In this work, cellulose nanocrystals (CNC) have been produced by hydrothermal method in a mixture of hydrochloric and nitric acids in molar ratios of 8:2, 7:3, 6:4 and 5:5. Hydrolysis of sulphate cellulose in the mixtures of nitric and hydrochloric acids was conducted in a sealed thick-walled stainless steel vessel with a teflon insert for 3 h at 110 °С. Properties of CNC have been characterized by applying different methods: elemental analysis, thermogravimetric analysis, IR spectroscopy, polarization optical microscopy, scanning electron microscopy, and dynamic light scattering. Yield of CNC, size and charge of the CNC particles, degree of polymerization, temperature of thermal destruction have been determined, and morphology of the CNC samples has been characterized. The highest CNC yield (32%) has been observed at a 7:3 ratio of nitric and hydrochloric acids. It has been established that the CNC particles are spherical and have an average size of 60-80 nm. An assumption has been made that presence of a strong oxidant (nitric acid) may cause hydrolysis of both amorphous and crystalline (in part) regions of cellulose, which affects the final shape of the CNC particles. It has been shown that the hydrolysis in a mixture of nitric and hydrochloric acids causes an oxidation of primary hydroxyl groups of the cellulose pyranose ring and formation of surface carboxyl groups. The CNC aqueous suspensions demonstrate high colloidal stability due to a rather high surface charge. It is noted that the CNC thermal stability is much higher than that of the CNC samples obtained by the standard sulfuric acid hydrolysis: the temperature of thermal destruction increases by 130-148 °С.
The article is devoted to one of the research areas of the thematic network' members "Working in the Arctic," the University of Arctic. The study was sponsored by the Russian President's grant for state support of young Russian scientists - PhD (MK-7500.2016.6). The aim of the present research is to study the dynamics of functional states of oil and gas workers of different professional groups during shift-in period in the Arctic and the development of measures to optimize them, and developing recommendations to optimize the functional state of workers in the Far North (to increase efficiency, reduce fatigue), as a factor of security and labor protection in complex natural and industrial conditions of the Far North by improving the efficiency of PPE. The study involved 70 oil and gas workers in the Nenets Autonomous Okrug of Russian Federation (the shift-in duration was 30 days) between the ages of 24 to 60 years (mean age 38,7 ± 9,7) from March to April 2015. Research methods are questioning, a complex visual-motor reaction (CVMR), "variation cardiointervalometry" (VCM); descriptive statistics and multivariate analysis of variance MANOVA. Treatment was carried out using the software package SPSS 22.00. Studying the functional states' dynamics of oil and gas employees during the period shift led to the conclusion that, despite the increase in the efficiency by the end of the shift period, there has been a pronounced decline in of working capacity for all employees (which is confirmed by both psychophysiological and psychological methods). The group at highest risk about level of efficiency and its reduction by the shift end include: drivers, operators of oil and gas, engineering and technical workers (due to the high intensity and complexity of the activity). For these staff' categories are necessary to provide special programs for the prevention of fatigue and increase working capacity. One of the ways to optimize of working capacity of oil and gas staff in the Arctic is the selection of the optimal special clothing and personal protective equipment.
The paper presents the architecture of a multi-agent system based on natural calculations, which places extra-large integrated circuits' components using the combined swarm intelligence models. The authors offer new structures of presenting a solution for the problem of placing extra-large integrated circuit elements as chromosomes. There is a modified particle swarm paradigm that differs from the canonical one by the possibility of using the positions with integral-valued parameter values in the affine space.A developed operator called directed mutation helps to move the swarm of particles in the observed solution area. The authors offer a modified structure of the bees algorithm. The key operation of the algorithm is the research on promising positions in the neighborhood of basic positions.The tests have proven that when integrating the behavior models of a bee swarm and a particle swarm, the results of the new hybrid algorithm appear to be 11-18 % better than each algorithm results separately.
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