399 research outputs found
Detection of stroboscopic effects in dependence of duty cycle, speed and illuminance level
Light-emitting diodes (LEDs) that are dimmed by pulse width modulation (PWM) may cause visually uncomfortable stroboscopic effects due to improper selection of operating parameters. Therefore, it is important to understand that the visibility of the stroboscopic effect depends on parameters such as duty cycle, speed, and illuminance level. These dependencies were analysed by using a LED light source illuminating a black-coated rotating disk with a white dot mounted on top of it. Modulating the light source with a square wave signal between 100 Hz and 4200 Hz and different duty cycles (10%, 30%, 50%, 70%, 80%), allowed us to determine the subject’s visibility of the stroboscopic effect for different rotation speeds (2m/s, 4m/s, 6m/s) and illuminance levels (100lx, 500lx, 1000lx). Based on the results of these experiments, objective models were developed, which can be used to increase the accuracy and validity of the stroboscopic visibility measure, and effectively reduce the stroboscopic effects
Gravitational Lensing by Transparent Janis-Newman-Winicour Naked Singularities
The Janis-Newman-Winicour (JNW) spacetime can describe a naked singularity
with a photon sphere that smoothly transforms into a Schwarzschild black hole.
Our analysis reveals that photons, upon entering the photon sphere, converge to
the singularity in a finite coordinate time. Furthermore, if the singularity is
subjected to some regularization, these photons can traverse the regularized
singularity. Subsequently, we investigate the gravitational lensing of distant
sources and show that new images emerge within the critical curve formed by
light rays escaping from the photon sphere. These newfound images offer a
powerful tool for the detection and study of JNW naked singularities.Comment: 28 pages, 5 figure
Editorial: Disease biomarker analysis based on optical biosensing
Disease biomarker analysis has become a crucial tool for diagnosing and evaluating disease prognosis, especially with the increasing understanding of diseases at the molecular level. Abnormalities in various biomarkers can indicate diseased states, and can be used to rapidly and specifically detect and quantify diseases using optical biosensing techniques (Gao et al., 2023). Optical biosensing techniques have several advantages over traditional methods including higher sensitivity, specificity, and faster analysis times (Plikusiene and Ramanaviciene, 2023). It also allows for non-invasive sample collection. With advancements in optical biosensing technology, many medical conditions including cancers, infectious diseases, and autoimmune disorders can be accurately diagnosed and efficiently treated (Singh et al., 2023; Tang et al., 2023). The combination of optical biosensing with emerging technologies such as material science, optics, and electronics has further accelerated its development in biomarker analysis (Qureshi et al., 2022). Interdisciplinary collaboration between experts in fields such as physics, chemistry, bioengineering, and medicine has helped pave the way for novel optical biosensing technologies as well as improving existing ones. Continued interdisciplinary collaboration is essential in advancing the field of disease biomarker analysis based on optical biosensing. This exciting area of research holds great potential for the future of personalized and precision medicine, and will likely lead to more effective disease diagnoses and treatments (Duo et al., 2023)
A Comprehensive Research of Atmospheric Haze by Optical Remote Sensing in Central China Region (CCR)
The function and regulation of heat shock transcription factor in Cryptococcus
Cryptococcus species are opportunistic human fungal pathogens. Survival in a hostile environment, such as the elevated body temperatures of transmitting animals and humans, is crucial for Cryptococcus infection. Numerous intriguing investigations have shown that the Hsf family of thermotolerance transcription regulators plays a crucial role in the pathogen-host axis of Cryptococcus. Although Hsf1 is known to be a master regulator of the heat shock response through the activation of gene expression of heat shock proteins (Hsps). Hsf1 and other Hsfs are multifaceted transcription regulators that regulate the expression of genes involved in protein chaperones, metabolism, cell signal transduction, and the electron transfer chain. In Saccharomyces cerevisiae, a model organism, Hsf1’s working mechanism has been intensively examined. Nonetheless, the link between Hsfs and Cryptococcus pathogenicity remains poorly understood. This review will focus on the transcriptional regulation of Hsf function in Cryptococcus, as well as potential antifungal treatments targeting Hsf proteins
Reconstructing Turbulent Flows Using Physics-Aware Spatio-Temporal Dynamics and Test-Time Refinement
Simulating turbulence is critical for many societally important applications
in aerospace engineering, environmental science, the energy industry, and
biomedicine. Large eddy simulation (LES) has been widely used as an alternative
to direct numerical simulation (DNS) for simulating turbulent flows due to its
reduced computational cost. However, LES is unable to capture all of the scales
of turbulent transport accurately. Reconstructing DNS from low-resolution LES
is critical for many scientific and engineering disciplines, but it poses many
challenges to existing super-resolution methods due to the spatio-temporal
complexity of turbulent flows. In this work, we propose a new physics-guided
neural network for reconstructing the sequential DNS from low-resolution LES
data. The proposed method leverages the partial differential equation that
underlies the flow dynamics in the design of spatio-temporal model
architecture. A degradation-based refinement method is also developed to
enforce physical constraints and further reduce the accumulated reconstruction
errors over long periods. The results on two different types of turbulent flow
data confirm the superiority of the proposed method in reconstructing the
high-resolution DNS data and preserving the physical characteristics of flow
transport.Comment: 19 page
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