Location Of Point Research Articles

Acupuncture in the treatment of cocaine addiction: how does it work?

Cocaine is a frequently abused and highly addictive drug that damages brain health and imposes substantial social and economic costs. Acupuncture has been used in the treatment of cocaine addiction and has been shown to improve abnormal mental and motor states. This article mainly focuses on the neurobiological mechanisms involving the central nervous system (CNS) and peripheral nervous system (PNS) that underlie the effects of acupuncture in the treatment of cocaine addiction. The central dopamine system is a key player in acupuncture treatment of cocaine addiction; the ventral tegmental area (VTA)-nucleus accumbens (NAc) signaling pathway, which has a modulatory influence on behavior and psychology after chronic use of cocaine, is a significant target of acupuncture action. Moreover, acupuncture alleviates cocaine-induced seizures or acute psychomotor responses through the paraventricular thalamus and the lateral habenula (LHb)-rostromedial tegmental (RMTg) nucleus circuits. The data suggest that acupuncture can impact various cocaine-induced issues via stimulation of diverse brain areas; nevertheless, the interconnection of these brain regions and the PNS mechanisms involved remain unknown. In this review, we also discuss the effects of specific acupuncture protocols on cocaine addiction and note that variations in needling modalities, current intensities and traditional acupuncture point locations have led to different experimental results. Therefore, standardized acupuncture protocols (with respect to stimulation methods, point locations and number of sessions) may become particularly important in future studies.

A Study on Scan Trajectory Based Effective Localization Method Using Mobile Anchor in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a collection of different nodes working together in a networked fashion in an ordered way. For many applications, sensor location in wireless sensor networks (WSN) is crucial. It is expensive to equip each sensor node with a GPS receiver. Numerous methods, including range-based and range-free methods, have been put forth in the past to determine the locations of sensor nodes that are randomly distributed. The majority of them make use of unique nodes known as anchor nodes, which are thought to be aware of their own positions. These anchor nodes supply the information that other sensors use to calculate their locations. Massive numbers of sensor nodes are used in wireless sensor networks (WSNs) to gather data about the immediate environment. However, this data is useless until the precise location of the data collection points is known. Sensor node localization in wireless sensor networks (WSNs) is important for a number of applications. The current research study develops a path planning technique to apply mobile anchors to the localization systems that are currently in use. The two mobile anchors supported by the effective trajectories, or effective SCAN, is the focus of the proposed research project. To localise the sensor node and transmit data, this method involves setting the mobile anchors to move in the opposite direction. The advantages of this dual movable anchor are demonstrated by the research study in terms of decreased localization time, localization error, and other factors.

Composite convolution: A flexible operator for deep learning on 3D point clouds

Deep neural networks require specific layers to process point clouds, as the scattered and irregular location of 3D points prevents the use of conventional convolutional filters. We introduce the composite layer, a flexible and general alternative to the existing convolutional operators that process 3D point clouds. We design our composite layer to extract and compress the spatial information from the 3D coordinates of points and then combine this with the feature vectors. Compared to mainstream point-convolutional layers such as ConvPoint and KPConv, our composite layer guarantees greater flexibility in network design and provides an additional form of regularization. To demonstrate the generality of our composite layers, we define both a convolutional composite layer and an aggregate version that combines spatial information and features in a nonlinear manner, and we use these layers to implement CompositeNets. Our experiments on synthetic and real-world datasets show that, in both classification, segmentation, and anomaly detection, our CompositeNets outperform ConvPoint, which uses the same sequential architecture, and achieve similar results as KPConv, which has a deeper, residual architecture. Moreover, our CompositeNets achieve state-of-the-art performance in anomaly detection on point clouds. Our code is publicly available at https://github.com/sirolf-otrebla/CompositeNet.

Investigation into the effect of deltoid ligament injury on rotational ankle instability using a three-dimensional ankle finite element model.

Injury to the lateral collateral ligament of the ankle may cause ankle instability and, when combined with deltoid ligament (DL) injury, may lead to a more complex situation known as rotational ankle instability (RAI). It is unclear how DL rupture interferes with the mechanical function of an ankle joint with RAI. To study the influence of DL injury on the biomechanical function of the ankle joint. A comprehensive finite element model of an ankle joint, incorporating detailed ligaments, was developed from MRI scans of an adult female. A range of ligament injury scenarios were simulated in the ankle joint model, which was then subjected to a static standing load of 300N and a 1.5Nm internal and external rotation torque. The analysis focused on comparing the distribution and peak values of von Mises stress in the articular cartilages of both the tibia and talus and measuring the talus rotation angle and contact area of the talocrural joint. The dimensions and location of insertion points of ligaments in the finite element ankle model were adopted from previous anatomical research and dissection studies. The anterior drawer distance in the finite element model was within 6.5% of the anatomical range, and the talus tilt angle was within 3% of anatomical results. During static standing, a combined rupture of the anterior talofibular ligament (ATFL) and anterior tibiotalar ligament (ATTL) generates new stress concentrations on the talus cartilage, which markedly increases the joint contact area and stress on the cartilage. During static standing with external rotation, the anterior talofibular ligament and anterior tibiotalar ligament ruptured the ankle's rotational angle by 21.8% compared to an intact joint. In contrast, static standing with internal rotation led to a similar increase in stress and a nearly 2.5 times increase in the talus rotational angle. Injury to the DL altered the stress distribution in the tibiotalar joint and increased the talus rotation angle when subjected to a rotational torque, which may increase the risk of RAI. When treating RAI, it is essential to address not only multi-band DL injuries but also single-band deep DL injuries, especially those affecting the ATTL.

Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy

Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optical coherence tomography (OCT) B-scan image in clinical practice face the dilemma of weak reference, poor reproducibility, and experience dependence. In this context, this paper constructs two schemes: Scheme Ⅰ draws on the idea of ensemble learning, namely, integrating multiple models for locating starting key point in the height direction of lesion in the inference stage, which appropriately improves the performance of a single model. Scheme Ⅱ designs an adaptive gradient threshold (AGT) technique, followed by the construction of cascading strategy, which involves preliminary location of starting key point through deep learning, and then employs AGT for precise adjustment. This strategy not only achieves effective location for starting key point, but also significantly reduces the large appetite of deep learning model for training samples. Subsequently, AGT continues to play a crucial role in locating the terminal key point in the height direction of lesion, further demonstrating its feasibility and effectiveness. Quantitative and qualitative key point location experiments in the height direction of lesion on 1152 samples, as well as the final height measurement display, consistently conveys the superiority of the constructed schemes, especially the cascading strategy, expanding another potential tool for the comprehensive analysis of CSCR.

A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

Obtaining automated, objective3-dimensional(3D) models of the Eustachian tube (ET) and the internal carotid artery (ICA) from computed tomography (CT) scans could provide useful navigational and diagnostic information for ET pathologies and interventions. We aim to develop a deep learning (DL) pipeline to automatically segment the ET and ICA and use these segmentations to compute distances between these structures. Retrospective cohort. Tertiary referral center. From a database of 30 CT scans, 60 ET and ICA pairs were manually segmented and used to train an nnU-Net model, a DL segmentation framework. These segmentations were also used to develop a quantitative tool to capture the magnitude and location of the minimum distance point (MDP) between ET and ICA. Performance metrics for the nnU-Net automated segmentations were calculated via the average Hausdorff distance (AHD) and dice similarity coefficient (DSC). The AHD for the ET and ICA were 0.922 and 0.246 mm, respectively. Similarly, the DSC values for the ET and ICA were 0.578 and 0.884. The mean MDP from ET to ICA in the cartilaginous region was 2.6 mm (0.7-5.3 mm)and was located on average 1.9 mm caudal from the bony cartilaginous junction. This study describes the first end-to-end DL pipeline for automated ET and ICA segmentation and analyzes distances between these structures. In addition to helping to ensure the safe selection of patients for ET dilation, this method can facilitate large-scale studies exploring the relationship between ET pathologies and the 3D shape of the ET.

Lateral loading response of monopiles in sand considering installation effect

The effect of pile installation is a critical issue in the analysis and design of pile foundations but it is commonly ignored due to various numerical difficulties. In this paper, the installation process of an open-ended pipe pile into a sand deposit is simulated by using the zipper technique combined with the Arbitrary Lagrangian-Eulerian (ALE) method in the framework of three-dimensional (3D) finite element modeling. The subsequent lateral load response of the pile is also simulated and compared with that without consideration of the pile installation. The state dependent behavior of sand in associated with the pile installation and the subsequent lateral load is described using an advanced constitutive model. The study shows that for a relatively loose sand deposit, the sand surrounding the pile exhibits contraction and the disturbance zone takes the form of a trapezoid, whereas for a dense sand deposit, the sand near the pile will dilate and the disturbance zone takes the form of an inversed trapezoid. Furthermore, the deformation mode of the surrounding sand under the lateral load differs to some extent from that without consideration of the installation effect. Particularly, the location of the rotation point for the laterally loaded pile tends to move downwards when the pile installation process is considered.

Research on the Vanishing Point Detection Method Based on an Improved Lightweight AlexNet Network for Narrow Waterway Scenarios

When an unmanned surface vehicle (USV) navigates in narrow waterway scenarios, its ability to detect vanishing points accurately and quickly is highly important for safeguarding its navigation safety and realizing automated navigation. We propose a novel approach for detecting vanishing points based on an improved lightweight AlexNet. First, a similarity evaluation calculation method based on image texture features is proposed, by which some scenarios are selected from the filtered Google Street Road Dataset (GSRD). These filtered scenarios, together with the USV Inland Dataset (USVID), compose the training dataset, which is manually labeled according to a non-uniformly distributed grid level. Next, the classical AlexNet was adjusted and optimized by constructing sequential connections of four convolutional layers and four pooling layers and incorporating the Inception A and Inception C structures in the first two convolutional layers. During model training, we formulate vanishing point detection as a classification problem using an output layer with 225 discrete possible vanishing point locations. Finally, we compare and analyze the labeled vanishing point with the detected vanishing point. The experimental results show that the accuracy of our method and the state-of-the-art algorithmic vanishing point detector improves, indicating that our improved lightweight AlexNet can be applied in narrow waterway navigation scenarios and can provide a technical reference for autonomous navigation of USVs.

Mission Planning of UAVs and UGV for Building Inspection in Rural Area

Unmanned aerial vehicles (UAVs) have become increasingly popular in the civil field, and building inspection is one of the most promising applications. In a rural area, the UAVs are assigned to inspect the surface of buildings, and an unmanned ground vehicle (UGV) is introduced to carry the UAVs to reach the rural area and also serve as a charging station. In this paper, the mission planning problem for UAVs and UGV systems is focused on, and the goal is to realize an efficient inspection of buildings in a specific rural area. Firstly, the mission planning problem (MPP) involving UGVs and UAVs is described, and an optimization model is established with the objective of minimizing the total UAV operation time, fully considering the impact of UAV operation time and its cruising capability. Subsequently, the locations of parking points are determined based on the information about task points. Finally, a hybrid ant colony optimization-genetic algorithm (ACO-GA) is designed to solve the problem. The update mechanism of ACO is incorporated into the selection operation of GA. At the same time, the GA is improved and the defects that make GA easy to fall into local optimal and ACO have insufficient searching ability are solved. Simulation results demonstrate that the ACO-GA algorithm can obtain reasonable solutions for MPP, and the search capability of the algorithm is enhanced, presenting significant advantages over the original GA and ACO.

Control of isolated response curves through optimization of codimension-1 singularities

We introduce a computational framework for controlling the location of isolated response curves, i.e. responses that are not connected to the main solution branch and form a closed curve in parameter space. The methodology relies on bifurcation tracking to follow the evolution of fold bifurcations in a codimension-2 parameter space. Singularity theory is used to distinguish points of isola formation and merger from codimension-2 bifurcations and an optimization problem is formulated to delay or advance the onset or merger of isolated response curves or control their position in the state/parameter space. We illustrate the methodology on three examples: a finite element model of a cantilever beam with cubic nonlinearity at its tip, a two-degree-of-freedom oscillator with asymmetry and a two-degree-of-freedom base-excited oscillator exhibiting multiple isolas. Our results show that the location of points of isola formation and mergers can effectively be controlled through structural optimization.

The MD study of water short-range order during liquid-liquid transition: Toward the second critical point

Full-scale thermodynamic experimental investigations of the liquid-liquid transition and different water phases remain challenging due to spontaneous crystallization and the complexity of studies on the nanosecond time scale. Moreover, the specific position of the second critical point in water is still unclear. This study used molecular dynamics to reproduce the structural properties of both low- and high-density waters and to characterize changes in the order parameters, average number of hydrogen bonds, and ordering of neighboring molecules during liquid-liquid transitions and in regimes of supercooled waters. A rapid change in calculated parameters under increased pressure could be attributed to a first-order phase transition. In addition, we provided evidence that low-density water becomes dissolved in high-density water inclusions as the temperature or pressure increases. The presumed location of the second critical point has been identified as TC ≈ 220 K, PC ≈ 1.5 kbar, and ρC ≈ 1.02 g/cm3.

An estimation method for switching points of multimode spatiotemporal data based on SFSTAR

Various traditional methods, including statistical and spatial map-based approaches, are employed to model spatiotemporal data. However, the lack of explicit descriptions of spatial and temporal dependencies leads to unnecessarily intensive and uninterpretable relationships among the variables. To address this problem, space–time autoregressive moving average (STARMA)-type models that can depict temporal and spatial dependencies in a parametric manner are adopted in this study. However, such models may not be applicable to unlabeled multimode spatiotemporal data. In this study, we propose a switching flexible space–time autoregressive (SFSTAR) model to describe multimode spatiotemporal data. Considering the coupling between the parameter estimation of each mode and determination of the switching points, an estimation method is proposed to identify the mode switching points to partition the multimode data into different segments. First, the proposed estimation method identifies the number of segments by locating the transition regions that enclose the switching points based on the spatiotemporal feature extraction proposed herein. Second, with the estimated number of segments that is actually the number modes and the constraints on the locations of the switching points given by the transition regions, the proposed method jointly estimates the switching points and the SFSTAR model parameters in each mode through Bayesian optimization. The effectiveness of the proposed method is evaluated using a numerical example and a fiber optic temperature measurement dataset.

Impact of Structural Compliance of a Six Degree of Freedom Joint Simulator on Virtual Ligament Force Calculation in Total Knee Endoprosthesis Testing.

The AMTI VIVO™ six degree of freedom joint simulator allows reproducible preclinical testing of joint endoprostheses under specific kinematic and loading conditions. When testing total knee endoprosthesis, the articulating femoral and tibial components are each mounted on an actuator with two and four degrees of freedom, respectively. To approximate realistic physiological conditions with respect to soft tissues, the joint simulator features an integrated virtual ligament model that calculates the restoring forces of the ligament apparatus to be applied by the actuators. During joint motion, the locations of the ligament insertion points are calculated depending on both actuators' coordinates. In the present study, we demonstrate that unintended elastic deformations of the actuators due to the specifically high contact forces in the artificial knee joint have a considerable impact on the calculated ligament forces. This study aims to investigate the effect of this structural compliance on experimental results. While the built-in algorithm for calculating the ligament forces cannot be altered by the user, a reduction of the ligament force deviations due to the elastic deformations could be achieved by preloading the articulating implant components in the reference configuration. As a proof of concept, a knee flexion motion with varying ligament conditions was simulated on the VIVO simulator and compared to data derived from a musculoskeletal multibody model of a total knee endoprosthesis.

Facility location decisions for drone delivery with riding: A literature review

This study presents a comprehensive literature survey on facility location problems for drone (uncrewed vehicle) delivery in situations where drones can ride in or on other vehicles. This includes facilities visited by only one type of vehicle, as well as facilities visited by both drones and other vehicles. Unlike traditional facility location problems for delivery systems with one vehicle type, hybrid vehicle-drone delivery systems usually require determining locations where the two vehicle types meet and separate. The main goals of this paper are to review the large volume of drone delivery literature with riding from a facility location perspective to provide a connection between the studies from different research areas that cover similar problems, and to highlight future research directions in this area. We first review the functions of drones, including aerial and ground drones, and the different types of facilities used for hybrid vehicle-drone delivery systems. The literature is categorized based on the presence of resupply operations, the locations of drone launch and retrieval points, the types of drones (aerial or ground) and the location space (discrete or continuous). Each category is analyzed in terms of the modeling approach, decision(s), objective function(s), constraints and additional features. The paper concludes with promising future research directions.

Stress state analysis of a cylindrical tank with water of an under water sports palace

The paper analyzes the stress state of a cylindrical tank, which is one of the main structural elements of a sports facility - an underwater sports palace. In the calculation of the cylindrical shell of the tank of constant thickness, the moment theory was used. The reservoir is, in fact, a swimming pool for conducting training sessions on underwater swimming in fins, diving, diving, is considered fixed in its base and filled with liquid (water of a special composition, homogeneous in depth, with a given specific gravity). It is known that integration of the calculation equations of the moment theory (of circular cylindrical shells), namely: a) differential equations of equilibrium; b) equations of deformations; c) equations of forces attributed to the unit length of the coordinate line (tangential forces, bending moments), is a complex mathematical problem associated with solving a system of partial differential equations with variable coefficients. Only the calculation of the curve of a cylindrical shell ultimately leads to a system of differential equations with constant coefficients. Under the assumption of significant depth of the tank compared to the thickness of its walls and the value of the radius of the cylinder base (which allows us to consider it as infinitely long), displacements and forces (tangential and transverse), bending moments are analytically found. The locations of the cylinder surface points, in which the indicated forces and moments acquire maximum values, have been determined; sketches of their diagrams, determining the character of change of these physical quantities (parameters) along the height of the tank, have been given. The results obtained in the work can be further used to clarify and improve engineering methods of calculation of structural elements of sports facilities of this type, both at the stages of their design and in the modes of real operation in order to prevent situations associated with the loss of their strength and stability.

Variation characteristics and homology analysis of loaded coal-rock's non-stress signals

When loaded coal-rock is deformed, various non-stress signals, such as temperature-type, electromagnetic-type, and vibration-type, exhibit distinct characteristics as stress'. In order to clarify the relationship between various coal-rock's non-stress signals and establish the corresponding relationship between these characteristics and the damage degree, the study first analysed the generation and evolution mechanisms of the three types of non-stress signals from the perspective of physical mechanisms and energy, and then investigated the changing characteristics of loaded coal-rock's non-stress signals based on uniaxial experiments at different rates. Finally, the homology of non-stress signals is verified by comparing the characteristics of different non-stress signals. The findings indicate that the variation of the non-stress signal is connected to the status of the coal-rock fracture, which is a physical expression of external mechanical energy dissipation. Moreover, the degree of damage inside the coal-rock is proportional to the strength of each non-stress signal source, and the location of the measurement point has no effect on the details associated with coal-rock damage in the non-stress signal. All of the non-stress signals display changing features and fracture precursors connected to the coal-rock damage state. Among the three kinds of non-stress signals, the temperature-type non-stress signal exhibits the most obvious stationarity and stage, whereas the electromagnetic-type and vibration-type signals would fluctuate because of the stress stability. However, they differ greatly in terms of sensitivity to stress variations and difficulties in diagnosing fracture precursors. In addition, the maximum of the vibration-type and electromagnetic-type signals often corresponds with the “plateau” of the temperature-type signal, which means that three different non-stress signal features occur together. Furthermore, the homology of loaded coal-rock's non-stress signals can be efficiently verified by both evidence from theory and experiment. This research can offer a way to determine the loading condition of coal-rock by using non-stress signals, and it can theoretically promote future studies on the prevention of coal and rock dynamic disasters by multi-information fusion.

Approach for contact medical device development via integrated testing, skeletal muscle modeling, and finite element analysis

Development of novel medical devices for the treatment of musculoskeletal pain associated with neuro-muscular trigger points requires a model for relating the mechanical responses of in vivo biological tissues to applied palliative physical pressures and a method to design treatments for optimal effects. It is reasonable to hypothesize that the efficacy of therapeutic treatment is proportional to the maximum tensile strain at trigger point locations. This work presents modeling of the mechanical behavior of biological tissue structures and treatment simulations, supported by indentation experiments and finite element (FE) modeling. The steady-state indentation responses of the tissue structure of the posterior neck were measured with a testing device, and an FE model was constructed using a first-order Ogden hyperelastic material model and calibrated with the experimental data. The error between experimental and FE-generated displacement-load curves was minimized via a two-stage optimization process comprised of an Optimal Latin Hypercube design-of-experiments analysis and a Bayesian optimization loop. The optimized Ogden model had an initial shear modulus (μ) of 5.16 kPa and a deviatoric exponent (α) of 11.90. Another FE model was developed to simulate the deformation of the tissue structures in the posterior neck adjacent to the C3 vertebrae in response to indentation loading, in order to determine the optimal location and angle to apply an indentation force for maximum therapeutic benefit. The optimal location of indentation was determined to be 28° lateral from the sagittal plane along the surface of the skin, measured from the centerline of the spine, at an angle of 8° counterclockwise from the surface normal vector. The optimized spatial orientation of the indentation corresponded to the average of the maximum principal strain across the deep muscle region of the model.

Thermodynamic and molecular dynamic insights into how fusion influences peptide-tag recognition of an antibody

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol−1 and the entropic loss only by 0.9 kcal mol−1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol−1 and the entropic loss by 3.2 kcal mol−1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

Subassemblage test and width-thickness design limit for steel built-up box columns subjected to axial load and cyclic lateral drift

This study investigates the behavior of first-story columns under reversed cyclic lateral loading and constant axial loading by using a full-scale, one-and-a-half story subassemblage testing scheme. Four subassemblages were designed with steel beams at the second floor and a moderately ductile built-up box column with a width-thickness ratio (b/t) of either 16.2 or 20.5, which are between the highly ductile (=12.9) and moderately ductile (=23.5) requirements in AISC 341 (2016). All built-up box columns were made by SM570MB steel with a nominal yield stress, Fy= 420 MPa. A high axial load (=4200–8000 kN, corresponding to 0.2–0.4 times the axial yield strength Py) was applied to the one-and-a-half story subassemblage column before cyclic lateral drifts. The second-floor beams and column provide rotational flexibility at the top end of first-story columns in the subassemblages, significantly changing column’s stiffness, moment distribution, and inflection point location observed from typical column testing. The subassemblage column and the isolated column had a similar maximum moment at the first cycle of 0.04 rad drift, but the later showed larger strength degradation in the following cycles due to larger fixity at the column top end. An experimental solution that relates the column width-thickness ratio to the moment strength deterioration was developed to obtain design b/t limits for highly and moderately ductile built-up box columns under combined high axial load (0.3–0.4Py) and cyclic lateral drift.

A novel dual-criterion framework for change point detection

In this work, we introduce a dual-criterion framework for change-point detection. This innovative approach intuitively facilitates the simultaneous determination of both the number and locations of change points, while effectively identifying and excluding outliers. Numerous one-dimensional criterion-based change point detection methods can be generalized and integrated within this novel framework.