Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates

In a completely randomized experiment, the variances of treatment effect estimators in the finite population are usually not identifiable and hence not estimable. Although some estimable bounds of the variances have been established in the literature, few of them are derived in the presence of covariates. In this paper, the difference-in-means estimator and the Wald estimator are considered in the completely randomized experiment with perfect compliance and noncompliance, respectively. Sharp bounds for the variances of these two estimators are established when covariates are available. Furthermore, consistent estimators for such bounds are obtained, which can be used to shorten the confidence intervals and improve the power of tests. Confidence intervals are constructed based on the consistent estimators of the upper bounds, whose coverage rates are uniformly asymptotically guaranteed. Simulations were conducted to evaluate the proposed methods. The proposed methods are also illustrated with two real data analyses.Comment: Accepted by Statistica Sinic

FreePIH: Training-Free Painterly Image Harmonization with Diffusion Model

This paper provides an efficient training-free painterly image harmonization (PIH) method, dubbed FreePIH, that leverages only a pre-trained diffusion model to achieve state-of-the-art harmonization results. Unlike existing methods that require either training auxiliary networks or fine-tuning a large pre-trained backbone, or both, to harmonize a foreground object with a painterly-style background image, our FreePIH tames the denoising process as a plug-in module for foreground image style transfer. Specifically, we find that the very last few steps of the denoising (i.e., generation) process strongly correspond to the stylistic information of images, and based on this, we propose to augment the latent features of both the foreground and background images with Gaussians for a direct denoising-based harmonization. To guarantee the fidelity of the harmonized image, we make use of multi-scale features to enforce the consistency of the content and stability of the foreground objects in the latent space, and meanwhile, aligning both fore-/back-grounds with the same style. Moreover, to accommodate the generation with more structural and textural details, we further integrate text prompts to attend to the latent features, hence improving the generation quality. Quantitative and qualitative evaluations on COCO and LAION 5B datasets demonstrate that our method can surpass representative baselines by large margins

Circ-CCS regulates oxaliplatin resistance via targeting miR-874-3p/HK2 axis in colorectal cancer

Background. Colorectal cancer (CRC) is a malignancy that threatens the patient’s life. Previous reports showed that circular RNAs (circRNAs) can affect CRC development. Herein, we demonstrated the characters of circular RNA copper chaperone for superoxide dismutase (circ-CCS) in CRC tissues and cells. Methods. Circ-CCS, CCS mRNA, microRNA-8743p (miR-874-3p) and hexokinase 2 (HK2) were indicated by qRT-PCR and western blot in CRC. The cell roles were examined. Additionally, the interaction between miR-874-3p and circ-CCS or HK2 was forecasted by the bioinformatics method and assessed by dual-luciferase reporter assay. Finally, the mouse test was implemented to demonstrate the effect of circ-CCS in vivo. Results. Circ-CCS and HK2 were increased, whereas miR-874-3p was diminished in CRC. Circ-CCS lack subdued the IC50 value of oxaliplatin, cell proliferation, migration, invasion and glycolysis metabolism in CRC cells, while it endorsed cell apoptosis. Furthermore, miR-874-3p was validated as having a tumor repressive effect in CRC cells by restraining HK2. The results also showed that HK2 could regulate the development of CRC. In mechanism, circ-CCS targeted miR-874-3p to control HK2. In addition, circ-CCS knock-down also attenuated tumor growth in mice. Conclusion. Circ-CCS expedited CRC through miR874-3p/HK

Dissecting Arbitrary-scale Super-resolution Capability from Pre-trained Diffusion Generative Models

Diffusion-based Generative Models (DGMs) have achieved unparalleled performance in synthesizing high-quality visual content, opening up the opportunity to improve image super-resolution (SR) tasks. Recent solutions for these tasks often train architecture-specific DGMs from scratch, or require iterative fine-tuning and distillation on pre-trained DGMs, both of which take considerable time and hardware investments. More seriously, since the DGMs are established with a discrete pre-defined upsampling scale, they cannot well match the emerging requirements of arbitrary-scale super-resolution (ASSR), where a unified model adapts to arbitrary upsampling scales, instead of preparing a series of distinct models for each case. These limitations beg an intriguing question: can we identify the ASSR capability of existing pre-trained DGMs without the need for distillation or fine-tuning? In this paper, we take a step towards resolving this matter by proposing Diff-SR, a first ASSR attempt based solely on pre-trained DGMs, without additional training efforts. It is motivated by an exciting finding that a simple methodology, which first injects a specific amount of noise into the low-resolution images before invoking a DGM's backward diffusion process, outperforms current leading solutions. The key insight is determining a suitable amount of noise to inject, i.e., small amounts lead to poor low-level fidelity, while over-large amounts degrade the high-level signature. Through a finely-grained theoretical analysis, we propose the Perceptual Recoverable Field (PRF), a metric that achieves the optimal trade-off between these two factors. Extensive experiments verify the effectiveness, flexibility, and adaptability of Diff-SR, demonstrating superior performance to state-of-the-art solutions under diverse ASSR environments

Attribute-Aware Representation Rectification for Generalized Zero-Shot Learning

Generalized Zero-shot Learning (GZSL) has yielded remarkable performance by designing a series of unbiased visual-semantics mappings, wherein, the precision relies heavily on the completeness of extracted visual features from both seen and unseen classes. However, as a common practice in GZSL, the pre-trained feature extractor may easily exhibit difficulty in capturing domain-specific traits of the downstream tasks/datasets to provide fine-grained discriminative features, i.e., domain bias, which hinders the overall recognition performance, especially for unseen classes. Recent studies partially address this issue by fine-tuning feature extractors, while may inevitably incur catastrophic forgetting and overfitting issues. In this paper, we propose a simple yet effective Attribute-Aware Representation Rectification framework for GZSL, dubbed $\mathbf{(AR)^{2}}$, to adaptively rectify the feature extractor to learn novel features while keeping original valuable features. Specifically, our method consists of two key components, i.e., Unseen-Aware Distillation (UAD) and Attribute-Guided Learning (AGL). During training, UAD exploits the prior knowledge of attribute texts that are shared by both seen/unseen classes with attention mechanisms to detect and maintain unseen class-sensitive visual features in a targeted manner, and meanwhile, AGL aims to steer the model to focus on valuable features and suppress them to fit noisy elements in the seen classes by attribute-guided representation learning. Extensive experiments on various benchmark datasets demonstrate the effectiveness of our method.Comment: 11 pages, 6 figure

High-Mobility and Bias-Stable Field-Effect Transistors Based on Lead-Free Formamidinium Tin Iodide Perovskites

Electronic devices based on tin halide perovskites often exhibit a poor operational stability. Here, we report an additive engineering strategy to realize high-performance and stable field-effect transistors (FETs) based on 3D formamidinium tin iodide (FASnI3) films. By comparatively studying the modification effects of two additives, i.e., phenethylammonium iodide and 4-fluorophenylethylammonium iodide via combined experimental and theoretical investigations, we unambiguously point out the general effects of phenethylammonium (PEA) and its fluorinated derivative (FPEA) in enhancing crystallization of FASnI3 films and the unique role of fluorination in reducing structural defects, suppressing oxidation of Sn2+ and blocking oxygen and water involved defect reactions. The optimized FPEA-modified FASnI3 FETs reach a record high field-effect mobility of 15.1 cm2/(V·s) while showing negligible hysteresis. The devices exhibit less than 10% and 3% current variation during over 2 h continuous bias stressing and 4200-cycle switching test, respectively, representing the best stability achieved so far for all Sn-based FETs.</p

High-Mobility and Bias-Stable Field-Effect Transistors Based on Lead-Free Formamidinium Tin Iodide Perovskites

Electronic devices based on tin halide perovskites often exhibit a poor operational stability. Here, we report an additive engineering strategy to realize high-performance and stable field-effect transistors (FETs) based on 3D formamidinium tin iodide (FASnI3) films. By comparatively studying the modification effects of two additives, i.e., phenethylammonium iodide and 4-fluorophenylethylammonium iodide via combined experimental and theoretical investigations, we unambiguously point out the general effects of phenethylammonium (PEA) and its fluorinated derivative (FPEA) in enhancing crystallization of FASnI3 films and the unique role of fluorination in reducing structural defects, suppressing oxidation of Sn2+ and blocking oxygen and water involved defect reactions. The optimized FPEA-modified FASnI3 FETs reach a record high field-effect mobility of 15.1 cm2/(V·s) while showing negligible hysteresis. The devices exhibit less than 10% and 3% current variation during over 2 h continuous bias stressing and 4200-cycle switching test, respectively, representing the best stability achieved so far for all Sn-based FETs.</p

Surface Plasmon Resonance Enhanced Spontaneous Upconversion and Stimulated Emissions in Glass Ceramics Containing Ba 2

Glass ceramics containing Yb3+, Er3+ codoped Ba2LaF7 nanocrystals were fabricated via melt quenching method and the subsequent heating treatment. The formation of Ba2LaF7 nanocrystals in the glass ceramics was confirmed by X-ray diffraction (XRD) and transmission electron microscope (TEM). The spontaneous upconversion (UC) emission and the stimulated counterpart as a random lasing action of Er3+, which were related to the characteristic transitions of Er3+ ions, were achieved in the Yb3+, Er3+-doped Ba2LaF7 nanocrystals embedded glass ceramic hybrid. Furthermore, the absorption spectra verified the surface plasmon resonance (SPR) band of Ag, which precipitated from the matrix glasses as Ag nanoparticles (NPs). By incorporating Ag NPs in the glass ceramic hybrid, spontaneous UC emission intensity of Er3+ in visible region was significantly enhanced, while the threshold of the random lasing was decreased from 480 to 350 nJ/cm2

StMAPKK5 responds to heat stress by regulating potato growth, photosynthesis, and antioxidant defenses

BackgroundsAs a conserved signaling pathway, mitogen-activated protein kinase (MAPK) cascade regulates cellular signaling in response to abiotic stress. High temperature may contribute to a significant decrease in economic yield. However, research into the expression patterns of StMAPKK family genes under high temperature is limited and lacks experimental validation regarding their role in supporting potato plant growth.MethodsTo trigger heat stress responses, potato plants were grown at 35°C. qRT-PCR was conducted to analyze the expression pattern of StMAPKK family genes in potato plants. Plant with StMAPKK5 loss-of-function and gain-of-function were developed. Potato growth and morphological features were assessed through measures of plant height, dry weight, and fresh weight. The antioxidant ability of StMAPKK5 was indicated by antioxidant enzyme activity and H2O2 content. Cell membrane integrity and permeability were suggested by relative electrical conductivity (REC), and contents of MDA and proline. Photosynthetic capacity was next determined. Further, mRNA expression of heat stress-responsive genes and antioxidant enzyme genes was examined.ResultsIn reaction to heat stress, the expression profiles of StMAPKK family genes were changed. The StMAPKK5 protein is located to the nucleus, cytoplasm and cytomembrane, playing a role in controlling the height and weight of potato plants under heat stress conditions. StMAPKK5 over-expression promoted photosynthesis and maintained cell membrane integrity, while inhibited transpiration and stomatal conductance under heat stress. Overexpression of StMAPKK5 triggered biochemical defenses in potato plant against heat stress, modulating the levels of H2O2, MDA and proline, as well as the antioxidant activities of CAT, SOD and POD. Overexpression of StMAPKK5 elicited genetic responses in potato plants to heat stress, affecting heat stress-responsive genes and genes encoding antioxidant enzymes.ConclusionStMAPKK5 can improve the resilience of potato plants to heat stress-induced damage, offering a promising approach for engineering potatoes with enhanced adaptability to challenging heat stress conditions

A multi-wavelength mid-IR laser based on BaGa4Se7 optical parametric oscillators

A multi-wavelength mid-IR laser consisting of 3.05 μm, 4.25 μm, and 5.47 μm BaGa4Se7(BGSe)optical parametric oscillators (OPOs) switched by DKDP electro-optic switches with one 10 Hz/7.6 ns pumping wave is demonstrated. Maximum energies at 3.05 μm, 4.25 μm, and 5.47 μm are 1.35 mJ, 1.03 mJ, and 0.56 mJ, respectively, corresponding to optical-to-optical conversion efficiencies of 9.4%, 7.6%, and 4.2%. To the best of our knowledge, this study is the first of generation of three mid-IR wavelength lasers using electro-optic switches. Furthermore, this study provides a viable solution for a high-energy or high-power, compact, or even portable multi-wavelength mid-IR laser device that employs a single pumping wave