Ligand Selectivity in the Recognition of Protoberberine Alkaloids by Hybrid-2 Human Telomeric G-Quadruplex: Binding Free Energy Calculation, Fluorescence Binding, and NMR Experiments

The human telomeric G-quadruplex (G4) is an attractive target for developing anticancer drugs. Natural products protoberberine alkaloids are known to bind human telomeric G4 and inhibit telomerase. Among several structurally similar protoberberine alkaloids, epiberberine (EPI) shows the greatest specificity in recognizing the human telomeric G4 over duplex DNA and other G4s. Recently, NMR study revealed that EPI recognizes specifically the hybrid-2 form human telomeric G4 by inducing large rearrangements in the 50-flanking segment and loop regions to form a highly extensive four-layered binding pocket. Using the NMR structure of the EPI-human telomeric G4 complex, here we perform molecular dynamics free energy calculations to elucidate the ligand selectivity in the recognition of protoberberines by the human telomeric G4. The MM-PB(GB)SA (molecular mechanics-Poisson Boltzmann/Generalized Born) Surface Area) binding free energies calculated using the Amber force fields bsc0 and OL15 correlate well with the NMR titration and binding affinity measurements, with both calculations correctly identifying the EPI as the strongest binder to the hybrid-2 telomeric G4 wtTel26. The results demonstrated that accounting for the conformational flexibility of the DNA-ligand complexes is crucially important for explaining the ligand selectivity of the human telomeric G4. While the MD-simulated (molecular dynamics) structures of the G-quadruplex-alkaloid complexes help rationalize why the EPI-G4 interactions are optimal compared with the other protoberberines, structural deviations from the NMR structure near the binding site are observed in the MD simulations. We have also performed binding free energy calculation using the more rigorous double decoupling method (DDM); however, the results correlate less well with the experimental trend, likely due to the difficulty of adequately sampling the very large conformational reorganization in the G4 induced by the protoberberine binding

Asynchronous Photoexcited Electronic and Structural Relaxation in Lead-Free Perovskites

Vacancy-ordered lead-free perovskites with more-stable crystalline structures have been intensively explored as the alternatives for resolving the toxic and long-term stability issues of lead halide perovskites (LHPs). The dispersive energy bands produced by the closely packed halide octahedral sublattice in these perovskites are meanwhile anticipated to facility the mobility of charge carriers. However, these perovskites suffer from unexpectedly poor charge carrier transport. To tackle this issue, we have employed the ultrafast, elemental-specific X-ray transient absorption (XTA) spectroscopy to directly probe the photoexcited electronic and structural dynamics of a prototypical vacancy-ordered lead-free perovskite (Cs3Bi2Br9). We have discovered that the photogenerated holes quickly self-trapped at Br centers, simultaneously distorting the local lattice structure, likely forming small polarons in the configuration of Vk center (Br2– dimer). More significantly, we have found a surprisingly long-lived, structural distorted state with a lifetime of ∼59 μs, which is ∼3 orders of magnitude slower than that of the charge carrier recombination. Such long-lived structural distortion may produce a transient “background” under continuous light illumination, influencing the charge carrier transport along the lattice framework

Modulating electron density of vacancy site by single Au atom for effective CO2_{2} photoreduction

The surface electron density significantly affects the photocatalytic efficiency, especially the photocatalytic CO$_{2}$ reduction reaction, which involves multi-electron participation in the conversion process. Herein, we propose a conceptually different mechanism for surface electron density modulation based on the model of Au anchored CdS. We firstly manipulate the direction of electron transfer by regulating the vacancy types of CdS. When electrons accumulate on vacancies instead of single Au atoms, the adsorption types of CO$_{2}$ change from physical adsorption to chemical adsorption. More importantly, the surface electron density is manipulated by controlling the size of Au nanostructures. When Au nanoclusters downsize to single Au atoms, the strong hybridization of Au 5d and S 2p orbits accelerates the photo-electrons transfer onto the surface, resulting in more electrons available for CO$_{2}$ reduction. As a result, the product generation rate of Au$_{SA}$/Cd$_{1-x}$S manifests a remarkable at least 113-fold enhancement compared with pristine Cd$_{1-x}$S

A 6G White Paper on Connectivity for Remote Areas

In many places all over the world rural and remote areas lack proper connectivity that has led to increasing digital divide. These areas might have low population density, low incomes, etc., making them less attractive places to invest and operate connectivity networks. 6G could be the first mobile radio generation truly aiming to close the digital divide. However, in order to do so, special requirements and challenges have to be considered since the beginning of the design process. The aim of this white paper is to discuss requirements and challenges and point out related, identified research topics that have to be solved in 6G. This white paper first provides a generic discussion, shows some facts and discusses targets set in international bodies related to rural and remote connectivity and digital divide. Then the paper digs into technical details, i.e., into a solutions space. Each technical section ends with a discussion and then highlights identified 6G challenges and research ideas as a list.Comment: A 6G white paper, 17 page

Improved Stability Criteria for Delayed Neural Networks via a Relaxed Delay-Product-Type Lapunov–Krasovskii Functional

In this paper, the asymptotic stability problem of neural networks with time-varying delays is investigated. First, a new sufficient and necessary condition on a general polynomial inequality was developed. Then, a novel augmented Lyapunov–Krasovskii functional (LKF) was constructed, which efficiently introduces some new terms related to the previous information of neuron activation function. Furthermore, based on the suitable LKF and the stated negative condition of the general polynomial, two criteria with less conservatism were derived in the form of linear matrix inequalities. Finally, two numerical examples were carried out to confirm the superiority of the proposed criteria, and a larger allowable upper bound of delays was achieved

Effect of Chickpea Flour on Noodle Quality and Glycemic Index

To improve the application scope and economic value of chickpea, chickpea flour with different additions (0%, 10%, 20%, 30%, and 40%) was mixed with wheat flour to make noodles. Texture quality, cooking quality, microstructure, and glycemic index (GI) were used to explore the effects of chickpea flour on noodles' processing quality and functional quality. The results showed that the addition of chickpea flour in the range of 0% to 20% had no significant effect on the texture quality, cooking quality, and microstructure of noodles. However, the texture quality and cooking quality of noodles were significantly reduced and the microstructure was significantly damaged when the addition amount was in the range of 20%~40%. The higher addition amount of chickpea flour deteriorated the processing quality of noodles. 0%, 10%, 20%, 30%, and 40% additions of chickpea flour noodles in vitro enzymatic method of the GI values were 76.97±0.49, 67.19±0.84, 64.95±0.71, 63.24±0.29 and 61.84±0.55, respectively. All belonged to middle GI food. The order of postprandial blood glucose in mice after gavage was wheat flour noodles>10% added chickpea flour noodles>20% added chickpea flour noodles>30% added chickpea flour noodles>40% added chickpea flour noodles. It was consistent with the results of in vitro enzymatic method. In summary, the addition of chickpea flour below 20% could improve the processing quality of noodles. The addition of chickpea flour could significantly reduce the digestive properties of starch. It would provide more choices for the diet of special populations such as diabetes

Reconstruction Mode of Rural Dilapidated Houses in Alpine and Gorge Area of Southwest China—A Case Study of Scientific Identification and Precision Reconstruction of Rural Dilapidated Houses in Luquan County, Yunnan Province

The transformation of dilapidated houses in rural areas is not only a livelihood project related to the broad masses of rural people, but also a major project to win the battle against poverty. Luquan Yi and Miao Autonomous County, Yunnan Province, located in the high mountain and gorge area along Jinsha River, is one of the key counties of poverty alleviation and development with a wide range of poverty and a deep degree of poverty. The incidence of poverty is 22.21%. Housing security is the focus, difficulty and emphasis of poverty alleviation in this county, the number of dilapidated houses is large, the type is complex, the transformation is difficult, and the implementation cost is high. Since the beginning of 2017, Luquan County has faced difficulties, explored in depth, pioneered and innovated, and completed the renovation of 54801 dilapidated houses in an all-round way. It created a road full of characteristics and effectiveness of rural dilapidated housing transformation, and explored a set of effective scientific identification and accurate transformation models for rural dilapidated housing worthy of reference and promotion. Successful renovation of dilapidated houses, combined with industrial poverty alleviation, education poverty alleviation, health poverty alleviation and other accurate poverty alleviation measures, have made Luquan County win a decisive victory in the fight against poverty. By the end of December 2018, the incidence of poverty in the county had dropped to 0.54 percent, and 115 poor villages (including 83 extremely poor villages) had successfully shaken off poverty.This paper analyzes and summarizes the concrete methods, main effects, characteristics and bright spots, successful experience, and reference significance of the scientific identification and precise transformation mode of rural dilapidated houses in this county, so as to provide a necessary reference for the transformation of rural dilapidated houses in Yunnan Province and even poor counties in similar provinces (cities and districts)

Experimental Characterization of Laser Trepanned Microholes in Superalloy GH4220 with Water-Based Assistance

An experiment using water-assisted millisecond laser trepanning on superalloy GH4220 was carried out, and the effects of pulse energy on the hole entrance morphology, diameter, roundness, cross-section morphology, taper angle, sidewall roughness, and recast layer in air and with water-based assistance were compared and analyzed. The results show that, compared with the air condition, the water-based assistance improved the material removal rate and hole quality, increased the diameter of the hole entrance and exit, increased the hole roundness, decreased the hole taper angle, decreased the hole sidewall roughness, and reduced the recast layer thickness. In addition, under the combined action of water and steam inside the hole, the sidewall surface morphology quality was improved. Compared with the air condition, the spatter around the hole entrance was reduced, but the oxidation phenomenon formed by the thermal effect surrounding the hole entrance with water-based assistance was more obvious. The research provided technical support for the industrial application of millisecond laser drilling

Formamidinium Lead Bromide (FAPbBr3) Perovskite Microcrystals for Sensitive and Fast Photodetectors

Because of the good thermal stability and superior carrier transport characteristics of formamidinium lead trihalide perovskite HC(NH2)2PbX3 (FAPbX3), it has been considered to be a better optoelectronic material than conventional CH3NH3PbX3 (MAPbX3). Herein, we fabricated a FAPbBr3 microcrystal-based photodetector that exhibited a good responsivity of 4000 A W−1 and external quantum efficiency up to 106% under one-photon excitation, corresponding to the detectivity greater than 1014 Jones. The responsivity is two orders of magnitude higher than that of previously reported formamidinium perovskite photodetectors. Furthermore, the FAPbBr3 photodetector’s responsivity to two-photon absorption with an 800-nm excitation source can reach 0.07 A W−1, which is four orders of magnitude higher than that of its MAPbBr3 counterparts. The response time of this photodetector is less than 1 ms. This study provides solid evidence that FAPbBr3 can be an excellent candidate for highly sensitive and fast photodetectors.[Figure not available: see fulltext.]

Improving Covariance-Regularized Discriminant Analysis for EHR-Based Predictive Analytics of Diseases

Linear Discriminant Analysis (LDA) is a well-known technique for feature extraction and dimension reduction. The performance of classical LDA however, significantly degrades on the High Dimension Low Sample Size (HDLSS) data for the ill-posed inverse problem. Existing approaches for HDLSS data classification typically assume the data in question are with Gaussian distribution and deal the HDLSS classification problem with regularization. However, these assumptions are too strict to hold in many emerging real-life applications, such as enabling personalized predictive analysis using Electronic Health Records (EHRs) data collected from an extremely limited number of patients who have been diagnosed with or without the target disease for prediction. In this paper, we revised the problem of predictive analysis of disease using personal EHR data and LDA classifier. To fill the gap, in this paper, we first studied an analytical model that understands the accuracy of LDA for classifying data with arbitrary distribution. The model gives a theoretical upper bound of LDA error rate that is controlled by two factors: (1) the statistical convergence rate of (inverse) covariance matrix estimators and (2) the divergence of the training/testing datasets to fitted distributions. To this end, we could lower the error rate by balancing the two factors for better classification performance. Hereby, we further proposed a novel LDA classifier De-Sparse that leverages De-sparsified Graphical Lasso to improve the estimation of LDA, which outperforms state-of-the-art LDA approaches developed for HDLSS data. Such advances and effectiveness are further demonstrated by both theoretical analysis and extensive experiments on EHR datasets