We report the detection of tryptophan at sub-ppb levels for a fluorometer based on Fresnel lenses and low-cost electronics. These fluorometers can be used to detect fecal contamination in drinking water, indicated by tryptophan-like fluorescence.
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A low-cost sensornode is introduced to monitor the 5G EMF exposure in the Netherlands for the four FR1 frequency bands. The sensornode is validated with in-lab measurements both with CW signals as for QAM signals and perform for both cases and for all frequency bands an error less than 1 dB for a dynamic range of 40 dB. This sensor is a follow up of the earlier version of our previously developed sensor and have substantial improvements in terms of linearity, error, and stability.
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Spectral imaging has many applications, from methane detection using satellites to disease detection on crops. However, spectral cameras remain a costly solution ranging from 10 thousand to 100 thousand euros for the hardware alone. Here, we present a low-cost multispectral camera (LC-MSC) with 64 LEDs in eight different colors and a monochrome camera with a hardware cost of 340 euros. Our prototype reproduces spectra accurately when compared to a reference spectrometer to within the spectral width of the LEDs used and the ±1σ variation over the surface of ceramic reference tiles. The mean absolute difference in reflectance is an overestimate of 0.03 for the LC-MSC as compared to a spectrometer, due to the spectral shape of the tiles. In environmental light levels of 0.5 W m−2 (bright artificial indoor lighting) our approach shows an increase in noise, but still faithfully reproduces discrete reflectance spectra over 400 nm–1000 nm. Our approach is limited in its application by LED bandwidth and availability of specific LED wavelengths. However, unlike with conventional spectral cameras, the pixel pitch of the camera itself is not limited, providing higher image resolution than typical high-end multi- and hyperspectral cameras. For sample conditions where LED illumination bands provide suitable spectral information, our LC-MSC is an interesting low-cost alternative approach to spectral imaging.
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We aim to set up a continuous low cost monitoring system for electromagnetic fields in the Netherlands, so that a trend in exposure to 5G signals can be observed. A number of options will be explored for this, such as software-defined radio and measurement nodes for specific 5G frequencies. We developed and tested low cost dedicated measurement nodes for four 5G bands: the 800, 1400, 2100 and 3500 MHz bands. Generally, the error is less than 1 dB and close to dynamic range limits (-65 to 5 dBm) the error increases to 3 dB.
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Inkjet printing is a rapidly growing technology for depositing functional materials in the production of organic electronics. Challenges lie among others in the printing of high resolution patterns with high aspect ratio of functional materials to obtain the needed functionality like e.g. conductivity. μPlasma printing is a technology which combines atmospheric plasma treatment with the versatility of digital on demand printing technology to selectively change the wetting behaviour of materials. In earlier research it was shown that with μPlasma printing it is possible to selectively improve the wetting behaviour of functional inks on polymer substrates using atmospheric air plasma. In this investigation we show it is possible to selectively change the substrate wetting behaviour using combinations of different plasmas and patterned printing. For air and nitrogen plasmas, increased wetting of printed materials could be achieved on both polycarbonate and glass substrates. A minimal track width of 320 μm for a 200 μm wide plasma needle was achieved. A combination of N2 with HMDSO plasma increases the contact angle for water up from <100 to 1050 and from 320 to 460 for DEGDMA making the substrate more hydrophobic. Furthermore using N2-plasma in combination with a N2/HMDSO plasma, hydrophobic tracks could be printed with similar minimal track width. Combining both N2 -plasma and N2/HMDSO plasma treatments show promising results to further decrease the track width to even smaller values.
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In this article we investigate the change in wetting behavior of inkjet printed materials on either hydrophilic or hydrophobic plasma treated patterns, to determine the minimum obtainable track width using selective patterned μPlasma printing. For Hexamethyl-Disiloxane (HMDSO)/N2 plasma, a decrease in surface energy of approx. 44 mN/m was measured. This resulted in a change in contact angle for water from <10 up to 105 degrees, and from 32 up to 46 degrees for Diethyleneglycol-Dimethaclylate (DEGDMA). For both the nitrogen, air and HMDSO/N2 plasma single pixel wide track widths of approx. 320 μm were measured at a plasma print height of 50 μm. Combining hydrophilic pretreatment of the glass substrate, by UV/Ozone or air μPlasma printing, with hydrophobic HMDSO/N2 plasma, the smallest hydrophilic area found was in the order of 300 μm as well.
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Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.
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Augmented Reality (AR) is increasingly explored as a low-burden alternative to pencil-and-paper cognitive tests for dementia and Parkinson’s Disease. Our objective with this review is to synthesize ten years (2014-2024) of empirical evidence on AR-based cognitive screening, estimate pooled diagnostic accuracy, and distil user-experience (UX) guidelines for people with neurodegenerative disorders. We searched Scopus with the string “aug-mented reality” AND cognitive AND (dementia OR Parkinson), screened 399 records, and retained 38 primary studies. Two reviewers independently extracted sample, task, hardware, and accuracy metrics. Optical see-through AR improved test sensitivity over matched non-immersive tests, while projection-based AR offered the largest UX gains. Hardware cost and eye-tracker drift were the main precision bottlenecks. AR can raise both diagnostic sensitivity and patient engagement, but only four studies used clinical-stage participants. Future work should couple low-cost hand-held AR with cloud inference to widen accessibility.
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Greenhouses are in need of new monitoring tools, as they size grow bigger and bigger but still using old labour intensive methods ways of caring for the crop. HiPerGreen is set out to create a new tool, which can drive onto the pre-existing heating pipes to provide a birds eye perspective for image analysis purposes. However, clear images are necessary for consistent usable data. This presentation resumes the steps taken during the reporting: the optimisation of a rail based system towards clear images. This is done through analysis of resulting images, understanding vibrations and oscillations, and finally presents results based on prototyping. Moreover, a re-design of the electronics and hardware was also introduce to facilitate prototyping. The results are promising, laying within the requirements.
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