Complete holography-based system for the identification of microparticles in water samples.

Here, we present a comprehensive holography-based system designed for detecting microparticles through microscopic holographic projections of water samples. This system is designed for researchers who may be unfamiliar with holographic technology but are engaged in microparticle research, particularly in the field of water analysis. Additionally, our innovative system can be deployed for environmental monitoring as a component of an autonomous sailboat robot.

COVID-19 Patterns in Araraquara, Brazil: A Multimodal Analysis.

The epidemiology of COVID-19 presented major shifts during the pandemic period. Factors such as the most common symptoms and severity of infection, the circulation of different variants, the preparedness of health services, and control efforts based on pharmaceutical and non-pharmaceutical interventions played important roles in the disease incidence. The constant evolution and changes require the continuous mapping and assessing of epidemiological features based on time-series forecasting.

Improving indoor air quality through an air purifier able to reduce aerosol particulate matter (PM) and volatile organic compounds (VOCs): Experimental results.

The adverse effects of fine particulate matter (PM) and many volatile organic compounds (VOCs) on human health are well known. Fine particles are, in fact, those most capable of penetrating in depth into the respiratory system. People spend most of their time indoors where concentrations of some pollutants are sometimes higher than outdoors.

Learning Diatoms Classification from a Dry Test Slide by Holographic Microscopy.

Diatoms are among the dominant phytoplankters in marine and freshwater habitats, and important biomarkers of water quality, making their identification and classification one of the current challenges for environmental monitoring. To date, taxonomy of the species populating a water column is still conducted by marine biologists on the basis of their own experience. On the other hand, deep learning is recognized as the elective technique for solving image classification problems.

High-Level Path Planning for an Autonomous Sailboat Robot Using Q-Learning.

Path planning for sailboat robots is a challenging task particularly due to the kinematics and dynamics modelling of such kinds of wind propelled boats. The problem is divided into two layers. The first one is global were a general trajectory composed of waypoints is planned, which can be done automatically based on some variables such as weather conditions or defined by hand using some human-robot interface (a ground-station).

Towards a Real-Time Embedded System for Water Monitoring Installed in a Robotic Sailboat.

Problems related to quality (and quantity) of water in natural resources or in artificial reservoirs are frequently arising and are at the center of attention of authorities and governments around the world. Many times the monitoring is not performed in an efficient time frame and a precise manner, whereas the adoption of fast and punctual solutions would undoubtedly improve the water quality and consequently enhance the life of people. To minimize or diminish such kinds of problems, we propose an architecture for sensors installed in a robotic platform, an autonomous sail boat, able to acquire raw data relative to water quality, to process and make them available to people that might be interested in such information.