Search Results (14)

In order to solve the problems of traditional RRT algorithms that are too random in planning, have low planning efficiency, and have insufficient security, this paper proposes an algorithm that fuses APF and the improved bidirectional RRT* algorithm and proposes a heuristic planning strategy to sort multiple target points so that the fusion improvement algorithm can traverse multiple target points with a short path length. This study also aims to improve the RRT* algorithm by using optimization strategies such as bidirectional sampling and adding an adaptive target bias strategy to improve its efficiency in obtaining global paths. The obstacle expansion strategy is used in the APF algorithm to expand the repulsion effect, and the APF algorithm after the obstacle expansion is fused with the improved bidirectional RRT* algorithm, adding gravitational potential field-guided sampling at random points, avoiding local optimum solution, and improving the sampling efficiency while accelerating the acquisition of global paths. The redundant node deletion strategy is introduced to simplify the path, and the repulsive potential field is used to improve the Bezier smoothing method, avoiding collisions caused by path distortion due to smoothing. A multi-target point heuristic planning strategy is proposed to achieve shorter global paths while maintaining shorter local paths, taking into account both local solutions and optimal solutions, so that the fusion algorithm can be applied to the path planning of multi-target points. Full article

Vesicular stomatitis (VS) is a vector-borne livestock disease caused by the vesicular stomatitis New Jersey virus (VSNJV). This study presents the first application of an SEIR-SEI compartmental model to analyze VSNJV transmission dynamics. Focusing on the 2014–2015 outbreak in the United States, the model integrates vertebrate hosts and insect vector demographics while accounting for heterogeneous competency within the populations and observation bias in documented disease cases. Key epidemiological parameters were estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) methods, including the force of infection, effective reproduction number ($R_t$), and incubation periods. The model revealed significant underreporting, with only 10–24% of infections documented, 23% of which presented with clinical symptoms. These findings underscore the importance of including competence and imperfect detection in disease models to depict outbreak dynamics and inform effective control strategies accurately. As a baseline model, this SEIR-SEI implementation is intended to serve as a foundation for future refinements and expansions to improve our understanding of VS dynamics. Enhanced surveillance and targeted interventions are recommended to manage future VS outbreaks. Full article

With the increasing utilization of sampling-based path planning methods in the field of mobile robots, the RRT* algorithm faces challenges in complex indoor scenes, including high sampling randomness and slow convergence speed. To tackle these issues, this paper presents an improved RRT* path-planning algorithm based on the generalized Voronoi diagram with an adaptive bias strategy. Firstly, the algorithm leverages the properties of the generalized Voronoi diagram (GVD) to obtain heuristic paths, and a sampling region with target bias is constructed, increasing the purposefulness of the sampling process. Secondly, the node expansion process incorporates an adaptive bias strategy, dynamically adjusting the step size and expanding direction. This strategy allows the algorithm to adapt to the local environment leading to improved convergence speed. To ensure the generation of smooth paths, the paper employs the cubic spline curve interpolation algorithm for trajectory optimization to ensure that the mobile robotic can obtain the best trajectory. Finally, the proposed algorithm is experimentally compared with existing algorithms, including the RRT* and Informed-RRT* algorithms, to verify the feasibility and stability. Full article

Aiming to address problems such as low sampling success rate and long computation time in the motion planning of a dual-arm cooperative system with multiple constraints, this paper proposes an Informed-Bi-Quick RRT* algorithm based on offline sampling. First, in the process of pre-sampling, the new algorithm relaxes the approximation of constrained manifolds by introducing the idea of incremental construction, and it incorporates the stochastic gradient descent method to replace global random sampling with local random sampling, which enriches the data set and shortens the offline sampling time of the data set. Second, the new algorithm improves the original Quick-RRT* algorithm by combining the two-tree idea and the multi-target bias expansion strategy, and it improves the adaptability of the algorithm to different obstacle environments. In addition, the loosely constrained motion and tightly constrained motion in the two-arm cooperative system are analyzed, and the adaptive planning of the two-arm trajectory in different motions is described in detail. In this paper, the two-arm cooperative model constructed with UR5 and UR10 robot arms is studied, and the ability of the proposed algorithm to deal with multiple constraints is verified by simulating assembly and handling tasks. The experimental results show that compared with other methods, the proposed algorithm has obvious advantages in path quality and planning efficiency. Full article

Sexual and gender minority (SGM) populations experience extensive health disparities compared to their straight and cisgender counterparts. The importance of addressing these disparities is paramount, as SGM groups often encounter significant barriers to accessing comprehensive healthcare, including societal stigma, provider bias, and financial constraints. This study utilizes a community-based system dynamics approach to understand and visualize the barriers to and facilitators of healthcare engagement for SGM groups across their life course. It aims to identify core constructs, relationships, and dynamic feedback mechanisms related to the experiences of connection/disconnection with physical, mental, and dental healthcare of SGM individuals. Barriers to access, such as discriminatory practices and the limited availability of SGM-informed healthcare professionals, exacerbate these disparities, underscoring the urgency of developing targeted interventions. System dynamics, a complex systems science (CSS) methodology, was used for this research. Group model building sessions were conducted with diverse SGM groups, including youth, older adults, and trans and gender-expansive community members. Causal loop diagrams were developed according to an iterative process, and a meta-model of their collective experiences was created. The study revealed extensive, dynamic, and shifting structural barriers for SGM community members accessing healthcare. Societal and structural stigma, provider bias, and pathologization were identified as significant barriers throughout their life course. Community-led interventions and SGM-focused holistic healthcare were identified as critical facilitators of SGM healthcare connection. The findings highlight the need for SGM-affirming and culturally responsive healthcare settings. This paper calls for a concerted effort from SGM health researchers to use CSS in developing interventions to reduce SGM health disparities. Full article

Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios, there exist many complex semantic relationships, which cannot be captured by the meta path. Therefore, a meta structure is proposed, which is a directed acyclic graph of object and relation types. In this paper, we explore the complex semantic meanings in HINs and propose a meta-structure-based similarity measure called StructSim. StructSim models the probability of subgraph expansion with bias from source node to target node. Different from existing methods, StructSim claims that the subgraph expansion is biased, i.e., the probability may be different when expanding from the same node to different nodes with the same type based on the meta structure. Moreover, StructSim defines the expansion bias by considering two types of node information, including out-neighbors of current expanded nodes and in-neighbors of next hop nodes to be expanded. To facilitate the implementation of StructSim, we further designed the node composition operator and expansion probability matrix with bias. Extensive experiments on DBLP and YAGO datasets demonstrate that StructSim is more effective than the state-of-the-art approaches. Full article

For the path planning of quad-rotor UAVs, the traditional RRT* algorithm has weak exploration ability, low planning efficiency, and a poor planning effect. A TD-RRT* algorithm based on target bias expansion and dynamic step size is proposed herein. First, random-tree expansion is combined with the target bias strategy to remove the blindness of the random tree, and we assign different weights to the sampling point and the target point so that the target point can be quickly approached and the search speed can be improved. Then, the dynamic step size is introduced to speed up the search speed, effectively solving the problem of invalid expansion in the process of trajectory generation. We then adjust the step length required for the expansion tree and obstacles in real time, solve the opposition between smoothness and real time in path planning, and improve the algorithm’s search efficiency. Finally, the cubic B-spline interpolation method is used to modify the local inflection point of the path of the improved RRT* algorithm to smooth the path. The simulation results show that compared with the traditional RRT* algorithm, the number of iterations of path planning of the TD-RRT* algorithm is reduced, the travel distance from the starting position to the end position is shortened, the time consumption is reduced, the path route is smoother, and the path optimization effect is better. The TD-RRT* algorithm based on target bias expansion and dynamic step size significantly improves the planning efficiency and planning effect of quad-rotor UAVs in a three-dimensional-space environment. Full article

To solve the problem of false tracks generated by breakdowns and clutter in point-target tracking in polar coordinates, a fusion tracking algorithm based on a converted measurement Kalman filter and random matrix expansion is proposed. The converted measurement Kalman filter (CMKF) transforms the polar coordinate data of the target at the current time into Cartesian coordinates without bias. Based on linear measurements and states, the position of the extended target and the group target was predicted and updated by using a random matrix, and its track was drawn by combining the nearest neighbors to realize the tracking of the size, shape and azimuth of the extended target. Compared with point-target tracking, the accuracy of extended multi-target tracking was increased by 45.8% based on data measured using NAVICO navigation radar aboard ships at sea. The experimental results showed that the improved method in this paper could effectively reduce the interference of clutter on target tracking and provide more information about the target motion features. Full article

Advanced manufacturing is the pillar for building a modern economic system. We measured the level of high-quality development of manufacturing (HQDM) in China, and found that it has gone through the three stages of expansion, cultivation, and promotion. Spatially, it is characterized as “high in the east, low in the west” and “fast in the west, slow in the east”, and presents non-equilibrium characteristics. To overcome the subjective bias introduced by artificially set clubs, we utilize a data-driven nonlinear time-varying factor model for clustering into four convergent clubs, where provinces with higher intensity of environmental regulation and environmental preference tend to move closer to the clubs with a higher level of HQDM. We reveal the convergence patterns and regional differences in HQDM, which provides a new perspective for determining the trends of high-quality manufacturing development, thus allowing for policy recommendations targeted at narrowing the manufacturing development gap. Full article

At frequencies below 1 GHz, conventional microwave absorbers are limited by their large thickness or narrow absorption bandwidth; therefore, new techniques for efficient absorption for the lower microwave band are highly demanded. Here, we propose and fabricate an ultrathin tunable metamaterial absorber combining magnetic nanomaterials and metamaterial resonant structures for use in the lower microwave band (P band). The proposed absorber utilizes electrically controlled varactors to enable frequency tunability and magnetic nanomaterials as dielectric slabs for thickness reduction and bandwidth expansion at low frequencies. By adjusting the bias voltages of varactors, the resonant behavior of the absorbing structure can be dynamically tuned that covers a continuously tunable absorbing band from 0.41 to 1.02 GHz (85.3% in fractional bandwidth) with at least 10 dB reflection reduction. The total thickness of this absorber is 5 mm, which is only about 1/146 the wavelength of the lowest frequency. The agreement between the simulated and measured results validates the proposed design, and the structure has good angular stability that may be used as complex targets for low-RCS applications. Full article

Lyme disease (LD) can have significant consequences for the health of workers. The frequency of infection can be estimated by using prevalence and incidence data on antibodies against Borrelia Burgdoferi (BB). A systematic search of studies published in English between 2002 and 2021 and a meta-analysis were conducted in PubMed/Medline, Web of Science, Scopus, and Google Scholar databases. Out of a total of 1125 studies retrieved, 35 articles were included in the systematic review. Overall, in these studies, outdoor workers showed a 20.5% BB seroprevalence rate. Meta-analysis, performed on 15 studies (3932 subjects), revealed a significantly increased risk in outdoor activities (OR 1.93 95%CI 1.15–3.23), with medium-level heterogeneity (I² = 69.2%), and non-significant publication bias. The estimated OR in forestry and agricultural workers was 2.36 (CI95% 1.28; 4.34) in comparison with the controls, while a non-significant increase in risk (OR = 1.05, CI95% 0.28; 3.88) was found in the remaining categories of workers (veterinarians, animal breeders, soldiers). The estimated pooled risk was significantly higher in the studies published until 2010 (OR 3.03 95%CI 1.39–6.61), while in more recent studies the odds became non-significant (OR 1.08 95% CI 0.63–1.85). The promotion of awareness campaigns targeting outdoor workers in endemic areas, and the implementation of local programs aimed at controlling range expansion of vectors, are key strategies for protecting workers. Full article

Integrated instrumentation packages are an attractive option for environmental and ecological monitoring at marine energy sites, as they can support a range of sensors in a form factor compact enough for the operational constraints posed by energetic waves and currents. Here we present details of the architecture and performance for one such system—the Adaptable Monitoring Package—which supports active acoustic, passive acoustic, and optical sensing to quantify the physical environment and animal presence at marine energy sites. we describe cabled and autonomous deployments and contrast the relatively limited system capabilities in an autonomous operating mode with more expansive capabilities, including real-time data processing, afforded by shore power or in situ power harvesting from waves. Across these deployments, we describe sensor performance, outcomes for biological target classification algorithms using data from multibeam sonars and optical cameras, and the effectiveness of measures to limit biofouling and corrosion. On the basis of these experiences, we discuss the demonstrated requirements for integrated instrumentation, possible operational concepts for monitoring the environmental and ecological effects of marine energy converters using such systems, and the engineering trade-offs inherent in their development. Overall, we find that integrated instrumentation can provide powerful capabilities for observing rare events, managing the volume of data collected, and mitigating potential bias to marine animal behavior. These capabilities may be as relevant to the broader oceanographic community as they are to the emerging marine energy sector. Full article

The NK cell population is characterized by distinct NK cell subsets that respond differently to the various activating stimuli. For this reason, the determination of the optimal cytotoxic activation of the different NK cell subsets can be a crucial aspect to be exploited to counter cancer cells in oncologic patients. To evaluate how the triggering of different combination of activating receptors can affect the cytotoxic responses of different NK cell subsets, we developed a microbead-based degranulation assay. By using this new assay, we were able to detect CD107a⁺ degranulating NK cells even within the less cytotoxic subsets (i.e., resting CD56^bright and unlicensed CD56^dim NK cells), thus demonstrating its high sensitivity. Interestingly, signals delivered by the co-engagement of NKp46 with 2B4, but not with CD2 or DNAM-1, strongly cooperate to enhance degranulation on both licensed and unlicensed CD56^dim NK cells. Of note, 2B4 is known to bind CD48 hematopoietic antigen, therefore this observation may provide the rationale why CD56^dim subset expansion correlates with successful hematopoietic stem cell transplantation mediated by alloreactive NK cells against host T, DC and leukemic cells, while sparing host non-hematopoietic tissues and graft versus host disease. The assay further confirms that activation of LFA-1 on NK cells leads to their granule polarization, even if, in some cases, this also takes to an inhibition of NK cell degranulation, suggesting that LFA-1 engagement by ICAMs on target cells may differently affect NK cell response. Finally, we observed that NK cells undergo a time-dependent spontaneous (cytokine-independent) activation after blood withdrawal, an aspect that may strongly bias the evaluation of the resting NK cell response. Altogether our data may pave the way to develop new NK cell activation and expansion strategies that target the highly cytotoxic CD56^dim NK cells and can be feasible and useful for cancer and viral infection treatment. Full article

The point detections obtained from radars or sonars in surveillance environments include clutter measurements, as well as target measurements. Target tracking with these data requires data association, which distinguishes the detections from targets and clutter. Various algorithms have been proposed for clutter measurement density estimation to achieve accurate and robust target tracking with the point detections. Among them, the spatial clutter measurement density estimator (SCMDE) computes the sparsity of clutter measurement, which is the reciprocal of the clutter measurement density. The SCMDE considers all adjacent measurements only as clutter, so the estimated clutter measurement density is biased for multi-target tracking applications, which may result in degraded target tracking performance. Through the study in this paper, a major source of tracking performance degradation with the existing SCMDE for multi-target tracking is analyzed, and the use of the clutter measurement probability is proposed as a remedy. It is also found that the expansion of the volume of the hyper-sphere for each sparsity order reduces the bias of clutter measurement density estimates. Based on the analysis, we propose a new adaptive clutter measurement density estimation method called SCMDE for multi-target tracking (MTT-SCMDE). The proposed method is applied to multi-target tracking, and the improvement of multi-target tracking performance is shown by a series of Monte Carlo simulation runs and a real radar data test. The clutter measurement density estimation performance and target tracking performance are also analyzed for various sparsity orders. Full article