MLS Communication Journal

Revista Subjects > Comunication Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines
Abierto Inglés El objetivo principal de Revista MLS Communication Journal es difundir obras inéditas relacionadas con los grandes retos y desafíos de la comunicación en sus diferentes ámbitos: el periodismo, la publicidad, la comunicación audiovisual, la comunicación interactiva o la comunicación en las organizaciones, entre otros. La revista tiene interés en la difusión de trabajos académicos y científicos que identifiquen, describan y divulguen hallazgos inéditos y de interés en estos campos desde la revisión teórica, la innovación metodológica, la experimentación y la apuesta por la innovación. Los estudios publicados en MLS Communication Journal se centran en reflexionar sobre los grandes hitos, las principales interrogantes y las tendencias más destacadas del escenario comunicativo, adoptando una perspectiva de estudio teórico-práctica. La revista tiene un marcado carácter iberoamericano e internacional, por lo que puede ser utilizada para su publicación en cualquier país de origen, siempre que éstos cumplan con las diferentes fases de la investigación con rigor metodológico. Constituye, por lo tanto, un medio de difusión del conocimiento derivado de diferentes entornos socioculturales. MLS Communication Journal pública trabajos en el idioma castellano, portugués e inglés, y se edita totalmente en el último idioma, manteniendo también una edición en el idioma original del manuscrito. Su estructura organizativa se compone principalmente de investigadores, ya que una revista científica, basada en principios, debe tener sus raíces en la comunidad investigadora que tiene la producción intelectual y las contribuciones relevantes en el tema dentro de sus respectivas instituciones. metadata UNSPECIFIED mail mls@devnull.funiber.org (2021) MLS Communication Journal. [Revista]

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Abstract

El objetivo principal de Revista MLS Communication Journal es difundir obras inéditas relacionadas con los grandes retos y desafíos de la comunicación en sus diferentes ámbitos: el periodismo, la publicidad, la comunicación audiovisual, la comunicación interactiva o la comunicación en las organizaciones, entre otros. La revista tiene interés en la difusión de trabajos académicos y científicos que identifiquen, describan y divulguen hallazgos inéditos y de interés en estos campos desde la revisión teórica, la innovación metodológica, la experimentación y la apuesta por la innovación. Los estudios publicados en MLS Communication Journal se centran en reflexionar sobre los grandes hitos, las principales interrogantes y las tendencias más destacadas del escenario comunicativo, adoptando una perspectiva de estudio teórico-práctica. La revista tiene un marcado carácter iberoamericano e internacional, por lo que puede ser utilizada para su publicación en cualquier país de origen, siempre que éstos cumplan con las diferentes fases de la investigación con rigor metodológico. Constituye, por lo tanto, un medio de difusión del conocimiento derivado de diferentes entornos socioculturales. MLS Communication Journal pública trabajos en el idioma castellano, portugués e inglés, y se edita totalmente en el último idioma, manteniendo también una edición en el idioma original del manuscrito. Su estructura organizativa se compone principalmente de investigadores, ya que una revista científica, basada en principios, debe tener sus raíces en la comunidad investigadora que tiene la producción intelectual y las contribuciones relevantes en el tema dentro de sus respectivas instituciones.

Item Type: Revista
Subjects: Subjects > Comunication
Divisions: Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines
Date Deposited: 14 Oct 2022 23:30
Last Modified: 14 Oct 2022 23:30
URI: https://repositorio.unincol.edu.co/id/eprint/238

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<a href="/12747/1/sensors-24-03754%20%281%29.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence

Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%.

Producción Científica

Hafeez Ur Rehman Siddiqui mail , Ambreen Akmal mail , Muhammad Iqbal mail , Adil Ali Saleem mail , Muhammad Amjad Raza mail , Kainat Zafar mail , Aqsa Zaib mail , Sandra Dudley mail , Jon Arambarri mail jon.arambarri@uneatlantico.es, Ángel Gabriel Kuc Castilla mail , Furqan Rustam mail ,

Siddiqui

<a class="ep_document_link" href="/11265/1/Food%20Frontiers%20-%202024%20-%20Cassotta%20-%20Human%E2%80%90based%20new%20approach%20methodologies%20to%20accelerate%20advances%20in%20nutrition%20research.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Human‐based new approach methodologies to accelerate advances in nutrition research

Much of nutrition research has been conventionally based on the use of simplistic in vitro systems or animal models, which have been extensively employed in an effort to better understand the relationships between diet and complex diseases as well as to evaluate food safety. Although these models have undeniably contributed to increase our mechanistic understanding of basic biological processes, they do not adequately model complex human physiopathological phenomena, creating concerns about the translatability to humans. During the last decade, extraordinary advancement in stem cell culturing, three-dimensional cell cultures, sequencing technologies, and computer science has occurred, which has originated a wealth of novel human-based and more physiologically relevant tools. These tools, also known as “new approach methodologies,” which comprise patient-derived organoids, organs-on-chip, multi-omics approach, along with computational models and analysis, represent innovative and exciting tools to forward nutrition research from a human-biology-oriented perspective. After considering some shortcomings of conventional in vitro and vivo approaches, here we describe the main novel available and emerging tools that are appropriate for designing a more human-relevant nutrition research. Our aim is to encourage discussion on the opportunity to explore innovative paths in nutrition research and to promote a paradigm-change toward a more human biology-focused approach to better understand human nutritional pathophysiology, to evaluate novel food products, and to develop more effective targeted preventive or therapeutic strategies while helping in reducing the number and replacing animals employed in nutrition research.

Producción Científica

Manuela Cassotta mail manucassotta@gmail.com, Danila Cianciosi mail , Maria Elexpuru Zabaleta mail maria.elexpuru@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es,

Cassotta

<a class="ep_document_link" href="/11322/1/journal.pone.0298582.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing

With the outbreak of the COVID-19 pandemic, social isolation and quarantine have become commonplace across the world. IoT health monitoring solutions eliminate the need for regular doctor visits and interactions among patients and medical personnel. Many patients in wards or intensive care units require continuous monitoring of their health. Continuous patient monitoring is a hectic practice in hospitals with limited staff; in a pandemic situation like COVID-19, it becomes much more difficult practice when hospitals are working at full capacity and there is still a risk of medical workers being infected. In this study, we propose an Internet of Things (IoT)-based patient health monitoring system that collects real-time data on important health indicators such as pulse rate, blood oxygen saturation, and body temperature but can be expanded to include more parameters. Our system is comprised of a hardware component that collects and transmits data from sensors to a cloud-based storage system, where it can be accessed and analyzed by healthcare specialists. The ESP-32 microcontroller interfaces with the multiple sensors and wirelessly transmits the collected data to the cloud storage system. A pulse oximeter is utilized in our system to measure blood oxygen saturation and body temperature, as well as a heart rate monitor to measure pulse rate. A web-based interface is also implemented, allowing healthcare practitioners to access and visualize the collected data in real-time, making remote patient monitoring easier. Overall, our IoT-based patient health monitoring system represents a significant advancement in remote patient monitoring, allowing healthcare practitioners to access real-time data on important health metrics and detect potential health issues before they escalate.

Producción Científica

Md. Milon Islam mail , Imran Shafi mail , Sadia Din mail , Siddique Farooq mail , Isabel de la Torre Díez mail , Jose Breñosa mail josemanuel.brenosa@uneatlantico.es, Julio César Martínez Espinosa mail ulio.martinez@unini.edu.mx, Imran Ashraf mail ,

Islam

<a href="/11666/1/Pneumonia_Detection_Using_Chest_Radiographs_With_Novel_EfficientNetV2L_Model.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Pneumonia Detection Using Chest Radiographs With Novel EfficientNetV2L Model

Pneumonia is a potentially life-threatening infectious disease that is typically diagnosed through physical examinations and diagnostic imaging techniques such as chest X-rays, ultrasounds or lung biopsies. Accurate diagnosis is crucial as wrong diagnosis, inadequate treatment or lack of treatment can cause serious consequences for patients and may become fatal. The advancements in deep learning have significantly contributed to aiding medical experts in diagnosing pneumonia by assisting in their decision-making process. By leveraging deep learning models, healthcare professionals can enhance diagnostic accuracy and make informed treatment decisions for patients suspected of having pneumonia. In this study, six deep learning models including CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L are implemented and evaluated. The study also incorporates the Adam optimizer, which effectively adjusts the epoch for all the models. The models are trained on a dataset of 5856 chest X-ray images and show 87.78%, 88.94%, 90.7%, 91.66%, 87.98% and 94.02% accuracy for CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L, respectively. Notably, EfficientNetV2L demonstrates the highest accuracy and proves its robustness for pneumonia detection. These findings highlight the potential of deep learning models in accurately detecting and predicting pneumonia based on chest X-ray images, providing valuable support in clinical decision-making and improving patient treatment.

Producción Científica

Mudasir Ali mail , Mobeen Shahroz mail , Urooj Akram mail , Muhammad Faheem Mushtaq mail , Stefanía Carvajal-Altamiranda mail stefania.carvajal@uneatlantico.es, Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Isabel De La Torre Díez mail , Imran Ashraf mail ,

Ali

<a class="ep_document_link" href="/12107/1/fphar-15-1368949.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Resveratrol and vascular health: evidence from clinical studies and mechanisms of actions related to its metabolites produced by gut microbiota

Cardiovascular diseases are among the leading causes of mortality worldwide, with dietary factors being the main risk contributors. Diets rich in bioactive compounds, such as (poly)phenols, have been shown to potentially exert positive effects on vascular health. Among them, resveratrol has gained particular attention due to its potential antioxidant and anti-inflammatory action. Nevertheless, the results in humans are conflicting possibly due to interindividual different responses. The gut microbiota, a complex microbial community that inhabits the gastrointestinal tract, has been called out as potentially responsible for modulating the biological activities of phenolic metabolites in humans. The present review aims to summarize the main findings from clinical trials on the effects of resveratrol interventions on endothelial and vascular outcomes and review potential mechanisms interesting the role of gut microbiota on the metabolism of this molecule and its cardioprotective metabolites. The findings from randomized controlled trials show contrasting results on the effects of resveratrol supplementation and vascular biomarkers without dose-dependent effect. In particular, studies in which resveratrol was integrated using food sources, i.e., red wine, reported significant effects although the resveratrol content was, on average, much lower compared to tablet supplementation, while other studies with often extreme resveratrol supplementation resulted in null findings. The results from experimental studies suggest that resveratrol exerts cardioprotective effects through the modulation of various antioxidant, anti-inflammatory, and anti-hypertensive pathways, and microbiota composition. Recent studies on resveratrol-derived metabolites, such as piceatannol, have demonstrated its effects on biomarkers of vascular health. Moreover, resveratrol itself has been shown to improve the gut microbiota composition toward an anti-inflammatory profile. Considering the contrasting findings from clinical studies, future research exploring the bidirectional link between resveratrol metabolism and gut microbiota as well as the mediating effect of gut microbiota in resveratrol effect on cardiovascular health is warranted.

Producción Científica

Justyna Godos mail , Giovanni Luca Romano mail , Lucia Gozzo mail , Samuele Laudani mail , Nadia Paladino mail , Irma Dominguez Azpíroz mail irma.dominguez@unini.edu.mx, Nohora Milena Martínez López mail nohora.martinez@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es, José L. Quiles mail jose.quiles@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es, Fabio Galvano mail , Filippo Drago mail , Giuseppe Grosso mail ,

Godos