bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of Complexity of Numerical Models of a Strengthened Timber Beam
Authors: Szczecina Michał
Published: May 2023

Laboratory research of wood–CFRP (carbon fiber reinforced polymer) structural elements, especially beams, is a scientific issue undertaken by many scientists. Research is often complemented with numerical analysis with the use of complex finite element method (FEM) models. Modern FEM software offers models that can reproduce such properties and phenomena as orthotropy and plasticity of wood and CFRP, delamination and mechanical behavior of adhesive layers, and damage of a strengthened element. The author of the paper reproduces numerical laboratory research of a four-point bending test of a glulam beam strengthened with CFRP tape. The main goal of the numerical research is an analysis of how the complexity of the FEM model influences the results of calculations, especially stress, deflection, and bearing capacity of the glulam beam. In some cases, a simpler model can be satisfactory, especially for a structural engineer, who takes into account serviceability limit states (permissible deflection of a structural member) and assumes that stress should not exceed the yield stress of timber.
Utilizing ANN for Predicting the Cauchy Stress and Lateral Stretch of Random Elastomeric Foams under Uniaxial Loading
Authors: Liu Zhentao , Wang Chaoyang , Lai Zhenyu , Guo Zikang , Chen Liang , Zhang Kai , Yi Yong
Published: May 2023

As a result of their cell structures, elastomeric foams exhibit high compressibility and are frequently used as buffer cushions in energy absorption. Foam pads between two surfaces typically withstand uniaxial loads. In this paper, we considered the effects of porosity and cell size on the mechanical behavior of random elastomeric foams, and proposed a constitutive model based on an artificial neural network (ANN). Uniform cell size distribution was used to represent monodisperse foam. The constitutive relationship between Cauchy stress and the four input variables of axial stretch λU, lateral stretch λL, porosity φ, and cell size θ was given by con-ANN. The mechanical responses of 500 different foam structures (20% < φ < 60%, 0.1 mm < θ < 0.5 mm) under compression and tension loads (0.4 < λU < 3) were simulated, and a dataset containing 100,000 samples was constructed. We also introduced a pre-ANN to predict lateral stretch to address the issue of missing lateral strain data in practical applications. By combining physical experience, we chose appropriate input forms and activation functions to improve ANN’s extrapolation capability. The results showed that pre-ANN and con-ANN could provide reasonable predictions for λU outside the dataset. We can obtain accurate lateral stretch and axial stress predictions from two ANNs. The porosity affects the stress and λL, while the cell size only affects the stress during foam compression.
Fabrication and Characterization of Eco-Friendly Thin Films as Potential Optical Absorbers for Efficient Multi-Functional Opto-(Electronic) and Solar Cell Applications
Authors: El-Newehy Mohamed H. , El-Mahalawy Ahmed M. , Thamer Badr M. , Moydeen Abdul Hameed Meera
Published: May 2023

The necessity for reliable and efficient multifunctional optical and optoelectronic devices is always calling for the exploration of new fertile materials for this purpose. This study leverages the exploitation of dyed environmentally friendly biopolymeric thin films as a potential optical absorber in the development of multifunctional opto-(electronic) and solar cell applications. Uniform, stable thin films of dyed chitosan were prepared using a spin-coating approach. The molecular interactivity between the chitosan matrix and all the additive organic dyes was evaluated using FTIR measurements. The color variations were assessed using chromaticity (CIE) measurements. The optical properties of films were inspected using the measured UV-vis-NIR transmission and reflection spectra. The values of the energy gap and Urbach energy as well as the electronic parameters and nonlinear optical parameters of films were estimated. The prepared films were exploited for laser shielding as an attenuated laser cut-off material. In addition, the performance of the prepared thin films as an absorbing organic layer with silicon in an organic/inorganic heterojunction architecture for photosensing and solar energy conversion applicability was studied. The current-voltage relation under dark and illumination declared the suitability of this architecture in terms of responsivity and specific detectivity values for efficient light sensing applications. The suitability of such films for solar cell fabrications is due to some dyed films achieving open-circuit voltage and short-circuit current values, where Saf-dyed films achieved the highest Voc (302 mV) while MV-dyed films achieved the highest Jsc (0.005 mA/cm2). Finally, based on all the obtained characterization results, the engineered natural cost-effective dyed films are considered potential active materials for a wide range of optical and optoelectronic applications.
Prediction of Primary Dendrite Arm Spacing of the Inconel 718 Deposition Layer by Laser Cladding Based on a Multi-Scale Simulation
Authors: Jin Zhibo , Kong Xiangwei , Ma Liang , Dong Jun , Li Xiaoting
Published: May 2023

Primary dendrite arm spacing (PDAS) is a crucial microstructural feature in nickel-based superalloys produced by laser cladding. In order to investigate the effects of process parameters on PDAS, a multi-scale model that integrates a 3D transient heat and mass transfer model with a quantitative phase-field model was proposed to simulate the dendritic growth behavior in the molten pool for laser cladding Inconel 718. The values of temperature gradient (G) and solidification rate (R) at the S/L interface of the molten pool under different process conditions were obtained by multi-scale simulation and used as input for the quantitative phase field model. The influence of process parameters on microstructure morphology in the deposition layer was analyzed. The result shows that the dendrite morphology is in good agreement with the experimental result under varying laser power (P) and scanning velocity (V). PDAS was found to be more sensitive to changes in laser scanning velocity, and as the scanning velocity decreased from 12 mm/s to 4 mm/s, the PDAS increased by 197% when the laser power was 1500 W. Furthermore, smaller PDAS can be achieved by combining higher scanning velocity with lower laser power.
Identification of the Domain Structure Defects of a Radially Magnetized Rubber–Ferritic Conglomerate
Authors: Popowska Karolina , Gontarz Szymon , Szulim Przemysław
Published: May 2023

Modern solutions in materials engineering are designed not just for the improvement in the mechanical or electromagnetic properties of materials but also to begin to fulfill specific functional roles. A good example of such a modern solution is a composite made of steel and rubber–ferritic conglomerate, which is the research object of the article. The composite, when properly magnetized, can act as a magnetic encoder ring for reading the angular displacement, speed, or acceleration parameter. The paper addresses the problem of identifying and assessing the defects of the magnetic encoder ring domain structure in the form of a radially magnetized ring. It discusses the essential types of the ring’s degradation, such as mechanical, thermal, and magnetic, and presents problems related to the identification of emerging defects. The conducted research allows a better understanding of the degradation process in the context of magnetic encoder ring reliability. Based on the conducted research on the proposed test stand, it is possible to track the progressive degradation related to each effect. These degradation case analyses consider both quantitative and qualitative changes in the encoder ring’s domain structure. The proposed parameters show the possibilities and perspectives for detecting the ring’s defects in the early stage of its development. Solely such an approach will allow for proper exploitation and extension of the applicability of this kind of ‘intelligent material’. Additionally, the developed parameters for the encoder ring’s defects detection can support the progress of rapidly evolving methods for diagnosing mechanical systems based on a signal from such an element.
Simulation and Experiment on the Low-Velocity Impact Response of Flax Fabric Reinforced Composites
Authors: Xiong Xiaoshuang , Wang Zisheng , Zhang Zihao , Li Qiaomin , Shen Chen , Fan Fei , Li Xiang , Chen Mingzhang
Published: May 2023

Natural fiber reinforced composites are increasingly used to fabricate structural components prone to suffering low-velocity impacts. The low-velocity impact response of flax fabric reinforced composites under different impact energies is experimentally studied and numerically simulated. A multi-scale finite element analysis strategy for the progressive damage prediction of flax fabric reinforced composites is developed. Micro- and meso-scale analyses are conducted to predict the effective properties of the woven unit cell. Macro-scale analysis is carried out subsequently to predict the impact response of composite laminates using the results of micro- and meso-scale analyses as inputs. Simulation results and experimental results both show that most of the impact energy is absorbed by the specimens when the impact energy is lower than 4 J, and the absorption ratio of impact energy slightly increases with the increase in impact energy. On the contrary, a dramatic decrease occurs in the absorption ratio when the impact energy is 6 J, due to the severe damage to the specimen. In addition, simulation results indicate that matrix shear damage and interlaminar damage are the primary failure modes of composites under high impact energy. The numerical results of impact force, absorbed energy, and damage morphologies on both sides for all specimens show good agreement with the experimental results.
Provision of Rational Parameters for the Turning Mode of Small-Sized Parts Made of the 29 NK Alloy and Beryllium Bronze for Subsequent Thermal Pulse Deburring
Authors: Martyushev Nikita V. , Bublik Dmitriy A. , Kukartsev Vladislav V. , Tynchenko Vadim S. , Klyuev Roman V. , Tynchenko Yadviga A. , Karlina Yuliya I.
Published: May 2023

The increase in the share of physical and technical processing methods in the arsenal of deburring technologies used in modern production is associated both with the use of difficult-to-machine materials, such as beryllium bronze and the 29 NK alloy, and with the need to solve technological problems for the production of small-sized products with hard-to-reach surfaces. The aim of the study is to improve the processes of blade processing of small-sized parts made of beryllium bronze and the 29 NK alloy to provide rational conditions for thermal pulse deburring. Surface samples were experimentally obtained after turning in different modes on a CITIZEN CINCOM K16E-VII automatic lathe equipped with an Applitec micromechanics tool. The surface quality and burr characteristics were examined using a JEOL JIB-Z4500 electron microscope and a ContourGT-K optical profilometer. The program Statistica 6 allowed processing of the results. The relationship between the parameters of the turning mode and the thickness of the root of the burrs formed on the machined surface, the limitation of which is one of the conditions for the application of the thermal pulse method, was established. The obtained empirical regression dependencies establish a rational range of cutting mode parameters, and the implementation of the formulated recommendations for setting blade modes ensures deburring by the thermal pulse method in compliance with the requirements of drawing under maximum processing performance.
Influence of Disinfection Methods on Cinematographic Film
Authors: Knotek Vítězslav , Ďurovič Michal , Dolenský Bohumil , Hrdlička Zdeněk
Published: May 2023

Microbiological contamination of cinematographic films can cause damage and loss of image information. A large part of the films is made with the base of cellulose triacetate, which has been used from the 1940s until today. Cellulose triacetate is relatively resistant to common organic solvents, but some types of microorganisms can contribute to its faster degradation. In this work, we tested four types of disinfectants suitable for mass disinfection and sufficiently effective against various types of microorganisms. Butanol vapours, a commercial mixture of alcohols (Bacillol® AF), Septonex® (an aqueous solution of [1-(ethoxycarbonyl)pentadecyl] trimethylammonium bromide) and ethylene oxide applied as a gas mixed with carbon dioxide were tested. Samples of a commercial film made of cellulose triacetate were disinfected. The samples were aged for 56 days at 70 °C and 55% RH. Changes in optical, mechanical and chemical properties were studied. None of the disinfectants affected the change in the degree of substitution. For samples disinfected with Bacillol® AF (alcohol mixture), part of the plasticiser (triphenyl phosphate) was extracted and the intrinsic viscosity of the cellulose triacetate solution was reduced after ageing. A slight decrease in intrinsic viscosity also occurred after disinfection with ethylene oxide. Compared to the non-disinfected samples, butanol vapours and Septonex® appear to be the most gentle disinfectants for the cellulose triacetate film base, within the studied parameters.
Cysteine as an Alternative Eco-Friendly Corrosion Inhibitor for Absorption-Based Carbon Capture Plants
Authors: Habibullah Mohamed Ishaq , Veawab Amornvadee
Published: May 2023

Inorganic corrosion inhibitors are commonly applied to mitigate severe corrosion in absorption-based carbon capture plants. They are, however, not environmentally friendly, posing a health risk, harming the environment, and making chemical handling and disposal costly. Therefore, this study evaluated the corrosion inhibition performance of an amino acid, namely cysteine, with the aim of providing an eco-friendly alternative to the commercial inorganic corrosion inhibitors. Electrochemical and weight loss corrosion measurements showed that cysteine was effective in protecting carbon steel at all process operating conditions. At 80 °C, a 500 ppm cysteine could provide up to 83% and 99% inhibition efficiency under static and dynamic flow conditions, respectively. Its inhibition efficiency could be improved when the cysteine concentration, solution temperature, and flow condition were altered. Cysteine was an anodic corrosion inhibitor and underwent spontaneous, endothermic, and combined physical and chemical adsorption that followed the Langmuir adsorption isotherm model. The quantum chemical analysis indicated that cysteine had a high reactivity with metal surfaces due to its low energy gap and high dipole moment. The EDX analysis revealed a significant sulphur content on the metal substrate, indicating that cysteine’s mercapto group played an integral role in forming an effective adsorption layer on the metal interface.
Recent Progress on Creep Properties of ODS FeCrAl Alloys for Advanced Reactors
Authors: Jia Haodong , Wang Yingjie , Wang You , Han Lu , Zhang Yujuan , Zhou Zhangjian
Published: May 2023

In order to meet the growing energy demand, more environmentally friendly and efficient GEN-IV reactors have emerged. Additionally, nuclear structural materials need larger more safety margins for accident scenarios as a result of the Fukushima accident. In order to extend the failure time and lessen the effect of accidents, this design method for accident-tolerant fuel materials calls for cladding materials to maintain good corrosion resistance and mechanical properties during a beyond design basis accident (BDBA). Accidents involving nuclear reactors would undoubtedly result in higher temperatures, which would make it much harder for materials to withstand corrosion. Oxide dispersion strengthened (ODS) FeCrAl alloys have shown promise as candidate materials because of their extraordinarily slow reaction rates under high-temperature steam. However, the addition of the Al element renders the alloy’s high-temperature mechanical properties insufficient. In particular, studies on the alloy’s creep properties are extremely rare, despite the fact that the creep properties are crucial in the real service environment. Therefore, this paper focuses on the creep properties of ODS FeCrAl alloy, summarizes and analyzes the research results of this material, and provides a reference for future research and applications.
Production of AC from Bamboo, Orange, and Paulownia Waste—Influence of Activation Gas and Biomass Maturation
Authors: Grima-Olmedo Carlos , Valle-Falcones Laura M. , Galindo Dulce Gómez-Limón , Esparver Ramón Rodríguez-Pons
Published: May 2023

The production of agricultural waste is associated with environmental problems and risks to public health. The general interest demands, as an ecological alternative, the proper management of waste generated by industrial activity through its transformation into value-added products. Carbonization/activation (2 h/2 h) at 700 °C in a vertical furnace (20 K/min), to produce biochar and activated carbon (AC) from bamboo, orange, and paulownia residue, was carried out in a laboratory facility with physical activation by CO2 and steam. The characterization of the carbonaceous material obtained was based on the determination of the N2 adsorption–desorption isotherms at 77 K, the specific surface area with the BET procedure, and its internal structure by means of SEM images. The BET surface area values obtained as a function of the CO2/steam agent used were 911/1182 m2/g, 248/388 m2/g, and 800/1166 m2/g for bamboo, orange, and paulownia, respectively. The range of variation of porosity in paulownia residue generated after steam activation was 485–1166 m2/g, varying depending on the degree of maturity of the biomass used. Research has shown that both the type of activation agent used to produce AC and the degree of plant maturation of the precursor residue affect the quality and characteristics of the final product.
Self-Healing and Self-Adhesive Substrate-Free Tattoo Electrode
Authors: Chen Yuanfen , Yuan Xiaoming , Li Chunlin , Ruan Ruicheng , You Hui
Published: May 2023

Electronic tattoos have great potential application in the biomedical field; moreover, the substrate-free electronic tattoo offers better comfortability and conformal contact. However, the substrate-free electronic tattoo is more prone to malfunction, including fall off and fracture. In this paper, a self-healing and self-adhesive substate-free tattoo based on PEDOT: PSS is studied and reported. The dry composite electrode will turn into self-healing material while it transforms into hydrogel, and a cut with a width up to 24 μm could be healed in 1 s. In terms of adhesion performance, the substrate-free electrode can hang a 28.2 g weight by a contact area of 8 mm × 8 mm. Additionally, the substate-free electrode could maintain fully conformal contact with porcine skin in 15 days by its self-adhesiveness. When applied as a substrate-free tattoo, the contact impedance and ECG signal measurement performance before and after self-healing are almost the same. At a frequency of 10 Hz, the contact impedance of the undamaged electrode, healed electrode, and Ag/AgCl gel electrode are 32.2 kΩ, 39.2 kΩ, and 62.9 kΩ, respectively. In addition, the ECG signals measured by the undamaged electrode and healed electrode are comparable to that of Ag/AgCl electrode. The self-healing and self-adhesive substrate-free tattoo electrode reported here has broad application in health monitoring.
Evaluation of Early Concrete Damage Caused by Chloride-Induced Steel Corrosion Using a Deep Learning Approach Based on RNN for Ultrasonic Pulse Waves
Authors: Mukhti Julfikhsan Ahmad , Robles Kevin Paolo V. , Lee Keon-Ho , Kee Seong-Hoon
Published: May 2023

The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurements as an early detection method for corrosion-induced concrete damages. A series of experiments are conducted using concrete cube specimens, at a size of 200 mm, with a reinforcing steel bar (rebar) embedded in the center. The main variables include the water-to-cement ratio of the concrete (0.4, 0.5, and 0.6), the diameter of the rebar (10 mm, 13 mm, 19 mm, and 22 mm), and the corrosion level (ranging from 0% to 20% depending on rebar diameter). The impressed current technique is used to accelerate corrosion of rebars in concrete immersed in a 3% NaCl solution. Ultrasonic pulse waves are collected from the concrete specimens using a pair of 50 kHz P-wave transducers in the through-transmission configuration before and after the accelerated corrosion test. Deep learning techniques, specifically three recurrent neural network (RNN) models (long short-term memory, gated recurrent unit, and bidirectional long short-term memory), are utilized to develop a classification model for early detection of concrete damage due to rebar corrosion. The performance of the RNN models is compared to conventional ultrasonic testing parameters, namely ultrasonic pulse velocity and signal consistency. The results demonstrate that the RNN method outperforms the other two methods. Among the RNN methods, the bidirectional long short-term memory RNN model had the best performance, achieving an accuracy of 74% and a Cohen’s kappa coefficient of 0.48. This study establishes the potentiality of utilizing deep learning of ultrasonic pulse waves with RNN models for early detection of concrete damage associated with steel corrosion.
Design and Microscale Fabrication of Negative Poisson’s Ratio Lattice Structure Based on Multi-Scale Topology Optimization
Authors: An Ran , Ge Xueyuan , Wang Miaohui
Published: May 2023

The current design of negative Poisson’s ratio lattice structures is mainly forward-looking and predominantly dependent on several known deformation patterns. To automate the generation of structures with programmable Poisson’s ratio, the study utilized the energy homogenization method and the Solid Isotropic Material with Penalization (SIMP) method to establish an optimization model for negative Poisson’s ratio. By proposing a relaxed objective function and eliminating damping in the Optimality Criteria (OC) method, the study achieves the automatic evolution of negative Poisson’s ratio programmable lattice unit cells, with the lowest Poisson’s ratio achieving −0.5367, and an equivalent elastic matrix is derived. The iterative process’s efficiency is comparable to that of commercial software, with a maximum iteration time of 300 s, enabling the prompt identification of fundamental configurations. To validate the method’s effectiveness, finite element analysis was performed on four tubular structures, revealing evident tension–compression deformation patterns. Moreover, the microscale selective laser melting was used to successfully prepare multiple sets of tubular samples made from 316L stainless steel, each with a height of 5 mm. Quasi-static compression experiments showed negative Poisson’s ratio effects and buckling forms that align with finite element analysis results, providing valuable insights for industry applications.
Overview of Selective Laser Melting for Industry 5.0: Toward Customizable, Sustainable, and Human-Centric Technologies
Authors: Rahmani Ramin , Karimi Javad , Resende Pedro R. , Abrantes João C. C. , Lopes Sérgio I.
Published: May 2023

Industry 5.0 combines automation/digitalization with human capabilities to create a more intuitive, interactive, and sustainable working environment. Additive manufacturing, widely known as 3D printing, is a key technology used to increase customization and efficiency and reduce waste in manufacturing. Industry 5.0 enables manufacturers to create environmentally sustainable and consumer-centric products. However, there is a lack of studies on the introduction of AM technologies to Industry 5.0. The present study investigates the use of additive manufacturing for the fabrication of metallic parts/assemblies and the correlation between human-centric technologies, additive manufacturing, and environmental sustainability. Effective communication between these components is the key to achieving the goals of Industry 5.0, and the important parameters are shown in this article. The present work is focused on an overview and the impact of the futuristic subdivision of additive manufacturing applied to the fabrication of metallic parts/assemblies, more specifically, the 3D printing of challenging alloys or composites (such as copper alloys and/or composites with hard particles).
High-Performance Vernier Machines with Halbach Array Permanent Magnets for Direct Drive Applications
Authors: Allahyari Arash , Bostanci Emine , Mahmoudi Amin
Published: May 2023

This paper investigates the performance enhancements of permanent magnet Vernier machines (PMVMs) that can be achieved using a new structure of Halbach array permanent magnets (HAPMs) for a direct-drive motorcycle application. To start with, size and design specifications of the electric machine are determined based on the assumed acceleration and drive cycle performance of a motorcycle. Then, five-segment Halbach array permanent magnet Vernier machines (HAPMVMs) with two different slot/pole combinations (24 s/44 p and 12 s/20 p) are suggested and optimized to achieve a high torque density with an acceptable power factor while maintaining a low torque ripple. Two selected designs from optimizations are investigated in the full speed range considering power factor and efficiency maps. Consequently, in order to demonstrate the effectiveness of the proposed five-HAPM structure, the same optimization methods are repeated with three-segment HAPMs as well as with single-piece PMs. The comparisons show a great enhancement in torque and power factor achieved with the use of five HAPMs. For instance, for 22 s/44 p topology, generated torque doubles with the use of five-segment PMs compared to single-segment PMs. Finally, the harmonics of magnetic flux density in the airgap of PMVMs and HAPMVMs are compared and investigated to reveal the reasons behind the superiority of VMs with HAPMs.
Neuron-by-Neuron Quantization for Efficient Low-Bit QNN Training
Authors: Sher Artem , Trusov Anton , Limonova Elena , Nikolaev Dmitry , Arlazarov Vladimir V.
Published: May 2023

Quantized neural networks (QNNs) are widely used to achieve computationally efficient solutions to recognition problems. Overall, eight-bit QNNs have almost the same accuracy as full-precision networks, but working several times faster. However, the networks with lower quantization levels demonstrate inferior accuracy in comparison to their classical analogs. To solve this issue, a number of quantization-aware training (QAT) approaches were proposed. In this paper, we study QAT approaches for two- to eight-bit linear quantization schemes and propose a new combined QAT approach: neuron-by-neuron quantization with straight-through estimator (STE) gradient forwarding. It is suitable for quantizations with two- to eight-bit widths and eliminates significant accuracy drops during training, which results in better accuracy of the final QNN. We experimentally evaluate our approach on CIFAR-10 and ImageNet classification and show that it is comparable to other approaches for four to eight bits and outperforms some of them for two to three bits while being easier to implement. For example, the proposed approach to three-bit quantization of the CIFAR-10 dataset results in 73.2% accuracy, while baseline direct and layer-by-layer result in 71.4% and 67.2% accuracy, respectively. The results for two-bit quantization for ResNet18 on the ImageNet dataset are 63.69% for our approach and 61.55% for the direct baseline.
SlowFast Multimodality Compensation Fusion Swin Transformer Networks for RGB-D Action Recognition
Authors: Xiao Xiongjiang , Ren Ziliang , Li Huan , Wei Wenhong , Yang Zhiyong , Yang Huaide
Published: May 2023

RGB-D-based technology combines the advantages of RGB and depth sequences which can effectively recognize human actions in different environments. However, the spatio-temporal information between different modalities is difficult to effectively learn from each other. To enhance the information exchange between different modalities, we introduce a SlowFast multimodality compensation block (SFMCB) which is designed to extract compensation features. Concretely, the SFMCB fuses features from two independent pathways with different frame rates into a single convolutional neural network to achieve performance gains for the model. Furthermore, we explore two fusion schemes to combine the feature from two independent pathways with different frame rates. To facilitate the learning of features from independent multiple pathways, multiple loss functions are utilized for joint optimization. To evaluate the effectiveness of our proposed architecture, we conducted experiments on four challenging datasets: NTU RGB+D 60, NTU RGB+D 120, THU-READ, and PKU-MMD. Experimental results demonstrate the effectiveness of our proposed model, which utilizes the SFMCB mechanism to capture complementary features of multimodal inputs.
What Have We Not Learned from the Convergence Debate?
Authors: Leonida Leone
Published: May 2023

We argue that the alternative hypotheses about cross-country convergence dynamics, namely the Conditional Convergence Hypothesis, Absolute Convergence Hypothesis, and Club Convergence hypothesis, build upon different modelling choices and answer different empirical questions. Hence, results favoring one hypothesis are not necessarily evidence against the other hypotheses. We apply several modelling approaches to a sample of world economies to support our argument, and present empirical evidence that yields controversial conclusions if the hypotheses about convergence are taken as competing. However, the controversy disappears as we note that there are neither theoretical nor empirical reasons to take evidence in favor of the Absolute Convergence Hypothesis as necessarily being against the Club Convergence Hypothesis, and vice versa. We present results for the world economies where the two processes co-exist. We conclude by arguing that when analysis is conducted at the regional level, the two processes are more likely to co-exist because regions share the same institutions, culture, natural resources, and other fundamental causes of growth. Consequently, a test for convergence that studies whether clusters converge or diverge once eventually emerged in the distribution of incomes is still needed. Finally, we argue that to study convergence dynamics, it is necessary to model relationships between economies.
Log-Linear-Based Logic Mining with Multi-Discrete Hopfield Neural Network
Authors: Manoharam Gaeithry , Kasihmuddin Mohd Shareduwan Mohd , Antony Siti Noor Farwina Mohamad Anwar , Romli Nurul Atiqah , Rusdi Nur ‘Afifah , Abdeen Suad , Mansor Mohd. Asyraf
Published: May 2023

Choosing the best attribute from a dataset is a crucial step in effective logic mining since it has the greatest impact on improving the performance of the induced logic. This can be achieved by removing any irrelevant attributes that could become a logical rule. Numerous strategies are available in the literature to address this issue. However, these approaches only consider low-order logical rules, which limit the logical connection in the clause. Even though some methods produce excellent performance metrics, incorporating optimal higher-order logical rules into logic mining is challenging due to the large number of attributes involved. Furthermore, suboptimal logical rules are trained on an ineffective discrete Hopfield neural network, which leads to suboptimal induced logic. In this paper, we propose higher-order logic mining incorporating a log-linear analysis during the pre-processing phase, the multi-unit 3-satisfiability-based reverse analysis with a log-linear approach. The proposed logic mining also integrates a multi-unit discrete Hopfield neural network to ensure that each 3-satisfiability logic is learned separately. In this context, our proposed logic mining employs three unique optimization layers to improve the final induced logic. Extensive experiments are conducted on 15 real-life datasets from various fields of study. The experimental results demonstrated that our proposed logic mining method outperforms state-of-the-art methods in terms of widely used performance metrics.
Authenticating q-Gram-Based Similarity Search Results for Outsourced String Databases
Authors: Yang Liangyong , Ye Haizhou , Liu Xuyang , Mao Yijun , Zhang Jilian
Published: May 2023

Approximate string searches have been widely applied in many fields, such as bioinformatics, text retrieval, search engines, and location-based services (LBS). However, the approximate string search results from third-party servers may be incorrect due to the possibility of malicious third parties or compromised servers. In this paper, we design an authenticated index structure (AIS) for string databases, which is based on the Merkle hash tree (MHT) method and the q-gram inverted index. Our AIS can facilitate verification object (VO) construction for approximate string searches with edit distance thresholds. We design an efficient algorithm named GS2 for VO construction at the server side and search result verification at the user side. We also introduce an optimization method called GS2-opt that can reduce VO size dramatically. Finally, we conduct extensive experiments on real datasets to show that our proposed methods are efficient and promising.
Race: How the Post-Genomic Era Has Unmasked a Misconception Promoted by Healthcare
Authors: Schaare Donna , Abenavoli Ludovico , Boccuto Luigi
Published: May 2023

The term “race” has been employed to categorize human beings into distinct groups based on some perceived biological distinctions. This concept was debunked with the completion of the Human Genome Project and its revolutionary findings that all humans are >99% genetically identical, subsequently making the term “race” obsolete. Unfortunately, the previous misconception is being propagated by the continued use of the term to capture demographic information in healthcare in an attempt to improve equity. This paper seeks to review the history of the term “race”, analyze the current policy, and discuss its limitations. It is important to note that our analysis was exclusively focused on the United States healthcare system and the Affordable Care Act; as such, it may not reflect other regions’ policies, including those in Africa, Asia, and the Middle East. However, we feel that this policy analysis may serve as a model to recommend alterations that mirror the post-genomic era. The need for this policy change was recently highlighted in the 2022 ASHG presidential address, One Human Race: Billions of Genomes, and will reflect the knowledge gleaned by the scientific community through the conclusions of the Human Genome Project.
Gene Expression Comparison between Alcohol-Exposed versus Not Exposed Pancreatic Ductal Adenocarcinoma Patients Reveals a Peculiar TGFβ-Related Phenotype: An Exploratory Analysis
Authors: Doronzo Antonio , Porcelli Letizia , Marziliano Donatello , Inglese Gianfranco , Argentiero Antonella , Azzariti Amalia , Solimando Antonio Giovanni
Published: May 2023

Background: Over the past few decades, there has been much debate and research into the link between alcohol consumption and the development and progression of pancreatic ductal adenocarcinoma (PDAC). Objectives: To contribute to the ongoing discussion and gain further insights into this topic, our study analysed the gene expression differences in PDAC patients based on their alcohol consumption history. Methods: To this end, we interrogated a large publicly available dataset. We next validated our findings in vitro. Results: Our findings revealed that patients with a history of alcohol consumption showed significant enrichment in the TGFβ-pathway: a signaling pathway implicated in cancer development and tumor progression. Specifically, our bioinformatic dissection of gene expression differences in 171 patients with PDAC showed that those who had consumed alcohol had higher levels of TGFβ-related genes. Moreover, we validated the role of the TGFβ pathway as one of the molecular drivers in producing massive stroma, a hallmark feature of PDAC, in patients with a history of alcohol consumption. This suggests that inhibition of the TGFβ pathway could serve as a novel therapeutic target for PDAC patients with a history of alcohol consumption and lead to increased sensitivity to chemotherapy. Our study provides valuable insights into the molecular mechanisms underlying the link between alcohol consumption and PDAC progression. Conclusions: Our findings highlight the potential significance of the TGFβ pathway as a therapeutic target. The development of TGFβ-inhibitors may pave the way for developing more effective treatment strategies for PDAC patients with a history of alcohol consumption.
Novel Approach to Landfill Wastewater Treatment Fouling Mitigation: Air Gap Membrane Distillation with Tin Sulfide-Coated PTFE Membrane
Authors: Khan Abdulaziz , Ibrar Ibrar , Mirdad Abeer , Al-Juboori Raed A. , Deka Priyamjeet , Subbiah Senthilmurugan , Altaee Ali
Published: May 2023

This study addressed the fouling issue in membrane distillation (M.D.) technology, a promising method for water purification and wastewater reclamation. To enhance the anti-fouling properties of the M.D. membrane, a tin sulfide (TS) coating onto polytetrafluoroethylene (PTFE) was proposed and evaluated with air gap membrane distillation (AGMD) using landfill leachate wastewater at high recovery rates (80% and 90%). The presence of TS on the membrane surface was confirmed using various techniques, such as Field Emission Scanning Electron Microscopy (FE-SEM), Fourier Transform Infrared Spectroscopy (FT-IR), Energy Dispersive Spectroscopy (EDS), contact angle measurement, and porosity analysis. The results indicated the TS-PTFE membrane exhibited better anti-fouling properties than the pristine PTFE membrane, and its fouling factors (FFs) were 10.4–13.1% compared to 14.4–16.5% for the PTFE membrane. The fouling was attributed to pore blockage and cake formation of carbonous and nitrogenous compounds. The study also found that physical cleaning with deionized (DI) water effectively restored the water flux, with more than 97% recovered for the TS-PTFE membrane. Additionally, the TS-PTFE membrane showed better water flux and product quality at 55 °C and excellent stability in maintaining the contact angle over time compared to the PTFE membrane.
Performance Enhancement of Ce0.8Sm0.2O1.9-Supported SOFC by Electrophoretic Formation of Modifying BaCe0.8Sm0.2O3 and Ce0.8Sm0.1Pr0.1O1.9 Layers
Authors: Pikalova Elena , Kalinina Elena
Published: May 2023

The strategy to increase the performance of the single solid oxide fuel cell (SOFC) with a supporting membrane of Ce0.8Sm0.2O1.9 (SDC) electrolyte has been implemented in this study by introducing a thin anode barrier layer of the BaCe0.8Sm0.2O3 + 1 wt% CuO (BCS-CuO) electrolyte and, additionally, a modifying layer of a Ce0.8Sm0.1Pr0.1O1.9 (PSDC) electrolyte. The method of electrophoretic deposition (EPD) is used to form thin electrolyte layers on a dense supporting membrane. The electrical conductivity of the SDC substrate surface is achieved by the synthesis of a conductive polypyrrole sublayer. The kinetic parameters of the EPD process from the PSDC suspension are studied. The volt-ampere characteristics and power output of the obtained SOFC cells with the PSDC modifying layer on the cathode side and the BCS-CuO blocking layer on the anode side (BCS-CuO/SDC/PSDC) and with a BCS-CuO blocking layer on the anode side (BCS-CuO/SDC) and oxide electrodes have been studied. The effect of increasing the power output of the cell with the BCS-CuO/SDC/PSDC electrolyte membrane due to a decrease in the ohmic and polarization resistances of the cell is demonstrated. The approaches developed in this work can be applied to the development of SOFCs with both supporting and thin-film MIEC electrolyte membranes.
Development of High-Performance Hydrogen-Air Fuel Cell with Flourine-Free Sulfonated Co-Polynaphthoyleneimide Membrane
Authors: Zavorotnaya Ulyana M. , Ponomarev Igor I. , Volkova Yulia A. , Sinitsyn Vitaly V.
Published: May 2023

This paper presents research on the technological development of hydrogen-air fuel cells with high output power characteristics using fluorine-free co-polynaphtoyleneimide (co-PNIS) membranes. It is found that the optimal operating temperature of a fuel cell based on a co-PNIS membrane with the hydrophilic/hydrophobic blocks = 70/30 composition is in the range of 60–65 °C. The maximum output power of a membrane-electrode assembly (MEA), created according to the developed technology, is 535 mW/cm2, and the working power (at the cell voltage of 0.6 V) is 415 mW/cm2. A comparison with similar characteristics of MEAs based on a commercial Nafion 212 membrane shows that the values of operating performance are almost the same, and the maximum MEA output power of a fluorine-free membrane is only ~20% lower. It was concluded that the developed technology allows one to create competitive fuel cells based on a fluorine-free, cost-effective co-polynaphthoyleneimide membrane.
Increasing Hardness and Wear Resistance of Austenitic Stainless Steel Surface by Anodic Plasma Electrolytic Treatment
Authors: Kusmanov Sergei , Mukhacheva Tatiana , Tambovskiy Ivan , Naumov Alexander , Belov Roman , Sokova Ekaterina , Kusmanova Irina
Published: May 2023

The results of modifying the surface of austenitic stainless steel by anodic plasma electrolytic treatment are presented. Surface treatment was carried out in aqueous electrolytes based on ammonium chloride (10%) with the addition of ammonia (5%) as a source of nitrogen (for nitriding), boric acid (3%) as a source of boron (for boriding) or glycerin (10%) as a carbon source (for carburizing). Morphology, surface roughness, phase composition and microhardness of the diffusion layers in addition to the tribological properties were studied. The influence of physicochemical processes during the anodic treatment of the features of the formation of the modified surface and its operational properties are shown. The study revealed the smoothing of irregularities and the reduction in surface roughness during anodic plasma electrolytic treatment due to electrochemical dissolution. An increase in the hardness of the nitrided layers to 1450 HV with a thickness of up to 20–25 μm was found due to the formation of iron nitrides and iron-chromium carbides with a 3.7-fold decrease in roughness accompanied by an increase in wear resistance by 2 orders. The carburizing of the steel surface leads to a smaller increase in hardness (up to 700 HV) but a greater thickness of the hardened layer (up to 80 μm) due to the formation of chromium carbides and a solid solution of carbon. The roughness and wear resistance of the carburized surface change are approximately the same values as after nitriding. As a result of the boriding of the austenitic stainless steel, there is no hardening of the surface, but, at the same time, there is a decrease in roughness and an increase in wear resistance on the surface. It has been established that frictional bonds in the friction process are destroyed after all types of processing as a result of the plastic displacement of the counter body material. The type of wear can be characterized as fatigue wear with boundary friction and plastic contact. The correlation of the friction coefficient with the Kragelsky–Kombalov criterion, a generalized dimensionless criterion of surface roughness, is shown.
Insight into the Influence of Alloying Elements on the Elastic Properties and Strengthening of Copper: A High-Throughput First-Principles Calculations
Authors: Zhang Jinhao , Zhang Youcheng , Wang Aiqin , Liang Tingting , Mao Zhiping , Su Bo , Li Haisheng , Xie Jingpei
Published: May 2023

In this work, using the high-throughput density functional theory calculation method, the influence of 36 alloying elements on the elastic properties of FCC-Cu was systematically studied, and based on the Labusch model, a linear relationship was fitted between the composition and lattice parameters, and the shear modulus. The solid solution strengthening behavior brought about by alloying was studied quantitatively. The results showed that most alloying elements have solid solution potentiality in copper. The change in the elastic modulus and the strengthening effect of alloying on solid solutions were determined by the elements’ positions in the periodic table. In the same period, the alloying elements located in the middle of the period tended to enhance the elastic modulus of copper, while the elements located at both ends have greater solid solution strengthening ability. The predicted results are in good agreement with the experimental values, which provide theoretical guidance for the design of high-performance copper alloys.
Benchtop NMR-Based Metabolomics: First Steps for Biomedical Application
Authors: Alonso-Moreno Pilar , Rodriguez Ignacio , Izquierdo-Garcia Jose Luis
Published: May 2023

Nuclear magnetic resonance (NMR)-based metabolomics is a valuable tool for identifying biomarkers and understanding the underlying metabolic changes associated with various diseases. However, the translation of metabolomics analysis to clinical practice has been limited by the high cost and large size of traditional high-resolution NMR spectrometers. Benchtop NMR, a compact and low-cost alternative, offers the potential to overcome these limitations and facilitate the wider use of NMR-based metabolomics in clinical settings. This review summarizes the current state of benchtop NMR for clinical applications where benchtop NMR has demonstrated the ability to reproducibly detect changes in metabolite levels associated with diseases such as type 2 diabetes and tuberculosis. Benchtop NMR has been used to identify metabolic biomarkers in a range of biofluids, including urine, blood plasma and saliva. However, further research is needed to optimize the use of benchtop NMR for clinical applications and to identify additional biomarkers that can be used to monitor and manage a range of diseases. Overall, benchtop NMR has the potential to revolutionize the way metabolomics is used in clinical practice, providing a more accessible and cost-effective way to study metabolism and identify biomarkers for disease diagnosis, prognosis, and treatment.
Herbivory Damage Increased VOCs in Wild Relatives of Murtilla Plants Compared to Their First Offspring
Authors: Chacón-Fuentes Manuel , Bardehle Leonardo , Seguel Ivette , Espinoza Javier , Lizama Marcelo , Quiroz Andrés
Published: May 2023

Murtilla (Ugni molinae) is a shrub native to Chile that has undergone an incipient domestication process aimed at increasing its productivity. The reduction in intrinsic chemical defenses due to the domestication process has resulted in a decrease in the plant’s ability to defend itself against mechanical or insect damage. In response to this damage, plants release volatile organic compounds (VOCs) as a means of defense. To understand how domestication has impacted the production of VOCs in the first offspring of murtilla, we hypothesized that their levels would be reduced due to the induction of mechanical and herbivore damage. To test this hypothesis, we collected VOCs from four offspring ecotypes and three wild relatives of murtilla. We induced mechanical and herbivore damage in the plants and then enclosed them in a glass chamber, where we captured the VOCs. We identified 12 compounds using GC-MS. Our results showed that wild relative ecotypes had a higher VOC release rate of 624.6 µg/cm2/day. Herbivore damage was the treatment that produced the highest release of VOCs, with 439.3 µg/cm2/day in wild relatives. These findings suggest that herbivory triggers defenses through the emission of VOCs, and that domestication has influenced the production of these compounds in murtilla. Overall, this study contributes to bridging the gap in the incipient domestication history of murtilla and highlights the importance of considering the impact of domestication on a plant’s chemical defenses.