The heating value of natural gas is used to determine the quality of the gas sample, hence accurate prediction of heating value helps in controlling the issue of underbilling and overbilling between a gas aggregator and an off-taker. Moreover, the heating value of natural gas is not a fixed value and the accuracy of it in real-time is essential. This study was focused on the prediction of the higher heating value (HHV) of natural gas based on percentage gas compositions obtained from Ghana’s offshore oil fields using Artificial Neural Networks (ANN), Adaptive Boost (AdaBoost), Extreme Gradient Boost (XGBoost), Linear Regression (LR). These algorithms were modelled to determine the best predictive model using 2021 sample data on gas specifications. Eighty percent (80%) of the data was used for training and the remaining 20% was used for testing. The performance of each algorithm was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), R2 and Adjusted R2. XGBoost performed better than all the other predictive models with an R2 and adjusted R2 of 91.18% and 90.93% respectively and RMSE, MAE, and MAPE of 1.7302, 0.5393 and 0.57% respectively. The incorporation of this method provides a diverse approach to the analysis of the pipeline dynamic results of the heating value of natural gas.

The gross calorific value (GCV) or heating value of a sample of fuel is one of the important properties which defines the energy of the fuel. Many researchers have proposed empirical formulas for estimating GCV value of coal. There are some known methods like Bomb Calorimeter for determining the GCV in the laboratory. But these methods are cumbersome, costly and time consuming. In this paper, multivariate regression analysis and Co-active neuro-fuzzy inference system (CANFIS) backed by genetic algorithm technique is used for the prediction of GCV, taking all the major constituents of the proximate and ultimate analyses properties as input parameters and the suitability of one technique over the other has been proposed based on the results.Correlations have been developed using multivariate regression analysis that are simple to use based on the proximate and ultimate analysis of data sets from 25 different states of USA because a very through study has been done and the data available is less variable. Also, CANFIS backed by genetic algorithm model is designed to predict the GCV of 4540 US coal samples from the abovementioned datasets. Optimization of the network architecture is done using a systematic approach (genetic algorithm). The network was trained with 4371, cross validation with 100, predicted with rest 69 datasets and the predicted results were compared with the observed values.The mean average percentage error in prediction is found to be negligible (0.2913%) and the generalization capability of the model was established to be excellent. A useful concept of sensitivity analysis is adopted to set the hierarchy of influence of input factors. The results of the present investigation provide functional and vital information for prediction of GCV of any type of coal in USA.

Introduction: Academic faculty members need to emphasize ethical principles in order to improve higher education, with the understanding of this importance, the current research was conducted with the aim of designing the ethical model of academic faculty members in Iran's higher education. Material & Methods: This research is a type of qualitative study that uses foundational data theory. The participants, including experts and faculty members of the country's public universities, who were responsible for the promotion of academic members, were selected as key informants through a targeted sampling method of 45 people. Data were collected through semi-structured interviews. The reliability and validity of the data were obtained from the two methods of reviewing the participants and recoding by experts. Data were analyzed by open, central and selective coding. Results: The results showed that the moral model of faculty members in Iran's higher education is explained in 10 main categories and 27 subcategories. Major and core categories in the form of 6 dimensions of causal conditions including (individual factors, organizational factors), core (cultural-educational, educational ethics, research ethics, scientific-executive), background conditions (higher education policies, moral activism), intervening conditions (environmental factors), strategies (micro level-university, macro level-higher education) and consequences (individual and organizational) were elevated to a higher abstract level and finally the research paradigm model was presented. Conclusion: The regulations for the promotion of academic staff members in Iran require a detailed revision of the content with an ethical and qualitative approach in order to make the indicators of the promotion regulations efficient and effective.

An analysis of the experimental characterization of the three agricultural residues redgram stalk, soyabean stalk, and chilli stalk (biomass) was carried out and the higher heating values (HHV) were determined using the available correlations from the literature. The selected agricultural residues proximate analysis results show moisture about 4.2 to 7.4%, the volatile matter about 79.3 to 85.8%, fixed carbon about 4 to 8.94%, and ash about 2.5 to 5.5%. The ultimate analysis results present elemental compositions such as carbon about 46 to 49%, hydrogen about 5%, oxygen about 30%, and the nitrogen about 3.1 to 3.7% with very low sulfur content. The HHV of agricultural residues varies from 14MJ kg-1 to 19MJ kg-1. The design of the downdraft gasifier to accommodate agricultural residues was carried out taking into account the characteristics of the agricultural residues and the specifications of the internal combustion (IC) engine. The characteristics of the agricultural residues depict that the three agricultural residues are suitable for gasification and can be used in a single gasifier.

Background and Objective: The increasing accumulation of spent coffee grounds (SCG) has raised serious environmental concerns. This study aimed to evaluate the efficiency of the hydrothermal carbonization process in converting SCG into a valuable solid fuel. . Materials and Methods: An experimental study was conducted using the design of experiments (DOE) approach and response surface methodology (RSM). The effects of key independent variables—including temperature (180–290 °C), reaction time (30–90 min), and liquid-to-solid ratio (L: S, 1: 1–15: 1)—on the properties of the produced hydrochar were investigated. A total of 20 experiments were carried out, and physicochemical analyses were performed on both the hydrochar and the process water. Results: The results indicated that the quadratic model demonstrated strong predictive capability for hydrochar yield (HY) and higher heating value (HHV) (R² > 0. 98). Analysis of variance showed that all three independent variables had significant effects on HY and HHV. The produced hydrochar showed HHV of 17. 9–28. 5 MJ/kg and HY of 17. 5–77. 2%. Response surface methodology identified 235 °C, 180 min, and L: S 4: 1 as optimal for desirable HY and HHV. Optimization indicated 229 °C, 160 min, and L: S 4: 1 yielded hydrochar with 27. 8 MJ/kg HHV, 67. 9% HY, with 0. 891 desirability. CHNSO analysis showed a decrease in H/C and O/C ratios and an increase in surface area from 2. 4 to 12. 6 m²/g. Conclusion: Given the favorable HHV of the produced hydrochar, it can be concluded that the proposed process is an effective method for converting biomass into solid fuel.

A B S T R A C T Temperature is one of the climate elements that has fluctuated a lot over time. When these fluctuations increase and decrease more than normal and are placed in the upper and lower regions of the statistical distribution, if continued, it can lead to the creation of heating and cooling waves. The purpose of this study is to analyze the temporal and spatial changes in heating and cooling waves in Iran during a period of 50 years. For this purpose, the temperature of 663 synoptic stations from 1962 to 2004 was obtained from the Esfazari database. Then, in order to complete this database, the daily temperature from 2004 to 2011 was obtained from the Meteorological Organization of the country and added to the aforementioned database. In order to perform calculations and draw maps, Matlab, grads and Surfer software have been used. The results of this study showed that the index of cooling waves and heating waves, while having a direct effect on each other, had an increasing trend in most of the area of Iran. The statistical distribution of the index of cooling waves is more heterogeneous than that of the index of heating waves. So that the spatial variation coefficient for cold waves is 84.22%. Also, the index of cooling waves has more spatial variability. The highest common diffraction of the index of heating and cooling waves has been seen in the northwest, east and along the Zagros mountains. Analysis of the indexes trends show that heat waves have intensified in 65.8% of Iran and the intensity of cold waves has decreased in 48.5% of Iran Extended Abstract Introduction Temperature is one of the major climatic variables, which it has a direct impact on different aspects of human life. It plays an essential role in the growth of crops and is considered a key driver of the biological system(Reicosky et al, 1988). It is associated with several types of extremes, for example, heat and cold waves which caused human societies maximum damage. Past occurrences of heat waves hitherto had significant impacts on several aspects of society. Have increased Mortality and morbidity. Ecosystems can be affected, as well as increased pressure on infrastructures that support society, such as water, transportation, and energy(Dewce, 2016). The long-term change of extreme temperatures has a key role in climatic change. The form of statistical distribution and the variability of mean values and also extreme event indicate a change in the region. It can be a small relative change in the mean as a result of a large change in the probability of extreme occurrence. Also, the variation in temperature data variance is significantly more important than the mean, for assessing the extreme occurrence of climate(Toreti and Desiato, 2008). The average surface temperature has increased the world between 0.56 and 0.92 ° C over the past 100 years(IPCC, 2007). Meanwhile, it was in the Middle East, the average daily temperature increased by 0.4-0.5 ° C in decades(Kostopoulou et al, 2014; Tanarhte et al, 2012). Considering that not many studies have been done in the field of spatio-temporal Variations of the heating and cooling waves thresholds in Iran, in this study, the spatio-temporal Variations of the heating and cooling waves thresholds in Iran during 50 years were examined and analyzed.   Methodology The daily temperature from the beginning of the year 21/03/1967 to 19/05/2005 was obtained from the Esfazari database prepared by Dr. Masoudian at the University of Isfahan. In order to increase the time resolution of the mentioned database, the daily temperature of observations from 05/21/2005 to 05/12/2012 has been added to the mentioned database using the same method, and the exact spatial resolution (15 x 15 km) is used as a database. Threshold indices of heating waves are the average numbers between the 95th and 99th percentiles, that is, the extreme hot threshold to the limit of excessively extreme hot. For extreme cool, from the 5th percentile down to zero is used. Of course, a condition was added to these thresholds, which is that these thresholds must be repeated two days in a row. These thresholds were extracted for each day in the 50 years of the study period and used as the original database. In order to analyze the relationship between cooling and heating waves, Pearson's correlation coefficient was used and regression was used to analyze the trend.   Results and discussion The average of cold waves was 5.26 ° C and for the heat waves is 30.20° C. Generally, if the temperature is upper or lower than this threshold, it is considered as hot or cold temperatures. A comparison of the median, mode, and average of cold waves with heat waves shows that the distribution is more heterogeneous for cold waves and its CV is 84.22%. In southern Iran, the average threshold heat waves are higher. This situation can be caused by the effects of subtropical high-pressure radiation, low latitude, and proximity to the sea. Though the threshold is higher in these areas, fewer fluctuations and changes are seen in the area. Heights moderate the temperature so they pose a minimum threshold for heat waves i.e. an iso-threshold of 25 ° C is consistent along the Zagros mountain chains, but in the west and east of Zagros Mountains, the threshold of heat waves is increased. Heat waves have increased in most areas of the country. So nearly 85 percent of the Iran has been an increasing trend, of which 65.8 percent is statistically significant at the 95% confidence level. Still, more areas of the country (60 percent) have a trend between 0.00828 and 0.00161. As can be seen, only 15% of the land area (including the southwest and northwest of the Country) had decreased heat waves. Cold waves, in most parts of the country, have a Positive Trend. However, about 25 percent of the study area's cold waves have a negative trend. they are located in areas higher than Latitude 30°. The largest decline of the wave's trend along the country is highlands. Nowadays, most of the country, has a trend between 0.01494 and 0.00828 ° C, respectively. Conclusion Common changes and effects of heat and cold waves had a direct relationship in many parts of the country. It is remarkable common variance in the East reached 55 percent, according to statistical significance. In some areas of the northwest and southwest, which have been impressive heights, the common variance is 40 percent. This common variance in mountains area has been high values. Investigation of heat waves trend shows that 65.8% of Iran significant positive trend and 7.1% significant negative trend. Also, the cold waves trend has indicated a 48.5% significant positive trend and a 10.8% significant negative trend. Climate change and global warming have changed the frequency and severity of temperature extremes. The present study, by examining the number of warm waves, concluded that the warm waves have increased in magnitude in 65.8% of the Iran zone. Also, the study of the cold waves trend showed that 48.5 percent of Iran had a positive trend, which means that the amount of temperature in the cold waves increased In other words, the severity of the cold has been reduced And only 10.8 percent of Iran had a negative cold wave trend And it shows the intensity of these waves is reduced.   Funding There is no funding support.   Authors’ Contribution The authors contributed equally to the conceptualization and writing of the article. All of the authors approthe contenttent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest The authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Hydrothermal carbonization is a thermal technique that offers numerous environmental benefits, particularly in managing solid waste streams by decomposing the raw materials of solid wastes and converting them into the renewable source of energy known as hydro-char. This study evaluates the heating value of hydro-char produced through the hydrothermal carbonization of cigarette butts, taking into account influential factors such as time, temperature, and pressure, as well as its benefits and economic implications, using a novel approach involving simulations aimed at reducing the number of required tests, saving time, and cutting costs.The range of 150 to 350 oC for temperature and 30 to 240 minutes for reaction time were considered and resulted in a thermal value range of 15.94 to 23.12 MJ/Kg for hydro-char, which makes its heat value greater than lignite coal and within the range of bituminous coal. The findings also indicated that temperature and time have a direct impact on the heat value, with time being the more influential factor, although high temperatures can expedite the reaction rate and should not be disregarded. Finally, the economic analysis of the project was conducted using the NPV method, which demonstrated that the viability of this method depends on the cost of coal, making it a promising alternative for accessing new and cost-effective fuel resources while considering environmental benefits. Besides, this study highlights the potential of hydrothermal carbonization as a viable and advantageous method for producing fuel resources from biomass and organic waste, and provides quantitative and comparable evidence of the applicability and benefits of the proposed hydrothermal carbonization methodology in comparison to conventional methods.