bluuebunny/crossref_metadata_2025 huggingface dataset:
Chimeric Antigen Receptor T-cell based cellular therapies for cancer: An introduction and Indian perspective
Authors: Rathod Reena J. , Sukumaran Reghu K. , Kedia Neelam , Kumar Jeevan , Nair Reena , Chandy Mammen , Gandikota Lakshmikanth , Radhakrishnan Vivek Sulekha
Published: September 2024

Using one’s own immune system for curing cancer has been an active field of research in cancer biology and therapeutics. One such opportunity in cellular immunotherapy is adoptive cell transfers. With the recent approval of CAR-T therapy as a cancer treatment, a whole new paradigm of cancer treatment has opened-up, with a ray of hope for relapsed/refractory cancer patients. Despite promising clinical outcomes, the therapy is in its early phase and remains out of reach for most patients due to its high cost and logistic challenges. In India, these therapies are unavailable and further confounded by the economic challenges and a large population. In this review, we discuss various aspects of T-cell immunotherapies with a special focus on CAR-T in the Indian scenario. We touch upon the basic scientific aspects, mechanism of action, manufacturing, clinical aspects and commercial aspects of the CAR-Tcell therapies and its future worldwide and in India.
Clinical efficacy evaluation of the implantation of a diffractive trifocal intraocular lens in high myopia eyes: Two-year follow-up
Authors: Liu Shasha , Wang Yao , Kang Tingting , Lv Wenhao , Ma Ruonan , Yu Ying , Yin Lianrong
Published: September 2024

Purpose:

To evaluate the long-term subjective and objective visual quality after implantation of a diffractive trifocal intraocular lens (IOL) in high myopic eyes.

Methods:

A total of 53 eyes from 38 patients with high myopia who underwent phacoemulsification and trifocal IOL implantation were investigated. The visual acuity, contrast sensitivity, diopter, defocus curve, and objective visual quality at 1 month, 3 months, 1 year, and 2 years after surgery, as well as the satisfaction questionnaire and VF-14 scale, were statistically analyzed.

Results:

The average age was 53.14 ± 4.70 years. The average preoperative spherical equivalent was −10.77 ± 3.98 D. Two years after surgery, 94.3% of the patients achieved an uncorrected distance visual acuity of 0.1 (LogMAR), and 84.9% and 94.3% of the patients had SE within ±0.50 D and ±1.0 D, respectively. The defocus curve was smooth and at a high value within the range of 0 D to −2.50 D. In CS or objective visual quality, there was no significant difference at 3 months, 1 year, and 2 years after operation (all P > 0.05). The rate of spectacle independence was 100%. The proportion of patients with moderate or severe glare and halo was 10.5% and 13.2%, respectively. Furthermore, 23.7%, 26.3%, and 18.4% of the patients had difficulties in reading small font, doing delicate tasks, and driving or riding at night, respectively.

Conclusion:

The diffractive trifocal IOL implantation provided good distance, intermediate, and near uncorrected visual acuity for patients with cataracts and high myopia. It was safe, effective, predictable, and stable. It provided long-term good visual quality after surgery, with high spectacle independence and high patient satisfaction.
Amniotic membrane graft (AMG) for persistent epithelial defects following infective corneal ulcers and keratitis – A systematic review
Authors: Thevi Thanigasalam , Abas Adinegara L , Dua Harminder S
Published: September 2024

Management of nonhealing corneal ulcers is challenging as it can lead to complications such as melting, descemetocele, and perforation, which can be prevented by amniotic membrane graft (AMG). The absence of any review (English language) on AMG for corneal ulcers prompted us to conduct this review. We looked for clinical trials (randomized and controlled) on the effect of AMG combined with other treatments, through various search engines utilizing the terms amniotic membrane and corneal ulcer. All patients who received AMG and/or conventional medication were included. Risk of bias tools derived from Cochrane collaboration were used to ascertain the standard and quality of the trials. Visual acuity and epithelial healing time were the main outcome measures studied. Three trials were finally selected for analysis. AMG was noted to be associated with better uncorrected visual acuity and reduction in neovascularization. There was no difference in best corrected visual acuity, epithelial healing time, and corneal opacity. There is evidence that the use of AMG is associated with improved uncorrected visual acuity as well as reduction in neovascularization of the cornea among patients with corneal ulcers, but there was no improvement in epithelial healing time or corneal opacity. Further multicenter randomized controlled trials are needed to elicit the beneficial effects of the intervention and augment the validity of this review.
Assessment of Nasal Morphology within various Sagittal Skeletal Growth Patterns—A Cross-sectional Cephalometric Study
Authors: Shah Romilkumar , Shah Aakash
Published: September 2024

ABSTRACT

Aim:

The present research aims to assess the nasal morphology within various Sagittal skeletal growth patterns like Classes I, II and III.

Material and Method:

The present research assesses various nasal parameters within equally distributed 150 lateral cephalograms having Skeletal Classes I, II, and III by manual tracing. The study identified differences in nasal morphology across different skeletal classes.

Result:

Naso-facial angle and Profile angle were greater in Class II cases, whereas Naso-mental angle was greater in Class III cases.

Conclusion:

Nasal morphology must be considered for accurate diagnosis, treatment planning, and facial reconstruction.
Prevalence, Pattern, and Etiology of Hearing Loss in a Tertiary Otolaryngology Center in Central Yemen
Authors: Al-Balasi Abdulkareem K. , Omer Dina M.
Published: September 2024

Background and Aims:

Hearing loss (HL) is a significant public health concern. Research on its prevalence and pattern are crucial for understanding its causes, identifying high-risk populations, developing prevention strategies, and ultimately, improving the quality of life for people with HL. Therefore, this study aims to investigate the prevalence, pattern, and causes (etiology) of HL among patients attending our ENT Hospital.

Study Design:

This study was a retrospective review of existing medical records of patients from a Tertiary ENT Hospital in Yemen to determine the prevalence, patterns, and causes of HL among patients attending ENT centers.

Results:

A total of 951 patients were included in this study. The prevalence of HL was found to be 29.7%. The most commonly affected age group was 11–20 years old, with conductive HL being the most frequent subtype 65.1%. Sensorineural HL followed at 27.8%, and mixed HL was present in 7.1% of patients. Chronic suppurative otitis media (CSOM) 29.5% was identified as the most common cause of HL, followed by otitis media with effusion and wax impaction.

Conclusion:

HL is a significant public health concern in developing countries. CSOM is a major contributor to HL in this population, and age plays a role in the type of HL experienced.
Copper Wire, Bare, High Purity
Authors:   AMS D Nonferrous Alloys Committee
Published: September 2024

This specification covers one type of copper in the form of wire (see 8.5).
Aluminum Bronze Alloy, Sand Castings, 85Cu - 11Al - 3.6Fe, Solution Heat Treated and Tempered
Authors:   AMS D Nonferrous Alloys Committee
Published: September 2024

This specification covers an aluminum bronze alloy in the form of sand castings (see 8.5).
Questioning profit inflation as an explanation of the post-pandemic inflation
Authors: Lavoie Marc
Published: September 2024

The COVID-19 pandemic eventually gave rise to large increases in profits, profit shares and inflation rates. A major controversy has developed among economists and in the media about whether this was largely caused by profit inflation, that is, by increases in the percentage mark-ups set by firms. The paper attempts to clear some confusions regarding the issue of profit inflation, dealing with its definitions and the complexities of its measures. In particular, it shows that increases in economic activity and increases in the relative cost of domestic or imported inputs will lead to an increase in realized profit margins even if percentage mark-ups remain constant. The paper also lists a series of factors that may mitigate the results of empirical studies that show an increase in the aggregate value of this percentage mark-up.
Inflation and income distribution in Brazil from a Kaleckian perspective*
Authors: Rolim Lilian
Published: September 2024

This article shows that income inequality and inflation in Brazil are multidimensional phenomena linked to the unemployment rate and to the foreign sector. Consequently, the relationship between inflation and income distribution depends on the source of inflationary pressures, as evident in the 2000 to 2020 period. This reflects significant differences in the dynamics of inflation in the tradable and non-tradable goods sectors and is consistent with the Kaleckian framework. Yet, a missing inequality puzzle is identified, suggesting that changes in the Industry sector’s relation with the foreign sector altered some of the relationships analyzed. The article also investigates the influence of the foreign sector on the intensity of the domestic distributive conflict in Brazil and discusses some implications of an intensified distributive conflict in terms of policies and regulations that alter the bargaining power of workers.
Prediction of potential geographic distribution of Capparis spinosa
Authors: Çıvğa Alican , Özdemir Serkan , Gülsoy Serkan
Published: September 2024

Capparis spinosa is a medicinal plant with economic (e.g., food, animal breeding, medicine) and ecological (e.g., erosion control, fighting wildfires) importance that is distributed in the western and southern coastal regions of Turkey. The MaxEnt model was used to simulate potential distribution areas of C. spinosa with the effect of environmental conditions. The results showed that the potential suitable area of C. spinosa is 6109 hectares, mainly distributed below 1000 meters in Babadağ Region. It was determined that the variables contributing to the model were bedrock, elevation, topographic position index and hillshade index, respectively. The acquired model presented excellent performance according to its AUC values (Training AUC: 0.909 and test AUC: 0.906). It is thought that the results revealed in the study will provide an insight for future investigations to be carried out for the species.
The effect of micro topographic features on the site selection of European ground squirrels (Spermophilus citellus): A case study from Tekirdag province, Thrace Peninsula (Türkiye)
Authors: Özşahin Emre , Öztürk Mikayil
Published: September 2024

The European ground squirrel (Spermophilus citellus) is a small mammal that inhabits the grasslands of central and southeastern Europe and is adapted to the Mediterranean climate. It is a group-living, semifossorial and mostly herbivorous rodent, and is considered an ecosystem engineer and a cornerstone of rangelands due to the benefits it provides to the ecosystem. The scientific determination of the habitat selection of European ground squirrels, whose population has decreased significantly in recent years due to various human activities, is essential for the survival of this endangered species. Micro topography is one of the main factors affecting the habitat selection of this creature, which hibernates in its individual caves for a long period of time from early fall to early spring. Therefore, the aim of this study was to investigate the effect of micro topographic features on the nest selection of European ground squirrels. The study was shaped according to the results of a sample area in Tekirdag province in the Thracian Peninsula of Türkiye, one of the southernmost distribution areas of European ground squirrels in Europe. The main data of the study consisted of high-resolution digital elevation model (DEM) and ortho-photo images obtained using an unmanned aerial vehicle (UAV) during field studies. These data were processed with Geographic Information Systems (GIS) techniques using an ecological niche modeling (ENM) approach. As a result of the study, it was determined that among the micro topography features in the sample area, the aspect factor was more important (56.412%) in the nest preference of the species. The results of the study shed light on the plans to be made for the maintenance and protection of potential and existing habitats, as well as supporting specific measures to be taken to strengthen the population of the species, which is under threat of extinction, and to improve habitat characteristics. It can also be used to expand areas important for the conservation of the species and improve the success of future reintroduction or introduction programs.
Comparison of stem cell CD45/34 fluorescent density with stem cell mobilization in patients under 65 and over
Authors: Meriç Neslihan , Parmaksız Ayhan , Gulbas Zafer
Published: September 2024

Abstract

In our research, we attempted to compare CD45/34 MFI (Mean Fluorescent Intensity) in patients younger and over 65 years of age with hematopoietic stem cell mobilization (HSCM).
The research involved a group of 76 individuals who had different types of cancer and were identified at the Bone Marrow Transplantation (BMT) Unit of Anadolu Medical Center Hospital from 2015 to 2016. To mobilize HSCs, participants were administered daily granulocyte colony-stimulating factor (G-CSF) (10 µg/kg/day) under the skin for 7-8 days. Calculating the appropriate level of peripheral blood (PB) CD34+ took into account the patients' WBC (White Blood Cell) counts. Our research revealed that HSCM patients above 65 had statistically greater CD45/34 MFI values than those under that age. Although the age factor for HSCM is important, according to our findings, age is not seen as a negative mobilization factor for HSCM in patients aged 65 and over, and should be supported by larger studies. Our research revealed that patients over 65 who underwent HSCM had statistically greater CD45/34 MFI values than younger patients. Given the decline in SC production observed in individuals aged 65 and above, along with the potential for other accompanying diseases, our results hold promise for elderly patients. However, it is important to validate these findings through multicenter studies with a larger patient population, while also taking into account the presence of other subsequent diseases in the patients under observation.

Keywords: Stem Cell Mobilization, Mean Fluorescent Intensity, CD45/34, Hematopoietic stem cell transplantation
Técnicas aplicadas de Informática Forense para la investigación de delitos telemáticos
Authors: Pérez Chacón Rubén , Gil Gamboa Adrián
Published: September 2024

El libro Técnicas aplicadas de Informática Forense para la investigación de delitos telemáticos está diseñado como una guía esencial y accesible para la asignatura de Informática Forense, impartida en el Doble Grado en Derecho y Criminología (tercer curso) y en el Grado en Criminología (cuarto curso) de la Universidad Pablo de Olavide. Este texto se centra en proporcionar a los estudiantes una formación práctica, enfocada en la aplicación directa de técnicas y herramientas para la identificación, análisis y resolución de delitos informáticos. A lo largo de sus capítulos, se abordan temas clave como la seguridad informática, el manejo de evidencias digitales y la implementación de metodologías forenses en la práctica diaria. Se hace hincapié en la aplicación de conceptos relevantes, desde el análisis de sistemas y redes hasta la utilización de técnicas criptográficas modernas en la preservación de la evidencia digital. El libro incluye secciones dedicadas a la práctica forense en distintos entornos, como equipos informáticos, redes de comunicación y dispositivos móviles, detallando paso a paso los procedimientos para la recolección, preservación y análisis de evidencias digitales. Además, se explora el marco legal y normativo que rige las investigaciones forenses, ofreciendo una perspectiva práctica sobre cómo aplicar estas leyes en la lucha contra los delitos cibernéticos. Este recurso no solo está pensado para estudiantes de criminología y derecho, sino también para profesionales que buscan actualizar sus habilidades prácticas en la investigación forense digital. Con un enfoque predominantemente práctico y aplicable, el libro prepara a los lectores para enfrentar los retos del ciberespacio con habilidades concretas y operativas, asegurando que adquieran las competencias necesarias para gestionar la evidencia digital, entender la cadena de custodia y ejecutar técnicas de análisis forense en diversos dispositivos y redes. El objetivo principal es dotar a los alumnos de las herramientas y experiencias prácticas necesarias para desenvolverse profesionalmente en el ámbito de las Tecnologías de la Información y la Comunicación (TIC), y fortalecer así su capacidad para realizar investigaciones forenses más eficientes y confiables. En ningún caso, el objetivo será la resolución de los ejercicios de forma guiada y secuencial. Dicha resolución debe ser competencia de los alumnos y podrán resolverlos en clase con ayuda del profesorado o de forma independiente y autónoma. Además, existen ciertos materiales digitales para la resolución de los ejercicios que se proporcionarán únicamente en clase. Cabe destacar que todos los alumnos tendrán acceso a una máquina virtual denominada “Informática Forense” dentro de la aplicación MyApps, proporcionada por la Universidad Pablo de Olavide.
Value-at-Risk: una comparación del modelo GARCH con distribución de error normal y t-Student durante la pandemia
Authors: Maldonado Méndez Luis Reynaldo , Maldonado Álava Pedro Luis , Méndez Maldonado Mónica Guadalupe , Maldonado Méndez Gianella Joyce
Published: September 2024

El objetivo principal de esta investigación es comparar la optimalidad de dos carteras de inversión que utilizan el criterio de minimización del Value at Risk (VaR). La volatilidad es estimada mediante un modelo de heterocedasticidad condicional autorregresiva generalizada GARCH (1,1) que difiere en la distribución de los errores: normal y t-student. El portafolio fue creado con las acciones provenientes de 9 stocks del sector financiero que cotizan en EE.UU. La comparación entre estos dos modelos concluye que el modelo de colas anchas fue superior al normal, debido al mayor número de aciertos durante la mayoría de los eventos, incluso reportó una alta precisión en uno de los eventos antes de que la OMS declare al Sars-Cov-2 como pandemia, momento a partir del cual ambos modelos llegan a ser deficientes, aunque el modelo de colas anchas mantiene una leve ventaja en dichos eventos.
El internet y su impacto en la economía digital con el uso del crowdfunding y crowdsourcing
Authors: Ulloa Armijos Ana , Vélez Cecilia , Jácome Tapia Julio
Published: September 2024

En un entorno globalizado es importante tener en cuenta que los nuevos modelos de negocios que salgan al mercado, cuyos proyectos son expuestos en plataformas, deben cumplir con los requerimientos de un buen servicio online, experiencia del cliente, conexión, formación del recurso humano que dirige los proyectos, conocer a los clientes, entre otros. Otro punto importante a considerar son los modelos regulatorios aplicados a las plataformas en el aspecto legal que debería ser unificado al ser establecido a nivel mundial para este tipo de modelo de negocios que aplica en este estudio el crowdfunding y crowdsourcing. Se presenta el tipo de crowdfunding más usado por los generadores de proyectos y los expuestos en diversas plataformas. Desde el punto de vista del usuario de estas, también se expone los pasos necesarios para publicar los nuevos negocios, teniendo en cuenta cual es la más adecuada para aplicar. A su vez se exponen plataformas para inversionistas desde el ámbito del crowdsourcing, y conocer los diversos riesgos que se pueden presentar y como mitigarlos. La presente investigación está sustentada en encuesta realizadas a estudiantes de último ciclo de diferentes carreras relacionadas al tema de crowdfunding. En cuanto al crowdsourcing, se presentan datos en base a las apreciaciones y experiencias de especialistas e inversionistas, obteniendo una escala probabilística de ocurrencia. Es necesario tener en cuenta la importancia en la toma de decisiones con relación a la selección de un tipo de plataforma, dado un conocimiento previo, de los sectores a los cuales e están enfocadas y que requerimientos solicitan.
APPLYING THE EXPERIENCE OF EU COUNTRIES FOR THE REVITALIZATION OF VILLAGES USING BIOMASS AS A RENEWABLE ENERGY SOURCE
Authors:   Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia - University of Belgrade, Mladenović Milica R. , Vučićević Biljana S. ,   Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia - University of Belgrade, Erić Aleksandar M. ,   Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia - University of Belgrade
Published: September 2024

The EU has recognised the issue of rural depopulation and has taken political measures to solve it. Smart rural communities, organised in cooperatives using indigenous biomass for energy purpose , are considered an effective solution to alleviate this problem by providing smart services to the local population, leading to higher economic competitiveness. The experience of Austria, Italy, Denmark, the Netherlands, and other countries that are leaders in this field, are valuable and can be implemented in our country as well. Restarting the agricultural village cooperative and directing them to produce, in addition to traditional crops, more profitable ones (medicinal plants, fruits, vegetables), to then process, store and market them at the most favorable time, for that and for animal breeding, using their autochthonous energy resources – biomass, is a way to organize sustainable production even on small rural farms. In addition to the above, all thermotechnical equipment and installations can be produced in domestic small and medium enterprises. In this approach, the country’s reindustrialization can begin while also reducing the decline of villages. The paper presents an overview of the steps that can lead to implementation of the above activities, noting that some parts of this work have already been presented before.
Tratamento de doenças peri-implantares: um desafio atual para a Odontologia - uma revisão de literatura
Authors: Schneider Wesley
Published: September 2024

A implantodontia surgiu com o objetivo de reabilitar pacientes edêntulos totais ou parciais de maneira fixa e eficiente retomando funções estéticas e funcionais. No entanto há agravantes e problemas que surgiram com a evolução clínica de casos com implantes dentários. Assim como a periodontia, uma subárea surgiu na implantodontia tendo com preocupação estudar e controlar as doenças que acometem os tecidos peri-implantares. O objetivo deste trabalho foi propor uma breve revisão de literatura sobre a evolução da reabilitação com implantes dentários e apresentar as a classificação e terapias alternativas para casos de doença peri-implantar, e apresentar alguns protocolos de tratamento para esses casos.
Desafios mecânicos em próteses sobre implantes
Authors: Morais Marcos Bernal de
Published: September 2024

A saúde e a qualidade de vida são profundamente impactadas pela dentição, e a perda de dentes, conhecida como edentulismo, apresenta desafios funcionais, psicossociais e estéticos ao paciente. A reabilitação com próteses sobre implante é uma opção viável, mas pode enfrentar complicações mecânicas, como afrouxamento de acessórios, fratura de pilares e perda de retenção de componentes protéticos. A identificação precoce dessas complicações é essencial para o reestabelecimento da prótese, portanto uma abordagem proativa, baseada em planejamento e compreensão dos fatores mecânicos e oclusais atuantes é fundamental para a prevenção ou resolução desses desafios. A compreensão detalhada desses aspectos não apenas facilita a prevenção de desafios, mas também orienta intervenções eficazes para garantir o sucesso a longo prazo da reabilitação com próteses sobre implantes. A abordagem integrada, considerando tanto a perspectiva técnica quanto a clínica, é fundamental para otimizar os resultados e a satisfação do paciente.
Reabilitação provisória de longa duração com resina composta pela técnica do index transparente de silicone: acompanhamento clínico de 15 meses
Authors: Schneider Wesley
Published: September 2024

A fase provisória em qualquer reabilitação dentária é essencial para a definição de alguns parâmetros para a fase definitiva, sendo eles estética, função, oclusão e adaptação do paciente. O objetivo desse estudo foi relatar um caso clínico sobre a utilização de restaurações provisórias aderidas confeccionadas através da técnica do index transparente de silicone. Houve um acompanhamento de 15 meses sobre uma reabilitação total em um paciente de sexo masculino de 59 anos, que apresentava desgastes severos nos dentes inferiores e iria realizar cirurgia de reabilitação dos dentes superiores com implantes dentários e prótese do tipo protocolo. A realização dos provisórios na arcada inferior teve objetivo de reestabelecer a dimensão vertical de oclusão e parâmetros estético e de oclusão, até que a prótese do tipo protocolo superior fosse concluída. As restaurações em resina são uma excelente alternativa para esse tipo de reabilitação, oferecendo uma condição ideal para reestabelecer a função mastigatória, estética de maneira imediata. Além disso o material obteve ótimo comportamento físico durante os 15 meses de acompanhamento.
The Relationship Between Defense Expenditures and Economic Growth: The Case of Türkiye
Authors: Alirzayev Hilal , Çifçi İsmail
Published: September 2024

This study aims to determine the impact of defense expenditures on economic growth in Türkiye for the period 1996-2022. Economic growth and defense are vital for the welfare and security of countries. Therefore, a three-stage time series method was employed to determine the impact of defense expenditures on economic growth in Türkiye. In the first stage, the stationarity levels of the variables were investigated using the Augmented Dickey-Fuller (ADF) unit root test and the Phillips-Perron (PP) unit root test. In the second stage, the presence of long-run relationships between the variables was examined using Johansen cointegration analysis. In the final stage, the long-run coefficients between the variables were estimated using the Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR) methods. The findings obtained from the analysis can be summarized as follows: i) According to the ADF and PP unit root test results, it was found that all variables contain unit roots at level values and become stationary when their first differences are taken. ii) In the Johansen cointegration analysis, the trace test and maximum eigenvalue test indicate that there are 2 cointegration equations between the variables. iii) According to the FMOLS, DOLS, and CCR methods, it was found that a 1 unit increase in the share of defense expenditures reduces economic growth approximately by 0.0776%.
GENETIC DIVERSITY OF Moringa oleifera Lam. IN SOUTHEASTERN MEXICO
Authors: Ruiz-Hernández Rafael , Pérez-Vázquez Arturo , Hernández-Rodríguez Martha , García-Pérez Eliseo , Morales-Trejo Fredy , Soto-Hernández Ramón Marcos
Published: September 2024

Moringa oleifera Lam. is a plant with nutritional and nutraceutical properties. It was introduced from India to Mexico, and some of its ecotypes are cultivated for industrial use. These ecotypes show morphological variations, indicating genetic variation. Therefore, the purpose of this study was to evaluate eight simple sequence repeat (SSR) loci to assess the genetic diversity of 10 cultivated M. oleifera populations collected from the southeast of Mexico. All markers generated a total of 127 alleles, with 15.8 alleles per locus. The polymorphic information content of markers was 0.869, with an average heterozygosity of 0.194. At the population level, the Nei´s gene diversity was found to be 0.66, with 4.9 different alleles per locus and 5.2 genotypes on average per accession. The distribution of genetic variation was 20 % among populations, 58 % between individuals, and 22 % within individuals. The principal coordinate analysis (PcoA) plot and unweighted pair group method with arithmetic mean (UPGMA) linkage revealed three groups, corresponding to the three original genetic populations identified through structure analysis (Delta K = 3). Results showed significant differences in genetic diversity in M. oleifera populations stablished in Southeastern Mexico, which can be leveraged to increase the use of this germplasm.
Neurological Interplay between Tinnitus and Temporomandibular Disorders: A Narrative Review of Mechanisms, Diagnosis and Treatment Strategies
Authors:   Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada, Elsaraj Sherif M
Published: September 2024

This manuscript explores the interconnectedness of Tinnitus and Temporomandibular Disorders (TMD), two conditions affecting the same anatomical region due to their proximity to the jaw and ears.
An Integrated Physical Security to Enhanced Smart Campus Conceptual Framework
Authors: Mustapha Usman , Haruna Khalid , Mustapha Rabi , Kakudi Habeebah Adamu
Published: September 2024

Background: A smart campus is an educational institution that uses Internet of things (IoT) devices, sensors, data analytics and other various digital technologies to improve various aspects of campus life such as security, learning experiences, communication etc to create a more connected and efficient campus environment. The quest of excellence in higher education has become inseparably intertwined with the implementation of smart campus solutions as universities and colleges work to develop more connected, intelligent, and responsive settings. The way educational institutions work has changed as a result of the integration of cutting-edge technologies and data-driven solutions, fostering creativity, efficiency, and better learning experiences. Studies have proposed the concept of a smart campus framework and investigated the effect of its implementation on the campus However, one of the often-overlooked aspects while talking about security in a smart campus is the implementation of physical security features Hence, this study bridges the gap Aim: The aim of this study is to enhance a conceptual framework of Smart Campus by integrating Physical security features using IoT technology. Method: The study integrated physical security features into a smart governance module of Smart Campus by considering three (3) additional factors thus: Radio frequency identification (RFID), Smart lock and Surveilance camera that makes a total of seven (7) factors in the framework. Results: The integration of physical security features into smart governance module of the Smart Campus resulted in a robust smart campus framework that give an improved security system on campus thereby promoting a safe campus for all.
Hybridized Conceptual Model of Artificial Intelligence Capability
Authors: Itodo Cecilia , Mustapha Rabi , Haruna Khalid
Published: September 2024

Background: Hybridization is the process of integrating two or more models together to have a robust model. Artificial intelligence capability is the ability of a firm to select, organize and use its AI specific resources. In other to study the impact of AI capability on organizational creativity, studies proposed the idea of framework of AI capability model, it’s concept that investigated the effect of AI capability on organizational creativity and it performance. However, some essential factors that are necessary and relevant in enhancing the effect of AI capability in business organization are inadequate, despite the revolutionary potential that AI capabilities may promote, hence, this study bridge the gap. Aim: This study is based on resource base theory of the firm in the business domain that explored the impact of a hybridized model of Artificial Intelligence capability on organizational success. Method: The study integrated and enhanced two AI capability model by hybridization and addition of more factors, thus thirteen (13) factors were added. They were classified into external, instantaneous and temporal factors. The external factors are the input factors to the model, they are the independent variables, the instantaneous otherwise known as the mediating factors are time bounded factors with no delay while the temporal factors are the dependent variables, and they are also time-bounded factors with delay. The identified factors were based on theories and other related literatures. Nodes was used to represent the factors and the casual relationship of the identified factors was represented in form of flow arrows to show its connectivity. This was how the conceptual model was derived. Results: The inclusion of the thirteen factors resulted in a robust conceptual model, used to influence important decisions in business organizations.
An Enhanced OWL-Time Ontology for Complex Recurring Temporal Patterns
Authors: Bolatito Yusuf Aminat , Balarabe Junaidu Sahalu , Ayodele Obiniyi Afolayan , Salisu Aliyu , Donfack Kana Armand Florentin
Published: September 2024

The effective representation of temporal information across various domains using semantic web specifications is crucial for enabling temporal reasoning and facilitating time-oriented queries. However, existing temporal ontologies often lack consistency in time representation within a single ontology and are typically tailored to specific domains, limiting their applicability to complex temporal information. Notably, prominent frameworks like OWL-Time frequently overlook the intricacies of complex recurring temporal features. To address this limitation within OWL-Time, this study introduces OWL-BOLA 1.0, an extension specifically engineered to enhance OWL-Time for handling complex recurring temporal patterns. The aim of this study is to augment OWL-Time with specialized concepts and properties using a lightweight approach suited for recurring time, enabling a more comprehensive representation of temporal knowledge and enhancing reasoning capabilities. The objective is to provide robust support for handling recurring temporal patterns within OWL-Time constructs, thus enabling the reasoning of both simple and complex recurring temporal patterns. The methodology utilized in this study involves extending OWL-Time by integrating additional concepts and properties that cater to recurring temporal features. This approach ensures a more explicit representation of temporal knowledge while maintaining the lightweight nature of the ontology. The evaluation of the proposed ontology is carried out by analyzing metrics such as the depth of class hierarchy and inheritance richness. The results demonstrate the efficacy of OWL-BOLA 1.0 in providing explicit representation and handling complex recurring temporal patterns. The ontology exhibits a depth of class hierarchy of 6 and a high inheritance richness of 0.915, highlighting its impressive performance and utility compared to existing ontologies. Although it shows slightly lower semantic richness (0.466) and data property richness (0.237) in conceptualization, OWL-BOLA 1.0 effectively reduces redundancy and maintains clarity. In conclusion, OWL-BOLA 1.0 offers a balanced and effective tool for various application domains by enhancing OWL-Time's capability to handle complex recurring temporal patterns. This study contributes to the field by providing a robust solution for temporal reasoning, making it applicable across diverse domains requiring sophisticated temporal information representation.
Exploring Artificial Intelligence (AI) Technologies in Predictive Medicine: A Systematic Review
Authors: Isiaka Salman O. , Babatunde Ronke S. , Isiaka Rafiu M.
Published: September 2024

Artificial Intelligence (AI) technologies, including cognitive computing, machine learning (ML), and deep learning (DL), have the potential to transform healthcare. They enhance patient care, improve symptom differentiation, address medication adherence issues, and facilitate continuous patient support. AI's promise in electronic health records (EHRs) includes extracting valuable insights and improving healthcare infrastructure through advanced disease detection and diagnostics. This study reviews and analyzes AI applications in predictive medicine, focusing on emerging pattern recognition techniques and prediction model algorithms. The goal is to assess the current state of AI applications, identify gaps, and develop models that tackle challenges and ethical dilemmas in predictive medicine. A systematic review was conducted using five major scientific literature databases (ScienceDirect, PubMed, Scopus, IEEE Xplore, and Web of Science). The review covered publications from 2015 to May 2024, employing comprehensive search strings to identify relevant studies. Articles were filtered using inclusion and exclusion criteria, and data were extracted and classified based on AI algorithms, application contexts, and key results. Performance metrics of various AI models and techniques were analyzed following PRISMA guidelines. The review found that deep learning models, particularly Convolutional Neural Networks (CNNs) and Gradient Boosting Machines (GBMs), performed best in personalized medicine. Recurrent Neural Networks (RNNs) and Random Forests (RFs) excelled in disease prediction. Machine learning algorithms, feature selection techniques, data fusion methods, and natural language processing (NLP) techniques improved hospital discharge decision-making. Data fusion methods achieved the highest performance metrics, though challenges such as model interpretability and data complexity were identified.
Exploring Heuristic Algorithms for the Knapsack Problem: A Comparative Analysis of Program Complexity and Computational Efficiency
Authors: Usman Bashar Bin , Kanoma Saminu Isah , Zakariyau Ibrahim , Niworu Hashimu Abubakar , Rilwan Adebayo Ademola
Published: September 2024

The knapsack problem is an optimization problem in computer science which involves determining the most valuable combination of items that can be packed into a knapsack (a container) with a limited capacity (weight or volume); the goal is to maximize the total profit of the items included in the knapsack without exceeding its capacity. This study extensively analyzes the knapsack problem, exploring the application of three prevalent heuristics: greedy, dynamic programming, and FPTAS algorithms implemented in Python. The study aims to assess how these algorithms perform differently, focusing on program complexity and computational speed. Our main objective is to compare these algorithms and determine the most effective one for solving the knapsack problem as well as to be chosen by the researchers and developers when dealing similar problem in real-world applications. Our methodology involved solving the knapsack problem using the three algorithms within a unified programming environment. We conducted experiments using varying input datasets and recorded the time complexities of the algorithms in each trial. Additionally, we performed Halstead complexity measurements to derive the volume of each algorithm for this study. Subsequently, we compared program complexity in Halstead metrics and computational speed for the three approaches. The research findings reveal that the Greedy algorithm demonstrates superior computational efficiency compared to both Dynamic Programming (D.P) and FPTAS algorithms across various test cases. To advance understanding of the knapsack problem, future research should focus on investigating the performance of other programming languages in addressing combinatorial optimization problems, which would provide valuable insights into language choice impact. Additionally, integrating parallel computing techniques could accelerate solution processes for large-scale problem instances.
Evaluating and Improving Adversarial Robustness of Deep Learning -Based Network Intrusion Detector
Authors: Mada Yusuf Magaji , Bello Ahmad
Published: September 2024

Network Intrusion Detection Systems (NIDS) are essential for protecting digital infrastructures. Deep learning Networks (DLNs) have shown great promise in detecting network threats, while existing IDS solutions continue to suffer from issues such as high false alarms, low detection rates and reduced false positives. Previous research has highlighted the effectiveness of DLs in NIDS and identified their susceptibility to Network attacks, a comprehensive evaluation and improvement framework is lacking. This study aims to fill that gap by developing a robust evaluation framework and implementing defense mechanisms such as Inception module, feature squeezing, multiple kernel sizes, and gradient masking. The UNSW-NB15 dataset will be used to train and test the models. The result obtained is an enhancement in the robustness of DL-based NIDS, measured by improved accuracy, reduced attack success rates, and better learning curves. Strengthening these systems will significantly enhance the security of digital infrastructures, providing a robust defense against sophisticated cyber threats.
Securing IoT Networks: An Intrusion Detection Framework Using Convolutional Neural Networks
Authors: Bello Ahmad , Mada Magaji Yusuf
Published: September 2024

The proliferation of the Internet of Things (IoT) has significantly transformed human lives, embedding interconnected devices across various sectors such as industry, healthcare, agriculture, and transportation. However, this growth has also attracted cybercriminals, leading to a surge in cyber-attacks targeting IoT devices. Intrusion Detection Systems (IDS) have emerged as a critical defense mechanism against such attacks. In this paper, we propose a Convolutional Neural Network (CNN)-based framework for IoT intrusion detection. The framework employs CNNs for automatic feature selection from raw network traffic data, enhancing classification performance and reducing dimensionality. We utilize the IoTID20 benchmark dataset for training and testing the proposed framework. Experimental results demonstrate the effectiveness of our approach, achieving high accuracy of 99.93%, precision of 1.00%, recall of 99.92%, and F1-score of 99.98% for binary classification. For multi-class category classification, the framework achieves an accuracy of 99.51%, precision of 99.98%, recall of 99.87%, and F1-score of 99.93%. For multi-class sub-category classification, the accuracy is 92.46%, precision is 97.25%, recall is 90.54%, and F1-score is 92.83%. Our proposed framework outperforms existing methods, making it a promising solution for IoT network security.
An Enhanced Message Encryption Approach Using Residue Number System
Authors: Tajudeen Kafayat Odunayo , Ameen Ahmed Oloduowo , Aro Oladele Taye , Kadri Akeem Femi , Asaju-Gbolagade Ayisat Wuraola
Published: September 2024

Safe transmission of messages over the internet is ensured by data security. The data should be protected against unauthorized access and transmitted to the legal recipient safely and formally called cryptography. The well-known cryptography types are asymmetric and symmetric and different symmetric encryption algorithms such as Advanced Encryption Standard (AES), Data Encryption Standard (DES), Blowfish were proposed to protect the confidentiality of the transmitted and stored data. However, most of these symmetric techniques are vulnerable to brute-force attack because the cipher text remains unintelligible for the original data to be found. Consequently, this challenge prompted researchers to introduce Residue Number System for encryption. RNS helps to withstand the vulnerability of the encryption algorithms in brute-force attacks making transmitted and stored data more secure. Hence, this paper introduced encryption by using RNS to improve the security of transmitted data. Traditional moduli set set {m_1=2^n-1,m_2= 2^n and 〖m_3=2〗^n+1} and Chinese Remainder Theorem (CRT) were used to encrypt and decrypt the data based on information exchange. Furthermore, this is done by representing each character in the plaintext data is assigned a unique number value and which is done by converting each character into its ASCII value and the ASCII value is then converted to Excess-3 value. Thus, anytime an attacker tries to access the data, the RNS algorithm will generate residues data, this helps to discourage an attacker from further threat. The result showed that the proposed system was able to resist brute-force attacks compared to others systems. Values of n for the moduli set were dynamic against encryption and decryption of data.
Boletim 02 DOXA Revista Brasileira de Psicologia e Educação
Authors: Santos Cruz José Anderson , Da Silva Alexander Vinicius Leite , Moreira Flavio Henrique Machado , Ganiko-Dutra Matheus , Crivellari Déborah Ramos , Cerantola Giovana Cordero , Coelho Matheus Guilherme Prudente
Published: September 2024

Esse boletim é uma publicação da Editora Ibero-Americana de Educação sobre a DOXA: Revista Brasileira de Psicologia e Educação. Seu objetivo é chamar a atenção dos leitores para artigos publicados na revista que abordam temáticas relacionadas à Educação e Psicologia, Educação e Sexualidade, e sua multidisciplinaridade.
Boletim 01 Revista Tempos e Espaços em Educação
Authors: Santos Cruz José Anderson , Da Silva Alexander Vinicius Leite , Moreira Flavio Henrique Machado , Bizelli Thaís Vargas , Ganiko-Dutra Matheus , Crivellari Déborah Ramos , Cerantola Giovana Cordero , Armelin Gabriela Rufino , Ribeiro João Gabriel Marcelino , Santos Natalia Trefilo
Published: September 2024

Esse boletim é uma publicação da Editora Ibero-Americana de Educação sobre a Revista Tempos e Espaços em Educação. O objetivo é despertar o interesse dos leitores para artigos de temáticas semelhantes, publicados na revista, que se concentram na área da Educação.
The Effects of product attributes of restaurant meal replacement on perceived value, attitude and behavioral intention
Authors:   The Foodservice Management Society Of Korea, Lee Hwa-Seon , Choi Yong-Seok
Published: September 2024

Objective:With recent increasing interest in restaurant meal replacement (RMR) products among the restaurant consumers, this study verified the impact relationship of perceived value, attitude, and behavioral intention towards RMR products.
Methods:This study conducted a survey using an online questionnaire from February 1st to February 29, 2024, with a total of 361 samples. Then, this study conducted an empirical analysis using the SPSS 24.0 statistical program.
Results:The results are as follow: First, among RMR product attributes, price, convenience, and brand were found to have a significant impact on economic value. Second, RMR product attributes were found to have a significant impact on perceived convenience. Third, perceived value had as ignificant impact on attitude. Fourth, attitude significantly affected the behavioral intention.
Implications:Based on these results, this study suggested practical implications for boosting the sale of RMR products and enhancing the competitiveness of food service companies.