSM) is a significant method in smart grid that helps the energy providers to shift behind the peak load. Some methods to reduce peak load have been studied in dynamic pricing. One of the purposes is to delay the demand to periods of low electricity price. The conventional scheduling method makes load curve that is inversely proportional to electricity prices as an objective load curve, and this strategy delay the expected demand curve as close as to the objective load curve. There is a problem, however, the scope of controlled object is limited and the whole load situation is not considered. This paper presents a method to smooth the demand situation of each house to reduce electricity prices by a Genetic Algorithm, in consideration of the amount of the whole demand and coordination between each group. The proposed method is able to give a higher value of objective to the group which has more shiftable demand, by adjusting the objective curve considering the delayable time. This feature makes the load as close as the object and reduces electricity price. Simulation results show that the proposed algorithm achieve the reduction of the peak load and the utility bill in smart grid.
Securing Distributed Wireless Sensor Networks: Issues and Guidelines

With the emergence of ubiquitous computing the role of sensor network is becoming more important which demands highest level security and energy efficiency. In this paper we have investigated the current available solutions and found that none of the solutions are completely meeting the basic security requirements such as authentication, access control, and non-repudiation, etc. Therefore we have proposed hypothetical framework called Tetra security framework for the distributed wireless sensor networks in order to achieve highest level security and overall energy efficiency
On the Structure of the Nonlinear Vacuum Solutions in Extended Electrodynamics

In this paper, in the frame of Extended Electrodynamics (EED), we study some of the consequences that can be obtained from the introduced and used by Maxwell equations complex structure \mathcal{J} in the space of 2-forms on \mathbb{R}^4, and also used in EED. First we give the vacuum EED equations with some comments. Then we recall some facts about the invariance group $G$ (with Lie algebra \mathcal{G}) of the standard complex structure $J$ in \mathbb{R}^2. After defining and briefly studying a representation of $G$ in the space of 2-forms on \mathbb{R}^4 and the joint action of $G$ in the space of \mathcal{G}-valued 2-forms on \mathbb{R}^4 we consider its connection with the vacuum solutions of EED. Finally we consider the case with point dependent group parameters and show that the set of the nonlinear vacuum EED solutions is a disjoint union of orbits of the $G$-action, noting some similarities with the quantim mechanical eigen picture and with the QFT creation and anihilation operators.
A monolithic 2.8 V, 3.2 W silicon bipolar power amplifier with 54% PAE at 900 MHz

This work presents a balanced two-stage monolithic power amplifier in Si bipolar technology for 0.8-1 GHz. On-chip transformers are used as input-baluns as well as for interstage matching. A closed-loop bias circuit is introduced to diminish break-down effects and increase the maximum usable supply voltage. The chip is operating from 2.8 V to 4.5 V. At 2.8 V the output power is 3.2 W with a power-added efficiency of 54%. The maximum output power of 7.7 W with an efficiency of 57% is achieved at 4.5 V supply voltage. The small-signal gain is 38 dB.
Two IP protection schemes for multi-FPGA systems

This paper proposes two novel protection schemes for multi-FPGA systems providing high security of IP designs licensed by IP vendors to system integrators and installed remotely in a hostile environment. In the first scheme, these useful properties are achieved by storing two different configuration keys inside an FPGA, while in the second scheme, they are obtained using a hardware white-box cipher for creating a trusted environment. Thanks to the proposed principles, FPGA configurations coming from different IP owners cannot be cloned or reverse-engineered by any involved party, including system integrator and other IP owners. The proposed schemes can be directly implemented in recent FPGAs such as Xilinx Spartan 6 and Virtex 6.
SITUATIONAL ARCHITECTURE ENGINEERING (SAE) - IMPROVING STRATEGIC CHANGE THROUGH ARCHITECTURE METHODS Ingénierie d'architecture en situation - Améliorer le changement stratégique au moyen de méthodes d'architecture

Market and environmental requirements call for constant changes in enterprises. To be able to record these changes in a structured way and to manage them it is helpful to use enterprise architectures as stable regulation frameworks. To support the development and the adaptation of the enterprise architectures there are numerous architecture methods (e.g. Zachman Framework, ARIS (Architecture of Integrated Information Systems), TOGAF (The Open Group Architecture Framework), DoDAF (Department of Defense Architecture Framework), BEN (Business Engineering Navigator), Semantic Object Model (SOM)), however, they often lack the necessary flexibility to enable a construction process adaptable to the given situation. This article presents a first approach towards making architecture methods flexible: meta models of the architecture frameworks of selected methods are generated and integrated into a joint meta model. The latter supports the situational adaptability of the enterprise architecture as the architecture method applied has been adapted.
Empowering geographically isolated communities with instant access to learning and training through satellite

Enabling learning for members of geographically isolated communities such as agrarian, or maritime communities presents benefits in terms of promoting regional development and cost savings for governments and companies. We present a methodology for designing a satellite and wireless based network infrastructure and learning services to support distance learning for such isolated communities. This methodology entails (a) the involvement of community members in the development of targeted learning services from an early stage and (b) a service-oriented approach to learning solution deployment. Here this methodology is applied in the context of the European research project BASE2 (BASE2 2006), in which the following two types of geographically isolated communities are considered: agrarian and maritime.
On the Use of Reservoir Computing in Popularity Prediction

Predicting the life cycle and the short-term popularity of a Web object is important for network architecture optimization. In this paper, we attempt to predict the popularity of a Web object given its historical access records using a novel neural network technique, reservoir computing (RC). The traces of popular videos at YouTube for five continuous months are taken as a case study. We compare RC with existing analytical models. Experimental results show that RC, given a 10-day trace composed of daily cumulative views for a video, is able to predict the next-day’s popularity with less than 5% relative square errors (RSEs). It is also demonstrated that RC achieves the best prediction performance among all compared models in longer-term prediction. The advantages and limitations of using RC in popularity prediction are discussed.