bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial intelligence for Microbiota Analysis: Advances and Applications
Authors: Patil Abhinandan , Singh Neha
Published: July 2023

The body's billions of bacteria—the microbiota—influence health and illness. The microbiome—the genetic material of these microbes—affects digestion, immunological function, and mental health. Due to bacterial variety, complicated relationships, and research technique constraints, investigating the microbiota is difficult. AI and machine learning have expanded microbiome research. Artificial intelligence (AI) systems can efficiently scan large microbiome datasets to help researchers understand microbial populations and their functions. AI-based predictive algorithms can analyze food impacts on microbial communities and forecast illness risks based on gut microbiota composition. AI helps find microbial biomarkers linked to specific health disorders, enabling early illness identification and targeted therapy. AI-driven medication development platforms also modulate microbiome to treat microbiota-related diseases. Understanding microbial populations' involvement in health and illness requires understanding complicated microbial interactions within the microbiome and between it and the host. AI systems improve human health by comprehending these complex relationships. AI in microbiota study must overcome various obstacles. Data quality and AI model interpretability are essential for accurate findings. Diverse and representative datasets avoid biases and strengthen AI-driven conclusions. AI in microbiota research requires data protection, informed permission, and appropriate use of sensitive data. AI is improving our understanding of the human microbiome and its health effects, changing microbiota research. Overcoming difficulties and adhering to ethical norms will enable the proper use of AI-driven findings, leading to microbiome insights and precision medical breakthroughs.
A Review on Carbon Dioxide Sequestration Methodology
Authors: Mwenketishi Gregory Tarteh , Rahmanian Nejat , Benkreira Hadj
Published: July 2023

Carbon subsurface storage (CSS) has already been recognised as a critical, urgent, and essential method for reducing anthropogenic CO2 emissions and mitigating the severe effects of climate change. CSS is the last stage in the carbon capture and storage (CCS) cycle and is accomplished chiefly via oceanic and subterranean geological sequestration, as well as mineral carbonation. The injection of supercritical CO2 into geological formations causes a disruption in the sub-surface's existing physical and chemical conditions; changes can occur in the pore fluid pressure, temperature state, chemical reactivity, and stress distribution of the reservoir rock. This paper aims to present a comprehensive review on the current advances in CSS, particularly CO2 storage methods and the challenges encountered during the implementation of each method and analyses on how key uncertainties in CSS can be reduce.
CSS sites are essentially unified systems; yet, given the scientific context, these systems are typically split during scientific investigations based on the physics and temporal/spatial scales involved. Separating the physics by using the system as a boundary condition is a strategy that works effectively for a wide variety of physical applications. Unfortunately, the separation technique does not accurately capture the behaviour of the larger important system in the case of water and gas flow in porous media. This is due to the complexity of geological subsurface systems, which prevents the approach from being able to effectively capture the behaviour of the larger relevant system. This consequently give rise to different CSS methods.
A good CSS application method can further improve the efficiency of greenhouse gas emission and their environmental impact, promoting the process sustainability and helping to tackle some of the most important issues that human being is currently accounting, global climate change. Though this technology is already large-scale development for the last decade, some issues and uncertainties are identified. Special attention was focused on the basic findings achieved in CO2 storage operational projects to date.
Modelling the Unidentified Abortion Burden from Four Infectious Pathogenic Microorganisms in Ewes based on Artificial Neural Networks Approach: The Epidemiological Basis for a Control Policy
Authors: Arteaga-Troncoso Gabriel , Luna-Alvarez Miguel , Hernández-Andrade Laura , Jiménez-Estrada Juan Manuel , Sánchez-Cordero Víctor , Botello Francisco , Montes de Oca-Jiménez Roberto , López-Hurtado Marcela , Guerra-Infante Fernando Martín
Published: July 2023

Unidentified abortion, of which leptospirosis, brucellosis and ovine enzootic abortion are important factors, is the main cause of disease spread between animals and humans in all agricultural systems in most developing countries. Although there are well-defined risk factors for these diseases, these characteristics do not represent the prevalence of the disease in different regions. This study predicts the unidentified abortion burden from multi-microorganisms in ewes based on artificial neural networks approach and GLM. Methods: A two-stage cluster survey design was conducted to estimate the seroprevalence of abortifacient microorganisms, and to identify putative factors of infectious abortion. Results: Overall seroprevalence of Brucella was 70.7%, while Leptospira spp. was 55.2%, C. abortus 21.9% and B. ovis 7.4%. Serological detection with the 4 abortion-causing microorganisms was determined only in 0.87% of sheep sampled. The best GLM is integrated by serological detection of serovar Hardjo and Brucella ovis in animals of the slopes with elevation between 2600 to 2800 meters above sea level from municipality of Xalatlaco, as well water supply, sheep pen built with materials of metal grids and untreated wood, with dirt and concrete floors, and bed of straw that remained independently associated with infectious abortion in ewes. Approximately 80% of those respondents did not wear gloves or masks to prevent the transmission of the abortifacient zoonotic microorganisms. Conclusions: Sensitizing stakeholders on good agricultural practices could improve public health surveillance. Further studies on the effect of animal-human transmission in such a setting are worthwhile to further support the One Health initiative.
Sustainable Waste Management in the Production of Medicinal and Aromatic Plants – A Systematic Review
Authors: Marcelino Sara , Gaspar Pedro Dinis , Paço Arminda
Published: July 2023

Due to the growing demand for Medicinal and Aromatic Plants (PAMs), environmental risks associated with overexploitation and inadequate waste management are increasing. Since MAPs residues have a notable potential to be valorised, the implementation of Circular Economy solutions can play a central role in transforming waste management problems into economic opportunities and in responding to the growing demand for MAPs. Circular economy is viewed as a solution for fostering a sustainable system planet and positively contributes to the economy and society. A systematic review was conducted aiming to identify potential applications for the valorisation of MAP, under a sustainable waste management and circular economy approach. A total number of 47 studies were analysed and it was verified that MAPs residues can be valorised for energy purposes, crop management and applications in chemical, food, pharmaceutical, cosmetic industries, among others. Despite the wide range of possible applications, to promote a progressive implementation of circular economy strategies by the industry, further investigation is needed regarding the development of more efficient techniques and technology to develop value-added products and the assessment of sustainable performance in empirical investigations, considering both economic and environmental indicators.
Espresso : a Global Deep Learning Model to Estimate Precipitations from Satellite Observations
Authors: Berthomier Léa
Published: July 2023

Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods these observations offer the opportunity to address the challenge of estimating precicpation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global aplications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 minutes.
In Vitro and In Silico Activities of E. radiata and E. cinerea as an Enhancer of Antibacterial, Antioxidant, and Anti-Inflammatory Agents
Authors: Elkolli Meriem , Hayet Elkolli , Ataya Farid , Salem-Bekhit Mounir M. , Ernst Barbara , Benguerba Yacine
Published: July 2023

Eucalyptus, a therapeutic plant mentioned in the ancient Algerian pharmacopeia, specifically two species belonging to the Myrtaceae family - E. radiata and E. cinerea, were investigated in this study for their antibacterial, antioxidant, and anti-inflammatory properties. The study used aqueous extracts (AE) obtained from these plants, and the extraction yields were found to be dif-ferent. The in vitro antibacterial activity was evaluated using a disc diffusion assay against three typical bacterial strains. The results showed that E. radiata EAq was effective against all three strains, while E. cinerea EAq was only effective against E. coli. Both extracts displayed significant antioxidant activity compared to BHT. The anti-inflammatory impact was evaluated using a pro-tein (BSA) inhibition denaturation test. The E. radiata extract was found to inhibit inflammation by 75% at a concentration of 250 g/ml, significantly higher than the placebo. Ellagic acid, a pri-mary phytochemical found in the extracts, demonstrated noteworthy toxic and pharmacokinetic characteristics and a maximum binding energy of -7.53 kcal/mol for its anti-TyrRS activity in sili-co. The study suggests that the extracts and their primary phytochemicals could enhance the effi-cacy of antibiotics, antioxidants, and non-steroidal anti-inflammatory drugs (NSAIDs). As phar-maceutical engineering experts, we believe this research contributes to developing natural-based drugs with potential therapeutic benefits.
Unraveling the Complex Interplay between lncRNAs and Myc in Breast Cancer
Authors: Mirmazhari Seyed Pedram , Abdi Mohammad Javad , Mosadeghrad Amir Hosein , Abedini Bonab Reza , Amani Babadi Arman , Rigi Garshasb , Shahrokhi Seyedeh Zahra , Chamanara Mohsen , Amodio Nicola , Heidari Reza
Published: July 2023

The Myc gene, widely studied in numerous cancer types, serves as a pivotal regulator of crucial cellular processes implicated in tumorigenesis, such as cell growth, proliferation, invasion, metastasis, and therapy resistance. LncRNAs have been identified as relevant partners of Myc. LncRNAs modulate chromatin structure and function, transcription, splicing, stability, and translation of mRNAs, thereby emerging as pivotal regulators in cell differentiation, metabolism, signaling. An intricate crosstalk exists between Myc and lncRNAs in a wide range of cancers, wherein they can physically and functionally interact through direct and indirect mechanisms. Some lncRNAs can regulate Myc activity at post-transcriptional level, affecting its stability, translation, or interactions with other proteins, thus acting as oncogenes, while others act as tumor suppressors. On the other hand, Myc can target numerous lncRNA genes and modulate their expression, affecting the expression of downstream targets involved in tumorigenesis. Given the significant role of the Myc-lncRNA network in various cancer types, exploring therapeutic strategies targeting these crucial cellular regulators is of utmost importance. This review article focuses on breast cancer, analyzing those lncRNAs influencing Myc as well as the Myc-regulated lncRNAs.
How Robust Are the Derived Design Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of Southern Germany
Authors: Laux Patrick , Weber Elena , Kunstmann Harald
Published: July 2023

Extreme value analysis (EVA) is well-established to derive hydrometeorological design values for infrastructure that has to withstand extreme events. Since there is evidence of increased extremes with higher hazard potential under climate change, alterations of EVA are introduced for which statistical properties are no longer assumed to be constant but vary over time. In this study, both stationary and non-stationary EVA models are used to derive design life levels (DLLs) of daily precipitation in the pre-alpine Oberland region of Southern Germany, an orographically complex region characterized by heavy precipitation events and climate change. As EVA is fraught with uncertainties, it is crucial to quantify its methodological impacts: two theoretical distributions (i.e., Generalized Extreme Value (GEV) and Generalized Pareto (GP) distribution), four different parameter estimation techniques, (i.e., Maximum Likelihood Estimation (MLE), L-moments, Generalized Maximum Likelihood Estimation (GMLE), and Bayesian estimation method) are compared. Discrepancies due to the parameter estimation methods may reach up to 45 % of the mean absolute value, while differences between stationary and non-stationary models are of the same magnitude (differences in design levels up to 40%). Despite the underlying large methodological uncertainties, there is a robust tendency for increased DLLs in the Oberland region towards the end of this century based on the (non-)stationary models.
Lithology Mapping in Vegetation-Covered Regions: RS imagery, Method, Challenge and Opportunities
Authors: Chen Yansi , Wang Yunchen , Zhang Feng , Dong Yulong , Song Zhihong , Liu Genyuan
Published: July 2023

Remote sensing (RS) technology has significantly contributed to geological exploration and mineral resource assessment. However, its effective application in vegetated areas encounters various challenges. This paper aims to provide a comprehensive overview of the challenges and opportunities associated with RS-based lithological identification in vegetated regions. The article begins by introducing the sources and processing methods of RS data, which serve as the foundation for subsequent analysis. Moreover, it highlights the techniques and methodologies employed for lithological classification in vegetated areas. Notably, hyperspectral RS and Synthetic Aperture Radar (SAR) have emerged as prominent tools in lithological identification. In addition, this paper addresses the limitations inherent in RS technology, including issues related to vegetation cover and terrain effects, which significantly impact accurate lithological mapping. To propel further advancements in the field, the paper proposes promising avenues for future research and development. These include the integration of multi-source data to enhance classification accuracy and the exploration of novel RS technologies and algorithms. In summary, this paper presents valuable insights and recommendations for advancing the study of RS-based lithological identification in vegetated areas.
Content of Fatty Acids in Relation to the Metal Concentration in the Muscle of Two Freshwater Fish Species
Authors: Jovičić Katarina , Djikanović Vesna , Santrač Isidora , Živković Sanja , Dimitrijević Milena , Vranković Jelena
Published: July 2023

In this study, the concentrations of metals (As, Cd, Co, Cr, Cu, Hg, Ni, Pb, and Zn) were deter-mined in two freshwater fish species. The same fish were also used to determine the content of fatty acids (FA), including saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). We investigated the species-specific relationship between bioaccumulation of metals and the content of FA. Roach and white bream were caught at two different sites in the Serbian part of the Danube. The measured metal concentrations were below the standard concentrations recommended in the guidelines of the EU and the Republic of Ser-bia. Among the non-essential metals, Ni had the highest concentration, ranging from 0.158 to 0.591 µg g-1. The muscle of the two fish species contained high concentrations of SFA, ranging from 36.31 to 51.79%, and MUFA, ranging from 33.56 to 43.70%. Polyunsaturated fatty acids were represented with the lowest percentage (5.32 - 27.18). Four of the nine metals studied (As, Hg, Ni and Pb) in one fish species and five of the nine metals studied (A, Cu, Ni, Pb and Zn) in the other fish species showed correlations with fatty acid content. These results help to reveal potential biomarkers of metal stress in lipid composition.
Plasma branched-chain amino acid concentrations in individuals without cardiovascular diseases versus patients diagnosed with hypertension and coronary artery disease
Authors: Kozhevnikova M. V. , Korobkova E. O. , Krivova A. V. , Kukharenko A. V. , Moskaleva N. E. , Shestakova K. M. , Mesonzhnik N. V. , Ageev A. A. , Boldin A. A. , Brito A. , Appolonova S. А. , Privalova E. V. , Belenkov Y. N.
Published: July 2023

Aim. Branched-chain amino acids (BCAAs) have been postulated as potential indicators of cardiovascular risk. The objective of this study was to explore the relationship between plasma BCAAs and different stages of cardiovascular disorders.

Material and methods. In our cross-sectional study, plasma BCAAs (valine, leucine and isoleucine) in individuals without cardiovascular diseases (CVDs) (nonCVD group, total n=27, with n=16 healthy, but with metabolic disorders) were compared to patients diagnosed with CVDs [CVD group, total n=109, being n=61 hypertension (n=31 with signs of beginning of myocardial remodeling) and n=48 patients with coronary artery disease (CAD)].

Results. The plasma concentration of BCAAs was significantly higher in the group of patients with cardiovascular disease compared with the healthy group (p<0.05 for all amino acids tested): valine concentration was 238.7 [219.6; 267.0] μM in the non-CVD group and 261.2 [233.8; 298.7] μM in the CVD group; leucine concentration was 134.8 [122.4; 153.2] μM and 146.8 [129.0; 166.6] μM, respectively; and isoleucine 72.7 [65.3; 84.4] μM and 81.7 [68.0; 96.2] μM, respectively. Leucine and isoleucine concentration levels were minimal in the healthy participant subgroup and maximal in the IBS patient subgroup. No statistically significant differences in BCAAs concentrations were found in the subgroups without CAD. Significant increases in concentrations were observed in the subgroups of patients with CAD as follows: valine concentration was 256.3 [219.0; 297.9] μM in hypertension group and 261.7 [236.5; 307.5] μM in CAD group; leucine concentration was 141.8 [123.5; 166.6] μM and 154.1 [134.7; 172.7] μM, respectively, and isoleucine 72.8 [65.7; 94.0] μM and 85.7 [74.9; 101.7] μM, respectively. BCAAs profiles in all participants with metabolic disorders had “good” diagnostic accuracy with area under the receiver operating characteristics curve being 0.72, 0.70 and 0.70 for valine, leucine and isoleucine, respectively.

Conclusion. BCAAs concentrations are elevated with higher severity of the cardiovascular disorder and exhibit potential as early independent indicators of coronary artery disease.
Nutraceutical support in the prevention and treatment of cardiovascular diseases
Authors: Gracheva E. V. , Starovoytova E. A. , Kulikov E. S. , Kirillova N. A. , Fedosenko S. V. , Balaganskaya M. A. , Kromka D. V.
Published: July 2023

Cardiovascular disease is the most common cause of death worldwide. In this regard, there is a need to find and implement effective methods for the prevention and treatment of such diseases. Lifestyle modification is an important component of a complex of preventive and therapeutic measures, including nutrition optimization, increased physical activity, and breaking bad habits. Currently, an actively developing area is the use of biologically active additives to food, in order to replenish the missing nutrients in the diet and maintain health. In the course of the present review, an analysis was made of randomized clinical trials performed over the past 5 years. The studies investigated both the short-term effects of taking omega-3 polyunsaturated fatty acids (effect on the blood lipid spectrum, blood pressure levels) and longterm results (development of myocardial infarction, stroke, cardiovascular mortality). This supplement has demonstrated a positive effect on immediate outcomes, namely the reduction of total cholesterol, low-density lipoprotein, triglycerides (lipid-lowering effect). However, there was no significant effect on long-term results. It also provides information on studies that have examined the cardioprotective effects of supplements such as resveratrol, red yeast rice, L-arginine, and curcumin. An analysis of publications has shown that these supplements have the potential to reduce the risk of development and progression of cardiovascular diseases due to possible hypolipidemic, endothelial protective, and antihypertensive effects. Nutraceutical support can be an effective addition to the basic treatment and help reduce morbidity and mortality due to cardiovascular disease.
Current insights into the possible role of laboratory monitoring of effectiveness and safety of direct oral anticoagulants
Authors: Gilyarevsky S. R. , Vereina N. K. , Golshmid M. V.
Published: July 2023

The article is devoted to the discussion of modern approaches to the use of laboratory methods to improve the tactics of using direct oral anticoagulants (DOACs) therapy. Clinical situations in which it may be reasonable to use data on the blood concentration of DOACs are given, including very old age, a marked deviation from the norm of body weight or impaired renal function. Data on the role of measuring the blood level of DOACs are considered in cases of the development of diseases or complications in which information is required on the preservation of the anticoagulant effect of DOACs, for example, in the development of severe bleeding or the need for urgent surgical intervention. The advantages and limitations of modern laboratory methods for assessing the blood concentration of DOACs are discussed. It is emphasized that one of the main advantages of using DOACs is the absence of the need to monitor laboratory parameters in most patients. Data from pharmacological studies are presented that may be useful in explaining the mechanisms that determine the higher safety of some DOACs compared to others. Promising methods for assessing the blood level of DOACs, as well as the possibility of using less specific reagents for assessing the concentration of DOACs, are considered. The possibility of using less specific, but more accessible methods for assessing the blood concentration of factor Xa inhibitors, in particular, a reagent for assessing the level of the antifactor, which is used to determine the blood level of heparin, is being considered. The opinions of experts on the role of assessing the blood level of DOACs and the possibility of tactics for selecting doses of DOACs based on laboratory analysis data are given.
Web-Based And Whatsapp Gateway Tuition Payment Information System (Case Study Of SMK Antartika 2 Sidoarjo)
Authors: Imanda Almyra Gitta , Eviyanti Ade , Hindarto Hindarto , Setiawan Hamzah
Published: July 2023

The tuition paymant system at Vocational High School Antartika 2 Sidoarjo is still carried out semi- manually, meaning that transactions are already using a computer but data recaps are still recorded in books manually. This can slow down the payment process causing some problems. The method used is an object-oriented method using the Unified Modeling Language (UML). While the data collection techniques used are by way of observation, interviews, and documentation. This journal will discuss the design of a web-based tuition paymant information system and Whatsapp gateway using Whatsapp messages to be sent to each student's guardian. This plan aims to facilitate the administration of the finance department in recording tuition paymant data and making reports, as well as making it easier for students' parents to provide payment information via Whatsapp messages. The author hopes that with this application planning it is hoped that it will run more effectively and efficiently both in conducting tuition paymant transactions, as well as in making reports so that it can help the school and parents of students also easily get information on tuition payments.
Salud mental positiva en estudiantes universitarios según variables sociodemográficas durante el Covid-19 en Arequipa
Authors: Calizaya-López José Manuel , Pinto-Pomareda Hilda , Alvarez-Salinas Liliana , Lazo-Manrique Merly , Cervantes-Rivera Roberto , Lopez Norman
Published: July 2023

Introducción. El cambio en el sistema educativo por Covid-19 desencadenó efectos negativos en la salud mental, sin embargo, desde el enfoque de la psicología positiva existe una explicación para entender cómo las personas pue- den desarrollar actitudes positivas para hacer frente a las adversidades. Objetivo. Se analizó la salud mental posi- tiva en estudiantes universitarios según variables sociodemográficas durante el Covid-19 en la ciudad de Arequipa, Perú. Método. Estudio descriptivo, cuantitativo, transversal; participaron 2236 estudiantes universitarios a quienes se les registró información sociodemográfica (edad, sexo, estado civil, ocupación, tipo de familia, religión y área de estudios), utilizándose el instrumento de medición validado para determinar el nivel de salud mental positiva. Se efectuaron análisis estadísticos no paramétricos para la comparación de datos (U de Mann Whitney, Kruskal Wallis). Resultados. Se encontró nivel medio de Salud Mental Positiva (84.7%), en la capacidad de adaptación los estudian- tes presentaron nivel medio (50.4%); en la satisfacción personal y autonomía presentaron nivel alto (44.7%) y en la dimensión tolerancia a la frustración nivel medio (44.7%). Además, el comportamiento de la Salud Mental Positiva difirió de acuerdo con las variables sociodemográficas sexo, edad, estado civil, tipo de familia, ocupación, religión y área de estudios (p< 0.05). Conclusiones. Los estudiantes universitarios presentaron dificultades para adaptarse a los nuevos cambios originados por el Covid-19, demostrando fortaleza en la satisfacción personal; considerando que la mayoría de los estudiantes aún frente a dificultades como la pandemia desarrollaron la autonomía, presen- tando problemas para ser tolerantes a la frustración.
Factores asociados a la discriminación en personas que se inyectan drogas de dos ciudades de Colombia
Authors: Bedoya-Mejia Sebastian , Ramos-Jaraba Sara Milena , Berbesí-Fernández Dedsy Yajaira
Published: July 2023

Objetivo: Describir los factores asociados a la discriminación en personas que se inyectan drogas (PID), en Cúcuta y Armenia, Colombia. Método: se realizó un estudio transversal, utilizando el muestreo dirigido por encuestados (MDE) en 2021, donde participaron 532 personas que se inyectan drogas (PID). Los datos agregados se ponderaron y se calcularon razones de prevalencia crudas para medir la asociación entre los factores seleccionados y la discriminación, además se realizó un análisis de correspondencia múltiple para conocer el perfil de discriminación en las PID. Resultados: la prevalencia de discriminación fue del 62% (IC del 95%:57,7 - 66). Esta se asoció de forma independiente con ser mujer, ser habitante de calle, compartir jeringas, consumir más de 5 sustancias psicoactivas en el último año, percibirse vulnerable al VIH, no acceder al tratamiento de metadona, sentirse deprimido, nervioso o preocupado, haber perdido la conciencia por sobredosis de heroína y ejercer el trabajo sexual. Conclusiones: La evidencia presentada muestra una alta percepción de discriminación. Estos hallazgos pueden utilizarse en el país para generar estrategias que reduzcan la discriminación en diversos entornos y se creen políticas antidiscriminatorias.
Influencia de los sesgos cognitivos en Instagram
Authors: Bermejo Siller Carmen
Published: July 2023

La investigación gira en torno a una contextualización del marketing en redes sociales, en concreto se estudia la publicidad en Instagram. De la definición del comportamiento del consumidor a través de sus características y de un análisis de cómo se construye la publicidad en entornos digitales tales como las redes sociales, a través del empleo de los sesgos cognitivos que mejor se adapten al objetivo de la campaña. Tras ello se realiza un análisis de las estrategias publicitarias de la marca Freshly Cosmetics, en concreto, en cómo se aplican los sesgos cognitivos en su publicidad con el fin último de utilizarlo en y para Instagram, se hace una definición del perfil del consumidor potencial para este tipo de comunicaciones publicitarias de Freshly Cosmetics para finalmente acabar con un análisis de la influencia y efecto de los sesgos concretados contenidos en las comunicaciones publicitarias de Freshly Cosmetics sobre el usuario potencial de Instagram, a través de la realización de una encuesta en una muestra de 100 personas para focalizar la búsqueda de información en base a las variables y objetivos planteados y obtener los datos necesarios para posteriormente sacar conclusiones sobre ellos.
La inteligencia artificial en la lucha contra la desinformación en las presidenciales brasileñas 2022
Authors: Welter Lahis , Canavilhas João
Published: July 2023

A forte polarização entre dois grupos políticos nas eleições brasileiras de 2022 forçou um segundo turno e culminou no resultado eleitoral mais equilibrado da história. Essa situação proporcionou um ambiente de desinformação ainda mais complexo do que nas eleições presidenciais anteriores, tendo a inteligência artificial (IA) como protagonista na produção e disseminação de informações falsas, as chamadas fake news . No entanto, a IA foi igualmente utilizada para detetar, verificar e verificar conteúdos de desinformação, numa tentativa de equilibrar as forças. Este trabalho pretende analisar este segundo caso, ou seja, a ação realizada pelos bots do bemcontra o mal. Para isso, foram utilizadas metodologias quantitativas e qualitativas, analisando a atuação de dois portais brasileiros – Aos factos e Lupa – no combate às falsas informações relacionadas ao segundo turno entre Lula e Bolsonaro. Os resultados mostram que a maior aposta dos aplicativos foi o conteúdo fabricado, ou seja, produzido de forma falsa, utilizando o nome e o design da mídia para dar credibilidade às peças. Concluiu-se também que os bots e as equipas jornalísticas dos dois portais foram eficientes no sentido de captar, verificar, conferir e reportar com veracidade os conteúdos previamente manipulados.
Gobernanza algorítmica en la opinión pública: una propuesta de estudio sobre la percepción de los refugiados
Authors: Lancho Bances Carlos Manuel
Published: July 2023

En la actualidad no se puede hablar de opinión pública sin poner atención a la influencia que ejercen los algoritmos, a través de las plataformas digitales, en la creación de los imaginarios colectivos. En este sentido, las investigaciones recientes hacen referencia a la gobernanza algorítmica para explicar el rol de la inteligencia artificial en la organización de la actividad social y la percepción de la realidad. En este contexto, es importante recordar que, detrás del diseño y la programación de los algoritmos, se halla una infraestructura comercial que persigue fines económicos determinados, por lo que la neutralidad de estas herramientas debe ser puesta a debate. El presente artículo tiene como objetivo estudiar este nuevo escenario y presentar una propuesta y una metodología para estudiar la manera en la que las herramientas algorítmicas generan un clima de mayor discriminación de poblaciones históricamente marginalizadas, como es el caso de los refugiados en el escenario europeo (y sobre todo en España).
Inteligencia artificial generativa e Inteligencia colectiva crowdsourcing para desarrollar Ebooks periodísticos
Authors: Gómez Monsalve Wilmar Daniel
Published: July 2023

En tiempos actuales, donde la Inteligencia artificial se volvió protagonista dentro del campo de la comunicación y el periodismo, se integra con gusto la inteligencia colectiva a través del modelo de trabajo colaborativo: crowdsourcing, con el que se puede generar un amalgama de saberes y prácticas propias del ecosistema digital. Este artículo tuvo como objetivo sistematizar una ejercicio académico que tomó varias sesiones de clase y en donde los estudiantes de Comunicación social y la IA se unieron para generar un libro electrónico en el que se consignaron las herramientas propias de la IA que todo periodista debe conocer y utilizar para la optimización de su trabajo. A través de una metodología llamada proyecto de aula y utilizando aplicaciones y software especializados como Chat GPT, Dall-E, Adobe Indesign, Moodle, entre otros, se lograron desarrollar las tres etapas de preproducción, producción y posproducción del producto editorial y presentar el libro ya terminado a la audiencia virtual.
relaciones públicas a partir de la neurocomunicación y las emociones: teoría y práctica.
Authors: Barrientos-Báez Almudena
Published: July 2023

Las relaciones públicas se han convertido en un elemento clave para cubrir la necesidad de los públicos de encontrar confianza en los medios de comunicación, en la publicidad, en las organizaciones e instituciones. Además, aportan y generan una comunicación fluida y efectiva entre estas organizaciones y sus públicos. Después de la crisis derivada de la pandemia de la covid-19 a nivel mundial, la confianza en los medios se ha visto alterada por la abrumadora acción de los bulos, las fake news y la desinformación. En este monográfico se presentan un total de ocho artículos que muestran la actual situación de áreas profesionales y académicas implicadas de lleno en la transformación social que estamos viviendo. Un mosaico de fácil lectura y, por qué no, de factible aplicación. El diseño de eventos experienciales resulta ser una solución dirigida a lo que deseas que haga sentir tu marca. Sabiendo dónde se encuentra el foco y el objetivo planteado, se desarrollarán acciones personalizadas tratando de emocionar al usuario porque lograremos que se identifique con la marca.
Evaluation of Asphalt Film Thickness and Metallic Material Leaching of Oxidizing Slag used as Aggregates in Dense-Graded Asphalt Concrete
Authors: Chang Jia-Ruey , Chien Hsiao-Tsun
Published: July 2023

Electric-arc-furnace steelmaking uses scrap iron and steel as raw materials. However, scrap iron and steel have complicated sources and contain heavy metal components, which may be released into the environment after long-term wear and tear. Oxidizing slag is a by-product of the electric-arc-furnace steelmaking process and approximately 1.2 million metric tons of oxidizing slag are produced every year in Taiwan. Substituting oxidizing slag in place of fine aggregates in dense-graded asphalt concrete, the main aims of this study are to evaluate the water resistance and asphalt film thickness, to explore the performance of oxidizing slag as paving material, to examine current regulations for using the dissolved amount and total amount of heavy metals, and to assess the environmental compatibility. The results show that, owing to the complicated sources of oxidizing slag, the basic properties should be checked for each batch and trial mixing should be carried out before producing dense-graded asphalt concrete in order to confirm the mixing time to achieve uniformity. The results also show that using oxidizing slag in dense-graded asphalt concrete yields good performance. In addition, the results of the toxicity characteristic leaching procedure (TCLP) meet the regulation requirements. However, the amounts of heavy metal elements obtained through microwave-assisted aqua-regia digestion exceed the monitoring standards for food crops. Considering environmental compatibility, it is recommended that controlling the total amount of heavy metals in oxidizing slag should be included in regulatory requirements.
FedRCD: A Federated Learning Algorithm Leveraging Distribution Extraction and Community Detection for Enhanced Clustering
Authors: Wang Ruicong , Bian Naizheng , Wu Yingjun
Published: July 2023

Clustering clients and performing federated learning within clusters is an effective method for overcoming the constraint of traditional federated learning algorithms in non-IID data scenarios. However, existing methods often rely on iterative processes and model parameters to represent and cluster clients, resulting in significant computational overhead and unsatisfactory clustering outcomes. To overcome these limitations, we propose a novel one-shot clustering federated learning algorithm called FedRCD. This algorithm extracts distribution information from clients’ datasets in a single step to represent them, reducing the reliance on model parameters. It further organizes clients into a graph and constructs clustering relationships using the Louvain algorithm, removing the need for pre-specifying the number of clusters. Experiments show that FedRCD significantly enhances the training effectiveness of neural networks compared to other federated learning algorithms in various non-IID data scenarios. Notably, on the CIFAR10 dataset, FedRCD achieves an impressive 37.08% accuracy improvement over the classical FedAvg and a 1.89% improvement over the recently released FeSEM, while demonstrating superior fairness performance.
Taxonomic and phylogenetic evidence reveal two new Russula species (Russulaceae, Russulales) from northern Thailand
Authors: Paloi Soumitra , Kumla Jaturong , Karunarathna Samantha , Lumyong Saisamorn , Suwannarach Nakarin
Published: July 2023

Russula is the most diverse genus within the family Russulaceae and has an ectomycorrhizal association with many host trees. During the monsoon season of 2022, five Russula specimens were collected in northern Thailand. After morphological and molecular analyses, the five specimens were determined to belong to Russula subgenus Heterophyllidia. A single specimen belonged to R. bellissima. Four other collected specimens were distinct from all other known species. We have identified these specimens as two new species, namely R. pseudomodesta and R. sribuabanensis. Russula pseudomodesta belongs to the subsection Modestinae, while R. sribuabanensis belongs to the subsection Virescentinae. The phylogenetic placement of two new species within Russula has been confirmed based on sequences of the nuclear internal transcribed spacer (nrITS) region and a large subunit (nrLSU) of the nuclear ribosomal RNA (nrRNA). Comprehensive morphological descriptions, field photographs, and comparisons of two new species with other morphologically and phylogenetically closely related species have been provided.
3D finite element analysis of stress distribution in dental tissues and materials as a result of oblique and horizontal forces after regenerative endodontic treatment Part II: Comparison of Material Thickness
Authors: Demircan Beril , Demir Pınar
Published: July 2023

Aim
This study aimed to evaluate the stress distribution caused by secondary trauma forces after regenerative endodontic treatment (RET) using different thicknesses of coronary barrier material, with three-dimensional finite element analysis(FEA).
Method
A control model was created using the tomography image of the immature maxillary central tooth with computer software. Study models were created with the modulus of elasticity and Poisson’s ratio of the materials used in RET.Enamel, dentin, cementum, periodontal ligament, cortical, and cancellous bone were modeled. Coronary barrier materials were applied in 3mm and 5mm thicknesses(Model 1:control model, model 2:3mm/Calcium Enriched Mixture(CEM), model 3:3mm/Mineral Trioxide Aggregate(MTA), model 4:3mm/Biodentin, model 5:5mm/CEM, model 6:5mm/MTA, model 7:5mm/Biodentin). Forthe trauma force simulation, 300N force in the horizontal direction was applied to the buccal surface of the tooth in the first scenario. For the second scenario, maximum bite force simulation, a force of 240N in the oblique direction was applied to the palatal surface of the tooth. FEA was performed with Algor Fempro. The resulting stresses were recorded as Von Mises, maximum and minimum principal stresses.
Results
Lower stress values were obtained in 5mm models compared to 3mmmodels. However, the difference between them was insignificant. Lower stress values were obtained in all RET models compared to the control model. The lowest stress values in dental tissues and bone tissue were obtained inthe CEM models.
Conclusion
This is the first study in which the stress caused by different thicknesses of CEM on dental tissues was evaluated with FEA. RET strengthens immature teeth biomechanically CEM andBiodentin are more successful materials in stress distribution than MTA. Considering the cost of treatment, 3 mm material thickness is ideal for RET since there is no significant difference between the stress values resulting from the use of 5mm and 3mm coronary barrier material.
Trajectories of Dental Caries From Childhood to Young Adulthood: Unsupervised Machine Learning Approach
Authors: Ogwo Chukwuebuka , Levy Steven , Warren John , Caplan Daniel , Brown Grant
Published: July 2023

Objective To determine the dental caries trajectories over the life course (from age 9 to 23) using an unsupervised machine learning approach.Methods This is a longitudinal study of caries trajectories over a life course using data from 1,382 individuals from the Iowa Fluoride Study birth cohort. The trajectory analysis of caries in the permanent dentition at ages 9, 13, 17 and 23 was performed using the unsupervised machine learning algorithm known as K-means for Longitudinal Data (KmL), a k-means based clustering algorithm implemented in R specifically designed for analyzing longitudinal data. The trajectory grouping was performed by assessing the distances of the individual trajectories from the centroid and the prediction of the “best” partition was performed based on the Calinsky & Harabatz criterion. The number of cluster partitions assessed was 2 to 6. The number of re-runs with different starting conditions for each number of clusters was 20.Results The trajectory analysis identified three trajectory groups with 70.5%, 21.1%, and 8.4% of participants in the low, medium, and high caries trajectory groups, respectively. The mean D2+MFS counts of the low caries trajectory groups at ages 9, 13, 17, and 23 were 0.23, 0.37, 1.10, and 1.56, respectively. The mean D2+MFS counts of the medium caries trajectory groups at ages 9, 13, 17, and 23 were 0.92, 2.09, 6.24, and 9.55, respectively. The mean D2+MFS counts of the high caries trajectory groups at ages 9, 13, 17, and 23 were 1.49, 4.80, 12.91, and 22.52, respectively. There were steeper increases in the D2+MFS scores of the three trajectory groups between age 13 and 17, with less steep but also strongly positive slopes from age 17 to 23, suggesting that the period from age 13 to 17 is the highest risk period.Conclusion There was an increase in the trajectory slopes after age 13 which might be due to changes in risk factors. The next step in this study will be to identify those factors that predict trajectory group membership by modeling their relationships using supervised machine learning techniques.
Uncovering Drone Intentions using Control Physics Informed Machine Learning
Authors: Perrusquia Adolfo , Guo Weisi , Fraser Benjamin , Wei Zhuangkun
Published: July 2023

Fully autonomous aerial platforms or drones are increasingly used across diverse application areas. Uncooperative drones do not announce their identity nor file flight plans and can pose a potential risk to a variety of critical infrastructures. Understanding an uncooperative drone's intention is important to assigning risk and executing countermeasures. Drones have rapidly changing design, flexible capabilities, and diverse underpinning algorithms. This makes distinguishing malicious from naive intentions across platforms difficult. Intentions are often intangible and unobservable, and a variety of tangible intention classes are often inferred as a proxy. However, inference of drone intention classes (e.g., via inverse learning) using observational data alone is inherently unreliable due to observational and learning bias.

Here we develop a novel control-physics informed machine learning (CPhy-ML) that can robustly infer across intention classes, out performing over expert-defined anomaly detection and inverse learning approaches. Our CPhy-ML complementary learning couples the representation power of deep learning with the conservation laws of aerospace control models, reducing bias and instability. The results in simulation and experimentation demonstrate that we can find common intention patterns across the inferred intention classes, ranging from trajectory to reward goals. We believe that this framework can provide deeper insight into the complex nature of intention and a firm step towards to its smooth integration in current counter drone technologies. The techniques developed here can aid the enforcement of drone incursions in a time where geo-fencing is no-longer efficiently enforceable. As transport and operational autonomy is increasingly used, enforcement algorithms can also inform the design of better criminal justice system and safer autonomous systems themselves.
Prasinezumab slows motor progression in rapidly progressing early-stage Parkinson’s disease
Authors: Pagano Gennaro , Taylor Kirsten , Cabrera Judith , Simuni Tanya , Marek Kenneth , Postuma Ronald , Pavese Nicola , Stocchi Fabrizio , Brockmann Kathrin , Svoboda Hanno , Trundell Dylan , Monnet Annabelle , Doody Rachelle , Fontoura Paulo , Kerchner Geoffrey , Brundin Patrik , Nikolcheva Tania , Bonni Azad
Published: July 2023

Background
Prasinezumab, a monoclonal antibody that binds aggregated alpha-synuclein, is currently being investigated as a potential disease-modifying therapy in early-stage Parkinson’s disease (PD). In the PASADENA Phase II study, prasinezumab-treated individuals exhibited slower progression of motor signs than placebo-treated participants (MDS-UPDRS Part III). Here, we explore whether prasinezumab showed greater benefits on motor progression in rapidly compared with more slowly progressing subpopulations of PD.
Methods
Prasinezumab’s effects on disease progression were assessed in pre-specified rapidly progressing and more slowly progressing subpopulations of PD during the double-blind phase of PASADENA (e.g., participants taking MAO-B inhibitors at baseline vs. treatment-naïve participants).
Results
In the rapidly progressing subpopulations of PASADENA, participants treated with prasinezumab showed less decline in MDS-UPDRS Part III compared with more slowly progressing subpopulations of PD.
Conclusion
Efficacy of prasinezumab was greater in individuals with early-stage PD with a more rapidly progressing clinical phenotype.