Coupling Metrics Research Articles

A Component Selection Framework of Cohesion and Coupling Metrics

Component-based software engineering is concerned with the development of software that can satisfy the customer prerequisites through reuse or independent development. Coupling and cohesion measurements are primarily used to analyse the better software design quality, increase the reliability and reduced system software complexity. The complexity measurement of cohesion and coupling component to analyze the relationship between the component module. In this paper, proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the repository. It measures the interface density modules of coupling and cohesion in a modular software system. This cohesion measurement has been taken into two parameters for analyzing the result of complexity, with the help of low cohesion and high cohesion. In coupling measures between the component of inside parameters and outside parameters. The final process of coupling and cohesion, the measured values were used for the average calculation of components parameter. This paper measures the complexity of direct and indirect interaction among the component as well as the proposed algorithm selecting the optimal component for the repository. The better result is observed for high cohesion and low coupling in component-based software engineering.

Local structural-functional connectivity decoupling of caudate nucleus in infantile esotropia.

Abnormal brain structural and functional properties were demonstrated in patients with infantile esotropia (IE). However, few studies have investigated the interaction between structural and functional connectivity (SC-FC) in patients with IE. Structural network was generated with diffusion tensor imaging and functional network was constructed with resting-state functional magnetic resonance imaging for 18 patients with IE as well as 20 age- and gender- matched healthy subjects. The SC-FC coupling for global connectome, short connectome and long connectome were examined in IE patients and compared with those of healthy subjects. A linear mixed effects model was employed to examine the group-age interaction in terms of the coupling metrics. The Pearson correlation between coupling measures and strabismus degree was evaluated in IE patients, on which the regulatory effect of age was also investigated through hierarchical regression analysis. Significantly decreased SC-FC coupling score for short connections was observed in left caudate nucleus (CAU) in IE patients, whereas no brain regions exhibited altered coupling metrics for global connections or long connections. The group-age interaction was also evident in local coupling metrics of left CAU. The age-related regulatory effect on coupling-degree association was distinguishing between brain regions implicated in visual processing and cognition-related brain areas in IE patients. Local SC-FC decoupling in CAU was evident in patients with IE and was initiated in their early postnatal period, possibly interfering the visual cortico-striatal loop and subcortical optokinetic pathway subserving visual processing and nasalward optokinesis during neurodevelopment, which provides new insight into underlying neuropathological mechanism of IE.

What does the Literature Say about Local Productive Arrangements?

Among the types of agglomerations, there are the local productive arrangements (APLs), understood as territorial agglomerations of economic, political and social agents, which focus on a specific set of economic activities and have links between them. We sought to analyze the research results in APLs from a systematic review of the literature on the Web of Science, a database of journals. A textual corpus consisted of 29 articles, 65 authors and co-authors in 29 scientific journals from 1998 to 2020. We analyzed citation, cocitation and bibliographic coupling metrics using the VOSviewer software. The results show that APLs are a recent research topic, focusing on the European scenario. We verified that the publications diversified into different journals with good reputations. On the main themes, keywords related to small companies, industrial districts and the very concept of APLs predominate.

Evolution of land surface feedbacks on extreme heat: Adapting existing coupling metrics to a changing climate

Episodes of extreme heat are increasing globally, and dry land surface states have been implicated as an amplifying factor in several recent heat waves. Metrics used to quantify land-heat coupling in the current climate, relating sensible heat fluxes to near-surface air temperature, are applied to multimodel simulations of the past, present, and future climate to investigate the evolving role of land–atmosphere feedbacks in cases of extreme heat. Two related metrics are used: one that describes the climatological state of land-heat coupling and one that gives an episodic estimate of land feedbacks, here defined as the metric’s value at the 90th percentile of monthly mean temperatures. To provide robust statistics, seasonal multimodel medians are calculated, with the significance of changes determined by the degree of model consensus on the sign of the change. The climatological land-heat coupling mirrors other metrics of land–atmosphere interaction, peaking in transition regions between arid and humid climates. Changes from preindustrial to recent historical conditions are dominated by decreased land surface controls on extreme heat, mainly over the broad areas that have experienced expanded or intensified agriculture over the last 150 years. Future projections for increased atmospheric CO2 concentrations show a waning of areas of weakened land-heat feedbacks, while areas of increasing feedbacks expand over monsoon regions and much of the midlatitudes. The episodic land-heat metric is based on anomalies, which creates a quandary: how should anomalies be defined in a nonstationary climate? When the episodic coupling is defined relative to the means and variances for each period, a broadly similar evolution to the climatological metric is found, with historically dominant decreases giving way to widespread moderate increases in future climate scenarios. Basing all statistics on preindustrial norms results in huge increases in the coupling metric, showing its sensitivity to the definition of anomalies. When the metric is reformulated to isolate the impact of changing land and temperature variability, the tropics and Western Europe emerge as regions with enhanced land feedbacks on heatwaves, while desert areas and much of the remainder of the midlatitudes show reduced land-heat coupling.

In-Depth Analysis and Prediction of Coupling Metrics of Open Source Software Projects

This research was conducted to perform an in-depth analysis of the coupling metrics of 10 Open Source Software (OSS) projects obtained from the Comets dataset. More precisely, we analyze the dataset of object-oriented OSS projects (having 17 code related metrics such as coupling, complexity, and size metrics) to (1) examine the relationships among the coupling and other metrics (size, complexity), (2) analyze the pattern in the growth of software metrics, and (3) propose a model for prediction of coupling. To generalize the model of coupling prediction, we have applied different machine learning algorithms and validated their performance on similar datasets. The results indicated that the Random forests algorithm outperforms all other models. The relation analysis specifies the existence of strong positive relationships between the coupling, size, and complexity metrics while the pattern analysis pinpointed the increasing growth trend for coupling. The obtained outcomes will help the developers, project managers, and stakeholders in better understating the state of software health

Brains in Sync: Practical Guideline for Parent-Infant EEG During Natural Interaction.

Parent–infant EEG is a novel hyperscanning paradigm to measure social interaction simultaneously in the brains of parents and infants. The number of studies using parent–infant dual-EEG as a theoretical framework to measure brain-to-brain synchrony during interaction is rapidly growing, while the methodology for measuring synchrony is not yet uniform. While adult dual-EEG methodology is quickly improving, open databases, tutorials, and methodological validations for dual-EEG with infants are largely missing. In this practical guide, we provide a step-by-step manual on how to implement and run parent–infant EEG paradigms in a neurodevelopmental laboratory in naturalistic settings (e.g., free interactions). Next, we highlight insights on the variety of choices that can be made during (pre)processing dual-EEG data, including recommendations on interpersonal neural coupling metrics and interpretations of the results. Moreover, we provide an exemplar dataset of two mother–infant dyads during free interactions (“free play”) that may serve as practice material. Instead of providing a critical note, we would like to move the field of parent–infant EEG forward and be transparent about the challenges that come along with the exciting opportunity to study the development of our social brain within the naturalistic context of dual-EEG.

Seasonal Prediction of the Quasi‐Biennial Oscillation

AbstractThe ability to forecast the Quasi‐Biennial Oscillation (QBO) was examined using Version 2 of NASA's Global Earth Observing System Subseasonal‐to‐Seasonal (GEOS‐S2S) forecasting system. The vertical and time structure of the QBO was characterized by the principal components of the first two empirical orthogonal functions (EOFs). A set of 9‐month retrospective forecasts was initialized four times each month between 1981 and early 2019. Validation of 1–9 months forecasts from GEOS‐S2S showed that the S2S retrospective QBO forecasts improved skill in predicting the QBO EOF‐based amplitude and phase over a simple QBO phase propagation model at forecast lead times of 1–3 months. Results from an initial assessment of whether more accurate QBO forecasts can improve Northern Hemisphere winter sea level pressure forecasts showed no significant forecast improvement at a 1‐month lead time, indicating the need for improved stratosphere‐troposphere QBO coupling metrics, pathway identification, and QBO modeling. Overall, these results suggest that future improvements in representing the QBO in global models can increase the skill of 1–3 months QBO forecasts and potentially extend useful QBO forecasts beyond 3 months.

Towards Group Decision Support in the Software Maintenance Process

Software maintenance is an element-key of the life cycle of software. However,the techniques of software maintenance do not consider the diversity and the complexity of decisions which do not stop increasing. So, there are at present a few tools, susceptible to insure the relevance and the efficiency of the decision-making in this phase. The work presented in this paper aims to eliminate or at least to reduce the effect to fall in an expensive change by reducing the time to find a compromise on the adequate change. The development of the decision support system for software maintenance is an answer to the problem. The developed tool allows:-to make a fast diagnosis on the software by using the coupling metrics;-to help the decision-makers of the maintenance, according to their preferences often conflicting, to adopt a change among several proposed. To answer this group decision where various points of view are considered, we propose a negotiation protocol. This protocol try to find a compromise that suits best all the decision-makers.

Sensitivity of land–atmosphere coupling strength to changing atmospheric temperature and moisture over Europe

Abstract. The quantification of land–atmosphere coupling strength is still challenging, particularly in the atmospheric segment of the local coupling process chain. This is in part caused by a lack of spatially comprehensive observations of atmospheric temperature and specific humidity which form the verification basis for the common process-based coupling metrics. In this study, we aim at investigating where uncertainty in the atmospheric temperature and moisture affects the land–atmosphere coupling strength over Europe, and how changes in the mean temperature and moisture, as well as their vertical gradients, influence the coupling. For this purpose, we implemented systematic a posteriori modifications to the temperature and moisture fields from a regional climate simulation to create a spread in the atmospheric conditions. Afterwards, the process-based coupling metric convective triggering potential – low-level humidity index framework was applied to each modification case. Comparing all modification cases to the unmodified control case revealed that a strong coupling hotspot region in northeastern Europe was insensitive to temperature and moisture changes, although the number of potential coupling days varied by up to 20 d per summer season. The predominance of positive feedbacks remained unchanged in the northern part of the hotspot, and none of the modifications changed the frequent inhibition of feedbacks due to dry conditions in the atmosphere over the Mediterranean and the Iberian Peninsula. However, in the southern hotspot region in the north of the Black Sea, the dominant coupling class frequently switched between wet soil advantage and transition zone. Thus, both the coupling strength and the predominant sign of feedbacks were sensitive to changes in temperature and moisture in this region. This implies not only uncertainty in the quantification of land–atmosphere coupling strength but also the potential that climate-change-induced temperature and moisture changes considerably impact the climate there, because they also change the predominant atmospheric response to land surface wetness.

Multi-phase locking value: A generalized method for determining instantaneous multi-frequency phase coupling

BackgroundMany physical, biological and neural systems behave as coupled oscillators, with characteristic phase coupling across different frequencies. Methods such as n:m phase locking value (where two coupling frequencies are linked as: mf1=nf2) and bi-phase locking value have previously been proposed to quantify phase coupling between two resonant frequencies (e.g. f,2f/3) and across three frequencies (e.g. f1,f2,f1+f2), respectively. However, the existing phase coupling metrics have their limitations and limited applications. They cannot be used to detect or quantify phase coupling across multiple frequencies (e.g. f1,f2,f3,f4,f1+f2+f3-f4), or coupling that involves non-integer multiples of the frequencies (e.g. f1,f2,2f1/3+f2/3). New methodsTo address the gap, this paper proposes a generalized approach, named multi-phase locking value (M-PLV), for the quantification of various types of instantaneous multi-frequency phase coupling. Different from most instantaneous phase coupling metrics that measure the simultaneous phase coupling, the proposed M-PLV method also allows the detection of delayed phase coupling and the associated time lag between coupled oscillators. ResultsThe M-PLV has been tested on cases where synthetic coupled signals are generated using white Gaussian signals, and a system comprised of multiple coupled Rössler oscillators, as well as a human subject dataset. Results indicate that the M-PLV can provide a reliable estimation of the time window and frequency combination where the phase coupling is significant, as well as a precise determination of time lag in the case of delayed coupling. This method has the potential to become a powerful new tool for exploring phase coupling in complex nonlinear dynamic systems.

A method for monitoring the coupling evolution of microservice-based architectures

The microservice architecture is claimed to satisfy ongoing software development demands, such as resilience, flexibility, and velocity. However, developing applications based on microservices also brings some drawbacks, such as the increased software operational complexity. Recent studies have also pointed out the lack of methods to prevent problems related to the maintainability of these solutions. Disregarding established design principles during the software evolution may lead to the so-called architectural erosion, which can end up in a condition of unfeasible maintenance. As microservices can be considered a new architecture style, there are few initiatives to monitoring the evolution of software microservice-based architectures. In this paper, we introduce the SYMBIOTE method for monitoring the coupling evolution of microservice-based systems. More specifically, this method collects coupling metrics during runtime (staging or production environments) and monitors them throughout software evolution. The longitudinal analysis of the collected measures allows detecting an upward trend in coupling metrics that could represent signs of architectural degradation. To develop the proposed method, we performed an experimental analysis of the coupling metrics behavior using artificially generated data. The results of these experiment revealed the metrics behavior in different scenarios, providing insights to develop the analysis method for the identification of architectural degradation. We evaluated the SYMBIOTE method in a real-case open source project called Spinnaker. The results obtained in this evaluation show the relationship between architectural changes and upward trends in coupling metrics for most of the analyzed release intervals. Therefore, the first version of SYMBIOTE has shown potential to detect signs of architectural degradation during the evolution of microservice-based architectures.

Vovel metrics-novel coupling metrics for improved software fault prediction.

Software is a complex entity, and its development needs careful planning and a high amount of time and cost. To assess quality of program, software measures are very helpful. Amongst the existing measures, coupling is an important design measure, which computes the degree of interdependence among the entities of a software system. Higher coupling leads to cognitive complexity and thus a higher probability occurrence of faults. Well in time prediction of fault-prone modules assists in saving time and cost of testing. This paper aims to capture important aspects of coupling and then assess the effectiveness of these aspects in determining fault-prone entities in the software system. We propose two coupling metrics, i.e., Vovel-in and Vovel-out, that capture the level of coupling and the volume of information flow. We empirically evaluate the effectiveness of the Vovel metrics in determining the fault-prone classes using five projects, i.e., Eclipse JDT, Equinox framework, Apache Lucene, Mylyn, and Eclipse PDE UI. Model building is done using univariate logistic regression and later Spearman correlation coefficient is computed with the existing coupling metrics to assess the coverage of unique information. Finally, the least correlated metrics are used for building multivariate logistic regression with and without the use of Vovel metrics, to assess the effectiveness of Vovel metrics. The results show the proposed metrics significantly improve the predicting of fault prone classes. Moreover, the proposed metrics cover a significant amount of unique information which is not covered by the existing well-known coupling metrics, i.e., CBO, RFC, Fan-in, and Fan-out. This paper, empirically evaluates the impact of coupling metrics, and more specifically the importance of level and volume of coupling in software fault prediction. The results advocate the prudent addition of proposed metrics due to their unique information coverage and significant predictive ability.

Evaluation of a land-atmosphere coupling metric computed from a ground-based infrared interferometer

AbstractLand-atmosphere feedbacks are a critical component of the hydrologic cycle. Vertical profiles of boundary layer temperature and moisture, together with information about the land surface, are used to compute land-atmosphere coupling metrics. Ground based remote sensing platforms, such as the Atmospheric Emitted Radiance Interferometer (AERI), can provide high temporal resolution vertical profiles of temperature and moisture. When co-located with soil moisture, surface flux, and surface meteorological observations, such as at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, it is possible to observe both the terrestrial and atmospheric legs of land-atmosphere feedbacks. In this study, we compare a commonly used coupling metric computed from radiosonde-based data to that obtained from the AERI to characterize the accuracy and uncertainty in the metric derived from the two distinct platforms. This approach demonstrates the AERI’s utility where radiosonde observations are absent in time and/or space. Radiosonde and AERI based observations of the Convective Triggering Potential and Low-Level Humidity Index (CTP-HIlow) were computed during the 1200 UTC observation time and displayed good agreement during both 2017 and 2019 warm seasons. Radiosonde and AERI derived metrics diagnosed the same atmospheric preconditioning based upon the CTP-HIlow framework a majority of the time. When retrieval uncertainty was considered, even greater agreement was found between radiosonde and AERI derived classification. The AERI’s ability to represent this coupling metric well enabled novel exploration of temporal variability within the overnight period in CTP and HIlow. Observations of CTP-HIlow computed within a few hours of 1200 UTC were essentially equivalent, however with greater differences in time arose greater differences in CTP and HIlow.

Prognostic Implication of RV Coupling to Pulmonary Circulation for Successful Weaning From Extracorporeal Membrane Oxygenation

ObjectivesThe aim of this study was to explore if right ventricular (RV) contractile function and its coupling to pulmonary circulation (PC) were associated with successful weaning from venoarterial−extracorporeal membrane oxygenation (VA-ECMO) at maintenance of pump flow. BackgroundLimited data are available on predictors of successful weaning from VA-ECMO. MethodsA total of 79 patients with cardiogenic shock underwent transthoracic echocardiography to evaluate weaning from ECMO and were prospectively enrolled between 2016 and 2019. The noninvasively measured RV-PC coupling index was acquired by indexing tricuspid annular S' velocity, tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and RV free-wall longitudinal strain (FWLS) to right ventricular systolic pressure (RVSP). ResultsTransthoracic echocardiography was performed at a median 3.0 days (range 1 to 6 days) after ECMO initiation at a median ECMO flow of 3.2 l/min (range 3.0 to 3.6 l/min). The RV-PC coupling matrix, tricuspid annular S'/RVSP, TAPSE/RVSP, and RV FWLS/RVSP exhibited satisfactory predictive performances for predicting successful weaning from ECMO. Using the best cutoff values derived from the area under the receiver-operator characteristic curve, tricuspid annular S'/RVSP demonstrated a significantly better predictive performance than conventional echocardiographic parameters (left ventricular ejection fraction >20%, left ventricular outflow tract time-velocity integral ≥10 cm, and mitral annular S' ≥6 cm/s). ConclusionsEchocardiographic RV-PC coupling metrics exhibited a significantly better performance for predicting successful weaning from VA ECMO compared with conventional echocardiographic criteria at maintenance of pump flow.

Validating the Land-Atmosphere Coupling Behavior in Weather and Climate Models Using Observationally-Based Global Products

AbstractThe interactions between land and atmosphere (with terrestrial and atmospheric coupling segments) play a significant role in weather and climate. A predominant segment of land-atmosphere (L-A) feedbacks is the coupling between soil moisture (SM) and surface heat fluxes, the terrestrial coupling leg. The lack of high-quality long-term globally distributed observations, however, has hindered a robust, realistic identification of the terrestrial leg strength on a global scale. This exploratory study provides insight into how SM signals are translated into surface flux signals through the construction of a global depiction of the terrestrial leg from several recently developed global, gridded, observationally- and satellite-based data sets. The feasibility of producing global gridded estimates of L-A coupling metrics is explored. Five weather and climate models used for subseasonal to seasonal forecasting are confronted with the observational estimates to discern discrepancies that may affect their ability to predict phenomena related to L-A feedbacks, such as drought or heat waves. The terrestrial feedback leg from observations corroborates the “hot spots” of L-A coupling found in modeling studies, but the variances in daily time series of surface fluxes differ markedly. Better agreement and generally higher confidence are seen in metrics using latent heat flux than sensible heat flux. Observational metrics allow for clear stratification of model fidelity that is consistent across seasons, despite observational uncertainty. The results highlight the impact of SM on partitioning available surface energy and illustrate the potential of global observationally-based data sets for the assessment of such relationships in weather and climate models.

Land–Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes between ARM Observations, Reanalysis, and Climate Model Simulations

AbstractUsing the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land–atmosphere (LA) coupling in the North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the local coupling metrics. NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local LA coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases toward mid-to-late summers, which may be an amplification through a positive LA feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

Aspect-Oriented System Coupling Metric and its Validation

Background:Aspect-oriented programming promises to enhance the extensibility and reusability of code through the removal of tangled and crosscutting code. Determining the degree of coupling for Aspect- Oriented Systems (AOSs) would assist in the quantification of various software attributes and hence improve quality.Objective:The research aims to present a novel Aspect-oriented System Coupling Metric (COAO), that calculates the coupling for the complete aspect-oriented system as a whole, based on the properties of elements and the relationships among them.Methods:The process of defining a metric essentially requires a clear, unambiguous definition of primary and relevant concepts related to Aspect-Oriented Programming. As such, first and foremost, novel definitions of basic concepts such as system, element, relation, module, and attribute are specified concerning Aspect- Oriented Programming. Subsequently, a metric for Aspect-Oriented System Coupling is proposed. Subsequently, the proposed metric is validated theoretically against Braiand properties for coupling of software systems. Finally, an illustration for calculation of the proposed metric is demonstrated using an exemplary aspect-oriented system.Results:The findings reveal that the proposed Aspect-Oriented Coupling metric conforms to the five Property- Based software engineering measurements given by Braiand et al. for coupling. This indicates that the proposed metric for the Aspect-oriented System Coupling metric COAO is a valid metric for measuring coupling in Aspect-oriented Software Systems.Conclusion:Results of validation along with the supportive illustration show that single metric to assess coupling for the complete Aspect-oriented Software System is theoretically sound and also easies the calculation of coupling of a software system.

Reassessment of land–atmosphere interactions over India during summer monsoon using state-of-the-art regional climate models

The evaluation and characteristics of land-surface processes over the Indian Summer Monsoon (ISM) region are studied using Dirmeyer's two-legged land-atmosphere coupling metrics in regional climate modelling system. Different land-atmosphere coupling metrics are used for assessing the “hot-spots” of land atmosphere feedback over the Indian subcontinent. The model simulations are performed using regional climate model (RCM)—RegCMv4.0, 4.2 and 4.4.5.10 at different horizontal resolutions. The monthly soil wetness climatology over India is calculated using European Space Agency (ESA) datasets. Maximum soil moisture(SM) is found over the western part of central India during June–September. The results from RCM simulations (RegCMv4.0, 4.2 and 4.4.5.10) indicate more soil wetness, systematically (over-predicted) over North India, Indo-Gangetic plains and central India during June, July, August and September, implying that model soil wetness is driven by precipitation minus evapotranspiration (P-E). The role of aerosols in land–atmosphere interactions along with the impact of mixed convective parameterization schemes over ocean and land on modelling SM and land–atmosphere interactions is also addressed. The spatial and temporal variation of atmospheric and terrestrial coupling indices during ISM regime concludes that May, June, July and August are the prime months of land–atmosphere interactions over central and north-west India reiterating results from previous GLACE (The Global Land–Atmosphere Coupling Experiment) studies. Model simulations also indicate that during the ISM season the terrestrial segment of land–atmosphere coupling (i.e. terrestrial coupling index of soil moisture, SM) from SM to latent heat flux varies around 35–40 W m−2, while the atmospheric segment of coupling (i.e. atmospheric coupling index of precipitation) from latent heat flux to precipitation modulates around 4–6 mm/day. Aerosols are found to influence land-atmosphere interactions over north-west India by modulating net radiation. More in-situ observations of land surface variables are required for verification of land-atmospheric interactions (along with impact of aerosols) using RCMs.

An Acute Bout of Soccer Heading Subtly Alters Neurovascular Coupling Metrics.

Objective: The current investigation examined how a bout of soccer heading may impact brain function.Design: Semi-randomized crossover cohort.Setting: Controlled soccer heading.Participants: Seven male soccer players (24.1 ± 1.5 years).Intervention: 40 successful soccer headers were performed in 20 min (25 m, launch velocity ~80 km/h). X2 xPatch recorded linear and rotational head accelerations during each impact. A contact control “sham” condition – ball made body contact, but not by the head; and a no activity time “control” condition were also completed.Main Outcome Measures: Posterior and middle cerebral artery (PCA and MCA, respectively), cerebral blood velocity (CBV) was recorded during a visual task (neurovascular coupling: NVC) alongside SCAT3 symptoms scores pre/post a controlled bout of soccer heading.Results: Cumulative linear and rotational accelerations were 1,574 ± 97.9 g and 313,761 ± 23,966 rads/s2, respectively, during heading and changes in SCAT3 symptom number (pre: 2.6 ± 3.0; post: 6.7 ± 6.2, p = 0.13) and severity (pre: 3.7 ± 3.6, post: 9.4 ± 7.6, p = 0.11) were unchanged. In the PCA, no NVC differences were observed, including: relative CBV increase (28.0 ± 7.6%, p = 0.71) and total activation (188.7 ± 68.1 cm, p = 0.93). However, MCA-derived NVC metrics were blunted following heading, demonstrating decreased relative CBV increase (7.8 ± 3.1%, p = 0.03) and decreased total activation (26.7 ± 45.3 cm, p = 0.04).Conclusion: Although an acute bout of soccer heading did not result in an increase of concussion-like symptoms, there were alterations in NVC responses within the MCA during a visual task. This suggests an acute bout of repetitive soccer heading can alter CBV regulation within the region of the brain associated with the header impacts.

Evaluation of a Meandering Track Primary Topology for EV Roadway Charging

Many inductive power transfer dynamic systems have been proposed over the last decade; however, few consider interoperability to various secondaries in the design. This article proposes a limited-length two-phase meandering track primary to investigate the feasibility and tradeoffs between this multicoil track topology and a typical lumped pad primary topology for dynamic applications. The purpose of the proposed track system is to deliver continuous power with a smooth coupling profile which naturally lowers the rating requirements of the secondary electronic components, and to be interoperable with many secondary topologies. The proposed track is compared with a previously published lumped system using double-D primary pads distributed one per meter by a normalized coupling metric. The results show that this meandering track primary has a smaller impact on system electronic components and has better interoperability while it requires lower primary compensation rating compared to the lumped pad primary for the same power level. A prototype of the track was built and the simulation results were verified. A 10 kW power experiment was achieved a dc–dc efficiency of around 83%, and the potential of this multicoil topology for interoperable and low-cost high-power dynamic charging was demonstrated.