Military Academy

About: Military Academy is a based out in . It is known for research contribution in the topics: Population & Fuzzy logic. The organization has 2478 authors who have published 3003 publications receiving 33188 citations.

DNA hypermethylation: when tumour suppressor genes go silent

Abstract: The phenotype of the cancerous cell may arise either from genetic alterations that disrupt gene function through sequence modifications (mutations) or epigenetic events that may alter the heritable state of gene expression (i.e. without changing the actual sequence of the genome). Whereas mutations in certain tumour suppressor genes are most often thought of in association with their inactivation during cancer initiation or progression, epigenetic alterations such as DNA methylation appear to be tightly linked to the sequential non-reversible events of normal tissue differentiation and organogenesis. This highlights a link between tissue differentiation and tumourigenesis with respect to the stable nature of certain epigenetic changes. In the case of tumourigenesis, both genetic and epigenetic mechanisms of altered gene expression often go hand in hand; not surprisingly, biallelic inactivation of a given tumour suppressor gene may occur via a combination of mutational and epigenetic events and is entirely consistent with the Knudson two-hit hypothesis of tumourigenesis. This review summarizes recent developments within the field of DNA methylation, highlighting its association with the transcriptional silencing of tumour suppressor genes in a variety of human cancers.

Rod-, flower-, and dumbbell-like MnO2: Highly active catalysts for the combustion of toluene

Abstract: The rod-like tetragonal α-MnO 2 , flower-like hexagonal ɛ-MnO 2 , and dumbbell-like tetragonal β-MnO 2 were prepared using the hydrothermal or water-bathing method under different conditions. It is shown that the α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 catalysts possessed a surface area of ca. 53, 30, and 114 m 2 /g, respectively. The oxygen adspecies concentration and low-temperature reducibility decreased in the order of α-MnO 2 > ɛ-MnO 2 > β-MnO 2 , coinciding with the sequence of their catalytic activities for toluene combustion. The well-defined morphological MnO 2 catalysts performed much better than the bulk counterpart. At a space velocity of 20,000 mL/(g h), the temperature for 90% toluene conversion was 238, 229, and 241 °C over α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 , respectively. The apparent activation energies of α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 were in the range of 20–26 kJ/mol. It is concluded that higher oxygen adspecies concentrations and better low-temperature reducibility were responsible for the good catalytic performance of the α-MnO 2 , ɛ-MnO 2 , and β-MnO 2 materials.

Thermal and mechanical stability of functionally graded carbon nanotubes (FG CNT)-reinforced composite truncated conical shells surrounded by the elastic foundations

Abstract: The thermal and mechanical stability of a functionally graded composite truncated conical shell reinforced by carbon nanotube fibers and surrounded by the elastic foundations are studied in this paper. Distribution of reinforcements across the shell thickness is assumed to be uniform or functionally graded. The equilibrium and linearized stability equations for the shells are derived based on the classical shell theory. Using Galerkin method, the closed – form expression for determining the linear thermal and mechanical buckling load is obtained. The paper also analyzed and discussed the effects of semi-vertex angle, shell length, volume fraction of fibers, distribution pattern of fibers, temperature, elastic foundations on the linear thermal and mechanical buckling loads of the functionally graded carbon nanotube fibers-reinforced composite (FG CNTRC) truncated conical shell in thermal environment.

Green logistic vehicle routing problem: Routing light delivery vehicles in urban areas using a neuro-fuzzy model

Abstract: Today's growth in the level of traffic in cities is leading to both congestion and environmental pollution (exhaust emissions and noise), as well as increased costs. Traffic congestion makes cities less pleasant places to live in, a particular problem being the negative impact on health as a result of increased exhaust emissions. In addition to these emissions, another major effect of transport which can lead to serious health problems is noise (EEA, 2013a, 2013b). There is a strong tendency in the world towards the development of ''clean'' motor vehicles that do not pollute the environment, that is, that do not emit harmful substances in their exhaust fumes and which create less noise without causing other types of pollution. The growth in the influence of transport on the environment has resulted in planners formulating procedures which take into account the effect of traffic on the quality of life in urban areas. This paper presents a model for the routing of light delivery vehicles by logistics operators. The model presented takes into account the fact that logistics operators have a limited number of environmentally friendly vehicles (EFV) available to them. When defining a route, EFV vehicles and environmentally unfriendly vehicles (EUV) are considered separately. For solving the problem of routing in the model, an adaptive neural network was used which was trained by a simulated annealing algorithm. An adaptive neural network was used for assessing the performance of the network branches. The input parameters of the neural network were the logistics operating costs and environmental parameters (exhaust emissions and noise) for the given vehicle route. Each of the input parameters of the neural network was thoroughly examined. The input parameters were broken down into elements which further describe the state of the environment, noise and logistics operating costs. After obtaining the performance of the network links for calculating the route for EFV and EUV vehicles a modified Clark-Wright algorithm was used. The proposed model was tested on a network which simulates the conditions in the very centre of Belgrade. All of the input parameters of the model were obtained on the basis of 40 automatic measuring stations for monitoring the air quality (SEA, 2012).