Search Results (771)

Life cycle greenhouse gas (GHG) accounting is increasingly required to substantiate the climate value of wind power beyond “zero-emission” operation, especially under China’s dual-carbon targets. Robust estimation of life cycle GHG emission intensity and the identification of actionable mitigation levers are therefore important for credible transition planning. In this study, a process-based life cycle assessment (LCA) was conducted for a representative 100 MW onshore wind farm in Gaoyou, Jiangsu Province, China, following ISO 14040/14044. To enhance engineering relevance, the construction and installation phase was modeled in a refined manner by decomposing it into road, wind-turbine, booster-station, and transmission-line engineering and further into unit processes. The results show that the overall life cycle GHG emission intensity of the studied wind farm is 24.6 g CO₂-eq/kWh. Scenario analysis further indicates that reducing curtailment and improving end-of-life recycling are effective pathways to lower emission intensity, while the net advantage of hybrid versus steel towers depends on recycling performance when end-of-life credits are included. The study also summarizes practical implications for low-carbon equipment/material procurement and green supply-chain governance, low-carbon construction and logistics, coordinated “source–grid–load–storage” planning to curb curtailment, and more standardized and comparable life cycle carbon accounting for wind projects in China. Full article

This paper will present a constant-force vibration isolator (CFVI), in which the isolated load is supported by two pulley-roller mechanisms, while the dynamic stiffness is modified by a cam mechanism with the piecewise profile redefined by the user. As a result, this model can generate the constant force-displacement response within the working region, thereby obtaining quasi-zero stiffness in this range. Because of the piecewise configuration of the cam, the system motion governed by the piecewise dynamic equation under base motion excitation will be analyzed and established. The approximate solution of the piecewise dynamic equation is derived by using the average method, from which the relative amplitude–frequency relation and the absolute amplitude transmissibility of the CFVI will be obtained. The effects of the key working parameters involving the damping coefficient, critical position, and excited amplitude on the dynamic behavior and isolation effectiveness of the CFVI are considered through numerical simulations. The simulation result reveals that the dynamic response of the CFVI offers two branches: resonance and isolation. The former is significantly affected by the working parameters, whereas the latter is weakly influenced. Furthermore, the isolation effectiveness of the CFVI will be compared with that of its linear counterpart and the quasi-zero stiffness vibration isolation model using a semicircle cam (QZSI). The results demonstrate that the CFVI outperforms the other models for base motion excitations. Full article

Countries around the world are committed to achieving the Sustainable Development Goals (SDGs). However, significant challenges remain—particularly the economic consequences of climate change. Using a GVAR model for 17 economies over the period 2001M1–2021M12, we explore how temperature anomalies affect industrial production through four potential mechanisms: food prices, credit costs, exchange rates and investment. Our theoretical model demonstrates that temperature anomalies lower agricultural production, which drives up food prices and reduces real wages. This in turn leads to lower investment and production in the industrial sector. Our empirical results indicate that rising temperature anomalies are associated with a decrease in industrial production and investment, as well as the depreciation of domestic currencies relative to the U.S. dollar. Additionally, we observe that the influence of temperature anomalies is more pronounced in hot regions than in cold regions. Our investigation underscores the importance of financial markets and investment as potential transmission channels for the impact of climate change on industrial production. This study provides empirical evidence to support policymaking aimed at mitigating the adverse impacts of climate change, thereby helping countries to advance toward key SDGs such as no poverty, zero hunger, and climate action. Full article

Motivated by heterogeneous data distributions and task-dependent aggregation requirements in federated learning, we study information-theoretic secure aggregation of linear functions over a two-hop hierarchical network. The system comprises an aggregation server, an intermediate layer of U relays, and $UV$ users, where each relay serves a disjoint cluster of V users. Each relay observes all uplink transmissions within its cluster and forwards a coded message to the server. The server is authorized to compute a prescribed linear function F of the users’ inputs with zero error, while being prevented from learning any additional information about an unauthorized linear function G. Moreover, each relay must obtain no information about any non-trivial linear function $B_u$ of the inputs in its own cluster. We define the communication rates on both hops as the number of transmitted symbols per input symbol. By deriving matching information-theoretic converse and achievability bounds, we fully characterize the optimal communication rates and propose an explicit linear coding scheme that achieves the resulting optimal region. Our results demonstrate that hierarchical architectures can attain optimal communication rates while substantially reducing the server-side masking burden, thereby enabling scalable secure aggregation of authorized linear functions. Full article

Future 6G-enabled smart hospital infrastructures will support latency-critical medical operations such as robotic surgery, autonomous monitoring, and real-time clinical decision systems, which require communication mechanisms that ensure both ultra-low latency and long-term cryptographic security. Existing security solutions either rely on classical cryptographic protocols that are vulnerable to quantum attacks or deploy isolated post-quantum primitives without providing a unified framework for secure real-time medical command transmission. This research presents a latency-aware, multi-layered post-quantum security architecture for 6G-enabled smart hospital environments. The proposed framework establishes an end-to-end secure command transmission pipeline that integrates hardware-rooted device authentication, post-quantum key establishment, hybrid payload protection, dynamic access enforcement, and tamper-evident auditing within a coherent system design. In contrast to existing approaches that focus on individual security mechanisms, the architecture introduces a structured integration of Kyber-based key encapsulation and Dilithium digital signatures with hybrid AES-based encryption and legacy-compatible key transport, while Physical Unclonable Function authentication provides hardware-bound device identity verification. Zero Trust access control, metadata-driven anomaly detection, and blockchain-style audit logging provide continuous verification and traceability, while threshold cryptography distributes cryptographic authority to eliminate single points of compromise. The proposed architecture is evaluated using a discrete-event simulation framework representing adversarial conditions in realistic 6G medical communication scenarios, including replay attacks, payload manipulation, and key corruption attempts. Experimental results demonstrate improved security and operational efficiency, achieving a 48% reduction in detection latency, a 68% reduction in false-positive anomaly detection rate, and a 39% improvement in end-to-end round-trip latency compared to conventional RSA-AES-based architectures. These results demonstrate that the proposed framework provides a practical and scalable approach for achieving post-quantum secure and low-latency command transmission in next-generation 6G smart hospital systems. Full article

Measurement results of train-induced vibrations are evaluated for characteristic frequencies, amplitudes and spectra, leading to a prediction which is based on transfer functions of the vehicle–track–soil system, the soil, and the building–soil system. The characteristic frequencies of train-induced vibrations are discussed following the propagation of vibrations from the source to the receiver: out-of-roundness frequencies of the wheels, the sleeper passage frequency, the vehicle–track eigenfrequency, the car-length frequency and multiples, axle-distance frequencies, bridge eigenfrequencies, the building–soil eigenfrequency, and floor eigenfrequencies. Amplitudes and spectra are compared for different train and track types, for different train speeds, and for different soft and stiff soils, where high frequencies are typically found for stiff soil and low frequencies for soft soil. The ground vibration is between the cut-on frequency due to the layering and the cut-off frequency due to the material damping of the soil, but the dominant frequency range also changes with distance from the track. The frequency band of the axle impulses due to the passing static loads obtains a signature from the axle sequence. The high amplitudes between the zeros of the axle-sequence spectrum are measured at the track, the bridge, and also in the ground vibrations, which are even dominant in the far field. A prediction software is presented, which includes all three parts: the excitation by the vehicle–track interaction, the wave transmission through the soil, and the transfer into a building. Full article

Urban water supply systems require considerable electrical energy inputs across all operational processes: raw water abstraction, treatment, transmission, and distribution. Consequently, water loss within these processes represents not merely a loss of water volume, but also additional energy consumption and an increase in carbon emissions, given that electricity generation relies predominantly on fossil fuels. This study applied two methodological approaches to analyze the role of water loss within the Water–Energy–Carbon (WEC) Nexus of the Metropolitan Waterworks Authority (MWA), Thailand, over the period 2017–2024. The first method utilized a detailed WEC linkage analysis to balance water inputs and outputs in each process to quantify specific losses: raw water, in-plant, transmission, and distribution losses. The second method applied the International Water Association’s Leakage Emissions Initiative framework, focusing specifically on potable real water loss in distribution process, which constituted the largest volume (64.85% of total losses) and embodied the highest specific energy consumption. Based on the first method, the average annual potable real water loss was 534.71 MCM/yr (23.58% of water supplied to distribution), corresponding to embedded energy and carbon emissions of 103.76 GWh/yr (24.89% of total energy consumption) and 49,562 tCO₂e/yr (24.89% of total carbon emission), respectively. Although the second method was considerably simplified, the estimated energy and carbon emission values were only slightly higher than those derived from the detailed method, demonstrating the second method’s effectiveness as a streamlined assessment tool. These findings underscored that water loss reduction initiatives are essential for minimizing energy consumption and carbon emissions, thereby supporting Thailand’s pathway toward Net Zero emissions by 2050. Full article

The generation from decentralized energy resources strongly depends on weather conditions, which causes fluctuations and degrades power grid quality. One of the most effective solutions in modern power systems to mitigate this issue is the use of energy storage systems (ESSs). These systems enhance the network performance by reducing power fluctuations. In this scope, and for frequency analysis, a model consisting of two interconnected microgrids was considered in this work. The frequency of these microgrids varies due to sudden changes in load or generation (or both). The frequency regulation was performed by an efficient load frequency controller (LFC). This regulation was essential and was employed to improve control performance, reduce the impact of load disturbances on frequency, and minimize power deviations in the power flow tie-lines. A fuzzy logic-based optimizer was installed in each microgrid to optimize the proposed proportional–integral–derivative (PID) controllers by generating their optimal parameters. The main objective of the LFC was to ensure zero steady-state error for system frequency and power deviations in the tie-lines. However, with the increasing integration of renewable energies and the intermittent nature of their production due to climate change, frequency fluctuations arise. To mitigate this issue, a coordinated AGC–PMS (automatic generation control–power management system) regulation with hybrid energy storage systems and interconnected microgrids was designed to enhance the quality and stability of the power network. This paper focuses on the load frequency control (LFC) technique applied to interconnected microgrids integrating renewable energy sources (RESs). It presents an optimization study based on artificial intelligence (AI) combined with the use of energy storage systems (ESSs) and high-voltage direct current (HVDC) transmission link for power management and control. The renewable energy sources used in this work are photovoltaic generators, wind turbines, and a solar thermal power plant. A hybrid energy storage system has been installed to ensure energy management and control. It consists of redox flow batteries (RFBs), a superconducting magnetic energy storage (SMES) system, electric vehicles (EVs), and fuel cells (FCs).The system behavior was analyzed through several case studies to improve frequency regulation and power management under renewable energy integration and load variation conditions. Full article

In this study, we propose a compartmental mathematical model that considers two interacting populations (citrus plants and insect vectors) and investigate the transmission dynamics of Huanglongbing in citrus crops. This disease is caused by the bacterium Candidatus Liberibacter asiaticus and is vectored by the psyllid Diaphorina citri. The disease is modeled under the following three main assumptions: there is vital dynamics with constant recruitment rates of citrus plants, the force of infection in both populations is a spatially dependent function varying with geographic location, and there is a spatial displacement of the vectors. In the main results of the paper, we formulate a coupled ordinary and partial differential equation system with initial and zero flux boundary conditions, establish the existence and uniqueness of solutions to the proposed model by applying semigroup theory, and introduce a numerical approximation of the system. Moreover, we develop a stability and persistence analysis. From the analytical point of view, we calculate the basic reproduction number $R_0$ and prove three facts: the disease-free equilibrium is globally asymptotically stable when $R_0<1$; the disease-free equilibrium is globally asymptotically stable when $R_0>1$; and the hybrid system exhibits uniform persistence of infection when $R_0>1$. In addition, we present some numerical examples. Full article

Zero-valent iron (Fe(0)) nanoparticles have a wide range of applications, including catalysis, energy storage, and even reported roles in human neurochemistry. This study demonstrated that [Fe₃(CO)₁₂] dissolves in N,N-Dimethylformamide (DMF) within a minute to resolve the dissolution problem of this complex. Dodecylamine (DDA) was used to produce DDA-coated Fe(0) at 383 K in 30 s with a microwave reactor. The powder X-ray diffraction (PXRD) of the Fe(0) profile indicated a pure-phase face-centred cubic (FCC) structure with Fm$\overline{3}$m space group. Varying the synthesis time from 30 s to 5 min did not significantly affect the unit cell parameters (3.5276 (±0.0001) and 3.5391 (±0.0001) Å). Microwave use yielded well-dispersed, pure Fe(0) nanoparticles, and the particle size, shape, elemental analysis, and surface oxidation of the Fe(0) nanoparticles were studied using scanning electron microscopy and dispersive X-ray spectroscopy (SEM/EDX). Annular Dark-Field Scanning Transmission Electron Microscopy (ADF-STEM) and Fourier-transform infrared (FT-IR) spectroscopy confirmed the surface coating of Fe(0) nanoparticles with DDA. Thermogravimetric analysis (TGA) was used to demonstrate the surface adsorption of DDA on Fe(0) nanoparticles. In addition, STEM showed that the average nanoparticle size under the stated synthesis conditions was 25.7 nm. This comparatively straightforward procedure offers advantages over existing practical approaches to the synthesis of Fe(0) nanoparticles, including safety, speed and reaction control. Full article

Against the backdrop of the accelerating global energy transition toward clean and low-carbon sources, hydrogen energy is emerging as a vital component of future energy systems due to its zero-carbon emissions, high energy density, and renewable nature. The safe and efficient transportation of hydrogen is a critical link in the hydrogen energy industry chain. As core connecting components in hydrogen transmission systems, the sealing integrity, hydrogen embrittlement resistance, and long-term service reliability of hydrogen pipeline joints directly impact the stable operation of entire hydrogen transmission systems and the feasibility of large-scale application. This study systematically reviews the research literature on hydrogen pipeline joints from 2014 to 2025 using bibliometric and knowledge graph analysis methods based on the Web of Science Core Collection database. It constructs co-occurrence networks and clustering graphs of keywords to identify core research themes in this field, including hydrogen embrittlement failure mechanisms, degradation of sealing material properties, structural design optimization of joints, and intelligent monitoring and fault diagnosis. Furthermore, this study highlights existing research gaps in evaluating joints’ long-term service performance, developing low-cost and efficient manufacturing technologies, and verifying reliability under complex operating conditions. This study provides a systematic bibliometric perspective on hydrogen pipeline joint technology development, aiding in identifying research frontiers and technological evolution pathways. It offers theoretical support and decision-making references for the safe construction and standardized development of hydrogen energy infrastructure. Full article

To address the challenges of complex operation, high server deployment costs, and insufficient automated identification capabilities in community-based centralized electrocardiogram (ECG) screening, a novel arrhythmia screening system based on handheld ECG leads and email transmission is proposed. The system is operated in a zero-interaction mode: ECG acquisition is initiated automatically upon skin contact with the electrodes, and upon completion, the ECG signal is automatically analyzed and the email transmission function is triggered—no user intervention being required. First, noise in the ECG signal is effectively suppressed by cascading a zero-phase high-pass filter with a sliding window and a zero-crossing-rate (ZCR) guided adaptive wavelet thresholding technique. Subsequently, RR interval sequences are extracted from the denoised signals and fed into a lightweight bidirectional long short-term memory (BiLSTM) network for automatic arrhythmia detection. In the final step, a 30 s standard ECG, screening status, and acquired image are automatically delivered to clinicians via standard IMAP/SMTP email protocols—eliminating the need for dedicated mobile applications or cloud platforms. Experimental results demonstrated that the relative signal-to-noise ratio (SNR_ECG) was improved by 2.36 dB. On the independent test set, a sensitivity of 97.98%, a specificity of 98.21%, and an AUC of 0.994 were achieved. Furthermore, an end-to-end email transmission latency of less than 7.68 s was recorded. These findings confirm the potential of the proposed system as a low-cost, easily deployable, and elderly-friendly remote ECG solution for primary healthcare settings. Finally, in a pilot screening involving 10 volunteers, one case of arrhythmia was successfully identified, which validated the feasibility of the system. Full article

Organizations usually rely on stringent access control mechanisms where access policies are an important asset. Their storage or transmission in plaintext can compromise sensitive access rules. It is important in dynamic environments where access decisions are made in real time such as Zero Trust (ZT). Existing ZT approaches were found to oversee the aspect of securing these policies. This investigation presents a Multi-layer Access Policy Encryption System for ZT systems (MAPE-ZT). The first stage uses the trapdoor index to generate a secure index to find the applicable access policies. Advanced Encryption Standard-256 is used in counter mode for the encryption of the policies. They are re-encrypted using the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to allow decryption based on a matching set of attributes. Various experiments using quantitative metrics, including comparison with baseline access control systems simulation, scalability evaluation, storage overhead, etc., highlight the efficacy of the MAPE-ZT and establish new benchmarks. The result count entropy for the policies ranged 3.84–4.21 for different scales of policies. The evaluation in different scales of systems shows that the MAPE-ZT reduces various observable patterns even if the deployment size grows. Its unique design of securing policies makes this approach scalable for multi-domain integration. Full article

To address the challenges associated with inter-module energy interaction and mode adjustment at load ports in distributed energy systems in the context of the energy transition, this paper proposes and designs a multi-port wireless energy interaction system based on LC series resonance and multi-coil magnetic coupling. The system aims to facilitate flexible energy interaction among power sources, energy storage units, and loads, as well as multi-modal port regulation. The system employs a multi-coil coupled full-bridge topology combined with a phase-shift control strategy to achieve energy exchange and power regulation among multiple ports. To meet the power demands of different ports, a port state control method incorporating a mode preset mechanism is proposed, enabling the intermediate port to switch seamlessly among input (source), output (load), and active relay modes. This paper analyzes the operating modes of a single port and establishes the dynamic mathematical model of the overall three-coil system as well as the small-signal model of the port output. Furthermore, it investigates the energy interaction mechanism to derive the operating characteristics and conditions under different modes, and elucidates the energy relay mechanism with zero active power consumption. A three-port hardware experimental platform was constructed based on a dsPIC33 controller. Experimental results indicate that: (1) the prototype achieved a maximum transmission power of 100 W; (2) the peak system efficiency reached $83.1\%$ under different load conditions; and (3) during mode switching, the system response time was less than 200 ms with no significant overshoot. The study demonstrates that the proposed topology and control strategy effectively realized dynamic energy interaction and seamless mode switching among multiple ports, providing a theoretical basis and engineering reference for multi-port energy interaction and wireless power transfer networks. Full article

This paper investigates Direction-of-Arrival (DOA) estimation of Long-Range Navigation-C (Loran-C) signals using an Ultra-Short Baseline (USBL) receiving array. Two least-squares angle estimation approaches based on inter-element delay measurements are examined, including Correlation-based Least-Squares (Corr-LS) and a Zero-Crossing-based Least Squares (ZC-LS). In both methods, relative delays are extracted only within the local array and subsequently mapped to azimuth through a geometric least squares formulation; the approach is, therefore, distinct from distributed time difference-of-arrival (TDOA) localization. For comparison, the Multiple Signal Classification (MUSIC) algorithm is implemented as a covariance-based DOA estimator that operates without explicit delay extraction. Experiments were conducted using Loran-C transmissions from the Xuancheng, Xi’an, and Rongcheng stations, with 100 valid pulse groups collected for each station. Statistical analysis using boxplots shows that Corr-LS exhibits the largest variance due to broadened or shifted correlation peaks, particularly under skywave–groundwave interference. ZC-LS reduces both variance and bias by exploiting the deterministic zero-crossing structure of the Loran-C waveform. MUSIC produces the most concentrated azimuth estimates but requires a well-conditioned covariance matrix and substantially higher computational costs. The results demonstrate that ZC-LS achieves a favorable balance among angular accuracy, robustness, and real-time feasibility, making it suited for compact Loran-C receivers and complementary navigation applications in GNSS-challenged environments. Full article