Analysis Of Variables Research Articles

MediVizor: Visual Mediation Analysis of Nominal Variables.

Mediation analysis is crucial for diagnosing indirect causal relations in many scientific fields. However, mediation analysis of nominal variables requires examining and comparing multiple total effects and their corresponding direct/indirect causal effects derived from mediation models. This process is tedious and challenging to achieve with classical analysis tools such as Excel tables. In this study, we worked closely with experts from two scientific domains to design MediVizor, a visualization system that enables experts to conduct visual mediation analysis of nominal variables. The visualization design allows users to browse and compare multiple total effects together with the direct/indirect effects that compose them. The design also allows users to examine to what extent the positive and negative direct/indirect effects contribute to and reduce the total effects, respectively. We conducted two case studies separately with the experts from the two domains, sports and communication science, and a user study with common users to evaluate the system and design. The positive feedback from experts and common users demonstrates the effectiveness and generalizability of the system.

FACTORS AFFECTING NURSES' SELF-EFFICACY IN PERFORMING TRIAGE IN THE EMERGENCY DEPARTMENT OF THE HOSPITAL OF FAITH IN BALIKPAPAN

Self efficacy is related to the belief that a person has the ability to be able to perform the expected action. Triage is the first aid action in the emergency room which aims to reduce morbidity and mortality for all patients who enter the emergency room. Nurses as a profession have a body of knowledge, namely nursing science obtained from formal education. This study is to analyse the factors that influence nurses' self-efficacy in performing triage in emergency room of RSUD Beriman Balikpapan. This research design uses descriptive correlation with cross sectional approach. Sampling technique is total sampling where all research population is used as research sample as many as 17 respondents. Univariate analysis of each research variable. Bivariate analysis uses chi square statistical test. The result of bivariate test analysis shows that self experience (p = 0.901), experience of others (p = 0.585), verbal persuasion (p = 0.027), physiological evaluation (p = 0.046). In this study, the factors of self-experience and experience of others showed the results did not have a significant relationship to the nurse's self-efficacy in carrying out Triage in the Emergency Room, while the factors of verbal persuasion and physiological evaluation showed the results there was a significant relationship to the nurse's self-efficacy in carrying out Triage in the Emergency Room.

STOPP-START Criteria Used to Identify the Elderly Population Prone to Potentially Inadequate Prescribing in a Colombian Cohort.

Elderly people have multiple comorbidities that often require treatment with multiple medications. Having strategies to lessen the risks associated with pharmacological interactions and potentially inadequate prescribing (PIP) is of major importance. The STOPP- START criteria are useful in identifying PIP along with other tools, such as LASA (look alike/sound alike) drugs and high-risk medications (HRM). We aimed to clinically and sociodemographically characterize the population with PIP according to the STOPP-START criteria in hospitalized elderly patients over 6 months in a third-level hospital in Colombia, South America. We also aimed to calculate the prevalence of PIP, LASA drugs and HRM and to identify other problems related with medication. Finally, we proposed an algorithm for the identification of PIP in this population. This was a descriptive, cross-sectional study in hospitalized patients older than 60 years during the first semester of 2021 to identify PIP according to STOPP- START criteria. An analysis of clinical and sociodemographic variables was conducted, as well as the construction of an algorithm to identify PIP in the elderly in a semiautomated way. Data were collected and analyzed using the software SPSS 2021, using descriptive statistics and measures of central tendency. The prevalence of PIP in the study population was 25%. Furthermore, 60% of patients had one problem related to medication, and 27% used at least one LASA drug or HRM. This study allows one to characterize, for the first time, the Colombian population prone to PIP, as well as the construction of an algorithm that identifies PIP in a semiautomated way.

SERUM 25 (OH) VITAMIN D AND CALCIUM LEVELS AND ADVERSE MATERNAL AND PERINATAL OUTCOMES IN PREGNANCY INDUCED HYPERTENSION

Objectives: Incidence of hypertensive disorders in pregnancy is about 5–10% of all pregnancies [1]. Pre-eclampsia alone or superimposed on chronic hypertension is the most threatening. This study is done to evaluate the levels of serum 25 (OH) Vitamin D and Calcium in normal antenatal patients and patients with pregnancy-induced hypertension and their effects on perinatal and maternal outcome. Hence, that timely intervention can prevent adverse perinatal and maternal outcomes. Methods: The present prospective observational study was done in the Department of Obstetrics and Gynecology, Government Medical College and Rajindra Hospital, Patiala, Punjab, India from May 2018 to April 2019. The study was conducted on 80 antenatal patients. Patients were divided into two groups with 40 patients in each group. Group I included patients with pregnancy-induced hypertension and Group II included normal antenatal patients. Serum levels of calcium and 25 (OH) Vitamin D were evaluated in both groups. Adverse perinatal and maternal outcomes were assessed in relation to the serum levels of calcium and 25 (OH) Vitamin D in patients with pregnancy-induced hypertension and normal antenatal patients. Categorical variables were analyzed by Chi-square test and Fisher’s exact test. The analysis of continuous variable was done by ANOVA. The data were analyzed using SPSS version 22 and Microsoft Excel. p≤0.05 is taken as statistically significant. Results: The mean value of serum Vitamin D level in Group I was 22.30±6.11 ng/ml and 36.68±9.34 ng/ml in Group II giving p=0.016 which was highly significant. In Group I, mean calcium levels were 8.58±0.63 mg/dl and 9.27±0.40 mg/dl in Group II giving p=0.018 which was highly significant. The Pearson’s correlation coefficient was −0.753 for serum Vitamin D and systolic blood pressure (BP) and the same for serum Vitamin D and diastolic BP with p=0.001 which was highly significant. The Pearson correlation coefficient was −0.537, −0.514 for serum calcium and systolic BP and serum calcium and diastolic BP, respectively, giving p=0.001. Conclusion: Serum levels of 25 (OH) Vitamin D and calcium have a significant relationship with pregnancy-induced hypertension. Low levels of calcium and 25 (OH) Vitamin D cause an increased risk of pregnancy-induced hypertension and supplementation of these reduces the incidence of pregnancy-induced hypertension. Hence, their supplementation can be used as a possible intervention strategy in preventing one of the most common causes of perinatal and maternal morbidity and mortality around the world.

The Leadership Influence on the Performance of Village-Owned Enterprise (BUMDesa) Employees of Lontar Sewu Gresik Regency

The aim of this research is to determine leadership influence on the performance of Village-Owned Enterprise (BUMDesa) Employees of Lontarsewu Gresik RegencyThe research used quantitative methods because it suits the purpose of this research, which aims to measure the leadership influence on the performance of BUMDesa Lontar Sewu employees, Hendrosari Village, Menganti District, Gresik Regency. Based on the results of processing, analysis, and discussion of research data, several points can be concluded as follows coefficient of determination value on the influence between leadership variables and employee performance is 0,55. Correlation coefficient value for the relationship between leadership variables and employee performance variables is 0,74 which interpreted as a strong level of relationship. It can be concluded that the better the leadership of the BUMDesa director, the better the performance of BUMDesa Lontar Sewu employees. The average value of the measurement components based on descriptive analysis of the leadership variable is 4,4 with a very successful interpretation; and the average value of the measurement component of the employee performance variable is 4,6 with a very high interpretation.

The Effect of Promotion and Service Quality on Customer Satisfaction of Bakso Juragan Perindustrian 1 Branch in Palembang City

This study aimed to analyze the effects of promotion and service quality on customer satisfaction at Bakso Juragan Perindustrian 1 Branch 1 in Palembang City. The research method was quantitative. The probability sampling technique was used to select 100 respondents. Data analysis was done through the t-test, f-test and multiple linear regression analysis. The t-test results showed that the promotion and service quality variables partially had a significant effect on customer satisfaction. The results of the f-test showed that the variable promotion and service quality simultaneously affected customer satisfaction. The results of the multiple linear regression analysis of the dominant variable were a promotion (X1) with a significance value of 0.00 and the largest beta value (0.398). Keywords: promotion, service quality, customer satisfaction

Culture media affect sex after IVF treatment-a detailed analysis of explanatory variables.

The purpose of this study was to provide a detailed analysis of clinical and laboratory factors associated with skewed secondary sex ratio (SSR) after ART. Retrospective cohort study of embryos resulting in live births, from frozen and fresh single blastocyst transfers. Embryos were cultured in either G-TL (n = 686) or Sage media (n = 685). Data was analyzed using a multivariate logistic regression model and a mixed model analysis. Significantly more male singletons were born after culture in Sage media compared to G-TL media (odds ratio (OR) 1.34, 95% CI (1.05, 1.70), P = 0.02). Inner cell mass grade B vs A (OR 1.36 95% CI (1.05, 1.76), P = 0.02) and one previous embryo transfer (OR 1.49, 95% CI (1.03, 2.16), P = 0.03) were associated with a significantly higher probability of male child at birth. Factors associated with a reduced probability of male child were expansion grade 3 vs 5 (OR 0.66, 95% CI (10.45, 0.96), P = 0.03) and trophectoderm grade B vs A (OR 0.57, 95% CI (0.44, 0.74), P = 0.00). Male embryos developed significantly faster in Sage media compared to G-TL media for the stages of blastocyst (- 1.12h, 95% CI (- 2.12, - 0.12)), expanded blastocyst (- 1.35h, 95% CI (- 2.34, - 0.35)), and hatched blastocyst (- 1.75h, 95% CI (- 2.99, - 0.52)). More male children were born after culture in Sage media compared to G-TL media. Male embryo development was affected by culture media. Our observations suggest that culture media impact male embryo quality selectively, thus potentially favoring the selection of male embryos.

Interleukin (IL)-23, IL-31, and IL-33 Play a Role in the Course of Autoimmune Endocrine Diseases.

Interleukins (IL)-23, 31, and 33 are involved in the regulation of T helper 17 (Th17)/regulatory T (Treg) cells balance. The role of IL-23, 31 and 33 in non-endocrine autoimmune diseases has been confirmed. Data on the involvement of these cytokines in endocrine autoimmune diseases are limited. This study aimed to determine the involvement of cytokines regulating the T helper 17 (Th17)/regulatory T (Treg) cells axis in the course of autoimmune endocrine diseases. A total number of 80 participants were divided into 4 groups: the autoimmune polyendocrine syndrome (APS) group consisting of APS type 2 (APS-2) and type 3 (APS-3) subgroups, the Hashimoto's thyroiditis (HT) group, the Graves' disease (GD) group and the control (C) group. Fifteen cytokines related to Th17 and Treg lymphocytes were determined in the serum of all participants. Higher levels of IL-23 and IL-31 were found in the APS, GD, and HT groups compared to the C group. Higher levels of IL-23 and IL-31 were also observed in the APS-2 group, in contrast to the APS-3 group. Correlation analysis of variables in the groups showed a statistically significant correlation between the cytokines IL-23, IL-31, and IL-33 in the APS and APS-2 groups, but no correlation in the APS-3 and C groups. IL-23 and IL-31 are independent factors in the course of HT, GD, and APS-2, in contrast to APS-3. The positive correlation between IL-23 and IL-31, IL-23 and IL-33, and between IL-31 and IL-33 in the APS, APS-2 groups, but the lack of correlation in the APS-3 and C groups may further suggest the involvement of these cytokines in the course of Addison's disease.

Preparation and interaction mechanism analysis of single-chain fragment variables against phenylethanolamine A

This is the first report on the screening, expression, and recognition mechanism analysis of single-chain fragment variable (scFv) against phenylethanolamine A (PEAA), a newly emerged β-adrenergic agonist illegally used as a feed additive for growth promotion. The PEAA-specific scFv scFv, called scFv-32, was screened from hybridoma cell lines by phage display and was found to be optimally expressed in the E. coli system. The ic-ELISA results revealed an IC50 value of 10.34 μg/L for scFv-32 and no cross-reactivity with other β-adrenergic agonists. Homology modeling and molecular docking revealed the key binding sites VAL178, TYP228, and ASP229. One hydrogen bond, two pi-sigma bonds, and one pi-pi bond maintain the formation of the antibody‒drug complex. Alanine scanning mutagenesis of the three predicted key binding sites showed that the mutants completely lost their recognition activity, which confirmed the accuracy of the theoretical analysis. These results are valuable for the preparation of scFvs and the analysis of the molecular recognition mechanism of antigen-antibodies.Graphical abstract

Modeling liquid rate through wellhead chokes using machine learning techniques

Precise measurement and prediction of the fluid flow rates in production wells are crucial for anticipating the production volume and hydrocarbon recovery and creating a steady and controllable flow regime in such wells. This study suggests two approaches to predict the flow rate through wellhead chokes. The first is a data-driven approach using different methods, namely: Adaptive boosting support vector regression (Adaboost-SVR), multivariate adaptive regression spline (MARS), radial basis function (RBF), and multilayer perceptron (MLP) with three algorithms: Levenberg–Marquardt (LM), bayesian-regularization (BR), and scaled conjugate gradient (SCG). The second is a developed correlation that depends on wellhead pressure (Pwh), gas-to-liquid ratio (GLR), and choke size (Dc). A dataset of 565 data points is available for model development. The performance of the two suggested approaches is compared with earlier correlations. Results revealed that the proposed models outperform the existing ones, with the Adaboost-SVR model showing the best performance with an average absolute percent relative error (AAPRE) of 5.15% and a correlation coefficient of 0.9784. Additionally, the results indicated that the developed correlation resulted in better predictions compared to the earlier ones. Furthermore, a sensitivity analysis of the input variable was also investigated in this study and revealed that the choke size variable had the most significant effect, while the Pwh and GLR showed a slight effect on the liquid rate. Eventually, the leverage approach showed that only 2.1% of the data points were in the suspicious range.

Effects of the prone position on gas exchange and ventilatory mechanics and their correlations with mechanical power in burn patients with ARDS

Background Prone position has many documented benefits on severe ARDS patients especially on mortality. The benefits in ARDS secondary to severe burns have not been fully documented. Aim To quantify the effects of prone positioning on gas exchange, ventilatory mechanics and their correlations with mechanical power in burn subjects with ARDS. Methods Cross-sectional observational analytical study that took place between January 2023 and October 2023 in Burns ICU in Brazil on subjects with moderate to severe ARDS ventilated with the volume controlled mode. Data were collected in the first prone positioning lasting 24 hours in the first 30 minutes after changing position and 30 minutes before returning to the supine position. The parameters of the components of mechanical ventilation and mechanical power calculated by the Gatinoni’s formula (respiratory rate, tidal volume, driving pressure, PEEP, peak and plateau pressures) were collected to evaluate ventilatory mechanics, and the values of the FiO2, PaO2, PaO2/FiO2 ratio, SpO2, EtCO2, PaCO2, PaCO2 - EtCO2 gradient to assess gas exchange. Mean, minimum and maximum values, 1st and 3rd quartiles, median and standard deviation are calculated. To compare the results obtained at the two evaluation moments, the student’s t-test for dependent samples and non-parametric Wilcoxon tests were considered. To evaluate the association between the variation between the two moments of each variable, and the variation in mechanical power, the Pearson correlation coefficient was calculated. The normality of the variables was assessed using the Jarque-Béra test. P values <0.05 indicated statistical significance. Results Except for EtCO2 (P 0.939) and PaCO2 (P 0.391) all other variables presented statistical significance in relation to their variations with reduction in FiO2 (P <0.001), reduction in PaCO2 - EtCO2 gradient (P 0.011), and increases in PaO2 (P 0.008), PaO2/FiO2 (P <0.001), SpO2 (P 0.004). In the analysis of variables, reduction in respiratory rate (P 0.142), VT (P 0.385), peak pressure (P 0.085), plateau pressure (P 0.009), PEEP (P 0.032), driving pressure (P 0.083), elastance (P 0.180), mechanical power (P < 0.001) with increase static compliance (P 0.414) and resistance pressure (P 0.443). Among the ventilatory mechanics variables, only the reductions in plateau pressure, PEEP, and mechanical power showed statistical significance. Conclusion The prone position in burns induced ARDS improved oxygenation and reduced arterial partial pressure to end tidal CO2 gradient, furthermore, reducing plateau pressures and PEEP, which in turn reduced mechanical power. Keywords: mechanical power, burns, ARDS, prone position

Improving protocols for α-synuclein seed amplification assays: analysis of preanalytical and analytical variables and identification of candidate parameters for seed quantification.

The effect of preanalytical and analytical factors on the α-synuclein (α-syn) seed amplification assay's (SAA) performance has not been fully explored. Similarly, there is limited knowledge about the most suitable assay protocol and kinetic parameters for misfolded α-syn seed quantification. We studied the effect of centrifugation, repeated freeze-thaw cycles (up to seven), delayed freezing, detergent addition, and blood contamination on the performance of the cerebrospinal fluid (CSF) α-syn SAA real-time quaking-induced conversion (RT-QuIC). Moreover, we analysed the inter- and intra-plate variability, the recombinant protein batch effect, and the RT-QuIC parameters' variability when multiple samples were run in controlled conditions. Finally, we evaluated the assay potential of quantifying α-syn seed by assessing kinetic curves in serial CSF dilutions. Among tested preanalytical variables, a≥0.01 % blood contamination and adding detergents significantly affected the RT-QuIC kinetic parameters and the number of positive replicates. Increasing the number of replicates improved result reproducibility. The number of positive replicates in serially diluted CSF samples improved discrimination between samples with high and low seeding activity, and the time to threshold (LAG) was the most reliable kinetic parameter in multiple experiment settings. Preanalytical variables affecting α-syn RT-QuIC performance are limited to blood contamination and detergent addition. The number of positive replicates and the LAG are the most reliable variables for quantifying α-syn seeding activity. Their consistent measurement in serial dilution experiments, especially when associated with an increased number of sample replicates, will help to develop the α-syn RT-QuIC assay further into a quantitative test.

Polarimetric Measures in Biomass Change Prediction Using ALOS-2 PALSAR-2 Data

The use of multiple synthetic aperture radar polarizations can improve biomass estimations compared to using a single polarization. In this study, we compared predictions of aboveground biomass change from ALOS-2 PALSAR-2 backscatter using linear regression based on (1) the cross-polarization channels, (2) the co- and cross-polarizations from fully polarimetric SAR, (3) Freeman–Durden polarimetric decomposition, and (4) the polarimetric radar vegetation index (RVI). Additionally, the impact of forest structure on the sensitivity of the polarimetric backscatter to AGB and AGB change was assessed. The biomass consisted of mainly coniferous trees at the hemi-boreal test site Remningstorp, located in southern Sweden. We found some improvements in the predictions when quad-polarized data (RMSE = 79.4 tons/ha) were used instead of solely cross-polarized data (RMSE = 84.9 tons/ha). However, when using Freeman–Durden decomposition, the prediction accuracy improved further (RMSE = 69.7 tons/ha), and the highest accuracy was obtained with the radar vegetation index (RMSE = 50.4 tons/ha). The corresponding R2 values ranged from 0.45 to 0.82. The bias was less than 1 t/ha for all models. An analysis of forest variables showed that the sensitivity to AGB was reduced for high values of basal-area-weighted mean height, basal area, and stem density when predicting absolute AGB, but the best change prediction model was sensitive to changes larger than the apparent saturation point for AGB state estimates. We conclude that by using fully polarimetric SAR images, forest biomass changes can be estimated more accurately compared to using single- or dual-polarization images. The results were improved the most (in terms of RMSE and R2) by using the Freeman–Durden decomposition model or the RVI, which captured especially the large changes better.

Ground air pollutants explanation based on multiple visibility graph of complex network by temporal community division.

In air pollution studies, the correlation analysis of environmental variables has usually been challenged by parametric diversity. Such variable variations are not only from the extrinsic meteorological conditions and industrial activities but also from the interactive influences between the multiple parameters. A promising solution has been motivated by the recent development of visibility graph (VG) on multi-variable data analysis, especially for the characterization of pollutants' correlation in the temporal domain, the multiple visibility graph (MVG) for nonlinear multivariate time series analysis has been verified effectively in different realistic scenarios. To comprehensively study the correlation between pollutant data and season, in this work, we propose a multi-layer complex network with a community division strategy based on the joint analysis of the atmospheric pollutants. Compared to the single-layer-based complex networks, our proposed method can integrate multiple different atmospheric pollutants for analysis, and combine them with multivariate time series data to obtain higher temporary community division for ground air pollutants interpretation. Substantial experiments have shown that this method effectively utilizes air pollution data from multiple representative indicators. By mining community information in the data, it successfully achieves reasonable and strong interpretive analysis of air pollution data.

Bespoke Metal Nanoparticle Synthesis at Room Temperature and Discovery of Chemical Knowledge on Nanoparticle Growth via Autonomous Experimentations

AbstractThe optimization of nanomaterial synthesis using numerous synthetic variables is considered to be an extremely laborious task because conventional combinatorial explorations are prohibitively expensive. In this work, an autonomous experimentation platform developed for the bespoke design of metal nanoparticles (NPs) with targeted optical properties is reported. This platform operates in a closed‐loop manner between the batch synthesis module of metal NPs and the UV–vis spectroscopy module, based on the feedback of the AI optimization modeling. With silver (Ag) NPs as a representative example, it is demonstrated that the Bayesian optimizer implemented with the early stopping criterion can efficiently produce Ag NPs at room temperature precisely possessing the desired absorption spectra within only 200 iterations (when optimizing among five aqueous synthetic reagents). In addition to the outstanding material developmental efficiency, the analysis of synthetic variables further reveals a novel chemistry involving the quantitative effects of citrate in Ag NP synthesis. The amount of citrate is key to controlling the competition between spherical and plate‐shaped NPs and, as a result, affects the shapes of the absorption spectra as well. This study highlights both capabilities of the platform to enhance search efficiencies and to provide novel chemical knowledge by analyzing datasets accumulated from autonomous experimentations.

Maximum Entropy Analysis of Bird Diversity and Environmental Variables in Nanjing Megapolis, China

Against the background of global climate change and urbanization, the biodiversity of birds is facing unprecedented threats. In this paper, taking the Nanjing megapolis as an example, based on the distribution sites of 79 bird species and 17 environmental variables, the MaxEnt model was used to simulate the distribution of bird diversity, and the most important environmental variables were analyzed. The results show that (1) the MaxEnt model is suitable for simulation of the potential distribution of bird diversity in the Nanjing megapolis; (2) the areas with the highest bird diversity in the Nanjing megapolis were mainly distributed in the mountains and hills where the forests are located; (3) the five most important environmental variables affecting bird distribution were ranked as maximum temperature of the warmest month (MTWM) > Digital Elevation Model (DEM) > precipitation of the wettest month (PWM) > distance to the nearest forest (DF) > Fractional Vegetation Cover index (FVC), with MTWM, PWM, and DF being negatively correlated with bird diversity, whereas FVC and DEM exhibited positive correlations with bird diversity; and (4) the contribution rates of the three types of environmental variables were ranked as follows: habitat environmental variables > meteorological environmental variables > disturbance environmental variables. Sufficient bird habitats should be maintained in cities, and disturbances from human activities should be reduced to achieve the harmonious coexistence of humans and animals in the context of climate change and urbanization, thereby promoting sustainable development.

Analysis of Rainfall as an Agroclimatological Element on Production and Determining the Planting Season of Shallots (Allium Cepa L.) in South Tapanuli Regency

The amount of rain that falls affects the availability of water for planting. For planting scheduling purposes, farmers still use conventional techniques. In our opinion, this decision is not the best. This research aims to determine the relationship between rainfall and the suitability of sweet potato plants by analyzing the impact of rainfall in South Tapanuli Regency on shallot production using rainfall data. Literature review and survey approach were the research methods used. This research uses a survey methodology using descriptive and correlational methodology to ascertain the relationship between rainfall and precipitation. The weakness of this positive influence is shown by the results of regression analysis and correlation of rainfall variables with the magnitude of productivity variables from research conducted a decade earlier. This information was conveyed by the South Tapanuli Regency Central Statistics Agency.

Evaluation of the drought resilience of indigenous irrigation water systems: a case study of dry zone Sri Lanka

The wave of modernization and globalization in the last century has rapidly involved a technological paradigm shift from indigenous irrigation water systems to modern systems in arid regions. Despite interest in the drought resilience of indigenous water systems, the impact of this paradigm shift on drought resilience remains poorly understood because previous studies have focused on fixed irrigation water systems. To fill this gap, we investigated the drought resilience of an indigenous and modern irrigation water system that coexists in the drought-prone Mahaweli H region of the Sri Lankan dry zone. To explain drought resilience, we quantified the historical irrigation system performance (1985–2021) of both water systems using the water duty indicator (i.e., the volume of water required to cultivate a unit land area). The statistical Pettitt test was used to detect significant change points in the time series of water duty, and we divided the time line into few periods based on the change points. Furthermore, a quantitative trend analysis of several socio-hydrological variables and a qualitative analysis of their socio-hydrological backgrounds with triggers of water duty were conducted to explain drought resilience path dependency in modern and indigenous water systems. The results indicated a higher drought resilience is embedded in the indigenous system as the mean water duty increment in drought years compared to non-drought years is 16.4% for the indigenous system and 58.3% for the modern system. In addition, drought resilience pathways that elucidated by water duty change points also demonstrated that indigenous water system features a higher drought resilience compared to the modern water system. The findings of this comparative study can contribute to the design of drought resilience improvement strategies in arid region irrigation water systems in a more comprehensive manner.

Global Solar Radiation and Its Interactions with Atmospheric Substances and Their Effects on Air Temperature Change in Ankara Province

On the analysis of solar radiation and meteorological variables measured in Ankara province in Türkiye from 2017 to 2018, an empirical model of global solar radiation was developed. The global solar radiation at the ground and at the top of the atmosphere (TOA) was calculated and in good agreement with the observations. This model was applied to compute the losses of global solar radiation in the atmosphere and the contributions by atmospheric absorbing and scattering substances. The loss of global solar radiation in the atmosphere was dominated by the absorbing substances. The sensitivity test showed that global solar radiation was more sensitive to changes in scattering (described by a scattering factor S/G, S and G are diffuse and global solar radiation, respectively) than to changes in absorption. This empirical model was applied to calculate the albedos at the TOA and the surface. In 2017, 2018, and 2019, the computed albedos were 28.8%, 27.8%, and 28.2% at the TOA and 21.6%, 22.1%, and 21.9% at the surface, which were in reasonable agreement with satellite retrievals. The empirical model is a useful tool for studying global solar radiation and the multiple interactions between solar energy and atmospheric substances. The comparisons of global solar radiation and its loss in the atmosphere, as well as meteorological parameters, were made at some representative sites on the Earth. Some internal relationships (between G and the absorbing and scattering substances, air temperature and atmospheric substances, air temperature increase and latitude, etc.) were found. Thus, it is suggested to thoroughly study solar radiation, atmospheric substances, and climate change as a whole system and reduce the direct emissions of all atmospheric substances and, subsequently, secondary products (e.g., CO2 and non-CO2) in the atmosphere for the achievement of slowing down climate warming.

Trend analysis of hydro-climatic variables in the Great Lakes Depression region of Mongolia

Abstract Arid and semi-arid regions are the first to be affected by hydro-climatic changes. The Great Lakes Depression Basin in western Mongolia is the most notable example of such a region. Therefore, analyzing hydro-climatic changes in the Great Lakes Depression region is essential for future climate, hydrological, eco-hydrological processes, and ecosystem studies in similar areas and basins. In this study, Mann–Kendall (MK), innovative trend analysis method (ITAM), and Sen's slope estimator test (SSET) were used to determine the interrelationship between climate and river discharge changes and lake water level changes through statistical analysis. During the last 30 years, the air temperature has increased by 1.2 °C (Z = 1.16). Total annual precipitation decreased by 23.44 mm, resulting in 134.16 mm (Z = −0.79). The river discharge of the major rivers, such as Khovd River (Z = −3.51) and Zavkhan River (Z = −6.01), has significantly decreased. In Uvs (Z = 0.30) and Khyargas (Z = 2.03) lakes, the water level has also dropped. This study confirms that the increase in air temperature in the depression area of the Great Lakes reduces the amount of precipitation, and the decrease in precipitation affects the decrease in river discharge, which further affects the water level of the inflowing lakes.