ISTRAŽIVANJE OPERACIJA MINIRANJA KORISTEĆI METODU ODLUČIVANJA

Blasting is one of the most important operations in the mining projects. Inappropriate blasting pattern may lead to unwanted events such as poor fragmentation, back break, fly rock etc. and affect the whole operation physically and economically. In fact selecting of the most suitable pattern among previously performed patterns can be considered as a Multi Attribute Decision MakingMiniranje je jedna od najvažnijih operacija pri projektiranju u rudarstvu. Nedovoljno dobar uzorak može pridonijeti nastanku neželjenih događaja kao što su fragmentizacija, pucanje, \u27fly rock\u27 itd. te utjecati na razvoj cijele operacije fizički i ekonomski. U principu, odabir najboljeg uzorka može se smatrati važnom odlukom

A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

AbstractIn blasting operation, the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak. Therefore, predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome. Since many parameters affect the blasting results in a complicated mechanism, employment of robust methods such as artificial neural network may be very useful. In this regard, this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran. Back propagation neural network (BPNN) and radial basis function neural network (RBFNN) are adopted for the simulation. Also, regression analysis is performed between independent and dependent variables. For the BPNN modeling, a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN, architecture 6-36-2 with spread factor of 0.79 provides maximum prediction aptitude. Performance comparison of the developed models is fulfilled using value account for (VAF), root mean square error (RMSE), determination coefficient (R2) and maximum relative error (MRE). As such, it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error. Also, sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak, respectively. On the other hand, for both of the outputs, specific charge is the least effective parameter

Determination of CPUA and distribution pattern of families Haemulidae, Nemipteridae and Ariidae in the Oman Sea

This trawl survey was carried out during 2013 for the stock assessment of families Haemulids, Nemipterids and Ariids in the Oman Sea. Sampling was carried out at five different stratum and depths. The highest value of CPUA of Haemulidae was estimated for Pomadasys stridens in “B” stratum (885.78 kg nm^-2), for Pomadasys kaakan at depths of 10-20 m (330.35 kg nm^-2), and for Nemipteridae it was estimated for Nemipterus japonicus in “D” stratum (1042.31 kg nm^-2) at 30-50 m depths (1734.97 kg nm^-2), and for Ariidae, it was estimated for Netuma thalassina in the stratum B (752.64 kg nm^-2) at 20-30 m depths (428.33 kg nm^-2). The highest biomass for Haemulidae was estimated in stratum B (320.53 ton) at 50-100 m depths (282.98 tons), and for Nemipteridae in “D” stratum (559.72 tons) and at depths of 30-50 m (604.04 tons), and for Ariidae it was estimated in “B” stratum (272.35 tons) and at 50-100 m depths (255.12 ton). Based on the results obtained, the highest species diversity for Haemulids was in “A” stratum at depths less than 50 m, while for Nemipterids it was similar in the total study area and different depth layers. Highest species diversity for Ariids were found in “A” and “D” strata at depth layers of 10-20 m and 30-50 m, respectively. In light of the fact that fishing efforts decreased during these years, our results illustrate that CPUA and biomass have ascending trends which indicate the relative stability of the stocks of these families

Shape-Based Separation of Micro-/Nanoparticles in Liquid Phases

The production of particles with shape-specific properties is reliant upon the separation of micro-/nanoparticles of particular shapes from particle mixtures of similar volumes. However, compared to a large number of size-based particle separation methods, shape-based separation methods have not been adequately explored. We review various up-to-date approaches to shape-based separation of rigid micro-/nanoparticles in liquid phases including size exclusion chromatography, field flow fractionation, deterministic lateral displacement, inertial focusing, electrophoresis, magnetophoresis, self-assembly precipitation, and centrifugation. We discuss separation mechanisms by classifying them as either changes in surface interactions or extensions of size-based separation. The latter includes geometric restrictions and shape-dependent transport properties

Measurement of Losses in a Austoft Sugarcane Harvester Case 7000

IntroductionSugarcane is one of the strategic products of Khuzestan province, which is cultivated in 10 active agro-industrial sites and covers an area of about 110,000 hectares of irrigated farms in the province. Sugarcane harvesting, like most crops, is done by special sugarcane harvesters. Due to the life of machines and also the amount of heavy machine operations in each season of sugarcane harvest, the loss is inevitable. On the other hand, in Khuzestan province, due to lack of studies, there is little information in this area. Therefore, the aim of this study is to investigate the extent of losses during sugarcane harvesting operations, taking into account factors such as cultivars, age of sugarcane, and reaping speed of the Astaf 7000 model. The study will be conducted at the sugarcane agro-industrial site of Dehkhoda in 2021.Materials and MethodsThe experiment was conducted as a factorial split-plot design based on randomized complete blocks (RCBD) with three replications. The first factor included four levels of cultivars (IRC-12, CP48-103, CP 73-21, and CP69-1062), the second factor included three levels of harvest age (plant, Ratoon 1, Ratoon 2), and the third factor included three levels of speed (3, 5, and 7 km h-1). Sampling was carried out under the same and constant conditions with respect to soil moisture content, harvester operator, harvester characteristics, harvester settings, and crop density in each field.Results and DiscussionThe results of analysis of variance of the data obtained from measuring sugarcane losses showed that the effect of cultivar on yield, full-length sugarcane, chopped sugarcane and splinter sugarcane had a significant effect at a probability level of one percent. The effect of age had a significant effect on yield, full-length sugarcane, chopped sugarcane with a probability level of one percent, but had no significant effect on the amount of splinter sugarcane. The interaction between cultivar and age had a significant effect on yield, chopped sugarcane, and full-length sugarcane with a probability level of one percent and on splinter sugarcane with a probability level of five percent. The effect of machine speed had a significant effect on full-length sugarcane, chopped sugarcane and splinter sugarcane with a probability level of one percent, but had no significant effect on yield. The interaction of cultivar and machine speed had a significant effect on yield, full-length sugarcane, chopped sugarcane and splinter sugarcane with a probability level of one percent. The interaction effect of age and machine speed on yield had a significant effect on full-length sugarcane and splinter sugarcane with a probability level of one percent and on the amount of splinter sugarcane with a probability level of five but had no significant effect on yield. Also, the interaction of cultivar, age and machine speed had a significant effect on yield, full-length sugarcane and chopped sugarcane with a probability level of one percent, but had no significant effect on the amount of splinter sugarcane. The results showed that the highest yield in CP69-1062 variety was observed in the plant farm with average machine speed (144.33 tons per hectare). Also, the highest amount of sugarcane losses in cultivar CP48-103 in Raton II and with 7 km h-1 machine speed (3.32 tons per hectare), the highest amount of chopped sugarcane losses in cultivar CP48-103 in plant farm and with average speed (1.78 tons per hectare) was observed. According to the results under the interaction of cultivar and device speed, the highest amount of sugarcane losses in CP69-1062 cultivar and high speed (0.314 tons per hectare) as well as IRC-12 cultivar and high speed (0.308 tons in Hectares), and under the interaction of farm age and speed of the harvester, the highest amount of sugarcane losses was observed in Ratoon farm and the high speed of the harvester (0.300 tons per hectare).ConclusionTherefore, in order to reduce the amount of losses in sugarcane fields, it is recommended to use resistant and somewhat later cultivars for cultivation, because early cultivars are more fragile during harvest due to stem fragility and the rate of losses increases. Also, Harvester speed optimization reduces the amount of losses, and due to the increase in the rate of losses in reclaimed farms, it is recommended to create more resistant stem tissue by proper plant nutrition and more care to reduce the rate of losses in ratoon farms

CAR-T cell. the long and winding road to solid tumors

Adoptive cell therapy of solid tumors with reprogrammed T cells can be considered the "next generation" of cancer hallmarks. CAR-T cells fail to be as effective as in liquid tumors for the inability to reach and survive in the microenvironment surrounding the neoplastic foci. The intricate net of cross-interactions occurring between tumor components, stromal and immune cells leads to an ineffective anergic status favoring the evasion from the host's defenses. Our goal is hereby to trace the road imposed by solid tumors to CAR-T cells, highlighting pitfalls and strategies to be developed and refined to possibly overcome these hurdles