bluuebunny/crossref_metadata_2025 huggingface dataset:
Bentonite–Concrete Interactions in Engineered Barrier Systems during the Isolation of Radioactive Waste Based on the Results of Short-Term Laboratory Experiments
Authors: Morozov Ivan , Zakusin Sergey , Kozlov Pavel , Zakusina Olga , Roshchin Marat , Chernov Michail , Boldyrev Kirill , Zaitseva Tatiana , Tyupina Ekaterina , Krupskaya Victoria
Published: March 2022

Bentonite clays have unique properties that determine their use as the main component of engineered barrier systems (EBS) for the isolation of radioactive waste. At present, the Russian Federation is elaborating the concept of deep geological disposal of radioactive waste in crystalline rocks of the Yeniseisky site, where bentonite clays play an important role in ensuring the safety of the repository for a long period of time. This work demonstrates the first results of short-term laboratory experiments (1 and 3 months) on the thermochemical interaction of bentonite and concrete in the presence of synthetic water at an elevated temperature. These experiments will help predict the effect of EBS materials on montmorillonite. Bentonite from the 10th Khutor deposit (Russia) and Portland cement were used in the experiments. At the first stage of the experiments, solutions were obtained after leaching the concrete with a synthetic groundwater solution for 1 month at 90 °C. At the second stage, the interactions of the obtained solutions with bentonite at 90 °C were studied. As a result of the experiments, the processes of concrete leaching were revealed, which changed the composition and acidity (an increase in the pH from 6.1 to 12.1) of the synthetic water and led to an increase in the porosity of the material in contact with the solution. However, no dissolution of montmorillonite was observed, and the changes were quite small. The research results show the high stability of bentonite from the 10th Khutor deposit under model conditions, which was confirmed by modeling. Thus, we can say that at pH ≈ 12 and at elevated temperatures, montmorillonite retains a stable structure for a long time, which is important for ensuring the safety of disposal in general.
Development of Automatic Crack Growth Simulation Program Based on Finite Element Analysis
Authors: Lee Gi-Bum , Park Seung-Hyun , Jang Youn-Young , Huh Nam-Su , Park Sung-Hoon , Park Noh-Hwan , Park Jun
Published: March 2022

A crack growth simulation program based on the advanced iterative-finite element method (AI-FEM) was developed to predict realistic crack growth of structures. The developed program was suggested to calculate the exact stress intensity factor for arbitrary structures by regenerating the crack tip mesh as the crack grows. The main advantages of the developed program are to estimate each different crack growths along the crack tip line and to simulate the cracking transition from a surface crack to a through-wall crack under a complex stress field. For these purposes, the sensitivity analyses were performed for various influence variables on stress intensity factors, such as element types and crack dimensions. Based on the results of sensitivity analyses, the appropriate criteria for crack tip modeling to be used in AI-FEM were suggested to calculate sufficient converged SIF. The program developed in this research was validated through stress corrosion crack growth and natural crack growth examples including cracking transition, and it was confirmed that the program simulates crack growth well and has reasonable methods for cracking transition.
Assessing Flood Indirect Impacts on Road Transport Networks Applying Mesoscopic Traffic Modelling: The Case Study of Santarém, Portugal
Authors: Shahdani Fereshteh Jafari , Santamaria-Ariza Mónica , Sousa Hélder S. , Coelho Mário , Matos José C.
Published: March 2022

The key aspect for the quantification of indirect impacts of flooding is the assessment of the disruption of the transportation service considering social and economic consequences. To investigate how flooding can affect road transportation, it is essential to analyze interaction during the flood event itself, as well as on the following days. In this work, two static and dynamic traffic models are applied to a study zone for quantification of the performance and functionality of the network during the flood and after the failure of infrastructure components. A mesoscopic simulation was applied to identify the traffic disruption in the face of flood events. This simulation is capable of considering the road network model, assigning trip paths with the impact of road closures and speed reductions, and evaluating travel time and vehicle volume redistribution in a given disruption scenario. By comparing the traffic analysis results (travel time, travelled distance and street speed changes) in normal and flooded situations, the impact of flooding on a transportation network could be examined. Moreover, modelling outputs from a case study in the Santarém region (Portugal) indicated that in analyzing the flood impacts on a traffic network, even non-flooded infrastructures must be taken into account because of their service disruption.
Recycled Paper Sludge (RPS)-Derived Nanocellulose: Production, Detection and Water Treatment Application
Authors: Maslennikov Alona , Peretz Roi , Vadivel Vinod Kumar , Mamane Hadas
Published: March 2022

Paper production and recycling result in large amounts of recycled paper sludge (RPS) that is currently being disposed of in very costly and unsustainable practices, raising the importance of developing green solutions for waste management. The use of nanocellulose (NC) as the next generation of materials has gained much attention due to its economic potential. However, there are substantial challenges in NC extraction, detection, and quantification methods. In this study, NC was produced from RPS as a means of converting waste into a resource. The process included a short, 30 min ozonation (21 mg O3/g RPS), which allowed a sufficient delignification and facilitated the following hydrolysis step. Among all tested durations, a 4-h hydrolysis with 64% w/w sulfuric acid resulted in the highest NC production. Fluorescent staining by calcofluor white was used for simple and low-cost detection of NC in-situ. Crude NC showed a significant 63% dye uptake of 0.1 ppm acid red 131 within 30 min. Compared to the standard disposal methods of RPS, its utilization for NC production supports the circular economy concept and significantly contributes to the development of cellulose bio-based nanomaterials for water treatment applications.
Reinforcement-Learning-Based Vibration Control for a Vehicle Semi-Active Suspension System via the PPO Approach
Authors: Han Shi-Yuan , Liang Tong
Published: March 2022

The vehicle semi-active suspension system plays an important role in improving the driving safety and ride comfort by adjusting the coefficients of the damping and spring. The main contribution of this paper is the proposal of a PPO-based vibration control strategy for a vehicle semi-active suspension system, in which the designed reward function realizes the dynamic adjustment according to the road condition changes. More specifically, for the different suspension performances caused by different road conditions, the three performances of the suspension system, body acceleration, suspension deflection, and dynamic tire load, were taken as the state space of the PPO algorithm, and the reward value was set according to the numerical results of the passive suspension, so that the corresponding damping force was selected as the action space, and the weight matrix of the reward function was dynamically adjusted according to different road conditions, so that the agent could have a better improvement effect at different speeds and road conditions. In this paper, a quarter–car semi-active suspension model was analyzed and simulated, and numerical simulations were performed using stochastic road excitation for different classes of roads, vehicle models, and continuously changing road conditions. The simulation results showed that the body acceleration was reduced by 46.93% under the continuously changing road, which proved that the control strategy could effectively improve the performance of semi-active suspension by combining the dynamic changes of the road with the reward function.
Terminalia ferdinandiana (Kakadu Plum)-Mediated Bio-Synthesized ZnO Nanoparticles for Enhancement of Anti-Lung Cancer and Anti-Inflammatory Activities
Authors: Ramadhania Zelika Mega , Nahar Jinnatun , Ahn Jong Chan , Yang Dong Uk , Kim Jong Hak , Lee Dong Wook , Kong Byoung Man , Mathiyalagan Ramya , Rupa Esrat Jahan , Akter Reshmi , Yang Deok Chun , Kang Se Chan , Kwak Gi-Young
Published: March 2022

Terminalia ferdinandiana (Kakadu plum) is an Australian native plant that has recently gained the attention of researchers due to its highly antioxidant compounds that have substantial health benefits. To raise the value, in this study, it is used for the first time to synthesize ZnO nanoparticles for anti-lung cancer and anti-inflammatory activities. The formation of KKD-ZnO-NPs (ZnO particles obtained from Kakadu plum) were confirmed using a UV-Visible spectrophotometer. Fourier transform infrared (FTIR) spectroscopy analysis confirmed the functional groups that are responsible for the stabilization and capping of KKD-ZnO-NPs. The flower shape of the synthesized KKD-ZnO-NPs was confirmed by field emission-scanning electron microscopy (FE-SEM) and field emission-transmission electron microscopy (FE-TEM) analyses. The crystallites were highly pure and had an average size of 21.89 nm as measured by X-ray diffraction (XRD). The dynamic light scattering (DLS) revealed size range of polydisperse KKD-ZnO-NPs was 676.65 ± 47.23 nm with a PDI of 0.41 ± 0.0634. Furthermore, the potential cytotoxicity was investigated in vitro against human lung cancer cell lines (A549) and Raw 264.7 Murine macrophages cells as normal cells to ensure safety purposes using MTT assay. Thus, KKD-ZnO-NPs showed prominent cytotoxicity against human lung adenocarcinoma (A549) at 10 μg/mL and increased reactive oxygen species (ROS) production as well, which could promote toxicity to cancer cells. Moreover, upregulation of p53 and downregulation of bcl2 gene expression as apoptosis regulators were confirmed via RT-PCR. In addition, KKD-ZnO-NPs possess a similar capacity of reduction in proinflammatory-nitric oxide (NO) production when compared to the L-NMMA as inflammation’s inhibitor, indicating anti-inflammatory potential. Incorporation of Kakadu plum extract as reducing and stabilizing agents enabled the green synthesis of flower-shaped KKD-ZnO-NPs that could be an initiative development of effective cancer therapy drug.
Mass Cultivation of Microalgae: I. Experiences with Vertical Column Airlift Photobioreactors, Diatoms and CO2 Sequestration
Authors: Eilertsen Hans Chr. , Eriksen Gunilla K. , Bergum John-Steinar , Strømholt Jo , Elvevoll Edel , Eilertsen Karl-Erik , Heimstad Eldbjørg Sofie , Giæver Ingeborg Hulda , Israelsen Linn , Svenning Jon Brage , Dalheim Lars , Osvik Renate , Hansen Espen , Ingebrigtsen Richard A. , Aspen Terje , Wintervoll Geir-Henning
Published: March 2022

From 2015 to 2021, we optimized mass cultivation of diatoms in our own developed vertical column airlift photobioreactors using natural and artificial light (LEDs). The project took place at the ferrosilicon producer Finnfjord AS in North Norway as a joint venture with UiT—The Arctic University of Norway. Small (0.1–6–14 m3) reactors were used for initial experiments and to produce inoculum cultures while upscaling experiments took place in a 300 m3 reactor. We here argue that species cultivated in reactors should be large since biovolume specific self-shadowing of light can be lower for large vs. small cells. The highest production, 1.28 cm3 L−1 biovolume (0.09–0.31 g DW day−1), was obtained with continuous culture at ca. 19% light utilization efficiency and 34% CO2 uptake. We cultivated 4–6 months without microbial contamination or biofouling, and this we argue was due to a natural antifouling (anti-biofilm) agent in the algae. In terms of protein quality all essential amino acids were present, and the composition and digestibility of the fatty acids were as required for feed ingredients. Lipid content was ca. 20% of ash-free DW with high EPA levels, and omega-3 and amino acid content increased when factory fume was added. The content of heavy metals in algae cultivated with fume was well within the accepted safety limits. Organic pollutants (e.g., dioxins and PCBs) were below the limits required by the European Union food safety regulations, and bioprospecting revealed several promising findings.
High-Speed Spiral Bevel GEAR Dynamic Rules Considering the Impact of Web Thicknesses and Angles
Authors: Hou Xiangying , Qiu Linyue , Zhang Yuzhe , Li Zhengminqing , Zhu Rupeng , Lyu Sung-Ki
Published: March 2022

Gear transmission system dynamic responses under high-speed and heavy-duty working conditions were obviously affected by support structures, especially in lightweight design. However, web thicknesses and angles were usually ignored in dynamic modeling process. Therefore, a full mesh model with web structure was built and its dynamic characteristics were analyzed by a modified vector form intrinsic finite element (VFIFE), which is proposed to solve high-speed dynamic problems with good efficiency. For spiral bevel gear pair dynamic characteristics, the impacts of web thicknesses and angles were simulated and discussed. Simulation results showed that web support angles will affect gear meshing performance and dynamic characteristics more remarkable than web thickness did. In addition, the good performance of the proposed modified VFIFE method was proved, which showed good computing efficiency.
Spatial Location of Sugarcane Node for Binocular Vision-Based Harvesting Robots Based on Improved YOLOv4
Authors: Zhu Changwei , Wu Chujie , Li Yanzhou , Hu Shanshan , Gong Haibo
Published: March 2022

Spatial location of sugarcane nodes using robots in agricultural conditions is a challenge in modern precision agriculture owing to the complex form of the sugarcane node when wrapped with leaves and the high computational demand. To solve these problems, a new binocular location method based on the improved YOLOv4 was proposed in this paper. First, the YOLOv4 deep learning algorithm was improved by the Channel Pruning Technology in network slimming, so as to ensure the high recognition accuracy of the deep learning algorithm and to facilitate transplantation to embedded chips. Secondly, the SIFT feature points were optimised by the RANSAC algorithm and epipolar constraint, which greatly reduced the mismatching problem caused by the similarity between stem nodes and sugarcane leaves. Finally, by using the optimised matching point to solve the homography transformation matrix, the space location of the sugarcane nodes was for the first time applied to the embedded chip in the complex field environment. The experimental results showed that the improved YOLOv4 algorithm reduced the model size, parameters and FLOPs by about 89.1%, while the average precision (AP) of stem node identification only dropped by 0.1% (from 94.5% to 94.4%). Compared with other deep learning algorithms, the improved YOLOv4 algorithm also has great advantages. Specifically, the improved algorithm was 1.3% and 0.3% higher than SSD and YOLOv3 in average precision (AP). In terms of parameters, FLOPs and model size, the improved YOLOv4 algorithm was only about 1/3 of SSD and 1/10 of YOLOv3. At the same time, the average locational error of the stem node in the Z direction was only 1.88 mm, which totally meets the demand of sugarcane harvesting robots in the next stage.
Implementation of the Modern Immersive Learning Model CPLM
Authors: Veber Matej , Pesek Igor , Aberšek Boris
Published: March 2022

The digitalization of industrial processes is being driven forward worldwide. In parallel, the education system must also be transformed. Currently, education does not follow the opportunities and development of technologies. We can ask ourselves how we can integrate technologies into a traditional learning process or how we can adapt the learning process to these technologies. We focused on robotics education in secondary vocational education. The paper contains research results from a modern learning model that addresses student problem-solving using cyber–physical systems. We proposed a reference model for industrial robotics education in the 21st century based on an innovative cyber-physical didactic model (CPLM). We conducted procedure time measurements, questionnaire evaluations, and EEG evaluations. We could use VR to influence the improvement of spatial and visual memory. The more intense representation of the given information influences multiple centers in the brain and, thus, the formation of multiple neural connections. We can influence knowledge, learning more effectively with short-term training in the virtual world than with classical learning methods. From the studied resources, we can conclude that the newer approach to teaching robotics is not yet available in this form. The emerging modern technologies and the possibility of developing training in this area should be investigated further.
Passive and Active Solar Systems in Eco-Architecture and Eco-Urban Planning
Authors: Zaręba Anna , Krzemińska Alicja , Kozik Renata , Adynkiewicz-Piragas Mariusz , Kristiánová Katarina
Published: March 2022

The subject of this article is a presentation of multi-scale passive and active solar and shading systems in urban areas. This research assumes the hypothesis that insolation systems are interdependent and that their integration in urbanized space affects the city biome. Attention has been paid to the role of innovative solutions used in the field of ur ban insolation, such as heliostats in the development of future eco-architecture and eco-urban planning. This research has been based on the assumption that only by taking into account the close symbiosis between an energy-efficient building and its appropriate insolation, in combination with properly planned surroundings, it is possible to actually achieve the principles of sustainable development in the urban fabric. The analytical part concerns detailed investigation into solutions in the field of passive and active solar architecture and urban planning, regarding both insolation and shading. The article analyzes source materials, includes descriptions of case studies, and presents a comparative analysis of passive and active solar and shading systems. The research method, both empirically and theoretically, is closely related to case study analysis and has involved collecting and systematizing data on micro and macro “solar” design systems.
Correction: Althalb et al. A Novel Approach to Enhance Crude Oil Recovery Ratio Using Selected Bacterial Species. Appl. Sci. 2021, 11, 10492
Authors: Althalb Hakima A. , Elmusrati Izzeddin M. , Banat Ibrahim M.
Published: March 2022

In the original publication [...]
Experimental Study of Downburst Wind Flow over a Typical Three-Dimensional Hill
Authors: Chen Yong , Li Yuhan , Yao Jianfeng , Shen Guohui , Lou Wenjuan , Xu Haiwei , Guo Yong
Published: March 2022

To achieve a comprehensive understanding of a three-dimensional (3D) wind field and the speed-up phenomenon in a downburst wind flow over a 3D hilly terrain, a succession of laboratory tests utilizing 12 hill models with cosine-squared cross-section was conducted using a physical downburst simulator with a jet diameter of 0.6 m. By placing the models in the strong horizontal wind region and the strong vertical wind region, the corresponding wind profiles for both the horizontal and vertical velocities were measured. It was found that the wind flowed predominantly over the crest of the hill in the case of low hills, whereas wind flow around the hill body became increasingly pronounced as the hill height increased. In addition, the speed-up region, where the horizontal wind velocity exceeds the impinging jet velocity, was identified, and found to move from the crest to the two sides of the hill as the hill height increased. Accordingly, the most significant topographic multipliers of all locations on the hill might appear at the crest, the hill foot, or elsewhere, depending largely on the hill height. Among all cases, the maximum topographic multiplier was 1.12, and occurred at the ridge, while the ratio of hill height to jet height was 5/12. Additionally, empirical equations are presented to facilitate the determination of wind loads induced by a downburst flow over an isolated hill.
Multi-Sensor GA-BP Algorithm Based Gearbox Fault Diagnosis
Authors: Fu Yuan , Liu Yu , Yang Yan
Published: March 2022

To address the problem of the low recognition rate of time-frequency domain methods gearbox fault identification, a method featuring decision-level fusion of DS evidence theory and GA-BP algorithm was proposed in the present study. Firstly, the fault data of each state of the gearbox was classified, based on which the time-frequency domain features were extracted and 19 significant features have been selected. Secondly, the accuracy of the traditional BP algorithm was compared with that of the GA-BP algorithm. On this basis, it has been concluded that the GA-BP algorithm is highly accurate, and the local diagnostic results obtained by the GA-BP algorithm have been used as the basic probability. Finally, the DS evidence theory is currently used to fuses with the GA. In addition, the final fault identification of the gearbox can be achieved by using the DS evidence theory and the multi-sensor local diagnosis results obtained by the GA-BP algorithm for decision fusion. The results of the simulations and experiments showed that the method proposed has improved accuracy over a single algorithm for fault identification of gearboxes, respectively.
Autostereoscopic-Raman Spectrometry-Based Three-Dimensional Metrology System for Measurements, Tracking and Identification in a Volume
Authors: Wang Jingfan , Zhao Xing , Li Da , Wen Ya , Wang Weihao , Wang Bin , Xu Xiaoxuan , Bai Hua , Liu Weiwei
Published: March 2022

Three-dimensional compound measurement within a volume of interest is of great importance in industrial manufacturing and the biomedical field. However, there is no current method that can simultaneously perform spatial localization and 3D measurement in a non-scanning manner as well as the identification of material in a volume. In this paper, an Autostereoscopic-Raman Spectrometry-based (ARS) three-dimensional measurement system is proposed. The target object in a large depth range is initially positioned by the autostereoscopic 3D measurement method, and then the accurate position information is cross-checked and obtained by combining the spectral signal. Meanwhile, the spectral signal at the precise excitation position guided by the autostereoscopic signal also carries the material composition information. In order to verify the proposed ARS method, an associated measurement system was developed, and experimental studies of detecting various fibers of different depths in multi-layer glass structure were conducted. The spatial locations and dimensional information of multiple different targets can be measured in a volume, and their material can also be identified at the same time. The average error between the calculated position processed by the ARS system and the actual spatial position is within sub-micron levels, and the success rate of spectrum acquisition reaches 98%.
Marine Geopolymer Concrete—A Hybrid Curable Self-Compacting Sustainable Concrete for Marine Applications
Authors: Rahman Sherin Khadeeja , Al-Ameri Riyadh
Published: March 2022

Marine environments are widely addressed as a serious threat to coastal concrete structures due to higher repair and rehabilitation costs. The rising concerns of climate change and related issues also require marine structures to be resilient and sustainable at the same time. Geopolymer concrete has been given more significant consideration as an alternative, reporting better resistance to harsh and hazardous environmental exposure, including sulphate attacks, chloride attacks, and freeze–thaw climates. This study investigated the mechanical properties of fly ash (FA) and ground granulated blast furnace slag (GGBFS)-based self-compacting geopolymer concrete (SCGC), subjected to short term ambient and marine curing conditions. The mechanical performance, inclusive of compressive strength, tensile strength, and modulus of elasticity under three-month marine exposure compared to an ambient environment, indicates that the SCGC mix offered an increase in strength. It is reported that the compressive strength of SCGC increased to the range of 50 MPa after marine exposure in comparison to the 40 MPa strength after 28-day curing. A similar increase in indirect tensile strength and modulus of elasticity were observed for the test specimens, with no signs of leaching of salts under marine exposure. Thus, the current SCGC acts as a sustainable construction material in counteracting the threats of marine degradation in civil structural components.
A Suggestion on the LDA-Based Topic Modeling Technique Based on ElasticSearch for Indexing Academic Research Results
Authors: Kim Mi , Kim Dosung
Published: March 2022

Most academic researchers use the academic information system when they want to write a reference, such as a related research for a paper. Specific classification rules are applied based on vast amounts of data and the latest references to classify and search keywords. Meta information is designed for specific classification rules and search results are restructured. The search results can be classified and rearranged to suit academic research paper keywords by applying the restructured classification system and the LDA-based topic modeling technique. To implement this, the ElasticSearch classification method and topic-based LDA model were applied to extract the characteristics of academic papers in this study. Stable topics that could detect topic estimation and keyword search results within the minimum time were extracted to classify the paper search results. In addition, by analyzing the distribution of document weight among topics, the system performance was proven to be excellent.
Temporal Variations of Heavy Metal Sources in Agricultural Soils in Malta
Authors: Costa Christine , Lia Frederick
Published: March 2022

In the opportunity to understand the benefits of Maltese soil and its importance to our climate, the content of heavy metals—including Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, and Zn—was studied in two fields in proximity in the south-east region of Malta. Analytical determinations were carried out using atomic absorption spectroscopy following heated aqua regia digestion on 50 collected samples using triple repeatability. The decreasing pattern of the concentrations obtained is Fe > Zn > Mn > Sr > Pb > Cu > Ni > Cr > Co. Correlations between pre-harvesting and post-harvesting concentrations were examined to assess lithogenic and anthropogenic relationships. Multivariate analysis including principal component analysis and factor analysis clarified the origin of heavy metals content reviewed. Some of the heavy metals studied showed a dominant relationship between concentration variation and their possible sources. Potential ecological risk assessment demonstrated that the fields reviewed are not contaminated by any of the heavy metals assessed except for Zn which posed a moderate/strong contamination but presented an overall low potential for ecological risk. Concentrations of heavy metals demonstrated no risk to human health and no carcinogenic risk through ingestion and dermal contact with the soil.
Hyperledger Fabric Access Control for Industrial Internet of Things
Authors: Shih Dong-Her , Wu Ting-Wei , Shih Ming-Hung , Chen Guan-Wei , Yen David C.
Published: March 2022

The Industrial Internet of Things (IIoT) plays an important role in Industry 4.0, but the existing IIoT systems could be vulnerable to a single point of failure and malicious attacks, failing to provide reliable services. IIoT devices have some particularities, such as mobility, limited performance, and distributed deployment, which are challenging to traditional centralized access control methods in the large-scale IIoT environment. To resolve the challenges, we propose an access control system for the Industrial Internet of Things. The system contains three smart contracts: device contract (DC), policy contract (PC), and access contract (AC). The device contract provides a method of storing the URL of the resource data generated by the equipment and a query method. The policy contract provides the function of managing the attribute-based access control (ABAC) of the administrator user. The access contract is the core program that implements the access control method for ordinary users. Combining ABAC and blockchain technology provides decentralized, fine-grained, and dynamic access control management for IIoT.
Salt Stress Tolerance-Promoting Proteins and Metabolites under Plant-Bacteria-Salt Stress Tripartite Interactions
Authors: Krishnamoorthy Ramasamy , Roy Choudhury Aritra , Walitang Denver I. , Anandham Rangasamy , Senthilkumar Murugaiyan , Sa Tongmin
Published: March 2022

The rapid increase in soil salinization has impacted agricultural output and poses a threat to food security. There is an urgent need to focus on improving soil fertility and agricultural yield, both of which are severely influenced by abiotic variables such as soil salinity and sodicity. Abiotic forces have rendered one-third of the overall land unproductive. Microbes are the primary answer to the majority of agricultural production’s above- and below-ground problems. In stressful conditions, proper communication between plants and beneficial microbes is critical for avoiding plant cell damage. Many chemical substances such as proteins and metabolites synthesized by bacteria and plants mediate communication and stress reduction. Metabolites such as amino acids, fatty acids, carbohydrates, vitamins, and lipids as well as proteins such as aquaporins and antioxidant enzymes play important roles in plant stress tolerance. Plant beneficial bacteria have an important role in stress reduction through protein and metabolite synthesis under salt stress. Proper genomic, proteomic and metabolomics characterization of proteins and metabolites’ roles in salt stress mitigation aids scientists in discovering a profitable avenue for increasing crop output. This review critically examines recent findings on proteins and metabolites produced during plant-bacteria interaction essential for the development of plant salt stress tolerance.
Comparison of the Performance of Artificial Intelligence Models Depending on the Labelled Image by Different User Levels
Authors: Sunwoo Hyobin , Choi Wonjun , Na Seunguk , Kim Cheekyeong , Heo Seokjae
Published: March 2022

As reconstruction and redevelopment accelerate, the generation of construction waste increases, and construction waste treatment technology is being developed accordingly, especially using artificial intelligence (AI). The majority of AI research projects fail as a consequence of poor learning data as opposed to the structure of the AI model. If data pre-processing and labeling, i.e., the processes prior to the training step, are not carried out with development purposes in mind, the desired AI model cannot be obtained. Therefore, in this study, the performance differences of the construction waste recognition model, after data pre-processing and labeling by individuals with different degrees of expertise, were analyzed with the goal of distinguishing construction waste accurately and increasing the recycling rate. According to the experimental results, it was shown that the mean average precision (mAP) of the AI model that trained on the dataset labeled by non-professionals was superior to that labeled by professionals, being 21.75 higher in the box and 26.47 in the mask, on average. This was because it was labeled using a similar method as the Microsoft Common Objects in Context (MS COCO) datasets used for You Only Look at Coefficients (YOLACT), despite them possessing different traits for construction waste. Construction waste is differentiated by texture and color; thus, we augmented the dataset by adding noise (texture) and changing the color to consider these traits. This resulted in a meaningful accuracy being achieved in 25 epochs—two fewer than the unreinforced dataset. In order to develop an AI model that recognizes construction waste, which is an atypical object, it is necessary to develop an explainable AI model, such as a reconstruction AI network, using the model’s feature map or by creating a dataset with weights added to the texture and color of the construction waste.
Vibration and Wave Analyses in the Functionally Graded Graphene-Reinforced Composite Plates Based on the First-Order Shear Deformation Plate Theory
Authors: Zhou Yunying , Liu Dongying , Zhu Jun
Published: March 2022

Graphene platelets (GPLs) can be used to enhance the mechanical and electrical properties of the matrix material, which efficiently determines and improves the dynamic behavior in composite structures. Based on the first-order shear deformation theory, this paper investigates the vibration and wave problems in a functionally graded graphene-reinforced composite plate. The composite plate is composed of the polymer matrix reinforced with GPLs that are dispersed along the thickness direction, following four kinds of functionally graded patterns. The governing equation of dynamic problems in the composite plate can be described in the state space formulation, and be solved using the method of reverberation-ray matrix (MRRM). Unlike the traditional state space method, this method is unconditionally stable due to introducing the dual coordinates, which can inherently avoid the numerical instability. After a validation study to verify the present analysis, a parametric study is conducted to analyze the effect of weight fraction, size and distribution patterns of the reinforments, as well as the boundary conditions and aspect ratios on the dynamic behaviors of the composite plate, hence providing a better way to achieve improved dynamic resistances of the GPLs composite plates.
Monocular Real Time Full Resolution Depth Estimation Arrangement with a Tunable Lens
Authors: Oliva-García Ricardo , Ceruso Sabato , Marichal-Hernández José G. , Rodriguez-Ramos José M.
Published: March 2022

This work introduces a real-time full-resolution depth estimation device, which allows integral displays to be fed with a real-time light-field. The core principle of the technique is a high-speed focal stack acquisition method combined with an efficient implementation of the depth estimation algorithm, allowing the generation of real time, high resolution depth maps. As the procedure does not depend on any custom hardware, if the requirements are met, the described method can turn any high speed camera into a 3D camera with true depth output. The concept was tested with an experimental setup consisting of an electronically variable focus lens, a high-speed camera, and a GPU for processing, plus a control board for lens and image sensor synchronization. The comparison with other state of the art algorithms shows our advantages in computational time and precision.
Application of Gamma Irradiation Treatment on the Physicochemical and Microbiological Quality of an Artisanal Hard Cheese
Authors: Nyamakwere Faith , Esposito Giulia , Dzama Kennedy , Gouws Pieter , Rapisarda Teresa , Belvedere Giovanni , Masucci Felicia , Raffrenato Emiliano
Published: March 2022

The objective of this study was to evaluate the efficacy of gamma irradiation, applied to different cheese sample sizes (250g and 500 g), against Listeria monocytogenes, Escherichia coli, coliforms and aerobic colony counts. The effects on cheese physicochemical and odour properties and all costs involved for the treatment were quantified. The Cobalt-60 γ-irradiator was used at a maximum dose of 5.0 kGy. The values for cheese moisture (28.6%), ash (3.78%), pH (5.1), protein (29.6%), fat (30.7%), salt (1.95%) and water activity (0.92%) were within the acceptable ranges for hard cheese after gamma irradiation treatment. The colour (yellowness, redness, chroma and hue angle) and texture (cohesiveness and springiness) values decreased (p < 0.05) with the treatment. Compounds such as safrole, acetylpyrazine, thiophene, 3,5-octadien-2-one and 1-Octen-3-one were present after the treatment, regardless of sample size. The gamma irradiation treatment resulted in 100%, 87.2%, 85.1% and 77.3% reduction in L. monocytogenes, coliforms, E. coli and aerobic colony counts, respectively. The study highlighted the efficacy of irradiation treatment and its affordability for resource-limited producers.
MMPCANet: An Improved PCANet for Occluded Face Recognition
Authors: Wang Zewei , Zhang Yongjun , Pan Chengchang , Cui Zhongwei
Published: March 2022

Principal Component Analysis Network (PCANet) is a lightweight deep learning network, which is fast and effective in face recognition. However, the accuracy of faces with occlusion does not meet the optimal requirement for two reasons: 1. PCANet needs to stretch the two-dimensional images into column vectors, which causes the loss of essential image spatial information; 2. When the training samples are few, the recognition accuracy of PCANet is low. To solve the above problems, this paper proposes a multi-scale and multi-layer feature fusion-based PCANet (MMPCANet) for occluded face recognition. Firstly, a channel-wise concatenation of the original image features and the output features of the first layer is conducted, and then the concatenated result is used as the input of the second layer; therefore, more image feature information is used. In addition, to avoid the loss of image spatial information, a spatial pyramid is used as the feature pooling layer of the network. Finally, the feature vector is sent to the random forest classifier for classification. The proposed algorithm is tested on several widely used facial image databases and compared with other similar algorithms. Our experimental results show that the proposed algorithm effectively improves the efficiency of the network training and the recognition accuracy of occluded faces under the same training and testing datasets. The average accuracies are 98.78% on CelebA, 97.58% on AR, and 97.15% on FERET.
Modification of Hand Muscular Synergies in Stroke Patients after Robot-Aided Rehabilitation
Authors: Scotto di Luzio Francesco , Cordella Francesca , Bravi Marco , Santacaterina Fabio , Bressi Federica , Sterzi Silvia , Zollo Loredana
Published: March 2022

The central nervous system (CNS) is able to control a very high number of degrees of freedom to perform complex movements of both upper and lower limbs. However, what strategies the CNS adopts to perform complex tasks are not completely clear and are still being studied. Recent studies confirm that stroke subjects with mild and moderate impairment show altered upper limb muscle patterns, but the muscular patterns of the hand have not completely investigated, although the hand represents a paramount tool for performing activities of daily living (ADLs) and stroke can significantly alter the mobilization of this part of the body. In this context, this study aims at investigating hand muscular synergies in chronic stroke patients and evaluating some possible benefits in the robot-aided rehabilitation treatment of the hand in these subjects. Seven chronic stroke patients with mild-to-moderate impairment (FM>30) were involved in this study. They received a 5-week robot-aided rehabilitation treatment with the Gloreha hand exoskeleton, and muscle synergies of both the healthy and injured hand were evaluated at the beginning and at the end of the treatment. The performed analysis showed a very high degree of similarity of the involved synergies between the healthy and the injured limb both before and after the rehabilitation treatment (mean similarity index values: H-BR: 0.88±0.03, H-AR: 0.94±0.03, BR-AR: 0.89±0.05). The increasing similarity is regarded as an effect of the robot-aided rehabilitation treatment and future activities will be performed to increase the population involved in the study.
Highway Tunnel Defect Detection Based on Mobile GPR Scanning
Authors: Zhai Junli , Wang Qiang , Wang Haozheng , Xie Xiongyao , Zhou Mingyi , Yuan Dongyang , Zhang Weikang
Published: March 2022

In order to overcome the difficulty in rapid detection for expressway tunnels, the coherence calculation of dual-frequency radar signal in the time domain is proposed to suppress the interference. A dual-frequency (400 MHz and 900 MHz) GPR and a manipulator are developed. In the horizontal direction, it has a −90°~90° range, a vertical rotation range from 0 to 90°, a length range from 5~9.5 m, and an antenna rotation between −40°~40°. The mobile scanning has been realized in the expressway tunnel, taking the vehicle as the mobile carrier. The research shows that: This equipment realizes the rapid detection of the tunnel without affecting the expressway’s opening. The imaging algorithm recognizes the structural thickness, reinforcement distribution characteristics, and structural diseases. According to the detection carried out in Zhejiang, China, the spacing between reinforcement in the second lining is 4 cm, and the thickness of the structure is about 0.55 m. However, the reinforcement has deformed badly, and the defects are also discerned in the structure. Compared with the traditional handheld radar detection, the equipment dramatically reduces the labor demand, time, and cost and can meet engineering needs. With the proposed method, the detection time is reduced to 12 min/km from 0.5 d/km, and the cost is reduced by more than two times. Furthermore, during the detection, the traffic can be maintained normally.
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics
Authors: Xue Honghu , Hein Benedikt , Bakr Mohamed , Schildbach Georg , Abel Bengt , Rueckert Elmar
Published: March 2022

We propose a deep reinforcement learning approach for solving a mapless navigation problem in warehouse scenarios. In our approach, an automatic guided vehicle is equipped with two LiDAR sensors and one frontal RGB camera and learns to perform a targeted navigation task. The challenges reside in the sparseness of positive samples for learning, multi-modal sensor perception with partial observability, the demand for accurate steering maneuvers together with long training cycles. To address these points, we propose NavACL-Q as an automatic curriculum learning method in combination with a distributed version of the soft actor-critic algorithm. The performance of the learning algorithm is evaluated exhaustively in a different warehouse environment to validate both robustness and generalizability of the learned policy. Results in NVIDIA Isaac Sim demonstrates that our trained agent significantly outperforms the map-based navigation pipeline provided by NVIDIA Isaac Sim with an increased agent-goal distance of 3 m and a wider initial relative agent-goal rotation of approximately 45∘. The ablation studies also suggest that NavACL-Q greatly facilitates the whole learning process with a performance gain of roughly 40% compared to training with random starts and a pre-trained feature extractor manifestly boosts the performance by approximately 60%.
A Photoelectrochemical Study of Hybrid Organic and Donor—Acceptor Dyes as Sensitizers for Dye-Sensitized Solar Cells
Authors: Barichello Jessica , Gullace Sara , Cusimano Alberto , Di Marco Gaetano , Matteocci Fabio , Calogero Giuseppe
Published: March 2022

An investigation on the photoelectrochemical and sensitizing properties of two different hybrid organic dyes, anchored as sensitizers on mesoporous TiO2, in Grätzel solar cells, is presented. Firstly, we studied the absorption properties of the C106 sensitizer, a Ru polypyridine complex, and of the Y123, an organic push and pull dye. In this work, we characterized these two dyes, employing two different electrolytes, with similar experimental condition and device parameters. From the J–V curves and IPCE photo action spectra, we performed an inedited bifacial study based on the comparison of their photovoltaic performances, exploiting several backgrounds (black or white). Among the obtained results from this study, we found the best bifaciality factor of 93% for C106 and the best power conversion efficiency of 12.8% for Y123. These results represent, concerning these two dyes and to the best of our knowledge, some of the highest values in literature.
Performance Assessment of Low-Temperature Solar Collector with Fullerenes C60 Manufactured at Low Cost in an Emerging Country
Authors: Barrera Esteban Eduardo , Medina Abraham , Díaz-Barriga Lucía Graciela , Zacarías Alejandro , Rubio José de Jesús , Gutiérrez Geydy Luz , Cruz José Michael , De Vega Mercedes , García Néstor , Venegas María
Published: March 2022

In this work, the performance of a low-temperature solar collector (LTSC) is evaluated, using carbon nanoparticles in water as working fluid. The nanoparticles used are crystallized fullerenes, with a red parameter of 1.42 nm ± 0.5 nm, with different volume fractions in water. The thickness of the carbon film was approximately 140 to 520 nm. The study is divided into three parts: modeling and simulation of an LTSC, low-cost production and characterization of nanoparticles, and thermal evaluation of the LTSC. For the study, fullerenes were produced by microwave synthesis from a terpenoid resin (Camphor) and the nanoparticles were characterized by scanning electron microscopy (SEM) and High-Resolution Transmission (HRTEM). Tests were carried out with different volumetric flow rates, 0.0111 LT/s, 0.0166 LT/s and 0.0194 L/s, and two volumetric concentrations, 0.035% and 0.063%. The results obtained from the fullerene nanofluid showed an improvement in the thermophysical properties compared to the properties of water. The performance results showed that the efficiency increases up to 47.2% compared to that of water, with a volume fraction of 0.063%, and a flow rate of 0.0194 LT/s.
Shear Behavior of Superposed Perfobond Connectors Considering Lateral Constraints
Authors: Guo Jiangran , Shi Qingxuan , Ma Ge , Li Tengfei
Published: March 2022

Superposed perfobond connectors are a type of connector used in composite structures. When the construction conditions are limited to increase the diameter of the opening, the shear capacity of the connector can be improved by enhancing the confining effect of the concrete dowel. In this study, 12 superposed perfobond connectors were fabricated to investigate the influence of lateral constraints on their shear behavior. The effects of hole area and holes’ number, diameter of the perforating rebar, concrete compressive strength, and the number of transverse reinforcements were investigated via the failure modes and load–slip curves. The results indicate that double-sided shear failure occurs in connectors with perfobond rib thicknesses exceeding 9 mm, and the connectors featuring strong lateral constraints not only exhibited higher bearing capacities but also superior load-holding capacities after peak load. Finally, an equation for the shear capacity of multi-hole perfobond connectors, considering lateral constraints, was proposed according to the double-sided shear theory.