Search Results (1,164)

Accurately predicting the compressive strength of high-performance concrete (HPC) is critical for ensuring structural integrity and promoting sustainable construction practices. However, HPC exhibits highly complex, nonlinear, and multi-factorial interactions among its constituents (such as cement, aggregates, admixtures, and curing conditions), which pose significant challenges to conventional predictive models. Traditional approaches often fail to adequately capture these intricate relationships, resulting in limited prediction accuracy and poor generalization. Moreover, the high dimensionality and noisy nature of HPC mix data increase the risk of model overfitting and convergence to local optima during optimization. To address these challenges, this study proposes a novel bio-inspired hybrid optimization model, AP-IVYPSO-BP, which is specifically designed to handle the nonlinear and complex nature of HPC strength prediction. The model integrates the ivy algorithm (IVYA) with particle swarm optimization (PSO) and incorporates an adaptive probability strategy based on fitness improvement to dynamically balance global exploration and local exploitation. This design effectively mitigates common issues such as premature convergence, slow convergence speed, and weak robustness in traditional metaheuristic algorithms when applied to complex engineering data. The AP-IVYPSO is employed to optimize the weights and biases of a backpropagation neural network (BPNN), thereby enhancing its predictive accuracy and robustness. The model was trained and validated on a dataset comprising 1,030 HPC mix samples. Experimental results show that AP-IVYPSO-BP significantly outperforms traditional BPNN, PSO-BP, GA-BP, and IVY-BP models across multiple evaluation metrics. Specifically, it achieved an R² of 0.9542, MAE of 3.0404, and RMSE of 3.7991 on the test set, demonstrating its high accuracy and reliability. These results confirm the potential of the proposed bio-inspired model in the prediction and optimization of concrete strength, offering practical value in civil engineering and materials design. Full article

This critical review synthesizes evidence on the multifactorial coupling mechanisms and time-dependent evolution of lateral pressure in concrete formworks, addressing significant limitations in current design standards (GB50666, CIRIA 108, ACI 347). Through a structured analysis of 60+ experimental and theoretical studies, we establish that lateral pressure is governed by nonlinear interactions between concrete rheology, casting dynamics, thermal conditions, and formwork geometry. The key findings reveal that (1) casting rate increments >5 m/h amplify peak pressure by 15–27%, while SCC thixotropy (Athix > 0.5) reduces it by 15–27% at <5 m/h; (2) secondary vibration induces 52–61% pressure surges through liquefaction; and (3) sections with a width >2 m exhibit 40% faster pressure decay due to arching effects. (4) Temporal evolution follows three distinct phases—rapid rise (0–2 h), slow decay (2–10 h), and sharp decline (>10 h)—with the temperature critically modulating transition kinetics. Crucially, the existing codes inadequately model temperature dependencies, SCC/HPC rheology, and high-speed casting (>10 m/h). This work proposes a parameter-specific framework integrating rheological thresholds (Athix, Rstr), casting protocols, and real-time monitoring to enhance standard accuracy, enabling an optimized formwork design and risk mitigation in complex scenarios, such as water conveyance construction and slipforming. Full article

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

Against the backdrop of multifaceted strategies to combat climate change, understanding soil erosion’s role in carbon cycling is critical due to terrestrial carbon pool vulnerability. This study integrates bibliometric methods with visualization tools (CiteSpace, VOSviewer) to analyze 3880 Web of Science core publications (1994–2024, inclusive), constructing knowledge graphs and forecasting trends. The results show exponential publication growth, shifting from slow development (1994–2011) to rapid expansion (2012–2024), aligning with international climate policy milestones. The Chinese Academy of Sciences led productivity (519 articles), while the US demonstrated major influence (H-index 117; 52,297 citations), creating a China–US bipolar research pattern. It was also found that Dutch journals dominate this research field. A keyword analysis revealed a shift from erosion-driven carbon transport to ecosystem service assessments. Emerging hotspots include microbial community regulation, climate–erosion feedback, and model–policy integration, though developing country collaboration remains limited. Future research should prioritize isotope tracing, multiscale modeling, and studies in ecologically vulnerable regions to enhance global soil carbon management. This study provides a novel analytical framework and forward-looking perspective for the soil erosion research on soil carbon cycling, serving as an extension of climate change mitigation strategies. Full article

Coarse-grained soils serve as essential fill materials in earth–rock dam engineering, where their mechanical properties critically influence dam deformation and stability, directly impacting project safety. Artificial intelligence (AI) techniques are emerging as powerful tools for predicting the mechanical properties of coarse-grained soils. However, AI-based prediction models for these properties face persistent challenges, particularly in parameter tuning—a process requiring substantial computational resources, extensive time, and specialized expertise. To address these limitations, this study proposes a novel prediction model that integrates Adaptive Simulated Annealing (ASA) with an improved Particle Swarm Optimization (PSO) algorithm to optimize the Elman Neural Network (ENN). The methodology encompasses three key aspects: First, the standard PSO algorithm is enhanced by dynamically adjusting its inertial weight and learning factors. The ASA algorithm is then employed to optimize the Adaptive PSO (APSO), effectively mitigating premature convergence and local optima entrapment during training, thereby ensuring convergence to the global optimum. Second, the refined PSO algorithm optimizes the ENN, overcoming its inherent limitations of slow convergence and susceptibility to local minima. Finally, validation through real-world engineering case studies demonstrates that the ASA-PSO-optimized ENN model achieves high accuracy in predicting the mechanical properties of coarse-grained soils. This model provides reliable constitutive parameters for stress–strain analysis in earth–rock dam engineering applications. Full article

The usage of fossil fuels has resulted in increasingly severe environmental problems, such as climate change, air pollution, water pollution, etc. Hydrogen energy is considered one of the most promising clean energies to replace fossil fuels due to its pollution-free and high-heat properties. However, the oxygen evolution reaction (OER) remains a critical challenge due to its high overpotential and slow kinetics during water electrolysis for hydrogen production. Electrocatalysts play an important role in lowering the overpotential of OER and promoting the kinetics. Co₃O₄-based electrocatalysts have emerged as promising candidates for the oxygen evolution reaction (OER) due to their favorable catalytic activity and good compatibility compared with precious metal-based electrocatalysts. This review presents a summary of the recent developments in the synthesis strategies and mechanisms of Co₃O₄-based electrocatalysts for the OER. Various synthesis strategies have been explored to control the size, morphology, and composition of Co₃O₄ nanoparticles. These strategies enable the fabrication of well-defined nanostructures with enhanced catalytic performance. Additionally, the mechanisms of OER catalysis on Co₃O₄-based electrocatalysts have been elucidated. Coordinatively unsaturated sites, synergistic effects with other elements, surface restructuring, and pH dependency have been identified as crucial factors influencing the catalytic activity. The understanding of these mechanisms provides insights into the design and optimization of Co₃O₄-based electrocatalysts for efficient OER applications. The recent advancements discussed in this review offer valuable perspectives for researchers working on the development of electrocatalysts for the OER, with the goal of achieving sustainable and efficient energy conversion and storage systems. Full article

Achieving sustainable development goals remains a core issue in global development. In response, China has proposed the development of new quality productive forces (NQPFs) through innovative thinking, emphasizing that fostering NQPFs is both an intrinsic requirement and a pivotal focus for advancing high-quality development. Concurrently, the intelligent transformation of the manufacturing sector serves as a critical direction for China’s economic restructuring and upgrading. This paper places “new quality productive forces” and “intelligent transformation of manufacturing” within the same analytical framework. Starting from the logical chain of “new quality productive forces—three major mechanisms—intelligent transformation of manufacturing,” it concretizes the value implications of new quality productive forces into a systematic conceptual framework driven by the synergistic interaction of three major mechanisms: the mechanism of revolutionary technological breakthroughs, the mechanism of innovative allocation of production factors, and the mechanism of deep industrial transformation and upgrading. This study constructs a “3322” evaluation index system for NQPFs, based on three formative processes, three driving forces, two supporting systems, and two-dimensional characteristics. Simultaneously, it builds an evaluation index system for the intelligent transformation of manufacturing, encompassing intelligent technology, intelligent applications, and intelligent benefits. Using national time-series data from 2012 to 2023, this study assesses the development levels of both NQPFs and the intelligent transformation of manufacturing during this period. The study further analyzes the impact of NQPFs on the intelligent transformation of the manufacturing sector. The research results indicate the following: (1) NQPFs drive the intelligent transformation of the manufacturing industry through the three mechanisms of innovative allocation of production factors, revolutionary breakthroughs in technology, and deep transformation and upgrading of industries. (2) The development of NQPFs exhibits a slow upward trend; however, the outbreak of the pandemic and Sino-US trade frictions have caused significant disruptions to the development of new-type productive forces. (3) The level of intelligent manufacturing continues to improve; however, from 2020 to 2023, due to the impact of the COVID-19 pandemic and Sino-US trade conflicts, the level of intelligent benefits has slightly declined. (4) NQPFs exert a powerful driving force on the intelligent transformation of manufacturing, exerting a significant positive impact on intelligent technology, intelligent applications, and intelligent efficiency levels. Full article

This paper examines Krivelj, a copper mining village in Serbia, as a critical yet overlooked node within global extractive networks. Despite supplying copper essential for renewable energy and sustainable architecture, Krivelj experiences severe ecological disruption, forced relocations, and socio-spatial destabilization, becoming a “sacrifice zone”—an area deliberately subjected to harm for broader economic interests. Employing a hybrid methodology that combines ethnographic fieldwork with Geographic Information Systems (GISs), this study spatializes narratives of extractive violence collected from residents through walking interviews, field sketches, and annotated aerial imagery. By integrating satellite data, legal documents, environmental sensors, and lived testimonies, it uncovers the concept of “slow violence,” where incremental harm occurs through bureaucratic neglect, ambient pollution, and legal ambiguity. Critiquing the abstraction of Planetary Urbanization theory, this research employs countertopography and forensic spatial analysis to propose a counter-cartographic framework that integrates geospatial analysis with local narratives. It demonstrates how global mining finance manifests locally through tangible experiences, such as respiratory illnesses and disrupted community relationships, emphasizing the potential of counter-cartography as a tool for visualizing and contesting systemic injustice. Full article

Vitamin D is the only vitamin that is conditionally essential, as it is synthesized from precursors after UV light exposure, whilst also being obtained from the diet. It has numerous health benefits, with deficiency becoming a major concern globally, such that dietary supplementation has more recently achieved vital importance to maintain satisfactory levels. In recent years, measurements made from blood have, therefore, become critical to determine the status of vitamin D levels in individuals and the larger population. Tests for vitamin D have routinely relied on laboratory analysis with sophisticated equipment, often being slow and costly, whilst rapid immunoassays have suffered from poor specificity and sensitivity. Here, we have evaluated a new rapid immunoassay test on the market (Rapi-D & IgLoo) to quickly and accurately measure vitamin D levels in small capillary blood specimens and compared this to measurements made using the standard laboratory method of liquid chromatography and mass spectrometry. Our results show that vitamin D can be measured very quickly and over a broad range using the new method, as well as correlate relatively well with standard laboratory testing; however, it cannot be fully relied upon currently to accurately diagnose deficiency or sufficiency in individuals. Our statistical and comparative analyses find that the rapid immunoassay with digital quantification significantly overestimates vitamin D levels, leading to diminished diagnosis of vitamin D deficiency. The speed and simplicity of the rapid method will likely provide advantages in various healthcare settings; however, further calibration of this rapid method and testing parameters for improving quantification of vitamin D from capillary blood specimens is required before integration of it into clinical decision-making pathways. Full article

Osteochondritis Dissecans (OCD) is a joint condition characterized by damage to the surface of the joint and the underlying subchondral bone, leading to early-onset osteoarthritis. It predominantly affects the knee, elbow, and ankle, with higher prevalence in juveniles actively participating in sports, which complicates the condition due to slow healing processes and prolonged restrictions on physical activities. This review aims to summarize current knowledge on OCD in athletes, with emphasis on sport-specific risk factors, diagnosis, and treatment, to support clinical decision-making and future research. We conducted searches in the PubMed and Embase databases, covering the period from 2014 to 2024. The keywords used in the search covered most common sports in combination with term osteochondritis dissecans. This review examines the impacts of various sports on the development of OCD, analyzing prevalence and risk factors, with a focus on sports-specific risks across athletic disciplines like football, basketball, baseball, and gymnastics. The significance of early detection, intervention, and sport-specific conditioning is underscored to prevent the condition and manage it effectively. Moreover, the review highlights the positive prognosis for athletes, particularly adolescents, recovering from OCD, with a high rate of return to sport. Understanding the sports-specific risks, ensuring early intervention, and adopting a cautious, stepwise return to sport are critical for managing OCD effectively, thereby safeguarding the health and careers of athletes. Full article

Over 40% of freshwater fish species in Europe are currently at risk of extinction, highlighting the need for improved conservation planning. This study examines whether the threat status is associated with life-history and ecological traits across 580 autochthonous (native and endemic) freshwater fish species in European inland waters. Using data from FishBase and the IUCN Red List, we assessed associations between threat level and both categorical (e.g., migratory behavior, commercial importance, reproductive guild, and body shape) and numerical traits (e.g., maximum length, weight, age, growth parameters, and maturity traits). Significant, though modest, associations were identified between species threat level and migratory behavior and reproductive guild. Non-migratory species exhibited higher median threat levels, while amphidromous species showed a non-significant trend toward higher threat, suggesting that limited dispersal ability and dependence on fragmented freshwater networks may increase extinction vulnerability. Species with unclassified reproductive strategies also showed elevated threat levels, possibly reflecting both actual risk and underlying data gaps. In contrast, body shape and trophic level were not significantly associated with threat status. Critically Endangered species tend to be larger, heavier, and mature later—traits characteristic of slow life history strategies that limit population recovery. Although length at maturity and maximum age did not differ significantly among IUCN categories, age at maturity was significantly higher in more threatened species, and growth rate (K) was negatively correlated with threat level. Together, these patterns suggest that slower-growing, later-maturing species face elevated extinction risk. Overall, the findings underscore that the threat level in European freshwater fish is shaped by complex interactions between intrinsic biological traits and external pressures. Trait-based approaches can enhance extinction risk assessments and conservation prioritization, especially in data-deficient freshwater ecosystems facing multifaceted environmental challenges. Full article

Drought is one of the most complex natural hazards, characterized by its slow onset, persistent nature, diverse sectoral impacts (e.g., agriculture, water resources, ecosystems), and dependence on meteorological, hydrological, and socioeconomic factors. Over the years, significant scientific effort has been devoted to developing methodologies that address its multifaceted nature, reflecting the interdisciplinary challenges of drought analysis. However, previous reviews have typically focused on individual methods, while this study presents a unified, multidisciplinary framework that integrates multiple drought analysis methods and links them to key factors guiding method selection. To address this gap, five widely used methods—index-based, remote sensing, threshold-level methods (TLM), impact-based methods, and the storyline approach—are critically evaluated from a multidisciplinary perspective. In addition, the study examines spatial and temporal trends in scientific publications, illustrating how the application of these methods has evolved over time and across regions. The primary objective of this review is twofold: (1) to provide a holistic, state-of-the-art synthesis of these methods, their applications, and their limitations; and (2) to evaluate and prioritize the critical decision-making factors, including drought type, data type/availability, study scale, and management objectives that influence method selection. By bridging this gap, the paper offers a conceptual decision-support framework for selecting context-appropriate drought analysis methods. However, challenges remain, including the vast diversity of methods beyond the scope of this review and the limited consideration of less influential factors such as user expertise, computational resources, and policy context. The paper concludes with insights and recommendations for optimizing method selection under varying circumstances, aiming to support both drought research and effective policy implementation. Full article

Segregative phase separation technology demonstrates substantial potential for precise molecular fractionation in food and biomaterial applications. The investigation elucidates the causal relationship between viscosity variations and phase separation dynamics, which govern molecular fractionation in GA/HPMC composite systems. By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. Further mechanistic investigation revealed that elevated HPMC viscosity enhances thermodynamic incompatibility while slowing interfacial mass transfer, synergistically driving component redistribution. These findings establish a quantitative viscosity–fractionation relationship, offering theoretical insights for optimizing GA/HPMC systems in emulsion stabilization, microencapsulation, and functional biopolymer purification via viscosity-mediated phase engineering. Full article

Background and Clinical Significance: Myxoid liposarcoma (MLS) is a malignant soft tissue tumor that often presents as a painless, slow-growing mass and is known for its atypical extrapulmonary metastatic pattern. Although sciatic nerve involvement is rare, when present, it usually causes neurologic symptoms. In this case, a large MLS silently expanded and completely encased the sciatic nerve without causing deficits, highlighting the importance of early imaging, multidisciplinary planning, and individualized surgical strategy in managing complex soft tissue sarcomas. Case Presentation: This case report describes a 67-year-old male with a 30 cm encapsulated myxoid liposarcoma of the posterior left thigh. The tumor had grown insidiously over one year and completely encased the sciatic nerve without causing pain, paresthesia, or motor impairment. Selective embolization was performed preoperatively to minimize blood loss. A posteromedial surgical approach allowed for en bloc resection with negative margins and preservation of sciatic nerve integrity. Histopathology confirmed a myxoid liposarcoma composed primarily of spindle-shaped tumor cells. The patient experienced no postoperative complications or neurologic deficits. At the two-year follow-up, he remains disease-free with full functional recovery. Conclusions: This case illustrates the potential for large, asymptomatic myxoid liposarcomas to encase critical neurovascular structures without infiltration. Preoperative embolization as part of a multidisciplinary plan was key to achieving safe resection and excellent functional outcomes. Full article

Bruton Tyrosine Kinase (BTK) has emerged as a critical mediator in the pathophysiology of neuroinflammation associated with neurodegenerative diseases. BTK, a non-receptor tyrosine kinase predominantly expressed in cells of the hematopoietic lineage, modulates B-cell receptor signaling and innate immune responses, including microglial activation. Recent evidence implicates aberrant BTK signaling in the exacerbation of neuroinflammatory cascades contributing to neuronal damage in disorders such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, ischemic stroke, and Huntington’s disease. Pharmacological inhibition of BTK has shown promise in attenuating microglial-mediated neurotoxicity, reducing pro-inflammatory cytokine release, and promoting neuroprotection in preclinical models. BTK inhibitors, originally developed for hematological malignancies, demonstrate favorable blood–brain barrier penetration and immunomodulatory effects relevant to central nervous system pathology. This therapeutic approach may counteract detrimental neuroimmune interactions without broadly suppressing systemic immunity, thus preserving host defense. Ongoing clinical trials are evaluating the safety and efficacy of BTK inhibitors in patients with neurodegenerative conditions, with preliminary results indicating potential benefits in slowing disease progression and improving neurological outcomes. This review consolidates current knowledge on BTK signaling in neurodegeneration and highlights the rationale for BTK inhibition as a novel, targeted therapeutic strategy to modulate neuroinflammation and mitigate neurodegenerative processes. Full article