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.

This study examines how the framing of organizational gender-equity policies shapes support among Generation Z employees. Drawing on performativity (Butler, 1990) and intersectionality (Crenshaw, 1991), we conceptualize framing as mediating how Gen Z employees perceive equity initiatives. Using a mixed-methods design, we combine survey data from 4,861 Gen Z respondents in 30 countries with directed content analysis of four HR policy documents (coded for equity vs enforcement, identity recognition, and youth engagement). Results reveal a gender gap: Gen Z women strongly endorse inclusive equity measures, consistent with evidence that women show stronger support for equality policies, whereas Gen Z men are more skeptical of policies framed as exclusive or punitive – mirroring polls finding many Gen Z men say equality efforts have gone too far. These findings suggest that performative policy framing activates social identities differently by gender and that intersectional policy language affects reception. Practically, we recommend framing equity initiatives in terms of shared fairness and collective benefit, using transparent rationale and inclusive identity language. Gen Zers expect fair pay, inclusive policies, and transparency, so HR communications should emphasize fairness and allyship to enhance legitimacy and support among this cohort.

The structure, thermodynamic stability, ionization potential (IP) and electron affinity (EA) energy level difference (E_g) and tension of lowest unoccupied orbit (LUMO) and highest occupied orbit (HOMO) of armchair single wall carbon nanotubes (C-NTs), BN hybrid carbon nanotubes (BC₂N-NTs) and all BN nanotubes (BN-NTs) were systematically studied with AM1 method in this paper. Calculation results show that when n value is constant, (n, n) C-NTs (n = 3,4,5,6) has the largest diameter and BN-NTs has the smallest diameter; (n, n) the values of E_g (HOMO-LUMO) and n of C-NTs and BC₂N-NTs are related; POAV analysis shows that different hybrid atoms have different contributions to the hybrid mode of nanotube atoms and the tension of nanotubes.