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Research on time series prediction of microclimate in agrivoltaic systems based on the long short-term memory and attention mechanism
Get PDFIntroduction: Agrivoltaic (AV) systems combine photovoltaic (PV) power generation with agriculture to enhance land use and energy production. However, accurately predicting the microclimate within AV systems remains a challenge, primarily due to existing models failing to get their inherent temporal and spatial variability.Methods: To address this, this study used long short-term memory (LSTM) networks to process time-series data and incorporated an attention mechanism to adjust the importance of temporal features. The model considered two environmental parameters, including solar radiation intensity and air temperature. Data collected from experimental AV systems with different PV panel density in Nanjing, China. The performance of the LSTM-Attention model was compared with traditional machine learning methods and standard LSTM models.Results: The results demonstrated that the LSTM-Attention model outperformed the other models in predicting both solar radiation intensity and air temperature within AV systems with different PV panel density. Specifically, the Root Mean Square Error (RMSE) for radiation intensity predictions decreased by 28.0%, 35.7%, and 42.1% at different coverage densities. For air temperature predictions, the RMSE dropped by 39.0% in summer and 18.1% in winter. Importantly, the LSTM-Attention model maintained stable prediction performance even in winter and rainy weather conditions.Discussion: The results indicated that the LSTM-Attention model could effectively captured the complex temporal variations in solar radiation and air temperature within AV systems, especially under varying weather conditions. The study provides theoretical support for improving crop management strategies within AV systems
Antecedents and outcomes of a later attention deficit hyperactivity disorder (ADHD) diagnosis in females
No full textBackground: Females are less likely than males to be diagnosed with attention deficit hyperactivity disorder (ADHD). When diagnosed, females are older than males. Aims: In this study, we examined the childhood antecedents of later ADHD diagnosis and its impact on adolescent/emerging adult outcomes, with a focus on females. Method: In this cohort study, we used data from a Welsh nation-wide electronic cohort of 13,593 individuals (N=2,680 (19.7%) females) diagnosed with ADHD and 578,793 individuals (N=286,734 (49.5%) females) without ADHD. We compared females with later diagnoses (ages 12–25) to those with earlier, timely diagnoses (ages 5–11) and no diagnosis, in terms of childhood (ages 5–11) antecedents and adolescent/adult (ages 12–25) outcomes. We also tested for sex differences. Results: Although females with earlier ADHD diagnosis showed more health and educational difficulties in childhood than those with later diagnosed ADHD (ORs ranged from 0.18–0.92), there was clear evidence of these difficulties in females with later diagnosed ADHD, compared to females without ADHD (ORs: 1.07–9.02). In adolescence/early adulthood, females with later diagnosed ADHD used more healthcare services and had worse mental health, educational and socioeconomic outcomes than females diagnosed earlier (ORs: 1.39–4.96) and those without ADHD (ORs: 1.54–23.98). Many of these outcomes were exacerbated in females compared to males. Conclusions: The results demonstrate that later ADHD diagnosis is associated with significant negative outcomes by adolescence and disproportionately disadvantages females. Despite later diagnosis, there was clear evidence of childhood mental health and educational difficulties when compared to females without ADHD. Therefore, timely childhood ADHD diagnosis may help to mitigate later risks, especially for females
Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for Parkinson's disease dementia
Get PDFIntroduction: Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are urgently needed. Plasma small extracellular vesicles (SEV) reflect molecular changes in living human brain. Next-generation RNA-sequencing (RNA-Seq) of PDD plasma SEV can advance our understanding of PDD molecular pathology, and identify blood-based biomarkers. Hence, we conducted the first comprehensive transcriptomic analysis of PDD plasma SEV. Methods: We investigated plasma SEV RNA of PDD, PD, and people without PD or dementia (Controls) using RNA-Seq (n = 15/group; N = 45). SEV were separated by ultracentrifugation, and characterized by cryo-transmission electron microscopy. We identified differentially expressed genes (DEGs) in PDD plasma SEV using an edgeR-based data analysis pipeline and verified them by high-throughput qPCR. We assessed functional implications of identified DEGs using Ingenuity Pathway and causal network analyses. Results: We identified 51 transcriptome-wide significant (edgeR q < 0.05) DEGs, compared to controls, and 26 transcriptome-wide significant DEGs, compared to PD, in PDD plasma SEV. The identified DEGs, which included WNT5A, MAPT, FOSB, MIR324, MIR574, MIR3161, and MIR6821 were significantly enriched among Tetrahydrofolate salvage, Reelin signalling, tRNA splicing, Wnt signalling, and ERBB signalling pathways. We identified eight potential multiplex plasma SEV RNA biomarker assays that can distinguish PDD from PD with at least 80 % sensitivity and specificity using an artificial intelligence-based algorithm. Conclusion: Future research on the identified dysfunctional molecular pathways may facilitate discovery of novel therapeutic targets for PDD. Diagnostic biomarker potential of the derived multiplex RNA biomarker assays should be investigated by larger clinical studies
Colonial legacies and cultural influences on discard behaviour: a systematic review
Get PDFIn the Global South, discarding practices are shaped not only by contemporary debates on circular economies and environmental justice, but also by enduring colonial legacies and cultural influences that continue to structure material flows and social responsibilities. We thematically synthesised 48-peer-reviewed articles on how household-level discard practices are informed by cultural meanings and colonial influences, offering a comprehensive account that bridges fragmented studies into a coherent decolonial perspective. Using the PRISMA methodology and Population, Experience, and Outcome framing, we identified five key themes: the legacies of imposed systems; the gradual erosion of traditional discard practices; religious paradigms of waste; women's invisible labour and stigmatisation; and the rise of informal waste economies in response to municipal voids. After drawing the distinction between waste colonialism and colonial influence on waste in the introductory section, our findings demonstrate how the latter have continued to shape contemporary waste infrastructure and behaviours, often conflicting with local cultural norms and practices. We propose hybrid waste governance models that integrate formal systems with community-based approaches, traditional practices, and informal economies. The review highlights the need to reframe waste management not just as a technical issue but also as a culturally mediated and historically situated practice. This review provides insights into the development of more equitable, effective, and culturally sensitive waste policies in the context of the Global South
Enhancing Deep Learning and Workload Management in Online Education: The Power of Scaffolded Weekly Assessments
Get PDFThis study investigates the use of scaffolded weekly assessments with individual feedback in promoting deep learning and managing workload among engineering students in online education. The research focuses on how these assessment strategies shape students’ learning approaches and workload distribution. The study involved the implementation of weekly assessments aligned with intended learning outcomes, complemented by personalized feedback. Data collection comprised student surveys and qualitative feedback to assess the impact on learning approaches and workload management. The qualitative results show that 91.9% of the students adopted deep learning, where only 8.1% engaging in surface learning. Students reported that this approach not only prepared them more effectively for summative evaluations but also contributed to more balanced and efficient workload management. This was particularly noteworthy in the context of online learning, where maintaining student engagement poses additional challenges. The study highlights that structured, feedback-rich assessments can enhance student engagement in online learning environments
Novel Symptom Subgroups in Patients with Irritable Bowel Syndrome Are Associated with Healthcare Utilisation in Secondary and Tertiary Care
Get PDFBackground & Aims: Current classification systems for irritable bowel syndrome (IBS) based on bowel habit do not consider psychological impact. We applied a previously validated latent class analysis (LCA) model to a cohort of patients with IBS in secondary and tertiary care to assess whether it predicted levels of healthcare utilisation. Methods: We applied our LCA model to a referral population with IBS. As described previously, we assigned cluster membership based on gastrointestinal symptom severity and psychological burden. We assessed demographics, symptom severity and quality of life at baseline and levels of healthcare utilisation during 12 months of longitudinal follow-up according to cluster. Results: We recruited 379 patients, of whom 249 (65.7%) met the Rome IV criteria. Those in the four clusters with higher psychological burden had more severe symptoms on the IBS-SSS and lower quality of life scores (p < 0.001 for both). Rates of discharge were generally lower in clusters with higher psychological burden (p = 0.05). Rates of prescribing a drug for IBS (p = 0.001), the mean number of drugs prescribed for IBS (p < 0.001) and the mean number of different drug types prescribed for IBS (p < 0.001 for trend) were highest in the four clusters with higher psychological burden. Conclusions: In patients with IBS in secondary and tertiary care, the LCA model identified groups of individuals with more severe symptoms and greater impairments in quality of life at baseline and significantly higher rates of healthcare utilisation during longitudinal follow-up
Dissecting the Polycrisis, Charting the Conceptual Terrain of Enquiry
Get PDF‘Polycrisis’ is generally defined as a cluster of distinct, yet interrelated crises which reinforce each other. There is, however, little consensus on its constituent parts. Helleiner, when assessing economic globalization’s polycrisis, includes the US-Chinese trade war, a global health crisis around Covid-19, an international security crisis due to the Ukraine war, an environmental crisis and a crisis of democracy. Re the EU, Nicoli and Zeitlin identify a first polycrisis around the sovereign debt crisis (2009–2016) and the migration crisis (2015–2016) and a second polycrisis brought about by the Covid-19 pandemic (2020–2021) and the Ukraine war (since 2022). They say little, however, about the importance of either or their interrelations.In this paper, I explore how we can distinguish between fundamental crises on one hand, and crises, which are simply the concrete manifestations of those deeper, structural crises on the other. Through a Marxist focus on the historical specificity of capitalism and its interrelations with patriarchy, racism and the relentless expansion into nature, I argue that we can identify four structural crises, i.e., the crises of global capitalism, global gender relations, global race relations and global ecology, all internally related and reinforcing each other
Exploring Stakeholder Acceptance of Workplace Personalization
Get PDFPersonalization in the workplace may be used to support workers by simplifying tasks or reducing workload, but requires the collection of personal data, and this raises concerns over privacy and possible discrimination if applied indiscriminately. The study explored the factors associated with acceptance of three types of workplace personalization system (Suggester, Swappers and Controller, within-subjects) and two personal data types (Heart Rate, Performance, between-subjects) by presenting vignettes using an online experimental platform (Prolific.com) and capturing respondents' (n = 204) attitudes using recognized acceptance questionnaires (e.g., the Advanced Transport Telematics Acceptance Assessment, [ATTAA]). Results show acceptance is influenced by the type of personalization system, particularly when physiological (heart rate) data is used, with “Swapper” systems receiving the highest ratings for “Usefulness” and “Satisfying” (interpreted as higher acceptance) compared to suggesters and controllers. Acceptance ratings were not significantly different between personalization types when performance data were used. The Affinity for Technology (AFT) and Need for Cognition (NFC) scales were used to categorize participant characteristics, but only revealed significant differences associated with NFC and usefulness—most notably when using performance data. Overall, the results support the need to consider the type of intervention and the type/amount of personal data required when designing and implementing workplace personalization systems and highlight a particular need for caution when physiological data is required
Elaborating the Motivations and Attitudes Driving Interest in Voluntary Biodiversity Credits
Get PDFGlobal biodiversity loss has prompted the search for new sources of conservation finance, such as voluntary biodiversity credits (VBCs). However, despite optimistic market projections, current uptake of VBCs is limited. Adopting an interpretive approach, we analyse 21 semistructured interviews with early market actors (buyers, sellers, intermediaries) in the United Kingdom to elaborate the motivations and attitudes fuelling interest in VBCs. Specifically, our findings show the drivers (including economic, environmental, socio-cultural) and barriers (including financial, reputational, methodological, capacity and policy) that are shaping the nascent market for VBCs. Our study has implications for theorising a changing interpretive domain in which biodiversity loss is becoming more central to strategy. We also offer practical implications from our findings on factors affecting market development
Correlation between heat exposure and perinatal depression - A spatial case-crossover study from Bangladesh, Lesotho, Mozambique, and Nepal
Get PDFThis study explores the correlation between heat exposure and perinatal depression in four low- and middle-income countries using a spatial, time-stratified case-crossover study. Cluster-level mental health data from the Demographic and Health Surveys (DHS) of Bangladesh, Lesotho, Mozambique, and Nepal was utilized. Availability of complete data on Patient Health Questionnaire 9 (PHQ-9) was an inclusion criterion. Heat exposure data was provided by the National Aeronautics and Space Administration (NASA). Spatial alignment between DHS clusters and meteorological points was achieved using bilinear interpolation. Heat exposure was defined as the daily maximum temperature exceeding the country-specific 50th percentile.This study included 1836 perinatal women with depression. The pooled prevalence of perinatal depression was 27% (range: 19%–31%). Using distributed lag non-linear model (DLNM), in Bangladesh, lower maximum ambient temperatures (25th-centile) had 5.34 (4.28, 6.66) times higher cumulative odds for perinatal depression compared to the median temperature. In Lesotho, Mozambique, and Nepal, exposure to higher maximum ambient temperature (75th centile) had cumulative higher odds of 1.19 (0.98, 1.43), 2.51 (1.96, 3.20), and 9.41 (4.88, 18.1), respectively, in comparison to the median temperatures.The results suggest that heat exposure is correlated with perinatal depression, undermining the need for intersectoral responses that address environmental and healthcare system factors
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