This paper highlights the critical role of pH or proton activity measurements in environmental studies and emphasises the importance of applying proper statistical approaches when handling pH data. This allows for more informed decisions to effectively manage environmental data such as from mining influenced water. Both the pH and {H+} of the same system display different distributions, with pH mostly displaying a normal or bimodal distribution and {H+} showing a lognormal distribution. It is therefore a challenge of whether to use pH or {H+} to compute the mean or measures of central tendency for further environmental statistical analyses. In this study, different statistical techniques were applied to understand the distribution of pH and {H+} from four different mine sites, Metsämonttu in Finland, Felsendome Rabenstein in Germany, Eastrand and Westrand mine water treatment plants in South Africa. Based on the statistical results, the geometric mean can be used to calculate the average of pH if the distribution is unimodal. For a multimodal pH data distribution, peak identifying methods can be applied to extract the mean for each data population and use them for further statistical analyses.

The prevention of musculoskeletal injuries and their related welfare and economic impacts represent an immediate priority for the horse racing industry. This prospective pilot study aimed to evaluate a method to quantitatively analyze scintigraphic features of specific anatomical regions of the horse\'s appendicular skeleton in combination with secondary measures of musculoskeletal metabolism in blood. Twelve horses referred for scintigraphic assessment of lameness were enrolled. Blood samples were collected immediately prior to the administration of radiotracer. Serum concentrations associated with bone turnover were determined for the following biomarkers: C-terminal telopeptides of type I collagen, proteoglycans and sulfated glycosaminoglycans, collagen type II, osteocalcin, and procollagen II C-terminal propeptide. Scintigraphic images underwent radiomic analysis of discrete regions of the distal limbs and these data were correlated to bone turnover markers. Three lame horses demonstrated asymmetrical radiomic abnormalities. The concentration of osteocalcin in the lame horses was significantly higher when compared to the control group, while no significant changes were observed for the other screened serum biomarkers. Findings from the current study provided evidence that radiomic analysis of equine scintigraphy is feasible. This method has the potential to interrogate which serum markers are associated with musculoskeletal injuries.

In order to promote sustainable agriculture and ensure food security, it has become more vital to identify the causes of soil pollution in agricultural areas. This study was carried out in order to determine the danger of heavy metal contamination in hazelnut production areas and to take the appropriate actions in accordance with the study\'s findings. In this context, the main objectives of this study were to (i) determine some physical, chemical, and biological properties and heavy metal concentrations of different soils in intensive hazelnut cultivation areas under humid ecological conditions; (ii) reveal the heavy metal pollution risks of these areas by their enrichment factor, contamination factor, geo-accumulation index, degree of contamination, pollution load index, and potential ecological risk index; (iii) analyze the quality of soils contaminated with heavy metals by their total enzyme activity index and the geometric mean of enzymatic activities; and (iv) explore the correlation between heavy metals and soil enzyme activity indices. According to our results, the average concentrations of heavy metals in the study area ranked as Fe > Mn > Zn > Cr > Ni > Cu > Co > Pb > Cd. Based on EF, the area was evaluated as between deficiency to low enrichment and moderate enrichment for all elements except for Cd. When the parameters used to assess the risk of heavy metal contamination were evaluated, it was determined that the risk of contamination of other elements in the study area, except Cd, was low. Finally, analyzing the heavy metals and soil enzyme activity indices shows that there is a negative correlation between Ni and GMea and TEI.

UNASSIGNED: Emerging evidence suggests that exercise is a simple and effective method for maintaining brain function.
UNASSIGNED: This review evaluates the effects of five physical exercises, including aerobic training (AT), high-intensity interval training (HIIT), combined training (CT), resistance training (RT), and AT+RT, on the serum level of brain-derived neurotrophic factor (BDNF) in healthy and non-healthy populations.
UNASSIGNED: We searched CNKI, PubMed, Embase, Scopus, Medline, Web of Science, and Cochrane Library databases to review randomized controlled studies on exercise interventions for BDNF. Quantitative merging analysis of the resulting data using Bayesian network meta-analysis.
UNASSIGNED: The screening and exclusion of the searched literature resulted in the inclusion of 39 randomized controlled trials containing 5 exercise interventions with a total of 2031 subjects. The AT, RT, AT+RT, HIIT, and CT groups (intervention groups) and the CG group (conventional control group) were assigned to 451, 236, 102, 84, 293, and 865 subjects, respectively. The Bayesian network meta-analysis ranked the effect of exercise on BDNF level improvement in healthy and non-healthy subjects as follows: RT > HIIT > CT > AT+RT > AT > CG. Better outcomes were observed in all five intervention groups than in the CG group, with RT having the most significant effect [MD = 3.11 (0.33, 5.76), p < 0.05].
UNASSIGNED: RT at moderate intensity is recommended for children and older adults in the case of exercise tolerance and is effective in maintaining or modulating BDNF levels for promoting brain health.
UNASSIGNED: https://inplasy.com, INPLASY202250164.

In a recent paper, Takacs and Bourrat (Biol Philos 37:12, 2022) examine the use of geometric mean reproductive output as a measure of biological fitness. We welcome Takacs and Bourrat\'s scrutiny of a fitness definition that some philosophers have adopted uncritically. We also welcome Takacs and Bourrat\'s attempt to marry the philosophical literature on fitness with the biological literature on mathematical measures of fitness. However, some of the main claims made by Takacs and Bourrat are not correct, while others are correct but not for the reasons they give.

Low cognitive scores are risk factors for cardiovascular outcomes. Whether this relationship is stronger using novel cognitive indices is unknown.
Participants in the Researching Cardiovascular Events with a Weekly Incretin in Diabetes (REWIND) trial who completed both the Montreal Cognitive Assessment (MoCA) score and Digit Substitution Test (DSST) at baseline (N = 8772) were included. These scores were used to identify participants with baseline substantive cognitive impairment (SCI), defined as a baseline score on either the MoCA or DSST ≥ 1.5 SD below either score\'s country-specific mean, or SCI-GM, which was based on a composite index of both scores calculated as their geometric mean (GM), and defined as a score that was ≥ 1.5 SD below their country\'s average GM. Relationships between these measures and incident major adverse cardiovascular events (MACE), and either stroke or death were analyzed.
Compared with 7867 (89.7%) unaffected participants, the 905 (10.3%) participants with baseline SCI had a higher incidence of MACE (unadjusted hazard ratio [HR] 1.34; 95% CI 1.11, 1.62; P = 0.003), and stroke or death (unadjusted HR 1.60; 95% CI 1.33, 1.91; P < 0.001). Stronger relationships were noted for SCI-GM and MACE (unadjusted HR 1.61; 95% CI 1.28, 2.01; P < 0.001), and stroke or death (unadjusted HR 1.85; 95% CI 1.50, 2.30; P < 0.001). For SCI-GM but not SCI, all these relationships remained significant in models that adjusted for up to 10 SCI risk factors.
Country-standardized SCI-GM was a strong independent predictor of cardiovascular events in people with type 2 diabetes in the REWIND trial.

The search algorithm based on symbiotic organisms\' interactions is a relatively recent bio-inspired algorithm of the swarm intelligence field for solving numerical optimization problems. It is meant to optimize applications based on the simulation of the symbiotic relationship among the distinct species in the ecosystem. The task scheduling problem is NP complete, which makes it hard to obtain a correct solution, especially for large-scale tasks. This paper proposes a modified symbiotic organisms search-based scheduling algorithm for the efficient mapping of heterogeneous tasks to access cloud resources of different capacities. The significant contribution of this technique is the simplified representation of the algorithm\'s mutualism process, which uses equity as a measure of relationship characteristics or efficiency of species in the current ecosystem to move to the next generation. These relational characteristics are achieved by replacing the original mutual vector, which uses an arithmetic mean to measure the mutual characteristics with a geometric mean that enhances the survival advantage of two distinct species. The modified symbiotic organisms search algorithm (G_SOS) aims to minimize the task execution time (makespan), cost, response time, and degree of imbalance, and improve the convergence speed for an optimal solution in an IaaS cloud. The performance of the proposed technique was evaluated using a CloudSim toolkit simulator, and the percentage of improvement of the proposed G_SOS over classical SOS and PSO-SA in terms of makespan minimization ranges between 0.61-20.08% and 1.92-25.68% over a large-scale task that spans between 100 to 1000 Million Instructions (MI). The solutions are found to be better than the existing standard (SOS) technique and PSO.

The U.S. Food Safety Modernization Act (FSMA) Produce Safety Rule (PSR) requires that farmers generate a Microbial Water Quality Profile (MWQP) from 20 samples per agricultural water source, taken over 2-4 years and five annual samples thereafter. Farmers must use the MWQP to ascertain a geometric mean (GM) of ≤126 CFU/100 mL and statistical threshold value (STV) of ≤410 CFU/100 mL of generic Escherichia coli. Farmers are responsible for collecting samples and paying for testing, incurring a financial and time burden. To determine if testing frequency can be reduced without compromising accuracy, water samples (n = 279) were collected from twelve sites in the U.S. Mid-Atlantic region from 2016 to 2018 comprising tidal brackish river, non-tidal fresh river, pond, vegetable processing, and reclaimed water. The GM and STV were calculated for all sites and water types using all samples, and for multiple sub-samples of <20 from each site and water type. A Monte Carlo simulation was used to determine the proportion of sub-sample sizes that yielded the same determination as the entire sample size of PSR standard compliance. Four sites, two pond and two reclaimed water sites, complied with PSR GM and STV requirements when using the entire sample set. When a water source\'s calculated GM and STV using the entire sample set hovered close to the PSR thresholds, sub-sample sizes approached the recommended 20 samples to reach a congruent compliance determination. However, 99% agreement was obtained with a sub-sample of five when the absolute difference between the GM and STV from total samples and the PSR thresholds was ≥2.6 and 4.5 log CFU/100 mL E. coli, respectively. These findings suggest that under certain conditions the MWQP may be generated with well below 20 samples, reducing the economic burden on farmers while still maintaining a representative MWQP.

The result in this paper explains some of the qualitative nature of Jensen\'s inequality. It is shown that the more disperse the distribution of a random variable is, the smaller is the expectation of any concave function of it. This result can be used to show the inadequacy of some current methods of reporting environmental data by using geometric means, and it extends the result of I. Billick, D. Shier, and C. H. Spiegelman, where symmetry of the error in environmental measurements is assumed.

We give bounds on the difference between the weighted arithmetic mean and the weighted geometric mean. These imply refined Young inequalities and the reverses of the Young inequality. We also studied some properties on the difference between the weighted arithmetic mean and the weighted geometric mean. Applying the newly obtained inequalities, we show some results on the Tsallis divergence, the Rényi divergence, the Jeffreys-Tsallis divergence and the Jensen-Shannon-Tsallis divergence.