Search Results (1,524)

Background: Electroencephalography (EEG) offers millisecond-precision measurement of neural oscillations underlying human cognition and emotion. Despite extensive research, systematic frameworks mapping EEG metrics to psychological constructs remain fragmented. Objective: This interdisciplinary scoping review synthesizes current knowledge linking EEG signatures to affective and cognitive models from a neuroscience perspective. Methods: We examined empirical studies employing diverse EEG methodologies, from traditional spectral analysis to deep learning approaches, across laboratory and naturalistic settings. Results: Affective states manifest through distinct frequency-specific patterns: frontal alpha asymmetry (8–13 Hz) reliably indexes emotional valence with 75–85% classification accuracy, while arousal correlates with widespread beta/gamma power changes. Cognitive processes show characteristic signatures: frontal–midline theta (4–8 Hz) increases linearly with working memory load, alpha suppression marks attentional engagement, and theta/beta ratios provide robust cognitive load indices. Machine learning approaches achieve 85–98% accuracy for subject identification and 70–95% for state classification. However, significant challenges persist: spatial resolution remains limited (2–3 cm), inter-individual variability is substantial (alpha peak frequency: 7–14 Hz range), and overlapping signatures compromise diagnostic specificity across neuropsychiatric conditions. Evidence strongly supports integrated rather than segregated processing, with cross-frequency coupling mechanisms coordinating affective–cognitive interactions. Conclusions: While EEG-based assessment of mental states shows considerable promise for clinical diagnosis, brain–computer interfaces, and adaptive technologies, realizing this potential requires addressing technical limitations, standardizing methodologies, and establishing ethical frameworks for neural data privacy. Progress demands convergent approaches combining technological innovation with theoretical sophistication and ethical consideration. Full article

This study integrates network toxicology with molecular docking technology to systematically elucidate the key molecular mechanisms and signaling pathways by which bisphenol A (BPA) induces obesity. By cross-referencing multiple databases—including the Comparative Toxicogenomics Database (CTD), SwissTarget prediction platform, and PharmMapper—potential BPA target genes were identified, yielding a total of 1326 candidate targets. Obesity-related genes were collected from GeneCards and OMIM databases, yielding 4570 disease-associated targets. Among these, 653 overlapping genes were identified as potential mediators linking BPA exposure to obesity. Protein interaction networks were constructed using STRING and Cytoscape, and the MCC algorithm identified five core hub genes: STAT3, MYC, TP53, IL6, and mTOR. Validation using random datasets demonstrated significant upregulation of these genes in the obesity group (p < 0.05), highlighting their potential central role in BPA-induced obesity effects. Functional enrichment analysis via GO and KEGG pathways indicated that BPA may promote obesity by interfering with endocrine signaling, activating lipid metabolism, and stimulating atherosclerosis pathways. Molecular docking analysis using CB-Dock2 confirmed strong binding affinity between BPA and core targets, providing structural evidence for their potential interactions. This study elucidates the potential biological mechanism by which BPA exacerbates obesity through endocrine disruption and metabolic reprogramming, employing a multidimensional approach encompassing cross-target analysis, pathway enrichment, and molecular interactions. It provides an innovative systems toxicology framework and empirical basis for assessing metabolic health risks induced by environmental pollutants. Full article

Background: Pediatric acute myeloid leukemia (pAML) is the second most common type of childhood leukemia, behind acute lymphoblastic leukemia. High-throughput technologies have enabled the identification of increasing molecular alterations linked to AML prognosis, revealing genomic heterogeneity among individual patients and providing clinically valuable diagnostic and prognostic information. This study systematically analyzed the correlation between high-frequency mutated genes and prognosis in pAML by performing whole-transcriptome sequencing (WTS) of bone marrow samples from newly diagnosed AML children in Southwest China and mapping their genetic profiles. Methods: pAML patients treated at the Department of Hematology and Oncology, Children’s Hospital of Chongqing Medical University, from January 2015 to October 2024, were enrolled, and WTS was performed. The study described the frequency, pathogenicity classification, and risk stratification of mutation genes and fusion genes, and constructed a genetic landscape. For high-frequency pAML mutations, the impact on early induction remission rate (CR) and long-term event-free survival (EFS) was evaluated. Results: A total of 134 pediatric AML patients from Southwest China were included, with a male-to-female ratio of 74:60 and a median diagnosis age of 5.96 years. Based on pathogenicity classification using WTS, fusion genes were categorized into level 1, level 2, and level 3 genes, as well as mutation genes. The study identified five fusion genes of level 1, the most frequent being RUNX1::RUNX1T1 (32/134, 23.88%), KMT2A rearrangements (29/134, 21.64%), and CBFB::MYH11 (13/134, 9.7%). Sixteen mutation genes of level 1 were detected, seven of which recurred in over 5% of patients, including NRAS (31/134, 23.13%), FLT3 (25/134, 18.66%), KIT (24/134, 17.91%), CEBPA (14/134, 10.45%), WT1 (13/134, 9.7%), KRAS (11/134, 8.2%), and PTPN11 (7/134, 5.22%). Sex-based analysis revealed that PTPN11 mutations were significantly more frequent in males (9.45% vs. 0%, p = 0.023), as were KIT mutations (24.32% vs. 10.00%, p = 0.044). Risk-stratified analysis showed that WT1 mutations (14.13% vs. 0%, p = 0.031) and FLT3-ITD mutations (13.19% vs. 0%, p = 0.042) were enriched in intermediate- and high-risk groups, whereas CEBPA (25.64% vs. 5.43%, p = 0.012), KIT (35.90% vs. 10.87%, p = 0.003), and KIT-E8 (20.51% vs. 1.10%, p < 0.001) mutations were more prevalent in low-risk groups. Prognostic analysis indicated that PTPN11 and KIT mutations did not affect CR or EFS across sexes, nor did WT1, CEBPA, or KIT mutations influence outcomes by risk stratification. However, FLT3-ITD-positive patients had significantly lower CRs (χ² value = 11.965, p = 0.007), although EFS differences were nonsignificant. In contrast, WT1 mutations were associated with inferior EFS compared to wild-type (p = 0.036). Furthermore, the univariate and multivariate Cox regression revealed consistent results with the above findings, indicating that WT1 mutation was an independent adverse prognostic factor for EFS (HR = 2.400, 95% CI: 1.101–5.233, p = 0.028). The results of univariate and multivariate logistic regression analyses also confirmed that FLT3-ITD mutation was an independent predictor of initial treatment response in our cohort (OR = 10.699, 95% CI: 2.108–54.302, p = 0.004). Conclusions: This study delineated the genetic landscape of pAML in Southwest China and explored the prognostic value of gene fusions and mutations in early and long-term outcomes. These findings provide a foundation for understanding the genetic heterogeneity of pAML and offer evidence for the development of precision medicine approaches. Full article

Agri-food supply chains, particularly in the rice sector, face persistent challenges in transparency, quality control, and sustainability due to their complexity and fragmentation. Blockchain technology provides a promising solution by ensuring secure, immutable, and verifiable records of production and supply chain activities, supporting both consumer trust and compliance with the EU Common Agricultural Policy (CAP). This study reports on the TRACE-RICE Mediterranean pilot project, which developed a blockchain-enabled traceability system for rice production in Portugal. A Rice Field Data Recording App, built with ArcGIS Survey123, digitized agronomic and compliance records from Integrated Production systems and linked them to blockchain-verified QR codes on consumer packaging. The pilot conducted during the 2023 harvest demonstrated the potential to enhance data consistency and streamline field recording processes, thereby improving transparency in farming practices. A total of 174 QR code interactions, primarily from Lisbon, revealed consumer engagement patterns valuable for future business analysis. The scaling phase during the 2024 harvest confirmed the system’s adaptability to different varieties and production contexts, positioning blockchain as a replicable model for sustainable and competitive rice supply chains. Full article

Carbon emissions from the manufacturing sector have long been a critical environmental concern. New quality productive forces (NEP), which integrate advanced technologies and innovative practices to enhance production efficiency while reducing environmental impact, provide robust support for the green and sustainable development of manufacturing. However, previous studies have not established empirical evidence linking NEP to manufacturing carbon emission intensity (CEI), nor have they identified the underlying transmission channels. This study makes a methodological innovation by explicitly differentiating technological innovation into disruptive and progressive categories to examine their distinct mediating roles. Using panel data from 30 Chinese provinces from 2012 to 2021, we investigate the direct, heterogeneous, and spatial effects of NEP on CEI, along with the mediating effects of different innovation types. The results demonstrate that NEP significantly reduces CEI, and this finding remains robust after addressing endogeneity concerns and conducting comprehensive robustness checks. Mechanism analysis reveals that NEP achieves emission reduction primarily through promoting disruptive innovation—fundamental shifts in operational paradigms that substantially reduce environmental footprints. Heterogeneity analysis indicates the strongest emission reduction effect in central China. Based on these findings, we propose targeted policy recommendations: cultivating NEP as a fundamental driver, accelerating green technology industrialization, establishing a three-dimensional policy framework integrating innovation incentives, market regulation, and supervisory safeguards, and implementing regionally differentiated strategies. These approaches provide actionable pathways for achieving China’s dual-carbon goals and promoting sustainable manufacturing development. Full article

Time-sensitive networking (TSN), a cutting-edge technology enabling efficient real-time communication and control, provides strong support for traditional Ethernet in terms of real-time performance, reliability, and deterministic transmission. In TSN systems, although time-triggered (TT) flows enjoy deterministic delay guarantees, audio video bridging (AVB) and best effort (BE) traffic still share link bandwidth through statistical multiplexing, a process that remains nondeterministic. This competition in shared memory switches adversely affects data transmission performance. In this paper, a priority queue threshold control policy is proposed and analyzed for mixed-critical traffic in time-sensitive networks. The core of this policy is to set independent queues for different types of traffic in the shared memory queuing system. To prevent low-priority traffic from monopolizing the shared buffer, its entry into the queue is blocked when buffer usage exceeds a preset threshold. A two-dimensional Markov chain is introduced to accurately construct the system’s queuing model. Through detailed analysis of the queuing model, the truncated chain method is used to decompose the two-dimensional state space into solvable one-dimensional sub-problems, and the approximate solution of the system’s steady-state distribution is derived. Based on this, the blocking probability, average queue length, and average queuing delay of different priority queues are accurately calculated. Finally, according to the optimization goal of the overall blocking probability of the system, the optimal threshold value is determined to achieve better system performance. Numerical results show that this strategy can effectively allocate the shared buffer space in multi-priority traffic scenarios. Compared with the conventional schemes, the queue blocking probability is reduced by approximately 40% to 60%. Full article

The Internet of Vehicles (IoV) provides an effective solution for alleviating traffic congestion and enhancing road safety. However, shared traffic messages in IoV may deviate from on-road conditions due to self-interest protection or insufficient sensor performance. Therefore, evaluating the trustworthiness of shared messages is essential for vehicles to make informed decisions. To this end, a truth-oriented trust model for shared traffic message is proposed, which is inspired by human trust establishment mechanisms (HS-TEMs). Firstly, we quantify the integrated trust value (I-VT) of the message sender by fusing self-experience-based vehicle trust (SEB-VT) and peer-recommendation-based vehicle trust (PRB-VT). In SEB-VT, a sample-size-dependent smoothing factor dynamically trades off prior information and empirical evidence, reducing instability under small-sample conditions. In PRB-VT, we employ link analysis to compute the reference degree of recommendation information, which mitigates biases arising from subjective cognitive limitations. Secondly, with the I-VT of vehicles, we calculate event trust (ET) by differentiating message attitudes and quantifying their relative influence, which effectively reduces the impact of individual bias on the final judgment. The simulation results show that HS-TEM can accurately and fairly evaluate the credibility of messages, which helps vehicles make informed decisions. Full article

Background: Pelvic autonomic nerve injury during colorectal surgery causes debilitating urinary, bowel, and sexual dysfunction. This review synthesizes contemporary evidence on neuroanatomy, nerve-sparing techniques, and functional outcomes to minimize iatrogenic injury while maintaining oncologic efficacy. Methods: Systematic analysis of cadaveric studies, clinical trials, and imaging advancements focused on the superior hypogastric plexus, hypogastric nerves, pelvic splanchnic nerves (S2–S4), and inferior hypogastric plexus. Surgical innovations evaluated included robotic-assisted dissection, fluorescence-guided visualization, and intraoperative neuromonitoring. We distinguished evidence for nerve identification from evidence for functional protection and graded study designs accordingly. Results: Anatomical variability (e.g., superior hypogastric plexus leftward deviation 58.8%; hypogastric nerve median width 3.5 mm) necessitates precision techniques. Nerve-sparing approaches reduce urinary dysfunction from 30–70% to 10–30% and sexual dysfunction from 40–80% to 15–30%. However, the functional benefit of specific technical steps is often derived from anatomical rationale and cohort studies, with limited randomized trials for individual maneuvers. While technique refinements such as Denonvilliers’ fascia preservation may offer early sexual function benefits, randomized evidence shows no 12-month urinary advantage and uncertainty regarding longer-term durability; routine adoption should be individualized. Advanced imaging (3 T MRI, diffusion tensor imaging) and fluorescence guidance improve pre-/intraoperative visualization, but randomized evidence for improved postoperative urinary or sexual function is limited. Randomized data support pelvic intraoperative neuromonitoring in reducing urinary deterioration; most adjuncts have observational or feasibility-level support. Conclusions: Integrating neuroanatomical knowledge with advanced technologies enhances identification and may support nerve-sparing execution; however, robust randomized evidence for durable functional protection of novel technologies and specific technical steps remains limited. Priorities include standardizing preservation protocols, conducting randomized trials that validate the efficacy of individual surgical maneuvers, linking identification to functional outcomes, and validating long-term patient-reported outcomes. Full article

Artificial intelligence technology is profoundly reshaping the aviation field, driving the accelerated evolution of air confrontation patterns toward intelligence and autonomy. Given that experimental aircraft platforms are key means to verify intelligent air confrontation technologies, this paper—on the basis of systematically sorting out the progress of intelligent technologies in the air confrontation domain at home and abroad—first focuses on analyzing the connotation, technological evolution path, and application prospects of experimental aircraft platforms, and deeply interprets the technological breakthroughs and application practices of typical experimental platforms such as X-37B and X-62A in the field of artificial intelligence integration. Furthermore, through the analysis of three typical air confrontation projects, it reveals the four core advantages of experimental aircraft platforms in intelligent technology research: efficient iterative verification, risk reduction, promotion of capability emergence, and provision of flexible carriers. Finally, this paper focuses on constructing a technical implementation framework for the deep integration of intelligent technologies and flight tests, covering key links such as requirement analysis and environmental test design, construction of intelligent test aircraft platforms and capability generation, ground verification, and test evaluation, and summarizes various key technologies involved in the technical implementation framework. This study can provide theoretical support for the deep integration of artificial intelligence technology and the aviation field, including an engineering path from intelligent algorithm design, verification to iterative optimization, supporting the transformation of air confrontation patterns from “human-in-the-loop” to “autonomous gaming,” thereby enhancing the intelligence level and actual confrontation effectiveness in the aviation field. Full article

Embodied energy flows link production systems with the energy sector, reflecting dependencies and structural risks under globalization and regional coordination. Guangdong, China’s most manufacturing-intensive, open, and energy-consuming province, is a central hub in both global value chains and domestic production networks, playing a pivotal role in national energy security. Understanding Guangdong’s embodied energy flows is essential for revealing the transmission of energy across multi-level spatial systems and the resilience of China’s energy infrastructure. This study integrates international (EXIOBASE) and Chinese inter-provincial input–output data to build a province-level nested global MRIO model, combined with Structural Path Analysis (SPA), to characterize Guangdong’s manufacturing embodied energy flows in domestic and international dual circulation from 2002 to 2017. Our findings confirm Guangdong’s pivotal bridging role in embodied energy transfers. First, flows are dual-directional and dominated by international transfers. Second, energy efficiency has improved, narrowing the intensity gap between export- and domestic-oriented industries. Third, flows have diversified spatially from concentration in developed regions toward developing regions, with domestic inter-provincial flows more dispersed. Finally, embodied energy remains highly concentrated across sectors, with leading industries shifting from labor- and capital-intensive to capital- and technology-intensive sectors. This research offers vital empirical evidence and policy reference for enhancing national energy security and optimizing spatial energy allocation. Full article

The quality of heavy plates produced from low-carbon steel is directly linked to the structural characteristics inherited from the initial continuously cast thick slabs. This study explores how different casting technologies affect the morphology and distribution of allotriomorphic ferrite along prior austenite grain boundaries (PAGBs) within these slabs. Using quantitative microstructural analysis based on advanced computer vision techniques (OpenCV), the research identifies significant variations in ferrite boundary thickness and volume fraction associated with different casting methods. These microstructural differences strongly correlate with variations in Charpy V-notch impact energy (KVZ20) and susceptibility to microcrack formation during subsequent rolling processes. The results obtained allow us to evaluate the influence of the cast structure on the formation of the initial structural characteristics of the material, especially on the formation of microcracks of the slab microstructure and their propagation during further processing. Full article

This study explores how digitalization by focal firms affects carbon performance across the entire supply chain, advancing the literature by adopting a holistic supply chain perspective rather than a single-firm lens. We further draw on dynamic capability theory to explain the mechanisms through which digitalization enhances supply chain carbon performance. Based on an unbalanced panel dataset of Chinese listed firms from 2008 to 2022, we construct a three-tier supply chain panel linking upstream, focal, and downstream firms. The benchmark regression results show that focal firm digitalization significantly enhances overall supply chain carbon performance. Mechanism analyses identify two critical transmission channels: (1) optimizing supply chain resource allocation efficiency, through improved inventory turnover and strengthened supply chain finance; and (2) enabling collaborative technological upgrading, by enhancing the total factor productivity of upstream and downstream partners. Further heterogeneity analysis reveals that the effect of digitalization on improving carbon performance is more pronounced in regions with stronger environmental regulation and in non-regulated industries. In addition, we analyze the moderating role of the Supply-Chain Pilot-Cities Program. The findings provide practical insights for firm managers globally seeking to leverage digitalization for supply chain decarbonization and for policymakers across jurisdictions aiming to design supportive mechanisms that facilitate digital and green integration. Full article

Background/Objective: Milk and fermented dairy products are widely consumed functional foods and beverages, offering not only essential nutrients but also bioactive compounds with potential to modulate host immunity, metabolism, and the gut microbiome. This narrative review aims to synthesize current knowledge on the relationship between dairy consumption, gut microbiome, immune modulation, adverse reactions to food, physical performance and cardiometabolic health. Methods: An extensive literature analysis was conducted to explore how milk and fermented dairy products modulate the gut microbiome and influence the immune and cardiometabolic health. This study synthesis focused on key dairy bioactive compounds, such as probiotics, miRNAs, milk-derived peptides and exosomes and on evaluating their proposed mechanisms of action in inflammation and metabolic regulation, and their possible influence on physical performance through gut–microbiome interactions. Additionally, advances in metagenomic and metabolomic technologies were reviewed for their potential to uncover host–microbiota interactions relevant to precision nutrition strategies. Results: Fermented dairy products have shown potential in promoting beneficial bacteria growth such as Lactobacillus and Bifidobacterium, short-chain fatty acid synthesis and reduction in proinflammatory biomarkers. Specific dairy-derived peptides and exosomal components may further support gut barrier integrity, immune regulation and improve physical performance and reduce cardiometabolic risk factors. Additionally, emerging evidence links individual gut microbiota profiles to specific metabolic responses, including tolerance to lactose and bovine milk proteins. Conclusions: Integrating microbiome science with traditional nutritional paradigms enhances our understanding of how dairy influences immune and cardiometabolic health. Overall, current evidence suggests that investigating dairy-microbiome interactions, alongside lifestyle factors such as physical activity, may inform future personalized nutrition strategies aimed at supporting metabolic and immune health. Full article

In recent years, the global energy crisis, concerns about energy security and grid parity, and the pressure to develop policies for reducing the environmental impact of anthropogenic activities have accelerated investments in renewable energy. A growing body of literature applies the real options approach (ROA) to renewable energy projects, recognizing its value in capturing irreversibility and flexibility under uncertainty. The present work provides a detailed state-of-the-art analysis on the adoption of real options to evaluate mixes of energy technologies for power generation, with a special emphasis on investments in hydropower and solar photovoltaics. The objective is to assess current applications, identify knowledge gaps, and outline priorities for advancing decision-making tools in this domain. We performed a systematic literature review following the PRISMA protocol, identifying 38 papers from the Scopus database up to February 2024. Eligible studies were peer-reviewed articles in English applying the ROA to power generation, following a technology selection process; policy evaluation or research and development studies were excluded. The selected papers were analyzed to identify trends over time and space, adopted energy technology, types of real options with valuation methods, and sources of uncertainty. The present paper also discusses the main findings and emerging gaps, providing an overview of hybrid renewable energy systems. Our analysis suggests that, despite the significant advances achieved in this area, further research is needed to exploit the potential of the ROA in investment decisions for combined renewable energy technologies, especially in cases where internal uncertainty and community perspectives need to be explicitly considered. By linking the ROA to the challenges of mixed renewable energy projects, this study enhances understanding of investment decision-making under uncertainty and identifies pathways toward more robust and adaptive project evaluation. Full article

6G low-power and lossy network (6G LLN) is a kind of distributed network designed for IoT and edge computing scenarios of the sixth-generation mobile communication technology. Its routing technologies should fully consider characteristics of green and low carbon, constrained nodes, lossy links, etc. This paper proposes an improved routing protocol for low-power and lossy networks (I-RPL) to better suit the characteristics of 6G LLN and meet its application requirements. I-RPL has designed new context-aware routing metrics, which include the residual energy indicator, buffer utilization ratio, ETX, delay, and hop count to meet multi-dimensional network QoS requirements. The candidate parent and its preferred parent’s residual energy indicator and buffer utilization ratio are calculated recursively to reduce the effect of upstream parents. ETX and delay calculating methods are improved to ensure a better performance. Moreover, I-RPL has optimized the network construction process to improve energy and protocol efficiency. I-RPL has designed scientific multiple routing metrics evaluation theories (Lagrangian multiplier theories), proposed new rank computing and optimal route selecting mechanisms to simplify protocol, and optimized broadcast suppression and network reliability. Finally, theoretical analysis and experiment results show that the average end-to-end delay of I-RPL is 13% lower than that of RPL; the average alive node number increased 11% and so on. So, I-RPL can be applied well to the 6G LLN and is superior to RPL and its improvements. Full article