High Density Resistive Array Readout System for Wearable Electronics.

This work presents a wearable sensing system for high-density resistive array readout. The system comprising readout electronics for a high-density resistive sensor array and a rechargeable battery, was realized in a wristband. The analyzed data with the proposed system can be visualized using a custom graphical user interface (GUI) developed in a personal computer (PC) through a universal serial bus (USB) and using an Android app in smartphones via Bluetooth Low Energy (BLE), respectively. The readout electronics were implemented on a printed circuit board (PCB) and had a compact dimension of 3 cm × 3 cm. It was designed to measure the resistive sensor with a dynamic range of 1 KΩ-1 MΩ and detect a 0.1% change of the base resistance. The system operated at a 5 V supply voltage, and the overall system power consumption was 95 mW. The readout circuit employed a resistance-to-voltage (R-V) conversion topology using a 16-bit analog-to-digital converter (ADC), integrated in the Cypress Programmable System-on-Chip (PSoC®) 5LP microcontroller. The device behaves as a universal-type sensing system that can be interfaced with a wide variety of resistive sensors, including chemiresistors, piezoresistors, and thermoelectric sensors, whose resistance variations fall in the target measurement range of 1 KΩ-1 MΩ. The system performance was tested with a 60-resistor array and showed a satisfactory accuracy, with a worst-case error rate up to 2.5%. The developed sensing system shows promising results for applications in the field of the Internet of things (IoT), point-of-care testing (PoCT), and low-cost wearable devices.

Quick overview of diagnostic kits and smartphone apps for urologists during the COVID-19 pandemic: a narrative review.

The COVID-19 pandemic was an unprecedented event that has caused incredible challenges in all areas of society. However, unlike previous global pandemics, modern advancements in technology and medicine have made it possible to respond much more rapidly. Within months, countries around the world developed diagnostic kits and smartphone applications to tackle the virus. Many of these diagnostic kits vary in what they target and have different uses. Smartphone applications have been developed to provide real-time information to users regarding potential exposure, statistics, updated news, etc. Depending on the country, resources and government policies have created a wide range of products and applications. This narrative review paper focuses on providing a general overview of diagnostic kits and smartphone applications in three major countries, the U.S., South Korea, and China. Smartphone applications were used for tracing person-to-person contact and preventing the spread of COVID-19. These tools allowed public health officials to quickly identify people who may have had exposure to COVID-19 and allows them to act accordingly. In addition to discussing the mechanisms behind diagnostic kits, topics in legislation and policy for contact tracing will also be discussed. As nations enter into the next phase of the pandemic, there are serious considerations to be made about how technology can be integrated into handling future healthcare crises.

Nanoengineering Approaches Toward Artificial Nose.

Significant scientific efforts have been made to mimic and potentially supersede the mammalian nose using artificial noses based on arrays of individual cross-sensitive gas sensors over the past couple decades. To this end, thousands of research articles have been published regarding the design of gas sensor arrays to function as artificial noses. Nanoengineered materials possessing high surface area for enhanced reaction kinetics and uniquely tunable optical, electronic, and optoelectronic properties have been extensively used as gas sensing materials in single gas sensors and sensor arrays. Therefore, nanoengineered materials address some of the shortcomings in sensitivity and selectivity inherent in microscale and macroscale materials for chemical sensors. In this article, the fundamental gas sensing mechanisms are briefly reviewed for each material class and sensing modality (electrical, optical, optoelectronic), followed by a survey and review of the various strategies for engineering or functionalizing these nanomaterials to improve their gas sensing selectivity, sensitivity and other measures of gas sensing performance. Specifically, one major focus of this review is on nanoscale materials and nanoengineering approaches for semiconducting metal oxides, transition metal dichalcogenides, carbonaceous nanomaterials, conducting polymers, and others as used in single gas sensors or sensor arrays for electrical sensing modality. Additionally, this review discusses the various nano-enabled techniques and materials of optical gas detection modality, including photonic crystals, surface plasmonic sensing, and nanoscale waveguides. Strategies for improving or tuning the sensitivity and selectivity of materials toward different gases are given priority due to the importance of having cross-sensitivity and selectivity toward various analytes in designing an effective artificial nose. Furthermore, optoelectrical sensing, which has to date not served as a common sensing modality, is also reviewed to highlight potential research directions. We close with some perspective on the future development of artificial noses which utilize optical and electrical sensing modalities, with additional focus on the less researched optoelectronic sensing modality.

Challenges in Urology during the COVID-19 Pandemic.

The COVID-19 pandemic has caused a global health threat. This disease has brought about huge changes in the priorities of medical and surgical procedures. This short review article summarizes several test methods for COVID-19 that are currently being used or under development. This paper also introduces the corresponding changes in the diagnosis and treatment of urological diseases during the COVID-19 pandemic. We further discuss the potential impacts of the pandemic on urology, including the outpatient setting, clinical work, teaching, and research.

Biomarker discovery and beyond for diagnosis of bladder diseases.

Molecular biosignatures of altered cellular landscapes and functions have been casually linked with pathological conditions, which imply the promise of biomarkers specific to bladder diseases, such as bladder cancer and other dysfunctions. Urinary biomarkers are particularly attractive due to costs, time, and the minimal and noninvasive efforts acquiring urine. The evolution of omics platforms and bioinformatics for analyzing the genome, epigenome, transcriptome, proteome, lipidome, metabolome, etc., have enabled us to develop more sensitive and disease-specific biomarkers. These discoveries broaden our understanding of the complex biology and pathophysiology of bladder diseases, which can ultimately be translated into the clinical setting. In this short review, we will discuss current efforts on identification of promising urinary biomarkers of bladder diseases and their roles in diagnosis and monitoring. With these considerations, we also aim to provide a prospective view of how we can further utilize these bladder biomarkers in developing ideal and smart medical devices that would be applied in the clinic.

Classification of the urinary metabolome using machine learning and potential applications to diagnosing interstitial cystitis.

With the advent of artificial intelligence (AI) in biostatistical analysis and modeling, machine learning can potentially be applied into developing diagnostic models for interstitial cystitis (IC). In the current clinical setting, urologists are dependent on cystoscopy and questionnaire-based decisions to diagnose IC. This is a result of a lack of objective diagnostic molecular biomarkers. The purpose of this study was to develop a machine learning-based method for diagnosing IC and assess its performance using metabolomics profiles obtained from a prior study. To develop the machine learning algorithm, two classification methods, support vector machine (SVM) and logistic regression (LR), set at various parameters, were applied to 43 IC patients and 16 healthy controls. There were 3 measures used in this study, accuracy, precision (positive predictive value), and recall (sensitivity). Individual precision and recall (PR) curves were drafted. Since the sample size was relatively small, complicated deep learning could not be done. We achieved a 76%-86% accuracy with leave-one-out cross validation depending on the method and parameters set. The highest accuracy achieved was 86.4% using SVM with a polynomial kernel degree set to 5, but a larger area under the curve (AUC) from the PR curve was achieved using LR with a l 1-norm regularizer. The AUC was greater than 0.9 in its ability to discriminate IC patients from controls, suggesting that the algorithm works well in identifying IC, even when there is a class distribution imbalance between the IC and control samples. This finding provides further insight into utilizing previously identified urinary metabolic biomarkers in developing machine learning algorithms that can be applied in the clinical setting.

Automated genome-wide visual profiling of cellular proteins involved in HIV infection.

Recent genome-wide RNAi screens have identified >842 human genes that affect the human immunodeficiency virus (HIV) cycle. The list of genes implicated in infection differs between screens, and there is minimal overlap. A reason for this variance is the interdependence of HIV infection and host cell function, producing a multitude of indirect or pleiotropic cellular effects affecting the viral infection during RNAi screening. To overcome this, the authors devised a 15-dimensional phenotypic profile to define the viral infection block induced by CD4 silencing in HeLa cells. They demonstrate that this phenotypic profile excludes nonspecific, RNAi-based side effects and viral replication defects mediated by silencing of housekeeping genes. To achieve statistical robustness, the authors used automatically annotated RNAi arrays for seven independent genome-wide RNAi screens. This identified 56 host genes, which reliably reproduced CD4-like phenotypes upon HIV infection. The factors include 11 known HIV interactors and 45 factors previously not associated with HIV infection. As proof of concept, the authors confirmed that silencing of PAK1, Ku70, and RNAseH2A impaired HIV replication in Jurkat cells. In summary, multidimensional, visual profiling can identify genes required for HIV infection.

Hidden Markov model-based weighted likelihood discriminant for 2-D shape classification.

The goal of this paper is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional maximum likelihood (ML) methods, in which classification is based on probabilities from independent individual class models as is the case for general hidden Markov model (HMM) methods, proposed method utilizes information from all classes to minimize classification error. The proposed approach uses a HMM for shape curvature as its 2-D shape descriptor. We introduce a weighted likelihood discriminant function and present a minimum classification error strategy based on generalized probabilistic descent method. We show comparative results obtained with our approach and classic ML classification with various HMM topologies alongside Fourier descriptor and Zernike moments-based support vector machine classification for a variety of shapes.

High-content classification of nucleocytoplasmic import or export inhibitors.

Transcription factors of the nuclear factor kappa B family are the paradigm for signaling dependent nuclear translocation and are ideally suited to analysis through image-based chemical genetic screening. The authors describe combining high-content image analysis with a compound screen to identify compounds affecting either nuclear import or export. Validation in silico and in vitro determined an EC(50) for the nuclear export blocker leptomycin B of 2.4 ng/mL (4.4 nM). The method demonstrated high selectivity (Z' >0.95), speed, and robustness in a screen of a compound collection. It identified the IkappaB protein kinase inhibitor BAY 11 7082 as an import inhibitor, the p38 mitogen-activated protein (MAP) kinase inhibitor PD98509 as an import enhancer, and phorbol ester as an export inhibitor. The results establish a robust method for identifying compounds regulating nucleocytoplasmic import or export and also implicate MAP kinases in nuclear import of nuclear factor kappa B.

Improved analysis on the viewing angle of integral imaging.

There have already been several analyses about the viewing angle of integral imaging (InIm). However, they can be applied only under the assumption that the original image is merely a single point source and are not suitable for application to an actual condition. We propose an improved analysis based on the actual InIm image, not on a single point source. It is possible to analyze and predict the viewing angle of an InIm system with good accuracy with the new analytic method because almost all the parameters of the InIm system such as the size and focal length of the lens array, image distance, the size and resolution of the image, and the location of the observers are included in this analysis.

Wide-viewing-angle integral three-dimensional imaging system by curving a screen and a lens array.

A wide-viewing-angle integral three-dimensional imaging system made by curving a screen and a lens array is described. A flexible screen and a curved lens array are incorporated into an integral imaging system in place of a conventional flat display panel and a flat lens array. One can effectively eliminate flipped images by adopting barriers. As a result, the implemented system permits the limitation of viewing angle to be overcome and the viewing angle to be expanded remarkably. Using the proposed method, we were able to achieve a viewing angle of 33 degrees (one side) for real integral imaging and 40 degrees (one side) for virtual integral imaging, which is four times wider than that of the currently used conventional techniques. The principle of the implemented system is explained, and some experimental results are presented.

Depth extraction by use of a rectangular lens array and one-dimensional elemental image modification.

Stereo matching, a technique for acquiring depth information from many planar images obtained by several cameras, was developed several decades ago. Recently a novel depth-extraction technique that uses a lens array instead of several cameras has attracted much attention because of the advantages offered by its compact system configuration. We present a novel depth-extraction method that uses a lens array consisting of vertically long rectangular lens elements. The proposed method rearranges the horizontal positions of the pixels from the collection of perspective images while it leaves the vertical positions of the pixels unchanged. To these rearranged images we apply a correlation-based multibaseline stereo algorithm in properly modified form. The main feature of the proposed method is the inverse dependency of the disparity in depth between horizontal and vertical directions. This inverse dependency permits the extraction of exact depth from extremely periodically patterned object scenes and reduces quantization error in the depth extraction.

Depth-enhanced integral imaging by use of optical path control.

The image depth of integral imaging is enhanced by doubling the number of central depth planes by use of optical path control. To accomplish this, the optical path lengths are changed by controlling whether reflections occur behind the lens array. We propose three schemes that use mirrors, a combination of beam splitters and polarizers, and polarization beam splitters, respectively. In experiments we implement the systems that are completely electronically controllable, are compact, and provide two central depth planes with 50.4-mm separation.

Viewing-angle-enhanced integral imaging system using a curved lens array.

We propose an enhanced three-dimensional integral imaging system using a curved lens array. Incorporation of a curved lens array instead of a conventional flat lens array expands the viewing angle remarkably. The flipped images are eliminated effectively by adopting barriers. The principle of the proposed system is explained and the experimental results are also presented.

Wide-viewing integral three-dimensional imaging by use of orthogonal polarization switching.

A wide-viewing integral three-dimesional (3D) imaging system that adopts orthogonal polarization switching is proposed and demonstrated. In our scheme,the polarizing sheet attached to the lens array and the orthogonal polarization switching of the elemental image array perform elemental lens switching. The experimental results document that the viewing angle becomes remarkably wider than that of the conventional method. The distinguishing feature of our system is that it requires no mechanical moving part. In addition, because a commercially available polarization shutter screen is used for electrical switching, it is easy to implement this as a practical system. We believe that the proposed method facilitates the practical use of this wide-viewing integral 3D imaging system.

Multiple-viewing-zone integral imaging using a dynamic barrier array for three-dimensional displays.

In spite of many advantages of integral imaging, the viewing zone in which an observer can see three-dimensional images is limited within a narrow range. Here, we propose a novel method to increase the number of viewing zones by using a dynamic barrier array. We prove our idea by fabricating and locating the dynamic barrier array between a lens array and a display panel. By tilting the barrier array, it is possible to distribute images for each viewing zone. Thus, the number of viewing zones can be increased with an increment of the states of the barrier array tilt.

Viewing-angle-enhanced integral three-dimensional imaging along all directions without mechanical movement.

Integral three-dimensional (3D) imaging provides full-motion parallax, unlike other conventional stereoscopy-based techniques. To maximize this advantage, a 3D system with a wide view along all directions is required. We propose and demonstrate a new integral imaging (InIm) method to enhance the viewing angle along both horizontal and vertical directions. Elemental lens switching is performed by a combination of spatial and time multiplexing by use of double display devices and orthogonal polarizations. Experimental results show that the viewing angle of the system is enhanced along all directions without any mechanical movement or any cross talk between afterimages. We believe that the proposed method has the potential to facilitate practical use of the wideviewing InIm system.

Integral imaging with multiple image planes using a uniaxial crystal plate.

Integral imaging has been attracting much attention recently for its several advantages such as full parallax, continuous view-points, and real-time full-color operation. However, the thickness of the displayed three-dimensional image is limited to relatively small value due to the degradation of the image resolution. In this paper, we propose a method to provide observers with enhanced perception of the depth without severe resolution degradation by the use of the birefringence of a uniaxial crystal plate. The proposed integral imaging system can display images integrated around three central depth planes by dynamically altering the polarization and controlling both elemental images and dynamic slit array mask accordingly. We explain the principle of the proposed method and verify it experimentally.

Viewing-angle-enhanced integral imaging by elemental image resizing and elemental lens switching.

Integral imaging (II) is one of the promising techniques in the field of autostereoscopic three-dimensional display. Despite of its many advantages, the narrow viewing angle has been a drawback. We propose a technique that enhances the viewing angle of II by resizing the elemental images taken by the pickup process and switching the elemental lenses in the display process. We explain the principle of the proposed technique, analyze the effect on the resolution of the integrated image, and show the experimental results.