In the past few decades, minimum and maximum temperatures have shown different behaviors. The difference between these two variables, known as the diurnal temperature range (DTR), is one way to detect climate change in a region. Therefore, in this study, the DTR trend in West Azerbaijan province was examined in order to show the spatial and temporal of these changes in the statistical period (1992-2021) on annual and seasonal scales. For this purpose, the Mann-Kendall test was used to examine the trend, and the Sen's Slope Estimator was used to examine the intensity of the changes. The results of the spatial distribution of DTR changes in the studied period showed that the range of diurnal temperature changes in West Azerbaijan province is between 8 to 14.3 0C. The trend of seasonal changes also indicates an increase in the diurnal temperature range in most regions of the province except for the Piranshahr and Khoy stations, especially in the summer and autumn seasons. According to the results, the highest rate of trend and changes in terms of time was observed in the summer season and the lowest in the autumn season. In terms of temporal, the highest intensity of changes is related to the southeastern and central regions of the province, and the lowest intensity of changes is related to the southwestern and northwestern regions of the province. The detection of DTR changes on an annual basis also showed that changes have become significant in all regions of the province except for Mako. These significant changes also have an increasing trend in other regions except for the Piranshahr and Khoy stations, which are decreasing. The annual change intensity rate is also between -0.01- 0.031 0C per year in the study period.

This research was conducted with the aim of investigating the day and night temperatures in Iran. For this purpose, the minimum and maximum temperatures during 40 years (1981-2020) were examined using the AgERA5 dataset. Then, the diurnal temperature range (DTR) was calculated. In order to evaluate the performance of the AgERA5 dataset, the data from 56 meteorological stations and RMSE and R2 metrics were used, and the Theil-Sen test was used to analyze the average trend. The results of the evaluation of the minimum and maximum temperatures showed that the AgERA5 dataset has high accuracy for temperature estimation. The trend showed that the monthly trend of minimum and maximum temperatures in Iran is increasing. The increasing trend of temperature over time is not constant and its rate varies in different months. However, the increasing trend of temperature during different months of the year is consistent for the two variables of minimum temperature and maximum temperature. In all months, the maximum temperature increase is observed in winter and March. The DTR index in Iran is a minimum of 0.48 and a maximum of 16.6 °C, which occurs in December and July, respectively. The maximum DTR occurs in the interior dry regions and the minimum occurs in northern and northwestern Iran. The maximum increasing trend of minimum and maximum temperatures is in March, which increases by 0.8 oC/decade and 1.2 oC/decade, respectively. In contrast to the maximum temperature, there is a decreasing trend of the minimum and maximum minimum temperature in November, which decreases by -0.1 oC/decade and -0.2 oC/decade, respectively.

Background: The aim of this study was to determine the monthly DTR mass load of amphetamine-type compounds in Poland as well as an investigation of cyclical behaviour by using time series analysis and especially trends analysis.Methods: Amphetamine, methamphetamine and MDMA (ecstasy) were detected in wastewater samples collected from the main Wastewater Treatment Plant in the city of Poznan using liquid chromatography/tandem mass spectrometry (LC-MS-MS). Back-calculations used in the sewage epidemiology approach were applied to estimate the DTR mass load level of the drugs analyzed. Trends analysis was performed by fitting the data to a simple linear regression and then by using smoothing by means of a moving average (Mat lab 2013a). Trend analysis displays a steady tendency of increase or decrease throughout time series. When we plot the observation against time, we may notice that a straight line can describe the increase or decrease in the series as time goes on. Simple linear regression and method of last squares to estimate parameters of a straight-line model were used. Additionally, a lagged plot (autocorrelation plot) was used to investigate an appearance of correlation between amphetamines throughout time.Results: Trends analysis showed the slight increase in consumption of amphetamine and decreasing trend in case of ecstasy and methamphetamine within the investigated period. There is also visible, strong correlation between ecstasy and methamphetamine consumption which cannot be stated in case of amphetamine.Conclusion: Trends analysis is a very useful tool to analyse the increasing or decreasing tendency in consumption of illicit drugs based on the DTR mass load data.

Climate is an important and determinning factor affecting many agricultural products. Diurnal temperature range (DTR) is an effective parameter in assessing climate change impacts on environment in a region. This parameter is determined by the difference between minimum and maximum air temperatures. In this study, changes in the daily DTR collected from 11 synoptic stations were analyzed. The selected sites cover 50 years of daily observations from 1956 to 2005, specifying suitable geographical distribution throughout the country. Kolmogrov, Smirnov test was used to check the normal distribution and Run, test to control the quality of the temperature data. Trend investigation of DTR data was carried out by using Mann, Kendall test (MK) and linear regression method (LR) at 95 percent confidence level for monthly and annual time scales. About 18 percent of the study sites showed no significant DTR trend, but the rest of the sites (82%) revealed significant negative (decreasing) trends for the observed diurnal temperature difference time series. However, few months experienced no DTR trend in the selected sites. In about 95.5 percent of the studies cases, the existence of trend and the decreasing DTR trends obtained by MK test were also confirmed by the LR method. In this research, the minimum and maximum slopes were determined by the LR method. The analysis of the measured temperature data showed an average decreasing in DTR slope about, 0.445oC per decade for the selected sites. According to the results, the decreasing DTR trends in northern and central sites were more significant than those in the southern regions. Detailed evaluation and substantiation.

Temperature is one of the important thermodynamic meteorological elements the change of which can cause many physical, chemical and environmental variations. The history of measuring temperature is relatively long compared to that of other elements in meteorology. In spite of some evidence and experts" belief about the global warming in the years 1947 and 1948, the idea of stationary climatic condition persisted till 1970s.Many research done at national, regional, and global levels indicate an increase in temperature in many parts of the world. In other words they prove an increase in the mean global temperature. Although there is a marked increase in maximum temperature in many parts of the world owing to its lower increase rate, compared to that of minimum temperature, DTR has decreased. The results obtained for maximum, minimum, and mean temperatures are quite different from one another. Positive trend for minimum temperature in majority of Iranian synoptic stations especially in those located in cities with high urban growth rate, are remarkable. For instance, it is strong in Esfahan. Moreover, we found a jump in annual temperature series in the 1970s that is consistent with the jump in many places in the world. DTR in large cities like Esfahan, Shiraz, and Tehran has decreased significantly. In this regard, a 4°C decrease in Esfahan can be noticed. In addition to some exceptions, quality and quantity of trends are also discussed.

Background: The diurnal temperature range (DTR), representing the difference between daily maximum temperature (Tmax) and minimum temperature (Tmin), is a vital climatic indicator with significant environmental and public health implications. This study examined long-term trends and seasonal patterns of DTR in five cities in Khuzestan Province, Iran (Abadan, Ahvaz, Aghajari, Masjed Soleiman, and Safi Abad) from 1990 to 2022.   Materials and Methods: Meteorological data, including Tmax and Tmin, were used to calculate daily DTRs and annual averages. Temporal trends were assessed using linear regression models, while seasonal decomposition analysis identified trend, seasonal, and residual components. Visualization techniques, such as line plots and decomposition graphs, illustrated the findings. Results: The results indicated statistically significant increasing trends in DTR across all cities, with annual increases ranging from 0.0567 to 0.1347 units. Seasonal patterns showed consistent summer peaks and winter troughs, with notable long-term trends and climatic anomalies detected in residual components. These trends mirror global patterns of increasing variability between daytime and nighttime temperatures. Conclusion: The rising DTR, particularly in Abadan and Aghajari, elevates heat stress and public health risks. Ahvaz and Safi Abad also exhibited significant trends, highlighting the need for targeted policy measures. Given the association of high DTR with increased cardiovascular and respiratory diseases, integrating DTR metrics into health action plans is critical, especially for vulnerable populations. In conclusion, DTR serves as a crucial marker of climatic and health risks, reinforcing the urgency of climate adaptation strategies in Khuzestan Province to protect vulnerable groups.

Background: Bloodstream infections (BSIs) caused by Pseudomonas aeruginosa have high mortality rates and pose a significant threat to healthcare settings. Objectives: We aimed to investigate the clinical risk factors related to mortality and the development of P. aeruginosa with difficult-to-treat resistance (DTR-PA) BSI in the intensive care unit. Methods: This was a retrospective, single-center study that included patients with P. aeruginosa BSI who were hospitalized between 2020 and 2022. The risk factors affecting 30-day mortality and the development of DTR-PA were investigated using both univariate and multivariate analyses. Results: A total of 140 patients were analyzed. The mean age was (66 ± 17.5) years, and 48% of the patients were male. Previous meropenem use was an independent risk factor for DTR-PA BSI (odds ratio, 2.68; 95% CI, 1.24 to 5.80; P = 0.012). Multivariate analysis demonstrated that the requirement for inotropic support was an independent risk factor for 30-day mortality [hazard ratio, 2.50; 95% confidence interval (CI), 1.33 to 4.68; P = 0.004]. Conclusions: Prior meropenem use was an independent risk factor for DTR-PA development. Strict policies for Carbapenem use and infection control procedures are essential to combat infections caused by DTR-PA.

Ensemble modelling is expanding in several areas of engineering, especially different aspects of water engineering. Accurate estimation of saffron water requirement (SWR), an essential strategic production of the agriculture sector, is a crucial and influencing act in local water planning of this region. Hence, this study aimed to check the applicability of ensemble modelling in enhancing SWR at Birjand, Southern Khorasan, Iran. The actual water requirement of saffron was recorded in the field lysimetric laboratory at the University of Birjand. The simulation of water requirement was conducted utilizing Decision Tree Regression (DTR) with input climate features. Additionally, Boosting and Bagging methods were employed to establish and enhance the ensemble process of soil water requirement (SWR) simulations. To track the effectiveness of any method, some comparative tests were designed, such as statistical criteria (RMSE and MAE) detection, Violin plot analysis, over/underestimation, times series comparison, and error improvement test. Results indicated that although the acceptable performance of DTR in simulating SWR, the probable improvement was potentially felt. Derived results confirmed that supervised ensemble modelling (Boosting) could enhance the accuracy of DTR by more than 30 percent (reducing absolute error from 36 mm to 23.65 mm), resulting in declining RMSE from 0.44 mm to 0.07 mm. Further, different experiment outcomes revealed that the Boosting algorithm quality is more appealing than DTR and Bagging outputs.

For a given connected graph G = (V, E), a set Dtr ÍV(G) is a total restrained dominating set if it is a dominating set and both (Dtr) and (V(G)- Dtr) do not contain isolated vertices. The cardinality of the minimum total restrained dominating set in G is the total restrained domination number and is denoted by γtr(G). In this paper, we continue the study of total restrained domination number of graphs. We first give some results on total restrained domination number of graphs. And then, we characterize all graphs G of order n for which (1) γtr(G)=n, (2) γ (G)=1 and γtr(G)=3, and (3) γtr(G)=2. Furthermore, we give some bounds on total restrained domination number of graphs with diameter 3. Finally, we present some bounds for total restrained domination number of some planar graphs with diameter 2 and g-set of cardinality 2.