Search Results (4,331)

RGBT tracking holds irreplaceable value in unmanned aerial vehicle (UAV) ground observation missions, effectively supporting scenarios such as nighttime monitoring and low-altitude reconnaissance. However, existing frameworks based on CNNs or Transformers face inherent trade-offs between interaction capabilities and computational efficiency. Furthermore, current methods perform poorly in challenging scenarios involving target scale variations and rapid motion from UAV perspectives. To address these issues, this paper proposes a novel multimodal interaction and fusion Mamba network (MIFMNet), which achieves fundamental innovations relative to existing RGB-T fusion trackers and recent Mamba-based tracking methods. Different from existing RGB-T trackers that rely on CNN’s local convolution or Transformer’s quadratic-complexity self-attention for cross-modal fusion, MIFMNet departs from these architectures and designs modality-adaptive interaction mechanisms based on Mamba, fully leveraging the complementary information while resolving the efficiency-accuracy trade-off. Specifically, this paper designs the scale differential enhanced Mamba (SDEM), which expands the receptive field through multiscale parallel convolutions while amplifying complementary information via differential strategies to enhance feature responses to scale-varying objects. Furthermore, we propose flow-guided multilayer interaction Mamba (FMIM), which integrates inter-frame motion information into scanning prediction. This enables the network to adaptively adjust interaction priorities between shallow texture and high-level semantic features based on motion intensity, mitigating early information forgetting and enhancing robustness in dynamic scenes. Extensive experiments on four major benchmarks demonstrate that MIFMNet achieves state-of-the-art performance on precision and success rate, particularly excelling in UAV scenarios involving occlusion, scale variations, and rapid motion. Simultaneously, it achieves an inference speed of 35.3 FPS, enabling efficient deployment on resource-constrained platforms, thereby providing robust support for UAV applications of RGBT tracking. Full article

We propose stateful order-preserving encryption (SOPE), a novel framework designed to realize human-centric data security and privacy, the fundamental values of the Fifth Industrial Revolution. Conventional order-preserving encryption supports efficient queries in cloud databases but fundamentally leaks plaintext distributions, leaving data vulnerable to inference attacks. To mitigate this vulnerability while maintaining query efficiency, SOPE introduces a partition-based dynamic density adjustment mechanism under an honest-but-curious threat model. This mechanism offsets density imbalances between partitions in real time by inserting decoy ciphertexts, thereby limiting the leakage scope to the order of data while obscuring frequency information. Our analysis and empirical evaluations demonstrate that SOPE’s ciphertexts consistently approach a uniform distribution by adaptively compensating for the underlying plaintext distribution through decoy insertion. While the continuous insertion of decoy ciphertexts inevitably incurs additional storage overhead (controlled by a tunable parameter $\lambda$), our evaluations demonstrate practical performance. By striking an optimal balance between efficiency and human privacy rights, SOPE provides a trustworthy infrastructure for secure data utilization. Full article

Sewerage systems are a main element of a city’s infrastructure. Roughness coefficients are fundamental parameters for sewage system operation. The intermittent nature of the flow leads to the appearance of deposits that become an integral part of the sewerage systems. Deposited material not only leads to the loss of hydraulic capacity and decreases the concentration of dissolved oxygen (which is found in direct relation to all quality parameters), but it also results in more transported particles being intercepted. In the design calculations, the roughness coefficient is estimated rather than calculated. It has been demonstrated that the estimation of stress within and above roughness elements improves the predictive capability for the concentration of suspended sediment. In this study, we focused on a local evaluation of the roughness coefficient when the flow velocity is below the minimum self-cleansing velocity. Some authors consider the selection of the most reliable method for estimating bed shear stress to be the main challenge. Other authors have suggested that all possible methods should be applied simultaneously to achieve a reliable bed shear stress estimation, knowing that the roughness coefficient can be determined through the shear boundary stress. We calculate the local roughness coefficient in Manning’s equation using a laboratory model, considering clear water flowing over a solid boundary with consolidated deposits, represented by artificial roughness elements (calibrated hemispheres). The European standard EN 752:2017 specifies a minimum average cross-sectional velocity of 0.7 m/s for pipe self-cleansing. This study established the range of possible roughness coefficient values when the minimum velocity design criterion is not met. The second criterion was to consider acceptable a sediment deposit occupying between 1% and 2% of the collector diameter. Velocity distributions around artificial roughness and statistical parameters of the turbulent flow were obtained using a PIV system. Five methods were implemented and the range of roughness coefficient values varied between 0.007 and 0.023. This variation is closely related to sewer performance. We selected the dissipation method as the primary reference for this study, as it is most closely aligned with the underlying physics of flow over roughness elements. This approach allows for robust validation by correlating multiple characteristic mechanisms of the turbulent cascade. Full article

The pore pressure coefficient B, defined as the change in pore pressure per unit increment of confining pressure under undrained conditions, is a fundamental parameter in soil mechanics. It characterizes the coupling between soil skeleton deformation and pore water pressure and plays a critical role in establishing the effective stress framework for frozen soils. Existing studies mainly focus on unfrozen soils, while the temperature sensitivity and stress-path dependence of B in frozen soils undergoing phase transition remain insufficiently understood. To address this gap, this study conducts temperature-controlled triaxial tests and constant strain-rate loading tests to investigate the evolution of B in frozen sandy silt over a temperature range of −11 °C to −2 °C under different stress histories. The results show that: (1) post-loading B-values at −5 °C to −8 °C are significantly higher than those at −2 °C and −10 °C, by 6.5% and 8.2%, respectively; (2) within the framework of Gassmann’s equation, a theoretical model incorporating the soil freezing characteristic curve and the coupled effects of ice–water phase transition and soil skeleton deformation is developed to explain the temperature-dependent behavior of unfrozen water and B; and (3) a predictive model incorporating a temperature correction factor is proposed, which accurately captures the variation trend of B in frozen sandy silt. This study elucidates the evolution mechanism of the pore pressure coefficient under multi-field coupling conditions and provides a theoretical basis for frost heave assessment and constitutive modeling in cold-region engineering. Full article

The heat release rate in internal combustion engines obtained from in-cylinder pressure data is a fundamental method to analyse the combustion characteristics of engines. As the measured in-cylinder pressure is lower than the pressure in the absence of heat loss to the walls, the methodology typically leads to the apparent rate of heat release as the heat loss to the cylinder walls cannot be segregated. Heat loss can then be inferred by reference to the chemical fuel energy expected to be released by the fuel. Typically, in engine thermodynamic analysis, the lower heating value is used to determine the energy released by the fuel. However, in this article, we argue that when detailed comparison with validated combustion modelling was done, it was concluded that the higher heating value is the more appropriate calorific value. In this research, the analysis of heat release rate and its determination using the first law of thermodynamics with constant ratio of specific heats γ and also varying γ is discussed. It was noted that the use of the “3rd term” (term due to the dγ/dϑ) in the heat release rate is advisable as it gives a more reasonable heat loss even in the compression stroke. Full article

Agricultural waste management is a strategic priority for reducing greenhouse gas emissions and transitioning to a circular bioeconomy. The thermochemical conversion of residual biomass into biochar offers a dual solution: waste recovery and the production of high-value functional materials. This narrative review summarizes the relationships among the composition of agricultural biomass, the conversion process parameters, and the structural properties of biochar, highlighting advanced modification strategies: controlled pyrolysis, physical and chemical activation, surface functionalization, and hybrid composite formation. Fundamental adsorption mechanisms, redox processes, and photocatalytic behavior are discussed, with a focus on applications in water treatment (heavy metals, dyes, emerging contaminants). The article proposes an integrative structure–property–performance framework and explores emerging concepts such as sequential use and post-use valorization of saturated biochar. Challenges related to reproducibility, industrial scaling, life cycle assessment, and carbon accounting are analyzed. Finally, a SWOT analysis is presented that highlights the potential of modified biochar as a strategic material in the circular economy. Full article

Inclusion and preference relations are fundamental comparison tools in intuitionistic fuzzy set (IFS) theory and play an important role in decision analysis under uncertainty. In IFS representations, the hesitation degree reflects information that is not captured by membership and non-membership values alone. This study investigates the structural relationship between hesitation and the inclusion and preference relations of IFSs. A proposed interpretation of membership and non-membership degrees is employed to provide a geometric perspective on hesitation. Within this framework, analytical relations between hesitation inequalities and preference conditions are derived. In particular, it is shown that the hesitation inequality constitutes a necessary condition for preference, whereas inclusion relations remain compatible with a wider range of hesitation configurations. The theoretical observations are illustrated using electoral datasets from the 2002 South Korean presidential election and the 2000 United States presidential election in Florida. Regional vote shares are transformed into intuitionistic fuzzy representations to analyze the distribution of hesitation across regions. The examples demonstrate how hesitation may influence the stability of preference relations while inclusion relations remain structurally preserved. Full article

With the increasing consumer demand for high-quality lamb, crossbreeding has become a key technology for improving the production performance and meat quality of sheep. To evaluate the meat quality advantages and characteristics of Suffolk (SFK) and Hu sheep (HH) and their F₁ crossbreds (SH), thirty-six 3-month-old male lambs of SFK (n = 12), HH (n = 12), and SH (n = 12) were selected and raised in individual pens under the same nutritional and management conditions. After standardized feeding until 6 months of age, the Longissimus dorsi muscle was collected to determine meat quality traits, amino acid and fatty acid profiles, and volatile flavor compounds. The results indicated that the L*, a* and b* values of the SH group were significantly lower than those of the parental breeds (p < 0.05), with tenderness being intermediate between the two parent breeds. Notably, drip loss and cooking loss were significantly lower in the SH group (p < 0.05), indicating superior water-holding capacity. In terms of amino acid profiles, the contents of non-essential amino acids (NEAAs) and sweet-tasting amino acids in the SH group were significantly higher than those of the parent breeds (p < 0.05), with the overall profile meeting the FAO/WHO ideal protein pattern. Analysis of fatty acid profiles revealed that the SH group had significantly lower total saturated fatty acids (SFAs) (p < 0.05) and significantly higher levels of functional fatty acids (such as CLA), resulting in a significantly higher UFAs (unsaturated fatty acids)/SFAs (saturated fatty acids) ratio (p < 0.05) and superior nutritional value of fat. Furthermore, 32 volatile flavor compounds were detected in the SH group; among them, key aroma-active compounds such as isoamyl formate, 3-methyl-1-butanol, and acetoin were significantly higher than in the parental breeds (p < 0.05), contributing to a unique flavor profile. Consequently, this study systematically reveals the advantages of Suffolk × Hu F₁ crossbreds in terms of meat quality, nutritional value, and flavor characteristics, providing fundamental data for the optimization of crossbreeding systems, breeding selection, and the quality improvement of sheep meat products. Full article

The development of cementitious materials with multifunctional performance is increasingly important to address environmental demands and durability requirements in modern infrastructure. This study investigates calcium sulfoaluminate (CSA) cement partially substituted with blast furnace slag (BFS), fly ash (FA), and TiO₂ nanoparticles, aiming to combine sustainability with photocatalytic self-cleaning functionality. Phase analysis by X-ray diffraction confirmed the formation of characteristic CSA hydration products, including ettringite, ye’elimite, anhydrite, and calcite, indicating that partial substitution did not disrupt the primary hydration mechanisms. Microstructural observations revealed that the incorporation of BFS, FA, and TiO₂ induced noticeable morphological changes, with increased porosity and microstructural heterogeneity at higher replacement levels. Mechanical testing showed that moderate BFS contents of 5 to 10 wt% enhanced compressive strength in reference mixtures, while systems containing TiO₂ exhibited slightly lower strength values and increased dispersion, particularly at elevated slag contents. The photocatalytic performance, evaluated through Rhodamine B degradation under solar irradiation, demonstrated a marked improvement for TiO₂-containing samples, reaching degradation efficiencies of up to 80%, in contrast to negligible activity in unmodified systems. These results confirm that the combined use of industrial by-products and photocatalytic nanoparticles in CSA-based matrices represents a viable strategy for producing sustainable cementitious materials with added environmental functionality, without compromising fundamental structural performance. Full article

This study presents an integrated simulation framework that combines agent-based transport modeling with probabilistic load-flow analysis to quantify power system loading of long-haul heavy-duty electrification. The approach is applied to a case study considering fully electrified road freight in the Skåne region in Sweden, using high-resolution transport demand data and the actual power grid model used by the grid owner in the study area. The synthetic freight population covers the full long-haul truck segment intersecting Skåne. Both public en-route fast charging and end-of-trip depot charging are considered. The analysis reveals two fundamentally different charging demand profiles: a heavily fluctuating profile for public en-route charging, accounting on average for 82% of the total daily charging energy, and a stable profile for end-of-trip depot charging, covering on average the remaining 18%. The latter is achieved through a Linear Programming (LP) optimization model that flattens the load by scheduling charging across depot stay windows. These profiles serve as inputs to a probabilistic load-flow simulation that computes loading distributions for substation transformers. The simulation results show that in 4 of the 43 primary substations studied, the maximum transformer loading exceeds 100% following the introduction of truck charging, with peak loading at the most affected substation rising from 99% to 159%. This stress is primarily caused by the public charging demand, which peaks from late morning to noon, aligning with the early stages of logistics operations. However, there is no clear correlation between the magnitude of the truck charging load and the impact on transformer loading, since this is also highly dependent on local grid conditions. These findings highlight the value of integrated transport-energy simulations for planning resilient infrastructure and guiding targeted grid reinforcements. Full article

Lithium-ion batteries (LiBs) are fundamental to modern energy systems, particularly in electric vehicle (EV) applications, due to their high energy density, long cycle life, and low self-discharge characteristics. Accurate State-of-Charge (SoC) estimation is essential for ensuring reliable performance, efficient energy usage, and the safety of Battery Management Systems (BMSs). However, the nonlinear and time-varying characteristics of LiBs, along with the difficulty in directly measuring internal states, pose significant challenges for parameter identification and SoC estimation. This study presents an advanced approach based on the Weighted Mean of Vectors optimization algorithm to simultaneously identify the unknown parameters of an extended Thevenin Equivalent Circuit Model (ECM) and estimate the SoC. Unlike previous methods that use static parameters for specific battery modes, the proposed technique accounts for dynamic changes during both charging and discharging operations. The algorithm demonstrates superior adaptability by continuously adjusting model parameters to reflect real-time battery behavior under varying operational conditions. The algorithm also models the relationship between SoC and open-circuit voltage (Voc) using data collected from real lithium-ion cells tested under a controlled load profile in the laboratory. This experimental validation ensures the practical applicability and robustness of the proposed methodology. The simulation results confirm the effectiveness and precision of the proposed approach, showing excellent agreement between measured and estimated values, with minimal errors in both voltage and SoC prediction. The enhanced accuracy achieved through this dynamic parameter identification framework represents a significant advancement in battery state estimation technology. Full article

Rigid-body chain following on piecewise analytic paths is a fundamental subroutine in motion planning and multibody simulation. The problem is nontrivial when only the leader trajectory of the first node is available: enforcing fixed inter-node distances reduces to circle–curve intersection, which is generally multi-valued and becomes particularly challenging near non-smooth junctions. We present a Dichotomy Geometric Path Search (DGPS) framework that converts each constraint into a one-dimensional root-finding task and resolves the branch selection through no-backtracking ordering: at every time step, the admissible solution for the current node is the nearest feasible root in the past relative to its immediately preceding node. DGPS combines backward bracketing with bisection, achieving robust convergence. Compared with the inverse Jacobian method, which maps end-effector velocities to joint velocities via explicit inversion, the proposed approach avoids Jacobian inversion and globally coupled nonlinear solves. We further characterize the local structure of the zero set and establish monotonicity/uniqueness conditions that justify stable root selection across piecewise junctions. Extensive tests on representative piecewise trajectories (line–arc–line, polylines with corners, piecewise sinusoids, and time reparameterization) show that DGPS enforces distance constraints to near machine precision, produces interpretable speed/acceleration transients around non-smooth events, and exhibits computational costs consistent with iteration difficulty. The results support DGPS as a general, efficient solver requiring only the prescribed leader trajectory. Full article

Ischemia–reperfusion injury (IRI) is a prevalent pathological process in clinical settings characterized by complex pathogenesis involving the interplay of oxidative stress, inflammation, mitochondrial dysfunction, and diverse cell death pathways. Fundamentally, IRI manifests as a complication arising from reperfusion therapies aimed at restoring blood flow following ischemia. Despite the existence of various therapeutic strategies, the development of effective interventions for IRI remains a significant challenge. Rutin, a low-molecular-weight flavonoid glycoside ubiquitously present in vegetables, fruits, and herbal medicines, exhibits promising therapeutic potential due to its pleiotropic biological activities, including antioxidant, anti-inflammatory, and cytoprotective effects against cell death. This review systematically elucidates the molecular mechanisms underlying the protective effects of rutin against IRI and synthesizes evidence from preclinical studies regarding its diverse modes of action. However, the clinical application of rutin is currently hampered by its relatively low bioavailability. Future research should prioritize the development of innovative pharmaceutical formulations to enhance its bioavailability, thereby fully unlocking its clinical translational value. Full article

Mechanical pretreatment techniques are essential for overcoming lignocellulosic biomass recalcitrance in emerging biorefineries. This review critically synthesizes advances from 2020 to 2025 across fundamental mechanisms, hybrid technologies, energy efficiency, Life Cycle Assessment, and industrial scalability. The analysis reveals that effective pretreatment targets supramolecular modification—defect generation in cellulose crystallites and the creation of reactive sites—beyond simple particle size reduction. Impact–shear regimes prove most effective for fibrous materials. Hybrid approaches are examined: mechanocatalysis enables solvent-free depolymerization, while mechanoenzymatic technologies achieve hydrolysis without bulk water, though enzyme denaturation under mechanical stress remains unresolved. Energy consumption is the primary upscaling barrier, with Life Cycle Assessment identifying electricity use as the dominant environmental hotspot and emphasizing burden per unit of final product as the critical metric. Technology Readiness Level assessment provides a strategic framework: continuous extruders and mills are industrially mature for bulk applications, while high-intensity batch devices are suited for high-value coproducts. A research agenda prioritizing mechanistic understanding, hybrid process engineering, feedstock diversification, and embedded sustainability assessment is proposed. Full article

Operative vaginal delivery (OVD) via vacuum extraction is a fundamental component of modern obstetric management, yet it carries specific risks of failure and maternal–fetal complications, such as cup detachment, cephalohematoma, and intracranial hemorrhage. The success and safety of the procedure rely heavily on the correct application of the vacuum cup over the “flexion point” of the fetal head. Traditional identification of this landmark via digital examination is often hindered by caput succedaneum and cranial molding, leading to high rates of diagnostic error, particularly in dystocic labor, due to fetal head malpositions and malpresentation. Intrapartum ultrasound (ITU) has demonstrated superior accuracy compared to clinical examination in assessing fetal head position and station and internal rotation. This expert commentary and technical proposal analyzes the current literature regarding vacuum extraction application and failures, focusing on the predictive value of ITU parameters (e.g., Angle of Progression, Midline Angle, Head-Symphysis Distance) and the impact of ITU on cup placement and delivery outcomes. Furthermore, we propose a novel technique: the “Ultrasound Flexion Point” (UFP). This method utilizes translabial ultrasound to identify the specific intersection of the fetal midline and the biparietal diameter as an objective sonographic proxy for the classical flexion point. By providing spatial orientation guidance immediately before the procedure, this technique aims to guide the operator in aligning the cup’s notch with the sonographically identified target zone, using the midline angle as orientation reference, thereby potentially minimizing paramedian or deflexing applications and reducing the incidence of vacuum detachment and associated neonatal trauma. This expert commentary and technical proposal synthesizes current evidence and proposes a protocol requiring prospective validation through randomized controlled trials. Full article