Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Modeling of Linkage and Association: Identifying Snps Responsible for a Linkage Signal

Once genetic linkage has been identified for a complex disease, the next step is often association analysis, in which single-nucleotide polymorphisms (SNPs) within the linkage region are genotyped and tested for association with the disease. If a SNP shows evidence of association, it is useful to know whether the linkage result can be explained, in part or in full, by the candidate SNP. We propose a novel approach that quantifies the degree of linkage disequilibrium (LD) between the candidate SNP and the putative disease locus through joint modeling of linkage and association. We describe a simple likelihood of the marker data conditional on the trait data for a sample of affected sib pairs, with disease penetrances and disease-SNP haplotype frequencies as parameters. We estimate model parameters by maximum likelihood and propose two likelihood-ratio tests to characterize the relationship of the candidate SNP and the disease locus. The first test assesses whether the candidate SNP and the disease locus are in linkage equilibrium so that the SNP plays no causal role in the linkage signal. The second test assesses whether the candidate SNP and the disease locus are in complete LD so that the SNP or a marker in complete LD with it may account fully for the linkage signal. Our method also yields a genetic model that includes parameter estimates for disease-SNP haplotype frequencies and the degree of disease-SNP LD. Our method provides a new tool for detecting linkage and association and can be extended to study designs that include unaffected family members.
A low cost oscillator for high data rate E-band transceivers

This paper proposes an oscillator design capable of achieving high data transmission rates of up to 1.5 Gbps with a modulation scheme of 256 QAM at E-band frequencies. A low phase noise oscillator and high quality factor resonator are implemented in this work. The proposed cavity resonator design is embedded in a low cost gold plated brass casing. Eigenmode simulations yield an unloaded quality factor in excess of 5800 at 20 GHz. The low phase noise oscillator comprises of commercially available and low cost components surface mounted on a low loss millimeter-wave substrate. The proposed 20 GHz oscillator makes use of a frequency doubler to drive a sub-harmonically pumped mixer aimed for E-band frequencies of 80 GHz. The expected phase noise of the oscillator is better than −103 dbc/Hz with 100 kHz offset while operating at 80 GHz.
Label Tree Embeddings for Acoustic Scene Classification

We present in this paper an efficient approach for acoustic scene classification by exploring the structure of class labels. Given a set of class labels, a category taxonomy is automatically learned by collectively optimizing a clustering of the labels into multiple meta-classes in a tree structure. An acoustic scene instance is then embedded into a low-dimensional feature representation which consists of the likelihoods that it belongs to the meta-classes. We demonstrate state-of-the-art results on two different datasets for the acoustic scene classification task, including the DCASE 2013 and LITIS Rouen datasets.
JTourBus: Simplifying Program Understanding by Documentation that Provides Tours Through the Source Code

Many small and medium-sized systems have little or no design documentation, which makes program understanding during maintenance enormously more difficult when performed by outsiders. Thus, if only minimal design documentation is available, which form should it take to maximize its usefulness? We suggest that it is helpful if the documentation describes a tour through the source code, leading the user directly to relevant details. This work reports an evaluation of this conceptual idea in the form of a controlled experiment with 59 student subjects working on a difficult program understanding task in the context of the 27 KLOC JHotDraw graphics framework. One group received a plain text documentation, the other received tour-structured documentation which they navigated by using an Eclipse plugin called JTourBus that we constructed for the experiment. The results indicate that program understanding can be achieved somewhat faster (albeit not more correctly) with JTourBus than with a plain text document.
Tagging Webcast Text in Baseball Videos by Video Segmentation and Text Alignment

Sports video annotation, an active research area in the field of multimedia content understanding, is an essential process in applications, such as summarization, highlight extraction, event detection, and retrieval. This paper considers the issue in relation to the annotation of baseball videos. Conventional baseball video annotation frameworks are based primarily on video content analysis, such as scoreboard recognition and machine learning techniques, which require a substantial amount of human input to collect and organize training data. The performance of such frameworks might become unstable if they encounter audiovisual patterns not included in the training data. To address the issue, we propose a novel framework for baseball video annotation that aligns high-level webcast text with low-level video content. Several cues, which are derived from the video content and webcast text, are utilized for alignment by leveraging hierarchical agglomerative clustering and genetic algorithm optimization. In addition, we develop an unsupervised method to learn the pitch segment properties of baseball videos by Markov random walk, and thereby reduce the need for human intervention substantially. Our experiments demonstrate that the proposed framework yields a robust result against a variety of video content and enhances the automaticity in baseball video annotation.
A New Scheme for Vision Based Flying Vehicle Detection Using Motion Flow Vectors Classification

This paper presents a vision based scheme for detecting flying vehicle using a new feature extraction and correspondence algorithm as well as a motion flow vectors classifier. The base of detection is to classify the motion flow vectors of object and scene at two video sequences from a mobile monocular CCD camera. For this purpose, we introduce a method to extract robust features from fuzzified edges at first frame. Then, correspondence features are approximated at second video frame by a multi resolution feature matching processing based on edge Gaussian pyramids. In next stage, the estimated motion flow vectors classify into two object and scene classes using a supervised machine learning method based on MLPs neural network. In final step, the flying vehicle localize by approximating the contour of object based on a convex hull algorithm. Experimental results demonstrate that the proposed method has proper stability and reliability especially for the detection of aerial vehicle in applications with mobile camera.
An Evaluation Summary Method Based on a Combination of Content and Linguistic Metrics

This paper presents a new automated method for evaluating the content of a text summary. The proposed method is based on a combination of features encompassing scores of content and others of linguistic quality. This method relies on a learning technique called linear regression. The objective of this combination is to predict the PYRAMID score from the features used. In order to evaluate the presented method, we are interested in two levels of granularity evaluation: the first is named Microevaluation and proposes an evaluation of each summary while the second is called Macro-evaluation and it is applied at the level of each system. The resulting metric shows an improvement upon standard metrics by increasing the correlation with the PYRAMID metric.
6-T SRAM performance assessment with stacked silicon nanowire MOSFETs

This paper assesses the 6-T SRAM performance and provides the design methodology with stacked gate-all-around silicon nanowire (NW) MOSFETs. To achieve high density design while preserving performance, different numbers of stacked NW MOSFETs are investigated via three-dimensional TCAD simulation. Due to tradeoff between read stability and writeability margins, adjusting the relative strengths of the transistors is needed but it can not be done straightforwardly as the widths of transistors are now quantized. Furthermore, when 3D stacking nanowires technique is used, another design issue with various stacked transistors has to be taken into account. This work simulates butterfly curves and N-curves to assess the device performance and provides an optimal design methodology for feasible manufacturability and good performance while using high density stacking technique. It is suggested that for the same stacked layers, though high stacking number favors writeability, it is limited to three layers due to source/drain series resistances. The double stacking is feasible for balanced read and write performances.
A Nonintrusive and Single-Point Infrastructure-Mediated Sensing Approach for Water-Use Activity Recognition

Recent years, a variety of infrastructure-mediated sensing methods have been proposed to recognize activities of daily living (ADLs). However, due to the inconvenience such as high-cost, difficult-to-install, intrusive and applicable to the house with specific architectures alone, existing water-use activity recognition methods cannot be widely used into people's houses. In this paper, a single-point infrastructure-mediated sensing technique is proposed for water-use activity recognition. A single 3-axis accelerometer sensor is attached to the surface of the main water pipe in the house to detect and collect the vibration signals of the main water pipe. These signal data are then processed through six modules in the proposed activity recognition system. Four classes of water-use activities (Bathing, Flushing toilet, Cooking and Washing) are classified by the system and experimental results show that our system can recognize about 70.37% water-use activities.
Memory and surprisal in human sentence comprehension

Humboldt famously described language as a system of rules which “makes infinite use of finite means” (Humboldt, 1836; Chomsky, 1965) and this is doubly true in the study of language comprehension. On the one hand, the comprehender’s knowledge of language must be finitely characterized: the brain itself as a computational device is finite, as is the comprehender’s experience of her native language. Hence understanding is an act of generalization: the comprehender must apply the knowledge gleaned from her lifetime of previous linguistic experience to analyze a new sentence and infer what the speaker is likely to have intended to mean. This need for analysis gives rise to the second sense in which Humboldt’s aphorism is true: to understand a sentence in real time the comprehender must deploy her limited cognitive resources to analyze input that is potentially unbounded in its complexity. Nowhere are these truths more evident than in the determination of sentence structure during language comprehension, as in (1) below. Before you go on reading, take as much time as you need to fully understand this sentence, and while you are doing so, reflect upon what you find difficult about it. You may even want to write down your reflections on its difficulty so that you can remind yourself of them once you reach the end of the chapter.
Geometry of giant star model atmospheres: a consistency test

Aims. We investigate the effect of a geometric inconsistency in the calculation of synthetic spectra of giant stars. Methods. Spectra computed with model atmospheres calculated in spherical geometry while using the plane-parallel approximation for line formation calculations (s_p), as well as the fully plane-parallel case (p_p), are compared to the consistently spherical case (s_s). Results. We present abundance differences for solar metallicity models with Teff ranging from 4000 to 6500 K and log g from 0.5 to 3.0 [cgs]. The effects are smaller for s_p calculations (−0.1 dex in the worst case) than for the p_p case (up to +0.35 dex for minority species and at most −0.04 dex for majority species), both with respect to the s_s case. In the s_p case the differences increase slightly with temperature, while in the p_p case they show a more complex behaviour. In both cases the effects decrease with increasing log g and increase with equivalent width. Conclusions. Within the parameter range of F, G and K giants, consistency seems to be less important than using a spherical model atmosphere. The abundance differences due to sphericity effects presented here can be used for error estimation in abundance studies relying on plane-parallel modelling.
Pharmaceutical treatment studies in autism and ADHD: A design based review of study quality

Abstract The overall design quality of studies conducted on psychotropic substances prescribed to autism spectrum disorder and attention deficit hyperactivity disorder children is reviewed. Searches were conducted on Medline and Cochrane Controlled Trials Register. Peer-reviewed, published studies, written in English were included. Only studies that focused on children, had a minimal sample size of ten participants, and were conducted between 1994 and 2004 were included in the review. Two hundred and eighty one studies were identified and reviewed with 184 (65.5%) focused primarily on methylphenidate, with the remaining 97 studies examined stimulants, antipsychotics, antidepressants, alpha agonists, anxiolytics, and mood stabilizers. Of these, 152 (54.1%) did not employ optimal double blind placebo controlled design and 106 (37.7%) were conducted with less than 30 participants. The upper quartile for median study duration across all medications examined was 9.75 weeks for double-blinded studies and 16 weeks for all studies. Many pharmacotherapy studies conducted on children with autism spectrum disorder and attention deficit hyperactivity disorder are of limited duration, weak quality design and may be seriously underpowered. The issue of follow-up is rarely adequately addressed. These findings raise both safety and efficacy questions that have yet to be adequately studied.
Implementation of mail filtering based on multi-attribute group decision making

The judgment of spam usually has some uncertainties, so it is easy to be misjudged, which lead to great loss. Aiming at the situation of misjudgment to mail filter presently, a method of spam filtering based on multi-attribute group decision making is presented in this paper. This kind of mail filtering is considered as processing of uncertain information. A reasonable comprehensive evaluation value is computed as a membership degree by integrating ordered weighted averaging (OWA) operator and combination weighted averaging (CWAA) operator. Fuzzy support vector machines (FSVM) classification algorithm is used to classify mails. The experiments show that this method of mail filtering improves the Recall and Precision of spam filtering to some extent.
A low‐complexity QoS aware resource allocation algorithm for multi pair device‐to‐device (D2D) communications

Device‐to‐device (D2D) communication underlaying cellular networks is considered a promising technology to enhance network throughput, spectral efficiency, and performance of next generation networks. However, these potential gains hinge on the exploiting mechanism for resource sharing between cellular users (CUs) and D2D pairs. In this paper, we analytically formulate the problem of resource sharing as an optimization problem to maximize network throughput while guaranteeing the required quality‐of‐service (QoS) for both cellular and D2D users. We propose a low‐complexity four‐step resource allocation algorithm to address the optimization problem. We exploit a distance‐based method to derive a resource reuse candidacy graph (RCG) and three exclusive regions (ERs) to evaluate the suitability of resource sharing between each CU and D2D pair. Then, we use a paring mechanism to find the optimal set of D2D pairs for spectrum sharing with each CU to maximize network throughput. The performance of the proposed algorithm is investigated in terms of network throughput, outage probability, and computational complexity. Numerical results show that the proposed algorithm provides high throughput and spectrum utilization with low complexity while efficiently guaranteeing QoS for CUs and D2D pairs.
Data object and label placement for information abundant visualizations

Placing numerous data objects and their corresponding labels in limited screen space is a challenging problem in information visualization systems. Extending map-oriented techniques, this paper describes static placement algorithms and develops metrics (such as compactness and labeling rate) as a basis for comparison among these algorithms. A control panel facilitates user customization by showing the metrics for alternative algorithms. Dynamic placement techniques that go beyond map-oriented techniques demonstrate additional possibilities. User actions can lead to selective display of data objects and their labels.
Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference.
Digital PWM-Control-Based Active Vibration Cancellation for Switched Reluctance Motors

This paper presents a study on a control strategy for active vibration cancellation (AVC) and noise reduction in switched reluctance (SR) motors. It has been revealed that two-stage commutation control based on the natural frequency of the stator body has been effective in suppressing the vibration occurring on the stator body at the commutation. According to some considerations on the generation mechanism of the vibration, a new AVC control for variable-speed SR motor drives under digital PWM control is proposed. Experimental studies using a 12-kW three-phase 12/8 SR motor demonstrate that the proposed two-step commutation control using negative voltage PWM is much effective as an AVC and noise reduction technique. Moreover, the proposed control is evaluated from the viewpoints of drive performances such as torque ripple and copper loss.
Football boot insoles and sensitivity to extent of ankle inversion movement

Background: The capacity of the plantar sole of the foot to convey information about foot position is reduced by conventional smooth boot insoles, compared with barefoot surface contact. Objective: To test the hypothesis that movement discrimination may be restored by inserting textured replacement insoles, achieved by changing footwear conditions and measuring the accuracy of judgments of the extent of ankle inversion movement. Methods: An automated testing device, the ankle movement extent discrimination apparatus (AMEDA), developed to assess active ankle function in weight bearing without a balance demand, was used to test the effects of sole inserts in soccer boots. Seventeen elite soccer players, the members of the 2000 Australian Women’s soccer squad (34 ankles), took part in the study. Subjects were randomly allocated to start testing in: bare feet, their own football boots, own football boot and replacement insole, and on the left or right side. Subjects underwent six 50 trial blocks, in which they completed all footwear conditions. The sole inserts were cut to size for each foot from textured rubber “finger profile” sheeting. Results: Movement discrimination scores were significantly worse when subjects wore their football boots and socks, compared with barefoot data collected at the same time. The substitution of textured insoles for conventional smooth insoles in the football boots was found to restore movement discrimination to barefoot levels. Conclusions: The lower active movement discrimination scores of athletes when wearing football boots with smooth insoles suggest that the insole is one aspect of football boot and sport shoe design that could be modified to provide the sensory feedback needed for accurate foot positioning.
Brief therapy for post-traumatic stress disorder symptoms in maltreated youth in a shelter care facility

Therapy to address post-traumatic stress disorder (PTSD) symptoms in maltreated youth has re- ceived increased research attention in recent years. However, little data are available regarding the treat- ment of youth temporarily housed in shelter care facilities when parents are unavailable or inaccessible. The present study examined a brief group therapy protocol for such youth in a county-operated shelter. Participants received 1-6 sessions of treatment depending on their length of stay at the shelter. Treatment components included psychoeducation, anxiety management, cognitive restructuring and coping skills, emotional expression, mindfulness, exposure-based practice, boundary setting, and journaling. Results re- vealed a significant reduction in PTSD symptoms overall and the number of group therapy sessions medi- ated pre-treatment and post-treatment scores on various dependent measures. In addition, level of pre- treatment dissociation predicted reduction in PTSD levels. These preliminary results indicate that brief treatment for youth temporarily housed in a shelter care facility can provide some amelioration of PTSD- related symptoms.
Feature Space Modification for Content-Based Music Retrieval Based on User Preferences

This paper proposes a feature space modification method for feature extraction of music, which is effective for the development of a content-based music information retrieval (MIR) system based on user preferences. The proposed method conducts clustering of all songs in the music collection, and utilizes the resulting cluster IDs as training data for feature space modification, and is capable to automatically generate a feature space which is suitable to the content of any music collection. Experiment results prove that the proposed method improves accuracy of user preference based MIR