bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of the field of view (FOV) on image quality in MDCT angiography of the lower extremities
Authors: Salimova Nigar , Hinrichs Jan B. , Gutberlet Marcel , Meyer Bernhard C. , Wacker Frank K. , von Falck Christian 
Published: December 2021

Abstract

Objectives
To evaluate the impact of the reconstructed field-of-view (FOV) on image quality in computed-tomography angiography (CTA) of the lower extremities.

Methods
A total of 100 CTA examinations of the lower extremities were acquired on a 2 × 192-slice multidetector CT (MDCT) scanner. Three different datasets were reconstructed covering both legs (standard FOV size) as well as each leg separately (reduced FOV size). The subjective image quality was evaluated for the different vessel segments (femoral, popliteal, crural, pedal) by three readers using a semi-quantitative Likert scale. Additionally, objective image quality was assessed using an automated image quality metric on a per-slice basis.

Results
The subjective assessment of the image quality showed an almost perfect interrater agreement. The image quality of the small FOV datasets was rated significantly higher as compared to the large datasets for all patients and vessel segments (p < 0.05) with a tendency towards a higher effect in smaller vessels. The difference of the mean scores between the group with the large FOV and small FOV was 0.68 for the femoral level, 0.83 for the popliteal level, 1.12 for the crural level, and 1.08 for the pedal level. The objective image quality metric also demonstrated a significant improvement of image quality in the small FOV datasets.

Conclusions
Side-separated reconstruction of each leg in CTA of the lower extremities using a small reconstruction FOV significantly improves image quality as compared to a standard reconstruction with a large FOV covering both legs.

Key Points
• In CT angiography of the lower legs, the side-separated reconstruction of each leg using a small field-of-views improves image quality as compared to a standard reconstruction covering both legs.
• The side-separated reconstruction can be readily implemented at every commercially available CT scanner.
• There is no need for additional hardware or software and no additional burden to the patient.
A new limited memory method for unconstrained nonlinear least squares
Authors: Kimiaei Morteza , Neumaier Arnold 
Published: December 2021

AbstractThis paper suggests a new limited memory trust region algorithm for large unconstrained black box least squares problems, called LMLS. Main features of LMLS are a new non-monotone technique, a new adaptive radius strategy, a new Broyden-like algorithm based on the previous good points, and a heuristic estimation for the Jacobian matrix in a subspace with random basis indices. Our numerical results show that LMLS is robust and efficient, especially in comparison with solvers using traditional limited memory and standard quasi-Newton approximations.
Stability of health-related quality of life and morbidity burden from 18 months after diagnosis of prostate cancer: results of a UK-wide population-based outcome cohort
Authors: Mason Samantha J. , Downing Amy , Wilding Sarah , Hounsome Luke , Wright Penny , Watson Eila , Wagland Richard , Butcher Hugh , Kind Paul , Selby Peter , Gavin Anna , Glaser Adam W. 
Published: December 2021

Abstract
Objective
To evaluate the dynamic nature of self-reported health-related quality of life (HRQL) and morbidity burden in men diagnosed with prostate cancer, we performed a follow-up study of the Life After Prostate Cancer Diagnosis (LAPCD) study cohort 12 months after initial survey.

Methods
The LAPCD study collected information from 35,823 men across the UK who were 18–42 months post-diagnosis of prostate cancer. Men who were still alive 12 months later were resurveyed. Generic HRQL (EQ-5D-5L plus self-assessed health rating) and prostate cancer-specific outcomes (EPIC-26) were assessed. Treatment(s) received was self-reported. Previously defined clinically meaningful differences were used to evaluate changes in outcomes over time.

Results
A total of 28,450 men across all disease stages completed follow-up surveys (85.8% response). Of the 21,700 included in this study, 89.7% reported no additional treatments since the first survey. This group experienced stable urinary and bowel outcomes, with good function for most men at both time points. On-going poor (but stable) urinary issues were associated with previous surgery. Sexual function scores remained low (mean: 26.8/100). Self-assessed health ratings were stable over time. The largest declines in HRQL and functional outcomes were experienced by men reporting their first active treatment between surveys.

Discussion
The results suggest stability of HRQL and most specific morbidities by 18–42 months for men who report no further treatment in the subsequent 12 months. This is reassuring for those with good function and HRQL but re-enforces the need for early intervention and support for men who experience poor outcomes.
Pairing and sharing: The birth of the sense of us
Authors: Vincini Stefano 
Published: December 2021

AbstractThe goal of this paper is to show that a particular view of emotion sharing and a specific hypothesis on infant social perception strengthen each other. The view of emotion sharing is called “the straightforward view.” The hypothesis on infant social perception is called “the pairing account.” The straightforward view suggests that participants in emotion sharing undergo one and the same overarching emotion. The pairing account posits that infants perceive others’ embodied experiences as belonging to someone other than the self through a process of assimilation to, and accommodation of, their own embodied experience. The connection between the two theories lies in the domain-general process of association by similarity, which functions both in the individuation of a unitary emotion and in the interpretation of the sensory stimulus. By elaborating on this connection, the straightforward view becomes more solid from the cognitive-developmental standpoint and the pairing account expands its explanatory power. Since the straightforward view requires minimal forms of self- and other-awareness, the paper provides a characterization of the developmental origin of the sense of us, i.e., the experience of self and other as co-subjects of a shared emotional state.
Lead (Pb) exposure from outdoor air pollution: a potential risk factor for cervical intraepithelial neoplasia related to HPV genotypes
Authors: Zhang Ji , Nazeri Seyed Ali , Sohrabi Amir 
Published: December 2021

AbstractHuman papillomavirus genotypes (HPVs) have been confirmed to be the major cause of cervical intraepithelial neoplasia (CIN) that remains to be one of the most common women cancers around the world. It seems other risk factors have synergistic effects on cervical cancer occurrence including smoking, dietary pattern, sexual behavior, ethnicity, epigenetics, and environmental hazardous materials. Our study characterized the potential cancerous role of lead (Pb) as a common toxic environmental pollutant agent on CIN outcomes. Lead concentration was quantified using an atomic absorption spectrometer in liquid-based cytology specimens of 40 CIN-HPV positive subjects, 50 HPV infected non-cancerous cases, and 43 non-HPV infected/non-cancerous women. Pb concentration was 5.5 (4.7–6.4) μg/dL, 4.7 (4.2–8.7) μg/dL, and 4.7 (4.5–5.4) μg/dL in the CIN-HPV positive group, HPV infected non-cancerous cases, and non-HPV infected/non-cancerous group, respectively. The results showed higher Pb concentration is associated with higher risk for cervical malignancy in comparison with non-HPV infected/non-cancerous subjects, after controlling for age effect (aOR = 4.55, 95% CI: 1.55–15.07, P < 0.01). Our finding suggested a direct significant association between Pb accumulation and CIN existence. The consequences need to be further validated by including more relevant risk factors and controlling the confounders for better understating of Pb impact from outdoor air pollution on cervical cancer progression.
Regulating Polyamine Metabolism by miRNAs in Diabetic Cardiomyopathy
Authors: Kambis Tyler N. , Tofilau Hadassha M. N. , Gawargi Flobater I. , Chandra Surabhi , Mishra Paras K. 
Published: December 2021

Abstract

Purpose of Review
Insulin is at the heart of diabetes mellitus (DM). DM alters cardiac metabolism causing cardiomyopathy, ultimately leading to heart failure. Polyamines, organic compounds synthesized by cardiomyocytes, have an insulin-like activity and effect on glucose metabolism, making them metabolites of interest in the DM heart. This review sheds light on the disrupted microRNA network in the DM heart in relation to developing novel therapeutics targeting polyamine biosynthesis to prevent/mitigate diabetic cardiomyopathy.

Recent Findings
Polyamines prevent DM-induced upregulation of glucose and ketone body levels similar to insulin. Polyamines also enhance mitochondrial respiration and thereby regulate all major metabolic pathways. Non-coding microRNAs regulate a majority of the biological pathways in our body by modulating gene expression via mRNA degradation or translational repression. However, the role of miRNA in polyamine biosynthesis in the DM heart remains unclear.

Summary
This review discusses the regulation of polyamine synthesis and metabolism, and its impact on cardiac metabolism and circulating levels of glucose, insulin, and ketone bodies. We provide insights on potential roles of polyamines in diabetic cardiomyopathy and putative miRNAs that could regulate polyamine biosynthesis in the DM heart. Future studies will unravel the regulatory roles these miRNAs play in polyamine biosynthesis and will open new doors in the prevention/treatment of adverse cardiac remodeling in diabetic cardiomyopathy.
Trends of Selective Fetal Reduction and Selective Termination in Multiple Pregnancy, in England and Wales: a Cross-Sectional Study
Authors: Sam Sreya , Tai-MacArthur Sarah , Shangaris Panicos , Sankaran Srividhya 
Published: December 2021

AbstractSelective abortion was shown to be increasingly common in England and Wales over a 9-year period, occurring most frequently as twin to singleton reductions in the 1st trimester. We analysed the trends in selective abortion (SA) in multiple pregnancies in England and Wales between 2009 and 2018. This is a cross-sectional study looking at 1143 women with multiple pregnancies in England and Wales undergoing SA. There were a total of 1143 cases of SA between 2009 and 2018 in England and Wales, representing 0.07% of total abortions. There has been a steady increase in cases, from 90 in 2009 to 131 in 2018, with 82.3% justified under ground E of The Abortion Act 1967. The majority of SAs were carried out at 13–19 weeks gestation, and intracardiac injection of potassium chloride was the most prevalent method (75%). Twin to singleton reductions accounted for 59%, the most common form of SAs. Over half of all cases (59%) were performed in women aged 30–39 years, and 84% of all women were of White ethnicity. SA has been an option available for couples diagnosed with multiple pregnancy, especially when there are discordant anomalies. Although SA may decrease multiple pregnancy-related complications, preventative methods must be championed.
Consistent Construction of Evaluation Threshold Values and Rules for Heterogeneous Linguistic Input Information
Authors: Qian Gang , Zhang ErZi , Chen ZhiSong , Mesiar Radko , Yager Ronald R. , Jin LeSheng 
Published: December 2021

AbstractThis study firstly proposes a simpler method for evaluating one certain object’s quality with multiple criteria according to some preset evaluation threshold values that are real numbers. In real life, numerous individual valuations are provided with distributional linguistic input information and with multiple criteria, and thus they can become heterogeneous. Against this background, by using OWA weight functions we propose an extended setting and some methods to generate distributional evaluation threshold values which are suitable for the corresponding thresholds-based evaluation method. Some special definitions and formulations are also well provided with necessary analyses and comments. A numerical example of reservoir evaluation and effect are also illustrated.
An Intelligent Question Answering System of the Liao Dynasty Based on Knowledge Graph
Authors: Liu Shuang , Tan Nannan , Yang Hui , Lukač Niko 
Published: December 2021

AbstractThe Liao Dynasty was a minority regime established by the Khitan on the grasslands of northern China. To promote and spread the cultural knowledge of the Liao Dynasty, an intelligent question-and-answer system is constructed based on the knowledge graph in the historical and cultural field of the Liao Dynasty. In the traditional question answering system, the quality of answers was not high due to incomplete data and distinctive vocabulary. To solve this problem, a combination method of Liao Dynasty question-and-answer database and KB is proposed to realize knowledge graph question answering, and a joint model of Siamese LSTM and fusion MatchPyramid is proposed for semantic matching between questions in the question-and-answer database. With the joint model, it is easy to perform semantic matching by fusing sentence-level and word-level interactive features through LSTM and MatchPyramid. Furthermore, the question sentence with the same semantics as the user input question sentence is retrieved in the question-and-answer database, and the answer corresponding to the question sentence is returned as the result. The experimental results show that our proposed method has achieved relatively good performance in the historical domain of the Liao Dynasty and the open-domain knowledge graph, and improved the accuracy of question and answer.
A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System
Authors: Mallika C. , Selvamuthukumaran S. 
Published: December 2021

AbstractDiabetes is an extremely serious hazard to global health and its incidence is increasing vividly. In this paper, we develop an effective system to diagnose diabetes disease using a hybrid optimization-based Support Vector Machine (SVM).The proposed hybrid optimization technique integrates a Crow Search algorithm (CSA) and Binary Grey Wolf Optimizer (BGWO) for exploiting the full potential of SVM in the diabetes diagnosis system. The effectiveness of our proposed hybrid optimization-based SVM (hereafter called CS-BGWO-SVM) approach is carefully studied on the real-world databases such as UCIPima Indian standard dataset and the diabetes type dataset from the Data World repository. To evaluate the CS-BGWO-SVM technique, its performance is related to several state-of-the-arts approaches using SVM with respect to predictive accuracy, Intersection Over-Union (IoU), specificity, sensitivity, and the area under receiver operator characteristic curve (AUC). The outcomes of empirical analysis illustrate that CS-BGWO-SVM can be considered as a more efficient approach with outstanding classification accuracy. Furthermore, we perform the Wilcoxon statistical test to decide whether the proposed cohesive CS-BGWO-SVM approach offers a substantial enhancement in terms of performance measures or not. Consequently, we can conclude that CS-BGWO-SVM is the better diabetes diagnostic model as compared to modern diagnosis methods previously reported in the literature.
Network Intrusion Detection: An Analytical Assessment Using Deep Learning and State-of-the-Art Machine Learning Models
Authors: Al-Imran Md , Ripon Shamim H. 
Published: December 2021

AbstractThe internet connected devices are prone to cyber threats. Most of the companies are developing devices with built-in cyber threat protection mechanism or recommending prevention measure. But cyber threat is becoming harder to trace due to the availability of various tools and techniques to bypass the normal prevention measures. A data mining-based intrusion detection system can play a key role to handle such cyberattacks. This paper proposes a threefold approach to analyzing intrusion detection system. In the first phase, experiments have been conducted by applying SVM, Decision Tree, and KNN. In the second phase, Random Forest, and XGBoost are applied as lately they have been showing significant improved performance in supervised learning. Finally, deep learning techniques, namely, Feed Forward, LSTM, and Gated Recurrent Unit neural network are applied to conduct the experiment. Kyoto Honeypot Dataset is used for experimental purpose. The results show a significant improvement in IDS outperforming the state of the arts on this dataset. Such improvement strengthens the applicability proposed model in IDS.
Analysis of Edit Operations for Post-editing Systems
Authors: Kapusta Jozef , Benko Ľubomír , Munkova Dasa , Munk Michal 
Published: December 2021

AbstractPost-editing has become an important part not only of translation research but also in the global translation industry. While computer-aided translation tools, such as translation memories, are considered to be part of a translator's work, lately, machine translation (MT) systems have also been accepted by human translators. However, many human translators are still adopting the changes brought by translation technologies to the translation industry. This paper introduces a novel approach for seeking suitable pairs of n-grams when recommending n-grams (corresponding n-grams between MT and post-edited MT) based on the type of text (manual or administrative) and MT system used for machine translation. A tool that recommends and speeds up the correction of MT was developed to help the post-editors with their work. It is based on the analysis of words with the same lemmas and analysis of n-gram recommendations. These recommendations are extracted from sequence patterns of the mismatched words (MisMatch) between MT output and post-edited MT output. The paper aims to show the usage of morphological analysis for recommending the post-edit operations. It describes the usage of mismatched words in the n-gram recommendations for the post-edited MT output. The contribution consists of the methodology for seeking suitable pairs of words, n-grams and additionally the importance of taking into account metadata (the type of the text and/or style and MT system) when recommending post-edited operations.
Research on Multi-label Text Classification Method Based on tALBERT-CNN
Authors: Liu Wenfu , Pang Jianmin , Li Nan , Zhou Xin , Yue Feng 
Published: December 2021

AbstractSingle-label classification technology has difficulty meeting the needs of text classification, and multi-label text classification has become an important research issue in natural language processing (NLP). Extracting semantic features from different levels and granularities of text is a basic and key task in multi-label text classification research. A topic model is an effective method for the automatic organization and induction of text information. It can reveal the latent semantics of documents and analyze the topics contained in massive information. Therefore, this paper proposes a multi-label text classification method based on tALBERT-CNN: an LDA topic model and ALBERT model are used to obtain the topic vector and semantic context vector of each word (document), a certain fusion mechanism is adopted to obtain in-depth topic and semantic representations of the document, and the multi-label features of the text are extracted through the TextCNN model to train a multi-label classifier. The experimental results obtained on standard datasets show that the proposed method can extract multi-label features from documents, and its performance is better than that of the existing state-of-the-art multi-label text classification algorithms.
On the Higher-Order Inhomogeneous Heisenberg Supermagnetic Models
Authors: Han Rong , Sun Haichao , Jiang Nana , Yan Zhaowen 
Published: December 2021

AbstractThis paper is concerned with the construction of the fifth-order inhomogeneous Heisenberg supermagnetic models. Moreover, the Lax representations of the models are presented. By means of the gauge transformation, we establish their gauge equivalent equations with different quadratic constraints, i.e., the super and fermionic fifth-order inhomogeneous nonlinear Schrödinger equations, respectively. In addition, we investigate their Lax representations and Bäcklund transformations from which the solutions of the super integrable systems have been discussed.
Turing Patterns for a Nonlocal Lotka–Volterra Cooperative System
Authors: Mi Shao-Yue , Han Bang-Sheng , Zhao Yu-Tong 
Published: December 2021

AbstractThis paper is devoted to investigating the pattern dynamics of Lotka–Volterra cooperative system with nonlocal effect and finding some new phenomena. Firstly, by discussing the Turing bifurcation, we build the conditions of Turing instability, which indicates the emergence of Turing patterns in this system. Then, by using multiple scale analysis, we obtain the amplitude equations about different Turing patterns. Furthermore, all possible pattern structures of the model are obtained through some transformation and stability analysis. Finally, two new patterns of the system are given by numerical simulation.
Nonlinear Model of Coastal Flooding by a Highly Turbulent Tsunami
Authors: Arsen’yev Sergey A. , Eppelbaum Lev V. 
Published: December 2021

AbstractWhen a tsunami wave comes from ocean and propagates through the shelf, it is very important to predict several dangerous factors: (a) maximum flooding of the coast, (b) tsunami wave height on the coast, (c) velocity of the tsunami front propagation through the coast, and (d) time of tsunami arriving at a given point in the coast and around it. In this study we study the separate case where the angle of inclination α of the seacoast is equal to zero. A linear solution of this problem is unsatisfactory since it gives an infinite rate of the coastal inundation that means the coast is flooded instantly and without a frontal boundary. In this study, we propose a principally new exact analytical solution of this problem based on nonlinear theory for the reliable recognizing these essential tsunami characteristics. The obtained formulas indicate that the tsunami wave can be stopped (or very strongly eliminated) in the shelf zone until approaching the shoreline. For this aim, it is necessary to artificially raising several dozens of bottom protrusions to the level of the calm water.
KdV Equation Model in Open Cylindrical Channel under Precession
Authors: Alshoufi Hajar 
Published: December 2021

AbstractA new model for Korteweg and de-Vries equation (KdV) is derived. The system under study is an open channel consisting of two concentric cylinders, rotating about their vertical axis, which is tilted by slope $$\tau$$
τ
from the inertial vertical $$z$$
z
, in uniform rate $${\Omega }_{1}=\tau \Omega$$

Ω
1

=
τ
Ω

, and the whole tank is elevated over other table rotating at rate $$\Omega$$
Ω
. Under these conditions, a set of Kelvin waves is formed on the free surface depending on the angle of tilt, characterized by the slope $$\tau$$
τ
, volume of water, and rotation rate. The resonant mode in the system appears in the form of a single Kelvin solitary wave, whose amplitude satisfies the Korteweg-de Vries equation with forced term. The equation was derived following classical perturbation methods, the additional term made the equation a non-integrable one, that cannot be solved without the help of numerical methods. Invoking the simple finite difference scheme method, it was found that the numerical results are in a good agreement with the experiment.