Search Results (7,268)

This study proposes an image-enhancement method to address the challenges of low visibility and color distortion in images captured during yellow sandstorms for an image sensor based outdoor surveillance system. The technique combines traditional image processing with deep learning to improve image quality while preserving color consistency during transformation. Conventional methods can partially improve color representation and reduce blurriness in sand–dust environments. However, they are limited in their ability to restore fine details and sharp object boundaries effectively. In contrast, the proposed method incorporates Retinex-based processing into the training phase, enabling enhanced clarity and sharpness in the restored images. The proposed framework comprises three main steps. First, a cycle-consistent generative adversarial network (CycleGAN) is trained with unpaired images to generate synthetically paired data. Second, CycleGAN is retrained using these generated images along with clear images obtained through multiscale image decomposition, allowing the model to transform dust-interfered images into clear ones. Finally, color preservation is achieved by selecting the A and B chrominance channels from the small-scale model to maintain the original color characteristics. The experimental results confirmed that the proposed method effectively restores image color and removes sand–dust-related interference, thereby providing enhanced visual quality under sandstorm conditions. Specifically, it outperformed algorithm-based dust removal methods such as Sand-Dust Image Enhancement (SDIE), Chromatic Variance Consistency Gamma and Correction-Based Dehazing (CVCGCBD), and Rank-One Prior (ROP+), as well as machine learning-based methods including Fusion strategy and Two-in-One Low-Visibility Enhancement Network (TOENet), achieving a Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score of 17.238, which demonstrates improved perceptual quality, and an Local Phase Coherence-Sharpness Index (LPC-SI) value of 0.973, indicating enhanced sharpness. Both metrics showed superior performance compared to conventional methods. When applied to Closed-Circuit Television (CCTV) systems, the proposed method is expected to mitigate the adverse effects of color distortion and image blurring caused by sand–dust, thereby effectively improving visual clarity in practical surveillance applications. Full article

This study investigates the primary frequency regulation dynamic characteristics of industrial steam extraction turbine units under deep peak regulation conditions. A high-fidelity integrated dynamic model was established, incorporating the governor system, steam turbine with extraction modules, and interconnected pipeline dynamics. Through comparative simulations and experimental validation, the model demonstrates high accuracy in replicating real-unit responses to frequency disturbances. For the power grid system in this study, the frequency disturbance mainly comes from three aspects: first, the power imbalance formed by the random mutation of the load side and the intermittence of new energy power generation; second, transformation of the energy structure directly reduces the available frequency modulation resources; third, the system-equivalent inertia collapse effect caused by the integration of high permeability new energy; the rotational inertia provided by the traditional synchronous unit is significantly reduced. In the cogeneration unit and its control system in Guangxi involved in this article, key findings reveal that increased peak regulation depth (30~50% rated power) exacerbates nonlinear fluctuations. This is due to boiler combustion stability thresholds and steam pressure variations. Key parameters—dead band, power limit, and droop coefficient—have coupled effects on performance. Specifically, too much dead band (>0.10 Hz) reduces sensitivity; likewise, too high a power limit (>4.44%) leads to overshoot and slow recovery. The robustness of parameter configurations is further validated under source-load random-intermittent coupling disturbances, highlighting enhanced anti-interference capability. By constructing a coordinated control model of primary frequency modulation, the regulation strategy of boiler and steam turbine linkage is studied, and the optimization interval of frequency modulation dead zone, adjustment coefficient, and frequency modulation limit parameters are quantified. Based on the sensitivity theory, the dynamic influence mechanism of the key control parameters in the main module is analyzed, and the degree of influence of each parameter on the frequency modulation performance is clarified. This research provides theoretical guidance for optimizing frequency regulation strategies in coal-fired units integrated with renewable energy systems. Full article

Globalization, digital transformation, and organizational changes have led to significant transformations in the world of work, substantially increasing workloads, which can result in high levels of stress and burnout among employees. The main objective of this study was to investigate the association between occupational stress and perceived performance and whether this relationship was mediated by burnout. In addition, we sought to understand whether the work regime (in-person, hybrid, and remote) moderates the relationship between occupational stress and burnout. The sample for this study consisted of 325 participants working in organizations based in Portugal. The data collection procedure was non-probabilistic, intentional, and snowball-type. This is an exploratory, correlational, and cross-sectional study. The results indicate that only the dimension ‘stress with users’ has a negative and significant association with performance. On the other hand, the dimension ‘stress with career and remuneration’ has a positive and significant association with performance. The dimensions ‘stress with users’ and ‘stress with workload’ have a positive and significant association with performance. Only ‘stress with workload’ has a positive and significant association with exhaustion. Distancing has a total mediating effect on the relationship between stress with users and perceived performance. The work regime has a significant effect on distancing. The work regime moderates the relationship between ‘stress with working’ conditions and exhaustion. Given the current work regimes, especially after the COVID-19 pandemic, it can be concluded that, among the dimensions of occupational stress, the most critical is stress with working conditions. Full article

The acceleration of industrialization and urbanization have led to the increasingly serious problem of waste gas pollution. Pollutants such as sulfur dioxide (SO₂), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH₃), formaldehyde (HCHO), and hydrogen sulfide (H₂S) emitted from industrial production, transportation, and agricultural activities have posed a major threat to the ecological environment and public health. Although traditional physical and chemical treatment methods can partially reduce the concentration of pollutants, they face three core bottlenecks of high cost, high energy consumption, and secondary pollution, and it is urgent to develop sustainable alternative technologies. In this context, probiotic waste gas treatment technology has become an emerging research hotspot due to its environmental friendliness, low energy consumption characteristics, and resource conversion potential. Based on the databases of PubMed, Web of Science Core Collection, Scopus, Embase, and Cochrane Library, this paper systematically searched the literature published from 2014 to 2024 according to the predetermined inclusion and exclusion criteria (such as research topic relevance, experimental data integrity, language in English, etc.). A total of 71 high-quality studies were selected from more than 600 studies for review. By integrating three perspectives (basic theory perspective, environmental application perspective, and waste gas treatment facility perspective), the metabolic mechanism, functional strain characteristics, engineering application status, and cost-effectiveness of probiotics in waste gas bioconversion were systematically analyzed. The main conclusions include the following: probiotics achieve efficient degradation and recycling of waste gas pollutants through specific enzyme catalysis, and compound flora and intelligent regulation can significantly improve the stability and adaptability of the system. This technology has shown good environmental and economic benefits in multi-industry waste gas treatment, but it still faces challenges such as complex waste gas adaptability and long-term operational stability. This review aims to provide useful theoretical support for the optimization and large-scale application of probiotic waste gas treatment technology, promote the transformation of waste gas treatment from ‘end treatment’ to ‘green transformation’, and ultimately serve the realization of sustainable development goals. Full article

The Belt and Road Initiative (BRI) promotes significant cross-border investment, raising critical questions about its environmental consequences, particularly regarding carbon emissions. This paper uses panel data from 47 countries that participated in the “Belt and Road Initiative” earlier from 2000 to 2020 to conduct theoretical analysis and empirical research on the relationship between the coordinated development of two-way FDI and carbon emission intensity, dividing it into scale effect, technology effect and structure effect. The coordinated development of two-way FDI can have an increasing or decreasing impact on carbon emission intensity through these three effects. The main findings of this paper are as follows: (1) The improvement of the degree of coordinated development of two-way FDI significantly reduces carbon emission intensity. (2) The improvement of the degree of coordinated development of two-way FDI can enhance the level of technological innovation, while the improvement of the level of technological innovation will increase carbon emission intensity, thereby reducing the carbon emission reduction effect of the coordinated development of two-way FDI. (3) The improvement of the degree of coordinated development of two-way FDI can reduce carbon emission intensity by promoting the upgrading of industrial structure. Based on the above conclusions, this paper puts forward the following suggestions for the subsequent development of countries along the “Belt and Road”: (1) Further increase two-way FDI and promote the coordinated development of two-way FDI. (2) Promote the upgrading of industrial structure and the green transformation of technology. (3) Increase economic freedom to provide a good environment for economic development. Full article

To understand how landscapes have changed in Yanqing District, Beijing, during its urban development over the past 15 years, we referred to the Landscape Character Assessment (LCA) theory, selecting altitude, slope, roughness, forest type, land cover, and forest vegetation cover as characteristic factors, identified nine types of landscape character types (LCTs) from 2005 to 2020 through unsupervised clustering. Then, we applied multi-model interpreters, including the Optimal Parameter-Based Geographical Detector (OPGD) and SHapley Additive exPlanations (SHAP), to analyze how social and natural factors impact the spatiotemporal changes of these LCTs. The results indicate that over the past 15 years, the landscape character of Yanqing District has undergone significant changes, with more frequent changes occurring in the “piedmont” areas where mountains meet plains. Slope and precipitation are the main factors affecting the intensity of LCT changes. In contrast, the transformation of different landscape characters is affected by factors such as altitude, slope, precipitation, and distance to artificial surfaces. This study reveals the dynamic changes in landscape character and their driving mechanisms, helping to develop more targeted strategies for landscape management in Yanqing District to promote sustainable regional development. Full article

Urban development is the planned growth of cities that takes into account ecological issues, the needs of urban life, social and technical equipment standards, and quality of life. However, as a result of policies implemented by decision-makers and users, both planned and unplanned, urban space is expanding spatially outwards from the city, while also experiencing densification in vacant areas within the city and functional transformations in land use. This process, known as urban sprawl, has been intensely debated over the past century. Making the negative effects of urban sprawl measurable and understandable from a scientific perspective is critically important for sustainable urban planning and management. Transportation surfaces hold a significant share in the land use patterns of expanding cities in physical space, and accessibility is one of the main driving forces behind land use change. Therefore, the most significant consequence of urban sprawl is the increase in urban mobility, which is shaped by the needs of urban residents to access urban functions. This increase poses risk factors for the planning period in terms of time, cost, and especially environmental impact. Urban space has a dynamic and complex structure. Planning is based on being able to guess how this structure will change over time. At first, geometric models were used to study cities, but as time went on and the network of relationships became more complicated, more modern and technological methods were needed. Artificial Neural Networks, Support Vector Machines, Agent-Based Models, Markov Chain Models, and Cellular Automata, developed using computer-aided design technologies, can be cited as examples of these approaches. In this study, the temporal change in urban sprawl and its relationship with influencing factors will be revealed using the SLEUTH model, which is one of the cellular automata-based urban simulation models. Erzurum, one of the medium-sized metropolitan cities that gained importance after the conversion of provincial borders into municipal borders with the Metropolitan Law No. 6360, has been selected as the case study area for this research. The urban sprawl process and determining factors of Erzurum will be analyzed using the SLEUTH model. By creating a simulation model of the current situation within the specified time periods and generating future scenarios, the aim is to develop planning decisions with sustainable, ecological, and optimal size and density values. Full article

The crystal structure, texture, martensitic transformation, and magnetic properties of magnetic shape-memory Heusler alloys of Ni_51−xMn_33.4In_15.6V_x (x = 0; 0.1; 0.3; 0.5; 1) were investigated. Experimental studies of the magnetic properties and meta-magnetostructural transition (martensitic transition—MT) confirm the main sensitivity of the martensitic transition temperature to vanadium doping and to an applied magnetic field. This makes this family of shape-memory alloys promising for use in numerous applications, such as magnetocaloric cooling and MEMS technology. Diffuse electron scattering was analyzed, and the structures of the austenite and martensite were determined, including the use of TEM in situ experiments during heating and cooling for an alloy with a 0.3 at.% concentration of V. In the austenitic state, the alloys are characterized by a high-temperature-ordered phase of the L2₁ type. The images show nanodomain structures in the form of tweed contrast and contrast from antiphase domains and antiphase boundaries. The alloy microstructure in the temperature range from the martensitic finish to 113 K consists of a six-layer modulated martensite, with 10 M and 14 M modulation observed in local zones. The morphology of the double structure of the modulated martensite structure inherits the morphology of the nanodomain structure in the parent phase. This suggests that it is possible to control the structure of the high-temperature austenite phase and the temperature of the martensitic transition by alloying and/or rapidly quenching from the high-temperature phase. In addition, attention is paid to maintaining fine interface structures. High-resolution transmission electron microscopy showed good coherence along the austenite–martensite boundary. Full article

Amorphous solid dispersions (ASDs) represent a promising formulation strategy for improving the solubility and bioavailability of poorly water-soluble drugs, a major challenge in pharmaceutical development. This review provides a comprehensive analysis of the physicochemical principles underlying ASD stability, with a focus on drug–polymer miscibility, molecular mobility, and thermodynamic properties. The main manufacturing techniques including hot-melt extrusion, spray drying, and KinetiSol^® dispersing are discussed for their impact on formulation homogeneity and scalability. Recent advances in excipient selection, molecular modeling, and in silico predictive approaches have transformed ASD design, reducing dependence on traditional trial-and-error methods. Furthermore, machine learning and artificial intelligence (AI)-based computational platforms are reshaping formulation strategies by enabling accurate predictions of drug–polymer interactions and physical stability. Advanced characterization methods such as solid-state NMR, IR, and dielectric spectroscopy provide valuable insights into phase separation and recrystallization. Despite these technological innovations, ensuring long-term stability and maintaining supersaturation remain significant challenges for ASDs. Integrated formulation design frameworks, including PBPK modeling and accelerated stability testing, offer potential solutions to address these issues. Future research should emphasize interdisciplinary collaboration, leveraging computational advancements together with experimental validation to refine formulation strategies and accelerate clinical translation. The scientists can unlock the full therapeutic potential with emerging technologies and a data-driven approach. Full article

This paper presents the design and experimental evaluation of a compact microstrip patch antenna and a 4 × 4 phased antenna array system tailored for Wi-Fi 6E applications, U-NII-5 band. A single inset-fed microstrip patch antenna was first optimized through full-wave simulations, achieving a resonant frequency of 5.96 GHz with a measured return loss of −17.5 dB and stable broadside radiation. Building on this element, a corporate-fed 4 × 4 array was implemented on an FR4 substrate, incorporating stepped-impedance transmission lines and λ/4 transformers to ensure equal power division and impedance matching across all ports. A 4-bit digital phase shifter, controlled by an ATmega328p microcontroller, was integrated to enable electronic beam steering. Simulated results demonstrated accurate beam control within ±28°, with directional gains above 13 dBi and minimal degradation compared to the broadside case. Over-the-air measurements validated these findings, showing main lobe steering at 0°, ±15°, +33° and −30° with peak gains between 7.8 and 11.5 dBi. The proposed design demonstrates a cost-effective and practical solution for Wi-Fi 6E phased array antennas, offering enhanced beamforming, improved spatial coverage, and reliable performance in next-generation wireless networks. Full article

This paper considers how Buddhist art of the early Tang dynasty was shaped by concerns with states of consciousness and transmigrating spiritual entities. Focusing on the Medicine Buddha (Skt. Bhaiṣajyaguru) tableau in the main chamber of Mogao Cave 220, dated to 642 CE and among the earliest full wall transformation tableaux at Dunhuang, I propose that the tableau depicts a structured process centered around the transmigrating spiritual entity of spirit consciousness (shenshi 神識) and its transformations that were visually expressed by lighting devices. Other elements in the tableau, such as the dancers and bodhisattvas seated in the pond, are also part and parcel to this visual project of transformation, as indicated through the colors of their attire and the types of dance being performed. The spirit consciousness could be visualized through lighting devices in the Medicine Buddha tableau because of the associations of lamps with vital, spiritual parts of humans since the first century CE. More importantly, the central role of the spirit consciousness in the Medicine Buddha tableau shows that such Buddhist murals depicting rituals and performances situated among grand edifices could be visual expressions of states of spiritual entities and their transformations. Seemingly intangible spiritual entities in Buddhist art were thus inextricably intertwined with and visually expressed through physical objects and their representations. To this end, this study is a first step towards understanding the pictorial program of Mogao Cave 220 and similar cases through explorations of cognitive templates that informed the creation and production of Buddhist art, with the spirit consciousness as a case in point. Full article

Background: Facing global wheat production pressures such as environmental degradation and reduced cultivated land, breeding innovation is urgent to boost yields. Genomic selection (GS) is a useful wheat breeding technology to make the breeding process more efficient, increasing the genetic gain per unit time and cost. Precise genomic estimated breeding value (GEBV) via genome-wide markers is usually hampered by high-dimensional genomic data. Methods: To address this, we propose GRE, a framework combining genome-wide association study (GWAS)’s biological significance and random forest (RF)’s prediction efficiency for an explainable machine learning GS model. First, GRE identifies significant SNPs affecting wheat yield traits by comparison of the constructed 24 SNP subsets (intersection/union) selected by leveraging GWAS and RF, to analyze the marker scale’s impact. Furthermore, GRE compares six GS algorithms (GBLUP and five machine learning models), evaluating performance via prediction accuracy (Pearson correlation coefficient, PCC) and error. Additionally, GRE leverages Shapley additive explanations (SHAP) explainable techniques to overcome traditional GS models’ “black box” limitation, enabling cross-scale quantitative analysis and revealing how significant SNPs affect yield traits. Results: Results show that XGBoost and ElasticNet perform best in the union (383 SNPs) of GWAS and RF’s TOP 200 SNPs, with high accuracy (PCC > 0.864) and stability (standard deviation, SD < 0.005), and the significant SNPs identified by XGBoost are precisely explained by their main and interaction effects on wheat yield by SHAP. Conclusions: This study provides tool support for intelligent breeding chip design, important trait gene mining, and GS technology field transformation, aiding global agricultural sustainable productivity. Full article

The continuous increase in urbanization and global population has led to the generation of a substantial amount of kitchen waste, posing severe environmental and disposal challenges. The utilization of kitchen waste as organic biomass for biochar production offers a promising, sustainable, and cost-effective solution. This review comprehensively analyzes the recent developments in the transformation of kitchen waste into biochar. Moreover, the current study involves various synthesis techniques, the physicochemical characteristics of biochar, and its applications in soil and water remediation. Afterwards, the experimental parameters and feedstock types are critically evaluated in terms of their key characteristics for biochar. Moreover, the current study highlights the effectiveness of kitchen waste-derived biochar (KWBC) in decomposing organic pollutants, heavy metals, and pharmaceutical pollutants from contaminated environments. Additionally, the mechanisms of adsorption, ion exchange, complexation, and redox interactions are thoroughly illustrated to evaluate the pollutant removal pathways. At the end of the study, experimental parameters such as pH, dosage, contact time, and initial pollutant concentration are discussed, which play the main role in enhancing the adsorption capacity of biochar. Finally, this review outlines current limitations and proposes future directions for optimizing biochar performance and promoting its large-scale application in sustainable environmental management. Full article

The evaluation and enhancement of image aesthetics play a pivotal role in the development of visual media, impacting fields including photography, design, and computer vision. Composition, a key factor shaping visual aesthetics, significantly influences an image’s vividness and expressiveness. However, existing image optimization methods face practical challenges: compression-induced distortion, imprecise object extraction, and cropping-caused unnatural proportions or content loss. To tackle these issues, this paper proposes an image aesthetic evaluation with composition and similarity (IACS) method that harmonizes composition aesthetics and image similarity through a unified function. When evaluating composition aesthetics, the method calculates the distance between the main semantic line (or salient object) and the nearest rule-of-thirds line or central line. For images featuring prominent semantic lines, a modified Hough transform is utilized to detect the main semantic line, while for images containing salient objects, a salient object detection method based on luminance channel salience features (LCSF) is applied to determine the salient object region. In evaluating similarity, edge similarity measured by the Canny operator is combined with the structural similarity index (SSIM). Furthermore, we introduce a Framework for Image Aesthetic Evaluation with Composition and Similarity-Based Optimization (FIACSO), which uses semantic segmentation and generative adversarial networks (GANs) to optimize composition while preserving the original content. Compared with prior approaches, the proposed method improves both the aesthetic appeal and fidelity of optimized images. Subjective evaluation involving 30 participants further confirms that FIACSO outperforms existing methods in overall aesthetics, compositional harmony, and content integrity. Beyond methodological contributions, this study also offers practical value: it supports photographers in refining image composition without losing context, assists designers in creating balanced layouts with minimal distortion, and provides computational tools to enhance the efficiency and quality of visual media production. Full article

This submission is focused on the implementation of a system that acquires data from various types of sensors and securely stores them after encryption on a chip with a reconfigurable architecture. The system has the unique capability of encrypting the input data with a single secret cryptographic key, which is stored only inside the hardware of the system itself, so the key remains unrecognizable upon completion of the system synthesis for any unauthorized user. Being stored as a part of the whole system architecture, the cryptographic key cannot be attained. It is not stored separately on the system RAM or any other supported memory, making the collected data fully protected. The reported work shows a data acquisition system which measures temperature with a high level of precision, transforms it to degrees Celsius, stores the collected data, and transfers them via serial interface when requested. Before storage, the data are encrypted with a 256-bit key, applying the AES algorithm. The data which are stored in the system memory and sent as UART packets towards the main computer do not include the cryptographic key in the data stream, so it is impossible for it to be retrieved from them. We show the flexibility of such kinds of data acquisition systems for sensing different types of signals, emphasizing secure storage and transferring, including data from meteorological sensors or highly confidential or biometrical data. Full article