bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Mesoporous Silica Speed Up Degradation of Benzodiazepines? Hints from Quantum Mechanical Investigations
Authors: Delle Piane Massimo , Corno Marta
Published: February 2022

This work reports for the first time a quantum mechanical study of the interactions of a model benzodiazepine drug, i.e., nitrazepam, with various models of amorphous silica surfaces, differing in structural and interface properties. The interest in these systems is related to the use of mesoporous silica as carrier in drug delivery. The adopted computational procedure has been chosen to investigate whether silica–drug interactions favor the drug degradation mechanism or not, hindering the beneficial pharmaceutical effect. Computed structural, energetics, and vibrational properties represent a relevant comparison for future experiments. Our simulations demonstrate that adsorption of nitrazepam on amorphous silica is a strongly exothermic process in which a partial proton transfer from the surface to the drug is observed, highlighting a possible catalytic role of silica in the degradation reaction of benzodiazepines.
Advances in Carbon-Based Microwave Absorbing Materials
Authors: Du Yunchen
Published: February 2022

Electromagnetic (EM) pollution has been evolving as one of the most concerning environmental problems in current society, due to the extensive application of EM technology, from household electronic apparatuses to wireless base stations, as well as military radars [...]
Corrosion Resistance of Novel Fly Ash-Based Forsterite-Spinel Refractory Ceramics
Authors: Nguyen Martin , Sokolář Radomír
Published: February 2022

This article aims to investigate the corrosion resistance of novel fly ash–based forsterite–spinel (Mg2SiO4-MgAl2O4) refractory ceramics to various corrosive media in comparison with reactive alumina–based ceramics. Because fly ash is produced in enormous quantities as a byproduct of coal-burning power stations, it could be utilized as an affordable source of aluminum oxide and silicon oxide. Corrosion resistance to iron, clinker, alumina, and copper was observed by scanning electron microscope with an elemental probe. The influence on the properties after firing was also investigated. Fly ash–based and reactive alumina–based mixtures were designed to contain 10%, 15% and 20% of spinel after firing. Raw material mixtures were sintered at 1550 °C for two hours. X-ray diffraction analysis and scanning electron microscopy were used to analyze sintered samples. The apparent porosity, bulk density, modulus of rupture, and refractory and thermo–mechanical properties were also investigated. The experimental results disclosed that the modulus of rupture, thermal shock resistance and microstructure were improved with increasing amounts of spinel in the fired samples. An analysis of the transition zones between corrosive media and ceramics revealed that all mixtures have good resistance against corrosion to iron, clinker, aluminum and copper.
Quantification of Residual Stress Relief by Heat Treatments in Austenitic Cladded Layers
Authors: Rebelo Kornmeier Joana , Marques Maria José , Gan Weimin , Batista António Castanhola , Paddea Sanjooram , Loureiro Altino
Published: February 2022

The effect of the heat treatment on the residual stresses of welded cladded steel samples is analyzed in this study. The residual stresses across the plate’s square sections were determined using complementary methods; applying diffraction with neutron radiation and mechanically using the contour method. The analysis of the large coarse grain austenitic cladded layers, at the feasibility limits of diffraction methods, was only made possible by applying both methods. The samples are composed of steel plates, coated on one of the faces with stainless steel filler metals, this coating process, usually known as cladding, was carried out by submerged arc welding. After cladding, the samples were submitted to two different heat treatments with dissimilar parameters: one at a temperature of 620 °C maintained for 1 h and, the second at 540 °C, for ten hours. There was some difference in residual stresses measured by the two techniques along the surface of the coating in the as-welded state, although they are similar at the welding interface and in the heat-affected zone. The results also show that there is a residual stress relaxation for both heat-treated samples. The heat treatment carried out at a higher temperature showed sometimes more than 50% reduction in the initial residual stress values and has the advantage of being less time consuming, giving it an industrial advantage and making it more viable economically.
Biocompatibility and Antibacterial Action of Salvadora persica Extract as Intracanal Medication (In Vitro and Ex Vivo Experiment)
Authors: Abdeltawab Samah Samir , Abu Haimed Tariq S. , Bahammam Hammam Ahmed , Arab Wafaa Talat , Abou Neel Ensanya A. , Bahammam Laila Ahmed
Published: February 2022

This study aimed to test the biocompatibility and antibacterial properties of Salvadora persica (S. persica) extract, a natural product, as an intracanal medication in comparison with calcium hydroxide (Metapaste, META BIOMED, Cheongju, Korea). The pH values of both materials were tested. The biocompatibility of S. persica extract and Metapaste was determined using light microscopy and MTT assays. The antibacterial action was tested using the zone of bacterial inhibition on four common bacterial species. In addition, intracanal medication was administered using 68 extracted single-rooted teeth contaminated with Enterococcus faecalis (E. faecalis), and the percentage reduction in colony count (% RCC) at 1, 3, and 7 days was measured. The extension of activity for both materials was assessed using histological sections and scanning electron microscopy. S. persica was found to be acidic in nature. Both materials showed significantly lower cell viability than the positive control cells on days 1 and 3 but not on day 7. S. persica showed better antibacterial effects against E. faecalis and S. mutans. S. persica extract showed 97.6%, 98.9%, and 99.3% RCC values at 1, 3, and 7 days, respectively, which are comparable to those of Metapaste. S. persica herbal extract is a promising material that can be utilized as an intracanal medication, but its use requires further research.
Embedded Target Filler and Natural Fibres as Interface Agents in Controlling the Stretchability of New Starch and PVOH-Based Materials for Rethinked Sustainable Packaging
Authors: Dimonie Doina , Trica Bogdan , Damian Celina , Trusca Roxana
Published: February 2022

A structuring solution converting starch into a multiphase polymeric material was obtained through a melt compounding sequence, which can be irreversibly shaped by thermoforming into rethinked, sustainable packaging, based on the physical modification of starch with polyvinyl alcohol (PVOH), target fillers, (CaCO3 and wood flour), and a good plasticizer compatible with the polar components. Polymeric material can be thermoformed if it can be stretched without breaking in the positive temperature range, have functional properties required by the application, and keep its shape and properties after stretching for more than six months. The properties of the selected quaternary starch-based compound, fulfil the requirements for a thermoformable polymeric material due to the chemical compatibility between the components and the compounding in a selected procedure and optimal conditions wich ensure a comfortable miscibility. Most likely, the obtained miscibility can be explained only by the arrangement of the wood flour at the interface, where it acts as compatibilizer with a main role in structuring the new starch-based materials. The compatibilizer role of the wood flour was proved for the quaternary selected blend by the changing of the thermal degradation mechanism, from one with two stages for binary and tertiary blends, to one consisting of a single stage: decreasing till elimination of morphological defects, the reproducibility of the mechanical properties, stretching without breaking, and dimensional stability after stretching. Future studies will aim to achieve rethinked packaging for applications that require higher strength properties.
Assessment of the Influence of Selected Technological Parameters on the Morphology Parameters of the Cutting Surfaces of the Hardox 500 Material Cut by Abrasive Water Jet Technology
Authors: Krenicky Tibor , Olejarova Stefania , Servatka Milos
Published: February 2022

This article deals with the evaluation of selected aspects of abrasive water jet technology (AWJ) in the cutting of abrasion-resistant steel (HARDOX 500) with a thickness of 40 mm. The high abrasion resistance as a typical significant property of this steel ranks it among the special materials that are increasingly used. As the AWJ is a multiparametric technology, selected levels of feed rate, abrasive mass flow and pump working pressure were used in the experiments from the spectrum of technological parameters. For the purposes of evaluation, the examined cut surfaces were documented by a modified photographic method of displaying the cut surface by means of side lighting on the untreated cutting surface. The experimental part evaluates the dependences of selected cutting surface quality parameters (surface roughness and abrasive water jet deflection) on selected important technological parameters of the production system with AWJ technology (abrasive mass flow, technological head feed rate and pump working pressure). Based on the evaluation of the experiments, regression models were created to interpolate and extrapolate data to compare or supplement existing solutions in the field of research and as a basis for optimizing operating costs and increasing the efficiency of production systems with abrasive water jet technology.
Preparation and Characterization of Glass-Ceramic Foam from Clay-Rich Waste Diatomaceous Earth
Authors: Sedlačík Martin , Nguyen Martin , Opravil Tomáš , Sokolář Radomír
Published: February 2022

In this study, the potential use of waste diatomaceous earth from the production of diatomaceous earth for filtration purposes, as an alternative raw material for foam glass production, was explored. The chemical and mineralogical composition and the high temperature behavior of waste diatomite were studied to assess its suitability for foam glass production. Glass-ceramic foams were prepared using NaOH solution as a foaming agent, via a hydrate mechanism. The influence of different pretreatments and firing temperatures on the foam’s structure, bulk density and compressive strength was investigated. High temperature behavior was studied using TG/DTA analysis and high temperature microscopy. Phase composition was studied using X-ray diffraction analysis. Glass-ceramic foam samples of a high porosity comparable to conventional foam glass products were fabricated. The pretreatment temperature, foaming temperature and sintering holding time were found to have a significant influence on foam properties. With increased pretreatment temperature, pyrogenic carbon from the thermal decomposition of organic matter contained in the raw material acted as an additional foaming agent and remained partially unoxidized in prepared foams. The bulk densities of prepared samples ranged from 150 kg/m3 to 510 kg/m3 and their compressive strengths were between 140 and 1270 kPa.
The Effect of Cooling Rate on the Microstructure Evolution and Mechanical Properties of Ti-Microalloyed Steel Plates
Authors: Li Xiaolin , Li Qian , Li Haozhe , Gao Xiangyu , Deng Xiangtao , Wang Zhaodong
Published: February 2022

Ti-bearing microalloyed steel plates with a thickness of 40 mm were subjected to ultra-fast cooling (UFC) and traditional accelerate cooling after hot-rolling, aiming to investigate the effect of cooling rate on the microstructure and mechanical properties homogeneity, and thus obtain thick plates with superior and homogeneous mechanical properties. Yield strength, tensile strength, and elongation were 642 MPa, 740 MPa, 19.2% and 592 MPa, 720 MPa and 16.7%, respectively, in the surface and mid-thickness of the steel with ultra-fast cooling, while in the steel with traditional accelerate cooling, 535 MPa, 645 MPa, 23.4% and 485 MPa, 608 MPa, 16.2% were obtained in the surface and mid-thickness of the plate. The yield strength has been greatly improved after UFC, for the refinement of grain and precipitates produced by UFC. In addition, the equivalent grain size and precipitates size in the thick plate with UFC are homogeneous in the thickness direction, leading to uniform mechanical properties. The crystallographic characteristics of different precipitates have been studied. The precipitates formed in the austenite deformation stage obey Kurdjumov–Sachs orientation relationship with the ferrite matrix, while the fine precipitates formed in the ferrite obey [112]MC//[110]α and (1¯1¯1)MC//(1¯12)α orientation relationship with the ferrite matrix.
A Review of Research on Mechanical Properties and Durability of Concrete Mixed with Wastewater from Ready-Mixed Concrete Plant
Authors: Yao Xianhua , Xi Junyi , Guan Junfeng , Liu Lijun , Shangguan Linjian , Xu Zhaowen
Published: February 2022

The wastewater from ready-mixed concrete plants is currently being recycled as concrete mixing water. It has attracted significant attention from the construction industry and researchers since it promotes sustainable development through environmental protection, energy-saving, and emissions reduction. This article review first introduces the nature of wastewater in ready-mixed concrete plants in different regions. Then the effects of solid content in water on various properties of concrete, including working performance, durability and microscopic properties, are reviewed, respectively, when concrete is mixed with wastewater instead of tap water. Furthermore, the microscopic mechanism of action in concrete mixing with wastewater is discussed, and future work is recommended. This review provides fundamentals on the study of the properties of concrete after wastewater is mixed into concrete.
The Performance Evaluation of Asphalt Mortar and Asphalt Mixture Containing Municipal Solid Waste Incineration Fly Ash
Authors: Zhao Xiaowen , Ge Dongdong , Wang Jiaqing , Wu Dianwen , Liu Jun
Published: February 2022

The aim of the research is to quantify the property of asphalt mortar and asphalt mixture containing municipal solid waste incineration (MSWI) fly ash. The potential of partially replacing mineral fillers with MSWI fly ash in asphalt mixture production was investigated. Five different MSWI fly ash replacement ratios, which include 0%, 25%, 50%, 75%, and 100%, were adopted to assess the influence of fly ash dosage, and the optimum fly ash replacement ratio was proposed. The rheological characteristics of asphalt mortar with MSWI fly ash were assessed with the dynamic shear rheometer (DSR) and bending beam rheometer (BBR). The high temperature properties of the mixture with MSWI fly ash were assessed with the Marshall stability test and the rutting test. The low temperature cracking property was determined with the indirect tensile strength test at low temperatures. The moisture stability property was identified with the immersed Marshall test and the freeze-thaw cycles conditioned indirect tensile strength test. Based on the test results, the addition of fly ash and mineral filler remarkably increased the ǀG*ǀ of the asphalt mortar. The δ of asphalt decreased as the dosage of fly ash and mineral filler increased. The addition of fly ash and mineral filler degraded the low temperature characteristics of the mortar. Fly ash improved the high temperature characteristics of the asphalt mixture. The asphalt mixture with MSWI fly ash was more susceptible to thermal cracking than the control sample. The addition of fly ash weakened the moisture stability of the asphalt mixture. In order to guarantee the low temperature characteristics and the moisture susceptibility of the asphalt mixture, the fly ash replacement ratio was recommended to be set around 25%. With proper mixture design and fly ash dosage, the asphalt mixture would have adequate performance, as well as reduced environmental impact.
Structural, Morphological, Optical and Electrical Characterization of Gahnite Ferroan Nano Composite Derived from Fly Ash Silica and ZnO Mixture
Authors: Panda Sushree Saraswati , Tripathy Hara Prasada , Pattanaik Priyabrata , Mishra Dilip Kumar , Kamilla Sushanta Kumar , Khandual Asimananda , Holderbaum William , Sherwood Richard , Hawkins Gary , Masakapalli Shyam Kumar
Published: February 2022

The synthesis of a high value-added product, gahnite ferroan nano composite, from a mixture of fly ash silica and ZnO is a low-cost and non-expensive technique. The XRD pattern clearly reveals the synthesized product from fly ash after leaching is a product of high-purity gahnite ferroan composite. The grains are mostly cubical in shape. The optical band gap of powdered gahnite ferroan nano composite is 3.37 eV, which acts as a UV protector. However, the bulk sample shows that the 500 to 700 nm wavelength of visible light is absorbed, and UV light is allowed to pass through. So, the bulk sample acts as a band pass filter of UV light which can be used in many optical applications for conducting UV-irradiation activity. Dielectric permittivity and dielectric loss increase with a rise in temperature. The increase in the ac conductivity at higher temperatures denotes the negative temperature coefficient resistance (NTCR) behavior of the material.
Feasibility of Predictive Models for the Quality of Additive Manufactured Components Based on Artificial Neural Networks
Authors: Grozav Sorin D. , Sterca Alexandru D. , Kočiško Marek , Pollák Martin , Ceclan Vasile
Published: February 2022

Additive manufacturing technologies present a series of advantages such as high flexibility, direct CAD to final product fabrication, and compact production techniques which make them an attractive option for fields ranging from medicine and aeronautics to rapid prototyping and Industry 4.0 concepts. However, additive manufacturing also presents a series of disadvantages, the most notable being low dimensional accuracy, low surface quality, and orthotropic mechanical behaviour. These characteristics are influenced by material properties and the process parameters used during manufacturing. Therefore, a predictive model for the characteristics of additive manufactured components is conceivable. This paper proposes a study on the feasibility of implementing Deep Neural Networks for predicting the dimensional accuracy and the mechanical characteristics of components obtained through the Fused Deposition Modelling method using empirical data acquired by high precision metrology. The study is performed on parts manufactured using PETG and PLA materials with known process parameters. Different Deep Neural Network architectures are trained using datasets acquired by high precision metrology, and their performance is tested by comparing the mean absolute error of predictions on training and validation data. Results show good model generalisation and convergence at high accuracy, indicating that a predictive model is feasible.
A Systematic Analysis of Printed Circuit Boards Bending during In-Circuit Tests
Authors: Oliveira Rui , Freitas Luís , Costa Diogo , Vicente José , Gonçalves Arminda Manuela , Malheiro Teresa , Machado José
Published: February 2022

When performing In-Circuit Tests (ICTs) of Printed Circuit Boards (PCBs), there are certain phenomena related with strain analysis that must be known in order to obtain stronger and more accurate testing results. During testing, PCBs are often subjected to mechanical bending efforts that induce excessive strain. This study focuses on the building of a Finite Elements Analysis (FEA) methodology that prevents excessive bending strain in critical points of a PCB during an ICT. To validate this methodology, a set of experimental tests, matched with a set of FEA, were carried out. Thus, companies, before the development of an ICT machine (fixture), will be able to use this FEA methodology to predict whether the maximum strain of a PCB under study, when subjected to its ICT, will damage it, thus reducing unnecessary production costs. A guideline was thus designed to enable the creation of the most representative Finite Elements Model (FEM) for any PCB, based on its amount and direction of copper traces.
Design Framework for Motion Generation of Planar Four-Bar Linkage Considering Clearance Joints and Dynamics Performance
Authors: Liu Xueao , Ding Jianzhong , Wang Chunjie
Published: February 2022

In this paper, we present a novel design framework to connect linkage synthesis with dynamics performance of the linkage. The aim of the design framework is to improve the dynamics performance of the mechanism through linkage design, instead of improving manufacturing accuracy or changing driving strategy. Specifically, the design framework is to complete motion generation of four-bar linkage, considering clearance joints and dynamics performance. The constraint model of motion generation and the dynamics model of four-bar linkage are established, respectively. The coordinates of four joints of four-bar linkage are divided into two parts, one of parts is the parameters to improve the dynamics performance of the linkage and is selected as the optimization variables. The other parts of joint coordinates is to satisfy the kinematics requirements and is obtained by solving constraint equations of motion generation. Through optimization calculation, we can obtain the optimal configuration of the four-bar linkage that achieves specified task positions with high motion accuracy and low wear extent of clearance joint. Finally, a numerical example is proposed to demonstrate the novel design framework.
Rocio Virus Encephalitis: In Silico Evidence for Drug Repurposing
Authors: Sagini João Pedro , Arantes Pablo Ricardo , Pedebos Conrado , Ligabue-Braun Rodrigo
Published: February 2022

Arboviral diseases have a high incidence in Brazil and constitute a serious public health problem. Rocio virus (ROCV) is an arbovirus belonging to the family Flaviviridae. It was responsible for the emergence of an outbreak of encephalitis on the São Paulo state coast in the late 1970s. Although no recent case of this virus has been reported, data suggest the circulation of ROCV throughout the Brazilian territory. Given these indications and the strong presence of fundamental factors for the resurgence of emerging diseases in Brazil, we conducted this study using virtual screenings to identify targets and therapeutic molecules that could be redirected to fight infections related to ROCV. Herein, we demonstrated that the National List of Essential Medicines of the Brazilian Unified Health System (SUS) has several molecules that could be redirected to combat this flavivirus, namely simeprevir, daclatasvir, iloprost, and itraconazole. Among them, itraconazole was found to be an interesting candidate since it interacts with both structural and nonstructural proteins of this virus and it is a strong binder to the NS1 protein, as confirmed by molecular simulations.
TAID-LCA: Segmentation Algorithm Based on Ternary Trees
Authors: Castro-López Claudio , Vicente-Galindo Purificación , Galindo-Villardón Purificación , Borrego-Hernández Oscar
Published: February 2022

In this work, a statistical method for the segmentation of samples and/or populations is presented, which is based on a ternary tree structure. This approach overcomes known limitations of other segmentation methods such as CHAID, concerning the multivariate response and the non-symmetric relationship between explanatory and response variables. The multivariate response segmentation problem is handled through latent class models, while the factorial decomposition of the explanatory capability of variables is based on the Non-Symmetrical Correspondence Analysis. Stop criteria based on the CATANOVA index and impurity measures are proposed. A Simulated Annealing based post-pruning strategy is considered to avoid over-fitting relative to the training set and guarantee a better generalization capability for the method.
Single-Block Recursive Poisson–Dirichlet Fragmentations of Normalized Generalized Gamma Processes
Authors: James Lancelot
Published: February 2022

Dong, Goldschmidt and Martin (2006) (DGM) showed that, for 0<α<1, and θ>−α, the repeated application of independent single-block fragmentation operators based on mass partitions following a two-parameter Poisson–Dirichlet distribution with parameters (α,1−α) to a mass partition having a Poisson–Dirichlet distribution with parameters (α,θ) leads to a remarkable nested family of Poisson—Dirichlet distributed mass partitions with parameters (α,θ+r) for r=0,1,2,⋯. Furthermore, these generate a Markovian sequence of α-diversities following Mittag-Leffler distributions, whose ratios lead to independent Beta-distributed variables. These Markov chains are referred to as Mittag-Leffler Markov chains and arise in the broader literature involving Pólya urn and random tree/graph growth models. Here we obtain explicit descriptions of properties of these processes when conditioned on a mixed Poisson process when it equates to an integer n, which has interpretations in a species sampling context. This is equivalent to obtaining properties of the fragmentation operations of (DGM) when applied to mass partitions formed by the normalized jumps of a generalized gamma subordinator and its generalizations. We focus primarily on the case where n=0,1.
COVID-19 Detection Systems Using Deep-Learning Algorithms Based on Speech and Image Data
Authors: Nassif Ali Bou , Shahin Ismail , Bader Mohamed , Hassan Abdelfatah , Werghi Naoufel
Published: February 2022

The global epidemic caused by COVID-19 has had a severe impact on the health of human beings. The virus has wreaked havoc throughout the world since its declaration as a worldwide pandemic and has affected an expanding number of nations in numerous countries around the world. Recently, a substantial amount of work has been done by doctors, scientists, and many others working on the frontlines to battle the effects of the spreading virus. The integration of artificial intelligence, specifically deep- and machine-learning applications, in the health sector has contributed substantially to the fight against COVID-19 by providing a modern innovative approach for detecting, diagnosing, treating, and preventing the virus. In this proposed work, we focus mainly on the role of the speech signal and/or image processing in detecting the presence of COVID-19. Three types of experiments have been conducted, utilizing speech-based, image-based, and speech and image-based models. Long short-term memory (LSTM) has been utilized for the speech classification of the patient’s cough, voice, and breathing, obtaining an accuracy that exceeds 98%. Moreover, CNN models VGG16, VGG19, Densnet201, ResNet50, Inceptionv3, InceptionResNetV2, and Xception have been benchmarked for the classification of chest X-ray images. The VGG16 model outperforms all other CNN models, achieving an accuracy of 85.25% without fine-tuning and 89.64% after performing fine-tuning techniques. Furthermore, the speech–image-based model has been evaluated using the same seven models, attaining an accuracy of 82.22% by the InceptionResNetV2 model. Accordingly, it is inessential for the combined speech–image-based model to be employed for diagnosis purposes since the speech-based and image-based models have each shown higher terms of accuracy than the combined model.
Time-Varying Causalities in Prices and Volatilities between the Cross-Listed Stocks in Chinese Mainland and Hong Kong Stock Markets
Authors: Lu Xunfa , Ye Zhitao , Lai Kin Keung , Cui Hairong , Lin Xiao
Published: February 2022

Due to the heterogeneity of investor structure between the Chinese mainland stock market (A-share market) and the Hong Kong stock market (H-share market) as well as the limitations on arbitrage activities, most cross-listed stocks in the two markets (AH stocks) have the characteristics of “one asset, two prices”, in which AH stocks with the same vote rights and dividend streams are traded at different prices in different markets. Based on the VAR (LA-VAR as well) model and a four-variable system including AH stock indices (AHXA, AHXH), the China Securities Index 300 (CSI 300), and the Hang Seng Index (HSI), this paper applies a new time-varying causality test to examine the causalities in prices and volatilities for two pairings (AXHA-AHXH pairing and CSI 300-HSI pairing) during the sample period spanning from 4 January 2010 to 21 May 2021. The empirical results exhibit statistically significant time-varying causalities of the two pairings. Specifically, at the price level, AHXH has a significant negative causal effect on AHXA from October 2017 to February 2020 except for several months in 2018, while AHXA merely has a negative impact on AHXA during a short period from March 2017 to May 2017. Of note, the direction of causalities in volatilities between AHXA and AHXH reverses. A positive causality is found from AHXA to AHXH at the 5% significance level during the period of April 2014 through May 2021, while no causality is detected in the opposite direction during the whole sample period. Meanwhile, the volatilities of CSI 300 significantly Granger cause those of HSI over the whole sample period, but not vice versa. Implications of our results are discussed.
Enhanced Convolutional Neural Network Model for Cassava Leaf Disease Identification and Classification
Authors: Lilhore Umesh Kumar , Imoize Agbotiname Lucky , Lee Cheng-Chi , Simaiya Sarita , Pani Subhendu Kumar , Goyal Nitin , Kumar Arun , Li Chun-Ta
Published: February 2022

Cassava is a crucial food and nutrition security crop cultivated by small-scale farmers and it can survive in a brutal environment. It is a significant source of carbohydrates in African countries. Sometimes, Cassava crops can be infected by leaf diseases, affecting the overall production and reducing farmers’ income. The existing Cassava disease research encounters several challenges, such as poor detection rate, higher processing time, and poor accuracy. This research provides a comprehensive learning strategy for real-time Cassava leaf disease identification based on enhanced CNN models (ECNN). The existing Standard CNN model utilizes extensive data processing features, increasing the computational overhead. A depth-wise separable convolution layer is utilized to resolve CNN issues in the proposed ECNN model. This feature minimizes the feature count and computational overhead. The proposed ECNN model utilizes a distinct block processing feature to process the imbalanced images. To resolve the color segregation issue, the proposed ECNN model uses a Gamma correction feature. To decrease the variable selection process and increase the computational efficiency, the proposed ECNN model uses global average election polling with batch normalization. An experimental analysis is performed over an online Cassava image dataset containing 6256 images of Cassava leaves with five disease classes. The dataset classes are as follows: class 0: “Cassava Bacterial Blight (CBB)”; class 1: “Cassava Brown Streak Disease (CBSD)”; class 2: “Cassava Green Mottle (CGM)”; class 3: “Cassava Mosaic Disease (CMD)”; and class 4: “Healthy”. Various performance measuring parameters, i.e., precision, recall, measure, and accuracy, are calculated for existing Standard CNN and the proposed ECNN model. The proposed ECNN classifier significantly outperforms and achieves 99.3% accuracy for the balanced dataset. The test findings prove that applying a balanced database of images improves classification performance.
Free Vibration of FG-CNTRCs Nano-Plates/Shells with Temperature-Dependent Properties
Authors: Melaibari Ammar , Daikh Ahmed Amine , Basha Muhammad , Abdalla Ahmed W. , Othman Ramzi , Almitani Khalid H. , Hamed Mostafa A. , Abdelrahman Alaa , Eltaher Mohamed A.
Published: February 2022

This article presents a mathematical continuum model to analyze the free vibration response of cross-ply carbon-nanotube-reinforced composite laminated nanoplates and nanoshells, including microstructure and length scale effects. Different shell geometries, such as plate (infinite radii), spherical, cylindrical, hyperbolic-paraboloid and elliptical-paraboloid are considered in the analysis. By employing Hamilton’s variational principle, the equations of motion are derived based on hyperbolic sine function shear deformation theory. Then, the derived equations are solved analytically using the Galerkin approach. Two types of material distribution are proposed. Higher-order nonlocal strain gradient theory is employed to capture influences of shear deformation, length scale parameter (nonlocal) and material/microstructurescale parameter (gradient). Temperature-dependent material properties are considered. The validation of the proposed mathematical model is presented. Detailed parametric analyses are carried out to highlight the effects of the carbon nanotubes (CNT) distribution pattern, the thickness stretching, the geometry of the plate/shell, the boundary conditions, the total number of layers, the length scale and the material scale parameters, on the vibrational frequencies of CNTRC laminated nanoplates and nanoshells.
Cytotoxic Compounds from Alcyoniidae: An Overview of the Last 30 Years
Authors: Cerri Federico , Saliu Francesco , Maggioni Davide , Montano Simone , Seveso Davide , Lavorano Silvia , Zoia Luca , Gosetti Fabio , Lasagni Marina , Orlandi Marco , Taglialatela-Scafati Orazio , Galli Paolo
Published: February 2022

The octocoral family Alcyoniidae represents a rich source of bioactive substances with intriguing and unique structural features. This review aims to provide an updated overview of the compounds isolated from Alcyoniidae and displaying potential cytotoxic activity. In order to allow a better comparison among the bioactive compounds, we focused on molecules evaluated in vitro by using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, by far the most widely used method to analyze cell proliferation and viability. Specifically, we surveyed the last thirty years of research, finding 153 papers reporting on 344 compounds with proven cytotoxicity. The data were organized in tables to provide a ranking of the most active compounds, to be exploited for the selection of the most promising candidates for further screening and pre-clinical evaluation as anti-cancer agents. Specifically, we found that (22S,24S)-24-methyl-22,25-epoxyfurost-5-ene-3β,20β-diol (16), 3β,11-dihydroxy-24-methylene-9,11-secocholestan-5-en-9-one (23), (24S)-ergostane-3β,5α,6β,25 tetraol (146), sinulerectadione (227), sinulerectol C (229), and cladieunicellin I (277) exhibited stronger cytotoxicity than their respective positive control and that their mechanism of action has not yet been further investigated.
Favourable Changes in C-Peptide, C-Reactive Protein and Lipid Profile, and Improved Quality of Life in Patients with Abnormal Body Mass Index after the Use of Manual Lymphatic Drainage: A Case Series with Three-Month Follow-Up
Authors: Antoniak Klaudia , Zorena Katarzyna , Hansdorfer-Korzon Rita , Wojtowicz Dagmara , Koziński Marek
Published: February 2022

Aim: to try to assess the effect of manual lymphatic drainage on the biochemical parameters and quality of life of patients with abnormal body mass index. The study included three women, average age 46 years (patient 1 with normal body weight as a control; patient 2: overweight; patient 3 with class 2 obesity). After qualification, physiotherapeutic interview and examination was carried out; the concentrations of glycosylated haemoglobin (HbA1c), C-peptide, high-sensitivity C-reactive protein (hsCRP), lipid profile, and quality of life were also examined. Additionally, in patients with abnormal body mass index, biochemical parameters were monitored for 3 months. Each patient underwent 10 manual lymphatic drainage (MLD) therapy sessions, three times a week for 30 min. In the overweight patient (patient 2), a decrease in the concentration of C-peptide, hsCRP and triglycerides was observed after the series of MLD therapy. An improvement in the quality of life, intestinal motility, and a reduction in the frequency of flatulence were also noted. Moreover, after the therapy, patient 2 reported better sleep and increased vitality. In contrast, in patient 3 (with grade 2 obesity), a decrease in triglyceride levels, but not other biomarkers, was detected after the series of MDL therapy. Additionally, in patient 3, an improvement in the quality of life, an improvement in intestinal peristalsis, and reduction of menstrual pain were observed after MLD therapy. For comparison, in a patient with a normal body weight as a control (patient 1), there were no changes in biochemical parameters or improvement in the quality of life after MLD therapy. Our preliminary research indicates improvement of the concentration C-peptide, lipid profile, a reduction in the inflammation, and improved quality of life in patients with abnormal body mass index after MLD therapy. However, more studies are needed to elucidate the effectiveness of MLD therapy in patients with varying degrees of abnormal body mass index, i.e., from overweight to obesity.
The Modelling of Surface Roughness after the Ball Burnishing Process with a High-Stiffness Tool by Using Regression Analysis, Artificial Neural Networks, and Support Vector Regression
Authors: Kanovic Zeljko , Vukelic Djordje , Simunovic Katica , Prica Miljana , Saric Tomislav , Tadic Branko , Simunovic Goran
Published: February 2022

Surface roughness is an important indicator of the quality of the machined surface. One of the methods that can be applied to improve surface roughness is ball burnishing. Ball burnishing is a finishing process in which a ball is rolled over the workpiece surface. Defining adequate input variables of the ball burnishing process to ensure obtaining the required surface roughness is a typical problem in scientific research. This paper presents the results of experiments to investigate ball burnishing of AISI 4130 alloy steel with a high-stiffness tool and a ceramic ball. The experiments were conducted following a randomized full factorial design for different levels of input variables. The input variables included the initial arithmetic mean roughness (the initial surface roughness), the depth of ball penetration, the burnishing feed, and the burnishing ball diameter, while the output variable was the arithmetic mean roughness after ball burnishing (the final surface roughness). The surface roughness modeling was performed based on the experimental results, using regression analysis (RA), artificial neural network (ANN), and support vector regression (SVR). The regression model displayed large prediction errors at low surface roughness values (below 1 μm), but it proved to be reliable for higher roughness values. The ANN and SVR models have excellently predicted roughness across a range of input variables. Mean percentage error (MPE) during the experimental training research was 29.727%, 0.995%, and 1.592%, and MPE in the confirmation experiments was 34.534%, 1.559%, and 2.164%, for RA, ANN, and SVR, respectively. Based on the obtained MPEs, it can be concluded that the application of ANN and SVR was adequate for modeling the ball burnishing process and prediction of the roughness of the treated surface in terms of the possibility of practical application in real industrial conditions.
Effects of Blade Numbers on Wind-Induced Fatigue Lives of Straight-Bladed Vertical-Axis Wind-Turbine Tower Bases
Authors: Zheng Hua-Dong , Zhang Bo , Wang Sheng-Bin , Zhou Guan-Zheng
Published: February 2022

Vertical-axis wind turbines (VAWTs) are being reconsidered as a complementary technology to the more commercially used horizontal-axis wind turbines (HAWTs) because of their economical installation and maintenance. The selection of the blade numbers is one of the crucial concerns for VAWTs. This study focuses on the effects of the blade numbers on the fatigue lives of VAWT tower bases subjected to wind loading. Three straight-bladed VAWTs, with the same solidity ratios but different blade numbers, varying from two to four, were designed. The aerodynamic loading incurred by the VAWTs was computed using the corrected double-disk multistreamtube (DMS) model. The dynamic equations of the turbine systems were solved using the explicit central difference method. Then, a fatigue assessment model, including the crack-initiation and crack-propagation stages, was developed for the turbine tower bases. The results indicate that the three- and four-bladed VAWTs always presented better performances than the two-bladed VAWT in terms of the fatigue life. Moreover, increasing the number of blades from two to three improves the fatigue life of the tower base more than increasing it from three to four at lower wind speeds, while the latter is the more effective way to improve the tower-base fatigue life at higher wind speeds.
Understanding Uncertainty in Microstructure Evolution and Constitutive Properties in Additive Process Modeling
Authors: Rolchigo Matthew , Carson Robert , Belak James
Published: February 2022

Coupled process–microstructure–property modeling, and understanding the sources of uncertainty and their propagation toward error in part property prediction, are key steps toward full utilization of additive manufacturing (AM) for predictable quality part development. The OpenFOAM model for process conditions, the ExaCA model for as-solidified grain structure, and the ExaConstit model for constitutive mechanical properties are used as part of the ExaAM modeling framework to examine a few of the various sources of uncertainty in the modeling workflow. In addition to “random” uncertainty (due to random number generation in the orientations and locations of grains present), the heterogeneous nucleation density N0 and the mean substrate grain spacing S0 are varied to examine their impact of grain area development as a function of build height in the simulated microstructure. While mean grain area after 1 mm of build is found to be sensitive to N0 and S0, particularly at small N0 and large S0 (despite some convergence toward similar values), the resulting grain shapes and overall textures develop in a reasonably similar manner. As a result of these similar textures, ExaConstit simulation using ExaCA representative volume elements (RVEs) from various permutations of N0, S0, and location within the build resulted in similar yield stress, stress–strain curve shape, and stress triaxiality distributions. It is concluded that for this particular material and scan pattern, 15 layers is sufficient for ExaCA texture and ExaConstit predicted properties to become relatively independent of additional layer simulation, provided that reasonable estimates for N0 and S0 are used. However, additional layers of ExaCA will need to be run to obtain mean grain areas independent of build height and baseplate structure.
Whole-Genome Sequencing Enables Molecular Characterization of Non-Clonal Group 258 High-Risk Clones (ST13, ST17, ST147 and ST307) among Carbapenem-Resistant Klebsiella pneumoniae from a Tertiary University Hospital Centre in Portugal
Authors: Mendes Gabriel , Ramalho João F. , Bruschy-Fonseca Ana , Lito Luís , Duarte Aida , Melo-Cristino José , Caneiras Cátia
Published: February 2022

The carbapenem-resistant Enterobacterales (CRE) strains have been identified by the World Health Organization as critical priority pathogens in research and development of diagnostics, treatments, and vaccines. However, recent molecular information about carbapenem-resistant K. pneumoniae (CRK) epidemiology in Portugal is still scarce. Thus, this study aimed to provide the molecular epidemiology, resistome, and virulome of CRK clinical strains recovered from a tertiary care hospital centre (2019–2021) using polymerase chain reaction (PCR) and the advanced molecular technique whole-genome sequencing (WGS). PCR amplification of carbapenemase genes was performed in 437 carbapenem-resistant K. pneumoniae strains. The most frequent carbapenemases were: KPC-3 (42%), followed by OXA-181 (20%), GES-5 (0.2%), and NDM-1 (0.2%). Additionally, 10 strains (2%) coproduced KPC-3 and OXA-181, and 1 strain coproduced KPC-3 and OXA-48 (0.2%). The genomic population structure of 68 strains characterized by WGS demonstrated the ongoing dissemination of four main high-risk clones: ST13, ST17, ST147, and ST307, while no clones belonging to the European predominant clonal groups (CG15 and CG258) were found. Moreover, we describe one K. pneumoniae ST39-KL62 that coproduced the NDM-1 carbapenemase and the extended-spectrum beta-lactamase CTX-M-15, and one K. pneumoniae ST29-KL54 GES-5 and BEL-1 coproducer. Furthermore, a high prevalence of iron siderophores were present in all CRK strains, with several strains presenting both colibactin and the hypermucoviscosity phenotype. Thus, the data presented here highlight an uncommon molecular epidemiology pattern in Portugal when compared with most European countries, further supporting the emergence and dissemination of nonclonal group 258 hypervirulent multidrug high-risk clones and the need to promote in-depth hospital molecular surveillance studies.
Real-Time PCR-Based Methods for Detection of Hepatitis E Virus in Pork Products: A Critical Review
Authors: Cook Nigel , D’Agostino Martin , Wood Ann , Scobie Linda
Published: February 2022

Standard methods for detection of hepatitis A virus and norovirus in at-risk foodstuffs are available, but currently there is no standard method for detection of hepatitis E virus (HEV) in pork products or other foods that can be contaminated with the virus. Detection assays for HEV are mainly based on nucleic acid amplification, particularly the reverse transcription polymerase chain reaction (RTPCR) in real-time format. RTPCR-based methods can be sensitive and specific, but they require a suite of controls to verify that they have performed correctly. There have been several RTPCR methods developed to detect HEV in pork products, varying in details of sample preparation and RTPCR target sequences. This review critically discusses published HEV detection methods, with emphasis on those that have been successfully used in subsequent studies and surveys. RTPCR assays have been used both qualitatively and quantitatively, although in the latter case the data acquired are only reliable if appropriate assay calibration has been performed. One particular RTPCR assay appears to be ideal for incorporation in a standard method, as it has been demonstrated to be highly specific and sensitive, and an appropriate control and calibration standard is available. The review focuses on the detection of HEV in pork products and similar foodstuffs (e.g., boar). The information may be useful to inform standardisation activities.
Two-Drug Regimens for HIV—Current Evidence, Research Gaps and Future Challenges
Authors: Pérez-González Alexandre , Suárez-García Inés , Ocampo Antonio , Poveda Eva
Published: February 2022

During the last 30 years, antiretroviral treatment (ART) for human immunodeficiency virus (HIV) infection has been continuously evolving. Since 1996, three-drug regimens (3DR) have been standard-of-care for HIV treatment and are based on a protease inhibitor (PI) or a non-nucleoside reverse transcriptase inhibitor (NNRTI) plus two nucleoside reverse transcriptase inhibitors (NRTIs). The effectiveness of first-generation 3DRs allowed a dramatic increase in the life expectancy of HIV-infected patients, although it was associated with several side effects and ART-related toxicities. The development of novel two-drug regimens (2DRs) started in the mid-2000s in order to minimize side effects, reduce drug–drug interactions and improve treatment compliance. Several clinical trials compared 2DRs and 3DRs in treatment-naïve and treatment-experienced patients and showed the non-inferiority of 2DRs in terms of efficacy, which led to 2DRs being used as first-line treatment in several clinical scenarios, according to HIV clinical guidelines. In this review, we summarize the current evidence, research gaps and future prospects of 2DRs.