bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Combined Use of Olive Mill Waste Compost and Sprinkler Irrigation on GHG Emissions and Net Ecosystem Carbon Budget under Different Tillage Systems
Authors: Fernández-Rodríguez Damián , Fangueiro David Paulo , Peña Abades David , Albarrán Ángel , Rato-Nunes Jose Manuel , Martín-Franco Carmén , Terrón-Sánchez Jaime , Vicente Luis Andrés , López-Piñeiro Antonio
Published: December 2022

Traditional rice (Oryza sativa L.) production by flooding is a source of greenhouse gases (GHG), especially methane. The high consumption of water, as well as the chemical and physical degradation caused by these traditional practices in rice soils, is promoting a decrease in rice production in the Mediterranean area. The aim of this study was to monitor GHG emissions and the net ecosystem carbon balance (NECB) from rice produced with sprinkler irrigation techniques and also assess the impact of olive mill waste compost (C-OW) application and tillage on GHG emissions and the NECB. A field experiment for irrigated rice production was implemented by considering four different treatments: (1) tillage (T); (2) no tillage—direct seeding techniques (DS); (3) application of C-OW followed by tillage (TC); and (4) application of C-OW followed by direct seeding (DSC). The C-OW was only applied in the first year at a dose of 80 Mg ha−1. GHG emissions were monitored over three years in these four treatments in order to estimate the direct (first year) and residual (third year) effects of such practices. The application of C-OW caused an increase of 1.85 times the emission of CO2-C in the TC-DSC compared to the T-DS in the first year. It is noteworthy that the TC treatment was the only one that maintained an emission of CO2-C that was 42% higher than T in the third year. Regardless of the treatments and year of the study, negative values for the cumulative CH4 were found, suggesting that under sprinkler irrigation, CH4 oxidation was the dominant process. A decrease in N2O emissions was observed under direct seeding relative to the tillage treatments, although without significant differences. Tillage resulted in an increase in the global warming potential (GWP) of up to 31% with respect to direct seeding management in the third year, as a consequence of the greater carbon oxidation caused by intensive tillage. DS presented a positive NECB in the accumulation of C in the soil; therefore, it provided a greater ecological benefit to the environment. Thus, under Mediterranean conditions, rice production through a sprinkler irrigation system in combination with direct seeding techniques may be a sustainable alternative for rice crops, reducing their GWP and resulting in a lower carbon footprint. However, the use of C-OW as an organic amendment could increase the GHG emissions from rice fields irrigated by sprinklers, especially under tillage conditions.
Afforestation of Taxodium Hybrid Zhongshanshan Influences Soil Bacterial Community Structure by Altering Soil Properties in the Yangtze River Basin, China
Authors: Shi Qin , Zhou Zhidong , Wang Ziyang , Lu Zhiguo , Han Jiangang , Xue Jianhui , Creech David , Yin Yunlong , Hua Jianfeng
Published: December 2022

Taxodium hybrid Zhongshanshan has been widely planted in the Yangtze River Basin (YRB) for soil and carbon conservation, with quantities over 50 million. The objective of this study was to determine how T. hybrid Zhongshanshan plantations affected soil physicochemical properties and bacterial community structure in the YRB, and to examine the consistency of changes by afforestation. Soils under T. Zhongshanshan plantations across six sites of the YRB were compared with soils of adjacent non-forested sites. Soil physicochemical properties and bacterial community structure were determined to clarify edaphic driving factors and reveal the effects of afforestation on bacteria. The results indicated that most soil attributes manifested improvements, e.g., total nitrogen in Jiangxi and Shanghai; available phosphorus in Hubei, Chongqing and Yunnan, exhibited the potential to maintain or ameliorate soil quality. A decrease in soil bulk density caused by plantation was also observed at the expense of soil macro-aggregates augment. Afforestation of T. Zhongshanshan plantation has habitually improved Shannon diversity and Chao1 richness, of which dominant phyla were Proteobacteria, Acidobacteria, and Actinobacteria, and increased the relative abundance of the phyla Proteobacteria and Nitrospirae, and the classes Flavobacteriia, Acidobacteria_Gp5, and Bacilli. We concluded that T. Zhongshanshan plantation can be employed to facilitate soil nutrient accumulation in the YRB, but that the degree, rate and direction of changes in soil attributes are sites dependent. It is recommended that afforestation of nutrient-depleted and less productive lands in the YRB should utilize this fast-growing species in combination with proper fertilization.
Olive Bud Dormancy Release Dynamics and Validation of Using Cuttings to Determine Chilling Requirement
Authors: Rubio-Valdés Guillermo , Cabello Diego , Rapoport Hava F. , Rallo Luis
Published: December 2022

Dormancy release dynamics in olive tree (Olea europaea L.) reproductive buds as affected by cold accumulation, tree bearing status, and budburst temperature was studied under natural and controlled conditions, using both cuttings and container- and field-grown plants. The chilling necessary for dormancy release was acquired at different times within the bud population, presenting a progressive pattern of reproductive budburst. Once sufficient chilling is accumulated, 20 °C is a suitable temperature for reproductive budburst, although higher temperature, e.g., 30 °C, during dormancy release can inhibit budburst. While the bearing status of trees determined the amount of return bloom, dormancy release followed a similar pattern for previously bearing and non-bearing trees. Concurrent with investigating budburst factors, the use of shoot cuttings was tested as a method for olive dormancy release studies by contrasting with results from whole trees. It was found it to be valid for studying reproductive budburst, thus providing a useful method to screen chilling requirements in cultivar evaluation and the breeding programs currently ongoing in this species. However, the method was not valid for vegetative budburst, with varying results between cuttings and the whole plant.
Field Evaluation of Wheat Varieties Using Canopy Temperature Depression in Three Different Climatic Growing Seasons
Authors: Chai Yongmao , Zhao Zhangchen , Lu Shan , Chen Liang , Hu Yingang
Published: December 2022

During the breeding progress, screening excellent wheat varieties and lines takes lots of labor and time. Moreover, different climatic conditions will bring more complex and unpredictable situations. Therefore, the selection efficiency needs to be improved by applying the proper selection index. This study evaluates the capability of CTD as an index for evaluating wheat germplasm in field conditions and proposes a strategy for the proper and efficient application of CTD as an index in breeding programs. In this study, 186 bread wheat varieties were grown in the field and evaluated for three continuous years with varied climatic conditions: normal, spring freezing, and early drought climatic conditions. The CTD and photosynthetic parameters were investigated at three key growth stages, canopy structural traits at the early grain filling stage, and yield traits at maturity. The variations in CTD among varieties were the highest in normal conditions and lowest in spring freezing conditions. CTD at the three growing stages was significantly and positively correlated for each growing season, and CTD at the middle grain filling stage was most significantly correlated across the three growing seasons, suggesting that CTD at the middle grain filling stage might be more important for evaluation. CTD was greatly affected by photosynthetic and canopy structural traits, which varied in different climatic conditions. Plant height, peduncle length, and the distance of the flag leaf to the spike were negatively correlated with CTD at the middle grain filling stage in both normal and drought conditions but positively correlated with CTD at the three stages in spring freezing conditions. Flag leaf length was positively correlated with CTD at the three stages in normal conditions but negatively correlated with CTD at the heading and middle grain filling stages in spring freezing conditions. Further analysis showed that CTD could be an index for evaluating the photosynthetic and yield traits of wheat germplasm in different environments, with varied characteristics in different climatic conditions. In normal conditions, the varieties with higher CTDs at the early filling stage had higher photosynthetic capacities and higher yields; in drought conditions, the varieties with high CTDs had better photosynthetic capacities, but those with moderate CTD had higher yield, while in spring freezing conditions, there were no differences in yield and biomass among the CTD groups. In sum, CTD could be used as an index to screen wheat varieties in specific climatic conditions, especially in normal and drought conditions, for photosynthetic parameters and some yield traits.
Transcriptome and Gene Regulatory Network Analyses Reveal New Transcription Factors in Mature Fruit Associated with Harvest Date in Prunus persica
Authors: Núñez-Lillo Gerardo , Pérez-Reyes Wellasmin , Riveros Anibal , Lillo-Carmona Victoria , Rothkegel Karin , Álvarez José Miguel , Blanco-Herrera Francisca , Pedreschi Romina , Campos-Vargas Reinaldo , Meneses Claudio
Published: December 2022

Harvest date is a critical parameter for producers and consumers regarding agro-industrial performance. It involves a pleiotropic effect controlling the development of other fruit quality traits through finely controlling regulatory mechanisms. Fruit ripening is a process in which various signals and biological events co-occur and are regulated by hormone signaling that produces the accumulation/degradation of multiple compounds. However, the regulatory mechanisms that control the hormone signaling involved in fruit development and ripening are still unclear. To investigate the issue, we used individuals with early, middle and late harvest dates from a peach segregating population to identify regulatory candidate genes controlling fruit quality traits at the harvest stage and validate them in contrasting peach varieties for this trait. We identified 467 and 654 differentially expressed genes for early and late harvest through a transcriptomic approach. In addition, using the Arabidopsis DAP-seq database and network analysis, six transcription factors were selected. Our results suggest significant hormonal balance and cell wall composition/structure differences between early and late harvest samples. Thus, we propose that higher expression levels of the transcription factors HB7, ERF017 and WRKY70 in early harvest individuals would induce the expression of genes associated with the jasmonic acid pathway, photosynthesis and gibberellins inhibition. While on the other hand, the high expression levels of LHY, CDF3 and NAC083 in late harvest individuals would promote the induction of genes associated with abscisic acid biosynthesis, auxins and cell wall remodeling.
The Influence of the Surface Chemistry of Cellulose Nanocrystals on Ethyl Lauroyl Arginate Foam Stability
Authors: Czakaj Agnieszka , Chatzigiannakis Emmanouil , Vermant Jan , Krzan Marcel , Warszyński Piotr
Published: December 2022

Guanidine-based surfactant ethyl lauroyl arginate (LAE) and cellulose nanocrystals (CNCs) form complexes of enhanced surface activity when compared to pure surfactants. The LAE-CNC mixtures show enhanced foaming properties. The dynamic thin-film balance technique (DTFB) was used to study the morphology, drainage and rupture of LAE-CNC thin liquid films under constant driving pressure. A total of three concentrations of surfactant and the corresponding mixtures of LAE with sulfated (sCNC) and carboxylated (cCNC) cellulose nanocrystals were studied. The sCNC and cCNC suspension with LAE formed thin films, with stability increasing with surfactant concentration and with complex rheological properties. In the presence of LAE, the aggregation of CNC was observed. While the sCNC aggregates were preferentially present in the film volume with a small fraction at the surface, the cCNC aggregates, due to their higher hydrophobicity, were preferentially located at film interfaces, forming compact layers. The presence of both types of aggregates decreased the stability of the thin liquid film compared to the one for the LAE solution with the same concentration. The addition of CNC to LAE was critical for foam formation, and foam stability was in qualitative agreement with the thin films’ lifetimes. The foam volume increased with the LAE concentration. However, there was an optimum surfactant concentration to achieve stable foam. In particular, the very resistant foam was obtained with cCNC suspensions that formed the interfaces with a complex structure and rheology. On the other hand, at high LAE concentrations, the aggregates of CNC may exhibit antifoaming properties
Molecular Dynamics Simulation of Poly(Ether Ether Ketone) (PEEK) Polymer to Analyze Intermolecular Ordering by Low Wavenumber Raman Spectroscopy and X-ray Diffraction
Authors: Yang Xiaoran , Yokokura Seiya , Nagahama Taro , Yamaguchi Makoto , Shimada Toshihiro
Published: December 2022

Poly(ether ether ketone) (PEEK) is an important engineering plastic and evaluation of its local crystallinity in composites is critical for producing strong and reliable mechanical parts. Low wavenumber Raman spectroscopy and X-ray diffraction are promising techniques for the analysis of crystal ordering but a detailed understanding of the spectra has not been established. Here, we use molecular dynamics combined with a newly developed approximation to simulate local vibrational features to understand the effect of intermolecular ordering in the Raman spectra. We found that intermolecular ordering does affect the low wavenumber Raman spectra and the X-ray diffraction as observed in the experiment. Raman spectroscopy of intermolecular vibration modes is a promising technique to evaluate the local crystallinity of PEEK and other engineering plastics, and the present technique offers an estimation without requiring heavy computational resources.
Considering Electrospun Nanofibers as a Filler Network in Electrospun Nanofiber-Reinforced Composites to Predict the Tensile Strength and Young’s Modulus of Nanocomposites: A Modeling Study
Authors: Gavande Vishal , Nagappan Saravanan , Lee Won-Ki
Published: December 2022

In this study, a simple approach was described to investigate the theoretical models for electrospun polymer nanofiber-reinforced nanocomposites. For predicting the tensile strength of the electrospun nylon 6 nanofiber-reinforced polyurethane acrylate composites, conventional Pukanszky, Nicolais–Narkis, Halpin–Tsai, and Neilson models were used, while for Young’s modulus, Halpin–Tsai, modified Halpin–Tsai, and Hui–Shia models were used. As per the Pukanszky model, composite films showed better interaction since the values of the interaction parameter, B, were more than 3. Similarly, the value of an interfacial parameter, K, was less than 1.21 (K = −5, for the curve fitting) as per the Nicolais–Narkis model, which indicated better interfacial interaction. For composite films, the modified Halpin–Tsai model was revised again by introducing the orientation factor, α, which was 0.333 for the randomly oriented continuous nanofiber-reinforced composites, and the exponential shape factor, ξ = (2l/d)e−avf−b, which showed the best agreement with the experimental Young’s modulus results. Based on mentioned remarks, these models would be applicable for estimating the tensile strength and Young’s modulus of electrospun nanofiber-reinforced polymer composite films.
Model Development of a Hybrid Battery–Piezoelectric Fiber System Based on a New Control Method
Authors: Hesarian Mir Saeid , Tavoosi Jafar , Alanazi Tarek I.
Published: December 2022

By increasing the application of smart wearables, their electrical energy supply has drawn great attention in the past decade. Sources such as the human body and its motion can produce electrical power as renewable energy using piezoelectric yarns. During the last decade, the development of the piezoelectric fibers used in smart clothes has increased for energy-harvesting applications. Therefore, the energy harvesting from piezoelectric yarns and saving process is an important subject. For this purpose, a new control system was developed based on the combination of the sliding mode and particle swarm optimization (PSO). Using this method, due to the piezoelectric yarn cyclic deformation process, electrical power is produced. This power is considered the input voltage to the controlling system modeled in this article. This system supplies constant voltage to be saved in a battery. The battery supplies power for the electrical elements of smart fabric structure for different applications, such as health care. It is shown that the presence of PSO led to the improvement of system response and error reduction by more than 30%.
Facile Access to Gleditsia microphylla Galactomannan Hydrogel with Rapid Self-Repair Capacity and Multicyclic Water-Retaining Performance of Sandy Soil
Authors: Liu Chuanjie , Tang Meng , Zhang Fenglun , Lei Fuhou , Li Pengfei , Wang Kun , Zeng Hongbo , Jiang Jianxin
Published: December 2022

Sandy soil has poor water-holding performance, making it difficult for plants to survive, which worsens the deterioration of the ecological environment. Therefore, borax cross-linked Gleditsia microphylla galactomannan hydrogel (GMGH) was prepared, and its practicability as a water-retaining agent was analyzed. GMGH exhibited fast self-healing performance (150 s, ≈100%) and a high swelling index (88.70 g/g in pH 9). The feasibility of improving the water absorption and retention properties of sandy soil was explored by mixing different proportions (0.1, 0.3, 0.5 wt % sandy soil) of GMGH and sandy soil. The results showed that sandy soil had a more porous structure after adding 0.5 wt % GMGH, and its water absorption index increased from 15.68 to 38.12%. In an artificial climate box, the water-holding time of the sandy soil was extended from 3 to 23.5 days, and the cycles of water absorption and retention were more than 10 times. Therefore, GMGH has broad application prospects as a potential water-retaining agent for desertification control.
Application of Superhydrophobic Mesh Coated by PDMS/TiO2 Nanocomposites for Oil/Water Separation
Authors: Cao Kun , Huang Xi , Pan Jie
Published: December 2022

Superhydrophobic materials have recently attracted great interest from both academia and industry due to their promising applications in self-cleaning, oil–water separation, etc. Here, we developed a facile method to prepare hybrid PDMS/TiO2 fiber for superhydrophobic coatings. TiO2 could be uniformly distributed into PDMS, forming a hierarchical micro/nano structure on the surface of the substrate. The contact angle of the superhydrophobic coating could reach as high as 155°. The superhydrophobic coating possessed good self-cleaning performance, corrosion resistance, and durability. It was found that gravity-driven oil–water separation was achieved using stainless steel mesh coated with the PDMS/TiO2 coating. More importantly, the coated filter paper could not only separate oil and pure water but also corrosive solutions, including the salt, acid, and alkali solution.
Application Status and Development Trend of Continuous Casting Reduction Technology: A Review
Authors: Nian Yi , Zhang Liqiang , Zhang Chaojie , Ali Naqash , Chu Jianhua , Li Jiale , Liu Xiang
Published: December 2022

Continuous casting is a dominant steelmaking process due to its steady-state nature, enhanced yield of steel production, and low consumption of energy and manpower. However, the production of defect-free cast products is still a big challenge, as the internal defects, including macro-segregation of alloying elements, cracks, and pores, can be easily formed during the solidification process, which seriously deteriorates the microstructure and mechanical properties of the cast products. Therefore, this paper puts forward the common solutions to overcome these problematic issues. The reduction technology can effectively improve the center segregation of the billet, bloom, and slab. The history of the development of the reduction technology is summarized and classified according to the variations in research trend. Furthermore, the basic principles and parameters of reduction technology are described to implement them in the actual production process. This paper compares the similarities and differences between soft reduction (SR) and heavy reduction (HR) technologies with a particular focus on the theoretical research of HR technology and further elaborates the key parameter and equipment problems during implementation of HR. Moreover, this paper also considers the HR technology adopted by Baosteel as a case study, which helped to put forward some viewpoints for the future development of reduction technology.
Investigation and Characterisation of New Eco-Friendly Cosmetic Ingredients Based on Probiotic Bacteria Ferment Filtrates in Combination with Alginite Mineral
Authors: Tóth Pál , Németh Áron
Published: December 2022

In light of the fact that three of the five healthiest meals on earth are fermented, fermentation came into focus of both customers, product developers, and researchers all around the world. Even in the cosmetics industry, fermented cosmetics have been increasingly introduced, creating a market emphasising the positive image that healthy fermented substances are environment-friendly and that it also aids skin health. Moreover, discovering usages for various naturally occurring organo-mineral rocks is a growing area of research. Thus, this study’s aim was to combine the benefits of alginite and Lactobacilli (LAB) for cosmetic applications and investigate their combined effect on the skin considering the fermentation parameters as well, such as biomass and lactic acid concentration. The examined LAB strains were Lactobacillus rhamnosus, Lactobacillus acidophilus, Limosilactobacillus reuteri, and Lactococcus lactis, and a non-LAB probiotic strain Bifidobacterium adolescentis was also studied for the same purposes. The cell-free broth, also called as “filtrates”, of the fermentations—both those that included alginite and those that did not—were tested for skin moisturising with a corneometer and for antioxidant activity with DPPH scavenging, as well as for skin-whitening properties with the inhibition of mushroom tyrosinase. The findings suggest that the combination of alginite and Limosilactobacillus reuteri is a potential novel cosmeceutical component with skin tanning capabilities. This result may help create more readily available, environmentally friendly, natural, and sustainable cosmetic ingredients.
Action Possibilities Enhancing the Spiritual Wellbeing of Young Children: Applying Affordance Theory to the Godly Play Room
Authors: Hyde Brendan
Published: December 2022

Godly Play is an approach to religious education for young children between the ages of three and eight. The Godly Play room, modelled on Montessori’s prepared environment, provides opportunities for young children to respond to Sacred stories, Parables and Liturgical actions presented by the Storyteller through art using any of the materials available to them. However, there is a paucity of research into how different spatial affordances may enhance opportunities for spiritual development in the Godly Play room. This article examines the Godly Play room through the lens of affordance theory. It applies elements of the notion of affordances to three documented anecdotes of Godly Play storytellers to show how particular action possibilities enhance opportunities for spiritual development and wellbeing. The analysis highlights the importance of the Storyteller’s guidance, the readily accessible materials, and the dedicated space in which Godly Play is undertaken.
DSM Generation from Multi-View High-Resolution Satellite Images Based on the Photometric Mesh Refinement Method
Authors: Lv Benchao , Liu Jianchen , Wang Ping , Yasir Muhammad
Published: December 2022

Automatic reconstruction of DSMs from satellite images is a hot issue in the field of photogrammetry. Nowadays, most state-of-the-art pipelines produce 2.5D products. In order to solve some shortcomings of traditional algorithms and expand the means of updating digital surface models, a DSM generation method based on variational mesh refinement of satellite stereo image pairs to recover 3D surfaces from coarse input is proposed. Specifically, the initial coarse mesh is constructed first and the geometric features of the generated 3D mesh model are then optimized by using the information of the original images, while the 3D mesh subdivision is constrained by combining the image’s texture information and projection information, with subdivision optimization of the mesh model finally achieved. The results of this method are compared qualitatively and quantitatively with those of the commercial software PCI and the SGM method. The experimental results show that the generated 3D digital surface has clearer edge contours, more refined planar textures, and sufficient model accuracy to match well with the actual conditions of the ground surface, proving the effectiveness of the method. The method is advantageous for conducting research on true 3D products in complex urban areas and can generate complete DSM products with the input of rough meshes, thus indicating it has some development prospects.
Sonar Image Target Detection Based on Style Transfer Learning and Random Shape of Noise under Zero Shot Target
Authors: Xi Jier , Ye Xiufen , Li Chuanlong
Published: December 2022

With the development of sonar technology, sonar images have been widely used to detect targets. However, there are many challenges for sonar images in terms of object detection. For example, the detectable targets in the sonar data are more sparse than those in optical images, the real underwater scanning experiment is complicated, and the sonar image styles produced by different types of sonar equipment due to their different characteristics are inconsistent, which makes it difficult to use them for sonar object detection and recognition algorithms. In order to solve these problems, we propose a novel sonar image object-detection method based on style learning and random noise with various shapes. Sonar style target sample images are generated through style transfer, which enhances insufficient sonar objects image. By introducing various noise shapes, which included points, lines, and rectangles, the problems of mud and sand obstruction and a mutilated target in the real environment are solved, and the single poses of the sonar image target is improved by fusing multiple poses of optical image target. In the meantime, a method of feature enhancement is proposed to solve the issue of missing key features when using style transfer on optical images directly. The experimental results show that our method achieves better precision.
AdaSplats: Adaptive Splatting of Point Clouds for Accurate 3D Modeling and Real-Time High-Fidelity LiDAR Simulation
Authors: Richa Jean Pierre , Deschaud Jean-Emmanuel , Goulette François , Dalmasso Nicolas
Published: December 2022

LiDAR sensors provide rich 3D information about their surroundings and are becoming increasingly important for autonomous vehicles tasks such as localization, semantic segmentation, object detection, and tracking. Simulation accelerates the testing, validation, and deployment of autonomous vehicles while also reducing cost and eliminating the risks of testing in real-world scenarios. We address the problem of high-fidelity LiDAR simulation and present a pipeline that leverages real-world point clouds acquired by mobile mapping systems. Point-based geometry representations, more specifically splats (2D oriented disks with normals), have proven their ability to accurately model the underlying surface in large point clouds, mainly with uniform density. We introduce an adaptive splat generation method that accurately models the underlying 3D geometry to handle real-world point clouds with variable densities, especially for thin structures. Moreover, we introduce a fast LiDAR sensor simulator, working in the splatted model, that leverages the GPU parallel architecture with an acceleration structure while focusing on efficiently handling large point clouds. We test our LiDAR simulation in real-world conditions, showing qualitative and quantitative results compared to basic splatting and meshing techniques, demonstrating the interest of our modeling technique.
Identification and Analysis of Landslides in the Ahai Reservoir Area of the Jinsha River Basin Using a Combination of DS-InSAR, Optical Images, and Field Surveys
Authors: Li Yongfa , Zuo Xiaoqing , Zhu Daming , Wu Wenhao , Yang Xu , Guo Shipeng , Shi Chao , Huang Cheng , Li Fang , Liu Xinyu
Published: December 2022

We employed ascending and descending Sentinel-1A, optical image data, and field investigation methods to identify and monitor landslides in the Jinsha River Basin to overcome the difficulties associated with the use of a single method and its inaccuracies in identifying landslides in the alpine and canyon areas. Using distributed scatterer-synthetic aperture radar interferometry (DS-InSAR), Sentinel-1A ascending and descending data were integrated to obtain surface deformation information within the study area from July 2017 to May 2019. Thereafter, high-resolution optical image data were introduced to interpret landslides, and field investigations were conducted to validate landslides. These combined methods enabled the assessment of spatiotemporal evolutionary characteristics, and their accuracy in identifying typical landslides was verified. The results showed that the use of both ascending and descending data effectively avoided certain problems, such as the inability to identify certain landslide hazards or the retrieval of incomplete identification results due to geometric distortion associated with single-track SAR imaging. The combined use of these methods effectively improves the timeliness and verification of the accuracy of landslides. Fifteen landslides were identified in the study area, which had different degrees of tension cracks, vertical dislocations, and slip marks that were verified in the field. Of these, two landslides show serious deformation characteristics that currently pose a serious threat to lives and infrastructure. Follow-up monitoring of these landslides is essential. These findings will assist in obtaining comprehensive information about the distribution of landslides and their deformation developmental trends in the Ahai Reservoir area of the Jinsha River Basin and show that the combined methods can be employed to prevent and control landslides in this area.
Detecting Spatially Non-Stationary between Vegetation and Related Factors in the Yellow River Basin from 1986 to 2021 Using Multiscale Geographically Weighted Regression Based on Landsat
Authors: Wang Xiaolei , Shi Shouhai , Zhao Xue , Hu Zirong , Hou Mei , Xu Lei
Published: December 2022

As an important ecological barrier in northern China, the ecological environment of the Yellow River Basin (YRB) has been greatly improved in recent decades. However, due to spatially non-stationarity, the contribution of human activities and natural factors to vegetation restoration may exhibit different coupling effects in various areas. In this paper, the Normalized Difference Vegetation Index (NDVI) of the YRB from 1986 to 2021 was used as the dependent variable, and terrain, meteorological, and socioeconomic factors were used as independent variables. With the help of Multiscale Geographically Weighted Regression (MGWR), which could handle the scale difference well, combined with Ordinary Least Squares (OLS) and traditional Geographically Weighted Regression (GWR), the spatial non-stationary relationship between vegetation and related factors was discussed. The results showed that: (1) The vegetation was subject to fluctuating changes from 1986 to 2021, mainly improving, with a growth rate of 0.0018/year; the spatial distribution pattern of vegetation in the basin was high in the southeast and low in the northwest. (2) Compared with the OLS and GWR, the MGWR could better explain the relationship between vegetation and various factors. (3) The response scale of vegetation and related factors was significantly variant, and this scale changed with time. The effect scale of terrain factor is lower than climate and social factors. (4) There was obvious spatial heterogeneity in the effects of various influencing factors on vegetation. The vegetation of the upstream was mainly positively affected by mean annual temperature (coefficients ∈ [1.507, 1.784]); while potential evapotranspiration was the dominant factor of vegetation in the middle and lower reaches of the basin (coefficients ∈ [−1.724, −1.704]); it was worth noting that the influence of social factors on vegetation was relatively small. This study deeply explores the spatial non-stationarity of vegetation and various related factors, thereby revealing the evolution law of vegetation pattern and providing scientific support for monitoring and improving the ecological environment quality of the YRB.
Evaluation of Six Satellite Precipitation Products over the Chinese Mainland
Authors: Liu Zhenwei , Di Zhenhua , Qin Peihua , Zhang Shenglei , Ma Qian
Published: December 2022

Satellite precipitation products have been applied to many research fields due to their high spatial and temporal resolution. However, satellite inversion of precipitation is indirect, and different inversion algorithms limit the accuracy of the measurement results, which leads to great uncertainty. Therefore, it is of great significance to quantify and record the error characteristics of different satellite precipitation products for their better application in hydrology and other research fields. In this study, based on CN05.1, which is a set of site–based interpolation data, we evaluated the accuracies of the six satellite precipitation datasets (IMERG–E, IMERG–L, IMERG–F, GSMaP, CMORPH, and PERSIANN–CDR) at different temporal scales (daily, monthly, and yearly) in mainland China for the period from 2001 to 2015. The results were as follows: (1) In terms of mean precipitation, IMERG–F was superior to other data in all areas. IMERG products and PERANN–CDR performed better than other products at all scales and were more suitable for precipitation research in mainland China. Site correction can effectively improve the accuracy of product inversion, so IMERG–F was significantly better than IMERG–E and IMERG–L. (2) Except PERSIANN–CDR, all precipitation products underestimated precipitation in the range of 1–4 mm/day and had a high coincidence with CN05.1 in the range of 4–128 mm/day. (3) The performance of six types of satellite precipitation products in summer was better than that in winter. However, the error was larger in seasons with more precipitation. (4) In the Qinghai–Tibet Plateau, where there are few stations, the inversion of precipitation by satellite products is closer to the actual situation, which is noteworthy. These results help users understand the characteristics of these products and improve algorithms for future algorithm developers.
Lightweight Multimechanism Deep Feature Enhancement Network for Infrared Small-Target Detection
Authors: Zhang Yi , Nian Bingkun , Zhang Yan , Zhang Yu , Ling Feng
Published: December 2022

Specific to the problem of infrared small-target detection in complex backgrounds, a multimechanism deep feature enhancement network model (MDFENet) was proposed. A lightweight multimechanism attention collaborative fusion module was proposed to efficiently fuse low-level features and high-level features to solve the problem that small infrared targets are easy to annihilate in the deep layer of the network. Based on the analysis of the background and target data, a normalized loss function was proposed, which integrates the segmentation threshold selection into the network and normalizes the probability of the network output to simulate a step function and reflect relative differences. Aiming at the sparseness of infrared target features, we used the subpixel convolution method to upsample the features to obtain high-resolution feature images while expanding the size of the feature map. We conducted detailed comparison and ablation experiments, comparing MDFENet with ALCNet, APGCNet, and other state-of-the-art networks to verify the effectiveness and efficiency of the network. Results show that the MDFENet algorithm achieves the optimal result in the balance of detection efficiency and lightweightedness on two datasets.
Improving Spatial Resolution of Satellite Imagery Using Generative Adversarial Networks and Window Functions
Authors: Karwowska Kinga , Wierzbicki Damian
Published: December 2022

Dynamic technological progress has contributed to the development of systems imaging of the Earth’s surface as well as data mining methods. One such example is super-resolution (SR) techniques that allow for the improvement of the spatial resolution of satellite imagery on the basis of a low-resolution image (LR) and an algorithm using deep neural networks. The limitation of these solutions is the input size parameter, which defines the image size that is adopted by a given neural network. Unfortunately, the value of this parameter is often much smaller than the size of the images obtained by Earth Observation satellites. In this article, we presented a new methodology for improving the resolution of an entire satellite image, using a window function. In addition, we conducted research to improve the resolution of satellite images acquired with the World View 2 satellite using the ESRGAN network, we determined the number of buffer pixels that will make it possible to obtain the best image quality. The best reconstruction of the entire satellite imagery using generative neural networks was obtained using a Triangular window (for 10% coverage). The Hann-Poisson window worked best when more overlap between images was used.
Conception of a High-Level Perception and Localization System for Autonomous Driving
Authors: Dauptain Xavier , Koné Aboubakar , Grolleau Damien , Cerezo Veronique , Gennesseaux Manuela , Do Minh-Tan
Published: December 2022

This paper describes the conception of a high level, compact, scalable, and long autonomy perception and localization system for autonomous driving applications. Our benchmark is composed of a high resolution lidar (128 channels), a stereo global shutter camera, an inertial navigation system, a time server, and an embedded computer. In addition, in order to acquire data and build multi-modal datasets, this system embeds two perception algorithms (RBNN detection, DCNN detection) and one localization algorithm (lidar-based localization) to provide real-time advanced information such as object detection and localization in challenging environments (lack of GPS). In order to train and evaluate the perception algorithms, a dataset is built from 10,000 annotated lidar frames from various drives carried out under different weather conditions and different traffic and population densities. The performances of the three algorithms are competitive with the state-of-the-art. Moreover, the processing time of these algorithms are compatible with real-time autonomous driving applications. By providing directly accurate advanced outputs, this system might significantly facilitate the work of researchers and engineers with respect to planning and control modules. Thus, this study intends to contribute to democratizing access to autonomous vehicle research platforms.
Enhanced Heart Rate Prediction Model Using Damped Least-Squares Algorithm
Authors: An Angela , Al-Fawa’reh Mohammad , Kang James Jin
Published: December 2022

Monitoring a patient’s vital signs is considered one of the most challenging problems in telehealth systems, especially when patients reside in remote locations. Companies now use IoT devices such as wearable devices to participate in telehealth systems. However, the steady adoption of wearables can result in a significant increase in the volume of data being collected and transmitted. As these devices run on limited battery power, they can run out of power quickly due to the high processing requirements of the device for data collection and transmission. Given the importance of medical data, it is imperative that all transmitted data adhere to strict integrity and availability requirements. Reducing the volume of healthcare data and the frequency of transmission can improve a device’s battery life via an inference algorithm. Furthermore, this approach creates issues for improving transmission metrics related to accuracy and efficiency, which are traded-off against each other, with increasing accuracy reducing efficiency. This paper demonstrates that machine learning (ML) can be used to overcome the trade-off problem. The damped least-squares algorithm (DLSA) is used to enhance both metrics by taking fewer samples for transmission whilst maintaining accuracy. The algorithm is tested with a standard heart rate dataset to compare the metrics. The results showed that the DLSA provides the best performance, with an efficiency of 3.33 times for reduced sample data size and an accuracy of 95.6%, with similar accuracies observed in seven different sampling cases adopted for testing that demonstrate improved efficiency. This proposed method significantly improve both metrics using ML without sacrificing one metric over the other compared to existing methods with high efficiency.
Improvement of Visible Photodetection of Chemical Vapor Deposition-Grown MoS2 Devices via Graphene/Au Contacts
Authors: Hwa Yeongsik , Chee Sang-Soo
Published: December 2022

Two-dimensional (2D) molybdenum disulfide (MoS2) is a promising material for constructing high-performance visible photosensor arrays because of its high mobility and scale-up process. These distinct properties enable the construction of practical optoelectrical sensor arrays. However, contact engineering for MoS2 films is not still optimized. In this work, we inserted a graphene interlayer between the MoS2 films and Au contacts (graphene/Au) via the wet-transfer method to boost the device performance. Using graphene/Au contacts, outstanding electrical properties, namely field-effect mobility of 12.06 cm2/V∙s, on/off current ratio of 1.0 × 107, and responsivity of 610 A/W under illumination at 640 nm, were achieved. These favorable results were from the Fermi-level depinning effect induced by the graphene interlayer. Our results may help to construct large-area photonic sensor arrays based on 2D materials.
Development of a Flexible Integrated Self-Calibrating MEMS Pressure Sensor Using a Liquid-to-Vapor Phase Change
Authors: Kang Yuhong , Mouring Scott , de Clerck Albrey , Mao Shuo , Ng Wing , Ruan Hang
Published: December 2022

Self-calibration capabilities for flexible pressure sensors are greatly needed for fluid dynamic analysis, structure health monitoring and wearable sensing applications to compensate, in situ and in real time, for sensor drifts, nonlinearity effects, and hysteresis. Currently, very few self-calibrating pressure sensors can be found in the literature, let alone in flexible formats. This paper presents a flexible self-calibrating pressure sensor fabricated from a silicon-on-insulator wafer and bonded on a polyimide substrate. The sensor chip is made of four piezoresistors arranged in a Wheatstone bridge configuration on a pressure-sensitive membrane, integrated with a gold thin film-based reference cavity heater, and two thermistors. With a liquid-to-vapor thermopneumatic actuation system, the sensor can create precise in-cavity pressure for self-calibration. Compared with the previous work related to the single-phase air-only counterpart, testing of this two-phase sensor demonstrated that adding the water liquid-to-vapor phase change can improve the effective range of self-calibration from 3 psi to 9.5 psi without increasing the power consumption of the cavity micro-heater. The calibration time can be further improved to a few seconds with a pulsed heating power.
The Effect of Initial Water Content and Density on the Swelling-Shrinkage and Cracking Characteristics of Compacted Clay
Authors: Zhong Yuqing , Cai Guanghua , Zeng Gang
Published: December 2022

The swelling-shrinkage and cracking characteristics of compacted clay under the coupling effect of initial conditions are rarely studied. The dry-wet cycle test of compacted clay with varying initial water contents and densities was performed in this study; the size and cracking conditions were investigated. The results showed that when the initial moisture content was 21% and the dry density was 1.65 g/cm3, the longitudinal expansion amount of the compacted clay was relatively small. However, it was rather large when the initial water content was 17% and 19%. Under the same dry density, the final vertical shrinkage ratio of the sample with a water content of 21% was the smallest, while that of the samples with a water content of 23% and 25% was rather big. Under the same water content, the final vertical shrinkage ratio decreased with the increase in dry density. After three wetting-drying cycles, compacted clay with a dry density of 1.65 g/cm3 and an optimal initial water content of 21% produced the fewest cracks and had the lowest cracking factor (CF) (only 7.58%). The compacted clay specimens with the dry densities of 1.55 g/cm3 and 1.60 g/cm3 had rather significant cracking at the same initial moisture content of 21%. The mercury intrusion porosimetry (MIP) test demonstrated that in the first two dry and wet cycles, the distribution of large pores decreased and that of tiny pores increased. After the third cycle, the distribution of small and medium pores decreased slightly. The results of this study will provide theoretical guidance for selecting cover soils in landfills.
Advanced Treatment of Direct Dye Wastewater Using Novel Composites Produced from Hoshanar and Sunny Grey Waste
Authors: Akhtar Amna , Hanif Muhammad , Rashid Umer , Bhatti Ijaz , Alharthi Fahad , Kazerooni Elham
Published: December 2022

The present project is designed to investigate the potential of hoshanar and sunny grey marble wastes to remove direct violet 51 dye from wastewater using adsorption process. The effect of different parameters such as pH, adsorbent dose, initial dye concentration, and contact time were studied to optimize the results of adsorption process. Different isothermic models (Temkin, Langmuir isotherm, Freundlich isotherm, Harkin Jura, and Dubinin-Radushkevich models) and kinetic models (pseudo-first order and pseudo-second order) were employed to adsorption data to find out the best fit model, i.e., Langmuir isotherm and pseudo-second order model. Marble waste composites were also characterized by using different techniques such as scanning electron microscopy (SEM) for surface morphology and Fourier transform infrared spectroscopy (FTIR) to determine chemical arrangements, structure, and functional groups of adsorbents. Hoshanar treated with a mixture of potassium ferricyanide, and sodium meta silicate showed maximum adsorption capacity of 105.31 mg/g as compared to untreated hoshanar (67.19.45 mg/g). So, the conversion of HM into HMPS makes it an affordable, efficient, and available adsorbent for wastewater treatment.