bluuebunny/crossref_metadata_2025 huggingface dataset:
Wideband Ring-Monopole Flexible Antenna with Stub for WLAN/C-Band/X-Band Applications
Authors: Lee Hoosung , Park Yong Bae
Published: October 2022

In this paper, we designed a flexible antenna operating in the WLAN/C-band/X-band and analyzed the antenna bending characteristics. It is advantageous to have a wide bandwidth because the resonant frequency of the flexible antenna can be changed when it is bent. The proposed antenna was designed based on a ring monopole antenna with broadband characteristics. Slots and t-strip lines to the ring, stubs to the feed, and stepped structures to the ground plane were added to increase bandwidth. As a result of analyzing the characteristics of the proposed antenna when bent through the S-parameter, it was confirmed that the proposed antenna is suitable at the target frequency, even if it is bent. The size of the antenna is 0.256 λ × 0.32 λ × 0.0016 λ (32×40×0.2 mm3) at 2.4 GHz, and the antenna bandwidth is 15.68% (2.36 GHz~2.87 GHz) at 2.615 GHz and 111.69% (3.4 GHz~12 GHz) at 7.7 GHz.
Dynamic Response of Rectangular Tunnels Embedded at Various Depths in Spatially Variable Soils
Authors: Zhang Yanjie , Zhang Houle , Wu Yongxin
Published: October 2022

This study investigated the seismic response of rectangular tunnels with various embedment depths considering the spatial variability of soil shear modulus. The spectral representation method was adopted to simulate the anisotropic random field of soil. The excess pore water pressure, the liquefied zone, the ground displacement and the uplift displacement of the tunnel were obtained through the random finite difference method to analyze the seismic response. It was observed that the soil excess pore water pressure ratio under the tunnel gradually decreased and the liquefaction degree reduced with depth increase. The peak value of the liquefied zone range increased with the increase in embedment depth. The mean response of stochastic analysis was smaller than the deterministic calculation results when the tunnel embedment depth was less than 10 m. The maximum tunnel floating displacement obtained from random analyses had the probability of 67.3%, exceeding the value calculated by deterministic analyses when H = 12 m.
Numerical Study on Aerodynamic Noise Reduction of Pantograph
Authors: Shi Fangcheng , Shi Fushan , Tian Xudong , Wang Tiantian
Published: October 2022

A hybrid method incorporating the simulations of noise sources with delayed detached eddy simulation (DDES) and calculations of far-field noise with the Ffowcs Williams–Hawkings (FW-H) equation is used to study the suppression technique for the aerodynamic noise of a Faiveley CX-PG pantograph. Considering that China’s Fuxing bullet trains operate at 350 km/h, the inflow velocity of 350 km/h is applied in this paper. The noise radiated from the panhead area, middle area, and bottom area at an inflow velocity of 350 km/h is distinguished. The noise intensities at the standard observer show that the noise radiated from the panhead area is the strongest, and the sound pressure level spectrum value is larger than the other two in the range above 500 Hz. The influence of applying the wavy rods and modifying the contact strip shape on the aerodynamic noise is discussed in detail. By comparing the acoustic source distribution and the far-field noise intensity, it is found that applying the wavy rods can effectively reduce the panhead noise, especially around the peak frequency. Modifying the shape of the contact strip to a hexagon can suppress the vortex shedding, leading to a lower surface pressure level. Combining the strip modification and wavy rods, the total noise intensity can be diminished by about 3.0 dB.
Safety Workplace: The Prevention of Industrial Security Risk Factors
Authors: Erazo-Chamorro Vanessa C. , Arciniega-Rocha Ricardo P. , Rudolf Nagy , Tibor Babos , Gyula Szabo
Published: October 2022

“To earn a living”. The definition of work and our understanding of the workplace have changed in recent years due to the emergence of occupational health and is now a field of study under continuous improvement. Despite the fact that there is a huge amount of information, studies, and guidance about how to improve occupational security, the factors that must be considered in a workplace as real hazards to avoid in order to achieve a truly healthy workplace are always subject to debate. This research contributes to efforts in two important ways. The first goal assesses the information about security risk factors established and mentioned by official international institutions aimed at safety and security science by using the relationship and categorization between the identified risks during work activities performance. The second goal is to establish the necessary requirements to be fulfilled to ensure that a workplace will be considered “healthy and safe”. As a result, it is defined that the lack of ergonomics represents the most critical risk factor in order to reduce the incidence of work-related illness during the design and continuous improvement of a tailored workplace.
PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform
Authors: Tian Bin , Wen Shiqiang , Li Xi , Ju Jianping , Tang Jianyin , Xiong Naixue
Published: October 2022

Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line system). Moreover, a new information extraction technique is extended by employing Synchrosqueezed Wavelet Transform (SSWT) to improve the accuracy of the MASD method. With the extended information extraction technique, the time-frequency information of the anomalies can be efficiently distinguished from the power frequency magnetic anomaly signal. The multi-component of the time-frequency information is separated by extracting the time-frequency ridges in the spectrogram. The complexity of time-frequency information is evaluated using Rayleigh entropy. Compared with the continuous wavelet transform and short-time Fourier transform, the Rayleigh entropy of our method is reduced by 4.1886 and 4.3623, respectively. Finally, the efficiency of the new method is verified by the outfield experiments.
Efficient Reliability-Based Inspection Planning for Deteriorating Bridges Using Extrapolation Approaches
Authors: Kwon Kihyon , Park Ki-Tae , Jung Kyu-San , Kim Sunyong
Published: October 2022

In this study, inspection planning of deteriorating bridges is optimized to determine the inspection application times and methods based on various objectives. These objectives can be formulated by considering the probabilistic structural performance and service life after inspection and maintenance. Probabilistic structural performance and service life prediction are generally based on the probability of failure (or reliability). However, there are difficulties associated with optimizing inspection planning when a low probability of failure is estimated. In this study, we address inspection planning using extrapolation approaches to efficiently compute a low probability of failure. The inspection planning method proposed in this study determines the inspection application times for a given inspection method. We investigated the applicability of direct Monte Carlo simulation (MCS), subset simulation, and two extrapolation approaches (i.e., kernel density estimation (KDE) and KDE combined with generalized Pareto distribution (GPD)) for inspection planning. The probability of failure for optimum inspection planning was based on the damage detection-based state function and extended service life-based state function. These state functions were formulated by considering damage propagation, damage detection by inspections, and service life extensions by maintenance. Illustrative applications to general examples and an existing bridge are provided to investigate the effects of approaches for computing the failure probability on the accuracy and variation of the optimum inspection application times. Finally, the most appropriate approach for optimum inspection planning was determined considering the accuracy and reliability of the solution, computational efficiency, and the applicability of the probabilistic optimization process. The presented investigations revealed that KDE is more appropriate than MCS and the combination of KDE and GPD for optimum inspection planning.
Research on a Day-Ahead Grouping Coordinated Preheating Method for Large-Scale Electrified Heat Systems Based on a Demand Response Model
Authors: Guo Guodong , Gong Yanfeng
Published: October 2022

In recent years, the increasing winter load peak has brought great pressure on the operation of power grids. The demand response on the load side helps to alleviate the expansion of the power grid and promote the consumption of renewable energy. However, the response of large-scale electric heat loads to the same electricity price curve will lead to new load peaks and regulation failure. This paper proposes a grouping coordinated preheating framework based on a demand response model, which realizes the interaction of information between the central controller and each regulation group. The room thermal parameter model and the performance map of the inverter air conditioner/heat pump are integrated into the demand response model. In this framework, the coordination mechanism is adopted to avoid regulation failure, an edge computing structure is applied to consider the users’ preferences and plans, the grouping and parallel computing structure is proposed to improve the computing efficiency. Users optimize their heat load curves based on a demand response model, which can consider travel planning and ensure user comfort. The central controller updates the marginal cost curve based on the predicted scenario set to coordinate the regulation groups and suppress the new peaks. The simulation results show that the proposed method can promote the consumption of renewable energy through coordinated preheating and reduce the system energy consumption cost and user bills. The parallel computing structure within the regulation group also ensures the computing efficiency under large-scale loads.
Predicting Hospital Admissions to Reduce Crowding in the Emergency Departments
Authors: Cusidó Jordi , Comalrena Joan , Alavi Hamidreza , Llunas Laia
Published: October 2022

Having an increasing number of patients in the emergency department constitutes an obstacle to the admissions process and hinders the emergency department (ED)’s ability to deal with the continuously arriving demand for new admissions. In addition, forecasting is an important aid in many areas of hospital management, including elective surgery scheduling, bed management, and staff resourcing. Therefore, this paper aims to develop a precise prediction model for admissions in the Integral Healthcare System for Public Use in Catalonia. These models assist in reducing overcrowding in emergency rooms and improve the quality of care offered to patients. Data from 60 EDs were analyzed to determine the likelihood of hospital admission based on information readily available at the time of arrival in the ED. The first part of the study targeted the obtention of models with high accuracy and area under the curve (AUC), while the second part targeted the obtention of models with a sensitivity higher than 0.975 and analyzed the possible benefits that could come from the application of such models. From the 3,189,204 ED visits included in the study, 11.02% ended in admission to the hospital. The gradient boosting machine method was used to predict a binary outcome of either admission or discharge.
Learning from Multiple Instances: A Two-Stage Unsupervised Image Denoising Framework Based on Deep Image Prior
Authors: Xu Shaoping , Chen Xiaojun , Tang Yiling , Jiang Shunliang , Cheng Xiaohui , Xiao Nan
Published: October 2022

Supervised image denoising methods based on deep neural networks require a large amount of noisy-clean or noisy image pairs for network training. Thus, their performance drops drastically when the given noisy image is significantly different from the training data. Recently, several unsupervised learning models have been proposed to reduce the dependence on training data. Although unsupervised methods only require noisy images for learning, their denoising effect is relatively weak compared with supervised methods. This paper proposes a two-stage unsupervised deep learning framework based on deep image prior (DIP) to enhance the image denoising performance. First, a two-target DIP learning strategy is proposed to impose a learning restriction on the DIP optimization process. A cleaner preliminary image, together with the given noisy image, was used as the learning target of the two-target DIP learning process. We then demonstrate that adding an extra learning target with better image quality in the DIP learning process is capable of constraining the search space of the optimization process and improving the denoising performance. Furthermore, we observe that given the same network input and the same learning target, the DIP optimization process cannot generate the same denoised images. This indicates that the denoised results are uncertain, although they are similar in image quality and are complemented by local details. To utilize the uncertainty of the DIP, we employ a supervised denoising method to preprocess the given noisy image and propose an up- and down-sampling strategy to produce multiple sampled instances of the preprocessed image. These sampled instances were then fed into multiple two-target DIP learning processes to generate multiple denoised instances with different image details. Finally, we propose an unsupervised fusion network that fuses multiple denoised instances into one denoised image to further improve the denoising effect. We evaluated the proposed method through extensive experiments, including grayscale image denoising, color image denoising, and real-world image denoising. The experimental results demonstrate that the proposed framework outperforms unsupervised methods in all cases, and the denoising performance of the framework is close to or superior to that of supervised denoising methods for synthetic noisy image denoising and significantly outperforms supervised denoising methods for real-world image denoising. In summary, the proposed method is essentially a hybrid method that combines both supervised and unsupervised learning to improve denoising performance. Adopting a supervised method to generate preprocessed denoised images can utilize the external prior and help constrict the search space of the DIP, whereas using an unsupervised method to produce intermediate denoised instances can utilize the internal prior and provide adaptability to various noisy images of a real scene.
The Effects of Origanum vulgare L. Essential Oils on Anaesthesia and Haemato-Biochemical Parameters in Mozambique Tilapia (Oreochromis mossambicus) Post-Juveniles
Authors: Gabriel Ndakalimwe Naftal , Liswaniso Gadaffi M. , Haihambo Wilhelm , Abasubong Kenneth Prudence
Published: October 2022

This study investigated the effects of oregano (Origanum vulgare) essential oil (OEO) anaesthesia and stress-related physiological parameters in tilapia mossambicus (Oreochromis mossambicus) post-juveniles. Fish were subjected to different concentrations of OEO (25, 50, 100, and 150 μL L−1) to assess the effects of the anaesthesia and recovery time. A second experiment subjected fish to other handling treatments, including a control (no OEO exposure), ethanol solution, 25 μL L−1 (low effective anaesthesia concentration of OEO), and 100 μL L−1 high effective anaesthesia concentration of OEO) for 10 min to assess the haemato-biochemical indices and survival rate at 0 h and after 24 h. Moreover, all the tested OEO concentrations induced anaesthesia in the studied fish, where the anaesthesia induction time decreased with increased OEO concentrations. Meanwhile, the inverse was reported for recovery time. Based on the ideal anaesthetic criteria, 50 μL L−1 and 100 μL L−1 were the suitable concentrations that could be recommended for quick anaesthesia. However, according to the haemato-biochemical parameters and survival results, 25 μL L−1 was safe to anaesthetise tilapia mossambicus for 10 min and could be recommended for time-consuming fish-handling procedures. Future studies should investigate multiple factors that influence anaesthesia in fish for better optimisation of OEO in tilapia mossambicus.
Concentration, Source, and Health Risk Assessment of Polycyclic Aromatic Hydrocarbons: A Pilot Study in the Xuanwei Lung Cancer Epidemic Area, Yunnan Province, China
Authors: Zhang Mengyuan , Shao Longyi , Jones Timothy P. , Feng Xiaolei , Schnelle-Kreis Jürgen , Cao Yaxin , BéruBé Kelly A.
Published: October 2022

Polycyclic aromatic hydrocarbons (PAHs) are toxic and hazardous volatile environmental pollutants that have been studied as possible major causative agents of lung cancer in Xuanwei. In this paper, indoor and outdoor PM2.5 samples were collected from two homes at different time periods in Hutou, the lung cancer epidemic area in Xuanwei. The results showed that PAH pollution levels from coal combustion in Xuanwei lung cancer epidemic area were significant. The mass concentrations of total PAHs, major carcinogenic compounds, and benzo[a]pyrene-based equivalent concentration (BaPeq) were significantly higher in the coal-using home than in the electricity-using home. For the coal-using home, the PAHs were mainly derived from coal combustion. For the electricity-using home, the PAHs might have been a combination of traffic and coal combustion sources. The human health risk due to inhalation exposure to the PAHs was represented by the incremental lifetime cancer risk (ILCR) of the inhalation exposure. The results showed that the indoor cancer risk for the coal-using home in Xuanwei is higher than that of the electricity-using home and much higher than that of Chinese megacities such as Beijing and Tianjin. Long-term exposure to indoor coal-burning environments containing high levels of PAHs may be one of the main reasons for the high incidence of lung cancer in Xuanwei.
Adaptation Analysis in IMERG Precipitation Estimation for the Dongting Lake Basin, China
Authors: Li Shanshan , Jiang Changbo , Ma Yuan , Long Yuannan , Wu Ruixuan , Zhu Qingxiong , Li Donglin , Li Chuannan , Ning Zihao
Published: October 2022

Precipitation data from ground-based observatories in the Dongting Lake basin are often missing, resulting in large errors in surface precipitation data obtained by interpolation, which affects the accuracy of hydro-meteorological studies. Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) is the main high-resolution precipitation product, which is available to supplement measured missing data. To evaluate the applicability of this product in the Dongting Lake basin at multiple spatial and temporal scales, this paper analyzes daily, monthly, seasonal, annual, and extreme precipitation events of the three latest IMERG precipitation products (IPPs) (IMERG-F, IMERG-E, and IMERG-L) using eight statistical evaluation metrics. We find that the spatial and temporal performance of IMERG precipitation products varies over different time scales and topographic conditions. However, all three metrics (CC, RMSE, and RB) of the IMERG-F precipitation products outperform the IMERG-E and IMERG-L precipitation products for the same period. In the comparison of IMERG and TRMM (Tropical Rainfall Measuring Mission) precipitation products on monthly and seasonal scales, IMERG-F performed the best. IPPs can capture precipitation more accurately on seasonal scales and perform better in winter, indicating good detection of trace precipitation. Both high and low altitudes are not favorable for the satellite detection of extreme precipitation in both general and extreme precipitation events. Overall, the accuracy of IMERG-F with correction delay is slightly better than that of IMERG-E and IMERG-L without correction under near-real-time conditions, which is applicable in the Dongting Lake basin. However, the correction process also exacerbates overestimation of the precipitation extent.
Predicting PM2.5 in the Northeast China Heavy Industrial Zone: A Semi-Supervised Learning with Spatiotemporal Features
Authors: Jiang Hongxun , Wang Xiaotong , Sun Caihong
Published: October 2022

Particulate matter PM2.5 pollution affects the Chinese population, particularly in cities such as Shenyang in northeastern China, which occupies a number of traditional heavy industries. This paper proposes a semi-supervised learning model used for predicting PM2.5 concentrations. The model incorporates rich data from the real world, including 11 air quality monitoring stations in Shenyang and nearby cities. There are three types of data: air monitoring, meteorological data, and spatiotemporal information (such as the spatiotemporal effects of PM2.5 emissions and diffusion across different geographical regions). The model consists of two classifiers: genetic programming (GP) to forecast PM2.5 concentrations and support vector classification (SVC) to predict trends. The experimental results show that the proposed model performs better than baseline models in accuracy, including 3% to 18% over a classic multivariate linear regression (MLR), 1% to 11% over a multi-layer perceptron neural network (MLP-ANN), and 21% to 68% over a support vector regression (SVR). Furthermore, the proposed GP approach provides an intuitive contribution analysis of factors for PM2.5 concentrations. The data of backtracking points adjacent to other monitoring stations are critical in forecasting shorter time intervals (1 h). Wind speeds are more important in longer intervals (6 and 24 h).
A Computational Approach to a Model for HIV and the Immune System Interaction
Authors: Attaullah  , Zeeshan  , Tufail Khan Muhammad , Alyobi Sultan , Yassen Mansour F. , Prathumwan Din
Published: October 2022

This study deals with the numerical solution of the human immunodeficiency virus (HIV) infection model, which is a significant problem for global public health. Acquired immunodeficiency syndrome (AIDS) is a communicable disease, and HIV is the causative agent for AIDS, which damages the ability of the body to fight against disease and easily usual innocuous infections attack the body. On entering the body, HIV infects a large amount of CD4+ T-cells and disturbs the supply rate of these cells from the thymus. Herein, we consider the model with variable source terms in which the production of these cells is a monotonically decreasing function of viral load. Based on the reproduction number, we describe the stability of free equilibrium. The continuous Galerkin–Petrov method, in particular the cGP(2)-method, is implemented to determine the numerical solutions of the model. The influence of different parameters on the population dynamics of healthy/infected CD4+ T-cells and free HIV particles are examined, and the results are presented graphically. On the other hand, the model is solved using the fourth-order Runge–Kutta method, and briefly, the RK4-method, and the results of the proposed schemes are compared with those obtained from other classical schemes such as the Bessel collocation method (BCM), Laplace Adomian decomposition method (LADM), perturbation iteration algorithm (PIA), modified variational iteration method (MVIM), differential transform method (DTM), and exponential Galerkin method (EGM), numerically. Furthermore, absolute errors relative to the RK4 method are computed to describe the accuracy of the proposed scheme. It is presented that the cGP(2)-method gains accurate results at larger time step sizes in comparison with the results of the aforementioned methods. The numerical and graphical comparison reveals that the proposed scheme yields more accurate results relative to other traditional schemes from the literature.
Hybrid Fuzzy Contraction Theorems with Their Role in Integral Inclusions
Authors: Ali Faryad , Shagari Mohammed Shehu , Azam Akbar
Published: October 2022

The focus of this paper is to establish a new concept of b-hybrid fuzzy contraction regarding the study of fuzzy fixed-point theorems in the setting of b-metric spaces. This idea harmonizes and refines several well-known results in the direction of point-valued, multivalued, and fuzzy-set-valued maps in the comparable literature. To attract new researchers to this field, some important results are shown to be corollaries. Moreover, a result is presented to establish sufficient conditions for the existence of solutions of integral inclusion of Fredholm type. Lastly, illustrations are presented to validate the suppositions of the given theorems.
The General Analytic Expression of a Harvested Logistic Model with Slowly Varying Coefficients
Authors: Alharbi Fahad M.
Published: October 2022

The harvested logistic model with a slow variation in coefficients has been considered. Two cases, which depend on the harvest rate, were identified. The first one is when the harvest is subcritical, where the population evolves to an equilibrium. The other is supercritical harvesting, where the population decreases to zero at finite times. The single analytic approximate expression, which is capable of describing both harvesting cases, is readily and explicitly obtained using the multi-time scaling method together with the perturbation approach. This solution fits for a wide range of coefficient values. In addition, such an expression is validated by utilizing numerical computations, which are obtained by using the fourth-order Runge–Kutta technique. Finally, the comparison shows a very good agreement between the two methods.
Variational Iteration Method for Solving Fractional Integro-Differential Equations with Conformable Differointegration
Authors: Damak Mondher , Mohammed Zaid Amer
Published: October 2022

Multidimensional integro-differential equations are obtained when the unknown function of several independent variable and/or its derivatives appear under an integral sign. When the differentiation or integration operators or both are of fractional order, the integral equation in this case is called a multidimensional fractional integro-differential equation. Such equations are difficult to solve analytically; therefore, as the main objective of this paper, an approximate method—which is the variational iteration method—will be used to solve this type of equation with conformable fractional-order derivatives and integrals. First, we drive the iterative sequence of approximate solutions using the proposed method, and then, under certain conditions over the kernel of the integro-differential equation, prove its convergence to the exact solution. Two illustrative examples, linear and nonlinear, are given, and their approximated solutions are simulated using computer programs in order to verify from the reliability and applicability of the proposed method.
Effect of Thermal Abuse Conditions on Thermal Runaway of NCA 18650 Cylindrical Lithium-Ion Battery
Authors: Jeon Minkyu , Lee Eunsong , Park Hyunwook , Yoon Hongsik , Keel Sangin
Published: October 2022

In energy storage systems and electric vehicles utilizing lithium-ion batteries, an internal short circuit or a thermal runaway (TR) may result in fire-related accidents. Particularly, under non-oxygenated conditions, a fire can spread as a result of TR. In this study, a TR experiment was performed on a nickel–cobalt–aluminum 18650 cylindrical lithium-ion battery via thermal conduction. The time required to attain TR (temperature range: 250–500 °C) was drastically reduced from approximately 1200 s to 1 s. The chemical reaction rate of thermal runaway was classified according to temperature into two global mechanisms and applied to the Arrhenius equation, thereby yielding a correlation between plate temperature (TP) and time difference of TR times ∆t (i.e., t1−t0 or t2−t0). As a result, activation energy for the overall reaction of the TR was estimated to be 39.9 kJ/mol. Furthermore, the safety guarantee time mandated by the safety regulation for vehicle batteries is 5 min; an analysis of the experiment results reveals that the following conditions can be satisfied: TP = 308.4 °C, Δtt1−t0 = 5 min; TP = 326.2 °C, Δtt2−t0 = 5 min. The experiment results offer a scientific basis for predicting the time of occurrence of TR and establishing safety standards.
Classification of Scientific Documents in the Kazakh Language Using Deep Neural Networks and a Fusion of Images and Text
Authors: Bogdanchikov Andrey , Ayazbayev Dauren , Varlamis Iraklis
Published: October 2022

The rapid development of natural language processing and deep learning techniques has boosted the performance of related algorithms in several linguistic and text mining tasks. Consequently, applications such as opinion mining, fake news detection or document classification that assign documents to predefined categories have significantly benefited from pre-trained language models, word or sentence embeddings, linguistic corpora, knowledge graphs and other resources that are in abundance for the more popular languages (e.g., English, Chinese, etc.). Less represented languages, such as the Kazakh language, balkan languages, etc., still lack the necessary linguistic resources and thus the performance of the respective methods is still low. In this work, we develop a model that classifies scientific papers written in the Kazakh language using both text and image information and demonstrate that this fusion of information can be beneficial for cases of languages that have limited resources for machine learning models’ training. With this fusion, we improve the classification accuracy by 4.4499% compared to the models that use only text or only image information. The successful use of the proposed method in scientific documents’ classification paves the way for more complex classification models and more application in other domains such as news classification, sentiment analysis, etc., in the Kazakh language.
Neuroprotective Effect of Abelmoschus manihot Flower Extracts against the H2O2-Induced Cytotoxicity, Oxidative Stress and Inflammation in PC12 Cells
Authors: Wang Shih-Wei , Chang Chi-Chang , Hsuan Chin-Feng , Chang Tzu-Hsien , Chen Ya-Ling , Wang Yun-Ya , Yu Teng-Hung , Wu Cheng-Ching , Houng Jer-Yiing
Published: October 2022

The progression of neurodegenerative diseases is associated with oxidative stress and inflammatory responses. Abelmoschus manihot L. flower (AMf) has been shown to possess excellent antioxidant and anti-inflammatory activities. This study investigated the protective effect of ethanolic extract (AME), water extract (AMW) and supercritical extract (AMS) of AMf on PC12 neuronal cells under hydrogen peroxide (H2O2) stimulation. This study also explored the molecular mechanism underlying the protective effect of AME, which was the best among the three extracts. The experimental results showed that even at a concentration of 500 μg/mL, neither AME nor AMW showed toxic effects on PC12 cells, while AMS caused about 10% cell death. AME has the most protective effect on apoptosis of PC12 cells stimulated with 0.5 mM H2O2. This is evident by the finding when PC12 cells were treated with 500 μg/mL AME; the viability was restored from 58.7% to 80.6% in the Treatment mode (p < 0.001) and from 59.1% to 98.1% in the Prevention mode (p < 0.001). Under the stimulation of H2O2, AME significantly up-regulated the expression of antioxidant enzymes, such as catalase, glutathione peroxidase and superoxide dismutase; promoted the production of the intracellular antioxidant; reduced glutathione; and reduced ROS generation in PC12 cells. When the acute inflammation was induced under the H2O2 stimulation, AME significantly down-regulated the pro-inflammatory cytokines and mediators (e.g., TNF-α, IL-1β, IL-6, COX-2 and iNOS). AME pretreatment could also greatly promote the production of nucleotide excision repair (NER)-related proteins, which were down-regulated by H2O2. This finding indicates that AME could repair DNA damage caused by oxidative stress. Results from this study demonstrate that AME has the potential to delay the onset and progression of oxidative stress-induced neurodegenerative diseases.
Relationships between the Clinical Test Results and Neurophysiological Findings in Patients with Thoracic Outlet Syndrome
Authors: Kaczmarek Agata Maria , Huber Juliusz , Leszczyńska Katarzyna , Wietrzak Paulina , Kaczmarek Katarzyna
Published: October 2022

A thoracic outlet syndrome (TOS) is the type of brachial plexus disorder most difficult to objectively assess using a clinical examination and differential diagnosis. Its symptoms can be frequently misdiagnosed, especially among others with cervical disc-root conflicts, plexopathies, and peripheral neuropathies. In this study, we aim to identify the correlations between positive Doppler ultrasonography results indicating pathological changes in the subclavian flow velocity, clinical tests, and chosen clinical neurophysiology recordings as proposed alternative or supplementary diagnostic tools for evaluating TOS patients. Sixty TOS patients with positive Doppler ultrasonography and Roos test results and sixty healthy people as a control group were bilaterally examined, and the results were compared. Pain intensity was assessed using a visual analogue scale (VAS). Sensory perceptions within C4–C8 dermatomes were assessed with Von Frey filament (FvF) tests. The activity of motor units in the proximal and distal muscles of the upper extremities was evaluated using surface electromyography (sEMG) during maximal contractions before and after a provocative raised hands test (RHT). An electroneurography (ENG) was used to evaluate the transmission of nerve impulses peripherally. Motor evoked potential (MEP) recordings, induced by the over-vertebral magnetic stimulation of the C5–C7 neuromeres, were used to examine motor transmissions from the cervical motor centres to the upper extremities muscles. The results revealed a relationship between positive Doppler test scores and pathological changes in the subclavian flow velocity through the results of the following diagnostic tools: a VAS score of 1.9 was detected on average, superficial sensory perception abnormalities were found in the innervation areas of the ulnar nerves detected by FvF tests, a decrease in the amplitudes of sEMG recordings was seen in distal rather than proximal muscles (especially following the RHT), a decrease in the motor and sensory peripheral transmissions of nerve impulses in the median, ulnar and cutaneous anterobrachial median nerves was seen, as well as MEP amplitudes recorded from the abductor pollicis brevis muscle. The provocative RHT combined with sEMG and MEP recordings can be considered accurate and objective clinical neurophysiology tools that could supplement the commonly used clinical tests. Such an approach may result in a more precise neurogenic TOS diagnostic algorithm.
Engineered Tissue for Cardiac Regeneration: Current Status and Future Perspectives
Authors: Li Junjun , Liu Li , Zhang Jingbo , Qu Xiang , Kawamura Takuji , Miyagawa Shigeru , Sawa Yoshiki
Published: October 2022

Heart failure (HF) is the leading cause of death worldwide. The most effective HF treatment is heart transplantation, the use of which is restricted by the limited supply of donor hearts. The human pluripotent stem cell (hPSC), including human embryonic stem cell (hESC) and the induced pluripotent stem cells (hiPSC), could be produced in an infinite manner and differentiated into cardiomyocytes (CMs) with high efficiency. The hPSC-CMs have, thus, offered a promising alternative for heart transplant. In this review, we introduce the tissue-engineering technologies for hPSC-CM, including the materials for cell culture and tissue formation, and the delivery means into the heart. The most recent progress in clinical application of hPSC-CMs is also introduced. In addition, the bottleneck limitations and future perspectives for clinical translation are further discussed.
Efficient and Economic Heparin Recovery from Porcine Intestinal Mucosa Using Quaternary Ammonium-Functionalized Silica Gel
Authors: Karimi Abdolmaleki Mahmood , Das Anushree , Khambhati Devang P. , Shafiee Ali , Dimas Kayli , Velazquez Carlo Alberto , Davachi Seyed Mohammad , Choubtarash Abardeh Sima
Published: October 2022

Heparin, usually isolated from porcine intestinal mucosa, is an active pharmaceutical ingredient of great material value. Traditionally, diverse types of commercial resins were employed as an adsorbent for heparin retrieval from biological samples. However, more recent years have encouraged the advent of new cost-effective adsorbents to achieve enhanced heparin retrieval. Inexpensive cationic ammonium-functionalized silica gels, monodispersed with larger surface area, porosity, and higher thermal stability, were chosen to evaluate the heparin recovery yield from porcine intestinal mucosa. We demonstrated that higher positively charged and less bulky quaternary modified silica gel (e.g., QDASi) could adsorb ~28% (14.7 mg g−1) heparin from the real samples. In addition, we also determined suitable surface conditions for the heparin molecule adsorption by mechanistic studies and optimized different variables, such as pH, temperature, etc., to improve the heparin adsorption. This is going to be the first reported study on the usage of quaternary amine-functionalized silica gel for HEP uptake.
Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality
Authors: Neculai-Valeanu Andra-Sabina , Ariton Adina-Mirela
Published: October 2022

To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow’s productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.
Reinvestigation of the Late Devonian Lycopsid Sublepidodendron grabaui from Anhui Province, South China
Authors: Xu Peng , Liu Le , Wang Deming
Published: October 2022

South China displays Devonian strata with well-exposed outcrops and is regarded as a diversity hotspot of Late Devonian lycopsids. The heterosporous lycopsid Sublepidodendron grabaui has been studied for over ten years, with its general morphology, aerial stem anatomy, microsporangiate strobili, and growth architecture reported. Based on new specimens from Guangde City, Anhui Province, this study provides further knowledge about the megasporangiate strobili and megaspores of S. grabaui. Its slender megasporangiate strobili occur singly or in pairs and occasionally bifurcate in the middle-upper portion. Each megasporophyll consists of a flattened pedicel and an adaxially curved lamina. The lamina forms a downturned heel at the base. Each sessile megasporangium contains at least eight Lagenicula-type megaspores with a small gula. The other observed characteristics of S. grabaui in this study conform to those previously known and are compared to relative coeval taxa.
Neurophysiological Response of Adults with Cerebral Palsy during Inclusive Dance with Wheelchair
Authors: Mendoza-Sánchez Sandra , Murillo-Garcia Alvaro , Leon-Llamas Juan Luis , Sánchez-Gómez Jesús , Gusi Narcis , Villafaina Santos
Published: October 2022

A total of 16 adults with cerebral palsy (age = 37.50 (7.78)) participated in this cross-sectional study. The electroencephalographic (EEG) data were recorded under three conditions: (1) baseline; (2) while listening to music; (3) while performing inclusive dance choreography with wheelchair. EEG data was banded into theta (4–7 Hz), alpha (8–12 Hz), and beta (13–30 Hz). Significantly higher values of theta, alpha, and beta bands were found in dance conditions than in the baseline. Significant differences between baseline and listening to music conditions were not found in any of the power spectrum bands. Differences between listening to music conditions and inclusive dance with wheelchair were observed in theta and beta power spectrum band studies in the F4 electrode. Inclusive dance with wheelchair increases theta, alpha, and beta power spectra when compared to baseline. In addition, the beta power spectrum is greater only during inclusive dance conditions, which could be modulated by emotions. However, future studies should corroborate this hypothesis.
SLC16A7 Promotes Triglyceride Deposition by De Novo Lipogenesis in Chicken Muscle Tissue
Authors: Wang Yongli , Liu Lu , Liu Xiaojing , Tan Xiaodong , Zhu Yuting , Luo Na , Zhao Guiping , Cui Huanxian , Wen Jie
Published: October 2022

Triglyceride (TG) content in chicken muscle tissue signifies intramuscular fat (IMF) content, which is important for improving meat quality. However, the genetic basis of TG deposition in chicken is still unclear. Using 520 chickens from an artificially selected line with significantly increased IMF content and a control line, a genome-wide association study (GWAS) with TG content reports a region of 802 Kb located in chromosome 1. The XP-EHH and gene expression analysis together reveal that the solute carrier family 16 member A7 (SLC16A7) gene is the key candidate gene associated with TG content in chicken muscle tissue. Furthermore, the weighted gene co-expression network analysis (WGCNA) confirmed the regulatory effects of SLC16A7 on promoting TG deposition by de novo lipogenesis (DNL). Functional verification of SLC16A7 in vitro also supports this view, and reveals that this effect mainly occurs in myocytes. Our data highlight a potential IMF deposition pathway by DNL, induced by SLC16A7 in chicken myocytes. These findings will improve the understanding of IMF regulation in chicken and guide the formulation of breeding strategies for high-quality chicken.
Identification of NRAS Downstream Genes with CRISPR Activation Screening
Authors: Tatsumi Akiya , Hirakochi Haruka , Inoue Satomi , Tanaka Yosuke , Furuno Hidehiro , Ikeda Masumi , Ishibashi Sachiko , Taguchi Towako , Yamamoto Kouhei , Onishi Iichiroh , Sachs Zohar , Largaespada David A. , Kitagawa Masanobu , Kurata Morito
Published: October 2022

Mutations in NRAS constitutively activate cell proliferation signaling in malignant neoplasms, such as leukemia and melanoma, and the clarification of comprehensive downstream genes of NRAS might lead to the control of cell-proliferative signals of NRAS-driven cancers. We previously established that NRAS expression and proliferative activity can be controlled with doxycycline and named as THP-1 B11. Using a CRISPR activation library on THP-1 B11 cells with the NRAS-off state, survival clones were harvested, and 21 candidate genes were identified. By inducting each candidate guide RNA with the CRISPR activation system, DOHH, HIST1H2AC, KRT32, and TAF6 showed higher cell-proliferative activity. The expression of DOHH, HIST1H2AC, and TAF6 was definitely upregulated with NRAS expression. Furthermore, MEK inhibitors resulted in the decreased expression of DOHH, HIST1H2AC, and TAF6 proteins in parental THP-1 cells. The knockdown of DOHH, HIST1H2AC, and TAF6 was found to reduce proliferation in THP-1 cells, indicating that they are involved in the downstream proliferation of NRAS. These molecules are expected to be new therapeutic targets for NRAS-mutant leukemia cells.
Correction: Pluta et al. Platelet–Leucocyte Aggregates as Novel Biomarkers in Cardiovascular Diseases. Biology 2022, 11, 224
Authors: Pluta Kinga , Porębska Kinga , Urbanowicz Tomasz , Gąsecka Aleksandra , Olasińska-Wiśniewska Anna , Targoński Radosław , Krasińska Aleksandra , Filipiak Krzysztof J. , Jemielity Marek , Krasiński Zbigniew
Published: October 2022

The authors would like to make the following correction to the published paper [...]
Correction: Gao et al. TGF-β1 Facilitates TAp63α Protein Lysosomal Degradation to Promote Pancreatic Cancer Cell Migration. Biology 2021, 10, 597
Authors: Gao Guohui , Chen Jie , Wang Dongbo , Li Qiao , Yang Xiaojiao , Wang Jindan , Pan Zhiyong , Xiao Zhi-Xiong Jim , Yi Yong
Published: October 2022

In the original publication [...]
Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer
Authors: Li Yaning , Liang Xinyue , Che Gang , Chen Yutong , Luo Lisi , Liu Kecheng , Xie Rongzhi , Zeng Linjuan
Published: October 2022

Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles.