Miracle-dz/UniFAR-FTUs huggingface dataset:
UniAlign: protein structure alignment meets evolution

MOTIVATION During the evolution, functional sites on the surface of the protein as well as the hydrophobic core maintaining the structural integrity are well-conserved. However, available protein structure alignment methods align protein structures based solely on the 3D geometric similarity, limiting their ability to detect functionally relevant correspondences between the residues of the proteins, especially for distantly related homologous proteins. RESULTS In this article, we propose a new protein pairwise structure alignment algorithm (UniAlign) that incorporates additional evolutionary information captured in the form of sequence similarity, sequence profiles and residue conservation. We define a per-residue score (UniScore) as a weighted sum of these and other features and develop an iterative optimization procedure to search for an alignment with the best overall UniScore. Our extensive experiments on CDD, HOMSTRAD and BAliBASE benchmark datasets show that UniAlign outperforms commonly used structure alignment methods. We further demonstrate UniAlign's ability to develop family-specific models to drastically improve the quality of the alignments. AVAILABILITY AND IMPLEMENTATION UniAlign is available as a web service at: http://sacan.biomed. drexel.edu/unialign CONTACT ahmet.sacan@drexel.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Novel 10-kHz High-frequency Therapy (HF10 Therapy) Is Superior to Traditional Low-frequency Spinal Cord Stimulation for the Treatment of Chronic Back and Leg Pain: The SENZA-RCT Randomized Controlled Trial

Background:Current treatments for chronic pain have limited effectiveness and commonly known side effects. Given the prevalence and burden of intractable pain, additional therapeutic approaches are desired. Spinal cord stimulation (SCS) delivered at 10 kHz (as in HF10 therapy) may provide pain relief without the paresthesias typical of traditional low-frequency SCS. The objective of this randomized, parallel-arm, noninferiority study was to compare long-term safety and efficacy of SCS therapies in patients with back and leg pain. Methods:A total of 198 subjects with both back and leg pain were randomized in a 1:1 ratio to a treatment group across 10 comprehensive pain treatment centers. Of these, 171 passed a temporary trial and were implanted with an SCS system. Responders (the primary outcome) were defined as having 50% or greater back pain reduction with no stimulation-related neurological deficit. Results:At 3 months, 84.5% of implanted HF10 therapy subjects were responders for back pain and 83.1% for leg pain, and 43.8% of traditional SCS subjects were responders for back pain and 55.5% for leg pain (P < 0.001 for both back and leg pain comparisons). The relative ratio for responders was 1.9 (95% CI, 1.4 to 2.5) for back pain and 1.5 (95% CI, 1.2 to 1.9) for leg pain. The superiority of HF10 therapy over traditional SCS for leg and back pain was sustained through 12 months (P < 0.001). HF10 therapy subjects did not experience paresthesias. Conclusion:HF10 therapy promises to substantially impact the management of back and leg pain with broad applicability to patients, physicians, and payers.
Analysis of individual driver velocity prediction using data-driven driver models with environmental features

Driver behavior is a key factor in vehicle energy demand calculation required for vehicle optimization strategies and range calculations of electric vehicles. Thereby the vehicle speed resulting from the driver demand has a major influence on the energy consumption. Thus, if the individual speed profile of a driver can be predicted accurately, the energy demand of a vehicle for a given route can be estimated, enabling better range calculation and optimization strategies. However, the driver behavior depends on multidimensional input factors, varies from driver to driver and can change over time. In this paper a learning approach is proposed to predict the individual speed profile. This approach takes environmental influences on the driver behavior into account. Different artificial neural network models and a Kernel regression approach for driver velocity prediction are investigated. The learned models are evaluated on real drive data from different drivers on a specified route. Results show that Long Short-term Memory networks can predict the driver behavior very accurately, leading to small prediction error.
Adenosine Kinase Modulates Root Gravitropism and Cap Morphogenesis in Arabidopsis1[W][OA]

Adenosine kinase (ADK) is a key enzyme that regulates intra- and extracellular levels of adenosine, thereby modulating methyltransferase reactions, production of polyamines and secondary compounds, and cell signaling in animals. Unfortunately, little is known about ADK's contribution to the regulation of plant growth and development. Here, we show that ADK is a modulator of root cap morphogenesis and gravitropism. Upon gravistimulation, soluble ADK levels and activity increase in the root tip. Mutation in one of two Arabidopsis (Arabidopsis thaliana) ADK genes, ADK1, results in cap morphogenesis defects, along with alterations in root sensitivity to gravistimulation and slower kinetics of root gravitropic curvature. The kinetics defect can be partially rescued by adding spermine to the growth medium, whereas the defects in cap morphogenesis and gravitropic sensitivity cannot. The root morphogenesis and gravitropism defects of adk1-1 are accompanied by altered expression of the PIN3 auxin efflux facilitator in the cap and decreased expression of the auxin-responsive DR5-GUS reporter. Furthermore, PIN3 fails to relocalize to the bottom membrane of statocytes upon gravistimulation. Consequently, adk1-1 roots cannot develop a lateral auxin gradient across the cap, necessary for the curvature response. Interestingly, adk1-1 does not affect gravity-induced cytoplasmic alkalinization of the root statocytes, suggesting either that ADK1 functions between cytoplasmic alkalinization and PIN3 relocalization in a linear pathway or that the pH and PIN3-relocalization responses to gravistimulation belong to distinct branches of the pathway. Our data are consistent with a role for ADK and the S-adenosyl-l-methionine pathway in the control of root gravitropism and cap morphogenesis.
Contrast‐enhanced magnetic resonance angiography in peripheral arterial disease: Improving image quality by automated image registration

In peripheral arterial disease, contrast‐enhanced MR angiography (MRA) is a noninvasive imaging alternative for catheter‐based digital subtraction angiography (DSA). In DSA, final images are generated by subtracting a native mask image from subsequent contrast‐enhanced images. Image quality is routinely improved by digitally shifting the mask image prior to subtraction if the patient has moved during angiography. This study investigated whether such image registration may also help to improve the image quality of MRA. In all, 545 MRA examinations of pelvic and leg arteries in patients with symptoms of peripheral arterial disease were studied retrospectively. Standard nonregistered MRA was compared to automatically linear, affine, and warp registered MRA by visual analysis and by three image quality parameters, including vessel detection probability (VDP) of angiographic maximum intensity projections. Most MRA of pelvic and upper leg arteries showed good nonregistered image quality. However, the 15% of lower legs with a body shift of 1 mm or more had relatively low nonregistered image quality, which improved significantly with image registration (VDP gain more than 18%, P < 0.05). The visual analysis gave similar results. In conclusion, image registration can improve image quality of MRA in peripheral arterial disease, especially in the lower legs. Magn Reson Med 60:224–229, 2008. © 2008 Wiley‐Liss, Inc.
Consensus nomenclature for the human ArfGAP domain-containing proteins

At the FASEB summer research conference on “Arf Family GTPases”, held in Il Ciocco, Italy in June, 2007, it became evident to researchers that our understanding of the family of Arf GTPase activating proteins (ArfGAPs) has grown exponentially in recent years. A common nomenclature for these genes and proteins will facilitate discovery of biological functions and possible connections to pathogenesis. Nearly 100 researchers were contacted to generate a consensus nomenclature for human ArfGAPs. This article describes the resulting consensus nomenclature and provides a brief description of each of the 10 subfamilies of 31 human genes encoding proteins containing the ArfGAP domain.
Enteral albuterol decreases the need for chronotropic agents in patients with cervical spinal cord injury–induced bradycardia

BACKGROUND Cervical spinal cord injury (CSCI) is often complicated by autonomic instability and life-threatening bradycardia. &bgr;-adrenergic receptors offer a potential target for modulating cardiac vagal activity and heart rate. Enteral albuterol may mitigate symptomatic bradycardia in CSCI patients. The purpose of this study was to examine the effect of enteral albuterol on the frequency of symptomatic bradycardia and the need for rescue therapy in CSCI patients. METHODS The charts of CSCI patients admitted to a Level I trauma center from February 2008 through March 2012 were reviewed for demographics, episodes of symptomatic bradycardia (defined as heart rate < 60 beats per minute and systolic blood pressure < 90 mm Hg), use of enteral albuterol, hospital days requiring chronotropic use, and total atropine administered. In the albuterol group, patients received scheduled enteral albuterol after experiencing symptomatic bradycardia, with chronotropic agents used as needed for rescue treatment. In the no-albuterol group, only chronotropic agents were used as needed for rescue treatment. The albuterol and no-albuterol groups were compared using independent-samples Kruskal-Wallis test for total number of bradycardic episodes, hospital days requiring chronotropic use, and total atropine administered. RESULTS Eighteen patients with CSCI-induced bradycardia were identified. Eight patients received treatment with enteral albuterol, and 10 patients did not. The median age did not differ significantly between the two groups. However, the median Injury Severity Score (ISS) was higher in the albuterol group (median ISS, 36.5; interquartile range, 35–66.5 vs. median ISS 26; interquartile range, 27–37.25 in no-albuterol group). Patients receiving albuterol experienced 1.8 symptomatic bradycardic episodes versus 4.3 episodes in those patients not receiving albuterol (p = 0.08). Hospital days on chronotropic agents were significantly less in the albuterol group (1.8 vs. 8.6, p = 0.01). One patient, in the no-albuterol group, required pacemaker placement. CONCLUSION Enteral albuterol may reduce the frequency of symptomatic bradycardia in patients with CSCI, resulting in less rescue therapy using chronotropic agents. LEVEL OF EVIDENCE Therapeutic study, level IV.
A Guideline for Establishing Local Energy-Efficiency Programs in Virginia

From a big picture perspective, investing in energy efficiency in the existing stock of residential buildings in the United States brings unquestioned economic, employment and environmental benefits. The aggregation of energy and dollar savings from millions of small improvements in efficiency adds up to enormous regional and national savings. By employing cost-effective investments in building efficiency, we could reduce the cumulative energy use of America‟s housing stock by twenty-eight percent, save Americans $41 billion annually, abate 360 megatons of CO-2 (Choi Granade, et.al., 2009), and meet fifty percent or more of the expected electric load growth by 2025 (EPA, 2008). In Virginia alone investing in the efficiency of our existing stock of buildings could save the commonwealth‟s residents $2.2 billion annually by 2025 (ACEEE, 2008). But from the perspective of the individual property owner the potential benefits of investing in energy efficiency, although just as real, are either less obvious or have impediments to their attainment. Understanding and overcoming these micro-impediments to energy investing is essential to realizing the macro-benefits of energy efficiency. Consequently, any successful local energy program must tailor its efforts to address the barriers to investing in efficiency at the level of the individual consumer. This thesis, through an analysis of existing and emerging residential energy programs, along with a review of the behavioral and economic literature on the subject, aims to point out the micro-impediments to achieving macro-reductions in energy use. Becoming familiar with these obstructions on the level of the individual consumer is the first necessary step in producing
A Reserve-Based Method for Mitigating the Impact of Renewable Energy

The fundamental operating paradigm of today’s power systems is undergoing a significant shift. This is partially motivated by the increased desire for incorporating variable renewable energy resources into generation portfolios. While these generating technologies offer clean energy at zero marginal cost, i.e. no fuel costs, they also offer unique operating challenges for system operators. Perhaps the biggest operating challenge these resources introduce is accommodating their intermittent fuel source availability. For this reason, these generators increase the system-wide variability and uncertainty. As a result, system operators are revisiting traditional operating strategies to more efficiently incorporate these generation resources to maximize the benefit they provide while minimizing the challenges they introduce. One way system operators have accounted for system variability and uncertainty is through the use of operating reserves. Operating reserves can be simplified as excess capacity kept online during real time operations to help accommodate unforeseen fluctuations in demand. With new generation resources, a new class of operating reserves has emerged that is generally known as flexibility, or ramping, reserves. This new reserve class is meant to better position systems to mitigate severe ramping in the net load iii profile. The best way to define this new requirement is still under investigation. Typical requirement definitions focus on the additional uncertainty introduced by variable generation and there is room for improvement regarding explicit consideration for the variability they introduce. An exogenous reserve modification method is introduced in this report that can improve system reliability with minimal impacts on total system wide production costs. Another potential solution to this problem is to formulate the problem as a stochastic programming problem. The unit commitment and economic dispatch problems are typically formulated as deterministic problems due to fast solution times and the solutions being sufficient for operations. Improvements in technical computing hardware have reignited interest in stochastic modeling. The variability of wind and solar naturally lends itself to stochastic modeling. The use of explicit reserve requirements in stochastic models is an area of interest for power system researchers. This report introduces a new reserve modification implementation based on previous results to be used in a stochastic modeling framework. With technological improvements in distributed generation technologies, microgrids are currently being researched and implemented. Microgrids are small power systems that have the ability to serve their demand with their own generation resources and may have a connection to a larger power system. As battery technologies improve, they are becoming a more viable option in these distributed power systems and research is necessary to determine the most efficient way to utilize them. This report will investigate several unique operating strategies for batteries in small power systems and
Exploring Joint Disease Risk Prediction

Disease risk prediction has been a central topic of medical informatics. Although various risk prediction models have been studied in the literature, the vast majority were designed to be single-task, i.e. they only consider one target disease at a time. This becomes a limitation when in practice we are dealing with two or more diseases that are related to each other in terms of sharing common comorbidities, symptoms, risk factors, etc., because single-task prediction models are not equipped to identify these associations across different tasks. In this paper we address this limitation by exploring the application of multi-task learning framework to joint disease risk prediction. Specifically, we characterize the disease relatedness by assuming that the risk predictors underlying these diseases have overlap. We develop an optimization-based formulation that can simultaneously predict the risk for all diseases and learn the shared predictors. Our model is applied to a real Electronic Health Record (EHR) database with 7,839 patients, among which 1,127 developed Congestive Heart Failure (CHF) and 477 developed Chronic Obstructive Pulmonary Disease (COPD). We demonstrate that a properly designed multi-task learning algorithm is viable for joint disease risk prediction and it can discover clinical insights that single-task models would overlook.
Simulation and control of Takagi-Sugeno uncertain model of buck converter by linear programming

This paper deals with the problem of stabilization and reference input tracking by fuzzy PDC controller of discrete Takagi-Sugeno (T-S) uncertain model of Buck converter by linear programming (LP) while imposing positivity in closed-loop. The stabilization conditions are derived using the single Lyapunov-Krasovskii Functional (LKF). Simulation results by linear programming methods are given to illustrate the validity of the proposed method.
Fluxomics links cellular functional analyses to whole-plant phenotyping

Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.
How Can the Optimal Scale of Operations Be Estimated? A Proposal.

The paper proposes a framework that can be utilized for deciding upon the optimal scale of operations for a firm. The basic premise of the paper is that a firm that operates in a stable economic environment and a stable mode of business operations experiences a varying elasticity of scale that, after some scale level, becomes less than one and continues to decline with further increases in scale. A firm operating in such a stable system can search for its optimal scale of operations. The paper's premise does not refute the possibility that a firm can experience a shift from a lower elasticity of scale to a higher one; but this shift is not part of the mechanics of a stable system. Rather, it is due to some shock to the economic environment and/or the firm's mode of operations. Firms that operate under the assumption that they face a constant elasticity of scale, when in fact the elasticity varies, expose themselves to detrimental consequences. The model is in congruence with the Tobin's q criteria and can shed some light on why average q is a poor estimate for marginal q.
Consumer Decision-Making Styles Extension to Trust-Based Product Comparison Site Usage Model

The paper describes an implementation of extended consumer decision-making styles concept in explaining consumer choices made in product comparison site environment in the context of trust-based information technology acceptance model. Previous research proved that trust-based acceptance model is useful in explaining purchase intention and anticipated satisfaction in product comparison site environment, as an example of online decision shopping aids. Trust to such aids is important in explaining their usage by consumers. The connections between consumer decision-making styles, product and sellers opinions usage, cognitive and affective trust toward online product comparison site, as well as choice outcomes (purchase intention and brand choice) are explored trough structural equation models using PLS-SEM approach, using a sample of 461 young consumers. Research confirmed the validity of research model in explaining product comparison usage, and some consumer decision-making styles influenced consumers’ choices and purchase intention. Product and sellers reviews usage were partially mediating mentioned relationships.