Prediction of Algal Bloom Using Genetic Programming

In this study, an attempt was made to mathematically model and predict algal blooms in Tolo Harbor (Hong Kong) using genetic programming (GP). Chlorophyll plays a vital role in blooms and was used in this model as a measure of algal bloom biomass, and eight other variables were used as input for its prediction. It has been observed that GP evolves multiple models with almost the same values of errors-of-measure. Previous studies on GP modeling have primarily focused on comparing GP results with actual values. In contrast, in this study, the main aim was to propose a systematic procedure for identifying the most appropriate GP model from a list of feasible models (with similar error-of-measure) using a physical understanding of the process aided by data interpretation. Evaluation of the GP-evolved equations shows that they correctly identify the ecologically significant variables. Analysis of the final GP-evolved mathematical model indicates that, of the eight variables assumed to affect algal blooms, the most significant effects are due to chlorophyll, total inorganic nitrogen and dissolved oxygen for a 1-week prediction. For longer lead predictions (biweekly), secchi-disc depth and temperature appear to be significant variables, in addition to chlorophyll

The impact of climate change on crop pests and diseases, and adaptation strategies for the Greater Mekong Sub-Region

The workshop report provided evidences from numerous single factorial laboratory studies and modelling exercises that crop pests and diseases were affected by the vagaries of climate change viz., temperature, rainfall and wind patterns. There was also adequate support for the notion on the innate ability of crop pests and diseases to adapt to changing environmental conditions. It was revealed that organisms respond in different ways to various ecosystem templates thus lending credence to the fundamental need for one to be cognitive of organisms’ ecology and that of the nexus with ecosystem services. In contrast, it was recognized that there were conflicting messages on impacts of climate change on crop pests and diseases that were sent out to policy makers and farmers. Several key aspects were identified and the following needs for refinement were recognised: (i) Research designs that span across spatial and temporal landscapes; (ii) Effective modalities of communicating impacts to influence policies and changes and (iii) Re-designing policies and national agricultural frameworks to enhance resilience to climate changes (e.g. ecological engineering). The workshop highlighted several issues pertinent to climate impact on pests and diseases. The issues focused on the following questions: (i) The specific needs (viz. ecological and implementation) in the development of climate change adaptation strategies for P&D management, (ii) New policies or infrastructure that need to be designed to enhance sustainable agriculture, (iii) Policy change activities that could be initiated, and (iv) the key imperatives that need to be addressed to improve farmer livelihoods, learning and motivation. Overall, the workshop provided a valuable opportunity to take stock of the current state of affairs pertaining to the impact of climate change on crop pests and diseases and the adaptation strategies needed to plan and prepare the best set of collective actions in the face of climate change. The output list of recommendations and next steps will enable us to forge ahead with the directions and plans to diagnose and identify optimum efforts that will benefit the rural poor who are chronically vulnerable to the threats of climate change

Modelling the elements of flash flood hydrograph using genetic programming

1031-1038A novel approach is proposed in this work on constructing the flash flood hydrograph by modelling the elements of the hydrograph namely the time to start of the initial flood (ti), the time to peak discharge (tp), the peak discharge (Qp) and the base time (tb) using Genetic Programming (GP). The proposed method is applied to the Kickapoo River catchment in Wisconsin, USA. It is demonstrated that even under limited data scenario, for a poorly gauged station, GP is able to model the elements of hydrograph with reasonably high accuracy thereby offering considerable lead time to predict the flash flood. The mathematical models developed by GP also offer some understanding of the influence of rainfall events and the stream discharge in producing the flash floods

Modeling studies on the behavior of single and double rubble mound breakwaters using genetic programming tool

Experimental investigation on wave transmission, reflection and dissipation characteristics of rubble mound breakwater models are time consuming and expensive. However, such studies are required for designing the rubble mound breakwaters for marine structures in an optimal condition. In order to overcome such problems many researchers used various soft computing techniques such as Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Interference System (ANFIS), Genetic Programming (GP), Support Vector Machine (SVM) etc, in order to predict the design factors in the field of coastal engineering. The current work proposes Genetic Programming (GP) as a modeling tool to evolve mathematical models for the behavior of single and double breakwaters. Based on the detailed experimental data, GP models were performed to predict the reflected wave height (Hr), wave height on the breakwater (H5) and transmitted wave height (Ht) by considering with and without trigonometric effects of those breakwaters. The quality of predictability of the present model is measured by the statistical parameter, RMSE (Root Mean Square Error). Since the waves were more complex in nature, it is very essential in considering the trigonometric function’s effect in the modeling aspects. It is evident that, the GP model accurately described the non linear complex effects

Pharmacological insights into antioxidants against colorectal cancer: A detailed review of the possible mechanisms

Colorectal cancer (CRC) is ranked as the fourth most lethal and commonly diagnosed cancer in the world ac-cording to the National Cancer Institute’s latest report. Treatment methods for CRC are constantly being studied for advancement, which leads for more clinically effective cancer curing strategy. Patients with prolonged chronic inflammation caused by ulcerative colitis or similar inflammatory bowel disease are known to have high risks of developing CRC. But at a molecular level, oxidative stress due to reactive oxygen species (ROS) is an important trigger for cancer. Hence, in recent years, exogenous antioxidants have been immensely experimented in pre-clinical and clinical trials, considering it as a potential cure for CRC. Significantly, potential antioxidant compounds especially derivatives of medicinal plants have received great attention in the current research trend for CRC treatment. Though antioxidant compounds seem to have beneficial properties for the treatment of CRC, there are also limitations for pure compounds to be tested clinically. Therefore, this review aims to delineate the pharmacological awareness among researchers on using antioxidant compounds to treat CRC and the measures taken to prove the effectiveness of such compounds as impending drug candidates for CRC treatment in modern medication

Systematic Investigation of Expression of G2/M Transition Genes Reveals CDC25 Alteration in Nonfunctioning Pituitary Adenomas

Hungarian Resarch Fund (OTKA PD100648) National Development Agency (KTIA_AIK-2-2012-0010)

Computation of Turbulent Jets in Annual Counter Flow

A turbulent jet issuing into a uniform counter-flow has many engineering applications in various mixing and combustion processes. In this paper the flow field of a turbulent jet issuing into a uniform annular confined counter-flow stream was computationally investigated. The results are presented in terms of the velocity field, pertinent velocity and length scales, and turbulence characteristics and compared with available experimental data

Numerical And Experimental Studies on an Aerodynamic Distortion Grill

An aerodynamic distortion grill is employed to create non-uniform flow from arbitrary uniform upstream flow conditions. Such grills find widespread use in aerodynamic testing applications to generate non-uniform flow conditions. In this paper, the numerical results of the distortion created by one such aerodynamic distortion grill are reported. The computational results were validated against the experimentally observed distortion indices. Further, parametric numerical studies were done by varying the inlet turbulence intensity and by scaling up the geometry of the flow system