Optimization Model for Maintenance Planning of Loading Equipment in Open Pit Mines

Maintenance plays a significant role in operating costs in the mining industry. Improving this matter controls maintenance costs and enhances productivity and production effectively. Shovels are one of the most widely used loading machines in non-continuous activities. Thus, evaluating and optimizing their availability is one of the essential solutions to achieving high productivity and cost reduction. This paper presents a mathematical programming model to maximize availability and minimize the total expected costs. We programmed the proposed nonlinear planning model using the Symbiotic Organisms Search (SOS) meta-heuristic algorithm in Matlab software. It determines the optimal maintenance intervals for different parts of the shovel. The maintenance benefit analysis approach selects various maintenance activities in optimal maintenance intervals. The model is implemented in a practical case study, Chadormalu Iron Mine, to evaluate its performance. The failure distribution matches the Weibull distribution function. The computational results show the efficiency of the presented approach

Novel Pipeline for Diagnosing Acute Lymphoblastic Leukemia Sensitive to Related Biomarkers

Acute Lymphoblastic Leukemia (ALL) is one of the most common types of childhood blood cancer. The quick start of the treatment process is critical to saving the patient's life, and for this reason, early diagnosis of this disease is essential. Examining the blood smear images of these patients is one of the methods used by expert doctors to diagnose this disease. Deep learning-based methods have numerous applications in medical fields, as they have significantly advanced in recent years. ALL diagnosis is not an exception in this field, and several machine learning-based methods for this problem have been proposed. In previous methods, high diagnostic accuracy was reported, but our work showed that this alone is not sufficient, as it can lead to models taking shortcuts and not making meaningful decisions. This issue arises due to the small size of medical training datasets. To address this, we constrained our model to follow a pipeline inspired by experts' work. We also demonstrated that, since a judgement based on only one image is insufficient, redefining the problem as a multiple-instance learning problem is necessary for achieving a practical result. Our model is the first to provide a solution to this problem in a multiple-instance learning setup. We introduced a novel pipeline for diagnosing ALL that approximates the process used by hematologists, is sensitive to disease biomarkers, and achieves an accuracy of 96.15%, an F1-score of 94.24%, a sensitivity of 97.56%, and a specificity of 90.91% on ALL IDB 1. Our method was further evaluated on an out-of-distribution dataset, which posed a challenging test and had acceptable performance. Notably, our model was trained on a relatively small dataset, highlighting the potential for our approach to be applied to other medical datasets with limited data availability

Cavity Preparation by Laser in Primary Teeth: Effect of 2 Levels of Energy Output on the Shear Bond Strength of Composite Restoration to Dentin

Introduction: One of the main applications of laser in dentistry is the removal of dental caries and preparation of restorative cavities. The morphology and wettability of laser prepared surfaces are different from that of those prepared with conventional method which may affect the quality of the adhesive potential of bonding agents in these surfaces. This study aimed to assess the shear bond strength of a total-etch and self-etch adhesive system to primary tooth dentin prepared by two different energy densities of Er:YAG laser in comparison with surfaces prepared by bur.Methods: A total of 60 human primary second molars extracted for orthodontic purposes were selected and randomly divided into 3 main groups of equal (n = 20). Group A: Preparation of dentin surface by bur; group B: Preparation of dentin surface by laser with 300 mJ energy level; group C: Preparation of dentin surface by laser with 400 mJ energy level. In each of the main groups, the teeth were randomly assigned to 2 subgroups. Composite resin material was bonded with the total-etch adhesive system in subgroups A1, B1, and C1 and with the self-etch adhesive system in subgroups A2, B2, and C2. The samples were thermo-cycled, and composite restorations shear bond strength was measured in MPa. Data were analyzed using two-way analysis of variance (ANOVA), and P values less than 0.05 were considered statistically significant.Results: The highest and the lowest shear bond strength values were observed in group A2 (Preparation by bur- Composite resin material bonded by Clearfil SE Bond) and group C2 (Preparation by laser with 400 mJ energy level - Composite resin material bonded by Clearfil SE Bond), respectively. The results showed no statistically significant differences between the study subgroups (P > 0.05).Conclusion: It is concluded that in terms of shear bond strength to dentin, Single Bond and Clearfil SE Bond adhesive agents adequately perform in primary tooth dentin prepared by Er: YAG laser with energy levels of 300 and 400 mJ and frequency of 10 Hz

Investigating the effects of cow manure, vermicompost and Azolla fertilizers on hydraulic properties of saline-sodic soils

Purpose Soil salinity and sodicity are among the factors involved in soil degradation, especially in arid and semi-arid areas of the world. The use of modifiers, including organic matters, can be considered as an appropriate strategy to improve the fertility of saline-sodic soils.  Method In this study, saline-sodic control soil was collected from Karaj and mixed with three levels of 1%, 3% and 5% of cow manure, vermicompost and Azolla. The soil columns were then incubated at 20 °C and field capacity moisture for 5 months. The physical and chemical properties of the treatments were evaluated before and after incubation. Results After the incubation period, the lowest salinity level was observed in 5% Azolla and vermicompost treatments. The highest amount of change in sodium absorption ratio was related to 5% cow manure treatment. There was an insignificant difference in moisture levels in a given suction among the different treatments. After the incubation period, salinity and sodium absorption decreased and increased in most of the treatments, respectively. Moreover, the decrease of saturation dehydration coefficient in the treatments revealed the disruption of soil structure and conversion of large pores to fine grains as a result of adding the mentioned organic matters. Conclusion According to the results, cow manure at 1% level had no significant effect on soil properties. However, at higher levels, it had a negative effect on quality and conditions of the saline-sodic soil in terms of physical and chemical properties. In contrast, Azolla and vermicompost fertilizers at 5% proved to be suitable for correcting the saline-sodic soil

Probabilistic Proximity-aware Resource Location in Peer-to-Peer Networks Using Resource Replication

Nowadays, content distribution has received remarkable attention in distributed computing researches and its applications typically allow personal computers, called peers, to cooperate with each other in order to accomplish distributed operations such as query search and acquiring digital contents. In a very large network, it is impossible to perform a query request by visiting all peers. There are some works that try to find the location of resources probabilistically (i.e. non-deterministically). They all have used inefficient protocols for finding the probable location of peers who manage the resources. This paper presents a more efficient protocol that is proximity-aware in the sense that it is able to cache and replicate the popular queries proportional to distance latency. The protocol dictates that the farther the resources are located from the origin of a query, the more should be the probability of their replication in the caches of intermediate peers. We have validated the proposed distributed caching scheme by running it on a simulated peer-to-peer network using the well-known Gnutella system parameters. The simulation results show that the proximity-aware distributed caching can improve the efficiency of peer-to-peer resource location services in terms of the probability of finding objects, overall miss rate of the system, fraction of involved peers in the search process, and the amount of system load

Identification and prioritization of efficiency-influencing factors in banking using MADM technique (Case study: Tejarat Bank)

The present study is an attempt to identify and prioritize efficiency-influencing factors in banking system based on Analytic Hierarchy Process (AHP) and (topsis), performed by considering comments and remarks of Tejarat bank experts in Tehran. For this purpose, first the most important efficiency-influencing factors were identified by studying the related literature, background of the study, and interviews with some of Tejarat bank’s managers and authorities. Then, by performing a field study, it was attempted to ask Tejarat bank experts for their opinions in Tehran as the statistical population of the study. After analyzing data and testing measures using T- student test, it was finally found that all recognized variables and factors influence banking efficiency. Results obtained from Analytic Hierarchy Process (AHP)-based statistical studies and analyses indicated that among the main criteria, the criteria of hardware, software, and working systems are the most important, followed by manpower; financial tools and attitudes have the lowest priority. Also, regarding sub-criteria, the sub-criteria of customers-specific convenient facilities, targeted marketing and advertisement of products and services had the highest rank

Identification and prioritization of efficiency-influencing factors in banking using MADM technique (Case study: Tejarat Bank)

The present study is an attempt to identify and prioritize efficiency-influencing factors in banking system based on Analytic Hierarchy Process (AHP) and (topsis), performed by considering comments and remarks of Tejarat bank experts in Tehran. For this purpose, first the most important efficiency-influencing factors were identified by studying the related literature, background of the study, and interviews with some of Tejarat bank’s managers and authorities. Then, by performing a field study, it was attempted to ask Tejarat bank experts for their opinions in Tehran as the statistical population of the study. After analyzing data and testing measures using T- student test, it was finally found that all recognized variables and factors influence banking efficiency. Results obtained from Analytic Hierarchy Process (AHP)-based statistical studies and analyses indicated that among the main criteria, the criteria of hardware, software, and working systems are the most important, followed by manpower; financial tools and attitudes have the lowest priority. Also, regarding sub-criteria, the sub-criteria of customers-specific convenient facilities, targeted marketing and advertisement of products and services had the highest rank

Identification and prioritization of efficiency-influencing factors in banking using MADM technique (Case study: Tejarat Bank)

The present study is an attempt to identify and prioritize efficiency-influencing factors in banking system based on Analytic Hierarchy Process (AHP) and (topsis), performed by considering comments and remarks of Tejarat bank experts in Tehran. For this purpose, first the most important efficiency-influencing factors were identified by studying the related literature, background of the study, and interviews with some of Tejarat bank’s managers and authorities. Then, by performing a field study, it was attempted to ask Tejarat bank experts for their opinions in Tehran as the statistical population of the study. After analyzing data and testing measures using T- student test, it was finally found that all recognized variables and factors influence banking efficiency. Results obtained from Analytic Hierarchy Process (AHP)-based statistical studies and analyses indicated that among the main criteria, the criteria of hardware, software, and working systems are the most important, followed by manpower; financial tools and attitudes have the lowest priority. Also, regarding sub-criteria, the sub-criteria of customers-specific convenient facilities, targeted marketing and advertisement of products and services had the highest rank

The role of glutathione-S-transferase polymorphisms on clinical outcome of ALI/ARDS patient treated with N-acetylcysteine

SummaryOxidative stress has a proven role in pathophysiology of acute respiratory distress syndrome. The antioxidant drugs, especially N-acetylcysteine (NAC) have been used for years to overcome oxidative stress effects in patients. In the present study we have investigated the effects of NAC treatment (IV NAC in 150mg/kg at the first day followed by 50mg/kg/day for three days) on 27 ICU patients with ALI/ARDS considering the glutathione-S-transferase genetic variations, as an important enzyme contributing in oxidative stress pathways. The results indicated that NAC improved oxygenation (increase in PaO2/FiO2) and decreased mortality rate in treated patients compared to control group (p<0.05). Evaluation of three isoforms of glutathione-S-transferase (GST M1, P1 and T1), in these patients have showed an association between GST M1 null, and GST M1 and T1 double null polymorphisms with increased mortality in control group, suggesting antioxidant therapy critical for this group of patients