Specific Field Research Articles

A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging

In the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.

Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis

We present a novel framework for analyzing and interpreting electron microscopy images in semiconductor manufacturing using vision-language instruction tuning. The framework employs a unique teacher-student approach, leveraging pretrained multimodal large language models such as GPT-4 to generate instruction-following data for zero-shot visual question answering (VQA) and classification tasks, customizing smaller multimodal models (SMMs) for microscopy image analysis, resulting in an instruction tuned language-and-vision assistant. Our framework merges knowledge engineering with machine learning to integrate domain-specific expertise from larger to smaller multimodal models within this specialized field, greatly reducing the need for extensive human labeling. Our study presents a secure, cost-effective, and customizable approach for analyzing microscopy images, addressing the challenges of adopting proprietary models in semiconductor manufacturing.

Work motivation and personal adaptation potential of specialists in the real estate field

Work motivation and personal adaptation potential of specialists in the real estate field

Application of Clavien-Dindo Complications Classification in Cardiac Surgery Practice: A Narrative Review

Background: Cardiac surgery is a complex medical specialty known for its potential complications, necessitating accurate evaluation and reporting. Current prediction scales have limitations in capturing the full spectrum of complications experienced by patients undergoing cardiac surgery. The Clavien-Dindo Complications Classification (CDCC) and the Comprehensive Complications Index (CCI) have emerged as promising tools for assessing complications in various surgical specialties, including cardiac surgery. Method: This comprehensive review synthesizes the available literature to assess the application of CDCC and CCI in the context of cardiac surgery. The effectiveness of CDCC and CCI in measuring the nature and clinical impact of complications in this specialized field is explored. Additionally, methods from other medical specialties are reviewed to enhance our understanding of the practical implementation of these classification systems in cardiac surgery. Results: The present study, including significant contributions by Mélanie Hébert et al., highlights the potential of CDCC and CCI to quantify both the number and severity of complications in adult cardiac surgery. Their utility in this specialized field presents opportunities for robust data collection and outcome evaluation. Conclusion: While the application of CDCC and CCI in cardiac surgery shows promise, the notable scarcity of comprehensive evaluation studies has hindered the accessibility of these systems to clinicians. This study provides a clear and accessible reference for healthcare professionals seeking to integrate CDCC and CCI into their cardiac surgery practice. Additionally, we propose the need for guideline studies to address this gap in the field.

FROM NOTHING TO SOMETHING: TALE OF UNRAVELING THE SECRET TO SUCCESS OF A NEOPHYTE CRIMINOLOGIST IN TAKING LICENSURE EXAM

This phenomenological study aimed to fathom the tale of unravelling the secret to the success of neophyte criminologists in passing the licensure examination. The study utilized a qualitative research design using a phenomenological approach, with 18 criminologists from Ramon Magsaysay Memorial College, General Santos City, chosen through purposive sampling. Thematic analysis was used as a data analysis tool. In light of this, results revealed the themes developed wherein this also discovered that the secret to the success of criminologists in taking and passing the CLE where they experienced mixed emotions, very challenging, stressful phenomena, feelings of nervousness, lack of preparation, frustrating events, remaining hopeful and positivism helps. In addition, criminologists experienced challenges like time constraints, financial problems, no face-to-face review, sleepless nights, anxiety situations and restrictions during the pandemic. On the coping mechanisms, criminologists pray harder, seek help, manage time well, rest when necessary, study hard, boost self-esteem, enrol in a review centre and practice the elimination methods. Furthermore, criminologists’ insights or realization revealed that preparation is necessary: take the review seriously, join a group study, give your best shot, surpass trials, increase faith and prioritize well-being. Taking a criminologist licensure exam requires extensive preparation and perseverance as they will encounter many challenges before they pass it. The insights learned by the neophyte criminologists make them more competent as professionals in their field of specialization.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0787/a.php" alt="Hit counter" /></p>

Value and Role of Obesity and Metabolic Surgery in the Study of Human Medicine, Academic Teaching and Advanced Training

In teaching, obesity and metabolic surgery play only a limited role. However, due to the rapidly increasing number of surgical interventions, communication of knowledge in the study of human medicine as well as in gastroenterological and surgical residency (general and abdominal surgery) is required.Narrative review. · Currently, lectures on obesity and metabolic surgery do not belong to the current surgical curriculum of human medicine at all University Medical Schools, which needs to be absolutely established step by step - based on their topicality and importance in the clinical spectrum of clinical care.. · This rapidly developing special area of abdominal surgery is characterized by specific and diverse interdisciplinarity.. · Multimorbidity, changes in resorption mechanisms but also psychological changes have a substantial impact on the indication and patient outcome.. · The increase in endoscopic, surgical and also robotic interventions and surgical methods in this special field requires a broad knowledge of all surgical disciplines in intervention preparation, perioperative and follow-up management of obesity-associated basic diagnosis. This objective is important even in the study of human medicine and further advanced training.. The inclusion of such complex contents on obesity and metabolic surgery into surgical teaching and into residency of general and abdominal surgery is essential to be future-oriented and prepared for the development of the discipline.

Assessing the State of Training in Congenital Interventional Cardiology: A Global Survey of Program Directors.

This study aimed to evaluate the current state of congenital interventional cardiology training worldwide, with a focus on case volumes, competency assessment, and the need for ongoing mentorship during early career stages. A survey was conducted among program directors (PDs) of congenital interventional training programs across the globe. The survey gathered data on training pathways, case volumes, types of procedures performed, trainee competency assessment, and the role of ongoing mentorship. Of the 79 PDs who completed the survey, it was observed that training pathways and case volumes varied significantly, particularly between the United States and other countries. Most PDs reported an annual laboratory case volume of >500 congenital cardiac cases, with most cases being interventional. While trainees demonstrated competency in simple procedures (diagnostic cases, simple ASD closure), complex interventions (such as patent ductus arteriosus closure in premature infants) require ongoing mentorship for graduates. PDs recommended a minimum case volume of 400 total cases for trainees, including 250 interventional cases. In addition to case volumes, assessing trainee competency was deemed important, with clinical reasoning, judgment, skillset, teamwork, and complication management being key areas of evaluation. The study highlights the variability in congenital interventional cardiology training and the need for ongoing mentorship during the early career years. External mentorship programs, facilitated by national and international societies, are proposed to provide critical support for early career interventionalists thus enhancing patient care for congenital heart disease. Ultimately, the findings of this survey may serve as a framework for future training standards and guidelines in this specialized field.

Developing a governance process for apps can help enhance and change the skills base and visibility of health librarians.

The traditional qualifications and work of a health librarian may not, at first glance, seem like they readily lend themselves to the wider work of an organisation. Too often librarians are seen as experts in a small specialist field. However, as librarians, we know that at our core is extensive digital experience and knowledge as well as a core set of transferrable skills that can be adapted to meet the ever-changing needs of the organisation. This article describes how the library evidence team became part of a wider board project to develop a governance system for Apps. It also describes how the skills of librarians can be developed to work in this area and raise the profile of the team within the board.

A comprehensive bibliometric analysis of global research on the role of acrolein in Alzheimer's disease pathogenesis: involvement of amyloid-beta.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive and behavioral decline. Acrolein, an environmental pollutant and endogenous compound, is implicated in AD development. This research employs bibliometric analysis to assess current trends and key areas concerning acrolein-AD interaction. The Web of Science was used to extensively review literature on acrolein and AD. Relevant data were systematically gathered and analyzed using VOSviewer, CiteSpace, and an online bibliometric tool. We identified 120 English publications in this specialized field across 19 journals. The Journal of Alzheimer's Disease was the most prominent. The primary contributors, both in terms of scientific output and influence, were the USA, the University of Kentucky, and Ramassamy C, representing countries/regions, institutions, and authors, respectively. In this field, the primary focus was on thoroughly studying acrolein, its roles, and its mechanisms in AD utilizing both in vivo and in vitro approaches. A significant portion of the research was based on proteomics, revealing complex molecular processes. The main focuses in the field were "oxidative stress," "lipid peroxidation," "amyloid-beta," and "cognitive impairment." Anticipated future research trajectories focus on the involvement of the internalization pathway, covering key areas such as synaptic dysfunction, metabolism, mechanisms, associations, neuroinflammation, inhibitors, tau phosphorylation, acrolein toxicity, brain infarction, antioxidants, chemistry, drug delivery, and dementia. Our analysis also supported our previous hypothesis that acrolein can interact with amyloid-beta to form a protein adduct leading to AD-like pathology and altering natural immune responses. This study provides a broad and all-encompassing view of the topic, offering valuable insights and guidance to fellow researchers. These emerging directions underscore the continuous exploration of the complexities associated with AD. The analyses and findings aim to enhance our understanding of the intricate relationship between acrolein and AD for future research.

USE OF INTELLIGENT FUZZY IMAGE SEGMENTATION SYSTEMS IN THE PROFESSIONAL TRAINING OF FUTURE SPECIALISTS IN ENGINEERING AND PEDAGOGICAL FIELDS

Relevance: The article addresses the critical issue of integrating intelligent image segmentation systems that utilize fuzzy logic into the training processes for future specialists in engineering and pedagogical fields. This integration is a significant aspect of the digitization of higher education. Aim: The goal is to implement intelligent vehicle image segmentation systems using fuzzy logic to train specialists in engineering and pedagogical fields. Methods: The preliminary processing of the images of the studied objects (vehicles) involved digital filtering methods, contour detection, profile analysis, and contrast enhancement. Image segmentation was performed using watershed methods, contour lines, and region growing. After segmentation, the obtained segments were selected based on size. Fuzzy membership functions were then applied to determine the degree of affiliation of the segments to the meaningful parts of the studied objects, ensuring reliable recognition of these parts and stable operation of the intelligent system despite external influences on the acquired images. Results: A computer system has been developed for the segmentation of vehicle images using fuzzy logic, which has been integrated into the training of specialists in engineering and pedagogical fields. The segmentation methods isolate objects within the images, which are then recognized using fuzzy logic. Thanks to the fuzzy membership functions, elements of vehicle images are reliably recognized even when there is some ambiguity in the shapes of the segments. The practical significance of the developed system is demonstrated through the processing of car images. Conclusions: The integration of the developed system into the educational process provides students with both theoretical knowledge and practical skills related to intelligent image processing systems.

Bioinspired directional structures for inhibiting wetting on super-melt-philic surfaces above 1200 °C

Over the past two decades, superhydrophobic surfaces that are easily created have aroused considerable attention for their superior performances in various applications at room temperature. Nowadays, there is a growing demand in special fields for the development of surfaces that can resist wetting by high-temperature molten droplets (>1200 °C) using facile design and fabrication strategies. Herein, bioinspired directional structures (BDSs) were prepared on Y2O3-stabilized ZrO2 (YSZ) surfaces using femtosecond laser ablation. Benefiting from the anisotropic energy barriers, the BDSs featured with no additional modifiers showed a remarkable increase from 9.2° to 60° in the contact angle of CaO–MgO–Al2O3–SiO2 (CMAS) melt and a 70.1% reduction in the spreading area of CMAS at 1250 °C, compared with polished super-CMAS-melt-philic YSZ surfaces. Moreover, the BDSs demonstrated exceptional wetting inhibition even at 1 400 °C, with an increase from 3.3° to 31.3° in contact angle and a 67.9% decrease in spreading area. This work provides valuable insight and a facile preparation strategy for effectively inhibiting the wetting of molten droplets on super-melt-philic surfaces at extremely high temperatures.

The scientific knowledge of three large language models in cardiology: multiple choice questions examination-based performance

Background: The integration of artificial intelligence (AI) chatbots like Google’s Bard, OpenAI’s ChatGPT, and Microsoft’s Bing Chatbot into academic and professional domains, including cardiology, has been rapidly evolving. Their application in educational and research frameworks, however, raises questions about their efficacy, particularly in specialized fields like cardiology. This study aims to evaluate the knowledge depth and accuracy of these AI chatbots in cardiology using a multiple-choice question (MCQ) format. Methods: The study was conducted as an exploratory, cross-sectional study in November 2023 on a bank of 100 MCQs covering various cardiology topics that was created from authoritative textbooks and question banks. These MCQs were then used to assess the knowledge level of Google’s Bard, Microsoft Bing, and ChatGPT 4.0. Each question was entered manually into the chatbots, ensuring no memory retention bias. Results: The study found that ChatGPT 4.0 demonstrated the highest knowledge score in cardiology, with 87% accuracy, followed by Bing at 60% and Bard at 46%. The performance varied across different cardiology subtopics, with ChatGPT consistently outperforming the others. Notably, the study revealed significant differences in the proficiency of these chatbots in specific cardiology domains. Conclusion: This study highlights a spectrum of efficacy among AI chatbots in disseminating cardiology knowledge. ChatGPT 4.0 emerged as a potential auxiliary educational resource in cardiology, surpassing traditional learning methods in some aspects. However, the variability in performance among these AI systems underscores the need for cautious evaluation and continuous improvement, especially for chatbots like Bard, to ensure reliability and accuracy in medical knowledge dissemination.

Surgical Residency Training in Nigeria: An Audit Through the Lenses of the Trainee and Trainer

IntroductionResident doctors constitute an important workforce of the Nigerian healthcare system wherein they undergo structured training to become competent specialists in different fields of medicine. The aim of this survey was to audit the surgical residency training process, incorporating both the trainer's and the trainee's perspectives, with a view to improving both residency training and overall patient care. MethodsThis was a multicenter descriptive cross-sectional study involving consultant surgeons and surgical trainees in selected tertiary healthcare institutions in Nigeria. A link to an online semi-structured and pretested questionnaire was sent to study participants whose agreement to fill out the questionnaire was taken as implied consent for the study. The perception of respondents on key areas of surgical residency training like the quality of training, skill acquisition, mentorship, supervision, operative exposures, research, funding, didactic sessions, and work schedule was assessed using a Likert scale. Their perceived challenges to training and measures to improve the quality of training were recorded. Data were analysed using version 23 of the SPSS. ResultsA total of 127 participants (25 trainers and 102 trainees) were recruited with a mean age of 34.8 ± 3.5 y for the trainees and 47.5 ± 6.9 y for the trainers. The majority of both the trainers and trainees (72%, n = 18 and 93%, n = 96, respectively) were dissatisfied with the quality of surgical residency training in Nigeria with the trainers (88%, n = 22) and trainees (97.1%, n = 99) mostly agreeing that surgical training should be standardized across training centres in Nigeria. The trainees and trainers rated mentorship, research, funding, and overall quality of surgical residency training as inadequate, while most of the trainees and trainers rated supervision of trainees as adequate. The trainees predominantly identified poor training facilities as the most important challenge to surgical residency, followed by high clinical workload, while the majority of the trainers identified workplace bullying and high clinical workload as being the predominant factors. The nine-pronged recommendations by both the trainers and trainees to improve surgical training in Nigeria include mentorship program for trainees, funding of surgical residency training, provision of facilities and equipment for training, adequate supervision of trainees by trainers, job description and defined work schedule for trainees, health insurance of patients, overseas training of trainees during the residency program, improved remuneration of trainees, and adequate motivation of trainers. ConclusionsThe quality of surgical residency training in Nigeria is perceived as suboptimal by trainees and trainers. Perceived common challenges to surgical residency training include poor training facilities, workplace bullying, and high clinical workload. Adequate funding of surgical residency program, standardized mentorship, and training of trainees with improved remuneration of trainees and motivation of their trainers would enhance the overall quality of surgical residency training in Nigeria.

Diode-pumped cascade Tm:YAG laser at ∼2 μm and ∼2.3 μm

We report on the first cascade continuous-wave operation of the Tm:YAG crystals with different doping concentrations (2 at.% Tm:YAG and 3.5 at.% Tm:YAG) on the 3F4 → 3H6 (at ∼2 μm) and 3H4 → 3H5 (at ∼2.3 μm) transitions. With the lower concentration of Tm-doped YAG, the cascade laser generated a maximum total output power of 4.70 W with a higher slope efficiency of 23.9 %, out of which 0.79 W are obtained based on the 3H4 → 3H5 transition at ∼2.3 μm. Such laser that combing the two emission wavelengths makes it has potential application in some special field, e.g., gas detection.

Demographic Diversity and Economic Research: Fields of Specialization and Research on Race, Ethnicity, and Inequality

Using dissertation research topics found in the EconLit database and large-scale algorithmic methods that identify author demographics based on names, we explore the link between race and ethnicity and fields of economic research. We find that underrepresented racial and ethnic minority (URM) researchers are more likely to write dissertations in some unexpected subfields of economics but limited evidence that they are more likely to write dissertations on racial topics once we include basic controls. These descriptive results may be due to limitations in the data, intrinsic motivations, or external constraints.

Studying the history of histopathology in preclinical medical education as a guide for the uniform integration of radiology in medical education

Radiology and pathology, though distinct fields within medical education, share a common foundation in their essential roles for accurate diagnosis and understanding of diseases. While pathology, particularly histopathology, has long been integrated into preclinical medical education in the United States, radiology education has traditionally been less emphasized. This paper examines the historical development of histopathology training in medical education and its central role, contrasting it with the comparatively peripheral position of radiology education. We explore the historical context of medical education in the United States, tracing the integration of histopathology following the Flexner Report of 1910. In contrast, radiology, emerging later as a specialized field, has faced challenges in achieving comparable integration into medical curricula. Despite the increasing importance of medical imaging in diagnosis and treatment, radiology education remains variable and often lacking in standardization across medical schools. We highlight the need for greater emphasis on radiology education to better prepare medical students for modern clinical practice, where medical imaging plays an increasingly pivotal role. A call for a comprehensive assessment of radiology education and advocacy for its integration into preclinical curricula is made, emphasizing the importance of collaboration between the radiology profession and accrediting bodies to ensure competence in imaging across medical specialties. As medical imaging continues to advance and become more integral to healthcare, it is imperative that medical education reflects this evolution by establishing radiology as a fundamental component of preclinical training.

Causal Inference and Prefix Prompt Engineering Based on Text Generation Models for Financial Argument Analysis

The field of argument analysis has become a crucial component in the advancement of natural language processing, which holds the potential to reveal unprecedented insights from complex data and enable more efficient, cost-effective solutions for enhancing human initiatives. Despite its importance, current technologies face significant challenges, including (1) low interpretability, (2) lack of precision and robustness, particularly in specialized fields like finance, and (3) the inability to deploy effectively on lightweight devices. To address these challenges, we introduce a framework uniquely designed to process and analyze massive volumes of argument data efficiently and accurately. This framework employs a text-to-text Transformer generation model as its backbone, utilizing multiple prompt engineering methods to fine-tune the model. These methods include Causal Inference from ChatGPT, which addresses the interpretability problem, and Prefix Instruction Fine-tuning as well as in-domain further pre-training, which tackle the issues of low robustness and accuracy. Ultimately, the proposed framework generates conditional outputs for specific tasks using different decoders, enabling deployment on consumer-grade devices. After conducting extensive experiments, our method achieves high accuracy, robustness, and interpretability across various tasks, including the highest F1 scores in the NTCIR-17 FinArg-1 tasks.

Осознанность, перфекционизм и профессиональное выгорание у специалистов в сфере информационных технологий

This article examines the relationship between mindfulness and socially prescribed perfectionism with professional burnout among specialists in the information technology field in Moldova, with an emphasis on age and gender differences. The research group consisted of 120 IT professionals: 58% male and 42% female. The analysis showed that there is a significant negative correlation between mindfulness and professional burnout (correlation coefficient -0.649), indicating a decrease in burnout risk with increased levels of mindfulness. At the same time, socially prescribed perfectionism enhances professional burnout, with a positive correlation of 0.391, especially among young men. These results highlight the need to consider psychological factors when developing corporate well-being strategies.

THE IMPACT OF THE PROBLEMS OF DETERMINING JURISDICTION IN THE VIRTUAL SPACE ON THE PROVISION OF HUMAN RIGHTS AND FREEDOMS

In many cases, the existing legal regulations are not adequate to solve the legal problems created by the Internet. Solving the legal problems created by the Internet with existing positive regulations is a situation specific to the special field of law. In cases where the existing normative documents are insufficient, it is considered appropriate to add new provisions that complement each other, and if this is not possible, to make independent legal regulations. The fact that such arrangements are based on doctrine rather than spontaneity can ultimately lead to successful practice. Therefore, the interpretation of the human rights aspect of issues related to virtual space is one of the most important topics today. The most important issue related to the protection of human rights violated in the virtual space is the resolution of the issue of jurisdiction. Issues related to the Internet have also been reflected in all international declarations adopted in the field of information society construction, including the provision of information rights. At the regional level, the Declaration "On Freedom of Communication on the Internet" adopted by the Committee of Ministers of the Council of Europe in 2003, the Recommendations of the Committee of Ministers of the Council of Europe on the Human Rights Guide for Internet Users to Member States, etc. such documents are of special importance for the regulation of Internet legal relations. However, no international norm fully covers the issue of jurisdiction in virtual space. In the presented article, as a result of the research, it was concluded that it is necessary to create unified substantive and procedural legal norms that are mandatory for all in order to solve jurisdictional problems in the virtual space. Acceleration of integration and globalization processes in the world increases the interest of states in the unification of their legal norms. Because the countries of the world, which often protect their citizens from violations of their rights on the Internet, as well as from more dangerous information wars and psychological attacks, need the existence of a unified legal regulation. For this purpose, the creation and unification of legal norms that resolve jurisdictional issues in the virtual space should be implemented at different levels: bilateral, regional and universal levels

The Effect of Learning Style Preference, Clerkship Training and Role Model on Specialization Selection

Aim: The clerkship period in medical schools is an integrated learning experience that is also helpful in choosing a future career. The aim of this study was to evaluate the effect of both general surgery clerkshipship and awareness of learning styles on specialty preferences of medical students. Methods: In this study, which was planned as an educational intervention, a questionnaire questioning specialty preferences and a learning style scale were administered to fourth-year medical students before their general surgery clerkships. Following the questionnaire, brief training was given about specialty branches and learning styles. After the clerkship, the students were asked to answer the questionnaire again about their specialty preferences. Changes between clerkship training, learning style awareness and specialty preferences were evaluated. Results: One hundred eight students participated in the study (M:81, F:27). The mean age was 23.0. The most important factor in choosing a specialty is professional satisfaction (64%) with the work in that specialty. The approach of the trainers in the clerkship training (67%) was to focus on the most influential mind-changing factors for the choice of specialty. The most common learning styles among female students were kinesthetic and visual, while the most common learning style among male students was auditory. However, the learning style of students who preferred surgical branches was generally in the kinesthetic group. Conclusions: An effective clerkship program in which students encounter effective positive role models, gain knowledge about their field of specialization and learning styles, and increase their awareness will provide the right guidance in their specialization preferences.