bluuebunny/crossref_metadata_2025 huggingface dataset:
Lanthanum Supplementation Alleviates Tomato Root Growth Suppression under Low Light Stress
Authors: Iguchi Syo , Tokunaga Tatsuya , Kamon Eri , Takenaka Yuto , Koshimizu Shizuka , Watanabe Masao , Ishimizu Takeshi
Published: July 2023

Supplementation with rare earth elements (REEs) such as lanthanum and cerium has been shown to promote plant elongation and/or increase crop yields. On the other hand, there are reports that REE supplementation of plants has no such effect. The appropriate modes for REE utilization and the underlying mechanism are not fully understood. In this study, we investigated how REE supplementation of plants under low light stress affects plant growth and gene expression. Under low light stress conditions, tomato root elongation was observed to be reduced by about half. This suppression of root elongation was found to be considerably alleviated by 20 mM lanthanum ion supplementation. This effect was plant-species-dependent and nutrient-condition-dependent. Under low light stress, the expression of the genes for phytochrome-interacting factor, which induces auxin synthesis, and several auxin-synthesis-related proteins were markedly upregulated by lanthanum ion supplementation. Thus, we speculate that REE supplementation of plants results in auxin-induced cell elongation and alleviates growth suppression under stress conditions.
Polypropylene-Based Polymer Locking Ligation System Manufacturing by the Ultrasonic Micromolding Process
Authors: Elías-Grajeda Alex , Vázquez-Lepe Elisa , Siller Héctor R. , Perales-Martínez Imperio Anel , Reséndiz-Hernández Emiliano , Ramírez-Herrera Claudia Angélica , Olvera-Trejo Daniel , Martínez-Romero Oscar
Published: July 2023

In recent years, there has been a growing demand for biocompatible medical devices on the microscale. However, the manufacturing of certain microfeatures has posed a significant challenge. To address this limitation, a new process called ultrasonic injection molding or ultrasonic molding (USM) has emerged as a potential solution. In this study, we focused on the production of a specific microdevice known as Hem-O-Lok, which is designed for ligation and tissue repair during laparoscopic surgery. Utilizing USM technology, we successfully manufactured the microdevice using a nonabsorbable biopolymer that offers the necessary flexibility for easy handling and use. To ensure high-quality microdevices, we extensively investigated various processing parameters such as vibration amplitude, temperature, and injection velocity. Through careful experimentation, we determined that the microdevice achieved optimal quality when manufactured under conditions of maximum vibrational amplitude and temperatures of 50 and 60 °C. This conclusion was supported by measurements of critical microfeatures. Additionally, our materials characterization efforts revealed the presence of a carbonyl (C=O) group resulting from the thermo-oxidation of air in the plasticizing chamber. This finding contributes to the enhanced thermal stability of the microdevices within a temperature range of 429–437 °C.
Phase Change Microcapsule Composite Material with Intelligent Thermoregulation Function for Infrared Camouflage
Authors: Su Ying , Zhao Xiaoming , Han Yue
Published: July 2023

The infrared camouflage textile materials with soft and wear-resistant properties can effectively reduce the possibility of soldiers and military equipment being exposed to infrared detectors. In this paper, the infrared camouflage textile composites with intelligent temperature adjustment ability were prepared by different methods, using phase change microcapsule as the main raw material and high polymer polyurethane as the matrix, combining the two factors of temperature control and emissivity reduction. It was tested by differential scanning calorimeter, temperature change tester, infrared emissivity tester, and infrared imager. The results show that the temperature regulation effect of textile materials finished by coating method is better than dip rolling method, the temperature regulation ability and presentation effect are the best when the microcapsule content is 27%. When the bottom layer of infrared camouflage textile composite is 27% phase change microcapsule and the surface layer is 20% copper powder, its infrared emissivity in the band of 2–22 μm is 0.656, and the rate of heating and cooling is obviously slowed down. It has excellent heat storage and temperature regulation function, which can reduce the skin surface temperature by more than 6 °C and effectively reduce the infrared radiation. This study can provide reference for laboratory preparation and industrial production of infrared camouflage composite material. The infrared camouflage textile composite prepared are expected to be used in the field of military textiles.
Feasibility of 3D-Printed Locking Compression Plates with Polyether Ether Ketone (PEEK) in Tibial Comminuted Diaphyseal Fractures
Authors: Chung Hyung-Jin , Lee Ho-Beom , Park Kwang-Min , Jung Tae-Gon , Kim Sang-Bum , Lee Byoung-Gu , Kim Wan-Chin , Lee Jeong-Kil
Published: July 2023

The applicability of a polyether ether ketone locking compression plate (PEEK LCP) fabricated using FDM (fused deposition modeling)-based 3D printing to treat actual patients was studied. Three different tests—bending, axial compression, and axial torsion—were conducted on tibial non-osteoporotic comminuted diaphyseal fracture samples fixed with the commercial titanium alloy LCP and 3D-printed PEEK LCP. Comparing the outcomes of these tests revealed that the commercial titanium alloy LCP underwent plastic deformation in the bending and axial torsion tests, though the LCP did not fail even when an external force greater than the maximum allowable load of the tibia fixture of the LCP was applied. Elastic deformation occurred in the 3D-printed PEEK LCP in the bending and axial torsion tests. However, deformation occurred even under a small external force, and its stiffness was 10% compared to commercial titanium alloy LCP. Thus, 3D-printed PEEK LCP can be applied to the fracture conditions in non-weight-bearing regions. The experimental results reveal detailed insights into the treatment of actual patients by considering the stiffness and high toughness of 3D-printed PEEK LCP.
The Mechanical Properties Relationship of Radiation-Cured Nanocomposites Based on Acrylates and Cationic Polymerized Epoxies and the Composition of Silane-Modified Tungsten Disulfide Nanoparticles
Authors: Gercci Yarden , Yosef-Tal Natali , Bendikov Tatyana , Dodiuk Hanna , Kenig Samuel , Tenne Reshef
Published: July 2023

The effect of semiconducting tungsten disulfide (WS2) nanoparticles (NPs), functionalized by either methacryloxy, glycidyl, vinyl, or amino silanes, has been studied in photocuring of acrylate and epoxy resins (the latter photocured according to a cationic mechanism). The curing time, degree of curing (DC), thermal effects, and mechanical properties of the radiation-cured resins were investigated. X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) analyses confirmed that a silane coating was formed (1–4 nm) on the NPs’ surface having a thickness of 1–4 nm. Fourier transition infrared (FTIR) was used to determine the DC of the nanocomposite resin. The curing time of the epoxy resin, at 345–385 nm wavelength, was 10 to 20 s, while for acrylate, the curing time was 7.5 min, reaching 92% DC in epoxy and 84% in acrylate. The glass transition temperature (Tg) of the photocured acrylates in the presence of WS2 NPs increased. In contrast to the acrylate, the epoxy displayed no significant variations of the Tg. It was found that the silane surface treatments enhanced the DC. Significant increases in impact resistance and enhancement in shear adhesion strength were observed when the NPs were treated with vinyl silane. A previous study has shown that the addition of WS2 NPs at a concentration of 0.5 wt.% is the optimal loading for improving the resin’s mechanical properties. This study supports these earlier findings not only for the unmodified NPs but also for those functionalized with silane moieties. This study opens new vistas for the photocuring of resins and polymers in general when incorporating WS2 NPs.
Experimental and Simulation Analysis of Siloxane Mixtures Used in Organic Rankine Cycle with Thermal Stability Limits
Authors: Wang Wenhuan , Tian Lei , Shi Lin , Dai Xiaoye
Published: July 2023

The thermal stability of siloxanes has significant influence on the selection of working fluid and the performance of organic Rankine cycle systems. In this study, a thermal decomposition experimental apparatus was designed to measure the thermal stability of hexamethyldisiloxane (MM), octamethyltrisiloxane (MDM), and their mixtures; a reaction kinetics model based on first order reaction theory was built to analyze the thermal stability of siloxane mixture fluids in a long operation period. And the influence of the mass fraction and evaporation temperature on the net power and thermal efficiency of the system was analyzed under the constraints of thermal stability. The results showed that the thermal stability of MDM was worse than that of MM, and the mixture of MM and MDM had significant inhibition effects on the de-composition of pure fluids. The activation energy of decomposition reaction was 50.50 kJ/mol, and the pre-exponential factor was 5.80 × 10−3 s−1. With the evaporation temperature limit, the net power and thermal efficiency were both lower than those without the evaporation temperature limit. Comparing the obvious decrease in the thermal efficiency, the change of the net power was limited. Siloxane mixtures emerged as a superior choice for ORC systems in the conditions of this paper. MM/MDM (0.6/0.4) improved the net power and heat efficiency of the system by 8.1% and 1.7%, respectively, comparing with that of the pure working fluids.
Study on Production Characteristics during N2 Flooding in Low Permeability Reservoirs: Effect of Matrix Permeability and Fracture
Authors: Wang Ruofan , Arkin Kurbanjan , Liang Yanyan , Li Haibo , Zheng Lei , Li Haifeng , Li Binfei
Published: July 2023

The N2 flooding enhanced oil recovery process is an important technical means for the development of low permeability reservoirs due to its good energy enhancement effect and good injectivity. Low permeability reservoirs have a large permeability span and strong heterogeneity, which will have a significant impact on gas injection development. In order to explore the influence of matrix permeability and fractures on the production characteristics of N2 flooding, this study conducted a series of displacement experiments with full-scale matrix permeability (0.1–50 mD) and different fracture conditions. The research results indicate that, in non-fracture low permeability cores, the pressure difference decreased with the matrix permeability increase, and the volume of N2 injection required to achieve the highest injection pressure decreased. In addition, the increase in matrix permeability accelerates the gas breakthrough and gas channeling, but is beneficial for improving no-gas oil recovery and ultimate oil recovery due to the decrease in crude oil flow resistance. The impact of different matrix permeability ranges on production characteristics varies. When the matrix permeability is less than 2 mD, the characteristics of oil and gas production are significantly affected by changes in matrix permeability. When the matrix permeability is greater than 2 mD, the impact of changes in matrix permeability on development effectiveness is weakened. The existence of fracture causes a high permeability channel to appear in the low permeability matrix, exacerbating the gas breakthrough and channeling, and significantly reducing the utilization of matrix crude oil (about a 50% decrease in oil recovery). The increase in matrix permeability is beneficial for weakening the heterogeneity between fractures and the matrix, alleviating the gas channeling, thereby increasing the swept volume in the low permeability matrix and improving oil recovery.
Effect of Motor Installation Heights on the Performance of an Isolated Centrifugal Fan
Authors: Li Zhehong , Luo Ping , Zhu Meijun , Chen Ziyun , Liu Yang , Li Guohui
Published: July 2023

For this paper, an investigation into the differences in the aerodynamic performance of fans caused by installation heights was conducted using computational fluid simulation. The predictions presented in this paper are in great agreement with the experimental data. The results show that a vortex is observable on the side of the motor, as it first accelerates and then obviously decelerates while passing through the impeller inlet to the front of the blade passage. Higher motor installation heights result in a decrease in static pressure and static pressure efficiency at higher flow rates. At the maximum flow rate, the static pressure efficiency of the fan at a lower installation height increased by 10% with the original fan, and the static pressure coefficient increased by 23% as well. The results reported in this paper demonstrate that installation heights greatly affect the aerodynamic performance of an isolated centrifugal fan under higher flow rate conditions and that the range of fan operation is extended at reasonable heights.
Numerical Simulation and Experimental Study on Sediment Wear of Fixed Guide Vanes of Hydraulic Turbines in Muddy River Based on Discrete Phase Model
Authors: Jia Lu , Zeng Yongzhong , Liu Xiaobing , Huang Wanting
Published: July 2023

The erosion of the fixed guide vane of a hydraulic turbine by sandy water is influenced not only by flow velocity and mud concentration but also by the direction and speed of the sandy water over the surface. This study aims to investigate the erosive effect of sediment-laden water on a specific type of hydraulic turbine’s fixed guide vane, validate the efficacy of the discrete phase model (DPM) in simulating wear on the fixed guide vane, and identify the critical areas of wear on its surface. To achieve these objectives, the wear model and DPM model are employed to conduct numerical simulations on the fixed guide vane. Additionally, samples of sand are collected from the power station site, and laboratory tests are conducted on the hydraulic turbine’s flow passage components using actual sediment concentration and sand-to-water ratio to determine the sediment wear conditions. The numerical simulation results of the guide vane’s surface wear rate are compared with the experimental data to verify the wear condition of the fixed guide vane under its rated working condition. These findings serve as a reference for the later-stage design of erosion-resistant solid guide vanes for hydraulic turbines.
Mini-Review of Best Practices for Greenhouse Gas Reduction in Singapore’s Semiconductor Industry
Authors: Zhu Shikai , Hu Haoqian , Yang Haoyi , Qu Yunzhuo , Li Yuanzhe
Published: July 2023

Climate change is an urgent global concern driven by human activities and the subsequent rise in greenhouse gas (GHG) emissions. The semiconductor industry has emerged as a significant contributor to GHG emissions, yet there is a lack of clear guidelines for effective reduction methods specifically tailored to domestic and international semiconductor manufacturing. This mini-review addresses this gap by proposing implementation principles for optimal control technology aimed at mitigating GHG emissions in the semiconductor industry. Drawing upon guidance from the Intergovernmental Panel on Climate Change (IPCC) and established reduction methods, our focus is on the deployment of efficient exhaust gas destruction equipment for removing GHGs from critical processes such as Etching, ThinFilm (including chemical/physical vapor deposition), and Diffusion. By examining and consolidating current best practices, this review provides a foundation for developing comprehensive guidelines and standards that support the semiconductor industry’s transition to more sustainable operations. Considering the vast body of literature in this field, we highlight the significance of this study as it contributes to the ongoing research efforts in reducing GHG emissions. The objective of this study is to identify research gaps and motivate further investigations, while also providing practical recommendations for reducing GHG emissions in the semiconductor industry.
A Theocentric Environmental Ethic
Authors: DeWeese Garrett J.
Published: July 2023

An influential view among environmentalists and ecologists is that religion, in general, and Christianity, in particular, not only have nothing to offer to environmental ethics but are actually hostile to the environment. I argue that a biblically informed theocentric environmental ethic of stewardship offers rich resources for duty-based environmental ethics in general and, in particular, for establishing grounds for restoration, conservation, and preservation of the environment.
An Improved Doppler-Aided Smoothing Code Algorithm for BeiDou-2/BeiDou-3 un-Geostationary Earth Orbit Satellites in Consideration of Satellite Code Bias
Authors: Gao Xiao , Ma Zongfang , Jia Luxiao , Pan Lin
Published: July 2023

The extensive use of carrier-aided smoothing code (CSC) filters has led to a reduction in the noise level of raw code measurements in GNSS positioning and navigation applications. However, the existing CSC technique is sensitive to the changes in the integer ambiguity, and then the smoothing procedure needs to be restarted in the presence of cycle slips. As the Doppler shift is instantaneously observed and immune to cycle slips, the Doppler-aided smoothing code (DSC) algorithm would be more promising in a challenged environment. Based on the Hatch filter, an optimal DSC approach is proposed with the principle of minimum variance. Meanwhile, to inhibit the effect of the integral cumulative error of the Doppler, a balance factor is adopted to adjust the contributions of raw code and DSC. The noise level of code observable is not only affected by thermal noise, but also limited by systematic bias. Satellite code bias (SCB) was identified in the raw code observable on each frequency for each BDS-2 satellite. By minimizing the sum of the absolute value of residuals, the polynomial segment fitting algorithm as a function of elevation angles is applied to establish the SCB correction model based on epoch-differenced multipath (MP) deviations. Finally, different types of experiments demonstrate the validity and efficiency of the refined DSC filter with SCB corrections on each available frequency for BDS un-GEO satellites.
Estimating the Aboveground Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data
Authors: Huang Tianbao , Ou Guanglong , Wu Yong , Zhang Xiaoli , Liu Zihao , Xu Hui , Xu Xiongwei , Wang Zhenghui , Xu Can
Published: July 2023

It is important to improve the accuracy of models estimating aboveground biomass (AGB) in large areas with complex geography and high forest heterogeneity. In this study, k-nearest neighbors (k-NN), gradient boosting machine (GBM), random forest (RF), quantile random forest (QRF), regularized random forest (RRF), and Bayesian regularization neural network (BRNN) machine learning algorithms were constructed to estimate the AGB of four forest types based on environmental factors and the variables selected by the Boruta algorithm in Yunnan Province and using integrated Landsat 8 OLI and Sentinel 2A images. The results showed that (1) DEM was the most important variable for estimating the AGB of coniferous forests, evergreen broadleaved forests, deciduous broadleaved forests, and mixed forests; while the vegetation index was the most important variable for estimating deciduous broadleaved forests, the climatic factors had a higher variable importance for estimating coniferous and mixed forests, and texture features and vegetation index had a higher variable importance for estimating evergreen broadleaved forests. (2) In terms of specific model performance for the four forest types, RRF was the best model both in estimating the AGB of coniferous forests and mixed forests; the R2 and RMSE for coniferous forests were 0.63 and 43.23 Mg ha−1, respectively, and the R2 and RMSE for mixed forests were 0.56 and 47.79 Mg ha−1, respectively. BRNN performed the best in estimating the AGB of evergreen broadleaved forests; the R2 was 0.53 and the RMSE was 68.16 Mg ha−1. QRF was the best in estimating the AGB of deciduous broadleaved forests, with R2 of 0.43 and RMSE of 45.09 Mg ha−1. (3) RRF was the best model for the four forest types according to the mean values, with R2 and RMSE of 0.503 and 52.335 Mg ha−1, respectively. In conclusion, different variables and suitable models should be considered when estimating the AGB of different forest types. This study could provide a reference for the estimation of forest AGB based on remote sensing in complex terrain areas with a high degree of forest heterogeneity.
A Convolution and Attention Neural Network with MDTW Loss for Cross-Variable Reconstruction of Remote Sensing Image Series
Authors: Li Chao , Wang Haoran , Su Qinglei , Ning Chunlin , Li Teng
Published: July 2023

Environmental images that are captured by satellites can provide significant information for weather forecasting, climate warning, and so on. This article introduces a novel deep neural network that integrates a convolutional attention feature extractor (CAFE) in a recurrent neural network frame and a multivariate dynamic time warping (MDTW) loss. The CAFE module is designed to capture the complicated and hidden dependencies within image series between the source variable and the target variable. The proposed method can reconstruct the image series across environmental variables. The performance of the proposed method is validated by experiments using a real-world remote sensing dataset and compared with several representative methods. Experimental results demonstrate the emerging performance of the proposed method for cross-variable image series reconstruction.
Combined PS-InSAR Technology and High-Resolution Optical Remote Sensing for Identifying Illegal Underground Mining in the Suburb of Yangquan City, Shanxi Province, China
Authors: Xia Yuanping , Xia Fei , Hui Zhenyang , Li Huaizhan , Wan Ranran , Ai Jinquan
Published: July 2023

Illegal mining is one of the biggest problems in many coal mines. With the rapid development of the economy, driven by huge economic benefits, some outlaws illegally exploit mineral resources without a mining license, which is destructive and a potential safety hazard. In order to avoid inspection by law enforcement officials, some outlaws, regardless of the cost or risk, privately and surreptitiously excavate coal mines in self-built houses. The coal resources they excavate are shallow coal resources. Because surface buildings can maintain strong and stable radar scattering characteristics over a long time series, in this study, we combined PS-InSAR technology and high-resolution optical remote sensing to extract the subsidence information of surface buildings corresponding to PS point sets and analyzed their spatiotemporal characteristics. Finally, we developed a fast and accurate method for detecting suspected illegal mining sites from building subsidence information over a larger area. We also carried out a case study using Shandi Village, a suburb of Yangquan City, Shanxi Province, China, as our research object. QuickBird-2, WorldView-2 data, and 20 PALSAR scenes were selected for the experimental research, and two illegal mining sites were detected from 29 December 2006 to 9 January 2011. By comparing our results with previous investigation data, it was found that the accuracy rate reached 40% in local areas, and the detection rate reached 66.67%. In addition, the mining periods were basically consistent. This research shows that our method is feasible and has certain engineering applicability and practical value.
A Sub-Bottom Type Adaption-Based Empirical Approach for Coastal Bathymetry Mapping Using Multispectral Satellite Imagery
Authors: Ji Xue , Ma Yi , Zhang Jingyu , Xu Wenxue , Wang Yanhong
Published: July 2023

Accurate bathymetric data in shallow water is of increasing importance for navigation safety, coastal management, and marine transportation. Satellite-derived bathymetry (SDB) is widely accepted as an effective alternative to conventional acoustic measurements in coastal areas, providing high spatial and temporal resolution combined with extensive repetitive coverage. Many previous empirical SDB approaches are unsuitable for precision bathymetry mapping in various scenarios, due to the assumption of homogeneous bottom over the whole region, as well as the neglect of various interfering factors (e.g., turbidity) causing radiation attenuation. Therefore, this study proposes a bottom-type adaption-based SDB approach (BA-SDB). Under the consideration of multiple factors including suspended particulates and phytoplankton, it uses a particle swarm optimization improved LightGBM algorithm (PSO-LightGBM) to derive depth of each pre-segmented bottom type. Based on multispectral images of high spatial resolution and in situ observations of airborne laser bathymetry and multi-beam echo sounder, the proposed approach is applied in shallow water around Yuanzhi Island, and achieves the highest accuracy with an RMSE value of 0.85 m compared to log-ratio, multi-band, and classical machine learning methods. The results of this study show that the introduction of water-environment parameters improves the performance of the machine learning model for bathymetric mapping.
Evaluation of the Horizontal Winds Simulated by IAP-HAGCM through Comparison with Beijing MST Radar Observations
Authors: Tian Yufang , Chai Zhaoyang , Yu Zipeng , Chen Ze , Jin Jiangbo
Published: July 2023

The performance of general circulation models (GCMs) in simulating horizontal winds is important because the distribution and variation in horizontal winds are central to investigating atmospheric dynamic characteristics and processes. Also, horizontal wind data can be used to extract some of the required information on gravity waves, tides, and planetary waves. In this context, the present paper evaluates the capability of the Institute of Atmospheric Physics atmospheric general circulation model high-top version (IAP-HAGCM) in simulating the horizontal winds and tides of the troposphere and lower stratosphere by presenting a climatological and statistical comparison against observations of the powerful Beijing mesosphere–stratosphere–troposphere (MST) radar (39.78°N, 116.95°E) during 2012–2014. The results illustrated that the IAP-HAGCM can successfully reproduce the time–altitude distribution of the monthly mean zonal wind and diurnal tide amplitude, albeit with some underestimation. The mean correlation coefficients and root-mean-square error for the zonal (meridional) winds were 0.94 (0.73) and 6.60 m s−1 (2.90 m s–1), respectively. Additionally, the IAP-HAGCM can capture the temporal variation in both the zonal and meridional winds. It is worth noting that, compared with the seven coupled model intercomparison project phase 6 (CMIP6) models, the IAP-HAGCM performs better in meridional wind simulations below 15 km. However, there are discrepancies in altitudinal ranges with large wind velocities, such as the westerly jet, in the transition region of the troposphere and stratosphere, and in February, April, July, and September. It is suggested that model users should take advantage of the model’s simulation ability by combining this information regarding when and where it is optimal with their own research purposes. Moreover, the evaluation results in this paper can also serve as a reference for guiding improvements of the IAP-HAGCM.
Application of the Concept of Land Degradation Neutrality for Remote Monitoring of Agricultural Sustainability of Irrigated Areas in Uzbekistan
Authors: Kust German , Andreeva Olga , Shklyaeva Darya
Published: July 2023

A scientific approach to the assessment of trends in land changes based on the novel concept of Land Degradation Neutrality (LDN) was applied to monitor the sustainability of irrigated farmlands in test areas in Uzbekistan (the Andijan, Namangan, Fergana, and Syrdarya regions). The tool “Trends.Earth”, which was recommended by the UN Convention to Combat Desertification and developed as a special plugin for the Quantum GIS platform, was used to describe the dynamics of land degradation in the period 2001–2020. This study demonstrates the results of monitoring land productivity dynamics that reflect the investments in irrigation improvement during the last 10–15 years. A comparison between changes in land productivity measured via Normalized Difference Vegetation Index and its average value for the entire observation period is more informative than comparison with the initial 5-year period. More details could be noted through application of the “moving average” calculation method. The described trends demonstrate that the use of sustainable land management practices in the last decade led to a decreasing proportion of degraded lands compared to the average figure for the period 2001–2020 (from 25–40% to 10–20%). This trend is confirmed by reviewing state statistics and indicates the success of national policies and approaches to adaptation. However, the dynamics of land productivity in the study areas is diverse and includes “dry” and “humid” extremes, depending on climate fluctuations. Despite the generally positive trends identified across regions, the high dynamics of degraded hotspots and improved lands within certain areas confirm the instability of ongoing changes.
Automated Categorization of Multiclass Welding Defects Using the X-ray Image Augmentation and Convolutional Neural Network
Authors: Say Dalila , Zidi Salah , Qaisar Saeed Mian , Krichen Moez
Published: July 2023

The detection of weld defects by using X-rays is an important task in the industry. It requires trained specialists with the expertise to conduct a timely inspection, which is costly and cumbersome. Moreover, the process can be erroneous due to fatigue and lack of concentration. In this context, this study proposes an automated approach to identify multi-class welding defects by processing the X-ray images. It is realized by an intelligent hybridization of the data augmentation techniques and convolutional neural network (CNN). The proposed data augmentation mainly performs random rotation, shearing, zooming, brightness adjustment, and horizontal flips on the intended images. This augmentation is beneficial for the realization of a generalized trained CNN model, which can process the multi-class dataset for the identification of welding defects. The effectiveness of the proposed method is confirmed by testing its performance in processing an industrial dataset. The intended dataset contains 4479 X-ray images and belongs to six groups: cavity, cracks, inclusion slag, lack of fusion, shape defects, and normal defects. The devised technique achieved an average accuracy of 92%. This indicates that the approach is promising and can be used in contemporary solutions for the automated detection and categorization of welding defects.
Homogeneous Sensor Fusion Optimization for Low-Cost Inertial Sensors
Authors: Nemec Dusan , Andel Jan , Simak Vojtech , Hrbcek Jozef
Published: July 2023

The article deals with sensor fusion and real-time calibration in a homogeneous inertial sensor array. The proposed method allows for both estimating the sensors’ calibration constants (i.e., gain and bias) in real-time and automatically suppressing degraded sensors while keeping the overall precision of the estimation. The weight of the sensor is adaptively adjusted according to the RMSE concerning the weighted average of all sensors. The estimated angular velocity was compared with a reference (ground truth) value obtained using a tactical-grade fiber-optic gyroscope. We have experimented with low-cost MEMS gyroscopes, but the proposed method can be applied to basically any sensor array.
Electroencephalography Signal Processing: A Comprehensive Review and Analysis of Methods and Techniques
Authors: Chaddad Ahmad , Wu Yihang , Kateb Reem , Bouridane Ahmed
Published: July 2023

The electroencephalography (EEG) signal is a noninvasive and complex signal that has numerous applications in biomedical fields, including sleep and the brain–computer interface. Given its complexity, researchers have proposed several advanced preprocessing and feature extraction methods to analyze EEG signals. In this study, we analyze a comprehensive review of numerous articles related to EEG signal processing. We searched the major scientific and engineering databases and summarized the results of our findings. Our survey encompassed the entire process of EEG signal processing, from acquisition and pretreatment (denoising) to feature extraction, classification, and application. We present a detailed discussion and comparison of various methods and techniques used for EEG signal processing. Additionally, we identify the current limitations of these techniques and analyze their future development trends. We conclude by offering some suggestions for future research in the field of EEG signal processing.
Federated Learning-Based Spectrum Occupancy Detection
Authors: Kułacz Łukasz , Kliks Adrian
Published: July 2023

Dynamic access to the spectrum is essential for radiocommunication and its limited spectrum resources. The key element of dynamic spectrum access systems is most often effective spectrum occupancy detection. In many cases, machine learning algorithms improve this detection’s effectiveness. Given the recent trend of using federated learning, we present a federated learning algorithm for distributed spectrum occupancy detection. This idea improves overall spectrum-detection effectiveness, simultaneously keeping a low amount of data that needs to be exchanged between sensors. The proposed solution achieves a higher accuracy score than separate and autonomous models used without federated learning. Additionally, the proposed solution shows some sort of resistance to faulty sensors encountered in the system. The results of the work presented in the article are based on actual signal samples collected in the laboratory. The proposed algorithm is effective (in terms of spectrum occupancy detection and amount of exchanged data), especially in the context of a set of sensors in which there are faulty sensors.
Experimental Study of Bridge Expansion Joint Damage Based on Natural Frequency
Authors: Li Junshi , Wen Feng , Chen Jun , Yang Caiqian , Du Wenping , Xu Limin , Li Peng
Published: July 2023

In this paper, three studies on modal bridge expansion joints were conducted through experiments. The advantages and disadvantages of acceleration and fiber optic strain sensors in the tested modal expansion joints were compared. Secondly, the variation in the natural frequency of the modal bridge expansion joints at different concrete curing periods was investigated. Finally, the effect of damage on natural frequency in different parts (the center beam, the support bar, and concrete in the anchorage zone) of the modal bridge expansion joint was analyzed. For this purpose, three specimens were cast, each with six damage states. Manual methods damaged the specimens. An impact hammer was used to excite the corresponding parts of the different components. The results showed that the acceleration sensor is optimal for the modal bridge expansion joint test. The specimen’s natural frequency increased with the curing time’s growth. The natural frequency increased by 10 Hz from day 3 to day 28 of curing. With the gradual increase in damage, the natural frequencies of the center beam and support bar showed a gradual decreasing trend. The damage to the concrete in the anchorage zone caused less significant changes in the natural frequency, but the overall natural frequency still had a decreasing trend. The sensitivity of each frequency to the damage was different in different parts.
Real-Time Recognition and Detection of Bactrocera minax (Diptera: Trypetidae) Grooming Behavior Using Body Region Localization and Improved C3D Network
Authors: Sun Yong , Zhan Wei , Dong Tianyu , Guo Yuheng , Liu Hu , Gui Lianyou , Zhang Zhiliang
Published: July 2023

Pest management has long been a critical aspect of crop protection. Insect behavior is of great research value as an important indicator for assessing insect characteristics. Currently, insect behavior research is increasingly based on the quantification of behavior. Traditional manual observation and analysis methods can no longer meet the requirements of data volume and observation time. In this paper, we propose a method based on region localization combined with an improved 3D convolutional neural network for six grooming behaviors of Bactrocera minax: head grooming, foreleg grooming, fore-mid leg grooming, mid-hind leg grooming, hind leg grooming, and wing grooming. The overall recognition accuracy reached 93.46%. We compared the results obtained from the detection model with manual observations; the average difference was about 12%. This shows that the model reached a level close to manual observation. Additionally, recognition time using this method is only one-third of that required for manual observation, making it suitable for real-time detection needs. Experimental data demonstrate that this method effectively eliminates the interference caused by the walking behavior of Bactrocera minax, enabling efficient and automated detection of grooming behavior. Consequently, it offers a convenient means of studying pest characteristics in the field of crop protection.
Empowering Patient Similarity Networks through Innovative Data-Quality-Aware Federated Profiling
Authors: Navaz Alramzana Nujum , Serhani Mohamed Adel , El Kassabi Hadeel T. El , Taleb Ikbal
Published: July 2023

Continuous monitoring of patients involves collecting and analyzing sensory data from a multitude of sources. To overcome communication overhead, ensure data privacy and security, reduce data loss, and maintain efficient resource usage, the processing and analytics are moved close to where the data are located (e.g., the edge). However, data quality (DQ) can be degraded because of imprecise or malfunctioning sensors, dynamic changes in the environment, transmission failures, or delays. Therefore, it is crucial to keep an eye on data quality and spot problems as quickly as possible, so that they do not mislead clinical judgments and lead to the wrong course of action. In this article, a novel approach called federated data quality profiling (FDQP) is proposed to assess the quality of the data at the edge. FDQP is inspired by federated learning (FL) and serves as a condensed document or a guide for node data quality assurance. The FDQP formal model is developed to capture the quality dimensions specified in the data quality profile (DQP). The proposed approach uses federated feature selection to improve classifier precision and rank features based on criteria such as feature value, outlier percentage, and missing data percentage. Extensive experimentation using a fetal dataset split into different edge nodes and a set of scenarios were carefully chosen to evaluate the proposed FDQP model. The results of the experiments demonstrated that the proposed FDQP approach positively improved the DQ, and thus, impacted the accuracy of the federated patient similarity network (FPSN)-based machine learning models. The proposed data-quality-aware federated PSN architecture leveraging FDQP model with data collected from edge nodes can effectively improve the data quality and accuracy of the federated patient similarity network (FPSN)-based machine learning models. Our profiling algorithm used lightweight profile exchange instead of full data processing at the edge, which resulted in optimal data quality achievement, thus improving efficiency. Overall, FDQP is an effective method for assessing data quality in the edge computing environment, and we believe that the proposed approach can be applied to other scenarios beyond patient monitoring.
Surface Quality Improvement for Ultrasonic-Assisted Inner Diameter Sawing with Six-Axis Force Sensors
Authors: Zhao Jinghe , Wang Lulu , Jiang Bo , Pei Yongchen , Lu Huiqi
Published: July 2023

Ultrasonic-assisted inner diameter machining is a slicing method for hard and brittle materials. During this process, the sawing force is the main factor affecting the workpiece surface quality and tool life. Therefore, based on indentation fracture mechanics, a theoretical model of the cutting force of an ultrasound-assisted inner diameter saw is established in this paper for surface quality improvement. The cutting experiment was carried out with alumina ceramics (99%) as an exemplar of hard and brittle material. A six-axis force sensor was used to measure the sawing force in the experiment. The correctness of the theoretical model was verified by comparing the theoretical modeling with the actual cutting force, and the influence of machining parameters on the normal sawing force was evaluated. The experimental results showed that the ultrasonic-assisted cutting force model based on the six-axis force sensor proposed in this paper was more accurate. Compared with the regular tetrahedral abrasive model, the mean value and variance of the proposed model’s force prediction error were reduced by 5.08% and 2.56%. Furthermore, by using the proposed model, the sawing processing parameters could be updated to improve the slice surface quality from a roughness Sa value of 1.534 µm to 1.129 µm. The proposed model provides guidance for the selection of process parameters and can improve processing efficiency and quality in subsequent real-world production.
Measurement of Shoulder Abduction Angle with Posture Estimation Artificial Intelligence Model
Authors: Kusunose Masaya , Inui Atsuyuki , Nishimoto Hanako , Mifune Yutaka , Yoshikawa Tomoya , Shinohara Issei , Furukawa Takahiro , Kato Tatsuo , Tanaka Shuya , Kuroda Ryosuke
Published: July 2023

Substantial advancements in markerless motion capture accuracy exist, but discrepancies persist when measuring joint angles compared to those taken with a goniometer. This study integrates machine learning techniques with markerless motion capture, with an aim to enhance this accuracy. Two artificial intelligence-based libraries—MediaPipe and LightGBM—were employed in executing markerless motion capture and shoulder abduction angle estimation. The motion of ten healthy volunteers was captured using smartphone cameras with right shoulder abduction angles ranging from 10° to 160°. The cameras were set diagonally at 45°, 30°, 15°, 0°, −15°, or −30° relative to the participant situated at a distance of 3 m. To estimate the abduction angle, machine learning models were developed considering the angle data from the goniometer as the ground truth. The model performance was evaluated using the coefficient of determination R2 and mean absolute percentage error, which were 0.988 and 1.539%, respectively, for the trained model. This approach could estimate the shoulder abduction angle, even if the camera was positioned diagonally with respect to the object. Thus, the proposed models can be utilized for the real-time estimation of shoulder motion during rehabilitation or sports motion.
Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi
Authors: Cereja Rui , Cruz Joana P. C. , Heumüller Joshua , Vicente Bernardo , Amorim Ana , Carvalho Frederico , Cabral Sara , Chainho Paula , Brito Ana C. , Ferreira Inês J. , Diniz Mário
Published: July 2023

Bivalves accumulate toxins produced by microalgae, thus becoming harmful for humans. However, little information is available about their toxicity to the bivalve itself. In the present work, the physiological stress and damage after the ingestion of toxic dinoflagellate species (Gymnodinium catenatum) and a diatom species (Skeletonema marinoi, which is non-toxic to humans but may be to grazers) in the oyster Magallana angulata are evaluated against a control treatment fed with the chlorophyte Tetraselmis sp. Oysters were exposed for two hours to a concentration of 4 × 104 cells/L of G. catenatum and 2 × 107 cells/L of S. marinoi. The biomarkers superoxide dismutase (SOD), catalase (CAT), glutathione S-Transferase, total Ubiquitin (Ubi) and Acetylcholinesterase (AchE) were assessed. The exposure of M. angulata to G. catenatum lead to a reduction in SOD and AchE activity and ubiquitin concentrations when compared to the control treatment. Moreover, it increased CAT activity in the adductor muscle, and maintained its activity in the other tissues tested. This may be related to the combination of reduced metabolism with the deployment of detoxification processes. S. marinoi also lead to a decrease in all biomarkers tested in the gills and digestive glands. Therefore, both species tested caused physiological alterations in M. angulata after two hours of exposure.
Sustainability at Play: Educational Design Research for the Development of a Digital Educational Resource for Primary Education
Authors: Sá Patrícia , Silva Patrícia Christine , Peixinho Joana , Figueiras Ana , Rodrigues Ana V.
Published: July 2023

Quality education is an indispensable element for the successful implementation of the 2030 Agenda for Sustainable Development, as it equips all children with the essential skills to promote sustainable development within the context of their lifestyles, in line with the fourth Sustainable Development Goal (SDG4). This will have to be an innovative education, not only in the contents and guidelines to be followed but also in the educational strategies and resources to be used. This article aims to present and describe the methodology used to develop the digital educational resource (DER) “Sustainability at Play,” a serious game intended for primary education and based on the concept of the ecological footprint. This DER was developed through educational design research (EDR) by a multidisciplinary team within a project to create Digital Educational Resources for Primary Education. The EDR approach was organized in four phases—Phase I—Problem Analysis, Phase II—Exploration of Possible Solutions, Phase III—Design, and Phase IV—Reflection—allowing for an iterative DER development process shared by different participants (researchers, illustrators, web designers, primary school teachers and students). As a result, this study enabled not only the development of an innovative DER to work on issues related to education for sustainability in primary school but also the understanding and validation of the suitability of the EDR methodology for the development of this type of educational resource.