Sensor Instrumentation Research Articles

A new semi-analytical model for retrieving chlorophyll a concentration and magnitude of fluorescence in the South China Sea

The red band signal of the color spectrum is of significant interest because its remote sensing reflectance yields valuable information on phytoplankton. In this study, we combined a fluorescence model with a modified version of the Garver-Siegel-Maritorena (GSM) algorithm to retrieve the chlorophyll a concentration (Chla) and the magnitude of fluorescence in coastal waters. An analytical inverse optimization procedure was performed using the measured reflectance over the whole visible spectrum with a focus on the Ocean and Land Color Instrument (OLCI) sensor (from 413 to 709 nm). The coupled visible-infrared model (GSM&Fluo) was validated by a comparison with Chla that was measured in situ in a wide variety of productive coastal water conditions in the South China Sea. The coefficients of determination (r2) were 0.79 and 0.88 for the GSM and our algorithm, respectively. The combined approach produced more accurate results in our study location. The coupled GSM&Fluo model was able to avoid being trapped in a local optimum by adding an estimation of the fluorescence signal. The results also showed that the suspended particulate matter (SPM) played a major role in the magnitude of the reflectance peak in the chlorophyll fluorescence emission band, and the Fluorescence Line Height (FLH) calculated with a simple baseline approach tended to overestimate the true magnitude of the fluorescence emission as SPM increased.

Object Tracking Glove

Hand gestures are a type of nonverbal communication that can be applied to a variety of sectors, including deaf-mute communication, human–computer interaction (HCI), medical applications, robot control and home automation. Various strategies have been used in hand gesture research articles, including those based on instrumented sensor technology and computer vision. In this paper, we have proposed an object tracking glove that uses simple hand motions and sensor technology to operate computer systems. Withthe assistanceof the webcamthe colourofthe object over the glove is detectedand therefore thecolorare going to bereflected onthe PCscreen, this willbe accomplished withthe utilizationof IDE processingreferred to ascalibration. Withan easymovement of the hand, the pointerare oftenmoved tothe acceptablespot onthe PCduring thisapplication the hall sensor acts as a switch or button, which helps to open any menu or software application when the cursor is moved overthe specifiedmenu. Whenever the hall sensor is messed with the magnet then the data from the sensor passes to the microcontroller. This microcontroller sends data to the Bluetooth module, and the signals are then passed on to the system, allowing it to perform the actions. Our application controls the lights/fans of a room controlled using the glove.

Comparison of Head Impact Exposure Across Common Activities in Youth Soccer

The objective of this study was to compare head impact exposure across common training activities in soccer. Soccer is a popular youth sport in the United States, but repetitive head impacts during training may result in neurocognitive deficits. Current research has identified factors associated with increased head impact exposure in soccer, but research has yet to contextualize head impact exposure across soccer activities. Modifying practice structure may be an avenue for reducing head impact exposure and concussion risk in soccer. Eight U15 soccer players participated in this study for 2 soccer seasons. Players wore a custom instrumented mouthpiece sensor during all practices and games. On-field activities were recorded with a time-synchronized camera. Research personnel recorded the duration of all practice (e.g., technical training, team interaction) and game activities performed by each player, and film review was performed to identify all head contact events during each session. Head impact exposure was quantified in terms of peak kinematics and impacts per player per hour. The amount of time an athlete was exposed to an activity was also evaluated. Mixed effects models were used to compare peak kinematics and generalized linear models were used to compare impact rates across activity types. Activity types were associated with peak kinematics and impact rate. Technical training activities were associated with higher impact rates and lower mean kinematics compared to other activity types. Team interaction activities and game play were associated with the highest rotational kinematics, but the lowest impact rates. A similar number of player-to-player contact events occurred within technical training, team interaction, and game play activities. Interventions designed to reduce head impact frequency in soccer may benefit from targeting technical training activities; whereas, interventions designed to reduce head impact magnitude may benefit from targeting team interaction and game activities.

A Review of Sign Language Recognition Techniques

Sign language recognition is important for natural and convenient communication between deaf community and hearing majority. Hand gestures are a form of nonverbal communication that makes up the bulk of the communication between mute individuals, as sign language constitutes largely of hand gestures. Research works based on hand gestures have adopted many different techniques, including those based on instrumented sensor technology and computer vision. In other words, the hand sign can be classified under many headings, such as posture and gesture, as well as dynamic and static, or a hybrid of the two. This paper focuses on a review of the literature on computer based sign language recognition approaches, their motivations, techniques, observed limitations and suggestion for improvement.

Correlation analysis of Land Surface Temperature (LST) measurement using DJI Mavic Enterprise Dual Thermal and Landsat 8 Satellite Imagery (case study: Surabaya City)

Landsat 8 Satellite Imagery (Landsat Data Continuity Mission, LDCM) is a satellite product made by Orbital Science Corporation, which launched with The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments as the latest features. One of the Thermal Infrared Sensor (TIRS) instruments is called Band 10, that provide temperature information on the earth’s surface. As many research conduct the temperature comparison between satellite imagery analysis and land cover temperature has been come with positive correlation for both of the variable. As to prove the temperature relationship, it is necessary to validate the actual temperature values on the earth’s surface by conduct the temperature survey in the area using the temperature measurement tools. One of the tools is DJI Mavic Enterprise Dual Thermal camera as the camera that capable to take samples data of particular objects categories that included urban areas, waters, vegetation, open land, settlements, and industrial factories. Using the satellite imagery’s temperature data and the land cover temperature data survey, comparing and accuration assessment are needed to see how close the value of both variable. The data processing carried out that both of the data have a positive correlation as the relationship, which have a Pearson correlation value of 0.892 and sig. (2-tailed) at the number 0.000000068. This correlation value showed that the relationship between both data is acceptable as the both data can represent each other to conduct any research. However, as the satellite imagery contains 29,85% of cloud cover, the temperature obtained lower in the Landsat 8 satellite image rather than the actual temperature on the earth’s surface.

Experimental studies and a double gate JFET model for analog integrated circuits

One of directions of improving parameters of analog integrated circuits is a development of new and modernization of existing designs of integrated elements without significantly changing of a technological route of integrated circuit manufacturing with a simultaneous creation of new integrated elements models. The article considers the results of experimental studies of the double gate junction field-effect transistor manufactured according to the 3CBiT technological route of JSC Integral. Based on the obtained results, the electrical model of double gate junction field-effect transistor is proposed, which describes the features of its application in analog integrated circuits. Comparison of I-V characteristics of measurements results and created model simulation are presented. A small capacity and a reverse current of a double gate junction field-effect transistor top gate, an ability to compensate for the DC (direct current) component of an input current provide a significant improvement in the characteristics of analog integrated circuits such as electrometric operational amplifiers and charge-sensitive amplifiers. The developed double gate junction field-effect transistor can be used in signal readout devices required in the analog interfaces of space instrument sensors and nuclear electronics.

Plasmonic Biosensors for the Detection of Lung Cancer Biomarkers: A Review

Lung cancer is the most common and deadliest cancer type globally. Its early diagnosis can guarantee a five-year survival rate. Unfortunately, application of the available diagnosis methods such as computed tomography, chest radiograph, magnetic resonance imaging (MRI), ultrasound, low-dose CT scan, bone scans, positron emission tomography (PET), and biopsy is hindered due to one or more problems, such as phenotypic properties of tumours that prevent early detection, invasiveness, expensiveness, and time consumption. Detection of lung cancer biomarkers using a biosensor is reported to solve the problems. Among biosensors, optical biosensors attract greater attention due to being ultra-sensitive, free from electromagnetic interference, capable of wide dynamic range detection, free from the requirement of a reference electrode, free from electrical hazards, highly stable, capable of multiplexing detection, and having the potential for more information content than electrical transducers. Inspired by promising features of plasmonic sensors, including surface plasmon resonance (SPR), localised surface plasmon resonance (LSPR), and surface enhanced Raman scattering (SERS) such as ultra-sensitivity, single particle/molecular level detection capability, multiplexing capability, photostability, real-time measurement, label-free measurement, room temperature operation, naked-eye readability, and the ease of miniaturisation without sophisticated sensor chip fabrication and instrumentation, numerous plasmonic sensors for the detection of lung cancer biomarkers have been investigated. In this review, the principle plasmonic sensor is explained. In addition, novel strategies and modifications adopted for the detection of lung cancer biomarkers such as miRNA, carcinoembryonic antigen (CEA), cytokeratins, and volatile organic compounds (VOCs) using plasmonic sensors are also reported. Furthermore, the challenges and prospects of the plasmonic biosensors for the detection of lung cancer biomarkers are highlighted.

Simulation of the Schiaparelli Entry and Comparison to Aerosciences Flight Data

The European Space Agency flew an entry, descent, and landing demonstrator module called Schiaparelli that entered the atmosphere of Mars on 19 October 2016. The entry and descent instrumentation suite had sensors on both the heat shield and backshell and included forebody pressure transducers and thermocouples (Atmospheric Mars Entry and Landing Investigations and Analysis, or AMELIA), along with aftbody pressure transducers and heat flux (COMbined Aerothermal and Radiometer Sensors instrument package, or COMARS) and narrowband radiative heatflux sensors (Infrared CO Two Measurement, or ICOTOM). Because of the failed landing attempt, only a subset of the flight data was transmitted before and after plasma blackout. The goal of this paper is to present comparisons of the flight data with calculations using NASA’s aerodynamic and aeroheating simulation tools. Simulations were conducted at various angles of attack to compare against forebody pressure data and to infer the angle of attack used in full three-dimensional simulations to calculate the total heat flux at the sensor locations. Comparisons with the COMARS total heat flux data and backshell pressure data are presented. Furthermore, due to the sparse dataset, results are also compared with the reconstructed heat flux, which was calculated from an inverse analysis of the AMELIA thermocouple data. The simulations agree within 16% for both the total heat flux measured in flight and the heat flux reconstructed from the thermocouple data. A potential link between the Schiaparelli high spin rate observed during entry as documented in the anomaly report and the unexpected stagnation point pressure measurement is also discussed.

Phytoplankton Genera Structure Revealed from the Multispectral Vertical Diffuse Attenuation Coefficient

The composition of phytoplankton and the concentration of pigments in their cells make their absorption and specific absorption coefficients key parameters for bio-optical modeling. This study investigated whether the multispectral vertical diffuse attenuation coefficient of downward irradiance (Kd) gradients could be a good framework for accessing phytoplankton genera. In situ measurements of remote sensing reflectance (Rrs), obtained in an Amazon Floodplain Lake (Lago Grande do Curuai), were used to invert Kd, focusing on Sentinel-3/Ocean and Land Color Instrument (OLCI) sensor bands. After that, an analysis based on the organization of three-way tables (STATICO) was applied to evaluate the relationships between phytoplankton genera and Kd at different OLCI bands. Our results indicate that phytoplankton genera are organized according to their ability to use light intensity and different spectral ranges of visible light (400 to 700 nm). As the light availability changes seasonally, the structure of phytoplankton changes as well. Some genera, such as Microcystis, are adapted to low light intensity at 550–650 nm, therefore high values of Kd in this range would indicate the dominance of Microcysts. Other genera, such as Aulacoseira, are highly adapted to harvesting blue-green light with higher intensity and probably grow in lakes with lower concentrations of colored dissolved organic matter that highly absorbs blue light (405–498). These findings are an important step to describing phytoplankton communities using orbital data in tropical freshwater floodplains. Furthermore, this approach can be used with biodiversity indexes to access phytoplankton diversity in these environments.

Phycocyanin Monitoring in Some Spanish Water Bodies with Sentinel-2 Imagery

Remote sensing is an appropriate tool for water management. It allows the study of some of the main sources of pollution, such as cyanobacterial harmful algal blooms. These species are increasing due to eutrophication and the adverse effects of climate change. This leads to water quality loss, which has a major impact on the environment, including human water supplies, which consequently require more expensive purification processes. The application of satellite remote sensing images as bio-optical tools is an effective way to monitor and control phycocyanin concentrations, which indicate the presence of cyanobacteria. For this study, 90 geo-referenced phycocyanin measurements were performed in situ, using a Turner C3 Submersible Fluorometer and a laboratory spectrofluorometer, both calibrated with phycocyanin standard, in water bodies of the Iberian Peninsula. These samples were synchronized with Sentinel-2 satellite orbit. The images were processed using Sentinel Application Program software and corrected with the Case 2 Regional Coast color-extended atmospheric correction tool. To produce algorithms that would help to obtain the phycocyanin concentration from the reflectance measured by the multispectral instrument sensor of the satellite, the following band combinations were tested, among others: band 665 nm, band 705 nm, and band 740 nm. The samples were equally divided: half were used for the algorithm’s calibration, and the other half for its validation. With the best adjustment, the algorithm was made more robust and accurate through a recalculation, obtaining a determination coefficient of 0.7, a Root Mean Square Error of 8.1 µg L−1, and a Relative Root Mean Square Error of 19%. In several reservoirs, we observed alarming phycocyanin concentrations that may trigger many environmental health problems, as established by the World Health Organization. Remote sensing provides a rapid monitoring method for the temporal and spatial distribution of these cyanobacteria blooms to ensure good preventive management and control, in order to improve the environmental quality of inland waters.

Human Computer Interaction – Hand Gesture Recognition

The creation of intelligent and natural interfaces between users and computer systems has received a lot of attention. Several modes of knowledge like visual, audio, and pen can be used individually or in combination have been proposed in support of this endeavour. Human communication relies heavily on the use of gestures to communicate information. Gesture recognition is a subject of science and language innovation that focuses on numerically quantifying human gestures. It is possible for people to communicate properly with machines using gesture recognition without the use of any mechanical devices. Hand gestures are a form of nonverbal communication that can be applied to several fields, including deaf-mute communication, robot control, human–computer interaction (HCI), home automation, and medical applications. Many different methods have been used in hand gesture research papers, including those focused on instrumented sensor technology and computer vision. To put it another way, the hand sign may be categorized under a variety of headings, including stance and motion, dynamic and static, or a combination of the two. This paper provides an extensive study on hand gesture methods and explores their applications.

TempSense: A Four-Channel Temperature Logger Based on a USB Bridge and CircuitPython

Accurate temperature measurements are needed to monitor and reduce energy use and greenhouse gas emissions in building, industrial, and other processes. This paper describes a temperature sensor instrument, named TempSense, developed for classroom demonstrations of thermal phenomena. The instrument can monitor, record, and visualize data from multiple temperature sensors using a K-type amplifier and thermocouples. It has an accuracy of ±2 deg C from -200 to +700 deg C and an accuracy of ±6 deg C from –270 to +1372 deg C. The instrument uses a USB bridge and the Python language to interface with open-source thermocouple amplifiers without the need for byte-level programming. Its design allows novice experimenters to inspect the build and operation and even customize it to their needs. TempSense can be extended via Python libraries to provide internet communication, visualization, and analysis.

Development of a Low-Power Instrumented Mouthpiece for Directly Measuring Head Acceleration in American Football.

Instrumented mouthpieces (IM) offer a means of measuring head impacts that occur in sport. Direct measurement of angular head kinematics is preferential for accuracy; however, existing IMs measure angular velocity and differentiate the measurement to calculate angular acceleration, which can limit bandwidth and consume more power. This study presents the development and validation of an IM that uses new, low-power accelerometers for direct measurement of linear and angular acceleration over a broad range of head impact conditions in American football. IM sensor accuracy for measuring six-degree-of-freedom head kinematics was assessed using two helmeted headforms instrumented with a custom-fit IM and reference sensor instrumentation. Head impacts were performed at 10 locations and 6 speeds representative of the on-field conditions associated with injurious and non-injurious impacts in American football. Sensor measurements from the IM were highly correlated with those from the reference instrumentation located at the maxilla and skull center of gravity. Based on pooled data across headform and impact location, R2 ≥ 0.94, mean absolute error (AE) ≤ 7%, and mean relative impact angle ≤ 11° for peak linear and angular acceleration and angular velocity while R2 ≥ 0.90 and mean AE ≤ 7% for kinematic-based injury metrics used in helmet tests.

The limnology and spectral behaviour of a freshwater lake at Harmony Point, Nelson Island, Antarctica

AbstractThe present study investigates the effect of limnology on the spectral reflectance of a freshwater lake, located in an ice-free area in the Antarctic Peninsula. Field-collected samples generated limnological and spectral parameters. This fact indicates that the studied lake has an ultra-oligotrophic/oligotrophic nature based on chlorophyll a (chl a), which registered concentrations below 3 μg l-1 with no total suspended solids, almost neutral pH and transparency equalled by depth. The water spectral behaviour in each sampling station indicates that the benthic characteristics of the lake have a strong influence as the reflectance at the 705 nm wavelength being greater than that at 583 nm signals the presence of soil and/or vegetation at its bottom. Hence, it is believed that the orbital sensors with spectral bands focused on regions between the green and red edge, such as the MultiSpectral Instrument (MSI) sensor, may present better results for distinguishing the different bottom types found in the research area.

Ionizing radiation influence on parameters of analog components of the master slice array МН2ХА030

Structured arrays and master slice arrays are often used to reduce cost, design and test time for radiation hardened analog integrated circuits. One of such master slice arrays is МН2ХА030, which uses bipolar and junction field-effect transistors. The purpose of this article is to estimate the effect of ionizing radiation on the parameters of the operational amplifier OAmp2 and comparators ADComp1 and ADComp3 created on the МН2ХА030 master slice array. Еhe results of measurements of analog components after exposure to 60Co gamma quanta with an absorbed dose of up to 700 krad and a fast electron fluence of up to 2.9·1015 el./cm2 with an energy of 6 MeV are presented. The OAmp2 operational amplifier provides a satisfactory level of basic static parameters (input current, offset voltage, voltage gain) at a fast electron fluence of up to 3.7·1014 el./cm2 with an energy of 6 MeV. There are a decrease in the voltage gain and an increase in the offset voltage at electron fluence of greater than 1015 el./cm2. The latter can be caused by a decrease in the efficiency of the common-mode signal feedback integrated into operational amplifier with a significant drop in current gain of bipolar transistors. All considered analog components provide a satisfactory level of basic static parameters at a fast electron fluence of up to 3.7·1014 el./cm2 with an energy of 6 MeV and an absorbed dose of 60Co gamma quanta of at least 700 krad. It is assumed that resistance of OAmp2, ADComp1, ADComp3 to the action of 60Co gamma quanta is significantly higher and requires further research. The developed analog components can be used in signal reading devices required in front-end of sensors for space instrumentation and nuclear electronics.

A Study on Characteristics of Vehicular Lateral Position on Rural Highways

Many pieces of research have concentrated on traffic speed, time headway, space headway, and so on under non-lane-based heterogeneous traffic streams. In contrast, limited studies have been conducted for analyzing and modeling the vehicular lateral position. The lateral position of vehicles plays an equally vital role in the development of microscopic models. Moreover, the vehicle characteristics such as the lateral position and speed are considered independent in the traffic simulation modeling, ignoring their correlation. This study investigates the relationship between the lateral position of vehicles with traffic speed on rural highways. For this purpose, the traffic data related to different vehicles’ lateral positions and speed were collected using an infra-red sensor instrument from the National Highways in India. The relationship of vehicles’ lateral position with the traffic speeds under different ranges is analyzed to understand their dependence. The study results show that the relationship between vehicles’ lateral position is significantly associated with the traffic speed. The study findings help formulate a microscopic simulation model to reproduce accurate maneuvering in the traffic stream, which is useful for analyzing traffic characteristics.

Quantifying Scales of Spatial Variability of Cyanobacteria in a Large, Eutrophic Lake Using Multiplatform Remote Sensing Tools

Harmful algal blooms of cyanobacteria are increasing in magnitude and frequency globally, degrading inland and coastal aquatic ecosystems and adversely affecting public health. Efforts to understand the structure and natural variability of these blooms range from point sampling methods to a wide array of remote sensing tools. This study aims to provide a comprehensive view of cyanobacterial blooms in Clear Lake, California — a shallow, polymictic, naturally eutrophic lake with a long record of episodic cyanobacteria blooms. To understand the spatial heterogeneity and temporal dynamics of cyanobacterial blooms, we evaluated a satellite remote sensing tool for estimating coarse cyanobacteria distribution with coincident, in situ measurements at varying scales and resolutions. The Cyanobacteria Index (CI) remote sensing algorithm was used to estimate cyanobacterial abundance in the top portion of the water column from data acquired from the Ocean and Land Color Instrument (OLCI) sensor on the Sentinel-3a satellite. We collected hyperspectral data from a handheld spectroradiometer; discrete 1 m integrated surface samples for chlorophyll-a and phycocyanin; multispectral imagery from small Unmanned Aerial System (sUAS) flights (∼12 cm resolution); Autonomous Underwater Vehicle (AUV) measurements of chlorophyll-a, turbidity, and colored dissolved organic matter (∼10 cm horizontal spacing, 1 m below the water surface); and meteorological forcing and lake temperature data to provide context to our cyanobacteria measurements. A semivariogram analysis of the high resolution AUV and sUAS data found the Critical Scale of Variability for cyanobacterial blooms to range from 70 to 175 m, which is finer than what is resolvable by the satellite data. We thus observed high spatial variability within each 300 m satellite pixel. Finally, we used the field spectroscopy data to evaluate the accuracy of both the original and revised CI algorithm. We found the revised CI algorithm was not effective in estimating cyanobacterial abundance for our study site. Satellite-based remote sensing tools are vital to researchers and water managers as they provide consistent, high-coverage data at a low cost and sampling effort. The findings of this research support continued development and refinement of remote sensing tools, which are essential for satellite monitoring of harmful algal blooms in lakes and reservoirs.

Comparative assessment of drought monitoring index susceptibility using geospatial techniques.

There are two main categories of dryness monitoring indices based on spectral feature space. One category uses the vertical distance from any point to a line passing through the coordinate origin, which is perpendicular to a soil line, to monitor the dryness conditions. The most popular indices are the Perpendicular Dryness Index (PDI) and the modified perpendicular dryness index (MPDI). The other category uses the distance from any point in feature space to the coordinate origin to represent the dryness status, for instance, the soil moisture (SM) monitoring index (SMMI) and the modified soil moisture monitoring index (MSMMI). In this study, the performances and differences of these four indicators were evaluated using field-measured SM (FSM) data based on Gaofen-1 (GF-1) wide field of view (WFV), Landsat-8 Operational Land Imager (OLI), and Sentinel-2 Multi-Spectral Instrument (MSI) sensors. Performance evaluations were conducted in two study areas, namely an arid and semi-arid region of northwest China and a humid agricultural region of southwest Canada. We employed gradient-based structural similarity (GSSIM) to quantitatively assess the similarity of the structural information and structural characteristics among these four indicators. Monitoring SM in bare soil or low vegetation-covered areas in the semi-arid region, the SMMI, PDI, MSMMI, and MPDI from Near-Infrared (NIR)-Red had significantly negative linear correlations with the FSM at 0-5-cm depth (P < 0.01). However, SMMI was better than PDI in estimating SM in bare soil, which was better than MSMMI and MPDI for GF-1. Moreover, the PDI and SMMI had similar SM evaluation abilities, which were better than those of MPDI and MSMMI for Landsat-8. The GSSIM map of the SMMI/PDI and the MSMMI/MPDI showed that the low change areas accounted for 99.89% and 98.89% for GF-1, respectively, and 95.78% and 94.45% for Landsat-8, respectively. This result indicated that the SMMI, PDI, MSMMI, and MPDI values from NIR-Red in low vegetation cover were similar. In monitoring SM in agricultural vegetation areas, the accuracy of the four indices from Short-Wave Infrared (SWIR) feature space was higher than that from NIR-Red feature space for Sentinel-2. The SM monitoring effect of MSMMI and MPDI was better than that of SMMI and PDI. Due to the lack of SWIR band, GF-1 was limited in monitoring SM in vegetation-covered areas. The SMMI and MSMMI, which do not rely on the soil line, were more suitable than PDI and MPDI for retrieving SM in the complex surface environment depending on the soil line and the number of parameters. GF-1 with 16-m resolution had higher accuracy in SM assessment than Landsat-8 with 30-m resolution and had almost the same accuracy as Sentinel-2 with 20 m.

Concussion History and Balance Performance in Adolescent Rugby Union Players

Background: Sports-related concussion is a worldwide problem. There is a concern that an initial concussion can cause prolonged subclinical disturbances to sensorimotor function that increase the risk of subsequent injury. The primary aim of this study was to examine whether a history of sports-related concussion has effects on static and dynamic balance performance in adolescent rugby players. Hypothesis: Dynamic balance would be worse in players with a history of concussion compared with those with no history of concussion. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Male adolescent rugby players aged 14 to 18 years from 5 schools were recruited before the start of the 2018-2019 playing season. Participants completed questionnaires and physical tests, including dynamic Y balance and single-leg static balance (eyes closed) tests, while performing single and dual tasks. Dynamic balance was assessed using inertial sensor instrumentation. Dependent variables were normalized reach distance and the sample entropy (SEn) of the 3 axes (x, y, and z). Results: Of the 195 participants, 100 reported a history of concussion. Those with a history of concussion demonstrated higher SEn in all directions, with highest values during anterior (standardized mean difference [SMD], 0.4; 95% CI, 0.0-0.7; P = .027) and posteromedial (SMD, 0.5; 95% CI, 0.2-0.9; P = .004) reach directions compared with those with no history. There was no difference between groups (concussion history vs control) in traditional Y balance reach distances in the anterior or posteromedial directions or single-leg static balance during both single- (P = .47) and dual-task (P = .67) conditions. Conclusion: Adolescent rugby union athletes with a history of concussion had poorer dynamic balance during performance tasks compared with healthy controls. Static single-leg balance tests, either single or dual task, may not be sensitive enough to detect sensorimotor deficits in those with a history of concussion.

Use of augmented reality-enabled prototyping of cyber-physical systems for improving cyber-security education

The use of augmented reality-enabled scenarios in cybersecurity teaching is proposed in the article to respond to new requirements for the rapid adoption of new technologies and profound knowledge of cybersecurity issues by professionals. Implementation of project-type activities based on real cybersecurity issues in application fields of cyber-physical systems is suggested to improve the competence forming. A use-case of agricultural cyber-physical system of systems is discussed as a viable example of augmented reality-enabled prototyping of cybersecurity risk-aware architecture. The necessary steps are analysis of general and business-specific tasks on cybersecurity, creation of a list of competencies, formalized in educational standards and curricula, development of gaming scenarios for the formation of hard and soft skills, development of the scenario management system for AR interfaces. The system using AR tools can be easily adapted to different cybersecurity training activities. Industrial cyber-physical systems may be vulnerable due to insecure wireless connectivity, lack of encryption, inadequate access policy. The project-based learning complex is focused on the implementation of a data acquisition, storage and processing platform for new sensor networks and instruments. Representing all the diverse information on different layers will be greatly improved by use of the developed holographic projection AR tools.