Search Results (3,899)

Transcatheter aortic valve implantation (TAVI) has transformed the management of severe aortic stenosis (AS), evolving from a therapy reserved for inoperable patients to a viable treatment across the spectrum of surgical risk. This success has stimulated innovation in transcatheter therapies for other valvular heart diseases, including aortic regurgitation (AR). In contrast to AS, AR is characterised by heterogeneous aetiologies, absence of annular calcification, larger and more elliptical annular dimensions, and concomitant aortopathy. These challenges have limited the efficacy and safety of conventional transcatheter aortic valves (TAVs), use of which in pure native AR is associated with high rates of valve embolisation, significant residual regurgitation, permanent pacemaker implantation, and mortality. The development of dedicated TAVs designed specifically for the treatment of AR has addressed many of these anatomical challenges. The JenaValve Trilogy and J-Valve systems incorporate leaflet-grasping mechanisms that enable secure anchoring independent of calcification, resulting in transformation of procedural and clinical outcomes. Recent prospective registry data, including the landmark ALIGN-AR trial, demonstrate high technical and procedural success rates, low residual regurgitation, acceptable safety profiles, and meaningful improvements in functional status and ventricular remodelling. These data have informed contemporary guideline updates, with the 2025 European Society of Cardiology (ESC)/European Association of Cardiothoracic Surgery (EACTS) Guidelines for the management of valvular heart disease issuing the first conditional recommendation for TAVI in selected patients with severe AR and the National Institute for Health and Care Excellence (NICE) recommending TAVI for native AR in patients for whom surgical AVR is not available or is high risk. This review summarises the clinical implications of AR, examines current guideline recommendations for management, and critically appraises the evidence supporting transcatheter treatment strategies. Full article

Seafloor hydrothermal systems at mid-ocean ridges are focal points for heat and matter exchange between the seawater and lithosphere. While seafloor seismographs (OBS) and pressure recorders (BPR) are standard for regional monitoring, achieving high-precision, vertical sub-surface data in complex hydrothermal terrains remains a significant technical objective. This study presents a novel in situ penetration probe designed for multi-parameter monitoring of marine hydrothermal vent areas. A key innovation of this work is its operational versatility and engineering efficiency: the probe is specifically designed for post-drilling deployment in boreholes, effectively utilizing existing coring sites to achieve direct coupling with the deep-seated crust, or for targeted placement via Remotely Operated Vehicles (ROVs). The device integrates a titanium-alloy conical tip and cylindrical chamber, housing tri-axial accelerometers and dual temperature-pressure sensors. Numerical simulations using the SST k-ω turbulence model and finite element analysis optimized the cone aperture and assessed fluid–structure stability under deep-sea conditions. Laboratory vibration tests and shallow-water sea trials validated the probe’s basic dynamic response, electromechanical integrity, and capability to acquire coupled environmental parameters. This compact, modular design provides a scalable and cost-effective framework for precise three-dimensional observation of sub-surface hydrothermal processes and deep-sea resource exploration. Full article

In contemporary debates on the United Nations Sustainable Development Goals, there is growing recognition that artificial intelligence (AI) may contribute meaningfully to SDG 2 (Zero Hunger), particularly by enhancing the efficiency of food aid distribution and resource allocation. However, such optimism must be critically situated within the broader institutional and ethical contexts in which AI operates. This study argues that the effectiveness of AI in conflict-affected settings is contingent not only on technical capacity but also on governance structures, ethical safeguards, and institutional trust, dimensions closely aligned with SDG 16 (Peace, Justice, and Strong Institutions). Using the Gaza Strip as a case study, this article demonstrates that AI-driven food assistance mechanisms may inadvertently reinforce structural vulnerabilities. Specifically, algorithmic targeting of aid risks deepening dependency, exacerbating digital exclusion, and weakening already fragile governance systems. The absence of robust data accountability frameworks further complicates these dynamics, raising concerns regarding transparency, fairness, and long-term sustainability. The findings caution against privileging technical efficiency at the expense of socio-political stability. Rather, they highlight that the sustainability of AI interventions in humanitarian contexts fundamentally depends on the credibility and legitimacy of institutions. Accordingly, this study proposes a conceptual model for AI in hunger relief and digital humanitarianism that integrates technical innovation with institutional accountability and social trust. This study presents a narrative review informed by structural searching that examines the influence of AI on food security interventions in fragile contexts. This analysis applies a combined ethical governance and sustainability lens to assess current applications and risks. This research advances a broader analytical framework that moves beyond purely technical interpretations of AI, emphasizing its role as a socio-political tool, through identifying five key pillars for sustainable AI governance: data sovereignty, algorithmic accountability, inclusive system design, community-led governance, and market integrity. Full article

With the increasing penetration of wind and solar renewable energy into modern power systems, grids exhibit ‘dual-high’ (i.e., a high proportion of both renewable energy and power electronic devices) and ‘dual-low’ (i.e., low equivalent rotational inertia and low short-circuit capacity) structural characteristics. This leads to critical challenges, notably insufficient short-circuit capacity, declining voltage and frequency stability, and weakened system damping. To address the stability requirements of new power systems, this study proposes and systematically investigates a variable-speed synchronous condenser based on AC excitation technology. The research encompasses the operational principles, starting mechanisms, and control strategies of the device, with a particular focus on analyzing its stator-flux-oriented vector control method and active–reactive power decoupling regulation mechanism. By independently adjusting the frequency, amplitude, and phase of the AC excitation on the rotor side, the system achieves a millisecond-level dynamic reactive power response, rapid frequency support, and self-starting capability without the need for external starting devices. To validate the effectiveness of the theoretical analysis and engineering practicality, this study presents grid-connected operational tests using a 3600 kVar engineering prototype at a wind farm. The test results demonstrate that the variable-speed synchronous condenser performs excellently in speed regulation, dynamic reactive power response, and primary frequency modulation. It effectively provides short-circuit capacity, enhances system damping, and significantly improves the voltage and frequency stability of power grids with high penetration of renewable energy. This study offers innovative technical pathways and empirical evidence for constructing a stability support system that meets the developmental needs of new power systems. It holds significant theoretical value and engineering guidance for promoting the smooth transition of power grids from synchronous machine-dominated to power electronics-based architectures. Full article

Translating diverse stakeholders’ needs for tourism into precise technical requirements for mobile resilience applications is a significant challenge, especially for at-risk coastal communities. Therefore, we developed a structured decision-support framework that uses the Analytic Hierarchy Process (AHP) combined with Multi-Criteria Decision Analysis (MCDA) to systematically identify and prioritize functional features for a disaster-resilient tourism application called AuTour. The framework was validated through a case study in Aurora Province, Philippines, involving 152 diverse stakeholders, including government officials, tourism operators, and technology students. The AHP analysis results revealed that safety infrastructure (a mean weight of 0.5256) was the dominant design criterion, far outweighing environmental sustainability (0.2480) and community preparedness (0.1241). The MCDA ranked key functional modules using these criteria to determine an optimal system architecture. The highest-priority features identified were a real-time Disaster Preparedness Alert module, a geospatial Smart Tourism Guide, and a participatory Health Surveillance module. The analysis results confirmed high utility for features incorporating AI-powered chatbots (a mean score of 4.1921) and multi-dialect communication capabilities (4.1513). The developed scalable, data-driven framework can be used for user-centered design in the critical domain of disaster-resilient technology. By translating stakeholder priorities into a ranked set of technical specifications, the framework contributes to the development of resilient mobile systems, supporting the achievement of Sustainable Development Goals for innovation (SDG 9) and resilient infrastructure (SDG 11). Full article

As a core load-bearing component, the aero-engine rear cooling plate requires its design to simultaneously meet strength requirements and lightweight indicators. The topology optimization method considering stress constraints is the core technical path to achieve this goal, but it suffers from insufficient control precision in key areas, easily leading to material redundancy. To address this issue, a partitioned topology optimization method based on the multi-feature K-means algorithm is proposed. First, by integrating multi-dimensional features including element stress, physical density, and spatial position, an innovative multi-feature K-means algorithm is employed to realize dynamic adaptive partitioning during the optimization process. Secondly, combined with the p-norm method for partitioned stress aggregation, a precise prediction and control method for partitioned stress is adopted to refine stress constraints. Thirdly, a topology optimization model of the rear cooling plate with multi-feature partitioned stress constraints is constructed, and the adjoint method is used to solve the stress sensitivities under centrifugal loads. Finally, the effectiveness of the proposed method is verified using the rear cooling plate model. The rear cooling plate is discretized with 0.5 mm 2D axisymmetric finite elements, the filter radius is 4 mm, and the Method of Moving Asymptotes (MMA) is employed for the solution. The mass fraction of the finally optimized rear cooling plate structure is 0.157, which is 13.7% lower than that obtained by the global stress constraint method and 11.3% lower than that obtained by the topology optimization method considering both the geometric partitioned stress constraints and global stress constraints. The proposed method provides a new approach for the lightweight design of the aero-engine rear cooling plate. Full article

Leaching carbon residue (LCR) is a carbonaceous solid waste generated during the hydrometallurgical recycling of spent lithium-ion batteries. Although its high graphite content offers substantial potential for resource recovery, the residual heavy metals and fluorides present in LCR pose considerable environmental risks. Currently, LCR has not garnered sufficient attention within the industry, and the lack of recycling technologies suitable for large-scale disposal results in resource wastage and environmental pollution. To address these challenges, this study proposes an innovative strategy based on the concept of multi-field synergistic enhancement. The proposed approach involves recovering and regenerating graphite (RG) from LCR via low-temperature molten salt roasting assisted by high-pressure and mechanical activation. A combination of advanced characterization techniques was employed to compare the physicochemical properties of RG and commercial graphite (CG) and to systematically evaluate the technical feasibility of using regenerated graphite as an anode material for lithium-ion batteries. The results demonstrate that, under optimized molten salt roasting and aqueous leaching conditions, the carbon content of RG reaches 99.94 wt%, indicating the efficient removal of non-carbon impurities from the graphite matrix. Compared to CG, RG retains a typical layered structure; however, a lower carbon content (99.94 wt%) and poorer structural order (I_D/I_G = 0.30) are observed. In terms of electrochemical performance, RG delivers a discharge specific capacity of 394.64 mAh/g during the first cycle and exhibits excellent cycling stability, with a capacity retention of 86.50% after 100 cycles. This electrochemical performance is comparable to that of commercial graphite. The proposed multi-field-assisted low-temperature molten salt roasting technique enables the efficient recovery of high-value graphite resources from LCR, establishing a full-lifecycle recycling strategy tailored for lithium-ion battery applications. Full article

To address the application requirements of energy storage devices for new energy electric vehicles—including high energy density, high-power density, fast charging and discharging, and long-term cycling stability—traditional symmetric supercapacitors are often limited by low energy density and poor compatibility between the anode and cathode, making it difficult to meet the high-efficiency energy storage demands under the dynamic operating conditions of electric vehicles. This study focuses on the regulation of hierarchical thin-film structures and the innovative heterogeneous coating interface engineering with precise slurry coating and film-forming optimization and designs and fabricates NiCo₂O₄/NiFeO composite thin-film electrodes and Mn-doped porous carbon (Mn-PC) thin-film electrodes. The uniform, compact and stable coating formation on nickel foam substrates via controllable slurry coating facilitates the efficient integration of active materials and conductive supports. The electrode slurries were coated onto conductive nickel foam substrates, and high-performance aqueous supercapacitors were assembled using an asymmetric configuration. A systematic study was conducted covering material preparation, structural characterization, electrochemical testing, and full-device performance evaluation. Using techniques such as XRD, XPS, SEM, TEM, BET, and an electrochemical workstation, the study revealed the structure–activity relationships among material morphology, crystalline phases, pore structure, and electrochemical performance, elucidating the charge storage mechanisms of the composite electrode films and the principles of synergistic adaptation between the anode and cathode. The results indicate that NiCo₂O₄ nanowires decorated with in situ-grown NiFeO nanosheets to form a composite structure; when coated onto nickel foam, this forms a uniform, porous electrode film with a specific surface area of 171.3 m²/g, a specific capacitance as high as 1746 F/g at 1 A/g, and a capacity retention rate of 94.0% after 10,000 cycles. After coating and film formation, the Mn-PC anode introduced pseudocapacitive active sites through uniform Mn doping, resulting in a film electrode specific capacitance of 348 F/g and significantly improved rate and cycling performance. The assembled NiCo₂O₄/NiFeO//Mn-PC asymmetric supercapacitor exhibits a thin-film electrode specific capacitance of 153 F/g at 1 A/g, with a maximum energy density of 52 Wh/kg. Even at a power density of 9000 W/kg, it maintains 45 Wh/kg, and retains 89.5% of its capacity after 10,000 cycles, with overall performance outperforming most previously reported transition metal-based devices. This coating-engineered electrode fabrication strategy breaks through the interface mismatch and structural instability bottlenecks of traditional thin-film electrodes, providing a novel material system and an efficient coating assembly strategy for high-performance supercapacitor thin-film electrodes in new energy electric vehicles, and offers experimental evidence and technical references for the development and application of high-power energy storage coating devices for automotive use, as well as the innovative design of electrode coating engineering in energy storage fields. Full article

This study comprehensively analyzed the effects of gamma irradiation (GI) on the flavor profile of aged light-flavor tartary buckwheat Baijiu (LTB) using E-nose, E-tongue, and high-sensitivity headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS). A total of 30 volatile organic compounds (VOCs) were identified, with concentrations showing significant dose-dependent correlations with GI treatment. Aging alone reduced harsh and pungent VOCs (e.g., 1-propanol, 2-methyl butanoic acid ethyl ester), while GI followed by aging further decreased undesirable compounds (e.g., butanal-D, pyrrolidine) and enhanced beneficial flavor components, such as 1,1-diethoxy ethane-D and butanoic acid propyl ester. Notably, this treatment partially restored 1-propanol, triethylamine, and 2-butanone-M, though their levels remained significantly lower than in newly brewed LTB, achieving a more balanced purity and flavor complexity. The significantly elevated levels of tetrahydrofuran-M/D, 1,1-diethoxy ethane-D, and cyclohexane in GI-treated aged LTB, along with their dose-dependent accumulation patterns, suggest their potential as reliable markers. Multivariate analysis confirmed that all three techniques (E-nose, E-tongue, and HS-GC-IMS) effectively differentiated LTB samples, with strong correlations between E-nose and HS-GC-IMS data, as well as between E-tongue and HS-GC-IMS results. This work provides flavor fingerprints and potential markers for gamma-irradiated LTB identification, while proposing an innovative technical approach for rapid flavor assessment of light-flavor Baijiu. Full article

A phage is a virus that targets bacteria with high precision. While phage therapy provides a targeted alternative to broad-spectrum antibiotics, it is not completely free from the challenges of antimicrobial resistance, as phages can facilitate the horizontal transfer of resistance genes through transduction and promote the growth of phage-resistant strains. Nonetheless, within the One Health framework, the strategic use of phages remains a vital and promising tool for addressing the global antimicrobial resistance crisis. This paper reviews current research on phage therapy for gastrointestinal diseases such as cirrhosis, enteritis, and Helicobacter pylori infection. It also details how phages help regulate gut microecological balance and discusses how phage dysbiosis can lead to innate immune dysfunction and worsen conditions like inflammatory bowel disease. The review summarizes both the therapeutic potential and limitations observed in clinical trials and fundamental studies. Transitioning from laboratory research to clinical practice is hindered by multiple complex challenges, including the stomach’s extreme acidity, physical entrapment by the intestinal mucus layer, the rapid co-evolution of bacterial resistance, and ecological risks associated with temperate phages. To overcome challenges like gastrointestinal barrier tolerance and address ethical, technical, and practical hurdles for clinical use, the paper outlines treatment strategies for specific conditions and highlights future directions, providing guidance for employing phages in digestive system disease management. These future innovations focus on integrating artificial intelligence-driven precision matching, advanced bioengineering for durable delivery systems, and multimodal combination therapies to safely modulate the intestinal microecology. Full article

Over the past decades, neurosurgery has undergone a profound transformation driven by technological innovation and a paradigm shift toward patient-centered outcomes. Historically evaluated through mortality rates and extent of resection, modern neurosurgery increasingly prioritizes preservation of neurological function, cognitive integrity, and quality of life. Innovations such as intraoperative mapping, multimodal neuromonitoring, image-guided surgery, minimally invasive techniques, and enhanced recovery protocols have reshaped surgical decision-making. However, the true value of these advancements lies in their measurable impact on clinically meaningful outcomes. This narrative review examines how technical progress translates into functional, cognitive, and quality-of-life benefits, while critically discussing current limitations of evidence and future directions toward personalized, outcome-driven neurosurgery. Full article

Background: Sensors and mass spectrometry (MS) are frequently used in combination for food safety and quality assessment, yet their functional integration lacks a formal methodological framework. This review categorizes the synergies between these technologies into distinct Relational Connections. Methodology: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 155 original research articles published between 2015 and 2025 were systematically analyzed. Records were identified via the Scopus database within the food science domain. Experimental meta-data, including extraction protocols, instrumental configurations (ionization source, mass analyzer, cost tier), and chemometric strategies, were extracted to identify core methodological patterns. Statistical associations were quantified using chi-squared tests with Cramer’s V effect sizes. Results: Five Relational Connections were identified: (1) MS as reference for sensor validation (25.2%); (2) MS-sensor correlative analysis (10.3%); (3) MS quantifying data to train predictive sensor models (6.5%); (4) MS identifying targets for sensor detection (7.1%); and (5) MS enabling sensor classification models (51.0%). Technology pairing is governed by a three-level hierarchy: analyte polarity determines the ionization source (V = 0.69), required precision determines the mass analyzer (V = 0.64), and cost/availability constraints shape the practical integration strategy. Gas Chromatography (GC)-MS is predominantly coupled with Electronic Noses for volatile profiling (86% of classification studies), while Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) pairs with biosensors for contaminant analysis (74% of reference validation studies). Systematic analysis of the full pairing matrix reveals that 75% of theoretically possible MS-sensor combinations remain unexplored or underrepresented, identifying both technical boundaries and innovation frontiers. Discussion: The findings clarify the strategic logic behind technology pairings, demonstrating that MS provides the quantitative molecular data required for sensor training. The hierarchical decision framework and identification of underexplored pairings provide an evidence-based guide for designing future integrated food analysis systems. Full article

This study examines the influences of various organizational performance factors on the application of Lean tools and the effects of Lean methodology implementation. Although Lean management has been widely studied, empirical evidence on the combined influence of internal organizational capabilities and external environmental pressures on Lean adoption and outcomes in transition economies remains limited. In particular, the relative importance of internal resources and competitive pressures in shaping Lean implementation results has not been sufficiently explored. Therefore, this study aims to analyze how different organizational and environmental factors influence both the application of Lean tools and the effects of Lean methodology implementation. The independent variables considered include: business performance, organizational culture, company size, technical infrastructure and resources, education and competence of employees, training for Lean methodology, management support, competitive pressure and motivation to reduce costs, degree of innovation in the company, the role of the Lean concept in strategic planning, years of company existence, and years of Lean tool implementation. The research was conducted among food industry companies in Serbia, and a total of 183 valid questionnaires were collected. The results indicate that the application of Lean tools is most strongly influenced by training for Lean methodology, followed by business performance and company size. In contrast, the effects of Lean methodology implementation are primarily affected by competitive pressure and motivation to reduce costs, as well as management support. Furthermore, the analysis shows that Lean application and Lean outcomes function as two distinct dimensions: companies may apply Lean tools without achieving significant effects if managerial support or competitive pressure is insufficient. Conversely, firms with strong competitive drivers and committed management achieve noticeably higher performance improvements even with moderate levels of Lean tool adoption. Overall, the findings suggest that the application of Lean tools largely depends on the company’s internal resources, such as employee knowledge and training, business strength, and scale of operations, while the success and outcomes of Lean implementation are more strongly driven by external competitive pressures and the degree of managerial understanding and support. By distinguishing between the determinants of Lean tool adoption and the determinants of Lean implementation outcomes, this study contributes to a clearer understanding of Lean effectiveness in the context of transition economies. Full article

Non-small cell lung cancer (NSCLC) accounts for nearly 85% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Advances in molecular diagnostics and targeted therapies have transformed treatment paradigms, yet the integration of molecular testing into routine care for resected NSCLC specimens continues to face significant challenges. This review outlines the technical, clinical, and systemic barriers that limit the effectiveness of molecular testing. Key considerations include tissue quality, the limitations of formalin-fixed paraffin-embedded (FFPE) samples, and the comparative roles of conventional methods—such as immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and reverse transcription polymerase chain reaction (RT-PCR)—versus next-generation sequencing (NGS). We also discuss the prevalence and clinical relevance of common genomic alterations, including TP53, KRAS, EGFR, and ALK, as well as their impact on prognosis and treatment selection. Real-world obstacles such as accessibility, reimbursement, delays in testing, interdisciplinary coordination, and sample adequacy are critically examined. Emerging innovations—including multi-omics integration, spatial profiling, liquid biopsy, artificial intelligence, and novel targeted therapies—offer opportunities to overcome current limitations and improve patient outcomes. Finally, practical recommendations are proposed to optimize tissue handling, testing algorithms, and access to precision-guided therapies. By addressing these challenges, molecular testing in NSCLC can be more effectively leveraged to personalize treatment strategies and enhance survival outcomes. Full article

Sulfur-mediated autotrophic denitrification (SAD) is an innovative and sustainable water treatment technology, which operates without an external carbon source and achieves lower sludge production. Firstly, this review provides a detailed examination of sulfur-based fillers, encompassing their respective types, preparation methods, advantages and drawbacks. Subsequently, it reviews the mainstream functional microbial communities across various process stages, such as Thiobacillus, Sulfurimonas, and Ignavibacterium. Moreover, the process characteristics of mainstream SAD reactor types, such as fluidized bed, fixed bed, and moving bed biofilm reactors, are reviewed, and the effects of key process parameters like pH, temperature, and dissolved oxygen on treatment efficiencies are further analyzed. Additionally, the applications cases of SAD in advanced wastewater treatment, river remediation, wetland restoration, and groundwater purification are summarized, demonstrating its broad and diverse application potential in environmental engineering. Finally, key challenges of SAD are identified, including the complexity of microbial metabolic interactions, the accumulation of intermediate products, and the need for improved fillers and reactor configurations. Future research priorities are discussed in three areas: microbial community regulation, control and utilization of intermediate products, and development of advanced fillers and reactor configurations. Overall, this review integrates key technical parameters and operational experience of SAD, providing a consolidated reference for researchers and practitioners interested in the development and application of this technology. Full article