bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and determinants of insomnia among patients living with asthma in Northwest Ethiopian University specialised hospitals: Multicentre cross-sectional study
Authors: Belachew Eyayaw Ashete , Sendekie Ashenafi Kibret , Ayele Emneteab Mesfin , Netere Adeladlew Kassie
Published: November 2022

Objective

The study was aimed to determine the prevalence and contributing factors of insomnia among patients with bronchial asthma.

Design

A multicentre cross-sectional survey was used.

Setting

This study was carried out from January to March 2022 in three university comprehensive specialised hospitals in Northwest Ethiopia.

Participants

422 patients with bronchial asthma were approached of which 93.8% completed the survey.

Outcomes

The degree of asthma control and the severity of insomnia were evaluated using the Asthma Control Test and Insomnia Severity Index (ISI), respectively. The characteristics of the participants were presented, arranged and summarised using descriptive statistical analysis, and correlations between predictors and outcome variables were examined using logistic regression. The cut-off point was a p value of 0.05.

Results

Participants’ ages ranged from 33.6 to 65.2 years on average. Just under three-fourths (71.4%) of the participants had at least one episode of insomnia as per the ISI measurement (score ≥10). The odds of insomnia episodes were about 5.4 and 1.93 times higher in patients with uncontrolled asthma and partially controlled asthma status, with adjusted OR (AOR)=5.4 (95% CI 4.4 to 6.79, p<0.001) and AOR=1.93 (95% CI 1.21 to 4.11, p<0.001), respectively.

Conclusion

Insomnia episodes were substantially higher in bronchial patients with asthma. Insomnia is accompanied by asthma severity, and uncontrolled asthma and partially controlled asthma status are the two most determining factors for experiencing sleep disturbance. Furthermore, a prospective follow-up study must determine the real association found between insomnia and asthma control.
Why might medical student empathy change throughout medical school? Protocol for a systematic review and thematic synthesis of qualitative studies
Authors: Howick Jeremy , Ahmed Ahmed , Dudko Maya , Feng Shi Nan , Nockels Keith , Alluri Namitha , Winter Rachel , Holland Richard
Published: November 2022

Introduction

Several studies suggest that medical student empathy declines throughout medical school. However, no studies have systematically investigated why. The objective of our proposed review is to conduct a systematic review and thematic synthesis of qualitative studies investigating the reasons empathy may change throughout medical school.

Methods and analysis

This systematic review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We have searched MEDLINE, Scopus, CINAHL, ERIC and APA PsycINFO for relevant studies. We will also search reference lists of included studies and contact experts to identify additional studies. We will include any qualitative study investigating the reasons why empathy changes throughout medical school. We will use the Joanna Briggs Institute tool to evaluate the risk of bias in the included studies. We will use thematic analysis to synthesise our results. For all included studies, we will summarise the main characteristics including the number of participants, medical school year, country and gender. In our discussion, we will summarise the limitations of the evidence (including the risk of bias and inconsistency), and provide a general interpretation of the results and important implications.

Ethics and dissemination

This study will not require ethical approval since no original data will be collected. The results of this review will be published through peer-reviewed publications and conference presentations. Additionally, this review will inform changes to the enhanced empathy curriculum at the Leicester Medical School.
The FCC-ee vacuum system, from conceptual to prototyping
Authors: Kersevan Roberto
Published: November 2022

The FCC-ee is a very challenging accelerator project from the point of view of vacuum. Apart from the sheer size of the machine, a twin-ring of 100 km circumference, the vacuum system design must be capable of dealing with the low-energy 45.6 GeV, high-current version of the machine (the Z-pole) as well as the higher energy, lower current versions. The main difficulty is related to the very much different synchrotron radiation (SR) spectra of the Z-pole vs the other energies, in particular the ttbar at 182.5 GeV. The critical energy of the SR spectrum of the Z-pole is 19.5 keV, while the ttbar exceeds 1.2 MeV. It is particularly challenging in terms of shielding the beryllium chamber in the detectors, for the Machine Detector Interface (MDI) area. We discuss the evolution of the vacuum system design for the arc sections, and some new ideas on NEG-coating, SR absorbers, and pumping system, with the aim to build prototypes soon, in the framework of the FCC Innovation Study program. The design of the vacuum hardware depends on the choices made for the magnets, and the required shielding from high-energy radiation generated by the circulating beam interacting with the residual gas and the interaction of the intense SR fans with the photon. There is also an important collaboration with the engineering integration of the vacuum system in the tunnel, particularly considering the full-energy booster injector, which is not detailed here. We also briefly describe the raytracing montecarlo modelling efforts carried out in the MDI area, and its pumping configuration.
The structure of symmetric tensor powers of composition algebras
Authors: Razon Aharon
Published: November 2022

Let [Formula: see text] be a composition algebra which is either the Hamilton quaternion algebra [Formula: see text] or the Cayley octonion algebra [Formula: see text] over [Formula: see text]. In a previous work, the nth symmetric power [Formula: see text] of [Formula: see text] is shown to be a direct sum of central simple algebras, corresponding to the partitions of [Formula: see text] of length [Formula: see text], such that the component corresponding to the partition [Formula: see text] is isomorphic to the component [Formula: see text] of [Formula: see text] corresponding to the partition [Formula: see text] of [Formula: see text]. In this work, we study the building blocks [Formula: see text] of these decompositions. We show that the “local” structure of [Formula: see text], i.e. the complex-like subfields of [Formula: see text], determine both the complement of [Formula: see text] in [Formula: see text] and the trace map of [Formula: see text], induced from the trace map of [Formula: see text]. We also derive a recursive trace formula on the [Formula: see text]’s. We use the “local-global” results to define positive definite symmetric bilinear forms on the vector space [Formula: see text], which has a natural structure of a commutative and associative algebra. Finally, the structure of the central simple algebra [Formula: see text] is described.
Design and Performance Analysis of Zinc Oxide Thin Film Transistor (ZnO2TFT) with High-k Dielectric Materials
Authors: Kaur Parminder , Raj Balwinder , Gill Sandeep Singh
Published: November 2022

ZnO has been extensively used as oxide in the thin film electronics industry because of its performance advantages such as electrical and optical properties. This study represents the design and optimization of the ZnO thin film transistor (TFT). The characteristics of the device are studied using the software Silvaco TCAD ATLAS. The improvement in the performance of the device has been observed in optimizing dielectric layer thickness ([Formula: see text]). Further SiO2oxide layer is replaced with the high-[Formula: see text] dielectric to improve its performance. The use of high-[Formula: see text] dielectric gives the concept of equivalent oxide thickness (EOT) in which physical thickness (PT) of the dielectric layer is increased without increasing electric thickness (effective thickness), which improves the reliability of the device. The electrical parameters extracted for the low-[Formula: see text] SiO2 ([Formula: see text]) at thickness (TSiO2) 50[Formula: see text]nm are [Formula: see text][Formula: see text]A, [Formula: see text][Formula: see text]A, [Formula: see text], [Formula: see text][Formula: see text]V/decade, [Formula: see text][Formula: see text]V. The high performance of the device has been achieved using Al2O3and HfO2as the dielectric material.
Oasis
: Controlling Data Migration in Expansion of Object-based Storage Systems
Authors: Zhang Yiming , Wang Li , Gai Shun , Ke Qiwen , Li Wenhao , Song Zhenlong , Xue Guangtao , Shu Jiwu
Published: November 2022

Object-based storage systems have been widely used for various scenarios such as file storage, block storage, blob (e.g., large videos) storage, and so on, where the data is placed among a large number of object storage devices (OSDs). Data placement is critical for the scalability of decentralized object-based storage systems. The state-of-the-art CRUSH placement method is a decentralized algorithm that deterministically places object replicas onto storage devices without relying on a central directory. While enjoying the benefits of decentralization such as high scalability, robustness, and performance, CRUSH-based storage systems suffer from
uncontrolled
data migration when expanding the capacity of the storage clusters (i.e., adding new OSDs), which is determined by the nature of CRUSH and will cause significant performance degradation when the expansion is nontrivial.

This article presents
MapX
, a novel extension to CRUSH that uses an extra time-dimension mapping (from object creation times to cluster expansion times) for controlling data migration after cluster expansions. Each expansion is viewed as a new layer of the CRUSH map represented by a virtual node beneath the CRUSH root.
MapX
controls the mapping from objects onto layers by manipulating the timestamps of the intermediate placement groups (PGs).
MapX
is applicable to a large variety of object-based storage scenarios where object timestamps can be maintained as higher-level metadata. We have applied
MapX
to the state-of-the-art Ceph-RBD (RADOS Block Device) to implement a migration-controllable, decentralized object-based block store (called
Oasis
).
Oasis
extends the RBD metadata structure to maintain and retrieve approximate object creation times (for migration control) at the granularity of expansion layers. Experimental results show that the
MapX
-based
Oasis
block store outperforms the CRUSH-based Ceph-RBD (which is busy in migrating objects after expansions) by 3.17× ∼ 4.31× in tail latency, and 76.3% (respectively, 83.8%) in IOPS for reads (respectively, writes).
End-to-end I/O Monitoring on Leading Supercomputers
Authors: Yang Bin , Xue Wei , Zhang Tianyu , Liu Shichao , Ma Xiaosong , Wang Xiyang , Liu Weiguo
Published: November 2022

This paper offers a solution to overcome the complexities of production system I/O performance monitoring. We present Beacon, an end-to-end I/O resource monitoring and diagnosis system for the 40960-node Sunway TaihuLight supercomputer, currently the fourth-ranked supercomputer in the world. Beacon simultaneously collects and correlates I/O tracing/profiling data from all the compute nodes, forwarding nodes, storage nodes, and metadata servers. With mechanisms such as aggressive online and offline trace compression and distributed caching/storage, it delivers scalable, low-overhead, and sustainable I/O diagnosis under production use. With Beacon’s deployment on TaihuLight for more than three years, we demonstrate Beacon’s effectiveness with real-world use cases for I/O performance issue identification and diagnosis. It has already successfully helped center administrators identify obscure design or configuration flaws, system anomaly occurrences, I/O performance interference, and resource under- or over-provisioning problems. Several of the exposed problems have already been fixed, with others being currently addressed. Encouraged by Beacon’s success in I/O monitoring, we extend it to monitor interconnection networks, which is another contention point on supercomputers. In addition, we demonstrate Beacon’s generality by extending it to other supercomputers. Both Beacon codes and part of collected monitoring data are released.

1
InDe: An Inline Data Deduplication Approach via Adaptive Detection of Valid Container Utilization
Authors: Lin Lifang , Deng Yuhui , Zhou Yi , Zhu Yifeng
Published: November 2022

Inline deduplication removes redundant data in real-time as data is being sent to the storage system. However, it causes data fragmentation: logically consecutive chunks are physically scattered across various containers after data deduplication. Many rewrite algorithms aim to alleviate the performance degradation due to fragmentation by rewriting fragmented duplicate chunks as unique chunks into new containers. Unfortunately, these algorithms determine whether a chunk is fragmented based on a simple pre-set fixed value, ignoring the variance of data characteristics between data segments. Accordingly, when backups are restored, they often fail to select an appropriate set of old containers for rewrite, generating a substantial number of invalid chunks in retrieved containers.

To address this issue, we propose an inline deduplication approach for storage systems, called
InDe
, which uses a greedy algorithm to detect valid container utilization and dynamically adjusts the number of old container references in each segment. InDe fully leverages the distribution of duplicated chunks to improve the restore performance while maintaining high backup performance. We define an effectiveness metric,
valid container referenced counts (VCRC)
, to identify appropriate containers for the rewrite. We design a rewrite algorithm
F-greedy
that detects valid container utilization to rewrite low-VCRC containers. According to the VCRC distribution of containers, F-greedy dynamically adjusts the number of old container references to only share duplicate chunks with high-utilization containers for each segment, thereby improving the restore speed. To take full advantage of the above features, we further propose another rewrite algorithm called
F-greedy+
based on adaptive interval detection of valid container utilization. F-greedy+ makes a more accurate estimation of the valid utilization of old containers by detecting trends of VCRC’s change in two directions and selecting referenced containers in the global scope. We quantitatively evaluate InDe using three real-world backup workloads. The experimental results show that compared with two state-of-the-art algorithms (Capping and SMR), our scheme improves the restore speed by 1.3×–2.4× while achieving almost the same backup performance.
Extending and Programming the NVMe I/O Determinism Interface for Flash Arrays
Authors: Li Huaicheng , Putra Martin L. , Shi Ronald , Kurnia Fadhil I. , Lin Xing , Do Jaeyoung , Kistijantoro Achmad Imam , Ganger Gregory R. , Gunawi Haryadi S.
Published: November 2022

Predictable latency on flash storage is a long-pursuit goal, yet unpredictability stays due to the unavoidable disturbance from many well-known SSD internal activities. To combat this issue, the recent NVMe IO Determinism (IOD) interface advocates host-level controls to SSD internal management tasks. Although promising, challenges remain on how to exploit it for truly predictable performance.

We present
IODA
,

1

an I/O deterministic flash array design built on top of small but powerful extensions to the IOD interface for easy deployment.
IODA
exploits data redundancy in the context of IOD for a strong latency predictability contract. In
IODA
, SSDs are expected to quickly fail an I/O on purpose to allow predictable I/Os through proactive data reconstruction. In the case of concurrent internal operations,
IODA
introduces busy remaining time exposure and predictable-latency-window formulation to guarantee predictable data reconstructions. Overall,
IODA
only adds five new fields to the NVMe interface and a small modification in the flash firmware while keeping most of the complexity in the host OS. Our evaluation shows that
IODA
improves the 95–99.99
th
latencies by up to 75×.
IODA
is also the nearest to the ideal, no disturbance case compared to seven state-of-the-art preemption, suspension, GC coordination, partitioning, tiny-tail flash controller, prediction, and proactive approaches.
Route
: Roads Not Taken in UI Testing
Authors: Lin Jun-Wei , Salehnamadi Navid , Malek Sam
Published: November 2022

Core features (functionalities) of an app can often be accessed and invoked in several ways, i.e., through alternative sequences of user-interface (UI) interactions. Given the manual effort of writing tests, developers often only consider the typical way of invoking features when creating the tests (i.e., the “sunny day scenario”). However, the alternative ways of invoking a feature are as likely to be faulty. These faults would go undetected without proper tests. To reduce the manual effort of creating UI tests and help developers more thoroughly examine the features of apps, we present
Route
, an automated tool for feature-based UI test augmentation for Android apps.
Route
first takes a UI test and the app under test as input. It then applies novel heuristics to find additional high-quality UI tests, consisting of both inputs and assertions, that verify the same feature as the original test in alternative ways. Application of
Route
on several dozen tests for popular apps on Google Play shows that for 96% of the existing tests,
Route
was able to generate at least one alternative test. Moreover, the fault detection effectiveness of augmented test suites in our experiments showed substantial improvements of up to 39% over the original test suites.
Employee Green Behavior as the Core of Environmentally Sustainable Organizations
Authors: Zacher Hannes , Rudolph Cort W. , Katz Ian M.
Published: November 2022

Environmental sustainability has become an ethical and strategic imperative for organizations, and more and more employees are interested, encouraged, or instructed to act in environmentally sustainable ways. Consequently, organizational scholars have increasingly studied individual-level antecedents of employee pro-environmental or employee green behavior (EGB). We argue that, to advance this literature and to inform effective interventions, research should investigate how EGB, as a compound performance domain, is associated with antecedents and consequences at multiple levels (i.e., individual, team, work context, organization, society). Accordingly, we pursue three interrelated goals with this review. We first present a comprehensive review of research on EGB, including definitions, theoretical frameworks, methodological approaches, and empirical findings. Second, we develop an integrative conceptual model of EGB as the core of organizational environmental sustainability. Third, we conclude with recommendations for future theory development and methodological improvements, as well as practical implications for employees, leaders, and human resource management.
Job Demands–Resources Theory: Ten Years Later
Authors: Bakker Arnold B. , Demerouti Evangelia , Sanz-Vergel Ana
Published: November 2022

Burnout refers to a work-related state of exhaustion and a sense of cynicism. In contrast, work engagement is a positive motivational state of vigor, dedication, and absorption. In this article, we discuss the concepts of burnout and work engagement and review their antecedents and consequences. We look back at our inaugural Annual Reviews article ( Bakker et al. 2014 ) and highlight new empirical findings and theoretical innovations in relationship to job demands–resources (JD-R) theory. We discuss four major innovations of the past decade, namely ( a) the person × situation approach of JD-R, ( b) multilevel JD-R theory, ( c) new proactive approaches in JD-R theory, and ( d) the work–home resources model. After discussing practical implications, we elaborate on more opportunities for future research, including JD-R interventions, team-level approaches, and demands and resources from other life domains.
Statistical Data Privacy: A Song of Privacy and Utility
Authors: Slavković Aleksandra , Seeman Jeremy
Published: November 2022

To quantify trade-offs between increasing demand for open data sharing and concerns about sensitive information disclosure, statistical data privacy (SDP) methodology analyzes data release mechanisms that sanitize outputs based on confidential data. Two dominant frameworks exist: statistical disclosure control (SDC) and the more recent differential privacy (DP). Despite framing differences, both SDC and DP share the same statistical problems at their core. For inference problems, either we may design optimal release mechanisms and associated estimators that satisfy bounds on disclosure risk measures, or we may adjust existing sanitized output to create new statistically valid and optimal estimators. Regardless of design or adjustment, in evaluating risk and utility, valid statistical inferences from mechanism outputs require uncertainty quantification that accounts for the effect of the sanitization mechanism that introduces bias and/or variance. In this review, we discuss the statistical foundations common to both SDC and DP, highlight major developments in SDP, and present exciting open research problems in private inference.
Innovation Diffusion Processes: Concepts, Models, and Predictions
Authors: Guidolin Mariangela , Manfredi Piero
Published: November 2022

Innovation diffusion processes have attracted considerable research attention for their interdisciplinary character, which combines theories and concepts from disciplines such as mathematics, physics, statistics, social sciences, marketing, economics, and technological forecasting. The formal representation of innovation diffusion processes historically used epidemic models borrowed from biology, departing from the logistic equation, under the hypothesis that an innovation spreads in a social system through communication between people like an epidemic through contagion. This review integrates basic innovation diffusion models built upon the Bass model, primarily from the marketing literature, with a number of ideas from the epidemiological literature in order to offer a different perspective on innovation diffusion by focusing on critical diffusions, which are key for the progress of human communities. The article analyzes three key issues: barriers to diffusion, centrality of word-of-mouth, and the management of policy interventions to assist beneficial diffusions and to prevent harmful ones. We focus on deterministic innovation diffusion models described by ordinary differential equations.
[Retracted] Correlation Analysis of Inflammatory Markers CRP and IL‐6 and Postoperative Delirium (POD) in Elderly Patients: A Meta‐Analysis of Observational Studies
Authors: Huang Xiaoling , Li Lanyang , Feng Qiuping
Published: November 2022

Background. Postoperative delirium (POD) is very common in the elderly surgical population, and its occurrence is associated with multiple factors such as preoperative, intraoperative, and postoperative factors, and the increase of serum inflammatory markers such as C‐reactive protein (CRP) and interleukin‐6 (IL‐6) is considered to be associated with the occurrence of POD, but the results of multiple studies are inconsistent. In this study, we investigated the correlation between inflammatory markers CRP and IL‐6 and POD in elderly patients by literature search and meta‐analysis. Methods. We searched PubMed, Web of Science, the Cochrane library, Embase, Ovid, and Springer Link for cohort studies or case‐control studies that investigated the factors involved in the occurrence of POD, used the Newcastle‐Ottawa Scale (NOS) to assess the quality of the selected literature, and combined the differences in serum CRP and IL‐6 levels between POD and non‐POD patients after surgery to evaluate the predictive value of CRP and IL‐6 for the occurrence of POD. Results. This research comprised 16 papers for quantitative analysis, with a total of 2967 patients, 758 with POD and 2209 with non‐POD. There were 16 cohort studies (100%) and 0 case‐control studies (0%) across all the collected literatures; there were 15 prospective cohort studies and 1 retrospective cohort research. A meta‐analysis revealed a statistically significant difference in serum IL‐6 levels between POD patients after surgery and non‐POD patients [MD = 115.68, 95% CI (25.70, 206.66), Z = 2.52, P = 0.012], as well as a statistically significant difference in serum CRP levels [MD = 27.67, 95% CI (12.77, 42.58), Z = 3.64, P = 0.0003]. Discussion. Early after surgery, serum IL‐6 and CRP levels were considerably higher in POD patients than in non‐POD patients, indicating that early serum inflammatory variables are likely to be predictors of POD. After surgery, the levels of the aforementioned inflammatory factors should be actively monitored to forecast the emergence of delirium, and active treatment should be used to limit the creation and release of the aforementioned inflammatory factors.
Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis
Authors: Yang Hairuo
Published: November 2022

Under the background of the gradual development and popularization of mobile Internet information technology, this paper realizes network public opinion monitoring and emotion analysis based on the deep learning method, aiming at the research needs of people’s ideological changes and emotional trends. Aiming at the shortcomings of sentiment dictionaries or machine learning methods in sentiment analysis tasks, this paper builds a sentiment classification model based on deep learning methods. First, the current main text preprocessing methods are introduced, and then a sentiment classification model, BCBL, is proposed, combining BERT, CNN, and Bi LSTM. Compared with traditional models, BCBL can better complete text sentiment classification tasks on standard datasets. Next, in view of the problem that BCBL does not consider the distribution of vocabulary weights, an attention mechanism is introduced to improve BCBL, and then the BCBL-Att model is proposed. Set up multiple sets of comparative experiments again and find that the classification effect and overall performance of BCBL-Att on standard datasets are better than BCBL, indicating that BCBL-Att has more advantages in text sentiment classification tasks.
Activation of Delta-Opioid Receptor Protects ARPE19 Cells against Oxygen-Glucose Deprivation/Reoxygenation-Induced Necroptosis and Apoptosis by Inhibiting the Release of TNF-α
Authors: Guo Runjie , Chen Ping , Fu Tiantian , Zhang Ren , Zhu Yuan , Jin Nange , Xu Hong , Xia Yong , Tian Xuesong
Published: November 2022

Purpose. Retinal ischemia–reperfusion injury (RIRI) is the basis of the pathology that leads to many retinal diseases and induces necroptosis and apoptosis. Tumor necrosis factor-α (TNF-α) is critically involved in necroptosis and apoptosis. Delta-opioid receptor (DOR) activation inhibits TNF-α release in our previous studies, it might prevent necroptosis and apoptosis by inhibiting the release of TNF-α. However, the role of TNF-α and DOR in necroptosis and apoptosis of retinal pigment epithelial (RPE) cells remains largely unknown. Here, we explored the mechanisms of TNF-α and DOR in necroptosis and apoptosis using an oxygen-glucose deprivation/reoxygenation (OGD/R) model of adult retinal pigment epithelial cell line-19 (ARPE19) cells. Materials and Methods. ARPE19 cells were exposed to OGD/R conditions to mimic RIRI in vitro. Cell viability was quantified using the Cell Counting Kit-8 (CCK-8) assay. Morphological changes were observed by inverted microscopy. TNF-α protein levels in cell lysates were measured by enzyme-linked immunosorbent assay (ELISA). The DOR agonist TAN-67 and antagonist naltrindole (NTI) were used to pretreat cells for 1 or 2 hours before OGD24/R36 administration. Calcein acetoxymethylester/propidium iodide (Calcein-AM/PI) and Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining were used to detect necroptotic and apoptotic ARPE19 cells, respectively. The protein expression of DOR, p-RIP1 (RIP1), p-RIP3 (RIP3), p-MLKL (MLKL), and cleaved Caspase3 (Caspase3) was measured by western blotting. Results. OGD severely damaged ARPE19 cells. Prolonged reoxygenation significantly increased TNF-α level and decreased DOR expression in ARPE19 cells. Pretreatment with the DOR agonist TAN-67 (10 µM) significantly improved ARPE19 cell viability after OGD24/R36 by reducing the number of necroptotic and apoptotic cells. Furthermore, DOR activation significantly inhibited TNF-α release and suppressed the expression of proteins related to necroptosis and apoptosis, including p-RIP1, p-RIP3, p-MLKL, and cleaved Caspase3, after OGD24/R36. This effect was reversed by the DOR antagonist NTI. Conclusion. These results strongly suggest that DOR activation inhibits necroptosis and apoptosis by decreasing TNF-α release, leading to the prevention of OGD/R-induced injury in ARPE19 cells. This study provides an innovative idea for clinical treatment strategies for retinal damage and vision loss due to RIRI.
Multidisciplinary Reliability Design Considering Hybrid Uncertainty Incorporating Deep Learning
Authors: Bi Wei , Chen Wenhua , Pan Jun
Published: November 2022

Multidisciplinary reliability design optimization is considered an effective method for solving complex product design optimization problems under the influence of uncertainty factors; however, the high computational cost seriously affects its application in practice. As an important part of multidisciplinary reliability design optimization, multidisciplinary reliability analysis plays a direct leading role in its computational efficiency. At present, multidisciplinary reliability analysis under mixed uncertainty is still nested or sequential execution mode, which leads to the problem of poor disciplinary autonomy and inefficiency in the reliability analysis of complex products. To this end, a multidisciplinary reliability assessment method integrating deep neural networks and probabilistic computational models under mixed uncertainty is proposed for the problem of multidisciplinary reliability analysis under mixed uncertainty. The method considers the stochastic-interval-fuzzy uncertainty, decouples the nested multidisciplinary probability analysis, multidisciplinary likelihood analysis, and multidisciplinary interval analysis, uses deep neural networks to extract subdisciplinary high-dimensional features, and fuses them with probabilistic computational models. Moreover, the whole system is divided into several independent subsystems, then the collected reliability data are classified, and the fault data are attributed to each subsystem. Meanwhile, the environmental conditions of the system are considered, and the corresponding environmental factors are added as input neurons along with each subsystem. In this paper, the effectiveness of the proposed method is verified on numerical calculations and real inverter power failure data.
Region‐Based Segmentation and Classification for Ovarian Cancer Detection Using Convolution Neural Network
Authors: Hema L. K. , Manikandan R. , Alhomrani Majid , Pradeep N. , Alamri Abdulhakeem S. , Sharma Shakti , Alhassan Musah
Published: November 2022

Ovarian cancer is a serious sickness for elderly women. According to data, it is the seventh leading cause of death in women as well as the fifth most frequent disease worldwide. Many researchers classified ovarian cancer using Artificial Neural Networks (ANNs). Doctors consider classification accuracy to be an important aspect of making decisions. Doctors consider improved classification accuracy for providing proper treatment. Early and precise diagnosis lowers mortality rates and saves lives. On basis of ROI (region of interest) segmentation, this research presents a novel annotated ovarian image classification utilizing FaRe‐ConvNN (rapid region‐based Convolutional neural network). The input photos were divided into three categories: epithelial, germ, and stroma cells. This image is segmented as well as preprocessed. After that, FaRe‐ConvNN is used to perform the annotation procedure. For region‐based classification, the method compares manually annotated features as well as trained feature in FaRe‐ConvNN. This will aid in the analysis of higher accuracy in disease identification, as human annotation has lesser accuracy in previous studies; therefore, this effort will empirically prove that ML classification will provide higher accuracy. Classification is done using a combination of SVC and Gaussian NB classifiers after the region‐based training in FaRe‐ConvNN. The ensemble technique was employed in feature classification due to better data indexing. To diagnose ovarian cancer, the simulation provides an accurate portion of the input image. FaRe‐ConvNN has a precision value of more than 95%, SVC has a precision value of 95.96%, and Gaussian NB has a precision value of 97.7%, with FR‐CNN enhancing precision in Gaussian NB. For recall/sensitivity, SVC is 94.31 percent and Gaussian NB is 97.7 percent, while for specificity, SVC is 97.39 percent and Gaussian NB is 98.69 percent using FaRe‐ConvNN.
Particle Flow Analysis of Acoustic Emission Features of Rock under Rock Burst Stress Path
Authors: Wang Yalei , Xu Jinming
Published: November 2022

The AE (acoustic emission) features could reflect the process of fracture initiation and propagation in rocks. Taking Lalin railway tunnel granite as an example, a three-dimensional particle flow numerical model of rock was established based on the PFC (particle flow code). The mechanical properties between particles were simulated using parallel bond. The rock burst stress path was simulated using the movement of the wall in the particle flow model. The results of uniaxial compression tests in a laboratory were used to calibrate the mesoscale mechanical parameters of the particle flow model. AE features of rock deformation and failure under different confining pressures were then studied. It shows that the unloading direction of rock may produce strong dilatation deformation during rock burst; with the increase of confining pressure, the more obvious dilatation deformation and the more possibility of serious rock burst to occur; the unloading failure of rock reveals that rock burst is a mixed failure of tensile and shear, and the tensile cracks account for about 70%; the number of AE events of rock unloading failure occur at the top and bottom of the rock first and then expand rapidly to the middle part until the rock is completely destroyed; in the process of rock burst, AE rupture strength is relatively concentrated, the number of AE events surge obviously, and the number of AE events in surge period account for more than 80% of all AE events. The results presented herein may be referable in analyzing the mechanism of rock burst.
Analysis of Business Environment and Medical Insurance Coverage Rates in the Destination of China’s Migrant Population: Based on Geographically and Temporally Weighted Regression Model for Panel Data
Authors: Liu Yang , Chen Xiaoyu , Zhang Yujie
Published: November 2022

Health risk is an important issue in the process of population spatial mobility, and it is also an important issue in the process of urbanization in China. Using the dynamic monitoring data of China’s migrant population and 31 provincial business environment data from 2011 to 2018, this study systematically investigated the spatial distribution and evolution characteristics of the migrant population’s participation in medical insurance in the destination areas and combined it with the Geographically and Temporally Weighted Regression Model for Panel Data (PGTWR) to analyze the impact of the regional business environment on the medical insurance coverage rate of the inflow area. The results are as follows: first, the spatial pattern of the insurance coverage rate is high in Eastern China and low in Western China. The areas with high insurance coverage rates are mainly distributed in the three major economic circles of China and provinces such as Shandong and Xinjiang. Second, there is significant spatial autocorrelation in the coverage rate, which shows that cities with high participation rates tend to form agglomeration areas in geographical space, and so do cities with low participation rates. The coverage rate of the popular areas is scattered, while the unpopular areas are concentrated. Third, the estimation results of the Geographically and Temporally Weighted Regression Model for Panel Data show that the macroeconomic and infrastructure indicators in the business environment have a greater impact on the insurance rate, while the impact of policy environment indicators is relatively weak. However, the overall improvement of the business environment can significantly improve the probability of the migrant population participating in medical insurance in the inflow area.
Serum Metabolomics of Benign Essential Blepharospasm Using Liquid Chromatography and Orbitrap Mass Spectrometry
Authors: Zhao Han , Wang Wushuang , Lin Tong , Gong Lan
Published: November 2022

Background. Benign essential blepharospasm (BEB) is a form of focal dystonia that causes excessive involuntary spasms of the eyelids. Currently, the pathogenesis of BEB remains unclear. This study is aimed at investigating the serum metabolites profiles in patients with BEB and healthy control and to identify the mechanism and biomarkers of this disease. Methods. 30 patients with BEB and 33 healthy controls were recruited for this study. We conducted the quantitative and nontargeted metabolomics analysis of the serum samples from 63 subjects by using liquid chromatography and Orbitrap mass spectrometry (LC-Orbitrap MS). Multivariate statistical analysis was performed to detect and identify different metabolites between the two groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and receiver operating characteristic (ROC) curve analysis of the altered metabolites were performed. Results. A total of 134 metabolites were found and identified. The metabolites belonged to several metabolic pathways including phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, linoleic acid metabolism, tryptophan metabolism, aminoacyl-tRNA biosynthesis, sphingolipid metabolism, glycosphingolipid biosynthesis, leucine and isoleucine biosynthesis, and vitamin B6 metabolism. Eight metabolites were identified as the potential biomarkers. Conclusions. These results demonstrated that serum metabolic profiling of BEB patients was significantly different from healthy controls based on LC-Orbitrap MS. Besides, metabolomics might provide useful information for a better understanding of BEB.
Low-Dose ACTH Stimulation Test in Obesity: A Randomized Dose Assessment
Authors: Mancillas-Adame Leonardo G. , Sánchez-García Adriana , Rodriguez-Gutierrez Rene , Gonzalez-Velazquez Camilo , Lavalle-Gonzalez Fernando Javier , Zuñiga-Hernandez Jorge A. , Rios-Ortega Adriana Gabriela , González-González José Gerardo
Published: November 2022

Background. The short cosyntropin test is widely used for adrenal insufficiency screening and diagnosis. Lower cosyntropin doses may have greater sensitivity vs. the standard dose in detecting adrenal dysfunction. Obesity and overweight are increasing, impacting the clinical presentation of some diseases. Currently more than 50% of the subjects diagnosed with autoimmune adrenal insufficiency have a BMI greater than 25, and hence individuals living with overweight and obesity are more frequently requiring evaluation of the adrenal cortical function. Fixed-dose cosyntropin stimulation may not be appropriate for individuals with obesity. Objective. The primary objective was to compare cortisol response to a weight-adapted cosyntropin dose vs. a fixed low dose (1 µg) and a more physiologically fixed dose (10 µg). Methods. Twenty individuals with obesity and 20 age-matched healthy controls underwent in a randomized sequence at least one-week apart, to the The short cosyntropin test with three different doses, 0.2 µg/kg of body weight, 1 or 10 µg fixed dose stimuli. The assessment and data analysis were blinded to the individual and the investigator. Results. Cortisol response was reduced in the group with obesity with the 1 µg fixed dose stimuli at 30 minutes (median, IQR) 649.6 µg, 567.3–738.4 µg for the control group vs. 568.6 µg, 528.4–623.13 µg,

p
=
0.04

; there was a lower cortisol peak at 60′ in all the three evaluated doses, with a dose-dependent trend. A weight-adapted cosyntropin dose of 0.2 µg in obesity produces a similar response to the one observed in individuals without obesity. The 1 µg ACTH test falls short on stimulating the cortisol adrenal response in individuals with obesity.
Hypoxia Enhances Glioma Resistance to Sulfasalazine-Induced Ferroptosis by Upregulating SLC7A11 via PI3K/AKT/HIF-1α Axis
Authors: Sun Shicheng , Guo Changfa , Gao Taihong , Ma Dengzhen , Su Xiangsheng , Pang Qi , Zhang Rui
Published: November 2022

Glioma is the most common primary brain tumor, with a high rate of recurrence and treatment resistance. Glioblastoma is highly invasive, infiltrating surrounding brain parenchyma, and is known to cause intracranial metastasis resulting in a dismal prognosis. Hypoxia contributes significantly to chemo- and radiotherapy resistance in cancer. Ferroptosis is a nonapoptotic oxidative cell death that has been identified as a potential anticancer mechanism. Sulfasalazine (SAS) activates ferroptosis and plays a potential role in tumor treatment. However, the relationship between hypoxia and SAS resistance has not been elucidated. This study is aimed at investigating the role of hypoxia in SAS-induced ferroptosis and the underlying mechanisms. Here, we found that hypoxia significantly suppressed SAS-induced ferroptosis by upregulating SLC7A11 expression in the U87 and U251 glioma cell lines. Hypoxia promotes SLC7A11 expression by enhancing the PI3K/AKT/HIF-1α pathway. The AKT inhibitor MK-2206 and HIF-1α inhibitor PX-478 significantly reversed this effect. In addition, under normoxia, PX-478 induced a higher lipid peroxidation level by decreasing SLC7A11 expression in the U87 and U251 cells but could not induce cell death directly; it could significantly enhance the tumor cell killing effect of SAS. In vivo, the combination of PX-478 and SAS had a coordinated synergistic effect on anticancer activity, as revealed by subcutaneous and orthotopic xenograft mouse models. In conclusion, hypoxia enhanced glioma resistance to SAS-induced ferroptosis by upregulating SLC7A11 via activating the PI3K/AKT/HIF-1α axis. Combination therapy with PX-478 and SAS may be a potential strategy against glioma.
Japanese Encephalitis Vaccine Generates Cross-Reactive Memory T Cell Responses to Zika Virus in Humans
Authors: Wang Ran , Zhang Meng , Zhang Linlin , Liu Mengjia , Shan Chao , An Jing , Xie Zhengde
Published: November 2022

Objective. Zika virus (ZIKV) and Japanese encephalitis virus (JEV) are mosquito-borne flaviviruses with sequence homology. ZIKV circulates in some regions where JEV also circulates, or where JE vaccination is used. Cross-immunity between flaviviruses exists, but the precise mechanisms remain unclear. We previously demonstrated that T cell immunity induced by the live-attenuated Japanese encephalitis (JE) SA14-14-2 vaccine conferred protective immunity against ZIKV infection in mice, which could even bypass antibody-dependent enhancement. However, the role of T cell immune, especially memory T cell subsets, in cross-reactive immune responses between JE vaccine and ZIKV in humans has not been reported. Methods. We examined central and effector memory CD4+ and CD8+ T cell (TCM and TEM) responses (including degranulation, cytokines, and chemokines) in the presence of JEV and ZIKV, respectively, by using qualified peripheral blood mononuclear cell samples from 18 children who had recently received a two-dose course of JE vaccine SA14-14-2 as well as seven children without JE vaccination. Results. Cross-reactive CD8+ TCM in response to ZIKV was characterized by secretion of IFN-γ, whereas CD8+ TEM did not show significant upregulation of functional factors. In the presence of ZIKV, IFN-γ and TNF-α expression was upregulated by CD4+ TEM, and the expression signature of CD4+ TCM is more cytotoxic potential. Conclusions. We profiled the cross-reactive memory T cell responses to ZIKV in JE vaccine recipients. These data will provide evidence for the mechanism of cross-reactive memory T cell immune responses between JEV and ZIKV and a more refined view of bivalent vaccine design strategy.
Application of Emotional Education in College Physical Education Based on Mobile Internet of Things Model
Authors: Huang Yanqun , Li Kun
Published: November 2022

Emotional education is an indispensable and important link in today’s educational philosophy. In college physical education, students’ emotions are often easily ignored, resulting in a feeling of weariness. What kind of method can effectively apply emotional education to physical education to improve students’ enthusiasm for learning has become one of the current research topics that has attracted much attention. Aiming at this problem, it has great research significance for the field of sports emotion education. With the deepening of emotional education research, the research on mobile Internet of Things (IoT) in college education continues to deepen, which is the key to solving the application problem of emotional education. The purpose of this paper is to study the application of college physical education and emotional education integrating mobile IoT model. Through the analysis and research of mobile IoT and emotional education, it can be applied to the construction of emotional education methods to solve the problem of improving students’ enthusiasm for learning. This paper analyzed mobile IoT, college physical education, and emotional education, which conducted experimental analysis of method functions and used related theoretical formulas to explain. The results have shown that the emotional education method is more effective than the traditional method in improving students’ enthusiasm for learning, and the difference between the two in the evaluation of teaching satisfaction is 31.89%. It can be seen that this kind of emotional education can meet the needs of improving students’ enthusiasm for learning, and the satisfaction and learning efficiency are greatly improved.