Statistical Interpretation Research Articles

A mathematical framework for the statistical interpretation of biological growth models

Biological entities are inherently dynamic. As such, various ecological disciplines use mathematical models to describe temporal evolution. Typically, growth curves are modelled as sigmoids, with the evolution modelled by ordinary differential equations. Among the various sigmoid models, the logistic, Gompertz and Richards equations are well-established and widely used for the purpose of fitting growth data in the fields of biology and ecology. The present paper puts forth a mathematical framework for the statistical analysis of population growth models. The analysis is based on a mathematical model of the population–environment relationship, the theoretical foundations of which are discussed in detail. By applying this theory, stochastic evolutionary equations are obtained, for which the logistic, Gompertz, Richards and Birch equations represent a limiting case. To substantiate the models of population growth dynamics, the results of numerical simulations are presented. It is demonstrated that a variety of population growth models can be addressed in a comparable manner. It is suggested that the discussed mathematical framework for statistical interpretation of the joint population-environment evolution represents a promising avenue for further research.

Latent class analysis of post-acute sequelae of SARS-CoV-2 infection.

Symptoms post-SARS-CoV-2 infection may persist for months and cause significant impairment and impact to quality of life. Acute symptoms of SARS-CoV-2 infection are well studied, yet data on clusters of symptoms over time, or post-acute sequelae of SARS-CoV-2 infection (PASC), are limited. We aim to characterize PASC phenotypes by identifying symptom clusters over a six-month period following infection in individuals vaccinated (boosted and not) and those unvaccinated. Subjects with ≥1 self-reported symptom and positive RT-PCR for SARS-CoV-2 at CVS Health US test sites were recruited between January and April 2022. Patient-reported outcomes symptoms, health-related quality of life (HRQoL), work productivity and activity impairment (WPAI) were captured at 1 month, 3 months, and 6 months post-acute infection. Phenotypes of PASC were determined based on subject matter knowledge and balanced consideration of statistical criteria (lower AIC, lower BIC, and adequate entropy) and interpretability. Generalized estimation equation approach was used to investigate relationship between QoL, WPAI and number of symptoms and identified phenotypes, and relationship between phenotypes and vaccination status as well. LCA identified three phenotypes that are primarily differentiated by number of symptoms. These three phenotypes remained consistent across time periods. Subjects with more symptoms were associated with lower HRQoL, and worse WPAI scores. Vaccinated individuals were more likely to be in the low symptom burden latent classes at all time points compared to unvaccinated individuals.

Numerical Computation and Statistical Interpretations of Heat Transfer of Tween-20/ethyl Acetate Nanofluid Flow with Melting Rheological Quality and Activation Energy

Tween-20 plays a significant role in the biological, food, and pharmaceutical industries. Additionally, it plays a vital role in improving the quality of reverse mechanisms of multi-drug resistance. This paper uses artificial neural computing to examine Tween-20 nanoparticles’ behaviors in a base fluid called ethyl acetate to enhance the applications in nanomedicine, drug delivery and biotechnology. The study focuses on the nonlinear model of a viscous fluid at the stagnation point, where mixed convection processes and activation energy are present. The study incorporates slip velocity and melting boundary conditions to examine heat and mass transfer, taking into account thermal and solutal stratification. Various fields of research and technology, specially in industrial engineering that include hydrodynamics, panto-graph systems, and biomedical mathematics, extensively utilize artificial computing. The datasets are based on velocity, temperature, and concentration outlines. The fourth-order Runge-Kutta method is used to generate the datasets. To validate the LMM-ABNNs, we have compared them with a numerical solution, showing a high level of agreement. We utilize the error histogram and mean square error results to validate the performance, scrutinize the training and testing methods, and explore the validity of the approximate answer. Furthermore, the quality characteristics such as skin friction, rate of heat, and mass movement (Nusselt and Sherwood numbers) are statistically analyzed to forecast the model’s durability. This article is the best example of investigating different fluid parameters with the latest artificial neural computing.

Evaluation of Lower Extremities Power, Movement, Position and Effectiveness in Volleyball

Background: This paper presents research on the comparison and evaluation of lower limb power, movement, position on the court, and effectiveness in the players of men’s volleyball. The study involved professional players in the first division of a men’s volleyball team. The main aim of this paper was to show the correlation between lower limb power, movement, position on the pitch, and volleyball efficiency. Methods: The authors presented basic somatic characteristics of anthropology metrics, advanced research results obtained with the Optojump measuring system, players’ results statistics obtained with the Data Volley software (v.4.2024.01), and by applying scientific statistical methods and graphics interpretation. Results: The analyses with the Kruskal-Wallis test showed statistically significant differences in all the variables studied. Flight time (TF, H = 122.967; p < 0.001.) was the shortest for the players in the libero position, then the setter, attacker, middle and longest flight time was shown by the receiving players. The height of the jumps (JH, H = 123.018; p < 0.001) was the highest for receiving and mid players, and then attackers and setters, and the lowest jumps were recorded by libero players. The highest power of lower limbs (P, H = 20.392; p < 0.001) was characteristic for receivers, setters, mid-players and, curiously, libero achieved a better result than attackers. Conclusions: The analysis shows that the power of the lower extremities in volleyball players is associated with the function they perform on the court.

A Retrospective Report of Carprofen Administration as Post-Operative Analgesia Reveals Negative Effects of Recommended Doses.

Effective pain management in laboratory animals is crucial for both animal welfare and the reliability of scientific research. We retrospectively examined the effects of carprofen as post-operative analgesia in Sprague Dawley rats following stereotactic surgery. Our data indicate that administering carprofen twice daily (5 mg/kg), as currently recommended by Die Gesellschaft für Versuchstierkunde/Society for Laboratory Animal Science (GV-SOLAS), led to adverse effects such as reduced food and water intake, disrupted fecal excretion, and abdominal bloating consistent with peritonitis. Continued administration exacerbated these symptoms, with post-mortem findings of intestinal obstructions and ulcers. However, when the frequency was reduced to once daily, such adverse symptoms were not observed. These results are based on incidental data collected from various neuroscientific experiments, resulting in small and uneven sample groups across various experimental cohorts. The inherent imbalances in these groups present challenges for statistical interpretation. While the findings suggest that less frequent carprofen use may reduce adverse effects, the surgical interventions and concurrent use of other drugs in these experiments likely exacerbated these outcomes. Further investigation into the interactions between carprofen, surgical stress, and other perioperative factors is needed to refine analgesia protocols in laboratory animals. Despite these limitations, these observations contribute to understanding analgesia protocols and may assist in improving animal welfare practices.

Determinants Influencing Utilization of Antenatal Care Services in Tabora Region, Tabora Municipality, Tanzania

This study examines the determinants influencing the utilization of antenatal care services (ANC) in in Tabora region with a particular focus on Tabora Municipality, Tanzania. The study used both quantitative and qualitative methods to analyze the problem. The study uses primary and secondary data obtained from the field. Tools used for data collection were questionnaires, interviews, and observation. This study employed a cross-sectional research design. This design was preferred because the design allowed the collection of data from different groups of respondents at one point at a time. Similarly, the design had a greater degree of accuracy and precision in the data collected and used for statistical description and interpretation. The study found that there was low utilization of antenatal care services in Tabora Municipality. The study revealed that the low utilization of ANC in Tabora Municipality can be solved by addressing the determinants that are responsible for the low use of ANC services. The study identified a number of determinants that influence ANC visits such as spousal involvement in antenatal clinics, the attitudes of health service professionals, clinic opening days for the antenatal care services by client satisfaction and integrated approach to antenatal care services. The determinants that affect the use of ANC visits are not only many and complex, but they play different roles in different situations. The study revealed that men and the whole community should be included in the ANC campaign so that they understand more about potential risks for pregnant women. This would increase the level of ANC use and thus reduce the high incidence of maternal and neonatal death in Tanzania including the Tabora region that results from poor utilization of ANC services. Also, this study adds knowledge to health service providers in understanding the determinants that limit pregnant women’s utilization of antenatal services finding ways to improve the services and encourage women to utilize ANC services. The study findings will enable programme planners, policymakers, implementers and managers to come up with strategies for interventions that will enable pregnant women to start seeking and utilizing ANC services early in pregnancy and to have fewer pregnancy complications that lead to maternal and neonatal deaths

Resistance of the Steel Lap Joints Connected by Spot Welding and Brazing

Welding technologies are constantly evolving, and their applicability is expanding, considering also the construction domain. Steel structures benefit from the advances in welding technologies due to the use of thin gauge steel sheets which can now be connected at high quality and automatically. The resistance of the connection between the thin steel sheets is crucial for the durability and safety of a structure made of built-up thin-walled cold-formed steel elements. Generally, self-drilling screws or bolts are used for the connection between thin-walled elements, but the quantity of time and manpower necessary for a large number of connections demands an improved solution. Conventional welding techniques are unsuitable for joining thin sheets, ranging from 0.4 to 1.0 mm to thicker ones measuring 1.0 to 3.5 mm. This article compares the results of an experimental investigation into lap joints connected by spot welding and MIG brazing with the design code provisions. The study examines single-lap joints in steel sheets of 0.8, 1.0, 1.2, 1.5, 2.0 and 2.5 mm thickness, connected using these welding technologies. The results obtained are then compared with analytical relations and processed according to EN 1990. Depending on the thickness of the connected sheets, spot welding can lead to two failure modes: button pull-out fracture and interfacial fracture. MIG brazing, a welding technology that deposits material below the melting point of the base material, is known for its advantages, such as low energy consumption, spatter-free operation, high welding speed, and compatibility with thin sheet metals. However, its application in the structural engineering of cold-formed elements lacks documentation. In the study, the MIG brazed specimens failed in the heat-affected zone of the connection. The results indicate the dependence of the spot weld lap joint resistance on the connected sheets' thickness, while the resistance of the MIG brazed lap joints is influenced by the minimum thickness of the connected steel sheet. The study aims to demonstrate the feasibility of the proposed solutions, evaluate their performance, and establish the limits of their applicability. A statistical interpretation of the results highlights the precision and reliability of joint resistance.

Interpretation of statistical findings in randomised trials: a survey of statisticians using thematic analysis of open-ended questions

SummaryBackgroundDichotomisation of statistical significance, rather than interpretation of effect sizes supported by confidence intervals, is a long-standing problem.MethodsWe distributed an online survey to clinical trial statisticians across the UK, Australia and Canada asking about their experiences, perspectives and practices with respect to interpretation of statistical findings from randomised trials. We report a descriptive analysis of the closed-ended questions and a thematic analysis of the open-ended questions.ResultsWe obtained 101 responses across a broad range of career stages (24% professors; 51% senior lecturers; 22% junior statisticians) and areas of work (28% early phase trials; 44% drug trials; 38% health service trials). The majority (93%) believed that statistical findings should be interpreted by considering (minimal) clinical importance of treatment effects, but many (61%) said quantifying clinically important effect sizes was difficult, and fewer (54%) followed this approach in practice.Thematic analysis identified several barriers to forming a consensus on the statistical interpretation of the study findings, including: the dynamics within teams, lack of knowledge or difficulties in communicating that knowledge, as well as external pressures. External pressures included the pressure to publish definitive findings and statistical review which can sometimes be unhelpful but can at times be a saving grace. However, the concept of the minimally important difference was identified as a particularly poorly defined, even nebulous, construct which lies at the heart of much disagreement and confusion in the field.ConclusionThe majority of participating statisticians believed that it is important to interpret statistical findings based on the clinically important effect size, but report this is difficult to operationalise. Reaching a consensus on the interpretation of a study is a social process involving disparate members of the research team along with editors and reviewers, as well as patients who likely have a role in the elicitation of minimally important differences.

A codifiable methodology for estimating pallet sliding displacements on steel racking systems

AbstractTo facilitate the logistic processes within a modern warehouse, the contents of steel racking systems are not mechanically connected to the supporting beams, allowing a content‐sliding mechanism to develop when static friction is exceeded. Given that the mass of contents is dominant, this is beneficial for limiting the apparent inertia. On the other hand, pallet fall‐off may occur during strong seismic excitations, which is a failure mode that is not addressed by current seismic design processes and guidelines for racks. Along these lines, a codifiable methodology is proposed for estimating sliding displacements on steel racking systems, based on the statistical interpretation of a large set of response history analyses, using different rack configurations and ground motions. Firstly, a multi‐parametric analysis is conducted using simplified rack models to (i) select the intensity measure and engineering demand parameter that can best describe the problem of pallet sliding and (ii) identify the salient rack characteristics that dominate sliding behavior. Thereafter, a series of multi‐stripe analyses are performed using 180 rack realizations with different feature combinations to derive a so‐called, Empirical Sliding Prediction Equation (ESPE) by following a three‐step procedure: (a) perform regression on maximum sliding, (b) perform regression on the normalized sliding profile, and (c) combine steps a‐b to derive the denormalized profile at a given confidence level. The proposed empirical relationships are then validated through a comparison between the observed and fitted sliding displacements in three rack case studies.

Beyond the Surface: Investigating Clinical and Magnetic Resonance Imaging Dynamics in Knee Injuries: A Cross-sectional Study

Abstract Context: Orthopedic surgeons frequently encounter knee soft tissue injuries such as meniscal and ligament injuries. This study seeks to explore the diagnostic efficacy of clinical examination, magnetic resonance imaging (MRI), and arthroscopy in identifying knee injuries. Subjects and Methods: This prospective observational study enrolled 120 patients with knee injuries slated for arthroscopic surgery based on clinical and MRI assessments. The study assessed and compared the diagnostic accuracy of clinical and MRI findings. Statistical Analysis Used: Statistical analysis was performed using SPSS software (SPSS Inc., Chicago, IL, USA) for the Windows program (21.0 version). The Spearman correlation analysis was done to assess the relationship between the various parameters. The level of agreement was assessed using Cohen’s kappa statistics. Interpretation of kappa statistics is as follows: 0 to 0.20-Slight agreement; 0.1 to 0.39-Fair; 0.40 to 0.59-Moderate; 0.60 to 0.79- Substantial and 0.80 to 0.90-Almost perfect agreement. Sensitivity, specificity, accuracy, positive predictive value and negative predictive value were calculated and observed by using 2 × 2 contingency table. P < 0.05 was considered statistically significant. Results: When comparing MRI and arthroscopy findings, the anterior cruciate ligament (ACL) tear exhibited the highest sensitivity and specificity at 100.00% and 91.84%, respectively, while the medial meniscus tear had the lowest sensitivity and specificity at 80.23% and 61.76%. Regarding the comparison between clinical examination and arthroscopy, the Lachman test displayed the highest sensitivity at 95.92%, whereas McMurray’s test (Lateral Meniscus) had the lowest sensitivity at 54.55%, and the posterior Drawer’s test showed the lowest specificity at 60.00%. Lachman also demonstrated the highest diagnostic accuracy at 98.33%, while the posterior Drawer’s test had the lowest diagnostic accuracy at 70.00%. Conclusions: Despite a few limitations, clinical examination and MRI currently stand out as the most precise non-invasive methods for detecting abnormalities in the menisci and the ACL. These diagnostic approaches provide valuable insights into the structural integrity of these knee components, allowing for a comprehensive assessment without the need for invasive procedures.

The identity of religion always comes up: the war, the mass media and the reproduction of Muslim identity in the west

Islamophobia in the media occurs when media sources present hostile, inaccurate, and/or deceptive stories about Islam, Muslims, or Arabs. Islamophobia is the term used to describe strong antipathy or prejudice toward Muslims, intense hatred or fear of Islam, particularly as a political force, and the study of how and to what extent the media promotes There has been a lot of scholarly and political discourse on Islamophobia. The discourse around Islamophobia in the media often focuses on the rhetorical strategies utilized by individual media outlets or by the mass media of a given nation or region, such the US or Europe. A few instances of this are when Islam is portrayed in a poor light relative to other religions, when Muslims are linked to terrorism, when Muslims and their followers are portrayed as aggressive or primitive, and when Muslim viewpoints are excluded from discussions on politics and academia, among other subjects. On the other hand, reactions to talks about Islamophobia in the media frequently cast doubt on what actually qualifies as Islamophobia, how frequently, how severe, and how effective Islamophobic language is, as well as the political reasons for such talks. This study aims to determine whether or not there was obvious inherent bias by examining the tone, structure, and topics offered by the print media prior to a terrorist event. This study examines how the world press has connected Islam to terrorism and emphasizes how subliminal print messages might contribute to Muslim racial profiling and the spread of Islamophobia. The editorials of six prominent international newspapers between 2014 and 2017 provided the data for this study, which created strata of ten significant worldwide terrorism incidents at random. The investigator examined editorials for a month following the event. The researcher’s results and conclusions are obtained by statistical interpretation following data analysis using event methodology and content analysis.

CyCadas: accelerating interactive annotation and analysis of clustered cytometry data.

Single cell profiling by cytometry has emerged as a key technology in biology, immunology and clinical-translational medicine. The correct annotation, which refers to the identification of clusters as specific cell populations based on their marker expression, of clustered high-dimensional cytometry data, is a critical step of the analysis. Its accuracy determines the correct interpretation of the biological data. Despite the progress in various clustering algorithms, the annotation of clustered data still remains a manual, time consuming and error-prone task. We developed a user-friendly cluster annotation and differential abundance detection tool that can be applied on data generated with Self Organizing Map clustering algorithms, thus simplifying the annotation process of datasets that consist of hundreds or thousands of clusters. We present Cytometry Cluster Annotation and Differential Abundance Suite (CyCadas), a semi-automated software tool that facilitates cluster annotation in cytometry data by offering both visual and computational guidance. CyCadas addresses the critical need for efficient and accurate annotation of high-resolution clustered cytometry data, significantly reducing the time needed to perform the analysis compared to both manual gating approaches and manual annotation of clustered data. The tool features a user-friendly interface, visual tools enabling data exploration and automated threshold estimation to separate negative and positive marker expression. It facilitates the definition and annotation of cell phenotypes among multiple clusters in a tree-based data structure. Finally, it calculates the abundance of various cell populations across the conditions with statistical interpretation. It is an ideal resource for researchers aiming to streamline their cytometry workflow. CyCadas is available as open source at: https://github.com/DII-LIH-Luxembourg/cycadas.

8737 Primary Hyperparathyroidism (PHPT) “Phenotypes” and the Results of Parathyroid [99mTc]Tc-Sestamibi SPECT/CT Scintigraphy: Minimizing the Risk of Negative Imaging Results

Abstract Disclosure: K. Kucharczyk: None. A. Drynda: None. J. Podlewski: None. M. Trofimiuk-Muldner: None. A. Hubalewska-Dydejczyk: None. Introduction. Primary hyperparathyroidism (PHPT) is a prevalent endocrinopathy typically identified through biochemical testing. PHPT is characterized by hypercalcemia accompanied by increased or inappropriately normal plasma parathyroid hormone (PTH) concentrations. Preoperative imaging is conducted when surgery is indicated to pinpoint parathyroid adenomas. [99mTc]Tc-Sestamibi scintigraphy is highly specific and sensitive in diagnosing PHPT, with a higher adenoma detection rate demonstrated for patients with larger lesions or higher blood calcium concentrations. The study aimed to investigate the relationship between the results of biochemical tests and clinical manifestations (PHPT “phenotype”) and the rate of positive results of parathyroid [99mTc]Tc-Sestamibi scintigraphy. Materials and methods. This was a retrospective study of patients suspected of PHPT who underwent parathyroid [99mTc]Tc-Sestamibi SPECT/CT scintigraphy between 2010 and 2022. Patients’ cluster analysis was conducted based on PTH, serum calcium (Ca), and phosphate (Pi) concentrations to find distinct patterns in these parameters. Furthermore, we compared the distributions of additional patients’ attributes, including gender, lesion size, serum vitamin D, ALP concentrations, urinary calcium, urolithiasis prevalence, as well as parathyroid scintigraphy results. Results. 513 patients were divided into 5 clusters using different algorithms. Finally, clusters from K-means methods were selected based on statistical metrics and expert interpretation. Those were organized in ascending order of positive scintigraphy results, with Cluster 5 reaching a 79.5% positivity rate and median values of PTH - 315.5 pmol/L, Ca - 2.96 mmol/L, and Pi - 0.7 mmol/L. As the proportion of positive imaging outcomes declined, median PTH and calcium concentrations decreased while phosphate concentrations increased. In Cluster 1, with 30% of positive imaging results, medians were as follows: PTH - 79.06 pmol/L, Ca - 2.55 mmol/L and Pi - 1.1 mmol/L. A comparative analysis of various clinical and biochemical parameters revealed statistically significant differences between clusters. Patients from Clusters with a higher frequency of positive scintigraphy were significantly more likely to be males, vitamin D deficient, with higher ALP concentrations, diagnosed with urolithiasis, and harbouring larger lesions. Conclusions. PHPT “phenotypes” correlated with disease severity are evidently linked to parathyroid scintigraphy detection rate. Therefore, it is crucial to know that false-negative imaging is more likely in PHPT patients with minor deviations in laboratory tests. Judicious assessment of biochemical and clinical features may limit the number of redundant parathyroid scintigraphies and, in consequence, reduce healthcare costs and unnecessary radiation exposure. Presentation: 6/2/2024

Mastering meta-analysis in Microsoft Excel with MetaXL add-in: A comprehensive tutorial and guide to meta-analysis.

Meta-analysis, a powerful technique for combining effect estimates from multiple studies, enhances statistical power and precision. However, its adoption can be hindered by challenges in statistical interpretation and the complexity of specialized software. MetaXL, a freely available Microsoft Excel add-in, aims to mitigate these barriers by providing comprehensive support and facilitating seamless integration of meta-analytical results into research publications. This tutorial illustrates the practical application of MetaXL for synthesizing meta-analytical evidence, with a focus on common effect sizes and their presentation. This paper reintroduce MetaXL's functions and provide concise explanations of common effect sizes employed in meta-analysis. The tutorial delves into fundamental concepts such as the selection of appropriate effect sizes for pooling and the choice of meta-analytical models. Eight illustrative examples are presented, incorporating diverse effect sizes and data formats, including scenarios involving incidence rate ratios, weighted and standardized mean differences, hazard ratios, and prevalence. Additionally, key concepts in network meta-analysis are discussed, along with their implementation in MetaXL. MetaXL provides convenient access to data formatting templates tailored to various data types and effect sizes encountered in included studies. This tutorial offers researchers, particularly those with limited resources, detailed explanations and insights into commonly used methodologies for pooling effect sizes. Furthermore, it introduces the new Excel functions that comes with the MetaXL add-in. Accurate population of this function and adherence to the correct format are essential to ensure error-free analyzes.

Overcoming the pitfalls of categorizing continuous variables in ecology, evolution and behaviour.

Many variables in biological research-from body size to life-history timing to environmental characteristics-are measured continuously (e.g. body mass in kilograms) but analysed as categories (e.g. large versus small), which can lower statistical power and change interpretation. We conducted a mini-review of 72 recent publications in six popular ecology, evolution and behaviour journals to quantify the prevalence of categorization. We then summarized commonly categorized metrics and simulated a dataset to demonstrate the drawbacks of categorization using common variables and realistic examples. We show that categorizing continuous variables is common (31% of publications reviewed). We also underscore that predictor variables can and should be collected and analysed continuously. Finally, we provide recommendations on how to keep variables continuous throughout the entire scientific process. Together, these pieces comprise an actionable guide to increasing statistical power and facilitating large synthesis studies by simply leaving continuous variables alone. Overcoming the pitfalls of categorizing continuous variables will allow ecologists, ethologists and evolutionary biologists to continue making trustworthy conclusions about natural processes, along with predictions about their responses to climate change and other environmental contexts.

20 years of monitoring of a steel jacket offshore platform: variability of environmental and modal parameters

The fixed steel offshore platform VEGA-A has been operating in the Sicily channel since 1988. The platform, one of the largest in the Mediterranean Sea, is equipped with a monitoring system that collects environmental (by means of a current meter, a depth gauge, and a system for detecting wind speed and direction) and structural (by means of nine accelerometers) data. After a description of the recording system, this paper provides a statistical interpretation of the structural response of the platform over the last 20 years. The structural monitoring system is aimed at performing dynamic identification (i.e., evaluating main frequencies and mode shapes), and part of the acquired data is directly processed on the platform in order to constantly check their representativeness in relation to the structural control of the platform. The possible variation of main frequencies and mode shapes over time may be due to both changes in environmental loads/conditions and/or structural damage; in this respect, a data-driven approach capable of recognizing anomalies in the dynamic behavior was adopted here to assess the performances of the platform over the 20 years monitoring period.

Numerical illustration using finite difference method for the transient flow through porous microchannel and statistical interpretation of entropy using response surface methodology

The current article discloses the influence of the hyperbolic tangent nanofluid on time dependent flow through a microchannel when a magnetic field is applied. The porous medium was incorporated using the Darcy–Forchheimer model. The chemical reaction is explained by Arrhenius activation energy. Temperature is determined by convective boundary conditions. The irreversibility occurring in the flow is analyzed. The modeled problem gives rise to partial differential equations, which are computed by finite difference method. Response surface methodology, an optimization technique, is used to attain the optimal conditions for entropy generated for the flow of fluid. Results of the analysis reveal that concentration decreases with the rise in reaction rate parameter and increases with activation energy parameter. Prandtl and Eckert numbers, with their increase, enhance entropy, and fluid friction irreversibility is at its highest. Perfect co-relation is attained for the model by the response surface methodology, with a co-relation coefficient of 100 %. The Weissenberg number is highly sensitive to change in the present modeling, followed by Darcy and Reynolds numbers. The Reynolds number and Darcy number show positive sensitivity, while the Weissenberg number shows negative sensitivity to the entropy generated.

Design of integrated evolutionary finite differences for nonlinear electrohydrodynamics ion drag flow in cylindrical conduit model

This research implements an evolutionary optimized finite differences scheme (FDS) for nonlinear electrohydrodynamics ion drag flow dynamics in a cylindrical conduit (EHD-IDFCC). In the scheme, finite differences are exploited to discretize governing expressions of EHD-IDFCC, represented with a nonlinear singular seconder order differential equation, into a nonlinear equations-based system. The fitness function based on residual error is constructed for the FDS-based discretized EHD-IDFCC model. Its optimization is conducted with the global search capability of genetic algorithms (GAs) aided by the local search efficacy of the interior-point method (IPM), i.e., FDS-GA-IPM. The performance of the designed stochastic numerical solver FDS-GA-IPM is evaluated for a variant of the EHD-IDFCC model for different scenarios to measure the effect of axial flow velocity by varying the electric Hartmann numbers, as well as the nonlinearity factor. Statistical interpretations based on histogram illustrations, probability plots, and boxplots in terms of the cost function, mean absolute error (MAE), Thai inequality coefficients (TIC), and coefficient of determination metrics (R2) are used to endorse the accuracy, convergence, stability, and strength of the FDS-GA-IPM.

Random measurement and prediction errors limit the practical relevance of two velocity sensors to estimate the 1RM back squat.

While maximum strength diagnostics are applied in several sports and rehabilitative settings, dynamic strength capacity has been determined via the one-repetition maximum (1RM) testing for decades. Because the literature concerned several limitations, such as injury risk and limited practical applicability in large populations (e.g., athletic training groups), the strength prediction via the velocity profile has received increasing attention recently. Referring to relative reliability coefficients and inappropriate interpretation of agreement statistics, several previous recommendations neglected systematic and random measurement bias. This article explored the random measurement error arising from repeated testing (repeatability) and the agreement between two common sensors (vMaxPro and TENDO) within one repetition, using minimal velocity thresholds as well as the velocity = 0m/s method. Furthermore, agreement analyses were applied to the estimated and measured 1RM in 25 young elite male soccer athletes. The results reported repeatability values with an intraclass correlation coefficient (ICC) = 0.66-0.80, which was accompanied by mean absolute (percentage) errors (MAE and MAPE) of up to 0.04-0.22m/s and ≤7.5%. Agreement between the two sensors within one repetition showed a systematic lower velocity for the vMaxPro device than the Tendo, with ICCs ranging from 0.28 to 0.88, which were accompanied by an MAE/MAPE of ≤0.13m/s (11%). Almost all estimations systematically over/ underestimated the measured 1RM, with a random scattering between 4.12% and 71.6%, depending on the velocity threshold used. In agreement with most actual reviews, the presented results call for caution when using velocity profiles to estimate strength. Further approaches must be explored to minimize especially the random scattering.

Effect of secondary processes on the petrophysical properties of sand rock of the tanopchin formation of the Tambey field (Yamalo-Nenets autonomous okrug)

Relevance. Finding the correlation between filtration-capacitive properties and secondary processes helps to identify missed oil and gas deposits. Traditional methods of processing geophysical information are becoming less and less effective, and accordingly there is a need to introduce new techniques for detecting missed hydrocarbon deposits. Aim. To study the effect of secondary processes on the filtration and reservoir properties of rocks in the productive lower strata of the tanopchin formation of the North Tambey license area, located within the Tambey field, using materials from geophysical surveys of wells and core data. Methods. The statistical-correlation interpretation method represents a significant breakthrough in the field of interpretation of well logging data. It allows for a more accurate interpretation of data from existing reservoir studies, which makes it possible to identify productive sections of wells where hydrocarbons could not be detected by traditional methods. Statistical correlation interpretation is carried out on the basis of data from secondary geochemical processes occurring in the formation. The scientific novelty. Identification of the relationship between the intensity of secondary processes and the petrophysical properties of the rocks of the Lower Cretaceous productive horizon of the Tambey field (Yamalo-Nenets autonomous okrug). Results and conclusions. The author has determined the dependence of the filtration-capacitive properties of rocks on the intensity of secondary geochemical processes. It was established that secondary geochemical processes such as carbonatization and pyritization worsen reservoir properties, while kaolinization and pelitization lead to an improvement in the filtration and reservoir properties of reservoir rocks. The paper explains the mechanism of effect of secondary processes on filtration-capacitive properties. Pelitization of potassium feldspars leads to the formation of three-layer clay minerals, which have the largest sorption surface area and cation exchange capacity; as a result, the reservoir capacity increases, which leads to an increase in permeability several times.