bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution of Molar Mass Distributions Using a Method of Partial Moments: Initiation of RAFT Polymerization
Authors: Johnson Charles H. J. , Spurling Thomas H. , Moad Graeme
Published: November 2022

We describe a method of partial moments devised for accurate simulation of the time/conversion evolution of polymer composition and molar mass. Expressions were derived that enable rigorous evaluation of the complete molar mass and composition distribution for shorter chain lengths (e.g., degree of polymerization, Xn = N < 200 units) while longer chains (Xn ≥ 200 units) are not neglected, rather they are explicitly considered in terms of partial moments of the molar mass distribution, μxN(P)=∑n=N+1∞nx[Pn] (where P is a polymeric species and n is its’ chain length). The methodology provides the exact molar mass distribution for chains Xn < N, allows accurate calculation of the overall molar mass averages, the molar mass dispersity and standard deviations of the distributions, provides closure to what would otherwise be an infinite series of differential equations, and reduces the stiffness of the system. The method also allows for the inclusion of the chain length dependence of the rate coefficients associated with the various reaction steps (in particular, termination and propagation) and the various side reactions that may complicate initiation or initialization. The method is particularly suited for the detailed analysis of the low molar mass portion of molar mass distributions of polymers formed by radical polymerization with reversible addition-fragmentation chain transfer (RAFT) and is relevant to designing the RAFT-synthesis of sequence-defined polymers. In this paper, we successfully apply the method to compare the behavior of thermally initiated (with an added dialkyldiazene initiator) and photo-initiated (with a RAFT agent as a direct photo-iniferter) RAFT-single-unit monomer insertion (RAFT-SUMI) and oligomerization of N,N-dimethylacrylamide (DMAm).
Preparation and Phytotoxicity Evaluation of Cellulose Acetate Nanoparticles
Authors: Lima Regiane G. , Maranni Maria , Araujo Leandro O. , Maciel Bruno Marinho , Canassa Thalita , Caires Anderson R. L. , Cena Cícero
Published: November 2022

The use of biocompatible and low-cost polymeric matrices to produce non-phytotoxic nanoparticles for delivery systems is a promising alternative for good practices in agriculture management and biotechnological applications. In this context, there is still a lack of studies devoted to producing low-cost polymeric nanoparticles that exhibit non-phytotoxic properties. Among the different polymeric matrices that can be used to produce low-cost nanoparticles, we can highlight the potential application of cellulose acetate, a natural biopolymer with biocompatible and biodegradable properties, which has already been used as fibers, membranes, and films in different agricultural and biotechnological applications. Here, we provided a simple and low-cost route to produce cellulose acetate nanoparticles (CA-NPs), by modified emulsification solvent evaporation technique, with a main diameter of around 200 nm and a spherical and smooth morphology for potential use as agrochemical nanocarriers. The non-phytotoxic properties of the produced cellulose acetate nanoparticles were proved by performing a plant toxic test by Allium cepa assay. The cytotoxicity and genotoxicity tests allowed us to evaluate the mitotic process, chromosomal abnormalities, inhibition/delay in root growth, and micronucleus induction. In summary, the results demonstrated that CA-NPs did not induce phytotoxic, cytotoxic, or genotoxic effects, and they did not promote changes in the root elongation, germination or in the mitotic, chromosomal aberration, and micronucleus indices. Consequently, the present findings indicated that CA-NPs can be potentially used as environmentally friendly nanoparticles.
Magnetic Resonance Imaging: Time-Dependent Wetting and Swelling Behavior of an Auxetic Hydrogel Based on Natural Polymers
Authors: Haas Sandra , Schmieg Barbara , Wendling Paul , Guthausen Gisela , Hubbuch Jürgen
Published: November 2022

A time-dependent understanding of swelling characteristics and external stimuli behavior is crucial for the development and understanding of functional hydrogels. Magnetic resonance imaging (MRI) offers the opportunity to study three-dimensional (3D) soft materials nondestructively. This technique is already widely used as an image-based medical diagnostic tool and is applied here to evaluate complex structures of a hydrogel—a double network of chemically crosslinked casein enhanced with alginate—fabricated by 3D printing. When hydrogel disks immersed in four different liquid systems were analyzed, the material exhibited distinct system-dependent behavior characterized by rheological and mechanical measurements. Further material functionalization was achieved by macroscopic structuring of the hydrogel as an auxetic material based on a re-entrant honeycomb structure. MRI offers the advantage of monitoring overall changes in the area of the analyzed specimen and internal structural changes simultaneously. To assess the behavior of this complex structure, a series of short MRI measurements, each lasting 1.7 min, captured liquid diffusion and thus structural swelling behavior. A clear dependence of external and internal structural changes as a function of liquid properties causing these changes was observed. In conclusion, this approach might pave the way for prospective applications to monitor liquid diffusion into (e.g., vascularization) and swelling behavior of functional hydrogels.
Design and Ballistic Performance of Hybrid Plates Manufactured from Aramid Composites for Developing Multilayered Armor Systems
Authors: Shih Cheng-Hung , You Jhu-Lin , Lee Yung-Lung , Cheng An-Yu , Chang Chang-Pin , Liu Yih-Ming , Ger Ming-Der
Published: November 2022

In this study, the impact resistance of aramid fabric reinforced with shear thickening fluids (STFs), epoxy or polyurea elastomers is examined through ballistic tests. According to the ballistic test results, the aramid composite structure treated with polyurea elastomers absorbs the most impact energy per unit area density and has the best impact resistance. However, the occurrence of stress concentration during ballistic impact reduces the impact resistance of the aramid composite structure treated with epoxy. On the other hand, aramid fabric impregnated with STF improves structural protection, but it also increases the weight of the composite structure and reduces the specific energy absorption (SEA). The results of this study analyze the energy absorption properties, deformation characteristics, and damage modes of different aramid composites, which will be of interest to future researchers developing next-generation protective equipment.
Synthesis and Characterization of PU/PLCL/CMCS Electrospun Scaffolds for Skin Tissue Engineering
Authors: Gao Xiang , Wen Meiling , Liu Yang , Hou Tian , Niu Bin , An Meiwen
Published: November 2022

As tissue regeneration material, electrospun fibers can mimic the microscale and nanoscale structure of the natural extracellular matrix (ECM), which provides a basis for cell growth and achieves organic integration with surrounding tissues. At present, the challenge for researchers is to develop a bionic scaffold for the regeneration of the wound area. In this paper, polyurethane (PU) is a working basis for the subsequent construction of tissue-engineered skin. poly(L-lactide-co-caprolactone) (PLCL)/carboxymethyl chitosan (CMCS) composite fibers were prepared via electrospinning and cross-linked by glutaraldehyde. The effect of CMCS content on the surface morphology, mechanical properties, hydrophilicity, swelling degree, and cytocompatibility were explored, aiming to assess the possibility of composite scaffolds for tissue engineering applications. The results showed that randomly arranged electrospun fibers presented a smooth surface. All scaffolds exhibited sufficient tensile strength (5.30–5.60 MPa), Young’s modulus (2.62–4.29 MPa), and swelling degree for wound treatment. The addition of CMCS improved the hydrophilicity and cytocompatibility of the scaffolds.
Facile Fabrication of a Bio-Inspired Leaf Vein-Based Ultra-Sensitive Humidity Sensor with a Hygroscopic Polymer
Authors: Li Pin-Hsuan , Madhaiyan Govindasamy , Shin Ying-Yi , Tsai Hsu-Yang , Meng Hsin-Fei , Horng Sheng-Fu , Zan Hsiao-Wen
Published: November 2022

Bio-inspired materials have received significant interest in the development of flexible electronics due to their natural grid structures, especially natural leaf vein networks. In this work, a bio-inspired leaf vein-based flexible humidity sensor is demonstrated. The proposed sensor is composed of a leaf/Al/glycerin/Ag paste. The Al-deposited leaf vein networks are used as a bottom electrode with a resistance of around 100 Ω. The humidity sensor responds well to relative humidity (RH) levels ranging from 15% to 70% at room temperature. The fabricated humidity sensor exhibits an ultra-sensitive response to different humidity conditions due to the biodegradable insulating hygroscopic polymer (glycerin), specifically the ionic conductivity reaction. To further verify the presence of ionic conduction, the device performance is tested by doping NaCl salt into the hygroscopic polymer sensing layer. In addition, both the repeatability and flexibility of the sensor are tested under different bending angles (0°, 90°, 180°, and 360°). The bioinspired ultrasensitive humidity sensor with a biocompatible and biodegradable sensing layer holds great potential, especially for health care applications (e.g., respiratory monitoring) without causing any body harm.
Molecular Dynamics Simulation of the Interfacial Shear Properties between Thermoplastic Polyurethane and Functionalized Graphene Sheet
Authors: Wang Yuyang , Zou Guangping , Liu Junpeng
Published: November 2022

In this study, the effect of the type and content of functional groups on the interfacial shear properties of a functionalized graphene sheet (FGS)/thermoplastic polyurethane (TPU) nanocomposite are investigated by molecular dynamics (MD) simulations. The maximum pull-out force and separation energy were used to characterize the interfacial strength of the FGS/TPU nanocomposite in sliding mode. To find out how the type and content of functional groups affect the interfacial shear properties of the TPU/FGS system from an atomic view, the details of interactions between FGS and TPU were characterized. Based on the results, stronger interfacial shear properties of the TPU/FGS system can be achieved by adding the carboxyl group or hydroxyl group on the surface of graphene than that between TPU and FGS modified by the amine group or epoxy group, because of the strong interaction of electrostatic forces and H-bonds. In addition, interfacial shear properties can also be enhanced by increasing the content of functional groups modified on the surface of graphene.
The Mixture of Probability Distribution Functions for Wind and Photovoltaic Power Systems Using a Metaheuristic Method
Authors: Khamees Amr Khaled , Abdelaziz Almoataz Y. , Eskaros Makram R. , Attia Mahmoud A. , Badr Ahmed O.
Published: November 2022

The rising use of renewable energy sources, particularly those that are weather-dependent like wind and solar energy, has increased the uncertainty of supply in these power systems. In order to obtain considerably more accurate results in the analysis of power systems, such as in the planning and operation, it is necessary to tackle the stochastic nature of these sources. Operators require adequate techniques and procedures to mitigate the negative consequences of the stochastic behavior of renewable energy generators. Thus, this paper presents a modification of the original probability distribution functions (PDFs) where the original PDFs are insufficient for wind speed and solar irradiance modeling because they have a significant error between the real data frequency distribution and the estimated distribution curve. This modification is using a mixture of probability distributions, which can improve the fitting of data and reduce this error. The main aim of this paper is to model wind speed and solar irradiance behaviors using a two-component and a three-component mixture of PDFs generated from the integration of the original Weibull, Lognormal, Gamma, and Inverse-Gaussian PDFs. Three statistical errors are used to test the efficiency of the proposed original and mixture PDFs, which are the root mean square error (RMSE), the coefficient of correlation (R2), and the Chi-square error (X2). The results show that the mixture of PDFs gives better fitting criteria for wind speed and solar irradiance frequency distributions than the original PDFs. The parameters of the original and the mixture of PDFs are calculated using the innovative metaheuristic Mayfly algorithm (MA). The three-component mixture of PDFs lowered the RMSE by about 73% and was 17% more than the best original and the two-component mixture distributions.
Optimization of Anti-Plugging Working Parameters for Alternating Injection Wells of Carbon Dioxide and Water
Authors: Li Kemin , Cao Guangsheng , Shan Gaojun , Zhang Ning , Liu Xincheng , Zhai Shengbo , Bai Yujie
Published: November 2022

In the process of oilfield development, the use of CO2 can improve the degree of reservoir production. Usually, CO2 is injected alternately with water to expand the spread range of CO2, and CO2 presents a supercritical state in the formation conditions. In the process of alternating CO2 and water injection, wellbore freezing and plugging frequently occur. In order to determine the cause of freezing and plugging of injection wells, the supercritical CO2 flooding test area of YSL Oilfield in China is taken as an example to analyze the situation of freezing and plugging wells in the test area. The reasons for hydrate freezing and plugging are obtained, the distribution characteristics and sources of hydrate near the well are clarified, and a coupling model is established to calculate the limit injection velocity and limit shut-in time of CO2 and water alternate injection wells. The results show that the main reasons for freezing and plugging of supercritical CO2 water alternate injection wells are long time shut down after alternate injection, improper operation when stopping injection and starting and stopping pumps, and slow injection speed during alternate injection. In the process of supercritical CO2 water alternative injection, in the case of post-injection, the CO2 in the formation will reverse diffuse to the injection well end. With the continuous increase of daily water injection, the initial diffusion position and the time of CO2 diffusion to the perforated hole after well shut-in gradually increase. The time of CO2 reverse diffusion to the bottom of the well is 1.6–32.3 d, and the diffusion time in the perforated hole is 1.0–4.5 d. Therefore, the limit shut-in time following injection is 2.6–36.8 d. Following gas injection, the limit shut-in time of a waterproof compound can be divided into three stages according to the change of wellbore pressure: the pressure stabilization stage, pressure-drop stage and formation fluid-return stage. The limit shut-in time of a waterproof compound following gas injection is mainly affected by permeability, cumulative gas injection rate and formation depth. The limit shut-in time of a waterproof compound is 20.0~30.0 days. The research results provide technical support for the wide application of CO2 flooding.
The Mechanism Research of Low-Frequency Pressure Oscillation in the Feeding Pipe of Cryogenic Rocket Propulsion System
Authors: Zhu Chengfeng , Li Yanzhong , Xie Fushou , Wang Lei , Ma Yuan
Published: November 2022

In the propulsion system of cryogenic liquid rockets, low-frequency pressure oscillation is a long-standing issue occurring in its feeding pipe, and is not conducive to the normal operation of the rocket. Its mechanism and excitation process are not very clear due to the limitation of the existing numerical method and the difficulty of the real dynamic experiment. Inspired by the periodic suck-back flow phenomenon of steam condensation, the fluctuation of the two-phase interface might be the crucial factor to initiate the low-frequency pressure oscillation. To simulate this interfacial characteristic of cryogenic propellant, a novel numerical model is proposed to predict the mass transfer rate weighted by the interfacial curvature. Aiming at the oxygen jet condensation simulation, the low-frequency pressure oscillation phenomenon is obtained successfully with the excitation frequency of 10.6 Hz, consistent with the natural frequency of the engine test run. It is conducted so the low-frequency pressure oscillation is caused by the periodic condensation of the continuous oxygen vapour plume, along with an oxygen suck-back flow phenomenon. In addition, the results indicate that both the oxygen and liquid oxygen mass flux promote the rise in the frequency of pressure oscillation. These conclusions provide theoretical instructions for the design and operation of the propulsion system of a cryogenic liquid rocket.
Investigation of the Vertical Propagation Pattern of the 3D Hydraulic Fracture under the Influence of Interlayer Heterogeneity
Authors: Wan Bingqian , Liu Yancheng , Zhang Bo , Luo Shuai , Wei Leipeng , Li Litao , He Jiang
Published: November 2022

The low permeability and thinly interbedded reservoirs have poor physical properties and strong interbedded heterogeneity, and it is difficult to control the hydraulic fracture (HF) height and width during hydraulic fracturing, which affects the effect of HF penetration and sand addition. In this work, a three-dimensional fluid–solid fully coupled HF propagation model is established to simulate the influence of interlayer heterogeneity on vertical HF height and HF width, and the relationship between HF length and HF width under different treatment parameters is further studied. The results show that, in thin interbedded strata, the high interlayer stress contrast, high tensile strength, and low Young’s modulus will inhibit the vertical propagation of HFs. The interlayer heterogeneity results in the vertical wavy distribution of HF width. Under the high interlayer stress contrast, Young’s modulus, and tensile strength, the HF width profile becomes narrow and the variation amplitude decreases. The HF length decreases and the HF width increases as the injection rate and fracturing fluid viscosity increase. This study is of great significance for clarifying the vertical propagation pattern in thinly interbedded reservoirs, optimizing the treatment parameters, and improving the effect of cross fracturing and proppant distribution.
Sunflower Oil Flavored by Spearmint through Conventional and Ultrasound-Assisted Maceration: Differences in Oxidative Stability, Microbial Contamination and Sensory Properties
Authors: Lu Xinjian , Yang Haoduo , Meng Yudong , Wang Dongying
Published: November 2022

The preparation of flavored vegetable oils using spice and herb plants is considered to be an indispensable opportunity for the application of these plants. In the present exploration, sunflower oil (SFO) samples flavored by Mentha spicata L. (spearmint) were prepared using the maceration method (MM) and ultrasound-assisted maceration (UM). The antioxidant effects, sensory evaluation and the oxidative stability during accelerated storage; the physicochemical properties including the levels for acid value (AV), peroxide value (PV) and p-anisidine value (AnV); and the specific extinction values at 232 nm (K232) and 268 nm (K268) of the SFO samples were measured. The contents of beneficial ingredients including chlorophylls, carotenoids, polyphenols and tocopherols, and the micro-organism colonies for yeasts, molds, Listeria monocytogenes and Enterobacteriaceae bacteria were determined. The results show that the physicochemical properties, beneficial ingredients, antioxidant effects, sensory attributes and the oxidative stability in accelerated storage were greater in the flavored SFO sample than the control. Therefore, the SFO flavored by spearmint can be developed as flavored vegetable oils, and the ultrasound-assisted maceration can be widely employed in the preparation of flavored vegetable oils in the future.
Modification of Flux Oxygen Behaviour via Co-Cr-Al Unconstrained Metal Powder Additions in Submerged Arc Welding: Gas Phase Thermodynamics and 3D Slag SEM Evidence
Authors: Coetsee Theresa , De Bruin Frederik
Published: November 2022

Aluminium metal is avoided as main reactant in submerged arc welding (SAW) because it is easily oxidised in this process. Aluminium is an effective de-oxidiser and can be used to prevent Cr and Co loss to the slag by preventing oxidation of these metals. In our novel application of aluminium metal powder in SAW we demonstrate the modification of flux oxygen behaviour. The Co-Cr-Al-alloyed weld metal total oxygen content is decreased to 180 ppm O, compared to 499 ppm O in the weld metal from the original flux, welded without metal powder additions. The flux oxygen behaviour is modified by the added aluminium powder through the lowering of the original flux-induced partial oxygen pressure in the arc cavity and at the molten flux-weld pool interface. Carbon steel was alloyed to 5.9% Co, 6.3 % Cr and 5.1% Al at 81% Co yield, 87% Cr yield and 70% Al yield. Gas-slag-alloy thermochemical equilibrium calculations confirm the partial oxygen-pressure-lowering effect of aluminium. BSE (backscattered electron) images of the three-dimensional (3D) post-weld slag sample show dome structures which contain features of vapour formation and re-condensation. These features consist of small spheres (sized less than 10 μm) and smaller needle-shaped particles coalescing into a porous sphere. EDX analyses show that the spheres consist of Si-Na-K-Fe-Mn-Co-Cr oxy-fluoride and the needles consist of low oxygen Si-Al-Ca-Mg-Na-K-Fe-Mn-Co-Cr oxy-fluoride. The element distribution and speciation data from the EDX analyses confirm modification of the flux oxygen behaviour via aluminium powder addition in lowering the partial oxygen pressure, which in turn prevents oxidation of Cr and Co and minimise losses to the slag.
Physical Environment Study of Traditional Village Patterns in Jinxi County, Jiangxi Province Based on CFD Simulation
Authors: Zhou Zhiyi , Deng Jun , Wang Pengfei , Zhou Chunlei , Xu Yuxuan , Jiang Wanping , Ma Kai
Published: November 2022

As a theory in ancient China, Feng Shui is used in terrain exploring to find ideal living environments. In this study, 62 traditional villages documented on China’s and Jiangxi’s protection lists in Jinxi County, Jiangxi Province were divided into four categories according to their landscape patterns and were simulated by CFD (computational fluid dynamics) with PHOENICS and quantitatively analyzed based on their wind and thermal environments. The results showed that hills greatly improve the wind environment of villages when they are in the windward direction. Concerning thermal environments, water and vegetation effectively reduced the summer temperatures in villages, while hills kept villages warm in winter. This paper verified the positive effect of elements such as mountains, water and forests on the improvement of wind and thermal environments of villages and the rationality of the site election principle of Bei Shan Mian Shui, also known as back mountain facing water, which is upheld by Feng Shui. This paper explored the philosophy of traditional village location selection, demonstrating the ecological wisdom of ancient Chinese people in creating a good living environment, and provides a new direction for current sustainable development planning.
Model Forecasting Development for Dengue Fever Incidence in Surabaya City Using Time Series Analysis
Authors: Othman Mahmod , Indawati Rachmah , Suleiman Ahmad Abubakar , Qomaruddin Mochammad Bagus , Sokkalingam Rajalingam
Published: November 2022

Dengue hemorrhagic fever (DHF) is one of the most widespread and deadly diseases in several parts of Indonesia. An accurate forecast-based model is required to reduce the incidence rate of this disease. Time-series methods such as autoregressive integrated moving average (ARIMA) models are used in epidemiology as statistical tools to study and forecast DHF and other infectious diseases. The present study attempted to forecast the monthly confirmed DHF cases via a time-series approach. The ARIMA, seasonal ARIMA (SARIMA), and long short-term memory (LSTM) models were compared to select the most accurate forecasting method for the deadly disease. The data were obtained from the Surabaya Health Office covering January 2014 to December 2016. The data were partitioned into the training and testing sets. The best forecasting model was selected based on the lowest values of accuracy metrics such as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The findings demonstrated that the SARIMA (2,1,1) (1,0,0) model was able to forecast the DHF outbreaks in Surabaya City compared to the ARIMA (2,1,1) and LSTM models. We further forecasted the DHF cases for 12 month horizons starting from January 2017 to December 2017 using the SARIMA (2,1,1) (1,0,0), ARIMA (2,1,1), and LSTM models. The results revealed that the SARIMA (2,1,1) (1,0,0) model outperformed the ARIMA (2,1,1) and LSTM models based on the goodness-of-fit measure. The results showed significant seasonal outbreaks of DHF, particularly from March to September. The highest cases observed in May suggested a significant seasonal correlation between DHF and air temperature. This research is the first attempt to analyze the time-series model for DHF cases in Surabaya City and forecast future outbreaks. The findings could help policymakers and public health specialists develop efficient public health strategies to detect and control the disease, especially in the early phases of outbreaks.
Enhancing the Surface Quality of FDM Processed Flapping Wing Micro Mechanism Assembly through RSM–TOPSIS Hybrid Approach
Authors: Rajamani Devaraj , Balasubramanian Esakki , Yang Lung-Jieh
Published: November 2022

Improving surface quality attributes is a critical task in the production of micro-sized near-net-shaped components for end-use applications using additive manufacturing techniques. In the present study, we investigated the effect of fused deposition modeling (FDM) process parameters such as layer thickness, part orientation, raster width and raster angle on the surface quality characteristics of as-fabricated test specimens in order to develop the assembly of a flapping wing micro mechanism. Through a Box–Behnken design, a suitable experimental strategy was developed, and test specimens were manufactured. The performance of the experiments was statistically assessed using multi-response analysis of variance (ANOVA). The microstructures of the test specimens produced with various processing parameters were examined using a scanning electron microscope to identify micro surface flaws under various processing conditions. Furthermore, the optimal FDM parameters for improved surface quality attributes such as Ra, Rz and Rq were obtained using a statistical optimization technique known as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).
Deep Reinforcement Learning for Traffic Light Timing Optimization
Authors: Wang Bin , He Zhengkun , Sheng Jinfang , Chen Yu
Published: November 2022

Existing inflexible and ineffective traffic light control at a key intersection can often lead to traffic congestion due to the complexity of traffic dynamics, how to find the optimal traffic light timing strategy is a significant challenge. This paper proposes a traffic light timing optimization method based on double dueling deep Q-network, MaxPressure, and Self-organizing traffic lights (SOTL), namely EP-D3QN, which controls traffic flows by dynamically adjusting the duration of traffic lights in a cycle, whether the phase is switched based on the rules we set in advance and the pressure of the lane. In EP-D3QN, each intersection corresponds to an agent, and the road entering the intersection is divided into grids, each grid stores the speed and position of a car, thus forming the vehicle information matrix, and as the state of the agent. The action of the agent is a set of traffic light phase in a signal cycle, which has four values. The effective duration of the traffic lights is 0–60 s, and the traffic light phases switching depends on its press and the rules we set. The reward of the agent is the difference between the sum of the accumulated waiting time of all vehicles in two consecutive signal cycles. The SUMO is used to simulate two traffic scenarios. We selected two types of evaluation indicators and compared four methods to verify the effectiveness of EP-D3QN. The experimental results show that EP-D3QN has superior performance in light and heavy traffic flow scenarios, which can reduce the waiting time and travel time of vehicles, and improve the traffic efficiency of an intersection.
Numerical Study on Pile Group Effect and Carrying Capacity of Four-Barreled Suction Pile Foundation under V-H-M Combined Loading Conditions
Authors: Qi Zhen , Wei Tongzhong , Wang Changtao , Wang Fengyun , Wang Yin , Wang Jianghong , Li Juan
Published: November 2022

Multi-barreled composite foundations are generally used in offshore oil platform structure. However, there is still a lack of theoretical analyses and experimental research. This paper presents the results of a three-dimensional finite element analysis of a four-barreled suction pile foundation in heterogeneous clay foundation. The pile group effect and carrying capacity are numerically simulated. The effects of different pile embedment depths, pile spacings and non-uniformity coefficients of clay on the pile group effect are studied. Considering the changes in the foundation carrying capacity under vertical, horizontal and bending moment coupling loads, the foundation carrying capacity envelopes under horizontal and moment (H-M) and vertical, horizontal and moment (V-H-M) loading modes are drawn. The results show that pile spacing and embedment depth have great influence on the pile group effect. The bearing capacity envelope of foundations under V-H-M loading mode is greatly affected by vertical load V. This can provide a reference for the selection of pile spacing and embedded depth in practical engineering design. Furthermore, the stability of foundations can be evaluated according to the relative relationship between design load and failure envelope.
Exploiting the Complementary Potential of Rice Bran Oil as a Low-Cost Raw Material for Bioenergy Production
Authors: Costa Emanuel , Almeida Manuel Fonseca , Alvim-Ferraz Maria Conceição , Dias Joana Maia
Published: November 2022

Rice is one of the most consumed cereals in the world. From rice processing, rice bran is obtained, and only a part of this by-product is effectively used. Rice bran oil can be obtained and used as an alternative feedstock for biodiesel production, although few studies exist to support its exploitation. In addition, pretreatment is required to reduce its acidity and allow for its integration in the conventional industrial process. This work evaluated two pretreatment processes aiming to reduce the free fatty acids (FFAs) content of rice bran oil by employing an acid-catalyzed process and a biocatalyzed process. The results allowed us to assess the efficiency and effectiveness of both pretreatments. For that purpose, acid (45, 55 and 65 °C, using H2SO4 concentrations of 2 wt.% or 4 wt.% and a methanol:oil molar ratio of 9:1) and enzymatic FFAs conversion (35 °C using a 6:1 methanol:oil molar ratio and 5 wt.% of Thermomyces lanuginosus) were evaluated using rice bran oil with an acid value around 47 mg KOH.g−1, and the reaction kinetics were assessed. Acid esterification enabled a 92% acidity reduction (65 °C, 4 wt.% of catalyst) after 8 h, with the final product presenting an acid value of 3.7 mg KOH.g−1 and a biodiesel purity of 42 wt.%. The enzymatic process allowed an acidity reduction of 82%, resulting in a product with an acid value of 7.0 mg KOH.g−1; however, after 24 h, the biodiesel purity was 87 wt.% (almost a two-fold increase compared to that obtained in the homogeneous process), revealing the conversion of both free fatty acids and glycerides. The study of the reaction kinetics of the homogeneous (acid) esterification showed that, for temperatures > 45 °C, the constant rate increased with temperature. A higher constant rate was obtained for the temperature of 55 °C using 4 wt.% of catalyst (k′ = 0.13 min−1). For the heterogeneous (enzymatic) esterification, the constant rate obtained was lower (k′ = 0.028 min−1), as expected. The study revealed the technical viability of the esterification pretreatment of rice bran oil and the important parameters concerning the performance of the pretreatment solutions. Finally, the enzymatic process should be further explored, aiming to develop more ecofriendly processes (water and energy savings) to produce biodiesel from oils with a high acidity (low-cost raw materials).
IoT-Based Smart Water Management Systems for Residential Buildings in Saudi Arabia
Authors: AlGhamdi Rayed , Sharma Sunil Kumar
Published: November 2022

Water is a precious resource that can be intelligently managed. Effective water usage demands computerized home water supply management in a culture where water tanks, motors, and pumps are ubiquitous. Water management is crucial for the government and the citizens in countries like Saudi Arabia. The issue is providing a constant, high-quality, low-cost water supply. This study introduces a smart water management (IoT-SWM) system that may be used in structures that do not have access to a constant water supply but instead have water stored in enormous tanks underneath. The GSM module collects water use data from each home in a community and transmits it to the cloud, where it is analyzed. A smart water grid is a hybrid application that uses an inspection mode to identify leaks and measure the resulting height differences to keep track of the tank’s water level. The system automatically deactivates the affected section after detecting any water shortage or malfunction in the system mechanism, such as broken valves, pumps, or pipes. It sends an emergency signal to building managers. It monitors essential water quality elements regularly, and if they fall below acceptable levels, it sends warning signals to the building management, who can take action. Over an extended period, the system monitored and recorded all water quality metrics. The system restarts when the water pump has been reconnected and sends an emergency alert. As a result, the suggested system has been an excellent replacement for Saudi Arabia’s mechanically operated system.
Mathematical Modeling of Thin Layer Drying Kinetics and Moisture Diffusivity Study of Pretreated Moringa oleifera Leaves Using Fluidized Bed Dryer
Authors: Ambawat Shobhit , Sharma Alka , Saini Ramesh Kumar
Published: November 2022

Investigations were undertaken to study the drying kinetics of pretreated and unblanched leaves of Moringa oleifera dried in a fluidized bed dryer (FBD) using nine established thin layer drying mathematical models. The statistical software tool Statistica was utilized to carry out regression analysis, and the model constants were evaluated using nonlinear regression. In nonlinear regression, the R2 and reduced χ2 were employed to evaluate the goodness of fit of several mathematical models to the data generated experimentally. The model with the highest R2 and the lowest reduced χ2 and root mean square error (RMSE) values was adjudged as best fit to the drying curves. The drying kinetics of drumstick leaves was best explained by the Midilli–Kucuk model, followed by the Logarithmic model. The R2, reduced χ2, and RMSE values of the Midilli–Kucuk model under fluidized bed drying varied from 0.9982–0.9997, 0.00003–0.00029, and 0.0059–0.0166 in pretreated and 0.9945–0.9961, 0.00019–0.00054 and 0.0136–0.227 in unblanched Moringa leaves dried at 50–70 °C, respectively. The diffusivity (Deff) values ranged between 2.96 × 10−9–3.59 × 10−9 m2 s−1 and 2.92 × 10−9–3.04 × 10−9 m2 s−1, and activation energy varied from 13.67–14.07 (KJ/mol) and 13.85–14.11 (KJ/mol) for pretreated and unblanched dried leaves at 50–70 °C drying temperatures, respectively.
Field Form of the Dynamics of Classical Many- and Few-Body Systems: From Microscopic Dynamics to Kinetics, Thermodynamics and Synergetics
Authors: Zakharov Anatoly Yu.
Published: November 2022

A method is proposed for describing the dynamics of systems of interacting particles in terms of an auxiliary field, which in the static mode is equivalent to given interatomic potentials, and in the dynamic mode is a classical relativistic composite field. It is established that for interatomic potentials, the Fourier transform of which is a rational algebraic function of the wave vector, the auxiliary field is a composition of elementary fields that satisfy the Klein-Gordon equation with complex masses. The interaction between particles carried by the auxiliary field is nonlocal both in space variables and in time. The temporal non-locality is due to the dynamic nature of the auxiliary field and can be described in terms of functional-differential equations of retarded type. Due to the finiteness mass of the auxiliary field, the delay in interactions between particles can be arbitrarily large. A qualitative analysis of the dynamics of few-body and many-body systems with retarded interactions has been carried out, and a non-statistical mechanisms for both the thermodynamic behavior of systems and synergistic effects has been established.
The Characteristics of Changes in State-Church Relations in Korea’s COVID-19 Pandemic
Authors: Yi Jungyeon
Published: November 2022

Following the COVID-19 outbreak in 2020, the Korean government announced restrictions on religious activities such as worship services and small group gatherings. Unlike their Buddhist and Catholic counterparts, who responded relatively pliably to the government’s quarantine guidelines, Protestants were divided in their responses: some churches actively complied with the government’s instructions, while other churches voiced opposition. This study analyzes the cases of two churches that responded differently to the government’s quarantine restrictions. The goal is to analyze the characteristics of changes in Korea’s ‘state-religion’ relationship in the midst of the COVID-19 pandemic. The first characteristic of the changing state-religious relationship is that the state-church relationship can no longer be divided into a progressive or conservative dichotomy like before but rather is individualized for each church. The second is that the state-church relationship differs by issue and that regional variables play a bigger role than before. Local churches, in particular, are more likely to become influenced by their region in their relationship with the government than those in Seoul and other metropolitan areas. This is because these churches are able to exert more influence in the region with their human and material resources. The local church’s response to the COVID-19 quarantine guidelines showed how the church could either bond with or confront the government in dealing with natural and social disasters, as well as local problems. The changes and characteristics of the state-church relationship in the COVID-19 pandemic in Korea provide insight into future analyses of state-religious relations.
A Method for Forest Canopy Height Inversion Based on Machine Learning and Feature Mining Using UAVSAR
Authors: Luo Hongbin , Yue Cairong , Xie Fuming , Zhu Bodong , Chen Si
Published: November 2022

The mapping of tropical rainforest forest structure parameters plays an important role in biodiversity and carbon stock estimation. The current mechanism models based on PolInSAR for forest height inversion (e.g., the RVoG model) are physical process models, and realistic conditions for model parameterization are often difficult to establish for practical applications, resulting in large forest height estimation errors. As an alternative, machine learning approaches offer the benefit of model simplicity, but these tools provide limited capabilities for interpretation and generalization. To explore the forest height estimation method combining the mechanism model and the empirical model, we utilized UAVSAR multi-baseline PolInSAR L-band data from the AfriSAR project and propose a solution of a mechanism model combined with machine learning. In this paper, two mechanism models were used as controls, the RVoG three-phase method and the RVoG phase-coherence amplitude method. The vertical structure parameters of the forest obtained from the mechanism model were used as the independent variables of the machine learning model. Random forest (RF) and partial least squares (PLS) regression models were used to invert the forest canopy height. Results show that the inversion accuracy of the machine learning method, combined with the mechanism model, is significantly better than that of the single-mechanism model method. The most influential independent variables were penetration depth, volume coherence phase center height, coherence separation, and baseline selection. With the precondition that the cumulative contribution of the independent variables was greater than 90%, the number of independent variables in the two study areas was reduced from 19 to 4, and the accuracy of the RF-RVoG-DEP model was higher than that of the PLS-RVoG-DEP model. For the Lope test area, the R2 of the RVoG phase coherence amplitude method is 0.723, the RMSE is 8.583 m, and the model bias is −2.431 m; the R2 of the RVoG three-stage method is 0.775, the RMSE is 7.748, and the bias is 1.120 m, the R2 of the PLS-RVoG-DEP model is 0.850, the RMSE is 6.320 m, and the bias is 0.002 m; and the R2 of the RF-RVoG-DEP model is 0.900, the RMSE is 5.154 m, and the bias is −0.061 m. The results for the Pongara test area are consistent with the pattern for the Lope test area. The combined “fusion model” offers a substantial improvement in forest height estimation from the traditional mechanism modeling method.
Frequency-Domain Q-Compensated Reverse Time Migration Using a Stabilization Scheme
Authors: Ma Xiong , Li Hao , Gui Zhixian , Peng Xiaobo , Li Guofa
Published: November 2022

Seismic attenuation occurs during seismic wave propagation in a viscous medium, which will result in a poor image of subsurface structures. The attenuation compensation by directly amplifying the extrapolated wavefields may suffer from numerical instability because of the exponential compensation for seismic wavefields. To alleviate this issue, we have developed a stabilized frequency-domain Q-compensated reverse time migration (FQ-RTM). In the algorithm, we use a stabilized attenuation compensation operator, which includes both the stabilized amplitude compensation operator and the dispersion correction operator, for the seismic wavefield extrapolation. The dispersion correction operator is calculated based on the frequency-domain dispersion-only viscoacoustic wave equation, while the amplitude compensation operator is derived via a stabilized division of two propagation wavefields (the dispersion-only wavefield and the viscoacoustic wavefield). Benefiting from the stabilization scheme in the amplitude compensation, the amplification of the seismic noises is suppressed. The frequency-domain cross-correlation imaging condition is exploited to obtain the compensated image. The layered model experiments demonstrate the effectiveness and great compensation performance of our method. The BP gas model examples further verify its feasibility and stability. The field data applications indicate the practicability of the proposed method. The comparison between the acoustic and compensated results confirms that the proposed method is able to compensate for the seismic attenuation while suppressing the amplification of the high-frequency seismic noise.
Run-Length-Based River Skeleton Line Extraction from High-Resolution Remote Sensed Image
Authors: Wang Helong , Shen Dingtao , Chen Wenlong , Liu Yiheng , Xu Yueping , Tan Debao
Published: November 2022

Automatic extraction of the skeleton lines of river systems from high-resolution remote-sensing images has great significance for surveying and managing water resources. A large number of existing methods for the automatic extraction of skeleton lines from raster images are primarily used for simple graphs and images (e.g., fingerprint, text, and character recognition). These methods generally are memory intensive and have low computational efficiency. These shortcomings preclude their direct use in the extraction of skeleton lines from large volumes of high-resolution remote-sensing images. In this study, we developed a method to extract river skeleton lines based entirely on run-length encoding. This method attempts to replace direct raster encoding with run-length encoding for storing river data, which can considerably compress raster data. A run-length boundary tracing strategy is used instead of complete raster matrix traversal to quickly determine redundant pixels, thereby significantly improving the computational efficiency. An experiment was performed using a 0.5 m-resolution remote-sensing image of Yiwu city in the Chinese province of Zhejiang. Raster data for the rivers in Yiwu were obtained using both the DeepLabv3+ deep learning model and the conventional visual interpretation method. Subsequently, the proposed method was used to extract the skeleton lines of the rivers in Yiwu. To compare the proposed method with the classical raster-based skeleton line extraction algorithm developed by Zhang and Suen in terms of memory consumption and computational efficiency, the visually interpreted river data were used to generate skeleton lines at different raster resolutions. The results showed that the proposed method consumed less than 1% of the memory consumed by the classical method and was over 10 times more computationally efficient. This finding suggests that the proposed method has the potential for river skeleton line extraction from terabyte-scale remote-sensing image data on personal computers.
Spectral Discrimination of Pumice Rafts in Optical MSI Imagery
Authors: Chen Xi , Sun Shaojie , Zhao Jun , Ai Bin
Published: November 2022

Pumice rafts are considered to be a long-range drifting agent that promotes material exchange and the dispersal of marine species. Large ones can also interfere with vessel navigation and have a negative impact on the social economy and marine ecosystems. Synoptic observations from the Multispectral Instrument (MSI) on-board Sentinel-2, with a spatial resolution of up to 10 m, provide an excellent means to monitor and track pumice rafts. In this study, the use of a Spectral-Feature-Based Extraction (SFBE) algorithm to automatically discriminate and extract pumice on the ocean surface from submarine volcano eruptions was proposed. Specifically, a Pumice Raft Index (PRI) was developed based on the spectral signatures of pumice in MSI imagery to identify potential pumice features. After pre-processing, the PRI image was then subjected to a series of per-pixel and object-based processes to rule out false-positive detections, including shallow water, striped edges, mudflats, and cloud edges. The SFBE algorithm showed excellent performance in extracting pumice rafts and was successfully applied to extract pumice rafts near the Fiji Yasawa islands in 2019 and Hunga Tonga island in 2022, with an overall pumice extraction accuracy of 95.5% and a proportion of pixels mis-extracted as pumice of <3%. The robustness of the algorithm has also been tested and proved through applying it to data and comparing its output to results from previous studies. The timely and accurate detection of pumice using the algorithm proposed here is expected to provide important information to aid in response actions and ecological assessments, and will lead to a better understanding of the fate of pumice.