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Body-Part Enabled Wildlife Detection and Tracking in Video Sequences
Get PDFTracking wild animals through videos presents a non-intrusive and cost-effective way of gathering scientific information key for conservation. State-of-the-art research has shown convolutional neural networks to be highly accurate, however, the application of this field on wild animal tracking has had relatively little interest. This is potentially due to the challenges of varying illumination, noisy backgrounds and camouflaged animals intrinsic to the problem. The aim of this work is to explore and apply state-of-the-art research to detect and track wild animals (specifically bears and primates, including their body parts) in video sequences in real-time. Due to obstructors such as foliage being prevalent in wild animal environments, body part tracking presents a solution to detecting animals when they are obstructed. Two deep convolutional neural networks (YOLOv4 and YOLOv4-Tiny) are trained to detect and track animals in their natural habitat. By using the knowledge that an animal is composed of body parts, the score of weakly predicted bounding is boosted from the relative distance of related body parts. For tracking, the K-Means algorithm is used to locate the average position of each animal in frame. With the introduction of a body-part confidence boosting, the detection rate can be increased by approximately 2% for a weakly predicted class
Eco-inspired synthesis of silver nanoparticles from Prunus avium stems: Mechanistic insights into multifunctional biomedical activities
Get PDFSilver nanoparticles (AgNPs) fabricated via green approaches have emerged as attractive candidates for multifunctional biomedical applications. In the present work, an environmentally benign method was employed to synthesize AgNPs using Prunus avium L. stem extract (AgNPs@PAS), followed by detailed physicochemical characterization with different techniques. Structural analyses verified the formation of predominantly spherical AgNPs@PAS with particle sizes mainly ranging from 10 to 35 nm, while FT-IR spectra confirmed the presence of phytochemical compounds acting as surface-capping agents. Biological investigations revealed broad-spectrum antibacterial properties, with the highest efficacy observed against Escherichia coli (MBC= 140 μg/mL), as well as considerable antifungal activity against Candida albicans (MIC= 17.5 μg/mL). The synthesized AgNPs@PAS also displayed strong antioxidant performance, achieving 93 % DPPH radical scavenging at a concentration of 140 μg/mL. Furthermore, in vivo burn wound experiments illustrated a significant enhancement in wound closure following treatment with AgNPs@PAS. Cytotoxicity assessment indicated notable anticancer property on the MCF-7 breast cancer cell line, with an IC50 value of 78.8 μg/mL. Collectively, these results suggest that AgNPs@PAS represent a promising multifunctional nanoplatform for biomedical applications, particularly in burn wound healing
Achieving safely managed services and climate mitigation in the sanitation sector in Indonesia: Key findings and recommendations from the EMISI project
No full textFine-grained urban land use simulation: Integrating spatial dynamic modeling with a pre-trained vision-language model
Get PDFAccurate prediction of urban land use changes at fine spatial scales is essential for developing healthy and sustainable cities, yet traditional simulation models struggle to capture local dynamics due to limited availability of fine-grained data and insufficient complexity in modeling urban systems. To address these limitations, we propose a novel approach that leverages advances in pre-trained vision-language foundation models combined with spatial dynamic modeling to forecast detailed urban land use patterns. Specifically, we collected a spatially dense collection of street view images (SVIs) throughout Shenzhen, China, and applied UrbanCLIP, a specialized vision-language prompting framework, to perform zero-shot inference of urban land use directly from images without labeled datasets and model retraining. The resulting fine-grained classifications delineate eight distinct urban land use types, producing a detailed urban functional map. These high-resolution patterns were then integrated into a spatial dynamic model enhanced by polynomial regression to simulate urban evolution toward 2035. This approach effectively captures neighborhood influences, socioeconomic drivers, and urban planning policies. Our simulation provides actionable insights for sustainable development in Shenzhen by identifying areas for balanced growth, targeted infrastructure investments, and ecological preservation. Compared to conventional methods, our methodology significantly improves predictive accuracy and spatial granularity. By incorporating foundation models, our approach addresses traditional data constraints, offering scalable and robust tools for informed urban governance and decision-making
Obesogens in prostate cancer: an endocrine and metabolic threat
Get PDFPurpose of Review
This review addresses the contribution of obesogenic endocrine-disrupting chemicals (EDCs) to prostate carcinogenesis. It provides an in-depth overview of obesogens, tracing their mechanisms of action and effects impacting prostate cell fate. The direct effects of obesogens in disrupting adipose tissue and metabolic homeostasis, as well as disturbing prostate cells, are discussed, along with the potential indirect effects mediated by the dysregulation of the adipose tissue.
Recent Findings
Obesogens represent a group of EDCs that interfere with endocrine and metabolic processes, underpinning the spread of obesity. Moreover, the ubiquitous presence in the environment, the ability to accumulate in adipose tissue and the broad range of effects targeting several biological pathways highlight that obesogens can be detrimental to human health beyond their action on promoting obesity. Prostate cancer (PCa) is a hormone-dependent cancer for which environmental influences and obesity are established risk factors, with emerging evidence suggesting that obesogens may affect its development and progression.
Summary
The available data indicate that obesogens may contribute to the development of PCa. They can have direct actions in prostate cells modulating signalling pathways that drive tumour aggressiveness. Moreover, the adipose tissue dysregulated by obesogens can acquire an obesity-like phenotype, which may play a crucial role in facilitating tumour growth. Further research is needed to clarify the liaison between obesogen-induced dysregulation of the periprostatic adipose tissue depot and PCa aggressiveness. Unravelling this complex crosstalk will be pivotal for identifying novel therapeutic strategies and preventing aggressive PCa, especially in obese patients
Acetyl-phosphate dependent protein acetylation in Neisseria gonorrhoeae.
Get PDFThe disease gonorrhoea is caused by the sexually transmitted pathogen Neisseria gonorrhoeae. This bacterium is an obligate human pathogen that can survive intracellularly through the expression of specific pathogenicity determinants. Protein post-translational modifications have been shown to be involved in the regulation of gene transcription and metabolism. Here, we studied the role of non-enzymatic acetylation by acetyl-phosphate in N. gonorrhoeae. This was achieved through the deletion of pta and ackA genes from the phosphotransacetylase-acetate kinase pathway (PTA-AKA) that modulate the level of acetyl-phosphate in the cell. As predicted, more protein acetylation was observed in the ΔackA strain. Using immunoaffinity purification of acetylated peptides and LC-MS/MS we demonstrated that 88% of the detectable N. gonorrhoeae proteome (1343 proteins) is acetylated. With many of the acetylated proteins involved in central metabolism especially in pyruvate utilisation. Growth studies showed that the ΔackA strain was unable to utilise pyruvate as a carbon source, whereas it could grow on glucose as well as the wild-type. Furthermore, a deacetylase enzyme was identified and its gene mutated (Δhdac), this allowed the identification of a number of putative targets for HDAC, including phosphotransacetylase. We found that gonococcal pathogenicity was changed by acetyl-phosphate concentration, with the ΔackA strain killing the wax moth larvae faster than the wild-type, whereas the Δpta strain was non-pathogenic in this model. The data obtained suggest that non-enzymatic protein acetylation in N. gonorrhoeae plays an important role in the central metabolism, carbon source utilisation, and virulence of this bacterium
Impact of land-use change on ecosystem services in Africa’s Great Green Wall
Get PDFAfrica’s Sahel faces severe land degradation, threatening livelihoods and regional stability. To address this challenge, the Great Green Wall (GGW) initiative aims to restore 100 million hectares of degraded land. Achieving this goal requires an improved understanding of recent land use and land cover (LULC) dynamics and their impacts on ecosystem services. This study quantifies the impacts of land-use transitions between 2007 and 2019 on multiple ecosystem services and identifies spatial trade-offs and synergies to inform restoration planning across the GGW region. We integrated MODIS land-use/land-cover data with geospatial ecosystem service models and applied the Ecosystem Service Contribution Index (ESCI) to quantify the effects of LULC transitions on carbon stock, water yield, soil conservation, sand stabilisation, and grain production. Bivariate Moran’s I was applied to explore associations among services. Land use reconfigured substantially, with grasslands declining and cropland and barren land expanding. Ecosystem service responses were heterogeneous: carbon stock increased in the Ethiopian Highlands and Nigerian agricultural zones, and sand stabilisation improved in parts of Niger and Chad, whereas soil conservation and water yield declined in several arid areas. Grain production rose by 31.1%, but cropland conversion generated trade-offs with wind-erosion control and soil retention. Across climatic gradients, synergies emerged between carbon stock and soil conservation in wetter or highland zones, while trade-offs between provisioning and regulating services dominated in farmed and arid areas. These findings show that LULC in the GGW region is dynamic and variable, with changes enhancing ecosystem services in some areas and compromising them in others. To strengthen ecosystem resilience and support sustainable livelihoods, ecological restoration strategies need to vary in response to local ecological and social conditions
Comparing news beat structures across 13 countries: From geographic to topical and sub-specialised division of labour
Get PDFAlmost 200 years after their inception, news beats became a dominant factor that shapes newsrooms. This study explores the beat mix of leading quality dailies in 13 countries. Findings are based on executive interviews triangulated with other data sources. They indicate a shift from geographic to thematic division of labour and the rising trend of beat sub-specialisation. Newsroom size matters but not linearly: larger newsrooms are not larger across the board. Despite the “interpretive turn”, the iconic figure of the newsroom is still the news reporter, with commentators having a minor share. The studied newsrooms are still based on full timers, with restricted reliance on freelancers and part-timers, mainly in softer news. Gender differences have not disappeared; however, they are smaller and nuanced. These findings suggest that beat systems are responsive to ontological, cultural and environmental changes, while preserving their basic logic of newsmaking at least regarding their core staffs
Navigating GenAI in Psychology Education: Assessment Validity, Academic Integrity, and the Realities of Teaching in an AI-Rich Era
Get PDFThis review examines how psychology educators are responding to the rapid rise of generative artificial intelligence (GenAI), focusing on implications for assessment validity, academic integrity and organisational learning. Although universities have issued policy guidance, these frameworks often overlook psychology's distinctive epistemic, methodological and pedagogical practices. Drawing on empirical research, sector reports, survey findings and my experience as academic integrity lead in a UK university, the review identifies five interconnected challenges: unreliable detection technologies, ambiguity in marking and feedback, threats to the validity of psychology-specific assessments, increasingly complex integrity casework, and limited institutional support. It argues that psychology is well positioned to provide sector-wide leadership because of its emphasis on empirical reasoning, ethical judgement and reflective practice. The article synthesises emerging discipline-sensitive strategies and offers a forward-looking agenda for research, assessment design and staff development, emphasising approaches that foreground reasoning processes, ethical awareness and critical engagement with GenAI. It concludes by calling for a coordinated institutional response that integrates clearer policy, systematic staff training and strengthened communities of practice to support academic integrity and student learning in a GenAI-rich environment
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