Miracle-dz/UniFAR-FTUs huggingface dataset:
Pedigree generator Chromosome simulator Sampling and marker tool Population parameters Coalescence simulator Chromosome simulator tool Sampling Marker tool Pedigree generator Disease model and sample sizes Population parameters Chromosomal parameters Allele data Allele data Disease model and sample 

We propose a novel two-phase population simulator for generating diploid marker allele data in isolated populations. Our simulator extends Populus, an exact forward-in-time simulator for isolated populations, with a coalescent simulator. The coalescent, while not suitable for completely replacing Populus, is an useful substitute for the over-simpli ed founder generator used in Populus. We believe that this combination makes Hybridsim a very attractive choice for simulating large populations for case-control studies. First in the simulation process a founder population is simulated using an approximated coalescent process with a stepwise and/or in nite sites mutation model in order to establish a realistic genealogy and mutation history for the founders. In the second phase, a separate genealogy and an exact recombination history is generated for the isolate with a discrete generation version of Populus. This enables an accurate simulation of a large population isolate. A dominant mutation disease model can be speci ed into the population afterwards, and nally samples of various types can be obtained for further study. An arbitrary amount of SNP and/or STR markers generated in the coalescence process can be used as markers in the nal allele data. We also discuss some implementation issues and describe our own implementation, which is available for download along with simulated data.
GTI at TASS 2016: Supervised Approach for Aspect Based Sentiment Analysis in Twitter

This paper describes the participation of the GTI research group of AtlantTIC, University of Vigo, in tass 2016. This workshop is framed within the XXXII edition of the Annual Congress of the Spanish Society for Natural Language Processing event. In this work we propose a supervised approach based on classifiers, for the aspect based sentiment analysis task. Using this technique we managed to improve the performance of previous years, obtaining a solution reflecting the actual state-of-the-art.
Adaptive Data Replication Scheme Based on Access Count Prediction in Hadoop

Hadoop, an open source implementation of the MapReduce framework, has been widely used for processing massive-scale data in parallel. Since Hadoop uses a distributed file system, called HDFS, the data locality problem often happens (i.e., a data block should be copied to the processing node when a processing node does not possess the data block in its local storage), and this problem leads to the decrease in performance. In this paper, we present an Adaptive Data Replication scheme based on Access count Prediction (ADRAP) in a Hadoop framework to address the data locality problem. The proposed data replication scheme predicts the next access count of data files using Lagrange’s interpolation with the previous data access count. With the predicted data access count, our adaptive data replication scheme determines whether it generates a new replica or it uses the loaded data as cache selectively, optimizing the replication factor. Furthermore, we provide a replica placement algorithm to improve data locality effectively. Performance evaluations show that our adaptive data replication scheme reduces the task completion time in the map phase by 9.6% on average, compared to the default data replication setting in Hadoop. With regard to data locality, our scheme offers the increase of node locality by 6.1% and the decrease of rack and rack-off locality by 45.6% and 56.5%, respectively. Hadoop, Data locality, Access prediction, Data replication, Data placement
Secure program update using broadcast encryption for clustered wireless sensor networks

Securing Network Program update is essential for many crucial military applications. Present Network Programming protocols proposed by Hailun Tan et al. provides confidentiality and authentication with high computational effort and power consumption. We have developed a confidential network program update protocol for clustered wireless sensor networks. Our scheme has two phases, key computation phase and network program update phase. In key computation phase, we provide an efficient key computation scheme for securing the program image. The key is dynamically computed using broadcast encryption scheme when required without storing neither any keys before deployment, nor communicating directly. Network program update phase follows an approach based on Deluge, an open source code dissemination protocol, and provides confidentiality along with authentication. An immediate and independent authentication is achieved without time synchronization between the base station and the sensor nodes. The scheme is resilient to malicious program image injection by the compromised nodes. Mobile agents are used to know about the node compromise. We implement our scheme in TinyOS and evaluate the performance.
New Instructional Design Model for Learning Objects : AAUF Model

In today’s learning and education systems, educational technology and E-learning systems become an integral part of the school environment. A successful Elearning system requires different components such as IT infrastructure, smart classrooms, learning gateways, and digital content or E-content. The e-content, is an important component due to the fact that any digital content must match the expectations of both educators and students. The core of an effective digital content is the design and development of the Learning Objects. Building interactive Learning Objects incorporates both pedagogical and technical factors. The development of LO’s must consider several factors such as the instructional design, graphical design, and usability. This paper introduces a new development model of Learning Objects that incorporates both the pedagogical and technical issues. The new model integrates interactive factors related to the instructional design process and blends them with the factors related to the software development.
Distinct Morphological Stages of Dentate Granule Neuron Maturation in the Adult Mouse Hippocampus

Adult neurogenesis in the dentate gyrus may contribute to hippocampus-dependent functions, yet little is known about when and how newborn neurons are functional because of limited information about the time course of their connectivity. By using retrovirus-mediated gene transduction, we followed the dendritic and axonal growth of adult-born neurons in the mouse dentate gyrus and identified distinct morphological stages that may indicate different levels of connectivity. Axonal projections of newborn neurons reach the CA3 area 10–11 d after viral infection, 5–6 d before the first spines are formed. Quantitative analyses show that the peak of spine growth occurs during the first 3–4 weeks, but further structural modifications of newborn neurons take place for months. Moreover, the morphological maturation is differentially affected by age and experience, as shown by comparisons between adult and postnatal brains and between housing conditions. Our study reveals the key morphological transitions of newborn granule neurons during their course of maturation.
Higher Education Institutional and Program Evaluations in Taiwan and the Emerging Roles of Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT).

Post-secondary education institutions in Taiwan are divided into two tracks, general higher education (HE) and technological and vocational education (TVE). The evaluation of all universities/colleges is mandated by the University Act. Higher education institutions receive mandated institutional evaluation every six years and program evaluation every five years. The purpose of this paper is to briefly introduce the status of higher education institutional and program evaluations in Taiwan as well as the emerging roles of the Higher Education Evaluation and Accreditation Council of Taiwan (HEEACT). Both institutional and program evaluations are accreditation-oriented, adopting the PDCA (Plan-Do-Check-Act) cycle with an emphasis on institutional and program self-positioning, student learning outcome, and mechanism for continuous improvement. As the third-party planner and implementer of higher education institutional and program evaluations, HEEACT has conducted internal and external assessments as well as entrusted third-party meta-evaluation to assure its quality of work. Faced with the emerging challenges, such as the Ministry of Education’s new policy on requiring some universities/colleges to implement self-conducted external evaluation in replacement of the thirdparty program evaluation, HEEACT has to alter its roles and becomes a Critical Friend of higher education institutions and programs, a Change Agent of higher education institutional and program evaluation, and an Effective Facilitator of the international exchanges and cooperation on quality assurance and mutual recognitions of national qualifications.
Abeta(1-42) Enhances Neuronal Excitability in the CA1 via NR2B Subunit-Containing NMDA Receptors

Neuronal hyperexcitability is a phenomenon associated with early Alzheimer's disease. The underlying mechanism is considered to involve excessive activation of glutamate receptors; however, the exact molecular pathway remains to be determined. Extracellular recording from the CA1 of hippocampal slices is a long-standing standard for a range of studies both in basic research and in neuropharmacology. Evoked field potentials (fEPSPs) are regarded as the input, while spiking rate is regarded as the output of the neuronal network; however, the relationship between these two phenomena is not fully clear. We investigated the relationship between spontaneous spiking and evoked fEPSPs using mouse hippocampal slices. Blocking AMPA receptors (AMPARs) with CNQX abolished fEPSPs, but left firing rate unchanged. NMDA receptor (NMDAR) blockade with MK801 decreased neuronal spiking dose dependently without altering fEPSPs. Activating NMDARs by small concentration of NMDA induced a trend of increased firing. These results suggest that fEPSPs are mediated by synaptic activation of AMPARs, while spontaneous firing is regulated by the activation of extrasynaptic NMDARs. Synaptotoxic Abeta(1-42) increased firing activity without modifying evoked fEPSPs. This hyperexcitation was prevented by ifenprodil, an antagonist of the NR2B NMDARs. Overall, these results suggest that Abeta(1-42) induced neuronal overactivity is not dependent on AMPARs but requires NR2B.
Discovery of MicroRNA conservative sites in drosophila melanogaster

MicroRNAs(MiRNAs) are ∼22nt non-coding RNAs which regulate gene expression in numerous species. Several computational approaches have been conducted to predict precursor miRNA secondary structure, discover target gene and study miRNA regulatory mechanism. However, there are few studies for analyzing mature miRNA sites. This paper proposes a novel framework, based on information entropy, to discover mature miRNA site. The structure information and sequence information are both taken into account. The important degree of sites is evaluated by information entropy. A lower information entropy usually means the miRNA site is more conservative. The experimental results indicate that our approach is useful to identify mature miRNA sites.
Generalized delay optimization of resistive interconnections through an extension of logical effort

The resistance of VLSI interconnections is significant. Previous studies have proposed optimal repeater schemes using simple buffers for delay optimization of the interconnection. A more general approach that handles arbitrary logic gates as well as buffers is proposed. The methodology is based on an extension of the concept of logical effort. The optimization yields proper spacing of the given logic gates, additional repeaters (buffers) required for a given RC line, and sizing of all the gates. This approach is applicable to design situations where existing CMOS logic gates must be considered in the overall repeater scheme. <<ETX>>
Analyzing fault tolerance on parallel genetic programming by means of dynamic-size populations

This paper presents an experimental research on the size of individuals when dynamic size populations are employed with Genetic Programming (GP). By analyzing the individual's size evolution, some ideas are presented for reducing the length of the best individual while also improving the quality. This research has been performed studying both individual's size and quality of solutions, considering the fixed-size populations and also dynamic size by means of the plague operator. We propose an improvement to the Plague operator, that we have called Random Plague, that positively affects the quality of solutions and also influences the individuals' size. The results are then considered from a quite different point of view, the presence of processors failures when parallel execution over distributed computing environments are employed. We show that results strongly encourage the use of Parallel GP on non fault-tolerant computing resources: experiments shows the fault tolerant nature of Parallel GP.
Complexity of nding dense subgraphs

The k-f(k) dense subgraph problem((k; f(k))-DSP) asks whether there is a k-vertex subgraph of a given graph G which has at least f(k) edges. When f(k)= k(k − 1)=2, (k; f(k))-DSP is equivalent to the well-known k-clique problem. The main purpose of this paper is to discuss the problem of nding slightly dense subgraphs. Note that f(k) is about k for the k-clique problem. It is shown that (k; f(k))-DSP remains NP-complete for f(k)= (k ) where may be any constant such that 0¡ ¡ 1. It is also NP-complete for “relatively” slightly-dense subgraphs, i.e., (k; f(k))-DSP is NP-complete for f(k)= ek=v(1+O(v −1)), where v is the number of G’s vertices and e is the number of G’s edges. This condition is quite tight because the answer to (k; f(k))-DSP is always yes for f(k)= ek2=v2(1− (v− k)=(vk − k)) that is the average number of edges in a subgraph of k vertices. Also, we show that the hardness of (k; f(k))-DSP remains for regular graphs: (k; f(k))-DSP is NP-complete for (v 1 )-regular graphs if f(k)= (k 2 ) for any 0¡ 1; 2 ¡ 1. 2002 Elsevier Science B.V. All rights reserved.
Data Analysis Techniques for Human Microwire Recordings: Spike Detection and Sorting, Decoding, Relation between Neurons and Local Field Potentials

This chapter gives a technical perspective on the procedures for an experiment to proceed from the acquisition of continuously sampled data from microwires all the way to points of time a putative single neuron fired a spike, to local field potential (LFP) recordings, and to decoding neurophysiological signals in single trials and in real time. In order to analyze extracellular waveforms, it is important to acquire data with high sampling rates. Sampling rates below 16 kHz can miss important aspects of the submillisecond structure of action potential waveforms. Current systems typically have sampling rates above 30 kHz. Another methodological consideration involves the use of 60 Hz notch filters. While purists will advocate examining raw data without any filters, the clinical environment often presents significant challenges and electrical artifact contaminations for neurophysiological recordings. Removing 60 Hz and harmonics with a notch filter can significantly enhance the signal-to-noise ratio (SNR) to discriminate action potentials. The focus in this chapter starts at the point of time the data has been stored by the acquisition system whereas chapter 5 in this volume describes the acquisition system and electrodes themselves. Microwires record the extracellular voltage at a particular point in space. This signal, a voltage as a function of time, is the linear superposition of a great number of current sources generated by electrically active components of the brain (Buzsáki et al., 2012), including synaptic events and action potentials propagating down an axon or backpropagating inside dendrites. In general, it is extremely difficult to decompose the extracellular signal into the single events that give rise to it. An important aspect of the extracellular signals that can sometimes lead to a reasonable interpretation is the occurrence of action potentials in the near vicinity of the microwire tip. In the rat hippocampus CA1 region, it has been estimated that electrodes can distinguish extracellular spikes from neuronal processes located as far away as 140 μm from the tip of the electrode (Buzsáki, 2004). The peak amplitude depends on the physical size of the neurons under study, making it most likely that a majority of extracellular recordings involve pyramidal cells (Henze et al., 2000) (see also brief discussion of extracellular waveforms in chapter 8). To our knowledge, in human recordings, there are no quantitative 6 Data Analysis Techniques for Human Microwire Recordings: Spike Detection and Sorting, Decoding, Relation between Neurons and Local Field Potentials
A new method for fuzzy interpolative reasoning in sparse fuzzy rule-based systems

In this paper, we present a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems. The proposed method not only can deal with multiple fuzzy rules interpolation based on polygonal membership functions, but also can overcome the drawbacks of the existing methods. It also guarantees the convexity of fuzzy interpolative reasoning results. The experimental result shows that the proposed method can generate more reasonable fuzzy interpolative reasoning results than the existing methods for sparse fuzzy rule-based systems.
A Mechanistic Model of Botrytis cinerea on Grapevines That Includes Weather, Vine Growth Stage, and the Main Infection Pathways

A mechanistic model for Botrytis cinerea on grapevine was developed. The model, which accounts for conidia production on various inoculum sources and for multiple infection pathways, considers two infection periods. During the first period (“inflorescences clearly visible” to “berries groat-sized”), the model calculates: i) infection severity on inflorescences and young clusters caused by conidia (SEV1). During the second period (“majority of berries touching” to “berries ripe for harvest”), the model calculates: ii) infection severity of ripening berries by conidia (SEV2); and iii) severity of berry-to-berry infection caused by mycelium (SEV3). The model was validated in 21 epidemics (vineyard × year combinations) between 2009 and 2014 in Italy and France. A discriminant function analysis (DFA) was used to: i) evaluate the ability of the model to predict mild, intermediate, and severe epidemics; and ii) assess how SEV1, SEV2, and SEV3 contribute to epidemics. The model correctly classified the severity of 17 of 21 epidemics. Results from DFA were also used to calculate the daily probabilities that an ongoing epidemic would be mild, intermediate, or severe. SEV1 was the most influential variable in discriminating between mild and intermediate epidemics, whereas SEV2 and SEV3 were relevant for discriminating between intermediate and severe epidemics. The model represents an improvement of previous B. cinerea models in viticulture and could be useful for making decisions about Botrytis bunch rot control.
Bounding sphere CAD model simplification for efficient collision detection in offline programming

Collision detection performance is one of the major bottlenecks of Automated Offline Programming (AOLP). Simplifying CAD models allows collision detection algorithms to run more quickly, as a result more complex procedures are able to be calculated in a reasonable amount of time using AOLP. This paper presents a randomised bounding volume method for calculating a sphere based representation of a CAD model while conservatively removing small features. The output has fewer spheres when compared with other sphere packing techniques due to the first stage of the algorithm which removes small features from the model. Using the representation generated by the bounding sphere simplification algorithm for collision detection can dramatically improve performance in simulations and motion planning processes commonly used in AOLP.
Developing Ontological Theories for Conceptual Models using Qualitative Research

Conceptual modelling is believed to be at the core of the IS discipline. There have been attempts to develop theoretical foundations for conceptual models, in particular ontological models as axiomatic reference systems. Although the notion of ontology has become popular in modelling theories, criticism has risen as to its philosophical presuppositions. Taking on this criticism, we discuss the task of developing socially constructed ontologies for modelling domains and outline how to enhance the expressiveness of ontological modelling theories by developing them via qualitative research methods such as Grounded Theory.
An Analysis of Alternative Measures of Fiscal Capacity for Regions of the Russian Federation

Some measure of fiscal capacity should be an important component of the system of equalization transfers for the regions of the Russian Federation. In order to enhance the understanding of the concepts and measurement issues involved, ISP Working Paper 97-3 discusses the concept of fiscal capacity as well as some general measurement issues. In that note, six measures are presented that can be used to measure the fiscal capacity of subnational regions. These six measures are (1) current or lagged revenue collections, (2) per capita personal income, (3) gross regional product, (4) total taxable resources, (5) the representative tax system and (6) the representative tax system using regression analysis.The purpose of the current note is to actually compute various measures of fiscal capacity for the subjects of the Russian Federation, and to demonstrate how these measures are computed. This is done in Section II. Next, Section III will present a comparison of each of the measures of fiscal capacity that are computed in Section II. Section IV contains a summary and some concluding remarks.
Demand for Irrigation Water for Pistachio Production from Depleting Groundwater Resources: Spatial Econometric Approach

Depletion of groundwater resources is an international problem, and groundwater is probably the world’s most extracted raw material. The agriculture sector is one of the biggest users of groundwater resources for irrigation activities, and it plays an important role in the depletion of these resources. The estimation of demand function for groundwater resources is the first step toward any policy recommendation in this field of research. However, only scarce attention has been given to empirical studies of the demand structure of groundwater resources by the help of econometrics and considering the quality of the resources in the context of a single aquifer. Therefore, an empirical estimation of the demand function for individual users which considers water quality enhances further economic analysis and results in better policy recommendations. In this study, we have analysed the economic factors and the groundwater quality as influencing variables on derived demand function for irrigation water in the pistachio production of the Rafsanjan aquifer in the southeastern part of Iran. The field study was conducted from November 2008- February 2009. Translog cost function has been applied for the estimation of the derived demand function for groundwater in pistachio production and its shadow price. The spatial econometrics has been applied to correct the results. Results show that water pumping costs are much less than their shadow prices.