Search Results (705)

This article analyzes the operating principle of the BMM sensor emitter in order to improve the accuracy of the wireless determination of the BMM sensor coordinates under a massif of destroyed rock in the context of the problem of determining the shift of rocks during gold ore mining. Using numerical simulations, FEM has been developed to develop digital models reflecting individual cases of the propagation of the magnetic field of the emitter located in various geological conditions and positions relative to the rock surface and the vertical axis. The accuracy of determining the coordinates of the radio beacon in the rock has been analyzed, and data on the deviation of the coordinates of the peaks of the magnetic field strength from the radio beacon axis have been obtained in cases of a heterogeneous composition of the rock massif, the influence of the deviation of the emitter axis angle from the vertical, the influence of the unevenness of the collapse relief, and the influence of the superposition of fields from different radiation sources. A study has been carried out to determine the direction of the radio beacon search based on the resulting vector of the emitter’s magnetic field strength. Full article

In outdoor environments, GNSS is commonly used for vehicle navigation and various location-based ITS services. However, in GNSS shadow roads such as tunnels and underground highways, it is challenging to provide these services. With the rapid expansion of GNSS shadow roads, the need for radio positioning technology that can serve the role of GNSS in these areas has become increasingly important to provide accurate vehicle navigation and various location-based ITS services. This paper proposes a new GNSS shadow road radio positioning technology using multidirectional BLE beacon signals. The structure of a multidirectional BLE beacon that radiates different BLE beacon signals in two or four directions is introduced, and explains the principle of differential RSSI technology to determine the vehicle’s location using these signals. Additionally, the technology used to determine the vehicle’s speed is described. A testbed was constructed to verify the performance of the developed multidirectional BLE beacon-based radio navigation system. The current status and future plans of the testbed installation are introduced, and the results of position and speed experiments using the testbed for constant speed and deceleration driving are presented. Full article

Accurate localization plays a critical role in enabling underwater vehicle autonomy. In this work, we develop a robust infrastructure-based localization framework that estimates the position and orientation of underwater vehicles using only range measurements from long baseline (LBL) acoustic beacons to multiple on-board receivers. The proposed framework integrates three key components, each formulated as a convex optimization problem. First, we introduce a robust calibration function that unifies multiple sources of measurement error—such as range-dependent degradation, variable sound speed, and latency—by modeling them through a monotonic function. This function bounds the true distance and defines a convex feasible set for each receiver location. Next, we estimate the receiver positions as the center of this feasible region, using two notions of centrality: the Chebyshev center and the maximum volume inscribed ellipsoid (MVE), both formulated as convex programs. Finally, we recover the vehicle’s full 6-DOF pose by enforcing rigid-body constraints on the estimated receiver positions. To do this, we leverage the known geometric configuration of the receivers in the vehicle and solve the Orthogonal Procrustes Problem to compute the rotation matrix that best aligns the estimated and known configurations, thereby correcting the position estimates and determining the vehicle orientation. We evaluate the proposed method through both numerical simulations and field experiments. To further enhance robustness under real-world conditions, we model beacon-location uncertainty—due to mooring slack and water currents—as bounded spherical regions around nominal beacon positions. We then mitigate the uncertainty by integrating the modified range constraints into the MVE position estimation formulation, ensuring reliable localization even under infrastructure drift. Full article

This paper presents a hybrid indoor localization framework combining time difference of arrival (TDoA) measurements with a swarm intelligence optimization technique. To address the nonlinear optimization challenges in three-dimensional (3D) indoor localization via TDoA measurements, we systematically evaluate the artificial bee colony (ABC) algorithm and chimpanzee optimization algorithm (ChOA). Through comprehensive Monte Carlo simulations in a cubic 3D environment with eight beacons, our comparative analysis reveals that the ChOA achieves superior localization accuracy while maintaining computational efficiency. Building upon the ChOA framework, we introduce a multi-beacon fusion strategy incorporating a local outlier factor-based linear weighting mechanism to enhance robustness against measurement noise and improve localization accuracy. This approach integrates spatial density estimation with geometrically consistent weighting of distributed beacons, effectively filtering measurement outliers through adaptive sensor fusion. The experimental results show that the proposed algorithm exhibits excellent convergence performance under the condition of a low population size. Its anti-interference capability against Gaussian white noise is significantly improved compared with the baseline algorithms, and its anti-interference performance against multipath noise is consistent with that of the baseline algorithms. However, in terms of dealing with UWB device failures, the performance of the algorithm is slightly inferior. Meanwhile, the algorithm has relatively good time-lag performance and target-tracking performance. The study provides theoretical insights and practical guidelines for deploying reliable localization systems in complex indoor environments. Full article

Directed grey-box fuzzers focus on testing specific target code. They have been utilized in various security applications, such as reproducing known crashes and identifying vulnerabilities resulting from incomplete patches. Distance-guided directed fuzzers calculate the distance to the target node for each node in a CFG or CG, which has always been the mainstream in this field. However, the distance can only reflect the relationship between the current node and the target node, and it does not consider the impact of the reaching sequence before the target node. To mitigate this problem, we analyzed the properties of the instrumented function’s call graph after selective instrumentation, and the complexity of reaching the target function sequence was estimated. Assisted by the sequence complexity, we proposed a two-stage function call sequence-based seed-scheduling strategy. The first stage is to select seeds with a higher probability of generating test cases that reach the target function. The second stage is to select seeds that can generate test cases that meet the conditions for triggering the vulnerability as much as possible. We implemented our approach in SEZZ based on SelectFuzz and compare it with related works. We found that SEZZ outperformed AFLGo, Beacon, WindRanger, and SelectFuzz by achieving an average improvement of 13.7×, 1.50×, 9.78×, and 2.04× faster on vulnerability exposure, respectively. Moreover, SEZZ triggered three more vulnerabilities than the other compared tools. Full article

The rapid expansion of deep-sea sensing networks underscores the critical need for accurate underwater positioning of observation base stations. However, achieving precise acoustic localization, particularly at depths exceeding 4 km, remains a significant challenge due to systematic ranging errors, clock drift, and inaccuracies in sound speed modeling. This study proposes and validates a three-tier calibration framework consisting of a Dynamic Single-Difference (DSD) solver, a geometrically optimized reference buoy selection algorithm, and a Virtual Beacon (VB) depth inversion method based on sound speed profiles. Through simulations under varying noise conditions, the DSD method effectively mitigates common ranging and clock errors. The geometric reference optimization algorithm enhances the selection of optimal buoy layouts and reference points. At a depth of 4 km, the VB method improves vertical positioning accuracy by 15% compared to the DSD method alone, and nearly doubles vertical accuracy compared to traditional non-differential approaches. This research demonstrates that deep-sea underwater target calibration can be achieved without high-precision time synchronization and in the presence of fixed ranging errors. The proposed framework has the potential to lower technological barriers for large-scale deep-sea network deployments and provides a robust foundation for autonomous deep-sea exploration. Full article

Background/Objectives: Antibiotic resistance presents an urgent public health threat. By developing a streamlined and effective method for studying bacteriophage induction, this research marks a step further in understanding how antibiotic-resistant genes might spread across different environments. This knowledge is essential for creating strategies to reduce the spread of antimicrobial resistance (AMR), particularly from a One Health perspective. In this study, we develop and validate a Green Fluorescent Protein (GFP)-based method as a proxy for bacteriophage induction. This method screens compounds for their potential to promote bacteriophage induction. Methods: This study utilized a recA-GFP construct in Escherichia coli to measure fluorescence as an indicator of SOS response activation. The experiments involved treating E. coli cultures with varying concentrations of the DNA-damaging chemical mitomycin C and measuring fluorescence over time. Additionally, droplet digital PCR (ddPCR) quantified bacteriophage induction in a lambda phage-carrying E. coli strain, allowing for correlation analysis between the two methods. Results: The recA-driven SOS response depended on both dose and time, with increasing concentrations of mitomycin C leading to higher fluorescence. ddPCR analysis confirmed that mitomycin C induced prophage activation, with gene ratios increasing at higher drug concentrations over time. A strong Spearman correlation (>0.7) was noted between fluorescence and ddPCR results at elevated concentrations and relevant time points, indicating the validity of the GFP-based model as a proxy for bacteriophage induction. Conclusions: The findings demonstrate a strong association between the two methods of measuring phage induction, suggesting that the GFP-based E. coli model is a reliable, cost-effective, and efficient tool for studying phage induction and its potential role in AMR spread. This method could facilitate the screening of environmental samples and specific drugs to evaluate their impact on bacteriophage induction, which opens the door for applications such as screening for antibiotic resistance dissemination. Full article

The emergence of multidrug-resistant (MDR) bacteria and biofilm-associated infections has created a significant hurdle for conventional antibiotics, prompting the exploration of alternative strategies. Photodynamic therapy (PDT), a technique that utilizes photosensitizers activated by light to produce ROS, has emerged as a beacon of hope in the fight against MDR microorganisms. Among the natural photosensitizers, hypocrellins (A and B) have shown remarkable potential with their dual-mode photodynamic action, generating ROS via both Type I (electron transfer) and Type II (singlet oxygen) pathways. This unique action disrupts bacterial biofilms and inactivates MDR pathogens. The amphiphilic nature of hypocrellins further enhances their promise, enabling deep biofilm penetration and ensuring potent antibacterial effects even in hypoxic environments, surpassing the capabilities of synthetic photosensitizers. This study critically examines the antimicrobial properties of hypocrellin-based PDT, emphasizing its mechanisms, advantages over traditional antibiotics, and effectiveness against MDR pathogens. Comparative analysis with other photosensitizers, the role of nanotechnology-enhanced delivery systems, and future clinical applications are explored. Its combination with nanotechnology enhances therapeutic outcomes, providing a viable alternative to conventional antibiotics. Further clinical research is essential to optimize its application and integration into antimicrobial treatment protocols. Full article

The geometric distribution of seabed beacons significantly impacts the positioning accuracy of underwater acoustic navigation systems. To address this challenge, we propose a depth-constrained adaptive stochastic model optimization method based on singular value decomposition (SVD). The method quantifies the contribution weights of each beacon to the dominant navigation direction by performing SVD on the acoustic observation matrix. The acoustic ranging covariance matrix can be dynamically adjusted based on these weights to suppress error propagation. At the same time, the prior depth with centimeter-level accuracy provided by the pressure sensor is used to establish strong constraints in the vertical direction. The experimental results demonstrate that the depth-constrained adaptive stochastic model optimization method reduces three-dimensional RMS errors by 66.65% (300 m depth) and 77.25% (2000 m depth) compared to conventional equal-weight models. Notably, the depth constraint alone achieves 95% vertical error suppression, while combined SVD optimization further enhances horizontal accuracy by 34.2–53.5%. These findings validate that coupling depth constraints with stochastic optimization effectively improves navigation accuracy in complex underwater environments. Full article

The active safety of tractors remains a major concern in rural road environments, where tractor drivers face high crash risks due to limited vehicle visibility. In Serbia, 1.4% of crashes involve tractors, mainly due to poor visibility (64.3%), lack of beacon lights, unsafe overtaking, and unmarked stopped tractors (14.3% each). These issues reduce safety, increase fuel consumption and emissions, and cause economic losses. A driving simulator study with 117 drivers examined how visibility equipment affects speed perception. The results showed that 20 km/h was best estimated with all visibility aids, while 10 km/h was most accurately judged with only the slow-moving vehicle emblem. These findings emphasize the potential for simple, cost-effective visibility measures to enhance the active safety of tractors in mixed rural traffic conditions. By enhancing tractor visibility, these measures reduce crash risks, minimize unnecessary acceleration and deceleration, and lower fuel consumption and emissions associated with traffic disturbances. Furthermore, by preventing crashes, these solutions contribute to reducing resource consumption in crash-related medical care, vehicle repairs, and infrastructure damage. Integrating improved visibility equipment into rural traffic policy can significantly enhance tractors’ active safety and reduce the risk of crashes in agricultural regions. Full article

The optimization of workflows and processes based on available data and observations is very important for gaining efficiency, but is often limited by the amount of available information and the time required to collect it. In this paper we suggest a flexible solution, based on wearable radio beacons and software analysis of their inputs. A prototype of the system was built with NRF52832 smart tags and the Raspberry Pi 4 gateway and data analysis system. Experiments carried out on the first samples indicate that it is indeed possible to seamlessly collect and process information that is then used to optimize various actions, ranging from production to administrative tasks. Full article

This review paper addresses the design and testing of ultra-low temperature (ULT) freezers, highlighting their critical functions in various industries, particularly foods, medicine, and research. ULT freezers operating at temperatures of −86 °C and lower have come a long way with improvements in freezing technology, for instance, from traditional vapor compression systems to new multi-stage refrigeration technologies. This progress has added operational reliability and energy efficiency, essential for preserving delicate samples and facilitating groundbreaking research. The article deeply explores the contribution of refrigerants to ULT freezer efficiency and sustainability. With the use of chlorofluorocarbons (CFCs), previously reliant on them, being prohibited due to environmental concerns, the sector opted for environmentally friendly substitutes like hydrofluorocarbons (HFCs), natural refrigerants, and hydrofluoroolefins (HFOs). Regulatory compliance is ensured by rigid validation protocols to guarantee ULT freezers are safe and meet quality requirements without compromising the integrity of the stored material. In addition to their wide-ranging advantages, ULT freezers also have disadvantages, such as energy efficiency, incorporating automation, the integration of IoT and AI for proactive maintenance, and the development of environmentally sustainable refrigerants. Adequate management strategies, including regular employee training and advanced monitoring systems, are vital to counteract threats from temperature variations and reduce long-term diminished performance. Finally, subsequent innovations in ULT freezer technology will not only aid in research and medical initiatives but also support sustainable practices, ensuring their core role as beacons of innovation in preserving the quality of precious biological materials and increasing public health gains. Full article

This paper addresses the critical challenge of time management in wireless sensor networks (WSNs) applied to industrial process control. Although wireless technologies have gained ground in industrial monitoring, their adoption in control applications remains limited due to concerns around reliability and timing accuracy. This study proposes a practical, low-cost solution based on commercial off-the-shelf (COTS) components, leveraging the IEEE 802.15.4-2020 standard in Time-Slotted Channel-Hopping (TSCH) mode. A custom time management algorithm is developed and implemented on STM32 microcontrollers paired with AT86RF212B transceivers. The proposed system ensures a sub-millisecond synchronization drift across nodes by dividing communication into a structured slot frame and implementing precise scheduling and enhanced beacon-based synchronization. Validation is performed through experimental setups monitored with logic analyzers, demonstrating a time drift consistently below 600 microseconds. The results confirm the feasibility of using synchronized wireless nodes for real-time industrial control tasks, suggesting that further improvements in hardware precision could enable even tighter synchronization and broader applicability in fast and critical processes. Full article

Biodiversity conservation plays a pivotal role in achieving sustainable development and fostering harmonious coexistence between humans and nature. This study identifies avian conservation priority areas across China by analyzing multi-dimensional biodiversity, incorporating species diversity, functional diversity, and phylogenetic diversity. Through systematic conservation planning using Zonation version 4 software, we delineated priority areas across these diversity dimensions. Our results demonstrate a distinct south-to-north diversity gradient in China’s avifauna, with functional and phylogenetic diversity hotspots concentrated in Yunnan Province, the Hengduan Mountains, Hainan Island, Taiwan Island, and southeastern coastal regions. The identified priority conservation areas cover 14.6% of China’s terrestrial territory, protecting 89.8% of the country’s bird species—including 93.5% of endemic species and 88.9% of critically endangered species. Notably, existing nature reserves encompass merely 8.1% of these priority areas, revealing substantial conservation gaps within the current protection framework. Building upon China’s 3C Zoning Framework (Cities and farms, Shared landscapes, and Large wild areas), we propose zone-specific conservation strategies, with particular emphasis on strengthening protected area networks in the eastern coastal regions and the middle-lower Yangtze River basin, where urbanization pressures are most acute. These findings highlight the critical importance of incorporating multi-dimensional diversity in conservation planning and offer novel perspectives for optimizing China’s protected area system. Full article

Since its emergence in the United States in February 2022, Highly Pathogenic Avian Influenza (HPAI) H5N1 has caused significant losses for poultry operations, particularly in Iowa between February 2022 and December 2023. Branta canadensis (Canada goose), an abundant North American waterfowl species, is considered a potential reservoir host for H5N1. This study examined the relationship between Canada goose abundance and H5N1 occurrence in Iowa counties. Although counties with H5N1 cases comprised 13% of the state’s Canada goose population—and 32% of those counties had high goose abundance—an inverse relationship was observed. Bivariate analysis indicated that counties with high goose abundance were significantly less likely to report HPAI cases (χ² = 4.29, p = 0.04). Notably, intermediate goose abundance was associated with a 79% lower likelihood of HPAI occurrence (RR = 0.21, 95% CI [0.05, 0.90], p = 0.04). These findings highlight the limitations posed by the lack of accessible, high-resolution poultry farm location data, which hinders a definitive understanding of Canada geese’s role in H5N1 transmission. To address this gap, stakeholders should consider adopting next-generation surveillance tools like the Biothreats Emergence Analysis and Communication Network (BEACON) AI platform, or AI-integrated chemical sensors that generate real-time, actionable data for biosecurity decision-making. Given the uncertainty surrounding Canada goose role transmission dynamics, the species remains a relevant One Health concern. Full article