Effects of Nitrogen Application on N_2O Flux from Fluvo-Aquic Soil Subject to Freezing-Thawing Process

A lab-incubation experiment was conducted to investigate the effects of different forms of nitrogen application （ammonium, NH4＋-N; nitrate, NO3--N; and amide-N, NH2-N） and different concentrations （40, 200 and 800 mg L-1） on N2O emission from the fluvo-aquic soil subjected to a freezing-thawing cycling. N2O emission sharply decreased at the start of soil freezing, and then showed a smooth line with soil freezing. In subject to soil thawing, N2O emission increased and reached a peak at the initial thawing stage. The average N2O emissions with addition of NH4＋-N, NO3 -N and NH2-N are 119.01, 611.61 and 148. 22 ug m-2 h-1, respectively, at the concentration of 40 mg L-1; 205.28, 1 084.40 and 106.13 ug m2 h-1 at the concentration of 200 mg L-1; and 693.95, 1 820.02 and 49.74 ug m-2 h4 at the concentration of 800 mg L-1. The control is only 100.35 ug m-2 h-1. N2O emissions with addition of NH4＋-N and NO3--N increased with increasing concentration, by ranging from 17.49 to 425.67% for NH4＋-N, and from 563.38 to 1458.6% for NO3--N compared with control. There was a timelag for N2O emission to reach a steady state with an increase of concentration. In contrast, by adding NH2-N to soil, N2O emission decreased with increasing concentration. In sum, NH4＋-N or NO3--N fertilizer incorporated in soil enhanced the cumulative N2O emission from the fluvo-aquic soil relative to amide-N. This study suggested that ammonium and nitrate concentration in overwintering water should be less than 200 and 40 mg L-1 in order to reduce N2O emissions from soil, regardless of amide-N.

Seasonal freezing-thawing process and hydrothermal characteristics of soil on the Loess Plateau, China

In seasonally frozen soil regions,freezing-thawing action and hydrothermal effect have strong influence on physical and mechanical behavior of shallow soil.A field experiment on the Loess Plateau in Northwest China was carried out to analyze the freezing-thawing process and hydrothermal characteristics of shallow soil considering the climate influence.The results show that the maximum seasonal freezing depth under bare ground surface in this area is from 20 cm to 50 cm.The ground temperature shows a similar changing trend with air temperature,but it has lagged behind the air temperature,and the ground temperature amplitude exponentially decreases with the increase of soil depth.The seasonally frozen soil has experienced four typical stages:unfrozen period,alternate freezing period,freezing period and alternate thawing period.The freezing-thawing process is characterized by unidirectional freezing and bidirectional thawing.The water content of shallow soil is significantly affected by air temperature,evaporation and precipitation,and the soil water content shows a"low-high-low"changing trend with the increase of depth.The soil temperature and water content interact with each other,and are often coupled.The variation trend of soil moisture with time is consistent with the change trend of the ground temperature with time in each soil layer,andthe degree of consistency is higher in the near surface soil than that in the lower layer.Also,the spatial-temporal characteristics of soil moisture and temperature is that the volumetric water content and ground temperatureof near surface soil have strong variability,and the range valueKa and coefficient of variation Cvof soil water content and ground temperaturein different seasons show a decreasing trend with the increase of depth.

Numerical Simulation on Climate Effects of Freezing-Thawing Processes Using CCM3

A parameterization of soil freezing-thawing physics for use in the land-surface model of the National Center for Atmospheric Research(NCAR) Community Climate Model(CCM3) is developed and evaluated.The new parameterization scheme has improved the representation of physical processes in the existing land surface model.Numerical simulations using CCM3 with improved land-surface processes and with the original land-surface processes are compared against the NCEP reanalysis.It is found that the CCM3 version using the improved land surface model shows significant improvements in simulating precipitation in China during the summer season,the general circulation over East Asia,and wind fields over the Tibet Plateau.For the summer season,the improved model was able to better simulate the Indian summer monsoon components,including the mean northerly wind in the upper troposphere and mean southerly wind in the lower troposphere.

Response Relationship between the Seasonal Freezing-Thawing Process of Soil and Spatial Factor Changes in the Dayekou Basin of the Qilian Mountains

Objective: In this study, the influence and response relationship between the seasonal freezing-thawing process of soil and the spatial factor changes in the management and utilization of water resource processes were explored. Methods: The monitoring equipment in this study was arranged at different altitudes, gradients, and slope directions, such as the typical forest sample area in the Dayekou Basin of the Qilian Mountains. The spatial variation characteristics of the seasonal freezing-thawing process of the soil were analyzed, and a regression model was established. Results: 1) The results of this study determined that the rate of the soil’s freezing increased with the altitude in a trend of volatility. However, the rate of the thawing of the frozen soil was found to have an opposite trend. The variation degree of the freezing-thawing process increased with the altitude in a trend of volatility. The end time of the approximate soil freezing with altitude increased in a volatility trend ahead of schedule. However, the opposite was observed in the thawing rate of the frozen soil;2) The rate of the soil’s freezing under the mosses of the spruce forest at an altitude of 3028 m was found to be the lowest. However, in the sub-alpine scrub forest at an altitude of 3300 m, a maximum in the spatial ordering was observed, with an average of 1.9 cm·d-1. The thawing rate of the frozen soil in scrub-spruce forest at an altitude of 3300 m was found to be minimal. However, in the sunny slope grassland at an altitude of 2946 m, a maximum in the spatial ordering was observed, with an average of 1.5 cm·d-1. In the spatial ordering of the variation degree of the process of freezing-thawing with an average of 1.2, the scrub-grassland at an altitude of 2518 m was found to be the lowest, and the scrub-spruce forest at an altitude of 3195 m was also low;3) The soil freezing began on approximately October 20th, and the rate of soil freezing gradually became reduced. The arrival time of the frozen soil of up to 150 cm in depth in sub-alpine scrub forest was first observed at an altitude of 3028 m. However, the scrub-spruce forest at an altitude of 3100 m did not become frozen until approximately January 12th on average. Then, the thawing rate of the frozen soil increased gradually. The end time of the thawing was earliest observed in the sunny slope grassland at an altitude of 2946 m. However, the scrub-spruce forest at an altitude of 3100 m was found to be the last to thaw, and averaged approximately July 27th. The average durations of the freezing and thawing of the soil were 77 and 121 days, respectively, and the average duration of the entire process of freezing-thawing was 199 days;4) This study’s established regression models of the duration time of frozen soil’s thaw, and the rate of frozen soil’s thaw, all passed the R test of goodness of fit, F test of variance, and t test. Conclusions: The characteristics of the seasonal freezing-thawing process of the soil with the spatial changes were seasonal. However, the characteristics under the different spatial factor influences were not the same.

Effect of Freezing-Thawing Process on Wetland Soil Iron

The iron concentrations of snows,semi-melting snows,snowmelts,and ditch waters were observed in four typical microhabitats,Carex lasiocarpa marsh(Ⅰ), Calamagrostis angustifolia wet meadow(Ⅱ),dry land (Ⅲ)and paddy field(Ⅳ),of Sanjiang Plain Wetland, Northeast China.Each sample was collected from three sites of one microhabitat,mixed together, filtrated with 0.45μm membrane,and tested using atomic absorption spectrometry(AAS)for iron measurement.The iron concentrations of soil solutions were investigated as well.Each soil solution was in-situ extracted by negative pressure,filtrated with 0.45μm membrane,and tested using AAS,too. The results showed that the wet precipitation of iron from snow were little to detect.The loss of iron was attributed to the interaction of water and soil surface. The iron concentrations of snowmelts were 7.4,15,

Change in Grain-Size Composition of Lignite under Cyclic Freezing-Thawing and Wetting-Drying

The paper presents the change in grain-size composition of lignite under cyclic freezing-thawing (FTC) and wetting-drying (WDC). The article shows that in the spring and autumn periods the lignites can be subjected to repeated freezing-thawing and wetting-drying, which determines the possibility of changing their grain-size composition and structure. Experimental studies in laboratory conditions on the influence of cyclic freezing-thawing (FTC) and wetting-drying (WDC) on the quality indicators of lignites have been carried out, their granulometric (fractional) composition has been studied. Freezing-thawing cycle conditions are as follows (FTC): minimum exposure temperature: -20°C;maximum: +5°C;relative humidity: 30%;number of processing cycles: 3. Wetting-drying cycles are as follows (WDC): drying temperatures are +20, +40, +60, +80°C, drying time 90 minutes, the coals are further subjected to rain (soaking) for a period of water saturation to humidity of 30% - 40% and dry again. The number of wetting-drying cycles is 3 times. The tests have revealed the destructive effects of FTC and WDC on the samples of lower metamorphic grade coal, and the cycles of wet-dry lead to the much higher yield of fine sizes (-6+0;-13+0 mm) than the cycles of freeze-thaw. Furthermore, it is found that the increase in the yield of fines depends on the heating temperature: coal disintegration proceeds more intensively at a higher temperature of drying.

Effects of freezing-thawing on the engineering performance of core wall soil materials of a dam in the process of construction

The construction of water conservancy projects in cold regions experiences freezing-thawing cycles,which can greatly change the engineering properties of soil and have a significant impact on the construction of projects.Lianghekou Hydropower Station(LHS),is a controlling station with the largest installed capacity among the 7 middle reach projects in the Yalong River,the secondary tributary of the Yangtze River.LHS is located in a seasonally frozen soil area.Based on the measured data of air and ground temperature in winter in the dam core wall,the freezing-thawing variation of gravelly soil and contact clay during the filling process of the core wall are compared and analyzed,then the main impact factors of the freezing-thawing variation of soils are discussed.The results show that under the influence of air temperature,soil freezes unidirectionally from ground surface downward and deepens gradually,and the thawing processes are different at the aspects of thawing direction and rate.Air temperature and physical properties of soil including soil type,moisture content and dry density affect the freezingthawing processes of soils.And the impact of engineering construction is more remarkable than natural factors.The engineering construction affects soil temperature and freezing-thawing process by controlling the initial temperature of soil,the speed and duration of the technological conversion of paving,compaction,and the length of placed duration at night.Due to the long placed duration of soil with the slow construction method,the initial temperature of soil gradually reduces,the heat transfer process inside soil is fast.Then the internal heat of soil releases,the decreasing rate of ground temperature of soil at different depths is fast and the frozen depth deepens.While due to the short placed duration of soil with the rapid construction process,the initial temperature of soil is high,high internal heat of soil is supplied every day,and the heat transfer process inside soil is slow.Then the decreasing rate of temperature of soil at different depths is slow,and the variation amplitude of frozen depth is small.This study provides useful guidance for the freezingthawing prevention during the construction process of core wall dams located at high altitude region in winter.

Wetting-drying-freezing-thawing cycle effect on the hydro-mechanical behaviour of Yanji swelling mudstone

Swelling geomaterials in northwestern and northeastern China are exposed to both seasonal wettingdrying(DW)and freezing-thawing(FT)processes.The influence of full-process wetting-dryingfreezing-thawing(WDFT)cycles on their hydro-mechanical behaviour has not been well investigated.In this study,a series of swelling and compression tests was conducted on Yanji weathered mudstone subjected to different WD,FT and WDFT processes and the effects of seasonal processes and cyclic number on the swelling strain,compression index,rebound index and hydraulic conductivity were experimentally determined.With the increasing WD,FT and WDFT cycles,the starting time of primary swelling decreased first due to the increasing water infiltration with the appearance of large pores,and then increased because of the decreasing swelling potential of compact aggregates after two cycles.Moreover,as the cyclic number increased,the final swelling strain declined.Upon loading,the specimens after cyclic processes exhibited a smaller compression index at low stresses due to their smaller interparticle distance after swelling,but a larger one owing to the collapse of large pores and cracks at high vertical stresses.After unloading,the rebound index decreased with the increase of cyclic number due to the irreversible collapse of large pores and cracks.The hydraulic conductivity increased with the increasing cyclic number at low vertical stresses(large void ratios).With the further increase of vertical stress,the increase of hydraulic conductivity induced by cyclic processes became indiscernible.Moreover,a comparison among three processes suggested that the WDFT process exerted a more pronounced influence on the hydro-mechanical behaviour of Yanji mudstone than the separate WD or FT process.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Correlation of Microbiological Stability with Redox Processes in White Wines

In this paper, the authors analyzed the correlation between the microbiological stability of white wines and the content of sulfur dioxide, which influences the main redox processes that take place in the technological stages of the wine. The consecutive, parallel and spontaneous development of several redox processes and their impact on the quality, microbiological and crystalline stability of white wines were examined. The reduction of additive and subtractive technological interventions, of the amounts of adjuvants (sulphurous anhydride) is essential for the production of organic wines.

基于Arduino与Processing的心率检测计设计研究

随着社会经济的高速发展,人们的物质生活也有了极大的提高,但同时也伴随着各种疾病的到来,身体健康已经成为人们普遍关注的焦点,因此,心率检测仪、血压计、血糖仪等各种家用医疗监测仪器已经逐渐融入日常生活。心脏病是人们难以预防的突发致命疾病之一,本文介绍的是一款基于Arduino【是基于易用硬件和软件的原型开源平台,包由可编程的电路板(简称微控制器),以及集成开发环境(称为Arduino IDE)的现成软件组成】Processing(开源编程语言,包括编辑器、编译器、展示器)的简易心率检测计系统,其功能实用、操作简单,可以测量心率,当超出正常心率范围时及时预警,是一款便携的实时心率测试仪。

Cookie Baking Process Optimization and Quality Analysis Based on Food 3D Printing

In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.

Literature classification and its applications in condensed matter physics and materials science by natural language processing

The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.

THE EXTREMES OF DEPENDENT CHI-PROCESSES ATTRACTED BY THE BROWN-RESNICK PROCESS

Motivated by some recent works on the topic of the Brown-Resnick process, we study the functional limit theorem for normalized pointwise maxima of dependent chi-processes. It is proven that the properly normalized pointwise maxima of those processes are attracted by the Brown-Resnick process.

Investigation on taste characteristics and sensory perception of soft-boiled chicken during oral processing based on electronic tongue and electronic nose

The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual oral environment.To explore the oral processing characteristics of soft-boiled chicken,the sensory properties,texture,particle size,viscosity,characteristic values of electronic nose and tongue of different chicken samples were investigated.The correlation analysis showed that the physical characteristics especially the cohesiveness,springiness,resilience of the sample determined oral processing behavior.The addition of chicken skin played a role in lubrication during oral processing.The particle size of the bolus was heightened at the early stage,and the fluidity was enhanced in the end,which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose.But the effect of chicken skin on chicken thigh with relatively high fat content,was opposite in electronic nose,which had a certain masking effect on the perception of umami and sweet taste.In conclusion,fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken,which was more popular among people.

Modeling and analysis of air combustion and steam regeneration in methanol to olefins processes

Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.