Tbps wide-field parallel optical wireless communications based on a metasurface beam splitter.

Optical wireless communication (OWC) stands out as one of the most promising technologies in the sixth-generation (6G) mobile networks. The establishment of high-quality optical links between transmitters and receivers plays a crucial role in OWC performances. Here, by a compact beam splitter composed of a metasurface and a fiber array, we proposed a wide-angle (~120°) OWC optical link scheme that can parallelly support up to 144 communication users. Utilizing high-speed optical module sources and wavelength division multiplexing technique, we demonstrated each user can achieve a communication speed of 200 Gbps which enables the entire system to support ultra-high communication capacity exceeding 28 Tbps. Furthermore, utilizing the metasurface polarization multiplexing, we implemented a full range wide-angle OWC without blind area nor crosstalk among users. Our OWC scheme simultaneously possesses the advantages of high-speed, wide communication area and multi-user parallel communications, paving the way for revolutionary high-performance OWC in the future.

Decoupled graph knowledge distillation: A general logits-based method for learning MLPs on graphs.

While Graph Neural Networks (GNNs) have demonstrated their effectiveness in processing non-Euclidean structured data, the neighborhood fetching of GNNs is time-consuming and computationally intensive, making them difficult to deploy in low-latency industrial applications. To address the issue, a feasible solution is graph knowledge distillation (KD), which can learn high-performance student Multi-layer Perceptrons (MLPs) to replace GNNs by mimicking the superior output of teacher GNNs. However, state-of-the-art graph knowledge distillation methods are mainly based on distilling deep features from intermediate hidden layers, this leads to the significance of logit layer distillation being greatly overlooked. To provide a novel viewpoint for studying logits-based KD methods, we introduce the idea of decoupling into graph knowledge distillation. Specifically, we first reformulate the classical graph knowledge distillation loss into two parts, i.e., the target class graph distillation (TCGD) loss and the non-target class graph distillation (NCGD) loss. Next, we decouple the negative correlation between GNN's prediction confidence and NCGD loss, as well as eliminate the fixed weight between TCGD and NCGD. We named this logits-based method Decoupled Graph Knowledge Distillation (DGKD). It can flexibly adjust the weights of TCGD and NCGD for different data samples, thereby improving the prediction accuracy of the student MLP. Extensive experiments conducted on public benchmark datasets show the effectiveness of our method. Additionally, DGKD can be incorporated into any existing graph knowledge distillation framework as a plug-and-play loss function, further improving distillation performance. The code is available at https://github.com/xsk160/DGKD.

Overview of Bovine Mastitis: Application of Metabolomics in Screening Its Predictive and Diagnostic Biomarkers.

Bovine mastitis is an inflammatory disease of the mammary glands, and its pathogenesis and diagnosis are complicated. Through qualitative and quantitative analysis of small-molecule metabolites, the metabolomics technique plays an important role in finding biomarkers and studying the metabolic mechanism of bovine mastitis. Therefore, this paper reviews the predictive and diagnostic biomarkers of bovine mastitis that have been identified using metabolomics techniques and that are present in samples such as milk, blood, urine, rumen fluid, feces, and mammary tissue. In addition, the metabolic pathways of mastitis-related biomarkers in milk and blood were analyzed; it was found that the tricarboxylic acid (TCA) cycle was the most significant (FDR = 0.0015767) pathway in milk fluid, and glyoxylate and dicarboxylate metabolism was the most significant (FDR = 0.0081994) pathway in blood. The purpose of this review is to provide useful information for the prediction and early diagnosis of bovine mastitis.

Focusing on non-responders to infliximab with ulcerative colitis, what can we do first and next?

BACKGROUND: Ulcerative colitis (UC) is a chronic immune-mediated inflammation of the colorectum, for which infliximab (IFX) is currently the mainstay of treatment. However, one-third of patients with UC still fail to benefit from the IFX therapy, and early exposure to IFX impairs the efficacy of other subsequent biologics. Therefore, personalized therapeutic system is urgently needed to assist in clinical decision-making and precision treatment. METHODS: Four microarray datasets of colonic biopsies from UC patients treated with IFX were obtained from the GEO database to form the Training Cohort and Validation Cohort. Differentially expressed genes (DEGs) in Training Cohort were identified and enriched for GO, KEGG and immune cell infiltration analysis. A prediction model for IFX efficacy was developed based on the LASSO and Logistic regression. The predictive accuracy of the model was verified by the Validation Cohort, and the model-genes/proteins were validated by immunohistochemistry. Gene-drug, gene-ncRNA interaction analysis were performed to identify drugs or non-coding RNAs (ncRNAs) that potentially interacted with the model-genes. Homology Modeling and Molecular Docking were conducted to filter the optimal candidate as the subsequent adjuvant or alternative for IFX in predicted non-responders. At last, the down-regulation of the key model-gene/protein CYP24A1 by the drug candidate Deferasirox was verified by Western Blot and qRT-PCR Assay based on cellular experiments. RESULTS: A total of 113 DEGs were identified in the Training Cohort, mainly enriched in inflammatory cell chemotaxis, migration, and response to molecules derived from intestinal microbiota. Activated pro-inflammatory innate immune cells, including neutrophils, M1 macrophages, activated dendritic cells and mast cells, were significantly enriched in colons of non-responders. The prediction model based on three model-genes (IFI44L, CYP24A1, and RGS1) exhibited strong predictive efficacy, with AUC values of 0.901 and 0.80 in the Training and Validation Cohorts, respectively. Higher expression of the three model-genes/proteins in colons of non-responders to IFX was confirmed by clinical colonic mucosal biopsies. 4 Drugs (Calcitriol, Lunacalcipol, Deferasirox, Telaprevir), 15 miRNAs and 66 corresponding lnRNAs interacting with model-genes were identified. The protein 3D structure of the key model-gene/protein (human-derived CYP24A1) was developed. Through the Molecular Docking and cellular experimental validation, Deferasirox, which significantly down-regulated both the RNA and protein expression of CYP24A1, was identified as the optimal adjuvant or alternative for IFX in predicted non-responders with UC. CONCLUSION: This study developed a novel prediction model for pre-assessing the efficacy of IFX in patients with UC, as the first step towards personalized therapy. Meanwhile, drugs and non-coding RNAs were provided as potential candidates to develop the next-step precise treatment for the predicted non-responders. In particular, Defeasirox appears to hold promise as an adjuvant or alternative to IFX for the optimization of UC therapy.

SUMOylation at the crossroads of gut health: insights into physiology and pathology.

SUMOylation, a post-translational modification involving the covalent attachment of small ubiquitin-like modifier (SUMO) proteins to target substrates, plays a pivotal role at the intersection of gut health and disease, influencing various aspects of intestinal physiology and pathology. This review provides a comprehensive examination of SUMOylation's diverse roles within the gut microenvironment. We examine its critical roles in maintaining epithelial barrier integrity, regulating immune responses, and mediating host-microbe interactions, thereby highlighting the complex molecular mechanisms that underpin gut homeostasis. Furthermore, we explore the impact of SUMOylation dysregulation in various intestinal disorders, including inflammatory bowel diseases and colorectal cancer, highlighting its implications as a potential diagnostic biomarker and therapeutic target. By integrating current research findings, this review offers valuable insights into the dynamic interplay between SUMOylation and gut health, paving the way for novel therapeutic strategies aimed at restoring intestinal equilibrium and combating associated pathologies.

Sialylation in the gut: From mucosal protection to disease pathogenesis.

Sialylation, a crucial post-translational modification of glycoconjugates, entails the attachment of sialic acid (SA) to the terminal glycans of glycoproteins and glycolipids through a tightly regulated enzymatic process involving various enzymes. This review offers a comprehensive exploration of sialylation within the gut, encompassing its involvement in mucosal protection and its impact on disease progression. The sialylation of mucins and epithelial glycoproteins contributes to the integrity of the intestinal mucosal barrier. Furthermore, sialylation regulates immune responses in the gut, shaping interactions among immune cells, as well as their activation and tolerance. Additionally, the gut microbiota and gut-brain axis communication are involved in the role of sialylation in intestinal health. Altered sialylation patterns have been implicated in various intestinal diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), and other intestinal disorders. Emerging research underscores sialylation as a promising avenue for diagnostic, prognostic, and therapeutic interventions in intestinal diseases. Potential strategies such as sialic acid supplementation, inhibition of sialidases, immunotherapy targeting sialylated antigens, and modulation of sialyltransferases have been utilized in the treatment of intestinal diseases. Future research directions will focus on elucidating the molecular mechanisms underlying sialylation alterations, identifying sialylation-based biomarkers, and developing targeted interventions for precision medicine approaches.

Leveraging single-cell sequencing analysis and bulk-RNA sequencing analysis to forecast necroptosis in cutaneous melanoma prognosis.

Cutaneous melanoma, a malignancy of melanocytes, presents a significant challenge due to its aggressive nature and rising global incidence. Despite advancements in treatment, the variability in patient responses underscores the need for further research into novel therapeutic targets, including the role of programmed cell death pathways such as necroptosis. The melanoma datasets used for analysis, GSE215120, GSE19234, GSE22153 and GSE65904, were downloaded from the GEO database. The melanoma data from TCGA were downloaded from the UCSC website. Using single-cell sequencing, we assess the heterogeneity of necroptosis in cutaneous melanoma, identifying distinct cell clusters and necroptosis-related gene expression patterns. A combination of 101 machine learning algorithms was employed to construct a necroptosis-related signature (NRS) based on key genes associated with necroptosis. The prognostic value of NRS was evaluated in four cohorts (one TCGA and three GEO cohorts), and the tumour microenvironment (TME) was analysed to understand the relationship between necroptosis, tumour mutation burden (TMB) and immune infiltration. Finally, we focused on the role of key target TSPAN10 in the prognosis, pathogenesis, immunotherapy relevance and drug sensitivity of cutaneous melanoma. Our study revealed significant heterogeneity in necroptosis among melanoma cells, with a higher prevalence in epithelial cells, myeloid cells and fibroblasts. The NRS, developed through rigorous machine learning techniques, demonstrated robust prognostic capabilities, distinguishing high-risk patients with poorer outcomes in all cohorts. Analysis of the TME showed that high NRS scores correlated with lower TMB and reduced immune cell infiltration, indicating a potential mechanism through which necroptosis influences melanoma progression. Finally, TSPAN10 has been identified as a key target for cutaneous melanoma and is highly associated with poor prognosis. The findings highlight the complex role of necroptosis in cutaneous melanoma and introduce the NRS as a novel prognostic tool with potential to guide therapeutic decisions.

Dynamic establishment and maintenance of the human intestinal B cell population and repertoire following transplantation in a pediatric-dominated cohort.

Introduction: It is unknown how intestinal B cell populations and B cell receptor (BCR) repertoires are established and maintained over time in humans. Following intestinal transplantation (ITx), surveillance ileal mucosal biopsies provide a unique opportunity to map the dynamic establishment of recipient gut lymphocyte populations in immunosuppressed conditions. Methods: Using polychromatic flow cytometry that includes HLA allele group-specific antibodies distinguishing donor from recipient cells along with high throughput BCR sequencing, we tracked the establishment of recipient B cell populations and BCR repertoire in the allograft mucosa of ITx recipients. Results: We confirm the early presence of naïve donor B cells in the circulation (donor age range: 1-14 years, median: 3 years) and, for the first time, document the establishment of recipient B cell populations, including B resident memory cells, in the intestinal allograft mucosa (recipient age range at the time of transplant: 1-44 years, median: 3 years). Recipient B cell repopulation of the allograft was most rapid in infant (<1 year old)-derived allografts and, unlike T cell repopulation, did not correlate with rejection rates. While recipient memory B cell populations were increased in graft mucosa compared to circulation, naïve recipient B cells remained detectable in the graft mucosa for years. Comparisons of peripheral and intra-mucosal B cell repertoires in the absence of rejection (recipient age range at the time of transplant: 1-9 years, median: 2 years) revealed increased BCR mutation rates and clonal expansion in graft mucosa compared to circulating B cells, but these parameters did not increase markedly after the first year post-transplant. Furthermore, clonal mixing between the allograft mucosa and the circulation was significantly greater in ITx recipients, even years after transplantation, than in deceased adult donors. In available pan-scope biopsies from pediatric recipients, we observed higher percentages of naïve recipient B cells in colon allograft compared to small bowel allograft and increased BCR overlap between native colon vs colon allograft compared to that between native colon vs ileum allograft in most cases, suggesting differential clonal distribution in large intestine vs small intestine. Discussion: Collectively, our data demonstrate intestinal mucosal B cell repertoire establishment from a circulating pool, a process that continues for years without evidence of stabilization of the mucosal B cell repertoire in pediatric ITx patients.

Dihydromyricetin ameliorates experimental ulcerative colitis by inhibiting neutrophil extracellular traps formation via the HIF-1α/VEGFA signaling pathway.

Dihydromyricetin (DHM), which has various biological functions, possesses therapeutic potential for ulcerative colitis (UC). Neutrophil extracellular traps (NETs) and their components play a crucial role in several pathological processes in UC. However, whether DHM alleviates UC by regulating NETs remains unclear. Mice with dextran sulfate sodium (DSS)-induced acute colitis were treated with DHM at different concentrations, and the severity of colitis was evaluated by assessing body weight, colon length, histological scores, cytokine production, and epithelial barrier integrity. To quantify and visualize NETs, the expression of cell free-DNA (cf-DNA) in serum and Cit-H3 in colonic tissue was analyzed via western blotting and immunofluorescence analysis. HL-60 cells and mouse bone marrow-derived neutrophils (BMDNs) were used to evaluate the effects of DHM on NETs in vitro. NETs were treated with DHM at varying concentrations or DNase I and used to repair the intestinal epithelial barrier in a Caco-2/HIEC-6 cell monolayer model. Furthermore, the genes targeted by DHM through neutrophils for alleviating UC were identified by screening online databases, and the results of network pharmacological analysis were verified via western blotting and quantitative real-time polymerase chain reaction. DHM alleviated DSS-induced colitis in mice by reversing weight loss, increased DAI score, colon length shortening, enhanced spleen index, colonic pathological damage, cytokine production, and epithelial barrier loss in a dose-dependent manner. In addition, it inhibited the formation of NETs both in vivo and in vitro. Based on the results of network pharmacological analysis, DHM may target HIF-1α and VEGFA through neutrophils to alleviate UC. Treatment with PMA increased the expression of HIF-1α and VEGFA in D-HL-60 cells and BMDNs, whereas treatment with DHM or DNase I reversed this effect. Treatment with DMOG, an inhibitor of HIF prolyl hydroxylase (HIF-PH), counteracted the suppressive effects of DHM on NETs formation in D-HL-60 cells and BMDNs. Accordingly, it partially counteracted the protective effects of DHM on the intestinal epithelial barrier in Caco-2 and HIEC-6 cells. These results indicated that DHM alleviated DSS-induced UC by regulating NETs formation via the HIF-1α/VEGFA signaling pathway, suggesting that DHM is a promising therapeutic candidate for UC.

Nets in fibrosis: Bridging innate immunity and tissue remodeling.

Fibrosis, a complex pathological process characterized by excessive deposition of extracellular matrix components, leads to tissue scarring and dysfunction. Emerging evidence suggests that neutrophil extracellular traps (NETs), composed of DNA, histones, and antimicrobial proteins, significantly contribute to fibrotic diseases pathogenesis. This review summarizes the process of NETs production, molecular mechanisms, and related diseases, and outlines the cellular and molecular mechanisms associated with fibrosis. Subsequently, this review comprehensively summarizes the current understanding of the intricate interplay between NETs and fibrosis across various organs, including the lung, liver, kidney, skin, and heart. The mechanisms by which NETs contribute to fibrogenesis, including their ability to promote inflammation, induce epithelial-mesenchymal transition (EMT), activate fibroblasts, deposit extracellular matrix (ECM) components, and trigger TLR4 signaling were explored. This review aimed to provide insights into the complex relationship between NETs and fibrosis via a comprehensive analysis of existing reports, offering novel perspectives for future research and therapeutic interventions.

Deep-learning enhanced high-quality imaging in metalens-integrated camera.

Because of their ultra-light, ultra-thin, and flexible design, metalenses exhibit significant potential in the development of highly integrated cameras. However, the performances of metalens-integrated camera are constrained by their fixed architectures. Here we proposed a high-quality imaging method based on deep learning to overcome this constraint. We employed a multi-scale convolutional neural network (MSCNN) to train an extensive pair of high-quality and low-quality images obtained from a convolutional imaging model. Through our method, the imaging resolution, contrast, and distortion have all been improved, resulting in a noticeable overall image quality with SSIM over 0.9 and an improvement in PSNR over 3 dB. Our approach enables cameras to combine the advantages of high integration with enhanced imaging performances, revealing tremendous potential for a future groundbreaking imaging technology.

Exploring Cr(VI)-induced blood-brain barrier injury and neurotoxicity in zebrafish and snakehead fish, and inhibiting toxic effects of astaxanthin.

Cr(VI) is a common hazardous heavy metal contaminant that seriously endangers human and aquatic animal health. GPX4 was the key enzyme that reduces heavy metal toxicity through inhibiting ferroptosis pathway. Astaxanthin was GPX4 activator that can weaken biological toxicity induced by Cr(VI) exposure. The present study was conducted to evaluate the major role of GPX4 in astaxanthin protects Cr(VI)-induced oxidative damage, blood-brain barrier injury and neurotoxicity in brain-liver axis through inhibiting ferroptosis pathway. In the current study, astaxanthin intervention can effectively alleviate Cr(VI)-induced oxidative stress, blood-brain barrier damage, and neurotoxicity. GPX4 plays a major role in mediating astaxanthin nutritional intervention to reduce ROS and liver non-heme iron accumulation, which would contribute to the reduction of ferroptosis. Meanwhile, astaxanthin maintains the stability of transport receptors and protein macromolecules such as TMEM163, SLC7A11, SLC3A2, FPN1 and GLUT1 in the brain liver axis, promoting substance exchange and energy supply. Moreover, astaxanthin alleviates Cr(VI)-induced neurotoxicity by promoting tight protein expression and reducing blood-brain barrier permeability.

Assessment of the quality, diagnosis, and therapeutic recommendations of clinical practice guidelines on patients with Helicobacter pylori infection: A systematic review.

We conducted this study to systematically review and assess the current clinical practice guidelines (CPGs) related to the diagnosis and treatment of Helicobacter pylori (H. pylori) infection. The aim was to evaluate the quality of these included CPGs and provide clinicians with a convenient and comprehensive reference for updating their own CPGs. We searched four databases to identify eligible CPGs focusing on H. pylori diagnosis and treatment recommendations. The results were presented using evidence mappings. Quality and clinical applicability were assessed comprehensively using AGREE-II and AGREE-REX. Statistical tests, specifically Bonferroni tests, were employed to compare the quality between evidence-based guidelines and consensus. A total of 30 eligible CPGs were included, comprising 17 consensuses and 13 guidelines. The quality showed no statistical significance between consensuses and guidelines, mainly within the moderate to low range. Notably, recommendations across CPGs exhibited inconsistency. Nevertheless, concerning diagnosis, the urea breath test emerged as the most frequently recommended method for testing H. pylori. Regarding treatment, bismuth quadruple therapy stood out as the predominantly recommended eradication strategy, with high-dose dual therapy being a newly recommended option. Our findings suggest the need for specific organizations to update their CPGs on H. pylori or refer to recently published CPGs. Specifically, CPGs for pediatric cases require improvement and updating, while a notable absence of CPGs for the elderly was observed. Furthermore, there is a pressing need to improve the overall quality of CPGs related to H. pylori. Regarding recommendations, additional evidence is essential to elucidate the relationship between H. pylori infection and other diseases and refine test indications. Clinicians are encouraged to consider bismuth quadruple or high-dose dual therapy, incorporating locally sensitive antibiotics, as empirical radical therapy. .

Dynamic establishment and maintenance of the human intestinal B cell population and repertoire following transplantation.

It is unknown how intestinal B cell populations and B cell receptor (BCR) repertoires are established and maintained over time in humans. Following intestinal transplantation (ITx), surveillance ileal mucosal biopsies provide a unique opportunity to map the dynamic establishment of gut lymphocyte populations. Using polychromatic flow cytometry that includes HLA allele group-specific mAbs distinguishing donor from recipient cells along with high throughput BCR sequencing, we tracked the establishment of recipient B cell populations and BCR repertoire in the allograft mucosa of ITx recipients. We confirm the early presence of naïve donor B cells in the circulation and, for the first time, document the establishment of recipient B cell populations, including B resident memory cells, in the intestinal allograft mucosa. Recipient B cell repopulation of the allograft was most rapid in infant (<1 year old)-derived allografts and, unlike T cell repopulation, did not correlate with rejection rates. While recipient memory B cell populations were increased in graft mucosa compared to circulation, naïve recipient B cells remained detectable in the graft mucosa for years. Comparisons of peripheral and intra-mucosal B cell repertoires in the absence of rejection revealed increased BCR mutation rates and clonal expansion in graft mucosa compared to circulating B cells, but these parameters did not increase markedly after the first year post-transplant. Furthermore, clonal mixing between the allograft mucosa and the circulation was significantly greater in ITx recipients, even years after transplantation, than in healthy control adults. Collectively, our data demonstrate intestinal mucosal B cell repertoire establishment from a circulating pool, a process that continues for years without evidence of establishment of a stable mucosal B cell repertoire.

Exposure estimates of parabens from personal care products compared with biomonitoring data in human hair from Northeast China.

Parabens (PBs), a class of endocrine-disrupting chemicals (EDCs), are extensively used as additives in personal care products (PCPs); however, distinguishing between endogenous and exogenous contamination from PCPs in hair remains a challenge. We conducted a comprehensive analysis of the levels, distribution patterns, impact factors, and sources of PBs in 119 human hair samples collected from Changchun, northeast China. The detection rates of methylparaben (MeP), propylparaben (PrP), and ethylparaben (EtP) in hair samples were found to be 100%. The concentration of PBs in hair followed the order of MeP (57.48 ng/g) > PrP (46.40 ng/g) > EtP (6.80 ng/g). The concentration of PrP in female hair was significantly higher (65.38 ng/g) than that observed in male hair (7.82 ng/g) (p < 0.05). The levels of excretion rates of MeP (ERMeP) and excretion rates of PrP (ERPrP) in the hair-dying samples (ERMeP: 17.89 ng/day; ERPrP: 14.15 ng/day) were found to be 2.52 and 2.40 times higher, respectively, compared to the non-hair-dying samples (ERMeP: 7.09 ng/day; ERPrP: 6.05 ng/day). However, the system exposure dosage (SED) results revealed that although hair dyes exhibited higher PBs, human exposure was found to be lower than certain PCPs. The results of the correlation analysis revealed that toner, face cream, body lotion, and hair conditioner were identified as the primary sources of PBs in male hair. Furthermore, the human exposure resulting from the utilization of female hair dye and serum exhibited a positive correlation with hair ERMeP and ERPrP levels, indicating in the screening of samples, excluding hair samples using hair dye and haircare essential oil can effectively avoid the interference caused by exogenous contamination from PCPs.

Financial investment risk prediction under the application of information interaction Firefly Algorithm combined with Graph Convolutional Network.

This paper improves the performance of the model by Graph Convolutional Network (GCN) and Firefly Algorithm (FA) to optimize the financial investment risk prediction model. It studies the application of GCN in financial investment risk prediction model and elaborates on the role of FA in the model. To further improve the accuracy of the prediction model, this paper optimizes and improves the FA and verifies the effectiveness of the optimized model through experiments. Experimental results show that the optimized model performs well in feature selection, and the optimal accuracy of feature selection reaches 91.9%, which is much higher than that of traditional models. Meanwhile, in the analysis of the number of iterations of the model, the performance of the optimized algorithm gradually tends to be stable. When the number of iterations is 30, the optimal value is found. In the simulation experiment, when an unexpected accident occurs, the prediction accuracy of the model decreases, but the prediction performance of the optimized algorithm proposed here is significantly higher than that of the traditional model. In conclusion, the optimized model has high accuracy and reliability in financial investment risk prediction, which provides strong support for financial investment decision-making. This paper has certain reference significance for the optimization of financial investment risk prediction model.

Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models.

During image editing, existing deep generative models tend to re-synthesize the entire output from scratch, including the unedited regions. This leads to a significant waste of computation, especially for minor editing operations. In this work, we present Spatially Sparse Inference (SSI), a general-purpose technique that selectively performs computation for edited regions and accelerates various generative models, including both conditional GANs and diffusion models. Our key observation is that users prone to gradually edit the input image. This motivates us to cache and reuse the feature maps of the original image. Given an edited image, we sparsely apply the convolutional filters to the edited regions while reusing the cached features for the unedited areas. Based on our algorithm, we further propose Sparse Incremental Generative Engine (SIGE) to convert the computation reduction to latency reduction on off-the-shelf hardware. With about 1%-area edits, SIGE accelerates DDPM by 3.0× on NVIDIA RTX 3090 and 4.6× on Apple M1 Pro GPU, Stable Diffusion by 7.2× on 3090, and GauGAN by 5.6× on 3090 and 5.2× on M1 Pro GPU. Compared to our conference paper, we enhance SIGE to accommodate attention layers and apply it to Stable Diffusion. Additionally, we offer support for Apple M1 Pro GPU and include more results to substantiate the efficacy of our method.

Microstructure and Properties of Nickel-Based Gradient Coatings Prepared Using Cold Spraying Combined with Laser Cladding Methods.

A cold spray-laser cladding composite gradient coating (CLGC) was successfully formed on a Cu substrate. In comparison with traditional laser cladding gradient coatings (LGC), cold spraying the pre-set Ni-Cu alloy's intermediate transition layer not only mitigates the negative impacts due to the high reflectivity of the copper substrate but also helps to minimize the difference in the coefficients of thermal expansion (CTE) between the substrate and coating. This reduces the overall crack sensitivity and improves the cladding quality of the coating. Besides this, the uniform distribution of hard phases in CLGC, such as Ni11Si12 and Mo5Si3, greatly increases its microhardness compared to the Cu substrate, thus resulting in the value of 478.8 HV0.5 being approximately 8 times that of the Cu substrate. The friction coefficient of CLGC is lowered compared to both the Cu substrate and LGC with respective values of 0.28, 0.54, and 0.43, and its wear rate is only one-third of the Cu substrate's. These results suggest CLGC has excellent anti-wear properties. In addition, the wear mechanism was determined from the microscopic morphology and element distribution and was found to be oxidative and abrasive. This approach combines cold spraying and laser cladding to form a nickel-based gradient coating on a Cu substrate without cracks, holes, or other faults, thus improving the wear resistance of the Cu substrate and improving its usability.