Search Results (576)

With the deepening integration of 5G-Advanced (5G-A) technology into smart manufacturing, the large-scale deployment of dynamic terminals—such as mobile robots and automated guided vehicles (AGVs)—within industrial private networks introduces complex, time-varying penetration and path losses. This significantly degrades the accuracy of conventional signal quality and capacity estimation methods, which were primarily designed for static terminal scenarios, thereby posing substantial challenges to coverage and deployment planning of industrial 5G access points, with downstream implications for power capacity dimensioning. To address this problem, this paper proposes a coverage-driven base station deployment optimization method formulated as a combinatorial optimization problem. The study constructs a signal strength assessment and network throughput calculation model tailored for dynamic industrial environments. This model captures the joint impact of terminal mobility and environmental obstacles on signal propagation, thereby enabling more reliable estimation of coverage performance and power consumption. Furthermore, by formulating the base station placement optimization as a combinatorial optimization problem, and by introducing mechanisms for equivalent transformation of the objective function and data preprocessing, the proposed method substantially reduces redundant computations during heuristic iterations. Simulation results verify that, compared with conventional static planning approaches, the proposed scheme enhances both the accuracy and computational efficiency of deployment planning while maintaining coverage quality. This work provides a theoretical foundation and a practical methodology for deploying reliable and energy-efficient industrial 5G-A private networks. Full article

Co-channel interference (CCI) remains a critical factor affecting link reliability in narrowband wireless systems, especially in scenarios with intensive frequency reuse, overlapping coverage, and dense terminal access. Existing interference detection methods are either computationally simple but insufficiently sensitive to short-term spectral variations, or highly accurate but dependent on labeled data and nontrivial inference resources. To address this issue, this paper proposes a lightweight CCI detection method in the FFT domain based on spectrum-jump analysis. The proposed method does not rely on absolute power growth as the primary interference indicator. Instead, it tracks the temporal inconsistency of dominant spectral-bin indices across consecutive FFT frames and converts recurrent peak-bin migration into an interference decision through a short-window counting mechanism. The method is computationally efficient, interpretable, and suitable for real-time deployment without offline model training. SDR-based measurements are combined with controlled repeated experiments to assess detector performance under varying signal-to-noise ratio (SNR), interference-to-signal ratio (ISR), carrier-frequency offset (CFO), multi-peak ambiguity, and two-path Rayleigh fading conditions. On the measured SDR record, the proposed method captures all interference-positive windows after the marked onset, while the controlled SNR/ISR experiments yield an overall detection probability of 96.0% over 250 CCI trials with no false alarms over 250 normal trials. ROC and precision–recall analyses further show that the selected threshold lies within a broad validation plateau. The results also reveal clear applicability boundaries: when the CFO approaches zero, when the interference is very weak, or when multiple stationary peaks have nearly equal power, dominant-bin migration may be weak or ambiguous. Therefore, the proposed approach is a low-complexity online detector for CCI cases that induce observable FFT-bin instability, and it can also serve as a front-end trigger for more advanced interference analysis modules. Full article

Gold nanospheres (AuNPs) and gold nanoflowers (AuNFs) are widely used as platforms for DNA aptamer functionalization, while conjugation behavior and colloidal tolerance remain important factors affecting subsequent sensing-oriented optimization. In this study, 82-nt thiolated DNA aptamer constructs bearing either 3′-SH or 5′-SH terminal modification were immobilized onto citrate-stabilized AuNPs and AuNFs under matched stepwise salt-aging conditions. Apparent nanoparticle-associated DNA output was estimated by Qubit-based measurement of unbound ssDNA in the supernatant and expressed as mass-based loading output (ng). Under the tested stock-dispersion conditions, AuNP samples showed higher apparent conjugation output than AuNF samples. Specifically, the apparent conjugation yields for AuNPs were 80.65 ± 1.64% (3′-SH) and 84.76 ± 1.98% (5′-SH), whereas those for AuNFs were 66.64 ± 3.36% (3′-SH) and 73.65 ± 1.36% (5′-SH). The corresponding apparent DNA loading outputs were 2329.7 ± 47.4 ng and 2448.7 ± 57.1 ng for AuNPs, and 1925.1 ± 97.0 ng and 2127.4 ± 39.3 ng for AuNFs. DLS size increases and zeta potential shifts toward more negative values were consistent with the formation of a DNA-associated interfacial layer, while TEM images supported morphology retention after conjugation. A qualitative visual salt-challenge assessment indicated that aptamer-functionalized nanoparticles displayed improved resistance to salt-induced aggregation relative to bare particles under the tested conditions. Because the commercially supplied AuNP and AuNF dispersions were not normalized to identical particle number or accessible surface area, the reported values should be interpreted as comparative apparent outputs rather than intrinsic loading capacities. Within this scope, the present study provides a convenient preliminary materials-level evaluation of thiolated aptamer conjugation behavior and may support future glyphosate aptasensor optimization. Full article

In this paper, we propose an enhanced preamble scheme for the Physical Random Access Channel (PRACH) applied to low-altitude integrated sensing and communication (ISAC) systems, aiming to expand the sensing capability of traditional mobile networks with PRACH frames based on ZC sequences. To enable the network to possess target-sensing capability before successful terminal access, we transform PRACH from a mere initial access channel into an ISAC system capable of supporting high-speed terminal access and user equipment sensing by introducing a time–frequency orthogonal block structure and Orthogonal Cover Codes (OCCs). Specifically, we first derive the Cramér–Rao lower bound (CRLB) for estimating the distance and velocity of user equipment using OCC-ZC sequences, and we establish the evaluation metric for communications and named detection probabilities. Then, the ISAC problem is formulated as a multi-objective optimization function. Since the multi-objective optimization problem is non-convex, we propose the NSAG-II algorithm to solve it, simultaneously improving the estimation accuracy of distance and velocity in the sensing aspect and the detection probability in the communication aspect. Full article

Addressing the challenges of privacy leakage, fragmented data silos, and high computational overhead in traditional ciphertext-policy attribute-based encryption (CP-ABE) for medical data sharing, this paper proposes an improved CP-ABE framework with outsourced decryption, integrated with consortium blockchain and the InterPlanetary File System (IPFS). The framework introduces a medical-scenario-adapted CP-ABE architecture based on a lightweight FAME design, optimizing attribute key generation and transformation key design to accommodate resource-constrained medical terminals. A hybrid encryption system is employed, combining symmetric encryption for high-efficiency processing of large medical data and CP-ABE for fine-grained access control of symmetric keys. To reduce user computational burden, a proxy-assisted secure decryption architecture is implemented, where the proxy server handles most decryption tasks while ensuring resistance to malicious proxy behavior. Furthermore, the framework provides rigorous formal security verification, achieving IND-CPA security and resilience against collusion and malicious proxy attacks. Comprehensive performance evaluations demonstrate significant improvements in key generation, encryption, and decryption efficiency, offering a better balance between security and efficiency for practical medical data sharing applications. Full article

Cannabis sativa is a multipurpose dioecious species whose crop performance is governed by sex expression. Although sex is genetically determined by an X/Y chromosome system, plants can develop flowers of the opposite sex through sex reversion, commonly induced by manipulating endogenous hormone levels using plant growth regulators (PGRs). Here, we evaluated the effectiveness of PGRs that promote or inhibit major hormone pathways implicated in plant sex expression. Male and female clones from two accessions were treated with foliar applications of nine PGRs and four combinatory treatments to assess sex- and genotype-specific responses. Floral biomass and the proportion of each sex were recorded at harvest to assess treatment effectiveness. Ethylene emerged as the primary regulator of chemically modulated sex reversion in C. sativa, with its inhibition by silver thiosulfate inducing strong female-to-male reversion and its promotion by ethephon inducing equally strong male-to-female reversion in the inflorescences. Gibberellin promotion on its own resulted in female-to-male reversion at the axial nodes only, while its inhibition showed no reciprocal effects. The combination of silver thiosulfate and gibberellic acid resulted in the most complete female-to-male reversion, and all sex-reverted flowers were fertile. Together, the results indicated that flowers at axial nodes and at the terminal ends of inflorescences are under different hormonal control. Cytokinins, auxins, and jasmonates were found to exert minimal influence on sex reversion. All treatments exhibited pleiotropic effects, particularly gibberellic acid and paclobutrazol, which altered resource allocation, shifting biomass away from and towards floral tissue, respectively. These findings advance our understanding of the hormonal regulation of sex expression in C. sativa and identify optimized approaches for its manipulation. Full article

Partial agricultural production loads exhibit significant temporality. The concentrated access of temporary loads can easily trigger operational challenges in distribution networks, such as heavy overload, terminal voltage violations, and increased network losses. To address these issues, this paper proposes a coordinated dispatch strategy for multiple flexible resources to cope with temporary loads. First, combining the operational characteristics of motor-pumped well loads, a refined model for motor-pumped well loads is constructed to fully exploit their regulation potential as flexible loads. Second, considering the supporting role of mobile energy storage systems (MESS) for heavy overload distribution networks, a spatiotemporal dispatch model for MESS is established. Then, aiming to minimize the total system operating cost, an economic dispatch model coordinating multiple flexible resources, including MESS, distributed generators (DG), and flexible loads, is developed. The original non-convex problem is transformed into a mixed-integer second-order cone programming problem using Second-Order Cone Relaxation (SOCR) method for efficient solution. Finally, the effectiveness of the proposed strategy is verified on an improved IEEE 33-bus system. Full article

Surface Acoustic Wave (SAW) technology, long central to analog signal processing and RF filtering, is undergoing a major renewal. Driven by advances that decouple SAWs from traditional piezoelectric materials and fixed-function devices, the field is gaining unprecedented control over acoustic, optical, and electronic interactions at the micro and nanoscale. This review synthesizes these developments across four fronts: new physical mechanisms for SAW manipulation, emerging material platforms, ranging from thin films to 2D systems, along with reconfigurable device architectures and circuits, and the expanding landscape of applications they enable. Optical methods are reshaping how SAWs are generated and controlled, bypassing the limits of conventional electromechanical coupling. Coherent optical excitation of high-Q SAW cavities via Brillouin-like optomechanical interactions now grants access to modes in non-piezoelectric substrates such as diamond and silicon, while on-chip SAW excitation in photonic waveguides through backward stimulated Brillouin scattering opens new integrated sensing routes. In parallel, magneto-acoustic experiments have revealed nonreciprocal SAW diffraction from resonant scattering in magnetoelastic gratings. On the device side, ZnO thin-film transistors integrated on LiNbO₃ exploit acoustoelectric coupling to realize voltage-tunable phase shifters; UHF Z-shaped delay lines achieve high sensitivity in a compact footprint; and parametric synthesis of wideband, multi-stage lattice filters targets 5G-class performance. Atomistic simulations show that SAW propagation in 2D MXene films can be engineered via surface terminations, while aerosol jet printing and SAW-assisted particle patterning provide agile, cleanroom-light fabrication of microfluidic and magnetic components. These advances enable applications ranging from hybrid quantum systems and quantum links to lab-on-a-chip particle control, SBS-based and UHF sensing, reconfigurable RF front-ends, and soft robotic actuators based on patterned magnetic composites. At the same time, optical techniques offer non-contact probes of dissipation, and MXenes and other emerging materials open new regimes of acoustic control. Conclusively, they are transforming SAW technology into a versatile, programmable platform for mediating complex interactions in next-generation electronic, photonic, and quantum systems. Full article

The rational design of supported Lewis acid catalysts is frequently impeded by an incomplete understanding of how the support’s synthetic history governs its intrinsic acidity and catalytic efficacy. Herein, we elucidate the structure–property–performance relationship linking the aging dynamics of a boehmite precursor to the activity of the resultant chlorinated alumina (Al₂O₃–Cl) catalyst in n-butane isomerization. Using n-butane as the probe feedstock, we investigated how alumina supports with distinct physicochemical properties regulate the performance of Al₂O₃–Cl catalysts for n-butane isomerization. By systematically adjusting the aging parameters (stirring rate, temperature, and time), we reveal that the structural evolution of the alumina support transitions from initial particle aggregation to Ostwald ripening and surface reconstruction. A decisive structure–performance correlation is identified: precursor synthesis conditions govern both the population and accessibility of specific surface hydroxyls (notably Type II terminal OH groups), which act as anchoring sites for the generation of active Lewis acid centers upon chlorination. Optimal aging parameters (300 rpm, 90 °C, 6 h) promote the formation of a hierarchical pore architecture with a maximized density of accessible hydroxyls, thereby affording enhanced Lewis acidity and superior isomerization activity. This work provides a fundamental framework for tailoring solid acid catalysts by precisely engineering the precursor architecture. Full article

The increasing deployment of autonomous vehicles in port logistics requires safety assessment methods that remain valid in mixed traffic environments. This study evaluates the safety of mixed automated guided vehicle (AGV) and human-driven vehicle (HDV) traffic in a seaport terminal connected to an external urban road network. A microscopic traffic model was developed in AIMSUN Next to represent gate areas, internal roads, storage-yard access, berth interfaces, and external container-truck traffic. HDVs were modeled using a Gipps-based car-following model, whereas AGVs were represented through an Adaptive Cruise Control framework. Vehicle trajectories were exported to the Surrogate Safety Assessment Model (SSAM), where Time-to-Collision (TTC) and Post-Encroachment Time (PET) were used to detect and classify conflicts. Six staged fleet-composition scenarios were evaluated in 36 simulation runs, ranging from fully human-driven operation to full automation. Total conflicts decreased from 89 in the fully human-driven scenario to 43 in the fully automated scenario (−51.7%), while rear-end conflicts decreased from 70 to 30 (−57.1%). Crossing conflicts remained relatively stable across scenarios. At the same time, mean TTC decreased from 0.80 to 0.24 s and mean PET from 1.57 to 0.38 s, indicating tighter but more coordinated interactions under automated control. These results show that automation improves longitudinal safety performance in port traffic, but also that conventional TTC and PET thresholds calibrated for human-driven traffic may not be directly applicable to automated port operations. Automation-sensitive surrogate safety criteria are therefore needed for seaport mixed-traffic evaluation. Full article

Integrated sensing and communications (ISAC) requires tight coordination between spatial signal design and multiple-access strategies to balance communication throughput and sensing accuracy under shared spectral and hardware constraints. However, existing ISAC frameworks with rate-splitting multiple access (RSMA) typically rely on fixed antenna arrays and decoupled optimization, which fundamentally limit their ability to adapt to fast channel variations and dynamic sensing requirements. This paper introduces a fluid antenna-enabled RSMA-assisted ISAC architecture, in which movable antenna ports are exploited as a new spatial degree of freedom to enhance adaptability in both communication and sensing operations. Fluid antenna systems (FAS) are deployed at both the base station and user terminals, allowing dynamic port selection that reshapes the effective channel and sensing beampattern in real time. We formulate a joint sum-rate maximization problem subject to explicit sensing-quality constraints, capturing the coupled impact of antenna port selection, RSMA rate allocation, and multi-beam transmit design. The proposed framework maximizes the communication sum-rate while ensuring that the sensing functionality satisfies a predefined sensing quality constraint. This constraint-based ISAC formulation guarantees that sufficient sensing power is directed toward the target while optimizing communication performance. The resulting optimization involves strongly coupled discrete and continuous decision variables, rendering conventional optimization methods ineffective. To address this challenge, a hierarchical deep reinforcement learning (HDRL) framework is developed, where an upper-layer deep Q-network (DQN) determines discrete antenna port selection and a lower-layer twin delayed deep deterministic policy gradient (TD3) algorithm optimizes continuous beamforming and rate-splitting parameters. Numerical results demonstrate that the proposed approach significantly improves system performance, achieving higher communication sum-rate while satisfying sensing requirements under dynamic propagation conditions. Full article

Acetohydroxy acid synthase (AHAS) are key targets for herbicide resistance breeding in Brassica crops, yet the evolutionary origin and functional role of AHAS2 genes in Brassica napus (AACC) and B. carinata (BBCC) remain poorly understood. Here, we investigated the distribution, ancestry, and agronomic trait associations of AHAS2 across 227 accessions representing six Brassica species. Bra.AHAS2 was amplified in 21 of 42 B. rapa (AA) accessions, and Bol.AHAS2 in 10 of 15 B. oleracea (CC) accessions. In B. napus, BnaA.AHAS2 and BnaC.AHAS2 were amplified in 73/131 and 30/131 accessions, respectively, with 19 accessions showing amplification of both homologs. All seven B. carinata accessions amplified BcaC.AHAS2. No AHAS2 homologs were amplified in three B. nigra (BB) or 29 B. juncea (AABB) accessions. Phylogenetic and gene structure analyses revealed that BnaA.AHAS2 (in B. napus) originated from Bra.AHAS2 of B. rapa, whereas BnaC.AHAS2 (in B. napus) and BcaC.AHAS2 (in B. carinata) derived from Bol.AHAS2 of B. oleracea. Association analysis showed the amplification of BnaA.AHAS2 or BnaC.AHAS2 was not associated with tribenuron-methyl resistance. However, amplification of BnaA.AHAS2 was significantly associated with reduced plant height, branching height, silique number on the terminal raceme, seed yield per plant, and thousand-seed weight in B. napus. Furthermore, haplotypes of BnaA.AHAS2 (BnaA05g03070D) were significantly associated with eicosenoic acid content, oleic acid content, flowering time, and cadmium translocation. Collectively, these findings resolve the diploid progenitor origins of AHAS2 in Brassica allotetraploids and reveal previously unrecognized associations of AHAS2 with agronomic and stress-related traits, offering valuable insights for molecular breeding in oilseed Brassica crops. Full article

Lignin, a complex and heterogeneous polymer, poses significant challenges for effective thermal valorization due to its broad molecular weight distribution and structural diversity. This study systematically compares the effect of lignin’s molecular weight on product distribution under pyrolysis and Ru/C-catalyzed depolymerization conditions. Fractionated lignin samples with distinct molecular weights were subjected to identical thermal and catalytic conversion pathways. Pyrolysis results indicate that, compared with low-molecular-weight (low-MW) lignin, high-molecular-weight (high-MW) lignin more readily generates phenolic compounds, with the relative content of guaiacol increasing by nearly twofold. In contrast, products derived from low-MW lignin contain a higher abundance of unsaturated structures, such as 4-allyl-2,6-dimethoxyphenol, suggesting that side chain cleavage and rearrangement reactions are more pronounced. In contrast, Ru/C-catalyzed depolymerization exhibits a stronger molecular-weight-dependent selectivity, where low-MW lignin is more readily converted into carboxylic acids due to enhanced accessibility of terminal functional groups and reduced structural condensation. This comparative analysis demonstrates that lignin’s molecular weight plays a process-dependent role in governing product distribution, providing guidance for tailored lignin valorization strategies. Full article

Pseudomonas aeruginosa causes severe healthcare-associated infections, yet no vaccine has been licenced. To circumvent the antigenic variability of classical surface antigens, we evaluated LolB—an essential outer-membrane lipoprotein whose periplasmic orientation favours T-cell-dominant mechanisms with potential antibody access via outer-membrane vesicles (OMVs) or bacteriolysis. An integrative in silico pipeline combined multi-strain conservation (20 isolates), epitope discovery (B- and T-cell), safety filters, physicochemical profiling, de novo/refined 3D modelling, molecular dynamics (MD), and docking to TLR4/MD-2. LolB was highly conserved (95–100% identity) under strong purifying selection (dN/dS = 0.15). A conformational B-cell hotspot centred on Q72 mapped to a solvent-accessible flexible loop. Two class II epitopes—LAAQNSPLT and FLGSAAAVS—showed predicted high affinity (IC₅₀ < 10 nM), non-toxicity, and broad coverage, with the pooled set achieving 98.6% global HLA coverage in silico. The final 119-aa construct (N-terminal hBD-3 adjuvant; GPGPG linkers) was compact and tractable (MW = 12.7 kDa; instability index < 40; near-neutral GRAVY) and scored higher for antigenicity than native LolB (VaxiJen 0.82 vs. 0.41). MD supported thermal stability up to 350 K, linker RMSF < 1.5 Å, and a stable 18.2 ± 2.8 Å interdomain spacing. Docking predicted a 1420 Ų interface and ΔG = −10.2 kcal·mol⁻¹ (Kd = 28 nM) with reproducible polar contacts, suggesting productive TLR4/MD-2 engagement. A conservative R42A/K variant is proposed to temper IFN-γ bias. This work therefore suggests an essentiality-anchored LolB-derived multi-epitope construct as a computational vaccine candidate against multidrug-resistant P. aaeruginosa and defines specific experimentally testable hypotheses for future in vitro/in vivo assessment. Essentiality-anchored epitope selection plus adjuvant-surface engineering yielded a structurally coherent, immunologically rational LolB-derived multi-epitope vaccine warranting experimental validation. Full article

Telemedicine, driven by the Internet of Things (IoT) and wireless connectivity, is essential for managing cardiovascular diseases, where hypertension remains the primary risk factor. In preclinical research, rabbits are superior biological models compared to rodents due to their human-like lipid metabolism. However, continuous blood pressure monitoring in this species remains challenging. The gold-standard technique (direct carotid catheterization) requires terminal procedures, and indirect methods (Doppler, oscillometric) show limited agreement with direct measurements. Furthermore, commercially available implantable telemetry platforms, while enabling real-time monitoring in freely moving animals, require costly surgical implantation, specialized proprietary hardware, and post-operative recovery periods that may confound early hemodynamic data. To address these limitations, this study presents a low-cost, customizable, and minimally invasive monitoring system utilizing a pressure transducer in the central auricular artery. The device integrates an ESP32 microcontroller with IoT technology for digital signal processing and seamless wireless data transmission to the ThingSpeak cloud platform. Unlike implantable telemetry, the proposed approach avoids surgical implantation and its associated costs and recovery time, while still enabling continuous, real-time hemodynamic tracking throughout the experimental period. A pilot evaluation against the BIOPAC MP100 reference (carotid artery) demonstrated relative errors of 1.60% for mean arterial pressure, 8.58% for systolic blood pressure, and 2.43% for diastolic blood pressure. By reducing invasiveness and enhancing remote data accessibility, this system provides a promising framework for the preclinical evaluation of antihypertensive agents and cardiovascular mechanisms, bridging the gap between edge computing and remote clinical diagnostics. Full article