The major objective of this research paper is to assess the management effectiveness of Sheikh Badin National Park District Dera Ismail Khan Khyber Pakhtunkhwa, Pakistan with respect to tourist’s satisfaction. A sample size of 389 respondents (local community, wildlife staff, tourists) were selected through simple random sampling to conclude respondents’ attitude towards phenomenon investigated through three-level Likert scale as a measurement tool. Association between a dependent variable (management effectiveness) was assessed on the independent variables (tourist satisfaction) through a chi-square test. Association of management effectiveness was highly significant with tourists satisfaction from promos of park (p = 0.000), access to information (p = 0.000), roads network (p = 0.000), residential facilities (p = 0.000), trained guides (p = 0.000), safety from crimes and criminals (p = 0.000), provision of health and security services (p = 0.000), overall satisfaction of tourists (p = 0.000), recommendation of SBNP to other tourists (p = 0.000) and revisit intentions of tourists (p = 0.000). Improvement in security measures, better advertisement and improvement in park infrastructure were major recommendations considering the study.

Objective: To determine the presence of bacteria by means of microbiological analysis on the surfaces contacted by the operator during the taking and processing of intraoral radiographs at different times of the day in the Oral Radiology Service of the UPCH. Materials and methods: Nine surfaces of the oral radiology service were sampled. The samples were taken at two times by the same investigator; at the beginning and the end of the activities in the service, the surfaces were swabbed with Trypticase Soy Broth (TSB). The samples were inoculated and incubated in three culture media (Plate Count Agar, Lamb’s Blood Agar and Cetrimide Agar). Then the respective Colony Forming Unit (CFU) count was performed and Gram staining was also performed. Results: A high concentration of bacteria (4180 CFU/mL) and fungi was found in the oral radiology service. Gram-positive cocci were the most frequently found microorganisms and gram-negative bacilli were less frequently found. Conclusions: There is a high contamination of bacteria in the oral radiology service. When the activities are completed, the number of bacteria decreases, but the variety of bacteria increases.

In order to promote the application of noise map in high-speed railway noise management, the high-speed railway noise map drawing technology based on the combination of noise prediction model and geographic information system (GIS) is studied. Firstly, according to the distribution characteristics of noise sources and line structure characteristics of high-speed railway, the prediction model of multi equivalent sound sources and the calculation method of sound barrier insertion loss of high-speed railway are optimized; secondly, a three-dimensional geographic information model of a high-speed railway is built in GIS software, and the railway noise prediction technology based on the model is developed again; then, the noise of discrete nodes is calculated, and the continuous noise distribution map is drawn by spatial interpolation. The research results show that the comparison error between the noise map of a high-speed railway drawn by this technology and the measured results is less than 1 dB (A), which verifies the accuracy and practicality of the high-speed railway noise map, and can be used as a reference for the railway noise management department to formulate noise control countermeasures.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.