ZrO₂ thin film samples were produced by the sol-gel dip coating method. Four different absorbed dose levels (such as ~ 0.4, 0.7, 1.2 and 2.7 Gray-Gy) were applied to ZrO₂ thin films. Hence, the absorbed dose of ZrO₂ thin film was examined as physical dose quantity representing the mean energy imparted to the thin film per unit mass by gamma radiation. Modification of the grain size was performed sensitively by the application of the absorbed dose to the ZrO₂ thin film. Therefore the grain size reached from ~50 nm to 87 nm at the irradiated ZrO₂ thin film. The relationship of the grain size, the contact angle, and the refractive index of the irradiated ZrO₂ thin film was investigated as being an important technical concern. The irradiation process was performed in a hot cell by using a certified solid gamma ray source with 0.018021 Ci as an alternative technique to minimize the utilization of extra toxicological chemical solution. Antireflection and hydrophilic properties of the irradiated ZrO₂ thin film were slightly improved by the modification of the grain size. The details on the optical and structural properties of the ZrO₂ thin film were examined to obtain the optimum high refractive index, self-cleaning and anti-reflective properties.

Proactive coping behavior has been considered an important personal job resource for employees. Organizations have paid considerable attention to the proactive coping behavior of employees to maintain their competitive advantage. The purpose of the current study is to discover the relationship between organizational job resources, work engagement, and proactive coping using structural equation modeling. The participants were 340 licensed Chinese social workers. In the rapidly growing social work sector in China, social work organizations require psychologically connected and dedicated social workers. Findings include the effect of organizational job resources and work engagement on proactive coping. Based on the results, impacts on organizational management are discussed.

Focused Assessment with Sonography for Trauma (FAST) has been widely used and studied in blunt and penetrating trauma for the past 3 decades. Prior to FAST, invasive procedures such as diagnostic peritoneal lavage and exploratory laparotomy were commonly used to diagnose intra-abdominal injuries. Today, the FAST examination has evolved into a more comprehensive study of the abdomen, heart, thorax, inferior vena cava, among others, with many variations in technique, protocols and interpretation. Trauma management strategies such as laparotomy, endoscopy, computed tomography angiography, angiographic intervention, serial imaging and clinical observation have also changed over the years. This technique, at times, has managed to replace computed tomography and peritoneal lavage diagnosis, without producing delays in the surgical procedure. As such, the relationship between the patient’s clinical information and the results of the exam should be guided to guide therapeutic approaches in difficult to access settings such as intensive care units in war zones, rural or remote locations where other imaging methods are not available. This review will discuss the evolution of the FAST exam to its current status and evaluate its evolving role in the acute management of the trauma patient.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.