The effect of horseshoes and surfaces on horse and jockey centre of mass displacements at gallop

Horseshoes influence how horses’ hooves interact with different ground surfaces, during the impact, loading and push-off phases of a stride cycle. Consequently, they impact on the biomechanics of horses’ proximal limb segments and upper body. By implication, different shoe and surface combinations could drive changes in the magnitude and stability of movement patterns in horse-jockey dyads. This study aimed to quantify centre of mass (COM) displacements in horse-jockey dyads galloping on turf and artificial tracks in four shoeing conditions: 1) aluminium; 2) barefoot; 3) GluShu; and 4) steel. Thirteen retired racehorses and two jockeys at the British Racing School were recruited for this intervention study. Tri-axial acceleration data were collected close to the COM for the horse (girth) and jockey (kidney-belt), using iPhones (Apple Inc.) equipped with an iOS app (SensorLog, sample rate = 50 Hz). Shoe-surface combinations were tested in a randomized order and horse-jockey pairings remained constant. Tri-axial acceleration data from gallop runs were filtered using bandpass Butterworth filters with cut-off frequencies of 15 Hz and 1 Hz, then integrated for displacement using Matlab. Peak displacement was assessed in both directions (positive ‘maxima’, negative ‘minima’) along the cranio-caudal (CC, positive = forwards), medio-lateral (ML, positive = right) and dorso-ventral (DV, positive = up) axes for all strides with frequency ≥2 Hz (mean = 2.06 Hz). Linear mixed-models determined whether surfaces, shoes or shoe-surface interactions (fixed factors) significantly affected the displacement patterns observed, with day, run and horse-jockey pairs included as random factors; significance was set at p<0.05. Data indicated that surface-type significantly affected peak COM displacements in all directions for the horse (p<0.0005) and for all directions (p≤0.008) but forwards in the jockey. The largest differences were observed in the DV-axis, with an additional 5.7 mm and 2.5 mm of downwards displacement for the horse and jockey, respectively, on the artificial surface. Shoeing condition significantly affected all displacement parameters except ML-axis minima for the horse (p≤0.007), and all displacement parameters for the jockey (p<0.0005). Absolute differences were again largest vertically, with notable similarities amongst displacements from barefoot and aluminium trials compared to GluShu and steel. Shoe-surface interactions affected all but CC-axis minima for the jockey (p≤0.002), but only the ML-axis minima and maxima and DV-axis maxima for the horse (p≤0.008). The results support the idea that hoof-surface interface interventions can significantly affect horse and jockey upper-body displacements. Greater sink of hooves on impact, combined with increased push-off during the propulsive phase, could explain the higher vertical displacements on the artificial track. Variations in distal limb mass associated with shoe-type may drive compensatory COM displacements to minimize the energetic cost of movement. The artificial surface and steel shoes provoked the least CC-axis movement of the jockey, so may promote greatest stability. However, differences between horse and jockey mean displacements indicated DV-axis and CC-axis offsets with compensatory increases and decreases, suggesting the dyad might operate within displacement limits to maintain stability. Further work is needed to relate COM displacements to hoof kinematics and to determine whether there is an optimum configuration of COM displacement to optimise performance and minimise injury.

Lineament Extraction using Gravity Data in the Citarum Watershed

Lineament is one of the most important features showing subsurface elements or structural weakness such as faults. This study aims to identify subsurface lineament patterns using automatic lineament in Citarum watershed with gravity data. Satellite gravity data were used to generate a sub-surface lineament. Satellite gravity data corrected using Bouguer and terrain correction to obtain a complete Bouguer anomaly value. Butterworth filters were used to separate regional and residual anomaly from the complete Bouguer anomaly value. Residual anomaly gravity data used to analyze sub-surface lineament. Lineament generated using Line module in PCI Geomatica to obtain sub-surface lineament from gravity residual value. The orientations of lineaments and fault lines were created by using rose diagrams. The main trends observed in the lineament map could be recognized in these diagrams, showing a strongly major trend in NW-SE, and the subdominant directions were in N-S. Area with a high density of lineament located at the Southern part of the study area. High-density lineament might be correlated with fractured volcanic rock upstream of the Citarum watershed, meanwhile, low-density lineament is associated with low-density sediment. The high-density fracture might be associated with intensive tectonics and volcanism.

Optimized Analog Multi-Band Carrierless Amplitude and Phase Modulation for Visible Light Communication-Based Internet of Things Systems

This paper presents a multi-user Visible Light Communication (VLC)-based Internet of Things (IoT) system using multi band-Carrierless Amplitude and Phase (m-CAP) modulation for IoT applications. The proposed system uses a digital m-CAP modulator embedded in a ceiling LED light fixture and analog receivers, aiming at low-cost, low-power, and small-sized IoT devices. The performance was evaluated in terms of the filtering stage design and the usage of guard bands. Different pairs of emitter and receiver filters were considered. While Bessel and Butterworth analog filters were tested in the analog receiver, the digital m-CAP modulator pulse shaping filter considered raised cosine filters, as well as digital matched filters for the analog Bessel and Butterworth filters. Regarding the guard bands, two approaches were considered: either by using the raised cosine roll-off factor (bandwidth compression) or by suppressing the even bands. The Bit Error Rate (BER) performance was obtained by simulation. The usage of the Bessel filter in the receiver, along with a digital matched filter, proved to be the best solution, achieving a BER lower than 10−3 for an Eb/No of 6 dB, using a third-order filter. Furthermore, guard bands should be used in order to mitigate inter-band interference in order to have improved performance when multiple users intend to simultaneously communicate.

THREE DAYS MONITORING OF ACTIVITIES OF DAILY LIVING AMONG YOUNG HEALTHY ADULTS AND PARKINSON’S DISEASE PATIENTS

Parkinson’s Disease (PD) is a neurodegenerative disorder affecting the substantia nigra, which leads to more than half of PD patients are considered to be at high risk of falling. Recently, Inertial Measurement Unit (IMU) sensors have shown great promise in the classification of activities of daily living (ADL) such as walking, standing, sitting, and laying down, considered to be normal movement in daily life. Measuring physical activity level from longitudinal ADL monitoring among PD patients could provide insights into their fall mechanisms. In this study, six PD patients (mean age=74.3±6.5 years) and six young healthy subjects (mean age=19.7±2.7 years) were recruited. All the subjects were asked to wear the single accelerometer, DynaPort MM+ (Motion Monitor+, McRoberts BV, The Hague, Netherlands), with a sampling frequency of 100 Hz located at the L5-S1 spinal area for 3 days. Subjects maintained a log of activities they performed and only removed the sensor while showering or performing other aquatic activities. The resultant acceleration was filtered using high and low pass Butterworth filters to determine dynamic and stationary activities. As a result, it was found that healthy young subjects performed significantly more dynamic activities (13.2%) when compared to PD subjects (7%), in contrast, PD subjects (92.9%) had significantly more stationary activities than young healthy subjects (86.8%).

Fast algorithm for the determination of the optimum filter for bone SPECT image reconstruction

In SPECT, the reconstructed images are strongly affected by poisson noise, poor spatial resolution and bad contrast due to the radioactivity disintegration and procedures acquisition. In this paper, we propose an algorithm to improve the traditional FBP reconstruction and to choose the most suitable technique for bone SPECT image denoising. The proposed approach is composed of two steps. The first one consists of denoising the acquired sinograms using successively eight currently used filters in nuclear medicine: Wiener, Metz, Hamming, Hann, Shepp-Logan, Parzen, Butterworth and Gaussian combined with Butterworth filters. The second step is a simultaneous reconstruction of the axial slices using a new 3D FBP algorithm for each filter. A comparative study of these filters is tested and evaluated on a dataset containing thirty one bone SPECT image. The results show that the difference between these filters is statistically significantly different from each other (p<0.05) and the 3D FBP with the combination between Butterworth and Gaussian provide the best performance. The selected method is compared to three denoising methods. These methods are tested on a Shepp Logan phantom and bone SPECT images. Experimental results show that the 3D FBP reconstruction with the pre-processing combination (Gaussian (Std=0.3) + Butterworth (fc=0.47, ordre=3)) filter is more accurate and robust compared to other methods. It provides the highest performance in term of contrast, SNR, CNR ensuring a shorter processing time. It accelerates the reconstruction, reduces noise and artifacts while preserving detailed features. This approach could be considered as a valuable candidate to enhance the quality of the reconstructed bone SPECT image.

Modified Butterworth Filters in Solving the Inverse Problem of Analytical Design of Optimal Controllers

In this work, for linear stationary one-dimensional control objects, the inverse problem of analytical design of optimal controllers (ADOC) is considered, which consists in determining the weight coefficients of the quadratic functional of the optimality of the control process that provide the closed-loop control system with the specified values of the time of transient processes and overshoot. The time of the transient process (regulation time) of the synthesized system is understood in the sense of the classical theory of automatic control and is determined using a " tube" , the value of which is taken, in contrast to known works, equal to the required (desired) small value of the system overshoot of a few percent (2—5 %). The equality of the percentage values characterizing the " tube" and the desired overshoot of the synthesized system is a necessary condition for the maximum response rate of linear dynamic systems and, accordingly, ensures the unambiguity of the solution of the considered inverse ADOC problem in the class of fast-response systems. The proposed solution method provides for the transformation of the ADOC problem to the canonical form, in which the control object is described by a matrix differential equation in the Frobenius form, and the quality functional is defined as the integral of the sum of the products of the object’s canonical phase coordinates, as well as the square of the control signal with appropriate weight coefficients. It is shown that the solution of the inverse canonical ADOC problem is determined by the values of only three nonzero weight coefficients of the criterion, and one of them has a single value. The values of the other two coefficients are proposed to be found in the process of modeling the synthesized optimal control system from the conditions of providing for it a given control time and a given overshoot. To obtain numerical estimates of the two main weight coefficients of the quadratic quality criterion, the solution of the ADOC problem is considered with the limiting increase in the values of these weight coefficients. By the limiting solution of the ADOC problem, the transfer functions of dynamic systems with the limiting (maximum) speed are determined, which have a given overshoot of 4.321 %. The dynamical systems described by these transfer functions are called modified Butterworth filters due to the fact that the well-known Butterworth filters are obtained as their special case with a zero value of a certain constant. The parameters and indicators of the dynamics of these filters up to the sixth order are presented in the table. Using the indicators of Butterworth filters, numerical estimates of the weight coefficients of the quadratic quality criterion are established. Transfer functions of modified Butterworth filters are recommended to be used as reference transfer functions of synthesized high-speed control systems.

Butterworth filters as tracking differentiators

<div> <div> <div> <p>This letter describes how traditional Butterworth low pass filters can enhance the performance of the tracking differentiator introduced by Han by mitigating the effect of additive high frequency noise that corrupts the output measurement. The tracking differentiator obtains much of its utility from its realization in cascaded integral form. By combining the cascaded integral form realization of Butterworth low pass filters with its the noise rejection features one can design a tracking differentiator that is efficiently tuned to reject high frequency output noise. </p> </div> </div> </div>

Butterworth filters as tracking differentiators

<div> <div> <div> <p>This letter describes how traditional Butterworth low pass filters can enhance the performance of the tracking differentiator introduced by Han by mitigating the effect of additive high frequency noise that corrupts the output measurement. The tracking differentiator obtains much of its utility from its realization in cascaded integral form. By combining the cascaded integral form realization of Butterworth low pass filters with its the noise rejection features one can design a tracking differentiator that is efficiently tuned to reject high frequency output noise. </p> </div> </div> </div>