Turn Angle Research Articles

VNS-BA*: An Improved Bidirectional A* Path Planning Algorithm Based on Variable Neighborhood Search.

The A* algorithm is an effective method for path planning; however, it has certain drawbacks, such as a high number of turns, low planning efficiency, and redundant searches. To address these issues, this paper proposes an improved bidirectional A* global path planning algorithm based on a variable neighborhood search strategy, named VNS-BA*. The new algorithm first employs an 8-11-13 neighborhood search method for node expansion. Then, the bidirectional search strategy is optimized by using the current nodes of the opposite path and the global target point, enabling the two paths to meet in the middle of the map. Finally, redundant turns are removed from the path, and cubic spline interpolation is applied to achieve local smoothing at the turns. The effectiveness of the improved algorithm was validated on different maps and compared with A* and its three derived improved versions. The simulation results indicate that VNS-BA* shows significant improvements in terms of the number of path turns, turn angles, and planning efficiency.

Investigation of printing turn angle effects on structural deformation and stress in selective laser melting

Additive manufacturing (AM) technology facilitates the creation of complex structures, where the printing path significantly impacts thermal distribution, subsequently influencing stress distribution and structural deformation. The primary challenge in path planning is to determine a printing turn angle that ensures uniform thermal distribution, thereby minimizing structural deformation while maintaining printing efficiency. To address this issue, we propose a composite function, which comprehensively characterizes the effects of the printing turn angle and the length of the printing path on the printing results. Combining a specific cubic porous structure, we calculate the maximum (Pmax) and minimum (Pmin) values of the composite function P, and compare the structural deformation and stress of the Pmax and Pmin paths with those of the typical Pzigzag path. Finite element method (FEM) simulation and experimental validation show that the Pmax path achieves significantly lower structural deformation and residual stress compared to the Pzigzag path and Pmin path.

The statistical building blocks of animal movement simulations.

Animal movement plays a key role in many ecological processes and has a direct influence on an individual's fitness at several scales of analysis (i.e., next-step, subdiel, day-by-day, seasonal). This highlights the need to dissect movement behavior at different spatio-temporal scales and develop hierarchical movement tools for generating realistic tracks to supplement existing single-temporal-scale simulators. In reality, animal movement paths are a concatenation of fundamental movement elements (FuMEs: e.g., a step or wing flap), but these are not generally extractable from a relocation time-series track (e.g., sequential GPS fixes) from which step-length (SL, aka velocity) and turning-angle (TA) time series can be extracted. For short, fixed-length segments of track, we generate their SL and TA statistics (e.g., means, standard deviations, correlations) to obtain segment-specific vectors that can be cluster into different types. We use the centroids of these clusters to obtain a set of statistical movement elements (StaMEs; e.g.,directed fast movement versus random slow movement elements) that we use as a basis for analyzing and simulating movement tracks. Our novel concept is that sequences of StaMEs provide a basis for constructing and fitting step-selection kernels at the scale of fixed-length canonical activity modes: short fixed-length sequences of interpretable activity such as dithering, ambling, directed walking, or running. Beyond this, variable length pure or characteristic mixtures of CAMs can be interpreted as behavioral activity modes (BAMs), such as gathering resources (a sequence of dithering and walking StaMEs) or beelining (a sequence of fast directed-walk StaMEs interspersed with vigilance and navigation stops). Here we formulate a multi-modal, step-selection kernel simulation framework, and construct a 2-mode movement simulator (Numerus ANIMOVER_1), using Numerus RAMP technology. These RAMPs run as stand alone applications: they require no coding but only the input of selected parameter values. They can also be used in R programming environments as virtual R packages. We illustrate our methods for extracting StaMEs from both ANIMOVER_1 simulated data and empirical data from two barn owls (Tyto alba) in the Harod Valley, Israel. Overall, our new bottom-up approach to path segmentation allows us to both dissect real movement tracks and generate realistic synthetic ones, thereby providing a general tool for testing hypothesis in movement ecology and simulating animal movement in diverse contexts such as evaluating an individual's response to landscape changes, release of an individual into a novel environment, or identifying when individuals are sick or unusually stressed.

456 Allocating distribution of pasture utilization across the grazing landscape in grazing steers equipped with virtual fencing collars

Abstract Spatial utilization of pasture landscapes by grazing animals is often heterogeneous and driven by complex environmental and physiological interactions between plants and animals. Synergistic energy pathways can be modeled using mechanistic relationships describing resource distribution, animal behavior, metabolic energy rate, and pasture utilization using biometric sensors. The objective of this study was to demonstrate the ability to measure the energy landscape by mapping fine-scale contributions to animal energy expenditure, nutrient acquisition, growth, and overall economic profitability. We utilized animal trajectories and location fixes recorded by virtual fencing collars (Vence) daily body weight (BW) using precision livestock scales (Smartscale, C-Lock Inc.) and oxygen consumption (GreenFeeds, C-Lock Inc.) on steers (n = 127), managed as part of a broader project to evaluate environmental synergies in extensive grazing systems. Steers were allocated to one of six native grass pastures assigned to either rotational or continuous grazing strategies, and one of three stocking rates (low, moderate, high) in a 2 x 3 factorial arrangement. Space utilization was quantified as the frequency of fixes located within each cell of a 5 x 5-meter Grid and the distance between grid cells and water was calculated using the Pythagorean theorem. Movement behavior was quantified using Program R to calculate step length, the distance between two temporally continuous fix points utilizing the Pythagorean Theorem, and turn angles calculated as the cosine of the pre- and pro-ceeding step lengths where larger values indicated greater deviation from a straight trajectory. A mixed linear regression model was fitted using the lmer function in the lme4 package. Space utilization decreased with increased distance from water (P < 0.05), with rotational grazing strategies increasing concentration around water sources (P < 0.05). This indicates an opportunity to utilize precision livestock technology to facilitate pasture management and increase space utilization in grazing cattle.

Path planning of humanoid robots on complex terrains using an efficient regression-based chaotic Harris Hawks optimization approach

PurposeOptimal navigation and trajectory planning are in high demand because of the rise in automated systems. This study aims to focus on implementing an intelligent regression-based chaotic Harris Hawk optimization (LR-CHHO) to achieve a globally optimal path free from collisions.Design/methodology/approachThis study removes the drawbacks of the existing HHO model in terms of its exploration and exploitation behaviors. After the threat is encountered, the improved controller is activated. The LR tool, here, avoids the issue related to the sensitivity of the model. The virtual Hawks, as per the HHO technique, are generated and trained to enhance the diversity in Hawks population. The final controller then calculates the optimal turn angle for the humanoid to avoid threats before reaching the goal.FindingsModel showed an overall improvement greater than 4% in the path and 9% in time compared with standard models in Terrains 1 and 2. Regarding energy efficiency, a significant improvement of more than 20% in the hip, 14% in the knee and 30% in the ankle was observed on both even and uneven terrains.Originality/valueThe originality of this study focuses on improving the diversity in the HHO population by introducing the LR-based model to help the humanoids find an optimal path to the goal. Although the basic model lacked an optimal solution because of sensitivity, less diversity, etc., the proposed model helped resolve the issue and achieve an optimal turning angle for the humanoids to trace the optimal path.

Solving Advanced Missile Robotic Control Problem Via Integral Rohit transform

The problem of robotic control of an advanced missile requires designing control systems for remote-controlled missiles with sufficient abilities. These control systems need to handle navigation, guidance, propulsion, and potentially other tasks like target acquisition and avoidance of obstacles. The various aspects of missile dynamics are described by complex and non-linear differential equations. Due to this, it becomes difficult to obtain their analytical solutions. During system design and analysis, to solve these complex and non-linear differential equations, numerical techniques like Euler’s technique, the Runge-Kutta technique, or more advanced mathematical techniques are generally used. The advanced missile robotic control problem is one of the problems represented by second-order linear differential equations. In this paper, the integral Rohit transform (RT) has been applied to solve an advanced missile robotic control problem. This transformation has never been applied in working out the advanced missile robotic control problem. This paper applies a new technique for solving the second-order linear differential equation representing the advanced missile robotic control problem to obtain its required turn angle so that it will be able to catch and destroy the attacker. The necessary graphs are plotted to illustrate the numerical solution of the robotic control of an advanced missile. It reveals that the integral Rohit transform (RT) technique is an effective technique to solve the advanced missile robotic control problem.

Exact Mathematical Solution for Maximum Transient Offtracking Calculation of a Single-Unit Vehicle Negotiating Circular Curves

The low-speed turning maneuverability of vehicles is closely related to a well-known offtracking phenomenon which occurs when the rear wheels of a turning vehicle deviate towards the inside of a horizontal curve. Although numerous mathematical models and computer programs for vehicle swept path analysis have been developed in the past, only a few of them can calculate the maximum transient offtracking of a turning vehicle, yet with limited accuracy. The authors were motivated by this fact to find a new mathematical solution for maximum transient offtracking calculation of a single-unit vehicle when negotiating circular curves. In the first stage, a transcendental equation defining vehicle maximum transient offtracking position is derived and numerically solved by Python 3.10.12. In the second stage, the polynomial regression model predicting accurate numerical solutions of the transcendental equation with the desired level of accuracy was developed and tested. The new calculation method is simple enough to simply take the vehicle datum length, circular curve radii, and turn angle, while instantly producing the maximum transient offtracking value, without the need to draw any of the vehicle movement trajectories.

What Goes Around Comes Around: Covering Tours and Cycle Covers with Turn Costs

We investigate several geometric problems of finding tours and cycle covers with minimum turn cost, which have been studied in the past, with complexity, approximation results, and open problems dating back to work by Arkin et al. in 2001. Many new practical applications have spawned variants: For full coverage, all points have to be covered, for subset coverage, specific points have to be covered, and for penalty coverage, points may be left uncovered by incurring a penalty. We show that finding a minimum-turn (full) cycle cover is NP-hard even in 2-dimensional grid graphs, solving the long-standing open Problem 53 in The Open Problems Project edited by Demaine, Mitchell and O’Rourke. We also prove NP-hardness of finding a subset cycle cover of minimum turn cost in thin grid graphs, for which Arkin et al. gave a polynomial-time algorithm for full coverage; this shows that their boundary techniques cannot be applied to compute exact solutions for subset and penalty variants. We also provide a number of positive results. In particular, we establish the first constant-factor approximation algorithms for all considered subset and penalty problem variants for grid-based instances, based on LP/IP techniques. These geometric versions allow many possible edge directions (and thus, turn angles, such as in hexagonal grids or higher-dimensional variants); our approximation factors improve the combinatorial ones of Arkin et al.

Importance of preoperative HRCT temporal bone in the orientation of the cochlea and its relation to intra-operative difficulties in cochlear implantation – predicting the grades of difficulty

Objective: This study emphasizes the role of preoperative high-resolution computed tomography (HRCT) temporal bone in evaluating the variation in cochlear orientation and proposes a grading system to determine the level of intraoperative difficulties encountered. Methods: Preoperative correlation of middle ear and inner ear structures along with the basal turn angle (BTA) was done to assess the orientation. Patients were divided into three groups depending on BTA and radiology findings. Results: Group A (BTA = 55°-60°) had statistically significant (p < 0.05) correlation between middle ear to inner ear structures on HRCT, whereas group B (BTA >60°) and C (BTA <55°) had variations in the alignment of middle ear structures to their corresponding inner ear structures. Conclusion: The association of BTA to the correlation between middle ear and inner ear structures can determine the orientation of the cochlea. This evaluation makes the surgeon aware of intraoperative challenges and helps in surgical planning.

Treed Gaussian processes for animal movement modeling.

Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens (Tympanuchus pallidicinctus) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.

Polystyrene Plastic Particles Result in Adverse Outcomes for Hyalella azteca When Exposed at Elevated Temperatures

Micro- and nano-plastics are pervasive pollutants in global ecosystems, yet their interactions with aquatic wildlife and abiotic factors are poorly understood. These particles are recognized to cause subtle detrimental effects, underscoring the necessity for sensitive endpoints in ecotoxicological exposure studies. We investigated the effects of particle uptake, size, and temperature on Hyalella azteca. Organisms were exposed to blue fluorescent polystyrene beads (500 nm and 1000 nm in diameter) at 0.43 mg/L for 96 h at temperatures mirroring climate predictions (21 °C, 24 °C, 27 °C). Besides survival and growth, particle uptake, visualized via confocal microscopy, and swimming behavior were analyzed. Mortality rates increased at 27 °C, and particle presence and temperature affected organism growth. Particle treatments influenced various behaviors (thigmotaxis, cruising, movement, acceleration, meander, zone alternation, and turn angle), with hypoactivity observed with 1000 nm particles and hypo- as well as hyper-activity responses with 500 nm particles. Particle uptake quantities were variable and increased with temperature in 500 nm treatments, but no migration beyond the gut was observed. Particle size correlated with uptake, and relationships with behavior were evident. Elevated temperatures exacerbated particle effects, highlighting the urgency of addressing plastic pollution in light of climate change for aquatic organism welfare and ecosystem health.

Collision-free path planning for multiple robots using efficient turn-angle assignment

The ability to avoid collisions with moving robots is critical in many applications. Moreover, if the robots have limited battery life, the goal is not only to avoid collisions but also to design efficient trajectories in terms of energy consumption and total mission time. This paper proposes a novel strategy for assigning turn angles for collision-free path planning in scenarios where a small team of robots cooperate in a certain mission. The algorithm allows each robot to reach a predetermined destination safely. It establishes consecutive, short time intervals, and at each interval, possible conflicts are solved centrally in an optimal manner. This is done by keeping constant speeds but generating a discrete set of possible directions for each robot, and solving efficiently the turn-angle allocation for a collision-free path that minimizes the path deviation from the shortest one. Due to the discretization, the final paths are not optimal, but the system can react to possible failures during execution, as conflicts are resolved at each time interval. Computational results and Software-In-The-Loop simulations are presented in order to evaluate the proposed algorithm. A comparison with a state-of-the-art approach shows that our algorithm is more energy-efficient and achieves lower mission completion time.

The Impact of Dual-Tasks and Disease Severity on Posture, Gait, and Functional Mobility among People Living with Dementia in Residential Care Facilities: A Pilot Study.

Gait speed and timed-up-and-go (TUG) predict cognitive decline, falls, and mortality. Dual-tasks may be useful in cognitive screening among people living with dementia (PWD), but more evidence is needed. This cross-sectional study aimed to compare single- and dual-task performance and determine the influence of dementia severity on dual-task performance and interference. Thirty PWD in two residential care facilities (Age: 81.3 ± 7.1 years; Montreal Cognitive Assessment: 10.4 ± 6.0 points) completed two trials of single- (feet apart) and dual-task posture (feet apart while counting backward), single- (walk 4 m) and dual-task gait (walk 4m while naming words), and single- (timed-up-and-go (TUG)), and dual-task functional mobility (TUG while completing a category task) with APDM inertial sensors. Dual-tasks resulted in greater sway frequency, jerk, and sway area; slower gait speed; greater double limb support; shorter stride length; reduced mid-swing elevation; longer TUG duration; reduced turn angle; and slower turn velocity than single-tasks (ps < 0.05). Dual-task performance was impacted (reduced double limb support, greater mid-swing elevation), and dual-task interference (greater jerk, faster gait speed) was related to moderate-to-severe compared to mild PWD. Moderate-to-severe PWD had poorer dynamic stability and a reduced ability to appropriately select a cautious gait during dual-tasks than those with mild PWD, indicating the usefulness of dual-tasks for cognitive screening.

Effect of entomopathogenic fungi on behavior and physiology of Solenopsis invicta (Hymenoptera, Formicidae).

In an ant colony, a large number of nestmates with a similar gene pool coexist, making them more vulnerable to pathogenic attacks. These pathogens influence the behavior and physiology of the fire ant Solenopsis invicta Buren. Here, we evaluated the impact of entomopathogenic fungi (EPF) Metarhizium anisopliae on the behavior (locomotion and foraging) and physiology (biological molecules, anti-fungal activity, and survival) of S. invicta. Distance traveled and velocity significantly decreased, while turn angle and angular velocity significantly increased in ants exposed to a higher concentration of M. anisopliae compared to ants exposed to control after 36 h, which showed disturbed locomotion. Fungus infection significantly affected the foraging behavior of ants. Fungus-exposed ants spent significantly less time in the food zone (area with food) than in the inner zone (area without food). The activities of 4 enzymes, peroxidase, glutathione-S-transferase, hydrogen peroxide (H2O2), and carboxylesterase were significantly decreased. In contrast, catalase and anti-fungal activities were increased after fungal exposure compared to the control. The activity of acetylcholinesterase, which hydrolyses the important neurotransmitter acetylcholine, also decreased after fungal application compared to the control. Survival of ants was also significantly reduced after fungus infection compared to the control. Our findings help to understand the influence of M. anisopliae on the behavior and physiology of S. invicta, which will help in the management of S. invicta using the EPF M. anisopliae.

Whether search directions number affects the efficiency of the path planning algorithm: Taking an improved ACO algorithm with 32 directions for example

An improved Ant Colony Optimization (ACO) algorithm, named IACO, is proposed to address the inherent limitation of slow convergence, susceptibility to local optima and excessive number of inflection in traditional ACO when solving path planning problems. To this end, firstly, the search direction number is expanded from 4 or 8 into 32; Secondly, the distance heuristic information is replaced by an area heuristic function, which deviated from the traditional approach that only considers pheromone information between two points; Then, the influence of path angle and number of turns is taken into account in the local pheromone update. Additionally, a reward and punishment mechanism is employed in the global pheromone update to adjust the pheromone concentrations of different paths; Furthermore, an adaptive update strategy for pheromone volatility factor adaptive is proposed to expand the search range of the algorithm. Finally, simulation experiments are conducted under various scenarios to verify the superiority and effectiveness of the proposed algorithm.

Modelling individual variability in habitat selection and movement using integrated step‐selection analysis

Abstract Integrated step‐selection analysis (ISSA) is frequently used to study habitat selection using animal movement data. Methods for incorporating random effects in ISSA have been developed, making it possible to quantify variability among animals in their space‐use patterns. Although it is possible to model variability in both habitat selection and movement parameters, applications to date have focused on the former despite the widely acknowledged and important role that movement plays in determining ecological processes from the individual to ecosystem level. One potential explanation for this omission is the absence of readily available software or examples demonstrating methods for estimating movement parameters in ISSA with random effects. We demonstrated methods for characterizing among‐individual variability in both movement and habitat‐selection parameters using a simulated data set and by fitting two models to an acoustic telemetry data set containing locations of 35 red snapper (Lutjanus campechanus). Movement kernels were assumed to depend on either the type of benthic reef habitat in which the fish was located (model 1) or the distance between the fish's current location and the nearest edge habitat (model 2). In both models, we also quantified habitat selection for different benthic habitat classes and distance to edge habitat, and we allowed for individual variability in movement and habitat‐selection parameters using random effects. The simulation example highlights the benefits of a mixed‐effects specification, namely, we can increase precision when estimating individual‐specific movement parameters by borrowing information across like individuals. In our applied example, we found substantial among‐individual variability in both habitat selection and movement parameters. Nonetheless, most red snapper selected for hardbottom habitat and for locations nearer to edge habitat. They also moved less when in hardbottom habitat. Turn angles were frequently near ± π but were more dispersed when fish were far away from edge habitat. We provide code templates and functions for quantifying variability in movement and habitat‐selection parameters when implementing ISSA with random effects. In doing so, we hope to encourage ecologists conducting ISSA to take full advantage of their ability to model among‐individual variability in both habitat‐selection and movement patterns.

A path planning method for unmanned aerial vehicle based on improved wolf pack algorithm

SummaryIn the rapidly developing field of unmanned aerial vehicle (UVA) technology, solving local optimal problems and achieving efficient smooth planning are crucial for improving the operational efficiency and safety of UVA systems. To address these needs, our study introduces a novel optimization algorithm, called IWPA‐APF, which aims to improve path planning efficiency. This algorithm is a fusion of the artificial potential field (APF) method and the improved wolf‐pack algorithm (IWPA) to solve common problems such as local optima and inefficient planning in the path planning process. The IWPA‐APF algorithm improves search efficiency and accuracy by incorporating an adaptive step size that significantly refines the key behaviors of the traditional IWPA, which is based on the wolf pack algorithm (WPA). In addition, the algorithm incorporates specific planning constraints, such as turn angles and tolerance limits, to minimize getting stuck in local optima. The process involves generating initial plans through multiple iterations of the IWPA, followed by further refinement using the method of integrating APF's repulsive force field. Simulation results show that the IWPA‐APF algorithm outperforms traditional methods, offering shorter flight distances and improved safety, thereby establishing itself as a robust solution for UAV path planning in obstacle‐rich environments.

Development of a Novel Water Jet Polisher Using Soft Abrasives for Small Complex-Structure Heat Pipes of Aluminum Alloy Produced Using Additive Manufacturing.

It is a challenge to polish the interior surface of a small bent pipe with complex structures and sizes less than 0.5 mm. This is because of the fact that traditional polishing methods could destroy, block, or break the small complex structures. For a small bent pipe made of aluminum alloy produced using additive manufacturing, the defects, such as adhered powders and spatters, are easy to jam the pipe without polishing, possibly resulting in catastrophic failure for aerospace applications. To overcome this challenge, a novel water jet polisher was developed using soft polymethyl methacrylate (PMMA) abrasives. After polishing a specific area, the adhered powders on the interior surface were reduced from over 140 to 2, 3, and 6 by the soft abrasives with mesh sizes of 200, 400, and 600, respectively. The surface roughness Sa was decreased from 3.41 to 0.92 μm after polishing using PMMA abrasives with a mesh size of 200. In comparison, silica abrasives were also employed to polish the small bent pipes, leading to the bent part of pipes breaking. However, this kind of failure was absent when using soft abrasives. Computational fluid dynamics calculations elucidate that a peak erosion rate of silica abrasives for a bent pipe with a turn angle of 30° is 2.18 kg/(m2·s), which is 17 times that of soft abrasives. This is why the small bent pipe was broken using silica abrasives, whereas it remained intact when polished with soft abrasives. In addition, water jet polishing has a lower erosion rate, a relatively smooth erosion curve, and less erosion energy, leaving the bent parts intact. The developed soft abrasive water jet polisher and the findings of this study suggest new possibilities for cleaning the adhered powders and spatters and polishing the interior surface of small bent pipes with complex structures.

The Exploration of Joint Toxicity and Associated Mechanisms of Primary Microplastics and Methamphetamine in Zebrafish Larvae.

The co-existence of microplastics (MPs) and methamphetamine (METH) in aquatic ecosystems has been widely reported; however, the joint toxicity and associated mechanisms remain unclear. Here, zebrafish larvae were exposed individually or jointly to polystyrene (PS) and polyvinyl chloride (PVC) MPs (20 mg/L) and METH (1 and 5 mg/L) for 10 days. The mortality, behavioral functions, and histopathology of fish from different groups were determined. PS MPs posed a stronger lethal risk to fish than PVC MPs, while the addition of METH at 5 mg/L significantly increased mortality. Obvious deposition of MPs was observed in the larvae's intestinal tract in the exposure groups. Meanwhile, treatment with MPs induced intestinal deposits and intestinal hydrops in the fish, and this effect was enhanced with the addition of METH. Furthermore, MPs significantly suppressed the locomotor activation of zebrafish larvae, showing extended immobility duration and lower velocity. METH stimulated the outcome of PS but had no effect on the fish exposed to PVC. However, combined exposure to MPs and METH significantly increased the turn angle, which declined in individual MP exposure groups. RNA sequencing and gene quantitative analysis demonstrated that exposure to PS MPs and METH activated the MAPK signaling pathway and the C-type lectin signaling pathway of fish, while joint exposure to PVC MPs and METH stimulated steroid hormone synthesis pathways and the C-type lectin signaling pathway in zebrafish, contributing to cellular apoptosis and immune responses. This study contributes to the understanding of the joint toxicity of microplastics and pharmaceuticals to zebrafish, highlighting the significance of mitigating microplastic pollution to preserve the health of aquatic organisms and human beings.

The impact of the size and angle of the cochlear basal turn on translocation of a pre-curved mid-scala cochlear implant electrode

Scalar translocation is a severe form of intra-cochlear trauma during cochlear implant (CI) electrode insertion. This study explored the hypothesis that the dimensions of the cochlear basal turn and orientation of its inferior segment relative to surgically relevant anatomical structures influence the scalar translocation rates of a pre-curved CI electrode. In a cohort of 40 patients implanted with the Advanced Bionics Mid-Scala electrode array, the scalar translocation group (40%) had a significantly smaller mean distance A of the cochlear basal turn (p < 0.001) and wider horizontal angle between the inferior segment of the cochlear basal turn and the mastoid facial nerve (p = 0.040). A logistic regression model incorporating distance A (p = 0.003) and horizontal facial nerve angle (p = 0.017) explained 44.0–59.9% of the variance in scalar translocation and correctly classified 82.5% of cases. Every 1mm decrease in distance A was associated with a 99.2% increase in odds of translocation [95% confidence interval 80.3%, 100%], whilst every 1-degree increase in the horizontal facial nerve angle was associated with an 18.1% increase in odds of translocation [95% CI 3.0%, 35.5%]. The study findings provide an evidence-based argument for the development of a navigation system for optimal angulation of electrode insertion during CI surgery to reduce intra-cochlear trauma.