Search Results (1,305)

In scalable video transmission research, the video transmission process is commonly modeled as a Markov decision process, where deep reinforcement learning (DRL) methods are employed to optimize the wireless transmission of scalable videos. Furthermore, the adaptive DRL algorithm can address the energy shortage problem caused by the uncertainty of energy capture and accumulated storage, thereby reducing video interruptions and enhancing user experience. To further optimize resources in wireless energy transmission and tackle the challenge of balancing exploration and exploitation in the DRL algorithm, this paper develops an adaptive DRL algorithm that extends classical DRL frameworks by integrating dropout techniques during both the training and prediction processes. Moreover, to address the issue of continuous negative rewards, which are often attributed to incomplete training in the wireless video transmission DRL algorithm, this paper introduces the Cramér large deviation principle for specific discrimination. It identifies the optimal negative reward frequency boundary and minimizes the probability of misjudgment regarding continuous negative rewards. Finally, experimental validation is performed using the 2048-game environment that simulates wireless scalable video transmission conditions. The results demonstrate that the adaptive DRL algorithm described in this paper achieves superior convergence speed and higher cumulative rewards compared to the classical DRL approaches. Full article

Localized ionization enhancements (LIEs) in altitude range corresponding to the D-region ionosphere, disrupting Very-Low-Frequency (VLF) signal propagation. This case study focuses on Lightning-induced Electron Precipitation (LEP), analyzing amplitude and phase variations in VLF signals recorded in Belgrade, Serbia, from worldwide transmitters. Due to the localized, transient nature of Energetic Electron Precipitation (EEP) events and the path-dependence of VLF responses, research relies on event-specific case studies to model reflection height and sharpness via numerical simulations. Findings show LIEs are typically under 1000 × 500 km, with varying internal structure. Accumulated case studies and corresponding data across diverse conditions contribute to a broader understanding of ionospheric dynamics and space weather effects. These findings enhance regional modeling, support aerosol–electricity climate research, and underscore the value of VLF-based ionospheric monitoring and collaboration in Europe. Full article

DNA polymerase epsilon (POLe) is the leading strand replicative polymerase. POLe mutations located primarily in the proofreading domain cause replication errors and increase mutation burden in cancer cells. Consequently, POLe has been classified as a cancer driver gene. Certain POLe frameshift mutations that affect the proofreading domain are purified in cancer cells, but point mutations in other domains have also been reported. Here we use an artificial intelligence algorithm to determine what other mutations co-occur with POLe mutations in colorectal cancers. We partitioned POLe mutations into driver, passenger, and WT (no mutation), then assessed mutations in other genes in these three groups. We found that a driver POLe mutation is not likely to associate with driver mutations in other genes. Thus, driver mutations in colorectal cancers appear to purify in a manner that is independent of POLe. Mutations that affect POLe function do not necessarily increase the frequency of driver mutations in other genes. Structural analysis shows that many POLe driver mutations affect coordination of the Mg²⁺ ion in the active site. Our data show that the accumulation of colorectal cancer mutations is driven by complex factors. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

Fiber Bragg grating (FBG) exhibits strong resistance to electromagnetic interference and excellent linear strain response, making it highly promising for structural health monitoring (SHM) in pavement. This research investigates the strain transfer characteristics of embedded FBG in pavement structure and materials by using the relevant theoretical models. Results indicate adhesive layer thickness and sheath modulus are the primary factors influencing the strain transfer coefficient. A thinner adhesive layer and high modulus of sheath enhance the coefficient. Additionally, the strain distribution of sheath significantly affects the transfer efficiency. When the stress level near the grating region is lower than the both ends, the coefficient increases and even exceeds 1, which typically occurs under multi-axle conditions. As for asphalt mixture, high temperature leads to lower efficiency, while accumulated plastic strain improves it. Although the increased load frequency results a higher strain transfer coefficient, the magnitude of this change is negligible. By employing polynomial fitting to the sheath strain distribution, the boundary condition of theoretical equation could be removed. The theoretical and numerical results of strain transfer coefficient for pavement embedded FBG demonstrate good consistency, indicating the polynomial fitting is adoptable for the theoretical calculation with non-uniform strain distribution. This study utilizes the FEM to clarify the evolution of FBG strain transfer in pavement structures and materials, providing a theoretical basis for the design and implementation of embedded FBG in pavement. Full article

Existing Simultaneous Localization and Mapping (SLAM) algorithms provide precise local pose estimation and real-time scene reconstruction, widely applied in autonomous navigation for land vehicles. However, the odometry of SLAM algorithms exhibits localization drift and error divergence over long-distance operations due to the lack of inherent global constraints. In this paper, we propose a real-time geo-localization method for land vehicles, which only relies on a LiDAR-inertial-visual SLAM (LIV-SLAM) and a referenced image. The proposed method enables long-distance navigation without requiring GPS or loop closure, while eliminating accumulated localization errors. To achieve this, the local map constructed by SLAM is real-timely projected onto a downward-view image, and a highly efficient cross modal matching algorithm is proposed to estimate the global position by aligning the projected local image to a geo-referenced satellite image. The cross-modal algorithm leverages dense texture orientation features, ensuring robustness against cross-modal distortion and local scene changes, and supports efficient correlation in the frequency domain for real-time performance. We also propose a novel adaptive Kalman filter (AKF) to integrate the global position provided by the cross-modal matching and the pose estimated by LIV-SLAM. The proposed AKF is designed to effectively handle observation delays and asynchronous updates while simultaneously rejecting the impact of erroneous matches through an Observation-Aware Gain Scaling (OAGS) mechanism. We verify the proposed algorithm through R³LIVE and NCLT datasets, demonstrating superior computational efficiency, reliability, and accuracy compared to existing methods. Full article

Lightweight speech denoising models have made remarkable progress in improving both speech quality and computational efficiency. However, most models rely on long temporal windows as input, limiting their applicability in low-latency, real-time scenarios on edge devices. To address this challenge, we propose a lightweight hybrid module, Temporal Statistics Enhancement, Squeeze-and-Excitation-based Dual Convolutional Attention, and Band-wise Attention (TSE, SDCA, BA) Module. The TSE module enhances single-frame spectral features by concatenating statistical descriptors—mean, standard deviation, maximum, and minimum—thereby capturing richer local information without relying on temporal context. The SDCA and BA module integrates a simplified residual structure and channel attention, while the BA component further strengthens the representation of critical frequency bands through band-wise partitioning and differentiated weighting. The proposed model requires only 0.22 million multiply–accumulate operations (MMACs) and contains a total of 112.3 K parameters, making it well suited for low-latency, real-time speech enhancement applications. Experimental results demonstrate that among lightweight models with fewer than 200K parameters, the proposed approach outperforms most existing methods in both denoising performance and computational efficiency, significantly reducing processing overhead. Furthermore, real-device deployment on an improved hearing aid confirms an inference latency as low as 2 milliseconds, validating its practical potential for real-time edge applications. Full article

Background/Objectives: Hodgkin’s lymphoma (HL) affects 2–4 individuals per 100,000 annually. Standard treatment includes radiotherapy and ABVD chemotherapy, achieving a 95% survival rate. However, HL survivors face an elevated risk of treatment-related morbidity, particularly the development of secondary malignancies. Previous studies have demonstrated that ABVD treatment induces a high frequency of chromosomal aberrations (CAs) in lymphocytes from HL patients, with higher frequencies one year after treatment than during treatment. This study aimed to determine whether HL treatment also induces unclassified chromosomal/nuclear aberrations (UnCAs) in the lymphocytes of HL patients, and whether these alterations may serve as complementary indicators of genomic instability. Methods: Peripheral blood lymphocytes from HL patients were collected at three time points: before treatment (BT), during treatment (DT), and one year after treatment (1yAT) with ABVD chemotherapy and radiotherapy. A minimum of 3000 nuclei were analyzed per patient to identify and quantify UnCAs. These results were compared to UnCA frequencies in healthy individuals. Results: The percentage of cells presenting UnCAs per 3000 nuclei was 23.92% BT, 18.58% DT, and 30.62% 1yAT. All values were significantly higher (p < 0.016) than the 8.16% observed in healthy controls. The increase was primarily driven by free chromatin and micronuclei clusters. UnCA frequency was lower during treatment than one year after, likely due to the elimination of highly damaged cells through apoptosis or lack of proliferative capacity. Over time, however, persistent genomic damage appears to accumulate in surviving cells, becoming more evident post-treatment. A parallel trend was observed between the frequencies of UnCAs free chromatin, micronucleus and micronuclei clusters, and classical CAs, showing a similar pattern of genomic damage induced by therapy. Conclusions: The post-treatment increase in UnCAs indicates ongoing genomic instability, possibly driven by the selective survival of hematopoietic stem cells with higher genomic fitness. Given their persistence and association with therapy-induced damage, free chromatin and micronuclei clusters may serve as early biomarkers for secondary cancer risk in HL survivors. Full article

Integrated sensing and communication (ISAC) has become a key enabler in 5G-Advanced (5G-A) and future 6G systems, with Orthogonal Frequency Division Multiplexing (OFDM) widely adopted as the underlying waveform. However, due to the inherent structure of OFDM signals, traditional sensing algorithms often suffer from a limited sensing range in practical applications. To address this issue, we propose a delay compensation algorithm that mitigates the impact of delay and ensures the gain of range-Doppler processing. Furthermore, we analyze the issue of ambiguous targets in CP-OFDM systems, considering both single-target and multi-target scenarios. To improve the detection probability and suppress the accumulated echo energy corresponding to ambiguous targets, we propose a sequence design criterion, in which part of the original signal is replaced with a designed sequence. Simulation results demonstrate that the proposed algorithm effectively improves detection range and ensures unambiguous target identification, while achieving effective suppression of ambiguous target energy. Compared with a conventional algorithm, it achieves a processing gain of up to 20 dB. Moreover, the results show that different redundancy ratios can be selected in varying scenarios to balance communication and sensing performance in ISAC systems. Full article

As high-speed electric multiple units (EMUs) advance in speed and complexity, quasi-static design methods may underestimate the fatigue risks associated with high-frequency dynamic excitations. This study quantifies the contribution of gear meshing-induced vibrations (2512 Hz) to fatigue damage in EMU gearbox housings, revealing resonance amplification of local stresses up to 1.8 MPa at 300 km/h operation. Through integrated field monitoring and bench testing, we demonstrated that gear meshing excites structural modes, generating sustained, very high-cycle stresses (>10⁸ cycles). Crucially, fatigue specimens were directly extracted from in-service gearbox housings—overcoming the limitations of standardized coupons—passing the very high-cycle fatigue (VHCF) test to derive S-N characteristics beyond 10⁸ cycles. Results show a continuous decline in fatigue strength (with no traditional fatigue limit) from 10⁸ to 10⁹ cycles. This work bridges the gap between static design standards (e.g., FKM) and actual dynamic environments, proving that accumulated damage from low-amplitude gear-meshing stresses (3.62 × 10¹¹ cycles over a 12 million km lifespan) contributes to a 16% material utilization ratio. The findings emphasize that even low-magnitude gear-meshing stresses can significantly influence gearbox fatigue life due to their ultra-high frequency, warranting design consideration beyond current standards. Full article

Electrical connectors play a vital role in ensuring reliable signal transmission in high-frequency microsystems. This study explores the impact of microscale scratch-induced surface roughness on the alternating current (AC) contact impedance of RF coaxial connectors. Unlike traditional approaches that assume idealized surface conditions, controlled micro-defects were introduced at the central contact interface to establish a quantitative relationship between surface morphology and signal degradation. An equivalent circuit model was constructed to account for local impedance variations and the cumulative effects of cascaded connector interfaces. The model was validated using S-parameter measurements obtained from vector network analyzer (VNA) testing, showing strong agreement with simulation results. Experimental results reveal that the low-roughness (0.4 μm) contact surfaces lead to degraded signal integrity due to insufficient micro-contact formation. In contrast, scratch-induced moderate roughness (0.8–4.8 μm) improves transmission performance, although signal quality declines as roughness increases within this range. These effects are further amplified in multi-connector configurations due to accumulated impedance mismatches. This work provides new insight into the coupling between microscale surface features and frequency-domain transmission characteristics, offering practical guidance for surface engineering, contact design, and the development of miniaturized, high-reliability radio frequency interconnects for next-generation communication systems. Full article

With the continuous development of high-speed electric multiple units (EMUs), vibration issues of vehicles have become increasingly prominent. During operation, the underfloor equipment installed on the carbody is subjected to random multi-point vibrations transmitted from the carbody, inducing significant fatigue damage. This paper presents a comprehensive analysis of multi-channel vibration environment data for various underfloor equipment across different operating speeds obtained through on-site measurements. A spectral synthetic method grounded in statistical principles is then proposed to generate vibration environment spectra for diverse underfloor equipment. Finally, utilizing fatigue analysis in the frequency domain, the fatigue damage to underfloor equipment is assessed under different operational environments. The research results show that the vibration environment spectrum of the underfloor equipment in high-speed EMU trains differs significantly from the vibration spectrum specified in the IEC 61373 standard, especially at high frequencies. Despite this difference in spectral characteristics, the overall vibration energy values of the two spectra are comparable. Additionally, the vibration spectra of different underfloor equipment exhibit variations that can be attributed to their installation positions. As operational speed increases, the fatigue damage to the underfloor equipment exhibits exponential growth. However, the total accumulated fatigue damage remains relatively low, consistently staying below a value of 1. Full article

Floods are the biggest hydrometeorological disaster, affecting millions annually. Thus, flood hazard assessment is crucial and plays a pivotal role in rational water management. This study was undertaken to evaluate flood hazards through the application of MCDM methods and a bivariate statistical model integrated with GIS. The methodologies applied were AHP, fuzzy AHP, and the frequency ratio. Eight flood-related criteria were considered—elevation, flow accumulation, geology, slope, land use/land cover (LULC), distance from the drainage network, drainage density, and rainfall index—for the construction of a Flood Hazard Map for each methodology, with the aim to delineate the regions within the study area most prone to flooding. The results demonstrated that around 34% of the Chalkidiki regional unit presents a high and very high hazard to the occurrence of floods. The comparison of the maps generated using DSC demonstrated that all models are capable of delineating high and very high hazard areas with overlap values varying from 0.8 to 0.98. The validation results indicated that the models exhibit sufficient performance in flood hazard mapping with AUC-ROC scores of 66.6%, 65.7%, and 76.5% for the AHP, FAHP, and FR models, respectively. Full article

The time fluctuations of forest fires occurring in Basilicata, a region situated in Southern Italy, between 2004 and 2023 were investigated using various analytical approaches. Analysis revealed a clustering of fire occurrences over time, as indicated by a significantly high coefficient of variation. This suggests that the fire sequence does not follow a Poisson distribution and instead exhibits a clustered structure, largely driven by the heightened frequency of events during the summer seasons. The analysis of monthly forest fire occurrences and total burned area indicates a significant correlation between the two. This correlation is reinforced by shared patterns, notably an annual cycle that appears to be influenced by meteorological factors, aligning with the yearly fluctuations in the region’s weather conditions typical of a Mediterranean climate. Furthermore, the relationship between the Standardized Precipitation Evapotranspiration Index (SPEI) and forest fires revealed that the accumulation period of the SPEI corresponds to the cycle length of the fires: longer cycles in fire occurrences align with higher accumulation periods in SPEI data. Full article

The mechanisms of ictal discharge initiation remain incompletely understood, particularly the paradoxical role of inhibitory fast-spiking interneurons in seizure generation. Using simultaneous whole-cell recordings of interneurons and pyramidal neurons combined with extracellular [K⁺]_o monitoring in mouse entorhinal cortex-hippocampal slices (4-aminopyridine model of epileptiform activity), we identified a critical transition sequence: interneurons displayed high-frequency firing during the preictal phase before entering depolarization block (DB). DB onset coincided with the peak of rate of extracellular [K⁺] accumulation. Pyramidal cells remained largely silent during interneuronal hyperactivity but started firing within 1.1 ± 0.3 s after DB onset, marking the transition to ictal discharges. This consistent sequence (interneuron DB → [K⁺]_o rate peak → pyramidal cell firing) was observed in 100% of entorhinal cortex recordings. Importantly, while neurons across all entorhinal cortical layers synchronously fired during the first ictal discharge, hippocampal CA1 neurons showed fundamentally different activity: they generated high-frequency interictal bursts but did not participate in ictal events, indicating region-specific seizure initiation mechanisms. Our results demonstrate that interneuron depolarization block acts as a precise temporal switch for ictogenesis and suggest that the combined effect of disinhibition and K⁺-mediated depolarization triggers synchronous pyramidal neuron recruitment. These findings provide a mechanistic framework for seizure initiation in focal epilepsy, highlighting fast-spiking interneurons dysfunction as a potential therapeutic target. Full article