bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Integration of CNG Engine and Battery-Powered Plug-In Electric Vehicle with In-Wheel Motor and Rooftop Solar Panel System for Green commuting
Authors: KARTHIK MURI 
Published: February 2024

Abstract
The increasing concerns about environmental sustainability and the depletion of fossil fuels have propelled the automotive industry to explore innovative solutions for cleaner and more efficient transportation. In this context, this research paper proposes a concept for a hybrid vehicle that integrates a compressed natural gas (CNG) engine with a battery-powered plug-in electric vehicle (BEV), utilizing an in-wheel motor(s) and rooftop solar panel system. The hybridization of CNG and electric power offers a synergistic approach that combines the benefits of both technologies. The CNG engine serves as a range extender, providing additional power when the battery charge is depleted, thus addressing the issue of range anxiety associated with electric vehicles. Moreover, CNG combustion produces lower emissions compared to conventional gasoline engines, contributing to improved air quality and reduced greenhouse gas emissions.
The integration of in-wheel motors enhances the vehicle's efficiency and maneuverability by eliminating the need for traditional drivetrain components such as transmissions, driveshafts, and differentials. This distributed propulsion system enables precise torque control and regenerative braking, further optimizing energy utilization and enhancing driving dynamics. Additionally, the incorporation of a rooftop solar panel system supplements the vehicle's energy supply by harnessing renewable solar energy, reducing reliance on grid electricity and extending driving range. The solar panels are strategically integrated into the vehicle's design to maximize exposure to sunlight while maintaining aerodynamic efficiency.
Overall, this research presents a comprehensive approach towards sustainable transportation by combining multiple advanced technologies in a single vehicle platform. The proposed hybrid CNG-BEV with in-wheel motors and rooftop solar panels offers a promising solution to mitigate environmental impact, reduce dependence on fossil fuels, and promote the adoption of renewable energy in the automotive sector.
Synthesis, characterization and electrical properties of polyvinyl chloride doped with zinc oxide nanoparticles
Authors: Al-Shawabkeh Ali F. , Shaheen Adel A. , Elimat Ziad M. , Imran Mousa M. A. , Hamadneh Imad , AlDujaili Ammar 
Published: February 2024

Abstract
This work used AC impedance techniques to investigate the AC electrical properties of the synthesized polyvinyl chloride (PVC)/zinc oxide (ZnO) nanocomposite films. By using the casting method, PVC/ZnO nanocomposite films with weight% concentrations of 2.5, 5.0, 7.5, and 10.0% ZnO were prepared. Every mixture was prepared in a film and cast into a glass mold measuring 5 cm by 5 cm. The nanocomposites samples were characterized using Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). For the produced film under study, the following electrical properties were examined: AC conductivity ( σac ) real dielectric constant (∈'), imaginary dielectric constant (∈"), real electrical modulus (M''), and imaginary electric modulus (M"). The temperature ranges tested were 293-313 K and the frequency range was 2-6 MHz. The findings demonstrated that the frequency and concentration of ZnO nanoparticles in the PVC polymer matrix affected the behavior and characteristics of the PVC/ZnO nanocomposite films. Furthermore, the study's findings indicate that when temperature rises, σac increases dramatically. The remaining parameters, however, i.e., ∈', ∈", M' and M" are temperature independent.
Hybrid Extraordinary Transmission Structure for Plasmonic Light- Trapping Applications
Authors: Razavizadeh Seyed Mohammadreza 
Published: February 2024

Abstract
In this paper, we numerically studied a hybrid extraordinary optical transmission (EOT) structure including a nanoslit aperture surrounded by a parallel periodic rectangular grooves array in a thick Ag-film when a parallel Au-nanowires array was attached between the grooves. The effects of two types of rectangular and cylindrical nanowires morphology to launch surface plasmon polaritons (SPPs) under normal plane wave incidence have been investigated and compared. These proposed hybrid Ag-grooves/Au-nanowires EOT system offer compact platform and could be used as nanolens in future solar cells and similar optical devices which need an efficient light trapping like nano-biosensors.
Enhancing post-traumatic stress disorder patient assessment: Leveraging Natural Language Processing for Research of Domain Criteria Identification using electronic medical records
Authors: Miranda Oshin , Kiehl Sophie , Qi Xiguang , Ryan Neal David , Kirisci Levent , Brannock M. Daniel , Kosten Thomas , Wang Yanshan , Wang LiRong 
Published: February 2024

Abstract
Background
Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities.
Methods
In our study, we created an NLP workflow to analyze electronic medical record (EMR) data, and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, all-mpnet-base-v2. We subsequently built dictionaries from 100,000 clinical notes and analyzed 5.67 million clinical notes from 38,807 PTSD patients from the University of Pittsburgh Medical Center. Subsequently, we showcased the significance of our approach by extracting and visualizing RDoC information in two use cases: (i) across multiple patient populations and (ii) throughout various disease trajectories.
Results
The sentence transformer model demonstrated superior F1 macro scores across all RDoC domains, achieving the highest performance with a cosine similarity threshold value of 0.3. This ensured an F1 score of at least 80% across all RDoC domains. The study revealed consistent reductions in all six RDoC domains among PTSD patients after psychotherapy. Women had the highest abnormalities of sensorimotor systems, while veterans had the highest abnormalities of negative and positive valence systems. The domains following first diagnoses of PTSD were associated with heightened cue reactivity to trauma, suicide, alcohol, and substance consumption.
Conclusions
The findings provide initial insights into RDoC functioning in different populations and disease trajectories. Natural language processing proves valuable for capturing real-time, context dependent RDoC instances from extensive clinical notes.
DHFS-ECM: Design of a Dual Heuristic Feature Selection-based Ensemble
Classification Model for the Identification of Bamboo Species from
Genomic Sequences
Authors: Durge Aditi R. , Shrimankar Deepti D. 
Published: February 2024

Background:
Analyzing genomic sequences plays a crucial role in understanding biological
diversity and classifying Bamboo species. Existing methods for genomic sequence analysis suffer
from limitations such as complexity, low accuracy, and the need for constant reconfiguration in
response to evolving genomic datasets

Aim:
This study addresses these limitations by introducing a novel Dual Heuristic Feature Selection-
based Ensemble Classification Model (DHFS-ECM) for the precise identification of Bamboo
species from genomic sequences.

Methods:
The proposed DHFS-ECM method employs a Genetic Algorithm to perform dual heuristic
feature selection. This process maximizes inter-class variance, leading to the selection of informative
N-gram feature sets. Subsequently, intra-class variance levels are used to create optimal
training and validation sets, ensuring comprehensive coverage of class-specific features. The selected
features are then processed through an ensemble classification layer, combining multiple stratification
models for species-specific categorization.

Results:
Comparative analysis with state-of-the-art methods demonstrate that DHFS-ECM achieves
remarkable improvements in accuracy (9.5%), precision (5.9%), recall (8.5%), and AUC performance
(4.5%). Importantly, the model maintains its performance even with an increased number of
species classes due to the continuous learning facilitated by the Dual Heuristic Genetic Algorithm
Model.

Conclusion:
DHFS-ECM offers several key advantages, including efficient feature extraction, reduced
model complexity, enhanced interpretability, and increased robustness and accuracy through
the ensemble classification layer. These attributes make DHFS-ECM a promising tool for real-time
clinical applications and a valuable contribution to the field of genomic sequence analysis.
A Novel Approach to the Technique of Lung Region Segmentation Based on a
Deep Learning Model to Diagnose COVID-19 X-ray Images
Authors: Ding Xuejie , Zhou Qi , Liu Zifan , Hammad Kowah Jamal Alzobair , Wang Lisheng , Huang Xialing , Liu Xu 
Published: February 2024

Background::
The novel coronavirus pandemic has caused a global health crisis, placing immense strain on healthcare systems worldwide. Chest X-ray
technology has emerged as a critical tool for the diagnosis and treatment of COVID-19. However, the manual interpretation of chest X-ray films
has proven to be inefficient and time-consuming, necessitating the development of an automated classification system.

Objective::
In response to the challenges posed by the COVID-19 pandemic, we aimed to develop a deep learning model that accurately classifies chest X-ray
images, specifically focusing on lung regions, to enhance the efficiency and accuracy of COVID-19 and pneumonia diagnosis.

Methods::
We have proposed a novel deep network called FocusNet for precise segmentation of lung regions in chest radiographs. This segmentation
allows for the accurate extraction of lung contours from chest X-ray images, which are then input into the classification network, ResNet18. By
training the model on these segmented lung datasets, we sought to improve the accuracy of classification.

Results::
The performance of our proposed system was evaluated on three types of lung regions in normal individuals, COVID-19 patients, and those with
pneumonia. The average accuracy of the segmentation model (FocusNet) in segmenting lung regions was found to be above 90%. After reclassification
of the segmented lung images, the specificities and sensitivities for normal, COVID-19, and pneumonia were excellent, with values
of 98.00%, 99.00%, 99.50%, and 98.50%, 100.00%, and 99.00%, respectively. ResNet18 achieved impressive area under the curve (AUC) values
of 0.99, 1.00, and 0.99 for classifying normal, COVID-19, and pneumonia, respectively, on the segmented lung datasets. Moreover, the AUC
values of the three groups increased by 0.02, 0.02, and 0.06, respectively, when compared to the direct classification of unsegmented original
images. Overall, the accuracy of lung region classification after processing the datasets was 99.3%.

Conclusion::
Our deep learning-based automated chest X-ray classification system, incorporating lung region segmentation using FocusNet and subsequent
classification with ResNet18, has significantly improved the accuracy of diagnosing respiratory lung diseases, including COVID-19. The proposed
approach has great potential to revolutionize the diagnosis of COVID-19 and other respiratory lung diseases, offering a valuable tool to support
healthcare professionals during health crises.
Differentiating the Presence of Brain Stroke Types in MR Images using CNN
Architecture
Authors: Kaliannan Srisabarimani , Rengaraj Arthi 
Published: February 2024

Backgroud:
Stroke is reportedly the biggest cause of death and disability in the world, according to the World Health Organisation (WHO). The severity of a
stroke can be lowered by recognising the many stroke warning indicators early on. Using CNN, the primary goal of this study is to predict the
likelihood that a brain stroke would develop at an early stage.

Objective:
The novelty of the proposed work is to acquire models that can accurately differentiate between stroke and no-stroke (normal) cases using MR
Imaging sequences like DWI, SWI, GRE and T2 FLAIR aiding in timely diagnosis and treatment decisions.

Methods:
A dataset comprising real time MRI scans of patients with stroke and no-stroke conditions was collected and preprocessed for model training. The
preprocessing involves standardizing the resolution of the images, normalizing pixel values, and augmenting the dataset to enhance model
generalization. The ResNet, DenseNet, EfficientNet, and VGG16 architectures were implemented and trained on the preprocessed dataset. The
training process involved optimizing model parameters using stochastic gradient descent and minimizing the loss function.

Results:
The results demonstrate promising performance across all models by obtaining an accuracy of 98% for ResNet, DenseNet and EfficientNet, while
97% for VGG16 in differentiating the stroke using real time MRI data.

Conclusion:
The proposed work explored the effectiveness of CNN models, including ResNet, DenseNet, EfficientNet, and VGG16, for the differentiation of
stroke and no-stroke cases. The models were trained and evaluated using a real-time dataset of brain MR Images. The obtained accuracies highlight
the potential of CNN models in accurately differentiating between stroke and non-stroke cases.
O impacto da pandemia – Coronavírus no uso de tecnologia educacional: uma pesquisa exploratória no Estado do Rio de Janeiro.
Authors: T Lannes Vieira Anna Myrian , Greenhalgh Lins Arnaldo , Fernandes Roppa Cruz Valéria , Coelho Maria Priscilla , Martins Rodrigues M Carolina , Rodriguez Martius Vicente Rodriguez y 
Published: February 2024

O ano de 2020 foi marcado com o surgimento da pandemia pelo novo coronavírus, as escolas e grandes centros de conhecimento foram obrigados a se reinventarem. Diversos aplicativos e ferramentas como o Google Classroom, Google Meet e Zoom começaram a ser empregados no ensino remoto assistido por tecnologia. Este estudo possui carácter exploratório e descritivo e apresenta uma pesquisa realizada junto a professores de escolas e centros de ensino no Rio de Janeiro durante o período de pandemia. Objetivou-se a apresentação de novos recursos e ferramentas, além de inovações no ensino, bem como a criatividade para manter o espírito da sala de aula vivo durante o ensino à distância (EAD). Observou-se que as instituições privadas se adaptaram rapidamente ao EAD, conseguindo minimizar o atraso com a interrupção das atividades presenciais. Já instituições públicas tiveram como objetivo a promoção da inclusão digital dos alunos mais desfavorecidos socioeconomicamente. As ferramentas de ensino mais utilizadas foram o Google Classroom e Google Meet. Apesar do impacto da crise econômica gerada pelo coronavírus foi observada uma revolução no método de ensino e a aceleração importante da digitalização da educação.
Palavras- chave: coronavírus; educação; inovação.
Satisfação de clientes em uma empresa prestadora de serviço: modelo SERVQUAL
Authors: Barbieri da Rosa Luciana Aparecida , Umpierre Pablo Rodriguez , Martins Rodrigues Maria Carolina , Godoy Taís Pentiado , Camargo Caroline Rosseto , Godoy Leoni Pentiado 
Published: February 2024

As distintas mudanças sociais, culturais e políticas que acontecem no ambiente empresarial, impactam significativamente nas organizações. Para isso é preciso mensurar a satisfação do cliente, ou seja, analisar a expectativa e o desempenho. Utilizando como base o modelo SERVQUAL, um modelo baseado nas dimensões da qualidade, assim medindo o serviço. O objetivo do estudo é avaliar a qualidade da prestação do serviço, tendo em vista mapear as expectativas e potencializar a percepção do serviço. aplicou-se um questionário desenvolvido e adaptado do estudo de Bastos, Inacio e Bergiante (2015). Os sujeitos desse estudo foram os clientes da empresa Beta, resultando uma população total de cinquenta e um clientes. Por meio dessa investigação possibilitou-se identificar a existência de fatores que podem ser melhorados, com relação aos serviços prestados pela empresa, no sentido de oferecer serviços de maior qualidade.Os resultados deixam claro que, em algumas questões, a importância é excedida, existindo necessidades de mudanças, principalmente, no que tange à dimensão tangível, e presteza, cada dimensão com duas questões com Gaps negativos e a dimensão empatia com uma questão de Gap negativo.
Transatlantic relations between the US and the EU in the second and third decades of the 21st century - main challenges
Authors: Niewiadomski Michał , Niemczyk Agata , Pereira Fernanda , Surówka Marcin 
Published: February 2024

Historically, the development of new technologies has led to higher increase in productivity in Europe and the US compared to the rest of the world. This resulted in economic asymmetry in the global economy, which ultimately led to the geopolitical domination of Europe and the USA over Africa and Asia (Findlay, O'Rourke, 2007, p. 364). With the adoption of the Lisbon Treaty, the European Union has taken a step towards playing a significant role in trade, environment and social issues (Van Langenhove & Marchesi, 2009; Rudloff & Laurer, 2017). The aim of this work is to present the main challenges and changes taking place in transatlantic relations between the EU and the USA in the second and third decades of the 21st century. To achieve this goal, the descriptive method was applied.
The reforms carried out by the EU allowed it to act in the spectrum of international affairs. The conflict between Russia and Ukraine (in 2014 and 2022) showed that the EU is increasingly resorting to sanctions and conditionality instruments to promote its interests. In addition, the EU aims to create a common army. Despite the fact that these changes contribute to the increase of the EU's competitiveness in the world, US relations between the EU are extremely durable, and the transatlantic community is repairing mutual relations relatively quickly. Meanwhile, the EU's relations with China, the largest trading partner in 2021 (Eurostat, 2022), are confrontational.
Despite improvement in transatlantic relations, the earlier lack of communication led to a lack of confidence in the US on the part of Europeans. Relations between the US and the EU in the third decade of the 21st century remain tense – it is worth mentioning the AUKUS defense pact (agreement between Australia, Great Britain and the United States) on the exchange of defense technologies in this respect (Borges de Castro and Ricardo, 2021; Morcos 2021 ). It resulted in deterioration of relations between Paris and the US to such an extent that they were close to breaking. At the same time, at the beginning of the third decade of the 21st century, transatlantic relations sought stabilization. President Biden's administration has reaffirmed its commitment to alliances with European countries. In addition, the US returned to the Paris Agreement (United States Department of State, 2021) and rejoined the World Health Organization (WHO) (Keaten, 2021).
Pengaruh Kepemilikan Manajerial, Dewan Komisaris, dan Komite Audit terhadap Fraudulent Financial Statements
Authors: Ihsanti Mutiara , Cheisviyanny Charoline 
Published: February 2024

This research aims to obtain empirical evidence and analyze the influence of managerial ownership, board of commissioners and audit committee on fraudulent financial statements in pharmaceutical manufacturing companies listed on the Indonesia Stock Exchange 2018-2022. The population in this study were 12 pharmaceutical companies, while the sample in this study was 45 companies. This research uses secondary data obtained from the official website of the Indonesia Stock Exchange (BEI), namely www.idx.co.id, the BEI corner (Indonesia Stock Exchange) and company websites using the logistic regression analysis method. The results of this research conclude the managerial ownership, board of commissioners and audit committee have no effect on fraudulent financial statements.
Pelatihan Membaca al-Qur’an dengan Metode WAFA di Desa Sawangan Kecamatan Kebasen
Authors: Prayogi Adi , Hidayat Arif 
Published: February 2024

Metode WAFA merupakan sebuah sistem pembelajaran yang disusun dalam sebuah metode. Pada Metode WAFA ini menggunakan otak kanan sebagai daya imajinasi dan seni karena didalamnya menggunakan nada hijaz 3 pola nada. Metode ini digunakan untuk masyarakat yang ingin mempelajari Al-Qur’an, hingga diharapkan menjadi bisa dan lancar dalam membaca Al-Qur’an dengan laten yang benar. Dalam pengabdian masyarakat di desa Sawangan, permasalahan terjadi dimana kurangnya pengajar yang kompeten sehingga masyarakat cenderung masih banyak kesalahan dalam membaca dan mengeja huruuf-huruf Al-Qur’an. Ditambah kesadaran masyarakat terhadap baca tulis Al-Qur’an (BTA) masih sangat rendah. Kurangnya kesadaran ini disebabkan minimm sumber pengajar yang ada pada masyarakat desa Sawangan yang notabene sudah lanjut usia. Adapun tenaga pendidik Al-Qur’an masih mengandalkan orang yang sudah lancar dalam membaca Al-Qur’an, sehingga belum mampu memberikan wawasan dalam mengajarkan Al-Qur’an kepada masyarakat. Penulis menggunakan pendekatan kualitatif yang menghasilkan laporan data narasi dan studi kasus yang terjadi, hasil dari penelitian ini bertujuan untuk memberikan informasi kepada khalayak. Hasil dari pelatihan metode WAFA kepada masyarakat desa Sawangan, penulis melakukan pengenalan tentang metode WAFA dan mencontohkan huruf-huruf laten Al-Qur’an dengan baik dan benar. Setelah itu mencontohkan nada hijaz 3 pola nada agar masyarakat bisa membaca Al-Qur’an atau buku metode WAFA dengan nada tersebut, sehingga diharapkan dapat hafal secara sendirinya yang disebabkan oleh nada tersebut. Dari hasil kegiatan ini maka masyarakat dapat membaca Al-Qur’an dan mengucapkan huruf-huruf hijaiyah dengan benar sesuai kaidah laten atau mahroj hurufnya.
Meningkatkan Karakter Mandiri Siswa Melalui Penerapan Gerakan Literasi Sekolah Disajikan Untuk Pengabdian Pada Masyarakat di SDN 2 Sumampir
Authors: Kariadi Mustasyfa Thabib , Riyanton Muhammad , Andini Novita Pri , Sulistio Prayogo Hadi , Cakrawati Laxmi Mustika 
Published: February 2024

Literasi adalah salah satu aspek penting dalam menyerap dan menambah pengetahuan dan informasi dari berbagai sumber. Literasi sendiri menjadi hal yang dikembangkan di era sekarang ini. Hal ini terkait dengan pengembangan pengetahuan dan keterampilan yang mengarah pada kemandirian. Sedangkan kemandirian adalah tuntutan seiring dengan terus berkembangnya sains dan teknologi yang harus dikuasai. Kegiatan ini dilaksanakan untuk memberikan motivasi bagi guru dan siswa, khususnya di SD Negeri 2 Sumampir, Purwokerto untuk meningkatkan literasi secara mandiri melalui berbagai kegiatan literasi baik berbasis konvensional maupun digital. Ketersediaan referensi merupakan elemen penting dalam memotivasi guru dan siswa untuk meningkatkan dan mengembangkan kemampuan literasi mereka baik melalui media cetak maupun media digital. Kegiatan ini menggunakan metode Forum Grup Discussion di mana para guru dan siswa dikelompokkan berdasarkan minat dan bakat dalam berliterasi, antara lain melalui penulisan puisi, cerita pendek, diari, dll. Setelah dikelompokkan para guru dan siswa melakukan sesi diskusi yang bertujuan meningkatkan dan mengembangkan kemampuan literasi. Diharapkan dari kegiatan ini dapat memberikan manfaat dalam mengembangkan minat dan bakat melalui kegiatan literasi.