Monitoring PHB production in Synechocystis sp. with hyperspectral images.

Microalgae wastewater treatment systems have the potential for producing added-value products. More specifically, cyanobacteria are able to accumulate polyhydroxybutyrates (PHBs), which can be extracted and used for bioplastics production. Nonetheless, PHB production requires proper culture conditions and continue monitoring, challenging the state-of-the-art technologies. The aim of this study was to investigate the application of hyperspectral technologies to monitor cyanobacteria population growth and PHB production. We have established a ground-breaking measurement method able to discern spectral reflectance changes from light emitted to cyanobacteria in different phases. All in all, enabling to distinguish between cyanobacteria growth phase and PHB accumulation phase. Furthermore, first tests of classification algorithms used for machine learning and image recognition technologies had been applied to automatically recognize the different cyanobacteria species from a complex microbial community containing cyanobacteria and microalgae cultivated in pilot-scale photobioreactors (PBRs). We have defined three main indicators for monitoring PHB production: (i) cyanobacteria specific-strain density, (ii) differentiate between growth and PHB-accumulation and (iii) chlorosis progression. The results presented in this study represent an interesting alternative for traditional measurements in cyanobacteria PHB production and its application in pilot-scale PBRs. Although not directly determining the amount of PHB production, they would give insights on the undergoing processes.

A Survey of Alzheimer's Disease Early Diagnosis Methods for Cognitive Assessment.

Dementia is a syndrome that is characterised by the decline of different cognitive abilities. A high rate of deaths and high cost for detection, treatments, and patients care count amongst its consequences. Although there is no cure for dementia, a timely diagnosis helps in obtaining necessary support, appropriate medication, and maintenance, as far as possible, of engagement in intellectual, social, and physical activities. The early detection of Alzheimer Disease (AD) is considered to be of high importance for improving the quality of life of patients and their families. In particular, Virtual Reality (VR) is an expanding tool that can be used in order to assess cognitive abilities while navigating through a Virtual Environment (VE). The paper summarises common AD screening and diagnosis techniques focusing on the latest approaches that are based on Virtual Environments, behaviour analysis, and emotions recognition, aiming to provide more reliable and non-invasive diagnostics at home or in a clinical environment. Furthermore, different AD diagnosis evaluation methods and metrics are presented and discussed together with an overview of the different datasets.

Cognitive evaluation for the diagnosis of Alzheimer's disease based on Turing Test and Virtual Environments.

Alzheimer's screening tests are commonly used by doctors to diagnose the patient's condition and stage as early as possible. Most of these tests are based on pen-paper interaction and do not embrace the advantages provided by new technologies. This paper proposes novel Alzheimer's screening tests based on virtual environments and game principles using new immersive technologies combined with advanced Human Computer Interaction (HCI) systems. These new tests are focused on the immersion of the patient in a virtual room, in order to mislead and deceive the patient's mind. In addition, we propose two novel variations of Turing Test proposed by Alan Turing as a method to detect dementia. As a result, four tests are introduced demonstrating the wide range of screening mechanisms that could be designed using virtual environments and game concepts. The proposed tests are focused on the evaluation of memory loss related to common objects, recent conversations and events; the diagnosis of problems in expressing and understanding language; the ability to recognize abnormalities; and to differentiate between virtual worlds and reality, or humans and machines. The proposed screening tests were evaluated and tested using both patients and healthy adults in a comparative study with state-of-the-art Alzheimer's screening tests. The results show the capacity of the new tests to distinguish healthy people from Alzheimer's patients.