bluuebunny/crossref_metadata_2025 huggingface dataset:
Expression of RsPORB Is Associated with Radish Root Color
Authors: Kim Da-Hye , Lim Sun-Hyung , Lee Jong-Yeol
Published: June 2023

Radish (Raphanus sativus) plants exhibit varied root colors due to the accumulation of chlorophylls and anthocyanins compounds that are beneficial for both human health and visual quality. The mechanisms of chlorophyll biosynthesis have been extensively studied in foliar tissues but remain largely unknown in other tissues. In this study, we examined the role of NADPH:protochlorophyllide oxidoreductases (PORs), which are key enzymes in chlorophyll biosynthesis, in radish roots. The transcript level of RsPORB was abundantly expressed in green roots and positively correlated with chlorophyll content in radish roots. Sequences of the RsPORB coding region were identical between white (948) and green (847) radish breeding lines. Additionally, virus-induced gene silencing assay with RsPORB exhibited reduced chlorophyll contents, verifying that RsPORB is a functional enzyme for chlorophyll biosynthesis. Sequence comparison of RsPORB promoters from white and green radishes showed several insertions and deletions (InDels) and single-nucleotide polymorphisms. Promoter activation assays using radish root protoplasts verified that InDels of the RsPORB promoter contribute to its expression level. These results suggested that RsPORB is one of the key genes underlying chlorophyll biosynthesis and green coloration in non-foliar tissues, such as roots.
Alternative Rooting Methods for Medicinal Cannabis Cultivation in Denmark—Preliminary Results
Authors: Favero Bruno Trevenzoli , Salomonsen Jacob Kromann , Lütken Henrik
Published: June 2023

Cannabis sativa L. is typically propagated through micropropagation or vegetative cuttings, but the use of root-inducing hormones, such as indole-3-butyric acid (IBA), is not allowed for growing medicinal cannabis in Denmark. This study examined alternative rooting treatments, including Rhizobium rhizogenes inoculation, water-only as well as IBA treatments, in eight cannabis cultivars. PCR on root tissue suggested that 19% of R. rhizogenes-inoculated cuttings were transformed. These were derived from “Herijuana”, “Wild Thailand”, “Motherlode Kush”, and “Bruce Banner”, indicating a variation in cultivar susceptibility toward R. rhizogenes. A 100% rooting success was achieved regardless of cultivar and treatment, suggesting that alternative rooting agents are not required for efficient vegetative propagation. However, rooted cuttings differed in shoot morphology with improved shoot growth in cuttings treated with R. rhizogenes (195 ± 7 mm) or water (185 ± 7 mm) while inhibited shoot growth under IBA treatment (123 ± 6 mm). This could have advantageous economic implications should cuttings not treated with hormone reach maturity faster than those exposed to the hormone, thereby contributing to completing a full growing cycle more effectively. IBA exposure increased root length, root dry weight, and root/shoot dry weight ratio compared to cuttings treated with R. rhizogenes or water but simultaneously inhibited shoot growth compared to these.
Cassava Witches’ Broom Disease in Southeast Asia: A Review of Its Distribution and Associated Symptoms
Authors: Pardo Juan M. , Chittarath Khonesavanh , Vongphachanh Pinkham , Hang Le Thi , Oeurn Samoul , Arinaitwe Warren , Rodriguez Rafael , Sophearith Sok , Malik Al Imran , Cuellar Wilmer J.
Published: June 2023

Cassava witches’ broom disease (CWBD) is one of the main diseases of cassava in Southeast Asia (SEA). Affected cassava plants show reduced internodal length and proliferation of leaves (phyllody) in the middle and top part of the plant, which results in reduced root yields of 50% or more. It is thought to be caused by phytoplasma; however, despite its widespread distribution in SEA still little is known about CWBD pathology. The overarching goal of this study was to review and corroborate published information on CWBD biology and epidemiology considering recent field observations. We report the following: (1) CWBD symptoms are conserved and persistent in SEA and are distinct from what has been reported as witches’ broom in Argentina and Brazil. (2) In comparison with cassava mosaic disease, another major disease of cassava in SEA, symptoms of CWBD develop later. (3) Phytoplasma detected in CWBD-affected plants belong to different ribosomal groups and there is no association study available indicating phytoplasma as the causing agent of CWBD. These findings are essential clues for designing surveillance and management strategies and for future studies to better understand the biology, tissue localization and spatial spread of CWBD in SEA and other potential risk areas.
Foliar Nutrition Influences Yield, Nut Quality and Kernel Composition in Hazelnut cv Mortarella
Authors: Pannico Antonio , Modarelli Giuseppe Carlo , Stazi Silvia Rita , Giaccone Matteo , Romano Raffaele , Rouphael Youssef , Cirillo Chiara
Published: June 2023

In hazelnut, foliar nutrition is utilized globally to integrate microelement deficiencies and optimize their assimilation and effects on yield performances. Nevertheless, nut quality and kernel composition can be positively affected by foliar nutrition. Recently, several studies pointed out the need for increasing the sustainability of orchard nutrition by proposing the management of not only micronutrients, but also main components, such as nitrogen, through foliar spraying. In our study, different foliar fertilizers were used to understand the effectiveness of supporting hazelnut productivity and nut and kernel quality. Water was used as a control. Foliar fertilizations affected tree annual vegetative growth, improved kernel weight and decreased the incidence of blanks compared to the control. Differences in fat, protein, and carbohydrate concentration were also found among treatments, with increased fat concentrations and total polyphenols content in fertilized treatments. Foliar fertilization improved the oil composition of the kernels, though fatty acid composition responded differently to nutrients spray. Oleic acid concentration was promoted, while palmitic acid concentration was reduced in fertilized plants compared to control trees. Furthermore, CD and B trees were characterized by an increase in the ratio of unsaturated/saturated fatty acids compared to untreated trees. Finally, foliar spraying improved lipid stability compared to the control due to higher total polyphenol concentration.
Stimulation of Chondrocyte and Bone Marrow Mesenchymal Stem Cell Chondrogenic Response by Polypyrrole and Polypyrrole/Gold Nanoparticles
Authors: Uzieliene Ilona , Popov Anton , Lisyte Viktorija , Kugaudaite Gabija , Bialaglovyte Paulina , Vaiciuleviciute Raminta , Kvederas Giedrius , Bernotiene Eiva , Ramanaviciene Almira
Published: June 2023

Bone marrow mesenchymal stem cells (BMMSCs) possess a strong ability to differentiate into the chondrogenic lineage, which is important for cartilage regeneration. External stimuli, such as electrical stimulation (ES), are frequently studied for chondrogenic differentiation of BMMSCs; however, the application of conductive polymers such as polypyrrole (Ppy), has never been used for stimulating BMMSCs chondrogenesis in vitro before. Thus, the aim of this study was to evaluate the chondrogenic potential of human BMMSCs after stimulation with Ppy nanoparticles (Ppy NPs) and compare them to cartilage-derived chondrocytes. In this study, we tested Ppy NPs without and with 13 nm gold NPs (Ppy/Au) for BMMSCs and chondrocyte proliferation, viability, and chondrogenic differentiation for 21 days, without the use of ES. The results demonstrated significantly higher amounts of cartilage oligomeric matrix protein (COMP) in BMMSCs stimulated with Ppy and Ppy/Au NPs, as compared to the control. The expression of chondrogenic genes (SOX9, ACAN, COL2A1) in BMMSCs and chondrocytes were upregulated by Ppy and Ppy/Au NPs, as compared to controls. Histological staining with safranin-O indicated higher extracellular matrix production in Ppy and Ppy/Au NPs stimulated samples, as compared to controls. In conclusion, Ppy and Ppy/Au NPs stimulate BMMSC chondrogenic differentiation; however, BMMSCs were more responsive to Ppy, while chondrocytes possessed a stronger chondrogenic response to Ppy/Au NPs.
Synthesis and Properties of the Novel High-Performance Hydroxyl-Terminated Liquid Fluoroelastomer
Authors: Li Donghan , Yang Chen , Li Ping , Yu Lu , Zhao Shufa , Li Long , Kang Hailan , Yang Feng , Fang Qinghong
Published: June 2023

Functional liquid fluoroelastomers are in high demand in new energy fields. And these materials have potential applications in high-performance sealing materials and as electrode materials. In this study, a novel high-performance hydroxyl-terminated liquid fluoroelastomer (t-HTLF) with a high fluorine content, temperature resistance, and curing efficiency was synthesised from a terpolymer of vinylidene fluoride (VDF), tetrafluoroethylene (TFE), and hexafluoropylene (HFP). A carboxyl-terminated liquid fluoroelastomer (t-CTLF) with controllable molar mass and end-group content was first prepared from a poly(VDF-ter-TFE-ter-HFP) terpolymer using a unique oxidative degradation method. Subsequently, an efficient “one-step” reduction of the carboxyl groups (COOH) in t-CTLF into hydroxyl groups (OH) was achieved via the functional-group conversion method using lithium aluminium hydride (LiAlH4) as the reductant. Thus, t-HTLF with a controllable molar mass and end-group content and highly active end groups was synthesised. Owing to the efficient curing reaction between OH and isocyanate groups (NCO), the cured t-HTLF exhibits good surface properties, thermal properties, and chemical stability. The thermal decomposition temperature (Td) of the cured t-HTLF reaches 334 °C, and it exhibits hydrophobicity. The oxidative degradation, reduction, and curing reaction mechanisms were also determined. The effects of solvent dosage, reaction temperature, reaction time, and ratio of the reductant to the COOH content on the carboxyl conversion were also systematically investigated. An efficient reduction system comprising LiAlH4 can not only achieve an efficient conversion of the COOH groups in t-CTLF to OH groups but also the in situ hydrogenation and addition reactions of residual double bonds (C=C) groups in the chain, such that the thermal stability and terminal activity of the product are improved while maintaining a high fluorine content.
Improving Surface Wear Resistance of Polyimide by Inserting KH550 Grafted GO
Authors: Liu Chen , Song Jingfu , Zhao Gai , Ding Qingjun
Published: June 2023

To improve the wear resistance of polyimide (PI), surface modification was developed. In this study, the tribological properties of graphene (GN), graphene oxide (GO), and KH550-grafted graphene oxide (K5-GO) modified PI were evaluated by molecular dynamics (MD) at the atomic level. The findings indicated that the addition of nanomaterials can significantly enhance the friction performance of PI. The friction coefficient of PI composites decreased from 0.253 to 0.232, 0.136, and 0.079 after coating GN, GO and K5-GO, respectively. Among them, the K5-GO/PI exhibited the best surface wear resistance. Importantly, the mechanism behind the modification of PI was thoroughly revealed by observing the wear state, analyzing the changes of interfacial interactions, interfacial temperature, and relative concentration.
Blank Strip Filling for Logging Electrical Imaging Based on Multiscale Generative Adversarial Network
Authors: Sun Qifeng , Su Naiyuan , Gong Faming , Du Qizhen
Published: June 2023

The Fullbore Formation Micro Imager (FMI) represents a proficient method for examining subterranean oil and gas deposits. Despite its effectiveness, due to the inherent configuration of the borehole and the logging apparatus, the micro-resistivity imaging tool cannot achieve complete coverage. This limitation manifests as blank regions on the resulting micro-resistivity logging images, thus posing a challenge to obtaining a comprehensive analysis. In order to ensure the accuracy of subsequent interpretation, it is necessary to fill these blank strips. Traditional inpainting methods can only capture surface features of an image, and can only repair simple structures effectively. However, they often fail to produce satisfactory results when it comes to filling in complex images, such as carbonate formations. In order to address the aforementioned issues, we propose a multiscale generative adversarial network-based image inpainting method using U-Net. Firstly, in order to better fill the local texture details of complex well logging images, two discriminators (global and local) are introduced to ensure the global and local consistency of the image; the local discriminator can better focus on the texture features of the image to provide better texture details. Secondly, in response to the problem of feature loss caused by max pooling in U-Net during down-sampling, the convolution, with a stride of two, is used to reduce dimensionality while also enhancing the descriptive ability of the network. Dilated convolution is also used to replace ordinary convolution, and multiscale contextual information is captured by setting different dilation rates. Finally, we introduce residual blocks on the U-Net network in order to address the degradation problem caused by the increase in network depth, thus improving the quality of the filled logging images. The experiment demonstrates that, in contrast to the majority of existing filling algorithms, the proposed method attains superior outcomes when dealing with the images of intricate lithology.
Numerical Simulation of the Effect of Heat Conductivity on Proton Exchange Membrane Fuel Cell Performance in Different Axis Directions
Authors: Zhao Longsheng , Shang Kang , Wang Jiyao , Chen Zhenqian
Published: June 2023

In this paper, the effect of changes in the thermal conductivity of porous electrodes in three coordinate directions on the capability of proton exchange membrane fuel cells is investigated on the basis of current density versus voltammetry curves, and the temperature distribution and water-carrying capacity distribution of the membrane. The results show that when the cell discharge voltage of the PEMFC is 0.3 V, the thermal conductivity in the Z-direction of the porous electrode has a greater effect on the performance of the PEMFC than in the other directions, with the thermal conductivity in the X- and Y-directions of the porous electrode having less than a 5% effect on the performance of the PEMFC, which can therefore be neglected. When the thermal conductivity of the porous electrode in the Z-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 5.78% and 5.87%, respectively, and when the thermal conductivity of the porous electrode in the X-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 2.09% and 2.89%, and the PEMFC performance is improved by 1.51% and 2.00% when the Y-direction thermal conductivity of the porous electrode of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), respectively. The improvement in performance decreases with increasing thermal conductivity, because the thickness of the porous electrode is too thin. Since the side of the model is set to adiabatic heat exchange conditions, while the top and bottom surfaces are set to natural convection heat exchange conditions, the Z-direction thermal conductivity of the porous electrode plays the most important role in the temperature distribution of the PEMFC. The Z-direction thermal conductivity of the porous electrode causes the temperature distribution of the PEMFC assembly to be more uniform, and the Z-direction thermal conductivity of the porous electrode also causes the area of the high-water-content region on the proton exchange membrane to significantly increase.
Digital Twin Implementation for Manufacturing of Adjuvants
Authors: Phalak Poonam , Tomba Emanuele , Jehoulet Philippe , Kapitan-Gnimdu André , Soladana Pablo Martin , Vagaggini Loredana , Brochier Maxime , Stevens Ben , Peel Thomas , Strodiot Laurent , Dessoy Sandrine
Published: June 2023

Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a microfluidic formation of lipid particles. The twin uses a hybrid model for estimating the current state of the process and predicting system behavior in real time. The twin is used to control the adjuvant particle size, a critical quality attribute, by varying process parameters such as the temperature and inlet flow rates. We describe steps in the design and implementation of the twin, starting from the conception of the mechanistic model, up to the generation of its surrogate model used as state estimator, PATs and the setup of the information technology—Operational technology architecture. We demonstrate the performance of the twin by introducing different disturbances in the process and comparing the effect on the product critical quality attributes with and without the control of the digital twin. Finally, we showcase the digital twin implementation for the process in good manufacturing practice, through an engineering run, which demonstrated the robustness of the process when controlled by the digital twin.
Fast Deflagration-to-Detonation Transition in Helical Tubes
Authors: Shamshin Igor O. , Aksenov Viktor S. , Kazachenko Maxim V. , Gusev Pavel A. , Frolov Sergey M.
Published: June 2023

When designing a new type of power plants operating on pulsed detonations of gaseous or liquid fuels, the concept of fast deflagration-to-detonation transition (FDDT) is used. According to the concept, a flame arising from a weak ignition source must accelerate so fast as to form an intense shock wave at a minimum distance from the ignition source so that the intensity of the shock wave is sufficient for fast shock-to-detonation transition by some additional arrangements. Hence, the FDDT concept implies the use of special means for flame acceleration and shock wave amplification. In this work, we study the FDDT using a pulsed detonation tube comprising a Shchelkin spiral and a helical tube section with ten coils as the means for flame acceleration and shock amplification (focusing), respectively. To attain the FDDT at the shortest distances for fuels of significantly different detonability, the diameter of the pulsed detonation tube is taken close to the limiting diameter of detonation propagation for air mixtures of regular hydrocarbon fuels (50 mm). Experiments are conducted with air mixtures of individual gaseous fuels (hydrogen, methane, propane, and ethylene) and binary fuel compositions (methane–hydrogen, propane–hydrogen, and ethylene–hydrogen) at normal pressure and temperature conditions. The use of a helical tube with ten coils is shown to considerably extend the fuel-lean concentration limits of detonation as compared to the straight tube and the tube with a helical section with two coils.
The Poor in Society, Resurrection from Social Death, and Latin American Liberation Theology
Authors: Sung Jung Mo
Published: June 2023

Does Latin American liberation theology, with its option for the poor, still have something to contribute in a global scenario marked by neoliberal globalization and the discussion of identity politics? Based on the practices of Father Júlio Lancelotti against aporophobia (phobia against the poor) and the hostile architecture in Brazil, this article discusses the notion of the priority of orthopraxis over orthodoxy, the process of reordering the place of the poor in society and in the state budgets, and the notion of liberation practices and criticizes the process of dehumanization in neoliberal culture, in which personal identity and belonging to a community are marked by the pattern of consumption and wealth. Finally, it shows how the practices of recognizing the humanity of the poorest can been seen as a resurrection from social death, as a form of liberation within history, and as the affirmation of faith in a God who does not distinguish between human beings, while the idol demands sacrifices of life from the poor.
Combining Radiative Transfer Model and Regression Algorithms for Estimating Aboveground Biomass of Grassland in West Ujimqin, China
Authors: Zhang Linjing , Gao Huimin , Zhang Xiaoxue
Published: June 2023

Grassland aboveground biomass (AGB) is a crucial indicator when studying the carbon sink of grassland ecosystems. The exploration of the grassland AGB inversion method with viable reproducibility is significant for promoting the practicability and efficiency of grassland quantitative monitoring. Therefore, this study provides a novel retrieval method for grassland AGB by coupling the PROSAIL (PROSPECT + SAIL) model and the random forest (RF) model on the basis of the lookup-table (LUT) method. These sensitive spectral characteristics were optimized to significantly correlate with AGB (ranging from 0.41 to 0.68, p < 0.001). Four methods were coupled with the PROSAIL model to estimate grassland AGB in the West Ujimqin grassland, including the LUT method, partial least square (PLSR), RF and support vector machine (SVM) models. The ill-posed inverse problem of the PROSAIL model was alleviated using the MODIS products-based algorithm. Inversion results using sensitive spectral characteristics showed that the PROSAIL + RF model offered the best performance (R2 = 0.70, RMSE = 21.65 g/m2 and RMESr = 27.62%), followed by the LUT-based method, which was higher than the PROSAIL + PLSR model. Relatively speaking, the PROSAIL + SVM model was more challenging in this study. The proposed method exhibited strong robustness and universality for AGB estimation in large-scale grassland without field measurements.
Spatial Population Distribution Data Disaggregation Based on SDGSAT-1 Nighttime Light and Land Use Data Using Guilin, China, as an Example
Authors: Liu Can , Chen Yu , Wei Yongming , Chen Fang
Published: June 2023

A high-resolution population distribution map is crucial for numerous applications such as urban planning, disaster management, public health, and resource allocation, and it plays a pivotal role in evaluating and making decisions to achieve the UN Sustainable Development Goals (SDGs). Although there are many population products derived from remote sensing nighttime light (NTL) and other auxiliary data, they are limited by the coarse spatial resolution of NTL data. As a result, the outcomes’ spatial resolution is restricted, and it cannot meet the requirements of some applications. To address this limitation, this study employs the nighttime light data provided by the SDGSAT-1 satellite, which has a spatial resolution of 10 m, and land use data as auxiliary data to disaggregate the population distribution data from WorldPop data (100 m resolution) to a high resolution of 10 m. The case study conducted in Guilin, China, using the multi-class weighted dasymetric mapping method shows that the total error during the disaggregation is 0.63%, and the accuracy of 146 towns in the study area is represented by an R2 of 0.99. In comparison to the WorldPop data, the result’s information entropy and spatial frequency increases by 345% and 1142%, respectively, which demonstrates the effectiveness of this approach in studying population distributions with high spatial resolution.
Semi-Supervised Person Detection in Aerial Images with Instance Segmentation and Maximum Mean Discrepancy Distance
Authors: Zhang Xiangqing , Feng Yan , Zhang Shun , Wang Nan , Mei Shaohui , He Mingyi
Published: June 2023

Detecting sparse, small, lost persons with only a few pixels in high-resolution aerial images was, is, and remains an important and difficult mission, in which a vital role is played by accurate monitoring and intelligent co-rescuing for the search and rescue (SaR) system. However, many problems have not been effectively solved in existing remote-vision-based SaR systems, such as the shortage of person samples in SaR scenarios and the low tolerance of small objects for bounding boxes. To address these issues, a copy-paste mechanism (ISCP) with semi-supervised object detection (SSOD) via instance segmentation and maximum mean discrepancy distance is proposed (MMD), which can provide highly robust, multi-task, and efficient aerial-based person detection for the prototype SaR system. Specifically, numerous pseudo-labels are obtained by accurately segmenting the instances of synthetic ISCP samples to obtain their boundaries. The SSOD trainer then uses soft weights to balance the prediction entropy of the loss function between the ground truth and unreliable labels. Moreover, a novel evaluation metric MMD for anchor-based detectors is proposed to elegantly compute the IoU of the bounding boxes. Extensive experiments and ablation studies on Heridal and optimized public datasets demonstrate that our approach is effective and achieves state-of-the-art person detection performance in aerial images.
Autonomous Multi-Floor Localization Based on Smartphone-Integrated Sensors and Pedestrian Indoor Network
Authors: Shi Chaoyang , Teng Wenxin , Zhang Yi , Yu Yue , Chen Liang , Chen Ruizhi , Li Qingquan
Published: June 2023

Autonomous localization without local wireless facilities is proven as an efficient way for realizing location-based services in complex urban environments. The precision of the current map-matching algorithms is subject to the poor ability of integrated sensor-based trajectory estimation and the efficient combination of pedestrian motion information and the pedestrian indoor network. This paper proposes an autonomous multi-floor localization framework based on smartphone-integrated sensors and pedestrian network matching (ML-ISNM). A robust data and model dual-driven pedestrian trajectory estimator is proposed for accurate integrated sensor-based positioning under different handheld modes and disturbed environments. A bi-directional long short-term memory (Bi-LSTM) network is further applied for floor identification using extracted environmental features and pedestrian motion features, and further combined with the indoor network matching algorithm for acquiring accurate location and floor observations. In the multi-source fusion procedure, an error ellipse-enhanced unscented Kalman filter is developed for the intelligent combination of a trajectory estimator, human motion constraints, and the extracted pedestrian network. Comprehensive experiments indicate that the presented ML-ISNM achieves autonomous and accurate multi-floor positioning performance in complex and large-scale urban buildings. The final evaluated average localization error was lower than 1.13 m without the assistance of wireless facilities or a navigation database.
Research and Evaluation on Dynamic Maintenance of an Elevation Datum Based on CORS Network Deformation
Authors: Liang Shenghao , Zhang Chuanyin , Jiang Tao , Wang Wei
Published: June 2023

This paper presents a method for dynamically maintaining a regional elevation datum using CORS stations as core nodes. By utilizing CORS station data and surface mass loading data (including land water storage, sea level, and atmospheric pressure), the normal height changes of each station can be determined and dynamically maintained. The validity of this method is verified using multiple leveling survey results from five CORS stations in Beijing’s subsidence area between January 2012 and June 2021. Results show that it is necessary to derive and correct the height anomaly variation of CORS stations caused by surface mass loading using the remove-calculate-restore method and the Green’s function integration method, with the influence of surface mass changes reaching a subcentimeter level. CORS stations exhibiting great observation quality achieve a mean accuracy of 2.7 mm in determining normal height changes. Such accuracy surpasses the requirements of second-class leveling surveys covering route lengths exceeding 1.35 km, as well as conforming/closed loop routes with distances greater than 0.46 km. By strategically selecting CORS stations with long-term continuous observations and high-quality data as core nodes within the elevation control network, dynamic maintenance of the regional elevation datum can be achieved based on CORS station data.
An Extended Simultaneous Algebraic Reconstruction Technique for Imaging the Ionosphere Using GNSS Data and Its Preliminary Results
Authors: Long Yuanliang , Huo Xingliang , Liu Haojie , Li Ying , Sun Weihong
Published: June 2023

To generate high-quality reconstructions of ionospheric electron density (IED), we propose an extended simultaneous algebraic reconstruction technique (ESART). The ESART method distributes the discrepancy between the actual GNSS TEC and the calculated TEC among the ray–voxels based on the contribution of voxels to GNSS TEC, rather than the ratio of the length of ray–voxel intersection to the sum of the lengths of all ray–voxel intersections, as is adopted by conventional methods. The feasibility of the ESART method for reconstructing the IED under different levels of geomagnetic activities is addressed. Additionally, a preliminary experiment is performed using the reconstructed IED profiles and comparing them with ionosonde measurements, which provide direct observations of electron density. The root mean square errors (RMSE) and absolute errors of the ESART method, the simultaneous algebraic reconstruction technique (SART) method, and the International Reference Ionosphere (IRI) 2016 model are calculated to evaluate the effectiveness of the proposed method. Compared to the conventional SART method of ionospheric tomography and the IRI-2016 model, the reconstructed IED profiles obtained using the ESART method are in better agreement with the electron density obtained from the ionosondes, especially for the peak electron densities (NmF2). In addition, a case study of an intense geomagnetic storm on 17–19 March 2015 shows that the spatial and temporal features of storm-related ionospheric disturbances can be more clearly depicted using the ESART method than with the SART method.
Assessing Transferability of Remote Sensing Pasture Estimates Using Multiple Machine Learning Algorithms and Evaluation Structures
Authors: Smith Hunter D. , Dubeux Jose C. B. , Zare Alina , Wilson Chris H.
Published: June 2023

Both the vastness of pasturelands and the value they contain—e.g., food security, ecosystem services—have resulted in increased scientific and industry efforts to remotely monitor them via satellite imagery and machine learning (ML). However, the transferability of these models is uncertain, as modelers commonly train and test on site-specific or homogenized—i.e., randomly partitioned—datasets and choose complex ML algorithms with increased potential to overfit a limited dataset. In this study, we evaluated the accuracy and transferability of remote sensing pasture models, using multiple ML algorithms and evaluation structures. Specifically, we predicted pasture above-ground biomass and nitrogen concentration from Sentinel-2 imagery. The implemented ML algorithms include principal components regression (PCR), partial least squares regression (PLSR), least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine regression (SVR), and a gradient boosting model (GBM). The evaluation structures were determined using levels of spatial and temporal dissimilarity to partition the train and test datasets. Our results demonstrated a general decline in accuracy as evaluation structures increase in spatiotemporal dissimilarity. In addition, the more simplistic algorithms—PCR, PLSR, and LASSO—out-performed the more complex models RF, SVR, and GBM for the prediction of dissimilar evaluation structures. We conclude that multi-spectral satellite and pasture physiological variable datasets, such as the one presented in this study, contain spatiotemporal internal dependence, which makes the generalization of predictive models to new localities challenging, especially for complex ML algorithms. Further studies on this topic should include the assessment of model transferability by using dissimilar evaluation structures, and we expect generalization to improve for larger and denser datasets.
Design of a Planar Sensor Based on Split-Ring Resonators for Non-Invasive Permittivity Measurement
Authors: Alibakhshikenari Mohammad , Virdee Bal S. , Elwi Taha A. , Lubangakene Innocent D. , Jayanthi Renu K. R. , Al-Behadili Amer Abbood , Hassain Zaid A. Abdul , Ali Syed Mansoor , Pau Giovanni , Livreri Patrizia , Aïssa Sonia
Published: June 2023

The permittivity of a material is an important parameter to characterize the degree of polarization of a material and identify components and impurities. This paper presents a non-invasive measurement technique to characterize materials in terms of their permittivity based on a modified metamaterial unit-cell sensor. The sensor consists of a complementary split-ring resonator (C-SRR), but its fringe electric field is contained with a conductive shield to intensify the normal component of the electric field. It is shown that by tightly electromagnetically coupling opposite sides of the unit-cell sensor to the input/output microstrip feedlines, two distinct resonant modes are excited. Perturbation of the fundamental mode is exploited here for determining the permittivity of materials. The sensitivity of the modified metamaterial unit-cell sensor is enhanced four-fold by using it to construct a tri-composite split-ring resonator (TC-SRR). The measured results confirm that the proposed technique provides an accurate and inexpensive solution to determine the permittivity of materials.
Improving Energy Efficiency in LoRaWAN Networks with Multiple Gateways
Authors: Loubany Ali , Lahoud Samer , Samhat Abed Ellatif , El Helou Melhem
Published: June 2023

LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the Aloha access scheme, which leads to a high probability of collision at large scales, especially in dense environments such as cities. In this paper, we propose EE-LoRa, an algorithm to improve the energy efficiency of LoRaWAN networks with multiple gateways via spreading factor selection and power control. We proceed in two steps, where we first optimize the energy efficiency of the network, defined as the ratio between the throughput and consumed energy. Solving this problem involves determining the optimal node distribution among different spreading factors. Then, in the second step, power control is applied to minimize the transmission power at nodes without jeopardizing the reliability of communications. The simulation results show that our proposed algorithm greatly improves the energy efficiency of LoRaWAN networks compared to legacy LoRaWAN and relevant state-of-the-art algorithms.
A Multi-Global Navigation Satellite System (GNSS) Time Transfer Method with Federated Kalman Filter (FKF)
Authors: Liang Kun , Hao Shuangyu , Yang Zhiqiang , Wang Jian
Published: June 2023

Relative to single Global Navigation Satellite System (GNSS) measurements, i.e., the measurements from a single GNSS system, a single GNSS code, and a single GNSS receiver, multi-GNSS measurements for time transfer could improve reliability and provide better short-term stability. Previous studies applied equal weighting to different GNSS systems or different GNSS time transfer receivers, which, to some extent, revealed the improvement in the additional short-term stability from the combination of two or more kinds of GNSS measurements. In this study, the effects of the different weight allocation for multi-measurements of GNSS time transfer were analyzed, and a federated Kalman filter was designed and applied to fuse multi-GNSS measurements combined with the standard-deviation-allocated weight. Tests with real data showed that the proposed approach can reduce the noise level to well below about 250 ps for short averaging times.
Blue Seaports: The Smart, Sustainable and Electrified Ports of the Future
Authors: Clemente Daniel , Cabral Tomás , Rosa-Santos Paulo , Taveira-Pinto Francisco
Published: June 2023

Seaports are at the forefront of global trade networks, serving as hubs for maritime logistics and the transportation of goods and people. To meet the requirements of such networks, seaport authorities are investing in advanced technologies to enhance the efficiency and reliability of port infrastructures. This can be achieved through the digitalization and automation of core systems, aimed at optimizing the management and handling of both goods and people. Furthermore, a significant effort is being made towards a green energy transition at seaports, which can be supported through marine renewable sources. This promotes energy-mix diversification and autonomy, whilst reducing the noteworthy environmental footprint of seaport activities. By analyzing these pertinent topics under the scope of a review of container-terminal case studies, and these ports’ respective contexts, this paper seeks to identify pioneering smart seaports in the fields of automation, real-time management, connectivity and accessibility control. To foster the sustainable development of seaports, from an energy perspective, the potential integration with marine renewable-energy systems is considered, as well as their capabilities for meeting, even if only partially, the energy demands of seaports. By combining these fields, we attempt to construct a holistic proposal for a “model port” representing the expected evolution towards the seaports of the future.
How Does the Industrial Digitization Affect Carbon Emission Efficiency? Empirical Measurement Evidence from China’s Industry
Authors: Zhang Ren-Long , Liu Xiao-Hong , Jiang Wei-Bo
Published: June 2023

Based on the panel data of China’s industrial carbon emissions from 2015 to 2022, the S-SBM model is scientifically used to measure the industrial carbon emission efficiency, and a spatial model is constructed to empirically analyze the spatial effect of industrial digitalization on carbon emission efficiency. From the regional perspective, it is interesting to find that industrial digitization has shown an overall downward trend of the central, western and northeastern regions showing a roughly N-shaped trend of change. From an industry perspective, we also find that industrial digitization has a relatively high overall impact on the carbon emissions performance of the mining industry with significant changes in the performance of electricity and heat and gas and water production and supply industries. Therefore, the experimental results effectively provide the substantive empirical evidence for policy makers on how to best promote the development of industrial digitization and strengthen the effective application of digital technology affecting carbon emission control in China.
Shared Electric Scooter Users and Non-Users: Perceptions on Safety, Adoption and Risk
Authors: Pourfalatoun Shiva , Ahmed Jubaer , Miller Erika E.
Published: June 2023

Shared electric scooters (e-scooters) offer a potential strategy to mitigate environmental concerns and congestion. However, successfully addressing these issues with e-scooters requires adoption across a diverse array of consumers. Understanding the differences between users and non-users can improve shared e-scooter appeal, operation and safety. The objective of this paper is to compare shared e-scooter users and non-users in terms of their perceptions on safety, trip behaviors, other shared modes, risk propensity and willingness to adopt technology. A survey was conducted involving 210 (51.3%) users and 199 (48.7%) non-users of shared e-scooters. Binary logistic regression and chi-squared tests were performed. The results reveal that users demonstrated a higher risk propensity and were more likely to be early adopters of new technologies. Non-users tended to place higher importance on helmet use, while users have an overall increased feeling of safety associated with riding e-scooters in vehicle lanes, on sidewalks and being passed by e-scooters as a pedestrian. Overall, users also have a more positive perception of e-scooter sanitary levels than non-users, and a more positive perception on the sanitary levels and usability of e-scooters over e-bicycles. These findings can provide guidance to urban planners, municipal authorities and micromobility providers in developing infrastructure and policies to better support micromobility adoption.
Identification of Ecological Management Zoning on Arid Region from the Perspective of Risk Assessment
Authors: Yao Litang , Zhang Xuebin , Luo Jun , Li Xuehong
Published: June 2023

Strengthening ecosystem monitoring and improving the efficiency of ecological risk assessment are of great significance for the sustainable development of ecosystems in an arid area. Using remote sensing monitoring data of land use, the ecological risk status of typical arid areas is assessed, its spatial heterogeneity is analyzed from the perspective of space-time, and the key areas of ecological risk management are finally identified. The results show that (1) the transformation mode of landscape ecological risk was dominated by medium–low risk to medium risk, and low risk to medium–low risk as a secondary level; in addition, the ecological risk level of the region increased. From 2000 to 2020, the transformation mode of landscape ecological risk was dominated by medium risk to medium–low risk, and medium–low risk to low risk as a secondary level; in addition, the regional ecological risk level shows a moderating trend. (2) The spatial difference in the ecological risk level in the Hexi region is obvious, showing a gradual decline from east to west, and the spatial difference in the ecological risk level in the west is significant. (3) A total of 1194 grid units are identified as key areas for ecological risk management in the Hexi region, accounting for 43% of the study area. This study provides important theoretical basis for ecosystem monitoring and risk assessment management in similar areas of arid regions.
Investigation on the Influence of the Bit Radius and Impact Velocity on Rock Fragmentation by Discrete Element Method
Authors: Hernández-Vielma César , Estay Danilo , Cruchaga Marcela
Published: June 2023

The bit–rock interaction is a key point in the fracture process observed in excavation applications, which makes its analysis relevant. As the discrete element method (DEM) has been successfully applied to study rock breakage behavior, we apply it in the present study to analyze various aspects of the bit–rock interaction. This research focuses on numerically analyzing the bit–rock interaction, encompassing the force penetration relationship (FPR), mechanical energy transfer to the rock, and the efficiency of the mechanical energy transfer process. In order to perform this analysis, we simulate various bit radii and impact velocities. In this study, we establish a power–law function to describe the relationship between the energy transferred to the rock and the force, both as functions of bit penetration. The least-squares method is employed to accomplish this determination. Remarkably, it was observed that the latter aligns with the Hertzian contact law when lower impact velocities of the bit are employed. Moreover, a bit-radius-dependent optimal velocity for the mechanical energy transfer process was determined, signifying its significance in the design of excavation tools. The primary conclusion drawn from this research is the quantification of the influence of both the bit impact velocity and the bit radius on the force penetration relationship during the bit–rock interaction. This quantification was achieved by employing the coefficients derived from the regression model established for the FPR. These findings hold practical implications for the enhancement of excavation tools’ efficiency during the design phase, thus contributing to advancements in the field of excavation engineering.
Assessment and Factor Diagnosis of Water Resource Vulnerability in Arid Inland River Basin: A Case Study of Shule River Basin, China
Authors: Wu Lanzhen , Qian Chen , Shen Yilin , Sun Dongyuan
Published: June 2023

Water resources in arid and semi-arid inland regions are highly vulnerable, facing threats from global climate change and human activities. Ensuring water resource sustainability requires scientifically evaluating the vulnerability of water resources and its driving factors. Taking the Shule River Basin, an inland river in northwest China, as an example, this study established an assessment system considering 16 influencing factors based on three aspects, including natural vulnerability, anthropogenic vulnerability, and carrying capacity vulnerability. The mature-element fuzzy model based on comprehensive weight and the Delphi method were used to evaluate the water resource vulnerability of the basin from 2005 to 2021. The results were as follows: (1) The water resource vulnerability in the Shule River Basin was between severe and moderate from 2005 to 2021, with a trend towards severe vulnerability. (2) The barrier analysis at the index level shows that factors of natural vulnerability had a low impact on water resource vulnerability in the basin from 2005 to 2019 but exerted a greater impact in 2020–2021, an impact that was far higher than that caused by factors of man-made vulnerability and water resource vulnerability. The impact of factors of anthropogenic vulnerability on water resource vulnerability was relatively low in the entire study period, except in 2016, 2017, 2020, and 2021. In 2005–2010, the factors of bearing capacity vulnerability had a great impact on water resource vulnerability, but in 2011–2021, the impact was alleviated and was gradually reduced. (3) Among the 16 factors affecting water resource vulnerability, the obstacle degree was higher than 6.5% for the following factors: the ratio of irrigation water use on farmland, the annual precipitation, total water resources, the annual quantity of wastewater effluent, the urbanization rate, the surface water control rate, and the degree of groundwater resource amount, exploration, and utilization obstacle values.
Evaluation of Soil Loss and Sediment Yield Based on GIS and Remote Sensing Techniques in a Complex Amazon Mountain Basin of Peru: Case Study Mayo River Basin, San Martin Region
Authors: Camacho-Zorogastúa Katherine del Carmen , Cesar Minga Julio , Gómez-Lora Jhon Walter , Gallo-Ramos Víctor Hugo , Garcés Díaz Victor
Published: June 2023

This study aims to estimate the average annual rate of soil loss by rainfall in terms of spatial distribution and sediment rate using RUSLE and GIS techniques. Additionally, remote sensing and available soil property information are applied for erosion analysis. The work reveals a very severe type of soil erosion, with the highest mean rate in the steep areas. Annual mean erosion in many parts of the basin is in the range of 0 to 9237.0 t/km2/year with an average of 403 t/km2/year. Approximately 45% (in the upper basin) of the total area has moderate to high soil loss by water, especially in five catchments, namely Serranoyacu, Naranjos, Naranjillo, Yuracyacu, and Tonchima at 886.8 t/km2/yr, 985.1 t/km2/yr, 691.3 t/km2/yr, 567.3 t/km2/yr, and 506.9 t/km2/yr, respectively. Catchment-wise soil loss estimates suggest that these areas are experiencing much higher soil loss in comparison to others; hence, these catchments are prioritized for soil conservation efforts. Sediment rate assessments indicate high sediment deposition along the flow direction of the mainstream of the catchment; in the upper Mayo part, the highest sediment rates are in Yuracyacu, Serranoyacu and Tonchima. Finally, the parts most vulnerable to increased erosion rate are the central part of the basin, which indicates progressive sediment deposition.