bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel PMDI Fiber Optic Hydrophone Incorporating IOC-Based Phase Modulator
Authors: Zhang Chunxi , Yang Sufan , Wang Xiaxiao
Published: August 2023

Fiber-optic hydrophone (FOH) has significant potential in many applications of hydroacoustic sensing and underwater communication. A novel path-matched differential interferometer fiber optic hydrophone (PMDI-FOH) approach incorporating an integrated-optic component (IOC) is presented in this paper. It is presented to meet the demands for high-quality dynamic measurements, which solves the problems with the conventional homodyne detection system’s low modulation frequency. The IOC functions as a phase-generated carrier (PGC) component. The scheme is investigated both in theory and experiments. The theoretical and experimental results verify the effectiveness of the proposed scheme. It achieves a high SNR of up to 20.29 dB demodulations. The proposed system is cost-effective and has excellent potential in building next-generation underwater sensing and communication networks.
Electronically Excited States of Free Radicals
Authors: Khudyakov Igor V.
Published: August 2023

Formation of the excited doublet (D) and quartet (Q) states of free radicals under their photoexcitation is discussed. The relative positions of the D and Q states are compared to the positions of the photoexcited states of organic molecules (Jablonsky diagram). A number of representative cases of the excited states of free radicals detected by their transient absorption or emission are presented. A special case of the population having the lowest Q state in some radicals is discussed. A spin–statistical factor in the reactions of Q and D is debated.
14-3-3 Proteins and the Plasma Membrane H+-ATPase Are Involved in Maize (Zea mays) Magnetic Induction
Authors: Fiorillo Anna , Parmagnani Ambra S. , Visconti Sabina , Mannino Giuseppe , Camoni Lorenzo , Maffei Massimo E.
Published: August 2023

The geomagnetic field (GMF) is a natural component of the biosphere, and, during evolution, all organisms experienced its presence while some evolved the ability to perceive magnetic fields (MF). We studied the response of 14-3-3 proteins and the plasma membrane (PM) proton pump H+-ATPase to reduced GMF values by lowering the GMF intensity to a near-null magnetic field (NNMF). Seedling morphology, H+-ATPase activity and content, 14-3-3 protein content, binding to PM and phosphorylation, gene expression, and ROS quantification were assessed in maize (Zea mays) dark-grown seedlings. Phytohormone and melatonin quantification were also assessed by LG-MS/MS. Our results suggest that the GMF regulates the PM H+-ATPase, and that NNMF conditions alter the proton pump activity by reducing the binding of 14-3-3 proteins. This effect was associated with both a reduction in H2O2 and downregulation of genes coding for enzymes involved in ROS production and scavenging, as well as calcium homeostasis. These early events were followed by the downregulation of IAA synthesis and gene expression and the increase in both cytokinin and ABA, which were associated with a reduction in root growth. The expression of the homolog of the MagR gene, ZmISCA2, paralleled that of CRY1, suggesting a possible role of ISCA in maize magnetic induction. Interestingly, melatonin, a widespread molecule present in many kingdoms, was increased by the GMF reduction, suggesting a still unknown role of this molecule in magnetoreception.
Extraction of Polyphenols from Slovenian Hop (Humulus lupulus L.) Aurora Variety Using Deep Eutectic Solvents: Choice of the Extraction Method vs. Structure of the Solvent
Authors: Metaj Ilir , Hajdini Drilon , Gliha Kaja , Košir Iztok Jože , Ocvirk Miha , Kolar Mitja , Cerar Janez
Published: August 2023

Polyphenols from Slovenian hops (Humulus lupulus L.) of the Aurora variety were extracted by different methods and using classical solvents and several deep eutectic solvents (DES) based on choline chloride as the hydrogen bond acceptor component. The obtained extract solutions were analyzed by HPLC for the content of extracted α- and β-acids and extracted xanthohumol. It was found that choline chloride:phenol DES concentrated aqueous solution had an extraction efficiency close to that of diethyl ether, which is considered one of the best classical extraction solvents for polyphenols from hops. The comparison of the extraction efficiency with other choline chloride-based DESs showed that the chemical similarity of the phenol ring in the solvent DES with the polyphenols in hops may be crucial for a highly efficient extraction with choline chloride:phenol DES. On the other hand, the choice of extraction method and the viscosity of the solvents tested seem to play only a minor role in this respect. As far as we know, this is the first study to attempt to relate extraction efficiency in the extraction of hydrophobic solutes to the compressibility of the DES extractants, the latter of which may be correlated with the extent of hydrophobic hydration around the DES components. In addition, using the heating and stirring method for the preparation of choline chloride-based DES concentrated aqueous solutions we found no support for the occurrence of water in two different roles (in the structural and in the dilution role) in these solvents.
Biodiesel Production from the Marine Alga Nannochloropsis oceanica Grown on Yeast Wastewater and the Effect on Its Biochemical Composition and Gene Expression
Authors: Senousy Hoda H. , El-Sheekh Mostafa M. , Khairy Hanan M. , El-Sayed Heba S. , Mahmoud Ghada Abd-Elmonsef , Hamed Amal A.
Published: August 2023

Microalgae-based biodiesel synthesis is currently not commercially viable due to the high costs of culture realizations and low lipid yields. The main objective of the current study was to determine the possibility of growing Nannochloropsis oceanica on Saccharomyces cerevisiae yeast wastewater for biodiesel generation at an economical rate. N. oceanica was grown in Guillard F/2 synthetic medium and three dilutions of yeast wastewater (1, 1.25, and 1.5%). Biodiesel properties, in addition to carbohydrate, protein, lipid, dry weight, biomass, lipid productivity, amino acids, and fatty acid methyl ester (FAMEs) content, were analyzed and the quality of the produced biodiesel is assessed. The data revealed the response of N. oceanica to nitrogen-deficiency in the three dilutions of yeast wastewater. N. oceanica in Y2 (1.25%) yeast wastewater dilution exhibited the highest total carbohydrate and lipid percentages (21.19% and 41.97%, respectively), and the highest lipid productivity (52.46 mg L−1 day −1) under nitrogen deficiency in yeast wastewater. The fatty acids profile shows that N. oceanica cultivated in Y2 (1.25%) wastewater dilution provides a significant level of TSFA (47.42%) and can be used as a feedstock for biodiesel synthesis. In addition, N. oceanica responded to nitrogen shortage in wastewater dilutions by upregulating the gene encoding delta-9 fatty acid desaturase (Δ9FAD). As a result, the oleic and palmitoleic acid levels increased in the fatty acid profile of Y2 yeast wastewater dilution, highlighting the increased activity of Δ9FAD enzyme in transforming stearic acid and palmitic acid into oleic acid and palmitoleic acid. This study proved that the Y2 (1.25%) yeast wastewater dilution can be utilized as a growth medium for improving the quantity of specific fatty acids and lipid productivity in N. oceanica that affect biodiesel quality to satisfy global biodiesel requirements.
Dynamic Analysis of a Bolted Joint Rotor-Bearing System with a Blade–Casing Rubbing Fault
Authors: Wen Chuanmei , Zhu Zhimin , Fu Xuezhong , Long Tianliang , Li Bing
Published: August 2023

Bolted joints are widely used in aeroengine rotor systems to connect multiple components into an integrated structure and provide sufficient stiffness. The mechanical properties of a bolted joint have a significant effect on rotor dynamics. For modern aeroengine designs, the blade-tip clearance is gradually reduced to improve efficiency, which may lead to rubbing damage and affect safe operation. The mechanical properties of a bolted joint change significantly during the blade–casing rubbing process and influence the dynamic properties of the rotor system. Based on the finite element (FE) modeling method, a 15-node bolted joint rotor system model is established in this paper, in which the bolted joint is represented by a 2-node joint element, and the blade–casing rubbing force is considered. The Newmark method is used to solve the motion equations. The dynamic model is validated by comparing the frequency response characteristics for different numbers of blades with the results provided in other published studies. Based on the established model, the effects of the rotational speed, number of blades, and rubbing stiffness on the dynamic responses, normal rubbing forces, and bending stiffness of the bolted joint are evaluated by numerical simulation. The results show that the response amplitude and bending stiffness of the bolted joint change significantly under blade–casing rubbing faults, and the mean value of the vibration response deviates significantly from 0 as the number of blades increases. Meanwhile, the amplitude of the frequency component fVC and the maximum value of the normal rubbing force also increase as the number of blades increases. The main contribution of this paper is the establishment of a new model for a bolted joint rotor system, considering the time-varying bending stiffness of the bolted joint and the blade–casing rub fault, comparing the simulation results to obtain some general results bridging the current research gap. Meanwhile, the numerical results in this paper can provide a cognitive basis for the blade–casing rubbing fault mechanism of a bolted joint rotor system under the influence of speed, number of blades, and rubbing stiffness. The nonlinear dynamic characteristics observed in the present paper can be applied to the blade–casing rubbing fault diagnosis of turbomachines.
Fault Location Study of Overhead Line–Cable Lines with Branches
Authors: Cao Wensi , Zhao Lixing , Li Zhaohui , Chen Jianming , Xu Mingming , Niu Rongze
Published: August 2023

A new fault location method based on the three-terminal travelling wave method is proposed for the fault location problem of multi-branch overhead line–cable transmission lines. Firstly, the process of fault travelling wave propagation in overhead transmission lines and the phenomenon of refraction are analysed, and an improved phase-mode transformation is introduced to decouple the electromagnetic coupling and perform fault phase selection. Secondly, the Pearson correlation coefficient is introduced to compare the similarity of the current travelling waveforms at different measurement points in order to implement fault segmentation. To solve the problems of the complexity of the fault travelling wave propagation process and the difficulty of identifying the travelling wavehead, the Hilbert–Huang transform is used to extract the fault signal characteristics, and the travelling wave arrival moment is accurately calculated by the sampling error correction method to determine the fault location. Finally, the accuracy and stability of the method are verified via a simulation test on the MATLAB/Simulink platform. The results show that the proposed positioning method combining the three-terminal travelling wave method with HHT and sampling error correction can locate the fault location more accurately, and it has good potential for application in the engineering field. It provides a new technical means for fault location in overhead transmission lines, which is expected to become one of the most important technologies in the future power system.
Effects of Process Parameters on the Microstructure and Mechanical Properties of Large PE Pipe via Polymer Melt Jetting Stacking
Authors: Wu Shenglin , Zhang Wei , Zhu Yafeng
Published: August 2023

The conventional methods for producing large-diameter pipes, such as extrusion and winding fusion welding, suffer from various drawbacks including difficulties in forming, complex molds, and high costs. Moreover, the flexibility and production efficiency of traditional manufacturing processes are relatively low. To address these challenges, this study proposes a new manufacturing process for polymer melt jetting and stacking based on fused deposition modeling (FDM) and rolling forming principles. This innovative approach aims to overcome the limitations of conventional methods and improve the flexibility and production efficiency in large-diameter pipe manufacturing. In the polymer melt jetting and stacking process, a plastic melt with a specific temperature and pressure is extruded by an extruder. The melt is then injected through the nozzle embedded in the previous layer of the pipe blank. By utilizing the localized rolling action of the forming device and adjusting the diameter using a diameter adjustment device, the newly injected plastic melt bonds with the previous layer of the pipe blank. Finally, the continuous large-diameter plastic pipe is formed through cooling and solidification. Experimental investigations demonstrate that the polymer melt jetting and stacking process can produce pipes with diameters ranging from 780 mm to 850 mm and thicknesses of 20 mm to 25 mm. The radial tensile strength, impact strength, and microstructural orientation of the produced pipes exhibit superior performance compared to those in the axial direction. Additionally, process parameters such as rolling speed, cooling temperature, melt extrusion speed, and tractive velocity significantly influence the microstructure and mechanical properties of the pipes.
Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP
Authors: Ye Lixiao , Zhang Nan , Li Guanghui , Gu Dungang , Lu Jiaqi , Lou Yuhang
Published: August 2023

The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design efficiency, and minimize reliance on experience in the design process, a design methodology based on the GA-BP model is proposed in this paper. Firstly, a distillation column surrogate model is established using the back propagation neural network technique based on the training data from the rigorous simulation, which covers all possible changes in feed conditions, operating conditions, and design parameters. The essence of this step is to turn the distillation design process from model-driven to data-driven. Secondly, the model takes the minimum TAC as the objective function and performs the optimization search using a Genetic Algorithm to obtain the design solution with the minimum TAC, in which a life-cycle assessment (LCA) model is incorporated to evaluate the obtained optimized design solution from both economic and environmental aspects. Finally, the feasibility of the proposed method is verified with a propylene distillation column as an example. The results show that the method has advantages in convergence speed without sacrificing accuracy and can obtain an improved design solution with reduced cost and environmental impact. Compared with the original design using rigorous simulation, the TAC is reduced by 6.1% and carbon emission by 27.13 kgCO2/t.
Flotation Characteristics of Amphibole-Type Oxidized Iron Ore via Reverse Anionic Flotation
Authors: Huangfu Mingzhu , Hu Yiming , Zhou Yongcheng , Li Mingyang , Deng Jiushuai , Li Shan , Peng Guixiong
Published: August 2023

To explore the flotation feasibility and flotation law of iron minerals from amphibole-type iron oxide ore with full-size minerals, a systematic study on the flotation behaviors of single minerals hematite, quartz, and amphibole was carried out with the anionic reverse flotation system. The effects of collectors, depressants, activators, and pH on the floatabilities of three single minerals was investigated. The flotation separations of binary mixed minerals and ternary mixed ores were carried out, respectively. The study results show that CaCl2 is adsorbed on the surfaces of quartz and amphibole, which can activate them. The hydroxyl groups of the starch molecular chain were adsorbed on the surfaces of the hematite and amphibole in the form of hydrogen bonds, but were hardly adsorbed on surface of the quartz. Therefore, both hematite and amphibole were depressed, resulting in a poor separation effect of the three single minerals in the anionic flotation system.
Liquid–Liquid Two-Phase Flow and Size Prediction of Slug Droplets in Microchannels
Authors: Du Wei , Duan Yingfeng , Wang Lina , Liu Dayu
Published: August 2023

The liquid–liquid two-phase flow and size prediction of slug droplets in flow-focusing microchannels with different downstream orifice sizes were investigated experimentally. Aqueous solution of 50%-glycerol and mineral oil with 4 wt.% surfactant sorbitanlauric acid ester (Span 20) were used as the dispersed and continuous phases, respectively. Three characteristic flow patterns were identified: slug flow, dripping flow, and jetting flow. The slug flow region decreased but the jetting flow region increased with the decrease in the size of the channel orifice. Afterwards, the universal flow pattern maps of the liquid–liquid two-phase in three microchannels were obtained based on dimensionless analysis. Furthermore, two slug droplet formation regions were found: when φ−1Cac < 0.01, the droplet formation was mainly driven by the squeezing force Fp, while when φ−1Cac > 0.01, both the squeezing force Fp and shear force Fτ contributed to droplet formation. Additionally, the prediction correlations of the dimensionless sizes of the slug droplets in both regions were established based on the flow rate ratio of the two-phase, the dimensionless orifice size, and the Capillary number of the continuous phase. The predicted results are in good agreement with the experimental values.
Evaluating Model Fit in Two-Level Mokken Scale Analysis
Authors: Koopman Letty , Zijlstra Bonne J. H. , Van der Ark L. Andries
Published: August 2023

Currently, two-level Mokken scale analysis for clustered test data is being developed. This paper contributes to this development by providing model-fit procedures for two-level Mokken scale analysis. New theoretical insights suggested that the existing model-fit procedure from traditional (one-level) Mokken scale analyses can be used for investigating model fit at both level 1 (respondent level) and level 2 (cluster level) of two-level Mokken scale analysis. However, the traditional model-fit procedure requires some modifications before it can be used at level 2. In this paper, we made these modifications and investigated the resulting model-fit procedure. For two model assumptions, monotonicity and invariant item ordering, we investigated the false-positive count and the sensitivity count of the level 2 model-fit procedure, with respect to the number of model violations detected, and the number of detected model violations deemed statistically significant. For monotonicity, the detection of model violations was satisfactory, but the significance test lacked power. For invariant item ordering, both aspects were satisfactory.
Investigating the Potential Adoption of Product-Service Systems in the Luggage Industry to Promote Sustainability
Authors: Wilson Donald , Iacovidou Eleni
Published: August 2023

The travel-goods industry is an essential part of the larger travel and tourism sector, but it allegedly creates significant environmental impacts due to resource and energy consumption. This study investigates the potential of the product-service system (PSS) models to promote the transition to a sustainable travel industry in the future. It explores the drivers and barriers to PSS adoption within the luggage industry from a theoretical perspective and identifies opportunities for value creation using both consumer and luggage industry viewpoints. Four hypothetical PSS models are developed to highlight different pathways to PSS adoption, underpinned with empirical data collected via a consumer survey and semi-structured interviews with industry experts. Even though the analysis revealed shifting consumer attitudes towards servitisation concepts within the travel-goods market, at present, the widespread adoption of PSS is hindered by the fragmented nature of global supply chains and entrenched ownership values. Addressing supply chain issues in a way that empowers end-of-life systems to sustainably manage products beyond their functional obsolescence is critical. In parallel, product-oriented PSS models are more likely to increase, driven by a burgeoning resale market and supported by digital technologies, which in turn can lead to greater prospects for use-oriented PSS adoption in the long-term that would eventually promote sustainability.
A High-Precision 3D Target Perception Algorithm Based on a Mobile RFID Reader and Double Tags
Authors: Xie Yaqin , Gu Tianyuan , Zheng Di , Zhang Yu , Huan Hai
Published: August 2023

With the popularization of positioning technology, more and more industries have begun to pay attention to the application and demand of location information, and almost all industries can benefit from low-cost and high-precision location information. This paper introduces a novel three-dimensional (3D) low-cost, high-precision target perception algorithm that utilizes a Radio Frequency Identification (RFID) mobile reader and double tags. Initially, the Received Signal Strength (RSS) is employed to estimate the approximate position of the target along the length direction of the shelf. Additionally, double tags are affixed to the target, enabling the perception of its approximate height and depth through phase information measurements. Subsequently, the obtained rough position serves as an initial value for calibration using the proposed algorithm, allowing for the refinement of the target’s length information relative to the shelf. Simulation results demonstrate the exceptional accuracy of the proposed method in perceiving the 3D position information of the target, achieving centimeter-level sensing accuracy.
Tilt-to-Length Coupling Analysis of an Off-Axis Optical Bench Design for NGGM
Authors: Wu Kailan , Wu Jingui , Peng Bo , Jia Jianjun , Luo Honggang , Wang Yun , Zheng Yongchao , Yang Yichao , Lin Xuling , Lau Yun-Kau
Published: August 2023

A new off-axis optical design alternative to that of the GRACE Follow-on mission for future NGGM missions is considered. In place of the triple-mirror assembly of the GRACE Follow-on mission, a laser retro-reflector is instead generated by means of lens systems. The receiving (RX) beam and transmitting (TX) beam are enforced to be anti-parallel by a control loop with differential wavefront sensing (DWS) signals as readout, and a fast-steering mirror is employed to actuate the pointing of the local beam. The tilt-to-length (TTL) coupling noise of the new off-axis optical bench layout is carefully studied in the present work. Local TTL originated from piston noise as well as assembly and alignment errors of optical components are studied. Effort is also made to have an in depth understanding of global TTL due to relative attitude jitter between spacecraft. The margin of TTL noise in the position noise budget for laser ranging is examined. With an open loop control of the offset between the reference point of the optical bench and the centre of mass of a satellite, the TTL noise of the new off-axis optical bench design may be suppressed efficiently.
Validation of the Ocean Wave Spectrum from the Remote Sensing Data of the Chinese–French Oceanography Satellite
Authors: Li Songlin , Yu Huaming , Wu Kejian , Yin Xunqiang , Lang Shuyan , Ye Jiacheng
Published: August 2023

Since the launch of CFOSAT on 29 October 2018, more than three years of observational data of ocean wave spectra with a frequency range of 0.02–0.26 Hz and a horizontal resolution of 70–90 km have been obtained. This study compares wave spectra retrieved from 6°, 8°, and 10° incidence angle beams and their combination provided by CFOSAT with corresponding data from 98 buoys from the National Data Buoy Center (NDBC) in order to validate the remote sensing wave spectral accuracy from 1 January 2020 to 31 December 2022. The correlation coefficient of frequency spectra (Rs) between CFOSAT and buoys is used to represent the accuracy of the spectral form; the root mean square (RMS) of the significant wave height (SWH) is used to represent the accuracy of the total energy. The results indicate that CFOSAT can retrieve reliable wave frequency spectral forms with a high significant wave height (Rs > 0.8 when SWH > 3 m; RS < 0.4 when SWH < 1 m). The low-frequency noise in the swell part causes the main error, the RMS of the swell height is 0.4 m whereas the RMS of wind wave height is 0.24 m, and the mask filter used for spectral partitioned provided by CFOSAT can eliminate the low-frequency noise and improve the Rs of 10° beam wave spectra from 0.59 to 0.64. For the wind wave spectra, the correct spectra have been achieved and the mask filter cannot improve the accuracy. The wave spectra from the 10° beam without mask filtering provides the best estimation of total energy, the RMS of SWH is 0.23 m, after the mask filtering, the best estimation of spectral form can be achieved, the Rs is 0.64. The novelty of this study is that we found the strong correlation between SWH and Rs, where the scatter of SWH and Rs can be fitted as: Rs = 1 − exp(−0.89·SWH + 0.20); according to this approximate formula, we can estimate the reliability of wave spectra provided by CFOSAT according to the SWH in any region, which is important for wave spectral assimilation in the numerical model. The validation of wave direction indicates that the accuracy of wave spectra in the directional component is poor; further research is needed on the causes of directional errors. Generally, this study is not only an evaluation of the quality of the CFOSAT spectral data, but also an important reference for a series of research requiring the CFOSAT spectral data.
Neural Radiance Fields for High-Resolution Remote Sensing Novel View Synthesis
Authors: Lv Junwei , Guo Jiayi , Zhang Yueting , Zhao Xin , Lei Bin
Published: August 2023

Remote sensing images play a crucial role in remote sensing target detection and 3D remote sensing modeling, and the enhancement of resolution holds significant application implications. The task of remote sensing target detection requires a substantial amount of high-resolution remote sensing images, while 3D reconstruction tasks generate denser models from diverse view perspectives. However, high-resolution remote sensing images are often limited due to their high acquisition costs, a scarcity of acquisition views, and restricted view perspective variations, which pose challenges for remote sensing tasks. In this paper, we propose an advanced method for a high-resolution remote sensing novel view synthesis by integrating attention mechanisms with neural radiance fields to address the scarcity of high-resolution remote sensing images. To enhance the relationships between sampled points and rays and to improve the 3D implicit model representation capability of the network, we introduce a point attention module and batch attention module into the proposed framework. Additionally, a frequency-weighted position encoding strategy is proposed to determine the significance of each frequency for position encoding. The proposed method is evaluated on the LEVIR-NVS dataset and demonstrates superior performance in quality assessment metrics and visual effects compared to baseline NeRF (Neural Radiance Fields) and ImMPI (Implicit Multi-plane Images). Overall, this work presents a promising approach for a remote sensing novel view synthesis by leveraging attention mechanisms and frequency-weighted position encoding.
Converging Channel Attention Mechanisms with Multilayer Perceptron Parallel Networks for Land Cover Classification
Authors: Fan Xiangsuo , Li Xuyang , Yan Chuan , Fan Jinlong , Chen Lin , Wang Nayi
Published: August 2023

This paper proposes a network structure called CAMP-Net, which considers the problem that traditional deep learning algorithms are unable to manage the pixel information of different bands, resulting in poor differentiation of feature representations of different categories and causing classification overfitting. CAMP-Net is a parallel network that, firstly, enhances the interaction of local information of bands by grouping the spectral nesting of the band information and then proposes a parallel processing model. One branch is responsible for inputting the features, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) band information generated by grouped nesting into the ViT framework, and enhancing the interaction and information flow between different channels in the feature map by adding the channel attention mechanism to realize the expressive capability of the feature map. The other branch assists the network’s ability to enhance the extraction of different feature channels by designing a multi-layer perceptron network based on the utilization of the feature channels. Finally, the classification results are obtained by fusing the features obtained by the channel attention mechanism with those obtained by the MLP to achieve pixel-level multispectral image classification. In this study, the application of the algorithm was carried out in the feature distribution of South County, Yiyang City, Hunan Province, and the experiments were conducted based on 10 m Sentinel-2 multispectral RS images. The experimental results show that the overall accuracy of the algorithm proposed in this paper is 99.00% and the transformer (ViT) is 95.81%, while the performance of the algorithm in the Sentinel-2 dataset was greatly improved for the transformer. The transformer shows a huge improvement, which provides research value for developing a land cover classification algorithm for remote sensing images.
Developing a Pixel-Scale Corrected Nighttime Light Dataset (PCNL, 1992–2021) Combining DMSP-OLS and NPP-VIIRS
Authors: Li Shijie , Cao Xin , Zhao Chenchen , Jie Na , Liu Luling , Chen Xuehong , Cui Xihong
Published: August 2023

The spatial extent and values of nighttime light (NTL) data are widely used to reflect the scope and intensity of human activities, such as extracting urban boundaries, spatializing population density, analyzing economic development levels, etc. DMSP-OLS and NPP-VIIRS are widely used global NTL datasets, but their severe inconsistencies hinder long-time series studies. At present, global coverage, long time series, and public NTL products are still rare and have room for improvement in terms of pixel-scale correction, temporal and spatial consistency, etc. We proposed a set of inter-correction methods for DMSP-OLS and NPP-VIIRS based on two corrected DMSP-OLS and NPP-VIIRS products, i.e., CCNL-DMSP and VNL-VIIRS, with the goal of temporal and spatial consistency at the pixel-scale. A pixel-scale corrected nighttime light dataset (PCNL, 1992–2021) that met the needs of pixel-scale studies was developed through outlier removal, resampling, masking, regression, and calibration processes, optimizing spatial and temporal consistency. To examine the quality of PCNL, we compared it with two existing global long time series NTL products, i.e., LiNTL and ChenNTL, in terms of overall accuracy, spatial consistency, temporal consistency, and applicability in the socio-economic field. PCNL demonstrates great overall accuracy at both the pixel-scale (R2: 0.93) and the city scale (R2: 0.98). In developing, developed, and war regions, PCNL shows excellent spatial consistency. At global, national, urban, and pixel-scales, PCNL has excellent temporal consistency and can portray stable trends in stable developing regions and abrupt changes in areas experiencing sudden development or disaster. Globally, PCNL has a high correlation coefficient with GDP (r: 0.945) and population (r: 0.971). For more than half of the countries, the correlation coefficients of PCNL with GDP and population are higher than the results of ChenNTL and LiNTL. PCNL can analyze the dynamic changes in socio-economic characteristics over the past 30 years at global, regional, and pixel-scales.
Joint Direction of Arrival-Polarization Parameter Tracking Algorithm Based on Multi-Target Multi-Bernoulli Filter
Authors: Chen Zhikun , Wang Bin’an , Yang Ruiheng , Lou Yuchao
Published: August 2023

This paper presents a tracking algorithm for joint estimation of direction of arrival (DOA) and polarization parameters, which exhibit dynamic behavior due to the movement of signal source carriers. The proposed algorithm addresses the challenge of real-time estimation in multi-target scenarios with an unknown number. This algorithm is built upon the Multi-target Multi-Bernoulli (MeMBer) filter algorithm, which makes use of a sensor array called Circular Orthogonal Double-Dipole (CODD). The algorithm begins by constructing a Minimum Description Length (MDL) principle, taking advantage of the characteristics of the polarization-sensitive array. This allows for adaptive estimation of the number of signal sources and facilitates the separation of the noise subspace. Subsequently, the joint parameter Multiple Signal Classification (MUSIC) spatial spectrum function is employed as the pseudo-likelihood function, overcoming the limitations imposed by unknown prior information constraints. To approximate the posterior distribution of MeMBer filters, Sequential Monte Carlo (SMC) method is utilized. The simulation results demonstrate that the proposed algorithm achieves excellent tracking accuracy in joint DOA-polarization parameter estimation, whether in scenarios with known or unknown numbers of signal sources. Moreover, the algorithm demonstrates robust tracking convergence even under low Signal-to-Noise Ratio (SNR) conditions.
Seed Morphology of Three Neotropical Orchid Species of the Lycaste Genus
Authors: Alfaro Pinto Alejandra , McGill Craig , Nadarajan Jayanthi , Archila Morales Fredy , Clavijo McCormick Andrea
Published: August 2023

Neotropical orchids are vulnerable to extinction due to overharvesting, habitat destruction and climate change. However, a basic understanding of orchid seed biology to support conservation efforts is still lacking for most species. Seed morphology is linked to plant adaptation and evolution, influencing seed dispersal, dormancy, longevity, and germination, which are valuable traits for conservation. In this study, we characterized and compared the morphological traits of seed capsules (size, shape, and colour) and seeds (seed and embryo shape and size and internal airspace volume) for three epiphytic Neotropical orchid species of the genus Lycaste native to Guatemala: L. cochleata, L. lasioglossa, and L. virginalis. The three species show qualitative similarities in seed capsule colour and appearance and in seed morphology (i.e., scobiform oval-shaped seeds and prolate-spheroid embryos). All species have small-sized seeds (length of L. cochleata: 210 µm, L. lasioglossa: 230 µm, and L. virginalis: 260 µm), with proportionally large embryos (length of L. cochleata: 140 µm, L. lasioglossa: 120 µm, and L. virginalis: 150 µm) and an internal air-space volume that occupies less than half of the seed (L. cochleata: 17%, L. lasioglossa: 42%, and L. virginalis: 30%). This finding is consistent with previous reports for other epiphytic orchid species, which typically have lower air volumes than terrestrial orchids. These differences are likely a result of evolutionary changes associated with different habits and may influence seed dispersal. We also found some significant differences in seed morphology between the studied species, but their taxonomic, biological, and ecological relevance remain to be elucidated. More comparative studies, including on other Lycaste species with different habits, are needed to explore relationships between seed morphology, taxonomy, biology, and ecology in this genus to support its conservation.
An Overview of Plant Phenolics and Their Involvement in Abiotic Stress Tolerance
Authors: Kumar Krishna , Debnath Pratima , Singh Sailendra , Kumar Navin
Published: August 2023

Secondary metabolites, such as phenols and salicylic, play a crucial role in the regulation of development and tolerance mechanisms against a wide range of stresses. During adverse conditions such as biotic and abiotic stresses, plants induce the biosynthesis of phenolic compounds to provide tolerance. Phenolics are secondary aromatic metabolites synthesized through the shikimate/phenylpropanoid pathway or polyketide acetate/malonate pathway, which produce monomeric and polymeric phenolics. Phenolic compounds in plants not only take part in preventing stresses but also in regulating physiological activities. These compounds significantly regulate both below- and above-ground defense mechanisms. Plants synthesize thousands of phenolic compounds throughout their evolution to survive in changing environments. Environmental factors, such as high light, cold, drought, heavy metals, etc., increase the accumulation of phenolics to neutralize any toxic effects. This review focuses on the biosynthesis of phenolic compounds and their updated studies against abiotic stresses.
Spatial Heterogeneity of Urban Road Network Fractal Characteristics and Influencing Factors
Authors: Yang Yang , Fu Baibai
Published: August 2023

Fractal geometry has provided a new perspective for urban road network morphology research. This study systematically verifies and analyzes the spatial heterogeneity of fractal characteristics and influencing factors of urban road networks using spatial analysis. Here, Tokyo Metropolis was selected as a case, and the fractal dimensions of road networks were calculated. To determine the spatial heterogeneity in the relationship between fractal dimensions and influencing factors, we examined the spatial distribution characteristics of fractal dimensions using spatial autocorrelation analysis, selected population, build-up area density, and road network density as the explanatory variables, and established the global regression model and local regression model using ordinary least squares (OLS) and geographically weighted regression (GWR), respectively. The results indicated that the spatial distribution of fractal dimensions of the urban road network exhibited an obvious tendency toward geographical dependency. Considering the spatial heterogeneity in the relationship between the fractal characteristics of the road network and the influencing factors not only improves the reliability of analysis but also helps planners and decision-makers grasp the morphological characteristics of the urban road network and estimate the evolution of the road network, thereby promoting the development of urban road networks in a more orderly, efficient, and sustainable direction.
The 38th Annual Meeting of the Academy of Surgical Research: Summary of Presentations, Labs, and Workshops, Focusing on Experimental Surgery, La Jolla, CA, USA, 14–16 September 2022
Authors: Martunas Amy , Stoll Leslie , Graham Melanie
Published: August 2023

The 38th Annual Meeting of the Academy of Surgical Research took place in La Jolla, CA, USA, on 14–16 September 2022. For more than 40 years, the Academy has promoted the advancement of professional and academic standards in education and research in the arts and sciences of experimental surgery. The diverse membership includes technicians, veterinarians, medical doctors, and biomedical researchers from industry, academia, and complementary disciplines supporting discovery and translational research. At the annual meeting, this experimental surgery community shared the latest in research and surgical techniques, along with professional development that included cutting-edge lectures, hands-on training, and qualification exams for certifications. Over 130 participants from 26 different states and 3 countries were in attendance for the scientific program and social events. Two scientific tracks featuring three keynotes were presented together with a poster session. Participants could practice hands-on surgical techniques in dry and wet labs that ranged from applied surgical anesthesia to minimally invasive surgical skills, followed by in-depth discussion roundtables focused on improving study design and best practices in anesthesia and analgesia. The social program provided participants the opportunity to connect in person with potential mentors and collaborators. We present the highlights from this meeting in this report, together with selected abstracts that illustrate the diverse scientific expertise of the Academy and promising new surgical research.
Dynamic Evolutionary Game Approach for Blockchain-Driven Incentive and Restraint Mechanism in Supply Chain Financing
Authors: Su Limin , Cao Yongchao
Published: August 2023

The sustainability of financing is an important measure in the development of supply chains. However, the difficulty and high cost of financing have always been critical factors hindering the sustainable development of small and medium-sized enterprises (SMEs). Blockchain technology (BT) is an effective tool to relieve the current problem. Based on it, this study aims to establish Blockchain-driven incentives and restraint mechanisms for SME financing using a dynamic game model in which financial institutions (FIs) and new agricultural business entities (NABEs) are regarded as game subjects. By analyzing the impact of key parameters on the equilibrium state of the game for all stakeholders, several findings are drawn as follows. (1) The usage of BT affects FI loan strategies by influencing their cost in supply chain financing. (2) The usage of BT affects NABE’s strategy choice by influencing their loan interest rate. (3) The usage of BT affects NABE’s strategy choice by influencing their default losses. (4) The usage of BT affects NABE’s and FI’s strategy choices by influencing their additional benefits. This study provides decision-making support for optimal strategy decisions under different conditions and serves as a theoretical reference for the government in formulating financing incentive and restraint mechanisms.
Risk Simulation of Urban Rainstorm Flood Disasters Considering Crowd Activities
Authors: Huang Jing , Pang Tiantian , Liu Zhenzhen , Wang Zhiqiang , Wang Huimin
Published: August 2023

Social activities have a significant impact on the rainstorm flood disaster risk. It is crucial to explore the dynamic changes of urban rainstorm flood disaster risk caused by crowd activities. In this study, a risk simulation method of urban rainstorm flood disasters is proposed, composed of an urban rainstorm flood model based on SWMM and LISFLOOD-FP and a crowd activities model based on ABM. Taking the Futian District of Shenzhen as an example, the temporal and spatial changes in rainstorm flood disaster risk for buildings and roads are analyzed under three scenarios: midnight, morning peak, and evening peak. The results show that: (1) Although the overall risk of urban rainstorm flood disasters increases as the inundation area expands, the average risks of roads and buildings increase rapidly and then stabilize during the morning peak due to commuting activities, while the average risk of roads remains high level during the evening peak due to commuting activities, while; (2) The risk of urban rainstorm flood varies significantly at different time periods. The average risk of buildings is the largest during the morning peak, about twice that during the evening peak. The number of high-risk roads during the evening peak is much higher than in the morning peak, and both buildings and roads have the least risk during midnight; (3) The spatial distribution of urban rainstorm flood disaster risk changes with the crowd activities, shifting from residential areas to industrial areas, schools, shopping malls, etc., during the morning peak, while the evening peak shows the reverse.
Deep Learning Techniques for Web-Based Attack Detection in Industry 5.0: A Novel Approach
Authors: Salam Abdu , Ullah Faizan , Amin Farhan , Abrar Mohammad
Published: August 2023

As the manufacturing industry advances towards Industry 5.0, which heavily integrates advanced technologies such as cyber-physical systems, artificial intelligence, and the Internet of Things (IoT), the potential for web-based attacks increases. Cybersecurity concerns remain a crucial challenge for Industry 5.0 environments, where cyber-attacks can cause devastating consequences, including production downtime, data breaches, and even physical harm. To address this challenge, this research proposes an innovative deep-learning methodology for detecting web-based attacks in Industry 5.0. Convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models are examples of deep learning techniques that are investigated in this study for their potential to effectively classify attacks and identify anomalous behavior. The proposed transformer-based system outperforms traditional machine learning methods and existing deep learning approaches in terms of accuracy, precision, and recall, demonstrating the effectiveness of deep learning for intrusion detection in Industry 5.0. The study’s findings showcased the superiority of the proposed transformer-based system, outperforming previous approaches in accuracy, precision, and recall. This highlights the significant contribution of deep learning in addressing cybersecurity challenges in Industry 5.0 environments. This study contributes to advancing cybersecurity in Industry 5.0, ensuring the protection of critical infrastructure and sensitive data.
Chemical Source Profiles and Toxicity Assessment of Urban Fugitive Dust PM2.5 in Guanzhong Plain, China
Authors: Zhao Ziyi , Tian Jie , Zhang Wenyan , Zhang Qian , Wu Zhichun , Xing Yan , Li Fei , Song Xinyu , Li Zhihua
Published: August 2023

Urban fugitive dust is a significant contributor to atmospheric PM2.5 and a potential risk to humans. In 2019, both road dust and construction dust were collected from four cities, including Xi’an, Xianyang, Baoji, and Tongchuan, in Guanzhong Plain, China. Elements, water-soluble ions, and carbonaceous fractions were determined to establish the chemical source profile. High enrichment degrees of Se, Sc, Cl, and Zn in both road dust and construction dust indicated that the industrial system and energy consumption influenced Guanzhong Plain strongly. According to the coefficient of divergence, the two datasets within Xianyang and Tongchuan were similar. Combined with the chemical profile, road dust was affected by more stationary emission sources than construction dust in Xi’an, while biomass burning and vehicle exhaust contributed more to road dust than construction dust in Baoji. Moreover, the health risk of heavy metal was assessed, and corresponding influencing factors were identified. Road dust in all cities showed a non-negligible non-carcinogenic risk for children. Ingestion and inhalation were the main exposure pathways to which As and Co contributed the most, respectively. The land-use regression model revealed that the first-class road in a 100 m radius impacted all high-risk level metals, and the commercial building material and enterprises weakly influenced Co and Pb, respectively.