bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on Thermal Disturbance of Frozen Soil Around Piles by Concrete Hydration Heat
Authors: Sen Kong , Jialong Liu , Rui Liang , Baoqi Wang 
Published: July 2022

Abstract
In order to study the influence of the heat of hydration of concrete on the thermal disturbance of the frozen soil around the pile during the construction of cast-in-place piles in permafrost regions, a two-dimensional temperature field numerical model was established with non-steady state based on the heat conduction control equation and the freezing-thawing phase transition process. This model has been used to analyze and discuss the refreezing process of the concrete pile foundation, the heat flow transfer process between the pile foundation and the frozen soil, and the positive temperature curing process of the pile body. The research results have shown that the refreezing process of the pile foundation is a slow process. It took 28 days after the completion of the pile foundation construction that the negative temperature arose at the bottom of the pile. And 196 days after construction the temperature at the center of the pile dropped to negative. The heat brought by the cast-in-place pile is mainly released to the surrounding soil through the horizontal heat flow, and the thermal conductivity of the soil has a greater influence on this process.
Research status and development trend of optimization Angle of hydraulic fracturing in coal seams
Authors: Wang Zifan 
Published: July 2022

Abstract
Drilling along the coal seam is an effective method for large-scale gas control. The distribution law of the stress field is determined by the parameters affecting the drilling along the coal seam, thereby affecting the drainage effect of the drilling along the coal seam. In order to study the distribution law and drilling parameters of the borehole stress field along the coal seam, the residual plastic zone, the radius of the plastic softening zone, the radius of The radial displacement of the coal body on the hole wall and the axial plastic range are used to construct the calculation model of the sealing length; the calculation model of the sealing strength is established through the micro-element analysis of the packer rubber cylinder. The research finally determined that the most suitable drilling position is the original rock stress area; the reasonable sealing length and sealing strength were determined.
Simulation Analysis of Influencing Factors of Grinding Wheel Scribing Quality
Authors: Ma Yan , Jiang Xingqiao , Liu Huang , Zhang Zhiyong , Cao Zhengdi 
Published: July 2022

Abstract
The analysis on influence factors of wheel dicing saw machine to cutting quality is presented through orthogonal cross-cutting test. The effects of parameters such as the speed of the spindle, the cutting velocity of the spindle, the cutting depth of the spindle, the tool diameter are analysed. The results are analysed through the methods of range analysis, variance analysis, factor - index relationship trend chart analysis. The main influence factors for the cutting width and the maximum cross cutting width are gained. Based on the method of robustness design, many kinds of controllable factors is presented quantitatively through the orthogonal experiment. Analysis on data of the cross cutting width test and the largest cross cutting width test is presented. The biggest contribution factor is obtained, the appropriate level is selected. Simulation analysis on the largest contribution factor, the appropriate level, the optimal machining parameters is presented.
A Calculation Method of DC Current Reference Value for Suppressing Commutation Failure in LCC-HVDC System
Authors: Chen Xiaolong , Qi Xiaoqing , Li Yongli , Li Bin , Li Botong 
Published: July 2022

Abstract
Line commutated converter based high voltage direct current (LCC-HVDC) transmission system is prone to suffer commutation failure, which can lead to the increase of DC current and the interruption of DC transmission power. Furthermore, the increase of DC current might lead to subsequent commutation failure. Based on the reactive power balance of the inverter AC bus, this paper studies the functional relationship between DC current and commutation voltage. The DC current reference value is obtained by using the DC current acquired from the above functional relationship, and combining with the DC current order given by voltage dependent current order limiter (VDCOL). This calculation method can adjust the DC current reference value in time according to the commutation voltage, thus limiting the increase of DC current. In order to verify the commutation failure suppression ability of the proposed method, several simulations are conducted based on CIGRE benchmark HVDC model in PSCAD/EMTDC. Simulation results show that the proposed method can not only suppress commutation failure successfully, but also improve the fault recovery performance of the LCC-HVDC system.
A Fixed-Window Level-crossing ADC with a Single Comparator
Authors: Wei Yuming , Tong Xingyuan , Xin Xin 
Published: July 2022

Abstract
A fixed-window level-crossing analog-to-digital converter (LC-ADC) with a single comparator is proposed for the biomedical field. In this paper, a signal varying direction detection circuit is proposed to judge the trend of the input signal, instead of the low-precision comparator in the modified LC-ADC. The proposed LC-ADC utilizes only one continuous-time comparator instead of multiple comparators in traditional LC-ADC, leading to simplified implementation and significantly reducing the power consumption. The post-layout simulation results show that the power consumption of the proposed new signal varying direction detection circuit is significantly reduced, accounting for only 25.6% of the high-precision continuous-time comparator. Designed with a 0.18 μm CMOS technology, the core area of this LC-ADC is 0.007 mm2. With a 1.8 V supply and 1 kHz input signal frequency, it achieves 73.1-dB SNDR by consuming 20.1 μW power. The figure-of-merit value is 19.3 mm2·fJ/Conversion.
Research Progress of Test Methods for Unmanned Surface Vehicle in Complex Sea Conditions
Authors: Yang Shuo , Gao Cheng 
Published: July 2022

Abstract
Surface Vehicles are the product of the development of marine technology. As a new type of technical means, it has been widely used in the field of marine commissioning and defense. However, the testing technology of Unmanned Surface Vehicles is not comprehensive now, and in order to ensure the smooth progress of scientific research projects, testing is necessary, so testing technology is also a smooth part of scientific research projects. This article classifies the existing test research, summarizes the test and evaluation methods, summarizes the tests that have been carried out and speculates the tests that will be carried out in the future for the testing of Unmanned Surface Vehicles.
Renewable Energy Sources in the Era of the Fourth Industrial Revolution: a Perspective of Civilization Development
Authors: He Ping , Ni Xiaoting 
Published: July 2022

Abstract
Every emergence and development of industrial revolution in the history of human civilization is based on the extensive utilization of different energy sources. More than fifty years, the discussion of limited energy sources and sustainable development has acknowledged huge importance from the environmentalists. This study expanded the horizon of the debate about primary and renewable energy, analyzed the trend of renewable energy sources driven by the fourth industrial revolution. In this context, the study discussed the aspects of The Paris Agreement 2015, the responses to climate change and sustainable growth. Results indicated that primary energy sources, such as coal, oil, natural gas, hydroelectricity and nuclear energy, are the major energy sources which boosted up past industrial revolutions and hold the largest share of energy at present; whereas the share of renewable energy sources, especially the wind and solar sources which is going to be accelerated by the fourth industrial revolution, will be risen to high record in the future. The fourth industrial revolution, which has surged directly driven by artificial intelligent technologies, is going to speed up the utilization of renewable energy sources, and the clean, non-polluting, renewable energy is going to take the place of primary one sooner or later.
Investigating machine learning solutions for a 256 channel TCSPC camera with sub-70 ps single photon timing per channel at data rates >10 Gbps
Authors: Markfort A. , Baranov A. , Conneely T.M. , Duran A. , Lapington J. , Milnes J. , Moore W. , Mudrov A. , Tyukin I. 
Published: July 2022

Abstract
The development of a Time Correlated Single Photon Counting (TCSPC) camera with 256 channels has enabled several applications where single photon sensitivity is crucial, such as LiDAR, Fluorescent Lifetime IMaging (FLIM) and quantum information systems. The microchannel plate-based Multi-Anode Photo-Multiplier Tube (MAPMT) is a 16 × 16 array of 1.656 mm pitch pixels with an active anode area of 26.5 × 26.5 mm2. Each pixel can time single photons with an accuracy of 60 ps rms at a maximum photon rate of 480 KHz.
The timing electronics are capable of measuring 120 Mcps, producing huge volumes of data for processing, in the region of 10 Gbps per detector. Limitations in algorithmic data analysis techniques are critical for this application, hence this paper demonstrates a machine learning (ML) model which can determine the photon event coordinates with the objective of processing each one photon per 10 μs. The model applies calibrations for the detector and electronics such as amplitude walk, and charge measurement and channel to channel threshold variation. Optimisation of the model is detailed within the paper, including training hyperparameters, the clustering of coincident events and compression of the model through pruning techniques.
The ML model is trained and tested on a simulation of the microchannel plate (MCP) PMT with timing electronics configured for use as a TCSPC camera, utilising charge sharing techniques to further improve the spatial resolution of the detector. Further objectives of the research are to test the model on detector data, allowing assessment on the variance of accuracy between simulated and real data. Beyond this, assessment of the performance of this approach compared to algorithmic approaches and introduction of statistical reasoning of the robustness of the model will be completed.
An analysis of fire dynamics in and around indigenous territories and protected areas in a Brazilian agricultural frontier
Authors: Walker Kaitlin , Flores-Anderson Africa , Villa Lucio , Griffin Robert , Finer Matthew , Herndon Kelsey 
Published: July 2022

Abstract
Sustainable land management is integral to conserving tropical ecosystems and reducing carbon emissions. Human-set fires are part of the land cover change process and are the most common driver of deforestation and carbon emissions in Amazonia. Analyzing the behavior of major fire events provides insight into the effectiveness of current protections. This study aims to quantify the role of Indigenous Territories and Protected Areas (ITPAs) in characterizing anthropogenic fire regimes over the 2020 fire season in Mato Grosso, Brazil. Because of the rapid rate of land cover change and lack of widespread ground validation data in the region, we used a combination of ESA’s Sentinel-5 Precursor Aerosol Index, NASA’s Visible Infrared Imaging Radiometer Suite, and high resolution Planet satellite imagery for the Monitoring of the Andean Amazon Project to analyze spatial and temporal patterns by fire type. ITPAs cover 25% of the study area’s land and contained approximately 20% of significant recorded fires in 2020. Recently deforested areas, forest, grassland, and cropland fires showed varying seasonality and lower frequencies inside ITPAs, but mean fire start dates for all fire types occurred in mid-September. Results suggest that the overall density of major fires is reduced in ITs. PAs only inhibit the density of crop or pastureland fires, but no major fires occurred past 10 km inside their borders. Burn severity of major fires had a weak relationship to distance from ITPAs for some fire types. This study highlights the advantages of near real-time data for individual fire events, provides further evidence of the effect of ITPAs on fire behavior, and demonstrates the importance of adequate protection strategies for mitigating fire activity.
Synthesis of Calcium Carbonate Nanoparticles and its Application in Grey Water Treatment
Authors: Ali Al-Lezami Hajer Ahmed , Devi Geetha 
Published: July 2022

Abstract
Nanotechnology is one of the emerging technologies with unique functionalities and great potential in the removal of pollutants from waste water. Nanoparticle mediated waste water treatment is a promising alternative to traditional water treatment techniques. Considerable amount of grey water is thrown out of the household activities on a daily basis, which in turn lead to environmental pollution in the long run and hence results in increased fresh water consumption. The present study focused on the synthesis of calcium carbonate nanoparticles using homogenisation process for the treatment of grey water. The nanoparticles were characterised using Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and X-Ray Diffraction (XRD). The synthesised nanoparticles were employed in the batch treatment of grey water by varying the solution pH, stirring time; stirring speed and dosage of calcium carbonate nanoparticles. The pollutant removal efficiency of the nanoparticles were assessed by measuring the Chemical Oxygen demand (COD), Total Suspended solids (TDS), Total dissolved solids (TDS), Dissolved oxygen (DO) and turbidity. The study demonstrates that the optimum pollutant removal efficiency was obtained at pH 8.0, stirring speed of 100 rpm, mixing time of 75 minutes and 0.7 g dosage of calcium carbonate nanoparticles. The maximum reduction in COD at optimum processing condition was 78%. The outcome of the study suggests that calcium carbonate nanoparticle could effectively remove pollutants from grey water. This research is in line with the United Nations Sustainable Development Goals (UNSD), which is clean water and sanitation. This community engagement project will serve the society by saving the water and to produce a clean environment.
Statistical and Artificial Neural Network Analysis for Corrosion of Mild Steel in Hydrochloric Acid in Presence of Eco-Friendly Inhibitor
Authors: Khadom Anees A. , Fadhil Ahmed A. , Ahmed Salima K. , Mutasher Saad A. 
Published: July 2022

Abstract
In present work, the inhibition performance of the Portulaca Grandiflora Leaf Extract (PGL), as environmental-friendly corrosion inhibitor, for low-carbon steel in 0.5 M hydrochloric acid solution at variable inhibitor concentrations and temperatures is evaluated by mass loss technique. The dependent variable was corrosion rate, while the independent variables were inhibitor concentration and temperatures. Several mathematical and artificial neural network (ANN) models have been suggested. A computer aided program is used during regression and estimation processes. Several models were used. Polynomial – individual effect, polynomial – interaction effect, linear effect, exponential growth, and piecewise regression models were estimated. Results show that the Piecewise regression model was the best one with high correlation coefficient (R2) equal to 0.9994. For ANN studies, Linear Model (LM), Radial Basis Function (RBF), and Multi-Layer Perceptron (MLP) were evaluated. The data were divided into training and testing. MLP of two inputs, multi-hidden layers, and one output (2:2-8-1:1) was the highly accurate artificial neural network model ANN with a high correlation coefficient (R2=0.9826). The effect of temperature was lower than the effect of PGL concentration as shown by mathematical and ANN analysis.
Artificial Intelligence-based Fault Diagnosis Procedure for a Sustainable Manufacturing Industry
Authors: Anwarsha A , Narendiranath Babu T 
Published: July 2022

Abstract
All industries are fast transforming into smart industries as part of the sustainable developments in the fourth industrial revolution. Predictive maintenance is one of the most important aspects of such smart industries, to avoid unanticipated machine breakdowns and catastrophic failures. Machine vibration analysis is a common tool for predicting the state of machinery. Vibration analysis involves analysing vibration data collected from machinery and determining whether or not a fault exists. Despite the fact that different methods are utilized to handle data, artificial intelligence is capable of processing such data without the need for human intervention. Every day, a substantial amount of study is carried out in this field. New strategies, on the other hand, that yield greater classification accuracy have yet to be developed. With the use of artificial intelligence approaches, this research article attempts to offer an effective defect detection method for rolling element bearings. To illustrate the practical applications, the technique is used on real datasets which were developed by Case Western Reserve University, which is regarded as a gold standard for testing diagnostic algorithms.
IoT based Smart Battery Power and Wastage Level Tracking System for Solar Powered Waste Bin by GSM Technology
Authors: Kumaravel G , Ilankumaran V 
Published: July 2022

Abstract
Solid waste collection and disposal are the primary issues in Oman as the country is lacking in effective management and suitable technologies. Rapid development in urban areas adds the fuel in these issues as it increases the risk of land pollution and health issues. The rotten vegetable wastes in the overfilled waste bins, spread the vector borne diseases in the surroundings. So, a proper management and monitoring system is needed to empty the waste bins in appropriate time. In this paper, Internet of Things (IoT) based smart system is proposed, to empty the waste bins in proper time. This system is designed in such a way that it is self-powered by photovoltaic panel which is embedded on the top of the waste bin lid. An ultrasonic sensor is used to sense the filling level of wastes and energy sensor module is used to sense the voltage and power of the battery unit. A microcontroller is used to estimate the filling level of wastes and also used to measure the voltage and power of the battery unit. Later, this information is transferred to the IoT server with the help of GSM (Global System for Mobile communication module). The experimental results show that the proposed system is very effective. The performance of the system is also validated by comparing its results with other existing systems.
Isolation of phytate-degrading microorganisms with inorganic phosphate solubilizing activity (biofertilizers) for plant growth enhancement
Authors: Osman AA , El-Boussairi BM 
Published: July 2022

Abstract
Phosphorus (P) shortage in the soil is a key problem in agricultural output. Phytate (Myo-inositol phosphate), which is stable and unavailable to plants, is abundant in soils, accounting for up to 50% of all organic P. The conversion of phytate to Myo-inositol and phosphate is catalyzed by phytases. Microorganisms that solubilize P, biofertilizers, are common in soils and may play a major role in providing P to plants. Secreted microbial phytases enhancing plant development in terms of phosphorus availability. This study aimed to identify possible phytate degrading microorganisms from the rhizosphere, animal dung, soil, and livestock farms samples collected from farms in Khartoum, Sudan. Modified Luria Bertani and phytase screening media supplemented with wheat bran as a source of phytate were used as selection media. Each sample was serially diluted 10 times, and 100 µl from dilution 103 was distributed onto each of two screening medium plates, cultured aerobically at 37°C for 1 to 4 days, A putative phytate degrading bacterium was detected in isolates with a clear zone around their growing colonies. A total of 17 isolates were obtained, with 15/17 (88%) being bacterial isolates and 2/17 being fungal isolates. Phosphate solubilizing activity was performed on Pikovskaya’s agar plate, and plates were incubated at 37°C for 7 days. The plates were examined for the presence of a halo zone around each isolated culture. out of the 17 isolates, only one Gram-positive Bacilli (isolate AB13) was found to have phosphate solubilizing activity and the ability to liberate P from phytate, suggesting that it could be used as a biofertilizer.
Protocol for generating an arbitrary quantum state of the magnetization in cavity magnonics
Authors: Sharma Sanchar , S V Bittencourt VictorA , Viola Kusminskiy Silvia 
Published: July 2022

AbstractWe propose and numerically evaluate a protocol to generate an arbitrary quantum state of the magnetization in a magnet. The protocol involves repeatedly exciting a frequency-tunable superconducting transmon and transferring the excitations to the magnet via a microwave cavity. To avoid decay, the protocol must be much shorter than magnon lifetime. Speeding up the protocol by simply shortening the pulses leads to non-resonant leakage of excitations to higher levels of the transmon accompanied by higher decoherence. We discuss how to correct for such leakages by applying counter pulses to de-excite these higher levels. In our protocol, states with a maximum magnon occupation of up to ∼9 and average magnon number up to ∼4 can be generated with fidelity>0.75.
Gestational Weight Gain and Birth Outcome: A Comparison of Methods of Accounting for Gestational Age
Authors: Richards Megan , Strickland Matthew J , Flanders W Dana , Klein Mitchel , Darrow Lyndsey A 
Published: July 2022

AbstractCross-sectional studies of total gestational weight gain (GWG) and perinatal outcomes have used different approaches to operationalize GWG and adjust for duration of gestation. Using birth records from California (2007–2017), Nevada (2010–2017), and Oregon (2008–2017), we compared 3 commonly used approaches to estimate associations between GWG and cesarean delivery, small-for-gestational-age birth, and low birth weight (LBW): 1) the Institute of Medicine–recommended GWG ranges at a given gestational week, 2) total weight gain categories directly adjusting for gestational age as a covariate, and 3) weight-gain-for-gestational-age z scores derived from an external longitudinal reference population. Among 5,461,130 births, the 3 methods yielded similar conclusions for cesarean delivery and small-for-gestational-age birth. However, for LBW, some associations based on z scores were in the opposite direction of methods 1 and 2, paradoxically suggesting that higher GWG increases risk of LBW. This was due to a greater proportion of preterm births among those with high z scores, and controlling for gestational age in the z score model brought the results in line with the other methods. We conclude that the use of externally derived GWG z scores based on ongoing pregnancies can yield associations confounded by duration of pregnancy when the outcome is strongly associated with gestational age at delivery.