PCA-Based Identification of Built Environment Factors Reducing PM2.5 Pollution in Neighborhoods of Five Chinese Megacities

Air pollution, especially PM2.5 pollution, still seriously endangers the health of urban residents in China. The built environment is an important factor affecting PM2.5; however, the key factors remain unclear. Based on 37 neighborhoods located in five Chinese megacities, three relative indicators (the range, duration, and rate of change in PM2.5 concentration) at four pollution levels were calculated as dependent variables to exclude the background levels of PM2.5 in different cities. Nineteen built environment factors extracted from green space and gray space and three meteorological factors were used as independent variables. Principal component analysis was adopted to reveal the relationship between built environment factors, meteorological factors, and PM2.5. Accordingly, 24 models were built using 32 training neighborhood samples. The results showed that the adj_R2 of most models was between 0.6 and 0.8, and the highest adj_R2 was 0.813. Four principal factors were the most important factors that significantly affected the growth and reduction of PM2.5, reflecting the differences in green and gray spaces, building height and its differences, relative humidity, openness, and other characteristics of the neighborhood. Furthermore, the relative error was used to test the error of the predicted values of five verification neighborhood samples, finding that these models had a high fitting degree and can better predict the growth and reduction of PM2.5 based on these built environment factors.

Associations between genetic loci, environment factors and mental disorders: a genome-wide survival analysis using the UK Biobank data

It is well-accepted that both environment and genetic factors contribute to the development of mental disorders (MD). However, few genetic studies used time-to-event data analysis to identify the susceptibility genetic variants associated with MD and explore the role of environment factors in these associations. In order to detect novel genetic loci associated with MD based on the time-to-event data and identify the role of environmental factors in them, this study recruited 376,806 participants from the UK Biobank cohort. The MD outcomes (including overall MD status, anxiety, depression and substance use disorders (SUD)) were defined based on in-patient hospital, self-reported and death registry data collected in the UK Biobank. SPACOX approach was used to identify the susceptibility loci for MD using the time-to-event data of the UK Biobank cohort. And then we estimated the associations between identified candidate loci, fourteen environment factors and MD through a phenome-wide association study and mediation analysis. SPACOX identified multiple candidate loci for overall MD status, depression and SUD, such as rs139813674 (P value = 8.39 × 10–9, ZNF684) for overall MD status, rs7231178 (DCC, P value = 2.11 × 10–9) for depression, and rs10228494 (FOXP2, P value = 6.58 × 10–10) for SUD. Multiple environment factors could influence the associations between identified loci and MD, such as confide in others and felt hated. Our study identified novel candidate loci for MD, highlighting the strength of time-to-event data based genetic association studies. We also observed that multiple environment factors could influence the association between susceptibility loci and MD.

A Treatise on Isoattribute Curve Analysis, Consumer Induction Factor, and Country Brand Value

This research has endeavored to focus on three major issues that are yet to be explored as per the existing literature on marketing. The first issue focuses on the Isoattribute curve analysis, rooted in the theory of conjoint utility analysis. In other words, the first segment concentrates on the derivation of the Isoattribute curve model which helps to attain the consumer equilibrium condition in a two-commodity world (brand or non-brand products). The second segment of the chapter has transitioned from the microeconomic model to the macroeconomic perspective based on a ‘single-country' approach, i.e., USA, based on a derivation of consumer induction factor (CIF). Finally, the third and final segment of the chapter extends its horizon at a larger scale by conducting a cross-country time-series study of 10 years (2009 – 2018) which redefines branding in an absolutely new dimension where the ‘brand values' of seven sample countries are estimated by inculcating the socio-economic, political, and working environment factors as the major dimensions.

The Learning Environment and Non-cognitive Values of Secondary School Students in Cross River State, Nigeria

The study examined the predictive influence of learning environment factors on senior secondary school students’ non-cognitive values (attitude to school, interest in school and self-concept). A random sample of 965 senior secondary 2(SS2) students was used for the study. Results revealed, among others, that the learning environment factors jointly significantly predicted each of the non-cognitive characteristics of the students. It was, therefore, concluded that the learning environment, both at home and in school was key to the affective or non-cognitive development of the school learner. It was recommended, among other things, that parents and school administrators should balance firmness and supportiveness in the administration of discipline in homes and schools, respectively.

On Some Developmental Trends for The Russian-Mongolian Relationships

This article made available for publication is compiled on the basis of a report presented at the International Science Conference that took place on September 2nd, 2021, in the city of Vladivostok (Russky Island). It deals with the ordinary and megatrends reflecting the specific aspects in relation to the current stage of the Russian-Mongolian bilateral relationships. Such trends include, for example, diversification of external ties or orientation towards multidimensional collaboration. It is asserted that, throughout the century-old history of close interaction between Russia and Mongolia, since the establishment of diplomatic relations between the two states, there have been a lot of epoch-making events and developments of landmark nature, which up to date constitute the meaningful elements of historic memory for our peoples, defining the overriding megatrend of our mutual understanding and affinity that bears a sustainable character, defying any influence of the political and economic environment factors.

Factors Affecting Compliance to Ethical Standards in Public Procurement in Kenya: A Behavioral Model of Ethical and Unethical Decision Making Perspective

The study sought to investigate the factors affecting compliance to ethical standards in public procurement in Kenya. The study adopted it is specific objectives from a behavioral model of ethical and unethical decision making that is; professionalism factors, social factors, personality factors, legal framework factors and work environment factors on how they affect compliance to ethical standards in public procurement in Kenya. The study adopted descriptive research design as the study design, the population of the study was 40 employees and since the population was small the researcher employed census research design where all employees took part in the research. Primary data collection method was used by administering structured questionnaires. Descriptive statistics, correlation and multiple regression analysis were used to analyze the data. The finding of the study revealed that professionalism factors, legal framework factors, and work environment factors had a positive and statistical significant influence on compliance to ethical standards in public procurement in Kenya. Personal factors and social factors were found not to have statistical significant influence on compliance to ethical standards in public procurement in Kenya. The study recommended that administrative bodies and judiciary should enforce sanction to people who contravenes rules and code of ethics in public procurement. Public organization to invest in training their employees in public procurement code of ethics and rules to avoid the ignorance’s currently observed. This study had implications on knowledge and practices since it did not only investigate factors affecting compliance to ethical standards in public procurement in Kenya but also informed that professionalism factors, legal framework factors and work environment factors were the major factors affecting compliance to ethical standards in public procurement in Kenya.

Analyzing Multiscale Spatial Relationships between the House Price and Visual Environment Factors

House price is closely associated with the development of the national economy and people’s daily life. Understanding the spatial distribution characteristics and influencing factors of the house price is of great practical significance. Although a lot of attention has been paid to modeling the house price from structure and location attributes, limited work has considered the impact of visual attributes. Intuitively, a better visual environment may raise the surrounding house price. When aggregating multiple factors that influence house price, the multiscale geographically weighted regression (MGWR) provides a suitable solution. Specifically, the MGWR assigns each factor a bandwidth to model the spatial heterogeneity, e.g., a factor may have different influences at different places. In this paper, we introduce the visual environment factors into the MGWR method. In detail, we extract ten visual elements, e.g., sky, vegetation, road, from the Baidu street view (BSV) images, using a deep learning framework. We further define six visual environment factors to investigate their influence on house price. Based on the data from two representative Chinese cities, i.e., Beijing and Chongqing, we reveal the influence degree and spatial scale difference of six visual indexes on the house price in two cities. Results show that: (1) the influence intensity of our proposed six visual environment factors on the house price in different regions of the city can be identified, and the green view index (GVI) is the most important visual environmental factor; and (2) the influence of these view indexes changes significantly or even reversely depends on different areas.

The Mangrove Landscape and Zonation following Soil Properties and Water Inundation Distribution in Segara Anakan Cilacap

The mangrove zoning and landscape express the correlation between mangrove vegetation (density, biodiversity and species distribution) with environment factors like as water inundation, seatide, and soil properties. The research was conducted in Segara Anakan Lagoon to analysis community structure and mangrove landscape based on species distribution, biodiversity, environment factors, and mangrove zoning. The results showed that (a) Segara Anakan Lagoon had 4 mangrove zone's were dominated by Sonneratia alba, Rhizophora mucronata, Avicennia marina, Rhizophora apiculata, Rhizophora styllosa, and Nypa frutican; (b) the structure of ecosystem was showed by trend of mangrove ecosystem with equation y = 35.34x2 923.85x + 12817 with x = time (year) and y = mangrove area (ha), mangrove density between 1333367 ind ha-1 (West Segara Anakan) and 899–567 ind ha-1 (East Segara Anakan), dominated species were Nypa frutican, Rhizophora stylosa, Rhizophora apiculata, and Aegiceras corniculatum and mangrove biodiversity between 2,572,65 (moderate); (c) structure of environment factor showed single and semi double-type tides, water debit between 0.360.73 m s-1; water depth between 0.20–23.7 m and water inundation between 480cm; soil texture was clay and loam, soil nitrate of 1.5 mg 100 g-1, soil phosphate of 1.5 mg 100 g-1, C organic of 1.31%, soil pH of 6–7, and soil salinity of 6.5–10 ppt.