Addressing the prediction of Harmful Cyanobacterial Blooms (CyanoHABs) is critical due to the increasing strain on global water resources from climate change and overexploitation. This paper introduces a combined phys...
ISBN:
(纸本)9798331534202
Addressing the prediction of Harmful Cyanobacterial Blooms (CyanoHABs) is critical due to the increasing strain on global water resources from climate change and overexploitation. This paper introduces a combined physical and biological modeling approach for simulating the 3D migration, growth, and decay of cyanobacteria colonies in water bodies. Utilizing the Smoothed Particle Hydrodynamics (SPH) method, our model accommodates complex geometries with high accuracy. This adaptable open-source framework significantly enhances the simulation of cyanobacteria migration in three dimensions, a capability often lacking in existing environmental lake simulators. Moreover, it is being integrated into an advanced early warning system, representing a digital twin of the water body. This integration aims to improve the prediction and management of CyanoHABs, contributing to safeguard water quality and ecosystem health.
Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy...
ISBN:
(纸本)9798331534202
Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy, size, and cost. This study presents a methodology, integrating deep learning, modeling and simulation to enhance the design of microfluidic systems, used to develop an innovative approach for viscosity measurement of polymer melts. We use synthetic data generated from the simulations to train a deep learning model, which then identifies rheological parameters of polymer melts from pressure drop and flow rate measurements in a microfluidic circuit, enabling online estimation of fluid properties. By improving the accuracy and flexibility of microfluidic rheological estimation, our methodology accelerates the design and testing of microfluidic devices, reducing reliance on physical prototypes, and offering significant contributions to the field.
Addressing the prediction of Harmful Cyanobacterial Blooms (CyanoHABs) is critical due to the increasing strain on global water resources from climate change and overexploitation. This paper introduces a combined phys...
详细信息
Virtual Screening (VS) methods can considerably aid drug discovery research, predicting how ligands interact with drug targets. BINDSURF is an efficient and fast blind VS methodology for the determination of protein b...
详细信息
Microfluidic devices are increasingly used in biological and chemical experiments due to their cost-effectiveness for rheological estimation in fluids. However, these devices often face challenges in terms of accuracy...
详细信息
The aim of this paper is to present a new approach to creating high performance and low-power asynchronous circuits using high level design tools. In order to achieve this, we introduce a new timing model called Pseud...
详细信息
This work deals with the decrease of the computational cost in the task of feature weighting for the predictive models of the response to the treatment of migraine with OnabotulinumtoxinA (BoNT-A). More specifically, ...
详细信息
Migraine is one of the most disabling neurological diseases. Its prevalence reaches 15% of the population in developed countries and lead to high economic costs for private and national health systems. There is no cur...
详细信息
The natural progression from classic Model-Based Systems Engineering (MBSE) methodologies to Modeling and Simulation-Based Systems Engineering (M&SBSE) brings the need for more flexible and powerful validation too...
详细信息
We propose an evolutionary flow for finite state machine in- ference through the cooperation of grammatical evolution and a genetic algorithm. This coevolution has two main ad- vantages. First, a high-level descriptio...
详细信息
ISBN:
(纸本)9781450319645
We propose an evolutionary flow for finite state machine in- ference through the cooperation of grammatical evolution and a genetic algorithm. This coevolution has two main ad- vantages. First, a high-level description of the target prob- lem is accepted by the flow, being easier and affordable for system designers. Second, the designer does not need to de- fine a training set of input values because it is automatically generated by the genetic algorithm at run time. Our exper- iments on the sequence recognizer and the vending machine problems obtained the FSM solution in 99.96% and 100% of the optimization runs, respectively.
暂无评论