Kinetic Analysis of Lower Body Resistance Training Exercises

This study evaluated and compared the peak vertical ground reaction force (GRF) and rate of force development (RFD) for the eccentric and concentric phases of 4 lower body resistance training exercises, including the back squat, deadlift, step-up, and forward lunge. Sixteen women performed 2 repetitions of each of the 4 exercises at a 6 repetition maximum load. Kinetic data were acquired using a force platform. A repeated measures ANOVA was used to evaluate the differences in GRF between the exercises. Results revealed significant main effects for GRF both the eccentric (p ≤ 0.001) and concentric (p ≤ 0.001) phases. Significant main effects were also found for RFD for the eccentric (p ≤ 0.001) and concentric phases (p ≤ 0.001). Force and power requirements and osteogenic potential differ between these resistance training exercises

Antagonist conditioning contractions impair agonist functioning

This study assessed the effect of antagonist conditioning contractions (ACC) on the subsequent force and electromyography of an agonist. Twelve subjects performed isokinetic elbow flexion on a dynamometer in 4 test conditions including a baseline condition without, and 1, 3 and 6 seconds after, isometric triceps extension. Average peak torque (T), peak torque/body weight (T:BW), average power (P), and rate of torque development (RTD) were assessed. Electromyographic data were obtained from elbow extensors and flexors. A repeated measures ANOVA with post hoc analysis demonstrated that T, T:BW, P, and RTD were higher in the baseline, compared to the post ACC conditions (P ≤ 0.05), and appears to be due to higher brachioradialis activation in the baseline condition in compared to some post ACC conditions (P ≤ 0.05)

Unexpected High Intragenomic Variation in Two of Three Major Pest Thrips Species Does Not Affect Ribosomal Internal Transcribed Spacer 2 (ITS2) Utility for Thrips Identification

The mitochondrial cytochrome oxidase I gene (mtCO1) and the ribosomal internal transcribed spacer 2 region (ITS2) are among the most widely used molecular markers for insect taxonomic characterization. Three economically important species of thrips, Scirtothrips dorsalis, Thrips palmi, and Frankliniella occidentalis were selected to examine the extent of intragenomic variation within these two marker regions in the family Thripidae, and determine if this variation would affect the utility of markers in thrips molecular diagnostics. For each species, intragenomic (within individual) variation and intergenomic (among individuals) variation was assessed by cloning and sequencing PCR-amplified copies. Intergenomic variation was generally higher than intragenomic variation except in cases where intergenomic variation was very low, as in mtCO1 from S. dorsalis and F. occidentalis. Intragenomic variation was detected in both markers in all three of the thrips species, however, 2–3 times more intragenomic variation was observed for ITS2 than mtCO1 in both S. dorsalis and T. palmi. Furthermore, levels of intragenomic variation were low for both of the genes in F. occidentalis. In all of the three thrips species, no sex-based clustering of haplotypes was observed in either marker. Unexpected high intragenomic variation in ITS2 for two of three thrips species did not interfere with thrips diagnostics. However, caution should be taken in applying ITS2 to certain studies of S. dorsalis and T. palmi when high levels of intragenomic variation could be problematic or confounding. In such studies, mtCO1 may be a preferable marker. Possible reasons for discrepancies in intragenomic variation among genomic regions are discussed

Engagement Assessment Using EEG Signals

In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance

Model Individualization for Real-Time Operator Functional State Assessment

Proper assessment of Operator Functional State (OFS) and appropriate workload modulation offer the potential to improve mission effectiveness and aviation safety in both overload and under-load conditions. Although a wide range of research has been devoted to building OFS assessment models, most of the models are based on group statistics and little or no research has been directed towards model individualization, i.e., tuning the group statistics based model for individual pilots. Moreover, little emphasis has been placed on monitoring whether the pilot is disengaged during low workload conditions. The primary focus of this research is to provide a real-time engagement assessment technique considering individual variations in an aviation environment. This technique is based on an advanced machine learning technique, called enhanced committee machine. We have investigated two different model individualization approaches: similarity-based and dynamic ensemble selection-based. The basic idea of the similarity-based technique is to find similar subjects from the training data pool and use their data together with the limited training data from the test subject to build an individualized OFS assessment model. The dynamic ensemble selection dynamically select data points in a validation dataset (with labels) that are adjacent to each test sample, and evaluate all the trained models using the identified data points. The best performing models will be selected and maximum voting can be applied to perform individualized assessment for the test sample. To evaluate the developed approaches, we have collected data from a high fidelity Boeing 737 simulator. The results show that the performance of the dynamic ensemble selection approach is comparable to that achieved from an individual model (assuming sufficient data is available from each individual)

Estimating Bacterial diversity in scirtothrips dorsalis (thysanoptera: thripidae) Via Next generation sequencing

The last 2 decades have produced a better understanding of insect-microbial associations and yielded some important opportunities for insect control. However, most of our knowledge comes from model systems. Thrips (Thysanoptera: Thripidae) have been understudied despite their global importance as invasive species, plant pests and disease vectors. Using a culture and primer independent next-generation sequencing and metagenomics pipeline, we surveyed the bacteria of the globally important pest, Scirtothrips dorsalis Hood. The most abundant bacterial phyla identified were Actinobacteria and Proteobacteria and the most abundant genera were Propionibacterium, Stenotrophomonas, and Pseudomonas. A total of 189 genera of bacteria were identified. The absence of any vertically transferred symbiont taxa commonly found in insects is consistent with other studies suggesting that thrips primarilly acquire resident microbes from their environment. This does not preclude a possible beneficial/intimate association between S. dorsalis and the dominant taxa identified and future work should determine the nature of these associations

Drivers of advanced stage at breast cancer diagnosis in the multicountry African breast cancer - disparities in outcomes (ABC-DO) study.

Breast cancer (BC) survival rates in sub-Saharan Africa (SSA) are low in part due to advanced stage at diagnosis. As one component of a study of the entire journey of SSA women with BC, we aimed to identify shared and setting-specific drivers of advanced stage BC. Women newly diagnosed in the multicountry African Breast Cancer-Disparities in Outcomes (ABC-DO) study completed a baseline interview and their stage information was extracted from medical records. Ordinal logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for advanced stage (I, II, III, IV) in relation to individual woman-level, referral and biological factors. A total of 1795 women were included from Nigeria, Uganda, Zambia, and the multiracial populations of Namibia and South Africa, 1091 of whom (61%) were stage III/IV. Stage was lower in women with greater BC knowledge (OR 0.77 (95% CI: 0.70, 0.85) per point on a 6 point scale). More advanced stage was associated with being black (4.00 (2.79, 5.74)), having attended <secondary education (1.75 (1.42, 2.16)), having never heard of BC (1.64 (1.31, 2.06)), an unskilled job (1.77 (1.43, 2.20)) and pregnancy in the past 3 years (30% of ≤45 year olds) (1.63 (1.15, 2.31)), and were mediated through delays to diagnosis: symptom duration of ≥ 1 year (OR 2.47 (1.93, 3.15)). These findings provide further evidence that late-stage BC in SSA is largely attributed to modifiable factors and strategies to improve BC education and awareness in women and the health system should be intensified

A Systematic Approach for Real-Time Operator Functional State Assessment

A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement

Heart Rate and Energy Expenditure Concurrent Validity of Identical Garmin Wrist Watches During Moderately Heavy Resistance Training

Consistent with previous years, ACSM has found that wearable technology and resistance training (RT) are two of the top 5 fitness trends in 2023. Our lab recently found that wrist-worn devices, such as Garmin Instinct, are neither valid nor reliable at measuring average or maximal heart rate (HR) or estimating energy expenditure (EE) following light intensity circuit RT. We postulated that the errors may have been due to the device’s algorithms assuming higher intensity during RT. PURPOSE: The purpose of this study was to determine the concurrent validity of identical Garmin Instinct wrist-watches to record valid measures of average and maximal HR as well as estimated EE following moderately heavy RT. METHODS: Twenty-one adult participants completed this study (n=10 female, n=11 male). Two Garmin Instinct wrist-watches were evaluated, along with the Polar H10 chest strap and Cosmed K5 portable metabolic unit as the criterion devices for average/maximal HR and EE, respectively. Participants completed 8 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (4 sets) and moderately heavy (4 sets) intensity with 1 superset of 6 repetitions per exercise (12 repetitions per superset) and 1 min rest between supersets. Data were analyzed for validity (Mean Absolute Percent Error [MAPE] and Lin’s Concordance Coefficient [CCC]), with predetermined thresholds of MAPE\u3c10% and CCC\u3e0.70. A one-way repeated measures ANOVA with Sidak post-hoc test was used to determine differences (p\u3c0.05). RESULTS: The identical Garmin Instinct devices were not considered valid for average HR (MAPE range: 36.5-81.6%; CCC range: 0.07-0.18), maximal HR (MAPE range: 18.6-18.8%; CCC range: 0.15-0.31), or estimated EE (MAPE range: 14.0-16.4%; CCC range: 0.08-0.32) compared to the criterion references. The devices were significantly different than each other for average HR (p=0.005), maximal HR (p\u3c0.001), and estimated EE (p\u3c0.0001). CONCLUSION: The wearable wrist-worn devices tested herein should not be utilized for accurate measurements of HR or EE during RT, and there are even differences between identical devices. People who RT while using these devices should do so with caution if wishing to utilize them for physiological measures

Rating of Perceived Exertion, Average Heart Rate, and Energy Expenditure Following Indoor and Outdoor Moderately Heavy Superset Resistance Training

Our lab recently found that light intensity circuit resistance training outdoors had a significantly lower perception of effort (RPE) compared to indoor resistance training, despite no physiological differences in heart rate and energy expenditure. However, no study has examined other intensities or set schemes in differing environmental settings. PURPOSE: To determine how indoor or outdoor environments effect rating of perceived exertion (RPE) following light and moderately heavy intensity superset resistance training in recreationally resistance trained adults. METHODS: Twenty-three adult participants completed this study (n=10 female, n=13 male; age: 26.1±8.8 yrs; height: 172.2±9.5 cm; mass: 73.4±18.7 kg; RT experience: 5.3±4.8 yrs). Participants wore devices to measure heart rate (Polar H10 chest strap) and energy expenditure (Cosmed K5 Portable Metabolic Cart). Randomly in indoor and outdoor settings, participants completed 4 supersets of the reverse lunge and shoulder press exercises using dumbbells at a light (2 sets) and moderately heavy (2 sets) intensity with 1 superset of 6 repetitions per exercise (12 repetitions per superset) and 1 min rest between supersets. The OMNI Rating of Perceived Exertion Scale for Resistance Exercise 0-10 RPE scale was used following each superset. A paired T-test was used to determine differences between environmental setting (pRESULTS: No significant differences were observed between indoor and outdoor environments for average heart rate (129.4±17.2 and 127.8±23.3 bpm, p=0.67), energy expenditure (30.6±11.5 and 28.3±9.9 kcals; p=0.06), as well as RPE during light intensity (2.9±0.9 and 2.9±0.8 arbitrary units/AU’s, p=0.70) and moderately heavy intensity (6.5±1.7 and 6.3±1.5 AU’s, p=0.27) supersets. CONCLUSION: In recreationally resistance trained adults, light intensity and moderately heavy intensity superset resistance training in indoor or outdoor settings does not alter heart rate, energy expenditure, or perceived effort