Search Results (696)

The decarbonization of shipping and shipbuilding is a critical challenge under the Inter-national Maritime Organization’s (IMO) 2030 greenhouse gas (GHG) reduction target and 2050 net-zero strategy, requiring effective coordination between policy and technology. This study investigates how Japan, China, and Korea respond to these regulatory pressures by systematically analyzing their policy–technology linkages. A four-stage design was applied, combining qualitative case studies, policy–technology mapping, theoretical interpretation, and comparative analysis, to trace how national strategies shape eco-friendly transitions. Japan employs an innovation-led, institution-convergent model in which technological demonstrations drive institutional adaptation and diffusion, China follows a policy-designated, execution-oriented model where state-led interventions accelerate commercialization, and Korea adopts a coordination-based, cyclical model balancing public demonstrations, financial support, and international standardization to reduce transition costs. These findings demonstrate that sequencing between policy–technology linkage is context-dependent, shaped by technological maturity, economic feasibility and infrastructure, institutional predictability, and socio-environmental acceptance. The study contributes a cyclic co-evolutionary perspective that moves beyond technological or institutional determinism, reconceptualizes regulation as enabling infra-structure, and identifies implications for global standard-setting and industrial competitiveness. The insights inform practical strategies for major shipbuilding nations to reduce costs while sustaining competitiveness under the IMO’s decarbonization framework. Full article

Yellow rust (YR), caused by Puccinia striiformis f. sp. tritici (Pst), is a global disease infecting wheat that seriously affects the yield and the quality of grains. Wheat breeding line C855 is immune to the mixed Pst isolates CYR32 + CYR33 + CYR34 under field conditions. To identify the Yr-loci carried by C855, in this study, an F₂ population derived from the crossing of C855 with Yannong 999, a YR-sensitive cultivar, was established, and the infection type (IT) of each F₂ individual was estimated. The correlation analysis results show that YR resistance was significantly positively correlated with grain weight and grain size. Using a 120K single-nucleotide polymorphism (SNP) array, the F₂ population was genotyped, and a high-density genetic map covering 21 wheat chromosomes and consisting of 5362 SNP markers was built. Then, five Yr-QTLs on chromosomes 1B, 2A, 2B, and 2D were identified. Of these, the QTL on chromosome 2A, temporarily named QYr.sxau-2A.1, is a major-effect QTL explaining 15.62% of the phenotypic variance. One PCR-based marker SSR2A-14 for QYr.sxau-2A.1 was developed, and the C855 allele of SSR2A-14 corresponded to the stronger Yr resistance. QYr.sxau-2A.1, located in the 228.02~241.58 Mbp physical interval, is different from all the known Yr loci on chromosomes 2A. Within the interval, there are 30 annotated genes, including a nucleotide-binding site and a leucine-rich repeat (NBS-LRR)-encoding gene with the linkage marker NRM2A-16 of QYr.sxau-2A.1. Our results reveal a novel major-effect QYr.sxau-2A.1, which provided resistance to YR and is a molecular marker for wheat breeding. Full article

Extreme weather increasingly damages forest ecosystems, and affected areas are often remote or inaccessible, limiting field surveys. In such contexts, remote sensing can complement damage assessment. This study presents a regional case study evaluating established multi-temporal optical change detection for windthrow mapping in Triglav National Park (Slovenia) using Sentinel-2 and PlanetScope imagery. Bitemporal index differencing and fixed thresholds were applied, with accuracy quantified via a block bootstrap to account for spatial autocorrelation. Within-sample overall accuracy was 69.2% (95% CI: 67.4–71.2%) for Sentinel-2 and 72.9% (95% CI: 71.2–74.6%) for PlanetScope. Detection was strongly size-dependent: gaps greater than 0.5 ha were consistently detected, whereas gaps smaller than 0.1 ha were frequently omitted, particularly with Sentinel-2. Linking satellite-derived change maps with forest stand data enabled parcel-level estimates of damaged timber volume; this linkage was examined on a small, non-probability set of parcels and is therefore preliminary. We position the work strictly as a case study documenting within-sample performance in alpine terrain. Broader generalisation will require probability-based validation across additional events and forest types, and wider access to parcel-level official records. Full article

Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather forecasting accuracy and supports climate change research. China has complex topography and significant spatiotemporal variability in its circulation patterns, making the study of circulation type classification in this region highly significant. This study aims to evaluate the applicability of several mainstream objective CTC methods in the China region. We applied methods including T-mode principal component analysis (PCT), Ward linkage, K-means, and Self-Organizing Maps (SOM) to classify the sea-level pressure daily mean fields from 1993 to 2023 in the study area, and compared the classification results in terms of internal metrics, continuity, seasonal variation, separability of related meteorological variables (e.g., temperature, precipitation), and stability to spatiotemporal resolution. The results show that each method has its advantages in different contexts, with the K-means method showing the best overall performance. Additionally, an optimized approach combining PCT and K-means is proposed. Full article

Soil organic carbon (SOC) plays a critical role in the global carbon cycle and serves as a sensitive indicator of climate change impacts, with its dynamics significantly influencing regional ecological security and sustainable development. This study focuses on the Songnen Plain in Northeast China—a key black soil agricultural region increasingly affected by water erosion, primarily through surface runoff and rill formation on gently sloping cultivated land. We aim to investigate the spatiotemporal dynamics of SOC stocks across different cultivated land erosion zones under projected future climate change scenarios. To quantify current and future SOC stocks, we applied a boosted regression tree (BRT) model based on 130 topsoil samples (0–30 cm) and eight environmental variables representing topographic and climatic conditions. The model demonstrated strong predictive performance through 10-fold cross-validation, yielding high R² and Lin’s concordance correlation coefficient (LCCC) values, as well as low mean absolute error (MAE) and root mean square error (RMSE). Key drivers of SOC stock spatial variation were identified as mean annual temperature, elevation, and slope aspect. Using a space-for-time substitution approach, we projected SOC stocks under the SSP245 and SSP585 climate scenarios for the 2050s and 2090s. Results indicate a decline of 177.66 Tg C (SSP245) and 186.44 Tg C (SSP585) by the 2050s relative to 2023 levels. By the 2090s, SOC losses under SSP245 and SSP585 are projected to reach 2.84% and 1.41%, respectively, highlighting divergent carbon dynamics under varying emission pathways. Spatially, SOC stocks were predominantly located in areas of slight (67%) and light (22%) water erosion, underscoring the linkage between erosion intensity and carbon distribution. This study underscores the importance of incorporating both climate and anthropogenic influences in SOC assessments. The resulting high-resolution SOC distribution map provides a scientific basis for targeted ecological restoration, black soil conservation, and sustainable land management in the Songnen Plain, thereby supporting regional climate resilience and China’s “dual carbon” goals. These insights also contribute to global efforts in enhancing soil carbon sequestration and achieving carbon neutrality goals. Full article

An ethyl acetate extract from the deep-sea bacterium Galbibacter orientalis strain ROD011 (GOEE), collected from international waters, was investigated as a potential anti-inflammatory agent. In lipopolysaccharide (LPS)-stimulated murine macrophages, nitric oxide (NO) production fell by 72–87% at 5–20 µg/mL GOEE without detectable cytotoxicity. Cyclooxygenase-2 (COX-2 protein abundance decreased in a dose-dependent manner and was nearly absent at 20 µg/mL. In zebrafish embryos, survival was maintained up to 40 µg/mL, and LPS-induced signals were attenuated; the cell-death rate declined from 10 µg/mL onward, and at 20 µg/mL GOEE, reactive oxygen species (ROS) and NO decreased by 85% and 27%, respectively. To explain these effects, untargeted metabolomics with pathway enrichment and network mapping were performed in LPS-driven macrophages. Of the 58 KEGG pathways evaluated, 18 reached significance, notably purine and pyrimidine metabolism, vitamin B6 metabolism, and the one-carbon pool via folate. Coordinated shifts also involved amino-acid/tricarboxylic acid (TCA)-cycle linkages, glutathione and glyoxylate/dicarboxylate, and sphingolipid pathways. Network analysis identified hubs that were concomitantly reprogrammed. Collectively, GOEE achieved multi-level suppression of inflammatory outputs while preserving viability, and the metabolomic signature provides a mechanistic scaffold for its action. These findings nominate a deep-sea microbial extract as a promising anti-inflammatory lead and motivate fractionation and targeted validation of the highlighted metabolic nodes. Full article

The increasing construction-driven growth in urbanization requires innovative and holistic design approaches for sustainable housing. This study examines the relationship between Minimalist Design Principles (MDPs) and the UN SDGs and develops a multi-stage decision-support model to operationalize these links. The research adopts a five-stage mixed-methods design. It includes content analysis based on a systematic literature review, conceptual mapping, a two-round Delphi method (N = 56), Fuzzy AHP for criteria weighting, and SEM for model validation. A total of 13 MDPs were mapped against 17 SDGs and 169 subtargets, revealing particularly strong linkages with SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production). The SEM results confirm the structural validity of the proposed model. Among the minimalist principles, those associated with “resource, material, and process simplification” and “user needs, functional flexibility, and quality of life” emerged as the most influential factors for the SDGs. This study proposes a measurable, multidimensional decision-support model in sustainable architecture that clarifies how MDPs influence the SDGs. Full article

Commercial computer-aided design (CAD) software is often expensive. This paper examines the use of product manufacturing information (PMI) web visualization to address the challenges faced by production site personnel and external partners collaborating on product development. These individuals need to be able to view or query PMI in model-based definition models without having to install professional CAD software. A detailed analysis of the relationships between PMI entity attributes in standard for the exchange of product model data (STEP) AP242 files was conducted. An algorithm for the automatic parsing and mapping of PMI semantics to a web browser is presented. Using linear sizes as an example, this paper introduces a prototype system with the following features: PMI web visualization; automatic linkage of PMI to associated geometry; browser-native rendering without the need for dedicated applications; and integration of graphical presentation and semantic representation. The effectiveness and feasibility of the prototype system are validated through case studies. However, the system has limitations when handling large assemblies with compound tolerances, curved dimension placements, and overlapping annotations, which presents areas for future research. Full article

Leaf rust, a devastating fungal disease caused by Puccinia triticina (Pt), severely impacts wheat quality and yield. Identifying genetic loci for wheat leaf rust resistance, developing molecular markers, and breeding resistant varieties is the most environmentally friendly and economical strategy for disease control. This study utilized a recombinant inbred line (RIL) population of Doumai and Shi4185, combined with the wheat 90 K single nucleotide polymorphisms (SNPs) chip data and maximum disease severity (MDS) of leaf rust from four environments, to identify adult plant resistance (APR) loci through linkage mapping. Additionally, kompetitive allele-specific PCR (KASP) markers suitable for breeding were developed, and genetic effects were validated in a natural population. In this study, 5 quantitative trait loci (QTL) on chromosomes 1B (2), 2A and 7B (2) were identified through inclusive composite interval mapping, and named as QLr.lfnu-1BL1, QLr.lfnu-1BL2, QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2, respectively, explaining 4.54–8.91% of the phenotypic variances. The resistance alleles of QLr.lfnu-1BL1 and QLr.lfnu-1BL2 originated from Doumai, while the resistance alleles of QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 came from Shi4185. Among these, QLr.lfnu-1BL2, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 overlapped with previously reported loci, whereas QLr.lfnu-1BL1 and QLr.lfnu-2AL are likely to be novel. Two KASP markers, QLr.lfnu-2AL and QLr.lfnu-7BL, were significantly associated with leaf rust resistance in a diverse panel of 150 wheat varieties mainly from China. Totally, 34 potential candidate genes encoded the NLR proteins, receptor-like kinases, signaling kinases and transcription factors were selected as candidate genes for the resistance loci. These findings will provide stable QTL, available breeding KASP markers and candidate genes, and will accelerate the progresses of wheat leaf rust resistance improvement through marker-assisted selection breeding. Full article

Microwave pretreatment (MWP) has emerged as a promising strategy to enhance the pyrolysis of lignocellulosic biomass due to its rapid, volumetric, and selective heating. By disrupting the recalcitrant structure of cellulose, hemicellulose, and lignin, MWP improves biomass deconstruction, increases carbohydrate accessibility, and enhances yields of bio-oil, syngas, and biochar. When combined with complementary pretreatments—such as alkali, acid, hydrothermal, ultrasonic, or ionic-liquid methods—MWP further reduces activation energies, facilitating more efficient saccharification and thermal conversion. This review systematically evaluates scientific progress in this field through bibliometric analysis, mapping research trends, evolution, and collaborative networks. Key research questions are addressed regarding the technical advantages of MWP, the physicochemical transformations induced in biomass, and associated environmental benefits. Findings indicate that microwave irradiation promotes hemicellulose depolymerization, reduces cellulose crystallinity, and weakens lignin–carbohydrate linkages, which facilitates subsequent thermal decomposition and contributes to improved pyrolysis efficiency and product quality. From an environmental perspective, MWP contributes to energy savings, mitigates greenhouse gas emissions, and supports the integration of renewable electricity in biomass conversion. Full article

Background: Colorectal cancer (CRC) is significantly associated with multiple metabolic diseases, with plasma metabolites potentially mediating this relationship. This large-scale metabolomics study aims to (1) quantify the genetic correlations and causal effects between 10 metabolic disease-related phenotypes and CRC risk; (2) identify the plasma metabolites mediating these effects; and (3) explore downstream regulatory genes and druggable targets. Methods: Using linkage disequilibrium score regression and two-sample Mendelian randomization, we assessed the causal relationships between each metabolic trait and CRC. A total of 1091 plasma metabolites and 309 metabolite ratios were identified and analyzed for mediating effects by a two-step MR approach. Colocalization analyses evaluated shared genetic loci. The findings were validated in the UK Biobank for metabolite-trait associations. The expression of candidate genes was explored using data from TCGA, GTEx, and GEO. A FADS1-centered protein–protein interaction (PPI) network was constructed via STRING. Results: BMI, waist circumference, basal metabolic rate, insulin resistance and metabolic syndrome exhibited both genetic correlation and causal effects on CRC. Five plasma metabolites—mannonate, the glucose/mannose ratio, plasma free asparagine, 1-linolenoyl-2-linolenoyl-GPC (18:2/18:3), and the mannose/trans-4-hydroxyproline ratio—were identified as shared central mediators. A colocalization analysis showed rs174546 linked CRC and 1-linolenoyl-2-linoleoyl-GPC. Validation in the UK Biobank confirmed the associations between phosphatidylcholine (the lipid class of this metabolite), adiposity measures, and CRC risk. An integrative analysis of TCGA, GTEx, and GEO revealed consistent upregulation of FADS1/2/3 and FEN1 in CRC, with high FADS1 expression predicting a poorer prognosis and showing the distinct cell-type expression in adipose and colon tissue. The PPI network mapping uncovered nine FADS1 interacting proteins targeted by supplements such as α-linolenic acid and eicosapentaenoic acid. Conclusions: This study systematically reveals, for the first time, the shared intermediary plasma metabolites and their regulatory genes in the causal pathway from metabolic diseases to CRC. These findings provide candidate targets for subsequent functional validation and biomarker development. Full article

Coastal ecosystems sustain biodiversity, food resources, and human livelihoods, yet are increasingly exposed to climate change, pollution, and anthropogenic stressors. These pressures affect not only ecosystem integrity but also human health, highlighting the urgency of adopting the One Health framework. While One Health has gained global prominence, its systematic application in coastal and marine governance remains limited. This study provides the first bibliometric review of One Health research in coastal and marine contexts, analyzing 154 publications from Scopus (2003–2025) using Bibliometrix under PRISMA-S guidelines. Scientific output was minimal until 2015 but accelerated after 2020, peaking at 37 publications in 2024. Less than 20% of studies explicitly integrated all three One Health dimensions. Research has largely centered on environmental monitoring and aquaculture health, with antimicrobial resistance, climate–health linkages, and integrated coastal indicators underexplored. Keyword mapping revealed two distinct yet connected clusters: a biomedical cluster emphasizing antibiotics, resistance, and microbiology, and an environmental cluster focusing on pollution, ecosystems, and zoonotic risks. Outputs are geographically concentrated in high-income countries, particularly the USA, Brazil, and the UK, while contributions from low- and middle-income coastal regions remain scarce. These findings confirm both the rapid growth and the fragmentation of One Health scholarship in coastal contexts. By identifying gaps, trends, and collaboration patterns, this study builds an evidence base for embedding One Health in coastal monitoring, climate adaptation, and governance, advancing multiple United Nations’s Sustainable Development Goals. Full article

Highly Hazardous Pesticides (HHPs) pose severe risks to human health and the environment, making it essential to understand their molecular stability and degradation pathways. In this study, the Quantum Theory of Atoms in Molecules (QTAIM) was applied to four representative organophosphate pesticides, allowing the identification of electronically weak bonds as intrinsic sites of lability. These findings are consistent with reported hydrolytic, oxidative, enzymatic, and microbial degradation routes. Importantly, QTAIM descriptors proved largely insensitive to solvation, confirming their intrinsic character within the molecular electronic structure. To complement QTAIM, conceptual DFT (Density Functional Theory) reactivity indices were analyzed, revealing that solvent effects induce more noticeable variations in global and local descriptors than in topological parameters. In addition, a Topological Analysis of the Fukui Function (TAFF) was performed, which mapped nucleophilic, electrophilic, and radical susceptibilities directly onto QTAIM basins. The TAFF analysis confirmed that bonds identified as weak by QTAIM (notably P–O, P–S, and P–N linkages) also coincide with the most reactive sites, thereby reinforcing their mechanistic role in degradation pathways. This integrated framework highlights the robustness of QTAIM, the sensitivity of global and local reactivity descriptors to solvation revealed by conceptual DFT, and the complementary insights provided by TAFF, contributing to risk assessment, remediation strategies, and the rational design of safer pesticides. Full article

Analysis of selection signatures in the genomes of farm animals enables the detection of genomic regions affected by selection and contributes to the identification of genes underlying adaptive and productive traits. This research aimed to identify loci under selection pressure and to detect candidate genes in Dzhalgin Merino sheep by performing a comparative genomic analysis with the related Australian Merino and Rambouillet breeds. A total of 293 animals were included in the analysis, comprising Dzhalgin Merino (n = 53), Australian Merino (n = 50), Australian Industry Merino (n = 88), and Rambouillet (n = 102). Whole-genome SNP genotyping data for Dzhalgin Merino were generated within this study, while data for Australian Merino, Australian Industry Merino, and Rambouillet were obtained from the SheepHapMap project. For the purposes of analysis, Australian Merino and Australian Industry Merino were combined into a single group (n = 138). To enhance the reliability of the results, three independent methods were employed to detect selection signatures: the fixation index (FST), analysis of linkage disequilibrium variation (varLD), and the cross-population number of segregating sites by length (xp-nSL). The study showed that Dzhalgin Merino have unique genetic signatures potentially associated with adaptation and productivity, which opens up new opportunities for their selection. The identified genes can become the basis for developing new breeding programs aimed at improving both the productive qualities and the adaptive abilities of the breed. Further research should be aimed at a detailed investigation of gene structure within loci under selection pressure and at clarifying the mechanisms by which these genes influence animal phenotypes. A total of 185 genes were identified within genomic regions exhibiting selection signatures. Among these, particular attention was given to EPHA6, MLLT3, ROBO1, KIAA0753, MED31, SLC13A5, and ELAVL4, which are involved in biological processes such as growth, development, and reproduction. The identified genes represent potential targets for breeding programs aimed at increasing productivity and adaptive capacity of the breed. Full article

Drought severely threatens wheat production. Under drought conditions, root system architecture (DRSA)-related traits in common wheat significantly affect wheat production. In China, Zhoumai16 is a high-yield winter wheat variety in the Huang-Huai wheat region. It is suitable for high-fertilizer and high-water cultivation and has moderate drought tolerance. DK171 is a newly developed high-yield and stress-tolerant variety, with higher drought tolerance. Thus, identifying genetic loci associated with DRSA-related traits from DK171 and developing available molecular markers are of great importance for enhancing wheat stress tolerance breeding. In this study, DRSA-related traits, including the total root dry weight (DDRW), total root length (DTRL), total root area (DTRA), and the number of root tips (DNRT) under drought stress, were assessed using the hydroponic system in Zhoumai16/DK171 recombinant inbred lines (RIL) population. A total of five quantitative trait loci (QTL) for DRSA-related traits were identified, e.g., QDDRW.daas-1BL, QDTRS.daas-4AL, QDNRT.daas-4DS, QDTRL.daas-3AL, and QDDRW.daas-5D, and explained 6.1% to 18.9% of the phenotypic variances, respectively. Among these, QDTRS.daas-4AL and QDTRL.daas-3AL were consistent with previous reports, whereas the QDDRW.daas-1BL, QDNRT.daas-4DS, and QDDRW.daas-5D are novel. The favorable alleles of QDTRS.daas-4AL and QDNRT.daas-4DS were inherited from Zhoumai16, whereas the favorable alleles for QDDRW.daas-1BL, QDTRL.daas-3AL, and QDDRW.daas-5D were contributed by DK171. Furthermore, five kompetitive allele-specific PCR (KASP) markers, Kasp_1BL_DTRS (QDDRW.daas-1BL), Kasp_3AL_DTRS (QDTRL.daas-3AL), Kasp_4A_DTRS (QDTRA.daas-4A), Kasp_5D_DDRW (QDDRW.daas-5D), and Kasp_4D_DNRT (QDNRT.daas-4D), were developed and validated in a diverse panel with 108 wheat varieties mainly from China. Additionally, eight candidate genes related to plant hormone regulation, ABC transporters, and calcium-dependent lipid-binding domain proteins were identified. This study offers new loci, candidate genes, and available KASP markers for wheat drought tolerance breeding and facilitating progress in developing drought-tolerant wheat cultivars. Full article