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This paper analyzes the ethics of integrating Artificial Intelligence (AI), particularly regarding AI-generated educational content in academia. It attempts to explore how AI customization mimics human interaction and behavior in education, investigate ethical concerns in educational AI adoption, and assess ChatGPT’s ethical use for nurturing curiosity and maintaining academic integrity in education.

Fictional tales may help us think critically and creatively to uncover hidden truths. The narratives are analyzed to determine the affordances and drawbacks of Artificial Intelligence in Education (AIEd).

The study highlights the imperative for innovative, ethically grounded strategies in harnessing AI/GPT technology for education. AI can enhance learning, and human educators’ irreplaceable role is even more prominent, emphasizing the need to harmonize technology with pedagogical principles. However, ensuring the ethical integration of AI/GPT technology demands a delicate balance where the potential benefits of technology should not eclipse the essential role of human educators in the learning process.

This paper presents futuristic academic scenarios to explore critical dimensions and their impact on 21^st century learning. As AI assumes tasks once exclusive to human educators, it is essential to redefine the roles of both technology and human teachers, focusing on the future.

Recent empirical findings on the relationship between internationalization and firm performance (I–P) suggest a significant role of firm's context. Extending this line of argument, the authors study the effect of internationalization on firm's performance for emerging market firms from knowledge-intensive industries, taking into account the firm's motive of internationalization and host country’s location-based advantages.

The authors link host country-specific advantages (CSAs) with firm-specific advantages (FSAs) to identify three distinct settings of internationalization for emerging economy firms – (1) asset-exploitative internationalization in developing or least developed countries, (2) asset-exploitative internationalization in developed countries and (3) strategic asset-seeking internationalization. The authors test this study’s hypotheses on a sample of 415 Indian firms from knowledge-intensive industries.

The authors find that firm's performance upon internationalization is non-linear in each of the three different settings. The nature of the non-linear relationship depends upon location-based advantages of the host country and the motive of internationalization.

The motive of internationalization and the location-based advantages sought during internationalization are unique for emerging economy firms. Hence, the study extends understanding of the I–P linkage in an emerging economy context.

The purpose of this paper is to investigate experimentally the effect of several input process factors, namely, feed rate, spindle speed, ultrasonic power and coolant pressure, on hole quality measures (penetration rate [PR] and chipping diameter [CD]) in rotary mode ultrasonic drilling of macor bioceramic material.

The main experiments were planned using the response surface methodology (RSM). Scanning electron microscopy was also used to examine and study the microstructure of machined samples. This study revealed the existence of dominant brittle fracture and little plastic flow that resulted in a material loss from the base work surface. Experiment findings have shown the dependability and adequacy of the proposed mathematical model.

The percentage of brittle mode deformation rises as the penetration depth of abrasives increases (at increasing levels of feed rate). This was due to the fact that at greater depths of indentation, material loss begins in the form of bigger chunks and develops inter-granular fractures. These stated causes have provided an additional advantage to increasing the CD over the machined rod of bioceramic. The desirability method was also used to optimize multi-response measured responses (PR and CD). The mathematical model created using the RSM method will be very useful in industrial revelation. Furthermore, the investigated answers’ particle swarm optimization (PSO) and teacher-learner-based optimization (TLBO) make the parametric analysis more relevant and productive for real-life industrial practices.

Macor bioceramic has been widely recognized as one of the most highly demanded innovative dental ceramics, receiving expanded industry approval because of its outstanding and superior characteristics. However, effective and efficient processing remains a problem. Among the available contemporary machining methods introduced for processing typical and advanced materials, rotary mode ultrasonic machining has been identified as one of the best suitable candidates for precise processing of macor bioceramics, as this process produces thermal damage-free profiles, as well as high accuracy and an increased material removal rate. The optimized combined setting obtained using PSO is feed rate = 0.16 mm/s, spindle speed = 4,500 rpm, ultrasonic power = 60% and coolant pressure = 280 kPa with the value of fitness function is 0.0508. The optimized combined setting obtained using TLBO is feed rate = 0.06 mm/s, spindle speed = 2,500 rpm, ultrasonic power = 60% and coolant pressure = 280 kPa with the value of fitness function is 0.1703.

The purpose of this study was to design a multitask learning model so that biomedical entities can be extracted without having any ambiguity from biomedical texts.

In the proposed automated bio entity extraction (ABEE) model, a multitask learning model has been introduced with the combination of single-task learning models. Our model used Bidirectional Encoder Representations from Transformers to train the single-task learning model. Then combined model's outputs so that we can find the verity of entities from biomedical text.

The proposed ABEE model targeted unique gene/protein, chemical and disease entities from the biomedical text. The finding is more important in terms of biomedical research like drug finding and clinical trials. This research aids not only to reduce the effort of the researcher but also to reduce the cost of new drug discoveries and new treatments.

As such, there are no limitations with the model, but the research team plans to test the model with gigabyte of data and establish a knowledge graph so that researchers can easily estimate the entities of similar groups.

As far as the practical implication concerned, the ABEE model will be helpful in various natural language processing task as in information extraction (IE), it plays an important role in the biomedical named entity recognition and biomedical relation extraction and also in the information retrieval task like literature-based knowledge discovery.

During the COVID-19 pandemic, the demands for this type of our work increased because of the increase in the clinical trials at that time. If this type of research has been introduced previously, then it would have reduced the time and effort for new drug discoveries in this area.

In this work we proposed a novel multitask learning model that is capable to extract biomedical entities from the biomedical text without any ambiguity. The proposed model achieved state-of-the-art performance in terms of precision, recall and F1 score.

From the socioemotional wealth (SEW) perspective, family firms prioritize non-financial goals and show risk averse behaviour towards conducting acquisitions. In this paper, we study family firms' acquisitive behaviour while participating in CBA waves. Scholars have largely treated the cross border acquisition (CBA) wave and non-wave environments as homogeneous. We theorize that these two environments differ in their uncertainty and risk profiles on account of temporal clustering of acquisition deals. Accordingly, based on the SEW perspective, we examine the preference of family firms to participate in CBA waves.

The paper is based on CBAs conducted by Indian family firms between 2000 and 2018. These waves are identified by conducting a simulation based methodology.

Our findings suggest that foreign institutional ownership, firm age and acquisition relatedness moderate the relationship between family control and participation in CBA waves.

Our paper contributes towards the acquisitive behavior of family firms and their participation in CBA waves.

The purpose of this paper is to study the predictability of the recently proposed length scale-based two-equation k-kL model for external aerodynamic flows such as those also encountered in the high-lift devices.

The two-equation k-kL model solves the transport equations of turbulent kinetic energy (TKE) and the product of TKE and the integral length scale to obtain the effect of turbulence on the mean flow field. In theory, the use of governing equation for length scale (kL) along with the TKE promises applicability in a wide range of applications in both free-shear and wall-bounded flows with eddy-resolving capability.

The model is implemented in the in-house unstructured grid computational fluid dynamics solver to investigate its performance for airfoils in difficult-to-predict situations, including stalling and separation. The numerical findings show the good capability of the model in handling the complex flow physics in the external aerodynamic computations.

The model performance is studied for stationary turbulent external aerodynamic flows, using five different airfoils, including two multi-element airfoils in high-lift configurations which, in the knowledge of the authors, have not been simulated with k-kL model until now.

This paper aims to explore the local knowledge on climate change, its impacts and the responses they are making at the household or community level to deal with the changes on the basis of their experiences and perceptions.

The study was based on household survey conducted with one male and one female respondent in 202 households. Alongside, series of focused group discussions were conducted with local people to capture the perception on about climate change, its impacts and adaptation strategies applied to enhance their resilience capacity to changing climate. Rainfall and temperature data were collected from Department of Hydrology and Meteorology (DHM) for seven and four different stations, respectively, within Kathmandu Valley and analyzed to understand the climatic trend.

The perception of most of the local people on changes in temperature was almost in line with the recorded long-term climatic trend both showing an increasing trend, whereas the perception of decreasing both monsoon and non-monsoon rainfall did not match with the recorded data as the rainfall data analysis did not reflect any clear long-term pattern. People have been facing several impacts such as decrease in water sources, decrease in agricultural crop production, increase in new crop pest and weeds in agricultural crops. Local people are responding to these impacts as per their own skills and traditional knowledge.

This is totally original research article and the impacts and adaptations measures documented in this article may represent the case of peri-urban areas of least developed countries like Nepal.

This paper aims to examine the effect of perceived work–life balance on the perceived level of employer branding attraction valueand organizational talent management. Accordingly, the structural model is developed that delineates the interactions among these and explores the mediating effect of employer branding attraction value between the relationship of work–life balance and organizational talent management.

This study is based on survey results and review of literature in terms of their implications for the proposed framework. Data have been collected by convenience incidental sampling from middle-level executives working in different information and technology (IT) companies. The model and posited hypotheses were tested through structural equation modeling analysis.

Perceived work–life balance was found to be positive and significantly predicted the employer branding attraction value and organizational talent management. The study also showed that there exists a significant and positive correlation between employer branding attraction value and perceived organizational talent management. Further, employer branding attraction value found to be a mediating construct between the relationship of work–life balance and organizational talent management.

The present study will add insight into the human resource practitioners to design cost-effective and prolonged popular practices in order to meet the employees work and personal expectations under the organizational association. The research investigated issue within focused IT sector employees to understand and solve the issues generated with changing factors in an organizational environment such as increasing women participation, duel earning couple, and maintaining the difference between various categories of employees at the practice level.

The study has value at both the scholarly and practice level. At a scholarly level, the research investigated an important contemporary issue at both level individual as well as organizational level. In practice if organization implements people friendly work-life balance policies, then this will be surely be helpful in organizational productivity in form of talent management and employer branding and further this will improve the personal and professional performance of most elementary component of developing society.

Work–life balance much more depends upon employees' perception, but so far the study has neglected the impact of this perception on other organizational attributes maintained under human resource management. Changes in demographic characteristics and interchangeable role of the youth population in organizations and society as well thrive for the newer approach to deal with the personal and professional aspects of the employees.