Global NEST Journal

Land use and landcover change (LU/LC) are important in global change studies because they can transform the local and global environment by developing the biochemical, biochemical and biogeographic properties of the Earth's structure. This paper is intended to develop Hybrid Convolutional Neural Network (HCNN) for land use and land cover changes prediction in Tiruppur Tamilnadu. Initially, the databases are collected from the open-source system. And the image dataset has been pre-processed using the image augmentation technique. Through which the image has been resized and processed for training it with the proposed mode. The resized images are sent to the HCNN for prediction of land cover and land use changes in Tiruppur Tamilnadu. The proposed classifier is a combination of Convolutional Neural Network (CNN) and Remora Optimization Algorithm (ROA). In the CNN, the ROA is utilized to select the hyper parameters to enable efficient prediction in land use and land cover changes. The proposed classifier is implemented in MATLAB and performances is evaluated by performance metrices such as accuracy, precision, recall, sensitivity, F_Measure and Kappa. The proposed methodology is compared with the conventional techniques such as CNN, Markov chain model and Recurrent Neural Network (RNN) respectively.

Dimethoate is an organophosphate (OP) insecticide used in agriculture to kill insects. However, information on the effect of the insecticide on non-target organisms like phytoplankton is sparse. When dimethoate enters water ecosystems, it affects the photosynthesis of the phytoplankton cells. The effect of dimethoate on the photosynthesis mechanism of three Chlorophyceaen and two Bacillariophyceaen species was studied measuring oxygen production, chlorophyll fluorescence and xanthophyll pigments. Oxygen evolution rates of the five phytoplankton species decreased with increasing dimethoate concentrations. OJIP fluorescence characteristics in presence of dimethoate was similar to those of DCMU inhibition. DCMU is a PSII inhibitor used as a positive control. Non-photochemical quenching (NPQ) development and the concentration of specific xanthophyll pigments decreased with increasing insecticide concentration, giving another evidence for the target of dimethoate in the selected phytoplankton species. Dark relaxation kinetics did not show a photoinhibition of the cells in presence of dimethoate. Perfekthion, the commercial formulation of dimethoate, inhibited the photosynthesis of the tested phytoplankton species stronger than dimethoate, leading probably to photoinhibition.

Earth is consisting of land, air and water. Air contains oxygen, nitrogen, carbon dioxide, water vapor, other gases are present above the permissible limit, and it creates effects on human health. It is one of the most important public health issues due to development of urbanization, industrialization and globalization in large cities. Air pollution levels in developed countries have been increased in recent years. In developing countries air pollution levels are still high. In recent years, the health studies have become visible showing harmful health effects in lungs and respirable system. Air pollution is responsible for 7million deaths annually. It affects the health of humans and other living beings in our world. The government has developed the guidelines for air quality and rule to restrict emissions in effort to control air pollution. These updated AQGs provide exact guidelines for PM 10 and pm 2.5. The primary objective of this paper is to study the ambient air quality and its impact on lungs. Particulate matters are the particles suspended in air/atmosphere. Mainly PM10and PM 2.5Ultra fine particles (<1µm) are mainly responsible for causing interruption for human health.PM10 and PM2.5 are characterized by their presence only within the upper respiratory tract. Some PM 2.5 and Ultra fine particles are characterized by their presence deeper regions of alveoli. Ultrafine particles (PM0.1), which are present in the air in large numbers, pose a health risk. They generally enter the body through the lungs but translocation to essential organs. Compared to fine particles (PM2.5) ,they cause more pulmonary inflammation and are retained longer in the lung. Their toxicity is increased with smaller size, larger surface area, adsorbed surface material, and the physical characteristics of the particles. Exposure to PM0.1 induces cough and worsens asthma. Metal fume fever is a systemic disease of lung inflammation most likely caused by PM0.1. The disease is manifested by systemic symptoms hours after severe exposure to PM0.1 could cause systemic inflammation, endothelial dysfunction, and coagulation changes that predispose individuals to cardiovascular disease and hypertension.

The regional tourism economy of Guizhou Province (Latitude 26° 38' 49.1964'' N and Longitude: 106° 37' 47.9892'' E) can be developed by improving the transportation situation. The influence of transportation on the regional tourism economy is the main research content here. A correlation model is established to quantify the relationship between the two. Finally, the model experiment results are analyzed and summarized. Growth rate of total tourism revenue has the largest impact after a positive shock in the initial stage and then drops sharply, turning into the largest negative response. There are obvious shocks in the next few times. The impact gradually decreases and finally tends to 0. The impact of the shock disappears after 20 hits. When it is impacted by the total length of transportation lines, the growth rate of total tourism revenue doesn’t respond at the initial stage. It then responds negatively. The results indicate that there is a coupling relationship between transportation and tourism. The improvement of transportation serves as a strong booster for the tourism economy and supports the development of tourist attractions. The results are significant for promoting transportation and tourism in Guizhou Province.