Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between maternal age at conception and risk of idiopathic clubfoot

Background and purpose — Results from case-control studies of maternal age at conception and risk of idiopathic clubfoot have been inconsistent. We conducted a meta-analysis to determine whether there is any association between maternal age at conception and the morbidity of idiopathic clubfoot. Methods — We searched PubMed-MEDLINE, EMBASE, and the Cochrane Library up to June 2015 and supplemented the search with manual searches of the reference lists of the articles identified. 11 studies published between 1990 and 2015 were pooled. We investigated heterogeneity in maternal age and whether publication bias might have affected the results. Results — Compared to a control group, maternal age at conception of between 20 and 24 years old was associated with an increased risk of occurrence of clubfoot (OR = 1.2, 95% CI: 1.1–1.4). No such association was found for the age groups of ≥ 35, 30–34, 25–29, and < 20 years. There was no heterogeneity in the age groups of ≥ 35, 30–34, and 20–24 years, moderate heterogeneity in the 25- to 29-year age group, and a large degree of heterogeneity in the group that was < 20 years of age. The prediction intervals for the age groups of 25–29 and < 20 years were 0.56 to 1.3 and −0.39 to 2.4, respectively. We found no evidence of significant publication bias. Interpretation — From the results of this meta-analysis of 11 studies, maternal age at conception between 20 to 24 years of age appears to be associated with an increased risk of occurrence of clubfoot.
Minimum error bounded efficient ℓ1 tracker with occlusion detection

Recently, sparse representation has been applied to visual tracking to find the target with the minimum reconstruction error from the target template subspace. Though effective, these L1 trackers require high computational costs due to numerous calculations for ℓ1 minimization. In addition, the inherent occlusion insensitivity of the ℓ1 minimization has not been fully utilized. In this paper, we propose an efficient L1 tracker with minimum error bound and occlusion detection which we call Bounded Particle Resampling (BPR)-L1 tracker. First, the minimum error bound is quickly calculated from a linear least squares equation, and serves as a guide for particle resampling in a particle filter framework. Without loss of precision during resampling, most insignificant samples are removed before solving the computationally expensive ℓ1 minimization function. The BPR technique enables us to speed up the L1 tracker without sacrificing accuracy. Second, we perform occlusion detection by investigating the trivial coefficients in the ℓ1 minimization. These coefficients, by design, contain rich information about image corruptions including occlusion. Detected occlusions enhance the template updates to effectively reduce the drifting problem. The proposed method shows good performance as compared with several state-of-the-art trackers on challenging benchmark sequences.
Kinematic artifacts in prestack depth migration

Strong refraction of waves in the migration velocity model introduces kinematic artifacts? coherent events not corresponding to actual reflectors? into the image volumes produced by prestack depth migration applied to individual data bins. Because individual bins are migrated independently, the migration has no access to the bin component of slowness. This loss of slowness information permits events to migrate along multiple incident-reflected ray pairs, thus introducing spurious coherent events into the image volume. This pathology occurs for all common binning strategies, including common-source, common-offset, and common-scattering angle. Since the artifacts move out with bin parameter, their effect on the final stacked image is minimal, provided that the migration velocity model is kinematically correct. However, common-image gathers may exhibit energetic primary events with substantial residual moveout, even with the kinematically accurate migration velocity model.
Experiments in Multilingual Information

The multilingual information retrieval system of the future will need to be able to retrieve documents across language boundaries. This extension of the classical IR problem is particularly challenging, as signiicant resources are required to perform query translation. At Xerox, we are working to build a multilingual IR system and conducting a series of experiments to understand what factors are most important in making the system work. Using translated queries and a bilingual transfer dictionary, we have learned that cross-language multilingual IR is feasible, although performance lags considerably behind the monolingual standard. The experiments suggest that correct identiication and translation of multi-word terminology is the single most important source of error in the system, although ambiguity in translation also contributes to poor performance.
A Feature Survey for Emotion Classification of Western Popular Music

In this paper we propose a feature set for emotion classifi- cation of Western popular music. We show that by surveying a range of common feature extraction methods, a set of five features can model emotion with good accuracy. To evaluate the system we implement an in- dependent feature evaluation paradigm aimed at testing the property of generalizability; the ability of a machine learning algorithm to maintain good performance over different data sets.
Contributions of temporal fine structure cues to Chinese speech recognition in cochlear implant simulation

This study evaluated the relative contributions of temporal fine structure cues in different frequency bands to Mandarin speech recognition both in quiet and in noise. Chinese tone, vowel, consonant and sentence recognition scores were measured in a 4-channel continuous interleaved sampling (CIS) simulation model with six kinds of carriers: all noise carriers (N1234), all fine structure carriers (F1234) and fine structure carrier in one channel while noise carriers in the others (F1N234,F2N134, F3N124, F4N123). Results showed that low-frequency fine structure below 400 Hz contributed significantly to tone recognition, while mid-frequency fine structure from 400 to 1000 Hz contributed most to vowel and consonant recognition in quiet. But in severe noise it was the common contributions of the temporal fine structure in each band that improved the recognition performance of vowel and consonant significantly. For sentence recognition tones contributed most compared to vowel and consonant.
A Chemokine-Degrading Extracellular Protease Made by Group A Streptococcus Alters Pathogenesis by Enhancing Evasion of the Innate Immune Response

ABSTRACT Circumvention of the host innate immune response is critical for bacterial pathogens to infect and cause disease. Here we demonstrate that the group A Streptococcus (GAS; Streptococcus pyogenes) protease SpyCEP (S. pyogenes cell envelope protease) cleaves granulocyte chemotactic protein 2 (GCP-2) and growth-related oncogene alpha (GROα), two potent chemokines made abundantly in human tonsils. Cleavage of GCP-2 and GROα by SpyCEP abrogated their abilities to prime neutrophils for activation, detrimentally altering the innate immune response. SpyCEP expression is negatively regulated by the signal transduction system CovR/S. Purified recombinant CovR bound the spyCEP gene promoter region in vitro, indicating direct regulation. Immunoreactive SpyCEP protein was present in the culture supernatants of covR/S mutant GAS strains but not in supernatants from wild-type strains. However, wild-type GAS strains do express SpyCEP, where it is localized to the cell wall. Strain MGAS2221, an organism representative of the highly virulent and globally disseminated M1T1 GAS clone, differed significantly from its isogenic spyCEP mutant derivative strain in a mouse soft tissue infection model. Interestingly, and in contrast to previous studies, the isogenic mutant strain generated lesions of larger size than those formed following infection with the parent strain. The data indicate that SpyCEP contributes to GAS virulence in a strain- and disease-dependent manner.
A novel method for determining the phase-response curves of neurons based on minimizing spike-time prediction error

Regular firing neurons can be seen as oscillators. The phase-response curve (PRC) describes how such neurons will respond to small excitatory perturbations. Knowledge of the PRC is important as it is associated to the excitability type of neurons and their capability to synchronize in networks. In this work we present a novel method to estimate the PRC from experimental data. We assume that continuous noise signal can be discretized into independent perturbations at evenly spaced phases and predict the next spike based on these independent perturbations. The difference between the predicted next spike made at every discretized phase and the actual next spike time is used as the error signal used to optimize the PRC. We test our method on model data and experimentally obtained data and find that the newly developed method is robust and reliable method for the estimation of PRCs from experimental data.
Optimizing agent placement for flow reconstruction of DDoS attacks

The Internet today continues to be vulnerable to distributed denial of service (DDoS) attacks. We consider the design of a scalable agent-based system for collecting information about the structure and dynamics of DDoS attacks. Our system requires placement of agents on inter-autonomous system (AS) links in the Internet. The agents implement a self-organizing and totally decentralized mechanism capable of reconstructing topological information about the spatial and temporal structure of attacks. The system is effective at recovering DDoS attack structure, even at moderate levels of deployment. In this paper, we demonstrate how careful placement of agents within the system can improve the system's effectiveness and provide better tradeoffs between system parameters and the quality of structural information the system generates. We introduced two agent placement algorithms for our agent-based DDoS system. The first attempts to maximize the percentage of attack flows detected, while the second tries to maximize the extent to which we are able to trace back detected flows to their sources. We show, somewhat surprisingly, these two objectives are concomitant. Placement of agents in a manner which optimizes in the first criterion tends also to optimize with respect to the second criterion, and vice versa. Both placement schemes show a marked improvement over a system in which agents are placed randomly, and thus provide a concrete design process by which to instrument a DDoS flow reconstruction system that is effective at recovering attack structure in large networks at moderate levels of deployment.
Lessons Learned in Deploying the World’s Largest Scale Lustre File System

The Spider system at the Oak Ridge National Laboratory’s Leadership Computing Facility (OLCF) is the world’s largest scale Lustre parallel file system. Envisioned as a shared parallel file system capable of delivering both the bandwidth and capacity requirements of the OLCF’s diverse computational environment, the project had a number of ambitious goals. To support the workloads of the OLCF’s diverse computational platforms, the aggregate performance and storage capacity of Spider exceed that of our previously deployed systems by a factor of 6x 240 GB/sec, and 17x 10 Petabytes, respectively. Furthermore, Spider supports over 26,000 clients concurrently accessing the file system, which exceeds our previously deployed systems by nearly 4x. In addition to these scalability challenges, moving to a center-wide shared file system required dramatically improved resiliency and fault-tolerance mechanisms. This paper details our efforts in designing, deploying, and operating Spider. Through a phased approach of research and development, prototyping, deployment, and transition to operations, this work has resulted in a number of insights into large-scale parallel file system architectures, from both the design and the operational perspectives. We present in this paper our solutions to issues such as network congestion, performance baselining and evaluation, file system journaling overheads, and high availability in a system with tens of thousands of components. We also discuss areas of continued challenges, such as stressed metadata performance and the need for file system quality of service alongside with our efforts to address them. Finally, operational aspects of managing a system of this scale are discussed along with real-world data and observations.
Variable Viscosity Effect on Heat Transfer over a Continuous Moving Surface with Variable Internal H

The effect of temperature-dependent viscosity on heat transfer over a continuous moving surface with variable internal heat generation in micropolar fluids is studied. The fluid viscosity is assumed to vary as inverse linear function of temperature. The governing equations are transformed into dimensionless forms using the stream function and suitable variables then solved numerically using the Runge-Kutta numerical integration, procedure in conjunction with shooting technique. A parametric study illustrating the influence of the viscosity parameter, heat source generation and micropolar parameter on the velocity, microrotation and temperature profiles skin friction, couple stress as well as the Nusselt are investigated. The results of the parametric study are shown in graphic and tabulated.
Metallic Strip Gratings in the Sub-Subwavelength Regime

Metallic strip gratings (MSG) have different applications, ranging from printed circuits to filters in microwave domains. When they are under the influence of an electromagnetic field, evanescent and/or abnormal modes appear in the region between the traces, their utilization leading to the development of new electromagnetic nondestructive evaluation methods. This paper studies the behavior of MSGs in the sub-subwavelength regime when they are excited with TEz or TMz polarized plane waves and the slits are filled with different dielectrics. The appearance of propagating, evanescent and abnormal modes is emphasized using an electromagnetic sensor with metamaterials lens realized with two conical Swiss rolls, which allows the extraction of the information carried by the guided evanescent waves. The evanescent waves, manipulated by the electromagnetic sensor with metamaterial lenses, improve the electromagnetic images so that a better spatial resolution is obtained, exceeding the limit imposed by diffraction. Their theoretical and experimental confirmation opens the perspective for development of new types of sensors working in radio and microwave frequencies.
Iterative Frequency-Domain Equalization of Single-Carrier Transmissions over Doubly Dispersive Channels

Frequency-domain equalization (FDE) offers an attractive alternative to time-domain equalization in systems that communicate over large-delay-spread channels. Traditionally, FDE leverages the fact that time-domain convolution is equivalent to frequency-domain multiplication and the fact that time/frequency conversion is efficiently handled by the fast Fourier transform (FFT). In doubly dispersive channels, i.e., quickly varying large-delay-spread channels, the traditional FDE methods fail when the channel response varies significantly over the FFT analysis window. Here we present a new FDE that is based on Doppler channel shortening, soft iterative interference cancellation, and block decision feedback. Numerical simulations show that the proposed technique has advantages over the well-known FIR-MMSE-DFE in both performance and complexity.
Estimating the Economic Value of Lethal VersusNonlethal Deer Control in Suburban Communities

Negative people/wildlife interaction has raised public interest in wildlife population control. We present a contingent valuation study of alternative deer control measures considered for Hilton Head Island, SC. Lethal control using sharpshooters and nonlethal immuno-contraception techniques are evaluated. A mail-back survey was used to collect resident willingness-to-pay (WTP) information for reduced deer densities and consequent property damage. Residents are unwilling to spend more for the nonlethal alternative. The estimated WTP appears theoretically consistent as increasing levels of abatement for both lethal and nonlethal alternatives demonstrate diminishing marginal benefits. Over 60% of respondents bid zero regardless of control measure, suggesting a referendum would fail. However, only half of these zero bidders expressed no problem with deer, while the other half bid zero because of distaste for the control alternative, safety concerns, or doubt about effectiveness. Inclusion of these responses as legitimate zero bids depressed mean WTP estimates from 22 to 31%.
Analysis of Accuracy in Pointing with Redundant Hand-held Tools: A Geometric Approach to the Uncontrolled Manifold Method

This work introduces a coordinate-independent method to analyse movement variability of tasks performed with hand-held tools, such as a pen or a surgical scalpel. We extend the classical uncontrolled manifold (UCM) approach by exploiting the geometry of rigid body motions, used to describe tool configurations. In particular, we analyse variability during a static pointing task with a hand-held tool, where subjects are asked to keep the tool tip in steady contact with another object. In this case the tool is redundant with respect to the task, as subjects control position/orientation of the tool, i.e. 6 degrees-of-freedom (dof), to maintain the tool tip position (3dof) steady. To test the new method, subjects performed a pointing task with and without arm support. The additional dof introduced in the unsupported condition, injecting more variability into the system, represented a resource to minimise variability in the task space via coordinated motion. The results show that all of the seven subjects channeled more variability along directions not directly affecting the task (UCM), consistent with previous literature but now shown in a coordinate-independent way. Variability in the unsupported condition was only slightly larger at the endpoint but much larger in the UCM.
A constrained approach for extraction of pre-ictal discharges from scalp EEG

A constrained blind source separation (BSS) approach for separation of intracranial spikes from scalp electroencephalogram (EEG) has been proposed in this paper. This method is based on creating a template from intracranial data, which is then used in the form of a constraint in a BSS algorithm. To generate a suitable template, the segments during which the brain discharges are labelled are used to generate the necessary templates. Approximate entropy followed by peak detection and thresholding is used for this purpose. Constrained BSS is then applied to scalp data to extract the desired source and to evaluate its effect on scalp electrodes. The effectiveness of such a constrained approach has been demonstrated by comparing its outcome with that of the unconstrained method.
A Torso-Moving Balance Control Strategy for a Walking Biped Robot Subject to External Continuous Forces

Moving the torso laterally in a walking biped robot can be mechanically more torque-efficient than not moving the torso according to recent research. Motivated by this observation, a torque-efficient torso-moving balance control strategy of a walking biped robot subject to a persistent continuous external force is suggested and verified in this paper. The torso-moving balance control strategy consists of a preliminary step and two additional steps. The preliminary step (disturbance detection) is to perceive the application of an external force by a safety boundary of zero moment point, detected approximately from cheap pressure sensors. Step 1 utilizes center of gravity (COG) Jacobian, centroidal momentum matrix and linear quadratic problem calculation to shift the zero moment point to the center of the support polygon. Step 2 makes use of H∞ controllers for a more stable state shift from single support phase to double support phase. By comparing the suggested torso moving control strategy to the original control strategy that we suggested previously, a mixed balance control strategy is suggested. The strategy is verified through numerical simulation results.
A novel approach to data deduplication over the engineering-oriented cloud systems

This paper presents a duplication-less storage system over the engineering-oriented cloud computing platforms. Our deduplication storage system, which manages data and duplication over the cloud system, consists of two major components, a front-end deduplication application and a mass storage system as back-end. Hadoop distributed file system HDFS is a common distribution file system on the cloud, which is used with Hadoop database HBase. We use HDFS to build up a mass storage system and employ HBase to build up a fast indexing system. With a deduplication application, a scalable and parallel deduplicated cloud storage system can be effectively built up. We further use VMware to generate a simulated cloud environment. The simulation results demonstrate that our deduplication storage system is sufficiently accurate and efficient for distributed and cooperative data intensive engineering applications.