Search Results (192)

This paper presents a non-imaging landmine detection system that integrates a highly sensitive multiple-input multiple-output (MIMO) microwave sensor with a machine learning (ML) classifier for automated classification. The proposed sensor consists of two circular patch elements fed with two ports designed in a unique configuration, comprising a dual loop with a cross dipole, for enhancing sensitivity to changes in the environmental electrical properties (dielectric constant and electrical conductivity) induced by buried metallic objects. It operates in dual bands of 1.58 GHz and 1.75 GHz, within the operating frequency range of 1.3 to 2 GHz. The system’s performance was assessed using full-wave simulations and experimental measurements, involving a sand-filled foam container with a metal surrogate landmine placed at different depths. The sensor’s performance was evaluated by monitoring changes in the magnitude and phase of the reflection coefficient ($S_{11}$) and the transmission coefficient ($S_{21}$). The acquired scattering parameters data were processed using a Support Vector Machine (SVM) algorithm for automated classification. Results demonstrate the sensor’s high capability in detecting metallic targets at various depths and standoff distances. Compared to conventional imaging technologies, this system offers significant advantages in cost, simplicity, and ease of data processing. The SVM models trained on measurement data with proper feature selection showed a high level of agreement with their counterparts trained on simulation data. Stratified k-fold cross-validation was used to improve the reliability of accuracy metrics, with results showing 85% or higher mean accuracy in all classification scenarios. Full article

Although the economic importance of optimizing lighting systems and energy use in indoor farming is well known, there is a notable lack of studies focusing on economic trade-off analysis between agrivoltaic and grid-powered solutions integrated into light map analysis and revenue sensitivity assessments. To address this gap, this study investigates an indoor true vertical lettuce agrotunnel. Regional, seasonal, and market type sensitivity analyses were carried out on the prices and experimental yields to calculate the revenue from lettuce production. Technoeconomic analysis indicated that agrivoltaics outperformed the grid-only power supply by net present cost and levelized cost of electricity reductions of 13.2% and 44.2%, respectively. Photosynthetic photon flux density (PPFD) and daily light integral (DLI) were compared for the cases of 41–61 cm distances between the lights and the walls. With the 20 cm distance variations, 16.6–17.8% changes in the average PPFD were achievable without increasing energy consumption. In addition, annual revenue from lettuce green mix packs ranged from $61,735 to $86,164 USD for singles and from $83,603 to $116,685 USD for multiple plants per pot strategies, depending on the variety packs. Luxury and mid-range price categories kept the return on investment above 10% at all capital cost levels. The agrotunnel achieved the maximum specific yield of >70 kg/m²/year. Full article

This study investigates the environmental and energy performance of rice straw-based energy pathways in Egypt, combining life cycle assessment (LCA) with supply chain optimization to improve system efficiency. The analysis covers thirteen governorates producing over 4.45 million tons of rice straw annually. It examines the whole supply chain from paddy farming, straw collection, and transport to electricity generation and ash disposal. Total energy consumption was 11,287 TJ, dominated by farming (5673 TJ) and transport (5490 TJ). Greenhouse gas (GHG) emissions were estimated at 12,007.5 million kg CO₂-eq, with significant contributions from farming (5158 million), combustion (3630 million), and natural gas use (3039 million). Gross electricity output was 5525 GWh, yielding a net of 4973 GWh, equivalent to 1116.5 kWh per ton of straw. Scenario analysis highlighted that the optimized multi-hub system, prioritizing Cluster 1 in the Nile Delta, which contributes over 92% of straw production and 4607 GWh of net electricity, achieved a reduction of more than 25% in transport distances and an 18% decrease in diesel consumption and related emissions. Sensitivity analysis further indicated that delivered electricity and GHG intensity are more sensitive to conversion efficiency and transmission and distribution losses than to moderate changes in transport assumptions. In addition to environmental improvements, the optimized scenario indicates potential social co-benefits, including rural employment generation, additional income opportunities for farmers, and improved air quality associated with reduced open-field burning. These outcomes are presented as indicative qualitative insights. Findings confirm rice straw as a strategic, scalable, and sustainable energy resource aligned with Egypt’s Vision 2030 and the UN Sustainable Development Goals (SDGs). Full article

Marine controlled source electromagnetic (CSEM) surveys have been proven to be an effective tool in hydrocarbon exploration, principally due to the method’s ability (in the right circumstances) to identify electrical resistivity contrasts between hydrocarbon-saturated and brine-saturated sedimentary units. However, the sensitivity of such surveys decreases in shallow water, for deeper targets, and for targets with limited horizontal extent. In principle, the resolution and sensitivity of a survey can be improved by moving either the transmitting or the receiving dipoles into the sub-surface. We have therefore investigated the sensitivity of Seafloor to Borehole CSEM (sbCSEM) survey geometries, specifically for the case of simplified targets with small lateral dimensions in shallow water areas—including targets whose depth of burial substantially exceeds their lateral extent. The results are encouraging. Neither small target size nor shallow water presents obstacles in principle to the use of this approach. Our models reveal distinct lobes in the patterns of electric field and current density amplitudes around a sub-seafloor transmitting dipole. The shape, positions and amplitudes of these lobes are all strongly modified by the presence of one or more small resistive targets, and they are strongly influenced by the positions of target edges. These effects significantly modify the pattern of electric fields at the seafloor and hence result in good sensitivity for realistic survey geometries. Small targets can be detected by seafloor receivers when the sub-seafloor transmitting dipole is located at some distance laterally outside the targets—leading to potential applications in ‘step-out’ prospecting. The asymmetry of responses at the seafloor from targets that are offset with respect to transmitter location has potential applications in field appraisal, while monitoring of reservoirs during production provides another possible application. Varying the depth of the transmitter down the borehole generates a Vertical EM Profiling (VEMP) survey—analogous to Vertical Seismic Profiling (VSP)—and we demonstrate that this too can have useful applications. Modelling for deeper (3 km sub-seafloor) targets continues to yield encouraging results and suggests that step-out sbCSEM may be effective at depths beyond the detection limit of conventional seafloor–seafloor CSEM. Full article

This paper describes the benchmark dataset for the electric vehicle routing problem with time windows. It is designed to facilitate the large-scale and reproducible evaluation of routing approaches under diverse charging scenarios. It is an extension of the Homberger 1000-customer vehicle-routing benchmark dataset through the incorporation of computationally derived charging-station data. For the 60 base instances included in the dataset, charging-station locations are randomly generated within the customer-coordinate bounds, and two variants are provided, resulting in 120 benchmark problems used in the validation and baseline analyses. A normalized local customer-density score is derived for each station. It is used to determine charging rates and log-normal parameters for prices and waiting times. Two variants are included in the dataset. Variant A maintains the original customer time-window constraints, while Variant B relaxes customer due dates based on the distance from the depot, subject to the depot closing time. The dataset is complemented by instance files, station attributes, parameters, and scripts. It also includes the results of feasibility tests, baseline solver tests, difficulty analyses, and sensitivity tests. These results show that the benchmark includes both easier and harder instance classes under different charging settings. Overall, the dataset is intended to support its use as a reproducible benchmark. Full article

Morocco’s recent legalization of industrial and medicinal cannabis has created a rapidly expanding seed-oil sector whose sustainability has yet to be fully assessed. This study applies an environmental life cycle assessment (LCA) in accordance with ISO 14040:2006 and ISO 14044:2006, complemented by a qualitative social responsibility assessment based on ISO 26000:2010, aiming to evaluate the life cycle sustainability of Moroccan cannabis seed oil. Three representative processing chains, traditional artisanal presses, producer cooperatives and regulated industrial plants are compared using a functional unit of 1 kg of cold-pressed oil packaged for local distribution. Inventory data were drawn from field measurements and interviews and were modeled in OpenLCA with background datasets from Ecoinvent 3.8 and Agribalyse v3.1. Impact assessment used the ReCiPe 2016 (H) method at the midpoint level across nine categories (climate change, fossil resource scarcity, water use, freshwater eutrophication, terrestrial acidification, land occupation, carcinogenic, non-carcinogenic human toxicity, and fine particulate matter formation). Sensitivity analyses varied seed yield, electricity mix and transport distances by ±20% to gauge uncertainty. Results show that the cooperative scenario achieves the lowest impacts across nearly all categories because of higher extraction yields (3 kg seed per kg oil), lower energy use (0.54 kWh kg⁻¹ oil) and more effective co-product recovery. In contrast, artisanal extraction requires approximately 1 kg of additional seed input per functional unit compared to optimized scenarios, significantly increasing upstream environmental burdens and causing upstream agricultural burdens to multiply. Industrial facilities perform comparably to cooperatives if powered by renewable electricity. Integrating a semi-quantitative social responsibility assessment reveals that legalization has markedly improved organizational governance, labor conditions, consumer protection and community involvement. Cooperatives display the most balanced social performance, whereas industrial plants excel in governance and quality control. A set of recommendations, including drip irrigation, cultivar improvement, co-product valorisation, renewable energy adoption, eco-designed packaging and cooperative governance, is proposed to enhance the environmental and socio-economic sustainability of Morocco’s emerging cannabis seed-oil industry. Full article

The integration of distributed photovoltaics (PV) introduces time-varying electrical coupling in active distribution networks, limiting the efficacy of conventional forecasting methods that rely on incomplete topological information and static physical models. This paper proposes a physics-informed spatio-temporal graph attention network (PI-STGAT) for probabilistic load forecasting under highly fluctuating conditions. A condition-adaptive correlation blending mechanism, derived from voltage–power sensitivity principles, fuses physical priors with statistical correlations using a PV-weighted strategy to capture time-varying electrical connectivity. An impedance-weighted continuous physical gating architecture maps voltage correlation coefficients into continuous attention biases, reflecting the spatial continuity of electrical distances while suppressing long-range noise. An uncertainty-aware adaptive physical constraint strategy dynamically modulates physical loss weights based on prediction variance and PV penetration, balancing fitting accuracy against physical consistency. Validation on real-world distribution network data demonstrates that, over a 24 h day-ahead horizon, PI-STGAT achieves a MAPE of 5.50%, a 3.7% relative reduction compared with LSTM. The model further attains a prediction interval coverage probability of 97.9%, confirming reliable uncertainty estimates under complex conditions. Full article

Hydrogen has been widely regarded as a key energy carrier. However, its storage and long-distance transportation are challenging, resulting in the emergence of ammonia as a potential carrier of hydrogen due to its high hydrogen density, ease of liquefaction, and established transport infrastructure. This study presents a techno-economic and environmental impact assessment of two methods of hydrogen production from ammonia: catalytic cracking (ACC) and electrocatalytic (AEC) decomposition, modeled under the specific local economic conditions of Brunei Darussalam. Analysis over a 20-year plant lifetime under local economic conditions indicates that the more technologically established ACC achieves a higher net present value of USD 7.298 million, compared to USD 6.867 million for AEC, primarily due to its significantly lower replacement costs. Sensitivity analysis indicates that AEC becomes economically favorable at production rates above approximately 29.5 kg/h or electricity prices exceeding USD 0.13/kWh. Environmental impact analysis indicates that AEC produces higher lifetime CO₂ emissions of approximately 84.9 million kg, compared to ACC with approximately 44.0 million kg of CO₂ emissions under grid-based electricity supply. This is mainly due to its higher electricity demand. Overall, the study highlights clear economic–environmental trade-offs between ACC and AEC and underscores the importance of integrated techno-economic and environmental evaluation for ammonia-based hydrogen systems in a Bruneian context. Full article

Electrical Resistivity Tomography (ERT) has proven to be a highly sensitive geophysical method for characterizing the dynamics of seawater intrusion. This study uses tank experiments to simulate seawater intrusion, utilizing electrical resistivity tomography to monitor real-time changes in groundwater resistivity during the intrusion process. The objective is to quantitatively reveal the development and evolution mechanisms of seawater intrusion wedges in sandy aquifers, thereby establishing a real-time resistivity monitoring method for groundwater distribution and migration characteristics. This study improves resistivity imaging data processing methods, enhancing both efficiency and accuracy. The refined cross-hole ERT technique is applicable not only to meter-scale indoor experiments; its optimized forward and inverse algorithms can also be directly transferred to regional-scale field monitoring. Experimental results show that the average resistivity in the study area continuously decreases from 57 Ω·m in the initial freshwater state to 1.1 Ω·m at the intrusion stabilization point. Areas with resistivity values below 20 Ω·m corresponded exactly to the brine intrusion zone. The evolution of the freshwater-saltwater interface unfolded in three stages: Initially, the density difference (0.025 g/cm³) dominated, with the saltwater intrusion depth at the aquifer base reaching 0.45 m, significantly exceeding the 0.04 m penetration at the upper section. During the intermediate stage, the interface morphology differentiated into an “upper triangular, lower arc-shaped” configuration. The bottom intrusion distance increased to 1.65 m, and the thickness of the brackish-freshwater mixing zone expanded from 0.1 m to 0.3 m. In the final stage, the interface stabilized and began intruding toward the surface, establishing a new hydrodynamic equilibrium. In addition, the migration rate of saline water at the aquifer base gradually decreased from 6.25 × 10⁻⁴ cm/s initially to 1.16 × 10⁻⁵ cm/s at steady state. These results reflect the dynamic coupling process between seepage and dispersion and demonstrate that this method enables effective real-time monitoring of seawater intrusion development and conditions, as well as early warning capabilities. Full article

Reliable prediction of energy consumption for electric motorcycles in sub-Saharan Africa requires models that reflect local riding conditions and measured component behaviour. This paper presents a validated, physics-based simulator for the Roam Air electric motorcycle that combines longitudinal dynamics with empirically derived motor and inverter efficiency maps obtained from dynamometer testing. The model ingests measured drive cycles and elevation-derived gradients to compute tractive effort and battery power flow and is validated against six real-world city and highway trips in Nairobi. The simulator reproduces temporal battery-power profiles with strong correlations between 0.87 and 0.91 and predicts energy per distance with small positive bias, achieving errors between 0.4% and 11.3%, where the measured energy consumption per distance ranges between 30.2 and 51.7 Wh/km. A sensitivity analysis quantifies the influence of key design parameters, and a scenario analysis assesses the impact of representative African driving conditions, including terrain, posture, payload, and surface type. The resulting framework is compact, transparent, and potentially adaptable to a wide range of electric two-wheelers, supporting design optimisation and electrification planning in the region. Full article

With the rapid development of high-voltage DC (HVDC) power systems, accurate measurement of surface electrostatic potential on insulating components has become critical for electric field assessment and insulation reliability. This paper proposes an electrostatic potential sensor based on cantilever micro-vibration modulation, which employs piezoelectric actuators to drive high-frequency micro-vibration of cantilever-type shielding electrodes, converting the static electrostatic potential into an alternating induced charge signal. An electrostatic induction model is established to describe the sensing principle, and the influence of structural and operating parameters on sensitivity is analyzed. Multi-physics coupled simulations are conducted to optimize the cantilever geometry and modulation frequency, aiming to enhance modulation efficiency while maintaining a compact sensor structure. To validate the effectiveness of the proposed sensor, an electrostatic potential measurement platform for insulating components is constructed, obtaining response curves of the sensor at different potentials and establishing a compensation model for the working distance correction coefficient. The experimental results demonstrate that the sensor achieves a maximum measurement error of 0.92% and a linearity of 0.47% within the 1–10 kV range. Surface potential distribution measurements of a post insulator under DC voltage agreed well with simulation results, demonstrating the effectiveness and applicability of the proposed sensor for HVDC insulation monitoring. Full article

Coastal reclamation profoundly alters soil physicochemical conditions and strongly influences soil microbial ecology; however, the millennial-scale successional patterns and assembly mechanisms of prokaryotic communities under such long-term disturbance remain insufficiently understood. In this study, we investigated archaeal and bacterial communities in the plow layer along a 0–1000-year coastal reclamation chronosequence on the southern shore of Hangzhou Bay. We analyzed community abundance, diversity, composition and assembly processes, and quantified the relative contributions of geographic distance, environmental factors and reclamation years to microbial biogeographic patterns. The results showed that reclamation markedly drove continuous soil desalination, acidification, nutrient accumulation, and particle-size refinement. Bacterial abundance exhibited a sharp decline during the early stages of reclamation, whereas archaeal abundance remained relatively stable. The α-diversity of both archaea and bacteria peaked at approximately 210–230 years of reclamation. Community assembly processes differed substantially between the two microbial domains: the archaeal communities were dominated by stochastic processes (77.78%) identified as undominated processes and dispersal limitation, whereas bacterial communities were primarily shaped by deterministic processes (70.75%) driven as variable selection. Distance–decay analysis indicated that bacterial communities were more sensitive to environmental gradients. Multiple regression and variance partitioning further demonstrated that soil pH and electrical conductivity were the key drivers of community structure. Overall, this study reveals the millennial-scale community dynamics and assembly mechanisms of archaea and bacteria in response to coastal reclamation, providing mechanistic insights into long-term microbial ecological succession and offering valuable guidance for sustainable agricultural management and ecological restoration in reclaimed coastal regions. Full article

The interaction between laser irradiation and energetic materials is critically influenced by microstructural void defects that determine local energy deposition and initiation sensitivity. In this work, a three-dimensional finite-difference time-domain (3D-FDTD) method was employed to investigate the modulation effects of void defects on optical field distributions and hot spot formation in RDX energetic crystals. The influences of void geometry, spatial position, and void number on the modulation of the incident laser beam were systematically analyzed. It reveals that void defects exhibit strong focusing and scattering behavior, leading to localized high-intensity regions both inside RDX bulk crystals and in void defects. For a single void defect, increasing either the width or depth can significantly enhance the peak electric field and thus the laser sensitivity of RDX crystals. When two voids are present, the number of high-intensity spots first increases and then decreases with increasing separation distance, and the strongest modulation effects are obtained at separations of 0.75λ–3λ. Furthermore, as the number of void defects increases, the modulation effect intensifies, promoting the formation of more hot spots. These findings provide quantitative insight into how void structures govern laser–matter interactions in energetic crystals, offering guidance for understanding and controlling laser initiation behavior. Full article

Octachlorinated metal phthalocyanines (MPcCl₈, M = Co, Zn, VO) represent an underexplored class of functional materials with promising potential for chemiresistive sensing applications. This work is the first to determine the structure of single crystals of CoPcCl₈, revealing a triclinic (P-1) packing motif with cofacial molecular stacks and an interplanar distance of 3.381 Å. Powder XRD, vibrational spectroscopy, and elemental analysis confirm phase purity and isostructurality between CoPcCl₈ and ZnPcCl₈, while VOPcCl₈ adopts a tetragonal arrangement similar to its tetrachlorinated analogue. Thin films were fabricated via physical vapor deposition (PVD) and spin-coating (SC), with SC yielding highly crystalline films and PVD resulting in poorly crystalline or amorphous layers. Electrical measurements demonstrate that SC films exhibit n-type semiconducting behavior with conductivities 2–3 orders of magnitude higher than PVD films. Density functional theory (DFT) calculations corroborate the experimental findings, predicting band gaps of 1.19 eV (Co), 1.11 eV (Zn), and 0.78 eV (VO), with Fermi levels positioned near the conduction band, which is consistent with n-type character. Chemiresistive sensing tests reveal that SC-deposited MPcCl₈ films respond reversibly and selectively to ammonia (NH₃) and hydrogen sulfide (H₂S) at room temperature. ZnPcCl₈ shows the highest NH₃ response (45.3% to 10 ppm), while CoPcCl₈ exhibits superior sensitivity to H₂S (LOD = 0.3 ppm). These results suggest that the films of octachlorinated phthalocyanines produced by the SC method are highly sensitive materials for gas sensors designed to detect toxic and corrosive gases. Full article

Landfills situated in karst terrains pose unique sustainability challenges due to the complex geological characteristics of these environments. This is mainly due to the well-developed underground drainage systems, including discontinuities and caves that can quickly transport contaminants over long distances, reaching the water sources and ecosystems. The focus of this study is on multi-geophysical assessment incorporating electrical resistivity tomography (ERT) and seismic refraction tomography (SRT) to evaluate the volume of the waste and to delineate the contact between the waste material and the karst, offering a more comprehensive view of subsurface conditions. The presented examples include geophysical mapping of the landfills Sodol and Sorinj, situated in the immediate vicinity of sensitive water bodies, increasing the potential risk of environmental contamination. At both sites, the boundary between waste material and bedrock was clearly delineated. Bedrock was identified with P-wave velocities of approximately 3000 m/s at Sodol Landfill and 2000 m/s at Sorinj Landfill. Waste material, observed at both sites, exhibited electrical resistivity values up to 120 Ω·m. The combined use of ERT and SRT provides extensive coverage of the landfill area, surpassing what can typically be achieved through traditional methods such as boreholes or excavations. Overall, the obtained results show promising potential for using integrated geophysical methods to accurately characterize landfill sites in karst terrains, thereby improving environmental protection strategies in karst regions and contributing to sustainable waste management. Full article