On-line Vis-Nir sensor determination of soil variations of sodium, potassium and magnesium

Bu çalışma, Temmuz 23-26, 2016 tarihlerinde Shanghai[Çin]’da düzenlenen 2. International Conference on Agricultural and Biological Sciences (ABS) Kongresi‘nde bildiri olarak sunulmuştur.Among proximal measurement methods, visible and near infrared (Vis-Nir) spectroscopy probably has the greatest potential for determining the physico-chemical properties of different natural resources, including soils. This study was conducted to determine the sodium, potassium and magnesium variations in a 10. Ha field located in Karacabey district (Bursa Province, Turkey) using an on-line Vis-Nir sensor. A total of 92 soil samples were collected from the field. The performance and accuracy of the Na, K and Mg calibration models was evaluated in cross-validation and independent validation. Three categories of maps were developed: 1) reference laboratory analyses maps based on 92 points 2) Full-data point maps based on all 6486 on-line points Vis-Nir predicted in 2013 and 3) full-data point maps based on all 2496 on-line points Vis-Nir predicted in 2015. Results showed that the prediction performance in the validation set was successful, with average R2 values of 0.82 for Na, 0.70 for K, and 0.79 for Mg, average root mean square error of prediction (RMSEP) values of 0.02% (Na), 0.20% (K), and 1.32% (Mg) and average residual prediction deviation (RPD) values of 2.13 (Na), 0.97 (K), and 2.20 (Mg). On-line field measurement was also proven to be successful with validation results showing average R2 values of 0.78 (Na), 0.64 (K), and 0.60 (Mg), average RMSEP values of 0.04% (Na), 0.13% (K), and 2.19% (Mg) and average RPD values of 1.57 (Na) 1.68 (K) and 1.56 (Mg). Based on 3297 points, maps of Na, K and Mg were produced after N, P, K and organic fertilizer applications, and these maps were then compared to the corresponding maps from the previous year. The comparison showed a variation in soil properties that was attributed to the variable rate of fertilization implemented in the preceding year.FarmFUSE - ICT-AGRI - ERA-NETEuropean Commission under the 7. Framework ProgrammeUK Department of - Environment, Food and Rural Affairs - IF020

Effect of Antioxidants on the Outcome of Therapy in Paraquat-intoxicated Patients

Purpose: The present study was conducted to determine the effect of vitamins C and E administration on the outcome of therapy in patients with paraquat intoxication admitted in the Poisoning EmergencyDepartment (PED) of Noor Teaching General Hospital, Isfahan, Iran.Methods: We studied retrospectively medical records of 186 patients admitted to the PED in two different study periods: 157 patients were evaluated from 1985 to 2001 (first study period) in which patients received conventional treatment protocol consisting of fluid replacement, oral absorbents, haemodialysis, etc, Also, 29 other patients were assessed from 2001 to 2005 (second study period) in which vitamins C and E had been administered to the patients, in addition to the conventional protocol.The patients' mortality rate after the first study period was compared to that of the second one, with regard to the impact of the additional therapeutic intervention (use of antioxidant vitamins).Results: Most of the patients (40.5 %) had ingested more than 20 mL of 20 % paraquat solution and were admitted to the hospital during the first 4 h after exposure. Paraquat poisoning was more common in men (76.6 %), young adults in the age group 19 - 34 (47 %) and during summer (43.3 %). Mean (± SE) length of hospital stay was 62.6 ± 15.6 h. Overall mortality rates were 31 and 55.2 % in the first and second periods, respectively.Conclusion: Although the addition of antioxidants (vitamins C and E) to the conventional therapy did not reduce the mortality rate, other dependent variables including different doses of antioxidants may beconsidered for future studies

The Potential Use of Drones for Tourism in Crises: A Facility Location Analysis Perspective

Considering the recent lockdowns and travel bans due to COVID-19, novel tourism strategies are necessary to face the increasing need for innovative products and services and to ensure long-term sustainable growth. This study looks into the potential use of drones in providing online virtual tours of open-space tourist attractions. To do so, a novel mixed-integer linear mathematical model is developed to optimally determine the number and location of required facilities and the number of drones assigned to each center. The model is applied to a case study of Rome by selecting six historic sites as the tourist attractions and considering several candidate locations for establishing the facilities. The results of different potential scenarios imply that the project is profitable, even if the demand for virtual tours is low

Electro-magneto-thermo-mechanical Behaviors of a Radially Polarized FGPM Thick Hollow Sphere

ABSTRACT In this study an analytical method is developed to obtain the response of electro-magneto-thermoelastic stress and perturbation of a magnetic field vector for a thick-walled spherical functionally graded piezoelectric material (FGPM). The hollow sphere, which is placed in a uniform magnetic field, is subjected to a temperature gradient, inner and outer pressures and a constant electric potential difference between its inner and outer surfaces. The thermal, piezoelectric and mechanical properties except the Poisson's ratio are assumed to vary with the power law functions through the thickness of the hollow sphere. By solving the heat transfer equation, in the first step, a symmetric distribution of temperature is obtained. Using the infinitesimal electro-magnetothermo-elasticity theory, then, the Navier's equation is solved and exact solutions for stresses, electric displacement, electric potential and perturbation of magnetic field vector in the FGPM hollow sphere are obtained. Moreover, the effects of magnetic field vector, electric potential and material in-homogeneity on the stresses and displacements distributions are investigated. The presented results indicate that the material in-homogeneity has a significant influence on the electro-magneto-thermo-mechanical behaviors of the FGPM hollow sphere and should therefore be considered in its optimum design

Improving water resources management using different irrigation strategies and water qualities: Field and modelling study

The aim of this study was to investigate the effects of two different irrigation strategies, regulated deficit irrigation, RDI and partial root drying, PRD using surface freshwater (SW) and brackish treated wastewater (TWW) for maize and potato crops. The SALTMED model has been applied using the field measurements of two cropping seasons 2013 and 2014 at the Canale Emiliano Romagnolo, CER’s experimental farm located in Mezzolara di Budrio (Bologna, Italy). In 2013, PRD irrigated potato received 17% less irrigation water than RDI but produced nearly the same yield as under RDI. The water productivity, o naverage, was 11% higher for PRD compared with RDI. For maize 2014 season, the PRD strategy received almost 15% less irrigation water, but produced a yield only 6% lower than that of RDI and gave equal water productivity to RDI. Given that the two strategies received the same amount of rainfall the results favour the PRD over RDI. Had the site not received above average rainfall (258 mm in 2013 and 259 mm during the 2014 growing seasons), PRD might have produced higher yield and water productivity than RDI. In terms of model simulations, overall, the model showed a strong relationship between the observed and the simulated soil moisture and salinity profiles, total dry mater and final yields. This illustrates SALTMED model’s ability to simulate the dry matter and yield of C3 and C4 crops as well as to simulated different water qualities and different water application strategies. Therefore, the model can run with “what if” scenarios depicting several water qualities, crops and irrigation systems and strategies without the need to try them all in the field. This will reduce costs of labour and investment

Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan

The genetic basis of DOORS syndrome: an exome-sequencing study.

Deafness, onychodystrophy, osteodystrophy, mental retardation, and seizures (DOORS) syndrome is a rare autosomal recessive disorder of unknown cause. We aimed to identify the genetic basis of this syndrome by sequencing most coding exons in affected individuals