Improving students' code correctness and test completeness by informal specifications

The quality of software produced by students is often poor. How to teach students to develop good quality software has long been a topic in computer science education and research. We must conclude that we still do not have a good answer to this question. Specifications are necessary to determine the correctness of software, to develop error-free software and to write complete tests. Several attempts have been made to teach students to write specifications before writing code. So far, that has not proven to be very successful: Students do not like to write a specification and do not see the benefits of writing specifications. In this paper we focus on the use of informal specifications. Instead of teaching students how to write specifications, we teach them how to use informal specifications to develop correct software. The results were surprising: the number of errors in software and the completeness of tests both improved considerably and, most importantly, students really appreciate the specifications. We think that if students appreciate specification, we have a key to teach them how to specify and to appreciate its value.Comment: 14 page

Common core assessments in follow-up studies of adults born preterm-Recommendation of the Adults Born Preterm International Collaboration

Of all newborns, 1%-2% are born very preterm (VP; <32 weeks) or with very low birthweight (VLBW; ≤1500 g). Advances in prenatal and neonatal care have substantially improved their survival, and the first generations who have benefited from these advances are now entering middle age. While most lead healthy lives, on average these adults are characterised by a number of adversities. These include cardiometabolic risk factors, airway obstruction, less physical activity, poorer visual function, lower cognitive performance, and a behavioural phenotype that includes inattention and internalising and socially withdrawn behaviour that may affect life chances and quality of life. Outcomes in later adulthood are largely unknown, and identifying trajectories of risk or resilience is essential in developing targeted interventions. Joint analyses of data and maintenance of follow-up of cohorts entering adulthood are essential. Such analyses are ongoing within the Adults Born Preterm International Collaboration (APIC; www.apic-preterm.org). Joint analyses require data harmonisation, highlighting the importance of consistent assessment methodologies. To present an expert recommendation on Common Core Assessments to be used in follow-up assessments of adults born preterm. Principles of Common Core Assessments were discussed at APIC meetings. Experts for each specific outcome domain wrote the first draft on assessments pertaining to that outcome. These drafts were combined and reviewed by all authors. Consensus was reached by discussion at APIC meetings. We present a recommendation by APIC experts on consistent measures to be used in adult follow-up assessments. The recommendation encompasses both "core" measures which we recommend to use in all assessments of adults born preterm that include the particular outcome. This will allow comparability between time and location. The recommendation also lists optional measures, focusing on current gaps in knowledge. It includes sections on study design, cardiometabolic and related biomarkers, biological samples, life style, respiratory, ophthalmic, cognitive, mental health, personality, quality of life, sociodemographics, social relationships, and reproduction. [Abstract copyright: © 2020 The Authors. Paediatric and Perinatal Epidemiology published by John Wiley & Sons Ltd.

Health-related quality-of-life outcomes of very preterm or very low birth weight adults : evidence from an individual participant data meta-analysis

Background and Objective Assessment of health-related quality of life for individuals born very preterm and/or low birthweight (VP/VLBW) offers valuable complementary information alongside biomedical assessments. However, the impact of VP/VLBW status on health-related quality of life in adulthood is inconclusive. The objective of this study was to examine associations between VP/VLBW status and preference-based health-related quality-of-life outcomes in early adulthood. Methods Individual participant data were obtained from five prospective cohorts of individuals born VP/VLBW and controls contributing to the ‘Research on European Children and Adults Born Preterm’ Consortium. The combined dataset included over 2100 adult VP/VLBW survivors with an age range of 18–29 years. The main exposure was defined as birth before 32 weeks’ gestation (VP) and/or birth weight below 1500 g (VLBW). Outcome measures included multi-attribute utility scores generated by the Health Utilities Index Mark 3 and the Short Form 6D. Data were analysed using generalised linear mixed models in a one-step approach using fixed-effects and random-effects models. Results VP/VLBW status was associated with a significant difference in the Health Utilities Index Mark 3 multi-attribute utility score of − 0.06 (95% confidence interval − 0.08, − 0.04) in comparison to birth at term or at normal birthweight; this was not replicated for the Short Form 6D. Impacted functional domains included vision, ambulation, dexterity and cognition. VP/VLBW status was not associated with poorer emotional or social functioning, or increased pain. Conclusions VP/VLBW status is associated with lower overall health-related quality of life in early adulthood, particularly in terms of physical and cognitive functioning. Further studies that estimate the effects of VP/VLBW status on health-related quality-of-life outcomes in mid and late adulthood are needed

Analyzing the seasonal relations between in situ fpar / LAI of cotton and spectral information of RapidEye

Leaf Area Index (LAI) and the fraction of absorbed Photosynthetically Active Radiation (fPAR) are frequently used for biophysical modeling of crop growth and yield prediction. This study examines the calculation of LAI and fPAR of cotton using statistical regression with spectral information of RapidEye. Based on the knowledge that commonly used vegetation indices (NDVI, SAVI, EVI) may underperform in the situation of dense vegetation the growing season was divided into main growth and reproductive phases. To account for saturation effects indices including the curvature in the red edge part of the spectra were tested. Field measurements on LAI and fPAR were carried out during the vegetation period of 2011 on cotton fields in Uzbekistan. The LAI/fPAR results for RapidEye data will be used as input for an upscaling to TERRA-MODIS time series and transfer to larger areas of Central Asia

Vergleich zweier statistischer Methoden zur Ableitung des Anteils absorbierter Photosynthese wirksamer Strahlung (FAPAR) für Baumwolle

The fraction of absorbed photosynthetic active radiation (FAPAR) is an important input for modelling biomass increase and agricultural yield and can be calculated based on optical remote sensing data. In this study two remote sensing based approaches to derive the FAPAR for irrigated cotton in Fergana valley, Uzbekistan, are tested and compared: (i) FAPAR rescale from the normalized difference vegetation index (NDVI) (“percentile approach”), and (ii) an empirical regression approach based on NDVI. In the rescaling approach FAPAR was derived by relating upper and lower percentiles derived from the NDVI distribution of cotton fields from the entire study area to fixed FAPAR minima (bare soil) and maxima. NDVI was derived from multi-temporal 6.5 m RapidEye data acquired throughout 2011. For the regression approach FAPAR data was collected in situ from cotton fields during the vegetation season. The percentile approach delivered an RMSE of 0.10 whilst regression was only slightly better with an RMSE of 0.07. Hence, the percentile approach could be concluded as being a fast and easy alternative to field data demanding empirical regressions for the derivation of FAPAR on cotton fields

Comparison of two Statistical Methods for the Derivation of the Fraction of Absorbed Photosynthetic Active Radiation for Cotton

The fraction of absorbed photosynthetic active radiation (FAPAR) is an important input for modelling biomass increase and agricultural yield and can be calculated based on optical remote sensing data. In this study two remote sensing based approaches to derive the FAPAR for irrigated cotton in Fergana valley, Uzbekistan, are tested and compared: (i) FAPAR rescale from the normalized difference vegetation index (NDVI) (“percentile approach”), and (ii) an empirical regression approach based on NDVI. In the rescaling approach FAPAR was derived by relating upper and lower percentiles derived from the NDVI distribution of cotton fields from the entire study area to fixed FAPAR minima (bare soil) and maxima. NDVI was derived from multi-temporal 6.5 m RapidEye data acquired throughout 2011. For the regression approach FAPAR data was collected in situ from cotton fields during the vegetation season. The percentile approach delivered an RMSE of 0.10 whilst regression was only slightly better with an RMSE of 0.07. Hence, the percentile approach could be concluded as being a fast and easy alternative to field data demanding empirical regressions for the derivation of FAPAR on cotton fields