Abstract

Abstract
Malnutrition is widespread among older adults, and its determinants may differ between countries. We compared Portuguese and Turkish non-institutionalized older adults regarding nutritional status, sociodemographic, health and anthropometric characteristics and studied the relationships between nutritional status and those characteristics. This cross-sectional study analyzed data from 430 Portuguese and 162 Turkish non-institutionalized older adults regarding sociodemographics, health conditions, the Mini-Nutritional Assessment (MNA-FF) and anthropometry. Turkish older adults were more likely to be malnourished or at risk of malnutrition and had lower average BMI but a higher calf circumference. A higher proportion of the Portuguese sample had tooth loss, diabetes, hypertension, oncologic diseases, kidney diseases, osteoarticular problems or eye problems, while less had anemia. A better nutritional status (higher MNA-FF score) was found among the Portuguese, males, people using dentures, those without tooth loss, hypertension, cardiovascular diseases, anemia or oncological diseases and was related to younger age, higher BMI and a higher calf circumference. Malnutrition and its risk were higher among older adults from Turkey, despite Portuguese older adults presenting a higher prevalence of chronic diseases. Being female, older age, tooth loss, hypertension, anemia, CVD or oncological disorders and having a lower BMI or CC were associated with higher rates of malnutrition among older adults from Portugal and Turkey.

Abstract
In this work, we study last-mile delivery with the option of crowd shipping. A company uses occasional drivers to complement its fleet in the activity of delivering products to its customers. We model it as a variant of the stochastic capacitated vehicle routing problem. Our approach is data-driven, where not only customer orders but also the availability of occasional drivers are uncertain. It is assumed that marginal distributions of the uncertainty vector are known, but the joint distribution is difficult to estimate. We optimize considering a worst-case joint distribution and model with a strategic planning perspective, where we calculate an optimal a priori solution before the uncertainty is revealed. A limit on the infea-sibility of the routes due to the capacity is imposed using probabilistic constraints. We propose an extended formulation for the problem using column-dependent rows and implement a branch-price-and-cut algorithm to solve it. We also develop a heuristic approximation to cope with larger instances of the problem. Through computational experiments, we analyze the solution and performance of the implemented algorithms.

Abstract
In “Effectiveness of Secondary Risk–Reducing Strategies in Patients With Unilateral Breast Cancer With Pathogenic Variants of BRCA1 and BRCA2 Subjected to Breast-Conserving Surgery: Evidence-Based Simulation Study” (JMIR Form Res 2022;6(12):e37144) the authors noted one error. In the originally published article Figure 6 appeared as a duplicate of Figure 5. Figure 6 has been corrected as follows: (Figure Presented) The correction version appeared in the online version of the paper on the JMIR Publications website on January 18, 2023. Because this was made after submission to full-text repositories, the corrected article has also been resubmitted to those repositories. © Jelena Maksimenko, Pedro Pereira Rodrigues, Miki Nakazawa-Miklaševica, David Pinto, Edvins Miklaševics, Genadijs Trofimovics, Janis Gardovskis, Fatima Cardoso, Maria João Cardoso.

Abstract
Automatic grading based on unit tests is a key feature of massive open online courses (MOOC) on programming, as it allows instant feedback to students and enables courses to scale up. This technique works well for sequential programs, by checking outputs against a sample of inputs, but unfortunately it is not adequate for detecting races and deadlocks, which precludes its use for concurrent programming, a key subject in parallel and distributed computing courses. In this paper we provide a hands-on evaluation of verification and testing tools for concurrent programs, collecting a precise set of requirements, and describing to what extent they can or can not be used for this purpose. Our conclusion is that automatic grading of concurrent programming exercises remains an open challenge.

Abstract
Aim There has been an increase in the development of technologies that can deliver personalised dietary advice. Devising healthy, sustainable dietary plans will mean taking into consideration extrinsic factors such as individual social circumstances. The aim of this study was to identify societal groups more or less receptive to and likely to engage with personalised nutrition initiatives. Sample and methods Volunteers were recruited via a social research agency from within the UK. The resultant sample (N = 1061) was 49% female, aged 18-65 years. Results MANOVA (Tukey HSD applied) indicated that females and younger people (aged 18-29 years) had more favourable attitudes and were more likely to intend to adopt personalised nutrition. There were no differences in attitude toward or intention to adopt personalised nutrition between different education levels, income brackets or occupational groups. Conclusion These results imply that females and younger people may be most likely to adopt personalised nutrition in the future. Initiatives to promote healthy eating should target males and older people.