bluuebunny/crossref_metadata_2025 huggingface dataset:
Hexakis(μ-3-aminopropanethiolato-1κ6N,S:2κ3S;3κ6N,S:2κ3S)cadmium(II)dirhodium(III) Dibromide Tetrahydrate
Authors: Kouno Masahiro , Yoshinari Nobuto , Kojima Tatsuhiro , Konno Takumi
Published: July 2023

Cadmium(II) complexes with thiolate ligands have received considerable attention because of their intriguing structural features and relevance to metalloproteins. In this study, a new cadmium(II)–rhodium(III) trinuclear complex, [Cd{Rh(apt)3}2]Br2·4H2O (1, apt = 3-aminopropanethiolate), was synthesized by the reaction of fac-[Rh(apt)3] with cadmium bromide. Compound 1 was characterized using elemental analysis, X-ray fluorescence and IR spectroscopies, and powder X-ray diffraction study. Single-crystal X-ray analysis revealed that the cadmium(II) center in 1 was surrounded by six thiolato S atoms from two fac-[Rh(apt)3] units.
A New Method of Predicting the Parameters of the Rotational Friction Welding Process Based on the Determination of the Frictional Heat Transfer in Ti Grade 2/AA 5005 Joints
Authors: Lacki Piotr , Adamus Janina , Więckowski Wojciech , Motyka Maciej
Published: July 2023

The article presents an original approach to determining the basic parameters of rotational friction welding (RFW) based on the analysis of friction heat transfer at the faying surfaces. Dissimilar Ti Grade 2/AA 5005 joints were used to demonstrate the method. The work established that for the analyzed joint, the optimum temperature at the faying surface that allow for a good quality weld to be obtained should be ~505 °C. On this basis, a map of optimal parameters was developed to achieve this temperature. This approach could potentially allow for more precise control of the welding process, leading to better joint quality and performance. The paper includes both a description of the technological process of friction welding and an attempt to explain the mechanism of the phenomena occurring in the welding area. The numerical calculations presented in the article were carried out using the ADINA System v. 9.8.2, which allows for the consideration of heat friction in the axial symmetric thermo-mechanical model. Frictional resistance was determined by the temperature-dependent friction coefficient. The assumed thermo-mechanical model required the determination of elastic-plastic properties versus temperature for the analyzed materials. The simulations of the friction welding were carried out for the different welding parameters and time. The different variants of friction welding were modelled.
The Effect of Hydrothermal, Microwave, and Mechanochemical Treatments of Tin Phosphate on Sorption of Some Cations
Authors: Zakutevskyy Oleg , Khalameida Svitlana , Sydorchuk Volodymyr , Kovtun Mariia
Published: July 2023

The samples of precipitated tin (IV) phosphate, modified using hydrothermal, microwave, and mechanochemical procedures, were studied in the process of Cs(I), Sr(II), and U(VI) ion sorption. The initial and modified samples were investigated before and after sorption using XRD, XRF, FTIR, and nitrogen adsorption–desorption. It was found that the modification procedures transformed the micro-mesoporous structure of the initial sample into a meso–macroporous structure. As a result, the sorption capacity in relation to all ions increases several times. This indicates the determining role of the porous structure, primary content, and mesopore size on the sorption activity of tin phosphate. The samples, treated in the form of a wet gel, which is a novel procedure, showed the maximum sorption indicators. The sorption of all the tested ions is described by the Langmuir isotherm.
Research on the Model for the Friction Coefficient of Resin-Based Friction Material and Its Experimental Verification
Authors: Fang Shanglong , Xiao Wei , Chen Kewen , Song Xuding
Published: July 2023

Resin-based friction materials have been widely used in the friction braking of automobiles and power machinery. Based on experiments for the variation law of friction and wear morphology, a new model for the friction coefficient of resin-based friction materials was proposed, which includes the effects of both the micro convex body on the surface of the friction material and the frictional film generated during the friction process. This quantitative model of friction coefficient materials was established for the modelling of shear strength, compressive strength, shear strength of the frictional film, contact load and wear morphology. The shear strength, compressive strength and wear morphology of the friction material were adjusted by changing the content of basalt fibers and flaky potassium magnesium titanate. Finally, the accuracy of this quantitative model of friction coefficient was verified through experiments on friction samples with different formulations and by changing the frictional contact load. The results show that the predicted friction coefficient of the model is in good agreement with the experimental friction coefficient, the difference between the upper and lower limits of the forecast is only 5.03% and 2.30%, respectively. Meanwhile, the influence of the ratio of shear strength to compressive strength on the friction coefficient is greater than the proportion of wear morphology. The proposed friction model provides a reference value for the study of new resin-based friction materials.
A Comprehensive Review of the Current Research Status of Biodegradable Zinc Alloys and Composites for Biomedical Applications
Authors: Kong Lingyun , Heydari Zahra , Lami Ghadeer Hazim , Saberi Abbas , Baltatu Madalina Simona , Vizureanu Petrica
Published: July 2023

Zinc (Zn)-based biodegradable materials show moderate degradation rates in comparison with other biodegradable materials (Fe and Mg). Biocompatibility and non-toxicity also make them a viable option for implant applications. Furthermore, Pure Zn has poor mechanical behavior, with a tensile strength of around 100–150 MPa and an elongation of 0.3–2%, which is far from reaching the strength required as an orthopedic implant material (tensile strength is more than 300 MPa, elongation more than 15%). Alloy and composite fabrication have proven to be excellent ways to improve the mechanical performance of Zn. Therefore, their alloys and composites have emerged as an innovative category of biodegradable materials. This paper summarizes the most important recent research results on the mechanical and biological characteristics of biodegradable Zn-based implants for orthopedic applications and the most commonly added components in Zn alloys and composites.
Numerical and Experimental Analysis of Horizontal-Axis Wind Turbine Blade Fatigue Life
Authors: Shah Imran , Khan Abdullah , Ali Muhsin , Shahab Sana , Aziz Shahid , Noon Muhammad Adnan Aslam , Tipu Javed Ahmad Khan
Published: July 2023

Horizontal-axis wind turbines are the most popular wind machines in operation today. These turbines employ aerodynamic blades that may be oriented either upward or downward. HAWTs are the most common non-conventional source of energy generation. These turbine blades fail mostly due to fatigue, as a large centrifugal force acts on them at high rotational speeds. This study aims to increase a turbine’s service life by improving the turbine blades’ fatigue life. Predicting the fatigue life and the design of the turbine blade considers the maximum wind speed range. SolidWorks, a CAD program, is used to create a wind turbine blade utilizing NACA profile S814. The wind turbine blade’s fatigue life is calculated using Morrow’s equation. A turbine blade will eventually wear out due to several forces operating on it. Ansys software is used to analyze these stresses using the finite element method. The fatigue study of wind turbine blades is described in this research paper. To increase a turbine blade’s fatigue life, this research study focuses on design optimization. Based on the foregoing characteristics, an improved turbine blade design with a longer fatigue life than the original one is intended in this study. The primary fatigue parameters are the length of a chord twist angle and blade length. The experimental data computed with the aid of a fatigue testing machine are also used to validate the numerical results, and it is found that they are very similar to one another. By creating the most effective turbine blades with the longest fatigue life, this research study can be developed further. The most effective turbine blades with the longest fatigue life can be designed to further this research investigation.
Discontinuous PWM Strategy with Frequency Modulation for Vibration Reduction in Asynchronous Machines
Authors: Ruiz-González Antonio , Heredia-Larrubia Juan-Ramón , Pérez-Hidalgo Francisco M. , Meco-Gutiérrez Mario Jesus
Published: July 2023

The aim of this paper is to present our research into the reduction of vibrations in induction motors. The use of power inverters results in the generation of electrical harmonics, which increase the level of the mechanical vibrations of electrical machines. To reduce these harmonics, we present a discontinuous pulse-width modulation (PWM) control strategy based on carrier-wave modulation applied to multilevel inverters. Using the proposed modulation technique, the amplitude of the electrical harmonics is reduced, as compared to other conventional techniques. These current harmonics produce the MMF (magnetomotive force) harmonics in the air gap, which are one of the main sources of vibrations. The control strategy makes it possible to vary the electrical spectrum at the output of a multilevel inverter by modifying a control parameter of the carrier wave in the PWM, thus avoiding the natural frequencies of mechanical resonance. The proposed technique also has the feature of attenuating the total harmonics distortion of the voltage of the multilevel inverters, as well as the achievement of a higher RMS value of the output voltage for the same DC level. Laboratory results for an induction motor with different modulation strategies, applied in a multilevel inverter and compared to the strategy presented, are attached.
Mitigation of Lightning-Induced Transient Effects on a Hybrid Photovoltaic–Wind System Based on Lightning Protection Standards
Authors: Abda Zmnako Mohammed Khurshid , Ab Kadir Mohd Zainal Abidin , Hizam Hashim , Gomes Chandima
Published: July 2023

Installing surge protection devices in a hybrid photovoltaic (PV)–wind system is essential to guarantee the survival of the system’s components. If the surge arresters are connected without taking into account the recommendations given by standards, the equipment to be protected might be damaged despite the energy coordination of the arresters. In this study, nonlinear surge protective devices (SPDs) are designed for a multi-MW hybrid system based on lightning protection standards with optimised threat level ratings to investigate the mitigation of lightning transients to an acceptable level. The system is implemented using Power System Computer-Aided Design for Electromagnetic Transients including Direct Current (PSCAD/EMTDC) software. It comprises a 2 MW PV farm, a 2 MW wind farm, and a backup energy storage system (ESS), which are all connected to a 132 kV grid via a step-up transformer and a transmission line. The results were obtained at critical system nodes for two standard lightning current surges, i.e., 1/10 µs and 10/350 µs, considering two lightning strike point scenarios with and without a lightning protection system (LPS). The simulation results showed that the connected SPDs could successfully limit the transient overvoltage in the system to an acceptable level. The analysis in this work is crucial for designing, operating, and maintaining a hybrid PV–wind system. It can help to find the potential vulnerability areas within such a system and implement appropriate protection measures since there is no available lightning standard for such systems. Additionally, it assists the system operators in increasing the uptime and dependability of their RE systems, limiting expensive downtime and environmental effects while optimising energy output. Based on the results obtained, recommendations were made for lightning protection developers.
Development of a Digital Twin for a Hydraulic, Active Seat Suspension System
Authors: Antonelli Michele Gabrio , Brunetti Jacopo , D’Ambrogio Walter , Fregolent Annalisa , Nataletti Pietro
Published: July 2023

The vibrations induced by the soil irregularities and other equivalent disturbances on agricultural tractors represent a major cause of disease for tractor drivers. The reduction of vibration exposure of operators is a topic of interest for the (Italian) National Institute for Insurance against Accidents at Work (INAIL). Several passive, semi-active, and active solutions are commercially available for the seat or the cabin suspension to isolate the driver from the vibrations. A prototype of a hydraulic active suspension system for the operator seat has been developed in the laboratories of INAIL. In this paper, nonlinear multi-physics modeling of the prototype has been carried after an experimental identification of the actuation system and specifically of the control valve parameters. The model is adjusted to retrace the system’s response and is used as a digital twin of the physical prototype to develop and optimize the control system. An equivalent simplified model is obtained to design a proper control strategy for the active suspension system. Finally, the controller is tested on the digital twin of the system to assess its performance in isolating vibrations.
A Study of Knee Exoskeleton Configuration Based on Lower Limb Motion Characteristics Analysis
Authors: Tang Xinyao , Wang Xupeng , Xue Yanmin , Yin Rong , Yang Jiayin
Published: July 2023

In order to solve poor coordination between the exoskeleton and the human leg, this article analyzed the spatiotemporal characteristics of lower limb motion using data collection from human walking gait experiments. According to the macro- and micro-motion mechanisms of the knee joint, six knee exoskeleton configurations were proposed. Combined with the analysis of gait characteristics, mathematical models for lower limb kinematics and dynamics were established and verified with numerical simulation. Using human–machine coupling simulation experiments, different knee exoskeleton devices were simulated for wear, and a configuration of the exoskeleton mechanism compatible with human knee motion was selected, which improved human–machine adaptability and coordination. This study provides a new method for studying adaptive knee exoskeletons.
Existence and Uniqueness of Non-Negative Solution to a Coupled Fractional q-Difference System with Mixed q-Derivative via Mixed Monotone Operator Method
Authors: Meng Yuan , He Conghong , Ma Renhao , Pang Huihui
Published: July 2023

In this paper, we study a nonlinear Riemann-Liouville fractional a q-difference system with multi-strip and multi-point mixed boundary conditions under the Caputo fractional q-derivative, where the nonlinear terms contain two coupled unknown functions and their fractional derivatives. Using the fixed point theorem for mixed monotone operators, we constructe iteration functions for arbitrary initial value and acquire the existence and uniqueness of extremal solutions. Moreover, a related example is given to illustrate our research results.
A Dual Rumor Spreading Model with Consideration of Fans versus Ordinary People
Authors: Xiao Hongying , Li Zhaofeng , Zhang Yuanyuan , Lin Hong , Zhao Yuxiao
Published: July 2023

The spread of rumors in online social networks (OSNs) has caused a serious threat to the normal social order. In order to describe the rumor-spreading dynamics in OSNs during emergencies, a novel model with consideration of fans versus ordinary people is proposed in this paper. In contrast to previous studies, we consider the case that two rumors exist simultaneously. It is assumed that one is an entertainment rumor that fans care about, and the other is a common rumor. First, we derive the mean-field equations that describe the dynamics of this dual rumor propagation model and obtain the threshold parameter. Secondly, after finding the necessary and sufficient conditions for the existence of equilibriums, we examine the equilibrium’s local and global stability. Finally, simulations are used to explain how various parameters affect the process of spreading rumors.
Crossing Numbers of Join Product with Discrete Graphs: A Study on 6-Vertex Graphs
Authors: Fortes Jana , Staš Michal
Published: July 2023

Reducing the number of crossings on graph edges can be useful in various applications, including network visualization, circuit design, graph theory, cartography or social choice theory. This paper aims to determine the crossing number of the join product G*+Dn, where G* is a connected graph isomorphic to K2,2,2∖{e1,e2} obtained by removing two edges e1,e2 with a common vertex and a second vertex from the different partitions of the complete tripartite graph K2,2,2, and Dn is a discrete graph composed of n isolated vertices. The proofs utilize known exact crossing number values for join products of specific subgraphs Hk of G* with discrete graphs in combination with the separating cycles. Similar approaches can potentially estimate unknown crossing numbers of other six-vertex graphs with a larger number of edges in join products with discrete graphs, paths or cycles.
Contagion Patterns Classification in Stock Indices: A Functional Clustering Analysis Using Decision Trees
Authors: Razo-De-Anda Jorge Omar , Romero-Castro Luis Lorenzo , Venegas-Martínez Francisco
Published: July 2023

This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies. To do that, first, the B-spline method and Bezier curves are used to smooth observations by minimizing the noise. Subsequently, the Functional Principal Component Analysis (FPCA) methodology is applied. Then, the K-means clustering algorithm is used to determine the main groups using the silhouette method and cross-validation, considering the sum of squares of the distances as the function to minimize. Finally, classification trees and macroeconomic and financial analyses are used to determine the rules of variables that give a direct explanation of the contagion (clustering) between the stock indices. The main empirical results obtained suggest that the most significant macroeconomic variables are the Gross Domestic Product, the Consumer Price Index, and Foreign Direct Investment, while in the financial aspect and the most representative are Domestic Credit and number of companies listed on the stock market. It is worth noticing that government spending does not have a significant effect at any time as a determinant of contagion. Finally, it is important to mention, and surprising, that Mexico’s IPC was not clustered in the same group of US stock market indices anytime, despite the strong commercial relationship and the geographical closeness.
Model-Based Simultaneous Multi-Slice (SMS) Reconstruction with Hankel Subspace Learning for Accelerated MR T1 Mapping
Authors: Kim Sugil , Wu Hua , Han Jae-Ho
Published: July 2023

Herein, we propose a novel model-based simultaneous multi-slice (SMS) reconstruction method by exploiting data-driven parameter modeling for highly accelerated T1 parameter quantification. We assume that the predefined slice-specific null space operator remains invariant along the parameter dimension. We incorporate the parameter dimension into SMS-HSL to exploit Hankel-structured and Casorati matrices. Given this consideration, the SMS signal is reformulated in k-p space as a constrained optimization problem that exploits rank deficiency for the Hankel-structured matrix and a finite-dimensional basis for a subspace containing slowly evolving signals in the parameter direction. The proposed model-based SMS reconstruction method is validated on in vivo data and compared with state-of-the-art methods with slice acceleration factors of 3 and 5, including an in-plane acceleration factor of 2. The experimental results demonstrate that the proposed method performs effective slice unfolding and signal recovery in reconstructed images and T1 maps with high precision as compared to the state-of-the-art methods.
A Surface Family with a Mutual Geodesic Curve in Galilean 3-Space G3
Authors: Al-Jedani Awatif , Abdel-Baky Rashad A.
Published: July 2023

This article gives an approach for establishing a surface family with a mutual geodesic curve in Galilean 3-space G3. Given a smooth space curve, we derive the sufficient and necessary condition for the given curve to be geodesic on it. Furthermore, we resolve the conditions when the surface is a ruled surface. Consequently, its ability to develop with the mutual geodesic of the elements of the surface family is researched. Meanwhile, we explain this approach by submitting considerable examples.
A New Extension of CJ Metric Spaces—Partially Controlled J Metric Spaces
Authors: Subhi Aiadi Suhad , Mior Othman Wan Ainun , Wong Kok Bin , Mlaiki Nabil
Published: July 2023

This article introduces the concept of partially controlled J metric spaces; in particular, the J metric space with self-distance is not necessarily zero, which is important in computer science. We prove the existence of a unique fixed point for linear and nonlinear contractions, provide some examples to prove the existence of this metric space, and present some important applications in fractional differential equations, i.e., “Riemann–Liouville derivatives”.
Multi-View Learning-Based Fast Edge Embedding for Heterogeneous Graphs
Authors: Liu Canwei , Deng Xingye , He Tingqin , Chen Lei , Deng Guangyang , Hu Yuanyu
Published: July 2023

Edge embedding is a technique for constructing low-dimensional feature vectors of edges in heterogeneous graphs, which are also called heterogeneous information networks (HINs). However, edge embedding research is still in its early stages, and few well-developed models exist. Moreover, existing models often learn features on the edge graph, which is much larger than the original network, resulting in slower speed and inaccurate performance. To address these issues, a multi-view learning-based fast edge embedding model is developed for HINs in this paper, called MVFEE. Based on the “divide and conquer” strategy, our model divides the global feature learning into multiple separate local intra-view features learning and inter-view features learning processes. More specifically, each vertex type in the edge graph (each edge type in HIN) is first treated as a view, and a private skip-gram model is used to rapidly learn the intra-view features. Then, a cross-view learning strategy is designed to further learn the inter-view features between two views. Finally, a multi-head attention mechanism is used to aggregate these local features to generate accurate global features of each edge. Extensive experiments on four datasets and three network analysis tasks show the advantages of our model.
Literature Review on Integrating Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) and Deep Neural Networks in Machine Learning for Climate Forecasting
Authors: Munandar Devi , Ruchjana Budi Nurani , Abdullah Atje Setiawan , Pardede Hilman Ferdinandus
Published: July 2023

The issue of climate change holds immense significance, affecting various aspects of life, including the environment, the interaction between soil conditions and the atmosphere, and agriculture. Over the past few decades, a range of spatio-temporal and Deep Neural Network (DNN) techniques had been proposed within the field of Machine Learning (ML) for climate forecasting, using spatial and temporal data. The forecasting model in this paper is highly complex, particularly due to the presence of nonlinear data in the residual modeling of General Space-Time Autoregressive Integrated Moving Average (GSTARIMA), which represented nonstationary data with time and location dependencies. This model effectively captured trends and seasonal data with time and location dependencies. On the other hand, DNNs proved reliable for modeling nonlinear data that posed challenges for spatio-temporal approaches. This research presented a comprehensive overview of the integrated approach between the GSTARIMA model and DNNs, following the six-stage Data Analytics Lifecycle methodology. The focus was primarily on previous works conducted between 2013 and 2022. The review showed that the GSTARIMA–DNN integration model was a promising tool for forecasting climate in a specific region in the future. Although spatio-temporal and DNN approaches have been widely employed for predicting the climate and its impact on human life due to their computational efficiency and ability to handle complex problems, the proposed method is expected to be universally accepted for integrating these models, which encompass location and time dependencies. Furthermore, it was found that the GSTARIMA–DNN method, incorporating multivariate variables, locations, and multiple hidden layers, was suitable for short-term climate forecasting. Finally, this paper presented several future directions and recommendations for further research.
Invertibility and Fredholm Property of Fock Toeplitz Operators
Authors: Xu Chunxu , Yu Tao
Published: July 2023

We characterize some necessary and sufficient conditions of invertible Toeplitz operators acting on the Fock space. In particular, we study the Fredholm properties of Toeplitz operators with BMO1 symbols, where their Berezin transforms are bounded functions of vanishing oscillation. We show the Fredholm index of the Toeplitz operator via the winding of its Berezin transform along a sufficiently large circle and provide a characterization of invertible Toeplitz operators with non-negative symbols, possibly unbounded, such that the Berezin transforms of the symbols are bounded and of vanishing oscillation.
Adaptive End-Effector Buffeting Sliding Mode Control for Heavy-Duty Robots with Long Arms
Authors: Wu Wenqiang , Qin Guangxiang , Xiao Zhongmin , Wu Weicong , Chen Chaozheng , Yu Mingfeng , Ren Zhiye , Zhang Tie , Long Gaofeng
Published: July 2023

This study aims to resolve the problems of low precision, poor flexibility and unstable operation in the control performance of loading robots with long telescopic booms and heavy loads. Firstly, the kinematics and dynamics of long-arm heavy-duty robots are analyzed, and the dynamics model of a long-arm heavy-duty robot is established using the Lagrange method. A new power-hybrid sliding-mode approach law is proposed, and a hybrid force/position control strategy is used to control long-arm heavy-duty robots. The position control of long-arm heavy-duty robots uses a new sliding-mode adaptive control to improve the position accuracy of important joints, and PD control is used to force control the other joints. The two-stage telescopic arm is flexible and the long-arm heavy-load robot is simulated. The simulation results show that the long-arm heavy-load robot obtained using the improved sliding-mode adaptive control algorithm has good track-tracking and jitter-suppression effects. The new power-hybrid sliding-mode controller designed in this paper reduces the jitter amplitude of the end-effector of long-arm heavy-duty robots by 28.75%, 10.92% and 16.22%, respectively, compared with the existing new approach law sliding-mode controller. The simulation results show that the proposed power-hybrid reaching law sliding-mode controller can effectively reduce the amplitude difference of the end-effector. Finally, the force/position control strategy is combined with force-based impedance control, and the design process of impedance controller parameters is introduced, which provides a reference for the trajectory-tracking and vibration-suppression of end-effectors of long-arm heavy-duty robots.
Protective Effect of Fucoxanthin on Zearalenone-Induced Hepatic Damage through Nrf2 Mediated by PI3K/AKT Signaling
Authors: Ben Ammar Rebai , Zahra Hamad Abu , Abu Zahra Abdulmalek Mohammad , Alfwuaires Manal , Abdulaziz Alamer Sarah , Metwally Ashraf M. , Althnaian Thnaian A. , Al-Ramadan Saeed Y.
Published: July 2023

Hepatotoxic contaminants such as zearalenone (ZEA) are widely present in foods. Marine algae have a wide range of potential applications in pharmaceuticals, cosmetics, and food products. Research is ongoing to develop treatments and products based on the compounds found in algae. Fucoxanthin (FXN) is a brown-algae-derived dietary compound that is reported to prevent hepatotoxicity caused by ZEA. This compound has multiple biological functions, including anti-diabetic, anti-obesity, anti-microbial, and anti-cancer properties. Furthermore, FXN is a powerful antioxidant. In this study, we examined the effects of FXN on ZEA-induced stress and inflammation in HepG2 cells. MTT assays, ROS generation assays, Western blots, and apoptosis analysis were used to evaluate the effects of FXN on ZEA-induced HepG2 cell inflammation. Pre-incubation with FXN reduced the cytotoxicity of ZEA toward HepG2 cells. FXN inhibited the ZEA-induced production of pro-inflammatory cytokines, including IL-1 β, IL-6, and TNF-α. Moreover, FXN increased HO-1 expression in HepG2 by activating the PI3K/AKT/NRF2 signaling pathway. In conclusion, FXN inhibits ZEA-induced inflammation and oxidative stress in hepatocytes by targeting Nrf2 via activating PI3K/AKT signaling.
Investigation of Microstructure and Mechanical Properties of Layered Material Produced by Adding Al2O3 to 316L Stainless Steel
Authors: Albahlol Osama Albahl Alshtewe , Elkilani Rajab , Çuğ Harun , Erden Mehmet Akif , Özmen Ramazan , Esen Ismail
Published: July 2023

This study developed new advanced composite materials consisting of functional grading of 316L and Al2O3 specially designed for potential biomedical applications. Mechanical properties were characterized by tensile testing, and microstructural properties by optical microscope, scanning electron microscope (SEM), and Energy Dispersive X-Ray (EDX) analyses. The uniform mixture in the material, up to 40% by weight of Al2O3, is uniformly distributed in the 316L matrix that shows disintegration. Then, samples with 2, 3, 4, and 5 layers were produced in functionally graded 6, 7, 8, and 9 material types, respectively. The layer thicknesses were formed with an average of 900 µm. The results show that new composite materials can be produced functionally using 316L and Al2O3 in a layered manner. As a result of the mechanical experiments, it has been observed that the tensile strength of the layered composite structures remains within the range of 91–191 MPa, depending on the layer type. It has been observed that the elongation varies between 3.16 and 12.46%. According to these results, the materials obtained are considered suitable for use as an alternative prosthetic material in biomedical applications. The tensile strength, % elongation of the Composition 7, and yield strength of functionally graded (316 + (316L-10 Al2O3) + (316L-20 Al2O3) + (316L-30 Al2O3)) material are 123 megapascals (MPa), 7.3%, and 111MPa, respectively, and according to the literature, the mechanical strength of human bone is very close to this composition properties.
Near-Infrared Spectroscopy: A Free-Living Neuroscience Tool to Better Understand Diabetes and Obesity
Authors: Rebelos Eleni , Malloggi Eleonora , Parenti Martina , Dardano Angela , Tura Andrea , Daniele Giuseppe
Published: July 2023

The human brain is the least accessible of all organs and attempts to study it in vivo rely predominantly on neuroimaging. Functional near-infrared spectroscopy (fNIRS) allows for the study of cortical neural activity in a non-invasive manner that may resemble free-living conditions. Moreover, compared to other neuroimaging tools, fNIRS is less expensive, it does not require the use of ionizing radiation, and can be applied to all study populations (patients suffering from claustrophobia, or neonates). In this narrative review, we provide an overview of the available research performed using fNIRS in patients with diabetes and obesity. The few studies conducted to date have presented controversial results regarding patients with diabetes, some reporting a greater hemodynamic response and others reporting a reduced hemodynamic response compared to the controls, with an unclear distinction between types 1 and 2. Subjects with obesity or a binge eating disorder have reduced prefrontal activation in response to inhibitory food or non-food stimuli; however, following an intervention, such as cognitive treatment, prefrontal activation is restored. Moreover, we discuss the potential of future applications of fNIRS for a better understanding of cortical neural activity in the context of metabolic disorders.
Metabolite Changes of Perna canaliculus Following a Laboratory Marine Heatwave Exposure: Insights from Metabolomic Analyses
Authors: Azizan Awanis , Venter Leonie , Jansen van Rensburg Peet J. , Ericson Jessica A. , Ragg Norman L. C. , Alfaro Andrea C.
Published: July 2023

Temperature is considered to be a major abiotic factor influencing aquatic life. Marine heatwaves are emerging as threats to sustainable shellfish aquaculture, affecting the farming of New Zealand’s green-lipped mussel [Perna canaliculus (Gmelin, 1791)]. In this study, P. canaliculus were gradually exposed to high-temperature stress, mimicking a five-day marine heatwave event, to better understand the effects of heat stress on the metabolome of mussels. Following liquid chromatography-tandem mass spectrometry analyses of haemolymph samples, key sugar-based metabolites supported energy production via the glycolysis pathway and TCA cycle by 24 h and 48 h of heat stress. Anaerobic metabolism also fulfilled the role of energy production. Antioxidant molecules acted within thermally stressed mussels to mitigate oxidative stress. Purine metabolism supported tissue protection and energy replenishment. Pyrimidine metabolism supported the protection of nucleic acids and protein synthesis. Amino acids ensured balanced intracellular osmolality at 24 h and ammonia detoxification at 48 h. Altogether, this work provides evidence that P. canaliculus has the potential to adapt to heat stress up to 24 °C by regulating its energy metabolism, balancing nucleotide production, and implementing oxidative stress mechanisms over time. The data reported herein can also be used to evaluate the risks of heatwaves and improve mitigation strategies for aquaculture.
Antioxidant and Anticancer Assessment and Phytochemical Investigation of Three Varieties of Date Fruits
Authors: Abdelbaky Ahmed S. , Tammam Mohamed A. , Ali Mohamed Yassin , Sharaky Marwa , Selim Khaled , Semida Wael M. , Abd El-Mageed Taia A. , Ramadan Mohamed Fawzy , Oraby Hesham F. , Diab Yasser M.
Published: July 2023

Date palm (Phoenix dactylifera L.) fruits contain high concentrations of phenolic compounds, particularly flavonoids and other micronutrients, which impact human health due to their potent antioxidant, anti-inflammatory, and anticancer characteristics. In the present study, the effect of ethyl acetate, hydroethanol, hydromethanol, and aqueous extract from three date palm varieties (i.e., Ajwa, Siwi, and Sukkari) on phytochemical profiles and antioxidant and anticancer activities was investigated. Fruit extracts were screened for their antioxidant activity using the DPPH· method. Phenolic constituents were quantified and identified using HPLC-DAD. Extracts (ethyl acetate, hydroethanol, and hydromethanol) were assessed for cytotoxicity on nine human cancer cell lines, i.e., MG-63, HCT116, MCF7, MDA-MB-231, HEPG2, HUH7, A549, H460, and HFB4, using the sulphorhodamine-B (SRB) assay. Results showed that the ethyl acetate extract of the Sukkari fruits has the greatest antioxidant potential with an IC50 value of 132.4 ± 0.3 μg·mL−1, while the aqueous extract of Ajwa date fruits exhibited the lowest antioxidant effect with an IC50 value of 867.1 ± 0.3 μg·mL−1. The extracts exhibited potent to moderate anticancer activities against the investigated cancer cell line in a source-dependent manner. Methanol extract of Siwi fruits exhibited the most potent anticancer activity (IC50 = 99 ± 1.6 µg·mL−1), followed by the same extract of Sukkari fruits with an IC50 value of 119 ± 3.5 µg·mL−1 against the cell line of human breast cancer (MDA-MB-231). Additionally, principal component analysis (PCA) was investigated to determine the relationship among the investigated traits and treatments. Our findings reveal that date palm fruit-derived extracts are excellent sources of biologically active constituents and substantiate their potential use in new anticancer strategies from natural resources.
Memristor Crossbar Circuits Implementing Equilibrium Propagation for On-Device Learning
Authors: Oh Seokjin , An Jiyong , Cho Seungmyeong , Yoon Rina , Min Kyeong-Sik
Published: July 2023

Equilibrium propagation (EP) has been proposed recently as a new neural network training algorithm based on a local learning concept, where only local information is used to calculate the weight update of the neural network. Despite the advantages of local learning, numerical iteration for solving the EP dynamic equations makes the EP algorithm less practical for realizing edge intelligence hardware. Some analog circuits have been suggested to solve the EP dynamic equations physically, not numerically, using the original EP algorithm. However, there are still a few problems in terms of circuit implementation: for example, the need for storing the free-phase solution and the lack of essential peripheral circuits for calculating and updating synaptic weights. Therefore, in this paper, a new analog circuit technique is proposed to realize the EP algorithm in practical and implementable hardware. This work has two major contributions in achieving this objective. First, the free-phase and nudge-phase solutions are calculated by the proposed analog circuits simultaneously, not at different times. With this process, analog voltage memories or digital memories with converting circuits between digital and analog domains for storing the free-phase solution temporarily can be eliminated in the proposed EP circuit. Second, a simple EP learning rule relying on a fixed amount of conductance change per programming pulse is newly proposed and implemented in peripheral circuits. The modified EP learning rule can make the weight update circuit practical and implementable without requiring the use of a complicated program verification scheme. The proposed memristor conductance update circuit is simulated and verified for training synaptic weights on memristor crossbars. The simulation results showed that the proposed EP circuit could be used for realizing on-device learning in edge intelligence hardware.
Fabrication of Circular Cross-Section Microchannels with 3-D Lattice Arrangement and Their Use as On-Off Valves
Authors: Uehara Kaori , Hori Yutaka , Ishigure Takaaki
Published: July 2023

In this paper, circular cross-section microchannels with 3-D lattice arrangements are designed and fabricated using the Mosquito method in order to construct on-off valves. The 3-D microchannels with on-off valves consist of two types of lines: the flow lines for chemical liquid flow and the control lines to activate the valves. We confirmed that both a circular cross-section and a PDMS with low elastic modulus used as the microchannel material contribute to a valve that can be closed with a lower pressure. Then, we demonstrated liquid flow to evaluate the functionality of the valve. Fluorescein solution was flown into a flow line. We found that the fluorescence intensity decreases at the intersection between the flow and control lines when the flow line is closed by the inflation of the control line, experimentally confirming the functionality of the valve microchannels fabricated via the Mosquito method.
Perspectives on the Probiotic Potential of Indigenous Moulds and Yeasts in Dry-Fermented Sausages
Authors: Álvarez Micaela , Andrade María J. , Cebrián Eva , Roncero Elia , Delgado Josué
Published: July 2023

The role of indigenous fungi in the appropriate development of sensory properties and the safety of dry-fermented sausages has been widely established. Nonetheless, their applications as probiotic agents have not been elucidated in such products yet, despite their promising functional features. Thus, it should be interesting to evaluate the probiotic potential of native Debaryomyces hansenii isolates from dry-fermented sausages and their application in the meat industry, because it is the most frequently isolated yeast species from these foodstuffs and its probiotic effects for animals as well as its possible probiotic activity for human beings have been demonstrated. Within the functional ability of foodborne yeasts, anti-inflammatory, antioxidant, antimicrobial, antigenotoxic, and immunomodulatory properties have been reported. Similarly, the use of dry-fermented sausages as vehicles for probiotic moulds remains a challenge because the survival and development of moulds in the gastrointestinal tract are still unknown. Nevertheless, some moulds have been isolated from faeces possibly from their spores as a form of resistance. Additionally, their beneficial effects on animals and humans, such as the decrease in lipid content and the anti-inflammatory activity, have been reported, although they seem to be more related to their postbiotic capacity due to the generated bioactive compounds with profunctional attributes than to their role as probiotics. Therefore, further studies providing knowledge useful for generating dry-fermented sausages with improved functionality are fully necessary.
Conversion of Similar Xenochemicals to Dissimilar Products: Exploiting Competing Reactions in Whole-Cell Catalysis
Authors: Sannelli Francesca , Sindahl Nikoline Corell , Warthegau Stefan S. , Jensen Pernille Rose , Meier Sebastian
Published: July 2023

Many enzymes have latent activities that can be used in the conversion of non-natural reactants for novel organic conversions. A classic example is the conversion of benzaldehyde to a phenylacetyl carbinol, a precursor for ephedrine manufacture. It is often tacitly assumed that purified enzymes are more promising catalysts than whole cells, despite the lower cost and easier maintenance of the latter. Competing substrates inside the cell have been known to elicit currently hard-to-predict selectivities that are not easily measured inside the living cell. We employ NMR spectroscopic assays to rationally combine isomers for selective reactions in commercial S. cerevisiae. This approach uses internal competition between alternative pathways of aldehyde clearance in yeast, leading to altered selectivities compared to catalysis with the purified enzyme. In this manner, 4-fluorobenzyl alcohol and 2-fluorophenylacetyl carbinol can be formed with selectivities in the order of 90%. Modification of the cellular redox state can be used to tune product composition further. Hyperpolarized NMR shows that the cellular reaction and pathway usage are affected by the xenochemical. Overall, we find that the rational construction of ternary or more complex substrate mixtures can be used for in-cell NMR spectroscopy to optimize the upgrading of similar xenochemicals to dissimilar products with cheap whole-cell catalysts.
Preparation and Performance of Regenerated Al2O3-Coated Cathode Material LiNi0.8Co0.15Al0.05O2 from Spent Power Lithium-Ion Batteries
Authors: Ma Liwen , Liu Guangyun , Wang Yuehua , Xi Xiaoli
Published: July 2023

In this study, LiNi0.8Co0.15Al0.05O2@x%Al2O3-coated cathode materials were regeneratively compounded by the solid-phase sintering method, and their structural characterization and electrochemical performance were systematically analyzed. The regenerated ternary cathode material precursor synthesized by the co-precipitation method was roasted with lithium carbonate at a molar ratio of 1:1.1, and then completely mixed with different contents of aluminum hydroxide. The combined materials were then sintered at 800 °C for 15 h to obtain the regenerated coated cathode material, LiNi0.8Co0.15Al0.05O2@x%Al2O3. The thermogravimetry analysis, phase composition, morphological characteristics, and other tests show that when the added content of aluminum hydroxide is 3%, the regenerated cathode material, LiNi0.8Co0.15Al0.05O2@1.5%Al2O3, exhibits the highest-order layered structure with Al2O3 coating. This material can better inhibit the production of Ni2+, and improve material structure and electrochemical properties. The first charge–discharge efficiency of the battery assembled with this regenerated cathode material is 97.4%, a 50-cycle capacity retention is 93.4%, and a 100-cycle capacity retention is 87.6%. The first charge–discharge efficiency is far better than that of the uncoated regenerated battery.
Palladium and Platinum Complexes of the Antimetabolite Fludarabine with Vastly Enhanced Selectivity for Tumour over Non-Malignant Cells
Authors: Schleser Sebastian W. , Krytovych Oleksandr , Ziegelmeier Tim , Groß Elisabeth , Kasparkova Jana , Brabec Viktor , Weber Thomas , Schobert Rainer , Mueller Thomas
Published: July 2023

The purine derivative fludarabine is part of frontline therapy for chronic lymphocytic leukaemia (CLL). It has shown positive effects on solid tumours such as melanoma, breast, and colon carcinoma in clinical phase I studies. As the treatment of CLL cells with combinations of fludarabine and metal complexes of antitumoural natural products, e.g., illudin M ferrocene, has led to synergistically enhanced apoptosis, in this research study different complexes of fludarabine itself. Four complexes bearing a trans-[Br(PPh3)2]Pt/Pd fragment attached to atom C-8 via formal η1-sigma or η2-carbene bonds were synthesised in two or three steps without protecting polar groups on the arabinose or adenine. The platinum complexes were more cytotoxic than their palladium analogues, with low single-digit micromolar IC50 values against cells of various solid tumour entities, including cisplatin-resistant ones and certain B-cell lymphoma and CLL, presumably due to the ten-fold higher cellular uptake of the platinum complexes. However, the palladium complexes interacted more readily with isolated Calf thymus DNA. Interestingly, the platinum complexes showed vastly greater selectivity for cancer over non-malignant cells when compared with fludarabine.
Using Open-Source Automatic Speech Recognition Tools for the Annotation of Dutch Infant-Directed Speech
Authors: van der Klis Anika , Adriaans Frans , Han Mengru , Kager René
Published: July 2023

There is a large interest in the annotation of speech addressed to infants. Infant-directed speech (IDS) has acoustic properties that might pose a challenge to automatic speech recognition (ASR) tools developed for adult-directed speech (ADS). While ASR tools could potentially speed up the annotation process, their effectiveness on this speech register is currently unknown. In this study, we assessed to what extent open-source ASR tools can successfully transcribe IDS. We used speech data from 21 Dutch mothers reading picture books containing target words to their 18- and 24-month-old children (IDS) and the experimenter (ADS). In Experiment 1, we examined how the ASR tool Kaldi-NL performs at annotating target words in IDS vs. ADS. We found that Kaldi-NL only found 55.8% of target words in IDS, while it annotated 66.8% correctly in ADS. In Experiment 2, we aimed to assess the difficulties in annotating IDS more broadly by transcribing all IDS utterances manually and comparing the word error rates (WERs) of two different ASR systems: Kaldi-NL and WhisperX. We found that WhisperX performs significantly better than Kaldi-NL. While there is much room for improvement, the results show that automatic transcriptions provide a promising starting point for researchers who have to transcribe a large amount of speech directed at infants.