Search Results (114)

With the rapid growth of energy demand, the development of efficient energy-conversion technologies (e.g., water splitting, fuel cells, metal-air batteries, etc.) becomes an important way to circumvent the problems of fossil fuel depletion and environmental pollution, which motivates the pursuit of high-performance electrocatalysts with controllable compositions and morphologies. Among them, two-dimensional (2D) Pt-group metallic electrocatalysts show a series of distinctive architectural merits, including a high surface-to-volume ratio, numerous unsaturated metal atoms, an ameliorative electronic structure, and abundant electron/ion transfers channels, thus holding great potential in realizing good selectivity, rapid kinetics, and high efficiency for various energy-conversion devices. Considering that great progress on this topic has been made in recent years, here we present a panoramic review of recent advancements in 2D Pt-group metallic nanocrystals, which covers diverse synthetic methods, structural analysis, and their applications as electrode catalysts for various energy-conversion technologies. At the end, the paper also outlines the research challenges and future opportunities in this emerging area. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

Research on the supply–demand relationships of ecosystem services (ESs) in alpine pastoral regions remains relatively scarce, yet it is crucial for regional ecological management and sustainable development. This study focuses on the Sanjiangyuan Region, a typical alpine pastoral area and significant ecological barrier, to quantitatively assess the supply–demand dynamics of key ESs and their spatial heterogeneity from 2000 to 2020. It further aims to elucidate the underlying driving mechanisms, thereby providing a scientific basis for optimizing regional ecological management. Four key ES indicators were selected: water yield (WY), grass yield (GY), soil conservation (SC), and habitat quality (HQ). ES supply and demand were quantified using an integrated approach incorporating the InVEST model, the Revised Universal Soil Loss Equation (RUSLE), and spatial analysis techniques. Building on this, the spatial patterns and temporal evolution characteristics of ES supply–demand relationships were analyzed. Subsequently, the Geographic Detector Model (GDM) and Geographically and Temporally Weighted Regression (GTWR) model were employed to identify key drivers influencing changes in the comprehensive ES supply–demand ratio. The results revealed the following: (1) Spatial Patterns: Overall ES supply capacity exhibited a spatial differentiation characterized by “higher values in the southeast and lower values in the northwest.” Areas of high ES demand were primarily concentrated in the densely populated eastern region. WY, SC, and HQ generally exhibited a surplus state, whereas GY showed supply falling short of demand in the densely populated eastern areas. (2) Temporal Dynamics: Between 2000 and 2020, the supply–demand ratios of WY and SC displayed a fluctuating downward trend. The HQ ratio remained relatively stable, while the GY ratio showed a significant and continuous upward trend, indicating positive outcomes from regional grass–livestock balance policies. (3) Driving Mechanisms: Climate and natural factors were the dominant drivers of changes in the ES supply–demand ratio. Analysis using the Geographical Detector’s q-statistic identified fractional vegetation cover (FVC, q = 0.72), annual precipitation (PR, q = 0.63), and human disturbance intensity (HD, q = 0.38) as the top three most influential factors. This study systematically reveals the spatial heterogeneity characteristics, dynamic evolution patterns, and core driving mechanisms of ES supply and demand in an alpine pastoral region, addressing a significant research gap. The findings not only provide a reference for ES supply–demand assessment in similar regions regarding indicator selection and methodology but also offer direct scientific support for precisely identifying priority areas for ecological conservation and restoration, optimizing grass–livestock balance management, and enhancing ecosystem sustainability within the Sanjiangyuan Region. Full article

The rapid urbanization in the Kabul River Basin has increased the demand for water for both drinking and commercial purposes, leading to domestic and industrial water insecurity. Assessing the groundwater potential of the Kabul River Basin is highly crucial for effective water management. The aim of this paper is to identify potential zones for groundwater by employing a Geographic Information System and an Analytical Hierarchy Process approach to formulate a cumulative score based on seven thematic images—rainfall, geology, lineament density, drainage density, land use/land cover, soil type, and slope—within the Kabul River, with assigned weightages of 32%, 27%, 12%, 10%, 8%, 6%, and 5%, respectively, with a consistency ratio of 0.053 (5%), demonstrating the reliability of the results. The study shows that the first three factors contribute more to the percentages of Groundwater Potential Zones. The identified groundwater potential is classified into very good, good, medium, poor, and very poor zones, covering 35.45% (19,989 km²), 37.2% (20,978 km²), 23.16% (13,063 km²), 4.13% (2332 km²), and 0.06% (19 km²), respectively. Groundwater potential in the basin is predominantly classified as good to medium; however, there are notable variations across sub-basins. The Swat sub-basin and western parts of the Kabul River Basin, encompassing the Panjshir and Parwan districts, exhibit exceptionally high groundwater potential. In contrast, the Panjkora sub-basin (Dir district) and southwestern areas of the Kabul River Basin, covering parts of the Ghazni and Wardak districts, have very limited groundwater potential. Full article

Climate change requires efficient water resource management, especially in regions where viticulture is developing. This study evaluates the water requirements, precipitation deficits, and irrigation needs of vineyards in two locations in southern Poland. The analysis covers both a reference period (1931–2020) and a forecast period (2030–2100), based on two climate change scenarios: RCP 4.5 and RCP 8.5. Grapevine water requirements were estimated using a crop coefficient tailored to Poland’s agroclimatic conditions, combined with meteorological data on air temperature and precipitation. Monthly crop coefficient values were calculated as the ratio of grapevine potential evapotranspiration, estimated using the Penman–Monteith method, to reference evapotranspiration, calculated using the Treder approach for the period 1981–2010. Precipitation deficits were assessed for normal, medium dry, and very dry years using the Ostromęcki method. Irrigation water demand was estimated for light, medium, and heavy soils using the Pittenger method. The results indicate a significant increase in both water demand and precipitation deficits in the forecast period, regardless of the scenario. In very dry years, irrigation will be necessary for all soil types. In medium dry years, water deficits will primarily affect vineyards on light soils. These findings underscore the urgent need for improvements in irrigation planning, especially in areas with low soil water. They offer practical insights for estimating future water storage needs and implementing precision irrigation adapted to changing climate conditions. Adopting such adaptive strategies is essential for sustaining vineyard productivity and improving water use efficiency. This study also supports the integration of climate projections into regional planning and calls for investment in innovative, water-saving technologies to strengthen the long-term resilience of Poland’s wine industry. Full article

With economic development and improved living standards, the demand for mutton and wool continues to grow, and improving the production performance and genetic potential of sheep breeds has become the key to promoting the high-quality development of the sheep industry. Thus, this study analyzes the influencing factors of the early production traits of Yunnan semi-fine wool sheep, optimizes the genetic evaluation model, and relies on accurate genetic parameter estimation to provide a theoretical basis for formulating a scientific and efficient breeding strategy for this breed. Data were collected from the Laishishan and Xiaohai breeding farms in Qiaojia, Yunnan, covering production records of the core flock from 2018 to 2022. Using the GLM procedure in SAS 9.4 software, this study analyzed the non-genetic influences on early production traits in Yunnan semi-fine wool sheep. Concurrently, Danish Milk Unit 5 (DMU 5) software estimated the variance components across various animal models for each trait. Employing the Akaike Information Criterion (AIC) and likelihood ratio test (LRT), six models were tested, incorporating or excluding maternal inheritance and environmental impacts, to identify the optimal model for deriving the genetic parameters. The results show that the birth year, dam age, sex, flock and litter size significantly affect both the Birth Weight (BWT) and Weaning Weight (WWT) (p < 0.01). Additionally, the birth month was found to exert a significant effect on Birth Weight (BWT) (p < 0.01), the weaning month has a significant effect on the Weaning Weight (WWT) (p < 0.05). No significant effects of farm location were observed on either trait (p > 0.05). The most accurate genetic evaluation model determined the heritability of the Birth Weight (BWT) and Weaning Weight (WWT) as 0.3123 and 0.3471. From a production perspective, improving lamb birth, Weaning Weight (WWT), feed composition, and maternal nutrition during gestation is vital for breeding efficiency. This study not only identified the optimal animal models for early growth traits in Yunnan semi-fine wool sheep, offering a precise basis for estimating genetic parameters but also provides theoretical guidance for genetic selection and breed improvement in this population. Full article

Bell towers, due to their slender geometry and structural configuration, are among the buildings most susceptible to deterioration from weathering and seismic events. These aspects influence the structural assessment of these historic towers, which is essential for their conservation and maintenance. The “Carmine Maggiore” bell tower in Naples (Italy) has been an important and prominent landmark of the city for centuries. It is square in plan and 72 m high. Over time, it suffered extensive damage and was severely damaged by the earthquake of 1456. Reconstruction began in the first decade of the 17th century and the original design was modified, adding two stories and changing the shape of the plan to octagonal. In the centuries that followed, the structure was damaged again and further interventions were carried out, adding tie-rods and replacing damaged elements. Today, the bell tower has very elaborate façades with mouldings and decorations, so that the supporting structure appears to be covered with plaster, stucco, and stone elements. This paper describes the results of FEM analyses of the bell tower, obtained from models with different levels of complexity to evaluate the influence of stone cladding elements on the seismic behaviour. In particular, the difference in the IS safety indices, calculated as the ratio of capacity to demand, exceeds 15%, due to the mechanical consistency of the cladding elements, which contribute significantly to both stiffness and strength. Full article

The terahertz (THz) band, ranging from 0.1 to 10 THz, offers substantial bandwidths that are essential for meeting the ever-increasing demands for high data rates in future wireless communication systems. This paper presents a comprehensive comparative analysis of various multicarrier waveforms suitable for THz-band communications. We explore the performance, advantages, and limitations of several waveforms, including Orthogonal Frequency Division Multiplexing (OFDM), Filter Bank Multicarrier (FBMC), Universal Filtered Multicarrier (UFMC), and Generalized Frequency Division Multiplexing (GFDM). The analysis covers key parameters such as spectral efficiency, the peak-to-average power ratio (PAPR), robustness to phase noise, and computational complexity. The simulation results demonstrate that while OFDM offers simplicity and robustness to multipath fading, it suffers from high PAPR and phase noise sensitivity. FBMC and UFMC, with their enhanced spectral efficiency and reduced out-of-band emissions, show promise for THz-band applications but come at the cost of increased computational complexity. GFDM presents a flexible framework with a trade-off between complexity and performance, making it a potential candidate for diverse THz communication scenarios. Our study concludes that no single waveform universally outperforms the others across all metrics. Therefore, the choice of multicarrier waveform for THz communications should be tailored to the specific requirements of the application, balancing performance criteria and implementation feasibility. Future research directions include the development of hybrid waveforms and adaptive techniques to dynamically optimize performance in varying THz communication environments. Full article

Background: Systemic advanced therapies, including biologic drugs and Janus kinase (JAK) inhibitors, have revolutionized atopic dermatitis management. The increasing number of available options for such complex diseases demands careful treatment selection for each patient, considering numerous variables. Comparative analyses of these treatment modalities in the real world are still limited. Only a faithful basal characterization would enable posterior meaningful and accurate comparisons of the efficacy and safety profiles of these groups of drugs. This communication focuses on describing and comparing the baseline demographics and comorbidities of patients with atopic dermatitis currently treated with biologic therapies versus JAK inhibitors in our setting. Methods: We conducted an observational, descriptive, and ambispective study across three hospitals covering a population of over 500,000 inhabitants from January 2019 to December 2024. Baseline demographic data, anthropometric measures, lifestyle factors, cardiovascular risk factors, and comorbidities were analyzed using descriptive and inferential statistics. Additionally, basal severity and effectivity over time have also been compared. Results: A total of 150 patients were analyzed. A total of 102 had received biological therapies (dupilumab or tralokinumab), whereas 48 patients had received JAK inhibitors (upadacitinib, baricitinib, or abrocitinib). Ages ranged from 11 to 76 years. The overall cohort had a mean age of 35.87 ± 14.37 years and a male predominance (male-to-female ratio 1.63:1). Hypertension was more prevalent in the JAK inhibitors group (p = 0.0175), yet other cardiovascular risk factors, body measurements, atopic and non-atopic comorbidities, and disease severity were comparable across both groups. Conclusions: This study helped to characterize the baseline characteristics of patients treated with advanced systemic therapies in a real-world clinical setting. It pointed to just slight differences between the profiles of patients treated with biologics versus JAK inhibitors. This homogeneity in baseline characteristics sets the ground for further future comparisons of treatment outcomes in this cohort as potential confounding factors related to group imbalances are minimized. Full article

Due to the energy transition, the future electric power system will face further challenges that affect the functionality of the electricity grid and therefore the security of supply. For this reason, this article examines the future frequency stabilisation in a 100% renewable electric power system. A focus is set on the provision of inertia and frequency containment reserve. Today, the frequency stabilisation in most power systems is based on synchronous generators. By using grid-forming frequency converters, a large potential of alternative frequency stabilisation reserves can be tapped. Consequently, frequency stabilisation is not a problem of existing capacities but whether and how these are utilised. Therefore, in this paper, a collaborative approach to realise frequency stabilisation is proposed. By distributing the required inertia and frequency containment reserve across all technologies that are able to provide it, the relative contribution of each individual provider is low. To cover the need for frequency containment reserve, each capable technology would have to provide less than 1% of its rated power. The inertia demand can be covered by the available capacities at a coverage ratio of 171% (excluding wind power) to 217% (all capacities). As a result, it is proposed that provision of frequency stabilisation is made mandatory for all capable technologies. The joint provision distributes the burden of frequency stabilisation across many participants and hence increases redundancy. It ensures the stability of future electricity grids, and at the same time, it reduces the technological and economic effort. The findings are presented for the example of the German electricity grid. Full article

This paper presents a comprehensive review of automated modal identification techniques, focusing on various established and emerging methods, particularly Stochastic Subspace Identification (SSI). Automated modal identification plays a crucial role in structural health monitoring (SHM) by extracting key modal parameters such as natural frequencies, damping ratios, and mode shapes from vibration data. To address the limitations of traditional manual methods, several approaches have been developed to automate this process. Among these, SSI stands out as one of the most effective time-domain methods due to its robustness in handling noisy environments and closely spaced modes. This review examines SSI-based algorithms, covering essential components such as system identification, noise mode elimination, stabilization diagram interpretation, and clustering techniques for mode identification. Advanced SSI implementations that incorporate real-time recursive estimation, adaptive stabilization criteria, and automated mode selection are also discussed. Additionally, the review covers frequency-domain methods like Frequency Domain Decomposition (FDD) and Enhanced Frequency Domain Decomposition (EFDD), highlighting their application in spectral analysis and modal parameter extraction. Techniques based on machine learning (ML), deep learning (DL), and artificial intelligence (AI) are explored for their ability to automate feature extraction, classification, and decision making in large-scale SHM systems. This review concludes by highlighting the current challenges, such as computational demands and data management, and proposing future directions for research in automated modal analysis to support resilient, sustainable infrastructure. Full article

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by $96.275\times {10}^8\mathrm{t}$, $81.210\times {10}^8\mathrm{t}$, and $84.13\times {10}^8\mathrm{t}$ relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply. Full article

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km² study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km²), 47.68% (3617.13 km²), 37.12% (2816.13 km²), and 5.97% (452.70 km²) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 10⁶ m³/year, constituting 22.7% of the total precipitation volume (11,227 × 10⁶ m³/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation. Full article

Metal matrix composites (MMCs) are essential materials in various industries due to superior properties, such as high strength-to-weight ratios, better corrosion resistance, improved wear resistance and adaptability, developed by continuous improvements in their fabrication methods. This helps to meet the growing demand for high-performance and sustainable products. The industries that stand to gain the most are automotive and aerospace, where MMCs are used for car parts, airplane frames, and jet engines that need to be strong and lightweight. Furthermore, MMCs are being extensively used in the biomedical industry for implants and medical equipment because of their suitable mechanical integrity and corrosion resistance. Applications in heavy construction, defense, and even space exploration are noteworthy. The advancements in fabrication of MMCs have revolutionized the composite industry with their improved mechanical, tribological, and metallurgical properties. This review article offers an introduction and thorough examination of the most recent advancements (mostly within the last five years) in fabrication methods of MMCs. The novelty and modernization in the traditional processes and advanced processes are covered, along with discussing the process parameters’ effects on the microstructure and properties of the composites. The review focuses on features and prospective applications of MMCs that have been greatly improved and extended due to such advancements. The most recent methods for developing MMCs, including friction stir processing (FSP), ultrasonic-assisted stir casting, and additive manufacturing, are discussed. Artificial intelligence and machine learning interventions for composite manufacturing are also included in this review. This article aims to assist researchers and scholars and encourage them to conduct future research and pursue innovations to establish the field further. Full article

Polyurethanes are the result of a reaction between an isocyanate and a polyol. The large variety of possible reagents creates many possible polyurethanes to be made, such as soft foams, rigid foams, coatings, and adhesives. This polymer is one of the most produced and consumed polymers in the world with an ever-increasing demand. Despite its usual petrochemical nature, research on bio-based polyurethanes flourishes due to the ease in creating bio-based polyols. This work covers the synthesis of a novel macauba kernel oil polyol by the epoxidation of the oil, followed by a ring-opening reaction of the epoxide with glycerol, used for the preparation of polyurethane foams using different NCO/OH ratios. The FTIR and H¹ results confirm the formation of the epoxide and polyol, and the polymers in all NCO/OH ratios were confirmed by FTIR, showing great similarities between the samples, especially PU 1.0 and PU 1.2. Despite the TGs showing close behaviors for the three samples, their DTGs showed great difference between the samples, with PU 1.0 presenting a regular PU DTG profile with three degradation peaks while the other two sample presented five degradation peaks, indicating a higher crosslinking density in them. Full article