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The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

While there are many guides available on how to construct academic texts, the actual experience of writing can often remain unspoken. In this chapter, I share my personal experience of academic writing in entrepreneurship research, including the enabling and constraining aspects. My aim is to make academic writing more visible and encourage open discussion about this important activity. I approach academic writing as a comprehensive experience, encompassing various dimensions such as embodied, emotional and social aspects. I reflect on the influence of my body, physical conditions, emotions and writing habits on my writing process. Additionally, I consider the impact of external expectations and the context of working in entrepreneurship research, and how they shape my writing style. By examining these different dimensions of my writing experience, I hope to provide insight into the multifaceted nature of academic writing in entrepreneurship research.

While known by many names, qualifying exams function as gatekeepers to graduate student advancement to PhD candidacy, yet there has been little formal study on best qualifying exam practices particularly in biomedical and related STEM PhD programs. The purpose of this study is to examine the current state of qualifying exams through an examination of the literature and exploration of university-wide policies.

The authors conducted a literature review of studies on qualifying exams and completed an external evaluation of peer institutions’ and internal institutional qualifying exam requirements to inform our discussion of qualifying exams practices in PhD training at a research-intensive US institutions.

This study identified the need for more research on qualifying exams to establish evidence-based best practices. The authors found a wide variety of qualifying exam formats, with little evidence in support for specific formats. The authors also found little evidence that student expectations are made clear. The lack of evidence-based best practices coupled with insufficient clarity for students has a real potential to disadvantage PhD students, particularly first generation, underrepresented minority, international and/or other trainees who are not privileged or socialized to navigate training environments with vague landmarks such as the qualifying exams.

There are very few studies that evaluate qualifying exams in US doctoral education, particularly in STEM fields, and to the authors’ knowledge, there has been no analysis of campus-wide policies on qualifying exams reported. The lack of evidence for best practices and the need for to evaluate the implementation and effectiveness of qualifying exams are discussed.

This study aims to develop a building renovation duration prediction model incorporating both scope and non-scope factors.

The study used a questionnaire to obtain basic information relating to identified project scope factors as well as information relating to the impact of the non-scope factors on the duration of building renovation projects. The study retrieved 121 completed questionnaires from construction firms on tertiary education trust fund (TETFund) building renovation projects. Artificial neural network was then used to develop the model using 90% of the data, while mean absolute percentage error was used to validate the model using the remaining 10% of the data.

Two artificial neural network models were developed – a multilayer perceptron (MLP) and a radial basis function (RBF) model. The accuracy of the models was 86% and 80%, respectively. The developed models’ predictions were not statistically different from those of actual duration estimates with less than 20% error margin. Also, the study found that MLP models are more accurate than RBF models.

The developed models are only applicable to projects that suit the characteristics and nature of the data used to develop the models. Hence, models can only predict the duration of building renovation projects.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it; it also helps clients to effectively benchmark projects duration and contractors to accurately estimate duration at tendering stage.

The study presents models that combine both scope and non-scope factors in predicting the duration of building renovation projects so as to ensure more realistic predictions.

This study aims to investigate student mentors' perceptions of peer mentor relationships in a health professions education program.

The design uses embodied hermeneutic phenomenology. The data comprise 10 participant interviews and visual “body maps” produced in response to guided questions.

The findings about student mentors' perceptions of peer mentor relationships include a core theme of nurturing a trusting learning community and five related themes of attunement to mentees, commonality of experiences, friends with boundaries, reciprocity in learning and varied learning spaces.

The study contributes original insights by highlighting complexity, shifting boundaries, liminality, embodied social understanding and trusting intersubjective relations as key considerations in student peer mentor relationships.

Background: This paper examines the impact of coronavirus COVID-19 outbreak on employees’ mental health, specifically psychological distress and depression. It aims at identifying the main stressors during and post COVID-19, examining the main moderating factors which may mitigate or aggravate the impact of COVID-19 on employees’ mental health and finally to suggest recommendations from a human resource management perspective to mitigate COVID-19’s impact on employees’ mental health.

Methods: This paper is a literature review. The search for articles was made in Google scholar, Web of Science and Semantic scholar. We used a combination of terms related to coronavirus OR COVID-19, workplace and mental health. Due to the paucity of studies on the COVID-19 impact on employees’ mental health, we had to draw on studies on recent epidemics.

Results: The identified literature reports a negative impact of COVID-19 on individual’s mental health. Stressors include perception of safety, threat and risk of contagion, infobesity versus the unknown, quarantine and confinement, stigma and social exclusion as well as financial loss and job insecurity. Furthermore, three dimensions of moderating factors have been identified: organizational, institutional and individual factors. In addition, a list of recommendations has been presented to mitigate the impact of COVID-19 on the employee’s mental health, during and after the outbreak, from a human resource management perspective.

Conclusions: Coronavirus is new and is in a rapid progress while writing this paper. Most of current research are biomedical focusing on individuals’ physical health. In this context, mental health issues seem overlooked. This paper helps to broaden the scope of research on workplace mental health, by examining the impact of a complex new pandemic: COVID-19 on employees’ mental health, from social sciences perceptive, mobilizing psychology and human resource management.

With increased populations and movement of people worldwide, traffic emissions will lead to an increase in carbon dioxide emissions, which is one of the greenhouse gases. This will increase outdoor air pollution and other environmental risks that will impact people's health and livelihood, crops, as well as the built environment such as architecture, buildings and other structures. Few studies have been devoted to addressing the effect of air pollution on historic buildings. However, there is no specific study on the impact of traffic-related emissions.

A thorough analysis has been conducted in selecting eight historic districts (HDs) among all of 31 located within the city of San Antonio. Motor Vehicle Emission Simulator (MOVES) software has been utilized to process the data collected from the average annual daily traffic (AADT) and vehicle operational speeds and evaluate the amounts of emissions for each HD.

MOVES outcomes showed that HDs are under the threat of deterioration caused by traffic emissions. Therefore, transportation and environmental planners need to implement sustainable solutions to reduce the impact of CO₂ emissions on HDs and, ultimately, historic buildings.

This study will help policymakers plan a better course of action for the future conditions associated with the increased traffic volumes. It is also beneficial for the developers, preservationists, architects and all other stakeholders willing to preserve the history of a country.

World Health Organizations (WHO) (2023) states that governments and employers have a responsibility to uphold that right by providing work that simultaneously prevents workers from experiencing excessive stress and mental health risks. The business environment continues to produce a lot of stress on workers, which includes internal pressures to achieve results and employees suffer the consequences. Some companies have turned to mindfulness as a technique that helps mitigate these consequences and have joined Kaizen as a process improvement technique in the work environment. Therefore, this study has a research purpose: “to comprehend the possible linkage between Kaizen philosophy from an individual perspective, with Mindfulness ZEN Buddhism technique to understand the individual benefit (well-being) of each employee in organizations.” The answer to this represents the research gap in this article. The research questions governing this study are as follows: RQ1: Does Mindfulness is used as Kaizen technique of personal-individual improvement in 21st-century organizations? RQ2: What elements and characteristics of Kaizen and mindfulness can be found working together? And RQ3: Which qualitative impact of mindfulness and Kaizen in the workplace outcome (well-being, performance of the job (process)) and relationships with other employees)?

This research used a qualitative approach due to the recent phenomenon studied. In a certain way, it was used a mixed-method (combination of qualitative data – web search secondary data analysis and qualitative research-Convergence Model). First, it was done an intensive web search with the aim to identify companies' corporate mindfulness programs, along with companies which have applied mindfulness and Kaizen programs. It was identified a group of big companies with global and international presence (“famous” for their products and services) in diverse industrial and service sectors, country of origin and business locations; with the purpose of getting a holistic vision of all organizations which have practice Kaizen and mindfulness. Therefore, this study explored secondary data related to both practices, analyzing reports or briefings published in management magazines and official WEB pages and/or business magazines.

As a result of the triangulation of the data with its secondary data convergence model and qualitative research, a theoretical framework was reached that shows the benefits of the two combined twin techniques of Kaizen and mindfulness. The worker experiences a path that goes from concentrating on the execution of their processes, following their operating standards (Standardize, Do, Check, Act [SDCA] cycle), going through the evolution to continuous improvement or Plan-Do-Check-Act (PDCA) cycle, experiencing work with concentration-awareness and reducing your daily stress, maintaining high sensitivity to the work process and your environment and finally, discovering an essential life purpose. Finally, worker experiences benefit when there is wide application of both with the SDCA and PDCA cycles such as high motivation, constant learning from your mistakes, day-to-day learning and the Munen Musso (not using the mind).

The main limitation is the qualitative methodological bias and secondary data research. In addition, to have a theoretical sample. However, the richness of the data helps to overcome this limitation. On the other hand, the qualitative research interviews are for a certain geographical area, therefore, the results cannot be generalized.

The results of this research can shed light on operations managers in the use of techniques for continuous improvement and improvement of people's quality of life, such as mindfulness. In Mexico, they are beginning to be used jointly (twin techniques) to comply with Regulation 035 of psychosocial risk, the researchers are sure that in other countries it will be used in the same way to comply with regulations. However, the research findings show the benefits that can be provided to workers in organizations by applying Kaizen and Mindfulness together.

To the best of the authors’ knowledge, according to the literature review, this is the first article that explores the relationship between Kaizen and Mindfulness as twin techniques that help improve the individual quality of life of employees in organizations.

The purpose of this paper is to understand the post-COVID-19 fluctuations in the building construction demand from various angles at the national, regional, and sectoral levels. Despite the significant impact of COVID-19 on the building construction industry, a detailed quantitative analysis of the COVID-19 impact on the building construction demand is still lacking. The current study aims to (1) establish a statistical approach to quantify the COVID-19 impact on the building construction demand; (2) investigate the post-COVID-19 fluctuations in the construction demand of different building services, regional markets, and building sectors using the historical time series of the architecture billings index (ABI); and (3) identify vulnerable market and sector and discuss the post-COVID-19 recovery strategies.

The research methodology follows four steps: (1) collecting national, regional, and sectoral ABIs; (2) creating seasonal autoregressive integrated moving average models; (3) illustrating cumulative sum control charts to identify significant ABI deviations; and (4) quantifying the post-COVID-19 ABI fluctuations.

The results show that all the ABIs experienced a statistically significant decrease after COVID-19. The project inquiries index reduced more but recovered faster than billings and design contracts indices. The midwest billings index decreased the most among the regional ABIs and the commercial/industrial billing index dropped the most among the sectoral ABIs.

This study is unique in the way that it utilized the ABI data and the approach using SARIMA models and CUSUM control charts to assess the post-COVID-19 building construction demand represented by ABI fluctuations.