Anti‐counterfeiting techniques have become a global topic since they is correlated to the information and data safety, in which multimodal luminescence is one of the most desirable candidates for ...practical applications. However, it is a long‐standing challenge to actualize robust multimodal luminescence with high thermal stability and humid resistance. Conventionally, the multimodal luminescence is usually achieved by the combination of upconversion and downshifting luminescence, which only responds to the electromagnetic waves in a limited range. Herein, the Yb3+/Er3+/Bi3+ co‐doped Cs2Ag0.6Na0.4InCl6 perovskite material is reported as an efficient multimodal luminescence material. Beyond the excitation of ultraviolet light and near‐infrared laser (980 nm), this work extends multimodal luminescence to the excitation of X‐ray. Besides the flexible excitation sources, this material also shows the exceptional luminescence performance, in which the X‐ray detection limit reaches the level of nGy s−1, indicating a great potential for further application as a colorless pigment in the anti‐counterfeiting field. More importantly, the obtained double perovskite features high stability against both humidity and temperature up to 400 °C. This integrated multifunctional luminescent material provides a new directional solution for the development of multifunctional optical materials and devices.
A Yb3+/Er3+/Bi3+ co‐doped Cs2Ag0.6Na0.4InCl6 double‐perovskite material shows multi‐modal luminescence under excitation by X‐rays, ultraviolet light, and near‐infrared laser light (980 nm), which also features high stability against humidity and high temperature (up to 400 °C). This luminescent material further extends the functionality and potential for future commercial applications in anti‐counterfeiting and X‐ray detection.
Along with the technology evolution for dense integration of high-power, high-frequency devices in electronics, the accompanying interfacial heat transfer problem leads to urgent demands for advanced ...thermal interface materials (TIMs) with both high through-plane thermal conductivity and good compressibility. Most metals have satisfactory thermal conductivity but relatively high compressive modulus, and soft silicones are typically thermal insulators (0.3 W m–1 K–1). Currently, it is a great challenge to develop a soft material with the thermal conductivity up to metal level for TIM application. This study solves this problem by constructing a graphene-based microstructure composed of mainly vertical graphene and a thin cap of horizontal graphene layers on both the top and bottom sides through a mechanical machining process to manipulate the stacked architecture of conventional graphene paper. The resultant graphene monolith has an ultrahigh through-plane thermal conductivity of 143 W m–1 K–1, exceeding that of many metals, and a low compressive modulus of 0.87 MPa, comparable to that of silicones. In the actual TIM performance measurement, the system cooling efficiency with our graphene monolith as TIM is 3 times as high as that of the state-of-the-art commercial TIM, demonstrating the superior ability to solve the interfacial heat transfer issues in electronic systems.
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Grain boundaries (GBs) in polycrystalline materials act as impediments to dislocation motion and result in strengthening. Understanding slip transmission through GBs, specifically ...twin boundaries, is essential to understand the plastic deformation behavior of polycrystalline fcc materials. In this study the interaction between a glide dislocation and Σ3{112} incoherent twin boundary (ITB) in copper is investigated using a combined atomistic and mesoscale approach. The material parameters and structure of the GB in the mesoscale phase field dislocation dynamics (PFDD) model are informed from Molecular Statics (MS) simulations. The structural unit of the ITB consists of an array of three partial dislocations. The interaction between a glide dislocation impinging on each of the GB partial dislocations is investigated using both PFDD and Molecular Dynamics (MD) with two boundary conditions. Transmission planes predicted by both PFDD and MD (NVT) are in agreement, and show that not all transmission events are direct. Critical transmission stresses predicted by PFDD are in the range of 276 MPa to 1380 MPa, while MD predictions are in the range from 100 MPa to 700 MPa. The PFDD and MD predictions of slip transmission are explained using dislocation theory based on isotropic linear elasticity.
Highlights • 39 cohort and 2 case-control studies involving 990,649 participants are reached. • We evaluate study quality using the Newcastle–Ottawa Scale. • Statin use before or after cancer ...diagnosis improves survival of cancer patients. • The dose–response effects of postdiagnosis statin use on mortality is assessed.
Polar auxin transport, mediated by influx and efflux transporters, controls many aspects of plant growth and development. The auxin influx carriers in Arabidopsis have been shown to control lateral ...root development and gravitropism, but little is known about these proteins in rice. This paper reports on the functional characterization of OsAUX1. Three OsAUX1 T‐DNA insertion mutants and RNAi knockdown transgenic plants reduced lateral root initiation compared with wild‐type (WT) plants. OsAUX1 overexpression plants exhibited increased lateral root initiation and OsAUX1 was highly expressed in lateral roots and lateral root primordia. Similarly, the auxin reporter, DR5‐GUS, was expressed at lower levels in osaux1 than in the WT plants, which indicated that the auxin levels in the mutant roots had decreased. Exogenous 1‐naphthylacetic acid (NAA) treatment rescued the defective phenotype in osaux1‐1 plants, whereas indole‐3‐acetic acid (IAA) and 2,4‐D could not, which suggested that OsAUX1 was a putative auxin influx carrier. The transcript levels of several auxin signalling genes and cell cycle genes significantly declined in osaux1, hinting that the regulatory role of OsAUX1 may be mediated by auxin signalling and cell cycle genes. Overall, our results indicated that OsAUX1 was involved in polar auxin transport and functioned to control auxin‐mediated lateral root initiation in rice.
In this study, we detail investigated function of OsAUX1 (LOC_Os01g63770). OsAUX1 was abundantly expressed in root tips, lateral roots and lateral root primordial, three OsAUX1 T‐DNA mutants and RNAi plants exhibited a reduced number of primordia and lateral roots, and the overexpression lines exhibited an increased number of primordia and lateral roots. Analysis of IAA content detection and DR5::GUS expression suggested that there was significant reduction in auxin levels in the root tips of osaux1 mutants, and transcriptome analysis also showed that expressions of several auxin regulated genes were altered in osaux1. The results indicated that OsAUX1 was involved in polar auxin transport and controlled lateral root initiation in rice.
Hospital readmission costs a lot of money every year. Many hospital readmissions are avoidable, and excessive hospital readmissions could also be harmful to the patients. Accurate prediction of ...hospital readmission can effectively help reduce the readmission risk. However, the complex relationship between readmission and potential risk factors makes readmission prediction a difficult task. The main goal of this paper is to explore deep learning models to distill such complex relationships and make accurate predictions.
We propose CONTENT, a deep model that predicts hospital readmissions via learning interpretable patient representations by capturing both local and global contexts from patient Electronic Health Records (EHR) through a hybrid Topic Recurrent Neural Network (TopicRNN) model. The experiment was conducted using the EHR of a real world Congestive Heart Failure (CHF) cohort of 5,393 patients.
The proposed model outperforms state-of-the-art methods in readmission prediction (e.g. 0.6103 ± 0.0130 vs. second best 0.5998 ± 0.0124 in terms of ROC-AUC). The derived patient representations were further utilized for patient phenotyping. The learned phenotypes provide more precise understanding of readmission risks.
Embedding both local and global context in patient representation not only improves prediction performance, but also brings interpretable insights of understanding readmission risks for heterogeneous chronic clinical conditions.
This is the first of its kind model that integrates the power of both conventional deep neural network and the probabilistic generative models for highly interpretable deep patient representation learning. Experimental results and case studies demonstrate the improved performance and interpretability of the model.
The effect of extracellular polysaccharides on the structural stability of granular sludge is widely recognized, and determining their mechanism of action on the stability of granules remains ...challenging. Herein, enzymatic experiments were used to systematically study the stability changes and internal mechanisms of anammox granular sludge following hydrolysis of extracellular proteins and polysaccharides (PS). The results revealed that the selective hydrolysis of the proteins hardly affected the stability of the granules, while the hydrolysis of the PS branched chains caused the granules to disintegrate. The hydrolysis of the PS chains in the EPS matrix decreased the degree of branching, width and height via nuclear magnetic resonance (NMR) spectroscopy and atomic force microscopy (AFM), and these parameters are closely related to granular stability. Moreover, scanning electron microscopy (SEM) showed a large number of pores and cracks on the granules, bacterial adhesion decreased, and the EPS adhered to the surface of the granules dissolved. The changes in the gel characteristics of the granules were studied by rheology, and the mechanical strength and viscosity of the granular sludge decreased. For the surface characteristics of granules, the zeta potential and hydrophobicity both decreased, revealing that changes in the branched-chain configuration of the PS and the degree of branching caused granular disintegration. Spectral analysis showed that the hydrolysis of the branch points and the branched glycosides of PS led to a higher proportion of hydrophilic and electronegative groups in the EPS matrix, which hindered bacterial aggregation and reduced anammox granule stability. This investigation clarifies the impact of the branched-chain configuration of the PS and their degree of branching on anammox granule stability, which will promote the further application of anammox granules.
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•The total protein and polysaccharide is not a parameter to the granular stability.•Changes of polysaccharide chains were characterized by AFM.•Polysaccharide branched chains affected granular mechanical strength and viscosity.•Polysaccharide branched chains affected granular zeta potential and hydrophobicity.•Granular stability and polysaccharide branched structure is well correlated.
Graph domain adaptation (GDA) aims to address the challenge of limited label data in the target graph domain. Existing methods such as UDAGCN, GRADE, DEAL, and COCO for different-level (node-level, ...graph-level) adaptation tasks exhibit variations in domain feature extraction, and most of them solely rely on representation alignment to transfer label information from a labeled source domain to an unlabeled target domain. However, this approach can be influenced by irrelevant information and usually ignores the conditional shift of the downstream predictor. To effectively address this issue, we introduce a target-oriented unsupervised graph domain adaptive framework for graph adaptation called TO-UGDA. Particularly, domain-invariant feature representations are extracted using graph information bottleneck. The discrepancy between two domains is minimized using an adversarial alignment strategy to obtain a unified feature distribution. Additionally, the meta pseudo-label is introduced to enhance downstream adaptation and improve the model's generalizability. Through extensive experimentation on real-world graph datasets, it is proved that the proposed framework achieves excellent performance across various node-level and graph-level adaptation tasks.
In some emerging wireless applications, such as wearable communication and low-power sensor network applications, wireless devices or nodes not only require simple physical implementation approaches ...but also require certain reliable receiver techniques to overcome the effects of multipath or shadowed fading. Switched diversity combining (SDC) systems could be a simple and promising solution to the above requirements. Recently, a Fisher-Snedecor ℱ composited fading model has gained much interest because of its modeling accuracy and calculation tractability. However, the performance of SDC systems over ℱ fading channels has not yet been analyzed in the open literature. To this end, this paper presents a systematic analysis of SDC systems over ℱ fading channels, including dual-branch switch-and-stay combining (SSC), multibranch switch-and examine combining (SEC), and SEC with post-examining selection (SECps) systems. We first investigate the statistical characteristics of univariate and bivariate ℱ distributions. Then, these statistical expressions are introduced into the above SDC systems and the statistical metrics of the output signal-to-noise ratio (SNR) for these systems are deduced in different ℱ fading scenarios. Thirdly, certain exact and novel expressions of performance criteria, such as the outage probability, the average bit error probability and average symbol error probability, as well as the average channel capacity for SSC, SEC, and SECps are derived. To find the optimum performance, optimal analysis is performed for the independent and identically distributed cases. Finally, numerical evaluation and simulations are carried out to demonstrate the validity of the theoretical analysis under various ℱ fading scenarios. According to the obtained results, the multipath fading parameter has more influence on the performance of SDC systems than the shadowing parameter, the correlation coefficient, or the average SNR. Importantly, the SDC systems can provide switched diversity gains only when the switching threshold is not too large or too small compared to the average SNR.
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