Search Results (2,800)

The spatial heterogeneity of land surface temperature (LST) within cities is profoundly influenced by the built environment. Although significant progress has been made in the study of the urban thermal environment, there is still a lack of research on how the pattern and structural layout of the built environment affects the thermal environment. In this study, we take the Fifth Ring Road of Beijing as an example, invert the urban LST on the basis of multisource spatial data, characterize the built environment, and use k-means cluster analysis to investigate the main influencing factors of the LST in different functional areas and building patterns within the city, as well as the spatial relationship between the built environment and the urban LST. The results show the following: (1) The urban heat island (UHI) effect occurs to varying degrees over a large part of the study area, and these UHI areas are mainly concentrated in the southwestern part of the city, forming a large contiguous area between the second and fifth ring roads. (2) Class 1 is dominated by transport blocks, Class 3 is dominated by commercial blocks, and Class 5 is dominated by green space blocks, with a clustering index of 0.38. (3) The high-density, high-height class (HH-Class 2) has a greater number of blocks distributed in a ring shape around the periphery of the second ring road. The high-density, low-height class (HL-Class 2) has a relatively small number of blocks but a relatively large area, and the largest blocks are located in the western part of the study area. (4) In the HH and HL building patterns, extreme heat scenarios often occur; from the perspective of functional areas, the probability of extreme heat in the transport block is much higher than that of other functional areas, and except for the HH scenario, the green space functional area plays a very important role in reducing the temperature. This study explores the characteristics of the built environment that influence the urban LST from the perspective of different urban functional zones in cities to provide decision support for quantitative territorial spatial planning, optimization, and management. Full article

The scarcity of hardwoods from tropical forests makes the search for alternative species necessary for commercialization. This study aimed to establish groups of timber species from the Amazon Forest with potential for logging purposes through the assessment of their physical-mechanical properties, aiming to identify alternative species that can meet the market demands. We utilized data from the Forest Products Laboratory (LPF) (containing information on basic density and other wood mechanical properties) and the Timberflow platform, as well. We applied a multivariate cluster analysis technique with the aim of grouping species based on the technological characteristics of their wood and evaluating similarity among them to obtain homogeneous groups in terms of economic potential and utilization. The results indicated four homogeneous groups: Cluster 1 (40.72% of species, basic density-db: 690 kg m⁻³), Cluster 2 (13.92%, db: 260 and 520 kg m⁻³), Cluster 3 (27.32%, db: 550 and 830 kg m⁻³), and Cluster 4 (18.04%, db: 830 kg m⁻³). Most of the 20 listed species are classified as more commercially viable (70%), with high wood density. Species identified as alternatives include Dialium guianense and Zollernia paraensis for Dipteryx odorata, Terminalia argentea for Dinizia excelsa, Terminalia amazonia and Buchenavia grandis for Goupia glabra, and Protium altissimum and Maclura tinctoria for Hymenaea courbaril. The analysis highlighted the overexploitation of a restricted group of species and the need to find alternatives to ensure the sustainability of forest management. This study contributed to identifying species that can serve as alternatives to commercial ones, promoting a more balanced and sustainable forest management. Full article

Understanding the density of possible prices in one-minute intervals provides traders, investors, and financial institutions with the data necessary for making informed decisions, managing risk, optimizing trading strategies, and enhancing the overall efficiency of the cryptocurrency market. While high accuracy is critical for researchers and investors, market nonlinearity and hidden dependencies pose challenges. In this study, the filtered historical simulation is used to generate pathways for the next hour on the one-minute step for Bitcoin and Ethereum quotes. The innovations in the simulation are standardized historical returns resampled with the method of block bootstrapping, which helps to capture any hidden dependencies in the residuals of a conditional parameterization in the mean and variance. Ordinary bootstrapping requires the feed innovations to be free of any dependencies. To deal with complex data structures and dependencies found in ultra-high-frequency data, this study employs block bootstrap to resample contiguous segments, thereby preserving the sequential dependencies and sectoral clustering within the market. These techniques enhance decision-making and risk measures in investment strategies despite the complexities inherent in financial data. This offers a new dimension in measuring the market risk of cryptocurrency prices and can help market participants price these assets, as well as improve the timing of their entry and exit trades. Full article

The spatial allocation of urban public sports facilities is critical for ensuring equitable access to basic public services and maintaining urban spatial cohesion. This study examines central cities in the Yangtze River Delta, utilizing Point of Interest (POI) data to characterize urban sports service facilities. Employing methods such as kernel density estimation, the nearest neighbor index, spatial autocorrelation, and coefficient of variation, this study analyzes the spatial aggregation, synergy, and equalization of sports service facilities at the community scale. The findings indicate that: (1) the spatial distribution of sports service facilities within community life circles demonstrates a clustered pattern, forming a concentric core-to-periphery structure, with notable variations in clustering degrees across different cities; (2) synergy among sports service facilities has significantly improved, with the emergence of multiple high-value clusters and low-value dispersions across various cities; and (3) the level of equalization of sports service facilities in community life circles follows the general order of Shanghai > Nanjing > Hangzhou > Hefei. These insights offer valuable guidance for the planning and optimization of urban public sports facilities. Full article

Hydrogen storage has been a bottleneck factor for the application of hydrogen energy. Hydrogen storage capacity for titanium-decorated boron-doped C₂₀ fullerenes has been investigated using the density functional theory. Different boron-doped C₂₀ fullerene absorbents are examined to avoid titanium atom clustering. According to our research, with three carbon atoms in the pentagonal ring replaced by boron atoms, the binding interaction between the Ti atom and C₂₀ fullerene is stronger than the cohesive energy of titanium. The calculated results revealed that one Ti atom can reversibly adsorb four H₂ molecules with an average adsorption energy of −1.52 eV and an average desorption temperature of 522.5 K. The stability of the best absorbent structure with a gravimetric density of 4.68 wt% has been confirmed by ab initio molecular dynamics simulations. These findings suggest that titanium-decorated boron-doped C₂₀ fullerenes could be considered as a potential candidate for hydrogen storage devices. Full article

Cybersecurity threats, particularly those involving lateral movement within networks, pose significant risks to critical infrastructures such as Microsoft Active Directory. This study addresses the need for effective defense mechanisms that minimize network disruption while preventing attackers from reaching key assets. Modeling Active Directory networks as a graph in which the nodes represent the network components and the edges represent the logical interactions between them, we use centrality metrics to derive the impact of hardening nodes in terms of constraining the progression of attacks. We propose using Unsupervised Learning techniques, specifically density-based clustering algorithms, to identify those nodes given the information provided by their metrics. Our approach includes simulating attack paths using a snowball model, enabling us to analytically evaluate the impact of hardening on delaying Domain Administration compromise. We tested our methodology on both real and synthetic Active Directory graphs, demonstrating that it can significantly slow down the propagation of threats from reaching the Domain Administration across the studied scenarios. Additionally, we explore the potential of these techniques to enable flexible selection of the number of nodes to secure. Our findings suggest that the proposed methods significantly enhance the resilience of Active Directory environments against targeted cyber-attacks. Full article

A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time–frequency domain features, which adopts multi-level processing to solve the time–frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time–frequency image is obtained; then, the fixed frequency signal is removed based on the feature of connected domains, and the conventional frequency hopping (CFH) signal is removed by density-based spatial clustering of applications with noise (DBSCAN); finally, the overlapping region is cropped by the joint energy peak time–domain continuity properties. After the above multi-level joint processing method, the problem of VFH signal processing is effectively solved. The simulation result shows that the Mean Square Error (MSE) between the output results and the time–frequency image of the original VFH signal tends to be close to 0 when the Signal-to-Noise ratio (SNR) is 5 dB. Full article

Regional socioeconomic development is intricately tied to reasonable land-use resources. Although many studies have analyzed land-use carbon emissions, there is a lack of analysis of the concept of intensity. Studying the land-use carbon emission intensity (LUCEI) is crucial for shaping effective land management strategies that support the integrated sustainable development of society, the economy, and the environment. This study examines land-use changes on the Loess Plateau (LP) from 2000 to 2020. The coefficient method, spatial autocorrelation analysis, and optimal parameters-based geographical detector model are used to identify and analyze the spatial clustering patterns and influencing factors affecting LUCEI, which provides more in-depth insights for the study of LUCEI. The results indicate: (1) Urban and Grassland areas showed the most significant growth, with Urban areas expanding by 10,845.21 km² and Grasslands by 7848.91 km², respectively. This Urban expansion was mainly caused by the conversion of Grassland and Cropland, while Grassland expansion was primarily attributed to the decline in Barren. (2) The average LUCEI on the LP climbed from 0.38 in 2000 to 0.73 in 2020, indicating a 190.70% growth rate. (3) The spatial pattern of LUCEI remained stable but unevenly distributed, with extensive High-High and Low-Low clusters. (4) Socioeconomic factors had a greater explanatory power for LUCEI in the LP than natural factors. The LUCEI is not driven by a single factor, but by the combined influence of multiple factors. The interaction between nighttime light and population density explained the spatial distribution of LUCEI most strongly, with a q-value of 0.928. The findings underscore the critical role of socioeconomic development in shaping carbon emission dynamics on the LP. By linking LUCEI growth to land-use changes, this study offers concrete scientific guidance for policymakers seeking to balance socioeconomic growth with sustainable land-use practices. Based on these results, we recommend developing appropriate urban development plans that optimize land-use structures, enhance regional carbon sequestration capacities, and fully implement green transition requirements. Full article

Prior studies have failed to adequately address intangible characteristics and lacked a comprehensive quantification of cultural dimensions. Additionally, such works have not merged supervised and unsupervised classification methodologies. To address these gaps, this study employed multidimensional numerical techniques for precise spatial pattern recognition and urban morphology classification at the block scale. By examining building density, mean floor numbers, functional compositions, and street block mixed-use intensities, alongside historical and contemporary cultural assets within blocks—with assigned weights and entropy calculations from road networks, building vectors, and POI data—a hierarchical categorization of high, medium, and low groups was established. As a consequence, cluster analysis revealed seven distinctive morphology classifications within the studied area, each with unique spatial configurations and evolutionary tendencies. Key findings include the dominance of high-density, mixed-use blocks in the urban core, the persistence of historical morphologies in certain areas, and the emergence of new, high-rise clusters in recently developed zones. The investigation further elucidated the spatial configurations and evolutionary tendencies of each morphology category. These insights lay the groundwork for forthcoming studies to devise morphology-specific management strategies, thereby advancing towards a more scientifically grounded, rational, and precision-focused approach to urban morphology governance. Full article

Magnesium hydride solids doped with transition metals have received attention recently as prospective hydrogen storage materials for a green energy source and a hydrogen economy. In this study, MgTiH_n (n = 1–20) clusters were investigated for the first time by employing the B3PW91 hybrid density functional theory computational chemistry technique with all electron basis sets to determine precise cluster structures and the maximum hydrogen capacity for this model system. We find that hydrogen atoms bind to the metal cluster core until a MgTiH₁₄ saturation limit is reached, with hydrogen dissociation from this system occurring for MgTiH₁₅ and larger cluster sizes. This MgTiH₁₄ cluster contains a large 16.4% hydrogen by mass. This saturation size limit and hydrogen mass percent is larger than the analogous MgScH_n system previously reported. The clusters relative stabilities and electronic properties are discussed along with a possible novel hydrogen dissociation pathway. MgTiH₁₀ and MgTiH₁₃ clusters are predicted to be especially stable species in this size range. Full article

L-cone opsin expression by gene therapy is a promising treatment for blue cone monochromacy (BCM) caused by congenital lack of long- and middle-wavelength-sensitive (L/M) cone function. Eight patients with BCM and confirmed pathogenic variants at the OPN1LW/OPN1MW gene cluster participated. Optical coherence tomography (OCT), chromatic perimetry, chromatic microperimetry, chromatic visual acuity (VA), and chromaticity thresholds were performed with unmodified commercial equipment and/or methods available in the public domain. Adaptive optics scanning laser ophthalmoscope (AOSLO) imaging was performed in a subset of patients. Outer retinal changes were detectable by OCT with an age-related effect on the foveal disease stage. Rod and short-wavelength-sensitive (S) cone functions were relatively retained by perimetry, although likely impacted by age-related increases in the pre-retinal absorption of short-wavelength lights. The central macula showed a large loss of red sensitivity on dark-adapted microperimetry. Chromatic VAs with high-contrast red gratings on a blue background were not detectable. Color vision was severely deficient. AOSLO imaging showed reduced total cone density with majority of the population being non-waveguiding. This study developed and evaluated specialized outcomes that will be needed for the determination of efficacy and safety in human clinical trials. Dark-adapted microperimetry with a red stimulus sampling the central macula would be a key endpoint to evaluate the light sensitivity improvements. VA changes specific to L-opsin can be measured with red gratings on a bright blue background and should also be considered as outcome measures in future interventional trials. Full article

Understanding the spatial distribution and sustainable development of rural tourism is essential for promoting balanced regional growth and formulating optimized policy strategies. This study aims to provide insights into sustainable development and policy optimization. Utilizing geographic information system technology, dominance analysis, and Geodetector statistical methods, this research offers a comprehensive examination of the spatial patterns and determinants of these distributions. The findings reveal significant regional disparities and clustering, with a higher concentration of key villages in economically developed eastern and central regions and fewer in the less developed western regions. The dominance analysis highlights that provinces such as Zhejiang, Shandong, and Beijing demonstrate strong advantages across multiple dimensions, including ecological environment, economic development, tourism infrastructure, transportation accessibility, policy support, and social development. Conversely, regions such as Ningxia, Qinghai, and Tibet exhibit lower dominance scores, indicating challenges in rural tourism development due to limited resources and infrastructure. Key influencing factors include forest coverage, GDP per capita, the number of star-rated hotels, transportation network density, policy initiatives, and urbanization rates. The results underscore the importance of a multi-dimensional approach to enhance rural tourism competitiveness and suggest targeted strategies for underperforming regions. This study contributes to advancing the theoretical framework of sustainable rural tourism and provides actionable insights for policymakers to foster balanced regional development, ecological conservation, and community-centered tourism practices. Full article

Lithium-sulfur (Li-S) batteries are a promising option for energy storage due to their theoretical high energy density and the use of abundant, low-cost sulfur cathodes. Nevertheless, several obstacles remain, including the dissolution of lithium polysulfides (LiPS) into the electrolyte and a restricted operational temperature range. This manuscript presents a promising approach to addressing these challenges. The manuscript describes a straightforward and scalable in situ thermal polymerization method for synthesizing a quasi-solid-state electrolyte (QSE) by gelling pentaerythritol tetraacrylate (PETEA), azobisisobutyronitrile (AIBN), and a dual salt lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and lithium nitrate (LiNO₃)-based liquid electrolyte. The resulting freestanding quasi-solid-state electrolyte (QSE) effectively inhibits the polysulfide shuttle effect across a wider temperature range of −25 °C to 45 °C. The electrolyte’s ability to prevent LiPS migration and cluster formation has been corroborated by scanning electron microscopy (SEM) and Raman spectroscopy analyses. The optimized QSE composition appears to act as a physical barrier, thereby significantly improving battery performance. Notably, the capacity retention has been demonstrated to reach 95% after 100 cycles at a 2C rate. Furthermore, the simple and scalable synthesis process paves the way for the potential commercialization of this technology. Full article

A root factor for the accuracy of all quantum chemical calculations of nuclear magnetic resonance (NMR) chemical shifts is the quality of the molecular equilibrium geometry used. In turn, this quality depends largely on the basis set employed at the geometry optimization stage. This parameter represents the main subject of the present study, which is a continuation of our recent work, where new pecG-n (n = 1, 2) basis sets for the geometry optimization were introduced. A goal of this study was to compare the performance of our geometry-oriented pecG-n (n = 1, 2) basis sets against the other basis sets in massive calculations of ¹³C NMR shielding constants/chemical shifts in terms of their efficacy in reducing geometry factor errors. The testing was carried out with both large-sized biologically active natural products and medium-sized compounds with complicated electronic structures. The former were treated using the computation protocol based on the density functional theory (DFT) and considered in the theoretical benchmarking, while the latter were treated using the computational scheme based on the upper-hierarchy coupled cluster (CC) methods and were used in the practical benchmarking involving the comparison with experimental NMR data. Both the theoretical and practical analyses showed that the pecG-1 and pecG-2 basis sets resulted in substantially reduced geometry factor errors in the calculated ¹³C NMR chemical shifts/shielding constants compared to their commensurate analogs, with the pecG-2 basis set being the best of all the considered basis sets. Full article

The Large and Small Magellanic Clouds (LMC and SMC) form the closest interacting galactic system to the Milky Way, therewith providing a laboratory to test cosmological models in the local Universe. We quantify the likelihood for the Magellanic Clouds (MCs) to be observed within the ΛCDM model using hydrodynamical simulations of the IllustrisTNG project. The orbits of the MCs are constrained by proper motion measurements taken by the Hubble Space Telescope and Gaia. The MCs have a mutual separation of dMCs=24.5kpc and a relative velocity of vMCs=90.8kms−1, implying a specific phase-space density of fMCs,obs≡(dMCs·vMCs)−3=9.10×10−11km−3s3kpc−3. We select analogues to the MCs based on their stellar masses and distances in MW-like halos. None of the selected LMC analogues have a higher total mass and lower Galactocentric distance than the LMC, resulting in >3.75σ tension. We also find that the fMCs distribution in the highest resolution TNG50 simulation is in 3.95σ tension with observations. Thus, a hierarchical clustering of two massive satellites like the MCs in a narrow phase-space volume is unlikely in ΛCDM, presumably because of short merger timescales due to dynamical friction between the overlapping dark matter halos. We show that group infall led by an LMC analogue cannot populate the Galactic disc of satellites (DoS), implying that the DoS and the MCs formed in physically unrelated ways in ΛCDM. Since the 20∘ alignment of the LMC and DoS orbital poles has a likelihood of P=0.030 (2.17σ), adding this χ2 to that of fMCs gives a combined likelihood of P=3.90×10−5 (4.11σ). Full article