bluuebunny/crossref_metadata_2025_split huggingface dataset:
En-PaFlower: An Ensemble Approach using PSO and Flower Pollination Algorithm for Cancer Diagnosis
Authors: Senapati Sudhir Kumar , Shrivastava Manish , Mahapatra Satyasundara 
Published: September 2023

Machine learning now is used across many sectors and provides consistently precise predictions. The machine learning system is able to learn effectively because the training dataset contains examples of previously completed tasks. After learning how to process the necessary data, researchers have proven that machine learning algorithms can carry out the whole work autonomously. In recent years, cancer has become a major cause of the worldwide increase in mortality. Therefore, early detection of cancer improves the chance of a complete recovery, and Machine Learning (ML) plays a significant role in this perspective. Cancer diagnostic and prognosis microarray dataset is available with the biopsy dataset. Because of its importance in making diagnoses and classifying cancer diseases, the microarray data represents a massive amount. It may be challenging to do an analysis on a large number of datasets, though. As a result, feature selection is crucial, and machine learning provides classification techniques. These algorithms choose the relevant features that help build a more precise categorization model. Accurately classifying diseases is facilitated as a result, which aids in disease prevention. This work aims to synthesize existing knowledge on cancer diagnosis using machine learning techniques into a compact report. Current research work aims to propose an ensemble-based machine learning model En-PaFlower using Particle Swarm Optimization (PSO) as the feature selection algorithm, Flower Pollination algorithm (FPA) as the optimization algorithm with the majority voting algorithm. Finally, the performance of the proposed algorithm is evaluated over three different types of cancer disease datasets with accuracy, precision, recall, specificity, and F-1 Score etc as the evaluation parameters. The empirical analysis shows that the proposed methodology shows highest accuracy as 95.65%.
A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications
Authors: V. Abilasha , A. Karthikeyan 
Published: September 2023

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime.
A Hybrid Multi-user Cloud Access Control based Block Chain Framework for Privacy Preserving Distributed Databases
Authors: Krishna Ch. Nanda , Bharati K.F. 
Published: September 2023

Most of the traditional medical applications are insecure and difficult to compute the data integrity with variable hash size. Traditional medical data security systems are insecure and it depend on static parameters for data security. Also, distributed based cloud storage systems are independent of integrity computational and data security due to unstructured data and computational memory. As the size of the data and its dimensions are increasing in the public and private cloud servers, it is difficult to provide the machine learning based privacy preserving in cloud computing environment. Block-chain technology plays a vital role for large cloud databases. Most of the conventional block-chain frameworks are based on the existing integrity and confidentiality models. Also, these models are based on the data size and file format. In this model, a novel integrity verification and encryption framework is designed and implemented in cloud environment. In order to overcome these problems in the cloud computing environment, a hybrid integrity and security-based block-chain framework is designed and implemented on the large distributed databases. In this framework,a novel decision tree classifier is used along with non-linear mathematical hash algorithm and advanced attribute-based encryption models are used to improve the privacy of multiple users on the large cloud datasets. Experimental results proved that the proposed advanced privacy preserving based block-chain technology has better efficiency than the traditional block-chain based privacy preserving systems on large distributed databases.
Image based Seen Detection in Real Time Video Interpretation for Surveillance Systems using Support Vectors Machine
Authors: Suryanarayana G. , Prakash K LNC. , Aruna E R , Nagaraj Seema , Swapna N. 
Published: September 2023

People that are perpetually hunting for knowledge will benefit from data acquisition. The early phase in video data acquisition is splitting the video into images. Many images are tiny and don't reveal a lot about the picture's information. Scene boundary identification, or video segmentation into action sequences, enables a more complete comprehension of the image sequence by classifying images based on comparable visual content. The purpose of this article is to discuss video scene recognition, particularly video structure extraction for pattern comparison with significant properties. The article designed and developed a methodology that would include stages for image collection, detecting commonalities among frames, selecting important frames, and detecting the time at where the relevant frame is identified. The pictures are generated by Python's OpenCV and scene classification metrics are used to assess the method. As assessed by numerous parameters, the findings shows that scene identification and accuracy are considerable. Furthermore, we investigated and researched contemporary identification and assessment techniques. Moreover, we have tested extensively our research framework on a variety of publicly available event video databases, and these outperformed several futuristic techniques. The outcomes of this research can be utilized to generate real-time definitional video assessments.
The effect of academic stress on lifestyle habits among medical students
Authors: Al Mohsen Zahra 
Published: September 2023

Stress plays a role in altering people's lifestyles. When individuals experience stress and its associated pressures and anxiety, they often respond by engaging in unhealthy behaviors that can have a negative impact on their health. Assessing the impact of perceived stress is crucial in motivating students to adopt positive health behaviors as long-term coping strategies.Study the link between perceived stress and lifestyle behaviors among medical students. Additionally, to explore how health-related behaviors impact the association between perceived stress and lifestyle in the same group of medical students.: To investigate the impact of perceived academic stress on the lifestyle habits of the medical students and to explore how health-related lifestyle factors mediate the relationship between increased perceived stress and changes in lifestyle. Perceived stress will serve as the independent variable in this non-experimental, descriptive cross-sectional study, where the focus is on observing the effects of academic stress on the lifestyle habits of the participants.Significant association between levels of stress and both real change of lifestyle and perceived change of lifestyle risk factors were increased.Promoting positive health behaviors among students for coping purposes is crucial. By helping young individuals develop these coping techniques for handling stressful situations, we offer them the chance to enhance their appearance, boost body image and self-esteem, improve academic and work performance, lower the risk of depression, and ultimately enhance their overall quality of life.
A diversidade de vínculos de trabalho nas cooperativas portuguesas
Authors: Fernandes Tiago Pimenta 
Published: September 2023

En derecho cooperativo, son varios los tipos de vínculos que pueden establecerse entre la cooperativa y el prestador, lo que da lugar a una multiplicidad de niveles de protección social de este último. Internamente, consideraremos la labor de gestión realizada por el miembro del órgano de administración de la cooperativa, así como, en el caso de las cooperativas de trabajo asociado, la figura del cooperativista de trabajo asociado, entendido como aquel que entra a formar parte de la cooperativa a través de la prestación de una determinada actividad. En cuanto a las relaciones con terceros, la cooperativa también podrá celebrar un contrato de trabajo, un contrato de prestación de servicios o incluso un contrato voluntario, y en cada uno de estos casos se aplicará el marco legal respectivo.
Recibido: 17 mayo 2023Aceptado: 12 junio 2023
Clinical case of catheter-directed thrombolysis in cancer associated pulmonary embolism
Authors: Parkhomenko S. I. , Glebovskaya T. D. , Malikov K. N. , Zubarev D. D. , Alekseeva D. V. , Simakova M. A. 
Published: September 2023

Pulmonary embolism (PE) associated with malignant neoplasms is a frequent complication of the oncological process and leads to a decrease in survival and quality of life of these patients. In some cases, pulmonary embolism can become the debut of a current active oncological disease, which requires increased cancer alertness in patients with PE without clear predisposing factors, especially in cancer risk groups.The article demonstrates a clinical case of an individualized approach to choosing an interventional strategy in a comorbid patient with high-risk PE. The tactics of active oncological screening made it possible to confirm a pulmonary embolism against the background of current prostate cancer.
Rs401681 and rs402710 polymorphisms of <i>CLPTM1L</i> gene in cancerous and healthy lung tissues
in patients with lung adenocarcinoma
Authors: Żywiec Joanna , Rydel Mateusz , Drozdzowska Bogna , Klimczyk Katarzyna , Kasperczyk Janusz , Czyżewski Damian 
Published: September 2023

Wstęp<i></i>Poszukiwanie czynników wpływających na przeżycie chorych z nowotworami płuc jest stale aktualne. Takim potencjalnym czynnikiem jest polimorfizm genu <i>CLPTM1L</i> (<i>cleft lip and palate transmembrane 1-like</i>), włączony w proces karcynogenezy. Celem pracy była ocena rozkładu genotypów i alleli wybranych polimorfizmów genu <i>CLPTM1L</i> – rs401681 i rs402710 – w tkance zmienionej nowotworowo i w tkance zdrowej płuc u chorych z gruczolakorakiem płuca oraz ich związku z przeżyciem chorych.Materiał i metodyBadaniami objęto 133 chorych w wieku ujawnienia nowotworu płuca wynoszącym średnio 65 lat, u których w przeszłości dokonano usunięcia gruczolakoraka płuc. Z zabezpieczonych w parafinie próbek tkanki zdrowej płuc i z tkanki zmienionej chorobowo wyizolowano materiał genetyczny – kwas deoksyrybonukleinowy (DNA) – oraz przeprowadzono genotypowanie polimorfizmów <i>CLPTM1L</i>. Uzyskane wyniki poddano analizie wraz z danymi demograficznymi, wywiadem dotyczącym palenia tytoniu, wywiadem rodzinnym obciążonym nowotworowo, stadium choroby w klasyfikacji TNM (<i>tumor, node, metastasis</i>), zaawansowaniem klinicznym nowotworu i czasem przeżycia chorych.WynikiŚredni czas obserwacji wynosił 44,5 miesiąca. Chorzy, którzy zmarli, żyli średnio 22,6 miesiąca od czasu postawienia diagnozy nowotworu. Nie stwierdzono znamiennych różnic pomiędzy rozkładem genotypów ani alleli w tkankach chorej i zdrowej płuc oraz ich związku z przeżyciem chorych. Czynnikami wpływającymi na przeżycie chorych były wiek w czasie postawienia diagnozy nowotworu, kategoria N w klasyfikacji TNM oraz wysokie zaawansowanie kliniczne nowotworu.WnioskiNie stwierdzono związku pomiędzy zmiennością polimorficzną rs401681 i rs402710 w tkance chorej i zdrowej płuc a przeżyciem chorych.
Algoritma Apriori Dalam Identifikasi Pola Pembelian Konsumen Pada Produk Minuman
Authors: Nisa Vita Choirul , Khasanah Fata Nidaul 
Published: September 2023

Competition between companies is getting tougher and entrepreneurs indirectly need a better product marketing strategy. Inventory management system is a very popular business in Indonesia, especially in the beverage industry. Related to inventory, there is a technique in the development of science today, one of which is data mining techniques or mining techniques. In data mining, a priori algorithms contain a type of association rules that aim to find interesting relationships between combinations of elements hidden within the dataset. The application of a priori algorithm in this study can help Pekopen tavern managers find the right consumer buying behaviour . So that it can be used as material for business decision-makers to determine marketing strategies and optimize sales of menu variants, especially for several types that are in great demand. These results are used to find new information to determine a better product marketing strategy. Data processing using apriori algorithm is carried out by conducting the highest frequency analysis based on the minimum support value followed by determining the association rules based on the confidence value and then continued with the evaluation process through determining the lift ratio. There are 2000 sales transaction data processed from the data processing process obtained from a combination of itemset {Chizu Redvelvet, Cokolateh} with a support value of 40% and a confidence value of 67%.
Cyber Security Logical and Probabilistic Model of a Critical Infrastructure Facility in the Electric Energy Industry
Authors: Alekseichuk Lesia , Novikov Oleksii , Yakobchuk Dmytro , Rodionov Andrii 
Published: September 2023

In the work, a cyber security logical and probabilistic model of a critical infrastructure facility in the energy sector was developed and investigated. The cyber security logical and probabilistic model describes the development of adverse events that arise in the Industrial Control System of the electrical network from the realization of possible threats from cyberspace, such as attacks on the protection system through the corporate network, connection through a modem and wireless connection. The resulting model is based on sequentially developed structural, logical and probabilistic models.
The field of use of the developed model is automation systems for designing information protection systems or designing trajectories of attacks on these systems. The model was also applied to study the sensitivity of the probability of the development of adverse events to variations in the probability of realization of possible threats to the system.
Financial Knowledge and Finance Behaviors in Latin America and its Relationship with the COVID-19 Pandemic Period
Authors: Sandoval Juan S. , Collazos María , Sarmiento Julio , Cayón Edgardo 
Published: September 2023

Abstract
Governments worldwide conceive financial education as a crucial tool for enhancing the financial well-being of families. However, the relationship between financial knowledge and financial behaviors remains inconclusive, particularly in developing countries where a limited number of studies have explored this connection. This study employed a subjective and an objective measure of financial knowledge and assessed 16 financial behaviors of participants from Argentina, Colombia, Ecuador, Mexico, and Peru. Out of these 16 financial behaviors, 14 have a relationship with at least one of the two measures. This study found positive correlations between financial knowledge and various financial behaviors, including planning behaviors, acquisition of formal financial products, willingness to assume risks, seeking financial advice, and cautious management of their financial products. The relationship between the acquisition of informal financial products was positive with the objective financial knowledge measure but negative with the subjective measure. The identification of causal relationships proved challenging and often yield inconclusive results due to identified endogeneity issues and the presence of weak instruments. In general, during the COVID-19 period, participant displayed increased prudency in their financial practices and managing their products. This effect was larger among participants with higher levels of financial knowledge. Future research in Latin America should incorporate the distinction between financial literacy and financial knowledge, explore qualitative research designs, and evaluate the effectiveness of financial educational programs.
JEL classification codes: G51, G53
Assessment of Depression and Internalized-Stigma among Adult Asthma Patients in Bangladesh
Authors: Ahmed-Chowdhury Saquib , Ahmad Sohail , Sarker Md. Moklesur Rahman , Ismail Nahlah Elkudssiah 
Published: September 2023

Abstract
Objective: Suboptimal asthma control among patients is associated with psychosocial factors, including depression and stigma, hindering effective asthma management. This study aims to assess depressive symptoms and internalized stigma among adult asthma patients while investigating their relationships with sociodemographic and asthma-related medical factors.
Methods: In this cross-sectional study, 325 adult asthma patients (aged > 18 years old) were recruited from the National Asthma Centre in Dhaka, Bangladesh, using a researcher-administered questionnaire and convenience sampling. The questionnaire included sections on sociodemographic characteristics, medical data, the 9-item Patient Health Questionnaire (PHQ-9) to assess depressive symptoms, and a 22-item stigma scale to assess internalized stigma. Data were analyzed using descriptive and inferential statistics.
Results: The majority of participants were aged 18-40 years (54.2%), male (53.5%), from rural areas (50.8%), with a monthly family income of <US$250 (55.1%), and diagnosed with asthma for >5 years (46.5%). The mean PHQ-9 score was 7.36 (±6), indicating mild depressive symptoms, and the internalized stigma score was 62.2 (±10.26), indicating moderate internalized stigma. Depression and stigma varied significantly across several factors, including age, education, ED visits, hospitalizations for asthma, number of asthma medicines, home nebulizer use, PEF rate, BMI, comorbidities, and asthma symptom control (p<0.05). Stigma was correlated with depression and negatively correlated with age and years since asthma diagnosis (p<0.01).
Conclusion: This study highlights associations between depressive symptoms, internalized stigma, and various sociodemographic and medical factors among asthma patients. Notably, stigma was higher among younger adults and recently diagnosed patients. Effective interventions are needed to mitigate stigma and depression in this patient population.
Impact of Nonpharmaceutical Interventions during COVID-19 on Future Influenza Trends in Mainland China
Authors: Liu Xiaofan , Peng Ying , Chen Zhe , Jiang Fangfang , Ni Fang , Tang Zhiyong , Yang Xun , Song Cheng , Yuan Mingli , Tao Zhaowu , Xu Junjie , Wang Ying , Qian Qiong , Ewing Rob M. , Yin Ping , Hu Yi , Wang Weihua , Wang Yihua 
Published: September 2023

Abstract
Background
Influenza is a common illness for its high rates of morbidity and transmission. The implementation of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic to manage its dissemination could affect the transmission of influenza.
Methods
A retrospective analysis, between 2018 and 2023, was conducted to examine the incidence of influenza virus types A and B among patients in sentinel cities located in North or South China as well as in Wuhan City. For validations, data on the total count of influenza patients from 2018 to 2023 were collected at the Central Hospital of Wuhan, which is not included in the sentinel hospital network. Time series methods were utilized to examine seasonal patterns and to forecast future influenza trends.
Results
Northern and southern cities in China had earlier outbreaks during the NPIs period by about 8 weeks compared to the 2018-2019. The implementation of NPIs significantly reduced the influenza-like illness (ILI) rate and infection durations. Influenza B Victoria and H3N2 were the first circulating strains detected after the relaxation of NPIs, followed by H1N1 across mainland China. The SARIMA model predicted synchronized H1N1 outbreak cycles in North and South China, with H3N2 expected to occur in the summer in southern cities and in the winter in northern cities over the next 3 years. The ILI burden is expected to rise in both North and South China over the next 3 years, with higher ILI% levels in southern cities throughout the year, especially in winter, and in northern cities mainly during winter. In Wuhan City and the Central Hospital of Wuhan, influenza levels are projected to peak in the winter of 2024, with 2 smaller peaks expected during the summer of 2023.
Conclusions
In this study, we report the impact of NPIs on future influenza trends in mainland China. We recommend that local governments encourage vaccination during the transition period between summer and winter to mitigate economic losses and mortality associated with influenza.