Southwestern Iran Research Articles

Frequency and types of antibiotic usage in a referral neonatal intensive care unit, based on the world health organization classification (AwaRe)

BackgroundExcessive prescription of antibiotics in infants increases the risk of short-term and lifelong morbidity and mortality. Nonetheless, the use of antibiotics in neonatal intensive care units (NICUs) is significantly high. This is primarily because neonatologists are concerned about the fragile immune systems of newborns, their vulnerability to serious infectious diseases, and the challenge of accurately distinguishing between infectious and non-infectious conditions.MethodA five-month cross-sectional prospective study was conducted in southwestern Iran’s largest neonatal intensive care unit. This study aimed to evaluate the dose and duration of antibiotic therapy and identify the prescribing pattern of antibiotics based on the Access, Watch, and Reserve (AWaRe) classification recommended by the World Health Organization (WHO).ResultsOut of 502 examined patient files, antibiotics were prescribed for 483 neonates. The most common drug combinations were ampicillin and amikacin. The mean number and duration of antibiotic administration were 2.14 drugs and 7.78 days, respectively. 84.3% of infants received antibiotics for ten days or less. The mean course of antibiotic prescription for newborns was 1.1, and 83.1% of prescribed antibiotics were from the Access Group.ConclusionThe antibiotic prescription rate was high in our study’s department. Most neonates received two antibiotics in one course from the Access group.

Seroepidemiological Study of Human Herpes Viruses (EBV, CMV, VZV, HSV-1&2) Among Age Groups in Ahvaz, Iran Between 2011 - 2023

Background: Herpesviruses are widespread pathogens worldwide, often establishing lifelong infections in humans. However, seroprevalence data remain scarce for certain populations. To address this gap, a study was conducted to estimate the seroprevalence of human herpesviruses, including Epstein-Barr virus (EBV), Cytomegalovirus (CMV), Varicella zoster virus (VZV), and Herpes simplex virus types 1 and 2 (HSV-1&2), among different age groups in Ahvaz, Iran. Despite previous reports, detailed data on multiple herpesvirus infections are lacking in this region. Objectives: This study aimed to investigate the 11-year prevalence of human herpesviruses (EBV, CMV, VZV, HSV-1&2) among various age groups. Methods: A cross-sectional descriptive-analytical study was conducted on 14,126 serum samples from individuals aged 1 to 88 years. ELISA methods were used to test for the presence of the viruses. Results: The seroprevalence varied significantly by age and gender. The highest seroprevalence was observed for CMV (IgG) at 29.2%, while the lowest was for HSV-1&2 (IgM) at 0.8%. The highest seroprevalence was recorded in the 31 - 40 age group, whereas the lowest was in the 11 - 20 age group. Gender analysis revealed that seropositivity was higher in females (56.3%) compared to males (43.7%), with CMV IgG being the most common seropositive marker in both sexes. Conclusions: These findings underscore the potential for implementing targeted screening and vaccination programs for specific high-risk age groups. The data provide valuable epidemiological insights into the transmission of herpesviruses in southwestern Iran, emphasizing the need for enhanced prevention measures and further research into herpesvirus-related diseases.

Evaluation of Meteorological Drought Using SPI and SPEI on Wheat Yield in Southwestern Iran

The objective of this research is to determine the meteorological drought index and the effective rainfall model that exhibit the highest correlation with the yield of rainfed wheat in the Karkheh watershed. Additionally, using spatial statistics analysis, the trend and status of drought in various parts of the watershed will be identified. This will allow for the determination of suitable areas for rainfed wheat cultivation in the near future. In this research, meteorological drought monitoring was conducted using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) drought indices at 34 synoptic stations of the Karkheh watershed in southwestern Iran from 1981 to 2016. Effective precipitation (EPCP) was calculated using four methods, namely the United States bureau of reclamation method (USBR), the simplified version of soil conservation service of the United States department of agriculture method (USDA-SCS simplified), the food and agriculture organization of the United Nations method (FAO), and the CROPWAT version of the USDA-SCS method (USDA-SCS CROPWAT). The correlation between SPI and SPEI and between wheat yield and these indices was performed using Pearson’s correlation coefficient (R) to select the best index for assessing the effects of meteorological droughts on the agricultural sector. The analysis of the drought features showed that the SPEI reported milder and longer droughts in most synoptic stations. The spatial pattern of drought in the Karkheh watershed was determined using spatial statistics methods, and global Moran’s I statistic showed that the drought in the Karkheh watershed had spatial autocorrelation and a clustered pattern with a 99% confidence level. The results of global and local Moran’s I and the Getis-Ord statistic (Gi*) showed that milder droughts prevailed in the northern clusters and more severe droughts in the southern clusters. Also, the correlation between wheat yield and the SPI and SPEI was positive in all stations except for the stations of Kermanshah province and Aqa Jan Bolaghi, which is due to the existence of numerous dams and springs in these areas. Considering the impact of temperature (Tmean) on meteorological drought, it is suggested that in addition to the SPI, the SPEI should also be used to predict droughts in the Karkheh watershed.

Comparison of the Effects of Brief Intervention (BI) on Relapse Prevention and Withdrawal Permanency in Opioid Addicts and Stimulant Users: A Quasi-Experimental Study

Background: Addiction to narcotics and stimulants is a major social and health challenge worldwide. Objectives: Considering the importance of non-medical treatments in addiction rehabilitation and the necessity of psychotherapy programs in substance abuse rehabilitation centers, the present study aimed to compare the effects of Brief Intervention (BI) on relapse prevention and sustained abstinence in opioid addicts and stimulant abusers seeking help from drop-in-centers (DICs) dedicated to harm reduction in Ahvaz, a city in southwestern Iran. Methods: This applied, quasi-experimental study employed a pre-test, post-test, and follow-up design. The statistical population included 120 male substance abusers and opioid addicts aged 18 to 59, systematically selected from 467 individuals with active files in Iran’s Drug and Alcohol Treatment Information System (IDATIS) under the Ministry of Health in 2023. Participants were selected based on inclusion and exclusion criteria and randomized into four groups: Two experimental groups and two control groups, each with 30 participants. Brief Intervention was provided only to the two experimental groups in four 60-minute sessions, while no intervention was offered to the control groups. Testing tools included specific kits for screening morphine and amphetamines in the urine of participants. Data were analyzed using analysis of variance (ANOVA) with repeated measures and descriptive statistical methods, utilizing SPSS version 24. Results: The study demonstrated that BI was significantly effective in relapse prevention and promoting sustained abstinence in opioid addicts attending harm reduction centers in Ahvaz (P < 0.001). However, BI was not effective in preventing relapse or promoting abstinence in stimulant abusers (P = 0.235). Conclusions: The findings suggest that BI is an effective intervention for preventing relapse and promoting abstinence in opioid abusers. It is recommended that executive managers of addiction harm reduction centers guide their experienced social workers to implement this method as a selective psychotherapy approach complementary to medical treatment for opioid addicts.

A provenance study on the ceramics excavated at the Varzaneh Plain, central Iran

Forty-six ceramic shards from the Early Bronze Age (EBA) archaeological site of Tappeh Gabri (the archaeological site 013), dated back to the latter half of the third millennium BCE and located at the Varzaneh Plain, central Iran, were studied using micro energy dispersive X-ray fluorescence (µ-EDXRF) and petrographic analysis. The precision and accuracy of quantitative data obtained by µ-EDXRF were tested using a series of geological certified reference materials (CRM). The expanded uncertainty and the Mantel test on data obtained by µ-EDXRF showed accurate and precise quantitative µ-EDXRF estimation of elements present in the CRMs above their quantification limit. We show that the majority of the ceramics at the Varzaneh Plain is most probably local product. Discussions prompted collecting further compositional data and performing petrographic investigation from the ceramic shards from southern and south-western Iran in order to shed light on the origin of the ceramic shards excavated at the Varzaneh Plain.

Uncovering implicit Seismogenic associated regions towards promoting urban resilience

Earthquakes pose a significant threat to urban environments, highlighting the need for enhanced seismic resilience. To improve understanding of earthquake dynamics and the interplay of seismic activity across space, this study introduces a novel approach for identifying associated regions that exhibit interdependence seismic behavior, revealing a network structure of earthquake interplays. This model was applied to earthquakes exceeding 3.0 Mw in Iran (1976–2023), using a 1° × 1° grid. Monthly and seasonal timespans were evaluated to capture potential short-term and long-term interactions. The model revealed a network of interdependent seismic regions in southern and southwestern Iran, predominantly located within the Zagros belt. Notably, the strongest associations were observed between spatial units 45 and 36, located approximately 6° apart in southern Iran. These units exhibited significant association in both monthly and seasonal scenarios, with support values of 0.28 and 0.65, and average confidence values of 0.58 and 0.84, respectively. The second significant bilateral relation was detected between neighboring spatial units 22 and 36, with support values of 0.26 and 0.59, and average confidence values of 0.57 and 0.80, respectively. The recognized structure was compared to the established seismotectonic zoning. This network aligns with established seismotectonic provinces, particularly in the seasonal scenario. The model also identified potential interactions between distinct zones in the monthly scenario, highlighting areas where urban development strategies might need reevaluation. Additionally, the analysis revealed implicit causal relationships between spatial units, pinpointing areas susceptible to or influencing seismic activities elsewhere. These results contribute to a deeper understanding of crustal structure, earthquake propagation, and the potential for seismic activity to trigger earthquakes in nearby or distant areas. This knowledge is crucial for developing effective strategies to build earthquake-resilient cities.

Determinants of Livelihood Strategy Choice Among Herder Households: Implications for Poverty Alleviation in Southwestern Iran

Determinants of Livelihood Strategy Choice Among Herder Households: Implications for Poverty Alleviation in Southwestern Iran

Analysis of cutaneous leishmaniasis among military personnel in the Islamic Republic of Iran: a spatiotemporal study between 2018 and 2022, trend forecasting based on ARIMA model

BackgroundCutaneous leishmaniasis is one of the few infectious diseases whose global prevalence is on the rise. Iran ranks among the eight most affected countries in the world. Iranian military personnel are often sent to endemic areas for cutaneous leishmaniasis without prior immunity, and they have fewer health facilities in military centers than the general population. This study aims to comprehensively investigate the situation of cutaneous leishmaniasis in Iranian military personnel across all units from 2018 to 2022 and predict the disease trend using time series analysis up to the end of 2025.MethodsWe analyzed data from the Iranian Ministry of Health to perform spatiotemporal and descriptive analyses based on patient frequency. Variables examined included age distribution, cutaneous leishmaniasis types (zoonotic or anthroponotic), month of healthcare facility visits, and lesion locations. This study employed the ARIMA model (p = 2, d = 0, q = 1)(P = 3, D = 0, Q = 0), for time series analysis and forecasting the disease trend up to 36 months after 2022.ResultsOver five years, 2,894 patients were reported. The Esfahan, Khuzestan, and Ilam provinces had the highest average patient counts, with hot spots primarily found in central, south, southwestern, and western Iran. Although the total number of patients with zoonotic cutaneous leishmaniasis was almost equal to anthroponotic cutaneous leishmaniasis, in high-risk provinces such as Esfahan, Khuzestan, and Ilam, the confirmed cases of zoonotic cutaneous leishmaniasis were much more than anthroponotic cutaneous leishmaniasis. patient numbers peak in October and November. Demographic analysis revealed that younger patients outnumbered older patients. Lesion locations were frequent on the forelimbs and lower limbs. The time series analysis for 36 months after 2022 indicated the seasonal pattern of the disease and predicted an upward trend after 2022.ConclusionWhile overall cases have declined, provinces such as Esfahan exhibit an upward trend. The expansion of hotspots from the west and southwestern to the center and south of Iran, coupled with an increasing trend in time series analysis, suggests the potential emergence of new foci and a rise in patient numbers in the future. In provinces with high disease prevalence, preventive measures should be prioritized, particularly in Ilam, Khuzestan, and Esfahan.

Provision of land use and forest density maps in semi-arid areas of Iran using Sentinel-2 satellite images and vegetation indices

Zagros forests of Iran have several environmental, ecological, and socioeconomic values which provide the unique habitats for many endemic species. However, these ecosystems have severely been destroyed by many anthropogenic and natural factors in recent years. Knowledge of area, distribution, and density of these forests and current natural and human-made land uses inside these ecosystems is necessary for protective management of Zagros forests. This research was performed to obtain the land use and forest density maps in Zagros vegetative area of Fars province in southwestern Iran using Sentinel-2A, vegetation indices, Google Earth, and field data. First, the boundary of Zagros forests in Fars province was digitized on Google Earth images. Then, Sentinel-2A satellite images covering the forest region in Fars province were obtained from Copernicus website. A pilot area (16000 ha) in the province was considered to investigate the precision of different classification methods. Then, Sentinel-2A satellite image of pilot region was classified by some supervised classification methods (ML: maximum likelihood, MD: minimum distance, MaD: mahalanobis distance, SAM: spectral angle mapper, NN: neural network, SVM: support vector machine, and RF: random forest). In addition, the efficiency of different vegetation indices (NDVI, TNDVI, SAVI, and RVI) was evaluated for classifying the forest density in the pilot region. Furthermore, pilot area was considered to test the precision of Google Earth satellite images in this study. For this purpose, 270 field samples were taken as square plots in nine land uses. Selection of the plots inside each land use was randomly. After initial analysis, all satellite images covering the forest area in Fars province were classified by the most accurate algorithm (SVM) to obtain the land use map. On the other hand, the most accurate vegetation index (SAVI) was used to classify the forest density in the study area. Validation of final maps was performed using several random plots on Google Earth images. The initial results of this research indicated that Google Earth images have an overall accuracy (OA) of 96 % compared to ground truth in Zagros vegetative area of Fars province. Results of land use map showed that Zagros forest has covered an area of 794651.79 ha in Fars province. The findings of this research demonstrated that SVM algorithm (OA: 92.94 %, and k: 0.85) has efficiently classified the land uses in Fars province. In addition, SAVI (r2 = 0.719, p < 0.001) has highly been correlated to the forest density in Zagros vegetative area of Fars province. Therefore, land use mapping using SVM algorithm and Sentinel-2A images, and forest density mapping using SAVI is highly recommended in Zagros forests of Fars province in time series which are essential for protective management of these forests in spatio-temporal scale.

Geological characteristics of coal mines in the Zagros basin of Iran: Unveiling rock mechanical properties and time-dependent behavior

The Zagros Basin in southwestern Iran is a significant source of coal, with numerous coal mines operating in the region. Ensuring the stability of coal mines is crucial for safe and efficient mining operations. This study investigates the time-varying response of rocks and roof resistance in coal mines in the Zagros Mountains using a novel approach that combines numerical simulation, relaxation testing, and rock displacement studies. The results show that rocks exhibit significant time-dependent behavior, with changes in rock mechanical properties over time. A comprehensive viscoelastic-plastic model is developed to accurately describe the time-varying strain-softening response of rocks and simulate laboratory tests. The model integrates the Burgers and strain-softening models, simulating stress relaxation curves and rock displacement over time. The study reveals that the rock mass displays significant nonlinear behavior, with changes in rock mechanical properties over time. The findings of this study highlight the importance of considering the time-varying response of rocks and roof resistance in coal mine stability analysis. The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran, which can inform mining practices and mitigate potential hazards. Results in this study can contribute to developing strategies for improving roof stability and reducing the likelihood of roof collapses.

Investigating Some Effective Factors on the Prediction of Continuous Positive Airway Pressure Failure Rate in COVID-19-Related Hypoxemia.

Considering the importance of using Non-Invasive Ventilation (NIV) in COVID-19-related hypoxemia, the present study was conducted to determine the effective factors on Continuous Positive Airway Pressure (CPAP) failure rate in COVID-19-related hypoxemia. This research was a retrospective cross-sectional study (2021) investigating the records of 200 adult patients with the medical diagnosis of acute respiratory failure (ARF) of COVID-19, admitted to the Intensive Care Unit (ICU) in Shoushtar (southwestern Iran) who underwent CPAP therapy. The Heart rate, Acidosis, Consciousness, Oxygenation, and Respiratory rate (HACOR) scores were measured before the treatment and 1 h after undergoing CPAP treatment. Moreover, patients' demographic and clinical data were recorded. Data were analyzed using the Mann-Whitney, Chi-square, Wilcoxon, and logistic regression tests. The significance level was set at p ≤ 0.05. The mean standard deviation [SD]) age of patients was 63.96 (16.23) years. Among all 200 patients, 78.50% (n = 157) experienced CPAP failure and the remaining 21.50% (n = 43) underwent successful CPAP therapy. Failure chance was 7.10% higher in patients with higher HACOR scores undergoing 1 h CPAP treatment than others. It was also 14.92% higher among patients with diabetes mellitus (DM) than non-DM patients. Additionally, old age (z = 2591.50, p value = 0.02), obesity (z = 2433.00, p value = 0.024), and elevated Blood Urea Nitrogen (BUN) (z = 2620.00, p value = 0.0) impacted CPAP failure rates among patients. The HACOR score 1 h after CPAP, DM, old age, obesity, and elevated BUN favor increased CPAP failure rates among patients.

Karst leakage analysis of Roudbal Dam, southwestern Iran, using geological, hydrogeological, hydrochemical and stable-isotopic approaches

Karst leakage analysis of Roudbal Dam, southwestern Iran, using geological, hydrogeological, hydrochemical and stable-isotopic approaches

Iranian farmers' response to the drought crisis: How can the consequences of drought be reduced?

Climate change (CC) is an undeniable global phenomenon, impacting various regions, including Iran. Key components of CC, including the increase in greenhouse gases, rising temperatures, and fluctuations in precipitation patterns, are expected to significantly reduce agricultural crop yields in the near future. In response, identifying effective adaptation strategies is critical for mitigating these adverse effects. This study investigates the role of environmental values, risk perception, and psychological distance in shaping Iranian farmers’ adaptation strategies to CC. A sample of 390 farmers from Shushtar County in southwestern Iran was selected through a multi-stage stratified sampling method. Using structural equation modeling (SEM), the analysis revealed complex interrelationships between environmental values (biospheric, altruistic, and egoistic), beliefs, risk perception, psychological distance, and farmers' adaptation responses to CC. Furthermore, the results indicated that the study variables explain 67.6 % of the variance in farmers' adaptive behaviors, with belief in CC emerging as the most influential factor. These findings not only enrich the current body of literature but also provide actionable insights for policymakers to foster adaptive strategies among farmers.

Biogeography of the Iranian snakes.

The events of the Cenozoic era such as mountain formation caused Iran to become one of the most amazing biodiversity hotspots in the world today. This pioneering study on Iranian snake biogeography integrates historical and ecological analyses. A phylogeographic review traces speciation and dispersal, while cluster analysis with a new snake checklist assesses faunistic similarities within Iran and its surroundings. Jaccard and Sorenson indices generate similarity dendrograms, Indicator Species Analysis pinpoints regional key species, and Endemism index calculates regional endemism rates, enriching our knowledge of Iran's species diversity. Phylogeographic analyses identify four biogeographical corridors for snake ingress into Iran: the Arabian region through southwestern Iran, the Western Asian mountainous transition zone via northwestern Iran, the Turanian region into northeastern Iran, and the Indus River Valley into southeastern and eastern Iran. Dendrogram analysis divides snake fauna into three groups. The first group associates western Zagros and Khuzestan fauna with the Sahara and Arabian regions. The second group links Kopet Dagh and Turkmen Steppe fauna with the Turanian region, and Central Plateau and Baluchistan fauna with the Iranian region. The third group connects northwest highlands, Alborz and Zagros mountains, and Caspian Sea coasts with the Western Asian Mountain transition zone. The study validates broad biogeographic patterns via ecoregional associations and indicator species analysis, providing finer resolution. Species like Platyceps najadum in Caspian Hyrcanian mixed forests exemplify ecoregional alignment, while Zagros and Alborz mountains exhibit unique faunal indicators, indicating species-level divergence. Shared indicators among widespread ecoregions reflect habitat continuity; exclusive indicators emphasize regional distinctiveness. Despite endemic species prevalence, they seldom act as significant indicators due to various factors. Our research confirms the Zagros Mountains, Khuzestan Plain, Alborz Mountains, and Persian Gulf coasts as snake diversity hotspots, marked by higher species richness compared to other Iranian regions.

Clinical Manifestations and Molecular Identification of Giardia duodenalis in Pediatric and Adolescent Cancer Patients in Southwestern Iran.

This study aimed to investigate the clinical and molecular characteristics of Giardia duodenalis (G. duodenalis) infection and identify potential risk factors in children and teenagers with malignancies in Shiraz, southwestern Iran. A total of 200 fresh fecal samples were collected from children and adolescents suffering from 32 different cancer types at Amir, Nemazee, and Saadi hospitals affiliated with Shiraz University of Medical Sciences between October 2021 and May 2022. Direct microscopy using saline and iodine wet mount was conducted, and all fecal samples were rechecked by SSU-PCR. Subsequently, a specific fragment of the tpi gene was amplified on all samples for prevalence, sequencing, and assemblage identification. Our study found a 4% (8/200) prevalence of G. duodenalis using microscopy and PCR. The molecular findings were consistent with the microscopic results. All eight positive samples with SSU-rRNA gene were also detected as positive with tpi gene and were correctly sequenced. Among the examined cancer patients, two assemblages were identified: A [sub-assemblage AI (2/8, 25%) and sub-assemblage AII (3/8, 37.5%)] and B [sub-assemblage BIV (3/8, 37.5%)]. Notably, patients were more vulnerable to G. duodenalis infection after receiving at least 8 treatment episodes (p < 0.05) and displaying gastrointestinal symptoms (p > 0.05). The demographic characteristics of cancer patients with G. duodenalis infection and the statistical conclusions were separately detailed. The small sample size and low prevalence rate in this study hindered precise epidemiological conclusions. Nonetheless, the results suggest that G. duodenalis infection among cancer patients in Shiraz city originates from humans, without any specific animal groups (C-H) involved.

Health risk assessment of potentially toxic elements of corn fields in southern Iran

Potentially toxic elements (PTEs) are among the stable and dangerous environmental pollutants that cause complications in the human body. The present study was conducted to assess the health risk of PTEs in corn fields in southwestern Iran. In the summer and autumn of 2022, 180 samples were collected from corn fields in six regions of Khuzestan Province. Potential elements were measured using the atomic absorption method and an AA240Z device. The average concentrations of Cd, Ni, Zn, and Cu in soil samples from corn fields were found to be 0.20 ± 0.01, 48.96 ± 12.63, 59.93 ± 8.77, and 27.31 ± 5.92 mg/kg, respectively. There was no significant difference in the concentrations of PTEs between the two sampling periods (p > 0.05), but a significant difference was observed among the concentrations of PTEs in the six studied farms (p < 0.05). The highest transfer factor for Zn in corn was 0.62, while the transfer factor for Cu was 0.12, which was lower than that of other elements. The average concentrations of Cd, Ni, Zn, and Cu in corn samples from agricultural fields during the summer and autumn seasons were 0.058, 21.39, 36.52, and 6.60 mg/kg, respectively. The Target Hazard Quotient (THQ) for Cd, Ni, Zn, and Cu was 0.33, 6.11, 0.69, and 0.94 for adults and 1.54, 28.52, 3.24, and 4.4 for children. THQ values for the metals in corn for children were higher than 1. Additionally, the THQ for Ni in adults was higher than 1, indicating a potential health risk. Therefore, based on the data analysis, the THQ of Cd, Ni, Cu, and Zn in corn can pose a danger to human health. According to the results of the Cd carcinogenesis risk index, corn consumption appears to be hazardous for both adults and children.

Prevalence and associated risk factors of intraventricular hemorrhage in preterm newborns in Southwestern Iran.

The purpose of this study was to investigate the prevalence of IVH and its associated risk factors in premature newborn admitted to NICU in Southwestern Iran. This cross-sectional study involved all premature newborn admitted to Namazee NICU, Southwestern Iran, during the year 2022. The diagnosis of IVH was confirmed using brain ultrasonography, following Papille's criteria. Demographic data and potential risk factors were collected and analyzed for two groups: neonate diagnosed with IVH and those without the condition. Among the 275 preterm neonates studied (125 girls, 150 boys), the mean gestational age was 29.22 ± 1.44 weeks. The prevalence of IVH was found to be 20.4% within the first 7th day after birth. The recognized risk factors of IVH in our study were gestational age, pneumothorax, hypoxia, antenatal steroids, and transfusion of packed red blood cell. Duration of intubation and CPAP therapy were found to be other risk factors, too. The logistic regression model showed preterm newborns born between gestational age of 28+1 and 30+6 weeks had a twofold increased risk of developing IVH. The prevalence of IVH in NICU hospitalized newborns with a gestational age of ≤ 32 weeks was around 20%, which is consistent with other studies conducted in Iran. The findings emphasize the importance of enhanced antenatal care for early intervention for neonates born at early gestational age to reduce or prevent the risk of IVH.

Microfacies and sedimentary environment of the Kazhdumi formation in the northern flank of the Khami Anticline, Zagros Basin, southwestern Iran

Microfacies and sedimentary environment of the Kazhdumi formation in the northern flank of the Khami Anticline, Zagros Basin, southwestern Iran

RNN-Based Monthly Inflow Prediction for Dez Dam in Iran Considering the Effect of Wavelet Pre-Processing and Uncertainty Analysis

In recent years, deep learning (DL) methods, such as recurrent neural networks (RNN). have been used for streamflow prediction. In this study, the monthly inflow into the Dez Dam reservoir from 1955 to 2018 in southwestern Iran was simulated using various types of RNNs, including long short-term memory (LSTM), bidirectional long short-term memory (Bi-LSTM), gated recurrent unit (GRU), and stacked long short-term memory (Stacked LSTM). It was observed that considering flow discharge, temperature, and precipitation as inputs to the models yields the best results. Additionally, wavelet transform was employed to enhance the accuracy of the RNNs. Among the RNNs, the GRU model exhibited the best performance in simulating monthly streamflow without using wavelet transform, with RMSE, MAE, NSE, and R2 values of 0.061 m3/s, 0.038 m3/s, 0.556, and 0.642, respectively. Moreover, in the case of using wavelet transform, the Bi-LSTM model with db5 mother wavelet and decomposition level 5 was able to simulate the monthly streamflow with high accuracy, yielding RMSE, MAE, NSE, and R2 values of 0.014 m3/s, 0.008 m3/s, 0.9983, and 0.9981, respectively. Uncertainty analysis was conducted for the two mentioned superior models. To quantify the uncertainty, the concept of the 95 percent prediction uncertainty (95PPU) and the p-factor and r-factor criteria were utilized. For the GRU, the p-factor and r-factor values were 82% and 1.28, respectively. For the Bi-LSTM model, the p-factor and r-factor values were 94% and 1.06, respectively. The obtained p-factor and r-factor values for both models are within the acceptable and reliable range.

Identifying and detecting causes of changes in spatial patterns of extreme rainfall in southwestern Iran

Identifying and detecting causes of changes in spatial patterns of extreme rainfall in southwestern Iran