Search Results (2,201)

This paper addresses the core issue of the imbalance between supply and demand for high-level medical–engineering integration talents under the “Healthy China” strategy in the AI+ era. Based on human capital theory and innovation capital theory, it constructs a six-dimensional collaborative theoretical model for the cultivation of medical–engineering integration postgraduates, driven by high-quality employment and guided by innovative financial capital. This model breaks through the disciplinary barriers and institutional constraints of traditional postgraduate education and for the first time creates a knowledge graph curriculum system for medical–engineering interdisciplinary studies. It also establishes a multi-dimensional evaluation index system that integrates the appreciation of innovation capital and the premium of human capital. Through the case of the six-dimensional collaborative research and development and transformation of intelligent medical equipment by our research group, the feasibility and promotion value of this new paradigm for future postgraduate education have been fully verified. Full article

Continual learning (CL) is a key technology for enabling data-driven autonomous guidance systems to operate stably and persistently in complex and dynamic environments. Its core goal is to enable the model to continuously learn new scenarios and tasks after deployment, without forgetting existing knowledge, and finally achieving stable decision-making in the different scenarios over a long period. This paper proposes a continual learning method that combines feature-generation-replay with Mixture-of-Experts and Low-Rank Adaptation (MoE-LoRA). This method retains the key features of historical tasks by feature repla and realizes the adaptive selection of old and new knowledge by the Mixture-of-Experts (MoE), which alleviates the conflict between knowledge while ensuring learning efficiency. In the comparison experiments, we compared the proposed method with the representative continual learning methods, and the experimental results show that our method outperforms the representative continual learning methods, and the ablation experiments further demonstrate the role of each component. This work provides technical support for the long-term maintenance and new task expansion of data-driven autonomous guidance systems, laying a foundation for their stable operation in complex, variable real-world scenarios. Full article

Lumpy Skin Disease Virus (LSDV), a member of the poxvirus family, represents a significant threat to global cattle industries. This review presents an analysis of LSDV-encoded proteins and their interactions with host systems, elucidating the molecular mechanisms governing viral life cycle progression and immune evasion strategies. We provide detailed characterization of the complex architecture of LSDV virions, including Intracellular Mature Virus (IMV), Extracellular Enveloped Virus (EEV), lateral bodies, and the core components, while summarizing the crucial functions of viral proteins throughout various stages of infection—entry, replication, transcription, translation, assembly, and egress. Particular attention is given to the immunomodulatory strategies employed by LSDV to subvert both innate and adaptive immune responses. These mechanisms encompass molecular mimicry of cytokines and chemokines, interference with antigen presentation pathways, inhibition of key immune signaling cascades, and modulation of apoptosis and autophagy processes. Through comparative analysis with homologs from related poxviruses, especially vaccinia virus, we highlight both evolutionarily conserved functions and potential unique adaptations in LSDV proteins. This review further identifies critical knowledge gaps in current understanding and proposes promising research directions. We emphasize that integrating multi-omics approaches with structural biology will be essential for advancing our understanding of LSDV pathogenesis and for developing novel preventive and therapeutic strategies against this important animal pathogen. Full article

Blast damage to structural members poses serious risks to both buildings and people, making it important to understand how these elements behave under extreme loads. Columns in reinforced concrete (RC) structures are especially critical, as their sudden failure can trigger progressive collapse, unlike beams or slabs that have more redundancy. This state-of-the-art review brings together the current knowledge of the blast response of RC columns, focusing on their failure patterns, dynamic behavior, and key loading mechanisms. The studies covered include experiments, high-fidelity numerical simulations, emerging machine learning approaches, and analytical models for columns of different shapes (square, rectangular, circular) and strengthening methods, such as fiber reinforcement, steel-concrete composite confinement, and advanced retrofitting. Composite columns are also reviewed to compare their hybrid confinement and energy-absorption advantages over conventional RC members. Over forty specific studies on RC columns were analyzed, comparing the results based on geometry, reinforcement detailing, materials, and blast conditions. Both near-field and contact detonations were examined, along with factors like axial load, standoff distance, and confinement. This review shows that RC columns respond very differently to blasts depending on their shape and reinforcement. Square, rectangular, and circular sections fail in distinct ways. Use of ultra-high-performance concrete, steel fibers, steel-concrete composite, and fiber-reinforced polymer retrofits greatly improves peak and residual load capacity. Ultra-high-performance concrete can retain a significantly higher fraction of axial load (often >70%) after strong blasts, compared to ~40% in conventional high-strength RC under similar conditions. Larger sections, closer stirrups, higher transverse reinforcement, and good confinement reduce spalling, shear failure, and mid-height displacement. Fiber-reinforced polymer and steel-fiber wraps typically improve residual strength by 10–15%, while composite columns with steel cores remain stiff and absorb more energy post-blast. Advanced finite element simulations and machine learning models now predict displacements, damage, and residual capacity more accurately than older methods. However, gaps remain. Current design codes of practice simplify blast loads and often do not account for localized damage, near-field effects, complex boundary conditions, or pre-existing structural weaknesses. Further research is needed on cost-effective, durable, and practical retrofitting strategies using advanced materials. This review stands apart from conventional literature reviews by combining experimental results, numerical analysis, and data-driven insights. It offers a clear, quantitative, and comparative view of RC column behavior under blast loading, identifies key knowledge gaps, and points the way for future design improvements. Full article

Natural disasters occur continuously across the globe, posing severe threats to human life and property. Remote sensing technology has provided powerful technical means for large-scale and rapid disaster monitoring. However, the deep integration of remote sensing observations with sector-specific disaster statistical data to construct a knowledge system that supports early warning decision-making remains a significant challenge. This study aims to address the bottleneck in the “data-information-knowledge-service” transformation process by constructing an integrated natural disaster early warning knowledge graph that incorporates multi-source heterogeneous data. We first designed an ontological schema layer comprising six core elements: disaster type, event, anomaly information, impact information, warning information, and decision information. Subsequently, multi-source data were integrated from various sources, including the Emergency Events Database (EM-DAT), sector-specific websites, encyclopedic pages, and remote sensing imagery such as Gaofen-2 (GF-2) and Sentinel-1. A Bidirectional Encoder Representations from Transformers with a Conditional Random Field layer (BERT-CRF) model was employed for entity and relation extraction, and the knowledge was stored and visualized using the Neo4j graph database. The core innovation of this research lies in proposing a quantitative methodology for assessing disaster intensity, impact, and trends based on remote sensing evaluation, establishing a knowledge conversion mechanism with sector-specific warning levels, and designing explicit warning issuance rules. A case study on a specific wildfire event (2017-0417-PRT, Coimbra, Portugal) demonstrates that the knowledge graph not only achieves organic integration and visual querying of multi-source disaster knowledge but also facilitates warning decision-making driven by remote sensing assessment indicators. For this event, quantitative analysis of Gaofen-2 imagery yielded intensity, impact, and trend levels of 4, 3, and 3, respectively, which, when applied to our warning rule (intensity ≥ 1 or impact ≥ 1 or trend ≥ 3), automatically triggered an early warning, thereby validating the rule’s practicality. A preliminary performance evaluation on 50 historical wildfire events demonstrated promising results, with an F1-score of 74.3% and an average query response time of 128 ms, confirming the system’s practical responsiveness and detection capability. In conclusion, this study offers a novel and operational technical pathway for the deep interdisciplinary integration of remote sensing and disaster science, effectively bridging the gap between data silos and actionable warning knowledge. Full article

Artificial intelligence has revolutionized multiple aspects of human existence and raised substantive questions regarding the ultimate purpose of the human person. Spiritual knowledge advances through scientific discovery, as understanding the universe contributes to knowledge of God. Theology, as a discipline that is both theocentric and anthropocentric, considers AI a product of human scientific ingenuity. Despite extensive debate over the decades concerning AI’s impact on the human person, few studies have resolved the complex theological and epistemological issues involved. This article contends that AI represents a significant development in creation, rapidly redefining established paradigms. How does AI as imago hominis reshape Christian anthropology, and what are the socio-theological implications? This core question guides our exploration. We will examine the human person as an individual endowed with intellect, sensibility, volition, as well as imago Dei. In contrast, AI is governed by code and programmers, and is characterized as imago hominis, subject to inherent limitations. By examining the relationship between AI as imago hominis and the human person as imago Dei, this paper succinctly addresses some key ethical and anthropological concerns. Full article

Earth-rock dams are critical components of hydraulic engineering, undertaking core functions such as flood control and disaster mitigation. However, the potential occurrence of dam breach poses a severe threat to regional socioeconomic stability and ecological security. To address the limitations of traditional Bayesian network (BN) in capturing the complex nonlinear coupling and dynamic mutual interactions among risk factors, they are integrated with machine learning techniques, based on a collected dataset of earth-rock dam breach case samples, the PC structure learning algorithm was employed to preliminarily uncover risk associations. The dataset was compiled from public databases, including the U.S. Army Corps of Engineers (USACE) and Dam Safety Management Center of the Ministry of Water Resources of China, as well as engineering reports from provincial water conservancy departments in China and Europe. Expert knowledge was integrated to optimize the network topology, thereby correcting causal relationships inconsistent with engineering mechanisms. The results indicate that the established hybrid model achieved AUC, accuracy, and F1-Score values of 0.887, 0.895, and 0.899, respectively, significantly outperforming the data-driven model G1. Forward inference identified the key drivers elevating breach risk. Conversely, backward inference revealed that overtopping was the direct failure mode with the highest probability of occurrence and the greatest contribution. The integration of data-driven approaches and domain knowledge provides theoretical and technical support for the probabilistic quantification of earth-rock dam breach and risk prevention and control decision-making. Full article

Introduction: Major depressive disorder (MDD) is a mental disorder with a high prevalence rate and a high recurrence rate. Therefore, identifying and intervening in the core symptoms of MDD patients is of great significance. Anhedonia is manifested as an individual losing interest in activities or experiencing a significant decrease in the sense of pleasure, which is one of the two core symptoms of MDD. Episodic Future Thinking (EFT) training refers to the process of stimulating individuals’ hope for positive future scenarios and encouraging them to take purposeful actions, which may have an effect in alleviating anhedonia. However, the perception of anhedonia of MDD patients among Chinese healthcare professionals is still unclear, and there has been no exploration of the views of healthcare professionals regarding the implementation of EFT training for MDD patients led by psychiatric nurses in a clinical setting. Aim: This study aimed to understand the attention paid by Chinese healthcare professionals to the symptom of anhedonia in patients with MDD, as well as their previous coping strategies. This study further explored the views of healthcare professionals regarding the implementation of EFT training for MDD patients led by psychiatric nurses with a psychological therapist certificate in China, as well as suggestions for future implementation. Methods: This qualitative descriptive study adopted a phenomenological approach. Using purposive sampling, 15 healthcare professionals (psychiatrists, psychiatric nurses and psychological counselors) were recruited from the psychiatry department of a public tertiary hospital in Wuhan, Hubei Province, China. Using the NVivo 12 Plus software, the semi-structured interviews and analyses were conducted by applying Colaizzi’s seven-step phenomenological method. Rigor was ensured through checks of credibility, dependability, and confirmability during data collection and analysis. Results: A thematic analysis revealed that, while psychia-trists and psychological counselors viewed anhedonia as a significant treatment target, nurses were more focused on immediate patient safety concerns. Participants recognized the potential of EFT training to alleviate anhedonia but identified several implementation challenges, including patient resistance, cognitive limitations, and the need for tailored interventions. Conclusions: The research results indicated that psychiatric nurses had relatively poor ability to identify anhedonia. Therefore, it is necessary to enhance the awareness of psychiatric nurses regarding the clinical significance of anhedonia, and incorporate knowledge related to anhedonia into routine nursing training. It is suggested that communication and collaboration among psychiatrists, psychiatric nurses and psychological counselors should be strengthened, and an assessment and feedback process for the lack of anhedonia in patients with MDD should be established, so as to assist these patients in achieving faster psychological recovery. Given the sufficient staffing conditions in the field of psychiatry nursing in China, the design concept and curriculum of EFT training for psychiatry nurses with a psychological therapist certificate should be promoted. Encourage psychiatry nurses with a psychological therapist certificate to conduct offline and online group EFT training intervention forms for MDD patients in the hospital wards during their hospitalization periods, as well as after discharge at home. Full article

The atmospheric pressure plasma jet (APPJ) is a popular type of cold atmospheric plasma (CAP). APPJs based on a pulsed atmospheric arc (PAA) are widely spread in industrial processing. A plasma jet of this type, PlasmaBrush PB3 (PB3), is a subject of diverse research activities. The characteristic feature of PB3 is the generation of a low-current (300 mA), high-voltage (1500 V) pulsed (54 kHz) atmospheric arc. A gas flow vortex is used to stabilize the arc and to sustain the circular motion of the cathodic arc foot. During long periods of operation, nozzles acting as arc discharge cathodes erode. Part of the eroded material is emitted as nanoparticles (NPs). These NPs are not wanted in many processing applications. Knowledge of the number, type, and size distribution of emitted NPs is essential to minimize their emissions. In this study, NPs in the size range of 6 to 220 nm, emitted from four different nozzles operated with PB3, are investigated. The differences between the nozzles are in the eroded surface material (copper, tungsten, and nickel), the diameter of the nozzle orifice, the length of the discharge channel, and the position of the cathodic arc foot. Significant differences in the particle size distribution (PSD) and particle mass distribution (PMD) of emitted NPs are observed depending on the type and condition of the nozzle and their operating time. Monomodal and bimodal PMD models are used to approximate emissions from the nozzles with tungsten and copper cores, respectively. The skew-normal distribution function is deemed suitable. The results of this study can be used to control NP emissions, both to avoid them and to utilize them intentionally. Full article

Background: Swimming is a common goal for children with disability, and the most popular sport for children in Australia. This study explored swimming and rehabilitation professionals’ perceptions of swimming for Australian children with disability. Methods: Rehabilitation and swimming professionals with recent experience working with children with disability completed an online survey. Quantitative data from binary and Likert-scale questions were analysed descriptively. Qualitative data from open-ended questions was evaluated using reflexive thematic analysis and mapped to the family of Participation-Related Constructs (fPRC). Results: Ninety-one swimming and 55 rehabilitation professionals (n = 146) responded. Most were confident supporting children with disability with swimming goals (rehabilitation = 71.6%, swimming = 73.8%) but had neutral–very low knowledge of para-swimming eligibility and classification (rehabilitation = 75%, swimming = 77.7%). Ten themes (33 code groups) covering all core elements of the fPRC were identified. Barriers/facilitators included pool accessibility (physical and sensory); program availability; affordability; acceptability (of content and culture); and having accommodating professionals and programs. Professionals believed that swimming programs should develop children’s confidence, water-safety, swimming skills, and fitness. Conclusion: Rehabilitation and swimming professionals should review existing programs to ensure they meet the needs of children with disability. Further research is needed to create an action plan to improve swimming participation for Australian children with disability. Full article

Historic floors, including mosaics, stone slabs, and decorated pavements, are fragile elements that can be easily damaged during restoration works. Risks arise from falling tools, concentrated loads of scaffolding or equipment, and the repeated passage of workers. Traditional protection methods, such as plywood sheets, mats, multilayer systems, or modular plastic panels, have been applied in different sites but often present limitations in adaptability to irregular surfaces, in moisture control, and in long-term reversibility. This paper introduces an innovative approach developed within the 3D-EcoCore project. The proposed solution consists of a bio-inspired modular sandwich system manufactured by 3D printing with biodegradable polymers. Each module contains a Voronoi-inspired cellular core, shaped to match the geometry of the floor obtained from digital surveys, and an upper flat skin that provides a safe and resistant surface. The design ensures mechanical protection, adaptability to uneven pavements, and the possibility to integrate ventilation gaps, cable pathways, and monitoring systems. Beyond heritage interventions, the system also supports routine architectural maintenance by enabling safe, reversible protection during inspections and minor repairs. The solution is strictly temporary and non-substitutive, fully aligned with conservation principles of reversibility, recognizability, and minimal intervention. The Ninfeo Ponari in Cassino is presented as a guiding example, showing how multilevel knowledge and thematic mapping become essential inputs for the tailored design of the modules. The paper highlights both the technical innovation of the system and the methodological contribution of a knowledge-based design process, opening future perspectives for durability assessment, pilot installations, and the integration of artificial intelligence to optimise core configurations. Full article

Background/Objectives: As safe, eco-friendly, and legally compliant solutions for the disposal of unwanted medications, drug take-back systems have attracted extensive research attention. However, there is a lack of systematic mapping of global trends, collaborative networks, research themes, and hotspots in this field. This study aimed to conduct a comprehensive bibliometric analysis and review of global academic research on drug take-back programs. Methods: Peer-reviewed research articles on drug take-back programs, published between 2005 and 2025, were retrieved from the Web of Science Core Database. Microsoft Office Excel 2019, VOSviewer (v.1.6.17), and CiteSpace (v.6.1.R3 Advanced) were used to assess publication/citation trends, countries, institutions, authors, journals, disciplines, references, and keywords. Narrative analysis was employed to synthesize data from the included articles and identify core research themes. Results: A total of 149 eligible articles with 4520 citations were included, involving 619 authors, 52 countries/regions, 310 institutions, and 95 journals. Publication/citation counts increased significantly between 2005 and 2025. The United States led in both publication output and collaborative research; Mercer University was the most influential institution, but international and cross-institutional collaboration remained limited. Environmental Sciences ranked first among disciplinary categories in drug take-back research, followed by Pharmacology/Pharmacy. Core research themes underpinning this field included stakeholders’ knowledge–attitude–practice assessment (76 articles), returned medication treatment (37 articles), intervention evaluation (25 articles), policy analysis (7 articles), and the role of drug take-back programs in mitigating environmental and public health hazards caused by medicine wastes (4 articles). Conclusions: Scholarly attention to drug take-back programs has grown steadily. Future research should prioritize cross-sectoral and international cooperation, develop and adopt evidence-based interventions to optimize the safety, sustainability, and accessibility of drug take-back systems on a global scale. Full article

In the study of linear dispersive media, it is of primary interest to gain knowledge of the impulse response of the material. The standard approach to compute the response involves a Laplace transform inversion, i.e., the solution of a Bromwich integral, which can be a notoriously troublesome problem. In this paper we propose a novel approach to the calculation of the impulse response, based on the well-assessed method of the steepest descent path, which results in the replacement of the Bromwich integral with a real line integral along the steepest descent path. In this exploratory investigation, the method is explained and applied to the case study of the Klein–Gordon equation with dissipation, for which analytical solutions of the Bromwich integral are available, so as to compare the numerical solutions obtained by the newly proposed method to exact ones. Since the newly proposed method, at its core, consists of replacing a Laplace transform inverse with a potentially much less demanding real line integral, the method presented here could be of general interest in the study of linear dispersive waves in the presence of dissipation, as well as in other fields in which Laplace transform inversion comes into play. Full article

The escalating challenges of climate change, soil degradation, and the need to ensure global food security are driving the transition towards more sustainable agricultural practices. Biostimulants, a diverse category of substances and microorganisms, have emerged as promising tools to enhance crop resilience, improve nutrient use efficiency (NUE), and support sustainable intensification. However, their widespread adoption is hampered by significant variability in efficacy and a lack of consensus on their optimal use. This comprehensive review synthesizes current scientific knowledge to critically evaluate the performance of biostimulants within sustainable agricultural systems. It aims to move beyond isolated case studies to provide a holistic analysis of their modes of action, efficacy under stress, and interactions with the environment. The analysis confirms that biostimulant efficacy is inherently context-dependent, governed by a complex interplay of biological, environmental, and management factors. Performance variability is explained by four core principles: the Limiting Factor Principle, the Biological Competition Axiom, the Stress Gradient Hypothesis, and the Formulation and Viability Imperative. A significant disconnect exists between promising controlled-environment studies and variable field results, highlighting the danger of extrapolating data without accounting for real-world agroecosystem complexity. Biostimulants are not universal solutions but are sophisticated tools whose value is realized through context-specific application. Their successful integration requires a precision-based approach aligned with specific agronomic challenges. We recommend that growers adopt diagnostic tools and on-farm trials, while producers must provide transparent multi-location field data and invest in advanced formulations. Future research must prioritize field validation, mechanistic studies using omics tools, and the development of crop-specific protocols and industry-wide standards to fully unlock the potential of biostimulants for building resilient and productive agricultural systems. Full article

Aerobic anoxygenic phototrophs (AAPs) are intrinsically paradoxical; these species use a pathway commonly found in oxygen-deprived environments called anoxygenic photosynthesis, as a supplementary energy source to their obligately aerobic respiration. At the surface, such a combination seems odd, but AAPs thrive in a plethora of environments and are phylogenetically broad, suggesting that this feature is advantageous and ecologically valuable. The range of habitats and taxonomy have been reviewed, yet the main element which unites the group, their anoxygenic photosynthesis, which is diverse in its components, has not received the deserved attention. The intricate light-capturing photosynthetic complex forms the site of photon-induced energy transfer and therefore, the core basis of the process. It has two parts: the reaction center and light harvesting complex(es). The variability in composition and overall usage of the apparatus is also reflected in the genome, specifically the photosynthetic gene cluster. In this review, what is known about the differences in structure, light wavelength absorption range, activity, and related genomic content and the insights into potential AAP evolution from anaerobic anoxygenic phototrophs will be discussed. The work provides an elegant summation of knowledge accumulated about the photosynthetic apparatus and prospects that can fill yet remaining gaps. Full article