bluuebunny/crossref_metadata_2025_split huggingface dataset:
42. ĐẶC ĐIỂM LÂM SÀNG VÀ MỘT SỐ YẾU TỐ LIÊN QUAN CỦA BỆNH BẠCH BIẾN TẠI BỆNH VIỆN DA LIỄU TRUNG ƯƠNG GIAI ĐOẠN 2016-2017
Authors: Hiền Đỗ Thị Thu , Nhung Đỗ Thị Hồng , Tiên Nguyễn Thị Kim 
Published: April 2024

Mục tiêu: Mô tả đặc điểm lâm sàng và một số yếu tố liên quan của bệnh bạch biến tại Bệnh viện Da liễu Trung ương giai đoạn 2016-2017.
Đối tượng và phương pháp: Nghiên cứu mô tả cắt ngang trên 80 bệnh nhân bạch biến đến khám và điều trị tại Bệnh viện da liễu Trung ương từ 10/2016 – 9/2017.
Kết quả: Độ tuổi khởi phát bệnh trung bình là 26,89 ± 18,38, trong đó nhóm tuổi chiếm tỷ lệ cao nhất (40%) là từ 15 đến 30 tuổi. Tỷ lệ mắc bệnh của nữ (56,2%) cao hơn nam (43,8%). Tỷ lệ bệnh đồng mắc với bạch biến qua khai thác tiền sử người bệnh là 17,5%, trong đó chủ yếu là các bệnh viêm loét dạ dày – tá tràng, viêm da cơ địa và bệnh lý dị ứng, không khai thác được tiền sử bệnh lý tuyến giáp. Bệnh nhân bị bạch biến có type da IV chiếm tỷ lệ 93,7%, type III chiếm 6,3%. Vị trí tổn thương thường gặp nhất ở mặt - cổ chiếm 46,3%, sau đó đến thân mình chiếm 24,3%, đầu chi ít gặp nhất với tỷ lệ 1,5%. Thể lâm sàng gặp chủ yếu là thể không đứt đoạn lan tỏa với 46,3%, thể đứt đoạn chỉ chiếm 2,5%. 71/80 bệnh nhân có giai đoạn hoạt động bệnh (với chỉ số VIDA +1,+2,+3,+4) chiếm tỷ lệ 88,7%, trong đó chỉ số VIDA +4 chiếm tỷ lệ cao nhất (38,7%).
Kết luận: Bạch biến thường gặp ở người trẻ tuổi, bệnh có thể gặp ở cả nam và nữ. Bệnh chủ yếu gặp ở bệnh nhân có type da IV và thể bệnh không đứt đoạn lan tỏa là thể thường gặp nhất. Một bệnh nhân có thể có nhiều vị trí tổn thương phối hợp, vị trí tổn thương ở vùng mặt là vị trí hay gặp nhất.
43. ĐẶC ĐIỂM LÂM SÀNG VÀ CÁC YẾU TỐ LIÊN QUAN CỦA BỆNH NẤM MÓNG TẠI BỆNH VIỆN DA LIỄU TRUNG ƯƠNG NĂM 2018
Authors: Hiền Đỗ Thị Thu , Nhiên Nguyễn Thị Thu , Mạnh Hoàng Hồng 
Published: April 2024

Mục tiêu: Khảo sát đặc điểm lâm sàng và các yếu tố liên quan của bệnh nấm móng tại Bệnh viện Da Liễu Trung ương năm 2018.
Đối tượng và phương pháp: Nghiên cứu mô tả cắt ngang trên 110 bệnh nhân được chẩn đoán xác định nấm móng bằng nuôi cấy nấm tại Bệnh viện Da Liễu Trung ương từ 8/2018 đến 7/2019.
Kết quả: Tuổi mắc bệnh thường trong độ tuổi lao động 20-59 tuổi chiếm 70%, chủ yếu là nữ chiếm 61,3% và tỷ lệ bệnh nhân sống ở nông thôn cao gấp 2,66 lần bệnh nhân ở thành thị. Nghề nghiệp hay gặp là lao động tay chân, tiếp xúc với nước như nông dân, người tiếp xúc với vật nuôi, gia súc, gia cầm (38,2%) và công nhân làm việc trong môi trường ẩm ướt (19,1%). Dạng tổn thương hay gặp nhất là tổn thương bờ bên và bờ xa dưới móng chiếm (71/110, 64,5%), tổn thương bờ gần dưới móng là (48/110, 43,6%), tổn thương bề mặt móng là (38/110, 34,5%). Tổn thương cơ bản hay gặp là tổn thương có khối sừng mủn dưới móng (53/110, 48,2%). Trong tổng số 110 bệnh nhân được chẩn đoán nấm móng dựa vào nuôi cấy, 96 bệnh nhân (87,3%) có kết quả soi tươi có nấm, 14 (12,7%) bệnh nhân có kết quả soi tươi không thấy nấm.
Kết luận: Nấm móng hay gặp ở người ở độ tuổi lao động, đặc biệt người làm việc trong môi trường ẩm ướt. Hình thái lâm sàng hay gặp là nấm móng ở bờ bên và bờ xa dưới móng và khối sừng mủn dưới móng. 87,3% bệnh nhân có tương đồng kết quả giữa soi tươi và nuôi cấy cho thấy độ tin cậy khá cao của soi tươi trong chẩn đoán nấm móng.
Morphometric studies of the skin of calfs
Authors: Shafiev A. P. , Kudryashov A. A. , Safronov D. I. 
Published: April 2024

Relevance. Previously, we conducted comparative morphometric studies of skin samples from different topographic sites in adult cows obtained in winter. At the same time, morphological features of the skin of different topographic areas were established. In this paper, the purpose of our study was to conduct comparative morphometric studies of the skin of different topographic areas in calves.Methods. Morphometric studies of histological preparations were carried out at the Department of Pathological Anatomy and Forensic Veterinary Medicine and at the Department of Biology, Ecology and Histology. Morphometric studies of histological preparations were used to study the thickness of the dermis proper, as well as bundles of collagen fibers of the mesh layer of the dermis. The research results were statistically processed using the "Biostat" program.Results. Morphological features of the skin of different topographic areas in calves have been established, manifested by different thicknesses of skin layers and bundles of collagen fibers of the dermis. The morphometry performed made it possible to supplement the data on the morphological structure of the skin of cattle and can also be used in the study of morpho- and pathogenesis of skin diseases.
The practice of creating buffer zones in anti-epizootic measures for rabies using the example of the border zone with Finland
Authors: Fogel L. S. , Gruzdev K. N. , Krotov L. N. , Danko Yu. Yu. 
Published: April 2024

One of the important tasks of veterinary medicine in the Russian Federation is the implementation of measures to prevent and eliminate infectious animal diseases[2]. Animal rabies is a zoonotic transboundary disease. It is characterized by natural focality, and wild carnivores, in particular the fox, are considered a reservoir of the rabies pathogen. Since the end of the twentieth century, oral rabies vaccines have been used to prevent rabies in Western Europe and the United States [1,3].This article presents the results of research work in 2003-2009. to create a buffer zone against animal rabies on the border with Finland by oral vaccination of wild carnivores in the Leningrad region, the Republic of Karelia. Live vaccines were used in the work: "FUCHSORAL" (Germany) and domestic ones - "SINRAB" (FGBU "ARRIAH, Vladimir) and its analogue - the vaccine "ORALRABIVAK" produced by OJSC "PZB" (Pokrov).In the Leningrad region and the Republic of Karelia in 2003, the FUCHSORAL vaccine (Germany) was used once, and in subsequent years, double annual vaccination was carried out with domestic vaccines. In Finland, people were constantly vaccinated with the oral rabies vaccine “FUCHSORAL” (Germany), from the “SAD B19” strain [4]We carried out annual 2-fold vaccination (in spring and autumn) of wild carnivores, in accordance with the instructions for use of vaccines, at air temperatures from +2 to +8 C in a zone 50-80 km wide from the border for 6 years. The number of blood serum samples containing a level of rabies virus-neutralizing antibodies sufficient to protect against rabies in the Republic of Karelia increased from 0% to 80%, and in the Leningrad region. from 0% to 70%.As a result of the implementation of planned work in the period 2003-2009. to prevent rabies among wild carnivores in the Leningrad region and the Republic of Karelia, epizootic freedom from rabies was achieved, satisfying the neighboring country.
АНАЛИЗ ВЛИЯНИЯ ФАКТОРОВ НА ПОТЕНЦИАЛ СРЕДОВОЙ ВОВЛЕЧЕННОСТИ
Authors: Proshunina Kseniya Alekseyevna , Khomenko Tatyana Vladimirovna 
Published: April 2024

Приведены результаты моделирования потенциала средовой вовлеченности от взаимосвязи независимых переменных в территориально-распределенной пространственной системе на примере существующей застройки жилых домов. При этом
рассмотрено два фактора влияния: площадь благоустройства, количество жильцов. Анализ результатов показал процент
влияния рассматриваемых факторов на возможности территориально-распределенной пространственной системы жилой среды, что чем выше показатели свободной территориальной площади благоустройства в существующей среде, тем выше значения потенциала средовой вовлеченности, и соответственно актуальней проведение мероприятий по замене существующих объектов благоустройства с учетом вместимости предлагаемых площадок, отвечающих запросам жильцов. Предложенный анализ может найти практическое применение при оценке существующей среды в генеративном проектировании общественных пространств, способствуя повышению обоснованности принимаемых решений.
НЕСТАЦИОНАРНЫЙ НАГРЕВ МЕТАЛЛИЧЕСКИХ ДЕТАЛЕЙ В МАШИНОСТРОЕНИИ ЛУЧИСТЫМ ПОТОКОМ ТЕПЛА С УЧЕТОМ ИЗМЕНЕНИЯ ТЕПЛОФИЗИЧЕСКИХ ХАРАКТЕРИСТИК
Authors: Legkiy Aleksandr Dmitriyevich , Veselova Natalya Mikhaylovna , Karapuzov Vladislav Igorevich , Brenina Tatyana Pavlovna 
Published: April 2024

Рассмотрен метод исследования нестационарного нагрева лучистого потока тепла металлических заготовок квадратного сечения с переменными теплофизическими характеристиками. Описан метод получения массивных и крупногабаритных элементов для деталей машин методом термообработки. Преимущество данного метода является его применения
в различных отраслях машиностроения, а также при производстве отдельных строительных конструкций. Кроме того, в статье приведен математический анализ, методом конечно-разностных уравнений при помощи компьютерного моделирования, который с высокой достоверностью позволяет получить расчета температурных режимов нагрева стальных заготовок в производстве деталей сельскохозяйственных машин. Результаты расчетов нагрева бруса методом конечно-разностных уравнений сопоставлены с опытными данными.
СРАВНЕНИЕ ТЕМПЕРАТУРНЫХ ПОЛЕЙ МОНОЛИТНЫХ ЖЕЛЕЗОБЕТОННЫХ КОНСТРУКЦИЙ, ПОЛУЧАЕМЫХ В РЕЗУЛЬТАТЕ ЭКСПЕРИМЕНТАЛЬНОГО И ЧИСЛЕННОГО МОДЕЛИРОВАНИЯ ПРОЦЕССА ЭЛЕКТРОПРОГРЕВА БЕТОНА
Authors: Leontyev Stepan Vasilyevich , Taleyko Andrey Alekseyevich 
Published: April 2024

В статье приводятся результаты сравнения температурных полей, построенных по данным численного моделирования
процесса прогрева бетона греющим проводом, и значений температур бетона, полученных в ходе проведения аналогичного натурного эксперимента. Суть эксперимента состояла в прогреве элемента бетонной конструкции с помощью нихромовой проволоки, размещенной в теле бетона. В качестве источника напряжения использовался инверторный сварочный аппарат, напряжение на концах проволоки было постоянным, регулирование прогрева осуществлялось периодическим включением и выключением питания. Измерение температуры бетона в процессе тепловой обработки осуществлялось в центральной и угловой точках конструкции. Полученные в ходе натурного эксперимента температурные данные сравнивались с данными аналогичной модели, построенной в программном комплексе Elcut. По результатам исследований был сделан вывод о сходимости результатов, получаемых с помощью модели, и данных натурного эксперимента, а также проанализированы факторы, объясняющие имеющиеся расхождения данных.
РЕШЕНИЕ ОБРАТНОЙ ЗАДАЧИ ШТУРМА – ЛИУВИЛЛЯ ПРИ ВОССТАНОВЛЕНИИ СКОРОСТНЫХ ХАРАКТЕРИСТИК КВАЗИБЕСКОНЕЧНОЙ СТРУНЫ
Authors: Berezhnoy Dmitriy Valerievich , Sabitov Linar Salikhzanovich , Garkin Igor Nikolayevich , Sekayeva Liliya Ravilyevna , Mikheyev Vladimir Vladimirovich 
Published: April 2024

Задачи изучения скоростного строения геологических сред являются важными и актуальными на сегодняшний день. При этом несмотря на развитие и возможности современных технологических подходов, верхняя часть разреза до сих пор
остается плохо изученной. Связано это с рядом факторов, одним из которых является отсутствие на данных горизонтах полезных ископаемых, таких как залежи углеводорода. Для нефтяных промышленностей бурение верхних слоев является относительно простой задачей, не требующей глубокого изучения свойств предповерхностного грунта. Поэтому данных по верхней части разреза собирается мало. В настоящей работе авторами представлено решение обратной задачи Штурма –
Лиувилля определения скоростной характеристики верхней части разреза геологической среды. В работе рассматриваются два подхода к решению поставленной задачи, с помощью спектральной и кепстральной методик. Показывается применение методов на синтетических данных, полученные 1Д решением, а также приводятся ограничения применимости этих подходов.
ПЕРСПЕКТИВЫ РАЗВИТИЯ ГОРОДСКОЙ НАБЕРЕЖНОЙ МЕТОДОМ СОЦИАЛЬНОГО ОПРОСА
Authors: Dakheel Heba 
Published: April 2024

Данная статья разработана по результатам социального исследования для оценки качества набережной города Джабла
в Сирии. В ходе исследования было опрошено 200 человек. Цель – предоставление жителям возможности сформулировать
новые точки зрения, которые могут быть полезны в будущем для изучен6ия. Основной вывод заключается в том, что набережная нуждается в специальном развитии, которое стимулировало бы социальное взаимодействие. По итогам проведенного исследования были разработаны рекомендации и описание предложенного автором проектного решения по развитию набережной зоны. Полученные результаты позволят сделать набережные комфортными, доступными и интересными
для посетителей и в дальнейшем могут быть использованы при оформлении набережных в других сирийских городах с некоторыми изменениями в зависимости от города.
MFGC: Minimal First Garbage Collection for Monitoring of Context-Aware Victim Selection
Authors: P. K. Singh Shweta, 
Published: April 2024

SSDs based on NAND flash are becoming a feasible secondary storage option for many computer systems. Because NAND flash memory is dif- ferent from regular HDDs, flash-based SSDs frequently have an interface layer known as Flash Translation Layer (FTL). Garbage collection tech- nique is required to free up space. Garbage collection policy is primarily concerned with cleaning costs and wear-leveling. To achieve the above design principles, we have proposed an effective minimal first garbage col- lection termed as MFGC. MFGC manages the blocks in the list, sorted in descending order of erase count. This list is divided into two regions: preference region and alternate region. The adaptive window for victim selection is used, which adapts dynamically as the cleaning cost changes. After the victim selection, effective data identification of valid hot page and valid cold page is done based on threshold and redistribution of them is done to free blocks. A Series of trace simulations is performed to evaluate the performance of proposed approach with other existing approaches. MFGC outperforms GR, CB, CAT, CATA and MCSGC by 85.5%, 77.1%,61.7%, 56.7% and 43.5% respectively.The outcome of the simulation demonstrates that our approach is superior to others in terms of erase and copy operations as well as wear leveling of blocks.
Research on The Application of Data Mining in Evaluation of Curriculum Teaching
Authors: Li Dandan 
Published: April 2024

The effectiveness of moral education is the fundamental standard to test all the work in colleges and universities, evaluation of curriculum teaching is very important for teachers to accurately master students' learning effects .Data mining technology has great advantages in curriculum evaluation. Guided by the concept of OBE (Outcomes-based Education), this paper obtains evaluation data through data mining from the goal of talent training. The data is processed through data collection, data integration, data selection, data cleaning, data conversion ,then the AHP(Analytic Hierarchy Process)-FCE(Fuzzy Comprehensive Evaluation) analysis model is constructed for empirical analysis, and the educational effect of big data and accounting courses is evaluated. Carrying out evaluation of curriculum teaching can promote teaching, improve the quality of personnel training, and achieve the goal of educating people.On the one hand, evaluation of curriculum teaching can provide an empirical basis to improve the talent training quality. On the other hand, it can provide theoretical reference for other majors to carry out curriculum teaching evaluation
A Generalized Two-Level Ensemble Method for Spam Mail Detection
Authors: C. Nagaraju B. Aruna Kumari, 
Published: April 2024

Email is the most cost-effective way to communicate with people across the world. It offers a simple and convenient way to send and receive messages. However, it is susceptible to various types of threats. The most significant risk to emailers is spam, which refers to unsolicited emails that are often sent in large numbers to multiple recipients. Malicious spam includes links to phishing websites. These links not only pose a threat to our system, but also make our personal information accessible to hackers. Spammers often create fake profiles and email accounts making it easier for them to deceive unsuspecting victims. In this paper, the content of the email is used to detect spam which provides more information than a URL. It has been found that several techniques have been proposed to efficiently identify spam emails but current email spam detection methods have not yet achieved high accuracy. It is necessary to improve their performance in spam detection, a generalized two-level ensemble technique is explored irrespective of the type of spam datasets. The proposed two-level ensemble algorithm compares with various machine learning techniques such as SVM, Regression, and kNN, along with their variants, Finally, a K-fold and voting algorithms are applied to make the final prediction.
Forecasting the Future: A Comprehensive Review of Time Series Prediction Techniques
Authors: Sandhya Arora Milind Kolambe, 
Published: April 2024

Time series forecasting is a critical aspect of data analysis, with applications ranging from finance and economics to weather prediction and industrial processes. This review paper explores the evolution of time series forecasting techniques, analyzing the progression from classical methods to modern approaches. It synthesizes key advancements, discusses challenges, future directions and provides insights into emerging trends. Traditional forecasting methods often struggle with capturing the complex patterns and dynamics present in real-world time series data. This study explores the efficacy of cutting-edge models, such as long short-term memory (LSTM) networks, and recurrent neural networks (RNNs), in capturing intricate temporal dependencies. It also aims to guide researchers and practitioners in selecting appropriate methods for diverse time series forecasting applications. We categorize existing approaches, discuss their strengths and limitations, and highlight emerging trends in the field.
Deep Learning in Agritech: Exploring Techniques and Architectures for Plant Disease Detection
Authors: Thelma D. Palaoag, Carl Angelo S. Pamplona Nerissa L. Javier, 
Published: April 2024

Disease detection in agriculture is crucial for maintaining crop health and productivity. Traditional methods of detection rely on manual observation and expert knowledge, which can be time-consuming and subjective. In recent years, deep learning techniques have emerged as a promising approach for automated disease detection. This paper investigates the performance of three state-of-the-art deep learning models, ResNet34, MobileNetv2, And Yolov8, in detecting and categorizing leaf diseases among corns. The study revealed that MobileNet2 demonstrates computational effectiveness in classifying corn leaf diseases, with a low average loss and the ability to discriminate between specific illnesses. Yolov8 is identified as a strong candidate for real-world applications due to its consistently high precision (95.73%), recall (94.81%), accuracy (96.18%), and F1 score (95.22%) across all disease categories. It excels in distinguishing between Blight and Common Rust and accurately recognizing healthy leaves. ResNet34 and MobileNetv2 also show competitive results, but Yolov8 performs better overall, particularly in terms of precision and recall. However, the choice of the optimal model depends on the specific application's demands, computational effectiveness, and the balance between recall and precision. Further investigation and refinement endeavors are recommended to augment the potential of these models and address any remaining obstacles in disease identification.
Ear Biometry: Protection Safeguarding Ear Acknowledgment Framework utilizing Transfer Learning in Industry 4.0
Authors: Shilpi Sharma, Swapnita Srivastava, Vipul Narayan Rahul Sawhney, 
Published: April 2024

Human-Recognition using biometric features proposes a noble way of uniquely identifying individuals considering they do not require people to keep loads of passwords in mind to prove their identity. Biometrics have aided in people unable to render other’s identity as well and have advanced over the years. Identification using ear biometric technique is considered to outrun other features since passive human involvement and ease-of-access are its strong set of attributes, not seen in any other biometric techniques. It has managed to identify criminals in the Crime Branch and has various helpful applications in the industry. Even in times of pandemic, it can serve its purpose in identifying individuals due to its feasibility. Models for Ear Image Identification have been proposed by various researchers over time utilizing Deep Learning and its Networks achieving high accuracy results, presenting faster and accurate identification models, boosting Ear Biometry as a secure Human Identification Tool. The learnings of this study on the AMI Ear Dataset and the OCEar dataset prove Ear Uniqueness of individuals demonstrating the identification of individuals, introducing passive identification into play, as well as computes on another dataset OCEar to study the similarity of both ears for identifying an individual.
Enhancing MANET Performance: A Novel Approach Through Nature-Inspired Scheduling Algorithms
Authors: Syed Wajahat Abbas Rizvi,  Soumen Kanrar Abhishek Shukla, 
Published: April 2024

In the rapidly evolving landscape of Mobile Ad Hoc Networks (MANETs), the quest for optimal performance through efficient scheduling remains paramount. This paper, titled "Enhancing MANET Performance: A Novel Approach Through Nature-Inspired Scheduling Algorithms," introduces an innovative methodology that leverages the intricate mechanisms of nature to address the complex challenges inherent in MANET scheduling. Drawing inspiration from the adaptive behaviors observed in natural systems, we have developed a suite of nature-inspired algorithms—encompassing the genetic algorithm, particle swarm optimization, and ant colony optimization—tailored specifically to enhance the scheduling efficiency within the dynamic and decentralized context of MANETs.
Our research undertakes a comprehensive evaluation of these algorithms against traditional scheduling methods, showcasing a notable improvement in key performance metrics such as network throughput, latency, and energy consumption. The novel contribution of this study lies in the adaptation and optimization of these bio-inspired algorithms for the unique demands of MANET scheduling, culminating in the development of a proprietary analytical model that significantly outperforms existing strategies. Through a rigorous comparative analysis, our results illuminate the superiority of our approach, demonstrating not only enhanced network efficiency but also improved scalability and reliability under varying conditions.
The implications of this research extend beyond the immediate enhancements to MANET performance, proposing a paradigm shift in how scheduling challenges are approached within ad hoc networks. By bridging the gap between biological principles and technological applications, this study paves the way for future innovations in network management, offering a blueprint for the development of more adaptive, robust, and efficient networking solutions.