Design of an unmanned aerial vehicle survey system based on embedded 3D machine vision imaging perception

At present, the application of UAV in urban planning and construction is mainly manifested in urban planning survey, urban illegal building supervision and environmental monitoring of urban construction projects. Secondly, based on embedded technology can be managed by multiple users, you can run multiple processes program, open and run the code, the system powerful, which makes it to be able to do many tasks in the field of, and running is stable, many developers will be able to enjoy its source code publicly, relative to other real-time operating system has the absolute advantage.

Land Value Taxation: A Spatially Explicit Economic Experiment with Endogenous Institutions

An economic experiment with endogenous institutions informs the political economy of land value taxation relative to uniform property taxation in terms of efficiency and sprawl reduction. Heterogeneous type distributions were used so that land value taxation was earnings-rational, relative to uniform property taxation, for 40, 60, and 80 percent of the participants. The model’s induced values predict land value taxation leads to less sprawl, more earnings, and more tax revenue than uniform property taxation. Experimental data do not consistently match this prediction, where both tax institutions led to more sprawl and lower earnings than predicted. Results show participants voted for the tax institution that does not maximize their individual earnings in 16.7 percent of rounds. These earnings-irrational choices occurred when the type distributions were 40 and 60 percent in favor of land value taxation. The experiment results nonetheless show the absolute advantage of land value taxation for producing less sprawl, more tax revenue, and more earnings. Moreover, the behavioral evidence suggests that relative advantage of land value taxation in reducing sprawl is greater than predicted by the model. This suggests further inquiry about whether land value taxation promotion activities may best be targeted towards cities using uniform property taxation where economies are vibrant, land uses are already relatively intensive, and greater-than-average population density already exists.

Activity-educational aspects of geological excursions

The purpose of this article is to discuss the educational tour as a form of educational process in the activity-the educational aspect of the geological excursion in the study of rock outcrops career «Borok» of Novosibirsk as a geological object of interest for educational tours and training-practical work. To write the article, we used methods of comparative analysis, generalization, field geological observations, sampling, cross-section sketches, descriptions of outcrops, including working with a mountain compass and methods of conducting a training geological-geographical and geoecological route, drawing up a map of the territory, laboratory studies of rocks. The absolute advantage of the Borok quarry is its location, as well as optimal conditions for a thorough inspection and description of rock outcrops. Branched dikes and veins are visible in the walls of the quarry, as well as the overlap of igneous Paleozoic rocks with sedimentary later deposits. Dumps of various Intrusive igneous, dike rocks and pegmatites, hydrothermal veins with ore minerals are of educational interest during excursions. The Borok quarry cooperates with schools, colleges, and Universities in Novosibirsk and is a platform for educational excursions to the production site and a place for training practices, as well as a venue for educational Olympiads in Geology and Geoecology. On the example of one of the production facilities of the city of Novosibirsk - the stone quarry «Borok», the possibilities of organizing and conducting geological excursions in order to study the geological structure of the territory, consolidate theoretical geological and geoecological knowledge, acquire skills in educational and practical work and analyze the results obtained are demonstrated.

Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix

Background The COVID-19 pandemic occurred and rapidly spread around the world. Some online dashboards have included essential features on a world map. However, only transforming data into visualizations for countries/regions is insufficient for the public need. This study aims to (1) develop an algorithm for classifying countries/regions into four quadrants inn GSM and (2) design an app for a better understanding of the COVID-19 situation. Methods We downloaded COVID-19 outbreak numbers daily from the Github website, including 189 countries/regions. A four-quadrant diagram was applied to present the classification of each country/region using Google Maps run on dashboards. A novel presentation scheme was used to identify the most struck entities by observing (1) the multiply infection rate (MIR) and (2) the growth trend in the recent 7 days. Four clusters of the COVID-19 outbreak were dynamically classified. An app based on a dashboard aimed at public understanding of the outbreak types and visualizing of the COVID-19 pandemic with Google Maps run on dashboards. The absolute advantage coefficient (AAC) was used to measure the damage hit by COVID-19 referred to the next two countries severely hit by COVID-19. Results We found that the two hypotheses were supported: India (i) is in the increasing status as of April 28, 2021; (ii) has a substantially higher ACC(= 0.81 > 0.70), and (iii) has a substantially higher ACC(= 0.66 < 0.70) as of May 17, 2021. Conclusion Four clusters of the COVID-19 outbreak were dynamically classified online on an app making the public understand the outbreak types of COVID-19 pandemic shown on dashboards. The app with GSM and AAC is recommended for researchers in other disease outbreaks, not just limited to COVID-19.

The Effects Pandemic Covid-19 on Indonesia Foreign Trade

Indonesia is a developing country whose needs are exported from abroad. Therefore Indonesia needs foreign trade to fulfill goods that cannot be produced domestically or to distribute goods in which Indonesia has an absolute advantage in producing these goods. However, the policies are taken by the domestic government and Indonesia's foreign trading partner countries to limit the spread of the Covid-19 virus have an impact on the inflow of goods to and from abroad. Thus, this study intends to see how the Covid-19 pandemic has affected Indonesia's foreign trade by using the Paired Sample T-test, which observes conditions before and during/after a pandemic occurs. This study found that the Covid-19 pandemic had an impact on Indonesia's foreign trade from the aspect of oil and gas exports, imports of raw materials, and imports of Indonesian capital goods.

Using the Absolute Advantage Coefficient(AAC) to Measure the Strength of Damage Hit by COVID-19 in India on a Growth-Share Matrix

Background: The COVID-19 pandemic occurred and rapidly spread around the world. Some online dashboards have included essential features on a world map. However, only transforming data into visualizations for countries/regions is insufficient for the public need. This study aims to (1) develop an algorithm for classifying countries/regions into four quadrants inn GSM and (2) design an app for a better understanding of the COVID-19 situation.Methods: We downloaded COVID-19 outbreak numbers daily from the Github website, including 189 countries/regions. A four-quadrant diagram was applied to present the classification of each country/region using Google Maps run on dashboards. A novel presentation scheme was used to identify the most struck entities by observing (1) the multiply infection rate(MIR) and (2) the growth trend in the recent seven days. Four clusters of the COVID-19 outbreak were dynamically classified. An app based on a dashboard aimed at public understanding of the outbreak types and visualizing of the COVID-19 pandemic with Google Maps run on dashboards. The absolute advantage coefficient(AAC) was used to measure the damage hit by COVID-19 referred to the next two countries severely hit by COVID-19.Results: We found that the two hypotheses were supported: India (i) is in the increasing status as of April 28, 2021, (ii) has a substantially higher ACC(=0.81>0.70), and (iii) has a substantially higher ACC(=0.66<0.70) as of May 17,2021. Conclusion: Four clusters of the COVID-19 outbreak were dynamically classified online on an app making the public understand the outbreak types of COVID-19 pandemic shown on dashboards. The app with GSM and AAC is recommended for researchers in other disease outbreaks, not just limited to COVID-19.

Correlation between the imaging manifestations of cerebellar infarction and the clinical characteristics of patients: a retrospective analysis

Background The aim of this study was to analyze the correlation between the imaging manifestations of cerebellar infarction and the clinical characteristics of patients. Methods A total of 83 patients with acute cerebellar infarction were included in this analysis. The NIHSS score, TOAST classification, CT and MRI examinations and serum laboratory tests were performed. The statistics of the data were carried out through descriptive statistics, T test and analysis of variance. Results Hyperlipidemia (66.3%), hypertension (77.1%) and carotid atherosclerosis (97.6%) were the main underlying causes of cerebellar infarction. Ataxia (67.5%) and brainstem syndrome (60.2%) were main clinical manifestations. Patients with NIHSS score ≤ 5 accounted for the majority (87.9%) and SAO (43.3%) and LAA (50.6%) were the main TOAST classifications. The cerebellar infarction caused by obstruction of SCA accounted for the majority (69.9%) and there was no statistical difference in the detection ability of CTA and MRA (P > 0.05). The incidence of left hemisphere cerebellar infarction was the highest (56.7%) and MRI showed an absolute advantage in showing the area of cerebellar infarction compared with CT (P < 0.001). The serum concentrations of D-dimer, LDL, and triglycerides were higher in patients with high NIHSS scores than in those with low scores (P < 0.05), while the serum HDL levels were just the opposite (P < 0.05). The serum D-dimer concentrations in patients classified as CE by TOAST were higher than that in patients classified as LAA and SAO (P < 0.05), while the serum concentrations of LDL were just the opposite (P < 0.05). The lesion sizes of cerebellar infarction were negatively related to the patient's serum HDL concentrations (P < 0.05) but it positively correlated with the NIHSS scores (P < 0.05). The patients classified as LAA had larger lesion sizes of cerebellar infarction than those classified as SAO and CE (P < 0.001). Conclusions CTA and MRA are comparable in showing the stenosis and obstruction of the cerebellar artery. However, MRI has an absolute advantage in showing the area of cerebellar infarction. The serum concentrations of D-dimer, HDL, LDL, and triglycerides are correlated with the patient’s NIHSS scores, TOAST classification and infarct sizes, which are helpful in evaluating the condition of the disease.

METHODOLOGICAL PROBLEMS OF SELF-AWARENESS RESEARCH IN RUSSIAN PSYCHOLOGY

The article identifies methodological problems of self-awareness research in Russian psychology. The relationship between the definitions of consciousness and self-consciousness is considered. It is established that self-consciousness is a more complex psychological formation in relation to consciousness. It occurs in the process of human ontogenesis. This methodological approach raises the problem of finding the determinants of the development of self-consciousness in the basis of consciousness. The concept and structure of self-consciousness in the works of Soviet and Russian psychologists are analyzed. There is a variety of ideas about this psychological education in Russian science. Each author's concept seeks to introduce new elements into the content of self-consciousness by using additional psychological tools. The lack of universality in the definition and structure of self-consciousness leads to a methodological problem of its research. This situation is due to the fact that the authors of concepts, in different ways, determine the content of this complex phenomenon of the psyche, based on their life experience and theoretical preferences. The experimental methods used by researchers in the study of this psychological education are defined. In Russian psychology, the most common standardized and non-standardized self-reports, as well as psychosemantic methods. The absolute advantage of these methods is a large variety of responses of subjects about their own "I". However, when describing themselves, subjects sometimes try to demonstrate socially desirable qualities, which creates a problem of reliability of the results obtained. The main principles of self-awareness research in Russian psychology are described: the principle of consciousness and activity, the principle of development, the principle of personal approach, and the cultural and historical principle. Their role in overcoming the methodological difficulties of its study is established. Promising ways of self-awareness research and methodological problems that may arise on the way to their implementation are outlined.

Using the IPcase Index with Inflection Points and the Corresponding Case Numbers to Identify the Impact Hit by COVID-19 in China: An Observation Study

Coronavirus disease 2019 (COVID-19) occurred in Wuhan and rapidly spread around the world. Assessing the impact of COVID-19 is the first and foremost concern. The inflection point (IP) and the corresponding cumulative number of infected cases (CNICs) are the two viewpoints that should be jointly considered to differentiate the impact of struggling to fight against COVID-19 (SACOVID). The CNIC data were downloaded from the GitHub website on 23 November 2020. The item response theory model (IRT) was proposed to draw the ogive curve for every province/metropolitan city/area in China. The ipcase-index was determined by multiplying the IP days with the corresponding CNICs. The IRT model was parameterized, and the IP days were determined using the absolute advantage coefficient (AAC). The difference in SACOVID was compared using a forest plot. In the observation study, the top three regions hit severely by COVID-19 were Hong Kong, Shanghai, and Hubei, with IPcase indices of 1744, 723, and 698, respectively, and the top three areas with the most aberrant patterns were Yunnan, Sichuan, and Tianjin, with IP days of 5, 51, and 119, respectively. The difference in IP days was determined (χ2 = 5065666, df = 32, p < 0.001) among areas in China. The IRT model with the AAC is recommended to determine the IP days during the COVID-19 pandemic.

Characteristics of Hydrochars Derived from Glucose, Protein, and Cellulose by Hydrothermal Carbonization Treatment

With hydrothermal carbonization (HTC) treatment, wet biomass can be rapidly converted into hydrochar product with high-carbon content and calorific value. The current study employed glucose, protein, and cellulose as raw materials to investigate the effects of reaction temperature and residence time on characteristics of hydrochars. Results showed that the optimal reaction temperatures for glucose, protein, and cellulose were 240 °C, 190 °C and 220 °C, respectively. The optimal residence times were 4 h, 3 h and 4 h respectively, under which carbon microspheres with smooth surface and uniform particle size tended to form. The increased temperature promoted decomposition of bio-oil in the hydrothermal system and improved the quality of carbon microspheres, but much higher temperature deformed the surface of the carbon microspheres. Appropriate residence time ensured full growth of carbon microspheres but excessive residence time made the formed carbon microspheres to crosslink with each other, causing roughness to the surface. In addition, comparison of the specific surface area showed that the cellulose carbon microspheres exhibited an absolute advantage.