bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulating Polymerization by Boltzmann Inversion Force Field Approach and Dynamical Nonequilibrium Reactive Molecular Dynamics
Authors: Monteferrante Michele , Succi Sauro , Pisignano Dario , Lauricella Marco
Published: October 2022

The radical polymerization process of acrylate compounds is, nowadays, numerically investigated using classical force fields and reactive molecular dynamics, with the aim to probe the gel-point transition as a function of the initial radical concentration. In the present paper, the gel-point transition of the 1,6-hexanediol dimethacrylate (HDDMA) is investigated by a coarser force field which grants a reduction in the computational costs, thereby allowing the simulation of larger system sizes and smaller radical concentrations. Hence, the polymerization is investigated using reactive classical molecular dynamics combined with a dynamical approach of the nonequilibrium molecular dynamics (D-NEMD). The network structures in the polymerization process are probed by cluster analysis tools, and the results are critically compared with the similar all-atom system, showing a good agreement.
Investigation of Hemp and Flax Fiber-Reinforced EcoPoxy Matrix Biocomposites: Morphological, Mechanical, and Hydrophilic Properties
Authors: Atmakuri Ayyappa , Palevicius Arvydas , Janusas Giedrius , Eimontas Justas
Published: October 2022

Modern day industries are highly focused on the development of bio-inspired hybrid natural fiber composites for lightweight biosensor chips, automobile, and microfluidic applications. In the present research, the mechanical properties and morphological characteristics of alkaline (NaOH)-treated hemp, flax, noil hemp, and noil flax fiber-reinforced ecopoxy biocomposites were investigated. The samples were fabricated by employing the hand layup technique followed by the compression molding process. A total of two sets of composites with various weight fractions were fabricated. The samples were tested for mechanical properties such as flexural strength, interlaminar shear strength, moisture absorption, and contact angle measurement. The treated fibers were analyzed by using an optical microscope and Fourier transform infrared spectrometer (FTIR). The morphological characteristics, such as porosity and fracture mechanisms, were investigated by using scanning electron microscopy and SEM−EDX spectroscopy. The results revealed that the flexural properties of hybrid composites vary from 22.62 MPa to 30.04 MPa for hemp and flax fibers and 21.86 MPa to 24.70 MPa for noil fibers, whereas in individual fiber composites, the strength varies from 17.11 MPa to 21.54 MPa for hemp and flax fibers and 15.83 MPa to 18.79 MPa for noil fibers. A similar trend was observed in interlaminar shear properties in both cases. From moisture analysis, the rate of absorption is increased with time up to 144 h and remains constant in both cases. The moisture gain was observed more in individual composites than hybrid composites in both cases. Hence, the impact of hybridization was observed clearly in both cases. Also, hybrid composites showed improved properties compared to individual fiber composites.
Development of an Epoxy-Based Rapid Tool with Low Vulcanization Energy Consumption Channels for Liquid Silicone Rubber Injection Molding
Authors: Kuo Chil-Chyuan , Tasi Qing-Zhou , Hunag Song-Hua
Published: October 2022

Liquid silicone rubber (LSR) parts have some distinct characteristics such as superior heat stability, low-temperature flexibility, aging resistance, and chemical resistance. From an industrial standpoint, the uniform vulcanization temperature of LSR is an important research point. However, the uniformity of the vulcanization temperature of LSR has been limited since the layout of the cartridge heater incorporated in the conventional steel mold does not follow the profile of the mold cavity. Metal additive manufacturing can be used to make LSR injection molds with conformal heating channels and conformal cooling channels simultaneously. However, this method is not suitable for a mold required to develop a new LSR product. In this study, a cost-effective approach was proposed to manufacture an LSR injection mold for the pilot run of a new optical lens. A rapid tool with low vulcanization energy consumption channels was proposed, which was incorporated with both a conformal heating channel (CHC) and conformal cooling channel (CCC) simultaneously. The function of the CHC was to vulcanize the LSR in the cavity uniformly, resulting in a shorter cycle time. The function of the CCC was to keep the LSR in a liquid state for reducing runner waste. It was found that the equation of y = −0.006x3 + 1.2114x2 − 83.221x + 1998.2 with the correlation coefficient of 0.9883 seemed to be an optimum trend equation for predicting the solidification time of a convex lens (y) using the vulcanizing hot water temperature (x). Additionally, the equation of y = −0.002x3 + 0.1329x2 − 1.0857x + 25.4 with the correlation coefficient of 0.9997 seemed to be an optimum prediction equation for the solidification time of a convex lens (y) using the LSR weight (x) since it had the highest correlation coefficient. The solidification time of a convex lens could be reduced by about 28% when a vulcanizing hot water temperature of 70 °C was used in the LSR injection mold with CHC.
Monitoring the Recombinant Adeno-Associated Virus Production using Extended Kalman Filter
Authors: Iglesias Cristovão Freitas , Xu Xingge , Mehta Varun , Akassou Mounia , Venereo-Sanchez Alina , Belacel Nabil , Kamen Amine , Bolic Miodrag
Published: October 2022

The recombinant adeno-associated virus (rAAV) is a viral vector technology for gene therapy that is considered the safest and most effective way to repair single-gene abnormalities in non-dividing cells. However, improving the viral titer productivity in rAAV production remains challenging. The first step to this end is to effectively monitor the process state variables (cell density, GLC, GLN, LAC, AMM, and rAAV viral titer) to improve the control performance for an enhanced productivity. However, the current approaches to monitoring are expensive, laborious, and time-consuming. This paper presents an extended Kalman filter (EKF) approach used to monitor the rAAV production using the online viable cell density measurements and estimating the other state variables measured at a low frequency. The proposed EKF uses an unstructured mechanistic kinetic model applicable in the upstream process. Three datasets were used for parameter estimation, calibration, and testing, and the data were collected from the production of rAAV through a triple-plasmid transfection of HEK293SF-3F6 cells. Overall, the proposed approach accurately estimated metabolite concentrations and the rAAV production yield. Therefore, the approach has a high potential to be extended to an online soft sensor and to be classified as a cost-effective and fast approach to the monitoring of rAAV production.
Recent Advances in the Equal Channel Angular Pressing of Metallic Materials
Authors: Cui Lang , Shao Shengmin , Wang Haitao , Zhang Guoqing , Zhao Zejia , Zhao Chunyang
Published: October 2022

Applications of a metallic material highly depend on its mechanical properties, which greatly depend on the material’s grain sizes. Reducing grain sizes by severe plastic deformation is one of the efficient approaches to enhance the mechanical properties of a metallic material. In this paper, severe plastic deformation of equal channel angular pressing (ECAP) will be reviewed to illustrate its effects on the grain refinement of some common metallic materials such as titanium alloys, aluminum alloys, and magnesium alloys. In the ECAP process, the materials can be processed severely and repeatedly in a designed ECAP mold to accumulate a large amount of plastic strain. Ultrafine grains with diameters of submicron meters or even nanometers can be achieved through severe plastic deformation of the ECAP. In detail, this paper will give state-of-the-art details about the influences of ECAP processing parameters such as passes, temperature, and routes on the evolution of the microstructure of metallic materials. The evolution of grain sizes, grain boundaries, and phases of different metallic materials during the ECAP process are also analyzed. Besides, the plastic deformation mechanism during the ECAP process is discussed from the perspectives of dislocation slipping and twinning.
Effect of Poultry Manure-Derived Compost on the Growth of eucalypts spp. Hybrid Clones
Authors: Rizzo Pedro F. , Salinas María C. , Della Torre Virginia , Diez Juan P. , Sallesses Leonardo F. , Riera Nicolás I. , Pathauer Pablo S. , Komilis Dimitrios , Sánchez Antoni
Published: October 2022

Interspecific hybrids of E. grandis × E. camaldulensis were generated to widen the plantation area. The aim of this study was to assess root capability and development for six different clones of eucalyptus grown in substrates made with three different composts derived from poultry manure. A factorial design was used to assess the effect of different composts on six growth variables. The analysis detected a greater effect from the genotype than the substrate. E. grandis × E. camaldulensis hybrid vegetative propagation was successful in alternative substrates formulated from composted poultry manure. GC8 was the genotype that showed the greatest differences for four the different variables among the substrates, being both the most sensitive and the one with the highest values for all parameters measured. The hybrids’ vegetative propagation was determined in alternative substrates formulated from poultry manure compost. The physicochemical characteristics of substrates composed of pine bark and sawdust provided adequate conditions for the growth of eucalyptus. GC8 was the genotype most sensitive to the use of different substrates, showing significant differences in the ratio of roots/callus, radicular dry weight, and cutting dry weight. These clones might be a good option for evaluating compost-based substrates for forestry applications.
Coal-Scenedesmus Microalgae Co-Firing in a Fixed Bed Combustion Reactor: A Study on CO2, SO2 and NOx Emissions and Ash
Authors: Magida Nokuthula Ethel , Dugmore Gary , Ogunlaja Adeniyi Sunday
Published: October 2022

This study investigated the effect of coal–Scenedesmus microalgae (with blending ratios of 100:0 (coal), 95:5 (Coalgae® 5%), 90:10 (Coalgae® 10%), 85:15 (Coalgae® 15%) and 80:20 (Coalgae® 20%)) on combustion temperature, mass loss, the formation of CO2, SO2 and NOx gases, and ash content under constant atmospheric air flow. Coalgae® refers to a material formed after blending coal and microalgae. The results showed that NOx came mainly from Coalgae® 10% and 15%, and this observation could be attributed to a variable air concentration level (O2 level) in the environment that could influence NOx during the combustion process, irrespective of the blending ratios. CO2 emission reductions (12%, 17%, 21% and 29%) and SO2 emission reductions (3%, 12%, 16% and 19%) increased with the increasing coal-microalgae blending ratio (Coalgae® 5–20%), respectively. Bubble-like morphology was observed in the ash particles of coal–microalgae blends through SEM, while the TEM confirmed the formation of carbon-based sheets and graphitic-based nanocomposites influenced by the microalgae amounts. Ash residues of the coal–microalgae blends contained high amounts of fluxing compounds (Fe2O3, K2O, CaO and MgO), which resulted in an increased base/acid ratio from 0.189 (coal) to 0.568 (Coalgae® 20%). Based on the above findings, the co-firing of coal–Scenedesmus microalgae led to a reduction in CO2, SO2, and NOx emissions. As such, lower Coalgae® blends can be considered as an alternative fuel in any coal-driven process for energy generation.
Omega-3 Fatty Acid Retention and Oxidative Stability of Spray-Dried Chia–Fish-Oil-Prepared Microcapsules
Authors: Rahim Muhammad Abdul , Imran Muhammad , Khan Muhammad Kamran , Haseeb Ahmad Muhammad , Nadeem Muhammad , Khalid Waseem , Lorenzo Jose Manuel , Afifi Mohamed M. , AL-Farga Ammar , Aljobair Moneera O.
Published: October 2022

Background: Omega-3 fatty acids are essential fatty acids that the body cannot create itself; thus, they must be obtained from functional foods. Therefore, the food processing industries are becoming more interested in the production of omega-3 enriched food products, as consumers and healthcare organizations are increasingly demanding functional foods with minimal fatty acid loss and higher oxidative stability. Moreover, the stability of long-chain, polyunsaturated fatty acids in functional foods is a major challenge for the food processing industries. Therefore, the spray drying method was used to prepare spray-dried microcapsules (SDMs) with the minimum loss of, and more stable, fatty acids. Methods: In this study, emulsion blends of chia seed oil (CSO, 50%) and fish oil (FO, 50%) were spray-dried using varied operating conditions, including the inlet air temperature (IAT) (125, 140, 155, 170, and 185 °C), wall material (WM) (5, 10, 15, 20, and 25%), pump speed (PS) (3, 4, 5, 6, and 7 mL/min), and needle speed (NS) (3, 5, 7, 9, and 11 S). Results: The maximum loss of ALA in the spray-dried microcapsules (SDMs) was observed (9.90 ± 0.40%) at 170 °C, and the minimum loss was 4.18 ± 0.20% in run order 9. A similar trend was observed in the maximum retention loss of EPA and DHA (9.71 ± 0.39% and 9.77 ± 0.39%) at a high temperature of 170 °C, while the minimum losses of EPA and DHA were observed in run order 9. Furthermore, the maximum peroxide value (PV) of the SDMs was observed at a lower temperature of 140 °C (1.45 ± 0.19 meq O2/kg), and the minimum PV was 1.33 ± 0.16 meq O2/kg. Conclusions: Overall, based on the results, we concluded that the oxidative stability of the SDMs was improved and that it can be used as a fortifying agent in the processing of many food products.
Deep Learning with Spatial Attention-Based CONV-LSTM for SOC Estimation of Lithium-Ion Batteries
Authors: Tian Huixin , Chen Jianhua
Published: October 2022

Accurate estimation of the state of charge (SOC) is an indispensable part of a vehicle management system. The accurate estimation of SOC can ensure the safe and reliable operation of the vehicle management system. With the development of intelligent transportation systems (ITS), vehicles can not only obtain the dynamic changes inside the battery through sensors, but also obtain the traffic information around the vehicle through vehicle–road collaboration. In addition, the development of onboard graphic processing units (GPUs) and Internet of Vehicles (IOV) technology make the computing power of vehicles no longer limited by hardware, which makes neural networks applied to the intelligent control of vehicles. Aiming at the problem that the traditional network cannot effectively obtain the complex spatial information of sample attributes, we developed an attention-based CONV-LSTM module for SOC prediction based on a convolutional neural network (CNN) and a long short-term memory (LSTM) network. Different from the traditional LSTM network, the algorithm not only considers the temporal correlation of the data stream, but also captures the spatial correlation information of the input data by convolution. It then uses the different weights, automatically assigned by the attention mechanism, to correctly distinguish the importance of different input data streams. In order to verify the validity of the model, this paper selects the degradation data set of the aeroengine as the verification data set. Experiments show that the proposed model has achieved good results. Finally, the proposed model is applied to the actual vehicle running data, and the effectiveness of the proposed model is verified by comparing it with the Multi-Layer Perceptron (MLP), LSTM, and CNN-LSTM models.
A High-Throughput Screening Procedure (Py-Fe3+) for Enhancing Ethanol Production by Saccharomyces cerevisiae Using ARTP Random Mutagenesis
Authors: Wang Wei-Yang , Wu Shi-Hua , Xie Yuan-Han , Zhong Miao , Wei Man-Li , Li Ze-Yang , Long Xiu-Feng , Niu Fu-Xing
Published: October 2022

Saccharomyces cerevisiae is an important microbial organization involved in ethanol synthesis. Mutant strains that can withstand multiple pressures during this process are critical to the industrial development of biofuels. In this study, a dual high-throughput screening method of Triphenyl-2H-tetrazoliumchloride (TTC)-based macroscopic observation and the reaction of ferric nitrate with pyruvate (or pyruvate radical ion) in fermentation broth was used. Using this, an S. cerevisiae mutant library that could tolerate 381 g/L sucrose was established by ARTP random mutation and adaptive evolution to select the best strain; its ethanol yield was increased by an additional 20.48%; and the sucrose utilization rate was 81.64%. This method is specific to the selection of strains with increased ethanol production.
Destabilization Mechanism and Stability Control of the Surrounding Rock in Stope Mining Roadways below Remaining Coal Pillars: A Case Study in Buertai Coal Mine
Authors: Fu Qiang , Yang Ke , He Xiang , Liu Qinjie , Wei Zhen , Wang Yu
Published: October 2022

To study the stability control of stope mining roadways below remaining coal pillars, the present study investigates the destabilization mechanism of coal pillars and roadways in sections under the dual action of supporting pressure on the floor of the remaining coal pillar in the overlying coal seam and the mining at the working face of the lower coal seam and clarify the principle of surrounding rock stability control based on theoretical analysis, numerical simulation, and industrial testing. The results yielded the following findings. After the stope mining of the overlying coal seam working face, the stress transfer of the T-shaped remaining coal pillar significantly increased the vertical stress of the lower coal seam. The lateral support pressure generated by the stope mining at the lower coal seam working face further aggravated the stress concentration in the coal, leading to severe compression-shear failure of the surrounding rock. As the sectional coal pillar becomes wider, the roadway gradually avoids the area of peak superimposed support pressure. The vertical stress curve of the sectional coal pillar shifts from single-peaked to asymmetrically double-peaked, and the stress difference between the two roadway ribs and the stress concentration coefficients decrease continuously. A stability control method of long anchor cable reinforcement support is proposed. In-situ industrial testing showed that the surrounding rock deformation was basically stable during the service period of the 42202 stope mining roadway, thus achieving the stability control of the stope mining roadway.
Desired Dynamics-Based Generalized Inverse Solver for Estimation Problems
Authors: Liu Shaojie , Zhang Yulong , Gao Zhiqiang , Chen Yangquan , Li Donghai , Zhu Min
Published: October 2022

An important task for estimators is to solve the inverse. However, as the designs of different estimators for solving the inverse vary widely, it is difficult for engineers to be familiar with all of their properties and to design suitable estimators for different situations. Therefore, we propose a more structurally unified and functionally diverse estimator, called generalized inverse solver (GIS). GIS is inspired by the desired dynamics of control systems and understanding of the generalized inverse. It is similar to a closed-loop system, structurally consisting of nominal models and an error-correction mechanism (ECM). The nominal models can be model-based, semi-model-based, or even model-free, depending on prior knowledge of the system. In addition, we design the ECM of GIS based on desired dynamics parameterization by following a simple and meaningful rule, where states are directly used in the ECM to accelerate the convergence of GIS. A case study considering a rotary flexible link shows that GIS can greatly improve the noise suppression performance with lower loss of dynamic estimation performance, when compared with other common observers at the same design bandwidth. Moreover, the dynamic estimation performances of the three GIS approaches (i.e., model-based, semi-model-based, and model-free) are almost the same under the same parameters. These results demonstrate the strong robustness of GIS (although by means of the uniform design method). Finally, some control cases are studied, including a comparison with DOB and ESO, in order to illustrate their approximate equivalence to GIS.
S-Velocity Profile of Industrial Robot Based on NURBS Curve and Slerp Interpolation
Authors: Wang Guirong , Xu Fei , Zhou Kun , Pang Zhihui
Published: October 2022

This paper presents a novel algorithm for industrial robot trajectory planning based on the NURBS(Non-Uniform Rational B-Spline) curve and Slerp interpolation aiming at the problems that the trajectory of a six-axis industrial robot is not smooth enough in the operation process, the posture planning process is non-uniform, and the six-axis industrial robot starts and stops frequently. Firstly, aiming at the first problem, the trajectory planning algorithm based on the NURBS curve is presented to improve the smoothness of the trajectory curve. Combined with Slerp posture planning based on quaternion description, which realizes the uniform change of posture on the robot’s end-effector. Secondly, aiming at the second problem, the S-velocity planning algorithm is presented in the interpolation interval of the robot, which realizes the operation process of complex curves continuously, and improves the operation quality. Finally, this paper uses Bernoulli’s lemniscate as the incentive trajectory, and the contrast experiment of trajectory planning between two incentive profiles is designed, which are the NURBS curve and the five-order polynomial curve. The result of the experiment indicates that the planning algorithm proposed in this paper could effectively improve the smoothness of trajectory in a Cartesian workspace, decrease the impact and tremulous in a Cartesian workspace, and effectively improve the performance of the robot working process. The results drawn from this paper lay a certain foundation for the future high-precision control of industrial robots.
Flexible Ring Sensor Array and Machine Learning Model for the Early Blood Leakage Detection during Dialysis
Authors: Huang Ping-Tzan , Lin Chia-Hung , Li Chien-Ming
Published: October 2022

Severe blood leakage resulting from the detachment of dialysis tubing is often difficult to detect by nurses in busy clinics. This paper presents a flexible blood leakage detection system featuring a ring-light sensor array with an operating wavelength of 500–700 nm, which is held in place by the gauze covering the dialysis puncture site. A ring-light sensor is connected to a bidirectional hetero-associative memory network, which interprets detected changes in signal strength, the output signal of which is transmitted via WiFi to a server at the nursing station where a machine learning algorithm determines whether blood leakage has occurred. The compact design of this early warning system greatly enhances the comfort and mobility of patients undergoing dialysis. The efficacy of the proposed system was demonstrated in experiments involving artificial blood.
Reaction of Chloroacetyl-Modified Peptides with Mercaptoundecahydrododecaborate (BSH) Is Accelerated by Basic Amino Acid Residues in the Peptide
Authors: Kitamatsu Mizuki , Inoue Ken , Yamagata Naoki , Michiue Hiroyuki
Published: October 2022

We assessed a reactivity of chloroacetyl-modified tripeptides consisting of various amino acid residues (Cl-3X) and mercaptoundecahydrododecaborate (BSH) by converting Cl-3X to its reactant (BS-3X). We showed that the Cl-3X consisting of basic amino acid residues (e.g., Arg) reacted with BSH effectively and its conversion decreased as the number of Arg residues in the Cl-3X decreased. Furthermore, a reactivity of the peptides with introduction of an alkyl linker between the triarginine and the chloroacetyl group (Cl-Cn-3R) with BSH decreased with increasing alkyl linker length. These results indicate that an electrostatic attraction of positively charged amino acid residues in the tripeptides and negatively charged BSH causes BSH to gather in a vicinity of the chloroacetyl group, resulting in an accelerated reaction. This work should aid a development of new boron agents using BSH in boron neutron capture therapy.
Deep-Learning Algorithmic-Based Improved Maximum Power Point-Tracking Algorithms Using Irradiance Forecast
Authors: Roh Chan
Published: October 2022

Renewable energy is a key technology for achieving carbon-free energy transitions, and solar power systems are one of the most reliable resources for achieving this. Solar power systems have a simple structure and are inexpensive. However, depending on the input irradiance, the existing maximum output control algorithm (P&O) has disadvantages due to its slow transient response and steady-state vibration. Therefore, in this paper, we propose a maximum output control algorithm based on a deep learning algorithm that can predict the input irradiance. This can achieve a quick transient response and steady-state stability. The proposed method predicts the irradiance based on the output voltage/current and power of the photovoltaic (PV) system and calculates the duty ratio that can accurately follow the maximum output point according to the irradiance. The deep learning model applied in this study was trained based on the experimental results using a 100 W PV panel, and the performance of the proposed algorithm was verified by comparing its performance with that of the conventional algorithm under various input irradiance conditions. The proposed algorithm exhibits a maximum efficiency increase of 11.24% under the same input conditions as those of the existing algorithms.
Identification and Mapping of Three Distinct Breakup Morphologies in the Turbulent Inertial Regime of Emulsification—Effect of Weber Number and Viscosity Ratio
Authors: Håkansson Andreas , Olad Peyman , Innings Fredrik
Published: October 2022

Turbulent emulsification is an important unit operation in chemical engineering. Due to its high energy cost, there is substantial interest in increasing the fundamental understanding of drop breakup in these devices, e.g., for optimization. In this study, numerical breakup experiments are used to study turbulent fragmentation of viscous drops, under conditions similar to emulsification devices such as high-pressure homogenizers and rotor-stator mixers. The drop diameter was kept larger than the Kolmogorov length scale (i.e., turbulent inertial breakup). When varying the Weber number (We) and the disperse-to-continuous phase viscosity ratio in a range applicable to emulsification, three distinct breakup morphologies are identified: sheet breakup (large We and/or low viscosity ratio), thread breakup (intermediary We and viscosity ratio > 5), and bulb breakup (low We). The number and size of resulting fragments differ between these three morphologies. Moreover, results also confirm previous findings showing drops with different We differing in how they attenuate the surrounding turbulent flow. This can create ‘exclaves’ in the phase space, i.e., narrow We-intervals, where drops with lower We break and drops with higher We do not (due to the latter attenuating the surrounding turbulence stresses more).
Synthesis and Characterization of Lignin-Incorporated Carboxymethyl Cellulose (CMC) Films from Oil Palm Lignocellulosic Waste
Authors: Song Cai-Li , Othman Jofry B.
Published: October 2022

An environmentally friendly, biobased film was prepared from cellulose and lignin extracted from oil palm dried long fiber (DLF). DLF crude cellulose was first extracted from this lignocellulosic biomass by an alkaline pretreatment process at an elevated temperature (5.75 wt% NaOH, 200 °C, and 1 h), before it was carboxymethylated to obtain carboxymethyl cellulose (CMC). CMC is highly soluble in water, whereas lignin was precipitated out of the filtrate of the alkaline pretreatment process by adding acid to pH 2 (50 wt% H2SO4). The lignin/CMC films were synthesized at varying lignin concentrations of 0.25%, 0.5%, and 1% (w/v) in ethanolic solution with 0.25% (v/v) of glycerol; a neat CMC film was also prepared as a control. These lignin/CMC films were evaluated and compared for their morphological, physical, chemical, and thermal characteristics. The films displayed a brownish physical appearance, which was attributed to the natural color of lignin. The successful incorporation of lignin in the films was confirmed with the characteristic spectral bands of lignin in the mid-IR range (4000–400 cm−1). When measured with UV-vis spectrometer, the lignin/CMC films showed more enhanced UV blocking properties than the neat CMC film. The CMC films incorporated with lignin also showed slightly improved hydrophobicity and thermal stability. However, due to the low compatibility of lignin with CMC, the distribution of the lignin/CMC film was observed to be inhomogeneous in SEM images. Nonetheless, the addition of lignin to CMC in synthesizing biobased films is promising, potentially providing better properties that can be useful as biodegradable material.
Time-Series Monitoring of Transgenic Maize Seedlings Phenotyping Exhibiting Glyphosate Tolerance
Authors: Tao Mingzhu , Bai Xiulin , Zhang Jinnuo , Wei Yuzhen , He Yong
Published: October 2022

Glyphosate is a widely used nonselective herbicide. Probing the glyphosate tolerance mechanism is necessary for the screening and development of resistant cultivars. In this study, a hyperspectral image was used to develop a more robust leaf chlorophyll content (LCC) prediction model based on different datasets to finally analyze the response of LCC to glyphosate-stress. Chlorophyll a fluorescence (ChlF) was used to dynamically monitor the photosynthetic physiological response of transgenic glyphosate-resistant and wild glyphosate-sensitive maize seedlings and applying chemometrics methods to extract time-series features to screen resistant cultivars. Six days after glyphosate treatment, glyphosate-sensitive seedlings exhibited significant changes in leaf reflection and photosynthetic activity. By updating source domain and transfer component analysis, LCC prediction model performance was improved effectively (the coefficient of determination value increased from 0.65 to 0.84). Based on the predicted LCC and ChlF data, glyphosate-sensitive plants are too fragile to protect themselves from glyphosate stress, while glyphosate-resistant plants were able to maintain normal photosynthetic physiological activity. JIP-test parameters, φE0, VJ, ψE0, and M0, were used to indicate the degree of plant damage caused by glyphosate. This study constructed a transferable model for LCC monitoring to finally evaluate glyphosate tolerance in a time-series manner and verified the feasibility of ChlF in screening glyphosate-resistant cultivars.
Application of Parameterized Grain-Size Endmember Modeling in the Study of Quaternary Oxbow Lake Sedimentation: A Case Study of Tövises Bed Sediments in the Eastern Great Hungarian Plain
Authors: Eltijani Abdelrhim , Molnár Dávid , Makó László , Geiger János , Sümegi Pál
Published: October 2022

Abandoned channels are essential in the Quaternary floodplains, and their infill contains different paleoenvironment recorders. Grain-size distribution (GSD) is one proxy that helps characterize the alluviation and associated sedimentological processes of the abandoned channels. The classic statistical methods of the grain-size analysis provide insufficient information on the whole distribution; this necessitates a more comprehensive approach. Grain-size endmember modeling (EMM) is one approach beyond the traditional procedures that helps unmix the GSDs. This study describes the changes in the depositional process by unmixing the GSDs of a Holocene abandoned channel through parameterized EMM integrated with lithofacies, age–depth model, loss-on-ignition (LOI), and magnetic susceptibility (MS). This approach effectively enabled the quantification and characterization of up to four endmembers (EM1-4); the characteristics of grain-size endmembers imply changes in sedimentary environments since 8000 BP. EM1 is mainly clay and very fine silt, representing the fine component of the distribution corresponding to the background of quiet water sedimentation of the lacustrine phase. EM2 and EM3 are the intermediate components representing the distal overbank deposits of the flood. EM4 is dominated by coarse silt and very fine sand, representing deposition of overbank flow during the flood periods. This paper demonstrates that the parametrized grain-size EMM is reasonable in characterizing abandoned channel infill sedimentary depositional and sedimentation history.
Disease, Demon, and the Deity: Case of Corona Mātā and Coronāsur in India
Authors: Yadav Megha
Published: October 2022

As India faced multiple waves of the pandemic, religious responses arose to accommodate and make sense of the situation. In the face of uncertainty, disease and death, people turn not just towards the medical sciences but also religion. The emergence of a new Hindu goddess, Corona Mātā/Coronavirus Mardhinī encapsulates people’s fear, faith, and devotion. Although the goddess is new, the tradition of disease goddesses is ancient. The Indian Subcontinent has a long history of mother goddesses who have been protecting their devotees from diseases such as smallpox, fever, plague, etc. This paper attempts to examine the emergence of Corona Mātā in the historical context of these ‘protective mothers’. On one hand, historically, these goddesses have emerged as a result of interaction between Brahmanical religion and regional practices. On the other hand, these disease-centred goddesses can also be seen as the result of fear and faith. This paper will analyse the location of Corona Mātā in the ever-evolving pantheon of Hindu deities in the context of a 21st-century pandemic.
The Influence of Daoist Astrology on the Chinese Visual Representation of Tejaprabhā Buddha
Authors: Chen Yushu , Huang Bing
Published: October 2022

Tejaprabhā Buddha is the lord of the constellations and one of the most significant esoteric deities. Its image occurs in a number of Chinese visual presentations dating from the Tang Dynasty to the Ming Dynasty. The cult of Tejaprabhā was also disseminated to Korea and Japan and spawned related local visual creations. Tejaprabhā Buddha and his followers do not belong to the core group of Buddhist deities but are instead connected to the Daoist deities. This was most likely due to the fact that asterism held a greater significance to Daoists, for whom it was the most important of all the power sources derived from the cosmos. The focus of this study is on unearthing the Daoist astrological influences in the visual presentation and its adaptation of Tejaprabhā Buddha and the accompanied luminary deities in China. The cult of constellations and Tejaprabhā in the context of Chinese Esoteric Buddhism was constantly evolving under the influence of Daoism, gleaned by examining and comparing the quantity and visual variations of luminaries in the artworks of Tejaprabhā of different periods.
The Extent of Insulin Resistance in Patients That Cleared Viral Hepatitis C Infection and the Role of Pre-Existent Type 2 Diabetes Mellitus: A Meta-Analysis
Authors: Popescu Marian-Sorin , Drocas Andrei Ioan , Osman Andrei , Firu Dan-Mihai , Pădureanu Vlad , Mărginean Cristina Maria , Pîrvu Daniel-Cristian , Mitruț Radu , Mărgăritescu Dragoș Nicolae , Radu Antonia , Calina Daniela , Docea Anca Oana , Mitruț Paul
Published: October 2022

A high risk of developing insulin resistance (IR) and, eventually, type 2 diabetes mellitus (T2DM) is associated with chronic hepatitis C virus (HCV). Multiple mechanisms can account for the development of IR in chronic HCV patients, steatosis or fatty liver that can lead to metabolic syndrome, and the inflammatory process associated with the presence of HCV infection. In this article, we analyze the reported values of homoeostasis model assessment (HOMA-IR) before and after successful direct-acting agents (DAAs) treatment in the literature (23 studies) at certain intervals, respectively 12, 24, and 52 weeks depending on the presence of T2DM among patients. The meta-analysis showed improvement of IR in most cases except for three studies that presented a minimal increase in HOMA-IR value for the non-T2DM group at the 12- and 24-week check-ups possibly hinting at a prediabetes group. All other studies showed an important decrease in HOMA-IR post-DAA treatment specifically for the T2DM group. The most significant change in HOMA-IR values was noticed after 24 weeks in all categories. Our meta-analysis showed that clearance of HCV leads to improvement of IR, especially in the case of patients with T2DM.
Intrathecal Cell Therapy with Autologous Bone Marrow Stromal Cells as a New Tool for Neurologic Sequels after Spinal Cord Surgery: A Report of Two Cases
Authors: Zurita Mercedes , Bonilla Celia , Aguayo Concepción , Fernández-Mateos Cecilia , Martínez Paula , De La Calle Silvia , Repollés Nieves , Moñivas Esther
Published: October 2022

Background aims: The possibility of permanent neurological sequels after surgery of benign lesions affecting the spinal cord is well known. Frequently, they are irreversible, with no effective treatment other than rehabilitation. However, in recent years, intrathecal cell therapy with autologous bone marrow stromal cells (MSCs) in patients with incomplete paraplegia has shown benefits for diverse sequels of spinal cord injury (SCI). Methods: We present two patients with chronic spinal cord sequels after a surgery, who underwent cell therapy treatment with NC1 medicament (repeated intrathecal administrations of MSCs). Results: In both cases, cell therapy achieved a clear improvement in neurological sequels, such as recovery of gait disturbances, bowel dysfunction, or neuropathic pain. Conclusion: Intrathecal cell therapy with autologous MSCs offers a new approach for neurological sequels after spinal cord surgery.
The Quality of Reserve Risk Calculation Models under Solvency II and IFRS 17
Authors: Arató N. Miklós , Martinek László
Published: October 2022

We analyse four stochastic claims reserving methods in terms of their capability to estimate reserve risk and how successful they are at predicting distributions and VaRs of claim developments in particular. Both actual data and hypothetical claim triangles support our results. The appropriateness of the Solvency II risk margin on a one-year horizon and of the IFRS 17 risk adjustment in the long run largely vary by the chosen risk model. Despite the fact that IFRS 17 does not uniquely prescribe the metric for risk adjustment, we expect that VaR will be widely applied by insurance firms. Overall, actual data suggest that VaRs are predominantly underestimated by the models. Nevertheless, the 99.5%-VaRs under Solvency II are mostly sufficient on a 10-year-horizon to cover liabilities.
Coherent Diversification Measures in Portfolio Theory: An Axiomatic Foundation
Authors: Koumou Gilles Boevi , Dionne Georges
Published: October 2022

We provide an axiomatic foundation for the measurement of correlation diversification in a one-period portfolio model. We propose a set of eight desirable axioms for this class of diversification measures. We name the measures satisfying these axioms coherent correlation diversification measures. We study the compatibility of our axioms with rank-dependent expected utility theory. We also test them against the two most frequently used methods for measuring correlation diversification in portfolio theory: portfolio variance and the diversification ratio. Lastly, we provide an example of a functional representation of a coherent correlation diversification measure.
New Advances of the Multiscale Approach for the Analyses of InSAR Ground Measurements: The Yellowstone Caldera Case-Study
Authors: Barone Andrea , Pepe Antonio , Tizzani Pietro , Fedi Maurizio , Castaldo Raffaele
Published: October 2022

In this study, we describe new advances in the multiscale methodology to allow a more realistic interpretation of volcanic deformation fields by investigating geometrically irregular bodies and multi-source scenarios. We propose an integrated approach to be applied to InSAR measurements, employing the Multiridge and ScalFun methods and the Total Horizontal Derivative (THD) technique: this strategy provides unconstrained information on the source geometrical parameters, such as the depth, position, shape, and horizontal extent. To do this, we start from conditions where the biharmonic deformation field satisfies Laplace’s equation and homogeneity law. We test the use of the multiscale procedures to model single and multisource scenarios with irregular geometries by retrieving satisfactory results for a set of simulated sources. Finally, we employ the proposed approach to the 2004–2009 uplift episode at the Yellowstone Caldera (U.S.) measured by ENVISAT InSAR to provide information about the volcanic plumbing system. Our results indicate a single ~50×20 km2 extended source lying beneath the caldera at around 10 km b.s.l. (depth to the center), which is shallower below both the resurgent domes (6–7 km b.s.l. depth to the top).
Comparison of Mean Dynamic Topography Modeling from Multivariate Objective Analysis and Rigorous Least Squares Method
Authors: Wu Yihao , He Xiufeng , Huang Jia , Shi Hongkai , Wang Haihong , Wu Yunlong , Ding Yuan
Published: October 2022

Filtering methods are usually used to combine the mean sea surface (MSS) and geoid (computable by global geopotential model (GGM)) into a common subspace, to model mean dynamic topography (MDT), which may lead to signal leakage and distortion problems. The use of the rigorous least squares (LS) method and multivariate objective analysis (MOA) alleviates these problems, and the derived MDTs from these two methods show better performance than MDTs derived from filtering methods. However, the advantages and disadvantages of these two methods have not been evaluated, and no direct comparison has yet been conducted between these two approaches regarding the performances in MDT recovery. In this study, we compare the performances of the MOA method with the LS method, providing information with respect to the usability of different methods in MDT modeling over regions with heterogeneous ocean states and hydrological conditions. We combined a recently published mean sea surface called DTU21MSS, and a satellite-only GGM named GO_CONS_GCF_2_DIR_R6, for MDT computation over four typical study areas. The results showed that the MDTs derived from the LS method outperformed the MOA method, especially over coastal regions and ocean current areas. The root mean square (RMS) of the discrepancies between the LS-derived MDT and the ocean reanalysis data was lower than the RMS of the discrepancies computed from the MOA method, by a magnitude of 1–2 cm. The formal error of the MDT estimated by the LS method was more reasonable than that derived from the MOA method. Moreover, the geostrophic velocities calculated by the LS-derived MDT were more consistent with buoy data than those calculated by the MOA-derived solution, by a magnitude of approximately 1 cm/s. The reason can be attributed to the fact that the LS method forms the design matrix segmentally, based on the error characteristics of the GGM, and suppresses high-frequency noise by applying constraints in different frequency bands, which improves the quality of the computed MDT. Our studies highlight the superiority of the LS-derived method versus the MOA method in MDT modeling.
An Enhanced Spectral Fusion 3D CNN Model for Hyperspectral Image Classification
Authors: Zhou Junbo , Zeng Shan , Xiao Zuyin , Zhou Jinbo , Li Hao , Kang Zhen
Published: October 2022

With the continuous development of hyperspectral image technology and deep learning methods in recent years, an increasing number of hyperspectral image classification models have been proposed. However, due to the numerous spectral dimensions of hyperspectral images, most classification models suffer from issues such as breaking spectral continuity and poor learning of spectral information. In this paper, we propose a new classification model called the enhanced spectral fusion network (ESFNet), which contains two parts: an optimized multi-scale fused spectral attention module (FsSE) and a 3D convolutional neural network (3D CNN) based on the fusion of different spectral strides (SSFCNN). Specifically, after sampling the hyperspectral images, our model first implements the weighting of the spectral information through the FsSE module to obtain spectral data with a higher degree of information richness. Then, the weighted spectral data are fed into the SSFCNN to realize the effective learning of spectral features. The new model can maximize the retention of spectral continuity and enhance the spectral information while being able to better utilize the enhanced information to improve the model’s ability to learn hyperspectral image features, thus improving the classification accuracy of the model. Experiment results on the Indian Pines and Pavia University datasets demonstrated that our method outperforms other relevant baselines in terms of classification accuracy and generalization performance.
Capability of Phenology-Based Sentinel-2 Composites for Rubber Plantation Mapping in a Large Area with Complex Vegetation Landscapes
Authors: Li Hongzhong , Zhao Longlong , Sun Luyi , Li Xiaoli , Wang Jin , Han Yu , Liang Shouzhen , Chen Jinsong
Published: October 2022

Mapping rubber plantations in a large area is still challenging in high-cloud-cover and complex-vegetation landscapes. Existing studies were often confined to the discrimination of rubber trees from natural forests and rarely concerned other tropical tree species. The Sentinel-2 constellation, with improved spatial, spectral, and temporal resolution, offers new opportunities to improve previous efforts. In this paper, four Hainan Sentinel-2 composites were generated based on the detailed phenological stages delineation of rubber trees. The random forest classifier with different phenological stage combinations was utilized to discuss the capability of Sentinel-2 composites to map rubber plantations. The optimal resultant rubber plantation map had a producer’s accuracy, user’s accuracy, and F1 score of 81%, 84.4%, and 0.83, respectively. According to the rubber plantation map in 2020, there was a total of 5473 km2 rubber plantations in Hainan, which was 2.93% higher than the statistical data from the Hainan Statistical Yearbook. According to the Hainan Statistical Yearbook, the area-weighted accuracy at the county level was 82.47%. The mean decrease in accuracy (MDA) was used to assess the feature importance of the four phenological stages. Results showed that the recovery growth stage played the most important role, and the resting stage was the least important. Moreover, in terms of the combinations of phenological stages, any dataset group with two phenological stages was sufficient for rubber tree discrimination. These findings were instrumental in facilitating the rubber plantation mapping annually. This study has demonstrated the potential of Sentinel-2 data, with the phenology-based image-compositing technique, for mapping rubber plantations in large areas with complex vegetation landscapes.