Search Results (4,732)

Voltage source converters (VSCs), together with their inner current and outer power/voltage control loops, are fundamental building blocks in the modern, converter-dominated power systems, particularly within high-voltage DC (HVDC) frameworks. Selecting effective control methods for VSCs is essential to ensure the stability, power quality, and dynamic performance of HVDC grids. This paper seeks to advance the current body of research by delivering an in-depth, consistent, unified framework and systematic examination of VSC control architectures within HVDC networks. It thoroughly explores various control strategies for VSCs interfacing with HVDC grids, such as grid-following and grid-forming strategies, with particular emphasis on both stationary ($\alpha \beta$) and synchronous (dq) reference frames. Moreover, the paper provides a comprehensive analysis of the theoretical underpinnings and decoupled control strategies, like the feedforward decoupling of the d- and q-axis currents in the dq frame and the inherently decoupled structure of the αβ frame. Additionally, advanced filtering techniques, including Moving Average Filter (MAF), Cascaded Delayed Signal Cancellation (DSC), and LCL filters, are analyzed. In addition, harmonic mitigation strategies, like parallel/multiple resonant (PR) terms in the αβ frame and cascaded notch filters in the dq frame, are presented. Furthermore, precise power control approaches and synchronization methods are discussed in detail. Also, this paper presents a detailed comparison of the performance characteristics of phase-locked loop (PLL) and frequency-locked loop (FLL) in response to grid frequency variations. Moreover, this paper proposes circuit representations and VSC models in both synchronous and stationary reference frames. The simulation results corroborate the theoretical insights discussed in the paper under various operational conditions, including initial responses, grid disturbances, three-phase-to-ground temporary fault scenarios, harmonic distortions, and load imbalances, in terms of overshoot, settling time, active- and reactive-power fluctuation reduction, voltage unbalance factor, total harmonic distortion, and post-fault convergence time, all evaluated in accordance with the limits defined in EN-50160. This comprehensive comparison of the presented control strategies facilitates researchers in identifying the most appropriate controller depending on their specific application requirements. Full article

Prenatal alcohol exposure (PAE) is recognized as a major public health concern due to its profound and lasting effects on the central nervous system (CNS) and its ability to induce fetal alcohol spectrum disorders (FASD), which encompass a wide range of cognitive, behavioural, and neuropsychiatric disorders that persist throughout life. Experimental and clinical studies have identified several mechanisms underlying ethanol impairing brain development, including apoptosis, oxidative stress, disruption of morphogen and growth factor signalling pathways, impaired neuronal proliferation and migration, neurotransmitter systems’ dysfunction, glial cells damage associated with deficient myelination, vascular and blood–brain barrier (BBB) alterations, and lasting epigenetic reprogramming. However, to date no widely accepted integrative framework explaining how these impairments underline the heterogeneous phenotype observed in FASD is available. The present brings together developmental neurobiology and computational neuroscience to conceptualize PAE as a disorder of emerging neural and functional architecture. Here, we summarize the pharmacokinetics of ethanol in pregnancy, critical windows of vulnerability, and the classical pathways of alcohol teratogenesis affecting neuronal survival, migration, synaptogenesis, myelination, and gene regulation. We have also reviewed MRI, diffusion imaging, and EEG/MEG evidence showing altered brain volumes, white matter microstructure, functional connectivity, and network organization in individuals with PAE. Finally, we propose a systems-level model that conceptualizes PAE as a disorder of emerging neuro-computational architecture, in which ethanol-induced cellular and molecular perturbations collectively alter the building blocks and self-organization rules of brain network assembly. Full article

3D city models (3DCMs) are increasingly used in urban simulations, cadastral workflows, and digital building permit processes, and automated validation of these models has become a routine requirement. Existing validation services typically produce dense, frequently generated by SHACL engines, text-based reports that are difficult for users without a semantic-web background to interpret. This paper describes the CHEK Validation Results Viewer (CHEK VRV), a Flask-based web application that couples the OGC Data Completeness Validator with an interactive Three.js 3D viewer of the CityJSON input. SHACL violations and geometric invalidities are spatially explorable on a visual representation of the model, and the tool supports both predefined CHEK Building Block Profiles and user-uploaded custom profiles. We report a formative usability study with twelve domain experts (urban planners, data vendors, academics) and use it to identify the tool’s current strengths, its limitations, and a prioritized development roadmap. As reported by the participant experts, such a presentation is easier to interpret than the raw JSON-LD report. Full article

High-dynamic amusement ride conditions involving impacts, rapid rotations, and abrupt posture changes introduce severe motion artifacts that degrade vital sign quality and destabilize physiological state recognition. This study aims to develop an engineering-ready closed-loop framework for robust passenger monitoring and intelligent diagnosis. A multimodal sensing and modeling pipeline was designed to jointly leverage physiological signals such as heart rate and SpO₂ and kinematic measurements, including acceleration, angular rate, velocity, and attitude. Inertial and PPG signals were preprocessed into supervised samples through wavelet multiresolution denoising and coordinate frame unification, while a strapdown inertial navigation system was used to propagate a 12-channel physical quantity sequence. To ensure interpretability and standards compliance, constraints from GB 8408-2018 were translated into executable threshold rules, enabling standards-driven auto-labeling and rule-based early warning. Building on this foundation, three learning modules were developed: a fusion model for high-dynamic heart rate estimation, a CNN–LSTM dynamic-threshold-enhanced network TAPNet for rapid kinematic anomaly screening, and an attention-augmented hybrid model HS-BANet integrating one-dimensional residual blocks, bidirectional LSTM, and multi-head attention for fine-grained arrhythmia classification. Experimental results demonstrated accurate and consistent heart rate estimation with RMSE of 1.18 bpm on HSSH-I and 1.24 bpm on the independent HSSH-II set, strong agreement with training and testing correlations of 0.9928 and 0.9865, and near-zero bias in Bland–Altman analysis. TAPNet achieved 96.9% validation accuracy and 98.2% test accuracy for kinematic anomaly recognition, maintaining robust generalization under class imbalance. HS-BANet enabled multi-class identification of PVC, PAC, VT, SVT, and AF, achieving an accuracy of 92.37%, an F1-score of 86.87%, a precision of 88.45%, a sensitivity of 88.14%, and a specificity of 89.42%. Overall, the proposed two-stage multimodal closed-loop—fast, interpretable early warning based on physical quantity thresholds followed by fine-grained diagnosis from physiological signals—supports stable feature extraction and reliable decision-making under strong motion artifacts and non-stationary dynamics, balancing responsiveness and diagnostic credibility, while showing potential for practical safety early warning and future deployment-oriented operational support in amusement ride scenarios. Full article

Façades play a decisive role in shaping the visual and symbolic character of historic urban environments. Recent European funding schemes promoting energy-efficient retrofitting have accelerated interventions on building envelopes. Although aligned with decarbonization objectives, these processes are generating significant chromatic and material transformations that risk eroding the visual coherence and cultural sustainability of consolidated urban areas. In the historic Ensanches of San Sebastián, the replacement of traditional envelope systems with new cladding solutions is leading to the loss of the architectural style of some facades and altering their materials, textures, and colors. A progressive “contagion effect” has been identified, whereby dissonant chromatic schemes—often associated with the proliferation of so-called “zebra blocks”, residential buildings with façades clad in alternating black and white stripes that have proliferated in recent urban developments—are replicated across adjacent buildings, gradually weakening spatial continuity and the genius loci of the neighborhood. In response to this phenomenon, this research develops a systematic methodology to analyze, quantify, and anticipate chromatic transformation in consolidated urban fabrics. The study combines historical morphological analysis, classification of architectural periods, and chromatic mapping of recent façade interventions. Based on this framework, a CARI, Chromatic Alteration Risk Index is proposed to evaluate the potential impact of façade alterations on urban chromatic coherence. Drawing on an epidemiological framework, the methodology enables the identification of critical transformation clusters, the assessment of contagion dynamics, and the definition of regulatory thresholds for color and material interventions. By integrating perceptual criteria, urban morphology, and spatial distribution patterns, the study moves beyond descriptive diagnosis and offers a transferable tool for municipal planning. The proposed approach supports the proactive regulation of façade rehabilitation processes, balancing energy efficiency objectives with the preservation of collective memory, material identity, and urban sensory quality. This study proposes a quantitative model of “urban chromatic contagion” to assess how façade color interventions propagate within a neighborhood. We define the Chromatic Integration Percentage (CIP) and the Chromatic Alteration Risk Index (CARI) of the analyzed area. Results indicate that poorly regulated façades show higher chromatic dissonance (low CIP) and act as contagion hotspots, while a clear risk gradient emerges: highly protected buildings present lower risk, whereas mixed typologies and recent rehabilitations concentrate higher CARI values. The model supports preventive urban color management by identifying areas at risk before visible alteration. Full article

Vernacular housing in the Andean region embodies long-standing building knowledge, environmental adaptation, and forms of social organization rooted in rural life. Over recent decades, these dwellings have undergone visible transformations linked to migration, changing aspirations, and the growing presence of industrialized construction materials. Rather than disappearing, vernacular forms have increasingly merged with contemporary solutions, producing hybrid architectural landscapes whose local dynamics are still insufficiently documented. This study analyzes the material, typological, and functional transformation of rural housing in Las Lagunas and Quisquinchir, two Indigenous communities located in Saraguro, Loja, Ecuador. A total of 192 houses were recorded through field observation and a structured digital survey implemented with KoBoCollect. The information was processed in R using descriptive statistics, contingency tables, chi-square tests, Cramér’s V, and standardized residual analysis. The findings show that architectural change in both communities does not occur through a simple replacement of traditional housing by modern models. Instead, vernacular, hybrid, and modern/eclectic typologies coexist within the same rural setting, revealing uneven and locally specific processes of transformation. The clearest differences emerge in construction materiality. Las Lagunas preserves a stronger presence of traditional wall systems, especially adobe and bahareque, while Quisquinchir shows a broader incorporation of industrialized materials, particularly concrete block. Statistical analysis confirmed significant associations between community and wall material, as well as between typology and wall material, whereas the relationship between community and architectural typology was comparatively weaker. Functional changes were also identified through the reduction or reconfiguration of intermediate spaces such as portals, patios, and corridors, suggesting a gradual shift toward more enclosed and specialized domestic environments. These results contribute empirical evidence for understanding architectural hybridization in Indigenous rural territories and support conservation and planning approaches capable of recognizing continuity, adaptation, and change within evolving Andean built landscapes. Full article

Modern logistics and manufacturing environments simultaneously demand mobility platforms that are compact enough to navigate narrow aisles and powerful enough to transport oversized or heavy components. We previously developed a compact Steering–Drive–Suspension (SDS) module that integrates steering, in-wheel drive, and suspension within a single wheel envelope, achieving $\pm {90}^{\circ }$ wide-angle steering with a single actuator. The present paper extends that hardware-centric work by treating the two-wheel (2WD) configuration assembled from two SDS modules as the unit module of the platform, building a four-wheel (4WD) operation by coupling two such 2WD units, and developing a unified balance and impedance-based control scheme. We derive a cart–pole inverted-pendulum model for the 2WD configuration and a planar 2-DOF bicycle model for the coupled and cooperative configurations, with full controllability proof and quantitative LQR robustness margins. Three Python 3.12 based scenarios validate the framework: (i) a 2WD inverted-pendulum tracking task, (ii) a forward and lateral relocation maneuver compared across SDS Crab, Ackermann, and four-wheel-steering modes, and (iii) cooperative transport of a $100\mathrm{kg}$ steel plate by two impedance-coupled 2WD units. Across all scenarios the proposed controllers achieve sub-centimetre tracking gap, pitch deviation within $\pm 2^{\circ }$, and well-damped cooperative behavior without payload sloshing. The results substantiate the central design claim that the SDS module’s compactness enables a single hardware platform to act simultaneously as an autonomous small-payload mover, a building block of a 4WD platform, and a cooperative agent for oversized loads. Full article

Edge vision systems require convolutional neural networks (CNNs) that preserve recognition accuracy under strict storage, computation, and latency constraints. Although ResNet18 is a compact residual backbone, direct deployment on resource-constrained devices remains costly, whereas simple channel reduction weakens representation capacity. This study aims to build a deployable ResNet18-based classifier that reduces model complexity while recovering the accuracy lost during compression. We propose a lightweight framework that combines global channel scaling, a re-parameterized attention residual block, and teacher–student knowledge distillation. The proposed block uses multi-branch convolution and squeeze-and-excitation attention during training, then folds the linear branches into a single 3-by-3 convolution for inference. Experiments on CIFAR-100 show that the final model reduces parameters from 11.220 M to 2.841 M, retains comparable Top-1 accuracy (0.7579 vs. 0.7606), improves Top-5 accuracy (0.9340 vs. 0.9253), and reduces graphics processing unit (GPU) batch inference latency from 3.279 ms to 2.161 ms. Deployment on PYNQ-Z2 verifies the complete camera-based CPU-side inference workflow, with an average end-to-end latency of 421.467 ms/frame. The results indicate that residual topology preservation, re-parameterized feature enhancement, and distillation form a practical route for edge-oriented lightweight CNN deployment. Full article

The transition toward a circular economy is accelerating the development of high-performance, sustainable polymeric materials derived from renewable resources. Medium-chain-length polyhydroxyalkanoates (mcl-PHAs) represent a versatile class of biodegradable polyesters with inherent flexibility and tunable side-chain chemistry, making them attractive candidates for advanced polymer applications. Here, we report a novel class of bio-based polyurethanes (PUs) incorporating mcl-PHAs as soft segments, marking their first application in polyurethane synthesis and shifting towards greener PU synthesis. Polyurethane networks were prepared using castor oil (CO) and mcl-PHAs as polyols, with hexamethylene diisocyanate (HMDI) as a hard segment. Material properties were systematically tuned by varying the mcl-PHA/CO ratio (100/0 to 0/100), enabling precise control over structure–property relationships. Comprehensive characterization confirmed urethane bond formation and revealed predominantly amorphous materials with tunable thermal and mechanical behavior. Increasing mcl-PHA content enhanced elasticity and influenced phase organization, underscoring its role as a flexible, bio-derived soft segment. The resulting materials exhibited competitive mechanical performance alongside adjustable swelling behavior and morphology. Importantly, in vitro biocompatibility (MRC-5 fibroblasts) and eco-toxicological evaluation (Caenorhabditis elegans) confirmed the absence of toxicity. These findings highlight the potential of mcl-PHAs as sustainable building blocks for advanced polyurethane systems. Full article

Deep excavation groups in soft soil can endanger adjacent historic buildings. This paper presents a 3D finite element analysis of a project in Ningbo, employing the HSS constitutive model. Three excavation schemes were compared. The small-zone staged excavation from near to far proved optimal: relative to the conventional large-block scheme, it reduced maximum wall displacement on the heritage-building side by 37.0% and building tilt by 54.0%; servo struts were then introduced in the critical sub-excavation and optimized via response surface methodology. A layered control hierarchy was revealed—wall bulging is governed by the third and fourth struts (F₃ ≈ F₄ > F₂), and mean settlement by the third strut (F₃ > F₂ ≈ F₄). Building tilt control relies on synergistic action of all three struts (F₃ > F₂ > F₄), with significant antagonistic interactions among struts at high force levels. The optimal combination (F₂ = 1200 kN, F₃ = 1800 kN, F₄ = 1550 kN) limits maximum tilt to 0.380‰, well below the 1.0‰ code limit, and remains robust under various weighting scenarios. Full article

In the context of global climate change and rapid urbanization, urban outdoor thermal environment issues in summer have become increasingly severe. Shading has been widely recognized as an effective strategy for improving outdoor thermal comfort, yet existing evaluation methods still suffer from limitations in adaptability and accuracy. Taking Chongqing, a typical hot-humid city in China, as a case study, this paper proposes an evaluation method that accounts for human thermal adaptation, introducing three complementary indicators, namely Universal Thermal Climate Index Load (UTCIL), cumulative UTCIL (cUTCIL), and Heat Stress Duration (HSD). Focusing on four shading-related urban canyon morphological factors—orientation, aspect ratio (H/W), building asymmetry, and leaf area index (LAI) of street trees—a series of simulation scenarios was designed to quantitatively explore their impacts on summer outdoor thermal comfort. The applicability and reliability of the ENVI-met model for block-scale outdoor thermal environment simulation were validated by comparing field-measured microclimate data with simulation results. The findings demonstrate that all four morphological factors substantially influence the outdoor thermal environment. Canyon orientation considerably affects thermal comfort, with a 30° clockwise deviation from the north–south yielding optimal conditions, whereas the east–west (90°) orientation produces the poorest thermal environment, with a maximum UTCI of approximately 48.9 °C. For aspect ratio, thermal comfort improves continuously as H/W increases, with the benefit stabilizing beyond H/W = 3.5. Building asymmetry also plays a notable role: raising building height on one side can effectively reduce outdoor thermal stress, and canyons with taller west-side buildings show better thermal performance under the same asymmetry ratio. Furthermore, street tree shading and aspect ratio exhibit a synergistic cooling effect, where high LAI (e.g., 4.77) reduces UTCI_max by approximately 1.8 °C at H/W = 1, but this benefit diminishes as H/W increases. The optimal outdoor thermal environment is achieved through the combination of a high aspect ratio and high LAI. These findings provide a quantitative basis and design references for optimizing outdoor thermal comfort in Chongqing. In addition, the quantitative evaluation proposed method can offer a methodological reference for other hot-humid regions. Full article

Urban flooding poses escalating threats to high-density cities, yet the nonlinear mechanisms linking rainfall characteristics and urban morphology to waterlogging severity remain poorly understood. This study proposes a rainfall-stratified explainable machine learning framework to distinguish deep from shallow inundation at the block scale, taking Shanghai as a case study. Four models (XGBoost, random forest, SVM, and logistic regression) were compared via nested cross-validation and Bayesian optimization, with XGBoost identified as the optimal model. Three physically distinct rainfall dimensions and multi-dimensional urban morphological indicators were incorporated as predictive features. SHAP-based attribution and PDP were employed to unveil the driving mechanisms behind inundation severity, characterizing scenario-dependent shifts in driver dominance and nonlinear threshold effects. Urban morphology primarily governs spatial risk under non-extreme rainfall, with building shape coefficient (BSC) remaining the primary driver overall. Meteorologically, waterlogging severity surges beyond critical thresholds for maximum hourly rainfall (>18.40 mm/h) and total volume (>139 mm), while duration exhibits an inverted U-shaped response. Morphologically, a high BSC (>0.39 m⁻¹) is consistently associated with elevated deep inundation probability, whereas higher SDBV (>54,155 m³) and greater DR (>582 m) are associated with a severity-attenuating effect. These findings provide threshold-driven insights for integrating morphological resilience into urban renewal and sustainable flood adaptation strategies in high-density metropolises. Full article

The synthetic strategy relies on the highly diastereoselective alkylation at the C4 position of L-pyroglutamic acid derivatives, followed by a decarboxylation-allylation process that enables the incorporation of diverse substituents, including aromatic substituents, affording trans-3,5-disubstituted γ-lactams with excellent diastereiosmeric ratio (dr > 98:2). The resulting γ-lactams were efficiently transformed into a series of α,γ-disubstituted γ-amino acids through hydrogenation and acidic hydrolysis. Furthermore, cross-metathesis reactions with styrene and 1-decene enabled the introduction of structurally diverse lipophilic side chains, furnishing the corresponding γ-amino acids in good overall yields (71–77%) and high diastereoisomeric ratio from >98:2 to 92:8. In addition, N-allylation followed by ring-closing metathesis and hydrogenation provided access to a previously unexplored conformationally constrained γ-amino acid. Overall, seven α,γ-disubstituted γ-amino acids, including fluorinated and conformationally restricted derivatives, were synthesized from common intermediates with high stereocontrol. The developed methodology offers a versatile platform for the preparation of structurally diverse and underexplored γ-amino acid building blocks of potential interest in peptide synthesis, medicinal chemistry, and antimicrobial agent development. Full article

Urban vitality research treats food-and-beverage venues as aggregate point-of-interest counts and existing morphometric classification frameworks operate at the building, block or neighbourhood scale, leaving the commercial ground-floor interface without a programme-specific typology. This study develops GATE (Ground-floor Architectural Typology at the street Edge), a 22-variable morphological framework operating at the venue–street–interface scale, and applies it to 85 interfaces across eleven commercial arteries in the core of a mid-sized Turkish city. Ward hierarchical clustering yields a single dendrogram read at macro (k = 3) and micro (k = 7) resolutions, validated through Kruskal–Wallis tests that separate 17 and 19 of the 22 variables, respectively. Three macro types emerge: narrow-fronted apartment-ground-floor venues, detached garden-plot pavilion venues and vertically organised transparent-fronted venues. Space Syntax Integration, Choice and Shannon diversity produce no significant relationship with pedestrian density in the aggregate. Type stratification points to a resolution-dependent moderator effect: the apartment-ground-floor type shows negative Integration and positive Choice coupling, while the transparent vertical type shows positive Integration coupling, producing a directional pattern consistent with Simpson’s paradox. GATE provides one of the first programme-specific venue-level morphological frameworks and establishes an explicit quantitative mapping of the Panerai–Castex analytical typology with future multi-city applications to test its generalisability. Full article

Industry 4.0 is speeding up the move to connected, data-driven, and automated production, where the Internet of Things (IoT) enables sensing, communication, and real-time support for decisions. At the same time, rapid growth in industrial IoT studies has led to scattered technologies, architectures, and results. This paper fills this gap through a systematic literature review on IoT for Industry 4.0. It also helps readers compare methods and choose suitable building blocks for real deployments today. We focus on key technologies, integration architectures, application areas, challenges, trends, and reported benefits. Using PRISMA 2020, we searched five major databases (Scopus, MDPI, IEEE Xplore, ScienceDirect, and Web of Science) for 2020–2025 and found 584 records. After removing duplicates and screening, we kept 96 peer-reviewed studies for detailed analysis. Results show that most studies use a layered stack that combines sensing/actuation, industrial networking, data collection pipelines, and analytics across edge, fog, and cloud resources. MQTT, OPC UA, CoAP, LPWAN, and 5G connectivity are often used for communication, while RAMI 4.0, IIRA, and similar layered models guide system design. Many architectures follow an edge–cloud pattern, with growing focus on digital twin/CPS links and security-by-design. Applications are mainly smart manufacturing, predictive maintenance, and logistics, with added work in energy management, Construction 4.0, and agri-food monitoring. The key barriers remain interoperability, data quality and evaluation gaps, cybersecurity risks, legacy integration, and deployment limits. The review points to future work on edge AI/TinyML, deterministic connectivity, scalable digital twins, trusted data sharing, and sustainable industrial IoT. Full article