Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning About Machine Learning: The Promise and Pitfalls of Big Data and the Electronic Health Record.

In medicine, we are often interested in understanding differences between those with and without a specific disease. Such differences may point toward modifiable risk factors or, when combined into a quantitative model, allow us to predict who is at high risk of disease development to direct treatment. Along these lines, predictive models of heart failure (HF) have been a popular target: in the past decade, over 28 models of incident HF have been published.1 Most have good discriminatory properties (C statistics ranging from 0.70 to 0.89) and were developed using a modest number of predictors (typically <15), combined in linear models. Study populations varied from traditional epidemiological cohorts with regularly scheduled visits and physician-adjudicated outcomes to large patient databases that rely on diagnostic codes for defining HF cases and supplying predictive features. Article, see p 649 In recent years, there has been increasing excitement about the application of machine-learning strategies toward these same problems.2 Although such approaches are based on the same goal of patient classification, the machine-learning community, with its roots in computer science, tends to embrace far larger numbers of predictors, sometimes transformed or grouped or even derived empirically through feature engineering. These new predictors are then incorporated into a more flexible range of models to improve performance. Beyond attempting to achieve superior models, practitioners of machine learning also look to implement clinical decision support tools that use model predictions to guide physician behavior. In this issue of Circulation: Cardiovascular Quality and Outcomes , Ng et al3 describes an application of machine-learning approaches toward the problem of predicting incident HF within the electronic health record (EHR) with its potentially vast trove of data. A unique aspect of this study is the authors’ interest in not just reporting their model performance but its sensitivity to critical …
Volumetric imaging of rod and cone photoreceptor structure with a combined adaptive optics-optical coherence tomography-scanning laser ophthalmoscope

Abstract. We have designed and implemented a dual-mode adaptive optics (AO) imaging system that combines spectral domain optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO) for in vivo imaging of the human retina. The system simultaneously acquires SLO frames and OCT B-scans at 60 Hz with an OCT volume acquisition time of 4.2 s. Transverse eye motion measured from the SLO is used to register the OCT B-scans to generate three-dimensional (3-D) volumes. Key optical design considerations include: minimizing system aberrations through the use of off-axis relay telescopes, conjugate pupil plane requirements, and the use of dichroic beam splitters to separate and recombine the OCT and SLO beams around the nonshared horizontal scanning mirrors. To demonstrate system performance, AO-OCT-SLO images and measurements are taken from three normal human subjects ranging in retinal eccentricity from the fovea out to 15-deg temporal and 20-deg superior. Also presented are en face OCT projections generated from the registered 3-D volumes. The ability to acquire high-resolution 3-D images of the human retina in the midperiphery and beyond has clinical importance in diseases, such as retinitis pigmentosa and cone–rod dystrophy.
Precision Medicine in Cats: Novel Niemann‐Pick Type C1 Diagnosed by Whole‐Genome Sequencing

State‐of‐the‐art health care includes genome sequencing of the patient to identify genetic variants that contribute to either the cause of their malady or variants that can be targeted to improve treatment. The goal was to introduce state‐of‐the‐art health care to cats using genomics and a precision medicine approach. To test the feasibility of a precision medicine approach in domestic cats, a single cat that presented to the University of Missouri, Veterinary Health Center with an undiagnosed neurologic disease was whole‐genome sequenced. The DNA variants from the cat were compared to the DNA variant database produced by the 99 Lives Cat Genome Sequencing Consortium. Approximately 25× genomic coverage was produced for the cat. A predicted p.H441P missense mutation was identified in NPC1, the gene causing Niemann‐Pick type C1 on cat chromosome D3.47456793 caused by an adenine‐to‐cytosine transversion, c.1322A>C. The cat was homozygous for the variant. The variant was not identified in any other 73 domestic and 9 wild felids in the sequence database or 190 additionally genotyped cats of various breeds. The successful effort suggested precision medicine is feasible for cats and other undiagnosed cats may benefit from a genomic analysis approach. The 99 Lives DNA variant database was sufficient but would benefit from additional cat sequences. Other cats with the mutation may be identified and could be introduced as a new biomedical model for NPC1. A genetic test could eliminate the disease variant from the population.
Discriminative multiview nonnegative matrix factorization with large margin for image classification

Image classification has attracted lots of attentions in recent years. To improve classification accuracy, multiple features are usually extracted to represent the context of images, which imposes a challenge for the combination of those features. To address this problem, we present a discriminative nonnegative multi-view learning approach for image classification based on the observation that those features are often nonnegative. For discrimination, we utilize class label as an auxiliary information to learn discriminative common representations through a set of nonnegative basis vectors with large margin. Meanwhile, view consistency constraint is imposed on the low-dimensional representations and correntropy-induced metric (CIM) is adopted for the measurement of reconstruction errors. We utilized half-quadratic optimization technique to solve the optimization problem and obtain an effective multiplicative update rule. Experimental results demonstrate the learned common latent representations by the proposed method are more efficient than other methods.
Efficient Thermal Noise Removal for Sentinel-1 TOPSAR Cross-Polarization Channel

The intensity of a Sentinel-1 Terrain Observation with Progressive Scans synthetic aperture radar image is disturbed by additive thermal noise, particularly in the cross-polarization channel. Although the European Space Agency provides calibrated noise vectors for noise power subtraction, residual noise contributions are significant when considering the relatively narrow backscattering distribution of the cross-polarization channel. In this paper, we investigate the characteristics of noise and propose an efficient method for noise reduction based on a three-step correction process comprised of azimuth descalloping, noise scaling and interswath power balancing, and local residual noise power compensation. The core idea is to find the optimal correction coefficients resulting in the most noise-uncorrelated gentle backscatter profile over a homogeneous region and to combine them with the scalloping gain for a reconstruction of the complete 2-D noise field. Denoising is accomplished by subtracting the reconstructed noise field from the original image. The performance improvement in some applications by adopting the denoising procedure shows the effectiveness of the proposed method.
From Word Hypotheses to Logical Form: An Efficient Interleaved Approach

This paper revisits word lattice search whose task is to find a plausible semantic interpretation for a given utterance. Our approach of interleaved search and analysis is designed to break the frontier of "toy" applications. The framework is implemented in two interacting modules, running in parallel. Instead of simply parsing a word lattice, we rather do tree decoding with a probabilistic approximation of a given grammar, employing a beam search strategy.  Logical form is build up in tandem according to the decoded derivation histories, using a codescriptive HPSG grammar for dialog turns.  The proposed architecture only uses the knowledge necessary in every processing step, the key aspect being an asynchronous coupling of the two specialized modules.
The acceptance of E-payment among Indonesian millennials

Financial technology has become the newest technology advancement being adopted by young people in Indonesia, as it provides simplicity and speed of use. The objective of this study is to explain how e-Payment system is being adopted by the millennial generation in Indonesia. This study applies the Technology Acceptance Model approach and a quantitative method, by analyzing 424 Paytren e-Payment users, born between 1977 and 1998 using Smart PLS 2.0. The results show all independent variables have the significant relationship to dependent variables. Among them, perceived ease of use has the strongest relationship with perceived of the usefulness of e-Payment adoption. Meanwhile, the attitude towards using score shows the best predictive power in this model. The gender was proposed as a moderator variable. However, the findings did not support this role. Compared to e-Payment adoption in Jordan and Greece, this study may provide a new perspective on how e-Payment being adopted by the millennial generation in Indonesia.
Legionella pneumophila OxyR Is a Redundant Transcriptional Regulator That Contributes to Expression Control of the Two-Component CpxRA System

ABSTRACT Nominally an environmental organism, Legionella pneumophila is an intracellular parasite of protozoa but is also the causative agent of the pneumonia termed Legionnaires' disease, which results from inhalation of aerosolized bacteria by susceptible humans. Coordination of gene expression by a number of identified regulatory factors, including OxyR, assists L. pneumophila in adapting to the stresses of changing environments. L. pneumophila OxyR (OxyRLp) is an ortholog of Escherichia coli OxyR; however, OxyRLp was shown elsewhere to be functionally divergent, such that it acts as a transcription regulator independently of the oxidative stress response. In this study, the use of improved gene deletion methods has enabled us to generate an unmarked in-frame deletion of oxyR in L. pneumophila. Lack of OxyRLp did not affect in vitro growth or intracellular growth in Acanthamoeba castellanii protozoa and U937-derived macrophages. The expression of OxyRLp does not appear to be regulated by CpxR, even though purified recombinant CpxR bound a DNA sequence similar to that reported for CpxR elsewhere. Surprisingly, a lack of OxyRLp resulted in elevated activity of the promoters located upstream of icmR and the lpg1441-cpxA operon, and OxyRLp directly bound to these promoter regions, suggesting that OxyRLp is a direct repressor. Interestingly, a strain overexpressing OxyRLp demonstrated reduced intracellular growth in A. castellanii but not in U937-derived macrophages, suggesting that balanced expression control of the two-component CpxRA system is necessary for survival in protozoa. Taken together, this study suggests that OxyRLp is a functionally redundant transcriptional regulator in L. pneumophila under the conditions evaluated herein. IMPORTANCE Legionella pneumophila is an environmental pathogen, with its transmission to the human host dependent upon its ability to replicate in protozoa and survive within its aquatic niche. Understanding the genetic factors that contribute to L. pneumophila survival within each of these unique environments will be key to limiting future point-source outbreaks of Legionnaires' disease. The transcriptional regulator L. pneumophila OxyR (OxyRLp) has been previously identified as a potential regulator of virulence traits warranting further investigation. This study demonstrated that oxyR is nonessential for L. pneumophila survival in vitro and in vivo via mutational analysis. While the mechanisms of how OxyRLp expression is regulated remain elusive, this study shows that OxyRLp negatively regulates the expression of the cpxRA two-component system necessary for intracellular survival in protozoa.
Sketch-based cross-domain image retrieval via heterogeneous network

The development of image diversity has led multiple fields' application of cross-domain image retrieval. In this paper, we propose a heterogeneous dual network (two different networks) based on sketches and images. End-to-end cross-domain image retrieval is realized by limiting the similarity of features extracted from the two networks through the method of combining the contrastive loss with the triplet ranking loss. We also study how the order of drawings affects the sketch retrieval. Compared to the Siamese network, we avoid edge extraction for preprocessing, and the effect of fine-grained retrieval is further enhanced.
Predictive Neuroimaging Markers of Psychotherapy Response: A Systematic Review

IntroductionPredictive neuroimaging markers of treatment response are increasingly sought in order to inform the treatment of major depressive and anxiety disorders. We review the existing literature regarding candidate predictive neuroimaging markers of psychotherapy response and assess their potential clinical utility. MethodsWe searched Embase, PsycINFO, and PubMed up to October 2014 for studies correlating pretreatment neuroimaging parameters with psychotherapy response in major depressive and anxiety disorders. Our search yielded 40 eligible studies. ResultsThe anterior cingulate cortex, amygdala, and anterior insula emerged as potential markers in major depressive disorder and some anxiety disorders. Results across studies displayed a large degree of variability, however, and to date the findings have not been systematically validated in independent clinical cohorts and have not been shown capable of distinguishing between medication and psychotherapy responders. Also limited is the examination of how neuroimaging compares or might add to other prognostic clinical variables. ConclusionWhile the extant data suggest avenues of further investigation, we are still far from being able to use these markers clinically. Future studies need to focus on longitudinal testing of potential markers, determining their prescriptive value and examining how they might be integrated with clinical factors.
A Tangent Stiffness MLPG Method for Atom/Continuum Multiscale Simulation

The main objective of this paper is to develop a multiscale method for the static analysis of a nano-system, based on a combination of molecular mechanics and MLPG methods. The tangent-stiffness formulations are given for this multiscale method, as well as a pure molecular mechanics method. This method is also shown to naturally link the continuum local balance equation with molecular mechanics, directly, based on the stress or force. Numerical results show that this multiscale method quite accurate. The tangent-stiffness MLPG method is very effective and stable in multiscale simulations. This multiscale method dramatically reduces the computational cost, but it still can provide reasonable accuracy in some regions of the model. keyword: Molecular mechanics, Multiscale method, continuum mechanics, MLPG.
Covariate-modulated local false discovery rate for genome-wide association studies

MOTIVATION Genome-wide association studies (GWAS) have largely failed to identify most of the genetic basis of highly heritable diseases and complex traits. Recent work has suggested this could be because many genetic variants, each with individually small effects, compose their genetic architecture, limiting the power of GWAS, given currently obtainable sample sizes. In this scenario, Bonferroni-derived thresholds are severely underpowered to detect the vast majority of associations. Local false discovery rate (fdr) methods provide more power to detect non-null associations, but implicit assumptions about the exchangeability of single nucleotide polymorphisms (SNPs) limit their ability to discover non-null loci. METHODS We propose a novel covariate-modulated local false discovery rate (cmfdr) that incorporates prior information about gene element-based functional annotations of SNPs, so that SNPs from categories enriched for non-null associations have a lower fdr for a given value of a test statistic than SNPs in unenriched categories. This readjustment of fdr based on functional annotations is achieved empirically by fitting a covariate-modulated parametric two-group mixture model. The proposed cmfdr methodology is applied to a large Crohn's disease GWAS. RESULTS Use of cmfdr dramatically improves power, e.g. increasing the number of loci declared significant at the 0.05 fdr level by a factor of 5.4. We also demonstrate that SNPs were declared significant using cmfdr compared with usual fdr replicate in much higher numbers, while maintaining similar replication rates for a given fdr cutoff in de novo samples, using the eight Crohn's disease substudies as independent training and test datasets. Availability an implementation: https://sites.google. com/site/covmodfdr/ CONTACT : wes.stat@gmail.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
An appetitive experience after fear memory destabilization attenuates fear retention: involvement GluN2B-NMDA receptors in the Basolateral Amygdala Complex

It is known that a consolidated memory can return to a labile state and become transiently malleable following reactivation. This instability is followed by a restabilization phase termed reconsolidation. In this work, we explored whether an unrelated appetitive experience (voluntary consumption of diluted sucrose) can affect a contextual fear memory in rats during the reactivation-induced destabilization phase. Our findings show that exposure to an appetitive experience following reactivation can diminish fear retention. This effect persisted after 1 wk. Importantly, it was achieved only under conditions that induced fear memory destabilization. This result could not be explained as a potentiated extinction, because sucrose was unable to promote extinction. Since GluN2B-containing NMDA receptors in the basolateral amygdala complex (BLA) have been implicated in triggering fear memory destabilization, we decided to block pharmacologically these receptors to explore the neurobiological bases of the observed effect. Intra-BLA infusion with ifenprodil, a GluN2B-NMDA antagonist, prevented the fear reduction caused by the appetitive experience. In sum, these results suggest that the expression of a fear memory can be dampened by an unrelated appetitive experience, as long as memory destabilization is achieved during reactivation. Possible mechanisms behind this effect and its clinical implications are discussed.
Detection of acetone in air using silver ion exchanged ZSM-5 and zinc oxide sensing films

DETECTION OF ACETONE IN AIR USING SILVER ION EXCHANGED ZSM-5 AND ZINC OXIDE SENSING FILMS Kurt Lawrence Gerfen May 2012 Zinc oxide (ZnO) based gas sensors with sliver ion exchanged ZSM-5 (Ag+ZSM5) zeolite overlayer were created and tested for detection of acetone vapor in air. The ZnO and Ag+ZSM-5 films were deposisted on 40011m by 40011m platinum interdigitated electrodes on a silicon dioxide film on a silicon substrate. The microfabrication process of the interdigitated electrodes used for the sensors is presented. The synthesis and materials characterization of ZnO and Ag+ZSM-5 is discussed. Two types of sensors were developed, one with only a ZnO film and the other a ZnO film with Ag+ZSM-5 film on top. The acetone sensitivity was examined by exposing both sensors to dry air containing varying parts per million acetone at 350°C then measunng the resulting change in resistance across the electrodes. Both sensors showed sensitivity to acetone in air, however, the sensitivity in the ZnO and Ag+ZSM-5 films were greater than that of just the ZnO film. The utilization of the ZnO and Ag +ZSM-5 films as sensor has potential for detection of acetone in other gaseous mixtures, to include human breath.
Effects of school meals with weekly fish servings on vitamin D status in Danish children : secondary outcomes from the OPUS School Meal Study

Children’s vitamin D intake and status can be optimised to meet recommendations. We investigated if nutritionally balanced school meals with weekly fish servings affected serum 25-hydroxyvitamin D (25(OH)D) and markers related to bone in 8to 11-year-old Danish children. We conducted an explorative secondary outcome analysis on data from 784 children from the OPUS School Meal Study, a cluster-randomised cross-over trial where children received school meals for 3 months and habitual lunch for 3 months. At baseline, and at the end of each dietary period, 25(OH)D, parathyroid hormone (PTH), osteocalcin (OC), insulin-like growth factor-1 (IGF-1), bone mineral content (BMC), bone area (BA), bone mineral density (BMD), dietary intake and physical activity were assessed. School meals increased vitamin D intake by 0·9 (95 % CI 0·7, 1·1) μg/d. No consistent effects were found on 25(OH) D, BMC, BA, BMD, IGF-1 or OC. However, season-modified effects were observed with 25(OH)D, i.e. children completing the school meal period in January/February had higher 25(OH)D status (5·5 (95 % CI 1·8, 9·2) nmol/l; P = 0·004) than children completing the control period in these months. A similar tendency was indicated in November/December (4·1 (95 % CI –0·12, 8·3) nmol/l; P = 0·057). However, the effect was opposite in March/April (–4·0 (95 % CI –7·0, –0·9) nmol/l; P= 0·010), and no difference was found in May/June (P= 0·214). Unexpectedly, the school meals slightly increased PTH (0·18 (95 % CI 0·07, 0·29) pmol/l) compared with habitual lunch. Small increases in dietary vitamin D might hold potential to mitigate the winter nadir in Danish children’s 25(OH)D status while higher increases appear necessary to affect status throughout the year. More trials on effects of vitamin D intake from natural foods are needed.
Evaluation of Potassium Perchlorate as a Burning Rate Modifier in Composite Propellant Formulations

The burning rate of a solid composite propellant is one of its most important ballistic properties. To achieve a specified burning rate, transition metal oxides are used as burning rate modifiers. However, addition of transition metal oxides creates inertness in the composition. To avoid such inertness, an attempt has been made to incorporate potassium perchlorate (KP) as a burning rate modifier by partially replacing ammonium perchlorate (AP), up to the 10% level, and the composition was then studied in detail for its mechanical, thermal and ballistic properties. The data revealed that no change occurred in the case of the mechanical properties, however, the thermal stability decreased as the KP content was increased. The burning rate data revealed that on incorporation of 10% KP, there was an enhancement in the burning rate of up to 35% in comparison to the original composite propellant formulation, but beyond this no enhancement in burning rate was observed, indicating that the optimum content for KP in the composition had been reached.