bluuebunny/crossref_metadata_2025_split huggingface dataset:
A proficient data gathering technique for unmanned aerial vehicle‐enabled heterogeneous wireless sensor networks
Authors: Singh Samayveer , Malik Aruna , Kumar Rajeev , Singh Pradeep Kumar 
Published: August 2021

SummaryUnmanned aerial vehicle (UAV)‐enabled wireless sensor networks (WSNs) have evolved as the significant paradigms to communicate the information among the devices in today's scenario instantly. These technologies support for developing smart crop spraying, smart infrastructure, aerial photography and videography, emergency services, etc. in providing smart solutions. Therefore, there is a dire need to develop an energy‐efficient solution for data gathering through UAVs. In this paper, an optimum weighted probability function is proposed by considering residual node energy, node spacing, and average energy of networks. This function helps in optimizing the clustering process for three‐tier heterogeneity by minimizing the energy of the proposed network. The proposed methods achieve 29.45% and 52.48% increment in the network lifespan as compared to the existing algorithm. The reason for such a gigantic enhancement in the network lifespan is the selection of the highest capable node as a cluster head using the proposed function.
A Framework for Utilizing High-Resolution Mass Spectrometry and Nontargeted Analysis in Rapid Response and Emergency Situations
Authors: Phillips Allison L. , Williams Antony J. , Sobus Jon R. , Ulrich Elin M. , Gundersen Jennifer , Langlois-Miller Christina , Newton Seth R. 
Published: August 2021

Abstract
Unknown chemical releases constitute a large portion of the rapid response situations to which the US Environmental Protection Agency is called on to respond. Workflows used to address unknown chemical releases currently involve screening for a large array of known compounds using many different targeted methods. When matches are not found, expert analytical chemistry knowledge is used to propose possible candidates from the available data, which generally includes low-resolution mass spectra and situational clues such as the location of the release, nearby industrial operations, and other field-reported facts. The past decade has witnessed dramatic improvements in capabilities for identifying unknown compounds using high-resolution mass spectrometry (HRMS) and nontargeted analysis (NTA) approaches. Complementary developments in cheminformatics tools have further enabled an increase in NTA throughput and identification confidence. Together with the expanding availability of HRMS instrumentation in monitoring laboratories, these advancements make NTA highly relevant to rapid response scenarios. In this article, we introduce the concept of NTA as it relates to rapid response needs and describe how it can be applied to address unknown chemical releases. We advocate for the consideration of HRMS-based NTA approaches to support future rapid response scenarios. Environ Toxicol Chem 2022;41:1117–1130. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.
Post quantum secure conditional privacy preserving authentication for edge based vehicular communication
Authors: Dharminder Dharminder , Kumari Saru , Kumar Uddeshaya 
Published: August 2021

AbstractA vehicular ad hoc network possesses highly advanced functioning in the intelligent transportation system. This system helps moving nodes equipped with advanced smart devices, to establish reliable communication with vehicles or usable roadside units (RSUs). It has been ascertained that the privacy of the user is essential in vehicular communication to share resources among both unknown vehicles and unknown RSUs. There are some privacy‐preserving authentication schemes based on number‐theoretic assumptions, but they do not support security against quantum computers due to Shor's algorithm. Moreover, these schemes have disfavor with repeated authentication of the earlier transmitted message and being unsuccessful to search messages no longer valid during batch verification. To resolve most of the existing issues, this article brings something new to an environment, that is, edge‐computing construction into the message‐verification procedure of the system. In the proposed design, a RSU can expeditiously verify messages from nearby legitimate vehicles and broadcast to all vehicles within its communication range, which leads to a reduction in redundant verification of messages. To ensure security against quantum attacks, we have introduced an advanced design based on the hardness of a short integer solution in some random lattice. This framework guarantees autonomous driving, regular vehicular traffic flow, and a process of revocation in the advanced quantum era.
Mixed‐effects multilevel analysis followed by canonical correlation analysis is an effective fMRI tool for the investigation of idiosyncrasies
Authors: Jo Sungman , Kim Hyun‐Chul , Lustig Niv , Chen Gang , Lee Jong‐Hwan 
Published: August 2021

AbstractWe report that regions‐of‐interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed‐effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). A real‐world dataset for the neuronal response to nicotine use was acquired using a custom‐made MRI‐compatible apparatus for the smoking of electronic cigarettes (e‐cigarettes). Nineteen participants smoked e‐cigarettes in an MRI scanner using the apparatus with two experimental conditions: e‐cigarettes with nicotine (ECIG) and sham e‐cigarettes without nicotine (SCIG) and subjective ratings were collected. The right insula was identified in the ECIG condition from the χ2‐test of the MEMA but not from the t‐test, and the corresponding activations were significantly associated with the similarity scores (r = −.52, p = .041, confidence interval [CI] = [−0.78, −0.17]) and the urge‐to‐smoke scores (r = .73, p <.001, CI = [0.52, 0.88]). From the contrast between the two conditions (i.e., ECIG > SCIG), the right orbitofrontal cortex was identified from the χ2‐tests, and the corresponding neuronal activations showed a statistically meaningful association with similarity (r = −.58, p = .01, CI = [−0.84, −0.17]) and the urge to smoke (r = .34, p = .15, CI = [0.09, 0.56]). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was further evaluated using the fMRI and behavioral data acquired from the working memory and gambling tasks available from the Human Connectome Project.
Understanding the development of honesty in children through the domains‐of‐socialization approach
Authors: Tong Donia , Talwar Victoria 
Published: August 2021

AbstractHonesty is an important value that children acquire through socialization. To date, the socialization process by which children learn to behave honestly remains relatively unexamined. Researchers may have left this area of research relatively unexamined because there is no framework to understand how parents socialize honesty and lie‐telling in their children. As such, we suggest that the domains‐of‐socialization approach, which organizes the socialization process into various domains based on different aspects of the caregiver‐child relationship, may provide such a framework. Using this framework, researchers can operationalize vague parenting variables and identify gaps in the research, allowing them to investigate the relationship between socialization and developmental trajectories of honesty and lie‐telling tendencies more thoroughly. In this paper, we review the literature on factors influencing children's lie‐telling and honesty in relation to the five domains to demonstrate the applicability of the domains‐of‐socialization framework to research on the socialization of honesty. We also provide recommendations for future research on the socialization of honesty using a domain‐specific approach, which will contribute to our understanding of how children develop into normative or problematic liars.
Follow‐up of renal transplant recipients after acute COVID‐19—A prospective cohort single‐center study
Authors: Basic‐Jukic Nikolina , Juric Ivana , Furic‐Cunko Vesna , Katalinic Lea , Radic Josipa , Bosnjak Zrinka , Jelakovic Bojan , Kastelan Zeljko 
Published: August 2021

AbstractIntroductionAlthough most patients recover within several weeks after acute COVID‐19, some of them develop long‐lasting clinical symptoms. Renal transplant recipients have an increased mortality risk from COVID‐19. We aimed to describe complications occurring after COVID‐19 in this group of patients.MethodsA prospective single‐center cohort study was conducted at University Hospital Centre Zagreb. Patients with two negative reverse transcriptase‐polymerase chain reaction (RT‐PCR) tests for SARS‐CoV‐2 after COVID‐19 were eligible for further follow‐up at our outpatient clinic. They underwent detailed clinical and laboratory assessments. The primary outcome was the development of complications after COVID‐19.ResultsOnly 11.53% of renal transplant recipients who survived acute COVID‐19 were symptomless and free from new‐onset laboratory abnormalities during the median follow‐up of 64 days (range: 50–76 days). Three patients died from sepsis after discharge from the hospital. In 47 patients (45.2%), clinical complications were present, while 74 patients (71.2%) had one or more laboratory abnormalities. The most common clinical complications included shortness of breath (19.2%), tiredness (11.5%), peripheral neuropathy (7.7%), self‐reported cognitive impairments (5.7%), and dry cough (7.7%). Most common laboratory abnormalities included shortened activated partial thromboplastin time (50%), elevated D‐dimers (36.5%), elevated fibrinogen (30.16%), and hypogammaglobulinemia (24%). Positive RT‐PCR for cytomegalovirus (8.7%), Epstein–Barr virus (26%), or BK virus (16.3%). Multivariate analysis identified the history of diabetes mellitus and eGFR CKD‐EPI as predictors for the development of post‐COVID clinical complications. Six months after acute COVID‐19, elevated D‐dimers persisted with normalization of other laboratory parameters. Twenty‐nine patients were hospitalized, mostly with several concomitant problems. However, initially reported clinical problems gradually improved in the majority of patients.ConclusionPost‐COVID‐19 clinical and laboratory complications are frequent in the renal transplant population, in some of them associated with significant morbidity. All patients recovered from acute COVID‐19 should undergo long‐term monitoring for evaluation and treatment of complications.
Programmed death‐ligand 1 expression in swine chronic infections and enhancement of interleukin‐2 production via programmed death‐1/programmed death‐ligand 1 blockade
Authors: Ganbaatar Otgontuya , Konnai Satoru , Okagawa Tomohiro , Nojima Yutaro , Maekawa Naoya , Ichikawa Yoshiki , Kobayashi Atsushi , Shibahara Tomoyuki , Yanagawa Yojiro , Higuchi Hidetoshi , Kato Yukinari , Suzuki Yasuhiko , Murata Shiro , Ohashi Kazuhiko 
Published: August 2021

AbstractIntroductionChronic infections lead to the functional exhaustion of T cells. Exhausted T cells are phenotypically differentiated by the surface expression of the immunoinhibitory receptor, such as programmed death‐1 (PD‐1). The inhibitory signal is produced by the interaction between PD‐1 and its PD‐ligand 1 (PD‐L1) and impairs the effector functions of T cells. However, the expression dynamics of PD‐L1 and the immunological functions of the PD‐1/PD‐L1 pathway in chronic diseases of pigs are still poorly understood. In this study, we first analyzed the expression of PD‐L1 in various chronic infections in pigs, and then evaluated the immune activation by the blocking assay targeting the swine PD‐1/PD‐L1 pathway.MethodsIn the initial experiments, anti‐bovine PD‐L1 monoclonal antibodies (mAbs) were tested for cross‐reactivity with swine PD‐L1. Subsequently, immunohistochemical analysis was conducted using the anti‐PD‐L1 mAb. Finally, we assessed the immune activation of swine peripheral blood mononuclear cells (PBMCs) by the blockade with anti‐PD‐L1 mAb.ResultsSeveral anti‐PD‐L1 mAbs tested recognized swine PD‐L1‐expressing cells. The binding of swine PD‐L1 protein to swine PD‐1 was inhibited by some of these cross‐reactive mAbs. In addition, immunohistochemical analysis revealed that PD‐L1 was expressed at the site of infection in chronic infections of pigs. The PD‐L1 blockade increased the production of interleukin‐2 from swine PBMCs.ConclusionsThese findings suggest that the PD‐1/PD‐L1 pathway could be also involved in immunosuppression in chronic infections in pigs. This study provides a new perspective on therapeutic strategies for chronic diseases in pigs by targeting immunosuppressive pathways.
Use of an artificial intelligence‐based rule extraction approach to predict an emergency cesarean section
Authors: Nagayasu Yoko , Fujita Daisuke , Ohmichi Masahide , Hayashi Yoichi 
Published: August 2021

AbstractObjectiveOne of the major problems with artificial intelligence (AI) is that it is generally known as a “black box”. Therefore, the present study aimed to construct an emergency cesarean section (CS) prediction system using an AI‐based rule extraction approach as a “white box” to detect the cause for the emergency CS.MethodsData were collected from all perinatal records of all delivery outcomes at Osaka Medical College between December 2014 and July 2019. We identified the delivery method for all deliveries after 36 gestational weeks as either (1) vaginal delivery or scheduled CS, or (2) emergency CS. From among these, we selected 52 risk factors to feed into an AI‐based rule extraction algorithm to extract rules to predict an emergency CS.ResultsWe identified 1513 singleton deliveries (1285 [84.9%] vaginal deliveries, 228 emergency CS [15.1%]) and extracted 15 rules. We achieved an average accuracy of 81.90% using five‐fold cross‐validation and an area under the receiving operating characteristic curve of 71.46%.ConclusionTo our knowledge, this is the first study to use interpretable AI‐based rule extraction technology to predict an emergency CS. This system appears to be useful for identifying hidden factors for emergency CS.
A Multiple Logistic Regression Model Based on Gamma‐Glutamyl Transferase as a Biomarker for Early Prediction of Drug‐Induced Liver Injury in Vietnamese Patients
Authors: Nguyen Phuong Thi Thu , Hoang Dung Van , Pham Khue Minh , Nguyen Hoi Thanh 
Published: August 2021

AbstractThe discovery of new biomarkers and the causality of drug‐induced liver injury (DILI) is a major focus in modern medicine. Alcoholism is considered a risk factor for DILI. However, the extraction and assessment of alcohol history are difficult due to noncooperation by patients and intermittent management. Therefore, we conducted a case‐control study of 1277 patients diagnosed with DILI according to the Roussel Uclaf Causality Assessment Method scale to evaluate gamma‐glutamyl transferase (GGT) as a biomarker for predicting DILI in Vietnamese patients, where the proportion of alcoholism is quite high. Further, we built and validated a logistic regression model to predict the risk of DILI in hospitalized patients. The risk of DILI increased by 10% for 1 UI/L higher levels of GGT before prescription (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.00‐1.01). A history of alcoholism was not a risk factor for DILI occurrence (OR, 1.83; 95%CI, 0.99‐3.04; P = .057). A logistic regression model was successfully built and validated based on age; sex; initial levels of alanine aminotransferase, alkaline phosphatate, GGT, likelihood score of the suspected drug, and history of liver disease; the area under the receiver operating characteristic curve of the model was 0.883 (95%CI, 0.868‐0.897). Our results thus suggest the necessity of exercising caution when prescribing to patients without a history of alcoholism but having high GGT levels. This model can be applied clinically to assess the risk of DILI before prescribing to reduce the risk of DILI in the patient.
Four‐Dimensional Flow Magnetic Resonance Imaging in the Assessment of Blood Flow in the Heart and Great Vessels: A Systematic Review
Authors: Doyle Ciara M. , Orr Jenny , Greenwood John P. , Plein Sven , Tsoumpas Charalampos , Bissell Malenka M. 
Published: August 2021

Four‐dimensional (4D) flow magnetic resonance imaging (MRI) allows multidirectional quantification of blood flow in the heart and great vessels. Comparability of the technique to the current reference standards of flow assessment—two‐dimensional (2D) flow MRI and Doppler echocardiography—varies in the literature. Image acquisition parameters likely impact upon the accuracy and reproducibility of 4D flow MRI. We therefore sought to review the current literature on 4D flow MRI in the heart and great vessels, in comparison to 2D flow MRI, Doppler echocardiography, and invasive catheterization. Using a predefined search strategy and inclusion and exclusion criteria, the databases EMBASE and Medline were searched in January 2021 for peer‐reviewed research articles comparing cardiac 4D flow MRI to 2D flow MRI, Doppler echocardiography and/or invasive catheterization. The data from all relevant articles were assimilated and analyzed using Mann–Whitney U and chi χ2 test. Forty‐four manuscripts met the eligibility criteria and were included in the review. The review showed agreement of 4D flow MRI to the reference standard methods of flow assessment, particular in the measurement of peak velocity and stroke volume in 55% of manuscripts. The use of valve tracking significantly improves agreement between 4D flow MRI and the reference modalities (79% matching with the use of valve tracking vs. 50% without, P = 0.04). This review highlights that the impact of acquisition parameters on 4D flow MRI accuracy is multifactorial. It is therefore important that each center conducts its own quality assurance prior to using 4D flow MRI for clinical decision‐making.Level of Evidence2Technical EfficacyStage 2
Evolution of viral variants in remdesivir‐treated and untreated SARS‐CoV‐2‐infected pediatrics patients
Authors: Boshier Florencia A. T. , Pang Juanita , Penner Justin , Parker Matthew , Alders Nele , Bamford Alasdair , Grandjean Louis , Grunewald Stephanie , Hatcher James , Best Timothy , Dalton Caroline , Bynoe Patricia Dyal , Frauenfelder Claire , Köeglmeier Jutta , Myerson Phoebe , Roy Sunando , Williams Rachel , de Silva Thushan I. , Goldstein Richard A. , Breuer Judith ,   The COVID‐19 Genomics UK (COG‐UK) consortium
Published: August 2021

AbstractDetailed information on intrahost viral evolution in SARS‐CoV‐2 with and without treatment is limited. Sequential viral loads and deep sequencing of SARS‐CoV‐2 from the upper respiratory tract of nine hospitalized children, three of whom were treated with remdesivir, revealed that remdesivir treatment suppressed viral load in one patient but not in a second infected with an identical strain without any evidence of drug resistance found. Reduced levels of subgenomic RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication. Haplotype reconstruction uncovered persistent SARS‐CoV‐2 variant genotypes in four patients. These likely arose from within‐host evolution, although superinfection cannot be excluded in one case. Although our dataset is small, observed sample‐to‐sample heterogeneity in variant frequencies across four of nine patients suggests the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalization could compromise the penetration of remdesivir into the lung, limiting the drugs in vivo efficacy, as has been observed in other lung infections.
Effects of Atlantic multidecadal oscillation and Pacific decadal oscillation on interdecadal variability of fog frequency in autumn–winter season in Southwest China
Authors: Liu Peng , Zhang Ying , Tang Mingyue 
Published: August 2021

AbstractBased on the Atlantic multidecadal oscillation (AMO) and the Pacific decadal oscillation (PDO) indexes, the observation of fog frequency in China and the reanalysis data from the National Centres for Environmental Prediction/National Center for Atmospheric Research during 1958–2007 are selected to study the effects of the AMO and PDO on the interdecadal variability of fog frequency in autumn–winter in Southwest China (SWC). The results suggest that the fog frequency in SWC is highest in autumn–winter season and shows a characteristic of strong interdecadal variation. When the north Atlantic and the north Pacific are abnormally cold (warm), which corresponds to the negative (positive) phase of the AMO and the positive (negative) phase of the PDO respectively, the fog in SWC occurs more (less) frequently. The atmosphere is unstable because of the eastward propagation of Rossby wave train and the anomaly of Siberian high‐pressure, which are affected by the AMO and PDO, respectively. The AMO particularly affects the atmospheric stability in the middle and lower level, while the PDO mainly affects that of the whole layer. The water vapour is modulated by the southward movement of cold air in Northern China during the negative phase of the AMO and positive phase of the PDO. This results in the decreasing of temperature and specific humidity, and further leads to the supersaturation of water vapour in the lower atmosphere of SWC. The AMO particularly affects the temperature and water vapour supersaturation in the lower atmosphere, while the PDO mostly modulates the atmospheric stability of the whole layer and the southward movement of cold air.
Carnitine deficiency among hospitalized pediatric patients: A retrospective study of critically ill patients receiving extracorporeal membrane oxygenation therapy
Authors: Kelley Jenna , Sullivan Erin , Norris Marie , Sullivan Sarah , Parietti Jennifer , Kellogg Kimberly , Scott Anna I. 
Published: August 2021

AbstractBackgroundThe metabolic demands associated with critical illness place patients at risk for nutrition deficits. Carnitine is a small molecule essential for fatty acid oxidation and gluconeogenesis. Secondary carnitine deficiency can have clinically significant complications and has been observed anecdotally in patients receiving extracorporeal membrane oxygenation (ECMO) therapy at our institution. Guidelines for monitoring and supplementing carnitine are lacking. This retrospective study determined whether critically ill pediatric patients receiving ECMO have an increased risk of carnitine deficiency.MethodsAcylcarnitine analysis was performed on residual specimens from patients who received ECMO therapy. The control data were a convenience sample gathered by chart review of patients who had been tested for carnitine during a hospitalization.ResultsAcylcarnitines were measured in 217 non‐ECMO patients and 81 ECMO patients. Carnitine deficiency, based on age‐specific reference ranges, was observed in 41% of ECMO cases compared with 21% of non‐ECMO cases. Multivariable analysis of age‐matched patients identified that the odds of carnitine deficiency were significantly lower among patients on the floor compared with ECMO patients (odds ratio, 0.21; 95% CI, 0.10–0.44). Age‐specific frequency of qualitative carnitine deficiency ranged from 15% (patients >5 years old) to 56% (patients 1 week to 1 month old) in ECMO patients and 15% (patients >5 years old) to 34% (patients 1–5 years old) in non‐ECMO patients.ConclusionIn this study, ECMO patients were carnitine deficient more frequently compared with other inpatients, with the highest rates of deficiency among ECMO patients between 1 week and 1 month old.