bluuebunny/crossref_metadata_2025 huggingface dataset:
Effective Continuous Quantitative Measures for End-to-End AI Guardrails
Authors: Pittman Jason
Published: December 2024

Large Language Models such as ChatGPT have brought cutting-edge AI systems into the cultural zeitgeist. As a result, AI is no longer an isolated fief of academia or forward-leaning businesses. There are more than 35 million visits to open-source models in public repositories monthly. Clearly, the general technology community has caught onto the power of such systems and is keen to harness the promise of efficiency, productivity, and enhanced capability. Concurrent to this uptrend, AI systems are understood to be potentially vulnerable to various ethical issues. Such issues range from bias and fairness, to explainability and trustworthiness. More than mere theory, such vulnerabilities have manifested in mainstream settings such as politics, medicine, and law. The ethical implementation and operation of AI systems is, therefore, of critical interest as the democratization of such systems gains accelerates. However, there is an ongoing challenge insofar as there is little consensus on what constitutes quantitative ethical and responsible AI guardrails. This leaves AI practitioners without sufficient guidance to implement systems reasonably free from societal level harm. Accordingly, this work presents a structured taxonomy and concept matrix consisting of 39 discrete guardrails arrayed across a three-phased AI system lifecycle. Measure families further organize measures in terms such as bias mitigation, adversarial robustness, and anomaly monitoring. Then, I provide specific quantitative metrics for each measure construct. The intended takeaway is for AI practitioners to have the means to select appropriate and effective metrics for assuring ethical and responsible guardrails.
Artificial Intelligence Life Cycle: The Detection and Mitigation of Bias
Authors: Aninze Ashionye
Published: December 2024

The rapid expansion of Artificial Intelligence(AI) has outpaced the development of ethical guidelines and regulations, raising concerns about the potential for bias in AI systems. These biases in AI can manifest in real-world applications leading to unfair or discriminatory outcomes in areas like job hiring, loan approvals or criminal justice predictions. For example, a biased AI model used for loan prediction may deny loans to qualified applicants based on demographic factors such as race or gender. This paper investigates the presence and mitigation of bias in Machine Learning(ML) models trained on the Adult Census Income dataset, known to have limitations in gender and race. Through comprehensive data analysis, focusing on sensitive attributes like gender, race and relationship status, this research sheds light on complex relationships between societal biases and algorithmic outcomes and how societal biases can be rooted and amplified by ML algorithms. Utilising fairness metrics like demographic parity(DP) and equalised odds(EO), this paper quantifies the impact of bias on model predictions. The results demonstrated that biased datasets often lead to biased models even after applying pre-processing techniques. The effectiveness of mitigation techniques such as reweighting(Exponential Gradient(EG)) to reduce disparities was examined, resulting in a measurable reduction in bias disparities. However, these improvements came with trade-offs in accuracy and sometimes in other fairness metrics, identified the complex nature of bias mitigation and the need for precise consideration of ethical implications. The findings of this research highlight the critical importance of addressing bias at all stages of the AI life cycle, from data collection to model deployment. The limitation of this research, especially the use of EG, demonstrates the need for further development of bias mitigation techniques that can address complex relationships while maintaining accuracy. This paper concludes with recommendations for best practices in Artificial Intelligence development, emphasising the need for ongoing research and collaboration to mitigate bias by prioritising ethical considerations, transparency, explainability, and accountability to ensure fairness in AI systems.
AI, Personalized Education, and Challenges
Authors: Mimoudi Aziz
Published: December 2024

Artificial Intelligence (AI) is gaining traction in education, with potential applications that range from personalized learning to automated administrative tasks. However, the integration of AI into educational systems is not without its challenges. This paper explores both the opportunities and obstacles that AI presents in the field of education, particularly through the use of Intelligent Tutoring Systems (ITS) and Adaptive Learning Management Systems (ALMS). These technologies aim to tailor learning experiences to individual students by analyzing data and adjusting content to suit their needs. While this personalized approach could enhance student engagement and comprehension, it relies on vast amounts of data, raising concerns about privacy and the potential misuse of personal information. Moreover, AI’s impact on education extends to supporting educators by providing insights into student performance and automating routine tasks. However, the effectiveness of AI systems in this regard remains questionable, particularly when considering the limitations in current AI models and the challenges of integrating them into existing educational frameworks. The risk of algorithmic bias is also a critical issue, as AI systems can inadvertently reinforce inequalities present in the data they are trained on, leading to unfair or discriminatory outcomes. Additionally, while AI promises to streamline certain aspects of education, there are concerns that over-reliance on technology could depersonalize the learning process. Human educators play a crucial role in fostering not only intellectual growth but also emotional and social development—elements that AI systems are currently unable to replicate. This paper argues that while AI holds significant promise in education, its deployment must be carefully managed, with attention to ethical considerations, equity in access, and the preservation of the human elements essential to effective learning. Addressing these challenges is key to ensuring that AI contributes meaningfully to education rather than exacerbating existing issues.
Balancing AI in SMEs: Overcoming Psychological Barriers and Preserving Critical Thinking
Authors: Block Madeleine
Published: December 2024

The rapid integration of artificial intelligence (AI) into various business sectors is transforming the operational landscape. This paper focuses on small and medium-sized enterprises (SMEs) and examines how they can achieve an optimal psychological balance when using AI. The goal is to encourage employees to adopt AI while maintaining critical thinking and autonomy. This research paper uses theoretical analysis as the research method, drawing on established psychological theories such as the Technology Acceptance Model and the Job Demands-Resources Model. The findings are used to propose a model for determining an optimal balance for SMEs. The analysis reveals several psychological barriers related to anxiety, which can lead to increased stress, lower motivation, and general resistance to the use of AI tools. Conversely, once the fear is overcome, there is a risk of over-reliance on AI. Therefore, it is important to provide training that helps employees recognize the benefits of AI and its impact on their tasks, critically evaluate AI recommendations, and find a balance between automated guidance with human judgement. Finding the optimal balance in the use of AI is critical. Fostering a culture of continuous learning, and adaptability, together with supportive leadership, can help maintain this balance. In summary, through a strategic application of psychological theories, SMEs can harness the potential of AI to improve work performance and mitigate labour shortages while developing motivated and critically thinking employees.
An Analysis of Knowledge Management Changes Through Artificial Intelligence with Probst's Model
Authors: Toptas Burak
Published: December 2024

In recent years, the integration of Artificial Intelligence (AI) into Knowledge Management (KM) has led to transformational changes. These changes have significantly enhanced traditional KM processes. To identify how AI technologies improve and reshape knowledge processes, this study conducted a systematic literature review. The review identified AI technologies suitable for each of Probst's building blocks, which outline the eight central KM processes. The research reveals a wide range of AI technologies, including machine learning, natural language processing and chatbots such as ChatGPT. These technologies can be applied in different domains and introduce innovative approaches to improve KM processes. Based on the AI technologies analysed, this study proposes a four-stage model to support the documentation and application of best practices and lessons learned. The model is designed to enhance the knowledge development process and aims to document and secure key project developments in the long term. A further objective was to analyse which KM process is most affected by chatbots. The findings indicate that chatbots have the potential to transform the use of knowledge in organisations. They act as facilitators by breaking down existing barriers, foster an open culture of knowledge sharing, streamline workflows and increase the accessibility of knowledge. The study also examines the broader changes that AI will bring to KM and forecasts the sixth generation of KM. It draws on Bencsik's (2021) evolutionary and revolutionary perspectives that specifically forecast this next generation. The study shows that AI not only enhances existing KM processes but also has the potential to fundamentally disrupt traditional methods and approaches. These findings underline the need for future research to explore the effective integration and scalability of AI technologies in real-world KM environments. This will help ensure that their long term impact and potential benefits are fully understood across different industries and organisational contexts.
Transcending Fixed Meanings: Exploring the Impact of Linguistic Relativism on Adaptive Language Models in Generative AI
Authors: Namburi Subhangi
Published: December 2024

This research paper aims to start a discourse exploring the impact of linguistic relativism on adaptive language models within the field of generative AI, challenging the traditional fixed-meaning approach to natural language processing (NLP). It argues for a shift towards more personalised AI systems that can adapt to individual users' language nuances, rather than relying solely on large datasets with predetermined meanings. The current NLP models, based on conventional semantics, assume that language has a stable, objective reality where words have universally accepted meanings. This approach limits AI's ability to understand and generate language that reflects personal or contextual variations. The paper debates that generative AI should move towards a model that embraces the fluidity and subjectivity of language, where meanings are not fixed but can change depending on the speaker's intent or the situational context. This would involve incorporating user-specific data and situational awareness into AI systems, enabling them to interpret not just the literal meanings of words but also the speaker's intentions and the circumstantial cues that may alter these meanings. Such an approach would lead to the development of AI systems that are more adaptive and sensitive to the nuances of personal expression and contextual interpretation. However, the paper also acknowledges the potential ethical challenges associated with this approach. If AI systems are designed to allow for fluid and personalized meanings, they could be manipulated to shape public discourse in ways that reflect the biases or intentions of their developers. This raises concerns about the potential misuse of AI in influencing perceptions and realities, particularly when the fluidity of language is taken to an extreme where communication becomes chaotic and ineffective. Ultimately, suggesting personalised language models offer significant potential for enhancing AI's ability to understand and generate human-like language, there is a need for a balance between individual linguistic creativity and the communal aspects of language that ensure effective communication. The paper concludes that integrating linguistic relativism into AI models could advance the theoretical understanding of language in AI, but it must be approached with caution to avoid undermining the stability and clarity essential for meaningful human interaction.
Artificial Intelligence and Trend Forecasting in the Fashion Industry: Ethical and Anticipated Ethical Issues
Authors: Wilson Richard , Bowles Olivia
Published: December 2024

Trend forecasting within the fashion industry is aimed at predicting the of future popular styles, materials, colors, and all things related to the development of fashion. Trend forecasting is based on information collected about past, present, and projected future developments in the fashion world. AI, as it has been applied in other areas in society, is now being applied within the fashion industry. This analysis will focus on AI being applied to trend forecasting within the fashion industry. Using AI in trend forecasting brings a number of advantages for those in the fashion industry while at the same time raising a number of ethical concerns. Three significant ethical concerns that are related to the employment of AI in the fashion industry are, the invasion of privacy from the data mining required to gather data to make predictions about fashion trends, the consequences for businesses of incorrect trend predictions, and the anticipated environmentally unsustainable nature of fast fashion due to the overconsumption that consumers practice and that is increasingly promoted by AI. Overconsumption is the product of how AI is involved in rapidly forecasting new trends in fashion that consumers then follow. Addressing all of these ethical issues is needed because fast fashion has continued to be demanded by both consumers and investors. New technologies, particularly AI, have allowed fashion brands to develop methods that allow them to be ahead of rapidly changing fashion trends and put high-demand products in stores faster, increasing the prevalence of fast fashion within the fashion industry. Questions now arise about how to address these ethical concerns. Important questions for the fashion industry include what issues will the use of AI in trend forecasting create in the long run within the fashion industry, and how can proactive action be taken within the fashion industry to prevent future ethical issues in the fashion industry? This paper which employs empirical methods to describe the fashion industry while also employing conceptual analysis related to philosophical ethics. The goal of the analysis is to provide, an informative ethical analysis of AI in trend forecasting, while also attempting to develop ethical guidance for concerns involving the use of AI in trend forecasting. The paper perform an anticipatory ethical analysis that attempts to address future concerns about fashion and will close by drawing conclusions about the direction of future analysis related to the application of AI in the fashion industry.
Can Robots Laugh? An Inquiry in the Nature of AI
Authors: Tomé Eduardo , Gromova Elizaveta
Published: December 2024

In this paper we discuss the possibility of robots having a mind and being able to act like human beings and even surpass the human intelligence, and in consequence taking over the world. It is possibility that has been put forward in human history long ago, and that has been accentuated with the new advances in technology from the last few years, of which Chat GPT is the last very well-known example. We base ourselves in a literature review made on eight basic features we define as characteristic of humans, namely: Reproduction, Creation, Belonging, Citizenship, Self-Awareness, Mortality, Rationality, Humour, Feelings and Emotions. We use a plurality of databases as Google and SCOPUS. As a result, we conclude that even if robots may express themselves as humans, and may beat humans in specific activities, they lack most of the features that define human beings and most probably they will ever do. As with time and space travelling, robots that would take power on Earth are a utopia that will probably never happen, but whose pursue will be beneficial  for the human race. The paper has the limitation of being only theoretical, and the originality of being based on Philosophy of Artificial Intelligence and presented in a scientific environment.
AI Generative in Brazil’s Public Schools: The Teachers’ Perspective
Authors: Jussara Reis-Andersson
Published: December 2024

Artificial Intelligence (AI) alters the societal landscape and transforms people's lives. In the realm of education, AI offers many opportunities and challenges in teaching and learning. While AI holds promise in enriching learning experiences and fostering motivation, its successful integration into educational practice necessitates that both students and teachers possess digital competence. Education plays a critical role in preparing future workforces. In South America, Brazil stands as the most populous country, with 212.6 million people. The utilisation of AI generative tools, such as ChatGPT, for teaching purposes in the country, is on the rise, albeit constrained within the educational context. Challenges faced in integrating AI generative tools in Brazil’s education system include the facilitation of plagiarism and teachers’ insufficient digital competence. In an effort to delve into the intricacies of teachers’ experiences and challenges regarding the integration of AI generative tools into their pedagogical practice, a qualitative study was conducted, and nine teachers in an upper secondary school in Brazil answered a questionnaire involving seven open questions. The teachers perceive the integration of AI generative tools into teaching practice as an instrument that enhances opportunities for improving the quality of teaching, stimulating student interest, and enriching the dynamism of the content learning process. Teachers have highlighted ChatGPT as a valuable tool for research and consultation. This tool can simplify teaching tasks and is typically well-received by students. Both teachers and students can utilise this tool to generate materials such as lyrics and textual variations and even produce fully composed songs ready for listening. ChatGPT is also used to prepare and correct assessments, ensuring consistency in evaluation. Teachers use AI to prepare texts, quizzes, and multiple-choice tests. AI-generated images are also used to enhance illustrations, making learning materials more engaging and visually appealing. Although AI simplifies complex subjects and makes the learning process more engaging, it is essential to provide adequate training on AI tools to enhance student involvement and educational results.
Artificial intelligence and the ethics of tomorrow
Authors: VAN WYK Brenda , Holmner Marlene
Published: December 2024

Traversing our digital information society safely and responsibly rests mainly on our comprehension of the vast sociotechnical nature of AI ethics risks, its implications and consequences. Ultimately, we all would prefer to live in a mature information society that is technologically just, inclusive and sophisticated, firmly rooted in ethical information philosophy and values. In this paper the findings of a scoping review of recent reported research look, in particular, at the sociotechnical changes and impact that disruptive AI innovation has on societies, and how this could impact new and futuristic nuances in AI ethics. The study delves into the interdisciplinarity of AI ethics.  The role of intergovernmental collaboration in researching and availing  frameworks and  guardrails in upholding AI ethics is critically interrogated and explored. The study alludes to gaps in current research around AI ethics and impresses the need to deliberate on future AI ethics dimensions. The prerequisites for fostering further confidence and trust in AI technology are synthesised. The study concluded that inclusivity and justice in AI Ethics is not yet achieved on a global level, and that there is still a tendency towards cultural and other biases in designing, planning, implementing and also regulating AI. More research is needed on the impact and trends of AI innovation in the Global South compared to the Global North.
Comparing human-labeled and AI-labeled speech datasets for TTS
Authors: Wirth Johannes , Peinl René
Published: December 2024

As the output quality of neural networks in the fields of automatic speech recognition (ASR) and text-to-speech (TTS) continues to improve, new opportunities are becoming available to train models in a weakly supervised fashion, thus minimizing the manual effort required to annotate new audio data for supervised training. While weak supervision has recently shown very promising results in the domain of ASR, speech synthesis has not yet been thoroughly investigated regarding this technique despite requiring the equivalent training dataset structure of aligned audio-transcript pairs. In this work, we compare the performance of TTS models trained using a well-curated and manually labeled training dataset to others trained on the same audio data with text labels generated using both grapheme- and phoneme-based ASR models. Phoneme-based approaches seem especially promising, since even for wrongly predicted phonemes, the resulting word is more likely to sound similar to the originally spoken word than for grapheme-based predictions. For evaluation and ranking, we generate synthesized audio outputs from all previously trained models using input texts sourced from a selection of speech recognition datasets covering a wide range of application domains. These synthesized outputs are subsequently fed into multiple state-of-the-art ASR models with their output text predictions being compared to the initial TTS model input texts. This comparison enables an objective assessment of the intelligibility of the audio outputs from all TTS models, by utilizing metrics like word error rate and character error rate. Our results not only show that models trained on data generated with weak supervision achieve comparable quality to models trained on manually labeled datasets, but can outperform the latter, even for small, well-curated speech datasets. These findings suggest that the future creation of labeled datasets for supervised training of TTS models may not require any manual annotation but can be fully automated.
Dilbilimsel Tefsirle İlgili Akademik Çalışmalara Bir Bakış
Authors: Karaca Abdullah
Published: December 2024

Dilbilimsel tefsir ekolü/yöntemi tefsir literatürünün en önemli alanlarından biridir. Dilbilimsel tefsir etrafında klasik dönemde gelişen zengin bir literatür bulunmaktadır. Çağdaş dönemde de dilbilimsel tefsir çalışmaları canlılık kazanmış, pek çok akademik araştırmayla zengin bir literatür oluşmuştur. Dilbilimsel tefsir hakkındaki akademik araştırmalara dair yazılı bir çalışma yapılmamıştır. Bu makalede dilbilimsel tefsir hakkındaki akademik araştırmalar bütüncül bir okumaya tabi tutulmuştur. Çalışmada öncelikle ekolün ve yöntemin tarihi gelişimiyle ilgili bir özet sunulmuştur. Akabinde dilbilimsel tefsir kapsamındaki akademik çalışmalar gözden geçirilmiştir. Dilbilimsel tefsir literatürüne yönelik araştırmalar ve çalışma alanları yirmi başlık/tür içerisinde değerlendirilmiştir. Başlığın sonunda dilbilimsel tefsir araştırmalarında henüz yeterince çalışılmamış bakir alanlara işaret edilmiştir. Son olarak tefsirlerdeki dilbilimsel uygulamaların analizinde izlenen yöntemler hakkında bilgi verilmiştir. Neticede dilbilimsel tefsir alanında git gide gelişmekte olan ciddi bir birikim görülmektedir. Bununla birlikte araştırmalarda halen eksiklerin bulunduğu da bir gerçektir.
Green Finance: Reduce, Reuse & Recycle Strategy for the Environment
Authors: Akhila K H , Nedumaran G
Published: December 2024

Green finance has emerged as a pivotal strategy in addressing environmental challenges and promoting sustainability in the banking sector. This study explores the role of green financial forecasting with a focus on the ‘Reduce, Reuse, and Recycle’ (RRR) strategy, specifically emphasizing the Reduce component. Utilizing a correlation matrix and regression analysis, the research examines the relationship between green banking initiatives and key variables like the use of ATMs and checking balances, to assess the impact of reducing environmental footprints on financial outcomes. Findings reveal a strong positive correlation between green banking practices and financial sustainability, highlighting the importance of integrating eco-friendly strategies within banking operations. Additionally, the study introduces the FAIR Model—a comprehensive framework for implementing sustainable banking practices—demonstrating its applicability in fostering green banking in India. The paper also outlines avenues for further development of green banks in India, emphasizing the need for innovation in infrastructure, energy efficiency, and the role of green financial products. The insights drawn from this research provide valuable guidance for policymakers, financial institutions, and investors aiming to align financial strategies with environmental sustainability.
Resistance to Oppression in The Book of Negroes by Lawrence Hill
Authors: Udhayakumar S.
Published: December 2024

This article explores Lawrence Hill’s historical fiction, The Book of Negroes, a retelling of the brutality of slavery. This fictional slave narrative captures the voice of a slave girl, yearning for freedom and identity. Hill portrays the experiences of slavery, freedom, and her struggle and fight against oppressive forces by narrating her journey from being a slave to becoming an empowered woman who spoke for her people. The novel highlights that her education helped her significantly combat all the oppressions she faced. Furthermore, book captures the physical, sexual, emotional, religious, and economic violations that led to her enslavement. Notably, the metanarrative in the novel explicates the components of resistance literature, leaving space for a critical interpretation of the text and deep understanding of the counter narratives against the imperial forces and abolitionists. As a result, the study categorizes the novel primarily as a resistance narrative, as encapsulated by Barbara Harlow in her seminal work, Resistance Literature.
DESCRIPTION OF MOTHER'S KNOWLEDGE ABOUT STIMULATION IN CHILDREN AGED 3-6 YEARS WHO ARE GIVEN BRAIN GYM AT HARAPAN BANGSA PLAYGROUPS AND MASYITHOH KAUMAN KINDERGARTEN BANTUL
Authors: Ariyani Antika Indah , Ayuningrum Lia Dian , Pangastuti Restu
Published: December 2024

Stimulation can excite brain cells and is crucial for enhancing a child's sensory, emotional, social, linguistic, cognitive, independent, and creative abilities. For the proper development of their behavioral and mental health, children must also receive enough stimulation from an early age, in both quantity and quality. Youngsters who grow up with lots of encouragement will mature more quickly than those who don't. Parents can stimulate their child's growth in a fun way, such as by participating in brain gym. This study was to find out the description of mothers' knowledge about stimulation for children aged 3rd-6th years who were given brain gym. This type of research is quantitative cross sectional with the sample at Harapan Bangsa playgropus and Masyithoh Kauman Kindergarten was 106 mother of students. It was known that the age of the majority of respondents was between 25th–35th,most of their was senior high school, income was minimum wage, most of respondents cared for themselves and time spent with children per day was > 12hours. The majority of respondents had good knowledge. This study suggests that parents—particularly mothers—should provide their children more stimulation through Brain Gym in order to enhance their development.
Метод снижения помехового воздействия базовых станций IMT на космические аппараты на основе применения масок математического ожидания ЭИИМ
Authors: А.С. Пастух
Published: December 2024

В статье рассмотрен метод снижения помехового воздействия от базовых станций (БС) IMT на приемники спутниковых служб, основанный на использовании маски математического ожидания эквивалентной изотропно-излучаемой мощности (ЭИИМ) в верхней полусфере. Для иллюстрации эффективности данного метода проведена оценка применения масок математического ожидания ЭИИМ в диапазоне 6425–7125 МГц при совместной эксплуатации с космическими станциями, работающими в рамках фиксированной спутниковой службы (ФСС).

The article examines a method to reduce interference from IMT base stations (BS) on satellite service receivers based on the application of the expected equivalent isotropic radiated power (EIRP) mask in the upper hemisphere. To demonstrate the effectiveness of this method, an assessment of the application of expected EIRP masks in the 6425–7125 MHz band was conducted, considering its shared use space stations operating within Fixed Satellite Service (FSS).
PRIMARY SJÖGREN'S SYNDROME AND THE RISK FOR DEVELOPING LYMPHOMAS
Authors: Panchovska М
Published: December 2024

Първичният синдром на Sjӧgren бележи в своя ход повишен риск относно развитие на лимфоми. Съпоставен с риска спрямо здравата популация ,този риск може да достигне 44 пъти по-висока честота. В хода на относително спокойно протичане на болестта, може да настъпи „пречупване“ в клиничната картина и разгръщане проявите на малигнен лимфом. Налични са обачеа с различни давност  клинични и лабораторни отклонения, които със сумирането си във времето скъсяват пътя към малигнената лимфопролиферация. Обособяването на групи пациенти с повишен риск относно развитие на лимфом и проследяването им е в основата на персонализирания подход при болните от синдром на  Sjӧgren.
Geoinformation modeling of population density dynamics in the Stavropol Krai
Authors: Katorgin Igor , Turun Pavel , Roman Alexander , Yurin Dmitry
Published: December 2024

The article is dedicated to the issues of geoinformation modeling of population density dynamics at the regional level, as well as the territorial features of the distribution and changes in the population of the Stavropol Krai for the period from 1959 to 2020. To model the population density of the constituent entity based on data from the All-Union and All-Russian censuses, a method was chosen to create digital models using algorithms for estimating kernel density. MapInfo geographic information software with the Vertical Mapper and Global Mapper modules, which have the necessary functionality for modeling and analysis spatial data, were chosen as tools for spatial analysis and mapping of population density. The author’s methodology for creating population density maps is proposed, which makes it possible to take into account the entire area and configuration of a settlement when performing modeling and, accordingly, more accurately display the settlement framework. Using modeling technologies and spatial analysis we identified regional features of population density dynamics in the Stavropol Krai for the last six census periods in particular, as well as for the 60-year period 1959–2020, in general. The presented methodology for creating maps of changes in population density in a region allows us to reflect with a high degree of reliability the ongoing changes in the evolution of settlement. The created models can be useful for studying settlement and demographic processes in the territory of the Stavropol Krai; they allow drawing conclusions and predicting the directions of development of certain parts of the region; they can also be useful in carrying out territorial planning and making management decisions within the framework of regional policy.
ПЕДАГОГІЧНІ УМОВИ ПРОФІЛАКТИКИ ІНФОРМАЦІЙНОГО НАСИЛЬСТВА В ОСВІТНЬОМУ СЕРЕДОВИЩІ ПЕДАГОГІЧНИХ ЗАКЛАДІВ ВИЩОЇ ОСВІТИ
Authors: Акімов Вадим
Published: December 2024

The article presents the results of theoretical substantiation of the pedagogical conditions for the prevention of information violence in the educational environment of pedagogical higher education institutions. It is emphasized that the integration of information and communication technologies into the educational process of pedagogical higher education institutions, although creating new methodological and didactic opportunities for the professional development of future specialists, at the same time creates new risks associated with manifestations of information violence.
The purpose of the article is to identify and substantiate the pedagogical conditions for the prevention of information violence in the educational environment of pedagogical higher education institutions.
The results of a comprehensive analysis of scientific literature have shown that there is a lack of research in this area and have determined the need to develop innovative strategies for preventing information violence in the educational environment of a pedagogical higher education institution.
The author outlines three key interrelated pedagogical conditions for the prevention of information violence, which are based on the diagnosis of the educational environment, theoretical and practical training of higher education students and coordination of efforts of all structural units of a higher education institution. It is advisable to implement the proposed pedagogical conditions in a sequential chronology, which will ensure the comprehensiveness of preventive measures.
Prevention of information violence in the educational environment requires a comprehensive approach that includes both the development of competencies in countering infections in students and the creation of appropriate pedagogical conditions. The traditional organisation of the educational process, focused on the object and environment of learning, should be adapted to achieve these goals.
It is emphasized that the implementation of the proposed author's pedagogical conditions for the prevention of information violence in the educational environment of a pedagogical institution of higher education will create a safe educational space of the university, form future teachers' competencies in countering information violence and ensure effective prevention of this phenomenon.
El condicional en la interlengua de estudiantes italófonos de ELE
Authors: Longobardi Sara
Published: December 2024

En este artículo se analizan las dificultades de aprendizaje más comunes en la producción escrita de estudiantes italianos de ELE, en los niveles C1 y B2, en relación con el uso del condicional simple. El estudio se basa en un corpus de 184 ejercicios de traducción pedagógica creados con base en los principios del Análisis Contrastivo (AC). A través del uso tanto del condicional de conjetura como del condicional con valor de futuro en el pasado se revelan los errores más difundidos detectados en la interlengua en los casos de discentes de ELE que nacieron en Italia. Dichas faltas se explican en relación con los diferentes valores del condicional simple en italiano y en español debido a su diferente evolución diacrónica. Los resultados del análisis que se ha realizado en este trabajo ponen de relieve la importancia de aplicar un enfoque didáctico que fomente la reflexión metalingüística y contrastiva en el aula de ELE con particular atención a estudiantes de lenguas afines, que quieren mejorar sus destrezas lingüísticas (tanto expresión oral como escrita) y alcanzar un nivel alto de español.
PREVALENCE OF WPW SYNDROME AMONG ALL SUPRA VENTRICULAR TACHYCARDIA PATIENTS IN A TERTIARY CARE HOSPITAL IN RAJASTHAN
Authors: Goyal Aditya , Mashru Parth , Sharma Rajeev , Sethiya Bhartesh , Jain Akash
Published: December 2024

A frequent reason for hospital admissions, supraventricular tachycardia (SVT) can result in severe discomfort and distress for patients.
Atrioventricular nodal re-entrant tachycardia, atrioventricular re-entrant tachycardia, and atrial tachycardia are the three most prevalent SVT.
Electrocardiography during tachycardia can often be used to determine the underlying mechanism by comparing it with sinus rhythm and
evaluating the onset and offset of tachycardia. Re-entrant tachycardias involving the atrioventricular node, such as atrioventricular nodal re-entrant
tachycardia and atrioventricular re-entrant tachycardia, are extremely responsive to vagal manoeuvres and adenosine administration for
termination. Due to a pre-existing or rate-related bundle branch block, any SVT may manifest as a broad complex tachycardia. VT should always
be regarded as a differential diagnosis of broad complex tachycardia due to the potential for diagnostic uncertainty. As many patients go
undiagnosed and suffer from recurrent tachycardia which leads to morbidity and mental distress, patients with SVT should be referred to an
electrophysiologist for electrophysiological study and Radiofrequency ablation as definitive treatment. This study was done to look for the
prevalence of WPWamong all patients with SVTwho presented to tertiary care centre of Rajasthan
A COMPARATIVE STUDY OF BASKA MASK WITH AMBU AURAGAIN IN ADULT PATIENTS UNDERGOING SURGERY UNDER GENERAL ANAESTHESIA
Authors: Zafer Zeeshan , Srivastava Anurag , Bhamri Prem Kumari , Sharma Neha , Gupta Prakriti
Published: December 2024

Introduction- Supraglottic airway devices (SGAD) provide a viable alternative to endotracheal intubation for airway management. Our study
aimed to compare the clinical performance of Baska mask (B), a novel SGAD and Ambu Auragain (A), an anatomically curved second generation
SGAD in patients undergoing general anaesthesia (GA). To compare oropharyngeal leak pressure (OLP), Objectives- time for insertion, number
of attempts, ease of insertion, bronchoscopic view of glottis (Brimacombe score) & complications between the two devices. Material and
Methods- Total of 60 patients of age ranges between 18 and 60 years of either sex, ASA Grade 1 and 2, receiving general anaesthesia were
randomly allocated to either group A (n=30) group B (n=30). Following induction of anaesthesia, respective SGAD was inserted and
oropharyngeal leak pressure (OLP), time for insertion, number of attempts, ease of insertion, bronchoscopic view of glottis (Brimacombe score) &
complications were noted. Data collected was tabulated and analysed using appropriate statistical tests. The demographic parameters in Resultsthe two groups were comparable. OLP was significantly higher in group B(25.67±2.23 cm of H2O) as compared to group A(20.03±1.92 cm of
H2O) with P<0.001.Time for insertion (15.90±4.24 seconds versus 22.40±5.91 seconds) was significantly lower for group B. Baska mask had
significantly better ease of insertion than Auragain, (p=0.046). With higher Brimacombe score (3.57±0.5 versus 3.13±0.87, p=0.03), group B
provided a better fibreoptic view of the glottis. No patients in either group required a second insertion attempt or faced device failure. Rate of
complications was comparable between the two devices. With higher OLP, better fibreoptic glottic view Conclusion- , less time of insertion and
better ease of insertion, Baska mask is a better alternative to Ambu auragain in patients undergoing general anaesthesia.
A PROSPECTIVE STUDY COMPARING FUNCTIONAL AND RADIOLOGICAL OUTCOMES OF CLOSED REDUCTION EXTERNAL FIXATION VERSUS OPEN REDUCTION INTERNAL FIXATION IN INTRA-ARTICULAR DISTAL RADIUS FRACTURES
Authors: Sharda Parth Narayan , V. Yadkikar Shriniwas , Choudhary M. S. , Verma Gaurav , Parwez Danish
Published: December 2024

Aim: To compare the outcomes of closed reduction and external fixation using the JESS fixator versus open reduction and internal fixation(ORIF)
using the LCP for intra-articular distal end radius fractures. This prospective study was conducted Material And Methods: at JNU Hospital and
included 40 patients aged 18 to 65 years with distal end radius (DER) fractures. The patients were randomly assigned to two groups of 20 each, and
their functional and radiological outcomes were assessed. The average follow-up period was one year Results: . The range of motion and functional
outcomes were evaluated using the modified Gartland and Werley scoring system. In the JESS group, 10%of patients had excellent results, 45%had
good results, 40%had fair results, and 5%had poor results. In the volar LCP group, 10%had excellent results, 75%had good results, 10%had fair
results, and 5% had poor results. According to the Stewart scoring system, the JESS group had 10%excellent, 45%good, 40%fair, and 5%poor
results, while the LCP group had 10%excellent, 75%good, 10%fair, and 5%poor results. The average tim Conclusions: e to union was 5.15 months
in the LCP group and 3.40 months in the JESS group. Functional and anatomical evaluations indicated that volar LCP fixation provided better
outcomes compared to JESS fixation. Better functional results are expected in the early post-operative period with open reduction and internal
fixation. However, in the long term, the results are comparable to those of JESS fixation.
MIRROR'S HIDDEN DEPTHS- LAPAROSCOPIC CHOLECYSTECTOMY IN SITUS INVERSUS TOTALIS
Authors: Santharaj Swathi , Noorul Hassan Mir MD
Published: December 2024

Situs inversus totalis is a rare congenital abnormality characterised by a mirror-image transposition of both abdominal and thoracic organs. This
anatomical disposition of organs not only influences the localisation of symptoms and signs arising from a diseased organ but also imposes special
demands on the diagnostic and surgical skills of the surgeon. We present a case of a 28-year-old female patient diagnosed as chronic calculous
cholecystitis with situs inversus totalis. Elective laparoscopic cholecystectomy was performed safely, and the patient was discharged on
postoperative day two with no significant postoperative complications.
NON-INVASIVE ASSESSMENT OF IRON OVERLOAD IN Β-THALASSEMIA PATIENTS: CORRELATING PERLS' PRUSSIAN BLUE STAINING IN BUCCAL CELLS WITH SERUM FERRITIN LEVELS
Authors: Kriplani Yogita , Koshti Ashish , Uniya Upasana , Sulya Maneesh , Jain Pramila , C M Chaitra
Published: December 2024

Introduction: β-Thalassemia is a hereditary disorder requiring frequent blood transfusions, leading to iron overload, which can cause serious
complications. While serum ferritin levels are commonly used to assess iron overload, they are influenced by various factors, necessitating a more
reliable, non-invasive method. This study evaluates the use of oral exfoliative cytology with Perls' Prussian blue stain for assessing iron overload in
β-thalassemia patients. The study aims to assess iron overload in β-thalassemia patients using Perls' Aims&Objectives: Prussian blue stain on oral
exfoliative cytology and correlate the findings with serum ferritin levels to evaluate its potential as a diagnostic tool. A total of 200 Methodology:
β-thalassemia patients were enrolled from August 2022 to January 2024 at the Department of Pathology, Gandhi Medical College, Bhopal. Oral
exfoliative cytology samples were stained with Perls' Prussian blue, and serum ferritin levels were measured. Statistical analysis was used to
determine the correlation. Perls' Prussian blue staining was positive for iron deposits in 85% of pat Results: ients. A strong positive correlation (r =
0.78, p < 0.01) was observed between Perls' staining and serum ferritin levels, particularly in patients with ferritin >1000 ng/mL. Oral Conclusion:
exfoliative cytology with Perls' Prussian blue stain is a reliable, non-invasive method for assessing iron overload in β-thalassemia patients and
correlates well with serum ferritin levels, making it a promising diagnostic tool.
Analysis of the Organizational Structure of the Health Service of the Principality of Asturias (SESPA). Past, Present and Challenges for the Future
Authors: Pimenta Clayson Cosme Da Costa , Prieto Daniel Zarzuelo , Primo Luis Rodríguez , Piñera Laura Rodríguez
Published: December 2024

This article deals with the reorganization of the health map in the Principality of Asturias, highlighting the reduction of the current eight areas to three as the central axis of the proposal. The unification seeks to optimize resources, improve operational efficiency and offer more integrated health services adapted to the changing needs of the population. Structural changes are detailed, including the possible creation of new departments and sub-directorates, as well as the concentration of healthcare services in the university hospitals, which could generate additional displacements for users. The concerns of healthcare professionals and unions are analyzed, especially in terms of forced mobility, which could affect job satisfaction and quality of care. Concerns about working conditions are also highlighted, as well as the possible effects on resource management and bureaucracy. The Regional Ministry of Health highlights the expected benefits, such as improved management of human and technological resources and the attraction of talent, as well as assuring that there will be no hospital closures, and that the reorganization will not negatively affect the quality of care or working conditions. Finally, the paper concludes that, although some objectives have been met, others require further analysis and could be the subject of future research.
Relationship between Radial Artery Diameters with Incidence of Radial Artery Occlusion after Transradial Coronary Catheterization: An Observational Cohort Study
Authors: Sanketh Dr S J , Charantimath Dr Naveen V. , Kumar Dr. Sameer
Published: December 2024

Background: Radial artery Occlusion (RAO) is a potential complication of transradial coronary catheterization procedures. The association between radial artery diameter and the risk of RAO remains controversial, with conflicting findings reported in previous studies. Objectives: To investigate the relationship between radial artery diameter with incidence of radial artery occlusion after transradial coronary catheterization and to assess the independent predictive value of radial artery diameter for RAO. Methods: This prospective, observational cohort study enrolled 300 patients undergoing transradial coronary angiography or percutaneous coronary intervention at a single center. Radial artery diameter was measured using a standardized ultrasound protocol before the procedure. Radial artery patency was assessed immediately after the procedure and at a 24-48 hour follow-up visit, with RAO defined as the absence of detectable blood flow on Doppler ultrasound. Multivariate logistic regression analysis was performed to evaluate the independent association between radial artery diameter and RAO, adjusting for potential confounders. Results: Radial artery occlusion occurred in 38 patients (12.7%). Patients with a small radial artery diameter (<2.5mm) had a significantly higher incidence of RAO (24.0%) compared to those with a larger radial artery diameter (6.7%) (p=0.003). On multivariate analysis, small radial artery diameter (OR 3.24, 95% CI: 1.52-6.91, p=0.002) and larger sheath size (OR 1.85 per 1 Fr increase, 95% CI: 1.21-2.83, p=0.005) were independent predictors of RAO. Conclusions: Smaller radial artery occlusion following transradial coronary catheterization procedures. Radial artery diameter is significantly associated with an increased risk of radial artery assessment may help identify patients at higher risk for RAO and guide personalized decision-making regarding vascular access site selection and procedural techniques.