Ground-to-air aircraft infrared image deblurring based on imaging degradation simulation.

The issue of infrared image deblurring has been a significant concern. However, in some specific scenes, the current mainstream deblurring algorithms based on optimization or deep learning fail to provide satisfactory results. Aiming to address the ineffectiveness of deep learning methods due to the low-cost datasets' unavailability for specific scenes, we innovatively propose a relatively simple full-chain imaging degradation simulation method using ground-to-air aircraft infrared imaging scene as an example, which considers the effects of blur and noise caused by the atmosphere, imaging system, target motion and detector.

Aberration aware feature detection and description.

Feature detection and description are crucial for image matching, as better performance at this stage leads to more accurate matching results, which is essential for subsequent vision-based tasks. However, images captured by different optical systems may suffer from various optical aberrations, especially in off-axis field and out-of-depth-of-field regions, making it challenging for models to extract consistent feature locations and descriptors. In this paper, we propose what we believe to be a novel method for training feature detection and description networks by incorporating optical system aberrations modeled by point spread function(PSF).

Optical degradation correction of manufacturing-perturbed glass-plastic hybrid lens systems via a joint hardware-software optimization framework.

Glass-plastic hybrid lens systems are increasingly critical in various optical applications due to their unique advantages and growing demands. Due to limitations in manufacturing processes and costs, the yield rate of glass-plastic hybrid lens systems in mass production struggles to match that of mature all-plastic ones. In this work, we propose a pioneering joint hardware-software optimization framework designed for correcting optical degradation in manufacturing-perturbed glass-plastic hybrid lens systems.

Toward Model-Informed Precision Dosing for Remimazolam: A Population Pharmacokinetic-Pharmacodynamic Analysis.

Remimazolam, widely used for procedural sedation and general anesthesia, is a new ultra short-acting benzodiazepine for intravenous sedation and anesthesia. We aim to characterize the pharmacokinetics/pharmacodynamics (PK/PD) of remimazolam and its metabolite CNS 7054 in healthy Chinese volunteers using population analysis and suggest an optimal dosing regimen for sedation therapy. Data were collected from a single-center, placebo-controlled, randomized, and dose-escalation clinical pharmacology study.

Hydrogen sulfide coordinates glucose metabolism switch through destabilizing tetrameric pyruvate kinase M2.

Most cancer cells reprogram their glucose metabolic pathway from oxidative phosphorylation to aerobic glycolysis for energy production. By reducing enzyme activity of pyruvate kinase M2 (PKM2), cancer cells attain a greater fraction of glycolytic metabolites for macromolecule synthesis needed for rapid proliferation. Here we demonstrate that hydrogen sulfide (HS) destabilizes the PKM2 tetramer into monomer/dimer through sulfhydration at cysteines, notably at C326, leading to reduced PKM2 enzyme activity and increased PKM2-mediated transcriptional activation.

Cep57 regulates human centrosomes through multivalent interactions.

Human Cep57 is a coiled-coil scaffold at the pericentriolar matrix (PCM), controlling centriole duplication and centrosome maturation for faithful cell division. Genetic truncation mutations of Cep57 are associated with the mosaic-variegated aneuploidy (MVA) syndrome. During interphase, Cep57 forms a complex with Cep63 and Cep152, serving as regulators for centrosome maturation.

Trilaciclib dosage in Chinese patients with extensive-stage small cell lung cancer: a pooled pharmacometrics analysis.

This study aimed to analyze potential ethnic disparities in the dose-exposure-response relationships of trilaciclib, a first-in-class intravenous cyclin-dependent kinase 4/6 inhibitor for treating chemotherapy-induced myelosuppression in patients with extensive-stage small cell lung cancer (ES-SCLC). This investigation focused on characterizing these relationships in both Chinese and non-Chinese patients to further refine the dosing regimen for trilaciclib in Chinese patients with ES-SCLC. Population pharmacokinetic (PopPK) and exposure-response (E-R) analyses were conducted using pooled data from four randomized phase 2/3 trials involving Chinese and non-Chinese patients with ES-SCLC.

Epigenetic modulation through BET bromodomain inhibitors as a novel therapeutic strategy for progranulin-deficient frontotemporal dementia.

Frontotemporal dementia (FTD) is a debilitating neurodegenerative disorder with currently no disease-modifying treatment options available. Mutations in GRN are one of the most common genetic causes of FTD, near ubiquitously resulting in progranulin (PGRN) haploinsufficiency. Small molecules that can restore PGRN protein to healthy levels in individuals bearing a heterozygous GRN mutation may thus have therapeutic value.

Wavelength encoding spectral imaging based on the combination of deeply learned filters and an RGB camera.

Hyperspectral imaging is a critical tool for gathering spatial-spectral information in various scientific research fields. As a result of improvements in spectral reconstruction algorithms, significant progress has been made in reconstructing hyperspectral images from commonly acquired RGB images. However, due to the limited input, reconstructing spectral information from RGB images is ill-posed.

Safety of teriflunomide in Chinese adult patients with relapsing multiple sclerosis: A phase IV, 24-week multicenter study.

Background: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS.

Methods: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.

Reliable image dehazing by NeRF.

Image dehazing is a typical low-level visual task. With the continuous improvement of network performance and the introduction of various prior knowledge, the ability of image dehazing is becoming stronger. However, the existing dehazing methods have problems such as the inability to obtain real shooting datasets, unreliable dehazing processes, and the difficulty to deal with complex lighting scenes.

Dark2Light: multi-stage progressive learning model for low-light image enhancement.

Due to severe noise and extremely low illuminance, restoring from low-light images to normal-light images remains challenging. Unpredictable noise can tangle the weak signals, making it difficult for models to learn signals from low-light images, while simply restoring the illumination can lead to noise amplification. To address this dilemma, we propose a multi-stage model that can progressively restore normal-light images from low-light images, namely Dark2Light.

Design of an optimized Alvarez lens based on the fifth-order polynomial combination.

This paper proposes an optimized design of the Alvarez lens by utilizing a combination of three fifth-order - polynomials. It can effectively minimize the curvature of the lens surface to meet the manufacturing requirements. The phase modulation function and aberration of the proposed lens are evaluated by using first-order optical analysis.

ASF-Transformer: neutralizing the impact of atmospheric turbulence on optical imaging through alternating learning in the spatial and frequency domains.

Atmospheric turbulence, a pervasive and complex physical phenomenon, challenges optical imaging across various applications. This paper presents the Alternating Spatial-Frequency (ASF)-Transformer, a learning-based method for neutralizing the impact of atmospheric turbulence on optical imaging. Drawing inspiration from split-step propagation and correlated imaging principles, we propose the Alternating Learning in Spatial and Frequency domains (LASF) mechanism.

Image restoration for optical zooming system based on Alvarez lenses.

Alvarez lenses are known for their ability to achieve a broad range of optical power adjustment by utilizing complementary freeform surfaces. However, these lenses suffer from optical aberrations, which restrict their potential applications. To address this issue, we propose a field of view (FOV) attention image restoration model for continuous zooming.

Retinal Thinning as a Marker of Disease Severity in Progressive Supranuclear Palsy.

Objective: Progressive supranuclear palsy (PSP) involves a variety of visual symptoms that are thought to be partially caused by structural abnormalities of the retina. However, the relationship between retinal structural changes, disease severity, and intracranial alterations remains unknown. We investigated distinct retinal thinning patterns and their relationship with clinical severity and intracranial alterations in a PSP cohort.

Direct distortion prediction method for AR-HUD dynamic distortion correction.

Dynamic distortion is one of the most critical factors affecting the experience of automotive augmented reality head-up displays (AR-HUDs). A wide range of views and the extensive display area result in extraordinarily complex distortions. Existing methods based on the neural network first obtain distorted images and then get the predistorted data for training mostly.

Nighttime Image Dehazing by Render.

Nighttime image dehazing presents unique challenges due to the unevenly distributed haze caused by the color change of artificial light sources. This results in multiple interferences, including atmospheric light, glow, and direct light, which make the complex scattering haze interference difficult to accurately distinguish and remove. Additionally, obtaining pairs of high-definition data for fog removal at night is a difficult task.

External evaluation of the predictive performance of published population pharmacokinetic models of linezolid in adult patients.

Objectives: Several linezolid population pharmacokinetic (popPK) models have been established to facilitate optimal therapy; however, their extrapolated predictive performance to other clinical sites is unknown. This study aimed to externally evaluate the predictive performance of published pharmacokinetic models of linezolid in adult patients.

Methods: For the evaluation dataset, 150 samples were collected from 70 adult patients (72.

Snapshot hyperspectral imaging based on equalization designed DOE.

Hyperspectral imaging attempts to determine distinctive information in spatial and spectral domain of a target. Over the past few years, hyperspectral imaging systems have developed towards lighter and faster. In phase-coded hyperspectral imaging systems, a better coding aperture design can improve the spectral accuracy relatively.

Model Informed Development of SIM0295 in Patients with Gout and Hyperuricemia and Healthy Volunteers Using a Population Pharmacokinetics/ Pharmacodynamics Approach.

Background: SIM0295, a novel inhibitor of human uric acid transporter 1 (hURAT1), is used to treat patients with gout and hyperuricemia. This study aimed to develop population pharmacokinetics and pharmacodynamics (popPK/PD) models of SIM0295 and explore potential covariates to inform clinical drug development.

Research Design And Methods: Data were obtained from four phase I studies conducted in healthy Korean and Chinese subjects and two phase II studies conducted in Korean patients with gout and hyperuricemia.

Elimination of varying chromatic aberrations based on diffractive optics.

In telescopic systems consisting of Alvarez lenses, chromatic aberrations vary with the magnifications and the fields of view. Computational imaging has developed rapidly in recent years, therefore we propose a method of optimizing the DOE and the post-processing neural network in 2 stages for achromatic aberrations. We apply the iterative algorithm and the gradient descent method to optimize the DOE, respectively, and then adopt U-Net to further optimize the results.

External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients.

Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors.