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Recent studies have shed light on how the COVID-19 pandemic changed our lives, and most of them have documented its detrimental effect on eating habits. Until now, the effects of this global crisis on negative body image and its association with disordered eating behaviors remain largely understudied. This study aimed to investigate changes in frequency of disordered eating behaviors (i.e., restrictive eating, emotional eating, and overeating) and negative body image (i.e., shape and weight concern, and body dissatisfaction) among a community sample of women during the COVID-19 pandemic (October 2020–May 2021). Furthermore, we explored the possible relation between body image-related variables and changes in the frequency of disordered eating behaviors in the context of the pandemic. A total of 161 self-identified female participants enrolled in an online-based survey. Descriptive statistics showed that women did not report clinically significant levels of weight and body shape concerns, but participants reported being dissatisfied with their body. One sample Wilcoxon Signed Rank tests revealed a tendency toward an increasing of the frequency of all disordered eating behaviors during the COVID-19 pandemic. Multinomial logistic regressions showed that weight concerns predicted an overall increase in the frequency of restrictive eating behaviors, whereas higher body dissatisfaction was associated with a moderate self-perceived increase in the frequency of emotional eating. These results shed light on a risk pattern of phenomena in a non-clinical sample of women, as they represent the key risk factors for the development of eating disorders. Findings could have implications for designing and implementing prevention programs.

The chemical composition of dark chocolate has a significant impact on its complex flavor profile. This study aims to investigate the relationship between the volatile chemical composition and perceived flavor of 54 dark chocolate samples made from Trinitario cocoa beans from the Dominican Republic. The samples were evaluated by a trained panel and analyzed using gas chromatography-mass spectrometry (GC-MS) to identify and quantify the volatile compounds. Predictive models based on a partial least squares regression (PLS) allowed the identification of key compounds for predicting individual sensory attributes. The models were most successful in classifying samples based on the intensity of bitterness and astringency, even though these attributes are mostly linked to non-volatile compounds. Acetaldehyde, dimethyl sulfide, and 2,3-butanediol were found to be key predictors for various sensory attributes, while propylene glycol diacetate was identified as a possible marker for red fruit aroma. The study highlights the potential of using volatile compounds to accurately predict chocolate flavor potential.

Arduino is an open-source electronics platform based on cheap hardware and the easy-to-use software Integrated Development Environment (IDE). Nowadays, because of its open-source nature and its simple and accessible user experience, Arduino is ubiquitous and used among hobbyist and novice programmers for Do It Yourself (DIY) projects, especially in the Internet of Things (IoT) domain. Unfortunately, such diffusion comes with a price. Many developers start working on this platform without having a deep knowledge of the leading security concepts in Information and Communication Technologies (ICT). Their applications, often publicly available on GitHub (or other code-sharing platforms), can be taken as examples by other developers or downloaded and used by non-expert users, spreading these issues in other projects. For these reasons, this paper aims at understanding the current landscape by analyzing a set of open-source DIY IoT projects and looking for potential security issues. Furthermore, the paper classifies those issues according to the proper security category. This study’s results offer a deeper understanding of the security concerns in Arduino projects created by hobbyist programmers and the dangers that may be faced by those who use these projects.

In order for a lignocellulosic bioenergy feedstock to be considered sustainable, it must possess a high rate of growth to supply biomass for conversion. Despite the desirability of a fast growth rate for industrial application, it is unclear what effect growth rate has on biomass composition or saccharification. We characterized Klason lignin, glucan, and xylan content with response to growth in Corymbia interspecific F1 hybrid families (HF) and parental species Corymbia torelliana and C. citriodora subspecies variegata and measured the effects on enzymatic hydrolysis from hydrothermally pretreated biomass. Analysis of biomass composition within Corymbia populations found similar amounts of Klason lignin content (19.7-21.3%) among parental and hybrid populations, whereas glucan content was clearly distinguished within C. citriodora subspecies variegata (52%) and HF148 (60%) as compared to other populations (28-38%). Multiple linear regression indicates that biomass composition is significantly impacted by tree size measured at the same age, with Klason lignin content increasing with diameter breast height (DBH) (+0.12% per cm DBH increase), and glucan and xylan typically decreasing per DBH cm increase (-0.7 and -0.3%, respectively). Polysaccharide content within C. citriodora subspecies variegata and HF-148 were not significantly affected by tree size. High-throughput enzymatic saccharification of hydrothermally pretreated biomass found significant differences among Corymbia populations for total glucose production from biomass, with parental Corymbia torelliana and hybrids HF-148 and HF-51 generating the highest amounts of glucose (~180 mg/g biomass, respectively), with HF-51 undergoing the most efficient glucan-to-glucose conversion (74%). Based on growth rate, biomass composition, and further optimization of enzymatic saccharification yield, high production Corymbia hybrid trees are potentially suitable for fast-rotation bioenergy or biomaterial production.