bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Inbred Maize (Zea mays L.) for Tolerance to Low Phosphorus at the Seedling Stage
Authors: Uddin Md. Shalim , Akter Farzana , Azam Md. Golam , Bagum Shamim Ara , Hossain Neelima , Billah Masum , Biswas Priya Lal , Hasibuzzaman Abu Sayeed Md. , Khaldun Abul Bashar Mohammad , Alsuhaibani Amnah Mohammed , Gaber Ahmed , Hossain Akbar
Published: June 2023

In underdeveloped nations where low-input agriculture is practiced, low phosphorus (LP) in the soil reduces the production of maize. In the present study, a total of 550 inbred maize lines were assessed for seedling traits under LP (2.5 × 10−6 mol L−1 of KH2PO4) and NP (2.5 × 10−4 mol L−1 of KH2PO4) hydroponic conditions. The purpose of this study was to quantify the amount of variation present in the measured traits, estimate the genetic involvement of these characteristics, examine the phenotypic correlation coefficients between traits, and to integrate this information to prepare a multi-trait selection index for LP tolerance in maize. A great deal of variability in the maize genotype panel was confirmed by descriptive statistics and analysis of variance (ANOVA). Estimated broad-sense heritability (h2) ranged from 0.7 to 0.91, indicating intermediate to high heritability values for the measured traits. A substantial connection between MSL and other root traits suggested that the direct selection of MSL (maximum shoot length) could be beneficial for the enhancement of other traits. The principal component analysis (PCA) of the first two main component axes explained approximately 81.27% of the variation between lines for the eight maize seedling variables. TDM (total dry matter), SDW (shoot dry weight), RDW (root dry weight), SFW (shoot fresh weight), RFW (root fresh weight), MRL (maximum root length), and MSL measurements accounted for the majority of the first principal component (59.35%). The multi-trait indices were calculated based on PCA using all the measured traits, and 30 genotypes were selected. These selected lines might be considered as the potential source for the improvement of LP tolerance in maize.
Development of an Injection Mold with High Energy Efficiency of Vulcanization for Liquid Silicone Rubber Injection Molding of the Fisheye Optical Lens
Authors: Kuo Chil-Chyuan , Tasi Qing-Zhou , Hunag Song-Hua , Tseng Shih-Feng
Published: June 2023

Liquid silicone rubber (LSR) techniques are experiencing exponential growth, particularly in the field of high technology due to the low-temperature flexibility, superior heat stability, chemical resistance, and aging resistance of LSR components. Enhancing the curing rate of LSR parts in liquid silicone rubber injection molding is an important research topic. In this study, an injection mold with high energy efficiency of vulcanization for the liquid silicone rubber injection molding of a fisheye lens was developed and implemented. The LSR injection mold has a conformal heating channel (CHC) and conformal cooling channel (CCC) simultaneously. The function of CHC is to enhance the curing rate of a fisheye lens in the LSR injection molding to meet the requirements of sustainable manufacturing. The curing rates of a fisheye lens were numerically examined using the Moldex3D molding simulation software. It was found that the curing rate of the fisheye optical lens cured by injection mold with CHC was better than that of the injection mold with a conventional heating channel. The curing efficiency could be increased by about 19.12% when the heating oil temperature of 180 °C was used to cure the fisheye optical lens. The simulation results showed that the equation y = −0.0026x3 + 1.3483x2 − 232.11x + 13,770 was the most suitable equation for predicting the curing time (y) through the heating oil temperature (x). It was found that the trend of the experimental results was consistent with the simulation results. In addition, the equation y = −0.0656x2 + 1.5827x − 0.894 with the correlation coefficient of 0.9974 was the most suitable equation for predicting the volumetric shrinkage of the fisheye optical lens (y) through the heating oil temperature (x). The volume shrinkage of the fisheye optical lens cured by injection mold with CHC was very similar to that of the injection mold with a conventional heating channel. The maximum volume shrinkage of the fisheye optical lens cured at 180 °C was about 8.5%.
Development of MWCNT/Magnetite Flexible Triboelectric Sensors by Magnetic Patterning
Authors: Esteves David Seixas , Pereira Manuel F. C. , Ribeiro Ana , Durães Nelson , Paiva Maria C. , Sequeiros Elsa W.
Published: June 2023

The fabrication of low-electrical-percolation-threshold polymer composites aims to reduce the weight fraction of the conductive nanomaterial necessary to achieve a given level of electrical resistivity of the composite. The present work aimed at preparing composites based on multiwalled carbon nanotubes (MWCNTs) and magnetite particles in a polyurethane (PU) matrix to study the effect on the electrical resistance of electrodes produced under magnetic fields. Composites with 1 wt.% of MWCNT, 1 wt.% of magnetite and combinations of both were prepared and analysed. The hybrid composites combined MWCNTs and magnetite at the weight ratios of 1:1; 1:1/6; 1:1/12; and 1:1/24. The results showed that MWCNTs were responsible for the electrical conductivity of the composites since the composites with 1 wt.% magnetite were non-conductive. Combining magnetite particles with MWCNTs reduces the electrical resistance of the composite. SQUID analysis showed that MWCNTs simultaneously exhibit ferromagnetism and diamagnetism, ferromagnetism being dominant at lower magnetic fields and diamagnetism being dominant at higher fields. Conversely, magnetite particles present a ferromagnetic response much stronger than MWCNTs. Finally, optical microscopy (OM) and X-ray micro computed tomography (micro CT) identified the interaction between particles and their location inside the composite. In conclusion, the combination of magnetite and MWCNTs in a polymer composite allows for the control of the location of these particles using an external magnetic field, decreasing the electrical resistance of the electrodes produced. By adding 1 wt.% of magnetite to 1 wt.% of MWCNT (1:1), the electric resistance of the composites decreased from 9 × 104 to 5 × 103 Ω. This approach significantly improved the reproducibility of the electrode’s fabrication process, enabling the development of a triboelectric sensor using a polyurethane (PU) composite and silicone rubber (SR). Finally, the method’s bearing was demonstrated by developing an automated robotic soft grip with tendon-driven actuation controlled by the triboelectric sensor. The results indicate that magnetic patterning is a versatile and low-cost approach to manufacturing sensors for soft robotics.
Alkenyl Succinic Anhydride: The Question of Covalent Bonding and Chemistry Considerations for Better Sizing—Review
Authors: Ntifafa Yao , Xu Lebo , Bollinger Sara , Ji Yun , Hart Peter W.
Published: June 2023

Alkenyl Succinic Anhydride (ASA) is a sizing agent used in papermaking to increase the water repellency of paper. Almost 60 years after the introduction of the chemical in papermaking, scientists still have differing views on how ASA interacts with cellulose. Several experiments were conducted to bring more clarity to the ASA sizing mechanism, especially on the contentious question of ASA-cellulose covalent bonding or the esterification reaction between ASA and cellulose during papermaking. Herein, research papers and patents, including experiments and results, from the 1960s to 2020 were reviewed. Our investigation revealed that the ester bond formation between ASA and cellulose is insignificant and is not a prerequisite for sizing effectiveness; the main ASA-related material found in sized paper is hydrolyzed ASA or both hydrolyzed ASA and ASA salt. In addition, ASA emulsion stability and ASA emulsion retention are important for sizing efficiency improvement.
Material-Dependent Effect of Common Printing Parameters on Residual Stress and Warpage Deformation in 3D Printing: A Comprehensive Finite Element Analysis Study
Authors: Alzyod Hussein , Ficzere Peter
Published: June 2023

Additive manufacturing (AM), commonly known as 3D printing, has gained significant popularity for its ability to produce intricate parts with high precision. However, the presence of residual stresses and warpage deformation are common issues affecting the quality and functionality of 3D-printed parts. This study conducts a comprehensive finite element analysis (FEA) to investigate the material-dependent impact of key printing parameters on residual stress and warpage deformation in 3D printing. The research focuses on three distinct materials: polyetherimide (PEI), acrylonitrile butadiene styrene (ABS), and polyamide 6 (PA6). Various printing parameters are systematically varied, including printing temperature, printing speed, bed temperature, infill density, layer thickness, and infill pattern. The study employs the Taguchi L27 orthogonal array and employs the analysis of variance (ANOVA) statistical technique to assess the significance of the input parameters. The obtained results reveal that certain parameters exhibit a greater sensitivity to material differences, whereas the layer thickness parameter demonstrates a relatively lower sensitivity. Notably, infill density and printing temperature play a crucial role in reducing residual stress for PA6, while the infill pattern parameter proves to be a significant contributor to minimizing warpage deformation across all three materials. These findings underscore the importance of conducting material-specific analyses to optimize 3D printing parameters and achieve the desired quality outcomes while mitigating residual stress and warpage deformation.
Stability Analysis and Nonlinear Chatter Prediction for Grinding a Slender Cylindrical Part
Authors: Sun Tianyi , Yan Yao
Published: June 2023

A cylindrical plunge grinding process was modeled to investigate nonlinear regenerative chatter vibration. The rotating workpiece was a slender Euler–Bernoulli beam, and the grinding wheel was a rigid body moving towards the workpiece at a very low feed speed. A numerical method was proposed to provide the critical boundaries for chatter-free grinding. It was demonstrated that the intersection set surrounded by these critical boundaries was the chatter-free region for the considered parameters. When these parameters were outside of the chatter-free region, the stable grinding process underwent a supercritical Hopf bifurcation, resulting in the loss of the chatter-free behavior and the emergence of periodic chatter motions. Then, the periodic motions of both the grinding wheel and the workpiece were predicted analytically using the method of multiple scales, showing the effect of the regenerative force on the grinding process. We demonstrated that the analytical prediction was valid since it agreed with the numerical simulation. The results showed that there exist three kinds of nonlinear chatter motion, with different amplitudes and mode frequencies.
Research Progress and Development Trend of Prognostics and Health Management Key Technologies for Equipment Diesel Engine
Authors: Liu Zichang , Zhang Cuixuan , Dong Enzhi , Wang Rongcai , Li Siyu , Han Yueming
Published: June 2023

The diesel engine, as the main power source of equipment, faces practical problems in the maintenance process, such as difficulty in fault location and a lack of preventive maintenance techniques. Currently, breakdown maintenance and cyclical preventive maintenance are the main means of maintenance support after a diesel engine failure, but these methods require professional maintenance personnel to carry out manual fault diagnosis, which is time-consuming. Prognostics and health management (PHM), as a new technology in the field of equipment maintenance support, has significant advantages in improving equipment reliability and safety, enhancing equipment maintenance support capability, and reducing maintenance support costs. In view of this, when introducing PHM into diesel engine maintenance support, the research progress and development trend of the key technologies of PHM for diesel engines are carried out with the objective of achieving precise maintenance and scientific management of diesel engines, and the key technologies demand traction. Firstly, the development history of PHM technology is reviewed, and its basic concept and main functions are introduced. Secondly, the system architecture of PHM for diesel engines is constructed, and its key technologies are summarized. Then, the research progress in the field of PHM for diesel engines is reviewed from four aspects: data acquisition, data processing, fault diagnosis, and health status assessment. Finally, the challenges faced by diesel engine PHM in engineering applications are analyzed, effective solutions to address these challenges are explored, and the future development trend is foreseen.
Numerical Study of the Effects of Roughness Coupled with Inclination on a Turbulent Flow around an Obstacle
Authors: Brahimi Amine , Rebhi Redha , Alliche Mounir
Published: June 2023

In this study, we simulate the cooling of a microprocessor by thermal convection in three different shapes: a square, a trapezoidal, and a triangular shape. The latter is improved by a variety of types of roughness, including square roughness, triangular roughness Type 1, triangular roughness Type 2, and triangular roughness Type 3. The microprocessors are kept at a constant temperature, the air flow is constant, and the geometry is fixed. The physical phenomenon is simulated by the ANSYS software. The numerical results reported in this study cover the ranges of the obstacle’s angle of inclination, 0°≤θ≤45°, (square obstacles, θ=0°, trapezoidal obstacles, 0°<θ<45°, triangular obstacles, θ=45°) and Reynolds number, 2500≤Re≤10,000. The findings relate to streamlines, dynamic pressure (max), mean velocity, temperature field, mean Nusselt number (Nu/Nu0) profiles, local coefficient of friction (Cf/f0), mean coefficient of friction (f/f0) profiles, mean velocity field with roughness, and fluid temperature field with roughness. The aim of the study is to show the interaction between the roughness parameter and the obstacle geometry. In the case of a triangular obstacle, the contact between the cold air and the obstacle is significant downstream of the obstacle, which gives us good cooling, and the Nusselt number has an important value because the agitation of the flow increases convective heat transfer, and the coefficient of friction is low because the air flow is uniform.
The Sustainability Study and Exploration in the Building Commercial Complex System Based on Life Cycle Assessment (LCA)–Emergy–Carbon Emission Analysis
Authors: Cao Jun , Zhu Yangfei , Zhang Junxue , Wang Hechi , Zhu Haohao
Published: June 2023

This paper focuses on the sustainable exploration of building systems, which combines ecological concepts and low-carbon designs for a comprehensive sustainability assessment investigation. The study employed the Life Cycle Assessment (LCA)-Emergy and Life Cycle Assessment (LCA)-Carbon emission methods to discuss a range of topics, including the main contributing factors, sustainability index verification, sensitivity analysis, and potential improvement measures. From an ecological sustainability perspective, the results indicate that the building operation stage plays a critical role, accounting for approximately 45% of the entire emergy in the building commercial complex. The sustainable index (ESI) is 0.354, which is below the standard of 1. Moreover, the building operation stage also significantly contributes to carbon emissions, particularly in the 50th anniversary of operation. Based on these findings, the study recommends two potential strategies to improve the ecological state and low-carbon design which involve the use of renewable energy and carbon sink improvement, respectively.
The Human Being in Eastern Church Father’s and Al-Ghazali’s Philosophical Theology
Authors: Kirabaev Nur Serikovich , Chistyakova Olga Vasilievna
Published: June 2023

The authors analyze two historical types of philosophical culture—the classical Eastern Patristics and Arab–Muslim medieval thought. They are united by the religious doctrine of man, which allows considering the intercultural and inter-theological nature of these traditions. In more particular terms, the article examines the understanding of the human being of the thinkers of Nicaea and post-Nicaea periods of Eastern patristics—Athanasius of Alexandria and Maximus the Confessor—and Abu Hamid al-Ghazali as the most profound representative of the Sufi philosophical–theological system of the Middle Ages. The authors highlight the philosophical, intercultural, and interreligious significance of the mentioned anthropological concepts. The article focuses on the comparability and consistency of the ideas of the Church Fathers and al-Ghazali. Particular attention is paid to Islam’s theoretical image of man as a caliph—a successor—of the Creator on the Earth. Comparative studies reveal the patristic vision of man, containing in himself the fullness of Divinity and humanity. The main points of the dyophysite Christian understanding of the God Incarnate in contrast to the monophysite currents of Apollinarianism are revealed. The depth of the Christological views of Athanasius of Alexandria and Maximus the Confessor is presented. Al-Ghazali’s doctrine of man is substantiated as a conceptual understanding of man’s place in the system of the world created by God, which is seen as a holistic and systematized doctrine of humanity in Muslim philosophy. Conclusions are made about the comparability and the presence of intersections between Eastern Christian, Byzantine, and Muslim types of thought.
The Qurʾān and the Bible: Abrogation (naskh) or Confirmation (taṣdīq)?
Authors: Abdelnour Mohammed Gamal
Published: June 2023

Two Qurʾānic concepts have largely defined how the Qurʾān related to previous revelations. Those two concepts are taḥrīf (alteration) and naskh (abrogation). Appealing to those two concepts, the mainstream understating of the Qurʾān was that it superseded pre-Islamic scriptures and that, after its revelation, such scriptures had limited epistemic value. With this in mind, this article aims to achieve descriptive and prescriptive goals. With the descriptive goal, it problematizes the theories of taḥrīf and naskh, with a view to showing how such concepts influenced Muslim understanding of the Straight Path (al-Ṣirāṭ al-mustaqīm). With the prescriptive goal, it proposes the concept of taṣdīq (confirmation) as an alternative. In doing so, this article demonstrates how, despite the fact that the Qurʾān never shied away from critiquing what it believes to be forms of deviation in the Bible, it never introduced itself as an “abrogator” (nāsikh) to it but rather as a “confirmer” (muṣaddiq) in no less than 12 occurrences in the Qurʾān, but the concept of taṣdīq was largely overshadowed by the overemphasis on taḥrīf and naskh.
How to Survive in a Totalitarian Regime: Education of Salesians in Slovakia in the Period of Socialism (1948–1989)
Authors: Kudláčová Blanka , Rajský Andrej
Published: June 2023

After the Communist coup in February 1948, all areas of society in Czechoslovakia were indoctrinated by the ideology of Marxism–Leninism. The Christian Churches became the biggest internal enemies of the state, since, especially in Slovakia, they had a strong tradition and numerous representations. The government tracked representatives and members of the Church and controlled all their activities. The activities of religious orders were prohibited, which de facto abolished them. The only possibility of their preservation was to continue the life, education and work of individual orders in secret. Our goal was to examine how the Salesian order survived in this situation; specifically, we focused on the forms of formation and illegal study of the Salesians during the totalitarian regime. Research in these activities is rather demanding, since they could not be documented for security reasons. So-called memoir literature, the oral history method, and private archival sources were used in the research. Despite the fact that it seems that religious orders would not survive in this historical situation, the opposite was true: in the period of persecution, the orders were not only able to survive, but also raised a new generation that ensured their continuity and the continuation of their activities.
Sustainable Municipal Waste Management during the COVID-19 Pandemic—A Case Study of Poland
Authors: Urbańska Weronika , Janda Anna , Osial Magdalena , Słowikowski Mateusz
Published: June 2023

With the outbreak of the COVID-19 pandemic, the waste management sector had to face new challenges, e.g., changes in the size and composition of the waste stream, or the presence of potentially infectious waste. This article is based on a case study in Poland. The data analysis showed that the increase in municipal waste mass during the pandemic did not differ from statistics observed in previous years and ranged from 0.3 to 0.5 million tons per year. Lifestyle changes caused a decrease in the amount of waste generated outside households. Social migrations contributed to rapid changes in the mass of waste generated in selected agglomerations by up to 80 kg/capita. In the waste stream, significant amounts of specific groups of waste related to the pandemic (“corona waste”) as well as packaging and food waste were noted. Despite the pandemic, in 2020, Poland recorded an increase in selective waste collection by 6.7 percentage points (pp.) Data on municipal waste management showed an increase in the mass of waste sent for recycling by 0.7 million tons, while the mass of landfilled waste decreased by 0.3 million tons. The observed positive changes in waste management allow the implementation of sustainable development assumptions to a greater extent.
The Recovery of Bioactive Compounds from Olive Pomace Using Green Extraction Processes
Authors: Stramarkou Marina , Missirli Theodora-Venetia , Kyriakopoulou Konstantina , Papadaki Sofia , Angelis-Dimakis Athanasios , Krokida Magdalini
Published: June 2023

In this study, solid olive mill waste (SOMW) was used to obtain antioxidant compounds using solid–liquid extraction. The effect of different extraction methods, namely microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), Soxhlet, and conventional solvent extraction, on the yield, total phenolics, and total antioxidant activity of SOMW extracts was investigated. Untreated and dried SOMW were subjected to extraction with water and methanol. The antioxidant activity of the extracts was evaluated using the DPPH assay, while their total phenolic content was measured using the Folin–Ciocalteu method. For the characterisation of the extracts, HPLC-DAD analysis was performed. The results showed that the extraction yield was significantly influenced (p < 0.05) by the solvent used, the material treatment prior to extraction, the moisture content of SOMW samples, and the extraction time. The optimised parameters were water, as the extraction solvent, and MAE as the extraction technique (extraction temperature of 50 °C and time of 1 h). The evaluation of the antioxidant activity of the extracts indicated that phenolics were the dominant bioactive compounds. The extracts were found to be rich in several hydroxytyrosol derivatives. Therefore, SOMW can be a valuable resource for bioactive compounds using conventional and innovative extraction techniques.
Simulation of Seismoelectric Waves Using Time-Domain Finite-Element Method in 2D PSVTM Mode
Authors: Li Jun , Yin Changchun , Liu Yunhe , Wang Luyuan , Ma Xinpeng
Published: June 2023

The study of the numerical simulation of seismoelectric effects is very helpful for understanding the theory and mechanism of seismoelectric activities. Quasi-static approximation is widely used in the numerical simulation of seismoelectric fields. However, numerical errors occur when the model domain is not within the near-field area of EM waves or the medium is of high salinity. To solve this problem, we propose a time-domain finite-element algorithm (FETD) based on the full-wave electromagnetic (EM) equation to simulate seismoelectric waves in 2D PSVTM mode. By decomposing the electrokinetic coupling equations into two independent ones, we can solve the seismoelectric waves separately. In our implementation, we focus our attention on the solution of EM waves based on vector–scalar potentials, while using the open-source code SPECFEM2D to explicitly solve Biot’s equations and obtain the relative fluid–solid displacement, which is taken as the source for the complete Maxwell’s equations. In the solution of EM wave fields, we use an unconditionally stable implicit method for time discretization. Computation efficiency can be improved by combining explicit and implicit recursions. After conducting the mathematical formulation, we first validate our method by comparing its results with the analytic solutions for a half-space and a two-layer model, as well as with a quasi-static approximation method. Moreover, we run numerical simulations and wavefield analyses on an elliptical hydrocarbon reservoir, and reveal that the interface responses are promising for the identification of underground interfaces and hydrocarbon reservoir exploration.
Estimation of the Seawater Lidar Ratio by MODIS: Spatial–Temporal Characteristics and Ecological Significance
Authors: Zhu Xiaoan , Zhao Hongkai , Hu Enjie , Gao Yubin , Zhou Yudi , Liu Dong
Published: June 2023

The lidar ratio of seawater is an essential quantity related to both lidar retrieval and water constituent. However, few studies discuss its spatial–temporal characteristics and ecological significance, which limits its applications in lidar remote sensing and marine science. This paper investigates the spatial–temporal characteristics and ecological significance of the lidar ratio of seawater using satellite passive remote sensing, which is validated by in situ measurements. Spatially, nearshore lidar ratio values are higher than offshore, mainly owing to the high concentration of colored dissolved organic matter in nearshore water. Temporally, the lidar ratio in each hemisphere exhibits lower values in summer than in winter due to the annual boom–bust cycle of phytoplankton. Furthermore, the variability patterns of the lidar ratio are nearly consistent with those of the chlorophyll-to-carbon ratio, implying the high ecological significance of phytoplankton physiology. These findings will provide the foundation for the application of lidar ratio in marine science and lidar remote sensing.
Dual-View Hyperspectral Anomaly Detection via Spatial Consistency and Spectral Unmixing
Authors: Zhang Jingyan , Zhang Xiangrong , Jiao Licheng
Published: June 2023

Anomaly detection is a crucial task for hyperspectral image processing. Most popular methods detect anomalies at the pixel level, while a few algorithms for anomaly detection only utilize subpixel level unmixing technology to extract features without fundamentally analyzing the anomalies. To better detect and separate the anomalies from the background, this paper proposes a dual-view hyperspectral anomaly detection method by taking account of the anomaly analysis at both levels mentioned. At the pixel level, the spectral angular distance is adopted to calculate the similarities between the central pixel and its neighbors in order to further mine the spatial consistency for anomaly detection. On the other hand, from the aspect of the subpixel level analysis, it is considered that the difference between the anomaly and the background usually arises from dissimilar endmembers, where the unmixing will be fully implemented. Finally, the detection results of both views are fused to obtain the anomalies. Overall, the proposed algorithm not only interprets and analyzes the anomalies from dual levels, but also fully employs the unmixing for anomaly detection. Additionally, the performance of multiple data sets also confirmed the effectiveness of the proposed algorithm.
Thermokarst Lake Susceptibility Assessment Induced by Permafrost Degradation in the Qinghai–Tibet Plateau Using Machine Learning Methods
Authors: Wang Rui , Guo Lanlan , Yang Yuting , Zheng Hao , Liu Lianyou , Jia Hong , Diao Baijian , Liu Jifu
Published: June 2023

The rapidly warming climate on the Qinghai–Tibet Plateau (QTP) leads to permafrost degradation, and the thawing of ice-rich permafrost induces land subsidence to facilitate the development of thermokarst lakes. Thermokarst lakes exacerbate the instability of permafrost, which significantly alters regional geomorphology and hydrology, affecting biogeochemical cycles. However, the spatial distribution and future changes in thermokarst lakes have rarely been assessed at large scales. In this study, we combined various conditioning factors and an inventory of thermokarst lakes to assess the spatial distribution of susceptibility maps using machine-learning algorithms. The results showed that the extremely randomized trees (EXT) performed the best in the susceptibility modeling process, followed by random forest (RF) and logistic regression (LR). According to the assessment based on EXT, the high- and very high-susceptibility area of the present (2000–2016) susceptibility map was 196,222 km2, covering 19.67% of the permafrost region of the QTP. In the future (the 2070s), the area of the susceptibility map was predicted to shrink significantly under various representative concentration pathway scenarios (RCPs). The susceptibility map area would be reduced to 37.06% of the present area in RCP 8.5. This paper also performed correlation and importance analysis on the conditioning factors and thermokarst lakes, which indicated that thermokarst lakes tended to form in areas with flat topography and high soil moisture. The uncertainty of the susceptibility map was further assessed by the coefficient of variation (CV). Our results demonstrate a way to study the spatial distribution of thermokarst lakes at the QTP scale and provide a scientific basis for understanding thermokarst processes in response to climate change.
A Three-Dimensional Conceptual Model for Estimating the Above-Ground Biomass of Winter Wheat Using Digital and Multispectral Unmanned Aerial Vehicle Images at Various Growth Stages
Authors: Zhu Yongji , Liu Jikai , Tao Xinyu , Su Xiangxiang , Li Wenyang , Zha Hainie , Wu Wenge , Li Xinwei
Published: June 2023

The timely and accurate estimation of above-ground biomass (AGB) is crucial for indicating crop growth status, assisting management decisions, and predicting grain yield. Unmanned aerial vehicle (UAV) remote sensing technology is a promising approach for monitoring crop biomass. However, the determination of winter wheat AGB based on canopy reflectance is affected by spectral saturation effects. Thus, constructing a generic model for accurately estimating winter wheat AGB using UAV data is significant. In this study, a three-dimensional conceptual model (3DCM) for estimating winter wheat AGB was constructed using plant height (PH) and fractional vegetation cover (FVC). Compared with both the traditional vegetation index model and the traditional multi-feature combination model, the 3DCM yielded the best accuracy for the jointing stage (based on RGB data: coefficient of determination (R2) = 0.82, normalized root mean square error (nRMSE) = 0.2; based on multispectral (MS) data: R2 = 0.84, nRMSE = 0.16), but the accuracy decreased significantly when the spike organ appeared. Therefore, the spike number (SN) was added to create a new three-dimensional conceptual model (n3DCM). Under different growth stages and UAV platforms, the n3DCM (RGB: R2 = 0.73–0.85, nRMSE = 0.17–0.23; MS: R2 = 0.77–0.84, nRMSE = 0.17–0.23) remarkably outperformed the traditional multi-feature combination model (RGB: R2 = 0.67–0.88, nRMSE = 0.15–0.25; MS: R2 = 0.60–0.77, nRMSE = 0.19–0.26) for the estimation accuracy of the AGB. This study suggests that the n3DCM has great potential in resolving spectral errors and monitoring growth parameters, which could be extended to other crops and regions for AGB estimation and field-based high-throughput phenotyping.
Seeing the Forest for the Trees: Mapping Cover and Counting Trees from Aerial Images of a Mangrove Forest Using Artificial Intelligence
Authors: Schürholz Daniel , Castellanos-Galindo Gustavo , Casella Elisa , Mejía-Rentería Juan , Chennu Arjun
Published: June 2023

Mangrove forests provide valuable ecosystem services to coastal communities across tropical and subtropical regions. Current anthropogenic stressors threaten these ecosystems and urge researchers to create improved monitoring methods for better environmental management. Recent efforts that have focused on automatically quantifying the above-ground biomass using image analysis have found some success on high resolution imagery of mangrove forests that have sparse vegetation. In this study, we focus on stands of mangrove forests with dense vegetation consisting of the endemic Pelliciera rhizophorae and the more widespread Rhizophora mangle mangrove species located in the remote Utría National Park in the Colombian Pacific coast. Our developed workflow used consumer-grade Unoccupied Aerial System (UAS) imagery of the mangrove forests, from which large orthophoto mosaics and digital surface models are built. We apply convolutional neural networks (CNNs) for instance segmentation to accurately delineate (33% instance average precision) individual tree canopies for the Pelliciera rhizophorae species. We also apply CNNs for semantic segmentation to accurately identify (97% precision and 87% recall) the area coverage of the Rhizophora mangle mangrove tree species as well as the area coverage of surrounding mud and water land-cover classes. We provide a novel algorithm for merging predicted instance segmentation tiles of trees to recover tree shapes and sizes in overlapping border regions of tiles. Using the automatically segmented ground areas we interpolate their height from the digital surface model to generate a digital elevation model, significantly reducing the effort for ground pixel selection. Finally, we calculate a canopy height model from the digital surface and elevation models and combine it with the inventory of Pelliciera rhizophorae trees to derive the height of each individual mangrove tree. The resulting inventory of a mangrove forest, with individual P. rhizophorae tree height information, as well as crown shape and size descriptions, enables the use of allometric equations to calculate important monitoring metrics, such as above-ground biomass and carbon stocks.
Numerical Solution of the Atmospheric Perturbations Triggered by Persistent Lithospheric Vibrations
Authors: Lin Kai , Mao Zhiqiang , Xu Ziniu , Dong Lei , Zhang Xuemin , Gao Yongxin , Chen Chieh-Hung
Published: June 2023

Recently, atmospheric perturbations residing over around epicenters of forthcoming earthquakes were remotely sensed by the multiple instruments of the MVP-LAI (Monitoring of Vibrations and Perturbations in Lithosphere, Atmosphere and Ionosphere) system. In this study, we found another way and proposed a theory for the evolution of the perturbations in the atmosphere from the aspect of numerical simulation. We started from the fundamental hydromechanics equations for the perturbations based on the atmospheric dynamics in the cylindrical symmetric coordinate to solve their analytical solution. The solution shows that a persistent vibration at the bottom of the cylindrical symmetric coordinate tends to decay exponentially with along altitude. In other words, a persistent ground vibration in a wide area can rapidly evolve into small-scale perturbations in the atmosphere. The preliminary theoretical model in this study shows the kernel concept for the coupling of geospheres.
Quantifying Multi-Scale Performance of Geometric Features for Efficient Extraction of Insulators from Point Clouds
Authors: Tang Jie , Tan Junxiang , Du Yongyong , Zhao Haojie , Li Shaoda , Yang Ronghao , Zhang Tao , Li Qitao
Published: June 2023

Insulator extraction from images or 3D point clouds is an important part of automatic power inspection by unmanned airborne vehicles (UAVs), which is vital for improving the efficiency of inspection and the stability of power grids. However, for point cloud data, many challenges, such as the diversity of pylon shape and insulator type, complex topology, and similarity of structures, were not tackled with the study of power element extraction. To efficiently identify the small insulators from complex power transmission corridor (PTC) scenarios, this paper proposes a robust extraction method by fusing multi-scale neighborhood and multi-feature entropy weighting. The pylon head is segmented according to the aspect ratio of horizontal slices following the locating of the pylons based on the height difference and continuous vertical distribution firstly. Aiming to quantify the different contributions of features in decision-making and better segment insulators, a feature evaluation system combined with information entropy, eigen entropy-based optimal neighborhood selection, and designed multi-scale features is constructed to identify suspension insulators and tension insulators. In the optimization step, a region erosion and growing method is proposed to segment complete insulator strings by enlarging the perspectives to obtain more object representations. The extraction results of 82 pylons with 654 insulators demonstrate that the proposed method is suitable for different pylon shapes and sizes. The identification accuracy of the whole line achieves 98.23% and the average F1 score is 90.98%. The proposed method can provide technical support for automatic UAV inspection and pylon reconstruction.
Detection and Identification for Void of Concrete Structure by Air-Coupled Impact-Echo Method
Authors: Ju Jinghui , Tian Xiushu , Zhao Weigang , Yang Yong
Published: June 2023

In the field of non-destructive testing (NDT) for concrete structures, the traditional air-coupled impact-echo technology often has the problems of complex operation and low efficiency. In order to solve these problems, this study uses Comsol software to establish a finite element model (FEM) of the concrete structure with different void sizes and obtains the variation rule of peak frequency. The recognition property of the concrete void based on peak frequency is proposed, which is explained and validated by relevant theory and experiments. The results show that compared with the depth of the void, the influence of the void width on the peak frequency increases significantly. When the void width is greater than 0.3 m, the peak frequency of the sound wave decreases with the increase in the width, and the change is obvious. This paper describes the applicability of concrete void depth less than 0.4 m for the air-coupled method and, when the concrete void depth is less than 0.4 m, the peak frequency can be used to effectively identify void widths greater than 0.3 m. The research results will be beneficial to void detection of concrete structures such as tunnel lining and pavements.
Deep Learning-Aided Inertial/Visual/LiDAR Integration for GNSS-Challenging Environments
Authors: Abdelaziz Nader , El-Rabbany Ahmed
Published: June 2023

This research develops an integrated navigation system, which fuses the measurements of the inertial measurement unit (IMU), LiDAR, and monocular camera using an extended Kalman filter (EKF) to provide accurate positioning during prolonged GNSS signal outages. The system features the use of an integrated INS/monocular visual simultaneous localization and mapping (SLAM) navigation system that takes advantage of LiDAR depth measurements to correct the scale ambiguity that results from monocular visual odometry. The proposed system was tested using two datasets, namely, the KITTI and the Leddar PixSet, which cover a wide range of driving environments. The system yielded an average reduction in the root-mean-square error (RMSE) of about 80% and 92% in the horizontal and upward directions, respectively. The proposed system was compared with an INS/monocular visual SLAM/LiDAR SLAM integration and to some state-of-the-art SLAM algorithms.
Coelenterazine Indicators for the Specific Imaging of Human and Bovine Serum Albumins
Authors: Kim Sung-Bae , Kamiya Genta , Furuta Tadaomi , Kitada Nobuo , Maki Shojiro A.
Published: June 2023

Albumin assays in serum are important for the prognostic assessment of many life-threatening diseases, such as heart failure, liver disease, malnutrition, inflammatory bowel disease, infections, and kidney disease. In this study, synthetic coelenterazine (CTZ) indicators are developed to quantitatively illuminate human and bovine serum albumins (HSA and BSA) with high specificity. Their functional groups were chemically modified to specifically emit luminescence with HSA and BSA. The CTZ indicators were characterized by assaying the most abundant serum proteins and found that the CTZ indicators S6 and S6h were highly specific to HSA and BSA, respectively. Their colors were dramatically converted from blue, peaked at 480 nm, to yellowish green, peaked at 535 nm, according to the HSA–BSA mixing ratios, wherein the origins and mixing levels of the albumins can be easily determined by their colors and peak positions. The kinetic properties of HSA and BSA were investigated in detail, confirming that the serum albumins catalyze the CTZ indicators, which act as pseudo-luciferases. The catalytic reactions were efficiently inhibited by specific inhibitors, blocking the drug-binding sites I and II of HSA and BSA. Finally, the utility of the CTZ indicators was demonstrated through a quantitative imaging of the real fetal bovine serum (FBS). This study is the first example to show that the CTZ indicators specify HSA and BSA with different colors. This study contributes to the expansion of the toolbox of optical indicators, which efficiently assays serum proteins in physiological samples. Considering that these CTZ indicators immediately report quantitative optical signals with high specificity, they provide solutions to conventional technical hurdles on point-of-care assays of serum albumins.
System Based on an Inertial Measurement Unit for Accurate Flight Time Determination in Vertical Jumps
Authors: Moreno-Pérez Juan A. , Ruiz-García Isidoro , Navarro-Marchal Ismael , López-Ruiz Nuria , Gómez-López Pablo J. , Palma Alberto J. , Carvajal Miguel A.
Published: June 2023

The world of elite sports has always been characterized by intense competition, where victories are often determined by minimal differences. This means that every little detail in the preparation of top-level athletes is crucial to their performance at the highest level. One of the most significant aspects to monitor is the jumping capacity, as it enables the measurement of performance, progression, and helps prevent injuries. Herein, we present the development of a system capable of measuring the flight time and height reached by the user, reporting the results through a smartphone using an Android ad-hoc application, which handles all the data processing. The system consists of an affordable and portable circuit based on an accelerometer. It communicates with the smartphone via UART using a Bluetooth module, and its battery provides approximately 9 h of autonomy, making it suitable for outdoor operations. To evaluate the system’s precision, we conducted performance tests (counter-movement jumps) with seven subjects. The results confirmed the system’s potential for monitoring high-level sports training sessions, as the average deviation obtained was only 2.1% (~0.01 s) in the analysis of flight time and 4.6% (~0.01 m) in jump height.
Augmented Reality-Assisted Deep Reinforcement Learning-Based Model towards Industrial Training and Maintenance for NanoDrop Spectrophotometer
Authors: Alatawi Hibah , Albalawi Nouf , Shahata Ghadah , Aljohani Khulud , Alhakamy A’aeshah , Tuceryan Mihran
Published: June 2023

The use of augmented reality (AR) technology is growing in the maintenance industry because it can improve efficiency and reduce costs by providing real-time guidance and instruction to workers during repairs and maintenance tasks. AR can also assist with equipment training and visualization, allowing users to explore the equipment’s internal structure and size. The adoption of AR in maintenance is expected to increase as hardware options expand and development costs decrease. To implement AR for job aids in mobile applications, 3D spatial information and equipment details must be addressed, and calibrated using image-based or object-based tracking, which is essential for integrating 3D models with physical components. The present paper suggests a system using AR-assisted deep reinforcement learning (RL)-based model for NanoDrop Spectrophotometer training and maintenance purposes that can be used for rapid repair procedures in the Industry 4.0 (I4.0) setting. The system uses a camera to detect the target asset via feature matching, tracking techniques, and 3D modeling. Once the detection is completed, AR technologies generate clear and easily understandable instructions for the maintenance operator’s device. According to the research findings, the model’s target technique resulted in a mean reward of 1.000 and a standard deviation of 0.000. This means that all the rewards that were obtained in the given task or environment were exactly the same. The fact that the reward standard deviation is 0.000 shows that there is no variability in the outcomes.
Advancements in Neighboring-Based Energy-Efficient Routing Protocol (NBEER) for Underwater Wireless Sensor Networks
Authors: Shah Sayyed Mudassar , Sun Zhaoyun , Zaman Khalid , Hussain Altaf , Ullah Inam , Ghadi Yazeed Yasin , Khan Muhammad Abbas , Nasimov Rashid
Published: June 2023

Underwater wireless sensor networks (UWSNs) have gained prominence in wireless sensor technology, featuring resource-limited sensor nodes deployed in challenging underwater environments. To address challenges like power consumption, network lifetime, node deployment, topology, and propagation delays, cooperative transmission protocols like co-operative (Co-UWSN) and co-operative energy-efficient routing (CEER) have been proposed. These protocols utilize broadcast capabilities and neighbor head node (NHN) selection for cooperative routing. This research introduces NBEER, a novel neighbor-based energy-efficient routing protocol tailored for UWSNs. NBEER aims to surpass the limitations of Co-UWSN and CEER by optimizing NHNS and cooperative mechanisms to achieve load balancing and enhance network performance. Through comprehensive MATLAB simulations, we evaluated NBEER against Co-UWSN and CEER, demonstrating its superior performance across various metrics. NBEER significantly maximizes end-to-end delay, reduces energy consumption, improves packet delivery ratio, extends network lifetime, and enhances total received packets analysis compared to the existing protocols.
VUV to IR Emission Spectroscopy and Interferometry Diagnostics for the European Shock Tube for High-Enthalpy Research
Authors: Grosso Ferreira Ricardo , Carvalho Bernardo Brotas , Alves Luís Lemos , Gonçalves Bruno , Villace Victor Fernandez , Marraffa Lionel , Lino da Silva Mário
Published: June 2023

The European Shock Tube for High-Enthalpy Research is a new state-of-the-art facility, tailored for the reproduction of spacecraft planetary entries in support of future European exploration missions, developed by an international consortium led by Instituto de Plasmas e Fusão Nuclear and funded by the European Space Agency. Deployed state-of-the-art diagnostics include vacuum-ultraviolet to ultraviolet, visible, and mid-infrared optical spectroscopy setups, and a microwave interferometry setup. This work examines the specifications and requirements for high-speed flow measurements, and discusses the design choices for the main diagnostics. The spectroscopy setup covers a spectral window between 120 and 5000 nm, and the microwave interferometer can measure electron densities up to 1.5 × 1020 electrons/m3. The main design drivers and technological choices derived from the requirements are discussed in detail herein.