bluuebunny/crossref_metadata_2025_split huggingface dataset:
ĐẶC ĐIỂM LÂM SÀNG, CẬN LÂM SÀNG VÀ KẾT QUẢ ĐIỀU TRỊ LAO PHỔI CHẨN ĐOÁN DỰA TRÊN BẰNG CHỨNG MÔ BỆNH HỌC
Authors: Nguyễn Bích Ngọc , Nguyễn Kim Cương 
Published: February 2025

Mục tiêu: Mô tả một số đặc điểm lâm sàng, cận lâm sàng bệnh nhân lao phổi chẩn đoán dựa trên bằng chứng mô bệnh học và đánh giá kết quả điều trị sau 2 tháng tấn công ở nhóm bệnh nhân nghiên cứu tại Bệnh viện Phổi Trung ương. Đối tượng và phương pháp: Nghiên cứu mô tả có theo dõi dọc, hồi cứu kết hợp tiến cứu trên 66 người bệnh có tổn thương nghi lao phổi trên XQ, CT mà không có bằng chứng vi khuẩn lao được sinh thiết phổi chẩn đoán mô bệnh học và được hội chẩn, điều trị tại Bệnh viện Phổi Trung ương từ 01/2023 đến 06/2024. Kết quả: Tuổi trung bình là 48,5 ± 16,6 năm, Nam giới chiếm 62,1%. Tỷ lệ lao động tự do 22 (33,3%); 25,8% nông dân. BMI trung bình là 20,7±2,6. Tỉ lệ có hút thuốc lá là 43,9% và tiền sử bệnh mạn tính là 45,5%. Các triệu chứng toàn thân, cơ năng của đối tượng nghiên cứu sau 2 tháng điều trị tấn công giảm: Mệt mỏi từ 78,8 % – 7,6%; Sốt từ 30,3% – 1,5%; Đau ngực 71,2% - 10,6%; Ho kéo dài 71,2% – 4,5%; Ho ra máu, khó thở 0%. Có 8 trường hợp MGIT đờm (+) lúc đầu giảm xuống còn 1 trường hợp MGIT đờm (+). Kích thước tổn thương cả ĐK ngang và ĐK trước sau có sự khác nhau trước và sau điều trị, sự khác biệt có ý nghĩa thống kê với p<0,05. Kết luận: Các triệu chứng toàn thân, cơ năng của đối tượng nghiên cứu sau 2 tháng điều trị tấn công đã giảm đi đáng kể. Có mối liên quan giữa kích thước tổn thương cả ĐK ngang và ĐK trước sau có sự khác nhau trước và sau điều trị.
NGHIÊN CỨU ĐẶC ĐIỂM LÂM SÀNG, CẬN LÂM SÀNG, KẾT QUẢ ĐIỀU TRỊ NGƯỜI BỆNH NHỒI MÁU NÃO CẤP MỨC ĐỘ NHẸ TẠI BỆNH VIỆN ĐA KHOA TỈNH YÊN BÁI NĂM 2024
Authors: Lê Đức Thuận , Hoàng Tiến Hảo , Ngô Hùng Cường , Nguyễn Văn Chúc 
Published: February 2025

Mục tiêu: Tìm hiểu đặc điểm lâm sàng, cận lâm sàng và kết quả điều trị nhồi máu não cấp mức độ nhẹ tại Bệnh viện Đa khoa tỉnh Yên Bái. Phương pháp nghiên cứu: Nghiên cứu mô tả cắt ngang. Đối tượng nghiên cứu là những bệnh nhân được chẩn đoán xác định nhồi máu não cấp trong vòng 24 giờ từ khi khởi phát có NIHSS ≤ 4 điểm, trên 18 tuổi, điều trị tại Bệnh viện Đa khoa tỉnh Yên Bái từ tháng 1/2024 đến tháng 7/2024, theo dõi kết cục lâm sàng sau khi ra viện 03 tháng. Kết quả: Tổng số đối tượng nghiên cứu là 33 bệnh nhân, trong đó tỉ lệ nam/nữ = 1,35/1. Tuổi trung bình: 66.52±12.97, nhóm tuổi trên 45 tuổi chiếm tỉ lệ 90.9%, nhóm tuổi dưới 45 tuổi chiếm tỉ 9,1%. Số bệnh nhân nhập viện 6 giờ - 24 giờ sau khởi phát chiếm tỉ lệ cao nhất 45,5%. Trong các yếu tố nguy cơ, thường gặp nhất là tăng huyết áp và rối loạn chuyển hóa lipid lần lượt là 90,9% và 84,8%, đái tháo đường 15,2% và đột quỵ não cũ 21,2%. Phân loại theo ¹TOAST, nguyên nhân bệnh mạch máu nhỏ chiếm tỉ lệ cao nhất 63,6%, thuyên tắc mạch từ tim chiếm 12,1%. Tại thời điểm ra sau ra viện 03 tháng, bệnh nhân phục hồi tốt có điểm mRS 0 -1 chiếm 87,9%. Bệnh nhân có tiền sử đột quỵ trước đó và hẹp mạch máu lớn có nguy cơ tiến triển nặng và kết quả phục hồi thần kinh kém. Kết luận: Nghiên cứu cho thấy các đặc điểm lâm sàng riêng biệt ở nhóm bệnh nhân nhồi máu não mức độ nhẹ tại Bệnh viện Đa khoa tỉnh Yên Bái với tỷ lệ hồi phục cao, căn nguyên mạch máu nhỏ chiếm phần lớn. Tiền sử đột quỵ não cũ và hẹp mạch lớn là yếu tố tiên lượng nguy cơ tiến triển nặng và kết quả phục hồi thần kinh kém ở bệnh nhân đột quỵ nhồi máu não mức độ nhẹ.
An Assessment of the Extent of Inter-Ethnic Cohesion Among the Border Communities of Kisumu and Nandi Counties, Kenya
Authors: Kida Jacob Keta , Simiyu Ruth 
Published: February 2025

This study assesses the extent of inter-ethnic cohesion among the border communities of Kisumu and Nandi counties, Kenya. The border communities have been experiencing sporadic and recurring ethnic conflicts and tensions for many years. Since 2013-2023, several peace-building strategies have been initiated by several actors to enhance inter-ethnic cohesion among the border communities. Therefore, this study seeks to assess the extent of inter-ethnic cohesion. The theory of primordialism of ethnicity supports the study. The study adopted an explanatory design. The target population are the people who live and work within the Muhoroni and Tinderet Sub-counties. The study population comprised household heads, community leaders, state officers, and non-state actors. The sample size was 320 household heads, community heads, state actors, and non-state actors. The study employed purposive sampling technique to select four wards and eight villages from four wards and simple random to select households. The researcher used questionnaires and interview schedules to collect primary data. Secondary data was collected from journals, books, government and NGO reports, and theses. Statistical Package for the Social Sciences (SPSS) (V.30.1) was used to analyze quantitative data, which provided frequencies and percentages and was presented in tables and figures. Thematic and content analysis methods were used to analyze the qualitative data. Findings on the extent of inter-ethnic cohesion show that despite the high extent of harmony (79%) in the study area, there is a high extent of intolerance (80%) and a low level of trust (57%). The high extent of intolerance and low level of trust are caused by stock theft (34.4%), national politics (27%), boundary dispute (22%), nepotism (9.3%), and youth unemployment (7.3%). However, these communities still interact through intermarriages (85%), shared institutions (62%), and trade (60%). The study concludes that despite the high extent of harmony among the border communities, the extent of trust and tolerance is very low. However, the border communities still interact through social cultural activities, border markets and common schooling. The study recommends that to enhance the ethnic cohesion among the border communities, there is a need for more sociocultural integration in the area.
Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend
Authors: Capozzi Vincenzo , Serrapica Francesco , Rocco Armando , Annella Clizia , Budillon Giorgio 
Published: February 2025

Abstract. This work presents an analysis of historical snow precipitation data collected in the period 1951–2001 in central and southern Apennines (Italy), an area scarcely investigated so far. To pursue this aim, we used the monthly observations of the snow cover duration, number of days with snowfall and total height of new snow collected at 129 stations located between 288 and 1750 m above sea level. Such data have been manually digitised from the Hydrological Yearbooks of the Italian National Hydrological and Mareographic Service. The available dataset has been primarily analysed to build a reference climatology (related to the 1971–2000 period) for the considered Apennine region. More specifically, using a methodology based on principal component analysis and k-means clustering, we have identified different modes of spatial variability, mainly depending on the elevation, which reflect different climatic zones. Subsequently, focusing on the number of days with snowfall and snow cover duration on the ground, we have carried out a linear trend analysis, employing the Theil–Sen estimator and the Mann–Kendall test. An overall negative tendency has been found for both variables. For clusters including only stations above 1000 m above the sea level, a significant (at 90 % or 95 % confidence levels) decreasing trend has been found in the winter season (i.e. from December to February), with −3.2 [−6.0 to 0.0] d per 10 years for snow cover duration and −1.6 [−2.5 to −0.6] d per 10 years for number of days with snowfall. Moreover, in all considered seasons, a clear and direct relationship between the trend magnitude and elevation has emerged. In addition, using a cross-wavelet analysis, we found a close in-phase linkage on a decadal timescale between the investigated snow indicators and the Eastern Mediterranean teleconnection Pattern. For both snow cover duration and number of days with snowfall, such connection appears to be more relevant in the full (i.e. from November to April) and in the late (i.e. from February to April) seasons.
Deep learning Models for Trust management in Social Internet of Things
Authors: Anciline Jenifer J  
Published: February 2025

Introduction: The growing prevalence of IoT has resulted in both human-to-thing(H2T) communication and thing-to-thing(T2T) communication. In recent years, a new paradigm merging IoT with social networks has arisen, termed the Social Internet of Things (SIoT), where devices are not only intelligent but also socially conscious. Trust is an important element in SIoT and it allows reliable automatic communication between items and trust management is also an essential aspect for secure communications between IoT devices, In the dynamic SIoT environment, a traditional trust framework's static or heuristic approach is ineffective.
Objectives: To study the Deep Learning (DL) Models for trust management in SIoT and to suggest a hybrid model to predict the trustworthiness of the IoT devices in SIoT Networks.
Methods: A combined strategy is suggested in this study using Graph Neural Networks (GNN) and Recurrent Neural networks (RNN) to predict the trustworthiness of SIoT using vast high-dimensional data and detect specific trends in social communications.
Results: The finding shows that the hybrid GNN and RNN model outperforms with an accuracy of 91.8% over the standalone GNN and RNN methods.
Conclusions: The integrated model that includes both GNN and RNN techniques gives better results in terms of accuracy, precision, recall, and F1-score over the other methods assessed separately. The ability of deep learning to interpret complex multidimensional data and adapt to the highly dynamic nature of social and physical interaction is significant in maintaining trust within SIoT networks.
Optimization of VM migration and Energy Consumption using Genetic Algorithm
Authors: Harmeet Kaur  
Published: February 2025

Introduction: The substantial energy usage in the cloud computing system is a significant drawback both for the cloud providers along with the cloud service users. In order to decrease the amount of energy used, it is necessary to implement virtualization techniques.
Objectives: this paper employs a GA to optimize the migration of VMs and reduce energy usage in a cloud environment.
Methods: The VM consolidation method effectively handles cloud resources, meeting the needs of both cloud consumers and suppliers. Moreover, it helps in enhancing the efficiency of servers while simultaneously decreasing the excessive energy usage in data canters. Nevertheless, the unnecessary activities of the VM consolidation technique result in inadequate VM selection and improper VM assignment, causing low performance, QoS, and violations of SLAs. Data center management struggles with energy consumption. VM migration and placement works well for this. Data centers require energy-saving solutions without affecting other parameters.
Results: The performance of the proposed method has been evaluated utilizing factors like CPU usage, memory usage, network speed, power usage, and SLA breaches.
Conclusions: The comparative analysis of the proposed approach with existing methods highlights its effectiveness and trustworthiness.
Unfolding the Rise of Direct Selling Formats in India: An Explanatory Analysis
Authors: Aisha Ibrahim Mohammed  
Published: February 2025

The Indian direct selling industry has been analysed using a framework developed from the environmental theory of retail evolution, relationship marketing theory, and Porter's five forces model. The developed heuristic framework provides a basis as to how retail institutions adapt to changes subject to the changes occurring in the firms' environment subject to the constraint that firms in the long run earn profits by maintaining long-term relationships with the consumers such that the so-called consumers turns into the patrons of the company. The identified factors in the firms’ environment are consumers, competitors, suppliers, public policy factors and information technology factors. Through the descriptive analytical analysis, it has been found that direct selling in the Indian context has evolved due to the changes happening in the direct selling’s operational milieu wherein these firms adapt to changes that happening in India’s macro and microenvironment. The opening up of the economy, and changing consumer demographics have been the driving force behind the direct selling industry in India. However, the public policy factors through the enactment of regulations have been a key catalyst that helps the business in protecting consumers' interest, warding off illegal competition, with the support of MSME coupled with advancements in information technology that transformed the business operation whilst ensuring transparency. Though the environment has been conducive to the growth of the direct selling industry, the industry has faced huge setbacks in terms of litigation.
Transformational Leadership Qualities, Performance of School Administrators and Teachers’ Self-Efficacy: Basis for Transformational Leadership Model
Authors: Mari Daisy O. Corral  
Published: February 2025

The purpose of this study is to examine the relationship between transformational leadership and teachers’ self-efficacy through analysing school administrators’ performance - in terms of instructions, research and extension - and quality. The study made use of a combination of the descriptive and correlational methods of research. The descriptive design helped the researcher to characterize the leadership performance of the school administrators and their qualities. The correlational approach was used to determine the magnitude of the relationship between the leadership performances and qualities of the school administrators, and teachers’ efficacy of the participating state universities. The study utilized the descriptive-correlational method as a quantitative research design. It involved participants who were school administrators and regular faculty members of state universities in the province of Cavite, with a total enumeration of 226 participants accounted in the study with the participation of 51 school administrators. Questionnaires were the primary instruments in data gathering which were developed by the researcher. The data collected were analyzed using the use of median, frequency, percentage, Kruskal-Wallis, Friedman’s, and Spearman Rank Correlation Coefficient. The data revealed that as per the level of the following transformational leadership quality of the school administrators, the majority of the participants constitutes Very Satisfactory level of transformational leadership by their leaders and Inspirational Motivation obtained Excellent verbal interpretation, and this implies that participants were satisfied as to transformational qualities of their leaders, with a high regard for Inspirational Motivation. In terms of performance, leaders manifesting high performance in the three-fold areas obviosuly showed Very Satisfacory performance in terms of Instructions, Research and Extension, Over-all results showed that the school administrators’ performance and qualities highly influenced teachers’ efficacy.
Advancements and Challenges in Optimal node localization for Energy-efficient data transmission in IoT assisted Wireless Sensor Network: A Survey
Authors: Surabhi Sushant Sawant  
Published: February 2025

Optimal node localization is a key area of research focused on enhancing energy efficiency and data transmission accuracy within Internet of Things (IoT)-assisted Wireless Sensor Networks (WSNs). Despite advancements in localization methodologies, the field encounters significant challenges, including adapting to dynamic environmental conditions, managing energy constraints, and ensuring scalability across various network topologies. This survey provides a systematic review of around 30 research articles, focusing on the techniques used, challenges faced, and outcomes achieved in node localization for WSNs. By critically examining existing methods such as clustering, routing, and hybrid optimization approaches often integrated with machine learning this research highlights each strategy's strengths and limitations, providing insights into their applicability and effectiveness in real-world scenarios. Ultimately, the survey aims to guide future research toward developing more robust, adaptable, and energy-efficient localization solutions, contributing to enhanced network performance and prolonged sensor lifetimes in IoT-integrated WSN environments.
Integration of AI Functions for Automatic Identification of Morphological Parameters in Medical Images Using MATLAB
Authors: Dafina Xhako  
Published: February 2025

Introduction: Artificial intelligence (AI) is transforming medical imaging by automating complicated and challenging processes with remarkable accuracy. This paper examines the adoption of AI algorithms using MATLAB for the automated recognition of morphological structures in medical imaging.
Methods: This research utilizes advanced machine learning (ML) and deep learning (DL) methods to address essential tasks like image segmentation, feature extraction, and parameter estimation. MATLAB's intuitive interface and powerful computational capabilities make it easy to create and test models for specific medical imaging tasks. Segmentation and parameter prediction are carried out with great accuracy in experiments carried out on publically available datasets, such as brain MRI and lung CT scans. In many instances, the Dice coefficients surpass 0.9. While tackling issues like data quality, model interpretability, and computational efficiency, this study emphasizes the benefits of MATLAB for developing and implementing AI solutions in healthcare.
Results: The results emphasize MATLAB's capability to improve diagnostic accuracy and operational effectiveness in clinical environments, facilitating future advancements in customized medicine. There has to be effective software for automated analysis and interpretation of the ever-increasing amount of medical imaging data.
Conclusions: The purpose of this research is to examine the feasibility of using MATLAB's AI features for the automated detection of morphological parameters in medical images. Here, we compare AI-driven algorithms to more conventional image processing approaches for typical morphological metrics like area, perimeter, shape descriptors, and object recognition, and we find that the former are more accurate and efficient. To verify the efficacy of the suggested AI model, statistical analysis is carried out on a dataset consisting of medical photographs.
PENYAMBUTAN KEDATANGAN KRI DEWA RUCI DI DERMAGA 100 PELABUHAN TRISAKSI BANJARMASIN YANG DIHARIDIRI DIREKTUR BERSAMA TARUNA-TARUNI AKADEMI MARITIM NUSANTARA BANJARMASIN
Authors: Moch. Nurdin  , Edison Edison 
Published: February 2025

KRI Dewaruci telah berusia 64 tahun. Sepanjang rentang usia sejak dia dibuat di galangan kapal Stulcken & Sohns di Hamburg, pada 1952 dan masuk dinas TNI AL pada 1953, sudah ada puluhan komandan kapalnya. sebagian dari para mantan komandan KRI Dewaruci itu berkumpul dan berlayar bersama, dalam pelayaran nostalgia dengan misi istimewa: membicarakan kelangsungan kapal latih TNI AL itu hingga mampu berlayar 100 tahun. Selain pada mantan komandan, juga beberapa mantan perwira pelaksana kapal, perwira-perwira yang pernah bertugas di KRI Dewaruci, dan kalangan sipil yang pernah berkecimpung dengan KRI Dewaruci juga serta.Di antara para mantan komandan KRI Dewaruci yang turut hadir adalah Laksamana Pertama TNI (Purnawirawan) Didin Z Abidin, Laksamana Pertama TNI Gig Sipasulta, dan Kolonel Pelaut Akmal. Sedangkan perwira yang pernah bertugas di KRI Dewaruci yang pernah bertugas di sana dan turut dalam pelayaran ini adalah Letnan Kolonel Pelaut Alfred Daniel dan Mayor Pelaut Pius H. Pelayaran istimewa ini tidak lama, hanya dua malam saja, dan bertolak dari dermaga Madura di Komando Armada Indonesia Kawasan Timur TNI AL pada 15 Agustus lalu.

Metode pelaksanaan dalam rangka Penyambutan kedatangan KRI dewa ruci di Dermaga 100 pelabuhan trisaksi Banjarmasin yang diharidiri Direktur bersama Taruna-taruni Akademi Maritim Nusantara Banjarmasin, sesuai undangan yang diterima sebelum kegiatan berlangsung, dengan demikian, Direktur, salah satu Staf dan Taruna-taruni Akademi Maritim Nusantara Banjarmasin bersiap pada kegiatan penyambutan dari awal, baik adanya sambutan pidato dari Gubernur Kalimantan Selatan, hingga penutupan serta di akhiri dengan dokumentasi pada kegiatan tersebut dan tentunya Kapal yang menjadi sejarah atau Legenda Indonesia.

Pada kegiatan penyambutan kedatangan KRI Dewa Ruci di dermaga 100 Pelabuhan Trisaksi Banjarmasin yang dihadiri Direktur bersama Taruna-taruni Akademi Maritim Nusantara Banjarmasin. Mengikuti dari awal kegiatan hingga proses akhir penyambutan Kedatangan KRI Dewa Ruci tersebut. Adapun hasil dari kegiatan dari proses penyambutan, pidato, hingga dokumentasi bersamaKRI Dewa Ruci bersama Taruna-taruni AAL, selain itu ada sambutan pidato oleh Gubernur Kalimantan Selatan. Kedatangan kapal legendaris dengan julukan Sang Legenda, kata Gubernur yang akrab disapa Paman Birin, menjadi suatu kebanggaan bagi masyarakat Kalsel Babussalam Tampak di atas tiang-tiang kapal, terdapat bendera dari berbagai negara yang sudah disambangi oleh kapal layar tipe Barquentine itu.Diketahui, KRI Dewa Ruci sendiri merupakan kapal latih bagi taruna atau kadet Akademi Angkatan Laut (AAL) yang berbasis di Surabaya. Setiap tahunnya, kadet AAL berlayar menggunakan KRI Dewa Ruci ke berbagai belahan dunia untuk berlatih pelayaran bintang atau disebut Kartika Jala Krida.