bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and Experimental of Seeding Process of Pneumatic Split Seeder for Cotton
Authors: Li Kezhi , Li Shufeng , Ni Xiangdong , Lu Bo , Zhao Binqiang
Published: May 2023

In order to study the working mechanism and sowing effect of seed delivery pipes and their associated cavity seeders, the factors affecting the sowing test were first derived through pressure loss theory and force analysis of cotton seed particles in the gas-solid coupling field. Secondly, Ansys fluent was used to simulate the flow field of seed delivery pipe joints to study the effect of seed delivery pipe joints on the overall pressure loss and uniformity of air pressure distribution and to determine the optimal structure of seed delivery pipe joints. Then, the EDEM was simulated for the overall seed delivery pipe and its associated cavity seeders in the absence of positive pressure to analyze the transport pattern of each cotton seed. Finally, CFD-DEM gas-solid coupling simulation experiments were conducted on the center of two rows of seed delivery pipes and their connected cavity seeders to analyze the trajectory of cotton seeds under different rotational speeds of cavity seeders and different positive seed delivery pressures and to deeply analyze the causes of Multiple seeding and Miss-seeding. At the same time, the seeding performance was evaluated by coupling simulation values with single seeding rate and multiple seeding rate as seeding performance evaluation indexes and compared with bench test. The results show that in the coupling simulation, when the speed of the cavity seeders is 20~40 rev/min and the seed delivery tube is passed into 50~150 Pa positive pressure airflow, the single seeding rate is not less than 83.06%, and the missed seeding rate is not more than 9.23%. In the bench test, the single seeding rate was not less than 80.64%, and the missed seeding rate was not more than 9.86% under the same cavity seeders speed and positive pressure, and the results of the bench test and the simulation test were close and consistent, which verified the feasibility of the simulation.
Fermentation Quality and Chemical Composition of Industrial Hemp (Cannabis sativa L.) Silage Inoculated with Bacterial Starter Cultures—A Pilot Study
Authors: Wróbel Barbara , Hryniewicz Marek , Kulkova Iryna , Mazur Kamila , Jakubowska Zuzanna , Borek Kinga , Dobrzyński Jakub , Konieczna Anita , Miecznikowski Antoni , Piasecka-Jóźwiak Katarzyna , Fabiszewska Agata
Published: May 2023

Industrial hemp (Cannabis sativa L.) is a plant species cultivated as a raw material for fiber extraction. Alternatively, hemp biomass can be used for feeding or energy purposes. This study was conducted to investigate the effect of inoculation with a lactic acid bacteria starter culture on the fermentation and chemical compositions of hemp silages. Hemp shoots (HS) and hemp flowers (HF) were ensiled in mini laboratory silos without or with the inoculation of the commercial starter culture Lactosil Biogaz (Lentilactobacillus buchnerii KKP 907 p; L. buchneri A KKP 2047 p; Pediococcus acidilactici KKP 2065 p). After 7 and 42 days of ensiling, the fermentation quality and chemical compositions of the silages were assessed. The use of Lactosil Biogas for hemp resulted in a decrease in pH, increase in lactic acid (LA), and reduction in fungal abundance in the HS silage. In the case of the HF silage, the bacterial inoculation was less effective; however, an increase in LA and a decrease in butyric acid (BA) were observed. As a result of the ensilage process, decreases in crude fiber and hemicellulose were observed in the HS and HF silages. Thus, hemp ensiling with biological additives is an effective pre-treatment of hemp plants for subsequent biofuel production that can preserve the biomass and provide the year-round availability of feedstock.
Petal Morphology Is Correlated with Floral Longevity in Paeonia suffruticosa
Authors: Guo Yingzi , Qiu Yongjie , Hu Huan , Wang Yanli , Mi Zhaorong , Zhang Shulin , He Songlin , Jia Wenqing
Published: May 2023

Floral longevity (FL) is an important floral functional trait which is critical for flowering plants. FL shows great diversity among angiosperms; however, there is limited information on the mechanisms that influence differences in floral longevity, especially the relationship between petal anatomical traits and floral longevity. We aimed to examine (1) the relationships between petal anatomical traits and FL in tree peony cultivars and (2) the petal anatomical characteristics of longer FL cultivars. Eleven traits of six tree peony cultivars with different FL were investigated, including six water conservation traits (petal thickness, cuticle thickness, number of cell layers, mesophyll thickness, adaxial epidermis thickness and abaxial epidermis thickness), three water supply traits (vein density, number of xlylem vessels and xylem vessel diameter), petal fresh mass and petal dry mass across cultivars. There are significant differences in traits related to water conservation and water supply ability of tree peonies with different FL. Tree peony cultivars with long FL were characterized by the thicker Mesophyll, cuticles, adaxial and abaxial epidermis of the petals. There was a positive correlation between FL and vessel number and vessel diameter. These results suggest that the ability to retain water in flowers is associated with floral longevity. Petal traits related to water conservation and supply, including vein densities, mesophyll thickness, and epidermis thickness, are beneficial for prolonging the flower longevity in tree peonies.
MbNAC22, a Malus baccata NAC Transcription Factor, Increased Drought and Salt Tolerance in Arabidopsis
Authors: Jiao Kuibao , Han Jiaxin , Guo Baitao , Wu Yuqi , Zhang Lei , Li Yuze , Song Penghui , Han Deguo , Duan Yadong , Li Xingguo
Published: May 2023

As an excellent grafting material, Malus baccata (L.) Borkh is native to Liaoning, Jilin, Heilongjiang and other regions in China, with a strong adverse environmental adaptability. As a typical transcription factor, the NAC gene acts as a regulator in many molecular pathways responding to abiotic stress. However, research of NAC in the Malus baccata has just begun. In the present research, a new NAC transcription factor, MbNAC22, was obtained from the seedlings of Malus baccata, and its function in drought and salt treatments was studied by heterologous expression. The open reading frame of the MbNAC22 gene is 768, encoding 255 amino acids (aa). Through confocal microscopy, MbNAC22 was found to be located in the nucleus. The heterologous expression of MbNAC22 in Arabidopsis showed that it enhanced the viability of Arabidopsis under drought and salt treatments. Under stresses, the chlorophyll content of the plants decreased, but the decline of the overexpressed-MbNAC22 Arabidopsis was relatively low. Through phenotypic observation and determination of stress-related physiological indicators, it was found that compared with WT Arabidopsis, overexpressed-MbNAC22 Arabidopsis had a higher tolerance to stresses. Under stresses, the overexpression of MbNAC22 positively regulated ion-transport-related genes (AtNHX1 and AtSOS1), the key genes of the ABA pathway (AtNCED3 and AtDREB2A), the proline synthesis gene (AtP5CS2) and the drought-induced gene (AtERD11), while the expression of the leaf senescence-associated gene (AtSAG21) and programmed cell death related gene (AtAEP1) was inhibited. Therefore, we speculate that MbNAC22 responds positively to drought and salt stresses by regulating the expression of stress-related genes.
Quinolone Resistance in Gallibacterium anatis Determined by Mutations in Quinolone Resistance-Determining Region
Authors: Rømer Villumsen Kasper , Allahghadry Toloe , Karwańska Magdalena , Frey Joachim , Bojesen Anders Miki
Published: May 2023

Control of the important pathogen, Gallibacterium anatis, which causes salpingitis and peritonitis in poultry, relies on treatment using antimicrobial compounds. Among these, quinolones and fluoroquinolones have been used extensively, leading to a rise in the prevalence of resistant strains. The molecular mechanisms leading to quinolone resistance, however, have not previously been described for G. anatis, which is the aim of this study. The present study combines phenotypic antimicrobial resistance data with genomic sequence data from a collection of G. anatis strains isolated from avian hosts between 1979 and 2020. Minimum inhibitory concentrations were determined for nalidixic acid, as well as for enrofloxacin for each included strain. In silico analyses included genome-wide queries for genes known to convey resistance towards quinolones, identification of variable positions in the primary structure of quinolone protein targets and structural prediction models. No resistance genes known to confer resistance to quinolones were identified. Yet, a total of nine positions in the quinolone target protein subunits (GyrA, GyrB, ParC and ParE) displayed substantial variation and were further analyzed. By combining variation patterns with observed resistance patterns, positions 83 and 87 in GyrA, as well as position 88 in ParC, appeared to be linked to increased resistance towards both quinolones included. As no notable differences in tertiary structure were observed between subunits of resistant and sensitive strains, the mechanism behind the observed resistance is likely due to subtle shifts in amino acid side chain properties.
Daptomycin Pharmacokinetics in Blood and Wound Fluid in Critical Ill Patients with Left Ventricle Assist Devices
Authors: Calov Stefanie , Munzel Frederik , Roehr Anka C. , Frey Otto , Higuita Lina Maria Serna , Wied Petra , Rosenberger Peter , Haeberle Helene A. , Ngamsri Kristian-Christos
Published: May 2023

Daptomycin is a cyclic lipopeptide antibiotic with bactericidal effects against multidrug-resistant Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecalis (VRE). For critically ill patients, especially in the presence of implants, daptomycin is an important therapeutic option. Left ventricle assist devices (LVADs) can be utilized for intensive care patients with end-stage heart failure as a bridge to transplant. We conducted a single-center prospective trial with critically ill adults with LVAD who received prophylactic anti-infective therapy with daptomycin. Our study aimed to evaluate the pharmacokinetics of daptomycin in the blood serum and wound fluids after LVAD implantation. Daptomycin concentration were assessed over three days using high-performance liquid chromatography (HPLC). We detected a high correlation between blood serum and wound fluid daptomycin concentration at 12 h (IC95%: 0.64 to 0.95; r = 0.86; p < 0.001) and 24 h (IC95%: −0.38 to 0.92; r = 0.76; p < 0.001) after antibiotic administration. Our pilot clinical study provides new insights into the pharmacokinetics of daptomycin from the blood into wound fluids of critically ill patients with LVADs.
Antimicrobial Use by Peri-Urban Poultry Smallholders of Kajiado and Machakos Counties in Kenya
Authors: Mutua Florence , Kiarie Gideon , Mbatha Miriam , Onono Joshua , Boqvist Sofia , Kilonzi Emily , Mugisha Lawrence , Moodley Arshnee , Sternberg-Lewerin Susanna
Published: May 2023

Antimicrobial use (AMU) is a major driver of antimicrobial resistance (AMR). An understanding of current practices can lead to better targeting of AMU-reducing interventions. An analysis of the distribution and current usage of veterinary drugs in peri-urban smallholder poultry systems in Kenya was undertaken. A survey among poultry farmers and key informant interviews with agrovet operators and other players in the value chain was conducted in Machakos and Kajiado counties. Interview data were analyzed using descriptive and thematic approaches. A total of 100 farmers were interviewed. The majority (58%) were > 50 years old, and all kept chickens, while 66% kept other livestock. Antibiotics constituted 43% of the drugs reportedly used on the farms (n = 706). These were mostly administered by the farmers themselves (86%) through water (98%). Leftover drugs were stored for later use (89%) or disposed of (11%). Incineration was the main method for the disposal of leftover drugs and empty containers. As described by the key informants (n = 17), the drug distribution chain relied on agrovet shops that were supplied by local distributors and pharmaceutical companies, which, in turn, supplied drugs to the farmers. Farmers reportedly purchased drugs without prescriptions and rarely observed the withdrawal periods. Drug quality was a concern, especially for products requiring reconstitution.
Molecular Detection of Metronidazole and Tetracycline Resistance Genes in Helicobacter pylori-Like Positive Gastric Samples from Pigs
Authors: Cortez Nunes Francisco , Taillieu Emily , Letra Mateus Teresa , Teixeira Sílvia , Haesebrouck Freddy , Amorim Irina
Published: May 2023

Antimicrobial resistance is a major public health concern. The aim of this study was to assess the presence of antibiotic resistance genes, previously reported in Helicobacter pylori, in gastric samples of 36 pigs, in which DNA of H. pylori-like organisms had been detected. Based on PCR and sequencing analysis, two samples were positive for the 16S rRNA mutation gene, conferring tetracycline resistance, and one sample was positive for the frxA gene with a single nucleotide polymorphism, conferring metronidazole resistance. All three amplicons showed the highest homology with H. pylori-associated antibiotic resistance gene sequences. These findings indicate that acquired antimicrobial resistance may occur in H. pylori-like organisms associated with pigs.
Exploring the Potential of Supercritical Fluid Extraction of Matricaria chamomilla White Ray Florets as a Source of Bioactive (Cosmetic) Ingredients
Authors: Pastare Laura , Berga Marta , Kienkas Liene , Boroduskis Martins , Ramata-Stunda Anna , Reihmane Dace , Senkovs Maris , Skudrins Gundars , Nakurte Ilva
Published: May 2023

Aromatic and medicinal plants are a great source of useful bioactive compounds for use in cosmetics, drugs, and dietary supplements. This study investigated the potential of using supercritical fluid extracts obtained from Matricaria chamomilla white ray florets, a kind of industrial herbal byproduct, as a source of bioactive cosmetic ingredients. Response surface methodology to optimize the supercritical fluid extraction process by analyzing the impact of pressure and temperature on yield and the main bioactive compound groups were used. High-throughput 96-well plate spectrophotometric methods were used to analyze the extracts for total phenols, flavonoids, tannins, and sugars, as well as their antioxidant capacity. Gas chromatography and liquid chromatography–mass spectrometry was used to determine the phytochemical composition of the extracts. The extracts were also analyzed for antimicrobial activity, cytotoxicity, phototoxicity, and melanin content. Statistical analysis was performed to establish correlations between the extracts and develop models to predict the targeted phytochemical recovery and chemical and biological activities. The results show that the extracts contained a diverse range of phytochemical classes and had cytotoxic, proliferation-reducing, and antimicrobial activities, making them potentially useful in cosmetic formulations. This study provides valuable insights for further research on the uses and mechanisms of action of these extracts.
Effects of Antioxidants in Fermented Beverages in Tissue Transcriptomics: Effect of Beer Intake on Myocardial Tissue after Oxidative Injury
Authors: Gallinat Alex , Vilahur Gemma , Padro Teresa , Badimon Lina
Published: May 2023

Fermented beverages, such as wine and beer, are rich in polyphenols that have been shown to have protective effects against oxidative stress. Oxidative stress plays a central role in the pathogenesis and progression of cardiovascular disease. However, the potential benefits of fermented beverages on cardiovascular health need to be fully investigated at a molecular level. In this study, we aimed at analyzing the effects of beer consumption in modulating the transcriptomic response of the heart to an oxidative stress challenge induced by myocardial ischemia (MI) in the presence of hypercholesterolemia in a pre-clinical swine model. Previous studies have shown that the same intervention induces organ protective benefits. We report a dose-dependent up-regulation of electron transport chain members and the down-regulation of spliceosome-associated genes linked to beer consumption. Additionally, low-dose beer consumption resulted in a down-regulation of genes associated with the immune response, that was not shown for moderate-dose beer consumption. These findings, observed in animals having demonstrated beneficial effects at the organ-level, indicate that the antioxidants in beer differentially affect the myocardial transcriptome in a dose-dependent manner.
Old and Novel Predictors for Cardiovascular Risk in Diabetic Foot Syndrome—A Narrative Review
Authors: Adam Cristina Andreea , Marcu Dragos Traian Marius , Mitu Ovidiu , Roca Mihai , Aursulesei Onofrei Viviana , Zabara Mihai Lucian , Tribuș Laura Carina , Cumpăt Carmen , Crișan Dabija Radu , Mitu Florin
Published: May 2023

Diabetic foot syndrome (DFS) is a complication associated with diabetes that has a strong negative impact, both medically and socio-economically. Recent epidemiological data show that one in six patients with diabetes will develop an ulcer in their lifetime. Vascular complications associated with diabetic foot have multiple prognostic implications in addition to limiting functional status and leading to decreased quality of life for these patients. We searched the electronic databases of PubMed, MEDLINE and EMBASE for studies that evaluated the role of DFS as a cardiovascular risk factor through the pathophysiological mechanisms involved, in particular the inflammatory ones and the associated metabolic changes. In the era of evidence-based medicine, the management of these cases in multidisciplinary teams of “cardio-diabetologists” prevents the occurrence of long-term disabling complications and has prognostic value for cardiovascular morbidity and mortality among diabetic patients. Identifying artificial-intelligence-based cardiovascular risk prediction models or conducting extensive clinical trials on gene therapy or potential therapeutic targets promoted by in vitro studies represent future research directions with a modulating role on the risk of morbidity and mortality in patients with DFS.
A Multi-Model Proposal for Classification and Detection of DDoS Attacks on SCADA Systems
Authors: Söğüt Esra , Erdem O. Ayhan
Published: May 2023

Industrial automation and control systems have gained increasing attention in the literature recently. Their integration with various systems has triggered considerable developments in critical infrastructure systems. With different network structures, these systems need to communicate with each other, work in an integrated manner, be controlled, and intervene effectively when necessary. Supervision Control and Data Acquisition (SCADA) systems are mostly utilized to achieve these aims. SCADA systems, which control and monitor the connected systems, have been the target of cyber attackers. These systems are subject to cyberattacks due to the openness to external networks, remote controllability, and SCADA-architecture-specific cyber vulnerabilities. Protecting SCADA systems on critical infrastructure systems against cyberattacks is an important issue that concerns governments in many aspects such as economics, politics, transport, communication, health, security, and reliability. In this study, we physically demonstrated a scaled-down version of a real water plant via a Testbed environment created including a SCADA system. In order to disrupt the functioning of the SCADA system in this environment, five attack scenarios were designed by performing various DDoS attacks, i.e., TCP, UDP, SYN, spoofing IP, and ICMP Flooding. Additionally, we evaluated a scenario with the baseline behavior of the SCADA system that contains no attack. During the implementation of the scenarios, the SCADA system network was monitored, and network data flow was collected and recorded. CNN models, LSTM models, hybrid deep learning models that amalgamate CNN and LSTM, and traditional machine learning models were applied to the obtained data. The test results of various DDoS attacks demonstrated that the hybrid model and the decision tree model are the most suitable for such environments, reaching the highest test accuracy of 95% and 99%, respectively. Moreover, we tested the hybrid model on a dataset that is used commonly in the literature which resulted in 98% accuracy. Thus, it is suggested that the security of the SCADA system can be effectively improved, and we demonstrated that the proposed models have a potential to work in harmony on real field systems.
Spatial Distribution of Cu, Zn, Pb, Cd, Co, Ni in the Soils of Ili River Delta and State Natural Reserve “Ili-Balkhash”
Authors: Madibekov Azamat , Ismukhanova Laura , Opp Christian , Saidaliyeva Zarina , Zhadi Askhat , Sultanbekova Botakoz , Kurmanova Meruert
Published: May 2023

River delta soils are the final spatial units of the matter flow within the whole river catchment. Due to their spatial position in the catchment and due to their fine grain size composition, river delta soils are important matter sinks in general, especially for heavy metals. The article presents the results of spectrometric analysis of heavy metals in the soils of the Ili River Delta and State Natural Reserve “Ili-Balkhash” in 2021. This area is included in the list of wetlands of international importance under the Convention on Wetlands. Heavy metals in the samples were determined using the flame atomic absorption spectrometric method using the AA-7000 atomic absorption spectrophotometer. The spatial distribution of the metals was visualized in the ArcGIS 10.5 environment. Copper concentrations were measured in the soils of the dry steppe, semi-desert and desert zones with average values up to 28.5 mg kg−1 and a maximum level of 75.1 mg kg−1. The concentrations of lead are 8.0–15.9 mg kg−1. The cadmium content exceeds the standards from 2.1 to 6.5 mg kg−1 on the whole territory at MPC 2.0 mg kg−1, reaching up to 3.3 MPC (Maximum Permissible Concentration). The cobalt concentration ranges from 6.7 to 20.6 mg kg−1, and nickel ranges from 11.3 to 22.2 mg kg−1. Soil contamination due to cobalt and nickel is observed in the northern and eastern parts of the study area. The received data about pollution of the soil cover by heavy metals makes it possible to assess the degree of anthropogenic load of the unique natural environment in the Ili River Delta and natural reserve.
A Comparative Study on Bioleaching Properties of Various Sulfide Minerals Using Acidiphilium cryptum
Authors: Cho Kang-Hee , Kim Hyun-Soo , Lee Chang-Gu , Park Seong-Jik , Choi Nag-Choul
Published: May 2023

Bioleaching has been regarded as a green alternative to chemical leaching in metal extraction processes. In this study, the bioleaching properties of indigenous acidophilic bacteria for various sulfide minerals were compared and evaluated in terms of pH reduction and metal leaching. The primary minerals in the samples were sphalerite (ZnS) (SP), galena (PbS) (GN1 and GN2), pyrite (FeS2) (PY), and chalcopyrite (CuFeS2) (CCP), and an indigenous acidophilic bacterium, Acidiphilium cryptum (99.56%), was applied for bioleaching experiments. The metal extraction in bioleaching differed according to the mineral content. The leached metal concentration of Zn was higher than that of Pb for the SP sample with a high ZnS content, whereas the concentration of Pb was higher than that of Zn for the GN1 and GN2 samples with a high PbS content. Meanwhile, the leaching rate of Zn was faster than that of Pb for all samples. Corrosion action was observed on the surface of bacterial residues in SP and GN1 samples. These results show that the bioleaching mechanism based on sulfide minerals proceeds through indirect biological oxidation, chemical oxidation, and direct bacterial oxidation. The results of this study can provide basic research data for process optimization when employing bioleaching to extract valuable metals.
Research on Calibration Method of Line-Structured Light Based on Multiple Geometric Constraints
Authors: Li Chunfeng , Xu Xiping , Ren Zhen , Liu Siyuan
Published: May 2023

Line-structured light calibration is an important step in the process of the visual measurement of structured light, and in the calibration process, the light plane equation is fitted by the camera coordinates of the data points on the light plane. There is error in solving the spatial coordinates of the data points, and the existing methods generally cannot effectively find the deviation points in the fitted data points, which leads to deviation when solving the parameters of the light plane equation. To correct the error caused by the deviation point in the calibration, this paper established a calibration method based on geometric constraints. In the method, the first constraint was that all fit points involved in the fitting had a certain consistency, and a part of the error points could be filtered by the distance from the data point to the light plane. In order to further improve the calibration accuracy, the laser was moved on a linear guide, the optimized objective function was established by the second geometric constraint, and the constraint was the relationship that the light plane at each position was parallel. In the experiment, a high-precision gauge block was used as the measured object, and the measurement results could be obtained. The calibration method can improve the calibration accuracy according to the experimental results.
Modeling Nonlinear Aeroelastic Forces for Bridge Decks with Various Leading Edges Using LSTM Networks
Authors: An Xingyu , Li Shaopeng , Wu Teng
Published: May 2023

With the rapid increase in bridge spans, the mitigation of risk to flutter (aeroelastic instability) is of critical importance in the design of long-span bridges, especially considering the more frequent intense hurricanes under climate change. Although the strong nonlinearities of the aeroelastic (self-excited) forces in wind–bridge interactions can be well captured through either numerical simulations or experimental tests, both are expensive and time consuming. Hence, it is important to develop an efficient reduced-order model for the simulations of nonlinear aeroelastic forces on the bridge decks. This study proposes a reduced-order model based on the long short-term memory (LSTM) network to simulate the nonlinear aeroelastic forces on bridge decks with various leading edges, and thus rapidly predict the corresponding post-flutter behaviors of long-span bridges. To generate the training datasets, computational fluid dynamics (CFD) was employed to simulate the nonlinear aeroelasticities of bridge decks with a wide range of leading-edge configurations and wind speeds. Trained on the high-fidelity CFD datasets, the LSTM network takes the motion of a bridge deck, leading-edge angles and wind speeds as inputs and outputs the nonlinear aeroelastic forces on the bridge decks. A hybrid loss function utilizing the prediction errors of both aeroelastic forces simulated by the LSTM network and the bridge deck responses calculated by the Newmark-β algorithm was introduced into the training process to improve the network performance. The prediction results of the trained LSTM model were compared with the CFD simulations, which demonstrated that the nonlinear aeroelastic forces of the bridge deck with various leading edges can be accurately and efficiently acquired by the proposed LSTM model.
Non-Destructive Evaluation of In-Plane Waviness in Carbon Fiber Laminates Using Eddy Current Testing
Authors: Newton Matthew , Chowdhury Tonoy , Gravagne Ian , Jack David
Published: May 2023

Non-destructive detection of the in-plane waviness of carbon fiber-reinforced plastic (CFRP) laminates is of interest in a wide variety of industries, as wrinkles and other fiber alignment defects significantly impact the mechanical performance of the composites. This work demonstrates a method to detect in-plane wrinkles on a 5-ply unidirectional CFRP laminate with a customized eddy current testing (ECT) system. The results show that the ECT system is effective in detecting and quantifying in-plane waviness, and the results are compared to conventional X-ray computed tomography (CT) and ultrasonic testing (UT) methods. Using the anisotropic conductive nature of the aligned CFRP lamina, the ECT system was able to clearly detect throughout the part changes in the local fiber orientation, wave tangent angle, and wrinkle width.
A Comparative Analysis of Feature Detectors and Descriptors for Image Stitching
Authors: Sharma Surendra Kumar , Jain Kamal , Shukla Anoop Kumar
Published: May 2023

Image stitching is a technique that is often employed in image processing and computer vision applications. The feature points in an image provide a significant amount of key information. Image stitching requires accurate extraction of these features since it may decrease misalignment flaws in the final stitched image. In recent years, a variety of feature detectors and descriptors that may be utilized for image stitching have been presented. However, the computational cost and correctness of feature matching restrict the utilization of these techniques. To date, no work compared feature detectors and descriptors for image stitching applications, i.e., no one has considered the effect of detectors and descriptors on the generated final stitched image. This paper presents a detailed comparative analysis of commonly used feature detectors and descriptors proposed previously. This study gives various contributions to the development of a general comparison of feature detectors and descriptors for image stitching applications. These detectors and descriptors are compared in terms of number of matched points, time taken and quality of stitched image. After analyzing the obtained results, it was observed that the combination of AKAZE with AKAZE can be preferable almost in all possible situations.
Electric Vehicles: Benefits, Challenges, and Potential Solutions for Widespread Adaptation
Authors: Alanazi Fayez
Published: May 2023

The world’s primary modes of transportation are facing two major problems: rising oil costs and increasing carbon emissions. As a result, electric vehicles (EVs) are gaining popularity as they are independent of oil and do not produce greenhouse gases. However, despite their benefits, several operational issues still need to be addressed for EV adoption to become widespread. This research delves into the evolution of EVs over time and highlights their benefits, including reducing carbon emissions and air pollution. It also explores the challenges and difficulties faced in their adoption, such as the high cost of infrastructure, scarcity of charging stations, limited range or range anxiety, and the performance of batteries. To overcome these challenges, potential solutions include enhancing the charging infrastructure, increasing the number of charging stations, using battery swapping techniques, and improving battery technology to address range anxiety and reduce charging times. Governments can incentivize consumers to purchase EVs through tax credits or subsidies and invest in building a robust charging infrastructure. Industry stakeholders can collaborate with governments to address these challenges and promote the adoption of EVs, which can contribute to reducing carbon emissions and air pollution.
Damage Analysis of Reinforced Concrete Columns Based on Fiber Beam–Column Element
Authors: Gao Ying , Zheng Liang , Han Yunshan , Zhao Zhiyi
Published: May 2023

The method of damage analysis of reinforced concrete columns based on the fiber element model is established by combining the uniaxial damage constitutive model of concrete and steel with the fiber beam–column element model. The quasi-static test and the shaking table test of reinforced concrete columns are simulated and analyzed, respectively. The results show that the established fiber element model can predict nonlinear mechanical behavior and the damage distribution of reinforced concrete columns with good accuracy. Furthermore, the model can effectively simulate the evolution process of damage of columns, and describe weak parts of columns, and has high computational efficiency and solution accuracy, thus providing a practical analysis method for the simulation of building structures during earthquake.
Creating an Interactive Urban Traffic System for the Simulation of Different Traffic Scenarios
Authors: Weißmann Marco , Edler Dennis , Keil Julian , Dickmann Frank
Published: May 2023

The social and political efforts to fight climate change have contributed to a re-thinking of traffic systems, especially in urban areas under constant transformation. To simulate and visualize planning scenarios of urban traffic systems in a realistic way, the possibilities of virtual 3D environments have regularly been used. The modern potentials of (immersive) virtual reality, however, still require exploration, evaluation, and further development. Using the game engine Unity, an immersive virtual environment was developed to visualize and experience dynamic traffic conditions of a highly dense urban area. The case study is based on the characteristic model of a Central European city (not a representation of a real city), which brings together the specific considerations of urban traffic, such as mirroring the complex interplay of pedestrians as well as individual and public transport. This contribution has an applied methodological focus and considers possibilities as well as difficulties in the design of a reliably running (open-end) traffic system. The applied tool for the creation of a modular and customizable traffic system in Unity resulted in a traffic system that is capable of reacting to the individual behavior of the user (including the individualized motion of the avatar), without leading to accidents or uncorrectable traffic jams. Therefore, the tool used could be a valuable option for any developer of immersive virtual environments in Unity to equip these immersive virtual environments with a traffic system, without the use of additional third-party software.
Study on the Thermal Fatigue Effect of Carboxymethylcellulose Solution Media Dissolved in Water as a Quenching Cooling Medium
Authors: Nejneru Carmen , Cimpoesu Ramona , Vizureanu Petrica , Epure Elena-Luiza , Perju Manuela Cristina , Lupescu Ștefan-Constantin
Published: May 2023

The degradation of a quenching cooling medium is a particularly important technical aspect in the technology of primary and final thermal treatments. This paper studied the effect of the thermal cycles of heating and cooling on a tempering medium type of 2.5% carboxymethyl cellulose solution in water. The main characteristic of a cooling medium is the absorption of heat from the part, which is influenced by the physico-chemical characteristics of the cooling liquid according to the degree of thermal fatigue. For this, the main properties of the environment are analyzed, such the chemical composition, corrosion capacity, wetting capacity and cooling characteristics. To analyze the change in properties during the operation, we studied the effect of thermal cycles on the physico-chemical characteristics of the quenching medium to determine the optimal period when the quenching medium could function in good parameters without the necessary corrections. For this purpose, cyclic and linear corrosion tests, FTIR compositional analyses and contact angle measurements were conducted.
Ultrasensitive Phototransistor Based on Laser-Induced P-Type Doped WSe2/MoS2 Van der Waals Heterojunction
Authors: Zhu Junqiang , Yue Xiaofei , Chen Jiajun , Wang Jing , Wan Jing , Bao Wenzhong , Hu Laigui , Liu Ran , Cong Chunxiao , Qiu Zhijun
Published: May 2023

Out-of-plane p-n heterojunctions based on two-dimensional layered materials (2DLMs) with unusual physical characteristics are attracting extensive research attention for their application as photodetectors. However, the present fabrication method based on 2DLMs produces out-of-plane p-n homojunction devices with low photoresponsivity and detectivity. This work reports an ultrasensitive phototransistor based on a laser-induced p-doped WSe2/MoS2 van der Waals heterojunction. The laser treatment is used for p-doping WSe2 nanoflakes using high work function WOx. Then, an n-type MoS2 nanoflake is transferred onto the resulting p-doped WSe2 nanoflake. The built-in electric field of p-doped WSe2/MoS2 is stronger than that of pristine WSe2/MoS2. The p-n junction between p-doped WSe2 and MoS2 can separate more photogenerated electron–hole pairs and inject more electrons into MoS2 under laser illumination than pristine WSe2/MoS2. Thus, a high photoresponsivity (R) of ~1.28 × 105 A·W−1 and high specific detectivity (D*) of ~7.17 × 1013 Jones are achieved under the illumination of a 633 nm laser, which is approximately two orders higher than the best phototransistor based on a WSe2/MoS2 heterojunction. Our work provides an effective and simple method to enhance photoresponsivity and detectivity in two-dimensional (2D) heterojunction phototransistors, indicating the potential applications in fabricating high-performance photodetectors based on 2DLMs.
Long-Tailed Metrics and Object Detection in Camera Trap Datasets
Authors: He Wentong , Luo Ze , Tong Xinyu , Hu Xiaoyi , Chen Can , Shu Zufei
Published: May 2023

With their advantages in wildlife surveys and biodiversity monitoring, camera traps are widely used, and have been used to gather massive amounts of animal images and videos. The application of deep learning techniques has greatly promoted the analysis and utilization of camera trap data in biodiversity management and conservation. However, the long-tailed distribution of the camera trap dataset can degrade the deep learning performance. In this study, for the first time, we quantified the long-tailedness of class and object/box-level scale imbalance of camera trap datasets. In the camera trap dataset, the imbalance problem is prevalent and severe, in terms of class and object/box-level scale. The camera trap dataset has worse object/box-level scale imbalance, and too few samples of small objects, making deep learning more challenging. Furthermore, we used the BatchFormer module to exploit sample relationships, and improved the performance of the general object detection model, DINO, by up to 2.9% and up to 3.3% in terms of class imbalance and object/box-level scale imbalance. The experimental results showed that the sample relationship was simple and effective, improving detection performance in terms of class and object/box-level scale imbalance, but that it could not make up for the low number of small objects in the camera trap dataset.
Size Effect of Silver Nanoparticles Derived from Olive Mill Wastewater in THP-1 Cell Lines
Authors: De Matteis Valeria , Griego Anna , Scarpa Edoardo , Cascione Mariafrancesca , Singh Jagpreet , Rizzello Loris
Published: May 2023

The constant demand of silver nanoparticles (AgNPs) for different applications requires a new selection of solvents and reagents for their synthesis, to make them less toxic to living organisms and the environment. Among the alternative technologies that can be used to exclude the use of toxic products, green chemistry is based on the employment of biomolecules derived from plants or microorganisms to achieve NPs. Therefore, with the aim of applying the principles of circular economy, the waste deriving from the production of olive oil represents a useful source of polyphenols to be used as reduction agents to obtain AgNPs. In our work, we employed the Olive Mill Wastewater (OMWW), the so-called vegetation water typical of the Mediterranean geographical area, to achieve two sizes of AgNPs, i.e., 50 nm and 30 nm. These NPs were tested on the human monocytic cell line (THP-1) using two concentrations (3 µM and 5 µM) to understand their ability to trigger or not the inflammatory response. This was undertaken following IL-6, IL-8, IL-5 and TNF-α secretion and the NF-kB translocation. We concluded that the AgNPs did not induce strong activation of these pathways, especially when the cells were treated with higher dimensional NPs. Consequently, the application of these NPs in vivo for therapeutic purpose could be significant.
Optimization of Ultrasonic Powder Coatings on the Surface of Treated Materials
Authors: Gradov Oleg M.
Published: May 2023

By generalizing the theory of contact of solids for the case of triple contact of working bodies, the powder particle, the treated surface and the problem of establishing an optimal value for the amplitude of ultrasonic exposure, at which the coating process proceeds most efficiently, were solved. The relevance of such a solution is directly determined by the need to obtain high-quality coating. Analytical expressions of the desired values for the physical parameters of the materials of the objects participating in the working process were obtained. Possible limitations regarding the most important characteristics of the installation were analyzed. Approximate evaluation of the optimal number of working bodies for the resonant chamber was derived. The basic time of the process duration was estimated for the total treatment of the chosen surface by working bodies.
Effects of Shading on the Growth and Carbon Storage of Enhalus acoroides
Authors: Fu Miao , Song Yanwei , Wang Yang , Fu Guowei , Zhang Xiang
Published: May 2023

Light intensity is one of the main factors determining the growth and distribution of seagrasses, but seagrasses differ in their responses to changes in the light environment, resulting in inconsistent adaptation. To investigate the effect of light reduction on Enhalus acoroides (L. f.) Steud., we simulated different light intensities by setting up in situ shade shelters with three light environments: full light (CK), moderate shading (MS) and high shading (HS), and investigated the growth response and adaptation mechanism of E. acoroides to a low-light environment. The results showed that the leaf length and leaf width of E. acoroides decreased in the low-light environment. Plant density, biomass, and chlorophyll content (Chl) decreased significantly with the prolongation of shading. In addition, the sediment carbon content of seagrass beds was significantly reduced in the shading treatments compared to the full-light treatment. After the restoration of light, the chlorophyll content of E. acoroides increased compared to that in the shading period, but its leaf morphology, plant density and biomass did not return to the level of full light treatment. Our study highlights that long-term light reduction leads to a significant reduction in seagrass biomass and its sediment carbon content, which in turn, may reduce the carbon storage capacity of seagrass beds.
ChatGPT Challenges Blended Learning Methodologies in Engineering Education: A Case Study in Mathematics
Authors: Sánchez-Ruiz Luis M. , Moll-López Santiago , Nuñez-Pérez Adolfo , Moraño-Fernández José A. , Vega-Fleitas Erika
Published: May 2023

This research aims to explore the potential impact of the ChatGPT on b-learning methodologies in engineering education, specifically in mathematics. The study focuses on how the use of these artificial intelligence tools can affect the acquisition of critical thinking, problem-solving, and group work skills among students. The research also analyzes the students’ perception of the reliability, usefulness, and importance of these tools in academia. The study collected data through a survey of 110 students enrolled in a Mathematics I course in BEng Aerospace Engineering where a blended methodology, including flipped teaching, escape room gamification, problem-solving, and laboratory sessions and exams with a computer algebraic system were used. The data collected were analyzed using statistical methods and tests for significance. Results indicate students have quickly adopted ChatGPT tool, exhibiting high confidence in their responses (3.4/5) and general usage in the learning process (3.61/5), alongside a positive evaluation. However, concerns arose regarding the potential impact on developing lateral competencies essential for future engineers (2.8/5). The study concludes that the use of ChatGPT in blended learning methodologies poses new challenges for education in engineering, which requires the adaptation of teaching strategies and methodologies to ensure the development of essential skills for future engineers.
Special Issue on Cryptography and Information Security
Authors: Por Lip Yee , Yang Jing , Ku Chin Soon , Khan Abdullah Ayub
Published: May 2023

In today’s increasingly connected world, the demand for secure computing and data protection is soaring [...]
Impact of Cytochrome P450 Enzymes on the Phase I Metabolism of Drugs
Authors: Iacopetta Domenico , Ceramella Jessica , Catalano Alessia , Scali Elisabetta , Scumaci Domenica , Pellegrino Michele , Aquaro Stefano , Saturnino Carmela , Sinicropi Maria Stefania
Published: May 2023

The cytochrome P450 (CYP) enzyme family is the major enzyme system catalyzing the phase I metabolism of xenobiotics, including pharmaceuticals and toxic compounds in the environment. A major part of the CYP-dependent xenobiotic metabolism is due to polymorphic and inducible enzymes, which may, quantitatively or qualitatively, alter or enhance drug metabolism and toxicity. Drug–drug interactions are major mechanisms caused by the inhibition and/or induction of CYP enzymes. Particularly, CYP monooxygenases catalyze hydroxylation reactions to form hydroxylated metabolites. The secondary metabolites are sometimes as active as the parent compound, or even more active. The aim of this review is to summarize some of the significative examples of common drugs used for the treatment of diverse diseases and underline the activity and/or toxicity of their metabolites.
BILSTM-Based Deep Neural Network for Rock-Mass Classification Prediction Using Depth-Sequence MWD Data: A Case Study of a Tunnel in Yunnan, China
Authors: Cheng Xu , Tang Hua , Wu Zhenjun , Liang Dongcai , Xie Yachen
Published: May 2023

Measurement while drilling (MWD) data reflect the drilling rig–rock mass interaction; they are crucial for accurately classifying the rock mass ahead of the tunnel face. Although machine-learning methods can learn the relationship between MWD data and rock mechanics parameters to support rock classification, most current models do not consider the impact of the continuous drilling-sequence process, thereby leading to rock-classification errors, while small and unbalanced field datasets result in poor model performance. We propose a novel deep neural network model based on Bi-directional Long Short-Term Memory (BILSTM) to extract information-related sequences in MWD data and improve the accuracy of the rock-mass classification. Two optimization modules were designed to improve the model’s generalization performance. Stratified K-fold cross-validation was used for model optimization in small and unbalanced datasets. Model validation is based on the MWD dataset of a highway tunnel in Yunnan, China. Multiple metrics show that the prediction ability of the network is significantly better than those of a multilayer perceptron (MLP) and a support-vector machine (SVM), while the model exhibits an improved generalization performance. The accuracy of the network can reach 90%, which is 13% and 15% higher than the MLP and SVM, respectively.