bluuebunny/crossref_metadata_2025 huggingface dataset:
Micro Spectrometers Based on Materials Nanoarchitectonics
Authors: Qiu Yanyan , Zhou Xingting , Tang Xin , Hao Qun , Chen Menglu
Published: March 2023

Spectral analysis is an important tool that is widely used in scientific research and industry. Although the performance of benchtop spectrometers is very high, miniaturization and portability are more important indicators in some applications, such as on-site detection and real-time monitoring. Since the 1990s, micro spectrometers have emerged and developed. Meanwhile, with the development of nanotechnology, nanomaterials have been applied in the design of various micro spectrometers in recent years, further reducing the size of the spectrometers. In this paper, we review the research progress of micro spectrometers based on nanomaterials. We also discuss the main limitations and perspectives on micro spectrometers.
Experimental and Numerical Analysis of the Residual Stresses in Seamed Pipe in Dependence on Welding and Metal Forming
Authors: Solfronk Pavel , Sobotka Jiří , Bukovská Šárka , Bradáč Josef
Published: March 2023

Concerning the increasingly widespread utilization of the finite element method (FEM), the concept of the so-called virtual factory is also gaining ground, and not only in the engineering industry. This approach does not use numerical simulations of individual production technologies separately but treats the entire production process as a chain of interrelated technologies. Thus, the output data from one technology is taken as input data for the following technology. The resulting thermal and mechanical effects are then not only dealt with within one technology but always comprehensively within the production process. In the consideration of the loading and subsequent service lives of manufactured components, values of residual stresses are one of the very important characteristics. For these reasons, this paper deals with the effect of residual stresses’ magnitude and distribution during the formation and the final springback of the seamed pipe end section with and without respect to the influence of the preceding welding. The resulting residual stress values from numerical simulations are subsequently compared with the actual values of residual stresses experimentally measured using X-ray diffraction.
Numerical Simulation of Temperature Fields during Laser Welding–Brazing of Al/Ti Plates
Authors: Behúlová Mária , Babalová Eva
Published: March 2023

The formation of dissimilar weld joints, including Al/Ti joints, is an area of research supported by the need for weight reduction and corrosion resistance in automotive, aircraft, aeronautic, and other industries. Depending on the cooling rates and chemical composition, rapid solidification of Al/Ti alloys during laser welding can lead to the development of different metastable phases and the formation of brittle intermetallic compounds (IMCs). The effort to successfully join aluminum to titanium alloys is associated with demands to minimize the thickness of brittle IMC zones by selecting appropriate welding parameters or applying suitable filler materials. The paper is focused on the numerical simulation of the laser welding–brazing of 2.0 mm thick titanium Grade 2 and EN AW5083 aluminum alloy plates using 5087 aluminum filler wire. The developed simulation model was used to study the impact of laser welding–brazing parameters (laser power, welding speed, and laser beam offset) on the transient temperature fields and weld-pool characteristics. The results of numerical simulations were compared with temperatures measured during the laser welding–brazing of Al/Ti plates using a TruDisk 4002 disk laser, and macrostructural and microstructural analyses, and weld tensile strength measurements, were conducted. The ultimate tensile strength (UTS) of welded–brazed joints increases with an increase in the laser beam offset to the Al side and with an increase in welding speed. The highest UTS values at the level of 220 MPa and 245 MPa were measured for joints produced at a laser power of 1.8 kW along with a welding speed of 30 mm·s−1 and a laser beam offset of 300 μm and 460 μm, respectively. When increasing the laser power to 2 kW, the UTS decreased. The results exhibited that the tensile strength of Al/Ti welded–brazed joints was dependent, regardless of the welding parameters, on the amount of melted Ti Grade 2, which, during rapid solidification, determines the thickness and morphology of the IMC layer. A simple formula was proposed to predict the tensile strength of welded–brazed joints using the computed cross-sectional Ti weld metal area.
Bi-Functionalized Transferrin@MoS2-PEG Nanosheets for Improving Cellular Uptake in HepG2 Cells
Authors: Xu Si , Liang Shanshan , Wang Bing , Wang Jiali , Wang Meng , Zheng Lingna , Fang Hao , Zhang Tingfeng , Bi Yi , Feng Weiyue
Published: March 2023

Pre-coating with a protein corona on the surface of nanomaterials (NMs) is an important strategy for reducing non-specific serum protein absorption while maintaining targeting specificity. Here, we present lipoic acid-terminated polyethylene glycol and transferrin bi-functionalized MoS2 nanosheets (Tf@MoS2-PEG NSs) as a feasible approach to enhance cellular uptake. Tf@MoS2-PEG NSs can maintain good dispersion stability in cell culture medium and effectively protect MoS2 NSs from oxidation in ambient aqueous conditions. Competitive adsorption experiments indicate that transferrin was more prone to bind MoS2 NSs than bovine serum albumin (BSA). It is noteworthy that single HepG2 cell uptake of Tf@MoS2-PEG presented a heterogeneous distribution pattern, and the cellular uptake amount spanned a broader range (from 0.4 fg to 2.4 fg). Comparatively, the intracellular Mo masses in HepG2 cells treated with BSA@MoS2-PEG and MoS2-PEG showed narrower distribution, indicating homogeneous uptake in the single HepG2 cells. Over 5% of HepG2 cells presented uptake of the Tf@MoS2-PEG over 1.2 fg of Mo, about three-fold that of BSA@MoS2-PEG (0.4 fg of Mo). Overall, this work suggests that Tf coating enhances the cellular uptake of MoS2 NSs and is a promising strategy for improving the intracellular uptake efficiency of cancer cells.
Electrochemical Atomic Force Microscopy Study on the Dynamic Evolution of Lithium Deposition
Authors: Shi Xixiu , Yang Jingru , Wang Wenyang , Liu Zhaoping , Shen Cai
Published: March 2023

Lithium metal is one of the most promising anode materials for lithium-ion batteries; however, lithium dendrite growth hinders its large-scale development. So far, the dendrite formation mechanism is unclear. Herein, the dynamic evolution of lithium deposition in etheryl-based and ethylene carbonate (EC)-based electrolytes was obtained by combining an in situ electrochemical atomic force microscope (EC-AFM) with an electrochemical workstation. Three growth modes of lithium particles are proposed: preferential, merged, and independent growth. In addition, a lithium deposition schematic is proposed to clearly describe the morphological changes in lithium deposition. This schematic shows the process of lithium deposition, thus providing a theoretical basis for solving the problem of lithium dendrite growth.
Rheological Behavior of the A356 Alloy in the Semisolid State at Low Shear Rates
Authors: Martin-Raya Oscar , Menargues Sergi , Martin Enric , Baile Maria Teresa , Picas Josep A.
Published: March 2023

To control the semisolid processing of aluminum alloys produced by the additive manufacturing technique, an exhaustive knowledge of their rheological behavior is required. In the semisolid state, metallic materials can show rheological characteristics similar to those of polymers, so semisolid state shaping is one of the currently considered routes for additive manufacturing with metallic materials. In this work, an approximation of the rheological control of the A356 aluminum alloy for its subsequent 3D manufacturing was carried out at a very low shear rate. A continuous cooling rheometer was designed and used, evaluating the influence of different process parameters on the viscosity variation of the aluminum alloy in the semisolid state. The results show an anomalous flow variation, indicating dilatant, and not thixotropic behavior, for very low shear rates.
Thermo-Hydrodynamic Effect of Gas Split Floating Ring Seal with Rayleigh Step Grooves
Authors: Bai Shaoxian , Chu Dongdong , Ma Chunhong , Yang Jing , Bao Shiyi
Published: March 2023

The force equilibrium and moment equilibrium play a significant role on the sealing performance of gas split floating ring seals. A small deflection angle may generate seriously wear on sealing surface and cause seal failure. Therefore, the thermo-hydrodynamic lubrication analysis of gas split floating ring seal with Rayleigh grooves is investigated considering the deflection angle and frictional heat of surface contact, which is beneficial to grasp the hydrodynamic characteristics and rules under high-temperature and high-speed conditions. Pressure and temperature distributions of sealing rings are numerically calculated for the cases with different deflection angle, rational speed, seal pressure and ambient temperature. Then, the hydrodynamic effect and sealing performance are analyzed. The obtained results show that, the surface Rayleigh step grooves do not present obvious hydrodynamic effect when split seal ring has no deflection. While, a significant hydrodynamic effect can be obtained when the split seal ring presents a deflection angle about dozens of micro radians. Here, a 10% increase of opening force is achieved when the deflection angle reaches 80 μrad in the case of speed 30,000 r/min and seal pressure 0.2 MPa. Moreover, the hydrodynamic effect becomes obvious with increasing deflection angle as well as rotational speed. Meanwhile, the growth of rotational speed results in an obvious increase of film temperature. The increase of ambient temperature has a significant influence on the decrease of leakage rate. When the ambient temperature increases from 340 K to 540 K, the leakage rate reduces exceeding 50%, however, it does not present obvious effect on the opening force. The proposed model has the potential to provide the theoretical basis and design guidance for surface grooves of gas split floating ring seal in the future.
Effect of Heat Input on the Microstructure and Mechanical Properties of Local Dry Underwater Welded Duplex Stainless Steel
Authors: Hu Yu , Shi Yonghua , Wang Kai , Huang Jiqiang
Published: March 2023

Duplex stainless steel welded metals were underwater local dry prepared on S32101 lean duplex stainless steel trapezoidal groove plates with a self-made drain cover employing Supercore 2205P flux-cored filler wire. Different heat inputs were employed to investigate the effects on mechanical characteristics and the microstructure of welded metals. The results demonstrated that as the heat was applied, austenite concentrations in the weld metals increased. It was found that the austenite concentration and the fraction of Σ3-austenite twin-grain boundaries followed the same trends. With increasing heat input, the recrystallized ferrite and austenite grains initially decreased and subsequently increased, whereas the fraction of interphase boundaries between special ferrite and austenite exhibited the reverse trend. With a heat input of 1.4 kJ/mm, the toughness and plasticity of the weld metals were enhanced by an increase in austenite content, Σ3 recrystallized grains, and austenite twin-grain boundaries. The plasticity and tensile strength values of the welded metal changed more when the heat input was raised from 1.0 to 1.2 kJ/mm than when it was raised from 1.2 to 1.4 kJ/mm. Considering energy conservation, it is recommended to adopt 1.2 kJ/mm for welding heat input.
Predicting Failure of Additively Manufactured Specimens with Holes
Authors: Schmeier Gina Eileen Chiara , Tröger Clara , Kwon Young W. , Sachau Delf
Published: March 2023

Experimental and computational studies were conducted to predict failure loads of specimens containing different-sized holes made using the additive manufacturing (AM) technique. Two different types of test specimens were prepared. Flat specimens, manufactured from polylactic acid (PLA), were subjected to uniaxial loading. Tubular specimens, made of polycarbonate (PC), were subjected to combined loading that was applied using uniaxial testing equipment. Test specimens were uniquely designed and printed to apply the combined bending and torsional loads to tubular specimens. A newly developed failure theory was applied to predict the loads that would result in the fracture of these test specimens. This theory is composed of two conditions related to stress and the stress gradient to be simultaneously satisfied to predict failure. The failure loads predicted using the new failure criteria were compared closely with the experimental data for all test specimens. In addition, a semi-empirical equation was developed to predict the critical failure surface energy for different printing angles. The critical failure surface energy is a material property and is used for the stress gradient condition. Using the semi-empirically determined values for the failure criterion provided close agreement with experimental results.
Adaptive Robust Autonomous Obstacle Traversal Controller for Novel Six-Track Robot
Authors: Bai Rengui , Niu Runxin , Wang Jie , Xu Zhaosheng
Published: March 2023

The separate control method of flippers and the movement of the mass center makes the active articulated tracked robot unable to realize higher-level motion and difficult to adapt to rough and complex obstacle terrain. In this paper, a new design method of distributed autonomous obstacle traversal controller for the novel six-track robot is proposed. The controller establishes a unified control framework that includes all degrees of freedom of the robot so that the center of mass tracking error and flipper motion tracking error can converge simultaneously to achieve obstacle traversal independently of specific terrain or tasks. First, the forward kinematics model and differential kinematics model of tracked robot are established to generate 3D motion, including flipper angular velocity and body traction velocity. Then, the differential drive robot model is extended into the differential kinematic model to eliminate the slip effect during obstacle traversal. Finally, the feedback control law of the control system and the optimal solution for the singular position of the robot structure are established. In addition, several simulation experiments and physical prototype experiments in different obstacle terrains are executed. In the virtual simulation experiment, the average trajectory error of the flipper is about 0.029 m. In the physical prototype experiment, compared to the manual remote controller and the prior art controller, the average error norm of the center of mass is reduced by 40.7% and 13.5%, respectively; the maximum slip norm is reduced by 34.6% and 19.9%, respectively; and the obstacle crossing time is reduced by 21.3% and 9.3%, respectively, and they validate the accuracy and effectiveness of the designed controller.
A Portable Real-Time Test Bench for Dielectric Elastomer Actuators
Authors: Sohlbach Lukas , Bhatta Sushil , Perez-Peña Fernando , Schmidt Karsten
Published: March 2023

Recently, a significant amount of research has been devoted to soft robots. Artificial muscles belong to the most important components of soft robots. Dielectric elastomer actuators (DEAs) represent the technology that comes closest to the capabilities of a natural muscle, making them the best candidates for artificial muscles in robotics and prosthetics applications. To develop these applications, an analysis of DEAs in a test bench must be possible. It is important that the environmental conditions are known, and all components are specified, which is not the case in most publications. This paper focuses on the development of a real-time test bench for DEAs which provides environmental conditions and all components that are specified. Its goal is to open up the research field of dielectric elastomer actuators or soft robots. The stacked DEA used is powered by a high-voltage amplifier, which can be controlled via a real-time block diagram environment together with a data acquisition (DAQ) device. The response of the actuator is measured with a laser triangulation sensor. Furthermore, information about the applied voltage, the operating current, the temperature, and the humidity are collected. It was demonstrated that the selected laser sensor is a suitable device for this application. Moreover, it was shown that the selected high-voltage amplifier is adequate to power a DEA. However, the DAQ is not fast enough to measure the actuator current. It was demonstrated that housing keeps environmental conditions constant, is transportable, and offers the flexibility to investigate different DEAs.
Preparation of Magnetic Iron Oxide Incorporated Mesoporous Silica Hybrid Composites for pH and Temperature-Sensitive Drug Delivery
Authors: Santhamoorthy Madhappan , Thirupathi Kokila , Krishnan Selvakumar , Guganathan Loganathan , Dave Sushma , Phan Thi Tuong Vy , Kim Seong-Cheol
Published: March 2023

In clinical applications for cancer treatment, chemotherapy coupled with thermotherapy is highly considered. The development of multifunctional nanocomposite materials is an appealing strategy for use in various applications including biomedical applications. We present the preparation of dopamine-modified mesoporous silica material, in which magnetic iron oxide nanoparticles (FeNP) were grown onto the outer surface via the complexation of iron (Fe(III) and Fe(II)) ions with the dopamine groups modified on the silica hybrid and subsequent chemical reduction approaches. The prepared magnetic iron oxide incorporated with mesoporous silica hybrid composite nanoparticles (FeNP@MSHC NPs) had a large surface area (346 m2/g), pore size (3.2 nm), and pore volume (0.048 cm3/g). The formation of FeNP on the outer surface of the FeNP@MSHC NPs results in superparamagnetic characteristics. Furthermore, the prepared FeNP@MSHC NPs have a high drug (Dox) loading capacity (~62%) as well as pH- and temperature-responsive drug release efficiency. In addition, the MTT assay result shows the biocompatibility of the prepared FeNP@MSHC NPs. As a result, the FeNP@MSHC NPs could be utilized in cancer treatment for pH and temperature-sensitive delivery of chemotherapeutic agents to the target sites.
Human Action Recognition-Based IoT Services for Emergency Response Management
Authors: Noor Talal H.
Published: March 2023

Emergency incidents can appear anytime and any place, which makes it very challenging for emergency medical services practitioners to predict the location and the time of such emergencies. The dynamic nature of the appearance of emergency incidents can cause delays in emergency medical services, which can sometimes lead to vital injury complications or even death, in some cases. The delay of emergency medical services may occur as a result of a call that was made too late or because no one was present to make the call. With the emergence of smart cities and promising technologies, such as the Internet of Things (IoT) and computer vision techniques, such issues can be tackled. This article proposes a human action recognition-based IoT services architecture for emergency response management. In particular, the architecture exploits IoT devices (e.g., surveillance cameras) that are distributed in public areas to detect emergency incidents, make a request for the nearest emergency medical services, and send emergency location information. Moreover, this article proposes an emergency incidents detection model, based on human action recognition and object tracking, using image processing and classifying the collected images, based on action modeling. The primary notion of the proposed model is to classify human activity, whether it is an emergency incident or other daily activities, using a Convolutional Neural Network (CNN) and Support Vector Machine (SVM). To demonstrate the feasibility of the proposed emergency detection model, several experiments were conducted using the UR fall detection dataset, which consists of emergency and other daily activities footage. The results of the conducted experiments were promising, with the proposed model scoring 0.99, 0.97, 0.97, and 0.98 in terms of sensitivity, specificity, precision, and accuracy, respectively.
Financial Risk Measurement and Spatial Spillover Effects Based on an Imported Financial Risk Network: Evidence from Countries along the Belt and Road
Authors: Chen Shaowei , Guo Long , Zhang Weike
Published: March 2023

Using the financial market data of 35 countries along the Belt and Road (B&R), this paper constructs an imported financial risk network based on the conditional expected shortfall (CoES) to measure the systemic financial risk of the countries along the B&R. Furthermore, complex network theory is combined with spatial econometrics to construct a spatial, financial network panel model to measure the spatial spillover effects of imported financial risks and further explore the macroeconomic influences on systemic financial risks. The results show that among the countries along the B&R, the level of systemic financial risk in the European region is higher than that in the Asian region from the imported risk perspective. The spatial spillover effect of financial risk and the spatial spillover effect from the imported risk perspective have time-varying characteristics, with the spatial spillover effect increasing significantly during crisis periods. In addition, indicators of the three dimensions of economic openness, the institutional environment, and the external policy environment all have significant effects on systemic financial risk, but the effects differ across regions and periods.
Recent Developments in Game-Theory Approaches for the Detection and Defense against Advanced Persistent Threats (APTs): A Systematic Review
Authors: Khalid Mohd Nor Akmal , Al-Kadhimi Amjed Ahmed , Singh Manmeet Mahinderjit
Published: March 2023

Cybersecurity has become a prominent issue in regard to ensuring information privacy and integrity in the internet age particularly with the rise of interconnected devices. However, advanced persistent threats (APTs) pose a significant danger to the current contemporary way of life, and effective APT detection and defense are vital. Game theory is one of the most sought-after approaches adopted against APTs, providing a framework for understanding and analyzing the strategic interactions between attackers and defenders. However, what are the most recent developments in game theory frameworks against APTs, and what approaches and contexts are applied in game theory frameworks to address APTs? In this systematic literature review, 48 articles published between 2017 and 2022 in various journals were extracted and analyzed according to PRISMA procedures and our formulated research questions. This review found that game-theory approaches have been optimized for the defensive performance of security measures and implemented to anticipate and prepare for countermeasures. Many have been designed as part of incentive-compatible and welfare-maximizing contracts and then applied to cyber–physical systems, social networks, and transportation systems, among others. The trends indicate that game theory provides the means to analyze and understand complex security scenarios based on technological advances, changes in the threat landscape, and the emergence of new trends in cyber-crime. In this study, new opportunities and challenges against APTs are outlined, such as the ways in which tactics and techniques to bypass defenses are likely to evolve in order to evade detection, and we focused on specific industries and sectors of high interest or value (e.g., healthcare, finance, critical infrastructure, and the government).
Machine-Learning Approach for Risk Estimation and Risk Prediction of the Effect of Climate on Bovine Respiratory Disease
Authors: Gwaka Joseph K. , Demafo Marcy A. , N’konzi Joel-Pascal N. , Pak Anton , Olumoh Jamiu , Elfaki Faiz , Adegboye Oyelola A.
Published: March 2023

Bovine respiratory disease (BRD) is a major cause of illness and death in cattle; however, its global extent and distribution remain unclear. As climate change continues to impact the environment, it is important to understand the environmental factors contributing to BRD’s emergence and re-emergence. In this study, we used machine-learning models and remotely sensed climate data at 2.5 min (21 km2) resolution environmental layers to estimate the risk of BRD and predict its potential future distribution. We analysed 13,431 BRD cases from 1727 cities worldwide between 2005 and 2021 using two machine-learning models, maximum entropy (MaxEnt) and Boosted Regression Trees (BRT), to predict the risk and geographical distribution of the risk of BRD globally with varying model parameters. Different re-sampling regimes were used to visualise and measure various sources of uncertainty and prediction performance. The best-fitting model was assessed based on the area under the receiver operator curve (AUC-ROC), positive predictive power and Cohen’s Kappa. We found that BRT had better predictive power compared with MaxEnt. Our findings showed that favourable habitats for BRD occurrence were associated with the mean annual temperature, precipitation of the coldest quarter, mean diurnal range and minimum temperature of the coldest month. Similarly, we showed that the risk of BRD is not limited to the currently known suitable regions of Europe and west and central Africa but extends to other areas, such as Russia, China and Australia. This study highlights the need for global surveillance and early detection systems to prevent the spread of disease across borders. The findings also underscore the importance of bio-security surveillance and livestock sector interventions, such as policy-making and farmer education, to address the impact of climate change on animal diseases and prevent emergencies and the spread of BRD to new areas.
Large-Scale Competitive Learning-Based Salp Swarm for Global Optimization and Solving Constrained Mechanical and Engineering Design Problems
Authors: Qaraad Mohammed , Aljadania Abdussalam , Elhosseini Mostafa
Published: March 2023

The Competitive Swarm Optimizer (CSO) has emerged as a prominent technique for solving intricate optimization problems by updating only half of the population in each iteration. Despite its effectiveness, the CSO algorithm often exhibits a slow convergence rate and a tendency to become trapped in local optimal solutions, as is common among metaheuristic algorithms. To address these challenges, this paper proposes a hybrid approach combining the CSO with the Salp Swarm algorithm (SSA), CL-SSA, to increase the convergence rate and enhance search space exploration. The proposed approach involves a two-step process. In the first step, a pairwise competition mechanism is introduced to segregate the solutions into winners and losers. The winning population is updated through strong exploitation using the SSA algorithm. In the second step, non-winning solutions learn from the winners, achieving a balance between exploration and exploitation. The performance of the CL-SSA is evaluated on various benchmark functions, including the CEC2017 benchmark with dimensions 50 and 100, the CEC2008lsgo benchmark with dimensions 200, 500 and 1000, as well as a set of seven well-known constrained design challenges in various engineering domains defined in the CEC2020 conference. The CL-SSA is compared to other metaheuristics and advanced algorithms, and its results are analyzed through statistical tests such as the Friedman and Wilcoxon rank-sum tests. The statistical analysis demonstrates that the CL-SSA algorithm exhibits improved exploitation, exploration, and convergence patterns compared to other algorithms, including SSA and CSO, as well as popular algorithms. Furthermore, the proposed hybrid approach performs better in solving most test functions.
Lung Nodule CT Image Segmentation Model Based on Multiscale Dense Residual Neural Network
Authors: Zhang Xinying , Kong Shanshan , Han Yang , Xie Baoshan , Liu Chunfeng
Published: March 2023

To solve the problem of the low segmentation accuracy of lung nodule CT images using U-Net, an improved method for segmentation of lung nodules by U-Net was proposed. Initially, the dense network connection and sawtooth expanded convolution design was added to the feature extraction part, and a local residual design was adopted in the upsampling process. Finally, the effectiveness of the proposed algorithm was evaluated using the LIDC-IDRI lung nodule public dataset. The results showed that the improved algorithm had 7.03%, 14.05%, and 10.43% higher performance than the U-Net segmentation algorithm under the three loss functions of DC, MIOU, and SE, and the accuracy was 2.45% higher compared with that of U-Net. Thus, the proposed method had an effective network structure.
Shunting Inhibitory Cellular Neural Networks with Compartmental Unpredictable Coefficients and Inputs
Authors: Akhmet Marat , Tleubergenova Madina , Zhamanshin Akylbek
Published: March 2023

Shunting inhibitory cellular neural networks with compartmental periodic unpredictable coefficients and inputs is the focus of this research. A new algorithm is suggested, to enlarge the set of known unpredictable functions by applying diagonalization in arguments of functions of several variables. Sufficient conditions for the existence and uniqueness of exponentially stable unpredictable and Poisson stable outputs are obtained. To attain theoretical results, the included intervals method and the contraction mapping principle are used. Appropriate examples with numerical simulations that support the theoretical results are provided. It is shown how dynamics of the neural network depend on a new numerical characteristic, the degree of periodicity.
A Review of Chaotic Systems Based on Memristive Hopfield Neural Networks
Authors: Lin Hairong , Wang Chunhua , Yu Fei , Sun Jingru , Du Sichun , Deng Zekun , Deng Quanli
Published: March 2023

Since the Lorenz chaotic system was discovered in 1963, the construction of chaotic systems with complex dynamics has been a research hotspot in the field of chaos. Recently, memristive Hopfield neural networks (MHNNs) offer great potential in the design of complex, chaotic systems because of their special network structures, hyperbolic tangent activation function, and memory property. Many chaotic systems based on MHNNs have been proposed and exhibit various complex dynamical behaviors, including hyperchaos, coexisting attractors, multistability, extreme multistability, multi-scroll attractors, multi-structure attractors, and initial-offset coexisting behaviors. A comprehensive review of the MHNN-based chaotic systems has become an urgent requirement. In this review, we first briefly introduce the basic knowledge of the Hopfiled neural network, memristor, and chaotic dynamics. Then, different modeling methods of the MHNN-based chaotic systems are analyzed and discussed. Concurrently, the pioneering works and some recent important papers related to MHNN-based chaotic systems are reviewed in detail. Finally, we survey the progress of MHNN-based chaotic systems for application in various scenarios. Some open problems and visions for the future in this field are presented. We attempt to provide a reference and a resource for both chaos researchers and those outside the field who hope to apply chaotic systems in a particular application.
Model Predictive Control of Parabolic PDE Systems under Chance Constraints
Authors: Voropai Ruslan , Geletu Abebe , Li Pu
Published: March 2023

Model predictive control (MPC) heavily relies on the accuracy of the system model. Nevertheless, process models naturally contain random parameters. To derive a reliable solution, it is necessary to design a stochastic MPC. This work studies the chance constrained MPC of systems described by parabolic partial differential equations (PDEs) with random parameters. Inequality constraints on time- and space-dependent state variables are defined in terms of chance constraints. Using a discretization scheme, the resulting high-dimensional chance constrained optimization problem is solved by our recently developed inner–outer approximation which renders the problem computationally amenable. The proposed MPC scheme automatically generates probability tubes significantly simplifying the derivation of feasible solutions. We demonstrate the viability and versatility of the approach through a case study of tumor hyperthermia cancer treatment control, where the randomness arises from the thermal conductivity coefficient characterizing heat flux in human tissue.
Computational and Stability Analysis of MHD Time-Dependent Thermal Reaction Flow Impinging on a Vertical Porous Plate Enclosing Magnetic Prandtl Number and Thermal Radiation Effect
Authors: Zeeshan  , Ahammad N. Ameer , Shah Nehad Ali , Chung Jae Dong , Khan Muhammad Shoaib
Published: March 2023

The aim of the present study is to investigate magnetohydrodynamic (MHD) time-dependent flow past a vertical slanted plate enclosing heat and mass transmission (HMT), induced magnetic field (IMF), thermal radiation (TR), and viscous and magnetic dissipation characteristics on a chemical reaction fluid flow. A boundary layer estimate is taken to develop a movement that exactly captures the time-dependent equations for continuity, momentum, magnetic induction, energy, concentration, generalized Ohm’s law, and Maxwell’s model. Partial differential equations designate the path occupied by the magnetized fluid as it passes through the porous matrix. In addition, a heat source is included in the model in order to monitor the flow nature in the current study. Because of the nonlinearity in the governing equations, the mathematical models are computed numerically by RK4 method. Further, tables and graphs are depicted to elucidate the physical influence of important factors on the flow characteristics. The novelty of the present work is investigating the irregular heat source and chemical reaction over the porous rotating channel. It is perceived that high thermal radiation occurs with increases in temperature and concentration. It is witnessed that the IMF effect is diminished for large values of magnetic Prandtl number (MPN). It is also analyzed that with increasing the heat source factor, the velocity of the fluid enhances. For stability analysis, the existing effort is compared with the published work and good agreement is found. Moreover, the residue error estimation confirms our solution.
Machine Learning Techniques Applied to the Harmonic Analysis of Railway Power Supply
Authors: Panoiu Manuela , Panoiu Caius , Mezinescu Sergiu , Militaru Gabriel , Baciu Ioan
Published: March 2023

Harmonic generation in power system networks presents significant issues that arise in power utilities. This paper describes a machine learning technique that was used to conduct a research study on the harmonic analysis of railway power stations. The research was an investigation of a time series whose values represented the total harmonic distortion (THD) for the electric current. This study was based on information collected at a railway power station. In an electrified substation, measurements of currents and voltages were made during a certain interval of time. From electric current values, the THD was calculated using a fast Fourier transform analysis (FFT) and the results were used to train an adaptive ANN—GMDH (artificial neural network–group method of data handling) algorithm. Following the training, a prediction model was created, the performance of which was investigated in this study. The model was based on the ANN—GMDH method and was developed for the prediction of the THD. The performance of this model was studied based on its parameters. The model’s performance was evaluated using the regression coefficient (R), root-mean-square error (RMSE), and mean absolute error (MAE). The model’s performance was very good, with an RMSE (root-mean-square error) value of less than 0.01 and a regression coefficient value higher than 0.99. Another conclusion from our research was that the model also performed very well in terms of the training time (calculation speed).
The Ergodicity and Sensitivity of Nonautonomous Discrete Dynamical Systems
Authors: Li Risong , Lu Tianxiu , Wang Hongqing , Zhou Jie , Ding Xianfeng , Li Yongjiang
Published: March 2023

Let (E,h1,∞) be a nonautonomous discrete dynamical system (briefly, N.D.D.S.) that is defined by a sequence (hj)j=1∞ of continuous maps hj:E→E over a nontrivial metric space (E,d). This paper defines and discusses some forms of ergodicity and sensitivity for the system (E,h1,∞) by upper density, lower density, density, and a sequence of positive integers. Under some conditions, if the rate of convergence at which (hj)j=1∞ converges to the limit map h is “fast enough” with respect to a sequence of positive integers with a density of one, it is shown that several sensitivity properties for the N.D.D.S. (E,h1,∞) are the same as those properties of the system (E,h). Some sufficient conditions for the N.D.D.S. (E,h1,∞) to have stronger sensitivity properties are also presented. The conditions in our results are less restrictive than those in some existing works, and the conclusions of all the theorems in this paper improve upon those of previous studies. Thus, these results are extensions of the existing ones.
Ovarian Cancer—Insights into Platinum Resistance and Overcoming It
Authors: Havasi Andrei , Cainap Simona Sorana , Havasi Ana Teodora , Cainap Calin
Published: March 2023

Ovarian cancer is the most lethal gynecologic malignancy. Platinum-based chemotherapy is the backbone of treatment for ovarian cancer, and although the majority of patients initially have a platinum-sensitive disease, through multiple recurrences, they will acquire resistance. Platinum-resistant recurrent ovarian cancer has a poor prognosis and few treatment options with limited efficacy. Resistance to platinum compounds is a complex process involving multiple mechanisms pertaining not only to the tumoral cell but also to the tumoral microenvironment. In this review, we discuss the molecular mechanism involved in ovarian cancer cells’ resistance to platinum-based chemotherapy, focusing on the alteration of drug influx and efflux pathways, DNA repair, the dysregulation of epigenetic modulation, and the involvement of the tumoral microenvironment in the acquisition of the platinum-resistant phenotype. Furthermore, we review promising alternative treatment approaches that may improve these patients’ poor prognosis, discussing current strategies, novel combinations, and therapeutic agents.
Chemical Composition, Antibacterial Activity and In Vitro Anticancer Evaluation of Ochradenus baccatus Methanolic Extract
Authors: Khojali Weam M. A. , Hussein Weiam , Bin Break Mohammed Khaled , Alafnan Ahmed , Huwaimel Bader , Khalifa Nasrin E. , Badulla Wafa F. S. , Alshammari Raghad Abdulkarem , Alshammari Lama Khalid , Alshammari Rehab Aladham Raji , Albarak Sara Mohsen , Alrkad Enas Hmdan , Mahboob Tooba , Alshammari Hisham
Published: March 2023

Background and Objectives: Ochradenus baccatus belongs to the family Resedaceae. It is widely spread in Saudi Arabia and other countries in Southwest Asia. O. baccatus is extensively used in traditional medicine as an anti-inflammatory and antibacterial agent, in addition to being a vital source of food for certain desert animal species. The aim of the present study was to investigate the chemical composition and antibacterial/anticancer activities of O. baccatus methanolic extracts collected from Hail, Saudi Arabia. Materials and Methods: The O. baccatus extracts were obtained by macerating the crude powder in methanol, followed by filtration and evaporation. Liquid chromatography–mass spectrometry (LC-MS) was used to analyze the methanolic extracts’ chemical constituents. Broth microdilution assay for minimum inhibitory concentration (MIC) determination was used to assess antimicrobial activity, while the extracts’ anticancer potential was assessed by sulforhodamine B Assay (SRB) assay. Results: The results of the antibacterial assay showed that the methanolic extracts from the roots and branches possessed varying degrees of activity against particular bacterial strains, with the highest activity being exerted by the branches’ extract against Escherichia coli and Salmonella typhimurium (St), demonstrating MIC values of 15.6 µg/mL and 20 µg/mL, respectively. Furthermore, the SRB cell viability assay revealed that only the branches’ extract inhibited the growth of A549 cancer cells, with an IC50 value of 86.19 µg/mL. The LC-MS analysis of the methanolic extracts from the plant’s roots and branches was then conducted, resulting in the identification of 8 and 13 major chemical constituents, respectively. Azelaic acid, β-amyrin, and phytanic acid are some of the bioactive compounds that were detected in the extracts via LC-MS, and they are thought to be responsible for the observed antibacterial/anticancer activity of O. baccatus methanolic extracts. Conclusions: This study confirmed the antibacterial/anticancer potential of O. baccatus methanolic extracts and analyzed their phytochemical constituents. Further isolation and biological screening are warranted to understand the therapeutic potential of O. baccatus.
Spectrum of Autoimmune Diseases—Chronic Lymphocytic Inflammation with Pontine Perivascular Enhancement Responsive to Steroids (CLIPPERS)—Clinical Case
Authors: Meller Agnieszka , Pawlukowska Wioletta , Machowska-Sempruch Karolina , Marta Masztalewicz
Published: March 2023

Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) syndrome is a rare inflammatory disease of an undetermined aetiology. The condition is characterised by a range of clinical manifestations generally associated with damage to brainstem structures, the cerebellum, with characteristic magnetic resonance imaging (MRI) findings. The main feature is a good clinical and radiological response to glucocorticosteroid (GCS)-based immunosuppressive treatment. The diagnosis of CLIPPERS is difficult and requires extensive differential diagnosis. A specific biomarker in serum or cerebrospinal fluid (CSF) for this disorder is currently unknown. The pathogenesis of CLIPPERS remains poorly understood and its nosological position has not yet been established. Whether CLIPPERS represents an independent, genuine new disorder or a syndrome in the course of diseases with heterogeneous aetiology and/or their precursor stages remains debatable and incompletely clarified. We present a case report of a patient who was diagnosed with CLIPPERS syndrome on the basis of her clinical and radiological features and by performing an extensive differential diagnosis. The patient has been under neurological follow-up for five years.
The HIT Study—The Hydroxychloroquine Effect in the Treatment of Patients with Age-Related Macular Degeneration: A Randomized Controlled Trial
Authors: Yahalomi Tal , Pikkel Yoav , Arnon Roee , Porat Dafi , Pikkel Joseph
Published: March 2023

Background and Objectives: Decreased age-related macular degeneration (AMD) has been reported in individuals with rheumatoid arthritis treated with hydroxychloroquine (HCQ, plaquenil). Materials and Methods: In a randomized controlled trial with a parallel study design, we assessed visual acuity, central macular thickness measured with macular optical coherence tomography (OCT), and the number and size of drusen, following treatment with HCQ or a placebo in individuals with AMD. The patients received a daily dosage of 400 mg hydroxychloroquine (study group) or placebo (control group) during 12 months, and underwent complete ophthalmic examinations at 3, 6, 9, 12 and 24 months after initiation of treatment. Results: Of the 110 patients who were randomized to the treatment groups, 46 (29 females) in the study group and 50 (29 females) in the control group completed the study. The study group showed less visual acuity deterioration at two-year follow-up than did the control group (−0.03 ± 0.07 vs. −0.07 ± 0.07, p = 0.027). At two years after treatment initiation, the mean number of drusen per eye was lower for ARDS2 (8.1 vs. 12.3, p = 0.045) in the study group, compared to the control group. Compared to the control group, the proportion of eyes with increased drusen growth was smaller for both ARDS2 and ARDS3 drusen in the study group, and the proportion of the total drusen with growth was smaller for the study group as well: 32/46 eyes (70%) vs. 40/50 eyes (80%). Drusen volume growth, as calculated by the area and height measured with macular OCT, was also more reduced in the study than the control group (0.20 ± 0.15 vs. 0.23 ± 0.16 mm4, p = 0.05). None of the participants showed HCQ toxicity or adverse effects. Conclusion: Among patients with AMD, visual deterioration, the growth and the amount of drusen formation at two years after treatment initiation was less among those treated with HCQ than with a placebo. In this study, there was a negative association between HCQ treatment and wet AMD development.
Performance of Six Clinical Physiological Scoring Systems in Predicting In-Hospital Mortality in Elderly and Very Elderly Patients with Acute Upper Gastrointestinal Bleeding in Emergency Department
Authors: Wu Po-Han , Hung Shang-Kai , Ko Chien-An , Chang Chia-Peng , Hsiao Cheng-Ting , Chung Jui-Yuan , Kou Hao-Wei , Chen Wan-Hsuan , Hsieh Chiao-Hsuan , Ku Kai-Hsiang , Wu Kai-Hsiang
Published: March 2023

Background and Objectives: The aim of this study is to compare the performance of six clinical physiological-based scores, including the pre-endoscopy Rockall score, shock index (SI), age shock index (age SI), Rapid Acute Physiology Score (RAPS), Rapid Emergency Medicine Score (REMS), and Modified Early Warning Score (MEWS), in predicting in-hospital mortality in elderly and very elderly patients in the emergency department (ED) with acute upper gastrointestinal bleeding (AUGIB). Materials and Methods: Patients older than 65 years who visited the ED with a clinical diagnosis of AUGIB were enrolled prospectively from July 2016 to July 2021. The six scores were calculated and compared with in-hospital mortality. Results: A total of 336 patients were recruited, of whom 40 died. There is a significant difference between the patients in the mortality group and survival group in terms of the six scoring systems. MEWS had the highest area under the curve (AUC) value (0.82). A subgroup analysis was performed for a total of 180 very elderly patients (i.e., older than 75 years), of whom 27 died. MEWS also had the best predictive performance in this subgroup (AUC, 0.82). Conclusions: This simple, rapid, and obtainable-by-the-bed parameter could assist emergency physicians in risk stratification and decision making for this vulnerable group.