Growth,yield,yield components,and grain qualities of groundnut(Arachis hypogaea L.)as affected by liming and phosphorus rates in southwest Ethiopia

Two field experiments were conducted in the main seasons of 2021/22 at the farmers'farm in two districts of southwest Ethiopia to investigate the effects of lime and phosphorus on groundnut yield and yield components,employing four levels of lime(0,2,4,and 6 t CaCO_(3)ha^(-1))and phosphorus(0,46,69,and 92 kg P_(2)O_(5)ha^(-1))arranged in factorial RCBD design with three replications.Data on the yield and its components were collected and subjected to an ANOVA using SAS software.The result demonstrated that plant height,number of branches,canopy spread,and shelling percentage were affected significantly by liming while effective nodule number,total peg,matured pod,and pod yield of groundnut significantly influenced by the main factors and their interactions.The combined application of 4 t lime and 46 kg P_(2)O_(5)ha^(-1)resulted in the highest number of effective nodules(147.23 plant^(-1)),total pod(72.6 plant^(-1)),mature pod(62.4 plant^(-1)),pod yield(4.49 t ha^(-1)),oil content(50.6%)and protein content(33.1%)whereas the lowest values of these parameters were seen in plots where neither lime nor phosphorus was applied.Therefore,it is advised that groundnut growers in the study areas,and similar agroecologies,apply the combination of 4 t lime and 46 kg P_(2)O_(5)ha^(-1).

SOC Turnover and Lime-CO₂Evolution during Liming of an Acid Andisol and Ultisol

Agricultural liming contributes significantly to atmospheric CO2 emission from soils but data on magnitude of lime- contributed CO2 in a wide range of acid soils are still few. Data on lime-contributed CO2 and SOC turnover for global acid soils are needed to estimate the potential contribution of agricultural liming to atmospheric CO2. Using Ca13CO3 (13C 99%) as lime and tracer, here we separated lime-contributed and SOC-originated CO2 evolution in an acidic Kuroboku Andisol from Tanashi, Tokyo Prefecture (35°44′ N, 139°32′ E) and Kunigami Mahji Ultisol of Nakijin, Okinawa Prefecture, Japan (26°38′ N, 127°58′ E). On the average, lime-CO2 was 76.84% (Kuroboku Andisol) and 66.36% (Kunigami Mahji Ultisol) of overall CO2 emission after 36 days. There was increased SOC turnover in all limed soils, confirming priming effect (PE) of liming. The calculated PE of lime (Kuroboku Andisol, 51.97% - 114.95%;Kunigami Mahji Ultisol, 10.13% - 35.61%) was entirely 12C turnover of stable soil organic carbon (SOC) since SMBC, a labile SOC pool, was suppressed by liming in our experiment. Our results confirmed that mineralization of lime-carbonates is the major source of CO2 emission from acid soils during agricultural liming. Liming can influence the size of CO2 evolution from agricultural ecosystems considering global extent of acid soils and current volume of lime utilization. We propose the inclusion of liming in simulating carbon dynamics in agricultural ecosystems.

Liming and Fertilizer Potentials of Some Underutilized Plant Materials in Southwestern Nigeria

Soil acidification and phosphorus deficiency are a major constraint to crop production in tropical soils. Use of conventional liming materials is associated with some limitations viz： inability to solely improve nitrogen and available phosphorus in soils, loss of soil organic carbon and soil aggregate stability. Liming and fertilizer potentials of leaves from three plant materials （Tithonia diversifolia （TL）, Imperata cylindrica （SG） and Gliricidia sepium （GL）） widely growing in Ogbomoso, southwest Nigeria, were tested under incubation condition. Each of the plant material was applied at.the rate of 10 t·hm-2 with and without 50% concentration of NPK 15 ： 15 ： 15-urea mix in 500 g acidic soiL Sole lime applied at 1 t·hm-2, sole NPK 15 ： 15 ： 15 applied at 60 kg·hm2 mixed with urea at 60 kg N· hm2 and an unamended soil were compared in completely randomized design in three replicates. The treated soils were incubated for 12 weeks. Thereafter, maize seeds were raised in each pot for a period of 3 weeks. Data coUected were subjected to analysis of variance. Regression analysis was used to predict contributions of increased soil pH in plant material treated soils to exchangeable A1, H, dry root weight of maize and available phosphorus. Results indicated that sole plant materials were the order SG〉TL〉GL significantly （P〈0.05） reduced exchangeable acidity compared to unamended and sole NPK. Sole NPK had the highest exchangeable acidity （4.7 cmol·kg-1） compared to unamended soil （3.3 cmol·kg-1） and sole lime （2.7 cmol·kg-1）. Application of sole Tithonia diversifolia increased available phosphorus by 214% and 97% compared to unamended and sole NPK treated soils respectively. Sole plant materials increased maize root weight by 33% compared to sole NPK. Increasing soil pH at harvesting in plant material treated soils significantly reduced exchangeable H and A1. Soil pH was responsible for up to 33% and 53% reductions in exchangeable Al and H, respectively. This culminated into up to 22% increases in dry root weight of maize seedling. Present results showed ability of the plant materials tested to ameliorate soil acidity and improved soil available phosphorus. The plant materials should be explored for using as green manure and composting feedstock. It will go a long way to reduce high dosage use of conventional liming and fertilizer materials on acidic nutrient degraded soils.

Shenyang Liming Garments Group

The Shenyang Liming Garments Group is a large consortium, specializing in garments and the development of wool-spinning maerials, and combining science and technology with industry, trade and real estate. It consists of more than 20 enterprises, with total assets of RMB 650 million, it has imported garment production equipment from Japan. the USA and Germany, and its automatic computer composition, plate making mid cutting systems have reached the world’s advanced level. The group produces, mainly the following: western-style clothes for men and women, overcoats, unlined and cotton-padded jackets, shirts, and a series of fine woolen products. Its Lifu Brand Westem-style clothes were designated One of the "

Effect of Liming on Cadminm Forms and Its Toxicity inRed Soils

The effect of liming 4 red soils developed from Quaternary red clay and red sandstone on the cadmiumforms and its toxicity were investigated. Liming the acid red soils could greatly reduce Cd toxicity to plantsbecause the soluble Cd and organic Cd in the soils decreased significantly while Cd bound to minerals/oxidesand residual Cd increased markedly with increasing lime rates (pH).

Use of Sewage Sludge After Liming as Fertilizer for Maize Growth

The use of sewage sludge on agricultural land provides an alternative for its disposal. Therefore, the aim of the present study was to evaluate the feasibility of using industrial sewage sludge produced in Pakistan, as an agricultural fertilizer. The agricultural soil amended with 250 g kg^-1 sewage sludge with or without lime treatment was used for the growth of the common local grain crop, maize （Zea maize）. The mobility of the trace and toxic metals in the sludge samples was assessed by applying a modified BCR sequential extraction procedure. The single extraction procedure was comprised of the application of a mild extractant （CaCl2） and water, for the estimation of the proportion of easily soluble metal fractions. To check the precision of the analytical results, the concentrations of trace and toxic metals in every step of the sequential extraction procedure were summed up and compared with total metal concentrations. The plant-available metal contents, as indicated by the deionized water and 0.01 mol L^-1 CaCl2 solution extraction fractions and the exchangeable fraction of the sequential extraction, decreased significantly （P 〈 0.05） with lime application because of the reduced metal availability at a higher pH, except in the cases of Cd and Cu, whose mobility was slightly increased. Sludge amendment enhanced the dry weight yield of maize and the increase was more obvious for the soil with lime treatment. Liming the sewage sludge reduced the trace and toxic metal contents in the grain tissues, except Cu and Cd, which were below the permissible limits of these metals. The present experiment demonstrates that liming was an important factor in facilitating the growth of maize in sludge-amended soil.

Liming Characteristics of a High-Calcium Dry Flue Gas Desulfurization By-Product and a Class-C Fly Ash

Due to coal’s availability and low cost, coal combustion continues to be the United States’ primary energy source. However, coal combustion produces large quantities of waste material. Some coal combustion by-products (CCBs) have chemical and physical characteristics that make them potentially useful as soil amendments. The objectives of this study were to characterize a relatively new, high-calcium dry flue gas desulfurization (DFGD) by-product and compare its agronomic liming potential to a Class-C fly ash (FA) and reagent-grade calcium carbonate (CaCO3). Calcium car-bonate equivalence (CCE), degree of fineness (DOF), and effective neutralizing value (ENV) for each CCB were determined using standard methods. The CCBs and CaCO3 were also incubated with an acidic (~4.5) clay sub-soil at application rates equiva-lent to 0, 0.5, 1, and 2 times the soil’s lime requirement and compared to an una-mended control. Soil pH was then measured periodically during a 40-day incubation. The ENV of 79.4% for the DFGD by-product and 57.3% for the FA were comparable to those of commercially available liming materials, but were significantly lower (P < 0.05) than that of reagent-grade CaCO3. After 40 days of incubation at the 0.5× ap-plication rate, both CCBs raised the pH of the clay soil to only 5.0, while the CaCO3 raised the pH to 6.5. After 40 days at the 1× rate, all three materials had raised the soil pH to between 6.5 and 7.0, although the FA increased the soil pH more slowly than did the other two materials. At the 2× rate, both CCBs increased the soil pH to between 7.5 and 8.0, while the CaCO3 increased the soil pH to only 7.0. Both CCBs appear to be useful as soil liming materials, although care should be taken to avoid over-application, as this may make the soil too alkaline for optimum plant growth.

Biochar derived from invasive plants improved the pH,macronutrient availability and biological properties better than liming for acid rain-affected soil

Rapid development in industrialization and urbanization causes serious environmental issues,of which acid rain is one of the quintessential hazards,negatively affecting soil ecology.Liming has been investigated for a long time as the most effective amendment to alter the adverse effects of soil acidity resulting from acid rain.Herein,this study tested the biochar produced from invasive plants as an alternative amendment and hypothesized that biochar can maintain better availability of macronutrients under acid rain than liming by improving soil chemical and biological properties.Therefore,a pot experiment was conducted to compare the effects of lime and biochar at two rates(1%and 3%)on soil available nitrogen(N),phosphorous(P)and potassium(K)under simulated acid rain of two pH levels(4.5:pH_(4.5) and 2.5:pH_(2.5))as compared with tap water(pH7.1)as a control treatment.Biochar was produced using different invasive plants,including Blackjack(Biden Pilosa),Wedelia(Wedelia trilobata)and Bitter Vine(Mikania micrantha Kunth).Liming decreased the availability of soil N,P,and K by 36.3%as compared with the control due to the great increment in soil pH and exchangeable calcium(Ca^(2+))by 59%and 16-fold,respectively.Moreover,liming reduced the alpha diversity of soil bacteria and fungi by 27%and 11%,respectively.In contrast,biochar at different types and rates resulted in a fourfold increment in the available N,P,and K as an average under acid rain(pH_(4.5) and pH_(2.5))owing to maintaining a neutral pH(6.5-7),which is the most favorable level for soil microbial and enzymatic activites,and the bioavailability of soil nutrients.Furthermore,biochar caused balanced increments in Ca^(2+)by threefold,cation exchange capacity by 45%,urease activity by 16%,and fungal diversity by 10%,while having a slight reduction in bacterial diversity by 2.5%.Based on the path,correlation,and principal component analyses,the exchangeable aluminum was a moderator for the reductions in macronutrients’availability under acid rain,which decreased by 40%and 35%under liming and biochar,respectively.This study strongly recommended the use of biochar from invasive plants instead of lime for sustainable improvements in soil properties under acid rain.

基于前背景特性的逆光交通场景图像增强

由于逆光交通场景下采集到的图像存在前景亮度过低、背景亮度失真等特点,导致采集图像清晰度低、信息丢失严重和可识别性差,针对逆光图像前背景的不同特性,研究提出了一种分区域增强方法。对逆光图像使用最大类间方差法(OTSU法)分割图像的前景和背景;对逆光图像全局使用LIME方法,提升前景亮度的同时保持色彩的失真度;单独将背景部分RGB三个通道上的全局直方图均衡化结果一一映射到对应的限定区间内,提高了背景的对比度;使用Canny算子检测出前背景拼接处的黑边,根据黑边生成3个自适应的滤波模板对黑边进行分步均值滤波处理,消除了黑色边缘,提升了图像的视觉质量。在实验室自建的CHD_B数据集上,所提方法在4种常用客观评价指标上综合占优。实验结果表明,所提出的图像增强算法能有效地消除图像中的逆光现象。

数据故事化解释中分类型预测结果的反转点识别方法研究——基于LIME算法

[目的/意义]实现数据故事化中的反转点识别,有助于非专业人士理解分类型预测结果的产生原因,同时对于推动故事情节发展并使其快速到达故事高潮点具有促进作用。[方法/过程]提出故事点与反转点概念,基于LIME解释技术和反转点识别过程,设计了用于数据故事化中反转点识别的算法方案,并提出了面向分类模型的反转点识别流程。[结果/结论]将反转点识别算法应用到贷款数据集,证明此算法在数据故事化过程中寻找反转点的有效性,在获得用户期望的预测结果和快速识别反转点方面具有应用价值。

Multi-scale analysis of carbon mineralization in lime-treated soils considering soil mineralogy

Mineral carbonation is emerging as a reliable CO_(2) capture technology that can mitigate climate change.In lime-treated clayey soils,mineral carbonation occurs through the carbonation of free lime and cementitious products derived from pozzolanic reactions.The kinetics of the reactions in lime-treated clayey soils are variable and depend primarily on soil mineralogy.The present study demonstrates the role of soil mineralogy in CO_(2) capture and the subsequent changes caused by carbon mineralization in terms of the unconfined compressive strength(UCS)of lime-treated soils during their service life.Three clayey soils(kaolin,bentonite,and silty clay)with different mineralogical characteristics were treated with 4%lime content,and the samples were cured in a controlled environment for 7 d,90 d,180 d,and 365 d.After the specified curing periods,the samples were exposed to CO_(2) in a carbonation cell for 7 d.The non-carbonated samples purged with N2 gas were used as a benchmark to compare the mechanical,chemical-mineralogical,and microstructure changes caused by carbonation reactions.Experimental investigations indicated that exposure to CO_(2) resulted in an average increase of 10%in the UCS of limetreated bentonite,whereas the strength of lime-treated kaolin and silty clay was reduced by an average of 35%.The chemical and microstructural analyses revealed that the precipitated carbonates effectively filled the macropores of the treated bentonite,compared to the inadequate cementation caused by pozzolanic reactions,resulting in strength enhancement.In contrast,strength loss in lime-treated kaolin and silty clay was attributed to the carbonation of cementitious phases and partly to the tensile stress induced by carbonate precipitation.In terms of carbon mineralization prospects,lime-treated kaolin exhibited maximum carbonation due to the higher availability of unreacted lime.The results suggest that,in addition to the increase in compressive strength,adequate calcium-bearing phases and macropores determine the efficiency of carbon mineralization in lime-treated clayey soils.

基于暂态时-频特征差异的配电网高阻接地故障识别方法

高阻接地故障发生时,故障特征微弱,传统故障识别方法存在特征提取困难、阈值选取灵活性较差的技术瓶颈,导致极端故障场景下出现漏判。为此,提出基于暂态时-频特征差异的配电网高阻接地故障识别方法。首先,结合小波包香农熵量化分析高阻接地故障与正常扰动工况暂态信号的时频分布,发现二者存在显著差异:频域上,扰动工况信号的能量集中于低频,而高阻故障信号能量分布相对均匀;时域上,扰动工况信号能量集中于时间窗的前半段,高阻故障信号能量在整个时间窗内均匀分布。在此基础上,以暂态信号时-频域波形作为输入样本,将传统卷积神经网络(convolutional neural networks,CNN)模型中的softmax分类器改进为支持向量机(support vector machine,SVM)分类器,构建适应配电网高阻接地故障识别小样本场景下的CNN-SVM复合分类模型,以卷积层作为特征提取器,以SVM作为分类器,实现高阻接地故障识别。最后,为论证所提方法具有强适应性的内在原因,利用LIME可解释性分析算法可视化展现模型训练过程中的高关注度区域,从模型分类原理层面证明所提方法不受各种故障条件的影响,克服了传统故障识别方法在极端故障场景下出现漏判的缺陷,能准确识别配电线路末端10 kΩ高阻接地故障。

Optimization of the main liming process for inulin crude extract from Jerusalem artichoke tubers

A three-stage homogenate extraction was used as a new method for inulin extraction from Jerusalem artichoke tubers. Compared with the results from conventional hot water extraction, the three-stage homogenate extraction gave higher yields and caused less degradation of the inulin. The inulin crude extract was then clarified by a carbonate-precipitation method, during which three variables -- the quicklime mass, the reaction temperature and the reaction time were optimized for the main liming process to give the best clarification effect. A Plackett- Burman design, the path of steepest ascent method, a Box- Behnken design and response surface methodology （RSM） were employed in the experimental design. The optimal conditions for the main liming process were determined to be 12.0g/L, 71.4℃ and 8min. The confirmatory tests proved that the best clarification efficiency （92.74%） was achieved at these conditions and this was approximately equal to the value predicted by the model.

Performance evaluation of laterite soil embankment stabilized with bottom ash,coir fiber,and lime

In tropical regions,heavy rainfall induces erosion and shallow landslides on road embankments.Cement-based stabilization methods,common in these regions,contribute to climate change due to their high carbon footprint.This study explored the potential application of coir fiber-reinforced laterite soil-bottom ash mixtures as embankment materials in the tropics.The objective is to enhance engineered embankment slopes'erosion resistance and stability while offering reuse options for industrial byproducts.This study examined various mix designs for unconfined compressive strength(UCS)and permeability,utilizing 30%bottom ash(BA)and 1%coir fiber(CF)with varying sizes ranging from 10 to 40 mm,6%lime,and laterite soil(LS),followed by microstructural analyses.The results demonstrate that the compressive strength increases as the CF length increases to 25 mm.In contrast,permeability increases continuously with increasing CF length.Lime-treated mixtures exhibit superior short-and long-term strength and reduce permeability owing to the formation of cementitious materials,as confirmed by microstructural analyses.A lab-scale slope box was constructed to evaluate the surface erosion of the stabilized laterite soil embankment.Based on the rainfall simulation results,the LS-BA-CF mixtures show better resistance to erosion and deformation compared to untreated LS,especially when lime is added to the top layer.This study provides insights into a sustainable and cost-effective approach for slope stabilization using BA and CF,offering a promising solution for tropical regions susceptible to surface erosion and landslides.

Biopolymer stabilization of clayey soil

This study investigates the efficacy of sodium alginate(SA),xanthan gum(XG),guar gum(GG)and chitosan(CS)d each applied at five different solid biopolymer-to-water mass ratios(or dosages)and cured for 7 d and 28 d d on the unconfined compressive strength(UCS)performance of a high plasticity clayey soil.Moreover,on identifying the optimum biopolymer-treatment scenarios,their performance was compared against conventional stabilization using hydrated lime.For a given curing time,the UCS for all biopolymers followed a riseefall trend with increasing biopolymer dosage,peaking at an optimum dosage and then subsequently decreasing,such that all biopolymer-stabilized samples mobilized higher UCS values compared to the unamended soil.The optimum dosage was found to be 1.5%for SA,XG and CS,while a notably lower dosage of 0.5%was deemed optimum for GG.Similarly,for a given biopolymer type and dosage,increasing the curing time from 7 d to 28 d further enhanced the UCS,with the achieved improvements being generally more pronounced for XG-and CS-treated cases.None of the investigated biopolymers was able to produce UCS improvements equivalent to those obtained by the 28-d soilelime samples;however,the optimum XG,GG and CS dosages,particularly after 28 d of curing,were easily able to replicate 7-d lime stabilization outcomes achieved with as high as twice the soil’s lime demand.Finally,the fundamental principles of clay chemistry,in conjunction with the soil mechanics framework,were employed to identify and discuss the clayebiopolymer stabilization mechanisms.

Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking process.The ELM model exhibites the best performance compared with the models of MLR and SVR.OS-ELM and FOS-ELM are applied for sequential learning and model updating.The optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the population.The variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization ratio.The lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one month.The hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,respectively.The coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,respectively.The system exhibits desirable performance for applications in actual industrial pro-duction.

面向网络欺凌文本检测模型的算法解释及其故事化呈现研究

[目的/意义]利用可解释性技术与故事化方法研究网络欺凌检测有助于识别欺凌内容、参与网络言论治理以及净化网络生态。[方法/过程]详细分析LIME解释算法的选择依据与文本解释原理,并提出LIME算法在网络欺凌检测模型中的“钻石结构式”应用流程,进一步构建了“数据层—模型层—解释层—叙事层”的故事化呈现框架,最后通过实验验证了该框架的有效性。[结果/结论]可解释性技术辅助网络欺凌检测模型有利于提高模型应用价值与可信度,权衡模型准确性与可解释性二者的关系,而基于数据分析及解释结果的故事化呈现方法为网络信息平台数据治理提供可信、可靠、可理解依据。

Cement and Lime Stabilization Effect on the Evolutivity of an Expansive Overconsolidated Clay

This paper presents and analyzes the results of a series of compaction,fragmentability and damage tests performed on an expansive overconsolidated clay treated with cement and lime.This clay was obtained from the urban site of Sidi-Hadjrès city(wilaya of M'sila,Algeria),where significant damages frequently appears in the road infrastructures,roadway systems and light structures.Tests results obtained show that the geotechnical parameters values deduced from these tests are concordant and confirm the evolutivity of this natural clay treated with composed Portland cement or extinct lime and compacted under optimum Proctor conditions.

Explainable Deep Fake Framework for Images Creation and Classification

Deep learning is a practical and efficient technique that has been used extensively in many domains. Using deep learning technology, deepfakes create fake images of a person that people cannot distinguish from the real one. Recently, many researchers have focused on understanding how deepkakes work and detecting using deep learning approaches. This paper introduces an explainable deepfake framework for images creation and classification. The framework consists of three main parts: the first approach is called Instant ID which is used to create deepfacke images from the original one;the second approach called Xception classifies the real and deepfake images;the third approach called Local Interpretable Model (LIME) provides a method for interpreting the predictions of any machine learning model in a local and interpretable manner. Our study proposes deepfake approach that achieves 100% precision and 100% accuracy for deepfake creation and classification. Furthermore, the results highlight the superior performance of the proposed model in deep fake creation and classification.

基于可解释关系模型的SCR入口气温预测

新能源在全社会发电中占比不断增高,为了能够辅助电网进行削峰填谷,火电机组需要增加在低负荷范围内的运行时间,这会对选择性催化还原(selective catalytic reduction,SCR)的脱硝效果产生负面影响。因此,对SCR入口烟气温度(SCR gas temperature,SCRIGT)进行准确预测非常重要。首先,采用极限梯度提升(extreme gradient boosting,XGBOOST)模型,以电厂的运行参数作为输入,功率与SCRIGT的比值作为输出进行预测,然后计算得到SCRIGT。结果显示,对于两个不同锅炉类型的火电机组,平均绝对百分比误差(mean absolute percentage error,MAPE)分别为3.07%和2.49%。其次,采用不可知模型的局部可解释(local interpretable model-agnostic explanations,LIME)算法分析XGBOOST模型的预测结果,显示功率和功率与SCRIGT的比值之间存在线性关系,且R2(R-squared)为0.994,基于此构建了一种可解释关系模型进行SCRIGT预测。最后,比较分析显示,对于试验中的两个机组,可解释关系模型预测结果的MAPE分别改进至0.68%和0.97%。