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Abstract Objective To evaluate the effectiveness and safety of tofacitinib in patients with ulcerative colitis (UC) in clinical practice in Lebanon. Design This was a retrospective cross-sectional study. The data were collected from hospital records. Patients with moderate to severe UC treated with tofacitinib between 2018 and 2021 were included. Patients’ demographics, disease-specific characteristics, clinical assessment at three time points (8, 26, and 52 weeks), endoscopic evaluation at 24 weeks, and adverse events were collected. Results A total of 60 UC patients with a mean duration of disease of 7.9 ± 4.7 years were enrolled. 61.7% of patients had extensive disease, and 58.3% had received ≥ 1 biologic prior to tofacitinib. Clinical remission was reported in 25, 34, and 31 patients (41.7%, 56.7%, and 56.4%) at 8, 26, and 52 weeks respectively. Endoscopic remission (endoscopic Mayo score 0 or 1) was observed in 58.3% of patients at 52 weeks. About one-third of patients (31.7%) stopped tofacitinib at one year, primarily for lack of efficacy or loss of response, with no significant difference between biologics-naïve and experienced patients (24% vs. 37.1% respectively). No serious adverse events or deaths were reported. Adverse events were reported in 3 patients (5.0%) - one C. difficile infection, one case of reversible lymphopenia, and one case of facial acne. No serious adverse events or deaths were noted. On multivariate analysis, biologic-naïve status and reduction or normalization of CRP were associated with clinical remission (OR = 10.87, 95% CI = 1.57, 100, and OR = 78.47, 95% CI = 2.09, 2940.32 respectively), while reduction or normalization of CRP was associated with endoscopic remission at 1 year (OR = 19.03, 95% CI = 1.64, 221.09). Conclusion Tofacitinib was effective in the treatment of moderately severe ulcerative colitis in this real-world cohort in Lebanon. Further, the predictors associated with clinical and endoscopic remissions were found to be biologic-naïve status and reduction in CRP. Observed AEs were consistent with the known safety profile. One of the major limitations of this study is the smaller sample size and the retrospective nature of the study.

Background: Celiac disease is an autoimmune disorder triggered by gluten, that occurs in susceptible individuals and is associated with dietary restriction and subsequent nutritional deficiencies. This study investigated the diet quality, nutrition imbalances and nutrition status among young children,adolescents and adults with CD who were referred to several hospitals in Lebanon. Methods: A cross-sectional study in 50 individuals (31.74 ± 15.64 years) with CD who follow a gluten free diet was conducted, using biochemical parameters, anthropometric measurements, dietary and physical activity assessments. Results: Of the 50 participants, 38% and 16% were presenting low serum levels of iron and vitamin B12, respectively. The majority of participants were physically inactive and around 40% of them had low muscle mass. A weight loss of 10% to 30% indicating mild to moderate malnutrition was shown in 14% of individuals. The assessment of food-related behaviors shows that 80% of participants were reading nutrition labels and 96% of them were following gluten-free diets (GFD). Some barriers including family ignorance (6%), language of the nutrition labels (20%) and expensive GF products (78%) were limiting the adherence to GFD. The inadequacy of the daily energy intake along with insufficient intakes of calcium and vitamin D were remarked among individuals with CD. However, protein and iron intake were exceeding the recommendations among all age groups, except in males aged 4-8 years and 19-30 years. Half the study participants were using dietary supplements where 38%, 10%, 46%, 18%, 16% and 4% used vitamin D, vitamin B12, iron, calcium, folate and probiotics, respectively. Conclusion: GFD is the key treatment for CD. However, it is not without inadequacies and may cause certain deficiencies such as calcium and vitamin D leading to reduced bone density. This underlines the critical role of dietitians in education and maintenance of healthy GFD among individuals with CD.

Background: Celiac disease is an autoimmune disorder triggered by gluten, that occurs in susceptible individuals and is associated with dietary restriction and subsequent nutritional deficiencies. This study investigated the diet quality, nutrition imbalances and nutrition status among young children,adolescents and adults with CD who followed a gluten free diet an who were referred to several hospitals in Lebanon. Methods: A cross-sectional study in 50 individuals (31.74 ± 15.64 years) with CD was conducted, using biochemical parameters, anthropometric measurements, dietary and physical activity assessments. Results: Of the 50 participants, 38% and 16% were presenting low serum levels of iron and vitamin B12, respectively. The majority of participants were physically inactive and around 40% of them had low muscle mass. A weight loss of 10% to 30% indicating mild to moderate malnutrition was shown in 14% of individuals. The assessment of food-related behaviors shows that 80% of participants were reading nutrition labels and 96% of them were following gluten-free diets. Some barriers including family ignorance (6%), language of the nutrition labels (20%) and expensive GF products (78%) were limiting the adherence to GFD. The inadequacy of the daily energy intake along with insufficient intakes of calcium and vitamin D were remarked among individuals with CD. However, protein and iron intake were exceeding the recommendations among all age groups, except in males aged 4-8 years and 19-30 years. Half the study participants were using dietary supplements where 38%, 10%, 46%, 18%, 16% and 4% used vitamin D, vitamin B12, iron, calcium, folate and probiotics, respectively. Conclusion: GFD is the key treatment for CD. However, it is not without inadequacies and may cause certain deficiencies such as calcium and vitamin D leading to reduced bone density. This underlines the critical role of dietitians in education and maintenance of healthy GFD among individuals with CD.

Background: Celiac disease (CD) is an autoimmune disorder triggered by gluten, that occurs in susceptible individuals and is associated with dietary restriction and subsequent nutritional deficiencies. This study investigated the diet quality, nutrition imbalances and nutrition status among young children, adolescents and adults with CD who were referred to several hospitals in Lebanon. Methods: A cross-sectional study in 50 individuals (31.74 ± 15.64 years) with CD was conducted, using biochemical parameters, anthropometric measurements, dietary and physical activity assessments. Results: Of the 50 participants, 38% and 16% were presenting low serum levels of iron and vitamin B12, respectively. The majority of participants were physically inactive and around 40% of them had low muscle mass. A weight loss of 10% to 30% indicating mild to moderate malnutrition was shown in 14% of individuals. The assessment of food-related behaviors shows that 80% of participants were reading nutrition labels and 96% of them were following gluten-free diets (GFD). Some barriers including family ignorance (6%), language of the nutrition labels (20%) and expensive GF products (78%) were limiting the adherence to GFD. The inadequacy of the daily energy intake along with insufficient intakes of calcium and vitamin D were remarked among individuals with CD. However, protein and iron intake were exceeding the recommendations among all age groups, except in males aged 4-8 years and 19-30 years. Half the study participants were using dietary supplements where 38%, 10%, 46%, 18%, 16% and 4% used vitamin D, vitamin B12, iron, calcium, folate and probiotics, respectively. Conclusion: GFD is the key treatment for CD. However, it is not without inadequacies and may cause certain deficiencies such as calcium and vitamin D leading to reduced bone density. This underlines the critical role of dietitians in education and maintenance of healthy GFD among individuals with CD.

Abstract Estimating petrophysical properties in carbonate rocks is challenging due to their complex pore structure, which leads to scattered data when analyzing the relationship between formation resistivity factor (F) and porosity. Traditional electrical rock typing methods showed limited success in reducing data scattering, as they primarily focused on the relationship between cementation factor and porosity. These methods often overlooked the importance of electrical quality in their analyses. In this study, the Electrical Zone Indicator (EZI) was introduced as a novel method that provides more accurate determination of reservoir electrical parameters compared to techniques like the Electrical Quality Index (EQI). EZI enhances EQI by minimizing its dependence on porosity that results in fewer and more precise electrical rock types. The method offers improved estimates of formation resistivity factor (F), cementation factor (m), and tortuosity factor (a). For instance, the cementation factor values for dataset 1 range from 1.685 to 3.33, and for dataset 2 from 2.108 to 3.268 values that align more closely with those expected in carbonate rocks. Data analysis confirms that EZI delivers highly accurate rock typing with determination coefficients (R²) greater 0.96. EZI enables a more comprehensive and accurate evaluation of reservoir rock types by providing more precise calculations of F and eliminating the need for data exclusion. In conclusion, the EZI method significantly improves the estimation of key reservoir parameters which makes it a valuable tool for petrophysical analysis in carbonate formations.

Introduction: Given the importance of the employment status of graduates for countries, the current study aims to investigate the employment status of occupational health and safety engineering (OHS) graduates from Kashan University of Medical Sciences (KAUMS), from the establishment of the field in 1996 up until 2023 Material and Methods: The cross-sectional study examined the employment status of OHS graduates of KAUMS using a researcher-developed Google form questionnaire. The questionnaire included demographic characteristics, five questions for unemployed individuals, and 60 questions for employed individuals. Finally, descriptive and analytical analyses of the study were performed using SPSS v16 software. Results: A total of 229 graduates participated in this study. The results regarding the frequency of employed and unemployed participants showed that 198 (86.5%) participants were employed, and 31 (13.5%) were unemployed at the time of the study. Most employed participants (46%, or 90 individuals) work in the industry and mining sector. Evaluating the effectiveness of the educational course of employed participants in relation to their jobs revealed that 88 participants (44.4%) believe that the subjects taught in the courses are moderately compatible with work needs. Conclusion: With the advancement of industries and the expansion of production, the need to control harmful factors and improve workers’ health is more evident than ever before, making it likely that graduates of this field will have favorable job prospects in the future. On the other hand, the academic conditions should be improved, particularly regarding the quality of the educational and curriculum programs of KAUMS.

Background: the urban Health Commission of Wuhan City, China, issued an emergency notice due to an incidence of viral pneumonia of unknown cause in December 2019. The World Health Organization officially named it the 2019 novel coronavirus. Since the course of the disease is not the same in the countries and regions of the world, and the study of this diversity is an important source of information for policymakers and researchers. The current study aims to cluster selected countries of the world based on its incidence and it was done according to the trajectories shape. Methods: the data set analyzed, included new cases of COVID-19(per million people) in 13 countries of the world, which were published on the World Health website from March, 2020, to October, 2021 monthly then analyzed by the k-means clustering method using Fréchet distance and R software V4.0.5. in addition, clustercrit and kmlshape packages were utilized for trajectory clustering. Result: Research results show that, 13 countries of the world were classified into 2 clusters with high and low incidence. The cluster with high incidence included 8(62%) countries. The 2 cluster exhibits the highest outlier in COVID-19 incidence. In the analyzed nations, United States and Brazil exhibited the highest incidence rate in clusters 1 and 2, respectively. Conclusion: The present findings showed that there are 2 patterns in the epidemic of COVID-19. The first pattern includes severe fluctuations and the next pattern includes low fluctuations. The results revealed that the method used in this article has the potential to understand incidence trends regardless of the time of disease onset. Since the Covid-19 infection process experiences fluctuations over time that vary based on when the pandemic began in each country, it's essential to analyze the similarity and shape of infection trends collectively, independent of their starting points.

Abstract Rock typing techniques have relied on either electrical or hydraulic properties. The study introduces a novel approach for reservoir rock typing, the hydraulic-electric index (HEI), which combines the strengths of traditional electrical and hydraulic rock typing methods to characterize carbonate reservoirs more accurately. By normalizing the ratio of permeability and formation resistivity factor (K/FRF) with respect to porosity, the HEI method is applied to two datasets of carbonate core samples: dataset 1 consists of 112 carbonate core samples from the Tensleep formation in the Bighorn basin of Wyoming and Montana, and dataset 2 includes 81 carbonate core samples from the Asmari formation in the south-west of Iran. Statistical analysis confirms the effectiveness of the HEI in predicting permeability, with high determination coefficients for both datasets (resulting in determination coefficients (R2) of 0.965 and 0.904 for dataset 1 and dataset 2, respectively). The results classify the rock samples into distinct rock types, nine rock types for dataset 1 and four rock types for dataset 2, and demonstrate the HEI ability to capture the relationship between hydraulic conductivity and electrical resistivity in carbonate reservoir rocks. Applying the HEI method to the validation dataset yielded highly accurate permeability predictions, with average of determination coefficients of 0.883 and 0.859 for dataset 1 and dataset 2, respectively. Validation of the HEI method further confirms (20% of the dataset was set aside for validation, while the remaining 80% was used for the rock typing approach (5 folds)) its accuracy in predicting permeability, highlighting its robust predictive capacity for estimating permeability in carbonate reservoirs.

As the depth of mineral exploration has increased in recent years, multiple exploration methods have become necessary to obtain more accurate depth and surface data. Each type of exploratory data has different uncertainty, resolution, and efficiency levels. Using these data individually or preparing traditional models based on a single data type often fails to meet the desired accuracy level. Therefore, mineral prospectivity mapping (MPM) has become more common in integrating these data. MPM methods require determining the importance of the data used. This importance is expressed as the weight of the layers (evidence). Typically, data-driven methods cannot be used to determine the weight of evidence layers in green areas due to the need for sufficient deposits. In these areas, knowledge-based methods, using the opinions of expert geologists, are often used to determine the weight of the layers. However, the weights determined by different experts may vary depending on their perspectives. Therefore, one of the challenges of using MPM methods in green areas is determining a reliable weight for the layers. This paper uses different exploration data, such as airborne geophysical data, geochemistry, geology, and remote sensing data, to prepare suitable reference layers. Due to the limited mineral prospects available in this area, we used the prediction-area (P-A) method to calculate the layers' weights without experts' opinions. We then used these weights to produce the gold prospectivity map in this area using the multi-index overlay (MIO) and the (Adjusted, Conventional, and Modified) TOPSIS methods. Finally, the obtained results were used to evaluate the efficiency of these methods and the calculated weights for this area.

Background & Aims: Noise exposure can impact nurses' performance and may result in disruptions to their tasks. This study aimed to examine the correlation between the average equivalent sound level and the occurrence of medication errors. Materials & Methods: This cross-sectional study involved 150 nurses in Iran in 2020. First, two medical and two surgical wards were randomly selected using a coin toss method. Second, the nurses who worked in those wards were sampled using the convenience method. Nurses' medication errors were assessed using a questionnaire. A sound level meter was used to measure the sound level in decibel. Data were analyzed using analytical tests, including Kruskal-Wallis, Spearman correlation coefficient, and Poisson model. Results: The mean sound equivalent level in the cardio-respiratory internal ward (58.94 ± 1.88) was higher than the same level in the other internal and surgical wards (p < 0.001). An increase in the mean sound equivalent level in the wards was accompanied by an increase in the mean number of medication errors among unmarried individuals (e0.22 = 1.25), which was 1.25 times more than the errors made by married individuals. Finally, an increase in age and the mean sound equivalent level resulted in the occurrence of medication errors (p < 0.002). Conclusion: The results showed that there was no relationship between the sound pressure level and nurses’ medication errors in the research environment. Therefore, it is necessary to conduct more studies to investigate the factors that increase the incidence of medication errors.

Objectives: This study aims to develop strategies for risk management and accurately model the potential outcomes in hazardous zones.Methods: The initial step of this study involved conducting HAZOP studies to identify all process nodes and deviations in an urban water-treatment plant located in Markazi province. Subsequently, all risks associated with the identified deviations were evaluated using a qualitative risk matrix. To enhance the scientific accuracy of the risk assessment results, the fuzzy HAZOP methodology was employed. Finally, the assessed risks were prioritized with precision, and PHAST software was utilized to visualize critical scenarios and determine the zones of catastrophic consequences.Results: The initial findings from the HAZOP investigations conducted in the chlorination unit of the treatment facility reveal a total of 41 deviations out of 55 identified risks. Out of these risks, 47 (85%) were classified as high risk (HR), while 8 (15%) were categorized as medium risk (MR). The results of the risk assessment clearly demonstrate that the risks are of significant concern, despite the presence of existing controls. Ultimately, eight scenarios were identified and extracted from the analysis.Conclusion: Based on the research results, it is imperative that all chlorination facilities undergo redesigning to prevent corrosion, erosion, leakage, and rupture and to conduct risk-based inspections (RBI). Furthermore, regular chlorine leakage drills should be included to enhance emergency response and preparedness.

Introduction: Given that hospital air is one of the important environmental sources for transmission of microorganisms, the importance of airborne transmission in the epidemiology of hospital-acquired infections (HAIs) has gained attention in the past two decades. Therefore, the present study aims to determine the concentration of bacteria in association with airborne particulate matter (PM) in the outdoor and indoor air of two hospital wards. Materials and methods: The GRIMM 1.109 dust monitor and the Andersen one-stage viable impactor were used for particle counting and bioaerosol sampling, respectively. Results: The average levels of airborne bacteria sampled from outdoor air were 33 colony-forming units (CFU/m3), and in the air samples of medical and infectious disease wards, they were 76 and 85 CFU/m3, respectively. Staphylococcus spp. and Acinetobacter spp. were the most prevalent bacteria in the samples. Statistical analysis showed a significant association between PM2.5, and PM10 particle mass concentrations and airborne bacteria concentrations in indoor air samples (P-value < 0.05). Conclusion: Some bacterial agents of HAIs existed in hospital air and may be problematic for immunocompromised patients. Higher levels of bacteria in indoor air compared to outdoor air may indicate that the bacteria were of indoor origin, such as the presence and activities of people. Moreover, the results showed that particle counting may be a useful tool for airborne bacteria monitoring.

This research presents a case study that employs the Fuzzy Ordered Weighted Averaging (FOWA) method to develop mineral prospectivity/potential maps (MPM) for the Chahargonbad district in southeastern Iran. The primary objective of the study is to uncover intricate and concealed relationships between various evidence layers and known ore occurrences through a comprehensive analysis of multi-disciplinary geospatial data. Consequently, thirteen evidence layers were meticulously derived from existing databases, encompassing geological, geochemical, geophysical, and remote sensing data, which were then integrated using the FOWA multi-criteria decision-making approach to delineate favorable zones for porphyry Cu mineralization.The FOWA methodology employs a diverse array of decision strategies to synthesize input geospatial evidence by incorporating multiple values for an alpha parameter. This parameter serves as the cornerstone of the algorithm, influencing experts' perspectives on MPM risk. The methodology generates seven mineral potential maps to identify the most suitable one(s). By considering a prediction-area plot for data-driven weight assignment to each evidence map, the hybrid FOWA outputs were scrutinized to pinpoint the most appropriate map for targeting significant Cu occurrences. The resulting synthesized evidence map indicates an ore prediction rate of 77%, with known Cu deposits primarily located within favorable zones occupying 23% of the entire district area.

The objective of petrophysical studies is to assess the quality of hydrocarbon reservoir layers and to zone the reservoir for identifying optimal zones for exploitation and informed development of oil fields. In some regions, there are zones that exhibit lower electrical resistivity values than their actual values. These low-resistivity zones are often identified through petrophysical investigations and conventional well logs, where water saturation levels are estimated higher due to their reduced resistivity. These zones, despite their hydrocarbon potential, are often neglected during production cycles. To overcome this challenge, nuclear magnetic resonance (NMR) logging tools can be employed to provide accurate estimations of free fluid saturation, irreducible fluid saturation, permeability, and effective porosity in such low-resistivity zones, making them more identifiable.In this article, we utilized conventional well logs and NMR log from the A well in the Sarvak reservoir of one of the oil fields in southwestern Iran. Based on the obtained results, depth interval 9586 to 9783 ft in the Sarvak Formation, along with two intervals (10661-10815 ft) and (10830-11063 ft) in the Int zone, were identified as potential low-resistivity zones in the reservoir. By analyzing the high-resistivity logs, water saturation percentage was calculated for these zones, and the results from NMR logging confirmed their favorable reservoir potential (e.g., free fluid saturation, effective porosity, viscosity, and permeability).Furthermore, to extend the petrophysical parameters, such as free fluid saturation and porosity, throughout the entire hydrocarbon field, various approaches including single- attribute methods, multi attribute methods, and neural networks were evaluated. The neural network method demonstrated higher accuracy in determining the parameters. Ultimately, the values of porosity and free fluid saturation in the study area were determined with 91% and 95.8% matching accuracy, respectively. The final results were validated using unseen data, and the high precision of the obtained results was confirmed.

Abstract In order to achieve proper water consumption efficiency in micro-irrigation systems, the space and flow rate of the drippers should match the hydraulic characteristics of the soil and the time and amount of plant irrigation water. As a result, having proper information about the width and depth of the wetted soil (wetting volume) is essential for the design, planning, and proper management of drip irrigation systems. The aim of this study was to obtain a set of semi-empirical relationships for more accurate and easier estimation of the diameter and depth of the wetting front. Field data of drip irrigation systems were collected by wet front detector (WFD) installed in three different conditions in terms of soil texture and flow rates of 4 and 8 L/h. Due to the technical problems and errors in the measurement of saturated hydraulic conductivity, which is the main representative of soil properties, the relationships presented here estimate the dimensions of the wetted soil volume based on the infiltration time and the volume of water stored in the reservoir. No need for hydraulic conductivity of the soil. The equations obtained in this research predict the diameter and depth of the wetted soil volume with a correlation coefficient of 89 and 98%, respectively.

Abstract This research aims at investigating the idea of anti‐bacterial self‐healing coatings based on polyurea formaldehyde microcapsules (MCs), with the repair agent being ZnO‐containing linseed oil. ZnO nanoparticles were added to the repair agent with the idea of developing an antibacterial coating. The idea was to entrap some ZnO nanoparticles inside microcapsules, aiming for some local release of ZnO nanoparticles where the coating is damaged. The corrosion resistances of the coatings were studied using the Tafel polarization test. The structure of the coating samples was evaluated using a scanning electron microscope. To check the antibacterial properties of ZnO‐containing self‐healing samples, Escherichia coli and Staphylococcus aureus bacteria were used. Results showed that ZnO nanoparticles were distributed not only inside microcapsules but also over the walls, inferring that overall protection can also be attained in addition to local anti‐bacterial performance. Results showed that the proposed multi‐functional coating has promising antibacterial and self‐healing responses.

Fractures are one of the most important geological features that affect production from most carbonate reservoirs. A large amount of the world’s hydrocarbon resources are located in fractured reservoirs and the identification of fractures is one of the important steps in reservoir development. Due to the high cost of tools that are used in the petroleum industry to identify fractures such as image logs, and their inaccessibility in most of the studied areas, it is often tried to use other available data to identify fractures. Due to the ever-increasing progress of data-driven methods such as neural networks and machine learning, this study has tried to apply a 1D-Convolutional Neural Network (1D-CNN) which is one of the deep learning algorithms on well-logging data and seismic attributes in a carbonate reservoir to identify the existing fractures in the investigating area. The approach used in this research is a binary classification which is applied first in the well location. To validate the method, results are compared with the reports obtained from image logs. Finally, the fracture density map is drawn in the entire reservoir area.

Abstract Diabetes, a major non-communicable disease, presents challenges for healthcare systems worldwide. Traditional regression models focus on mean effects, but factors can impact the entire distribution of responses over time. Linear mixed quantile regression models (LQMMs) address this issue. A study involving 2791 diabetic patients in Iran explored the relationship between Hemoglobin A1c (HbA1c) levels and factors such as age, sex, body mass index (BMI), disease duration, cholesterol, triglycerides, ischemic heart disease, and treatments (insulin, oral anti-diabetic drugs, and combination). LQMM analysis examined the association between HbA1c and the explanatory variables. Associations between cholesterol, triglycerides, ischemic heart disease (IHD), insulin, oral anti-diabetic drugs (OADs), a combination of OADs and insulin, and HbA1c levels exhibited varying degrees of correlation across all quantiles (p 0.05), it was found to be significant in the higher quantiles (p

The Birjand region is a part of the South Khorasan province, situated in the structural-magmatic zone of eastern Iran. As a part of the continental shelf, it forms from subduction during the Cenozoic and subsequent continental collisions. This region is favorable for copper and gold mineralization for various geological reasons. The ultimate goal of this study is to create a Cu geochemical potential map to delimit prone regions for further mining activities. A total of 2468 geochemical samples were gathered to run a 20-element analysis. Taking data preprocessing approaches such as correction of outlier data and data normalization into consideration, a fractal graph through Concentration-Number (C-N) model was produced to isolate different geochemical populations of Cu, Pb, Zn, Ag, Ba, and Ni for Cu targeting. Then, a Prediction-Area (P-A) graph was plotted for each geochemical variable to determine the weight of each evidence map. The results show that Barium map indicates a prediction rate of 72% and specifying 28% of the studied areas as mineralization prone areas. The zinc geochemical map presents an ore prediction rate of 65% and 35% of area as potential zone. In addition, copper with an ore prediction of 56% covered 44% of the Birjand region. Finally, a hybrid evidence map was overlaid. Accordingly, the geochemical potential areas are further located towards the south and south-east of Birjand, which are closely related. Moreover, there are highly favorable areas in the middle part. It is noteworthy that the copper potential map has higher efficiency over each individual geochemical evidence, with an ore prediction rate of 75% and occupying 25% of the area as favorable zones.

One of the specific features of porphyry copper (Cu) mineralization is the distinct occurrence of hydrothermal alteration zones, which can be mapped by processing various satellite images. Among free multispectral images, Landsat 8 OLI and ASTER data are known to be efficient in mapping different geological features, such as alteration zones and tectonic lineaments. This study aims to show the potential of these data types in mapping porphyry Cu mineralization by proposing a framework for employing and integrating different image processing methods. These methods include principal component analysis (PCA), spectral angle mapper (SAM), and matched filtering (MF) employed on these satellite images to map target al.teration zones. Moreover, PCA and directional filtering are applied to the ASTER dataset to enhance and map structural features. The results are evaluated and then combined to provide a potential map of Cu mineralization in the Chahargonbad area, located within the Urumieh-Dokhtar magmatic belt (UDMB) in Kerman province, Iran. The prediction-area plot and normalized density, which are data-driven methods, are used to assign the relative weight of each layer and evaluate them. Finally, using the calculated weights, data-driven multi-index overlay (DMIO) and fuzzy ordered weighted averaging (FOWA) methods are applied to combine the evidential layers. The potential mineralization maps created by the DMIO and FOWA provide a prediction rate of 80% and 82%, respectively. Furthermore, the accuracy of the integrated maps is investigated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curves. The AUC scores obtained from the ROC curves of DMIO and FOWA methods are 0.85 and 0.88, respectively, representing powerful positive spatial relationships with mineralization areas. Based on the results, the proposed framework can be applied to provide a potential map of porphyry Cu mineralization, particularly in arid regions, with reasonable accuracy.

In the last few decades, in many research fields, different methods were introduced to discover groups with the same trends in longitudinal data. The clustering process is an unsupervised learning method, which classifies longitudinal data based on different criteria by performing algorithms. The current study was performed with the aim of reviewing various methods of longitudinal data clustering, including two general categories of non-parametric methods and model-based methods. PubMed, SCOPUS, ISI, Ovid, and Google Scholar were searched between 2000 and 2021. According to our systematic review, the non-parametric k-means Clustering Method utilizing Euclidean distance emerges as a leading approach for clustering longitudinal data This research, with an overview of the studies done in the field of clustering, can help researchers as a toolbox to choose various methods of longitudinal data clustering in idea generation and choosing the appropriate method in the classification and analysis of longitudinal data.

In integrating geospatial datasets for mineral potential mapping (MPM), the uncertainty model of MPM can be inferred from the Dempster – Shafer rules of combination. In addition to generating the uncertainty model, evidential belief functions (EBFs) present the belief, plausibility, and disbelief of MPM, whereby four models can be simultaneously utilized to facilitate the interpretation of mineral favourability output. To investigate the functionality and applicability of the EBFs, we selected the Naysian porphyry copper district located on the Urmia – Dokhtar magmatic belt in the northeast of Isfahan city, central Iran. Multidisciplinary datasets- that are geochemical and geophysical data, ASTER satellite images, Quickbird, and ground survey- were designed in a geospatial database to run MPM. Implementing the Dempster law through the intersection (And) and union (OR) operators led to different MPM performances. To amplify the accuracy of the generated favourability maps, a combinatory EBFs technique was applied in three ways: (1) just OR operator, (2) just And operator, and (3) combination of And and OR operators. The plausibility map (as mineral favourability map) was compared to Cu productivity values derived from drilled boreholes, where the MPM accuracy of the hybrid method was higher than each operator. Of note, the success rate of the hybrid method validated by 21 boreholes was about 84%, and it demarcates high favourability zones occupying 0.67 km2 of the studied area.

The effects of different filler metals on the microstructure and mechanical properties of buttered API X65/AISI 304L stainless steel dissimilar joint have been investigated. The use of a butter layer and a suitable filler metal have major implications for the properties of dissimilar joints. In this study, API X65 high-strength low-alloy (HSLA) steel was first buttered with an austenitic Ni-based ERNiCr3 layer, followed by a post-weld heat treatment (PWHT) at 650 °C. ER308L (W308), ER309L (W309), and ERNiCr3 (WNiCr3) filler metals were then used to join the buttered API X65 side to AISI 304L stainless steel. All joints were first evaluated by radiographic testing to make sure that a flawless weldment has been attained. A scanning electron microscope (SEM), an optical microscope (OM), and energy-dispersive X-ray spectroscopy (EDS) were used to study microstructures of joints. Standard-sized and sub-sized tensile and impact tests were carried out. Microhardness profilometry was also conducted across the joint. Results showed that the finest grain structure was attained in the heat affected zone (HAZ) at the AISI 304L side and the lowest δ ferrite content was achieved in samples with the filler metal ERNiCr3 (WNiCr3). It appears that the heat input, generated by WNiCr3 filler metal, is comparatively lower than those generated in W308 and W309 samples. WNiCr3 weldment showed the highest hardness due to the formation of fine carbide particles such as NbC and TiC. Results of sub-sized impact tests showed that the highest impact energy was attained in the HAZ of the WNiCr3 sample.

Background: Coronavirus disease 2019 (COVID-19) has a high rate of mortality, but data regarding its prognosis are scarce. This study aimed to identify the risk factors associated with mortality and survival of COVID-19 patients in a southern province of Iran. Materials and Methods: This was a cross-sectional study with a secondary database of 3172 people who were admitted to hospitals for COVID-19 treatment. Relative risk (RR) was computed to estimate mortality risk between groups, and the log-rank test was used to compare the survival functions in different levels of categorical variables. Finally, the multivariable extended Cox model was employed to determine the factors that affected the survival of COVID-19 patients. Results: The 10- and 15-day survival rate of 3172 patients was 89% and 80%, respectively, and the median survival time was 30 days. Based on the extended Cox model, age, oxygen therapy, intensive care unit (ICU) admission, invasive ventilation, chronic cardiac disease, chronic kidney disease, and cancer were the most important variables affecting the survival of COVID-19 patients. Conclusion: Older people (older than 40 years) and those with comorbidities (e.g., chronic cardiac disease, chronic kidney disease, and cancer) had a higher mortality rate; therefore, health-related organizations need to plan for the prevention and early detection of comorbidities to reduce the burden of diseases such as the pandemic of COVID-19 as much as possible in the future.

A pressure maintenance strategy is crucial in reservoir management, especially in single-phase oil reservoirs, to keep the reservoir pressure above the bubble point. Water injection is a common way to prevent pressure decline due to production. Water may be injected into oil zone and/or aquifer. Analytical and semi-analytical methods are applied to analyze the reservoir response and pressure alteration during the water injection and pressure maintenance operation. Capacitance- Resistance Model (CRM) is a well-known semi-analytical method to predict oil production by water flooding.In this work, Static Capacitance- Resistance Model (SCRM) in which time constant parameter is unique value in whole matching duration has been applied to estimate water injection in the reservoirs with charging aquifer; in addition to, our aim is analytical investigation of water injection performance in the aquifer zone. As a matter of fact, SCRM has been coupled for the reservoir and aquifer in which SCRM has been written for a reservoir and an aquifer zone as two independent porous medium. Consequently, SCRM has been developed to estimate pressure maintenance performance in the cases of charging aquifer; moreover, new parameter is defined as pressure difference between aquifer and reservoir transition zone (DP) is added to SCRM tuning parameters that can indicate flow and reverse flow between reservoir and aquifer.This parameter is a water saturation-dependent function considered as another tuning parameter. Two synthetic reservoirs were simulated in this work, including homogenous and streak cases with nine spot patterns. The developed SCRM has shown acceptable accuracy, of which 6.1% of total absolute error was obtained for the homogenous case and 7.5% for the streak case.

This paper investigates the idea of using Cu/CNT composite interlayer in the transient liquid phase (TLP) bonding of Ti–6Al–4V/AISI 304 stainless steel. In this investigation, initially TLP was carried out using a pure copper interlayer at 900, 950 and 1000 °C with the holding time 60 min. The TLP joining was then carried out at 900 °C with Cu/CNT interlayer, with the CNT weight percent, ranging from 0 to 3%. CNT was deposited on Cu foils, using electrophoretic deposition technique. Microstructure and mechanical properties of the joints were investigated with optical/electron microscopes, microhardness, and shear tests. Results showed that the interface microstructure can be divided into athermal solidification zone, isothermal solidification zone, and diffusion affected zone. The phase structure and compositions in CNT-containing samples are relatively similar to TLP samples with pure Cu interlayer. Results showed that CNT addition has expanded the diffusion areas and facilitated the diffusion across the interface. CNT addition up to 3 wt. % resulted in a significant increase in hardness up 500 VHN. The increase in hardness in the joint area can be related to the presence of various intermetallic compounds at the TLP region. The correlations between mechanical properties and microstructure and the implications of CNTs for mechanical properties of the joints are discussed.

Background and Objective: Resilience is the process of coping and successfully adapting to challenging and life-threatening situations which is a kind of positive adaptation to adverse conditions. One of the most serious challenges in the industry is maintaining the health and safety of employees while performing their job duties. The present study aimed to quantitatively evaluate resilience engineering indicators in the metal industries of Kashan, Iran, and prioritize using the AHP method. Materials and Methods: The present cross-sectional study had two stages. First, the resilience questionnaire was distributed among 110 employees of six metal industry companies in Kashan by convenience sampling method. In the second stage, a questionnaire consisting of 6 questions was completed by 15 occupational health and metal industry experts and then the prioritization of resilience indicators was determined using hierarchical analysis. Expert choice software was used to determine the priorities. The total resilience score was calculated and statistically compared by t-test and ANOVA after weighting. Results: The results indicated that the six main indicators of emergency preparedness, management commitment, reporting culture, awareness, learning culture, and flexibility with a final score of 0.921, 0,852, 0.517, 0.513, 0.485, and 0. 428 were ranked first to sixth. Conclusion: Emergency preparedness and management commitment were the most important indicators and the total resilience score in the metal industries of Kashan was 0.619.

Introduction: Patients with Tuberculosis (TB) still have barriers in accessing high quality care and treatment services. In this qualitative study, we investigated barriers in accessing TB health services including confirmatory diagnosis, treatment adherence and recurrence of pulmonary TB using patients, physicians, and policy makers point of view. Materials and methods: In this qualitative research from November to March 2021, 3 policy makers from the Ministry of Health, 12 provincial TB experts and physicians from the TB control program and 33 patients diagnosed with TB from 4 provinces were enrolled for a semi-structured in-depth interview. All interviews were audio recorded and then transcribed. Framework analysis was done by MAXQDA 2018 software to identify key themes. Results: Several barriers reported for TB care and treatment: Poor knowledge of patents about TB symptoms, failure to screen for TB among at-risk patients by physicians, similar symptoms between TB and other lung diseases, low sensitivity of TB diagnostic tests, incomplete case finding and contact-tracing, stigma related to TB, and patients poor adherence due to long TB treatment. In addition, COVID-19 pandemic disrupted TB services and decreased detection, care and treatment services for TB patients. Conclusion: Our findings highlight the need for interventions to increase public and healthcare providers awareness about TB symptoms, using more sensitive diagnostic tests, and interventions to reduce stigma, and improve case finding and contact tracing effort. Improving patients’ adherence required better monitoring and shorter effective treatment regimes.

Background: Bayesian mixture cure rate frailty model is a model used in survival analysis by controlling frailty when the fraction of cured individuals exists. The present study was performed as the first systematic review in survival analysis with cure fraction. The aim of this systematic review was to study and evaluate the related studies on Bayesian mixture cure rate frailty model. Also, this model was used to demonstrate its importance and applicability in determining the variables affecting the survival of patients with gastric cancer.Methods: This systematic review was done based on the PRISMA guideline by considering related searching keywords in PubMed, Scopus, Science Direct, Web of Science, and Google Scholar. Also, Bayesian mixture cure rate frailty model was used to analyze gastric cancer data.Results: In the beginning, 882 studies related to survival analysis of cure rate model were found. Finally, by reading the full-text, only 4 related studies were found based on the inclusion and exclusion criteria. In these studies, semi-parametric models and parametric model with Weibull distribution were used for time-to-event data. Also, based on the results of the model, significant and affective variables on the survival of patients with gastric cancer were found.Conclusion: According to the results of this study, in the cure model, choice of proper distribution for the frailty variable and baseline distribution can influence the results. It was also found that place of residence, chemotherapy, morphology, and metastasis are effective variables on survival of patients with gastric cancer.

Introduction: Workers' health status is one of the main factors affecting industry productivity. Therefore, effective employee periodic examinations are important not only for the benefit of industries and for improving the health of workers but also for the health of the community. Methods: This descriptive study was done in98 on 60 cases of industries of Kashan that they had occupational health expert. The tools were occupational medicine items Ministry of Health checklists after weight by Analytical Hierarchy Process. Data were analyzed by SPSS 21 software. Results: Assessing the occupational medicine status of Kashan industries with this checklist showed that according to cut-off point 70, 18 industries (30% of the industries) scored poorly. Results of linear regression analysis showed that there is a significant relationship between work experience of occupational health experts with occupational health status of industry (P

This work presents a hybrid-based clustering approach for mineral potential mapping (MPM) of porphyry-type Cu mineralization at Kerman province in the SE of Iran. Whereby a multidisciplinary geospatial data set was processed and integrated in the Chahargonbad district. Data-driven prediction-area (P-A) plots were drawn for each evidence layer derived from geological, geochemical, geophysical and satellite imagery data. The P-A plots provide insight into the weight of evidence for synthesizing all geospatial layers. Out of many knowledge-driven methods which biasing from experts' opinions, index overlay and fuzzy operators were employed to find out an optimum Cu favorability map through calculating an efficiency index representing the performance of each MPM. A concentration-area (C-A) fractal model was implemented to separate the mineral favorability map into some populations to ensure correct determining the cluster numbers. Clusters number is a prerequisite which must be defined correctly to increase the performance of clustering analysis for generating reliable results in MPM. Such an appropriate number of clusters can be incorporated in running three prevalent groups of clustering methodologies as data-driven approaches in MPM. They are self-organizing map, fuzzy c-means, and k-means algorithms. One of the reasons for this tendency to consider a hybrid-based method is that it overcomes the shortcomings of the both methods (bias of experts’ opinions and unknown clusters number) in mineral favorability mapping. The unknown number of clusters was determined through a knowledge-driven method, and then it was passed to an unsupervised data-driven method, i.e. clustering algorithm. This hybrid method produces synthesized maps in close association with known porphyry-Cu mineralization in the Chahargonbad area.

Background: This study highlights the effect of nonlinear and linear teaching methods and inclusive education on the self-esteem and motor proficiency of ordinary and overactive children. Methods: This quasi-experimental research involved two groups of girls who had a 9-week intervention. One group consisting of 14 ordinary children (M age= 6.53, SD age= 0.49) with one overactive and obese child (age =6 years, height=115 cm and weight =27 kg) were trained using nonlinear pedagogy. The other group comprising of 14 ordinary children (Mage= 6.58, SD age= 0.52) and one overactive obese child (age =6 years, height=117 cm and weight =28 kg) were trained using a linear method. Quantitative and qualitative instruments were used to collect data. Results: The qualitative results showed control of violence and pleasure of the game, as well as family, educational and social relationships, improved in the obese and overactive child who practiced with the nonlinear pedagogy. Quantitative results indicated that general, family, social and school self-esteem, and motor proficiency increased, but BMI decreased in both children with ADHD. The result of the ANCOVA test indicates that self-esteem (P= 0.000, F=27.88) and motor proficiency (P= 0.001, F=15.7) improved in the nonlinear pedagogy compared to the linear method. Conclusion: Results emphasized the importance of applying nonlinear pedagogy for motor skills development and in inclusive education to enhance physical activity participation for children with Attention deficit hyperactivity disorder (ADHD). Findings make a strong case for manipulating tasks and eliminating environmental constraints in inclusive settings to develop motor skills of all children.

Introduction: The current gait profile of children with attention deficit-hyperactivity disorder (ADHD) is incomplete and mainly based on a short-time walking without the involvement of different senses. The aim of this study was to investigate the dual-task gait of ADHD and typically-developed (TD) children while receiving sustained visual-vestibular stimulus.Materials and Methods: 21 children with ADHD and 12 TD children (7-10 years) participated in the study. Participants walked on the treadmill in three self-selected speeds three-minute trials in single-task (without visual instructions) and dual-task (simultaneously following visual-vestibular saccade and smooth pursuit stimuli) conditions. Stride length, global angle of the dominant leg, step width, and the variability of these parameters were assessed using a factor analysis of variance at significant level of α = 0.05.Results: The effect of group-stimulus interaction on stride length was not significant (P = 0.860), but its variability was significant [less variability for typical children compared to children with ADHD (P = 0.001)]. The interactive effects on the global angle were significant (P = 0.001), but its variability was not significant (P = 0.720). In without instruction and in smooth pursuit conditions, significant ankle rotation was observed in children with ADHD (P = 0.001) compared to that of typical children. Step width (P = 0.001) and its variability (P = 0.003) were significantly affected and typical children had wider walking with less variability than the other groups (P = 0.001).Conclusion: Different visual-vestibular instructions can affect the gait of the children with ADHD in various ways. These results can be considered as a basis for the integration of dualistic and synergy models and guidance for educators of children with ADHD.

Background: The health of patients with weakened immune systems is endangered by presenting of bacteria and fungi in the internal units of hospital as well as development of nosocomial infections in them. The current article aimed to investigate the bacterial and fungal contamination degree in internal units and outdoor of the hospital in which some points are mainly considered such as the nosocomial infections and the discussion of improving the quality of hospital spaces and providing appropriate conditions to maintain the health of patients. Materials and Methods: This study is a cross sectional study conducted in Kashan Beheshti hospital in 2018. Air sampling is done by direct bacterial sampler (Quick Take 30) along with identification of type and the number of fungi and bacterial colonies including 180 samples from internal units and outdoor spaces. Data was analyzed statistically by SPSS 22, EXCELL and BONFERRONI test. Results: The obtained results from 180 samples showed that bacterial and fungal contamination among 180 samples was 97% and 47.8%, respectively. Also, the most bacterial and fungal contamination presented in medical units and outdoors, respectively. Conclusion: The results revealed that the micro-organism concentration in internal units is more than in outdoors that results can be related with the presence of the patients, air conditioning and inappropriate cleaning. For this reason, improving sanitation standards and setting the appropriate air-conditioning are suggested in internal units of the hospital.

Background:Cardiovascular diseases are still among the most important causes of death in different countries. There are several risk factors for the onset of this disease. The rating of these risk factors is very important for informing the community and planning for the future.Methods: Linear regression is one of the classic statistical methods that has many applications in medical sciences. When dealing with fuzzy data, it is not possible to use linear regression. The use of angiography to estimate the extent of congestion is associated with an estimate of more or less stenosis and the increase of atherosclerosis. Hence, this variable has been considered as a fuzzy variable. Fuzzy linear regression (FLR) was used to rank and compare the known risk factors for coronary artery occlusion.Results:After analyzing the data by least squares FLR, the most important risk factors included Family history, history of diabetes, age, history of hypercholesterolemia, history of cigarette smoking, Body Mass Index and history of hypertension respectively.Conclusion: When it is not possible to calculate the response variable or one of the independent variables examined in the model accurately, FLR, or to be more precise, regression in fuzzy environment can be a good alternative for conventional regression analysis.

Introduction: The identification of the factors affecting the physical performance and development of childrenchr('39')s motor skills can be of great importance in participating in physical activities, preventing overweight and obesity, as well as identifying and guiding the top talented children in sport. Therefore, this study aimed to investigate the effect of different ACE (I/D) and ACTN-3 (R/X) genotypes on some factors of physical fitness and motor skill performance in children. Materials & Methods: The statistical population of this study included 6-8-year-old school children in Tehran, Iran. In total, 50 cases were selected randomly using the cluster-sampling method. The data were collected using the Physical Fitness Test, Test of Gross Motor Development-Third Edition (TGMD-3), and PCR for the determination of ACE and ACTN-3 polymorphism. Furthermore, a one-way analysis of variance and independent t-test were used to analyze the study data. A p-value less than 0.05 was considered statistically significant. Ethics code: IR.KHU.REC.1399.010 Findings: The results showed that children carrying allele D of ACE gene, (DD or ID genotype), compared to those with II genotype (P0.05). Discussions & Conclusions: According to the results of the study, it can be said that the children carrying DD or ID genotype of ACE and RR or RX genotype of ACTN-3 had a higher level of physical development and consequently higher levels of locomotor skill performance. Therefore, if they are provided with desirable environmental conditions, they will be able to do sport skills accompanied by higher levels of performance.

Salt rocks have one of the most complex behaviors among different rock types due to their creep behavior. Creep in rocks can cause a lot of undesired displacenments imposing tremendeous rehabilitation and maintenance costs to the projects. Creep depends on many factors such as rock type, stress level, and boundary conditions in order for rock to move freely. Amongst intrinsic factors in the rock type, the impurity of salt samples (either in gas, liquid, and/or solid form) is one of the least studied factors. This study aims to present the influence of impurity on the creep behavior of the salt rocks of the Hormuz series, as the case study. This series is one of the oldest evaporitic deposits in the world resulted in more than 350 salt domes in Iran and other parts of the Middle East. Unfortunately, there has been no comprehensive rock mechanics study on the Hormuz salt rocks so far. In this study, a few recovered cores were obtained and prepared from the exploration boreholes drilled in this formation, and the creep parameters were determined using laboratory tests. Also, the effect of impurity percentage on the creep properties of the Hormuz salt rocks was investigated. Since in salt rock masses the purity percentage is different, impurity affects the creep behavior. The tested samples were categorized into seven different groups, based on the quantity of the impurity, which consists mainly of anhydrite and quartzite. Laboratory tests showed that the uniaxial compressive and tensile strength values increase by increasing the solid impurity in the samples. In contrast, the maximum and instantaneous strains reduce by increasing the percentage of impurities in different stages of the creep test. Increasing the amount of impurity in pure samples led to increasing Burger's parameters. Also, it was observed that obtaining creep parameters from laboratory test results with mathematical approximation method had fewer errors compared to the manual method explained by Goodman. This is worth for the development of underground mining operations in salt structures. Accurate recognition of creep properties might have a considerable impact on the design as well.In the present study, the effect of impurity percentage is investigated on the creep properties of Hormuz salt rock. Because in salt rock masses, purity percentage is different, impurity and its amounts affects creep behavior. The tested samples were categoried into seven different groups based on the quantity of the impurity (which consists mainly of anhydrite and quartzite). Laboratory tests showed that the uniaxial compressive strength and tensile strength increase by increasing solid impurity in the samples. In contrast, the maximum strain and instantaneous strain reduce by increasing the percentage of impurities in different stages of creep test. Increasing amount of impurity in pure sample led to increasing Burger's parameters. Also it was observed that obtaining creep parameters from laboratory test results with mathematical approximation method has less error than the manual method explained by Goodman. This might be worth noticing because for development of underground mining operations in relation with salt structures, accurate recognition of creep properties might have considerable impact on the design.

Motor Imagery provides a special context for representation of movements. This feature has been investigated in typical developing children in several studies, but there is little information in the field of motor imagery in children with autism. Therefore, the aim of the present study was to investigate this component in children with autism spectrum disorder aged 8 to 12 years compared to typical developing peers. 40 ASD children and 40 TD children who were age and IQ matched, purposefully and available selected and participated in the research voluntarily. To investigate motor imagery, the hand rotation paradigm in 3D software was used. The task involves two blocks of 12 hand-pattern which rotates randomly three times at six angles. The reaction time and error numbers were recorded as the performance scores of each subject. In order to analyze the data, two analysis of variance tests were used to evaluate and compare the reaction times and the U-man Whitney test used for the number of errors separately for back and palm view of hand. The findings confirmed that children with autism are able to use this feature same TD, although this operation is less accurate and longer. So that in the reaction time and the number of error variables, the ASD group performed worse than TD peers. Although the disorder may effect on cognitive function underlying motor behaviors in these children, nevertheless the capacity required to learn and develop motor skills in these children is developed, usable, and exploitable.

Introduction: There are significant interactions between motor and cognitive development through life span. Investigation of cognitive processes and behavioral infrastructure is very valuable, so the present study aimed to determine the developmental changes of motor imagery in typical and high functioning autism spectrum disorder children aged 8 to 12 years. Methods: The present study was a semi- quasi one that done in a cross - sectional design. 40 children aged 8 to 10 and 40 children aged 10 to 12 years (in each age group 20 autism spectrum disorder (ASD) and 20 typical development (TD), who matched in terms of age and IQ, were selected purposefully and accessibly selected and participated in the research voluntarily. To investigate the motor imagery, the hand rotation paradigm was used in the form of 3-D software. After calculating the reaction time and the number of errors related to the medial and lateral stimuli, repeated measures ANOVA used to analyze the reaction time data and the Mann Whitney U test used to analyze the error numbers data. All statistical tests were performed using SPSS software version 21. Results: The findings showed that the typical development (TD) group decreased its reaction time (P=0.001) and number of errors (P=0.001) by age increasing, which was not seen in the autism spectrum disorder (ASD) group. Conclusion: It seems that the cognitive and important processes involved in learning and controlling motor skills will not improve by age and will require specialized interventions and coherent programs for this purpose.

Introduction: Since occupational diseases are costly and have a direct impact on workers’ health, their identification and investigation are necessary. The purpose of this study was to investigate changes in the results of periodic occupational examinations and their effective factors over the last four years in Steel Industry of Kashan City. Methods: This longitudinal study was conducted in a steel company in 2018. In order to investigate the changes, the results of periodic occupational examinations in this company were reviewed from 2014 to 2018. Blood pressure, blood glucose, audiometry, optometry, spirometry, and liver enzymes were evaluated. The results of medical records were analyzed by SPSS software version 21. Results: The mean age, work experience, and body mass index of participants were 19.19 years, 9.45 years, and 27.58, respectively. The results showed that the most common disease was hearing loss. High levels of glucose and high cholesterol increased dramatically over the studied period. A significant difference was observed between AST and ALT in 2014 (P

IntroductionCutaneous leishmaniasis (CL) is currently a health problem in several parts of Iran, particularly Kerman. This study was conducted to determine the incidence and trend of CL in Kerman during 2014-2020 and its forecast up to 2023. The effects of meteorological variables on incidence was also evaluated.Materials and methods4993 definite cases of CL recorded from January 2014 to December 2020 by the Vice-Chancellor for Health at Kerman University of Medical Sciences were entered. Meteorological variables were obtained from the national meteorological site. The time series SARIMA methods were used to evaluate the effects of meteorological variables on CL.ResultsMonthly rainfall at the lag 0 (β = -0.507, 95% confidence interval:-0.955,-0.058) and monthly sunny hours at the lag 0 (β = -0.214, 95% confidence interval:-0.308,-0.119) negatively associated with the incidence of CL. Based on the Akaike information criterion (AIC) the multivariable model (AIC = 613) was more suitable than univariable model (AIC = 690.66) to estimate the trend and forecast the incidence up to 36 months.ConclusionThe decreasing pattern of CL in Kerman province highlights the success of preventive, diagnostic and therapeutic interventions during the recent years. However, due to endemicity of disease, extension and continuation of such interventions especially before and during the time periods with higher incidence is essential.

Background: Logistic regression is one of the most common models used to predict and classify binary and multiple state responses in medicine. Genetic algorithms search techniques inspired by biology have recently been used successfully as a predictive model. Objective: The aim of this study was to use the genetic algorithm and logistic regression models in diagnosing and predicting factors affecting breast cancer mortality. Method: In this study, data of 2836 people with breast cancer during the years 2014-2018 was examined; their information was recorded in the cancer registration system of Kerman University of Medical Sciences. Death status was considered a dependent variable, while age, morphology, tumor differentiation (grad), residence status, and place of residence were considered independent variables. Sensitivity, specificity, accuracy, and area under the ROC curve were used to compare the models. Results: the logistic regression model determined factors affecting the breast cancer mortality rate, (with sensitivity (0.62), specificity (0.81), area under the ROC curve (0.74), and accuracy (0.84)), and genetic algorithm model (, with sensitivity (0.19), specificity (0.97), area under the ROC curve (0.58) and accuracy (0.87)). Conclusions: The sensitivity and area under the ROC curve of the logistic regression model were higher than those of the genetic algorithm, but the specificity and accuracy of the genetic algorithm were higher than those of the logistic regression. According to the purpose of the study, two models can be used simultaneously.

This study presents a failure analysis in two reformer tubes used for hydrogen production in a petrochemical industry. These tubes (Tube A and Tube B) were made by the centrifugal casting of HP-Nb alloy in such a way that one contained titanium as a micro-element, and the other was free from titanium in its chemical composition. Although the two tubes were subjected to similar creep conditions, Tube A failed after only 46,000 h of operation against the design life of 100,000 h. SEM images showed initiation and growth of creep pores next to chromium carbide particles, as well as the formation of microcracks in Cr23C6 carbides. Pore initiation occurs as a result of grain boundary sliding and is strongly dependent on structural morphology. The tube containing titanium (Tube B) showed higher thermal stability and higher creep resistance than the tube without titanium (Tube A), which was due to the formation of finer and more discrete carbide particles. The final fracture of the tube without titanium (Tube A) occurred due to the coalescence of creep pores and the creation of grain boundary cracks.

Background: In December 2019, the spread of a new infectious disease was reported in Wuhan, caused by a new coronavirus named COVID-19 by the World Health Organization. This study aims to compare the dispersion of COVID-19 disease among four Iranian cities in North Khorasan named Bojnord, Farooj, Jajarm, and Shirvan. Materials and Methods: This cross-sectional study includes information about the daily morbidity and mortality of COVID-19 in 1124 patients from March to May 2021. The analysis of variance method, Scheffe post hoc technique and Leven's test are used to compare the means and the variances of daily morbidity and mortality of these cities. Finally, the coefficients of variation (CVs) of the morbidity and mortality are compared. Results: The means of daily morbidity in Bojnord, Farooj, Jajarm, and Shirvan cities are 6.387, 0.946, 1.150, and 2.193, respectively. Furthermore, the means of daily mortality in Bajnourd, Farooj, Jajarm, and Shirvan are 0.763, 0.193, 0.161, and 0.290, respectively. The means and the variances of both daily mortality and morbidity are significantly different in all four cities (P < 0.05). Furthermore, CVs of daily morbidity in the cities of Bojnord, Farooj, Jajarm, and Shirvan are 0.665, 1.026, 1.032, and 0.787, respectively. The CVs of daily mortality in these cities are 1.196, 2.052, 2.468, and 1.728, respectively. The CVs of both daily mortality and morbidity are significantly different in all four cities (P < 0.05). Conclusion: The ratio of CVs is a good option for comparing the spread of COVID-19 in different regions with different means and variances.

Introduction: Noise is one of the most common and harmful physical factors in the working environment and has physical and psychological effects on individuals. In this study, the audiometry results of industrial workers were modeled and the effect of noise and other factors on hearing loss was examined. Materials and Methods: This was a longitudinal study based on the records of workers who had worked over 10 years in the industry and had recorded audiometries since their employment. Data was analyzed through linear mixed models. Results: During each year of noise exposure, hearing loss was 1.9 db at 4000 Hz; 0.059 in low frequencies and 0.62 db in high frequencies. At 8000 Hz the effect of the age at employment on hearing loss was significant (P=0.014). At low frequencies the interaction of smoking and age at employment was significantly related to hearing loss (P˂0.001). Conclusion: This study showed that despite acquaintance with safety measures, workers still face hearing loss in industry and employers should put workers under more surveillance for using protective gear. Smoking might be another risk factor for hearing loss.

Aims: Psychological stress at workplace plays an important role in employees' well-being and performance. The prevalence of suspected employees suffering from psychological stress and factors influencing it was studied at a major regional manufacturer of tiles in Kashan, Central Iran, where employees often struggled with the harsh working conditions. Materials and Methods: This cross-sectional study was conducted on all 263 male employees of a major regional manufacturer of tiles in Kashan using both General Health Questionnaire-28 and demographic questionnaires. SPSS software (version 16) was used to analyze the data corresponding to descriptive and analytical statistic tests. Results: The frequencies of mental disorder, sleep disorder and anxiety, social function disorder, as well as depression and physical symptoms were found to be 52.3%, 52.8%, 75.7%, 12.8%, and 48.3%, respectively. There was a significant relationship between anxiety with work tenure and work shift, depression with income level, and general mental health with work shift and income. Conclusion: The results show that psychiatric disorders in this industry are significant, so implementation of prevention and treatment programs is of great importance for improving production and performance of workers, especially in high-risk groups.

Background: Alcohol use and drug injection are prevalent among homeless youths. The aim of this study wasto identify the associated factors of alcohol consumption and drug injection among homeless youths aged18-29 years.Methods: Data on 202 homeless youths (111 males and 91 females) were collected using a standardizedquestionnaire and face-to-face interview. Lasso logistic regression was applied to determine the impact ofassociated factors on alcohol consumption and drug injection.Findings: The mean age of the participants was 26.30 ± 3.19 years. Also, the prevalence of alcoholconsumption and drug injection was 33.0% [95% confidence interval (CI): 30-36] and 4.0% (95% CI: 0-8),respectively; 6 people (3.0%) consumed alcohol and injected drugs at the same time. Correlates of alcoholconsumption and drug injection were male sex [odds ratio (OR)Alc = 5.7], age (ORAlc = 0.96 and ORDI = 0.98),bachelor or higher education level (ORAlc = 1.34), non-Iranian nationality (ORAlc = 0.05 and ORDI = 0.18),food score (ORDI = 0.92), smoking (ORAlc = 2.05), substance use (ORAlc = 1.12), opposite sex relationship(ORAlc = 1.6), homosexual relationship (ORAlc = 3.56 and ORDI = 2.69), and mental disorder (ORAlc = 0.99).Conclusion: Based on our findings, it seems that the homeless youth are more desired to use alcohol and druginjection, whereas the prevalence of alcohol consumption and drug injection in homeless youth was higherthan general youth population in Iran. Therefore, some suitable solutions are needed to prevent thehomelessness. Also, the effective variables that were identified in this study for alcohol use and drug injectioncan help design and implement beneficial interventions.

Background: Two main issues that challenge model building are number of Events Per Variable and multicollinearity among exploratory variables. Our aim is to review statistical methods that tackle these issues with emphasize on penalized Lasso regression model. The present study aimed to explain problems of traditional regressions due to small sample size and multi-colinearity in trauma and influenza data and to introduce Lasso regression as the most modern shrinkage method. Methods: Two data sets, corresponded to Events Per Variable of 1.5 and 3.4, were used. The outcomes of these two data sets were hospitalization due to trauma and hospitalization of patients suffering influenza respectively. In total, four models were developed: classic Cox and logistic regression models, as well as their penalized lasso form. The tuning parameters were selected through 10-fold cross validation. Results: Traditional Cox model was not able to detect significance of any of variables. Lasso Cox model revealed significance of respiratory rate, focused assessment with sonography in trauma, difference between blood sugar on admission and 3 h after admission, and international normalized ratio. In the second data set, while lasso logistic selected four variables as being significant, classic logistic was able to identify only the importance of one variable. Conclusion: The AIC for lasso models was lower than that for traditional regression models. Lasso method has practical appeal when Events Per Variable is low and multicollinearity exists in the data.

Background:Dialysis is a process for eliminating extra uremic fluids of patients with chronic renal failure. The present study aimed to determine the variables that influence the survival of dialysis patients using random survival forest model (RSFM) in low-dimensional data with low events per variable (EPV). Methods:In this historical cohort study, information was collected from 252 dialysis patients in Bandar Abbas hospitals, Iran. The survival time of the patients was calculated in years from the onset of dialysis to death or until the end of the study in 2016. RSFM was used as the number of events per variable (EPV) was low. The data collected from 252 patients were randomly divided into training and testing sets, and this process was repeated 100 times. C-index and Brier Score (BS) were used to assess the performance of the model in the test set. Results: In this study, 35 (13.9%) mortality cases were observed. Based on the findings, the mean C-index value in training and testing sets was 0.640 and 0.687, and the mean BS value in training and testing sets was 0.017 and 0.023, respectively. The results of the RSFM revealed that BMI, education, occupation, dialysis duration, number of dialysis sessions and age at dialysis onset were the most important factors. Conclusion: RSFM can be used to determine the survival of dialysis patients and manage low-dimensional data with few-events if the researcher desires to select a nonparametric model.