bluuebunny/crossref_metadata_2025 huggingface dataset:
Safer Baby Bundle: study protocol for the economic evaluation of a quality improvement initiative to reduce stillbirths
Authors: Callander Emily Joy , Andrews Christine , Sketcher-Baker Kirstine , Nicholl Michael Christopher , Farrell Tanya , Karger Shae , Flenady Vicki
Published: August 2022

Introduction

Stillbirth continues to be a public health concern in high-income countries, and with mixed results from several stillbirth prevention interventions worldwide the need for an effective prevention method is ever present. The Safer Baby Bundle (SBB) proposes five evidence-based care packages shown to reduce stillbirth when implemented individually, and therefore are anticipated to produce significantly better outcomes if grouped together. This protocol describes the planned economic evaluation of the SBB quality improvement initiative in Australia.

Methods and analysis

The implementation of the SBB will occur over three state-based health jurisdictions in Australia—New South Wales, Queensland and Victoria, from July 2019 onwards. The intervention is being applied at the state level, with sites opting to participate or not, and no individual woman recruitment. The economic evaluation will be based on a whole-of-population linked administrative dataset, which will include the data of all mothers, and their resultant children, who gave birth between 1 January 2016 and 31 December 2023 in these states, covering the preimplementation and postimplementation time period. The primary health outcome for this economic evaluation is late gestation stillbirths, with the secondary outcomes including but not limited to neonatal death, gestation at birth, mode of birth, admission to special care nursery and neonatal intensive care unit, and physical and mental health conditions for mother and child. Costs associated with all healthcare use from birth to 5 years post partum will be included for all women and children. A cost-effectiveness analysis will be undertaken using a difference-in-difference analysis approach to compare the primary outcome (late gestation stillbirth) and total costs for women before and after the implementation of the bundle.

Ethics and dissemination

Ethics approval for the SBB project was provided by the Royal Brisbane & Women’s Hospital Human Research Ethics Committee (approval number: HREC/2019/QRBW/47709). Approval for the extraction of data to be used for the economic evaluation was granted by the New South Wales Population and Health Services Research Ethics Committee (approval number: 2020/ETH00684/2020.11), Australian Institute of Health and Welfare Human Research Ethics Committee (approval number: EO2020/4/1167), and Public Health Approval (approval number: PHA 20.00684) was also granted. Dissemination will occur via publication in peer reviewed journals, presentation at clinical and policy-focused conferences and meetings, and through the authors’ clinical and policy networks.

This study will provide evidence around the cost effectiveness of a quality improvement initiative to prevent stillbirth, identifying the impact on health service use during pregnancy and long-term health service use of children.
Which decentralised trial activities are reported in clinical trial protocols of drug trials initiated in 2019–2020? A cross-sectional study in ClinicalTrials.gov
Authors: de Jong Amos J , Grupstra Renske J , Santa-Ana-Tellez Yared , Zuidgeest Mira G P , de Boer Anthonius , Gardarsdottir Helga
Published: August 2022

Objectives

Decentralised clinical trial activities—such as participant recruitment via social media, data collection through wearables and direct-to-participant investigational medicinal product (IMP) supply—have the potential to change the way clinical trials (CTs) are conducted and with that to reduce the participation burden and improve generalisability. In this study, we investigated the decentralised and on-site conduct of trial activities as reported in CT protocols with a trial start date in 2019 or 2020.

Design

We ascertained the decentralised and on-site conduct for the following operational trial activities: participant outreach, prescreening, screening, obtaining informed consent, asynchronous communication, participant training, IMP supply, IMP adherence monitoring, CT monitoring, staff training and data collection. Results were compared for the public versus private sponsors, regions involved, trial phases and four time periods (the first and second half of 2019 and 2020, respectively).

Setting

Phases 2, 3 and 4 clinical drug trial protocols with a trial start date in 2019 or 2020 available from ClinicalTrials.gov.

Outcome measures

The occurrence of decentralised and on-site conduct of the predefined trial activities reported in CT protocols.

Results

For all trial activities, on-site conduct was more frequently reported than decentralised conduct. Decentralised conduct of the individual trial activities was reported in less than 25.6% of the 254 included protocols, except for decentralised data collection, which was reported in 68.9% of the protocols. More specifically, 81.9% of the phase 3 protocols reported decentralised data collection, compared with 73.3% and 47.0% of the phase 2 and 4 protocols, respectively. For several activities, including prescreening, screening and consenting, upward trends in reporting decentralised conduct were visible over time.

Conclusions

Decentralised methods are used in CTs, mainly for data collection, but less frequently for other activities. Sharing best practices and a detailed description in protocols can drive the adoption of decentralised methods.
Lived experiences of parents providing care to young people who self-harm: a protocol for a meta-aggregative synthesis of qualitative studies
Authors: Zhao Yanli , D Dela Rosa Ronnell , Zhang Qiushi , Zhao Wei , Xu Hui , Wang Rui , Ma Ling
Published: August 2022

Introduction

The self-harm of young people can cause tremendous distress to their parents/carers and impair parents’ ability to provide care. At the same time, parents play an essential role in supporting their child during the management and treatment of self-harm. The synthesis of evidence about parental experiences and needs can inform mental health practice and the development of interventions to provide better care to young people who self-harm and their parents.

Methods and analysis

A comprehensive search will be conducted across several information sources, including multiple electronic databases (eg, PubMed, Embase, CINAHL, PsycINFO, ProQuest, CNKI, Wanfang, VIP and SinoMed), grey literature, the websites of specific organisations and hand-searched reference lists of all the relevant studies. Qualitative studies published in English or Chinese and focusing on the lived experiences of parents whose child self-harms will be included. Two reviewers will independently screen all the retrieved articles according to the flow diagram proposed by PRISMA (the Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Two independent reviewers will then appraise the methodological quality of all the included articles using the JBI (Joanna Briggs Institute) critical appraisal checklist for qualitative research. The meta-aggregation approach will be used to synthesise the findings of the included qualitative studies, and the level of confidence in the synthesised findings will be assessed using the Confidence in the Qualitative synthesised finding approach.

Ethics and dissemination

No additional ethical clearance is required since this review is a secondary analysis of published primary studies. The findings will be disseminated through publication in a peer-reviewed journal and conference presentations.

PROSPERO registration number

CRD42021265525.
Hereditary haemorrhagic telangiectasia in Danish patients with pathogenic variants inSMAD4:a nationwide study
Authors: Jelsig Anne Marie , Kjeldsen Anette , Christensen Lise Lotte , Bertelsen Birgitte , Karstensen John Gásdal , Brusgaard Klaus , Torring Pernille M
Published: August 2022

Background and aims

Hereditary haemorrhagic telangiectasia (HHT) is an autosomal dominant condition characterised by recurrent epistaxis, telangiectatic lesions in the skin and mucosal membranes, and arteriovenous malformations (AVMs) in various organs. In 3%–5% of patients, HHT is caused by pathogenic germline variants (PVs) inSMAD4, and these patients often have additional symptoms of juvenile polyposis syndrome and thoracic aneurysms. The phenotypic spectrum ofSMAD4-associated HHT is less known, including the penetrance and severity of HHT. We aimed to investigate the phenotypic spectrum of HHT manifestations in Danish patients with PVs inSMAD4and compare the findings with current literature.

Methods

The study is a retrospective nationwide study with all known Danish patients with PVs inSMAD4. In total, 35 patients were included. The patients were identified by collecting data from genetic laboratories, various databases and clinical genetic departments across the country. Clinical information was mainly collected from the Danish HHT-Centre at Odense University Hospital.

Results

Twenty-nine patients with PVs inSMAD4(83%) were seen at the HHT-Centre. Seventy-six per cent of these fulfilled the Curaçao criteria, 86% experienced recurrent epistaxis and 83% presented with telangiectatic lesions at different anatomical localisations. Almost 60% had AVMs, mainly pulmonary and hepatic, while none was found to have cerebral AVMs. Fifteen per cent had thoracic aortic abnormalities.

Conclusion

We present a nationwide study of one of the largest populations of patients with PVs inSMAD4that has systematically been examined for HHT manifestations. The patients presented the full spectrum of HHT-related manifestations and the majority fulfilled the Curaçao criteria.
Perceived exertion and dyspnea while cycling during a hypoxic and hyperoxic placebo
Authors: Kipp Shalaya , Leahy Michael G. , Hanna Jacob A. , Sheel A. William
Published: August 2022

Rating of perceived exertion (RPE) is used to subjectively quantify the perception of physical activity, breathlessness or dyspnea, and leg discomfort (RPElegs) during exercise. However, it is unknown how dyspnea or RPElegs can be influenced by expectations. Thirty healthy, active participants (19 males, 11 females) completed five, 5-minute submaximal cycling trials at 60% peak work rate. We deceived participants by telling them they were inspiring different hypoxic and hyperoxic gases, when in fact they breathed room air. Cardiorespiratory variables were similar between the trials, however, dyspnea and RPElegs evaluated with a Borg scale changed in a dose–response manner. When participants believed they were breathing 15% O2, they significantly increased dyspnea +0.70 ± 0.2 units ( p = 0.03) compared to room air, whereas RPElegs was unchanged +0.35 ± 0.1 units ( p = 0.70). When participants believed they were breathing 15% O2, they significantly increased dyspnea +1.05 ± 0.4 units ( p = 0.003) compared to 23% hyperoxic condition, whereas RPElegs was unchanged +0.35 ± 0.1 units ( p = 0.70). We found that dyspnea during exercise is susceptible to expectancy, without any accompanying physiological changes. Given coaches and clinicians use perceived exertion to prescribe exercise intensity and evaluate treatments, our findings show that the effect of expectations must be considered when interpreting sensations of breathlessness.
Effects of dam-induced delays on system-wide survival of Atlantic salmon smolts during high-flow, high-survival years in the Penobscot River, Maine, USA
Authors: Molina-Moctezuma Alejandro , Stich Daniel S. , Zydlewski Joseph D.
Published: August 2022

System-wide survival of hatchery-reared Atlantic salmon ( Salmo salar) smolts was evaluated (2017–2019) in the Penobscot River and compared to survival estimates from previous years that spanned major changes (2005–2016). This system was transformed through two dam removals in 2012 and construction of a nature-like passage structure at a third. The main stem had three dams (five prior to 2012), while the main tributary had four dams (one with the new nature-like passage). We estimated survival using acoustic telemetry mark–recapture ( n = 1482) from 2017 to 2019. Six release sites and two release dates were included to assess system-wide survival. Survival from 2017 to 2019 was higher than previous years, with total cumulative survival > 0.75, independently of year and release sites, compared to survival < 0.5 in previous years. These years coincided with exceptional high flows not seen previously. We found an effect of delays on survival, longer delays associated with lower survival. Overall, survival in these years increased in all reaches relative to previous years except for one dam, Weldon Dam, which was a site of sustained high mortality.
A Frequency Adaptive Data Collection Method for Internet of Things Nodes
Authors: Liu Bo , Yang Aiqiang , Tan Xuyang , Deng Mengyao
Published: August 2022

The aim of this paper is to solve the problem of a large amount of redundant data in the process of large-scale acquisition of Internet of Things sensors. This paper proposes a frequency adaptive data sensing method based on revolving gate algorithm for STM32 power safety data acquisition system. The method realizes the intelligent control of current protection terminal through three-stage current protection algorithm and frequency adaptive data acquisition algorithm. First, the three-stage current protection algorithm is used to protect the circuit, which can trip quickly in case of overload, and reduce the peak current caused by some equipment when starting up, so as to avoid damage to the equipment. Second, the arithmetic mean of each statistic is compared with the last value reported to the server. If the absolute value of the difference between the two exceeds the specified threshold range, the reported value is updated. Otherwise, it is filtered out, and the data smoothness is calculated according to the rules. The data collection interval is dynamically adjusted according to the data smoothness, which can greatly reduce the collection of redundant data and the traffic consumption of Internet of Things devices. On the server side, the inverse algorithm is used for interpolation and reconstruction to recover the collected data. This method is applied to the developed electricity safety equipment, and the electricity consumption is monitored and collected continuously for 24 h. After filtering by the frequency adaptive algorithm, only 108 pieces of data records are reported for 28,713 pieces of original data, and the compression ratio reaches 99.49[Formula: see text]. Compared with other data collection strategies, this method significantly reduces the amount of redundant data collection and the energy consumption of terminal nodes. Furthermore, this method realizes the real-time perception of line data and environmental data through current, residual current, temperature sensor and electric energy metering chip, and controls the opening and closing of wire controlled micro circuit breaker through PC817 optocoupler to protect the safety of the circuit.
Phase Space Transport in a Symmetric Caldera Potential with Three Index-1 Saddles and No Minima
Authors: Katsanikas Matthaios , Agaoglou Makrina , Wiggins Stephen , Mancho Ana M.
Published: August 2022

We apply the method of Lagrangian Descriptors (LDs) to a symmetric Caldera-type potential energy surface which has three index-1 saddles surrounding a relatively flat region that contains no minimum. Using this method we show the phase space transport mechanism that is responsible for the existence and nonexistence of the phenomenon of dynamical matching for this form of Caldera potential energy surface.
An Image Encryption Algorithm Based on an Epidemic Spreading Model
Authors: Zhang Wei , Wang Shuwen , Zhu Guangdong , Han Weijie , Zhu Zhiliang
Published: August 2022

An intrinsic similarity was noted between epidemic spreading models and diffusion operations in cryptography. In this paper, a new image encryption algorithm is proposed based on an epidemic spreading model. The notable feature of the model is the evolution of the network node state. We utilize the evolution of an epidemic spreading model, namely the susceptible-infectious-recovered (SIR) model, to drive the encryption progress by abstracting pixels to the network nodes. In the new cryptosystem, the pixels in plain-text are considered as susceptible individuals, permutation and diffusion are seamlessly integrated rather than having two independent stages, and the encryptions are performed in a two-dimensional and nonlinear manner. Simulation results demonstrate its high encryption speed and excellent encryption security.
A Fractional-Order Food Chain System Incorporating Holling-II Type Functional Response and Prey Refuge
Authors: Zhang Na , Kao Yonggui
Published: August 2022

A fractional-order three-species food chain ecosystem with prey refuge and Holling-II type functional response for predation is proposed and studied. Several sufficient conditions for the existence and uniqueness of the solution of the fractional-order system are obtained. The boundedness of the solution of the system is proven. We investigate the asymptotic behavior of the model by using eigenvalue analysis, and some sufficient conditions on local asymptotic stability of the equilibrium points are given. Furthermore, the conditions for the occurrence of bifurcation at some equilibrium points are presented. We find that the order of the proposed fractional-order ecosystem is one of the parameters for its bifurcation. Several numerical simulations are provided to show the effectiveness of our findings in this paper. Lastly, some new numerical simulations are given to discuss the influence of the half-saturation constant, prey refuge coefficient and the order of fractional-order derivative on the stability of the discussed fractional-order system.
Stability Analysis, Hopf Bifurcation and Drug Therapy Control of an HIV Viral Infection Model with Logistic Growth Rate and Cell-to-Cell and Cell-Free Transmissions
Authors: Roomi Vahid , Gharahasanlou Tohid Kasbi , Hemmatzadeh Zeynab
Published: August 2022

It is well known that dynamical systems are very useful tools to study viral diseases such as HIV, HBV, HCV, Ebola and Influenza. This paper focuses on a mathematical model of the cell-to-cell and the cell-free spread of HIV with both linear and nonlinear functional responses and logistic target cell growth. The reproduction number of each mode of transmission has been calculated and their sum has been considered as the basic reproduction number. Based on the values of the reproduction number, the local and global stabilities of the rest points are investigated. Choosing a suitable bifurcation parameter, some conditions for the occurrence of Hopf bifurcation are also obtained. Moreover, numerical simulations are presented to support the analytical results. Finally, to study the effect of the drug on the disease process, some control conditions are determined. Since two modes of transmission and both linear and nonlinear functional responses have been included in this manuscript, our obtained results are a generalization of those in the literature. Moreover, the results are obtained with weaker assumptions in comparison with the previous ones.
Stability Analysis and Coexisting Behaviors of a Delayed Multiplex Network Under Electromagnetic Radiation
Authors: Mao Xiaochen , Lei Fuchen
Published: August 2022

This paper studies the dynamics of a nonlinear network with many interacting neural populations and time-delayed couplings under electromagnetic radiation. The influence of the electromagnetic radiation is described by using flux-controlled memristor. The delay-induced instability and bifurcated periodic oscillations of the memristive multiplex network are determined by decomposing and analyzing the characteristic equations. The bifurcation diagrams are shown and complicated dynamical behaviors are explored, such as multi-periodic orbits and period doubling bifurcations. These interesting phenomena are also observed from the circuit realization. It is found that both time delay and electromagnetic radiation have great effects on the performance of the network, such as synchronization transitions and multistability coexistence.
A Novel Megastable System: Cloud, Kite, and Arrow-Like Attractors and Their Dynamics
Authors: Ramakrishnan Balamurali , Natiq Hayder , Rajagopal Karthikeyan , Jafari Sajad , Nazarimehr Fahimeh
Published: August 2022

A megastable oscillator with various types of attractors is proposed. The oscillator shows interesting dynamics like cloud, kite, and arrow-like attractors. As we know, such a megastable oscillator with the dynamic shapes was not previously reported. There is an infinite number of arrow-like attractors in this oscillator. Investigating equilibrium points of the oscillator and their stabilities shows that two of the attractors, the largest cloud-like and smallest kite-like, are self-excited, while the others are hidden. The basin of attraction for the oscillator is studied for various attractors. Then, a forcing term is added to the oscillator, and its dynamics are investigated. The bifurcations and Lyapunov exponents of each type of attractor are investigated by changing the coefficient of the sinusoidal term [Formula: see text]. Each of the attractors shows various periodic, quasi-periodic, and chaotic dynamics for various [Formula: see text]. Also, the basin of attraction of the forced oscillator is investigated.
Cross-scale Graph Interaction Network for Semantic Segmentation of Remote Sensing Images
Authors: Nie Jie , Huang Lei , Zheng Chengyu , Lv Xiaowei , Wang Rui
Published: August 2022

Semantic segmentation of remote sensing (RS) images plays a vital role in a variety of fields, including urban planning, natural disaster monitoring, and land resource management. Due to the complexity and low resolution of RS images, many approaches have been proposed to handle the related task. However, these previously developed approaches dedicate to contextual interaction but ignore the cross-scale semantic correlation and multi-scale boundary information. Therefore, we propose a Cross-scale Graph Interaction Network (CGIN) to address semantic segmentation problems of RS images, which consists of a semantic branch and a boundary branch. In the semantic branch, we first apply atrous convolution to extract multi-scale semantic features of RS images. Particularly, based on the multi-scale semantic features, a Cross-scale Graph Interaction (CGI) module is introduced, which establishes cross-scale graph structures and performs adaptive graph reasoning to capture the cross-scale semantic correlation of RS objects. In the boundary branch, we propose a Multi-scale Boundary Feature Extraction (MBFE) module that utilizes atrous convolutions with different dilation rates to extract multi-scale boundary features. Finally, to address the problem of sparse boundary pixels in the fusion process of the two branches, we propose a Multi-scale Similarity-guided Aggregation (MSA) module by calculating the similarity of semantic features and boundary features at the corresponding scale, which can emphasize the boundary information in semantic features. Our proposed CGIN outperforms state-of-the-art approaches in numerical experiments conducted on two benchmark remote sensing datasets.
TokenAware: Accurate and Efficient Bookkeeping Recognition for Token Smart Contracts
Authors: He Zheyuan , Song Shuwei , Bai Yang , Luo Xiapu , Chen Ting , Zhang Wensheng , He Peng , Li Hongwei , Lin Xiaodong , Zhang Xiaosong
Published: August 2022

Tokens have become an essential part of blockchain ecosystem, so recognizing token transfer behaviors is crucial for applications depending on blockchain. Unfortunately, existing solutions cannot recognize token transfer behaviors accurately and efficiently because of their incomplete patterns and inefficient designs. This work proposes
TokenAware
, a novel online system for recognizing token transfer behaviors. To improve accuracy,
TokenAware
infers token transfer behaviors from modifications of internal bookkeeping of a token smart contract for recording the information of token holders (e.g., their addresses and shares). However, recognizing bookkeeping is challenging, because smart contract bytecode does not contain type information.
TokenAware
overcomes the challenge by first learning the instruction sequences for locating basic types and then deriving the instruction sequences for locating sophisticated types that are composed of basic types. To improve efficiency,
TokenAware
introduces four optimizations. We conduct extensive experiments to evaluate
TokenAware
with real blockchain data. Results show that
TokenAware
can automatically identify new types of bookkeeping and recognize 107,202 tokens with 98.7% precision.
TokenAware
with optimizations merely incurs 4% overhead, which is 1/345 of the overhead led by the counterpart with no optimization. Moreover, we develop an application based on
TokenAware
to demonstrate how it facilitates malicious behavior detection.
Electrodeposition and Electrodissolution of Li Metal in Nanohole Arrays of Anodic Porous Alumina
Authors: Kondo Toshiaki , Yoshida Masahiro , Yanagishita Takashi , Masuda Hideki
Published: August 2022

Electrodeposition and electrodissolution of Li metal in an anodic porous alumina that has an ideal hole array structure were demonstrated. Electrodeposition and electrodissolution of Li metal in the hole array structures could be repeatedly carried out without any formation of dendritic Li. Although the hole diameter of the anodic porous alumina was reduced from the micrometer to nanometer scale, deposition and dissolution of Li metal could be stably conducted. The present process is expected to be applicable to the fabrication of a safe rechargeable Li-metal battery.
Perspective—Does the Sand Equation Reliably Predict the Onset of Morphological Evolution in Lithium Electrodeposition?
Authors: Wasalathanthri Ruwani N. , Akolkar Rohan
Published: August 2022

For galvanostatic metal electrodeposition under diffusion-limited conditions, the Sand’s equation provides the time at which the concentration of the cation being reduced reaches zero at the electrode-electrolyte interface. Such a condition causes amplification of the electrodeposit roughness and triggers dendritic growth during electrodeposition. In this perspective article, the question of whether the classical Sand equation reliably predicts the onset of morphological evolution in lithium electrodeposition is addressed and answered in the negative. A comparison of Sand’s times (

t

Sand

) with experimentally observed lithium dendrite onset times reveals significant discrepancies over a wide range of Li electrodeposition current densities. Specifically, it is shown that morphology evolution in lithium electrodeposition from organic liquid electrolytes commences at time-scales that are at least 1–2 orders of magnitude lower than Sand’s time. To explain this discrepancy, we present a modified Sand’s approach in which transient multi-phase diffusion through the liquid electrolyte as well as through the solid-electrolyte-interphase (SEI) layer is considered. The proposed approach leads to increased accuracy in the prediction of the morphology onset time in lithium electrodeposition. We hope that this perspective helps researchers circumvent the erroneous application of the classical Sand’s equation for lithium electrodeposition, and stimulates experimental and theoretical research into the complex multi-phase transport processes relevant to morphology evolution in lithium electrodeposition.
Vascular contributions to cognitive impairment/dementia in diabetes: role of endothelial cells and pericytes
Authors: Edgerton-Fulton Mia , Ergul Adviye
Published: August 2022

Vascular contributions to cognitive impairment/dementia (VCID) are a leading cause of dementia, a known neurodegenerative disorder characterized by progressive cognitive decline. Although diabetes increases the risks of stroke and the development of cerebrovascular disease, the cellular and vascular mechanisms that lead to VCID in diabetes are yet to be determined. A growing body of research has identified that cerebrovascular cells within the neurovascular complex display an array of cellular responses that impact their survival and reparative properties, which plays a significant role in VCID development. Specifically, endothelial cells and pericytes are the primary cell types that have gained much attention in dementia-related studies due to their molecular and phenotypic heterogeneity. In this review, we will discuss the various morphological subclasses of endothelial cells and pericytes as well as their relative distribution throughout the cerebrovasculature. Furthermore, the use of diabetic and stroke animal models in preclinical studies has provided more insight into the impact of sex differences on cerebral vascularization in progressive VCID. Understanding how cellular responses and sex differences contribute to endothelial cell and pericyte survival and function will set the stage for the development of potential preventive therapies for dementia-related disorders in diabetes.
From the nose to the lungs: the intricate journey of airborne pathogens amid commensal bacteria
Authors: Costantini Claudio , Nunzi Emilia , Romani Luigina
Published: August 2022

The recent COVID-19 pandemic has dramatically brought the pitfalls of airborne pathogens to the attention of the scientific community. Not only viruses but also bacteria and fungi may exploit air transmission to colonize and infect potential hosts and be the cause of significant morbidity and mortality in susceptible populations. The efforts to decipher the mechanisms of pathogenicity of airborne microbes have brought to light the delicate equilibrium that governs the homeostasis of mucosal membranes. The microorganisms already thriving in the permissive environment of the respiratory tract represent a critical component of this equilibrium and a potent barrier to infection by means of direct competition with airborne pathogens or indirectly via modulation of the immune response. Moving down the respiratory tract, physicochemical and biological constraints promote site-specific expansion of microbes that engage in cross talk with the local immune system to maintain homeostasis and promote protection. In this review, we critically assess the site-specific microbial communities that an airborne pathogen encounters in its hypothetical travel along the respiratory tract and discuss the changes in the composition and function of the microbiome in airborne diseases by taking fungal and SARS-CoV-2 infections as examples. Finally, we discuss how technological and bioinformatics advancements may turn microbiome analysis into a valuable tool in the hands of clinicians to predict the risk of disease onset, the clinical course, and the response to treatment of individual patients in the direction of personalized medicine implementation.
Talking the talk: tips for effective oral presentations in biomedical research
Authors: Seals Douglas R.
Published: August 2022

In this Perspective, I share several personal thoughts and recommendations with early-career stage investigators for developing and delivering effective oral research presentations in the biomedical sciences. I begin by emphasizing the importance of this professional skill and describing numerous opportunities for gaining experience as well as sources of guidance and feedback. I then discuss considerations for deciding whether and when to present, tips for developing a fundamentally sound presentation, and suggestions on preparing for and delivering a compelling talk. Lastly, I provide my insights on optimal performance during the Q&A (question and answer) period, discuss the concept of “audience good will,” and provide advice on how to best maintain that good will during your presentation.
A Comprehensive Quantitative and Biological Neural Network Optimization Model of Sports Industry Structure Based on Knowledge Mapping
Authors: Wang Zhaohong , Gao Yang , Li Wenge
Published: August 2022

In this paper, a comprehensive quantitative and biological neural network optimization model of sports industry structure is thoroughly studied and analyzed using knowledge graphs. To address the problems of poor performance interpretability deficiency of knowledge graph-based recommendation methods in the face of relational sparse graphs, a pretraining-based implicit characterization algorithm strategy is proposed for the recall stage, which can solve the problems of difficulty in going online and high delay in the recall stage of the recommendation system while improving the accuracy, and not only this can be applied in the recall stage, but also the sorting and postsorting modules can be used as features. To study the relationship between signaling activity and energy metabolism of pyramidal neurons, an empirical model of the synaptic vesicle cycle is proposed to simulate the synaptic transmission process, the role played by energy metabolism in synaptic transmission is studied from the perspective of feedback control, and the quantitative relationship between neuronal pulse discharge frequency, energy consumption, and information quantity in dendritic integration is analyzed using the cable theory and atrial chamber model. It was found that, when

0
≤
ε
≤
0.6

, the chaotic region shrinks and eventually disappears with the increase of the memory factor

ε

; however, when

0.6
≤
ε
≤
1

is used, chaos is recreated and the chaotic area gradually increases with the increase of the memory factor

ε

. This paper conducts comparative experiments on data sets in the recommendation domain and verifies that the proposed model and the feature intersection module can effectively perform feature interaction between items and entities, thus enhancing the recommendation effect.
Fuzzy Analysis of SVIRS Disease System with Holling Type-II Saturated Incidence Rate and Saturated Treatment
Authors: Zhang Hu , Madhusudanan V. , Murthy B. S. N. , Srinivas M. N. , Adugna Biruk Ambachew
Published: August 2022

This article presents a fuzzy SVIRS disease system with Holling type-II saturated incidence rate and saturated treatment, in which all parameters related to population dynamics have been considered as fuzzy numbers. Then, the existence condition and permanence of the SVIRS model have been discussed and we derived disease-free and endemic equilibrium points of the proposed fuzzy system. The local stability conditions of the fuzzy system around these equilibrium points using Routh–Hurwitz criteria are discussed. We also verified global stability around the interior steady state using Lozinskii measure. Computer simulations are provided to understand the dynamics of the proposed system. Parameter analysis is carried out with the help of computer simulation. Fuzzy provides better solution for any disease modeling in many ways like disease detection and transmission, different stages of disease, risk analysis (through parameter analysis), and optimal recovery solutions. Earlier literature acts as background to startup this disease modeling and optimal solutions provided by fuzzy logic is one of the motivational key element behind this fuzzy SVIRS model with Holling type-II and its analysis by both analytical and computer simulation.
Nursing Skill Assessment of Hospital Nurses in Management of Critically Ill Patients
Authors: Xu Lingli , Sun Qiyu , Feng Jiayi , Huang Li Jing , Xu Chunjing , Shen Weihong , Ding Jian , Jin Yongmei
Published: August 2022

Objective. To analyze the application of standardized nursing procedures in critically ill patients’ nursing evaluation. Methods. 90 cases of critically ill patients aged from 18 to 65 who were treated in our hospital from April 2020 to April 2021 were selected and divided into the control group and observation group, respectively, with 45 cases according to the drawing method. The rescue time, blood pressure, heart rate before and after nursing, adverse mood, length of stay, incidence of adverse events, ICU transfer and death, and satisfaction of 2 groups were statistically analyzed and compared. Results. The rescue time of cardiopulmonary resuscitation, oxygen inhalation, venous opening, and endotracheal resuscitation in the observation group was

3.24
±
1.01

, which is lower than that in the control group,

6.65
±
2.11

, with statistical significance (

P
<
0.05

). Similarly, the vital signs in the observation group were

2.45
±
0.44

, which is also significantly lower than that in the control group,

5.67
±
1.56

. After nursing, the blood pressure and heart rate in the observation group were lower than those in control group, with statistical significance (

P
<
0.05

). The adverse mood of the observation group after nursing was lower than that of the control group, with statistical significance (

P
<
0.05

). The length of stay, incidence of adverse events, intensive care unit (ICU) transfer, and death in the observation group were lower than those in the control group, with statistical significance (

P
<
0.05

). The length of stay in the observation group was

8.87
±
2.11

, while

11.34
±
2.45

in the observation group. The incidence of adverse events in the observation group was 1, while 8 in the observation group. The length of stay in the observation group was

8.87
±
2.11

, while

11.34
±
2.45

in the observation group. The ICU transfer in the observation group were 2, while 9 in the observation group. There was no death in the observation group, however, 4 in the observation group. Nursing satisfaction in the observation group was higher than that in the control group, with statistical significance (

P
<
0.05

). The number of patients that are very satisfied in the observation group was 28, while 20 in the control group. The number of patients that are satisfied in the observation group was the same as in the control group, both 15. However, the number of patients that are dissatisfied in the observation group was 2, while 10 in the control group. Conclusion. The application of the standardized nursing process in the nursing of critically ill patients can not only effectively reduce the self-rating anxiety scale (SAS) and sarcoidosis diagnostic score (SDS) of patients but also reduce the incidence of complications and improve the nursing satisfaction of patients.
Deformation Characteristics of the Foundation Pit of the Underpass Viaduct and Grey Relational Analysis of the Maximum Horizontal Deflection of the Retaining Wall
Authors: Sun Shoubang , Yan Songhong , Cao Xiaoping , Li Xiaozhong
Published: August 2022

With the rapid development of rail transit, the excavation of new foundation pits will inevitably approach or pass through existing structures. Therefore, choosing a reasonable support scheme can effectively control the deformation of the foundation pit and ensure the safety of existing structures. This paper investigates the excavation of a typical foundation pit in Guangdong that underpasses a viaduct as the research object. This study uses field monitoring and numerical simulations to analyze the deformation characteristics of the supporting structure and introduces grey relational analysis (GRA) to investigate the key factors that influence the maximum horizontal deflection of the retaining wall. The results indicate that all monitored values are substantially less than the warning value specified in the code. Moreover, the horizontal deflection of the retaining wall and the horizontal displacement of the top of the wall at the measuring points near the existing bridge piles are smaller than at other measuring points. This support system has a high safety factor and a large space for optimization. The main factors affecting the maximum horizontal deflection of the retaining wall are as follows: second strut horizontal spacing > first strut horizontal spacing > layered excavation thickness > retaining wall thickness > retaining wall stiffness. The results of this study will provide technical guidance for the design of similar projects and optimization of their construction.
Biomedical Diagnosis of Leukemia Using a Deep Learner Classifier
Authors: Shawly Tawfeeq , Alsheikhy Ahmed A.
Published: August 2022

Leukemia cancer is the most common type of cancer that occurs in childhood. The most common types are acute lymphocytic leukemia (ALL) and acute myelogenous leukemia (AML) which affect children and adults, respectively. Several health issues occur due to these cancers. Leukemia affects the bone marrow or the lymph nodes. Leukemia produces abnormal white blood cells via the bone marrow system. The affected white blood cells are unable to perform their tasks properly. Detecting leukemia usually requires taking a blood smear from a patient and working with expert hematologists who analyze the smear with a microscope. In this paper, a method to detect ALL and AML using a deep learner classifier is developed and proposed. The method detects both types, determines their severity, and creates a message that recommends next steps to patients. This approach works based on image segmentation and a convolutional neural network (CNN) tool called AlexNet. The obtained results from the proposed approach and using MATLAB reached more than 98% accuracy. The margin exists because several operations are needed to fully detect the blood cancer. A dataset of leukemia from the Kaggle site is used to test the developed method and illustrate its effectiveness. This dataset is C-NMC_Leukemia, and it consists of nearly 10 GB worth of 15,000 images. A confusion matrix of testing images is provided to prove the correctness of the presented approach. Furthermore, a comparative analysis between the proposed algorithm and some works from the literature is presented. This analysis compares the method used to extract features, the classifier that is utilized, the accuracy, the precision, and the recall. The obtained results indicate that the proposed method outperforms other works and produces better results.
Resilient Supply Chain Planning for the Perishable Products under Different Uncertainty
Authors: Chen Gaofeng , kaveh Farshad , Peivandizadeh Ali
Published: August 2022

In this research, the perishable products’ closed-loop supply chain network design problem is assessed by considering the disruption in production and distribution capacity and taking into account the uncertainty in customer demand. The main contribution of this research is modeling perishable products’ supply chain optimization and providing intelligent solution methods. In this regard, a mixed-integer mathematical model is proposed. This mathematical model consists of three objective functions. The first objective function is related to profit maximization, the second objective function is to minimize delivery time, and the third objective function is to reduce lost business days. Moreover, non-dominated sorting genetic algorithm II (NSGAII) and Multi-Objective Evolutionary Algorithm (MOEA) have been applied to optimize the proposed model. The research results show that the proposed meta-heuristic algorithm can provide a complete set of Pareto solutions in a reasonable amount of time. Moreover, based on different criteria, MOEA provides the non-dominated solutions with a higher quality, while NSGAII presents the Pareto boundary with more solutions than MOEA.
Lithology Logging Recognition Technology Based on GWO-SVM Algorithm
Authors: Lu Shengyan , Li Moujie , Luo Na , He Wei , He Xiaojun , Gan Changjian , Deng Rui
Published: August 2022

Accurate identification of lithology is the basis and key process of fine logging interpretation and evaluation. However, reservoirs formed by different sedimentary environments and tectonic movements generally have the characteristics of complex and diverse lithology and strong heterogeneity, which brings great difficulty to the identification of reservoir lithology. This paper proposes an automatic identification technology for lithology logging based on the GWO-SVM algorithm model. The technology is actually applied, and the results are compared with the results of the support vector machine cross-validation optimization model, PNN (probabilistic neural network) model, and ELM (extreme learning machine) model. The results show that the GWO-SVM lithology logging recognition model can efficiently solve the lithology recognition and classification problems in complex reservoir analysis and has strong adaptability and higher recognition accuracy.
Mayfly Taylor Optimisation-Based Scheduling Algorithm with Deep Reinforcement Learning for Dynamic Scheduling in Fog-Cloud Computing
Authors: Shruthi G. , Mundada Monica R. , Sowmya B. J. , Supreeth S.
Published: August 2022

Fog computing domain plays a prominent role in supporting time-delicate applications, which are associated with smart Internet of Things (IoT) services, like smart healthcare and smart city. However, cloud computing is a capable standard for IoT in data processing owing to the high latency restriction of the cloud, and it is incapable of satisfying needs for time-sensitive applications. The resource provisioning and allocation process in fog-cloud structure considers dynamic alternations in user necessities, and also restricted access resources in fog devices are more challenging. The global adoption of IoT-driven applications has led to the rise of fog computing structure, which permits perfect connection for mobile edge and cloud resources. The effectual scheduling of application tasks in fog environments is a challenging task because of resource heterogeneity, stochastic behaviours, network hierarchy, controlled resource abilities, and mobility elements in IoT. The deadline is the most significant challenge in the fog computing structure due to the dynamic variations in user requirement parameters. In this paper, Mayfly Taylor Optimisation Algorithm (MTOA) is developed for dynamic scheduling in the fog-cloud computing model. The developed MTOA-based Deep Q-Network (DQN) showed better performance with energy consumption, service level agreement (SLA), and computation cost of 0.0162, 0.0114, and 0.0855, respectively.
Effect of 1 + N Extended Nursing Service on Functional Recovery of Colostomy Patients
Authors: Feng Chunlan , Lv Caixia , Zhang Xia , Guo Yumei , Li Xiaojun
Published: August 2022

To many hospitals' management as well as to patients, the nursing service is one of the most important aspects. Many diseases like sugar, blood pressure, urine passage, and gas are a little bit dangerous to handle by patients themselves. The earlier stage models are unable to give good services to patients; therefore, an advanced JHE: Effect of 1 + N extended nursing service is necessary to crossover the above limitations. Colostomy and colorectal cancers are very dangerous syndromes thus, disease monitoring is so difficult. In this research work, an extended JHE: Effect of 1 + N extended nursing service modeling is discussed with experimental modeling. Apart from conventional nursing care provided by the observation group, it was given online training as well as service providing. Self-efficacy and self-care competence were assessed in both groups 6 months after the discharge. Quality of life and mental health were also assessed. Besides, their dimensional and total self-care ability scores, and the observation group’s self-efficacy ratings were substantially higher than those of the control group (

P

0.05) after the intervention. It was observed that the intervention group’s 6-month adjustment to the stoma was statistically more favorable than the control group’s (

P

0.001), and only the intervention group showed a significantly major change (

P

0.001) between their two evaluations. This proposed methodology can improve the accuracy rate by 93.23%, and succussive treatment rate of 92.14% had been attained.