bluuebunny/crossref_metadata_2025 huggingface dataset:
Distributed Predefined-Time Optimization for Second-Order Systems under Detail-Balanced Graphs
Authors: De Villeros Pablo , Sánchez-Torres Juan Diego , Muñoz-Vázquez Aldo Jonathan , Defoort Michael , Fernández-Anaya Guillermo , Loukianov Alexander
Published: February 2023

This paper studies the problem of distributed predefined-time optimization for leaderless consensus of second-order multi-agent systems under a class of weighted digraphs. The proposed framework has two main steps. In the first step, the agents communicate to perform a consensus-based distributed predefined-time optimization and to generate a constant optimal output reference for each agent. In the second step, each agent tracks its corresponding optimal output reference, using a sliding-mode controller to reach the global optimum in a predefined time, even under matched disturbances. The proposed algorithm relies explicitly on user-defined constant parameters. Numerical simulations are performed to validate the efficacy of the algorithm.
Design of Spoke-Type Permanent Magnet Synchronous Generator for Low Capacity Wind Turbine Considering Magnetization and Cogging Torques
Authors: Kim Dong-Ho , Pyo Hyun-Jo , Kim Won-Ho , Lee Ju , Lee Ki-Doek
Published: February 2023

Permanent magnet synchronous generators (PMSGs) with high output density per unit volume are becoming widespread in wind-power generation systems. Among them, spoke-type PMSGs are more challenging to magnetize than other PMSGs, owing to their structural characteristics. Magnetization performance is critical because it is directly related to the demagnetization and mass productivity of permanent magnets, and load performance is reduced when non-magnetization occurs due to the low magnetization performance. Additionally, the starting performance is crucial in wind turbines and is influenced by the cogging torque of the PMSG. This is because starting a wind turbine with a large cogging torque is more challenging. Therefore, this study proposes a spoke-type PMSG rotor shape design for low capacity wind turbines that considers magnetization and cogging torques. We analyzed the principle of magnetization and the factors influencing magnetization performance, and designed a rotor shape with improved magnetization performance. Additionally, we applied an asymmetric rotor barrier structure to reduce the cogging torque and analyze the performance of the final model using finite element analysis. We analyzed the temperature saturation during the operation of the final model using a thermal network method and validated the irreversible demagnetization accordingly.
Fingerprinting-Based Indoor Positioning Using Data Fusion of Different Radiocommunication-Based Technologies
Authors: Csik Dominik , Odry Ákos , Sarcevic Peter
Published: February 2023

Wireless-radio-communication-based devices are used in more and more places with the spread of Industry 4.0. Localization plays a crucial part in many of these applications. In this paper, a novel radiocommunication-based indoor positioning method is proposed, which applies the fusion of fingerprints extracted with various technologies to improve the overall efficiency. The aim of the research is to apply the differences, which occur due to that different technologies behave differently in an indoor space. The proposed method was validated using training and test data collected in a laboratory. Four different technologies, namely WiFi received signal strength indication (RSSI), ultra-wideband (UWB) RSSI, UWB time of flight (TOF) and RSSI in 433 MHz frequency band and all of their possible combinations, were tested to examine the performance of the proposed method. Three widely used fingerprinting algorithms, the weighted k-nearest neighbor, the random forest, and the artificial neural network were implemented to evaluate their efficiency with the proposed method. The achieved results show that the accuracy of the localization can be improved by combining different technologies. The combination of the two low-cost technologies, i.e., the WiFi and the 433 MHz technology, resulted in an 11% improvement compared to the more accurate technology, i.e., the 433 MHz technology. Combining the UWB module with other technologies results in a less significant improvement since this sensor provides lower error rates, when used alone.
Effects of Tooth Modification in the Involute Helical Gear Form-Grinding Process on Loaded Transmission Character with Consideration of Tooth Axial Inclination Error
Authors: Yang Yongming , Wu Yunlong , Li Yan , Liu Xinrong
Published: February 2023

Due to the existence of machining and installation errors, axis parallelism error of gear pairs occurs, which causes eccentric load and mesh in-out impact, thus weakening loaded transmission character. To solve this problem, the axis parallelism error of gear pairs was equated with tooth axial inclination error based on the gear-meshing principle. On this basis, we established the tooth modification model with tooth axial inclination error as the variable according to involute helical gear form-grinding process. Then, the degradation of loaded transmission character caused by axis parallelism error of gear pairs was quantitatively analyzed. The gear grinding, gear measuring, and gearbox vibration measuring were, respectively, performed on high-precision CNC horizontal gear form-grinding machine tool L300G, Gleason 350 GMS, and JWY-II multifunctional gearbox loading test bench. The results show that the proposed method can effectively reduce eccentric load and mesh in-out impact and significantly improve loaded transmission character. Therefore, it can provide a theoretical and experimental basis for the research of high-performance gear-grinding technology of gear-grinder machines.
A Hybrid Fuzzy Multi-Criteria Decision-Making Model for Evaluating the Influence of Industry 4.0 Technologies on Manufacturing Strategies
Authors: Abdullah Fawaz M. , Al-Ahmari Abdulrahman M. , Anwar Saqib
Published: February 2023

Manufacturing is transitioning from traditional and mass manufacturing to mass personalization, fast, and intelligent production. Through full automation in various fields and data sharing, Industry 4.0 (I4.0) contributes to the digitalization of manufacturing by enhancing industrial flexibility and product customization. I4.0 is being utilized as a strategy for advanced manufacturing to counter global competitiveness. A company’s manufacturing strategy outputs (MSOs) are critical to its ability to move forward and remain competitive. Despite their importance, I4.0 technologies have received less attention in the literature, and it is unclear how they influence MSOs. Thus, this study aims to build a powerful hybrid MCDM method for ranking the influence of I4.0 technologies on MSOs by adopting a combination of AHP and fuzzy TOPSIS. The application of fuzzy set theory has addressed the ambiguity in comparing various I4.0 technologies. The AHP was used to calculate the weights of criteria and sub-criteria, and the fuzzy-TOPSIS method was utilized to rank the I4.0 technologies. The results revealed that the cost criterion is the most critical factor when implementing I4.0 technologies. In contrast, additive manufacturing (AM) is the most suitable I4.0 technology for countering global competition.
Typical Fault Modeling and Vibration Characteristics of the Turbocharger Rotor System
Authors: Wang Jiahao , Wen Huabing , Qian Haiyu , Guo Junhua , Zhu Junchao , Dong Jiwei , Shen Hua
Published: February 2023

To study the typical failure mechanism (rotor unbalance, rotor friction, and rotor crack) and vibration characteristics of the turbocharger rotor system, a rotor system dynamics simulation model was established by an improved four-node aggregate parameter method. The geometric and physical characteristics of the rotor system under three failure states and its dynamics under operation were analyzed. Thus, a typical failure dynamics simulation model of the rotor system was established. On this basis, the output failure simulation signal was extracted using the Hu invariant moment feature extraction method to analyze the system vibration characteristics under each typical failure state of the rotor system. The results show that the model in this paper can effectively reduce the computational volume and computational time, and the errors of numerical simulation were less than 3%. When an unbalance fault occurred in the rotor system, the shaft trajectory was “0” shaped and the response spectrum was dominated by 1X. When the rotor system was frictional, the shaft trajectory was a slightly concave “8” shape, and the response spectrum was dominated by 0.5X. When the rotor system was cracked, the axial trajectory was a “vortex”, and the response spectrum was dominated by 0.5X. Thus, the study of typical failure mechanism and vibration characteristics of a turbocharger rotor system by simulation calculation is effective and has good research prospects, providing an important technical reference for dynamic analysis and fault diagnosis of the rotor system.
A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data
Authors: Noroznia Hassan , Gandomkar Majid , Nikoukar Javad , Aranizadeh Ali , Mirmozaffari Mirpouya
Published: February 2023

Today, the chemical corrosion of metals is one of the main problems of large productions, especially in the oil and gas industries. Due to massive downtime connected to corrosion failures, pipeline corrosion is a central issue in many oil and gas industries. Therefore, the determination of the corrosion progress of oil and gas pipelines is crucial for monitoring the reliability and alleviation of failures that can positively impact health, safety, and the environment. Gas transmission and distribution pipes and other structures buried (or immersed) in an electrolyte, by the existing conditions and due to the metallurgical structure, are corroded. After some time, this disrupts an active system and process by causing damage. The worst corrosion for metals implanted in the soil is in areas where electrical currents are lost. Therefore, cathodic protection (CP) is the most effective method to prevent the corrosion of structures buried in the soil. Our aim in this paper is first to investigate the effect of stray currents on failure rate using the condition index, and then to estimate the remaining useful life of CP gas pipelines using an artificial neural network (ANN). Predicting future values using previous data based on the time series feature is also possible. Therefore, this paper first uses the general equipment condition monitoring method to detect failures. The time series model of data is then measured and operated by neural networks. Finally, the amount of failure over time is determined.
A Review of Fluid-Induced Excitations in Centrifugal Pumps
Authors: Wu Chengshuo , Yang Jun , Yang Shuai , Wu Peng , Huang Bin , Wu Dazhuan
Published: February 2023

This paper describes the related research work in the field of fluid-induced vibration of centrifugal pumps conducted by many researchers. In recent years, all walks of life have put forward higher demands for the vibration performance of pumps which drives the investigation on the root cause of pump vibration and the development of guidelines for the design of low-vibration pumps. Fluid-induced excitation is the most important and significant source of pump vibration. Understanding its generation mechanism and dominant characteristics is important for developing low-vibration pump design methodology. This paper starts with the analysis of unsteady flow in the centrifugal pump and summarizes unsteady flow characteristics such as jet–wake structure, secondary flow, and rotational stall in the operating pump. Based on the understanding of the unsteady flow structure in the pump, the fluid-induced excitation mechanism and its characteristics based on the investigation of unsteady pressure pulsation and excitation forces in the pump are summarized. For the pump operating at nominal flow rate, the excitation at blade passing frequency (BPF) dominates and related suppression methods are classified and summarized to provide reference for the design of a low-vibration pump.
Solving One-Dimensional Cutting Stock Problems with the Deep Reinforcement Learning
Authors: Fang Jie , Rao Yunqing , Luo Qiang , Xu Jiatai
Published: February 2023

It is well known that the one-dimensional cutting stock problem (1DCSP) is a combinatorial optimization problem with nondeterministic polynomial (NP-hard) characteristics. Heuristic and genetic algorithms are the two main algorithms used to solve the cutting stock problem (CSP), which has problems of small scale and low-efficiency solutions. To better improve the stability and versatility of the solution, a mathematical model is established, with the optimization objective of the minimum raw material consumption and the maximum remaining material length. Meanwhile, a novel algorithm based on deep reinforcement learning (DRL) is proposed in this paper. The algorithm consists of two modules, each designed for different functions. Firstly, the pointer network with encoder and decoder structure is used as the policy network to utilize the underlying mode shared by the 1DCSP. Secondly, the model-free reinforcement learning algorithm is used to train network parameters and optimize the cutting sequence. The experimental data show that the one-dimensional cutting stock algorithm model based on deep reinforcement learning (DRL-CSP) can obtain the approximate satisfactory solution on 82 instances of 3 data sets in a very short time, and shows good generalization performance and practical application potential.
Photovoltaic Power Prediction Based on VMD-BRNN-TSP
Authors: Chen Guici , Zhang Tingting , Qu Wenyu , Wang Wenbo
Published: February 2023

Overfitting often occurs in neural network training, and neural networks with higher generalization ability are less prone to this phenomenon. Aiming at the problem that the generalization ability of photovoltaic (PV) power prediction model is insufficient, a PV power time-sharing prediction (TSP) model combining variational mode decomposition (VMD) and Bayesian regularization neural network (BRNN) is proposed. Firstly, the meteorological sequences related to the output power are selected by mutual information (MI) analysis. Secondly, VMD processing is performed on the filtered sequences, which is aimed at reducing the non-stationarity of the data; then, normalized cross-correlation (NCC) and signal-to-noise ratio (SNR) between the components obtained by signal decomposition and the original data are calculated, after which the key influencing factors are screened out to eliminate the correlation and redundancy of the data. Finally, the filtered meteorological sequences are divided into two datasets based on whether the irradiance of the day is zero or not. Meanwhile, the predictions are performed using BRNN for each of the two datasets. Then, the results are reordered in chronological order, and the prediction of PV power is realized conclusively. It was experimentally verified that the mean absolute value error (MAE) of the method proposed in this paper is 0.1281, which is reduced by 40.28% compared with the back propagation neural network (BPNN) model on the same dataset, the mean squared error (MSE) is 0.0962, and the coefficient of determination (R2) is 0.9907. Other error indicators also confirm that VMD is of much significance and TSP is contributive.
Optimal Control Problem for Minimization of Net Energy Consumption at Metro
Authors: Udriste Constantin , Tevy Ionel , Antonescu Paun
Published: February 2023

The optimal control currently decides the minimum energy consumption within the problems attached to subways. Among other things, we formulate and solve an optimal bi-control problem, the two controls being the acceleration and the feed-back of a Riemannian connection. The control space is a square, and the optimal controls are of the bang–bang type. The third component of the optimal solution is the maximum value function, as a solution of the Hamilton–Jacobi–Bellman PDE. The examples of energy optimal trajectories refer to the lines of the Bucharest subway.
Fractional-Order SEIRD Model for Global COVID-19 Outbreak
Authors: Yousif Rana , Jeribi Aref , Al-Azzawi Saad
Published: February 2023

With the identification of new mutations in the coronavirus with greater transmissibility and pathogenicity, the number of infected people with COVID-19 worldwide has increased as from 22 June 2021, and a new wave has been created. Since the spread of the coronavirus, many studies have been conducted on different groups. The current research was adopted on the implementations of fractional-order (SEIRD: Susceptible, Exposed, Infected, Recovered, Died) people model with a Caputo derivative for investigating the spread of COVID-19. The characteristics of the system, such as the boundedness, existence, uniqueness and non-negativity of the solutions, the equilibrium points of system, and the basic reproduction number, were analyzed. In the numerical part, a simulation for the spread of the virus is presented, which shows that this wave of spread will continue for the next few months and an increasing number of people becoming infected. Furthermore, the numerical results obtained from several types of fractional-order derivatives are compared with real data, which subsequently shows that the Caputo fractional-order derivative follows real data better than others. In addition, the obtained reproduction number has a value greater than one, indicating a continuation of the disease outbreak and the necessity of taking more control decisions.
Economic Order Quantity for Growing Items with Mortality Function under Sustainable Green Breeding Policy
Authors: Nobil Amir Hossein , Nobil Erfan , Cárdenas-Barrón Leopoldo Eduardo , Garza-Núñez Dagoberto , Treviño-Garza Gerardo , Céspedes-Mota Armando , Loera-Hernández Imelda de Jesús , Smith Neale R.
Published: February 2023

Determining the optimal slaughter age of fast-growing animals regarding the mortality rates and breeding costs plays an important and major role for companies that benefit from their meat. Additionally, the effects of carbon dioxide (CO2) emissions during the growth cycle of animals are a significant concern for governments. This study proposes an economic order quantity (EOQ) for growing items with a mortality function under a sustainable green breeding policy. It assumes that CO2 production is a practical polynomial function that depends on the age of the animals as well as the mortality function. The aim of the model is to determine the optimal slaughter age and the optimal number of newborn chicks, purchased from the supplier, to minimize the total costs. We propose an analytical approach, with five simple steps, to find the optimal solutions. Finally, we provide a numerical example and some model management insights to help practitioners in this area.
Analysis of Multi-Server Queueing System with Flexible Priorities
Authors: Samouylov Konstantin , Dudina Olga , Dudin Alexander
Published: February 2023

In this paper, a multi-server queueing system providing service to two correlated flows of requests was considered. Non-preemptive priority was granted to one flow via the preliminary delay of requests in the intermediate buffers with different rates of extracting from the buffers. Customers’ impatience during waiting in the intermediate and main buffers was taken into account. The possibility of the use of the results of the mathematical analysis for managerial goals is numerically illustrated.
A Blockwise Empirical Likelihood Test for Gaussianity in Stationary Autoregressive Processes
Authors: Marange Chioneso S. , Qin Yongsong , Chiruka Raymond T. , Batidzirai Jesca M.
Published: February 2023

A new and simple blockwise empirical likelihood moment-based procedure to test if a stationary autoregressive process is Gaussian has been proposed. The proposed test utilizes the skewness and kurtosis moment constraints to develop the test statistic. The test nonparametrically accommodates the dependence in the time series data whilst exhibiting some useful properties of empirical likelihood, such as the Wilks theorem with the test statistic having a chi-square limiting distribution. A Monte Carlo simulation study shows that our proposed test has good control of type I error. The finite sample performance of the proposed test is evaluated and compared to some selected competitor tests for different sample sizes and a variety of alternative applied distributions by means of a Monte Carlo study. The results reveal that our proposed test is on average superior under the log-normal and chi-square alternatives for small to large sample sizes. Some real data studies further revealed the applicability and robustness of our proposed test in practice.
A Study of Privacy-Preserving Neural Network Prediction Based on Replicated Secret Sharing
Authors: Zhang Yanru , Li Peng
Published: February 2023

Neural networks have a wide range of promise for image prediction, but in the current setting of neural networks as a service, the data privacy of the parties involved in prediction raises concerns. In this paper, we design and implement a privacy-preserving neural network prediction model in the three-party secure computation framework over secret sharing of private data. Secret sharing allows the original data to be split, with each share held by a different party. The parties cannot know the shares owned by the remaining collaborators, and thus the original data can be kept secure. The three parties refer to the client, the service provider and the third server that assist in the computation, which is different from the previous work. Thus, under the definition of semi-honest and malicious security, we design new computation protocols for the building blocks of the neural network based on replicated secret sharing. Experimenting with MNIST dataset on different neural network architectures, our scheme improves 1.3×/1.5× and 7.4×/47.6× in terms of computation time as well as communication cost compared to the Falcon framework under the semi-honest/malicious security, respectively.
Non-Identical Inverter Rings as an Entropy Source: NIST-90B-Verified TRNG Architecture on FPGAs for IoT Device Integrity
Authors: Mahalingam Hemalatha , Rethinam Sivaraman , Janakiraman Siva , Rengarajan Amirtharajan
Published: February 2023

True random key generator (TRNG) architectures play a notable role in strengthening information security infrastructure. The development of new entropy sources based on reconfigurable hardware is always in demand, especially for the integrity of devices in IoT applications. TRNGs can be adopted for generating unique device IDs that form the data network in the IoT. A ring oscillator (RO) is an efficient entropy source which can be implemented on FPGAs or realised as ASIC hardware. This work proposes a non-identical RO array as an entropy source. The TRNG architecture, based on an increasing odd number of inverters per ring, was extensively studied. The various statistical and hardware analyses provided encouraging results for this reliable entropy unit. The suggested device-independent non-identical RO structure was implemented on five different types of FPGA hardware belonging to the Xilinx and Intel families, consuming 13 registers and nearly 15 combinational functions. This TRNG achieved a throughput of 3.5 Mbps. While the emergence of the Gaussian response evaluated true randomness, the NIST 800-90B and NIST 800-22 tests yielded good results in terms of the justification of randomness evolving from the proposed TRNG architecture.
Hybrid Traffic Accident Classification Models
Authors: Zhang Yihang , Sung Yunsick
Published: February 2023

Traffic closed-circuit television (CCTV) devices can be used to detect and track objects on roads by designing and applying artificial intelligence and deep learning models. However, extracting useful information from the detected objects and determining the occurrence of traffic accidents are usually difficult. This paper proposes a CCTV frame-based hybrid traffic accident classification model that enables the identification of whether a frame includes accidents by generating object trajectories. The proposed model utilizes a Vision Transformer (ViT) and a Convolutional Neural Network (CNN) to extract latent representations from each frame and corresponding trajectories. The fusion of frame and trajectory features was performed to improve the traffic accident classification ability of the proposed hybrid method. In the experiments, the Car Accident Detection and Prediction (CADP) dataset was used to train the hybrid model, and the accuracy of the model was approximately 97%. The experimental results indicate that the proposed hybrid method demonstrates an improved classification performance compared to traditional models.
Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19
Authors: Abugabah Ahed , Shahid Farah
Published: February 2023

The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root mean squared error (RMSE), R2, and mean absolute percentage error (MAPE). The results generated with TDGRU are compared with actual numbers as well as predictions with conventional time-series techniques, such as autoregressive integrated moving average (ARIMA), machine learning model of linear regression (LR), and the time series-based deep learning method of long short-term memory (LSTM). The experiment results on different time horizons show that the TDGRU model outperforms the other forecasting methods that deliver correct predictions with lower prediction errors. Furthermore, since this TDGRU is based on a relatively simpler architecture than the LSTM, in comparison to LSTM-based models, it features a significantly reduced number of parameters, a shorter training period, a lower memory storage need, and a more straightforward hardware implementation.
Algebraic Methods for Achieving Super-Resolution by Digital Antenna Arrays
Authors: Lagovsky Boris A. , Rubinovich Evgeny Ya.
Published: February 2023

The actual modern problem of developing and improving measurement and observation systems (including robotic ones) is to increase the volume and quality of the information received. Increasing the angle resolution to values significantly exceeding the Rayleigh criterion, i.e. achieving super-resolution is one of important ways to solve the problem. Angular super-resolution which makes it possible to detail images of research objects and their individual fragments, improves the quality of solutions to detection, recognition and identification problems, increases the range of such systems. In many papers methods developed by authors to achieve a super-resolution based on approximate solutions of inverse problems in the form of Fredholm integral equation of the first kind of convolution type called algebraic are presented. The methods used, as well as their varieties, make it possible to reduce solutions of inverse problems posed to solving sets of linear algebraic equations (SLAE). This paper presents results of further improvement of algebraic methods based on intelligent analysis of received signals. It is shown that their use in systems based on digital antenna arrays makes it possible to increase the achieved degree of exceeding the Rayleigh criterion. In the course of numerical experiments with a mathematical model, the stability of the solutions obtained and their adequacy were confirmed. The numerical results obtained open the following possibilities: (1) obtaining images of studied objects with a resolution exceeding the Rayleigh criterion by 4 to 10 times, (2) determining the angular coordinates of individual small-sized objects as part of multi-element complex objects (group targets), (3) clarifying boundaries of extended objects and their individual elements, (4) localizing individual bright objects on a smoothly inhomogeneous reflective background. Applying presented new methods does not require a significant computing power, what allows you to work in a real time mode using relatively simple and inexpensive computing devices. The ways of further improvement of presented algebraic methods for solving applied inverse problems are described.
Fast Single-Parameter Energy Function Thresholding for Image Segmentation Based on Region Information
Authors: Lan Rong , Feng Danlin , Zhao Feng , Fan Jiulun , Yu Haiyan
Published: February 2023

To solve the problems of image threshold segmentation based on weak continuous constraint theory, the running time is long, and the two parameters need to be selected manually, and therefore a fast single-parameter energy function thresholding for image segmentation based on region information (FSEFTISRI) is proposed in this paper. The proposed FSEFTISRI algorithm uses simple linear iterative clustering (SLIC) technology to pre-block the image, extract the image super-pixels, and then map the image super-pixels to the interval type-2 fuzzy set (IT2FS), so as to construct the single-parameter energy function to search the optimal threshold, and adaptively select the penalty parameters in the energy function through the class uncertainty theory. On a non-destructive testing (NDT) database and Berkeley segmentation datasets and benchmarks (BSDS), the proposed FSEFTISRI is compared with five related algorithms. The average misclassification error (ME) of the proposed FSEFTISRI algorithm on NDT and BSDS are 0.0466 and 0.0039, respectively. The results show that the proposed FSEFTISRI has acquired more satisfactory results in visual effect and evaluation index, and the running time of the proposed FSEFTISRI algorithm is shorter, which shows the effectiveness of the proposed FSEFTISRI.
Crustin Defense against Vibrio parahaemolyticus Infection by Regulating Intestinal Microbial Balance in Litopenaeus vannamei
Authors: Lv Xinjia , Li Shihao , Yu Yang , Zhang Xiaojun , Li Fuhua
Published: February 2023

Crustins are a kind of antimicrobial peptide (AMP) that exist in crustaceans. Some crustins do not have direct antimicrobial activity but exhibit in vivo defense functions against Vibrio. However, the underlying molecular mechanism is not clear. Here, the regulatory mechanism was partially revealed along with the characterization of the immune function of a type I crustin, LvCrustin I-2, from Litopenaeus vannamei. LvCrustin I-2 was mainly detected in hemocytes, intestines and gills and was apparently up-regulated after Vibrio parahaemolyticus infection. Although the recombinant LvCrustin I-2 protein possessed neither antibacterial activity nor agglutinating activity, the knockdown of LvCrustin I-2 accelerated the in vivo proliferation of V. parahaemolyticus. Microbiome analysis showed that the balance of intestinal microbiota was impaired after LvCrustin I-2 knockdown. Further transcriptome analysis showed that the intestinal epithelial barrier and immune function were impaired in shrimp after LvCrustin I-2 knockdown. After removing the intestinal bacteria via antibiotic treatment, the phenomenon of impaired intestinal epithelial barrier and immune function disappeared in shrimp after LvCrustin I-2 knockdown. This indicated that the impairment of the shrimp intestine after LvCrustin I-2 knockdown was caused by the dysbiosis of the intestinal microbiota. The present data suggest that crustins could resist pathogen infection through regulating the intestinal microbiota balance, which provides new insights into the functional mechanisms of antimicrobial peptides during pathogen infection.
Hemoglobin-Based Oxygen Carriers: Where Are We Now in 2023?
Authors: Chen Lin , Yang Zeyong , Liu Henry
Published: February 2023

The pursuit for blood a substitute has spanned over a century, but a majority of the efforts have been disappointing. As of today, there is no widely accepted product used as an alternative to human blood in clinical settings with severe anemic condition(s). Blood substitutes are currently also termed oxygen therapeutics. There are two major categories of oxygen therapeutics, hemoglobin-based and perfluorocarbon-based products. In this article, we reviewed the most developed but failed products and products still in active clinical research in the category of hemoglobin-based oxygen carriers. Among all of the discussed hemoglobin-based oxygen therapeutics, HemAssist, PolyHeme, Hemolink, Hemospan, and Hemoximer were discontinued. Hemopure is in clinical use in South Africa and Russia. Oxyglobin, the sister product of Hemopure, has been approved for veterinary use in the European Union and the United States. HemO2life has recently been approved for organ preservation in organ transplantation in the European Union. OxyVita and Sanguinate are still undergoing active clinical studies. The field of oxygen therapeutics seems to be entering a phase of rapid growth in the coming 10–20 years.
Placental Growth Factor and Pregnancy-Associated Plasma Protein-A as Potential Early Predictors of Gestational Diabetes Mellitus
Authors: Yanachkova Vesselina , Staynova Radiana , Stankova Teodora , Kamenov Zdravko
Published: February 2023

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and one of the main causes of adverse pregnancy outcomes. An early diagnosis of GDM is of fundamental importance in clinical practice. However, the major professional organizations recommend universal screening for GDM, using a 75 g oral glucose tolerance test at 24–28 weeks of gestation. A selective screening at an early stage of pregnancy is recommended only if there are maternal risk factors for diabetes. As a result, the GDM diagnosis is often delayed and established after the appearance of complications. The manifestation of GDM is directly related to insulin resistance, which is closely associated with endothelial dysfunction. The placenta, the placental peptides and hormones play a pivotal role in the manifestation and progression of insulin resistance during pregnancy. Recently, the placental growth factor (PlGF) and plasma-associated protein-A (PAPP-A), have been shown to significantly affect both insulin sensitivity and endothelial function. The principal function of PAPP-A appears to be the cleavage of circulating insulin-like growth factor binding protein-4 while PlGF has been shown to play a central role in the development and maturation of the placental vascular system and circulation. On one hand, these factors are widely used as early predictors (11–13 weeks of gestation) of complications during pregnancy, such as preeclampsia and fetal aneuploidies, in most countries. On the other hand, there is increasing evidence for their predictive role in the development of carbohydrate disorders, but some studies are rather controversial. Therefore, this review aims to summarize the available literature about the potential of serum levels of PlGF and PAPP-A as early predictors in the diagnosis of GDM.
Cardiopulmonary Cement Embolism Following Cement-Augmented Pedicle Screw Fixation: A Narrative Review
Authors: Morimoto Tadatsugu , Kobayashi Takaomi , Hirata Hirohito , Tsukamoto Masatsugu , Yoshihara Tomohito , Toda Yu , Mawatari Masaaki
Published: February 2023

Fixation using cement-augmented pedicle screws (CAPS) is being increasingly performed. However, CAPS-associated cement leakage is a critical problem that can lead to cardiopulmonary cement embolism (CPCE). This narrative review aimed to explore the incidence of and risk factors and treatment strategies for CPCE and cement leakage-related complications after CAPS fixation. Data were extracted from each article, including characteristics of CPCE after CAPS fixation (incidence, location, diagnostic method and criteria, treatment, and outcome and prognosis). Overall, 28 case series and 14 case reports that met the inclusion criteria were included. Of the 1974 cases included in the review, CPCE was noted in 123, symptomatic CPCE in 35, and death in six, respectively. The frequencies of PCE and symptomatic PCE after CAPS fixation were 6% (range: 0–28.6%) and 1.3% (range: 0–26%), respectively. The range of frequencies of PCE and symptomatic PCE after CAPS fixation may have been wide because the definition of CPCE and data collection methods differed among the reports analyzed. Since PCE due to large cement emboli may be primarily related to the surgical technique, improved technique, such as minimizing the number of CAPSs by injecting low-volume high-viscosity cement at low velocity and pressure, and careful observation of cement leakage during CAPS insertion may reduce PCE associated with cement leakage. Spinal surgeons should pay more attention to the occurrence of CPCE during and after CAPS insertion, which can cause serious complications in some patients.
Extremely Low Activity of Serum Alanine Aminotransferase Is Associated with Long-Term Overall-Cause Mortality in the Elderly Patients Undergoing Percutaneous Coronary Intervention after Acute Coronary Syndrome
Authors: Kim Doo Young , Park Si-Woon , Han Hyung-Wook , Kim Myeong-Kon , Kim Ha-Jung
Published: February 2023

Background and Objectives: Recent studies revealed that the extremely low activity of serum alanine aminotransferase (ALT) is associated with frailty and contributes to increased mortality after acute physical stress. We aimed to investigate whether the extremely low activity of serum ALT (<10 U/L) at the time of diagnosis can be used to predict overall-cause mortality in elderly patients that underwent percutaneous coronary intervention (PCI) after acute coronary syndrome (ACS) diagnosis. Materials and Methods: A retrospective medical record review was performed on 1597 patients diagnosed with ACS who underwent PCI at a single university hospital from February 2014 to March 2020. The associations between the extremely low activity of serum ALT and mortality were assessed using a stepwise Cox regression (forward: conditional). Results: A total of 210 elderly patients were analyzed in this study. The number of deaths was 64 (30.5%), the mean survival time was 25.0 ± 18.9 months, and the mean age was 76.9 ± 7.6 years. The mean door-to-PCI time was 74.0 ± 20.9 min. The results of stepwise Cox regression analysis showed that the extremely low activity of serum ALT (adjusted hazard ratio: 5.157, 95% confidence interval: 3.001–8.862, p < 0.001) was the independent risk factor for long-term overall-cause mortality in the elderly who underwent PCI after ACS diagnosis. Conclusions: The extremely low activity of serum ALT at ACS diagnosis is a significant risk factor for increased long-term overall-cause mortality in the elderly who underwent PCI after ACS diagnosis. It is noteworthy that a simple laboratory test at the time of diagnosis was found to be a significant risk factor for mortality.
Fasting Protocols Do Not Improve Intestinal Architecture and Immune Parameters in C57BL/6 Male Mice Fed a High Fat Diet
Authors: Ageeli Raed Y. , Sharma Sunita , Puppa Melissa , Bloomer Richard J. , Buddington Randal K. , van der Merwe Marie
Published: February 2023

Background: The intestinal ecosystem, including epithelium, immune cells, and microbiota, are influenced by diet and timing of food consumption. The purpose of this study was to evaluate various dietary protocols after ad libitum high fat diet (HFD) consumption on intestinal morphology and mucosal immunity. Methods: C57BL/6 male mice were fed a 45% high fat diet (HFD) for 6 weeks and then randomized to the following protocols; (1) chow, (2) a purified high fiber diet known as the Daniel Fast (DF), HFD consumed (3) ad libitum or in a restricted manner; (4) caloric-restricted, (5) time-restricted (six hours of fasting in each 24 h), or (6) alternate-day fasting (24 h fasting every other day). Intestinal morphology and gut-associated immune parameters were investigated after 2 months on respective protocols. Results: Consuming a HFD resulted in shortening of the intestine and reduction in villi and crypt size. Fasting, while consuming the HFD, did not restore these parameters to the extent seen with the chow and DF diet. Goblet cell number and regulatory T cells had improved recovery with high fiber diets, not seen with the HFD irrespective of fasting. Conclusion: Nutritional content is a critical determinant of intestinal parameters associated with gut health.
Quercetin-Loaded Polycaprolactone-Polyvinylpyrrolidone Electrospun Membranes for Health Application: Design, Characterization, Modeling and Cytotoxicity Studies
Authors: Viscusi Gianluca , Paolella Gaetana , Lamberti Elena , Caputo Ivana , Gorrasi Giuliana
Published: February 2023

Fibrous membranes of polycaprolactone (PCL)-polyvinylpyrrolidone (PVP) encapsulating 15% wt of quercetin are fabricated by a uniaxial electrospinning technique. Morphological analysis of the electrospun systems proved the fabrication of micrometric fibers (1.58 µm for PCL/PVP and 2.34 µm for quercetin-loaded membrane). The liquid retention degree of the electrospun membranes is evaluated by testing four different liquid media. The contact angle estimation is performed by testing three liquids: phosphate buffer solution, basic solution (pH = 13) and acidic solution (pH = 3), showing high hydrophobicity degree (contact angles > 90°) in all cases. The release of quercetin from the nanofibers in PBS (phosphate buffer solution) and pH = 3 medium, modeled through different models, shows the possibility of a fine tuning of drug release (up to 7 days) for the produced materials. The release profiles attained a plateau regime after roughly 50 h up to 82% and 71% for PBS and pH = 3 media, respectively. Then, since quercetin is known to undergo photooxidation upon UV radiation, release tests after different UV treatment times are carried out and compared with the untreated membrane, demonstrating that the release of the active drug changes from 82% for no-irradiated sample up to 57% after 10 h of UV exposure. The biology activity of released quercetin is evaluated on two human cell lines. The reported results demonstrate the ability of the quercetin-loaded membranes to reduce cell viability of human cell lines in two different conditions: direct contact between cells and quercetin-loaded membranes and cells treatment with culture medium previously conditioned with quercetin-loaded membranes. Therefore, the reported preliminary data confirm the possibility of applying the electrospun quercetin-loaded PCL-PVP membranes for health applications.
Design and Validation of an Experimental Setup for Evaluation of Gas Permeation in Ceramic Membranes
Authors: Carvalho Sabrina G. M. , Muccillo Eliana N. S. , Muccillo Reginaldo
Published: February 2023

An experimental setup for the evaluation of permeation of gaseous species with the possibility of simultaneously collecting electrochemical impedance spectroscopy data in disk-shaped ceramic membranes was designed and assembled. It consists of an alumina sample holder with thermocouple tips and platinum electrodes located close to both sides of the sample. Water-cooled inlet and outlet gas connections allowed for the insertion of the sample chamber into a programmable split tubular furnace. Gas permeation through a ceramic membrane can be monitored with mass flow controllers, a mass spectrometer, and an electrochemical impedance analyzer. For testing and data validation, ceramic composite membranes were prepared with the infiltration of molten eutectic compositions of alkali salts (lithium, sodium, and potassium carbonates) into porous gadolinia-doped ceria. Values of the alkali salt melting points and the permeation rates of carbon dioxide, in agreement with reported data, were successfully collected.
The Formation of β-Strand Nine (β9) in the Folding and Insertion of BamA from an Unfolded Form into Lipid Bilayers
Authors: Herwig Sascha , Kleinschmidt Jörg H.
Published: February 2023

Transmembrane proteins span lipid bilayer membranes and serve essential functions in all living cells. Membrane-inserted domains are of either α-helical or β-barrel structure. Despite their biological importance, the biophysical mechanisms of the folding and insertion of proteins into membranes are not well understood. While the relative composition of the secondary structure has been examined by circular dichroism spectroscopy in folding studies for several outer membrane proteins, it is currently not known how individual β-strands fold. Here, the folding and insertion of the β-barrel assembly machinery protein A (BamA) from the outer membrane of Escherichia coli into lipid bilayers were investigated, and the formation of strand nine (β9) of BamA was examined. Eight single-cysteine mutants of BamA were overexpressed and isolated in unfolded form in 8 M urea. In each of these mutants, one of the residues of strand β9, from R572 to V579, was replaced by a cysteine and labeled with the fluorophore IAEDANS for site-directed fluorescence spectroscopy. Upon urea-dilution, the mutants folded into the native structure and were inserted into lipid bilayers of dilauroylphosphatidylcholine, similar to wild-type BamA. An aqueous and a membrane-adsorbed folding intermediate of BamA could be identified by strong shifts in the intensity maxima of the IAEDANS fluorescence of the labeled mutants of BamA towards shorter wavelengths, even in the absence of lipid bilayers. The shifts were greatest for membrane-adsorbed mutants and smaller for the inserted, folded mutants or the aqueous intermediates. The spectra of the mutants V573C-, L575C-, G577C-, and V579C-BamA, facing the lipid bilayer, displayed stronger shifts than the spectra recorded for the mutants R572C-, N574C-, T576C-, and K578C-BamA, facing the β-barrel lumen, in both the membrane-adsorbed form and the folded, inserted form. This alternating pattern was neither observed for the IAEDANS spectra of the unfolded forms nor for the water-collapsed forms, indicating that strand β9 forms in a membrane-adsorbed folding intermediate of BamA. The combination of cysteine scanning mutagenesis and site-directed fluorescence labeling is shown to be a valuable tool in examining the local secondary structure formation of transmembrane proteins.
Cholesterol Regulation of Membrane Proteins Revealed by Two-Color Super-Resolution Imaging
Authors: Yuan Zixuan , Hansen Scott B.
Published: February 2023

Cholesterol and phosphatidyl inositol 4,5-bisphosphate (PIP2) are hydrophobic molecules that regulate protein function in the plasma membrane of all cells. In this review, we discuss how changes in cholesterol concentration cause nanoscopic (<200 nm) movements of membrane proteins to regulate their function. Cholesterol is known to cluster many membrane proteins (often palmitoylated proteins) with long-chain saturated lipids. Although PIP2 is better known for gating ion channels, in this review, we will discuss a second independent function as a regulator of nanoscopic protein movement that opposes cholesterol clustering. The understanding of the movement of proteins between nanoscopic lipid domains emerged largely through the recent advent of super-resolution imaging and the establishment of two-color techniques to label lipids separate from proteins. We discuss the labeling techniques for imaging, their strengths and weakness, and how they are used to reveal novel mechanisms for an ion channel, transporter, and enzyme function. Among the mechanisms, we describe substrate and ligand presentation and their ability to activate enzymes, gate channels, and transporters rapidly and potently. Finally, we define cholesterol-regulated proteins (CRP) and discuss the role of PIP2 in opposing the regulation of cholesterol, as seen through super-resolution imaging.