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This study examines the influence of career satisfaction and self-esteem on job stress among selected workers in the Lagos metropolis. The research aimed to explore how career satisfaction and self-esteem contribute to job stress and to identify potential differences in job stress experiences across demographic groups. Participants were approached at their respective locations within a school environment, and their consent was sought before administering questionnaires. Rapport was established to ensure participants felt comfortable, and sufficient time was given to read and clarify the questionnaire contents. The questionnaires, distributed with the assistance of research assistants, were carefully completed and scored according to the prescribed scales. Data collected were analyzed using the Statistical Package for Social Sciences (SPSS). Descriptive and inferential statistics were employed to interpret the results. Pearson Product Moment Correlation was used to examine relationships between job stress, career satisfaction, and self-esteem. Linear regression analysis assessed the predictive power of career satisfaction and self-esteem on job stress. Additionally, T-tests were conducted to explore differences in job stress levels based on gender and age. Findings from this study contribute to understanding the interplay between career satisfaction, self-esteem, and job stress, providing insights for developing workplace interventions aimed at reducing stress and enhancing employee well-being. [ABSTRACT FROM AUTHOR]

This study aims to evaluate how SiO2 fiber additions affect the mechanical properties of hybrid nanocomposites composed of polypropylene (PP), sisal, and Kevlar fibers. Different concentrations of SiO2 are integrated into these composites to systematically analyze their tensile, flexural, and impact strengths. Utilizing G-power calculations with 80% power and α = 0.05 ensures robust statistical analysis, which indicates significant variations in mechanical properties across SiO2 compositions (p < 0.05). The results reveal that higher SiO2 fiber content significantly enhances the mechanical performance of the composites, suggesting potential applications in advanced materials engineering. This study underscores the importance of SiO2 in improving the mechanical properties of PP/sisal/Kevlar fiber hybrid nanocomposites. [ABSTRACT FROM AUTHOR]

Satisfaction among shoppe and Facebook application users is a need that local people want to get the products they want or it could also be called loyalty for their satisfaction. Based on the results of this research survey, it can be seen and compared what percentage of people are satisfied with shoppe users and Facebook users in terms of brand level, quality, price and others. The e-serqual method used in this research is to measure the level of satisfaction and loyalty on shoppe and Facebook using a distributed questionnaire. From the results of this research, it is found that Shoppe is superior to Facebook, where in the Likert scale calculation using the e-Serqual method and assisted by SPSS, there is a value that almost the application users prefer Shoppe to Facebook based on the site organization satisfaction level. Reliability, User Friendliness, Personal Need while the shoppe Loyalty level has a positive value with Responsiveness, User Friendliness, Efficiency. [ABSTRACT FROM AUTHOR]

Copyright of Al Bashaer Economic Journal is the property of Al Bashaer Economic Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and Communication Research of the Hanover University of Music, Drama and Media, we have transitioned the SDA education to R. We share our concept and demonstrate its success. The results of an online survey indicate that students perceived most teaching elements as helpful, recognizing both opportunities and challenges. We present key learnings designed to assist others in successfully integrating R into SDA education. [ABSTRACT FROM AUTHOR]

Abstract Air pollution is a multifaceted issue affecting people’s health, environment, and biodiversity. Gaining comprehension of the interactions between natural and anthropocentric pollutant concentrations and local climate is challenging. This study aims to address the following two questions: (1) What is the influential mechanism of climatic and anthropogenic factors on the ground-level ozone (O3) concentrations in an urban environment during different seasons? (2) Can the ozone weekend effect be observed in a medium-sized city like Craiova, and under which conditions? In order to answer these questions, ozone interactions with meteorological parameters (temperature, pressure, relative humidity) and pollutant concentrations (particulate matter, carbon dioxide, volatile organic compounds, formaldehyde, nitrogen dioxide, nitric oxide and carbon monoxide) is evaluated based on a one-year dataset given by a low-cost sensor and one-year dataset provided by the National Environment Agency. Using two statistical analysis programs, Python and SPSS, a good understanding of the correlations between these variables and ozone concentration is obtained. The SPSS analysis underscores the significant impact of three meteorological factors and nine other pollutants on the ozone level. A positive correlation is noticed in the summer when sunlight is intense and photochemical reactions are elevated. The relationship between temperature and ozone concentration is strong and positive, as confirmed by Spearman’s rho correlation coefficient (r = 0.880). A significant negative correlation is found between relative humidity and ozone (r = -0.590). Moreover, the analysis shows that particulate matter concentrations exhibit a significant negative correlation with ozone (r ≈ -0.542), indicating that higher particulate matter concentrations reduce ozone levels. Volatile organic compounds show a significant negative correlation with ozone (r = -0.156). A negative relationship between ozone and carbon dioxide (r = -0.343), indicates that elevated carbon dioxide levels might also suppress ozone concentrations. A significant positive correlation between nitrogen dioxide and ozone (r = 0.060), highlights the role of nitrogen dioxide in the production of ozone through photochemical reactions. However, nitric oxide shows a negative correlation with ozone (r = -0.055) due to its role in ozone formation. Carbon monoxide has no statistically significant effect on ozone concentration. To observe the differences between weekdays and weekends, T-Test was used. Even though significant differences were observed in temperature, humidity, carbon dioxide, volatile organic compounds, nitrogen dioxide, nitric oxide and carbon monoxide levels between weekdays and weekends, the T-Test did not highlight a significant weekend ozone effect in a mid-sized city as Craiova. Using Python, the daily values were calculated and compared with the limit values recommended by the World Health Organization (WHO) and European Environment Agency (EEA). The WHO O3 recommended levels were exceeded for 13 times in one year. This study offers a comprehensive understanding of ozone pollution in a mid-sized city as Craiova, serving as a valuable reference for local decision-makers. It provides critical insights into the seasonal dynamics of ozone levels, emphasizing the significant role of temperature in ozone formation and the complex interactions between various pollutants and meteorological factors.

E-learning is becoming the courseware in this global digital era transforming how learning takes place. Regardless of distance and time, e-learning is becoming unstoppable with its synchronous and asynchronous mode of instructional presentation. This study investigated the impact of e-learning on lecturers’ knowledge of quantitative data analysis in SPSS at the Federal College of Education (Special) Oyo State, Nigeria. A descriptive survey research design was adopted in the study. A total number of one hundred and fifty (150) lecturers were selected through simple random sampling techniques for the study. Purposive sampling was used to select the school that was adopted for the study. Three (3) Research questions were generated and answered in this study. Data collected from the sampled population employing a questionnaire were analyzed using simple percentages and mean scores to answer the three research questions. The results of the findings revealed that e-learning is an important platform accessible and utilized by college lecturers. The findings also revealed that lecturers gained knowledge in data analysis in SPSS through an e-learning platform as it serves as a research and leisure tool which provides various opportunities to many people worldwide, particularly college of education lecturers.

PT Inti Jasa Kreatif is an Event Organizer company that relies heavily on the quality of information systems to maintain smooth operations, efficiency, and client satisfaction. This company uses websites to convey business information. To improve the quality of design and user interaction, PT Inti Jasa Kreatif uses the WebQual 4.0 method in analyzing website quality. This study will analyze the quality of the service information system www.intijasakreatif.co.id with a focus on the aspects of usability, informativeness, and trustworthiness, measuring client needs and satisfaction with services using the Webqual 4.0 method. The Webqual 4.0 method is a method developed to measure the quality of web-based services with the data used being the respondents of the questionnaire that has been distributed. The data collection method uses primary data in the form of questionnaires distributed to 102 respondents. Based on data processing, it can be seen that in the validity test of variable X1 (Usability Quality) the results show that variable X1 correlates with the potential quality of website usability that respondents find it easy to use the website application. From the results above, the author concludes that variable X1 has more influence than variables X2 and X3 on user satisfaction.

Air pollution is a multifaceted issue affecting people's health, environment, and biodiversity. Gaining comprehension of the interactions between natural and anthropocentric pollutant concentrations and local climate is challenging. This study aims to address the following two questions: (1) What is the influential mechanism of climatic and anthropogenic factors on the ground-level ozone (O3) concentrations in an urban environment during different seasons? (2) Can the ozone weekend effect be observed in a medium-sized city like Craiova, and under which conditions? In order to answer these questions, ozone interactions with meteorological parameters (temperature, pressure, relative humidity) and pollutant concentrations (particulate matter, carbon dioxide, volatile organic compounds, formaldehyde, nitrogen dioxide, nitric oxide and carbon monoxide) is evaluated based on a one-year dataset given by a low-cost sensor and one-year dataset provided by the National Environment Agency. Using two statistical analysis programs, Python and SPSS, a good understanding of the correlations between these variables and ozone concentration is obtained. The SPSS analysis underscores the significant impact of three meteorological factors and nine other pollutants on the ozone level. A positive correlation is noticed in the summer when sunlight is intense and photochemical reactions are elevated. The relationship between temperature and ozone concentration is strong and positive, as confirmed by Spearman's rho correlation coefficient (r = 0.880). A significant negative correlation is found between relative humidity and ozone (r = -0.590). Moreover, the analysis shows that particulate matter concentrations exhibit a significant negative correlation with ozone (r ≈ -0.542), indicating that higher particulate matter concentrations reduce ozone levels. Volatile organic compounds show a significant negative correlation with ozone (r = -0.156). A negative relationship between ozone and carbon dioxide (r = -0.343), indicates that elevated carbon dioxide levels might also suppress ozone concentrations. A significant positive correlation between nitrogen dioxide and ozone (r = 0.060), highlights the role of nitrogen dioxide in the production of ozone through photochemical reactions. However, nitric oxide shows a negative correlation with ozone (r = -0.055) due to its role in ozone formation. Carbon monoxide has no statistically significant effect on ozone concentration. To observe the differences between weekdays and weekends, T-Test was used. Even though significant differences were observed in temperature, humidity, carbon dioxide, volatile organic compounds, nitrogen dioxide, nitric oxide and carbon monoxide levels between weekdays and weekends, the T-Test did not highlight a significant weekend ozone effect in a mid-sized city as Craiova. Using Python, the daily values were calculated and compared with the limit values recommended by the World Health Organization (WHO) and European Environment Agency (EEA). The WHO O3 recommended levels were exceeded for 13 times in one year. This study offers a comprehensive understanding of ozone pollution in a mid-sized city as Craiova, serving as a valuable reference for local decision-makers. It provides critical insights into the seasonal dynamics of ozone levels, emphasizing the significant role of temperature in ozone formation and the complex interactions between various pollutants and meteorological factors. [ABSTRACT FROM AUTHOR]

Introduction: Pneumonia which is a form of acute lower respiratory tract infection, affects the lung parenchyma and destructs alveolar air space. Pneumonia continues to be a leading cause of morbidity and mortality in children. An institutional cross-sectional study was employed. Aim: The aim of this study specifically focused on dynamically monitoring the levels of specific biomarkers, including C-reactive protein (CRP), soluble triggering receptor expressed on myeloid cell (s-TREM), Chitinase-3-like protein 1 (CHI3L1) and white blood cell (WBC) in the blood (serum) of children with pneumonia. Material and methods: The study involved 120 children diagnosed with pneumonia in Iraq, classified into different age groups. In total, 53 individuals with pneumonia infection were investigated. Biomarker levels including sTREM-1, CRP, CHI3L1, and WBC were analyzed to assess the severity of the disease. The data was collected from November 2023 to April 2024 and analyzed using SPSS software and Microsoft Excel 2019. Pearson's correlation was used to evaluate the relationship between biomarker levels and pneumonia severity. Results and discussion: The results indicated that pneumonia was more frequent in children of under 5 years old. Interestingly, sTREM-1 level was consistently higher than other biomarkers, while WBC counts were the lowest among all biomarkers in all ages and pneumonia cases of study children. These differences were statistically significant, meaning they are likely not random findings. Conclusions: sTREM-1 followed by CHI3L1 may be more useful tools for identifying pneumonia and assessing its severity in young children compared to traditional biomarkers like WBC and CRP. [ABSTRACT FROM AUTHOR]

During the current study, several single odometer tests were executed to explore the exert an influence of initial saturation levels on the collapsibility of both natural and polymer-treated gypseous soil. Two gypseous soils with different gypsum concentrations (18 and 58%) were taken from various locations within the Salah-Al-Deen government in Iraq. Many studies have examined the influence of polymer content on the shear strength, collapsibility, and permeability of gypseous soil. This study aims to ascertain how polymer-treated compacted gypseous soils at field dry unit weight are influenced by the initial saturation ratio considering their collapsibility. Soils were compacted with different initial water content to specify different initial saturation levels from 20 to 90% for each case. Polymer was added to soils with three percent (3, 6, and 9%). The stabilizer concentration of the polymer was previously diluted in water added to the soil mixture. Depending on the moisture content, the dilution ratio was specified to achieve a certain saturation degree and the amount of stabilizer used. The results show that the collapse index sharply dropped as the beginning saturation ratio increased. The optimum initial saturation level that achieves minimum collapse index is 50% for natural and polymer-treated soil. The optimum polymer content that achieved the minimum collapse index was 3%. The soil was compacted at an initial saturation level of 50% and polymer content of 3%, decreasing the collapse index for soil with gypsum content of 18% and 58% by 92% and 89%, respectively. A theoretical equation (which yielded an R2 value of 0.925) was predicted to calculate the potential collapse index of natural and polymer-treated gypseous soils that incorporates all the coefficients studied during this research. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Road congestion in Amman City has been increasing yearly, due to the increase in private car ownership and traffic volumes. This study aims to (a) evaluate the toll road's effects on society and the economy in Amman, Jordan, through a survey questionnaire using statistical software (SPSS), (b) assess the impact of the toll road on reducing congestion and delays using micro-simulation (VISUM), (c) identify the optimal toll price for a selected road using VISUM and (d) validate the simulated models with the optimal revenue. Traffic, geometric, and cost data about the toll technique of two sections on the Airport Highway (from the Ministry of Foreign Affairs to the Madaba Interchange; and from the Madaba Interchange to the Queen Alia International Airport (QAIA) Interchange) were used for simulation purposes. The toll road (across seven different scenarios at different prices) was evaluated for optimal revenue. The survey questionnaire was made based on all scenarios, including the AM peak hour. The operation cost for the toll road was determined based on the Greater Amman Municipality (GAM). The best scenario was determined based on the value of revenue (JOD). The results indicate that higher acceptance is achieved when applying road pricing during the AM peak hour and that users prefer the charging method based on travelled distance (54.02%). Additionally, the total cost of the manual toll collection (MTC) method is 126,935 JOD. Road pricing can reduce traffic delay (or speed up traffic flow) by 4.61 min in the southbound direction and by 9.52 min in the northbound direction. The optimal toll value is 0.25 JOD (34.08%), with revenues of 1089.6 JOD for 2024 and 1122.6 JOD for 2025. Eventually, applying road pricing on the airport road is shown to be effective and economically feasible only when using the manual method. [ABSTRACT FROM AUTHOR]

This study explores the deployment analysis of the Synergistic Cyber Security Awareness Model for the Elderly (SCSAM-Elderly) in Malaysia. The incidence of cyber security events has been steadily increasing, particularly affecting the elderly demographic. The SCSAM-Elderly has been developed to address persistent challenges posed by cybercrimes, such as phishing, romance scams, and identity theft, with the primary objective of educating and heightening awareness among the elderly. Designed to be user-friendly and tailored for the elderly population, the SCSAM-Elderly aims to enhance their awareness. The study's objective is to analyze the pre-survey and post-survey data collected from elderly individuals in Malaysia using SPSS to confirm and validate the effectiveness of the SCSAMElderly model. Surveys were distributed to 50 elderly individuals in Melaka, and the data were analyzed using SPSS Version 27.0. This study employed a paired sample t-test, a statistical method used to determine if there is a significant difference between the average scores of two related groups. In this study, the two groups are the pre-survey and postsurvey scores from the same participants. The results indicated that the SCSAM-Elderly model showed a significant increase in awareness after the implementation of cybersecurity training compared to before the training. The findings indicate that elderly individuals who underwent cyber security awareness training using this model demonstrated an improved ability to detect and counteract the impacts of cybercrimes. The novelty of this study lies in being the first cybersecurity awareness model focusing on the elderly with less technicality. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Most construction projects in Telangana, India, are subject to time and cost overruns. This phenomenon may adversely affect the progress of the construction industry in Telangana, India, and potentially lead to the collapse of many construction organizations. This study focuses on identifying and evaluating the factors contributing to time and cost overruns in construction projects in Telangana, India, specifically in the construction of irrigation projects. To achieve the objectives of this study, initial questionnaire surveys were conducted, followed by factor analysis of time and cost overruns. Approximately ten projects were visited, and data were collected over a span of twenty-two months. The factors causing time and cost overruns in irrigation construction projects in Telangana were categorized into four major groups: manpower-related, machinery-related, equipment-related, and financial-related. These factors were analyzed using Statistical Package for Social Sciences (SPSS) software for factor analysis. Factor analysis was conducted using two distinct approaches: Exploratory Factor Analysis which explores underlying structures without prior hypotheses and Confirmatory Factor Analysis (CFA) which tests a pre-specified model, requiring prior knowledge. EFA and CFA are complementary techniques for understanding the underlying structure of a set of variables. CFA can refine the factor structure suggested by EFA. The combined results from these analyses contribute to the development of reliable and valid measurement scales. [ABSTRACT FROM AUTHOR]

Background: African higher education institutions lag behind their global counterparts in the number of research outputs produced. To address this shortcoming, early-career researcher development programmes play a critical role. Monitoring and evaluation (ME) are vital in assuring that such programmes deliver meaningful outcomes. However, ME is an expensive process, which is problematic in the resource-constrained context of the African continent. Traditionally, practitioners use expensive data analysis software suites such as the Statistical Package for the Social Sciences (SPSS) for analysing quantitative ME data. Although open-source programming languages such as Python are free to use, there are no libraries in Python aimed at the analyses needed for quantitative ME data, resulting in a steep learning curve for new Python users. Objectives: The objective of this article was to develop a Python library of functions to make Python a user-friendly alternative for analysing quantitative ME data. Method: A Python library of functions automating ME data analysis procedures was developed. The Python ME library was tested in this article on quantitative evaluation data of an early-career researcher development programme event and the output compared to that obtained using the SPSS general user interface (GUI). Results: The Python ME library functions produced identical results to the output produced using the SPSS GUI. Conclusion: The results showed that the Python ME library makes Python a viable, free and time-saving alternative for the analysis of quantitative ME data. Contribution: This article contributes by providing a free alternative method for analysing quantitative ME data, which can help evaluation practitioners in the developing world reduce the costs associated with evaluating capacity development programmes.

In Ethiopia, investigation of fiber quality and commercialization is limited to conventional cotton and there is no fiber property analysis for Organic and genetically modified cotton. The objective of this study is to characterize organic and genetically modified cotton and compare them to conventional cotton varieties. Conventional varieties with chemically treated and untreated seed cotton; organic and genetically modified cotton samples were collected using random sampling methods from different regions of Ethiopia. Cotton fiber qualities are tested on High-Volume Instruments based on the ASTM standard. The tested data is experimentally designed and analyzed using SPSS software version 22. The model is significant for the effect of fiber quality parameters on the similar and different cotton varieties p

Dünya genelinde yaşanan enerji kaynaklarındaki yetersizlik ve aşırı fiyat artışları, mevcut kaynakların sürdürülebilir şekilde kullanılmasını gerekli kılmıştır. Var olan kaynakların korunması ve tüketimin tasarruflu olarak yapılması enerjinin sürdürülebilir kullanımını sağlayacaktır. Bu bağlamda, özellikle enerjinin kullanımının kontrolüne yönelik faaliyetlerin yürütülmesi son derece önemlidir. Bu nedenle yapılan bu çalışmada, Bursa ilinde merkez kamu kurumlarında görev yapan personelin, elektrik enerjisi kullanım alışkanlıkları ve enerji tüketimi konusundaki duyarlılıklarını belirlemeye yönelik bir anket çalışması gerçekleştirilmiştir. İlgili kurumlarda yönetici pozisyonu dışında çalışan toplam 1405 personele uygulanan 25 soruluk anket çalışması neticesinde elde edilen veriler, Statistical Package for the Social Sciences (SPSS) programıyla değerlendirilmiştir. Değerlendirme sonucunda enerji ve özellikle elektrik enerjisi tasarrufu konusunda katılımcıların kontrollü tüketim alışkanlığına sahip oldukları ve mevcut enerji kaynaklarının korunma ve sürdürülebilirliğinin temin edilmesi hususunda duyarlı oldukları belirlenmiştir.

This study examines the influence of different behavioral biases on the investment choices made by individual investors in the Indian capital market. The study utilizes a cross-sectional design, which entails gathering a substantial amount of data at a specific point in time. The study employed a survey methodology to collect data from a sample of 497 individual investors using purposive and snowball sampling. The data was collected using structural equation modeling (SEM), utilizing SPSS version 25 and AMOS version 26 as statistical software. This study characterizes individual investors as displaying irrational conduct. The study reveals a significant and positive association between representativeness, anchoring, and loss aversion biases and the investment decision-making process of individual investors in India. This study will enhance the current corpus of literature by examining the field of behavioral finance, which is gaining acknowledgment. Furthermore, few researchers have specifically examined these biases in developing countries, such as India.

Introduction: Hypertension is the leading modifiable cause of premature death and hence World Health Organization (WHO) has made it one of its global prevention priorities. It is a major risk factor for stroke, myocardial infarction, vascular disease, and chronic kidney disease. The prevention and treatment of hypertension imposes a significant public health challenge owing to its related morbidity and mortality as well as the expense to society. Hypertension is referred to as a silent and an invisible killer and affects at least 1.4 billion people globally. Less than half of adults (42%) with hypertension are diagnosed and treated. Methodology The research design was an institution based single centered, observational descriptive study, cross sectional in design and was carried out for a duration of 28 days (4 weeks) from 01.06.2024 to 29.06.2024. The study was conducted in the Outpatient Department (OPD) of Regimenal therapies, National Institute of Unani Medicine (NIUM), Bengaluru. All people above 21 years of age attending OPD constituted study population. In present study, 524 patients were included in the study. The diagnosis of hypertension was done as per WHO guidelines. Data analysis was done using SPSS version 24. Results: The study revealed that prevalence of hypertension was 35.87% in the study population. In the present study, 53.20% of diagnosed hypertensive patients were females and rest 46.80% were males. Majority of diagnosed hypertensive patients (39.89%) belonged to the age group of above 60 years. Conclusion: Prevalence of hypertension is significantly increasing at a greater pace globally as well as in India. Periodic screening and raising awareness about hypertension in general population is necessary to reduce the prevalence of the disease and thereby the associated morbidity and mortality. [ABSTRACT FROM AUTHOR]

This study investigates the components that affect online consumer engagement for Amazon, one of the best ecommerce sites worldwide. It's important to comprehend how Amazon interacts with its consumers given the expanding popularity of online purchasing. According to latest figures India has a 47% penetration rate with 627 million internet users. Amongst all Indian internet users with 20 million active users, Amazon accounts for around 3.2%. The dimension of this study is to focus on efficiency, and determining aspects of online consumer involvement for Amazon. Data were gathered via a survey from 400 individuals using a convenience sample approach. For the purpose to solidify the literature review and create a theoretical framework, the study used factor analysis and bibliometric modeling. The data were examined using SPSS yielding thorough insights. In the international market, online consumer involvement was first offered in 1999, and by 2001, researchers had started to quantify its importance. This facet of online customer engagement was available in India in 2019-2020 (COVID-19); the research measures, develop and understand the theoretical framework for Online Customer Engagement and study the factors influencing Customers of Amazon for Online Customer Engagement. [ABSTRACT FROM AUTHOR]

The contemporary business environment presents numerous challenges for Human Resource Management (HRM). These include globalization, economic and legal environment changes, workforce diversity, technological advancements, and evolving employee expectations. This study aims to identify these challenges, explore strategies to address them, and assess their impact on employees and employers. Utilizing hypothesis testing and statistical analysis, this research provides insights into the significant issues HR managers face and offers solutions to navigate the complexities of modern HRM. [ABSTRACT FROM AUTHOR]

Work-Place spirituality is on the fast track and those days are gone when scholars face problem in defining the same. Spirituality has deep relation with personality and all the linked abstracts with personality are in lab with workplace spirituality at current time. This study is one of the case of that chain where spirituality is observed with job satisfaction, organizational culture and role of gender. The method for gathering the data was stratified random sampling. 457 replies were obtained from 500 teaching faculty members at several universities in Khyber Pakhtunkhwa, Pakistan, who were given an approved questionnaire. AMOS and SPSS Package-21 have been used to find analytical results. The tool's validity and dependability were guaranteed. Values for the model fit index were confirmed. The study has shown and analyzed the model's path coefficient with and without moderating and interaction factors. It was discovered that Work-place Spirituality has encouraging behavior for job satisfaction of the employee and organizational culture further enhance the behavior while gender is unaware about the behavior of WPS. The study's role in literature and industry has been defined. At the completion of this inquiry, there are limitations and recommendations based on the findings. [ABSTRACT FROM AUTHOR]

The biggest difference in statistical training from previous decades is the increased use of software. However, little research examines how software impacts learning statistics. Assessing the value of software to statistical learning demands appropriate, valid, and reliable measures. The present study expands the arsenal of tools by reporting on the psychometric properties of the Value of Software to Statistical Learning (VSSL) scale in an undergraduate student sample. We propose a brief measure with strong psychometric support to assess students' perceived value of software in an educational setting. We provide data from a course using SPSS, given its wide use and popularity in the social sciences. However, the VSSL is adaptable to any statistical software, and we provide instructions for customizing it to suit alternative packages. Recommendations for administering, scoring, and interpreting the VSSL are provided to aid statistics instructors and education researchers understand how software influences students' statistical learning. [ABSTRACT FROM AUTHOR]

BACKGROUND: The insurance sector in Jordan stands to gain significant benefits from the adoption of Accounting Intelligence (AI) systems, which can transform decision-making processes, enhance operational efficiency, and elevate customer satisfaction. OBJECTIVE: This study investigates the mediating role of organizational culture in the relationship between three key organizational factors—top management support (TMS), information technology (IT), and organizational size (OS)—and AI system adoption (AIA) in Jordan's insurance companies. METHODS: Using a quantitative approach, the study surveyed 274 employees from Jordanian insurance companies. The data was analyzed using structural equation modeling (SEM) and confirmatory factor analysis (CFA) to assess the study's hypotheses and ensure data reliability and validity. RESULTS: The findings revealed substantial support for the relationships between TMS, IT, OS, and organizational culture (ORC). Additionally, organizational culture emerged as a mediating factor influencing AI system adoption (AIA) adoption. However, certain direct relationships, such as ORC and AIA, and the mediating role of organizational culture in the relationship between IT and AIA, were context-dependent and lacked support. IMPLICATIONS: Organizational culture plays a critical role in mediating the relationship between key organizational factors and AIA in Jordan's insurance sector. [ABSTRACT FROM AUTHOR]

Background: Polycystic Ovary Disorder (PCOS) is a complicated endocrine problem influencing ladies of reproductive age, with ramifications for fertility, metabolic process plus cardio health and wellness. personalized medication supplies a confident technique by customizing therapies to specific genetic hormone as well as ecological accounts. Methods: This research used a mixed-methods, incorporating measurable hereditary screening and also scientific examinations with qualitative person meetings to personalized therapy prepare for ladies with PCOS in Baghdad. Individuals were ladies aged 18-45 detected with PCOS, chosen with strict incorporation as well as exemption standards. Information evaluation included analytical screening to analyze the effect of individualized therapies on different PCOS signs together with pens. Measurable information was analyzed and examined based on topics of mathematical statistics using the statistical program SPSS for detailed data, t-tests, as well as chi-square examinations for value (p. value 0.05). Results: The research entailed 150 individuals exposing substantial irregularity in PCOS signs and symptoms and also hereditary pens. Individualized therapies resulted in substantial enhancements: menstruation uniformity raised in 85% of the individuals (p. value 0.01) hirsutism ratings lowered by 60% (p. value 0.05) acne enhanced in 70% of instances (p & lt; 0.01), and also BMI decreases were observed in 75% of individuals (p. value 0.001). Additionally, insulin degrees stabilized in 80% (p. value 0.001) together with cholesterol degrees boosted in 65% (p. value 0.05) of the research study team. Conclusion: Personalized medication in PCOS administration reveals assurance in boosting individual results by attending to hereditary, hormone, way of living as well as ecological aspects. This strategy calls for a standard change in the direction of personalized treatment in gynecology possibly establishing brand-new requirements for PCOS therapy. [ABSTRACT FROM AUTHOR]

This article offers a thorough review of shape memory alloys' (SMAs') uses in the Space research field. The utility of SMAs in a variety of applications, including morphing wings (using both experimental and modelling methods), customising orientation and inlet shapes for various propulsion systems, implementing flexible chevrons to improve thrust while lowering noise, and reducing overall power consumption, is the main topic of this paper. The use of SMAs in applications in space is also covered in the paper, including how they may be used to create low-shock launchers, isolate microvibrations, and enable self-deployable solar sails. The essay also emphasises the novel structures and tools made possible by SMAs. One noteworthy method covered in the article is putting SMA wires in the laminate's midplane and embedding them into the fabric a layer of composite laminates. When compared to traditional composite constructions, the incorporation of SMAs into composite has shown better damage resistance and ductility. The reaction of a bright hybrid plastic composite plates to a very low-velocity impact is examined experimentally and numerically in this paper, which highlights the benefits of inserting SMA wires. Among these benefits are improved damage resistance, better ductility, higher composite hardness, and increased energy absorption before failure. Shape memory alloy (SMA) are the subject of extensive industrial applications and ongoing study in the field of materials. Its two distinguishing qualities, the shape memory impact and superelasticity, are mostly to blame for this. A composition's structure that suffered a phase transition as a result of temperatures, pressures, mechanical forces, and other factors is implies to as having a "shape memory effect". The composition, despite the very significant plastic deformation to which its surface is susceptible to, may recover to its original form under the influence of temperature as well as other factors. [ABSTRACT FROM AUTHOR]

AI enhances customer engagement and brand loyalty by delivering tailored, efficient, and smooth interactions. Through the power of AI, brands are empowered to provide personalized, efficient, and timely experiences to customers, fostering lasting engagement and loyalty. By leveraging AI technologies effectively, companies can cultivate strong and enduring relationships with their customers, leading to heightened retention and advocacy. The study utilizes a comprehensive research approach, incorporating both qualitative and quantitative data collection analysis. Participants from diverse industries are chosen and data is gathered through surveys, interviews, and observations. The survey includes inquiries concerning customer engagement, brand loyalty, and perceptions of AI. Consumers perceive companies utilizing AI technologies as more innovative, efficient, and responsive to their needs. Moreover, AI's ability to provide personalized and customized experiences enhances customer satisfaction and increases their intention to remain loyal to the brand. The study also reveals that the level of trust in AI technologies plays a crucial role in its impact on customer loyalty. The findings provide empirical evidence on the significant effect of AI on consumer long-term engagement and brand loyalty. Businesses can leverage these insights to design effective AI-based strategies that enhance customer experiences and foster brand loyalty. Additionally, the work points out the significance of building customer trust in AI technologies, emphasizing the need for transparent and ethical AI practices. The findings shows that recommendation systems do have an impact over long term customer engagement, whereas perceived personalization doesn't have an impact over long term customer engagement. Predictive personalization and personalized algorithms, AI based brand loyalty programs, product innovation, self learning, AI-based service quality and customer engagement have a significant impact over brand loyalty. [ABSTRACT FROM AUTHOR]