Probability Values Research Articles

Shannon’s entropy and its bounds for some a priori known equiprobable states

AbstractIt is known that Shannon’s entropy is nonnegative and its maximum value is reached for equiprobable events. Adding or removing impossible events does not affect Shannon’s entropy. However, if we increase the number of events and consider not necessarily all of them equiprobable, but at least as many of them as the initial number of equiprobable events, how does Shannon’s entropy change? We study the lower bound of the interval where the probability value of the a priori assumed equiprobable states must belong when the entropy increases.

FACTORS INFLUENCING POST-CIRCUMCISION WOUND HEALING

Objective: This study aims to determine the effect of the penile gland and smegma smear, the expression of collagen and fibroblasts in the preputium, on post-circumcision wound healing. Material & Methods: A cross-sectional study conducted in Malang with samples obtained by purposive sampling on September 17, 2022. Inclusive criteria were uncircumcised males who agreed to be circumcised and had no contraindications to the procedure. Furthermore, the preputium obtained from the circumcision procedure was stained with Hematoxylin-Eosin (HE) and counted under an optical microscope. Post-circumcision evaluation was carried out seven days after the procedure. The data were analyzed using the regression method; p denotes the probability value or significance level, while the b score denotes the degree of influence. Results: There were total of 31 research samples that had a significant difference in the average age between the samples with post-circumcision complaints (11.25 ± 2.75) and those without complaints (8.5 ± 2.73) (p=0.05). The regression test found that bacterial culture, fibroblasts, and collagen had significant effects of 24%, 25%, and 24%, respectively. Conclusions: Skin elasticity decreases with age, as marked by increased fibroblasts and decreased collagen density. Fibroblast factors, collagen, and bacterial culture are significant in wound healing. Keywords: Circumcision, collagen, fibroblast, wound healing.

A copula-based approach to instream ecological flow determination considering inter- and intra-annual runoff variability

ABSTRACT Instream ecological flow (IEF) provides a flow reference value for maintaining the stability of river ecosystems and enriching biodiversity. Existing methods for determining the IEF often consider only one of the intra-annual runoff distribution characteristics or the inter-annual runoff distribution characteristics. In this study, a copula-based ecological runoff determination method is proposed to consider both annual and monthly runoff magnitudes. The marginal distribution functions of annual and monthly runoff are first determined using the great likelihood method. Then the copula function is used to construct the joint distribution function of annual and monthly runoff series. Using the flow duration curve method, the IEF under different annual and monthly runoff exceedance probabilities is calculated. The probability values are combined with the initial IEF values to determine the final IEF process. A case study is conducted using real-world data from the Tongtian River in China. The results show that the total annual basic ecological water demands of the Tongtian River under abundant, flat, and dry water years are 138, 102 and 72. 2 billion m3. The proposed method effectively avoids the disturbance of extreme runoff.

Pengaruh Kombinasi Stimulasi Pijat bayi dan Esensial Oil Lavender Terhadap Motorik Kasar dan Motorik Halus Pada Bayi Usia 3-12 Bulan di Kota Bengkulu

Background: The growth and development period of infants needs special attention because the process is very fast. There are still toddlers who experience gross motor and fine motor disorders. World Health Organization (WHO) 2016 globally states that around 20-40% of infants aged 0-2 years experience problems with delays in the development process, 5-25% of toddlers who experience gross motor and fine motor disorders. The impact of delays in infant gross motor development causes a decrease in creativity in the adaptation period while the impact of delays in fine motor development causes obstacles in the child's learning process. Efforts that can be made in optimizing the growth and development of fine motor and gross motor in infants in addition to nutrition provided by the mother and one of the other ways needs stimulation. The combination of stimulation of baby massage and lavender essential oil is one of the stimulations to improve gross motor and fine motor in infants aged 3-12 months. Objective: Proving the effect of a combination of baby massage stimulation and lavender essential oil on improving gross motor and fine motor in infants aged 3-12 months. Methods: Pre-experimental quantitative research design with one group pretest-postest design. Sample 40 infants aged 3-12 months. Analysis used to assess the effect on the improvement of gross motor and fine motor in 2 PMB using t test. Results: Hypothesis testing in this study using the Wilcoxon test. Obtained a probability value (p value) of (p value) 0.02 or < 0.05, which means that there is a combined effect of baby massage stimulation and lavender essential oil on improving gross motor and fine motor in infants aged 3-12 months. The intervention was given for 4 weeks, twice a week the intervention was given a combination of baby massage and lavender essential oil, then an evaluation was carried out using the Pre-Developmental Screening Questionnaire (KPSP), consisting of 10 assessment items, starting from gross motor, fine motor, socialization and independence assessments. as well as speech and language skills. Conclusion: The combination of baby massage stimulation and lavender essential oil has an effect on improving gross motor and fine motor in infants aged 3-12 months. Suggestion: parents who have babies are expected to routinely provide baby massage stimulation.

Optimal sizing of standalone hybrid renewable energy system based on reliability indicator: A case study

The economical electrification of rural settlements extensively utilizes renewable energy sources. In recent years, the deployment of solar photovoltaic, wind turbine, and biomass gasifier-based power generation technologies for electricity accessibility in remote regions has received greater prominence. This paper presents an optimal component design of a hybrid solar PV-wind and battery system along with a biomass gasifier to provide continuous electricity for rural communities of Uttarakhand, India. In this study, a recently developed population-based giza pyramids construction (GPC) methodology is applied to determine the optimal component sizing. The findings of the GPC method are contrasted with the particle swarm optimization (PSO) methodology to assess the effectiveness of the proposed method. The annualized system cost and levelized cost of energy of the hybrid renewable energy system have been minimized subject to technical reliability indicators such as loss of power supply probability and renewable fraction.Moreover, a systematic exploration of the system has been conducted to assess its optimal feasibility across different values of power loss probability ranging from (0% to 4%). The simulation indicates that the proposed method adeptly identifies globally optimal values, leading to a $177 decrease in annual cost and 8% reduction in average simulation time compared to PSO. The research reveals that the balanced point (relative attainment), where system reliability and cost-effectiveness intersect optimally, is achieved at a 3% power loss level, resulting in the most significant cost reduction of $199 compared to other probability levels.

EFFECT OF PRODUCT MARKET MATRIX ON THE PERFORMANCE OF MEDIUM ENTERPRISES IN NORTH CENTRAL, NIGERIA

This research work examined the effect of product market matrix on the performance of medium enterprises in North Central, Nigeria. The researcher used primary data source from a sample of three hundred and eighty four (384) respondents obtained by the use of a structured questionnaire. The data collected was analyzed using descriptive statistics such as frequency, simple percentage and the relationship between the variables of the model were tested using multiple linear regression analysis. The hypotheses of the study were tested using the probability value of the regression estimates. The result of the regression analysis indicates that Market penetration strategy's regression coefficient is 0.401 and significant (p0.05). Product development strategy is -0.059 and negligible (p0.05). A one-unit increase in product development decreases medium firm performance by 0.059 units. A one-unit increase in market development strategy increases medium firm performance by 0.196 units (p0.05). Product diversification approach has a strong coefficient of 0.319. This means a one-unit improvement in product diversification strategy increases medium firm performance by 0.319 units. It was concluded that businesses must consider the region's market conditions, competitive hurdles, and client behaviors to flourish. It was recommended among others that Market Penetration and Product Diversification Strategies are advised for medium enterprises in North Central Nigeria due to their benefits. Expanding market share and targeting existing clients can increase performance. Diversifying products to fulfill client needs can enhance revenue and performance. Firms should use both methods to optimize profits.

Life tables of annual life expectancy and risk factors for mortality in cats in the UK.

The aims of the present study were to generate the first life tables for the UK companion cat population overall as well as broken down by sex and breed status, and to quantify associations between mortality and traits such as sex, neuter status, breed status and body weight in relation to mortality. Life table construction and modelling included data on 7936 confirmed deaths in cats under primary veterinary care at clinics participating in the VetCompass Programme in 2019. The life tables were built for cats overall, female and male cats, and crossbred and purebred cats. Multivariable generalised linear regression models were generated to explore the risk factors for a shortened lifespan. Life expectancy at age 0 for UK companion cats overall was 11.74 years (95% confidence interval [CI] 11.61-11.87). The probability of death at each year interval increased with age from year interval 3-4, with the probability value not exceeding 0.05 before year 9. Female cats (12.51 years; 95% CI 12.32-12.69) had a 1.33-year longer life expectancy than male cats (11.18 years; 95% CI 11.01-11.38) at age 0. Among the 12 breeds (including crossbred) analysed, Burmese and Birman had the longest life expectancy at year 0, showing 14.42 years (95% CI 12.91-15.93) and 14.39 years (95% CI 12.87-15.91), respectively. Sphynx had the shortest life expectancy at year 0 among the analysed breeds at 6.68 years (95% CI 4.53-8.83). Being entire, purebred and with a non-ideal body weight were significantly linked to a decreased lifespan. The life tables presented here for companion cats in the UK overall, by sex, and by crossbred and purebred cats can contribute to a better understanding of the life trajectory of cats, helping with evidence-based decision-making for cat owners and the veterinary profession. We have also provided an updated life expectancy at age 0 for various cat breeds for 2019 and showed evidence of the association between non-ideal weight and a decreased lifespan.

Application of Monte Carlo simulation for the estimation of production availability in geothermal well

Wellbore simulation is one of the methods used in geothermal system performance analysis using a mathematical model of the geothermal system that considers parameters such as operating conditions, feed zone parameters, and well geometry. One of the methods used to perform wellbore simulation is the homogenous method. However, the results may still have a high level of uncertainty. To overcome this, probabilistic methods such as the Monte Carlo method can improve the accuracy of geothermal well production capacity modelling. The Monte Carlo method determines variability and uncertainty in the data being analysed. In determining geothermal well production capacity, the Monte Carlo method can take random samples of various influencing parameters, such as operating conditions, feed zone parameters, and well geometry. By conducting a Monte Carlo simulation, a more comprehensive probability distribution related to well production capacity will be obtained, considering the uncertainties associated with the available data. This research aims to determine the probability of production capacity of a candidate well in a geothermal field by considering uncertainty factors. In this research, a simulation is carried out until it converges using the Monte Carlo method so that the probability value will be obtained. Based on the analysis using the Montecarlo method, the probability of production capacity at the VY-1 Well of Vyatra Field is obtained, namely the P10 value with a large Mwe of 8.31 with an error of 0.102. Next, the P50 value obtained a Mwe value of 11.44 with an error of 0.001. Then P90 was obtained at 14.44 with an error of 0.012. Based on the analysis results, the most influential parameter in determining the production capacity of a Geothermal well is the productivity index value, followed by temperature and reservoir pressure.

Principal Uncertainty Quantification With Spatial Correlation for Image Restoration Problems.

Uncertainty quantification for inverse problems in imaging has drawn much attention lately. Existing approaches towards this task define uncertainty regions based on probable values per pixel, while ignoring spatial correlations within the image, resulting in an exaggerated volume of uncertainty. In this paper, we propose PUQ (Principal Uncertainty Quantification) - a novel definition and corresponding analysis of uncertainty regions that takes into account spatial relationships within the image, thus providing reduced volume regions. Using recent advancements in generative models, we derive uncertainty intervals around principal components of the empirical posterior distribution, forming an ambiguity region that guarantees the inclusion of true unseen values with a user-defined confidence probability. To improve computational efficiency and interpretability, we also guarantee the recovery of true unseen values using only a few principal directions, resulting in more informative uncertainty regions. Our approach is verified through experiments on image colorization, super-resolution, and inpainting; its effectiveness is shown through comparison to baseline methods, demonstrating significantly tighter uncertainty regions.

Risk-based life cycle cost–benefit analysis for progressive collapse design of RC frame structures

Progressive structural collapse is a typical low-probability high-consequence event. Progressive collapse design can effectively improve the robustness of structures against accidental local damage and reduce the probability of collapse. However, progressive collapse design also increases the construction cost of buildings. Hence, it is necessary to conduct cost-benefit analyses for the progressive collapse design of building structures. This study first designs a reinforced concrete (RC) frame based on a progressive collapse design program that simultaneously optimizes material consumption and structural resistance. Then, the structural failure probability is quantified using an alternative path (AP) method-based fragility analysis that considers the structural uncertainties. Based on this, the life cycle costs and benefits of the structure designed with different design load factors are investigated. A four-story RC frame is used as an example. By considering the time value of money and threat probability, the break-even points and optimized design load factors for the progressive collapse design of the RC frame are analyzed. These research outcomes can help promote progressive collapse design in engineering practice and provide references for proposing scientific and reasonable design load factors.

HRUNet: Assessing Uncertainty in Heart Rates Measured From Facial Videos.

Video-based Photoplethysmography (VPPG) offers the capability to measure heart rate (HR) from facial videos. However, the reliability of the HR values extracted through this method remains uncertain, especially when videos are affected by various disturbances. Confronted by this challenge, we introduce an innovative framework for VPPG-based HR measurements, with a focus on capturing diverse sources of uncertainty in the predicted HR values. In this context, a neural network named HRUNet is structured for HR extraction from input facial videos. Departing from the conventional training approach of learning specific weight (and bias) values, we leverage the Bayesian posterior estimation to derive weight distributions within HRUNet. These distributions allow for sampling to encode uncertainty stemming from HRUNet's limited performance. On this basis, we redefine HRUNet's output as a distribution of potential HR values, as opposed to the traditional emphasis on the single most probable HR value. The underlying goal is to discover the uncertainty arising from inherent noise in the input video. HRUNet is evaluated across 1,098 videos from seven datasets, spanning three scenarios: undisturbed, motion-disturbed, and light-disturbed. The ensuing test outcomes demonstrate that uncertainty in the HR measurements increases significantly in the scenarios marked by disturbances, compared to that in the undisturbed scenario. Moreover, HRUNet outperforms state-of-the-art methods in HR accuracy when excluding HR values with 0.4 uncertainty. This underscores that uncertainty emerges as an informative indicator of potentially erroneous HR measurements. With enhanced reliability affirmed, the VPPG technique holds the promise for applications in safety-critical domains.

Modeling the Subgrid-Scale Scalar Variance: A Priori Tests and Application to Supersaturation in Cloud Turbulence

Abstract The subgrid-scale (SGS) scalar variance represents the “unmixedness” of the unresolved small scales in large-eddy simulations (LES) of turbulent flows. Supersaturation variance can play an important role in the activation, growth, and evaporation of cloud droplets in a turbulent environment, and therefore efforts are being made to include SGS supersaturation fluctuations in microphysics models. We present results from a priori tests of SGS scalar variance models using data collected in turbulent Rayleigh–Bénard convection in the Michigan Tech Pi chamber for Rayleigh numbers Ra ∼ 108–109. Data from an array of 10 thermistors were spatially filtered and used to calculate the true SGS scalar variance, a scale-similarity model, and a gradient model for dimensionless filter widths of h/Δ = 25, 14.3, and 10 (where h is the height of the chamber and Δ is the spatial filter width). The gradient model was found to have fairly low correlations (ρ ∼ 0.2), with the most probable values departing significantly from the one-to-one line in joint probability density functions (JPDFs). However, the scale-similarity model was found to have good behavior in JPDFs and was highly correlated (ρ ∼ 0.8) with the true SGS variance. Results of the a priori tests were robust across the parameter space considered, with little dependence on Ra and h/Δ. The similarity model, which only requires an additional test filtering operation, is therefore a promising approach for modeling the SGS scalar variance in LES of cloud turbulence and other related flows.

Improving a method for detecting stealth aerial vehicles by using a network of two small-sized radars with decentralized information processing

Improving a method for detecting stealth aerial vehicles by using a network of two small-sized radars with decentralized information processing

Evaluation of malaria cases among the outpatient visits to Ekiti State University Health Centre Ado-Ekiti, Nigeria: Pre- and Post-COVID incidence

The occurrence of COVID-19 pandemic that broke into the world in early 2020 was envisaged to affect existing diseases. This study evaluated the extent to which COVID-19 pandemic has affected malaria cases among the staff and students of Ekiti State University (EKSU), Ado-Ekiti, Nigeria. Clinical data involving malaria cases of outpatient visits to EKSU Health Centre during 2019 and 2021 were collected from the Record Department of the Health Centre for statistical analysis. Data were analyzed with SPSS version 20 with probability value of < 0.05 as significant. Results showed that 1,246 people visited EKSU Health Centre as outpatients in 2019 and 1,243 in 2021. Only 642 (51.5%) had malaria in 2019 while 604 (48.6%) had malaria in 2021 with no significant difference (P= 0.143) in both years. The highest malaria cases was observed in April (57.7%) in 2019 and December (55.6%) in 2021. There was no significant difference in the malaria cases across the different months of both years. Malaria cases was higher in males than females in both years but without significant difference (P= 0.429). COVID-19 appears not to have effect on malaria cases in Ekiti State University Community Ado-Ekiti and possibly in other Nigerian universities.

Potential of Establishing Industrial Hemp Value Chains in Northern Australia

Globally, industrial hemp offers consumers with over 25,000 value-added products that are valued at approximately US$4.2 billion of current market value and likely to surpass US$26.6 billion by 2025. In Northern Australia, the industrial hemp sector is at infancy stages of development. Given the suitability of certain Northern Australia’s geographical zones in terms of soil, water, and climate, a study was conducted to identify potential industrial hemp value chains. Probable value chains were developed by characterizing the production to market segments of the supply chains to determine the return on investment and analyzing the capacity of the stakeholders in terms of communication and relationships. Consequently, the strengths, weaknesses, opportunities and threats (SWOT) of the developed value chains were analyzed. This study collected data from three complementary sources that included review of the literature, results of variety trials evaluation conducted in Northern Australia, and survey of hemp industry stakeholders. Results suggested that Northern Australia offers conducive growing conditions for hemp that allows for the development of three value chains including seed, fiber and silage. The research recommended ongoing investment in the industry through engagement of public and private sector while focusing on further establishment of the industry.

Pengaruh PMA, PMDN, Ekspor, Belanja Pendidikan dan Belanja Kesehatan terhadap Pertumbuhan Ekonomi Di Provinsi dalam Pulau Sumatera

This was a quantitative study. The data were secondary data from six Provinces in Sumatera in the period 2010-2021 obtained from the BPS and DJPK. The data were panel data analysis using the fixed effect regression model processed by Eviews 12. The results of the study showed that: 1) foreign investment have significant positive effect on economic growth in Sumatera with a probability value of 0.0035. 2) domestic investment have significant positive effect on economic growth in Sumatera with a probability value of 0.0001. 3) Exports have no significant effect on economic growth on the island of Sumatra with a probability value of 0.08019. 4) Education spending has a positive and significant influence on economic growth on the island of Sumatra with a probability value of 0.0006. 5) Health expenditure has a positive and significant influence on economic growth on the island of Sumatra with a probability value of 0.0091. The R-squared value in this study is 0.986931, this means that the contribution of all independent variables in explaining the variable is 98.69%.

Augmented reality integrated education game using problem-based learning model to improve critical thinking skills

Limited students' critical thinking skills in learning can be strengthened by using augmented reality technology applications. The main objective of this research is to analyze the problem-based learning model with integrated augmented reality educational games in improving students' critical thinking abilities. This quasi-experimental research used a nonequivalent control group design. The research sample consisted of 60 students from SD Muhammadiyah 09 Surabaya who were selected using purposive sampling. Data was collected by observing the implementation of learning and testing students' critical thinking levels. The data obtained in the research was processed statistically based on research obtained with a significant value of 0.000 < 0.05, confirming that Ho was rejected and H1 was accepted. Thus, the probability value is 0.000 < 0.05, so all coefficients have meaning. Applying the PBL model with integrated augmented reality educational games on critical thinking skills has a significant effect. From the ANOVA test or F-test, Fcount was 45,348 with a significance level of 0.000. This probability is smaller than 0.05, so the learning model to predict the level of participation in learning with a problem-based learning model through educational games integrated with augmented reality influences students' critical thinking skills.

On probabilistic mean value theorem and covariance identities

In this paper, further results for a probabilistic analogue of the mean value theorem proposed by Di Crescenzo (1999) are studied, focused on Normal and Poisson distributions. By applying this theorem for two normally distributed random variables with the same variance, a new symmetric unimodal distribution is obtained, and statistical measures of it are provided. By introducing a family of real valued continuous distributions, covariance identities are also investigated. Covariance identities are also explored for a Poisson distributed random variable. Some illustrative examples are finally given.

Prevalence and Variation of Medical Comorbidities in Oral Surgery Patients: A Retrospective Study at Jazan University.

BACKGROUND An aged population is susceptible to chronic diseases, which impacts oral surgery treatment procedures. This retrospective study aimed to evaluate the incidence of medical comorbidities in 640 oral surgery patients treated at the College of Dentistry, Jazan University. MATERIAL AND METHODS This single-center observational study investigated medical records of outpatients who visited Jazan University Dental College Hospital in a 1-year period (2018-2019). Patients’ clinical and radiographic archives were screened to obtain relevant data. Categorical and continuous variables were expressed in terms of frequency and mean values, respectively. Differences in variables were statistically analyzed using the chi-square goodness of fit and proportional test, with a probability value P≤0.05 considered significant. RESULTS Analysis of 640 patient records included records of 300 men and 340 women who underwent oral surgery, of whom 176 patients (27.5%), including 97 men and 79 women, had medical comorbidities. The most common comorbidities were endocrine disease (7.03%), cardiovascular disease (6.71%), respiratory disease (4.53%), and hematological disorders (3.43%). Individual diseases that showed higher prevalence were diabetes mellitus (4.68%), hypertension (3.43%), bronchial asthma (2.65%), and anemia (1.4%). Differences by sex were observed in many individual disorders. CONCLUSIONS Outpatients in oral surgery clinics presented a significant variance in the incidence of medical comorbidities, among which diabetes and hypertension were most common. A proper case history is the best preventive measure that helps a surgeon avert medical emergencies and post-surgical complications.

The Influence of TAM Variables and Financial Literacy on QRIS Payment Decisions with Interest as an Intervening Variable (Study on Semarang State Polytechnic Students)

The rapid evolution of digital technology, especially in the digital economy and payment sector, has driven the widespread adoption of digital payment services utilizing QR Codes. The Quick Response Code Indonesian Standard (QRIS), introduced by Bank Indonesia and the Indonesian Payment System Association (ASPI) on August 17, 2019, serves as the national QR code standard, facilitating QR code-based payments across Indonesia. QRIS presently allows the acceptance of payment applications, whether from banks or non-banks, at various establishments. This study, involving 370 students from a population of 6,128, utilizes the Structural Equation Model (SEM) for analysis, demonstrating a robust fit with a GFI value surpassing 0.913. The findings reveal that TAM variables—perceived ease of use, perceived usefulness, perceived enjoyment, and financial literacy—significantly influence decision of QRIS payment through interest in adopting digital payments as an intervening variable, supported by probability values below 5%