Miracle-dz/UniFAR-FTUs huggingface dataset:
FamLBL: detecting rare haplotype disease association based on common SNPs using case-parent triads

MOTIVATION In recent years, there has been an increasing interest in using common single-nucleotide polymorphisms (SNPs) amassed in genome-wide association studies to investigate rare haplotype effects on complex diseases. Evidence has suggested that rare haplotypes may tag rare causal single-nucleotide variants, making SNP-based rare haplotype analysis not only cost effective, but also more valuable for detecting causal variants. Although a number of methods for detecting rare haplotype association have been proposed in recent years, they are population based and thus susceptible to population stratification. RESULTS We propose family-triad-based logistic Bayesian Lasso (famLBL) for estimating effects of haplotypes on complex diseases using SNP data. By choosing appropriate prior distribution, effect sizes of unassociated haplotypes can be shrunk toward zero, allowing for more precise estimation of associated haplotypes, especially those that are rare, thereby achieving greater detection power. We evaluate famLBL using simulation to gauge its type I error and power. Compared with its population counterpart, LBL, highlights famLBL's robustness property in the presence of population substructure. Further investigation by comparing famLBL with Family-Based Association Test (FBAT) reveals its advantage for detecting rare haplotype association. AVAILABILITY AND IMPLEMENTATION famLBL is implemented as an R-package available at http://www.stat.osu.edu/∼statgen/SOFTWARE/LBL/.
Data in Business Process Models, A Preliminary Empirical Study (Short Paper)

Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling data-or knowledge-intensive processes. We assume that traditional activity-centric process modeling languages lack the capabilities to adequately capture the complexity of such processes. To verify this assumption we conducted an online interview among BPM experts. The results not only allow us to identify various profiles of persons modeling business processes, but also the problems that exist in contemporary modeling languages w.r. t. The modeling of business data. Overall, this preliminary empirical study confirms the necessity of data-awareness in process modeling notations in general.
Development of a Modular Assay for Detailed Immunophenotyping of Peripheral Human Whole Blood Samples by Multicolor Flow Cytometry

The monitoring of immune cells gained great significance in prognosis and prediction of therapy responses. For analyzing blood samples, the multicolor flow cytometry has become the method of choice as it combines high specificity on single cell level with multiple parameters and high throughput. Here, we present a modular assay for the detailed immunophenotyping of blood (DIoB) that was optimized for an easy and direct application in whole blood samples. The DIoB assay characterizes 34 immune cell subsets that circulate the peripheral blood including all major immune cells such as T cells, B cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), neutrophils, eosinophils, and basophils. In addition, it evaluates their functional state and a few non-leukocytes that also have been associated with the outcome of cancer therapy. This DIoB assay allows a longitudinal and close-meshed monitoring of a detailed immune status in patients requiring only 2.0 mL of peripheral blood and it is not restricted to peripheral blood mononuclear cells. It is currently applied for the immune monitoring of patients with glioblastoma multiforme (IMMO-GLIO-01 trial, NCT02022384), pancreatic cancer (CONKO-007 trial, NCT01827553), and head and neck cancer (DIREKHT trial, NCT02528955) and might pave the way for immune biomarker identification for prediction and prognosis of therapy outcome.
A Novel 3-D Error Correcting Code Model with its Optimal Time Algorithm Analysis

For improving the reliability of the data stored up, this paper brings forward an improvement scheme. It expands the error correction from One-dimensional (1-D) model to Three-dimensional (3-D) model. This thesis has listed and has analyzed three models' (1-D, Two-dimensional (2-D) and 3-D) structure method and their error correction process, and from all-round aspects to compare the three kinds of models by using a procedure to simulate the actual error correction process. From large amount of result, we can see that the error correction ability of the advanced model has improved greatly comparing with the original model, and by optimizing the error correction process, the time of accomplishing error correction process has fallen to the lowest point, and has reached an agreeable level. Finally, by comparing the advanced model with RAID1 [1], testify further the reliability of the advanced model.
On Throughput-Fairness Tradeoff in Virtual MIMO Systems with Limited Feedback

We investigate the performance of channel-aware scheduling algorithms designed for the downlink of a wireless communication system. Our study focuses on a two-transmit antenna cellular system, where the base station can only rely on quantized versions of channel state information to carry out scheduling decisions. The motivation is to study the interaction between throughput and fairness of practical spatial multiplexing schemes when implemented using existing physical layer signaling, such as the one that exists in current wideband code division multiple access downlink. Virtual MIMO system selects at each time instant a pair of users that report orthogonal (quantized) channels. Closed-form expressions for the achievable sum-rate of three different channel-aware scheduling rules are presented using an analytical framework that is derived in this work. Our analysis reveals that simple scheduling procedures allow to reap a large fraction (in the order of 80%) of the sum-rate performance that greedy scheduling provides. This overall throughput performance is obtained without affecting considerably the optimal short-term fairness behavior that the end users would perceive.
A Study of Spectrum Sensing Algorithm for Ultra High Speed WLAN

For a higher transmission rate and a greater throughput, New Generation Ultra High Speed WLAN must introduce Cognitive Radio (CR) technology to enhance frequency spectrum utilization. To detect the channel, this paper using two spectrum sensing algorithms, energy detection and preamble detection. The former utilizes the energy in signal to detect; the latter utilizes some features of the signal in the channel to detect. This paper then tests and verifies the two algorithms, and the model uses the 8X8 MIMO-OFDM system and high order modulation, so they can be used for detecting channel in Ultra High Speed WLAN environment. From the result, this two algorithms are feasible.
Title : Distinguishing and understanding thermogenic and biogenic sources of methane using multiply substituted isotopologues

Sources of methane to sedimentary environments are commonly identified and quantified using the stable-isotopic compositions of methane. The methane “clumped-isotope geothermometer”, based on the measurement of multiply substituted methane isotopologues (CH3D and CH2D2), shows promise in adding new constraints to the sources and formational environments of both biogenic and thermogenic methane. However, questions remain about how this geothermometer behaves in systems with mixtures of biogenic and thermogenic gases and different biogenic environments. We have applied the methane clumped-isotope thermometer to a mixed biogenic-thermogenic system (Antrim Shale, USA) and to biogenic gas from gas seeps (Santa Barbara and Santa Monica Basin, USA), a pond on the Caltech campus, and methanogens grown in pure-culture. We demonstrate that clumped-isotope based temperatures add new quantitative constraints to the relative amounts of biogenic vs. thermogenic gases in the Antrim Shale indicating a larger proportion (~50%) of thermogenic gas in the system than previously thought. Additionally, we find that the clumped-isotope temperature of biogenic methane appears related to the environmental settings in which the gas forms. In systems where methane generation rates appear to be slow (e.g., the Antrim Shale and gas seeps), microbial methane forms in or near both internal isotopic equilibrium and hydrogen-isotope equilibrium with environmental waters. In systems where methane forms rapidly, microbial methane is neither in internal isotopic equilibrium nor hydrogen-isotope equilibrium with environmental waters. A quantitative model of microbial methanogenesis that incorporates isotopes is proposed to explain these results. 1 Corresponding author: 1200 E. California Blvd, Pasadena, CA 91125, dstolper@caltech.edu, 626-395-3753
General vs. Interval Mappings for Streaming Applications

This paper deals with the problem of mapping pipelined applications on heterogeneous platforms whose processors are subject to failures. We address a difficult bi-criteria problem, namely deciding which stages to replicate, and on which resources, in order to optimize the reliability of the schedule, while guaranteeing a minimal throughput. Previous work had addressed the complexity of interval mappings, where the application is partitioned into intervals of consecutive stages (which are then replicated and assigned to processors). In this paper we investigate general mappings, where stages may be partitioned without any constraint, thereby allowing a better usage of processors and communication network capabilities. The price to pay for general mappings is a dramatic increase in the problem complexity. We show that computing the period of a given general mapping is an NP-complete problem, and we provide polynomial bounds to determine a (conservative) approximated value. The bi-criteria mapping problem itself becomes NP-complete on homogeneous platforms, while it is polynomial with interval mappings. We design a set of efficient heuristics, which we compare with interval mapping strategies through extensive simulations.
An Examination of Co-Teaching

Co-teaching has been developed as an instructional approach to support students with disabilities in general education classrooms. The purpose of this study was to identify teachers’ and students’ perspectives of co-teaching and the efficacy of this teaching approach. Forty-five co-teachers and 58 students with disabilities (N = 103), all of whom were new to co-taught classrooms during the 2004 through 2005 school year, participated in this study. Data were collected from surveys, observations, and records review. Significant differences in student academic and behavioral performances were found in comparisons between the year before co-teaching and the year of co-teaching. Students with disabilities and their teachers also reported positive perspectives about co-teaching. Based on these preliminary results, co-teaching appears to be an effective instructional delivery option for meeting the needs of students with disabilities in general education classrooms.
A Comparative Study of Free-Viewpoint Video Techniques For sports events

This paper presents a quantitative analysis of free-viewpoint video techniques applied to the problem of virtual view synthesis in sports events. A consideration of errors in the synthesis pipeline is presented along with a taxonomy of these errors and a framework for evaluating the quality of view synthesis when compared to ground truth. Three reconstruction techniques are evaluated, billboarding, shape from silhouette and view-dependent shape from silhouette. View-dependent rendering is used for virtual view synthesis. It is shown that currently the shape from silhouette technique provides the best completeness, while the view-dependent shape from silhouette technique provides the best appearance.
When is a Work-Around? Conflict & Negotiation in Computer Systems Development

The notion of a 'work-around' is a much used resource within the sociology of technology, reflecting an interest in showing how users are not simply shaped by technologies but how through adopting artefacts in ways other than for which they were designed or intended are also shapers of technology. Using the language and concerns of actor network theory, and focusing on recent developments within computer systems implementation, this article seeks to explore and add to our understanding of work-arounds through unpacking the work of one group of 'users' as they attempt to tailor and roll-out a system within the administration departments of their university. The argument is made that paying attention to the various networks which lead to and from work-arounds can improve our understanding of the way users both shape and are shaped by technologies. Focusing on work-arounds as 'networks-inplace' also allows us to highlight some of their contingencies; i.e., the other actors and entities on which these depend and are constituted.
Influence of a post-­graduate physical therapy residency program on clinical reasoning, professional development, and career advancement in Nairobi, Kenya

All rights reserved. This publication is intended for use solely by faculty, students, and staff of Nova Southeastern University. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, now known or later developed, including but not limited to photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author or the publisher.
ASYMPTOTIC STABILITY AND STABILITY SWITCHES IN A LINEAR INTEGRO-DIFFERENTIAL SYSTEM

This paper is concerned with the stability problem of a linear integro-differential sys- tem with distributed delay in the diagonal terms. We establish some explicit conditions for the zero solution of the system to be asymptotically stable. In particular, as the delay parameter increases monotonously under certain conditions, the zero solution switches finite times from stability to instability to stability, and becomes unstable eventually.
Design of a high-speed permanent magnet motor for the drive of a fuel cell air-compressor

This paper deals with the design of a 500 W permanent magnet machine used to drive the air-compressor of a 5 kW fuel cell. The authors focus on the optimization of the motor efficiency in order to minimize the energy consumption of the air-compressor which can represent up to 30% of the electrical energy delivered by the fuel cell. The authors justify the use of a permanent magnet machine by the fact that, by using rare earth Nd-Fe-B magnets, such a type of machine makes it possible to reach a high efficiency as well as a high power density. The optimized machine presented in this paper have theoretically more than 25% of its working area with an efficiency higher than 90% and the efficiency at the rated point equals to 92%. Those promising results of computation are confirmed by the first experimental results obtained with a prototype.
Marriage, Education and Housing Price

There are several reasons to explain why residential construction should depend on the population's education structure and marriage structure. We used Taiwanese time series data to estimate the relationships between them. Our results indicate that large groups of divorce adults are associated with higher rates of residential construction. Also, education-related factors are the dominant factors that can drive the housing demand.
Characterizing T Cells in SCID Patients Presenting with Reactive or Residual T Lymphocytes

Introduction. Patients with severe combined immunodeficiency (SCID) may present with residual circulating T cells. While all cells are functionally deficient, resulting in high susceptibility to infections, only some of these cells are causing autoimmune symptoms. Methods. Here we compared T-cell functions including the number of circulating CD3+ T cells, in vitro responses to mitogens, T-cell receptor (TCR) repertoire, TCR excision circles (TREC) levels, and regulatory T cells (Tregs) enumeration in several immunodeficinecy subtypes, clinically presenting with nonreactive residual cells (MHC-II deficiency) or reactive cells. The latter includes patients with autoreactive clonal expanded T cell and patients with alloreactive transplacentally maternal T cells. Results. MHC-II deficient patients had slightly reduced T-cell function, normal TRECs, TCR repertoires, and normal Tregs enumeration. In contrast, patients with reactive T cells exhibited poor T-cell differentiation and activity. While the autoreactive cells displayed significantly reduced Tregs numbers, the alloreactive transplacentally acquired maternal lymphocytes had high functional Tregs. Conclusion. SCID patients presenting with circulating T cells show different patterns of T-cell activity and regulatory T cells enumeration that dictates the immunodeficient and autoimmune manifestations. We suggest that a high-tolerance capacity of the alloreactive transplacentally acquired maternal lymphocytes represents a toleration advantage, yet still associated with severe immunodeficiency.
Impact of the Phytoestrogen Content of Laboratory Animal Feed on the Gene Expression Profile of the Reproductive System in the Immature Female Rat

The effect of the dietary background of phytoestrogens on the outcome of rodent bioassays used to identify and assess the reproductive hazard of endocrine-disrupting chemicals is controversial. Phytoestrogens, including genistein, daidzein, and coumestrol, are fairly abundant in soybeans and alfalfa, common ingredients of laboratory animal diets. These compounds are weak agonists for the estrogen receptor (ER) and, when administered at sufficient doses, elicit an estrogenic response in vivo. In this study, we assessed the potential estrogenic effects of dietary phytoestrogens at the gene expression level, together with traditional biologic end points, using estrogen-responsive tissues of the immature female rat. We compared the gene expression profile of the uterus and ovaries, as a pool, obtained using a uterotrophic assay protocol, from intact prepubertal rats fed a casein-based diet (free from soy and alfalfa) or a regular rodent diet (Purina 5001) containing soy and alfalfa. Estrogenic potency of the phytoestrogen-containing diet was determined by analyzing uterine wet weight gain, luminal epithelial cell height, and gene expression profile in the uterus and ovaries. These were compared with the same parameters evaluated in animals exposed to a low dose of a potent ER agonist [0.1 μg/kg/day 17α-ethynyl estradiol (EE) for 4 days]. Exposure to dietary phytoestrogens or to a low dose of EE did not advance vaginal opening, increase uterine wet weight, or increase luminal epithelial cell height in animals fed either diet. Although there are genes whose expression differs in animals fed the soy/alfalfa-based diet versus the casein diet, those genes are not associated with estrogenic stimulation. The expression of genes well known to be estrogen regulated, such as progesterone receptor, intestinal calcium-binding protein, and complement component 3, is not affected by consumption of the soy/alfalfa-based diet when assessed by microarray or quantitative reverse transcriptase–polymerase chain reaction analysis. Our results indicate that although diet composition has an impact on gene expression in uterus and ovaries, it does not contribute to the effects of an ER agonist.
The accuracy of telling time via oscillatory signals

Circadian clocks are the central timekeepers of life, allowing cells to anticipate changes between day and night. Experiments in recent years have revealed that circadian clocks can be highly stable, raising the question how reliably they can be read out. Here, we combine mathematical modeling with information theory to address the question how accurately a cell can infer the time from an ensemble of protein oscillations, which are driven by a circadian clock. We show that the precision increases with the number of oscillations and their amplitude relative to their noise. Our analysis also reveals that their exists an optimal phase relation that minimizes the error in the estimate of time, which depends on the relative noise levels of the protein oscillations. Lastly, our work shows that cross-correlations in the noise of the protein oscillations can enhance the mutual information, which suggests that cross-regulatory interactions between the proteins that read out the clock can be beneficial for temporal information transmission.
Wavelet analysis of the seismograms of the 2004 Sumatra‐Andaman earthquake and its application to tsunami early warning

We applied the wavelet transform in an attempt to detect long‐period components early in a seismogram. We analyzed the displacement seismograms of the 26 December 2004 Sumatra‐Andaman earthquake (Mw = 9.2) and the 28 March 2005 Nias earthquake (Mw = 8.7). Wavelet analysis is able to clearly distinguish the amplitudes of the long‐period W phase between the seismograms of the two earthquakes before the S wave reaches the station. It shows that the 2004 earthquake generates a W phase of significantly greater amplitude. This facility has potential application to the rapid identification of truly great earthquakes with high tsunami potential.
Minimizing a Convex Cost Closure Set

We study here a convex optimization problem with variables subject to a given partial order. This problem is a generalization of the known maximum (or minimum) closure problem and the isotonic regression problem. The algorithm we devise has complexity O(mnlog n2/m + n log U), for U the largest interval of values associated with a variable. For the quadratic problem and for the closure problem the complexity of our algorithm is strongly polynomial, O(mnlog n2/m). For the isotonic regression problem the complexity is O(n log U).