Eng

Accurate early-stage assessment of building energy and carbon performance is essential for informed sustainable design yet remains challenging due to limited design detail and simulation effort. This study presents a Building Information Modeling–Machine Learning (BIM-ML) framework for predicting office building energy and carbon performance at early design stages using simulation-based datasets. A reduced-factorial Design of Experiments (DOE) generated 210 parametric office building models for Orlando, Florida (ASHRAE Climate Zone 2A), complemented by additional climate scenarios. Systematic variations in geometry, envelope, building systems, and operational schedules produced a dataset with 14 independent variables and five performance indicators: Energy Use Intensity, Operational Energy, Operational Carbon, Embodied Carbon, and Total Carbon. Four regression methods—Linear Regression, Model Tree (M5P), Sequential Minimal Optimization Regression, and Random Forest—were trained and evaluated using 10-fold cross-validation. Random Forest showed the strongest overall predictive performance. Feature-importance analysis identified HVAC system type, Window-to-Wall Ratio, and operational schedule as the most influential parameters, while geometric factors had lower impact. Cross-climate analysis and validation with measured data from two university office buildings indicate that the framework is adaptable and generalizable, supporting reliable early-stage evaluation of energy and carbon performance. Full article

To comprehensively evaluate the thermal risk parameters of the HMX synthesis process via the acetic anhydride method, we systematically investigated the safety of raw materials, ingredient mixing, nitration, and crystal transformation processes using DSC, ARC, and reaction calorimetry, which enabled the optimization of feeding strategies based on the exothermic characteristics observed during both ingredient mixing and nitration. Results indicate that the decomposition temperatures of raw materials and products are all above 200 °C, showing excellent thermal stability. Thus, multi-batch feeding is preferred for reaction material preparation. For the nitration process, continuous and stable feeding must be guaranteed during the feeding stage. During nitration, the temperature relationship satisfies T_p < MTSR < MTT < T_D24, wherein the risk of secondary decomposition and overflow is low. Additionally, both the nitration filtrate and crystal transformation filtrate exhibit low thermal hazards. These collective findings indicate that the acetic anhydride-based HMX synthesis process maintains relatively safe operational characteristics under standard processing conditions. Full article

This study introduces a hybrid methodological approach for personalised clinical decision support, integrating SHACL-based deterministic constraints with Bayesian probabilistic models. The primary goal is to validate the model and demonstrate the benefits of combining encoded clinical knowledge with probabilistic uncertainties in managing complex therapeutic scenarios. The framework was applied to recurrent urinary tract infections (UTIs) in postmenopausal patients, a clinical context marked by high frequency, treatment challenges, and potential conflicts among therapeutic guidelines. Realistic simulated case studies were developed, encompassing both simple clinical profiles and complex situations, such as patients with antibiotic resistance. Each profile was modelled in RDF/Turtle, enabling semantic representation of clinical features and therapeutic rules. The system automatically calculates success and failure probabilities for different therapeutic scenarios, dynamically adapting them based on follow-up data. This allows clinicians to assess not only the initial therapy choice (Case study no. 1) but also the potential addition of supplementary interventions during treatment (Case study no. 2). Results highlight that the proposed hybrid SHACL–Bayesian framework enables tightly coupled deterministic–probabilistic reasoning, where SHACL constraints define the admissible clinical decisions and Bayesian inference operates within this validated space. Compared to deterministic or probabilistic approaches, the combined framework more effectively handles uncertainty, guideline conflicts, and temporal updates. The scientific contribution lies in showing that this integration enhances decision support for recurrent UTIs in postmenopausal patients, providing clinically consistent, transparent, and adaptive therapeutic recommendations aligned with the patient’s evolving condition. Full article

The objective of this research is to enable the engineered manufacturing of sewn and embroidered e-textiles. It is achieved by conducting sewability assessments of commercially available conductive yarns and providing optimal sewing parameters to ensure electrical performance and mechanical suitability. Our approach includes yarn sampling, measurements, sewing experiments, statistical modeling, and performance tests of sewn sensors. We have scrutinized a range of conductive yarns with different formation mechanisms and electrical conductivities. Highly conductive, flexible, and fine count yarns are of particular interest in this proposed research. The physical properties of selected conductive yarns have been characterized and sewing experiments have been followed to evaluate the machine sewability of these conductive yarns under diverse sewing conditions. Using multiple logistic regressions and machine learning, these empirical observations are generalized and sewability models are established. Full article

To reduce mold costs in composite forming, multi-point tooling technology has been integrated into the hot diaphragm forming process. However, this approach still faces several challenges, including time-consuming prepreg layup, high energy consumption, and poor surface quality. This study proposes a heating pad-assisted multi-point thermoforming process: the prepreg is embedded in the thermal functional layers, placed on the lower mold, and formed via the downward movement of the upper mold to accomplish mold closure. Instead of the conventional rectangular array, this study adopted multi-point tooling with a hexagonal pin arrangement. Compared to traditional configurations, this hexagonal layout increases the punch support area by 9.8%, while its dense punch arrangement improves the accuracy of the molded curved surface. Taking a saddle-shaped surface as the target, a prototype part was fabricated. Subsequent analysis of the part’s surface quality identified three defects: dimples, fiber distortion, and ridge protrusions. The surface dimples were eliminated by adjusting the distance between the upper and lower molds. Notably, ridge protrusion is a defect unique to the hexagonal pin arrangement. We conducted a detailed analysis of its causes and solutions, finding that this defect arises from the combined effect of the pin arrangement and the saddle-shaped surface. Through a series of height compensation experiments, the maximum deviation at the ridges was reduced from 0.46 mm to approximately 0.35 mm, which is consistent with the deviation of defect-free areas. This work demonstrates that the multi-point hot-pressing process provides a potential, efficient, and low-cost method for manufacturing double-curvature composite components, whose effectiveness has been verified through the saddle-shaped case study. Full article

Instability in dump slopes frequently induces landslides, a process governed by complex factors. To investigate the impact of gradation composition on dump slope stability, four distinct gradations were designed, and large-scale laboratory triaxial tests were conducted to characterize their strength and deformation behaviors under varying confining pressures. Concurrently, numerical models of dump slopes with these four gradations were established using Particle Flow Code (PFC) to simulate rainfall infiltration processes. Through a comparative analysis of particle contact force chains, pore water pressure evolution, particle displacement under varying rainfall durations, and safety factors under natural and rainfall conditions, the mechanisms governing the influence of gradation composition on slope stability were elucidated from both macroscopic and microscopic perspectives. Results indicate the following: (1) Gradation composition significantly affects the strength and deformation characteristics of dump materials. Sample group 3 (with a fine-to-coarse particle ratio of 4:6) exhibited the highest strength among the four test samples, with peak deviatoric stresses of 610 kPa, 1075 kPa, and 1539 kPa under confining pressures of 200 kPa, 400 kPa, and 600 kPa, respectively. Its corresponding shear strength parameters were a cohesion of 38.45 kPa and an internal friction angle of 32.55°. In contrast, sample group 4 (fine-to-coarse ratio of 6:4) showed the lowest strength, with peak deviatoric stresses of 489 kPa, 840 kPa, and 1290 kPa under the same confining pressures, and shear strength parameters of c = 25.35 kPa and φ = 30.02°. (2) Gradation modulates contact forces and failure modes via a “skeleton-filling” mechanism. (3) Gradation plays a critical role in controlling pore water pressure evolution and the seepage characteristics of the dump slope model. Among the four designed gradations and their corresponding numerical models, Model 3 was characterized by the highest contact forces and the lowest pore water pressure. It exhibited the highest stability under both natural and rainfall conditions, with safety factors of 1.70 and 1.22, respectively. Conversely, Model 4 showed weak particle contact forces and high pore pressure, demonstrating the poorest stability. It yielded safety factors of only 1.25 and 1.02 under natural and rainfall-saturated conditions, indicating that it represents the least favorable gradation composition. These findings provide valuable references for the optimization of dumping processes and stability control in similar engineering projects. Full article

We quantify the transmission and absorption of 75–110 GHz radiation through ex vivo porcine skin. Millimeter waves are currently used in a range of technologies, including communication systems, fog-penetrating radar, and the detection of hidden weapons or drugs. They have also been proposed for use in non-lethal weaponry and, more recently, in targeted cancer therapies. Since pigs are often used as biological models for humans, determining how deeply millimeter waves penetrate a pig’s skin and influence the underlying tissues is essential for understanding their potential effects on humans. This experimental study aims to quantify that penetration and associated energy loss. The results show significant absorption in the skin and fat layer. Attenuation of over three orders of magnitude can be expected in penetration through a layer with a thickness of about 12 mm (−30 dB). The reflectance from the skin is similar at all frequencies. The values range from −10 to −20 dB, which probably depends on the texture of the skin. Therefore, most skin transfer loss is caused by absorption. Full article

This paper investigates bipartite synchronization in signed Lur’e networks influenced by semi-Markovian jump dynamics. A control strategy is proposed that adapts to mode-dependent switching by combining quantized feedback with selective pinning. The approach accommodates both leaderless and leader–following synchronization scenarios. For each switching mode, Lyapunov–Krasovskii-based analysis is employed to establish sufficient conditions using linear matrix inequalities (LMIs). The robustness and convergence of the method are confirmed through simulation studies, even in the presence of stochastic switching and limited communication precision. Full article

In the face of escalating energy demand, this research proposes a demand-side management (DSM) strategy that focuses on appliance-level load shifting in residential environments. The proposed approach utilizes detailed energy consumption forecasts that are generated by ensemble machine learning models, which predict usage at both whole-household and individual appliance levels. This granular forecasting enables the development of customized load-shifting schedules for controllable devices. These schedules are optimized using a metaheuristic genetic algorithm (GA) with the objectives of minimizing consumer energy costs and reducing peak demand. The iterative nature of GA allows for continuous fine-tuning, thereby adapting to dynamic energy market conditions. The implemented DSM technique yields significant results, successfully reducing the daily energy consumption cost for shiftable appliances. Overall, the proposed system decreases the per-day consumer electricity cost from 237 cents (without DSM) to 208 cents (with DSM), achieving a 12.23% cost saving. Furthermore, it effectively mitigates peak demand, reducing it from 3.4 kW to 1.2 kW, which represents a substantial 64.7% reduction. These promising outcomes demonstrate the potential for substantial consumer savings while concurrently enhancing the overall efficiency and reliability of the power grid. Full article

This study presents the design, fabrication, and performance evaluation of a solar dryer capsule cabinet equipped with a parabola reflector, developed to enhance drying efficiency through the reflection of sunlight onto both the upper and lower surfaces of the product. Conventional solar drying exposes only the upper surface, resulting in uneven heating and the need for manual turning. The proposed system integrates a parabolic reflector and IoT-based monitoring sensors (BH1750 light sensor and DHT22 temperature-humidity sensor) to optimize heat distribution and record real-time environmental parameters. Dry experiments were conducted using Citrus hystrix DC. (Makrut lime) peels under natural sunlight from 9:00 a.m. to 5:00 p.m. The moisture loss achieved with the proposed dryer (P-DSD) was 45.66%, compared with 6.79% for direct solar drying (DSD). The drying rate increased from 3.05 g h⁻¹ (DSD) to 20.50 g h⁻¹ (P-DSD), while the specific energy consumption (SEC) decreased from 3519.75 kWh kg⁻¹ to 523.67 kWh kg⁻¹, representing an 85.13% energy reduction. Economic analysis showed a system cost of $1384 and a return on investment of 30.0%. These results demonstrate that the proposed solar dryer capsule cabinet with a parabola reflector offers a low-cost, eco-friendly, and high-efficiency solution for drying agricultural and herbal products, significantly shortening the drying time and improving product quality. Full article

(1) Background: HTPLA FDM-printed cutting guides enable the low-cost, in-hospital production of patient-specific instruments. However, annealing, which is required for steam sterilization, may alter the dimensions of fit-critical fixation pin holes. (2) Methods: HTPLA cylindrical specimens (height 5 mm) were printed with fixed process parameters and vertical orientation. Inner diameter (1.6–5.0 mm) and wall thickness (2–6 mm) were varied using a two-factor Central Composite Design (n = 13). Following a two-stage annealing treatment (80 °C, 10 min; 100 °C, 50 min), post-annealing dimensions were measured and modeled using Response Surface Methodology. An illustrative verification was performed on additional specimens. (3) Results: Annealing induced a systematic decrease in inner diameter (−0.4 to −0.9 mm) and an increase in wall thickness (+0.1 to +0.4 mm). A reduced quadratic model accurately captured these trends within the investigated range, with small residuals observed during verification (≤0.1 mm). (4) Conclusions: The proposed local, geometry-driven model supports compensation in fixation pin-hole dimensions in annealed HTPLA cutting guides, improving dimensional predictability within a defined design and process window. Full article

Designing armor units that can withstand harsh marine environments while remaining cost-effective is a central challenge in modern breakwater engineering. This study introduces a newly designed artificial armor unit and evaluates its performance in comparison with established alternatives such as the accropode, core-loc, and conventional rock armor. The findings reveal that the new unit achieves a lower packing density, reducing the number of units required and thereby improving overall cost-effectiveness. Armor layers formed from the newly designed unit exhibited higher porosity than accropode but lower than core-loc, effectively avoiding the slender geometries that compromise durability. Structural analysis using STAAD.Pro confirmed that the new unit developed lower tensile stresses, with reductions of 15% compared to accropode and 35% compared to core-loc under flexure, torsion, and combined loading, demonstrating superior integrity. Hydraulic stability tests showed that the randomly placed newly designed units resisted failure at a stability number (N_s) of 1.4, lowering run-up by 50% and overtopping by 59%, while the uniformly placed newly designed units reached 1.5 without failure, with run-up and overtopping reductions of 30% and 37%, respectively. Collectively, these outcomes highlight the clear hydraulic and structural advantages of the new design over conventional systems, establishing it as a stronger and more resilient solution for breakwater protection. Full article

This computational study examined how variations in the seatback angle of two generic child restraint systems (CRSs) affect spinal loading in young occupants (1.5 YO and 3 YO) during frontal impacts, performed according to the specifications included in UNECE R129. CRS seatback angle dictates torso recline, which in turn influences head, chest, and spine kinematics and loading. While manufacturers typically recommend 30–45° for rear-facing CRSs and an upright position for forward-facing CRSs, little is known about the biomechanical implications of deviating from these guidelines. Using PIPER human body models representing a 1.5-year-old in a rear-facing CRS and a 3-year-old in a forward-facing CRS, simulations were performed under UN-R129 frontal impact conditions. The seatbacks were rotated 5° and 10° more upright or reclined relative to the nominal angle, with occupants restrained by a five-point harness and CRSs secured with ISOFIX, top tether, or three-point belt. The results showed that reclined configurations generally increased the predictions of spinal loading (forces and/or moments) given by the PIPER model, while nominal or more upright angles reduced loads, particularly in the lumbar spine of the 3-year-old model. Overall, the study highlights how computational tools can guide CRS design improvements to optimize spinal protection and enhance child safety beyond current regulatory requirements. Full article

Three-leg AC-DC Vienna rectifiers are susceptible to single open-switch faults, which make DC-link voltage ripple and make three-leg input AC currents distorted and unbalanced. Thus, this paper presents a quick identification method for single open-switch faults based on three-leg fault currents and output capacitors voltage difference. Fault-leg identification depended on zero-plateaus in the three-leg fault currents, whereas fault-side identification was dependent on reconstruction variables obtained through Clark transformation and phase shifting. In order to improve the reliability of the diagnosis system, the harmonic component of capacitor voltage difference is used to realize the missed diagnosis detection and adjust the time threshold automatically. This method requires no additional hardware and is easy to implement. Experimental results verify the effectiveness of this strategy. It is shown that the fault diagnosis method proposed in this paper has the advantages of fast diagnosis speed, high accuracy and good robustness. Full article

Accurate segmentation of ischemic stroke lesions from multimodal magnetic resonance imaging (MRI) is fundamental for quantitative assessment, treatment planning, and outcome prediction; yet, it remains challenging due to highly heterogeneous lesion morphology, low lesion–background contrast, and substantial variability across scanners and protocols. This work introduces Tri-UNetX-2D, a large-kernel and scale-aware 2D convolutional network with explicit boundary refinement for automated ischemic stroke lesion segmentation from DWI, ADC, and FLAIR MRI. The architecture is built on a compact U-shaped encoder–decoder backbone and integrates three key components: first, a Large-Kernel Inception (LKI) module that employs factorized depthwise separable convolutions and dilation to emulate very large receptive fields, enabling efficient long-range context modeling; second, a Scale-Aware Fusion (SAF) unit that learns adaptive weights to fuse encoder and decoder features, dynamically balancing coarse semantic context and fine structural detail; and third, a Boundary Refinement Head (BRH) that provides explicit contour supervision to sharpen lesion borders and reduce boundary error. Squeeze-and-Excitation (SE) attention is embedded within LKI and decoder stages to recalibrate channel responses and emphasize modality-relevant cues, such as DWI-dominant acute core and FLAIR-dominant subacute changes. On the ISLES 2022 multi-center benchmark, Tri-UNetX-2D improves Dice Similarity Coefficient from 0.78 to 0.86, reduces the 95th-percentile Hausdorff distance from 12.4 mm to 8.3 mm, and increases the lesion-wise F1-score from 0.71 to 0.81 compared with a plain 2D U-Net trained under identical conditions. These results demonstrate that the proposed framework achieves competitive performance with substantially lower complexity than typical 3D or ensemble-based models, highlighting its potential for scalable, clinically deployable stroke lesion segmentation. Full article

Rare earth elements are indispensable for a wide range of advanced technologies, which underscores their strategic importance. This study investigates the kinetics of extracting heavy rare earth elements—lutetium, thulium, yttrium, erbium, and dysprosium—from industrial phosphoric acid solutions generated during apatite processing. A comparative approach using both solvent and solid-phase extraction with di-(2-ethylhexyl)phosphoric acid (D2EHPA) was applied to elucidate the underlying mechanisms. Optimal solvent extraction parameters ($V_{aq}:V_{org}$ = 2:1, ${\phi }_{D2EHPA}$ = 0.2, 298 K, stirring at 350 rpm) achieved efficiencies exceeding 85%. Efficient solid-phase recovery was attained under mild conditions (298 K, m:V = 1:10, shaking at 100 opm). The rate-limiting steps were identified as diffusion-controlled for solvent extraction, governed primarily by agitation intensity, and as a mixed external–internal diffusion regime for solid-phase extraction. Calculated activation energies for each element corroborate these findings. Full article

Clarifying the mechanical properties and failure patterns of layered coal–rock combinations in coal-measure strata is critical to guiding hydraulic fracturing design in petroleum and mining engineering. This paper investigates the mechanical properties, failure patterns, and stress distributions of sandstone–coal–sandstone (SCS) and mudstone–coal–mudstone (MCM) combinations under different confining pressures and thickness ratios based on the 3D combined finite–discrete element method (3D FDEM). The results show that the mechanical strength of the SCS combination is higher than that of the MCM combination under the same conditions. As the thickness ratio increases, the overall peak stress and elastic modulus of the combination decrease gradually and eventually approach those of the pure coal. As confining pressure increases, the peak stress of layered coal–rock combinations rises gradually, plastic behaviors become increasingly prominent, and the failure mode of the mudstone layer transitions from tensile-dominated to shear-dominated. Under different thickness ratios and confining pressures, the coal layer in the combinations primarily develops shear-dominated cracks, whereas the sandstone layer mainly generates tensile-dominated cracks. An increase in confining pressure elevates the critical thickness ratio for sandstone layer failure in the SCS combination. Essentially, the changes in stress state caused by rock types, thickness ratios, and confining pressures are important reasons for the variations in the failure patterns of each layer in layered coal–rock combinations. The key findings of this paper are expected to provide theoretical guidance for the field design of petroleum and coal mine engineering. Full article

Reducing fuel costs, maximizing waste utilization, and improving energy efficiency are critical challenges in agricultural thermal processes. This study addresses these issues by developing and evaluating a mixed-fuel burner and furnace system for steaming mushroom substrate cubes using crude glycerol and recycled vegetable oil as low-cost alternative energy sources. The experimental investigation assessed boiler thermal efficiency, combustion efficiency, exhaust-gas composition, temperature distribution, steam generation, and combustion-gas dispersion within the furnace. In parallel, analytical modeling of pressure, temperature, and gas-flow behavior was performed to validate the experimental observations. Five fuel compositions were examined, including 100% used vegetable oil, 100% crude glycerol, and blended ratios of 50/50, 25/75, and 10/90 (glycerol/vegetable oil), with all tests conducted in accordance with DIN EN 203-1 standards. The results demonstrate that blending used vegetable oil with glycerol significantly improves flame stability, increases peak combustion temperatures, and suppresses incomplete-combustion byproducts compared with pure glycerol operation. Combustion efficiencies of 90–99% and boiler thermal efficiencies of 72–73% were achieved. Among the tested fuels, the optimal balance between combustion stability, efficiency, and cost was achieved with a 25% glycerol and 75% used vegetable oil mixture. Economic analysis revealed that the proposed mixed-fuel system offers superior viability compared with LPG, reducing annual fuel costs by approximately 50%, shortening steaming time by 2 h per batch, and achieving a payback period of only 3.26 months. These findings confirm the feasibility of the proposed waste-to-energy system for small- and medium-scale agricultural applications. To further enhance sustainability and renewable fuel utilization, future work should focus on improving air–fuel mixing for higher glycerol fractions, scaling the system for larger farms, and extending its application to other agricultural thermal processes. Full article

In this study, we employ impedance spectroscopy to investigate the internal mechanisms influencing the efficiency and performance of perovskite solar cells (PSCs). Using SCAPS-1D software (version 3.3.10), we simulate the FTO/ZnO/MASnI₃/NiOx/Au heterostructure to analyze the complex impedance (Z*) and electric modulus (M*). This approach allows us to differentiate between bulk material properties and interface phenomena, such as ion migration, charge transport, and recombination dynamics. Through Nyquist and Bode plots, we identify three distinct relaxation processes associated with charge migration, interface polarization, and charge injection/extraction at the electrodes. To achieve a more comprehensive understanding, we model the impedance and modulus spectra using an equivalent electrical circuit, which accurately reproduces the experimental data. Our analysis reveals that increasing the bias voltage extends the relaxation times for charge transport and interface polarization, highlighting a decline in performance under higher operational voltages. This performance drop is attributed to elevated resistive losses and enhanced recombination processes, which become more pronounced at higher fields. These findings emphasize the importance of optimizing both bulk material properties and interface engineering to mitigate losses and improve the overall performance and stability of PSCs. Full article