Adjacent Slice Feature Guided 2.5D Network for Pulmonary Nodule Segmentation

More and more attention has been paid to the segmentation of pulmonary nodules. Among the current methods based on deep learning, 3D segmentation methods directly input 3D images, which takes up a lot of memory and brings huge computation. However, most of the 2D segmentation methods with less parameters and calculation have the problem of lacking spatial relations between slices, resulting in poor segmentation performance. In order to solve these problems, we propose an adjacent slice feature guided 2.5D network. In this paper, we design an adjacent slice feature fusion model to introduce information from adjacent slices. To further improve the model performance, we construct a multi-scale fusion module to capture more context information, in addition, we design an edge-constrained loss function to optimize the segmentation results in the edge region. Fully experiments show that our method performs better than other existing methods in pulmonary nodule segmentation task

ASF-Net: Robust Video Deraining via Temporal Alignment and Online Adaptive Learning

In recent times, learning-based methods for video deraining have demonstrated commendable results. However, there are two critical challenges that these methods are yet to address: exploiting temporal correlations among adjacent frames and ensuring adaptability to unknown real-world scenarios. To overcome these challenges, we explore video deraining from a paradigm design perspective to learning strategy construction. Specifically, we propose a new computational paradigm, Alignment-Shift-Fusion Network (ASF-Net), which incorporates a temporal shift module. This module is novel to this field and provides deeper exploration of temporal information by facilitating the exchange of channel-level information within the feature space. To fully discharge the model's characterization capability, we further construct a LArge-scale RAiny video dataset (LARA) which also supports the development of this community. On the basis of the newly-constructed dataset, we explore the parameters learning process by developing an innovative re-degraded learning strategy. This strategy bridges the gap between synthetic and real-world scenes, resulting in stronger scene adaptability. Our proposed approach exhibits superior performance in three benchmarks and compelling visual quality in real-world scenarios, underscoring its efficacy. The code is available at https://github.com/vis-opt-group/ASF-Net

CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model

Instruction tuning has recently been recognized as an effective way of aligning Large Language Models (LLMs) to enhance their generalization ability across various tasks. However, when tuning publicly accessible, centralized LLMs with private instruction data, privacy concerns are inevitable. While direct transfer of parameterized modules between models is a plausible approach to address this, its implications and effectiveness need further exploration. This paper focuses on Offsite-Tuning (OFT), a representative technique that transfers transformer blocks between centralized LLMs and downstream emulators. Given the limited understanding of the underlying mechanism of OFT, we perform an empirical analysis on LLMs from the perspectives of representation and functional similarity. Interestingly, our findings reveal a unique modular structure within the layers of LLMs that appears to emerge as the model size expands. Simultaneously, we note subtle but potentially significant changes in representation and intermediate predictions across the layers. Inspired by these observations, we propose CRaSh, involving Clustering, Removing, and Sharing, a training-free strategy to derive improved emulators from LLMs. CRaSh significantly boosts performance of OFT with billions of parameters. Furthermore, we investigate the optimal solutions yielded by fine-tuning with and without full model through the lens of loss landscape. Our findings demonstrate a linear connectivity among these optima falling over the same basin, thereby highlighting the effectiveness of CRaSh and OFT. The source code is publicly available at https://github.com/TsinghuaC3I/CRaSh.Comment: Accepted to EMNLP 2023 (Main Conference

Quantum dot passivation of halide perovskite films with reduced defects, suppressed phase segregation, and enhanced stability

Structural defects are ubiquitous for polycrystalline perovskite films, compromising device performance and stability. Herein, a universal method is developed to overcome this issue by incorporating halide perovskite quantum dots (QDs) into perovskite polycrystalline films. CsPbBr3 QDs are deposited on four types of halide perovskite films (CsPbBr3, CsPbIBr2, CsPbBrI2, and MAPbI3) and the interactions are triggered by annealing. The ions in the CsPbBr3 QDs are released into the thin films to passivate defects, and concurrently the hydrophobic ligands of QDs self-assemble on the film surfaces and grain boundaries to reduce the defect density and enhance the film stability. For all QD-treated films, PL emission intensity and carrier lifetime are significantly improved, and surface morphology and composition uniformity are also optimized. Furthermore, after the QD treatment, light-induced phase segregation and degradation in mixed-halide perovskite films are suppressed, and the efficiency of mixed-halide CsPbIBr2 solar cells is remarkably improved to over 11% from 8.7%. Overall, this work provides a general approach to achieving high-quality halide perovskite films with suppressed phase segregation, reduced defects, and enhanced stability for optoelectronic applications.Peer ReviewedPostprint (author's final draft

Changes in grassland soil types lead to different characteristics of bacterial and fungal communities in Northwest Liaoning, China

IntroductionSoil microbial communities are critical in regulating grassland biogeochemical cycles and ecosystem functions, but the mechanisms of how environmental factors affect changes in the structural composition and diversity of soil microbial communities in different grassland soil types is not fully understood in northwest Liaoning, China.MethodsWe investigated the characteristics and drivers of bacterial and fungal communities in 4 grassland soil types with 11 sites across this region using high-throughput Illumina sequencing.Results and DiscussionActinobacteria and Ascomycota were the dominant phyla of bacterial and fungal communities, respectively, but their relative abundances were not significantly different among different grassland soil types. The abundance, number of OTUs, number of species and diversity of both bacterial and fungal communities in warm and temperate ecotone soil were the highest, while the warm-temperate shrub soil had the lowest microbial diversity. Besides, environmental factors were not significantly correlated with soil bacterial Alpha diversity index. However, there was a highly significant negative correlation between soil pH and Shannon index of fungal communities, and a highly significant positive correlation between plant cover and Chao1 index as well as Observed species of fungal communities. Analysis of similarities showed that the structural composition of microbial communities differed significantly among different grassland soil types. Meanwhile, the microbial community structure of temperate steppe-sandy soil was significantly different from that of other grassland soil types. Redundancy analysis revealed that soil total nitrogen content, pH and conductivity were important influencing factors causing changes in soil bacterial communities, while soil organic carbon, total nitrogen content and conductivity mainly drove the differentiation of soil fungal communities. In addition, the degree of connection in the soil bacterial network of grassland was much higher than that in the fungal network and soil bacterial and fungal communities were inconsistently limited by environmental factors. Our results showed that the microbial community structure, composition and diversity of different grassland soil types in northwest Liaoning differed significantly and were significantly influenced by environmental factors. Microbial community structure and the observation of soil total nitrogen and organic carbon content can predict the health changes of grassland ecosystems to a certain extent

Different responses of soil fungal and bacterial communities to nitrogen addition in a forest grassland ecotone

IntroductionContinuous nitrogen deposition increases the nitrogen content of terrestrial ecosystem and affects the geochemical cycle of soil nitrogen. Forest-grassland ecotone is the interface area of forest and grassland and is sensitive to global climate change. However, the structure composition and diversity of soil microbial communities and their relationship with soil environmental factors at increasing nitrogen deposition have not been sufficiently studied in forest-grassland ecotone.MethodsIn this study, experiments were carried out with four nitrogen addition treatments (0 kgN·hm−2·a−1, 10 kgN·hm−2·a−1, 20 kgN·hm−2·a−1 and 40 kgN·hm−2·a−1) to simulate nitrogen deposition in a forest-grassland ecotone in northwest Liaoning Province, China. High-throughput sequencing and qPCR technologies were used to analyze the composition, structure, and diversity characteristics of the soil microbial communities under different levels of nitrogen addition.Results and discussionThe results showed that soil pH decreased significantly at increasing nitrogen concentrations, and the total nitrogen and ammonium nitrogen contents first increased and then decreased, which were significantly higher in the N10 treatment than in other treatments (N:0.32 ~ 0.48 g/kg; NH4+-N: 11.54 ~ 13 mg/kg). With the increase in nitrogen concentration, the net nitrogen mineralization, nitrification, and ammoniation rates decreased. The addition of nitrogen had no significant effect on the diversity and structure of the fungal community, while the diversity of the bacterial community decreased significantly at increasing nitrogen concentrations. Ascomycetes and Actinomycetes were the dominant fungal and bacterial phyla, respectively. The relative abundance of Ascomycetes was negatively correlated with total nitrogen content, while that of Actinomycetes was positively correlated with soil pH. The fungal community diversity was significantly negatively correlated with nitrate nitrogen, while the diversity of the bacterial community was significantly positively correlated with soil pH. No significant differences in the abundance of functional genes related to soil nitrogen transformations under the different treatments were observed. Overall, the distribution pattern and driving factors were different in soil microbial communities in a forest-grassland ecotone in northwest Liaoning. Our study enriches research content related to factors that affect the forest-grassland ecotone

Perovskite quantum dot solar cells fabricated from recycled lead-acid battery waste

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Materials Letters, copyright © 2021 American Chemical Societ, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsmaterialslett.1c00592.A cost-effective and environmentally friendly Pb source is a prerequisite for achieving large-scale, low-cost perovskite photovoltaic devices. Currently, the commonly used method to prepare the lead source is based on a fire smelting process, requiring a high temperature of more than 1000 °C, which results in environmental pollution. Spent car lead acid batteries are an environmentally hazardous waste; however, they can alternatively serve as an abundant and inexpensive Pb source. Due to “self-purification”, quantum dots feature a high tolerance of impurities in the precursor since the impurities tend to be expelled from the small crystalline cores during colloidal nucleation. Herein, PbI2 recycled from spent lead acid batteries via a facile low-temperature solution process is used to synthesize CsPbI3 quantum dots, which simultaneously brings multiple benefits including (1) avoiding pollution originating from the fire smelting process; (2) recycling the Pb waste from batteries; and (3) synthesizing high-quality quantum dots. The resulting CsPbI3 quantum dots have photophysical properties such as PLQY and carrier lifetimes on par with those synthesized from the commercial PbI2 due to expelling of the impurity Na atoms. The resulting solar cells deliver comparable power conversion efficiencies: 14.0% for the cells fabricated using recycled PbI2 and 14.7% for the cells constructed using commercial PbI2. This work paves a new and feasible path to applying recycled Pb sources in perovskite photovoltaics.Peer ReviewedPostprint (author's final draft

Efficient elimination of chlorinated organics on a phosphoric acid modified CeO2 catalyst: a hydrolytic destruction route

The development of efficient technologies to prevent the emission of hazardous chlorinated organics from industrial sources without forming harmful by-products, such as dioxins, is a major challenge in environmental chemistry. Herein, we developed a new hydrolytic destruction route for efficient chlorinated organics elimination and demonstrated that phosphoric acid modified CeO2 (HP-CeO2) can hydrolytically destruct chlorobenzene (CB) without forming polychlorinated congeners under the industry-relevant reaction conditions. The active site and origin of hydrolysis reactivity of HP-CeO2 were probed, which showed the surface phosphate groups can hydrolytically react with CB and water to form phenol and HCl, thus facilitating the chlorine desorption and ensuring a continual O2 activation. Subsequent density functional theory (DFT) calculations revealed a distinctly decreased formation energy of oxygen vacancy nearest (VO-1) and next-nearest (VO-2) to the bonded phosphate groups, which led to a significantly improved oxidizing ability of the catalyst. Significantly, no toxic dioxins were detected from the hydrolysis destruction of CB, which has been frequently cited as a significant challenge to avoid in the conventional oxidation route. This work not only reports an efficient route and corresponding phosphate active site for chlorinated organics elimination, but also illustrates that rational design of reaction route can solve some of the most important challenges in environmental catalysis

Anomalous structural evolution and glassy lattice in mixed-halide hybrid perovskites

Hybrid halide perovskites have emerged as highly promising photovoltaic materials because of their exceptional optoelectronic properties, which are often optimized via compositional engineering like mixing halides. It is well established that hybrid perovskites undergo a series of structural phase transitions as temperature varies. In this work, the authors find that phase transitions are substantially suppressed in mixed-halide hybrid perovskite single crystals of MAPbI3-xBrx (MA = CH3NH3+ and x = 1 or 2) using a complementary suite of diffraction and spectroscopic techniques. Furthermore, as a general behavior, multiple crystallographic phases coexist in mixed-halide perovskites over a wide temperature range, and a slightly distorted monoclinic phase, hitherto unreported for hybrid perovskites, is dominant at temperatures above 100 K. The anomalous structural evolution is correlated with the glassy behavior of organic cations and optical phonons in mixed-halide perovskites. This work demonstrates the complex interplay between composition engineering and lattice dynamics in hybrid perovskites, shedding new light on their unique properties.Peer ReviewedPostprint (published version