Evaluating Maintainability Prejudices with a Large-Scale Study of Open-Source Projects

Exaggeration or context changes can render maintainability experience into prejudice. For example, JavaScript is often seen as least elegant language and hence of lowest maintainability. Such prejudice should not guide decisions without prior empirical validation. We formulated 10 hypotheses about maintainability based on prejudices and test them in a large set of open-source projects (6,897 GitHub repositories, 402 million lines, 5 programming languages). We operationalize maintainability with five static analysis metrics. We found that JavaScript code is not worse than other code, Java code shows higher maintainability than C# code and C code has longer methods than other code. The quality of interface documentation is better in Java code than in other code. Code developed by teams is not of higher and large code bases not of lower maintainability. Projects with high maintainability are not more popular or more often forked. Overall, most hypotheses are not supported by open-source data.Comment: 20 page

Expedited batch processing and analysis of transposon insertions

<p>Abstract</p> <p>Background</p> <p>With advances in sequencing technology, greater and greater amounts of eukaryotic genome data are becoming available. Often, large portions of these genomes consist of transposable elements, frequently accounting for 50% or more in vertebrates. Each transposable element family may have thousands or tens of thousands of individual copies within a given genome, and therefore it can take an exorbitant amount of time and effort to process data in a meaningful fashion.</p> <p>Findings</p> <p>In order to combat this problem, we developed a set of bioinformatics techniques and programs to streamline the analysis. This includes a unique Perl script which automates the process of taking BLAST, Repeatmasker and similar data to extract and manipulate the hit sequences from the genome. This script, called Process_hits uses an object-oriented methodology to compile all hit locations from a given file for processing, organize this data into useable categories, and output it in multiple formats.</p> <p>Conclusions</p> <p>The program proved capable of handling large amounts of transposon data in an efficient fashion. It is equipped with a number of useful sub-functions, each of which is contained within its own sub-module to allow for greater expandability and as a foundation for future program design.</p

Qualitative evaluation of a deferred consent process in paediatric emergency research: a PREDICT study

Background: A challenge of conducting research in critically ill children is that the therapeutic window for the intervention may be too short to seek informed consent prior to enrolment. In specific circumstances, most international ethical guidelines allow for children to be enrolled in research with informed consent obtained later, termed deferred consent (DC) or retrospective consent. There is a paucity of data on the attitudes of parents to this method of enrolment in paediatric emergency research. Objectives: To explore the attitudes of parents to the concept of DC and to expand the knowledge of the limitations to informed consent and DC in these situations.MethodChildren presenting with uncomplicated febrile seizures or bronchiolitis were identified from three separate hospital emergency department databases. Parents were invited to participate in a semistructured telephone interview exploring themes of limitations of prospective informed consent, acceptability of the DC process and the most appropriate time to seek DC. Transcripts underwent inductive thematic analysis with intercoder agreement, using Nvivo 11 software. Results: A total of 39 interviews were conducted. Participants comprehended the limitations of informed consent under emergency circumstances and were generally supportive of DC. However, they frequently confused concepts of clinical care and research, and support for participation was commonly linked to their belief of personal benefit. Conclusion: Participants acknowledged the requirement for alternatives to prospective informed consent in emergency research, and were supportive of the concept of DC. Our results suggest that current research practice seems to align with community expectations.</jats:sec

A Database and Evaluation for Classification of RNA Molecules Using Graph Methods

In this paper, we introduce a new graph dataset based on the representation of RNA. The RNA dataset includes 3178 RNA chains which are labelled in 8 classes according to their reported biological functions. The goal of this database is to provide a platform for investigating the classication of RNA using graph-based methods. The molecules are represented by graphs representing the sequence and base-pairs of the RNA, with a number of labelling schemes using base labels and local shape. We report the results of a number of state-of-the-art graph based methods on this dataset as a baseline comparison and investigate how these methods can be used to categorise RNA molecules on their type and functions. The methods applied are Weisfeiler Lehman and optimal assignment kernels, shortest paths kernel and the all paths and cycle methods. We also compare to the standard Needleman-Wunsch algorithm used in bioinformatics for DNA and RNA comparison, and demonstrate the superiority of graph kernels even on a string representation. The highest classication rate is obtained by the WL-OA algorithm using base labels and base-pair connections

Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.The authors would like to thank COST Action FP0804-Forest Management Decision Support Systems (FORSYS) for financing a three month Short-Term Scientific Mission (STSM) in Forest Research (Roslin, UK) in 2012, making possible this research; Spanish Ministry of Economy and Competitiveness for supporting the project Multicriteria Techniques and Participatory Decision-Making for Sustainable Management (Ref. ECO2011-27369) where the leading author is involved; and the Regional Ministry of Education, Culture and Sports (Valencia, Spain) for financing a research fellowship (Ref. ACIF/2010/248).Valls Donderis, P.; Ray, D.; Peace, A.; Stewart, A.; Lawrence, A.; Galiana, F. (2013). Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?. Scandinavian Journal of Forest Research. 29(1):71-83. https://doi.org/10.1080/02827581.2013.837950S7183291Arnstein, S. R. (1969). A Ladder Of Citizen Participation. Journal of the American Institute of Planners, 35(4), 216-224. doi:10.1080/01944366908977225Atwell, R. C., Schulte, L. A., & Westphal, L. M. (2011). Tweak, Adapt, or Transform: Policy Scenarios in Response to Emerging Bioenergy Markets in the U.S. Corn Belt. Ecology and Society, 16(1). doi:10.5751/es-03854-160110Barac, A., Kellner, K., & De Klerk, N. (2004). Land User Participation in Developing a Computerised Decision Support System for Combating Desertification. Environmental Monitoring and Assessment, 99(1-3), 223-231. doi:10.1007/s10661-004-4022-6Bennet, A., & Bennet, D. (2008). The Decision-Making Process in a Complex Situation. Handbook on Decision Support Systems 1, 3-20. doi:10.1007/978-3-540-48713-5_1Blackstock, K. L., Kelly, G. J., & Horsey, B. L. (2007). Developing and applying a framework to evaluate participatory research for sustainability. Ecological Economics, 60(4), 726-742. doi:10.1016/j.ecolecon.2006.05.014Breuer, N. E., Cabrera, V. E., Ingram, K. T., Broad, K., & Hildebrand, P. E. (2007). AgClimate: a case study in participatory decision support system development. Climatic Change, 87(3-4), 385-403. doi:10.1007/s10584-007-9323-7Bunch, M. J., & Dudycha, D. J. (2004). Linking conceptual and simulation models of the Cooum River: collaborative development of a GIS-based DSS for environmental management. Computers, Environment and Urban Systems, 28(3), 247-264. doi:10.1016/s0198-9715(03)00021-8Byrne, E., & Sahay, S. (2007). Participatory design for social development: A South African case study on community-based health information systems. Information Technology for Development, 13(1), 71-94. doi:10.1002/itdj.20052Cain, J. ., Jinapala, K., Makin, I. ., Somaratna, P. ., Ariyaratna, B. ., & Perera, L. . (2003). Participatory decision support for agricultural management. A case study from Sri Lanka. Agricultural Systems, 76(2), 457-482. doi:10.1016/s0308-521x(02)00006-9Chakraborty, A. (2011). Enhancing the role of participatory scenario planning processes: Lessons from Reality Check exercises. Futures, 43(4), 387-399. doi:10.1016/j.futures.2011.01.004Cinderby, S., Bruin, A. de, Mbilinyi, B., Kongo, V., & Barron, J. (2011). Participatory geographic information systems for agricultural water management scenario development: A Tanzanian case study. Physics and Chemistry of the Earth, Parts A/B/C, 36(14-15), 1093-1102. doi:10.1016/j.pce.2011.07.039Drew, C. H., Nyerges, T. L., & Leschine, T. M. (2004). Promoting Transparency of Long‐Term Environmental Decisions: The Hanford Decision Mapping System Pilot Project. Risk Analysis, 24(6), 1641-1664. doi:10.1111/j.0272-4332.2004.00556.xDriedger, S. M., Kothari, A., Morrison, J., Sawada, M., Crighton, E. J., & Graham, I. D. (2007). Using participatory design to develop (public) health decision support systems through GIS. International Journal of Health Geographics, 6(1), 53. doi:10.1186/1476-072x-6-53Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53. doi:10.1108/14777830810840354Iivari, N. (2011). Participatory design in OSS development: interpretive case studies in company and community OSS development contexts. Behaviour & Information Technology, 30(3), 309-323. doi:10.1080/0144929x.2010.503351Innes, J. E., & Booher, D. E. (1999). Consensus Building and Complex Adaptive Systems. Journal of the American Planning Association, 65(4), 412-423. doi:10.1080/01944369908976071Jakku, E., & Thorburn, P. J. (2010). A conceptual framework for guiding the participatory development of agricultural decision support systems. Agricultural Systems, 103(9), 675-682. doi:10.1016/j.agsy.2010.08.007Jessel, B., & Jacobs, J. (2005). Land use scenario development and stakeholder involvement as tools for watershed management within the Havel River Basin. Limnologica, 35(3), 220-233. doi:10.1016/j.limno.2005.06.006Kautz, K. (2011). Investigating the design process: participatory design in agile software development. Information Technology & People, 24(3), 217-235. doi:10.1108/09593841111158356Kowalski, K., Stagl, S., Madlener, R., & Omann, I. (2009). Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis. European Journal of Operational Research, 197(3), 1063-1074. doi:10.1016/j.ejor.2007.12.049Lawrence, A. (2006). ‘No Personal Motive?’ Volunteers, Biodiversity, and the False Dichotomies of Participation. Ethics, Place & Environment, 9(3), 279-298. doi:10.1080/13668790600893319Mao, J., & Song, W. (2008). Empirical study of distinct features and challenges of joint development of information systems: The case of ABC bank. Tsinghua Science and Technology, 13(3), 414-419. doi:10.1016/s1007-0214(08)70066-xMenzel, S., Nordström, E.-M., Buchecker, M., Marques, A., Saarikoski, H., & Kangas, A. (2012). Decision support systems in forest management: requirements from a participatory planning perspective. European Journal of Forest Research, 131(5), 1367-1379. doi:10.1007/s10342-012-0604-yMoote, M. A., Mcclaran, M. P., & Chickering, D. K. (1997). RESEARCH: Theory in Practice: Applying Participatory Democracy Theory to Public Land Planning. Environmental Management, 21(6), 877-889. doi:10.1007/s002679900074Peleg, M., Shachak, A., Wang, D., & Karnieli, E. (2009). Using multi-perspective methodologies to study users’ interactions with the prototype front end of a guideline-based decision support system for diabetic foot care. International Journal of Medical Informatics, 78(7), 482-493. doi:10.1016/j.ijmedinf.2009.02.008Pretty, J. N. (1995). Participatory learning for sustainable agriculture. World Development, 23(8), 1247-1263. doi:10.1016/0305-750x(95)00046-fReed MS. 2008. Stakeholder participation for environmental management: a literature review. Sustainability Research Institute, School of Earth and Environment, University of Leeds.Reed, M. S., & Dougill, A. J. (2010). Linking degradation assessment to sustainable land management: A decision support system for Kalahari pastoralists. Journal of Arid Environments, 74(1), 149-155. doi:10.1016/j.jaridenv.2009.06.016Rowe, G., & Frewer, L. J. (2000). Public Participation Methods: A Framework for Evaluation. Science, Technology, & Human Values, 25(1), 3-29. doi:10.1177/016224390002500101Schielen, R. M. J., & Gijsbers, P. J. A. (2003). DSS-large rivers: developing a DSS under changing societal requirements. Physics and Chemistry of the Earth, Parts A/B/C, 28(14-15), 635-645. doi:10.1016/s1474-7065(03)00109-8Sheppard, S. R. J., & Meitner, M. (2005). Using multi-criteria analysis and visualisation for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 207(1-2), 171-187. doi:10.1016/j.foreco.2004.10.032Thursky, K. A., & Mahemoff, M. (2007). User-centered design techniques for a computerised antibiotic decision support system in an intensive care unit. International Journal of Medical Informatics, 76(10), 760-768. doi:10.1016/j.ijmedinf.2006.07.011Webler, S. T., Thomas. (1999). Voices from the Forest: What Participants Expect of a Public Participation Process. Society & Natural Resources, 12(5), 437-453. doi:10.1080/089419299279524Van Meensel, J., Lauwers, L., Kempen, I., Dessein, J., & Van Huylenbroeck, G. (2012). Effect of a participatory approach on the successful development of agricultural decision support systems: The case of Pigs2win. Decision Support Systems, 54(1), 164-172. doi:10.1016/j.dss.2012.05.002Von Geibler, J., Kristof, K., & Bienge, K. (2010). Sustainability assessment of entire forest value chains: Integrating stakeholder perspectives and indicators in decision support tools. Ecological Modelling, 221(18), 2206-2214. doi:10.1016/j.ecolmodel.2010.03.02

Antipsychotics and Torsadogenic Risk: Signals Emerging from the US FDA Adverse Event Reporting System Database

Background: Drug-induced torsades de pointes (TdP) and related clinical entities represent a current regulatory and clinical burden. Objective: As part of the FP7 ARITMO (Arrhythmogenic Potential of Drugs) project, we explored the publicly available US FDA Adverse Event Reporting System (FAERS) database to detect signals of torsadogenicity for antipsychotics (APs). Methods: Four groups of events in decreasing order of drug-attributable risk were identified: (1) TdP, (2) QT-interval abnormalities, (3) ventricular fibrillation/tachycardia, and (4) sudden cardiac death. The reporting odds ratio (ROR) with 95 % confidence interval (CI) was calculated through a cumulative analysis from group 1 to 4. For groups 1+2, ROR was adjusted for age, gender, and concomitant drugs (e.g., antiarrhythmics) and stratified for AZCERT drugs, lists I and II (http://www.azcert.org, as of June 2011). A potential signal of torsadogenicity was defined if a drug met all the following criteria: (a) four or more cases in group 1+2; (b) significant ROR in group 1+2 that persists through the cumulative approach; (c) significant adjusted ROR for group 1+2 in the stratum without AZCERT drugs; (d) not included in AZCERT lists (as of June 2011). Results: Over the 7-year period, 37 APs were reported in 4,794 cases of arrhythmia: 140 (group 1), 883 (group 2), 1,651 (group 3), and 2,120 (group 4). Based on our criteria, the following potential signals of torsadogenicity were found: amisulpride (25 cases; adjusted ROR in the stratum without AZCERT drugs = 43.94, 95 % CI 22.82-84.60), cyamemazine (11; 15.48, 6.87-34.91), and olanzapine (189; 7.74, 6.45-9.30). Conclusions: This pharmacovigilance analysis on the FAERS found 3 potential signals of torsadogenicity for drugs previously unknown for this risk

Economic burden and comorbidities of attention-deficit/hyperactivity disorder among pediatric patients hospitalized in the United States

<p>Abstract</p> <p>Background</p> <p>This retrospective database analysis used data from the Healthcare Cost and Utilization Project's Nationwide Inpatient Sample (NIS) to examine common primary diagnoses among children and adolescents hospitalized with a secondary diagnosis of attention- deficit/hyperactivity disorder (ADHD) and assessed the burden of ADHD.</p> <p>Methods</p> <p>Hospitalized children (aged 6-11 years) and adolescents (aged 12-17 years) with a secondary diagnosis of ADHD were identified. The 10 most common primary diagnoses (using the first 3 digits of the ICD-9-CM code) were reported for each age group. Patients with 1 of these conditions were selected to analyze demographics, length of stay (LOS), and costs. Control patients were selected if they had 1 of the 10 primary diagnoses and no secondary ADHD diagnosis. Patient and hospital characteristics were reported by cohort (i.e., patients with ADHD vs. controls), and LOS and costs were reported by primary diagnosis. Multivariable linear regression analyses were undertaken to adjust LOS and costs based on patient and hospital characteristics.</p> <p>Results</p> <p>A total of 126,056 children and 204,176 adolescents were identified as having a secondary diagnosis of ADHD. Among children and adolescents with ADHD, the most common diagnoses tended to be mental health related (i.e., affective psychoses, emotional disturbances, conduct disturbances, depressive disorder, or adjustment reaction). Other common diagnoses included general symptoms, asthma (in children only), and acute appendicitis. Among patients with ADHD, a higher percentage were male, white, and covered by Medicaid. LOS and costs were higher among children with ADHD and a primary diagnosis of affective psychoses (by 0.61 days and $51), adjustment reaction (by 1.71 days and$940), or depressive disorder (by 0.41 days and $124) versus controls. LOS and costs were higher among adolescents with ADHD and a primary diagnosis of affective psychoses (by 1.04 days and$352), depressive disorder (by 0.94 days and $517), conduct disturbances (by 0.86 days and$1,330), emotional disturbances (by 1.45 days and $1,626), adjustment reaction (by 1.25 days and$702), and neurotic disorders (by 1.60 days and $541) versus controls.</p> <p>Conclusion</p> <p>Clinicians and health care decision makers should be aware of the potential impact of ADHD on hospitalized children and adolescents.</p

Shallow water marine sediment bacterial community shifts along a natural CO2 gradient in the Mediterranean Sea off Vulcano, Italy.

The effects of increasing atmospheric CO(2) on ocean ecosystems are a major environmental concern, as rapid shoaling of the carbonate saturation horizon is exposing vast areas of marine sediments to corrosive waters worldwide. Natural CO(2) gradients off Vulcano, Italy, have revealed profound ecosystem changes along rocky shore habitats as carbonate saturation levels decrease, but no investigations have yet been made of the sedimentary habitat. Here, we sampled the upper 2 cm of volcanic sand in three zones, ambient (median pCO(2) 419 μatm, minimum Ω(arag) 3.77), moderately CO(2)-enriched (median pCO(2) 592 μatm, minimum Ω(arag) 2.96), and highly CO(2)-enriched (median pCO(2) 1611 μatm, minimum Ω(arag) 0.35). We tested the hypothesis that increasing levels of seawater pCO(2) would cause significant shifts in sediment bacterial community composition, as shown recently in epilithic biofilms at the study site. In this study, 454 pyrosequencing of the V1 to V3 region of the 16S rRNA gene revealed a shift in community composition with increasing pCO(2). The relative abundances of most of the dominant genera were unaffected by the pCO(2) gradient, although there were significant differences for some 5 % of the genera present (viz. Georgenia, Lutibacter, Photobacterium, Acinetobacter, and Paenibacillus), and Shannon Diversity was greatest in sediments subject to long-term acidification (>100 years). Overall, this supports the view that globally increased ocean pCO(2) will be associated with changes in sediment bacterial community composition but that most of these organisms are resilient. However, further work is required to assess whether these results apply to other types of coastal sediments and whether the changes in relative abundance of bacterial taxa that we observed can significantly alter the biogeochemical functions of marine sediments