bluuebunny/crossref_metadata_2025 huggingface dataset:
COMPLICATIONS ASSOCIATED WITH INTERNAL ILIAC LIGATION IN THE CONTEXT OF SEVERE POST-PERIPARTUM HYSTERECTOMY BLEEDING
Authors: ULLAH S , QAZI Q , KHAN N , KHAN H , SHAHBAZ N
Published: March 2024

Severe post-peripartum hysterectomy bleeding poses a critical threat to maternal health, necessitating swift and effective interventions to ensure favorable outcomes. The main objective of the study is to find the potential complications associated with internal iliac ligation in the context of severe post-peripartum hysterectomy bleeding. This prospective observational study was conducted in the gynecology and obstetrics department of Lady Reading Hospital Peshawar from June 2022 til the required sample size is obtained. The study included women who had significant and profuse post-peripartum hysterectomy bleeding. All women with post-peripartum hysterectomy hemorrhage were identified, focusing specifically on cases where internal iliac ligation was employed as an intervention. The demographic information, including patient age, parity, medical history, and obstetric details, was collected on predesigned proforma. Data was collected from 196 patients. The mean age of the patients was 31.5±4.2 years. About 97% of patients were multiparas, and all patients presented with postpartum hemorrhage (100%). The mode of delivery was vaginal in 89% of cases. It is concluded that internal iliac ligation, while effective in controlling severe post-peripartum hysterectomy hemorrhage, presents a nuanced landscape marked by a low incidence of vascular (1.5%) and ureteric (0.5%) injuries. Consequently, we believe that procedure is worth try in the face of catastrophic uncontrolled haemorrhage, especially in low-income countries.
Data augmentation-based enhanced fingerprint recognition using deep convolutional generative adversarial network and diffusion models
Authors: Liu Yukai
Published: March 2024

The progress of fingerprint recognition applications encounters substantial hurdles due to privacy and security concerns, leading to limited fingerprint data availability and stringent data quality requirements. This article endeavors to tackle the challenges of data scarcity and data quality in fingerprint recognition by implementing data augmentation techniques. Specifically, this research employed two state-of-the-art generative models in the domain of deep learning, namely Deep Convolutional Generative Adversarial Network (DCGAN) and the Diffusion model, for fingerprint data augmentation. Generative Adversarial Network (GAN), as a popular generative model, effectively captures the features of sample images and learns the diversity of the sample images, thereby generating realistic and diverse images. DCGAN, as a variant model of traditional GAN, inherits the advantages of GAN while alleviating issues such as blurry images and mode collapse, resulting in improved performance. On the other hand, Diffusion, as one of the most popular generative models in recent years, exhibits outstanding image generation capabilities and surpasses traditional GAN in some image generation tasks. The experimental results demonstrate that both DCGAN and Diffusion can generate clear, high-quality fingerprint images, fulfilling the requirements of fingerprint data augmentation. Furthermore, through the comparison between DCGAN and Diffusion, it is concluded that the quality of fingerprint images generated by DCGAN is superior to the results of Diffusion, and DCGAN exhibits higher efficiency in both training and generating images compared to Diffusion.
Exploring the potential of data augmentation in poetry generation with small-scale corpora
Authors: Huang Renxiang
Published: March 2024

Poetry generation is a complex task in the field of natural language processing, especially when working with small datasets. Data augmentation techniques have been shown to be an effective way to improve the performance of deep learning models in various tasks, including image classification and speech recognition. Therefore, this study focuses on exploring the impact of four different data augmentation methods - Synonym Replacement, Random Insertion, Random Swap, and Random Deletion - on the performance of poetry generation with a small poetry dataset. The results of the study reveal that Random Insertion performed well in terms of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation (ROUGE), and manual evaluation when compared to other data augmentation techniques. Synonym Replacement performed poorly in all three evaluations. This study confirms the potential value of data augmentation technology in poetry generation tasks and provides innovative perspectives and directions for future research in this area. Data augmentation can be employed to help address the problem of limited data in poetry generation tasks and enhance the efficiency of deep learning models. Future research could focus on exploring more advanced data augmentation techniques and their impact on poetry generation tasks.
Designing a bias-rating news recommendation system
Authors: Liu Siqian
Published: March 2024

Media bias can significantly influence public perception, often subconsciously shaping opinions. To understand and measure this bias, diverse methodologies have emerged. While models from social sciences offer in-depth evaluations, they involve intensive manual analysis. In contrast, computerized models provide speed but often lack depth. This research explores the synergy between these disciplines, aiming to create a robust bias detection tool that combines the meticulousness of social science models with the automation of computer science. Using this interdisciplinary approach, a system was developed to evaluate articles and instantly present a 'bias score' on the user interface. This score offers readers an immediate indication of potential news slant. The research also integrated web crawling techniques into the system, allowing it to identify and recommend alternative articles on analogous subjects. This innovative feature enriches readers' choices, equipping them with multiple narratives for an enriched understanding. In conclusion, this work bridges the gap between depth and speed in media bias detection, offering a novel tool that promotes informed readership. The contribution of this study lies in its interdisciplinary approach and the development of a system that fosters holistic media consumption.
Research on the application of graph neural networks in text classification
Authors: Xu Chuangyu
Published: March 2024

With the rapid development of the Internet and social media, a large amount of text data is constantly generated, and text classification has become an important task. Text classification is an important branch in the field of natural language processing and has attracted the attention of many researchers in recent years. Due to the ease of editing text data, most texts in the network are manually constructed and uploaded by users. Therefore, the standardization of online texts and the classification of texts with different granularity are of great significance in the field of information retrieval. This article introduces the basic concepts of text classification and three text classification methods: knowledge engineering (rule) based text classification methods, traditional machine learning-based text classification methods, and deep neural network-based text classification methods. This article also analyzes the advantages and disadvantages of the three methods. Subsequently, the basic concepts and common models of graph neural networks were explored. An application case of graph neural networks in text classification is provided. This article provides effective suggestions for text classification applications in the field of natural language processing.
Investigating the working principle of the recommending system and designing a personal music recommending system
Authors: Ha Arvin
Published: March 2024

This paper, Investigating the Working Principle of the Recommending System and Designing a Personal Music Recommending System, delves into the intricacies of recommendation systems, with a specific focus on music. It begins by exploring the fundamental principles that underpin recommendation systems.The latter part of the paper presents the design of a novel personal music recommendation system. This system leverages the results of K-means clustering to provide faster personalized music recommendations. It considers various auditory factors such as valence (the musical positiveness conveyed by a track), duration (the length of the track), and energy (a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity). These factors are calculated by Spotify and made available in an open data set. This research contributes significantly to the field by providing a deeper understanding of recommendation systems and proposing an innovative solution for personalized music recommendations. The novelty of this system lies in its use of K-means clustering and the specific auditory factors it considers, which sets it apart from existing systems.
Evolution of the encryption and analysis of algorithm
Authors: Zhao Zichun
Published: March 2024

This paper examines how cryptography has developed from the ancient kingdom to the present and examines what modern humans understand by an acceptable encryption scheme. The significance of encryption is evident; it is typically present in data, banks and governments in offline procedures, or VPNs in online ones. Additionally, the research shows how cryptography manifests itself in the world and highlights the confidentiality and universality of encryption techniques. However, the article also discusses the similarities and differences between pure mathematics and cryptography. It presents the two most widely used encryption techniques in computer science, RSA and Hush, and outlines their benefits to show why these techniques are the most often used as well as how challenging it is to comprehend and apply. It also provides some advice and recommendations to achieve the purpose of improving ability.
Random Forest model-based risk prediction of COVID-19 regional infection
Authors: Li Yang
Published: March 2024

The current prevalence of the COVID-19 pandemic worldwide has posed numerous challenges and questions. To assist governments, medical institutions, and the public in making informed decisions and minimize the risk of further spread of COVID-19, this paper employs the Random Forest model to predict the infection risk within certain regions. The dataset utilized underwent data cleaning and feature engineering, allowing predictions to be made using publicly accessible data such as local basic climate conditions. After conducting performance comparisons with other common machine learning models, including Linear Regression and Decision Tree Regressor, it was found that the Random Forest Regressor model exhibited superior performance across all evaluation metrics, with all error values below 0.05. Notably, the MAE for the Random Forest model was only 0.001089. This strongly suggests that the Random Forest model outperforms the other models used in this task.
NFT auction: Implementing smart contracts for decentralized transactions
Authors: Xiao Boning
Published: March 2024

In the wake of blockchain and Web3 technological advancements, Non-Fungible Tokens (NFTs) have emerged as prominent digital assets within the realms of art, gaming, and virtual commodities. Unlike their traditional counterparts, NFT auctions harness the virtues of decentralization, transparency, and immutability, ushering in a new era for trading artworks and other digital assets. This paper embarks on an exploration, first laying down the foundational principles of blockchain technology and NFTs. A comparative analysis follows, juxtaposing the dynamics of NFT auctions with the modus operandi of traditional auctions. Within the theoretical scaffold, the nuances of decentralization and trust in NFT auctions are elucidated, spotlighting the pivotal role of smart contracts throughout the auction trajectory. The emphasis also gravitates towards transparency and security, two cornerstones ensuring the integrity of the auction process. Diving into the methodology, this section delineates the research blueprint and the techniques employed for program testing. Delving into the practicalities, the discourse meticulously unpacks the architecture and operability of the smart contract, gauging its efficacy through rigorous assessments. Beyond the present scope, the paper ventures to uncover potential applications and horizons awaiting NFT auctions across diverse sectors.
Comparison of transfer-learning for lightweight pre-trained model on image classification
Authors: Zheng Wenhan
Published: March 2024

This paper presents a comparative study of the performance of three convolutional neural network (CNN) architectures - EffcientNet-B0, ResNet-50, and AlexNet - for a given image classification task. The study provides a comprehensive investigation of the training process, hardware configurations, training time, and individual model performance. The investigation also assesses the models suitability for different applications. The findings can help both researchers and practitioners select the most suitable model for their specific needs and applications. The paper provides an analysis of each CNN architecture and discusses their strength and weaknesses. The results demonstrate that EffcientNet-B0 achieves the highest accuracy, but its training performance is not optimal. ResNet-50, on the other hand, exhibits high accuracy with efficient training using transfer learning. Finally, ALEXNET provides a baseline for comparison with traditional CNN designs. The paper also highlights the trade-offs involved in selecting a CNN architecture and highlights their relative advantages and disadvantages. The reader is provided with insights into which CNN architecture is most suitable for specific applications based on their requirements.
An improved BiGAN model for anomaly detection in finance
Authors: Chen Guanda
Published: March 2024

Financial systems play a pivotal role in shaping contemporary society, and the detection of financial anomalies holds immense significance in mitigating the adverse repercussions of market uncertainties on the global economy. In this context, this study presents an innovative LSTM-GANs model, specifically crafted to enhance the detection of anomalies in financial stock markets. The model introduces an "Anomaly Score" as a pivotal metric, which is computed through a combination of factors such as Reconstruction Loss, Latent Space Distance, and Discriminator Score. This composite score provides a quantitative assessment of the anomaly level within the financial data. By applying a predefined threshold to this Anomaly Score, the model efficiently identifies and flags anomalies. In a world where financial markets are increasingly complex and prone to unexpected events, the ability to detect and respond to anomalies swiftly is paramount. This novel LSTM-GANs model offers a promising approach to bolster the accuracy and effectiveness of financial anomaly detection, thereby contributing to the stability and resilience of global financial systems.
Accelerating autonomous vehicles: Harnessing FPGA power for deep learning advancements
Authors: Zhang Yumo
Published: March 2024

In the rapidly developing field of autonomous vehicles (AV), the integration of deep learning algorithms has become the cornerstone for improving vehicle perception and decision-making ability. This study investigates the potential of field-programmable gate arrays (FPGAs) as hardware accelerators for deep-learning tasks in self-driving cars. This study used a Zynq UltraScale+ MPSoC FPGA board from Xilinx, known for its performance and adaptability, and combined it with a high-resolution camera to simulate real-world visual data encountered by AVs. The approach involved implementing a convolutional neural network (CNN) to perform tasks such as object detection, lane detection, and traffic sign classification. The model was quantized and converted to VHDL code using Xilinx Vivado HLS to optimize the deep learning algorithm for FPGA.The results show that the FPGA-based model significantly outperforms the traditional CPU-based model in terms of processing speed and energy efficiency without sacrificing accuracy. This study highlights the critical role of FPGAs in supporting deep learning tasks in self-driving cars and paves the way for safer and more efficient transportation solutions in the future.
A binarization method for logos
Authors: Fan Zhentao
Published: March 2024

In the field of digital image processing, the binarization of logo images presents a significant challenge due to the diversity in their color distribution and graphical structures. Logos, as distinctive visual symbols, are integral to brand recognition and commercial advertising. Traditional binarization methods often struggle with this diversity, leading to difficulties in preserving the original color and details of the images. To address this issue, this paper introduces a novel binarization approach specifically designed for logo images. The method comprises three stages: preprocessing, binarization, and noise removal. In the binarization stage, the Otsu method is adapted from a global to a local thresholding technique, combining both global and local thresholds for each pixel. The efficacy of this method is demonstrated through comparative experiments with logos of varying colors and structures, showing superior performance in maintaining image color and detail restoration over traditional methods. Additionally, the preprocessing and noise removal steps further enhance the method's effectiveness in handling logos with rich background colors and complex details. Overall, this approach proves to be highly adaptable across a wide range of logo types.
Usability Testing pada Aplikasi Kas Berbasis Android dan Teknologi API menggunakan Metode System Usability Scale
Authors: Al Muharom Nurul Ibnu , Suarna Nana , Dana Raditya Danar
Published: March 2024

Aplikasi manajemen kas digunakan untuk menyimpan data transaksi dan membuat laporan kas masuk dan kas keluar yang lebih efektif daripada menggunakan buku. Tetapi, saat ini belum dilakukan pengujian usability sehingga cukup sulit untuk menentukan langkah pengembangan aplikasi  ke depannya. Tujuan penelitian ini adalah mengukur tingkat kebergunaan aplikasi manajemen kas berbasis android menggunakan metode System Usability Scale (SUS)  yaitu 10 pertanyaan kuesioner skala likert yang di sebar kepada responden dengan hasil akhir berupa skor 0-100. Jumlah responden sebanyak 15 orang yang merupakan karyawan CV. Jaya Mukti. Pengujian ini dilakukan untuk mengetahui tingkat kemudahan dan kepuasan pengguna. Hasil dari penelitian memperoleh skor 84,7, skor tersebut menunjukkan tingkat persentil sebesar 96%, Grade Scale  A, Acceptability Ranges masuk dalam kategori Acceptable artinya dapat diterima, serta Adejctive Rating masuk dalam kategori Excellent. Jika dikorelasikan dengan NPS masuk pada kategori promoter artinya pengguna akan merekomendasikan aplikasi. Hasil tersebut menunjukkan bahwa aplikasi dapat diterima oleh pengguna dan sudah sangat baik serta berada di atas standar nilai kegunaan yang sudah ditetapkan. Penelitian ini juga menghasilkan 4 rekomendasi perbaikan berdasarkan hasil jawaban kuesioner sehingga dapat menjadi evaluasi untuk pengembangan aplikasi ke depannya.
Enhanced Sign Language Communication through Deep Learning-based Gesture and Action Recognition and Correction
Authors:   Student , Department of Artificial Intelligence and Data Science,  Bannari Amman Institute Of Technology, Sathyamangalam,, S Jayaprakash
Published: March 2024

Sign language is a crucial form of communication for the hearing impaired, presenting unique challenges for technological interpretation. This project focuses on developing a Sign Language Detection Using Action Recognition (SLDAR) system to address these challenges. Leveraging Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and multimodal fusion techniques, our system aims to accurately detect and recognize sign language gestures in real-time. The project involves collecting and annotating a diverse dataset comprising video, audio, and text data. We then design and train a deep learning model that combines features from these modalities to improve accuracy and robustness.The project involves collecting and annotating a diverse dataset, designing a deep learning model for multimodal fusion, and implementing a user-friendly interface for real-time interaction. The system's performance is evaluated using metrics such as accuracy, precision, and recall. Our goal is to enhance accessibility and communication for the hearing impaired through the development of this advanced sign language recognition system. Keywords:Acoustic Features, Linguistic Context, Mean Opinion Score (MOS), Natural Language Processing, NLP Algorithms, Signal-to-Noise Ratio (SNR), Speech Enhancement, Speech Quality, Telecommunication Systems, Voice Assistants.
RECYCLE AND REUSE OF PLASTER OF PARIS
Authors:   Department of civil engineering   K. K. Wagh Polytechnic, Nashik, Khairnar Nikhil Prashant
Published: March 2024

In this venture we are expecting to decrease the ecological contamination, caused due to visarjan of different idols of God during celebrations. The primary driver behind taking this task is to forestall the contamination in the climate particularly water contamination. Water contamination is the defilement of water bodies for the most part because of human exercises, so it adversely influence its purposes. Water bodies incorporate lakes, streams, sea, supplies and ground water. Pop isn't water dissolvable. Additionally, the paints used to make the symbols are oil paints which comprise of profoundly harmful synthetic compounds and weighty metals that caused water contamination. Thus, the idols made of pop and synthetic substances actually hurts climate. Key Words: Water Bodies, Contamination, POP.
The Impact of Data Analytics and Mining in Transforming the Decision-Making System
Authors:   Jain (Deemed to be University)- Center for Management Studies, Bengaluru, B.K Ms. Sunitha
Published: March 2024

In an increasingly data-driven world, effective decision-making hinges on the ability to use the power of information and technology supporting it. This research paper explores the transformative role of data analytics and mining in shaping the once upon a time decision support systems through a profound understanding and analysis of the existing research. This paper highlights the significance of leveraging data analytics and mining techniques to extract valuable insights from vast datasets. By uncovering hidden patterns and trends within the data, businesses can make informed and strategic choices that drive success and outperform their competitors. The practical applications of data analytics and mining are vast, including domains such as customer relationship management, fraud detection, and market analysis. The paper discusses the various ways in which these techniques enable organizations to obtain a competitive edge in the market by unlocking valuable data-driven insights. Real-world case studies are used to illustrate the tangible benefits of this approach. Overall, the research paper showcases the critical role of data analytics and mining in encouraging a data-driven decision-making culture across the business world. By equipping businesses with the analytical tools to unveil the true potential of their data, this approach paves the way for improved performance, sustained success and can guide organizations towards achieving their long-term objectives. Keywords: Data Analytics, Data Mining, Decision Making, Data, Technology, Information.
Advancements in Precision Agriculture: Integrating Computer Vision for Intelligent Soil and Crop Monitoring in the Era of Artificial Intelligence
Authors:   Parul Institute of Computer Applicaton Parul University Vadodara, Gujarat, India, Boahen Jeffrey Obiri
Published: March 2024

Precision Agriculture has witnessed significant advancements with the integration of computer vision and artificial intelligence (AI) technologies, marking a transformative era in modern farming practices. This research explores the synergies between computer vision and intelligent soil and crop monitoring in the context of precision agriculture. The study aims to contribute insights into the application of advanced technologies for optimizing agricultural processes, enhancing resource efficiency, and improving overall crop yield. Keywords— Precision Agriculture, Computer Vision, Artificial Intelligence, Soil Monitoring, Crop Monitoring, Image Processing, Machine Learning, Deep Learning, Agricultural Technology, Intelligent Farming, Data Analytics, Precision Farming, Sensor Technologies, Agricultural Innovation, Sustainable Agriculture.
Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment
Authors: Pedroza Juan Carlos , Peña Alejandro , Sepúlveda-Cano Lina , Carvalho João Vidal
Published: March 2024

Destabilised approaches have been the primary cause of fatal accidents during the approach and landing phase, as stated in  (Airbus, 2023). The stabilised approach concept is of great importance for the safe operation of an airline during the approach and landing phases (Acarbay & Kiyak, 2020). The elements highlighted in the approach phases are the runway's dry or contaminated condition and length. In the crew, we analyse their competence, recurrence, and fatigue. Another variable is the type of approach, whether it is precision, non-precision or visual. The external conditions of the aerodrome include obstacles, wind, and wildlife—the type of aircraft, whether light, medium or heavy.  Due to the large amount of qualitative information derived from the pilots' experience about risk management in the approach and landing phases, this paper proposes an Analytic Hierarchy Process model (AHP) for threat characterisation and risk analysis to achieve a stabilised approach. The results show that AHP proposed model establishes a new methodology for identifying potential in-flight risks to air operations based on expert criteria, improving the decisions to land at an alternate airport based on qualitative information from expert pilots in the risk management field.
Analysing the Effectiveness of Monetary Transmission Mechanism in Mozambique: A VAR Model Approach
Authors: Bahadur Khalilahmad Mussa
Published: March 2024

This study analyses the effectiveness of monetary transmission mechanism in Mozambique spanning from January 2008 to December 2022, employing a Vector Autoregressive (VAR) model. The analysis focuses on Gross Domestic Product (GDP) and inflation, exploring how these variables respond to changes in monetary policy. The study’s findings underscore a negligible impact of monetary transmission channel variables on GDP. In terms of inflation, the study identifies the existence of interest rate, money, and exchange channel, while credit channel exhibit negligible effect. Variance decomposition and impulse response analysis confirm the transitory nature of monetary shocks on GDP and the comparatively stronger influence on inflation.
Should Serum Levels of Creatine Kinase be Evaluated in Patients with Acne Vulgaris Treated with Systemic Isotretinoin
Authors:   Gazi University School of Medicine Department of Dermatology, Ankara, Turkey, Tamer Funda , Farajsoylu Laman ,   Gazi University School of Medicine Department of Dermatology, Ankara, Turkey, Adisen Esra ,   Gazi University School of Medicine Department of Dermatology, Ankara, Turkey
Published: March 2024

The laboratory tests that should be performed and their frequency during isotretinoin treatment are controversial. We
wanted to investigate muscle and joint pain and laboratory tests in acne patients who received isotretinoin. Between April 2019
and February 2023, serum CK, AST, ALT, and GGT levels were retrospectively evaluated in acne patients before and three months
after systemic isotretinoin treatment. This study included 410 patients. The median serum AST, ALT, and GGT levels significantly
increased, whereas serum CK levels were similar in all patients three months after treatment. 23 (5.6%) patients revealed muscle
or joint pain after treatment. No significant difference was detected in patients with or without pain in the median serum CK,
AST, ALT, and GGT levels after treatment. Isotretinoin treatment at a dose of 10 mg/day was more common in patients with pain
than in those without pain, whereas none of the patients who received isotretinoin 40 mg/day developed muscle or joint pain.
We suggest that routine evaluation of serum CK levels is unnecessary in acne patients treated with isotretinoin. However, muscle
and joint pain may develop even at doses as low as 10 mg/day. Furthermore, monitoring AST, ALT, and GGT levels may be
beneficial in acne patients treated with isotretinoin.
Pyloric-preserving Pancreaticoduodenectomy with Duct to Mucosa Pancreatico-gastrostomy Reconstruction: Long-term Follow-up in a Tertiary Center
Authors:   Baqiyatallah University of Medical Sciences, Tehran, Iran, Najafizadeh-Sari Shahriar , Moghadam Jamal A. ,   Department of General Surgery, Trauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran, Gholizadeh Hamed ,   Department of General Surgery, Trauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran, Ranaei-Kenarsari Alireza ,   Department of Emergency Medicine, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran, Heiat Mohammad ,   Baqiyatallah Research Center for Gastroenterology and Liver Diseases, Baqiyatallah University of Medical Sciences, Tehran, Iran, Raei Mehdi ,   Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran, Manoochehry Shahram ,   Department of General Surgery, Trauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Published: March 2024

Background: Duct to mucosa Pancreatico-gastrostomy (DMPG) is a method for reconstruction of pancreatic mass
following pancreaticoduodenectomy (PD). There are still controversies about the benefits of this surgical technique compared to
the old ones. Objectives: This study aimed to evaluate the long-term outcomes of DMPG reconstruction following PD operation.
Method: Through a prospective observational setting, 164 patients, undergoing PD surgery, with diagnosed pancreatic head or
peri-ampullary cancer, were enrolled. A pylorus-preserving PD and DMPG were done for all patients to reconstruct the pancreatic
mass. Patients were followed up to a mean of 21.06±14.12 months. Demographic data, risk factors, tumoral staging, and
postoperative follow-up data were collected for the analytic study. Results: The mean survival of the patients was 21.06±14.23
months after surgery. DGE (delayed gastric emptying) (34.75%), pancreatic fistula (21.34%), bile duct fistula (7.31%), and
hemorrhage (5.5%) were recorded as the most important complication in patients. Some post-operative complications were
significantly observed in patients with diabetes mellitus (pancreatic fistula, increased amylase, and DGE), Smokers (bile duct
fistula, hemorrhage, and increased Amylase), and the elders (bile duct fistula) (p-value 0.05). Conclusions: Although our results
indicate that DMPG reconstruction is a safe technique, our findings did not confirm the priority of this method over the older
techniques.
O avanço do ensino superior na capital do Amazonas e seu impacto no desenvolvimento da indústria de duas rodas
Authors: Paiva Francisco Canindé de , Harb Antônio Geraldo
Published: March 2024

Este estudo investiga a interconexão entre o avanço industrial e o progresso educacional em Manaus, Amazonas, com foco especial no desenvolvimento do setor de Duas Rodas no período entre 2017 e 2019. O objetivo principal foi avaliar o impacto desse crescimento industrial nos índices de educação superior dos cursos de engenharia através da análise de correlações e tendências. A abordagem metodológica utilizada foi de caráter descritiva e quantitativa, fundamentada em dados do Caderno de Indicadores de Desempenho do Polo Industrial de Manaus (PIM), de 2015 a 2020, publicado pela Superintendência da Zona Franca de Manaus, além de estatísticas sobre o número de estudantes matriculados em cursos de engenharia no triênio 2017/2019. Os resultados obtidos demonstraram diferenças estatisticamente significativas entre as variáveis estudadas, assim como correlações relevantes. Duas variáveis econômicas demonstraram ter uma relação significativa com o aumento no número de estudantes nos cursos de engenharia analisados. Esse achado sugere que o crescimento do número de matrículas nesses cursos está associado ao avanço de ambas as variáveis econômicas. Esses resultados são de grande relevância para os tomadores de decisão, indicando que a sinergia entre o setor industrial e educacional pode gerar benefícios mútuos. Portanto, esse estudo contribui significativamente para a compreensão da relação entre o desenvolvimento do setor de Duas Rodas e a evolução dos indicadores educacionais no ensino superior, oferecendo insights valiosos para o planejamento estratégico da região.
Relato de experiência de ensino em Unidade Básica de saúde: uma abordagem transformadora
Authors: Ramalho Elyakym Alvarenga Terto Vieira , Schneweiss Elyssama Alvarenga Ramalho , Sales Vitoria Laiza Sousa , Aquino Marina Braga Santos Pessoa de , Aquino Aleuda Cartaxo Moura Rodrigues de , Rodrigues Bruna Rachel de Oliveira , Barreto Giuliana Porto , Brito Jonas Lourenço Freire de
Published: March 2024

Introdução: Este relato descreve uma experiência de ensino em uma Unidade Básica de Saúde (UBS) em Bayeux, Paraíba, onde alunos participam de atividades de atendimento em saúde e ensino. A Estratégia de Saúde da Família (ESF) é um modelo de atenção primária que visa à reorganização da atenção básica no Brasil de acordo com os preceitos do Sistema Único de Saúde (SUS). Objetivo: Este relato tem como objetivo compartilhar a experiência de ensino em uma UBS, destacando suas atividades e impacto na formação dos alunos. Método: Este relato de experiência é fundamentado no método de observação sistemática da realidade. Os dados foram obtidos por meio da experiência pessoal dos preceptores, reflexões e observações sobre a prática clínica e o ensino dos internos em medicina. Resultados e discussões: A experiência na UBS foi fundamental para o desenvolvimento de habilidades e competências essenciais para a prática médica. Durante o período de internato, os alunos puderam aprimorar habilidades técnicas, como a realização de exames físicos, a interpretação de exames laboratoriais e a elaboração de planos de tratamento. Além disso, a interação constante dos alunos da unidade com pacientes e profissionais de saúde permitiu aos mesmos desenvolver habilidades interpessoais, como a comunicação eficaz e a empatia. Considerações finais: A experiência de ensino, demonstrou ser uma oportunidade valiosa para a formação dos alunos de medicina. Os alunos puderam aplicar os conhecimentos teóricos adquiridos em sala de aula, desenvolver habilidades técnicas e interpessoais essenciais, compreendendo a importância da atenção primária à saúde através da aplicação prática desse conhecimento em um ambiente real. A experiência na UBS permitiu um entendimento da realidade da saúde no Brasil e a importância do cuidado centrado no paciente.
Potential Vulnerability of Natural Populations of Camu-camu (Myrciaria dubia) to Anthropogenic Stressors in Southwestern Amazon
Authors: Leandro Raimundo Cajueiro , Chagas Edvan Alves , Feitosa Izabela de Lima , Aragón Susan
Published: March 2024

One economically promising Amazonian species is camu-camu (Myrciaria dubia) which fruits have the highest content of vitamin C recorded, with a high potential for applications on the food, supplement and cosmetic industry and which can be a cornerstone for agroforestry initiatives for Amazonian peasants. Camu-camu has an Amazon wide distribution although most studies and collections have occurred on the Central and Western Amazon. The aim of this study is to assess the distribution and potential vulnerability of camu-camu populations in the state of Rondônia, Brazil, the southern limit of its distribution, which exhibit a drier climate.  We use data recorded in herbaria and a bioprospecting expedition and data on anthopogenic stressors, estratified at the municipal level, like fire events, deforestation and dams. Camu-camu records occur preferentially in the Central and Northern part of the state, however most of the collections are around cities, major rivers and roads, showing a strong collector bias. Municipalities with camu-camu records suffered higher rates of deforestation and show higher occurrence of fire events and planned dams than municipalities without camu-camu records. Camu-camu populations in Rondônia are thriving on drier conditions and may be more adapted for future prevalent conditions for the Amazon under climate change. These adaptations may be useful for future domestication efforts.  We call for an increasing effort of collecting and salvaging camu-camu populations on human dominated landscapes and to encourage participatory conservation with local farmers, for an ex-situ conservation on rural landscapes, especially under the prospect of climate change.
A greve política e seu tratamento jurídico no Brasil
Authors: Leite Carlos Henrique Bezerra , Lucena Filho Humberto Lima de , Linhares Renan de Oliveira Lima
Published: March 2024

A greve, conforme prevê o artigo 9° da Constituição Federal, é direito assegurado aos trabalhadores, cabendo a estes decidir sobre a oportunidade de exercê-lo e os interesses que devem por meio dele defender, impostos limites apenas no que diz respeito aos abusos porventura cometidos. O presente artigo dedica-se ao estudo das greves por motivação política, levando à compreensão da repercussão dos movimentos paredistas no âmbito do Direito Coletivo do Trabalho, bem como se debruça sobra a análise de suposta abusividade de tais manifestações. A pesquisa observa o método lógico-dedutivo, operacionalizado pelo auxílio da revisão bibliográfica, posicionamentos jurisprudenciais e legislação aplicável. Como resultado, nota-se que, embora o direito à greve seja reconhecido e protegido pelo texto constitucional, o TST frequentemente impõe restrições ao seu exercício. Como conclusão, compreende-se como necessária a regulamentação da matéria no sentido de estabelecer claramente eventuais limites relacionados à motivação dos movimentos paredistas e suas eventuais ilegalidade.
RESGATE NO SÍTIO ARQUEOLÓGICO TAQUARA I EM CAAPORÃ – PARAÍBA
Authors: Mendes Junior Valmir Manoel , Fontes Mauro Alexandre Farias , Viana Willian Carboni
Published: March 2024

Antes da colonização, populações nativas do tronco linguístico Tupi habitavam a região litorânea da Paraíba, como, por exemplo, os Tabajara ao sul, os Potiguara ao norte e os Cariri em direção ao semiárido. Outras populações, como os Goitacazes, Aimorés e Tremembés ocupavam áreas costeiras, chamadas de Tapuias pelos Tupis. No século XVII, colonos europeus chegaram à Paraíba, inicialmente para proteger a região contra invasões francesas exploradoras de pau-brasil e depois para desenvolver a indústria açucareira, além da agricultura e pecuária no agreste e sertão. Caaporã, habitada por grupos Tabajara e Potiguara, foi palco de encontros entre portugueses e indígenas no século XVI, com disputas territoriais. A introdução do trabalho escravo africano fortaleceu a produção açucareira na região. Caaporã se tornou município por volta de 1768, com a construção de moradias ao longo da estrada que ligava Goiânia às praias de Pitimbu e Acaú (litoral paraibano). Este artigo objetivou apresentar os resultados do programa de resgate no sítio Taquara I, em Caaporã, buscando a aquisição de informações e produção a conhecimento sobre os processos de ocupação do Nordeste brasileiro por meio da cultura material. Os achados, no sítio Taquara I, incluem vestígios pré-coloniais e coloniais, como fragmentos de cerâmica tupi e louças faianças portuguesas, que remontam, respectivamente, desde o período pré-colonial aos séculos XVI ao XIX.
POLITICAL AND ECONOMIC ASPECTS OF INTEGRATED URBAN WATER RESOURCES MANAGEMENT (IUWRM) IN SEMARANG CITY INDONESIA
Authors: Budiati Lilin , Supriyadi  , Elizabeth Misbah Zulfa
Published: March 2024

Purpose: This study aims to find out the aspects of politics and economics of integrated urban water resources management in Semarang City and their impact on the practices of qualities of water resources management.
 
Methods: This research used the qualitative method and field research approach. The focus data are the regulation and the implementation of water resources management in Semarang City Indonesia. The data was drawn from documents and interview with some resource persons.
 
Results and Conclusion:  The study found that the city government, which should carry out the function of conserving water resources, actually polluted the Kaligarang River through one of its institutions: Local Water Drinking Company, “Tirta Moedal”. This company disposes of waste sludge containing aluminum metal directly into the river without any treatment processes that impacted in pollution in the river and causing siltation of the river downstream.
 
Research implications: the enactment of the comprehensive and integrated water resources management will has a positive impact on the practices of water resources management in Semarang specifically and Indonesia and even world countries generally. The implementation of comprehensive and integrated water resources management will also support the achievement of the sustainable development Goal.
 
Originality/value: Semarang City government must be supported to arrange a comprehensive and integrated water resources management (WRM) policy. There must be a clear legal law for the water resources management.
Wind Load on A Triangular Cross-Section Tall Building Using Ansys
Authors: Saxena Vaibhav , Verma Dr. Astha
Published: March 2024

Due to the scarcity of land these days, there is a growing need for tall straight buildings. With this growing need, architectural planning is becoming more and more unusual as these tall buildings are proposed which makes them very airy. This requires analysing air volume in several buildings and in response to structural disruption due to the presence of other structures next to it. This paper is focused on observing variance in the distribution of pressure on different faces of a triangular plan-shaped tall building and also the velocity distribution. ANSYS CFX is utilized for the analysis of the variance of pressures distribution.
VOLUNTEER FIRE BRIGADES IN THE CONTEXT OF SHAPING THE SAFETY CULTURE OF THE LOCAL COMMUNITY ON THE EXAMPLE OF THE RURAL MUNICIPALITY OF TOMASZÓW MAZOWIECKI
Authors: Wojciechowski Mateusz , Wojakowska Monika
Published: March 2024

In times of contemporary challenges and threats, the aspect of building social resilience throughthe formation of the safety culture, especially at a local level, is of particular importance. Theprocess of its shaping tends to differ in each community. However, the source of success is theopenness and involvement of all actors in a given community (citizens, local authorities, safetyinstitutions and rescue entities or non-governmental organisations). One of the critical and highlycommitted bodies in local communities, especially rural municipalities, are the Volunteer FireBrigades (VFBs). The authors of the article undertook research to determine the extent to whichthe functioning of VFBs influences the shaping of the safety culture of local communities on theexample of the rural municipality of Tomaszów Mazowiecki. The article presents the results ofresearch carried out by means of a diagnostic survey among the inhabitants of this commune. It hasbeen shown that the activity of VFBs is very highly rated and has a significant impact on increasingthe sense of security of the local community. The local community appreciates the openness andinvolvement of the local VFB in various dimensions of functioning of the Tomaszów Mazowieckirural municipality. An important result of the research are also suggestions and recommendationsfor improving the functioning of local VFB units with aim to shape the safety culture in all itsdimensions - organisational, spiritual and material.
NAVIGATOR PREPARATION DURING SPRAYING BY UAVS
Authors: Janosz Piotr , Fellner Andrzej , Fellner Radosław , Kułakowski Marek
Published: March 2024

The article presents the results of research on the implementation of navigator preparation duringagricultural spraying, conditioning the safe and precise performance of the task. This assumptionwas confirmed during spraying with unmanned aerial vehicles carried out in 2021–2023. Theexperience gained and conclusions enabled the development of a concept of initial and directnavigational preparation for unmanned aircraft systems performing spraying. It is also possibleto use this algorithm to perform deactivation by drones. The results obtained from the conductedaerial tests (within two scenarios: agricultural spraying and decontamination) have also shown thatthe risk analysis methodology recommended by EASA (SORA) entails a number of limitations andcannot be applied during spraying as it causes gaps in safety management. Therefore, a proprietaryEPEP risk analysis method has been developed specifically for spraying, which allows the pilot,the operator of an unmanned aircraft, to perform a risk analysis and manage it accordinglyimmediately before performing the task, compensating or minimizing the hazards that should beat an acceptable level before spraying.
El desarrollo humano y su incidencia en el desarrollo local de los adolescentes de Comuna Febres Cordero 2021-2022
Authors: Guale-Flores Glenda Mercy , Bojorque-Pazmiño Jorge Erick
Published: March 2024

El presente estudio tiene como finalidad conocer la importancia que tiene el desarrollo humano desde los adolescentes y su incidencia en el aporte al desarrollo local de la comuna Febres Cordero, la misma que identifica desde las variables: educación, salud y seguridad humana, cómo estos elementos contribuyen al desarrollo y desenvolvimiento del ser humano, componentes que apoyan de manera positiva en su formación, desplegando en ellos sus potencialidades, que servirá para buscar estrategias y soluciones que permitan alcanzar una sociedad más equitativa y sustentable. La metodología utilizada es de enfoque de estudio cualitativo, no experimental y de corte transversal, el instrumento que se utilizó fue la entrevista la que se realizó con adolescentes, permitiendo establecer importantes resultados dentro de la familia y comunidad, los que permiten sugerir cambios dentro de los hogares, fomentar los valores, crear espacios de diálogos y cambios en los patrones culturales, porque los hijos en la mayoría de casos quiere seguir el ejemplo de sus padres, y que las autoridades fomenten espacios de capacitación para los padres y fortalecer el desarrollo y preparación de sus hijos.

Palabras claves: Desarrollo humano, desarrollo local problemas sociales, desigualdad social, comportamiento, responsabilidad social.