Search Results (2,074)

This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO₂ geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project in the Ordos Basin, eight full-chain carbon capture, utilization, and storage (CCUS) scenarios were analyzed. The results indicate that environmental and cost performance are primarily influenced by technology choices across carbon capture, transport, and storage stages. The scenario employing potassium carbonate-based capture, pipeline transport, and brine reinjection after a reverse osmosis treatment (S5) achieved the most balanced outcome. Breakeven analyses under three carbon price projection models revealed that carbon price trajectories critically affect project viability, with a steadily rising carbon price enabling earlier profitability. By decoupling CCUS from power systems and focusing on unit CO₂ removal, this study provides a transparent and transferable framework to support cross-sectoral deployment. The findings offer valuable insights for policymakers aiming to design effective CCUS support mechanisms under future carbon neutrality targets. Full article

Various factors influence the formation and adjustment of network freight prices, including transportation costs, cargo characteristics, and policies and regulations. The interaction of these factors increases the difficulty of accurately predicting network freight prices through regressions or other machine learning models, especially when the amount and quality of training data are limited. This paper introduces large language models (LLMs) to predict network freight prices using their inherent prior knowledge. Different data sorting methods and serialization strategies are employed to construct the corpora of LLMs, which are then tested on multiple base models. A few-shot sample dataset is constructed to test the performance of models under insufficient information. The Chain of Thought (CoT) is employed to construct a corpus that demonstrates the reasoning process in freight price prediction. Cross entropy loss with LoRA fine-tuning and cosine annealing learning rate adjustment, and Mean Absolute Error (MAE) loss with full fine-tuning and OneCycle learning rate adjustment to train the models, respectively, are used. The experimental results demonstrate that LLMs are better than or competitive with the best comparison model. Tests on a few-shot dataset demonstrate that LLMs outperform most comparison models in performance. This method provides a new reference for predicting network freight prices. Full article

Traditional hydrogel preparation methods typically require multiple steps and certain external stimuli. In this study, rapid and stable gelation of polyvinyl alcohol (PVA)-tannic acid (TA)-based hydrogels was achieved through the regulation of hydrogen bonds. The cross-linking between PVA and TA is triggered by the evaporation of ethanol. Rheological testing and analysis of the liquid-solid transformation process of the hydrogel were performed. The gelation onset time (GOT) could be tuned from 10 s to over 100 s by adjusting the ethanol content and temperature. The addition of polyhydroxyl components (e.g., glycerol) significantly enhances the hydrogel’s water retention capacity (by 858%) and tensile strain rate (by 723%), while concurrently increasing the gelation time. Further studies have shown that the addition of alkaline substances (such as sodium hydroxide) promotes the entanglement of PVA molecular chains, increasing the tensile strength by 23% and the fracture strain by 41.8%. The experimental results indicate that the optimized PVA-TA hydrogels exhibit a high tensile strength (>2 MPa) and excellent tensile properties (~600%). Moreover, the addition of an excess of weakly alkaline substances (such as sodium acetate) reduces the degree of hydrolysis of PVA, enabling the system to form a hydrogel with extrudable characteristics before the ethanol has completely evaporated. This property allows for patterned printing and thus demonstrates the potential of the hydrogel in 3D printing. Overall, this study provides new insights for the application of PVA-TA based hydrogels in the fields of rapid prototyping and strength optimization. Full article

Background: Type 2 diabetes (T2D) is a global health epidemic with rising prevalence within Asian populations, particularly amongst individuals with high visceral adiposity and ectopic organ fat, the so-called Thin-Outside, Fat-Inside phenotype. Metabolomic and microbiome shifts may herald T2D onset, presenting potential biomarkers and mechanistic insight into metabolic dysregulation. However, multi-omics datasets across ethnicities remain limited. Methods: We performed cross-sectional multi-omics analyses on 171 adults (99 Asian Chinese, 72 European Caucasian) from the New Zealand-based TOFI_Asia cohort at 4-years follow-up. Paired plasma and faecal samples were analysed using untargeted metabolomic profiling (polar/lipid fractions) and shotgun metagenomic sequencing, respectively. Sparse multi-block partial least squares regression and discriminant analysis (DIABLO) unveiled signatures associated with ethnicity, glycaemic status, and sex. Results: Ethnicity-based DIABLO modelling achieved a balanced error rate of 0.22, correctly classifying 76.54% of test samples. Polar metabolites had the highest discriminatory power (AUC = 0.96), with trigonelline enriched in European Caucasians and carnitine in Asian Chinese. Lipid profiles highlighted ethnicity-specific signatures: Asian Chinese showed enrichment of polyunsaturated triglycerides (TG.16:0_18:2_22:6, TG.18:1_18:2_22:6) and ether-linked phospholipids, while European Caucasians exhibited higher levels of saturated species (TG.16:0_16:0_14:1, TG.15:0_15:0_17:1). The bacteria Bifidobacterium pseudocatenulatum, Erysipelatoclostridium ramosum, and Enterocloster bolteae characterised Asian Chinese participants, while Oscillibacter sp. and Clostridium innocuum characterised European Caucasians. Cross-omic correlations highlighted negative correlations of Phocaeicola vulgatus with amino acids (r = −0.84 to −0.76), while E. ramosum and C. innocuum positively correlated with long-chain triglycerides (r = 0.55–0.62). Conclusions: Ethnicity drove robust multi-omic differentiation, revealing distinctive metabolic and microbial profiles potentially underlying the differential T2D risk between Asian Chinese and European Caucasians. Full article

The port logistics service innovation (PLSI) is closely associated with cross-border e-commerce (CBEC) enterprise performance, given that the port, as the spatial carrier and the joint point of goods, information, customs house affairs, etc., is essentially a key node of the CBEC logistics chain. However, the influence mechanism of PLSI on CBEC enterprise performance has still not yet been elaborated by consensus. To fill this gap, this study aims to figure out the effect mechanism integrating the probe into two variables (i.e., information interaction and environmental upgrade) in a moderated mediation model. Specifically, this study collects questionnaire survey data of logistics enterprises and CBEC enterprises in the Ningbo-Zhoushan Port of China by the Bootstrap method in the software SPSS 26.0. The results show the following: (1) PLSI can positively affect the CBEC enterprise performance; (2) information interaction plays an intermediary role between PLSI and CBEC enterprise performance; and (3) environmental upgrade can not only positively regulate the relationship between information interaction and CBEC enterprise performance, but also enhance the mediating role of information interaction with a moderated intermediary effect. Full article

To evaluate the efficiency of innovation development in China’s high-tech manufacturing industry, this paper constructs a two-stage dynamic network cross-efficiency model. This model divides innovation activities into two stages: technology research and development and achievement transformation and introduces a 2-year lag period in the technology research and development stage and a 1-year lag period in the achievement transformation stage. It proposes the overall efficiency and efficiency models for each stage. The model was applied to 30 provinces in China, and the results showed that most provinces have achieved relatively ideal results in the overall efficiency and achievement transformation stage of high-tech manufacturing, while the efficiency in the technology research and development stage is generally lower than that in the achievement transformation stage. It is recommended that enterprises increase their R&D investments, break through technological barriers, and optimize the innovation chain. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

Polyethylene oxide (PEO) is the most well-studied polymer used in solid polymer electrolytes (SPEs) for lithium ion batteries (Li-ion batteries). However, ionic conductivity is greatly reduced in the low temperature range due to the crystallization of PEO. Therefore, methods to suppress the crystallization of PEO at room temperature by cross-linking or introducing a branched structure are currently being investigated. In this study, we synthesized new comb-type ion-conducting polyethers with two different side chains such as polydimethylsiloxane (PDMS) and polyethylene glycol monomethyl ether (mPEG) segments as flexible and ion-conducting segments, respectively. The introduction of the PDMS segment was found to prevent a decrease in ionic conductivity in the low-temperature region, but led to an ionic conductivity decrease in the high temperature region. On the other hand, the introduction of mPEG segments improved ionic conductivity in the high-temperature region. The introduction of mPEG segments with longer chains resulted in a significant decrease in ionic conductivity in the low-temperature region. Full article

The results of this study highlight the effectiveness of the proposed semantic security detection framework, SSB, in identifying a wide range of vulnerabilities in smart contracts tailored for industrial control scenarios. Compared to existing tools like ZEUS, Securify, and VULTRON, SSB demonstrates superior logical coverage across various vulnerability types, as evidenced by its performance on smart contract samples. This suggests that semantic-based approaches, which integrate domain-specific invariants and runtime monitoring, can address the unique challenges of ICS, such as real-time constraints and semantic consistency between code and physical control logic. The framework’s ability to model industrial invariants—covering security, functionality, consistency, time-related, and resource consumption aspects—provides a robust mechanism to prevent critical errors like unauthorized access or premature equipment operation. However, the lack of real-world ICS validation due to confidentiality constraints limits the generalizability of these findings. Future research should focus on adapting SSB for real industrial deployments, exploring scalability across diverse ICS architectures, and integrating advanced AI techniques for dynamic invariant adjustment. Additionally, addressing cross-chain interoperability and privacy concerns could further enhance the framework’s applicability in complex industrial ecosystems. Full article

Objective: To explore the relationship between type of grocery store used (chain vs. independent), transportation access, food insecurity, and fruit and vegetable intake in Detroit, Michigan, USA, during the COVID-19 pandemic. Design: A cross-sectional online survey was conducted from December 2021 to May 2022. Setting: Detroit, Michigan. Participants: 656 Detroit residents aged 18 and older. Results: Bivariate analyses showed that chain grocery store shoppers reported significantly greater fruit and vegetable intake (2.42 vs. 2.14 times/day for independent grocery store shoppers, p < 0.001) and lower rates of food insecurity compared to independent store shoppers (45.9% vs. 65.3% for independent grocery store shoppers, p < 0.001). Fewer independent store shoppers used their own vehicle (52.9% vs. 76.2% for chain store shoppers, p < 0.001). After adjusting for socioeconomic and demographic variables transportation access was strongly associated with increased odds of shopping at chain stores (OR = 1.89, 95% CI [1.21,2.95], p = 0.005) but food insecurity was no longer associated with grocery store type. Shopping at chain grocery stores was associated with higher fruit and vegetable intake after adjusting for covariates (1.18 times more per day, p = 0.042). Qualitative responses highlighted systemic barriers, including poor food quality, high costs, and limited transportation options, exacerbating food access inequities. Conclusions: These disparities underscore the need for targeted interventions to improve transportation options and support food security in vulnerable populations, particularly in urban areas like Detroit. Addressing these structural challenges is essential for reducing food insecurity and promoting equitable access to nutritious foods. Full article

Background and Aims: The majority of individuals with COVID-19 developed acute symptoms. Post-COVID-19 syndrome refers to the signs and symptoms of COVID-19 that persist for more than 12 weeks. The present study was conducted to estimate the prevalence and risk factors for post-COVID-19 syndrome in the Omani population. Methods: This is a cross-sectional study that was conducted at the University Hospital Center (UHC). All patients diagnosed with COVID-19 (through polymerase chain reaction PCR testing) between March 2020 and March 2022 were included. Eligible participants were interviewed through a phone call, informed about the study procedure, and invited to participate in the study. Results: The study enrolled 265 COVID-19 patients, of whom 156 (59.2%) were females and 204 (77.3%) had been vaccinated. The overall prevalence of post-COVID-19 syndrome was 48.5%. The most common symptom was fatigue (71, 26.9%), followed by joint pain (44, 16.7%). The other symptoms included loss of taste/smell (34, 12.9%), cough (32, 12.1%), palpitation (25, 9.5%), and hair loss (27, 10.2%). Unvaccinated patients showed a higher incidence of fatigue (p = 0.03) and loss of smell/taste (p = 0.01) on univariate analysis. Females were at high risk for the development of various symptoms, including fatigue, muscular pain, breathing difficulty, cough, chest pain, palpitation, headache, and hair loss. Multivariate analysis showed that female gender is a significant independent predictor (odds ratio: 3.1; p = 0.00) for the development of post-COVID-19 syndrome. Conclusions: The prevalence of post-COVID-19 syndrome among the Omani population was high, highlighting the need for targeted interventions to manage long-term symptoms in vulnerable groups. Full article

Traumatic brain injury (TBI) initiates a complex cascade of pathophysiological events that have far-reaching consequences beyond the initial injury. This review examines the current state of the literature on the mechanisms underlying neurotrauma and neuroinflammation, with particular emphasis on the molecular cross-talk between these disparate pathways that ultimately precipitates the development of chronic traumatic encephalopathy (CTE). We integrate this mechanistic knowledge with potential diagnostic biomarkers, such as glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and advances in neuroimaging and machine learning-based predictive tools. Finally, we discuss the current therapeutic approaches under investigation, and highlight which molecular targets have yet to be explored for potential therapeutic development. Full article

Starch extracted from malanga (Colocasia esculenta) is a biopolymer with considerable industrial potential thanks to its high starch content (70–80% on a dry basis) and small granule size, which give it distinctive functional properties. To expand its applications in advanced processes such as encapsulation, it is necessary to modify its structural and physicochemical characteristics. This study evaluated the effects of ultrasound (US) and chemical cross-linking (CL) on the properties of this starch. US was applied at various times and amplitudes, while CL was performed using sodium trimetaphosphate and sodium tripolyphosphate, with sodium sulfate as a catalyst. US treatment reduced particle size and increased amylose content, resulting in lower viscosity and gelatinization temperature, without affecting granule morphology. Meanwhile, CL induced phosphate linkages between starch chains, promoting aggregation and reducing amylose content and enthalpy, but increasing the gelatinization temperature. The modified starches exhibited low syneresis, making them potentially suitable for products such as pastas, baby foods, and jams. Additionally, ultrasound modification enabled the production of fine starch microparticles, which could be applied in the microencapsulation of bioactive compounds in the food and pharmaceutical industries. These findings suggest that modified malanga starch can serve as a functional and sustainable alternative in industrial applications. Full article

Scientific evidence has suggested, in most cases, that nullity of the GSTM1 and GSTT1 genes is associated with worse pathological outcomes and viral infections. In this sense, the main objective of this work was to determine the genotypic frequencies of GSTM1 and GSTT1 polymorphisms in individuals with HIV and to establish a possible relationship with CD4+ T lymphocyte count. This was a cross-sectional study, with a quantitative approach, composed of 182 HIV-positive patients. To detect GSTM1 and GSTT1 polymorphisms by the multiplex polymerase chain reaction (PCR), oral mucosa samples were collected. Regarding genotypic frequencies, GST nullity was high in the population, being 97.5% and 97.6%, respectively, for GSTM1− and GSTT1−. Although there was no association between the GST polymorphism and the viral load and CD4+ T lymphocyte counts at diagnosis, when related to the current CD4+ count, the isolated and combined null alleles, GSTT1 (ORadj: 0.219; p = 0.004), GSTM1 (ORadj: 0.219; p = 0.004), and GSTM1/T1 (ORadj: 0.219; p = 0.004), were defined as factors favorable to a minimum CD4+ T lymphocyte count of 350 cells. Therefore, this study demonstrated a probable relationship between the GSTT1 and GSTM1 genetic polymorphisms and HIV. Full article

Objectives: The present cross-sectional analysis aimed to investigate whether Large Language Model-based chatbots can be used as reliable sources of information in orthodontics by evaluating chatbot responses and comparing them to those of dental practitioners with different levels of knowledge. Methods: Eight true and false frequently asked orthodontic questions were submitted to five leading chatbots (ChatGPT-4, Claude-3-Opus, Gemini 2.0 Flash Experimental, Microsoft Copilot, and DeepSeek). The consistency of the answers given by chatbots at four different times was assessed using Cronbach’s α. Chi-squared test was used to compare chatbot responses with those given by two groups of clinicians, i.e., general dental practitioners (GDPs) and orthodontic specialists (Os) recruited in an online survey via social media, and differences were considered significant when p < 0.05. Additionally, chatbots were asked to provide a justification for their dichotomous responses using a chain-of-through prompting approach and rating the educational value according to the Global Quality Scale (GQS). Results: A high degree of consistency in answering was found for all analyzed chatbots (α > 0.80). When comparing chatbot answers with GDP and O ones, statistically significant differences were found for almost all the questions (p < 0.05). When evaluating the educational value of chatbot responses, DeepSeek achieved the highest GQS score (median 4.00; interquartile range 0.00), whereas CoPilot had the lowest one (median 2.00; interquartile range 2.00). Conclusions: Although chatbots yield somewhat useful information about orthodontics, they can provide misleading information when dealing with controversial topics. Full article