bluuebunny/crossref_metadata_2025_split huggingface dataset:
Percepções da monitoria acadêmica no ensino de Histologia Básica e Comparada
Authors: De Oliveira Salmo Azambuja , Caneguim Breno Henrique 
Published: November 2023

Introdução: a monitoria acadêmica é uma atividade de apoio ao ensino que auxilia os alunos nas dificuldades de aprendizagem, contribui para a melhoria da qualidade do ensino e estimula o interesse pela docência. Objetivo: este relato de experiência apresenta os dados obtidos e as percepções do monitor durante suas atividades na disciplina de Histologia Básica e Comparada de duas turmas do curso de graduação em Ciências Biológicas de uma instituição de ensino superior. Metodologia: nos semestres letivos de 2017 e 2018, o monitor obteve a frequência de procura pela monitoria e pelos conteúdos de cada avaliação, os conteúdos de maior e menor dificuldade da disciplina e o grau de satisfação discente em relação ao material complementar produzido. Os relatos discentes e as reflexões do monitor a respeito da experiência também foram objeto de análise. Resultados: os resultados mostraram que a frequência de procura pelo monitor aumentou ao longo dos dois semestres letivos, e que a interpretação e esquematização das fotomicrografias foram um dos conteúdos mais procurados pelas duas turmas, mas não os mais difíceis. Nesse quesito, os conteúdos sobre os tecidos cartilaginosos, nervoso, sanguíneo e do sistema circulatório foram considerados os de maior dificuldade, mas sem consenso entre as turmas. Entretanto, ambas concordaram que o material complementar produzido foi útil. Para o monitor, esta experiência mostrou-se fundamental para o seu crescimento pessoal, acadêmico e profissional. Conclusão: assim, a monitoria acadêmica possibilitou o aprofundamento dos conteúdos da disciplina e o desenvolvimento de habilidades didáticas e pedagógicas pelo monitor, bem como ferramenta diagnóstica para o professor.
Hybrid Approach Using Physical Insights and Data Science for Stuck-Pipe Prediction
Authors: Kaneko Tatsuya , Inoue Tomoya , Nakagawa Yujin , Wada Ryota , Abe Shungo , Yasutake Gota , Fujita Kazuhiro 
Published: November 2023

Summary
Early detection of stuck-pipe incidents is crucial because of the enormous costs of recovering from such incidents. Previous studies have leaned significantly toward a physics-based or data science approach. However, both approaches have challenges, such as the uncertainty of the physics-based model and the lack of data in the data science approach. In this study, we propose a hybrid approach using physical insights and data science and discuss the possibility of stuck-pipe prediction.
The proposed method comprises two steps. In the first step, a data-driven model with physical insights is trained using the historical data of the in-situ well to estimate some of the drilling variables. In the second step, the risk of stuck-pipe occurrence (hereafter referred to as sticking risk) is calculated based on the historical and current measured data and the estimation of the trained model. This approach is expected to overcome the limitations of the previous methods as it allows the construction of a detection model tuned to the in-situ well. In the case studies, models for estimating the topdrive torque and standpipe pressure were constructed. The performance of the models is discussed using actual drilling data from drilling fields, including 21 stuck-pipe incidents during drilling operations.
The proposed method was first examined using short-term output. The output confirmed that the sticking risk increased shortly (up to 20 hours) before the stuck-pipe incident occurred in 15 cases. This increase in sticking risk was consistent with physical considerations. Subsequently, this study examined the long-term output over several months; this was rarely done in previous studies. Even within this long-term output, some cases had good performance with only a few false alarms, while others had problems with many false alarms. For cases of low performance, several model improvements, such as adding mud information or making the learning and threshold-setting methods more robust to outliers, were found to have the potential to improve performance.
The novelty of our research lies in creating a broad framework for the stuck-pipe prediction by using both physical insights and data science methods. The proposed hybrid approach demonstrated the potential to reduce false alarms and improve interpretability compared with previous methods. The framework is highly extensible, and further performance improvements can be expected in the future.
A System to Detect Oilwell Anomalies Using Deep Learning and Decision Diagram Dual Approach
Authors: Aranha P. E. , Lopes L. G. O. , Paranhos Sobrinho E. S. , Oliveira I. M. N. , de Araújo J. P. N. , Santos B. B. , Lima Junior E. T. , da Silva T. B. , Vieira T. M. A. , Lira W. W. M. , Policarpo N. A. , Sampaio M. A. 
Published: November 2023

Summary
Detecting unexpected events is a field of interest in oil and gas companies to improve operational safety and reduce costs associated with nonproductive time (NPT) and failure repair. This work presents a system for real-time monitoring of unwanted events using the production sensor data from oil wells. It uses a combination of long short-term memory (LSTM) autoencoder and a rule-based analytic approach to perform the detection of anomalies from sensor data. Initial studies are conducted to determine the behavior and correlations of pressure and temperature values for the most common combinations of well valve states. The proposed methodology uses pressure and temperature sensor data, from which a decision diagram (DD) classifies the well status, and this response is applied to the training of neural networks devoted to anomaly detection. Data sets related to several operations in wells located at different oil fields are used to train and validate the dual approach presented. The combination of the two techniques enables the deep neural network to evolve constantly through the normal data collected by the analytical method. The developed system exhibits high accuracy, with true positive detection rates exceeding 90% in the early stages of anomalies identified in both simulated and actual well production scenarios. It was implemented in more than 20 floating production, storage, and offloading (FPSO) vessels, monitoring more than 250 production/injection subsea wells, and can be applied both in real-time operation and in testing scenarios.
Identification of Potential Therapeutic Target SPP1 and Related RNA Regulatory Pathway in Keloid Based on Bioinformatics Analysis
Authors: Xie Ruxin , Yun Jiao , Li Chenyu , Zhang Shiwei , Zhong Ai , Wu Junliang , Cen Ying , Chen Junjie 
Published: November 2023

Abstract
Objective
To explore the complex mechanisms of keloid, new approaches have been developed by different strategies. However, conventional treatment did not significantly reduce the recurrence rate. This study aimed to identify new biomarkers and mechanisms for keloid progression through bioinformatics analyses.
Methods
In our study, microarray datasets for keloid were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by R software. Multiple bioinformatics tools were used to identify hub genes, and reverse predict upstream miRNAs and lncRNA molecules of target hub genes. Finally, the total RNA-sequencing technique and miRNA microarray were combined to validate the identified genes.
Results
Thirty-one DEGs were screened out and the upregulated hub gene SPP1 was finally identified, which was consistent with our RNA-sequencing analysis results and validation dataset. In addition, a ceRNA network of mRNA (SPP1)-miRNA (miR-181a-5p)-lncRNA (NEAT1, MALAT1, LINC00667, NORAD, XIST and MIR4458HG) was identified by the bioinformatics databases. The results of our miRNA microarray showed that miR-181a-5p was upregulated in keloid, also we found that the lncRNA NEAT1 could affect keloid progression by retrieving the relevant literature.
Conclusions
We speculate that SPP1 is a potential candidate biomarker and therapeutic target for patients with keloid, and NEAT1/miR-181a-5p/SPP1 might be the RNA regulatory pathway that regulates keloid formation.
Conditioning of agro-industrial residues for producing enzymes, additives and chemical precursors
Authors: Rivero Mayola García , Venegas Isabel de la Luz Membrillo , Trujillo María Aurora Martínez 
Published: November 2023

Abstract

Purpose Show how the most common conditioning treatments of lignocellulosic agricultural residues determine the performance of specific biological processes and after a review propose a final use for the resulting residues.
Methods Conditioning treatments such as drying and size reduction for prickly pear peels, or soaking and ultrasound for pineapple peels were applied before using these materials in a solid state-culture or an enzymatic saccharification, respectively. A detailed analysis about the fate of those solids obtained after solidstate culture on prickly pear peels or saccharification of pineapple peels was done to propose the integral use of these materials in the bioprocess performance.
Results In a solid-state culture using 1.84 mm particles of sun-dried prickly pear peels, Aspergillus niger produced eight-fold more xylanases and twice more laccases than those obtained on 1.09 mm wave-dried particles. Conversely, the highest enzymatic saccharification yields of pineapple peels were obtained with unconditioned peels, which means an advantage for the economy and operation of the process. The resulting residual composites can have several fates. Conclusion Agricultural residues are a potential material for obtaining biotechnological products, and some of the conditioning treatments are not necessary to use them in a bioprocess. These residues can have an integral use along the bioprocess development.
A Voyage from Imitation to Real – Knowledge-Enabled Generationof Semantically Annotated Datasets and Deep Learning Techniquesfor Robot Vision Impacts
Authors: Alam Mansoor , Parasad Mukesh , Mustapha Jawahir Che , Su'ud Mazliham Mohd , Sultana Saima 
Published: November 2023

Abstract
Computer vision technologies have fascinated substantial concern to visionary mission duringrecent years. At the edge of industry 4.0, Artificial intelligence comprehend Robotics andcomputer vision. Which briskly results as novel innovations, thematic invention and esteemedresearch at numerous fields of technology. To enclose the most recent research of Robot vision,the current study is designed. The coverage arena of this study is span over, but not limitedto Robot vision Datasets, Deep learning tools and techniques and labeling toolkits for visiondatasets. The features targeted through these data-driven approaches are highly robust than theirmanually engineered counterparts. The research study covers the most recent, state of the art andin-fashion researches debuted to Robot vision.
Unleashing the Power of Indirect Attacks against Trust Prediction via Preferential Path
Authors: Bu Yu , Zhu Yulin , Geng Longling , Zhou Kai 
Published: November 2023

Abstract

In the realm of network security, adversarial attacks pose a significant threat, prompting research into innovative strategies for enhancing both attack and defense mechanisms. This paper presents a novel exploration into the enhancement of adversarial attacks on Fairness and Goodness Algorithm (FGA) and Review to Reviewer (REV2), focusing on trust prediction within signed graphs. In contrast to traditional time-based dynamics, the trust propagation in FGA and REV2 is grounded on iterative processes. Through meticulous analysis of network structures, this research uncovers the strong ties and weak ties within FGA. Additionally , it reveals the existence of preferential paths in REV2, which significantly influence the spread of information during algorithm iterations. Leveraging these revelations, we introduce a novel approach known as vicinage-attack designed to bolster adversarial attacks by strategically targeting edges along these influential pathways. The significance of this work lies in identifying adversarial perturbation patterns that impact trust prediction on signed graphs, shedding light on their pervasive influence. Our findings not only contribute to the advancement of adver-sarial attack techniques but also lay the foundation for a deeper understanding of trust propagation patterns. By elucidating the propagation bias within FGA and REV2, this research offers new insights for both network security strategies and adversarial mitigation techniques in trust prediction.
Clinical and neuropsychological variables associated with subjective cognitive decline and its progression
Authors: Villino-Rodríguez Rafael , Ríos-Rivera Mirla M. , Imaz-Aguayo Laura , Espinoza-Vinces Christian , Pérez-Prol Cristina , Montoya-Murillo Genoveva , Arrondo Carlota , Riverol Mario 
Published: November 2023

Abstract
Background and Objectives:
This study aimed to compare clinical and neuropsychological variables between patients with subjective cognitive decline (SCD) and healthy controls in a memory clinic, while identifying variables associated with progression to mild cognitive impairment (MCI) or dementia.
Methods:
We retrospectively analysed data from 945 patients with SCD and 68 healthy controls (HCs) who visited the Clínica Universidad de Navarra memory clinic between 2001 and 2017. Among them, 450 participants were followed up longitudinally in at least one visit until January 2020. All patients underwent medical interviews, laboratory tests, neuropsychological assessments (during the first interview and follow-ups) and brain magnetic resonance imaging. Of the 945 participants, 131 progressed to MCI or dementia due to Alzheimer’s disease. The neuropsychological assessment encompassed the following domains: cognitive functions (i.e. global cognition, episodic visual and verbal memory, executive functions, phonetic fluency, cognitive flexibility, interference and language), neuropsychiatric symptoms and functional status. All variables were adjusted for age, sex and education.
Results:
Participants with subjective cognitive decline were younger and had higher education than HCs. Additionally, they presented more vascular risk factors. Age at diagnosis, years of education and the presence of hypercholesterolemia were among the demographic variables that were positively associated with the development of MCI or dementia. In the neuropsychological assessment, individuals with SCD showed worse results in global cognition, verbal memory and semantic and phonetic fluency and exhibited more depressive symptoms. Moreover, exhibiting worse performance on tests evaluating episodic verbal memory was found to be correlated with an elevated likelihood of transitioning to MCI and dementia.
Discussion:
The development of SCD and its progression to MCI or dementia is a multifaceted process involving clinical and neuropsychological factors. Younger age and increased vascular risk factors are characteristics of individuals with SCD. Neuropsychologically, they tend to display weaker performance in global cognition, fluency tasks, verbal memory and executive functions. Several variables were identified as potential indicators of disease progression. These include age at diagnosis, hypercholesterolemia and poorer results in tests measuring semantic fluency, verbal and visual memory and executive functions.
Risk factors for and developmental relation of delayed oral nutrition in infants with congenital diaphragmatic hernia
Authors: Yamamichi Taku , Imanishi Yousuke , Sakai Takaaki , Yoshida Mina , Takayama Keita , Uga Naoko , Umeda Satoshi , Usui Noriaki 
Published: November 2023

Abstract
Purpose: To identify risk factors for delayed oral nutrition in infants with a congenital diaphragmatic hernia (CDH) and its impact on developmental delay at 18 months of age.
Methods: This retrospective single-center cohort study compared the clinical parameters in patients with isolated CDH born and treated at our hospital between 2006 and 2020. We evaluated clinical features significantly related to delayed oral nutrition (defined as taking ≥30 days from weaning from mechanical ventilation to weaning from tube feeding)
Results: Twenty-six of the 80 cases had delayed oral nutrition. Univariate analyses showed significant differences. Multivariate analyses were performed on the three items of preterm delivery, defect size (over 50% to nearly entire defect), and ventilation for ≥9 days. We identified the latter two items as independent risk factors. The adjusted odds ratios were 4.65 (95% confidence interval, 1.27–7.03) and 6.02 (1.65–21.90), respectively. Delayed oral nutrition was related to a significantly higher probability of developmental delay at 18 months (crude odds ratio 4.16, 1.19–14.5).
Conclusion: In patients with CDH, a large defect and ventilatory management over 9 days are independent risk factors for delayed oral nutrition, which is a potent predictor of developmental delay that requires active developmental care.
An Identification Method for Dynamic Systems with SCNs Hysteresis Compensator: Application to the Inchworm Piezo Motor
Authors: Han Shuo , Xu Yunlang , Yu Jianbo , Yang Xiaofeng 
Published: November 2023

Abstract
It is widely known that inchworm piezo motors are being used in ultra-precision detection platforms where high clamping force and nano-precision are required. This paper examines and proposes a dynamic model of the inchworm piezo motor to improve the performance and controller. Traditional identification strategies have not been adopted for calculating parameters for the dynamic model exhibiting hysteresis nonlinearity. In addition, hysteresis deteriorates the accuracy of positioning of inchworm piezo motors. It has been proposed to solve these problems using a feedforward controller, a hysteresis compensator based on a stochastic configuration networks algorithm (SCNs). Using the SCNs algorithm, both voltage and displacement inputs can be used to describe the nonlinear memory of hysteresis, and the kernel function provides a flexible and accurate representation of this behavior. This method enables the dynamic model parameters of the inchworm piezo motor to be identified using frequency sweeps. A proportional-integral (PI) controller is used to verify the positioning accuracy, and experimental results show that an inchworm piezo motor has a positioning accuracy of about 1nm when the laser interference is low with a 10M Hz adoption rate and 0.1nm resolution.
Application the reduced method for Characterization the photonic properties of amorphous Se 79.13 S 11.41 Te 9.64 Nano thin film composition Part(I)
Authors: Elsayed Samy A. , Khalifa Zaki 
Published: November 2023

Abstract
Application the reduced method for determination the optical properties of nano thin film chalcogenide composition Se79.13S11.41Te9.64 reveals that the refractive index (n) is wavelength (λ) dependent. Cauchy dispersion equation is fit the obtained results of n = f (λ) for the measured wavelength and Cauchy dispersion coefficients are determined. The optical band edge is equal to 1.8eV. The optical energy gap is allowed indirect equals to 4 eV, The sup energy level in the gap equals to ≈ 3eV. From the dependence of extinction coefficient on λ the Fermi level of the nano thin film Se79.13S11.41Te9.64 is determined equals to 2.528 eV. Applying Wemple- DiDomenico The single oscillator model, the effective dispersion oscillator energy E o = 1.17 eV and the dispersion energy Ed is determined equal to ≈3.87 eV. Also, the following results determined, the static refractive index no =2.15, the static dielectric constant εo = 4.62 and the average bond strength is \({E}_{g}^{WD}=1.95eV\) The effect of lone pair concentration in chalcogenides on the energy gap and nonlinearity properties of amorphous chalcogenides is the subject of the second part of this work.
The Prevalence and Post-Operative Complications of Uterine Leiomyomas in South-Western Nigeria and Northern Nigeria: A Comparartive Review
Authors: Anaziah Grace , Lawal Yusuf , OC Ezechi 
Published: November 2023

Abstract
Background: Uterine Leiomyoma are benign tumors which commonly affect women of reproductive age, however only a subset of women has their fibroids clinically detected, symptomatic or warrant surgical treatment. Its removal is associated with complications. To control the occurrence of this complication requires the understanding of the factors associated with the complications.
Methods: The study was carried at two large tertiary hospitals in South-western and Northern region of Nigeria. It was a descriptive cross-sectional study that was conducted among patients in these regions. Information such as sociodemographic characteristics was recorded in questionnaire including retrospective review of case records of all surgically managed cases of uterine leiomyoma (from one hundred and fifty-nine women) was obtained after formal consent from the hospital’s ethics committee.
Results: In Both regions of Nigeria, the common presenting complaints from 36-40 years old patients were menstrual irregularities, Abdominal swelling, and infertility. The commonest anatomical position of the nodules were multiple positions and intramural.
The majority (79.9%) of the women in South-Western Nigeria presented with multiple leiomyomas. While the majority (48.8%) of the women in Northern Nigeria presented multiple leiomyomas which accounted for almost half of the patients diagnosed in that region. In the South-western region of Nigeria, post-operative complications occurred in 20.9 % of cases with post-operative pyrexia (13.5%), blood loss warranting transfusion (12.8%) and post-operative anemia (10.4%) been the most common complications. While in the Northern region of Nigeria no complications were recorded.
Conclusion: Uterine leiomyomas is common in Nigeria and usually presents with menorrhagia, pelvic pain, recurrent miscarriage, and infertility. The surgery may be complicated by post operative pyrexia, blood loss, wound infection and even death. Midline incision, closure of rectus sheet with chromic catgut and myomectomy were associated with postoperative complications in this review. To avoid postoperative morbidities associated with surgical management of fibroid, Pfannenstiel incision where feasible, use of non-absorbable or delayed absorbable sutures and hysterectomy in women who have completed family should be adopted in the Southwestern region of Nigeria. Whereas prevalence of uterine leiomyomas is generally prevalent in the Southwest, there are varying age prevalence’s in the North and Southwest.