Application of pattern recognition in detection of buried archaeological sites based on analysing environmental variables, Khorramabad Plain, West Iran

Archaeologists continue to search for techniques that enable them to analyze archaeological data efficiently with artificial intelligence approaches increasingly employed to create new knowledge from archaeological data. The purpose of this paper is to investigate the application of Pattern Recognition methods in detection of buried archaeological sites of the semi-arid Khorramabad Plain located in west Iran. This environment has provided suitable conditions for human habitation for over 40,000 years. However, environmental changes in the late Pleistocene and Holocene have caused erosion and sedimentation resulting in burial of some archaeological sites making archaeological landscape reconstructions more challenging. In this paper, the environmental variables that have influenced formation of archaeological sites of the Khorramabad Plain are identified through the application of Arc GIS. These variables are utilized to create an accurate predictive model based on the application of One-Class classification Pattern Recognition techniques. These techniques can be built using data from one class only, when the data from other classes are difficult to obtain, and are highly suitable in this context. The experimental results of this paper confirm one-class classifiers, including Auto-encoder Neural Network, k-means, principal component analysis data descriptor, minimum spanning tree data descriptor, k-nearest neighbour and Gaussian distribution as promising applications in creating an effective model for detecting buried archaeological sites. Among the investigated classifiers, minimum spanning tree data descriptor achieved the best performance on the Khorramabad Plain data set. © 2016 Elsevier Ltd

A study of the photoneutron dose equivalent resulting from a Saturne 20 medical linac using Monte Carlo method

High energy linacs have several advantages including lower skin dose and higher dose rate at deep sighted tumors. But, at higher energies photonuclear reactions produce neutron contamination. Photoneutron contamination has been investigated from the early days of modern linacs. However, more studies have become possible using Monte Carlo codes developed in recent years. The aim of this study was to investigate the photoneutron spectrum and dose equivalent produced by an 18 MV Saturne linac at different points of a treatment room and its maze. The MCNP4C code was used to simulate the transport of photoneutrons produced by a typical 18 MV Saturne linac. The treatment room of a radiotherapy facility in which a Saturne 20 linac is installed was modeled. Neutron dose equivalent was calculated and its variations at various distances from the center of the X-ray beam was studied. It was noted that by increasing the distance from the center of the beam, fast neutrons decrease rapidly, but thermal neutrons do not change significantly. In addition, the photoneutron dose equivalent was lower for smaller fields. The fast photoneutrons were not recorded in the maze. It can be concluded that the fast photoneutrons are highly attenuated by concrete barrier, while the slow photoneutrons are increased. In addition, increasing the X-ray field size increases the photoneutron dose equivalent around the treatment room and maze. It seems that the walls play an effective role in increasing the photoneutron dose equivalent

Estimating the Absorbed Dose to Critical Organs During Dual X-ray Absorptiometry

Objective: The purpose of this study is to estimate a patient's organ dose (effective dose) during performance of dual X-ray absorptiometry by using the correlations derived from the surface dose and the depth doses in an anthropomorphic phantom. Materials and Methods: An anthropomorphic phantom was designed and TLDs (Thermoluminescent Dosimeters) were placed at the surface and these were also inserted at different depths of the thyroid and uterus of the anthropomorphic phantom. The absorbed doses were measured on the phantom for the spine and femur scan modes. The correlation coefficients and regression functions between the absorbed surface dose and the depth dose were determined. The derived correlation was then applied for 40 women patients to estimate the depth doses to the thyroid and uterus. Results: There was a correlation between the surface dose and depth dose of the thyroid and uterus in both scan modes. For the women's dosimetry, the average surface doses of the thyroid and uterus were 1.88 μGy and 1.81 μGy, respectively. Also, the scan center dose in the women was 5.70 μGy. There was correlation between the thyroid and uterus surface doses, and the scan center dose. Conclusion: We concluded that the effective dose to the patient's critical organs during dual X-ray absorptiometry can be estimated by the correlation derived from phantom dosimetry

Performance, kinetic, and biodegradation pathway evaluation of anaerobic fixed film fixed bed reactor in removing phthalic acid esters from wastewater

Emerging and hazardous environmental pollutants like phthalic acid esters (PAEs) are one of the recent concerns worldwide. PAEs are considered to have diverse endocrine disrupting effects on human health. Industrial wastewater has been reported as an important environment with high concentrations of PAEs. In the present study, four short-chain PAEs including diallyl phthalate (DAP), diethyl phthalate (DEP), dimethyl phthalate (DMP), and phthalic acid (PA) were selected as a substrate for anaerobic fixed film fixed bed reactor (AnFFFBR). The process performances of AnFFFBR, and also its kinetic behavior, were evaluated to find the best eco-friendly phthalate from the biodegradability point of view. According to the results and kinetic coefficients, removing and mineralizing of DMP occurred at a higher rate than other phthalates. In optimum conditions 92.5, 84.41, and 80.39% of DMP, COD, and TOC were removed. DAP was found as the most bio-refractory phthalate. The second-order (Grau) model was selected as the best model for describing phthalates removal

Scaling Consultative Selling with Virtual Reality: Design and Evaluation of Digitally Enhanced Services

Virtual, augmented, and mixed reality technologies allow creation of powerful customer experiences and illustrative demonstrations especially in use cases that benefit from spatial visualizations. Our study focuses on the natural resource management sector and digitalizing of consultative selling process. More specifically, we look at how to improve customer engagement with the use of virtual reality (VR) and thus digitally scale consultative selling. In this process, a VR application is used to demonstrate various management operations and their economic results. Design research methodology is applied to a pre-development phase and three application development iterations between 2016 and 2018. Data consists of user interviews and video observations (N = 129) during various development iterations and three application development plans. The results show that VR offers an emotionally engaging and illustrative tool in consultative selling. Further, it opens a novel way for interaction between the salesperson and customer and possibilities to scale consultative selling digitally, emphasizing the role of trust.Peer reviewe

Global, regional, and national burden of chronic kidney disease, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, −1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, −1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI

Investigating relationships between cost and CO₂ emissions in reinforced concrete structures using a BIM-based design optimisation approach

An integrated design approach for the cost and embodied carbon optimisation of reinforced concrete structures is presented in this paper to inform early design decisions. A BIM-based optimisation approach that utilises Finite Element Modelling (FEM) and a multi-objective genetic algorithm with constructability constraints is established for that purpose. A multilevel engineering analysis model is developed to perform structural layout optimisation, slab and columns sizing optimisation, and slab and columns reinforcement optimisation. The overall approach is validated using real buildings and the relationships between cost and carbon optimum solutions are explored. The study exhibits how cost effective and carbon efficient solutions could be obtained without compromising the feasibility of the optimised designs. Results demonstrate that the structural layout and the slab thickness are amongst the most important design optimisation parameters. Finally, the overall analysis suggests that the building form can influence the relationships between cost and carbon for the different structural components