Search Results (3,963)

Climate risks are one of the major challenges facing sustainable development. This study examines how physical and transition climate risks influence the volatility and correlation of fossil energy futures and clean energy stock indices, using a mixed-frequency modeling framework. Taking the Paris Agreement as the starting point for the global energy transition, we aim to compare the impacts of climate risks on various fossil energy assets and clean energy assets and investigate how the dynamic linkages between clean energy and fossil energy assets have evolved under the influence of climate risks. The results show that climate risks have increased the volatility of fossil energy and clean energy assets to varying degrees. Correlation patterns vary by energy type: crude oil futures and clean energy indices exhibit a decoupling trend under climate risks, while natural gas futures show a more consistent, positive linkage. These findings not only provide useful guidance for investors in formulating more effective strategies under increasing climate risks but also offer policymakers valuable insights into designing optimal approaches to balance decarbonization objectives with energy security. Full article

Background/Objectives: This study aimed to synthesize a novel, high-molecular-weight acyclic heterocyclic compound, compound 5, via a one-pot reaction between Trichloroisocyanuric acid (TCCA) and ethanolamine, and evaluate its anticancer, antioxidant, and antifungal activities. Methods: Its complex tetrameric structure, assembled through N-N linkages, was unequivocally confirmed by a full suite of spectroscopic techniques including IR, ¹H & ¹³C NMR, ²D-NMR, and high-resolution mass spectrometry (LC/Q-TOF/MS). The MTT assay was used to assess the anticancer activity of compound 5 against four different human cancer cell lines. Results: The findings indicate that human colon (HT29) and ovarian (OVCAR3) cancer cells were sensitive to the treatment, whereas brain (glioblastoma) (T98G) cancer cells were resistant. The most pronounced cytotoxic effect was observed in pancreatic (MiaPaCa2) cancer cells. Notably, compound 5 exhibited potent antifungal properties, achieving 100% inhibition of the pathogenic water mould Saprolegnia parasitica zoospores at 100 µM after 10 min. Molecular docking studies corroborated the biological data, revealing a high binding affinity for key cancer and fungal targets (Thymidylate Synthase and CYP51), providing a strong mechanistic basis for its observed activities. Conclusions: These findings establish compound 5 as a promising dual-action agent with significant potential as both a targeted anticancer lead and an eco-friendly antifungal for applications in aquaculture. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

Transportation networks are critical lifelines in national infrastructure but are increasingly exposed to risks arising from climate variability, cyber threats, aging assets, and limited resources. This paper presents a scoping review of 58 peer-reviewed studies published between 2015 and 2025 that examine the role of Artificial Intelligence (AI) in strengthening infrastructure resilience, with transportation systems adopted as the strategic case. The review classifies applications along five dimensions: technological approach, infrastructure sector, transportation linkage, resilience/security aspect, and key research gaps. Findings show that AI, machine learning (ML), and the Internet of Things (IoT) dominate current applications, particularly in predictive maintenance, intelligent monitoring, early-warning systems, and optimization. These applications extend beyond transport to energy, water, and agri-food systems that indirectly sustain transport resilience. Persistent challenges include affordability, data scarcity, infrastructural limitations, and limited real-world validation, especially in Sub-Saharan African contexts. The paper synthesizes cross-sector pathways through which AI enhances transport resilience and outlines practical implications for policymakers and practitioners. A targeted research agenda is also proposed to address methodological gaps, enhance deployment in resource-constrained settings, and promote hybrid and explainable AI for trust and scalability. Full article

Agriculture and its allied activities contribute to the primary sector in India and act as the basis for the country’s economy. Available agricultural landholdings are scattered as multiple plots across the country. Land fragmentation has led to problems achieving economies of scale and economies of scope; lower productivity, efficiency, and modernization; loss of biodiversity; and little scope for mechanization and technology. FPOs are small clusters of farmers who collaborate to enhance their bargaining strength through collective procurement, processing, and marketing efforts. To enhance the performance of FPOs at the grassroots level, the engagement of cluster-based business organizations (CBBOs) is vital. Millet FPOs are similar to voluntary farmer groups that are involved in the cultivation and promotion of millets. IIMR-promoted millet FPOs were selected purposively for the present study as they are involved in millet cultivation and farming. A total of 450 millet farmers from 15 FPOs and 3 states were randomly chosen for this action research study. The present research identified 10 key factors and collected farmers’ opinions toward member participation in millet FPOs using interpretive structural modeling. The ISM approach provided a clear understanding of how the selected factors interconnect hierarchically with each other as foundational drivers and dependent outcomes. The results from the MICMAC analysis demonstrated that foundational interventions, such as post-harvest technology availability (V2) and knowledge transfer by KVKs (V5), directly support higher-level objectives. Intermediate factors like economies of scale (V1) and market and credit linkages (V3) transform these services into operational advantages, while the outcome factors of business planning (V8), FPO branding (V7), and bargaining power (V9) emerge as dependent variables. The model demonstrates that V2 catalyzes improvements across the production, market, and institutional domains, cascading through intermediate enablers (V1, V4, V5, V6) to strengthen outcomes (V3, V7, V8, V9, V10). This hierarchy demonstrates that investing in post-harvest technology and complementary extension services is critical for building resilient millet FPOs and enhancing member participation. Full article

Improving ovine reproductive efficiency is an important breeding goal that could substantially enhance economic viability in the sheep industry. The histone cell cycle regulator (HIRA) gene has been functionally validated as a reproductive regulator in model organisms such as Drosophila and murine species; however, research on the effects of HIRA on the prolificacy in sheep remains scarce. Thus, this study aimed to investigate the association between genetic variants of HIRA and litter size in sheep. In brief, we identified 15 novel exonic mutations in the Sonid sheep breed via direct sequencing. Notably, a linkage disequilibrium including the c.1521C>G, c.1572C>T, and c.1578G>A mutations on exon 14 of HIRA exhibited a significant association with litter size in Sonid sheep (p < 0.01). Meanwhile, it was predicted that mutations play a major role in enhancing the stability of the mRNA secondary structure by lowering the minimum free energy, and mutations were also thought to change the mRNA secondary structure of ovine HIRA. Therefore, these findings may provide potentially useful molecular markers for optimizing reproductive performance in Sonid sheep. 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

Simulation-based studies can support breeders’ decisions inexpensively, since there is no need to perform a new procedure. The objective was to assess the efficiency of recurrent genomic selection in panmictic population under additive–dominance and additive–dominance with epistasis models. We assumed two broiler chicken populations with contrasting linkage disequilibrium (LD) levels, 38,500 SNPs, and 1000 genes controlling feed conversion ratio. We applied recurrent genomic selection over seven cycles. The genomic selection efficacy, expressed as realized total genetic gain, was proportional to the LD level and genotypic variance. Genomic selection required model updating to achieve a higher efficacy. The training set size required by genomic selection can be as low as 10%/generation. Under this low-cost scenario, the genomic selection efficacy was slightly lower than the maximum efficacy. There is no difference between genetic evaluation methods regarding the decrease in the genotypic variance due to selection. In general, additive value prediction accuracies and realized genetic gains were highly correlated. The accumulated inbreeding level was not high due to avoidance of sib cross. The genomic inbreeding coefficient over generations was close to zero. Except for dominant epistasis, the efficacy of genomic selection was 4.1 to 46.2% lower than the efficacy under no epistasis. Full article

This paper utilizes unique high-frequency, daily electricity consumption data across economic sectors to examine the impact of monetary policy shocks on economic output, with a particular focus on the network spillover effects and sectoral heterogeneity introduced by inter-sector linkages. The study finds that quantity-based monetary policy (e.g., M2) generates significant positive and cascading spillover effects within the production network. However, the total effects of monetary policy shocks are broadly similar across upstream, midstream, and downstream sectors, exhibiting only minor differences. Notably, the proportion of network (indirect) effects increases systematically from upstream to downstream sectors and displays marked sectoral heterogeneity. In contrast, interest-rate-based monetary policy displays insufficient spatial spillover through production networks. These findings offer important insights for policymakers to optimize structural policy design and promote coordinated sectoral chain development, which can guide the pursuit of sustainable economic strategies that balance growth, resource utilization and sectoral interdependencies. Full article

Brushless DC (BLDC) motors are increasingly used in industrial applications due to their high efficiency, reliability, and low weight. However, their performance strongly depends on the electromagnetic properties of stator and rotor core materials. This study evaluates six BLDC motor configurations, employing materials such as M19 electrical steel, 1010 low-carbon steel, magnetic PLA, and ABS, and analyzes their impact using FEMM 4.2 finite element simulations. Key electromagnetic characteristics—including flux linkage, Back-EMF, torque, and torque ripple—were compared across configurations. The reference motor with M19 steel stator and 1010 steel rotor achieved ~7 mWb flux linkage, ~39 V pk–pk Back-EMF, and 1.44 Nm torque with ~49% ripple, confirming the suitability of laminated steels for high-power-density designs. Substituting M19 with 1010 steel in the stator reduced torque by less than 10%, indicating material interchangeability with minimal performance loss. By contrast, polymer-based designs exhibited drastic degradation: magnetic PLA yielded only 3.5% of the baseline torque with sixfold ripple increase, while ABS delivered nearly zero torque and >700% ripple. Hybrid configurations improved PLA-based results by 15–20%, though they remained far below ferromagnetic cores. Overall, results demonstrate a nearly linear relationship between material permeability and both flux linkage and Back-EMF, alongside a sharp rise in torque ripple at low permeability. The findings highlight the advantages of ferromagnetic and laminated steel cores for efficiency and stability, while polymer and hybrid cores are limited to lightweight demonstrator applications. 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

This study examines the genetic diversity and population structure of silver carp (Hypophthalmichthys molitrix), an ecologically and economically important freshwater species. Samples were collected from 17 sites along the Yangtze River, including LCH, LCS, LJHK, and LXZX, as well as one population from the United States (SV). Restriction-site associated DNA sequencing (RAD-seq) generated 759,453 high-quality single-nucleotide polymorphisms (SNPs) for population genomic analyses, including genetic differentiation (F_ST), population structure, and linkage disequilibrium (LD) decay. Genetic variation was primarily found within populations (78.05%), with 21.94% among populations. Most sites exhibited low genetic differentiation (F_ST < 0.05), suggesting high admixture along the river, although a few sites displayed elevated values (F_ST > 0.15). Rapid LD decay in LCH, LCS, and LJZ indicated frequent recombination and moderate to large effective population sizes. These patterns reflect the influence of geographic and ecological factors on population structure. Conservation strategies should maintain genetic connectivity while protecting distinct genetic resources. Populations with high differentiation, such as LXZX and LWZ, warrant targeted management to preserve unique genetic diversity. 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

Alkaptonuria (AKU) is a rare metabolic disorder caused by homogentisate 1,2-dioxygenase (HGD) deficiency, leading to homogentisic acid (HGA) accumulation and ochronotic pigment deposition, which drug therapy cannot reverse. The process of pigment formation and deposition is still unclear. This study offers molecular insights into the polymeric structure, with the goal of developing future adjuvant strategies that can inhibit or reverse pigment formation, thereby complementing drug therapy in AKU. HGA polymerisation was examined under physiological, acidic, and alkaline conditions using liquid and solid phase nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), and polyacrylamide gel electrophoresis. At physiological pH, HGA polymerised slowly, while alkaline catalysis accelerated pigment formation while retaining the HGA aromatic scaffold. During the process, EPR detected a semiquinone radical intermediate, consistent with an oxidative coupling mechanism. Reactivity profiling showed the diphenol ring was essential for polymerisation, while –CH₂COOH modifications did not impair reactivity. Pigments displayed a polydisperse molecular weight range (11–50 kDa) and a strong negative charge. Solid-state NMR has revealed the presence of phenolic ether and biphenyl linkages. Collectively, these identified structural motifs can serve as a foundation for future molecular targeting related to pigment formation. Full article