Tracking Characteristics Research Articles

Numerical study of the effects of unmatched pressure on the supersonic particle-laden mixing layer

The dispersion of monodisperse, inertial particles in a supersonic mixing layer consisting of two sheared flows with differing pressures (P1 for the particle-laden jet flow and P2 for the airflow) is numerically investigated using large Eddy simulation and Euler–Lagrange methods. The calculations reveal the following insights: The pressure disparity between the two flows induces a transverse gas flow effect, which swiftly deflects the mixing layer from the high-pressure side to the low-pressure side. The growth rate of mixing layer increases with the ratio of P2/P1 and while the deflected displacement correlates with the pressure difference |P2-P1|. However, the particles exhibit delayed tracking characteristics to the deflected mixing layer because of their relative relaxation to the transverse gas velocity, particularly in the upstream region of the mixing layer (also known as the Kelvin–Helmholtz instability developing zone or KH zone). Notably, when the P2 exceeds that of the P1, particles can more easily penetrate into the vortices of KH zone, significantly enhancing the downstream gas–particle mixing. This mixing enhancement is particularly pronounced for larger particles due to their increased inertia, which allows them to advance into the vortices of KH zone more effectively than smaller ones.

Two-Staged Technology for CoCr Stent Production by SLM

Additive manufacturing of porous materials with a specific macrostructure and tunable mechanical properties is a state-of-the-art area of material science. Additive technologies are widely used in industry due to numerous advantages, including automation, reproducibility, and freedom of design. Selective laser melting (SLM) is one of the advanced techniques among 3D fabrication methods. It is widely used to produce various medical implants and devices including stents. It should be noticed that there is a lack of information on its application in stent production. The paper presents the technological aspects of CoCr stent SLM fabrication, including design of stents and development of regimes for their manufacturing. Physical, chemical, and technological properties of CoCr powder were initially determined. Parametric design of mesh stent models was adopted. A two-stage approach was developed to ensure dimensional accuracy and quality of stents. The first stage involves a development of the single-track fusion process. The second stage includes the stent manufacturing according to determined technological regimes. The single-track fusion process was simulated to assign laser synthesis parameters for stent fabrication. Melting bath temperature and laser regimes providing such conditions were determined. Twenty-seven SLM manufacturing regimes were realized. Dependence of single-tracks width and height on the laser power, exposition time, and point distance was revealed. The qualitative characteristics of tracks imitating the geometry of the stent struts as well as favorable and unfavorable fusion regimes were determined. The results of surface roughness regulating of the stents’ structural elements by various methods were analyzed. Thus, this two-staged approach can be considered as a fundamental approach for CoCr stent SLM fabrication.

Climatological Tracking and Lifecycle Characteristics of Mesoscale Convective Systems in Northwestern South America

AbstractMesoscale convective systems (MCSs) are crucial in shaping large‐scale tropical circulation and the hydrological cycle, particularly in Northwestern South America (NwSA), a region marked by complex terrain and significant MCS activity. Understanding MCSs in NwSA is vital due to their impact on precipitation patterns and potential for severe weather events. To enhance this understanding, the ATRACKCS algorithm was developed for tracking convective systems, utilizing precipitation and brightness temperature data sets. This research focuses on documenting the spatiotemporal variability of MCS occurrence, life cycle, and movement. Notably, MCS hotspots were identified to the west of the major orographic features in the region, with maximum occurrences at night, contrasting with the region's typical afternoon peak in land convection. MCS movement is also heavily influenced by topography, with higher velocities on the eastern (windward) side of the Andes compared to velocities on the western (leeward) side. MCSs generally move westward, driven by easterly winds, but this pattern is not consistent throughout the year or region. Northward movement is predominant to the west of the Andes, while southward movement is observed to the east. These seasonal and regional movement variations are linked to factors such as the intertropical convergence zone position, moisture availability, topography, and low‐level jets. This research underscores the complexity of MCSs in NwSA and emphasizes the need for detailed studies on the atmospheric environment shaping these systems. Additionally, it provides a robust 21‐year MCS database for NwSA and an advanced tracking tool for research in various geographic contexts and impact areas.

A case study of railway curve squeal radiated from both the outer and inner wheel

This case study is presented after observations were made that partially contrast the prevailing picture of railway curve squeal given in the literature. These are observations with significance both for modelling and condition monitoring. The current case study will be followed by a subsequent investigation focused on the validation and application of a simulation model to investigate root-causes for curve squeal at the Stockholm metro. Curve squeal in a 213 m radius curve on the Stockholm metro is studied. Data includes track characteristics (rail profile, rail roughness and gauge width) and noise measured at the trackside as well as by two vehicles equipped with an on-board mounted noise monitoring system. The current case study contrasts field measurements of curve squeal reported in the literature by a relative shift of emitted noise towards higher frequencies. Wayside noise measurements in the studied curve during a few hours showed squeal generation for all vehicle passages with dominating 1/3 octave band centre frequencies in the range between 6.3–15.8 kHz. Noise data measured during one year of regular traffic of two vehicles equipped with a monitoring system were obtained. The occurrence of curve squeal was analysed through an implementation of the curve squeal detection algorithm in operation at the Stockholm metro. This algorithm was also applied to search for events of squeal noise radiation from the outer wheel. Results show emissions of squeal noise from the inner and outer wheel for 65 % and 8 % of the vehicle passages through the studied curve, respectively. Further, the occurrence of curve squeal radiated from the inner wheel was found to increase by 10 % after rail grinding. In the literature, squeal radiated from the outer wheel is described as having an intermittent character with magnified spectral components in the frequency range between 5–10 kHz. In contrast, the current work presents sustained tonal squeal generated from the outer wheel with similar noise characteristics as typically related to ordinary curve squeal.

Research on Velocity Feedforward Control and Precise Damping Technology of a Hydraulic Support Face Guard System Based on Displacement Feedback

The hydraulic support face guard system is essential for supporting the exposed coal wall at the working face. However, the hydraulic support face guard system approaching the coal wall may cause impact disturbances, reducing the load-bearing capacity of coal walls. Particularly, the hydraulic support face guard system is characterized by a large turning radius when mining thick coal seams. A strong disturbance and impact on the coal wall may occur if the approaching speed is too fast, leading to issues such as rib spalling. In this paper, a feedforward fuzzy PID displacement velocity compound controller (FFD displacement speed compound controller) is designed. The PID controller, fuzzy PID controller, feedforward PID controller, and FFD displacement speed compound controller are compared in terms of the tracking characteristics of the support system and the impact response of the coal wall, validating the controller’s rationality. The results indicate that the designed FFD displacement speed compound controller has significant advantages. This controller maintains a tracking error range of less than 1% for target displacement with random disturbances in the system, with a response adjustment time that is 34% faster than the PID controller. Furthermore, the tracking error range for target velocity is reduced by 8.4% compared to the feedforward PID controller, reaching 13.8%. Additionally, the impact disturbance of the support system on the coal wall is suppressed by the FFD displacement speed compound controller, reducing the instantaneous contact impact between the support plate and the coal wall by 350 kN. In summary, the FFD compound controller demonstrates excellence in tracking responsiveness and disturbance rejection, enhancing the efficacy of hydraulic supports, and achieving precise control over the impact on the coal wall.

Epidemiology of injuries in united states high school track and field jumping events from 2008 – 2019

ABSTRACT Objectives Reports of injury characteristics of high school track and field athletes participating in jumping events in the United States are limited. In this descriptive epidemiological study, we report injury rates and patterns in these athletes. Methods Injuries and athletic exposures (AE) from the National High School Sports Related Injury Surveillance System, and High School Reporting Information Online (RIO) from 2008-2019 were analyzed. Jumping events included high jump, long jump, triple jump, and pole vault. Injury rate ratios (IRR) and injury proportion ratios (IPR) were examined by sex. Results A total of 727 injuries related to jumping events during 5,486,279 AEs occurred with the highest frequency at the thigh (20.3%) followed by the ankle (18.2%), knee (16.1%), and lower leg (11.0%). The most common types of injuries were muscle strain (29.0%) and ligament sprain (21.2%). Most athletes returned to sport within 1 week (43.1%, n = 312) or 3 weeks (34.7%, n = 243). Few jumping-related injuries resulted in surgery (4.9%, n = 35) or medical disqualification (4.4%, n = 31). The jumping-related injury rate was 1.33 injuries/10,000 AEs from 2008 to 2019. The rate of jumping-related injuries was higher in competition than in practice (IRR = 2.63, 95% confidence interval [CI]: 2.25–3.06). Injury rates were significantly higher in practice for female athletes than for males (IRR = 1.51, 95% CI: 1.23–1.86). Compared to male athletes, female athletes sustained a higher proportion of ankle injuries (IPR = 1.63, 95% CI: 1.15–2.32) and ligament sprains (IPR = 1.55, 95% CI: 1.16–2.09). Conclusions This study describes injury characteristics of high school track and field jumping athletes from 2008 to 2019. We found an overall injury rate of 1.33 injuries per 10,000 AEs. Higher overall rates of jumping-related injuries occurred during competitions than in practice, and female athletes displayed a significantly higher rate of injuries during practices compared to male athletes.

Enhanced rainfall nowcasting of tropical cyclone by an interpretable deep learning model and its application in real-time flood forecasting

Reliable Tropical Cyclone (TC) rainfall and flood forecasts play an important role in disaster prevention and mitigation. Numerous studies have demonstrated the promising performance of deep learning in hydrometeorological forecasts. However, few studies have investigated the potential enhancement of advanced TC track forecasts in predicting rainfall and induced flood. In this study, a novel rainfall nowcasting model (TCRainNet) is developed by fusing TC track characteristics with antecedent rainfall in a Convolution LSTM to predict hourly rainfall with a lead time of 6 h. The nowcasts are subsequently used to drive an event-based Xin’anjiang hydrological model for real-time flood forecasting. The model performance is interpretated by the occlusion sensitivity approach, and the propagation of errors from TC track forecasts to flood forecasts is quantified. The results underscore the superiority of TC track characteristics as input features for rainfall nowcasts, as indicated by a Mutual Information value of up to 0.51. The generated nowcasts are found to have averaged Probability of Detection (POD) and Critical Success Index (CSI) greater than 0.27 and 0.2 respectively. The Mean Absolute Error (MAE) of the nowcasts falls below 2.6 mm, which is only 46 % of the ECMWF operational high-resolution forecasts. The rainfall-driven flood forecasts have NSE greater than 0.7 and PBIAS smaller than 20 % with lead time up to + 4 h. It is shown that the position error of 0.45° and intensity error of 10 hPa&7.8 m/s in TC track forecasts generally result in 0.9 mm degradation in rainfall forecasts and 10% decline in the accuracy of rainfall-driven flood forecasts. The effectiveness of our method presents favorable applicability in advancing disaster mitigation efforts.

Examining fishing activities based on in-situ tracking and oceanographic characteristics in Aru Sea and surroundings

Fisheries activites and oceanographic conditions have a strong relationship. Understanding the complex interplay between fisheries and oceanographic conditions is essential for effective fisheries management. The aim of this research is to analyze the in-situ fishing activities with oceanographic conditions in the Fisheries Management Area (FMA) or WPP-NRI 718 located in the Aru Sea and its surroundings. The main data source is from open global data ship tracking and oceanographic conditions from satellite data. In general, fishing is conducted around the waters of Aru Island. The fishing grounds are strongly influenced by a combination of environmental factors, including sea surface temperatures, chlorophyll-a (Chlor-a) concentrations, sea surface height, and current velocities. A decrease in fishing patterns around Aru Island waters occurs in the eastern season, where fishing tends to occur in the western region (near Timor-Leste). Based on the oceanographic conditions, fishing tends to occur in regions with warmer conditions ranging from 27 to 29 °C, moderate Chlor-a (1.02–3.01 mg/m3), a relatively high surface height (0.17–0.32 m), and slow surface currents.

Sewerage surveillance tracking characteristics of human antibiotic resistance genes in sewer system

Sewage surveillance is widely applied to track valid human excretion information and identify public health conditions during corona virus disease 2019 (COVID-19) pandemic. This approach can be applied to monitor the antibiotic resistance level in sewers and to assess the risk of spreading antibiotic resistance in municipal wastewater systems. However, there is still little information about human antibiotic resistance occurrence characteristics in sewer system. This study conducted a field trial for whole year to advance understanding on spatial and temporal occurrence of antibiotic resistance genes (ARGs) in gravity sewerage. The spatial distribution of ARGs along the drainage pipe line (from human settlements to wastewater treatement pant (WWTP)) was insignificant, which may be affected by irregular human emission alongside the pipeline. The correlation between ARGs and antibiotics in sewage was insignificant. The temporal distribution showed that the effect of temperature on ARGs abundance was evident, the ARGs abundance in sewage was generally higher during the cold season. Metagenomic analysis revealed that the detected ARGs were mainly distributed in Proteobacteria (47.51 %) and Antinobacteria (20.11 %). Potential hosts of ARGs in sewage were mainly identified as human gut microorganisms, including human pathogenic bacteria, such as Prevotella, Kocuria, and Propionibacterium, etc. This study provides a new insight into the sewerage surveillance tracking characteristics of human ARGs in sewer system, and suggesting that the sewage-carried ARGs surveillance is a promising method for assessment and management of antibiotic resistance level on population size.

Research on the Relationship Between College Physical Education and Students Physical Fitness Development: Based on the Comparison of Different Sports Programs

This paper discusses the influence of college physical education on the development of students physical quality, and focuses on comparing the different effects of different sports items on students physical quality. By analyzing the training characteristics of track and field, basketball, swimming and yoga and their influence on students physical fitness, this paper aims to provide reference for the setting of physical education courses in colleges and universities and promote the comprehensive development of students comprehensive quality. The research shows that different sports programs have different effects in promoting students strength, speed, endurance, sensitivity and flexibility, and provide powerful practical guidance for physical education in colleges and universities.

Graphene/MXene/Cellulose cellulosic paper-based flexible bifunctional sensors utilizing molecular bridge strategy with tunable piezoresistive effect for Temperature-Pressure sensing

Wearable technology is changing the way we interact with the digital world. Wearable systems can enable a smarter lifestyle when connected to other smart devices. This work reports a bifunctional sensor prepared from cellulosic paper as substrate for response to both temperature and pressure. The introduction of CMC-Na improves the dispersion of the binary hybrid conductive fillers in the deionized water. Meanwhile, relying on the intermolecular forces of both hydrogen bonding and cation-π interaction, the interfacial interactions of the binary hybrid conductive fillers are strengthened, which is anticipated to create a stable and homogenous conductive layer. And the concept of “effective conductive fillers distribution density” is introduced to explain and analyze the pressure sensing mechanism. The reported sensor has a pressure sensitivity of −1.6189 %/kPa, a sensing range of 370 kPa, and a response recovery time of 37.5 ms/37.5 ms. In addition to its response to mechanical force, the sensor has a detecting range of 23–58 °C, a response recovery time of 325 ms/1000 ms, and a temperature coefficient of resistance (TCR) of −1.77 %/°C. The potential applications of this sensor demonstrate the excellent gesture tracking characteristics, multi-point tactile sensing capability, and dual stimulus–response of the sensor.

Laser metal deposition of thin-walled parts of Al0.8CrFe2Ni2 high-entropy alloy: Process window, microstructure, wear resistance and mechanical anisotropy

In this paper, an exponential regression model is employed to analyze the sensitivity of the geometrical characteristics of single track, building efficiency and powder efficiency to the process parameters for the Al0.8CrFe2Ni2 high entropy alloy (HEA) fabricated by laser metal deposition (LMD). Based on the exponential regression model and sensitivity analysis, an effective process window is obtained to deposit a multilayer thin-walled structure. The Al0.8CrFe2Ni2 HEA consists of the (Fe, Cr, Ni)-rich faced centered cubic (FCC) phase and (Al, Ni)-rich B2 phase. An anisotropic mechanical property along the building direction and scanning direction is discovered due to the different strengthening mechanisms and fracture modes. Dislocation strengthening dominates in the building direction, while the high yield strength in the scanning direction is the result of dislocation, grain boundaries and precipitation strengthening. Compared to 400 °C, the Al0.8CrFe2Ni2 HEA has a lower wear rate at 25 °C owing to the self-lubricating protection provided by the completed oxide glaze layer. The findings provide guidelines for improving the anisotropic mechanical properties of thin-walled parts of LMD-deposited HEAs.

Research on the Optimization of Ship Trajectory Clustering Based on the OD–Hausdorff Distance

With the growth of global trade, port shipping is becoming more and more important. In this paper, an analysis of a ship’s inbound and outbound track characteristics is conducted using the OD–Hausdorff distance. The accuracy and efficiency of trajectory data analysis have been enhanced through clustering analysis. Trajectories are arranged in a time sequence, and representative port segments are selected. An improved OD–Hausdorff distance method is employed to capture the dynamic characteristics of a ship’s movements, such as speed and heading. Additionally, the DBSCAN algorithm is utilized for clustering, allowing for the processing of multidimensional AIS data. Data cleaning and preprocessing have ensured the reliability of the AIS data, and the Douglas–Peucker algorithm is used for trajectory simplification. Significant improvements in the accuracy and efficiency of trajectory clustering have been observed. Therefore, the main channel of the Guan River and the right side of Yanwei Port are usually followed by ships greater than 60 m in length, with a lateral Relative Mean Deviation (RMD) of 7.06%. Vessels shorter than 60 m have been shown to have greater path variability, with a lateral RMD of 7.94%. Additionally, a crossing pattern at Xiangshui Port is exhibited by ships shorter than 60 m due to the extension of berths and their positions at turns. Enhanced clustering accuracy has provided more precise trajectory patterns, which aids in better channel management.

A Study on the Structural, Wear, and Corrosion Properties of CoCuFeNiMo High-Entropy Alloy

This study investigates the structural properties, wear resistance and corrosion behavior of a CoCuFeNiMo equiatomic high-entropy alloy. The alloy was prepared using a vacuum arc melting device, and its structural properties were analyzed through X-ray diffraction (XRD) and scanning electron microscopy (SEM). Wear tests were conducted using a pin-on-disc machine against 4140 stainless steel at different loads. Corrosion behavior was evaluated through potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) in a 3.5wt% NaCl solution. The results indicated the presence of a major face-centered cubic (FCC) phase and a minor (µ) phase. The alloy exhibited segregation of Cu, attributed to positive mixing enthalpy. The coefficient of friction exhibited stability under lower loads but fluctuated under higher loads, possibly due to inhomogeneity in the microstructure caused by Cu segregation. Wear rates increased linearly with applied loads, indicating a direct relationship between load and wear properties. The worn surfaces displayed characteristics of mild abrasive wear, with delaminations, ploughing, and abrasive wear tracks. Pitting corrosion was observed, and the corrosion process was explained as the attack of Cl- ions leading to galvanic corrosion between different phases. In the corrosion analysis, the Ecorr value was -0.616V, and the icorr value was found to be 2.22 × 10-5 A/cm2.

Optimization of the cruising speed for high-speed trains to reduce energy consumed by motion resistances

As one of the effective measures to reduce energy consumption of high-speed railway, train operation control has gained much attention because of its cost-effectiveness. Conventional approaches to eco-driving generally rely on single-mass train models and lack a thorough investigation into the vehicle cruising process, which can overlook real-world operation conditions and hinder further improvements in energy efficiency. To address these issues, this paper proposes a comprehensive framework for optimizing the cruising speed of high-speed trains (HSTs) based on track conditions to reduce energy consumed by motion resistances (ECMR). Firstly, a multibody dynamics simulation model of the HST is developed and validated to accurately evaluate ECMR under a range of operation scenarios. Simulation results show that the impact of speed on ECMR varies considerably according to track characteristics. Subsequently, a neural network is constructed to derive the regressive relationship between operation conditions and ECMR. On this basis, an optimization model for the cruising speed under different track conditions is formulated to minimize the ECMR of a railway segment with a given operation time. Finally, the effectiveness of the model is validated through case studies, which demonstrate that ECMR can be reduced by up to 27.85% compared to traditional control strategies. The proposed optimization method can be integrated with current train speed profiles to further enhance energy efficiency. This framework has broad applicability for addressing engineering problems related to train operation optimization.

Experimental study on the dynamic characteristics of bi-block ballastless track under the combined action of vehicle load and temperature gradient

The unit ballastless track structure, persistently exposed to environmental conditions, experiences significant vertical temperature gradients, leading to warping deformation of the track bed and impacting track smoothness. This study investigates the relationship between temperature gradients and warping deformation of the track bed through the analysis of on-site measurement data combined with a dynamic simulation model. It also examines how temperature gradients influence the dynamic response and the interlayer contact area of the ballastless track. Findings reveal that vertical displacement of the track bed follows a diurnal cycle and shows a positive correlation with temperature gradients, with pronounced differences between the slab's corners and center. Under a positive temperature gradient, the vertical displacement of the track bed is high in the middle and low at the ends, with the vehicle load causing longitudinal tensile strain in the slab’s side surface center. Conversely, under a negative temperature gradient, the vertical displacement is low in the middle and high at the ends, with the vehicle load inducing longitudinal compressive strain in the slab’s side surface center. Additionally, warping deformation of the track bed leads to incomplete contact with the base plate, creating a local support state and reducing interlayer contact area as the gradient increases. Positive temperature gradients result in an "oval" distribution of interlayer delamination areas, while negative gradients mainly affect the sides and ends. Dynamic loads from trains temporarily counteract warping deformation, briefly increasing the interlayer contact area, but their effectiveness diminishes as temperature gradients rise.

Robust reinforcement learning control for quadrotor with input delay and uncertainties

In this paper, a new control method is proposed for the control of the quadrotor with time-varying input delay and uncertainties. The controller is primarily composed of two components: the reinforcement learning (RL) component and the robust component. The robust component is designed to ensure basic control performance. The basic control performance can guarantee the tracking characteristics with nonlinear uncertainties. The tracking error can be arbitrarily small by robust component. The RL component further improves the convergence speed and control precision on the basis of the basic control performance. Both components have input delay problems, and each component of the proposed method solves this problem separately. For the robust component, the filter is used to eliminate the uncertainties and restrain the influence of the input delay. It can ensure safety during the initial training period. For the RL component, the extended state method and the extending control period method are used to handle the problem of input delay with lower computational complexity. In addition, the convergence of network weights is proven, and the stability of the whole system is analyzed according to the Lyapunov method. Finally, simulation results are presented to illustrate the effectiveness and superior performance of our method.

Влияние режимов лазерной наплавки на геометрические размеры стального трека

Introduction. Laser surfacing is one of the leading trends in the field of additive technologies, which consists in layer-by-layer build of material using a laser as an energy source. To obtain a high-quality product, it is necessary to select the optimal building parameters correctly. The problem is that such optimization is necessary for all equipment, since minor differences in its characteristics can make significant changes in the parameters of layer-by-layer build. In order to determine the optimal build mode, it is enough to analyze the effect of various equipment parameters on the characteristics of single tracks. Therefore, the purpose of this work is to determine the most important parameters of laser radiation that affect the surfacing process and the optimal mode for building a single track of chromium-nickel steel. The work investigated single tracks obtained by laser surfacing of powder from austenitic chromium-nickel steel AISI 316L. The optimization factors included such characteristics as laser power, beam speed, flow rate of supplied powder and laser spot size. The wavelength of laser radiation was 1.07 μm. Research methods. To determine the quality and geometric dimensions of single tracks, the macrostructure of cross sections of specimens was studied using metallography and scanning electron microscopy methods. Results and discussion. It is established that the optimal mode for growing single tracks of steel AISI 316L is characterized by a laser radiation power of 1,250 W and a scanning speed of 25 mm/s. In this case, the optimal powder consumption rate is 12 g/min, and the laser spot size is 4.1 mm. The work shows that the powder consumption and laser spot size have the greatest influence on the coefficient of effective use of powder material. By changing it, the surfacing performance can be increased by 10–15 %.

Epidemiology of injuries in U.S. high school track and field throwing events from 2008 to 2019.

Injury characteristics of high school track and field throwing athletes in the United States are not well studied. Understanding epidemiology of injuries is important to identify treatment and prevention strategies. To describe injury rates and patterns in U.S. high school track and field throwing events from a longitudinal national sports injury surveillance system. Descriptive epidemiology study. Data were provided by the National High School Sports Related Injury Surveillance System, High School RIO (Reporting Information Online). Athletic trainers reported injury and exposure data through the High School RIO website on a weekly basis. An athlete exposure (AE) was defined as one athlete participating in one school-sanctioned practice or competition. Throwing events of discus, shot put, and javelin were analyzed in this study. Injury rate, rate ratios (RR), injury proportion ratios (IPR). U.S. high school athletes. A total of 267 track and field throwing injuries occurred during 5,486,279 AEs. Overall, the rate of injuries in competition was higher than in practice (RR 1.35, 95% confidence interval [CI] 1.01-1.80). In practice, the rate of injuries was higher for girls than boys (RR 1.53, 95% CI 1.12-2.08). The most frequently injured body part was the shoulder (21.7%), followed by the ankle (16.5%) and knee (12.0%). The most common types of injury were muscle strains (26.14%) and ligament sprains (25%). Recurrent injuries accounted for a higher proportion of chronic injuries compared to new injuries (IPR 1.85, 95% CI 1.16-2.97). This study described injury characteristics of high school track and field throwing athletes from 2008 to 2019. Based on our results, injury prevention may be particularly important for female throwers with prior injury.

Generation of Vessel Track Characteristics Using a Conditional Generative Adversarial Network (CGAN)

ABSTRACT Machine learning (ML) models often require large volumes of data to learn a given task. However, access and existence of training data can be difficult to acquire due to privacy laws and availability. A solution is to generate synthetic data that represents the real data. In the maritime environment, the ability to generate realistic vessel positional data is important for the development of ML models in ocean areas with scarce amounts of data, such as the Arctic, or for generating an abundance of anomalous or unique events needed for training detection models. This research explores the use of conditional generative adversarial networks (CGAN) to generate vessel displacement tracks over a 24-hour period in a constraint-free environment. The model is trained using Automatic Identification System (AIS) data that contains vessel tracking information. The results show that the CGAN is able to generate vessel displacement tracks for two different vessel types, cargo ships and pleasure crafts, for three months of the year (May, July, and September). To evaluate the usability of the generated data and robustness of the CGAN model, three ML vessel classification models using displacement track data are developed using generated data and tested with real data.