Quantitative Perspective Research Articles

Triply periodic minimal surfaces based topology optimization for the hydrodynamic and convective heat transfer

Triply periodic minimal surfaces (TPMS), possessing diverse and crucial properties for thermal convection analysis, hold significant promise for topology optimization in convective and hydrodynamic systems. This study aims to develop an innovative topology optimization method based on TPMS for channel shape design. We focus on maximizing heat dissipation and mass flux while maintaining a constant mean curvature. The channel structures undergo free evolution during the optimization process, resulting in efficient and intricate geometries based on the TPMS assumption. To incorporate TPMS properties, we modify the original energy formulation, which comprises kinetic energy, thermal energy, and Ginzburg–Landau energy. The governing system encompasses the phase field model, the Darcy–Stokes model, and the reaction–diffusion heat transfer model. The hydrodynamic response within the phase change structure is computed by solving the transient Darcy–Stokes equation augmented with a temperature-dependent diffusion term. To achieve second-order temporal and spatial accuracy, we employ the Crank–Nicolson method for the time scale and the central difference method for the spatial scale. Through the utilization of the Lagrange multiplier method, we establish the unconditional decrease of the discretized original energy. This implies that the proposed scheme can utilize a large time step. To verify the robustness of our proposed method, we conduct several numerical tests from both qualitative and quantitative perspectives. The results demonstrate the effectiveness of our method in enhancing heat and mass transfer capabilities.

How Has LVMH Performed Financially from 2018 to 2022: A Fundamental Financial Analysis of LVMH

This thesis will analyze and evaluate the value of the LVMH Group from a quantitative and qualitative perspective as part of its examination and evaluation as the topic of my dissertation. We are going to examine the qualitative analysis of COVID-19, the CEO of LVMH Bernard Arnault who is the richest man in the world, and LVMH's purchase of Tiffany in the qualitative analysis. As part of the quantitative analysis, the CAPM model and the Sharpe ratio were used to examine LVMH from a quantitative perspective. In addition, we also chose DCF, WACC, and relative valuation as measures of how well LVMH is performing. In the end, it was determined through a series of analyses and assessments made at various stages in the process that LVMH's stock price has been overvalued by the market. As a result of this, the luxury industry is generating enormous revenues, and a majority of the businesses are overvalued.

Intersectional analysis of inequalities in self-reported breast cancer screening attendance using supervised machine learning and PROGRESS-Plus framework.

Breast cancer is a critical public health concern in Spain, and organized screening programs have been in place since the 1990s to reduce its incidence. However, despite the bi-annual invitation for breast cancer screening (BCS) for women aged 45-69, significant attendance inequalities persist among different population groups. This study employs a quantitative intersectional perspective to identify intersectional positions at risk of not undergoing breast cancer screening in Spain. Women were selected from the 2020 European Health Interview Survey in Spain, which surveyed the adult population (> 15 years old) living in private households (N = 22,072; 59% response rate). Inequality indicators based on the PROGRESS-Plus framework were used to disentangle existing social intersections. To identify intersectional groups, decision tree models, including classification and regression trees (CARTs), chi-squared automatic interaction detector (CHAID), conditional inference rees (CITs), and C5.0, along with an ensemble algorithm, extreme gradient boosting (XGBoost), were applied. XGBoost (AUC 78.8%) identified regional differences (Autonomous Community) as the most important factor for classifying BCS attendance, followed by education, age, and marital status. The C5.0 model (balanced accuracy 81.1%) highlighted that the relative importance of individual characteristics, such as education, marital status, or age, for attendance differs based on women's place of residence and their degree of interaction. The highest risk of not attending BCS was observed among illiterate older women in lower social classes who were born in Spain, were residing in Asturias, Cantabria, Basque Country, Castile and León, Extremadura, Galicia, Madrid, Murcia, La Rioja, or Valencian Community, and were married, divorced, or widowed. Subsequently, the risk of not attending BCS extends to three other groups of women: women living in Ceuta and Melilla; single or legally separated women living in the rest of Spain; and women not born in Spain who were married, divorced, or widowed and not residing in Ceuta or Melilla. The combined use of decision trees and ensemble algorithms can be a valuable tool in identifying intersectional positions at a higher risk of not utilizing public resources and, thus, can aid substantially in developing targeted interventions to increase BCS attendance.

BI-CAM: Generating Explanations for Deep Neural Networks Using Bipolar Information

The higher requirements for deep neural networks are driving researchers to have a deeper understanding of the internals of neural networks. The class activation map (CAM) based methods can provide a convincing interpretation of the features extracted by the neural network from both visual and quantitative perspectives. However, the existing CAM methods do not take into account that the non-target region also contains target-related activation, which results in the generated saliency map containing noise from unrelated regions. In addition, the soft mask with continuous value not only contains more non-target regions for gradient-free CAM, but also causes the characteristics and distribution of the target region to be disturbed. This paper proposed a novel CAM method named Bipolar Information CAM (BI-CAM) to interpret convolutional neural networks (CNNs) and graph convolutional networks (GCNs). Firstly, dual-stream information is proposed to precisely quantify the relationship between the target region and the non-target region for an image/graph. Secondly, binary reformation is also proposed to generate a hard mask that can retain the original features and regions. Finally, we propose to use concise and effective Point-wise Mutual Information (PMI) to measure the quantitative relationship between the image and the local region with respect to the label. The results of the experiment show that the proposed BI-CAM achieves significantly better performance in the faithfulness evaluation from the perspectives of visualization and quantitative analysis than other competitive interpretation methods.

Analyzing the Water, Energy, and Food Security Nexus Index in Morocco

The WEF Nexus Index’s quantitative perspective provides a way to evaluate the trade-offs that need to be taken into account for sustainable development. Morocco’s natural resources are being impacted by climate change, and the demand for energy, water, and food are increasing the pressure on these resources. Academics are becoming more interested in measuring the synergies and trade-offs between this resource. The purpose of this paper is to offer an interpretation of how the Morocco WEF Nexus Index has changed over the course of 5 years, as determined by open databases. The index’s value decreased and Morocco’s ranking deteriorated during this period, as evidenced by the results. The results are useful for evaluating Morocco’s progress in managing integrated resources and aiding in decision-making and policy development. On an interactive website, A group of visual representations linked to WEF Nexus Index has been put together.

The complex relationship between technostress and academic performance in young college students

The study was carried out with the aim of evaluating the relationship between technostress and the academic performance of young university students. The research was developed from a quantitative perspective using a deductive and correlational explanatory method. A twenty-eight (28) question Likert scale type instrument was structured to measure the variables. The TE technostress construct was measured with an instrument adapted from the RED-Technostress scale and for the academic performance variable RA, the items were adapted from a scale of their own. Non-probabilistic convenience sampling was used, and the construct was evaluated with structural equation modelling supported by SPSS V24 software and its AMOS add-on. A total of 260 questionnaires were administered. As a result, it was found that there is a negative and insignificant relationship between technostress (TE) and academic performance (RA) (-0,184; p < 0,00). In relation to the dimensions of technostress and academic performance, we obtained scepticism (E) (-0,264; p < 0,00); fatigue (F) (-0,143; p < 0,00); anxiety (A) (-0,179; p < 0,00); inefficacy (I) (-0,214; p < 0,00); and addition (AD) (0,222; p < 0,00). In conclusion, the levels of technostress experienced by the young students were low, while the relationship between technostress and academic performance was negative; however, it is not the levels expected and evidenced in other studies. It is noted that this study contributes to understanding an understudied phenomenon in young educational populations that appears to behave differently from older populations in the business field

Practical Guide to Achieve Rigor and Data Integration in Mixed Methods Research

Mixed methods research represents a dynamic approach, that combines quantitative and qualitative perspectives in the same study to answer complex questions, beyond the reach of each method used separately. This type of research is increasingly used in health sciences and in social sciences, where it is possible to identify important contributions to knowledge and the practice, derived from the characteristic integration of this approach. Nevertheless, it important to reiterate the importance of recognizing their own perspectives, methods, rigor criteria, and challenges. This work presents general aspects of the epistemological perspective of mixed methods research, describes basic and advanced designs, forms and possible integration moments of each design, as well as the rigor criteria that guide these types of studies. Graphic elements are presented to facilitate recognizing the structure of each design. Furthermore, a visual tool is introduced denominated “anatomy of mixed methods research”, which seeks to guide researchers regarding each of the key elements in the design and development of this type of research.

Organisation design in a nursing department: a quantitative and work sampling perspective

Organisation design in a nursing department: a quantitative and work sampling perspective

Can Migration-Based Dynamic Platform Technique Work Effectively: A Quantitative Analysis Perspective

Can Migration-Based Dynamic Platform Technique Work Effectively: A Quantitative Analysis Perspective

Motor Skills, Social Skills, and Participation of Autistic Children

Generally, participation levels of autistic children are lower than neurotypical children in social and physical activities. The range of activities that autistic children participate in is also less diverse. Building on previous qualitative work, the current research provides a quantitative perspective to explore the relationship between social skills and motor skills in autistic children, and the association with participation at home, school, and in the community. Caregivers and their 5-to-11-year-old autistic children participated in this research. Motor skills were assessed with performance-based (BOT-2-SF) and caregiver-report measures (MABC-2 checklist). Caregivers also completed questionnaires to quantify social skills (SRS-2) and participation (PEM-CY) patterns. Motor assessments were not correlated, suggesting use of the MABC-2 checklist in conjunction with the BOT-2-SF may not be well-suited for younger participants. Discordant results of proxy (i.e., social/motor skills predicted participation frequency at school, with social skills contributing to the model) and performance-based (i.e., social/motor skills predicted participation frequency at home, and average involvement in the community) reports were attributed to caregiver's focus on fine motor performance in school-based settings, considering the established link between social and fine motor skills in autism. Non-significant findings were explained by heterogeneity in social/motor skills among autistic children. Overall, while continued research is warranted, findings support a person-centered (i.e., individualized) approach to address participation of autistic children.

Literacy in the Kingdom of Judah: A Typology of Approaches and a Criticism of Quantitative Perspectives

The subject of literacy in ancient Israel and Judah remains hotly debated among scholars, and the case of the Kingdom of Judah proves especially controversial. To disentangle a complicated issue, this article first draws up a typology of approaches used by scholars to tackle questions such as the population’s rate of literacy, the Judeans’ ability to write down literary texts, and the development of literacy throughout the centuries. Then, it critically examines two quantitative approaches, which have been highly influential and currently promote the thesis that the levels of literacy were minimal in the early monarchic period in Judah (in contrast to the situation in Israel) and considerably increased at the end of this period.

Art and Wellbeing, Amidst the COVID-19 Pandemic, Through the Lens of College Students: A Quantitative Perspective

Art and Wellbeing, Amidst the COVID-19 Pandemic, Through the Lens of College Students: A Quantitative Perspective

A bibliometric analysis regarding Brazilian studies of counterfactual novels

This paper studied the postmodern posture through the hybridism between History and Literature by electing the counterfactual novel as its object. The paper’s aim is to analyze the production of counterfactual literature studies in Brazil under qualitative and quantitative perspective. The hypotheses contemplated is that Brazilian counterfactual literature studies are yet incipient and due to this fact must be promoted. The chosen methodology was Bibliometrics. Researchers used the terms: “história contrafactual”, “história alternativa”, “romance histórico” and “metaficcção científica”. Since 2013, the results display an increase in number of publications. The authors have a network of publications/citations for terms “história contrafactual” and “romance histórico”. The VOSViewer software was used to develop a quantitative analysis and an author network.

Assessment and Optimizing Task Performance through Artificial Intelligence Systems in Hangzhou Ruinan Information Technology Co., Ltd

This research study employs a quantitative-descriptive approach to evaluate and enhance task performance through the utilization of Artificial Intelligence (AI) systems at Hangzhou Ruinan Information Technology Co., Ltd., a key player in the technology hub of Hangzhou City, China. The study comprises four main parts: examining AI system characteristics and provisioning, assessing actual task performance, investigating factors influencing system effectiveness, and identifying challenges impacting performance. Participants include management, IT professionals, and employees working with AI systems, providing valuable insights into system implementation and operation. Data analysis, utilizing weighted mean and verbal description techniques, offers both quantitative and qualitative perspectives on AI's role in optimizing task performance. Findings reveal strong scalability, efficient overall performance, and positive impacts on workflow processes and resource utilization. Security measures, especially in data protection, and usability aspects require attention for further enhancement. The study underscores the importance of reliable data, seamless user adoption, enhanced expertise, and consistent system performance in optimizing task performance through AI within the organization. Conclusions emphasize the need to strengthen security measures, enhance usability, and address areas for improvement. The study underscores the value of AI in achieving the organization's goal of enhancing task performance and productivity. Recommendations include initiatives to enhance data quality, streamline user acceptance, invest in employee skill development, and improve scalability and performance. These recommendations aim to guide Hangzhou Ruinan Information Technology Co., Ltd. in refining its AI systems to drive efficiency and excellence in its operations.

Analysis of the self-consistency of nucleation in the diffuse interface limit of binary alloy phase field models

This paper examines the process of nucleation in phase field (PF) models, with the aim of elucidating how the use of diffuse interfaces often employed for quantitative modelling of solidification affects nucleation rates and distribution statistics in relation to the predictions of classical nucleation theory. Nucleation is simulated through the use of noise in a quantitative binary alloy PF model using different interface widths. Our results reveal that the rate of nucleation in the PF model is found to be strongly dependent on the scale of the interface width and the numerical discretization, but that careful control of these quantities offers the possibility of a consistent interpretation of nucleation rate. The paper ends by assessing some of the practical merits of seeded versus noise-induced nucleation in PF modelling in the diffuse-interface limit, while also emphasizing how nucleation in this limit is fundamentally flawed from a quantitative perspective.

Editorial

I am delighted to announce the publication of the inaugural issue of “Qualitative Inquiry in Education: Theory & Practice (QIETP)” under the umbrella of EDU Publishing. It’s a great pleasure to reconnect with you through this new journal. QIETP, being the first thematic journal in its field in Türkiye, builds upon the experience I gained during my 10-year tenure (2013-2023) as the founding and chief editor of the Journal of Qualitative Research in Education (ENAD). I aim to advance this experience further in QIETP. I am fully confident that, with the support of our valued authors, reviewers, editors, and readers, QIETP will soon earn a respectable position in the field. The first issue of QIETP comprises 5 articles: 4 research articles and 1 review study. The first study in this issue, “A critical view to educational technologies in the context of social inequalities,” comes from Fatma Akgün, Cem Çuhadar, and Şenay Ozan Deniz of Trakya University. The authors have examined the use of technology in the learning-teaching process from a phenomenological perspective regarding social equality. The second study, “A critical overview of Turkish research on 21st-century skills in education: 2017- 2022,” is authored by H. Ferhan Odabaşı, Elif Akyol Emmungil, Elif Atabay, and Melkaç Değer Demir from Anadolu University. This article evaluates studies conducted in Türkiye between 2017 and 2022 on 21st-century skills in education through meta-synthesis. The third study in this issue is “How to integrate sustainable development in English lessons: Reflections from teachers, students, and academicians,” conducted by Yasemen Şanal, Sena Sezgin, Seden Doğa Döker, Furkan Yavuz, and Gülçin Mutlu from İzmir Democracy University. In their qualitative descriptive study, the authors aimed to examine the characteristics of a middle school foreign language curriculum that incorporates the concept of sustainability. The fourth study of this issue, “How phenomenological are phenomenology studies in educationalsocial sciences: A sample from TR Dizin,” is a research article by M. Emir Rüzgâr and İbrahim Sözcü. The authors have evaluated how much the phenomenology studies published in the national TR Dizin index in Türkiye adhere to the assumptions of phenomenology. Although the study’s findings are presented from a quantitative perspective, it was deemed worth publishing in QIETP as it directly evaluates phenomenological studies. The only review article in this issue is “Educational science traditions and qualitative research” by Ali Yıldırım from the University of Gothenburg. In this article, Yıldırım presents the relationship between qualitative research methods and two main traditions in teacher education: the Anglo-American and the Continental European. This informative work discusses both the teacher training in these traditions and their relation to qualitative research. I am grateful to many esteemed individuals who have shown their close interest and support throughout this process. I extend my endless thanks to all colleagues who have been part of QIETP’s boards and provided technical support. I feel indebted to thank Prof. Ali Yıldırım, a pioneer in the field of Qualitative Research Methods in Türkiye, for his role in forming the international editorial board and supporting the publication of articles in the first issue.

Comparison of multi-factor spatial downscaling models for high-resolution LST estimation in mountainous and hilly open-pit mines

The stripping of soil and vegetation by mining activities in mountainous and hilly areas of southern China has caused drastic surface disturbance and serious ecological and environmental problems. The spatial distribution of Land Surface Temperature (LST) in the mine site can better reflect the ecological disturbances caused by mining and is an important parameter for assessing the ecological environment of the mining sites. The classic Distrad thermal pixel decomposition model was improved by using different regression factors and linear and nonlinear fitting methods in this study, and three multi-factor downscaling models were proposed. Finally, four downscaling models were used to estimate the high spatial resolution LST for three three typical open-pit mining areas and explore the contribution of different surface parameters in the downscaling process from qualitative and quantitative perspectives. The results show that: (1) The MTVET (Extremely Randomized Trees regression model with multitype predictor variables) model exhibits the most accurate prediction accuracy in all three mining areas. The spatial distribution of errors shows that the area share of absolute errors between 0 and 1 K exist in 86.48 %, 81.38 %, and 84.51 % of the areas in Ganzhou rare earth mine, Dexing copper mine and Pingxiang coal mine, respectively. Based on the Root Mean Square Error (RMSE) assessment, the three mines are 0.699 K, 0.790 K, and 0.751 K, respectively, which are all controlled within 1 K; (2) The downscaled results of the MTVET model show rich and clear LST spatial texture features when typical mine sites are selected in each mining areas for detail comparison; (3) It was found that the topographic index has the greatest impact on accuracy enhancement, suggesting that topographic factors have an important influence in the study of LST downscaling in mountainous and hilly areas of southern China.

Protecting Rural Large Old Trees with Multi-Scale Strategies: Integrating Spatial Analysis and the Contingent Valuation Method (CVM) for Socio-Cultural Value Assessment

Governments are faced with the unique challenge of implementing large-scale and targeted protection against the global decline of large old trees. Incorporating socio-cultural values and encouraging public involvement are important parts of conservation policy. However, current studies on the socio-cultural valuation of large old trees are still limited, and how rural residents perceive the human-related value of large old trees remains largely unknown. Using a quantitative, spatial analysis and the contingent valuation method (CVM), we tried to explore a multi-scale socio-cultural valuation and protection framework based on a case study of Baoding City and Xiongan New Area in North China. The results showed that (1) the scattered large old trees in the study area were generally at a relatively younger stage, showing normal growth performance but having poor living environments. Some 96.99% of the trees resided in the countryside. Their distribution showed an agglomerative pattern with several clusters. (2) The species richness was relatively lower than that reported in urban areas. The species diversity had an obvious high–low gradient from the mountain to plain areas. Most endemic species were found in habitats of the village fringe (VF) and government/community/institutional ground (GC). (3) The mean willingness to pay (WTP) for the socio-cultural value of scattered large old trees was CNY 132.48 per year per person (1 US dollar equals about 7.2 CNY) of all the respondents, and CNY 84.30 per year per person with regard to farmers, which is relatively higher than that reported in large cities. (4) Economic income, gender, age, education level, place of residence, diameter at breast height, and tree habitat were factors that significantly influenced the WTP, among which economic income was the most significant. (5) The importance ranking of socio-cultural value connotations perceived by rural residents was as follows: spiritual attachment and homesickness > fengshui > social bond > witnessing history > education > creative inspiration. (6) The annual gross value was estimated to be CNY 349 million in the study area, and CNY 169,500 for a single tree on average. Based on the case study, a conceptual framework for socio-cultural value assessment and multi-scale protection of large old trees was proposed, which can provide references for the improvement of current conservation policies from both quantitative and qualitative perspectives, and give insights into rural revitalization strategies in China.

Learning from User-driven Events to Generate Automation Sequences

Enabling smart devices to learn automating actions as expected is a crucial yet challenging task. The traditional Trigger-Action rule approach for device automation is prone to ambiguity in complex scenarios. To address this issue, we propose a data-driven approach that leverages recorded user-driven event sequences to predict potential actions users may take and generate fine-grained device automation sequences. Our key intuition is that user-driven event sequences, like human-written articles and programs, are governed by consistent semantic contexts and contain regularities that can be modeled to generate sequences that express the user's preferences. We introduce ASGen, a deep learning framework that combines sequential information, event attributes, and external knowledge to form the event representation and output sequences of arbitrary length to facilitate automation. To evaluate our approach from both quantitative and qualitative perspectives, we conduct two studies using a realistic dataset containing over 4.4 million events. Our results show that our approach surpasses other methods by providing more accurate recommendations. And the automation sequences generated by our model are perceived as equally or even more rational and useful compared to those generated by humans.

"It's very saddening, you keep on wondering when the symptoms will be over": A qualitative study exploring the long-term chikungunya disease impact on daily life and well-being, 6 years after disease onset.

Long-term chikungunya is a mosquito-borne disease, characterized by disabling rheumatic symptoms persisting for years, after infection with the chikungunya virus. Previous studies focused on assessing the well-being of affected individuals from a quantitative perspective using generic instruments, and have reported physical and psychological impairment. However, a common critique is that generic instrument's structured responses and pre-defined health domains selected by health professionals, may not capture the full extent of well-being impairment experienced by patients. This study aimed to explore in-depth to which extent long-term chikungunya disease impacts daily living and the physical, psychological, and social well-being from the experiences and perspective of affected individuals. Using open-ended questions, in-depth interviews were conducted with 20 purposively selected individuals with long-term chikungunya disease, in Curaçao. Interview audio-recordings were transcribed verbatim. The data were thematically analyzed. Living with persistent rheumatic symptoms affected the participant's daily living and well-being in several ways: experience of physical impact (restricted physical functioning and limitations in activities of daily life); experience of psychological impact (altered emotional state, fear of walking and running, psychosocial aspects of footwear adaptations, and uncertainty about disease progression and future health); and experience of social impact (social isolation and impaired relational maintenance, social dependency, challenges of social support, at-work productivity loss, and giving up leisure activities after work). This study, the first of its kind, indicated that the adverse impact of long-term chikungunya disease is currently underreported. The persistent rheumatic symptoms had a negative effect on functional ability, which in turn impacted broad aspects of daily life and well-being, beyond what is captured by generic instruments. In the view of the findings, physical exercise programs including manual therapy, aerobics, resistance and stretching exercises, and orthopaedic footwear interventions in a multidisciplinary patient-centred approach may improve physical function and subsequently overall well-being.