Students as co-producers in a multidisciplinary software engineering project: addressing cultural distance and cross-cohort handover

This article reports on an undergraduate software engineering project in which, over a period of two years, four student teams from different cohorts developed a note-taking app for four academic clients at the students’ own university. We investigated how projects involving internal clients can give students the benefits of engaging in real software development while also giving them experience of a student-staff collaboration that has its own benefits for students, academics, and the university more broadly. As the university involved is a Sino-Foreign university located in China, where most students are Chinese and most teaching staff are not, this ‘student as co-producer’ approach interacts with another feature of the project: cultural distance. Based on analysis of notes, reports, interviews, and focus groups, we recommend that students should be provided with communicative strategies for dealing with academics as clients; universities should develop policies on ownership of student-staff collaborations; and projects should include a formalised handover process. This article can serve as guidance for educators considering a ‘students as co-producers’ approach for software development projects

Low-Density Water Structure Observed in a Nanosegregated Cryoprotectant Solution at Low Temperatures from 285 to 238 K

The structure of liquid water is defined by its molecular association through hydrogen bonding. Two different structures have been proposed for liquid water at low temperatures: low-density liquid (LDL) and high-density liquid (HDL) water. Here, we demonstrate a platform that can be exploited to experimentally probe the structure of liquid water in equilibrium at temperatures down to 238 K. We make use of a cryoprotectant molecule, glycerol, that, when mixed with water, lowers the freezing temperature of the solution nonmonotonically with glycerol concentration. We use a combination of neutron diffraction measurements and computational modeling to examine the structure of water in glycerol–water liquid mixtures at low temperatures from 285 to 238 K. We confirm that the mixtures are nanosegregated into regions of glycerol-rich and water-rich clusters. We examine the water structure and reveal that, at the temperatures studied here, water forms a low-density water structure that is more tetrahedral than the structure at room temperature. We postulate that nanosegregation allows water to form a low-density structure that is protected by an extensive and encapsulating glycerol interface

Critical care resources in the Solomon Islands: a cross-sectional survey

<p>Abstract</p> <p>Background</p> <p>There are minimal data available on critical care case-mix, care processes and outcomes in lower and middle income countries (LMICs). The objectives of this paper were to gather data in the Solomon Islands in order to gain a better understanding of common presentations of critical illness, available hospital resources, and what resources would be helpful in improving the care of these patients in the future.</p> <p>Methods</p> <p>This study used a mixed methods approach, including a cross sectional survey of respondents' opinions regarding critical care needs, ethnographic information and qualitative data.</p> <p>Results</p> <p>The four most common conditions leading to critical illness in the Solomon Islands are malaria, diseases of the respiratory system including pneumonia and influenza, diabetes mellitus and tuberculosis. Complications of surgery and trauma less frequently result in critical illness. Respondents emphasised the need for basic critical care resources in LMICs, including equipment such as oximeters and oxygen concentrators; greater access to medications and blood products; laboratory services; staff education; and the need for at least one national critical care facility.</p> <p>Conclusions</p> <p>A large degree of critical illness in LMICs is likely due to inadequate resources for primary prevention and healthcare; however, for patients who fall through the net of prevention, there may be simple therapies and context-appropriate resources to mitigate the high burden of morbidity and mortality. Emphasis should be on the development and acquisition of simple and inexpensive tools rather than complicated equipment, to prevent critical care from unduly diverting resources away from other important parts of the health system.</p

An empirical comparison of commercial and open‐source web vulnerability scanners

Web vulnerability scanners (WVSs) are tools that can detect security vulnerabilities in web services. Although both commercial and open-source WVSs exist, their vulnerability detection capability and performance vary. In this article, we report on a comparative study to determine the vulnerability detection capabilities of eight WVSs (both open and commercial) using two vulnerable web applications: WebGoat and Damn vulnerable web application. The eight WVSs studied were: Acunetix; HP WebInspect; IBM AppScan; OWASP ZAP; Skipfish; Arachni; Vega; and Iron WASP. The performance was evaluated using multiple evaluation metrics: precision; recall; Youden index; OWASP web benchmark evaluation; and the web application security scanner evaluation criteria. The experimental results show that, while the commercial scanners are effective in detecting security vulnerabilities, some open-source scanners (such as ZAP and Skipfish) can also be effective. In summary, this study recommends improving the vulnerability detection capabilities of both the open-source and commercial scanners to enhance code coverage and the detection rate, and to reduce the number of false-positives

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Quality standards for the management of alcohol-related liver disease: consensus recommendations from the British Association for the Study of the Liver and British Society of Gastroenterology ARLD special interest group

Objective Alcohol-related liver disease (ALD) is the most common cause of liver-related ill health and liver-related deaths in the UK, and deaths from ALD have doubled in the last decade. The management of ALD requires treatment of both liver disease and alcohol use; this necessitates effective and constructive multidisciplinary working. To support this, we have developed quality standard recommendations for the management of ALD, based on evidence and consensus expert opinion, with the aim of improving patient care. Design A multidisciplinary group of experts from the British Association for the Study of the Liver and British Society of Gastroenterology ALD Special Interest Group developed the quality standards, with input from the British Liver Trust and patient representatives. Results The standards cover three broad themes: the recognition and diagnosis of people with ALD in primary care and the liver outpatient clinic; the management of acutely decompensated ALD including acute alcoholrelated hepatitis and the posthospital care of people with advanced liver disease due to ALD. Draft quality standards were initially developed by smaller working groups and then an anonymous modified Delphi voting process was conducted by the entire group to assess the level of agreement with each statement. Statements were included when agreement was 85% or greater. Twenty-four quality standards were produced from this process which support best practice. From the final list of statements, a smaller number of auditable key performance indicators were selected to allow services to benchmark their practice and an audit tool provided. Conclusion It is hoped that services will review their practice against these recommendations and key performance indicators and institute service development where needed to improve the care of patients with ALD