Four-Level Decay Model of^6P_(7/2) Excited State of Eu^(2+) Ion in KMgF_3

A four-level decay model of ~6P_(7/2) excited state of Eu^(2+_ ion in KMgF_3: Eu^(2+) has been proposed. The decay profiles of the ~6P_(7/2) excited state of Eu^(2+) are two exponential and the physical implication of each term in the fit equation responsible for the model is interpreted. The data obtained spectroscopically are in good agreement with the fit results.

Short-term forecast in the early stage of the COVID-19 outbreak in Italy. Application of a weighted and cumulative average daily growth rate to an exponential decay model

To estimate the size of the novel coronavirus(COVID-19)outbreak in the early stage in Italy,this paper introduces the cumulated and weighted average daily growth rate(WR)to evaluate an epidemic curve.On the basis of an exponential decay model(EDM),we provide estimations of the WR in four-time intervals from February 27 to April 07,2020.By calibrating the parameters of the EDM to the reported data in Hubei Province of China,we also attempt to forecast the evolution of the outbreak.We compare the EDM applied to WR and the Gompertz model,which is based on exponential decay and is often used to estimate cumulative events.Specifically,we assess the performance of each model to short-term forecast of the epidemic,and to predict the final epidemic size.Based on the official counts for confirmed cases,the model applied to data from February 27 until the 17th of March estimate that the cumulative number of infected in Italy could reach 131,280(with a credibility interval 71,415-263,501)by April 25(credibility interval April 12 to May 3).With the data available until the 24st of March the peak date should be reached on May 3(April 23 to May 23)with 197,179 cumulative infections expected(130,033e315,269);with data available until the 31st of March the peak should be reached on May 4(April 25 to May 18)with 202,210 cumulative infections expected(155.235 e270,737);with data available until the 07st of April the peak should be reached on May 3(April 26 toMay 11)with 191,586(160,861-232,023)cumulative infections expected.Based on the average mean absolute percentage error(MAPE),cumulated infections forecasts provided by the EDM applied to WR performed better across all scenarios than the Gompertz model.An exponential decay model applied to the cumulated and weighted average daily growth rate appears to be useful in estimating the number of cases and peak of the COVID-19 outbreak in Italy and the model was more reliable in the exponential growth phase.

A novel adaptive temporal-spatial information fusion model based on Dempster-Shafer evidence theory

In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an adaptive temporal-spatial information fusion model is proposed.Firstly,an adaptive evaluation correction mechanism is constructed by the evidence distance and Deng entropy,which realizes the credibility discrimination and adaptive correction of the spatial evidence.Secondly,the credibility decay operator is introduced to obtain the dynamic credibility of temporal evidence.Finally,the sequential combination of temporal-spatial evidences is achieved by Shafer’s discount criterion and Dempster’s combination rule.The simulation results show that the proposed method not only considers the dynamic and sequential characteristics of the temporal-spatial evidences com-bination,but also has a strong conflict information processing capability,which provides a new refer-ence for the field of temporal-spatial information fusion.

Terrain or climate factor dominates vegetation resilience?Evidence from three national parks across different climatic zones in China

Vegetation resilience(VR),providing an objective measure of ecosystem health,has received considerable attention,however,there is still limited understanding of whether the dominant factors differ across different climate zones.We took the three national parks(Hainan Tropical Rainforest National Park,HTR;Wuyishan National Park,WYS;and Northeast Tiger and Leopard National Park,NTL)of China with less human interference as cases,which are distributed in different climatic zones,including tropical,subtropical and temperate monsoon climates,respectively.Then,we employed the probabilistic decay method to explore the spatio-temporal changes in the VR and their natural driving patterns using Geographically Weighted Regression(GWR)model as well.The results revealed that:(1)from 2000 to 2020,the Normalized Difference Vegetation Index(NDVI)of the three national parks fluctuated between 0.800 and 0.960,exhibiting an overall upward trend,with the mean NDVI of NTL(0.923)>HTR(0.899)>WYS(0.823);(2)the positive trend decay time of vegetation exceeded that of negative trend,indicating vegetation gradual recovery of the three national parks since 2012;(3)the VR of HTR was primarily influenced by elevation,aspect,average annual temperature change(AATC),and average annual precipitation change(AAPC);the WYS'VR was mainly affected by elevation,average annual precipitation(AAP),and AAPC;while the terrain factors(elevation and slope)were the main driving factors of VR in NTL;(4)among the main factors influencing the VR changes,the AAPC had the highest proportion in HTR(66.7%),and the AAP occupied the largest area proportion in WYS(80.4%).While in NTL,elevation served as the main driving factor for the VR,encompassing 64.2%of its area.Consequently,our findings indicated that precipitation factors were the main driving force for the VR changes in HTR and WYS national parks,while elevation was the main factors that drove the VR in NTL.Our research has promoted a deeper understanding of the driving mechanism behind the VR.

Bioremediation Potential of the Macroalga Ulva lactuca (Chlorophyta) for Ammonium Removal in Elastomer Industry Wastewater

During the production of nitrile rubber, significant amounts of nitrogen in the form of ammonium are generated in the wastewater. The discharge of this high-nitrogen wastewater can lead to serious environmental issues, including eutrophication, disruption of aquatic ecosystems, and groundwater contamination. To mitigate these impacts, this research explored the bioremediation capabilities of the macroalgae Ulva lactuca (Chlorophyta) for removing nitrogen from nitrile rubber production wastewater. The study employed single-phase and Michaelis-Menten decay models based on ammonium consumption, using various dilutions of wastewater to identify the optimal concentration for treatment. The physiological state of the macroalgae was monitored by measuring the photosynthetic capacity and specific growth rate during the experiments. In the presence of U. lactuca, ammonium concentrations decreased in all treatment groups, confirming that the ammonium kinetics conformed to both applied models. Our results show that U. lactuca effectively reduces ammonium concentrations, with an approximate removal rate of 0.020 µM·g−1·min−1 across different wastewater concentrations (70%, 80%, 90%, and 100%). Notably, the treatments with 70%, 80%, and 90% wastewater strength achieved about 67% reduction in ammonium, demonstrating the alga’s capacity to treat high-nitrogen wastewater. The photosynthetic performance of U. lactuca initially declined in control conditions but stabilized across all treatments, highlighting its adaptability. The kinetic analysis using the Michaelis-Menten model indicated a Vmax of 1342 μM·g−1·DMh−1, suggesting a robust capacity for ammonium uptake when fully saturated. Our study underscores the potential of Ulva lactuca as a cost-effective and efficient agent for wastewater bioremediation, particularly in settings with high nitrogen loads.

Typhoon wind hazard model and estimation on return period of typhoon wind speed

Typhoons are one of the most serious natural disasters that occur annually on China’s southeast coast.A technique for analyzing the typhoon wind hazard was developed based on the empirical track model,and used to generate 1000-year virtual typhoons for Northwest Pacific basin.The influences of typhoon decay model,track model,and the extreme value distribution on the predicted extreme wind speed were investigated.We found that different typhoon decay models have least influence on the predicted extreme wind speed.Over most of the southeast coast of China,the predicted wind speed by the non-simplified empirical track model is larger than that from the simplified tracking model.The extreme wind speed predicted by different extreme value distribution is quite different.Four super typhoons Meranti(2016),Hato(2017),Mangkhut(2018)and Lekima(2019)were selected and the return periods of typhoon wind speeds along the China southeast coast were estimated in order to assess the typhoon wind hazard.

Calibration of Soil Electromagnetic Conductivity in Inverted Salinity Profiles with an Integration Method

Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity (ECa) and soil electrical conductivity of a saturated soil paste extract (ECe) or a 1:5 soil water extract (EC1:5) using an electromagnetic induction instrument (EM38). The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1:5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1:5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1:5 continuously with depth.

Evaluating the effects of granular and membrane filtrations on chlorine demand in drinking water

In this study, chlorine decay experiments were conducted for the raw water from Nakdong River that is treated by Chllseo Water Treatment Plant （CWTP） situated in Haman, Korea as well as the effluents from sand and granular activated carbon （GAC） filters of CWTP and fitted using a chlorine decay model. The model estimated the fast and slow reacting nitrogenous as well as organic/inorganic compounds that were present in the water. It was found that the chlorine demand due to fast and slow reacting （FRA and SRA） organic/inorganic substances was not reduced significantly by sand as well as GAC filters. However, the treated effluents from those filters contained FRA and SRA that are less reactive and had small reaction rate constants. For the effluents from microfiltration, ultrafiltration, and nanofiltration the chlorine demand because FRA and SRA were further reduced but the reaction rate constants were larger compared to those of sand and GAC filter effluents. This has implications in the formation of disinfection by products （DBPs）. If DBPs are assumed to form due to the interactions between chlorine and SRA, then it is possible that the DBP formation potential in the effluents from membrane filtrations could be higher than that in the effluents from granular media filters.

Seasonal Variation of Carbon and Nitrogen Emissions from Turfgrass

The role of turfgrasses in C and N cycling in the southeastern U.S. has not been well documented. The objectives of this research were to determine the characterization of chemical quality, clipping decomposition rates, and C and N release from warm- and cool-season turfgrasses. The study was conducted for 46 weeks in 2012 in Auburn, AL. Four warm season turfgrasses were used included (bermudagrass [Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt Davy], centipedegrass (Eremochloa ophiuroides (Munro) Hack), St. Augustinegrass (Stenotaphrum secundatum (Walter) Kuntze), zoysiagrass (Zoysia japonica Steud.), and one cool season turfgrass (tall fescue (Festuca arundinacea Schreb)). Litter was placed into nylon bags at an oven dry rate of 3.6 Mg?ha?1. Litter bags were retrieved after 0, 1, 2, 4, 8, 16, 24, 32, and 46 weeks, and analyzed for total C and N. A double exponential decay model was used to describe mass, C, and N loss. Results indicated that tall fescue decomposition occurred rapidly compared to warm season turfgrasses. Litter mass loss measured after 46 weeks was determined to be 61.7%, 73.7%, 72.2%, 86.8%, and 45.4% in bermudagrass, centipedegrass, St. Augustinegrass, tall fescue, and zoysiagrass respectively. Zoysiagrass litter had a higher lignin concentration, while tall fescue had the lowest lignin. Over 46 weeks’ release of C was in the order: zoysiagrass > bermudagrass = centipedegrass = St. Augustinegrass > tall fescue, and release of N was in the order zoysiagrass > centipedegrass > bermudagrass = St. Augustinegrass > tall fescue. Our study concluded that, zosiagrass is a better choice for home lawns.

Reliable Analytic Strategy to Correlate the Morphological and Cytological Parameters on Lupinus termis L, against Fusarium oxysporum Infection

Many analytic strategies have emerged to estimate plant responses to Fusarium wilt. The demand for fast and reliable method （diagnosis, prediction） to determine isolate strength accurately is not established yet. Early determination of pathogen strength helps in plant medication. The aim of this study was to develop a faster strategy and method for early determination of fungal isolates strength in correlation to plant response. Till now, the scientists have no consensus on the most correlated parameters that could express wilt precisely. In this study, 30 isolates of Fusarium oxysporum isolated from Lupinus termis L. were used to provide an explicit image about the real strength of Fusarium isolates and its impact on the plant. Wilting percentage ranged from 26.67% to 93.33% of the infected plants depending on isolate virulence. Some of cellular, morphological and physical measurements were conducted on 8 out of 30 isolates, including root （length, fresh weight （FW） and dry weight （DW））, nodules （water content （WC）, FW, DW）, stem （height, WC, FW, DW）, total leaves/plant （WC, FW, DW） and the fourth leaf （WC, FW, DW, leaf area, epidermal cell area, epidermal cell number, succulence）. Hierarchical clustering was used to determine the variance between the isolates. Detrended correspondence analysis （DCA） and canonical correspondence analysis （CCA） were used to determine the most important growth parameters that could express wilting accurately. The CCA results showed that most of the measured parameters on the fourth leaf, except for leaf epidermal cell number, were highly and positively correlated to wilt. That makes these specific parameters valuable and sensitive for any changes in isolates strength. Accordingly, a mathematical model was created to be helpful in the quick determination of isolate strength and precise medication.

Modeling and simulation of landfill gas production from pretreated MSW landfill simulator

The cumulative landfill gas （LFG） production and its rate were simulated for pretreated municipal solid waste （MSW） landfill using four models namely first order exponential model, modified Gompertz model, single component combined growth and decay model and Gaussian function. Considering the behavior of the pretreated MSW landfill, a new multi component model was based on biochemical processes that occurring in landfilled pretreated MSW. The model was developed on the basis of single component combined growth and decay model using an anaerobic landfill simulator reactor which treats the pretreated MSW. It includes three components of the degradation i.e. quickly degradable, moderately degradable and slowly degradable. Moreover, the devel- oped model was statistically analyzed for its goodness of fit. The results show that the multi components LFG production model is more suitable in comparison to the simulated models and can efficiently be used as a modeling tool for pretreated MSW landfills. The proposed model is likely to give assistance in sizing of LFG collection system, generates speedy results at lower cost, improves cost-benefit analysis and decreases LFG project risk. It also indicates the stabilization of the landfill and helps the managers in the reuse of the landfill space. The proposed model is limited to aerobically pretreated MSW landfill and also requires the values of delay times in LFG productions from moderately and slowly degradable fractions ofpretreated MSW.

Strong decays of newly observed heavy flavor hadrons

In this talk, we briefly review the experimental status of newly observed charmed hadrons during the past years. Then we introduce the theoretical progresses on these charmed hadrons, especially our studies on the strong decays of new charmed hadrons during the past one year.

Dependence of multiplicity and transverse energy distributions on nuclear geometry at RHIC

We study the dependence of multiplicity and transverse energy on nuclear geometry at RHIC at SNN1/2=19.6,130,and 200 GeV basing on ellipsoidal decay model.It is found that the ellipsoidal decay model can describe the data well.

Optimal phase sensitivity of atomic Ramsey interferometers with coherent spin states

We present a detailed analysis of phase sensitivity for a nonlinear Ramsey interferometer, which utilize effective mean-field interaction of a two-component Bose-Einstein condensate in phase ac- cumulation. For large enough particle number N and small phase shift φ, analytical results of the Ramsey signal and the phase sensitivity are derived for a product coherent state θ, 0）. When collisional dephasing is absent, we confirm that the optimal sensitivity scales as 2/N3/2 for polar angle of the initial state θ = π/4 or 3π/4. The best-sensitivity phase satisfies different transcendental equations, depending upon the initial state and the observable being measured after the phase accumulation. In the presence of the collisional dephasing, we show that the N-3/2-scaling rule of the sensitivity maintains with spin operators jx and jy measurements. A slightly better sensitivity is attainable for optimal coherent state with θ = π/6 or 5π/6.