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Traffic accident prediction based on dashboard cameras is of great significance for ensuring the guaranteed-safety of self-driving systems and reducing the occurrence of accidents. Due to complexity of traffic scenarios and wide range of object's motion, early prediction of accidents remains a challenge. However, the existing methods process all traffic objects and all video frames indiscriminately, thus leading to poor prediction performance. To address this issue, we propose a novel traffic accident prediction framework, namely two-layer hidden state aggregation based two-stream network (THAT-Net). The proposed method first fuses the spatial and temporal flow to capture complementary spatio-temporal information, which filters out irrelevant objects in traffic scenes to reduce the influence of the object's motion state. Furthermore, a two-layer hidden state aggregation structure is designed to reintegrate the hidden state weights of gated recurrent units. It captures contextual information through frame-level and segment-level aggregation and decreases the influence of irrelevant frames to reduce the complexity of traffic scenes. Experiments based on two real-world datasets show the state-of-the-art performance of THAT-Net. Our proposed method achieves the highest accuracy by predicting accidents 0.48 sec to 2.8 sec earlier compared to the baseline methods in more challenging situations. Our code is available at: https://github.com/redeyezt/THAT-Net. • We propose a novel traffic accident prediction framework named THAT-Net. • We introduce the optical flow information of the video to reduce the influence of irrelevant objects on accident prediction. • We use a CTA module to reduce the impact of irrelevant frames in videos on traffic accident prediction. • Compared with other accident prediction models, THAT-Net can forecast accidents earlier and with greater precision. [ABSTRACT FROM AUTHOR]

DLSS (Deep Learning Super Sampling) is a technology that upscales game graphics in real time, improving visual quality and increasing frame rates. It has evolved significantly since its introduction in 2019, with DLSS 2.0 being a major breakthrough that improved image quality and provided more control over its application. DLSS 3.0 and 3.5 introduced features like optical flow interpolation and denoising for ray-traced images, further enhancing performance and fidelity. DLSS demonstrates the potential of AI in graphics processing, with AI already being used to optimize new graphics cards. While AI won't replace graphics cards, it has changed their design and purpose, making them part of a pipeline that relies on offline rendering for detailed frames. [Extracted from the article]

DLSS 3's new feature is just the latest in a string of technologies which Nvidia has created with the potential to become an industry standard, just like Variable Refresh Rates (G-sync), temporal upsampling (DLSS) and low input latency (Reflex). DLSS 2 - a recap If you're a high-end PC gamer, chances are you're already familiar with Nvidia's DLSS 2 technology. Unfortunately, if you're the existing owner of an RTX 2000 or 3000 GPU, both cards which also feature Optical Flow Accelerators, don't get too excited though, as DLSS 3's Frame Generation is locked to the RTX 4000's Ada Lovelace architecture. DLSS 3 includes DLSS Super Resolution which helps boost the input frame rate (including the main game loop) for DLSS Frame Generation by up to 2x. [Extracted from the article]

Group activity recognition (GAR) aiming at understanding the behavior of a group of people in a video clip has received increasing attention recently. Nevertheless, most of the existing solutions ignore that not all the persons contribute to the group activity of the scene equally. That is to say, the contribution from different individual behaviors to group activity is different; meanwhile, the contribution from people with different spatial positions is also different. To this end, we propose a novel Position-aware Participation-Contributed Temporal Dynamic Model (P2CTDM), in which two types of the key actor are constructed and learned. Specifically, we focus on the behaviors of key actors, who maintain steady motions (long moving time, called long motions) or display remarkable motions (but closely related to other people and the group activity, called flash motions) at a certain moment. For capturing long motions, we rank individual motions according to their intensity measured by stacking optical flows. For capturing flash motions that are closely related to other people, we design a position-aware interaction module (PIM) that simultaneously considers the feature similarity and position information. Beyond that, for capturing flash motions that are highly related to the group activity, we also present an aggregation long short-term memory (Agg-LSTM) to fuse the outputs from PIM by time-varying trainable attention factors. Four widely used benchmarks are adopted to evaluate the performance of the proposed P2CTDM compared to the state of the art. [ABSTRACT FROM AUTHOR]

Nvidia's 40-series flagship chews through futuristic ray-traced games too, propelled by more-advanced 3rd-gen RT cores and a radical new Frame Generation DLSS 3 feature that doubles (or more) frame rates yet again with a heaping helping of AI. DEPARTMENTS Nvidia's $1,599 GeForce RTX 4090 graphics card (fave. co/3DOEuWk) sports a luxury price tag, but you get a truly luxurious gaming experience in return. Nvidia claims the RTX 4090 FE "delivers the highest airflow ever measured in a discrete Nvidia GPU, achieving 15 percent more airflow than an RTX 3090 at the same acoustic level." Each game is tested using its in-game benchmark, sanity checked by Nvidia's FrameView tool (fave. co/3T8Cbpa), at the highest possible graphics presets unless otherwise noted, with VSync, frame rate caps, real-time ray-tracing or DLSS effects, and FreeSync/G-Sync disabled, along with any other vendor-specific technologies like FidelityFX tools or Nvidia Reflex. [Extracted from the article]

JOYFUL COLOR AND WORDPLAY Though attracted early on to vivid hues, Nunno's real color breakthrough came about with her still life series of crystal figurines and fruit, begun several years ago. Since color vibrancy is especially important to Nunno's Candy series, she sticks close to her own tried-and-true guidelines (see Compelling Color, right). Features Simply put, Judy Nunno's recent series of paintings, "Candy", is the epitome of visual indulgence - designed to sweeten anyone's art-craving palate. Although Nunno has been depicting glass and cut crystal in her paintings for several years, tackling the cellophane in her "Candy" series was a new venture. [Extracted from the article]

GE Precision Healthcare LLC has been issued a patent for a system and method that utilizes a single ultrasound imaging device to simultaneously measure the heart rates of multiple fetuses and the maternal heart rate. The patent describes how ultrasound devices can be used to produce images and monitor heart rates, but the use of multiple transducers can be uncomfortable for the patient. The system described in the patent uses a single wearable transducer that can be positioned on the abdomen and is coupled to a computing device. The system utilizes different algorithms to focus on each fetus and maintain monitoring without having to reposition the transducer. This technology provides a more comfortable experience for patients and avoids the need for multiple bulky transducers. [Extracted from the article]

A patent application has been submitted for a system and method that uses neural networks to detect cardiovascular anomalies, specifically congenital heart defects (CHD), using medical imaging. The system processes ultrasound images and video clips to generate spatial and temporal outputs, which are then combined to determine the likelihood of CHD or other cardiovascular anomalies. The goal of this system is to improve the detection of these conditions, particularly in complex anatomy and prenatal imaging, to enable early diagnosis and intervention. The patent application provides further details and claims about the method and system. [Extracted from the article]

The article focuses on a new method for frame alignment in time-lapse cell microscopy. Topics include the development of a sub-pixel precise alignment technique using recurrent all-pairs field transforms (RAFT), its application for correcting drift and jitter in multi-sample observations, and the creation of an open-source tool for this purpose.

A recent report from the Institute for Cancer Research and Treatment in Rome, Italy provides new insights into engineering and its application in macular pucker surgery. The study examined the coronal and sagittal retinal displacement before and after surgery, as well as changes in vision loss and metamorphopsia. The research involved 10 patients and found that postoperative displacement was greater than preoperative displacement, with sagittal displacement being greater than coronal displacement. The study also found correlations between displacement and changes in visual acuity and metamorphopsia. This research has been peer-reviewed and provides valuable information for those interested in the field of engineering and its impact on surgical procedures. [Extracted from the article]

A recent study conducted by the Chinese Academy of Sciences in Shenzhen, People's Republic of China, explores the use of tele-ultrasound (Tele-US) for diagnosing blast lung injury (BLI). BLI is a significant concern in cases of explosive events and early symptom confirmation and intervention are crucial. The study proposes an explainable two-stream tele-US diagnosis method called IM3S-Fusion, which integrates optical flow into US videos to enhance interpretability and improve diagnostic accuracy. The results show promising accuracy, recall, precision, specificity, and F1-score. The study also provides explanatory assistance for doctors to facilitate their diagnosis. [Extracted from the article]

A recent study conducted by researchers at the University of Bucharest in Romania has developed a label-free flow cytometry (FCM) method for rapidly evaluating the bactericidal activity of disinfectants. The study compared the efficacy of this method with standard qualitative/quantitative suspension tests and found that the FCM measurements showed excellent correlation with the standard assays. This label-free FCM protocol offers a novel and rapid tool for environmental health experts to optimize disinfectant selection for the prevention and control of healthcare-associated infections (HAIs). The research provides valuable insights for infection prevention and control procedures in healthcare environments. [Extracted from the article]

We present adversarial event prediction (AEP), a novel approach to detecting abnormal events through an event prediction setting. Given normal event samples, AEP derives the prediction model, which can discover the correlation between the present and future of events in the training step. In obtaining the prediction model, we propose adversarial learning for the past and future of events. The proposed adversarial learning enforces AEP to learn the representation for predicting future events and restricts the representation learning for the past of events. By exploiting the proposed adversarial learning, AEP can produce the discriminative model to detect an anomaly of events without complementary information, such as optical flow and explicit abnormal event samples in the training step. We demonstrate the efficiency of AEP for detecting anomalies of events using the UCSD-Ped, CUHK Avenue, Subway, and UCF-Crime data sets. Experiments include the performance analysis depending on hyperparameter settings and the comparison with existing state-of-the-art methods. The experimental results show that the proposed adversarial learning can assist in deriving a better model for normal events on AEP, and AEP trained by the proposed adversarial learning can surpass the existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

A multi-purpose mechanical platform to track moving objects in three-dimensional space has been developed. It is composed of one main microcontroller board that processes all system data, two cameras, three motors, and one secondary microcontroller board to position a platform with three degrees of freedom. The system computes the optical flow and moves the cameras accordingly, tracking motion within the visual scene. The platform operates autonomously. To the best of our knowledge, there are no similar systems reported with low-resolution image sensors and low-cost microcontrollers. Existing solutions rely on personal computers and advanced FPGAs to process image data. This article concludes that the optical flow operation is efficient even using an image sensor with very low resolution. Thus, the system complexity and image data processing are alleviated significantly. The platform can be easily adapted to different application scenarios by adding new peripherals, sensors, or image processing algorithms. A detailed description of the system design and experimental results are provided. [ABSTRACT FROM AUTHOR]

Mimetrik Solutions Limited, based in Leeds, United Kingdom, has been issued a patent for a computer-implemented method that determines the spatial relationship between a patient's upper teeth and their facial skeleton. Traditionally, this relationship is captured using a facebow or earbow, but these methods are complex, expensive, and prone to error. The newly patented method uses a 3D model of the patient's upper teeth, a facial model generated from multiple images of the patient's face, and a computer algorithm to determine the spatial relationship accurately and cost-effectively. This invention has the potential to improve the fabrication of dental prosthetics by ensuring that they align harmoniously with the patient's face. [Extracted from the article]

A patent application has been submitted for an endoscope control method and surgical robot system. The method involves controlling the motion of an endoscope, obtaining images from different imaging units, generating a composite scene image to remove the actual image of the end instrument, and generating a virtual image of the end instrument. The robot system includes a motion arm, an endoscope with imaging units and an end instrument, a control device, and a display device. The invention aims to improve the accuracy of surgical operations by providing a clearer visual field for surgeons. [Extracted from the article]

Ground-based sky imagers have become a valuable tool for cloud monitoring as they allow to observe the local sky in great detail due to their temporally and spatially high-resolution imagery. Set up in pairs, they can be used to estimate both cloud geometry and motion. While considerable effort is currently devoted to their use for cloud shadow forecasting and short-term prediction of solar irradiance for renewable energies, their potential for vertical wind profiling and cloud evolution monitoring has not yet received much attention. We evaluate the accuracy and reliability of such retrievals from two sky imagers in stereo mode by comparing derived 3D cloud motion vector fields with observations from a wind lidar. We find that the wind vectors derived from the detected motion of cumulus clouds and multiple cloud layers can be retrieved with a quality comparable to a wind lidar. Differences in wind speed and direction from both methods remain mostly below 1 to 3ms-1 in wind speed and 6° to 20° in wind direction, depending on cloud type. [ABSTRACT FROM AUTHOR]

Stereo vision is widely deployed on robots and drones to enable depth estimation at a low cost. The combination of lightweight deep neural network (DNN) and cost volumes algorithm is proved to possess the advantages of both high depth estimation accuracy and speed. However, currently there is no accelerator architecture compatible with both efficient DNN inference and cost generation algorithms such as stereo matching. This work proposes a stereo vision accelerator called Dadu-eye, dedicated to real-time processing of high-resolution image streams. The proposed architecture adopts a pipelined hardware design with the techniques of operation approximation and scheduling-level optimization. First, a cost estimation block is designed to generate cost volumes from both luminance and color information. Second, a super pipelined multiplication and accumulation array with a row scan-based fused-layer convolution scheduling is proposed to perform the encoding and decoding neural network efficiently. Finally, an optical flow block is designed and cooperates with the array to approximately predict half of the frames’ depth to achieve real-time (30fps) processing on 1080p view. Based on the SMIC 40 nm CMOS process, this stereo vision accelerator achieves 5.3 TOPS/W power efficiency and significantly reduces 81% off-chip memory access. [ABSTRACT FROM AUTHOR]

Disentangling the sources of visual motion in a dynamic scene during self-movement or ego motion is important for autonomous navigation and tracking. In the dynamic image segments of a video frame containing independently moving objects, optic flow relative to the next frame is the sum of the motion fields generated due to camera and object motion. The traditional ego-motion estimation methods assume the scene to be static, and the recent deep learning-based methods do not separate pixel velocities into object- and ego-motion components. We propose a learning-based approach to predict both ego-motion parameters and object-motion field (OMF) from image sequences using a convolutional autoencoder while being robust to variations due to the unconstrained scene depth. This is achieved by: 1) training with continuous ego-motion constraints that allow solving for ego-motion parameters independently of depth and 2) learning a sparsely activated overcomplete ego-motion field (EMF) basis set, which eliminates the irrelevant components in both static and dynamic segments for the task of ego-motion estimation. In order to learn the EMF basis set, we propose a new differentiable sparsity penalty function that approximates the number of nonzero activations in the bottleneck layer of the autoencoder and enforces sparsity more effectively than L1- and L2-norm-based penalties. Unlike the existing direct ego-motion estimation methods, the predicted global EMF can be used to extract OMF directly by comparing it against the optic flow. Compared with the state-of-the-art baselines, the proposed model performs favorably on pixelwise object- and ego-motion estimation tasks when evaluated on real and synthetic data sets of dynamic scenes. [ABSTRACT FROM AUTHOR]

A recent study conducted at Hallym University in Chuncheon, South Korea, explores the use of deep learning technology to provide low-cost CPR education. The researchers developed a model that converts chest compression videos captured via smartphones into images and provides feedback on key components of high-quality CPR. By allowing many individuals to simultaneously receive CPR training in an optimized educational environment, the researchers hope to improve the survival rate of cardiac arrest patients. The study has been peer-reviewed and published in Expert Systems with Applications. [Extracted from the article]

A recent preprint abstract discusses the neural mechanism for optic flow parsing in the macaque visual cortex. Optic flow parsing is a proposed visual mechanism that allows the brain to compute object motion in the world during self-motion by discounting the global patterns of image motion caused by self-motion. The study demonstrates that neural activity in macaque area MT is biased by peripheral optic flow, which can partially account for perceptual biases induced by flow parsing. These findings provide the first neural basis for the computation of scene-relative object motion based on flow parsing. However, it is important to note that this preprint has not yet been peer-reviewed. [Extracted from the article]

A report from Burapha University in Chonburi, Thailand discusses the use of continuous flow synthesis as a promising platform for the production of nanoparticles for drug and vaccine delivery. This method offers several advantages over conventional batch manufacturing, including reduced process duration, control over particle size and distribution, increased productivity, and the ability to perform complex chemistry. The report explores the fundamental concepts of flow nanoparticle synthesis and its applications in drug and vaccine delivery, as well as discussing its potential and future prospects in the pharmaceutical industry. The research has been peer-reviewed and published in the Journal of Drug Delivery Science and Technology. [Extracted from the article]

The Particle Image Velocimetry (PIV) method is widely used for optical measurment of flow velocity fields. This paper demonstrates the possibilities of using high-level libraries for GPU-accelerated PIV data analysis in Python. The Torch PIV library for the analysis of 2D PIV experiments based on the deep learning framework PyTorch with CUDA support was developed. The library implements a multi pass cross-correlation FFT PIV algorithm with an interrogation window shift. The chosen implementation does not require compilation from the user, has a compact codebase, is able to run both on the CPU and the GPU depending on the user choice, and also it is as flexible as the Python module. In this work, the performance of the CPU version of the developed method was compared with existing open source implementations. It is shown that the main functions of the developed module can be executed on the GPU at the speed of CUDA implementations. The developed library is tested on synthetic images and experimental data. Program title : TorchPIV. CPC Library link to program files : https://doi.org/10.17632/yw43vjc36h.1. Developer's repository link : https://github.com/NikNazarov/TorchPIV. Licensing provisions : MIT license. Programming language : Python. Nature of problem : PIV experiments often require analyzing a large number of images in order to determine the statistical characteristics of the flow. GPUs are actively used in this field to speed up the data analysis process. Open-source software solutions to this problem usually require build and are difficult to integrate into the analysis pipelines. Solution method : The main feature of the developed module is its flexibility and simple distribution. The module is cross-platform, and installation does not require compilation from the user. The developed library can be imported as an ordinary Python module, at the same time it allows to get a significant performance gain when analyzing PIV experiments by using NVIDIA GPUs. Implementation in pure Python allows the module to serve as a backend for more complex experimental data processing systems. The core library of this method is one of the most reliable and widespread in the field of machine learning. [ABSTRACT FROM AUTHOR]

A research report from Maulana Azad National Institute of Technology in Bhopal, India discusses the importance of motion estimation in various applications such as surveillance, traffic management, fire identification, weather prediction, and COVID-19 detection. The report presents a nonlinear fractional order variational model for estimating optical flow, which is a 2D vector field that illustrates object motion behavior. The model aims to provide dense and discontinuity preserving optical flow for different spectra and is robust against noise and outliers. The research concludes by verifying the validity of the proposed model through comparisons with other existing models. [Extracted from the article]

BrightHeart SAS has been issued a patent for their innovative systems and methods that utilize imaging technology to detect cardiovascular anomalies. This patent addresses the limitations of current imaging systems, which can be biased and inaccurate. By analyzing medical images from multiple imaging systems and incorporating style data, the new systems and methods aim to overcome these issues. This technology has the potential to greatly improve the detection of congenital heart defects and other cardiovascular abnormalities, ultimately leading to better healthcare outcomes. The patent provides detailed technical information about the methodology and algorithms used, making it a valuable resource for researchers in this field. [Extracted from the article]

Researchers from the University of Muenster Medical Center in Germany conducted a study on the effects of the Preserflo MicroShunt on glaucoma patients. The study used optical coherence tomography angiography (OCTA) to assess changes in retinal flow density (FD) over a six-month period. The results showed that the Preserflo MicroShunt significantly reduced intraocular pressure (IOP) and had a significant impact on the microvascular flow density in the radial peripapillary plexus (RPC). However, the microvascular structure of the macula appeared to be more resilient to changes in IOP. These findings suggest dysfunctional autoregulatory mechanisms in capillaries surrounding the optic nerve head in advanced glaucoma. [Extracted from the article]

To achieve high-quality imaging in low-light conditions, a remote sensing camera usually adopts a dynamic time-delay-integration imaging approach, which requires an accurate matching relationship between the optical image field motion and the photo-induced charge transfer. High-frequency motion aberrations still exist due to the measurement frequency limitation of physical attitude and position measurement sensors. However, conventional inversion imaging methods, such as blind deconvolution, can only measure and remove low-frequency motion aberrations. Here, an efficient dynamic inversion imaging algorithm based on double deep learning networks is proposed, which is able to measure and remove high-frequency motion aberrations. To measure high-frequency motion aberrations, we constructed two supervised online deep learning networks, a high-frequency motion aberration inversion learning network (HMAILN) and an optical flow inversion learning network (OFILN). The OFILN can measure the accurate optical flow information, which forms the input training set of the HMAILN. The HMAILN completes the measurement of high-frequency motion aberrations. Finally, the measured high-frequency motion aberrations from the HMAILN were used to construct the motion point spread function for imaging compensation to remove high-frequency motion aberrations. The proposed method was experimentally confirmed, opening the door for the successful implementation of dynamic high-resolution imaging without high-frequency motion aberrations. [ABSTRACT FROM AUTHOR]

In this paper a novel descriptor is proposed for anomaly detection in crowd videos at a global level. Traditional approaches for anomaly detection in crowd videos face the dilemma of trade-off between high accuracy and real time performance. In order to resolve this issue, we propose an efficient descriptor composed of three different features extracted from the optical flow (OF) of a video sequence. The first feature is the sum of the optical flow field magnitude computed after applying a threshold. The second feature is the joint entropy of the OF magnitude of two consecutive frames used to measure the dissimilarity. The third feature is the variance computed from a space–time cuboid constructed using history of the OF field magnitude. Performance of the proposed descriptor is evaluated on the widely used UMN dataset in terms of accuracy and processing time. For UMN dataset, the proposed descriptor provides the highest area under the curve (AUC) compared to the approaches already published in literature. [ABSTRACT FROM AUTHOR]

A recent study conducted at the Second Affiliated Hospital in Fuzhou, China, explored the clinical efficacy of modified Buyang Huanwu Decoction in treating non-proliferative diabetic retinopathy (NPDR) in patients with qi and yin deficiency and stagnation of collaterals. The study used optical coherence tomography angiography (OCTA) to quantitatively analyze changes in peripapillary vessel density before and after treatment. The results showed that the group receiving modified Buyang Huanwu Decoction in addition to basic treatment experienced improved visual acuity, traditional Chinese medicine efficacy, peripapillary vessel density, and peripapillary retinal nerve fiber layer thickness compared to the control group. The researchers concluded that modified Buyang Huanwu Decoction may improve blood flow to the optic disc and reduce damage to the retinal nerve fiber layer in patients with NPDR. [Extracted from the article]

A recent study conducted at Westfield State University examined the effects of optical flow perturbations on standing balance in people with multiple sclerosis (MS). The researchers hypothesized that these perturbations would cause higher variability in standing balance for individuals with MS compared to controls. The study found that individuals with MS did indeed exhibit higher trunk sway variability in response to anterior-posterior (A-P) perturbations compared to controls. These findings suggest that optical flow perturbations may have the potential to identify balance deficits in people with MS. [Extracted from the article]

Cell Membrane, Cells, Cellular Structures, Intercellular Junctions, Max-Planck-Gesellschaft, Neurons, Synapses Keywords: Cell Membrane; Cells; Cellular Structures; Intercellular Junctions; Max-Planck-Gesellschaft; Neurons; Synapses EN Cell Membrane Cells Cellular Structures Intercellular Junctions Max-Planck-Gesellschaft Neurons Synapses 1746 1746 1 10/16/23 20231020 NES 231020 2023 OCT 20 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Recognizing motion requires an enormous amount of computing power from the brain. Keywords for this news article include: Neurons, Synapses, Cell Membrane, Cellular Structures, Intercellular Junctions, Max-Planck-Gesellschaft. [Extracted from the article]

This paper introduces an event-based luminance-free algorithm for line and segment detection from the output of asynchronous event-based neuromorphic retinas. These recent biomimetic vision sensors are composed of autonomous pixels, each of them asynchronously generating visual events that encode relative changes in pixels’ illumination at high temporal resolutions. This frame-free approach results in an increased energy efficiency and in real-time operation, making these sensors especially suitable for applications such as autonomous robotics. The proposed algorithm is based on an iterative event-based weighted least squares fitting, and it is consequently well suited to the high temporal resolution and asynchronous acquisition of neuromorphic cameras: parameters of a current line are updated for each event attributed (i.e., spatio-temporally close) to it, while implicitly forgetting the contribution of older events according to a speed-tuned exponentially decaying function. A detection occurs if a measure of activity, i.e., implicit measure of the number of contributing events and using the same decay function, exceeds a given threshold. The speed-tuned decreasing function is based on a measure of the apparent motion, i.e., the optical flow computed around each event. This latter ensures that the algorithm behaves independently of the edges’ dynamics. Line segments are then extracted from the lines, allowing for the tracking of the corresponding endpoints. We provide experiments showing the accuracy of our algorithm and study the influence of the apparent velocity and relative orientation of the observed edges. Finally, evaluations of its computational efficiency show that this algorithm can be envisioned for high-speed applications, such as vision-based robotic navigation. [ABSTRACT FROM AUTHOR]

An optical flow cytometer comprising a cuvette according to claim 1, wherein a speed of a sample injection via the sample injection element is adjusted to a flow speed of a sheath fluid. An optical flow cytometer comprising a cuvette for use in an optical flow cytometer, wherein the cuvette has a hollow structure comprising a cuboid sheath preparation area arranged fluidically upstream from a curved sample injection area with a rectangular cross section arranged fluidically upstream from a pyramidal shaped flow formation area arranged fluidically upstream from a flow cell, wherein a sample injector is arranged along an intersection plane of both the cuboid sheath preparation area and the curved sample injection area, wherein a major axis of the sample injector is arranged perpendicular to a path of a laser beam of the optical flow cytometer. A cuvette for use in an optical flow cytometer, wherein the cuvette has a hollow structure comprising a cuboid sheath preparation area arranged fluidically upstream from a curved sample injection area with a rectangular cross section arranged fluidically upstream from a pyramidal shaped flow formation area, wherein a sample injector is arranged along an intersection plane of both the cuboid sheath preparation area and the curved sample injection area. [Extracted from the article]

If the size of the region is less than the smallest detector MLM input size, the region may be expanded (without rescaling) so that the size of the expanded region matches the input size of the smallest detector MLM. The freed processing resources may be used for deployment, on the same computational platforms, of more advanced MLMs (e.g., MLMs having more processing layers) that are capable of more complete object detection and more accurate classification of the detected objects." If the size of the region is larger than the largest detector MLM input size, the region may be downscaled to the largest detector MLM input size. [Extracted from the article]

Keywords: Chicago; State:Illinois; United States; North and Central America; Angiography; Biomarkers; Cardiology; Cardiovascular Diagnostic Techniques; Diabetic Angiopathies; Diabetic Retinopathy; Diagnostics and Screening; Eye Diseases and Conditions; Health and Medicine; Imaging Technology; Nutritional and Metabolic Diseases and Conditions; Ophthalmology; Optical Coherence Tomography; Retinal Diseases and Conditions; Retinopathy; Technology; Vascular Diseases and Conditions EN Chicago State:Illinois United States North and Central America Angiography Biomarkers Cardiology Cardiovascular Diagnostic Techniques Diabetic Angiopathies Diabetic Retinopathy Diagnostics and Screening Eye Diseases and Conditions Health and Medicine Imaging Technology Nutritional and Metabolic Diseases and Conditions Ophthalmology Optical Coherence Tomography Retinal Diseases and Conditions Retinopathy Technology Vascular Diseases and Conditions 321 321 1 08/14/23 20230814 NES 230814 2023 AUG 14 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- Current study results on Nutritional and Metabolic Diseases and Conditions - Diabetic Retinopathy have been published. For more information on this research see: Normalized Blood Flow Index In Optical Coherence Tomography Angiography Provides a Sensitive Biomarker of Early Diabetic Retinopathy. [Extracted from the article]

Keywords: Tokyo; Japan; Asia; Algorithms; Crohn's Disease; Digestive System Diseases and Conditions; Gastroenteritis; Gastroenterology; Gastrointestinal; Gastrointestinal Diseases and Conditions; Health and Medicine EN Tokyo Japan Asia Algorithms Crohn's Disease Digestive System Diseases and Conditions Gastroenteritis Gastroenterology Gastrointestinal Gastrointestinal Diseases and Conditions Health and Medicine 600 600 1 08/07/23 20230807 NES 230807 2023 AUG 7 (NewsRx) -- By a News Reporter-Staff News Editor at Gastroenterology Week -- Research findings on Digestive System Diseases and Conditions - Crohn's Disease are discussed in a new report. Tokyo, Japan, Asia, Algorithms, Crohn's Disease, Digestive System Diseases and Conditions, Gastroenteritis, Gastroenterology, Gastrointestinal, Gastrointestinal Diseases and Conditions, Health and Medicine. [Extracted from the article]

Systems for practicing the subject methods having a laser, an acousto-optic device, a radiofrequency generator and a controller for adjusting the amplitude of the radiofrequency drive signals to produce an output laser beam of angularly deflected laser beams with a predetermined intensity profile are also described. The system of claim 17, the system further comprising: a first optical adjustment component for inverting the first set of angularly deflected laser beams and overlap the second set of angularly deflected beams; and a second optical adjustment component for optically combining the inverted first set of angularly deflected laser beams with the second set of angularly deflected laser beams to produce a recombined output laser beam. The method of claim 7, wherein the intensity of the angularly deflected laser beam at the center of the output excitation beam is from 0.1% to about 99% of the intensity of the angularly deflected laser beams at the edge of the output excitation beam along the horizontal axis. [Extracted from the article]

College Park, State:Maryland, United States, North and Central America, Life Science, Biomechanical Engineering Keywords for this news article include: College Park, Maryland, United States, North and Central America, Life Science, Biomechanical Engineering, University of Maryland. Keywords: College Park; State:Maryland; United States; North and Central America; Life Science; Biomechanical Engineering EN College Park State:Maryland United States North and Central America Life Science Biomechanical Engineering 5329 5329 1 07/31/23 20230804 NES 230804 2023 AUG 4 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Current study results on Life Science have been published. [Extracted from the article]

Video semantic segmentation (VSS) is a fundamental machine vision task with various practical applications, such as autonomous driving and automated surveillance. Current studies mainly utilize temporal features based on optical flow and the self-attention mechanism to improve VSS accuracy. However, these studies still face challenges like reduced accuracy and computational overhead due to inaccurate optical flow and the computational cost of the self-attention mechanism. To solve these problems, we propose a Temporal Difference Segmentation Net (TDSNet). Additionally, to improve accuracy and keep low computational costs, TDSNet employs temporal-difference-based temporal feature through the Temporal Feature Refine Module (TFRM). To further improve the accuracy of VSS, TDSNet adaptively fuses temporal features of varied motion magnitude with the Motion Magnitude Refine Module (MMRM). This module weighs and fuses temporal features of different magnitudes between frames. Extensive experimental results demonstrate that the comprehensive performance of TDSNet outperforms that of State-Of-The-Art (SOTA) VSS models on two large-scale public datasets: VSPW and Cityscapes. For instance, on VSPW, TDSNet achieves higher faster FPS than the SOTA model CFFM++ does by 13.2 frames per second, while the mIoU of the proposed model is only 0.7% lower than that of CFFM++. These results indicate promising performance in VSS applications. • The model TDSNet is constructed to accurately segment frames of the video. • The temporal-difference-based temporal features are utilized to improve accuracy of the segmentation. • The temporal features are adaptively aggregated according to motion information. • The experimental results indicate that the proposed work is able to accurately segment the target of the video. [ABSTRACT FROM AUTHOR]

IN THE LAB EVERY COUPLE OF years, the planets align in such a way that allows for the birth of a new generation of graphics cards. We suspect the RTX 4090 will reign over this generation of GPUs, though we haven't seen AMD's RDNA 3, due in the next month or two. The RTX 4090 has more GPU cores and higher clocks than the outgoing 3090 Ti - we saw clocks of 2.7GHz or more while gaming. [Extracted from the article]

Most of the existing 3D video quality assessment (3D-VQA/SVQA) methods only consider spatial information by directly using an image quality evaluation method. In addition, a few take the motion information of adjacent frames into consideration. In practice, one may assume that a single data-view is unlikely to be sufficient for effectively learning the video quality. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose an effective multi-view feature learning metric for blind stereoscopic video quality assessment (BSVQA), which jointly focuses on spatial information, temporal information and inter-frame spatio-temporal information. In our study, a set of local binary patterns (LBP) statistical features extracted from a computed frame curvelet representation are used as spatial and spatio-temporal description, and the local flow statistical features based on the estimation of optical flow are used to describe the temporal distortion. Subsequently, a support vector regression (SVR) is utilized to map the feature vectors of each single view to subjective quality scores. Finally, the scores of multiple views are pooled into the final score according to their contribution rate. Experimental results demonstrate that the proposed metric significantly outperforms the existing metrics and can achieve higher consistency with subjective quality assessment. [ABSTRACT FROM AUTHOR]

Keywords: Diabetic Angiopathies; Diabetic Retinopathy; Eye Diseases and Conditions; Health and Medicine; Imaging Technology; Nutritional and Metabolic Diseases and Conditions; Ophthalmology; Optical Coherence Tomography; Retinal Diseases and Conditions; Retinopathy; Technology; Vascular Diseases and Conditions EN Diabetic Angiopathies Diabetic Retinopathy Eye Diseases and Conditions Health and Medicine Imaging Technology Nutritional and Metabolic Diseases and Conditions Ophthalmology Optical Coherence Tomography Retinal Diseases and Conditions Retinopathy Technology Vascular Diseases and Conditions 113 113 1 03/23/23 20230313 NES 230313 2023 MAR 13 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- Current study results on diabetic retinopathy have been published. Diabetic Angiopathies, Diabetic Retinopathy, Eye Diseases and Conditions, Health and Medicine, Imaging Technology, Nutritional and Metabolic Diseases and Conditions, Ophthalmology, Optical Coherence Tomography, Retinal Diseases and Conditions, Retinopathy, Technology, Vascular Diseases and Conditions. [Extracted from the article]

According to news reporting out of Guangzhou, People's Republic of China, by NewsRx editors, research stated, "Benign paroxysmal positional vertigo (BPPV) is the most common vestibular peripheral vertigo disease characterized by brief recurrent vertigo with positional nystagmus. Keywords: Guangzhou; People's Republic of China; Asia; Ear Diseases and Conditions; Health and Medicine; Labyrinth Diseases and Conditions; Nervous System Diseases and Conditions; Otorhinolaryngologic Diseases and Conditions; Vertigo; Vestibular Diseases and Conditions EN Guangzhou People's Republic of China Asia Ear Diseases and Conditions Health and Medicine Labyrinth Diseases and Conditions Nervous System Diseases and Conditions Otorhinolaryngologic Diseases and Conditions Vertigo Vestibular Diseases and Conditions 4749 4749 1 03/23/23 20230303 NES 230303 2023 MAR 3 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Researchers detail new data in Nervous System Diseases and Conditions - Vertigo. [Extracted from the article]