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Although mass spectrometry (MS) has its unique advantages in speed, specificity and sensitivity, its application in quantitative chiral analysis aimed to determine the proportions of multiple chiral isomers is still a challenge. Herein, we present an artificial neural network (ANN) based approach for quantitatively analyzing multiple chiral isomers from their ultraviolet photodissociation mass spectra. Tripeptide of GYG and iodo-L-tyrosine have been applied as chiral references to fulfill the relative quantitative analysis of four chiral isomers of two dipeptides of L/DHisL/DAla and L/DAspL/DPhe, respectively. The results show that the network can be well-trained with limited sets, and have a good performance in testing sets. This study shows the potential of the new method in rapid quantitative chiral analysis aimed at practical applications, with much room for improvement in the near future, including selecting better chiral references and improving machine learning methods.

Background: A novel method to detect the text region from the natural image using the discriminative deep feature of text regions is presented with deep learning concept in this manuscript. Objective: Curve Text Detection (CTD) from the natural image is generally based on two different tasks: learning of text data and text region detection. In the learning of text data, the goal is to train the system with a sample of letters and natural images, while, in the text region detection, the aim is to confirm whether the detected regions are text region or not. The emphasis of this research is on the development of deep learning algorithm. Methods: A novel approach has been proposed to detect the text region from natural images which simultaneously tackles three combined challenges: 1) pre-processing of the image without losing text region; 2) appropriate segmentation of text region using their strokes, and 3) training of data. In pre-processing, image enhancement and binarization are done then morphological operations are defined with the Maximally Stable Extremal Region (MSER) based segmentation technique which operates on the basis of stroke region of text and then finds out the (Speed Up Robust Feature) SURF key point from those regions. Results: Based on the SURF feature, text region is detected from the images using a trained structure of Artificial Neural Network (ANN) which is based on deep learning mechanism. Conclusion: CTW-1500 dataset is used to simulate the proposed work and the parameters like Precision, Recall, F-Measure (H-mean), Execution time, Accuracy and Error Rate are computed and are compared with the existing work to depict the effectiveness of the work.

Additional file 1: Figure S1. The structure of DBMN. Figure S2. Size (A) and zeta potential (B) distributionof MN, HMN and DBMN tested by DLS. Figure S3. TGA (A) and DSC (B) curves of MN, HMN andDBMN. C) The image of the samples after being subjected to a high temperatureof 1000 °C. Figure S4. UV-Vis absorption spectra of the mainreactants and products. Figure S5. MN and DBMN accumulated over time under the magnetic field. Figure S6. Magnetic responsiveness of T cells after incubatingwith DBMN. Culture plate was shaken every 10 minutes for 0.5 hours. Figure S7. A)The scheme of circulation of DBMN-HEK293T-GFP cells in vitro under the magnetic field. B) Fluorescence image ofcatheter near the magnet (This image was composed of three pictures from top tobottom). Figure S8. The photos of thedevice for verifying the magnetic responsiveness of magnetic cells by IVIS. Figure S9.Fluorescence images of DBMN-HEK293T-GFP cells undermagnetic field, captured by IVIS. Blue dashed box, the magnet. Figure S10.Representative flow cytometry pictures of CD8+ T cells proportion inblood (A), spleens (B) and tumors (C). Figure S11.Representative immunofluorescence images of CD8+T cells and IFN-γ in DBMN-T group. Scale bar, 50 µm. FigureS12.Representative H&E staining photographs of hearts, livers, spleens,lungs and kidneys in each group of mice. Yellow arrow, tumor metastasis site. Scale bar,100 µm. Figure S13. The expression of CD44 on 4T1 cells and E.G7-OVA cells. Left is blank.

Understanding gluon density distributions and how they are modified in nuclei are among the most important goals in nuclear physics. In recent years, diffractive vector meson production measured in ultra-peripheral collisions (UPCs) at heavy-ion colliders has provided a new tool for probing the gluon density. In this Letter, we report the first measurement of $J/\psi$ photoproduction off the deuteron in UPCs at the center-of-mass energy $\sqrt{s_{_{\rm NN}}}=200~\rm GeV$ in d$+$Au collisions. The differential cross section as a function of momentum transfer $-t$ is measured. In addition, data with a neutron tagged in the deuteron-going Zero-Degree Calorimeter is investigated for the first time, which is found to be consistent with the expectation of incoherent diffractive scattering at low momentum transfer. Theoretical predictions based on the Color Glass Condensate saturation model and the gluon shadowing model are compared with the data quantitatively. A better agreement with the saturation model has been observed. With the current measurement, the results are found to be directly sensitive to the gluon density distribution of the deuteron and the deuteron breakup, which provides insights into the nuclear gluonic structure., Comment: Final published version Phys. Rev. Lett. 128, 122303

Supplementary

Background: Pelvic girdle pain (PGP) is a multifactorial condition with a partly unknown etiology. This condition can be mentally and physically compromising both during and after pregnancy. To provide all-round preventive measures to improve the recovery from PGP, it is of a necessity for obstetricians and orthopaedists to develop predictive studies about the worse prognosis for this condition. Therefore, this study aims to determine whether personality traits can predict the consequences of long-term pregnancy-related PGP.Methods: This was a prospective study conducted from January 2015 to August 2018. A total of 387 pregnant women were enrolled in this study. According to whether they had experienced PGP during the past four weeks, the subjects were classified into no PGP and PGP groups. Persistent PGP after the pregnancy was defined as a recurrent or continuous visual analog score (VAS) pain rating of ≥ 3 for more than one week. The Quick Big Five Personality Test (QBFPT) was used to assess personality traits. Data were obtained by mail or in the clinic. The authors collected data including age, BMI, educational level, annual household income, cesarean delivery, breastfeeding, unexpected sex of the baby, parity, sick leave, no or rare ability to take rest breaks at work, and LBP in the previous pregnancy. Results: Of 387 included women, 264 subjects experienced PGP during the pregnancy with the mean age of 26.3 ± 4.5 years. A total of 80 of 264 (30.3%) women experienced persistent PGP after the pregnancy. Persistent PGP after the pregnancy was associated with higher levels of neuroticism (OR= 2.12, P=0.001). Compared to persistent PGP after the pregnancy, women who reported higher levels of extraversion and conscientiousness were more likely to recover from this condition (OR=0.65, P = 0.001; OR= 0.82, P = 0.01, respectively). Besides, neuroticism was positively associated with higher pain scores (r=0.52, P=0.005). However, extraversion and conscientiousness domains showed negative correlations with pain score (r=-0.48, P=0.003; r=-0.36, P=0.001).Conclusions: Personality traits were significantly associated with the outcomes of PGP.

Background Polydatin has been reported to possess remarkable anti-atherosclerotic activities. However, there are different opinions on its regulatory mechanisms. It remains unclear whether the anti-atherosclerotic mechanism of polydatin is related to its autophagic restoration or not. The aim of this study was to explore the question. Methods Using atherosclerotic model induced by high-fat diet in apolipoprotein E-deficient mice, the investigation was performed with polydatin alone or in combination with autophagic inhibitor or inducer intervention. Inhibitory sites of polydatin to PI3K were identified by molecular docking. Results Polydatin can significantly inhibit PI3K/Akt/mTOR pathway proteins expression, improve autophagic dysfunction and reduce atherosclerotic lesions. These effects could be antagonized and reinforced by adding autophagic inhibitor and inducer, respectively. Inhibitory sites of polydatin to PI3K were found to be ASP-810, SER-854, VAL-851, LEU-807, SER-774, LYS-802, ASP-933, SER-919, ASN-920, PHE-930, MEF-922, GLN-859 of PI3Kα. Conclusions The mechanism of polydatin to alleviate atherosclerotic lesions was achieved by autophagic restoration.

Our previous study reported that a more dispersed palygorskite (Pal) with a multiparous structure can be fabricated from rigid nano-rods by ion beam bombardment. In this study, the new multiparous structure of Pal (MPal) was used to carry a nanocomposite prepared from graphitic carbon nitride (CN) and nano zero-valent iron (NZVI) following a simple thermopolymerisation method for the first time. The as-prepared sample (MPal/NZVI/CN) achieved broader light absorption in the visible light region and low recombination, according to the characterisation results of the UV–vis diffuse reflectance and photoluminescence (PL) spectra of the photocatalysts. The photocatalysis of CrVI and methylene blue (MB) in an aqueous solution by MPal/NZVI/CN revealed that the MPal/NZVI/CN-1:5:6 composites exhibited superior catalytic activity, with CrVI and MB removal efficiencies of 98.48% and 99.2% in 120 min, respectively. Additionally, the reaction rate constants (kCr and kMB) of MPal/NZVI/CN were much higher than those of CN, NZVI/CN, and MPal/CN because the formation of MPal and NZVI composites with CN promoted the separation of photo-generated electron-hole pairs. After four cycles, MPal/NZVI/CN exhibited great photoactivity, which could not only be attributed to the improved dispersion of MPal, but also to the ability of the photo-generated electrons of CN to reduce the FeIII/FeII to Fe0. This study opens new opportunities for modifying photocatalysts using the inorganic nanomaterials readily formed by physical irradiation.

Using attapulgite (ATP) as matrix, chitosan (CS) as functional monomer, and introducing the surface ion- imprinting concept, a new Cu(II)-IIP was prepared, and characterized by SEM, XRD and FT-IR. The adsorption of Cu(II) aqueous solution with Cu(II)-IIP was investigated by flame atomic adsorption spectroscopy (FAAS). The polymer has good selectivity for Cu(II) from competitive metal ions, and the selectivity coefficient of Cu(II) relation to Pb(II), Cd(II) was 78.45 and 82.44, respectively. Sorption equilibrium isotherms could be described by Langmuir and Freundlich models; the Freundlich isotherm has shown the best agreement with experimental data, and experimental value of max- imum adsorption capacity for Cu(II) was 35.20 mg/g. The obtained thermodynamic parameter (∆G o , ∆H o , ∆S o ) showed that the Cu(II) adsorption process is a spontaneous and endothermic process. The kinetic data showed that pseudo- second-order kinetic model agrees very well with the dynamic behavior for the sorption of Cu(II) onto Cu(II)-IIP.

This paper investigates the role of infrastructure capital in China’s regional economic development during 1990 to 2009 in a neoclassical economic growth model. Four types of infrastructure capital are discussed; electricity, road, rail, and land-line telephone. The results support a positive role of infrastructure in improving economic wellbeing in China. It shows that infrastructure has contributed to the convergence among China’s provinces. However, declining growth momentum from rapid increase of road infrastructure, in particular for the Western region, suggests that road development in the region has been growing too fast. The results counter the conventional wisdom of “road leads to prosperity” widely accepted among national and local governments in China. Thus, the seemingly productive infrastructure capital, when invested beyond a proper level or speed, will become unproductive. The results resonate with the theoretical literature on the inverse U shaped growth impact of infrastructure capital and the dominant “crowding out” of private capital if there is too much infrastructure. They also address the puzzle in the current literature debates as to the direction and magnitude of the growth impact of infrastructure capital.

In this article, hierarchical flower-like ZnO nanostructures with controlled morphology and dimensions have been synthesized by solution phase approach and functionalized by Au nanoparticles (AuNPs) with the combination of electrodeposition to explore novel applications. The photocatalytic activity and lithium storage capacity of these hybrid nanostructures have been investigated. It has been found that hybrid nanostructure combining the large specific surface area, stability and catalytic activity of small AuNPs, demonstrate the higher photocatalytic activity than that of pure ZnO. Furthermore, an initial discharge capacity of 1280 mA h g−1 and a reversible capacity over 392 mA h g−1 at the 50 cycles are achieved for the Au–ZnO hybrid nanostructure, which is found to be much better than that of any previously reported ZnO anodes. The improved lithium storage capacity and cycle life of the Au–ZnO electrode result from the Li activity of Au–ZnO phase. The photocatalytic and electrochemical activity of Au–ZnO hybrid nanostructures provide a new platform for energy storage, environmental remediation and photocatalysis applications.