Stand-alone Program Research Articles

DeepSig: deep learning improves signal peptide detection in proteins.

MotivationThe identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.ResultsHere, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification.Availability and implementationDeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website.Supplementary information Supplementary data are available at Bioinformatics online.

BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches.

With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typically, predictors based on machine learning techniques contain three main steps: feature extraction, predictor construction and performance evaluation. Although several Web servers and stand-alone tools have been developed to facilitate the biological sequence analysis, they only focus on individual step. In this regard, in this study a powerful Web server called BioSeq-Analysis (http://bioinformatics.hitsz.edu.cn/BioSeq-Analysis/) has been proposed to automatically complete the three main steps for constructing a predictor. The user only needs to upload the benchmark data set. BioSeq-Analysis can generate the optimized predictor based on the benchmark data set, and the performance measures can be reported as well. Furthermore, to maximize user's convenience, its stand-alone program was also released, which can be downloaded from http://bioinformatics.hitsz.edu.cn/BioSeq-Analysis/download/, and can be directly run on Windows, Linux and UNIX. Applied to three sequence analysis tasks, experimental results showed that the predictors generated by BioSeq-Analysis even outperformed some state-of-the-art methods. It is anticipated that BioSeq-Analysis will become a useful tool for biological sequence analysis.

Effects of a Social Empowerment Intervention on Economic Vulnerability for Adolescent Refugee Girls in Ethiopia

PurposeThis article examines the effects of a girls' social empowerment program, Creating Opportunities through Mentoring, Parental Involvement and Safe Spaces, on economic vulnerability of participating adolescent refugee girls in Ethiopia. MethodsAdolescents aged 13–19 years from three refugee camps were randomly assigned to either a treatment (n = 457) or control (n = 462) condition. Participants in the treatment condition received 40 fixed-curriculum, mentor-facilitated sessions once a week over a period of 10 months, whereas those in the control condition were not exposed to the curriculum. Caregivers of girls in the treatment arm also participated in 10 discussion sessions held once a month over the same period, where they learned about issues relevant to adolescent girls' well-being and safety. Data were collected from adolescent girls at baseline and approximately 10 months following intervention initiation. ResultsUsing logistic regression modeling, we found that, following the intervention, girls in the treatment arm were no more or less likely than those in the control arm to attend school, work for pay, work for pay while not being enrolled in school, or engage in transactional sexual exploitation. ConclusionsFindings suggest that stand-alone social empowerment programs may not reduce economic vulnerability for adolescent girls without simultaneously implementing economic empowerment programs or taking additional measures to address broader structural barriers.

Developing the next generation of engaged youth: Inspire Aspire – Global Citizens in the Making

School-based character education (CE) programs provide an opportunity to increase the moral fortitude of adolescents. This study is a preliminary evaluation of Inspire Aspire, a CE program that was implemented with 13- to 14-year-olds in Scotland. A relational developmental systems meta-theoretical approach and person-centered analyses were employed to understand whether teacher implementation variability is associated with student outcomes. The study aimed to: assess variation in program implementation across teachers; assess student poster quality, which served as a youth outcome measure; and, assess the relationship between variations in program implementation and poster quality. Teachers who fully integrated Inspire Aspire with the broader curriculum (as opposed to using it as a standalone program) as well as teachers who made more modifications to Inspire Aspire tended to have students with higher quality posters. This finding stands in contrast to the common narrative regarding evidence-based programs that requires teachers to strictly adhere to program guidelines in order to maintain implementation fidelity.

Automation of a DXA-based finite element tool for clinical assessment of hip fracture risk

Finite element analysis of medical images is a promising tool for assessing hip fracture risk. Although a number of finite element models have been developed for this purpose, none of them have been routinely used in clinic. The main reason is that the computer programs that implement the finite element models have not been completely automated, and heavy training is required before clinicians can effectively use them. By using information embedded in clinical dual energy X-ray absorptiometry (DXA), we completely automated a DXA-based finite element (FE) model that we previously developed for predicting hip fracture risk. The automated FE tool can be run as a standalone computer program with the subject's raw hip DXA image as input. The automated FE tool had greatly improved short-term precision compared with the semi-automated version. To validate the automated FE tool, a clinical cohort consisting of 100 prior hip fracture cases and 300 matched controls was obtained from a local community clinical center. Both the automated FE tool and femoral bone mineral density (BMD) were applied to discriminate the fracture cases from the controls. Femoral BMD is the gold standard reference recommended by the World Health Organization for screening osteoporosis and for assessing hip fracture risk. The accuracy was measured by the area under ROC curve (AUC) and odds ratio (OR). Compared with femoral BMD (AUC = 0.71, OR = 2.07), the automated FE tool had a considerably improved accuracy (AUC = 0.78, OR = 2.61 at the trochanter). This work made a large step toward applying our DXA-based FE model as a routine clinical tool for the assessment of hip fracture risk. Furthermore, the automated computer program can be embedded into a web-site as an internet application.

Validation of a Commercial Assay and Decision Support Tool for Routine Paclitaxel Therapeutic Drug Monitoring (TDM).

The value of therapeutic drug monitoring (TDM) for paclitaxel (PTX) was recently demonstrated in the largest TDM trial ever conducted in oncology. The trial demonstrated significant reduction in neuropathy when using TDM. Dose adjustment for PTX was based on time above a threshold concentration (Tc>0.05). Tc>0.05 must be calculated with a pharmacokinetic model and complex nonlinear mixed-effects software. The use of the software and chromatographic methods to measure PTX requires specialized expertise. User-friendly methods to quantitate PTX and calculate Tc>0.05 could simplify the introduction of TDM into routine clinical practice. The immunoassay (MyPaclitaxel) was used to quantitate PTX in samples from the clinical trial; the results were used to calculate Tc>0.05 using a stand-alone computer program with a simple, friendly graphical user interface for nonlinear mixed-effects pharmacokinetic calculations (MyCare Drug Exposure Calculator). The resulting dose recommendations from the calculated Tc>0.05 were compared with those using liquid chromatography-ultraviolet detection and NONMEM to examine the efficacy of the simpler tools for TDM. There was a good agreement between the immunoassay and liquid chromatography-ultraviolet detection: Passing-Bablok regression slope was 1.045 and intercept was -6.00, R was 0.9757, and mean bias was -1.77 ng/mL (-2.07 nmol/L). Dosing recommendations were identical for 70% of the cycles and within 10% for 89% of the samples. All Tc>0.05 values were at the same or adjacent medical decision points. MyPaclitaxel assay and MyCare Drug Exposure Calculator are convenient, user-friendly tools that may be suitable for routine TDM of PTX in clinical care.

Development of a hydraulic stimulation simulator toolbox for enhanced geothermal system design

Abstract Hydraulic stimulation is the key technology in the enhanced geothermal system (EGS) development. In this study, a reservoir stimulation simulator toolbox was developed for the comprehensive EGS design considering the natural fracture distribution, borehole stability, hydraulic stimulation and the thermal performance of the reservoir. The toolbox program consists of five modules, i.e., 3D discrete fracture network (DFN) generation, borehole stability analysis, hydrofracturing estimation, hydroshearing estimation and reservoir temperature prediction. Each module is implemented with graphic user interface using MATLAB® and available as a stand-alone program. The program allows independent analysis of each module and combined analyses with compatible data among the related modules, which provides extensive applicability to a variety of tasks associated with EGS stimulation, shale gas fracturing and CO2 geosequestration.

Ultrafast Peptide Label-Free Quantification with FlashLFQ.

The rapid and accurate quantification of peptides is a critical element of modern proteomics that has become increasingly challenging as proteomic data sets grow in size and complexity. We present here FlashLFQ, a computer program for high-speed label-free quantification of peptides following a search of bottom-up mass spectrometry data. FlashLFQ is approximately an order of magnitude faster than established label-free quantification methods. The increased speed makes it practical to base quantification upon all of the charge states for a given peptide rather than solely upon the charge state that was selected for MS2 fragmentation. This increases the number of quantified peptides, improves replicate-to-replicate reproducibility, and increases quantitative accuracy. We integrated FlashLFQ into the graphical user interface of the MetaMorpheus search software, allowing it to work together with the global post-translational modification discovery (G-PTM-D) engine to accurately quantify modified peptides. FlashLFQ is also available as a NuGet package, facilitating its integration into other software, and as a standalone command line software program for the quantification of search results from other programs (e.g., MaxQuant).

DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication.

SummaryWe developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 min, with rich information such as pseudogenes, translation exceptions and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.Availability and implementationThe software is implemented in Python 3 and runs in both Python 2.7 and 3.4—on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/.Supplementary information Supplementary data are available at Bioinformatics online.

DHCAL with minimal absorber: measurements with positrons

In special tests, the active layers of the CALICE Digital Hadron Calorimeter prototype, the DHCAL, were exposed to low energy particle beams, without being interleaved by absorber plates. The thickness of each layer corresponded approximately to 0.29 radiation lengths or 0.034 nuclear interaction lengths, defined mostly by the copper and steel skins of the detector cassettes. This paper reports on measurements performed with this device in the Fermilab test beam with positrons in the energy range of 1 to 10 GeV. The measurements are compared to simulations based on GEANT4 and a standalone program to emulate the detailed response of the active elements.

Shallow and deep learning for image classification

The paper is focused on the idea to demonstrate the advantages of deep learning approaches over ordinary shallow neural network on their comparative applications to image classifying from such popular benchmark databases as FERET and MNIST. An autoassociative neural network is used as a standalone program realized the nonlinear principal component analysis for prior extracting the most informative features of input data for neural networks to be compared further as classifiers. A special study of the optimal choice of activation function and the normalization transformation of input data allows to improve efficiency of the autoassociative program. One more study devoted to denoising properties of this program demonstrates its high efficiency even on noisy data. Three types of neural networks are compared: feed-forward neural net with one hidden layer, deep network with several hidden layers and deep belief network with several pretraining layers realized restricted Boltzmann machine. The number of hidden layer and the number of hidden neurons in them were chosen by cross-validation procedure to keep balance between number of layers and hidden neurons and classification efficiency. Results of our comparative study demonstrate the undoubted advantage of deep networks, as well as denoising power of autoencoders. In our work we use both multiprocessor graphic card and cloud services to speed up our calculations. The paper is oriented to specialists in concrete fields of scientific or experimental applications, who have already some knowledge about artificial neural networks, probability theory and numerical methods.

XtalOpt version r11: An open-source evolutionary algorithm for crystal structure prediction

Version 11 of XtalOpt, an evolutionary algorithm for crystal structure prediction, has now been made available for download from the CPC library or the XtalOpt website, http://xtalopt.github.io. Whereas the previous versions of XtalOpt were published under the Gnu Public License (GPL), the current version is made available under the 3-Clause BSD License, which is an open source license that is recognized by the Open Source Initiative. Importantly, the new version can be executed via a command line interface (i.e., it does not require the use of a Graphical User Interface). Moreover, the new version is written as a stand-alone program, rather than an extension to Avogadro. New version program summaryProgram Title:XtalOptProgram Files doi:http://dx.doi.org/10.17632/jt5pvnnm39.2Licensing provisions: 3-Clause BSD [1]Programming language: C++External routines/libraries:Qt [2], Qwt [3], Avogadro 2 (optional) [4], libssh [5] and one of: VASP [6], PWSCF [7], GULP [8], CASTEP [9], SIESTA [10]Subprograms used:Spglib [11], XtalComp [12], RandSpg [13]Nature of problem: The computational prediction of a stable crystal structure given only its stoichiometry.Solution method: Evolutionary algorithms (EAs) are optimization algorithms that use features from biological evolution to attempt to find the global minimum solution for a problem that has many degrees of freedom. In the case of a priori crystal structure prediction, EAs search for the atomic coordinates that correspond to the most stable regions of a given potential energy landscape. The XtalOpt EA for crystal structure prediction has now been made available under the 3-Clause BSD License, which is an open-source license that is officially recognized by the Open Source Initiative [14]. More information is available in the following publications: XtalOpt’s original implementation [15], previous version announcements [16,17,18], and also in manuscripts detailing the subprograms XtalOpt employs: XtalComp [19] and RandSpg [20].Reasons for new version: Since the release of XtalOpt version r10 in August 2017, the following changes have been made: •Removed dependence on Avogadro and Open Babel, making XtalOpt a stand-alone program rather than an extension.•Changed the license from GPLv2 to a 3-Clause BSD license.•Added the optional use of Avogadro 2 to render crystals through a remote procedure call (RPC) protocol.•Added a command-line interface (CLI) to run the program and generate plots.•Added the ability for the user to define custom minimum inter-atomic distances (IAD) between pairs of atom types.•Implemented various bug fixes.Summary of revisions: Dependence on the programs Avogadro and Open Babel has been removed from XtalOpt, so that XtalOpt is now a stand-alone program instead of an extension. This major development has allowed us to change the license from GPLv2 to the more flexible 3-Clause BSD license. To enable users to continue using Avogadro to render molecules, inter-process communication now occurs through a remote procedure call (RPC) protocol in such a way that a user may open Avogadro 2 at any time while the program is running in order to render the crystals they select. A command-line interface (CLI) has also been added so that the user may run the program without the use of the graphical user interface (GUI). Finally, the ability for the user to define minimum inter-atomic distances between pairs of atom types allows for more control in creating the initial generation of random structures.

Semi-automated camera trap image processing for the detection of ungulate fence crossing events.

Remote cameras are an increasingly important tool for ecological research. While remote camera traps collect field data with minimal human attention, the images they collect require post-processing and characterization before it can be ecologically and statistically analyzed, requiring the input of substantial time and money from researchers. The need for post-processing is due, in part, to a high incidence of non-target images. We developed a stand-alone semi-automated computer program to aid in image processing, categorization, and data reduction by employing background subtraction and histogram rules. Unlike previous work that uses video as input, our program uses still camera trap images. The program was developed for an ungulate fence crossing project and tested against an image dataset which had been previously processed by a human operator. Our program placed images into categories representing the confidence of a particular sequence of images containing a fence crossing event. This resulted in a reduction of 54.8% of images that required further human operator characterization while retaining 72.6% of the known fence crossing events. This program can provide researchers using remote camera data the ability to reduce the time and cost required for image post-processing and characterization. Further, we discuss how this procedure might be generalized to situations not specifically related to animal use of linear features.

Quality improvement of surface triangular mesh using a modified Laplacian smoothing approach avoiding intersection.

We present a systematic procedure to improve the qualities of triangular molecular surface meshes and at the same time preserve the manifoldness. The procedure utilizes an algorithm to remove redundant points having three or four valences and another algorithm to smooth the mesh using a modified version of Laplacian method without causing intersecting triangles. This approach can be effectively applied to any manifold surface meshes with arbitrary complex geometry. In this paper, the tested meshes are biomolecular surface meshes exhibiting typically highly irregular geometry. The results show that the qualities of the surface meshes are greatly improved and the manifoldness of the surface meshes are preserved. Compared with the original meshes, these improved molecular surface meshes can be directly applied to boundary element simulations and generation of body-fitted volume meshes using Tetgen. The procedure has been incorporated into our triangular molecular surface mesh generator, TMSmesh 2.0. It can be also used as a standalone program and works together with any other surface triangular mesh generator to obtain qualified manifold mesh. The package is downloadable at https://doi.org/10.6084/m9.figshare.5346169.v1 and can be run online at http://www.xyzgate.com.

Development of window design guideline and tools for early stage decision support

As building envelope design influences the appearance of a building, various alternatives are suggested during the early stages of designing the building. Windows greatly affect the energy performance of the building and also the comfort of the occupants. Therefore, in an attempt toward making the window design information readily available, many countries have developed and distributed guidelines with formats varying in terms of their contents and purposes. The aim of this study is to present the development process of a window design guideline and the tools for various climatic conditions. Based on preceding research, the guideline prepared in this work has three parts: a downloadable document file, a webpage and a stand-alone program. This guideline can be used as a decision support tool by architecture professionals in the early stages of window design. We intend to present this guideline to government institutions to help shape policies on building design.

P178 Evaluation of computerized virtual crossmatch program VxMatch

Aim Our aim is to evaluate the performance of a computerized virtual crossmatch within the Duke University Medical Center HLA laboratory. Our HLA lab has used virtual crossmatch (vXM) to select deceased donors for heart and lung transplantations for more than ten years, which has allowed us to accept donors from outside of our Organ Procurement Organization territory. The virtual crossmatches were done by manually checking the recipient’s HLA antibody profiles within our lab database against the potential donor’s HLA typing to identify if the recipient has any donor-specific antibodies (DSA) in the most recent serum tested and in historical sera. To ensure no DSA was missed, the vXM was manually done by multiple transplant professionals at different stages for each sensitized recipient when a donor offer was available. Laboratory informatics vendor HLA Data Systems, developers of the mTilda Lab Management System, has developed a stand-alone software program which performs a computerized vXM (cVXM) under the product name VxMatch. The VxMatch program directly connects to any HLA lab database to query required data for analysis. Methods We performed 56 cVXMs by using the new program for patients who had previously received manual vXMs (mVXM) over the past few months. 35 of the 56 patients have calculated panel reactive antibodies (cPRA) = >80%. Results We found a 100% concordance for identification of DSA between cVXM and mVXM. It took less than 5 min to complete the cVXM while the conventional mVXM took 30 min on average. For each identified unacceptable antigen, the cVXM program provides detailed information, including antibody specificities, mean fluorescence intensity (MFI), serum date and a graph showing the MFI changes of DSA over time. The mTilda cVXM can operate in two different modes: a technologist’s level and supervisory level. The supervisory module allows us to review each individual bead carrying potential unacceptable HLA antigen at alpha chain, beta chain, or allele level. This cVXM can also be used to identify the sera (for example the serum with peak DSA) for final XM and the ability to track the change of DSA post-transplant. Conclusion Our evaluation suggests that this new computerized vXM program is a user-friendly, reliable and powerful tool for HLA testing and management.

A novel data structure to support ultra-fast taxonomic classification of metagenomic sequences with k-mer signatures.

Metagenomic read classification is a critical step in the identification and quantification of microbial species sampled by high-throughput sequencing. Although many algorithms have been developed to date, they suffer significant memory and/or computational costs. Due to the growing popularity of metagenomic data in both basic science and clinical applications, as well as the increasing volume of data being generated, efficient and accurate algorithms are in high demand. We introduce MetaOthello, a probabilistic hashing classifier for metagenomic sequencing reads. The algorithm employs a novel data structure, called l-Othello, to support efficient querying of a taxon using its k-mer signatures. MetaOthello is an order-of-magnitude faster than the current state-of-the-art algorithms Kraken and Clark, and requires only one-third of the RAM. In comparison to Kaiju, a metagenomic classification tool using protein sequences instead of genomic sequences, MetaOthello is three times faster and exhibits 20-30% higher classification sensitivity. We report comparative analyses of both scalability and accuracy using a number of simulated and empirical datasets. MetaOthello is a stand-alone program implemented in C ++. The current version (1.0) is accessible via https://doi.org/10.5281/zenodo.808941. liuj@cs.uky.edu. Supplementary data are available at Bioinformatics online.

Piecewise holistic autotuning of parallel programs with CERE

SummaryCurrent architecture complexity requires fine tuning of compiler and runtime parameters to achieve best performance. Autotuning substantially improves default parameters in many scenarios, but it is a costly process requiring long iterative evaluations. We propose an automatic piecewise autotuner based on CERE (Codelet Extractor and REplayer). CERE decomposes applications into small pieces called codelets: Each codelet maps to a loop or to an OpenMP parallel region and can be replayed as a standalone program. Codelet autotuning achieves better speedups at a lower tuning cost. By grouping codelet invocations with the same performance behavior, CERE reduces the number of loops or OpenMP regions to be evaluated. Moreover, unlike whole‐program tuning, CERE customizes the set of best parameters for each specific OpenMP region or loop. We demonstrate the CERE tuning of compiler optimizations, number of threads, thread affinity, and scheduling policy on both nonuniform memory access and heterogeneous architectures. Over the NAS benchmarks, we achieve an average speedup of 1.08× after tuning. Tuning a codelet is 13× cheaper than whole‐program evaluation and predicts the tuning impact with a 94.7% accuracy. Similarly, exploring thread configurations and scheduling policies for a Black‐Scholes solver on an heterogeneous big.LITTLE architecture is over 40× faster using CERE.

Can Bundled Payments Be Successful in the Medicaid Population for Primary Joint Arthroplasty?

BackgroundAlthough some bundled payment models have had success in total joint arthroplasty, concerns exist about access to care for higher cost patients who use more resources. The purpose of this study is to determine whether Medicaid patients have increased hospital costs and more resource utilization in a 90-day episode of care than Medicare or privately insured patients. MethodsWe retrospectively reviewed a consecutive series of 7268 primary hip and knee arthroplasty patients at a single institution. Using a propensity score-matching algorithm for demographic variables, we matched the 92 consecutive Medicaid patients with 184 privately insured and 184 Medicare patients. Hospital-specific costs, discharge disposition, complications, and 90-day readmissions were analyzed. ResultsMedicaid patients had higher mean inpatient hospital costs than both of the matched Medicare and privately insured groups ($15,396 vs $12,165 vs $13,864, P < .001) with longer length of stay (3.34 vs 2.49 vs 1.46 days, P < .001). Medicaid and Medicare patients were more likely to be discharged to a rehabilitation facility than privately insured patients (17% vs 21% vs 1%, P < .001). When controlling for demographic factors and comorbidities, Medicaid insurance was a significant independent risk factor for increased hospital costs (odds ratio 3.64, 95% confidence interval 1.80-7.38, P < .001). ConclusionBecause of increased hospital costs, current bundled payment models should not include Medicaid patients because of concerns about patient selection and access to care. Further study is needed to determine whether bundling Medicaid arthroplasty costs in a stand-alone program with a separate target price will result in improved outcomes and decreased costs.

Global Value Chains, Emerging Markets, and IB Education

This article addresses the key challenge for IB teachers: the declining demand for stand-alone IB courses and programs due to the commonly made, fallacious assumption that integrating “international” in other courses by simply adding an “internationally-oriented” chapter to textbooks would suffice. Based on this assumption, the “value added” and uniqueness of IB as its own domain has been questioned. Furthermore, the crucial competences of the IB field are discussed and suggestions for teaching and curriculum changes are added that will facilitate the (re-)establishment of IB as a core discipline, and so contribute to regaining relevance and legitimacy.