Relationships between Racket Arm Joint Moments and Racket Head Speed during the Badminton Jump Smash Performed by Elite Male Malaysian Players

Three-dimensional position data of nineteen elite male Malaysian badminton players performing a series of maximal jump smashes were collected using a motion capture system. A ‘resultant moments’ inverse dynamics analysis was performed on the racket arm joints (shoulder, elbow and wrist). Relationships between racket head speed and peak joint moments were quantified using correlational analyses, inclusive of a Benjamini–Hochberg correction for multiple-hypothesis testing. The racket head centre speed at racket–shuttlecock contact was, on average, 61.2 m/s with a peak of 68.5 m/s which equated to average shuttlecock speeds of 95.2 m/s with a peak of 105.0 m/s. The correlational analysis revealed that a larger shoulder internal rotation moment (r = 0.737), backwards shoulder plane of elevation moment (r = 0.614) and wrist extension moment (r = −0.564) were associated with greater racket head centre speed at racket–shuttlecock contact. Coaches should consider strengthening the musculature associated with shoulder internal rotation, plane of elevation and wrist extension. This work provides a unique analysis of the joint moments of the racket arm during the badminton jump smash performed by an elite population and highlights significant relationships between racket head speed and peak resultant joint moments.

Validity of the AdMos, Advanced Sport Instruments, GNSS Sensor for Use in Alpine Skiing

The AdMos receiver from Advanced Sport Instruments is a global navigation satellite system (GNSS) frequently used in alpine ski racing, with users from national and professional teams. Therefore, a validation was conducted for use of the AdMos in alpine skiing, using data from both recreational and competitive skiers. Athletes skied a total of 60 km in different measurement and skiing conditions, while carrying both an AdMos and a differential GNSS, which was used as the gold standard. From the GNSS position data, speed, acceleration, turn radius, trajectory incline and impulse were calculated as instantaneous and turn average measures for both GNSS systems and errors between the systems were calculated. The median and interquartile range (IQR) for the instantaneous errors were below 3.5 (3.5) m for horizontal plane position and below 7.0 (4.3) m for the 3D position. The median and IQR for instantaneous errors and turn average errors, respectively, were below 0.04 (0.24)/0.04 (0.16) m/s for speed, below 0.23 (1.06)/0.35 (0.63) m/s2 for acceleration, below 0.47 (5.65)/0.73 (5.3) m for turn radius, and below 0.043 (1.96)/0.42 (1.42) degrees for trajectory incline. The median and IQR for turn average impulse were 0.025 (0.099) BWs. The position error changed gradually and randomly over time, with low noise levels causing smooth trajectories of similar shape but spatially shifted from the true trajectory that allowed the position–time derivation of the performance parameters, and detection of turns with 3% median and 5% IQR error. The accuracy assessment revealed that (1) the error levels were comparable to other consumer-grade standalone GNSS units designed for sport; (2) the trajectories closely resembled the true trajectories but with a random shift that changed over time and had a low noise level; (3) there was a very low instantaneous speed error that may allow the detection of many performance aspects of skiing and other sports; and (4) there were larger instantaneous errors for the remaining performance parameters, which decreased substantially when averaged over a turn.

The catscape: spatial manifestation of a pet cat population with outdoor access

The domestic cat (Felis catus) is the most popular companion animal and the most abundant carnivore globally. It is also a pet with an immense ecological footprint, because even non-feral and food-subsidized cats are prolific predators. Whereas knowledge about the spatial behavior of individual domestic cats is growing, we still know little about how a local population of free-ranging pet cats occupies the landscape. Using a citizen science approach, we GPS-tagged 92 pet cats with outdoor access living in a residential area in southern Norway. The resulting position data allowed us to construct both individual home range kernels and a population-level utilization distribution. Our results reveal a dense predatory blanket that outdoor cats drape over and beyond the urban landscape. It is this population-level intensity surface - the catscape - that potential prey have to navigate. There were almost no gaps in the catscape within our residential study area and therefore few terrestrial refuges from potential cat predation. However, cats spent on average 79% of their outdoor time within 50 meters to their owner's home, which suggests that the primary impact is local and most acute for wildlife in the vicinity to homes with cats. We discuss the catscape as a conceptual and quantitative tool for better understanding and mitigating the environmental impact of domestic cats.

Increasing Step Rate Affects Rearfoot Kinematics and Ground Reaction Forces during Running

Relatively high frontal and transverse plane motion in the lower limbs during running have been thought to play a role in the development of some running-related injuries (RRIs). Increasing step rate has been shown to significantly alter lower limb kinematics and kinetics during running. The purpose of this study was to evaluate the effects of increasing step rate on rearfoot kinematics, and to confirm how ground reaction forces (GRFs) are adjusted with increased step rate. Twenty runners ran on a force instrumented treadmill while marker position data were collected under three conditions. Participants ran at their preferred pace and step rate, then +5% and +10% of their preferred step rate while being cued by a metronome for three minutes each. Sagittal and frontal plane angles for the rearfoot segment, tibial rotation, and GRFs were calculated during the stance phase of running. Significant decreases were observed in sagittal and frontal plane rearfoot angles, tibial rotation, vertical GRF, and anteroposterior GRF with increased step rate compared with the preferred step rate. Increasing step rate significantly decreased peak sagittal and frontal plane rearfoot and tibial rotation angles. These findings may have implications for some RRIs and gait retraining.

FP-Growth Algorithm for Discovering Region-Based Association Rule in the IoT Environment

With the development of the Internet of things (IoT), both types and amounts of spatial data collected from heterogeneous IoT devices are increasing. The increased spatial data are being actively utilized in the data mining field. The existing association rule mining algorithms find all items with high correlation in the entire data. Association rules that may appear differently for each region, however, may not be found when the association rules are searched for all data. In this paper, we propose region-based frequent pattern growth (RFP-Growth) to search for association rules by dense regions. First, RFP-Growth divides item transaction included position data into regions by a density-based clustering algorithm. Second, frequent pattern growth (FP-Growth) is performed for each transaction divided by region. The experimental results show that RFP-Growth discovers new association rules that the original FP-Growth cannot find in the whole data.

Numerical Study of Microplastic Dispersal in Simulated Coastal Waters Using CFD Approach

Microplastics are accumulated in coastal regions due to human activity. Although limited data from beach surveys show an increase in microplastics in marine habitats, continuous monitoring is required on microplastics loading and distribution in the marine environment. In this study, CFD numerical simulations using VOF and Airy wave models coupled with DPM were carried out to investigate the effects of various variables on microplastics motion and distribution in a simulated coastal marine environment. PET, PU, and PP microplastic particles were released from the oceanside to investigate the effects of microplastic type, size, and shape with two different ocean–water flow velocities and temperature conditions. Particle position data from their tracking were used to determine the effect of each variable on the spatial distribution of particles. The quantitative analysis of vertical and horizontal distribution of microplastics particles revealed that, with low water velocity, most of the large denser spherical PET and PU microplastics would sink towards the bottom and settle at the ocean floor, while most of the small non-spherical particles would float near the surface and travel towards the shoreline. For lighter PP microplastics, larger spherical particles would float more readily than denser spherical ones. Large spherical and smaller non-spherical PP particles travel farthest reporting to the shoreline. Increasing the oceanwater velocity altered the distribution patterns in which lighter PP particles, almost independent of shape and size, travel swiftly to the shoreline together with smaller non-spherical denser microplastics. Lastly, the simulation results revealed that the oceanwater temperature did not play any significant role in the spatial distribution of microplastic particles.

The “Hockey” Assist Makes the Difference—Validation of a Defensive Disruptiveness Model to Evaluate Passing Sequences in Elite Soccer

With the growing availability of position data in sports, spatiotemporal analysis in soccer is a topic of rising interest. The aim of this study is to validate a performance indicator, namely D-Def, measuring passing effectiveness. D-Def calculates the change of the teams’ centroid, centroids of formation lines (e.g., defensive line), teams’ surface area, and teams’ spread in the following three seconds after a pass and therefore results in a measure of disruption of the opponents’ defense following a pass. While this measure was introduced earlier, in this study we aim to prove the usefulness to evaluate attacking sequences. In this study, 258 games of Dutch Eredivisie season 2018/19 were included, resulting in 13,094 attacks. D-Def, pass length, pass velocity, and pass angle of the last four passes of each attack were calculated and compared between successful and unsuccessful attacks. D-Def showed higher values for passes of successful compared to unsuccessful attacks (0.001 < p ≤ 0.029, 0.06 ≤ d ≤ 0.23). This difference showed the highest effects sizes in the penultimate pass (d = 0.23) and the maximal D-Def value of an attack (d = 0.23). Passing length (0.001 < p ≤ 0.236, 0.08 ≤ d ≤ 0.17) and passing velocity (0.001 < p ≤ 0.690, −0.09 ≤ d ≤ 0.12) showed inconsistent results in discriminating between successful and unsuccessful attacks. The results indicate that D-Def is a useful indicator for the measurement of pass effectiveness in attacking sequences, highlighting that successful attacks are connected to disruptive passing. Within successful attacks, at least one high disruptive action (pass with D-Def > 28) needs to be present. In addition, the penultimate pass (“hockey assist”) of an attack seems crucial in characterizing successful attacks.

In the Neck of Time

<p>Numerous studies over the past decade have investigated to making human animation as realistic as possible, especially facial animation. Let’s consider facial animation for human speech. Animating a face, to match up to a speech, requires a lot of effort. Most of the process has now been automated to make it easier for the artist to create facial animation along with lip sync based on a speech provided by the user. While these systems concentrate on the mouth and tongue, where articulation of speech takes place, very little effort has gone to understand and to recreate the exact motion of the neck during speech. The neck plays an important role in voice production and hence it is essential to study the motion created by it. The purpose of this research is to study the motion of the neck during speech. This research makes two contributions. First, predicting the motion of the neck around the strap muscles for a given speech. This is achieved by training a program with position data of marker placed on the neck along with its speech analysis data. Second, understanding the basic neck motion during speech. This will help an artist understand how the neck should be animated during speech.</p>

In the Neck of Time

<p>Numerous studies over the past decade have investigated to making human animation as realistic as possible, especially facial animation. Let’s consider facial animation for human speech. Animating a face, to match up to a speech, requires a lot of effort. Most of the process has now been automated to make it easier for the artist to create facial animation along with lip sync based on a speech provided by the user. While these systems concentrate on the mouth and tongue, where articulation of speech takes place, very little effort has gone to understand and to recreate the exact motion of the neck during speech. The neck plays an important role in voice production and hence it is essential to study the motion created by it. The purpose of this research is to study the motion of the neck during speech. This research makes two contributions. First, predicting the motion of the neck around the strap muscles for a given speech. This is achieved by training a program with position data of marker placed on the neck along with its speech analysis data. Second, understanding the basic neck motion during speech. This will help an artist understand how the neck should be animated during speech.</p>

U.S. Housing as a Global Safe Asset: Evidence from China Shocks

This paper demonstrates that the measured stock of China's holding of U.S. assets could be much higher than indicated by the U.S. net international investment position data due to unrecorded historical Chinese in ows into an increasingly popular global safe haven asset: U.S. residential real estate. We first use aggregate capital ows data to show that the increase in unrecorded capital in ows in the U.S. balance of payment accounts over the past decade is mainly linked to in ows from China into U.S. housing markets. Then, using a unique web traffic dataset that provides a direct measure of Chinese demand for U.S. housing at the zip code level, we estimate via a difference-in-difference matching framework that house prices in major U.S. cities that are highly exposed to demand from China have on average grown 7 percentage points faster than similar neighborhoods with low exposure over the period 2010-2016. These average excess price growth gaps co-move closely with macro-level measures of U.S. capital in ows from China, and tend to widen following periods of economic stress in China, suggesting that Chinese households view U.S. housing as a safe haven asset.