Co-ordinately embedding machine learning and optimization in the Monte Carlo simulation is proposed as a new framework for reliability evaluation, which is becoming more challenging due to the joining of variability and intermittency of the renewable generation and components’ ageing. As a machine learning method, the dynamic Bayesian belief network predicts the renewable outputs by generating their probability distributions through historical data to overcome the defect of rarely grasping the low-probability events in the traditional methods, which either predict a single-point value or presume a parametric probability distribution. As the internal operation module of the framework, the rolling-horizon unit commitment maintains the complexity of the operation model and meantime punctually updates the predicted renewable generation and the components’ ageing. The dynamic Bayesian belief network and the rolling-horizon unit commitment traverse time step after time step throughout the horizon, and thus form one bid of the Monte Carlo simulation. In each time step, the dynamic Bayesian belief network extracts the probability distributions of the renewable generation, from which the boundary of the commitment is sampled, and the impact of scheduling the generators on their ageing is then accumulated from the commitment. The proposed framework has its effectiveness proved on a microgrid.
Livestock grazing is the most important factor in the destruction of rangeland. The aim of this study was to investigate dung changes in terms of numbers and weight in different grazing zones and the feasibility of modeling changes in the grazing gradient. For this purpose, random plots settled at regular intervals 50,150, 350, 650, and 1050 meters and after counting, dung was transported to the laboratory for drying and determining the dry weight. The result showed that the distance from the sheepfold and reduce grazing pressure, the weight of dung shows a declining trend. Duncan test results showed that had a significant difference (P-value =0.05) in terms of the number and weight of dungs. Also, to predict changes of dung numbers compare to grazing gradient, Quadratic regression showed best fit the coefficient of determination 0.91. Changes of dung dry weight along the grazing gradient with the third grade of regression have a 0.89 coefficient of determination. We can conclude that grazing zones changes are visible, significantly, through the calculation of livestock dung parameters. According to the model\'s results, considering the number of dung is a better method to determine the grazing intensity.
Introduction: Metabolic syndrome (MetS) and obesity are important public health problems associated with adipose tissue mass. Asprosin, visfatin, and subfatin are new members of which fate in MetS and obesity has not been fully revealed yet. Thus, this study was to investigate the association between asprosin, visfatin, subfatin, and biochemical values, demographic data, and body composition measurement values in MetS patients with and without obesity. \nMethods: Blood samples were taken from a total of 90 people, including 31 MetS patients with obesity, 29 MetS patients without obesity, and 30 healthy (control). Asprosine, visfatin, and subfatin were studied by the ELISA method. \nResults: There was a negative correlation between asprosin and Body Mass Index (BMI) in the MetS+Obese group. The correlations between asprosin and urea and fasting insulin (FI) levels in the MetS group were positive and statistically significant (p <0.05). While there was a statistically significant negative correlation (p <0.05) between visfatin and BMI in the MetS+Obese group, the correlation with waist circumference in the MetS+Obese and MetS groups was statistically significant and negative (p <0.05). There was a statistically significant negative relationship (p <0.05) between aspartate aminotransferase (AST) value and visfatin. The results between visfatin values and asprosin and subfatin in all groups were significant (p <0.05). \nConclusion: There is a direct relationship between circulating amounts of asprosin, visfatin, and subfatin hormones and age, weight, height, DBP, HDL-C, AST, ALT, and creatinine. Therefore, asprosin, visfatin, and subfatin hormones are the new biomarkers of metabolic turbulence.
This study aimed at determining the transpiration characters of Juniperus macrocarpa in a close to 40-year-old even-aged stand categorized into three classes based on canopy size, over a two-year period (2011-2012). The site is located in Palaiochora, 77 km south of Chania, on the southwest coast of Crete. Sap flow techniques (Granier-type) were used to determine water use. Annual trends in sap flow were generally bell-shaped, and varying significantly between seasons and canopy classes. Winter sap flow was minimal but trees were active when temperatures were above freezing point and trees depended on deep water (below 60 cm) for transpiration. Rates increased from 1.46Ld-1 in winter to 3.32 Ld-1 in the spring, irrespective of tree canopy class, because of improvement in weather conditions. Maximum transpiration rates were observed during the growing season with an average of 134.42 Ld-1 for dominant trees and 8.68Ld-1 for suppressed ones. The daily variations in photosynthetically active radiation, vapor pressure deficit, air temperature, and surface soil water were the principal drivers for transpiration during the growing season. The findings have shown that climate in Crete does not limit the expansion of J. macrocarpa and that this expansion will have potentially significant impacts on the ecohydrology of the system.
This paper explores the use of multi-criteria optimization to find better combination of parameters of friction welding process to provide better mechanical properties at the welded joints. This is achieved by developing a new hybrid methodology by integrating TOPSIS method and entropy measurement. TOPSIS method is used to find the order preference by similarity to ideal solution. Entropy method is used to find the weights of output responses. The mechanical strength of friction welded joints depends on several process parameters namely size of work piece, spindle speed, friction time, forging time, friction pressure, etc., Better combination of process parameters leads to quality joint, reduction of cost and wastages. Hybrid TOPSIS method was proposed to predict parameters that resulting superior mechanical properties. Specimen were produced with the predicted parameters and tested to confirm the superiority. Taguchi’s L9 orthogonal array is selected for conducting experiments. It is observed that friction time and spindle speed are the foremost factors but friction pressure influences less on mechanical strength.
For today vehicles, ride comfort and dynamic control, are crucial criteria for customers and also for the selection of an appropriate vehicle. Tractors as vehicles are exposed to random vibrations caused by unevenness of road or soil profile, moving elements within the tractor or implements, while setting on a rigid seat without a backrest. Whole-body vibration transmission influences comfort, performance, and long-term health of the operator. This current study is to evaluate and controlled an agricultural tractor whole-body vibration comfort efficiency, which constitutes one aspect of the physical environment that can cause discomfort to operators, based on standard mathematical formulae and frequency analyses. A gravel road texture was selected and used. To assess vibrations transmitted to the operator, vibration dose values, kurtosis, international road roughness index and power spectral densities of the tractor (seat and floor) recorded signals were evaluated. Seat Effective Amplitude Transmissibility values based on the tractor seat pan vibration dose value (controlled and uncontrolled) outputs in the three-direction lateral, longitudinal and vertical) qualify vibration comfort efficiency. Tri-axial accelerometers were usually mounted on the tractor seat pan and floor. Data are frequency weighted in order to model the human response to vibration in that location and direction.