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Due to their widespread adoption, frequent use, and diverse sensor capabilities, smartphones have become a powerful tool for academic studies focused on sampling human behaviour. While packing many technological advances, the need for researchers to develop their own software packages in order to run smartphone-based studies has resulted in a clear barrier to entry for researchers without the financial means, time, or technical knowledge required to overcome this technical barrier. We present AWARE-Light, a new smartphone application for data collection from study participants, which is accompanied by a website that provides any researcher the possibility to easily configure their own study. To highlight the possibilities of our tool, we present a research scenario on digital phenotyping for mental health. Furthermore, we describe the methodological configuration possibilities offered by our tool, and complement the technical configuration possibilities with recommendations from the existing literature. [ABSTRACT FROM AUTHOR]

The development of immune checkpoint blockade (ICB) has changed the way we treat various cancers. While ICB produces durable survival benefits in a number of malignancies, a large proportion of treated patients do not derive clinical benefit. Recent clinical profiling studies have shed light on molecular features and mechanisms that modulate response to ICB. Nevertheless, none of these identified molecular features were investigated in large enough cohorts to be of clinical value. Literature review was carried out to identify relevant studies including clinical dataset of patients treated with ICB [anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1), anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4) or the combination] and available sequencing data. Tumor mutational burden (TMB) and 37 previously reported gene expression (GE) signatures were computed with respect to the original publication. Biomarker association with ICB response (IR) and survival (progression-free survival/overall survival) was investigated separately within each study and combined together for meta-analysis. We carried out a comparative meta-analysis of genomic and transcriptomic biomarkers of IRs in over 3600 patients across 12 tumor types and implemented an open-source web application (predictIO.ca) for exploration. TMB and 21/37 gene signatures were predictive of IRs across tumor types. We next developed a de novo GE signature (PredictIO) from our pan-cancer analysis and demonstrated its superior predictive value over other biomarkers. To identify novel targets, we computed the T-cell dysfunction score for each gene within PredictIO and their ability to predict dual PD-1/CTLA-4 blockade in mice. Two genes, F2RL1 (encoding protease-activated receptor-2) and RBFOX2 (encoding RNA-binding motif protein 9), were concurrently associated with worse ICB clinical outcomes, T-cell dysfunction in ICB-naive patients and resistance to dual PD-1/CTLA-4 blockade in preclinical models. Our study highlights the potential of large-scale meta-analyses in identifying novel biomarkers and potential therapeutic targets for cancer immunotherapy. • Large pan-cancer GE meta-analysis identified a de novo GE signature, called PredictIO. • PredictIO demonstrated better and more consistent ability to predict IR as compared to TMB and other signatures. • F2RL1 and RBFOX2 exhibited strong association with ICB resistance, T-cell dysfunction and pro-tumoral microenvironment. • F2RL1 and RBFOX2 appear as an interesting therapeutic target to improve ICB efficacy. • An open-source web application (PredictIO.ca) was developed, allowing researcher to explore their biomarker of interest. [ABSTRACT FROM AUTHOR]

Scientific software incorporates models that capture fundamental domain knowledge. This software is becoming increasingly more relevant as an instrument for food research. However, scientific software is currently hardly shared among and (re-)used by stakeholders in the food domain, which hampers effective dissemination of knowledge, i.e. knowledge transfer. This paper reviews selected approaches, best practices, hurdles and limitations regarding knowledge transfer via software and the mathematical models embedded in it to provide points of reference for the food community. The paper focusses on three aspects. Firstly, the publication of digital objects on the web, which offers valorisation software as a scientific asset. Secondly, building transferrable software as way to share knowledge through collaboration with experts and stakeholders. Thirdly, developing food engineers' modelling skills through the use of food models and software in education and training. • Re-use of models and software should favour knowledge transfer in the food domain. • Suitable diffusion channel depends on the type of model. • Diffusion channels relying on web-based technologies are most promising solutions. • Building scientific software from shared knowledge facilitates knowledge transfer. • Initiatives for teaching modelling online are being developed by food scientists. [ABSTRACT FROM AUTHOR]

Software development for data reduction and analysis at large research facilities is increasingly professionalized, and internationally coordinated. To foster software quality and sustainability, and to facilitate collaboration, representatives from software groups of European neutron and muon facilities have agreed on a set of guidelines for development practices, infrastructure, and functional and non-functional product properties. These guidelines have been derived from actual practices in software projects from the EU funded consortium 'Science and Innovation with Neutrons in Europe in 2020' (SINE2020), and have been enriched through extensive literature review. Besides guiding the work of the professional software engineers in our computing groups, we hope to influence scientists who are willing to contribute their own data treatment software to our community. Moreover, this work may also provide inspiration to scientific software development beyond the neutron and muon field. [ABSTRACT FROM AUTHOR]

Scientific software from all areas of scientific research is pivotal to obtaining novel insights. Yet the coding standards adherence of scientific software is rarely assessed, even though it might lead to incorrect scientific results in the worst case. Therefore, we have developed an open source tool and benchmark called SoftWipe, that provides a relative software coding standards adherence ranking of 48 computational tools from diverse research areas. SoftWipe can be used in the review process of software papers and to inform the scientific software selection process. [ABSTRACT FROM AUTHOR]

• The matrix-operator method (MOM) is convenient for polarized atmospheric correction (AC). • A new modification of our vector radiative transfer (RT) code provides elements of MOM as standard output, while the surface model is now excluded from the RT solver. • Using this output, we account for polarization in the Green's function formalism for the AC. • The "equations + code" bundle helps document the algorithm and reproduce our results. In passive satellite remote sensing of the Earth, separation of the path radiance (atmosphere-only contribution) from the surface reflection remains a " significant challenge ". Recent literature names it among the gaps in radiative transfer (RT) topics that "require continued research in the near future ". The challenge comes from multiple reflections (bouncing) between the atmosphere and surface – radiative interaction. In this paper we use a known RT technique, the matrix-operator method (MOM), and a new modification of the monochromatic vector RT (vRT) code IPOL (Intensity and POLarization) to simulate the interaction of a plane-parallel atmosphere and a few widely used surface reflection models. Following the idea of the Green's function method, IPOL no longer takes the surface model parameters on input. Instead, it provides the path radiance, and the atmospheric reflection and transmission matrices as output. Despite many RT codes use the MOM formalism, this output does not seem common. The surface reflection matrix is computed externally. Therefore, this paper extends the Green's function atmospheric correction technique to the case of polarized light. Aiming clarity rather than performance, we explain in Python the structure of the surface matrices for the isotropic (Lambertian), directional unpolarized, and polarized ocean reflection models. We then combine these surface matrices and the precomputed IPOL output to get numerically accurate signal at the top of atmosphere (TOA) and test it vs. published benchmarks. Then, for each benchmark scenario we show how to get the surface from the TOA signal, i.e. perform the RT-based atmospheric correction. [ABSTRACT FROM AUTHOR]

In this work we formally derive and prove the correctness of the algorithms and data structures in a parallel, distributed-memory, generic finite element framework that supports h-adaptivity on computational domains represented as forest-of-trees. The framework is grounded on a rich representation of the adaptive mesh suitable for generic finite elements that is built on top of a low-level, light-weight forest-of-trees data structure handled by a specialized, highly parallel adaptive meshing engine, for which we have identified the requirements it must fulfill to be coupled into our framework. Atop this two-layered mesh representation, we build the rest of the data structures required for the numerical integration and assembly of the discrete system of linear equations. We consider algorithms that are suitable for both subassembled and fully assembled distributed data layouts of linear system matrices. The proposed framework has been implemented within the FEMPAR scientific software library, using p4est as a practical forest-of-octrees demonstrator. A strong scaling study of this implementation when applied to Poisson and Maxwell problems reveals remarkable scalability up to 32.2K CPU cores and 482.2M degrees of freedom. Besides, a comparative performance study of FEMPAR and the state-of-the-art deal.II finite element software shows at least comparative performance, and at most a factor of 2{3 improvement in the h-adaptive approximation of a Poisson problem with first- and second-order Lagrangian finite elements, respectively. [ABSTRACT FROM AUTHOR]

As a scientific field, scientific mapping offers a set of standardized methods and tools which can be consistently adopted by researchers in different knowledge domains to answer their own research questions. This study examined the scientific articles that applied science mapping tools (SMT) to analyze scientific domains and the citations of these application articles. To understand the roles of these application articles in scholarly communication, we analyzed 496 application articles and their citations from 14 SMT by classifying them into library and information science (LIS) and other fields (non-LIS) in terms of both publication venues and analyzed domains. In our study, we found that science mapping, a topic that is deeply situated in the LIS field, has gained increasing attention from various non-LIS scientific fields over the last few years, especially since 2012. Science mapping application studies practically grew up in LIS domain and spread to other fields. The application articles within and outside of the LIS fields played different roles in advancing the application of science mapping and knowledge discovery. Especially, we have discovered the important role of articles, which studied non-LIS domains but published in LIS journals, in advancing the application of SMTs. [ABSTRACT FROM AUTHOR]

Data analysis of Quasi-elastic Neutron Scattering (QENS) experiments often requires multiple steps involving fitting the elastic and quasi-elastic parts of spectra with several empirical functions and analytical models. Parameters of those models can be interdependent and also dependent on the momentum transfer vector Q. Here we present a modern data analysis interface dedicated for QENS data analysis implemented within the open source software Mantid. The interface has been implemented using the state-of-the-art design pattern Model-View-Presenter (MVP). The MVP, an architectural software design pattern, facilitates automated unit tests as well as decoupling of the business logic, presentation logic and the graphical interface. Several models are implemented for analysing both elastic and quasi-elastic parts of the dynamical scattering function S (Q , ω) and intermediate scattering function I (Q , t). To understand the nature of dynamics in a QENS experiments, several models are also implemented for elastic incoherent structure factor (EISF) and jump diffusions. The interface has been validated by analysing a sample of liquid water at room temperature. The nature of hydrogen bond dynamics of the hydrogen bonded organic ferroelectric 2, 4, 5 − Br 3 imidazole, for the first time has been analysed using this newly implemented software. It is found that protons exhibit localised random motion in this material. [ABSTRACT FROM AUTHOR]

Detection of developmental phenotypes in zebrafish embryos typically involves a visual assessment and scoring of morphological features by an individual researcher. Subjective scoring could impact results and be of particular concern when phenotypic effect patterns are also used as a diagnostic tool to classify compounds. Here we introduce a quantitative morphometric approach based on image analysis of zebrafish embryos. A software called FishInspector was developed to detect morphological features from images collected using an automated system to position zebrafish embryos. The analysis was verified and compared with visual assessments of 3 participating laboratories using 3 known developmental toxicants (methotrexate, dexamethasone, and topiramate) and 2 negative compounds (loratadine and glibenclamide). The quantitative approach exhibited higher sensitivity and made it possible to compare patterns of effects with the potential to establish a grouping and classification of developmental toxicants. Our approach improves the robustness of phenotype scoring and reliability of assay performance and, hence, is anticipated to improve the predictivity of developmental toxicity screening using the zebrafish embryo. [ABSTRACT FROM AUTHOR]

The article presents rules to make software that is impactful and usable by using software engineering best practices. It mentions that modern integrated development environments will frequently generate documentation strings automatically as researchers write code, that takes the burden of the need to remember to write comments. It states that people more probably to use it as part of their research if they can quickly start playing with the tool.

Abstract Inelastic neutron scattering (INS) spectroscopy, contrary to other vibrational spectroscopic techniques such as infrared or Raman spectroscopies, provides much richer microscopic insight into a material due to the absence of selection rules induced by the system's symmetry and v i a its dependence on both energy (E) and momentum (Q) transfer. First-principles density functional theory (DFT) based calculations are now routinely used to interpret infrared and Raman spectra. These calculations can also be used to interpret INS spectra, however, the need to include the neutron scattering cross sections, overtones and combination modes, together with instrument specific E- Q windows make the data analysis challenging. Here we present AbINS: a new generation of software to interpret INS spectra using ab initio phonon data. AbINS is an open-source package implemented as a plugin to the neutron data analysis software, Mantid and offers the facility to plot the full (Q , E) map for powder samples, with the option to extract individual atomic contributions. This option is then applied to analyse the vibrational spectrum of non-hydrogenous K 2 S i F 6 to extract atom-type contributions identifying T 1 g librational mode of the [ S i F 6 ] 2 − ion together with the T 2 u F–Si–F bending mode. [ABSTRACT FROM AUTHOR]

We present a performance analysis appropriate for comparing algorithms using different numerical discretizations. By taking into account the total time-to-solution, numerical accuracy with respect to an error norm, and the computation rate, a cost-benefit analysis can be performed to determine which algorithm and discretization are particularly suited for an application. This work extends the performance spectrum model in [J. Chang et al., Concurrency and Computation Practice and Experience, 30 (2017), e4401] for interpretation of hardware and algorithmic trade-offs in numerical PDE simulation. As a proof-of-concept, popular finite element software packages are used to illustrate this analysis for Poisson's equation. [ABSTRACT FROM AUTHOR]

Geppetto is an open-source platform that provides generic middleware infrastructure for building both online and desktop tools for visualizing neuroscience models and data and managing simulations. Geppetto underpins a number of neuroscience applications, including Open Source Brain (OSB), Virtual Fly Brain (VFB), NEURON-UI and NetPyNE-UI. OSB is used by researchers to create and visualize computational neuroscience models described in NeuroML and simulate them through the browser. VFB is the reference hub for Drosophila melanogaster neural anatomy and imaging data including neuropil, segmented neurons, microscopy stacks and gene expression pattern data. Geppetto is also being used to build a new user interface for NEURON, a widely used neuronal simulation environment, and for NetPyNE, a Python package for network modelling using NEURON. Geppetto defines domain agnostic abstractions used by Geppetto is an open-source platform that provides generic middleware infrastructure for building both online and desktop tools for visualizing neuroscience models and data and managing simulations. Geppetto underpins a number of neuroscience applications, including Open Source Brain (OSB), Virtual Fly Brain (VFB), NEURON-UI and NetPyNE-UI. OSB is used by researchers to create and visualize computational neuroscience models described in NeuroML and simulate them through the browser. VFB is the reference hub for Drosophila melanogaster neural anatomy and imaging data including neuropil, segmented neurons, microscopy stacks and gene expression pattern data. Geppetto is also being used to build a new user interface for NEURON, a widely used neuronal simulation environment, and for NetPyNE, a Python package for network modelling using NEURON. Geppetto defines domain agnostic abstractions used by all these applications to represent their models and data and offers a set of modules and components to integrate, visualize and control simulations in a highly accessible way. The platform comprises a backend which can connect to external data sources, model repositories and simulators together with a highly customizable frontend. This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'. [ABSTRACT FROM AUTHOR]

Background: AceTree, a software application first released in 2006, facilitates exploration, curation and editing of tracked C. elegans nuclei in 4-dimensional (4D) fluorescence microscopy datasets. Since its initial release, AceTree has been continuously used to interact with, edit and interpret C. elegans lineage data. In its 11 year lifetime, AceTree has been periodically updated to meet the technical and research demands of its community of users. This paper presents the newest iteration of AceTree which contains extensive updates, demonstrates the new applicability of AceTree in other developmental contexts, and presents its evolutionary software development paradigm as a viable model for maintaining scientific software. Results: Large scale updates have been made to the user interface for an improved user experience. Tools have been grouped according to functionality and obsolete methods have been removed. Internal requirements have been changed that enable greater flexibility of use both in C. elegans contexts and in other model organisms. Additionally, the original 3-dimensional (3D) viewing window has been completely reimplemented. The new window provides a new suite of tools for data exploration. Conclusion: By responding to technical advancements and research demands, AceTree has remained a useful tool for scientific research for over a decade. The updates made to the codebase have extended AceTree's applicability beyond its initial use in C. elegans and enabled its usage with other model organisms. The evolution of AceTree demonstrates a viable model for maintaining scientific software over long periods of time. [ABSTRACT FROM AUTHOR]

Today's Geodynamic models can, often do, and sometimes have to become very complex. Their underlying, increasingly elaborate numerical codes produce a growing amount of raw data. Post-processing such data becomes therefore more and more challenging and time consuming. In addition, visualising processed data and results has, in times of coloured figures and a wealth of half-scientific software, become one of the weakest pillars of science, widely mistreated and ignored. Efficient and automated Geodynamic diagnostics and sensible, scientific visualisation, preventing common pitfalls, is thus more important than ever. Here, a collection of numerous diagnostics for plate tectonics and mantle dynamics is provided and a case for truly scientific visualisation is made. Amongst other diagnostics are a most accurate and robust plate-boundary identification, slab-polarity recognition, plate-bending derivation, surface-topography component splitting and mantle-plume detection. Thanks to powerful image processing tools and other elaborate algorithms, these and many other insightful diagnostics are conveniently derived from only a subset of the most basic parameter fields. A brand-new set of scientifically proof, perceptually uniform colour maps including "devon", "davos", "oslo" and "broc" is introduced and made freely available. These novel colour maps bring a significant advantage over misleading, non-scientific colour maps like "rainbow"', which is shown to introduce a visual error to the underlying data of up to 7.5%. Finally, StagLab (http://www.fabiocrameri.ch/software) is introduced, a software package that incorporates the whole suite of automated Geodynamic diagnostics and, on top of that, applies state-of-the-art, scientific visualisation to produce publication-ready figures and movies, all in a blink of an eye, all fully reproducible. StagLab, a simple, flexible, efficient and reliable tool, made freely available to everyone, is written in MatLab and adjustable for use with Geodynamic mantle-convection codes. [ABSTRACT FROM AUTHOR]

This paper aims to show the potential of mailing list archives as primary sources for studying recent history of science. In order to focus on the debates regarding software within the computational chemistry community in the 1990s, the corpus we rely on consists in a scholarly mailing list, a typical corpus from its time, conceived, constructed and maintained by a community. The threaded conversations of the list also constitute a unique rhetorical form in its organisation which is technically bound to the Internet-based media of that time. We first present the issues at stake within our research topic and show how relevant is such a corpus to address them. We then discuss the "ethnographic" characteristics and the structure of the corpus. Its most interesting parts are the "flame wars", that is outbursts of heated, short and dense debates, in an ocean of evenly distributed polite messages. We unveil how the relevant flame wars are located and extracted by producing a graphical representation of the number of messages per day over time. Once flame wars are isolated, the messages exchanged by practitioners are studied precisely to comprehend the argumentative structure of the debates and the different viewpoints of actors. [ABSTRACT FROM AUTHOR]

This paper proposes the description of an original smart-grids test bed aimed at teaching novel feeder automation functions to students from both university and industry origins. With this test bed, a lab class proposes to students, first, to develop feeder automation functions using scientific software and, then, to experiment by practically testing them on an emulated distribution grid platform, called PREDIS. This platform includes real medium-voltage reduced-scale loads, generators, and a supervisory control and data acquisition system. The presented lab class is part of a dedicated complete pedagogic module with lectures and experiments. Through the development, the tests and the deployments of their own solutions in an actual distribution grid, the students learn by doing from theory to practice the complete chain of smart-grids solutions: from the electrical to the communication layers. [ABSTRACT FROM AUTHOR]

Computing affects how scientific knowledge is constructed, verified, and validated. Rapid changes in hardware capability, and software flexibility, are coupled with a volatile tool and skill set, particularly in the interdisciplinary scientific contexts of oceanography. Existing research considers the role of scientists as both users and producers of code. We focus on how an intentional, individually-initiated but socially-situated, process of uptake influences code written by scientists. We present an 18-month interview and observation study of four oceanography teams, with a focus on ethnographic shadowing of individuals undertaking code work. Through qualitative analysis, we developed a framework of deliberate individual change, which builds upon prior work on programming practices in science through the lens of sociotechnical infrastructures. We use qualitative vignettes to illustrate how our theoretical framework helps to understand changing programming practices. Our findings suggest that scientists use and produce software in a way that deliberately mitigates the potential pitfalls of their programming practice. In particular, the object and method of visualization is subject to restraint intended to prevent accidental misuse. [ABSTRACT FROM AUTHOR]

Background: ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Results: We rewrote the entire ImageJ codebase, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements. This next-generation ImageJ, called "ImageJ2" in places where the distinction matters, provides a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. Conclusions: Scientific imaging benefits from open-source programs that advance new method development and deployment to a diverse audience. ImageJ has continuously evolved with this idea in mind; however, new and emerging scientific requirements have posed corresponding challenges for ImageJ's development. The described improvements provide a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs. Future efforts will focus on implementing new algorithms in this framework and expanding collaborations with other popular scientific software suites. [ABSTRACT FROM AUTHOR]

The ITER Radial Neutron Camera (RNC) is a neutron diagnostic intended for the measurement of the neutron emissivity radial profile and the estimate of the total fusion power. This paper presents a proof-of-principle method based on neural networks to estimate the neutron emissivity profile in different ITER scenarios and for different RNC architectures. The design, optimization and training of the implemented neural network is presented together with a decision algorithm to select, among the multiple trained neural networks, which one provides the inverted neutron emissivity profile closest to the input one. Examples are given for a selection of ITER scenarios and RNC architectures. The results from this study indicate that neural networks for the neutron emissivity recognition in ITER can achieve an accuracy and precision within the spatial and temporal requirements set by ITER for such a diagnostic. [ABSTRACT FROM AUTHOR]

Computational chemistry is a scientific field within which the computer is a pivotal element. This scientific community emerged in the 1980s and was involved with two major industries: the computer manufacturers and the pharmaceutical industry, the latter becoming a potential market for the former through molecular modeling software packages. We aim to address the difficult relationships between scientific modeling methods and the software implementing these methods throughout the 1990s. Developing, using, licensing, and distributing software leads to multiple tensions among the actors in intertwined academic and industrial contexts. The Computational Chemistry mailing List (CCL), created in 1991, constitutes a valuable corpus for revealing the tensions associated with software within the community. We analyze in detail two flame wars that exemplify these tensions. We conclude that models and software must be addressed together. Interrelations between both imply that openness in computational science is complex. [ABSTRACT FROM PUBLISHER]

Background: Depression is common mental health problem and leading contributor to the global burden of disease. The attitudes and beliefs of the public and of health professionals influence social acceptance and affect the esteem and help-seeking of people experiencing mental health problems. The attitudes of clinicians are particularly relevant to their role in accurately recognising and providing appropriate support and management of depression. This study examines the characteristics of the revised depression attitude questionnaire (R-DAQ) with doctors working in healthcare settings in Lahore, Pakistan. Methods: A cross-sectional survey was conducted in 2015 using the revised depression attitude questionnaire (R-DAQ). A convenience sample of 700 medical practitioners based in six hospitals in Lahore was approached to participate in the survey. The R-DAQ structure was examined using Parallel Analysis from polychoric correlations. Unweighted least squares analysis (ULSA) was used for factor extraction. Model fit was estimated using goodnessof- fit indices and the root mean square of standardized residuals (RMSR), and internal consistency reliability for the overall scale and subscales was assessed using reliability estimates based on Mislevy and Bock (BILOG 3 Item analysis and test scoring with binary logistic models. Mooresville: Scientific Software, 55) and the McDonald' s Omega statistic. Findings using this approach were compared with principal axis factor analysis based on Pearson correlation matrix. Results: 601 (86%) of the doctors approached consented to participate in the study. Exploratory factor analysis of R-DAQ scale responses demonstrated the same 3-factor structure as in the UK development study, though analyses indicated removal of 7 of the 22 items because of weak loading or poor model fit. The 3 factor solution accounted for 49.8% of the common variance. Scale reliability and internal consistency were adequate: total scale standardised alpha was 0.694; subscale reliability for professional confidence was 0.732, therapeutic optimism/pessimism was 0.638, and generalist perspective was 0.769. Conclusions: The R-DAQ was developed with a predominantly UK-based sample of health professionals. This study indicates that this scale functions adequately and provides a valid measure of depression attitudes for medical practitioners in Pakistan, with the same factor structure as in the scale development sample. However, optimal scale function necessitated removal of several items, with a 15-item scale enabling the most parsimonious factor solution for this population. [ABSTRACT FROM AUTHOR]

Despite the increasingly digital nature of society there are some areas of research that remain firmly rooted in the past; in this case the laboratory notebook, the last remaining paper component of an experiment. Countless electronic laboratory notebooks (ELNs) have been created in an attempt to digitise record keeping processes in the lab, but none of them have become a 'key player' in the ELN market, due to the many adoption barriers that have been identified in previous research and further explored in the user studies presented here. The main issues identified are the cost of the current available ELNs, their ease of use (or lack of it) and their accessibility issues across different devices and operating systems. Evidence suggests that whilst scientists willingly make use of generic notebooking software, spreadsheets and other general office and scientific tools to aid their work, current ELNs are lacking in the required functionality to meet the needs of the researchers. In this paper we present our extensive research and user study results to propose an ELN built upon a pre-existing cloud notebook platform that makes use of accessible popular scientific software and semantic web technologies to help overcome the identified barriers to adoption. [ABSTRACT FROM AUTHOR]

Scientific software production dates back to the days before the computer science discipline obtained its own name. Over the past 76 years, scientists have been producing software, which means that most of the modern techniques and software engineering methods available these days did not exist while part of this process was taking place. Change-driven development was born as a new approach to maintain and develop scientific software. Founded on the principles of software essence (changeability, complexity, intangibility, and conformity), integrated development tools, and automated source code transformation. This new, agile approach takes change as a working unit devised to drive the entire development process, which is performed in a four-stage cycle. One of the most interesting approaches to apply change-driven development on scientific software is to update, modernize and even parallelize sequential programs that have been written 20 or 30 years ago and are still running in production environments. This process will be thoroughly described and implemented. Two successful case studies will be presented and analyzed in depth. [ABSTRACT FROM AUTHOR]

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency. [ABSTRACT FROM AUTHOR]

We describe a new implementation of a two-level overlapping Schwarz preconditioner with energy-minimizing coarse space (GDSW: generalized Dryja--Smith--Widlund) and show numerical results for an additive and a hybrid additive-multiplicative version. Our parallel implementation makes use of the Trilinos software library and provides a framework for parallel two-level Schwarz methods. We show parallel scalability for two- and three-dimensional scalar second-order elliptic and linear elasticity problems for several thousands of cores. We also discuss techniques for the parallel construction of coarse spaces which are also of interest for other parallel preconditioners and discretization methods using energy minimizing coarse functions. We finally show an application in monolithic fluid-structure interaction, where significant improvements are achieved compared to a standard algebraic, one-level overlapping Schwarz method. [ABSTRACT FROM AUTHOR]

Parallel computation has been widely applied in a variety of large-scale scientific and engineering applications. Many studies indicate that exploiting both task and data parallelisms, i.e. mixed-parallel workflows, to solve large computational problems can get better efficacy compared with either pure task parallelism or pure data parallelism. Scheduling traditional workflows of pure task parallelism on parallel systems has long been known to be an NP-complete problem. Mixed-parallel workflow scheduling has to deal with an additional challenging issue of processor allocation. In this paper, we explore the processor allocation issue in scheduling mixed-parallel workflows of moldable tasks, called M-task, and propose an Iterative Allocation Expanding and Shrinking (IAES) approach. Compared to previous approaches, our IAES has two distinguishing features. The first is allocating more processors to the tasks on allocated critical paths for effectively reducing the makespan of workflow execution. The second is allowing the processor allocation of an M-task to shrink during the iterative procedure, resulting in a more flexible and effective process for finding better allocation. The proposed IAES approach has been evaluated with a series of simulation experiments and compared to several well-known previous methods, including CPR, CPA, MCPA, and MCPA2. The experimental results indicate that our IAES approach outperforms those previous methods significantly in most situations, especially when nodes of the same layer in a workflow might have unequal workloads. [ABSTRACT FROM AUTHOR]

We present mechanoChemML, a machine learning software library for computational materials physics. mechanoChemML is designed to function as an interface between platforms that are widely used for machine learning on one hand, and others for solution of partial differential equations-based models of physics. Of special interest here, and the focus of mechanoChemML, are applications to computational materials physics. These typically feature the coupled solution of material transport, reaction, phase transformation, mechanics, heat transport and electrochemistry. Central to the organization of mechanoChemML are machine learning workflows that arise in the context of data-driven computational materials physics. The mechanoChemML code structure is described, the machine learning workflows are laid out and their application to the solution of several problems in materials physics is outlined. [Display omitted] • We present a machine learning software library, mechanoChemML, for computational materials physics. • mechanoChemML serves as an interface between traditional PDE solver libraries and machine learning platforms. • mechanoChemML consists of various machine learning classes and data-driven workflows. [ABSTRACT FROM AUTHOR]

Background: More and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules. The rapidly increasing amount of publicly available data in biology and chemistry enables researchers to revisit interaction problems by systematic integration and analysis of heterogeneous data. Currently, some tools have been developed to represent these components. However, they have some limitations and only focus on the analysis of either small molecules or proteins or DNAs/RNAs. To the best of our knowledge, there is still a lack of freely-available, easy-to-use and integrated platforms for generating molecular descriptors of DNAs/RNAs, proteins, small molecules and their interactions. Results: Herein, we developed a comprehensive molecular representation platform, called BioTriangle, to emphasize the integration of cheminformatics and bioinformatics into a molecular informatics platform for computational biology study. It contains a feature-rich toolkit used for the characterization of various biological molecules and complex interaction samples including chemicals, proteins, DNAs/RNAs and even their interactions. By using BioTriangle, users are able to start a full pipelining from getting molecular data, molecular representation to constructing machine learning models conveniently. Conclusion: BioTriangle provides a user-friendly interface to calculate various features of biological molecules and complex interaction samples conveniently. The computing tasks can be submitted and performed simply in a browser without any sophisticated installation and configuration process. BioTriangle is freely available at .[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Segmentation and tracking of cells in long-term time-lapse experiments has emerged as a powerful method to understand how tissue shape changes emerge from the complex choreography of constituent cells. However, methods to store and interrogate the large datasets produced by these experiments are not widely available. Furthermore, recently developed methods for relating tissue shape changes to cell dynamics have not yet been widely applied by biologists because of their technical complexity. We therefore developed a database format that stores cellular connectivity and geometry information of deforming epithelial tissues, and computational tools to interrogate it and perform multi-scale analysis of morphogenesis. We provide tutorials for this computational framework, called TissueMiner, and demonstrate its capabilities by comparing cell and tissue dynamics in vein and inter-vein subregions of the Drosophila pupal wing. These analyses reveal an unexpected role for convergent extension in shaping wing veins. [ABSTRACT FROM AUTHOR]

In this paper we present a fully distributed, communicator-aware, recursive, and interlevel-overlapped message-passing implementation of the multilevel balancing domain decomposition by constraints (MLBDDC) preconditioner. The implementation highly relies on subcommunicators in order to achieve the desired effect of coarse-grain overlapping of computation and communication, and communication and communication among levels in the hierarchy (namely, interlevel overlapping). Essentially, the main communicator is split into as many nonoverlapping subsets of message-passing interface (MPI) tasks (i.e., MPI subcommunicators) as levels in the hierarchy. Provided that specialized resources (cores and memory) are devoted to each level, a careful rescheduling and mapping of all the computations and communications in the algorithm lets a high degree of overlapping be exploited among levels. All subroutines and associated data structures are expressed recursively, and therefore MLBDDC preconditioners with an arbitrary number of levels can be built while re-using significant and recurrent parts of the codes. This approach leads to excellent weak scalability results as soon as level-1 tasks can fully overlap coarser-levels duties. We provide a model to indicate how to choose the number of levels and coarsening ratios between consecutive levels and determine qualitatively the scalability limits for a given choice. We have carried out a comprehensive weak scalability analysis of the proposed implementation for the three-dimensional Laplacian and linear elasticity problems on structured and unstructured meshes. Excellent weak scalability results have been obtained up to 458,752 IBM BG/Q cores and 1.8 million MPI being, being the first time that exact domain decomposition preconditioners (only based on sparse direct solvers) reach these scales. [ABSTRACT FROM AUTHOR]

Software is increasingly important to the scientific enterprise, and science-funding agencies are increasingly funding software work. Accordingly, many different participants need insight into how to understand the relationship between software, its development, its use, and its scientific impact. In this article, we draw on interviews and participant observation to describe the information needs of domain scientists, software component producers, infrastructure providers, and ecosystem stewards, including science funders. We provide a framework by which to categorize different types of measures and their relationships as they reach around from funding, development, scientific use, and through to scientific impact. We use this framework to organize a presentation of existing measures and techniques, and to identify areas in which techniques are either not widespread, or are entirely missing. We conclude with policy recommendations designed to improve insight into the scientific software ecosystem, make it more understandable, and thereby contribute to the progress of science. [ABSTRACT FROM AUTHOR]

Unrestricted dissemination of methodological developments in neuroimaging became the propelling force in advancing our understanding of brain function. However, despite such a rich legacy, it remains not uncommon to encounter software and datasets that are distributed under unnecessarily restricted terms, or that violate terms of third-party products (software or data). With this brief correspondence we would like to recapitulate four important aspects of scientific research practice, which should be taken into consideration as early as possible in the course of any project. Keeping these in check will help neuroimaging to stay at the forefront of the open science movement. [ABSTRACT FROM AUTHOR]

Science is similar to a game, as both involve rules-based participation in search of optimal outcomes. Supported by key texts in history and philosophy of science, the authors propose a game-based model for understanding scientific inquiry and practice, particularly through computational resources. They conclude that this model creates space for more speculative and reflective approaches to scientific practice and can contribute to the design and development of better scientific software, simulation and visualization. [ABSTRACT FROM AUTHOR]

The article offers brief information on the IGMAP plant interactive mapping and clustering software.

The article reports that writing efficient scientific software that makes best use of the increasing complexity of computer architectures requires bringing together modeling, applied mathematics and computer engineering. It mentions that the use of computers to solve challenging theoretical problems that have no known analytical solution. It also mentions that the portability of imperative codes is not an issue as long as all computing platforms adhere to the same abstraction.

Aim Software use is ubiquitous in the species distribution modelling ( SDM) domain; nearly every scientist working on SDM either uses or develops specialist SDM software; however, little is formally known about the prevalence or preference of one software over another. We seek to provide, for the first time, a 'snapshot' of SDM users, the methods they use and the questions they answer. Location Global. Methods We conducted a survey of over 300 SDM scientists to capture a snapshot of the community and used an extensive literature search of SDM papers in order to investigate the characteristics of the SDM community and its interactions with software developers in terms of co-authoring research publications. Results Our results show that those members of the community who develop software and who are directly connected with developers are among the most highly connected and published authors in the field. We further show that the two most popular softwares for SDM lie at opposite ends of the 'use-complexity' continuum. Main conclusion Given the importance of SDM research in a changing environment, with its increasing use in the policy domain, it is vital to be aware of what software and methodologies are being implemented. Here, we present a snapshot of the SDM community, the software and the methods being used. [ABSTRACT FROM AUTHOR]

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/. [ABSTRACT FROM AUTHOR]

This paper is an extension of the debate on the nexus between the strength of intellectual property rights (IPRs) and prospects for knowledge economy. It assesses the relationships between software piracy and scientific publications in African countries for which data is available. The findings, which reveal a positive nexus, are broadly consistent with the school of thought postulating that the East Asian miracle has been largely due to weaker IPRs regimes at the early stages of development. As a policy implication, less stringent IPRs regimes on scientific-related software (at least in the short run) will substantially boost contributions to and dissemination of knowledge through scientific and technical publications in Africa. IPRs laws (treaties) on scientific-oriented software should be strengthened in tandem with progress in: (a) scientific and technical publications; and (b) knowledge spillovers essential for economic growth and development. More policy implications are discussed. [ABSTRACT FROM AUTHOR]