Modeling the subsidence development of Marvdasht plain in relation to groundwater abstraction

Excessive abstraction of groundwater aquifers in the country has caused a sharp drop in the aquifer water level and the loss of aquatic aquifers, the effects of which is the phenomenon of subsidence. In this study, simulation of groundwater level changes in Marvdasht-Kharameh basin from a validation period and processing of a large set of raw data in Modflow mathematical model was used. The output results of sensitivity analysis of effective parameters in the calibration of Marvdasht aquifer show the maximum effect of hydraulic conductivity parameters and horizontal hydraulic conductance anisotropy and a set of linear groups of water supply network. Therefore, it is in line with the statistics of the Fars Regional Water Organization that there are wells with high discharge in these areas. According to the conditions of the aquifer, if the current operation trend continues, it is predicted that the groundwater level will drop by 15 meters during the years 2019 to 2029. Also, according to the average land subsidence, which averages 0.76 meters per 10 meters. The average land subsidence with the current harvest trend in the next ten years is predictable 114.78 cm and with a 30% increase in harvest, the rate of aquifer decline over the next 20 years is about 37 meters with an annual decline of about It is 1.9 meters. Land subsidence in this case is also predicted to be about 280 cm. Finally, according to the maps prepared from Marvdasht aquifer, due to the alluvial nature of the groundwater aquifer, the effect of water level drop can be observed from a short distance. The rate of subsidence in the southern and southwestern margins of the plain due to the low thickness of sediments and in the northern and northeastern parts of the plain due to coarse-grained sediments, is less than the central parts of the plain

Chronic complications of diabetes mellitus in newly diagnosed patients

AbstractThe prevalence of Diabetes Mellitus (DM) has increased in recent decades. This study was designed to determine retinopathy, neuropathy, nephropathy, hypertension and hyperlipidemia and their interdependence in newly diagnosed diabetic patients. In this study, 200 consecutive newly diagnosed patients were evaluated and screening tests for retinopathy, neuropathy, nephropathy, hypertension and hyperlipidemia were undertaken.The frequency of positive screening tests for hyperlipidemia, hypertension, neuropathy, nephropathy and retinopathy was found to be 73.5%, 58.5%, 52%, 10%, and 6% respectively.A significant proportion of newly diagnosed diabetic patients have signs of these chronic complications

An integrated model of cellular manufacturing and supplier selection considering product quality

Today’s business environment has forced manufacturers and plants to produce high-quality products at low cost and the shortest possible delivery time. To cope with this challenge, manufacturing organizations need to optimize the manufacturing and other functions that are in logical association with each other. Therefore, manufacturing system design and supplier selection process are linked together as two major and interrelated decisions involved in viability of production firm. As a matter of fact, production and purchasing functions interact in the form of an organization’s overall operation and jointly determine corporate success. In this research, we tried to show the relationship between designing cellular manufacturing system (CMS) and supplier selection process by providing product quality considerations as well as the imprecise nature of some input parameters including parts demands and defects rates. A unified fuzzy mixed integer linear programming model is developed to make the interrelated cell formation and supplier selection decisions simultaneously and to obtain the advantages of this integrated approach with product quality and consequently reduction of total cost. Computational results also display the efficiency of proposed mathematical model for simultaneous consideration of cellular manufacturing design and supplier selection as compared to when these two decisions separately taken into account

Survey of Effective Factors in the Event of Neuropathy in Type 2 Diabetic Patients

Introduction: Diabetic neuropathy is a common and sever complication of diabetes that its progression can lead to disability and even amputation in diabetic patients. The aim of this study was to determine the effective factors in the event of neuropathy and to assess the cumulative incidence of neuropathy in patients with type 2 diabetes. Methods: In this cohort study, all patients with type 2 diabetes who were registered at Fereydunshahr Diabetes Clinic, Isfahan, Iran, were selected by census method. They were followed up for diagnosis of neuropathy since 2006 until March 2016. To investigate the quantitative and qualitative effective factors in the event of neuropathy, one-sample t-test and chi-square test, respectively, were used. And for modeling of effective factors in the event of neuropathy, logistic regression was used. All statistics were analyzed by R software (version 3.2.3) and P values less than 0.05 were considered significant. Results: At the end of 10-year follow-up, cumulative incidence and prevalence of neuropathy were estimated 31% and 41.6%, respectively. After removal of confounders in the final model, variables such as age, ethnicity, family history of diabetes, duration of diabetes, FBS and HDL levels were identified as effective factors in the event of neuropathy (P<0.05). Conclusion: Low levels of HDL and poor control of FBS level are modifiable risk factors for diabetic neuropathy. But non-modifiable risk factors include Persian ethnicity, family history of diabetes, age and increase of diabetes duration. For this reason, in order to increase the HDL level and to decrease FBS level, education is recommended particularly in elderly patients with a family history of diabetes

Survey of Effective Factors in the Event of Neuropathy in Type 2 Diabetic Patients

Introduction: Diabetic neuropathy is a common and sever complication of diabetes that its progression can lead to disability and even amputation in diabetic patients. The aim of this study was to determine the effective factors in the event of neuropathy and to assess the cumulative incidence of neuropathy in patients with type 2 diabetes. Methods: In this cohort study, all patients with type 2 diabetes who were registered at Fereydunshahr Diabetes Clinic, Isfahan, Iran, were selected by census method. They were followed up for diagnosis of neuropathy since 2006 until March 2016. To investigate the quantitative and qualitative effective factors in the event of neuropathy, one-sample t-test and chi-square test, respectively, were used. And for modeling of effective factors in the event of neuropathy, logistic regression was used. All statistics were analyzed by R software (version 3.2.3) and P values less than 0.05 were considered significant. Results: At the end of 10-year follow-up, cumulative incidence and prevalence of neuropathy were estimated 31% and 41.6%, respectively. After removal of confounders in the final model, variables such as age, ethnicity, family history of diabetes, duration of diabetes, FBS and HDL levels were identified as effective factors in the event of neuropathy (P<0.05). Conclusion: Low levels of HDL and poor control of FBS level are modifiable risk factors for diabetic neuropathy. But non-modifiable risk factors include Persian ethnicity, family history of diabetes, age and increase of diabetes duration. For this reason, in order to increase the HDL level and to decrease FBS level, education is recommended particularly in elderly patients with a family history of diabetes

Effects of hazelnuts consumption on fasting blood sugar and lipoproteins in patients with type 2 diabetes

Background: Previous studies have demonstrated that nuts consumption have beneficial effects on serum lipid profiles in hyperlipidemic or normolipidemic subjects. However, similar studies in diabetes field are quite rare. So, we aimed to investigate the effects of hazelnut consumption on fasting blood sugar (FBS) and lipid profiles in patients with type 2 Diabetes. Materials and Methods: An 8-week controlled randomized parallel study in patients with type 2 diabetes. Fifty eligible volunteers were assigned to either the control or intervention groups. 10% of total daily calorie intake was replaced with hazelnuts in intervention group. Blood samples were collected from fasting patients at the start and at the end of the study. Results: After 8 weeks, there were significant differences in high-density lipoprotein-cholesterol (HDL-C) concentrations between two groups, using analyses of covariance (P = 0.009), which was due to the larger HDL-C reduction in control group (P = 0.003). Although, Hazelnut group achieved greater reduction in triglyceride (TG) concentrations than control group, these changes were not statistically significant. Neither between-group changes nor within-group changes were significant for FBS, total cholesterol (TC), TG, and low-density lipoprotein-cholesterol (LDL-C) levels. Conclusion: Results of this study indicated that incorporation of hazelnuts into diet can prevent reduction of HDL-C concentrations in patients with type 2 diabetes, but had no effect on FBS or other lipid profile indices

Association Of Statin Therapy On Clinical Outcomes In Covid-19 Patients: An Updated Systematic Review And Meta-Analysis On All Related Evidences

Background: Statins is a class of lipid-lowering drugs and our previous investigations showed that statins have antiviral effects and have a wound healing effect in the lung. This systematic review and meta-analysis aimed to evaluate the effects of statin therapy on mortality and clinical outcomes in COVID-19 patients. Methods: A comprehensive search was conducted in international databases, including MEDLINE, Scopus, Web of Science, and Embase from December 1, 2019 until January 26, 2022 without any restriction in language. The random-effects model was used to estimate the pooled odds ratio (OR). Results: The statin therapy overally was associated with decrease in odds of ventilation [pooled OR (95% CI): 0.85 (0.70 to 0.99)] and mortality [pooled OR (95% CI): 0.73 (0.66 to 0.81)] but had no effects on the  ICU admission [pooled OR (95% CI):  0.93 (0.77 to 1.12)], oxygen therapy [pooled OR (95% CI): 0.85 (0.70 to 0.99)], recovery [pooled OR (95% CI): 1.85 (0.35 to 9.92)], kidney failure [pooled OR (95% CI): 1.01 (0.73 to 1.40)], hospitalization [pooled OR (95% CI): 1.45 (0.88 to 2.36)], asymptomatic disease [pooled OR (95% CI): 1.33 (0.24 to 7.44)], and ARDS [pooled OR (95% CI): 1.15 (0.88 to 1.49)]. Conclusions: The present meta-analysis showed that statin therapy was associated with a reduced risk of mortality and ventilation in patients with COVID-19 but had no effects on other clinical outcomes

A survey on some risk factors and evaluation of their impacts on streptococcosis incidence in rainbow trout farms in Fars province

Streptococcosis is an infectious bacterial disease that causes huge economic losses in cold water aquaculture industry. Disease outbreak was experienced in some of provinces farms in recent years. Fars Province, has produced 7,000 tons of cold-water fish. According to Streptococcosis report in 1381 from the province and Proceedings have been performed during 10 years against disease and also economic losses impact of disease on rainbow trout production, risk assessment of Streptococcosis conducted on the plan. In this study, of 586 sick fish (have symptoms) studied 230 fish (39.24%) Streptococcus and (26.62%) gram negative bacteria were isolated. Of 754 healthy grower fish and fry (with no clinical signs) 10 fish or fry (1.32%)infected with streptococcus and 60 fish or fry(7.95%) infected with gram negative bacteria (Yersinia ruckeri, Pseudomonas, entrobacteriaceae). According to biochemical tests and molecular examinations, isolated Streptococcuus iniae and Streptococcus sp. Furthermore some physical and chemical parameters measured and aerobic bacteria of selected farm water counted. These factors effects on disease incidence and changes were evaluated by applying logistic regression

A Comparative Analysis of Clinical Characteristics and Laboratory Findings of COVID-19 between Intensive Care Unit and Non-Intensive Care Unit Pediatric Patients: A Multicenter, Retrospective, Observational Study from Iranian Network for Research in Viral

Introduction: To date, little is known about the clinical features of pediatric COVID-19 patients admitted to intensive care units (ICUs).&nbsp;Objective: Herein, we aimed to describe the differences in demographic characteristics, laboratory findings, clinical presentations, and outcomes of Iranian pediatric COVID-19 patients admitted to ICU versus those in non-ICU settings.&nbsp;Methods: This multicenter investigation involved 15 general and pediatrics hospitals and included cases with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection based on positive real-time reverse transcription polymerase chain reaction (RT-PCR) admitted to these centers between March and May 2020, during the initial peak of the COVID-19 pandemic in Iran.&nbsp;Results: Overall, 166 patients were included, 61 (36.7%) of whom required ICU admission. The highest number of admitted cases to ICU were in the age group of 1–5 years old. Malignancy and heart diseases were the most frequent underlying conditions. Dyspnea was the major symptom for ICU-admitted patients. There were significant decreases in PH, HCO3 and base excess, as well as increases in creatinine, creatine phosphokinase (CPK), lactate dehydrogenase (LDH), and potassium levels between ICU-admitted and non-ICU patients. Acute respiratory distress syndrome (ARDS), shock, and acute cardiac injury were the most common features among ICU-admitted patients. The mortality rate in the ICU-admitted patients was substantially higher than non-ICU cases (45.9% vs. 1.9%, respectively; p&lt;0.001).&nbsp;Conclusions: Underlying diseases were the major risk factors for the increased ICU admissions and mortality rates in pediatric COVID-19 patients. There were few paraclinical parameters that could differentiate between pediatrics in terms of prognosis and serious outcomes of COVID-19. Healthcare providers should consider children as a high-risk group, especially those with underlying medical conditions

Comparing of cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Background: Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. Materials and Methods: This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model (P < 0.20) were entered into the multivariate Cox and parametric models (P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Results: Using Kaplan–Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy (P < 0.05). Conclusion: According to AIC, “log-normal” model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model