bluuebunny/crossref_metadata_2025 huggingface dataset:
Coupling a Parametric Wave Solver into a Hydrodynamic Circulation Model to Improve Efficiency of Nested Estuarine Storm Surge Predictions
Authors: Lodge Caleb T. , Weaver Robert J.
Published: August 2022

Efficiency in storm surge modeling is crucial for forecasting coastal hazards in real-time. While computation cost may not be the main concern for organizations with ample resources, the robustness of forecasts generated by most parties are restricted by wall-clock time. The Parametric Wave Solver (PARAM) was developed by Boyd and Weaver (2021) as an alternative to computationally expensive wind–wave models when modeling restricted estuarine environments. For this study, PARAM has been tightly coupled with the ADCIRC hydrodynamic model to create ADCparam, then integrated into the Multistage mini-ensemble modeling system (MMEMS), a one-way nesting framework for modeling waves and circulation in coastal estuaries developed by Taeb and Weaver (2019). In the MMEMS framework, ADCIRC + SWAN is used to simulate the coarser ocean domain and ADCparam is applied to the nested high resolution estuarine mesh. ADCparam has greatly reduced computation time for the high resolution nested sub-model compared to the third-generation wave model originally used. While the PARAM wave solution shows dissimilarities with the SWAN solution, significant wave height and wave period results are consistent and warrant further pursuit of the parametric wave ensemble method as a substitute to SWAN within MMEMS. ADCparam models demonstrated run times up to 51% faster than ADCIRC coupled with SWAN, an established iterative wave model tightly coupled to ADCIRC and packaged with the MMEMS repository. ADCparam wall time is comparable to running ADCIRC without wave forcing, nearly eliminating the computational cost of including the wave forcing in the high-resolution estuarine domain of MMEMS. Computational efficiency is greatly increased while maintaining solution integrity. Though ADCparam, and its application to MMEMS, are still being refined and validated, the coupled model system has proven to be an efficient, viable path for implementing waves in any estuarine circulation model.
The Role of the Pharmacist in Selecting the Best Choice of Medication Formulation in Dysphagic Patients
Authors: Zuccari Guendalina , Macis Sara , Alfei Silvana , Marchitto Leonardo , Russo Eleonora
Published: August 2022

Usually, the administration of drugs by feeding tube in dysphagic patients involves handling of marketing licenses outside their term, due to the lack of suitable formulations. This circumstance has put health professionals in the dilemma of choosing the formulation whose manipulation possibly does not alter the effectiveness of the drug. In this regard, a practical guide providing indications on the prescription, handling, and administration of drugs through enteral feeding tube could be of paramount utility. For this purpose, we have considered the 1047 solid oral pharmaceutical forms included in the formulary of San Paolo Hospital (Savona, Italy). From our analysis, it emerges that 95% of medicinal products are worryingly used off-label and 40% have to be managed by the hospital pharmacists without having suitable indications by either the manufacturers or by literature studies. To fill this gap, we have compiled a detailed table containing missing indications derived from pharmacist expertise and evidence-based practices, with the aim that the sharing of our procedures will contribute to make uniform pharmacological therapies from one hospital to another. This study will allow doctors to have easy access to information on drugs that can be prescribed and nurses to become familiar only with the pharmaceutical forms that can be administered.
Framework for Testing Robustness of Machine Learning-Based Classifiers
Authors: Chuah Joshua , Kruger Uwe , Wang Ge , Yan Pingkun , Hahn Juergen
Published: August 2022

There has been a rapid increase in the number of artificial intelligence (AI)/machine learning (ML)-based biomarker diagnostic classifiers in recent years. However, relatively little work has focused on assessing the robustness of these biomarkers, i.e., investigating the uncertainty of the AI/ML models that these biomarkers are based upon. This paper addresses this issue by proposing a framework to evaluate the already-developed classifiers with regard to their robustness by focusing on the variability of the classifiers’ performance and changes in the classifiers’ parameter values using factor analysis and Monte Carlo simulations. Specifically, this work evaluates (1) the importance of a classifier’s input features and (2) the variability of a classifier’s output and model parameter values in response to data perturbations. Additionally, it was found that one can estimate a priori how much replacement noise a classifier can tolerate while still meeting accuracy goals. To illustrate the evaluation framework, six different AI/ML-based biomarkers are developed using commonly used techniques (linear discriminant analysis, support vector machines, random forest, partial-least squares discriminant analysis, logistic regression, and multilayer perceptron) for a metabolomics dataset involving 24 measured metabolites taken from 159 study participants. The framework was able to correctly predict which of the classifiers should be less robust than others without recomputing the classifiers itself, and this prediction was then validated in a detailed analysis.
Ecosystem and Driving Force Evaluation of Northeast Forest Belt
Authors: Liao Zhihong , Su Kai , Jiang Xuebing , Zhou Xiangbei , Yu Zhu , Chen Zhongchao , Wei Changwen , Zhang Yiming , Wang Luying
Published: August 2022

The ecosystem in the Northeast Forest Belt (NFB) can provide various ecosystem services, such as soil conservation, habitat provision, water conservation, and so on. It is essential for maintaining the ecological environment in Northeast China and the entire country. In the face of increasingly severe environmental problems, the comprehensive and accurate evaluation of ecosystem conditions and their changes is significant for scientific and reasonable recovery and protection measures. In this study, the NFB was taken as the research area. The spatio-temporal changes in ecological quality from 2005 to 2015 and the main driving factors behind them were analyzed by constructing the comprehensive ecosystem evaluation index. The results showed that: The landscape types of the NFB were mainly forest, cropland, and grassland. And the better ecological environment of the NFB was mainly distributed in the south of Changbai Mountains (CBM), the middle of Lesser Khingan Mountains (LKM), and the northwest of Greater Khingan Mountains (GKM). In contrast, the northeast of CBM, the southwest of LKM, and the edge of southern GKM were relatively poor. During 2005–2015, the ecosystem in the NFB was in a relatively good state as a whole, showing a steady-to-good development trend. However, more attention needed to be paid to some areas where degradation still existed. Land use/cover, climate (annual average rainfall, etc.), and human disturbance were potential factors affecting ecosystem evolution in the NFB. This study aims to provide an effective scientific basis and policy reference for the environmental protection and construction of the NFB.
The Effect of Environment on the Evolution and Proliferation of Protocells of Increasing Complexity
Authors: Roy Suvam , Sengupta Supratim
Published: August 2022

The formation, growth, division and proliferation of protocells containing RNA strands is an important step in ensuring the viability of a mixed RNA–lipid world. Experiments and computer simulations indicate that RNA encapsulated inside protocells can favor the protocell, promoting its growth while protecting the system from being over-run by selfish RNA sequences. Recent work has also shown that the rolling-circle replication mechanism can be harnessed to ensure the rapid growth of RNA strands and the probabilistic emergence and proliferation of protocells with functionally diverse ribozymes. Despite these advances in our understanding of a primordial RNA–lipid world, key questions remain about the ideal environment for the formation of protocells and its role in regulating the proliferation of functionally complex protocells. The hot spring hypothesis suggests that mineral-rich regions near hot springs, subject to dry–wet cycles, provide an ideal environment for the origin of primitive protocells. We develop a computational model to study protocellular evolution in such environments that are distinguished by the occurrence of three distinct phases, a wet phase, followed by a gel phase, and subsequently by a dry phase. We determine the conditions under which protocells containing multiple types of ribozymes can evolve and proliferate in such regions. We find that diffusion in the gel phase can inhibit the proliferation of complex protocells with the extent of inhibition being most significant when a small fraction of protocells is eliminated during environmental cycling. Our work clarifies how the environment can shape the evolution and proliferation of complex protocells.
Emerging Immune-Monitoring System for Immune Checkpoint Inhibitors
Authors: Hamada Kazuyuki , Tsunoda Takuya , Yoshimura Kiyoshi
Published: August 2022

Immune checkpoint inhibitors (ICIs) have a major impact on cancer treatment. However, the therapeutic efficacy of ICIs is only effective in some patients. Programmed death ligand 1 (PD-L1), tumor mutation burden (TMB), and high-frequency microsatellite instability (MSI-high) are markers that predict the efficacy of ICIs but are not universally used in many carcinomas. The gut microbiota has received much attention recently because of its potential to have a significant impact on immune cells in the cancer microenvironment. Metabolites of the gut microbiota modulate immunity and have a strong influence on the therapeutic efficacy of ICI. It has been suggested that the gut microbiota may serve as a novel marker to predict the therapeutic efficacy of ICI. Therefore, there is an urgent need to develop biomarkers that can predict anti-tumor effects and adverse events, and the study of the gut microbiota is essential in this regard.
Microvasculopathy Evaluated by Dual-Energy Computed Tomography in Patients with Chronic Thromboembolic Pulmonary Hypertension and Pulmonary Arterial Hypertension
Authors: Miwa Keisuke , Taniguchi Yu , Fujii Hiroyuki , Matsuoka Yoichiro , Onishi Hiroyuki , Yanaka Kenichi , Izawa Yu , Tsuboi Yasunori , Kono Atsushi , Emoto Noriaki , Hirata Kenichi
Published: August 2022

Background: Poor subpleural perfusion (PSP) on dual-energy computed tomography (DE-CT) suggests microvasculopathy in chronic thromboembolic pulmonary hypertension (CTEPH). However, whether the microvasculopathy findings are equivalent to those in pulmonary arterial hypertension (PAH) remains unclear. The aim of this study was to elucidate the characteristics of microvasculopathy in CTEPH compared to those of that in PAH. Methods: We retrospectively reviewed subpleural perfusion on DE-CT and the hemodynamics of 23 patients with PAH and 113 with inoperable CTEPH. Subpleural perfusion on DE-CT was classified as poor (subpleural spaces in all segments with little or no perfusion) or normal. Results: PSP was observed in 51% of patients with CTEPH and in 4% of those with PAH (p < 0.01). CTEPH patients with PSP had poorer baseline hemodynamics and lower diffusing capacity for carbon monoxide divided by the alveolar volume (DLCO/VA) than those with CTEPH with normal perfusion (pulmonary vascular resistance [PVR]: 768 ± 445 dynes-sec/cm5 vs. 463 ± 284 dynes-sec/cm5, p < 0.01; DLCO/VA, 60.4 ± 16.8% vs. 75.9 ± 15.7%, p < 0.001). Despite the existence of PSP, hemodynamics improved to nearly normal in both groups after balloon pulmonary angioplasty. Conclusions: PSP on DE-CT, which is one of the specific imaging findings in CTEPH, might suggest a different mechanism of microvasculopathy from that in PAH.
Fiber-Bragg-Grating-Based Displacement Sensors: Review of Recent Advances
Authors: Bonopera Marco
Published: August 2022

With the development of fiber optical technologies, fiber Bragg grating (FBG) sensors are frequently utilized in structural health monitoring due to their considerable advantages, including fast response, electrical passivity, corrosion resistance, multi-point sensing capability and low-cost production, as well as high accuracy and resolution over a long period. These characteristics allow FBG to be a proper alternative sensing element for displacement measurements. In this article, the recent sensing advances and principles of detection of FBG-based displacement sensors are illustrated. Specifically, the latest FBG-based displacement technologies are examined from three principles of detection, i.e., wavelength, intensity and phase signal demodulation. Regarding wavelength detection methods, the problem related to the cross-sensitivity can significantly be reduced depending on the new type of cantilever–FBG-based sensing developed. Vice versa, only the packaging method of FBG prestressed between two fixed ends can still avoid the chirp phenomenon in the reflection spectrum. Moreover, to attenuate the influence of temperature variations on the accuracy of FBG displacement sensors, specific temperature self-compensation structures were successfully designed according to the concepts of phase signal demodulation. In future investigations, different elastic structures and gratings manufactured through special fibers and new methodologies for temperature compensation will still highly refine the efficiency of FBG-based displacement sensors.
Bonding and Strengthening the PLA Biopolymer in Multi-Material Additive Manufacturing
Authors: Brancewicz-Steinmetz Emila , Sawicki Jacek
Published: August 2022

3D printing is a revolutionary additive manufacturing method that enables rapid prototyping and design flexibility. A variety of thermoplastic polymers can be used in printing. As it is necessary to reduce the consumption of petrochemical resources, alternative solutions are being researched, and the interest in using bioplastics and biocomposites is constantly growing. Often, however, the properties of biopolymers are insufficient and need to be improved to compete with petroleum-based plastics. The paper aims to analyze the available information on elements produced from more than one material, with additive manufacturing resulting from 3D printing using biopolymer Polylactic Acid (PLA). The study notes the possibility of modifying and improving the properties of PLA using layered printing or by modifying PLA filaments. Several modifications improving and changing the properties of PLA were also noted, including printing parameters when combined with other materials: process temperatures, filling, and surface development for various sample geometries.
Enhancement Properties of Zr Modified Porous Clay Heterostructures for Adsorption of Basic-Blue 41 Dye: Equilibrium, Regeneration, and Single Batch Design Adsorber
Authors: Popoola Saheed A. , Al Dmour Hmoud , Rakass Souad , Fatimah Is , Liu Yan , Mohmoud Ahmed , Kooli Fethi
Published: August 2022

Zirconium porous clay heterostructures (Zr-PCH) were synthesized using intercalated clay minerals by zirconium species with different contents of zirconium. The presence of zirconium and silica species was confirmed by X-ray diffraction, X-ray fluorescence, and magic-angle spinning nuclear magnetic resonance. The insertion of zirconium improved the thermal stability, the specific surface area with a maximum of 950 m2/g, and the acidity concentration of 0.993 mol of protons per g of solid. These materials were used to adsorb the basic blue-41 from aqueous solution. The adsorption efficiency was examined at different conditions, with a maximum adsorbed amount of 346 mg/g as estimated from Langmuir model. This value was dependent on zirconium content in the PCHs. The adsorption process was found to be favorable and spontaneous. The efficiency of the spent materials was maintained after five reuse cycles with a decrease by 15% of the original value for a particular Zr-PCH material with a Zr content of 6.82%. Single stage batch adsorber was suggested using the mass balance equation and Langmuir isotherm model. The amount of PCH materials required depended on the target percentage of adsorption at specific volume and initial concentration of the basic-blue-41 dye solution.
Design of a Digital Twin for an Industrial Vacuum Process: A Predictive Maintenance Approach
Authors: Yakhni Mohammad F. , Hosni Houssem , Cauet Sebastien , Sakout Anas , Etien Erik , Rambault Laurent , Assoum Hassan , El-Gohary Mohamed
Published: August 2022

The concept of a digital twin is increasingly appearing in industrial applications, including the field of predictive maintenance. A digital twin is a virtual representation of a physical system containing all data available on site. This paper presents condition monitoring of ventilation systems through the digital twin approach. A literature review regarding the most popular system faults is covered. The motor current signature analysis is used in this research to detect system faults. The physical system is further described. Then, based on the free body diagram concept and Newton’s second law, the equations of motion are obtained. Matlab/Simulink software is used to build the digital twin. The Concordia method and the Fast Fourier Transform analysis are used to process the current signal, and physical and numerical system current measurements are obtained and compared. In the final step of the modeling, specific frequencies were adjusted in the twin to achieve the best simulation. In addition, a statistical approach is used to create a complete diagnostic protocol.
A Modified Radial Point Interpolation Method (M-RPIM) for Free Vibration Analysis of Two-Dimensional Solids
Authors: Sun Tingting , Wang Peng , Zhang Guanjun , Chai Yingbin
Published: August 2022

The classical radial point interpolation method (RPIM) is a powerful meshfree numerical technique for engineering computation. In the original RPIM, the moving support domain for the quadrature point is usually employed for the field function approximation, but the local supports of the nodal shape functions are always not in alignment with the integration cells constructed for numerical integration. This misalignment can result in additional numerical integration error and lead to a loss in computation accuracy. In this work, a modified RPIM (M-RPIM) is proposed to address this issue. In the present M-RPIM, the misalignment between the constructed integration cells and the nodal shape function supports is successfully overcome by using a fixed support domain that can be easily constructed by the geometrical center of the integration cell. Several numerical examples of free vibration analysis are conducted to evaluate the abilities of the present M-RPIM and it is found that the computation accuracy of the original RPIM can be markedly improved by the present M-RPIM.
Kinematic Modelling for Hyper-Redundant Robots—A Structured Guide
Authors: Cerrillo Diego , Barrientos Antonio , Del Cerro Jaime
Published: August 2022

Obtaining mathematical equations to model the kinematics of a hyper-redundant robot is not intuitive and of greater difficulty than for traditional robots. Depending on the characteristics of the robot, the most appropriate methodology to approach the modelling may be one or another. This article provides a general overview of the different approaches there are when modelling a hyper-redundant cable-driven robot, while proposing a guide to help the novel researcher that approaches this field decide which methodology to apply when modelling a robot. After providing some definitions, a simple framework to understand all the underlying models is presented. Afterwards, the mathematical equations for the most important methods of modelling are developed. Finally, the proposal for a step-by-step tutorial is included, and it is exemplified by applying it to three real robots.
Global Dynamics of the Vibrating System of a Tristable Piezoelectric Energy Harvester
Authors: Zhu Yijun , Shang Huilin
Published: August 2022

Global dynamics of a piezoelectric energy harvester with tristable potential is investigated. The dynamical model of a cantilever beam energy harvester is considered; its static bifurcation is also discussed. Multiple intra-well attractors and their basins of attraction are presented to discuss the mechanism of multistability and its initial sensitivity. Moreover, the Melnikov method is applied to present the conditions for global bifurcations and the induced complex dynamics. The results show that the variation of coefficients of the polynomial may affect the number and shapes of potential wells, while the increase of the excitation amplitude may trigger multistability around one equilibrium, initial-sensitive jump, inter-well attractor and chaos. The results may provide some theoretical reference for increasing the working performance of energy harvesters.
On the Asymptotic Behavior of Noncanonical Third-Order Emden–Fowler Delay Differential Equations with a Superlinear Neutral Term
Authors: Liu Qingmin , Grace Said R. , Jadlovská Irena , Tunç Ercan , Li Tongxing
Published: August 2022

The present paper is concerned with the asymptotic behavior of solutions to a class of noncanonical third-order Emden–Fowler delay differential equations with a superlinear neutral term. Using a Riccati-type transformation as well as integral criteria, we establish some new sufficient conditions guaranteeing that every solution of the equation considered either oscillates or converges to zero asymptotically. The results are illustrated with two examples.
Use of Spherical and Cartesian Features for Learning and Recognition of the Static Mexican Sign Language Alphabet
Authors: Rios-Figueroa Homero V. , Sánchez-García Angel J. , Sosa-Jiménez Candy Obdulia , Solís-González-Cosío Ana Luisa
Published: August 2022

The automatic recognition of sign language is very important to allow for communication by hearing impaired people. The purpose of this study is to develop a method of recognizing the static Mexican Sign Language (MSL) alphabet. In contrast to other MSL recognition methods, which require a controlled background and permit changes only in 2D space, our method only requires indoor conditions and allows for variations in the 3D pose. We present an innovative method that can learn the shape of each of the 21 letters from examples. Before learning, each example in the training set is normalized in the 3D pose using principal component analysis. The input data are created with a 3D sensor. Our method generates three types of features to represent each shape. When applied to a dataset acquired in our laboratory, an accuracy of 100% was obtained. The features used by our method have a clear, intuitive geometric interpretation.
Novel Approximations to the (Un)forced Pendulum–Cart System: Ansatz and KBM Methods
Authors: Alhejaili Weaam , Salas Alvaro H. , El-Tantawy Samir A.
Published: August 2022

In the present investigation, some novel analytical approximations to both unforced and forced pendulum–cart system oscillators are obtained. In our investigation, two accurate and effective approaches, namely, the ansatz method with equilibrium point and the Krylov–Bogoliubov–Mitropolsky (KBM) method, are implemented for analyzing pendulum–cart problems.The obtained results are compared with the Runge–Kutta (RK4) numerical approximation. The obtained approximations using both ansatz and KBM methods show good coincidence with RK4 numerical approximation. In addition, the global maximum error is estimated as compared to RK4 numerical approximation.
Stochastic Approach to Investigate Protected Access to Information Resources in Combined E-Learning Environment
Authors: Romansky Radi
Published: August 2022

The digital era expands the scope and application of information technologies, which also affects the forms of e-learning, motivating the development of combined systems with heterogeneous resources and services, including in the cloud. In this vein, the present article investigates the implementation of a set of procedures for maintaining regulated access to resources (identification, authentication, authorization, etc.) in a combined e-learning environment, with the main goal to confirm their effectiveness and correctness. The study was conducted through analytical modelling using stochastic tools from the theory of Petri nets and Markov chains with additional statistical analysis. The application of such a combined approach allows increased research efficiency and better adequacy of the obtained estimates.
Meta-Heuristic Optimization and Keystroke Dynamics for Authentication of Smartphone Users
Authors: El-Kenawy El-Sayed M. , Mirjalili Seyedali , Abdelhamid Abdelaziz A. , Ibrahim Abdelhameed , Khodadadi Nima , Eid Marwa M.
Published: August 2022

Personal Identification Numbers (PIN) and unlock patterns are two of the most often used smartphone authentication mechanisms. Because PINs have just four or six characters, they are subject to shoulder-surfing attacks and are not as secure as other authentication techniques. Biometric authentication methods, such as fingerprint, face, or iris, are now being studied in a variety of ways. The security of such biometric authentication is based on PIN-based authentication as a backup when the maximum defined number of authentication failures is surpassed during the authentication process. Keystroke-dynamics-based authentication has been studied to circumvent this limitation, in which users were categorized by evaluating their typing patterns as they input their PIN. A broad variety of approaches have been proposed to improve the capacity of PIN entry systems to discriminate between normal and abnormal users based on a user’s typing pattern. To improve the accuracy of user discrimination using keystroke dynamics, we propose a novel approach for improving the parameters of a Bidirectional Recurrent Neural Network (BRNN) used in classifying users’ keystrokes. The proposed approach is based on a significant modification to the Dipper Throated Optimization (DTO) algorithm by employing three search leaders to improve the exploration process of the optimization algorithm. To assess the effectiveness of the proposed approach, two datasets containing keystroke dynamics were included in the conducted experiments. In addition, we propose a feature selection algorithm for selecting the proper features that enable better user classification. The proposed algorithms are compared to other optimization methods in the literature, and the results showed the superiority of the proposed algorithms. Moreover, a statistical analysis is performed to measure the stability and significance of the proposed methods, and the results confirmed the expected findings. The best classification accuracy achieved by the proposed optimized BRNN is 99.02% and 99.32% for the two datasets.
Deep Learning-Based Remaining Useful Life Prediction Method with Transformer Module and Random Forest
Authors: Zhao Lefa , Zhu Yafei , Zhao Tianyu
Published: August 2022

This paper focuses on the prognosis problem in manufacturing of the electronic chips for devices. Electronic devices are of great importance at present, which are popularly applied in daily life. The basis of supporting the electronic device is the powerful electronic chip and its manufacturing technology. Chip manufacturing has been one of the most important technologies in recent years. The etching machine is the key equipment in the etching process of the wafers in chip manufacturing. Due to the high demands for precise manufacturing, monitoring the health state and predicting the remaining useful life (RUL) of the etching system is quite important. However, the task is very hard because of the lack of knowledge of exact onset of failure or degradation and the multiple operating conditions, etc. This paper proposes a novel deep learning-based RUL prediction method for the etching system. The transformer module and random forest are integrated in the methodology to identify the health state of the machine and predict its RUL, through training with the complex data of the etching machine’s sensors and exploring its underlying features. The experiments are based on the subject of the 2018 PHM Data Challenge—for estimating time-to-failure or RUL of Ion Mill Etching Systems in an online fashion using data from multiple sensors. The results indicate the proposed method is promising for the real applications of the prognosis of the etching system for electronic devices.
Simulating Portfolio Decisions under Uncertainty When the Risky Asset and Short Rate Are Modulated by an Inhomogeneous and Asset-Dependent Markov Chain
Authors: Vallejo-Jiménez Benjamín , Venegas-Martínez Francisco , De la Torre-Torres Oscar V. , Álvarez-García José
Published: August 2022

This paper aims to simulate portfolio decisions under uncertainty when the diffusion parameters of the risky asset and short rate paid for a bond are both modulated by a time-inhomogeneous Markov chain, with transition probabilities dependent on states, time, and asset prices. To do this, we first found closed-form solutions of the corresponding utility-maximization problem, which solves a rational consumer that makes portfolio and consumption decisions by using the corresponding infinitesimal generator associated with the Markov chain. Subsequently, as an illustration of the theoretical results obtained, several scenarios were simulated for the Mexican case. The expected economic policy was inferred from announced monetary policy decisions regarding the reference rate and possible changes in trend due to the lack of fiscal stimuli. Under this framework, states were defined from the current and expected economic policies, and transition probabilities were expressed in terms of the ratio between the prices of the risky asset and the bond. It should be noted, as far as the authors know, that no analytical solutions are known in the literature for the case of Markov-modulated time-inhomogeneous chains with transition probabilities that, themselves, are stochastic processes.
Generalized Randić Estrada Indices of Graphs
Authors: Lenes Eber , Mallea-Zepeda Exequiel , Medina Luis , Rodríguez Jonnathan
Published: August 2022

Let G be a simple undirected graph on n vertices. V. Nikiforov studied hybrids of AG and DG and defined the matrix AαG for every real α∈[0,1] as AαG=αDG+(1−α)AG. In this paper, we define the generalized Randić matrix for graph G, and we introduce and establish bounds for the Estrada index of this new matrix. Furthermore, we find the smallest value of α for which the generalized Randić matrix is positive semidefinite. Finally, we present the solution to the problem proposed by V. Nikiforov. The problem consists of the following: for a given simple undirected graph G, determine the smallest value of α for which AαG is positive semidefinite.
Strength and Fatigue Life at 625 K of the Ultrafine-Grained Ti-6Al-4V Alloy Produced by Equal-Channel Angular Pressing
Authors: Semenova Irina P. , Polyakov Alexander V. , Pesin Mikhail V. , Stotskiy Andrey G. , Modina Yulia M. , Valiev Ruslan Z. , Langdon Terence G.
Published: August 2022

Grain reduction in a widely used Ti-6Al-4V alloy increases its endurance limit at room temperature. In this work, the behavior of the ultrafine-grained alloy under cyclic load at the temperature of 625 K is considered. Research was conducted to examine the fatigue life in a low-cycle area of the ultrafine-grained Ti-6Al-4V alloy produced by equal-channel angular pressing. Tensile and fatigue testing of the Ti-6Al-4V samples with coarse-grained (CG) and ultrafine-grained (UFG) structures were carried out at 293 and 625 K. The alloy demonstrated an enhanced strength and fatigue life at both temperatures. The representative features of the microstructural evolution and the fracture features in the UFG and CG alloys after fatigue tests are described in detail. The prospects for the use of the UFG Ti-6Al-4V alloy for engineering applications, such as in the production of critical gas-turbine engine parts, is discussed.
Nosing Process of 2A12 Aluminum Alloy Spacing Shims for Non-disengagement Fastening Devices for Spacecrafts
Authors: Wang Xiaoliang , Cui Yunxian , Yuan Tiebing
Published: August 2022

In this study, a finite element simulation model for the nosing of the non-disengagement fastening device’s 2A12 aluminum alloy-spacing shim was established. Furthermore, the effects of the fillet radius, inclination angle, and stamping velocity of the nosing die on the formation of the spacing shim were examined. The following conclusions were drawn. (1) The die’s fillet radius primarily affects the spacing shim’s bending angle—as the die’s fillet radius increases, the bending performance decreases and meets the requirement when the fillet radius is 1.8 mm. (2) The die’s inclination angle affects the spacing shim’s nosing dimension: the nosing dimension increases with the increase in the die’s inclination angle and is optimal when the die’s inclination angle reaches 7°. (3) Within the range of 186–294 mm/s, the stamping velocity barely affects the formation of the spacing shim.
A Sample Preparation Method for the Simultaneous Profiling of Signaling Lipids and Polar Metabolites in Small Quantities of Muscle Tissues from a Mouse Model for Sarcopenia
Authors: He Yupeng , van Mever Marlien , Yang Wei , Huang Luojiao , Ramautar Rawi , Rijksen Yvonne , Vermeij Wilbert P. , Hoeijmakers Jan H. J. , Harms Amy C. , Lindenburg Peter W. , Hankemeier Thomas
Published: August 2022

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1∆/− mouse mutant exhibiting multiple–morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.
Secure Transmission of Terahertz Signals with Multiple Eavesdroppers
Authors: He Yuqian , Zhang Lu , Liu Shanyun , Zhang Hongqi , Yu Xianbin
Published: August 2022

The terahertz (THz) band is expected to become a key technology to meet the ever-increasing traffic demand for future 6G wireless communications, and a lot of efforts have been paid to develop its capacity. However, few studies have been concerned with the transmission security of such ultra-high-speed THz wireless links. In this paper, we comprehensively investigate the physical layer security (PLS) of a THz communication system in the presence of multiple eavesdroppers and beam scattering. The method of moments (MoM) was adopted so that the eavesdroppers’ channel influenced by the PEC can be characterized. To establish a secure link, the traditional beamforming and artificial noise (AN) beamforming were considered as transmission schemes for comparison. For both schemes, we analyzed their secrecy transmission probability (STP) and ergodic secrecy capacity (ESC) in non-colluding and colluding cases, respectively. Numerical results show that eavesdroppers can indeed degrade the secrecy performance by changing the size or the location of the PEC, while the AN beamforming technique can be an effective candidate to counterbalance this adverse effect.
Ti3C2Tx MXene-Polymeric Strain Sensor with Huge Gauge Factor for Body Movement Detection
Authors: Leong Wei Xian Rebecca , Al-Dhahebi Adel Mohammed , Ahmad Mohamad Radzi , Saheed Mohamed Shuaib Mohamed
Published: August 2022

In this work, a composite strain sensor is fabricated by synthesizing MXene and deposition of polypyrrole on top of the flexible electrospun PVDF nanofibers. The fabricated sensor exhibits a conductive network constructed with MXene and polypyrrole of microcracks network structure, demonstrating its strain sensing properties. The presence of these microcracks serves as mechanical weak points, which leads to sensitivity enhancement, while the electrospun fiber substrate act as a cushion for strain loading under large deformations. The as-prepared MXene@Polypyrrole PVDF sensor has a gauge factor range of 78–355 with a sensing range between 0–100%. Besides strain deformations, the sensor can operate in torsional deformation and human motion, indicating the sensor’s potential as a wearable health monitoring device.
Localized Induction Heating of Cu-Sn Layers for Rapid Solid-Liquid Interdiffusion Bonding Based on Miniaturized Coils
Authors: Hofmann Christian , Satwara Maulik , Kroll Martin , Panhale Sushant , Rochala Patrick , Wiemer Maik , Hiller Karla , Kuhn Harald
Published: August 2022

Considering the demand for low temperature bonding in 3D integration and packaging of microelectronic or micromechanical components, this paper presents the development and application of an innovative inductive heating system using micro coils for rapid Cu-Sn solid-liquid interdiffusion (SLID) bonding at chip-level. The design and optimization of the micro coil as well as the analysis of the heating process were carried out by means of finite element method (FEM). The micro coil is a composite material of an aluminum nitride (AlN) carrier substrate and embedded metallic coil conductors. The conductive coil geometry is generated by electroplating of 500 µm thick copper into the AlN carrier. By using the aforementioned micro coil for inductive Cu-Sn SLID bonding, a complete transformation into the thermodynamic stable ε-phase Cu3Sn with an average shear strength of 45.1 N/mm2 could be achieved in 130 s by applying a bond pressure of 3 MPa. In comparison to conventional bonding methods using conduction-based global heating, the presented inductive bonding approach is characterized by combining very high heating rates of about 180 K/s as well as localized heating and efficient cooling of the bond structures. In future, the technology will open new opportunities in the field of wafer-level bonding.
An AI-powered Electronic Nose System with Fingerprint Extraction for Aroma Recognition of Coffee Beans
Authors: Lee Chung-Hong , Chen I-Te , Yang Hsin-Chang , Chen Yenming J.
Published: August 2022

Aroma and taste have long been considered important indicators of quality coffee. Specialty coffee, that is, coffee from a single estate, farm, or village in a coffee-growing region, in particular, has a unique aroma that reflects the coffee-producing region. In order to enable the traceability of coffee origin, in this study we have developed an e-nose system to discriminate the aroma of freshly roasted coffee in different production regions. In the case study, we employed the e-nose system to experiment with various machine learning models for recognizing several collected coffee beans such as coffees from Yirgacheffe and Kona. Additionally, our contribution also includes the development of a method to create an aromatic digital fingerprint of a specific coffee bean to identify its origin. The experimental results show that the developed e-nose system achieves good recognition performance for coffee aroma recognition. The extracted digital fingerprints have great potential to be stored in an extensible coffee aroma database similar to a comprehensive library of specific coffee bean aroma characteristics, for traceability and reconfirmation of their origin.
Human Monkeypox: A Comprehensive Narrative Review and Analysis of the Public Health Implications
Authors: Di Gennaro Francesco , Veronese Nicola , Marotta Claudia , Shin Jae Il , Koyanagi Ai , Silenzi Andrea , Antunes Mario , Saracino Annalisa , Bavaro Davide Fiore , Soysal Pinar , Segala Francesco Vladimiro , Butler Laurie , Milano Eugenio , Barbagallo Mario , Barnett Yvonne , Parris Christopher , Nicastri Emanuele , Pizzol Damiano , Smith Lee
Published: August 2022

Recently, numerous cases of monkeypox were reported from several non-endemic countries in Europe, North America, and Oceania, suggesting an unusual and alarming public health issue, particularly considering that the disease is not directly related to human or animal travels. Attention is currently being drawn to this phenomenon since more than 70% of the global population is no longer vaccinated against smallpox. Indeed, the smallpox vaccination also confers some indirect degree of protection against other poxviruses, including monkeypox. We performed a narrative review to describe the existing literature with regard to monkeypox using the MEDLINE, EMBASE, and Scopus databases. This review aims to provide updated evidence of findings on the epidemiology, clinical features, diagnosis, management, and prevention of monkeypox, also considering the concurrent zoonotic pandemic caused by the COVID-19 coronavirus, SARS-CoV-2.
Immune and Oxidative Response against Sonicated Antigen of Mycoplasma capricolum subspecies capripneumonia—A Causative Agent of Contagious Caprine Pleuropneumonia
Authors: Haq Rather Izhar Ul , Parray Oveas Rafiq , Nazir Qurat Ul Ain , Bhat Riyaz Ahmed , Shah Showkat Ahmad , Kawoosa Majid Shafi , Rabaan Ali A. , Aljeldah Mohammed , Al Shammari Basim R. , Almogbel Mohammed S. , Alharbi Nada , Alrashoudi Reem , Sabour Amal A. , Alaeq Rana A. , Alshiekheid Maha A. , Alshamrani Saleh A. , Albutti Aqel , Alwashmi Ameen S.S. , Dhama Kuldeep , Yatoo Mohd. Iqbal
Published: August 2022

Vaccines are vital for prevention and control of mycoplasma diseases. The exploration of a vaccine candidate for the development of a vaccine is imperative. The present study envisages the evaluation of immune and oxidative response against an adjuvanted, sonicated antigen of Mycoplasma capricolum subsp. capripneumonia in male Angora rabbits (1 year old, 2 kg) divided in four groups, each having six animals. Group 1 was the healthy control and received 1 mL PBS via subcutaneous route. Group 2 was administered 1 mL of saponin-adjuvanted and -sonicated antigen, Group 3 was given 1 mL of montanide ISA 50-adjuvanted and-sonicated antigen, and Group 4 was given 1 mL of standard vaccine via subcutaneous route. Animals were evaluated for cellular and humoral immune response and oxidative parameters at 0, 7, 14, 21, and 28 days of the study. Total leukocytic, neutrophilic, and basophilic counts showed a significant (p < 0.05) increase in vaccinated groups compared to the healthy group on most of the intervals. TNF-α levels were significantly (p < 0.05) higher in the Group 2 than the Group 1 at all the time intervals and more comparable to Group 4 than Group 3. IL-10 levels were significantly (p < 0.05) higher in vaccinated groups compared to the healthy group on days 14, 21, and 28, but were lower in Group 3 than in Group 2 and Group 4. More hypersensitivity as inflammation and histopathological cellular infiltration in the ear was produced in Group 2 and Group 4 than in Group 3. IgG levels were significantly (p < 0.05) higher in Group 2 and Group 4 than in Group 3 on days 14 and 21. Antibody titers were comparatively higher in Group 4, followed by Group 2 and 3, than Group 1. Significantly (p < 0.05) higher oxidant and lower antioxidant values were noted in Group 2 and 4 compared to Group 3 and Group 1 on most of the intervals. The TLC and antibody titer showed increasing trend throughout the trial, whereas TNF-α, IgG, L, M and E started decreasing from day 14, and IL-10, N and B started decreasing from day 21. This study concludes that the saponin-adjuvanted and-sonicated antigen induces comparatively higher immune response than montanide but is associated with oxidative and inflammatory reactions.
Potential for Biological Control of Pythium schmitthenneri Root Rot Disease of Olive Trees (Olea europaea L.) by Antagonistic Bacteria
Authors: Legrifi Ikram , Al Figuigui Jamila , El Hamss Hajar , Lazraq Abderrahim , Belabess Zineb , Tahiri Abdessalem , Amiri Said , Barka Essaid Ait , Lahlali Rachid
Published: August 2022

Several diseases affect the productivity of olive trees, including root rot disease caused by Pythium genera. Chemical fungicides, which are often used to manage this disease, have harmful side effects on humans as well as environmental components. Biological management is a promising control approach that has shown its great potential as an efficient eco-friendly alternative to treating root rot diseases. In the present study, the antagonistic activity of ten bacterial isolates was tested both in vitro and in planta against Pythium schmitthenneri, the causal agent of olive root rot disease. These bacterial isolates belonging to the genera Alcaligenes, Pantoea, Bacillus, Sphingobacterium, and Stenotrophomonas were chosen for their potential antimicrobial effects against many pathogens. Results of the in vitro confrontation bioassay revealed a high reduction of mycelial growth exceeding 80%. The antifungal effect of the volatile organic compounds (VOCs) was observed for all the isolates, with mycelial inhibition rates ranging from 28.37 to 70.32%. Likewise, the bacterial cell-free filtrates showed important inhibition of the mycelial growth of the pathogen. Overall, their efficacy was substantially affected by the nature of the bacterial strains and their modes of action. A greenhouse test was then carried out to validate the in vitro results. Interestingly, two bacterial isolates, Alcaligenes faecalis ACBC1 and Bacillus amyloliquefaciens SF14, were the most successful in managing the disease. Our findings suggested that these two antagonistic bacterial isolates have promising potential as biocontrol agents of olive root rot disease.