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Background: Traumatic injury survivors often experience negative health consequences, impacting recovery. No studies have assessed the feasibility of evaluating the resiliency of hospitalized trauma patients using the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Purpose: The purpose of this study was to determine the most efficient method to collect survey responses on the CD-RISC-10. Methods: This cross-sectional study used a convenience sample of admitted patients with traumatic injury. Patients were randomized to complete the CD-RISC-10 using pen and paper, tablet, or workstation on wheels. Results: Of the 161 patient surveys, the tablet-based survey took the shortest time to complete (2 minutes, 21 seconds), and the paper survey resulted in the lowest percentage of missed questions (0.5%). Trauma patients reported high levels of resiliency. Conclusion: The CD-RISC-10 can be easily administered to trauma patients. Clinicians should balance efficiency and patient preferences when deciding on a survey collection method. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises form the largest group of business entities on the market.It was at the end of 2019 that these small and medium - sized enterprises were most affected by the COVID - 19 anti - pandemic measures.The study itself was performed on small and medium-sized enterprises in the brewing sector due to the direct intervention of anti-pandemic regulations by the Government of the Slovak Republic.The aim of the paper is to point out the results calculated using a one-factor ANOVA model with a fixed factor in the case of application to enterprises included in clusters created on the basis of calculated ratios from national financial statements for 2019.Leven's test of the agreement of the variance of the dependent variable was performed before applying the ANOVA analysis. [ABSTRACT FROM AUTHOR]

This research study aims to enhance our comprehension of organizational legitimacy in rural settings. While many researchers have examined how organizations acquire, manage, and leverage legitimacy in urban ventures, there is still a lack of consensus on the role of different types of legitimacy in rural ventures. This paper distinguishes between two types of legitimacy, political and market legitimacy, and utilizes ANOVA to identify variations in these types of legitimacy based on venture factors such as the leader's education and the venture's age. Our findings suggest that rural ventures tend to have stronger market legitimacy than political legitimacy, and that younger ventures exhibit stronger market legitimacy compared to older ones. [ABSTRACT FROM AUTHOR]

Step pools are micro-geomorphology hosted in gullies which are closely related to the channel erosion rate and hydraulic characteristics of runoff. These features are widely developed in the Yuanmou dry-hot Valley area of the Central Yunnan Plateau, China. In this paper, the morphological characteristics of different types of step pools in the Yuanmou dry-hot Valley were analyzed using analysis of variance and cluster analyses. The results show that: (1) step pools can be divided into differential, bedrock, barrier, and sub-erosion step pools based on the environment of development; the bedrock and differential step pools develop on a large scale, while barrier and sub-erosion step pools develop on a small scale; (2) the width and depth of the step, the height of the step, the width of the pool, and the depth of the step of the differential type, bedrock type, and sub-erosion type step pools exhibited a significant positive correlation (P < 0.01); the height of the step and the depth of the pool of the barrier type step pools were significantly negatively correlated with the height of the step and the concave hole depth of the sub-erosion type (P < 0.01); (3) the differential type and undercurrent type step pools were seriously eroded. The study of the types and morphologies of gully step pools in the Yuanmou dry-hot Valley helps understand the formation and evolution mechanisms of erosion gullies and provides a scientific basis for monitoring and controlling soil erosion. [ABSTRACT FROM AUTHOR]

This research study aims to enhance our comprehension of organizational legitimacy in rural settings. While many researchers have examined how organizations acquire, manage, and leverage legitimacy in urban ventures, there is still a lack of consensus on the role of different types of legitimacy in rural ventures. This paper distinguishes between two types of legitimacy, political and market legitimacy, and utilizes ANOVA to identify variations in these types of legitimacy based on venture factors such as the leader's education and the venture's age. Our findings suggest that rural ventures tend to have stronger market legitimacy than political legitimacy, and that younger ventures exhibit stronger market legitimacy compared to older ones. [ABSTRACT FROM AUTHOR]

The prediction of final semester grades is a crucial undertaking in education, offering insights into student performance and enabling timely interventions to support their academic journey. This paper employs a deep learning approach, specifically gated recurrent unit (GRU), in conjunction with feature optimization using analysis of variance (ANOVA), to forecast final semester grades. The predictive model is trained and evaluated on a handcrafted grade prediction dataset, which contains the academic performance of the students during Plus 2 and from Semester 1 to Semester 4 of a group of Computer science and Engineering majors in Kerala. By processing historical academic records and contextual information, the GRU model learns to predict future performance accurately. To enhance the model's efficacy and interpretability, ANOVA is applied to optimize the feature selection process. This statistical technique identifies the most influential factors contributing to final grades, refining the model's predictive power while reducing dimensionality. The experimental results showcase the model's effectiveness in predicting final semester grades, demonstrating superior accuracy and performance compared to grade prediction using CNN with Bayesian optimization and LSTM with L1-Norm optimization. [ABSTRACT FROM AUTHOR]

Obtaining the required surface finish and geometric accuracy together with attaining high production rate is a challenge in finishing of the inner surfaces of steel pipes and bushes. One of the promising techniques for finishing the surface of metal parts is electrochemical machining. In this paper, the surface roughness and dimensional inaccuracy of the inner surface of a CK45 steel bush were controlled electrochemically. For this, a special electrochemical finishing machine was constructed. The effect of electric potential difference along with temperature, flow rate and concentration of electrolyte on the material removal rate, surface roughness and dimensional accuracy were investigated. Box Behnken design (BBD) was used for designing the experiments. Analysis of variance (ANOVA) was performed for validating the experimental models. Also, multi-objective optimization was performed using response surface methodology (RSM) to achieve a predetermined level of surface roughness and dimensional accuracy along with maximizing the material removal rate. [ABSTRACT FROM AUTHOR]

The objective of this paper was to investigate the Cutting Speed, Feed Rate and Depth of Cut to predict Tool wear during Turning of AISI 1040 Medium Carbon Steel Blanks using Artificial Neural Network Approach. The significance of the cutting parameters was investigated using the Analysis of Variance and results revealed the feed rate as the most influential factor, followed by the interaction of cutting speed and depth of cut. The Artificial Neural Network model exhibited notable correlation coefficients (R) in training (0.81301), validation (0.99932), and test (0.99922) datasets, with an overall coefficient of 0.86662, affirming the model's efficacy in predicting tool wear. The minimum predicted tool wear (0.1007mm) was observed at a 0.50mm depth of cut, cutting speed of 200m/min, and feed rate of 0.15mm/rev, demonstrating a close alignment with the observed data. The ANN predictions effectively capture the intricate relationship between tool wear and process parameters, substantiated by high correlation coefficients. [ABSTRACT FROM AUTHOR]

This paper aims to assess the current knowledge, attitudes, and behaviors of nursing staff regarding sarcopenia and explore associating factors that influence them. Sarcopenia has an insidious onset and is easily overlooked. However, it is has become very common in older people, seriously jeopardizing the quality of life in patients. The present situation of nurses in China is inadequate, even though they are the primary professionals tasked with screening for sarcopenia, the ability to recognize and effectively manage the disease, and the critical role they play in preventing and controlling sarcopenia in patients. We conducted a cross-sectional design of nurses. Facilitated sampling was used in seven hospitals in Jiangsu Province, China. A total of 409 hospital nursing staff participated in the survey from December 2022 to March 2023. The main survey instruments were the nursing staff about the knowledge of sarcopenia, beliefs, a behavior questionnaire, and a self-designed general information questionnaire. Descriptive of general data, t-test, and ANOVA for influencing factors of three dimensions, whereas multiple linear regression analyses were performed using SPSS23.0 software. Questionnaires were distributed to 460 nurses, and of the 426 (92.6%) questionnaires returned, 409 (96.0%) were valid. The total mean score of nurses' knowledge, beliefs, and behavior about sarcopenia was 125.42 (SD 18.97), the mean score of knowledge latitude was 29.09 (SD 7.80), the mean score of attitude dimension was 57.53 (SD 7.63), and the mean score of behavior latitude was 38.80 (SD 10.71). Multiple linear regression analysis revealed that the nurse's position, Knowledge of sarcopenia, whether or not they were specialist nurses and years of experience in the workplace were the most significant factors correlated with the level of knowledge, belief, and practice (P < 0.05). In China, nurses have little knowledge about sarcopenia, but their attitude towards sarcopenia care is positive. However, there is potential for improvement in nursing behavior toward sarcopenia management. Managers are advised to develop targeted training programs for nurses. Further, it improves their screening and diagnosing abilities, allowing them to prevent and control sarcopenia more effectively. [ABSTRACT FROM AUTHOR]