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Bidirectional catalysts with dual-atom dynamic d-band centre modulation and support self-reconstruction for de/hydrogenation in MgH2/Mg
Hidden Markov models reveal ontogenetic plasticity in green and loggerhead sea turtles
FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis
Abstract Spatial transcriptomics (ST) has emerged as a powerful tool for analyzing cell-cell communication (CCC) across various biological processes, ranging from embryonic development to cancer progression. However, its limited resolution and high data sparsity hinder the detailed characterization of CCC patterns within complex tissues. Here, we introduce FineST , a deep contrastive learning model that leverages a histology foundation model to fuse ST and histology images, enabling Fine -grained S patial T ranscriptomics analysis. This approach facilitates precise nuclei segmentation, high-resolution RNA expression imputation, and the identification of intricate ligand-receptor interactions. Using both colorectal cancer VisiumHD and breast cancer Xenium datasets, we demonstrate that FineST significantly outperforms existing methods in high-resolution RNA imputation, cell type prediction, and CCC pattern discovery. With focused application to the Visium platform, FineST reveals novel biological insights into tumor-immune interactions across multiple cancer types, including invasive fronts in breast cancer, tertiary lymphoid structures in nasopharyngeal carcinoma, and PD-1 therapy resistance barriers in hepatocellular carcinoma. These findings highlight a new paradigm in ST analysis through the integration of readily available histology images.
Phase-dependent modulation of the MJO during cross-equatorial northerly surges (CENS)
Structured coherent thermal emission from non-Hermitian metasurfaces
Delayed goal-directed processing underlies inhibitory control challenges in adult ADHD
Coupled polarization dynamics and charge tunneling enable reconfigurable heterojunctions
Establishment of a rapid Brucella detection method based on MCDA-CRISPR dual signal amplification system for reducing transfusion-transmitted diseases
Synchronous activation of striatal cholinergic interneurons induces local serotonin release
Comparative effects of surface and underwater lighting methods on coastal fishery resources in Terengganu
Geo-spatial prospective life cycle sustainability of InGaN and InGaP compound semiconductors
Abstract This is the first study which presents integrated geo-spatial prospective life cycle and supply chain sustainability modelling of two compound semiconductors: Indium Gallium Nitride (InGaN) and Indium Gallium Phosphide (InGaP), in 80 international supply chain scenarios, incorporating 11 countries across 4-time horizons—024, 2030, 2040 and 2050. The results show environmental sustainability is geographic- and time- dependent and varied by properties of the supply chain characteristics. The manufacturing of InGaN and InGaP excel in UK based scenarios (~ 70% and 66% impact reduction from 2040 to 2050). Scenarios involving shared fabrication in the UK and US show strong sustainability performance in 2024, those for fabrication in Taiwan (for both materials) and US (InGaN) demonstrate increasing sustainability potential by 2050. Scenarios involving fabrication in China consistently led to a higher environmental impact. However, all 80 configurations demonstrate marked reductions in environmental impacts, primarily due to global electricity grid decarbonisation, and improved emissions controls. Despite this improvement in the clean room energy impact, epitaxial growth and substrate preparation remain the hotspots, calling for process innovation, cleaner precursors (e.g., replacing arsine or phosphine), and advanced material recycling. InGaN generally performs better than InGaP in most categories, attributed to its simpler material inputs and lower toxicity potential. InGaP scenarios exhibit higher marine ecotoxicity, carcinogenic toxicity, and mineral resource scarcity, driven by complex chemistries and Gallium Arsenide (GaAs) substrates. Interestingly, InGaP scenarios significantly outperform InGaN in stratospheric ozone depletion due to limited use of halogenated chemicals. This study provides compelling evidence to support reshoring or nearshoring of compound semiconductor fabrication to regions with cleaner energy profiles and stronger environmental regulations. Scenarios involving the UK, USA and Taiwan (specially in 2050), consistently achieve higher sustainability scores across global warming, toxicity, and resource depletion categories.
Growth, productivity and profitability of potato (Solanum tuberosum L.) as influenced by nitrogen fertilizer and intra-row spacing in Ethiopia highlands
Abstract Nitrogen fertilizer and intra-row spacing are critical agronomic practices influencing potato (Solanum tuberosum L.) production. In Ethiopia, smallholder farmers often apply nitrogen and manage plant spacing without evidence-based guidelines, resulting in low productivity. A field experiment was conducted during the 2023 main rain fall season on a farmer’s field in the Ethiopian highlands to assess the growth and seed tuber yield of the potato variety ‘Belete’ under different nitrogen rates and intra-row spacings. The study evaluated four nitrogen levels (0, 55, 110, and 165 kg N ha⁻¹) and three intra-row spacings (20, 30, and 40 cm) in a factorial randomized complete block design with three replications. Interaction effects of nitrogen and spacing significantly affected days to 50% flowering, stem number, yields of very small, small, and large-sized tubers, average tuber weight, marketable yield, and total tuber yield. The highest marketable tuber yield (41.38 t ha⁻¹) was recorded with 110 kg N ha⁻¹ and 20 cm spacing. However, partial budget analysis revealed that the combination of 110 kg N ha⁻¹ and 30 cm spacing provided the highest net benefit (236,614 ETB ha⁻¹) and marginal rate of return (12,692.11%). These results underscore the need to optimize nitrogen application and plant spacing for enhanced seed tuber productivity and economic returns. Therefore, applying 110 kg N ha⁻¹ with 30 cm intra-row spacing is recommended for profitable potato production, improving income and food security for smallholder farmers in the study area and similar agro-ecologies.
Aerial image segmentation using multilevel thresholding based on multi strategy Osprey optimization algorithm
A do-it-yourself water quality sensor network to elucidate contaminant signatures and improve land management advice
Abstract Quantifying contaminant loads to estuaries is essential for setting effective limits on resource use and safeguarding ecological values. Traditional monitoring programmes often rely on infrequent sampling, which can substantially underestimate loads and obscure key transport processes. While commercial high-frequency sampling stations are prohibitively expensive, open-source, do-it-yourself technologies now offer affordable alternatives for continuous monitoring. Here, we deployed ten low-cost, in situ monitoring stations equipped with research-grade sensors across an intensively farmed catchment draining to a sensitive estuarine environment in the Bay of Plenty, New Zealand. Using artificial neural network models trained on concurrent grab samples, we converted sensor measurements into reliable 15-min estimates of contaminant concentrations. High-frequency load calculations revealed nitrogen, phosphorus, and sediment exports to be 6–87% greater than estimates derived from traditional monthly sampling. Moreover, time-series outputs uncovered distinct sub-catchment contaminant mobilisation and transport dynamics that would otherwise remain undetected. These findings demonstrate that open-source, high-frequency monitoring can substantially improve contaminant load quantification, provide new insights into catchment processes, and inform the development of land management and policy strategies that reflect the unique spatio-temporal patterns of contaminant export.
Rhizospheric glycosyltransferase repertoires as a resource for enabling sustainable bioprocessing and green biocatalyst discovery
Hybrid dimension reduction and logit models for glare-induced crash severity
The impact of employees’ constrictive deviance on job performance: The roles of ethical conflict and moral identity
Systematic modeling of porphyrin-based photosensitizers for inhibiting Mycobacterium tuberculosis β-Carbonic Anhydrases
Intraspecific interactions in spring-staging geese reflect mate guarding and proximity to nesting dates
Abstract Wild geese form large flocks, benefiting from shared vigilance against predators which increases feeding time. As spring progresses, males invest more in mate-guarding to protect paternity, so we hypothesised that intraspecific aggression would rise with flock size and proximity to first egg dates. We tested this using field observations of four goose species staging in northeast Poland, February–April: one local breeder (nesting in March) and three Arctic-nesting species (laying from late May). Of 662 observed aggressive episodes, 643 (97%) were intraspecific, and aggression in all species increased with flock size. Locally breeding Greylag Geese Anser anser and Arctic-nesting Barnacle Geese Branta leucopsis showed consistently high probabilities of aggression (60–80%) throughout, although Barnacle sample sizes were too small for firm conclusions. The other two Arctic-nesting species (Greater White-fronted Anser albifrons and Tundra Bean Goose A. serrirostris ) showed aggression rising initially from zero to similarly high levels in the three weeks before departure for nesting areas. No differences were found between geese feeding on grassland versus arable fields (which offered higher food intake). We conclude that the predominance of intraspecific aggression is consistent with increasing mate-guarding (and related close-range social defence) as spring progresses relative to species-specific nesting schedules, and is unlikely to be driven primarily by interspecific competition for food or other types of interactions.