Search Results (1,214)

Population aging is driving the need for unobtrusive, continuous monitoring solutions in residential care environments. Radio-frequency (RF)-based technologies such as Ultra-Wideband (UWB) and millimeter-wave (mmWave) radar are particularly attractive for providing detailed information on presence and movement while preserving privacy. Building on a UWB–mmWave localization system deployed in a senior living residence, this paper focuses on the data-processing methodology for extracting quantitative mobility indicators from long-term indoor monitoring data. The system combines a device-free mmWave radar setup in bedrooms and bathrooms with a tag-based UWB positioning system in common areas. For mmWave data, an adaptive short-term average/long-term average (STA/LTA) detector operating on an aggregated, normalized radar energy signal is used to classify micro- and macromovements into bedroom occupancy and non-sedentary activity episodes. For UWB data, a partially constrained Kalman filter with a nearly constant velocity dynamics model and floor-plan information yields smoothed trajectories, from which daily gait- and mobility-related metrics are derived. The approach is illustrated using one-day samples from three users as a proof of concept. The proposed methodology provides individualized indicators of bedroom occupancy, sedentary behavior, and mobility in shared spaces, supporting the feasibility of combined UWB and mmWave radar sensing for longitudinal routine analysis in real-world elderly care environments. Full article

Symbiotic radio (SR) has recently emerged as a promising paradigm for enabling spectrum- and energy-efficient massive connectivity in low-power Internet-of-Things (IoT) networks. By allowing passive backscatter devices (BDs) to coexist with active primary link transmissions, SR significantly improves spectrum utilization without requiring dedicated spectrum resources. However, most existing studies on multi-tag multiple-input multiple-output (MIMO) SR systems assume homogeneous traffic demands among BDs and primarily focus on rate-based performance metrics, while neglecting system-level task completion time (TCT) optimization under heterogeneous data requirements. In this paper, we investigate a joint performance optimization framework for a multi-tag MIMO symbiotic radio network. We first formulate a weighted sum-rate (WSR) maximization problem for the secondary backscatter links. The original non-convex WSR maximization problem is transformed into an equivalent weighted minimum mean square error (WMMSE) problem, and then solved by a block coordinate descent (BCD) approach, where the transmit precoding matrix, decoding filters, backscatter reflection coefficients are alternatively optimized. Second, to address the transmission delay imbalance caused by heterogeneous data sizes among BDs, we further propose a rate weight adaptive task TCT minimization scheme, which dynamically updates the rate weight of each BD to minimize the overall TCT. Simulation results demonstrate that the proposed framework significantly improves the WSR of the secondary system without degrading the primary link performance, and achieves substantial TCT reduction in multi-tag heterogeneous traffic scenarios, validating its effectiveness and robustness for MIMO symbiotic radio networks. Full article

We present an adaptive governance engine for blockchain-enabled Vehicular Ad Hoc Networks (VANETs) that regulates the latency–energy–coherence trade-off under rapid topology changes. The core contribution is an Ideal Information Cycle (an operational abstraction of information injection/validation) and a modular VANET Engine implemented as a real-time control loop in NS-3.35. At runtime, the Engine monitors normalized Shannon entropies—informational entropy S over active transactions and spatial entropy $H_{\mathrm{spatial}}$ over occupancy bins (both on $[0,1]$)—and adapts the consensus mode (latency-feasible PoW versus signature/quorum-based modes such as PoS/FBA) together with rigor parameters via calibrated policy maps. Governance is formulated as a constrained operational objective that trades per-block resource expenditure (radio + cryptography) against a Quality-of-Information (QoI) proxy derived from delay/error tiers, while maintaining timeliness and ledger-coherence pressure. Cryptographic cost is traced through counted operations, $E_{\mathrm{crypto}}=e_h{n}_{\mathrm{hash}}+e_{\mathrm{sig}}{n}_{\mathrm{sig}}$, and coherence is tracked using the LCP-normalized definition $D_{\mathrm{ledger}}\left(t\right)$ computed from the longest common prefix (LCP) length across nodes. We evaluate the framework under urban/highway mobility, scheduled partitions, and bounded adversarial stressors (Sybil identities and Byzantine proposers), using 600 s runs with 30 matched random seeds per configuration and 95% bias-corrected and accelerated (BCa) bootstrap confidence intervals. In high-disorder regimes ($S\gtrsim 0.8$), the Engine reduces total per-block energy (radio + cryptography) by more than 90% relative to a fixed-parameter PoW baseline tuned to the same agreement latency target. A consensus-first triggering policy further lowers agreement latency and improves throughput compared with broadcast-first baselines. In the emphasized urban setting under high mobility ($v=30$ m/s), the Engine keeps agreement/commit latency in the sub-100 ms range while maintaining finality typically within sub-150 ms ranges, bounds orphaning (≤10%), and reduces average ledger divergence below $0.07$ at high spatial disorder. The main evaluation is limited to $N\le 100$ vehicles under full PHY/MAC fidelity. PoW targets are intentionally latency-feasible and are not intended to provide cryptocurrency-grade majority-hash security; operational security assumptions and mode transition safeguards are discussed in the manuscript. Full article

This work addresses the increasing complexity of urban mobility by proposing an intelligent optimization and resource-allocation framework for Vehicle-to-Infrastructure (V2I) communications. The model integrates a macroscopic mobility analysis, an Integer Linear Programming (ILP) formulation for optimal Road-Side Unit (RSU) placement, and a Smart Generic Network Controller (SGNC) based on Q-learning for dynamic radio-resource allocation. Simulation results in a realistic georeferenced urban scenario with 380 candidate sites show that the ILP model activates only 2.9% of RSUs while guaranteeing more than 90% vehicular coverage. The reinforcement-learning-based SGNC achieves stable allocation behavior, successfully managing 10 antennas and 120 total resources, and maintaining efficient operation when the system exceeds 70% capacity by reallocating resources dynamically through the $\lambda$-based alert mechanism. Compared with static allocation, the proposed method improves resource efficiency and coverage consistency under varying traffic demand, demonstrating its potential for scalable V2I deployment in next-generation intelligent transportation systems. Full article

While research on high-incidence tumors such as breast, prostate, and lung cancer has led to significant increases in patient survival in recent years, this has not been the case for low-incidence tumors such as high-grade gliomas, the most common and lethal brain tumors, for which the last significant therapeutic advance dates back to 2005. The high infiltration capacity of these tumors into normal brain tissue essential for both vegetative and relational life, the tumor microenvironment, with poor immunological activity, the multiple resistance mechanisms, and the unattractiveness of research investments due to the limited number of patients have made, and continue to make, the path to achieving significant improvements in the survival of patients with high-grade gliomas long and arduous. The objective of this article is to update the slow but continuous radiotherapeutic progress for adult and pediatric high-grade gliomas to the second half of 2023. We analyzed the progress of preclinical and clinical research on both adult and pediatric high-grade gliomas, with a particular focus on improvements in radiotherapy. Interactions between non-radiant new therapies and radiotherapy were also covered. A literature search was conducted in PubMed using the terms (“glioma* and radio*”) and the time limit of 1 July 2023 to 31 December 2023. The inclusion and exclusion criteria for the review were relevance to advances in radiotherapy for high-grade gliomas in adults and children. Treating patients with advanced disease progression only, using “historical” data as controls, as well as repurposing drugs developed for purposes completely different from their intended use, were the major (but not the only) methods to assess risk of bias in the included studies. The effect measures used in the synthesis or presentation of the results were tabulated and/or displayed in figures. A total of 100 relevant references were reviewed. Advances in preclinical studies and in clinical radiotherapy treatment planning, innovative fractionation, use of radioisotopes/radiopharmaceuticals, radiosensitization procedures, and radiation-induced damage were focused on. While this analysis may be limited by the relatively short publication period, high-grade glioma research remains impacted, especially at the clinical level, by potential issues with trial design, such as treating patients with advanced disease progression, using “historical” data as controls, and repurposing drugs developed for completely different purposes than intended. Addressing these aspects of high-grade glioma research could improve its efficacy, which often remains low despite the associated costs. Full article

Fibroblasts play a fundamental role in maintaining tissue architecture, regulating repair processes, and adapting to metabolic and inflammatory stress. Increasing evidence indicates that endogenous bioelectrical states contribute to gene expression regulation and cellular homeostasis. In this study, we investigated the effects of Radio Electric Asymmetric Conveyer (REAC) Metabolic Optimization–Inside Blue Zone (MO-IBZ) treatment on key regulators of stress response and metabolic control in human foreskin fibroblasts (HFF-1). Cells were exposed to nine standardized REAC MO-IBZ sessions, and changes in gene and protein expression were evaluated. Quantitative RT-PCR revealed a significant downregulation of SIRT1 and an upregulation of PPAR-γ expression in treated cells compared with untreated controls. These findings indicate molecular changes involving stress-responsive and metabolic regulatory pathways; however, they should be interpreted primarily as transcriptional signatures, as no direct functional stress-response or metabolic assays were performed. Immunofluorescence analysis showed visually increased expression of mTOR, IGF-1 receptor, and cytochrome c in REAC-treated fibroblasts, supporting a qualitative indication of activation of pathways associated with anabolic signaling, mitochondrial function, and metabolic efficiency. Taken together, these findings indicate that REAC MO-IBZ induces a coordinated molecular profile compatible with changes in cellular metabolic regulatory capacity. Within the framework of current bioelectrical literature, these changes may plausibly reflect broader regulatory adaptations; however, the present work does not provide direct measurements of bioelectrical parameters, functional metabolic activity, or epigenetic regulation, and therefore such interpretations remain speculative. These results provide descriptive mechanistic evidence supporting further investigation of REAC-based bioelectrical modulation as a potential strategy to influence cellular pathways involved in metabolic balance and tissue repair, encouraging future studies incorporating direct bioelectrical, epigenetic, and functional analyses. Full article

Despite several efforts to investigate the accretion disk and torus, near-simultaneous broadband studies of the nuclear regions of radio-quiet AGNs remain lacking. NGC 4151, one of the closest and brightest Seyfert galaxies, provides an excellent laboratory for probing the circum-nuclear regions of AGNs. A detailed, near-simultaneous broadband spectral study of NGC 4151 is carried out during one of its historic minimum activity states, using archival data from the Ultraviolet (UV) to the Infrared (IR) regions. We used the radiative transfer code SKIRT to model the source and to constrain the properties of the torus. We found that the observed broadband spectral energy distribution is best explained by a two-torus geometry with a polar conical shell structure. Full article

Medical imaging is an indispensable tool in clinical diagnosis and therapeutic decision-making, encompassing a wide range of modalities such as radiography, ultrasound, CT, and MRI. With the rapid advancement of deep learning technologies, significant progress has been made in medical image analysis. However, existing deep learning methods are often limited by dataset size, which can lead to overfitting, while traditional approaches relying on hand-crafted features lack specificity and fail to fully capture complex pathological information. To address these challenges, we propose RadioGuide-DCN, an innovative radiomics-guided decorrelated classification network. Our method integrates radiomics features as prior information into deep neural networks and employs a feature decorrelation loss mechanism combined with an anti-attention feature fusion module to effectively reduce feature redundancy and enhance the model’s capacity to capture both local details and global patterns. Specifically, we utilize a Kolmogorov–Arnold Network (KAN) classifier with learnable activation functions to further boost performance across various medical imaging datasets. Experimental results demonstrate that RadioGuide-DCN achieves an accuracy of 93.63% in BUSI image classification and consistently outperforms conventional radiomics and deep learning methods in multiple medical imaging classification tasks, significantly improving classification accuracy and AUC scores. Our study offers a novel paradigm for integrating deep learning with traditional imaging approaches and holds broad clinical application potential, particularly in tumor detection, image classification, and disease diagnosis. Full article

This work presents an experimental evaluation of a high-speed analog-to-digital conversion method based on passive reference waveform crossings combined with time-to-digital converter (TDC) time-tagging. Unlike conventional level-crossing event-driven analog-to-digital converters (ADCs) that require dynamically updated digital-to-analog converters (DACs), the proposed architecture compares the input waveform against a broadband periodic sampling function without active threshold control. Crossing instants are detected by a high-speed comparator and converted into rising and falling edge timestamps using a multi-channel TDC. A commercial ScioSense GPX2-based time-tagger with 30 ps single-shot precision was used for validation. A range of test signals—including 5 MHz sine, sawtooth, damped sine, and frequency-modulated chirp waveforms—were acquired using triangular, sinusoidal, and sawtooth sampling functions. Stroboscopic sampling was demonstrated using reference frequencies lower than the signal of interest, enabling effective undersampling of periodic radio frequency (RF) waveforms. The method achieved effective bandwidths approaching 100 MHz, with amplitude reconstruction errors of 0.05–0.30 RMS for sinusoidal signals and 0.15–0.40 RMS for sawtooth signals. Timing jitter showed strong dependence on the relative slope between the acquired waveform and sampling function: steep regions produced jitter near 5 ns, while shallow regions exhibited jitter up to 20 ns. The study has several limitations, including the bandwidth and dead-time constraints of the commercial TDC, the finite slew rate and noise of the comparator front-end, and the limited frequency range of the generated sampling functions. These factors influence the achievable timing precision and reconstruction accuracy, especially in low-gradient signal regions. Overall, the passive waveform-crossing method demonstrates strong potential for wideband, sparse, and rapidly varying signals, with natural scalability to multi-channel systems. Potential application domains include RF acquisition, ultra-wideband (UWB) radar, integrated sensing and communication (ISAC) systems, high-speed instrumentation, and wideband timed antenna arrays. Full article

Background/Objectives: The enhancement of antitumor immune responses by radiotherapy (RT) is partially attributed to the activation of the IFN-type-I pathway. However, the loss of HLA-class-I molecules, which occurs in a large percentage of non-small-cell lung cancers (NSCLCs), may block the cytotoxic effect of T-cells and immunotherapy (IO). Moreover, autophagy is also involved in HLA downregulation. We investigated the complex interactions between RT, HLA molecules, autophagy, and IFN-type-I responses. Methods: The A549, H1299, and ATG7-deficient NSCLC cell lines, along with the modified shLC3A H1299 cell line, were used for in vitro experiments. The effect of RT (8 and 3 × 8 Gy) on Interferon beta (IFNβ), IFN-stimulated genes (ISGs), and HLA-class-I expression in combination with IFN-type-I-response inhibitors (Ruxolitinib, Tofacitinib, Amlexanox) targeting the JAK and TBK1 was studied with Flow cytometry and RT-PCR. Results: RT significantly induced HLA-class-I expression. A parallel upregulation of IFNβ and ISGs mRNA levels was also documented. Although the IFN-type-I-response inhibitors suppressed the RT-induced IFNβ and ISGs expression, their effect on HLA-class-I expression was minimal. Blockage of LC3A autophagy (shLC3A cell line) significantly upregulated HLA-class-I basal levels, and RT further enhanced HLA expression. IFN-type-I-response inhibitors blocked the RT-inductive effect in the shLC3A H1299, but had no effect in the ATG7-deficient H1650 cell line. Conclusions: The current study supports the theory that baseline autophagy, RT-induced autophagy blockage, and IFN-type-I response enhancement define the HLA-class-I levels in NSCLC cells. This complex interplay emerges as a promising target for the development of radio-vaccination strategies to enhance the efficacy of radio-immunotherapy. Full article

Radionuclide-based molecular imaging modalities are active and developing areas of functional and molecular diagnosis. Among the radionuclides used for SPECT imaging in oncology, ^99mTc is a leading candidate for radiolabeling. At present, a sufficient number of complexons for ^99mTc have been described; however, the development of effective delivery systems for this isotope to the area of interest is a complex research task. The use of tumor-targeting molecules as carriers for radioactive tracers is an effective strategy that has enabled the development of many novel radiopharmaceuticals for cancer imaging. Background: To date, a number of studies have shown tumorotropicity of tetrapyrrole compounds to tumor tissues, in particular derivatives of natural chlorophyll A. Methods: Purification was performed using solid-phase extraction. Assessment of radiochemical yield and purity was performed via radio-ITLC. The in vitro tumor cell accumulation was assessed using SKOV-3 and A-431 cell lines. Dose-dependent biodistribution was evaluated in Nu/J mice bearing epidermoid carcinoma (A-431) xenografts. Results: In this work, we obtained complexes with ^99mTc based on water-soluble carboxylate chlorin e₆ derivatives in order to evaluate their potential for use as SPECT radiopharmaceuticals. We performed radiolabelling optimization of a series of the novel chlorins and primary preclinical studies, including an assessment of the effect of their lipophilicity and charge on tumor uptake. Conclusions: Modification of the periphery of the chlorin macrocycle with chelating groups allows for complexing a wide range of metals, including ^99mTc, which can be used for targeted delivery of the radionuclide to the area of interest. Full article

To enhance the monitoring and conservation efforts for China’s Class II endangered species, specifically the wild giant salamander and its ecosystems, this study addresses the urgent need to counteract the rapid decline of its wild population caused by habitat loss and insufficient surveillance. We present an innovative localization system based on passive Ultra-High-Frequency Radio Frequency Identification (UHF RFID) technology, employing a Double-Transform (D-Tr) methodology that integrates an enhanced 3D LANDMARC algorithm with GAIN generative adversarial networks. This system effectively reconstructs missing Received Signal Strength Indicator (RSSI) data due to environmental barriers by applying a log-distance path loss model. The D-Tr framework simultaneously generates RSSI sequences alongside their first-order differential characteristics, allowing for a comprehensive analysis of spatiotemporal signal relationships. Field tests conducted in the Hubei Xianfeng Zhongjian River Giant Salamander National Nature Reserve reveal that the positioning error consistently remains within 10 cm, with average accuracy improvements of 20.075%, 15.331%, and 12.925% along the X, Y, and Z axes, respectively, compared to traditional time-series models such as long short-term memory (LSTM) and gated recurrent unit (GRU). This system, designed to investigate the behavioral patterns and movement paths of farmed giant salamanders, achieves centimeter-level tracking of their cave-dwelling activities. It provides essential technical support for quantitatively assessing their daily activity patterns, habitat choices, and population trends, thereby promoting a shift from passive oversight to proactive monitoring in the conservation of endangered species. Full article

Perseus A (3C 84), a powerful radio source located at the centre of the giant elliptical galaxy NGC 1275—classified as a Seyfert type II AGN and the dominant member of the X-ray bright Abell 426 cluster–exhibits radio emission variability over a wide range of timescales, from decades to hours. This study investigates intraday variability (IDV) in the 6.5 GHz radio emission of 3C 84 using the RT-32 radio telescope in Zolochiv, Ukraine. A novel low-amplitude azimuthal scanning method enabled quasi-simultaneous measurements of antenna and system temperatures, allowing for separation of intrinsic source variations from propagation effects. During an observation session in August 2021, a burst with a peak intensity of 13.5 Jy above the background was detected, likely corresponding to a Fast Radio Burst (FRB). Additionally, quasi-periodic low-amplitude variations with timescales from 0.3 to 6 h were observed. These fluctuations correlate strongly with local atmospheric changes, such as dew formation on the telescope structure, and, to a lesser extent, with ionospheric acoustic–gravity waves. The findings highlight the importance of accounting for propagation conditions when interpreting short-timescale radio variability in AGNs and suggest the need for multi-station, multi-frequency monitoring campaigns to distinguish between intrinsic and environmental modulation of AGN flux densities. Full article

Background/Objectives: Overactivation of the HGF/c-MET pathway is implicated in various cancers, making its inhibition a promising therapeutic strategy. While several MET-targeting agents are currently approved or in advanced clinical development, patient selection often relies on invasive tissue-based assays. The development of a specific c-MET radioligand for PET imaging and radioligand therapy represents a non-invasive alternative, enabling real-time monitoring of target expression and offering a pathway to personalized treatment. Methods: Radiosynthesis of [⁶⁸Ga]Ga-DOTA-EMP100 was performed using a GMP-certified ⁶⁸Ge/⁶⁸Ga generator connected to an automated synthesis module. The radiopharmaceutical production was optimized by scaling down the amount of DOTA-EMP-100 from 50 to 20 μg. Synthesis efficiency and release criteria were assessed according to Ph. Eur. for all the final products by evaluating radiochemical yield (RY%), radiochemical purity, presence of free gallium (by Radio-UV-HPLC) and gallium colloids (by Radio-TLC), molar activity (Am), chemical purity, pH, and LAL test results. Results: An optimized formulation of [⁶⁸Ga]Ga-DOTA-EMP-100, using 40 μg of precursor, provided the best outcome in terms of radiochemical performance. Process validation across three independent productions confirmed a consistent radiochemical yield of 64.5% ± 0.5, high radiochemical purity (>99.99%), and a molar activity of 53.41 GBq/µmol ± 0.8. Conclusions: [⁶⁸Ga]Ga-DOTA-EMP-100 was successfully synthesized with high purity and reproducibility, supporting its potential for multi-dose application in clinical PET imaging and targeted radioligand therapy. Full article

Cancer therapy resistance emerges from highly integrated molecular systems that enable tumor cells to evade cell death and survive cytotoxic therapeutic stress. High Mobility Group Box 1 (HMGB1) is increasingly gaining recognition as a central coordinator of these resistance programs. This review delineates how HMGB1 functions as a molecular switch that dynamically redistributes between cellular compartments in response to stress, with each localization enabling a distinct layer of resistance. In the nucleus, HMGB1 enhances chromatin accessibility and facilitates the recruitment of DNA repair machinery, strengthening resistance to radio- and chemotherapeutic damage. Cytosolic HMGB1 drives pro-survival autophagy, maintains redox stability, and modulates multiple regulated cell death pathways, including apoptosis, ferroptosis, and necroptosis, thereby predominantly shifting cell-fate decisions toward survival under therapeutic pressure. Once released into the extracellular space, HMGB1 acts as a damage-associated molecular pattern (DAMP) that activates key pro-survival and inflammatory signaling pathways, establishing microenvironmental circuits that reinforce malignant progression and therapy escape. HMGB1 further intensifies resistance through upregulation of multidrug resistance transporters, amplifying drug efflux. Together, these compartmentalized functions position HMGB1 as a central node in the networks of cancer therapy resistance. Emerging HMGB1-targeted agents, ranging from peptides and small molecules to receptor antagonists and nanoformulations, show promise in reversing resistance, but clinical translation will require precise, context- and redox-informed HMGB1 targeting to overcome multifactorial resistance program in refractory cancers. Full article