Search Results (5,626)

This paper proposes a Gudermannian function-based proportional–integral–derivative (G-PID) controller to enhance the transient performance of automatic voltage regulator (AVR) systems operating under highly dynamic conditions. By embedding the smooth and bounded nonlinear mapping of the Gudermannian function into the classical PID structure, the proposed controller improves adaptability to large signal variations while effectively suppressing overshoot. The controller parameters are optimally tuned using the starfish optimization algorithm (SFOA), which provides a robust balance between exploration and exploitation in nonlinear search spaces. Simulation results demonstrate that the SFOA-optimized G-PID controller achieves superior transient performance, with a rise time of 0.0551 s, zero overshoot, and a settling time of 0.0830 s. Comparative evaluations confirm that the proposed approach outperforms widely used optimization algorithms (particle swarm optimization, grey wolf optimizer, success history-based adaptive differential evolution with linear population size, and Kirchhoff’s law algorithm) and advanced AVR control schemes, including fractional-order and higher-order PID-based designs. These results indicate that the proposed SFOA optimized G-PID controller offers a computationally efficient and structurally simple solution for high-performance voltage regulation in modern power systems. Full article

In recent decades, forest fires have become one of the most disruptive and complex natural hazards from both environmental and territorial perspectives. The Canary Islands represent a particularly suitable setting for analysing wildfire risk. This study aims to characterise the Large Forest Fires (LFFs) that occurred across the archipelago between 2012 and 2024 through an integrative approach combining geospatial, meteorological, and socio-environmental information. A total of 13 LFFs were identified in Tenerife, Gran Canaria, La Palma, and La Gomera, affecting 55,167 hectares—equivalent to 7.4% of the islands’ total land area. The results indicate a temporal concentration during the summer months and an altitudinal range between 750 and 1500 m, corresponding to transitional zones between laurel forest and Canary pine woodland. Meteorological conditions showed average temperatures of 24.3 °C, minimum relative humidity of 23.7%, and thermal inversion layers at around 270 m a.s.l., creating an environment conducive to fire spread. Approximately 81% of the affected area lies within protected natural spaces, highlighting a high level of ecological vulnerability. Analysis of the Normalized Burn Ratio (NBR) index reveals a growing trend in fire severity, while social impacts include the evacuation of more than 43,000 people. These findings underscore the urgency of moving towards proactive territorial management that integrates prevention, ecological restoration, and climate change adaptation as fundamental pillars of any disaster risk reduction strategy. Full article

The rapid urban expansion in the past few decades has resulted in a deficit of urban green space, and green roofs have become an effective way to expand urban green spaces. High nitrogen (N) deposition induced by urban development has threatened the health and sustainability of plants. The aim of this study was to evaluate the responses of plant growth performance and aesthetic value to N deposition in green roofs. Eleven species from four plant functional groups were grown under control, low N addition, and high N addition conditions to assess the effects of N addition on their growth performance, aesthetic value, soil properties, and plant functional traits. Different plant functional groups exhibited distinct traits, and their response to N addition was different. Under high N addition, the growth performance of sod-forming graminoids and tall forbs decreased by 47.0% and 23.7%, and their aesthetic value decreased by 24.4% and 16.2%, respectively. Growth performance of plant functional groups was mainly determined by plant functional traits rather than soil properties. The poor growth performance and aesthetic value of sod-forming graminoids and tall forbs challenged their widespread use under high N addition. This study highlighted the importance of selecting environmentally adaptive species from the perspective of plant functional groups, especially in the context of future high N deposition. Full article

The objective of the article is the assessment of the sensitivity of the equilibrium path of structures susceptible to loss of stability due to node snap-through. Increasingly, architectural designs feature organic forms and structures with complex geometry, which makes it possible to create very large, column-free spaces. These developments lead to the design of structures with ever smaller rise while simultaneously increasing their span. Due to the parameters of structures of this type, it is justified to analyze such systems with consideration of nonlinear effects. The Newton–Raphson algorithm was used to determine the limit points on the equilibrium path, employing both load control and displacement control. To accurately determine the position of the limit point on the equilibrium path, the step length was defined adaptively. Four dome space trusses were analyzed. Individual load sets were differentiated in terms of load location. The developed algorithm was implemented in a proprietary finite element method program created in the Matlab R2025b software. The analysis showed that, despite significant differences in the critical force (P_ult), the global response of the structure at the moment of snap-through remains similar. The displacement of the apex node at the moment of snap-through remains similar across most of the proposed load sets. In the case of low-rise structures, a significant increase in the sensitivity of the load location to the critical load value and in the displacement of the apex node at the moment of snap-through was observed. Full article

Indoor Air Quality (IAQ) is a major public health concern, as prolonged exposure to indoor environments can significantly affect users’ well-being. In this context, the research proposes a sampling protocol, developed in compliance with ISO 16000 principles, for the assessment of key chemical and physical parameters influencing air quality in inpatient rooms. These spaces host fragile users, while also requiring adequate protection for healthcare staff. Referring to the scope of the paper, the study outlines a comprehensive methodology for monitoring selected volatile organic compounds (VOCs) and microclimatic factors—temperature and relative humidity—using passive samplers and/or active sensors. The protocol also integrates outdoor measurements to better understand the contribution of internal emission sources. Monitoring activities are scheduled over one year, with regular sampling campaigns (at least one week per month) to analyze seasonal variations and long-term trends. The flexible structure of the protocol allows it to be adapted to different research objectives and types of healthcare facilities. Overall, the proposed approach provides a replicable framework for assessing IAQ in healthcare settings and identifying the main factors affecting indoor environmental performance. This supports improvements in both environmental quality and health protection within healing spaces. Full article

This article outlines the development of an inter-scale analytical tool designed to evaluate urban, intermediate, and domestic spaces from a gender perspective. Framed within feminist urbanism and ecofeminist theory, the study addresses the need to foster inclusive and equitable environments by incorporating gender-sensitive criteria into spatial planning processes. The methodology employed consists of a six-stage process: (1) a review of the existing literature; (2) the definition of scales of approach; (3) the formulation of indicators; (4) the establishment of evaluation criteria; (5) the design of data collection instruments; and (6) the refinement of the tool through field testing. The tool uses both qualitative and quantitative indicators across three spatial scales—neighbourhood, inter-block, and housing—organised into dimensions such as safety, accessibility, diversity, vitality, and representativeness. The evaluation process employs direct observation, graphic analysis, interviews, and participatory focus groups to provide a nuanced and multidimensional understanding of the built environment. The results confirm that both urban and domestic spaces have historically been designed from an androcentric perspective. They also highlight the potential of using gender-based evaluations to identify spatial inequalities and guide transformative interventions. The tool is replicable, adaptable, and scalable, and can therefore offer a robust framework for future research and public policy-making aimed at fostering gender equity in urban contexts. Full article

Customizing diffusion models via Low-Rank Adaptation (LoRA) has become a standard approach for customized concept injection. However, synthesizing multiple customized concepts within a single image remains challenging due to the parameter pollution problem, where naive fusion leads to gradient conflicts and severe quality degradation. In this paper, we introduce ConWave-LoRA, a novel framework designed to achieve hierarchical disentanglement of object and style concepts in LoRAs. Supported by our empirical validation regarding frequency distribution in the latent space, we identify that object identities are predominantly encoded in high-frequency structural perturbations, while artistic styles manifest through low-frequency global layouts. Leveraging this insight, we propose a Discrete Wavelet Transform (DWT) based filtering strategy that projects these concepts into orthogonal optimization subspaces during contrastive learning, thereby isolating structural details from stylistic attributes. Extensive experiments, including expanded ablation studies on LoRA rank sensitivity and style consistency, demonstrate that ConWave-LoRA consistently outperforms strong baselines, producing high-fidelity images that successfully integrate multiple distinct concepts without interference. Full article

Against the dual backdrop of rapid population aging and legacy neighborhood renewal, morphologically planning-locked legacy neighborhoods in high-density cities face persistent imbalances in outdoor activity spaces that undermine aging-in-place participation and health equity. This study advances a Spatial Pathology framework. Using nine representative communities in Longtan Subdistrict, Dongcheng District, Beijing, we develop a GIS-assisted spatial audit, a systematic behavioral observation protocol with temporal-intensity metrics, and a validated perception instrument. These tools form a closed evidentiary loop with explicit indicator definitions, formulas, and decision thresholds, alongside a reproducible analytic and visualization pipeline. Tri-dimensional baselines revealed substantial inter-community disparities: Spatial Quality Index (SQI) ranged from 43.3 to 77.0; activity intensity varied from 1.5 to 15.7 persons/100 m²·hour; and overall satisfaction scores spanned 3.88–4.49. It quantifies and identifies three core paradoxes in outdoor activity spaces within this context: (1) the Functional Failure Paradox with FFI exceeding +0.5 and ELR surpassing 60% in dormant communities; (2) the Value Misalignment Paradox where Facilities & Equipment showed the strongest satisfaction impact (β = 0.344) yet the largest unmet-need gap (VQGI > +8); (3) the Practice–Perception Decoupling Paradox evidenced by a negative correlation (r = −0.38) between usage intensity and satisfaction. These paradoxes reveal the spatial roots of planning-locked legacy neighborhoods—compound mechanisms of planning inertia, decision–demand information gaps, and elderly adaptability masking environmental deficits. We translate the diagnosis into typology-specific prescriptions—reactivating dormant spaces via “route–node–plane” continuity and proximal micro-spaces; decongesting peak periods through elastic zoning and equipment redistribution; and precision calibration of facilities and walking loops—implemented through co-creation and light-touch stewardship. This provides evidence-based, precision-targeted intervention pathways for micro-renewal of aging neighborhoods, supporting localized implementation of UN Sustainable Development Goals (SDG 11 Sustainable Cities; SDG 10 Reduced Inequalities). This methodological framework is transferable to other high-density aging cities, offering theoretical scaffolding and empirical reference for multi-source geographic data-driven urban spatial analysis and equity-oriented age-friendly retrofitting. Full article

This study aims to establish a method-integrative framework for emotion-oriented architectural image generation. The framework combines Stable Diffusion with targeted LoRA (Low-Rank Adaptation), a lightweight and parameter-efficient fine-tuning approach, together with ControlNet-based structural constraints, to examine how controllable design-element manipulations influence emotional responses. The methodology follows a closed-loop “generation–evaluation” workflow, with each LoRA module independently targeting a single design element. Guided by the relaxation–arousal emotional dimension, the framework is evaluated using subjective ratings and electroencephalogram (EEG) measures. Twenty-seven participants viewed six architectural space categories, each comprising four conditions (baseline, color, material, and form modification). EEG α/β power ratio (RAB) served as the primary neurophysiological marker of arousal. Statistical analysis indicated that LoRA-based modifications of design elements produced distinct emotional responses: color and material changes induced lower arousal, whereas changes in form elicited a bidirectional pattern involving relaxation and arousal. The right parietal P4 electrode site showed the most sensitive emotional response to design element changes, with consistent statistical significance. P4 is a human scalp EEG location associated with cortical activity related to visuospatial processing. Descriptive results suggested opposite directional effects with similar intensity trends; however, linear mixed-effects model (LMM) inference did not support significant group-level linear coupling, indicating individual variation. This study demonstrates the feasibility of emotion-guided architectural image generation, showing that controlled manipulation of color, material, and form can elicit measurable emotional responses in human brain activity. The findings provide a methodological basis for future multimodal, adaptive generative systems and offer a quantitative pathway for investigating the relationship between emotional states and architectural design elements. Full article

Thought processes in the brain occur as it continually modifies its use of energy. This review integrates research findings from molecular neurology, vascular physiology and non-equilibrium thermodynamics to create a comprehensive perspective on thinking as a coordinated energy process. Data shows that there is a relationship between the processing of information and metabolism throughout all scales, from the mitochondria’s electron transport chain to the rhythmic changes in the microvasculature. Through the cellular level of organization, mitochondrial networks, calcium (Ca²⁺) signals from astrocytes and the adaptive control of capillaries work together to maintain a state of balance between order and dissipation that maintains function while also maintaining the ability to be flexible. The longer-term regulatory mechanisms including redox plasticity, epigenetic programs and organelle remodeling may convert short-lived states of metabolism into long-lasting physiological “memory”. As well, data indicates that the cortical networks of the brain appear to be operating close to their critical regimes, which will allow them to respond to stimuli but prevent the brain from reaching an unstable energetic state. It is suggested that cognition occurs as the result of the brain’s ability to coordinate energy supply with neural activity over both time and space. Providing a perspective of the functional aspects of neurons as a continuous thermodynamic process creates a framework for making predictive statements that will guide future studies to measure coherence as a key link between energy flow, perception, memory and cognition. Full article

Adaptive reuse of heritage buildings is a vital strategy for balancing cultural preservation with modern functionality needs. This study provides a post-adaptive reuse evaluation of Dar Al Saraya in Madaba, Jordan, a significant Ottoman-era landmark, to examine how adaptive reuse strategies influence interior environments and heritage value. The analysis employs Zhang and Zhang’s evaluation framework focusing on existing fabric, special character, and policy and value, operationalized through 15 factors. A qualitative methodology was adopted, integrating site observations, photographic documentation, and semi-structured interviews with heritage experts, municipal representatives, residents, visitors, and site staff. Fieldwork was conducted in two phases (November 2024 and October 2025) to capture evolving conditions and perceptions. Findings indicate that challenges in spatial reconstruction were few and well addressed, but gaps in adaptation and reuse function strategies created significant issues. These included a lack of coordinated policies and the failure of municipal authorities and property owners to sustain the building’s reuse and involve the local community in reuse decisions. Despite various initiatives, from a museum, hotel, cultural center and gallery to its recent adaptation into a café, these efforts lacked sustainability and inclusive strategic planning. Consequently, the café has faced difficulties since opening, leaving its future uncertain. These findings highlight the importance of post-adaptive reuse evaluation and of integrating policy, planning, and community participation into adaptive reuse strategies to promote sustainable, community-centred conservation. Full article

Accurate group target association is essential for multi-sensor multi-target tracking, particularly in heterogeneous radar systems where systematic biases, asynchronous observations, and dense formations frequently cause ambiguous or incorrect associations. Existing approaches often rely on strict spatial assumptions or pre-trained models, limiting their robustness when measurement distortions and sensor-specific deviations are present. To address these challenges, this work proposes a robust association framework that integrates deep feature embedding, density-adaptive clustering, and global graph-theoretic matching. The method first applies an autoencoder–HDBSCAN clustering scheme to extract stable latent representations and obtain adaptive group structures under nonlinear distortions and non-uniform target densities. A weighted bipartite graph is then constructed, and a global optimal matching strategy is employed to compensate for heterogeneous systematic errors while preserving inter-group structural consistency. A mutual-support verification mechanism further enhances robustness against random disturbances. Monte Carlo experiments show that the proposed method maintains over 90% association accuracy even in dense scenarios with a target spacing of 1.4 km. Under various systematic bias conditions, it outperforms representative baselines such as Deep Association and JPDA by more than 20%. These results demonstrate the method’s robustness, adaptability, and suitability for practical multi-radar applications. The framework is training-free and easily deployable, offering a reliable solution for group target association in real-world multi-sensor fusion systems. Full article

In mobile robotics, path planning enables autonomous navigation to specified destinations. However, complex terrain can lead to excessive tilting or even overturning, compromising stability and safety. Traditional path-planning algorithms often fail to fully account for dynamic terrain variations and robot motion constraints. To address these limitations, this paper proposes the novel dual-layer Hybrid-A* algorithm, enhanced with dynamic phase windows. This approach represents a significant innovation by integrating real-time feedback mechanisms and adaptive adjustments to phase windows, enabling continuous path refinement in response to both environmental changes and robot motion limitations. The guidance layer introduces a bicubic interpolation-based super-resolution technique to refine elevation maps, offering more accurate posture estimation. In the planning layer, we propose the dynamic use of multiple cost functions, an adaptive expansion radius, pruning strategies, and a phase-window activation mechanism, effectively addressing the computational challenges posed by large search spaces. The integration of these strategies allows the algorithm to outperform traditional methods, particularly in unstructured environments with complex terrain. Experimental results demonstrate the effectiveness of the proposed method in generating optimized paths that satisfy robot motion constraints, ensuring both efficiency and safety in real-world applications. Full article

Microgravity during space travel induces significant regulatory changes in the body, posing health risks for astronauts, including alterations in cell morphology and cytoskeletal integrity. The Small Ubiquitin-like Modifier (SUMO) is crucial for cellular adaptation, regulating DNA repair, cytoskeletal dynamics, cell division, and protein turnover—all processes affected by microgravity. To determine the extent to which SUMO mediates the cellular response to microgravity stress, Saccharomyces cerevisiae cells were cultured under normal gravity and simulated microgravity (SMG) in rotating wall vessels. After 12 h of culture, we investigated changes in SUMO modified proteins and protein expression. We identified 347 SUMOylated proteins, 18 of which demonstrated a 50% change in abundance under SMG. Of 3773 proteins identified, protein expression for 34 proteins decreased and 8 increased by over 50% in SMG (p < 0.05). Differentially expressed proteins represented changes in cellular processes for DNA repair, cell division, histone modification, and cytoskeleton regulation. These findings underscore the pivotal role of SUMOylation in orchestrating cellular adaptation to the unique stress of microgravity, revealing potential targets for mitigating spaceflight-induced health risks. Full article

Accurate characterization of rail corrugation is essential for the operation and maintenance of urban rail transit. To enhance the representation capability for rail corrugation, this study proposes a sound–vibration feature fusion method based on Laplacian manifold learning. The method constructs a multidimensional feature space using real-world acoustic and vibration signals measured from metro vehicles, introduces a Laplacian manifold structure to capture local geometric relationships among samples, and incorporates inter-class separability into traditional intra-class compactness metrics. Based on this, a comprehensive feature evaluation index L_r is developed to achieve adaptive feature ranking. The final fusion indicator, LWVAF, is generated through weighted feature integration and used for rail corrugation characterization. Validation on in-service metro line data demonstrates that, after rail grinding, LWVAF exhibits a more pronounced reduction and higher sensitivity to changes compared with individual acoustic or vibration features, reliably reflecting improvements in rail corrugation. The results confirm that the proposed method maintains strong robustness and physical interpretability even under small-sample and weak-label conditions, offering a new approach for sound–vibration fusion analysis and corrugation evolution studies. Full article