Miracle-dz/UniFAR-FTUs huggingface dataset:
Monetary incentive with reputation for virtual market-place based P2P

One of the underlying assumptions on the design of peer-to-peer (P2P) network is that each peer trusts each other for forwarding transit messages. However, with the growth of P2P application, especially in business model, some peers may behave as selfish, irrational nodes due to conflict of interest or for conservation bandwidth. In our model, the P2P network is considered as a virtual market-place where peers can find, provide, and use services. Since peers are owned and operated by different entities, they do not necessarily share the same goals, but rather, to serve their own interests. In this paper, incentive mechanism to motivate peers to forward messages is proposed. We have implemented the monetary as an incentive mechanism, in which peers can setup their cost to charge for transiting a message. However, with only monetary incentive, peers may misbehave. Therefore, the decentralized reputation has been implemented with monetary mechanism. This will allow an application with dramatically improved utility, co-operate among peers and hence enable whole new domains of use.
Applying topic segmentation algorithms on arabic language

The need of having a topic segmentation system for Arabic text is to improve the functionalities of Arabic Information Retrieval (AIR). Topic segmentation of texts has been used to improve the accuracy of the subsequent processes such as question answering and information retrieval. In this paper, we present the assessment of two algorithms for Arabic text segmentation which are TextTilling and C99. We evaluate the performance of these algorithms using the classical Recall/Precision metrics and the Reader Judgment method.
Dystroglycan Binding to α-Neurexin Competes with Neurexophilin-1 and Neuroligin in the Brain*

Background: Extracellular matrix dystroglycan has essential functions at the neuromuscular junction and at inhibitory synapses in the brain. Results: Brain dystroglycan competes with neurexophilin-1 and neuroligins for binding to presynaptic α-neurexins. Conclusion: Competition between α-neurexin ligands in combination with alternative splicing determines formation of important trans-synaptic complexes. Significance: This is the first analysis of binding interference in α-neurexin multiplexes. α-Neurexins (α-Nrxn) are mostly presynaptic cell surface molecules essential for neurotransmission that are linked to neuro-developmental disorders as autism or schizophrenia. Several interaction partners of α-Nrxn are identified that depend on alternative splicing, including neuroligins (Nlgn) and dystroglycan (αDAG). The trans-synaptic complex with Nlgn1 was extensively characterized and shown to partially mediate α-Nrxn function. However, the interactions of α-Nrxn with αDAG, neurexophilins (Nxph1) and Nlgn2, ligands that occur specifically at inhibitory synapses, are incompletely understood. Using site-directed mutagenesis, we demonstrate the exact binding epitopes of αDAG and Nxph1 on Nrxn1α and show that their binding is mutually exclusive. Identification of an unusual cysteine bridge pattern and complex type glycans in Nxph1 ensure binding to the second laminin/neurexin/sex hormone binding (LNS2) domain of Nrxn1α, but this association does not interfere with Nlgn binding at LNS6. αDAG, in contrast, interacts with both LNS2 and LNS6 domains without inserts in splice sites SS#2 or SS#4 mostly via LARGE (like-acetylglucosaminyltransferase)-dependent glycans attached to the mucin region. Unexpectedly, binding of αDAG at LNS2 prevents interaction of Nlgn at LNS6 with or without splice insert in SS#4, presumably by sterically hindering each other in the u-form conformation of α-Nrxn. Thus, expression of αDAG and Nxph1 together with alternative splicing in Nrxn1α may prevent or facilitate formation of distinct trans-synaptic Nrxn·Nlgn complexes, revealing an unanticipated way to contribute to the identity of synaptic subpopulations.
Three-dimensional mapping of light transmittance and foliage distribution using lidar

The horizontal and vertical distributions of light transmittance were evaluated as a function of foliage distribution using lidar (light detection and ranging) observations for a sugar maple (Acer saccharum) stand in the Turkey Lakes Watershed. Along the vertical profile of vegetation, horizontal slices of probability of light transmittance were derived from an Optech ALTM 1225 instrument's return pulses (two discrete, 15-cm diameter returns) using indicator kriging. These predictions were compared with (i) below canopy (1-cm spatial resolution) transect measurements of the fraction of photosynthetically active radiation (FPAR) and (ii) measurements of tree height. A first-order trend was initally removed from the lidar returns. The vertical distribution of vegetation height was then sliced into nine percentiles and indicator variograms were fitted to them. Variogram parameters were found to vary as a function of foliage height above ground. In this paper, we show that the relationship between ground measurements of FPAR and kriged estimates of vegetation cover becomes stronger and tighter at coarser spatial resolutions. Three-dimensional maps of foliage distribution were computed as stacks of the percentile probability surfaces. These probability surfaces showed correspondence with individual tree-based observations and provided a much more detailed characterization of quasi-continuous foliage distribution. These results suggest that discrete-return lidar provides a promising technology to capture variations of foliage characteristics in forests to support the development of functional linkages between biophysical and ecological studies.
Mechanism of MicroRNA-Target Interaction: Molecular Dynamics Simulations and Thermodynamics Analysis

MicroRNAs (miRNAs) are endogenously produced ∼21-nt riboregulators that associate with Argonaute (Ago) proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target) and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1) three important (PAZ, Mid and PIWI) domains exist in Argonaute which define the global dynamics of the protein; 2) the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3) it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5′-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg2+) plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA). Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago.
Proxy support for service discovery using mDNS/DNS-SD in low power networks

We present a solution for service discovery of resource constrained devices based on mDNS/DNS-SD. We extend the mDNS/DNS-SD service discovery protocol with support for proxy servers. Proxy servers temporarily store information about services offered on resource constrained devices and respond on their behalf while they are not available. We analyze two protocols for the delegation mechanism between a service provider and a proxy server: an active proxy protocol, as used in the mDNS/DNS-SD implementation by Apple, and a new, passive proxy protocol. We implement and simulate both approaches. Based on the delay and energy usage, we show that the second approach converges faster, thus saving more energy by allowing the resource constrained device to be turned off earlier.
Improve Visual Tracking by End-to-end Multi-Tracker Selection

While many state-of-the-art trackers focus on solving certain parts of the tracking problem (e.g., dealing with occlusion and scale variation), it is beneficial to exploit the merits of multiple trackers to tackle different application scenarios. This paper proposes an end-to-end tracker selection method to improve visual tracking performance. Any trackers with arbitrary tracking strategy can be integrated in our framework without the need of modifying any single component tracker, which is simple and effective. We introduce a novel verification mechanism to select the most reliable tracking result from multiple trackers. Both qualitative and quantitative evaluations demonstrate that the proposed method achieves a consistent performance improvement on the benchmark dataset.
Cell Breathing Techniques for Load Balancing in Wireless LANs

Maximizing network throughput while providing fairness is one of the key challenges in wireless LANs (WLANs). This goal is typically achieved when the load of access points (APs) is balanced. Recent studies on operational WLANs, however, have shown that AP load is often substantially uneven. To alleviate such imbalance of load, several load balancing schemes have been proposed. These schemes commonly require proprietary software or hardware at the user side for controlling the user-AP association. In this paper we present a new load balancing technique by controlling the size of WLAN cells (i.e., AP's coverage range), which is conceptually similar to cell breathing in cellular networks. The proposed scheme does not require any modification to the users neither the IEEE 802.11 standard. It only requires the ability of dynamically changing the transmission power of the AP beacon messages. We develop a set of polynomial time algorithms that find the optimal beacon power settings which minimize the load of the most congested AP. We also consider the problem of network-wide min-max load balancing. Simulation results show that the performance of the proposed method is comparable with or superior to the best existing association-based methods.
Hybrid immune-inspired method for selecting the optimal or a near-optimal service composition

The increasing interest in developing optimization techniques that provide the optimal or a near-optimal solution of a problem in an efficient way has determined researchers to turn their attention towards biology. It has been noticed that biology offers many clues regarding the design of such optimization techniques, since biological systems exhibit self-optimization and self-organization capabilities in a decentralized way without the existence of a central coordinator. In this context we propose a bio-inspired hybrid method that selects the optimal or a near-optimal solution in semantic Web service composition. The proposed method combines principles from immune-inspired, evolutionary, and neural computing to optimize the selection process in terms of execution time and explored search space. We model the search space as an Enhanced Planning Graph structure which encodes all the possible composition solutions for a given user request. To establish whether a solution is optimal, the QoS attributes of the services involved in the composition as well as the semantic similarity between them are considered as evaluation criteria. For the evaluation of the proposed selection method we have implemented an experimental prototype and carried out experiments on a set of scenarios from the trip planning domain.
A Rule-based Security Auditing Tool for Software Vulnerability Detection

We can use information and software of various forms without being restricted for place and time if ubiquitous computing age comes. However, its reverse function is causing security problems such as outflow of personal information, hacking, diffusion of virus. Specially, dissemination of software that has malicious purpose in ubiquitous computing environment causes serious damage. We have studied about malicious code detection and software vulnerability detection tool to prevent this. But, existent detection tools are not suited to general software, because they are limitative in specification area. In addition, they can not detect a newly appeared malicious code. We must update pattern of new malicious code, because they use a simple pattern matching technique. In this paper, we propose rule-based security auditing tool that analyzes structure of target code to solve these problems, define this as rule, and detect malicious codes and software vulnerabilities. Proposed auditing tool can construct secure ubiquitous computing environment, because it will be used by a common software audit tool that detects malicious codes and software vulnerabilities at the same time
Accumulation of Palmitoylcarnitine and Its Effect on Pro‐Inflammatory Pathways and Calcium Influx in Prostate Cancer

Acylcarnitines are intermediates of fatty acid oxidation and accumulate as a consequence of the metabolic dysfunction resulting from the insufficient integration between β‐oxidation and the tricarboxylic acid (TCA) cycle. The aim of this study was to investigate whether acylcarnitines accumulate in prostate cancer tissue, and whether their biological actions could be similar to those of dihydrotestosterone (DHT), a structurally related compound associated with cancer development.
Recognition of alphabetical hand gestures using hidden Markov model

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). In particular, visual interpretation of hand gestures can help achieve easy and natural comprehension for HCI. Many methods for hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network (NN), and hidden Markov model (HMM)s. In our research, HMMs are proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and produces a trajectory. The spotting algorithm divides the trajectory into real and meaningless gestures. In constructing a feature database, the proposed approach uses the weighted ρ-φ-ν feature code, and employ a k-means algorithm for the codebook of HMM. In our experiments, 1,300 alphabetical and 1,300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfactory recognition rate for the images with different sizes, shapes and skew angles. key words: gesture recognition, hidden Markov model(HMM)
Motion-Based Geometry Compensation for DWT Compression of 3D mesh Sequences

In this paper, We propose an efficient compression method to encode the geometry of 3D mesh sequences of objects sharing the same connectivity. Our approach is based on the clustering of the input mesh geometry into groups of vertices following the same affine motion. The proposed algorithm uses a scan-based temporal wavelet filtering geometrically compensated. The wavelet coefficients are encoded by an efficient coding scheme that includes a bit allocation process, whereas the displacement vectors are lossless entropy encoded. Simulation results provides good compression performances compared to some state of the art coders.
Germline Stem Cell Gene PIWIL2 Mediates DNA Repair through Relaxation of Chromatin

DNA damage response (DDR) is an intrinsic barrier of cell to tumorigenesis initiated by genotoxic agents. However, the mechanisms underlying the DDR are not completely understood despite of extensive investigation. Recently, we have reported that ectopic expression of germline stem cell gene PIWIL2 is associated with tumor stem cell development, although the underlying mechanisms are largely unknown. Here we show that PIWIL2 is required for the repair of DNA-damage induced by various types of genotoxic agents. Upon ultraviolet (UV) irradiation, silenced PIWIL2 gene in normal human fibroblasts was transiently activated after treatment with UV light. This activation was associated with DNA repair, because Piwil2-deficienct mouse embryonic fibroblasts (mili-/- MEFs) were defective in cyclobutane pyrimidine dimers (CPD) repair after UV treatment. As a result, the UV-treated mili-/- MEFs were more susceptible to apoptosis, as characterized by increased levels of DNA damage-associated apoptotic proteins, such as active caspase-3, cleaved Poly (ADP-ribose) polymerase (PARP) and Bik. The impaired DNA repair in the mili-/- MEFs was associated with the reductions of histone H3 acetylation and chromatin relaxation, although the DDR pathway downstream chromatin relaxation appeared not to be directly affected by Piwil2. Moreover, guanine–guanine (Pt-[GG]) and double strand break (DSB) repair were also defective in the mili-/- MEFs treated by genotoxic chemicals Cisplatin and ionizing radiation (IR), respectively. The results indicate that Piwil2 can mediate DNA repair through an axis of Piwil2 → histone acetylation → chromatin relaxation upstream DDR pathways. The findings reveal a new role for Piwil2 in DNA repair and suggest that Piwil2 may act as a gatekeeper against DNA damage-mediated tumorigenesis.
Gender as Moderating Effect of Switching Barriers on Customer Satisfaction and Word-of-Mouth Behavior (Studies on BlackBerry Mobile Phone Customer in Malang)

The purpose of this study is to determine the effect of Switching Barriers on Customer Satisfaction, determine the effect of Customer Satisfaction and Switching Barriers directly on Word-of-Mouth, determine whether Customer Satisfaction as a mediating influence of Switching Barriers on Word-ofMouth, and find out if gender as the moderating effect of Switching Barriers on Customer Satisfaction, Customer Satisfaction moderating influence of the Word-of-Mouth, and moderating influence of Switching Barriers on Word-of-Mouth. The populations in this study are the BlackBerry users in Malang city in early adult age category (20-40 years old) who had been using the BlackBerry service facility for not less than 12 months. 250 respondents are set as the sample consisting of 125 female respondents and 125 male respondents. Analysis GSCA (Generalized Structured Component Analysis) is used to answer the hypotheses which multigroup moderating variable analysis is used to determine whether there is influence of gender as a moderating variable. The results of this study showed that gender is not a moderating variable on the effect of Switching Barriers on Customer Satisfaction, Customer Satisfaction on Word-of-Mouth, and Switching Barriers on Word-of-Mouth. The results also showed that Switching Barriers have direct and positive impacts on the Word-of-Mouth. Note also, Customer Satisfaction mediates the relationship of Switching Barriers and Word-of-Mouth. Even the influence of Switching Barriers on Word-of-Mouth becomes stronger if there is Customer Satisfaction as a mediating
Semantic Search Engine using Joomla Framework with Modified tf-idf and TRApriori Algorithm

As the amount of data available in a repository increases, content retrieval from the huge data stored in the repository becomes a tedious task. Though Content Management System helps us to manage the data, yet searching the relevant data is still a daunting task. For that, we need efficient Search Algorithms for maximizing the correlation between data required and data returned by semantic search engine. Many courseware repositories is an interface through which various students, teachers, etc can access on-line learning material, course contents, presentations, videos, lectures etc. in this paper we present a technique that automatically constructs ontology from the given courseware repositories. A search engine mechanism is developed that provide a semantic search capability based on a modified TF-IDF(term frequency inverse document frequency) weighting scheme and then determines the association among term through TRapriori algorithm. We evaluate our result with custom Google search engine.
WordNet Based Features for Predicting Brain Activity associated with meanings of nouns

Different studies have been conducted for predicting human brain activity associated with the semantics of nouns. Corpus based approaches have been used for deriving feature vectors of concrete nouns, to model the brain activity associated with that noun. In this paper a computational model is proposed in which, the feature vectors for each concrete noun is computed by the WordNet similarity of that noun with the 25 sensory-motor verbs suggested by psychologists. The feature vectors are used for training a linear model to predict functional MRI images of the brain associated with nouns. The WordNet extracted features are also combined with corpus based semantic features of the nouns. The combined features give better results in predicting human brain activity related to concrete nouns.
Impulsive Synchronization of Chaotic Lur'e Systems by Measurement Feedback

In this paper we consider impulsive control of master-slave synchronization schemes that consist of identical Lur’e systems. Impulsive control laws are investigated which make use of linear or nonlinear dynamic measurement feedback. A sucient condition for global asymptotic stability is presented which is characterized by a set of matrix inequalities. Synchronization is proven for the error between the output signals. The method is illustrated on Chua’s circuit and a hyperchaotic system with coupled Chua’s circuits.
Ultra Low Energy CMOS Logic Using Below-Threshold Dual-Voltage Supply

This paper investigates subthreshold voltage operation of digital circuits. Starting from the previously known single supply voltage for minimum energy per cycle, we further lower the energy consumption by using dual subthreshold supplies. Level converters, commonly used in the above threshold design, are found to be unacceptably slow for subthreshold voltage operation. Therefore, special constraints are used to eliminate level converters. We give a new mixed integer linear program (MILP) that automatically and optimally assigns gate voltages, avoids the use of level converters, and holds the minimum critical path delay, while minimizing the total energy per cycle. Using examples of a 16-bit ripple-carry adder and a 4 × 4 multiplier we show energy savings of 23% and 5%, respectively. The latter is a worst case example because most paths are critical. Alternatively, for the same energy as that of single below-threshold supply, an optimized dual voltage design can operate at 3 to 4 times higher clock rate. Also, we show energy saving up to 22.2% from the minimum energy point over ISCAS’85 benchmark circuits. The MILP optimization with special consideration for level converters is general and applicable to any supply voltage range.