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In this paper, we construct an explicit family of measures that are $p$ -adic doubling for any given pair of primes, yet not doubling. This generalizes the construction by Boylan, Mills, and Ward on a structure theorem on the intersection of dyadic doubling measures and tri-adic doubling measures. As some byproducts, we apply these results to show analogous statements about the reverse Hölder and Muckenhoupt $A_p$ classes of weights. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study a new class of function spaces, called N (p , q , s) -type spaces, in the unit ball B of C n . We establish some basic properties of this new function space, together with a characterization via Green's function, and finally, we study the Hadamard gap series in N (p , q , s) -type spaces. This is the first paper in a five part series. The second paper deals with the Carleson measure, while the third paper deals with several different characterizations of N (p , q , s) -type spaces via various norms and some applications to distance problems. Moreover, the fourth paper deals with the atomic decomposition of those functions belonging to N (p , q , s) -type spaces, and finally, the fifth paper deals with the Riemann–Stieltjes operators and multipliers on N (p , q , s) -type spaces. [ABSTRACT FROM AUTHOR]

In this note we give simple proofs of several results involving maximal truncated Calderón–Zygmund operators in the general setting of rearrangement-invariant quasi-Banach function spaces by sparse domination. Our techniques allow us to track the dependence of the constants in weighted norm inequalities; additionally, our results hold in ℝ n as well as in many spaces of homogeneous type. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study a new class of function spaces, called 𝒩 ⁢ (p , q , s) {\mathcal{N}(p,q,s)} -type spaces, in the unit ball 𝔹 {{\mathbb{B}}} of ℂ n {{\mathbb{C}}^{n}}. The Carleson measure on such spaces is investigated. Some embedding theorems among 𝒩 ⁢ (p , q , s) {\mathcal{N}(p,q,s)} -type spaces, weighted Bergman spaces and weighted Hardy spaces are established. As for applications, the Hadamard products and random power series on 𝒩 ⁢ (p , q , s) {\mathcal{N}(p,q,s)} -type spaces are also studied. [ABSTRACT FROM AUTHOR]

Monte Carlo (MC) methods for light transport simulation are flexible and general but typically suffer from high variance and slow convergence. Gradientdomain rendering alleviates this problem by additionally generating image gradients and reformulating rendering as a screened Poisson image reconstruction problem. To improve the quality and performance of the reconstruction, we propose a novel and practical deep learning based approach in this paper. The core of our approach is a multi-branch auto-encoder, termed GradNet, which end-to-end learns a mapping from a noisy input image and its corresponding image gradients to a high-quality image with low variance. Once trained, our network is fast to evaluate and does not require manual parameter tweaking. Due to the difficulty in preparing ground-truth images for training, we design and train our network in a completely unsupervised manner by learning directly from the input data. This is the first solution incorporating unsupervised deep learning into the gradient-domain rendering framework. The loss function is defined as an energy function including a data fidelity term and a gradient fidelity term. To further reduce the noise of the reconstructed image, the loss function is reinforced by adding a regularizer constructed from selected rendering-specific features. We demonstrate that our method improves the reconstruction quality for a diverse set of scenes, and reconstructing a high-resolution image takes far less than one second on a recent GPU. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to investigate the prognostic factors influencing the outcome of patients with Barcelona Clinic Liver Cancer stage C hepatocellular carcinoma (HCC) receiving salvage surgery after conversion therapy based on tyrosine kinase inhibitors (TKIs) and anti-programmed death-1 (PD-1) antibodies., Methods: From June 2018 to December 2022, patients receiving salvage surgery after conversion therapy based on PD-1 and TKIs at the Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital were retrospectively recruited for this study. Overall survival (OS) and recurrence-free survival (RFS) were observed as the primary end point in the Cox analysis of prognostic factors among this study., Results: The 6- and 12-month RFS rates were 77.0% and 64.8%, respectively, while the 6-, 12-, 24-, and 36-month OS rates were 98.4%, 93.4%, 76.8%, and 69.8%, respectively. The median OS and RFS were not reached. On multivariable Cox regression analyses, low serum alpha fetoprotein (AFP) level (≤20 ng/mL) after conversion therapy [hazard ratio (HR) 0.186, 95% CI: 0.039-0.887; P=0.035) and microvascular invasion (MVI) grade II (HR 3.054, 95% CI: 1.000-9.329; P=0.050) were independent factors associated with a higher OS and RFS., Conclusions: For patients with Barcelona Clinic Liver Cancer stage C (BCLC-C) HCC, lower AFP level after conversion therapy (<20 ng/mL) and MVI II were associated with a higher OS and lower RFS rate, respectively., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-70/coif). The authors have no conflicts of interest to declare., (2023 Translational Cancer Research. All rights reserved.)

In situ analysis of glycans is of great significance since they mediate a range of biological activities. Aberrant changes of glycosylation are closely related to cancer onset and progression. In this work, bifunctional laser cleavable mass probes (LCMPs) were developed for in situ glycan detection from both cells and tissues using laser desorption ionization mass spectrometry (LDI-MS). Specific recognition of glycans was achieved by lectins, and inherent signal amplification was achieved by the conversion of the detection of glycans to that of mass tags which overcame the low ionization efficiency and complicated mass spectra of glycans. Multiplexed glycan profiling was easy to implement due to the simple and generic synthetic route to LCMPs and serial alternative mass tags, which offers high sensitivity, low interference and in situ detection of glycans. Moreover, as an excellent inherent matrix, LCMPs facilitated direct glycan detection from the cell surface and tissue imaging using LDI-MS. Intrinsic and fine glycan distribution in human cancer and paracancerous tissues was strictly demonstrated by MS imaging to explore the correlation between glycosylation and various cancers. This approach presented a versatile LDI-MS based platform for fast and in situ multiplexed glycan engineering, thus providing a new perspective in glycobiology and clinical diagnosis.