Miracle-dz/UniFAR-FTUs huggingface dataset:
Assignment of Cells to Switches in a Cellular Mobile Environment Using Swarm Intelligence

The problem of assigning cells to switches in a mobile cellular network is a NP-Hard problem. It is therefore necessary to use a heuristic method to solve it in a reasonable amount of time with acceptable accuracy particularly for large sized problems. The assignment of cells to switches problem is characterized by minimization of the cabling cost, hand-off cost and switching costs in the whole network. We propose a swarm intelligence based technique to solve this problem. Ant colony optimization (ACO) and Particle swarm optimization (PSO) are typical swarm intelligence techniques. ACO technique was used for cell assignment problem in the recent past and shown to be better in comparison to the other schemes. In this paper, we propose a modified binary Particle Swarm Optimization (MBPSO) technique for this cell assignment problem. Our experimental results reveal better results in terms of accuracy and execution time compared to ACO for a large combination of parameters.
Profiling, Bioinformatic, and Functional Data on the Developing Olfactory/GnRH System Reveal Cellular and Molecular Pathways Essential for This Process and Potentially Relevant for the Kallmann Syndrome

During embryonic development, immature neurons in the olfactory epithelium (OE) extend axons through the nasal mesenchyme, to contact projection neurons in the olfactory bulb. Axon navigation is accompanied by migration of the GnRH+ neurons, which enter the anterior forebrain and home in the septo-hypothalamic area. This process can be interrupted at various points and lead to the onset of the Kallmann syndrome (KS), a disorder characterized by anosmia and central hypogonadotropic hypogonadism. Several genes has been identified in human and mice that cause KS or a KS-like phenotype. In mice a set of transcription factors appears to be required for olfactory connectivity and GnRH neuron migration; thus we explored the transcriptional network underlying this developmental process by profiling the OE and the adjacent mesenchyme at three embryonic ages. We also profiled the OE from embryos null for Dlx5, a homeogene that causes a KS-like phenotype when deleted. We identified 20 interesting genes belonging to the following categories: (1) transmembrane adhesion/receptor, (2) axon-glia interaction, (3) scaffold/adapter for signaling, (4) synaptic proteins. We tested some of them in zebrafish embryos: the depletion of five (of six) Dlx5 targets affected axonal extension and targeting, while three (of three) affected GnRH neuron position and neurite organization. Thus, we confirmed the importance of cell–cell and cell-matrix interactions and identified new molecules needed for olfactory connection and GnRH neuron migration. Using available and newly generated data, we predicted/prioritized putative KS-disease genes, by building conserved co-expression networks with all known disease genes in human and mouse. The results show the overall validity of approaches based on high-throughput data and predictive bioinformatics to identify genes potentially relevant for the molecular pathogenesis of KS. A number of candidate will be discussed, that should be tested in future mutation screens.
Preparation of Biocompatible Carboxymethyl Chitosan Nanoparticles for Delivery of Antibiotic Drug

Objective. To prepare biocompatible ciprofloxacin-loaded carboxymethyl chitosan nanoparticles (CCC NPs) and evaluate their cell specificity as well as antibacterial activity against Escherichia coli in vitro. Methods. CCC NPs were prepared by ionic cross-linking method and optimized by using Box-Behnken response surface method (BBRSM). Zeta potential, drug encapsulation, and release of the obtained nanoparticles in vitro were thoroughly investigated. Minimum inhibitory concentration (MIC) and killing profiles of free or ciprofloxacin-loaded nanoparticles against Escherichia coli were documented. The cytotoicity of blank nanoparticles and cellular uptake of CCC NPs were also investigated. Results. The obtained particles were monodisperse nanospheres with an average hydrated diameter of 151 ± 5.67 nm and surface of charge −22.9 ± 2.21 mV. The MICs of free ciprofloxacin and CCC NPs were 0.16 and 0.08 μg/mL, respectively. Blank nanoparticles showed no obvious cell inhibition within 24 h, and noticeable phagocytosis effect was observed in the presence of CCC NPs. Conclusion. This study shows that CCC NPs have stronger antibacterial activity against Escherichia coli than the free ciprofloxacin because they can easily be uptaken by cells. The obtained CCC NPs have promising prospect in drug delivery field.
The confounding effect of cryptic relatedness for environmental risks of systolic blood pressure on cohort studies

The impact of cryptic relatedness (CR) on genomic association studies is well studied and known to inflate false‐positive rates as reported by several groups. In contrast, conventional epidemiological studies for environmental risks, the confounding effect of CR is still uninvestigated. In this study, we investigated the confounding effect of unadjusted CR among a rural cohort in the relationship between environmental risk factors (body mass index, smoking status, alcohol consumption) and systolic blood pressure. We applied the methods of population‐based whole‐genome association studies for the analysis of the genome‐wide single nucleotide polymorphism data in 1622 subjects, and detected 20.2% CR in this cohort population. In the case of the sample size, approximately 1000, the ratio of CR to the population was 20.2%, the population prevalence 25%, the prevalence in the CR 26%, heritability for liability 14.3% and prevalence in the subpopulation without CR 26%, the difference of estimated regression coefficient between samples with and without CR was not significant (P‐value = 0.55). On the other hand, in another case with approximately >20% heritability for liability, we showed that confounding due to CR biased the estimation of exposure effects.
Belief Network Inference Algorithms: a Study of Performance Based on Domain Characterisation

In recent years belief networks have become a popular representation for reasoning under uncertainty and are used in a wide variety of applications. There are a number of exact and approximate inference algorithms available for performing belief updating, however in general the task is NP-hard. To overcome the problems of computational complexity that occur when modelling larger, real-world problems, researchers have developed variants of stochastic simulation approximation algorithms, and a number of other approaches involve approximating the model or limiting belief updating to nodes of interest. Typically comparisons are made of only a few algorithms, and on a particular example network. We survey the belief network algorithms and propose a system for domain characterisation as a basis for algorithm comparison. We present performance results using this framework from three sets of experiments: (1) on the Likelihood Weighting (LW) and Logic Sampling (LS) stochastic simulation algorithms; (2) on the performance of LW and Jensen's algorithms on state-space abstracted networks, (3) some comparisons of the time performance of LW, LS and the Jensen algorithm. Our results indicate that domain characterisation may be useful for predicting inference algorithm performance on a belief network for a new application domain.
Assessing users' acceptance toward a closed access Library Service System using the UTAUT model: A case study at the National Library of Indonesia

Today, technology has developed very rapidly, especially in the field of public information service. Information service aims to satify users of the service. The National Library of Indonesia is a non-ministerial government institution providing a services for the community and institutional, particularly library service. To improve library services, strategic and implementation of information technology is needed. As part of its development, the National Library of Indonesia has established Library Service System, which consists of an open and closed services. All of services was supported by a library service system in web-application namely INLIS (Integrated Library System) applications. INLIS consist of many application modules, such as OPAC to enable libraries to publish their catalog on a library website. To improve the service of the library, an assesment of the use OPAC and INLIS is needed. The assessment of a better use of the service can be done by examining users' acceptance toward the closed access library service system using UTAUT model. This model uses four assessment variables of users' acceptance toward the use of the closed library service. Based on the asssessment, conclusions can be drawn which serve as a foundation for the evaluation of the development of the closed service at the National Library of Indonesia.
Analysis of a Battery Management System (BMS) Control Strategy for Vibration Aged Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 Battery Cells

Electric vehicle (EV) manufacturers are using cylindrical format cells as part of the vehicle’s rechargeable energy storage system (RESS). In a recent study focused at determining the ageing behavior of 2.2 Ah Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 battery cells, significant increases in the ohmic resistance (RO) were observed post vibration testing. Typically a reduction in capacity was also noted. The vibration was representative of an automotive service life of 100,000 miles of European and North American customer operation. This paper presents a study which defines the effect that the change in electrical properties of vibration aged 18650 NMC cells can have on the control strategy employed by the battery management system (BMS) of a hybrid electric vehicle (HEV). It also proposes various cell balancing strategies to manage these changes in electrical properties. Subsequently this study recommends that EV manufacturers conduct vibration testing as part of their cell selection and development activities so that electrical ageing characteristics associated with road induced vibration phenomena are incorporated to ensure effective BMS and RESS performance throughout the life of the vehicle.
Locking effects in multiprocessor implementations of protocols

We investigate how to exploit shared memory multiprocessors for parallel protocol processing. We present a multiprocessor implementation of the x-kernel protocol environment from the University of Arizona. A "processor-per-message" paradigm is used to partition the work over processors. Locks are used to protect shared protocol state and data. Mutual exclusion by locking can be costly if the parallel protocol code frequently accesses shared state and data. This paper addresses the effect of locking on performance.The x-kernel is implemented in user address space on a Sequent Symmetry. Performance results of UDP/IP and TCP/IP are given, and we compare them to performance predictions from simulations. The measured speedups for the parallel implementations relative to the sequential ones are more than 12 times for UDP and 3 times for TCP. These limits are set by locking and machine contention.
Distance-based non-deterministic semantics for reasoning with uncertainty

Non-deterministic matrices, a natural generalization of many-valued matrices, are semantic structures in which the value assigned to a complex formula may be chosen non-deterministically from a given set of options. We show that by combining non-deterministic matrices and distance-based considerations, one obtains a family of logics that are useful for reasoning with uncertainty. These logics are a conservative extension of those that are obtained by standard (i.e., deterministic) distance-based semantics, and so usual distance-based methods (in the context of, e.g., belief revision, information integration, and social choice theory) are easily simulated within our framework. We investigate the basic properties of the distance-preferential non-deterministic logics, consider their application for reasoning with incomplete and inconsistent information, and show the correspondence between some particular entailments in our framework and well-known problems like max-SAT.
The Annual Runoff Forecasting Research Based on the Theory of Cointegration and Error Correction Model

An annual runoff forecasting method is presented based on unit root test, cointegration test and error correction model of the upper and lower reaches of the Second Songhua River. The method of cointegration analysis is applied to the annual runoff data of the Baishan and Fengman hydrology Stations; then the error correction model is set up, which can predict the annual runoff of Fengman hydrology Station from 1989 to 1998. The results show that the model based on cointegration analysis and error correction is suitable in runoff forecasting.
Spectrum sharing with smooth supermodular game in cognitive radio networks

In this paper, a supermodular game theoretic approach is investigated for spectrum sharing in cognitive radio networks. We consider a Bertrand competition model, in which primary service providers compete to sell their spare spectrum and then to maximize their individual profits. We demonstrate that the Bertrand competition is a smooth supermodular game, and a round-robin optimization algorithm is developed to obtain the optimal price solutions. Simulation results verify that the algorithm approximately converges to an equilibrium point, and the influence of the exogenous variable on the equilibrium point is analyzed.
A Comparative Study of Target Dependency Structures for Statistical Machine Translation

This paper presents a comparative study of target dependency structures yielded by several state-of-the-art linguistic parsers. Our approach is to measure the impact of these non-isomorphic dependency structures to be used for string-to-dependency translation. Besides using traditional dependency parsers, we also use the dependency structures transformed from PCFG trees and predicate-argument structures (PASs) which are generated by an HPSG parser and a CCG parser. The experiments on Chinese-to-English translation show that the HPSG parser's PASs achieved the best dependency and translation accuracies.
The Effect of Awareness Raising Technique towards Students’ Achievement and Reading Interest

Reading is one of the primary subjects that should be mastered by the students in language learning. Yet, reading activity tends to be a boring activity. To increase the students’ interest, the lecturers should be able to stimulate the students' awareness in reading. Therefore, this research is aimed to know the effect of Awareness Raising Technique in teaching reading toward students' achievement and reading interest. This research was experimental research. The population was the second year students of English department of Education Abdi STKIP Payakumbuh. There were three classes. The sample was chosen by cluster sampling. The instruments of this research were reading test and questionnaire. To analyze the data, the researcher used the t-test and ANOVA formula 2x2. After analyzing the data the researcher found (1)students who were taught by using Awareness Raising Technique have better reading achievement than those who were taught by using Presentation Technique, (2) students with high reading interest have better reading achievement than those who were taught by using Presentation Technique, (3) students with high reading interest have better reading achievement than those who were taught by using Presentation Technique, and (4) there is no interaction between techniques and students' reading interest toward students reading achievement at the second year English department of Education Abdi STKIP Payakumbuh.
Functional Integration of Grafted Neural Stem Cell-Derived Dopaminergic Neurons Monitored by Optogenetics in an In Vitro Parkinson Model

Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D2 autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2) and halorhodopsin (NpHR), respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD.
Performance-driven Development of Deep Packet Inspection Systems on Commodity Platforms

Deep Packet Inspection (DPI) systems have been increasingly performed on dedicated hardware, as an attempt to speed up the packet processing for high speed links. This is mainly caused by the current demand for CPU-intensive processing required by regular expression functions, which investigate the packet payload trying to match patterns of application signatures. This study proposes and evaluates techniques to optimize DPI systems using commodity hardware. At first, it is designed a new optimized software architecture. In the following, this architecture is implemented into a DPI software and those optimization techniques are then integrated. Our results show that the time spent with regular expression matching was actually improved, besides the packet loss rate when realizing online measurements meanwhile. The evaluation results state that the performance of a typical DPI process on a Linux box can be improved in almost 100%, and the amount of classified traffic may be increased 220%.
Influence Factors on Consumers' Cognition Level to Genetically Modified Food-taking Huangshi as an Example

This study aims to analyze the influence factors on consumers’ cognition level to genetically modified food and improve the consumers’ cognition level. In recent years, genetically modified foods in people’s daily life are becoming more and more common, but there is a lot of controversy about them. Based on the analysis of influence factors on consumers’ cognition level to GMF, a comprehensive system is established from four aspects, including the consumers’ personal characteristics, social-economic characteristics, household characteristics and awareness of risk. And Analytic Hierarchy Process (AHP) method is used to make the quantitative research via investigation data of Huangshi, analyze the major influence on consumers’ cognition level to GMF. Finally some suggestions are proposed to promote the consumers’ cognition level to GMF.
Quick analysis of nucleosome positioning experiments using the nucleR package

The nucleR package provides a high-level processing of genomic datasets focused in nucleosome positioning experiments, despite they should be also applicable to chromatin inmunoprecipitation (ChIP) experiments in general. The aim of this package is not providing an all-in-one data analysis pipeline but complement those existing specialized libraries for low-level data importation and pre-processment into R/Bioconductor framework. nucleR works with data from the two main high-troughput technologies available nowadays for ChIP: Next Generation Sequencing/NGS (ChIP-seq) and Tiling Microarrays (ChIPon-Chip). This is a brief summary of the main functions:
Idealized Self-Presentation Online: Relationships Among Anticipated Online vs. Offline Interaction, Self-Presentational Efficacy, Self-Presentation, and Self-Esteem

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A General Upper Bound on the List Chromatic Number of Locally Sparse Graphs

Suppose that G is a graph with maximum degree d(G) such that, for every vertex v in G, the neighbourhood of v contains at most d(G)2/f (f > 1) edges. We show that the list chromatic number of G is at most Kd(G)/log f, for some positive constant K. This result is sharp up to the multiplicative constant K and strengthens previous results by Kim [9], Johansson [7], Alon, Krivelevich and Sudakov [3], and the present author [18]. This also motivates several interesting questions. As an application, we derive several upper bounds for the strong (list) chromatic index of a graph, under various assumptions. These bounds extend earlier results by Faudree, Gyárfás, Schelp and Tuza [6] and Mahdian [13] and determine, up to a constant factor, the strong (list) chromatic index of a random graph. Another application is an extension of a result of Kostochka and Steibitz [10] concerning the structure of list critical graphs.
On a Simple, Practical, Optimal, Output-Sensitive Randomized Planar Convex Hull Algorithm

In this paper we present a truly practical and provably optimalO(nlogh) time output-sensitive algorithm for the planar convex hull problem. The basic algorithm is similar to the algorithm presented by2, where the median-finding step is replaced by an approximate median. We analyze two such schemes and show that for both methods, the algorithm runs in expectedO(nlogh) time. We further show that the probability of deviation from expected running time approaches 0 rapidly with increasing values ofnandhfor any input. Our experiments suggest that this algorithm is a practical alternative to the worst-caseO(nlogn) algorithms such as Graham's and is especially faster for small output-sizes. Our approach bears some resemblance to a recent algorithm of13, but our analysis is substantially different.