bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydrothermal Synthesis of Nanocrystalline ZrO2-8Y2O3-xLn2O3 Powders (Ln = La, Gd, Nd, Sm): Crystalline Structure, Thermal and Dielectric Properties
Authors: Piticescu Radu-Robert , Slobozeanu Anca Elena , Valsan Sorina Nicoleta , Ciobota Cristina Florentina , Ghita Andreea-Nicoleta , Motoc Adrian Mihail , Chiriac Stefania , Prakasam Mythili
Published: December 2021

Zirconium dioxide (ZrO2) is one of the ceramic materials with high potential in many areas of modern technologies. ZrO2 doped with 8 wt.% (~4.5 mol%) Y2O3 is a commercial powder used for obtaining stabilized zirconia materials (8 wt.% YSZ) with high temperature resistance and good ionic conductivity. During recent years it was reported the co-doping with multiple rare earth elements has a significant influence on the thermal, mechanical and ionic conductivity of zirconia, due complex grain size segregation and enhanced oxygen vacancies mobility. Different methods have been proposed to synthesize these materials. Here, we present the hydrothermal synthesis of 8 wt.% (~4.5 mol%) YSZ co-doped with 4, 6 and 8 wt.% La2O3, Nd2O3, Sm2O3 and Gd2O3 respectively. The crystalline phases formed during their thermal treatment in a large temperature range were analyzed by X-ray diffraction. The evolution of phase composition vs. thermal treatment temperatures shows as a major trend the formation at temperatures >1000 °C of a cubic solid solutions enriched in the rare earth oxide used for co-doping as major phase. The first results on the thermal conductivities and impedance measurements on sintered pellets obtained from powders co-doped with 8 wt.% Y and 6% Ln (Ln = La, Nd, Sm and Gd) and the corresponding activation energies are presented and discussed. The lowest thermal conductivity was obtained for La co-doped 8 wt.% YSZ while the lowest activation energy for ionic conduction for Gd co-doped 8 wt.% YSZ materials.
Study of the Mechanical, Sound Absorption and Thermal Properties of Cellular Rubber Composites Filled with a Silica Nanofiller
Authors: Pöschl Marek , Vašina Martin
Published: December 2021

This paper deals with the study of cellular rubbers, which were filled with silica nanofiller in order to optimize the rubber properties for given purposes. The rubber composites were produced with different concentrations of silica nanofiller at the same blowing agent concentration. The mechanical, sound absorption and thermal properties of the investigated rubber composites were evaluated. It was found that the concentration of silica filler had a significant effect on the above-mentioned properties. It was detected that a higher concentration of silica nanofiller generally led to an increase in mechanical stiffness and thermal conductivity. Conversely, sound absorption and thermal degradation of the investigated rubber composites decreased with an increase in the filler concentration. It can be also concluded that the rubber composites containing higher concentrations of silica filler showed a higher stiffness to weight ratio, which is one of the great advantages of these materials. Based on the experimental data, it was possible to find a correlation between mechanical stiffness of the tested rubber specimens evaluated using conventional and vibroacoustic measurement techniques. In addition, this paper presents a new methodology to optimize the blowing and vulcanization processes of rubber samples during their production.
Structural and Electrical Characterization of Pure and Al-Doped ZnO Nanorods
Authors: Panžić Ivana , Capan Ivana , Brodar Tomislav , Bafti Arijeta , Mandić Vilko
Published: December 2021

Pure and Al-doped (3 at.%) ZnO nanorods were prepared by two-step synthesis. In the first step, ZnO thin films were deposited on silicon wafers by spin coating; then, ZnO nanorods (NR) and Al-doped ZnO NR were grown using a chemical bath method. The structural properties of zincite nanorods were determined by X-ray diffraction (XRD) and corroborated well with the morphologic properties obtained by field-emission gun scanning electron microscopy (FEG SEM) with energy-dispersive X-ray spectroscopy (EDS). Morphology results revealed a minute change in the nanorod geometry upon doping, which was also visible by Kelvin probe force microscopy (KPFM). KPFM also showed preliminary electrical properties. Detailed electrical characterization of pure and Al-doped ZnO NR was conducted by temperature-dependent current–voltage (I–V) measurements on Au/(Al)ZnO NR/n-Si junctions. It was shown that Al doping increases the conductivity of ZnO NR by an order of magnitude. The I–V characteristics of pure and Al-doped ZnO NR followed the ohmic regime for lower voltages, whereas, for the higher voltages, significant changes in electric conduction mechanisms were detected and ascribed to Al-doping. In conclusion, for future applications, one should consider the possible influence of the geometry change of (Al)ZnO NRs on their overall electric transport properties.
Effect of Carbon Black and Hybrid Steel-Polypropylene Fiber on the Mechanical and Self-Sensing Characteristics of Concrete Considering Different Coarse Aggregates’ Sizes
Authors: Ahmed Shakeel , Hussain Abasal , Hussain Zahoor , Pu Zhang , Ostrowski Krzysztof Adam , Walczak Rafał
Published: December 2021

The effect of combining filler (carbon black) and fibrous materials (steel fiber and polypropylene fiber) with various sizes of coarse particles on the post-cracking behavior of conductive concrete was investigated in this study. Steel fibers (SF) and carbon black (CB) were added as monophasic, diphasic, and triphasic materials in the concrete to enhance the conductive properties of reinforced concrete. Polypropylene fiber (PP) was also added to steel fiber and carbon to improve the post-cracking behavior of concrete beams. This research mainly focused on the effects of macro fibers on toughness parameters and energy absorption capacity, as well as enhancing the self-sensing of multiple cracks and post-cracking behavior. Fractional changes in resistance and crack opening displacement (COD-FCR) and the relationship of load-deflection-FCR with different coarse aggregates of (5–10 mm and 15–20 mm) sizes were investigated, and the law of resistance signal changes with single and multiple cracking through load-time-FCR curves was explored. Results indicated that the smaller size coarse aggregates (5–10 mm) showed higher compressive strength: up to 8.3% and 14.83% with diphasic (SF + CB), respectively. The flexural strength of PC-10 increased 22.60 and 51.2%, respectively, with and without fibers, compared to PC-20. The diphasic and triphasic conductive material with the smaller size of aggregates (5–10 mm) increased the FCR values up to 38.95% and 42.21%, respectively, as compared to those of greater size coarse aggregates (15–20 mm). The hybrid uses of fibrous and filler materials improved post-cracking behavior as well as the self-sensing ability of reinforced concrete.
Modeling, System Measurements and Controller Investigation of a Small Battery-Powered Fixed-Wing UAV
Authors: Wang Yue , Zhu Hang , Zhao Zeyang , Zhang Cui , Lan Yubin
Published: December 2021

In this paper, a complete set of nonlinear modeling and controller design process for a small electric fixed-wing unmanned aerial vehicle (UAV) is presented. The nonlinear mathematical model and aerodynamic model of the small fixed-wing UAV are derived. The computational fluid dynamics (CFD) method was used to obtain the aerodynamic coefficients of the UAV, and the models of propulsion system components were established through experiments. Since the linearized and decoupled model of the fixed-wing UAV has a large error, a nonlinear model is established based on Simulink, which is utilized to design and verify the control algorithms. Based on the established nonlinear model, a stability controller, path following controller and path management controller of the aircraft are set up. The results indicate that system parameters of the aircraft can be quickly acquired and an efficient and practical model can be established by the methods. In addition, the controller designed and applied in this paper has good performance and small steady-state error, which can meet the basic flight mission requirements, including stability of flight attitude, path following and switching of different waypoints. These modeling and control methods can also be employed in other small battery-powered fixed-wing UAV projects.
Electrochemical, Electrocatalytic, and Magnetic Properties of Vanadium-Containing Polyoxometalates
Authors: Manga Joseph Dika , Teillout Anne-Lucie , Rivière Eric , de Oliveira Pedro , Mbomekallé Israël Martyr
Published: December 2021

Mono-substituted vanadium-containing Dawson-type polyoxometalates having the general formula α1-[VIVW17X2O62]8− and α2-[VIVW17X2O62]8−, with X = As or P, were synthesised and subject to a comprehensive electrochemical study comprising the pH dependency. These POMs exhibit an electrocatalytic behaviour towards the oxidation of thiols (namely cysteine), rendering them interesting species for mimicking oxidative stress situations, at physiological pH values. The efficiency of the electro-oxidation was assessed with thiols of different nature, and the substrate that responded best was used to compare the electrocatalytic capabilities of the POM series. The magnetic behaviour of these POMs was also evaluated and compared to their analogues, α1- and α2-[VVW17X2O62]7− (X = As or P), at low temperatures and showed, as expected, a paramagnetic behaviour of VIV based compounds.
An Unsupervised Machine Learning-Based Framework for Transferring Local Factories into Supply Chain Networks
Authors: Mad Ali Mohd Fahmi Bin , Ariffin Mohd Khairol Anuar Bin Mohd , Mustapha Faizal Bin , Supeni Eris Elianddy Bin
Published: December 2021

Transferring a local manufacturing company to a national-wide supply chain network with wholesalers and retailers is a significant problem in manufacturing systems. In this research, a hybrid PCA-K-means is used to transfer a local chocolate manufacturing firm near Kuala Lumpur into a national-wide supply chain. For this purpose, the appropriate locations of the wholesaler’s center points were found according to the geographical and population features of the markets in Malaysia. To this end, four wholesalers on the left island of Malaysia are recognized, which were located in the north area, right area, middle area, and south area. Similarly, two wholesalers were identified on the right island, which were in Sarawak and WP Labuan. In order to evaluate the performance of the proposed method, its outcomes are compared with other unsupervised-learning methods such as the WARD and CLINK methods. The outcomes indicated that K-means could successfully determine the best locations for the wholesalers in the supply chain network with a higher score (0.812).
Automatic Path Planning Offloading Mechanism in Edge-Enabled Environments
Authors: Herich Dušan , Vaščák Ján , Zolotová Iveta , Brecko Alexander
Published: December 2021

The utilization of edge-enabled cloud computing in unmanned aerial vehicles has facilitated advances in autonomous control by employing computationally intensive algorithms frequently related to traversal among different locations in an environment. A significant problem remains in designing an effective strategy to offload tasks from the edge to the cloud. This work focuses on creating such a strategy by employing a network evaluation method built on the mean opinion score metrics in concoction with machine learning algorithms for path length prediction to assess computational complexity and classification models to perform an offloading decision on the data provided by both network metrics and solution depth prediction. The proposed system is applied to the A* path planning algorithm, and the presented results demonstrate up to 94% accuracy in offloading decisions.
Artificial Intelligence for Stability Control of Actuated In–Wheel Electric Vehicles with CarSim® Validation
Authors: Cespi Riccardo , Galluzzi Renato , Ramirez-Mendoza Ricardo A. , Di Gennaro Stefano
Published: December 2021

This paper presents an active controller for electric vehicles in which active front steering and torque vectoring are control actions combined to improve the vehicle driving safety. The electric powertrain consists of four independent in–wheel electric motors situated on each corner. The control approach relies on an inverse optimal controller based on a neural network identifier of the vehicle plant. Moreover, to minimize the number of sensors needed for control purposes, the authors present a discrete–time reduced–order state observer for the estimation of vehicle lateral and roll dynamics. The use of a neural network identifier presents some interesting advantages. Notably, unlike standard strategies, the proposed approach avoids the use of tire lateral forces or Pacejka’s tire parameters. In fact, the neural identification provides an input–affine model in which these quantities are absorbed by neural synaptic weights adapted online by an extended Kalman filter. From a practical standpoint, this eliminates the need of additional sensors, model tuning, or estimation stages. In addition, the yaw angle command given by the controller is converted into electric motor torques in order to ensure safe driving conditions. The mathematical models used to describe the electric machines are able to reproduce the dynamic behavior of Elaphe M700 in–wheel electric motors. Finally, quality and performances of the proposed control strategy are discussed in simulation, using a CarSim® full vehicle model running through a double–lane change maneuver.
Investigation of the Stochastic Modeling of COVID-19 with Environmental Noise from the Analytical and Numerical Point of View
Authors: Hussain Shah , Madi Elissa Nadia , Khan Hasib , Etemad Sina , Rezapour Shahram , Sitthiwirattham Thanin , Patanarapeelert Nichaphat
Published: December 2021

In this article, we propose a novel mathematical model for the spread of COVID-19 involving environmental white noise. The new stochastic model was studied for the existence and persistence of the disease, as well as the extinction of the disease. We noticed that the existence and extinction of the disease are dependent on R0 (the reproduction number). Then, a numerical scheme was developed for the computational analysis of the model; with the existing values of the parameters in the literature, we obtained the related simulations, which gave us more realistic numerical data for the future prediction. The mentioned stochastic model was analyzed for different values of σ1,σ2 and β1,β2, and both the stochastic and the deterministic models were compared for the future prediction of the spread of COVID-19.
Enterprise Compensation System Statistical Modeling for Decision Support System Development
Authors: Mitsel Artur , Shilnikov Aleksandr , Senchenko Pavel , Sidorov Anatoly
Published: December 2021

This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management.
Mixture of Species Sampling Models
Authors: Bassetti Federico , Ladelli Lucia
Published: December 2021

We introduce mixtures of species sampling sequences (mSSS) and discuss how these sequences are related to various types of Bayesian models. As a particular case, we recover species sampling sequences with general (not necessarily diffuse) base measures. These models include some “spike-and-slab” non-parametric priors recently introduced to provide sparsity. Furthermore, we show how mSSS arise while considering hierarchical species sampling random probabilities (e.g., the hierarchical Dirichlet process). Extending previous results, we prove that mSSS are obtained by assigning the values of an exchangeable sequence to the classes of a latent exchangeable random partition. Using this representation, we give an explicit expression of the Exchangeable Partition Probability Function of the partition generated by an mSSS. Some special cases are discussed in detail—in particular, species sampling sequences with general base measures and a mixture of species sampling sequences with Gibbs-type latent partition. Finally, we give explicit expressions of the predictive distributions of an mSSS.
Determination of Bounds for the Jensen Gap and Its Applications
Authors: Ullah Hidayat , Adil Khan Muhammad , Saeed Tareq
Published: December 2021

The Jensen inequality has been reported as one of the most consequential inequalities that has a lot of applications in diverse fields of science. For this reason, the Jensen inequality has become one of the most discussed developmental inequalities in the current literature on mathematical inequalities. The main intention of this article is to find some novel bounds for the Jensen difference while using some classes of twice differentiable convex functions. We obtain the proposed bounds by utilizing the power mean and Höilder inequalities, the notion of convexity and the prominent Jensen inequality for concave function. We deduce several inequalities for power and quasi-arithmetic means as a consequence of main results. Furthermore, we also establish different improvements for Hölder inequality with the help of obtained results. Moreover, we present some applications of the main results in information theory.
Stability Analysis of Parameter Varying Genetic Toggle Switches Using Koopman Operators
Authors: Harrison Jamiree , Yeung Enoch
Published: December 2021

The genetic toggle switch is a well known model in synthetic biology that represents the dynamic interactions between two genes that repress each other. The mathematical models for the genetic toggle switch that currently exist have been useful in describing circuit dynamics in rapidly dividing cells, assuming fixed or time-invariant kinetic rates. There is a growing interest in being able to model and extend synthetic biological function for growth conditions such as stationary phase or during nutrient starvation. As cells transition from one growth phase to another, kinetic rates become time-varying parameters. In this paper, we propose a novel class of parameter varying nonlinear models that can be used to describe the dynamics of genetic circuits, including the toggle switch, as they transition from different phases of growth. We show that there exists unique solutions for this class of systems, as well as for a class of systems that incorporates the microbial phenomena of quorum sensing. Further, we show that the domain of these systems, which is the positive orthant, is positively invariant. We also showcase a theoretical control strategy for these systems that would grant asymptotic monostability of a desired fixed point. We then take the general form of these systems and analyze their stability properties through the framework of time-varying Koopman operator theory. A necessary condition for asymptotic stability is also provided as well as a sufficient condition for instability. A Koopman control strategy for the system is also proposed, as well as an analogous discrete time-varying Koopman framework for applications with regularly sampled measurements.
Study of Dynamics of a COVID-19 Model for Saudi Arabia with Vaccination Rate, Saturated Treatment Function and Saturated Incidence Rate
Authors: Alqahtani Rubayyi T. , Ajbar Abdelhamid
Published: December 2021

This paper proposes, validates and analyzes the dynamics of the susceptible exposed infectious recovered (SEIR) model for the propagation of COVID-19 in Saudi Arabia, which recorded the largest number of cases in the Arab world. The model incorporates a saturated incidence rate, a constant vaccination rate and a nonlinear treatment function. The rate of treatment is assumed to be proportional to the number of infected persons when this number is low and reaches a fixed value for large number of infected individuals. The expression of the basic reproduction number is derived, and the model basic stability properties are studied. We show that when the basic reproduction number is less than one the model can predict both a Hopf and backward bifurcations. Simulations are also provided to fit the model to COVID-19 data in Saudi Arabia and to study the effects of the parameters of the treatment function and vaccination rate on disease control.
A New Method for Time Normalization Based on the Continuous Phase: Application to Neck Kinematics
Authors: Llopis-Albert Carlos , Venegas Toro William Ricardo , Farhat Nidal , Zamora-Ortiz Pau , Page Del Pozo Álvaro Felipe
Published: December 2021

There is growing interest in analyzing human movement data for clinical, sport, and ergonomic applications. Functional Data Analysis (FDA) has emerged as an advanced statistical method for overcoming the shortcomings of traditional analytic methods, because the information about continuous signals can be assessed over time. This paper takes the current literature a step further by presenting a new time scale normalization method, based on the Hilbert transform, for the analysis of functional data and the assessment of the effect on the variability of human movement waveforms. Furthermore, a quantitative comparison of well-known methods for normalizing datasets of temporal biomechanical waveforms using functional data is carried out, including the linear normalization method and nonlinear registration methods of functional data. This is done using an exhaustive database of human neck flexion-extension movements, which encompasses 423 complete cycles of 31 healthy subjects measured in two trials of the experiment on different days. The results show the advantages of the novel method compared to existing techniques in terms of computational cost and the effectiveness of time-scale normalization on the phase differences of curves and on the amplitude of means, which are assessed by Root Mean Square (RMS) values of functional means of angles, angular velocities, and angular accelerations. Additionally, the confidence intervals are obtained through a bootstrapping process.
Tool Downscaling Effects on the Friction Stir Spot Welding Process and Properties of Current-Carrying Welded Aluminum–Copper Joints for E-Mobility Applications
Authors: Tchouaha Tankoua Aristide , Köhler Tobias , Bergmann Jean Pierre , Grätzel Michael , Betz Philip , Lindenau Dirk
Published: December 2021

According to the technical breakthrough towards E-Mobility, current-carrying dissimilar joints between aluminum and copper are gaining an increasing relevance for the automotive industry and thus, coming into focus of many research activities. The joining of dissimilar material in general is well known to be a challenging task. Furthermore, the current-carrying joining components in E-Drive consist of pure aluminum and copper materials with relatively thin sheet thickness, which are thermally and mechanically very sensitive, as well as highly heat and electrically conductive. This results in additional challenges for the joining process. Due to their properties, friction stir welding and especially fiction stir spot welding (FSSW) using pinless tools—i.e., as hybrid friction diffusion bonding process (HFDB) is more and more attractive for new application fields and particularly promising for aluminum–copper joining tasks in E-Mobility. However, the feasibility is restricted because of the relatively high process forces required during friction stir welding. Thus, to fulfill the high process and quality requirements in this above-mentioned application field, further research and process development towards process force reduction are necessary. This work deals with the application of the tool downscaling strategy as a mean of process force reduction in FSSW of thin aluminum and copper sheets for current-carrying applications in E-Mobility, where the components are very sensitive to high mechanical loads. The tool downscaling approach enables constant weld quality in similar process time of about 0.5 s despite reduced process forces and torques. By reducing the tool diameter from 10 mm to 6 mm, the process force could be reduced by 36% and the torque by over 50%. Furthermore, a similar heat propagation behavior in the component is observable. These results provide a good basis for the joining of E-Drive components with thermal and mechanical sensitive sheet materials using the pinless FSSW process.
Distortion-Induced Fatigue Reassessment of a Welded Bridge Detail Based on Structural Stress Methods
Authors: Quissanga Vencislau , Alencar Guilherme , de Jesus Abílio , Calçada Rui , da Silva José
Published: December 2021

Typically, bridge structural systems are affected by random loads that can cause significant damage. One challenging problem in this field is the high-stress amplitude associated with distortion-induced fatigue. In this study, the hot-spot method and the master S-N curve method were validated for the evaluation of fatigue resistance induced by distortion in welded joints of steel bridges. Validation of the master S-N curve method in this research was a necessary prior step for application of the method in real case studies of road bridges, which will be subject to loads of variable amplitudes in the near future, ensuring the basis for the application. The method of validation was based on an important available full-scale fatigue test database, which was generated decades ago to serve as the foundation for the assessment of distortion-induced fatigue. Modelling was carried out based on the finite element method with the aid of ANSYS software, considering the shell and solid elements and equivalent structural stresses. The experimental results were compared with the numerical ones obtained with the two methodologies, and the difference, in terms of global and local tension, was less than 1%.
Assessment of the Heat Input Effect on the Distribution of Temperature Cycles in the HAZ of S460MC Welds in MAG Welding
Authors: Moravec Jaromír , Švec Martin , Bukovská Šárka , Sobotka Jiří
Published: December 2021

Temperature cycles generated during welding have a significant effect on the changes in the HAZ of welds, regardless of whether these are changes in structure or mechanical properties; however, it is problematic to obtain temperature cycles with sufficient accuracy across the entire HAZ so that they can be generally taken and used in welding simulations and for real experiments of processes occurring in HAZ. In particular, for a study in a specific location, it is important to know the maximum temperature of the cycle and the cooling rate defined mainly by the parameter t8/5. No studies in which anybody tries to find a mathematical description defining the basic parameters of temperature cycles in the HAZ could be found in the performed research. Therefore, the study presented in this paper results in a mathematical description defining the dependence of achieved maximum temperature on the distance from the fusion line in the HAZ of S460MC welds and with heat input values in the interval from 8 to 14 kJ·cm−1. Moreover, this paper presents the influence of heat input value on the weld pool geometry, including the effect of heat input value on grain coarsening in the highly heated HAZ.
Finite-Elements Modeling and Simulation of Electrically-Assisted Rotary-Draw Bending Process for 6063 Aluminum Alloy Micro-Tube
Authors: Wang Xinwei , Xu Jie , Ding Minghan , Zhang Yanhu , Wang Zhenlong , Guo Bin , Shan Debin
Published: December 2021

Bent micro-tubes have been frequently applied in electronics, medical devices and aerospace for heat transfer due to the increasing heat flux in high-density electric packages. Rotary-draw bending (RDB) is a commonly used process in forming tubes due to its versatility. However, the control of forming defects is the key problem in micro-tube bending in terms of wall thinning, cross-sectional deformation and wrinkling. In this paper, a three-dimensional (3D) finite-elements (FE) modeling of electrically-assisted (EA) RDB of 6063 aluminum alloy micro-tubes is developed with the implicit method in ABAQUS. The multi-field coupled behavior was simulated and analyzed during the EA RDB of micro-tubes. Several process parameters such as micro-tube diameter, bending radius, current density and electrical load path were selected to study their effects on the bending defects of the Al6063 micro-tubes. The simulated results showed that the cross-sectional distortion could be improved when electrical current mainly pass through the vicinity of the tangent point in the micro-tube RDB, and the cross-sectional distortion tended to decrease with the increases of current density and tube diameter, and the decreases of bending speed and radius. A trade-off should be made between the benefit and side effect due to electrical current since the risk of wall thinning and wrinkling may increase.
Adipose Tissue Dysfunctions in Response to an Obesogenic Diet Are Reduced in Mice after Transgenerational Supplementation with Omega 3 Fatty Acids
Authors: Pinel Alexandre , Rigaudière Jean-Paul , Morio Béatrice , Capel Frédéric
Published: December 2021

Obesity is characterized by profound alterations in adipose tissue (AT) biology, leading to whole body metabolic disturbances such as insulin resistance and cardiovascular diseases. These alterations are related to the development of a local inflammation, fibrosis, hypertrophy of adipocytes, and dysregulation in energy homeostasis, notably in visceral adipose tissue (VAT). Omega 3 (n-3) fatty acids (FA) have been described to possess beneficial effects against obesity-related disorders, including in the AT; however, the long-term effect across generations remains unknown. The current study was conducted to identify if supplementation with n-3 polyunsaturated FA (PUFA) for three generations could protect from the consequences of an obesogenic diet in VAT. Young mice from the third generation of a lineage receiving a daily supplementation (1% of the diet) with fish oil rich in eicosapentaenoic acid (EPA) or an isocaloric amount of sunflower oil, were fed a high-fat, high-sugar content diet for 4 months. We explore the transcriptomic adaptations in each lineage using DNA microarray in VAT and bioinformatic exploration of biological regulations using online databases. Transgenerational intake of EPA led to a reduced activation of inflammatory processes, perturbation in metabolic homeostasis, cholesterol metabolism, and mitochondrial functions in response to the obesogenic diet as compared to control mice from a control lineage. This suggests that the continuous intake of long chain n-3 PUFA could be preventive in situations of oversupply of energy-dense, nutrient-poor foods.
Integrated Metabolomics and Proteomics Dynamics of Serum Samples Reveals Dietary Zeolite Clinoptilolite Supplementation Restores Energy Balance in High Yielding Dairy Cows
Authors: Maity Sudipa , Rubić Ivana , Kuleš Josipa , Horvatić Anita , Đuričić Dražen , Samardžija Marko , Ljubić Blanka Beer , Turk Romana , Gračner Damjan , Maćešić Nino , Valpotić Hrvoje , Mrljak Vladimir
Published: December 2021

Dairy cows can suffer from a negative energy balance (NEB) during their transition from the dry period to early lactation, which can increase the risk of postpartum diseases such as clinical ketosis, mastitis, and fatty liver. Zeolite clinoptilolite (CPL), due to its ion-exchange property, has often been used to treat NEB in animals. However, limited information is available on the dynamics of global metabolomics and proteomic profiles in serum that could provide a better understanding of the associated altered biological pathways in response to CPL. Thus, in the present study, a total 64 serum samples were collected from 8 control and 8 CPL-treated cows at different time points in the prepartum and postpartum stages. Labelled proteomics and untargeted metabolomics resulted in identification of 64 and 21 differentially expressed proteins and metabolites, respectively, which appear to play key roles in restoring energy balance (EB) after CPL supplementation. Joint pathway and interaction analysis revealed cross-talks among valproic acid, leucic acid, glycerol, fibronectin, and kinninogen-1, which could be responsible for restoring NEB. By using a global proteomics and metabolomics strategy, the present study concluded that CPL supplementation could lower NEB in just a few weeks, and explained the possible underlying pathways employed by CPL.
Direct Infusion Metabolomics of the Photosystem and Chlorophyll Related Metabolites within a Drought Tolerant Plant Introduction of Glycine max
Authors: Zemaitis Kevin J. , Ye Heng , Nguyen Henry T. , Wood Troy D.
Published: December 2021

Drought is the most prolific form of abiotic stress that legumes and cereal plants alike can endure, and the planting of an improper cultivar at the beginning of a season can cause unexpected losses up to fifty percent under water deficient conditions. Herein, a plant introduction (PI) of an exotic cultivar of soybean (Glycine max), PI 567731, which demonstrates a slow wilting (SW) canopy phenotype in maturity group III, was profiled under drought conditions in field trials in Missouri against a drought susceptible check cultivar, Pana. Metabolomic profiling was carried out on samples of leaves from each of these cultivars at V5 and R2 growth stages both while irrigated and while under drought stress for three weeks. PI 567731 was observed to have differential phytochemical content, and enhanced levels of chlorophyll (Chl) a/b and pheophytin (Pheo) were profiled by direct infusion electrospray Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Indicating drought induced changes of the photosystem and photosynthetic capabilities alongside water preservation strategies are important within the SW phenotype drought response. Subsequent multivariate analysis was able to form predictive models, encompassing the variance of growth and drought stress of the cultivar. Moreover, the existence of unique Chl-related metabolites (CRM) (m/z > 900) were confirmed through tandem mass spectrometry. The resultant coordination of fatty acids to the core of the porphyrin ring was observed and played an unknown role in the proliferation of the photosynthesis. However, the relative ratio of the most abundant CRM is undisturbed by drought stress in PI 567731, in contrast to the drought susceptible cultivar. These results provide key insights into drought related metabolic mechanisms.
Modeling and Simulation of the Surface Generation Mechanism of a Novel Low-Pressure Lapping Technology
Authors: Yu Ninghui , Li Lihua , Kee Chea-su
Published: December 2021

Aluminum alloy (Al6061) is a common material used in the ultraprecision area. It can be machined with a good surface finish by single-point diamond turning (SPDT). Due to the material being relatively soft, it is difficult to apply post-processing techniques such as ultraprecision lapping and ultraprecision polishing, as they may scratch the diamond-turned surface. As a result, a novel low-pressure lapping method was developed by our team to reduce the surface roughness. In this study, a finite element model was developed to simulate the mechanism of this novel lapping technology. The simulation results were compared with the experimental results so as to gain a better understanding of the lapping mechanism.
A Temperature Control Method for Microaccelerometer Chips Based on Genetic Algorithm and Fuzzy PID Control
Authors: Chen Jiaxiao , Lu Qianbo , Bai Jian , Xu Xiang , Yao Yuan , Fang Weidong
Published: December 2021

External temperature changes can detrimentally affect the properties of a microaccelerometer, especially for high-precision accelerometers. Temperature control is the fundamental method to reduce the thermal effect on microaccelerometer chips, although high-performance control has remained elusive using the conventional proportional-integral-derivative (PID) control method. This paper proposes a modified approach based on a genetic algorithm and fuzzy PID, which yields a profound improvement compared with the typical PID method. A sandwiched microaccelerometer chip with a measurement resistor and a heating resistor on the substrate serves as the hardware object, and the transfer function is identified by a self-built measurement system. The initial parameters of the modified PID are obtained through the genetic algorithm, whereas a fuzzy strategy is implemented to enable real-time adjustment. According to the simulation results, the proposed temperature control method has the advantages of a fast response, short settling time, small overshoot, small steady-state error, and strong robustness. It outperforms the normal PID method and previously reported counterparts. This design method as well as the approach can be of practical use and applied to chip-level package structures.
New Low-Frame-Rate Compensating Pixel Circuit Based on Low-Temperature Poly-Si and Oxide TFTs for High-Pixel-Density Portable AMOLED Displays
Authors: Fan Ching-Lin , Lin Wei-Yu , Chen Chun-Yuan
Published: December 2021

A new low-frame-rate active-matrix organic light-emitting diode (AMOLED) pixel circuit with low-temperature poly-Si and oxide (LTPO) thin-film transistors (TFTs) for portable displays with high pixel density is reported. The proposed pixel circuit has the excellent ability to compensate for the threshold voltage variation of the driving TFT (ΔVTH_DTFT). By the results of simulation based on a fabricated LTPS TFT and a-IZTO TFT, we found that the error rates of the OLED current were all lower than 2.71% over the range of input data voltages when ΔVTH_DTFT = ±0.33 V, and a low frame rate of 1 Hz could be achieved with no flicker phenomenon. Moreover, with only one capacitor and two signal lines in the pixel circuit, a high pixel density and narrow bezel are expected to be realized. We revealed that the proposed 7T1C pixel circuit with low driving voltage and low frame rate is suitable for portable displays.
An Overview of Helicobacter pylori Survival Tactics in the Hostile Human Stomach Environment
Authors: Cheok Yi Ying , Lee Chalystha Yie Qin , Cheong Heng Choon , Vadivelu Jamuna , Looi Chung Yeng , Abdullah Suhailah , Wong Won Fen
Published: December 2021

Helicobacter pylori is well established as a causative agent for gastritis, peptic ulcer, and gastric cancer. Armed with various inimitable virulence factors, this Gram-negative bacterium is one of few microorganisms that is capable of circumventing the harsh environment of the stomach. The unique spiral structure, flagella, and outer membrane proteins accelerate H. pylori movement within the viscous gastric mucosal layers while facilitating its attachment to the epithelial cells. Furthermore, secretion of urease from H. pylori eases the acidic pH within the stomach, thus creating a niche for bacteria survival and replication. Upon gaining a foothold in the gastric epithelial lining, bacterial protein CagA is injected into host cells through a type IV secretion system (T4SS), which together with VacA, damage the gastric epithelial cells. H. pylori does not only establishes colonization in the stomach, but also manipulates the host immune system to permit long-term persistence. Prolonged H. pylori infection causes chronic inflammation that precedes gastric cancer. The current review provides a brief outlook on H. pylori survival tactics, bacterial-host interaction and their importance in therapeutic intervention as well as vaccine development.
A Set of Plasmid-Based Modules for Easy Switching of C-Terminal Epitope Tags in Saccharomyces cerevisiae
Authors: Hayashi Hiroki , Kishi Tsutomu
Published: December 2021

Epitope tagging is a powerful strategy for analyzing the functions of targeted proteins. The use of this strategy has become more convenient with the development of the epitope switch, which is another type of epitope tagging designed to convert the previously tagged epitopes on the chromosome to other epitopes of interest. Various modules for C-terminal epitope switching have been developed and amplified using the one-step polymerase chain reaction (PCR) method before transformation. However, PCR amplification occasionally generates mutations that affect the fidelity of epitope switching. Here, we constructed several plasmids to isolate modules for epitope switching through digestion by restriction enzymes. The isolated modules contained DNA sequences for homologous recombination, various epitopes (13×Myc, 6×HA, GFP, Venus, YFP, mCherry, and CFP), and a transformation marker (Candida glabrata LEU2). The restriction enzyme-digested plasmids were used to directly transform the cells for epitope switching. We demonstrate the efficient and accurate switching of the MX6 module-based C-terminal tandem affinity purification tags to each aforementioned epitope. We believe that our plasmids can serve as powerful tools for the functional analysis of yeast proteins.
Responses of Soil Microbial Traits to Ground Cover in Citrus Orchards in Central China
Authors: Wu Yupeng , Wang Xue , Hu Ronggui , Zhao Jinsong , Jiang Yanbin
Published: December 2021

A clear understanding of which factors play an important role in the development of the soil microbial community in orchards will benefit our understanding of ground cover impacts on soil nutrient cycling. Thus, in the present study, grass properties, soil properties, and soil microbial community structure were determined in a citrus orchard after 5 years of management with different types of ground cover (NG: natural grass, LP: monoculture of legumes, and NL: mixed culture of natural grasses and legumes) to evaluate how ground cover biomass and nitrogen-fixing ability drive soil physicochemical and microbial traits. Plant biomass carbon (BC) and nitrogen (BN) were significantly higher in LP and NL than NG and showed a significant (p < 0.01) positive relationship with soil total carbon (TC), NO3−-N (NN), and dissolved organic carbon (DOC) content. In addition, the amount of biologically fixed nitrogen (FixN) showed a significant positive relationship with soil total nitrogen (TN) (p < 0.05) and NH4+-N (AN) content (p < 0.01). We also observed a difference in the soil microbial community structure between plots with and without legumes. The TC and BN were the most influential factors driving bacterial and fungal communities, respectively. Nevertheless, FixN explained less than 9% of the differences in soil bacterial and fungal communities. Our results suggest that grass biomass and FixN are the strong drivers of soil chemical properties, whereas ground cover and soil properties both contribute significantly to the soil microbial community structure.
Genomic and Metabolomic Insights into Secondary Metabolites of the Novel Bacillus halotolerans Hil4, an Endophyte with Promising Antagonistic Activity against Gray Mold and Plant Growth Promoting Potential
Authors: Thomloudi Eirini-Evangelia , Tsalgatidou Polina C. , Baira Eirini , Papadimitriou Konstantinos , Venieraki Anastasia , Katinakis Panagiotis
Published: December 2021

The endophytic bacterial strain Hil4 was isolated from leaves of the medicinal plant Hypericum hircinum. It exhibited antifungal activity against Botrytis cinerea and a plethora of plant growth promoting traits in vitro. Whole genome sequencing revealed that it belongs to Bacillus halotolerans and possesses numerous secondary metabolite biosynthetic gene clusters and genes involved in plant growth promotion, colonization, and plant defense elicitation. The Mojavensin cluster was present in the genome, making this strain novel among plant-associated B. halotolerans strains. Extracts of secreted agar-diffusible compounds from single culture secretome extracts and dual cultures with B. cinerea were bioactive and had the same antifungal pattern on TLC plates after bioautography. UHPLC-HRMS analysis of the single culture secretome extract putatively annotated the consecutively produced antimicrobial substances and ISR elicitors. The isolate also proved efficient in minimizing the severity of gray mold post-harvest disease on table grape berries, as well as cherry tomatoes. Finally, it positively influenced the growth of Arabidopsis thaliana Col-0 and Solanum lycopersicum var. Chondrokatsari Messinias after seed biopriming in vitro. Overall, these results indicate that the B. halotolerans strain Hil4 is a promising novel plant growth promoting and biocontrol agent, and can be used in future research for the development of biostimulants and/or biological control agents.
Identification of a Novel Therapeutic Target against XDR Salmonella Typhi H58 Using Genomics Driven Approach Followed Up by Natural Products Virtual Screening
Authors: Jalal Khurshid , Khan Kanwal , Hassam Muhammad , Abbas Muhammad Naseer , Uddin Reaz , Khusro Ameer , Sahibzada Muhammad Umar Khayam , Gajdács Márió
Published: December 2021

Typhoid fever is caused by a pathogenic, rod-shaped, flagellated, and Gram-negative bacterium known as Salmonella Typhi. It features a polysaccharide capsule that acts as a virulence factor and deceives the host immune system by protecting phagocytosis. Typhoid fever remains a major health concern in low and middle-income countries, with an estimated death rate of ~200,000 per annum. However, the situation is exacerbated by the emergence of the extensively drug-resistant (XDR) strain designated as H58 of S. Typhi. The emergence of the XDR strain is alarming, and it poses serious threats to public health due to the failure of the current therapeutic regimen. A relatively newer computational method called subtractive genomics analyses has been widely applied to discover novel and new drug targets against pathogens, particularly drug-resistant ones. The method involves the gradual reduction of the complete proteome of the pathogen, leading to few potential and novel drug targets. Thus, in the current study, a subtractive genomics approach was applied against the Salmonella XDR strain to identify potential drug targets. The current study predicted four prioritized proteins (i.e., Colanic acid biosynthesis acetyltransferase wcaB, Shikimate dehydrogenase aroE, multidrug efflux RND transporter permease subunit MdtC, and pantothenate synthetase panC) as potential drug targets. Though few of the prioritized proteins are treated in the literature as the established drug targets against other pathogenic bacteria, these drug targets are identified here for the first time against S. Typhi (i.e., S. Typhi XDR). The current study aimed at drawing attention to new drug targets against S. Typhi that remain largely unexplored. One of the prioritized drug targets, i.e., Colanic acid biosynthesis acetyltransferase, was predicted as a unique, new drug target against S. Typhi XDR. Therefore, the Colanic acid was further explored using structure-based techniques. Additionally, ~1000 natural compounds were docked with Colanic acid biosynthesis acetyltransferase, resulting in the prediction of seven compounds as potential lead candidates against the S. Typhi XDR strain. The ADMET properties and binding energies via the docking program of these seven compounds characterized them as novel drug candidates. They may potentially be used for the development of future drugs in the treatment of Typhoid fever.