Reionization and cosmic dawn astrophysics from the Square Kilometre Array:impact of observing strategies

Interferometry of the cosmic 21-cm signal is set to revolutionize our understanding of the epoch of reionization (EoR) and the cosmic dawn (CD). The culmination of ongoing efforts will be the upcoming Square Kilometre Array (SKA), which will provide tomography of the 21-cm signal from the first billion years of our Universe. Using a galaxy formation model informed by high-z luminosity functions, here we forecast the accuracy with which the first phase of SKA-low (SKA1-low) can constrain the properties of the unseen galaxies driving the astrophysics of the EoR and CD. We consider three observing strategies: (i) deep (1000 h on a single field); (ii) medium-deep (100 h on 10 independent fields); and (iii) shallow (10 h on 100 independent fields). Using the 21-cm power spectrum as a summary statistic, and conservatively only using the 21-cm signal above the foreground wedge, we predict that all three observing strategies should recover astrophysical parameters to a fractional precision of 3c0.1-10 per cent. The reionization history is recovered to an uncertainty of \u394z 7e 0.1 (1\u3c3 ) for the bulk of its duration. The medium-deep strategy, balancing thermal noise against cosmic variance, results in the tightest constraints, slightly outperforming the deep strategy. The shallow observational strategy performs the worst, with up to an 3c10-60 per cent increase in the recovered uncertainty. We note, however, that non-Gaussian summary statistics, tomography, as well as unbiased foreground removal would likely favour the deep strategy

A state of art review on methodologies for heat transfer and energy flow characteristics of the active building envelopes

Significant share of total final energy use is accounted by the building sector in most of the countries around the world. One way to reduce building energy consumption is to adopt energy efficiency technologies and strategies. Due to environmental concerns and high cost of energy in recent years there has been a renewed interest in building energy efficiency and integration of renewable energy technologies. Active building envelope technology, i.e. transpired solar collectors (TSCs), provides a cost-efficient way of minimizing energy demand of buildings in accordance with global principle of sustainability, which has also proven reliable for diverse applications such as preheating fresh air delivery into the buildings and supplying domestic hot water in summer etc. The objective of this paper is to review the heat transfer and energy flow characteristics of the active building envelopes, particularly focusing on various types of TSCs. Present work consists of background and concept of TSCs, research literature for thermal performance, theoretical modelling, experimental study and numerical simulation investigation. Diverse mathematical models, including thermal models, air flow models, porosity models, and turbulence models etc., have also been presented and compared. Following that, more than 20 parameters affecting TSC performance have been analyzed and evaluated. The literature has illustrated that the best overall performance of turbulence model is RNG k-ε; the effects of those parameters on TSC efficiency are completely different, depending on local climatic conditions, time and site constraints, and the interaction between different factors.Publisher Statement: This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/

A Bayesian Approach to Interpret Intervention Effectiveness in Strength and Conditioning Part 2: Effect Size Selection and Application of Bayesian Updating

Background Effect sizes are commonly used to assess the effectiveness of interventions in strength and conditioning (S&C). The purposes of this large meta-analysis were to investigate the properties of two different effect size statistics and synthesize the large amount of data available in the form of informative Bayesian priors to quantify effectiveness of future S&C interventions.    Methods An online database and hand search of published and unpublished S&C intervention studies from the 1950’s onwards was conducted. Pre- and post-intervention data comprising means and standard deviations were extracted from outcomes categorized as: maximum strength, jump performance or sprint performance. Standardised mean difference (SMDpre) and percentage improvement (%Improve) obtained from the response ratio were calculated and modelled with 4-level Bayesian hierarchical meta-analysis models. Results were also used to create normally distributed priors which were incorporated into an accessible tool for assessing the effectiveness of future S&C interventions through the use of Bayesian updating. Results Data from 628 studies comprising 5468 effect sizes were included in the analyses. Large differences were identified in the effect size distributions for maximum strength (pooled means: SMDpre =0.68 [95%CrI: 0.63 to 0.73]; %Improve = 14.3% [95%CrI: 13.3 to 15.4]) and sprint performance (pooled means: SMDpre =0.46 [95%CrI: 0.43 to 0.50]; %Improve = 6.8% [95%CrI: 6.3 to 7.3]). These differences were also reflected in development of Bayesian priors with the lowest means and largest relative variance obtained for sprint performance reflecting lower improvements in general, but also greater relative dispersion of results. Analysis of the tails of the effect size distributions indicated consistent overestimations of SMDpre values, likely caused by underestimated standard deviations.     Conclusions Future evaluations of S&C interventions are likely to be better performed and contextualised using Bayesian approaches featuring the information and informative priors developed in this meta-analysis. To facilitate an uptake of Bayesian methods within S&C, an easily accessible tool employing intuitive Bayesian updating was created. It is recommended that researchers and practitioners use the tool alongside the S&C specific threshold values, instead of continual isolated effect size calculations and Cohen’s generic values when evaluating the effectiveness of future S&C interventions. Researchers may choose to evaluate interventions using both SMDpre and percent improvement statistics given their different strengths and limitations

A Bayesian approach to interpret intervention effectiveness in strength and conditioning Part 1: A meta-analysis to derive context-specific thresholds

Background Strength and conditioning (S&C) interventions comprising methods such as resistance, sprint and plyometrics are used to enhance athleticism and sports performance. The effectiveness of interventions can be evaluated using effect sizes calculated from physical outcomes and then compared to threshold values. The purpose of this large meta-analysis was to identify threshold values specific to S&C and assess factors that influence effect size distributions. Methods An online database and hand search of published and unpublished S&C intervention studies from the 1950’s onwards was conducted. Interventions were categorized as the following: resistance, combined, plyometric, ballistic, sprint, isokinetic, concurrent, or agility. Pre- and post-intervention data comprising means and standard deviations were extracted from outcomes categorized as: maximum strength, power, explosiveness, jump, sprint, or agility. Study and participant data including intervention length, gender and training status (untrained, recreationally trained and highly trained) were also extracted. Standardised mean difference effect sizes (SMDpre) were calculated and modelled with 4-level Bayesian hierarchical meta-analysis models using 0.25-, 0.5-, and 0.75-quantiles to determine small, medium, and large threshold values, respectively. Results Data from 679 studies comprising 8904 effect sizes were included in the analyses. Threshold values obtained across the entire data were: small - 0.12 [95%CrI: 0.11 to 0.14]; medium - 0.43 [95%CrI: 0.42 to 0.45]; and large - 0.78 [95%CrI: 0.77 to 0.80]. Effect size distributions were shown to be shifted to higher values for longer duration interventions comprising maximum strength outcomes, untrained participants, females, and higher specificity coupling between training method and outcomes. Results from analyses were synthesised to provide updated threshold values to interpret effectiveness. Conclusions The effectiveness of S&C interventions are influenced by a range of factors creating systematic shifts in SMDpre values. It is recommended that researchers and practitioners use the S&C specific threshold values presented instead of Cohen’s generic values, with scope provided for adjustment based on relevant factors

Interpreting magnitude of change in strength and conditioning: effect size selection, threshold values and Bayesian updating.

The magnitude of change following strength and conditioning (S&C) training can be evaluated comparing effect sizes to threshold values. This study conducted a series of meta-analyses and compiled results to identify thresholds specific to S&C, and create prior distributions for Bayesian updating. Pre- and post-training data from S&C interventions were translated into standardised mean difference (SMDpre) and percentage improvement (%Improve) effect sizes. Four-level Bayesian hierarchical meta-analysis models were conducted to compare effect sizes, develop prior distributions, and estimate 0.25-, 0.5-, and 0.75-quantiles to determine small, medium, and large thresholds respectively. Data from 643 studies comprising 6574 effect sizes were included in the analyses. Large differences in distributions for both SMDpre and %Improve were identified across outcome domains (strength, power, jump and sprint performance), with analyses of the tails of the distributions indicating potential large overestimations of SMDpre values. Future evaluations of S&C training will be improved using Bayesian approaches featuring the information and priors developed in this study. To facilitate an uptake of Bayesian methods within S&C, an easily accessible tool employing intuitive Bayesian updating was created. It is recommended that the tool and specific thresholds be used instead of isolated effect size calculations and Cohen's generic values when evaluating S&C training

Differential hypoglycaemic, anorectic, autonomic and emetic effects of the glucagon-like peptide receptor agonist, exendin-4, in the conscious telemetered ferret.

Background: Rodents are incapable of emesis and consequently the emetic potential of glucagon-like peptide-1 receptor (GLP-1R) agonists in studies designed to assess a potential blood glucose lowering action of the compound was missed. Therefore, we investigated if the ferret, a carnivore with demonstrated translation capability in emesis research, would identify the emetic potential of the GLP-1R agonist, exendin-4, and any associated effects on gastric motor function, appetite and cardiovascular homeostasis. Methods: The biological activity of the GLP-1R ligands was investigated in vivo using a glucose tolerance test in pentobarbitone-anesthetised ferrets and in vitro using organ bath studies. Radiotelemetry was used to investigate the effect of exendin-4 on gastric myoelectric activity (GMA) and cardiovascular function in conscious ferrets; behaviour was also simultaneously assessed. Western blot was used to characterize GLP-1R distribution in the gastrointestinal and brain tissues. Results: In anesthetised ferrets, exendin-4 (30 nmol/kg, s.c.) reduced experimentally elevated blood glucose levels by 36.3%, whereas the GLP-1R antagonist, exendin (9–39) (300 nmol/kg, s.c.) antagonised the effect and increased AUC0–120 by 31.0% when injected alone (P < 0.05). In animals with radiotelemetry devices, exendin-4 (100 nmol/kg, s.c.) induced emesis in 1/9 ferrets, but inhibited food intake and decreased heart rate variability (HRV) in all animals (P < 0.05). In the animals not exhibiting emesis, there was no effect on GMA, mean arterial blood pressure, heart rate, or core body temperature. In the ferret exhibiting emesis, there was a shift in the GMA towards bradygastria with a decrease in power, and a concomitant decrease in HRV. Western blot revealed GLP-1R throughout the gastrointestinal tract but exendin-4 (up to 300 nM) and exendin (9–39), failed to contract or relax isolated ferret gut tissues. GLP-1R were found in all major brain regions and the levels were comparable those in the vagus nerve. Conclusions: Peripherally administered exendin-4 reduced blood glucose and inhibited feeding with a low emetic potential similar to that in humans (11% vs 12.8%). A disrupted GMA only occurred in the animal exhibiting emesis raising the possibility that disruption of the GMA may influence the probability of emesis occurring in response to treatment with GLP-1R agonists

A Novel Approach to 1RM Prediction Using the Load-Velocity Profile: A Comparison of Models

The study aim was to compare different predictive models in one repetition maximum (1RM) estimation from load-velocity profile (LVP) data. Fourteen strength-trained men underwent initial 1RMs in the free-weight back squat, followed by two LVPs, over three sessions. Profiles were constructed via a combined method (jump squat (0 load, 30–60% 1RM) + back squat (70–100% 1RM)) or back squat only (0 load, 30–100% 1RM) in 10% increments. Quadratic and linear regression modeling was applied to the data to estimate 80% 1RM (kg) using 80% 1RM mean velocity identified in LVP one as the reference point, with load (kg), then extrapolated to predict 1RM. The 1RM prediction was based on LVP two data and analyzed via analysis of variance, effect size (g/), Pearson correlation coefficients (r), paired t-tests, standard error of the estimate (SEE), and limits of agreement (LOA). p &lt; 0.05. All models reported systematic bias &lt; 10 kg, r &gt; 0.97, and SEE &lt; 5 kg, however, all linear models were significantly different from measured 1RM (p = 0.015 &lt;0.001). Significant differences were observed between quadratic and linear models for combined (p &lt; 0.001; = 0.90) and back squat (p = 0.004, = 0.35) methods. Significant differences were observed between exercises when applying linear modeling (p &lt; 0.001, = 0.67–0.80), but not quadratic (p = 0.632–0.929, = 0.001–0.18). Quadratic modeling employing the combined method rendered the greatest predictive validity. Practitioners should therefore utilize this method when looking to predict daily 1RMs as a means of load autoregulation

Empirically derived guidelines for interpreting the effectiveness of exercise therapy for tendinopathies: A meta-analysis

Objective To quantify and describe effect size distributions from exercise therapies across a range of tendinopathies and outcome domains to inform future research and clinical practice. Design An extensive search of the literature with meta-analysis exploring moderating effects and context specific small, medium, and large thresholds. Eligibility criteria Randomised and quasi-randomised controlled trials involving any persons with a diagnosis of&nbsp;rotator cuff,&nbsp;lateral elbow,&nbsp;patellar,&nbsp;Achilles&nbsp;or gluteal&nbsp;tendinopathy of any severity or duration. Methods Standardised mean difference (SMDpre) effect sizes were used with Bayesian hierarchical meta-analysis and meta-regression models to calculate the 0.25- (small), 0.5- (medium), and 0.75-quantiles (large) and compare pooled means across potential moderators. &nbsp; Results Data were analysed from 114 studies (171 treatment arms 4104 participants). SMDpre effect sizes and credible intervals (CrI) across all tendinopathies and outcome domains demonstrated sizeable values for small (0.34 [95%CrI:0.31-0.37]), medium (0.73 [95%CrI:0.70-0.77]), and large (1.21 [95%CrI:1.17-1.27]) thresholds. Values were similar across tendinopathies but varied substantially across outcome domains with greater threshold values obtained for self-reported measures of pain, disability and function (small~0.6, medium~1.0, large~1.6), and the lowest values obtained for quality of life and objective measures of physical function (small~0.15, medium~0.4, large~0.70). Potential moderating effects of assessment duration, exercise supervision and symptom duration were also identified, with greater pooled mean effect sizes estimated for longer assessment durations, supervised therapies, and studies comprising patients with shorter symptom durations. Conclusion Effect sizes vary for different outcomes but are similar across tendinopathies, with research and clinical outcomes needing to be judged accordingly. Mean treatment effects are expected to be influenced by a range of factors with the most consistent evidence obtained for assessment duration and exercise supervision. The outcomes of new interventions should be assessed against domain- and time-specific effect sizes to be correctly interpreted. Threshold values presented here should be used to guide interpretation

The effect of dose components on resistance exercise therapies for tendinopathy management: a systematic review and meta-analysis.

The purpose of this study was to investigate potential moderating effects of resistance exercise dose components including intensity, volume and frequency, for the management of common tendinopathies. The research was undertaken through a systematic review and meta-analysis, comprising an extensive search of databases and trial registries. Eligibility criteria for selecting studies included randomised and non-randomised controlled trials investigating resistance exercise as the dominant treatment class and reporting sufficient information regarding at least two components of exercise dose (intensity, frequency, volume). Non-controlled standardised mean difference effect sizes were calculated across a range out outcome domains and combined with Bayesian hierarchical meta-analysis models for domains generating large (disability; function; pain) and small (range of motion; physical function capacity; and quality of life) effect size values. Meta-regressions were used to estimate differences in pooled mean values across categorical variables quantifying intensity, frequency and volume. Ninety-one studies presented sufficient data to be included in meta-analyses, comprising 126 treatment arms (TAs) and 2965 participants. Studies reported on five tendinopathy locations (Achilles: 39 TAs, 31.0%; rotator cuff: 39 TAs, 31.0%; lateral elbow: 25 TAs, 19.8%; patellar: 19 TAs, 15.1%; and gluteal: 4 TAs, 3.2%). Meta-regressions provided consistent evidence of greater pooled mean effect sizes for higher intensity therapies comprising additional external resistance compared to body mass only (large effect size domains: 0.39 [95% CrI: 0.00 to 0.82; p = 0.976]; small effect size domains (0.09 [95% CrI: -0.20 to 0.37; p = 0.723]) when data were combined across tendinopathy locations or analysed separately. Consistent evidence of greater pooled mean effect sizes was also identified for the lowest frequency (less than daily) compared with mid (daily) and high frequencies (more than daily) for both large effect size domain ( -0.66 [95% CrI: -1.2 to -0.19; p >0.999]; -0.54 [95% CrI:-0.99 to -0.10; p >0.999]) and small effect size domains ( -0.51 [95% CrI: -0.78 to -0.24; p >0.999]; -0.34 [95% CrI: -0.60 to -0.06; p = 0.992]) when data were combined across tendinopathy locations or analysed separately. Minimal and inconsistent evidence was obtained for differences for a moderating effect of training volume. The study concluded that resistance exercise dose is poorly reported within the tendinopathy management literature. However, this large meta-analysis identified some consistent patterns indicating greater efficacy on average with therapies prescribing higher intensities (through the inclusion of additional external loads) and lower frequencies, potentially creating stronger stimuli and facilitating adequate recovery

The effect of dose on resistance exercise therapies for tendinopathy: a systematic review and meta-analysis protocol.

This is a preprint for a protocol. The purpose of the study described by the protocol was to investigate the effect of resistance exercise dose across multiple common tendinopathies (rotator cuff, lateral elbow, patellar or Achilles), where the frequency, volume and intensity can be accurately quantified. By combining a large data set with contemporary meta-analysis and meta-regression approaches (including relevant covariates within models), the systematic review attempted to explore statistical heterogeneity and better assess potential dose-response relationships that may exist. Where placebo and no-treatment arms were included, these studies were used to reduce heterogeneity and provide sensitivity analyses to support or refute analyses with larger, but more complex data