Nucleic acid (NA) computation has been widely developed in the past years to solve kinds of logic and mathematic issues in both information technologies and biomedical analysis. However, the ...difficulty to integrate non‐NA molecules limits its power as a universal platform for molecular computation. Here, we report a versatile prototype of hybridized computation integrated with both nucleic acids and non‐NA molecules. Employing the conformationally controlled ligand converters, we demonstrate that non‐NA molecules, including both small molecules and proteins, can be computed as nucleic acid strands to construct the circuitry with increased complexity and scalability, and can be even programmed to solve arithmetical calculations within the computational nucleic acid system. This study opens a new door for molecular computation in which all‐NA circuits can be expanded with integration of various ligands, and meanwhile, ligands can be precisely programmed by the nuclei acid computation.
With utilization of conformationally controlled ligand converters, different kinds of non‐nucleic acid molecules, including both small molecules and proteins, can be integrated into nucleic acid computation to construct circuitries with increased complexity and scalability and to even perform algorithmic calculations. This hybridized system establishes a universal platform for molecular computation.
The coronavirus disease 2019 (COVID-19) virus is spreading rapidly, and scientists are endeavoring to discover drugs for its efficacious treatment in China. Chloroquine phosphate, an old drug for ...treatment of malaria, is shown to have apparent efficacy and acceptable safety against COVID-19 associated pneumonia in multicenter clinical trials conducted in China. The drug is recommended to be included in the next version of the Guidelines for the Prevention, Diagnosis, and Treatment of Pneumonia Caused by COVID-19 issued by the National Health Commission of the People's Republic of China for treatment of COVID-19 infection in larger populations in the future.
Dynamic covalent polymer networks (DCPN) have historically attracted attention for their unique roles in chemical recycling and self-healing, which are both relevant for sustainable societal ...development. Efforts in these directions have intensified in the past decade with notable progress in newly discovered dynamic covalent chemistry, fundamental material concepts, and extension toward emerging applications including energy and electronic devices. Beyond that, the values of DCPN in discovering/designing functional properties not offered by classical thermoplastic and thermoset polymers have recently gained traction. In particular, the dynamic bond exchangeability of DCPN has shown unparalleled design versatility in various areas including shape-shifting materials/devices, artificial muscles, and microfabrication. Going beyond this basic bond exchangeability, various molecular mechanisms to manipulate network topologies (topological transformation) have led to opportunities to program polymers, with notable concepts such as living networks and topological isomerization. In this review, we provide an overview of the above progress with particular focuses on molecular design strategies for the exploitation of functional material properties. Based on this, we point out the remaining issues and offer perspectives on how this class of materials can shape the future in ways that are complementary with classical thermoplastic and thermoset polymers.
The spatial characteristics of cracks are significant indicators to assess and evaluate the health of existing buildings and infrastructures. However, the current manual crack description method is ...time consuming and labor consuming. To improve the efficiency of crack inspection, advanced computer vision‐based techniques have been utilized to detect cracks automatically at image level and grid‐cell level. But existing crack detections are of (high specificity) low generality and inefficient, in terms that conventional approaches are unable to identify and measure diverse cracks concurrently at pixel level. Therefore, this research implements a novel deep learning technique named fully convolutional network (FCN) to address this problem. First, FCN is trained by feeding multiple types of cracks to semantically identify and segment pixel‐wise cracks at different scales. Then, the predicted crack segmentations are represented by single‐pixel width skeletons to quantitatively measure the morphological features of cracks, providing valuable crack indicators for assessment in practice, such as crack topology, crack length, max width, and mean width. To validate the prediction, the predicted segmentations are compared with recent advanced method for crack recognition and ground truth. For crack segmentation, the accuracy, precision, recall, and F1 score are 97.96%, 81.73%, 78.97%, and 79.95%, respectively. For crack length, the relative measurement error varies from −48.03% to 177.79%, meanwhile that ranges from −13.27% to 24.01% for crack width. The results show that FCN is feasible and sufficient for crack identification and measurement. Although the accuracy is not as high as CrackNet because of three types of errors, the prediction has been increased to pixel level and the training time has been dramatically decreased to several per cents of previous methods due to the novel end‐to‐end structure of FCN, which combines typical convolutional neural networks and deconvolutional layers.
Halide perovskite quantum dots (QDs), primarily regarded as optoelectronic materials for LED and photovoltaic devices, have not been applied for photochemical conversion (e.g., water splitting or CO2 ...reduction) applications because of their insufficient stability in the presence of moisture or polar solvents. Herein, we report the use of CsPbBr3 QDs as novel photocatalysts to convert CO2 into solar fuels in nonaqueous media. Under AM 1.5G simulated illumination, the CsPbBr3 QDs steadily generated and injected electrons into CO2, catalyzing CO2 reduction at a rate of 23.7 μmol/g h with a selectivity over 99.3%. Additionally, through the construction of a CsPbBr3 QD/graphene oxide (CsPbBr3 QD/GO) composite, the rate of electron consumption increased 25.5% because of improved electron extraction and transport. This study is anticipated to provide new opportunities to utilize halide perovskite QD materials in photocatalytic applications.
Abstract
Motivation
Linkage disequilibrium (LD) decay is of great interest in population genetic studies. However, no tool is available now to do LD decay analysis from variant call format (VCF) ...files directly. In addition, generation of pair-wise LD measurements for whole genome SNPs usually resulting in large storage wasting files.
Results
We developed PopLDdecay, an open source software, for LD decay analysis from VCF files. It is fast and is able to handle large number of variants from sequencing data. It is also storage saving by avoiding exporting pair-wise results of LD measurements. Subgroup analyses are also supported.
Availability and implementation
PopLDdecay is freely available at https://github.com/BGI-shenzhen/PopLDdecay.
Lead halide perovskite nanocrystals (NCs) have demonstrated great potential as appealing candidates for advanced optoelectronic applications. However, the toxicity of lead and the intrinsic ...instability toward moisture hinder their mass production and commercialization. Herein, to solve such thorny problems, novel lead‐free Cs2AgBiBr6 double perovskite NCs fabricated via a simple hot‐injection method are reported, which exhibit impressive stability in moisture, light, and temperature. Such materials are then applied into photocatalytic CO2 reduction, achieving a total electron consumption of 105 µmol g−1 under AM 1.5G illumination for 6 h. This study offers a reliable avenue for Cs2AgBiBr6 perovskite nanocrystals preparation, which holds a great potential in the further photochemical applications.
Stable lead‐free Cs2AgBiBr6 double perovskite nanocrystals with a cubic shape and an average size of 9.5 nm are successfully synthesized via the hot‐injection route, and are employed as photocatalysts to convert CO2 into solar fuels (CO and CH4). This work offers a reliable avenue for Cs2AgBiBr6 perovskite nanocrystals preparation, which holds a great potential in the further photochemical applications.
Alginate, a linear polymer consisting of β-D-mannuronic acid (M) and α-L-guluronic acid (G) with 1,4-glycosidic linkages and comprising 40% of the dry weight of algae, possesses various applications ...in the food and nutraceutical industries. However, the potential applications of alginate are restricted in some fields because of its low water solubility and high solution viscosity. Alginate oligosaccharides (AOS) on the other hand, have low molecular weight which result in better water solubility. Hence, it becomes a more popular target to be researched in recent years for its use in foods and nutraceuticals. AOS can be obtained by multiple degradation methods, including enzymatic degradation, from alginate or alginate-derived poly G and poly M. AOS have unique bioactivity and can bring human health benefits, which render them potentials to be developed/incorporated into functional food. This review comprehensively covers methods of the preparation and analysis of AOS, and discussed the potential applications of AOS in foods and nutraceuticals.
Autonomous vehicles (AVs) are entering the market, which will have a great impact on future decision making on mode choice in transportation systems. The aim of this study is to explore the ...determinants which influence travelers' intentions to use AVs based on structural equation modelling (SEM). 310 valid sets of data from an online survey were collected to analyze factors which influence travelers' intentions. Data analyses were conducted using IBM SPSS Statistics 23 and AMOS 23. The results showed that personality and preferences in relation to AVs are the main potential factors that cause travelers' AVs use. Attitudes to modal services also affect intentions to use AVs. Personality has a significant positive effect on both attitude and preferences. The results provide exploratory empirical support for all hypotheses. The research results will help understand travelers' choice motivation from psychological and service perspectives, and provide support for governments and enterprises to improve the management and services of autonomous vehicles.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cost‐effective and efficient oxygen‐evolving electrocatalysts are urgently required for energy storage and conversion technologies. In this work, an amorphous trimetallic boride nanocatalyst ...(Fe–Co–2.3Ni–B) prepared by a simple approach is reported as a highly efficient oxygen evolution reaction electrocatalyst. It exhibits an overpotential (η) of 274 mV to deliver a geometric current density (jgeo) of 10 mA cm−2, a small Tafel slope of 38 mV dec−1, and excellent long‐term durability at a mass loading of 0.3 mg cm−2. The impressive electrocatalytic performance originates from the unique amorphous multimetal–metalloid complex nanostructure. From application's point of view, this work holds great promise as this process is simple and allows for large‐scale production of cheap, yet efficient, material.
Amorphous trimetallic boride demonstrates impressive electrocatalytic oxygen evolution activity, which originates from the tuned electronic properties of the constituent elements. Such an earth‐abundant boride electrocatalyst holds great promise for practical applications in water electrosplitting devices as the synthesis process is simple and allows for large‐scale production of cheap, yet efficient, material.
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