bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing Patient-Specific Mechanical Properties of Aortic Wall and Peri-Aortic Structures From In Vivo DENSE Magnetic Resonance Imaging Using an Inverse Finite Element Method and Elastic Foundation Boundary Conditions
Authors: Bracamonte Johane H. , Wilson John S. , Soares Joao S. 
Published: July 2020

Abstract
The establishment of in vivo, noninvasive patient-specific, and regionally resolved techniques to quantify aortic properties is key to improving clinical risk assessment and scientific understanding of vascular growth and remodeling. A promising and novel technique to reach this goal is an inverse finite element method (FEM) approach that utilizes magnetic resonance imaging (MRI)-derived displacement fields from displacement encoding with stimulated echoes (DENSE). Previous studies using DENSE MRI suggested that the infrarenal abdominal aorta (IAA) deforms heterogeneously during the cardiac cycle. We hypothesize that this heterogeneity is driven in healthy aortas by regional adventitial tethering and interaction with perivascular tissues, which can be modeled with elastic foundation boundary conditions (EFBCs) using a collection of radially oriented springs with varying stiffness with circumferential distribution. Nine healthy IAAs were modeled using previously acquired patient-specific imaging and displacement fields from steady-state free procession (SSFP) and DENSE MRI, followed by assessment of aortic wall properties and heterogeneous EFBC parameters using inverse FEM. In contrast to traction-free boundary condition, prescription of EFBC reduced the nodal displacement error by 60% and reproduced the DENSE-derived heterogeneous strain distribution. Estimated aortic wall properties were in reasonable agreement with previously reported experimental biaxial testing data. The distribution of normalized EFBC stiffness was consistent among all patients and spatially correlated to standard peri-aortic anatomical features, suggesting that EFBC could be generalized for human adults with normal anatomy. This approach is computationally inexpensive, making it ideal for clinical research and future incorporation into cardiovascular fluid–structure analyses.
Randomised, multicentre prospective trial of transarterial chemoembolisation (TACE) plus sorafenib as compared with TACE alone in patients with hepatocellular carcinoma: TACTICS trial
Authors: Kudo Masatoshi , Ueshima Kazuomi , Ikeda Masafumi , Torimura Takuji , Tanabe Nobukazu , Aikata Hiroshi , Izumi Namiki , Yamasaki Takahiro , Nojiri Shunsuke , Hino Keisuke , Tsumura Hidetaka , Kuzuya Teiji , Isoda Norio , Yasui Kohichiroh , Aino Hajime , Ido Akio , Kawabe Naoto , Nakao Kazuhiko , Wada Yoshiyuki , Yokosuka Osamu , Yoshimura Kenichi , Okusaka Takuji , Furuse Junji , Kokudo Norihiro , Okita Kiwamu , Johnson Philip James , Arai Yasuaki 
Published: July 2020

ObjectiveThis trial compared the efficacy and safety of transarterial chemoembolisation (TACE) plus sorafenib with TACE alone using a newly established TACE-specific endpoint and pre-treatment of sorafenib before initial TACE.DesignPatients with unresectable hepatocellular carcinoma (HCC) were randomised to TACE plus sorafenib (n=80) or TACE alone (n=76). Patients in the combination group received sorafenib 400 mg once daily for 2–3 weeks before TACE, followed by 800 mg once daily during on-demand conventional TACE sessions until time to untreatable (unTACEable) progression (TTUP), defined as untreatable tumour progression, transient deterioration to Child-Pugh C or appearance of vascular invasion/extrahepatic spread. Co-primary endpoints were progression-free survival (PFS), which is not a conventional one but defined as TTUP, or time to any cause of death plus overall survival (OS). Multiplicity was adjusted by gatekeeping hierarchical testing.ResultsMedian PFS was significantly longer in the TACE plus sorafenib than in the TACE alone group (25.2 vs 13.5 months; p=0.006). OS was not analysed because only 73.6% of OS events were reached. Median TTUP (26.7 vs 20.6 months; p=0.02) was also significantly longer in the TACE plus sorafenib group. OS at 1 year and 2 years in TACE plus sorafenib group and TACE alone group were 96.2% and 82.7% and 77.2% and 64.6%, respectively. There were no unexpected toxicities.ConclusionTACE plus sorafenib significantly improved PFS over TACE alone in patients with unresectable HCC. Adverse events were consistent with those of previous TACE combination trials.Trial registration numberNCT01217034.
Disseminated phaeohyphomycosis in a dog with seizures and suspected hyperadrenocorticism in the United Kingdom
Authors: Alonzi Consuelo , Ellis J , Corbetta D , Grau‐Roma L , Valls F 
Published: July 2020

SUMMARYA twelve‐year‐old female entire Lurcher‐cross dog presented for investigation of an acute onset of cluster seizures and elevation of the liver enzymes. Physical examination was unremarkable; neurological examination was suggestive of diffuse forebrain involvement. Abdominal ultrasound documented a hyperechoic hepatic parenchyma, bilateral adrenomegaly and a splenic irregular hypoechoic nodule. Splenic cytology revealed inflammation and numerous fungal elements. Low dose dexamethasone suppression test suggested the diagnosis of hyperadrenocorticism. Magnetic resonance (MRI) of the brain revealed multifocal cerebral lesions. Anti‐fungal therapy was started, but no clinical response was seen and euthanasia was elected. Postmortem examination confirmed the diagnosis of systemic mycosis with involvement of the brain and liver. Systemic mycoses are uncommonly reported in the UK, but this case report raises the importance of considering fungal encephalitis as a differential diagnosis in dogs with seizures and in particular in dogs with hyperadrenocorticism, as this endocrinopathy may act as a predisposing factor.
Qanuq ukua kanguit sunialiqpitigu?(What should we do with all of these geese?) Collaborative research to support wildlife co-management and Inuit self-determination
Authors: Henri Dominique A. , Carter Natalie A. , Irkok Aupaa , Nipisar Shelton , Emiktaut Lenny , Saviakjuk Bobbie , Salliq Project Management Committee  , Arviat Project Management Committee  , Ljubicic Gita J. , Smith Paul A. , Johnston Vicky 
Published: July 2020

Inuit living in Nunavut have harvested light geese and lived near goose colonies for generations. Inuit knowledge includes important information about light goose ecology and management that can inform co-management and enhance scientific research and monitoring. Since the 1970s, populations of light geese (Snow and Ross’ Geese; kanguit and kangunnait in Inuktut; Chen caerulescens (Linnaeus, 1758) and Chen rossii (Cassin, 1861)) have experienced significant increases in abundance which led to habitat alteration in some portions of the central and eastern Canadian Arctic. In response to concerns expressed by Inuit and wildlife managers about light goose abundance, we conducted a collaborative research project in Arviat and Salliq (Coral Harbour), Nunavut, aiming to mobilize and document Inuit knowledge about light goose ecology and management in the Kivalliq region. Here, we explore the potential of collaborative research for mobilizing Inuit knowledge to support informed and inclusive decision-making about wildlife resources. First, we describe the participatory research methods employed to explore Inuit-identified management recommendations for light geese and engage co-management partners and research contributors to explore select management options. Then, we present these light goose management recommendations and options. Lastly, we discuss opportunities and challenges around the use of collaborative research to support wildlife co-management and Inuit self-determination.Inuit nunaqaqtut Nunavuumi angunasuksimalirmata kanguqpangnik kangurniglu nunaqarvingita sanianni araagunik unuqtunnik. Inuit qaujimaningat ilaqaqpuq aturnilingnik kanguit niqinginnik mianirijauninginniklu tusaumatitaulutik qaujisarningit mianiriyaunigillu. Taimangat 1970s atuqtilugit, kanguit unirningit (kanguit amma kanguaryuit Inuktut; Chen caerulescens (Linnaeus, 1758) amma Chen rossii (Cassin, 1861)) ayunganaqtukut pisimangmata unulialiqlutik amma niqiqatiarungnauqlutik Kanataup uqiuktaqtunngani. Tamana piblugu Inuit uumayuliriyillu isumaalulirmata kanguit unulualirninginnik, taima qaujisarnirmik pigialauqpugut Arvianni and Sallim (Coral Harbour), Nunavuumi, aulataulutik amma qaujisagaulutik Inuit kaujimajagit kangurnik Kivallirmi. Tavani atuqtuuluaqtunik qaujisarnirmut mianiqsinirmullu pitaqaqpuq Inuit nagminiq isumaliurlutik nirjutinut atugaksanullu. Sivullirmik, qaujisarniup qanuinninga isumagilugu kanguit mianirijauninginut. Amma suli, uqausirilirlugu kanguit mianirijauningat atugaujuuluaqtullu. Kingulirmik, uqausirilugu atuinnaujut amma ajurutaujut qaujisarniup iluanni nirjutinik amma Inuit nagminiq aulatuulualirninginnik.
Naturally reductive homogeneous (α,β) spaces
Authors: Bahmandoust Parisa , Latifi Dariush 
Published: July 2020

In this paper, we study naturally reductive [Formula: see text]-metrics on homogeneous manifolds. We show that naturally reductive [Formula: see text]-metrics arise only when [Formula: see text] is naturally reductive and some conditions on [Formula: see text] is satisfied. We give an explicit formula for the flag curvature of naturally reductive [Formula: see text]metrics which improves the flag curvature formula of naturally reductive Randers metrics given in [D. Latifi, Naturally reductive homogeneous Randers spaces, J. Geom. Phys. 60 (2010) 1968–1973]. As a special case, we give an explicit formula for the flag curvature of bi-invariant [Formula: see text]-metrics on Lie groups.
Enhancing Oxygen Reduction Reaction Activity of α-MnO2 Nanowires Through Ag Doping
Authors: Wu Zixu , Li Guangxing , Liao Qin , Ding Ruida , Zuo Xuze , Liu Qilin , He Hao , Chen Shuguang 
Published: July 2020

Enhancing the catalytic activity of manganese oxide in oxygen reduction reaction (ORR) is a key issue for its large-scale application in metal-air fuel cells. Ag-doped [Formula: see text]-MnO2 nanowires without Ag or Ag2O have been successfully synthesized via a facile hydrothermal method, and the changes in both the structure and electrochemical catalytic performances after Ag doping are investigated. Compared with the pristine [Formula: see text]-MnO2, the as-prepared Ag-doped MnO2 exhibits a significantly enhanced catalytic activity in both ORR and Mg-air fuel cell application. With Ag/Mn ratio of 1:25, Ag-doped MnO2 exhibits a typical 4e-reaction pathway and presents a 163 mV higher half-wave potential than that of the pristine [Formula: see text]-MnO2. Furthermore, it demonstrates a power density of 75.1[Formula: see text]mW[Formula: see text]cm[Formula: see text] at current density of 134.5[Formula: see text]mA[Formula: see text]cm[Formula: see text] in the Mg-air fuel cells. The enhanced ORR performances are considered to be contributed from the activation of surface lattice oxygen, the improvement in conductivity and the increase in oxygen vacancies of [Formula: see text]-MnO2. These findings provide new understanding for developing high-performance manganese oxide catalysts.
Polylogarithmic Approximation Algorithms for Weighted-ℱ-deletion Problems
Authors: Agrawal Akanksha , Lokshtanov Daniel , Misra Pranabendu , Saurabh Saket , Zehavi Meirav 
Published: July 2020

For a family of graphs ℱ, the W<scp;>eighted</scp;> ℱ V<scp;>ertex</scp;> D<scp;>eletion</scp;> problem, is defined as follows: given an
n
-vertex undirected graph
G
and a weight function
w
:
V
(
G
)࢐ ℝ, find a minimum weight subset
S
⊆
V
(
G
) such that
G
-
S
belongs to ℱ. We devise a recursive scheme to obtain O(log
O(1)
n
)-approximation algorithms for such problems, building upon the classical technique of finding
balanced separators
. We obtain the first O(log
O(1)
n
)-approximation algorithms for the following problems.

• Let
F
be a finite set of graphs containing a planar graph, and ℱ=
G
(
F
) be the maximal family of graphs such that every graph
H
∈
G
(
F
) excludes all graphs in
F
as minors. The vertex deletion problem corresponding to ℱ=
G
(
F
) is the W
eighted
P
lanar
F
-M
inor
-F
ree
D
eletion
(WP
F
-MFD) problem. We give a randomized and a deterministic approximation algorithms for WP
F
-MFD with ratios O(log
1.5
n
) and O(log
2
n
), respectively. Prior to our work, a randomized constant factor approximation algorithm for the
unweighted
version was known [FOCS 2012]. After our work, a deterministic constant factor approximation algorithm for the
unweighted
version was also obtained [SODA 2019].

• We give an O(log
2
n
)-factor approximation algorithm for W
eighted
C
hordal
V
ertex
D
eletion
, the vertex deletion problem to the family of chordal graphs. On the way to this algorithm, we also obtain a constant factor approximation algorithm for M
ulticut
on chordal graphs.

• We give an O(log
3
n
)-factor approximation algorithm for W
eighted
D
istance
H
ereditary
V
ertex
D
eletion
.

We believe that our recursive scheme can be applied to obtain O(log
O(1)
n
)-approximation algorithms for many other problems as well.
Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
Authors: Wood Alexander , Najarian Kayvan , Kahrobaei Delaram 
Published: July 2020

Machine learning and statistical techniques are powerful tools for analyzing large amounts of medical and genomic data. On the other hand, ethical concerns and privacy regulations prevent free sharing of this data. Encryption techniques such as fully homomorphic encryption (FHE) enable evaluation over encrypted data. Using FHE, machine learning models such as deep learning, decision trees, and Naive Bayes have been implemented for privacy-preserving applications using medical data. These applications include classifying encrypted data and training models on encrypted data. FHE has also been shown to enable secure genomic algorithms, such as paternity and ancestry testing and privacy-preserving applications of genome-wide association studies.
This survey provides an overview of fully homomorphic encryption and its applications in medicine and bioinformatics. The high-level concepts behind FHE and its history are introduced, and details on current open-source implementations are provided. The state of fully homomorphic encryption for privacy-preserving techniques in machine learning and bioinformatics is reviewed, along with descriptions of how these methods can be implemented in the encrypted domain.
Unsupervised Derivation of Keyword Summary for Short Texts
Authors: Cao Bin , Wu Jiawei , Wang Sichao , Gao Honghao , Fan Jing , Deng Shuiguang , Yin Jianwei , Liu Xuan 
Published: July 2020

Automatically summarizing a group of short texts that mainly share one topic is a fundamental task in many applications, e.g., summarizing the main symptoms for a disease based on a group of medical texts that are usually short, i.e., tens of words. Conventional unsupervised short text summarization techniques tend to find the most representative short text document. However, they may cause privacy issues, e.g., personal information in the medical texts may be exposed. Moreover, compared with the complete short text where some unimportant words may exist, a summary consisting of only a few keywords is more preferable by the user due to its clear and concise form. Due to the above reasons, in this article, we aim to solve the problem of unsupervised derivation of keyword summary for short texts. Existing keyword extraction methods such as Latent Dirichlet Allocation cannot be applied to solve this problem, since (1) the ordering relations among the extracted keywords are ignored, which causes troubles for people to capture the main idea of the event, and (2) short texts contain limited context, which makes it hard to find the optimal words for semantic coverage. Hence, we propose a simple but yet effective method named
Frequent Closed Wordsets Ranking (FCWRank)
to derive the keyword summary from a short text cluster. FCWRank is an unsupervised method that builds on the idea of frequent closed itemset mining in transaction database. FCWRank first mines all frequent closed wordsets from a cluster of short texts and then selects the most important wordset based on an importance model where the similarity between closed wordsets and the relation between the closed wordset and the short text document are considered simultaneously. To make the keywords within the wordset more understandable, FCWRank further unfolds the semantics behind them by sorting them. Experiments on real-world short text collections show that FCWRank outperforms the state-of-the-art baselines in terms of Recall-Oriented Understudy for Gisting Evaluation-Longest common subsequence F1, precision and recall scores.
A Novel Multiobjective GDWCN-PSO Algorithm and Its Application to Medical Data Security
Authors: Bharti Vandana , Biswas Bhaskar , Shukla Kaushal Kumar 
Published: July 2020

Nature-inspired optimization is one of the most prevalent research domains with a confounding history that fascinates the research communities.
Particle Swarm Optimization
is one of the well-known optimizers that belongs to the family of nature-inspired algorithms. It often suffers from premature convergence leading to a local optimum. To address this, several methods were presented using different network topologies of the particles, but either lacked accuracy or were slow. To solve these problems, an improved version of the
Directed Weighted Complex Network Particle Swarm Optimization using the Genetic Algorithm (GDWCN-PSO)
is presented. This method uses the concept of the Genetic Algorithm after each update to enhance convergence and diversity. Since most of the real-world applications and complex optimization problems involve more than one objective function so to suit this problem, a multiobjective version of GDWCN-PSO is also proposed and validated on standard benchmarks. To demonstrate its applicability in real-world applications, GDWCN-PSO is applied to solve the optimal key-based medical image encryption. It is one of the most challenging problems in health IoTs for protecting sensitive and confidential patient data as well as addressing the major concern of integrity and security of data in today’s advanced digital world.
Deterministic Sparse Suffix Sorting in the Restore Model
Authors: Fischer Johannes , I Tomohiro , Köppl Dominik 
Published: July 2020

Given a text
T
of length
n
, we propose a deterministic online algorithm computing the sparse suffix array and the sparse longest common prefix array of
T
in O(
c
√ lg
n
+
m
lg
m
lg
n
lg
*
n
) time with O(
m
) words of space under the premise that the space of
T
is rewritable, where
m
≤
n
is the number of suffixes to be sorted (provided online and arbitrarily), and
c
is the number of characters with
m
≤
c
≤
n
that must be compared for distinguishing the designated suffixes.
Modified Ventricular Global Function Index Correlates With Exercise Capacity in Repaired Tetralogy of Fallot
Authors: Ta Hieu T. , Critser Paul J. , Alsaied Tarek , Germann Joshua , Powell Adam W. , Redington Andrew N. , Tretter Justin T. 
Published: July 2020

Background
Cardiac MRI (CMR) derived ventricular global function index (GFI), a ratio of stroke volume to the sum of mean ventricular cavity and myocardial volumes, has demonstrated improved prediction of clinical outcomes in adults with atherosclerotic disease over ejection fraction. We sought to assess CMR derived GFI and a novel modification that accounts for unique loading conditions in patients with repaired tetralogy of Fallot (rTOF) and determine its correlation with exercise performance.

Methods and Results

Seventy‐five patients with rTOF who underwent CMR were identified. Clinical variables were recorded and biventricular GFI calculated. A right ventricular (RV) effective GFI (eGFI) was derived by incorporating effective stroke volume. Thirty‐five pediatric patients were matched with 29 age‐matched healthy controls. Twenty‐five patients completed cardiopulmonary exercise tests within 6 months of CMR. Stepwise regression models were used to determine univariate and multivariable predictors of indexed and percent predicted peak VO
2
. Median age at CMR was 20 years (interquartile range, 13–28). Pediatric rTOF patients had lower RV eGFI (
P
< 0.001), RV ejection fraction (
P
=0.002), but higher indexed RV end‐diastolic and end‐systolic volumes (
P
< 0.001,
P
< 0.001) compared with controls. Univariate analysis demonstrated a correlation between indexed peak VO
2
with RV eGFI (
R
2
=0.32,
P
=0.004), but with neither RVGFI, RV ejection fraction, indexed RV volumes nor RV mass. RV eGFI remained significantly associated with indexed peak VO
2
during multivariable modeling.

Conclusions
Reduced RV eGFI was associated with reduced exercise capacity in rTOF patients, while RV GFI, RV ejection fraction, indexed RV volumes and mass were not. Our modification of the GFI, RV eGFI, may be a valuable non‐invasive marker of cardiac function in rTOF.
What’s Driving Me? Exploration and Validation of a Hierarchical Personality Model for Trust in Automated Driving
Authors: Kraus Johannes , Scholz David , Baumann Martin 
Published: July 2020

Objective This paper presents a comprehensive investigation of personality traits related to trust in automated vehicles. A hierarchical personality model based on Mowen’s (2000) 3M model is explored in a first and replicated in a second study. Background Trust in automation is established in a complex psychological process involving user-, system- and situation-related variables. In this process, personality traits have been viewed as an important source of variance. Method Dispositional variables on three levels were included in an exploratory, hierarchical personality model (full model) of dynamic learned trust in automation, which was refined on the basis of structural equation modeling carried out in Study 1 (final model). Study 2 replicated the final model in an independent sample. Results In both studies, the personality model showed a good fit and explained a large proportion of variance in trust in automation. The combined evidence supports the role of extraversion, neuroticism, and self-esteem at the elemental level; affinity for technology and dispositional interpersonal trust at the situational level; and propensity to trust in automation and a priori acceptability of automated driving at the surface level in the prediction of trust in automation. Conclusion Findings confirm that personality plays a substantial role in trust formation and provide evidence of the involvement of user dispositions not previously investigated in relation to trust in automation: self-esteem, dispositional interpersonal trust, and affinity for technology. Application Implications for personalization of information campaigns, driver training, and user interfaces for trust calibration in automated driving are discussed.