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Ovarian function suppression (OFS) plus other endocrine treatment was recommended to hormone receptor (HR)-positive breast cancer by some guidelines recently. We performed this study to validate the survival benefits of OFS plus aromatase inhibitors (AI) or selective estrogen receptor modulators (SERM) in the real world. All premenopausal, HR-positive breast cancer patients diagnosed between 1996 and 2017 were identified. Eligible patients were classified into three groups according to their adjuvant endocrine treatment, including OFS plus AI, OFS plus SERM and SERM alone. The primary outcome is invasive disease-free survival (iDFS), whereas the secondary outcome is overall survival (OS). Cox proportional hazards models and propensity score adjusted models were used to compare the survival benefits in three groups. We included 2838 patients, of which 246 received OFS plus AI, 175 received OFS plus SERM, and 2417 received SERM alone. Compared with SERM alone, OFS plus AI was associated with an improved iDFS (HR 0.59, 95% CI 0.36–0.96) and OS (HR 0.26, 95% CI 0.08–0.85). OFS plus SERM, however, was not significantly associated with extended iDFS or OS. Among patients older than 40 years old, OFS plus AI was more effective than OFS plus SERM (HR 0.38, 95% CI 0.17–0.88) or SERM alone (HR 0.44, 95% CI 0.23–0.84) in terms of iDFS. Our findings suggest that OFS plus AI treatment may extend both iDFS and OS among premenopausal patients with hormone receptor-positive breast cancer in the real world.

With the development of EMC technology, EMC assessment has become increasingly important in EMC design. Although numerous EMC assessment models are available today, few of them can provide a tradeoff between efficiency and accuracy for the specific case of military vehicular communication systems. Face to this situation, a modified four-level assessment model is proposed in the paper. First, the development of EMC assessment technology is briefly reviewed, and the theoretical mechanism of EMI environment is introduced. Then, the architecture of the proposed model is outlined, and the assessment methods are explored. To demonstrate the application of it, an example involving a communication system in a military vehicle is presented. From the physical layer to the signal layer, a hierarchical assessment on the entire system is successfully performed based on the proposed model, and we can make a qualitative EMC assessment on the EMC performance of the system. Based on a comparison with the traditional model, we conclude that the proposed model is more accurate, more efficient and less time-consuming, which is suitable for the EMC assessment on military vehicular communication systems. We hope that the proposed model will serve as a useful reference for system-level EMC assessments for other systems.

A novel simple and readily synthesized turn-on fluorescent probe 4-(benzo[d]thiazol-2-yl)-1,3-phenylene bis(2-chloroacetate) (BPBC) for cysteine (Cys) was reported. This probe was designed based on an excited-state intramolecular proton transfer (ESIPT) dye: benzothiazole, and two chloroacetate groups present in benzothiazole as the reaction sites for Cys. It shows high selectivity and sensitivity for Cys over other amino acids including the similar structured homocysteine (Hcy) and glutathione (GSH). In addition, probe BPBC was successfully applied to bioimage intracellular Cys in living cells with low cytotoxicity. More importantly, a paper test strip system was developed with probe BPBC for Cys detection conveniently.

Novel waterborne UV-curable hyperbranched polyurethane acrylate/silica (HBWPUA/SiO2) nanocomposites were prepared by a three-step procedure and sol–gel method. 1H NMR and 13C NMR results indicate that HBWPU is successfully synthesized. Surface tension and contact angle tests both demonstrate the good wettability of the nanocomposites. Besides, the kinetics of photopolymerization of HBWPUA/SiO2 films were analyzed by attenuated total reflection-Fourier transform infrared spectroscopy, which reveals that the modified SiO2 could accelerate the curing speed of HBWPUA coatings. Thermal gravity analysis indicates that the HBWPUA/SiO2 hybrid films have a better thermal stability than the pure HBWPUA cured films. Furthermore, the hybrid films show enhanced pencil hardness, abrasion resistance, and adhesion. On the basis of the above, HBWPUA/SiO2 nanocomposites were finally applied to waterborne UV-curing flexographic printing ink, which is printed on poly(ethylene terephthalate) and glass. The nanocomposite presents good rheological behavior because the ink has a lower Z0, a higher Z∞, and the viscosity rebuild time is 375 s. Three colors (red, yellow, and blue) of ink were used to test its printing quality, the curing time was below 30 s, and the adhesion was excellent without being stripped. All of the inks show good water resistance and abrasion resistance. Moreover, the red and blue inks possess better solid densities than the value of 1.07 of yellow ink, and are 1.83 and 1.84, respectively. The current study suggests that the process has promise in applications of food packages.

The near-infrared (NIR) fluorescent probe for rapid, highly sensitive and selective detection of cysteine (Cys) has great significance in both biological and environment sciences. In this work, a novel and specific dicyanoisophorone-based NIR probe for Cys was developed. This probe features remarkably large Stokes shift, with turn-on fluorescence property for highly sensitive and selective detection of Cys over other amino acids including the similar structured homocysteine (Hcy) and glutathione (GSH). The probe based on the conjugate addition-cyclization reaction, and has low detection limit of Cys. Furthermore, this probe shows great potential for Cys detection, which was successfully applied to bioimage Cys in living cells with low cytotoxicity.

In this paper, the LMS Virtual.Lab Motion multi-body dynamics simulation software was used to analyze the mid-low speed maglev train current collection system of the collector shoe and the conduct rail. After establishing the dynamic simulation model of the collector shoe and the whole vehicle respectively, the dynamic simulation model of the current collection system is established with considering the irregularity of the running rail and the conduct rail at the same time. The model uses contact force, contact resistance and offline rate to simulate the influence of vehicle running speed on the current collection quality. The following conclusions are obtained by analyzing the simulation results: The current collection system has good current collection characteristics with low speed; fluctuations in contact force and contact resistance and offline rate increases with the increasing speed, resulting in a decrease in the current collection quality; especially at high speeds, contact force, contact resistance fluctuates drastically and the offline rate increases significantly; the current collection system is not suitable for high-speed operation; the current collection system is more sensitive to track irregularity at high speed.

In this paper, the LMS Virtual. Lab Motion was used to analyze the dynamics of the bogie of Medium-speed maglev trains with a mid-mounted linear motor. Firstly, the multi-rigid-body model of the single bogie, the decentralized levitation control scheme and the magnet-rail relationship model were built in LMS Virtual. Lab Motion. The modal frequencies and modal shapes were obtained by using the linearization analysis function of the software. The modal analysis results were verified with the vibration response of the frequency sweeping analysis while applying a vertical force on the mid-mounted linear motor.

Enzyme immobilization is widely used for large-scale industrial applications. However, the weak absorption through physical methods limits the recovery ability. Here, affinity-binding immobilization of enzymes was explored using a silica-specific affinity peptide (SAP) as a fusion tag to intensify the binding force between the enzyme and mesoporous silica (MPS) carrier. d-amino acid oxidase (DAAO) of Rhodosporidium toruloides was used as a model enzyme. The optimal screened SAP (LPHWHPHSHLQP) was selected from a M13 phage display peptide library and fused to the C-terminal of DAAO to obtain fused DAAOs with one, two and three SAP tags, respectively. The activity of DAAO–SAP–MPS was superior comparing with DAAO–2SAP–MPS and DAAO–3SAP–MPS; meanwhile DAAO–SAP–MPS shows 36% higher activity than that of DAAO–MPS. Fusion with one SAP improved the thermal stability with a 10% activity increase for immobilized DAAO–SAP–MPS compared to that of DAAO–MPS at 50 °C for 3 h. Moreover, the activity recovery of immobilized DAAO–SAP–MPS was 25% higher in operation stability assessment after six-batch conversions of cephalosporin to glutaryl-7-amino cephalosporanic acid than that of DAAO–MPS.

Efficient and accurate analysis of the traffic data contained in the network is the key measure to detect the abnormal behavior, resist the invasion and protect the information security. In this paper, we make a comprehensive utilization of the characteristics of port mapping identification, payload identification, statistical analysis and SVM machine learning, and propose the dynamic hybrid strategy. Firstly, the machine learning training samples are obtained through port mapping and load feature recognition. Then, on the basis of information gain feature selection, the SVM machine learning model is built and trained. Finally, through the voting mechanism, we achieve comprehensive analysis of the traffic data. The experimental results show that the accuracy of the proposed algorithm is as high as 99.1%, and the number of manual decision analysis is greatly reduced at the same time.

Cross domain data such as numerical or categorical types are ubiquitous in practical network. Network anomaly detection based on cluster analysis exist some difficulties, for example, the initial center of cluster analysis is sensitive and easy to fall into the local optimal solution. Cross domain data involved great information, but can't be effectively used, which will influence the performance of detection. In this paper, we proposed the dynamic hierarchical clustering method. Firstly, the feature selection based on information gain was used to reduce the feature dimension. Next, to measure the cross domain data, we defined the generalized Euclidean distance to extend the traditional Euclidean distance. Thirdly, dynamic clustering accuracy was set to guide the dynamic hierarchical clustering, guaranteeing the clustering accuracy as well as the convergence of clustering. Finally, Anomaly detection and classification model was constructed by using the training sample data. Simulation results show that the proposed algorithm can achieve higher detection rate and lower false detection rate.

Glaucoma, a group of eye diseases, causes gradual loss of retinal ganglion cells (RGCs) and ultimately results in irreversible blindness. Studies of the underlying mechanisms of glaucoma and clinical trial are far from satisfactory. Results from a genome-wide association study have suggested that the CAV1/CAV2 locus is associated with glaucoma, but this association and its potential underlying mechanisms need to be confirmed and further explored. Here, we studied the function of caveolin-1 (Cav1) in an acute ocular hypertension glaucoma model. Cav1 deficiency caused an aggregated lesion in the retina. In addition, treatment with cavtratin, a membrane permeable Cav1 scaffolding domain peptide, enhanced RGC survival. After cavtratin treatment, microglial numbers decreased significantly, and the majority of them migrated from the inner retinal layer to the outer retinal layers. Furthermore, cavtratin promoted a change in the microglia phenotype from the neurotoxic pro-inflammatory M1 to the neuroprotective anti-inflammatory M2. In a molecular mechanism experiment, we found that cavtratin activated the phosphorylation of both AKT and PTEN in cultured N9 cells. Our data highlights the neuroprotective effect of Cav1 on acute ocular hypertension and suggests that Cav1 may serve as a novel therapeutic target for the treatment of glaucoma. We further propose that cavtratin is a therapeutic candidate for glaucoma clinical trials.

The band structures, density of states and absorption spectra of un-doped and Co-doped ZnO supercells of Zn 1− x Co x O ( x = 0.0417, 0.0625 and 0.1250) have been investigated using first-principles plate-wave uitrasoft pseudopotential method based on the density functional theory. The calculated results showed that the band gaps are broadened by Co doping in ZnO, which is because of the valence band undergoes a greater shift toward the low-energy region than the conduction band lead to. Moreover, the optical absorption edge exhibits a blue-shift, and the heavier the doping concentration is, the more significant the blue-shift will be, which is in agreement with the experimental results.

In the past work, the shear resistance of pure poly(n-butyl acrylate) was low, even incorporation of inorganic filler, silica in the composition. It is well-known that the copolymerization of n-butyl acrylate (BA) with methyl methacrylate (MMA) will increase the glass transition temperature, and enhance the shear resistance of acrylic polymers. In the current work, the preparation of a series of acrylic water-borne pressure-sensitive adhesives (PSAs) with the controlled composition and structure for the copolymerization of BA and acrylic acid (AA) with different MMA contents, poly(BA-co-MMA-co-AA) was reported and its effects on adhesive properties of the latices were investigated. The latices of poly(BA-co-MMA-co-AA) were prepared at a solid content of 50% by two-stage sequential emulsion polymerization, and this process consisted of a batch seed stage giving a particle diameter of 111 nm, which was then grown by the semicontinuous addition of monomers to final diameter of 303 nm. Dynamic light scattering (DLS) was used to monitor the particle diameters and proved that no new nucleation occurred during the growth stage. Copolymerization of BA with MMA raised the glass transition temperature (Tg) of the soft acrylic polymers, and had the effect of improving shear resistance, while the loop tack and peel adhesion kept relatively high. The relationship between pressure-sensitive properties and molecular parameters, such as gel content and molecular weight, was evaluated. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011

The properties and morphology of nano-calcium carbonate (nano-CaCO3) modified with the titanate coupling agent isopropyl trioleoyl titanate (IPTT) were characterized by Fourier transform infrared, thermogravimetric analyses, surface tension, and transmission electron microscopy. The results showed that the grafting ratio of IPTT on the surface of nano-CaCO3 (IPTT-Ca) increased with IPTT content. IPTT-Ca/PBA/PMMA (IPTT-Ca/ACR, PBA/PMMA core-shell polymer, referred to ACR) latexes were prepared by seeded emulsion polymerization. They were then used to mix with PVC resin. The outer layer (PMMA) enhanced the dispensability of IPTT-Ca/ACR in the PVC matrix by increasing the interfacial interaction of these composite particles with PVC. The notched impact strengths of the blends were influenced by the weight ratio of IPTT-Ca to BA/MMA monomers, the weight ratio of BA/MMA. The relationships between the mechanical properties and the core-shell composite structures were elaborated. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010

Silica with an average particle size of 125 nm was prepared by the sol–gel reaction of tetraethoxysilane with a base catalyst and then modified with a vinyl-functionalized silane [γ-methacryloxypropyl trimethoxysilane (MPS)]. The composite latex, with the modified silica as the core and poly(n-butyl acrylate-co-acrylic acid) [poly(BA-co-AA)] polymer as the shell, was synthesized by a semicontinuous emulsion polymerization and used as a pressure-sensitive adhesive. The structures were characterized by Fourier transform infrared spectrometry, X-ray photoelectron spectroscopy, elemental analysis, and transmission electron microscopy. The particle sizes of the silica and MPS-modified silica (MPS–silica)/poly(BA-co-AA) composite latexes were determined by dynamic light scattering in a semicontinuous emulsion polymerization online. The monomers of n-butyl acrylate and acrylic acid grew around the MPS–silica particles without significant secondary nucleation, and the composite latexes exhibited a core–shell structure with the modified silica particles enwrapped in poly(BA-co-AA). To compare the adhesion properties, including the loop tack force, peel strength, and shear resistance, by Federation Internationale des Fabricants et Transformateurs d'Adhesifs et Thermocollants sur Papiers et Autres Supports test methods, poly(methyl methacrylate-co-allyl methacrylate)/poly(BA-co-AA) latex and the full poly(BA-co-AA) latex were prepared with the same particle size and the same emulsion polymerization process. The shear resistance of the composite latex film greatly increased after the addition of the silica to the core of the poly(BA-co-AA) latex. The relationships between the adhesive properties and the different structures in the core components were examined. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009

One of the fundamental features of the visual system is the segregation of neural circuits that process increments and decrements of luminance into ON and OFF pathways. In mature retina, the dendrites of retinal ganglion cells (RGCs) in the inner plexiform layer (IPL) of retina are separated into ON or OFF sublaminaspecific stratification. At an early developmental stage, however, the dendrites of most RGCs are ramified throughout the IPL. The maturation of RGC ON/OFF dendritic stratification requires neural activities mediated by afferent inputs from bipolar and amacrine cells. The synchronized spontaneous burst activities in early postnatal developing retina regulate RGC dendritic filopodial movements and the maintenance or elimination of dendritic processes. After eye opening, visual experience further remodels and consolidates the retinal neural circuit into mature forms. Several neurotransmitter systems, including glutamatergic, acetylcholinergic, GAB Aergic, and glycinergic systems, might act together to modulate the RGC dendritic refinement. In addition, both the bipolar cells and cholinergic amacrine cells may provide laminar cues for the maturation of RGC dendritic stratification.

The complex relationship between maximum absorption wavelength ( λ max ), molar absorptivity ( e ) of the coordination compounds formed from m -acetyl-chlorophosphonazo (CPA-mA) and the metal ions, the acidity of coordination reaction, some properties of metal ions and the properties of more than 20 coordination compounds were studied using artificial neural networks with extended delta-bar-delta EDBD back learning algorithms in this paper. Six parameters: the pH of coordination reactions, metal ion radius ( R ), relative atomic weight (Wt), ionic electronic energy ( E ), metal ion standard Gibbs’ free energy (Δ G 0 ) and hard–soft acid–base dual scale ( f ) were used as input parameters, to predict the λ max and e of the coordination compounds. The structures of networks and the learning times were optimized. The best networks structure is 6–7–2. The optimum number of learning times is about 160 196. It is shown that the maximum relative error is no more than 6% in the testing set. The trained networks are used to simulate the complicated relations between the metal ion properties, coordination reaction conditions and the properties of coordination compounds. This optimized networks have been used for the prediction of the λ max and e of coordination compounds formed from Tb 3+ , Ho 3+ with CPA-mA separately and with satisfactory results.

This paper deals with the application of artificial neural networks (ANNs) to two common problems in spectroscopy: optimization of experimental conditions and non-linear calibration of the result, with particular reference to the determination of fluoride by flow injection analysis (FIA). The FIA system was based on the formation of a blue ternary complex between zirconium(IV), p-methyldibromoarsenazo and F- with the maximum absorption wavelength at 635 nm. First, optimization in terms of sensitivity and sampling rate was carried out by using jointly a central composite design and ANNs, and a neural network with a 3-7-1 structure was confirmed to be able to provide the maximum performance. Second, the relationship between the concentration of fluoride and its absorbance was modeled by ANNs. In this process, cross-validation and leave-k-out were used. The results showed that good prediction was attained in the 1-4-1 neural net. The trained networks proved to be very powerful in both applications. The proposed method was successfully applied to the determination of free fluoride in tea and toothpaste with recoveries between 96 and 101%.

The mammalian cerebral cortex plays a central role in higher cognitive functions and in the complex task of motor control. Maternally expressed gene 3 (Meg3) appears to play a role in cortical development and neurodegeneration, but the expression and regulation of Meg3 in the cortex is not clear. In this study, we examined the expression of transcript variants of Meg3 in the developing mouse cerebral cortex. By in situ hybridization, we found that a novel transcript variant of Meg3 with 8 small exons was expressed in the developing cortex, whereas the long isoforms of Meg3 (~11 kb) were enriched in corticospinal neurons (CSNs) in layer V of the cortex. No transcript variants of Meg3 were found in the neural progenitors at E12.5, when the intergenic differential methylation region (IG-DMR) near Meg3 was highly methylated. IG-DMR became demethylated at E15.5 and remained hypomethylated in early CSNs isolated from Fezf2-EGFP transgenic mice. The expression of Meg3 transcript variant 1 was inversely correlated with the IG-DMR methylation level during development. Moreover, expression of paternally expressed gene Peg11 was limited to the upper layers, consistent with the idea that the maternally expressed gene may be preferentially transcribed in the lower layers of the cortex. The spatiotemporal expression pattern of Meg3 suggests that it may participate in the early development of CSNs and contribute to cortical malfunctions related to aberrant imprinting in Meg3.

In this paper, we introduce a watermarking algorithm for halftone image. The arithmetic is based on HVS and multiscale error diffusion. We insert special binary image in the halftone image and study on it after printing and scanning. Using the proposed methods, several hundred information bits can be embedded into images with perfect recovery against the print-scan operation. Different printing resolution, different scanning resolution and printing paper type are experimented. The experiments show that the watermarking algorithm is robust to print-scan process.

There is an urgent demand on steganalysis, which analyzes if an image includes hidden information, or further decodes the hidden information. This paper proposes a steganalysis method based on statistics model in contourlet transform domain. The proposed method is a blind universal steganalysis method, which does not aim at specified steganography method. The contourlet coefficients of natural image shows obvious regularity which includes sparsity and clustering in subband and similarity across scales. The popular statistical model in wavelet subband is the generalized Gaussian distribution (GGD) model, which can capture the first-order statistical features in subband. While the GGD model can not characterize the dependency between coefficients. The proposed steganalysis method takes contourlet statistics in subband and dependency between contourlet coefficients into account. The dependencies are measured using mutual information. The selected features include parameters of GGD model in subband, the mutual information between coefficients. The classificator chose is Support Vector Machine (SVM). The experimental results show that the features used in the proposed method are valid, when the dependencies between contourlet coefficients are taken into account, the false positive rate is greatly lower than the case in which the dependencies are not considered.

A new rapid, selective and sensitive on-line microwave flow injection-kinetic method was developed for spectrophotometric determination of micro amounts of Ir(III), based on its catalytic effect on the m-acetylchlorophosphonazo (CPA-mA) and KIO(4) reaction in NaOH media. An on-line microwave oven was employed to accelerate the reaction. The reaction was followed spectrophotometrically by measuring the decrease of the absorbance of CPA-mA at 580 nm. The effect of five variables for the determination of Ir(III) was optimized by means of a multilayer artificial neural network using extended delta-bar-delta (EDBD) algorithms. Under the optimum experimental conditions, Ir(III) could be determined in the range 0.060-0.60 micro gZZZ;mL(-1) with detection limit of 0.02 micro gZZZ;mL(-1) and the sampling frequency of 34 h(-1). The proposed method was applied to the determination of micro amounts of Ir(III) in refined ore and secondary alloy with the recoveries from 91.4% to 109%.

A methodology based on the coupling of experimental design and a modified simplex method is proposed for the optimization of a new flow injection-kinetic system for the spectrophotometric determination of Os (IV) with m-acetylchlorophosphonazo, which has for the first time been used as chromogenic reagent in the quantitative analysis of this element. An orthogonal array design is utilized to design the experimental protocol, in which six variables are varied simultaneously, and obtain the initial simplex using 25 experiments. A modified simplex method is applied to continuously optimize the data of the orthogonal array design; the search for optimum conditions of 6 variables using the modified simplex method required only 25 experiments. The efficiency and simplicity of the coupling of the experimental design and the modified simplex method are attractive for the development of new analytical methods. The method has been applied to the determination of Os (IV) in a refined ore as well as in a secondary alloy and provided satisfactory results.

A methodology based on the coupling of experimental design and artificial neural networks (ANNs) is proposed in the optimization of a flow injection system for the spectrophotometric determination of Ru (III) with m-acetylchlorophosphonazo (CPA-mA), which has been for the first time used for the optimization of high-performance capillary zone electrophoresis (J. Chromatogr. A 793 (1998) 317). And since it has been applied in many other regions like micellar electrokinetic chromatography, ion-interaction chromatography, HPLC, etc. (J. Chromatogr. A 850 (1999) 345; J. Chromatogr. A 799 (1998) 35; J. Chromatogr. A 799 (1998) 47). An orthogonal design is utilized to design the experimental protocol, in which five variables are varied simultaneously (Anal. Chim. Acta 360 (1998) 227). Feedforward-type neural networks with extended delta-bar-delta (EDBD) algorithm are applied to model the system, and the optimization of the experimental conditions is carried out in the neural network with 5-5-1 structure, which have been confirmed to be able to provide the maximum performance. In contrast to traditional methods, the use of this methodology has advantages in terms of a reduction in analysis time and an improvement in the ability of optimization. Under the optimum experimental conditions, Ru (III) can be determined in the range 0.040-0.60 mug ml(-1) with detection limit of 0.03 mug ml(-1) and the sampling frequency of 34 h(-1). The method has been applied to the determination of Ru (III) in refined ore as well as in secondary alloy and provided satisfactory results.