bluuebunny/crossref_metadata_2025 huggingface dataset:
Sourcing Limestone Masonry for the Restoration of Heritage Buildings: Frumoasa Monastery Case Study
Authors: Onuțu Cătălin , Ungureanu Dragoș , Isopescu Dorina Nicolina , Vornicu Nicoleta , Spiridon Ionuț Alexandru
Published: October 2022

Cultural and religious heritage assessments and restorations are considered to be a fundamental requirement of any modern society because these constructions represent one of the most meaningful and tangible connections to our past. With rare exceptions, heritage buildings were built with materials and systems that could bear gravitational loads but not bending and shearing resulting from seismic loading. Thus, in many cases, earthquake ground motions have led to severe degradation and even the collapse of various parts of these structural systems. In order to address these issues, repair and replacement techniques are applied as common parts of restoration work. In the peculiar case of stone masonry structures, a standalone macroscopic examination is not self-assured and, most often, can lead to an inadequate selection of a replacement material. Therefore, a knowledge of mesoscopic, petrographic, physical and mechanical properties is compulsory in the design, planning and execution of restoration work. From this perspective, the present research has taken, as a case of study, the Frumoasa monastic complex from Iași, Romania, introducing microscopic, XRF (X-ray fluorescence) spectroscopy and petrographically based approaches, comparing three limestone samples with a sample dislodged from the original wall. The physical properties (bulk and real densities, open porosity and capillary water absorption coefficient) and the mechanical properties (compressive and tensile strengths) were also experimentally determined. The samples were extracted from stone quarries located on the territories that were part of the same historical region as the Frumoasa monastic complex. Based on the outcomes of this study, suitable criteria for the stone replacement—consisting of identifying the main structure, quarry rock petrographical parameters and physical and mechanical characteristics—were determined and applied.
Microstructural Features, Defects, and Corrosion Behaviour of 316L Stainless Steel Clads Deposited on Wrought Material by Powder- and Laser-Based Direct Energy Deposition with Relevance to Repair Applications
Authors: Revilla Reynier I. , De Graeve Iris
Published: October 2022

This work analyses the microstructural defects and the corrosion behaviour of 316L stainless steel clads deposited by laser metal deposition on wrought conventional material, which is a highly relevant system for repair applications. The different defects and microstructural features found in these systems were identified and analysed from a perspective relevant to the corrosion performance of these materials. The role of these features and defects on the corrosion process was evaluated by exposure of the samples to corrosive media and further examination of the corrosion morphology. The heat-affected zone, located on the wrought base material in close vicinity of the deposited clad, was identified to be the primary contributor to the corrosion activity of the system due to the large depletion of alloying elements in this region, which significantly decreased its pitting resistance. Alongside the heat-affected zones, relatively small (<30 µm in diameter) partially un-melted powder particles scattered across the surface of the clad were systematically identified as corrosion initiation spots, possibly due to their relatively high surface energy and therefore high reactivity compared to larger powder particles. This work highlights the need for more investigations on as-built surfaces of additively manufactured parts to better explore/understand the performance of the materials closer to their final applications. It demonstrates that the surface defects resulting from the additive manufacturing process, rather than the presence of the refined sub-granular cellular structure (as highlighted in previous works), play the predominant role in the corrosion behaviour of the system.
Roadmap: Numerical-Experimental Investigation and Optimization of 3D-Printed Parts Using Response Surface Methodology
Authors: Vanaei Hamid Reza , Khelladi Sofiane , Tcharkhtchi Abbas
Published: October 2022

Several process variables can be taken into account to optimize the fused filament fabrication (FFF) process, a promising additive manufacturing technique. To take into account the most important variables, a numerical-experimental roadmap toward the optimization of the FFF process, by taking into account some physico-chemical and mechanical characteristics, has been proposed to implement the findings through the thermal behavior of materials. A response surface methodology (RSM) was used to consider the effect of liquefier temperature, platform temperature, and print speed. RSM gave a confidence domain with a high degree of crystallinity, Young’s modulus, maximum tensile stress, and elongation at break. Applying the corresponding data from the extracted zone of optimization to the previously developed code showed that the interaction of parameters plays a vital role in the rheological characteristics, such as temperature profile of filaments during deposition. Favorable adhesion could be achieved through the deposited layers in the FFF process. The obtained findings nurture motivations for working on the challenges and bring us one step closer to the optimization objectives in the FFF process to solve the industrial challenges.
Effects of Severe Plastic Deformation and Ultrasonic Treatment on the Structure, Strength, and Corrosion Resistance of Mg-Al-Zn Alloy
Authors: Aksenov Denis A. , Nazarov Ayrat A. , Raab Georgiy I. , Raab Arseniy G. , Fakhretdinova Elvira I. , Asfandiyarov Rashid N. , Shishkunova Maria A. , Sementeeva Yulia R.
Published: October 2022

Nowadays, there is a great demand for increasing the strength and corrosion resistance of magnesium alloys for their wider use in machine engineering, oil industry, and medicine. This paper is devoted to a study on the effects of the combined process of reduction and equal channel angular pressing, as well as the subsequent ultrasonic irradiation on the structure, strength, and corrosion properties of the Mg-Al-Zn alloy. Deformation processing results in an increase of the strength up to 280 ± 10 MPa. A fine-grained structure is formed with a grain size of 10–20 µm and small recrystallized grains 1–2 µm in size. The corrosion resistance in the HCl medium falls down significantly. Action of ultrasound on the deformed specimen leads to an increased fraction of high-angle boundaries, in particular, the fractions of special, fully overlapping Σ13a boundaries and twin boundaries of Σ15b and Σ17a systems. Due to the ultrasonic treatment, the strength of the Mg-Al-Zn alloy increases up to 310 ± 5 MPa, while the corrosion resistance in HCl almost doubles.
Fiber-Optic Vector-Magnetic-Field Sensor Based on Gold-Clad Bent Multimode Fiber and Magnetic Fluid Materials
Authors: Liu Weinan , Pu Shengli , Hao Zijian , Wang Jia , Fan Yuanyuan , Zhang Chencheng , Wang Jingyue
Published: October 2022

A kind of bent multimode fiber (MMF) vector magnetic sensor based on surface plasmon resonance (SPR) was proposed. By plating gold film on the curved part of the bent multimode fiber, the surface plasmon mode (SPM) was excited via a whispering gallery mode (WGM). Fabricating the structure only required bending the fiber and plating it with gold, which perfectly ensured the integrity of the fiber and made it more robust compared with other structures. The sensor used magnetic fluid (MF) as the magnetically sensitive material. Through monitoring the shift of the surface plasmon resonance dip, the as-fabricated sensor not only had a high magnetic field intensity sensitivity of 9749 pm/mT but could also measure the direction of a magnetic field with a high sensitivity of 546.5 pm/°. The additional advantages of the proposed sensor lay in its easy fabrication and good integrity, which make it attractive in the field of vector-magnetic-field sensing.
Studying Performance and Kinetic Differences between Various Anode Electrodes in Proton Exchange Membrane Water Electrolysis Cell
Authors: Kang Zhenye , Fan Zihao , Zhang Fan , Zhang Zhenyu , Tian Chao , Wang Weina , Li Jing , Shen Yijun , Tian Xinlong
Published: October 2022

The electrode, as one of the most critical components in a proton exchange membrane water electrolysis (PEMWE) cell for hydrogen production, has a significant impact on cell performance. Electrodes that are fabricated via various techniques may exhibit different morphologies or properties, which might change the kinetics and resistances of the PEMWE. In this study, we have successfully fabricated several electrodes by different techniques, and the effects of electrode coating methods (ultrasonic spray, blade coating, and rod coating), hot press, and decal transfer processes are comprehensively investigated. The performance differences between various electrodes are due to kinetic or high frequency resistance changes, while the influences are not significant, with the biggest deviation of about 26 mV at 2.0 A cm−2. In addition, the effects of catalyst ink compositions, including ionomer to catalyst ratio (0.1 to 0.3), water to alcohol ratio (1:1 to 3:1), and catalyst weight percentage (10% to 30%), are also studied, and the electrodes’ performance variations are less than 10 mV at 2.0 A cm−2. The results show that the PEMWE electrode has superior compatibility and redundancy, which demonstrates the high flexibility of the electrode and its applicability for large-scale manufacturing.
Electrochemical SEIRAS Analysis of Imidazole-Ring-Functionalized Self-Assembled Monolayers
Authors: Pudžaitis Vaidas , Talaikis Martynas , Sadzevičienė Rita , Labanauskas Linas , Niaura Gediminas
Published: October 2022

An essential amino acid, histidine, has a vital role in the secondary structure and catalytic activity of proteins because of the diverse interactions its side chain imidazole (Im) ring can take part in. Among these interactions, hydrogen donating and accepting bonding are often found to operate at the charged interfaces. However, despite the great biological significance, hydrogen-bond interactions are difficult to investigate at electrochemical interfaces due to the lack of appropriate experimental methods. Here, we present a surface-enhanced infrared absorption spectroscopy (SEIRAS) and density functional theory (DFT) study addressing this issue. To probe the hydrogen-bond interactions of the Im at the electrified organic layer/water interface, we constructed Au-adsorbed self-assembled monolayers (SAMs) that are functionalized with the Im group. As the prerequisite for spectroelectrochemical investigations, we first analyzed the formation of the monolayer and the relationship between the chemical composition of SAM and its structure. Infrared absorption markers that are sensitive to hydrogen-bonding interactions were identified. We found that negative electrode polarization effectively reduced hydrogen-bonding strength at the Im ring at the organic layer–water interface. The possible mechanism governing such a decrease in hydrogen-bonding interaction strength is discussed.
Laboratory Investigation of the Low-Temperature Crack Resistance of Wood Tar-Based Rejuvenated Asphalt Mixture Based on the Semi-Circular Bend and Trabecular Bending Test
Authors: Liu Kefei , Liu Chonglin , Li Quan , Jiang Kang
Published: October 2022

Low-temperature crack resistance is the core issue affecting the promotion of rejuvenated asphalt, but most current studies do not consider the creep relaxation characteristics of rejuvenated asphalt mixture at low temperatures, which is inconsistent with the actual situation. To explore the low-temperature crack resistance of a wood tar-based rejuvenated asphalt mixture, we observed the low-temperature crack resistance of styrene butadiene styrene (SBS) modified asphalt, wood tar-based rejuvenated asphalt, and RA-102 rejuvenated asphalt and their mixtures using laboratory tests. Our results showed that the low temperature crack resistance of the wood tar-based rejuvenated asphalt mixture was better than that of the RA-102 rejuvenated asphalt mixture, but slightly worse than that of the original SBS asphalt mixture. After the synergistic action of wood tar and biomass fiber, wood tar can be fully mixed into the new asphalt, effectively alleviating the bonding failure between asphalt and aggregate and improving the stiffness of the mixture, so that the toughness and crack resistance of rejuvenated asphalt mixture at low temperatures are evidently improved. Wood tar-based rejuvenated asphalt mixture has a good creep deformation ability at low temperatures. The established creep damage model can better describe the flexural creep performance of rejuvenated asphalt mixtures at low temperatures, and can be used to infer the deformation characteristics at other low temperatures.
Unbalance Prediction of Low Pressure Rotor Based on Mechanism and Data Fusion
Authors: Wang Mingwei , Zhang Huibin , Liu Lei , Zhou Jingtao , Yao Lu , Ma Xin , Wang Manxian
Published: October 2022

The assembly, as the core part of low-pressure rotor manufacturing, is of great importance to ensure its unbalance. Low-voltage rotor assembly is a multi-process process influenced by the quality of part machining, assembly process, and assembly quality, resulting in unbalance that is difficult to predict during the assembly process. The unbalance measurement in the assembly process is important for the subsequent process optimization. Therefore, in order to achieve the prediction of unbalance measurement in the assembly process, this paper proposes an unbalance measurement prediction method based on mechanism and data fusion. Firstly, through research and analysis, the influencing factors of unbalance are determined, the low-pressure rotor blade sequencing mechanism model is established, and the blade sequencing optimization is realized by using reinforcement learning. Then, since the unbalance is formed after all the processes are completed and the subsequent work steps in the assembly process have not been carried out yet, the actual process parameters cannot be obtained, the semi-physical simulation method is used to combine the actual data of the assembled work steps with the theoretical data of the unassembled work steps to build a prediction model of the unbalance based on the BRNN (bidirectional recurrent neural network) network to achieve the prediction of the unbalance measurement in the assembly process. Finally, the model was validated using actual assembly process data, which proved the feasibility and effectiveness of the method.
Developing and Testing the Proto Type Structure for Micro Tool Fabrication
Authors: Xiao Hang , Hu Xiaolong , Luo Shaoqing , Li Wei
Published: October 2022

Compared with traditional machine tools, the micro machine tools have advantages of small volume, low cost, less energy consumption, high efficiency and high flexibility. Therefore, it is regarded as an important equipment for micro-cutting machining which has been used widely all over the world and. As a key component of the micro-cutting machine tools, the body structure directly influences the machining performance. Thus, an integral column and base structure for micro machining tools was proposed in this work, and the detailed structural parameters were designed based on parameter analysis. Besides, the static and dynamic performance of the proposed machine were analyzed and compared between the integral structure and the separated one. The deformation and stress of the proposed structures under typical working conditions were studied by numerical simulation, along with the natural frequencies, vibration modes and frequency response peaks. Further, optimization was performed on the integral body structure, the prototype of the micro-machine tool was trial-produced, and the positioning accuracy of each coordinate axis was qualitatively analyzed. In addition, the micro-milling test was carried out with 6061 aluminum alloy to show the performance of the novel cutting machine. The results revealed that the proposed integrated micro-machine bed structure is superior to the separated structure in terms of static deformation and harmonic response characteristics, with good comprehensive mechanical properties, greatly improved static and dynamic performance of the machine tool, significantly improved structural accuracy, improved processing quality of the specimen and good application value.
Improving Industrial Robot Positioning Accuracy to the Microscale Using Machine Learning Method
Authors: Bucinskas Vytautas , Dzedzickis Andrius , Sumanas Marius , Sutinys Ernestas , Petkevicius Sigitas , Butkiene Jurate , Virzonis Darius , Morkvenaite-Vilkonciene Inga
Published: October 2022

Positioning accuracy in robotics is a key issue for the manufacturing process. One of the possible ways to achieve high accuracy is the implementation of machine learning (ML), which allows robots to learn from their own practical experience and find the best way to perform the prescribed operation. Usually, accuracy improvement methods cover the generation of a positioning error map for the whole robot workspace, providing corresponding correction models. However, most practical cases require extremely high positioning accuracy only at a few essential points on the trajectory. This paper provides a methodology for the online deep Q-learning-based approach intended to increase positioning accuracy at key points by analyzing experimentally predetermined robot properties and their impact on overall accuracy. Using the KUKA-YouBot robot as a test system, we perform accuracy measurement experiments in the following three axes: (i) after a long operational break, (ii) using different loads, and (iii) at different speeds. To use this data for ML, the relationships between the robot’s operating time from switching on, load, and positioning accuracy are defined. In addition, the gripper vibrations are evaluated when the robot arm moves at various speeds in vertical and horizontal planes. It is found that the robot’s degrees of freedom (DOFs) clearances are significantly influenced by operational heat, which affects its static and dynamic accuracy. Implementation of the proposed ML-based compensation method resulted in a positioning error decrease at the trajectory key points by more than 30%.
Complex Dynamics of a Predator–Prey Interaction with Fear Effect in Deterministic and Fluctuating Environments
Authors: Santra Nirapada , Mondal Sudeshna , Samanta Guruprasad
Published: October 2022

Many ecological models have received much attention in the past few years. In particular, predator–prey interactions have been examined from many angles to capture and explain various environmental phenomena meaningfully. Although the consumption of prey directly by the predator is a well-known ecological phenomenon, theoretical biologists suggest that the impact of anti-predator behavior due to the fear of predators (felt by prey) can be even more crucial in shaping prey demography. In this article, we develop a predator–prey model that considers the effects of fear on prey reproduction and on environmental carrying capacity of prey species. We also include two delays: prey species birth delay influenced by fear of the predator and predator gestation delay. The global stability of each equilibrium point and its basic dynamical features have been investigated. Furthermore, the “paradox of enrichment” is shown to exist in our system. By analysing our system of nonlinear delay differential equations, we gain some insights into how fear and delays affect on population dynamics. To demonstrate our findings, we also perform some numerical computations and simulations. Finally, to evaluate the influence of a fluctuating environment, we compare our proposed system to a stochastic model with Gaussian white noise terms.
PARS: Proxy-Based Automatic Rank Selection for Neural Network Compression via Low-Rank Weight Approximation
Authors: Sobolev Konstantin , Ermilov Dmitry , Phan Anh-Huy , Cichocki Andrzej
Published: October 2022

Low-rank matrix/tensor decompositions are promising methods for reducing the inference time, computation, and memory consumption of deep neural networks (DNNs). This group of methods decomposes the pre-trained neural network weights through low-rank matrix/tensor decomposition and replaces the original layers with lightweight factorized layers. A main drawback of the technique is that it demands a great amount of time and effort to select the best ranks of tensor decomposition for each layer in a DNN. This paper proposes a Proxy-based Automatic tensor Rank Selection method (PARS) that utilizes a Bayesian optimization approach to find the best combination of ranks for neural network (NN) compression. We observe that the decomposition of weight tensors adversely influences the feature distribution inside the neural network and impairs the predictability of the post-compression DNN performance. Based on this finding, a novel proxy metric is proposed to deal with the abovementioned issue and to increase the quality of the rank search procedure. Experimental results show that PARS improves the results of existing decomposition methods on several representative NNs, including ResNet-18, ResNet-56, VGG-16, and AlexNet. We obtain a 3× FLOP reduction with almost no loss of accuracy for ILSVRC-2012ResNet-18 and a 5.5× FLOP reduction with an accuracy improvement for ILSVRC-2012 VGG-16.
Community Evolution Prediction Based on Multivariate Feature Sets and Potential Structural Features
Authors: Chen Jing , Zhao Haitong , Yang Xinyu , Liu Mingxin , Yu Zeren , Liu Miaomiao
Published: October 2022

The current study on community evolution prediction ignores the problem of internal community topology characteristics and does not take feature sets extraction into account. Therefore, the MF-PSF (Multivariate Feature sets and Potential Structural Features) method based on multivariate feature sets and potential structural features for community evolution prediction is proposed in this paper. Firstly, the multivariate feature sets are built from four aspects: community core node features, community structural features, community sequential features and community behavior features. Secondly, the community’s potential structural characteristics based on DeepWalk and spectral propagation theories are extracted, and the overall community’s internal structural characteristics and vertex distribution are analyzed. Finally, the community’s multivariate structural features and potential structural features are merged to predict community evolution events, and the importance of each feature in the process of evolutionary prediction is discussed. The experimental results show that compared with other community evolution prediction methods, the MF-PSF prediction method not only provides a foundation for analyzing the influence of various feature sets on predicted events, but it also effectively improves the accuracy of evolution prediction.
Bayesian and Frequentist Approaches for a Tractable Parametric General Class of Hazard-Based Regression Models: An Application to Oncology Data
Authors: Muse Abdisalam Hassan , Mwalili Samuel , Ngesa Oscar , Chesneau Christophe , Al-Bossly Afrah , El-Morshedy Mahmoud
Published: October 2022

In this study, we consider a general, flexible, parametric hazard-based regression model for censored lifetime data with covariates and term it the “general hazard (GH)” regression model. Some well-known models, such as the accelerated failure time (AFT), and the proportional hazard (PH) models, as well as the accelerated hazard (AH) model accounting for crossed survival curves, are sub-classes of this general hazard model. In the proposed class of hazard-based regression models, a covariate’s effect is identified as having two distinct components, namely a relative hazard ratio and a time-scale change on hazard progression. The new approach is more adaptive to modelling lifetime data and could give more accurate survival forecasts. The nested structure that includes the AFT, AH, and PH models in the general hazard model may offer a numerical tool for identifying which of them is most appropriate for a certain dataset. In this study, we propose a method for applying these various parametric hazard-based regression models that is based on a tractable parametric distribution for the baseline hazard, known as the generalized log-logistic (GLL) distribution. This distribution is closed under all the PH, AH, and AFT frameworks and can incorporate all of the basic hazard rate shapes of interest in practice, such as decreasing, constant, increasing, V-shaped, unimodal, and J-shaped hazard rates. The Bayesian and frequentist approaches were used to estimate the model parameters. Comprehensive simulation studies were used to evaluate the performance of the proposed model’s estimators and its nested structure. A right-censored cancer dataset is used to illustrate the application of the proposed approach. The proposed model performs well on both real and simulation datasets, demonstrating the importance of developing a flexible parametric general class of hazard-based regression models with both time-independent and time-dependent covariates for evaluating the hazard function and hazard ratio over time.
A Fast Singular Boundary Method for the Acoustic Design Sensitivity Analysis of Arbitrary Two- and Three-Dimensional Structures
Authors: Lan Liyuan , Cheng Suifu , Sun Xiatao , Li Weiwei , Yang Chao , Wang Fajie
Published: October 2022

This paper proposes a fast meshless scheme for acoustic sensitivity analysis by using the Burton–Miller-type singular boundary method (BM-SBM) and recursive skeletonization factorization (RSF). The Burton–Miller formulation was adopted to circumvent the fictitious frequency that occurs in external acoustic analysis, and then the direct differentiation method was used to obtain the sensitivity of sound pressure to design variables. More importantly, RSF was employed to solve the resultant linear system obtained by the BM-SBM. RSF is a fast direct factorization technique based on multilevel matrix compression, which allows fast factorization and application of the inverse in solving dense matrices. Firstly, the BM-SBM is a boundary-type collocation method that is a straightforward and accurate scheme owing to the use of the fundamental solution. Secondly, the introduction of the fast solver can effectively reduce the requirement of computer memory and increase the calculation scale compared to the conventional BM-SBM. Three numerical examples including two- and three-dimensional geometries indicate the precision and efficiency of the proposed fast numerical technique for acoustic design sensitivity analysis associated with large-scale and complicated structures.
The Impact of Intangible Assets on the Market Value of Companies: Cross-Sector Evidence
Authors: Dancaková Darya , Sopko Jakub , Glova Jozef , Andrejovská Alena
Published: October 2022

The impact of corporate intangibles on a company’s market value has been a widely debated topic. A large body of literature has separately examined the industry’s effect- or firm-specific attributes, such as industry type, company size, company age, or indebtedness and profitability, on the motivation to disclose information on intangible assets, but without considering a comprehensive view. This paper examines the role intangible assets play in a firm’s market valuation besides other firm-specific characteristics. The reducted dataset we use in this study comprises 250 publicly traded companies operating in four different business sectors in France, Germany, and Switzerland for the ten years from 2009 to 2018. Based on the panel data regression models, the study provides an extension of previous knowledge about the effect intangible assets may have on the investors’ view of a company’s value, where the value added of this paper is the empirical evidence of a possible link between the intangible assets’ disclosure and the market value of German, French, and Swiss enterprises. The importance of our contribution lies in a comparative analysis carried out to reveal substantial differences in the impact of intangible assets and innovation activity on the market value firms in three European countries and across four industry sectors. Although the results show the positive impact of intangible assets on the companies’ market value, we suggest that investors still assess companies based on their profitability rather than considering the information on intangible assets the enterprises disclose in their financial statements.
Bifurcation Analysis and Numerical Study of Wave Solution for Initial-Boundary Value Problem of the KdV-BBM Equation
Authors: Suebcharoen Teeranush , Poochinapan Kanyuta , Wongsaijai Ben
Published: October 2022

In this work, we study the bifurcation and the numerical analysis of the nonlinear Benjamin-Bona-Mahony-KdV equation. According to the bifurcation theory of a dynamic system, the various kinds of traveling wave profiles are obtained including the behavior of solitary and periodic waves. Additionally, a two-level linear implicit finite difference algorithm is implemented for investigating the Benjamin-Bona-Mahony-KdV model. The application of a priori estimation for the approximate solution also provides the convergence and stability analysis. It was demonstrated that the current approach is singularly solvable and that both time and space convergence are of second-order precision. To confirm the computational effectiveness, two numerical simulations are prepared. The findings show that the current technique performs admirably in terms of delivering second-order accuracy in both time and space with the maximum norm while outperforming prior schemes.
Comparison of Two Aspects of a PDE Model for Biological Network Formation
Authors: Astuto Clarissa , Boffi Daniele , Haskovec Jan , Markowich Peter , Russo Giovanni
Published: October 2022

We compare the solutions of two systems of partial differential equations (PDEs), seen as two different interpretations of the same model which describes the formation of complex biological networks. Both approaches take into account the time evolution of the medium flowing through the network, and we compute the solution of an elliptic–parabolic PDE system for the conductivity vector m, the conductivity tensor C and the pressure p. We use finite differences schemes in a uniform Cartesian grid in a spatially two-dimensional setting to solve the two systems, where the parabolic equation is solved using a semi-implicit scheme in time. Since the conductivity vector and tensor also appear in the Poisson equation for the pressure p, the elliptic equation depends implicitly on time. For this reason, we compute the solution of three linear systems in the case of the conductivity vector m∈R2 and four linear systems in the case of the symmetric conductivity tensor C∈R2×2 at each time step. To accelerate the simulations, we make use of the Alternating Direction Implicit (ADI) method. The role of the parameters is important for obtaining detailed solutions. We provide numerous tests with various values of the parameters involved to determine the differences in the solutions of the two systems.
Antimicrobial Secondary Metabolites from the Mangrove Plants of Asia and the Pacific
Authors: Sulaiman Mazdida , Nissapatorn Veeranoot , Rahmatullah Mohammed , Paul Alok K. , Rajagopal Mogana , Rusdi Nor Azizun , Seelan Jaya Seelan Sathya , Suleiman Monica , Zakaria Zainul Amiruddin , Wiart Christophe
Published: October 2022

Microbes such as the White Spot Syndrome Virus account for severe losses in the shrimp farming industry globally. This review examines the literature on the mangrove plants of Asia and the Pacific with antibacterial, antifungal, or antiviral activities. All of the available data published on this subject were collected from Google Scholar, PubMed, Science Direct, Web of Science, ChemSpider, PubChem, and a library search from 1968 to 2022. Out of about 286 plant species, 119 exhibited antimicrobial effects, and a total of 114 antimicrobial natural products have been identified including 12 with MIC values below 1 µg/mL. Most of these plants are medicinal. The mangrove plants of Asia and the Pacific yield secondary metabolites with the potential to mitigate infectious diseases in shrimp aquaculture.
Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort
Authors: Hong Seung Baek , Lee Nam Kyung , Kim Suk , Um Kyunga , Kim Keunyoung , Kim In Joo
Published: October 2022

The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman’s rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.
Nociception Level Index-Directed Erector Spinae Plane Block in Open Heart Surgery: A Randomized Controlled Clinical Trial
Authors: Balan Cosmin , Tomescu Dana R. , Valeanu Liana , Morosanu Bianca , Stanculea Iulia , Coman Antonia , Stoian Anca , Bubenek-Turconi Serban I.
Published: October 2022

Background and Objectives: The erector spinae plane block (ESPB) is a multimodal opioid-sparing component, providing chest-wall analgesia of variable extent, duration, and intensity. The objective was to examine the ESPB effect on perioperative opioid usage and postoperative rehabilitation when used within a Nociception Level (NOL) index-directed anesthetic protocol. Materials and Methods: This prospective, randomized, controlled, open-label study was performed in adult patients undergoing on-pump cardiac surgery in a single tertiary hospital. Eighty-three adult patients who met eligibility criteria were randomly allocated to group 1 (Control, n = 43) and group 2 (ESPB, n = 40) and received general anesthesia with NOL index-directed fentanyl dosing. Preoperatively, group 2 also received bilateral single-shot ultrasound-guided ESPB (1.5 mg/kg/side 0.5% ropivacaine mixed with dexamethasone 8 mg/20 mL). Postoperatively, both groups received intravenous paracetamol (1 g every 6 h). Morphine (0.03 mg/kg) was administered for numeric rating scale (NRS) scores ≥4. Results: The median (IQR, 25th–75th percentiles) intraoperative fentanyl and 48 h morphine dose in group 2-to-group 1 were 1.2 (1.1–1.5) vs. 4.5 (3.8–5.5) µg·kg−1·h−1 (p < 0.001) and 22.1 (0–40.4) vs. 60.6 (40–95.7) µg/kg (p < 0.001). The median (IQR) time to extubation in group 2-to-group 1 was 90 (60–105) vs. 360 (285–510) min (p < 0.001). Two hours after ICU admission, 87.5% of ESPB patients were extubated compared to 0% of controls (p < 0.001), and 87.5% were weaned off norepinephrine compared to 46.5% of controls (p < 0.001). The median NRS scores at 0, 6, 12, 24, and 48 h after extubation were significantly decreased in group 2. There was no difference in opioid-related adverse events and length of stay. Conclusions: NOL index-directed ESPB reduced intraoperative fentanyl by 73.3% and 48 h morphine by 63.5%. It also hastened the extubation and liberation from vasopressor support and improved postoperative analgesia.
Obtaining Bioproducts from the Studies of Signals and Interactions between Microalgae and Bacteria
Authors: Santo Évellin do Espirito , Ishii Marina , Pinto Uelinton Manoel , Matsudo Marcelo Chuei , Carvalho João Carlos Monteiro de
Published: October 2022

The applications of microalgae biomass have been widely studied worldwide. The classical processes used in outdoor cultivations of microalgae, in closed or open photobioreactors, occur in the presence of bacteria. Understanding how communication between cells occurs through quorum sensing and evaluating co-cultures allows the production of microalgae and cyanobacteria to be positively impacted by bacteria, in order to guarantee safety and profitability in the production process. In addition, the definition of the effects that occur during an interaction, promotes insights to improve the production of biomolecules, and to develop innovative products. This review presents the interactions between microalgae and bacteria, including compounds exchanges and communication, and addresses the development of new pharmaceutical, cosmetic and food bioproducts from microalgae based on these evaluations, such as prebiotics, vegan skincare products, antimicrobial compounds, and culture media with animal free protein for producing vaccines and other biopharmaceutical products. The use of microalgae as raw biomass or in biotechnological platforms is in line with the fulfillment of the 2030 Agenda related to the Sustainable Development Goals (SDGs).
Molecular Epidemiology of mcr-1-Positive Escherichia coli and Klebsiella pneumoniae Isolates: Results from Russian Sentinel Surveillance (2013–2018)
Authors: Shapovalova Valeria , Shaidullina Elvira , Azizov Ilya , Sheck Eugene , Martinovich Alexey , Dyachkova Marina , Matsvay Alina , Savochkina Yulia , Khafizov Kamil , Kozlov Roman , Shipulin German , Edelstein Mikhail
Published: October 2022

Background: The dissemination of mobile colistin resistance (mcr) genes is a serious healthcare threat because polymyxins represent “last-line” therapeutics for multi-drug-resistant Gram-negative pathogens. This study aimed to assess the prevalence of colistin resistance and mcr genes and characteristics of clinical Escherichia coli (Eco) and Klebsiella pneumoniae (Kpn) isolates and plasmids carrying these genes in Russia. Methods: A total of 4324 Eco and 4530 Kpn collected in the frame of sentinel surveillance in 2013–2018 were tested for susceptibility to colistin and other antibiotics using the broth microdilution method. mcr genes were screened by real-time PCR. Phylogeny, genomic features and plasmids of mcr-positive isolates were assessed using whole-genome sequencing and subsequent bioinformatic analysis. Results: Colistin resistance was detected in 2.24% Eco and 9.3% Kpn. Twenty-two (0.51%) Eco and two (0.04%) Kpn from distant sites carried mcr-1.1. Most mcr-positive isolates co-harbored ESBLs and other resistance determinants to various antibiotic classes. The mcr-positive Eco belonged to 16 MLST types, with ST359 being most common; Kpn belonged to ST307 and ST23. mcr-1.1 was carried mainly in IncI2 (n = 18) and IncX4 (n = 5) plasmids highly similar to those identified previously in human, animal and environmental isolates. Conclusion: This study demonstrated a dissemination of “typical” mcr-bearing plasmids among diverse Eco and Kpn genotypes and across a wide geographic area in Russia. Given the frequent association of mcr with other resistance determinants and potential clinical impact, the continual surveillance of this threat is warranted.
In Vitro Antiparasitic Activity of Propyl-Propane-Thiosulfinate (PTS) and Propyl-Propane-Thiosulfonate (PTSO) from Allium cepa against Eimeria acervulina Sporozoites
Authors: Aguinaga-Casañas María Arántzazu , Mut-Salud Nuria , Falcón-Piñeiro Ana , Alcaraz-Martínez Ángela , Guillamón Enrique , Baños Alberto
Published: October 2022

Among the alternatives to control avian coccidiosis, alliaceous extracts stand out due to their functional properties. Despite this, most of the references are focused just on garlic. In this study, we analyze the in vitro effects of propyl-propane thiosulfinate (PTS) and propyl-propane thiosulfonate (PTSO), two organosulfur compounds from onion, on MDBK cells infected with sporozoites of Eimeria acervulina. To this aim, two different experiments were performed. In the first experiment, sporozoites were previously incubated for 1 h at 1, 5 and 10 µg/mL of PTS or PTSO and added to MDBK cells. In the second experiment, MDBK cells were first incubated for 24 h at different concentrations of PTS or PTSO and then infected with E. acervulina sporozoites. Then, 24 h after inoculation, the presence of E. acervulina was quantified by qPCR. MDBK viability was measured at 72 h post-infection. Sporozoites incubated at 10 µg/mL of PTS and PTSO inhibited the capability to penetrate the cells up to 75.2% ± 6.44 and 71.7% ± 6.03, respectively. The incubation of MDBK with each compound resulted in a preventive effect against sporozoite invasion at 1 µg/mL of PTS and 1 and 10 µg/mL of PTSO. Cells incubated with PTSO obtained similar viability percentages to uninfected cells. These results suggest that the use of PTS and PTSO is a promising alternative to coccidiosis treatment, although further in vivo studies need to be performed.
Highly Efficient Solution-Processed Blue Phosphorescent Organic Light-Emitting Diodes Based on Co-Dopant and Co-Host System
Authors: Wang Jingyu , Yin Jiaxuan , Li Xiaofang , Wang Zhe , Wu Ruixia , Zhou Liang
Published: October 2022

The low-lying HOMO level of the blue emitter and the interfacial miscibility of organic materials result in inferior hole injection, and long exciton lifetime leads to triplet-triplet annihilation (TTA) and triplet-polaron annihilation (TPA), so the efficiencies of blue phosphorescent organic light-emitting diodes (PhOLEDs) are still unsatisfactory. Herein, we design co-host and co-dopant structures to improve the efficiency of blue PhOLEDs by means of solution processing. TcTa acts as hole transport ladder due to its high-lying HOMO level, and bipolar mCPPO1 helps to balance carriers’ distribution and weaken TPA. Besides the efficient FIr6, which acts as the dominant blue dopant, FCNIrPic was introduced as the second dopant, whose higher HOMO level accelerates hole injection and high triplet energy facilitates energy transfer. An interesting phenomenon caused by microcavity effect between anode and cathode was observed. With increasing thickness of ETL, peak position of electroluminescence (EL) spectrum red shifts gradually. Once the thickness of ETL exceeded 140 nm, emission peak blue-shifts went back to its original position. Finally, the maximum current efficiency (CE), power efficiency (PE), and external quantum efficiency (EQE) of blue phosphorescent organic light-emitting diode (PhOLED) went up to 20.47 cd/A, 11.96 lm/W, and 11.62%, respectively.
Novel Type of Tetranitrosyl Iron Salt: Synthesis, Structure and Antibacterial Activity of Complex [FeL’2(NO)2][FeL’L”(NO)2] with L’-thiobenzamide and L”-thiosulfate
Authors: Sanina Nataliya A. , Starostina Arina A. , Utenyshev Andrey N. , Dorovatovskii Pavel V. , Emel’yanova Nina S. , Krapivin Vladimir B. , Luzhkov Victor B. , Mumyatova Viktoriya A. , Balakina Anastasiya A. , Terentiev Alexei A. , Aldoshin Sergey M.
Published: October 2022

In this work a new donor of nitric oxide (NO) with antibacterial properties, namely nitrosyl iron complex of [Fe(C6H5C-SNH2)2(NO)2][Fe(C6H5C-SNH2)(S2O3)(NO)2] composition (complex I), has been synthesized and studied. Complex I was produced by the reduction of the aqueous solution of [Fe2(S2O3)2(NO)2]2− dianion by the thiosulfate, with the further treatment of the mixture by the acidified alcohol solution of thiobenzamide. Based on the structural study of I (X-ray analysis, quantum chemical calculations by NBO and QTAIM methods in the frame of DFT), the data were obtained on the presence of the NO…NO interactions, which stabilize the DNIC dimer in the solid phase. The conformation properties, electronic structure and free energies of complex I hydration were studied using B3LYP functional and the set of 6–31 + G(d,p) basis functions. The effect of an aquatic surrounding was taken into account in the frame of a polarized continuous model (PCM). The NO-donating activity of complex I was studied by the amperometry method using an “amiNO-700” sensor electrode of the “inNO Nitric Oxide Measuring System”. The antibacterial activity of I was studied on gram-negative (Escherichia coli) and gram-positive (Micrococcus luteus) bacteria. Cytotoxicity was studied using Vero cells. Complex I was found to exhibit antibacterial activity comparable to that of antibiotics, and moderate toxicity to Vero cells.
New Cycloadditon Reaction of 2-Chloroprop-2-enethioamides with Dialkyl Acetylenedicarboxylates: Synthesis of Dialkyl 2-[4,5-bis(alkoxycarbonyl)-2-(aryl{alkyl}imino)-3(2H)-thienylidene]-1,3-dithiole-4,5-dicarboxylates
Authors: Ogurtsov Vladimir A. , Rakitin Oleg A.
Published: October 2022

The 1,3-dipolar cycloaddition of 1,2-dithiole-3-thiones with alkynes to form 1,3-dithioles is one of the most studied reactions in this class of polysulfur-containing heterocycles. Nucleophilic substitution of chlorine atoms in dimethyl 2-(1,2-dichloro-2-thioxoethylidene)-1,3-dithiole-4,5-dicarboxylate, which was obtained by addition one molecules of DMAD to 4,5-dichloro-3H-1,2-dithiole-3-thione, led to a series of 2-chloro-2-(1,3-dithiol-2-ylidene)ethanethioamides. Cycloaddition reaction of 2-chloro-2-(1,3-dithiol-2-ylidene)ethanethioamides with activated alkynes led to the unexpected formation of 2-(thiophen-3(2H)-ylidene)-1,3-dithioles via new intermediate, 1-(1,3-dithiol-2-ylidene)-N-phenylethan-1-yliumimidothioate. Structure of dimethyl 2-(4,5-bis(methoxycarbonyl)-2-(phenylimino)thiophen-3(2H)-ylidene)-1,3-dithiole-4,5-dicarboxylate was finally proven by single crystal X-ray diffraction study. Optimized reaction conditions and a mechanistic rationale for the 1,3-dipolar cycloaddition of novel intermediate are presented.
Antifungal Activity of Amphiphilic Perylene Bisimides
Authors: Roa-Linares Vicky C. , Mesa-Arango Ana C. , Zaragozá Ramón J. , González-Cardenete Miguel A.
Published: October 2022

Perylene-based compounds, either naturally occurring or synthetic, have shown interesting biological activities. In this study, we report on the broad-spectrum antifungal properties of two lead amphiphilic perylene bisimides, compounds 4 and 5, which were synthesized from perylene-3,4,9,10-tetracarboxylic dianhydride by condensation with spermine and an ammonium salt formation. The antifungal activity was evaluated using a collection of fungal strains and clinical isolates from patients with onychomycosis or sporotrichosis. Both molecules displayed an interesting antifungal profile with MIC values in the range of 2–25 μM, being as active as several reference drugs, even more potent in some particular strains. The ammonium trifluoroacetate salt 5 showed the highest activity with a MIC value of 2.1 μM for all tested Candida spp., two Cryptococcus spp., two Fusarium spp., and one Neoscytalidium spp. strain. Therefore, these amphiphilic molecules with the perylene moiety and cationic ammonium side chains represent important structural features for the development of novel antifungals.