Local Regression Research Articles

Systematic Upstream Large-Scale Control of Subtropical Low-Cloud Properties

Abstract It has recently been shown that the slow adjustment of the atmospheric boundary layer (ABL) to perturbations of the large-scale atmospheric conditions translate into an upstream control of the low-cloud cover (LCC) variability at climatological timescales in the subtropics. In this study we expand upon this recent study to investigate upstream control of the climatology of low-cloud radiative effect (CRE), as well as cloud properties relevant to their radiative effect: cloud liquid water path (LWP), and cloud optical depth (COD).We use machine-learning statistical models with feature selection capabilities (random-forests) to determine the influence of the local and upstream large-scale conditions in monthly data. These conditions are determined using back-trajectories in monthly-mean wind fields. Total CRE, dominated by the shortwave contribution, exhibits a dependence on upstream Estimated Inversion Strength (EIS), but not on upstream Sea-Surface Temperature (SST) as LCC does. Upstream control of COD was present but was not as consistent as LCC or CRE across different regions and cloud regimes, while LWP does not exhibit strong upstream control at all. This implies that the control of other boundary layer properties could explain the differences in response between LCC and CRE to SST and EIS. Looking at five subtropical eastern basins, it appears that key lead times are region-specific. The inclusion of upstream control provides significant improvements to the predictive skill of statistical models over local linear regression, with improvements in variance explained well over 20% in many cases.

Predicting corrosion current density in magnesium alloy battery anodes: machine learning approach using rapid miner

ABSTRACT Magnesium (Mg) alloys are increasingly recognised for their potential as anode materials in batteries due to their high specific capacity and cost-effectiveness. However, their susceptibility to corrosion poses a significant challenge to practical applications. This study explores the effectiveness of various machine learning models – local polynomial regression, Decision Trees, Random Forest, Gradient Boost, and Extreme Gradient Boost – in predicting the corrosion behaviour of Mg alloy battery anodes in a 3.5 wt.% NaCl electrolyte. Experimental data on the corrosion current density of Mg alloys are collected and analysed using the RapidMiner tool for model training and evaluation. The findings highlight that the Extreme Gradient Boost (XGBoost) model excels among other machine learning techniques in accurately forecasting the corrosion rates of Mg alloys. XGBoost achieves an exceptional R2 value of 0.9931 in Tafel plots, indicating a robust fit to the data as evidenced by scatter plots. Furthermore, the XGBoost model demonstrates strong positive monotonic and ordinal relationships between actual and predicted corrosion current densities, as indicated by a Spearman correlation coefficient of 1 and a Kendall tau coefficient of 0.99. These outcomes underscore XGBoost's potential as a powerful tool for enhancing the understanding and management of corrosion in Mg alloy battery applications.

Development and validation of a novel comorbidity score specific for prostate cancer patients treated with robotic platform and its implication on DaVinci single-port system.

To develop and validate a novel Comorbidity score for Robotic Surgery (CRS) in predicting severe complications after robot-assisted radical prostatectomy (RARP). Furthermore, we investigated the impact of the surgical platform (Multi-Port - MP vs Single-Port - SP) according to this score. We included 2085 ("development cohort") and 595 ("validation cohort") patients undergoing RARP at two tertiary referral centers between 2014 and March 2024 in a retrospective study. Statistical analyses included validation of the Charlson Comorbidity Index (CCI) to predict 30-day severe complications (Clavien-Dindo ≥ 3a), development and external validation of CRS using calibration plots and decision curve analysis. Lastly, locally weighted scatterplot smoothing (LOWESS) analysis was used to graphically explore the impact of the robotic platform according to novel CRS. CCI exhibited limited predictive ability for severe complications (60% in the validation cohort). In multivariable logistic regression analyses testing the correlation between each condition included in CCI and severe complications, diabetes and myocardial infarction resulted as independent predictors (OR 1.75 [95%CI 1.05-2.82]; OR 1.92 [95%CI 1.26-2.88]) and were subsequently fitted into a multivariable logistic model including age, previous abdominal surgery and obesity (BMI > 30). The resulting predictive model demonstrated superior discrimination and clinical net benefit in predicting severe complications compared to CCI (AUC 64 vs 60%). At LOWESS analysis, SP platform was associated with lower risk of severe complications as CRS increased compared to MP system. The validated CRS showed better accuracy compared to CCI in predicting severe complications after RARP. Additionally, the use of SP robotic platform may reduce the risk of severe complications in highly comorbid patients according to CRS.

Improving Real-Time Trend Estimates Using Local Parametrization of Polynomial Regression Filters

This paper examines and compares real-time estimates of the trend-cycle component using moving averages constructed with local polynomial regression. It enables the reproduction of Henderson’s symmetric and Musgrave’s asymmetric filters used in the X-13ARIMA-SEATS seasonal adjustment algorithm. This paper proposes two extensions of local polynomial filters for real-time trend-cycle estimates: first including a timeliness criterion to minimize the phase shift; second with procedure for parametrizing asymmetric filters locally while they are generally parametrized globally, which can be suboptimal around turning points. An empirical comparison, based on simulated and real data, shows that modeling polynomial trends that are too complex introduces more revisions without reducing the phase shift, and that local parametrization reduces the delay in detecting turning points and reduces revisions. The results are reproducible and all the methods can be easily applied using the R package rjd3filters.

Spatial and Temporal Variation of GPP and Its Response to Urban Environmental Changes in Beijing

The carbon sequestration capacity of vegetation is the key to the carbon cycle in terrestrial ecosystems. It is significant to analyze the spatiotemporal variation and influencing factors of vegetation carbon sequestration ability to improve territorial carbon sink and optimize its spatial pattern. However, there is a lack of understanding of the impact of environmental conditions and human activity on the vegetation’s carbon sequestration ability, especially in highly urbanized areas. For example, effective vegetation management methods can enhance vegetation Gross Primary Productivity, while emissions of air pollutants like O3, CO, NO2, and PM2.5 can suppress it. This paper mainly explores the factors influencing vegetation carbon sequestration capacity across different regions of Beijing. Based on remote sensing data and site observation data, this paper analyzed the spatiotemporal variation trend of Annual Gross Primary Production (AGPP) and the influence of environmental factors and human activity factors on GPP in Beijing from 2000 to 2020 by using the Theil−Sen’s slope estimator, Mann−Kendall trend test, and comparing Geographically Weighted Regression method (GWR) and Geographically and Temporally Weighted Regression method (GTWR). GWR is a localized multiple regression technique used to estimate variable relationships that vary spatially. GTWR extends GWR by adding temporal analysis, enabling a comprehensive examination of spatiotemporal data variations. Besides, we used land use cover data to discuss the influence of land use cover change on AGPP. The results showed that the spatial distribution pattern of GPP in Beijing was higher in the northwest and lower in the southeast, and it showed an overall upward trend from 2000 to 2020, with an average annual growth rate of 14.39 g C·m−2·a−1. From 2000 to 2020, excluding the core urban areas, the GPP of 95.8% of Beijing increased, and 10.6% of Beijing showed a trend of significant increase, concentrated in Mentougou, Changping, and Miyun. GPP decreased in 4.1% of the regions in Beijing and decreased significantly in 1.4% of the areas within the sixth ring. The areas where AGPP significantly decreased were concentrated in those where land use types were converted to Residential land (impervious land), while AGPP showed an upward trend in other areas. CO and NO2 are the main driving forces of GPP change in Beijing. O3 and land surface temperature (LST) also exert certain influences, while the impact of precipitation (PRE) is relatively minor. O3 and CO have a positive impact on AGPP as a whole, while LST and NO2 generally exhibit negative impacts. PRE has a positive impact in the central area of Beijing, while it has a negative impact in the peripheral areas. This study further discusses opinions on future urbanization and environmental management policies in Beijing, which will promote the carbon peak and carbon neutrality process of ecological space management in Beijing. Besides, this study was conducted at the urban scale rather than at ecological sites, encompassing a variety of factors that influence vegetation AGPP. Consequently, the results also offer fresh insights into the intricate nexus between human activities, pollutants, and the GPP of vegetation.

Modelling of the trade-off between the deep soil moisture and vegetation restoration in the hilly area of the Loess Plateau, China

Excessive depletion of soil moisture by artificial forests in the vegetation restoration areas of the Loess Plateau has attracted widespread attention. To assess potential risks of soil moisture deficit, we needed on-site vegetation and soil sampling data, as well as UAV images from the Chaigou Watershed for three-dimensional analysis, combining both sampling and raster data. Three-dimensional surfaces for assessment of trade-off were established innovatively by the local regression and interpolation methods. The results indicated that soil moisture benefits at 20–40 cm depth are lower than at 0–20 cm due to infiltration and surface disturbance. In some areas of the Chaigou Watershed, grass and shrub-grass vegetation are facing risks of soil moisture deficit based on trade-off values (RSMD) and multiparameter evaluations. Analysis of deep soil water content variability revealed the moisture decreases significantly with the deepening of the soil layer in some plots. R (Richness), H (Shannon’s Diversity), Margalef, COHESION, and CONTAG were applicable in interpolation and fitted with the local regression model (R2 > 0.6) corresponding to the trade-off, but SPLIT was proven to be inapplicable in this study area. The zero trade-off inflection points were 6 %–8 %, while the trend inflection points were 7.5 %–9 % for soil moisture and vegetation indices of vegetation and landscape in typical sampling sites of the Chaigou Watershed. Three-dimensional fitting model is more comprehensive and effective in assessing deep soil moisture conditions and grass plots on shady slopes generally had the best trade-off status in this region.

Local polynomial trend regression for spatial data on Rd

Local polynomial trend regression for spatial data on Rd

Total burden of hepatitis B and C attributed to injecting drug use in 204 countries and territories from 1990 to 2021: Analyses based on the Global Burden of Disease Study 2021

This study assesses the global, regional, and national burden of hepatitis B (HBV) and hepatitis C (HCV) related to injecting drug use (IDU) from 1990 to 2021. Data from the global burden of disease study 2021 were analyzed to quantify deaths, age-standardized mortality rates (ASMR), disability-adjusted life years (DALYs), and age-standardized DALYs rates (ASDR) due to HBV and HCV from IDU across 204 countries. Trends was evaluated using estimated annual percentage change. Analyzing the association between ASDR and SDI using a loess regression model. From 1990 to 2021, the global burden of deaths and DALYs due to HBV and HCV attributed to IDU showed an increasing trend, especially among males, whose mortality rates were significantly higher than females. In 2021, global deaths due to HBV from IDU were 13,050.8, with an ASMR of 0.15 per 100,000 and an ASDR of 5.3, both showing an increasing trend with estimated annual percentage changes (EAPCs) of 1.09 and 0.96, respectively. HCV deaths reached 231,764.4, with an ASMR of 2.68 (EAPC: 0.38) and a relatively stable ASDR trend (EAPC: 0.01). Although raw death rates for HCV have increased, the ASMR and ASDR have remained stable or slightly declined, highlighting different trends across sexes and regions. India had the highest national deaths, while the highest ASDRs were in the Republic of Moldova (HBV) and Mongolia (HCV). South Asia recorded the highest regional deaths for both HBV and HCV. Positive correlations between ASDRs for HBV and HCV with SDI were observed. The burden of HBV and HCV due to IDU has increased from 1990 to 2021, especially among males, with significant regional and national disparities. Targeted drug prohibition interventions and policies are needed.

Global variations in coronary revascularisation and acute myocardial infarction mortality between 2006-2020: a longitudinal, population-level analysis of 16 high-income nations from the OECD database

Abstract Background Revascularisation options for ischaemic heart disease (IHD) includes either, percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). Whilst PCI remains the preferred choice in ST-elevation myocardial infarction (STEMI)(1), several landmark trials have questioned its universal superiority (2,3), thus prompting re-evaluation of guidelines. A wide-scale contemporary overview of revascularisation trends is lacking. Purpose To examine the evolving pattern in PCI and CABG rates, alongside mortality from acute myocardial infarction (AMI) across a group of 16 high-income countries between 2006 and 2020. Methods Standardized PCI and CABG procedure rates alongside AMI age-standardised mortality rate (ASMR) were obtained from the Organisation for Economic Co-operation and Development (OECD) database. Data from 2006-2020 was extracted for; Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom (UK). Together, these countries are commonly known as the European Union (EU) 15+ and represent a cluster of high-income nations with comparable levels of health expenditure. Procedural trends including the estimated annual percentage change (EAPC) were evaluated using Joinpoint analysis whilst Locally Weighted Scatterplot Smoothing (LOESS) models was used to analysis trends in AMI mortality. Results Over 15 years, 14.0 million PCI and 2.8 million CABG procedures were recorded in total. PCI rates varied amongst nations (Figure 1), however showed an overall increase in 11 countries, led by Finland (+36.0%). The steepest increase was observed in France between 2012-2018 (EAPC 5.4, 95% CI: 4.8 – 6.1). The greatest overall decrease in PCI was observed in Luxemburg (-33.5%). The fastest decrease was seen during 2018-2020 in the UK (EAPC -7.2, 95% CI: -9.7 – -4.6). CABG rates declined overall in 15 countries (Figure 1), with Luxembourg (-71.3%), experiencing the largest fall and showing the steepest decline between 2014-2018 (EAPC -20.7, 95% CI: -28.3 – -12.3). Ireland was the only country to show an increase in CABG rate (+16.3%). Throughout the study period, the PCI-to-CABG ratio increased (Figure 2A), whilst AMI mortality decreased consistently across all countries (Figure 2B). Conclusion Despite evidence supporting CABG over PCI in specific scenarios, CABG rates have declined, and PCI rates have increased. This trend may be influenced by several factors including patient preference for less invasive procedures and advancements in interventional techniques. The varied use of PCI among these nations, alongside a sustained decline in AMI mortality rates, may be expected given the importance of optimal medical therapy in the management of IHD. The results further highlight the significance of factors beyond revascularisation in driving improved outcomes.PCI and CABG rates between 2006 and 2020PCI to CABG ratio and AMI mortality rate

LVEF trajectory in HFimpEF and its association with prognosis

Abstract Background The 2021 revised Universal Definition of Heart Failure (HF) introduced the subgroup known as HF with improved ejection fraction (HFimpEF), aiming to establish a standardized definition for left ventricular ejection fraction (LVEF) improvement and emphasize the importance of longitudinally assessment of LVEF. However, there remains an insufficient characterization of the association between serial LVEF trajectory before and after impEF, and outcomes in HFimpEF. Purpose We aim to delineate the LVEF trajectory in patients with impEF and to discern specific LVEF trajectory pattern that portends an unfavorable prognosis. Methods We conducted a retrospective analysis by including hospitalized HF patients with baseline LVEF ≤ 40% and satisfactory serial echocardiographic follow-ups. ImpEF was defined as a follow-up LVEF measurement of > 40% with a ≥10-point increase from baseline. Longitudinal LVEF trajectories for patients with impEF (before and after LVEF improvement) were plotted according to the clinical outcome of all-cause death using Loess curves. LVEF changes over time were analyzed by unconditional non-linear mixed-effects modeling, and compared between the groups of patients who died and those who survived using conditional non-linear mixed-effects modeling. Results Among the initial 923 patients with reduced LVEF, 517 had impEF. According to Loess curves and non-linear mixed-effects analysis, LVEF trajectory of impEF differed according to the clinical outcome of death. For patients who suffered all-cause death, there was a comparatively limited improvement in LVEF followed by a more rapid plateauing and decline, exhibiting an inverted U-shaped pattern with lower LVEF values towards both ends of the distribution. Conclusions In HFimpEF, an inverted U-shaped trajectory of LVEF, characterized by limited initial improvement followed by subsequent decline, is associated with poorer prognosis. Serial LVEF monitoring in patients with HFimpEF could help with early identification of at-risk patients.Graphical Abstract

Leveraging Machine Learning for Photometric Redshift Estimation of JWST Galaxies

With the launch of JWST, the volume and complexity of astronomical data are increasing, a trend that will continue with future instruments such as SKA and Euclid. It is inevitable that data-driven methods will become more prominent alongside model-driven analysis. This research utilises machine learning, specifically a kernelised local linear regression model, in photometric redshift predictions of galaxies observed with JWST. With a spectroscopic dataset of 4605 galaxies, we trained the model and achieved a deviation of σdz = 0.018 and a catastrophic outlier rate of foutlier = 3.5%. These results demonstrate high accuracy and computational efficiency, highlighting the potential of machine learning for astronomical data analysis, in particular for large-scale surveys.

Biparietal diameter vs crown-rump length as standard parameter for late first-trimester pregnancy dating.

To compare the precision of biparietal diameter (BPD) and crown-rump length (CRL) as predictors of gestational age in the human fetus in the late first and early second trimesters, using a population-based approach. We constructed term and gestational-age prediction curves for first-trimester dating, based on 11 041 pregnancies with 12 260 measurements of CRL and/or BPD from a population-based Norwegian clinical database. We used a population-based approach with local linear quantile regression, combined with a time-to-event strategy that compensates for induced births. Term prediction precision was assessed by estimating and comparing the prediction residual curves using a time-to-event analysis. Individual differences in gestational-age predictions from CRL and BPD were assessed using measurements performed on the same fetus on the same day. A sensitivity analysis was performed to evaluate the effect of not distinguishing between non-spontaneous and spontaneous births. CRL and BPD provided almost identical term prediction precision judged from the residual distribution. In about 51% of examinations, the difference in predicted gestational age was 1 day or less; 24% of examinations had a difference of 2 days, 14% had a difference of 3 days, 7% had a difference of 4 days and only 5% of all examinations had a difference of 5 days or more. Incorrectly removing induced births from the analysis, or treating them as spontaneous, would cause a substantial systematic prediction bias of about 2 days. Based on population data, using comparisons at an individual level, our study found that BPD is as precise as CRL when used for first-trimester dating. BPD has advantages from a clinical point of view, since it is technically less challenging and less time-consuming to measure compared with CRL, and can be measured and assessed throughout the entire pregnancy. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

On Asymptotic Properties of Local Linear Regression Predictor

On Asymptotic Properties of Local Linear Regression Predictor

Table tennis ball landing control in a robotic system by cameras

Abstract Controlling the landing position of a spinning ball is difficult when using a table tennis robot. A complete physical model requires the factoring in of aerodynamic elements and object collisions, and inaccurate environmental coefficients would increase the landing position error. This study proposed a landing position control method based on a cascade neural network (CNN) that consists of forward and recurrent neural networks (RNNs). The forward NNs are used to estimate the velocity of the outgoing ball according to the velocity and acceleration of the incoming ball captured by cameras and the desired velocity of the outgoing ball. The RNN is employed to reverse-predict ball displacement based on the state of the incoming ball, desired landing point, and ball flight duration. The experiments verified that the method proposed in this study achieved control of differently spinning balls more effectively than the locally weighted regression (LWR)-based model did. The success rate of the CNN at two of six desired landing points was 25.9% and 32.9% higher, respectively, compared with use of the LWR-based model.

Cleaning method for abnormal energy big data based on sparse self-coding

In order to reduce the interference of abnormal energy big data and improve the accuracy of anomaly cleaning and detection, this paper proposes a method for cleaning abnormal energy big database based on sparse self-coding. Firstly, the abnormal data detection method based on multi-criteria evaluation is used to analyze the spectral feature distribution of abnormal energy big data. By using chaotic time series reconstruction model, robust local weighted regression analysis and sparse self-coding method, the feature decomposition of time series of energy data is realized. Then, according to the periodicity of the original sequence, the original sequence is segmitated adaptively to represent the morphological characteristics of the abnormal energy data sub-sequences driven by dynamic carbon emissions, and the anomaly index of each sub-sequence is obtained by AFCM algorithm. Secondly, an energy anomaly evaluation model based on LOF value is established. Finally, the output decision function of data cleaning is constructed to realize the abnormal energy big data cleaning. The test results show that the error detection rate of this method is 0.24%, the missing detection rate is 0.27%, the cleaning rate can reach 99.49%, and the cleaning time is less than 2s.

Reduced Effectiveness of Anti-IgE Treatment Among Adults with Severe Asthma with Older Age of Asthma Onset: Results from the CHRONICLE Study.

Younger age of asthma onset (AAO) has been associated with an allergic phenotype, whereas eosinophilic phenotypes have been associated with older AAO. In randomized trials, biologic efficacy among adults with severe asthma (SA) has varied by age at asthma onset. To determine whether these associations observed in trials apply to real-world outcomes, this study examined biologic effectiveness by AAO and biologic class in a large, real-world cohort. CHRONICLE is an ongoing, real-world study of US adults with subspecialist-treated SA receiving biologics, maintenance corticosteroids, or who are uncontrolled on high-dosage inhaled corticosteroids with additional controllers. Patients enrolled between February 2018 and February 2022 who initiated a biologic for SA and had complete data for analysis were included. A locally estimated scatterplot smoothing (LOESS) analysis was used to plot the relationship between percentage exacerbation rate reduction and AAO by biologic class. Of 578 patients with complete data, 198, 149, and 231 were diagnosed with asthma at age <18, 18-39, and ≥40 years, respectively. Across subgroups, patients were predominantly White (72-78%), female (67-73%), and commercially insured (54-71%). In the LOESS analysis, exacerbation rate reductions were similar for anti-IgE and anti-IL-5/5R and anti-IL-4R subgroups with younger AAO, but the exacerbation rate reduction diminished for patients with older AAO receiving anti-IgE therapy, particularly with asthma onset age ≥40 years. Clinicians should consider age of onset in biologic treatment decisions, given reduced effectiveness of omalizumab in patients with asthma onset at age ≥40 years. NCT03373045.

Prognostic value of a modified pathological staging system for gastric cancer based on the number of retrieved lymph nodes and metastatic lymph node ratio.

The prognosis for gastric cancer (GC) remains grim, underscoring the importance of accurate staging and treatment. Given the potential benefits of using lymph node ratio (LNR) for improved prognostication and treatment planning, it is critical to incorporate examined lymph nodes (ELN) count in an integrated GC staging system. Patients data from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 was utilized as training set. The Mantel-Cox survival test was used to calculate chi-square values for 40 LNR segments with a 0.025 interval, defining a novel LNR-based N (rN) classification based on the cutoff points. A revised AJCC (rAJCC) staging system was established by replacing the 8th AJCC N staging with a rN classification. The relationship between the ELN count and prognosis or positive lymph node detection was conducted by using multivariable models. The series of the odds ratios and hazard ratios were fitted with a locally weighted scatterplot smoothing (LOWESS) smoother, and the structural break points were determined by Chow test to clarify an optimal minimum ELN count. The integrated GC staging system incorporated both rAJCC system and the ideal ELN count. Discriminatory ability and prognostic homogeneity of the rAJCC and integrated staging system was compared with AJCC staging system in the SEER validation set (2016-2017), the Cancer Genome Atlas Program (TCGA) database, and the Third Affiliated Hospital of Sun Yat-sen University database. The current study found that LNR and ELN count are both significantly associated with the prognosis of GC patients (HR = 0.98, p < 0.001 and HR = 2.51, p < 0.001). Four peaks of the chi-square value were identified as LNR cut-off points at 0.025, 0.175, 0.45 and 0.6 to define a novel rN stage. In comparison to the 8th AJCC staging system, the rAJCC staging system demonstrated significant prognostic advantages and discriminatory ability in the training set (5-Y OS AUC: 71.7 vs. 73.0; AIC: 57,290.7 vs. 57,054.9). The superiority of the rAJCC staging system was confirmed in all validation sets. Using a LOWESS smoother and Chow test, a threshold ELN count of 30 was determined to maximum improvement in the prognosis of node-negative patients without downgrading due to potential metastasis, while also maximizing the detection efficiency of at least one involved lymph node. The integrated staging system, combining the refined rAJCC classification with an optimized ELN count threshold, has demonstrated superior discriminatory performance compared to the standalone rAJCC or the traditional AJCC system. The development of a novel GC staging system, which integrated the LNR-based N classification and the minimum ELN count, has exhibited superior prognostic accuracy, holding promise as a valuable asset in the clinical management of GC. However, it is crucial to recognize the limitations from the retrospective database, which should be addressed in subsequent analyses.

Associations Between Pelvis, Trunk, and Shoulder Girdle Muscle Activity; Age; and Scores During the Closed Kinetic Chain Upper Extremity Stability Test in Baseball Pitchers

OBJECTIVE: To evaluate associations between muscle activity, age, and scores on the Closed Kinetic Chain Upper Extremity Stability Test (CKCUEST). DESIGN: Quasi-experimental. METHODS: Pelvic, trunk, and shoulder girdle surface electromyography (sEMG) and kinematic data were measured in 21 high school and college male baseball pitchers (17.4 ± 2.0 years, 184.4 ± 5.7 cm, 78.4 ± 14.2 kg) while they performed the CKCUEST. Mean sEMG data were computed while in sole support on the throwing-arm side (TS) as the glove-arm side (GS) was horizontally translating. Correlations and local regressions were used to assess associations and general patterns between mean sEMG data, age, and scores. RESULTS: TS serratus anterior, TS external oblique, GS serratus anterior, and TS gluteus medius had the highest mean sEMG data. Low-to-high significant correlations were found between proximal muscle groups. Correlations with the highest magnitudes in descending order were TS external oblique and TS gluteus maximus, TS external oblique and TS serratus anterior, and GS external oblique and TS gluteus medius. Small significant associations were observed between other muscle groups and age; there were no associations between muscle activity and test performance. CONCLUSION: Associations were observed between mean muscle activity among muscle groups and age but not test outcome. JOSPT Open 2024;2(4):297-305. Epub 7 June 2024. doi:10.2519/josptopen.2024.1023

Value of cardiac enzyme spectrum for the risk assessment of mortality in critically ill children: a single-centre retrospective study

ObjectivesIdentifying high-risk paediatric patients with a poor prognosis and providing timely and adequate treatment are critical. This study aimed to evaluate the effects of different types of cardiac enzyme spectrum...

Local quadratic spectral and covariance matrix estimation

The problem of estimating the spectral density matrix of a multi‐variate time series is revisited with special focus on the frequencies and . Recognizing that the entries of the spectral density matrix at these two boundary points are real‐valued, we propose a new estimator constructed from a local polynomial regression of the real portion of the multi‐variate periodogram. The case is of particular importance, since is associated with the large‐sample covariance matrix of the sample mean; hence, estimating is crucial to conduct any sort of statistical inference on the mean. We explore the properties of the local polynomial estimator through theory and simulations, and discuss an application to inflation and unemployment.