Search Results (157)

Motivated by the increasing security requirements of next-generation satellite-terrestrial communication systems and the emergence of Open Radio Access Network (O-RAN) architectures, this paper presents a secrecy analysis of a novel reconfigurable intelligent surface (RIS)-assisted mixed free-space optical (FSO) and radio frequency (RF) satellite downlink transmission system within an O-RAN-enabled non-terrestrial network (NTN) framework. The inherent broadcast nature of RF transmissions presents significant eavesdropping risks, which serves as the primary impetus for this study. We analyze the combined effects of imperfect channel state information (CSI) and random link blockage within such integrated networks. The impact of discrete phase shift constraints at the RIS is also investigated. Closed-form expressions are derived for three key performance metrics: connection outage probability (COP), secrecy outage probability (SOP), and the probability of positive secrecy capacity (PPSC). Through high signal-to-noise ratio (SNR) asymptotic analysis, corresponding asymptotic expressions are obtained, and all analytical results are validated via extensive Monte Carlo simulations. Our findings demonstrate that: (i) Link blockage probability and channel estimation accuracy jointly govern the secrecy performance floor. (ii) Increasing the number of RIS elements enhances physical-layer security by driving both the COP and SOP toward their theoretical lower bounds. (iii) Improving channel estimation accuracy diminishes the eavesdropper’s channel advantage and improves the overall system security. These results offer valuable insights for designing secure mixed FSO/RF satellite-terrestrial systems within O-RAN-enabled NTN architectures that effectively balance connectivity and confidentiality. Full article

To address the problems of the Electromagnetic Wave Propagation Algorithm (EMWPA)—insufficient initial-population coverage, an imbalance between exploration and exploitation, and a tendency to fall into local optima—in high-dimensional complex optimization problems, this paper proposes a boosted electromagnetic wave propagation optimization algorithm, BEMWPA. First, a cubic chaotic map is introduced in the population-initialization stage to enhance the uniformity of the initial-solution distribution and the search-space coverage. Second, nonlinear phase modulation is applied to the electric- and magnetic-field driving terms, and a differentiated probabilistic switching mechanism is constructed to improve the dynamic coordination between global exploration and local exploitation. Furthermore, a Beta-distribution opposition-based learning strategy is introduced to enhance the algorithm’s ability to escape local optima by generating high-quality opposite candidate solutions. To verify the effectiveness of the proposed algorithm, systematic comparative experiments are conducted on the CEC2017 benchmark function set, and BEMWPA is combined with rapidly-exploring random tree (RRT) and applied to path planning of a welding manipulator in complex multi-workpiece scenarios. For a three-dimensional welding scenario containing 12 workpieces, 12 closed weld seams, and multiple obstacle constraints, BEMWPA-RRT reduces the initial inter-seam transfer path length of RRT from 586.00 mm to 479.11 mm, representing a relative reduction of 18.24%, and the complete end-effector path length is reduced from 2974.00 mm to 2867.11 mm, representing a relative reduction of 3.59%. Meanwhile, the optimized transfer path length is only 1.59 mm longer than the obstacle-free ideal transfer length of 477.52 mm, indicating that the proposed method can approach the geometric lower bound of this scenario while satisfying the obstacle-avoidance constraints. Kinematic verification on a seven-degrees-of-freedom welding manipulator further shows that the optimized Cartesian-space path can be converted into a continuously executable joint-space trajectory, providing an effective method for offline welding path planning of complex multi-workpiece tasks. Full article

The Damiao titanomagnetite deposit on the northern margin of the North China Craton is a typical Fe-Ti-P polymetallic ore with significant deep resource potential. However, the mineralogical factors controlling its beneficiation remain poorly quantified. This study integrates multi-element analysis, chemical phase analysis, XRD, EPMA, and MLA to systematically characterize the ore’s chemistry, mineralogy, element deportment, grain size, dissemination, and liberation. Results show that Fe (25.81% TFe), Ti (6.50% TiO₂), and P (0.95% P₂O₅) are the main valuables. Fe is mainly in magnetite (59.53%), Ti in ilmenite (48.90%) and rutile (33.89%), and P almost entirely in fluorapatite. Magnetite, ilmenite, apatite, and pyrite are coarse-grained and achieve >80% free + rich intergrowths at 60% passing −0.074 mm, while rutile is fine and poorly liberated, representing the key titanium bottleneck. Silicate-bound iron (28.07% of Fe) causes irreversible loss; Ca-gangue (>20%) and chlorite slimes interfere with flotation. A staged flowsheet—primary grinding, magnetic separation, regrinding of rough concentrate, desulfurization, and sequential flotation—is proposed. This work provides a mineralogical basis for process optimization and offers references for similar deposits. Full article

This paper presents FedGAT, a federated graph attention network for joint user association and inter-remote radio head (RRH) interference mitigation in cloud radio access networks (C-RAN). Centralized optimization requires global channel state information (CSI) at the baseband unit (BBU) pool, which adds fronthaul overhead and exposes user data. Existing federated learning schemes use flat local models that do not represent the interference graph, which lowers performance in heterogeneous multi-cell settings. In FedGAT, each RRH builds a local interference graph from its own CSI and trains a GATv2 model by local Adam gradient steps. Only the parameter increments are sent to the BBU pool, which combines them by weighted FedAvg without exchanging raw CSI. We formulate the joint user association and power allocation problem as a mixed-integer non-convex program and derive a graph neural network (GNN)-based continuous relaxation suitable for distributed training. A non-asymptotic convergence bound is obtained for non-identically distributed local interference graphs, showing that the optimality gap grows with the local step count and a measure of graph heterogeneity. Under the 3GPP Urban Macrocell channel model, FedGAT increases the steady-state weighted sum-rate by 18.7% over a federated multilayer perceptron baseline and by 49.2% over a centralized Graph Attention Network version 2 (GATv2) model at equal training budgets, while keeping raw CSI local. These margins are averaged over ten Monte Carlo channel realizations and reported with their standard deviations, and the fronthaul benefit of FedGAT refers to privacy and CSI-free inference after training rather than training-phase traffic. Full article

KRAS G12C, long considered an undruggable oncogenic driver, has become one of the most consequential therapeutic targets in non-small cell lung cancer (NSCLC). The discovery of a cryptic binding pocket accessible in the GDP-bound state enabled covalent inhibitors—sotorasib and adagrasib—that have received regulatory approval for previously treated KRAS G12C-mutant NSCLC, with sotorasib demonstrating PFS and OS superiority over docetaxel in CodeBreaK 200 and adagrasib showing meaningful intracranial activity and a progression-free survival benefit over docetaxel in KRYSTAL-12. Yet response durability is limited by on-target switch-II pocket mutations, upstream RTK and SHP2-mediated bypass signaling, downstream MAPK and PI3K-AKT reactivation, phenotypic plasticity, and adverse modulation by co-occurring STK11, KEAP1, and TP53 alterations. Next-generation covalent inhibitors (divarasib, glecirasib, olomorasib), tri-complex RAS(ON) inhibitors (RMC-6291), pan-KRAS agents, and rationally designed combinations with EGFR, SHP2, SOS1, and PD-1 inhibitors are repositioning KRAS-directed therapy toward earlier lines of treatment. This review integrates the structural, signaling, and clinical biology of KRAS G12C with contemporary trial and real-world evidence to examine the emerging case for first-line KRAS G12C inhibition in genomically defined subsets of NSCLC. First-line use nonetheless remains investigational; platinum-based chemoimmunotherapy remains the standard of care outside of clinical trials, and a frontline indication will require confirmation from randomized phase III trials. Full article

Binary actuator systems are widely used in industrial and agricultural automation because of their simple structure and low implementation cost. However, sensing delay and measurement noise can cause repeated triggering when threshold conditions are continuously evaluated using delayed feedback signals. This paper proposes a delay-aware switching framework for binary actuator systems operating under sensing uncertainty. The proposed framework structures the control cycle into sequential actuation, protected waiting, and idle phases. During the protected waiting phase, switching-condition evaluation is temporarily suspended to prevent redundant actuator commands caused by stale measurements. In addition, an adaptive supervisory mechanism updates the actuation duration and waiting interval using simple performance indicators obtained directly from sensor measurements, without requiring plant-model identification. The timing properties of the proposed switching sequence are analyzed, showing that the inter-event time is bounded below by a positive constant, thereby ensuring Zeno-free behavior. Simulation results demonstrate that the proposed framework eliminates repeated triggering and reduces oscillation amplitude under delayed and noisy measurements. Experimental validation using a Raspberry Pi-based thermal chamber further confirms bounded and regular switching behavior under artificially added measurement noise. Full article

The evolution of regenerative medicine has repositioned the extracellular matrix (ECM) from a passive structural scaffold to a dynamic signaling hub that dictates host immunity and tissue remodeling. A critical driver of this bioactivity is the matrix-bound nanovesicle (MBV), a distinct subclass of extracellular vesicles (EVs) physically embedded within collagen fibers. Unlike fluid-phase EVs, MBVs exhibit unique release kinetics triggered by matrix degradation and possess tissue-specific molecular signatures that dictate their therapeutic potential. This review evaluates the biogenesis, isolation, and cellular tropism of MBVs, highlighting the macrophage as a central mediator of their immunomodulatory effects. We propose a “precision medicine” framework for matching MBV tissue sources—ranging from pro-angiogenic small intestinal submucosa to anti-angiogenic cartilage—to the specific pathological requirements of the target injury. Furthermore, we discuss post-harvest engineering strategies, including surface functionalization via click chemistry and exogenous cargo loading, to enhance MBV targeting and potency. Finally, we address the translational hurdles of protocol standardization and pharmacokinetic characterization required to transition MBVs into a scalable, cell-free platform for regenerative therapy. Full article

Pedestrian detection is a fundamental component of Advanced Driver Assistance Systems (ADAS) and plays a key role in collision avoidance and the safety of vulnerable road users. This paper presents a structured review of pedestrian detection methodologies developed between 2000 and 2025, spanning classical vision techniques and modern deep learning architectures. We organize the review into two phases. First, we examine classical methods, including Histogram of Oriented Gradients (HOG)+Support Vector Machine (SVM), Viola–Jones, Deformable Part Models, and Integral Channel Features, which established the conceptual foundations of the field. Then, we analyze state-of-the-art deep learning architectures, categorized by detector stage (one-stage vs. two-stage), localization strategy (anchor-based vs. anchor-free), feature extraction paradigm (Convolutional Neural Network (CNN)-based vs. transformer-based), output representation (bounding box vs. instance segmentation), and computational profile (lightweight vs. heavyweight). Several design principles introduced by classical methods remain visible in modern architectures, indicating that they were not fully superseded. The review also examines publicly available benchmark datasets and compares the strengths and limitations of camera-, Light Detection And Ranging (LiDAR)-, radar-, and multi-sensor-fusion-based systems for ADAS deployment. We close by identifying six open problems for the field: adversarial robustness, real-time inference under embedded constraints, detection under adverse weather, dataset bias and demographic fairness, the deployment of Bird’s-Eye View (BEV) and unified perception on automotive hardware, and explainability for safety-critical use. Full article

Wild rice (Zizania palustris L.; WR) is a nutrient-dense whole grain, naturally rich in phenolic acids with established antioxidant and health-promoting properties. This study investigated the effect of cooking and in vitro gastrointestinal digestion on the phenolic composition, bioaccessibility, and antioxidant capacity of commercial WR samples. Free phenolics predominated over bound forms in both raw and cooked samples, indicating that WR is a rich source of extractable phenolics. Cooking reduced total phenolics by 17–23% across WR varieties. Among individual compounds, p-hydroxybenzoic acid (up to 58.3%) and caffeic acid (up to 56.5%) exhibited the greatest bioaccessibility indices, while ferulic acid remained largely insoluble. In vitro gastrointestinal digestion facilitated the release of some bound phenolics, particularly during the intestinal phase, resulting in a total phenolic content (TPC) bioaccessibility of up to 22.61%. However, antioxidant activities, as measured by DPPH and ABTS assays, declined compared to cooked samples (5.53% and 9.34%, respectively). These findings reveal dynamic changes in phenolic composition and bioaccessibility during cooking and digestion, with the intestinal phase being pivotal for releasing certain bound phenolics. This underscores WR’s promise as a functional food source for phenolics, while highlighting the importance of evaluating food bioactives under physiologically relevant conditions. Full article

Adsorption therapies in hemodialysis have emerged as an innovative approach for removing protein-bound uremic toxins (PBUTs). The present work focuses on the enhancement of the adsorption capacity of hemodialysis membranes through the incorporation of Metal–Organic Frameworks (MOFs). The removal capacity of PBUT p-cresyl sulfate by cellulose acetate (CA)/silica (SiO₂)/MOF mixed matrix membranes was investigated with two types of MOFs, UiO-66 which synthesis and characterization has been previously reported, and UiO-66-NH₂. The UiO-66-NH₂ MOFs were synthesized and characterized by infrared spectroscopy, X-ray diffraction, nitrogen adsorption–desorption equilibrium at −196 °C, and thermogravimetry analysis. Both mixed matrix membranes were synthesized by coupling the phase inversion technique with the sol–gel method and with casting solutions incorporating the MOF dispersions. The two membrane types of MOFs were characterized in terms of hydraulic permeability, molecular weight cut-off, and rejection coefficients to pCS and bovine serum albumin (BSA). The mixed matrix membranes CA/SiO₂/UiO-66-NH₂ exhibited lower permeability and molecular weight cut-off when compared to the CA/SiO₂/UiO-66 ones. In permeation tests simulating a hemodialysis session with a feed solution of 100 ppm pCS and 35 g/L BSA, it is shown the improved performance of MOFs membranes as the rejection coefficients of free pCS is 0.2% for the CA22/SiO₂/UiO-66 membrane with 1.5% of MOF and 2.6% for the CA22/SiO₂/UiO-66-NH₂ membrane with 2% of MOF. The capacity of these MOF membranes in removing pCS bound to BSA was addressed through the development of a new methodology to quantify the pCS free and bound to BSA. The CA22/SiO₂/UiO-66 membrane with 1.5% of MOF has a removal capacity of 99.8% and the CA22/SiO₂/UiO-66-NH₂ membrane with 2% of MOF 95.9%. Based on these results, it is concluded that the mixed matrix membranes CA22/SiO₂/UiO-66 and CA22/SiO₂/UiO-66-NH₂ are promising candidates for PBUTs removal in hemodialysis. Full article

To address the poor solubility, instability, and low oral bioavailability of quercetin (Q), Q-loaded nanoparticles (Q@DDZ) were fabricated using deamidated zein peptide (DDZ) via a pH-driven method. As a food-grade hydrophilic colloid, DDZ effectively improves the colloidal stability of the delivery system. Deamidation increased hydrophilic amino acids and surface negative charge. DDZ bound Q via static quenching with a higher binding constant (K_a = 2.25 × 10³ L/mol) and more binding sites (n = 1.7561) than zein, along with stronger hydrogen bonding and hydrophobic interactions. Q@DDZ exhibited higher encapsulation efficiency (45.36–87.32%) and loading capacity (1.82–12.27%) than Q@zein, with a smaller particle size and better dispersibility. At 50.0 μg/mL Q, Q@DDZ showed 41.06% (DPPH) and 46.62% (ABTS) higher scavenging rates than free Q. It displayed excellent stability under acidic, high ionic strength, and thermal conditions (80 °C, 180 min). In simulated digestion, Q@DDZ delayed Q release in the oral and gastric phases and prolonged intestinal release, which indicated potentially improved bioavailability. This study provides mechanistic insights into deamidation-modified plant protein delivery systems for hydrophobic bioactives, offering new perspectives for the development of functional biopolymer gel materials. Full article

This study investigated the dynamic changes and bioaccessibility of free and bound phenolics in rice bean (Vigna umbellata) during simulated gastrointestinal digestion. A total of 34 phenolic compounds were identified and quantified across oral, gastric, and intestinal phases by UPLC-MS/MS detected. Gastric digestion was identified as the critical stage for phenolic release, with multiple flavonoids increasing 2–3-fold, including rutin (205%), isoquercitrin (226%), and procyanidin B1 (134%). In contrast, in the intestinal phase, flavonoids including procyanidin B1, epicatechin, and quercetin became undetectable after extensive degradation, while phenolic acids such as p-hydroxybenzoic acid (157%) and trans-cinnamic acid (200%) accumulated gradually. Phloroglucinol showed a progressive accumulation increased continuously during digestion (10 to 36 mg/kg DW). Most bound phenolics remained remarkably stable, with over 85% retained throughout upper gastrointestinal transit, except for bound p-coumaric acid and phloroglucinol, which were gradually released. Notably, 3,4-dihydroxyphenylacetic acid was detected only in the bound form across all phases. These findings reveal the dual fates of rice bean phenolics, especially the bound fraction, and underscore the importance of their release and transformation during digestion when evaluating the bioactivity of rice bean polyphenols. Full article

Currently, there is no existing methodology within commercially available software packages for accurately simulating the gradual evaporation of the aqueous phase in batch thermomechanical dehydration processes involving highly stable water-hydrocarbon emulsions. This limitation constitutes a significant obstacle to the widespread industrial implementation of a promising approach for liquid hydrocarbon waste disposal, which relies on the evaporation of the aqueous phase under intensive stirring conditions, ultimately producing a hydrocarbon product with residual water content. In this study, the widely used Aspen HYSYS V12 software was employed to model these processes. The primary objective was to identify the most appropriate thermodynamic model accurately describing vapor–liquid phase transitions during the boiling of the aqueous phase in highly stable water–hydrocarbon emulsions, with water content ranging from 2 to 60% by weight. The modeling of the gradual boiling process was divided into several sequential stages, each representing a single evaporation step. The initial feedstock temperature was set at 90 °C, with subsequent stages involving temperature increments of 5 °C until the residual water content in the product fell below 0.5% by weight. Four thermodynamic models were evaluated for their ability to predict phase equilibria: Peng–Robinson, Wilson, UNIQUAC, and NRTL. It was observed that the Peng–Robinson model poorly describes the dehydration process, as it predicts water evaporation only at 100 °C, which contradicts experimental evidence indicating that evaporation occurs over a broader temperature range. The Wilson model significantly overestimates boiling points, reaching values up to 290 °C. Although the UNIQUAC model accurately reflects the process at higher water contents, it results in elevated energy consumption, necessitating substantial superheating of the feedstock up to 220 °C. The NRTL model provided the best correlation (among studied thermodynamic models) with experimental data, providing an average relative deviation of 3.68% and effectively capturing the two-stage evaporation mechanism: initial removal of free water at 100–110 °C, followed by bound moisture evaporation at temperatures approaching 160 °C. Vaporization rates were also examined across all models. The Peng–Robinson approach predicted the highest vaporization peaks but was the least representative of actual process conditions. Notably, in the NRTL model, the peak vaporization rates were 1.9 to 2.7 times higher than those estimated using the UNIQUAC and Wilson models. This parameter is critical for the optimal selection and design of subsequent condensation equipment. Based on these findings, the NRTL thermodynamic model is recommended for the industrial-scale implementation of thermomechanical dehydration processes involving heavy hydrocarbon feedstocks, given its accuracy in modeling phase transitions and the temperature-dependent vapor generation rates derived from sequential equilibrium flash calculations. Full article

The temporal dynamics of nitrogen (N) fractions and ammonia (NH₃) volatilization were investigated over a 56-day storage period using a laboratory-scale pig slurry pit simulator. A detailed N mass balance, encompassing total N (TN), total ammonium N (TAN), organic N, and nitrate N (NO₃⁻-N) fractions, yielded a N mass recovery of 96.5%, despite uncertainties associated with discrete emission measurements, with a TN reduction of 28.3 g vessel⁻¹ closely matched by cumulative NH₃-N emissions of 27.3 g. The NH₃ emission profile exhibited a distinct two-phase pattern. During Phase I (days 1–28), emissions remained stable at 16.7–19.5 g m⁻² d⁻¹, accounting for approximately 58% of total cumulative NH₃-N loss (518.6 g m⁻²), consistent with zero-order kinetics. Phase II (days 29–56) was characterized by first-order exponential decay (k = 0.0293 d⁻¹, R² = 0.982), coinciding with progressive TAN depletion. Measured emission rates were strongly correlated with theoretical free ammonia N (FAN) concentrations derived from pH and temperature (R² = 0.74), confirming that theoretical FAN provides a useful upper bound for emission potential, although the actual gaseous flux is restricted by mass-transfer limitations at the slurry–air interface. These results demonstrate that continuous pH and temperature monitoring provides a practical basis for tracking emission dynamics and informing the timing of mitigation interventions, particularly during the high-flux initial storage phase. Full article

Glyphosate is a highly polar herbicide, the reliable molecular recognition of which is complicated by co-occurring structural analogues, metabolites, and derivatives in real-world samples. Rather than reporting new aptamer discovery, this study establishes a standardized, solution-phase isothermal titration calorimetry (ITC) workflow to thermodynamically reassess two literature-reported glyphosate DNA aptamers, Seq03 and Seq05, under matched buffer composition and instrument settings. After verification of baseline stability and evaluation of heat-of-dilution contributions, ligand-to-aptamer titrations yielded apparent dissociation constants of approximately 8.14 μM for Seq03 and 40.2 μM for Seq05, enabling affinity-based prioritization of these reported candidates within the tested concentration window. To define an application-relevant selectivity boundary, we further constructed a counter-screen panel restricted to glyphosate-related chemicals, including structural analogues, metabolites, and derivatives, and evaluated all candidates using an identical ITC protocol with explicit background handling. None of the counter-screen compounds produced binding-consistent, saturable isotherms after integration and control-based interpretation; instead, their responses remained close to background heat and were therefore operationally classified as having no detectable binding under the tested conditions, including a reverse-titration format check with Glufosinate-N-acetyl. Collectively, these results position ITC as a label-free, platform-independent validation step for small-molecule aptamer benchmarking prior to analytical translation, while also highlighting that the present conclusions are bounded by the tested PBS-based conditions and the sensitivity window of the current ITC configuration. Full article