Growth Rate Data Research Articles

Growth of matter perturbations in some parametrization of dark energy models

In this work, we investigate the growth of matter perturbations in some known parameterizations of dark energy (DE) models i.e, CPL, JBP, BA, and a new parameterization of DE introduced in this study. We examine the growth of perturbations in the linear region by assuming the possibility of perturbations in DE. Then, we follow an overall likelihood analysis to put the same constraints on models using background and growth rate data, and we conclude that the reviewed DE parameterizations are compatible with the observational data at both background and perturbation levels. Furthermore, we find that DE parameterizations are comparable with each other, and with the Lambda CDM model. In particular, we obtain the following significant results: (i) the growth rate of matter perturbations in the homogeneous DE case is smaller than its value in the clustered case for CPL and BA models, while it is the opposite for JBP and the new model. (ii) The growth rate of matter perturbations related to the CPL and BA models have very similar behavior for both homogeneous and clustered DE cases at all redshift z. This is also true for JBP and the new model. (iii) We show that the growth rate of matter perturbations relevant to the models is lower than its value in the Lambda CDM model at low redshifts, and at high redshifts, the difference between them is insignificant. Finally, using AIC and BIC analysis, we conclude that the selection of a model that has better compatible with the observational data depends on the background and perturbation data.

Pemodelan Matematis Produk Domestik Regional Bruto Provinsi Sumatera Utara Berdasarkan Lapangan Usaha Dengan Regresi Linier Dan Nonlinier

Economic development is one of the important goals to be achieved by a country. Because basically economic development is an effort and policy with the aim of expanding employment opportunities, raising the standard of living of the people, and improving the regional regional economy. Gross Regional Domestic Product is an indicator that can be used to see economic growth in a region. North Sumatra's GRDP growth rate recorded in the Central Bureau of Statistics of North Sumatra has fluctuated. One way to find out if GRDP has increased or decreased is to use forecasting. In various fields, forecasting systems are needed that must be accurate to anticipate future events. One of the methods used is regression analysis, including polynomial and exponential regression, the data used is North Sumatra GRDP Growth Rate data from 2011 to 2021 where the X variable is the year and the Y variable is the GRDP growth rate each quarter, and the best method will be determined in this research. From the results obtained using the help of the Matlab application, the best forecasting model is by looking at the MSE which is close to zero where the MSE values are regression, namely: 1st Order Polynomial (MSE: 1.98e-05); Order 2 Polynomial (MSE: 0.0023); Order 3 Polynomial (MSE: 1.85e-04); Order 4 Polynomial (MSE: 12.65); Order 5 polynomial (MSE: 8.66); Exponential (MSE: 0.2447).

Plasmonic Functional Assay Platform Determines the Therapeutic Profile of Cancer Cells.

Functional assay platforms could identify the biophysical properties of cells and their therapeutic response to drug treatments. Despite their strong ability to assess cellular pathways, functional assays require large tissue samples, long-term cell culture, and bulk measurements. Even though such a drawback is still valid, these limitations did not hinder the interest in these platforms for their capacity to reveal drug susceptibility. Some of the limitations could be overcome with single-cell functional assays by identifying subpopulations using small sample volumes. Along this direction, in this article, we developed a high-throughput plasmonic functional assay platform to identify the growth profile of cells and their therapeutic profile under therapies using mass and growth rate statistics of individual cells. Our technology could determine populations' growth profiles using the growth rate data of multiple single cells of the same population. Evaluating spectral variations based on the plasmonic diffraction field intensity images in real time, we could simultaneously monitor the mass change for the cells within the field of view of a camera with the capacity of > ∼500 cells/h scanning rate. Our technology could determine the therapeutic profile of cells under cancer drugs within few hours, while the classical techniques require days to show reduction in viability due to antitumor effects. The platform could reveal the heterogeneity within the therapeutic profile of populations and determine subpopulations showing resistance to drug therapies. As a proof-of-principle demonstration, we studied the growth profile of MCF-7 cells and their therapeutic behavior to standard-of-care drugs that have antitumor effects as shown in the literature, including difluoromethylornithine (DFMO), 5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). We successfully demonstrated the resistant behavior of an MCF-7 variant that could survive in the presence of DFMO. More importantly, we could precisely identify synergic and antagonistic effects of drug combinations based on the order of use in cancer therapy. Rapidly assessing the therapeutic profile of cancer cells, our plasmonic functional assay platform could be used to reveal personalized drug therapies for cancer patients.

Genetic Analysis of Productive Performance in New Zealand White Rabbits

In this study, the genetic parmeters of the New Zealand white (NZW) rabbit were evaluated and clarified, including heritability and the common-litter effect, as well as genetic, common-litter, phenotypic correlations, and breeding values. For this purpose, 656 rabbits were kept at the Sakha research farm, for two years. A multi-trait animal model was used to analyze the body weights and relative growth rates data. Heritability estimations (h2a) for various body weights ranged from 0.15 to 0.30 and were low to moderate. The minimum estimate of h2a for relative growth rates at 4 to 6 weeks was 0.13, and the maximum estimate of h2a for relative growth rates at 10 to 12 weeks was 0.24. Moderate to high and positive genetic correlation (rg) between body weights, 0.36 to 0.73. rg estimates between relative growth rates ranged from moderate (0.45) to high (0.84) and positive. Common-litter correlation (rc) between body weights ranged from moderate (0.32) to high (0.71) and positive. rc estimates between relative growth rates ranged from moderate (0.43) to high (0.71) and positive. The phenotypic correlation (rp) between body weights was moderate (0.41) to high (0.80) and positive. rp estimates between the relative growth rates were high and positive. The estimated ranges of breeding values were 175.07, 263.89, 299.48, 267.78, and 279.86 for 4, 6, 8, 10, and 12 weeks, respectively. While were 24.56, 27.04, 31.80, 35.14, and 29.28 during the period of 4-6, 6-8, 8-10, 10-12, and 4-12 weeks, respectively.

Analysis of Factors Influencing the Population Growth Rate in West Sumatra Using Geographically Weighted Logistic Regression

The model of Geographically Weighted Logistic Regression (GWLR) was the development of a model of logistic regression that was implemented to data in spatial. GWLR model parameter estimation was carried out at each location for observation using spatial weighting. The research purposes was to reveal the GWLR model on the dichotomous data of the Population Growth Rate (PGR) indicator in each Districts/Cities in West Sumatra in 2020 and learn more factors that influence the probability that the population growth rate will increase in 19 Districts/Cities in West Sumatra in 2020. The parameters estimation of the GWLR model uses the Maximum Likelihood Estimation (MLE) method. Spatial weighting for parameter estimation is determined using the Fixed Gaussian Kernel weighting function and determining the optimal bandwidth using Akaike's Information Citerion (AIC) criteria. The variable of response that is categorical in this study is the rate of population growth in each districts/cities in West Sumatra in 2020 and the predictor variables are the couples number of childbearing age, the live births number, the in-migration number, and the out-migration number. The reseacrh result obtained from research were that the GWLR model is better than the logistic regression model and 4 groups of Districts/Cities are formed based on factors that affect the increase in population growth rate.

Investigations on the relation between China’s increasing renewable energy power generation and economic expansion

This study is intended to investigate the relation of China's economy expansion and renewable energy output. Expressing electricity production using renewable resources as the growth rate of renewable energy electricity output by category and the growth rate of renewable energy share, while denoting economic growth as GDP growth rate and electricity consumption per unit of GDP, the research examined the panel data from 2002 to 2020 with OLS model, and the robustness tests and heterogeneity analysis were completed. Research finds that China's renewable energy generation growth has a two-way relationship with economic growth. For heterogeneity analysis, the panel data of province GDP growth and electricity generation growth rates were used. The findings suggest that the classification criteria for provinces or the control factors that affect the findings need to be improved and taken into account. The finding shows that under the precondition that developing countries' rising energy usage benefits their economies' progress, optimizing the energy structure and promoting green transformation and sustainable development will both temporarily and permanently aid in the economy’s development.

Study on the three-child policy of the Chinese population based on the grey prediction model

In order to ensure the sustainable development of China's population and the stability of the economy and society, the implementation of the three-child policy [1] can solve the problem of China's population aging and promote the optimization of the population structure. Based on the analysis of the relevant population data in the National Bureau of Statistics, this paper mainly studies the problem of the three-child policy on China's population, and analyzes the changes of China's population. First, through the National Bureau of Statistics collected the data of China's population number, birth rate, mortality rate and natural growth rate in China in the past two decades, the change trend of China's population from 2021 to 2035 was obtained, and the final prediction results were obtained by using the grey prediction model GM (1,1). Secondly, the influence vector of the three-child policy is obtained by using the influence vector under the two-child policy, and the natural growth rate under the influence of the three-child policy from 2021-2025 is obtained. Then, the remaining natural growth rate from 2026-2035 is predicted according to the gray prediction model, and the predicted natural growth rate from 2022-2035 is deduced to deduce the population of China from 2022-2035. Finally, the study of this problem is related to China's population structure, labor resources, social security and economic development and other aspects, which needs to conduct in-depth research and analysis from multiple dimensions to formulate scientific and reasonable policies and measures, and provide important information for social and economic development planning.

A cyclic cohesive zone model for predicting hydrogen assisted fatigue crack growth (FCG) of subsea pipeline steels

A cyclic cohesive zone model for predicting hydrogen assisted fatigue crack growth is proposed, in which the degradation of cohesive strength and accumulated cohesive length is taken into account and an inverse Logistic formula is proposed for describing the degradation model of the accumulated cohesive length. A comparison between prediction results of the proposed model and experimental data of fatigue crack growth rates (FCGRs) of API 5L Grade B, X42 and X52 pipeline steels under hydrogen environment is then performed and the results show that the FCGRs predicted by the proposed model are in good agreement with the experimental data.

Screening and evaluation of phenol utilization and growth in Acinetobacter baumannii W29 of wastewater

Phenols are ubiquitous pollutants, mainly from industrial effluent, causing pollution of natural water resources. The research focused on screening efficient phenol-degrading bacteria and kinetic modelling of phenol biodegradation and growth. Membrane filtration was used for the isolation of bacteria from the wastewater sample. The screening of phenol-degrading bacteria was based on the efficiency of phenol utilization. The strain with efficient phenol degradation capacity was characterized by 16S rDNA sequencing and designated Acinetobacter baumannii W29. Biomass growth and phenol utilization rate of the strain were evaluated at different initial phenol concentrations (100-800 mgL-1). Specific growth rate data were fitted to five models, i.e. Monod, Haldane, Aiba, Teisser, and Webb model. The yield coefficient at different initial phenol concentrations was calculated from the slope of the specific growth rate (μ) versus the specific phenol utilization rate (q). The strain showed complete phenol degradation potential up to 1000 mgL-1. The maximal growth rate was achieved at 400 mgL-1 , which coincided with the maximum substrate utilization rate at the same concentration. The specific growth rate showed the best fit with the Haldane model. The strain had a yield coefficient of 0.70 (mg cell mg-1 phenol). The value of µ and Ks revealed the affinity of the strain for high-concentration phenol and the its ability to withstand high phenol concentrations. The kinetic growth behaviour of the strain fitted well with the Haldane model. The findings of the study could be applied to wastewater treatment with a high phenol load.

A robust probabilistic fatigue crack growth model based on walker’s crack growth rate equation for metallic materials

The fatigue crack growth data inherits statistical variation despite carefully controlled test procedures. The available probabilistic models rely extensively on fatigue crack growth test data of the coupon material under replicate loading conditions. In view of the often unavailability of such a database, this work proposes a new probabilistic model based on Walker’s crack growth rate equation and considers the variability in both the stress intensity factor range, ΔK and stress ratio, R. The optimum estimates of the model parameters are established using the maximum likelihood estimation (MLE) method. The model is examined using selected sets of measured fatigue crack growth curves of 7075-T6 and 2024-351 aluminum alloys. It demonstrates acceptable predictions for fatigue crack growth data on replicate and variable R-ratio loadings with failure probabilities in the range of 0.10 ≤pF≤ 0.90. The error on the observed fatigue crack growth rate data is normally distributed. The criterion of the minimum number of replicate tests for a valid probabilistic assessment of the fatigue crack growth data is established. Based on the mean squared error (MSE) parameter, the model provides a better representation of the mean fatigue crack growth rate behavior of the material for fatigue loading with variable R-ratios.

XENOFOOD-An Autoclaved Feed Supplement Containing Autoclavable Antimicrobial Peptides-Exerts Anticoccidial GI Activity, and Causes Bursa Enlargement, but Has No Detectable Harmful Effects in Broiler Cockerels despite In Vitro Detectable Cytotoxicity on LHM Cells.

Entomopathogenic bacteria are obligate symbionts of entomopathogenic nematode (EPN) species. These bacteria biosynthesize and release non-ribosomal-templated hybrid peptides (NR-AMPs), with strong, and large-spectral antimicrobial potential, capable of inactivating pathogens belonging to different prokaryote, and eukaryote taxa. The cell-free conditioned culture media (CFCM) of Xenorhabdus budapestensis and X. szentirmaii efficiently inactivate poultry pathogens like Clostridium, Histomonas, and Eimeria. To learn whether a bio-preparation containing antimicrobial peptides of Xenorhabdus origin with accompanying (in vitro detectable) cytotoxic effects could be considered a safely applicable preventive feed supplement, we conducted a 42-day feeding experiment on freshly hatched broiler cockerels. XENOFOOD (containing autoclaved X. budapestensis, and X. szentirmaii cultures developed on chicken food) were consumed by the birds. The XENOFOOD exerted detectable gastrointestinal (GI) activity (reducing the numbers of the colony-forming Clostridium perfringens units in the lower jejunum. No animal was lost in the experiment. Neither the body weight, growth rate, feed-conversion ratio, nor organ-weight data differed between the control (C) and treated (T) groups, indicating that the XENOFOOD diet did not result in any detectable adverse effects. We suppose that the parameters indicating a moderate enlargement of bursas of Fabricius (average weight, size, and individual bursa/spleen weight-ratios) in the XENOFOOD-fed group must be an indirect indication that the bursa-controlled humoral immune system neutralized the cytotoxic ingredients of the XENOFOOD in the blood, not allowing to reach their critical cytotoxic concentration in the sensitive tissues.

Wavelet Analysis of the Population Growth in a Depopulation Context Within Two Balkans Countries

Serbia and Bulgaria have been selected in order to demonstrate how the principles of wavelet engines are applied to real data for the population growth rate (POPG). The annual time series data are retrieved from the UN database covering the period from 1990 to 2021. The major part of relevant wavelet coefficients (those coefficients exceeding threshold bounds) are concentrated in the first few scales. It was observed that the more significant ‘‘wave’’ behavior over wavelet coefficients and scales for both countries was revealed with MODWT transformation in contrast to the discrete wavelet transform (DWT). The main use of the Multi-Resolution Analysis (MRA) was the separation of the ‘‘signal’’ of the original POPG series from its noise, at a specific decomposition level. In both countries persistent behavior in the POPG series was found. A proximate examination of the wavelet threshold noise series reveals moderate differences between the countries. The large outlying observation in 2020 is accurately identified for the POPG series of both countries. There is no doubt that the theoretical background presented in this study might be relevant for each of the countries within this study observing in one or the other way.

Fatigue Crack Growth Rate Description of RF-Plasma-Sprayed Refractory Metals and Alloys

A fitting method capable of describing the fatigue crack growth rate (FCGR) data in all stages of crack propagation by a simple Forman-style analytical formula was developed. To demonstrate its robustness, this method was used to quantify the fracture behavior of RF-plasma-sprayed W, Mo, W-Mo composite, and four selected Ni-based tungsten heavy alloys (WHA). The fitted FCGR parameters categorized the studied materials into two distinct sets. W, Mo, and W-Mo composite deposits made from inherently brittle refractory metals that contained a range of defects inherent to plasma spray process represented the first class. This class was characterized by low fracture toughness and a relatively wide range of fatigue crack growth thresholds. The second class of materials was represented by WHA. Here, the deposit defects were suppressed by liquid state diffusion that formed a typical WHA structure consisting of a Ni-rich matrix and large spherical W reinforcement particles. The WHA generally showed higher fatigue crack growth thresholds, but differed in fracture toughness values based on the W particle concentrations. The obtained fracture mechanical data represent a reference dataset of plasma-sprayed refractory materials, and their classification into groups clearly demonstrates the capabilities of the developed method to capture a wide range of different types of FCGR behavior.

Predicting fatigue crack growth through the small and long crack regimes for a military transport aircraft loading spectrum using FASTRAN

Predicting fatigue crack growth across the small and long crack regimes in airframe components is a challenging task. Current fracture mechanics methods require, amongst other things, high fidelity small crack growth rate data and a thorough understanding of the different behaviours of small and long cracks. This paper presents a case study where a fatigue crack growth prediction of Aluminium Alloy 7075-T7351 coupons tested to a military transport aircraft loading spectrum, from nucleation to failure, is attempted using the most recent version of the linear-elastic fracture mechanics-based analysis tool FASTRAN v5.76. The military transport aircraft loading spectrum was applied to different coupon configurations to show the effectiveness of FASTRAN for a range of crack growth scenarios. Crack growth rate data for the prediction in the near-threshold region was experimentally obtained from small cracks using quantitative fractography and this data is shown to be a determining factor in the accuracy of the prediction. This paper highlights the challenges faced by engineers in predicting fatigue crack growth under variable amplitude loading from nucleation to failure and demonstrates the ability of FASTRAN to accurately predict load history effects. Areas for continued improvement are identified with the aim of accurate and reliable fatigue crack growth prediction in a range of structures, conditions, and scenarios.

Fatigue crack growth analysis in polymeric materials

Abstract Fatigue crack growth in polymers is analyzed using the two-parametric approach. Polymers deform by crazing, viscoelastic deformation, or brittle fracture, contributing to crack growth. The analysis shows that irrespective of the nature of the deformation of the material ahead of the crack tip, the crack growth rate data can still be represented by the L-shaped curves in the ΔK–K max plane defining two limiting variables ΔK* and K max *. Thus, as in metals and alloys, the L-shaped curves depict the intrinsic fatigue behavior. The analysis further confirms that the load ratio effects in all materials are intrinsic to fatigue. A simple method for the prediction of these L-shaped fatigue curves is proposed.

Effect of compression precracking on the near threshold fatigue crack propagation in an AISI 316L stainless steel

This work addresses an alternative test procedure based on fatigue precracking under compression to mitigate the potential effects of crack closure on near-threshold fatigue data and, thus, to obtain more consistent and reliable ΔKth-values. The method relies on performing a compression precracking, in which both maximum and minimum loads are compressive, thereby resulting in a tensile residual stress field at the crack tip. Fatigue crack growth (FCG) tests conducted on an AISI 316L stainless steel provide the experimental data upon which the near-threshold fatigue crack growth rate data for different test techniques can be determined. The experimental program includes FCG tests conducted on conventional C(T) specimens with crack size to specimen width ratio a/W=0.2, single edge notched SE(B) specimens under three-point bending with a/W=0.2 and two different span sizes, S, characterized by S/W=4 and 8. Overall, the present investigation shows that combining the compression precracking technique with the utilization of non-standard bend specimens having increased span improves evaluation of the near-threshold fatigue crack growth rate data for the tested AISI 316L steel, thereby providing more accurate ΔKth-values.

DISCOVR strain pipeline screening – Part I: Maximum specific growth rate as a function of temperature and salinity for 38 candidate microalgae for biofuels production

To identify high productivity strains for microalgal biofuels generation, the maximum specific growth rate of 38 strains was measured as a function of salinity (i.e., 5, 15, and 35 PSU) and temperature (i.e., at 8 temperatures along a linear gradient from ca. 5 to 45 °C) to determine the most suitable growth medium salinity and best growing season, respectively, for outdoor raceway pond cultivation. The following strains were evaluated: Agmenellum quadruplicatum UTEX 2268, Anabaena sp. ATCC 33081, Arthrospira fusiformis UTEX 2721, Arthrospira platensis UTEX 3086, Chlorella vulgaris NREL 4-C12, Chlorella autotrophica CCMP 243, Chlorella sorokiniana DOE1044, Chlorella sorokiniana DOE 1116, Chlorella sorokiniana DOE 1412 (UTEXB3016), Chlorella vulgaris LRB AZ-1201, Chlorococcum littorale UTEX 117, Chlorococcum sp. UTEX-B P7, Chloromonas reticulata CCALA 870, Coelastrella sp. DOE 0202, Cyanobacterium sp. AB1, Micractinium reisseri NREL 14-F2, Microchloropsis gaditana CCMP1894, Microchloropsis salina CCMP 1776, Monoraphidium sp. MONOR1, Monoraphidium minutum 26B-AM, Nannochloropsis oceanica CCAP 849/10, Oscillatoria cf. priestleyi CCMEE 5020.1-1, Picochlorum celeri TG2-WT-CSM/EMRE, Picochlorum oklahomensis CCMP 2329, Picochlorum renovo NREL 39-A8, Picochlorum soloecismus DOE 101, Porphyridium cruentum CCMP 675, Scenedesmus acutus LRB-AP-0401, Scenedesmus obliquus DOE 0152.z, Scenedesmus obliquus UTEX393,Scenedesmus rubescens NREL 46B-D3, Scenedesmus sp. IITRIND2, Stichococcus minor CCMP 819, Stichococcus minutus CCALA 727, Synechococcus elongatus UTEX2973.1, Tetraselmis striata LANL 1001, Tisochrysis lutea CCMP 1324, and Tribonema minus UTEXB3156. For each strain, the identity and the presence of bacterial cohorts was determined using 18S and 16S rDNA sequencing, respectively. The maximum specific growth rate versus temperature data were also used to determine the activation energies (Arrhenius equation) for most strains. For all strains, the measured salinity and temperature tolerance data were compared to those reported in the literature. The fastest growing strains were down-selected for subsequent biomass productivity measurements in climate-simulation photobioreactors, as reported in the next paper in the issue.

Analisis Fungsi Pengeluaran Pemerintah terhadap Tingkat Pertumbuhan Ekonomi Provinsi Jawa Timur

Achieving of economic growth and development in a country is a goal to be achieved by a country. One of the economic data sets that are used as a reference in viewing the economic development of a region is to use economic data derived from Gross Domestic Regional Product. The value of GRDP reflects the potential for economic growth in a certain area. In achieving the goal of equitable growth and development, a budget or financing is needed to finance these development activities. These expenses are usually in the form of expenses for operational activities or investments. This research was conducted with the aim of observing and analyzing the impact of expenditures made by local government in relation to economic growth in east java province. This study uses a descriptive qualitative method and takes a sample of East Java government spending data for 2017-2020 and East Java GDRP Growth Rate data for 2017-2020. The results show that government spending affect the level of economic growth in an East Java Province.

Investigation of the effect of pitting corrosion on the fatigue strength degradation of structural steel using a short crack model

Steel support structures of offshore wind turbines (jackets and monopiles) undergo both fatigue and corrosion damage, impacting their lifetime. This paper investigates how pitting corrosion, caused by being exposed to the marine environment, affects the fatigue strength of structural steel. A short fatigue crack model is used to estimate the minimum required applied load amplitude which causes a growing crack emanating from the bottom of a semi-elliptical pit. Pit growth rate data, reported in literature, is employed to update the pit size and its sharpness at each time step. The modelling results show the fatigue strength degradation as a function of the exposure time to the corrosive environment. As exposure time increases, it is observed that degradation happens more quickly in the early years followed by a gradually decreasing degradation rate of the fatigue strength in the following years.

Substrate Inhibition Kinetics Models for Fitting the Growth Rate of Phenol by an Immobilized Pseudomonas putida

Phenol, in particular, is one of several dangerous synthetic compounds created by humans. There were more than 80,000 chemicals produced in the US for industrial use, and many of these are phenol and phenolic compounds that end up in the environment without being subjected to adequate safety assessment. There are several types of bacteria that may use phenol as a carbon source, making bioremediation of this dangerous material a promising possibility. We found that at very high concentrations of phenol, the growth rate of Pseudomonas putida NAUN-16 was significantly slowed down. The primary growth model modified Gompertz was utilized to obtain the growth parameter specific growth rate. In this study, we continue the work by further modelling the effect of substrate or phenol on the growth rate of the bacterium using several substrate inhibition kinetic models such as Monod, Haldane, Teissier, Aiba, Yano and Koga, Han and Levenspiel, Luong, Moser, Webb and Hinshelwood. The resultant fittings show appreciable fitting with the exception of the Monod model. The Teissier model, as opposed to the more widely used Haldane model, better suited the growth rate data at different concentrations of phenol as judged by the results of the RMSE, AICc, adjustedR2, F-test, and bias and accuracy factor. The designated values of the Teissier constants were maximal reduction rate, half saturation constant for maximal reduction and half inhibition constant which are symbolized by max, Ks and Ki were 0.150 1/hr (95% confidence interval 0.120 to 0.180), 162.19 mg/L (95% C.I.55.58 to 268.79) and 1291.94 mg/L (95% C.I. 1067.24 to 1516.65), respectively. The value generated from curve fitting interpolation should not be taken as the actual value and it should be warned of this as the true mumax should be where the gradient for the slope is zero and in this case the value was approximately 0.097 1/h at 385 mg/L phenol.