bluuebunny/crossref_metadata_2025 huggingface dataset:
A  creation in abstract 3D art insprired from Pavo muticus imperator
Authors: Sookkaew Jirawat , Chaikaew Nakarin , Chiewsuwan Donticha , Seviset Somchai
Published: August 2022

Creation of art as abstract art by choosing athree-dimensional (3D)art formto be used for creativity, has brought the characteristics of the peacock inspired by its forms, color characteristics, including its habitats to be usedas a mixture and elements in creating this art. Therefore, when combined with the key elements of a 3D object with depth dimension of the object in the Z axis, adopting the colors of the space and the atmosphere of thepeacock's habitat to the surface of the 3D pieces, which provide creative approaches and techniques that enable abstract 3D art to be realized by the shapes and formed by perspectives as a whole. Z-axis can create directions to display hundreds of perspectives. In addition, the colors that have beenused to blend in with the 3D objects create beauty inspired by the colors that can be found in nature. The peacock's art has been passed through with the distinctive features of 3D objects, resulting in creating such abstract 3D artpieces.
Computational phantoms for investigating impact of noise magnitude on modulation transfer function
Authors: Anam Choirul , Naufal Ariij , Sutanto Heri , Dougherty Geoff
Published: August 2022

Accurate measurement of spatial resolution in terms of modulation transfer function (MTF) is essential in computed tomography (CT) images. The purpose of this study was to developed a computational phantom that can be used to evaluate the effect of noise on the MTF in CT images. Our computational phantoms for measuring MTF in CT were developed with MATLAB software. The phantom image was blurred by a point spread function of a certain standard deviation. Subsequently, different noise levels were added to the phantoms. Next, an automatic MTF calculation was implemented. The first step of the MTF calculation was to determine the region of interest (ROI). Profile was generated from the ROI, and a line spread function (LSF) curve was formed. The LSF curve was Fourier transformed to produce a MTF curve. Greater noise added to phantom image, it yields greater effect of standard deviation on the measured MTF. The greater noise makes the MTF curve increases differently than MTF with 0 HU noise. The 10% MTF values at the 25% noise reach more than 2.0 cycle/mm. By the developed computational phantoms, the spatial resolution and the amount of noise can be determined independently.
An investigation of even ordered magic squares (4, 6, and 8): characteristic polynomials, eigenvalues, and encryption
Authors: Al-Ashhab Saleem , Al-qdah Majdi
Published: August 2022

In this paper, we discuss and mathematically compute the eigenvalues and the characteristic polynomials of special even square matrices of orders 4x4 and 8x8. Also, we introduce two 8th order compound magic squares. The computed values are verified using Maple software. First, for the 4th order square matrix, the characteristic polynomial was derived to be: λ(λ-2s)( λ²+4Θ) with the eigenvalues: 0,2 s, and two other conjugates. In further analysis, we performed numerical classification of the squares for the matrices of order 4. Second, for the 8th order magic square, the characteristic polynomial was obtained in the form: λ3(λ-4s)(λ4+Ωλ2+θ) where Ω,Θ are constants; the eigenvalues are 0,4 s, ∓√λ1, ∓√λ2; where λ1, λ2 are the roots of the quadratic equation: λ2+Ωλ+Θ=0. Third, for the franklin square, we obtained the eigenvalues 0,4 s, and the roots of the equation: λ2+aλ+b. Finally, we suggested a hybrid image encryption technique based on Franklin magic square matrices and improved substitution technique. The proposed a grayscale image encryption/ decryption algorithm uses circular rotation of bits and Franklin magic squares’ properties in conjunction with substitution techniques to obtain a very secure algorithm against attacks.
A secure communication protocol for civil drones
Authors: Al-Adhami Ayad , Hasoun Rajaa K. , K. Gbashi Ekhlas , Hassan Soukaena
Published: August 2022

This paper introduces a secure communication protocol that provides secured communication pathways to manipulate drones through unsecured communication. The deployment of the proposed protocol works through providing two secured communication paths; drones to the drone’s controller path and controller to data centre path. The first secured communication path has achieved a high level of security and privacy by using a modification of SHA-1 method and an advanced encryption method. The modification of the SHA-1 is called 83SHA-1. These modifications can increase rounds in the first stage up to 83 rounds, inject each round with expansion and S-Boxes procedures that are used in DES to extend length from 160 to 240 bits then reduce it from 240 to 160 bits. After hash data from the drone then use the advanced encryption method which is called Geffe-Genetic (GG) Encryption algorithm where three types of keys will be used for deception attackers. The second accomplishment is to ensure providing secure communication between the drone’s controller and datacentre by using RNA-RADG-CBC (RRCBC) encryption algorithm where will generate an initialization vector (IV) for cipher block chaining (CBC) randomly, generate keys, and propose an encryption/decryption method. The security analysis shows a promising high security level of drones’s data.
Autoregressive prediction analysis using machine deep learning
Authors: Khrisat Mohammad S. , Alabadi Anwar , Khawatreh Saleh , Al-Dwairi Majed Omar , Alqadi Ziad A.
Published: August 2022

Regression analysis, in statistic a modelling, is a set of statical processes that can be used to estimate the relationship between a dependent variable, commonly known as the outcome or response, and more independent variables generally called predictors of covariant. On the other hand, autoregression, which is based on regression equations, is a sequential model that uses time to predict the next step data from the previous step. Given the importance of accurate modelling and reliable predictions. in this paper we have analyzed the most popular methods used for data prediction. Nonlinear autoregressive methods were introduced, and then the machine deep learning approach was used to apply prediction based on a selected input data set. The mean square error was calculated for various artificial neural networks architecture to reach the optimal architecture, which minimized the error. Different artificial neural network (ANN) architectures were trained, tested, and validated using various regressive models, a recommendation was raised according to the obtained and analyzed experimental results. It was shown that using the concepts of machine deep learning will enhance the response of the prediction model.
Guide to choosing internet of things protocols
Authors: Elhadi Sakina , Chhiba Loubna , Sael Nawal , Marzak Abdelaziz
Published: August 2022

The internet of things (IoT) is a global infrastructure for the information society, enabling advanced services by interconnecting objects (physical or virtual) through existing or evolving interoperable information and communication technologies. Among the main keys to the IoT is the widespread adoption of clearly defined protocols. The implementation of its applications requires protocols capable of effectively managing these conditions, namely network protocols and applications. Considering the importance of using protocols in IoT applications, many protocols have been developed and used by various organizations according to their needs. However, choosing an adaptable, standard, and efficient protocol is a difficult decision, for all organizations and researchers. This difficulty, due to the complex nature of the IoT system and its requirements. Consequently, we propose a model for the use of IoT protocols based on criteria and metrics that will evolve the protocols. we call these models by the model of good practice of protocols of the Internet of things. Then, we implement these models in the form of a tool for choosing IoT (Networks and application) protocols. This study will allow researchers and developers to choose the appropriate protocols for an IoT application by allowing the result before the realization of the application.
Supervised learning through k-nearest neighbor, used in the prediction of university teaching performance
Authors: Chamorro-Atalaya Omar , Alvarado-Bravo Nestor , Aldana-Trejo Florcita , Poma-Garcia Claudia , Aliaga-Valdez Carlos , Peralta-Eugenio Gutember , Tasayco-Jala Abel
Published: August 2022

This study initially seeks to identify the most optimal supervised learning algorithm to be used in predicting the perception of teacher performance, and then to evaluate its performance indicators that validate its predictive capacity. For this, the Matlab R2021a software is used; the experimental results determine that the supervised learning algorithm K-Nearest Neighbor Weighted (Weighted KNN) will be correct in 98.10% in predicting the perception of teaching performance, this has been validated by carrying out two evaluations through its performance indicators obtained in the confusion matrix and the receiver operating characteristic (ROC) curve, in the first evaluation an average sensitivity of 97.9%, a specificity of 99.1%, an accuracy of 98.8% and a precision of 96.7% are observed, thus validating the ability of the Weighted KNN model to correctly predict the perception of teacher performance; while in the receiver operating characteristic (ROC) curve, values of the area under the curve (AUC) equal to 0.99 and 1 are obtained, with this it is possible to validate the capacity that the model will have to distinguish between the 4 classes of the perception of the university teaching performance.
Evolution of automated learning techniques for combating COVID-19: an analysis
Authors: Ghafour Mohammed Azheen , Shekhan Hamsheen Eman
Published: August 2022

It is now more than two years that the world is battling the tiny invisible virus, COVID-19. Since its appearance, it showered humankind with shock, fear, and death. In small words, this pandemic has paused human life in all its aspects and beauties. Governments, health industry researchers and laboratories have put all their efforts to achieve a universal goal that is, overcoming the crisis and putting an end to the pandemic. However, this goal was never achievable without the smart use of automated learning, artificial intelligence, machine learning and deep learning algorithms. This review paper presents a collection of the experimental research articles tackled using real-time official datasets from hospitals and governments. These datasets are processed using automated learning (AL) algorithms in order to find suitable solutions to most of the COVID-19 related problems. This paper presents the AL applications in a story telling manner, starting from the first phases of COVID-19, when doctors had no experience dealing with the disease and had difficulty in diagnosing it, then moving to the other phases like suggesting a medicine, drug repurposing, facial mask detection, fake news detection, vaccine development, pandemic management, post vaccine statistics and lastly post COVID-19 analysis.
Using a new coefficient conjugate gradient method for solving unconstrained optimization problems
Authors: M. Sulaiman Ranen , A. Hassan Basim
Published: August 2022

The conjugate gradient technique is a numerical solution strategy for finding minimization in mathematics. We present a simple, straightforward, efficient, and resilient conjugate gradient technique in this study. To address the convergence difficulty and descent property, the new technique is built on the quadratic model. Under some assumptions, the new improved approach meets the convergence characteristics and the adequate descent criterion. The suggested unique strategy is substantially more efficient than the classic FR method, according to our numerical analysis. The number of function evaluations, iterations and restarts are all included in the numerical results. The computational efficiency of the proposed approach is proved by comparative results.
An approach to classify distraction driver detection system by using mining techniques
Authors: Shankar Reddy Shiva , Neelima Pilli , Priyadarshini Voosala , Chigurupati Swaroop Ravi
Published: August 2022

According to the motor vehicle safety division, over the past 5-10 years, usage of motor vehicles has rapidly increased, in that specifical usage of cars has grown tremendously. The major contribution of this paper is a systematic evaluation of the scholarly literature on driver distraction detection techniques. Our driver distraction detection framework offers a systematic overview of evaluated methodologies for detecting driver attention. So, we need to develop a model that classifies each driver's behaviour and determines its corresponding class name. To overcome this dispute, we have attained an appreciable number of deep learning algorithms on the dataset like convolutional neural network (CNN) and VGG16 to detect what the driver is doing in the car as given in the driver images. This process can be done by predicting the likelihood of the driver's actions in each picture. Of all models, we distinguished that the VGG16 Algorithm has conquered CNN with a loss of 0.298 and an Accuracy of 91.7%.
Alzheimer’s disease prediction using three machine learning methods
Authors: Ahmed Shaymaa Taha , Kadhem Suhad Malallah
Published: August 2022

Alzheimer's disease (AD) is the most common incurable neurodegenerative illness, a term that encompasses memory loss as well as other cognitive abilities. The purpose of the study is using precise early-stage gene expression data from blood generated from a clinical Alzheimer's dataset, the goal was to construct a classification model that might predict the early stages of Alzheimer's disease. Using information gain (IG), a selection of characteristics was chosen to provide substantial information for distinguishing between normal control (NC) and early-stage AD participants. The data was divided into various sizes; three distinct machine learning (ML) algorithms were used to generate the classification models: support vector machine (SVM), Naïve Bayes (NB), and k-nearest neighbors (K-NN). Using the WEKA software tool and a variety of model performance measures, the capacity of the algorithms to effectively predict cognitive impairment status was compared and tested. The current findings reveal that an SVM-based classification model can accurately differentiate cognitively impaired Alzheimer's patients from normal healthy people with 96.6% accuracy. As discovered and validated a gene expression pattern in the blood that accurately distinguishes Alzheimer's patients and cognitively healthy controls, demonstrating that changes specific to AD can be detected far from the disease's core site.
Chaotic map technique for enhancement security for android mobile system based on image encryption
Authors: Thabt Saleh Kawther , Alhadi Jabr Nisreen Abd , Hussein Al-Qinani Iman
Published: August 2022

Network security continues to be the priority of many organizations. To ensure the protection of their data, they pay great attention to Encryption systems. Moreover, because of the enormous developments in networks of connection particularly the internet which has used by several people to share a variety of data kinds. The security of data has been a significant issue. As a result, there is a significant focus in using methods of decryption and encryption. Numerous encryption techniques have become advanced to preserve data protection, chaotic encryption systems are one of these methods widely used in recent years, where several techniques were proposed to use a chaotic map for encrypt images for the reason that of their characteristics e.g., random action unpredictability and initial conditions sensitivity. In this paper, proof authentication of sent information is used chaotic encryption algorithm to provide cipher text and hidden in image then send to another user. This approach is applied in cellular operating system environment (android). Thus, the sending and receiving of text will be safe and secure. The proposed approach is tested on different types of mobile. The proposed system gives good results.
A política nos limites do juízo meramente reflexionante: Arendt, leitora de Kant
Authors: Segatto Antonio Ianni
Published: August 2022

Comentadores frequentemente apontaram um conflito entre a concepção tardia de Arendt acerca do juízo como uma capacidade espiritual e sua concepção inicial, segundo a qual o juízo político estaria vinculado à ação. Haveria, pois, uma contradição entre o ponto de vista do espectador, assumido na concepção tardia, e ponto de vista do ator, que caracteriza a concepção inicial. Neste artigo, procuro mostrar que a origem de tal inconsistência reside no fato de que, desde seus comentários à filosofia kantiana da década de 1950, Arendt separava de maneira estrita juízos determinantes e juízos reflexionantes e, baseando-me em comentários recentes, apresento a possibilidade de uma leitura alternativa da filosofia kantiana que privilegia a unidade do sistema crítico.
A influência do nominalismo nas concepções de causalidade e justiça em Hume
Authors: Costa Ivo Fernando da
Published: August 2022

O objetivo do trabalho é apresentar a articulação entre as noções de causalidade e justiça em Hume, buscando mostrar como ambas estão fundamentadas no costume. Para tal fim, analisaremos brevemente a possibilidade de se fazer uma leitura do nominalismo como fundo ontológico de algumas teses humeanas, especialmente no que diz respeito ao peso conferido ao conhecimento sensitivo e à teoria da imaginação. Sob este horizonte, aparecerá o costume como peça-chave para compreender a noção de causa. Finalmente, examinaremos sua teoria das relações sociais que entende a justiça como uma virtude artificial. O artigo também mostrará a existência de um enquadramento aristotélico no que se refere a estes dois temas e um conteúdo que arriscaremos chamar de platonismo invertido.
Rede latino-americana de teatro em comunidade: reflexões sobre cultura viva comunitária e integração regional contra-hegemônica na América Latina entrevista - Adriano Mauriz, Edith Scher e Luis Vasquez
Authors: Ulian Eduardo Salles , Graziano Valéria Teixeira
Published: August 2022

A entrevista tem como objetivo refletir sobre as experiências que emergem do movimento latino-americano Cultura Viva Comunitária, a partir das relações entre políticas culturais, integração regional e emancipação social. Dentre os atores que compõem o movimento, destacamos na presente entrevista a Rede Latino-Americana de Teatro em Comunidade. Para tanto, entrevistamos três gestores de espaços culturais que integram a Rede: Edith Scher, fundadora e diretora do grupo de teatro comunitário Matemurga, no bairro Villa Crespo, Buenos Aires, Argentina; Luis Vasquez (Tin Tin), coordenador do Teatro Trono, localizado em El Alto, La Paz, Bolívia; e Adriano Mauriz, membro fundador do grupo Pombas Urbanas, que atua em Cidade Tiradentes, São Paulo, Brasil. Por meio da visibilização de atores e temáticas tradicionalmente ignorados pelo campo teórico das Relações Internacionais, esperamos contribuir para o debate sobre a urgência de descolonizar os estudos de integração regional e para a imaginação de alternativas contra-hegemônicas.
Linfoma cutâneo primário difuso de grandes células B, tipo perna – rápida evolução e desfecho desfavorável: relato de caso
Authors: Faria Fernanda Blasques de , Santos Isabela Espagolla , Mattos Amilcar Castro de , Machado Elaine Cristina Faria Abrahao , Gontijo Livia Matida
Published: August 2022

Linfomas cutâneos primários são a segunda forma mais comum de linfomas extranodais, sendo os linfomas de células B, (CBCLs) representantes de 20 a 30% dos casos. O linfoma cutâneo difuso de grandes células B, Tipo Perna (PCDLBCL-LT), representa o tipo mais agressivo de CBCLs. Na maioria dos casos, a apresentação clínica é caracterizada por placas ou tumores solitários, ora ulcerados, em uma ou ambas as pernas, de rápido crescimento. O diagnóstico é confirmado através do estudo histopatológico e imunohistoquímico. O tratamento é realizado por meio de quimioterapia e seu prognóstico é reservado com uma sobrevida de 50% a 60% em 05 anos. O objetivo deste trabalho é relatar um caso atendido de linfoma cutâneo primário difuso de grandes células B, tipo perna em um paciente de 75 anos, do sexo masculino com apresentação clínica clássica e desfecho desfavorável, realizar uma revisão bibliográfica do período de 2010 a 2020 na base de dados PUBMED sobre o assunto, dada sua raridade e agressividade ímpar. As informações foram obtidas através de revisão do prontuário, registro fotográfico e revisão da literatura. Por tudo isso, pode-se concluir a importância de estudos multidisciplinares, envolvendo dermatologistas, hematologistas, oncologistas e patologistas para que o diagnóstico e tratamento sejam instituídos o mais precoce possível, visto a raridade e agressividade do PCDLBCL-LT.
Hipotireoidismo e doença celíaca: correlações e implicações terapêuticas
Authors: Novaes Ruana Farias , Viana Lauro José Ribeiro
Published: August 2022

O hipotireoidismo é definido como uma hipofunção da tireoide, tendo como principal causa, atualmente, as doenças autoimunes da glândula, caracterizadas por uma resposta imune local e redução da produção dos hormônios tireoidianos. A doença celíaca (DC), por sua vez, é definida como uma enteropatia autoimune permanente desencadeada pelo glúten, na qual há produção de diversos autoanticorpos. Uma parcela significativa de pacientes com hipotireoidismo requer doses maiores de T4 para alcançar os níveis ideais de TSH, incluindo os pacientes celíacos. Ademais, dentre as causas que diversificam a apresentação clínica da DC destaca-se o hipotireoidismo. Com o objetivo de estabelecer associações entre ambas as doenças foi realizada uma revisão embasada nos bancos de dados MEDLINE e SciELO. Os resultados mostram que as doenças autoimunes comumente se associam e representam fatores de risco entre si. Porém, o rastreamento indiscriminado dessas ainda é inviável e pouco benéfico. Por isso, saber quando suspeitar clinicamente e como investigar o hipotireoidismo e/ou a DC é de extrema importância.
Percepção da população da cidade de Passos sobre os fatores que determinam o surgimento do câncer: mitos e verdades
Authors: Assad Núbia Taveira Carvalhaes , Carvalho Filho Aguimar Xavier de , Freire Maria Eduarda de Souza , Pereira Bruna Andrade , Rezende Bruno José Mendes , Costa Gabriel Kewen da , Sillos Isabela Ranieri , Barbosa Isabella Morato , Ribeiro Marina Lima , Marinho Micaella de Paula , Prado Trycyane Rodrigues Bueno , Pimenta Ruan , Faria Sabrina Thalita dos Reis
Published: August 2022

Introdução: As neoplasias malignas são responsáveis por inúmeras mortes em todo o mundo, por isso são encaradas pela população com muito temor e curiosidade. Sendo assim muitas pessoas recorrem aos meios de comunicação mais convenientes, que nem sempre abordam corretamente as doenças, para se informar sobre prevenção do câncer, ou então se baseiam na cultura popular passada por gerações sem nenhum embasamento científico. Objetivo: Analisar a percepção da população sobre os fatores de risco para o câncer e classificá-las de acordo com o nível de evidência encontrado nas pesquisas científicas. Metodologia: Foram selecionados 146 participantes, de maneira aleatória, que responderam a um questionário enviado por e-mail o qual indagava o que o pesquisado considera que seja um fator de risco para se desenvolver cânceres. Esses dados foram tabelados e uma pesquisa bibliográfica foi realizada para reconhecer os fatores de risco mencionados pela população como evidentes ou não evidentes cientificamente. Resultados: O estresse e causas psicológicas foram mencionados por 43,84% das pessoas pesquisadas e pelo estudo bibliográfico foi classificado como evidência parcialmente positiva. O cigarro foi mencionado por 39,04% dos participantes e foi classificado como evidência positiva, a herança genética foi indicada por 38,36% e classificada como evidência positiva, sexo sem proteção foi mencionado por apenas uma pessoa e foi classificado como evidência positiva. Conclusão: Com os dados obtidos observamos que, a maioria das respostas possuem relação com evidências científicas publicadas e comprovadas, no entanto, mais estudos e divulgações acerca de formas preventivas devem ser realizados.
Management and Outcomes of Primary Aldosteronism in Pregnancy: A Systematic Review
Authors: Sanga Viola , Rossitto Giacomo , Seccia Teresa Maria , Rossi Gian Paolo
Published: August 2022

Primary aldosteronism (PA) in pregnancy (PAP) can be a serious condition and is challenging to diagnose. This study was conceived to help in the diagnosis of PAP and provide suggestions on management of PAP based on evidence retrieved using a Population, Intervention, Comparison, and Outcome search strategy. Based on the changes of aldosterone and renin occurring in normal pregnancies, we developed a nomogram that will allow to identify PAP cases. Moreover, we found that published PAP cases fell into 4 main groups differing for management and outcomes: (1) unilateral medically treated, (2) unilateral surgically treated, (3) bilateral medically treated and (4) familial forms. Results showed that complications involved 62.2% of pregnant women with nonfamilial PA and 18.5% of those with familial hyperaldosteronism type I. Adrenalectomy during pregnancy in women with PAP did not improve maternal and fetal outcomes, over medical treatment alone. Moreover, cure of maternal hypertension and mother and baby outcome were better when unilateral PA was discovered and surgically treated before or after pregnancy. Therefore, fertile women with arterial hypertension should be screened for PA before pregnancy and, if necessary, subtyped to identify unilateral forms of PA. This will allow to furnish adequate counseling, a chance for surgical cure and, therefore, for a pregnancy not complicated by aldosterone excess.
Aldosterone as a Mediator of Cardiovascular Damage
Authors: Buffolo Fabrizio , Tetti Martina , Mulatero Paolo , Monticone Silvia
Published: August 2022

Besides the physiological regulation of water, sodium, and potassium homeostasis, aldosterone modulates several physiological and pathological processes in the cardiovascular system. At the vascular level, aldosterone excess stimulates endothelial dysfunction and infiltration of inflammatory cells, enhances the development of the atherosclerotic plaque, and favors plaque instability, arterial stiffness, and calcification. At the cardiac level, aldosterone increases cardiac inflammation, fibrosis, and myocardial hypertrophy. As a clinical consequence, high aldosterone levels are associated with enhanced risk of cardiovascular events and mortality, especially when aldosterone secretion is inappropriate for renin levels and sodium intake, as in primary aldosteronism. Several clinical trials showed that mineralocorticoid receptor antagonists reduce cardiovascular mortality in patients with heart failure and reduced ejection fraction, but inconclusive results were reported for other cardiovascular conditions, such as heart failure with preserved ejection fraction, myocardial infarction, and atrial fibrillation. In patients with primary aldosteronism, adrenalectomy or treatment with mineralocorticoid receptor antagonists significantly mitigate adverse aldosterone effects, reducing the risk of cardiovascular events, mortality, and incident atrial fibrillation. In this review, we will summarize the major preclinical and clinical studies investigating the cardiovascular damage mediated by aldosterone and the protective effect of mineralocorticoid receptor antagonists for the reduction of cardiovascular risk in patients with cardiovascular diseases and primary aldosteronism.
Ang II (Angiotensin II)–Induced FGFR1 (Fibroblast Growth Factor Receptor 1) Activation in Tubular Epithelial Cells Promotes Hypertensive Kidney Fibrosis and Injury
Authors: Xu Zheng , Luo Wu , Chen Lingfeng , Zhuang Zaishou , Yang Daona , Qian Jianchang , Khan Zia A. , Guan Xinfu , Wang Yi , Li Xiaokun , Liang Guang
Published: August 2022

Background:

Elevated Ang II (angiotensin II) level leads to a range of conditions, including hypertensive kidney disease. Recent evidences indicate that FGFR1 (fibroblast growth factor receptor 1) signaling may be involved in kidney injuries. In this study, we determined whether Ang II alters FGFR1 signaling to mediate renal dysfunction.

Methods:

Human archival kidney samples from patients with or without hypertension were examined. Multiple genetic and pharmacological approaches were used to investigate FGFR1-mediated signaling in tubular epithelial NRK-52E cells in response to Ang II stimulation. C57BL/6 mice were infused with Ang II for 28 days to develop hypertensive kidney disease. Mice were treated with either adeno-associated virus expressing FGFR1 shRNA or FGFR1 inhibitor AZD4547.

Results:

Kidney specimens from subjects with hypertension and mice challenged with Ang II have increased FGFR1 activity in renal epithelial cells. Renal epithelial cells in culture initiate extracellular matrix programming in response to Ang II, through the activation of FGFR1, which is independent of both AT1R (angiotensin II receptor type 1) and AT2R (angiotensin II receptor type 2). The RNA sequencing analysis indicated that disrupting FGFR1 suppresses Ang II–induced fibrogenic responses in epithelial cells. Mechanistically, Ang II–activated FGFR1 leads to STAT3 (signal transducer and activator of transcription 3) activation, which is responsible for fibrogenic factor expression in kidneys. In the mouse model of hypertensive kidney disease, genetic knockdown of FGFR1 or pharmacological inhibition of its activity protected kidneys from dysfunction and fibrosis upon Ang II challenge.

Conclusions:

Our studies uncover a novel mechanism causing renal fibrosis in hypertension and indicate FGFR1 as a potential target to preserve renal function and integrity.
Influence of Obstructive Sleep Apnea Severity on Muscle Sympathetic Nerve Activity and Blood Pressure: a Systematic Review and Meta-Analysis
Authors: Maier Lauren E. , Matenchuk Brittany A. , Vucenovic Ana , Sivak Allison , Davenport Margie H. , Steinback Craig D.
Published: August 2022

Background:

We conducted meta-analyses to identify relationships between obstructive sleep apnea (OSA) severity, muscle sympathetic nerve activity (MSNA), and blood pressure (BP). We quantified the effect of OSA treatment on MSNA.

Methods:

Structured searches of electronic databases were performed until June 2021. All observational designs (except reviews) were included: population (individuals with OSA); exposures (OSA diagnosis and direct measures of MSNA); comparator (individuals without OSA or different severity of OSA); outcomes (MSNA, BP, and heart rate).

Results:

Fifty-six studies (N=1872) were included. MSNA burst frequency was higher in OSA (27 studies; n=542) versus controls (n=488; mean differences [MDs], +15.95 bursts/min [95% CI, 12.6–17.6 bursts/min]; I2=86%). As was burst incidence (20 studies; n=357 OSA, n=312 Controls; MD, +22.23 bursts/100 hbs [95% CI, 18.49–25.97 bursts/100 hbs]; I2=67%). Meta-regressions indicated relationships between MSNA and OSA severity (burst frequency, R2=0.489; P<0.001; burst incidence, R2=0.573; P<0.001). MSNA burst frequency was related to systolic pressure (R2=0.308;P=0.016). OSA treatment with continuous positive airway pressure reduced MSNA burst frequency (MD, 11.91 bursts/min [95% CI, 9.36–14.47 bursts/min] I2=15%) and systolic (n=49; MD, 10.3 mm Hg [95% CI, 3.5–17.2 mm Hg]; I2=42%) and diastolic (MD, 6.9 mm Hg [95% CI, 2.3–11.6 mm Hg]; I2=37%) BP.

Conclusions:

MSNA is higher in individuals with OSA and related to severity. This sympathoexcitation is also related to BP in patients with OSA. Treatment effectively reduces MSNA and BP, but limited data prevents an assessment of the link between these reductions. These data are clinically important for understanding cardiovascular disease risk in patients with OSA.

Registration:

URL:https://www.clinicaltrials.gov; Unique identifier: CRD42021285159.
Systolic Blood Pressure and Effects of Screening for Atrial Fibrillation With Long-Term Continuous Monitoring (a LOOP Substudy)
Authors: Xing Lucas Yixi , Diederichsen Søren Zöga , Højberg Søren , Krieger Derk W. , Graff Claus , Olesen Morten Salling , Brandes Axel , Køber Lars , Haugan Ketil Jørgen , Svendsen Jesper Hastrup
Published: August 2022

Background:

Hypertension is a well-known risk factor for atrial fibrillation (AF) and stoke, but data on the interaction between systolic blood pressure (SBP) and effects of AF screening are lacking.

Methods:

The LOOP Study randomized AF-naïve individuals aged 70 to 90 years with additional stroke risk factors to either screening with implantable loop recorder (ILR) and anticoagulation initiation upon detection of AF episodes ≥6 minutes, or usual care. In total, 5997 participants with available baseline SBP measurements were included in this substudy. Outcomes were analyzed according to the time-to-first-event principle using cause-specific Cox models.

Results:

The hazard ratio of stroke or systemic arterial embolism for ILR versus control decreased with increasing SBP. ILR screening yielded a 44% risk reduction of stroke or systemic arterial embolism among participants with SBP ≥150 mm Hg (adjusted hazard ratio, 0.56 [0.37–0.83]). Within the ILR group, SBP≥150 mm Hg was associated with a higher incidence of AF episodes ≥24 hours than lower SBP (adjusted hazard ratio, 1.70 [1.08–2.69]) but not with the overall occurrence of AF (adjusted
P
>0.05).

Conclusions:

The impact of AF screening on thromboembolic events increased with increasing blood pressure. SBP≥150 mm Hg was associated with a >1.5-fold increased risk of AF episodes ≥24 hours, along with an almost 50% risk reduction of stroke or systemic arterial embolism by ILR screening compared to lower blood pressure. These findings should be considered hypothesis-generating and warrant further study.

Registration:

URL:
https://www.clinicaltrials.gov
; Unique Identifier: NCT02036450.
Perioperative Metabolites Are Associated With Adverse Neonatal Congenital Heart Disease Surgical Outcomes
Authors: Heibel Jessica , Graham Eric M. , Mahle William T. , Roux Aurelie , Graham David , Manlhiot Cedric , Everett Allen D.
Published: August 2022

Background

Clinical risk factors in neonatal cardiac surgery do not fully capture discrepancies in outcomes. Targeted metabolomic analysis of plasma from neonates undergoing heart surgery with cardiopulmonary bypass was performed to determine associations with clinical outcomes.

Methods and Result

Samples and clinical variables from 149 neonates enrolled in the Corticosteroid Therapy in Neonates Undergoing Cardiopulmonary Bypass trial with surgical treatment for congenital heart disease between 2012 and 2016 were included. Blood samples were collected before skin incision, immediately after cardiopulmonary bypass, and 12 hours after surgery. Outcomes include composite morbidity/mortality (death, extracorporeal membrane oxygenation, cardiac arrest, acute kidney injury, and/or hepatic injury) and a cardiac composite (extracorporeal membrane oxygenation, cardiac arrest, or increase in lactate level), hepatic injury, and acute kidney injury. Targeted metabolite levels were determined by high‐resolution tandem liquid chromatography and mass spectrometry. Principal component and regression analyses were used to assess associations between metabolic profiles and outcomes, with 2 models created: a base clinical model and a base model+metabolites. Of the 193 metabolites examined, 40 were detected and quantified. The first principal component, principal component 1, was composed mostly of preoperative metabolites and was significantly associated with the composite morbidity/mortality, cardiac composite, and hepatic injury outcomes. In regression models, individual metabolites also improved model performance for the composite morbidity/mortality, cardiac composite, and hepatic injury outcomes. Significant disease pathways included myocardial injury (false discovery rate, 0.00091) and heart failure (false discovery rate, 0.041).

Conclusions

In neonatal cardiac surgery, perioperative metabolites were associated with postoperative outcomes and improved clinical model outcome associations. Preoperative metabolite levels alone may improve risk models and provide a basis for optimizing perioperative care.
microRNA‐29a Regulates ADAM12 Through Direct Interaction With ADAM12 mRNA and Modulates Postischemic Perfusion Recovery
Authors: Lamin Victor , Verry Joseph , Dokun Olumayowa S. , Kronemberger Ana , Wong Thomas , Lira Vitor A. , Dokun Ayotunde O.
Published: August 2022

Background

Peripheral artery disease is caused by atherosclerotic occlusion of vessels outside the heart and most commonly affects vessels of the lower extremities. Angiogenesis is a part of the postischemic adaptation involved in restoring blood flow in peripheral artery disease. Previously, in a murine hind limb ischemia model of peripheral artery disease, we identified ADAM12 (a disintegrin and metalloproteinase gene 12) as a key genetic modifier of postischemic perfusion recovery. However, less is known about ADAM12 regulation in ischemia. MicroRNAs are a class of small, noncoding, single‐stranded RNAs that regulate gene expression primarily through transcriptional repression of messenger RNA (mRNA). We showed microRNA‐29a (miR‐29a) modulates ADAM12 expression in the setting of diabetes and ischemia. However, how miR‐29a modulates ADAM12 is not known. Moreover, the physiological effects of miR‐29a modulation in a nondiabetic setting is not known.

Methods and Results

We overexpressed or inhibited miR‐29a in ischemic mouse gastrocnemius and tibialis anterior muscles, and quantified the effect on perfusion recovery, ADAM12 expression, angiogenesis, and skeletal muscle regeneration. In addition, using RNA immunoprecipitation–based anti‐miR competitive assay, we investigated the interaction of miR‐29a and ADAM12 mRNA in mouse microvascular endothelial cell, skeletal muscle, and human endothelial cell lysates. Ectopic expression of miR‐29a in ischemic mouse hind limbs decreased ADAM12 mRNA expression, increased skeletal muscle injury, decreased skeletal muscle function, and decreased angiogenesis and perfusion recovery, with no effect on skeletal muscle regeneration and myofiber cross‐sectional area following hind limb ischemia. RNA immunoprecipitation–based anti‐miR competitive assay studies showed miR‐29a antagomir displaced miR‐29a and ADAM12 mRNA from the AGO‐2 (Argonaut‐2) complex in a dose dependent manner.

Conclusions

Taken together, the data show miR‐29a suppresses ADAM12 expression by directly binding to its mRNA, resulting in impaired skeletal muscle function, angiogenesis, and poor perfusion. Hence, elevated levels of miR‐29a, as seen in diabetes and aging, likely contribute to vascular pathology, and modulation of miR‐29a could be a therapeutic target.
MINT ÜLKELERİNDE CARİ İŞLEMLER AÇIĞI SÜRDÜRÜLEBİLİR Mİ?
Authors: HACIİMAMOĞLU Tunahan
Published: August 2022

Bu çalışmanın amacı 1987-2020 döneminde yıllık ihracat ve ithalat verileri kullanılarak MINT ülkeleri için cari açığın sürdürülebilir olup olmadığını Husted (1992) ve Quintos (1995) modelleri bağlamında analiz etmektir. Bu amaç doğrultusunda çalışmada eşbütünleşme ilişkisinin tahmini için Durbin-Hausman testi, katsayı tahmini için ortak ilişkili etkiler ortalama grup tahmincisi (CCE-MG), nedensellik ilişkisinin tahmini için ise Emirmahmutoğlu ve Köse (2011) bootstrap panel nedensellik yaklaşımları kullanılmıştır. Eşbütünleşme analizi sonuçları ihracat ve ithalat değişkenlerinin uzun dönemde birlikte hareket ettiklerini, diğer bir ifade ile eşbütünleşik olduklarını ortaya koymuştur. Dolayısı ile MINT ülkeleri için cari açığın sürdürülebilir olduğu ifade edilebilir. Öte yandan uzun dönem katsayı tahmincisi sonuçlarına göre MINT ülkeleri için ithalat değişkeninin katsayı değeri 0.31 olarak belirlenmiştir. Bu sonuç Husted (1992) ve Quintos (1995) modelleri bağlamında bu ülkeler için cari açığın zayıf düzeyde sürdürülebilir olduğu anlamına gelmektedir.
MESLEKİ BAĞLILIĞIN EKSTRA ROL DAVRANIŞI ÜZERİNDEKİ ETKİSİNDE İŞE ADANMANIN ARACILIK ROLÜ: ACİL YARDIM VE AFET YÖNETİMİ ÇALIŞANLARI ÜZERİNE BİR ARAŞTIRMA
Authors: MUMCU Ahmet
Published: August 2022

Bu çalışmanın amacı, çalışanlarının mesleki bağlılıklarının ekstra rol davranışları üzerindeki etkisinde işe adanmanın aracılık rolünü tespit etmektir. Bu amaç doğrultusunda araştırma Tokat ili merkez ilçesinde acil yardım ve afet yönetim sürecinde görev alan farklı kamu ve stk personelleri üzerinde gerçekleştirilmiştir. Araştırmanın örneklemi 162 acil yardım ve afet yönetimi personelinden oluşmaktadır. Araştırma verilerini test etmek amacıyla AMOS ve SPSS Process Macro programları kullanılmıştır. Aracılık modelinin açıklanmasında Zhao ve diğerleri tarafından geliştirilen aracılık tipoojisi kullanılmıştır. Araştırma verilerinden elde edilen bulgulara göre, mesleki bağlılığın işe adanma ve ekstra rol davranışı üzerinde pozitif yönlü etkiye sahip olduğu tespit edilmiştir. İşe adanmanın ekstra rol davranışı üzerinde pozitif yönlü etkiye sahip olduğu belirlenmiştir. Mesleki bağlılığın ekstra rol davranışı üzerindeki etkisinde işe adanmanın dolaylı aracılık rolüne sahip olduğu tespit edilmiştir. Çalışmanın sonunda uygulayıcılara ve araştırmacılara yönelik çeşitli öneriler sunulmuştur.
TWİTCH PLATFORMU ARACILIĞIYLA ELDE EDİLEN KAZANÇLARIN GELİR VERGİSİ AÇISINDAN DEĞERLENDİRİLMESİ
Authors: YEGEN Baki
Published: August 2022

Sanal ortamda video içerik platformlarının yoğun ilgi gördükleri içinde bulunduğumuz bu dönemde ülkemizde ve dünya çapında yaygın olarak kullanılan platformlardan biri de Twitch platformudur. Twitch platformu, başta video oyun kategorisi olmak üzere sohbet müzik ve doğa gibi çeşitli kategorilerdeki yayıncılara ait canlı görüntü akışlarının izleyicilerle paylaşılmasına aracılık etmektedir. Aynı zamanda platform yayıncılara kanallarında yayınlanan reklamlar üzerinden, platformda satılan sanal ürünler üzerinden ve bağış ödemeleri üzerinden olmak üzere farklı şekillerde kazanç elde etme imkânı sunmaktadır. Çalışmada platform aracılığıyla elde edilen farklı kazanç türlerinin vergilendirilmeleri hususunda geçmiş yıllarda yaşanan belirsizlikler üzerinde durulmuş ve belirsizlikleri gidermesi öngörülen güncel yasal düzenlemelere değinilmiştir. Bu kapsamda kazanç türleri gelir vergisi açısından ilgili kanun hükümleri, tebliğ ve özelgeler eşliğinde incelenmiş, özellikle 193 sayılı Gelir Vergisi Kanunu’na eklenen sosyal içerik üreticiliğinde kazanç istisnası ile ilgili açıklamalar üzerinde durulmuştur. Sonuçta Twitch platformu aracılığıyla elde edilen türü fark etmeksizin bütün gelirlerin ticari kazanç hükümlerine tabi oldukları anlaşılmış ve söz konusu kazançların etkin şekilde vergilendirilmeleri için çeşitli öneriler sunulmuştur.
THE CRIME OF INSULTING RELIGIOUS VALUES IN THE TURKISH PENAL CODE (TPC 216/3)
Authors: KAN Celal Hakan
Published: August 2022

Hate speech is a type of expression that results from people's inability to tolerate and tolerate certain characteristics of each other in society, such as religion, belief, and race. Such statements are one of the obstacles to the growth of a democratic society that dynamites the society's peace and serenity over time, if not in a short time. When it comes to expressions that can be classified as hate speech, the state's positive obligations in terms of protecting the beliefs and convictions of other individuals of the impacted society will come into play. The Turkish Penal Code (TPC) has laws on the punishment of hate speech expressions in this regard (TPC). One of them is TPC 216/3 on the crime of insulting religious values. Based on this context, the expression of insulting religious values within the scope of hate speech in this study is to examine the elements of the crime of insulting religious values, which is also subject to the decisions of international supervisory bodies, within the scope of TPC 216/3, of the crime of insulting the religious values of a section of the population.

Keywords: Hate Speech, Insulting Religious Values, Insulting Religion.
POOL SELECTION AND POOL MANAGEMENT APPROACH IN CASH FUNDING IN PARTICIPATION BANKS
Authors: TAĞTEKİN Teoman
Published: August 2022

The basic principle is to evaluate the savings collected by the participation banks, both in the pools of participation accounts and in the fund allocation phase, in order to increase the profit to be distributed to these pools, in line with the principles of participation finance. Especially in the fund allocation phase, in determination of the pool from which the fund to be used will be selected; there is a common opinion that participation pools should be prioritized in line firstly the pool occupancy rate, then with the criteria determined. However, in practice, it is seen that this view can be deviated from time to time, and different pools can be preferred instead of participation pools, even though the pool occupancy rate is suitable. In the study, it was stated that the implementation of the common opinion regarding the prioritization of participation pools in fund allocation pool selections and the standardization of all participation banks should be ensured with the arrangements to be made, without allowing the use of initiative. For this purpose, the actual financial data formed in the current situation were analyzed, pool-based inferences were made and suggestions were made in accordance with the purpose of the study.
Knowledge Representation and Reasoning for Complex Time Expression in
Clinical Text
Authors: Hu Danyang , Wang Meng , Gao Feng , Xu Fangfang , Gu Jinguang
Published: August 2022

Temporal information is pervasive and crucial in medical records and other clinical text, as it formulates the development process of medical conditions and is vital for clinical decision making. However, providing a holistic knowledge representation and reasoning framework for various time expressions in the clinical text is challenging. In order to capture complex temporal semantics in clinical text, we propose a novel Clinical Time Ontology (CTO) as an extension from OWL framework. More specifically, we identified eight time-related problems in clinical text and created 11 core temporal classes to conceptualize the fuzzy time, cyclic time, irregular time, negations and other complex aspects of clinical time. Then, we extended Allen's and TEO's temporal relations and defined the relation concept description between complex and simple time. Simultaneously, we provided a formulaic and graphical presentation of complex time and complex time relationships. We carried out empirical study on the expressiveness and usability of CTO using real-world healthcare datasets. Finally, experiment results demonstrate that CTO could faithfully represent and reason over 93% of the temporal expressions, and it can cover a wider range of time-related classes in clinical domain.