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).

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·hm^(-2) mixed with urea at 60 kg N·hm^(-2) 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 collected were subjected to analysis of variance.Regression analysis was used to predict contributions of increased soil p H in plant material treated soils to exchangeable Al,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 p H at harvesting in plant material treated soils significantly reduced exchangeable H and A_1.Soil p H 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.

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.

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 Cadmium Forms and Its Toxicity in Red Soils

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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.

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.

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.

样本级实时空中格斗决策可解释模型研究

空中格斗决策作为空战领域重要组成部分,格斗决策的实时性、准确性直接关系到空战的成败,构建一个有效的、高速的、可解释的空中格斗模型显得十分重要.实际场景中,基于深度强化学习的空中格斗决策模型为了实现强大的学习能力,往往得到的模型参数过多,这导致了决策时间的延迟,不能较好的满足实时性强的空中格斗场景.同时深度强化学习模型的黑盒特性,使得模型在智能决策过程中的决策原因不可知,可是每一次空战决策过程中的不可解释性在空战场景中存在极大的未知风险.为了解决这些问题,本文提出一种基于高效的轻量级决策树的模型用于空战中战斗决策,该轻量级模型不仅满足可解释性同时满足空战场景中的高速决策.为了解决智能决策模型在每一次决策过程中的黑箱特性,本文采用一种局部代理技术完成空战格斗中每一次决策过程中的样本级解释.实践表明本文所构建的空中格斗模型具有较高的决策精度、速度与实战性能.

Quality Improvement of Recycled Concrete Aggregate by Accelerated Carbonation under Different Pressure

Due to the presence of old mortar (OM) and interfacial transition zone (ITZ),recycled concrete aggregate (RCA) is inferior to natural aggregate (NA).The purpose of this paper was to study the effect of accelerated carbonation on the macro-properties and micro-properties of RCA under different pressure(0.05,0.15,0.30 MPa).The macro-property tests included colour change,apparent density,water absorption,and crushing value of RCA.The micro-property tests included scanning electron microscopy (SEM),X-ray diffraction (XRD),thermogravimetry-differential scanning calorimetry (TG-DSC),and Vickers micro-hardness(VMH).The results showed that the change trends of apparent density,water absorption,and crushing value of RCA displayed exponential relationships as pressure increasing,with the optimum pressure of 0.30 MPa.SEM images indicated that the calcite caused by the hydration products in RCA and the Ca(OH)_(2) derived from saturated lime water improved the properties of RCA;as the apparent density increased,the water absorption and crushing value decreased.The results of XRD and TG-DSC indicated that,as the pressure increased,the masses of Ca(OH)_(2) in carbonated RCA gradually decreased,while those of CaCO_(3) gradually increased,which demonstrated that the carbonation degree gradually increased.Besides,ITZ-2 was the weakest phase in RCA,but its improvement degree of VMH by accelerated carbonation was higher than that of OM.However,RCA was not completely carbonated,but only carbonated in a certain depth after 24 h accelerated carbonation.

Sustainability of lime stabilized road subgrade in mountainous regions of Türkiye

In this paper the use of lime stabilized subgrade for low volume roads in two regions with high mountains and different frost penetration conditions in Türkiye was investigated in terms of design,performance,and cost.Pavements on unstabilized and stabilized subgrade were designed for two regions(Izmir and Van),covering all climate variations.The resilient modulus of the lime stabilized subgrade with different soil pulverization levels for non-freezing and freezing conditions were taken from a previous laboratory study.Frost effects were considered in pavement design using two different approaches,including limited subgrade frost penetration method and reduced subgrade strength method.Detailed application and evaluation were performed for all steps.Lime stabilized subgrades significantly reduced the thickness of base courses,and the benefit of lime stabilization was highly dependent on soil pulverization level.A detailed cost analysis on the unstabilized and stabilized cases found that the use of lime stabilization in the subgrade provided significant initial cost savings.Comparative analysis by using the AASHTO(1993)method and KENPAVE software,and quantity effect of soil pulverization level on the performance of low volume roads from a service life perspective,show that subgrade resilient modulus can be estimated.It is also possible to make correct performance estimation in the field.The results of the study show that lime stabilization is a good solution for low volume roads in the mountainous regions of Türkiye.

Implementation of Rapid Code Transformation Process Using Deep Learning Approaches

Our previous work has introduced the newly generated program using the code transformation model GPT-2,verifying the generated programming codes through simhash(SH)and longest common subsequence(LCS)algo-rithms.However,the entire code transformation process has encountered a time-consuming problem.Therefore,the objective of this study is to speed up the code transformation process signi􀀀cantly.This paper has proposed deep learning approaches for modifying SH using a variational simhash(VSH)algorithm and replacing LCS with a piecewise longest common subsequence(PLCS)algorithm to faster the veri􀀀cation process in the test phase.Besides the code transformation model GPT-2,this study has also introduced MicrosoMASS and Facebook BART for a comparative analysis of their performance.Meanwhile,the explainable AI technique using local interpretable model-agnostic explanations(LIME)can also interpret the decision-making ofAImodels.The experimental results show that VSH can reduce the number of quali􀀀ed programs by 22.11%,and PLCS can reduce the execution time of selected pocket programs by 32.39%.As a result,the proposed approaches can signi􀀀cantly speed up the entire code transformation process by 1.38 times on average compared with our previous work.

Preliminary Study on the Treatment Efficiency of Pasteurized Lime Thermal Alkaline Hydrolysis for Excess Activated Sludge and Reduction of Tetracycline Resistance Genes

Thermal alkaline hydrolysis is a common pretreatment method for the utilization of excess activated sludge(EAS).Owing to strict environment laws and need for better energy utilization,new methods were developed in this study to improve the efficiency of pretreatment method.Direct thermal hydrolysis(TH),pasteurized thermal hydrolysis(PTH),and alkaline pasteurized thermal hydrolysis(PTH+CaO and PTH+NaOH)methods were used to treat EAS.Each method was compared and analyzed in terms of dissolution in ammonium nitrogen(NH_(4)^(+)-N)and soluble COD(SCOD)in EAS.Furthermore,the removal of tetracycline resistance genes(TRGs)and class 1 transposon gene intI1 from EAS was investigated.The NH_(4)^(+)-N and SCOD concentrations in EAS treated by PTH were 1.24 and 2.58 times higher than those of TH.However,the removal efficiency of total TRGs and intI1 between the groups was comparable.The SCOD concentration of the PTH+NaOH group was 4.37 times higher than that of the PTH group,and the removal efficiency of total TRGs was increased by 9.52%compared with that by PTH.The NH_(4)^(+)-N and SCOD concentrations of the PTH+CaO group could reach 85.04%and 92.14%of the PTH+NaOH group,but the removal efficiency of total TRGs by PTH+CaO was 19.78%lower than that by PTH+NaOH.Thus,to reduce the financial cost in actual operation,lime(CaO)can be used instead of a strong alkali(NaOH),and pasteurized steam at 70℃ instead of conventional high-temperature heating to treat EAS.This study provides a reference for the development of alkaline hydrolysis under moderate temperatures along with the removal of TRGs in EAS.

Detecting Deepfake Images Using Deep Learning Techniques and Explainable AI Methods

Nowadays,deepfake is wreaking havoc on society.Deepfake content is created with the help of artificial intelligence and machine learning to replace one person’s likeness with another person in pictures or recorded videos.Although visual media manipulations are not new,the introduction of deepfakes has marked a breakthrough in creating fake media and information.These manipulated pic-tures and videos will undoubtedly have an enormous societal impact.Deepfake uses the latest technology like Artificial Intelligence(AI),Machine Learning(ML),and Deep Learning(DL)to construct automated methods for creating fake content that is becoming increasingly difficult to detect with the human eye.Therefore,automated solutions employed by DL can be an efficient approach for detecting deepfake.Though the“black-box”nature of the DL system allows for robust predictions,they cannot be completely trustworthy.Explainability is thefirst step toward achieving transparency,but the existing incapacity of DL to explain its own decisions to human users limits the efficacy of these systems.Though Explainable Artificial Intelligence(XAI)can solve this problem by inter-preting the predictions of these systems.This work proposes to provide a compre-hensive study of deepfake detection using the DL method and analyze the result of the most effective algorithm with Local Interpretable Model-Agnostic Explana-tions(LIME)to assure its validity and reliability.This study identifies real and deepfake images using different Convolutional Neural Network(CNN)models to get the best accuracy.It also explains which part of the image caused the model to make a specific classification using the LIME algorithm.To apply the CNN model,the dataset is taken from Kaggle,which includes 70 k real images from the Flickr dataset collected by Nvidia and 70 k fake faces generated by StyleGAN of 256 px in size.For experimental results,Jupyter notebook,TensorFlow,Num-Py,and Pandas were used as software,InceptionResnetV2,DenseNet201,Incep-tionV3,and ResNet152V2 were used as CNN models.All these models’performances were good enough,such as InceptionV3 gained 99.68%accuracy,ResNet152V2 got an accuracy of 99.19%,and DenseNet201 performed with 99.81%accuracy.However,InceptionResNetV2 achieved the highest accuracy of 99.87%,which was verified later with the LIME algorithm for XAI,where the proposed method performed the best.The obtained results and dependability demonstrate its preference for detecting deepfake images effectively.

Explainable AI and Interpretable Model for Insurance Premium Prediction

Traditional machine learning metrics(TMLMs)are quite useful for the current research work precision,recall,accuracy,MSE and RMSE.Not enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%.We included in the prediction process,machine learning models(MLMs)with greater than 99%accuracy with a sensitivity of 95%–98%and specifically in the database.We need to explain the model to domain specialists through the MLMs.Human-understandable explanations in addition to ML professionals must establish trust in the prediction of our model.This is achieved by creating a model-independent,locally accurate explanation set that makes it better than the primary model.As we know that human interaction with machine learning systems on this model’s interpretability is more crucial.For supporting set validations in model selection insurance premium prediction.In this study,we proposed the use of the(LIME and SHAP)approach to understand research properly and explain a model developed using random forest regression to predict insurance premiums.The SHAP algorithm’s drawback,as seen in our experiments,is its lengthy computing time—to produce the findings,it must compute every possible combination.In addition,the experiments conducted were intended to focus on the model’s interpretability and explain its ability using LIME and SHAP,not the insurance premium charge prediction.Three experiments were conducted through experiment,one was to interpret the random forest regression model using LIME techniques.In experiment 2,we used the SHAP technique to interpret the model insurance premium prediction(IPP).

CI Acid Orange 52 Dye Removal Using Natural and Formulated Clay-Lime Materials: Isotherm, Kinetic and Thermodynamic Studies

The main objective of the study is to improve the removal efficiency of Ourlago-kaolin (Kao), sodium montmorillonite (Na-MMT), and two formulated clay-lime (F13 and F23) towards CI Acid Orange 52 dye (AO52). F13 and F23 were obtained by chemical stabilization through thermal treatment at 300°C. Fourier Transform Infrared spectra showed different surface functional groups on the clay materials, X-ray diffraction patterns revealed the raw materials contain many crystalline phases, scanning electron microscopy micrographs showed the variation of the layered structures of different clay materials, energy dispersive X-Ray analysis micrographs revealed compositional information and thermogravimetric-differential scanning calorimetry curves indicated the higher weight loss of 11.26% and 11.38% were observed for F13 and F23 respectively. BET surface area analyzed gave 133.0071 m2•g−1 for F13 and 132.34803 m2•g−1 for F23. The optimum pH value was 2.0 for Kao and Na-MMT. The adsorption experiments indicated that F13 and F23 have the maximum uptake abilities of 7.8740 and 3.1645 mg•g−1, respectively, compared to Kao (0.8761 mg•g−1) and Na-MMT (2.6178 mg•g−1). The pseudo-second-order model well described the adsorption kinetic model of AO52 dye onto the overall samples;Langmuir and Freundlich’s isotherms appropriately described the uptake mechanism. The positive values of ∆G° and negative value ∆H° indicated that the adsorption process was spontaneous and endothermic for Na-MMT, and non-spontaneous and exothermic for Kao, F13, and F23 because of their positive values of ∆G° and negative value of ∆H°. The modified clays have higher adsorption capacities and better life cycles compared hence opening new avenues for efficient wastewater treatment.

基于LIME算法的低照度图像增强方法研究

由于低照度图像存在颜色退化、曝光不足等问题,影响图像质量与信息量,因此文章研究了一种基于LIME算法的低照度图像增强方法。通过合成正常曝光图像与低照度图像的数据集,提取了低照度图像的纹理特征与频域特征,并基于Retinex理论与深度学习建立了低照度图像增强模型。通过使用LIME算法提高模型的可解释性,同时减少模型复杂度,提高模型的透明度。在测试集LOL上,PSNR值为21.898、SSIM值为0.902,证明了该方法的可行性和可靠性。

冲击载荷作用下脆性材料的失效波实验研究

为研究玻璃、陶瓷等脆性材料在冲击加载条件下的失效波问题,在一维应变条件下,采用VISAR测量了不同冲击载荷作用下A95氧化铝陶瓷和soda lime玻璃试件背面的粒子速度时间历程。结果显示:采用相同的实验方法,soda lime玻璃试件背面粒子速度时间曲线出现了表征失效波现象的再压缩信号,与文献[1,4,8-12,17-21]结果一致,而氧化铝陶瓷试件无此现象出现。这表明陶瓷与玻璃虽同为脆性材料,但是其破坏机制不尽相同,需要进一步开展研究。

我国HEV废旧镍氢电池包中稀贵金属资源化利用环境效益分析

废旧动力电池包中含有丰富的镍、钴、稀土等稀贵金属,其资源化利用是实现混合动力汽车(Hybrid Electrical Vehicle,简称HEV)全生命周期绿色化管理的重要内容之一。随着HEV的不断发展,动力电池包在未来几年将逐渐进入批量报废阶段,其资源化利用的环境效益成为值得关注的问题。鉴于此,以丰田混合动力汽车镍氢电池包为研究对象,利用GREET模型和LIME值法测算出,相比于原生矿开采,单位废旧镍氢电池包中稀贵金属资源化利用所产生的环境效益为1083元;根据报废周期,对我国市场上现存的HEV镍氢电池包的未来报废情况进行预测。结果表明,这些电池包将从2018年开始迎来报废,在2021年达到报废高峰,至2024年基本完成报废;预计其稀贵金属资源化利用的环境效益,可累计达9421万元。提出了加强废旧动力电池回收体系和资源化利用体系建设的政策建议。

Economic cost-benefit analysis for the agricultural use of sewage sludge treated with lime and fly ash

A tool for calculating the economic and environmental impacts of the use of byproducts of industrial processes that can substitute for perishable resources was presented.This was exemplified by fly ash(the fine fraction of ash originating from coal burned to generate electricity and collected by filtering exhaust gases leaving the furnace),added to soil as a component of sewage sludge stabilized with fly ash and lime(NVS).Application to soil of NVS has potential agricultural and environmental advantages and disadvantages.The costs and benefits of such application were calculated using both a database and expert opinions.The calculations assumed a representative assemblage of soils and crops,with weights assigned to each crop type and soil characteristic.The annual weighted benefits(additional income for the farmer)and costs per hectare reached 324$/ha and 131$/ha respectively.Major potential benefits include:Chemical fertilizer replacement,159$/ha;Improvement to the soil’s physical properties,75$/ha;Supply of vital trace elements,33$/ha.Major potential costs were:Regulatory limitations on marketing of crops pending proof of absence of risk of heavy metals or radionuclides accumulation in these crops,(17$/ha and 36$/ha respectively);Application and incorporation cost,50$/ha.The presented estimates of the costs and benefits refer to the array of soils and conditions typical to Israel.It is possible to maximize potential benefits by applying fly ash only to the most suitable agricultural soils while improper use of fly ash will increase the costs incurred from its use.