Search Results (7,143)

Motion-capture data provide high accuracy but are difficult to obtain, necessitating dataset augmentation. To our knowledge, no prior study has investigated few-shot generative models for motion-capture data that address both quality and diversity. We tackle the diversity loss that arises with extremely small datasets (n ≤ 10) by applying transfer learning and continual learning to retain the rich variability of a larger pretraining corpus. To assess quality, we introduce MFMMD (Motion Feature-Based Maximum Mean Discrepancy)—a metric well-suited for small samples—and evaluate diversity with the multimodality metric. Our method embeds an Elastic Weight Consolidation (EWC)-based regularization term in the generator’s loss and then fine-tunes the limited motion-capture set. We analyze how the strength of this term influences diversity and uncovers motion-specific characteristics, revealing behavior that differs from that observed in image-generation tasks. The experiments indicate that the transfer learning pipeline improves generative performance in low-data scenarios. Increasing the weight of the regularization term yields higher diversity in the synthesized motions, demonstrating a marked uplift in motion diversity. These findings suggest that the proposed approach can effectively augment small motion-capture datasets with greater variety, a capability expected to benefit applications that rely on diverse human-motion data across modern robotics, animation, and virtual reality. Full article

Metal–organic frameworks (MOFs) have characteristics such as a large specific surface area, distinct functional sites, and an adjustable pore size. However, the inherent low conductivity of MOFs significantly affects the charge transfer efficiency when they are used for electrocatalytic sensing. Combining MOFs with conductive materials can compensate for these deficiencies. For MOF/metal nanoparticle composites (e.g., composites with gold, silver, platinum, and bimetallic nanoparticles), the high electrical conductivity and catalytic activity of metal nanoparticles are utilized, and MOFs can inhibit the agglomeration of nanoparticles. MOF/carbon-based material composites integrate the high electrical conductivity and large specific surface area of carbon-based materials. MOF/conductive polymer composites offer good flexibility and tunability. MOF/multiple conductive material composites exhibit synergistic effects. Although MOF composites provide an ideal platform for electrocatalytic reactions, current research still suffers from several issues, including a lack of comparative studies, insufficient research on structure–property correlations, limited practical applications, and high synthesis costs. In the future, it is necessary to explore new synthetic pathways and seek; inexpensive alternative raw materials. Full article

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

The present study investigates dye-sensitized solar cells (DSSCs) incorporating natural extracts from the microalgae Spirulina and Chlorella as photosensitizers. TiO₂-based electrodes were prepared and immersed in methanolic algae extracts for 24 and 48 h. UV–Vis spectroscopy revealed absorption peaks near 400 nm and 650 nm, characteristic of chlorophyll. Electrochemical analyses, including photochronoamperometry and open-circuit potential, confirmed the photosensitivity and charge transfer capabilities of all systems. The cell sensitized with Chlorella after 48 h of immersion exhibited the highest energy conversion efficiency (0.0184% ± 0.0015), while Spirulina achieved 0.0105% ± 0.0349 after 24 h. Chlorella’s superior performance is attributed to its higher chlorophyll content and enhanced light absorption, facilitating more efficient electron injection and interaction with the TiO₂ surface. Although the efficiency remains lower than that of conventional silicon-based solar cells, the results highlight the potential of natural colorants as sustainable and low-cost alternatives for photovoltaic applications. Nonetheless, further, improvements are required, particularly in dye stability and anchorage, to improve device performance. This research reinforces the viability of natural photosensitizers in DSSC technology and supports continued efforts to optimize their application. Full article

This study proposes an innovative Thermodynamic Activity Controlled Homogeneous Charge Compression Ignition (TAC-HCCI) strategy for diesel–natural gas dual-fuel engines, aiming to achieve high thermal efficiency while maintaining low emissions. By employing numerical simulation methods, the effects of the intake pressure, intake temperature, EGR rate, intake valve closing timing, diesel injection timing, diesel injection pressure, and diesel injection quantity on engine combustion, energy distribution, and emission characteristics were systematically investigated. Through a comprehensive analysis of optimized operating conditions, a high-efficiency and low-emission TAC-HCCI combustion technology for dual-fuel engines was developed. The core mechanism of TAC-HCCI combustion control was elucidated through an analysis of the equivalence ratio and temperature distribution of the in-cylinder mixture. The results indicate that under the constraints of PCP ≤ 30 ± 1 MPa and RI ≤ 5 ± 0.5 MW/m², the TAC-HCCI technology achieves a gross indicated mean effective pressure (IMEPg) of 24.0 bar, a gross indicated thermal efficiency (ITEg) of up to 52.0%, and indicated specific NOx emissions (ISNOx) as low as 1.0 g/kW∙h. To achieve low combustion loss, reduced heat transfer loss, and high thermal efficiency, it is essential to ensure the complete combustion of the mixture while maintaining low combustion temperatures. Moreover, a reduced diesel injection quantity combined with a high injection pressure can effectively suppress NOx emissions. Full article

Background/Objectives: This study aims to design and evaluate transfer learning strategies that fine-tune multiple pre-trained convolutional neural network architectures based on their characteristics to improve the accuracy and generalizability of colorectal cancer histopathological image classification. Methods: The application of transfer learning with pre-trained models on specialized and multiple datasets is proposed, where the proposed models, CRCHistoDense, CRCHistoIncep, and CRCHistoXcep, are algorithmically fine-tuned at varying depths to improve the performance of colorectal cancer classification. These models were applied to datasets of 10,613 images from public and private repositories, external sources, and unseen data. To validate the models’ decision-making and improve transparency, we integrated Grad-CAM to provide visual explanations that influence classification decisions. Results and Conclusions: On average across all datasets, CRCHistoDense, CRCHistoIncep, and CRCHistoXcep achieved test accuracies of 99.34%, 99.48%, and 99.45%, respectively, highlighting the effectiveness of fine-tuning in improving classification performance and generalization. Statistical methods, including paired t-tests, ANOVA, and the Kruskal–Wallis test, confirmed significant improvements in the proposed methods’ performance, with p-values below 0.05. These findings demonstrate that fine-tuning based on the characteristics of CNN’s architecture enhances colorectal cancer classification in histopathology, thereby improving the diagnostic potential of deep learning models. Full article

A computational fluid dynamics (CFD) numerical simulation methodology was implemented to model transient heating processes in steel industry reheating furnaces, targeting combustion efficiency optimization and carbon emission reduction. The effects of oxygen concentration (O₂%) and different fuel types on the flow and heat transfer characteristics were investigated under both oxygen-enriched combustion and MILD oxy-fuel combustion. The results indicate that MILD oxy-fuel combustion promotes flue gas entrainment via high-velocity oxygen jets, leading to a substantial improvement in the uniformity of the furnace temperature field. The effect is most obvious at O₂% = 31%. MILD oxy-fuel combustion significantly reduces NOx emissions, achieving levels that are one to two orders of magnitude lower than those under oxygen-enriched combustion. Under MILD conditions, the oxygen mass fraction in flue gas remains below 0.001 when O₂% ≤ 81%, indicating effective dilution. In contrast, oxygen-enriched combustion leads to a sharp rise in flame temperature with an increasing oxygen concentration, resulting in a significant increase in NOx emissions. Elevating the oxygen concentration enhances both thermal efficiency and the energy-saving rate for both combustion modes; however, the rate of improvement diminishes when O₂% exceeds 51%. Based on these findings, MILD oxy-fuel combustion using mixed gas or natural gas is recommended for reheating furnaces operating at O₂% = 51–71%, while coke oven gas is not. Full article

As the core equipment for efficient wastewater treatment, the internal structure of microporous aeration bioreactors directly determines the mass transfer efficiency and treatment performance. Based on Computational Fluid Dynamics (CFD) technology, this study explores the optimization mechanism of a Spherical Grid-Structured on the internal flow field of the reactor through a 3D numerical simulation system, aiming to improve the aeration efficiency and resource utilization. This study used a combination of experimental and numerical simulations to compare and analyze different configurations of the Spherical Grid-Structure. The simulation results show that the optimal equilibrium of the flow field inside the reactor is achieved when the diameter of the grid sphere is 2980 mm: the average flow velocity is increased by 22%, the uniformity of the pressure distribution is improved by 25%, and the peak turbulent kinetic energy is increased by 30%. Based on the Kalman vortex street theory, the periodic vortex induced by the grid structure refines the bubble size to 50–80 microns, improves the oxygen transfer efficiency by 20%, increases the spatial distribution uniformity of bubbles by 35%, and significantly reduces the dead zone volume from 28% to 16.8%, which is a decrease of 40%. This study reveals the quantitative relationship between the structural parameters of the grid and the flow field characteristics through a pure numerical simulation, which provides a theoretical basis and quantifiable optimization scheme for the structural design of the microporous aeration bioreactor, which is of great significance in promoting the development of low-energy and high-efficiency wastewater treatment technology. Full article

In this study, we propose a bidirectional chemical sensor platform based on a reconfigurable ion-sensitive field-effect transistor (R-ISFET) architecture. The device incorporates Ni-silicide Schottky barrier source/drain (S/D) contacts, enabling ambipolar conduction and bidirectional turn-on behavior for both p-type and n-type configurations. Channel polarity is dynamically controlled via the program gate (PG), while the control gate (CG) suppresses leakage current, enhancing operational stability and energy efficiency. A dual-control-gate (DCG) structure enhances capacitive coupling, enabling sensitivity beyond the Nernst limit without external amplification. The extended-gate (EG) architecture physically separates the transistor and sensing regions, improving durability and long-term reliability. Electrical characteristics were evaluated through transfer and output curves, and carrier transport mechanisms were analyzed using band diagrams. Sensor performance—including sensitivity, hysteresis, and drift—was assessed under various pH conditions and external noise up to 5 V_pp (i.e., peak-to-peak voltage). The n-type configuration exhibited high mobility and fast response, while the p-type configuration demonstrated excellent noise immunity and low drift. Both modes showed consistent sensitivity trends, confirming the feasibility of complementary sensing. These results indicate that the proposed R-ISFET sensor enables selective mode switching for high sensitivity and robust operation, offering strong potential for next-generation biosensing and chemical detection. Full article

Internal fins are commonly utilized as a passive technique to enhance natural convection, but their efficiency depends on complex interplay between fin design, material properties, and convective strength. This study presents an extensive numerical analysis of buoyancy-driven flow in square cavities containing a single horizontal fin on the hot wall. Over 9000 simulations were conducted, methodically varying the Rayleigh number (Ra = 10 to 10⁵), Prandtl number (Pr = 0.1 to 10), and fin characteristics, such as length, vertical position, thickness, and the thermal conductivity ratio (up to 1000), to assess their overall impact on thermal efficiency. Thermal enhancements compared to scenarios without fins are quantified using local and average Nusselt numbers, as well as a Nusselt number ratio (NNR). The results reveal that, contrary to conventional beliefs, long fins positioned centrally can actually decrease heat transfer by up to 11.8% at high Ra and Pr due to the disruption of thermal plumes and diminished circulation. Conversely, shorter fins located near the cavity’s top and bottom wall edges can enhance the Nusselt numbers for the hot wall by up to 8.4%, thereby positively affecting the development of thermal boundary layers. A U-shaped Nusselt number distribution related to fin placement appears at Ra ≥ 10³, where edge-aligned fins consistently outperform those positioned mid-height. The benefits of high-conductivity fins become increasingly nonlinear at larger Ra, with advantages limited to designs that minimally disrupt core convective patterns. These findings challenge established notions regarding passive thermal enhancement and provide a predictive thermogeometric framework for designing enclosures. The results can be directly applied to passive cooling systems in electronics, battery packs, solar thermal collectors, and energy-efficient buildings, where optimizing heat transfer is vital without employing active control methods. Full article

Porous intermetallic compounds have the properties of porous materials as well as a combination of covalent and metallic bonds, and they exhibit high porosity, structural stability, and corrosion resistance. In this work, a porous TiNi₃ intermetallic compound was fabricated through reactive synthesis of elemental powders. Next, detailed studies of its phase composition and pore structure characteristics at different sintering temperatures, as well as its corrosion behavior against an alkaline environment, were carried out. The results show that the as-prepared porous TiNi₃ intermetallic compound has abundant pore structures, with an open porosity of 56.5%, which can be attributed to a combination of the bridging effects of initial powder particles and the Kirkendall effect occurring during the sintering process. In 1 M KOH solution, a higher positive corrosion potential (−0.979 V_SCE) and a lower corrosion current density (1.18 × 10⁻⁴ A∙cm⁻²) were exhibited by the porous TiNi₃ intermetallic compound, compared to the porous Ni, reducing the thermodynamic corrosion tendency and the corrosion rate. The corresponding corrosion process is controlled by the charge transfer process, and the increased charge transfer resistance value (713.9 Ω⋅cm²) of TiNi₃ makes it more difficult to charge-transfer than porous Ni (204.5 Ω⋅cm²), thus decreasing the rate of electrode reaction. The formation of a more stable passive film with the incorporation of Ti contributes to this improved corrosion resistance performance. Full article

Photocatalytic redox processes significantly contribute to shaping Earth’s surface environment. Semiconductor minerals exhibiting favorable photocatalytic properties are ubiquitous on rock and soil surfaces. However, the sunlight-responsive characteristics and functions of TiO₂, an excellent photocatalytic material, within natural systems remain incompletely understood, largely due to its wide bandgap limiting solar radiation absorption. This study analyzed surface coating samples, determining their elemental composition, distribution, and mineralogy. The analysis revealed enrichment of anatase TiO₂ and β-carotene. Informed by these observations, laboratory simulations were designed to investigate the synergistic effect of β-carotene on the sunlight-responsive behavior of anatase. Results demonstrate that β-carotene-sensitized anatase exhibited a 64.4% to 66.1% increase in photocurrent compared to pure anatase. β-carotene sensitization significantly enhanced anatase’s electrochemical activity, promoting rapid electron transfer. Furthermore, it improved interfacial properties and acted as a photosensitizer, boosting photo-response characteristics. The sensitized anatase displayed a distinct absorption peak within the 425–550 nm range, with visible light absorption increasing by approximately 17.75%. This study elucidates the synergistic mechanism enhancing the sunlight response between anatase and β-carotene in natural systems and its broader environmental implications, providing new insights for research on photocatalytic redox processes within Earth’s critical zone. Full article

Because artificially cemented granular (ACG) materials employ diverse combinations of aggregates and binders—including cemented soil, low-cement-content cemented sand and gravel (LCSG), and concrete—their stress–strain responses vary widely. In LCSG, the binder dosage is typically limited to 40–80 kg/m³ and the sand–gravel skeleton is often obtained directly from on-site or nearby excavation spoil, endowing the material with a markedly lower embodied carbon footprint and strong alignment with current low-carbon, green-construction objectives. Yet, such heterogeneity makes a single material-specific constitutive model inadequate for predicting the mechanical behavior of other ACG variants, thereby constraining broader applications in dam construction and foundation reinforcement. This study systematically summarizes and analyzes the stress–strain and volumetric strain–axial strain characteristics of ACG materials under conventional triaxial conditions. Generalized hyperbolic and parabolic equations are employed to describe these two families of curves, and closed-form expressions are proposed for key mechanical indices—peak strength, elastic modulus, and shear dilation behavior. Building on generalized plasticity theory, we derive the plastic flow direction vector, loading direction vector, and plastic modulus, and develop a concise, transferable elastoplastic model suitable for the full spectrum of ACG materials. Validation against triaxial data for rock-fill materials, LCSG, and cemented coal–gangue backfill shows that the model reproduces the stress and deformation paths of each material class with high accuracy. Quantitative evaluation of the peak values indicates that the proposed constitutive model predicts peak deviatoric stress with an error of 1.36% and peak volumetric strain with an error of 3.78%. The corresponding coefficients of determination R² between the predicted and measured values are 0.997 for peak stress and 0.987 for peak volumetric strain, demonstrating the excellent engineering accuracy of the proposed model. The results provide a unified theoretical basis for deploying ACG—particularly its low-cement, locally sourced variants—in low-carbon dam construction, foundation rehabilitation, and other sustainable civil engineering projects. Full article

High-performance hydrogen gas sensors have gained considerable interest for their crucial function in reducing H₂ explosion risk. Although MoS₂ has good potential for chemical sensing, its application in hydrogen detection at room temperature is limited by slow response and incomplete recovery. In this work, Pd-doped MoS₂ thin films are deposited on a Si substrate, forming Pd-doped MoS₂/Si heterojunctions via magnetron co-sputtering. The incorporation of Pd nanoparticles significantly enhances the catalytic activity for hydrogen adsorption and facilitates more efficient electron transfer. Owing to its distinct structural characteristics and sharp interface properties, the fabricated Pd-doped MoS₂/Si heterojunction device exhibits excellent H₂ sensing performance under room temperature conditions. The gas sensor device achieves an impressive sensing response of ~6.4 × 10³% under 10,000 ppm H₂ concentration, representing a 110% improvement compared to pristine MoS₂. Furthermore, the fabricated heterojunction device demonstrates rapid response and recovery times (24.6/12.2 s), excellent repeatability, strong humidity resistance, and a ppb-level detection limit. These results demonstrate the promising application prospects of Pd-doped MoS₂/Si heterojunctions in the development of advanced gas sensing devices. Full article

This study investigated into how different current input levels during cold metal transfer (CMT) welding affected the characteristics of the weld bead. For the current variation, three input values were taken: 80 A, 90 A, and 100 A. Weld beads fabricated from all three current inputs were compared by analysing their microstructure, microhardness, tensile strength, and residual stress. The microhardness of the weld bead decreased when the current parameter was increased from 80 A to 100 A. The average tensile strength increased from 80 A to 90 A. The lowest residual stress calculated was −135 MPa with 100 A current. Full article