Search Results (19,853)

The optimisation design of agricultural machinery is shifting from offline, experience-driven engineering towards adaptive, data-driven, and closed-loop intelligent optimisation. Conventional approaches based on computer-aided engineering (CAE), empirical testing, mathematical modelling, and static multi-objective optimisation have provided an important engineering foundation, but they remain limited under unstructured field conditions involving soil heterogeneity, crop variability, climatic disturbance, and nonlinear machinery–environment interactions. This review systematically examines the evolution of intelligent optimisation design for agricultural machinery from conventional simulation-based methods to artificial intelligence (AI)- and digital twin (DT)-enabled paradigms. First, mathematical modelling, response surface methodology, discrete element method (DEM), computational fluid dynamics (CFD), multi-body dynamics (MBD), heuristic algorithms, and early AI-assisted surrogate optimisation are reviewed to clarify their contributions and limitations. Second, frontier enabling technologies are analysed, including agriculture-specific large models, generative AI, lightweight edge intelligence, deep reinforcement learning (DRL), embodied AI, federated learning (FL), and privacy-preserving computing. Third, system-level applications integrating DT and AI are discussed, with emphasis on full-lifecycle machinery optimisation, device–edge–cloud collaborative control, multi-agent fleet coordination, predictive maintenance, and Agriculture 5.0-oriented intelligent equipment systems. Key deployment bottlenecks are further identified, including sim-to-real inconsistency, virtual–physical mismatch in DTs, edge-side trade-offs among accuracy, latency, energy consumption, and cost, insufficient validation standards, and economic adoption barriers. Finally, a 2025–2030 roadmap is proposed, highlighting large-model–DT closed loops, control biomimetics, green low-carbon optimisation, and trustworthy human–machine symbiosis for sustainable Agriculture 5.0. Full article

Particle swarm optimization (PSO) has been widely used in engineering optimization because of its simple structure and easy implementation. However, standard PSO and most of its variants mainly learn from the personal best position and the global best position. Thus, they often fail to preserve and reuse population-level knowledge generated during the search process. This problem becomes more evident when the search state changes or the swarm falls into stagnation, at which point useful search information may be ignored or forgotten. To address this issue, this paper proposes a state-adaptive knowledge recall PSO algorithm, termed SKRPSO. It includes three cooperative components. First, a state-aware adaptive aggregation mechanism adjusts the elite knowledge-pool size according to population dispersion and builds a rank-weighted knowledge vector for stable population-level guidance. Second, a stagnation-driven knowledge recall mechanism stores historical knowledge associated with global improvements in a bounded memory buffer and recalls recently successful knowledge with a time-decay preference when stagnation is detected. Third, a knowledge-fusion position update strategy uses current aggregated knowledge during normal search and recalled knowledge under stagnation, balancing local exploitation and stagnation escape. Experiments on the CEC2017 benchmark suite show that, based on 30 independent runs, SKRPSO achieves the best mean error on 22 of 29 functions and the best overall Friedman average rank of 1.431 among all compared algorithms. Engineering design results further indicate stable performance. Full article

Background: This study investigated the clinical timeline, patient monitoring behaviors, and cumulative bilateral treatment burden in patients with bilateral neovascular age-related macular degeneration. Methods: We retrospectively analyzed follow-up patterns and treatment intensity from first-eye (FE) diagnosis to second-eye (SE) conversion. Results: SE conversion occurred within a mean of 2.0 years in the FE-active group (62.5%) while the FE remained exudative, contrasting with 6.2 years in the FE-inactive group (37.5%). Upon SE conversion, the total annual intravitreal injection burden escalated 3.4-fold (p = 0.002). Notably, the FE-inactive group exhibited numerically lower annual outpatient visit counts (4.40 ± 2.71 vs. 10.29 ± 5.02; p = 0.116), which potentially widened the monitoring window. Additionally, baseline SE retinal pigment epithelium (RPE) abnormalities independently predicted progression (aOR: 19.04; p = 0.032). Conclusions: While previous literature focuses on individual eyes, our findings highlight a vigilance gap in SE detection based on FE status. Clinicians must maintain proactive surveillance for patients with baseline SE RPE abnormalities, particularly when FE stability or next-generation long-acting therapies extend clinic intervals. Due to the limited sample size, these preliminary findings warrant validation in larger prospective cohorts. Full article

Background/Objectives: Bipolar disorder affects about 40 million people worldwide, and the greatest burden of the disease is associated with depressive episodes. About 25% of patients experience drug-resistant depression, in which standard treatment turns out to be insufficient, and monotherapy often does not bring full remission. Despite the use of second-generation antipsychotics, the effectiveness of therapy in TRBD remains limited, which necessitates rational polypharmacotherapy and augmentation strategies. The paper discusses the receptor mechanisms of drug combination, current therapeutic regimens and new interventions such as ketamine acting on the glutamate anergic system. The aim was to synthetically compare the efficacy and safety of available augmentation strategies and polypharmacotherapy. Methods: The material consists of published clinical, observational and randomized trials on pharmacotherapy of drug-resistant bipolar depression, including atypical neuroleptics, ketamine, pramipexole, modafinil, lamotrigine, celecoxib and memantine. The authors analyze receptor mechanisms, neurobiological data and clinical trial results, comparing them with current definitions of TRBD according to ISBD and CINP. Biomarker data, such as the Systemic Immune-Inflammation Index, and the results of neuroimaging and metabolomic studies were also used in the work. Results: The analysis showed that atypical neuroleptics showed limited efficacy and high rates of side effects, while ketamine has the fastest and most pronounced antidepressant effect with a low risk of phase change. Pramipexole has shown promise in terms of long-term efficacy, but its use reduces the high risk of induction of mania and impulse control disorders. Celecoxib as an anti-inflammatory therapy significantly increased response and remission rates compared to escitalopram alone, and memantine showed only an early, short-term antidepressant effect. The results highlight that TRBD requires targeted polypharmacotherapy, with the most promising directions being glutamatergic modulation and anti-inflammatory therapies. Conclusions: Drug-resistant bipolar depression requires a departure from classical monotherapy in favor of rational, mechanistically justified polypharmacotherapy, targeting complex monoaminergic, glutamatergic and neuroinflammatory disorders. Available data indicate that ketamine has the greatest clinical potential among the current strategies, characterized by a rapid onset of action and a favorable safety profile compared to atypical neuroleptics or dopamine agonists. Modulation of inflammatory processes with the use of celecoxib also has promising results, which highlights the importance of biomarkers and personalization of therapy. However, further, large, and well-designed studies are needed to unambiguously determine optimal treatment strategies for TRBD and to verify the effectiveness of new pharmacological interventions. Full article

End-to-end autonomous driving remains fragile in long-tail scenarios, while incorporating vision-language models (VLMs) introduces substantial deliberation latency that cannot interfere with the real-time planning loop. We present ThinkDrive, a dual-process driving framework designed under explicit real-time queuing constraints. The framework contains four coordinated components. First, a Scene Complexity Estimator regulates System-2 activation through a trigger cool-down mechanism, allowing at most one asynchronous request every $\lceil L_2/\Delta t\rceil$ frames and thereby preventing queue saturation under a System-2 latency of $L_2=565$ ms. Second, a multi-modal System-1 planner generates $K_1=5$ candidate trajectories within 44 ms and is trained with winner-takes-all imitation learning together with explicit score supervision. Third, a two-stage Causal-CoT module uses the VLM to identify risk agents and predict a preferred spatial goal $G_{\mathrm{VLM}}$, after which a single batched scm_rollout selects the safest candidate and extracts its endpoint as a world-coordinate goal anchor ${\mathbf{g}}_{S2}$. Fourth, a Goal-Anchor Replanning module transforms ${\mathbf{g}}_{S2}$ into the current ego frame and selects the candidate whose waypoint at the remaining time horizon is closest to the transformed goal. This design avoids coordinate-space mixing, mitigates bias caused by mismatched temporal horizons, and prevents semantic instability across replanning cycles. On nuPlan test14-hard, ThinkDrive with InternVL2-8B and a 6.8% trigger rate achieves 74.9 PDMs, outperforming AdaThinkDrive at 73.1 while maintaining a nominal latency of 44 ms. Full article

The genetic parameters at 6, 9 and 12 years were studied in two progeny trials (one half-sib and one full-sib) of silver fir (Abies alba Mill.) in Romania, in order to establish an appropriate breeding strategy for advancing second-generation seed orchards. The half-sib trial (HS) consists of 60 open-pollinated families of plus trees from four first-generation seed orchards, while the full-sib trial (FS) consists of 51 half-diallel crosses of 11 plus trees from one seed orchard. Tree height and diameter were found to be under moderate to strong genetic control at both the family and individual levels. Total height showed a higher percentage of additive genetic variance than diameter in both types of progenies. Additive genetic variances increased with age for the diameter (from 12% to 36%), while for the total height, it decreased (from 76% to 35%). In the HS trial, family heritability was higher than individual heritability for both traits. The highest values of heritability were obtained for total height, both at the individual (0.76–0.35) and family levels (0.88–0.63). In FS progenies, the estimates of the narrow-sense individual heritability were lower than those at the family level and remained almost constant over time. The additive age-age genetic correlations and genetic correlations among growth traits were more stable and stronger in FS progeny than in HS progenies. Expected genetic gains were calculated at individual and family levels for different breeding strategies. The highest genetic gain will be obtained through selection of the best parents. Genetic gain slightly varied over age and for progeny tests. The level of genetic diversity, calculated for selected parents based on the breeding values, was high, while the inbreeding coefficient reduced. Combining the backward selection strategy with SSR analyses allows optimization for seed orchard design in order to mitigate inbreeding depression risks and enhance genetic diversity in the next breeding generation. Full article

Objective: Posaconazole, a second-generation triazole antifungal used for the prevention or treatment of invasive fungal infections, has been shown to markedly increase tacrolimus exposure in vivo when co-administered, potentially leading to clinically significant adverse events. A physiologically based pharmacokinetic (PBPK) model was developed to predict tacrolimus–posaconazole interactions in renal transplant recipients with different CYP3A5 genotypes, to inform tacrolimus dose adjustment in clinical practice. Methods: First, to obtain the critical inhibition parameters, in vitro enzyme kinetic studies were conducted. Based on these data, a whole-body physiologically based pharmacokinetic (PBPK) model for TAC was developed and validated in PK-Sim. A published, validated posaconazole PBPK model was applied concurrently. Model performance was evaluated against published pharmacokinetic data in healthy volunteers receiving tacrolimus with posaconazole. A virtual Chinese renal transplant recipient was generated by incorporating population-specific physiological parameters, including CYP3A5 genotype-dependent enzyme expression. Results: In vitro experimental results demonstrated that POSA acts as a potent reversible competitive inhibitor of CYP3A4/5-mediated TAC metabolism. The tacrolimus PBPK model adequately captured pharmacokinetics across CYP3A5 genotypes, and tacrolimus pharmacokinetics during co-administration with posaconazole were also predicted. Compared with CYP3A5 expressers, nonexpressers showed greater variability in tacrolimus whole-blood concentrations and greater susceptibility to posaconazole-mediated interactions. The CYP3A5*3*3 genotype was associated with higher C_max and AUC. Dose optimization simulations predicted that after 6–7 days of posaconazole co-administration, nonexpressers would require the reduction of tacrolimus dosing frequency from every 12 h to every 24 h to maintain trough concentrations within 8–15 ng/mL, whereas a 50% dose reduction was predicted to be optimal for expressers. Conclusions: A tacrolimus–posaconazole PBPK drug–drug interaction model was developed for the population of renal transplant recipients and used to simulate tacrolimus trough concentrations across CYP3A5 genotypes and dosing regimens, supporting genotype-informed co-administration in clinical practice. Full article

We present a composable, pipeline-based rules engine for detecting application-level intrusions in HTTP traffic with adaptive rule generation capabilities. Rules are expressed in JSON chain multi-step decoders (Base64, hex, XOR, zlib, gzip) with matching primitives (word boundaries, regular expressions, substring sets) to detect obfuscated payloads. To enable adaptation to novel attack patterns, we integrate a large language model (LLM) component as a second-opinion layer that automatically generates validated detection rules for previously unseen threats, combining the adaptability of machine learning with the interpretability of explicit rules. We evaluate the system on two standard benchmarks (CSIC 2010 and HttpParamsDataset) and present a head-to-head comparison with ModSecurity and the OWASP Core Rule Set, achieving 98.1% and 98.3% detection rates with F1 scores above 0.97 on both datasets while maintaining false positive rates below 0.51%. Full article

Small object detection in uncrewed aerial vehicle (UAV) imagery is hindered by limited pixels, insufficient detailed information, and strong background interference, leading to weak feature representation and poor contextual modeling. To address these issues, we propose a multi-domain enhancement and cross-layer feature fusion detection Transformer (MDCL-DETR) with progressive feature processing. First, a multi-domain enhancement module (MDEM) based on CSP (cross stage partial) structure is proposed, which fuses spatial and frequency-domain features in a lightweight manner to enhance object detail and global structures while effectively distinguishing object features from background interference. Second, a cross-layer feature extraction module (CLEM) is introduced to aggregate multi-scale features across layers, alleviate information loss caused by downsampling, and preserve spatial details of small objects while integrating high-level contextual semantics. Meanwhile, a gated Mamba fusion module (GMFM) is proposed, which adopts the Mamba architecture for long-range dependency modeling of multi-scale features and integrates a gating mechanism to realize the dynamic weighted fusion of local details and global context, further improving feature discriminability and global modeling capability. Finally, a fine-grained enhancement module (FGEM) is designed, which leverages feature reorganization and adaptive feature extraction to reinforce and compensate fine-grained features. Extensive experimental results validate the effectiveness and generalization of the proposed method, achieving mAP${}_{50}$ scores of $54.1\%$ and $56.2\%$ on the VisDrone2019 and AI-TOD datasets. Full article

With the increasing integration of high-penetration renewable energy and emerging loads, power system operation simulation faces two major challenges, namely strong uncertainty and significant heterogeneity in the output characteristics of multiple generator types. Traditional mathematical programming methods struggle to effectively handle uncertainty while meeting real-time computational requirements. Existing deep learning approaches fail to decouple the heterogeneous output characteristics of different generator types, which limits their ability to achieve coordinated operation. To address these issues, this paper proposes a task-decoupled and multi-task synergistic LLM-MoE method for power system operation simulation. First, a feature encoder based on Residual-Gated Linear Units is constructed to perform deep filtering and efficient representation of multi-source heterogeneous data. Second, a pre-trained large language model is employed as a temporal feature extractor to enhance temporal modeling capability and cross-scenario generalization. Finally, a customized gating-controlled mixture-of-experts decoder is developed. It dynamically coordinates task-specific and shared experts, which enables unified modeling of task decoupling, cross-task information sharing, and system physical constraints. Simulation results based on a provincial-level power grid in China demonstrate that the proposed method achieves high-accuracy and high-efficiency operation simulation while ensuring physical consistency. Full article

A Ti-Al-Si composite coating was prepared on Ti65 titanium alloy using a two-step hot-dipping + pre-oxidation method to improve its tribological performance and high-temperature oxidation resistance. The second-step dipping time strongly affected the coating microstructure and wear behavior. The optimal coating, prepared with a dipping time of 5 min in each step, exhibited negligible wear after oxidation at 800 °C for 1000 h and 2500 h, with slight adhesive wear and oxidative wear as the dominant mechanisms. Longer dipping times led to mixed wear modes and reduced wear resistance. Under high-temperature corrosion conditions, the coating showed good long-term stability in water vapor, with its mass gain following a sub-parabolic law, Δm = 0.39·t^0.47, because the internal multilayered structure effectively blocked inward oxygen diffusion. However, in environments containing NaCl or 75 wt.% Na₂SO₄ + 25 wt.% NaCl, catastrophic hot corrosion occurred, regardless of the presence of water vapor, through a chlorine-driven oxidation–chlorination–reoxidation autocatalytic cycle. In the mixed salt environment, Na₂SO₄ decomposition supplied additional oxygen and alkaline species, accelerating the degradation and spallation of the Al₂O₃ and TiO₂ scales. Water vapor further intensified this cycle by generating HCl, which promoted rapid consumption of Al and Ti in the coating. This study reveals the wear behavior and hot corrosion failure mechanisms of Ti-Al-Si coatings under complex conditions, providing guidance for process optimization and applications in marine atmospheres. Full article

Railway traction power supply systems (TPSSs) are evolving from passive grid-fed infrastructures into active energy systems with local photovoltaic (PV) generation capacity, energy storage systems (ESSs), and converter-based regulation. Unlike conventional microgrids, TPSSs feature single-phase, highly dynamic traction loads; short-duration regenerative braking bursts; and strict constraints on voltage quality, stability, and protection. These characteristics make the energy management of distributed PV-storage-integrated TPSSs a distinct research problem. This review examines the field from three coupled perspectives: supply architecture, power electronic interfaces, and energy management strategies. First, representative integration architectures are classified into substation-side, wayside-distributed, and hybrid multi-port schemes. Second, converter interfaces and flexible traction substations are analyzed as the enabling layer for coordinated control of PV, ESS, the utility grid, and traction feeders. Third, major energy management strategies, including rule-based, optimization-based, hierarchical multi-timescale, and uncertainty-aware methods, are compared. The review further discusses power quality, stability, protection, and battery degradation constraints that shape practical deployments. Finally, research gaps and future directions are identified to further the development of more robust, railway-specific, and implementation-oriented PV-storage energy management. Full article

Survivors of primary gastric lymphoma (PGL) face a significantly elevated and persistent risk of developing second primary malignancies (SPMs), with gastric adenocarcinoma representing the most frequent SPM and standardized incidence ratios reaching up to 16-fold above the general population. This excess risk persists for decades after initial treatment and is associated with increased cause-specific mortality compared to matched primary cancers. Among patients with PGL, approximately 5% develop gastric cancer (with two-thirds being metachronous), and nearly 15% harbor precancerous lesions including atrophic gastritis, intestinal metaplasia, and dysplasia. Beyond gastric malignancies, survivors also experience elevated rates of extra-gastric SPMs, particularly digestive system tumors (43%), respiratory cancers (21%), and urinary tract malignancies (13%). Key risk factors include treatment with immunochemotherapy or radiotherapy, advanced age, male sex, advanced stage at diagnosis, ulcerative-type lymphoma morphology, and persistent Helicobacter pylori (HP) infection. Patients receiving combined chemoradiotherapy demonstrate the highest SPM risk, particularly for gastric and pancreatic cancers. These findings underscore the critical importance of lifelong, risk-adapted surveillance strategies integrating both hematology and gastroenterology follow-up. Annual endoscopic surveillance is recommended for high-risk patients, with intervals adjusted according to lymphoma histology, HP status, and the presence of precancerous gastric lesions. Mandatory HP eradication with confirmation of response is essential for reducing gastric cancer risk. Future research priorities include prospective, standardized studies to better quantify SPM risk, validation of molecular and microbiological biomarkers for individualized risk stratification, and development of predictive models to enable personalized surveillance protocols and improve long-term outcomes in this vulnerable population. Full article

The Garisenda Tower, along with the neighboring Asinelli Tower, is arguably the symbol of the city of Bologna. They are the sole remnants of about one hundred towers that formed the city’s skyline in medieval times. As such, the monitoring of their state of health has been of great interest to the scientific community for more than a century—one example being the studies of Prof. Cavani in the early 1900s. The Garisenda Tower, famous for its impressive lean, is the object of Structural Health Monitoring (SHM) involving a multitude of devices. Some examples are a 30 m long pendulum installed on the inside of the tower to measure the planar displacement of the tower’s top; Fiber-Optical Strings (FOSs) installed in the walls of the basement to measure their vertical deformation; and piezoelectric acoustic emission (AE) sensors, also installed on the walls of the tower’s basement to detect elastic waves generated by micro-cracking. This rich experimental setup allows for the investigation of the tower’s stability and damage assessment. In this work, attention is focused on two analyses: The first is a Principal Component Analysis (PCA) study that investigates the correlation between AE data and other SHM data, such as in situ temperature, pendulum displacement, and AE rate. The second analysis corresponds with numerical finite element (FE) studies that assess damage in the base of the tower. Initially, the Smeared Cracking material model is used to understand which zones of the tower are more damaged. Moreover, a possible critical scenario due to increasing tower tilt is investigated. Finally, a viscoelastic formulation of the materials at the base of the tower is used to account for creep to understand the possible viscous effects at the base of the tower. Full article

Background and Clinical Significance: The coexistence of synchronous urologic malignancies may present diagnostic and therapeutic challenges, particularly when symptoms are minimal or nonspecific. This case illustrates the role of multimodal diagnostic correlation in identifying a second primary urologic malignancy during the evaluation of incidental PSA elevation. Case presentation: Case Presentation: We report the case of a 56-year-old male presenting with minimal lower urinary tract symptoms who underwent stepwise diagnostic evaluation including PSA (prostate specific antigen), free PSA, urinary SelectMDx RT-PCR testing (reverse transcription polymerase chain reaction), multiparametric MRI (magnetic resonance imaging), transrectal biopsy and inflammatory biomarker assessment. PSA was 17.69 ng/mL with a free PSA ratio of 6.56%. SelectMDx indicated a 90% probability of prostate cancer and a 65% risk of Gleason ≥ 7 disease. mpMRI demonstrated two suspicious lesions without extracapsular extension. Biopsy confirmed acinar adenocarcinoma Gleason 7 (3 + 4), Grade Group 2. Persistent post-biopsy hematuria led to additional imaging that revealed bladder wall thickening, and cystoscopy confirmed multifocal carcinoma in situ. Radical cystoprostatectomy with orthotopic ileal neobladder reconstruction was performed. Conclusions: This case illustrates the importance of diagnostic vigilance and multimodal correlation in a minimally symptomatic patient, particularly when persistent clinical findings are not fully explained by the initial diagnosis. The findings should be interpreted as illustrative and cannot be generalized beyond the single-case context. Full article