Search Results (498)

This paper analyzes the impact of COVID-19 on the supply chain and production, investigating countermeasures for industrial recovery. In particular, the study examines how COVID-19 has affected the raw material supply chain, production, and outages on a real case study, that is, Turkey’s Glass-Reinforced Plastic (GRP) pipe industry. Using two- and three-way analysis of variance (ANOVA), significant negative impacts on the raw material supply chain are identified with 95% confidence. To enhance decision-making, the fuzzy q-rung orthopair set (FQROPS) and entropy-based multi-criteria decision-making (MCDM) methods are integrated in the baseline method. Specifically, ANOVA-identified factors, such as cost, supply continuity, production capacity, and risk level, are used as criteria in the MCDM analysis. Entropy determined criteria weights and FQROPS evaluate alternatives based on their proximity to the ideal solution. Findings show that significant disruptions occurred due to the pandemic. In addition, the MCDM analysis reveals that pre-pandemic conditions for key materials, such as fiberglass and resin, were significantly more favorable in terms of cost, supply continuity, production capacity, and risk levels. This integrated approach provides strategic insights for managing supply chains and production in the GRP pipe industry during and after pandemic events. Full article

Background: Cardiac amyloidosis is characterized by progressive myocardial and atrial infiltration, leading to atrial mechanical dysfunction, atrial fibrillation, and thromboembolic complications. Left atrial (LA) strain is an established marker of atrial function; however, data on triplane LA strain in cardiac amyloidosis are limited. Methods: We evaluated transthoracic echocardiographic examinations of 24 patients with cardiac amyloidosis and 24 age-, sex-, rhythm-, and ejection fraction-matched control subjects (9 with atrial fibrillation in each group). Among amyloidosis patients, 21 had transthyretin and 3 had light-chain cardiac amyloidosis. All examinations were performed during 2025. Triplane and biplane LA reservoir strain were assessed using speckle-tracking echocardiography. Two-way analysis of variance tested the effects of disease (amyloidosis vs. control) and rhythm (sinus rhythm vs. atrial fibrillation). Agreement between triplane and biplane measurements was evaluated using Pearson correlation and Bland–Altman analyses. Results: Triplane LA reservoir strain was significantly lower in patients with cardiac amyloidosis compared with controls (6.7 ± 2.7% vs. 16.2 ± 8.3%, p < 0.001). Even in sinus rhythm, amyloidosis patients demonstrated markedly impaired LA strain, with mean values similar to those observed in control subjects with atrial fibrillation. Two-way ANOVA revealed significant main effects of disease (F = 68.9, p < 0.0001) and rhythm (F = 45.0, p < 0.0001), as well as a significant disease–rhythm interaction (F = 26.5, p < 0.0001). Triplane and biplane LA strain showed strong correlation (r = 0.90, p < 0.0001) with good agreement. Reproducibility was excellent (intra-observer ICC = 0.97; inter-observer ICC = 0.94). Conclusions: Triplane LA reservoir strain is markedly reduced in cardiac amyloidosis and enables comprehensive visualization of atrial mechanical dysfunction. The technique demonstrates high reproducibility and strong agreement with biplane analysis, supporting its use as a complementary tool for characterizing amyloid atriopathy. Full article

As agricultural labor shifted toward non-farm sectors and the farming population aged, innovative production arrangements became essential to sustain land productivity. While partial agricultural production chain management (PAPM) was widespread, the productivity impact of whole-process agricultural production chain management (WAPM)—a comprehensive model integrating all production stages—remained empirically underexplored. Using nationally representative panel data from the China Labor-force Dynamics Survey (CLDS, 2014–2018) for grain-producing households, this study estimates the differential impacts of WAPM and PAPM with a two-way fixed-effects (TWFE) model, supplemented by propensity score matching (PSM) as a robustness check. The results show that WAPM significantly enhanced land productivity. Notably, the effect size of WAPM (coefficient: 0.486) is substantially larger than that of PAPM (coefficient: 0.214), indicating that systematic integration of service chains offers superior efficiency gains over fragmented outsourcing. Mechanism analysis suggests that WAPM improves productivity primarily by alleviating labor constraints and mitigating the disadvantages of small-scale farming. Furthermore, heterogeneity analysis demonstrated that these benefits are amplified in major grain-producing regions and hilly areas. These findings support policies that facilitate a transition from single-link outsourcing toward whole-process integrated service provision. Full article

This review examines a small interfering RNA (siRNA) designed for intrathecal (IT) injection, which reduces the formation of amyloid beta precursor protein (APP), a critical factor in the pathology of Alzheimer’s disease (AD). The siRNA, designated ALN-APP, incorporates a 16-carbon chain (C16-siRNA) to enhance its delivery to the central nervous system (CNS) while leveraging advancements in specificity and duration of action based on previously approved drugs by the Food and Drug Administration. The development of ALN-APP involved a comprehensive analysis of the optimal carbon chain length and its conjugation position to the siRNA. Preclinical studies conducted on male Sprague Dawley rats, mice, and non-human primates (NHPs) demonstrated the efficacy of ALN-APP. In rats, an IT injection of C16-siRNAs at a concentration of 30 mg/mL, delivering a dose of 0.9 mg, resulted in cranial distribution via cerebrospinal fluid and led to a 75% reduction in copper-zinc superoxide dismutase 1 (SOD1) mRNA levels. These effects were dose-dependent and persisted for three months across multiple brain regions. Furthermore, studies in NHPs indicated that soluble APP levels were reduced to below 25%, sustained for two months. In the cerebrovascular amyloid Nos2^−/− (CVN) mouse model of AD, administration of 120 µg of siRNA via the intracerebroventricular route produced reductions in APP expression, with mRNA levels remaining suppressed for 60 days in the ventral cortex. Indeed, ALN-APP controlled neuropathology in 5xFAD mice by significantly reducing amyloid levels and brain neuroinflammation, with improved behaviors in the elevated plus maze. Following these promising results in animal models, ALN-APP advanced to a Phase 1 trial, designated ALN-APP-001, which assessed its safety and efficacy in 12 participants with early-onset Alzheimer’s disease (EOAD). Initial findings revealed a 55% reduction in soluble APPα and a 69% reduction in APPβ by day 15. These exploratory findings require further validation with larger cohorts and proper statistical analysis. In a subsequent cohort of 36 patients, administration of the 75 mg dose via IT injection led to mean reductions of 61.3% in soluble APPα (sAPPα) and 73.5% in soluble APPβ (sAPPβ) after one month. These silencing effects persisted for six months and were associated with important decreases in Aβ42 and Aβ40 levels. These results highlight the potential of ALN-APPs to address Alzheimer’s pathology while maintaining a favorable safety profile. Whether ALN-APP succeeds in further clinical trials, key challenges include ensuring accessibility and affordability due to treatment costs, the need for specialized intrathecal administration, and establishing infrastructure for large-scale production of siRNAs. In conclusion, advancements in ALN-APP represent a promising strategy to reduce beta-amyloid formation in AD, with substantial biomarker reductions suggesting potential disease-modifying effects. Continued development may pave the way for innovative treatments for neurodegenerative diseases. Full article

Accurate, real-time monitoring of meat freshness is essential for reducing food waste and safeguarding consumer health, yet conventional methods rely on costly, laboratory-grade spectroscopy or destructive analyses. This work presents a low-cost electronic-nose platform that integrates a compact array of metal-oxide gas sensors (Figaro TGS2602, TGS2603, and Sensirion SGP30) with a Gaussian Process Regression (GPR) model to estimate a continuous freshness index under refrigerated storage. The pipeline includes headspace sensing, baseline normalization and smoothing, history-window feature construction, and probabilistic prediction with uncertainty. Using factorial analysis and response-surface optimization, we identify history length and sampling interval as key design variables; longer temporal windows and faster sampling consistently improve accuracy and stability. The optimized configuration (≈143-min history, ≈3-min sampling) reduces mean absolute error from ~0.51 to ~0.05 on the normalized freshness scale and shifts the error distribution within specification limits, with marked gains in process capability and yield. Although it does not match the analytical precision or long-term robustness of spectrometric approaches, the proposed system offers an interpretable and energy-efficient option for short-term, laboratory-scale monitoring under controlled refrigeration conditions. By enabling probabilistic freshness estimation from low-cost sensors, this GPR-driven e-nose demonstrates a proof-of-concept pathway that could, after further validation under realistic cyclic loads and operational disturbances, support more sustainable meat management in future smart refrigeration and cold-chain applications. This study should be regarded as a methodological, laboratory-scale proof-of-concept that does not demonstrate real-world performance or operational deployment. The technical implications described herein are hypothetical and require extensive validation under realistic refrigeration conditions. Full article

Microplastics, plastic particles smaller than 5 mm, are now ubiquitous and represent a form of pollution that threatens ecosystems and human health, infiltrating the environment, air, and food chain. The search for solutions to microplastics requires industrial policies that limit plastic production and technological innovations for removal and recycling. Specifically, this paper reports a sustainable and cost-effective method for the detection of high-density polyethylene (HDPE) and low-density polyethylene (LDPE) microplastics using nitrogen-doped carbon dots (N-CD) synthesized from onion peel and L-cysteine via hydrothermal carbonization. Two precursor ratios (1:1 and 1:0.30 w/w) were evaluated. The resulting N-CDs exhibited bright yellow-green fluorescence (470–500 nm) and excitation-dependent photoluminescence under 365 nm UV light. FTIR and UV-Vis spectroscopy confirmed the presence of nitrogen-containing functional groups and effective graphitization, particularly in the 1:0.30 ratio. Fluorescence imaging revealed stronger intensity and greater stain uniformity in thermally softened MPs treated with 1:0.30 N-CDs, with a peak emission of 10,230.02 a.u. at 2 h and PMT 11—surpassing the 1:1 ratio. Bandgap and absorbance analyses supported the superior optical behavior of the lower-concentration formulation. Image analysis further indicated increased luminescent area over time, and two-way ANOVA confirmed statistically significant effects of heating time and PMT settings (p < 0.05). Compared to traditional filtration staining, thermal-assisted application offered enhanced and stable fluorescence. These findings demonstrate the efficacy of green-synthesized N-CDs for MP detection, with potential scalability and environmental applicability. Future work should explore alternative biomass sources and assess N-CD performance under field conditions to optimize environmental sensing strategies. Full article

This study develops an indicator system for provincial digital innovation in China from 2012 to 2022, drawing on four dimensions: actors, elements, environment, and outcomes. Its purpose is to identify the spatial evolution of China’s digital innovation network and reveal the mechanisms that drive this process. The findings contribute both to the scientific understanding of digital innovation dynamics and to policy practices aimed at enhancing regional coordination. We measure digital innovation using a modified gravity model, social network analysis, and a temporal exponential random graph model (TERGM). The results show a clear spatial pattern: digital innovation levels are higher in eastern provinces and lower in western regions, with a noticeable north–south divide. Spatial association intensity continues to increase, forming a distribution characterized by dense linkages in the east and sparse connections in the west. The spatial association network evolves steadily over time. Shanghai, Beijing, Jiangsu, Zhejiang, and Fujian hold dominant positions and are more likely to form ties with other provinces. The network can be divided into four blocks: a two-way Overflow block, a primary beneficiary block, and two broker blocks. Its structure is shaped primarily by chain-like linkages, supplemented by localized closed structures. The network also displays reciprocity, connectivity, cyclicity, and temporal dependence. Its formation is jointly driven by economic development, marketization, and geographic proximity. They also provide practical guidance for regional sustainable development, optimizing innovation resource allocation, and enhancing the efficiency of China’s digital innovation network. Full article

Industrial chain modernization is vital for driving the development of a modern country, boosting national competitiveness and upholding economic security. This study examines the impact of coordinated two-way FDI development on industrial chain modernization from the perspective of factor allocation, using panel data from 30 Chinese provinces from 2013 to 2023. The empirical results show that coordinated two-way FDI development significantly boosts industrial chain modernization. This finding holds across multiple robustness tests. Mechanism analysis confirms that the alleviation of capital-labor factor misallocation serves as a key transmission channel. Furthermore, heterogeneity analysis reveals significant heterogeneous effects across regions, ownership structures, investment types, and industry sectors. Notably, the synergistic interaction between downward-gradient inward FDI and reverse-gradient outward FDI, along with coordinated two-way FDI development in the manufacturing sector, has the highest gray correlation degree with industrial chain modernization. These findings provide a solid theoretical basis and practical policy insights for advancing industrial chain modernization. Full article

The COVID-19 pandemic had a major impact on the reliability of global supply chains, the availability of selected products including food, food prices, food purchase and consumption behaviour. The aim of this study is to identify potential differences in food waste levels and behaviours in Germany during the pandemic compared to pre-pandemic periods. The data are based on two highly representative household diary studies on food waste with sample sizes of over 6500 participants each. This study uses descriptive statistics as well as a mixed model approach to examine food waste amounts per product group, disposal reason and life cycle category and compare the survey year 2020 with the years 2016/17. A linear mixed model is applied to examine the effects of the pandemic and lockdown phases on the development of food waste amounts in 2020. The results show that total and unavoidable food waste increased significantly in the 2020 pandemic period compared to the same period in the 2016/17 survey, while avoidable food waste decreased. This suggests an improvement of food management skills while, at the same time, food consumption, and therefore also food waste, shifted from outside to inside the home. Also, the composition of product groups was affected by altered consumption patterns during the pandemic. The results are relevant to the post-pandemic period, as they raise the question of whether a deceleration in everyday life is a prerequisite for adopting more sustainable food behaviours and developing appropriate planning, storage and handling. Policies should therefore focus on encouraging citizens to engage with the issue, prioritise it and develop an interest in food management. Future research should focus on the ways in which behaviours that reduce food waste can be encouraged, as well as on the long-term effects of food supply chain disruptions and events altering everyday life in households in relation to food waste. Full article

Background/Objectives: Endothelial activation by lipopolysaccharides (LPS) contributes to inflammation and the development of cardiovascular disease, making n-3 polyunsaturated fatty acids (PUFAs) potential modulators capable of mitigating endothelial dysfunction. The current study examines the effects of long-chain eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), along with their precursor, α-linolenic acid (ALA), on oxidative stress, adhesion molecule expression, and cytokine milieu in LPS-stimulated human aortic endothelial cells (HAECs). Methods: HAECs (fifth passage) were cultured in control medium under standard conditions: ~37 °C, 5% CO₂, ≥80% humidity. Cells were incubated in control basal cell medium or medium supplemented with ALA, EPA, DHA, and their combination (50 µM; n = 5 per group). After 48 h, cells were treated overnight (~16 h) with LPS from E. coli (0.75 and 1 µg/mL). HAECs and supernatants were collected for flow cytometry, Luminex, and ELISA assays. Significance was assessed using two-way analysis of variance ANOVA, followed by post hoc analyses (p < 0.05). Spearman’s correlation analysis was performed between markers, and p-values were adjusted using the Benjamini–Hochberg (BH) correction. Results: PUFA supplementation, particularly with DHA and ALA, significantly reduced intracellular reactive oxygen species (ROS) production and the expression of adhesion molecules (ICAM-1, E-selectin) in HAECs under both basal and LPS-stimulated inflammatory conditions. All PUFAs reduced pro-inflammatory cytokine levels (IFNγ, TNFα, IL-6), while ALA increased IL-1α and endoglin expression, indicating differential immunomodulatory effects. EPA exhibited antioxidant and anti-inflammatory effects primarily at higher LPS concentrations. Correlation analysis demonstrated strong interdependence between oxidative stress, inflammatory markers, and vascular activation, further confirming PUFA-mediated endothelial protection. Conclusions: PUFA supplementation produced molecule-specific effects on endothelial inflammation. DHA and ALA consistently showed anti-inflammatory and antioxidative effects, while EPA’s beneficial effect was more pronounced under inflammatory conditions, emphasising the importance of PUFA type and context in managing vascular inflammation. Full article

Against the backdrop of safety becoming a key objective in the restructuring of industrial chains, the impact of China’s outbound foreign direct investment (OFDI) on industrial chain risks warrants further exploration. Based on the Asian Development Bank’s Multi-Regional Input-Output Data (ADB-MRIOD) from 2007 to 2023, this study measures the external risk exposure of industrial chains from both supply-side and demand-side perspectives across 41 Belt and Road Initiative (BRI) economies. Utilizing a two-way fixed effects panel model with lagged variables and instrumental techniques to mitigate endogeneity, we empirically investigate the mechanisms through which China’s OFDI influences the external risk exposure of industrial chains. The findings reveal that (1) China’s OFDI significantly reduces such risk exposure, and (2) effect heterogeneity observed across country groups and sectors—showing stronger mitigation in high-innovation and developing countries, as well as in capital-intensive industries. (3) Mechanism analysis identifies three transmission channels: enhancing the host country’s trade network status, rationalizing its industrial structure, and strengthening Sino-host country industrial linkages. The study provides empirical support for formulating targeted investment policies to enhance supply chain resilience under the BRI framework. Full article

Amid escalating global climate change and the urgent international demand for low-carbon development, enhancing the greenization level of manufacturing industrial chains has emerged as a critical policy priority. This study investigates the impact of environmental regulation on the greenization of China’s manufacturing industrial chains using provincial panel data from 30 regions (2010–2022), employing two-way fixed effects and spatial Durbin models. The results demonstrate that environmental regulation significantly promotes industrial chain greenization through three pathways: industrial structure rationalization, green technology innovation, and industrialization advancement. Heterogeneity analysis reveals stronger regulatory effects in regions characterized by coal-dependent energy structures, low shares of energy-intensive industries, and underdeveloped digital economies, while negligible impacts are observed in areas with cleaner energy mixes, high energy-intensive industrial concentrations, or advanced digitalization. Spatial econometric results confirm positive spatial spillovers, indicating that environmental regulation in one region enhances neighboring areas’ greenization through policy coordination and technology diffusion. Based on these findings, this study proposes tailored policy recommendations, including strengthening regulation in coal-reliant regions, optimizing industrial structures in energy-intensive hubs, and fostering cross-regional governance synergy to mitigate pollution haven effects. The research provides novel insights into achieving sustainable manufacturing transitions under the “dual carbon” framework. Full article

Background/Objectives: Despite the growing popularity of fresh food for dogs, there is an extremely small amount of literature evaluating the potential health benefits of fresh food and reduced processing compared to traditionally processed shelf stable cans, extruded kibble, or other food formats. Additionally, aging dogs have been previously documented to have altered metabolism and nutritional needs compared to a healthy adult dog population, but these differences are not well defined. The objective of the study was to compare the effects of feeding a fresh, human-grade food versus a standard extruded kibble diet in a year-long longitudinal study on serum metabolomic profiles in senior dogs. Methods: Twenty-two healthy mixed-breed geriatric Alaskan sled dogs were age- and sex matched into two feeding groups. All dogs were fed the extruded diet (control) for a 4-month washout period prior to being transitioned into their respective treatment group. Group 1 continued to be fed the control diet, while Group 2 was transitioned to a fresh, human-grade food (treatment). Body weight and body condition were assessed monthly, and calorie intake was adjusted to maintain body weight. Individual serum samples were collected at day 0 and months 1, 3, 6, and 12. Metabolomic profiling of serum samples was performed by Metabolon, Inc. (Durham, NC, USA). Data was analyzed using two-way analysis of variance with repeated measures to determine treatment differences. Results: Dogs fed the treatment food had an increase in branched-chain amino acid metabolism, creatine, carnosine, anserine, fatty acid metabolism, long-chain n-3 fatty acids, lipolysis, and ketogenesis. The treatment group had decreased advanced glycation end products, fatty acid synthesis, and creatinine. Conclusions: This study is the first long-term feeding study evaluating serum metabolomics in dogs that demonstrates the dramatic and sustained impact that diet can have on canine metabolism. Full article

Against the backdrop of rapid population aging and a high prevalence of cognitive impairment in China, identifying modifiable environmental risk factors is a public health priority. Although environmental noise is widely recognized as a significant stressor, its effects on cognitive health remain underexplored within the Chinese context. Drawing on balanced panel data from three waves of the China Health and Retirement Longitudinal Study (CHARLS), we examined 3459 individuals aged 45 and above to assess the association between noise pollution and cognitive function using a two-way fixed-effects model. Additionally, we employed a chained mediation approach to investigate whether sleep disturbances and depressive symptoms serve as intermediary mechanisms. The findings indicated a significant inverse relationship: each unit increase in the noise pollution index corresponded to a 0.41-point reduction in overall cognitive scores. These results were robust across various noise exposure measures. Sensitivity analyses using alternative noise metrics also supported this finding. Sleep duration and depression were identified as significant mediators in the relationship between noise pollution and cognitive decline. This longitudinal analysis offers compelling evidence that environmental noise constitutes a substantial risk factor for declining cognitive function in middle-aged and older adults in China. Full article

This paper investigates the role of digital marketing signals as alternative data for understanding financial and operational dynamics in the beverage supply chain. Drawing on web analytics covering multiple actors across a five-month horizon, we analyze traffic composition, user engagement, and acquisition channels through a panel econometric framework. Descriptive statistics reveal pronounced heterogeneity in channel reliance, with some firms emphasizing organic search visibility while others depend more on paid campaigns or social referrals. Correlation patterns indicate strong substitution between organic and paid search, while display advertising is positively associated with session depth, suggesting that differentiated digital strategies influence user engagement. Analysis of variance confirms significant structural differences across firms, with an effect size exceeding 0.90. A two-way fixed-effects regression demonstrates that brand-specific factors explain the vast majority of variation in digital visibility, overshadowing short-term fluctuations. These results highlight the potential of web-derived marketing metrics to serve as leading indicators of supply chain finance outcomes such as revenue growth, working-capital efficiency, and investor sentiment. By integrating digital signals into financial econometrics, this study contributes to emerging research on alternative data in supply chain contexts and offers practical implications for managers, investors, and policymakers. Full article