Equation discovery with ecological applications

1999 ◽  
pp. 185-207 ◽  
Author(s):  
Sašo Džeroski ◽  
Ljupčo Todorovski ◽  
Ivan Bratko ◽  
Boris Kompare ◽  
Viljem Križman
Keyword(s):  
Ecological Applications

Theoretical Ecology

2020 ◽  
Keyword(s):  
Global Change ◽  
Food Webs ◽  
Change Theory ◽  
Theoretical Ecology ◽  
Novel Theory ◽  
Ecological Applications ◽  
Population Interactions ◽  
Theoretical Science ◽  
The Way ◽  
Forward Looking

This book continues the authoritative and established edited series of theoretical ecology books initiated by Robert May which helped pave the way for ecology to become a more robust theoretical science, encouraging the modern biologist to better understand the mathematics behind their theories. This latest instalment in the Theoretical Ecology series builds on the legacy of its predecessors with a completely new set of contributions. Rather than placing emphasis on the historical ideas in theoretical ecology, the editors have encouraged each contribution to: i) synthesize historical theoretical ideas within modern frameworks that have emerged in the last ten to twenty years (e.g., bridging population interactions to whole food webs); ii) describe novel theory that has emerged in the last twenty years from historical empirical areas (e.g., macro-ecology); and iii) cover the booming area of theoretical ecological applications (e.g., disease theory and global change theory). The result is a forward-looking synthesis that will help guide the field through a further decade of development and discovery.

scholarly journals Straightforward Synthesis of Mn3O4/ZnO/Eu2O3-Based Ternary Heterostructure Nano-Photocatalyst and Its Application for the Photodegradation of Methyl Orange and Methylene Blue Dyes

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4661
Author(s):  
Jayachamarajapura Pranesh Shubha ◽  
Haralahalli Shivappa Savitha ◽  
Syed Farooq Adil ◽  
Mujeeb Khan ◽  
Mohammad Rafe Hatshan ◽  
...  
Keyword(s):  
Methylene Blue ◽  
Methyl Orange ◽  
Irradiation Time ◽  
Solar Irradiation ◽  
Anionic Dyes ◽  
One Pot ◽  
Sunlight Irradiation ◽  
Ft Ir ◽  
Degradation Activity ◽  
Ecological Applications

Zinc oxide-ternary heterostructure Mn3O4/ZnO/Eu2O3 nanocomposites were successfully prepared via waste curd as fuel by a facile one-pot combustion procedure. The fabricated heterostructures were characterized utilizing XRD, UV–Visible, FT-IR, FE-SEM, HRTEM and EDX analysis. The photocatalytic degradation efficacy of the synthesized ternary nanocomposite was evaluated utilizing model organic pollutants of methylene blue (MB) and methyl orange (MO) in water as examples of cationic dyes and anionic dyes, respectively, under natural solar irradiation. The effect of various experimental factors, viz. the effect of a light source, catalyst dosage, irradiation time, pH of dye solution and dye concentration on the photodegradation activity, was systematically studied. The ternary Mn3O4/ZnO/Eu2O3 photocatalyst exhibited excellent MB and MO degradation activity of 98% and 96%, respectively, at 150 min under natural sunlight irradiation. Experiments further conclude that the fabricated nanocomposite exhibits pH-dependent photocatalytic efficacy, and for best results, concentrations of dye and catalysts have to be maintained in a specific range. The prepared photocatalysts are exemplary and could be employed for wastewater handling and several ecological applications.

scholarly journals A contour-based topographic model for hydrological and ecological applications

1988 ◽  
Vol 13 (4) ◽  
pp. 305-320 ◽  
Author(s):  
I. D. Moore ◽  
E. M. O'Loughlin ◽  
G. J. Burch
Keyword(s):  
Topographic Model ◽  
Ecological Applications

scholarly journals Pitfalls and pointers: An accessible guide to marker gene amplicon sequencing in ecological applications

2021 ◽  
Author(s):  
Anita Porath‐Krause ◽  
Alexander T. Strauss ◽  
Jeremiah A. Henning ◽  
Eric W. Seabloom ◽  
Elizabeth T. Borer
Keyword(s):  
Marker Gene ◽  
Amplicon Sequencing ◽  
Ecological Applications

scholarly journals Prototyping Artificial Intelligent Classifiers using Deep Learning

2020 ◽  
Author(s):  
Herman Njoroge Chege
Keyword(s):  
Deep Learning ◽  
Citizen Science ◽  
Parameter Tuning ◽  
Biological Species ◽  
Biodiversity Monitoring ◽  
Practical Applications ◽  
Wide Range ◽  
Image Dataset ◽  
Ecological Applications

Point 1: Deep learning algorithms are revolutionizing how hypothesis generation, pattern recognition, and prediction occurs in the sciences. In the life sciences, particularly biology and its subfields,  the use of deep learning is slowly but steadily increasing. However, prototyping or development of tools for practical applications remains in the domain of experienced coders. Furthermore, many tools can be quite costly and difficult to put together without expertise in Artificial intelligence (AI) computing. Point 2: We built a biological species classifier that leverages existing open-source tools and libraries. We designed the corresponding tutorial for users with basic skills in python and a small, but well-curated image dataset. We included annotated code in form of a Jupyter Notebook that can be adapted to any image dataset, ranging from satellite images, animals to bacteria. The prototype developer is publicly available and can be adapted for citizen science as well as other applications not envisioned in this paper. Point 3: We illustrate our approach with a case study of 219 images of 3 three seastar species. We show that with minimal parameter tuning of the AI pipeline we can create a classifier with superior accuracy. We include additional approaches to understand the misclassified images and to curate the dataset to increase accuracy. Point 4: The power of AI approaches is becoming increasingly accessible. We can now readily build and prototype species classifiers that can have a great impact on research that requires species identification and other types of image analysis. Such tools have implications for citizen science, biodiversity monitoring, and a wide range of ecological applications.

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