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Finding and identifying the minimal number of sensor nodes for a sensor network is one of the most basic problems for the implementation of distributed state estimators. Despite a plethora of research studied sensor networks, most of them ignored this problem or assumed the considered sensor network comes with an ideal number of sensor nodes. We revisit this problem in the current paper. To this end, the minimal number of sensor nodes problem is first formalized and a novel observability condition, namely, minimal nodes uniform observability (MNUO), is then proposed. Next, this MNUO is applied to study the stability issues of the distributed Kalman filtering algorithm. In what follows, under the condition of MNUO, conditions to ensure its stability are given and the results about the relation of the filtering performance before and after selecting the minimal number of sensor nodes are obtained. Finally, optimization solutions and an example are given to find the minimal number of sensor nodes for a sensor network.

In vitroinvestigations of host-pathogen interactions of viruses are reliant on suitable cell and tissue culture models. Results are only as good as the model they have been generated in. However, choosing cell models forin vitrowork often depends on what is available in labs or what has previously been used. Despite the vast increase in coronavirus research activity over the past few years, researchers are still heavily reliant on: non-human cells, for example Vero E6, highly heterogeneous or not fully differentiated cells, such as Calu-3, or naturally unsusceptible cells requiring overexpression of receptors and other accessory factors, such as ACE2 and TMPRSS2. Complex cell models, such as primary cell-derived air-liquid interface epithelial models are highly representative of human tissues but are expensive and time-consuming to develop and maintain. They have limited suitability for large-scale and high-throughput analysis.Using tissue-specific expression pattern as a selection criteria, we identified human kidney cells as an ideal target for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and broader coronavirus infection. We show the use of the highly characterized human kidney cell line Caki-1 for infection with three human coronaviruses:BetacoronavirusesSARS-CoV-2 and Middle Eastern respiratory syndrome coronavirus (MERS-CoV) andAlphacoronavirushuman coronavirus 229E (hCoV-229E). Caki-1 cells show equal or superior susceptibility to all three coronaviruses when compared to other commonly used cell lines for the cultivation of the respective virus. Antibody staining against SARS-CoV-2 N protein shows comparable replication rates. Using a panel of 21 antibodies in infected Caki-1 cells using immunocytochemistry shows the location of viral proteins during replication. In addition, Caki-1 cells were found to be susceptible to two other human respiratory viruses, influenza A virus and respiratory syncytial virus, making them an ideal model for cross-comparison of not only a broad range of coronaviruses but respiratory viruses in general.Author SummaryInvestigating how viruses interact with their host relies models used for laboratory research. The closer a model matches the host, the more conclusive results are. Complex cell systems based on primary epithelial or stem cells are the gold standard ofin vitroresearch. However, they are expensive, time consuming, and laborious to establish. Therefore, cell lines remain the backbone of virus research.Despite vastly increased research into human coronaviruses following the COVID-19 pandemic, researchers continue to rely on suboptimal cell line models, for example ells of non-human origin like the VeroE6 African Green Monkey cell line. Using known expression patterns of the entry factors of the COVID-19 causative agent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) we identified the Caki-1 cell line as a target for SARS-CoV-2. This cell line could be shown to be infectable with a wide range of coronaviruses including common cold virus hCoV-229E, epidemic virus MERS-CoV, and SARS-CoV-2 as well as other important respiratory viruses influenza A virus and respiratory syncytial virus. We could show that SARS-CoV-2 proteins can be stained for and localized in Caki-1 cells and the cells are competent of forming a cellular immune response. Together, this makes Caki-1 cells a unique tool for cross-virus comparison in one cell line.

An inward-looking wearable antenna can be used for radio communications with internal transceivers in vivo. The radio transmissions are recorded using an array of electric field sensors on the skin. This paper reports the effect of living tissue on a small cavity-backed slot antenna pressed onto soft tissue of the human torso at 2.09 GHz. In-vivo measurements were made on the skin surface at 13 torso locations using eight participants (age range, 22-68 years old), with body mass index ranging between 20.3 and 31.6 kg/m2 . Ultrasound imaging was used to determine the skin and fat thickness at every measurement location. The variation in the antenna input impedance measurements demonstrated that the human tissues (fat and muscle) affect the antenna impedance but the mismatch creates field strength measurement errors of less than 2 dB. Fat thickness in the range of 3-30 mm can slightly degrade the performance of these wearable antennas. These effects can be partly mitigated by selective location and antenna retuning to improve transceiver communications. Bioelectromagnetics. 2021. © 2021 Bioelectromagnetics Society.

Athlete movement data are integral for optimizing athlete-performance and can lead to reduced fatigue and in turn can mitigate injury risk. There is a substantial amount of scientific literature, which investigates the ability of computer-vision and inertial sensor technologies to classify sport-specific movements. The coupling of automatic sport action labeling and athlete-monitoring data can significantly enhance athlete work-load monitoring. Two recent systematic reviews of the literature, pertinent to sport-specific movement classification, revealed that the majority of journal articles use athlete-dependent classification model training and evaluation methods. These methods can significantly enhance model classification performance, particularly with movements which have high interathlete technique variation. This is because it enables models to learn features distinctive to all athletes during training. This letter details the training and evaluation of supervised machine learning models to automatically classify running surface (athletics track, hard sand, and soft sand) using features extracted from an upper-back inertial measurement unit sensor. Possible classification performance enhancement is demonstrated by comparing athlete independent and athlete dependent supervised machine learning methods. Using athlete dependent methods significantly increased the classification performance in terms of weighted average precision, recall, F1-score, and accuracy ( p ) .

Frequency-selective surfaces (FSSs), have various applications in microwave electromagnetics. This paper reports a solution to the current FSS challenges of flexibly, low profile, simple fabrication and polarization control using a novel structure operating across X and Ku frequency bands where a linearly polarized wave is rotated by 90°. The FSSs were fabricated by laser engraving a thin layer of $5\mu \text{m}$ aluminum on a $65~\mu \text{m}$ Mylar substrate with a relative permittivity of 2.7, and separated by a dielectric spacing layer of 0.9 mm polypropylene substrate, with a relative permittivity of 3. The co and cross-polarized reflection and transmission response of the structure was investigated using numerical modeling and was measured experimentally. A parametric study was also conducted focusing on key performance indicators, and specifically the bandwidth of the structure. The novelty of this polarization rotation structure lies in its ultra-thin profile ( $0.034~\lambda _{0}$ ), flexibility and significant transmission bandwidth. The fabricated prototypes experimental results were in good agreement with the simulated results, with a simulated −6 dB bandwidth of 61% and a measured −6dB bandwidth of 60%. Applications include antenna radomes where polarization is particularly important, as well as other polarization filtering applications which require a conformal low profile structure.

Radio signal strength indicator (RSSI)-based localization methods for wireless capsule endoscopy (WCE) application require a patient to wear on-body sensors detecting the RF signals from the capsule. The main advantage of WCE is to allow the patient to live normally and to move freely during the natural transit time, which could take up to 73 hours. Changes in posture can be accompanied by the movement of soft tissues in the abdominal region. This will affect the propagation path length between on-body receiving sensors and the ingested wireless capsule, and consequently the received signal strength (RSS). This article explores potential variations in RSSI measurements created by postural change. Retroreflective markers placed in direct contact with the skin of a participant were used to represent appropriate locations of the on-body slot antennas, which could be used for WCE localization. Optical motion capture technology was used to determine an estimate of the location of the markers and corresponding skin position for different postures. The relative displacement of the markers from their initial location (the standing posture) was a maximum of 24 mm for the lying posture (supine position) for the participant with a BMI of 29 kg/m2. The maximum variation of the surface electric field of 13.77 dB was calculated using the attenuation path loss (PL) model for the human abdominal region propagation environment at 2.45 GHz. If not anticipated, posture-induced variations in RSSI can produce misleading interpretations and will require adjustments of WCE localization algorithms.

Machine learning is a powerful tool for data classification and has been used to classify movement data recorded by wearable inertial sensors in general living and sports. Inertial sensors can provide valuable biofeedback in combat sports such as boxing, however, the use of such technology has not had a global uptake. If simple inertial sensor configurations can be used to automatically classify strike type, then cumbersome tasks such as video labelling can be bypassed and the foundation for automated workload monitoring of combat sport athletes is set. This investigation evaluates the classification performance of six different supervised machine learning models (tuned and untuned) when using two simple inertial sensor configurations (configuration 1&mdash, inertial sensor worn on both wrists, configuration 2&mdash, inertial sensor worn on both wrists and third thoracic vertebrae [T3]). When trained on one athlete, strike prediction accuracy was good using both configurations (sensor configuration 1 mean overall accuracy: 0.90 &plusmn, 0.12, sensor configuration 2 mean overall accuracy: 0.87 &plusmn, 0.09). There was no significant statistical difference in prediction accuracy between both configurations and tuned and untuned models (p &gt, 0.05). Moreover, there was no significant statistical difference in computational training time for tuned and untuned models (p &gt, 0.05). For sensor configuration 1, a support vector machine (SVM) model with a Gaussian rbf kernel performed the best (accuracy = 0.96), for sensor configuration 2, a multi-layered perceptron neural network (MLP-NN) model performed the best (accuracy = 0.98). Wearable inertial sensors can be used to accurately classify strike-type in boxing pad work, this means that cumbersome tasks such as video and notational analysis can be bypassed. Additionally, automated workload and performance monitoring of athletes throughout training camp is possible. Future investigations will evaluate the performance of this algorithm on a greater sample size and test the influence of impact window-size on prediction accuracy. Additionally, supervised machine learning models should be trained on data collected during sparring to see if high accuracy holds in a competition setting. This can help move closer towards automatic scoring in boxing.

We report a sensitive, yet low-cost biosensor based on laser induced graphene for femtomolar microRNA (miRNA) detection. Combined with the miRNA extraction and magnetic isolation process, the target miRNAs were purified for further detection using laser induced graphene sensor. The laser induced graphene was prepared by direct laser writing on commercial polyimide (PI) and patterned via a computer-aided design system as an electrode for electrochemical biosensing. We found that the laser reduction of PI resulted in nitrogen-doped porous graphene, not only improving its conductivity but also its sensitivity to nucleic acids. Preeclampsia specific miRNA hsa-miR-486-5p was magnetically purified and directly adsorbed on the surface of graphene electrode via graphene-miRNA affinity interaction. Surface attached miRNAs were then electrochemically quantified using [Fe(CN)6]3-/4- redox system. Our assay demonstrates detection of miRNA has-miR-486-5p up to concentrations as low as 10 fM with excellent reproducibility. Owing to its facile fabrication, low cost and high performance, the laser induced N-doped graphene biosensor presented here shows great potential for applications in detecting miRNA in biomedical applications.

A small slot antenna has desirable characteristics for radio communications and location of an internal transceiver in-vivo medical applications. The effect of coupling between two identical antennas on the human torso was measured between 2.1 GHz antennas on the skin surface. The effect of an external field was measured as a function of the angle in the horizontal plane to quantify noise isolation. The perimeter separation loss was approximately 0.25 dB/mm. The external radio source induces currents in the soft conducting tissue resulting in a sinc radiation pattern for the antenna/body combination with a front-to-back ratio of approximately 12 dB. As the UHF band is commonly used in many non-medical applications, there is concern that external radio sources can result in a reduced signal to noise ratio and perturbed field strength measurements on the skin.

A small slot antenna has desirable characteristics for radio communications and location of an internal transceiver in-vivo medical applications. The effect of coupling between two identical antennas on the human torso was measured between 2.1 GHz antennas on the skin surface. The effect of an external field was measured as a function of the angle in the horizontal plane to quantify noise isolation. The perimeter separation loss was approximately 0.25 dB/mm. The external radio source induces currents in the soft conducting tissue resulting in a sinc radiation pattern for the antenna/body combination with a front-to-back ratio of approximately 12 dB. As the UHF band is commonly used in many non-medical applications, there is concern that external radio sources can result in a reduced signal to noise ratio and perturbed field strength measurements on the skin.

Objective : The precise location of an ingested radio transmitter/sensor is of importance in gastroenterology studies. Given the complex geometry of the gut and the very large variations in human size and electromagnetic characteristics, inverse modeling from surface-based measurements is very complex, and a unique location solution is not possible. This paper proposes a simple method based on far-field approximation of the attenuated field from the ingested transmitter. Methods : The validation experiments for an ellipsoid cylinder using averaged electromagnetic properties of the human gastrointestinal tract (conductivity 0.87 S/m, relative permittivity 62) and a Hertzian dipole radiator inside the body with a frequency of 433 MHz were conducted assuming a receiver dynamic range of less than 100 dB. Results : The surface field intensity distribution patterns and the amplitude ranges were established for different positions and orientation of the dipole in every segment of the tract. The reliability of the method was verified by comparison with finite-difference time-domain modeling. Conclusion : The method provides an analytical solution to estimate the surface field intensity depending on the dipole location and orientation with a negligible computational cost. Significance : This efficient algorithm can be incorporated into an inversion algorithm for localization of wireless endoscopy sensors to allow precise targeted treatment.

Defects and cracks in dried natural timber (relative permittivity 2–5) may cause structural weakness and enhanced warping in structural beams. For a pine wood beam (1200 mm × 70 mm × 70 mm), microwave reflection (S11) and transmission (S21) measurements using a cavity-backed slot antenna on the wood surface showed the variations caused by imperfections and defects in the wood. Reflection measurements at 4.4 GHz increased (&gt, 5 dB) above a major knot evident on the wood surface when the E-field was parallel to the wood grain. Similar results were observed for air cavities, independent of depth from the wood surface. The presence of a metal bolt in an air hole increased S11 by 2 dB. In comparison, transmission measurements (S21) were increased by 6 dB for a metal screw centered in the cavity. A kiln-dried pine wood sample was saturated with water to increase its moisture content from 17% to 138%. Both parallel and perpendicular E-field measurements showed a difference of more than 15 dB above an open saw-cut slot in the water-saturated beam. The insertion of a brass plate in the open slot created a 7 dB rise in the S11 measurement (p &lt, 0.0003), while there was no significant variation for perpendicular orientation. By measuring the reflection coefficient, it was possible to detect the location of a crack through a change in its magnitude without a noticeable change (&lt, 0.01 GHz) in resonant frequency. These microwave measurements offer a simple, single-frequency non-destructive testing method of structural timber in situ, when one or more plane faces are accessible for direct antenna contact.

Running surfaces influence energy consumption and gait parameters including swing time and stance time. This paper compares running gait cycle time, swing time and stance time, recorded on an athletics track, soft sand, and hard sand. The training and evaluation of supervised machine learning models for running surface prediction were developed using an ankle-worn inertial sensor. Models were trained using statistical features extracted from six participants using gyroscope-based stride cycles. Six different model types were trained and the performance of each model was evaluated using precision, recall, F1-score, Matthews correlation coefficient, area under the precision–recall curve and accuracy. There was a significant statistical difference in swing time and stance time across the surfaces for all participants (p

Floating wireless sensor networks present unique communications challenges. Monopole and loop antennas have been used in seawater; however, a hemispherical antenna has the advantage of an increased efficiency and propagation range compared to other designs. This paper reports the design, construction, testing, and simulation of a hemispherical antenna and its propagation across the sea surface. Antenna modeling shows a return loss of −15 dB and a radiation efficiency of 57% in a partially submerged condition. The modeled and measured bandwidths were 47% and 36%, respectively. The radiation pattern corresponds to that of a vertical monopole antenna, when the hemisphere is floating on the water surface. Propagation range measurements in a calm coastal bay showed two separate attenuation trends of 2 dB/m and 4 dB/m, before and after the reference distance (40 m), respectively. The link range was greater than 135 m using a transmit power of 10 dBm and a receiver sensitivity of −100 dBm. Results show that the floating hemispherical antenna can be successfully deployed and used in wireless sensor network applications for coastal areas.

Humans move continuously as part of normal living, even when asleep. The health of your heart, lungs, and digestive system-and even your mental health-are greatly improved through exercise. In modern times, technical aids have significantly reduced opportunities for physical activity; e.g., jobs are more sedentary, household chores require less physical effort, and commuting usually involves sitting in a vehicle. The result is increased obesity and ill health in the population, with the extreme case of type 2 diabetes becoming far too common in youth and younger adults. Individuals, governments, and corporations (particularly in the fitness industries) attempt to counter this through various exercise schemes, and, given the human motivation to win, sports are thought to play a leading role.

Graphene has excellent mechanical and conducting properties. Scattering parameter measurements were made in W‐band (75‐110 GHz) on 25 mm × 25 mm monolayer graphene film printed on polyethylene terephthalate (PET) substrate. From near field measurements using WR10 horn antennas the surface conductivity was de‐embedded after calibrating the s11 data against the reflection of a copper plate of same cross‐sectional dimensions as the DUT and calibrating the s21 data against horn‐to‐horn measurements. A monolayer graphene strip (20 mm × 2 mm) printed on PET substrate (25 mm × 25 mm) showed higher reflection when it was aligned with the E field of the incident radiation (as compared to H field alignment). The surface conductivity of graphene was de‐embedded from s11 measurements using standard transmission line theory and from s21 measurements using cascade matrix theory. The measured real part of the surface conductivity of graphene ranges between 0.7 and 1.8 mS/sq.

The fundamental properties of carbon nanotube (CN) loop antennas have been determined using numerical modeling in both transmitting and receiving modes. The variation of the antenna impedance, reflection coefficient, radiation efficiency, Q- factor, and extinction cross section with varying loop radii was determined numerically using method-of-moment simulations incorporating the quantum mechanical conductivity of carbon nanotubes. Contrary to metallic loop antennas (well known for their inductive input impedance), the carbon nanotube loops with a large circumference show capacitive reactance over the entire frequency range. Therefore, one cannot make CN loop to act as an inductive radiator or even a simple inductor (when $\boldsymbol {ka} \to 0$ ) if the circumference is beyond ∼56 μm. However, the carbon nanotube loops with circumference smaller than ∼56 μm exhibit properties similar to ordinary loop antennas by going through antiresonance and then resonance regions. Despite the dispersive conductivity model, carbon nanotube loop antennas possess normalized dispersion relation, which is linearly related to the frequency.

Frequency-selective surfaces (FSSs) are commonly employed at microwave frequencies in electromagnetic filtering applications. This paper reports the use of cascaded dual miniaturized elements for radio secure environments where miniaturized elements have been used creating a reduced unit cell (μm. The linearly polarized transmission response was investigated numerically by exploring the scattering parameters and the surface currents at resonance. Miniaturized elements in both single and cascaded FSS structures, have been explored to create both broadband and multiband responses across the L and S frequency bands. The theoretical and experimental results were in good agreement for the fabricated dual element dual layer translated band-stop FSS, displaying a resonant frequency reduction of 70% compared to a square loop with the same dimensions, along with significantly broad operation bandwidths of 118% and 104% for simulated and measured, respectively. These improvements were due to the selection of the individual elements in the array, their geometric arrangement, and the introduction of additional layers with lateral offsets.

Researchers have heralded the power of inertial sensors as a reliable swimmer-centric monitoring technology, however, regular uptake of this technology has not become common practice. Twenty-six elite swimmers participated in this study. An IMU (100Hz/500Hz) sensor was secured in the participant's third lumbar vertebrae. Features were extracted from swimming data using two techniques: a novel intrastroke cycle segmentation technique and conventional sliding window technique. Six supervised machine learning models were assessed on stroke prediction performance. Models trained using both feature extraction methods demonstrated high performance (≥ 0.99 weighted average precision, recall, F1-score, area under ROC curve and accuracy), low computational training times (3 seconds - bar XGB and when hyperparameters were tuned) and low computational prediction times (1 second). Significant differences were observed in weighted average stroke prediction F1-score (

Direct Contact Membrane Distillation (DCMD) is a promising and feasible technology for water desalination. Most of the models used to simulate DCMD are one-dimensional and/or use a linear function of vapour pressure which relies on experimentally determined parameters. In this study, the model of DCMD using Nusselt correlations was improved by coupling the continuity, momentum, and energy equations to better capture the downstream alteration of flow field properties. A logarithmic function of vapour pressure, which is independent from experiments, was used. This allowed us to analyse DCMD with different membrane properties. The results of our developed model were in good agreement with the DCMD experimental results, with less than 7% deviation. System performance metrics, including water flux, temperature, and concentration polarisation coefficient and thermal efficiency, were analysed by varying inlet feed and permeate temperature, inlet velocity, inlet feed concentration, channel length. In addition, twenty-two commercial membranes were analysed to obtain a real vision on the influence of membrane characteristics on system performance metrics. The results showed that the feed temperature had the most significant effect on water flux and thermal efficiency. The increased feed temperature enhanced the water flux and thermal efficiency, however, it caused more concentration and temperature polarisation. On the other hand, the increased inlet velocity was found to provide increased water flux and reduced temperature and concertation polarisation as well. It was also found that the membrane properties, especially thickness and porosity, can affect the DCMD performance significantly. A two-fold increase of feed temperature increased the water flux and thermal efficiency, 10-fold and 27%, respectively, however, it caused an increase in temperature and concertation polarisation, at 48% and 34%, respectively. By increasing Reynolds number from 80 to 1600, the water flux, CPC, and TPC enhanced by 2.3-fold, 2%, and 21%, respectively. The increased feed concentration from 0 to 250 [g/L] caused a 26% reduction in water flux. To capture the downstream alteration of flow properties, it was shown that the ratio of inlet value to outlet value of system performance metrics decreased significantly throughout the module. Therefore, improvement over the conventional model is undeniable, as the new model can assist in achieving optimal operation conditions.

Measuring isotopic ratios is a sensitive technique used to obtain information on stellar nucleosynthesis and chemical evolution. We present measurements of the carbon and sulphur abundances in the interstellar medium of the central region of our Galaxy. The selected targets are the +50km/s Cloud and several l.o.s. clouds towards Sgr B2(N). Towards the +50km/s Cloud, we observed the J=2-1 rotational transitions of CS, C34S, 13CS, C33S, and 13C34S, and the J=3-2 transitions of CS and C34S with the IRAM-30m telescope, as well as the J=6-5 transitions of C34S and 13CS with the APEX 12m telescope, all in emission. The J=2-1 rotational transitions of CS, C34S, 13CS, and 13C34S were observed with ALMA in the envelope of Sgr B2(N), with those of CS and C34S also observed in the l.o.s. clouds towards Sgr B2(N), all in absorption. In the +50km/s Cloud we derive a 12C13C isotopic ratio of ~22.1, that leads, with the measured 13CS/C34S line intensity ratio, to a 32S/34S ratio of 16.3+3.0-2.4. We also derive the 32S/34S isotopic ratio more directly from the two isotopologues 13CS and 13C34S, which leads to an independent 32S/34S estimation of 16.3+2.1-1.7 and 17.9+-5.0 for the +50km/s Cloud and Sgr B2(N), respectively. We also obtain a 34S/33S ratio of ~4.3 in the +50 km/s Cloud. Previous studies observed a decreasing trend in the 32S/34S isotopic ratios when approaching the Galactic centre. Our result indicates a termination of this tendency at least at a galactocentric distance of 130-30+60 pc. This is at variance with findings based on 12C/13C, 14N/15N and 18O/17O isotope ratios, where the above-mentioned trend is observed to continue right to the central molecular zone. This can indicate a drop in the production of massive stars at the Galactic centre, in the same line as recent metallicity gradient studies, and opens the work towards a comparison with Galactic and stellar evolution models., Comment: 16 pages, 7 figures, accepted for publication by A&A

The accurate location of an internal radio transmitter is important for long-term patient monitoring. An inverse solution for the surface field attenuation-based algorithm provides a simple position estimation but is degraded by noise and movement artefacts. Using the minimum cost function between the predicted and experimentally received signal strength indicators (RSSI) for four skin-surface receivers, the localization accuracy within 10 mm was achieved even with movement and external Gaussian noise. The relationship between RMSE value of each coordinate component in 3D under various noise levels provides a location accuracy estimate.

Sand sports include running, volleyball, soccer, beach flags, ironman, and fitness training. An increased amount of soft tissue injuries have been widely reported. A novel technique of determining the surface stiffness of beach sand in-situ used a simple drop-test penetrometer. The relationship between drop height and the depth of penetration squared was linear (Pearson’s correlation coefficient r2 > 0.92). The stiffness ratio between the soft dry sand and ocean-saturated wet sand compacted by eight hours of coastal water exposure was approximately seven, which was similar to previously reported stiffness measurements in a sand box. However, the absolute stiffness values were much smaller. While this technique was manually operated, an automatic system is postulated for future studies.

Variability in the running surface can cause an athlete to alter their gait. Most literature report running on grass, a treadmill or athletics running tracks using inertial sensors. This study compares the signals obtained by 9 degrees of freedom (DOF) inertial-magnetic sensors incorporating an accelerometer (±16 g), gyroscope (±2000°/s) and magnetometer (±8 gauss). The sensors were placed on the participant’s shank, knee, lower spine and upper spine, and the participants were asked to run on three different surfaces (running track, hard sand and soft sand). The calculated player loads for a 400 m run on each surface type was very similar. The mean and standard deviation values were 577 ± 130, 581 ± 128, 568 ± 124 for soft sand, hard sand and the running track, respectively. This did not correlate with the participant’s self-assessment RPE (Rate of perceived exertion), which demonstrated running on soft sand to be significantly more challenging, yielding a mean and standard deviation of 5.3 ± 2.5 (Hard to Very Hard). Soft sand running had a decreased swing time duration but increased variability (0.44 ± 0.02 s—Swing Time, 6.5 ± 1.1%—CV), hard sand running had the longest swing and intermediate variability duration (0.46 ± 0.02 s—Swing Time, 3.30 ± 2.58 %—CV) and running track running had the medium swing time but lowest variability (0.45 ± 0.02 s, 2.7 ± 0.9%—CV). Gait dominance was not consistent across the surfaces for each participant and remained below a ratio of 0.4. These results provide an insight into how athletes modify their gait mechanics to accommodate different running surfaces.

The use of wearable technologies for the monitoring of human movement has increased considerably in the past few years, with applications to sports and other physical activities. Energy expenditure, walking and running distance, step count, and heart rate are some of the metrics provided by such devices via smart phone applications. Most of the research studies have involved validating the accuracy and reliability of the activity monitors by using the post-processed data from the device. The aim of this preliminary study was to determine if we can trust sensor data obtained from an Apple watch. This study evaluated the pre-processed data from the watch through step counting and heart rate measurements, and compared it with known validated devices (in-house 9DOF inertial sensor and Polar H10TM). Repeated activities (walking, jogging, and stair climbing) of varying duration and intensity were conducted by participants of varying age and body mass index (BMI). Pearson correlation (r > 0.95) and Bland–Altman statistical analyses were applied to the data to determine the level of agreement between the validated devices and the watch. The sensors from the Apple watch counted steps and measured heart rate with a minimum error and performed as expected.

The ability to measure and classify spin has been of great interest to cricket organizations, coaches, and athletes. While video is common, an alternative approach is to use 3D motion capture analysis with reflective spheres, which changes the aerodynamics of the ball. An instrumented cricket ball has proved to be effective in measuring high-speed spin rates using gyroscopes. In this study, an instrumented ball with a 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer located at the center mass of the ball was constructed. The spin rate was calculated using the magnetometer, and two spin types (off-spin and leg-spin) were classified. The sensor data was validated using motion capture. In addition, inertial measurement units (IMUs) mounted on the wrist and elbow of a wrist-spin and off-spin bowler were used to verify and validate the spin classification. The magnetometer can be effectively used in conjunction with conventional IMU sensors on the bowler’s arm to tailor training sessions by addressing deficiencies identified in a bowler’s spinning technique and to monitor their performance.

Heading the ball is an important skill in soccer. Head impacts are of concern because of the potential adverse health effects. Many elite players now wear GPS (that include inertial monitoring units) on the upper spine for location tracking and workload measurement. By measuring the maximum acceleration of the head and the upper spine, we calculated the acceleration ratio as an attenuation index for participants (n = 8) of different skill levels during a front heading activity. This would allow for in-field estimates of head impacts to be made and concussive events detected. For novice participants, the ratio was as high as 8.3 (mean value 5.0 &plusmn, 1.8), whereas, for experienced players, the mean ratio was 3.2 &plusmn, 1.5. Elite players stiffen the neck muscles to increase the ball velocity and so the torso acts as a support structure. Electromyography (EMG) signals that were recorded from the neck and shoulder before and after a training intervention showed a major increase in mean average muscle activity (146%, p = 3.39 &times, 10&minus, 6). This was accompanied by a major decrease in acceleration ratio (34.41%, p = 0.008). The average head-ball impact velocity was 1.95 &plusmn, 0.53 m/s determined while using optical motion capture. For this low velocity, the impact force was 102 &plusmn, 19 N, 13% of the published concussive force. The voluntary action of neck muscles decreases isolated head movements during heading. Coaches and trainers may use this evidence in their development of junior players.

Laser reduction of graphene oxide is a promising technology for manufacturing advanced devices such as supercapacitors, sensors and transistors, owing to its distinctive advantages in selective and localized GO reduction, direct micro-nanoscale patterning, and no requirement for chemicals. However, the fundamental mechanism underlying the laser induced reduction is still not well understood. In this paper, we demonstrate that by adjusting the power and scanning speed of a 780 nm femtosecond laser, not only can one distinguish, but also effectively tune, two coexisting sub-processes during the laser reduction, namely the direct conversion from sp3 to sp2 carbon and removal of oxygen functional groups. Different oxygen containing groups demonstrate varied degrees of reduction when the power of the laser was varied. Our study provides solid and direct evidence for the coexistence of two sub-processes in the laser induced reduction of graphene oxide, which is essential for both mechanistic understanding and practical adoption of this technique in real word applications.