Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene-based multiple regression association testing for combined examination of common and low frequency variants in quantitative trait analysis

Multi-marker methods for genetic association analysis can be performed for common and low frequency SNPs to improve power. Regression models are an intuitive way to formulate multi-marker tests. In previous studies we evaluated regression-based multi-marker tests for common SNPs, and through identification of bins consisting of correlated SNPs, developed a multi-bin linear combination (MLC) test that is a compromise between a 1 df linear combination test and a multi-df global test. Bins of SNPs in high linkage disequilibrium (LD) are identified, and a linear combination of individual SNP statistics is constructed within each bin. Then association with the phenotype is represented by an overall statistic with df as many or few as the number of bins. In this report we evaluate multi-marker tests for SNPs that occur at low frequencies. There are many linear and quadratic multi-marker tests that are suitable for common or low frequency variant analysis. We compared the performance of the MLC tests with various linear and quadratic statistics in joint or marginal regressions. For these comparisons, we performed a simulation study of genotypes and quantitative traits for 85 genes with many low frequency SNPs based on HapMap Phase III. We compared the tests using (1) set of all SNPs in a gene, (2) set of common SNPs in a gene (MAF ≥ 5%), (3) set of low frequency SNPs (1% ≤ MAF < 5%). For different trait models based on low frequency causal SNPs, we found that combined analysis using all SNPs including common and low frequency SNPs is a good and robust choice whereas using common SNPs alone or low frequency SNP alone can lose power. MLC tests performed well in combined analysis except where two low frequency causal SNPs with opposing effects are positively correlated. Overall, across different sets of analysis, the joint regression Wald test showed consistently good performance whereas other statistics including the ones based on marginal regression had lower power for some situations.
Requirements analysis for customizable software: a goals-skills-preferences framework

Software customization has been argued to benefit both the productivity of software engineers and end users. However, most customization methods rely on specialists to manually tweak individual applications for a specific user group. Existing software development methods also fail to acknowledge the importance of different kinds of user skills and preferences and how these might be incorporated into a customizable software design. We propose a framework for performing requirements analysis on user goals, skills, and preferences in order to generate a customizable software design. We illustrate our methodology with an email system and review an on-going case study involving users with traumatic brain injury.
Measuring and partitioning the high‐order linkage disequilibrium by multiple order Markov chains

A map of the background levels of disequilibrium between nearby markers can be useful for association mapping studies. In order to assess the background levels of linkage disequilibrium (LD), multilocus LD measures are more advantageous than pairwise LD measures because the combined analysis of pairwise LD measures is not adequate to detect simultaneous allele associations among multiple markers. Various multilocus LD measures based on haplotypes have been proposed. However, most of these measures provide a single index of association among multiple markers and does not reveal the complex patterns and different levels of LD structure. In this paper, we employ non‐homogeneous, multiple order Markov Chain models as a statistical framework to measure and partition the LD among multiple markers into components due to different orders of marker associations. Using a sliding window of multiple markers on phased haplotype data, we compute corresponding likelihoods for different Markov Chain (MC) orders in each window. The log‐likelihood difference between the lowest MC order model (MC0) and the highest MC order model in each window is used as a measure of the total LD or the overall deviation from the gametic equilibrium for the window. Then, we partition the total LD into lower order disequilibria and estimate the effects from two‐, three‐, and higher order disequilibria. The relationship between different orders of LD and the log‐likelihood difference involving two different orders of MC models are explored. By applying our method to the phased haplotype data in the ENCODE regions of the HapMap project, we are able to identify high/low multilocus LD regions. Our results reveal that the most LD in the HapMap data is attributed to the LD between adjacent pairs of markers across the whole region. LD between adjacent pairs of markers appears to be more significant in high multilocus LD regions than in low multilocus LD regions. We also find that as the multilocus total LD increases, the effects of high‐order LD tends to get weaker due to the lack of observed multilocus haplotypes. The overall estimates of first, second, third, and fourth order LD across the ENCODE regions are 64, 23, 9, and 3%. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.
LRRK2 kinase activity and biology are not uniformly predicted by its autophosphorylation and cellular phosphorylation site status

Missense mutations in the Leucine-Rich Repeat protein Kinase 2 (LRRK2) gene are the most common genetic predisposition to develop Parkinson’s disease (PD) (Farrer et al., 2005; Skipper et al., 2005; Di Fonzo et al., 2006; Healy et al., 2008; Paisan-Ruiz et al., 2008; Lesage et al., 2010). LRRK2 is a large multi-domain phosphoprotein with a GTPase domain and a serine/threonine protein kinase domain whose activity is implicated in neuronal toxicity; however the precise mechanism is unknown. LRRK2 autophosphorylates on several serine/threonine residues across the enzyme and is found constitutively phosphorylated on Ser910, Ser935, Ser955, and Ser973, which are proposed to be regulated by upstream kinases. Here we investigate the phosphoregulation at these sites by analyzing the effects of disease-associated mutations Arg1441Cys, Arg1441Gly, Ala1442Pro, Tyr1699Cys, Ile2012Thr, Gly2019Ser, and Ile2020Thr. We also studied alanine substitutions of phosphosite serines 910, 935, 955, and 973 and specific LRRK2 inhibition on autophosphorylation of LRRK2 Ser1292, Thr1491, Thr2483 and phosphorylation at the cellular sites. We found that mutants in the Roc-COR domains, including Arg1441Cys, Arg1441His, Ala1442Pro, and Tyr1699Cys, can positively enhance LRRK2 kinase activity, while concomitantly inducing the dephosphorylation of the cellular sites. Mutation of the cellular sites individually did not affect LRRK2 intrinsic kinase activity; however, Ser910/935/955/973Ala mutations trended toward increased kinase activity of LRRK2. Increased cAMP levels did not lead to increased LRRK2 cellular site phosphorylation, 14-3-3 binding or kinase activity. In cells, inhibition of LRRK2 kinase activity leads to dephosphorylation of Ser1292 by Calyculin A and Okadaic acid sensitive phosphatases, while the cellular sites are dephosphorylated by Calyculin A sensitive phosphatases. These findings indicate that comparative analysis of both Ser1292 and Ser910/935/955/973 phosphorylation sites will provide important and distinct measures of LRRK2 kinase and biological activity in vitro and in vivo.
A Single-and Multi-Dimensional Cellular Automata Approach to Robot Formation Control

One of the challenges to the realization of harvesting solar power from space is overcoming the difficulties and high cost for the transportation and constructi on of a large orbiting solar reflector. One approach that has received attention is using thousands of individual robots moving in formation, each with a piece of the reflector attac hed, to form the structure. In previous work, we demonstrate an algorithm that treats a group of robots as a 1-dimensional ce llular automaton, which is able to establish formations de fined by a geometric description that can be expressed as a si ngle mathematical function. In this paper we extend the algorithm for robots to establish formations defined by multi ple mathematical functions in order to form grid structures.
A mobile game/app for enhanced ultrasound interpretation

Ultrasound imaging is widely used imaging modality. Ultrasound has many advantages: it is supporting continuous realtime imaging in 2D or 3D, relatively inexpensive, non invasive, and free of harmful radiation. Beside those advantages, it is being used in combination with navigation technology. Nevertheless, neurosurgeons need considerable experience to interpret ultrasound images. One possible solution is using the advantages of serious gaming to improve neurosurgeon’s skill. The feasibility of this solution was investigated by implementing a basic drawing application for drawing the tumor border in the specialization project. This thesis is a continuation of the specialization project. The first goal of this project was designing and implementing a full set of drawing and evaluation tools in the form of a serious game. After implementation, the most important goal was testing the effectiveness of the application. The goal was achieved by running a systematic experiment with real users. Participant’s results showed that they can learn to interpret by playing the application (MasterNeuroSurgeon). Feedback also reveals that the application is usable.
International Conference on Emerging Ubiquitous Systems and Pervasive Networks ( EUSPN-2013 ) An Engineering Design of 4-Bit Special Purpose Microprogrammed Processor

This work is a complementary part for what we proposed in [1]. In this paper, an undergraduate design experience for special purpose 4-bit microprocessor using the skills learned from digital logic design and Microprocessors courses is presented. The experience started in [1] by designing the ALU using the hardware printed circuit board and we are following it by completing the design by the instruction set architecture and the microprogram code. Our microprocessor contains – in addition to the ALUsix registers: A 4-bit accumulator register, Flag register that holds only zero (Z) and carry (C) flags, Program counter register (PC), Memory address register (MAR), Instruction register (IR), and Buffer Register. All programs and data are stored in the 1k RAM. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]
Estimating Distributions of Willingness to Pay for Heterogeneous Populations

Random parameters logit models have emerged as a standard approach in estimating public preferences for a range of goods and services. However, to simplify calculation of welfare measures, the marginal utility of income is often assumed to be constant across the population. We show that by shifting distributional assumptions from marginal utilities to the welfare measures themselves, a random parameters version of a censored logistic regression model (Cameron 1988) yields distributions of welfare measures more directly and without imposing any unnecessary assumption on the marginal utility of income. We develop the theoretical framework for the model and apply it to contingent choice survey data for siting a noxious facility in Rhode Island. In this application, our proposed model and random parameters logit yield similar mean willingness to pay, but welfare measures are more readily interpretable in the proposed model.
On the Main Parameters of Parameterized Codes

In this paper we will estimate the main parameters of some evaluation codes which are known as parameterized codes. We will find the length of these codes and we will give a formula for the dimension in terms of the Hilbert function associated to the vanishing ideal of the projective torus. Also we will find an upper bound for the minimum distance and, in some cases, we will give some lower bounds for the regularity index and the minimum distance. These lower bounds work in several cases, particularly for any parameterized code associated to the incidence matrix of uniform clutters and then they work in the case of graphs.
Hierarchical arc consistency: exploiting structured domains in constraint satisfaction problems

Constraint satisfaction problems can be solved by network consistency algorithms that eliminate local inconsistencies before constructing global solutions. We describe a new algorithm that is useful when the variable domains can be structured hierarchically into recursive subsets with common properties and common relationships to subsets of the domain values for related variables. The algorithm, HAC, uses a technique known as hierarchical arc consistency. Its performance is analyzed theoretically and the conditions under which it is an improvement are outlined. The use of HAC in a program for understanding sketch maps, Mapsee3, is briefly discussed and experimental results consistent with the theory are reported.
A Taxonomy of Active CodeD

We have developed a classiication of active networking archi-tectures which includes active packets and active extensions. This tax-onomy is based on the nature of the programs used by programmers. Pure active packets, like pure datagrams, carry suucient information for their evaluation. Pure active extensions prepare network elements for evaluation of subsequent packets. We develop a continuum based on the location of the code used to process a packet. The taxonomy allows us to predict the existence of a variety of new architectures. For example, caching code both improves performance and makes a system appear to be an active extension with high probability. Attractive hybrids can be constructed, with heavily authenticated code in an active extension invoked by lightweight active packets.
Ontology of Time in GFO

Time, events, changes and processes play a major role in conceptual modeling, and in information systems and computer science altogether. Accordingly, the representation of time structures and reasoning about temporal data and knowledge are important theoretical and practical research areas. We assume that a formal representation of temporal knowledge must use as a framework some toplevel ontology that describes the most general categories of temporal entities. In the current paper we discuss an ontology of time which is part of the foundational ontology GFO (General Formal Ontology). This ontology of time is inspired by ideas of Franz Brentano [1]. It is used to propose novel contributions to a number of problematic issues related to temporal representation and reasoning, among others, the Dividing Instant Problem and the problem of persistence and change. We present an axiomatization of the ontology as a theory in first-order logic. Eventually, metalogical analysis shows the consistency, completeness, and decidability of this theory.
Abnormal Response of the Proliferation and Differentiation of Growth Plate Chondrocytes to Melatonin in Adolescent Idiopathic Scoliosis

Abnormalities in the melatonin signaling pathway and the involvement of melatonin receptor MT2 have been reported in patients with adolescent idiopathic scoliosis (AIS). Whether these abnormalities were involved in the systemic abnormal skeletal growth in AIS during the peripubertal period remain unknown. In this cross-sectional case-control study, growth plate chondrocytes (GPCs) were cultured from twenty AIS and ten normal control subjects. Although the MT2 receptor was identified in GPCs from both AIS and controls, its mRNA expression was significantly lower in AIS patients than the controls. GPCs were cultured in the presence of either the vehicle or various concentrations of melatonin, with or without the selective MT2 melatonin receptor antagonist 4-P-PDOT (10 µM). Then the cell viability and the mRNA expression of collagen type X (COLX) and alkaline phosphatase (ALP) were assessed by MTT and qPCR, respectively. In the control GPCs, melatonin at the concentrations of 1, 100 nM and 10 µM significantly reduced the population of viable cells, and the mRNA level of COLX and ALP compared to the vehicle. Similar changes were not observed in the presence of 4-P-PDOT. Further, neither proliferation nor differentiation of GPCs from AIS patients was affected by the melatonin treatment. These findings support the presence of a functional abnormality of the melatonin signaling pathway in AIS GPCs, which might be associated with the abnormal endochondral ossification in AIS patients.
Optimal Mobile Data Offloading Policy through Delay Tolerant Networks with Selfish Nodes

Mobile data access is suffering the curse of the computationally enhanced increase of smart phones, which overloads the traditional cellular network. This paper tries to offload the cellular network traffic through Delay Tolerant Networks (DTN) formed by the short-range communication technologies in these smart phones (e.g., WiFi, Bluetooth). In particular, the content providers deliver L initial replicas of the same data through cellular network to L users. Then those users further propagate the information among all the subscribed users through opportunistic communications. However, phones are carried by different users who may be selfish and not want to help others. If the initial replicas are delivered to these selfish nodes, other users may not get data timely. This paper proposes a method to select the proper number of initial replicas and an optimal policy using the Markov process to distribute the limited initial replicas. Simulation results show the accuracy of the model, and numerical results show that our optimal policy can get better performance.
A Hybrid Meta Heuristic Algorithm for Discovering Classification Rule in Data Mining

The Meta heuristics provide acceptable solutions in a reasonable time for solving hard and complex problems in medical, science and engineering. In this paper we present a meta heuristic based technique for mining rule over a medical data base were the use of the ABC and PSO algorithm as new tool for data mining particularly in classification task. This new found tool, hybrid ABC and PSO, surely help the medical fraternity and diagnosis. The diagnosis quickly and accurately by applying the hybrid Meta heuristic algorithm. The proposed algorithm is compared with an existing algorithm.
Physical-Layer Network Coding in Two-Way Heterogeneous Cellular Networks With Power Imbalance

The growing demand for high-speed data, quality of service (QoS) assurance, and energy efficiency has triggered the evolution of fourth-generation (4G) Long-Term Evolution-Advanced (LTE-A) networks to fifth generation (5G) and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), which is a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximizing relay selection algorithm for a single cell with multiple relays assuming the decode-and-forward (DF) strategy. With nodes transmitting at different powers, the proposed algorithm adapts the resource allocation according to the differing link rates, and we prove theoretically that the optimization problem is log-concave. The proposed technique is shown to perform significantly better than the widely studied selection-cooperation technique. We then undertake an experimental study-on a software radio platform-of the decoding performance of PNC with unbalanced signal-to-noise ratios (SNRs) in the multiple-access transmissions. This problem is inherent in cellular networks, and it is shown that, with channel coding and decoders based on multiuser detection and successive interference cancellation, the performance is better with power imbalance. This paper paves the way for further research on multicell PNC, resource allocation, and the implementation of PNC with higher order modulations and advanced coding techniques.
Laparoscopy-Assisted Distal Gastrectomy for Early Gastric Cancer in the Elderly

Purpose With an increase in life expectancy, more elderly patients are presenting with gastric cancer. As a result it is yet be resolved whether laparoscopy assisted distal gastrectomy is a suitable treatment for elderly patients with early gastric cancer. This study retrospectively compared surgical outcomes of laparoscopy assisted distal gastrectomy between elderly and nonelderly patients with gastric cancer. Materials and Methods The study group was comprised of 316 patients who underwent laparoscopy assisted distal gastrectomy between April 2005 and December 2010. Of these patients, 93 patients whose ages were 65 years or more were compared with 223 patients who were younger. Results There were no differences in the short term outcome or minor complication rate between the elderly patients and the nonelderly patients. The hospital stay was significantly longer and the major complication rate was significantly higher for the elderly patients compared with nonelderly patients. Conclusions Laparoscopy assisted distal gastrectomy for early gastric cancer in the elderly patients had comparable operation time and blood loss with the nonelderly group. However, the safety and advantage of laparoscopy assisted distal gastrectomy in the elderly patients need to be further studied in higher volume trials.
Design of a Low Power Combinational Circuit by using Adiabatic Logic

A novel low power and Positive Feedback Adiabatic Logic (PFAL) combinational low power circuit is presented in this paper. The power consumption and general characteristics of the PFAL combinationallow power circuit arethen compared against two combinational low power circuit Efficient Charge Recovery Logic (ECRL), Conventional CMOS. The proposed PFAL combinational low power circuit design was proven to be superior to the other two designs in power dissipation and area. The combination of low power and low transistor count makes the new PFAL cell a viable option for low power design.
SIGNAL SYNTHESIS AND MIMO RADAR DETECTORS DESIGN: MORE ANTENNAS MEANS BETTER PERFORMANCE

The MIMO (multiple-input multiple-output) systems have gained popularity and attracted attention of late for their ability to enhance all areas of system performance. Inspired by the success of MIMO systems in communications, several publications have advocated the concept of new MIMO emerging active sensing radar technology from the system implementation point of view, as well as for signal processing techniques for target detection and parameter estimation. Reaping the full benefit of the superior performance enabled by the MIMO radar which exploits the special diversity of target scattering to improve detection performance over other types of array radars due to absence of target fades and analyse various topologies of multiple antenna systems in radars. In this paper, the present different digital arrays radar concepts are summarized, and performance is analyzed based on different modulation techniques to improve the resolution of the target parameters identifiability. This paper explores how transmit diversity can improve the direction finding performance of a radar utilizing an antenna array at the receiver and focuses on improving the performance of the signal detection.