bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resistance Distances In Simplicial Networks
Authors: Zhu Mingzhe , Xu Wanyue , Zhang Zhongzhi , Kan Haibin , Chen Guanrong 
Published: April 2022

Abstract
It is well known that in many real networks, such as brain networks and scientific collaboration networks, there exist higher order nonpairwise relations among nodes, i.e. interactions between more than two nodes at a time. This simplicial structure can be described by simplicial complexes and has an important effect on topological and dynamical properties of networks involving such group interactions. In this paper, we study analytically resistance distances in iteratively growing networks with higher order interactions characterized by the simplicial structure that is controlled by a parameter $q$. We derive exact formulas for interesting quantities about resistance distances, including Kirchhoff index, additive degree-Kirchhoff index, multiplicative degree-Kirchhoff index, as well as average resistance distance, which have found applications in various areas elsewhere. We show that the average resistance distance tends to a $q$-dependent constant, indicating the impact of simplicial organization on the structural robustness measured by average resistance distance.
3D Flattering Amplified Neural Network-Based Segmentation of Amygdala and Hippocampus
Authors: Smitha J C , Jane Ambily , Chandran Lekshmi 
Published: April 2022

Abstract
Recent emergence in deep learning resulted in significant improvement in the segmentation accuracy of sub cortical brain structures like hippocampus and amygdala. The traditional methods of segmentation cannot produce an ideal segmentation result that exhibits issues like redundant computations, inconsistencies, coefficient variations and motion artifacts. Therefore, in this paper, an improved 3D Flatteringly Amplified Neural Network model for biomedical imaging is efficiently proposed, which can make full use of the 3D spatial information of MRI image itself to overcome the inconsistency of segmented images along with equalizing the coefficient variation of tiny region of brain image segmentation. Also while equalizing the coefficient, certain significant minute details are lost due to motion artifacts hence, the robust Amyg-Hippo Seg algorithm has been introducing that extracts the features through deep learning, and achieve high-precision segmentation, it reduced the computational complexity without neglecting minute features. In addition, the Daytona dropout function provides uncertainty information and reduces over-fitting problems. The outcome of the proposed work efficiently segments the most significant regions of hippocampus and amygdala with 97.4% accuracy.
Intelligent Forecast of Stock Markets to Handle COVID-19 Economic Crisis by Modified Generative Adversarial Networks
Authors: Sornavalli G , Angelin Gladston , Khanna Nehemiah H 
Published: April 2022

Abstract
Stock markets have voluminous data and are subjected to uncertainty. The coronavirus disease of 2019 (COVID-19) pandemic has hit the stock markets and the trends of stock markets have accelerated share prices of few companies and has also brought freefall to certain companies. This factor highlights the importance of technical analysis of the stock markets over fundamental analysis. So, the proposed robust model for financial forecasting is built based on the technical indicators and the fake price data generated over a period of time from the stock dataset by a novel architecture of modified generative adversarial network, which uses a dense recurrent neural network as the generator and a dense spectrally normalized convolutional neural network as the discriminator. The hyperparameters used in the network model follow the two-time-scale-update rule and they are tuned by using the Bayesian optimization technique. The feature importance of the technical indicators in predicting the performance by the stock market is enhanced by the XGBoost algorithm. The generative adversarial networks (GAN) used for forecasting in the previous works suffer from problems like mode collapse and non-convergence. So, the proposed work concentrates on building a GAN model, which is stable, robust and converges to Nash equilibrium. The generated GAN model is applied on stock data from the major 100 companies of the S&P 500 stock for a period of 20 years. The modified GAN model predicts prices precise ~99 percentage, which maximizes the stock returns. The proposed modified GAN model outperforms the baseline GAN model and other state of the art approaches of forecasting on comparison.
The Diagnosability of Interconnection Networks with Missing Edges and Broken-Down Nodes Under the PMC and MM* Models
Authors: Guo Chen , Liu Qiuming , Xiao Zhifang , Peng Shuo 
Published: April 2022

Abstract
Diagnosability is often considered as an important factor for measuring the self-diagnostic ability of network systems. However, classic system-level diagnosis focuses only on processor faults and ignores the objective reality of communication faults. Under real circumstances, missing edges and node failures usually occur simultaneously in multiprocessor systems (called hybrid fault circumstances). Therefore, it is important to study the diagnosability of multiprocessor systems under hybrid fault circumstances. In this paper, we propose several diagnosabilities of interconnection networks with missing edges and faulty nodes. By exploring some important relationships between diagnosability and the minimum degree of a network under hybrid fault circumstances, we present and prove the diagnosability of several classic interconnection networks, including BC (bijective connection) networks, star graphs, folded hypercubes, exchanged hypercubes, exchanged crossed cubes, k-ary n-cubes, bubble-sort star graphs and balanced hypercubes, with missing edges and broken-down nodes under the PMC (Preparata, Metze and Chien) and MM* (Maeng and Malek) models.
Automated Computer-Aided Diagnosis of Diabetic Retinopathy Based on Segmentation and Classification using K-nearest neighbor algorithm in retinal images
Authors: Kaur Jaspreet , Kaur Prabhpreet 
Published: April 2022

AbstractDiabetic retinopathy (DR) is an eye oddity where the human retina is afflicted because of the ever-increasing quantity of insulin in the blood. It leads to the loss of sight. Preliminary diagnosis of DR assists to improve to inhibit future injury. Proper DR screening has been recognized as an economical way to accumulate health services. Automated retinal analysis become known as the most significant screening approach for primitive DR diagnosis, which leads to diminishing the workload related to manual screening and also, cost-effective and less time-consuming efforts. In the proposed work, the preprocessing, removal of applicant lesion pixels, and formulation of feature set have been examined which is fully appropriate for the classification task. In preprocessing approach, the framework removes the unwanted pixels, eliminates the optic disc, and extraction of the blood vessels from the retinal images. Morphological operations are applied to extract the boundaries of the blood vessels and then 2D discrete wavelet decomposition is applied to estimate the horizontal, vertical and diagonal coefficients. The candidate lesion pixels i.e. dark and bright DR pixels are detected using an adaptive threshold that uses local statistical, geometrical, and location-based characteristics of the background image. The extracted feature set is processed using a K-nearest neighbor (KNN) classifier with 80% of training data and 20% of testing data to diagnose the severity level of the disease. The proposed scheme is evaluated by the DIARETDB1 benchmark dataset with the performance parameters, i.e. 95% of accuracy, 92.6% of sensitivity and 87.56% specificity achieved with less computation time required.
Exploring the Relationship Between Bariatric Surgery and Inflammatory Bowel Disease: A Systematic Review
Authors: Wise Journey , Plescia Trevor , Cummings Bethany Paige , Lyo Victoria 
Published: April 2022

Abstract

Background
Obesity affects over 40% of Americans. Bariatric surgery is an increasingly popular and well-studied method to achieve weight loss, improve metabolic homeostasis, and resolve obesity-related comorbid conditions. While the impact of bariatric surgery on weight loss and metabolic health has been extensively studied, there is an increasing body of literature characterizing the impact of bariatric surgery on gastrointestinal health and inflammation. Inflammatory bowel disease (IBD) leads to inflammation in both the small and large intestine, and leads to significant patient morbidity. Similar to obesity, the incidence of IBD is also rising. Patients with IBD and obesity may seek bariatric surgery. The impact of bariatric surgery on IBD is not well understood, but critical to understand for optimal patient care. Herein, we review the currently available literature on the impact of bariatric surgery on IBD including common trends, discrepancies in findings, and remaining knowledge gaps in need of further study.

Methods
A systematic review of the PubMed/MEDLINE database using PRISMA guidelines was performed.

Results
We identified 12 manuscripts discussing de novo IBD after bariatric surgery and 16 studying bariatric surgery in patients with pre-existing IBD. Overall, bariatric surgery appears to be safe in patients with pre-existing IBD but may increase the risk of developing de novo IBD.

Conclusions
Further research into optimal surgical approaches, patient selection, and mechanisms on how bariatric surgery impacts IBD is needed.
Neutrophil inhibition improves acute inflammation in a murine model of viral myocarditis
Authors: Carai Paolo , González Laura Florit , Van Bruggen Stijn , Spalart Valerie , De Giorgio Daria , Geuens Nadéche , Martinod Kimberly , Jones Elizabeth Anne Vincent , Heymans Stephane 
Published: April 2022

Abstract

Aims
Viral myocarditis (VM) is an inflammatory pathology of the myocardium triggered by a viral infection that may cause sudden death or heart failure (HF), especially in the younger population. Current treatments only stabilize and improve cardiac function without resolving the underlying inflammatory cause. The factors that induce VM to progress to HF are still uncertain, but neutrophils have been increasingly associated with the negative evolution of cardiac pathologies. The present study investigates the contribution of neutrophils to VM disease progression in different ways.

Methods and results
In a coxsackievirus B3- (CVB3) induced mouse model of VM, neutrophils and neutrophil extracellular traps (NETs) were prominent in the acute phase of VM as revealed by enzyme-linked immunosorbent assay analysis and immunostaining. Anti-Ly6G-mediated neutrophil blockade starting at model induction decreased cardiac necrosis and leucocyte infiltration, preventing monocyte and Ly6CHigh pro-inflammatory macrophage recruitment. Furthermore, genetic peptidylarginine deiminase 4-dependent NET blockade reduced cardiac damage and leucocyte recruitment, significantly decreasing cardiac monocyte and macrophage presence. Depleting neutrophils with anti-Ly6G antibodies at 7 days post-infection, after the acute phase, did not decrease cardiac inflammation.

Conclusion
Collectively, these results indicate that the repression of neutrophils and the related NET response in the acute phase of VM improves the pathological phenotype by reducing cardiac inflammation.
Long-term trends in the epidemiology of cardiovascular diseases in the UK: insights from the British Heart Foundation statistical compendium
Authors: Cheema Katherine Margaret , Dicks Ed , Pearson Jeremy , Samani Nilesh J 
Published: April 2022

Abstract
The British Heart Foundation’s (BHF) annual statistical compendium is a comprehensive source of accessible epidemiological data in relation to cardiovascular disease (CVD) in the UK. Using datasets with multiple years of data from the compendium we have analysed trends in mortality, morbidity, and treatment for CVD within the UK. CVD mortality in the UK has consistently declined over recent decades, from 1045 deaths per 100 000 in 1969, shortly after the BHF was founded, to 255 per 100 000 in 2019. Despite this remarkable improvement, inequalities in CVD mortality persist in the UK nations, for example in 2019 the death rate in Scotland was 326 deaths per 100 000 compared with 246 per 100 000 in England. Improvements in CVD mortality have been paralleled by increased use of primary prevention medications (anti-hypertensives and statins) and interventional procedures. In recent years, progress in mortality outcomes has stalled, probably due to a combination of factors including a rise in risk factors such as obesity and diabetes. In terms of morbidity, CVD remains a significant burden in the UK, accounting for at least 1.18 million hospital admissions and reflects the enormous economic burden of CVD, estimated at £19bn in the UK. Our results highlight the importance of accessible and comprehensive statistics in relation to the burden of CVD and the value of the BHF’s annual compendium in drawing out conclusions and opportunities for future research. One key area is to improve the data on which estimation of prevalence is based. There is also a need for ongoing work to better understand the root causes of disparity between socio-economic groups in relation to CVD. One important way to address this will be to improve the consistency of reporting of CVD health data across all nations of the UK. Understanding the causes will inform UK healthcare planning in addition to providing analytical insights that will be applicable in other countries.
Psychometric Characteristics of the Visual Communication and Sign Language Checklist
Authors: Allen Thomas E , Morere Donna A 
Published: April 2022

Abstract
Since its publication in 2013, the Visual Communication and Sign Language (VCSL) Checklist has been widely utilized to assess the development of early American Sign Language skills of deaf children from birth to age 5. However, little research has been published using the results of VCSL assessments. Notably, no psychometric analyses have been conducted to verify the validity of the VCSL in a population whose characteristics are different from those of the small sample of native signing children from whom the published norms were created. The current paper, using data from the online version of the VCSL (VCSL:O), addresses this shortcoming. Ratings of the 114 VCSL items from 562 evaluations were analyzed using a partial-credit Rasch model. Results indicate that the underlying skill across the age range comprises an adequate single dimension. Within the items’ age groupings, however, the dimensionality is not so clear. Item ordering, as well as item fit, is explored in detail. In addition, the paper reports the benefits of using the resulting Rasch scale scores, which, unlike the published scoring strategy that focuses on basal and ceiling performance, makes use of the ratings of partial credit, or emerging, skills. Strategies for revising the VCSL are recommended.
A Narrative Systematic Review and Categorisation of Outcomes in Inflammatory Bowel Disease to Inform a Core Outcome Set for Real-world Evidence
Authors: Wong Charlotte , van Oostrom Joep , Bossuyt Peter , Pittet Valerie , Hanzel Jurij , Samaan Mark , Tripathi Monika , Czuber-Dochan Wladyslawa , Burisch Johan , Leone Salvatore , Saldaña Roberto , Baert Filip , Kopylov Uri , Jaghult Susanna , Adamina Michel , Gecse Krisztina , Arebi Naila 
Published: April 2022

Abstract

Background
Heterogeneity exists in reported outcomes and outcome measurement instruments [OMI] from observational studies. A core outcome set [COS] for observational and real-world evidence [RWE] in inflammatory bowel disease [IBD] will facilitate pooling large datasets. This systematic review describes and classifies clinical and patient-reported outcomes, for COS development.

Methods
The systematic review of MEDLINE, EMBASE, and CINAHL databases identified observational studies published between 2000 and 2021 using the population exposure outcome [PEO] framework. Studies meeting eligibility criteria were included. After titles and abstracts screening, full-text articles were extracted by two independent reviewers. Primary and secondary outcomes with corresponding OMI were extracted and categorised in accordance with OMERACT Filter 2.1 framework. The frequency of outcomes and OMIs are described.

Results
From 5854 studies, 315 were included: 129 [41%] Crohn’s disease [CD], 60 [19%] ulcerative colitis [UC], and 126 [40%] inflammatory bowel disease [IBD] studies with 600 552 participants. Totals of 1632 outcomes and 1929 OMI were extracted mainly from medical therapy [181; 72%], surgical [34; 11%], and endoscopic [6; 2%] studies. Clinical and medical therapy-related safety were frequent outcome domains recorded in 194 and 100 studies. Medical therapy-related adverse events [n = 74] and need for surgery [n = 71] were the commonest outcomes. The most frequently reported OMI were patient or event numbers [n = 914], Harvey-Bradshaw Index [n = 45], and Montreal classification [n = 42].

Conclusions
There is substantial variability in outcomes reporting and OMI types. Categorised outcomes and OMI from this review will inform a Delphi consensus on a COS for future RWE in IBD. Data collection standardisation may enhance the quality of RWE applied to decision-making.
Predation and Climate Limit Establishment Success of the Kyushu Strain of the Biological Control AgentAphalara itadori(Hemiptera: Aphalaridae) in the Northeastern United States
Authors: Andersen Jeremy C , Elkinton Joseph S 
Published: April 2022

AbstractSpecies of knotweeds, Reynoutria spp. Houtt. (Caryophyllales: Polygonaceae), including Japanese knotweed (R. japonica Houtt.), are among the most invasive and ecologically destructive plant species introduced to North America and Europe. The Kyushu strain of the psyllid Aphalara itadori Shinji (Hemiptera: Aphalaridae) has been approved as a biological control agent for release against Japanese knotweed in the United Kingdom, Canada, and the United States. However, recent reports from Canada suggest that both biotic and abiotic factors may limit its establishment. Therefore, we examined the potential role of predation by comparing open- versus closed-sleeve treatments, and climate mis-matches by collecting temperature data from release sites and performing climate suitability analyses using MaxEnt. Our results indicated that populations of the Kyushu strain could only be maintained in the field in closed-sleeve treatments, suggesting that predation is likely limiting the establishment success of this strain. In addition, we noted that daily maximum temperatures at our field sites might exceed documented developmental thresholds for this strain, and that MaxEnt species distribution modeling indicates no climate similarities between locations in eastern North America and Kyushu. Combined with previous results, our study suggests that the establishment of the Kyushu strain of A. itadori as a biological control agent for Japanese knotweed may be limited in eastern North America. We suggest that one strategy to increase the probability of establishment of the Kyushu strain could be to increase the number of release sites in an effort to find a more optimal niche with predator-free space.
Increasing Body Sizes in Anomala expansa expansa (Coleoptera: Scarabaeidae) Populations in Response to Rising Temperatures Over Time
Authors: Maher Ian M , Shelomi Matan 
Published: April 2022

Abstract
Many insects have been studied over wide geographical areas to determine whether they follow Bergmann’s Rule, which predicts that animal clades or populations should have smaller body sizes in warmer climates. While this ecogeographic rule is well supported in mammals and birds, insect latitudinal sizes can show Bergmann, converse Bergmann, or no size clines at all. Museum collections are typical sources of data for insect clines, and long-term collections should reflect rising global temperatures and shifting climates, possibly producing temporal size clines along with any geographical clines. We hypothesize that insects with Bergmann clines geographically will show Bergmann-like clines temporally as well, and that the converse and inverse of this rule are also true. By looking at museum samples going back a century, we tested whether Anomala expansa expansa (Bates, 1866), a species of Scarabaeidae beetle common in lowland Taiwan, was experiencing long-term changes in body size in response to rising temperatures. We found that overall, the size of these beetles increased over time. Within Taipei populations, this increase was correlated with rising average yearly temperatures. The impact of this pest species’ rising size with time will need to be monitored, and temporal size clines in other pests need to be investigated.
Incidence and predictors of mortality after an electrical storm in the ICU
Authors: Ninni Sandro , Layec Jeremy , Brigadeau François , Behal Hélène , Labreuche Julien , Klein Cédric , Schurtz Guillaume , Potelle Charlotte , Coisne Augustin , Lemesle Gilles , Lamblin Nicolas , Klug Didier , Lacroix Dominique 
Published: April 2022

Abstract

Aims
For assessing predictors of early mortality following hospitalization for electrical storm (ES), only limited data are available. The purpose of this study was to assess the incidence and predictors of early mortality following hospitalization in the intensive care unit (ICU) for ES in a large retrospective study.

Methods and results
In this retrospective study, we included all patients who were hospitalized for ES from July 2015 to May 2020 in our tertiary centre. A total of 253 patients were included. The median age was 66 [56; 73], and 64% had ischemic cardiomyopathy. A total of 37% of patients presented hemodynamic instability requiring catecholamine at admission. A total of 17% of patients presented an acute reversible cause for ES. The one-year mortality was 34% (95% CI, 30–43%), mostly driven by heart failure (HF). The multivariable Cox's regression model identified age, left ventricular ejection fraction, right ventricle dysfunction, haemoglobin level as independent predictors of one-year mortality. The use of catecholamine at admission was identified as the only variable related to the initial management of ES associated with an increased 30-day mortality risk (HR: 7.95 (95%CI, 3.18–19.85).

Conclusion
In patients admitted for ES in ICU, the one-year mortality remains high and mostly driven by HF. The use of catecholamine at admission is associated with a seven-fold risk for mortality within 30 days. In such patients, the potential use of VT ablation can be questioned and a careful action plan regarding invasive HF-related therapy could be considered.