An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications

The identification and modeling of the terrain from point cloud data is an important component of Terrestrial Remote Sensing (TRS) applications. The main focus in terrain modeling is capturing details of complex geological features of landforms. Traditional terrain modeling approaches rely on the user to exert control over terrain features. However, relying on the user input to manually develop the digital terrain becomes intractable when considering the amount of data generated by new remote sensing systems capable of producing massive aerial and ground-based point clouds from scanned environments. This article provides a novel terrain modeling technique capable of automatically generating accurate and physically realistic Digital Terrain Models (DTM) from a variety of point cloud data. The proposed method runs efficiently on large-scale point cloud data with real-time performance over large segments of terrestrial landforms. Moreover, generated digital models are designed to effectively render within a Virtual Reality (VR) environment in real time. The paper concludes with an in-depth discussion of possible research directions and outstanding technical and scientific challenges to improve the proposed approach

Graphene oxide-Fe(III) composite containing phosphate - a novel slow release fertilizer for improved agriculture management

Novel materials offer opportunities to develop new types of fertilizers which could potentially increase efficiency of nutrient use in agriculture. Slow-release fertilizers can be more effective than traditional nutrient sources and simultaneously reduce negative impacts of nutrients to the environment. Using low-cost, abundant natural material, graphite rock, a functionalized graphene oxide (GO)/iron (GO-Fe) composite was synthetised and examined as a new carrier of phosphate ions in order to improve nutrient delivery to plants. The morphology of the composite was examined with scanning electron microscopy (SEM), and X-ray diffraction (XRD) was used to determine the presence of crystal phases. The composite was also characterised with thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR). We found that the presence of ferric ions was responsible for attachment of phosphate ions onto the GO-Fe composite, providing a loading capacity of 48 mg P/g. The kinetics of P release were examined using a column perfusion test while P diffusion in three different types of soils was examined using a visualization technique and chemical analysis. Compared with commercial monoammonium phosphate (MAP) fertilizer, application of GO-Fe composite loaded with phosphate (GO-Fe-P) resulted in slower release of P, thus reducing the possibility for leaching or runoff of soluble P to surface and groundwaters.Ivan B. Andelkovic, Shervin Kabiri, Ehsan Tavakkoli, Jason K. Kirby, Michael J. McLaughlin, Dusan Losi

Ethnic Disparities in Early-Onset Gastric Cancer: a Population-Based Study in Texas and California

BACKGROUND: Incidence rates of gastric cancer are increasing in young adults (age \u3c50 \u3eyears), particularly among Hispanic persons. We estimated incidence rates of early-onset gastric cancer (EOGC) among Hispanic and non-Hispanic White persons by census tract poverty level and county-level metro/nonmetro residence. METHODS: We used population-based data from the California and Texas Cancer Registries from 1995 to 2016 to estimate age-adjusted incidence rates of EOGC among Hispanic and non-Hispanic White persons by year, sex, tumor stage, census tract poverty level, metro versus nonmetro county, and state. We used logistic regression models to identify factors associated with distant stage diagnosis. RESULTS: Of 3,047 persons diagnosed with EOGC, 73.2% were Hispanic White. Incidence rates were 1.29 [95% confidence interval (CI), 1.24-1.35] and 0.31 (95% CI, 0.29-0.33) per 100,000 Hispanic White and non-Hispanic White persons, respectively, with consistently higher incidence rates among Hispanic persons at all levels of poverty. There were no statistically significant associations between ethnicity and distant stage diagnosis in adjusted analysis. CONCLUSIONS: There are ethnic disparities in EOGC incidence rates that persist across poverty levels. IMPACT: EOGC incidence rates vary by ethnicity and poverty; these factors should be considered when assessing disease risk and targeting prevention efforts

Optimisation of phosphate loading on graphene oxide-Fe(iii) composites-possibilities for engineering slow release fertilisers

Current commercially available phosphorus (P) fertilisers, which are highly soluble salts, are susceptible to surface runoff to waterways, and leaching to groundwaters where soils are light/medium textured. Here, we report the synthesis of a graphene oxide (GO)/iron (GO–Fe) composite, a promising carrier for loading P. The GO–Fe carriers loaded with P acted as slow release fertilisers with tunable loading/release properties. The amount of P loaded onto the GO–Fe composite was 15%, similar to commercial products. Investigation of the morphology and spectroscopic and chemical analysis revealed a complex loading mechanism of Fe onto GO. Iron, as an active center for P sorption, could interact with the oxygen functional groups at the edge of GO sheets as well as the π-electron system of the aromatic part of GO. Column perfusion studies, visualisation of P diffusion in soils and chemical analysis of soils after diffusion showed the composites to have slow-release properties. Pot experiments using wheat and our composites resulted in the same yield as using highly soluble commercial fertiliser.Ivan B. Andelkovic, Shervin Kabiri, Rodrigo C. da Silva, Ehsan Tavakkoli, Jason K. Kirby, Dusan Losic and Michael J. McLaughli

Engineered phosphate fertilisers with dual-release properties

A new strategy to produce phosphate (P) fertilizers with both fast and slowly soluble P by the compaction method to produce composite products is presented. This unique composition is created by combining monoammonium phosphate (MAP) as a highly soluble P nutrient source, with a commercially available slow-release P such as struvite (Str) or P-loaded graphene oxide (GO). Graphene oxide-loaded P was synthesized by in situ oxidation of GO and ferrous ion (GO-Fe) mixtures with hydrogen peroxide and further loading of P onto the GO-Fe composite. The nutrient release in water was studied for dual-release MAP-Str and MAP-GO-Fe-P and compared to their corresponding slow- and fast-release sources. Column perfusion experiments showed a biphasic dissolution behavior with no significant difference between MAP-GO-Fe-P and MAP-Str. Visualization of P diffusion and chemical analysis of the soil after diffusion were used to assess the diffusion of P from different P fertilizers in various types of soil. Runoff and leaching simulations were performed to investigate the effects of the prepared fertilizer formulations on the environment. Overall, the diffusion of the dual-release fertilizers and the P loss in runoff and leaching experiments were less than for MAP. The better environmental performance of the dual-release fertilizers compared to MAP was related to the specific properties of the GO-based materials such as their two-dimensional structure and to the low solubility of the Str in the case of Str-based fertilizers.Shervin Kabiri, Ivan B. Andelkovic, Rodrigo C. da Silva, Fien Degryse, Roslyn Baird, Ehsan Tavakkoli, Dusan Losic, and Michael J. McLaughli

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation