bluuebunny/crossref_metadata_2025 huggingface dataset:
Elicitation of Stilbenes and Benzofuran Derivatives in Hairy Root Cultures of White Mulberry (Morus alba)
Authors: Fang Lingling , Sharma Amit Raj , Aniemena Chineche , Roedel Krystian , Henry Florence , Moussou Philippe , Samuga Anita , Medina-Bolivar Fabricio
Published: January 2023

Stilbene and benzofuran derivatives isolated from the root of white mulberry (Morus alba) have shown various biological activities, including anti-inflammatory, antioxidant, and antimicrobial properties. The objectives of this study were to develop hairy root cultures and assess the effect of multiple elicitors combinations including (I) methyl-β-cyclodextrin (CD), MgCl2, methyl jasmonate (MeJA), and H2O2, (II) CD, MgCl2, and MeJA and (III) CD, MgCl2, and H2O2, on the production of these bioactive compounds. The highest yields of stilbenes and benzofurans were obtained upon co-treatment with 18 g/L CD, 3 mM H2O2 and 1 mM MgCl2. The stilbenes oxyresveratrol, resveratrol, and 3′-prenylresveratrol accumulated up to 6.27, 0.61, and 5.00 mg/g DW root, respectively. Meanwhile, the aryl benzofurans moracin M and moracin C accumulated up to 7.82 and 1.82 mg/g DW root, respectively. These stilbenes and benzofurans accumulated in the culture medium of the elicited hairy root cultures. They were not detected in the root tissue. However, the oxyresveratrol diglucoside mulberroside A was only detected in the root tissue with yields up to 10.01 mg/g DW. The results demonstrated that co-treatment of white mulberry hairy root cultures with multiple elicitors can significantly enhance production and secretion of stilbenes and benzofurans in this controlled and sustainable axenic culture system.
Involvement of Target of Rapamycin (TOR) Signaling in the Regulation of Crosstalk between Ribosomal Protein Small Subunit 6 Kinase-1 (RPS6K-1) and Ribosomal Proteins
Authors: Bakshi Achala , Moin Mazahar , Gayatri Meher B. , Reddy Aramati B. M. , Datla Raju , Madhav Maganti S. , Kirti Pulugurtha B.
Published: January 2023

The target of rapamycin (TOR) protein phosphorylates its downstream effector p70kDa ribosomal protein S6 kinases (S6K1) for ribosome biogenesis and translation initiation in eukaryotes. However, the molecular mechanism of TOR-S6K1-ribosomal protein (RP) signaling is not well understood in plants. In the present study, we report the transcriptional upregulation of ribosomal protein large and small subunit (RPL and RPS) genes in the previously established TOR overexpressing transgenic lines of rice (in Oryza sativa ssp. indica, variety BPT-5204, TR-2.24 and TR-15.1) and of Arabidopsis thaliana (in Col 0 ecotype, ATR-1.4.27 and ATR-3.7.32). The mRNA levels of RP genes from this study were compared with those previously available in transcriptomic datasets on the expression of RPs in relation to TOR inhibitor and in the TOR-RNAi lines of Arabidopsis thaliana. We further analyzed TOR activity, i.e., S6K1 phosphorylation in SALK lines of Arabidopsis with mutation in rpl6, rpl18, rpl23, rpl24 and rps28C, where the rpl18 mutant showed inactivation of S6K1 phosphorylation. We also predicted similar putative Ser/Thr phosphorylation sites for ribosomal S6 kinases (RSKs) in the RPs of Oryza sativa ssp. indica and Arabidopsis thaliana. The findings of this study indicate that the TOR pathway is possibly interlinked in a cyclic manner via the phosphorylation of S6K1 as a modulatory step for the regulation of RP function to switch ‘on’/‘off’ the translational regulation for balanced plant growth.
Appraisal of Abelmoschus esculentus L. Response to Aluminum and Barium Stress
Authors: Kouki Rim , Dridi Nesrine , Vives-Peris Vicente , Gómez-Cadenas Aurelio , Caçador Isabel , Pérez-Clemente Rosa María , Sleimi Noomene
Published: January 2023

Trace metal element (TME) pollution is a major threat to plants, animals and humans. Agricultural products contaminated with metals may pose health risks for people; therefore, international standards have been established by the FAO/WHO to ensure food safety as well as the possibility of crop production in contaminated soils. This study aimed to assess the accumulating potential of aluminum and barium in the roots, shoots and fruits of Abelmoschus esculentus L., and their effect on growth and mineral nutrition. The content of proline and some secondary metabolites was also evaluated. After treating okra plants with aluminum/barium (0, 100, 200, 400 and 600 µM) for 45 days, the results showed that Al stimulated the dry biomass production, whereas Ba negatively affected the growth and the fructification yield. The okra plants retained both elements and exhibited a preferential accumulation in the roots following the sequence: roots > shoots > fruits, which is interesting for phytostabilization purposes. Al or Ba exposure induced a decline in mineral uptake (K, Ca, Mg, Zn and Fe), especially in roots and shoots. In order to cope with the stress conditions, the okra plants enhanced their proline and total phenol amounts, offering better adaptability to stress.
Characterizing Root Morphological Responses to Exogenous Tryptophan in Soybean (Glycine max) Seedlings Using a Scanner-Based Rhizotron System
Authors: Sanada Atsushi , Agehara Shinsuke
Published: January 2023

Tryptophan is a precursor of indole-3-acetic acid (IAA), which is the major auxin involved in the regulation of lateral root formation. In this study, we used a scanner-based rhizotron system to examine root growth and morphological responses of soybean (Glycine max, ‘Golden Harvest’) seedlings to exogenous tryptophan. Seeds were sown directly in the rhizotron filled with field soil. Tryptophan was applied at 1.9 and 3.8 mg plant−1 by soil drenching or foliar spray. Canopy and root projected area were monitored by analyzing canopy and rhizotron images using ImageJ software. Seedlings were sampled at the first trifoliate stage, 18 days after sowing (DAS), and root morphology was determined by analyzing washed root images using WinRHIZO software. According to contrast analysis, when all tryptophan treatments were pooled, tryptophan application increased canopy and root projected area by 13% to 14% compared with the control at 18 DAS. Tryptophan application also increased root dry matter accumulation by 26%, root:shoot ratio by 24%, and secondary root number by 13%. Tryptophan applied by soil drenching also increased root length and surface area of fine roots (<0.2 mm diameter) by 25% and 21%, respectively, whereas it slightly inhibited primary root elongation. The efficacy of tryptophan soil drenching in stimulating root formation became greater with increasing the application rate. These results suggest that exogenous tryptophan induces auxin-like activities in root development. Soil drenching of tryptophan appears to be an effective strategy in improving the establishment of soybean. Importantly, this strategy is easily implementable by commercial growers with no negative side effect.
Effect of Nano-SiO2 on Different Stages of UHMWPE/HDPE Fiber Preparation via Melt Spinning
Authors: Yang Qun , Zhang Run , Liu Mingfei , Xue Ping , Liu Lichao
Published: January 2023

Ultra-high molecular weight polyethylene (UHMWPE)/high-density polyethylene (HDPE) blend with lower viscosity is more suitable for melt spinning compared to pure UHMWPE; however, the mechanical property of the blend fiber is hard to dramatically improve (the maximum tensile strength of 998.27 MPa). Herein, different content modified-nano-SiO2 is incorporated to UHMWPE/HDPE blend fiber. After adding 0.5 wt% nano-SiO2, the tensile strength and initial modulus of UHMWPE/HDPE/nano-SiO2 fiber are increased to 1211 MPa and 12.81 GPa, respectively, 21.57% and 43.32% higher than that of UHMWPE/HDPE fiber. Meanwhile, the influence of the nano-SiO2 content on the performance for as-spun filament and fiber are emphatically analyzed. The crystallinity and molecular chain orientation of as-spun filament reduces with the addition of nano-SiO2. On the contrary, for fiber, the addition of nano-SiO2 promoted the crystallinity, molecular chain orientation and grain refinement more obvious at a lower content. Furthermore, the possible action mechanism of nano-SiO2 in the as-spun filament extrusion and fiber hot drawing stage is explained.
Wear and Friction Analysis of Brake Pad Material Using Natural Hemp Fibers
Authors: Naidu Mithul , Bhosale Ajit , Munde Yashwant , Salunkhe Sachin , Hussein Hussein Mohamed Abdelmoneam
Published: January 2023

Non-exhaust brake dust and pollution arising from metal, semi-metal, and ceramic brake pads have made recent research consider their replacement by potential natural fibers such as hemp, flax, sisal, etc. These natural fibers are lightweight, biodegradable, and cheap. This paper discusses the wear and friction analysis of hemp fiber reinforced polymer brake pad material. Three test specimens viz. HF4P20, HF5P20, and HF6P20 were prepared per ASTM G99 standards for the pin-on disc tribo-test. The test trials and validation were done using the Taguchi design of experiments and ANOVA. The optimum result showed a consistent coefficient of friction and lowered specific wear rate for HF6P20 brake pad material. Worn surface morphology was done using scanning electron microscopy.
Lightweight Glass Fiber-Reinforced Polymer Composite for Automotive Bumper Applications: A Review
Authors: Mohammadi Hossein , Ahmad Zaini , Mazlan Saiful Amri , Faizal Johari Mohd Aidy , Siebert Geralt , Petrů Michal , Rahimian Koloor Seyed Saeid
Published: January 2023

The enhancement of fuel economy and the emission of greenhouse gases are the key growing challenges around the globe that drive automobile manufacturers to produce lightweight vehicles. Additionally, the reduction in the weight of the vehicle could contribute to its recyclability and performance (for example crashworthiness and impact resistance). One of the strategies is to develop high-performance lightweight materials by the replacement of conventional materials such as steel and cast iron with lightweight materials. The lightweight composite which is commonly referred to as fiber-reinforced plastics (FRP) composite is one of the lightweight materials to achieve fuel efficiency and the reduction of CO2 emission. However, the damage of FRP composite under impact loading is one of the critical factors which affects its structural application. The bumper beam plays a key role in bearing sudden impact during a collision. Polymer composite materials have been abundantly used in a variety of applications such as transportation industries. The main thrust of the present paper deals with the use of high-strength glass fibers as the reinforcing member in the polymer composite to develop a car bumper beam. The mechanical performance and manufacturing techniques are discussed. Based on the literature studies, glass fiber-reinforced composite (GRP) provides more promise in the automotive industry compared to conventional materials such as car bumper beams.
Graphene Composite via Bacterial Cellulose Assisted Liquid Phase Exfoliation for Sodium-Ion Batteries
Authors: Shu Kewei , Tian Siyu , Wang Yu , Fei Guiqiang , Sun Liyu , Niu Huizhu , Duan Yihao , Hu Guangyu , Wang Haihua
Published: January 2023

One of the most critical challenges for commercialization of sodium-ion battery (SIB) is to develop carbon anodes with high capacity and good rate performance. Graphene would be an excellent SIB anode candidate due to its success in various kinds of batteries. Liquid-phase exfoliation (LPE) method is an inexpensive, facile and potentially scalable method to produce less-defected graphene sheets. In this work, we developed an improved, dispersant-assisted LPE method to produce graphene composite materials from raw graphite with high yield and better quality for SIB anode. Here, bacterial cellulose (BC) was used as a green dispersant/stabilizer for LPE, a “spacer” for anti-restacking, as well as a carbon precursor in the composite. As a result, the carbonized BC (CBC)/LPE graphene (LEGr) presented improved performance compared to composite with graphene prepared by Hummers method. It exhibited a specific capacity of 233 mAh g−1 at a current density of 20 mA g−1, and 157 mAh g−1 after 200 cycles at a high current density of 100 mA g−1 with capacity retention rate of 87.73%. This method not only provides new insight in graphene composites preparation, but also takes a new step in the exploration of anode materials for sodium-ion batteriesSIBs.
Preparation of Advanced Multi-Porous Carbon Nanofibers for High-Performance Capacitive Electrodes in Supercapacitors
Authors: Zhao Donghui , Wang Hui , Bai Yu , Yang Hao , Song Hongfang , Li Baohua
Published: January 2023

The booming demand for energy storage has driven the rapid development of energy storage devices such as supercapacitors, and the research on high-performance electrode materials, a key component of supercapacitors, has gained tremendous attention. In this research, phenolic resin-based multi-porous carbon nanofibers have been prepared by electrospinning, curing, carbonization and activation and then employed as advanced electrode materials in supercapacitors. We demonstrate that the material is nano-scale continuous fiber, and its surface has pore distribution of different sizes. It delivers a high specific capacitance of 242 F g−1 at a current density of 0.2 A g−1 and maintains 148 F g−1 even at a high current density of 20 A g−1. Moreover, it shows almost no capacitance decay at a current density of 2 A g−1 over 1000 cycles, demonstrating its great potential as high-performance electrodes in supercapacitors.
Synthesis and Characterization of Benzene- and Triazine-Based Azo-Bridged Porous Organic Polymers
Authors: Panić Barbara , Frey Tea , Borovina Mladen , Konopka Kristijan , Sambolec Miro , Kodrin Ivan , Biljan Ivana
Published: January 2023

Porous organic polymers incorporating nitrogen-rich functionalities have recently emerged as promising materials for efficient and highly selective CO2 capture and separation. Herein, we report synthesis and characterization of new two-dimensional (2D) benzene- and triazine-based azo-bridged porous organic polymers. Different synthetic approaches towards the porous azo-bridged polymers were tested, including reductive homocoupling of aromatic nitro monomers, oxidative homocoupling of aromatic amino monomers and heterocoupling of aromatic nitro monomers and a series of aromatic diamines of different lengths and rigidity. IR spectroscopy, 13C CP/MAS NMR spectroscopy, powder X-ray diffraction, elemental analysis, thermogravimetric analysis, nitrogen adsorption–desorption experiments and computational study were used to characterize structures and properties of the resulting polymers. The synthesized azo-bridged polymers are all amorphous solids of good thermal stability, exhibiting various surface areas (up to 351 m2 g−1). The obtained results indicated that the synthetic methods and building units have a pronounced effect on the porosity of the final materials. Reductive and oxidative homocoupling of aromatic nitro and amino building units, respectively, lead to 2D azo-bridged polymers of substantially higher porosity when compared to those produced by heterocoupling reactions. Periodic DFT calculations and Grand-canonical Monte Carlo (GCMC) simulations suggested that, within the used approximations, linear linkers of different lengths do not significantly affect CO2 adsorption properties of model azo-bridged polymers.
Incidence of Electric Field and Sulfuric Acid Concentration in Electrokinetic Remediation of Cobalt, Copper, and Nickel in Fresh Copper Mine Tailings
Authors: Ortiz-Soto Rodrigo , Leal Daniela , Gutierrez Claudia , Aracena Alvaro , León Marcelo , Lazo Andrea , Lazo Pamela , Ottosen Lisbeth , Hansen Henrik
Published: January 2023

In the present study, the assessment of heavy metal contaminant migration from fresh mine tailings was conducted using the electrokinetic remediation technique (EKR). In this sense, a pilot EKR cell was designed to evaluate the recovery potential of copper, nickel, and cobalt species. In particular, the focus was on the impacts of electric field intensity and pH in initial mixture and testing their interaction in copper, nickel, and cobalt migration. Experiments were made using a 22 factorial experimental design with a central point, using DC electric fields from 1.0 to 2.0 V cm−1 and H2SO4 pretreatment solutions from 1.0 to 2.0 mol L−1, along with an ANOVA test with error reduction. The metal removal rates were approximately 7% for cobalt, neglectable for copper, and 6% for nickel. In the best cases, the highest concentrations by migration at the cathodic zone were 11%, 31%, and 30%, respectively. According to ANOVA tests, factor interaction was proven for each metal in the half cell near the cathode and the closest zone from the cathode specifically. Both factors affected metal concentrations, which indicates that when the goal aims for species accumulation in a narrower section, each factor has a significant effect, and their interaction makes a proven enhancement. Thus, using 2.0 V cm−1 and 2.0 mol L−1 showed a high improvement in metal concentration in the cathodic zone.
Optimization of Glycerol Extraction of Chlorogenic Acid from Honeysuckle by Response Surface Methodology
Authors: Luo Mingsheng , Liu Xinyue , Zhao Zhijun , Wang Fengli , Shao Changke
Published: January 2023

Using honeysuckle as raw material, chlorogenic acid (CGA) was extracted with different alcohols. Based on the single-factor experiment design, the relationship between each parameter and the response value was explored by Box–Behnken method to optimize the process conditions. Best extraction results were obtained under the conditions of solid-to-liquid ratio of 1:20, the ultrasonic time of 40 min, the ultrasonic vibrator power of 240 w, and the CGA extraction rate of 2.98%. The experimental data show that the extraction rate of CGA is related to the length of the alcohol carbon chain and the number of hydroxyl groups in the extractant. The results from this work can provide technical basis for the safe and efficient production of CGA from honeysuckle.
Study on the Fracturing of Rock by High-Speed Water Jet Impact
Authors: Pan Yue , Zhai Shengyu , Meng Xinjia , Pei Kangchao , Huo Fulin
Published: January 2023

Due to the opaqueness of rock and the limitation of detection technology, it is impossible to accurately describe the crack growth process and determine the law of rock breakage. Based on smoothed particle hydrodynamics and the finite element method (SPH-FEM), a numerical model for high-speed water jet breaking was established in this work to simulate the fragmentation process of rock impacted by a high-speed water jet, and to study the effects of different jet angles on the propagation of microscopic cracks inside the rock. Additionally, we further analyzed the jet impact angle on the microscopic crack propagation trend of the rock by applying confining pressure to the rock. Theoretical and experimental analyses showed that the inclination angle of the jet determined the direction of axial crack propagation in the tension-type center. When the inclination angle of the jet exceeded 20°, the ability of water jet erosion was insufficient, and the efficiency of rock fragmentation was low. However, in the range of 15° to 20°, the capacity of erosion was strong, lamellar crack propagation was obvious, and rock chip block spalling was easily produced. The impact of the water jet on the rock at varying angles under rock confining pressure will make the crack propagation direction deviate from the direction without confining pressure and gradually become parallel to the rock plane, thereby promoting unilateral crack propagation in the direction of water jet impact, making the rock more likely to produce unilateral rock chip spalling.
Combining Deep Neural Network with Genetic Algorithm for Axial Flow Fan Design and Development
Authors: Liu Yu-Ling , Nisa Elsa Chaerun , Kuan Yean-Der , Luo Win-Jet , Feng Chien-Chung
Published: January 2023

Axial flow fans are commonly used for a system or machinery cooling process. It also used for ventilating warehouses, factories, and garages. In the fan manufacturing industry, the demand for varying fan operating points makes design parameters complicated because many design parameters affect the fan performance. This study combines the deep neural network (DNN) with a genetic algorithm (GA) for axial flow design and development. The characteristic fan curve (P-Q Curve) can be generated when the relevant fan parameters are imported into this system. The system parameters can be adjusted to achieve the required characteristic curve. After the wind tunnel test is performed for verification, the data are integrated and corrected to reduce manufacturing costs and design time. This study discusses a small axial flow fan NACA and analyzes fan features, such as the blade root chord length, blade tip chord length, pitch angle, twist angle, fan diameter, and blade number. Afterwards, the wind tunnel performance test was performed and the fan performance curve obtained. The feature and performance test data were discussed using deep learning. The Python programming language was used for programming and the data were trained repeatedly. The greater the number of parameter data, the more accurate the prediction. Whether the performance condition is met could be learnt from the training result. All parameters were calculated using a genetic algorithm. The optimized fan features and performance were screened out to implement the intelligent fan design. This method can solve many fan suppliers’ fan design problems.
Estimation of Small-Scale Kinetic Parameters of Escherichia coli (E. coli) Model by Enhanced Segment Particle Swarm Optimization Algorithm ESe-PSO
Authors: Azrag Mohammed Adam Kunna , Zain Jasni Mohamad , Kadir Tuty Asmawaty Abdul , Yusoff Marina , Jaber Aqeel Sakhy , Abdlrhman Hybat Salih Mohamed , Ahmed Yasmeen Hafiz Zaki , Husain Mohamed Saad Bala
Published: January 2023

The ability to create “structured models” of biological simulations is becoming more and more commonplace. Although computer simulations can be used to estimate the model, they are restricted by the lack of experimentally available parameter values, which must be approximated. In this study, an Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm that can estimate the values of small-scale kinetic parameters is described and applied to E. coli’s main metabolic network as a model system. The glycolysis, phosphotransferase system, pentose phosphate, the TCA cycle, gluconeogenesis, glyoxylate pathways, and acetate formation pathways of Escherichia coli are represented by the Differential Algebraic Equations (DAE) system for the metabolic network. However, this algorithm uses segments to organize particle movements and the dynamic inertia weight (ω) to increase the algorithm’s exploration and exploitation potential. As an alternative to the state-of-the-art algorithm, this adjustment improves estimation accuracy. The numerical findings indicate a good agreement between the observed and predicted data. In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. As a result of this innovative approach, it was concluded that small-scale and even entire cell kinetic model parameters can be developed.
Photo-Ordering and Deformation in Azobenzene-Containing Polymer Networks under Irradiation with Elliptically Polarized Light
Authors: Toshchevikov Vladimir , Saphiannikova Marina
Published: January 2023

Azobenzene-containing polymers (azo-polymers) have been a subject of extensive investigations during the last two and half decades, due to their remarkable ability to undergo pronounced alignment and deformation under irradiation with light. The molecular ordering and deformation in azo-polymers of various structures under irradiation with linearly polarized light was described in a series of theoretical works, based on the effect of the reorientation of azobenzene moieties due to the anisotropic character of the photoisomerization processes. In the present study, we generalize the previous orientation approach to describe the photo-alignment and deformation of azo-polymer networks under irradiation with elliptically polarized light. We demonstrate that, in general, the light-induced ordering and deformation have a biaxial symmetry defined by the polarization ellipse. Azobenzene chromophores have a tendency to align along the direction of light propagation, the orientation in the other two directions being dependent of the aspect ratio of the polarization ellipse. This causes deformation of azo-polymer networks along the direction of light propagation, the sign of which (expansion/contraction) is defined by a chemical structure of network strands. Theoretical results are in agreement with experiments and have a practical importance to predict the photo-mechanical response of azo-polymers depending on their structure and on the polarization of light.
How Soil Microbial Communities from Industrial and Natural Ecosystems Respond to Contamination by Polycyclic Aromatic Hydrocarbons
Authors: Picariello Enrica , Baldantoni Daniela , De Nicola Flavia
Published: January 2023

Soil microbial community plays a major role in removal of polycyclic aromatic hydrocarbons (PAHs) from soil, and bioremediation potentially offers an attractive and economic approach to the clean-up of polluted areas. To evaluate the contribution of different microbial groups in soil PAH degradation, enzymatic activity and phospholipid fatty acids (PLFAs) were analysed in a mesocosm trial in three different soils (two natural and one industrial) artificially contaminated with 3- and 5-rings PAHs. The Metabolic Activity Index (MAI) was applied to investigate the microbial community stability, in terms of resistance and resilience. Gram+ and Gram- bacteria were the predominant microbial groups in all soil types. In the first stage of incubation, fungi were predominant in the industrial soil, followed by mycorrhizae and actinomycetes, indicating their stimulation after PAH addition. In the two natural soils, several groups were predominant: actinomycetes in one, fungi and mycorrhizae in the other, indicating a different response of the two natural soils to PAH contamination. Regarding MAI calculated on the enzymatic activities, one natural soil showed a microbial community neither resistant nor resilient in respect to the other and to the industrial soil. Our results highlight that the microbial community changes its composition and then physiological functions according to the land use as a result of PAH addition.
Quality Control of Water-Efficient Products Based on DMAIC Improved Mode—A Case Study of Smart Water Closets
Authors: Bai Yan , Liu Jialin , Zhang Rui , Bai Xue
Published: January 2023

Water-efficient products, a key component of water-saving technology, are widely installed and utilized in all sectors of society. Due to China’s extensive and varied use of this product, advancements in effectiveness and quality will significantly enhance people’s standard of living. In recent years, manufacturers, corporate purchasers, and individual customers have given more attention to the quality of these items due to the spike in local market and export demands for water-efficient products in China. It has been a pressing problem to find a practical solution for increasing product quality in a reasonable and scientific manner. In order to build a DECIA quality improvement model for water-efficient product quality that is quantifiable and technically practical, this paper investigates how to improve the quality of smart water closets based on six-sigma management. Thus, the development of a water-efficient industry can be green and sustainable.
Task-Offloading and Resource Allocation Strategy in Multidomain Cooperation for IIoT
Authors: Dai Zuojun , Zhou Ying , Tian Hui , Ma Nan
Published: January 2023

This study proposes a task-offloading and resource allocation strategy in multidomain cooperation (TARMC) for the industrial Internet of Things (IIoT) to resolve the problem of the non-uniform distribution of task computation among various cluster domain networks in the IIoT and the solidification of traditional industrial wireless network architecture, which produces low efficiency of static resource allocation and high delay in closed-loop data processing. Based on the closed-loop process of task interaction of intelligent terminals in wireless networks, the proposed strategy constructs a network model of multidomain collaborative task-offloading and resource allocation in IIoT for flexible and dynamic resource allocation among intelligent terminals, edge servers, and cluster networks. Considering the partial offloading mechanism, various tasks were segmented into multiple subtasks marked at bit-level per demand, which enabled local and edge servers to process all subtasks in parallel. Moreover, this study established a utility function for the closed-loop delay and terminal energy consumption of task processing, which transformed the process of multidomain collaborative task-offloading and resource allocation into the problem of task computing revenue. Furthermore, an improved Cuckoo Search algorithm was developed to derive the optimal offloading position and resource allocation decision through an alternating iterative method. The simulation results revealed that TARMC performed better than strategies.
Liquid Loading of Horizontal Gas Wells in Changbei Gas Field
Authors: Huang Zhimin , Cai Wenbin , Zhang Huiren , Mo Xiangyang
Published: January 2023

The Changbei gas field, which initially exhibited high gas-production performance, is dominated by large-displacement horizontal wells. With the decrease in reservoir pressure, the liquid loading in the gas well is currently severe, and production has been rapidly decreasing. Thus, recognizing the gas-well liquid loading to maintain stable gas-well production is necessary. A method was established to identify the water source of the liquid loading in the Changbei gas field. First, formation water and condensate water were identified based on the mineralization of the recovered water and the mass concentration of Cl− and K+ + Na+, and then the condensate content of the water produced in the gas well was qualitatively evaluated. The water–gas ratio curve for the gas well was plotted to determine whether the produced water was edge-bottom water, pore water, or condensate. Then a method was established to distinguish the start time of liquid loading in the gas well using a curve depicting a decrease in production; the method was also used to estimate the depth of the gas well where liquid loading occurs, according to the bottomhole pressure. First, based on the available production data, the Arps decline model was applied to fit the production curve for the entire production phase; the resulting curve was compared with the actual production curve of the gas well, and the two curves diverged when fluid accumulation began in the gas well. Finally, the liquid-loading depth of the gas well was estimated based on the bottomhole pressure. This method can be used to determine the fluid accumulation and calculate the liquid-loading depth of gas wells with unconnected oil jackets. The analysis revealed that in the Changbei gas field, condensate was the type of water primarily produced in 35 gas wells, accounting for 62.5% of the total number of gas wells. Edge-bottom water was the type of water primarily produced in 16 gas wells, accounting for 28.6% of the total number of gas wells. In the remainder of the gas wells, pore water was the water primarily produced; the calculations of accumulation time and accumulation volume of typical gas wells in the block revealed that some gas wells started to accumulate liquid after 45–50 months, and the amount of accumulation could reach several tens of meters, while others were in good production condition. The method established in this paper could enhance our understanding of liquid loading in gas wells in the Changbei gas field and lay a foundation for the development of gas-well deliquification techniques.
Food Waste Prevention: Reduction, Reuse, and Recycling
Authors: Abeliotis Konstadinos , Lasaridi Katia
Published: January 2023

Food loss and waste (FLW) is a global concern that has adverse environmental, social, and economic impacts [...]
Quantifying the Reliability and Uncertainty of Satellite, Reanalysis, and Merged Precipitation Products in Hydrological Simulations over the Topographically Diverse Basin in Southwest China
Authors: Lei Huajin , Zhao Hongyu , Ao Tianqi , Hu Wanpin
Published: January 2023

With the continuous emergence of remote sensing technologies and atmospheric models, multi-source precipitation products (MSPs) are increasingly applied in hydrometeorological research, especially in ungauged or data-scarce regions. This study comprehensively evaluates the reliability of MSPs and quantifies the uncertainty of sources in streamflow simulation. Firstly, the performance of seven state-of-the-art MSPs is assessed using rain gauges and the Block-wise use of the TOPMODEL (BTOP) hydrological model under two calibration schemes over Jialing River Basin, China. Then, a variance decomposition approach (Analysis of variance, ANOVA) is employed to quantify the uncertainty contribution of precipitation products, model parameters, and their interaction in streamflow simulation. The MSPs include five satellite-based (GSMaP, IMERG, PERCDR, CHIRPS, CMORPH), one reanalysis (ERA5L), and one ensembled product (PXGB2). The results of precipitation evaluation show that the MSPs have temporal and spatial variability and PXGB2 has the best performance. The hydrologic utility of MSPs is different under different calibration methods. When using gauge-based calibration parameters, the PXGB2-based simulation performs best, whereas CHIRPS, PERCDR, and ERA5L show relatively poor performance. In comparison, the model recalibrated by individual MSPs significantly improves the simulation accuracy of most MSPs, with GSMaP having the best performance. The ANOVA results reveal that the contribution of precipitation products to the streamflow uncertainty is larger than model parameters and their interaction. The impact of interaction suggests that a better simulation attributes to an optimal combination of precipitation products and model parameters rather than solely relying on the best MSPs. These new findings are valuable for improving the suitability of MSPs in hydrologic applications.
A Structure Identification Method for Urban Agglomeration Based on Nighttime Light Data and Railway Data
Authors: Xie Zhiwei , Yuan Mingliang , Zhang Fengyuan , Chen Min , Tian Meng , Sun Lishuang , Su Guoqing , Liu Ruizhao
Published: January 2023

The urban spatial structure is a key feature of the distribution of social and economic resources. The spatial structure of an urban agglomeration is an abstract relationship expression of urbanization. Urban agglomerations develop for multiple reasons, including urban planning and natural evolution. To date, most research related to urban agglomeration has been based on single data source, which is a limitation. This research aims to propose a spatial structure identification method for urban agglomerations via a complex network based on nighttime light data and railway data. Firstly, we extracted the urban built-up area using defense meteorological satellite program/operational line scanner (DMSP/OLS) data, and divided it into urban objects to obtain the nighttime light urban network (NLUN) by borough. Secondly, we aggregated railway stations at municipal level using railway operation data to obtain the railway urban network (RUN). Following this, we established a composite urban network (CUN) consisting of the NLUN and the RUN based on the composite adjacency matrix. Finally, the Louvain algorithm and the comprehensive strength index (CSI) were used to detect the communities and central nodes of the CUN and obtain the urban agglomerations and core cities. The results show that urban agglomeration identification based on the CUN has the best accuracy, which is 5.72% and 15.94% higher than that of the NLUN and RUN, respectively. Core cities in the urban agglomeration identified by the CSI in the CUN are at least 3.04% higher than those in the single-source urban network. In addition, the distribution pattern of Chinese urban agglomerations in the study area is expressed as “three vertical”, and the development level of urban agglomeration shows an unbalanced trend.
Research on Optimization of Processing Parcels of New Bare Land Based on Remote Sensing Image Change Detection
Authors: Liu Lirong , Tang Xinming , Gan Yuhang , You Shucheng , Luo Zhengyu , Du Lei , He Yun
Published: January 2023

To meet the demands of natural resource monitoring, land development supervision, and other applications for high-precision and high-frequency information extraction from constructed land change, this paper focused on automatic feature extraction and data processing optimization methods for newly constructed bare land based on remote sensing images. A generalized deep convolutional neural network change detection model framework integrating multi-scale information was developed for the automatic extraction of change information. To resolve the problems in the automatic extraction of new bare land parcels, such as mis-extractions and parcel fragmentation, a proximity evaluation model that integrates the confidence-based semantic distance and spatial distance between parcels and their overlapping area is proposed to perform parcel aggregation. Additionally, we propose a complete set of optimized processing techniques from pixel pre-processing to vector post-processing. The results demonstrated that the aggregation method developed in this study is more targeted and effective than ArcGIS for the automatically extracted land change parcels. Additionally, compared with the initial parcels, the total number of optimized parcels decreased by more than 50% and the false detection rate decreased by approximately 30%. These results indicate that this method can markedly reduce the overall data volume and false detection rate of automatically extracted parcels through post-processing under certain conditions of the model and samples and provide technical support for applying the results of automatic feature extraction in engineering practices.
Enhancement of Photovoltaic Power Potential in China from 2010 to 2020: The Contribution of Air Pollution Control Policies
Authors: Zhang Yujie , Qin Wenmin , Wang Lunche , Yang Chao , Su Xin , Wu Jinyang
Published: January 2023

China is expected to have a total installed photovoltaic capacity of 1300 GW in 2050, accounting for 39% of the national electricity consumption. However, air pollutants consisting of gases and particulates have attenuation effects on the solar radiation reaching the photovoltaic panels. This work purports to assess the influence of air pollutants on the photovoltaic power potential. We calculated the hourly point-of-array irradiance (POAI) in China for 2010–2020 with a spatial resolution of 0.1° × 0.1° using the PV_LIB model and assessed the effect of air pollutants on POAI. The results indicated that the annual average POAI in China for 2010–2020 ranged from 118 to 286 Wm−2. The Air Pollution Control Action Plan (APPCAP) has played a certain role in photovoltaic power potential, and POAI has increased in areas where surface concentrations of air pollutants have declined. Especially in North China, the surface concentrations of CO, NO2, PM10, PM2.5, and SO2 decreased throughout the APPCAP period with −0.446, −4.985, −35.610, −30.700, and −26.251 μgm−3, respectively, corresponding to an increase in POAI of up to 4.917 Wm−2. The surface concentrations of CO, NO2, PM10, PM2.5, and SO2 were negatively correlated with POAI, with correlation coefficients of −0.764, −0.854, −0.204, −0.110, and −0.664, respectively. Surface concentrations of air pollutants (CO, NO2, PM10, PM2.5, and SO2) and clear-sky POAI in 2018 showed a High-Low clustering in Northeast China and North China. This study demonstrates the role of China’s air pollution control policy in enhancing photovoltaic power potential.
Effects of Mesoscale Eddies in the Northern South China Sea on Phytoplankton Size and Physiological Status
Authors: Chen Jinzheng , Liu Fenfen
Published: January 2023

Mesoscale eddies have essential effects on the distribution of the different sizes of phytoplankton and the status of phytoplankton physiology. The impact of mesoscale eddies on phytoplankton size and physiological level in the northern South China Sea is analyzed based on satellite data and HYCOM-simulated results from 2003 to 2018. The results show that there are higher nanophytoplankton levels for high and low nonlinearity in the center of cyclonic eddies. At the same time, the growth rate of phytoplankton increased, and the assimilation of phytoplankton decreased. Moreover, in the center of anticyclonic eddies, a lower nanophytoplankton level is observed in both high and low nonlinearity. At the same time, the growth rate of phytoplankton decreased, and the assimilation of phytoplankton increased. In addition, there is a higher nanophytoplankton level in the mode-water eddy, while the growth rate of phytoplankton is increased, and the assimilation of phytoplankton is decreased.
Improving the Operational Simplified Surface Energy Balance Evapotranspiration Model Using the Forcing and Normalizing Operation
Authors: Senay Gabriel B. , Parrish Gabriel E. L. , Schauer Matthew , Friedrichs MacKenzie , Khand Kul , Boiko Olena , Kagone Stefanie , Dittmeier Ray , Arab Saeed , Ji Lei
Published: January 2023

Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration (ETa) estimates with AmeriFlux eddy covariance (EC) and water balance ETa from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based ETa bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration (ETr) produced comparable ETa results, justifying the use of climatology ETr for the global SSEBop Landsat ETa that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of ETa for localized water budget applications.
Shallow-to-Deep Spatial–Spectral Feature Enhancement for Hyperspectral Image Classification
Authors: Zhou Lijian , Ma Xiaoyu , Wang Xiliang , Hao Siyuan , Ye Yuanxin , Zhao Kun
Published: January 2023

Since Hyperspectral Images (HSIs) contain plenty of ground object information, they are widely used in fine-grain classification of ground objects. However, some ground objects are similar and the number of spectral bands is far higher than the number of the ground object categories. Therefore, it is hard to deeply explore the spatial–spectral joint features with greater discrimination. To mine the spatial–spectral features of HSIs, a Shallow-to-Deep Feature Enhancement (SDFE) model with three modules based on Convolutional Neural Networks (CNNs) and Vision-Transformer (ViT) is proposed. Firstly, the bands containing important spectral information are selected using Principal Component Analysis (PCA). Secondly, a two-layer 3D-CNN-based Shallow Spatial–Spectral Feature Extraction (SSSFE) module is constructed to preserve the spatial and spectral correlations across spaces and bands at the same time. Thirdly, to enhance the nonlinear representation ability of the network and avoid the loss of spectral information, a channel attention residual module based on 2D-CNN is designed to capture the deeper spatial–spectral complementary information. Finally, a ViT-based module is used to extract the joint spatial–spectral features (SSFs) with greater robustness. Experiments are carried out on Indian Pines (IP), Pavia University (PU) and Salinas (SA) datasets. The experimental results show that better classification results can be achieved by using the proposed feature enhancement method as compared to other methods.
Monitoring the Production Information of Conventional Machining Equipment Based on Edge Computing
Authors: Wang Yuguo , Shen Miaocong , Zhu Xiaochun , Xie Bin , Zheng Kun , Fei Jiaxiang
Published: January 2023

A production status monitoring method based on edge computing is proposed for traditional machining offline equipment to address the deficiencies that traditional machining offline equipment have, which cannot automatically count the number of parts produced, obtain part processing time information, and discern anomalous operation status. Firstly, the total current signal of the collected equipment was filtered to extract the processing segment data. The processing segment data were then used to manually calibrate the feature vector of the equipment for specific parts and processes, and the feature vector was used as a reference to match with the real-time electric current data on the edge device to identify and obtain the processing start time, processing end time, and anomalous marks for each part. Finally, the information was uploaded to further obtain the part processing time, loading and unloading standby time, and the cause of the anomaly. To verify the reliability of the method, a prototype system was built, and extensive experiments were conducted on many different types of equipment in an auto parts manufacturer. The experimental results show that the proposed monitoring algorithm based on the calibration vector can stably and effectively identify the production information of each part on an independently developed edge device.