High Level Of Reliability Research Articles

Level of tobacco dependence and beliefs towards heated tobacco products

Abstract Nicotine dependence affects not only behaviors related directly to smoking, quit attempts or looking for alternative products but also beliefs about smoking. We sought to assess whether the level of tobacco dependence is associated with beliefs and feelings towards heated tobacco products (HTP) and to assess the relationship between tobacco dependence and the motivators to quit HTP use. Random population sample of Polish citizens aged 18+ years, former smokers, current HTP users was recruited. Tobacco dependence was assessed using 5 question; participants were classified into two groups of tobacco dependence (low or high) using a two-stage cluster analysis. An extensive questionnaire on beliefs on HTP use was administered. The χ2 test and logistic regression were used. There were 2,500 participants (62.6% women) of median age=36 years (Q1=29, Q3=45). The median number of years of smoking was 10 (Q1=5, Q3=15) and median number of years of HTP use was 2 (Q1=1, Q3=3). High tobacco dependence was found in 958 (38,3%) participants. Compared to low dependence, high tobacco dependence was related with feeling of strong need for HTP use (69.7% vs. 47.6%, p < 0,001). High level of tobacco dependence was positively related to perceived social pressure against smoking (72.9% vs. 44.9%, p < 0,001), but it did not differentiate perceived social pressure against HTP use. Compared to low tobacco dependence, participants with high tobacco dependence more often indicated fear of illness OR = 1,73 95%CI=1,46-2,07, own resolution OR = 1,32 95%CI =1,12-1,55 and price OR = 1,34 95%CI=1,13-1,59 as possible motivators to quit HTP use. Level of tobacco dependence in former smokers shaped beliefs and feelings towards HTP use. High tobacco dependence contributed to strong need to use HTP and also increased perception of social pressure against smoking, but not against using HTP. It also increased the importance of fear of illness, price and one’s own resolution as motivators to quit HTP use. Key messages • High level of tobacco dependence in former smokers results in stronger perceived social pressure against smoking but not against HTP use. • High tobacco dependence in former smokers is related with stronger need to use HTP.

Transitions in heating systems and impact on perceived wellbeing: a qualitative study

Abstract Background as part of the larger European WELLBASED project an urban program focusing on transitions in heating to tackle energy poverty, is implemented in 4 disadvantaged, predominantly Roma neighborhoods of Edirne, Türkiye. These neighborhoods have high levels of vulnerability, aid dependency, and energy poverty. This study investigated the impact on perceived wellbeing of implementing the heating system transition. Methods A qualitative methodology was applied; data was collected through semi-structured in-depth interviews among participants in the intervention group of the larger WELLBASED evaluation study. Diversity was ensured regarding gender, age, education level, and working status. Participants were 13 individuals from 13 households in which energy-efficient heating systems were installed. Interviews were audio-recorded, transcript verbatim and coded; thematic analysis was conducted. Results 3 main themes and 7 sub-themes (st) emerged in the preliminary analysis with regard to impact on well-being: perceived changes in living conditions (st: physical changes, financial implications, domestic burden), perceived effects on health (st. mental health, physical health), and expectations versus reality (st. insulation, efficiency). Experiences differed as per housing condition, type of energy used, usage proficiency, and income level. Conclusions Energy efficient heating system transition to tackle energy poverty at homes may not be sufficient to realize impact on perceived wellbeing. Housing conditions (ie. insulation), supported energy sources and management of expectations need to be considered as part of the program.

Implementation of Augmented Reality Teaching and Learning Kit to Enhance Visualization, Motivation and Understanding among TVET Students

Augmented Reality (AR) technology is one of the increasingly preferred choices for educational development of education. This study aims to identify the level of visualization, motivation and understanding by designing and developing an AR application for the topic of Engineering Drawing. This application enhances the user's clarity and comprehension on the types of drawings and the form of the drawing to be presented. The design and development process of this AR application uses the Hannafin and Peck model as a guideline. The research instruments used are expert review forms for product development and questionnaires. The study included a total of 52 students from Sungai Buloh Vocational College, Selangor, as participants. The findings were analysed descriptively using the Statistical Package for the Social Sciences (SPSS) software version 27. The evaluation was conducted on three (3) aspects, namely the level of visualisation, motivation and comprehension of the students, as well as the significance of research to examine the gender differences between the three aspects. The findings of the study revealed that the use of the AR application produced for the three (3) components yielded a favourable outcome with a reliability value of r=0.855, which demonstrates that the instrument possesses a high level of reliability. However, no significant difference was found between the genders of the students that participated in the study. In general, the findings of the study indicate that the implementation of the AR teaching and learning kit has yielded positive outcomes in terms of enhancing students' visualisation skills, motivation levels and comprehension of the Engineering Drawings subject.

Navigating the Social Shift: A Preliminary Study of Consumer Behavior on Malaysia's Social Commerce Platforms

The proliferation of online businesses coupled with the advancement of information and communication technologies (ICT) has led to the emergence of social commerce. The integration of social media platforms into e-commerce offers businesses a convenient avenue for engaging with consumers and a novel method for capturing additional sales volume. This seamless integration of social media platforms into current e-commerce practices has significantly increased its success. Research on the factors that affect purchase intentions in social commerce is still sparse, especially in the context of Malaysian consumers. In general, the causal model of purchase intentions on social commerce in this study aims to investigate the impact of the constructs of visibility and metavoicing on purchase intentions among Malaysian millennial consumers. Henceforth, this initial study specifically aims to evaluate the reliability and validity of the IT affordance constructs of visibility and metavoicing through rigorous assessments. At the items-construct level, the internal consistency assessment was conducted using McDonald’s Omega, which is known for its robustness in measuring the reliability of multi-item constructs. At the construct level, discriminant validity and the strength of linear relationships among variables were assessed using Pearson correlation analysis. The pilot dataset gathered was analyzed with SPSS 29, and the results have validated that the predictive model achieved high levels of reliability and validity at both the item and construct levels. Furthermore, the analysis revealed that the independent variables, metavoicing and visibility, have a significant association with purchase intentions, underscoring their importance in understanding consumer behavior.

The impact of widely used algorithms of large language models on information retrieval and the associated potential risks

Thesis. The aim of this work is to perform an analysis concerning the subject of arti- ficial intelligence integration and its application in modern knowledge acquisition. The article will be an overview of scientific research and papers to raise a discussion of the ad- vantages and potential hazards associated with the widespread implementation of large language models. Concept. The main part of the article will focus on describing the AI enhanced tools available on the market and common ways of utilising them. This knowledge will be jux- taposed with psychological research on human consciousness in the context of decision- making, creativity, and held beliefs to list potential threads related. Results. The analysis of tools that have recently been enhanced with algorithms un- equivocally indicates the dominance of the sector providing informational and creative support. These tools possess a measurably high level of reliability among the public, re- sulting in a reduced number of verification actions. A review of existing literature and research on human psychology shows a very strong correlation between the influence of previous social authorities on decision-making behaviour and an uncritical approach to information obtained through AI. Studies have shown that access to these tools, without proper controlling actions of results, exposes users to bias, manipulation, or susceptibility to marketing activities. Alternatively, with proper and rational use of these implemented algorithms, humans are able to obtain extraordinarily precise and knowledge-based sup- port in decision-making. Similar polarisations of results have been observed in the con- text of creativity, innovation, and inquisitiveness. Originality. The article addresses topics that relate to the psychological nature of hu- mans in the context of new and expanded AI augmented tools. The results of the explora- tory study clearly indicate that programmes supported by algorithms show potential in terms of both scientific and social development. Unfortunately, they also present many potential dangers for both, which, discussed in the foundation, provide the groundwork for more in-depth research.

Human Factors Considerations in Artificial Intelligence Applications for Nuclear Power Plants

In recent years, there has been a wave of artificial intelligence (AI) technologies that offer to solve problems from shopping habits to mortgage approvals to critical systems operations. The rapidity of the development of these systems has led to both excitement and apprehension about the roles these systems should play in our modern societies. This paper focuses on the critical infrastructure industry, in general, and nuclear power generation, in particular, and seeks to scrutinize how we can leverage these novel technologies in human-centered ways to maintain or enhance the established high levels of reliability and resilience in these industries. First, we discuss the broader aspects of cognitive systems and activities that are critical to understanding the human-AI space. Then we explore different approaches to explainability in AI and the notions of trust. We then move on to discuss several human factors concepts and methods and how they can support the design of human-AI teams. We then explore recent research related to nuclear power that has been undertaken and evaluate the current industry and regulatory landscapes. Finally, we discuss identified research gaps and recommendations for solving these for the critical infrastructure space.

Functional Capacity of Institutionalized Older People and Their Quality of Life, Depressive Symptoms and Feelings of Loneliness: A Cross-Sectional Study.

The increasing number of institutionalized older individuals worldwide stresses the need to evaluate the association between the functional profile of institutionalized older adults and their quality of life (QoL), depressive symptoms and feelings of loneliness. A cross-sectional study was conducted in 19 residential facilities in Alentejo, Portugal. Between March and September 2023, all individuals aged ≥65 years were invited to complete a structured questionnaire (n = 1303). Sociodemographic and clinical data were collected, and validated scales for the Portuguese older population were used. Linear regression and unconditional binary logistic models were computed. The highest level of dependence was observed in the self-care dimension (mean (SD) = 2.93 (1.21)), with 40% of participants exhibiting levels of dependence requiring daily care or total replacement. QoL was inversely associated with functionality in all dimensions, as well as with severe or complete dependence, even after adjusting for sex, age and education. Participants with depressive symptoms and feelings of loneliness were, respectively, three and two times more likely to be dependent on care (adjusted OR = 3.69, 95% CI: 1.80-7.52; adjusted OR = 2.04, 95% CI: 1.07-3.87). Public policies and interventions should include social and emotional support strategies alongside traditional medical interventions.

Heartbeat classification using various machine learning models: A comparative study

Cardiac arrhythmias, known as irregular heartbeats, pose a notable health threat that necessitates prompt diagnosis, as untreated arrhythmias can lead to severe heart complications. Among the various methods for arrhythmia detection, electrocardiography is the most prevalent due to its non-invasive monitoring of heart activity. However, manual electrocardiogram (ECG) analysis is inefficient and prone to errors, prompting the exploration of machine learning (ML) models for ECG feature recognition. Integrating ML models with ECG analysis can revolutionize cardiac diagnostics by improving healthcare efficiency and outcomes by enhancing the accuracy and consistency of existing approaches as well as their processing speed for large datasets. Unfortunately, current ML methods encounter two key limitations: prolonged training times and the need for manual feature selection. To address these issues, we propose using ML models enhanced with innovative techniques such as the Fourier transform (FT) and Gaussian noise injection for improved cardiac health assessment. To validate this approach, we utilized statistical tools, including Pearson correlation and p-values, to uncover relationships within the data. In addition, we employed the FT technique to extract and analyze frequency-domain features. Our comparative study of different ML models relied on metrics such as accuracy, precision, recall, F1 score, and receiver operating characteristic area under the receiver operating characteristic curve, demonstrating XGBoost’s impressive average recall of 0.956 with 99.96% overall accuracy. An average precision of 0.956 further underscored the accuracy of XGBoost’s predictions, indicating its high level of reliability in distinguishing various cardiac conditions. These results highlight the considerable potential of ML techniques for precise ECG-based clinical diagnoses, helping healthcare professionals make more accurate and timely decisions in patient care.

Circular economy for the management of disused tyre waste in Chongón - Guayaquil

Scrap tyres can cause a severe environmental impact on the community. To describe the contribution of the circular economy model to the management of scrap tyre waste in Chongón - Guayaquil. Quantitative, descriptive, correlational study, using a survey of 20 vulcanisers in the parish of Chongón in the city of Guayaquil. A high level of reliability was obtained with a Cronbach's alpha of 0.883, as well as a significant correlation between the variables of waste management of scrap tyres and the circular economy model, with a bilateral sig. of <0.05. The disposal of scrap tyres causes severe environmental impacts in the parish of Chongón-Guayaquil, however, the application of an optimal waste management of these wastes, recycling and reusing them in the manufacture of other products, corresponds to the circular economy model, promoting economic development, sustainability and environmental protection.

Developing and Validating Monosyllabic Speech Materials with Psychometric Homogeneity for Young Adult Turkish-Azeri Speakers in Iran and Compiling the Equivalent Word Lists

Background and Aim: For the Word Recognition Score (WRS) test, homogenous lists of words with similar difficulty levels are needed. This study aimed to develop and validate Turkish-Azeri monosyllabic words with phonetic balance and psychometric homogeneity for the WRS test in young adult Turkish-Azeri speakers in Iran and to compile four 25-item word lists. Methods: In this cross-sectional/comparative study, four lists of 25 monosyllabic words with phonetic balance were created by extracting common words from Turkish-Azeri dialects and assessing them in terms of ease of use, familiarity, and relevance. Then, the lists were tested on 40 young adult Azari speakers aged 18–25 years to determine the validity and reliability. Results: All four lists showed adequate face and content validity. Cronbach’s alpha and split-half values for all four lists were above 0.9, indicating acceptable internal consistency and reliability. Construct validity was confirmed the factor analysis with one-dimensional variance of 77.9%, 80.0%, 79.9%, and 88% for the word lists 1 to 4, respectively, and reported the single-factor solution of the index in all four lists. Also, test-retest reliability with a two-week interval with Pearson correlation coefficients of the lists were 0.94, 0.97, 0.97, and 0.96, respectively. Conclusion: The four developed Turkish-Azeri word lists have phonetic balance and psychometric homogeneity with a high level of validity and reliability, which makes them suitable for evaluating the recognition of monosyllabic words by young adults in hearing centers of Azeri cities in Iran. Keywords: Speech audiometry; speech discrimination test; Azeri; monosyllabic; validity and reliability; psychometric function

The preventive health management self-efficacy related to preterm labor scale in reproductive-aged women: Validation of Turkish reliability and factor structure.

This study aims to test and adapt the Turkish psychometric properties of the preventive health management self-efficacy related to premature labor (PHMSE-PL) scale for women of reproductive age. The study follows a methodological approach. The original scale comprises 34 items distributed across 5 subscales and is structured on a five-point Likert scale. The study sample consisted of 351 women aged 19 to 49, all without any physical or mental disabilities, irrespective of marital status or pregnancy status. Exclusion criteria encompassed women engaged in healthcare professions such as medical faculty, nursing, or midwifery, as well as those with a history of preterm birth during pregnancy. During the validity assessment of the scale, language, content, and construct validity were scrutinized. In the reliability phase, internal consistency and stability over time -analyses were conducted. Following confirmation of language validity, all items achieved a content validity index value exceeding 0.80. Exploratory and confirmatory factor analyses were employed to assess structural validity, revealing that the scale retained its original grouping into five sub-factors. These factors collectively accounted for 81.5% of the variance. The Cronbach's alpha coefficient for the entire scale reached 0.98, indicating high internal consistency. Test-retest analyses yielded a correlation coefficient of 0.99 between overall scale scores, demonstrating excellent consistency between the two measurement measurements. The PHMSE-PL scale adapted to Turkish culture demonstrated high levels of validity and reliability.

ANALYSIS OF THE REGULATORY AND METHODOLOGICAL APPARATUS FOR CARRYING OUT TESTS OF ARMORED TANK AND VEHICLE EQUIPMENT TO THE INFLUENCE OF EXTERNAL MECHANICAL AND CLIMATE FACTORS

In the work is carried out an analytical study of normative and methodical support of the processes of testing armored and automobile vehicles to the influence of climatic and mechanical factors. Unsolved aspects of the testing are highlighted. The advantages and disadvantages of conducting tests of military equipment and its components on the influence of external mechanical and climatic factors have been identified for national standards of Ukraine and national standards harmonized with international standards in order to form the direction of further improvement of the regulatory and methodical apparatus to increase the accuracy and reliability of equipment evaluation in operating conditions. The need to improve test methods based on increasing the accuracy and reliability of equipment evaluation during laboratory tests is substantiated. The provisions of foreign military standards, which are used in Ukraine and the world as basic – STANAG 4370, MIL-STD-810 were analyzed. Based on the analysis of these standards, which include requirements for conducting tests, methods, procedures and acceptance criteria for equipment in operational conditions, the direction and method of improving test methods is determined. Prospective directions for ensuring standardization in the process of testing are outlined, in which there is a high need to maintain a high level of reliability and efficiency of armored and automobile vehicles in operational conditions. The need to adapt standards to modern challenges and threats has been established by optimizing test methods in conditions that are as close as possible to real ones, as well as using the latest technologies to improve the processes of monitoring the state of equipment.

A study on music therapy aimed at psychological trauma recovery for bereaved families driven by artificial intelligence.

This study explores the effectiveness of music therapy in repairing psychological trauma in bereaved families, aiming to provide a comprehensive understanding of its potential therapeutic impact. It begins with an analysis of the current situation faced by bereaved families, identifying the psychological challenges they experience. The research design included the recruitment of participants from bereaved families, who were then divided into an experimental group and a control group. An optimized Long Short-Term Memory (LSTM) network model was constructed to analyze music therapy data, tailored specifically to capture the nuances of this therapeutic process. The experimental procedure detailed the specific operations involved in the music therapy sessions and established a clear comparison framework between the two groups. The performance of the proposed LSTM model demonstrated high accuracy (0.85), precision (0.86), recall (0.84), and F 1-score (0.85), indicating its effectiveness in predicting treatment outcomes. When compared to the Self-Reporting Inventory-90 (SCL-90) scale, the model captured the trend of treatment effects with a high level of accuracy and reliability. Notably, participants numbered 2, 6, and 8 in the experimental group showed substantial improvement rates of 67.21%, 71.45%, and 75.67%, respectively, in their psychological health issues. The comparative analysis between the experimental and control groups confirmed that the music therapy approach, as guided by the proposed LSTM model, led to a more significant improvement in psychological health issues for bereaved families. This suggests that the model offers a promising avenue for enhancing the effectiveness of music therapy in this context.

Adaptation of Childhood Emotional Abuse Measurement Instrumen in Indonesia

Childhood emotional abuse has long-term impacts on individuals. A specific measuring instrument to measure the history of childhood emotional abuse in Indonesian adolescents is needed. The current study adapted the Emotional Abuse Questionnaire developed by Momtaz et al. (2022) into an Indonesian version (ID-EAQ). Participants in this study were 100 adolescents aged 17-21 years, selected using a purposive sampling technique. The adaptation was carried out with the guidance of the International Test Commission (2016). The results showed that the ID-EAQ has a high level of validity and reliability with a value of 0.921. It can be concluded that the ID-EAQ is a valid and reliable measuring instrument to measure the history of childhood emotional abuse in adolescent samples

Multi-pressure based environmental vulnerability assessment in a coastal area of Bangladesh: A case study on Cox’s Bazar

Bangladesh ranks among the top 10 countries globally in terms of climate change impacts and faces numerous anthropogenic and natural pressures. Cox’s Bazar, its primary tourist district, is experiencing severe degradation of its physical and ecological environments due to anthropogenic disturbances and climate change. To improve its environmental quality and preserve its ecological resources effectively, it is essential to develop a spatial decision support instrument addressing multi-pressures and cumulative environmental vulnerability (EV). This study presents an expert opinion-independent, scalable, and customizable spatial methodological framework, integrating multi-sourced geospatial data with GIS-based Fuzzy Logic to assess spatial distributions of five pressure groups and their resulting EV in Cox’s Bazar. 18 criteria were chosen based on a structured literature review to evaluate the five pressure groups. Results revealed that 17 % to 27 % of the study area is exposed to high to very high hydro-meteorological, topographic, land resource, anthropogenic, and natural hazard pressures. The EV results indicated that one-third of the study area, majorly covering Kutubdia, Pekua, Cox’s Bazar Sadar, Teknaf, and Ukhia upazilas, is highly environmentally vulnerable. For enhanced environmental protection, this study improved the existing method of environmental protection zoning by introducing a novel zoning approach that integrates in-situ biodiversity data with EV data. This new zoning method delineated 24 % (555 sq. km.) as strict, 45 % (1047 sq. km.) as medium, and 31 % (725 sq. km.) as soft protection zones in the study area. The sensitivity analysis identified land resource pressure as the most influential component of EV. With a correlation coefficient of 0.91, the accuracy assessment confirms a high level of reliability in the EV results. This study provides valuable insights into environmental pressures and vulnerability in Cox’s Bazar, which are crucial for informing policies at various levels, including international and national frameworks, emphasizing terrestrial ecosystem protection, coastal vulnerability mitigation, climate change impact reduction, biodiversity preservation, and sustainable land resource management.

A-193 Optimizing Emergency Laboratory Operations Through Six-Sigma Strategies for Enhanced Efficiency and Effectiveness: A Pilot Study

Abstract Background Quality assurance is vital in laboratory diagnostics to ensure patient safety and accurate results. Laboratories employ internal and external quality control measures, particularly focusing on the analytical phase. Sigma metrics, representing process variation, play a crucial role in assessing accuracy, with Six Sigma setting high standards for operational excellence. This study aims to enhance laboratory testing procedures by analyzing the analytical phase. In 2022, the Emergency laboratory at KFAFH, Jeddah, achieved optimal sigma performance, marking a significant improvement in analytical testing. http://www.westgard.com/sigma-vp-kfafh.htm. In 2023, The study also demonstrated a 30% productivity increase, driven by sustained efforts and Sigma metrics implementation, leading to cost reductions and improved quality. Real-time patient moving averages enhance quality assurance, extending coverage to the total testing process. The primary objectives include redesigning IQC procedures and optimizing resource utilization. This will be accomplished by reducing the frequency of controls, minimizing unnecessary reruns, optimizing resource allocation, and managing total costs, all while ensuring compliance and averting violations. Methods A retrospective-prospective study was conducted at the Emergency Laboratory of King Fahad Armed Forces Hospital in Jeddah, Saudi Arabia, from May 2021 to October 2023. The study assessed 841,558 tests for 131,785 emergency patients. Forty-seven analytes were evaluated for Internal Quality Control and External Quality Control (CAP), with monthly data collection. Chemistry and Hematology parameters were analyzed using Unity Real-Time software on Alinity-ci and Alinity-hq analyzers. Data was collected in three stages: baseline, pre-Sigma verification, post-Sigma implementation, and a sustainability phase. The methodology involved DMAIC model tools like flowcharts, cause & effect analysis, and sigma metric scales. Six Sigma process tools, including DPM and process capability analysis, were used. Interventions included Six Sigma metrics for QC performance, DPM for TAT process improvement, and patient moving average Real-time for proactive risk management in reducing analytical testing variation. Results Excellent performance (> 6 sigma) was achieved for 70% of chemistry test parameters for three control levels.: This indicates a high level of process capability and reliability in laboratory operations, ensuring accuracy and consistency in test results. The study successfully reduced process variation in Emergency Room (ER) laboratory Turnaround times (TATs), leading to an increase in process capability as measured on the Sigma scale, which improved from 1.35 to 3.1, indicating a more robust and efficient laboratory operation. Reducing the cost and efficiency of internal failure controls by 29% and at the same time saving in labor cost/workload marked a decrease in QC frequency from 7.0% to 0.18%, reaching the target goal of TATs and satisfaction. Conclusions The adoption of Six Sigma methodologies resulted in a notable decrease in QC runs, signaling cost savings. These high-quality methods streamline laboratory operations, improve cost-effectiveness for the healthcare system, and ultimately benefit patients and clinicians. Six Sigma methodologies play a crucial role in selecting appropriate QC designs for each parameter, ensuring efficient control while maximizing cost-effectiveness. Emphasizing the importance of suitable QC strategies and continuous technologist training is vital for mitigating analytical errors and enhancing turnaround time through comprehensive automation of the analytical phase.

Theoretical computation of thermodynamic functions of sodium dimer with modified shifted Morse potential

In this article, the asymptotic iteration method and the Laguerre polynomials are employed to obtain the eigensolutions of the Schrödinger equation with modified shifted Morse potential model. Vibrational energy results for sodium dimer have been presented numerically and these results are compared with experimental data from available literatures. With the help of the energy expression, the partition function and other thermodynamic function expressions of this potential model for sodium dimer are obtained, using the Euler MacLaurin’s formula. For various vibrational quantum numbers considered, the thermodynamic functions show high level of dependence on the temperature parameter. These results are justified by the numerical results presented for the thermodynamic functions of sodium dimer. Our results also agree with the available results in literatures and can also serve as a guiding reference in further studies concerning chemical physics and spectroscopy.

Selected applications of satellite technologies in rail transport

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity requirements, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative documents. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the authors, the described methods can also be used in many other tasks related to rail transport.

COMPARISON OF VIRTUALIZATION TECHNOLOGIES TO OPTIMIZE THE USE OF HARDWARE IN DATA CENTERS

Virtualization is a key element in contemporary data centers, enabling efficient resource utilization, enhanced scalability, and cost reduction. This study aims to enhance the comprehension of virtualization technologies and guide the deployment of effective virtualization strategies in data centers. It conducts an analysis of hypervisors such as Hyper-V and Oracle VM VirtualBox, focusing on comparing their physical processor load. This comparison highlights the strengths and weaknesses of each hypervisor, providing insights into their optimal use cases and aiding in informed decision-making for data center optimization. The analysis reveals that Hyper-V offers superior performance and resource allocation efficiency compared to Oracle VM VirtualBox. This superiority is due to Hyper-V's optimization for enterprise and cloud environments, which require high levels of security, reliability, and scalability. Consequently, for data centers aiming for optimal resource utilization Hyper-V is the preferred choice. While Oracle VM VirtualBox demonstrates efficacy in smaller-scale projects and testing scenarios, Hyper-V offers enhanced capabilities tailored for scalable and mission-critical workloads.

A Simple Eco-Friendly HPLC-PDA Method for the Simultaneous Determination of Paclitaxel and Seliciclib in Plasma Samples for Assessing Their Pharmacodynamics and Pharmacokinetics in Combination Therapy for Uterine Sarcoma.

Background/Objectives: Uterine sarcoma, a rare cancer originating in the smooth muscle of the uterus, exhibits high rates of recurrence and metastasis. It represents one of the most challenging types of cancer due to its chemorefractory nature, showing little response to conventional chemotherapy methods and displaying a relative survival rate of 30-40%. A potentially promising approach for treating uterine sarcoma involves combination therapy with paclitaxel (PAC), a microtubule-targeting agent, and seliciclib (SEL), a cyclin-dependent kinase inhibitor. SEL has been identified as a drug that can enhance the effectiveness of PAC through synergistic effects. To further refine this treatment strategy, an efficient analytical tool capable of simultaneously measuring the concentrations of PAC and SEL in blood plasma is needed. This tool would make it easier to study the pharmacokinetic interactions of potential drugs and assist in monitoring therapy when administering this combination treatment. Regrettably, a method meeting these specific requirements has not been documented in the existing literature. Methods: This article introduces the first HPLC technique employing a PDA detector to concurrently measure PAC and SEL levels in plasma. The methodology underwent validation in accordance with the ICH standards for validating bioanalytical methods. Results: The method exhibited linearity in the concentrations ranging from 0.8 to 100 µg mL-1 for both PAC and SEL. The limits of quantification were determined and found to be 1.34 and 1.25 µg mL-1 for PAC and SEL, respectively. All the other validation criteria conformed to the ICH validation standards. The HPLC-PDA method was successfully employed to quantify both PAC and SEL in plasma samples with a high level of reliability (in terms of accuracy and precision). The eco-friendliness of the approach was verified using three thorough assessments. This technique serves as a valuable asset in establishing the correct dosage and administration schedule for the combined treatment involving PAC and SEL, ensuring the desired therapeutic effects and safety in managing uterine sarcoma. Conclusions: The proposed HPLC-PDA method is the first reliable and eco-friendly method developed to simultaneously determine PAC and SEL in high-throughput plasma samples in clinical laboratories.