Flexible materials with the ability to be bent, strained, or twisted play a critical role in soft robots and stretchable electronics. Although tremendous efforts are focused on developing new ...stretchable materials with excellent stability, inevitable mechanical damage due to long term deformation is still an urgent problem to be tackled. Here, a magnetic healing method based on Fe‐doped liquid metal (Fe‐GaIn) conductive ink via a noncontact way is proposed. Further, multifunctional flexible electronics are designed with combined performances of superior remote self‐healing under magnetic field, water‐degradable, and thermal transfer printing, which attribute to three parts of the materials including Fe‐GaIn conductive ink, degradable PVA substrate, and adhesive fructose. The as‐made light emitting diodes (LED) circuit is demonstrated with both structural and functional repairing after single or multipoint damage. The self‐healing time from multipoint damage is pretty fast within 10 s. Due to the water‐soluble PVA film, the recycling process is simple via immersing into water. Through heating, the electric circuit on fructose can be transferred to other flexible substrate with high efficiency, which broadens the practical applications of the present system. The novel and multifunctional electronics hold great promise for self‐healing electronics, transient electronics, and soft robots.
Multifunctional flexible electronics involving integrated features of remote self‐healing, water‐degradable and thermal transfer printing are developed. Here, a magnetic healing approach is proposed based on Fe‐doped liquid metal (Fe‐GaIn) conductive ink, which is demonstrated with both structural and functional repair under magnetic field with a magnet after single or multipoint damage.
Abstract
The errors of cosmological data generated from complex processes, such as the observational Hubble parameter data (OHD) and the Type Ia supernova (SN Ia) data, cannot be accurately modeled ...by simple analytical probability distributions, e.g., a Gaussian distribution. To constrain cosmological parameters from these data, likelihood-free inference is usually used to bypass the direct calculation of the likelihood. In this paper, we propose a new procedure to perform likelihood-free cosmological inference using two artificial neural networks (ANNs), the masked autoregressive flow (MAF) and the denoising autoencoder (DAE). Our procedure is the first to use DAE to extract features from data, in order to simplify the structure of MAF needed to estimate the posterior. Tested on simulated Hubble parameter data with a simple Gaussian likelihood, the procedure shows the capability of extracting features from data and estimating posterior distributions without the need of tractable likelihood. We demonstrate that it can accurately approximate the real posterior, achieve performance comparable to the traditional Markov chain Monte Carlo method, and MAF obtains better training results for a small number of simulation when the DAE is added. We also discuss the application of the proposed procedure to OHD and Pantheon SN Ia data, and use them to constrain cosmological parameters from the non-flat ΛCDM model. For SNe Ia, we use fitted light-curve parameters to find constraints on
H
0
, Ω
m
, and Ω
Λ
similar to relevant work, using less empirical distributions. In addition, this work is also the first to use a Gaussian process in the procedure of OHD simulation.
Breaking bad: Efficient copper‐catalyzed CF bond activation has been achieved by replacing fluorine with hydrogen. A copper hydride is proposed as the active intermediate, which proceeds through a ...nucleophilic attack on the fluorocarbon, as determined by experimental and theoretical results (see structure; C gray, H white, Cu light red, F light blue; distances in Å).
Deoxynivalenol (DON) in raw and processed grain poses significant risks to human and animal health. In this study, the feasibility of classifying DON levels in different genetic lines of barley ...kernels was evaluated using hyperspectral imaging (HSI) (382-1030 nm) in tandem with an optimized convolutional neural network (CNN). Machine learning methods including logistic regression, support vector machine, stochastic gradient descent, K nearest neighbors, random forest, and CNN were respectively used to develop the classification models. Spectral preprocessing methods including wavelet transform and max-min normalization helped to enhance the performance of different models. A simplified CNN model showed better performance than other machine learning models. Competitive adaptive reweighted sampling (CARS) in combination with successive projections algorithm (SPA) was applied to select the best set of characteristic wavelengths. Based on seven wavelengths selected, the optimized CARS-SPA-CNN model distinguished barley grains with low levels of DON (<5 mg/kg) from those with higher levels (5 mg/kg < DON ≤ 14 mg/kg) with an accuracy of 89.41%. The lower levels of DON class I (0.19 mg/kg ≤ DON ≤ 1.25 mg/kg) and class II (1.25 mg/kg < DON ≤ 5 mg/kg) were successfully distinguished based on the optimized CNN model, yielding a precision of 89.81%. The results suggest that HSI in tandem with CNN has great potential for discrimination of DON levels of barley kernels.
•Quantified the relationship between urban expansion and habitat quality in densely populated areas.•A coupled FLUS and InVEST model that includes the land use simulation and habitat quality ...assessment was developed.•The characteristics of urban expansion and habitat quality changes under different scenarios were analyzed.
The conflict between the human-environment is more prominent in densely populated areas (DPA) where urban expansion is increasingly disturbing the ecological environment, resulting in significant damage to habitat quality (HQ). However, a few studies have examined the impacts of urban expansion on HQ in the DPA under different scenarios, especailly in the Yellow River Basin. Therefore, we quantitatively analyzed the impacts of urban expansion on HQ from 1990 to 2018 by coupling the FLUS-InVEST model and predicted the changes of urban expansion and HQ by 2030. The results showed that: (1) the urban expansion rate of DPA was 46.4%. Among them, Hohhot-Baotou-Ordos-Yulin (HBOY) urban agglomeration expanded at the highest rate, with an expansion intensity of 0.16%. The urban expansion pattern was mainly edge expansion. (2) The overall HQ decreased by 1.6%. The HQ patch level was affected by urban expansion, and the higher-level habitat patches were easily shifted to lower-level habitat patches. Low HQ patches increased by 38.6% while high HQ gradually decreased. (3) Under the natural development scenario, the rate of urban expansion was 28.9% and HQ decreased by 2.9%. However, HQ only descesaed by 0.8% under HQ constraint scenario, indicating that urban expansion in a constrained way is of great benefit to improve HQ. These results provide a reference for ecological conservation and sustainable development in DPA.
We report on the observation of photoassociation resonances in ultracold collisions between ^{23}Na^{40}K molecules and ^{40}K atoms. We perform photoassociation in a long-wavelength optical dipole ...trap to form deeply bound triatomic molecules in electronically excited states. The atom-molecule Feshbach resonance is used to enhance the free-bound Franck-Condon overlap. The photoassociation into well-defined quantum states of excited triatomic molecules is identified by observing resonantly enhanced loss features. These loss features depend on the polarization of the photoassociation lasers, allowing us to assign rotational quantum numbers. The observation of ultracold atom-molecule photoassociation resonances paves the way toward preparing ground-state triatomic molecules, provides a new high-resolution spectroscopy technique for polyatomic molecules, and is also important to atom-molecule Feshbach resonances.
Crude oil leakage from tankers, offshore platforms, drilling rigs and wells, causing severe pollution to the environment has led to irreversible damage to ocean habitat and inhabitants. It has become ...one of the greatest global environmental concerns which has recently attracted major public awareness. In addition, the contamination of sea and inhabitants. It has significantly harmed the fishing and seafood industry, and even raises health and life issues for millions of human beings. Until now, there is still no viable and practical method to effectively reduce the damage from crude oil spill. This has attracted numerous researchers’ attention. For developing an environmentally friendly and cost-effective polymer absorbent for oil spill cleaning. Recently, among all the efforts, it is proven that biomass aerogel can be used as an outstanding absorbent for oil–water separation, which is a feasible solution for tackling the crude oil issue. In this article, a comprehensive review on the current state-of-art for biomass-based aerogels utilised in the field of oil/water separation is provided. This includes the preparation procedures, fabrication processes, and the categorisation of various types of aerogels. Additionally, the future direction and technological advancement will be discussed in detail.
Graphic abstract
Epstein‐Barr virus (EBV) infection is prevalent in global population and associated with multiple malignancies and autoimmune diseases. During the infection, EBV‐harbored or infected cell‐expressing ...antigen could elicit a variety of antibodies with significant role in viral host response and pathogenesis. These antibodies have been extensively evaluated and found to be valuable in predicting disease diagnosis and prognosis, exploring disease mechanisms, and developing antiviral agents. In this review, we discuss the versatile roles of EBV antibodies as important biomarkers for EBV‐related diseases, potential driving factors of autoimmunity, and promising therapeutic agents for viral infection and pathogenesis.
Indigenous Tibetan people have lived on the Tibetan Plateau for millennia. There is a long-standing question about the genetic basis of high-altitude adaptation in Tibetans. We conduct a genome-wide ...study of 7.3 million genotyped and imputed SNPs of 3,008 Tibetans and 7,287 non-Tibetan individuals of Eastern Asian ancestry. Using this large dataset, we detect signals of high-altitude adaptation at nine genomic loci, of which seven are unique. The alleles under natural selection at two of these loci methylenetetrahydrofolate reductase (MTHFR) and EPAS1 are strongly associated with blood-related phenotypes, such as hemoglobin, homocysteine, and folate in Tibetans. The folate-increasing allele of rs1801133 at the MTHFR locus has an increased frequency in Tibetans more than expected under a drift model, which is probably a consequence of adaptation to high UV radiation. These findings provide important insights into understanding the genomic consequences of high-altitude adaptation in Tibetans.
•MiRNA expression profiles of brain from different species after traumatic brain injury (TBI) were summarized.•MiRNA expression profile in blood and CSF of humans was summarized.•Specific microRNAs ...were singled out and summarized based on their known regulating function in TBI.•The prospects and difficulties involved in the clinical application of miRNAs were discussed.
Traumatic brain injury (TBI) is a public health problem that causes high mortality and disability worldwide. Secondary brain damage from this type of injury may cause brain edema, blood–brain barrier destruction, and neurological dysfunction. MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression at the post-transcriptional level and play vital roles in maintaining and regulating physiological function. Notably, studies suggest that miRNA levels are altered in the cerebral cortex and hippocampus of rats and mice after TBI. These miRNAs exhibit promoting or inhibiting effects on the formation of secondary brain damage, such as promotion of neuron regeneration and apoptosis, alleviation of leakage across the blood–brain barrier (BBB), disruption of intracellular transport, and decreasing the inflammatory response. miRNA levels are also altered in the blood and cerebral spinal fluid (CSF) of humans with TBI. Some special miRNAs in blood were used in clinical trials for TBI diagnosis and prognosis prediction. Treatment with miRNA agomirs or antagomirs alleviated the lesion volume and improved neurological deficits post-injury. We review the current progress of miRNA studies in TBI patients and animal models and identify the prospects and difficulties involved in the clinical applications of miRNAs.
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