Residue Mulching Alleviates Coastal Salt Accumulation and Stimulates Post-Fallow Crop Biomass under a Fallow–Maize (<i>Zea mays</i> L.) Rotation System

Fallow, a field where living plants are unplanted for a period, is continually implemented to accumulate moisture for the upcoming cultivation. However, there are less studies on the fallow strategies in one-crop-per-annum cropping system for coastal saline soils. In this study, 2-year “fallow + maize (Zea mays L.)” rotation experiments were carried out from 2016 to 2018 to assess how the mulching determine post-fallow soil moisture, salt distribution, and crop performance. Three treatments were designed, i.e., traditional cultivation without residue retention (TT), traditional tillage with total straw mulching during fallow (TT + SM), and no-till cultivation combined fallow mulching (NT + SM). After 2 years of fallow mulching with maize rotation, TT + SM reduced soil electrical conductivity (EC) and total salt of the upper 30 cm soil profile by 22.9% and 25.4% (p = 0.05), respectively, compared with the TT treatment. The results also indicate an improvement in volumetric soil water content (SWC) by 10.3%, soil organic matter (SOM) by 17.8%, and ultimately grain yield by 11.3% (p = 0.05) under the TT + SM treatment. Fallow mulching is recommended as an acceptable way to protect soil health in coastal fresh-starved or rain-fed farming practice

Effect of austenitizing temperature on the bainitic transformation in a high-carbon high-silicon steel

The effect of austenitizing temperature (880 - 1000°C) on the incubation period and bainitic transformation in steel 0.88% C - 1.35% Si - 1.0% Cr - 0.43% Mn is studied by the methods of x-ray diffraction and optical and transmission electron microscopy. The effect of the austenitizing temperature on the temperature and incubation period of the nose of the C-curve of the bainitic transformation is determined. The influence of a 20-min hold at 250°C after the austenitizing on the bainitic structure is studied

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems

Influence of Mineral Admixtures on the Performance of Pervious Concrete and Microscopic Research

Pervious concrete is an innovative eco-friendly construction material. Through the application of mineral admixtures and microscopic analysis to optimize its performance and analyze its mechanisms, its traits as a sustainable building option may be further improved. This study primarily examines the impact of the optimal blend quantities of fly ash, silica fume, and reinforcing agent on the attributes, micro-morphology, and phase composition of porous concrete. The optimal admixture was chosen after analyzing the effects of various factors on the mix ratio and properties of permeable concrete. To understand the degree of impact, performance tests were conducted on the 28-day compressive strength, water permeability coefficient, and porosity. Furthermore, the micro-mechanisms of the admixtures and reinforcing agents on the properties of permeable concrete were analyzed from a microscopic point of view using scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. This research found that the advantageous properties of permeable concrete were enhanced by the simultaneous integration of appropriate quantities of fly ash, silica fume, and reinforcing agent. This resulted in a 28-day compressive strength of 18.33 MPa and a permeability coefficient of 8.27 mm/s. Compared with the unadulterated mineral admixture, the optimal admixture of fly ash, silica fume, and reinforcing agent at the same time increased the 28-day compressive strength by about double; the permeability coefficient was reduced by 36%, but it was still at a high level; and the measured porosity did not differ much from the designed porosity. Through thorough microanalysis, the hydration reaction was significantly improved, which could enhance the microstructure and pore structure of the concrete. This was supported by a substantial increase in the macroscopic compressive strength and a decrease in the water permeability coefficient, which were consistent with the aforementioned enhancement found in the microanalysis

Bivariate Continuous Negatively Correlated Proportional Models with Applications in Schizophrenia Research

Bivariate continuous negatively correlated proportional data defined in the unit square (0,1)2 often appear in many different disciplines, such as medical studies, clinical trials and so on. To model this type of data, the paper proposes two new bivariate continuous distributions (i.e., negatively correlated proportional inverse Gaussian (NPIG) and negatively correlated proportional gamma (NPGA) distributions) for the first time and provides corresponding distributional properties. Two mean regression models are further developed for data with covariates. The normalized expectation&ndash;maximization (N-EM) algorithm and the gradient descent algorithm are combined to obtain the maximum likelihood estimates of parameters of interest. Simulations studies are conducted, and a data set of cortical thickness for schizophrenia is used to illustrate the proposed methods. According to our analysis between patients and controls of cortical thickness in typical mutual inhibitory brain regions, we verified the compensatory of cortical thickness in patients with schizophrenia and found its negative correlation with age

Multi-Objective Design for Critical Supporting Parameters of Vacuum-Insulated Glazing with a Case Study

Vacuum-insulated glazing (VIG) has excellent sound and heat insulation and anti-fogging properties, having been a typical structure–function-integrated glass deep processing product. However, overlapping, vacancy and excessive spacing distance of the supporting pillars will increase the concentrated stress for the glass substrate, raising the potential risk of failure. Therefore, this study, aiming to address the high cost of sample preparation and the multiple factors affecting stress distribution, developed a multi-objective design for supporting stress. In this paper, a multi-objective optimization model was designed based on comprehensive mechanical analysis under square-distributed supporting. The critical supporting pillars radius as well as the critical spacing distance were solved and met the strength requirement. Case simulation demonstrated that a 0.2 mm or more radius and a 63 mm or less spacing distance for the supporting pillars were acceptable placement methods which conformed to the design requirements. This research will act as a theoretical reference for future studies, promoting the in-depth development of VIG and exploration of high-strength safety products

Bivariate Continuous Negatively Correlated Proportional Models with Applications in Schizophrenia Research

Bivariate continuous negatively correlated proportional data defined in the unit square (0,1)2 often appear in many different disciplines, such as medical studies, clinical trials and so on. To model this type of data, the paper proposes two new bivariate continuous distributions (i.e., negatively correlated proportional inverse Gaussian (NPIG) and negatively correlated proportional gamma (NPGA) distributions) for the first time and provides corresponding distributional properties. Two mean regression models are further developed for data with covariates. The normalized expectation–maximization (N-EM) algorithm and the gradient descent algorithm are combined to obtain the maximum likelihood estimates of parameters of interest. Simulations studies are conducted, and a data set of cortical thickness for schizophrenia is used to illustrate the proposed methods. According to our analysis between patients and controls of cortical thickness in typical mutual inhibitory brain regions, we verified the compensatory of cortical thickness in patients with schizophrenia and found its negative correlation with age

Multi-Objective Design for Critical Supporting Parameters of Vacuum-Insulated Glazing with a Case Study

Vacuum-insulated glazing (VIG) has excellent sound and heat insulation and anti-fogging properties, having been a typical structure&ndash;function-integrated glass deep processing product. However, overlapping, vacancy and excessive spacing distance of the supporting pillars will increase the concentrated stress for the glass substrate, raising the potential risk of failure. Therefore, this study, aiming to address the high cost of sample preparation and the multiple factors affecting stress distribution, developed a multi-objective design for supporting stress. In this paper, a multi-objective optimization model was designed based on comprehensive mechanical analysis under square-distributed supporting. The critical supporting pillars radius as well as the critical spacing distance were solved and met the strength requirement. Case simulation demonstrated that a 0.2 mm or more radius and a 63 mm or less spacing distance for the supporting pillars were acceptable placement methods which conformed to the design requirements. This research will act as a theoretical reference for future studies, promoting the in-depth development of VIG and exploration of high-strength safety products

Hypergolic ignition modulated by head-on collision, intermixing and convective cooling of binary droplets with varying sizes

The hypergolic ignition induced by the head-on collision of TMEDA and WFNA droplets was experimentally investigated with emphasis on the effect of droplet size on the ignitibility and the ignition delay time. The ignitibility regime nomogram in We - d(o) space indicates that the reduction of droplet size tends to suppress the hypergolic ignition. The ignition delay time, which was precisely determined by using grayscale level analysis, becomes shorter for smaller droplets. The seemingly conflicting size effects were resolved by means of time scaling analysis to reveal the size dependence of the three pre-ignition processes, which were identified as the first stage of droplet collision, deformation and intermixing, the second stage of droplet heating from interior to surface, and the third stage of droplet vaporization subject to heat loss by convective cooling. (C) 2019 Elsevier Ltd. All rights reserved

MiR-501-3p Forms a Feedback Loop with FOS, MDFI, and MyoD to Regulate C2C12 Myogenesis

Skeletal muscle plays an essential role in maintaining body energy homeostasis and body flexibility. Loss of muscle mass leads to slower wound healing and recovery from illness, physical disability, poor quality of life, and higher health care costs. So, it is critical for us to understand the mechanism of skeletal muscle myogenic differentiation for maintaining optimal health throughout life. miR-501-3p is a novel muscle-specific miRNA, and its regulation mechanism on myoblast myogenic differentiation is still not clear. We demonstrated that FOS was a direct target gene of miR-501-3p, and MyoD regulated miR-501-3p host gene Clcn5 through bioinformatics prediction. Our previous laboratory experiment found that MDFI overexpression promoted C2C12 myogenic differentiation and MyoD expression. The database also showed there is an FOS binding site in the MDFI promoter region. Therefore, we hypothesize that miR-501-3p formed a feedback loop with FOS, MDFI, and MyoD to regulate myoblast differentiation. To validate our hypothesis, we demonstrated miR-501-3p function in the proliferation and differentiation period of C2C12 cells by transfecting cells with miR-501-3p mimic and inhibitor. Then, we confirmed there is a direct regulatory relationship between miR-501-3p and FOS, MyoD and miR-501-3p, FOS and MDFI through QPCR, dual-luciferase reporter system, and ChIP experiments. Our results not only expand our understanding of the muscle myogenic development mechanism in which miRNA and genes participate in controlling skeletal muscle development, but also provide treatment strategies for skeletal muscle or metabolic-related diseases in the future