Search Results (171)

Water is the source of life and also the lifeline of cities. The reconstruction of secondary water supply systems is a key component of urban renewal reforms, and the collaborative governance of such projects has become a focal topic through academic research. In this article, we try to discover the path to successful “bottom-up” collaborative water governance with Collins’s theory of interaction ritual chains (IRC) through a case study of a secondary water supply reconstruction program in J Estate, Jinshan District, Shanghai. The case study involved a total of 104 households, and we employed convenience sampling for all households through door-to-door inquiries, which included semi-structured interviews and non-participant observations. A total of 15 households participated in our interview. This study demonstrates that repeated social interactive rituals, such as bodily co-presence, rhythmic synchronization, and shared signs, can stimulate the accumulation of residents’ emotional energy, which becomes the initial power to promote community water governance and, in return, becomes the driving force for sustained collective action and mutual trust. Drawing on Collins’s theory of IRC, this article fills a gap by explaining the symbolic mechanism driven by emotions and personal relationships that macro-level governance ignores. We also demonstrate the spillover effects of such social rituals and propose policy recommendations that governments should apply, using these rituals to mobilize and consolidate residents’ emotions to create a virtuous circle of collaborative governance. Full article

The intensification of global climate change has led to an increased frequency of extreme rainfall and temperature events, posing severe threats to China’s ecosystems and socio-economic systems. This study, based on multi-year daily precipitation, monthly surface air temperature, and daily near-surface temperature datasets, employs multi-year averaging, EOF mode analysis, Mann–Kendall testing, and R/S analysis. By selecting heavy-rain days, rainfall amount, rainfall intensity, and drought indices, it explores the spatiotemporal evolution and driving mechanisms of extreme rainfall, drought, and compound events across China. The analysis of extreme rainfall reveals that precipitation in China shows a “more in the southeast, less in the northwest; abundant in the southeast, sparse in the northwest” pattern. EOF analysis identifies two spatial modes for rainfall parameters, the “Eastern Coordination Mode” and the “North–South Antiphase Mode,” corresponding to heavy rainfall days, rainfall amount, and rainfall intensity. The Mann–Kendall test shows that some regions in the eastern monsoon zone have experienced a significant increase in heavy rainfall parameters, while certain areas in the northeast, southern China, and northwest have also undergone significant changes. By contrast, parts of the southwest have seen a decrease. R/S analysis reveals that the Hurst index is high in the eastern monsoon region, indicating a strong likelihood of continued upward trends in the future, while regions in the western arid and semi-arid zones and parts of the Tibetan Plateau exhibit stronger randomness in trends, leading to more alternating drought and flood events. The analysis of the drought index (SPI-3) reveals synchronized drought patterns in the central-eastern and northern regions, with “synergistic consistency,” “Northwest–Northeast Antiphase,” and “Northern–Central-South Antiphase” characteristics. The Mann–Kendall test indicates a “north-wet, south-dry” differentiation, with significant wetting in the northern regions and parts of the Tibetan Plateau, and significant drying in the central-eastern and southwestern regions. R/S analysis shows high Hurst indices across most of the northwest and northern regions, indicating stronger drought persistence, while coastal areas in the east are more prone to dry–wet transitions. In terms of compound events, high-temperature and heavy rainfall events have increased from northwest to southeast over the past 40 years, with southern China experiencing more than 200 days of such events. Significant changes have been observed in the eastern and southern coastal regions, with high Hurst indices and strong persistence in the eastern coastal areas. Low-temperature and heavy rainfall events are more frequent in the eastern coast and southwestern regions, with higher Hurst indices in the eastern and central regions, indicating strong persistence. Full article

The performance of estrus synchronization protocols may be influenced by stressful environmental conditions, even in tropically adapted cattle. This study evaluated the efficacy of two synchronization protocols for fixed-time artificial insemination (FTAI) in crossbred Gyr dairy cows and their relationship with heat stress under Peruvian tropical conditions. Multiparous lactating cows under semi-intensive systems were synchronized and divided into two groups: the conventional protocol (PC9) and the prolonged proestrus protocol (J-Synch6). Estrus manifestation, pregnancy rate, and their association with the temperature–humidity index (THI) were analyzed across seven phases of the FTAI program (73 days). In PC9 cows, no significant effect of the number of hours in each heat stress category according to THI was found. Conversely, in J-Synch6 cows, more hours in Category 0 (THI < 72) during Phases 1 to 4 (follicular emergence to preovulatory follicle) had a positive effect on the estrus manifestation, whereas in Phase 3 (follicular growth), higher exposure to Category 3 (THI ≥ 83) had a negative effect on estrus manifestation. Both protocols demonstrated similar estrus and pregnancy rates, although heat stress affected estrus rates in J-Synch6, but not pregnancy. The choice of protocol should account for heat stress risks during specific periods of the year to maximize success. Full article

This paper presents the design, development, and experimental validation of a low-cost, modular, and scalable Advanced Driver Assistance System (ADAS) platform intended for research and educational purposes. The system integrates embedded computer vision and electronic control using an FPGA for accelerated real-time image processing and an STM32 microcontroller for sensor data acquisition and actuator management. The YOLOv3-Tiny model is implemented to enable efficient pedestrian and vehicle detection under hardware constraints, while additional vision algorithms are used for lane line detection, ensuring a favorable trade-off between accuracy and processing speed. The platform is deployed on a 1:5 scale gasoline-powered vehicle, offering a safe and cost-effective testbed for validating ADAS functionalities, such as lane tracking, pedestrian and vehicle identification, and semi-autonomous navigation. The methodology includes the integration of a CMOS camera, an FPGA development board, and various sensors (LiDAR, ultrasonic, and Hall-effect), along with synchronized communication protocols to ensure real-time data exchange between vision and control modules. A wireless graphical user interface (GUI) enables remote monitoring and teleoperation. Experimental results show competitive detection accuracy—exceeding 94% in structured environments—and processing latencies below 70 ms per frame, demonstrating the platform’s effectiveness for rapid prototyping and applied training. Its modularity and affordability position it as a powerful tool for advancing ADAS research and education, with high potential for future expansion to full-scale autonomous vehicle applications. Full article

The Shimizu–Morioka dynamical system is analytically investigated in this paper by means of the Optimal Auxiliary Functions Method (OAFM). This system has a chaotic dynamical behavior, specified for more physical applications as chaos synchronization, an attractive phenomenon involving various real-life processes. Semi-analytical solutions for the Shimizu–Morioka system are provided. A comparative analysis between the obtained results via the OAFM method and the corresponding numerical solution highlights the accuracy and efficiency of the involved method. The choice of the OAFM method is justified by the performance in comparison with the iterative method with 7–10 iterations. The physical parameters’ influence is investigated on damped oscillations and periodical behaviors of the obtained solutions. Full article

Grid-forming (GFM) energy storage can be utilized as a backup power source for the power grid to ensure the security of the power grid. GFM energy storage can also enhance the strength of the power grid and improve its stability. However, the GFM energy storage inherits the characteristics of the synchronous generator. Low-frequency oscillations may occur in GFM energy storage, which affect the stable operation of the power system. This paper proposed an additional damping control strategy for GFM energy storage to address the low-frequency oscillation. Firstly, this paper builds the state-space small-signal mathematical model of the GFM energy storage grid-connected system to analyze the participation factors of the low-frequency oscillation mode and clarify the key control parameters affecting the GFM energy storage grid-connected system the low-frequency oscillation. Then, this paper proposed an additional damping control strategy to increase the damping ratio of the low-frequency oscillation mode and improve the stability of the GFM energy storage grid-connected system. Finally, semi-physical experiments verified the effectiveness of the proposed additional damping control strategy. Full article

The Domain Name System (DNS) is a key part of the Internet, and it is used for global domain name resolution. However, it has security risks due to its centralized or semi-centralized design and reliance on a few root servers. To improve DNS security and long-term stability, this study proposes the consensus roots system, a blockchain-based distributed domain architecture. The system uses a 1 + N master-subchain structure to solve the problem of trust and data synchronization across blockchains. The master chain acts as a relay and uses Hyperledger Fabric, a consortium blockchain platform, to support semi-centralized cross-chain communication. Subchains are local blockchains that need to connect with the master chain. To ensure safe and reliable transactions, the system uses a staged-proposal atomic swap method on the master chain. Compared to prior approaches, this work introduces a cross-chain architecture that enables more efficient trust synchronization, reducing latency and improving scalability without compromising security. Full article

Effective monitoring of fish passage through river barriers is essential for evaluating fishway performance and supporting adaptive river management. Traditional methods are often invasive, labor-intensive, or too costly to enable widespread implementation across most fishways. Infrared (IR) beam-break counters offer a promising alternative, but their adoption has been limited by high costs and a lack of flexibility. We developed and tested a novel, low-cost infrared beam-break counter—FishTracker—based on open-source Raspberry Pi and Arduino platforms. The system detects fish passages by analyzing interruptions in an IR curtain and reconstructing fish silhouettes to estimate movement, direction, speed, and morphometrics under a wide range of turbidity conditions. It also offers remote access capabilities for easy management. Field validation involved controlled tests with dummy fish, experiments with small-bodied live specimens (bleak) under varying turbidity conditions, and verification against synchronized video of free-swimming fish (koi carp). This first version of FishTracker achieved detection rates of 95–100% under controlled conditions and approximately 70% in semi-natural conditions, comparable to commercial counters. Most errors were due to surface distortion caused by partial submersion during the experimental setup, which could be avoided by fully submerging the device. Body length estimation based on passage speed and beam-interruption duration proved consistent, aligning with published allometric models for carps. FishTracker offers a promising and affordable solution for non-invasive fish monitoring in multispecies contexts. Its design, based primarily on open technology, allows for flexible adaptation and broad deployment, particularly in locations where commercial technologies are economically unfeasible. Full article

Desktop Virtual Worlds (DVWs) offer unique spatial affordances for education, yet understanding of how these environments support meaningful learning experiences remains limited. This study introduces the Socio-Spatial Embodiment Model, a novel framework conceptualizing learning in DVWs as shaped by the interconnection of embodied presence, place-making, and community formation. Through semi-structured interviews conducted with 14 experienced educators from the Virtual Worlds Education Consortium, we investigated how these dimensions intersect and what design strategies facilitate this integration. Thematic analysis revealed that strategic design employs cognitive offloading techniques and biophilic metaphors to enhance embodied presence, balance familiar elements with spatial innovations to create meaningful places, and leverage synchronous engagement with institutional identity markers to facilitate learning communities. Our findings identified design strategies that facilitate stronger perceived student connections to the learning environment and community, when DVW designs address spatial, emotional, social, and cultural factors while reinforcing both cognitive and perceptual processes. This research advances understanding of embodied learning in virtual environments by identifying the dynamic interdependence among presence, place, and community, providing practical strategies for educators in creating more meaningful virtual learning experiences. Full article

Understanding indoor black carbon (BC) dynamics is important for assessing human exposure and informing air quality management in residential settings. This study presents a high-resolution, multi-sensor dataset collected over 24 days in a semi-occupied home in Zagreb, Croatia, designed to characterize the temporal behavior and sources of indoor BC. Indoor BC concentrations were measured at 1 min resolution using a dual-spot aethalometer, with source apportionment into biomass burning and fossil fuel components. Complementary contextual data including motion detection, door and window states, and traffic activity were collected in parallel using smart sensors and annotated experimental logs. Across the monitoring period, daily mean BC concentrations ranged from 174.7 and 1053.1 ng/m³ for biomass burning BC and between 53.2 and 880.3 ng/m³ for fossil fuel component. Statistical analyses revealed significant increases in BC concentrations during direct combustion-related activities, including scented candle burning and gas burner use. Additional BC elevations were associated with mechanical heat sources and nearby vehicle traffic, particularly affecting the fossil fuel BC component. In contrast, non-combustion activities such as brief human presence exhibited minor or inconsistent effects on indoor BC levels. This study elucidates the primary role of combustion-based indoor activities in influencing short-term BC exposure and highlights the importance of synchronized, high-resolution datasets for indoor air quality research. Full article

Hub motor-driven vehicles (HMDVs) suffer from poor handling and stability due to an increased unsprung mass and unbalanced radial electromagnetic forces. Although traditional ground-hook control reduces the dynamic tire load, it severely worsens the body acceleration. This paper presents a generalized ground-hook control strategy based on impedance transfer functions to address the parameter redundancy in structural methods. A quarter-vehicle model with a switched reluctance motor wheel hub drive was used to study different orders of generalized ground-hook impedance transfer function control strategies for dynamic inertial suspension. An enhanced fish swarm parameter optimization method identified the optimal solutions for different structural orders. Analyses showed that the third-order control strategy optimized the body acceleration by 2%, reduced the dynamic tire load by 8%, and decreased the suspension working space by 22%. This strategy also substantially lowered the power spectral density for the body acceleration and dynamic tire load in the low-frequency band of 1.2 Hz. Additionally, it balanced computational complexity and performance, having slightly higher complexity than lower-order methods but much less than higher-order structures, meeting real-time constraints. To address time-domain deviations from generalized ground-hook control in semi-active systems, a dynamic compensation strategy was proposed: eight topological structures were created by modifying the spring–damper structure. A deviation correction mechanism was devised based on the frequency-domain coupling characteristics between the wheel speed and suspension relative velocity. For ride comfort and road-friendliness, a dual-frequency control criterion was introduced: in the low-frequency range, energy transfer suppression and phase synchronization locking were realized by constraining the ground-hook damping coefficient or inertance coefficient, while in the high-frequency range, the inertia-dominant characteristic was enhanced, and dynamic phase adaptation was permitted to mitigate road excitations. The results show that only the T0 and T5 structures met dynamic constraints across the frequency spectrum. Time-domain simulations showed that the deviation between the T5 structure and the third-order generalized ground-hook impedance model was relatively small, outperforming traditional and T0 structures, validating the model’s superior adaptability in high-order semi-active suspension. Full article

Unmanned systems provide significant prospects for improving the efficiency of electromagnetic geophysical exploration in mineral prospecting and geological mapping, as they can significantly increase the productivity of field surveys by accelerating the movement of the measuring system along the site, as well as minimizing problems in cases where the pedestrian walkability of the site is a challenge. Lightweight and cheap UAV systems with a take-off weight in the low tens of kilograms are unable to carry a powerful current source; therefore, semi-airborne systems with a ground transmitter (an ungrounded loop or grounded at the ends of the line) and a measuring system towed on a UAV are becoming more and more widespread. This paper presents the results for a new generation of semi-airborne technology SibGIS UAV-TEMs belonging to the “line-loop” type and capable of realizing the transient/time-domain (TEM) electromagnetics method used for studying a uranium object of the paleovalley type. Objects of this type are characterized by a low resistivity of the ore zone located in relatively high-resistivity host rocks and, from the position of the geoelectric structure, can be considered a good benchmark for assessing the capabilities of different electrical exploration technologies in general. The aeromobile part of the geophysical system created is implemented on the basis of a hexacopter carrying a measuring system with an inductive sensor, an analog of a 50 × 50 m loop, an 18-bit ADC with satellite synchronization, and a transmitter. The ground part consists of a galvanically grounded supply line and a current source with a transmitter creating multipolar pulses of quasi-DC current in the line. The survey is carried out with a terrain drape based on a satellite digital terrain model. The article presents the results obtained from the electromagnetic soundings in comparison with the reference (drilled) profile, convincingly proving the high efficiency of UAV-TEM. This approach to pre-processing UAV–electrospecting data is described with the aim of improving data quality by taking into account the movement and swaying of the measuring system’s sensor. On the basis of the real data obtained, the sensitivity of the created semi-airborne system was modeled by solving a direct problem in the class of 3D models, which allowed us to evaluate the effectiveness of the method in relation to other geological cases. Full article

Regarding the high susceptibility problem of the Permanent Magnet Synchronous Motor (PMSM) to various uncertain factors, including load variations, parameter perturbations, and external interferences in the ship’s electric propulsion system, this paper presents a non-singular fast terminal composite sliding mode control (NFTCSMC) strategy based on the improved exponential reaching law. This strategy integrates the system’s state variables and the power function of the sliding mode surface into the traditional exponential reaching law, not only enhancing the sliding mode reaching rate but also effectively mitigating system chattering. Additionally, a sliding mode disturbance observer is developed to compensate for both internal and external disturbances in real time, further enhancing the system’s robustness. Finally, the proposed control strategy is experimentally validated using the rapid control prototyping (RCP) technology applied on a semi-physical experimental platform for ship electric propulsion. Experimental results indicate that, compared to traditional proportional–integral (PI), sliding mode control (SMC), and fast terminal sliding mode control (FTSMC) strategies, the NFTCSMC strategy enhances the propulsion and anti-interference capabilities of the propulsion motor, thereby improving the dynamic performance of the ship’s electric propulsion system. Full article

Fault detection is a critical research area, especially in the automotive sector, aiming to quickly assess component conditions. Machine Learning techniques, powered by Artificial Intelligence, now represent state-of-the-art methods for this purpose. This study focuses on durability testing of Permanent Magnet Synchronous Motors for automotive applications, using Autoencoders (AEs) to predict and prevent failures. This AI-based fault detection strategy employs acceleration signals coming from electric motors tested under challenging conditions with significant variations in torque and speed. This approach goes beyond typical fault detection in steady-state conditions. Based on a review of Neural Networks, including Variational Autoencoders (VAEs), Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, the performance of six AI architectures is compared: AE, VAE, 1D CNN AE, 1D CNN VAE, LSTM AE and LSTM VAE. The 1D CNN AE outperformed the other networks in fault detection, showing high accuracy, stability and computational efficiency. The model is integrated into an algorithm for semi-real-time fault monitoring. The algorithm effectively detects potential motor failures in real-world scenarios, including bearing faults, mechanical misalignments, and progressive wear of components, thereby proactively preventing damage and halving test bench downtime. Full article

Proton exchange membrane fuel cells (PEMFC), distinguished by rapid refueling capability and zero tailpipe emissions, have emerged as a transformative energy conversion technology for automotive applications. Nevertheless, their widespread commercialization remains constrained by technical limitations mainly in operational longevity. Precise prognostics of performance degradation could enable real-time optimization of operation, thereby extending service life. This investigation proposes a hybrid prognostic framework integrating steady-state modeling with dynamic condition. First, a refined semi-empirical steady-state model was developed. Model parameters’ identification was achieved using grey wolf optimizer. Subsequently, dynamic durability testing data underwent systematic preprocessing through a correlation-based screening protocol. The processed dataset, comprising model-calculated reference outputs under dynamic conditions synchronized with filtered operational parameters, served as inputs for a recurrent neural network (RNN). Comparative analysis of multiple RNN variants revealed that the hybrid methodology achieved superior prediction fidelity, demonstrating a root mean square error of 0.6228%. Notably, the integration of steady-state physics could reduce the RNN structural complexity while maintaining equivalent prediction accuracy. This model-informed data fusion approach establishes a novel paradigm for PEMFC lifetime assessment. The proposed methodology provides automakers with a computationally efficient framework for durability prediction and control optimization in vehicular fuel cell systems. Full article