Spherical Coefficients Research Articles

Tribological Properties and Seasonal Freezing Damage Evolution of Rotating Spherical Hinge Self-Lubricating Coating

The spherical hinge is an important part of rotating bridge construction, but over a long period of time, spherical hinge self-lubricating coating is easily eroded by water vapor. In this paper, the tribological properties and seasonal freezing damage evolution characteristics of a variety of rotating spherical hinge self-lubricating coating materials were studied by means of friction coefficient measurement experiments, friction and wear experiments and shear rheological experiments based on a self-developed indoor spherical hinge rotational friction coefficient tester. The results show that the self-developed indoor spherical hinge rotational friction coefficient tester can effectively and truly represent the working state and tribological properties of self-lubricating coating in practical engineering. A seasonal freezing environment has obvious influence on the tribological properties of spherical hinge self-lubricating coating, which is an irreversible process of deterioration. With the increase in the freezing–thawing cycle, the friction coefficient and viscosity of self-lubricating coating materials increase gradually, and the thixotropy and elastic recovery become worse and worse. When the content of graphene is 0.1%, the performance is the best. At room temperature and in a freeze–thaw environment, the friction coefficient of graphene grease is lower than that of PTFE 0.007 and 0.008, respectively. The diameter of the grinding plate is less than 0.075 mm and 0.001 mm, respectively. The maximum bite load without card is higher than 8.1% and 11.5%. The area of the thixotropic ring is lower than 41% and 42%. Phase transition points were higher than 42% and 64%. The apparent viscosity was higher than 6.6% and 74%. Graphene greases show the greatest bearing capacity, thixotropy and structural strength in conventional and seasonal freezing conditions and exhibit excellent tribological properties.

Experimental study and models of the settling of sand in heavy oil

In heavy crude oil, high viscosity exerts a large drag force on sand particles. In this paper, the influence of heavy oil viscosity on the natural settlement of sand is studied, and two models of settling velocity are established. These models have many practical applications such as calculating the time for sand to settle and designing separators and setting tanks. To visually observe and record the sand settlement process, transparent industrial white oil is used to simulate heavy oil in this study. The settling of individual particles of sand under the gravity force is experimentally studied, and drag coefficients are determined. Various models are used to predict drag coefficients of spherical and nonspherical particles, and predicted values are compared with experimental values. The results are analyzed to explore the influence of sand particle morphology on the prediction of drag coefficients. Two dimensionless settling velocity models are established and used to analyze the behavior of sand particles in heavy oil; the results prove the reliability and applicability of the settling velocity model. In this study, a nonspherical particle drag coefficient model has no advantage over a spherical particle drag coefficient model in terms of prediction accuracy. Thus, it is not necessary to consider the influence of sand particle morphology when making predictions of the characteristic parameters of sand sedimentation in heavy oil. An explicit settling velocity model is established on the basis of the Brown-Lawler drag coefficient model, and its prediction accuracy is greater than 90% for the settlement velocity of sand in heavy oil.

Varietal and moisture effect on physical properties of various pearl millet (Pennisetum glaucum) cultivars

Engineering properties of pearl millet varieties (Pusa composite 443, Pusa composite 701, Pusa1201 and Pusa1801) were evaluated at varying moisture content (10-25% wb). A significant varietal difference was found on studied properties. GMD, Surface area, thousand grain mass, the angle of repose, porosity, internal coefficient of friction, static coefficient of friction (Poly, GI, MS and Al) increased linearly with increase in moisture content within the range of 10 to 25% (w.b.) while the bulk density, true density and hardness decreased linearly with increase in moisture content within the same range. But the value of sphericity showed that direct and indirect relation with moisture content depending variety. The mean value of different cultivars observed and found extreme high and low value of bulk density, true density and porosity for PC701 and Pusa1201, geometric mean diameter and surface area for pusa1801 to Pusa1201, sphericity and internal coefficient of friction for Pusa1201 and PC443, grain mass for Pusa1801 and PC 701, angle of repose for Pusa1201 and PC701, hardness for PC701 and PC443 respectively at moisture ranges from 10 to 25% (wb).

Hypermetropia as a Risk Factor for Age-Related Macular Degeneration. Review

The authors presented a complete comprehensive analysis of the combined data of 11 cross-sectional (static) and 11 longitudinal cohort studies with follow-up durations of 5 to 14 years, 16 case-control studies, as well as 3 systemic meta-analyses and 1 “umbrella” study evaluating the scientific hypothesis that hypermetropia is a risk factor for the development of age-related macular degeneration (AMD). In these studies, AMD was verified against the diagnostic criteria of three different classification systems: those of the National Eye Institute (USA), the International System for the Study of Age-Related Maculopathy, and the Wisconsin Classification WARMGS. A total of 82308 patients with AMD were enrolled. 3 baseline indicators in the population were analyzed: the initial hypermetropia, the spherical coefficient (SE) and the axial length of the eye (AL), on the one hand, and the prevalence of AMD, on the other hand. Traditional statistical indicators were calculated: the risk ratio (RR) of AMD among hypermetropes compared to emetropes and a 95 % confidence interval (CI). Pooled data from meta-analyses showed significant associations between farsightedness, SE, AL, and the prevalence of early AMD. The combined RR and 95 % CI were: 1.13 (1.06–1.20), 1.10 (1.07–1.14), and 0.79 (0.73–0.85), respectively. An increase in SE by diopter was correlated with early AMD (RR 1.06; 95 % CI 1.02–1.10). The late AMD did not confirm its association with the refractive error. The umbrella meta-analysis lowered the statistical significance of this association for early AMD (RR 1.08, 95 % CI 1.01–1.18); with late AMD (RR 0.84, 95 % CI 0.77–0.91). In general, experts came to the conclusion that the likelihood of developing AMD depends on the refractive status of the patient.

Cumulative strain-based metrics for predicting subconcussive head impact exposure-related imaging changes in a cohort of American youth football players.

Youth football athletes are exposed to repetitive subconcussive head impacts during normal participation in the sport, and there is increasing concern about the long-term effects of these impacts. The objective of the current study was to determine if strain-based cumulative exposure measures are superior to kinematic-based exposure measures for predicting imaging changes in the brain. This prospective, longitudinal cohort study was conducted from 2012 to 2017 and assessed youth, male football athletes. Kinematic data were collected at all practices and games from enrolled athletes participating in local youth football organizations in Winston-Salem, North Carolina, and were used to calculate multiple risk-weighted cumulative exposure (RWE) kinematic metrics and 36 strain-based exposure metrics. Pre- and postseason imaging was performed at Wake Forest School of Medicine, and diffusion tensor imaging (DTI) measures, including fractional anisotropy (FA), and its components (CL, CP, and CS), and mean diffusivity (MD), were investigated. Included participants were youth football players ranging in age from 9 to 13 years. Exclusion criteria included any history of previous neurological illness, psychiatric illness, brain tumor, concussion within the past 6 months, and/or contraindication to MRI. A total of 95 male athletes (mean age 11.9 years [SD 1.0 years]) participated between 2012 and 2017, with some participating for multiple seasons, resulting in 116 unique athlete-seasons. Regression analysis revealed statistically significant linear relationships between the FA, linear coefficient (CL), and spherical coefficient (CS) and all strain exposure measures, and well as the planar coefficient (CP) and 8 strain measures. For the kinematic exposure measures, there were statistically significant relationships between FA and RWE linear (RWEL) and RWE combined probability (RWECP) as well as CS and RWEL. According to area under the receiver operating characteristic (ROC) curve (AUC) analysis, the best-performing metrics were all strain measures, and included metrics based on tensile, compressive, and shear strain. Using ROC curves and AUC analysis, all exposure metrics were ranked in order of performance, and the results demonstrated that all the strain-based metrics performed better than any of the kinematic metrics, indicating that strain-based metrics are better discriminators of imaging changes than kinematic-based measures. Studies relating the biomechanics of head impacts with brain imaging and cognitive function may allow equipment designers, care providers, and organizations to prevent, identify, and treat injuries in order to make football a safer activity.

Phaseless Spherical Near-Field to Far-Field Transformation Algorithm via Sparsity of Spherical Mode Coefficients

In order to overcome the difficulty in obtaining accurate phase information in antenna near-field measurement, this study proposes a phase recovery algorithm that can be applied to phaseless spherical near-field sampling data. Based on the sparsity of spherical mode coefficients (SMCs), under the condition of unknown sparsity level and low oversampling rate, the proposed algorithm can accurately recover SMC to obtain high-precision antenna radiation characteristics. To improve the recovery performance of the algorithm, a spherical sampling strategy matching with the algorithm is also presented. By calculating the correlation of the measurement matrix and comparing the accuracy of the reconstructed far field, a set of optimal parameter settings including the number of spheres, the distribution of the measurement points, radius difference, and polarization mode is determined. On the basis of the obtained measurement data, the performance advantage of the presented algorithm in recovering SMC is demonstrated.

Reflection and transmission coefficients of spherical waves at an interface separating two dissimilar viscoelastic solids

SUMMARY Spherical wave reflection and transmission (R/T) coefficients at an interface are not only of theoretical significance but also play an important role in the amplitude variation with offset (AVO) analysis of wide-angle reflection seismic data and cross-borehole surveys. For sources close to the interface the resulting wavefields cannot be adequately described in terms of a single incident plane wave. Rather, the spherical waves must be viewed as the superposition of an infinite number of plane waves. Moreover, the R/T coefficients for each individual plane wave in viscoelastic media have proven to be more complicated than expected due to the difficulty in selecting the correct vertical slowness. In such attenuating media the R/T coefficients cannot be properly determined by simply replacing the real elastic parameters with their complex viscoelastic counterparts. In this study, the reflection and transmission coefficients of spherical waves at a plane interface separating two dissimilar viscoelastic solids are rigorously investigated. The difficulty in selecting the vertical slowness is shown to be circumvented if the spherical wavefields are calculated from the plane wavefields using the Sommerfeld integral appropriate for the dissipative materials. However, some resulting phase curves of the complex spherical wave R/T coefficients tend to be of opposite sign to the corresponding phase curves of plane waves due to non-uniqueness of the latter for post-critical wave incidence. In this contribution we propose a new definition of spherical wave R/T coefficients for viscoelastic media which differs from the conventional one. Its advantages are that it is not explicitly expressed as a function of the R/T angles, it is valid for both P and S waves, yet it is consistent with the existing definitions of spherical wave R/T coefficients but is more robust. By way of examples we compute both spherical wave reflection coefficients (SWRC) and spherical wave transmission coefficients (SWTC) for two different viscoelastic models. Unlike plane waves, both the SWRC and the SWTC of converted PS waves are found to be non-zero at vertical incidence and may be drastically affected by the existence of longitudinal PS waves which are confirmed by full waveform calculations for the converted PS waves.

Monothetic Analysis and Response Surface Methodology Optimization of Calcium Alginate Microcapsules Characteristics.

Owing to bio-polymer’s low-cost, environmental friendliness and mechanically stable nature, calcium alginate microcapsules have attracted much interest for their applications in numerous fields. Among the common production methods, the Electrospraying technique has shown a great potential due to smaller shape capsule production and ease of control of independent affecting parameters. Although one factor at a time (OFAT) can predict the trends of parameter effect on size and sphericity, it is inefficient in explaining the complex parameter interaction of the electrospray process. In the current study, the effects of the main parameters affecting on size and sphericity of the microcapsules using OFAT were optimized to attain calcium alginate microcapsules with an average diameter below 100 µm. Furthermore, we propose a statistical model employing the Surface Responses Methodology (RSM) and Central Composite Design (CDD) to generate a quadratic order linear regression model for the microcapsule diameter and sphericity coefficient. Experimentally, microcapsules with a size of 92.586 µm and sphericity coefficient of 0.771 were predicted and obtained from an alginate concentration of 2.013 w/v, with a flowrate of 0.560 mL/h, a needle size of 27 G and a 2.024 w/v calcium chloride concentration as optimum parameters. The optimization processes were successfully aligned towards formation of the spherical microcapsules with smaller average diameter of less than 100 µm, owing to the applied high voltage that reached up to 21 kV.

Studies and Applications of Dual Pore Saturation Model Based on Pore Structure Classification in Tight Reservoirs

The complex pore structure of rock may influence resistivity logs and make it challenging to perform saturation estimations with better precision. For example, water saturation may go higher or lower when Archie’s formulae are used to obtain the saturation as the logging resistivity may become greater or smaller, due to the influences of complex pore structures in the reservoirs. In this paper, having considered the influences of pore structure on logging resistivity, we have developed a different algorithm to improve the equivalent rock element model (EREM, a rock conduction model) to have better water saturation. First of all, the nuclear magnetic resonance (NMR) echo data of cores are inverted by using the optimized inversion to calculate pore parameters, such as the average radius of spherical pore tubular pore, Cd path, and sorting coefficient. Secondly, according to the parameters derived from the optimization inversions, the pore structures of the core are divided into different groups. Based on the classifications of the pore structure, the conduction parameters of rock for different pore structures are determined by fitting the experimental conduction data of rock with a damping factor. Finally, the working flow of calculating fluid saturation according to the EREM model is determined for different conduction parameters. The key feature of the improved EREM saturation model is to eliminate the influence of pore structure on rock conduction, highlight the influence of pore fluid on rock conduction, and then improve the calculation accuracy of saturation in it. The applications of our research show that the saturation estimations derived from the improved EREM model appear to be more reasonable in terms of the saturation value and its numerical trend. Thus, the improved EREM model has potential in petroleum exploration and exploitation.

Scattering of arbitrary-shaped optical polarized beams by a PEMC sphere

The generalized Lorenz-Mie theory (GLMT) for a laser beam of arbitrary shape illuminating a perfect electromagnetic conductor (PEMC) sphere is presented. Making use of the vector angular spectrum decomposition method (VASDM), and the multipole expansion method (MEM), in which any beam is expressed in terms of vector spherical wave functions (VSWFs) and beam shape coefficients (BSCs), the BSCs are obtained and expressed by a vector angular spectrum. The incident and scattering waves are expanded using VSWFs. A relation between the coefficients of the scattering fields and the BSCs of the incident beam is established considering the appropriate boundary conditions at the surface of the PEMC sphere. Expressions for the extinction, scattering, and absorption cross-sections are derived and computed. By isolating the co-polarization and cross-polarization components of the scattering coefficients, individual expressions of these physical quantities are also provided. Considering the vector Bessel and Airy polarized beams as examples, the total electric field intensity, scattering cross-section and its co-polarized and cross-polarized components are numerically computed and discussed. The effects of beam polarization, size parameter of the sphere, the admittance M, and beam parameters are analyzed. It has been found that the intensity and distribution of the total (incident + scattered) electric field intensity in the transverse (yz) plane depends on the incident beam characteristics and its polarization states. As the dimensionless size ka increases, the amplitude of the scattering cross-section increases and then decreases as ka increases. As the admittance parameter M changes, there are different characteristics if the incident beam is different. Nonetheless, there is a common behavior that the trend of the co-polarized component of the scattering cross-section decreases first and then increases regardless of the beam and its polarization state. When it comes to the trend of the cross-polarized component versus M, it is opposite to that of the co-polarized component. A few resonance peaks are manifested in the plots when the incident beam is radially or azimuthally polarized. The results may have promising applications in scattering, particle manipulation, optical trapping, and other related researches dealing with a sphere exhibiting rotary polarization.

An Improved Method for Reconstructing Antenna Radiation Pattern in a Loaded Reverberation Chamber

It has been experimentally demonstrated that the antenna pattern can be reconstructed using correlation coefficients and spherical wave expansion in a well-stirred large reverberation chamber (RC) when the antenna under test (AUT) has little impact on the testing environment, but the method becomes ineffective for loaded RCs. To solve this problem, we apply a compensation method to the pattern reconstruction process by using a reference antenna, enabling AUT pattern reconstruction in a loaded RC. In the proposed method, the original radiation pattern of the reference antenna is measured in an anechoic chamber (AC), and the transmission coefficients of the reference antenna are obtained according to the spherical wave coefficient expansion theory. Then, by rotating the reference antenna in the RC, the corresponding antenna correlation and autocorrelation coefficients are obtained, and the radiation pattern of the AUT is reconstructed by using the least square method. Finally, the near-field spherical scattering signals of the reference antenna are used to compensate for the reconstructed results of the AUT spherical wave coefficients, and an improved far-field radiation pattern of the AUT is obtained. The feasibility and effectiveness of the proposed method are verified by simulation and measurement in a loaded RC.

Correlation of Roundness and Sphericity with Complex Fourier Descriptors of 2-Dimensional Projected Images of Soil Particles

Roundness and sphericity have long been considered as measurements of the basic morphological properties of soil particles. Recent progress in optical image processing and analysis has enabled us to automate and rapidly perform Fourier analysis. Thus, obtaining complex Fourier descriptors describing the outline boundary of a 2-dimensional projected image of a soil particle could be performed. In this regard, we performed correlation analysis with the values of roundness, sphericity, and complex Fourier descriptor coefficients for 115 images of soil particles measured and reported in previous studies. The results of the statistical analysis revealed that roundness was strongly negatively correlated with Fourier descriptors of the order less than −5 or higher than +5. The width-to-length ratio sphericity was strongly correlated with the Fourier descriptor of the order of +2.

A simulation study on expansion of a small intestine model reactor

In vitro digestion models and bionic reactors are usually made of soft elastic materials, which can be expanded in certain cases. However, little is known about the expansion of these models and reactors and the effect of the expansion on the fluid flow and concentration distribution. In this study, the expansion of a simplified small intestine model reactor is investigated using COMSOL Multiphysics. The results showed that the expansion rate significantly increased as Young’s modulus decreased; the influence of Poisson’s ratio on the expansion of the model with similar materials can be neglected. The model’s expansion rate increases significantly as the inlet velocity and fluid viscosity increase. However, the expansion rate decreases as the model’s spherical coefficient increases. The maximum expansion rate of the model in the given scope of the factors can be predicted using the regression equation obtained from Response Surface Methodology (RSM). It can also be concluded that the higher maximum expansion rate caused the velocity in radial and axial directions to be reduced and the pressure slightly reduced. Meanwhile, the model’s expansion would result in a nonuniform concentration distribution of the fluid in the model, which leads to a longer residence time of the fluid.

Sound classification using evolving ensemble models and Particle Swarm Optimization

Automatic sound classification attracts increasing research attention owing to its vast applications, such as robot navigation, environmental sensing, musical instrument classification, medical diagnosis, and surveillance. In this research, we propose an ensemble convolutional bidirectional Long Short-Term Memory (CBiLSTM) network with optimal hyper-parameter selection for undertaking sound classification. We first transform each audio signal into a spectrogram representation using the Short-time Fourier transform (STFT). A Particle Swarm Optimization (PSO) variant is subsequently proposed to optimize the learning rate, weight decay, numbers of filters and hidden units in the convolutional and BiLSTM layers, respectively, in order to extract effective spatial–temporal characteristics from the spectrogram inputs. To tackle the issue of stagnation in optimization, the proposed algorithm incorporates local exploitation using secant and Newton–Raphson methods, promising leader generation using regular and irregular super-ellipse formulae, and three-dimensional spherical search coefficients. Moreover, it takes into account multiple fused elite signals in conjunction with numerical analysis based exploitation to balance between diversification and intensification. A variety of CBiLSTM networks with distinctive optimized settings are devised. An ensemble model is then constructed by incorporating a set of three yielded networks based on a majority voting scheme. Evaluated using several audio data sets, our ensemble CBiLSTM networks outperform those with default and optimal settings identified by other search methods, existing deep architectures and state-of-the-art related studies. In addition to sound classification tasks, the proposed PSO algorithm also outperforms a number of classical and advanced search methods for solving diverse unimodal and multimodal benchmark functions with statistical significance.

Association of Left Atrial Sphericity with Risk of Stroke in Patients with Atrial Fibrillation. Sub-Analysis of the ASSAM Study

PurposeThe study was designed to evaluate the value of left atrial (LA) sphericity (LASP) in the identification of patients with atrial fibrillation (AF) who had prior ischemic stroke. The secondary aim was to investigate the possibility of improving stroke risk assessment based on six geometrical variables of LA.MethodsThis prospective observational study involved 157 patients: 74 in the stroke group and 83 in the control. All patients had cardiac computed tomography (CT) performed to analyze LA volume and dimensions. LASP and the discriminant function of six geometrical measurements were calculated.ResultsMultivariate logistic regression analysis showed a significant association of stroke with and gender, diabetes, CHA2DS2-VASc score, LA anteroposterior diameter, and LA sphericity. Patients with prior stroke had lower LASP than those without (66.6 ± 10.3% vs. 70.5 ± 7%; p = 0.0062). The most accurate identification of patients with a history of ischemic stroke was achieved by using a function of six geometrical measurements, the sphericity and volume coefficient. The C-statistic was higher for the above discriminant function (0.7273) than for LASP (0.3974). The addition of the discriminant function to the CHA2DS2-VASc score increased the performance of the risk score alone.ConclusionLASP is associated with prior stroke in AF patients. The proposed new formula for identification of AF patients who are at risk of stroke, based on geometrical measurements of LA, is superior to the basic LASP in identification of AF patients with a history of stroke.

Evaluation approach for whole dose distribution in clinical cases using spherical projection and spherical harmonics expansion: spherical coefficient tensor and score method.

Whole dose distribution results from well-conceived treatment plans including patient-specific (location, size and shape of tumor, etc.) and facility-specific (clinical policy and goal, equipment, etc.) information. To evaluate the whole dose distribution efficiently and effectively, we propose a method to apply spherical projection and real spherical harmonics (SH) expansion, thus leading to the expanded coefficients as a rank-2 tensor, SH coefficient tensor, for every patient-specific dose distribution. To verify the feature of this tensor, we introduce Isomap from the manifold learning method and multi-dimensional scaling (MDS). Subsequently, we obtained the MDS distance representing similarity, η, and the SH score, ζ, which is a Frobenius norm of the SH coefficient tensor. These were then validated in the intensity-modulated radiation therapy (IMRT) data sets of: (i) 375 mixing treated regions, (ii) 135 head and neck (HN), and (iii) 132 prostate cases, respectively. The MDS map indicated that the SH coefficient tensor enabled a quantitative feature extraction of whole dose distributions. In particular, the SH score systematically detected irregular cases as the deviation higher than +1.5 standard deviations (SD) from the average case, which matched up with clinically irregular case that required very complicated dose distributions. In summary, the proposed SH coefficient tensor is a useful representation of the whole dose distribution. The SH score from the SH coefficient tensor is a convenient and simple criterion used to characterize the entire dose distributions, which is not dependent on the data set.

Spherical Coefficients of Slice Regular Functions

Given a quaternionic slice regular function f, we give a direct and effective way to compute the coefficients of its spherical expansion at any point. Such coefficients are obtained in terms of spherical and slice derivatives of the function itself. Afterwards, we compare the coefficients of f with those of its slice derivative partial _{c}f obtaining a countable family of differential equations satisfied by any slice regular function. The results are proved in all details and are accompanied to several examples. For some of the results, we also give alternative proofs.

Optimisation of alginate-pectin bead formulation using central composite design guided electrospray technique

Alginate-pectin beads act as a carrier in improving the oral bioavailability of bioactive compounds. Electrospray technique facilitates the production of uniform size and shape of alginate-pectin beads. Interaction between key electrospray process parameters affects the size and shape of the beads. A proper model should be employed to establish these correlating interactions. In the present work, the electrospray technique was guided with a central composite design (CCD) and response surface methodology (RSM). One quadratic and one linear model were obtained for size and sphericity coefficient, respectively. The CCD-RSM empirical model derived from the present work is essential to determine the significant factors and their levels in producing beads with consistent size and sphericity coefficient. The results indicated that the applied voltage had the most significant influence on size, while the alginate-pectin concentration was the most prominent factor in producing spherical beads. Spherical beads with a minimum size of 2.97 mm were obtained at an alginate-pectin concentration of 3.5%, a flow rate of 10.0 mL/h, an applied voltage of 2.4 kV, and a distance between the nozzle and the gelation bath of 16.0 cm.

Analysis of longitudinal head impact exposure and white matter integrity in returning youth football players.

The objective of this study was to characterize changes in head impact exposure (HIE) across multiple football seasons and to determine whether changes in HIE correlate with changes in imaging metrics in youth football players. On-field head impact data and pre- and postseason imaging data, including those produced by diffusion tensor imaging (DTI), were collected from youth football athletes with at least two consecutive seasons of data. ANCOVA was used to evaluate HIE variations (number of impacts, peak linear and rotational accelerations, and risk-weighted cumulative exposure) by season number. DTI scalar metrics, including fractional anisotropy, mean diffusivity, and linear, planar, and spherical anisotropy coefficients, were evaluated. A control group was used to determine the number of abnormal white matter voxels, which were defined as 2 standard deviations above or below the control group mean. The difference in the number of abnormal voxels between consecutive seasons was computed for each scalar metric and athlete. Linear regression analyses were performed to evaluate relationships between changes in HIE metrics and changes in DTI scalar metrics. There were 47 athletes with multiple consecutive seasons of HIE, and corresponding imaging data were available in a subsample (n = 19) of these. Increases and decreases in HIE metrics were observed among individual athletes from one season to the next, and no significant differences (all p > 0.05) in HIE metrics were observed by season number. Changes in the number of practice impacts, 50th percentile impacts per practice session, and 50th percentile impacts per session were significantly positively correlated with changes in abnormal voxels for all DTI metrics. These results demonstrate a significant positive association between changes in HIE metrics and changes in the numbers of abnormal voxels between consecutive seasons of youth football. Reducing the number and frequency of head impacts, especially during practice sessions, may decrease the number of abnormal imaging findings from one season to the next in youth football.

Frequency Interpolation of LOFAR Embedded Element Patterns Using Spherical Wave Expansion

This paper describes the use of spherical wave expansion (SWE) to model the embedded element patterns of the LOFAR low-band array. The goal is to reduce the amount of data needed to store the embedded element patterns. The coefficients are calculated using the Moore–Penrose pseudoinverse. The Fast Fourier Transform (FFT) is used to interpolate the coefficients in the frequency domain. It turned out that the embedded element patterns can be described by only 41.8% of the data needed to describe them directly if sampled at the Nyquist rate. The presented results show that a frequency resolution of 1 MHz is needed for proper interpolation of the spherical wave coefficients over the 80 MHz operating frequency band of the LOFAR low-band array. It is also shown that the error due to interpolation using the FFT is less than the error due to linear interpolation or cubic spline interpolation.