Nighttime image dehazing is a challenging task due to the presence of multiple types adverse degrading effects including glow, haze, blur, noise, color distortion, and so on. However, most previous studies mainly focus on daytime or partial degradations presented in nighttime hazy scenes, which may lead unsatisfactory restoration results. In this paper, we propose an end-to-end transformer-based framework for haze removal, called NightHazeFormer. Our proposed approach consists two stages:...

Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment multi-scale snow degradations is critical for the network learn effective removal. In order handle diverse scenes, we propose a projection transformer (MSP-Former), which understands and covers variety degradation features in multi-path manner, integrates comprehensive scene context information clean reconstruction via self-attention operation. For local details various...

Underwater Image Rendering aims to generate a true-to-life underwater image from given clean one, which could be applied various practical applications such as enhancement, camera filter, and virtual gaming. We explore two less-touched but challenging problems in rendering, namely, i) how render diverse scenes by single neural network? ii) adaptively learn the light fields natural exemplars, i,e., realistic images? To this end, we propose rendering method for imaging, dubbed UWNR (Underwater...

A lightweight underwater image enhancement network is of great significance for resource-constrained platforms, but balancing model size, computational efficiency, and performance has proven difficult previous approaches. In this work, we propose the Five A$^{+}$ Network (FA$^{+}$Net), a highly efficient real-time with only $\sim$ 9k parameters 0.01s processing time. The FA$^{+}$Net employs two-stage structure. strong prior stage aims to decompose challenging degradations into sub-problems,...

In the real world, image degradations caused by rain often exhibit a combination of streaks and raindrops, thereby increasing challenges recovering underlying clean image. Note that raindrops have diverse shapes, sizes, locations in captured image, thus modeling correlation relationship between irregular artifacts is necessary prerequisite for deraining. This paper aims to present an efficient flexible mechanism learn model degradation relationships global view, achieving unified removal...

Despite recent advancements in unified adverse weather removal methods, there remains a significant challenge of achieving realistic fine-grained texture and reliable background reconstruction to mitigate serious distortions.Inspired by codebook vector quantization (VQ) techniques, we present novel Adverse Weather Removal network with Codebook Priors (AWRCP) address the problem removal. AWRCP leverages high-quality priors derived from undistorted images recover vivid details faithful...

Night photography often struggles with challenges like low light and blurring, stemming from dark environments prolonged exposures. Current methods either disregard priors directly fitting end-to-end networks, leading to inconsistent illumination, or rely on unreliable handcrafted constrain the network, thereby bringing greater error final result. We believe in strength of data-driven high-quality strive offer a reliable consistent prior, circumventing restrictions manual priors. In this...

Jieduquyuziyin prescription (JP) has been used to treat systemic lupus erythematosus (SLE). Although the effectiveness of JP in treatment SLE clinically proven, underlying mechanisms have yet be completely understood. We observed therapeutic actions MRL/lpr mice and their bone marrow-derived macrophages (BMDMs) potential mechanism inhibition inflammatory activity. To estimate effect on suppressing activity, BMDMs MRL/MP were treated with JP-treated serum, by for eight weeks. Among them, its...

Varicolored haze caused by chromatic casts poses removal and depth estimation challenges. Recent learning-based methods are mainly targeted at dehazing first estimating subsequently from haze-free scenes. This way, the inner connections between colored scene lost. In this paper, we propose a real-time transformer for simultaneous single image Depth Estimation Haze Removal (DEHRFormer). DEHRFormer consists of encoder two task-specific decoders. The decoders with learnable queries designed to...

Extracellular microRNA (miRNA) (exosomal miRNA) embedded in exosomes plays a vital role the progression of calcium oxalate disease. This study aimed to identify dysregulated miRNA expression profiles and their biological functions urinary patients with oxalate. Ultrahigh-speed centrifugation Illumina high-throughput sequencing were used isolate detect levels exocrine miRNAs urine samples from 10 stones matched normal persons, construct differential profiles. Bioinformatics analysis...

Real-world image dehazing remains a challenging task due to the diverse nature of haze degradation and lack large-scale paired datasets. Existing methods based on hand-crafted priors or generative struggle recover accurate backgrounds fine details from dense regions. In this work, we propose novel paradigm, PromptHaze, for real-world via depth prompt Depth Anything model. By employing prompt-by-prompt strategy, our method iteratively updates progressively restores background through network...

Existing low-light image enhancement (LIE) methods have achieved noteworthy success in solving synthetic distortions, yet they often fall short practical applications. The limitations arise from two inherent challenges real-world LIE: 1) the collection of distorted/clean pairs is impractical and sometimes even unavailable, 2) accurately modeling complex degradations presents a non-trivial problem. To overcome them, we propose Attribute Guidance Diffusion framework (AGLLDiff), training-free...

Obesity is a major contributor to male infertility, not only exacerbating infertility but also impairing the effectiveness of both surgical interventions and medical treatments. This review examines complex relationship between obesity, immune microenvironment, highlighting how obesity-induced changes in function lead testicular dysfunction impaired spermatogenesis. Key mechanisms include chronic low-grade inflammation, cell infiltration, dysregulated adipokines such as leptin adiponectin....

Underwater images typically experience mixed degradations of brightness and structure caused by the absorption scattering light suspended particles. To address this issue, we propose a Real-time Spatial Frequency Domains Modulation Network (RSFDM-Net) for efficient enhancement colors details in underwater images. Specifically, our proposed conditional network is designed with Adaptive Fourier Gating Mechanism (AFGM) Multiscale Convolutional Attention Module (MCAM) to generate vectors...

Video restoration networks aim to restore high-quality frame sequences from degraded ones. However, traditional video methods heavily rely on temporal modeling operators or optical flow estimation, which limits their versatility. The of this work is present a novel approach for that eliminates inefficient and pixel-level feature alignment in the network architecture. proposed method, Sequential Affinity Learning Network (SALN), designed based an affinity mechanism establishes direct...

Single-image snow removal aims to restore clean images from heterogeneous and irregular degradations. Recent methods utilize neural networks remove various degradations directly. However, these approaches suffer the limited ability flexibly perceive complicated degradation patterns insufficient representation of background structure information. To further improve performance generalization removal, this paper develop a novel efficient paradigm perspective perceiving modeling.

Cavernosal nerve (CN) injury is commonly caused by radical prostatectomy surgery, and it might directly lead to erectile dysfunction (ED). Currently, the role of mitogen-activated protein kinase (MAPK) family proteins in phenotypic transformation corpus cavernosum smooth muscle cell (CCSMC) after CNs poorly understood.To investigate p38 MAPK hypoxia-induced CCSMCs CN injury.In total, 20 Sprague-Dawley rats (male 8 weeks age) were randomly divided into 2 groups, including a sham group CNCI...

Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs. However, how to efficiently leverage such architectures remains an open problem. In this work, we present Dual-former whose critical insight is combine the powerful global modeling ability of self-attention modules and local convolutions in overall architecture. With convolution-based Local Feature Extraction equipped encoder decoder, only adopt a novel Hybrid Transformer Block...