Potential Challenges Research Articles

Organizational legitimacy and firm nonmarket strategies as catalysts of alliance green management

Numerous studies have previously highlighted the potential challenges in association with implementing green management practices within firms. However, there remains a lack of comprehensive understanding concerning the specific factors that drive firms to adopt alliance green management (AGM). To address the existing gap in knowledge, our research builds upon embeddedness perspective to unravel the underlying dynamics motivating firms to engage in AGM. Drawing on the data of 199 alliance firms in China, our findings demonstrate a positive relation between organizational legitimacy and AGM. We also find that firm nonmarket strategies can (green management within focal firm and corporate political activity) positively influence AGM. Further analyses suggest that environmental scanning enhances the positive relation between organizational legitimacy and AGM. Besides, the results indicate that environmental scanning enhances both the green management within focal firm – AGM linkage and the corporate political activity – AGM linkage. Collectively, our findings substantiate the important roles of organizational legitimacy and firm nonmarket strategies in shaping AGM in an emerging economy.

Cross-Sectional Survey of Student and Faculty Experiences with Feedback and Assessment of Clinical Competency on Final Year Rotations at American Association of Veterinary Medical Colleges (AAVMC) Member Institutions

The clinical experiences, feedback, and assessment that veterinary students receive during final year rotations have a significant impact on whether they will achieve entry-level competency at the time of graduation. In this study, a cross-sectional survey was administered to American Association of Veterinary Medical Colleges (AAVMC) member institutions to collect baseline data about current feedback and assessment practices to identify key target areas for future research and educational interventions. Responses were received from 89 faculty and 155 students distributed across 25 universities. The results indicated that there are significant gaps between evidence-based approaches for delivering feedback and assessment and what was being implemented in practice. Most feedback was provided to students in the form of end-of-rotation evaluations sometimes several weeks to months after the rotation finished when faculty were unlikely to remember specific interactions with students and there were limited opportunities for students to demonstrate progress towards addressing identified concerns. Although the most valuable type of feedback identified by students was verbal feedback delivered shortly after clinical experiences, this method was often not used due to factors such as lack of time, poor learning environments within veterinary teaching hospitals, and lack of faculty training in delivering effective feedback. The results also indicated potential challenges with how non-technical domains of competence within the AAVMC Competency-Based Veterinary Education (CBVE) Framework are currently evaluated. Finding avenues to improve feedback and assessment processes in final year clinical settings is essential to ensure that veterinary students are adequately prepared for practice.

Philosophy of future: analytical overview of interaction between education, science, and artificial intelligence in the context of contemporary challenges

Currently, artificial intelligence is changing the future landscape of technology and digitalization and transforming the way knowledge is generated and shared in education and science. The aim of the article is to interpret the future through interactions between education, science, and AI and to outline their potential challenges when digital transformations occur. While answering the research questions the mixed-methods approach was applied. For the study both quantitative and qualitative data was collected through descriptive and empirical survey. The empirical survey included computer-assisted web interview to assess the most relevant concepts according to the participants responses. The study involved 42 participants that were selected randomly. The selection criteria concerned educational background, previous experience, representation of diverse perspectives, theories, or approaches within the philosophy, active engagement in educational practice, and wiliness to participate. To analyse the data statistical software NVivo was applied. Approximately 70 recent scientific works were studied to present the problem through multifaceted approach. The findings show the participants’ anticipations are related to the cognitive load theory, constructivist theory, and socio-cultural theory. A number of challenges threatening innovative developments arise within the educational and scientific environments. They include ethical concerns, misinformation, digital divide, unequal infrastructure, lack of regulation, lack of digital skills, resistance to change, technology integration, and limited digital pedagogy. Ethics plays a crucial role in shaping digital transformations in education and science. The category of academic virtue is closely connected to ethical and responsible use of Ai. The paradigm of academic virtue includes ethical of knowledge, collaboration, responsibility, honesty, accuracy, adaptability, openness. AI brings automated content creation, language processing opportunities, real-time translation, and enhanced accessibility and, therefore, changes communication in the field of education and science. The research showed that the principles of effective implementation of AI in education and science include philosophical, educational, and ethical dimensions.

The role of Artificial Intelligence in digital forensics: Case studies and future directions

Key digested messageThe increase in digital evidence, especially in cases involving Indecent Images of Children (IIOC), presents a pressing challenge for law enforcement agencies. In this article, we discuss two of the most prominent types of Artificial Intelligence (AI) and how they can be used in digital forensic processes, providing examples, and highlighting potential challenges that are likely to be experienced in developing and adopting AI. The two main types are of Data-Driven Model (DDM) age classification and ModelBased Reasoning (MBR), and in this article, examples for both are provided and discussed in the contents of IIOC investigations.

ChatGPT for editors: enhancing efficiency and effectiveness

This tutorial examines how ChatGPT can assist journal editors in improving the efficiency and effectiveness of academic publishing. It highlights ChatGPT’s key characteristics, focusing on the use of “Custom instructions” to generate tailored responses and plugin integration for accessing up-to-date information. The tutorial presents practical advice and illustrative examples to demonstrate how editors can adeptly employ these features to improve their work practices. It covers the intricacies of developing advanced prompts and the application of zero-shot and few-shot prompting techniques across a range of editorial tasks, including literature reviews, training novice reviewers, and improving language quality. Furthermore, the tutorial addresses potential challenges inherent in using ChatGPT, which include a lack of precision and sensitivity to cultural nuances, the presence of biases, and a limited vocabulary in specialized fields, among others. The tutorial concludes by advocating for an integrated approach, combining ChatGPT’s technological advancements with the critical insight of human editors. This approach emphasizes that ChatGPT should be recognized not as a replacement for human judgment and expertise in editorial processes, but as a tool that plays a supportive and complementary role.

Beneficial and Detrimental Effects of Cytokines during Influenza and COVID-19.

Cytokines are signaling molecules that play a role in myriad processes, including those occurring during diseases and homeostasis. Their homeostatic function begins during embryogenesis and persists throughout life, including appropriate signaling for the cell and organism death. During viral infections, antiviral cytokines such as interferons and inflammatory cytokines are upregulated. Despite the well-known benefits of these cytokines, their levels often correlate with disease severity, linking them to unfavorable outcomes. In this review, we discuss both the beneficial and pathological functions of cytokines and the potential challenges in separating these two roles. Further, we discuss challenges in targeting these cytokines during disease and propose a new method for quantifying the cytokine effect to limit the pathological consequences while preserving their beneficial effects.

How Realistic Are Coal Phase-Out Timeline Targets for Turkey?

Coal phase-out is considered to be critical to the success of energy transition for all countries. Yet, recent assessments indicate that energy security aspects may affect phase-out plans and/or commitments and jeopardize energy transition ambitions. This study aims to question to what extent coal phase-out targets for Türkiye are realistic. Although previous research has mainly focused on direct emission reduction targets and just transition aspects, we include a down-to-earth discussion of the potential challenges before coal phase-out. The interaction between phasing-out coal power generation and energy security aspects is also analyzed. To understand the coal phase-out timeline targets, its limitations, and constraints within the framework of future power projections, a supply–demand model with different scenarios was developed. In addition, energy storage was also discussed as an option. Analysis revealed that energy storage, in the short- and medium-term, may not be the panacea, as it may not be deployed in the scale to substitute the energy security that coal provided. Moreover, our findings indicate that phasing-out is not as simple as assumed. A target timeline is certainly not realistic considering the energy security aspect and challenges. On the other hand, economically nonviable and technically nonavailable coal-fired power plants in the power system may retire gradually (as a natural phase-out process). This may occur even without waiting for the target timeline, if there would ever officially be one.

Reusing Thermal Insulation Materials: Reuse Potential and Durability Assessment of Stone Wool Insulation in Flat Roofs

In the building renovation industry, a growing volume of discarded insulation materials, such as stone wool insulation, prematurely finds its way to landfills or incinerators after building demolitions. However, these materials often did not reach their complete service life potential, and the reuse of insulation materials is usually not considered in current building practices. This study provides a comprehensive overview of the potential challenges associated with repurposing stone wool insulation from existing flat roofs. By means of detailed assessments via dismantling and performance evaluations of collected stone wool insulation boards up to 28 years old, this research reveals the unavoidable damages that occur upon dismantling yet emphasizes that this does not impede reuse. While density and thermal performance remain stable over time, water absorption and mechanical stability are affected. In total, 48% of all short-term tests revealed an increase in water absorption, possibly due to hydrophobic substance degradation. Mechanical performances of aged SW insulation from flat roofs depend on various factors, with 43% and 33% of compression and puncture resistance tests, respectively, not meeting current standards. Beyond a durability assessment, this study advocates for a multidisciplinary approach, uniting materials science, construction engineering, and sustainability insights, to creatively repurpose used insulation materials into future projects.

Manufacturing Cell and Gene Therapies: Challenges in Clinical Translation.

The safety and efficacy of both cell and gene therapies have been demonstrated in numerous preclinical and clinical trials. Chimeric antigen receptor T (CAR-T) cell therapy, which leverages the technologies of both cell and gene therapies, has also shown great promise for treating various cancers. Advancements in pertinent fields have also highlighted challenges faced while manufacturing cell and gene therapy products. Potential problems and obstacles must be addressed to ease the clinical translation of individual therapies. Literature reviews of representative cell-based, gene-based, and cell-based gene therapies with regard to their general manufacturing processes, the challenges faced during manufacturing, and QC specifications are limited. We review the general manufacturing processes of cell and gene therapies, including those involving mesenchymal stem cells, viral vectors, and CAR-T cells. The complexities associated with the manufacturing processes and subsequent QC/validation processes may present challenges that could impede the clinical progression of the products. This article addresses these potential challenges. Further, we discuss the use of the manufacturing model and its impact on cell and gene therapy.

The Role of Smart Farming Technologies in Enhancing Crop Yields and Resource Efficiency: A Global Perspective

This research article explores the role of smart farming technologies in improving crop yields and resource efficiency from a global perspective. Utilizing a qualitative methodology involving literature review and library research, the study aims to examine the various smart farming technologies and their impact on agricultural productivity and sustainability.
 The literature review encompasses a wide range of sources, including scholarly articles, reports, and case studies, to provide a comprehensive understanding of smart farming technologies. By synthesizing existing research, the article identifies key technologies such as precision agriculture, Internet of Things (IoT) sensors, drones, and data analytics, and examines their applications in enhancing crop yields and resource management.
 The findings highlight the significant contributions of smart farming technologies in optimizing agricultural practices, minimizing resource wastage, and maximizing efficiency. Through precision farming techniques and real-time monitoring systems, farmers can make data-driven decisions regarding irrigation, fertilization, and pest control, leading to improved crop quality and higher yields.
 Moreover, the study discusses the potential challenges and barriers to the adoption of smart farming technologies, including cost, infrastructure, and digital literacy issues, particularly in developing countries. It also explores the importance of supportive policies, capacity building initiatives, and public-private partnerships in facilitating the widespread adoption of these technologies.

Saudi Cerebral Palsy Register (SCPR): Protocol on the Methods and Technical Details.

This protocol presents a comprehensive proposal for the establishment of the Saudi Cerebral Palsy Register (SCPR), a crucial project for investigating and addressing the prevalence, etiology, and management of cerebral palsy (CP) in Saudi Arabia. The SCPR will not only provide a robust database for ongoing research and analysis but will also serve as a platform for investigating the causes of CP, implementing preventative strategies, and improving the quality of care and outcomes for people with CP and their families in Saudi Arabia. Detailed case definitions, inclusion/exclusion criteria, and data collection protocols are discussed to ensure the integrity and comparability of the data. The plan also outlines strategic funding, institutional and government endorsement, sustainability considerations, potential challenges and proposed solutions, and expected outcomes and impact. These include creating research and educational opportunities, fostering regional and international collaborations, and significantly contributing to CP prevention strategies. Overcoming anticipated obstacles, such as stigma, institutional policies, and collaborations, and securing both necessary funding and endorsements are highlighted as critical for the success of the SCPR. The project is not only aligned with promote prevention of health risks, a target of Vision 2030 in Saudi Arabia, but is also expected to have a substantial impact on the health and quality of life of people with CP and their families in Saudi Arabia, serving as inspiration for similar efforts worldwide.

Comprehension of Financial Literacy Programs in India as Gateway to Empowering Women: Gauging through Case Study Approach

Overtime India has emerged as a global economic powerhouse; certain demographic groupings still lack general knowledge about economics and money. There has been an increasing recognition of the women entrepreneurs playing a substantial role in driving the economic growth and fostering innovation. Governments around the world have progressively focused their attention on supporting and empowering women in the business landscape. In India, various government schemes and initiatives have been introduced to provide women entrepreneurs with the necessary tools, resources, and opportunities to succeed in the competitive business world. Existing financial literacy programs for Indian female entrepreneurs need evaluation to gauge effectiveness, measure their impact, and identify participation barriers. This research aims to assess programs, study their influence, and inform improved initiatives. The study attempts in showcasing real-life success stories of the women entrepreneurs who have benefited from the scheme's financial assistance and mentorship, potential challenges, and its contribution to fostering a culture of the women entrepreneurship & the social entrepreneurship. The study assesses the effectiveness of these programs in providing guidance, skill enhancement, and networking opportunities to the aspiring and also the established women entrepreneurs. While taking into account the many socioeconomic environments that women operate in, the study offers insights into the policy measures that can best promote and empower women to become active participants in economic growth.

The Growth Prospects for Nigeria in Joining the African Continental Free Trade Area

This paper examines the potential benefits and challenges of Nigeria joining the African Continental Free Trade Area (AfCFTA) agreement, which aims to create a single market for goods and services across Africa. Using a computable general equilibrium model, we simulate the effects of trade liberalization under different scenarios of tariff reduction, trade facilitation, and regional integration. We find that Nigeria stands to gain from participating in the AfCFTA, especially if it is accompanied by improvements in infrastructure, customs procedures, and regulatory harmonization. However, we also identify some potential costs and risks, such as trade diversion, revenue loss, and adjustment costs for some sectors and regions. We recommend that Nigeria adopts a proactive and strategic approach to maximize the opportunities and mitigate the challenges of the AfCFTA, such as diversifying its export basket, enhancing its competitiveness, strengthening its domestic policies, and engaging in regional cooperation. Keywords: AfCFTA, Nigeria, trade liberalization, regional integration, computable general equilibrium model

Clinical Evaluation of the Pancreatic Cancer Microenvironment: Opportunities and Challenges.

Advances in our understanding of pancreatic ductal adenocarcinoma (PDAC) and its tumor microenvironment (TME) have the potential to transform treatment for the hundreds of thousands of patients who are diagnosed each year. Whereas the clinical assessment of cancer cell genetics has grown increasingly sophisticated and personalized, current protocols to evaluate the TME have lagged, despite evidence that the TME can be heterogeneous within and between patients. Here, we outline current protocols for PDAC diagnosis and management, review novel biomarkers, and highlight potential opportunities and challenges when evaluating the PDAC TME as we prepare to translate emerging TME-directed therapies to the clinic.

When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications.

Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.

Navigating the discontinuation of multiple sclerosis first line treatments: A paradigm shift in patient care

BackgroundThis retrospective study, conducted between 2005 and 2016, investigated the outcomes of patients with multiple sclerosis (MS) who discontinued injectable first-line disease-modifying therapies (DMTs). The study aimed to identify factors influencing treatment discontinuation and assess the impact of discontinuation on disease progression. MethodsData was collected from 2,270 patients who received injectable DMTs for at least two years and subsequently discontinued treatment due to clinical and MRI remission, side effects, or noncompliance. Patients were categorized into two groups: those stable after discontinuation (SAD) and those with relapse after discontinuation (RAD). Survival analysis and logistic regression were employed to assess factors influencing treatment discontinuation. ResultsOf the 60 patients who discontinued DMTs, one-third (n = 20) remained stable, while 40 patients experienced clinical and/or MRI activity during follow-up. The SAD group had a significantly later age at treatment discontinuation compared to RAD patients (35.9 ± 11.1 vs. 30.7 ± 6.1, p = 0.025). Patients below 40 years old had a higher likelihood of experiencing worsening (75 %), while those over 50 years old demonstrated an 80 % stability rate. SAD patients used DMTs for a more extended period than RAD patients (69.1 ± 47.3 vs. 46.6 ± 20.3 months, p = 0.012). A notable proportion (42.9 %) of worsened patients discontinued DMTs without consulting a physician, emphasizing potential challenges in treatment adherence. After treatment discontinuation, RAD patients experienced relapses after a median of 21.0 months. Survival analysis suggested a more favorable disease course for patients who discontinued treatment after achieving a stable period (p = 0.237), with evidence of differentiation between groups after four years. Regression analysis indicated that older age at discontinuation had a favorable impact on relapse probability (HR: 0.904; p = 0.031; 95 % CI: 0.825, 0.991). Reasons for discontinuation unrelated to disease stability showed a positive but imprecise effect on relapse probability. ConclusionThis study provides insights into the outcomes of MS patients discontinuing injectable DMTs, emphasizing the importance of age at discontinuation and reasons for treatment cessation in predicting disease progression. The findings suggest that discontinuation after achieving stability may lead to more favorable outcomes, highlighting the need for personalized treatment decisions in MS management. Further research is warranted to validate these findings and inform clinical practices.

Rock mass classification in slope engineering with special emphasis on Slope mass rating: Current status and future projections

Rock mass classification (RMC) systems in the realm of rock slope engineering have gathered a lot of attention. The present review article delves into the major RMC systems, elucidating their fundamental principles, key parameters and practical applications. Among the various RMC systems for rock slope designing, Romana's Slope mass rating (SMR) was found to be the most comprehensive; therefore, the focus of the discussion centres around the SMR method. The article provides a crisp overview of the major advancements, evolution and potential challenges of SMR. The radical concept of wedge failure in SMR and the use of continuous functions are discussed in detail. A thorough discussion is provided on the efforts made by different researchers, encompassing the inclusion of novel factors such as slope height, heterogeneity in rock mass or lithology, weighted consideration of existing discontinuities, fuzzy sets and overburden thickness. Various automated calculation techniques and empirical correlations of SMR with other classification systems and rock engineering parameters are also outlined. Moreover, a critical examination of the variations among major extensions of SMR and their geotechnical relevance have also been discussed. Based on a meticulous assessment of the susceptibility to toppling failure in SMR, two sub‐factors to include block shape and interlayer slip between discontinuities have been suggested. These sub‐factors were validated by Goodman's tests for toppling failure. The scope of future projections or possible aspects for revisiting and refinement of the SMR method are suggested to enhance the applicability of the method under a diverse initial set of geotechnical conditions.

Emojis And Miscommunication in Text-Based Interactions Among Nigerian Youths

This paper explores the dynamic role of emojis in text-based communication among Nigerian youths and the potential implications for miscommunication. Emojis have become integral to contemporary digital conversations, offering users a visual means of expressing emotions, tone, and context within the constraints of text-based interactions. In the context of Nigeria, a country with a diverse linguistic landscape and a youthful population heavily engaged in online communication, understanding the impact of emojis on interpersonal exchanges becomes particularly pertinent. This paper examines the prevalence and patterns of emoji usage among Nigerian youths across various digital platforms. It investigates the cultural nuances and interpretations associated with emojis within the Nigerian context, considering factors such as regional differences, linguistic diversity, and socio-cultural influences. Furthermore, the study examines instances where emojis may contribute to miscommunication or misunderstanding, potentially exacerbating conflicts or hindering effective communication. Through a comprehensive review of existing literature, online discourse analysis, and case studies, this research aims to shed light on the ways in which emojis influence the interpretation of textual messages and the potential challenges they pose to clear and accurate communication. The study concludes that as digital communication continues to be a primary mode of interaction, it is essential for users to recognize the potential for misinterpretation, prompting the need for increased emoji literacy and awareness.

Skin and Syntax: Large Language Models in Dermatopathology.

This literature review introduces the integration of Large Language Models (LLMs) in the field of dermatopathology, outlining their potential benefits, challenges, and prospects. It discusses the changing landscape of dermatopathology with the emergence of LLMs. The potential advantages of LLMs include a streamlined generation of pathology reports, the ability to learn and provide up-to-date information, and simplified patient education. Existing instances of LLMs encompass diagnostic support, research acceleration, and trainee education. Challenges involve biases, data privacy and quality, and establishing a balance between AI and dermatopathological expertise. Prospects include the integration of LLMs with other AI technologies to improve diagnostics and the improvement of multimodal LLMs that can handle both text and image input. Our implementation guidelines highlight the importance of model transparency and interpretability, data quality, and continuous oversight. The transformative potential of LLMs in dermatopathology is underscored, with an emphasis on a dynamic collaboration between artificial intelligence (AI) experts (technical specialists) and dermatopathologists (clinicians) for improved patient outcomes.

A theoretical case study of the generalization of machine-learned potentials

Machine-learned interatomic potentials (MLIPs) are typically trained on datasets that encompass a restricted subset of possible input structures, which presents a potential challenge for their generalization to a broader range of systems outside the training set. Nevertheless, MLIPs have demonstrated impressive accuracy in predicting forces and energies in simulations involving intricate and complex structures. In this paper we aim to take steps towards rigorously explaining the excellent observed generalization properties of MLIPs. Specifically, we offer a comprehensive theoretical and numerical investigation of the generalization of MLIPs in the context of dislocation simulations. We quantify precisely how the accuracy of such simulations is directly determined by a few key factors: the size of the training structures, the choice of training observations (e.g., energies, forces, virials), and the level of accuracy achieved in the fitting process. Notably, our study reveals the crucial role of fitting virials in ensuring the consistency of MLIPs for dislocation simulations. Our series of careful numerical experiments encompassing screw, edge, and mixed dislocations, supports existing best practices in the MLIPs literature but also provides new insights into the design of data sets and loss functions.