bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailgut Cyst – A Case Report
Authors: Scolaro Bruno Lorenzo , Pereira Gustavo Becker , Ferrari Fangio , Dall'Agnol Letícia , Arias Lívia de Aragon , Souza Neto Anisio de 
Published: June 2022

AbstractRetrorectal hamartoma, also called tailgut cyst, is a congenital lesion resulting from the non-regression of embryo remnants of the hindgut. We describe in this work the case report of a 68-year-old man, previously healthy, complaining of rectal bulging for 4 months, which was diagnosed by nuclear magnetic resonance imaging as a multiloculated and mucinous lesion, suggestive of tailgut cyst. In view of the finding, the lesion was surgically resected, due to the potential for future complications, and, through the anatomopathological analysis, there were no findings of malignancy in the specimen.
Giant Colonic Diverticulitis, an Extremely Rare Presentation of a Rare Disease — Clinical Presentation and Literature Review
Authors: Bekhor Eliahu Y. , Orgad Ran , Shmilovitch Hila , Ayalon Rotem , Kaminsky Oleg 
Published: June 2022

AbstractIntroduction Giant colonic diverticulum (GCD) is rare phenomenon, with less than 200 cases described in the literature. One of the complications of GCD is diverticulitis. To date, there is paucity of data addressing the diagnosis and management of GCD complicated by acute diverticulitis.Objective To better understand the diagnostic tools, the initial management, and the long-term follow-up for this group of patients as well as to recommend a proper multidisciplinary approach to this infrequent disease.Method A systematic literature search was performed using the PubMed, Embase, and Cochrane databases to identify all the published studies on GCD complicated by diverticulitis. Two of the authors assessed the relevance of the included full-text papers. The articles were assessed independently.Results In total, 12 cases were identified. Our results show that 10/11 (91%) of the patients who had computed tomography (CT) scans during the initial evaluation had a correct diagnosis. There was no case of failure to non-operative approach (7/7). The patients who had an emergency operation were treated so due to diffuse peritonitis (two patients), acute hemorrhage arising from ulcers within the diverticula (one patient), and misdiagnosis (one patient).Conclusion Giant colonic diverticulitis is a very rare disease. Computed tomography scan is a valuable tool for the initial diagnosis as well as for treatment strategy planning. Non-operative management is a viable option for patients without diffuse peritonitis. Interval endoscopy is recommended if no contraindication exists.
Vulnerable Carotid Artery Plaques in Asymptomatic Patients—A Narrative Review
Authors: Rehman Zia Ur 
Published: June 2022

AbstractOver the last two decades, medical management of carotid artery patients has improved significantly. Most patients remain stable on best medical therapy (BMT), making interventions unnecessary in all patients. “Selective” intervention is advocated for only those few patients who are having vulnerable or unstable carotid artery plaques. Literature search was done to explore current concept and role of available investigations to identify vulnerable carotid plaques. Vulnerable plaque is defined as those plaques having active inflammation, high large necrotic lipid content, neovascularity, thin capsule, surface irregularity, or intraplaque hemorrhage. Ultrasound (US) is the simple, noninvasive, cost-effective investigation to differentiate soft (echolucent) from fibrocalcified (echogenic) plaques. It can also comment on other high-risk plaque features such as plaque volume and area. Contrast-enhanced US can visualize neovascularization and plaque surface irregularities better than conventional US. Computed tomography is limited in identifying most high-risk plaque features and is not useful. High-resolution magnetic resonance imaging is the most accurate and externally validated investigation to characterize most high-risk plaque components. Positron emission tomography has emerged as the most promising dynamic investigation to identify and quantify inflammatory plaques and will be clinically very useful in decision making.
A cognitive approach to metaphor translation in business texts
Authors: Shehab Ekrema Mohammad , Daragmeh Abdelkarim Tawfiq , Qadan Abdul-Rahman Saleh , Nazzal Reema Essam 
Published: June 2022

Abstract
A metaphor is normally deployed for specific rhetorical and aesthetic functions. However, in the commercial context, metaphor usage displays specific communicative functions as exhibited in the English business texts we sampled for this study. We examine the translation of business metaphor from English into Arabic with a special focus on the game/sports source domain. The authors collected a sample of metaphors from business articles which appear on the BBC, CNN, and Project Syndicate online websites. We use the collected business metaphors to determine the contextual functions as well as the significance and roles each metaphor plays in its context. We adopt the cognitive approach to metaphor analysis in order to identify the level of conceptual systems in the source and target metaphorical references. We have found out that the generic metaphorical instances are translated using the formal translation method while the more business context specific metaphors are simplified, paraphrased, or explicated.
Modelling the relationship between load and repetitions to failure in resistance training: A Bayesian analysis
Authors: Mitter Benedikt , Zhang Lei , Bauer Pascal , Baca Arnold , Tschan Harald 
Published: June 2022

ABSTRACTTo identify the relationship between load and the number of repetitions performed to momentary failure in the pin press exercise, the present study compared different statistical model types and structures using a Bayesian approach. Thirty resistance‐trained men and women were tested on two separate occasions. During the first visit, participants underwent assessment of their one‐repetition maximum (1‐RM) in the pin press exercise. On the second visit, they performed sets to momentary failure at 90%, 80% and 70% of their 1‐RM in a fixed order during a single session. The relationship between relative load and repetitions performed to failure was fitted using linear regression, exponential regression and the critical load model. Each model was fitted according to the Bayesian framework in two ways: using an across‐subjects pooled data structure and using a multilevel structure. Models were compared based on the variance explained (R2) and leave‐one‐out cross‐validation information criterion (LOOIC). Multilevel models, which incorporate higher‐level commonalities into individual relationships, demonstrated a substantially better fit (R2: 0.97–0.98) and better predictive accuracy compared to generalised pooled‐data models (R2: 0.89–0.93). The multilevel 2‐parameter exponential regression emerged as the best representation of data in terms of model fit, predictive accuracy and model simplicity. The relationship between load and repetitions performed to failure follows an individually expressed exponential trend in the pin press exercise. To accurately predict the load that is associated with a certain repetition maximum, the relationship should therefore be modelled on a subject‐specific level.
Excitation of semiconductor nanosystems by a few-photon frequency-multimode optical field
Authors: Tereshchenko I A , Tikhonova O V 
Published: June 2022

Abstract
The excitation of a semiconductor quantum nanosystem induced by a frequency-multimode nonclassical electromagnetic field is analytically investigated. The possibility to control the features and dynamics of different excitation channels by varying the weights and initial energy distribution in the considered field spectral modes is demonstrated. Strong coupling between different frequency modes is found to arise due to their interaction with electronic subsystem and is shown to influence dramatically on the excitation. The peculiarities of the excitation process induced by a multi-frequency Schmidt mode, which characterizes spectral distribution of squeezed vacuum light, are revealed. The optimal spectral profile of the Schmidt mode and initial energy distribution of different field spectral components providing the most efficient excitation of a nanosystem are found.
Electron emission from the focus of the Gaussian pulse
Authors: Borovskiy A V , Galkin A L 
Published: June 2022

Abstract
For a symmetric trajectory of an electron in the field of a Gaussian pulse, the parameters of radiation from a section in the vicinity of the focus are studied. It is shown that the modulus of velocity and modulus of acceleration are quasi-periodic, their maxima are separated in time. The radiation of an electron in the form of plane waves in the far zone is analyzed, and the intensity distribution over the solid angle is obtained. The radiation directivity diagrams are constructed, and the time profile of the radiation power is obtained. The difference from the dipole approximation is discussed. We consider the radiation of an electron that appears in the vicinity of the focus as a result of ionization.
Sensitive temperature-dependent phase resolution of polyethylene-clay nanocomposites
Authors: Sagitova E A , Donfack P , Prokhorov K A , Kuznetsov S M , Guseva M A , Gerasin V A , Nikolaeva G Yu , Materny A 
Published: June 2022

Abstract
With the help of spectroscopic and differential scanning calorimetry (DSC) techniques, we have studied conformational and phase reorganizations as function of temperature in intercalated polymer-clay nanocomposites based on low-, middle-, and high-density polyethylene (PE) matrices. We show that Raman spectroscopy is sensitive to structural changes appearing during heating at much lower temperatures (about 47 °C) in comparison to DSC measurements. In fact, in the melting region where DSC traces show endotherms, Raman spectra reveal dramatic changes in the phase and conformational compositions of PE and PE-matrices within PE-clay nanocomposites. Noteworthy, the structural reorganization pathway, through which the semicrystalline nanocomposites transform into a melt state, depends primarily on the PE density and weakly on the filler (nanoclay). Moreover, the temperature-dependent crystallinity degree and the total amount of trans-conformers of the PE system are determined, and the evidence for the formation of intermediate crystal-like phase during heating is shown.
Data parallel processing in block streams for analysis of long-term series of ozone content in ground atmosphere
Authors: Stepanov Eugene V 
Published: June 2022

Abstract
The article describes a new approach to the processing of long series of ozone monitoring data in the surface atmosphere called the Data Parallel Processing in Block Streams. The proposed method is based on splitting of a sequential series of initial data into blocks filled with surface ozone monitoring data for one day. Further, a chain is formed from such blocks, the length of which is determined by the total length of the monitoring process. Along this chain of blocks, parallel processing of the initial data is carried out, aimed at smoothing out fast fluctuations. The smoothed data is then used to determine the daily production of ozone due to photochemical reactions, its minimum nighttime levels, as well as the magnitude of nighttime maxima. The possibilities of the proposed approach are demonstrated using the analysis of surface ozone monitoring data in Moscow, Russia, in 2020. The prospects for further application of the developed method are discussed.
Driving potential and fission-fragment charge distributions
Authors: Su Yuan , Liu Min , Wang Ning 
Published: June 2022

Abstract
We propose an efficient approach to describe the fission-fragment charge yields for actinides based on the driving potential of the fissioning system. Considering the properties of primary fission fragments at their ground states, the driving potential, which represents the potential energies of the system around scission configuration and closely relates to the yields of fragments, can be unambiguously and quickly obtained from the Skyrme energy-density functional together with the Weizsäcker–Skyrme mass model. The fission-fragment charge distributions for thermal-neutron-induced fission and spontaneous fission of a series of actinides, especially the odd–even staggering in the charge distributions, can be well reproduced. Nuclear dynamical deformations and pairing corrections of fragments play an important role in the charge distributions.
Enhanced magnetic transduction of neuronal activity by nanofabricated inductors quantified via finite element analysis
Authors: Phillips Jack , Glodowski Mitchell , Gokhale Yash , Dwyer Matthew , Ashtiani Alireza , Hai Aviad 
Published: June 2022

Abstract

Objective. Methods for the detection of neural signals involve a compromise between invasiveness, spatiotemporal resolution, and the number of neurons or brain regions recorded. Electrode-based probes provide excellent response but usually require transcranial wiring and capture activity from limited neuronal populations. Noninvasive methods such as electroencephalography and magnetoencephalography offer fast readouts of field potentials or biomagnetic signals, respectively, but have spatial constraints that prohibit recording from single neurons. A cell-sized device that enhances neurogenic magnetic fields can be used as an in situ sensor for magnetic-based modalities and increase the ability to detect diverse signals across multiple brain regions. Approach. We designed and modeled a device capable of forming a tight electromagnetic junction with single neurons, thereby transducing changes in cellular potential to magnetic field perturbations by driving current through a nanofabricated inductor element. Main results. We present detailed quantification of the device performance using realistic finite element simulations with signals and geometries acquired from patch-clamped neurons in vitro and demonstrate the capability of the device to produce magnetic signals readable via existing modalities. We compare the magnetic output of the device to intrinsic neuronal magnetic fields (NMFs) and show that the transduced magnetic field intensity from a single neuron is more than three-fold higher at its peak (1.62 nT vs 0.51 nT). Importantly, we report on a large spatial enhancement of the transduced magnetic field output within a typical voxel (40 × 40 × 10 µm) over 250 times higher than the intrinsic NMF strength (0.64 nT vs 2.5 pT). We use this framework to perform optimizations of device performance based on nanofabrication constraints and material choices. Significance. Our quantifications institute a foundation for synthesizing and applying electromagnetic sensors for detecting brain activity and can serve as a general method for quantifying recording devices at the single cell level.
A Bayesian-optimized design for an interpretable convolutional neural network to decode and analyze the P300 response in autism
Authors: Borra Davide , Magosso Elisa , Castelo-Branco Miguel , Simões Marco 
Published: June 2022

Abstract

Objective. P300 can be analyzed in autism spectrum disorder (ASD) to derive biomarkers and can be decoded in brain–computer interfaces to reinforce ASD impaired skills. Convolutional neural networks (CNNs) have been proposed for P300 decoding, outperforming traditional algorithms but they (a) do not investigate optimal designs in different training conditions; (b) lack in interpretability. To overcome these limitations, an interpretable CNN (ICNN), that we recently proposed for motor decoding, has been modified and adopted here, with its optimal design searched via Bayesian optimization. Approach. The ICNN provides a straightforward interpretation of spectral and spatial features learned to decode P300. The Bayesian-optimized (BO) ICNN design was investigated separately for different training strategies (within-subject, within-session, and cross-subject) and BO models were used for the subsequent analyses. Specifically, transfer learning (TL) potentialities were investigated by assessing how pretrained cross-subject BO models performed on a new subject vs. random-initialized models. Furthermore, within-subject BO-derived models were combined with an explanation technique (ICNN + ET) to analyze P300 spectral and spatial features. Main results. The ICNN resulted comparable or even outperformed existing CNNs, at the same time being lighter. BO ICNN designs differed depending on the training strategy, needing more capacity as the training set variability increased. Furthermore, TL provided higher performance than networks trained from scratch. The ICNN + ET analysis suggested the frequency range [2, 5.8] Hz as the most relevant, and spatial features showed a right-hemispheric parietal asymmetry. The ICNN + ET-derived features, but not ERP-derived features, resulted significantly and highly correlated to autism diagnostic observation schedule clinical scores. Significance. This study substantiates the idea that a CNN can be designed both accurate and interpretable for P300 decoding, with an optimized design depending on the training condition. The novel ICNN-based analysis tool was able to better capture ASD neural signatures than traditional event-related potential analysis, possibly paving the way for identifying novel biomarkers.
Regularization and uniqueness of solutions of Volterra linear integral equations of the third kind
Authors: Toigonbaeva Aizat , Obodoeva Gumushai , Kambarova Aisalkyn 
Published: June 2022

AnnotationIntegral equations, as well as their solutions, play an important role in the study of various problems of science and technology. Of particular interest are the Volterra integral equations. In this paper, a regularizing operator is constructed using the method of M. M. Lavrentiev for solving a class of Volterra linear integral equations of the third kind.
Deformation analysis of CoCrMo-on-CoCrMo hip implant based on body mass index using 2D finite element procedure
Authors: Ammarullah Muhammad Imam , Afif Ilham Yustar , Maula Mohamad Izzur , Winarni Tri Indah , Tauviqirrahman Mohammad , Bayuseno Athanasius Priharyoto , Basri Hasan , Syahrom Ardiyansyah , Md Saad Amir Putra , Jamari  
Published: June 2022

AbstractThe paper available of total hip arthroplasty is still concerned with the external factors of implant user, but the internal factor that is the user’s body weight has not deeply understood. Our research presents deformation analysis of total hip arthroplasty with different loading conditions based on the patient’s body mass index category. 2D model is selected to conducting numerical analysis of CoCrMo-on-CoCrMo that giving vertical load from different category of body mass index, namely underweight, normal, overweight, and obese class I, obese class II, and obese class III using finite element procedures. Peak loading under normal walking conditions from actual condition of human hip joint is adopted. Our result explains that displacement in direction - y is larger in line with greater user’s body mass index.
Graph coloring program for variation of exam scheduling modeling at Binus University based on Welsh and Powell algorithm
Authors: Arifin Samsul , Muktyas Indra Bayu , Mandei Jeremy Matthew 
Published: June 2022

AbstractIn this article, we will design a computer program to solve graph colouring and to visualize the variation of exam scheduling modelling at Binus University in graphs based on the Welch and Powell Algorithm. A vertex colouring of graph G = (V, E) is an F: V → N mapping where the adjacent vertex are different colours in N, i.e. if the edge (u, v) are in E, then F (u) is not equal to F (v). The formulation of problems regarding computer programs based on a small experiment and variations in modelling exams is carried out in graph form using the Visual Basic Application.
Prospective elementary teachers’ attitude toward technology-based mathematics assessment
Authors: Putra Zetra Hainul , Rahmadhani Desri , Noviana Eddy , Hermita Neni 
Published: June 2022

Abstract
This research is motivated by the rapid development of information communication and technology (ICT) in the era of the industrial revolution 4.0. Most teachers seem to be unfamiliar with the use of technology in teaching and learning mathematics. In the present study, we are interested in investigating prospective elementary teachers’ attitudes towards technology-based mathematics assessment. We surveyed 70 prospective elementary teachers from a teacher education study program in Riau province, Indonesia. The study results show that prospective elementary teachers have positive attitudes towards the technology-based mathematics assessment. More than 75% and 55% of third and first-year students agreed with technology usage in mathematics assessment. They provided several reasons underlying the agreeableness of technology-based mathematics assessment, such as innovation, practices, and need to be used in line with the current situation.
The relationship between confidence and mathematics learning achievement of junior high school students
Authors: Febrianto  , Sulistiawati  , Rahman Bobbi , Arifin Samsul 
Published: June 2022

Abstract
Self-confidence is very important for students to actualize their potential and information on the level of student confidence is very helpful for teachers as a basis for decision making, as well as providing feedback to improve the learning process. This study aims to investigate whether there is a positive and significant relationship between self-confidence and student mathematics achievement. This research uses quantitative research methods, namely ex post facto type with a population of VII grade students of SMP Puspita Tangerang which consists of 5 classes total 188 students. Determination of the number of samples looked at the table of Issac and Michael with α = 0.05 and obtained a sample of 123 students. The data analysis of this study used a high confidence level of 95%. Based on the results of the simple linear regression test, it is found that the equation Ŷ = 21,714 + 0,374x means that there is a positive and significant relationship between self-confidence and student mathematics achievement. Then, the simple correlation coefficient test result count.
Mathematical thinking process based on student IQ test results and talented mathematical
Authors: Patmawati Hetty , Turmudi  , Prabawanto Sufyani 
Published: June 2022

Abstract
This study aims to determine how the students’ mathematical thinking processes are evaluated from the IQ test results and mathematical giftedness. Each student has his level of intelligence and talent in learning science, including mathematics. Until now, mathematics is considered a difficult subject to learn, including at the Elementary School level. However, there are elementary school students who have more advantages and have the talent to study and solve mathematical problems. The purpose of this research is to find out how the mathematical thinking ability of gifted elementary school students and how the type or model of the thinking process of gifted students in terms of the results of the IQ test, the Mathematical Gifted test. This research was conducted on elementary school students in the city of Tasikmalaya, who had been taken by purposive sampling to obtain 15 students who were used as research samples. IQ test results were obtained by 2 people belonging to the gifted category, and 13 people belonging to the superior category. The mathematical thinking process of two people who are classified as gifted fulfilled the indicators of representation, generalization, abstraction, and mathematical creativity.