Research In Field Research Articles

AI-generated text in otolaryngology publications: a comparative analysis before and after the release of ChatGPT.

This study delves into the broader implications of artificial intelligence (AI) text generation technologies, including large language models (LLMs) and chatbots, on the scientific literature of otolaryngology. By observing trends in AI-generated text within published otolaryngology studies, this investigation aims to contextualize the impact of AI-driven tools that are reshaping scientific writing and communication. Text from 143 original articles published in JAMA Otolaryngology - Head and Neck Surgery was collected, representing periods before and after ChatGPT's release in November 2022. The text from each article's abstract, introduction, methods, results, and discussion were entered into ZeroGPT.com to estimate the percentage of AI-generated content. Statistical analyses, including T-Tests and Fligner-Killeen's tests, were conducted using R. A significant increase was observed in the mean percentage of AI-generated text post-ChatGPT release, especially in the abstract (from 34.36 to 46.53%, p = 0.004), introduction (from 32.43 to 45.08%, p = 0.010), and discussion sections (from 15.73 to 25.03%, p = 0.015). Publications of authors from non-English speaking countries demonstrated a higher percentage of AI-generated text. This study found that the advent of ChatGPT has significantly impacted writing practices among researchers publishing in JAMA Otolaryngology - Head and Neck Surgery, raising concerns over the accuracy of AI-created content and potential misinformation risks. This manuscript highlights the evolving dynamics between AI technologies, scientific communication, and publication integrity, emphasizing the urgent need for continued research in this dynamic field. The findings also suggest an increasing reliance on AI tools like ChatGPT, raising questions about their broader implications for scientific publishing.

Extracellular Membrane Vesicles of Escherichia coli Induce Apoptosis of CT26 Colon Carcinoma Cells.

Escherichia coli (E. coli) is commonly utilized as a vehicle for anti-tumor therapy due to its unique tumor-targeting capabilities and ease of engineering modification. To further explore the role of E. coli in tumor treatment, we consider that E. coli outer membrane vesicles (E. coli-OMVs) play a crucial role in the therapeutic process. Firstly, E. coli-OMVs were isolated and partially purified by filtration and ultracentrifugation, and were characterized using techniques such as nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM) and Western Blot (WB). The obtained extracellular nanoparticles, containing OMVs, were found to inhibited the growth of CT26 tumor in mice, while the expression of Bax protein was increased and the expression of Bcl-2 protein decreased. In vitro experiments showed that E. coli-OMVs entered CT26 cells and inhibited cell proliferation, invasion and migration. In addition, in the presence of E. coli-OMVs, we observed an increase in apoptosis rate and a decrease in the ratio of Bcl-2/Bax. These data indicate that E. coli-OMVs inhibits the growth of CT26 colon cancer by inducing apoptosis of CT26 cells. These findings propose E. coli-OMVs as a promising therapeutic drug for colorectal cancer (CRC), providing robust support for further research in related fields.

An improved efficientnet B7 underwater marine organism image classification model based on the spatial group enhancement attention mechanisms

In this paper, we adopt the Efficientnet B7 model, which is an excellent performer in deep learning algorithms, and improve it by combining with the Spatial Group Enhancement attention mechanism to provide an innovative method for underwater biological image classification. After a reasonable division of the dataset, we introduced the improved Efficientnet B7 model for training. By observing the change of the loss curve on the training set, it can be seen that the loss value of the model gradually decreases from 0.6 to 0.05 and tends to be stable, which indicates that the classification prediction of the model is gradually close to the real result, and it can classify the underwater marine organisms images effectively. The accuracy on the training set gradually increases from the initial 80.12% to 98.31%, and the recall also grows from 75.82% to 98.93%, showing that the model predicts well. The performance on the test set shows an accuracy of 84.86%, a recall of 82.40%, and an F1 value of 80.2%, indicating that the model has good generalisation ability. This means that our proposed improved methods and ideas have achieved significant results in the task of underwater biological image classification, providing a useful reference for research in related fields. By comparing the experimental results, it can be seen that the optimisation of the Efficientnet B7 model by introducing the Spatial Group Enhancement attention mechanism achieves better performance in the underwater marine organisms image classification task, which lays the foundation for the future application of deep learning in underwater environments. This study is of positive significance for the promotion of underwater biology research, marine protection and other fields, and provides new ideas and methods for carrying out more in-depth related research.

Least Squares Estimation of Multifactor Uncertain Differential Equations with Applications to the Stock Market

Multifactor uncertain differential equations are powerful tools for studying dynamic systems under multi-source noise. A key challenge in this study is how to accurately estimate unknown parameters based on the framework of uncertainty theory in multi-source noise environments. To address this core problem, this paper innovatively proposes a least-squares estimation method. The essence of this method lies in constructing statistical invariants with a symmetric uncertainty distribution based on observational data and determining specific parameters by minimizing the distance between the population distribution and the empirical distribution of the statistical invariant. Additionally, two numerical examples are provided to help readers better understand the practical operation and effectiveness of this method. In addition, we also provide a case study of JD.com’s stock prices to illustrate the advantages of the method proposed in this paper, which not only provides a new idea and method for addressing the problem of dynamic system parameter estimation but also provides a new perspective and tool for research and application in related fields.

NAVIGATING FINANCIAL DECISIONS: A COMPREHENSIVE REVIEW OF THEORIES, BEHAVIOURS, AND INNOVATIONS

This literature review synthesizes seminal and contemporary research on financial decision-making, emphasizing theoretical frameworks and empirical findings. Fama's (1970) Efficient Market Hypothesis sets the foundation for understanding market behavior, while Kahneman and Tversky's (1979) Prospect Theory introduces psychological influences, highlighting biases such as loss aversion (Tversky & Kahneman, 1991). Jensen and Meckling (1976) provide insights into agency theory, exploring the implications of managerial behavior on firm performance. The influence of gender on investment strategies is examined by Barber and Odean (2001), illustrating the role of overconfidence. Additionally, the impact of social interactions on financial choices is explored by Bursztyn et al. (2014). Financial literacy, addressed by Lusardi and Mitchell (2014), underscores the importance of informed decision-making in personal finance. The review also highlights the integration of behavioral insights in corporate finance, particularly in capital structure decisions (Myers, 1984) and risk management practices (Hull, 2012). Overall, the collected works illustrate a rich tapestry of factors influencing financial decisions, blending economic theory with behavioral insights, and emphasizing the necessity for ongoing research in this dynamic field. KEYWORDS: Financial Decision-Making, Behavioral Finance, Prospect Theory, Market Efficiency, Agency Theory, Overconfidence, Financial Literacy, Risk Management, Capital Structure and Social Interactions.

Reactions Driven by Primitive Nonbiological Polyesters.

ConspectusAll life on Earth is composed of cells, which are built from and run by biological reactions and structures. These reactions and structures are generally the result of action by cellular biomolecules, which are indispensable for the function and survival of all living organisms. Specifically, biological catalysis, namely by protein enzymes, but also by other biomolecules including nucleic acids, is an essential component of life. How the biomolecules themselves that perform biological catalysis came to exist in the first place is a major unanswered question that plagues researchers to this day, which is generally the focus of the origins of life (OoL) research field. Based on current knowledge, it is generally postulated that early Earth was full of a myriad of different chemicals, and that these chemicals reacted in specific ways that led to the emergence of biochemistry, cells, and later, life. In particular, a significant part of OoL research focuses on the synthesis, evolution, and function of biomolecules potentially present under early Earth conditions, as a way to understand their eventual transition into modern life. However, this narrative overlooks possibilities that other molecules contributed to the OoL, as while biomolecules that led to life were certainly present on early Earth, at the same time, other molecules that may not have strict, direct biological lineage were also widely and abundantly present. For example, hydroxy acids, although playing a role in metabolism or as parts of certain biological structures, are not generally considered to be as essential to modern biology as amino acids (a chemically similar monomer), and thus research in the OoL field tends to perhaps focus more on amino acids than hydroxy acids. However, their likely abundance on early Earth coupled with their ability to spontaneously condense into polymers (i.e., polyesters) make hydroxy acids, and their subsequent products, functions, and reactions, a reasonable target of investigation for prebiotic chemists. Whether "non-biological" hydroxy acids or polyesters can contribute to the emergence of life on early Earth is an inquiry that deserves attention within the OoL community, as this knowledge can also contribute to our understanding of the plausibility of extraterrestrial life that does not exactly use the biochemical set found in terrestrial organisms. While some demonstrations have been made with respect to compartment assembly, compartmentalization, and growth of primitive polyester-based systems, whether these "non-biological" polymers can contribute any catalytic function and/or drive primitive reactions is still an important step toward the development of early life. Here, we review research both from the OoL field as well as from industry and applied sciences regarding potential catalysis or reaction driven by "non-biological" polyesters in various forms: as linear polymers, as hyperbranched polyesters, and as membraneless microdroplets.

Enriching the evidence base of co-creation research in public health with methodological principles of critical realism

ABSTRACT With the popularity of co-creation research in public health and other fields, there is a need to strengthen its evidence-base by developing a framework based on meta-theoretical principles. The lack of applying meta-theoretical principles in co-creation research impedes the theory- and evidence building. Critical realism seems a promising candidate for providing meta-theoretical principles to enrich the evidence base of co-creation research in public health. To this purpose we searched for relevant papers on critical realism methodological principles, clarified and subsequently applied such principles to a co-creation public health case study. We provide explanatory steps to apply five principles; 1) focusing on understanding an event, like childhood overweight, 2) exploring the broader structure and context surrounding the event, 3) constructing hypotheses about the underlying mechanism(s) of an event, 4) empirical testing to corroborate those hypotheses, and 5) using multiple methods and triangulation. Further, this study shows that critical realism can enrich co-creation research in public health by iteratively building theory and evidence following the five proposed principles.

상담분야에서의 과학자-실무자 모델을 중심으로 한 연구자 경험

Objectives The purpose of this study is to explore qualitative research experiences in the counseling field and understand the meaning of the internal-external experiences experienced as a counselor, researcher, and educator. In particular, this study explores what experiences are formed in relation to the identity of the researcher as a counselor and the counselor as a researcher. Methods To this end, the researcher described in chronological order what experiences I have as a qualitative researcher in the counseling field and formulated the research questions ‘What did you experience in the process of qualitative research in the counseling field?’, ‘How can qualitative research be connected in the field of counselor education?’ and studied using the autoethnography method to explore its meaning. Results The results of the study are as follows: First, the researcher as a counselor, second, the counselor as a researcher, and third, the counselor and the educator as a researcher. This study is meaningful in that it contains unique experiences in qualitative research in the field of counseling by vividly exploring one's experiences with the researcher's own voice, and expands and shares an empirical understanding of the process of forming one's identity as a scientist-practitioner. Conclusions Qualitative research experience in the field of counseling can be used as a foundation for growth and can provide important meaning to counseling, research, and educational practice.

Insulin resistance as the molecular link between diabetes and Alzheimer's disease.

Diabetes mellitus (DM) and Alzheimer's disease (AD) are two major health concerns that have seen a rising prevalence worldwide. Recent studies have indicated a possible link between DM and an increased risk of developing AD. Insulin, while primarily known for its role in regulating blood sugar, also plays a vital role in protecting brain functions. Insulin resistance (IR), especially prevalent in type 2 diabetes, is believed to play a significant role in AD's development. When insulin signalling becomes dysfunctional, it can negatively affect various brain functions, making individuals more susceptible to AD's defining features, such as the buildup of beta-amyloid plaques and tau protein tangles. Emerging research suggests that addressing insulin-related issues might help reduce or even reverse the brain changes linked to AD. This review aims to explore the rela-tionship between DM and AD, with a focus on the role of IR. It also explores the molecular mechanisms by which IR might lead to brain changes and assesses current treatments that target IR. Understanding IR's role in the connection between DM and AD offers new possibilities for treatments and highlights the importance of continued research in this interdisciplinary field.

Fish 3D Locomotion app: a user-friendly computer application package for automatic data calculation and endpoint extraction for novel tank behavior in fish.

This paper introduces the Fish 3D Locomotion app (F3LA), a Python-based, Graphical User Interface (GUI)-equipped tool designed to automate behavioral endpoint extraction in zebrafish locomotion assays. Building on our previous work, which utilized a specialized aquatic tank with a mirror and a single camera for fish movement tracking in three dimensions, F3LA significantly enhances data processing efficiency. Its accuracy was tested by reanalyzing and comprehensively comparing the calculated data with the previously published data from prior publications. From the comparison results, 90% of endpoints showed a similar statistical difference result. These minor differences were due to the different starting points for the dataset and updated calculation formulas that are implemented in F3LA. In addition, shoaling area or shoaling volume calculations are also included in F3LA as a new feature that can serve as sensitive indicators of social cohesion, group dynamics, or stress responses, offering insights into neuropsychological conditions or the effects of pharmacological interventions. Furthermore, F3LA offers a marked improvement over manual operations, being at least five times faster, while maintaining consistent accuracy as it reduces human-induced errors, ensuring a higher degree of reliability in the results. Finally, the potency of F3LA was tested to evaluate the toxicities of 14 rare earth elements (REEs) to the adult zebrafish behaviors. Based on the results, our findings suggested that each tested REE altered fish behaviors in different patterns and magnitudes to each other. However, among the tested light rare earth elements (LREEs), neodymium was demonstrated to cause more relatively severe behavior alterations than other LREEs, indicated by the statistically higher value of entropy (0.2695 ± 0.04977 (mean with a standard deviation)) than the control group (0.2352 ± 0.05896). Meanwhile, in terms of heavy rare earth elements (HREEs), erbium seemed to lead to more distinct behavior toxicities than other HREEs, which was shown by the statistically lower level of fractal dimension (2.022 ± 0.3412) than the untreated group (2.255 ± 0.1661). Taken together, F3LA's development marks a significant advance in high-throughput toxicological and pharmacological assessments in zebrafish, leveraging three-dimensional locomotion data for a more comprehensive analysis of fish behavior performance, providing a significant contribution to research in various fields.

Exploring the inflammation-related mechanisms of Lingguizhugan decoction on right ventricular remodeling secondary to pulmonary arterial hypertension based on integrated strategy using UPLC-HRMS, systems biology approach, and experimental validation

BackgroundPulmonary arterial hypertension (PAH) and the consequent right heart dysfunction persist with high morbidity and mortality, and the mechanisms and pharmacologic interventions for chronic right-sided heart failure (RHF) have not been adequately investigated. Research has shown that prolonged inflammation is critical in precipitating the progression of PAH-associated right heart pathology. Some research demonstrated that Lingguizhugan decoction (LGZGD), as a classical Chinese medicine formula, had beneficial effects in alleviating PAH and RHF, while its underlying mechanisms involved are not fully elucidated. PurposeBased on that, this study aims to investigate the effects and underlying mechanisms of LGZGD on PAH-induced RHF. Study DesignIn this study, we identified the serum constituents and deciphered the potential anti-inflammatory mechanism and crucial components of LGZGD using combined approaches of UPLC-HRMS, transcriptomic analysis, and molecular docking techniques. Finally, we used in vivo experiments to verify the expression of key targets in the monocrotaline (MCT)-induced RHF model and the intervene effect of LGZGD. ResultsIntegrated strategies based on UPLC-HRMS and systems biology approach combined with in vivo experimental validation showed that LGZGD could improve right heart fibrosis and dysfunction via regulating diverse inflammatory signaling pathways and the activity of immune cells, including chemokine family CCL2, CXCR4, leukocyte integrins family ITGAL, ITGB2, and M2 macrophage infiltration, as well as lipid peroxidation-associated HMOX1, NOX4, and 4-HNE. ConclusionThe present research demonstrated for the first time that LGZGD might improve PAH-induced RHF through multiple anti-inflammatory signaling and inhibition of ferroptosis, which could provide certain directions for future research in related fields.

Corporate Social Responsibility Disclosure Quality and Firms’ Investment Efficiency: Evidence from Chinese Listed Companies

In China, where the corporate social responsibility (CSR) process is relatively underdeveloped, the government has promulgated a series of laws and regulations on CSR disclosure in recent years to promote the sustainable transformation of the economy. Using data from A-share listed Chinese firms from 2009 to 2021, this study empirically examines the relationship between CSR disclosure quality and firm investment efficiency in China. The results indicate that (1) improvements in CSR disclosure quality significantly mitigate firms’ underinvestment and overinvestment, thereby enhancing investment efficiency. (2) Further analysis shows that high-quality CSR information also promotes investment efficiency by reducing agency costs and financing constraints and improving media evaluations of firms. (3) A heterogeneity analysis suggests that the positive effect of CSR disclosure on investment efficiency is stronger for firms with lower equity incentives, more severe financing constraints, and higher media attention. Our study extends the understanding of the mechanisms through which CSR disclosure affects firms’ investment efficiency, potentially providing insights for research in related fields and guiding future CSR disclosure practices in other developing countries.

Advancements in Fused Deposition Modeling for Aerospace: Optimizing Lightweight and High- Strength Components

Fused Deposition Modeling (FDM) has emerged as a pivotal technology in aerospace manufacturing, enabling the creation of lightweight and high-strength components. Recent advancements in FDM materials, process optimization, and design methodologies have significantly enhanced its applicability in producing aerospace parts that meet stringent performance criteria. This paper reviews the latest developments in FDM technology, focusing on material innovations, structural optimization techniques, design for additive manufacturing and practical applications in the aerospace sector. Key advancements include the use of high-performance thermoplastics, carbon fiber composites, and hybrid materials, as well as improved printing techniques that reduce defects and enhance mechanical properties. The potential of FDM to revolutionize aerospace manufacturing through cost- effective and efficient production of complex geometries is explored, highlighting ongoing research and future directions in this dynamic field.

Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses.

Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.

Improving the non-structural preparedness of the selected hospital based on the FOCUS-PDCA1 model: action research

IntroductionWith the intensification of the country’s development process, the expansion of cities and population, and the inclusion of Iran in the accident-prone category, reducing the vulnerability of non-structures has received more attention from the organizations involved. In addition to damage to communities and infrastructure, accidents can affect hospitals and their non-organizational components. Hospitals, as the front line of providing medical services after accidents, must maintain their stability, ensure the safety of their patients and employees, and continue to operate without interruption as in normal conditions. Therefore, it is necessary to evaluate the non-structural safety and their preparedness to ensure they can perform acceptable in critical conditions.MethodsThis applied research was conducted in 2023 (September to December) using the participatory action research method in all selected hospital departments. The level of non-structural preparedness of the hospital was checked using the valid “Hospital Safety Index” questionnaire and the non-structural weaknesses of the hospital were identified. Then, in action research using the FOCUS-PDCA model, a program was implemented to improve the non-structural preparedness of different departments of hospitals in the face of accidents and disasters. The non-structural readiness level of the hospital was compared before and after the implementation of the change.ResultsBased on the evaluation conducted in the present study, the lowest level of safety was observed in the water supply system, office furniture and appliances, and fuel storage. The waste management systems, the fire protection system, and the long-distance communication systems were at a desirable performance level. Although in the evaluation before the change, the overall score of the hospital was 71.01%, and it had a desirable performance level in non-structural factors, in all the involved parts of the hospital, the sensitive, critical, and practical parts in the operation of the hospital had an average and sometimes low safety level. According to the obtained safety score, the safety level of the selected hospital before the change was 7 out of 10 (level seven of safety evaluation = medium). After the change and corrective measures, the non-structural safety assessment score was 76.93, and the hospital’s safety level was raised by one step to 8 out of 10 (8th level of safety assessment = relatively favorable).ConclusionThe present study showed that the application of Total Quality Management (TQM), primarily its application tool FOCUS-PDCA, is efficient and helpful in improving the non-structural preparedness of hospitals. Using action research in the health field in accidents and disasters can open blind knots in different dimensions of preparedness (structural, non-structural, and functional).

High-Speed Stress Field Measurement In A Soft Substrate During Droplet Impact

In this study, we utilized high-speed photoelastic tomography to quantify dynamic stress fields within a soft substrate during droplet impact. This manuscript details the measurement technique, which employs a high-speed polarization camera and the principles of photoelastic tomography. Our method successfully enabled the quantitative measurement of dynamic stress fields in a soft substrate during droplet impact. Additionally, we conducted an analysis of the impact force derived through the spatial integration of the measured stress field. The discussion explored the interplay between the maximum impact force, droplet viscosity, and substrate elasticity. Our findings indicate that the maximum impact force 𝐹max can be expressed as a function with a self-similar variable of 𝑅𝑒 / 𝐶𝑎^2 , where 𝑅𝑒 is Reynolds number representing the droplet inertial force and droplet viscous force and 𝐶𝑎 is Cauchy number representing the ratio of the droplet inertial force and substrate elastic force. This combination, 𝑅𝑒 / 𝐶𝑎^2 , represents the relationship between the relaxation time of droplet and substrate deformation ( 𝜂/ 𝐸), the contact time of the droplet (𝑅 / 𝑉), and the ratio of substrate elastic force to droplet inertial force. Consequently, the maximum impact force 𝑅𝑒 / 𝐶𝑎^2 is determined by the balance between the relaxation and contact times. We believe that our developed method will significantly enhance the understanding of droplet impact phenomena. Furthermore, it holds potential for broader applications in various engineering processes, such as analyzing stress distribution in materials caused by liquid jet impact and studying cavitation bubbles in viscoelastic materials. This method's ability to provide detailed quantitative measurements of dynamic stress fields offers a valuable tool for future research and technological advancements in related fields.

ENTEROBACTER CLOACAE LIPOPOLYSACCHARIDE EXPORT SYSTEM PROTEIN (LPTC) GENE EXPRESSION VARIATION VIA EXPOSE TO BIOSYNTHESIZED ZINC OXIDE NANOPARTICLES

Synthetic nanoparticles (NPs) have become more widely used in the disinfection and health sectors owing to their ability to effectively penetrate biological systems. Recent research has demonstrated the ability of microbial proteins and enzymes to function as reducing agents throughout the NP-production process, providing a different option to chemical and physical techniques. This method not only saves money and is effective, but also has the least possible environmental impact. This work used Lactobacillus spp., as the reducing and capping agent to create zinc oxide nanoparticles, (ZnO NPs). Numerous analytical techniques were employed to examine the generated ZnO NPs; these techniques include ultraviolet–visible spectroscopy (UV–vis), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). As an opportunistic pathogenic bacterium, Enterobacter cloaca possesses several virulence characteristics that enable it to infiltrate target tissues. However, bacteria can become resistant to antibiotics, which in turn makes treating bacterial infections becomes more difficult. With the development of science at the biotechnology level, using zinc oxide ZnO NPs on isolates of Enterobacter cloacae, we conducted research in the promising field of nanotechnology. The impact of three different concentrations of ZnO NPs on the gene expression of Enterobacter cloaca lipopolysaccharide transport (Lpt) proteins in isolates obtained from some patients suffering of various infections was investigated. Bacteria with the highest multidrug resistance were selected for further analysis. Expression of LptC gene was reduced significantly at concentration of 125 mg/mL (P < 0.01) for all the isolate that treated with ZnO NPs.

The Use of Animation and Augmented Reality in Teaching Computer Programming

This paper presents the main difficulties in learning computer programming faced by primary and secondary education students and examines whether Augmented Reality (AR) and animation can contribute to more effective teaching of this subject. The benefits of AR and animation in learning programming are presented and analyzed, and an overview of related applications developed in recent years is provided, as evidenced by the literature. Finally, conclusions are drawn, and suggestions for future research in this specific field are made.

Human Brain Organoid Research and Applications: Where and How to Meet Legal Challenges?

An ethical and legal framework is needed to regulate the rapidly developing human brain organoid research field properly. However, considering the legal issues involved in human brain organoid research remains underdeveloped and scattered. This article reviews the legal issues of human brain organoid research, grouping them into the following five broad themes: (1) consciousness, (2) legal status, (3) consent, (4) ownership, and (5) transplantation. The issues in each topic include both the urgent (e.g., appropriate forms of consent) and the speculative (e.g., protection of conscious human brain organoids). Therefore, we have attempted to be as explicit as possible about the timescale within which each issue will be realized and to prioritize each. Examining these issues has revealed legal issues specific to human brain organoid research and issues common to research in other fields. Further discussion of human brain organoid research from a legal perspective is needed in the future, considering discussions in related fields.

Entrepreneurial intentions among polytechnic students in India: Examining the theory of planned behaviour using PLS-SEM

This study delves into the factors that kindle entrepreneurial intentions among Indian polytechnic students, shedding light on the pivotal roles of course curriculum, institutional support, family, and peers. Prior research in various fields has often employed the theory of planned behaviour to explore entrepreneurial intentions. However, a noticeable gap exists as no study has investigated this phenomenon among polytechnic students until now. This research uses the theory of planned behaviour to scrutinize entrepreneurial intentions among students in government polytechnic colleges in Malappuram and Calicut districts in India. Analyzing data from 254 valid questionnaires, the study employs the Partial Least Square Structural Equation Modeling method for analysis. The results reveal that peers significantly influence perceived behavioural control, attitude, and subjective norms. These findings resonate with earlier studies and emphasize the critical roles of peers, course curriculum, and institutional support in shaping entrepreneurial intentions. Ultimately, the findings underscore the potential of tailoring polytechnic education towards entrepreneurship, offering technical students opportunities for growth and facilitating positive economic and societal transformations.