Search Results (1,992)

The fastest growth in electricity demand in the industrialized world will likely come from the broad adoption of artificial intelligence (AI)—accelerated by the rise of generative AI models such as OpenAI’s ChatGPT. The global “data center arms race” is driving up power demand and grid stress, which creates local and regional challenges because people in the area understand that the additional data center-related electricity demand is coming from faraway places, and they will have to support the additional infrastructure while not directly benefiting from it. So, there is an incentive for the data center operators to manage the fast and unpredictable power surges internally so that their loads appear like a constant baseload to the electricity grid. Such high-intensity and short-duration loads can be served by hybrid energy storage systems (HESSs) that combine multiple storage technologies operating across different timescales. This review presents an overview of energy storage technologies, their classifications, and recent performance data, with a focus on their applicability to AI-driven computing. Technical requirements of storage systems, such as fast response, long cycle life, low degradation under frequent micro-cycling, and high ramping capability—which are critical for sustainable and reliable data center operations—are discussed. Based on these requirements, this review identifies lithium titanate oxide (LTO) and lithium iron phosphate (LFP) batteries paired with supercapacitors, flywheels, or superconducting magnetic energy storage (SMES) as the most suitable HESS configurations for AI data centers. This review also proposes AI-specific evaluation criteria, defines key performance metrics, and provides semi-quantitative guidance on power–energy partitioning for HESSs in AI data centers. This review concludes by identifying key challenges, AI-specific research gaps, and future directions for integrating HESSs with on-site generation to optimally manage the high variability in the data center load and build sustainable, low-carbon, and intelligent AI data centers. Full article

To address the depletion of shallow coal resources, mining activities have progressed to greater depths, where rock masses contain numerous fractures due to complex geological conditions, making grouting reinforcement essential for ensuring stability. Using digital image correlation, this study investigated the strain evolution characteristics of grouted fractured specimens of three rock types—mudstone, coal–rock, and sandstone—under uniaxial compression. Analysis of the strain evolution process focused on two typical fracture inclinations of 0° and 60°, while examination of the peak strain characteristics covered five inclinations, namely 0°, 15°, 30°, 45°, and 60°. The findings indicate that the mechanical response varies systematically with lithology and fracture inclination. The post-peak curves differ significantly among rock types: coal–rock shows a gentle descent, mudstone exhibits a rapid strength drop but higher residual strength, and sandstone is characterized by “serrated” fluctuations. The failure mode transitions from tensile splitting at a horizontal inclination of 0° to shear failure at inclinations of 15°, 30°, 45°, and 60°. Strain nephograms corresponding to the peak stress point D reveal sharp, band-shaped zones of strain localization. The maximum principal strain exhibits a non-monotonic trend, first increasing and then decreasing with increasing inclination angle. For grouted coal–rock and sandstone, the peak values of 47.47 and 45.00 occur at α = 45°. In contrast, grouted mudstone reaches a maximum value of 26.80 at α = 30°, indicating its lower susceptibility to damage. The study systematically clarifies the strain evolution behavior of grouted fractured rock masses, providing a theoretical basis for evaluating the effectiveness of reinforcement and predicting failure mechanisms. Crucially, the findings highlight mudstone’s role as a high-integrity medium and the particular vulnerability of horizontal fractures, offering direct guidance for the targeted grouting design in stratified rock formations. Full article

The design of a suitable experiencescape has now become critical for enhancing hedonic benefits and exceptional visitor experiences. However, there is a lack of research on determining its construct, especially with a wide exploration of practical context. This research uses qualitative methods and focuses on a sample of professional fishermen undertaking fishing trips in Greece, attempting to lay the foundations for the formation of a holistic space that will allow for the co-creation of experiences. The data collection was carried out through 30 on-site interviews where the order of questions was predetermined. The empirical findings reveal that the experience brokers play a decisive role in how the fishing excursion is staged and directed. Consequently, the results of this study provide useful guidance for policymakers aiming to foster an attractive investment environment and to design an optimal experiencescape. Full article

In this study, a hybrid deep learning model that combines the VGG16 and ResNet101V2 architectures is proposed for image-based fire detection. In addition, a balanced drone guidance algorithm is developed to efficiently assign tasks to available UAVs. In the fire detection phase, the hybrid model created by combining the VGG16 and ResNet101V2 architectures has been optimized with Global Average Pooling and layer merging techniques to increase classification success. The DeepFire dataset was used throughout the training process, achieving an extremely high accuracy rate of 99.72% and 100% precision. After fire detection, a task assignment algorithm was developed to assign existing drones to fire points at minimum cost and with balanced load distribution. This algorithm performs task assignments using the Hungarian (Kuhn–Munkres) method and cost optimization, and is adapted to direct approximately equal numbers of drones to each fire when the number of fires is less than the number of drones. The developed system was tested in a Python-based simulation environment and evaluated using performance metrics such as total intervention time, energy consumption, and task balance. The results demonstrate that the proposed hybrid model provides highly accurate fire detection and that the task assignment system creates balanced and efficient intervention scenarios. Full article

The effect of afforestation in infertile mountainous areas is closely related to the soil ecological environment. Soil enzyme activities and the structure and functions of microbial communities are core indicators reflecting soil quality. Clarifying the response patterns of the two to Cyclobalanopsis gilva afforestation in infertile mountainous areas can provide a key scientific basis for targeted improvement of the cultivation efficiency of C. gilva plantations under different site conditions in the eastern subtropical region of China. In this study, 7-year-old C. gilva young forests in infertile mountainous areas and control woodland areas were selected in Shouchang Forest Farm, Jiande, Zhejiang Province, located in the subtropical region of China. Soil enzyme activities and microbial biomass in different soil layers, as well as metagenomes of rhizosphere and bulk soils, were determined to explore the effects and internal correlations of site conditions on soil enzyme activities and microbial community characteristics of C. gilva forests. The results showed that the activities of urease and catalase, as well as the content of microbial biomass nitrogen in the surface soil of infertile mountainous areas, were significantly lower than those in control woodland areas. The shared dominant phyla in the two types of sites included Proteobacteria and Acidobacteria, and the shared dominant genera included Bradyrhizobium. In addition, the relative abundances of three unclassified populations of Proteobacteria and functional genes related to cofactor and vitamin metabolism in the rhizosphere soil of infertile mountainous areas were significantly higher than those in control woodland areas. Meanwhile, the dominant microbial phyla in the rhizosphere soil of infertile mountainous areas had a closer correlation with soil enzyme activities and microbial biomass. This study clarified the ecological strategy of C. gilva young forests adapting to infertile mountainous areas: by increasing the relative abundances of functional genes related to cofactor and vitamin metabolism in rhizosphere microorganisms, promoting the enrichment of microorganisms associated with soil nitrogen cycling, and enhancing the correlations between dominant microbial phyla and soil enzyme activities and microbial biomass, the nitrogen resource limitation on soil microbial activity in infertile mountainous areas is balanced. This finding provides direct guidance for optimizing the afforestation and management techniques of C. gilva in infertile mountainous areas and has important practical value for promoting forest ecological restoration. Full article

Lightning rods, while essential for protecting weather radars from direct lightning strikes, act as persistent non-meteorological scatterers that can interfere with signal transmission and reception and thereby degrade detection accuracy and product quality. Existing studies have mainly focused on X-band and C-band systems, and robust, measurement-based quantitative assessments for S-band dual-polarization radars remain scarce. In this study, a controllable tilting lightning rod, a high-precision Far-field Antenna Measurement System (FAMS), and an S-band dual-polarization weather radar (SAD radar) are jointly employed to systematically quantify lightning-rod impacts on antenna electromagnetic parameters under different rod elevation angles and azimuth configurations. Typical precipitation events were analyzed to evaluate the influence of the lightning rods on dual-polarization parameters. The results show that the lightning rod substantially elevates sidelobe levels, with a maximum enhancement of 4.55 dB, while producing only limited changes in the antenna main-beam azimuth and beamwidth. Differential reflectivity ($Z_{DR}$) is the most sensitive polarimetric parameter, exhibiting a persistent positive bias of about 0.24–0.25 dB in snowfall and mixed-phase precipitation, while no persistent azimuthal anomaly is evident during freezing rain; the co-polar correlation coefficient (${\rho }_{hv}$) is only marginally affected. Collectively, these results provide quantitative, far-field evidence of lightning-rod interference in S-band dual-polarization radars and provide practical guidance for more reasonable lightning-rod placement and configuration, as well as useful references for $Z_{DR}$-oriented polarimetric quality-control and correction strategies. Full article

Direct ethanol fuel cells (DEFCs) have gained considerable attention as promising power sources for sustainable energy conversion due to their high energy density, low toxicity, and renewable ethanol feedstock. However, the sluggish ethanol oxidation reaction (EOR) kinetics and the formation of strongly adsorbed intermediates (e.g., CO*, CH_x*) severely hinder catalytic efficiency and durability. Rhodium (Rh)-based catalysts stand out for their balanced intermediate adsorption, efficient C–C bond cleavage, and superior CO tolerance arising from their unique electronic structure. This review summarizes recent advances in Rh-based EOR catalysts, including monometallic Rh nanostructures, Rh-based alloys, and Rh–support composites. The effects of morphology, alloying, and metal–support interactions on activity, selectivity, and stability are discussed in detail. Strategies for structural and electronic regulation—such as nanoscale design, alloying modulation and interfacial engineering—are highlighted to enhance catalytic performance. Finally, current challenges and future directions are outlined, emphasizing the need for Rh-based catalysts with high activity, selectivity and stability, integrating in situ characterization with theoretical modeling. This work provides insights into the structure–activity relationships of Rh-based catalysts and guidance for designing efficient and durable anode catalysts for practical DEFC applications. Full article

Intracardiac echocardiography (ICE) is increasingly recognized as a valuable imaging modality in structural heart interventions, offering high-resolution, real-time visualization from within the cardiac chambers. Originally developed for electrophysiologic procedures, ICE has expanded its use across a broad spectrum of structural interventions, including atrial septal defect (ASD) and patent foramen ovale (PFO) closure, left atrial appendage occlusion (LAAO), transseptal puncture guidance, transcatheter edge-to-edge repair (TEER), balloon mitral valvuloplasty, and both mitral and tricuspid valve therapies. This review outlines the current role and technical principles of ICE, with an emphasis on catheter design, image acquisition protocols, and the emerging potential of 3D ICE. Comparisons with transesophageal echocardiography (TEE) and fluoroscopy are discussed, highlighting ICE’s ability to support minimally invasive, sedation-sparing procedures while maintaining procedural precision. We provide a focused analysis of ICE-guided applications in specific clinical scenarios, emphasizing its role in anatomical assessment, device navigation, and intra-procedural monitoring. Data from recent clinical studies and registries are reviewed to assess safety, feasibility, and outcomes. Practical considerations including operator learning curve, workflow integration, and limitations such as cost and field of view are also addressed. Lastly, we explore future directions including advanced 3D imaging, fusion imaging, artificial intelligence integration, and robotic catheter systems. Full article

This review focuses on the research progress on natural products as β-lactam antibiotic adjuvants, aiming to address the escalating challenge of antibiotic resistance, particularly the inactivation of antibiotics caused by β-lactamases. The article provides an in-depth analysis of the mechanisms by which plant-derived (e.g., flavonoids, tannins, phenolics, terpenoids, and alkaloids) and microbial-derived (e.g., clavulanic acid, fungal metabolites, bacteriophages) natural products enhance antimicrobial efficacy. Key potentiation strategies discussed include efflux pump inhibition, membrane permeability alteration, biofilm disruption, PBP2a inhibition, and direct β-lactamase inhibition. Additionally, the review outlines in vitro methods (e.g., dilution and checkerboard assays) and in vivo models (e.g., mouse infection models) used to assess synergistic effects. It also addresses major challenges in identifying active compounds, elucidating mechanisms of action, and pharmacokinetic characterization. Looking forward, the article highlights the potential of multi-omics approaches, artificial intelligence, and nanotechnology to overcome existing bottlenecks, providing novel strategies for the development of effective and safe antibiotic adjuvants. These advances are expected to provide both theoretical insights and practical guidance for combating antibiotic-resistant bacterial infections. Full article

Geostationary atmospheric motion vectors (e.g., FY4A AMVs) are routine mid-upper atmospheric observations used in numerical weather prediction (NWP) models, yet their complex spatiotemporal errors and assimilation limitations, i.e., high-temporal/coarse-spatial data and large-scale-adjustment/direct-assimilation scheme, leave unclear impacts of AMVs assimilation on nowcasting forecasts. To this end, a Nudging-Forced–3DVar scheme (NFV) is designed within a multi-scale (i.e., 12, 4, and 1 km) regional NWP framework to exploit AMVs characteristics; ablation experiments for the Zhengzhou “7.20” rainstorm isolate Nudging and 3DVar impacts on assimilation and nowcasting. Results show the following: (1) large-scale Nudging and high-resolution 3DVar both improve mid-upper analyses, with the former ingesting more observations; (2) Nudging retains large-scale background updates but yields significant misses, whereas 3DVar intensifies rainfall extremes yet blurs fine structures; (3) NFV merges its strengths, modulating deep convection through upper-level systems and markedly improving rainfall spatiotemporal patterns. Therefore, NFV is recommended for the FY4A AMVs’ future numerical nowcasting, which provides useful guidance for the regional application of geostationary 3D winds. Full article

This study investigated the effects of 6 weeks of plyometric training (PT) performed on soft (unstable) and hard (stable) surfaces compared with conventional training on the balance, explosive power, and muscle strength of adolescent female basketball players. The participants were randomly assigned to three groups: soft-surface PT (n = 14), hard-surface PT (n = 14), and conventional training (n = 14). Performance outcomes included 30 m sprint time, vertical jump height, plantar flexion and dorsiflexion maximal voluntary isometric contraction (MVIC) torque, Y-balance dynamic balance, and center of pressure-based static balance. Ground reaction forces, MVIC torques, and balance parameters were measured using high-precision force sensors to ensure accurate quantification of biomechanical performance. Statistical analyses were performed using two-way repeated-measures ANOVA with post hoc comparisons to evaluate group × time interaction effects across all outcome variables. Results demonstrated that soft- and hard-surface PT significantly improved sprint performance, vertical jump height, and plantar flexion MVIC torque compared with conventional training, while dorsiflexion MVIC increased similarly across all the groups. Notably, soft-surface training elicited greater enhancements in vertical jump height, dynamic balance (posteromedial and posterolateral directions), and static balance under single- and double-leg eyes-closed conditions. The findings suggest that PT on an unstable surface provides unique advantages in optimizing neuromuscular control and postural stability beyond those achieved with stable-surface or conventional training. Thus, soft-surface PT may serve as an effective adjunct to traditional conditioning programs, enhancing sport-specific explosive power and balance. These results provide practical guidance for designing evidence-based and individualized training interventions to improve performance and reduce injury risk among adolescent female basketball athletes. Full article

Underground coal gasification (UCG) is a controlled combustion process of in situ coal that produces combustible gases through thermal and chemical reactions. In order to investigate the UCG induced multi-physical field evolution and overlying strata fracture propagation of deep steeply inclined coal seam (SICS), which play a vital role in safety and sustainable UCG project, this study established a finite element model based on the actual geological conditions of SICS and the controlled retracting injection point (CRIP) technology. The results are listed as follows: (1) the temperature field influence ranges of the shallow and deep parts of SICS expanded from 15.56 m to 17.78 m and from 26.67 m to 28.89 m, respectively, when the burnout cavity length increased from 100 m to 400 m along the dip direction; (2) the floor mudstone exhibited uplift displacement as a result of thermal expansion, while the roof and overlying strata showed stepwise-increasing subsidence displacement over time, which was caused by stress concentration and fracture propagation, reaching a maximum subsidence of 3.29 m when gasification ended; (3) overlying strata rock damages occurred with induced fractures developing and propagating during UCG. These overlying strata fractures can reach a maximum height of 204.44 m that may result in groundwater influx and gasification failure; (4) considering the significant asymmetry in the evolution of multi-physical fields of SICS, it is suggested that the dip-direction length of a single UCG channel be limited to 200 m. The conclusions of this study can provide theoretical guidance and technical support for the design of UCG of SICS. Full article

Early age cracking induced by cement hydration heat in a 37.6 m-wide PK-section concrete box girder was investigated through full-scale field testing and numerical simulation. Material properties, temperature, and strain were measured, and the obtained thermal and mechanical parameters were used to simulate temperature and stress distributions during cantilever casting. Results show that direct casting on the foundation cap led to extensive vertical cracking in diaphragms, where tensile stresses exceeded concrete strength, corresponding to a cracking index of approximately 1.8, with thermal-to-shrinkage stress ratios up to 3:1 in critical regions. Under cantilever construction conditions, significant transverse stress occurred only at the diaphragm bottom, reaching a cracking index of about 1.6, with a thermal-to-shrinkage ratio of 2:1. Reducing casting temperature lowered thermal stress by 0.1 MPa/°C, while adding 0.9 kg/m³ polypropylene fibers increased early-age tensile strength by 15%. Optimized mix design or the inclusion of mineral admixtures such as silica fume further reduced shrinkage. The combined application of these measures effectively mitigated early-age cracking risk, providing practical guidance for the construction of wide-box girders in subtropical climates. Full article

Artificial intelligence technology has increased in popularity in the domain of accounting. Previous studies have focused on analysing the impact of AI integration on accounting in general and on work performance, with few researchers analysing the impact of AI on accounting information. Our study aims to determine the impact of AI on accounting information, on the one hand, and earnings management, on the other, using a bibliometric analysis that examines trends in scientific output. Our analysis was based on the use of the Bibliometrix package of RStudio software. The information is obtained from the “Web of Science” database, which identified 98 articles published in 37 journals that are the subject of our bibliometric analysis for the period 2017–2025. Our study shows that integrating AI into accounting can resolve the problem of information asymmetry, increase the transparency of financial information, and both limit earnings management practices and promote more sophisticated forms of earnings management. The bibliometric results show an increase in scientific output on our topic from 2023 onwards, reaching its peak in 2025. Bibliometric analysis presents productivity over time, identifies the most developed topics and the most cited authors and articles, and reveals the most frequently used keywords. This study provides guidance for future research directions. Full article

To address the thermal management challenges in electronic devices, this study systematically investigates the effects of injection molding and compression molding on the microstructure and thermal conductivity of poly(vinylidene fluoride)/boron nitride nanosheet (PVDF/BNNs) composites. Using 10 μm diameter BNNs as thermal conductive fillers and PVDF as the matrix, the composites were characterized via scanning electron microscopy (SEM), thermal conductivity measurements, rheological analysis, X-ray diffraction (XRD), and mechanical tests. The results demonstrate that the strong shear stress in injection molding induces significant alignment of BNNs along the flow direction, leading to remarkable thermal conductivity anisotropy. At a PVDF/BNNs mass ratio of 90/10, the in-plane thermal conductivity of the injection-molded composite reaches 1.26 W/(m·K), while the through-plane conductivity is only 0.40 W/(m·K). In contrast, compression molding, which involves minimal shear, results in randomly dispersed BNNs and isotropic thermal conductivity, with both in-plane and through-plane values around 0.41 W/(m·K) at the same filler loading. Both processing methods preserve the coexistence of α- and β-crystalline phases in PVDF. However, injection molding enhances matrix crystallinity through stress-induced crystallization, yielding composites with higher density and superior tensile properties. Compression molding, due to slower cooling, leads to incomplete PVDF crystallization, as evidenced by a shoulder peak near 164 °C in differential scanning calorimetry (DSC) curves. This study elucidates the mechanism by which processing methods regulate the structure and properties of PVDF/BNNs composites, offering theoretical and practical guidance for designing high-performance thermally conductive materials. Full article