Search Results (84,014)

This study investigates how supply chain co-innovation affects the high-quality development of SRDI enterprises, operationalized as total factor productivity (TFP) measured by the LP method. The mechanism remains unclear. Drawing on learning-by-doing theory, together with the resource-based view and stakeholder theory, we propose a sequential pathway: through repeated interactions and knowledge accumulation in collaborative innovation, SRDI enterprises improve their ESG performance, which in turn enhances TFP. Using a sample of listed “little giant” SRDI enterprises from 2018 to 2023, we find that supply chain co-innovation is significantly positively associated with TFP (coefficient 0.003), and the pattern is consistent with ESG performance playing a partial mediating role. Meanwhile, mechanistic analysis also reveals that this correlation is more pronounced in high-profitability enterprises and manufacturing enterprises. This research provides theoretical guidance for SRDI enterprises in choosing innovation models and managing supply chains, offering practical insights for improving total factor productivity. Full article

This study demonstrates a molecular size-dependent strategy to regulate the network structure of poly(vinyl alcohol) (PVA) hydrogels using a series of saccharides with increasing molecular size—glucose, maltose, raffinose, soluble starch, and amylose. FTIR, XPS, XRD, and TG analyses reveal that increasing saccharide size shifts the network from plasticization to reinforcement, which is further confirmed by mechanical testing and rheological analysis. Small-molecule saccharides disrupt hydrogen bonds and enhance chain mobility, while macromolecular starches promote network regularity through strong hydrogen bonding and crystallization induction. This structural tunability ndows the resulting hydrogels with integrated functionalities: tensile strain increases from 640% to 1500%, self-healing efficiency reaches up to 90.6%, and high-fidelity electrocardiogram (ECG) signal acquisition is achieved with a signal-to-noise ratio of 39.84 dB, comparing favorably with commercial electrodes. This work establishes a structure–property relationship linking saccharide molecular size to network architecture and provides a versatile material platform for next-generation flexible wearable sensors and bioelectrodes. Full article

Cardiac auscultation remains a widely used non-invasive method for assessing cardiac function; however, conventional acoustic stethoscopes are limited by subjective interpretation and lack of digital signal-handling capabilities. This study presents the design and fabrication of a chitosan-based diaphragm digital stethoscope using a biopolymer-derived acoustic interface. Chitosan was extracted from mealworm larvae shells through sequential chemical processing and subsequently processed into a glycerol-plasticized film via solution casting to obtain a flexible diaphragm. The mechanical properties of the diaphragm were evaluated to assess its suitability for acoustic applications. The diaphragm was mechanically coupled to a piezoelectric sensor and integrated into a custom 3D-printed chest piece connected to a microcontroller-based acquisition system. Heart sound signals were acquired from four conventional auscultation sites (aortic, pulmonic, tricuspid, and mitral regions). The recorded signals were processed using band-pass filtering, envelope extraction, and time–frequency analysis to visualize waveform morphology and frequency content. The signals obtained exhibited temporal and spectral features consistent with reported phonocardiography characteristics, including identifiable S1 and S2 components. These results demonstrate the feasibility of using chitosan-based diaphragm materials for heart sound acquisition in a digital stethoscope configuration, providing a low-complexity platform for further development of biopolymer-based acoustic sensing devices. Full article

Artificial Intelligence systems increasingly shape environmental decision making, infrastructure planning, and resource use across public and urban domains. However, prevailing AI trust and governance mechanisms, including labels, certifications, and assurance schemes, remain primarily focused on ethical and legal accountability, with limited operational attention to environmental sustainability. This paper reconceptualises AI trust mechanisms as socio-technical governance infrastructures that can support both ethical assurance and environmental accountability. Drawing on a comparative qualitative analysis of nine AI trust initiatives, the study develops a three-dimensional analytical framework embedding Environmental Performance Indicators across three governance dimensions: trust-building effectiveness, governance readiness, and sustainable adoption. Applying a systems governance lens, the framework examines how governance instruments structure information flows, institutional practices, and lifecycle feedback relevant to environmental performance. It is analytically illustrated through two urban mobility cases, Helsinki’s Whim application and Barcelona’s smart mobility system, to examine how governance conditions enable or constrain the integration of Environmental Performance Indicators in practice. Findings show that current trust mechanisms lack measurable and publicly visible environmental criteria, indicating a gap between AI assurance and environmental governance. The study contributes a systems-oriented framework for evaluating AI trust mechanisms as governance instruments capable of supporting environmental accountability. While exploratory and based on secondary data, the results indicate that future AI trust mechanisms must incorporate measurable sustainability indicators to support eco-efficient and accountable digital transformation. Full article

This study examines how manufacturing SMEs can structure digital transformation as a strategic, risk-managed process under demand uncertainty and resource constraints. Integrating digital maturity assessment with cost–benefit analysis (D3A–CBA framework), the study evaluates a phased investment strategy at a Turkish metal processing SME, grounding the analysis in real production order data and firm-level financial records. The phased structure—informed by real options reasoning—conditions capacity expansion on measurable Phase-1 performance thresholds, thereby limiting downside risk while preserving strategic flexibility. Under the base scenario (10% real discount rate), Phase-1 yields an NPV of TRY 3,830,738 and an IRR of 12.4%; the combined portfolio reaches TRY 17,365,066. However, a 10,000-iteration Monte Carlo simulation reveals a 29.8–33.0% probability of negative NPV, and sensitivity analysis exposes an asymmetric risk profile in which moderate demand shocks—rather than cost shocks—drive non-viability. The findings demonstrate that digital transformation in resource-constrained SMEs requires not only positive financial returns but also strategic mechanisms to manage demand uncertainty, exchange rate volatility, and organizational adaptation. The proposed framework offers SME managers a reproducible, evidence-based approach to aligning investment decisions with strategic objectives while containing capital risk. Full article

Growing consumer awareness of environmental and health issues has increased demand for sustainable products, yet a persistent gap remains between positive attitudes and actual purchasing behavior. This study addresses inconsistent findings in prior literature regarding the effects of psychological drivers on willingness to pay a premium for green products. Drawing on the Theory of Planned Behavior and value-based perspectives, this study examines how environmental concern, health consciousness, and consumer innovativeness influence purchase intention and willingness to pay a premium (WTP) for green cosmetics. Data were collected from 872 respondents in Indonesia and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with multi-group analysis (MGA) to capture demographic heterogeneity. The results show that all three drivers significantly influence purchase intention, which in turn affects WTP and acts as a partial mediator. Demographic differences further moderate several relationships, highlighting heterogeneity in green consumer behavior. This study contributes by integrating psychological drivers, behavioral mechanisms, and demographic heterogeneity into a unified framework to explain willingness to pay for green cosmetics. The findings offer practical insights for developing targeted strategies to promote sustainable consumption in emerging markets. Full article

Acute lymphoblastic leukemia (ALL) is a genetically and epigenetically heterogeneous malignant disease characterized by different subtypes with varying sensitivities to conventional chemotherapy. Despite significant improvements in survival rates, relapse remains the primary cause of treatment failure, often associated with intrinsic or acquired drug resistance. First-line therapy at diagnosis represents a major determinant of relapse in ALL. In this study, we performed a transcriptome and drug response profiling analysis to identify subtype-specific cell surface proteins that are overexpressed in patients with poor response to induction therapy. We summarize the current state of knowledge regarding chemotherapy responses, resistance mechanisms to standard cytostatic drugs and the increasing importance of cell biomarkers as predictors of an adverse disease course and potential therapeutic targets. We discuss the results of clinical and molecular studies linking specific genomic alterations—such as KMT2A-rearrangements, Ph-like, DUX4-rearrangements and T-ALL—to drug resistance and highlight surface antigens like CSPG4, HER2, MCAM and ROR1 that define high-risk leukemia phenotypes. The integration of transcriptomic, immunophenotypic and drug response data could enable a new generation of risk-adapted, surface-directed strategies for relapse treatment in ALL. Our analysis therefore provides subtype-specific predictive therapeutic targets for relapse treatment in ALL. Full article

Water quality classification is essential for freshwater ecosystem protection but faces challenges posed by spatiotemporal dependencies and class imbalance. To address these issues, this paper proposes the Adaptive Graph Convolutional Long Short-Term Memory Network (AGConvLSTM), which integrates adaptive graph convolution into the LSTM gating mechanism to explicitly capture spatiotemporal dependencies. As complementary components, station-wise Principal Component Analysis (PCA) preserves spatial heterogeneity in feature structures, while DTW-SMOTE with adaptive sampling and dynamic denoising mitigates class imbalance. Evaluated on five-year water quality data from 13 stations in the Taihu Basin, China, AGConvLSTM achieves a test accuracy of 69.34% and an F1 score of 69.68%, outperforming baseline models. Station-wise accuracy ranges from 49.12% to 88.48%, reflecting spatial heterogeneity. These results suggest that spatiotemporal fusion within recurrent units provides an effective pathway for multi-station water quality classification and offers practical value for watershed early warning systems. Full article

Background/Objectives: Restenosis following coronary artery bypass grafting (CABG) remains a major long-term complication that adversely affects patient prognosis. Although prior studies have investigated clinical features, imaging parameters, and circulating biomarkers for restenosis risk stratification, the metabolic mechanisms underlying long-term restenosis—particularly those reflecting both the local cardiac microenvironment and systemic circulation—remain poorly defined. Therefore, this study aims to identify restenosis-associated metabolic alterations and develop a risk prediction model based on integrated targeted metabolomic profiling of pericardial fluid (PF) and serum in patients undergoing isolated CABG. Methods: Patients undergoing isolated CABG were prospectively enrolled. Paired PF and serum samples were collected during surgery or the perioperative period for targeted metabolomic analysis. Differential metabolite (DM) analysis was performed between patients with and without restenosis. Key metabolites were selected to construct a restenosis risk prediction model, which was subsequently evaluated in training and validation cohorts. Results: Compared with patients without restenosis, those who developed restenosis exhibited two key differential metabolites identified in PF and serum: 7α-Hydroxy-4-cholesten-3-one and Phenoxyacetic acid (PAA). A logistic regression-based prediction model incorporating these metabolites was developed and evaluated using receiver operating characteristic (ROC) analysis, integrated discrimination improvement (IDI), and decision curve analysis (DCA). The model demonstrated robust predictive performance in both training and validation cohorts. Kaplan–Meier survival analysis further revealed that higher model scores were significantly associated with an increased risk of long-term restenosis in the training cohort (HR = 1.44, p = 0.047) and validation cohort (HR = 1.83, p = 0.012). Conclusions: This study provides the first evidence that integrated metabolomic signatures derived from PF and serum are associated with long-term restenosis after CABG. By capturing complementary metabolic information from the local cardiac microenvironment and systemic circulation, this integrated approach enhances current understanding of restenosis biology and supports the potential clinical utility of targeted metabolomics for long-term restenosis risk prediction following CABG. Full article

Rapid urbanization has profoundly reshaped land use patterns and intensified pressures on ecosystem structures, thereby exacerbating trade-offs and synergies among ecosystem services (ESs). Understanding ecosystem service trade-offs, synergies, and their attribution mechanisms is critical for balancing ecological conservation and regional sustainable development in rapidly developing regions. This study quantified provisioning, regulating, supporting, and cultural ecosystem services in Shandong Province from 2000 to 2020 using the InVEST model and spatial analysis. An integrated framework combining Pearson correlation and bagplot analysis was developed to identify linear and nonlinear ES trade-offs and synergies, while the XGBoost–SHAP model was applied to quantify the relative contributions of natural and socioeconomic drivers. Ecosystem service bundles were further identified using a self-organizing map to delineate spatially functional zones. The results showed that: (1) Provisioning and cultural services increased markedly, whereas regulating and supporting services generally declined. Spatially, provisioning services were concentrated in the western plains, regulating and supporting services in the central mountains and eastern hills, and cultural services in urban areas. (2) Strong trade-offs emerged between provisioning services and most regulating/supporting services, while regulating and supporting services exhibited pronounced synergies. Cultural services reflected a generally compatible relationship with other ESs. (3) Regulating and supporting services were primarily shaped by natural conditions and land use patterns, whereas provisioning and cultural services were more strongly driven by socioeconomic factors. (4) SOM clustering identified four major functional zones, the ecological core zone, the ecological degraded zone, the food production zone, and the urban composite zone, each corresponding to differentiated ecosystem functions and development trajectories. The integrated framework provides a scientific basis for ecosystem-service-oriented spatial zoning and targeted management strategies to reconcile ecological protection and urbanization in rapidly developing regions. Full article

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide. Despite their often-asymptomatic progression and complex therapeutic management, a substantial proportion of CVDs is preventable through early intervention and lifestyle modification. However, effective pharmacological strategies to fully reduce disease burden and associated risk factors remain limited. Polyphenols are a structurally diverse class of bioactive compounds widely distributed in plant-based foods, characterized by multiple phenolic and hydroxyl groups that confer potent redox-modulating properties. Increasing evidence indicates that dietary polyphenols exert cardioprotective effects through antioxidant, anti-inflammatory, and endothelial-modulating mechanisms. Experimental studies (in vitro and in vivo) have demonstrated that polyphenols regulate key molecular pathways involved in oxidative stress, inflammation, and vascular function, including PI3K/Akt/eNOS, AMPK/SIRT1, and Nrf2 signaling. In parallel, epidemiological and clinical evidence support their association with improvements in blood pressure, glycemic control, lipid profiles, and body weight, critical determinants of cardiovascular risk. Importantly, the biological response to polyphenol intake is highly variable and influenced by genetic background, metabolism, gut microbiota composition, and bioavailability constraints. This review provides an updated and integrative analysis of the molecular mechanisms underlying the cardioprotective effects of polyphenols, emphasizing their role in endothelial function and nitric oxide bioavailability. Additionally, it highlights recent advances in polyphenol-based nutraceuticals, discusses translational limitations, and outlines future perspectives for their application in cardiovascular disease prevention and management. Full article

Background: Tumour glycosylation regulates immune modulation and progression, but whether the CRC sialylome—the complete repertoire of sialylated glycans—defines a biologically distinct subtype remains unclear. We investigated how the “sugar code” shapes CRC biology, immunity, and therapeutic response. Methods: Transcriptomic data from three CRC cohorts (TCGA, Sidra-LUMC, and CPTAC-2; n = 988) were batch-corrected and integrated. Single-sample gene set enrichment analysis (ssGSEA) quantified sialyltransferase expression, sialic acid metabolism, EMT, MDR mechanisms, immune phenotypes, and Siglec-associated transcriptional signatures. GSEA, gene ontology enrichment analysis (GOEA), and drug ontology enrichment analysis (DOEA) characterised pathways and identified drug response-associated transcriptional signatures. Results: High sialylome activity defined a genomically stable but clinically advanced CRC subset enriched for left-sided tumours, mucinous histology, MSI, and BRAF mutations. At the transcriptional level, Sialyl-High tumours were associated with a mesenchymal, stromal-remodelling programme accompanied by reduced proliferative activity. They demonstrated enrichment of vesicular trafficking-related pathways alongside reduced representation of canonical efflux-associated programmes. Critically, the sialylome was associated with Siglec-related immune signatures, with sialylated glycan-related gene expression correlating with Siglec receptor expression (CD33 and SIGLEC7/9/10), consistent with an immune-inflamed yet structurally excluded microenvironment. DOEA identified selective enrichment of drug-response signatures related to sialic acid metabolism inhibitors (oseltamivir and Neu5Ac) and glycocalyx-disrupting agents (ginsenosides and soyasaponins). Conclusions: The CRC sialylome is associated with tumour phenotypic variation, including immune-excluded states linked to Siglec-associated transcriptional signatures and patterns consistent with non-canonical drug resistance programmes. These findings position the “sugar code” as a central organising principle in CRC and identify glycan-directed therapies as a promising strategy for the targeting of this aggressive subtype. Full article

This five-month epidemiological investigation evaluated pre-slaughter welfare, carcass-processing practices, and post-mortem lesion prevalence in 1012 cattle and 413 pigs slaughtered in Enugu State, Nigeria. Direct observations and post-mortem inspections were conducted following OIE standards. Animal welfare was markedly compromised. Cattle were dragged from the lairage to kill floor, restrained in lateral recumbency for over 30 min before bleeding, and slaughtered without stunning. Pigs were transported tied to motorcycles and processed on unsanitary floors. The lairages lacked roofing, clean water, and adequate drainage. Carcass handling was unhygienic, with meat processed near maggot-infested drains and transported in open vans or motorized tricycles used to commute passengers and cement. Of all cattle examined, 45.3% (458/1012) exhibited gross lesions attributable to contagious bovine pleuropneumonia (CBPP, 15.5%), fasciolosis (18%), liver abscessation (6.6%), ascariasis (4.6%), and bovine tuberculosis (0.5%). No lesions were detected in pigs. Lesion occurrence differed significantly (p < 0.05) by sex (males = 44.1%, females = 66.7%), age (<4 years = 54.1%, ≥4 years = 45.4%), breed (White Fulani = 45.5%, others = 36.7%), slaughterhouse location, and season (rainy = 45.2%, dry = 45.5%). Temporal analysis showed the highest lesion rate in April (68.3%), declining to 37.7% in May. Lesions of CBPP and fasciolosis were significantly more frequent in young cattle and during the rainy months (p < 0.05). These findings reveal systemic welfare violations and disease endemicity within the municipal abattoirs surveyed. The combination of poor pre-slaughter welfare, unhygienic meat handling, and high prevalence of zoonotic and economically important livestock disease lesions highlights urgent public health concerns. Strengthening abattoir infrastructure, enforcing pre-slaughter animal welfare and hygiene regulations, mechanizing slaughter processes, and instituting continuous surveillance within the One Health framework are essential for ensuring meat safety and public health security in Nigeria and beyond. Full article

Background/Objectives: Freshwater microalgae–bacteria consortia are increasingly utilized in wastewater treatment and biomass production. However, bacteria associated with the algal phycosphere may act as environmental reservoirs of multidrug-resistant (MDR) phenotypes and antibiotic resistance genes (ARGs), including resistance to last-resort antibiotics such as colistin. Methods: An axenic culture of the freshwater microalga Pectinodesmus pectinatus was established using a NaClO-based cleaning protocol. Three phycosphere-associated bacterial strains (Chryseobacterium sp., Pseudomonas monteilii, and Stenotrophomonas pavanii) were isolated and identified by 16S rRNA gene analysis. Antimicrobial susceptibility testing was performed using broth microdilution against 16 antibiotics. Whole-genome sequencing of the most resistant isolate, S. pavanii, was conducted using Oxford Nanopore technology, followed by genome annotation and in silico resistome analysis using CARD, AMRFinderPlus, and ResFinder. Results: Among the three isolates, S. pavanii exhibited the broadest resistance profile, including high minimum inhibitory concentrations (MICs) to multiple β-lactams and colistin (MIC ≥ 16 μg/mL). No plasmid-borne mcr genes were detected. Instead, the genome encoded multiple chromosomal determinants potentially associated with polymyxin non-susceptibility, including lipid A and lipopolysaccharide modification pathways (e.g., arn genes and eptA), outer-membrane maintenance and LPS transport systems, multidrug efflux pumps, and regulatory elements. Integration of genomic and phenotypic data suggested that the observed colistin non-susceptibility may be associated with intrinsic chromosomal determinants inferred from whole-genome analysis. Conclusions: This study demonstrates that the P. pectinatus phycosphere can harbor multidrug-resistant (MDR) bacteria, including strains exhibiting colistin non-susceptibility potentially associated with a repertoire of intrinsic chromosomal resistance mechanisms inferred from genomic analysis. Therefore, freshwater microalgae-based systems should be considered potential environmental reservoirs contributing to the dissemination of antimicrobial resistance. Full article

To study the influence of polyoxymethylene (POM) fibers on the mechanical properties of shotcrete for tunnel support, this research conducted four-point bending tests on concrete with different POM fiber dosages (0, 5, 7, and 9 kg/m³) and lengths (30 mm, 36 mm, and 42 mm). The mechanical properties are analyzed in terms of failure modes, flexural strength, and the toughness index. The results show that, with the increase fiber length and dosage, the incorporation of POM fibers can enhance the toughness of concrete and significantly improve the flexural performance of shotcrete, with the peak flexural strength increasing by 15.31% to 89.46%. Additionally, through scanning electron microscopy (SEM) image analysis, the reinforcing mechanism of POM fibers is revealed: when shotcrete with POM fibers is subjected to flexural loading, it undergoes four stages: elastic, elastic–plastic, yield, and failure. The addition of POM fibers increases the density and uniformity of concrete, and the flexural strength is indirectly enhanced by increasing frictional energy dissipation through the formation of fiber–matrix interfaces between fibers and concrete. The research findings provide a theoretical basis and design reference for the application of POM fiber-reinforced shotcrete in tunnel support. Full article