Citrus fruit detection based on an improved YOLOv5 under natural orchard conditions.

Accurate detection of citrus can be easily affected by adjacent branches and overlapped fruits in natural orchard conditions, where some specific information of citrus might be lost due to the resultant complex occlusion. Traditional deep learning models might result in lower detection accuracy and detection speed when facing occluded targets. To solve this problem, an improved deep learning algorithm based on YOLOv5, named IYOLOv5, was proposed for accurate detection of citrus fruits. An innovative Res-CSPDarknet network was firstly employed to both enhance feature extraction performance and minimize feature loss within the backbone network, which aims to reduce the miss detection rate. Subsequently, the BiFPN module was adopted as the new neck net to enhance the function for extracting deep semantic features. A coordinate attention mechanism module was then introduced into the network's detection layer. The performance of the proposed model was evaluated on a home-made citrus dataset containing 2000 optical images. The results show that the proposed IYOLOv5 achieved the highest mean average precision (93.5%) and F1-score (95.6%), compared to the traditional deep learning models including Faster R-CNN, CenterNet, YOLOv3, YOLOv5, and YOLOv7. In particular, the proposed IYOLOv5 obtained a decrease of missed detection rate (at least 13.1%) on the specific task of detecting heavily occluded citrus, compared to other models. Therefore, the proposed method could be potentially used as part of the vision system of a picking robot to identify the citrus fruits accurately

Interventions to mitigate infant food insecurity in high-income countries: an overview of current evidence.

Infant food insecurity (IFI) is a critical and often overlooked issue in high-income countries. This scoping review aims to identify and summarise interventions that reduce food insecurity or improve nutrition amongst families with infants in these regions. We searched the major electronic databases and websites of relevant UK and international organisations from 2010 to 2023 to identify reports written in English assessing food insecurity affecting infants (aged 0 to 2 years). The findings were presented in tables and summarised narratively. Out of 6194 records identified, 104 studies were screened, with only two studies meeting the inclusion criteria. Both studies were conducted in the USA. The KIND (Keeping Infants Nourished and Developing) intervention improved preventive care for food-insecure families, increasing lead level test completion rates and well-infant visits, but it did not affect weight-for-length at 9 months. The GWCC (Group Well-Child Care) intervention aimed at promoting responsive feeding amongst low-income caregivers but showed no significant impact on infant growth in the first year. However, caregiver interviews revealed important feeding-related themes. Evidence on interventions addressing infant food insecurity is limited, with none found in the UK. The KIND and GWCC interventions showed mixed outcomes, improving some aspects of care but not significantly affecting infant growth metrics. These findings highlight the need for further research to develop more effective strategies to address the nutritional needs of vulnerable infants in high-income countries

Resistance training beyond momentary failure: the effects of past-failure partials versus initial partials on calf muscle hypertrophy among a resistance-trained cohort.

This study compared calf training with initial partial repetitions versus full range-of-motion (ROM) repetitions followed by past-failure partials on gastrocnemius hypertrophy. Twenty-three participants (men: n = 16 and women: n = 7) performed four sets of unilateral Smith machine calf raises to momentary failure twice a week for 8 weeks. One leg was trained using initial partials to their individualized maximum dorsiflexion ROM. The contralateral leg was trained with a full ROM and continued with past-failure partials after failure in peak plantarflexion. Medial gastrocnemius muscle thickness was measured with ultrasonography both baseline and postintervention. A Bayesian framework was used to estimate the average treatment effect (ATE) using credible intervals and Bayes factors (BFs). The ATE posterior distribution indicated a greater increase in muscle hypertrophy for the initial partial condition (0.40 [95% CrI: −0.06 to 0.85 mm]; p (> 0) = 0.958), with a BF of 1.2 suggesting "anecdotal" evidence in favor of an effect. Within-condition analyses using standardized mean difference estimates indicated that the interventions were likely to produce medium to large improvements. These findings suggest that both initial partials and past-failure partials are viable strategies for achieving gastrocnemius hypertrophy. Although the average change favored initial partials, the estimated difference was uncertain, and the Bayes factor provided only anecdotal support for a differential effect

Data systems education: curriculum recommendations, course syllabi, and industry needs.

Data systems have been an important part of computing curricula for decades, and an integral part of data-focused industry roles such as software developers, data engineers, and data scientists. However, the field of data systems encompasses a large number of topics ranging from data manipulation and database distribution to creating data pipelines and data analytics solutions. Due to the slow nature of curriculum development, it remains unclear (i) which data systems topics are recommended across diverse higher education curriculum guidelines, (ii) which topics are taught in higher education data systems courses, and (iii) which data systems topics are actually valued in data-focused industry roles. In this study, we analyzed computing curriculum guidelines, course contents, and industry needs regarding data systems to uncover discrepancies between them. Our results show, for example, that topics such as data visualization, data warehousing, and semi-structured data models are valued in industry, yet seldom taught in courses. This work allows professionals to further align curriculum guidelines, higher education, and data systems industry to better prepare students for their working life by focusing on relevant skills in data systems education

Stitching urban vision (SUV): psychogeographic and visual content analysis in co-creating collaborative capacity among children. [Case study]

This case study explores the "Stitching Urban Vision" (SUV) method, which aims to help children develop negotiation skills with a view to achieving successful outcomes, rather than the delayed, unresolved or fragmented outcomes that can result from other negotiation methods. Studies in the use of SUV have demonstrated how disparate and self-drawn ideas can be stitched into an intelligible shared vision

A life cycle carbon assessment and multi-criteria decision-making framework for building renovation within the circular economy context: a case study.

Applying circular economy principles to the renovation of existing buildings is increasingly recognized as essential to achieving Europe's climate and energy goals. However, current decision-making frameworks rarely integrate life cycle carbon assessment with multi-criteria evaluation to support circular renovation strategies. This paper introduces an innovative framework that combines life cycle carbon assessment with multi-criteria decision analysis to identify and sequence circular renovation measures. The framework was applied to a residential case study in the Netherlands, using IES VE for operational carbon assessment and One Click LCA for embodied carbon assessment, with results evaluated using PROMETHEE multi-criteria analysis. Renovation measures were assessed based on operational and embodied carbon (including Module D), energy use intensity, cost, pay-back period, and disruption. The evaluation also introduced the embodied-to-operational carbon ratio (EOCR), a novel metric representing the proportion of embodied carbon, including Module D, relative to operational carbon savings over the building's lifecycle. The homeowner's preferences regarding these criteria were considered in determining the final ranking. The findings show that circular insulation options involving reused materials and designed for disassembly achieved the lowest embodied carbon emissions and lowest EOCR scores, with reused PIR achieving a 94% reduction compared to new PIR boards. The impact of including Module D on the ranking of renovation options varies based on the end-of-life scenario. The framework demonstrates how circular renovation benefits can be made more visible to decision-makers, promoting broader adoption

SSRI antidepressants and perceived loss of lean muscle in men: a qualitative exploration of some online anecdotal concerns.

This study examines anecdotal reports from online discussion forums suggesting possible links between SSRI antidepressants and loss of lean muscle mass, particularly in men. Given limited existing scientific research, this study bolsters academic discourse. The specific research question was, "Do self-reported experiences from internet forums indicate a perceived connection between SSRI use and muscle mass reductions?". A Google keyword search identified 202 posts from 14 randomly selected online antidepressant discussion forums. Posts were collected and thematically analysed. Forum users reported difficulties in maintaining or gaining lean muscle after commencing SSRI treatment. Key themes included frustration, confusion, and attempts to rationalise perceived changes. Findings suggest an area for further exploration, regarding the physiological impact of SSRIs on muscle composition. While reports remain anecdotal, they highlight concerns immediately relevant to both patients and healthcare professionals. As the study is based on self-reported experiences from anonymous sources, findings lack scientific validation, but highlight requirements for further studies to explore prevalence and broader applicability. Research observations spotlight a need for further, structured clinical research to investigate possible effects of SSRIs on muscle mass. Future research should include controlled clinical trials and longitudinal studies to examine a potential association in more detail

Embedding study skills in higher education.

Academics and practitioners in sport and exercise science higher education face challenges in producing graduates proficient in real-world employment skills and ensuring students have the necessary academic and scientific rigor. With a broader range of qualifications entering university courses, universities must ensure continuity and address students lacking study skills, which negatively impact their learning potential

Interpretable decision trees to predict solution fitness.

Metaheuristic algorithms are powerful tools for tackling complex optimization problems, but their black-box nature often hinders user trust and understanding. This paper presents a novel methodology for enhancing the explainability of metaheuristics by employing decision trees with splitting criteria based on Partial Solutions. These represent beneficial sub-structures of solutions and provide insights into the problem landscape and solution characteristics. By constructing decision trees that consider the presence or absence of specific patterns in solutions, we produce a transparent model capable of predicting solution fitness. The proposed methodology is evaluated on a diverse set of benchmark problems and metaheuristic algorithms, demonstrating its effectiveness and flexibility as a post-hoc explainability tool. Our results show that our decision trees can match and usually surpass traditional methods in predicting the fitness of candidate solutions for the tested benchmark problems, with one of our methods demonstrating an improvement between 4.4% and 16.7% in R2 predictive performance for shallower trees trained on a Genetic Algorithm's data. These trees are able to maintain competitive predictive performance while using more interpretable splitting criteria

Gen AI and the HE classroom: the good, the bad, the ugly.

This talk focuses on the implications of using Generative Artificial Intelligence (Gen AI) in the higher education classroom setting – the opportunities, challenges, and areas for caution in terms of its environmental costs. It seeks to raise awareness of the significant energy consumption, water utilisation and ethical dilemma with raw material extraction for graphic processing units