bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Elastohydrodynamic Lubrication (EHL) Characteristics of Port Plate Pair of a Piston Pump
Authors: Wang Zhaoqiang , Han Bo , Sun Lingtao
Published: November 2022

This article presents a steady-state elastohydrodynamic lubrication model for the contact and sliding interface of an axial piston pump’s port plate pair. The wedge-shaped oil film thickness, pressure, viscosity, and elastic deformation distribution of the port plate pair were investigated by using the finite difference method. The elastohydrodynamic lubrication characteristics for different operating parameters and two materials of the port plate pair were analyzed for comparison. Existing conditions for the EHL were calculated, and variations in leakage and friction coefficients were investigated. The results show that the elastic deformation of the interface greatly influences the oil film’s overall performance, which is related to the material, inlet pressure, velocity, viscosity, and the minimum oil film thickness that determines the EHL. The deformation caused by oil film pressure greatly influences the model leakage and friction coefficient, especially when the deformation is equal to the oil film clearance.
Effect of Metal-Oxide Phase on the Magnetic and Magnetocaloric Properties of La0.7Ca0.3MnO3-MO (MO=CuO, CoO, and NiO) Composite
Authors: Dhungana Surendra , Casey Jacob , Neupane Dipesh , Pathak Arjun K. , Karna Sunil , Mishra Sanjay R.
Published: November 2022

The study reports the synthesis and characterization of the magnetic and magnetocaloric effects of metal-oxide (MO) modified La0.7Ca0.3MnO3 perovskites manganite. The powder composite samples, with a nominal composition of (1 − x)La0.7Ca0.3MnO3-xMO (Wt.% x = 0.0, 2.5, 5.0), were prepared using the facile autocombustion method, followed by an annealing process. The phase purity and structure were confirmed by X-ray diffraction. Temperature and field-dependent magnetization measurements and Arrott analysis revealed mixed first- and second-order phase transition (ferromagnetic to paramagnetic) in composite samples. The phase transition temperature shifted to lower temperatures with the addition of MO in the composite. A large magnetic entropy change (4.75 JKg−1K−1 at 1T and 8.77 JKg−1K−1 at 5T) was observed in the La0.7Ca0.3MnO3 (LCMO) sample and was suppressed, due to the presence of the MO phase in the composite samples. On the other hand, the addition of MO as a secondary phase in the LCMO samples enhanced their relative cooling power (RCP). The RCP of all composite samples increased with respect to the pristine LCMO, except for LCMO–5%NiO. The highest RCP value of 267 JKg−1 was observed in LCMO–5%CuO samples, which was 23.4% higher than the 213 JKg−1 observed for the pure LCMO at a magnetic field of 5T. The enhanced RCP of these composites makes them attractive for potential refrigeration applications.
Taxonomy-Aware Prototypical Network for Few-Shot Relation Extraction
Authors: Wang Mengru , Zheng Jianming , Chen Honghui
Published: November 2022

Relation extraction aims to predict the relation triple between the tail entity and head entity in a given text. A large body of works adopt meta-learning to address the few-shot issue faced by relation extraction, where each relation category only contains few labeled data for demonstration. Despite promising results achieved by existing meta-learning methods, these methods still struggle to distinguish the subtle differences between different relations with similar expressions. We argue this is largely owing to that these methods cannot capture unbiased and discriminative features in the very few-shot scenario. For alleviating the above problems, we propose a taxonomy-aware prototype network, which consists of a category-aware calibration module and a task-aware training strategy module. The former implicitly and explicitly calibrates the representation of prototype to become sufficiently unbiased and discriminative. The latter balances the weight between easy and hard instances, which enables our proposal to focus on data with more information during the training stage. Finally, comprehensive experiments are conducted on four typical meta tasks. Furthermore, our proposal presents superiority over the competitive baselines with an improvement of 3.30% in terms of average accuracy.
Modeling and Stability Analysis of Within-Host IAV/SARS-CoV-2 Coinfection with Antibody Immunity
Authors: Elaiw Ahmed M. , Alsulami Raghad S. , Hobiny Aatef D.
Published: November 2022

Studies have reported several cases with respiratory viruses coinfection in hospitalized patients. Influenza A virus (IAV) mimics the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) with respect to seasonal occurrence, transmission routes, clinical manifestations and related immune responses. The present paper aimed to develop and investigate a mathematical model to study the dynamics of IAV/SARS-CoV-2 coinfection within the host. The influence of SARS-CoV-2-specific and IAV-specific antibody immunities is incorporated. The model simulates the interaction between seven compartments, uninfected epithelial cells, SARS-CoV-2-infected cells, IAV-infected cells, free SARS-CoV-2 particles, free IAV particles, SARS-CoV-2-specific antibodies and IAV-specific antibodies. The regrowth and death of the uninfected epithelial cells are considered. We study the basic qualitative properties of the model, calculate all equilibria and investigate the global stability of all equilibria. The global stability of equilibria is established using the Lyapunov method. We perform numerical simulations and demonstrate that they are in good agreement with the theoretical results. The importance of including the antibody immunity into the coinfection dynamics model is discussed. We have found that without modeling the antibody immunity, the case of IAV and SARS-CoV-2 coexistence is not observed. Finally, we discuss the influence of IAV infection on the dynamics of SARS-CoV-2 single-infection and vice versa.
Fixed/Predefined-Time Synchronization of Complex-Valued Stochastic BAM Neural Networks with Stabilizing and Destabilizing Impulse
Authors: You Jingjing , Abdurahman Abdujelil , Sadik Hayrengul
Published: November 2022

This article is mainly concerned with the fixed-time and predefined-time synchronization problem for a type of complex-valued BAM neural networks with stochastic perturbations and impulse effect. First, some previous fixed-time stability results on nonlinear impulsive systems in which stabilizing and destabilizing impulses were separately analyzed are extended to a general case in which the stabilizing and destabilizing impulses can be handled simultaneously. Additionally, using the same logic, a new predefined-time stability lemma for stochastic nonlinear systems with a general impulsive effect is obtained by using the inequality technique. Then, based on these novel results, two novel controllers are implemented to derive some simple fixed/predefined-time synchronization criteria for the considered complex-valued impulsive BAM neural networks with stochastic perturbations using the non-separation method. Finally, two numerical examples are given to demonstrate the feasibility of the obtained results.
A Method Combining Multi-Feature Fusion and Optimized Deep Belief Network for EMG-Based Human Gait Classification
Authors: He Jie , Gao Farong , Wang Jian , Wu Qiuxuan , Zhang Qizhong , Lin Weijie
Published: November 2022

In this paper, a gait classification method based on the deep belief network (DBN) optimized by the sparrow search algorithm (SSA) is proposed. The multiple features obtained based on surface electromyography (sEMG) are fused. These functions are used to train the model. First, the sample features, such as the time domain and frequency domain features of the denoised sEMG are extracted and then the fused features are obtained by feature combination. Second, the SSA is utilized to optimize the architecture of DBN and its weight parameters. Finally, the optimized DBN classifier is trained and used for gait recognition. The classification results are obtained by varying different factors and the recognition rate is compared with the previous classification algorithms. The results show that the recognition rate of SSA-DBN is higher than other classifiers, and the recognition accuracy is improved by about 2% compared with the unoptimized DBN. This indicates that for the application in gait recognition, SSA can optimize the network performance of DBN, thus improving the classification accuracy.
Global Stability of a Reaction–Diffusion Malaria/COVID-19 Coinfection Dynamics Model
Authors: Elaiw Ahmed M. , Al Agha Afnan D.
Published: November 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new virus which infects the respiratory system and causes the coronavirus disease 2019 (COVID-19). The coinfection between malaria and COVID-19 has been registered in many countries. This has risen an urgent need to understand the dynamics of coinfection. In this paper, we construct a reaction–diffusion in-host malaria/COVID-19 model. The model includes seven-dimensional partial differential equations that explore the interactions between seven compartments, healthy red blood cells (RBCs), infected RBCs, free merozoites, healthy epithelial cells (ECs), infected ECs, free SARS-CoV-2 particles, and antibodies. The biological validation of the model is confirmed by establishing the nonnegativity and boundedness of the model’s solutions. All equilibrium points with the corresponding existence conditions are calculated. The global stability of all equilibria is proved by picking up appropriate Lyapunov functionals. Numerical simulations are used to enhance and visualize the theoretical results. We found that the equilibrium points show the different cases when malaria and SARS-CoV-2 infections occur as mono-infection or coinfection. The shared antibody immune response decreases the concentrations of SARS-CoV-2 and malaria merozoites. This can have an important role in reducing the severity of SARS-CoV-2 if the immune response works effectively.
A Preserving Precision Mixed Finite Element Dimensionality Reduction Method for Unsaturated Flow Problem
Authors: Luo Zhendong , Li Yuejie
Published: November 2022

The unsaturated flow problem is of important applied background and its mixed finite element (MFE) method can be used to simultaneously calculate both water content and flux in soil, which is the most ideal calculation method. Nonetheless, it includes many unknowns. Thereby, herein we will employ the proper orthogonal decomposition (POD) to lower the dimension of unknown solution coefficient vectors in the MFE method for the unsaturated flow problem. Thus, we first examine the MFE method for the unsaturated flow problem and the existence and convergence of the classical MFE solutions. We then take advantage of the initial L MFE solution coefficient vectors to generate a set of POD basis vectors and utilize the most POD basis vectors to create the preserving precision MFE reduced-dimension (PPMFERD) format. Under the circumstances, the PPMFERD format has the same basis functions as the classical MFE format so that it can maintain the same accuracy as the classical MFE format, but it only includes a few unknowns, so it greatly lightens the calculating load, retards the accumulation of computing errors, saves CPU runtime, and improves the accuracy of the real-time calculation in the computational process. Next, we employ the analysis of matrices to demonstrate the existence and convergence of the PPMFERD solutions such that the theoretical analysis becomes very simple and elegant. Finally, we take advantage of some numerical simulations to check on the correctness of the PPMFERD method. It shows that the PPMFERD method is effective and feasible for simulating both water content and flux in unsaturated flow soil.
Generation of Synthetic Data for the Analysis of the Physical Stability of Tailing Dams through Artificial Intelligence
Authors: Pacheco Fernando , Hermosilla Gabriel , Piña Osvaldo , Villavicencio Gabriel , Allende-Cid Héctor , Palma Juan , Valenzuela Pamela , García José , Carpanetti Alex , Minatogawa Vinicius , Suazo Gonzalo , León Andrés , López Ricardo , Novoa Gullibert
Published: November 2022

In this research, we address the problem of evaluating physical stability (PS) to close tailings dams (TD) from medium-sized Chilean mining using artificial intelligence (AI) algorithms. The PS can be analyzed through the study of critical variables of the TD that allow estimating different potential failure mechanisms (PFM): seismic liquefaction, slope instability, static liquefaction, overtopping, and piping, which may occur in this type of tailings storage facilities in a seismically active country such as Chile. Thus, this article proposes the use of four machine learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural networks (ANN), and extreme gradient boosting (XGBoost), to estimate five possible PFM. In addition, due to the scarcity of data to train the algorithms, the use of generative adversarial networks (GAN) is proposed to create synthetic data and increase the database used. Therefore, the novelty of this article consists in estimating the PFM for TD and generating synthetic data through the GAN. The results show that, when using the GAN, the result obtained by the ML models increases the F1-score metric by 30 percentage points, obtaining results of 97.4%, 96.3%, 96.7%, and 97.3% for RF, SVM, ANN, and XGBoost, respectively.
A Bibliometric Analysis of the Use of Artificial Intelligence Technologies for Social Sciences
Authors: Bircan Tuba , Salah Almila Alkim Akdag
Published: November 2022

The use of Artificial Intelligence (AI) and Big Data analysis algorithms is complementary to theory-driven analysis approaches and becoming more popular also in social sciences. This paper describes the use of Big Data and computational approaches in social sciences by bibliometric analyses of articles indexed between 2015 and 2020 in Social Sciences Citation Index (SSCI) of the Web of Science repository. We have analysed especially the recent research direction called Computational Social Sciences (CSS) that bridges computer analytical approaches with social science challenges, generating new methodologies of Big Data and AI analytics for social sciences. The results indicate that AI and Big Data practices are not confined to CSS only and are diffused in a wide variety of disciplines under Social Sciences and are made use of in many main research lines as well. Thus, the anticipated overlap between the Social Sciences & AI specialization and CSS has yet to be crystallised. Moreover, the impact of computational social science studies is not permeated to social science citation networks yet. Lastly, we demonstrate that the AI and Big Data publications that appear under the SSCI index are more oriented towards computational studies than addressing social science concepts, concerns, and challenges.
Robust Control as a Mathematical Paradigm for Innovative Engineering Applications
Authors: Mercorelli Paolo
Published: November 2022

Robust control is a mathematical paradigm for innovative engineering applications [...]
Advanced Modulation Scheme of a Dual-Active-Bridge Series Resonant Converter (DABSRC) for Enhanced Performance
Authors: Hameed Asad , Nauman Ali , Quadir Munleef , Khan Irfan Latif , Iqbal Adeel , Hussain Riaz , Khurshaid Tahir
Published: November 2022

This paper proposes a two-degree-of-freedom (2-DoF) modulation technique for the efficient optimization of an open-loop three-phase dual-active-bridge series resonant converter (3P-DABSRC). The efficiency and performance of an conventional dual-active-bridge (DAB) converter decrease when it is operated over a wide range of voltage gain. The efficiency and performance of a DAB converter depend upon the switching and conduction losses. Circulating current is the main cause of conduction loss, and hard switching of active switches adds a switching loss. To increase the performance of DAB converters, the first objective is to minimize the conduction loss, and the second objective is to reduce the switching loss. Still, unfortunately, it is not easy to achieve these two objectives simultaneously. Circulating current helps us to reduce the switching loss, but the unbridled amount of circulating current will increase the root-mean-square inductor tank current, and as a result, the conduction loss will be increased. This paper presents an advanced modulation scheme for a 3P-DABSRC that can be used not only in low-power applications, but also in high-power applications. The DABSRC consists of a series LC resonant tank, isolated high-frequency transformer, and dual active bridge connected with the primary and secondary sides of the transformer. The proposed 2-DoF modulation technique not only minimizes the circulating current, but also eliminates the switching loss. Keeping the minimum phase shift between the primary and secondary bridges reduces the circulating current, and thus, all switches can be operated with zero-voltage switching (ZVS) for the entire power range. The power is controlled by changing the switching frequency from 45 to 63 kHz. To confirm the proposed topology and modulation scheme, a 1500 W DABSRC, which interfaces a 300 V DC bus with a 75 V DC bus, is simulated. A loss model of the proposed topology is also made to verify the results. The simulation results are used to confirm the proper operation of the 3P-DABSRC.
Anti-Biofilm Activity of a Hyaluronan-like Exopolysaccharide from the Marine Vibrio MO245 against Pathogenic Bacteria
Authors: Champion Marie , Portier Emilie , Vallée-Réhel Karine , Linossier Isabelle , Balnois Eric , Vignaud Guillaume , Moppert Xavier , Hellio Claire , Faÿ Fabienne
Published: November 2022

Biofilms, responsible for many serious drawbacks in the medical and marine environment, can grow on abiotic and biotic surfaces. Commercial anti-biofilm solutions, based on the use of biocides, are available but their use increases the risk of antibiotic resistance and environmental pollution in marine industries. There is an urgent need to work on the development of ecofriendly solutions, formulated without biocidal agents, that rely on the anti-adhesive physico-chemical properties of their materials. In this context, exopolysaccharides (EPSs) are natural biopolymers with complex properties than may be used as anti-adhesive agents. This study is focused on the effect of the EPS MO245, a hyaluronic acid-like polysaccharide, on the growth, adhesion, biofilm maturation, and dispersion of two pathogenic model strains, Pseudomonas aeruginosa sp. PaO1 and Vibrio harveyi DSM19623. Our results demonstrated that MO245 may limit biofilm formation, with a biofilm inhibition between 20 and 50%, without any biocidal activity. Since EPSs have no significant impact on the bacterial motility and quorum sensing factors, our results indicate that physico-chemical interactions between the bacteria and the surfaces are modified due to the presence of an adsorbed EPS layer acting as a non-adsorbing layer.
The Influence of Mechanical Stress Micro Fields around Pores on the Strength of Elongated Etched Membrane
Authors: Gumirova Venera , Razumovskaya Irina , Apel Pavel , Bedin Sergey , Naumov Andrey
Published: November 2022

The investigation of the mechanical properties of polymer track-etched membranes (TMs) has attracted significant attention in connection with the extended region of their possible applications. In the present work, the mechanical stress fields around the pores of an elongated polyethylene terephthalate TM and around the 0.3 mm holes in model polymer specimens were studied in polarized light and with the finite element method. A break-up experiment showed the controlling role of stress field interaction in the forming of a microcrack system and the generation of a main crack with rupture of the TM (or model pattern). This interaction depended on the relative distance between the pores (holes) and their orientation. The results of the calculations of the pore distribution function over the surface of the TM via the net method and wavelet analysis are presented. The fractal character of pore distribution was established. The geometric characteristics of the TM pore system as initial defects are inherited by obtaining TM-based composites.
Buccal Thin Films as Potent Permeation Enhancers for Cytisine Transbuccal Delivery
Authors: De Caro Viviana , Angellotti Giuseppe , D’Agostino Fabio , Di Prima Giulia
Published: November 2022

Cytisine (CYT) is a powerful anti-smoking compound which could greatly benefit from transbuccal delivery because of both its unfavorable pharmacokinetics after oral administration and its intrinsic ability to permeate the buccal mucosa. This work aims to design CYT-loaded buccal thin films suitable for transbuccal drug delivery due to its capability of promoting the interaction between CYT and the buccal membrane. The solvent casting method was employed to prepare several thin films combining various excipients such as matrixing polymers, mucoadhesion agents, plasticizers and other compounds as humectants and sweeteners, component ratios and solvents. A total of 36 compositions was prepared and four of them emerged as the most promising in terms of aspect and flexibility. They all demonstrated homogeneity, thinness, low swelling degree, and controlled drug release according to the Power Law and Peppas-Sahlin mathematical models. Mainly, they proved able to interact with the ex vivo porcine buccal mucosa producing mucoadhesive effects, and act as potent permeation enhancers. In particular, Film B emerged as suitable as it produced a 10.6-fold Kp enhancement and a great Js value (52.33 μg/cm2·h−1), even when compared to highly concentrated CYT solutions.
Effect of Shoulder Fillet Radius on Welds in Bobbin Tool Friction Stir Welding of A1050
Authors: Miao Huilin , Miura Takuya , Jiang Wei , Okada Masato , Otsu Masaaki
Published: November 2022

In this study, five bobbin tools with different shoulder fillet radii were employed for the bobbin tool friction stir welding (BT-FSW) of A1050-O sheets to systematically evaluate the effects of shoulder fillet radius on the welding defect formation, flash formation, weld thickness, grain size of the stir zone, and tensile properties. The quality classifications of the joints’ appearance were summarized as process windows, and the appropriate welding condition range for each shoulder fillet radius was clarified. It was observed that an increase in the shoulder fillet radius decreased the welding defects and flash formation; however, it increased the minimum thickness of the weld except when the shoulder fillet radius was 0.5 mm. The grain size of the stir zone increased with increasing shoulder fillet radius from 0.5 mm to 6 mm. The ultimate tensile strength (UTS) of the stir zone decreased with increasing shoulder fillet radius from 0.5 mm to 1 mm, increased from 1 mm to 3 mm, and remained constant from 3 mm to 6 mm. The results indicate that a shoulder fillet radius larger than 3 mm is effective in decreasing flash formation and maintaining a constant weld thickness.
Correction: Uwamahoro et al. An Assessment of the Lactic Acid-Producing Potential of Bacterial Strains Isolated from Food Waste. Microbiol. Res. 2022, 13, 278–291
Authors: Uwamahoro Henriette Peace , Li Fuyu , Timilsina Arbindra , Liu Binbin , Wang Xinzhen , Tian Yinping
Published: November 2022

The authors wish to make the following correction to this paper [...]
Magnetic Nanosorbents Based on Bentonite and CoFe2O4 Spinel
Authors: Khodosova Nataliya , Novikova Lyudmila , Tomina Elena , Belchinskaya Larisa , Zhabin Alexander , Kurkin Nikolay , Krupskaya Victoria , Zakusina Olga , Koroleva Tatiana , Tyupina Ekaterina , Vasiliev Alexander , Kazin Pavel
Published: November 2022

New magnetic nanocomposite sorbents were obtained by doping natural bentonite with nanosized CoFe2O4 spinel (10 and 20 wt.%). Nanocrystals of cobalt ferrite were synthesized by a citrate burning method. The structure and physical-chemical properties of the composites were characterized by XRD, XRF, TEM, BET, FTIR and Faraday balance magnetometry. During the formation of nanocomposites, 10–30 nm particles of cobalt ferrite occupied mainly the interparticle space of Fe-aluminosilicate that significantly changed the particle morphology and composite porosity, but at the same time retained the structure of the 2:1 smectite layer. A combination of two functional properties of composites, adsorption and magnetism has been found. The adsorption capacity of magnetic nanosorbents exceeded this parameter for bentonite and spinel. Despite the decrease in the adsorption volume, pore size and specific surface area of the composite material relative to bentonite, the sorption activity of the composite increases by 12%, which indicated the influence of the magnetic component on the sorption process. FTIR data confirmed the mechanism of formaldehyde sorption by the composite sorbent. The production of a magnetic nanosorbent opens up new possibilities for controlling the sorption processes and makes it possible to selectively separate the sorbent from the adsorption medium by the action of a magnetic field.
Assessment of Potentially Toxic Element Contamination in the Philippi Peatland, Eastern Macedonia, Greece
Authors: Zafeiriou Ioannis , Gasparatos Dionisios , Megremi Ifigeneia , Ioannou Dafni , Massas Ioannis , Economou-Eliopoulos Maria
Published: November 2022

The Philippi peatland is considered the biggest peat deposit in the Balkan Peninsula and one of the deepest in the world. The purpose of this study was to access the impact of eight potentially toxic elements (PTEs), i.e., As, Se, Pb, Cr, Ni, Zn, Mn and Cu, on the local environment. PTE content was determined in corn grains and surface soil samples collected from 16 sites in the peatland, and pollution indices were calculated to evaluate the environmental risks. Soil organic matter ranged between 93 and 557 g kg−1 soil, whereas the soil pH was >7, classifying the soils as neutral to slightly alkaline. Mean PTE contents in soil samples were 24.6 mg kg−1 soil for As, 1.68 mg kg−1 soil for Se, 113 mg kg−1 soil for Pb, 32 mg kg−1 soil for Cr, 36.3 mg kg−1 soil for Ni, 141.4 mg kg−1 soil for Zn, 35.5 mg kg−1 soil for Cu and 845 mg kg−1 soil for Mn. In corn grain samples, 0.06 mg kg−1 grain for As, 0.14 mg kg−1 grain for Se, 1.34 mg kg−1 grain for Cr, 0.69 mg kg−1 grain for Ni, 27 for Zn, 8.4 mg kg−1 grain for Cu and 3.2 mg kg−1 grain for Mn were recorded. No Pb was detected in the corn grains. The bioaccumulation factor (BF) was high for Cu, Zn and Se, indicating increased mobility of these elements in the soils and preferential plant uptake. For most soil samples, the geoaccumulation index (Igeo) and single pollution index (PI) showed low to moderate contamination. However, Igeo and PI values of Se in many sampling sites and of Pb and Zn in few were substantially increased, pointing to heavily contaminated soils. According to potential ecological risk (RI), the PTE content in the peat soils of Philippi imposes low to moderate risk on the environment.
In Situ Polymerization of Linseed Oil-Based Composite Film: Enhancement of Mechanical and Water Barrier Properties by the Incorporation of Cinnamaldehyde and Organoclay
Authors: Guesmi Rim , Benbettaieb Nasreddine , Ben Romdhane Mohamed Ramzi , Barhoumi-Slimi Thouraya , Assifaoui Ali
Published: November 2022

Linseed oil-based composite films were prepared with cinnamaldehyde (Cin) using a modified clay (organoclay) through in situ polymerization, which is the result of the interaction between Cin and organoclay. The incorporation of organoclay reduces the polymer chain’s mobility and, therefore, increases the thermal stability of the composite films. In some experimental conditions, the clay is located both inside and on the surface of the film, thus, affecting the mechanical and thermal properties as well as the surface properties of the composite films. The incorporation of organoclay decreases the water contact angle of the composite film by more than 15%, whatever the amount of cinnamaldehyde. However, the incorporation of cinnamaldehyde has the opposite effect on film surface properties. Indeed, for the water vapor permeability (WVP), the effect of cinnamaldehyde on the film barrier properties is much higher in the presence of organoclay. The incorporation of hydrophobic compounds into the polymer films reduces the water content, which acts as a plasticizer and, therefore, decreases the WVP by more than 17%. Linseed oil has a natural antioxidant activity (~97%) due to the higher content of unsaturated fatty acids, and this activity increased with the amount of organoclay and cinnamaldehyde.
In Vitro Determination of the Skin Anti-Aging Potential of Four-Component Plant-Based Ingredient
Authors: Quiles José , Cabrera Maria , Jones Jonathan , Tsapekos Menelaos , Caturla Nuria
Published: November 2022

The beauty industry is actively searching for solutions to prevent skin aging. Some of the crucial elements protecting cells from the aging process are telomere shortening, telomerase expression, cell senescence, and homeostasis of the redox system. Modification of these factors using natural antioxidants is an appealing way to support healthy skin aging. Therefore, in this study, we sought to investigate the antiaging efficacy of a specific combination of four botanical extracts (pomegranate, sweet orange, Cistanche and Centella asiatica) with proven antioxidant properties. To this end, normal human dermal fibroblasts were used as a cell model and the following studies were performed: cell proliferation was established by means of the MTT assay and the intracellular ROS levels in stress-induced premature senescence fibroblasts; telomere length measurement was performed under standard cell culture conditions using qPCR and under oxidative stress conditions using a variation of the Q-FISH technique; telomerase activity was examined by means of Q-TRAP; and AGE quantification was completed by means of ELISA assay in UV-irradiated fibroblasts. As a result, the botanical blend significantly reversed the H2O2-induced decrease in cell viability and reduced H2O2-induced ROS. Additionally, the presence of the botanical ingredient reduced the telomere shortening rate in both stressed and non-stressed replicating fibroblasts, and under oxidative stress conditions, the fibroblasts presented a higher median and 20th percentile telomere length, as well as a lower percentage of short telomeres (<3 Kbp) compared with untreated fibroblasts. Furthermore, the ingredient transiently increased relative telomerase activity after 24 h and prevented the accumulation of UVR-induced glycated species. The results support the potential use of this four-component plant-based ingredient as an antiaging agent.
Virtual Screening of Artemisia annua Phytochemicals as Potential Inhibitors of SARS-CoV-2 Main Protease Enzyme
Authors: Miandad Khalid , Ullah Asad , Bashir Kashif , Khan Saifullah , Abideen Syed Ainul , Shaker Bilal , Alharbi Metab , Alshammari Abdulrahman , Ali Mahwish , Haleem Abdul , Ahmad Sajjad
Published: November 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a human coronaviruses that emerged in China at Wuhan city, Hubei province during December 2019. Subsequently, SARS-CoV-2 has spread worldwide and caused millions of deaths around the globe. Several compounds and vaccines have been proposed to tackle this crisis. Novel recommended in silico approaches have been commonly used to screen for specific SARS-CoV-2 inhibitors of different types. Herein, the phytochemicals of Pakistani medicinal plants (especially Artemisia annua) were virtually screened to identify potential inhibitors of the SARS-CoV-2 main protease enzyme. The X-ray crystal structure of the main protease of SARS-CoV-2 with an N3 inhibitor was obtained from the protein data bank while A. annua phytochemicals were retrieved from different drug databases. The docking technique was carried out to assess the binding efficacy of the retrieved phytochemicals; the docking results revealed that several phytochemicals have potential to inhibit the SARS-CoV-2 main protease enzyme. Among the total docked compounds, the top-10 docked complexes were considered for further study and evaluated for their physiochemical and pharmacokinetic properties. The top-3 docked complexes with the best binding energies were as follows: the top-1 docked complex with a −7 kcal/mol binding energy score, the top-2 docked complex with a −6.9 kcal/mol binding energy score, and the top-3 docked complex with a −6.8 kcal/mol binding energy score. These complexes were subjected to a molecular dynamic simulation analysis for further validation to check the dynamic behavior of the selected top-complexes. During the whole simulation time, no major changes were observed in the docked complexes, which indicated complex stability. Additionally, the free binding energies for the selected docked complexes were also estimated via the MM-GB/PBSA approach, and the results revealed that the total delta energies of MMGBSA were −24.23 kcal/mol, −26.38 kcal/mol, and −25 kcal/mol for top-1, top-2, and top-3, respectively. MMPBSA calculated the delta total energy as −17.23 kcal/mol (top-1 complex), −24.75 kcal/mol (top-2 complex), and −24.86 kcal/mol (top-3 complex). This study explored in silico screened phytochemicals against the main protease of the SARS-CoV-2 virus; however, the findings require an experimentally based study to further validate the obtained results.
Discovery of New Glucose Uptake Inhibitors as Potential Anticancer Agents by Non-Radioactive Cell-Based Assays
Authors: Hung Hsueh-Chih , Li Li-Cheng , Guh Jih-Hwa , Kung Fan-Lu , Hsu Lih-Ching
Published: November 2022

Tumor cells rely on aerobic glycolysis to support growth and survival, thus require more glucose supply. Glucose transporters GLUTs, primarily GLUT1, are overexpressed in various cancers. Targeting GLUTs has been regarded as a promising anticancer strategy. In this study, we first evaluated 75 potential GLUT1 inhibitors obtained from virtual screening of the NCI chemical library by a high-throughput cell-based method using a fluorescent glucose analogue 2-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxy-d-glucose (2-NBDG) in COS-7 and SKOV3 cells that express high levels of GLUT1. Four compounds, #12, #16, #43 and #69, that significantly inhibited glucose uptake were further evaluated using flow cytometry directly measuring 2-NBDG uptake at the single-cell level and a Glucose Uptake-GloTM assay indirectly measuring 2-deoxy-d-glucose uptake in SKOV3, COS-7 or MCF-7 cells. The inhibitory effect on cancer cell growth was also determined in SKOV3 and MCF-7 cells, and #12 exhibited the best growth inhibitory effect equivalent to a known GLUT1 inhibitor WZB117. Although the anticancer effect of the identified potential GLUT1 inhibitors was moderate, they may enhance the activity of other anticancer drugs. Indeed, we found that #12 synergistically enhanced the anticancer activity of metformin in SKOV3 ovarian cancer cells.
Control Efficacy of Salicylic Acid Microcapsules against Postharvest Blue Mold in Apple Fruit
Authors: Wang Yifei , Chen Jiahao , Bian Wenyi , Yang Xiaobo , Ye Lin , He Shoukui , Song Xiaoqiu
Published: November 2022

Salicylic acid (SA) is a natural inducer of disease resistance in fruit, but its application in the food industry is limited due to low water solubility. Here, SA was encapsulated in β-cyclodextrin (β-CD) via the host–guest inclusion complexation method, and the efficacy of SA microcapsules (SAM) against blue mold caused by Penicillium expansum in postharvest apple fruit was elucidated. It was observed that SAM was the most effective in inhibiting the mycelial growth of P. expansum in vitro. SAM was also superior to SA for control of blue mold under in vivo conditions. Enzyme activity analysis revealed that both SA and SAM enhanced the activities of superoxide dismutase (SOD) and phenylalanine ammonia lyase (PAL) in apple fruit, whereas SAM led to higher SOD activities than SA. Total phenolic contents in the SAM group were higher than those in the SA group at the early stage of storage. SAM also improved fruit quality by retarding firmness loss and maintaining higher total soluble solids (TSS) contents. These findings indicate that microcapsules can serve as a promising formulation to load SA for increasing P. expansum inhibition activity and improving quality attributes in apple fruit.
Pharmacological Activities and Characterization of Phenolic and Flavonoid Compounds in Solenostemma argel Extract
Authors: Elsanhoty Rafaat M. , Soliman Mohamed S. M. , Khidr Yehia A. , Hassan Gamal O. O. , Hassan Ahmed R. A. , Aladhadh Mohammed , Abdella Asmaa
Published: November 2022

Solenostemma argel is a desert medicinal plant indigenous to African countries. This research aims to study the pharmacological properties of Solenostemma argel plant. Aerial parts (leaves and flowers) of Solenostemma argel (Delile) Hayane were tested for antibacterial activity, antioxidant activity, anticancer, and anti-inflammatory activity. Phenolic and flavonoid contents of the plant were characterized. There was an increase in the antioxidant activity of Solenostemma argel extract from 12.16% to 94.37% by increasing concentration from10 µg/mL to 1280 µg/mL. The most sensitive organism was S. epidermidis with chloroform extract. The MTT assay revealed that methanolic extracts of Solenostemma argel showed potent cytotoxic effects on the A549, Caco-2, and MDAMB-231 cell lines, respectively. The anti-inflammatory activity increased by increasing the concentration of methanolic extract of Solenostemma argel, using indomethacin as a standard. Gallic acid was the most abundant phenolic acid, followed by synergic acid and p-coumaric acid, respectively. Catechin, quercetin, luteolin, kaempferol and rutin flavonoids were also found in the methanolic extract. GC-mass analysis showed that aerial parts of Solenostemma argel were rich in 2-(5-methyl-5 vinyl tetrahydro-2-furanyl)-2-propanol (11.63%), hexanoic acid methyl ester (10.93%), 3-dioxolane,4-methyl-2-pentadecyl (9.69%), phenol, 2-(1,1-dimethylethyl) (8.50%). It can be concluded that Solenostemma argel methanolic extract contain natural bioactive constituents with potential medicinal importance such as antioxidants, antimicrobial, anti-inflammatory, and anticancer activities.
Rapid Detection of Porcine DNA in Meatball Using Recombinase Polymerase Amplification Couple with Lateral Flow Immunoassay for Halal Authentication
Authors: Yusop Mohd Hazim Mohd , Bakar Mohd Fadzelly Abu , Kamarudin Kamarul Rahim , Mokhtar Nur Fadhilah Khairil , Hossain Mohd Abd Motalib , Johan Mohd Rafie , Noor Nor Qhairul Izzreen Mohd
Published: November 2022

Point-of-care diagnostic methods for animal species determination are critical for rapid, simple, and accurate enforcement of food labelling. PCR is the most common method for species identification. However, the requirement of using a thermal cycler created drawbacks for the PCR application, particularly in low-resource settings. Hence, in this study, a method for porcine DNA detection using recombinase polymerase amplification (RPA), coupled with nucleic acid lateral flow immunoassay (NALFIA), was developed. Porcine-specific primers targeting pig (Sus scrofa) cytochrome b gene fragments specifically amplify a 197 bp fragment of the mitochondrial gene as being visualized by 2% agarose gel and PCRD NALFIA. The reaction temperature and time were 39 °C and 20 min, respectively. Herein, the specificity of the primers to porcine was confirmed after being assayed against six animal species, namely cow, goat, chicken, duck, dog, and rabbit. The porcine-specific RPA assay shows a high limit of detection of 0.01 ng/µL pork DNA. Based on the preliminary performance data obtained from this study, the potential of this method as a rapid and sensitive tool for porcine DNA detection in meat-based products is foreseen.
Ethanol Electrooxidation at 1–2 nm AuPd Nanoparticles
Authors: Strasser Juliette W. , Crooks Richard M.
Published: November 2022

We report a systematic study of the electrocatalytic properties and stability of a series of 1–2 nm Au, Pd, and AuPd alloy nanoparticles (NPs) for the ethanol oxidation reaction (EOR). Following EOR electrocatalysis, NP sizes and compositions were characterized using aberration-corrected scanning transmission electron microscopy (ac-STEM) and energy dispersive spectroscopy (EDS). Two main findings emerge from this study. First, alloyed AuPd NPs exhibit enhanced electrocatalytic EOR activity compared to either monometallic Au or Pd NPs. Specifically, NPs having a 3:1 ratio of Au:Pd exhibit an ~8-fold increase in peak current density compared to Pd NPs, with an onset potential shifted ~200 mV more to the negative compared to Au NPs. Second, the size and composition of AuPd alloy NPs do not (within experimental error) change following 1.0 or 2.0 h chronoamperometry experiments, while monometallic Au NPs increase in size from 2 to 5 nm under the same conditions. Notably, this report demonstrates the importance of post-catalytic ac-STEM/EDS characterization for fully evaluating NP activity and stability, especially for 1–2 nm NPs that may change in size or structure during electrocatalysis.
Dynamic Instability of Functionally Graded Graphene Platelet-Reinforced Porous Beams on an Elastic Foundation in a Thermal Environment
Authors: Zhang Jing , Lv Ying , Li Lianhe
Published: November 2022

Under thermal environment and axial forces, the dynamic instability of functionally graded graphene platelet (GPLs)-reinforced porous beams on an elastic foundation is investigated. Three modes of porosity distributions and GPL patterns are considered. The governing equations are given by the Hamilton principle. On the basis of the differential quadrature method (DQM), the governing equations are changed into Mathieu–Hill equations, and the main unstable regions of the porous composite beams are studied by the Bolotin method. Thermal buckling and thermo-mechanical vibration problems are also studied. The effects of porosity coefficients and GPL weight fraction, dispersion pattern, initial thermal loading, slenderness ratio, geometry and size, boundary conditions, and foundation stiffness are discussed. The conclusions show that an elastic foundation has an obvious enhancement effect on thermal buckling, free vibration, and dynamic instability, which improves the stiffness of the beam.
Study on Tensile Properties of Fly Ash, Sugarcane Fiber and Carbon Nanotube-Reinforced Polymer Matrix Composite Using Objective Evolutionary Algorithm
Authors: Venkatachalam Gopalan , Gopu Arunkumar , Velu Pitchumani Shenbaga , Venkataraman Neelanarayanan , Salunke Dinesh Ramesh , Mukkamala Raghava Rao
Published: November 2022

Composite materials have a wide range of applications in emerging eco-friendly environments. Composites that created from naturally available materials are easily decomposed over time and very cost-effective. Fly ash and sugarcane fiber are widely available waste materials produced on a massive scale. This research was aimed to find an optimal mixture of reinforced composites (fly ash, sugarcane fiber and CNTs) in order to maximize yield strength, ultimate tensile strength and Young’s modulus using a Multi-Objective Evolutionary Algorithm with Decomposition (MOEA/D). Optimizing one objective may have a negative impact on another objective, so the authors used the sophisticated MOEA/D algorithm to simultaneously find optimal values on all three objectives. The Design of Experiments (DOE) method was performed using ANOVA, and then regression equations were generated. The regression equations were optimized using the MOEA/D algorithm to obtain optimal values. Using the optimal compositional values produced by the algorithm, materials were fabricated. The fabricated materials were tested using a Shimadzu UTM machine to cross-validate the findings. A combination of 0.2 wt.% of fly ash, 2 wt.% of SCF, and 0.39 wt.% of CNTs showed a maximum yield strength of 7.52 MPa and Young’s modulus of 1281.18 MPa, with a quite considerable ultimate tensile strength of 10.54 MPa compared with the optimized results obtained through the response surface methodology.
The Utility of Automated ASPECTS in Acute Ischemic Stroke for Intravenous Recombinant Tissue Plasminogen Activator (IV-rtPA) Therapy
Authors: Shibata Soichiro , Sakurai Kenzo , Tachikawa Keiji , Ko Riyoko , Hino Sakae , Fukano Takayuki , Isahaya Kenji , Haraguchi Takafumi , Yamauchi Junji , Tanabe Kenichiro , Nagasaka Misako , Hagiwara Yuta , Shimizu Takahiro , Akiyama Hisanao , Kobayashi Yasuyuki , Hasegawa Yasuhiro , Yamano Yoshihisa
Published: November 2022

Purpose: This study aimed to investigate the accuracy and clinical significance of an artificial intelligence (AI)-based automated Alberta Stroke Program Early Computed Tomography (ASPECT) scoring software of head CT for the indication of intravenous recombinant tissue plasminogen activator (rt-PA) therapy. Methods: This study included two populations of acute ischemic stroke: one comprised patients who had undergone head CT within 48 h of presentation (Population #1, n = 448), while the other included patients within 4.5 h from onset (Population #2, n = 132). The primary endpoint was the concordance rate of ASPECTS of the neurologists and AI software against the benchmark score. The secondary endpoints were to validate the accuracy of the neurologist and AI software in assessing the ability to rule out extensive infarction (ASPECTS of 0–5) in population #2. Results: The reading accuracy of AI software was comparable to that of the board-certified vascular neurologists. The detection rate of cardiogenic cerebral embolism was better than that of atherothrombotic cerebral infarction. By excluding extensive infarction, AI-software showed a higher specificity and equivalent sensitivity compared to those of experts. Conclusions: The AI software for ASPECTS showed convincing agreement with expert evaluation and would be supportive in determining the indications of intravenous rt-PA therapy.
Effect of Chia (Salvia hispanica L.) Associated with High-Fat Diet on the Intestinal Health of Wistar Rats
Authors: Mishima Marcella Duarte Villas , Da Silva Bárbara Pereira , Gomes Mariana Juste Contin , Toledo Renata Celi Lopes , Mantovani Hilário Cuquetto , José Vinícius Parzanini Brilhante de São , Costa Neuza Maria Brunoro , Tako Elad , Martino Hércia Stampini Duarte
Published: November 2022

A direct correlation has been reported between excessive fat intake and the development and progression of various enteropathies. Plant foods may contain bioactive compounds and non-digestible dietary fiber, with potential to improve intestinal health. Chia is a good source of dietary fiber and bioactive compounds. Our study evaluated the role of chia flour associated with a high-fat diet (HFD) on colon histomorphometry, intestinal functionality and intestinal microbiome composition and function in Wistar rats. The study used 32 young male rats separated into four groups to receive a standard diet (SD) or HFD, with or without chia, for 35 days. At the end of the study, the cecum, cecal content and duodenum were collected. The consumption of chia increased the production of short-chain fatty acids and improved fecal moisture. Chia consumption improved the circular muscle layer in the SD group. The diversity and abundance of intestinal bacteria were not affected, but increased richness was observed in the microbiome of the SD+chia group. Moreover, chia consumption decreased the expression of proteins involved in intestinal functionality. Chia consumption improved intestinal morphology and functionality in young Wistar rats but was insufficient to promote significant changes in the intestinal microbiome in a short term of 35 days.