Vergence-Accommodation Conflict: Increased Presbyopia in Virtual Reality.

Background: Performance and symptoms in completing a visual search task on a PC monitor and using a head-mounted display (HMD) were compared for different viewing conditions and between users of different ages.

Patients And Methods: Twenty-three young (M = 30 y, SD = 7 y) and 23 older (M = 52 y, SD = 5 y) participants performed a visual search task presented on a PC monitor. The task was repeated using an HMD for a near and a far virtual viewing distance.

Graph Spatio-Temporal Networks for Manufacturing Sales Forecast and Prevention Policies in Pandemic Era.

Worldwide manufacturing industries are significantly affected by COVID-19 pandemic because of their production characteristics with low-cost country sourcing, globalization, and inventory level. To analyze the correlated time series, spatial-temporal model becomes more attractive, and the graph convolution network (GCN) is also commonly used to provide more information to the nodes and its neighbors in the graph. Recently, attention-adjusted graph spatio-temporal network (AGSTN) was proposed to address the problem of pre-defined graph in GCN by combining multi-graph convolution and attention adjustment to learn spatial and temporal correlations over time.

Positioning System of Infrared Sensors Based on ZnO Thin Film.

Infrared sensors incorporating suspended zinc oxide (ZnO) pyroelectric films and thermally insulated silicon substrates are fabricated using conventional MEMS-based thin-film deposition, photolithography, and etching techniques. The responsivity of the pyroelectric film is improved via annealing at 500 °C for 4 h. The voltage response of the fabricated sensors is evaluated experimentally for a substrate thickness of 1 µm over a sensing range of 30 cm.

Image registration method using representative feature detection and iterative coherent spatial mapping for infrared medical images with flat regions.

In the registration of medical images, nonrigid registration targets, images with large displacement caused by different postures of the human body, and frequent variations in image intensity due to physiological phenomena are substantial problems that make medical images less suitable for intensity-based image registration modes. These problems also greatly increase the difficulty and complexity of feature detection and matching for feature-based image registration modes. This research introduces an automatic image registration algorithm for infrared medical images that offers the following benefits: effective detection of feature points in flat regions (cold patterns) that appear due to changes in the human body's thermal patterns, improved mismatch removal through coherent spatial mapping for improved feature point matching, and large-displacement optical flow for optimal transformation.

Effect of synthesis time on plasmonic properties of Ag dendritic nanoforests.

The effects of synthesis time on the plasmonic properties of Ag dendritic nanoforests on Si substrate (Ag-DNF/Si) samples synthesized through the fluoride-assisted galvanic replacement reaction were investigated. The Ag-DNF/Si samples were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, reflection spectroscopy, X-ray diffraction and surface-enhanced Raman spectroscopy (SERS). The prolonged reaction time led to the growth of an Ag-DNF layer and etched Si hole array.

ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images.

Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss caused by this disease is irreversible and permanent. Color fundus photography is the most cost-effective imaging modality to screen for retinal disorders.

Automated segmentation of normal and diseased coronary arteries - The ASOCA challenge.

Cardiovascular disease is a major cause of death worldwide. Computed Tomography Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery disease, as well as evaluating and reconstructing heart and coronary vessel structures. Reconstructed models have a wide array of for educational, training and research applications such as the study of diseased and non-diseased coronary anatomy, machine learning based disease risk prediction and in-silico and in-vitro testing of medical devices.

Added Value of Computed Tomography Virtual Intravascular Endoscopy in the Evaluation of Coronary Arteries with Stents or Plaques.

Coronary computed tomography angiography (CCTA) is a widely used imaging modality for diagnosing coronary artery disease (CAD) but is limited by a high false positive rate when evaluating coronary arteries with stents and heavy calcifications. Virtual intravascular endoscopy (VIE) images generated from CCTA can be used to qualitatively assess the vascular lumen and might be helpful for overcoming this challenge. In this study, one hundred subjects with coronary stents underwent both CCTA and invasive coronary angiography (ICA).

Design and Application of MEMS-Based Hall Sensor Array for Magnetic Field Mapping.

A magnetic field measurement system based on an array of Hall sensors is proposed. The sensors are fabricated using conventional microelectromechanical systems (MEMS) techniques and consist of a P-type silicon substrate, a silicon dioxide isolation layer, a phosphide-doped cross-shaped detection zone, and gold signal leads. When placed within a magnetic field, the interaction between the local magnetic field produced by the working current and the external magnetic field generates a measurable Hall voltage from which the strength of the external magnetic field is then derived.

Risk of dementia in patients with periodontitis and related protective factors: A nationwide retrospective cohort study.

Aim: We aimed to evaluate the long-term risk of dementia in patients with periodontitis and its associated factors.

Materials And Methods: Using Taiwan's National Health Insurance Database, we identified 56,018 patients aged ≥50 years with newly diagnosed periodontitis in 2000-2008. A cohort of 56,018 adults without periodontitis was selected for comparison, with matching by age and sex.

SNP Data Science for Classification of Bipolar Disorder I and Bipolar Disorder II.

Bipolar disorder I (BD-I) and bipolar disorder II (BD-II) have specific characteristics and clear diagnostic criteria, but quite different treatment guidelines. In clinical practice, BD-II is commonly mistaken as a mild form of BD-I. This study uses data science technique to identify the important Single Nucleotide Polymorphisms (SNPs) significantly affecting the classifications of BD-I and BD-II, and develops a set of complementary diagnostic classifiers to enhance the diagnostic process.

Fully automated lesion segmentation and visualization in automated whole breast ultrasound (ABUS) images.

Background: The number of breast cancer patients has increased each year, and the demand for breast cancer detection has become quite large. There are many common breast cancer diagnostic tools. The latest automated whole breast ultrasound (ABUS) technology can obtain a complete breast tissue structure, which improves breast cancer detection technology.

Data Science for Extubation Prediction and Value of Information in Surgical Intensive Care Unit.

Besides the traditional indices such as biochemistry, arterial blood gas, rapid shallow breathing index (RSBI), acute physiology and chronic health evaluation (APACHE) II score, this study suggests a data science framework for extubation prediction in the surgical intensive care unit (SICU) and investigates the value of the information our prediction model provides. A data science framework including variable selection (e.g.

Decentralized allocation of emission permits by Nash data envelopment analysis in the coal-fired power market.

Allocation of emission permits (AEP) provides valuable guidelines to support environmental regulatory policies for pollutant emission, in particular, CO as the key contributors to climate change. Most of previous studies in literature developed the centralized AEP model and focused on the coal-fired power market, one of the main sources of air pollution. However, the power market is usually imperfectly competitive and some of them are gradually deregulated, this justifies the motivation of developing a decentralized AEP model.

Automated drosophila heartbeat counting based on image segmentation technique on optical coherence tomography.

Drosophila and human cardiac genes are very similar. Biological parametric studies on drosophila cardiac have improved our understanding of human cardiovascular disease. Drosophila cardiac consist of five circular chambers: a conical chamber (CC) and four ostia sections (O1-O4).

Cross-section and feasibility study on the non-invasive evaluation of muscle hemodynamic responses in Duchenne muscular dystrophy by using a near-infrared diffuse optical technique.

Duchenne muscular dystrophy (DMD) is an X-linked debilitating muscular disease that may decrease nitric oxide (NO) production and lead to functional muscular ischemia. Currently, the 6-minute walk test (6-MWT) and the North Star Ambulatory Assessment (NSAA) are the primary outcome measures in clinical trials, but they are severely limited by the subjective consciousness and mood of patients, and can only be used in older and ambulatory boys. This study proposed using functional near-infrared spectroscopy (fNIRS) to evaluate the dynamic changes in muscle hemodynamic responses (gastrocnemius and forearm muscle) during a 6-MWT and a venous occlusion test (VOT), respectively.

Well-aligned Vertically Oriented ZnO Nanorod Arrays and their Application in Inverted Small Molecule Solar Cells.

This manuscript describes how to design and fabricate efficient inverted solar cells, which are based on a two-dimensional conjugated small molecule (SMPV1) and [6,6]-phenyl-C71-butyric acid methyl ester (PC71BM), by utilizing ZnO nanorods (NRs) grown on a high quality Al-doped ZnO (AZO) seed layer. The inverted SMPV1:PC71BM solar cells with ZnO NRs that grew on both a sputtered and sol-gel processed AZO seed layer are fabricated. Compared with the AZO thin film prepared by the sol-gel method, the sputtered AZO thin film exhibits better crystallization and lower surface roughness, according to X-ray diffraction (XRD) and atomic force microscope (AFM) measurements.

An automated skin segmentation of Breasts in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to diagnose breast disease. Obtaining anatomical information from DCE-MRI requires the skin be manually removed so that blood vessels and tumors can be clearly observed by physicians and radiologists; this requires considerable manpower and time. We develop an automated skin segmentation algorithm where the surface skin is removed rapidly and correctly.

A feasibility study on non-invasive oxidative metabolism detection and acoustic assessment of human vocal cords by using optical technique.

Voice disorder such as vocal fatigue is a common and complex multifaceted clinical problem that presents a significant impact on quality of life. In this study, the functional near-infrared diffuse optical technique (fNIRS-DOT) was proposed as a novel approach for human vocal cords oxidative metabolism detection and acoustic assessment simultaneously to provide a multidimensional assessment of voice disorder. A totally of 60 healthy subjects included 30 male and 30 female adults of age-matched were recruited and performed a vocal loading task to trigger a mild inflammation of the vocal cords in this study.

Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding.

Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model.

Diffuser-aided time-domain diffuse optical imaging: a phantom study.

We present the first experimental results of time-resolved diffuser-aided diffuse optical imaging (DADOI) method in this paper. A self-manufactured diffuser plate was inserted between the optode and the surface of a scattering medium. The diffuser was utilized to enhance the multiple scattering that destroys the image information for baseline measurement of turbid medium.