Exercise intensity-dependent effects of arm and leg-cycling on cognitive performance

Physiological responses to arm and leg-cycling are different, which may influence psychological and biological mechanisms that influence post-exercise cognitive performance. The aim of this study was to determine the effects of maximal and submaximal (absolute and relative intensity matched) arm and leg-cycling on executive function. Thirteen males (age, 24.7 ± 5.0 years) initially undertook two incremental exercise tests to volitional exhaustion for arm-cycling (82 ± 18 W) and leg-cycling (243 ± 52 W) for the determination of maximal power output. Participants subsequently performed three 20-min constant load exercise trials: (1) arm-cycling at 50% of the ergometer-specific maximal power output (41 ± 9 W), (2) leg-cycling at 50% of the ergometer-specific maximal power output (122 ± 26 W), and (3) leg-cycling at the same absolute power output as the submaximal arm-cycling trial (41 ± 9 W). An executive function task was completed before, immediately after and 15-min after each exercise test. Exhaustive leg-cycling increased reaction time (p 0.05). Improvements in reaction time following arm-cycling were maintained for at least 15-min post exercise (p = 0.008, d = -0.73). Arm and leg-cycling performed at the same relative intensity elicit comparable improvements in cognitive performance. These findings suggest that individuals restricted to arm exercise possess a similar capacity to elicit an exercise-induced cognitive performance benefit

Artificial Intelligence and its future potential in lung cancer screening

Artificial intelligence (AI) simulates intelligent behavior as well as critical thinking comparable to a human being and can be used to analyze and interpret complex medical data. The application of AI in imaging diagnostics reduces the burden of radiologists and increases the sensitivity of lung cancer screening so that the morbidity and mortality associated with lung cancer can be decreased. In this article, we have tried to evaluate the role of artificial intelligence in lung cancer screening, as well as the future potential and efficiency of AI in the classification of nodules. The relevant studies between 2010-2020 were selected from the PubMed database after excluding animal studies and were analyzed for the contribution of AI. Techniques such as deep learning and machine learning allow automatic characterization and classification of nodules with high precision and promise an advanced lung cancer screening method in the future. Even though several combination models with high performance have been proposed, an effectively validated model for routine use still needs to be improvised. Combining the performance of artificial intelligence with a radiologist’s expertise offers a successful outcome with higher accuracy. Thus, we can conclude that higher sensitivity, specificity, and accuracy of lung cancer screening and classification of nodules is possible through the integration of artificial intelligence and radiology. The validation of models and further research is to be carried out to determine the feasibility of this integration

Aligning the Goals of the University with Opportunities in Education Abroad

This quantitative study was conducted at a large four year, high undergraduate, public university (for this article, called Midwest University) to compare and assess the perceived benefit of traditional study abroad and short-term, faculty-led study abroad on participants’ employability skills, cultural competency and global citizenship. Participants reported their education abroad experience enhanced their understanding of course content as well as their views about global citizenship. The survey collected data about participants’ perceptions about social responsibility, global competency, and global civic engagement. In addition, the survey collected data about career competency skills such as teamwork, interpersonal communication, networking ability, leadership, problem solving and foreign language skills. The study defined education abroad at Midwest University and determined how well the program delivered on the Midwest University promise of social and economic mobility. Given that the resources devoted to a short-term, faculty-led experience are significantly lower than in a traditional study abroad program, the authors argue that this type of experience is more accessible to the students and participants at Midwest University.

Six different football shoes, one playing surface and the weather; Assessing variation in shoe-surface traction over one season of elite football

<div><p>Introduction</p><p>An optimal range of shoe-surface traction (grip) exists to improve performance and minimise injury risk. Little information exists regarding the magnitude of traction forces at shoe-surface interface across a full season of elite football (soccer) using common football shoes.</p><p>Objective</p><p>To assess variation in shoe-surface traction of six different football shoe models throughout a full playing season in Qatar encompassing climatic and grass species variations.</p><p>Methods</p><p>Football shoes were loaded onto a portable shoe-surface traction testing machine at five individual testing time points to collect traction data (rotational and translational) on a soccer playing surface across one season. Surface mechanical properties (surface hardness, soil moisture) and climate data (temperature and humidity) were collected at each testing time point.</p><p>Results</p><p>Peak rotational traction was significantly different across shoe models (F = 218, df = 5, p <0.0001), shoe outsole groups (F = 316.2, df = 2, p < .0001), and grass species (F = 202.8, df = 4, p < 0.0001). No main effect for shoe model was found for translational traction (F = 2.392, p = 0.07).</p><p>Conclusions</p><p>The rotational (but not translational) traction varied substantially across different shoe types, outsole groups, and grass species. Highest rotational traction values were seen with soft ground outsole (screw-in metal studs) shoes tested on warm season grass. This objective data allows more informed footwear choices for football played in warm/hot climates on sand-based elite football playing surfaces. Further research is required to confirm if these findings extend across other football shoe brands.</p></div

A blinded determination of H0H_0 from low-redshift Type Ia supernovae, calibrated by Cepheid variables

Presently a ${>}3\sigma$ tension exists between values of the Hubble constant $H_0$ derived from analysis of fluctuations in the Cosmic Microwave Background by Planck, and local measurements of the expansion using calibrators of type Ia supernovae (SNe Ia). We perform a blinded reanalysis of Riess et al. 2011 to measure $H_0$ from low-redshift SNe Ia, calibrated by Cepheid variables and geometric distances including to NGC 4258. This paper is a demonstration of techniques to be applied to the Riess et at. 2016 data. Our end-to-end analysis starts from available CfA3 and LOSS photometry, providing an independent validation of Riess et al. 2011. We obscure the value of $H_0$ throughout our analysis and the first stage of the referee process, because calibration of SNe Ia requires a series of often subtle choices, and the potential for results to be affected by human bias is significant. Our analysis departs from that of Riess et al. 2011 by incorporating the covariance matrix method adopted in SNLS and JLA to quantify SN Ia systematics, and by including a simultaneous fit of all SN Ia and Cepheid data. We find $H_0 = 72.5 \pm 3.1$ (stat) $\pm 0.77$ (sys) km s$^{-1}$ Mpc$^{-1}$ with a three-galaxy (NGC 4258+LMC+MW) anchor. The relative uncertainties are 4.3% statistical, 1.1% systematic, and 4.4% total, larger than in Riess et al. 2011 (3.3% total) and the Efstathiou 2014 reanalysis (3.4% total). Our error budget for $H_0$ is dominated by statistical errors due to the small size of the supernova sample, whilst the systematic contribution is dominated by variation in the Cepheid fits, and for the SNe Ia, uncertainties in the host galaxy mass dependence and Malmquist bias.Comment: 38 pages, 13 figures, 13 tables; accepted for publication in MNRA

CLEANing the Reward: Counterfactual Actions to Remove Exploratory Action Noise in Multiagent Learning

Learning in multiagent systems can be slow because agents must learn both how to behave in a complex environment and how to account for the actions of other agents. The inability of an agent to distinguish between the true environmental dynamics and those caused by the stochastic exploratory actions of other agents creates noise in each agent's reward signal. This learning noise can have unforeseen and often undesirable effects on the resultant system performance. We define such noise as exploratory action noise, demonstrate the critical impact it can have on the learning process in multiagent settings, and introduce a reward structure to effectively remove such noise from each agent's reward signal. In particular, we introduce Coordinated Learning without Exploratory Action Noise (CLEAN) rewards and empirically demonstrate their benefit

Light attenuation characteristics of glacially-fed lakes

Transparency is a fundamental characteristic of aquatic ecosystems and is highly responsive to changes in climate and land use. The transparency of glacially-fed lakes may be a particularly sensitive sentinel characteristic of these changes. However, little is known about the relative contributions of glacial flour versus other factors affecting light attenuation in these lakes. We sampled 18 glacially-fed lakes in Chile, New Zealand, and the U.S. and Canadian Rocky Mountains to characterize how dissolved absorption, algal biomass (approximated by chlorophyll a), water, and glacial flour contributed to attenuation of ultraviolet radiation (UVR) and photosynthetically active radiation (PAR, 400–700 nm). Variation in attenuation across lakes was related to turbidity, which we used as a proxy for the concentration of glacial flour. Turbidity-specific diffuse attenuation coefficients increased with decreasing wavelength and distance from glaciers. Regional differences in turbidity-specific diffuse attenuation coefficients were observed in short UVR wavelengths (305 and 320 nm) but not at longer UVR wavelengths (380 nm) or PAR. Dissolved absorption coefficients, which are closely correlated with diffuse attenuation coefficients in most non-glacially-fed lakes, represented only about one quarter of diffuse attenuation coefficients in study lakes here, whereas glacial flour contributed about two thirds across UVR and PAR. Understanding the optical characteristics of substances that regulate light attenuation in glacially-fed lakes will help elucidate the signals that these systems provide of broader environmental changes and forecast the effects of climate change on these aquatic ecosystems