Multistep Dissociation of Fluorine Molecules under Extreme Compression.

All elements that form diatomic molecules, such as H_{2}, N_{2}, O_{2}, Cl_{2}, Br_{2}, and I_{2}, are destined to become atomic solids under sufficiently high pressure. However, as revealed by many experimental and theoretical studies, these elements show very different propensity and transition paths due to the balance of reduced volume, lone pair electrons, and interatomic bonds. The study of F under pressure can illuminate this intricate behavior since F, owing to its unique position on the periodic table, can be compared with H, with N and O, and also with other halogens. Nevertheless, F remains the only element whose solid structure evolution under pressure has not been thoroughly studied. Using a large-scale crystal structure search method based on first principles calculations, we find that, before reaching an atomic phase, F solid transforms first into a structure consisting of F_{2} molecules and F polymer chains and then into a structure consisting of F polymer chains and F atoms, a distinctive evolution with pressure that has not been seen in any other elements. Both intermediate structures are found to be metallic and become superconducting, a result that adds F to the elemental superconductors

Deep quantum neural networks equipped with backpropagation on a superconducting processor

Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report the first experimental demonstration of training deep quantum neural networks via the backpropagation algorithm with a six-qubit programmable superconducting processor. In particular, we show that three-layer deep quantum neural networks can be trained efficiently to learn two-qubit quantum channels with a mean fidelity up to 96.0% and the ground state energy of molecular hydrogen with an accuracy up to 93.3% compared to the theoretical value. In addition, six-layer deep quantum neural networks can be trained in a similar fashion to achieve a mean fidelity up to 94.8% for learning single-qubit quantum channels. Our experimental results explicitly showcase the advantages of deep quantum neural networks, including quantum analogue of the backpropagation algorithm and less stringent coherence-time requirement for their constituting physical qubits, thus providing a valuable guide for quantum machine learning applications with both near-term and future quantum devices.Comment: 7 pages (main text) + 11 pages (Supplementary Information), 10 figure

The temporal trend of disease burden attributable to metabolic risk factors in China, 1990–2019 : An analysis of the Global Burden of Disease study

Background and aims: The disease burden attributable to metabolic risk factors is rapidly increasing in China, especially in older people. The objective of this study was to (i) estimate the pattern and trend of six metabolic risk factors and attributable causes in China from 1990 to 2019, (ii) ascertain its association with societal development, and (iii) compare the disease burden among the Group of 20 (G20) countries. Methods: The main outcome measures were disability-adjusted life-years (DALYs) and mortality (deaths) attributable to high fasting plasma glucose (HFPG), high systolic blood pressure (HSBP), high low-density lipoprotein (HLDL) cholesterol, high body-mass index (HBMI), kidney dysfunction (KDF), and low bone mineral density (LBMD). The average annual percent change (AAPC) between 1990 and 2019 was analyzed using Joinpoint regression. Results: For all six metabolic risk factors, the rate of DALYs and death increased with age, accelerating for individuals older than 60 and 70 for DALYs and death, respectively. The AAPC value in rate of DALYs and death were higher in male patients than in female patients across 20 age groups. A double-peak pattern was observed for AAPC in the rate of DALYs and death, peaking at age 20–49 and at age 70–95 plus. The age-standardized rate of DALYs increased for HBMI and LBMD, decreased for HFPG, HSBP, KDF, and remained stable for HLDL from 1990 to 2019. In terms of age-standardized rate of DALYs, there was an increasing trend of neoplasms and neurological disorders attributable to HFPG; diabetes and kidney diseases, neurological disorders, sense organ diseases, musculoskeletal disorders, neoplasms, cardiovascular diseases, digestive diseases to HBMI; unintentional injuries to LBMD; and musculoskeletal disorders to KDF. Among 19 countries of Group 20, in 2019, the age-standardized rate of DALYs and death were ranked fourth to sixth for HFPG, HSBP, and HLDL, but ranked 10th to 15th for LBMD, KDF, and HBMI, despite the number of DALYs and death ranked first to second for six metabolic risk factors. Conclusions: Population aging continuously accelerates the metabolic risk factor driven disease burden in China. Comprehensive and tight control of metabolic risk factors before 20 and 70 may help to mitigate the increasing disease burden and achieve healthy aging, respectively

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Effects of Concentration of Soybean Protein Isolate and Maltose and Oil Phase Volume Fraction on Freeze–Thaw Stability of Pickering Emulsion

There is growing interest in enhancing the freeze–thaw stability of a Pickering emulsion to obtain a better taste in the frozen food field. A Pickering emulsion was prepared using a two-step homogenization method with soybean protein and maltose as raw materials. The outcomes showed that the freeze–thaw stability of the Pickering emulsion increased when prepared with an increase in soybean protein isolate (SPI) and maltose concentration. After three freeze–thaw treatments at 35 mg/mL, the Turbiscan Stability Index (TSI) value of the emulsion was the lowest. At this concentration, the surface hydrophobicity (H0) of the composite particles was 33.6 and the interfacial tension was 44.34 mN/m. Furthermore, the rheological nature of the emulsions proved that the apparent viscosity and viscoelasticity of Pickering emulsions grew with a growing oil phase volume fraction and concentration. The maximum value was reached in the case of the oil phase volume fraction of 50% at a concentration of 35 mg/mL, the apparent viscosity was 18 Pa·s, the storage modulus of the emulsion was 575 Pa, and the loss modulus was 152 Pa. This research is significant for the production of freeze–thaw resistant products, and improvement of protein-stabilized emulsion products with high freeze–thaw stability

Accurate MRCI calculations of the low-lying electronic states of the NCl molecule

Characterization of 22 electronic states of NCl correlating to the two lowest dissociation channels are carried out using high level CASSCF/MRCI calculations with a sextuple-ζ basis set including Davidson modification, core-valence correlation correction and scalar relativistic effects. As far as we know, this radical has never been the preference of theoretical researchers and experimental investigations only concern the ground state and the two low-lying metastable states. Accurate potential energy curves, dissociation energies as well as the equilibrium constants are determined and avoided crossings between the Π symmetry are studied. Moreover, spin-orbit splitting of several states and transition probabilities and radiative lifetimes for some allowed or forbidden transitions are presented

Influence Mechanism of Urban Staggered Shared Parking Policy on Behavioral Intentions of Users and Providers Based on Extended Planned Behavior Theory

Shared parking has been widely accepted as an effective way to deal with the mismatch between parking demand and supply. Especially for adjacent construction areas with mixed residential and commercial land, staggered shared parking has broad application prospects. From the previous practice, the public welfare from the government, the commercial interests of parking enterprises, and the individual income of residents will be the key elements to promote a staggered parking policy in adjacent construction areas. However, the current research on shared parking mainly focused on the commercial factors to improve the operating efficiency and operating benefit for parking enterprises; there is a lack of research on the implementation process of staggered parking policies which will solve residential areas’ parking problem with the interests of residents as the core. Here, this paper focuses on exploring residents’ and businesses’ intention to participate in the process of a staggered shared parking policy, where businesses have certain location and condition qualifications. Firstly, this study used two extended theoretical models of planned behavior to explore the behavioral intentions of users and providers in this staggered shared parking event, respectively. Secondly, the research hypothesis was examined using a structural equation approach, and a questionnaire was designed to survey 323 residents and 282 enterprises in the core urban area of Beijing. Ultimately, the study indicated that, for residents, perceptual behavior control has the greatest impact on the perceived intention, while the perceived ease of use and perceived usefulness play a crucial influential role in the willingness to use staggered shared parking. For companies, attitude has the strongest impact on the perceived intention. Our findings reveal the intrinsic impact mechanism of the policies in the decision-making process, contributing to the precise policy implementation to alleviate the problem of difficult parking for residents, thus improving the city’s parking management

Electrochemical Biosensing Methods for Detecting Epigenetic Modifications

Epigenetic modifications are closely related to diseases and physiological health, mainly including DNA methylation, RNA methylation, histone acetylation, and noncoding RNA. Recently, a large amount of research has been conducted on the detection of epigenetic modifications. Electrochemical biosensors, with their low cost, high sensitivity, high compatibility, and simple operation, have been widely used in the detection of epigenetic biomarkers. This review discusses the detection of epigenetic biomarkers using different electrochemical sensing methods. Here we discuss various aspects, including free labels, signal labeling, signal amplification, nano-based electrodes, and the combined use of other methods. By summarizing the existing electrochemical detection methods for epigenetic modifications, this review also proposes future development trends and challenges for electrochemical biosensors in this field