bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbiomics and volatile metabolomics-based investigation of changes in quality and flavor of oat (Avena sativa L.) silage at different stages
Authors: Deng Xiaochen , Jia Yushan , Ge Gentu , Wang Zhijun , Liu Mingjian , Bao Jian , Zhao Muqier , Si Qiang , Liu Yichao , Zhao Weixuan
Published: November 2023

Objective

This study aimed to analyze the fermentation quality, microbial community, and volatile metabolites of oat silage harvested at two different stages, while examining the correlation between microorganisms and volatile metabolites.

Methods

Oats were harvested at two growth stages (pre-heading [PRH] and post-heading [POH] stages), followed by 90 days of natural fermentation, with 6 replicates per treatment. Pre- and post-silage samples were randomly selected for nutrient composition, fermentation parameters, microbial population, and high-throughput sequencing analysis. Volatile metabolomics analysis was also performed on samples after 90 days of fermentation to detect differences in flavor quality after silage.

Results

The effect of growth stage on the nutrient content of oats was significant, with pre-heading oats having higher crude protein and post-heading oats having higher water soluble carbohydrates content (p < 0.05). Following a 90-day fermentation period, the pH and ammonia nitrogen/total nitrogen levels in the PRH-90 (silage from pre-heading oats after 90 days of fermentation) group demonstrated a significant decrease (p < 0.05), whereas the lactic acid content was notably higher compared to the POH-90 (silage from post-heading oats after 90 days of fermentation) group (p <0.05). Lactiplantibacillus dominated in the PRH-90 group and Enterococcus dominated in the POH-90 group, with abundances of (> 86%) and (> 87%), respectively. The differential volatile metabolites of the two treatment groups were dominated by esters and terpenoids, and the differences in flavor were mainly concentrated in sweet, green, and fruity odors. The results of Kyoto encyclopedia of genes and genomes pathway enrichment analysis demonstrated three major metabolic pathways: phenylpropanoid biosynthesis, phenylalanine metabolism, and biosynthesis of secondary metabolites. Specific microorganisms were significantly correlated with flavor indicators and flavor metabolites. Lactiplantibacillus was significantly positively correlated with flavor substances indicating sweet and fruity flavors, contributing to good flavor, while Enterococcus was significantly and positively correlated with flavor substances indicating bad flavors.

Conclusion

In summary, growth stage had significant effects on nutritional components, fermentation parameters and flavor quality of oats, with the fermentation process dominated by Lactiplantibacillus leading to good flavor, while the fermentation process dominated by Enterococcus led to the development of poor flavor.
Self-reported HPV vaccination status and HPV vaccine hesitancy in a nationally representative sample of emerging adults in Croatia
Authors: Nemeth Blažić Tatjana , Božičević Ivana , Kosanović Ličina Mirjana Lana , Štulhofer Aleksandar , Nola Iskra Alexandra
Published: November 2023

Introduction

The aim of this study was to determine self-reported human papillomavirus (HPV) vaccination status among emerging adults in Croatia, intention to get the HPV vaccine among unvaccinated individuals and correlates of HPV vaccine hesitancy.

Methods

Data were collected via a cross-sectional survey based on a probabilistic national sample. The sample included 1,197 individuals aged 18–25 years (50.6% were women) who were recruited from November 2021 to February 2022 as part of the commercial online panel. Analyses included 981 participants who correctly answered two “attention trap” questions using descriptive statistics and multivariate analyses. The data were post-hoc weighted for gender and age and adjusted for clustering effect. To adjust standard errors for the sampling design, multivariate analyses were carried out using the complex samples module in the IBM SPSS 27 statistical software package.

Results

Overall, 18.3% of participants (25.0% of women and 11.7% of men) reported that they were HPV vaccinated, while 21.9% did not know their HPV vaccination status. Of those vaccinated, 65.6% were women. The odds of being HPV-vaccinated were significantly higher among female participants. Among the unvaccinated, 35.4% expressed a willingness to get the vaccine. The odds of vaccination hesitancy were significantly lower among women, participants who reported a higher perceived risk of STIs, those who recognized that HPV could result in cervical cancer, and significantly higher among those who were more religious.

Conclusion

Our findings suggest a need to increase HPV vaccination uptake in Croatia through raising awareness about HPV vaccine effectiveness and also through the implementation of strategies to make vaccination more available.
Health care costs of cardiovascular disease in China: a machine learning-based cross-sectional study
Authors: Lu Mengjie , Gao Hong , Shi Chenshu , Xiao Yuyin , Li Xiyang , Li Lihua , Li Yan , Li Guohong
Published: November 2023

Background

Cardiovascular disease (CVD) causes substantial financial burden to patients with the condition, their households, and the healthcare system in China. Health care costs for treating patients with CVD vary significantly, but little is known about the factors associated with the cost variation. This study aims to identify and rank key determinants of health care costs in patients with CVD in China and to assess their effects on health care costs.

Methods

Data were from a survey of patients with CVD from 14 large tertiary grade-A general hospitals in S City, China, between 2018 and 2020. The survey included information on demographic characteristics, health conditions and comorbidities, medical service utilization, and health care costs. We used re-centered influence function regression to examine health care cost concentration, decomposing and estimating the effects of relevant factors on the distribution of costs. We also applied quantile regression forests—a machine learning approach—to identify the key factors for predicting the 10th (low), 50th (median), and 90th (high) quantiles of health care costs associated with CVD treatment.

Results

Our sample included 28,213 patients with CVD. The 10th, 50th and 90th quantiles of health care cost for patients with CVD were 6,103 CNY, 18,105 CNY, and 98,637 CNY, respectively. Patients with high health care costs were more likely to be older, male, and have a longer length of hospital stay, more comorbidities, more complex medical procedures, and emergency admissions. Higher health care costs were also associated with specific CVD types such as cardiomyopathy, heart failure, and stroke.

Conclusion

Machine learning methods are useful tools to identify determinants of health care costs for patients with CVD in China. Findings may help improve policymaking to alleviate the financial burden of CVD, particularly among patients with high health care costs.
A deep transfer learning approach for COVID-19 detection and exploring a sense of belonging with Diabetes
Authors: Ahmad Ijaz , Merla Arcangelo , Ali Farman , Shah Babar , AlZubi Ahmad Ali , AlZubi Mallak Ahmad
Published: November 2023

COVID-19 is an epidemic disease that results in death and significantly affects the older adult and those afflicted with chronic medical conditions. Diabetes medication and high blood glucose levels are significant predictors of COVID-19-related death or disease severity. Diabetic individuals, particularly those with preexisting comorbidities or geriatric patients, are at a higher risk of COVID-19 infection, including hospitalization, ICU admission, and death, than those without Diabetes. Everyone’s lives have been significantly changed due to the COVID-19 outbreak. Identifying patients infected with COVID-19 in a timely manner is critical to overcoming this challenge. The Real-Time Polymerase Chain Reaction (RT-PCR) diagnostic assay is currently the gold standard for COVID-19 detection. However, RT-PCR is a time-consuming and costly technique requiring a lab kit that is difficult to get in crises and epidemics. This work suggests the CIDICXR-Net50 model, a ResNet-50-based Transfer Learning (TL) method for COVID-19 detection via Chest X-ray (CXR) image classification. The presented model is developed by substituting the final ResNet-50 classifier layer with a new classification head. The model is trained on 3,923 chest X-ray images comprising a substantial dataset of 1,360 viral pneumonia, 1,363 normal, and 1,200 COVID-19 CXR images. The proposed model’s performance is evaluated in contrast to the results of six other innovative pre-trained models. The proposed CIDICXR-Net50 model attained 99.11% accuracy on the provided dataset while maintaining 99.15% precision and recall. This study also explores potential relationships between COVID-19 and Diabetes.
Molecular effects of intermittent stress on primary feline uroepithelial cell culture as an in vitro model of feline idiopathic cystitis
Authors: Hatala Patrícia , Sebők Csilla , Mackei Máté , Kárpáti Karina , Gálfi Péter , Neogrády Zsuzsanna , Mátis Gábor
Published: November 2023

Introduction

The most common cause of feline lower urinary tract disease (FLUDT) is feline idiopathic cystitis (FIC), which is a complex multifactorial disease with symptoms including stranguria, dysuria, hematuria, and pain during urination. The development of these symptoms is often triggered by stress, and in case of chronic stress, these symptoms will many times return. One of the most important stress hormones in the pathogenesis of FIC is norepinephrine (NE), as persistently elevated level of this hormone can be measured in the blood of cats with FIC. However, it is not well understood if recurrently elevated level of NE has any direct effect on urinary bladder, therefore the aim of this study was to investigate the molecular effects of intermittent NE exposure on feline primary uroepithelial cell culture.

Methods

Primary uroepithelial cells were gained from the mucosa of the bladder of a euthanized cat, and were cultured for 6 days, then they were exposed to 10, 100, and 1,000 μM NE treatment for 3 × 1 h, including a 1 h long regeneration period between exposures.

Results

NE was able to trigger pro-inflammatory response and oxidative stress in the uroepithelial cells by increasing the level of stromal cell derived factor 1 (SDF-1) and H2O2in cell culture media. In addition, NE increased the permeability of the uroepithelium, since decreased glycosaminoglycan (GAG) concentration, tight junction protein claudin-4 content, and TER values were measured after the NE treatments.

Discussion

Based on these results it can be concluded that recurrent stress mimicked by 3×1 h NE treatment has a direct molecular effect on the uroepithelial cells, which leads to inflammatory response, oxidative stress and decreased barrier function of the uroepithelium. Therefore, intermittent release of NE may have an important role in the pathogenesis of FIC and the results of this study may contribute to a better understanding of the development of this illness.
A Cooperative Target Localization Method Based on UAV Aerial Images
Authors: Du Minglei , Zou Haodong , Wang Tinghui , Zhu Ke
Published: November 2023

A passive localization algorithm based on UAV aerial images and Angle of Arrival (AOA) is proposed to solve the target passive localization problem. In this paper, the images are captured using fixed-focus shooting. A target localization factor is defined to eliminate the effect of focal length and simplify calculations. To synchronize the positions of multiple UAVs, a dynamic navigation coordinate system is defined with the leader at its center. The target positioning factor is calculated based on image information and azimuth elements within the UAV photoelectric reconnaissance device. The covariance equation is used to derive AOA, which is then used to obtain the target coordinate value by solving the joint UAV swarm positional information. The accuracy of the positioning algorithm is verified by actual aerial images. Based on this, an error model is established, the calculation method of the co-localization PDOP is given, and the correctness of the error model is verified through the simulation of the Monte Carlo statistical method. At the end of the article, the trackless Kalman filter algorithm is designed to improve positioning accuracy, and the simulation analysis is performed on the stationary and moving states of the target. The experimental results show that the algorithm can significantly improve the target positioning accuracy and ensure stable tracking of the target.
Detection and Analysis of Radiation Doses in Multiple Orbital Space during Solar Minimum
Authors: Wang Juyu , Zhang Shenyi , Shen Guohong , Sun Ying , Zhang Binquan , Chang Zheng , Wang Chunqin , Hou Donghui , Yang Zhe
Published: November 2023

Based on orbit detection data acquired by a positive channel Metal Oxide Semiconductor (PMOS) dose detectors on FY4-A (GEO), BD3-M15 (MEO), and YH1-01A (LEO) between November 2018 and November 2022, investigations reveal variations in total dose and the mechanism of radiation dose increase within the geostationary earth orbit (GEO), medium earth orbit (MEO), and low earth orbit (LEO) during the transition from the 24th to the 25th solar cycles. It provides the radiation dose parameters for the study of the space environment from different altitude orbits, and also provides an important basis for studying the solar minimum activity and dose generation The data indicate directional disparities in radiation doses among the orbital regions, with the hierarchy being FY4-A > YH1-01A > BD3-M15. Furthermore, the results show that the total doses of FY4-A and BD3-M15 were higher than that of YH1-01A by two orders of magnitude, with BD3-M15 > FY4-A > YH1-01A. The monthly radiation dose rates of FY4-A in GEO and BD3-M15 in MEO exhibited positive correlation with their corresponding APs during the solar minimum. Notably, for FY4-A, the monthly radiation dose rate during geomagnetic disturbed periods exceeded that of the dose rate during geomagnetic quiet periods by one order of magnitude. This analysis revealed the substantial impact of geomagnetic storms and space environment disturbances on radiation doses detected by MEO and GEO orbital satellites. These perturbations, attributable to medium- and small-scale high-energy electron storms induced by reproducible coronal holes, emerged as key driving factors of the increase in radiation doses in MEO and GEO environments.
Three-Dimensional Path-Following Control Method for Flying–Walking Power Line Inspection Robot Based on Improved Line of Sight
Authors: Feng Tianming , Lei Jin , Zeng Yujie , Qin Xinyan , Wang Yanqi , Wang Dexin , Jia Wenxing
Published: November 2023

The Flying–Walking Power Line Inspection Robot (FPLIR) faces challenges in maintaining stability and reliability when operating in harsh transmission line environments with complex conditions. The robot often switches modes frequently to land accurately on the line, resulting in increasing following errors and premature or delayed switching caused by reference path switching. To address these issues, a path-following control method based on improved line of sight (LOS) is proposed. The method features an adaptive acceptance circle strategy that adjusts the radius of the acceptance circle of the path point based on the angle of the path segment and the flight speed at the time of switching, improving path-following accuracy during reference trajectory switching. Also, an adaptive heading control with vertical distance feedback is designed to prioritize different path-following methods in real time based on variations in vertical distance, achieving rapid convergence along the following path. The state feedback following control law, based on the improved LOS, achieves the stable following of the reference path, which was validated by simulations. The simulation results show that the improved LOS reduces the convergence time by 0.8 s under controllable error conditions for path angles of θ ∈ (0, π⁄2). For path angles of θ ∈ (π⁄2, π), the following error is reduced by 0.3 m, and the convergence time is reduced by 0.4 s. These results validate the feasibility and effectiveness of the proposed method. This method demonstrates advantages over the traditional LOS in terms of following accuracy and convergence speed, providing theoretical references for future 3D path following for path-following robots and aerial vehicles.
Review of Energy-Efficient Embedded System Acceleration of Convolution Neural Networks for Organic Weeding Robots
Authors: Czymmek Vitali , Köhn Carolin , Harders Leif Ole , Hussmann Stephan
Published: November 2023

The sustainable cultivation of organic vegetables and the associated problem of weed control has been a current research topic for some time. Despite this, the use of chemical and synthetic pesticides increases every year. This is to be solved with the help of an automated robot system. The current version of the weeding robot uses GPUs to execute the inference phase. This requires a lot of energy for an 8-track robot. To enable autonomous solar operation, the system must be made more energy efficient. This work aims to evaluate possible approaches and the current state of research on implementing convolution neural networks on low power embedded systems. In the course of the work, the technical feasibility for the implementation of CNNs in FPGAs was examined, in particular, following the example of a feasibility analysis. This paper shows that the acceleration of convolution neural networks using FPGAs is technically feasible for use as detection hardware in the weeding robot. With the help of the current state of research and the existing literature, the optimization possibilities of the hardware and software have been evaluated. The trials of different networks on different hardware accelerators with diverse approaches were investigated and compared.
Directing the Apple Rhizobiome toward Resiliency Post-Fumigation
Authors: Somera Tracey , Mazzola Mark , Cook Chris
Published: November 2023

Currently, there are no standard management practices to counteract the adverse effects of fumigation on the soil microbiome. In this study, a variety of pre-plant soil amendments were examined for their ability to recruit and maintain apple rhizosphere microbiomes that are suppressive to pathogen re-infestation of fumigated orchard soils. The capacity of these amendments to improve other characteristics of soil productivity was also evaluated. Results suggest that composted chicken manure and liquid chitin are likely to be detrimental to plant and soil health when used as a post-fumigation soil amendment. In comparison, insect frass (IF) resulted in a significant increase in tree trunk diameter relative to the fumigated control. Following pathogen re-infestation of fumigated soil, however, IF induced a significant increase in Pythium ultimum in the rhizosphere. Therefore, IF can benefit the growth of young apple trees in fumigated soil but may stimulate pathogen activity upon re-infestation. To date, the possibility of using soil amendments to suppress pathogen re-infestation of fumigated soils has not been tested. Results from this study ground support the use of soil amendments as an intervention strategy for “steering” the soil and rhizosphere microbiome in more beneficial and/or prophylactic directions following fumigation.
Heredity and Regulation of a Potential Commercial Crop: Perilla frutescens
Authors: Shen Qi , Sun Di , Duan Wu , Yang Zhi Min
Published: November 2023

Perilla (Perilla frutescens L [...]
Collaborative Wheat Lodging Segmentation Semi-Supervised Learning Model Based on RSE-BiSeNet Using UAV Imagery
Authors: Zhi Hongbo , Yang Baohua , Zhu Yue
Published: November 2023

Lodging is a common natural disaster during wheat growth. The accurate identification of wheat lodging is of great significance for early warnings and post-disaster assessment. With the widespread use of unmanned aerial vehicles (UAVs), large-scale wheat lodging monitoring has become very convenient. In particular, semantic segmentation is widely used in the recognition of high-resolution field scene images from UAVs, providing a new technical path for the accurate identification of wheat lodging. However, there are still problems, such as insufficient wheat lodging data, blurred image edge information, and the poor accuracy of small target feature extraction, which limit the recognition of wheat lodging. To this end, the collaborative wheat lodging segmentation semi-supervised learning model based on RSE-BiseNet is proposed in this study. Firstly, ResNet-18 was used in the context path of BiSeNet to replace the original backbone network and introduce squeeze-and-excitation (SE) attention, aiming to enhance the expression ability of wheat lodging characteristics. Secondly, the segmentation effects of the collaborative semi-supervised and fully supervised learning model based on RSE-BiSeNet were compared using the self-built wheat lodging dataset. Finally, the test results of the proposed RSE-BiSeNet model were compared with classic network models such as U-Net, BiseNet, and DeepLabv3+. The experimental results showed that the wheat lodging segmentation model based on RSE-BiSeNet collaborative semi-supervised learning has a good performance. The method proposed in this study can also provide references for remote sensing UAVs, other field crop disaster evaluations, and production assistance.
Amyloid β-Oligomers Inhibit the Nuclear Ca2+ Signals and the Neuroprotective Gene Expression Induced by Gabazine in Hippocampal Neurons
Authors: Lobos Pedro , Vega-Vásquez Ignacio , Bruna Barbara , Gleitze Silvia , Toledo Jorge , Härtel Steffen , Hidalgo Cecilia , Paula-Lima Andrea
Published: November 2023

Hippocampal neuronal activity generates dendritic and somatic Ca2+ signals, which, depending on stimulus intensity, rapidly propagate to the nucleus and induce the expression of transcription factors and genes with crucial roles in cognitive functions. Soluble amyloid-beta oligomers (AβOs), the main synaptotoxins engaged in the pathogenesis of Alzheimer’s disease, generate aberrant Ca2+ signals in primary hippocampal neurons, increase their oxidative tone and disrupt structural plasticity. Here, we explored the effects of sub-lethal AβOs concentrations on activity-generated nuclear Ca2+ signals and on the Ca2+-dependent expression of neuroprotective genes. To induce neuronal activity, neuron-enriched primary hippocampal cultures were treated with the GABAA receptor blocker gabazine (GBZ), and nuclear Ca2+ signals were measured in AβOs-treated or control neurons transfected with a genetically encoded nuclear Ca2+ sensor. Incubation (6 h) with AβOs significantly reduced the nuclear Ca2+ signals and the enhanced phosphorylation of cyclic AMP response element-binding protein (CREB) induced by GBZ. Likewise, incubation (6 h) with AβOs significantly reduced the GBZ-induced increases in the mRNA levels of neuronal Per-Arnt-Sim domain protein 4 (Npas4), brain-derived neurotrophic factor (BDNF), ryanodine receptor type-2 (RyR2), and the antioxidant enzyme NADPH-quinone oxidoreductase (Nqo1). Based on these findings we propose that AβOs, by inhibiting the generation of activity-induced nuclear Ca2+ signals, disrupt key neuroprotective gene expression pathways required for hippocampal-dependent learning and memory processes.
Gaussian Mixture Model for Marine Reverberations
Authors: Sun Tongjing , Wen Yabin , Zhang Xuegang , Jia Bing , Zhou Mengwei
Published: November 2023

Ocean reverberations, a significant interference source in active sonar, arise as a response generated by random scattering at the receiving end, a consequence of randomly distributed clutter or irregular interfaces. Statistical analysis of reverberation data has revealed a predominant adherence to the Rayleigh distribution, signifying its departure from specific distribution forms like the Gaussian distribution. This study introduces the Gaussian mixture model, capable of simulating random variables conforming to a wide array of distributions through the integration of an adequate number of components. Leveraging the unique statistical attributes of reverberation, we initiate the Gaussian mixture model’s parameters via the frequency histogram of the reverberation data. Subsequently, model parameters are estimated using the expectation–maximization (EM) algorithm and the most suitable statistical model is selected based on robust model selection criteria. Through a comprehensive evaluation that encompasses both simulated and observed data, our results underscore the Gaussian mixture model’s effectiveness in accurately characterizing the distribution of reverberation data, yielding a mean squared error of less than 4‰.
The Dual-Parameter Control of Synchronization in Steel Box Girder Incremental Launching Construction
Authors: Li Qingfu , Guo Hao , Guo Biao
Published: November 2023

When a steel box girder is constructed using the jacking method, the contact area between the jack and the bottom of the girder is subjected to complex forces, and it is very critical to ensure the local stability of the girder. When the phenomenon of unsynchronized jacking occurs, it will lead to changes in the contact area and affect the structural safety. In order to solve the above problems, this paper takes the background of the incremental launching construction of the main bridge across the Yellow River on Jiao Ping Expressway, adopts the Midas FEA NX 2021 finite element software to establish a finite element hybrid unit model under the maximum cantilever condition for the first time, and analyzes the local stresses in this state. The results show that the local maximum equivalent stress of the steel box girder is 198.301 MPa, which meets the requirements. The effect of jacking asynchrony on the structural forces is analyzed by simulating jacking asynchrony in the local model. The results show that both vertical jacking asynchrony and lateral deflection will lead to an increase in local stresses in the steel box girder and even steel yielding. On the basis of the above single-parameter study, a two-parameter correlation analysis is carried out to obtain the two-parameter control equation of jacking, the control threshold of the vertical jacking height difference is formulated to be 15 mm, and the dynamic control of lateral deflection is realized according to the control equation. Through comparison, it is found that the two-parameter control threshold of jacking synchronization is reduced, which can supplement the unfavorable state missed during single-parameter control and is a safer and more effective means of control.
Parameter Identification of a Permanent Magnet Synchronous Motor Based on the Model Reference Adaptive System with Improved Active Disturbance Rejection Control Adaptive Law
Authors: Qi Xin , Sheng Chunyang , Guo Yongbao , Su Tao , Wang Haixia
Published: November 2023

Aiming at the problem that online parameter identification, based on the Model Reference Adaptive System (MRAS), is easily affected by the high-frequency noise of the sensor, an improved MRAS, based on variable bandwidth linear Active Disturbance Rejection Control (ADRC) adaptive law, is proposed. The proposed ADRC adaptive law, including an extended state observer, exhibits good anti-disturbance ability while effectively tracking the error signal through adjusting the bandwidth of the controller according to the observation error. When the observation error is large, the bandwidth of the controller is increased to enhance the tracking accuracy; in the opposite situation, the bandwidth is reduced to improve the anti-disturbance performance. To illustrate feasibility, a stability analysis of the proposed ADRC adaptive law is carried out and some comparison and validation experiments are designed to identify the inductance and flux linkage of the permanent magnet synchronous motor (PMSM). The experimental results show that the proposed method has better anti-disturbance performance than the MRAS based on traditional Proportional Integral (PI) adaptive law or switched PI adaptive law.
Research on Variable-Step-Size Adaptive Filter Algorithm with a Momentum Term
Authors: Li Binbin , Lu Bo , Kou Xiping , Shi Yang , Yu Li , Guo Hongtao , Lv Binbin , Zeng Kaichun
Published: November 2023

To address the contradiction between the convergence error and convergence rate in the LMS algorithm, this study proposes a variable-step-size adaptive filter algorithm with a momentum term based on the logistic function. First, the normalization LMS algorithm is obtained by seeking the extremum under the Lagrange function constraint. Second, to reduce the convergence error of the algorithm, the logistic model is used as a function model of step size variation with error, resulting in a variable-step normalization LMS algorithm. Our experimental results demonstrate that this algorithm achieves smaller convergence errors compared to those of the traditional LMS algorithm. Finally, to further improve the convergence rate of the algorithm, a momentum term is introduced into the weight coefficient update process of the LMS algorithm. This leads to the development of a variable-step adaptive filter algorithm with a momentum term based on the logistic function. The impact of different parameters on the algorithm performance is also investigated. In order to verify the rationality of the proposed algorithm, a dynamic system mathematical model was identified using the proposed algorithm. The results showed that the proposed algorithm had an identification accuracy of over 97% for the mathematical model parameters and a suppression of over 99% for noise. In order to verify the engineering application value of the proposed algorithm, real-time vibration data fitting experiments were conducted in the Aeroelasticity Laboratory of the China Aerodynamics Research and Development Center, and their results were compared with three algorithms: ARMAX, N4SID, and LMS. The results showed that the proposed algorithm had a higher fitting accuracy than the three others. Through simulations and experiments, it is demonstrated that this study has value both theoretically and in engineering applications, promoting engineering applications of adaptive filtering algorithms and providing strong support for the research of adaptive control.
Urban Road Traffic Spatiotemporal State Estimation Based on Multivariate Phase Space–LSTM Prediction
Authors: Wang Ning , Zhang Buhao , Gu Jian , Kong Huahua , Hu Song , Lu Shengchao
Published: November 2023

The road traffic state is usually analyzed from a temporal and macroscopic perspective; however, traffic flow parameters, such as density and spacing, can explain the evolution of traffic states from the microscopic perspective and the spatial distribution of vehicles in lanes. In this paper, we attempt to take both temporal and spatial characteristics into consideration simultaneously, and a parameter is defined as the traffic spatiotemporal state of urban road sections to represent the operational status of road traffic, using advanced prediction techniques to estimate its short-term trends. An estimation method is constructed for the traffic spatiotemporal state considering travel times, speeds, and queuing situations from temporal and spatial perspectives. Then, based on Takens’ theorem and the single variable phase space, the phase space of multiple traffic parameters is reconstructed and the chaotic characteristics are analyzed. Next, an LSTM prediction model is constructed based on the phase space reconstruction of multiple variables, and the traffic parameters are predicted by empirical analysis. The results show the proposed estimation method has a significantly improved accuracy. Finally, combined with RFID data, the traffic spatiotemporal state of the case section is calculated, which provides a theoretical basis and practical reference for road traffic state evaluations.
Cutibacterium acnes Dysbiosis: Alternative Therapeutics for Clinical Application
Authors: Sá Sara , Fernandes Ruben , Gestoso Álvaro , Macedo José Mário , Martins-Mendes Daniela , Pereira Ana Cláudia , Baylina Pilar
Published: November 2023

Cutibacterium acnes (C. acnes) is a Gram-positive anaerobic facultative bacterium that is part of the human skin commensal microbiome. It colonizes various regions of the body, including the face, back, and chest. While typically a harmless commensal, under certain conditions, C. acnes can become pathogenic, leading to or promoting conditions such as acne vulgaris (AV), post-surgical infections, prostate cancer, and sarcoidosis. Current treatments for C. acnes infections often involve antibiotics, but the rise of antibiotic resistance has raised concerns. This review presents the virulence factors, clinical relevance, and current treatments of C. acnes, highlighting its association with AV, post-surgical infections, and other diseases. It also explores alternative innovative therapies such as phage therapy in development/research that are gaining prominence, with a growing focus on personalized medical approaches. To enhance C. acnes treatment while minimizing side effects and antibiotic prescription concerns, numerous clinical studies have been undertaken. These investigations span various pathological profiles and employ diverse strategies, such as utilizing bacterial extracts and compounds to restore healthy skin flora. The limitations and challenges of current and innovative treatments are also addressed, emphasizing the need for multidisciplinary strategies to combat C. acnes infections effectively.
A Regularized Tseng Method for Solving Various Variational Inclusion Problems and Its Application to a Statistical Learning Model
Authors: Taiwo Adeolu , Reich Simeon
Published: November 2023

We study three classes of variational inclusion problems in the framework of a real Hilbert space and propose a simple modification of Tseng’s forward-backward-forward splitting method for solving such problems. Our algorithm is obtained via a certain regularization procedure and uses self-adaptive step sizes. We show that the approximating sequences generated by our algorithm converge strongly to a solution of the problems under suitable assumptions on the regularization parameters. Furthermore, we apply our results to an elastic net penalty problem in statistical learning theory and to split feasibility problems. Moreover, we illustrate the usefulness and effectiveness of our algorithm by using numerical examples in comparison with some existing relevant algorithms that can be found in the literature.
Development of PVA Electrospun Nanofibers for Fabrication of Bacteriological Swabs
Authors: Pellegrino Rebecca , Villani Stefania , Spagnolo Daniela , Carofalo Irene , Carrino Nico , Calcagnile Matteo , Alifano Pietro , Madaghiele Marta , Demitri Christian , Nitti Paola
Published: November 2023

In recent years, the enormous demand for swabs for clinical use has promoted their relevance and, consequently, brought the environmental issues due to their single use and lack of biodegradability to the attention of the healthcare industry. Swabs consist of a stick that facilitates their easy handling and manoeuvrability even in complex districts and an absorbent tip designed to uptake and release biological samples. In this study, we focused on the fabrication of an innovative biodegradable poly(vinyl alcohol) (PVA) nanofiber swab tip using the electrospinning technique. The innovative swab tip obtained showed comparable uptake and release capacity of protein and bacterial species (Pseudomonas aeruginosa and Staphylococcus aureus) with those of the commercial foam-type swab. In this way, the obtained swab can be attractive and suitable to fit into this panorama due to its low-cost process, easy scalability, and good uptake and release capabilities.
Significance of Premature Vertebral Mineralization in Zebrafish Models in Mechanistic and Pharmaceutical Research on Hereditary Multisystem Diseases
Authors: Van Wynsberghe Judith , Vanakker Olivier
Published: November 2023

Zebrafish are increasingly becoming an important model organism for studying the pathophysiological mechanisms of human diseases and investigating how these mechanisms can be effectively targeted using compounds that may open avenues to novel treatments for patients. The zebrafish skeleton has been particularly instrumental in modeling bone diseases as—contrary to other model organisms—the lower load on the skeleton of an aquatic animal enables mutants to survive to early adulthood. In this respect, the axial skeletons of zebrafish have been a good read-out for congenital spinal deformities such as scoliosis and degenerative disorders such as osteoporosis and osteoarthritis, in which aberrant mineralization in humans is reflected in the respective zebrafish models. Interestingly, there have been several reports of hereditary multisystemic diseases that do not affect the vertebral column in human patients, while the corresponding zebrafish models systematically show anomalies in mineralization and morphology of the spine as their leading or, in some cases, only phenotype. In this review, we describe such examples, highlighting the underlying mechanisms, the already-used or potential power of these models to help us understand and amend the mineralization process, and the outstanding questions on how and why this specific axial type of aberrant mineralization occurs in these disease models.
Dapagliflozin Mitigated Elevated Disomic and Diploid Sperm in a Mouse Model of Diabetes and Recover the Disrupted Ogg1, Parp1, and P53 Gene Expression
Authors: Albekairi Norah A. , Al-Hamamah Mohammed A. , Alshamrani Ali A. , Attia Mohamed S. M. , Nadeem Ahmed , Ansari Mushtaq A. , Ahmad Sheikh F. , Bakheet Saleh A. , Attia Sabry M.
Published: November 2023

Increases in numerical chromosomal syndromes were observed in children of diabetic mothers. However, the effects of diabetes on male reproduction, specifically numerical chromosomal aberrations (aneuploidy), have not been studied. Furthermore, despite the increasing use of dapagliflozin for diabetes treatment, no data exists on its ability to affect aneuploidy levels in germ cells. Thus, our investigation aimed to evaluate the effects of diabetes on spontaneous sperm aneuploidy and whether treatment with dapagliflozin influences the frequency of aneuploidy in the sperm of an experimental diabetic animal model. Our findings show that dapagliflozin has no aneugenic effects on the meiotic stages of spermatogenesis. In contrast, diabetes raised the frequency of aneuploidy, and dapagliflozin administration decreased the elevated levels of disomic and diploid sperm. The level of oxidative stress was markedly increased in diabetic mice, but were reduced by dapagliflozin treatment. Furthermore, the expression of some of DNA repair genes was disrupted in diabetic animals, whereas dapagliflozin therapy restored these disruptions and significantly enhanced DNA repair. Thus, dapagliflozin may effectively ameliorate diabetes-induced aneugenic effects on male meiosis and treating diabetic patients with dapagliflozin may effectively mitigate the transmission of diabetes-induced chromosomal defects to offspring.
Peak Bone Mass Formation: Modern View of the Problem
Authors: Akhiiarova Karina , Khusainova Rita , Minniakhmetov Ildar , Mokrysheva Natalia , Tyurin Anton
Published: November 2023

Peak bone mass is the amount of bone tissue that is formed when a stable skeletal state is achieved at a young age. To date, there are no established peak bone mass standards nor clear data on the age at which peak bone mass occurs. At the same time, the level of peak bone mass at a young age is an important predictor of the onset of primary osteoporosis. The purpose of this review is to analyze the results of studies of levels of peak bone mass in general, the age of its onset, as well as factors influencing its formation. Factors such as hormonal levels, body composition, physical activity, nutrition, heredity, smoking, lifestyle, prenatal predictors, intestinal microbiota, and vitamin and micronutrient status were considered, and a comprehensive scheme of the influence of these factors on the level of peak bone mass was created. Determining the standards and timing of the formation of peak bone mass, and the factors affecting it, will help in the development of measures to prevent its shortage and the consequent prevention of osteoporosis and concomitant diseases.
Kidney Renin Release under Hypoxia and Its Potential Link with Nitric Oxide: A Narrative Review
Authors: Kong Weiwei , Liao Yixin , Zhao Liang , Hall Nathan , Zhou Hua , Liu Ruisheng , Persson Pontus B. , Lai Enyin
Published: November 2023

The renin–angiotensin system (RAS) and hypoxia have a complex interaction: RAS is activated under hypoxia and activated RAS aggravates hypoxia in reverse. Renin is an aspartyl protease that catalyzes the first step of RAS and tightly regulates RAS activation. Here, we outline kidney renin expression and release under hypoxia and discuss the putative mechanisms involved. It is important that renin generally increases in response to acute hypoxemic hypoxia and intermittent hypoxemic hypoxia, but not under chronic hypoxemic hypoxia. The increase in renin activity can also be observed in anemic hypoxia and carbon monoxide-induced histotoxic hypoxia. The increased renin is contributed to by juxtaglomerular cells and the recruitment of renin lineage cells. Potential mechanisms regulating hypoxic renin expression involve hypoxia-inducible factor signaling, natriuretic peptides, nitric oxide, and Notch signaling-induced renin transcription.
Preparation and Application of a Fast, Naked-Eye, Highly Selective, and Highly Sensitive Fluorescent Probe of Schiff Base for Detection of Cu2+
Authors: Liu Juan , Cheng Peng-Yu , Chen Sai , Wang Meng , Wei Kai , Li Yuan , Cao Yao-Yao , Wang Xing , Li Hong-Lei
Published: November 2023

A fluorescent probe, N′-((3-methyl-5-oxo-1-phenyl-4, 5-dihydro-1H-pyrazol-4-yl) methylene)-2-oxo-2H-chromene-3-carbohydrazide (MPMC), was synthesized and characterized. Characterizations of the synthetic MPMC were conducted via proton nuclear magnetic resonance (1HNMR) spectroscopy and carbon-13 nuclear magnetic resonance spectroscopy (13C NMR). The fluorescence emission behaviors of the MPMC probe towards diverse metal ions were detected, and the probe exhibited high sensitivity and selectivity towards Cu2+ over other metal ions via the quenching of its fluorescence. Furthermore, the existence of other metal actions made no apparent difference to the fluorescence intensity of the MPMC-Cu2+ system; that is, MPMC displayed a good anti-interference ability. Job’s plot of the MPMC and copper ions indicated that the detection limit was 10.23 nM (R2 = 0.9612) for the assayed actions, with a stoichiometric ratio of 1:1 for MPMC and Cu2+. Additionally, the color of the MPMC probe solution changed from nearly colorless to yellow in the presence of Cu2+ in visible light, and the color change could be observed by the naked eye. Similarly, the color resolved from bright yellow into blue in ultraviolet light. Moreover, reusability studies indicated that the MPMC probe was reusable. The pH effect of the MPMC probe on Cu2+ had a broad range of pH detection, i.e., from 4.0 to 11.0. The response time of the MPMC probe for determining Cu2+ was within 1 min. The recognition of Cu2+ via MPMC performed on pre-treated paper under sunlight and UV light both had a distinct colour change. Thus, the solid-state method for detecting Cu2+ with the naked eye was both economical and convenient.
Pupils’ Attitudes toward Inclusive Education
Authors: Strnadova Anna , Potmesil Milon , Potmesilova Petra
Published: November 2023

The presented research is a study of the attitudes of adolescents toward individuals with disabilities and a description of the level of knowledge about this issue among a selected group of adolescents. The study is focused on the school social environment, specifically on pupils without disabilities and their attitudes toward pupils with disabilities, which is one of the factors influencing their school success. The target group was 1806 pupils between the ages of 11 and 16 from the entire Czech Republic, approached by random selection. The research tool for the quantitative approach was a questionnaire developed by the authors of this article. The questionnaire section with open questions served for the qualitative part of the research. The results show that 70% of the respondents have basic knowledge about people with disabilities. Furthermore, it was shown that these adolescents have an overall positive attitude toward people with disabilities. This attitude is statistically significantly better among the girls than the boys, and the girls are also more open to discussing individuals with disabilities. At the same time, even if attitudes are positive, they still depend on the type of disability. The greatest uncertainty or discomfort is manifested when interacting with individuals with intellectual disabilities.
Global Cardiac Surgery—Accessibility to Cardiac Surgery in Developing Countries: Objectives, Challenges, and Solutions
Authors: Agati Salvatore , Bellanti Ermanno
Published: November 2023

Cardiac surgery is a modern science in the history of medicine. The impact of cardiac disease, in terms of treatment and prognosis, has made this discipline indispensable to global health. In recent decades, the greatest investment has been dispensed to technological and material improvements to increase life expectancy. This surgery must address different epidemiological aspects dictated by the geography and economic–social conditions of the global populations. For this reason, it is progressively important to address the cardiac surgery accessibility disparity. Many scientific papers and international meetings have studied how cardiac surgery can be more accessible in various countries around the world. In this review, we analyze all the challenges, solutions, and suggestions that can make this surgery accessible to the entire global population, with the purpose of reducing its disparity across all seven continents. For a long time, high-income countries have invested in technological capabilities and experimental advancements without caring about unequal access in the rest of the world. We believe that it is time to reverse this growth trajectory, placing the accessibility and distribution of surgical science as a priority, which is significant for the right to health of all people worldwide. This is the real new challenge in cardiosurgery.
A Novel Methodology Analyzing the Influence of Micro-Stresses on Human-Centric Environments
Authors: Shakhovska Nataliya , Kaminskyy Roman , Khudoba Bohdan , Mykhailyshyn Vladyslav , Helzhynskyi Ihor
Published: November 2023

This article offers experimental studies and a new methodology for analyzing the influence of micro-stresses on human operator activity in man–machine information and search interfaces. Human-centered design is a problem-solving technique that puts real people at the center of the design process. Therefore, mindfulness is one of the most important aspects in various fields such as medicine, industry, and decision-making. The human-operator activity model can be used to create a database of specialized test images and a computer for its implementation. The peculiarity of the tests is that they represent images of real work situations obtained as a result of texture stylization and allow the use of an appropriate search difficulty scale. A mathematical model of a person who makes a decision is built. The requirements for creating a switch to solve the given problem are discussed. This work summarizes the accumulated experience of such studies.