Search Results (3,135)

The presence of sea ice threatens low ice-class vessels’ navigation safety in the Arctic, and traditional Navigation Risk Assessment Models based on sea ice parameters have been widely used to guide safe passages for ships operating in ice regions. However, these models mainly rely on empirical coefficients, and the accuracy of these models in identifying sea ice navigation risk remains insufficiently validated. Therefore, under the binary classification framework, this study used Automatic Identification System (AIS) data along the Northeast Passage (NEP) as positive samples, manual interpretation non-navigable data as negative samples, a total of 10 machine learning (ML) models were employed to capture the complex relationships between ice conditions and navigation risk for Polar Class (PC) 6 and Open Water (OW) vessels. The results showed that compared to traditional Navigation Risk Assessment Models, most of the 10 ML models exhibited significantly improved classification accuracy, which was especially pronounced when classifying samples of PC6 vessel. This study also revealed that the navigability of the East Siberian Sea (ESS) and the Vilkitsky Strait along the NEP is relatively poor, particularly during the month when sea ice melts and reforms, requiring special attention. The navigation risk output by ML models is strongly determined by sea ice thickness. These findings offer valuable insights for enhancing the safety and efficiency of Arctic maritime transport. Full article

High-precision positioning is the foundation for the functionality of various intelligent agents. In complex environments, such as urban canyons, relative pose estimation using cameras is a crucial step in high-precision positioning. To take advantage of the ability of an inertial measurement unit (IMU) to provide relatively accurate gravity prior information over a short period, we propose a minimal solution method for the relative pose estimation of a stereo camera system assisted by the IMU. We rigidly connect the IMU to the camera system and use it to obtain the rotation matrices in the roll and pitch directions for the entire system, thereby reducing the minimum number of corresponding points required for relative pose estimation. In contrast to classic pose-estimation algorithms, our method can also calculate the camera focal length, which greatly expands its applicability. We constructed a simulated dataset and used it to compare and analyze the numerical stability of the proposed method and the impact of different levels of noise on algorithm performance. We also collected real-scene data using a drone and validated the proposed algorithm. The results on real data reveal that our method exhibits smaller errors in calculating the relative pose of the camera system compared with two classic reference algorithms. It achieves higher precision and stability and can provide a comparatively accurate camera focal length. Full article

Accurate fire source location in an aircraft cargo compartment cannot be determined by common design practices. This study proposes an advanced fire location inversion framework based on a Convolutional Long-Short-Term Memory (ConvLSTM) network. A self-designed interpolation preprocessing module is introduced to realize the integration of spatial and temporal sensor data. The model was trained and validated using a comprehensive database generated from large-scale fire dynamics simulations. Hyperparameter optimization, including a learning rate of 0.001 and a 5 × 5 convolution kernel size, can effectively avoid the systematic errors introduced by interpolation preprocessing, further enhancing model robustness. Validation in simplified scenarios demonstrated a mean squared error of 0.0042 m and a mean positional deviation of 0.095 m for the fire source location. Moreover, the present study assessed the model’s timeliness and reliability in full-scale cabin complex scenarios. The model maintained high performance across varying heights within cargo compartments, achieving a correlation coefficient of 0.99 and a mean absolute relative error of 1.9%. Noteworthily, reasonable location accuracy can be achieved with a minimum of three detectors, even in obstructed environments. These findings offer a robust tool for enhancing fire safety systems in aviation and other similar complex scenarios. Full article

Hundreds of Japanese features of war (field positions, tunnels, and fortifications) were constructed in Hong Kong during World War II. However, most of them were poorly documented and were left unknown but still in relatively good condition because of their durable design, workmanship, and remoteness. These features of war form parts of Hong Kong’s brutal history. Conservation, at least in digital form, is worth considering. With the authors coming from multidisciplinary and varied backgrounds, this paper aims to explore these features using a scientific workflow. First, we reviewed the surviving archival sources of the Imperial Japanese Army and Navy. Second, airborne LiDAR data were used to form territory digital terrain models (DTM) based on the Red Relief Image Map (RRIM) for identifying suspected locations. Third, field expeditions of searching for features of war were conducted through guidance of Global Navigation Satellite System—Real-Time Kinetics (GNSS-RTK). Fourth, the found features were 3D-laser scanned to generate mesh models as a digital archive and validate the findings of DTM-RRIM. This study represents a reverse-engineering effort to reconstruct the planned Japanese defense tactics of guerilla fight and Kamikaze grottos that were never used in Hong Kong. Full article

This paper presents a novel approach to determine dynamic safety and comfort zones in human–robot interactions (HRIs), with a focus on service robots operating in dynamic environments with people. The proposed proxemic model leverages the golden ratio-based comfort zone distribution and ISO safety standards to define adaptive proxemic boundaries for robots around humans. Unlike traditional fixed-threshold approaches, this novel method proposes a gradual and context-sensitive modulation of robot behaviour based on human position, orientation, and relative velocity. The system was implemented on an NVIDIA Jetson Xavier NX platform using a ZED 2i stereo depth camera Stereolabs, New York, USA and tested on two mobile robotic platforms: Go1 Unitree, Hangzhou, China (quadruped) and Scout Mini Agilex, Dongguan, China (wheeled). The initial verification of proposed proxemic model through experimental comfort validation was conducted using two simple interaction scenarios, and subjective feedback was collected from participants using a modified Godspeed Questionnaire Series. The results show that the participants felt comfortable during the experiments with robots. This acceptance of the proposed methodology plays an initial role in supporting further research of the methodology. The proposed solution also facilitates integration into existing navigation frameworks and opens pathways towards socially aware robotic systems. Full article

In this research work, the authors propose an approach for analyzing a traffic accident involving a motorcycle and a pedestrian. The study was conducted under the condition that there are objects in the accident area that limit the visibility of the participants. For this purpose, a three-dimensional simulation model was developed to determine the relative positions of the pedestrian and the motorcycle-driver system at discrete moments, examining the period of time from the moment the pedestrian steps onto the roadway to the moment of contact between the participants. Data from a real traffic accident were used. Full article

Energy is a critical resource, and its optimization is central to sustainable building design. Occupant comfort, significantly influenced by factors, including mean radiant temperature (MRT), alongside air temperature, velocity, and humidity, is another key consideration. This paper introduces a hybrid crow search optimization (CSA) and penguin search optimization algorithm (PeSOA), termed (HCRPN), designed to simultaneously optimize building energy consumption and achieve MRT levels conducive to thermal comfort by adjusting HVAC system parameters. We first validate HCRPN using ZDT-1 and Shaffer N1 multi-objective benchmarks. Subsequently, we employ EnergyPlus simulations, utilizing a single-objective Particle Swarm Optimization (PSO) for initial parameter analysis to generate a dataset. Following correlation analyses to understand parameter relationships, we implement our hybrid multi-objective approach. Comparative evaluations against state-of-the-art algorithms, including MoPso, NSGA-II, hybrid Nsga2/MOEAD, and Mo-CSA, validated the effectiveness of HCRPN. Our findings demonstrate an average 7% reduction in energy consumption and a 3% improvement in MRT-based comfort relative to existing methods. While seemingly small, even minor enhancements in MRT can have a noticeable positive impact on well-being, particularly in large, high-occupancy buildings. Full article

This article presents an analysis on natural gas heating in residential areas, focusing on two primary systems: (1) local heating, where piped gas is delivered directly to individual dwellings equipped with autonomous gas boilers, and (2) district heating, where gas or an alternative fuel powers a central heating plant, and the generated heat is distributed to buildings via a thermal network. The choice between these systems should first consider safety and environmental factors, followed by the urban characteristics of the settlement. In particular, building typology—such as size, function, and spatial configuration—and urban topology, referring to the relative positioning of buildings, play a crucial role. For example, very tall buildings often exclude the use of piped gas due to safety concerns, whereas in other cases, economic efficiency becomes the determining factor. To support decision-making, a comparative cost analysis is conducted, assessing the required infrastructure for both systems, including pipelines, boilers, and associated components. The study identifies representative residential building types in selected urban areas of Serbia and Czechia that are suitable for either heating approach. Additionally, the article examines the broader energy context in both countries, with emphasis on recent developments in the natural gas sector and their implications for urban heating strategies. Full article

Plant growth regulators (PGRs) enhance crop stress resistance but their roles in microbial-mediated phosphorus cycling within intercropping systems are unclear. Thus, We conducted a two-year field study using corn (Zea mays L. cv. Denghai 605) and soybean (Glycine max L. cv. Hedou 22) in fluvisols and luvisols soil according to World Reference Base for Soil Resources (WRB) standard. Under a 4-row corn and 6-row soybean strip intercropping system, three treatments were applied: a water control (CK), and two plant growth regulators—T1 (EC: ethephon [300 mg/L] + cycocel [2 g/L]) and T2 (ED: ethephon [300 mg/L] + 2-Diethyl aminoethyl hexanoate [10 mg/L]). Foliar applications were administered at the V7 stage (seventh leaf) of intercropped corn plants to assess how foliar-applied PGRs (T1/T2) modulated the soil phosphorus availability, microbial communities, and functional genes in maize intercropping systems. PGRs increased the soil organic phosphorus and available phosphorus contents, and alkaline phosphatase activity, but not total phosphorus. PGRs declined the α-diversity in fluvisols soil but increased the α-diversity in luvisols soil. The major taxa changed from Actinobacteria (CK) to Proteobacteria (T1) and Saccharibacteria (T2) in fluvisols soil, and from Actinobacteria/Gemmatimonadetes (CK) to Saccharibacteria (T1) and Acidobacteria (T2) in luvisols soil. Functional gene dynamics indicated soil-specific regulation, where fluvisols soil harbored more phoD (organic phosphorus mineralization) and relA (polyphosphate degradation) genes, whereas phnP gene dominated in luvisols soil. T1 stimulated organic phosphorus mineralization and inorganic phosphorus solubilization in fluvisols soil, upregulating regulation genes, and T2 enhanced polyphosphate synthesis and transport gene expression in luvisols soil. Proteobacteria, Nitrospirae, and Chloroflexi were positively correlated with organic phosphorus mineralization and polyphosphate cycling genes, whereas Bacteroidetes and Verrucomicrobia correlated with available potassium (AP), total phosphorus (TP), and alkaline phosphatase (ALP) activity. Thus, PGRs activated soil phosphorus by restructuring soil type-dependent microbial functional networks, connecting PGRs-induced shifts with microbial phosphorus cycling mechanisms. These findings facilitate the targeted use of PGRs to optimize microbial-driven phosphorus efficiency in strategies for sustainable phosphorus management in diverse agricultural soils. Full article

Ensuring food security necessitates a high level of coordinated development between agricultural trade and production. Based on China’s provincial panel data from 2010 to 2023, this study constructs an evaluation index system for agricultural trade and production, employing an entropy-weighted TOPSIS model to measure their development levels. On this basis, a coupling coordination degree model and Moran’s I indices are used to analyze the coordinated development level’s temporal changes and spatial effects. The research finds that the development levels of China’s agricultural trade and production show an upward trend but currently still exhibit the pattern of higher levels in Eastern China and lower levels in Western China. The coupling coordination level between them demonstrates an increasing trend, yet the overall level remains relatively low, with an average value of only 0.445, consistently staying in a marginal disorder “running-in stage” and spatially presenting a distinct “east-high–west-low” stepped distribution pattern. Furthermore, from a spatial perspective, the Global Moran’s index decreased from 0.293 to 0.280. The coupling coordination degree of agricultural trade and production in China generally exhibits a positive spatial autocorrelation, but this effect has been weakening over time. Most provinces show spatial clustering characteristics of high–high and low–low agglomeration in local space, and this feature is relatively stable. Building on these insights, this study proposes a refinement of the coordination mechanisms between agricultural trade and production, alongside the implementation of differentiated regional coordinated development strategies, to promote the coupled and coordinated advancement of agricultural trade and production. Full article

Background/Objectives: Mycoplasma and Ureaplasma species are pathogens commonly associated with urogenital infections in sexually active individuals. Despite their clinical relevance, these organisms are less frequently studied than other sexually transmitted infections (STIs), leading to limited data on their antimicrobial susceptibility and resistance profiles. This study aimed to characterize the antimicrobial susceptibility and resistance patterns of Mycoplasma hominis and Ureaplasma spp. among individuals in Salvador, Bahia, Brazil, and to identify the potential associated risk factors. Methods: We conducted a retrospective descriptive study during 2022–2024 using secondary data obtained from the SMARTLab^® diagnostic system. Sociodemographic and epidemiological data, along with results from IST2 and IST3 diagnostic tests, were analyzed. Absolute and relative frequencies were calculated by sex, age group, and antimicrobial susceptibility profile. Results: Our results revealed a predominance of M. hominis and Ureaplasma spp. infection among women (98.5%), and in individuals aged 38 to 47 years. Ureaplasma spp. accounted for the majority of positive cases. High rates of resistance were observed in the IST2 test, with 75.0% of M. hominis and 84.1% of Ureaplasma urealyticum resistant to ciprofloxacin. In the IST3 test, Ureaplasma spp. demonstrated a 7.3% resistance rate to levofloxacin, which increased to 22.2% in cases of co-infection. Conclusions: These findings underscore the growing threat of antimicrobial resistance in Mycoplasma and Ureaplasma species and highlight the need for targeted public health strategies and diagnostic tools to manage infections caused by these organisms, particularly in high-risk populations. Full article

Furfural is a fascinating bio-based platform molecule that can be converted into useful cyclic compounds, among others. In this work, the hydrogenative rearrangement-dehydration of furfural towards cyclopentanone using a commercially available Pt/C catalyst was investigated in terms of its reaction performance to assess its feasibility as an industrial process. However, acquiring an acceptable cyclopentanone yield proved very difficult, and the reaction was constrained by unforeseen parameters, such as the relative liquid volume in the reactor and the substrate concentration. Most strikingly, the sacrificial formation of furanoic oligomers that precipitated onto the catalyst’s surface was a troublesome key factor that mediated the product’s selectivity versus the carbon mass balance. By applying a biphasic water–toluene solvent system, the yield of cyclopentanone was somewhat improved to a middling 59%, while tentatively positive distributions of reaction components over these solvent phases were observed, which could be advantageous for anticipated down-stream processing. Overall, the sheer difficulty of controlling this one-pot cascade transformation towards a satisfactory product output under rather unfavorable reaction parameters renders it unsuitable for industrial process development, and a multi-step procedure for this chemical transformation might be considered instead. Full article

The emergence of the Internet of Vehicles (IoV) has revolutionized intelligent transportation and communication systems. However, IoV presents many complex and ever-changing security challenges and thus requires robust cybersecurity protocols. This paper comprehensively describes and evaluates ensemble learning approaches for multi-class intrusion detection systems in the IoV environment. The study evaluates several approaches, such as stacking, voting, boosting, and bagging. A comprehensive review of the literature spanning 2020 to 2025 reveals important trends and topics that require further investigation and the relative merits of different ensemble approaches. The NSL-KDD, CICIDS2017, and UNSW-NB15 datasets are widely used to evaluate the performance of Ensemble Learning-Based Intrusion Detection Systems (ELIDS). ELIDS evaluation is usually carried out using some popular performance metrics, including Precision, Accuracy, Recall, F1-score, and Area Under Receiver Operating Characteristic Curve (AUC-ROC), which were used to evaluate and measure the effectiveness of different ensemble learning methods. Given the increasing complexity and frequency of cyber threats in IoV environments, ensemble learning methods such as bagging, boosting, and stacking enhance adaptability and robustness. These methods aggregate multiple learners to improve detection rates, reduce false positives, and ensure more resilient intrusion detection models that can evolve alongside emerging attack patterns. Full article

Inductive Wireless Power Transfer (WPT) technologies are advancing significantly in the electric vehicle (EV) charging applications. Misalignment between transmitting and receiving coils can considerably affect power transmission efficiency in WPT systems. Prior research involved power electronics as well as electromagnetic couplers. This work focuses on the coil design aspect of electromagnetic couplers. A relatively new concept of Symmetrical Cross Double-D (SCDD) type of the coil design is introduced specifically to maximize tolerance to misalignment while sustaining significant amount of power transferred. Mutual inductance was determined for the perfect alignment and misalignment positions of the SCDD coils. Mutual inductance obtained from the simulation was validated from the experimental measurements. The SCDD electromagnetic coupler demonstrated almost 2.5 times superior tolerance to misalignment of coils compared to the conventional circular coupler while maintaining at least 78% of maximum power transfer even at a lateral misalignment of 40 mm. Full article

The S100B protein, known for its role in the central and enteric nervous systems, has recently been identified in dietary sources such as milk, dairy products, fruits, and vegetables. Given its potential interaction with the gut microbiota, this study explores the relationship between dietary intake of S100B and microbiota biodiversity across different diets. A comprehensive study was conducted, estimating S100B concentrations in 13 dietary patterns recommended in different countries. This is the first study to provide a comparative estimation of S100B exposure from the diet and to explore its potential ecological and epidemiological relevance. The association between S100B levels and microbiota biodiversity was statistically analyzed, showing a direct correlation. Microbial diversity was assessed using the Shannon index, based on data extracted from studies reporting microbiota composition across dietary patterns. Additionally, the relative risk of Crohn’s disease was assessed in different populations to examine potential links between dietary patterns, S100B, and chronic disease prevention. A moderate positive correlation (R² = 0.537) was found between S100B concentration and Shannon index, suggesting that diets higher in S100B (e.g., Mediterranean diet) were associated with higher microbial alpha-diversity. Furthermore, Western-style diets, with the lowest S100B levels, exhibited a higher relative risk for Crohn’s disease (R² = 0.780). These findings highlight the potential role of dietary S100B content in modulating gut microbiota diversity and reducing chronic disease risk. Full article