bluuebunny/crossref_metadata_2025 huggingface dataset:
Changing physical activity behaviour for people with multiple sclerosis: protocol of a randomised controlled feasibility trial (iStep-MS)
Authors: Ryan Jennifer M , Fortune Jennifer , Stennett Andrea , Kilbride Cherry , Anokye Nana , Victor Christina , Hendrie Wendy , Abdul Mohamed , DeSouza Lorraine , Lavelle Grace , Brewin Debbie , David Lee , Norris Meriel
Published: May 2024

Introduction

Although physical activity may reduce disease burden, fatigue and disability, and improve quality of life among people with multiple sclerosis (MS), many people with MS are physically inactive and spend significant time in sedentary behaviour. Behaviour change interventions may assist people with MS to increase physical activity and reduce sedentary behaviour. However, few studies have investigated their effectiveness using objective measures of physical activity, particularly in the long term. Further, interventions that have proven effective in the short term may not be feasible in clinical practice because of the large amount of support provided. The iStep-MS trial aims to determine the safety, feasibility and acceptability of a behaviour change intervention to increase physical activity and reduce sedentary behaviour among people with MS.

Methods and analysis

Sixty people with MS will be randomised (1:1 ratio) to receive a 12-week intervention or usual care only. The intervention consists of four physical activity consultations with a physiotherapist supported by a handbook and pedometer. Outcomes assessed at baseline, 12 weeks and 9 months are physical activity (ActiGraph wGT3X-BT accelerometer), sedentary behaviour (activPAL3µ), self-reported activity and sitting time, walking capability, fatigue, self-efficacy, participation, quality of life and health service use. The safety of the intervention will be determined by assessing change in pain and fatigue and the incidence of adverse events during the follow-up period. A parallel process evaluation will assess the feasibility and acceptability of the intervention through assessment of fidelity to the programme and semistructured interviews exploring participants’ and therapists’ experiences of the intervention. The feasibility of conducting an economic evaluation will be determined by collecting data on quality of life and resource use.

Ethics and dissemination

Research ethics committee approval has been granted from Brunel University London. Results of the trial will be submitted for publication in journals and distributed to people with MS and physiotherapists.

Trial registration number

ISRCTN15343862(doi 10.1186/ISRCTN15343862). Protocol version: 1.0; Pre-results.
Psychological, behavioural and physiological effects of three long-acting reversible contraception (LARC) methods: protocol for an ancillary study of the ECHO randomised trial
Authors: Singata-Madliki Mandisa , Hofmeyr G Justus , Carayon-Lefebvre d’Hellencourt Florence , Lawrie Theresa Anne
Published: May 2024

Introduction

This is the protocol for an ancillary study to the multicentre Evidence for Contraceptive Options and HIV Outcomes (ECHO) Trial, a three-arm randomised trial comparing the effects of depot medroxyprogesterone acetate (DMPA), the levonorgestrel (LNG) implant and the copper intrauterine device (IUD) on HIV incidence (NCT02550067pre-results). The ancillary study will compare other non-contraceptive effects of these three long-acting, reversible contraceptions about which there is little existing comparative evidence.

Methods and analysis

Women randomised to IUD, DMPA and LNG implant (1:1:1) at one of the ECHO trial sites will be asked to participate in the ancillary study at the 1-month follow-up visit. Research staff will interview women that consent to participate at the 3-month follow-up visit. Primary outcomes are depression, sexual dysfunction and menstrual disturbances. The Beck Depression Inventory will be used to assess depression and the Arizona Sexual Experiences Scale to assess sexual dysfunction. Participants will also be asked to prospectively complete a 28-day symptom diary. The required sample size is 522 participants. Depression scores will be analysed as continuous and categorical variables. Analysis will be by intention to treat.

Ethics and dissemination

The ancillary study protocol received ethical approval from the University of the Witwatersrand Committee for Research on Human Subjects on 17 February 2016 (reference no. 14112). The results will be disseminated in a peer-reviewed open-access journal.

Trial registration number

PACTR201706001651380.
What are the barriers towards cervical cancer screening for vulnerable women? A qualitative comparative analysis of stakeholder perspectives in seven European countries
Authors: Bøje Rikke Buus , Bardou Marc , Mensah Keitly , Rico Berrocal Raquel , Giorgi Rossi Paolo , Bonvicini Laura , Auzzi Noemi , Taut Diana , Jiboc Nicoleta , Tisler Anna , Reintamm Kerli , Uusküla Anneli , Teixeira Margarida , Firmino-Machado João , Amorim Mariana , Baia Ines , Lunet Nuno , Michaylova Raya , Panayotova Yulia , Kotzeva Tatyana , Andersen Berit , Kirkegaard Pia
Published: May 2024

Objectives

The aim of this study was to map and compare stakeholders’ perceptions of barriers towards cervical cancer screening for vulnerable women in seven European countries.

Design

In Collaborative User Boards, stakeholders were invited to participate to identify barriers towards participation in cervical cancer screening.

Setting

The study is nested in the European Union-funded project CBIG-SCREEN which aims to tackle inequity in cervical cancer screening for vulnerable women (www.cbig-screen.eu). Data collection took place in Bulgaria, Denmark, Estonia, France, Italy, Portugal and Romania.

Participants

Participants represented micro-level stakeholders covering representatives of users, that is, vulnerable women, meso-level stakeholders covering healthcare professionals and social workers, and macro-level stakeholders covering programme managers and decision-makers.

Methods

Across the seven countries, 25 meetings in Collaborative User Boards with a duration of 2 hours took place between October 2021 and June 2022. The meetings were video recorded or audio recorded, transcribed and translated into English for a qualitative framework analysis.

Results

120 participants took part in the Collaborative User Boards. Context-specific barriers were related to different healthcare systems and characteristics of vulnerable populations. In Romania and Bulgaria, the lack of a continuous screening effort and lack of ways to identify eligible women were identified as barriers for all women rather than being specific for women in vulnerable situations. The participants in Denmark, Estonia, France, Italy and Portugal identified providers’ lack of cultural and social sensitivity towards vulnerable women as barriers. In all countries, vulnerable women’s fear, shame and lack of priority to preventive healthcare were identified as psychological barriers.

Conclusion

The study provides an overview of stakeholders’ perceived barriers towards vulnerable women’s cervical cancer screening participation in seven European countries. The organisation of healthcare systems and the maturity of screening programmes differ between countries, while vulnerable women’s psychological barriers had several similarities.
Association between hypertensive disorders and Bell’s palsy in pregnancy: protocol for a systematic review and meta-analysis
Authors: Liu Ya-Na , Yang Lin-Yi , Xue Zhi-Wei , Zhou Shu
Published: May 2024

Background

Bell’s palsy is an idiopathic peripheral nerve palsy involving the facial nerve. Pregnancy, diabetes mellitus and hypertension are the risk factors for Bell’s palsy. However, the association between hypertensive disorders and Bell’s palsy during pregnancy or the puerperium remains unclear. This systematic review will comprehensively summarise the literature and evaluate the association between Bell’s palsy and hypertensive disorders during pregnancy or the puerperium.

Methods and analysis

Systematic searches of PubMed, MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials will be undertaken using prespecified search strategies. Observational studies (cross-sectional studies, cohort studies, case reports and series case reports) written in English that investigate the association between hypertensive disorders of late pregnancy and Bell’s palsy during pregnancy or the puerperium will be included. Different authors will independently conduct the eligible study selection, perform data extraction and appraise the quality of included studies. Subgroup analysis will be carried out based on the age of pregnant women (≤35 years old, >35 years old), parity (primipara, multipara) and fetus number (singleton or multiple-gestation pregnancy).

Ethics and dissemination

This review will be based on published literature, and thus there is no requirement for ethics approval. The results of this study will aid in the knowledge of the relationship between Bell’s palsy during pregnancy or the puerperium and hypertensive disorders of late pregnancy. The results of this systematic review will be shared through publication in a peer-reviewed journal with good visibility for the field of obstetrics and presentations at academic conferences.

PROSPERO registration number

CRD42023422902.
Time to first birth and its predictors among reproductive-age women in Ethiopia: multilevel analysis using shared frailty model
Authors: Feyisa Bikila Regassa , Shiferaw Desalegn , Yesse Mubarek , Shama Adisu Tafari , Duressa Lemessa Terefe , Biru Bayise
Published: May 2024

Objective

To determine the time to first birth and its predictors among reproductive-age women in Ethiopia.

Design, setting and participants

Nationwide secondary data analysis using mini Ethiopian Demographic and Health Survey, 2019. A stratified, two-stage cluster sampling technique was used to select the sample. Among 9012 women of age 15–49 years, 8885 completed the interview yielding a response rate of 99%.

Main outcomes measured

Time to first birth was determined. Kaplan-Meier method was used to estimate the time to first birth. The lognormal inverse Gaussian shared frailty model was used to model the data at a 95% CI. CI and adjusted time ratio (ATR) were reported as effect size. Statistical significance was declared at p-value<0.05.

Results

The overall median time to give first birth was 18 years (IQR: 15, 21). Age 20–29 (ATR=1.08; 95% CI, 1.05 to 1.12), Age>29 years (ATR=1.08; 95% CI, 1.05 to 1.11), northern regions (ATR=1.06; 95% CI, 1.03 to 1.08), rural residence (ATR=0.95; 95% CI, 0.93 to 0.98), never using contraceptive methods (ATR=0.98; 95% CI, 0.96 to 0.99), sex of household head (ATR=1.01; 95% CI, 1 to 1.03), poorest wealth index (ATR=1.04; 95% CI, 1.02 to 1.06) and richest wealth index (ATR=1.07; 95% CI, 1.04 to 1.1) were the significant predictors of time to first birth among reproductive-age women.

Conclusion

In Ethiopia, women often gave birth to their first child at a younger age than what is recommended. Explicitly, women aged 20–29 and over 29, living in the northern region, leading a household as females, and belonging to the poorest or wealthiest wealth index tended to have a slightly delayed first childbirth. On the other hand, women in rural areas and those who had never used contraception were more likely to have an early first birth. The findings indicated the necessity of implementing targeted measures for rural Ethiopian women, especially those lacking knowledge about contraception.
Prevalence of neural tube defect and its identification during antenatal period: a cross-sectional study in eastern Indian state
Authors: Mahalik Santosh Kumar , Singh Arvind Kumar , Pati Akash Bihari , Rout Lipipuspa , Mallisha Subhra
Published: May 2024

Objective

To estimate the prevalence of neural tube defects among all birth outcomes in Odisha during 2016–2022. Additionally, to estimate the identification rate of neural tube defects during Pradhan Mantri Surakshit Matritva Abhiyan sessions.

Design

A population-based cross-sectional study with a household survey for neural tube defects using pictorial card as well as a hospital-based study for antenatal ultrasonography data.

Setting

The sample population was selected through multistage random sampling. In the first stage, one district from each zone was selected randomly. In the second stage, using simple random sampling, one community health centre and one urban primary health centre were selected from each district. In the third stage, the population from a block and ward were picked from the selected rural and urban settings, respectively.

Participants

All married women in the reproductive age group (18–49 years) residing in these cluster villages in the selected districts were enrolled.

Results

The study surveyed 49 215 women and recorded 50 196 birth outcomes, including 49 174 live births, 890 stillbirths and 132 medical terminations of pregnancy. A total of 30 neural tube defect cases were detected. The overall prevalence rate of neural tube defect was 0.59 per 1000 birth outcomes. Spina bifida was the most prevalent neural tube defect with the prevalence of, followed by anencephaly and encephalocele. Despite 26 860 mothers receiving antenatal ultrasonography Pradhan Mantri Surakshit Matritva Abhiyan session, data on neural tube defects and other birth defects detected through these scans is unavailable.

Conclusion

This study found a low prevalence of neural tube defect in Odisha, which is far lower compared with the older studies from India. There is an urgent need to strengthen the quality of antenatal care services provided under Pradhan Mantri Surakshit Matritva Abhiyan through better training regarding anomaly scans and better data keeping at public healthcare facilities.

Trial registration number

CTRI/2021/06/034487.
Coproduced, arts interventions for nurturing care (0–5 years) in low-income and middle-income countries (LMICs): a realist review
Authors: Gale Nicola Kay , Ahmed Kalim , Diarra Niélé Hawa , Manaseki-Holland Semira , Asamane Evans , Sidibé Cheick Sidya , Touré Ousmane , Wilson Michael , Griffiths Paula
Published: May 2024

Objectives

Community-based arts interventions have the potential to support contextually relevant nurturing care programmes and policies that adapt to different settings. Understanding the distinctive features of using the arts in local, culturally specific ways in low/middle-income countries (LMICs); how this varies by context; and gaining a better understanding of the perspectives on desirable outcomes for communities is important evidence that this review generates.

Design

We conducted a realist review of papers that covered outcomes related to child health or development (0–5 years) AND arts-based approaches AND community-based, participatory approaches AND based in LMICs using a range of databases and other networks. A coding framework was developed covering context, intervention, outcomes, mechanisms, study, sustainability, transferability and scalability.

Results

The included papers reported 18 unique interventions. Interventions covered 14 countries, with evidence lacking for South America, Arab countries and parts of Africa. Lead authors came from mostly clinical science-based disciplines and from institutions in a different country to the country/countries studied. Intended outcomes from interventions included clinical, health systems/organisation, changes in practices/behaviours/knowledge/attitudes, and wider social and educational goals. We identified three demi-regularities (semi-predictable patterns or pathways of programme functioning): participatory design based on valuing different sources of expertise; dynamic adaptation of intervention to context; and community participation in arts-based approaches.

Conclusions

Our findings suggest that arts-based, nurturing care interventions have greater potential when they include local knowledge, embed into existing infrastructures and there is a clear plan for ongoing resourcing of the intervention. Studies with better documentation of the lessons learnt, regarding the intervention delivery process and the power dynamics involved, are needed to better understand what works, for whom and in which contexts.
Unsupervised EEG-Based Seizure Anomaly Detection with Denoising Diffusion Probabilistic Models
Authors: Wang Jiale , Sun Mengxue , Huang Wenhui
Published: May 2024

While many seizure detection methods have demonstrated great accuracy, their training necessitates a substantial volume of labeled data. To address this issue, we propose a novel method for unsupervised seizure anomaly detection called SAnoDDPM, which uses denoising diffusion probabilistic models (DDPM). We designed a novel pipeline that uses a variable lower bound on Markov chains to identify potential values that are unlikely to occur in anomalous data. The model is first trained on normal data, then anomalous data is input to the trained model. The model resamples the anomalous data and converts it to normal data. Finally, the presence of seizures can be determined by comparing the before and after data. Moreover, the input 2D spectrograms are encoded into vector-quantized representations, which enables powerful and efficient DDPM while maintaining its quality. Experimental comparisons on the publicly available datasets, CHB-MIT and TUH, show that our method delivers better results, significantly reduces inference time, and is suitable for deployment in a clinical environments. As far as we are aware, this is the first DDPM-based method for seizure anomaly detection. This novel approach significantly contributes to the progression of seizure detection algorithms, thereby augmenting their practicality in clinical settings.
HDMA-CGAN: Advancing Image Style Transfer with Deep Learning
Authors: Liu Huaqun , Hu Benxi , Cao Yu
Published: May 2024

The integration of artificial intelligence (AI) and deep learning heralds a transformative era in pattern recognition and computer vision, notably in image style transfer. We introduce the hierarchical dynamic multi-attention cycle generative adversarial network (HDMA-CGAN), an innovative deep learning architecture poised to redefine image style transfer capabilities. HDMA-CGAN employs a novel multi-attention mechanism and color optimization strategies, enabling precise style replication with improved fidelity and vibrancy. Our model surpasses existing benchmarks in image quality, validated by leading metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and Fréchet inception distance (FID). Although HDMA-CGAN advances the state of the art, it necessitates high computational resources and faces challenges with very high-resolution images. Future work could explore optimizing the model’s efficiency for real-time applications and extending its application to video content. This work enhances the tools available for visual content creation and digital media enhancement, leveraging advanced pattern recognition and AI techniques to significantly impact computer vision and image processing.
Data-Driven Smart Assessment for Enterprise Audit Risks Based on Radial Base Function Neural Network and Grey Correlation Analysis
Authors: Yuan Jiezhen , Zhang Zhihong , Chen Zhuo
Published: May 2024

In the era of big data, audit risk assessment is facing increasing business volume. Hence, it is important to develop automatic audit risk assessment methods for enterprises with the assistance of intelligent algorithms. As a consequence, this paper proposes data-driven smart assessment for enterprise audit risks-based radial basis function (RBF) neural networks and grey correlation analysis (GCA). First, evaluation data are collected and analyzed to understand the characteristics and influencing factors of enterprise audit risks. Secondly, RBF interpolation is introduced to establish the network structure for RBF neural networks. Then, GCA is integrated with RBF Interpolation (RBFNN) to formulate the automatic audit risk evaluation method, and the proposal is named RBF and GCA. Such a combined methodology can improve audit risk assessment efficiency. Finally, we make some experiments to evaluate the proposed TBF-GCA on a real-world dataset, and some evaluation indicators are specified based on the actual audit risk situation of the enterprises. The obtained results reveal that RBF–GCA has high accuracy in identity precision and can effectively identify audit risks for enterprises.
An Attentional Recurrent Neural Network-Based Automatic Diagnosis Method for Machine Translation Errors
Authors: Huang Yan , Yu Xiaofang , Cheng Xiaoli , Wang Rujie
Published: May 2024

Although machine translation has achieved great progress in recent years, reliability always remains a concern in such task. Due to linguistic complexity and uncertainty, various errors are inevitably accompanied with machine translation results. It is also important to develop automatic error diagnosis methods for machine translation results. To deal with such an issue, this work combines both recurrent neural networks (RNN) and attention mechanisms. This work proposes an attentional RNN-based automatic error diagnosis method for machine translation. The collected machine translation results and corresponding reference results are collected to establish the experimental dataset. A large model named Recurrent Neural Machine Translation (RNMT) is utilized to extract semantic features from sentences generated by machine translation. A self-supervised diagnosis algorithm is accordingly formulated by introducing Jaccard similarity testing. Finally, the experiments are conducted on the specific dataset to evaluate the performance of the proposal. The research results show that the automatic diagnosis method obtained in this study has high accuracy, and it can meet the usage requirements in various aspects such as grammar, tense, single vocabulary and multi-vocabulary.
A note on invariant states of Gaussian quantum Markov semigroups
Authors: Fagnola Franco , Poletti Damiano
Published: May 2024

Gaussian quantum Markov semigroup on the algebra of bounded operator on a [Formula: see text]-mode Fock space is characterized either by the property of their predual that preserves quantum Gaussian states. In this paper, show that gaussian QMSs can have only Gaussian invariant states if the spectrum of the drift matrix does not contain points on the imaginary axis. Moreover, in this case, any initial state converges in trace norm toward a unique gaussian invariant state.
Nonlinear Effects of Mechanical and Aerodynamic Damping on a Motion-Amplitude-Dependent VIV Model
Authors: Qie Kai , Zhang Zhitian
Published: May 2024

Based on VIV time histories growing from still to limit cycle oscillations, the motion-amplitude dependence of the VIV loading model is determined. Energy-trapping properties corresponding to the entire process of motion evolution are described by the model parameters. The influence of nonlinear mechanical damping on the VIV loading model parameter is analyzed. Prediction of VIVs under higher mechanical damping ratios is performed by the identified VIV model. The results show that, while the model parameter [Formula: see text] varies drastically with the motion amplitude, the aerodynamic damping involves gently and monotonically towards a final value corresponding to an LCO state. Neglecting the nonlinearities in mechanical damping would result in significant deviations in model parameters and predicted VIV responses. By comparing the traditional fixed-[Formula: see text] model with the proposed nonlinear-[Formula: see text] model, it is found that the VIVs predicted by the former are about 1.5[Formula: see text]3.0 times those predicted by the latter or tested, which underlies the necessity of consideration of motion-amplitude-dependence of an aerodynamic model.
IMine: A CUSTOMIZABLE FRAMEWORK FOR INFLUENCE MINING IN COMPLEX NETWORKS
Authors: HUSSAIN OWAIS A. , ZAIDI FARAZ A.
Published: May 2024

The idea of discovering a few nodes with potential to impact an entire network, is known as Influence Maximization (IM) and has many real-world applications which make it one of well-studied research problems in the domain of network analysis. IM typically requires a fixed criteria of budget (number of influential nodes to be identified) as input. The fundamental premise of this research is that the budget is not the sole criteria for real-world applications. This study challenges the conventional method to identify influential nodes, and proves that it requires specification of the stoppage criteria and the model used to quantify influence. We analyze the complex interplay of various criteria that can be used to solve IM problem, and prove that changing the criterion also changes the algorithm determined as the top performer. A number of criteria are presented in this paper apart from budget, such as the spread achieved by the algorithm (in terms of number of nodes influenced) and absolute time. The proposed IMine framework provides an interface to apply influence problem on various stoppage criteria, while also providing customization option to change the model of quantifying influence spread.
Inhibition and Scavenging Free Radicals Activities by Natural Antioxidant: Honey Nanoparticles
Authors: Al-Mashhadani Asia H. , Ashour Omar S.
Published: May 2024

Honey nanoparticles have shown numerous unique characteristics such as biocompatibility and are excellent agents for biological applications. This study aims to investigate honey nanoparticles for 2, 2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical scavenging activity and their ability to offer protection against gamma radiation. In vitro antioxidant activity study of honey nanoparticles has shown good free radical scavenging activity for DPPH radical assayed within a concentration range of (0.05–2.5)[Formula: see text]×[Formula: see text][Formula: see text][Formula: see text]g/l, at higher concentrations of nanoparticles showed reverse trend in absorbance and inhibition indicating this finite range of concentration is suitable for scavenging free radicals, also nanoparticles were found to have significant antioxidant capacity and thus can be used as potential radical scavenger against deleterious damages caused by the free radicals.
An efficient implementation to compute the pseudoinverse for the incremental broad learning system on added inputs
Authors: Zhu Hufei , Liu Zhulin , Chen C. L. Philip , Liang Yanyang
Published: May 2024

In this paper, we improve the broad learning system (BLS) by speeding up the incremental learning for added inputs. We propose an efficient implementation for a step that is in the pseudoinverse computation of a partitioned matrix, to reduce the computational complexity. The proposed efficient implementation has two different forms for the cases of [Formula: see text] and [Formula: see text], respectively, where [Formula: see text] and [Formula: see text] denote the number of additional training samples and the total number of nodes, respectively. The proposed implementation for [Formula: see text] utilizes the inverse of a sum of matrices to compute only a [Formula: see text] matrix inverse, instead of a [Formula: see text] matrix inverse in the original implementation, and the corresponding speedup for the matrix inversion operation in the number of floating-point operations is [Formula: see text]. Moreover, it also speeds up two relevant matrix multiplication operations in the original implementation. On the other hand, the proposed implementation for [Formula: see text] speeds up one matrix multiplication operation in the original implementation. The numerical simulations show that both the proposed and original implementations always achieve the same testing accuracy. On the Modified National Institute of Standards and Technology dataset, the speedups of the proposed efficient BLS implementation over the original BLS implementation in total training time are 1.35–1.57 when [Formula: see text] and 1.09–1.13 when [Formula: see text], while on the NYU object recognition benchmark dataset, the speedups are 1.10–1.35 when [Formula: see text] and 1.07–1.09 when [Formula: see text].
Generalization bounds of incremental SVM
Authors: Zeng Jingjing , Zou Bin , Qin Yimo , Xu Jie
Published: May 2024

Incremental learning is one of the effective methods of learning from the accumulated training samples and the large-scale dataset. The main advantages of incremental learning consist of making full use of historical information, reducing the training scale greatly and saving space and time consumption. Despite extensive research on incremental support vector machine (SVM) learning algorithms, most of them are based on independent and identically distributed samples (i.i.d.). Not only that, there has been no theoretical analysis of incremental SVM learning algorithms. In this paper, we mainly study the generalization bounds of this incremental SVM learning algorithm whose samples are based on uniformly geometric Markov chains, and exponentially strongly mixing sequence. As a special case, we also obtain the generalization bounds of i.i.d. samples.
Body plan evolvability: The role of variability in gene regulatory networks
Authors: Spirov Alexander V. , Myasnikova Ekaterina M. , Holloway David M.
Published: May 2024

Recent computational modeling of early fruit fly (Drosophila) development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression. Gap genes are expressed with greater spatial precision than the maternal patterns. Computational modeling of the gap–gap regulatory interactions provides a mechanistic understanding for this robustness to maternal variability in wild-type (WT) patterning. A long-standing question in evolutionary biology has been how a system which is robust, such as the developmental program creating any particular species’ body plan, is also evolvable, i.e. how can a system evolve or speciate, if the WT form is strongly buffered and protected? In the present work, we use the WT model to explore the breakdown of such Waddington-type ‘canalization’. What levels of variability will push the system out of the WT form; are there particular pathways in the gene regulatory mechanism which are more susceptible to losing the WT form; and when robustness is lost, what types of forms are most likely to occur (i.e. what forms lie near the WT)? Manipulating maternal effects in several different pathways, we find a common gap ‘peak-to-step’ pattern transition in the loss of WT. We discuss these results in terms of the evolvability of insect segmentation, and in terms of experimental perturbations and mutations which could test the model predictions. We conclude by discussing the prospects for using continuum models of pattern dynamics to investigate a wider range of evo-devo problems.
Nonclassicality of squeezed number states
Authors: Gao Han-Xi , Ding Rong-Rong , Wang Lei-Lei , Jiang Li-Zhen , Chen Xiao-Yu
Published: May 2024

Nonclassicality is a useful quantum resource in quantum information and has important applications in various quantum tasks such as quantum computing, quantum communication. The robustness of nonclassicality is used to quantify the nonclassicality. The nonclassicality of number states, squeezed states and cat states has been known. We consider the nonclassicality of the squeezed number states. Several different upper and lower bounds for the nonclassicality of squeezed single photon state are obtained through analytical calculation, modeling analysis and numerical calculation. By comparing all these bounds, we find that the nonclassicality of squeezed single photon state can be well determined.
Quantum walk search for exceptional configurations
Authors: Giri Pulak Ranjan
Published: May 2024

There exist two types of configurations of marked vertices on a two-dimensional grid, known as the exceptional configurations, which are hard to find by the discrete-time quantum walk algorithms. In this article, we provide a comparative study of the quantum walk algorithm with different coins to search these exceptional configurations on a two-dimensional grid. We further extend the analysis to the hypercube, where only one type of exceptional configurations are present. Our observation, backed by numerical results, is that our recently proposed modified coin operator is the only coin which can search both types of exceptional configurations as well as nonexceptional configurations successfully. As a consequence, we observe that the existence of exceptional configurations are not a quantum phenomenon, rather a mere limitation of some of the coin operators.
Stellar modeling with quintessence field via embedding approach in Ratsall teleparallel gravity
Authors: Mahmood Irfan , Sohail Hira , Ditta Allah , Mahmood Asif
Published: May 2024

This paper proposes a new model for anisotropic compact stars with quintessence in Rastall teleparallel gravity via embedding approach. In the gravity, the acquired field equations encompassing the anisotropic matter source as well as the quintessence field are studied using the specific character of the scalar torsion [Formula: see text] for the observed stars candidates PSRJ[Formula: see text]1416–2230, 4U[Formula: see text]1608–52, CenX–3, EXO 1785–248 and SMC[Formula: see text]X–1. All of the stellar structures under consideration are said to be advantageously independent of any central singularity and are stable. A thorough graphical analysis reveals that numerous physical properties critical for forming stellar structures are satisfied.
Fuzzy Logic-Based Fragility Curve Development for Steel Moment-Resisting Frames Considering Uncertainties in Seismic Response
Authors: Jough Fooad Karimi Ghaleh
Published: May 2024

In this paper, a comprehensive range of uncertainties is considered to assess the seismic abilities of a moment-resisting system. To incorporate the parameter of construction quality, which has a descriptive nature, a suitable fuzzy logic engine has been developed. This engine, for the first time, addresses the quantitative assessment of construction quality parameters based on linguistic variables, including map accuracy, worker skills, material quality, and site supervision conditions. Instead of using random selection, a self-organizing map (SOM) algorithm is employed to carefully select strong ground motion records, reducing time costs. By applying incremental dynamic analysis (IDA) results, analytical equations are derived for the response surface method. These equations determine the collapse fragility’s mean and standard deviation. The material quality is modeled using the fuzzy inference engine, with the coefficient of logarithm response surface. Collapse fragility curves are created by taking into account many of their material quality values and utilizing the fuzzy model to estimate the modeling parameter based on the logarithm regression coefficients. These curves take into consideration various sources of uncertainty. In countries with inadequate material quality control, it is important to take cognitive uncertainty into account when developing fragility curves. This will help improve the overall risk management strategy.
A class of integer 3 × 3 matrices related to numerical semigroups with embedding dimension 4
Authors: Bajrami Merita , Dimovski Dončo , Angjelkoska Violeta
Published: May 2024

The aim of this paper is to present a class of integer [Formula: see text] matrices related to numerical semigroups with embedding dimension 4, generated by four integers [Formula: see text] and [Formula: see text] such that [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]. For a matrix [Formula: see text] of this class, we describe the Apéry set with respect to [Formula: see text], of the numerical semigroup related to [Formula: see text].
Investigation on relaxor-ferroelectric behavior of BNBT-KNN ceramics with Ta doping
Authors: Zhang Chenglong , Li Shurong , Li Suzhi , Zhang Le , Wu Haijun
Published: May 2024

In this study, BNBT-KNN-xTa2O5 was designed and synthesized, successfully achieving a reduction in the relaxor-ferroelectric phase transition temperature. Synergy between temperature-dependent ferroelectric testing and dielectric spectroscopy confirmed that the depoling temperature gradually decreased with increasing doping concentration. Fitting of the relaxation parameter and freezing temperature substantiated that the incorporation of Ta2O5 increased the degree of relaxation in BNBT-KNN-xTa2O5, thereby effectively lowering the relaxor-ferroelectric phase transition temperature.
Identifying the Impacts of Access to Different Information on Emergency Behaviors During COVID-19 Pandemic
Authors: Liu Qinliang , Li Xiaojing
Published: May 2024

Existing studies have verified the effect of information access on health behaviors, while less is known about the different impacts of distinct information access in a pandemic context. This study identified four information types (including disease knowledge, dynamic news, government measures, and social news) and then investigated how different information access affected preventive behaviors via perceived risk and media credibility during the COVID-19 outbreak in China. A nationally representative sampling survey on Chinese netizens was conducted ([Formula: see text]). It found that access to dynamic news, disease knowledge, and government measures positively predicted perceived severity, while only social news positively predicted perceived susceptibility. Access to disease knowledge, government measures, and social news were positively correlated with media credibility. The mediating roles of perceived risk and media credibility were proved. Besides, the statement of “cues-to-action” was also proved, which indicated that information access impacted behavioral changes more directly rather than through the mediators during COVID-19 pandemic. These findings contribute to a better understanding of how information access impacts public health behaviors in a pandemic context.
The First Principles: Setting the Context for a Safe and Secure Metaverse
Authors: Gupta Ankur , Sawhney Sahil , Kompella Kashyap
Published: May 2024

The metaverse delivered through converged and amalgamated technologies holds promise. No wonder technology heavyweights, large corporates, research organizations and businesses cutting across industry verticals are racing to put in place a metaverse-first strategy. The bets on consumers rapidly migrating from traditional social networks and collaborative applications to more immersive digital experiences have been placed. However, the transition is not expected to be seamless. Privacy, safety and security concerns abound in the early versions of the metaverse. Increased regulatory oversight and diverse national laws threaten to derail the hype around the metaverse. It is increasingly clear that the final iteration of the metaverse will need to assuage the concerns of individual users while addressing complex legal and regulatory requirements. Thus, a multi-perspective approach needs to be adopted to help set the agenda for the evolution of the metaverse. This research paper examines the different aspects and challenges which the future metaverse will need to address. A set of “first principles” are formulated, which if implemented will lead to the development of an equitable, inclusive, safe and secure metaverse.
Experimental Investigation of PEM Water Electrolyser Stack Performance Under Dynamic Operation Conditions
Authors: Liu Jingjing , Huang Liuyi , Leveneur Jérôme , Fiedler Holger , Clarke Sam , Larsen Thea , Kennedy John , Taylor Mark
Published: May 2024

Water electrolysis has been used to produce green hydrogen, for which identifying optimum operation parameters is crucial to improve its energy efficiency and energy consumption. This paper used a commercial proton exchange membrane (PEM) water electrolyser stack (180 W) to demonstrate the correlation between operating current change, temperature, and water flow rate and their impact on the thermal and electrical performance of the stack. It was found that the current control regime and temperature control can offset the voltage ageing in a long-term operating electrolyser with no negative impact on the H2 production rate. For a controlled decreasing current path, in the medium range of operating current, the stack’s energy efficiency was improved by 5%, and 3.7% specific energy consumption can be saved comparing to the standard operation (57.8 kWh·kg−1H2). The results provide insights into the potential optimisation in operation conditions to further increase cell energy efficiency and reduce energy consumption. This new finding sheds light on developing an energy- and cost-saving operating method for long-term green hydrogen production via water electrolysis.
Both endothelial mineralocorticoid receptor expression and hyperleptinemia are required for clinical characteristics of placental ischemia in mice
Authors: Moronge Desmond , Ayulo Victor , Elgazzaz Mona , Mellott Elisabeth , Ogbi Safia , Faulkner Jessica L.
Published: May 2024

Leptin is a key feature of preeclampsia that initiates vascular endothelial dysfunction in preeclampsia characterized by placental ischemia. Endothelial mineralocorticoid receptor (ECMR) deletion in placental ischemia protects pregnant mice from elevations in blood pressure and fetal growth restriction in pregnancy. Increases in leptin production mediate the key pathological feature of endothelial dysfunction in preeclampsia in rodents. ECMR activation contributes to the increase in blood pressure and fetal growth restriction in preeclampsia.
Identification of congenital aortic valve malformations in juvenile natriuretic peptide receptor 2-deficient mice using high-frequency ultrasound
Authors: Guruji Vrushali , Zhou Yu-Qing , Tang Mingyi , Mirzaei Zahra , Ding Yu , Elbatarny Malak , Latifi Neda , Simmons Craig A.
Published: May 2024

We developed a high-frequency ultrasound imaging protocol for diagnosing congenital aortic valve structural abnormalities in 4-wk-old mice. Our protocol defines specific criteria to distinguish mice with abnormal aortic valves from those with normal tricuspid valves using color Doppler, pulsed-wave Doppler, and two-dimensional (2-D) imaging with ultrahigh temporal resolution. This approach enables early identification of valvular abnormalities for efficient and ethical experimental design of longitudinal studies of congenital valve diseases and associated pathologies in mice.
The Renin-Angiotensin System Involvement in Cisplatin-Induced Nephrotoxicity: An Overview of Physiological and Pathological Mechanisms—A Systematic Review
Authors: Vakilian Aryan , Mohammadi Sina , Shokri Fatemeh , Maleki Maryam , Kheiry Maryam , Kheiri Amin
Published: May 2024

Cisplatin (CDDP) is a highly potent chemotherapy drug. But its nephrotoxicity poses a significant limitation to its use. The renin-angiotensin system (RAS) has been proposed to play a role in drug-induced nephrotoxicity. This systematic review (SR) sought to identify the link between CDDP-induced nephrotoxicity and the RAS pathway. In this SR, relevant keywords were employed to explore databases such as PubMed (MEDLINE), Scopus (Elsevier), and Institute for Scientific Information (ISI) Web of Science up to October 2023. Nine studies were selected based on predefined inclusion/exclusion criteria. The findings support the involvement of the RAS in the CDDP-induced nephrotoxicity model, along with the activation of inflammatory mediators, lipid peroxidation, and changes in markers of kidney tissue damage. Furthermore, physiology and pathology of RAS-related interventions in CDDP-induced nephrotoxicity models have involved the factors such as human organic cation transporter 2 (hOCT2), organic anion transporting polypeptides 1B1 (OATP1B1) and 1B3, kallikrein-kinin system, and bradykinin receptors. CDDP-induced nephrotoxicity has been found to be substantially influenced by both classic and nonclassic RAS axes. Angiotensin II exacerbates renal damage induced by CDDP. Conversely, inhibiting the pressor arm of RAS in males mitigates this damage. However, activation of the renal vasodepressor arm of RAS exacerbates CDDP-induced nephrotoxicity in females. These findings underscore gender differences in renal function and response to RAS-related interventions in the presence of CDDP. This SR provides insights into both beneficial and adverse interventions associated with RAS in the CDDP-induced nephrotoxicity, offering valuable considerations for researchers and clinicians.
Breaking Boundaries with Ceramic Matrix Composites: A Comprehensive Overview of Materials, Manufacturing Techniques, Transformative Applications, Recent Advancements, and Future Prospects
Authors: Rashid Adib Bin , Haque Mahima , Islam S. M. Mohaimenul , Uddin Labib K. M. Rafi , Chowdhury Pavel
Published: May 2024

Ceramic matrix composites (CMCs) are a category of advanced materials which have gained significant interest recently due to their remarkable mechanical and thermal characteristics. These composites are composed of ceramic fibers, particles, or other types of ceramics incorporated in a ceramic matrix and have shown the capability to be implemented in several sectors, including aerospace, energy, and biomedical engineering. This review paper will provide a synopsis of the current scenario and recent progress in CMCs, including materials and processing techniques, characterization methods, and applications. The paper discusses the advantages and limitations of CMCs, recent advancements, and future trends in research. The microstructural and mechanical properties of CMCs are also reviewed, highlighting their potential for various applications. The paper’s conclusion delivers a summary of the essential findings and a discussion of future directions for CMC research.
Intelligent Detection of Surface Defects in High‐Speed Railway Ballastless Track Based on Self‐Attention and Transfer Learning
Authors: Ye Wenlong , Ren Juanjuan , Li Chen , Liu Wengao , Zhang Zeyong , Lu Chunfang
Published: May 2024

The detection of ballastless track surface (BTS) defects is a prerequisite for ensuring the safe operation of high‐speed railways. Traditional convolutional neural networks fail to fully exploit contextual information and lack global pixel representations. The extensive stacking of convolutions leads deep learning models to play a black‐box detection role, lacking interpretability. Due to the current lack of sufficient high‐quality surface data for ballastless tracks, it is a severe constraint on the accurate identification of the substructure state in high‐speed railways. This paper proposes an intelligent detection method for BTS defects named TrackNet based on self‐attention and transfer learning. The method enhances the fusion ability of global features of BTS defects using multihead self‐attention. The model’s dependence on extensive defect data is reduced by transferring knowledge from large‐scale publicly available datasets. Experimental results demonstrate that compared to advanced Swin Transformer model results, the TrackNet model achieves improvements in average accuracy and F1‐score by 5.15% and 5.16%, respectively, on limited test data. The TrackNet model visualizes the decision regions of the model in identifying BTS defects, revealing the black‐box recognition mechanism of deep learning models. This research performs engineering applications and provides valuable insights for the multiclass recognition of BTS defects in high‐speed railways.
On Implicit Atangana–Baleanu–Caputo Fractional Integro-Differential Equations with Delay and Impulses
Authors: Karthikeyann Panjaiyan , Poornima Sadhasivam , Karthikeyan Kulandhaivel , Promsakon Chanon , Sitthiwirattham Thanin
Published: May 2024

In this paper, we study the existence and uniqueness of solutions for impulsive Atangana-Baleanu-Caputo ABC fractional integro-differential equations with boundary conditions. Schaefer’s fixed point theorem and Banach contraction principle are used to prove the existence and uniqueness results. An example is presented to illustrate the results.