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Nowadays, in situ analysis attracts the interests and becomes one of the main purposes in analytical chemistry. Design of portable analysis devices facilitates reaching this goal. An ideal analysis system contains different parts enabling extraction, detection and quantification of target analytes. Preparation of a portable quantification approach is a bottle neck in such system creation. Common lab analysis instruments do not have the transportation ability and using these facilities limits the complete in situ analysis. Smartphones are the modern life phenomena and their usage becomes more widespread, every day. Their abilities and features are also swiftly developed. There are several strategies making the smartphone a suitable quantifier. This paper provides an overview of the currently applications of smartphones in analytical chemistry. Different applications of smartphones including optical detection (colorimetric, fluorescence, chemiluminescence, bioluminescence, and photoluminescence detections, pixelation as well as label-free detection), electrochemical detection, barcode reading, chemometric applications and smartphone imaging with fluorescence microscopy were classified and advantages and disadvantages of each approach were investigated. This modern common item could be a new part of analytical chemistry.

Artificial Intelligence (A.I.) solutions are increasingly considered for telemedicine. For these methods to adapt to the field of behavioral pediatrics, serving children and their families in home settings, it will be crucial to ensure the privacy of the child and parent subjects in the videos. To address this challenge in A.I. for healthcare, we explore the potential for global image transformations to provide privacy while preserving behavioral annotation quality. Crowd workers have previously been shown to reliably annotate behavioral features in unstructured home videos, allowing machine learning classifiers to detect autism using the annotations as input. We evaluate this method with videos altered via pixelation, dense optical flow, and Gaussian blurring. On a balanced test set of 30 videos of children with autism and 30 neurotypical controls, we find that the visual privacy alterations do not drastically alter any individual behavioral annotation at the item level. The AUROC on the evaluation set was 90.0% +/- 7.5% for the unaltered condition, 85.0% +/- 9.0% for pixelation, 85.0% +/- 9.0% for optical flow, and 83.3% +/- 9.3% for blurring, demonstrating that an aggregation of small changes across multiple behavioral questions can collectively result in increased misdiagnosis rates. We also compare crowd answers against clinicians who provided the same annotations on the same videos and find that clinicians are more sensitive to autism-related symptoms. We also find that there is a linear correlation (r=0.75, p

In lithography using spatial light modulators, the irradiance is influenced by diffraction effects. The intensity distribution under diffraction effects due to binary reflections is investigated. Dynamic sub-pixelation, a method of dividing an image pixel reflected off a single micromirror into equal-sized sub-pixels on a translating substrate by the superposition of an array of image pixels, is proposed to enhance image resolution. The influence of dynamic sub-pixelation on exposure intensity distribution under diffraction effects is analyzed. The potential of utilizing dynamic sub-pixelation for suppressing diffraction effects and further enhancing image resolution while maintaining throughput is demonstrated through simulations and experiments.

We study how to build optimal light-field or plenoptic models. We quantify geometric errors in light-field representations and show how geometric error bounds directly affect rendering artifacts. Artifacts depend on how the light-field is parameterized, stored, reconstructed and rendered. We present the rendering artifacts and relate them to the presence of geometric errors in the four most common light-field implementations. We show how to optimize a light-field model. We take an arbitrary bounded object and construct the best possible representation using each of the four parameterizations. The best representation has the least geometric error bounds. We use two geometric errors, a positional and a directional error. We also quantify pixelation artifacts. Our analysis is useful to decide how to build a light-field model. It helps select a parameterization, build an optimal representation, and choose the samplings of the parameter spaces so that geometric errors and rendering artifacts are minimized.

We propose and experimentally demonstrate a novel concept to spatially resolve the chemical composition of complex biological samples by pixelation within a micro total analysis system (μTAS) platform. The device we developed images samples of interest by discretising targeted areas into droplets suspended in a two-phase microflow. These droplets are transferred from parallel to serial mode for data readout in a similar fashion to a CCD camera, thus referred as “microfluidic imaging”. Three major process steps are conducted within the device: (i) parallel pixelation and uptake of the sample (ii) sample transfer from parallel to serial mode into a microchannel for individual analysis and (iii) image generation. This microfluidic pixelation method is a technique suitable for obtaining non-averaged data from heterogeneous specimen. The concept attempts to reduce arduous preparation steps, allowing high throughput while retaining the spatial information.

We proposed the direct deposition of CsI(Tl) scintillator layer with pixelated structure on a CMOS image sensor (CIS) in order to improve the spatial resolution. CMOS sensors developed for test have a 128×128 photodiode array with 50 μm pixel pitch and integrated readout-electronics including a 10 bit pipe-lined ADC. CsI(Tl) layer has thickness of 50 μm. The modulation transfer function, the noise power spectrum, and the detective quantum efficiency of pixelated and non-pixelated CsI(Tl) X-ray image sensors (XIS) were estimated with a 50 kVp X-ray beam. At 10% of modulation transfer function (MTF), the spatial resolution of pixelated and non-pixleated XIS are about 8 and 6 lp/mm, respectively. It implies that pixelation enhances the spatial resolution by reducing the lateral light diffusion. Though the NPS of pixelated XIS was slightly higher than the non-pixelated XIS, its detective quantum efficiency (DQE) values were much better than non-pixelated XIS especially at high spatial frequencies.

An X-ray imaging detector consisting of a silicon charge coupled device (CCD) and pixel structured scintillator was developed to improve spatial resolution. The pixelated structure reduces spreading of scintillation light through the scintillator by providing air gap between scintillator pixels, and increased spatial resolution by reducing the cross-talk between CCD pixels. The modulation transfer functions (MTF) of the non-pixelated and pixilated scintillator detector were compared. The improvement in spatial resolution was evaluated by both computational simulation and experimental measurement of MTF; both results showed coincidence.

We report a new scintillator based on a transparent ceramic of Lu 2 O 3 :Eu. The material has an extremely high density of 9.4 g/cm 3 , a light output comparable to CsI:Tl, and a narrow band emission at 610 nm that falls close to the maximum of the response curve of CCDs. Pixelation of the scintillator to prevent lateral spread of light enhances the spatial and contrast resolution, providing imaging performance that equals or surpasses all other currently known scintillators. Upon further development of readout technologies to take full advantage of its transparency, the new scintillator should play a major role in digital radiographic systems.

Consider digitising a binary pattern on a regular lattice, so that each “face” or pixel of the lattice is given just one of the two colours in the pattern. If the pixelation algorithm is symmetric, meaning that a pixel which straddles the boundary between two colours inherits the colour that predominates in that particular face, then the systematic errors in pixel counts are generally small. However, they can be significant for asymmetric pixelations. In this paper we provide explicit corrections for systematic errors in area estimates based on asymmetric pixelation algorithms. The corrections are derived by interpreting systematic error as the bias in a statistical estimation problem, and arguing that the pattern was placed into the lattice in a stochastically uniform way. We suggest two sorts of correction: first, a “local” adjustment based on tracking the boundary and accumulating small amendments along the way; and secondly, a “global” correction based on parametric knowledge of the type of shape that is being digitised.

We developed an X-ray imaging detector consisting of a silicon charge coupled device and pixel structured CsI(Tl) scintillator in previous research. Scintillator pixelation for minimizing the spread of scintillation light enhanced spatial resolution. In this study, we investigated the effect of pixel size on spatial resolution using DETECT97 simulation and obtained the measured modulation transfer functions (MTFs) of pixelated CsI(Tl) scintillators. The size of a pixel is controlled by the pattern on glass substrate in the fabricating process.