Miracle-dz/UniFAR-FTUs huggingface dataset:
The Morphological Changes in the Capillary Architecture of the Tibial Nerve Associated with Spontaneous Aging and Aerobic Exercise Intervention during Aging in Rats

[Purpose] Peripheral nerve degradation associated with aging is linked to failure of interactions in capillary metabolism. The aim of this study was to morphologically investigate the age-related changes in the capillary architecture of the tibial nerve in spontaneous aging and with aerobic exercise intervention in rats. [Subjects] Male Sprague-Dawley rats (n=15) were used in the present study. [Methods] The rats were divided into control (Cont, n=5), elderly (Elder, n=5), and elderly with aerobic exercise (Elder+Ex, n=5) groups. Aerobic training of low intensity was performed for 10 weeks using a treadmill starting at 96 weeks of age by the Elder+Ex group. The capillary diameter, cross-sectional area and number of microvascular ramifications in the tibial nerve were compared among the Cont (20-week-old), Elder (106-week-old) and Elder+Ex groups using three-dimensional images gained from confocal laser scanning microscopy. [Results] The capillary diameter, cross-sectional area and number of microvascular ramifications in the Elder group were significantly smaller than those observed in the Cont and Elder+Ex groups. [Conclusion] These findings suggest that the capillaries in the peripheral nerve degrade with spontaneous aging and that aerobic exercise of low intensity promotes angiogenesis, and protects the capillary from oxidative stress.
New engineering technique of software development

Computer software is an engine of growth of social-economy development which requires new engineering techniques and strategies. The demand for quality in software applications has grown. Hence as software becomes more integrated into our lives, the effects of software failures become more acute. Testing is an essential part of software development providing an indicator of the quality of the software. Testing remains the primary way to improve reliability of software. Billions of dollars are spent on testing in the software industry, as testing usually accounts for more than half the cost of software development.
Automatically organising images using concept hierarchies

In this paper we discuss the use of concept hierarchies, an approach to automatically organize a set of documents based upon a set of concepts derived from the documents themselves for image retrieval. Co-occurrence between terms associated with image captions and a statistical relation called subsumption are used to generate term clusters which are organized hierarchically. Previously, the approach has been studied for document retrieval and results have shown that automatically generating hierarchies can help users with their search task. In this paper we present an implementation of concept hierarchies for image retrieval, together with preliminary ad-hoc evaluation. Although our approach requires more investigation, initial results from a prototype system are promising and would appear to provide a useful summary of the search results.
Contentious sites: Cultural memory, collective organizing, and symbolic struggles over the Park51 Islamic center

Working from a Goffmanian dramaturgical perspective, this article analyzes the struggle between two opposing social movement coalitions formed in response to the proposed construction of an Islamic center near Ground Zero. To this end, the authors conducted in-depth interviews with leaders from key organizations involved in the conflict, in addition to participant observation at rallies and meetings of the different organizations involved. The authors find that despite great differences between the two conflicting sides, both coalitions experienced similar internal challenges that had to be managed when staging the performance for the public eye. The struggle over memory, space, and language strongly impacted how these actors understand coalition-building and mobilization. The article makes a contribution at the intersection between memory and dramaturgical studies applied to collective action.
Let Cognitive Radios Imitate: Imitation-based Spectrum Access for Cognitive Radio Networks

In this paper, we tackle the problem of opportunistic spectrum access in large-scale cognitive radio networks, where the unlicensed Secondary Users (SU) access the frequency channels partially occupied by the licensed Primary Users (PU). Each channel is characterized by an availability probability unknown to the SUs. We apply evolutionary game theory to model the spectrum access problem and develop distributed spectrum access policies based on imitation, a behavior rule widely applied in human societies consisting of imitating successful behavior. We first develop two imitation-based spectrum access policies based on the basic Proportional Imitation (PI) rule and the more advanced Double Imitation (DI) rule given that a SU can imitate any other SUs. We then adapt the proposed policies to a more practical scenario where a SU can only imitate the other SUs operating on the same channel. A systematic theoretical analysis is presented for both scenarios on the induced imitation dynamics and the convergence properties of the proposed policies to an imitation-stable equilibrium, which is also the $\epsilon$-optimum of the system. Simple, natural and incentive-compatible, the proposed imitation-based spectrum access policies can be implemented distributedly based on solely local interactions and thus is especially suited in decentralized adaptive learning environments as cognitive radio networks.
ADAT: An Adaptable Dynamic Analysis Tool for Race Detection in OpenMP Programs

Shared-memory based parallel programming with OpenMP and Posix-thread APIs is becoming more common to fully take advantage of multiprocessor computing environments. One of the critical risks in the multithreaded programming is data races which are hard to debug and greatly damaging to parallel applications if they are uncaughted. Although ample effort has been made in building specialized data race detection techniques, the state of art tools such as Intel thread checker still have various functionality and performance problems. In this paper, we present an efficient data race detection mechanism named ADAT (Adaptive Dynamic Analysis Tool). ADAT analyzes target program models to categorize the race engines (RDC: Race-Detection Classification) and then selects adequate engines to detect races automatically based upon the RDC (ECPS: Engine Code Property Selector). ADAT constructs an emperically optimal set of race engines in the aspect of labeling, filtering, and detection. In addition to RDC and ECPS, we have implemented an OpenMP parser and a source instrument or in ADAT to support OpenMP programs. The functionality and efficiency of ADAT are compared with those of Intel thread checker by using a set of OpenMP based kernel programs. The experimental results show that ADAT can detect data races with more challenging target program models and can achieve a couple of orders of magnitude faster processing time than Intel thread checker.
Microbial Cellulose Utilization: Fundamentals and Biotechnology

SUMMARY Fundamental features of microbial cellulose utilization are examined at successively higher levels of aggregation encompassing the structure and composition of cellulosic biomass, taxonomic diversity, cellulase enzyme systems, molecular biology of cellulase enzymes, physiology of cellulolytic microorganisms, ecological aspects of cellulase-degrading communities, and rate-limiting factors in nature. The methodological basis for studying microbial cellulose utilization is considered relative to quantification of cells and enzymes in the presence of solid substrates as well as apparatus and analysis for cellulose-grown continuous cultures. Quantitative description of cellulose hydrolysis is addressed with respect to adsorption of cellulase enzymes, rates of enzymatic hydrolysis, bioenergetics of microbial cellulose utilization, kinetics of microbial cellulose utilization, and contrasting features compared to soluble substrate kinetics. A biological perspective on processing cellulosic biomass is presented, including features of pretreated substrates and alternative process configurations. Organism development is considered for “consolidated bioprocessing” (CBP), in which the production of cellulolytic enzymes, hydrolysis of biomass, and fermentation of resulting sugars to desired products occur in one step. Two organism development strategies for CBP are examined: (i) improve product yield and tolerance in microorganisms able to utilize cellulose, or (ii) express a heterologous system for cellulose hydrolysis and utilization in microorganisms that exhibit high product yield and tolerance. A concluding discussion identifies unresolved issues pertaining to microbial cellulose utilization, suggests approaches by which such issues might be resolved, and contrasts a microbially oriented cellulose hydrolysis paradigm to the more conventional enzymatically oriented paradigm in both fundamental and applied contexts.
Universal filter design using transconductance CMOS inverter based CCII+

This paper investigate the performance of the Universal filter with three input and single output based on Transconductance CMOS Inverter based positive type second generation current conveyor (TCI-CCII+) using two resistors and two capacitors. The filter realizes the three filter responses i.e. Low-pass, High-pass and Band-pass responses due to multiple responses generate by the filter by applying proper input voltages at the nodes of their input terminals, thus the filter name given universal filter. The filter is design on 0.18um technology with supply voltage of 1.8 volts. The analyses of transconductance behaviour of CMOS Inverter (TCI), Gain and 3-dB bandwidth calculation for Transconductance CMOS Inverter based positive type second generation current conveyor (TCI-CCII+) and Three filter responses i.e. Low-pass, High-pass and Band-pass are obtained. All simulation results are obtained on spectra tool using cadence 180 nm CMOS parameter.
A generalized learning paradigm exploiting the structure of feedforward neural networks

In this paper a general class of fast learning algorithms for feedforward neural networks is introduced and described. The approach exploits the separability of each layer into linear and nonlinear blocks and consists of two steps. The first step is the descent of the error functional in the space of the outputs of the linear blocks (descent in the neuron space), which can be performed using any preferred optimization strategy. In the second step, each linear block is optimized separately by using a least squares (LS) criterion. To demonstrate the effectiveness of the new approach, a detailed treatment of a gradient descent in the neuron space is conducted. The main properties of this approach are the higher speed of convergence with respect to methods that employ an ordinary gradient descent in the weight space backpropagation (BP), better numerical conditioning, and lower computational cost compared to techniques based on the Hessian matrix. The numerical stability is assured by the use of robust LS linear system solvers, operating directly on the input data of each layer. Experimental results obtained in three problems are described, which confirm the effectiveness of the new method.
Accurate and efficient layout-to-circuit extraction for high-speed MOS and bipolar/BiCMOS integrated circuits

In this paper, we describe how we have exploited the advantages of various methods for device recognition and modeling in a layout-to-circuit extractor, called Space. Hence, we have obtained a program that, for different technologies, can quickly translate a large layout into an equivalent network. The network includes layout parasitics of the interconnects and can directly be simulated by various simulation packages, such as Spice. The efficiency and accuracy of the extractor are confirmed by experimental results and enable a fast and reliable layout verification for both MOS and bipolar/BiCMOS technologies.
Effect of implant angulation, connection length, and impression material on the dimensional accuracy of implant impressions: an in vitro comparative study.

BACKGROUND With regard to implant-supported prostheses, to date no technique has been proven to guarantee a completely passive fit of prosthetic frameworks. Several clinical variables may affect the precision of impressions, particularly in the presence of implants. PURPOSE To compare the accuracy of implant impressions made with different materials, lengths of impression coping connections, and not parallel position of the implants. MATERIALS AND METHODS A calibrated testing device allowing reproducible standardized positions was used. Two control groups of master models and eight experimental groups with predetermined undercuts were used to make addition silicon and polyether implant impressions by means of the open-tray pick-up technique. Four reference distances were evaluated on each study cast by using a profile projector and a standardized measurement protocol. The data were statistically analyzed by means of three-factor analysis of variance. RESULTS The impressions made in the presence of angulated implants were significantly less accurate than the ones made with parallel implants. The tested addition silicon resulted advantageous in presence of nonparallel implants whereas the polyether achieved the best results with parallel implants and standard impression copings. CONCLUSIONS The angulation of the implants may cause strains of impressions, probably because of the higher forces required for the impression removal. Moreover, undercuts negatively affected the impression accuracy. More accurate casts were obtained using the tested addition silicon in the presence of nonparallel implants and using a standard length connection of the copings in the presence of parallel implants, respectively.
Functional Dependence of Secrets in a Collaboration Network

A collaboration network is a graph formed by communication channels between parties. Parties communicate over these channels to establish secrets, simultaneously enforcing interdependencies between the secrets. The paper studies properties of these interdependencies that are induced by the topology of the network. In previous work, the authors developed a complete logical system for one such property, independence, also known in the information flow literature as nondeducibility. This work describes a complete and decidable logical system for the functional dependence relation between sets of secrets over a collaboration network. The system extends Armstrong's system of axioms for functional dependency in databases.
Three-Dimensional Chemical Mapping by EFTEM-TomoJ Including Improvement of SNR by PCA and ART Reconstruction of Volume by Noise Suppression

Abstract Electron tomography is becoming one of the most used methods for structural analysis at nanometric scale in biological and materials sciences. Combined with chemical mapping, it provides qualitative and semiquantitative information on the distribution of chemical elements on a given sample. Due to the current difficulties in obtaining three-dimensional (3D) maps by energy-filtered transmission electron microscopy (EFTEM), the use of 3D chemical mapping has not been widely adopted by the electron microscopy community. The lack of specialized software further complicates the issue, especially in the case of data with a low signal-to-noise ratio (SNR). Moreover, data interpretation is rendered difficult by the absence of efficient segmentation tools. Thus, specialized software for the computation of 3D maps by EFTEM needs to include optimized methods for image series alignment, algorithms to improve SNR, different background subtraction models, and methods to facilitate map segmentation. Here we present a software package (EFTEM-TomoJ, which can be downloaded from http://u759.curie.fr/fr/download/softwares/EFTEM-TomoJ), specifically dedicated to computation of EFTEM 3D chemical maps including noise filtering by image reconstitution based on multivariate statistical analysis. We also present an algorithm named BgART (for background removing algebraic reconstruction technique) allowing the discrimination between background and signal and improving the reconstructed volume in an iterative way.
Achieving Natural Clustering by Validating Results of Iterative Evolutionary Clustering Approach

Clustering is an essential process that leads to the classification of a given set of instances based on user-specified criteria; and different factors may lead to different clustering results. Thus, a large number of clustering algorithms exist to satisfy different purposes. However, scalability and the fact that algorithms in general need the number of clusters be specified a priori, which is mostly hard to estimate even for domain experts, are two challenges that motivate the development of new algorithms. This paper presents a novel approach to handle these two issues. We mainly developed a clustering method that works as an iterative approach to handle the scalability problem; and we utilize multi-objective genetic algorithm combined with validity indexes to decide on the number of clusters. The basic idea is to partition the dataset first; then cluster each partition separately. Finally, each obtained cluster is treated as a single instance (represented by its centroid) and a conquer process is performed to get the final clustering of the complete dataset. Test results on one large real dataset demonstrate the applicability and effectiveness of the proposed approach
Reduced Sigma Point Filtering for Partially Linear Models

A method for performing unscented Kalman filtering with a reduced number of sigma points is proposed. The procedure is applicable when either the process or measurement equations are partially linear in the sense that only a subset of the elements of the state vector undergo a nonlinear transformation. It is shown that for such models second-order accuracy in the moments required for the unscented Kalman filter recursion can be obtained using a number of sigma points determined by the number of nonlinearly transformed elements rather than the dimension of the state vector. A procedure for computing the sigma points is developed. An application of the proposed method to smoothed target state estimation from bearings measurements is presented
The Role of Multi-Agent Social Networking Systems in Ubiquitous Education: Enhancing Peer-Supported Reflective Learning

Knowledge it could be argued is constructed from the information actors pick up from the environments they are in. Assessing this knowledge can be problematic in ubiquitous e-learning systems, but a method of supporting the critical marking of e-learning exercises is the Circle of Friends social networking tech- nology. Understanding the networks of practice in which these e-learning systems are part of requires a deeper understanding of information science frameworks. The Ecological Cognition Framework (ECF)�providesathoroughunderstandingofhowactorsrespondtoandinfluencetheirenvironment. � Forerunners to ecological cognition, such as activity theory have suggested that the computer is just a tool that mediates between the actor and the physical environment. Utilising the ECF it can be seen thatforane-learningsystemtobeaneffectiveteacheritneedstobeabletocreatefiveeffectsinthe� actors that use it, with those being the belonging effect, the demonstration effect, the inspiration effect, themobilisationeffect,�andtheconfirmationeffect. �Indesigningthesystemadeveloperwouldhaveto� consider who the system is going to teach, what it is going to teach, why it is teaching, which techniques itisgoingtousetoteachandfinallywhetherithasbeensuccessful. �Thischapterproposesamulti-agent� e-learning system called the Portable Assistant for Intelligently Guided Education (PAIGE), which is based around a 3D anthropomorphic avatar for educating actors ubiquitously. An investigation into the market for PAIGE was carried out. The data showed that those that thought their peers were the best form of support were less likely to spend more of their free time on homework. The chapter suggests that future research could investigate the usage of systems like PAIGE in educational settings and the effect they have on learning outcomes.
Adhesive and Lateral E-Cadherin Dimers Are Mediated by the Same Interface

ABSTRACT E-cadherin is a transmembrane protein that mediates Ca2+-dependent cell-cell adhesion. To study cadherin-cadherin interactions that may underlie the adhesive process, a recombinant E-cadherin lacking free sulfhydryl groups and its mutants with novel cysteines were expressed in epithelial A-431 cells. These cysteine mutants, designed according to various structural models of cadherin dimers, were constructed to reveal cadherin dimerization by the bifunctional sulfhydryl-specific cross-linker BM[PE0]3. Cross-linking experiments with the mutants containing a cysteine at strand B of their EC1 domains did show cadherin dimerization. By their properties these dimers correspond to those which have been characterized by coimmunoprecipitation assay. Under standard culture conditions the adhesive dimer is a dominant form. Calcium depletion dissociates adhesive dimers and promotes the formation of lateral dimers. Our data show that both dimers are mediated by the amino-terminal cadherin domain. Furthermore, the interfaces involved in both adhesive and lateral dimerization appear to be the same. The coexistence of the structurally identical adhesive and lateral dimers suggests some flexibility of the extracellular cadherin region.
An ILP algorithm for post-floorplanning voltage-island generation considering power-network planning

Power optimization is a crucial concern for modem circuit designs. Multiple supply voltages (MSV's) provide an effective technique for the power optimization. This paper addresses the voltage-island generation problem for MSV designs at the post-floorplanning stage. We first present a general formulation of this problem that considers level-shifter planning and power-network routing resources. Without loss of solution quality, we propose an economical graph-based representation that needs only a linear number of nodes to the block number to model the block adjacency in a floorplan for the voltage-island generation. In contrast, previous works need a quadratic number of nodes. To tackle the addressed problem, we employ an ILP formulation which consists of (1) level-shifter aware wirelength estimation to capture the timing overhead, (2) voltage-island-clustering inequalities to avoid complicated constraint transformations, and (3) inequalities to capture the power-network routing-resource usage. Compared with previous works, our algorithm can produce better voltage islands in terms of power-network routing resources. Experimental results show that our algorithm can effectively reduce the power-network routing resource by up to 19.46% with a reasonable overhead of 4.03% more power consumption and using reasonable running time.