Search Results (301)

Direct air capture of CO₂ (DAC) is an emerging engineered carbon removal technology designed to extract CO₂ directly from ambient air and support long-term net-negative emission pathways. Unlike point-source carbon capture, DAC operates under ultradilute CO₂ conditions, where the low partial pressure of CO₂, large air-processing demand, humidity fluctuations, and regeneration energy requirements impose coupled thermodynamic, kinetic, and engineering constraints. While numerous reviews have addressed DAC materials or specific process configurations, a systematic account of how capture performance is progressively lost through the transition from molecular binding to material shaping, contactor operation, regeneration, and final storage remains lacking. This review fills this gap by adopting a performance-transfer framework that bridges capture chemistry, sorbent architecture, contactor engineering, and scalable deployment. We systematically survey the literature of the past decade across capture chemistries, sorbent design principles, structured contactors, regeneration strategies, and system integration, with a focus on studies that report cyclic working capacity, regeneration energy, and material stability under realistic conditions. Rather than enumerating material properties, we analyze the cascading losses introduced at each scale and identify the key bottlenecks limiting net carbon removal. Based on this analysis, we propose a staged roadmap from standardized material reporting to integrated DAC with carbon storage, aiming to guide future research toward verifiable and durable CO₂ removal. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

Firmware forms the persistent software layer controlling embedded and Internet-of-Things (IoT) devices, industrial controllers, automotive systems, and cyber-physical infrastructure. Vulnerabilities in firmware enable remote compromise, supply-chain attacks, and long-lived implants that survive operating-system reinstallation. This review synthesises 118 works published from 2014 to 2026—comprising 78 primary research studies; 23 surveys and systematisations of knowledge; and 17 benchmarks, tools, and background references—covering the full firmware reverse engineering (FRE) pipeline: physical acquisition (including fault injection and side-channel extraction), format analysis and unpacking, static analysis (binary code similarity detection, protocol reverse engineering, and patch diffing), dynamic analysis and hardware emulation, fuzzing-based vulnerability discovery, and artificial intelligence (AI) and large language model (LLM)-assisted analysis. Three additional dimensions are surveyed: digital twin-assisted firmware security testing; secure boot, trusted execution environment (TEE), and over-the-air (OTA) update security; and firmware rootkit and implant detection. Coverage spans two axes—the firmware class (Linux-based IoT, microcontroller-unit bare-metal, RTOS, UEFI/BIOS, PLC/ICS, and automotive ECU) and analysis depth (surface scanning to exploit-validated vulnerability chains). We identify ten structural gaps, including the absence of unified evaluation benchmarks, fragmented peripheral modelling, the scalability–fidelity trade-off in re-hosting, and insufficient grounding of LLM tools in firmware-specific realities. We conclude with six research directions for trustworthy, scalable, and infrastructure-aware firmware analysis. Full article

Inductive power transfer (IPT) is a promising charging approach for rail trams because their trajectories are fixed, lateral displacement is constrained by the rails, and charging infrastructure can be installed at predetermined locations. Nevertheless, the long vehicle body, high power demand, variable air gap, and dynamic operating conditions of rail trams impose stringent requirements on magnetic-coupler design. This study proposes a bibliometric-assisted analytic hierarchy process (AHP) framework for the comprehensive performance evaluation of magnetic couplers used in rail–tram IPT systems. The framework considers five performance dimensions: power-efficiency characteristics, spatial characteristics, power density, time characteristics, and energy-transfer capability. Bibliometric keyword-occurrence statistics are introduced as an external source of evidence to support the initial construction of AHP judgment matrices, thereby reducing the exclusive dependence of conventional AHP on the judgments of a small expert group. A 2M2T low-floor tram is used as a case study, and two magnetic-coupler configurations, namely the $2\times 1$ and $3\times 1$ configurations, are evaluated using electromagnetic and circuit-simulation results. The case study illustrates the application of the proposed framework to the comparison of magnetic-coupler configurations under the operating and installation constraints of the investigated tram. The present validation is limited to simulation-based analysis of one tram platform and two configurations; further experimental and multi-configuration validation is required. Full article

In the present research, the application of a photocatalytic reactor operated under simulated solar-light-assisted air gap membrane distillation (AGMD) is proposed to remove ketoprofen from seawater. TiO₂ at a concentration of 1 g/L, containing sulfur, was applied as a photocatalyst. The AGMD process was carried out under a feed temperature of 60–80 °C and a membrane area of 131 cm² during long-term operation. Simulated solar light was applied as an irradiance source. At the first stage of the process, the feed was concentrated for 73 h, and after that, the solution of seawater spiked with ketoprofen was photocatalytically treated for 96 h. Based on the experiments, it was found that 51% of ketoprofen was removed after the solar-driven photocatalysis process. Pure distillate without salts (conductivity below 2 µS/cm) and ketoprofen were obtained after 73 h. The performance of the membrane exhibited ca. two times higher permeate flux at an operation temperature of 80 °C in comparison with 60 °C, i.e., 24.7 L/h·m² and 47.3 L/h·m², respectively. Despite the presence of small deposits on the membrane surface, no membrane wetting was observed. The concentration of ketoprofen in the concentrates during the AGMD process and solar-driven photocatalysis can remove this pharmaceutical even from matrices enriched with salts (high AGMD concentrate), with good efficiency. Full article

Climate change is increasingly affecting freshwater ecosystems across Northern Europe, yet the responses of inland waters differ according to regional climatic and environmental conditions. Latvia, located within the boreo-nemoral transition zone, provides an important case for understanding these responses. This review synthesises published evidence on climate-driven changes in Latvian inland surface waters by integrating information on climatic trends, hydrological processes, hydrochemical responses and freshwater biota. The available evidence indicates that increasing air temperature, changing precipitation patterns and more frequent hydrological extremes have altered river discharge, ice regimes, water temperature and lake processes. These hydrological changes generate cascading effects on nutrient transport, dissolved organic matter and water quality, ultimately influencing primary production, community composition, species redistribution and fish communities. The review identifies hydrology as the principal mechanism linking climatic forcing with hydrochemical and biological responses. Although the overall direction of change is consistent with observations across Northern Europe, local catchment characteristics and multiple stressors modify ecosystem responses in Latvia. The synthesis also identifies major knowledge gaps regarding ecosystem-scale processes, ecological thresholds and long-term integrated monitoring. Addressing these gaps will improve understanding of climate-driven changes in Latvian inland waters and strengthen the scientific basis for adaptive freshwater management in Latvia and comparable northern European regions. Full article

Continuous trajectory maintenance is important for aerial vehicle monitoring, threat assessment, and warning or interception decisions in ground-to-air remote sensing systems. In the considered system, radar and radio-frequency (RF) sensing are used together to produce fused aerial tracks. In practical monitoring, the fused trajectory can still be interrupted by occlusion, maneuvering, missed detections, poor sensing geometry, or unstable measurements. These interruptions produce fragmented tracks and reduce the reliability of long-term surveillance. This paper formulates 3D trajectory restoration as a post-processing task for fused aerial tracks and proposes AeroDiff-TIR, a conditional diffusion-based restoration framework. The method represents trajectories in a local Cartesian coordinate system and treats each interrupted segment as the missing part of a time series. Given the observed points before and after a gap, AeroDiff-TIR learns the conditional distribution of the missing segment and restores it through iterative denoising. Experiments on a simulated aerial vehicle trajectory benchmark and measured unmanned aerial vehicle (UAV) trajectories collected by a ground-to-air monitoring system show that AeroDiff-TIR improves trajectory consistency over the complete restored gap and can support trajectory continuity in aerial monitoring systems. Full article

During the entire service cycle, the Electro-Hydrostatic Actuators (EHAs) are subjected to multi-physical stresses, including coupling effects, including high temperatures, severe temperature variation, and high-frequency pulses. These stresses not only act on the mechanical structures but also continuously degrade the dielectric properties and mechanical strength of the insulation materials, with long-term accumulation potentially leading to deterioration in insulation performance. Consequently, whether the insulation system can remain stable under such harsh conditions becomes a core factor constraining EHA reliability, and its insulation reliability directly determines the operational safety of aircraft actuation systems. Targeting the aerospace EHA motor insulation system, this paper aims to construct a systematic condition assessment method and a life degradation feature based on the dynamic evolution characteristics of multi-dimensional dielectric parameters. This study conducts accelerated thermal aging and thermal cycling tests on a 270 V Type I aerospace EHA motor insulation system, with multi-parameter tracking of equivalent capacitance (Ceq), partial discharge inception voltage (PDIV), and leakage current (I). The results indicate that Ceq exhibits high sensitivity to early-stage insulation damage. PDIV presents non-monotonic fluctuations during aging, and combined with Paschen’s law, the reduction in air-gap dimensions due to thermal expansion in the mid-stage is the physical origin of its phased recovery—verifying the rationale in using PDIV as the electrical safety boundary. In contrast, leakage current shows significant hysteresis, remaining robust at 0.35–0.55 mA until a sharp jump signals the formation of through-going conductive channels, which serve as the ultimate failure criterion. On this basis, a hierarchical assessment framework is constructed: Ceq captures degradation precursors, PDIV defines the safety boundary, and leakage current acts as the final failure indicator. This study refines the multi-stress evaluation method for aerospace motor insulation and provides experimental support for reliability assessment and life prediction of actuation systems in next-generation more-electric aircraft. Full article

Background: High-dose-rate interventional radiotherapy (HDR IRT) relies on accurate dose calculations to ensure safe and effective treatment. The AAPM TG-43 formalism, based on homogeneous water assumptions, has long been the clinical standard, but the growing use of patient-specific applicators and heterogeneous materials challenges its accuracy. Materials and Methods: A literature narrative review was performed using PubMed and Scopus to identify studies comparing TG-43 and model-based dose calculation algorithms (MBDCAs), including deterministic methods (ACE, Acuros BV) and Monte Carlo simulations. Thirty-five studies were selected and qualitatively analyzed. Results: TG-43 yielded higher dose compared with MBDCAs, particularly in the presence of tissue heterogeneities, air gaps, shielding materials, and limited scatter conditions. Differences ranged from 2 to 5% in relatively homogeneous settings to more than 10–20% in complex geometries such as superficial mould treatments and head-and-neck IRT. Model-based approaches showed better agreement with Monte Carlo simulations and experimental measurements, especially in contact HDR IRT and applications involving 3D-printed applicators. Conclusion: While TG-43 remains clinically established and widely used, its limitations are increasingly evident in modern personalized HDR IRT. Model-based dose calculation algorithms provide greater dosimetric accuracy and should be progressively integrated into clinical practice, particularly in treatments involving significant heterogeneities. Full article

The Eddy Covariance station provides observations of agrometeorological variables and surface energy fluxes, collected from 2019 to 2022, in a citrus orchard located in the Souss-Massa plain, Morocco. The present dataset comprises measurements recorded via a set of aboveground and subsurface sensors. The aboveground setup consistently measures air temperature, relative humidity, wind speed, net radiation, and precipitation. Additionally, the subsurface setup continuously tracks soil temperature, moisture, and electrical conductivity at depths from 5 to 80 cm, along with soil heat flux. Moreover, these setups enable the measurement of turbulent fluxes (sensible and latent heat). Given the limited availability of long-term agrometeorological data in semi-arid regions of the Mediterranean, this paper addresses a critical data gap by providing a reliable agrometeorological dataset. The latter consists of two types of data: 30 min interval files and high-frequency files (20 Hz, i.e., one measurement every 50 ms). The processing of this data involved Card Convert, MATLAB EC-Pack, and Excel, with data quality control performed by removing outliers and excluding nighttime fluxes. The dataset is organized in a table and provided in a .csv format with standard metadata. It is designed for a wide range of applications, including evapotranspiration modeling, satellite product validation, agroclimatic monitoring, determining crop irrigation requirements, precision irrigation planning, and water management. Additionally, the dataset can be reused for crop and hydrological model calibration, as well as soil moisture and crop stress prediction using machine learning algorithms. Full article

Mitigating population exposure to fine particulate matter (PM_2.5) is a core prerequisite for advancing Sustainable Development Goal 11.6.2 and global urban sustainability. This study integrated 0.1° × 0.1° gridded PM_2.5 reanalysis data, WorldPop high-resolution population datasets, and official SDG 11.6.2 scoring records spanning 2000–2019, and adopted multi-scale spatial statistics and population-weighted exposure models to systematically explore the spatiotemporal differentiation of global PM_2.5 concentrations and associated population exposure risks, as well as their coupling relationship with SDG 11.6.2 implementation progress. This study employs ArcGIS 10.6 software to harmonize the spatial scales of multi-source heterogeneous data through spatial statistics and resampling methods, and applies the SDSN (Sustainable Development Solutions Network) standardized scoring framework to quantify long-term progress across regions in meeting urban air quality targets. The results reveal significant latitudinal spatial heterogeneity in global PM_2.5 concentrations, with values ranging from 0.95 to 262.15 μg/m³; severe pollution hotspots exceeding 35 μg/m³ were agglomerated across Asia, Africa and South America, while Canada, Greenland, the Tibetan Plateau and eastern Russia maintained ultra-low PM_2.5 levels below 5 μg/m³. Global SDG 11.6.2 standardized scores rose steadily from 71.05 in 2000 to 76.64 in 2019, with Asia and Africa achieving the most remarkable score growth despite low initial baselines. Regional gaps in target realization remained stark: North America, Oceania and Northern Europe basically met the PM_2.5 sustainability standards, whereas densely populated regions of Asia and Africa faced critical governance challenges. Among nine typical countries, only China and India recorded population-weighted PM_2.5 concentrations above 25 μg/m³ in 2019; China’s air pollution control policies delivered continuous emission reductions after 2013, while India sustained extremely high exposure risks. From 2010 to 2019, the global range of urban population-weighted PM_2.5 concentrations narrowed, yet Afghanistan, Tajikistan and North Korea remained the most severely exposed nations. This study verifies the severe cross-regional inequity of PM_2.5 exposure risks under the SDG framework, and provides multi-scale empirical evidence for differentiated air quality governance and international collaborative interventions to accelerate the delivery of the 2030 sustainable development agenda. Full article

Bolstered by emerging sixth-generation (6G) communication technology, space–air–ground– sea integrated networks (SAGSINs) are reshaping edge computing through the synergistic use of space, aerial, terrestrial, and maritime platforms. However, in such highly dynamic and heterogeneous network environments, long-term energy-efficient computation offloading in drone-enabled SAGSINs has not yet been thoroughly explored, particularly when dynamic task demands from user equipment (UE) are served under the constraints of energy-limited drones. To fill this gap, the problem of service node association and computing-frequency allocation under dynamic computation offloading demands at the edge of the networks is studied in this paper. However, the related problem turns out to be a stochastic optimization problem. To this end, through in-depth mathematical analysis based on the Lyapunov optimization method, it is found that the multi-time-slot long-term optimization problem can be transformed into several single-time-slot optimization problems, which enables an efficient solution to the original problem. The single time-slot problem is solved using graph theory, convex optimization, and optimization theory, where Lyapunov optimization is utilized to achieve queue stability and energy efficiency. Simulation results demonstrate that the proposed strategy effectively reduces energy consumption, ensures low delay, and maintains long-term queue stability in drone-enabled SAGSINs under dynamic task demands from UE. Full article

Geoelectric field observations play a vital role in geophysical exploration, geological disaster early warning, and underground resource detection. Traditional contact non-polarisable electrodes, which require burial and electrolyte coupling, are hindered by several issues, such as limited adaptability to challenging terrain, significant electrode potential drift, and high susceptibility to environmental interference. Existing non-contact electric field sensors often exhibit insufficient coupling capacitance, poor impedance matching for ultra-weak high-impedance signals, and inadequate low-frequency noise suppression, rendering them unsuitable for the precise acquisition of natural microvolt-level geoelectric field signals. To address these challenges, this study introduces an innovative non-contact geoelectric field sensor with a three-layer composite structure. The sensor operates based on the principle of a parallel-plate capacitor, with a conductive silver paste layer at the top acting as the signal acquisition electrode plate, which forms an equivalent parallel-plate capacitance model with the ground to achieve non-contact capacitive coupling for geoelectric field detection. The intermediate layer uses lead zirconate titanate (PZT) piezoelectric ceramics as a support medium with a high dielectric constant. At the bottom is a silicon-based, flexible, sensitive ground-contacting layer with high elasticity, which allows it to adapt to micro-level surface irregularities, eliminating air gaps between the electrode plate and the ground, increasing plate-to-ground coupling capacitance, and ensuring the stability of the capacitance. The three-layer structure was created using a dry-press sintering integration approach, which eliminates interlayer bonding materials while ensuring consistent dielectric performance and efficient charge transfer. Additionally, a specialised signal-conditioning circuit was designed to match the ultra-high-impedance sensitive unit, utilising the ADA4528-2 ultra-low-noise precision operational amplifier, which achieved low-loss conversion and strong noise suppression for ultra-weak high-impedance charge signals. The circuit simulation results demonstrate that the designed circuit achieves an input impedance of no less than 10 TΩ, an effective operating bandwidth from 0.02 Hz to 20 kHz, and a voltage noise density lower than 1.5 μV/√Hz at 10 Hz, fully covering the ultra-low-frequency effective band of natural geoelectric fields. Field experiments comparing artificial and natural field signals revealed that the proposed sensor could be quickly deployed by simply attaching it to the ground without burial. Its time-domain waveform consistency and frequency-domain component matching were nearly identical to those of commercial standard solid non-polarisable electrodes, with a cross-correlation coefficient greater than 0.98, indicating no significant potential drift or power-frequency interference. By structurally eliminating the inherent electrode potential difference, the sensor offers advantages such as ease of deployment, strong environmental adaptability, high precision for weak signal acquisition, and excellent engineering substitutability. It is well suited for long-term geoelectric field observations in complex field scenarios, including deserts, Gobi areas, and frozen soil regions, and provides a high-performance, novel sensing solution for geoelectric field detection in extreme environments. Full article

Air-gap variation in elevator brakes affects armature actuation, brake-shoe release/contact processes, and transient vibration responses, making it an important indicator for brake condition monitoring. However, long-duration vibration recordings acquired from brake-mounted sensors contain mixed operating stages, which makes it difficult to isolate short action-related impacts. This study develops an engineering-oriented sensor-based framework for elevator brake air-gap monitoring by combining RMS-envelope-guided transient impact extraction with an RBF-SVM classifier. A triaxial accelerometer was mounted on the right-side brake armature, and a fixed y-axis vibration channel was used as the baseline input for feature construction. The short-time RMS envelope was first used to identify operating-state transition boundaries. Brake-release and brake-engagement impact peaks were then localized within the neighborhoods of these boundaries, and fixed-length transient impact samples were extracted. Time-domain, frequency-domain statistical, and band-energy features were constructed to characterize impact intensity, spectral structure, and energy redistribution under different air-gap conditions. Experiments were conducted on an elevator traction-machine brake under six controlled air-gap states from 0.30 mm to 0.80 mm. The results show that brake-release impact features are more sensitive to air-gap variation than brake-engagement or combined impact features. Using brake-release features, the proposed RMS-IE-SVM method achieved an accuracy of 89.77% and a Macro F1 of 89.85% under the last-file split setting, and a mean accuracy of 83.62% and a mean Macro F1 of 79.07% under file-grouped cross-validation. In the common-sample multi-axis comparison, X + Y + Z feature-level fusion achieved a file-grouped cross-validation accuracy of 89.63% and a Macro F1 of 85.94%. Feature-group ablation shows that time-domain features provide the dominant information, while band-energy features offer complementary information. These results indicate that RMS-envelope-guided transient impact extraction provides an interpretable framework for controlled-condition elevator brake air-gap identification and that multi-axis vibration information can further improve cross-file generalization. Full article

The accelerating transition toward renewable electricity generation has elevated grid-scale electrochemical energy storage from an ancillary grid service to a foundational infrastructure requirement. This review provides a comprehensive account of rechargeable battery technologies for stationary grid applications, spanning advanced lithium-ion systems, sodium-ion and post-lithium multivalent chemistries, vanadium and organic flow batteries, solid-state architectures, and high-energy-density future systems such as lithium-sulfur and metal-air cells. The techno-economic context of grid-scale storage is systematically examined, including performance metrics, market drivers, and regulatory frameworks. Each battery chemistry is analyzed with respect to electrochemical mechanism, cycle life, energy density, safety profile, material availability, and commercial readiness. Non-electrochemical storage technologies are discussed as system-level alternatives. Battery safety engineering, thermal management system design, thermal runaway mechanisms and prevention, and failure containment strategies are examined in depth, followed by analysis of critical material supply-chain vulnerabilities, life-cycle assessment, and recycling pathways. The expanding role of artificial intelligence, machine learning, and digital twin frameworks in optimizing performance and enabling predictive maintenance is reviewed. Key challenges, including material bottlenecks, manufacturing scalability, long-duration storage gaps, and the absence of harmonized performance standards, are identified, and the review concludes with a techno-economic roadmap toward cost-competitive, resilient, and low-carbon grid storage. Full article