This study critically examines the multifaceted dynamics of foreign employee integration within the Czech Republic, with a specific focus on the Mladá Boleslav region. Conducted prior to the Ukrainian crisis, this research serves as a crucial baseline for understanding integration in a pre-crisis context and provides comparative insights into the evolving challenges and opportunities amid the subsequent migration movements. The study explores various aspects of integration and inclusion, drawing upon migration theories, economic factors, and sociological perspectives to understand the motivators and challenges faced by foreigners, particularly in light of the majority society’s perception, which often leans towards skepticism and negativity. The research methodology builds on grounded theory and integrates both quantitative and qualitative approaches, utilizing surveys and semi-structured interviews to explore the experiences of foreign nationals, with an emphasis on immigrant women. A key finding of the study is the significant role of employers in facilitating integration. The paper discusses how businesses, through inclusive policies and practices, can profoundly influence the integration experience. Cooperation between employers, local integration centers, and other relevant organizations emerges as vital, providing additional resources and support systems to enhance the integration process. The study concludes by emphasizing the critical role of various stakeholders, particularly employers, in shaping sustainable human resources practices that foster a more inclusive and harmonious society.

Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.

The optimized methodology and results of the new characterization in terms of dose and image quality of the X-ray system used in the main pediatric hemodynamics service in Chile are presented. In addition, scattered dose rate values at the operator’s eye level are reported for all acquisition modes available in different thicknesses of absorbent media and angiography. The characterization was performed according to the European DIMOND and SENTINEL protocols adapted to pediatric procedures. The air kerma at the entrance surface (ESAK) was measured and the image quality parameters signal-to-noise ratio (SNR) and a figure of merit (FOM) were calculated. The scattered dose rate was measured in personal dose equivalent units. The ESAK for fluoroscopic modes ranged from 0.2 to 35.6 μGy/image when passing from 4 to 20 cm of polymethyl methacrylate (PMMA). For the cine mode, these values ranged from 2.8 to 160.1 μGy/image. The values of the image quality parameters showed a correct system configuration, although abnormal values were observed in the medium fluoroscopic mode. As for the scattered dose rate at the level of the cardiologist’s eyes, the highest value is PMMA with a thickness of 20 cm, where the cine mode reached 9.41 mSv·h-1. The differences found from previous evaluations can be explained by the deterioration of the system and the change of one of the X-ray tubes.

Human resource management practices are crucial, especially in the private healthcare sector. This could be because managing personnel in the healthcare sector is particularly challenging; therefore, meeting every employee's needs is crucial. Recently, the healthcare sector has experienced a scarcity and unbalanced distribution of employees due to job turnover. In addition, employee performance in the private healthcare sector has shown a slight drop due to the dissatisfaction of employees toward human resource practices such as unattractive compensation and rewards packages, bias in performance appraisal, lack of training and development, and many more. Therefore, this study is conducted to examine the impact of human resource practices on employees' job performance. Specifically, there are three main human resource practices observed as factors that contribute to an employee's job performance. The three human resource practices are compensation and benefits, performance appraisal, and training and development. There were four private hospitals operating in Selangor, Malaysia, chosen as a sample for this study. The private hospitals are KPJ Selangor Specialist Hospital, Columbia Asia Hospital Puchong, Assunta Hospital PJ, and Sunway Medical Centre. Out of these four private hospitals, there were about 291 employees working at the front desk: nurses, clinical workers, and administration staff were chosen as respondents in this study. The questionnaires were distributed to the respondents by hand. The data collected was analyzed using SPSS version 29. The findings indicate that employee job performance in Malaysian private hospitals is positively correlated with compensation and benefits. Employees feel motivated by compensation, which encourages them to increase their production and work more efficiently. Additionally, the findings also suggest that performance appraisal and training and development significantly contribute to employee job performance.