Use of nonlinear regression techniques for describing concentration-response relationships of plant species exposed to contaminated site soils

2000 ◽  
Vol 19 (12) ◽  
pp. 2968-2981 ◽  
Author(s):  
Gladys L. Stephenson ◽  
Nicola Koper ◽  
Glenn F. Atkinson ◽  
Keith R. Solomon ◽  
Richard P. Scroggins
Keyword(s):  
Plant Species ◽  
Nonlinear Regression ◽  
Contaminated Site ◽  
Regression Techniques

scholarly journals Different Nonlinear Regression Techniques and Sensitivity Analysis as Tools to Optimize Oil Viscosity Modeling

Resources ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 99
Author(s):  
Dicho Stratiev ◽  
Svetoslav Nenov ◽  
Dimitar Nedanovski ◽  
Ivelina Shishkova ◽  
Rosen Dinkov ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Nonlinear Regression ◽  
Information Criterion ◽  
Least Square ◽  
Gas Oil ◽  
Oil Viscosity ◽  
Prediction Ability ◽  
Regression Techniques ◽  
Comparable Accuracy ◽  
Relative Errors

Four nonlinear regression techniques were explored to model gas oil viscosity on the base of Walther’s empirical equation. With the initial database of 41 primary and secondary vacuum gas oils, four models were developed with a comparable accuracy of viscosity calculation. The Akaike information criterion and Bayesian information criterion selected the least square relative errors (LSRE) model as the best one. The sensitivity analysis with respect to the given data also revealed that the LSRE model is the most stable one with the lowest values of standard deviations of derivatives. Verification of the gas oil viscosity prediction ability was carried out with another set of 43 gas oils showing remarkably better accuracy with the LSRE model. The LSRE was also found to predict better viscosity for the 43 test gas oils relative to the Aboul Seoud and Moharam model and the Kotzakoulakis and George.

scholarly journals The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

2019 ◽  
Vol 378 (2164) ◽  
pp. 20190165 ◽  
Author(s):  
K. Darshana Abeyrathna ◽  
Ole-Christoffer Granmo ◽  
Xuan Zhang ◽  
Lei Jiao ◽  
Morten Goodwin
Keyword(s):  
Nonlinear Regression ◽  
Binary Representation ◽  
Propositional Formula ◽  
New Class ◽  
Text Understanding ◽  
Novel Approach ◽  
Continuous Output ◽  
Regression Techniques ◽  
Regression Problems ◽  
Continuous Input

Relying simply on bitwise operators, the recently introduced Tsetlin machine (TM) has provided competitive pattern classification accuracy in several benchmarks, including text understanding. In this paper, we introduce the regression Tsetlin machine (RTM), a new class of TMs designed for continuous input and output, targeting nonlinear regression problems. In all brevity, we convert continuous input into a binary representation based on thresholding, and transform the propositional formula formed by the TM into an aggregated continuous output. Our empirical comparison of the RTM with state-of-the-art regression techniques reveals either superior or on par performance on five datasets. This article is part of the theme issue ‘Harmonizing energy-autonomous computing and intelligence’.

scholarly journals Polychlorinated Biphenyl (PCB)-Degrading Bacteria Associated with Trees in a PCB-Contaminated Site

2006 ◽  
Vol 72 (4) ◽  
pp. 2331-2342 ◽  
Author(s):  
Mary Beth Leigh ◽  
Petra Prouzová ◽  
Martina Macková ◽  
Tomáš Macek ◽  
David P. Nagle ◽  
...  
Keyword(s):  
Plant Species ◽  
Polychlorinated Biphenyl ◽  
Root Zone ◽  
Pinus Nigra ◽  
Contaminated Site ◽  
Rrna Gene ◽  
Mature Trees ◽  
Salix Caprea ◽  
Root Zones ◽  
Degrading Bacteria

ABSTRACT The abundance, identities, and degradation abilities of indigenous polychlorinated biphenyl (PCB)-degrading bacteria associated with five species of mature trees growing naturally in a contaminated site were investigated to identify plants that enhance the microbial PCB degradation potential in soil. Culturable PCB degraders were associated with every plant species examined in both the rhizosphere and root zone, which was defined as the bulk soil in which the plant was rooted. Significantly higher numbers of PCB degraders (2.7- to 56.7-fold-higher means) were detected in the root zones of Austrian pine (Pinus nigra) and goat willow (Salix caprea) than in the root zones of other plants or non-root-containing soil in certain seasons and at certain soil depths. The majority of culturable PCB degraders throughout the site and the majority of culturable PCB degraders associated with plants were identified as members of the genus Rhodococcus by 16S rRNA gene sequence analysis. Other taxa of PCB-degrading bacteria included members of the genera Luteibacter and Williamsia, which have not previously been shown to include PCB degraders. PCB degradation assays revealed that some isolates from the site have broad congener specificities; these isolates included one Rhodococcus strain that exhibited degradation abilities similar to those of Burkholderia xenovorans LB400. Isolates with broad congener specificity were widespread at the site, including in the biostimulated root zone of willow. The apparent association of certain plant species with increased abundance of indigenous PCB degraders, including organisms with outstanding degradation abilities, throughout the root zone supports the notion that biostimulation through rhizoremediation is a promising strategy for enhancing PCB degradation in situ.

scholarly journals Nonlinear flowering responses to climate: are species approaching their limits of phenological change?

2013 ◽  
Vol 368 (1624) ◽  
pp. 20120489 ◽  
Author(s):  
Amy M. Iler ◽  
Toke T. Høye ◽  
David W. Inouye ◽  
Niels M. Schmidt
Keyword(s):  
Regression Model ◽  
Plant Species ◽  
Plant Communities ◽  
Nonlinear Regression ◽  
Interannual Variation ◽  
Flowering Phenology ◽  
Climatic Conditions ◽  
Rate Of Change ◽  
Nonlinear Regression Model

Many alpine and subalpine plant species exhibit phenological advancements in association with earlier snowmelt. While the phenology of some plant species does not advance beyond a threshold snowmelt date, the prevalence of such threshold phenological responses within plant communities is largely unknown. We therefore examined the shape of flowering phenology responses (linear versus nonlinear) to climate using two long-term datasets from plant communities in snow-dominated environments: Gothic, CO, USA (1974–2011) and Zackenberg, Greenland (1996–2011). For a total of 64 species, we determined whether a linear or nonlinear regression model best explained interannual variation in flowering phenology in response to increasing temperatures and advancing snowmelt dates. The most common nonlinear trend was for species to flower earlier as snowmelt advanced, with either no change or a slower rate of change when snowmelt was early (average 20% of cases). By contrast, some species advanced their flowering at a faster rate over the warmest temperatures relative to cooler temperatures (average 5% of cases). Thus, some species seem to be approaching their limits of phenological change in response to snowmelt but not temperature. Such phenological thresholds could either be a result of minimum springtime photoperiod cues for flowering or a slower rate of adaptive change in flowering time relative to changing climatic conditions.

scholarly journals SERAPAN SIANIDA (CN) PADA Mikania cordata (Burm.f) B.L. Robinson, Centrosema pubescens Bth DAN Leersia hexandra Swartz YANG DITANAM PADA MEDIA LIMBAH TAILING TERKONTAMINASI CN

2016 ◽  
Vol 10 (1) ◽  
pp. 69
Author(s):  
Fauzia Syarif
Keyword(s):  
Heavy Metal ◽  
Plant Species ◽  
High Ratio ◽  
Green Technology ◽  
Contaminated Site ◽  
Randomized Design ◽  
Leersia Hexandra ◽  
Hyperaccumulator Plants ◽  
Leersia Hexandra Swartz

Some plant species growing in the contaminated areas, indicated high toleranceand potentially affective in accumulating pollutants in their roots and above groundportions. These plants can be utilized as hyperaccumulators for cleaning up thecontaminated sites. Study on heavy metal and CN contamination and potentialplant species for accumulator is urgently needed in order to understand the problemsand to obtain suitable technology for the solution. This research aims to examineCN accumulator plants growing in CN contaminated tailing to find a possible solutionof cleaning up by using green technology of phytoremediation. Phytoremediation isdefined as clean up of pollutants primarily mediated by photosynthetic plants. Thisstudy aims to characterized plants that grow under extreme contaminated media ofgold mined tailing and to analyse their potencies as hyperaccumulators. Mikaniacordata (Burm.f) B.L.Robinson,Centrosema pubescens Bth and Leersia hexandraSwartz which proven tolerant and dominant in the contaminated site were examinedin this research. The plants were grown in tailing waste media added by 0 ppm CN,2.5 ppm CN, 5 ppm CN dan 7.5 ppm CN using complete randomized design with 5replicates. The results showed that the plants were capable of growing under thehighest level of CN. Among three species, Mikania cordata showed the highestbiomass production followed by Centrosema pubescens and Leersia hexandra. TotalCN accumulation varied between species, the highest was reached in 2.5 ppm CNtreatment i.e. 22.48 mg/kg in Leersia hexandra, followed by Centrosema pubescens(18.92 mg/kg) and Mikania cordata (12.03 mg/kg). The highest CN content was0.085 mg in Mikania cordata treated with 7.5 ppm CN. High ratio of shoot to root CN(>1) was expected in hyperaccumulator plants to indicate that CN was more distributedin the above ground portions than in the roots. In this study the highest shoo to rootCN ratio was showed in Mikania cordata i.e.11.75

Phytoremediation ability of naturally growing plant species on the electroplating wastewater-contaminated site

2020 ◽  
Vol 42 (12) ◽  
pp. 4101-4111 ◽  
Author(s):  
Tripti Mishra ◽  
Vimal Chandra Pandey ◽  
Ashish Praveen ◽  
N. B. Singh ◽  
Nandita Singh ◽  
...  
Keyword(s):  
Plant Species ◽  
Contaminated Site ◽  
Electroplating Wastewater
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