bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification and categorisation of relevant outcomes for symptomatic uncomplicated gallstone disease: in-depth analysis to inform the development of a core outcome set
Authors: Cruickshank Moira , Newlands Rumana , Blazeby Jane , Ahmed Irfan , Bekheit Mohamed , Brazzelli Miriam , Croal Bernard , Innes Karen , Ramsay Craig , Gillies Katie
Published: June 2021

Background

Many completed trials of interventions for uncomplicated gallstone disease are not as helpful as they could be due to lack of standardisation across studies, outcome definition, collection and reporting. This heterogeneity of outcomes across studies hampers useful synthesis of primary studies and ultimately negatively impacts on decision making by all stakeholders. Core outcome sets offer a potential solution to this problem of heterogeneity and concerns over whether the ‘right’ outcomes are being measured. One of the first steps in core outcome set generation is to identify the range of outcomes reported (in the literature or by patients directly) that are considered important.

Objectives

To develop a systematic map that examines the variation in outcome reporting of interventions for uncomplicated symptomatic gallstone disease, and to identify other outcomes of importance to patients with gallstones not previously measured or reported in interventional studies.

Results

The literature search identified 794 potentially relevant titles and abstracts of which 137 were deemed eligible for inclusion. A total of 129 randomised controlled trials, 4 gallstone disease specific patient-reported outcome measures (PROMs) and 8 qualitative studies were included. This was supplemented with data from 6 individual interviews, 1 focus group (n=5 participants) and analysis of 20 consultations. A total of 386 individual recorded outcomes were identified across the combined evidence: 330 outcomes (which were reported 1147 times) from trials evaluating interventions, 22 outcomes from PROMs, 17 outcomes from existing qualitative studies and 17 outcomes from primary qualitative research. Areas of overlap between the evidence sources existed but also the primary research contributed new, unreported in this context, outcomes.

Conclusions

This study took a rigorous approach to catalogue and map the outcomes of importance in gallstone disease to enhance the development of the COS ‘long’ list. A COS for uncomplicated gallstone disease that considers the views of all relevant stakeholders is needed.
Rehabilitation of the frail older adults in primary healthcare in rural areas: a scoping review protocol
Authors: Hov Jorunn , Alteren Johanne , Kvigne Kari
Published: June 2021

Introduction

Frail older adults are particularly vulnerable to functional decline and adverse outcomes because they lack the necessary resistance and ability to cope. Rehabilitation services for the frail older adults are thus vital and require clarification. The aim of this review is to identify and map the scope and breadth of literature regarding rehabilitation of the frail older adults to develop a holistic rehabilitation service in primary healthcare in rural areas. The concept of rehabilitation, how rehabilitation services are organised, how patients and next of kin are involved in planning and evaluating services during rehabilitation, as well as reported results will be identified and mapped.

Methods and analysis

This scoping review will be conducted based on the methodology developed by Arksey and O’Malley. The search strategy will aim to locate both published and unpublished studies in relevant databases. Key information sources include CINAHL, MEDLINE, Embase, ProQuest and Google Scholar. Data will be extracted from papers that all three reviewers have chosen to include in the review. All three reviewers will participate in screening, assessment and selection of studies against the inclusion criteria for the review and work in teams of two. The full text of selected citations will be assessed in detail against the inclusion criteria by the same teams. Data will be extracted from papers included in the scoping review by two of the reviewers. Modifications will be detailed in the full review report. Any disagreements that arise between two reviewers will be resolved through discussion or with the third reviewer’s mediation. A narrative summary of the findings will be presented accompanied by tables that reflect the objective of the review.

Ethics and dissemination

Data will be obtained only from already publicly available materials. Special ethical approval is, therefore, not required.
Cohort profile: the MUNICH Preterm and Term Clinical study (MUNICH-PreTCl), a neonatal birth cohort with focus on prenatal and postnatal determinants of infant and childhood morbidity
Authors: Pangratz-Fuehrer Susanne , Genzel-Boroviczény Orsolya , Bodensohn Wolfgang , Eisenburger Robin , Scharpenack Janne , Geyer Philipp E , Müller-Reif Johannes B , van Hagen Nadja , Müller Alina M , Jensen Majken Karoline , Klein Christoph , Mann Matthias , Nussbaum Claudia
Published: June 2021

Purpose

The MUNICH Preterm and Term Clinical (MUNICH-PreTCl) birth cohort was established to uncover pathological processes contributing to infant/childhood morbidity and mortality. We collected comprehensive medical information of healthy and sick newborns and their families, together with infant blood samples for proteomic analysis. MUNICH-PreTCl aims to identify mechanism-based biomarkers in infant health and disease to deliver more precise diagnostic and predictive information for disease prevention. We particularly focused on risk factors for pregnancy complications, family history of genetically influenced health conditions such as diabetes and paediatric long-term health—all to be further monitored and correlated with proteomics data in the future.

Participants

Newborns and their parents were recruited from the Perinatal Center at the LMU University Hospital, Munich, between February 2017 and June 2019. Infants without congenital anomalies, delivered at 23–41 weeks of gestation, were eligible.

Findings

Findings to date concern the clinical data and extensive personal patient information. A total of 662 infants were recruited, 44% were female (36% in preterm, 46% in term). 90% of approached families agreed to participate. Neonates were grouped according to gestational age: extremely preterm (<28 weeks, N=28), very preterm (28 to <32 weeks, N=36), late preterm (32 to <37 weeks, N=97) and term infants (>37+0 weeks, N=501). We collected over 450 data points per child–parent set, (family history, demographics, pregnancy, birth and daily follow-ups throughout hospitalisation) and 841 blood samples longitudinally. The completion rates for medical examinations and blood samples were 100% and 95% for the questionnaire.

Future plans

The correlation of large clinical datasets with proteomic phenotypes, together with the use of medical registries, will enable future investigations aiming to decipher mechanisms of disorders in a systems biology perspective.

Trial registration number

DRKS (00024189); Pre-results.
Blood RNA sequencing shows overlapping gene expression across COPD phenotype domains
Authors: Ghosh Auyon J , Saferali Aabida , Lee Sool , Chase Robert , Moll Matthew , Morrow Jarrett , Yun Jeong , Castaldi Peter J , Hersh Craig P
Published: June 2021

Rationale

COPD can be assessed using multidimensional grading systems with components from three domains: pulmonary function tests, symptoms and systemic features. Clinically, measures may be used interchangeably, though it is not known if they share similar pathobiology.

Objective

To use RNA sequencing (RNA-seq) to determine if there is an overlap in the underlying biological mechanisms and consequences driving different components of the multidimensional grading systems.

Methods

Whole blood was collected for RNA-seq from current and former smokers in the Genetic Epidemiology of COPD study. We tested the overlap in gene expression and biological pathways associated with case–control status and quantitative COPD phenotypes within and between the three domains.

Results

In 2647 subjects, there were 3030 genes differentially expressed in any of the three domains or case–control status. There were five genes that overlapped between the three domains and case–control status, including G protein-coupled receptor 15(GPR15), sestrin 1 (SESN1) and interferon-induced guanylate-binding protein 1 (GBP1), which were associated with longitudinal decline in FEV1. The overlap between the three domains was enriched for pathways related to cellular components.

Conclusions

We identified gene sets and pathways that overlap between 12 COPD-related phenotypes and case–control status. There were no pathways represented in the overlap between the three domains and case–control status, but we identified multiple genes that demonstrated a consistent pattern of expression across several of the phenotypes. Patterns of gene expression correlation were generally similar to the correlation of clinical phenotypes in the PFT and symptom domains but not the systemic features.
Muon identification in a compact single-layered water Cherenkov detector and gamma/hadron discrimination using machine learning techniques
Authors: Conceição R. , González B. S. , Guillén A. , Pimenta M. , Tomé B.
Published: June 2021

The muon tagging is an essential tool to distinguish between gamma and hadron-induced showers in wide field-of-view gamma-ray observatories. In this work, it is shown that an efficient muon tagging (and counting) can be achieved using a water Cherenkov detector with a reduced water volume and 4 PMTs, provided that the PMT signal spatial and time patterns are interpreted by an analysis based on machine learning (ML). The developed analysis has been tested for different shower and array configurations. The output of the ML analysis, the probability of having a muon in the WCD station, has been used to notably discriminate between gamma and hadron induced showers with$$S/ \sqrt{B} \sim 4$$S/B∼4for shower with energies$$E_0 \sim 1\,$$E0∼1TeV. Finally, for proton-induced showers, an estimator of the number of muons was built by means of the sum of the probabilities of having a muon in the stations. Resolutions about$$20\%$$20%and a negligible bias are obtained for vertical showers with$$N_{\mu } > 10$$Nμ>10.
On the Appropriate Rotary Inertia in Timoshenko Beam Theory
Authors: Shi Guangyu , Guo Qiaorong
Published: June 2021

The rotary inertia defined by Timoshenko to account for the angular velocity effect in flexural vibration of beams has been questioned by some researchers in recent years, and it caused some confusions. This paper discusses the appropriate rotary inertia in Timoshenko beam theory (TBT) and evaluates the influence of the two forms of the rotary inertia on the prediction of the higher-mode frequencies of transversely vibrating beams. Based on the theory of elasticity and variational principle, this work shows that the rotary inertia in the original TBT, defined in terms of the rotation of beam cross-section induced by bending deformation, is variational consistent and is capable of yielding good results of the phase velocities of transversely vibrating beams even in the case where the wavelength of vibrating beams approaches the beam height. On the other hand, the so-called corrected TBT, in which the rotary inertia is defined in terms of the slope of beam deflection, is neither variational consistent nor accurate when the wavelength of vibrating beams approaches the beam height. Therefore, the rotary inertia in TBT defined by Timoshenko is correct and should be used in the dynamic analysis of beams.
SERS devices with “hedgehog-like” nanosphere arrays for detection of trace pesticides
Authors: Liu Yang , Li Xin , Cheng Jie , Zhou Na , Zhang Lingqian , Mao Haiyang , Huang Chengjun
Published: June 2021

The development of surface-enhanced Raman scattering (SERS) devices for detection of trace pesticides has attracted more and more attention. In this work, a large-area self-assembly approach assisted with reactive ion etching (RIE) is proposed for preparing SERS devices consisting of Ag-covered “hedgehog-like” nanosphere arrays (Ag/HLNAs). Such a SERS device has an enhancement factor of [Formula: see text], a limit of detection (LOD) up to 10[Formula: see text][Formula: see text]M for Rhodamine 6G (R6G) analytes, and a relative standard deviation (RSD) smaller than 10%, demonstrating high uniformity. Besides, for pesticide detections, the device achieves an LOD of 10[Formula: see text][Formula: see text]M for thiram molecules. It indicates that the proposed SERS device has a promising opportunity in detecting toxic organic pesticides.
Fusion of clathrin and caveolae endocytic vesicles revealed by line-switching dual-color STED microscopy
Authors: Ruan Hefei , Yu Jianqiang , Wu Yayun , Tang Xiaojun , Yuan Jinghe , Fang Xiaohong
Published: June 2021

Clathrin- and caveolae-mediated endocytosis are the most commonly used pathways for the internalization of cell membrane receptors. However, due to their dimensions are within the diffraction limit, traditional fluorescence microscopy cannot distinguish them and little is known about their interactions underneath cell membrane. In this study, we proposed the line-switching scanning imaging mode for dual-color triplet-state relaxation (T-Rex) stimulated emission depletion (STED) super-resolution microscopy. With this line-switching mode, the cross-talk between the two channels, the side effects from pulse picker and image drift in frame scanning mode can be effectively eliminated. The dual-color super-resolution imaging results in mixed fluorescent beads validated the excellent performance. With this super-resolution microscope, not only the ring-shaped structure of clathrin and caveolae endocytic vesicles, but also their semi-fused structures underneath the cell membrane were distinguished clearly. The resultant information will greatly facilitate the study of clathrin- and caveolae-mediated receptor endocytosis and signaling process and also our home-built dual-color T-Rex STED microscope with this line-switching imaging mode provides a precise and convenient way to study subcellular-scale protein interactions.
The extraction of early warning features for predicting financial distress based on XGBoost model and shap framework
Authors: Yang He , Li Emma , Cai Yi Fang , Li Jiapei , Yuan George X.
Published: June 2021

The purpose of this paper is to establish a framework for the extraction of early warning risk features for the predicting financial distress based on XGBoost model and SHAP. It is well known that the way to construct early warning risk features to predict financial distress of companies is very important, and by comparing with the traditional statistical methods, though the data-driven machine learning for the financial early warning, modelling has a better performance in terms of prediction accuracy, but it also brings the difficulty such as the one the corresponding model may be not explained well. Recently, eXtreme Gradient Boosting (XGBoost), an ensemble learning algorithm based on extreme gradient boosting, has become a hot topic in the area of machine learning research field due to its strong nonlinear information recognition ability and high prediction accuracy in the practice. In this study, the XGBoost algorithm is used to extract early warning features for the predicting financial distress for listed companies, with 76 financial risk features from seven categories of aspects, and 14 non-financial risk features from four categories of aspects, which are collected to establish an early warning system for the predication of financial distress. With applications, we conduct the empirical testing respect to AUC, KS and Kappa, the numerical results show that by comparing with the Logistic model, our method based on XGBoost model established in this paper has much better ability to predict the financial distress risk of listed companies. Moreover, under the framework of SHAP (SHAPley Additive exPlanations), we are able to give a reasonable explanation for important risk features and influencing ways affecting the financial distress visibly. The results given by this paper show that the XGBoost approach to model early warning features for financial distress does not only preform a better prediction accuracy, but also is explainable, which is significant for the identification of early warning to the financial distress risk for listed companies in the practice.
mTeeth
Authors: Akther Sayma , Saleheen Nazir , Saha Mithun , Shetty Vivek , Kumar Santosh
Published: June 2021

Ensuring that all the teeth surfaces are adequately covered during daily brushing can reduce the risk of several oral diseases. In this paper, we propose the mTeeth model to detect teeth surfaces being brushed with a manual toothbrush in the natural free-living environment using wrist-worn inertial sensors. To unambiguously label sensor data corresponding to different surfaces and capture all transitions that last only milliseconds, we present a lightweight method to detect the micro-event of brushing strokes that cleanly demarcates transitions among brushing surfaces. Using features extracted from brushing strokes, we propose a Bayesian Ensemble method that leverages the natural hierarchy among teeth surfaces and patterns of transition among them. For training and testing, we enrich a publicly-available wrist-worn inertial sensor dataset collected from the natural environment with time-synchronized precise labels of brushing surface timings and moments of transition. We annotate 10,230 instances of brushing on different surfaces from 114 episodes and evaluate the impact of wide between-person and within-person between-episode variability on machine learning model's performance for brushing surface detection.
LumNet
Authors: Songwa Prince U.C. , Saeed Aaqib , Bhardwaj Sachin , Kruisselbrink Thijs W. , Ozcelebi Tanir
Published: June 2021

High-quality lighting positively influences visual performance in humans. The experienced visual performance can be measured using desktop luminance and hence several lighting control systems have been developed for its quantification. However, the measurement devices that are used to monitor the desktop luminance in existing lighting control systems are obtrusive to the users. As an alternative, ceiling-based luminance projection sensors are being used recently as these are unobtrusive and can capture the direct task area of a user. The positioning of these devices on the ceiling requires to estimate the desktop luminance in the user's vertical visual field, solely using ceiling-based measurements, to better predict the experienced visual performance of the user. For this purpose, we present LUMNET, an approach for estimating desktop luminance with deep models through utilizing supervised and self-supervised learning. Our model learns visual representations from ceiling-based images, which are collected in indoor spaces within the physical vicinity of the user to predict average desktop luminance as experienced in a real-life setting. We also propose a self-supervised contrastive method for pre-training LUMNET with unlabeled data and we demonstrate that the learned features are transferable onto a small labeled dataset which minimizes the requirement of costly data annotations. Likewise, we perform experiments on domain-specific datasets and show that our approach significantly improves over the baseline results from prior methods in estimating luminance, particularly in the low-data regime. LUMNET is an important step towards learning-based technique for luminance estimation and can be used for adaptive lighting control directly on-device thanks to its minimal computational footprint with an added benefit of preserving user's privacy.
Toward User-Driven Sound Recognizer Personalization with People Who Are d/Deaf or Hard of Hearing
Authors: Goodman Steven M. , Liu Ping , Jain Dhruv , McDonnell Emma J. , Froehlich Jon E. , Findlater Leah
Published: June 2021

Automated sound recognition tools can be a useful complement to d/Deaf and hard of hearing (DHH) people's typical communication and environmental awareness strategies. Pre-trained sound recognition models, however, may not meet the diverse needs of individual DHH users. While approaches from human-centered machine learning can enable non-expert users to build their own automated systems, end-user ML solutions that augment human sensory abilities present a unique challenge for users who have sensory disabilities: how can a DHH user, who has difficulty hearing a sound themselves, effectively record samples to train an ML system to recognize that sound? To better understand how DHH users can drive personalization of their own assistive sound recognition tools, we conducted a three-part study with 14 DHH participants: (1) an initial interview and demo of a personalizable sound recognizer, (2) a week-long field study of in situ recording, and (3) a follow-up interview and ideation session. Our results highlight a positive subjective experience when recording and interpreting training data in situ, but we uncover several key pitfalls unique to DHH users---such as inhibited judgement of representative samples due to limited audiological experience. We share implications of these results for the design of recording interfaces and human-the-the-loop systems that can support DHH users to build sound recognizers for their personal needs.
We Hear Your PACE
Authors: Cai Chao , Pu Henglin , Wang Peng , Chen Zhe , Luo Jun
Published: June 2021

Indoor localization is crucial to enable context-aware applications, but existing solutions mostly require a user to carry a device, so as to actively sense location-discriminating signals. However, many applications do not prefer user involvement due to, e.g., the cumbersome of carrying a device. Therefore, solutions that track user locations passively can be desirable, yet lack of active user involvement has made passive indoor localization very challenging even for a single person. To this end, we propose Passive Acoustic loCalization of multiple walking pErsons (PACE) as a solution for small-scale indoor scenarios: it passively locates users by pinpointing the positions of their footsteps. In particular, PACE leverages both structure-borne and air-borne footstep impact sounds (FIS); it uses structure-borne FIS for range estimations exploiting their acoustic dispersion nature, and it employs air-borne FIS for Angle-of-Arrival (AoA) estimations and person identifications. To combat the low-SNR nature of FIS, PACE innovatively employs domain adversarial adaptation and spectral weighting to ranging/identification and AoA estimations, respectively. We implement a PACE prototype and extensively evaluate its performance in representative environments. The results demonstrate a promising sub-meter localization accuracy with a median error of 30 cm.
Designing Kitchen Technologies for Ageing in Place
Authors: Kuoppamäki Sanna , Tuncer Sylvaine , Eriksson Sara , McMillan Donald
Published: June 2021

Assistive technologies can significantly increase older adults' independent living if these technologies are designed to meet their needs and abilities. This study investigates conditions and present possibilities for assistive technology to provide physical and cognitive support to older adults in a specific domestic task, which is cooking a meal at home. The empirical material consists of six video recordings of adults aged 65 and over preparing a meal in their kitchen. The study unpacks the complexity of kitchen tasks, from the physical interactions involved to the temporal and spatial alignment of objects and goals in the kitchen. We focus on a) Physical manipulation, such as chopping, opening packages, and moving objects around the kitchen, b) Organisation and coordination, including switching, synchronising and monitoring cooking tasks, and c) Reorchestration and reorganisation in the form of inserting additional tasks, and rearranging tools and ingredients when adjustments need to be made in the cooking process. The study outlines design principles for operational and organisational interventions to support cooking a meal for independent living. The study concludes with discussing design implications for conversational user interfaces in the kitchen, and the significance of assistive kitchen technologies for ageing in place.
BlinkListener
Authors: Liu Jialin , Li Dong , Wang Lei , Xiong Jie
Published: June 2021

Eye blink detection plays a key role in many real-life applications such as Human-Computer Interaction (HCI), drowsy driving prevention and eye disease detection. Although traditional camera-based techniques are promising, multiple issues hinder their wide adoption including the privacy concern, strict lighting condition and line-of-sight (LoS) requirements. On the other hand, wireless sensing without a need for dedicated sensors gains a tremendous amount of attention in recent years. Among the wireless signals utilized for sensing, acoustic signals show a unique potential for fine-grained sensing owing to their low propagation speed in the air. Another trend favoring acoustic sensing is the wide availability of speakers and microphones in commodity devices. Promising progress has been achieved in fine-grained human motion sensing such as breathing using acoustic signals. However, it is still very challenging to employ acoustic signals for eye blink detection due to the unique characteristics of eye blink (i.e., subtle, sparse and aperiodic) and severe interference (i.e., from the human target himself and surrounding objects). We find that even the very subtle involuntary head movement induced by breathing can severely interfere with eye blink detection. In this work, for the first time, we propose a system called BlinkListener to sense the subtle eye blink motion using acoustic signals in a contact-free manner. We first quantitatively model the relationship between signal variation and the subtle movements caused by eye blink and interference. Then, we propose a novel method that exploits the "harmful" interference to maximize the subtle signal variation induced by eye blinks. We implement BlinkListener on both a research-purpose platform (Bela) and a commodity smartphone (iPhone 5c). Experiment results show that BlinkListener can achieve robust performance with a median detection accuracy of 95%. Our system can achieve high accuracies when the smartphone is held in hand, the target wears glasses/sunglasses and in the presence of strong interference with people moving around.
Who Will Survive and Revive Undergoing the Epidemic
Authors: Han Zhenyu , Fu Haohao , Xu Fengli , Tu Zhen , Yu Yang , Hui Pan , Li Yong
Published: June 2021

A rapid-spreading epidemic of COVID-19 hit China at the end of 2019, resulting in unignorable social and economic damage in the epicenter, Wuhan. POIs capture the microscopic behavior of citizens, providing valuable information to understand city reactions toward the epidemic. Leveraging large-scale check-in records, we analyze the POI visit trends over the epidemic period and normal times. We demonstrate that COVID-19 greatly influences the society, where most POIs demonstrate more than 60% of visit drops during the city lockdown period. Among them, Tourist Attractions received greatest impact with a 78.8% drop. Entertainment, Food, Medical and Shopping are sensible to the disease before lockdown, and we identify these "early birds" to investigate the public reaction in the early stage of the epidemic. We further analyze the revival trends, generating four different revival patterns that correlated with the necessity of POI functions. Finally, we analyze the perseverance during the COVID-19, finding no large-scale closures compared with the tremendous visit drop. The strong resilience in Wuhan supports the rapid recovery of society. These findings are important for researchers, industries, and governments to understand the city respondence under severe epidemic, proposing better regulations to respond, control, and prevent public emergencies.
AI for Conservation
Authors: Cheng Zezhou , Maji Subhransu , Sheldon Daniel
Published: June 2021

How deep neural networks can process millions of weather radar data points to help researchers monitor continental-scale bird migration.
The protective effects of 1,3-butanediol acetoacetate diester on decompression sickness in rats
Authors: Zhang Kun , Zhang Haidong , Yi Hongjie , Huang Guoyang , Zhao Xupeng , Yu Shichong , Xu Weigang
Published: June 2021

This is the first study exploring the effects of BD-AcAc2 on DCS prevention, and it was proven to be an efficient and simple method. The role of BD-AcAc2 in increasing ppO2, anti-inflammatory and antioxidant properties was thought to be the critical mechanism in DCS prevention.
Neural adaptations to long-term resistance training: evidence for the confounding effect of muscle size on the interpretation of surface electromyography
Authors: Škarabot Jakob , Balshaw Thomas G. , Maeo Sumiaki , Massey Garry J. , Lanza Marcel B. , Maden-Wilkinson Thomas M. , Folland Jonathan P.
Published: June 2021

In a large sample of long-term resistance-trained individuals, we showed greater maximal M-wave amplitude of the elbow flexors and knee extensors compared with untrained individuals, which appears to be at least partially mediated by differences in muscle size. The lack of group differences in voluntary EMG amplitude when normalized to maximal M-wave suggests that differences in muscle morphology might impair interpretation of voluntary EMG as an index of central neural activity.
Enhanced splenic volume and contraction in elite endurance athletes
Authors: Holmström Pontus K. , Karlsson Öyvind , Lindblom Hampus , McGawley Kerry , Schagatay Erika K.
Published: June 2021

This study demonstrates that elite biathletes have larger splenic volume, apnea-induced splenic contraction, and Hb elevation compared with untrained individuals, which is likely functional to cope with high O2demands and substantial O2deficits. We believe that enhanced splenic contraction may be of importance during competitions involving cross-country skiing, to regulate circulating Hb and enhance O2-carrying capacity, which may protect [Formula: see text] and increase O2uptake.
Effect of combination inhaled therapy on ventilation distribution measured by SPECT/CT imaging in uncontrolled asthma
Authors: Rutting Sandra , Chapman David G. , Thamrin Cindy , Tang Francesca S. M. , Dame Carroll Jessica R. , Bailey Dale L. , Trifunovic Marko , Magnussen John S. , King Gregory G. , Farrow Catherine E.
Published: June 2021

This study provides insights into the mechanisms of high-dose ICS treatment in uncontrolled asthma. Ventilation defects as measured by SPECT/CT imaging, respond heterogeneously to increased ICS/LABA treatment, with improvement occurring when ventilation defects and impairment of convection-dependent small airway function are more severe. Persistent correlations between ventilation defects and measures of small airway function, suggests the potential presence of ICS non-responsive inflammation and/or remodelling.
ShipYOLO: An Enhanced Model for Ship Detection
Authors: Han Xu , Zhao Lining , Ning Yue , Hu Jingfeng
Published: June 2021

The application of ship detection for assistant intelligent ship navigation has stringent requirements for the model’s detection speed and accuracy. In response to this problem, this study uses an improved YOLO-V4 detection model (ShipYOLO) to detect ships. Compared to YOLO-V4, the model has three main improvements. Firstly, the backbone network (CSPDarknet) of YOLO-V4 is optimized. In the training process, the 3 × 3 convolution, 1 × 1 convolution, and identity parallel mode are used to replace the original feature extraction component (ResUnit) and more features are extracted. In the inference process, the branch parameters are combined to form a new backbone network named RCSPDarknet, which improves the inference speed of the model while improving the accuracy. Secondly, in order to solve the problem of missed detection of the small-scale ships, we designed a new amplified receptive field module named DSPP with dilated convolution and Max-Pooling, which improves the model’s acquisition of small-scale ship spatial information and robustness of ship target space displacement. Finally, we use the attention mechanism and Resnet’s shortcut idea to improve the feature pyramid structure (PAFPN) of YOLO-V4 and get a new feature pyramid structure named AtFPN. The structure effectively improves the model’s feature extraction effect for ships of different scales and reduces the number of model parameters, further improving the model’s inference speed and detection accuracy. In addition, we have created a ship dataset with a total of 2238 images, which is a single-category dataset. The experimental results show that ShipYOLO has the advantage of faster speed and higher accuracy even in different input sizes. Considering the input size of 320 × 320 on the PC equipped with NVIDIA 1080Ti GPU, the FPS and mAP@5 : 5:95 (mAP90) of ShipYOLO are increased by 23.7% and 13.6% (10.6%), respectively, with an input size of 320 × 320, ShipYOLO, compared to YOLO-V4.
Performance Evaluation of Waste Crumb Rubber/Silica Fume Composite Modified Pervious Concrete in Seasonal Frozen Regions
Authors: Luo Guobao , Zhao Pin , Zhang Yangpeng , Xie Zhengzhuan
Published: June 2021

The waste crumb rubber (WCR) and silica fume (SF), as industrial waste and byproduct, are widely used as additives in road construction materials, which can not only realize waste utilization and protect the environment but also reduce the consumption of building material resources. At present, most of the research has focused on the properties of concrete modified only by WCR or SF; there are few studies concentrated on composite modified concrete by the two, especially the study on pervious concrete (PC). This article aims to study the mechanical strength, deformability, and freeze‐thaw (F‐T) resistance of waste crumb rubber/silica fume composite modified pervious concrete (RSFPC). The RSFPC and control specimens were manufactured in the lab. The experiments of compressive strength, flexural strength, flexural failure strain, flexural elastic modulus, and F‐T cycles were conducted. In addition, the properties of RSFPC were compared with WCR and SF single modification PC. The results indicate that the composite modification of WCR and SF can give full play to the advantages of the two materials so that the strength property and elastic modulus of PC will not be decreased and the F‐T resistance and deformability can be greatly improved. Compared to a single modification group by WCR or SF, RSFPC has a more balanced and comprehensive performance, which will greatly expand the application of PC.
Protective Effect of Zinc Oxide and Its Association with Neutrophil Degranulation in Piglets Infected with Porcine Epidemic Diarrhea Virus
Authors: Zhang Qian , Wu Tao , Li Siyuan , Meng Yuxuan , Tan Zihan , Wu Mengjun , Yi Dan , Wang Lei , Zhao Di , Hou Yongqing
Published: June 2021

Porcine epidemic diarrhea virus (PEDV) has reemerged throughout the world in the past ten years and caused huge economic losses to the swine industry. No drugs are available to prevent or treat PEDV infection in piglets. Zinc oxide (ZnO) has been shown to reduce diarrhea. However, little is known about its role in PEDV infection. In this study, twenty‐four 7‐day‐old piglets were randomly divided into three treatment groups: control, PEDV, and ZnO+PEDV. Piglets in the ZnO+PEDV group were orally administered with 100 mg/kg·BW ZnO and then inoculated PEDV at a dose of 104.5 TCID50 (50% tissue culture infectious dose) per pig. Growth performance, histologic lesions, viral load, indicators of intestinal damage, inflammation, and oxidative stress were recorded or detected to determine the effect of ZnO on PEDV infection. And the underlying mechanisms were revealed by microarray and proteomic analyses. Results showed that ZnO administration mitigated diarrhea and the reduction of average daily weight gain induced by PEDV infection. ZnO could inhibit PEDV replication in the small intestine and colon. Both villus height and crypt depth were affected by PEDV infection in the duodenum and jejunum, which could be rescued by ZnO administration. Moreover, the activity of catalase was decreased both in plasma and intestine after PEDV infection, while increased in the intestine by ZnO administration. PEDV infection also significantly increased the concentration of H2O2 in jejunal and ileum and decreased the activity of total superoxide dismutase and glutathione peroxidase in plasma, whereas ZnO administration obviously increased the activity of total superoxide dismutase and decreased the concentration of H2O2 in the ileum. The concentrations of IL‐1β, IL‐6, and IL‐8 in the plasma were all decreased upon ZnO administration. A large number of differentially expressed genes and proteins were identified in the ileum among the three groups by microarray and proteomic analyses. Gene Ontology and Reactome pathway analyses indicated that neutrophil degranulation and nutrient metabolism were the main biological process and pathways in both PEDV infection and ZnO administration. Overall, ZnO administration could improve growth performance, intestinal redox status, morphology, and function and reduce diarrhea in PEDV‐infected piglets; ZnO could exert antiviral and anti‐inflammatory effects on PEDV‐infected piglets probably through regulating neutrophil degranulation. Our findings have important implications in piglet and infant nutrition.
Aerodynamic and Vibration Characteristics of the Micro-Octocopter at Low Reynolds Number
Authors: Zou Xiaohua , Ling Mingsheng , Zhai Wenzheng
Published: June 2021

With the development of flight technology, the need for stable aerodynamic and vibration performance of the aircraft in the civil and military fields has gradually increased. In this case, the requirements for aerodynamic and vibration characteristics of the aircraft have also been strengthened. The existing four-rotor aircraft carries limited airborne equipment and payload, while the current eight-rotor aircraft adopts a plane layout. The size of the propeller is generally fixed, including the load capacity. The upper and lower tower layout analyzed in this paper can effectively solve the problems of insufficient four-axis load and unstable aerodynamic and vibration performance of the existing eight-axis aircraft. This paper takes the miniature octorotor as the research object and studies the aerodynamic characteristics of the miniature octorotor at different low Reynolds numbers, different air pressures and thicknesses, and the lift coefficient and lift-to-drag ratio, as well as the vibration under different elastic moduli and air pressure characteristics. The research algorithm adopted in this paper is the numerical method of fluid-solid cohesion and the control equation of flow field analysis. The research results show that, with the increase in the Reynolds number within a certain range, the aerodynamic characteristics of the miniature octorotor gradually become better. When the elastic modulus is 2.5 E, the aircraft’s specific performance is that the lift increases, the critical angle of attack increases, the drag decreases, the lift-to-drag ratio increases significantly, and the angle of attack decreases. However, the transition position of the flow around the airfoil surface is getting closer to the leading edge, and its state is more likely to transition from laminar flow to turbulent flow. When the unidirectional carbon fiber-reinforced thickness is 0.2 mm and the thin arc-shaped airfoil with the convex structure has a uniform thickness of 2.5% and a uniform curvature of 4.5%, the aerodynamic and vibration characteristics of the octorotor aircraft are most beneficial to flight.
An Approach to the Geometric‐Arithmetic Index for Graphs under Transformations’ Fact over Pendent Paths
Authors: Asif Muhammad , Almohamedh Hamad , Hussain Muhammad , Alhamed Khalid M , Almutairi Abdulrazaq A. , Almotairi Sultan
Published: June 2021

Graph theory is a dynamic tool for designing and modeling of an interconnection system by a graph. The vertices of such graph are processor nodes and edges are the connections between these processors nodes. The topology of a system decides its best use. Geometric‐arithmetic index is one of the most studied graph invariant to characterize the topological aspects of underlying interconnection networks or graphs. Transformation over graph is also an important tool to define new network of their own choice in computer science. In this work, we discuss transformed family of graphs. Let be the connected graph comprises by k number of pendent path attached with fully connected vertices of the n‐vertex connected graph Γ. Let and be the transformed graphs under the fact of transformations Aα and , 0 ≤ α ≤ l, 0 ≤ β ≤ k − 1, respectively. In this work, we obtained new inequalities for the graph family and transformed graphs and which involve GA(Γ). The presence of GA(Γ) makes the inequalities more general than all those which were previously defined for the GA index. Furthermore, we characterize extremal graphs which make the inequalities tight.
CYP2J2 Is a Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Kidney Renal Clear Cell Carcinoma
Authors: Zou Xiong , Mo Zengnan
Published: June 2021

Cytochrome P450 family 2 subfamily J member 2 (CYP2J2), a member of the monooxygenase cytochrome P450 (CYP) family and the only member of the human CYP2J subfamily, has many functions, including regulation of oxidative stress, inflammation, apoptosis, and immune responses. However, its role in cancer development has not been clearly elucidated. In this study, expression levels of CYP2J2 in various cancer types were determined using the Oncomine, the Gene Expression Profiling Interactive Analysis (GEIPA), DriverDBv3, UALCAN, and Tumor Immune Estimation Resource (TIMER) databases. The prognostic value of CYP2J2 for KIRC was analyzed using GEPIA, UALCAN, OSkirc, and DriverDBv3 databases. We evaluated the expression levels of CYP2J2 transcript, protein, and promoter methylation at different clinical characteristics in KIRC through the UALCAN database. Simultaneously, CYP2J2 network‐related functions were evaluated using the GeneMANIA interactive tool while the biological processes involved in CYP2J2 and its interactive genes were investigated through Metascape and FunRich. Then, we used TIMER to determine the correlation between CYP2J2 expression levels and immune infiltration levels in KIRC. In KIRC, the CYP2J2 gene, RNA, and protein were found to be overexpressed. However, the methylation level of CYP2J2 promoter in KIRC was lower than in normal tissues. Surprisingly, elevated expression levels of CYP2J2 exhibited better prognostic outcomes in KIRC. Evaluation of protein‐protein interaction networks and biological processes revealed that CYP2J2 was principally involved in immune responses, apoptosis, and other metabolic processes. Moreover, we found that the expression levels of CYP2J2 were positively correlated with infiltration levels of B cells, CD8 + T cells, neutrophils, and dendritic cells in KIRC. Therefore, we speculated that the overexpression of CYP2J2 prolonged the survival outcome of KIRC patients, which may be related to the change of tumor immune microenvironment. Moreover, all these new understandings of CYP2J2 may provide important value for the early diagnosis and new targeted drug therapy of KIRC.
Research on Intelligent Recognition and Classification Algorithm of Music Emotion in Complex System of Music Performance
Authors: Wang Daliang , Guo Xiaowen
Published: June 2021

In the complex system of music performance, there are differences in the expression of music emotions by listeners, so it is of great significance to study the classification of different emotions under different audio signals. In this paper, the research of human emotional intelligence recognition and classification algorithm in the complex system of music performance is proposed. Through the recognition of SVM, KNN, ANN, and ID3 classifiers, the accuracy of a single classifier is compared, and then the four classifiers are combined to compare the classification accuracy of audio signals before and after preprocessing. The results show that the accuracy of SVM and ANN fusion is the highest. Finally, recall and F1 are comprehensively compared in the fusion algorithm, and the fusion classification effect of SVM and ANN is better than that of the algorithm model.
Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki‐67 Proliferation Index
Authors: Guo Yuan , Kong Qing-cong , Li Li-qi , Tang Wen-jie , Zhang Wan-li , Ning Guan-yuan , Xue Jun , Zhou Qian-wei , Liang Ying-ying , Wu Mei , Jiang Xin-qing
Published: June 2021

Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki‐67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki‐67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age (P < 0.001) and lesion size (P = 0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER‐2) status (both P = 0.001) and estrogen receptor (ER)/progesterone receptor (PR) status (P = 0.020 and P = 0.041, respectively). Among all breast cancer lesions, 35 tumours in the low‐proliferation group (Ki − 67 < 14%) and 70 tumours in the high‐proliferation group (Ki − 67 ≥ 14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki‐67 status (P = 0.007 and P < 0.001, respectively), and there were weak correlations between ADC entropy (r = 0.383) and skewness (r = 0.209) and the Ki‐67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.
A Case of Spontaneous Coronary Artery Dissection in a Patient with Severe Anorexia Nervosa
Authors: O’Neil Jessica , Mazumder Soumyaa , Sanborn Danita Yoerger , Wu Samantha
Published: June 2021

There are a variety of cardiac complications of anorexia nervosa including arrythmias, valvopathies, and myopathies. Spontaneous coronary artery dissection (SCAD) has not been widely reported among this patient population. This case report describes a middle-aged female with severe anorexia nervosa, who presented after being found unconscious, and was later diagnosed with SCAD. A literature review revealed one previous case of SCAD in a patient with anorexia nervosa and prompted a discussion of a series of possible predisposing factors for SCAD in this patient population. Patients with anorexia nervosa may be at increased risk for SCAD due to their complex nutritional and endocrine imbalances. This case highlights a possible underdiagnosed cardiac complication of anorexia nervosa.