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This paper studies the principal component (PC) method-based estimation of weak factor models with sparse loadings. We uncover an intrinsic near-sparsity preservation property for the PC estimators of loadings, which comes from the approximately upper triangular (block) structure of the rotation matrix. It implies an asymmetric relationship among factors: the rotated loadings for a stronger factor can be contaminated by those from a weaker one, but the loadings for a weaker factor is almost free of the impact of those from a stronger one. More importantly, the finding implies that there is no need to use complicated penalties to sparsify the loading estimators. Instead, we adopt a simple screening method to recover the sparsity and construct estimators for various factor strengths. In addition, for sparse weak factor models, we provide a singular value thresholding-based approach to determine the number of factors and establish uniform convergence rates for PC estimators, which complement Bai and Ng (2023). The accuracy and efficiency of the proposed estimators are investigated via Monte Carlo simulations. The application to the FRED-QD dataset reveals the underlying factor strengths and loading sparsity as well as their dynamic features., Comment: 54 pages, 5 figures

Photocatalysis is a feasible technology to solve energy shortage and environmental pollution by using solar energy. Semiconductor photocatalysts with low cost, high stability and environmental friendliness are demonstrated advantages for the production of solar fuel, CO2 reduction, and degradation of pollutants. Among them, Cu2O presents numerous potential for photocatalysis because of its narrow band gap and high activity under visible light. However, the rapid recombination of photoinduced electron-hole pairs and the instability of Cu2O under light irradiation limit its photocatalytic performance. In order to solve the above issues, researchers prefer to incorporate Cu2O with n-type semiconductors to design p-n heterojunction composites, thus regulating the band structure, promoting the separation and transfer of electrons and holes, and accelerating the redox reaction onto the surface. In this manuscript, the preparation methods of Cu2O/n-type semiconductor composites such as hydrothermal method, electrodeposition method, and in situ method are concluded, the photocatalytic applications including CO2 reduction, hydrogen production, and degradation are presented, and the catalytic mechanism like Z-scheme, p-n heterojunction, etc. are discussed, respectively. This review also proposes that there are still challenges in broadening the photocatalytic application of Cu2O/n-type semiconductor composites.

Naringenin, a natural plant flavonoid found in citrus fruits, has been reported to exhibit a wide range of pharmacological functions, including anticancer, antioxidant, antiatherogenic, antithrombotic, and vasodilator activities. Naringenin can be produced from the naringinase (NGase)-catalyzed enzymatic hydrolysis of naringin. However, the poor solubility of naringin in aqueous systems considerably limits the efficiency of naringenin biocatalysis. In this work, a novel substrate adsorption system was proposed for naringin adsorption to increase the efficiency of naringin hydrolysis and naringenin production. Three Amberlite macroporous resins, namely, XAD-4, XAD-7HP and XAD-16, were investigated for their naringin adsorption capacities and effects on NGase hydrolysis. Results indicated that the physical properties of the resins played a critical role in naringin adsorption and naringenin enzymatic synthesis. Naringin hydrolysis was carried out using free and adsorbed substrates. The substrate adsorption strategy could increase the catalytic efficiency at a high naringin concentration. In addition, the reaction conditions for enzymatic naringenin synthesis were optimized, and naringenin was prepared at a liter scale with a high substrate concentration. These results suggested that substrate adsorption is a promising strategy to increase the enzymatic hydrolysis efficiency of naringenin in aqueous systems.

This paper proposes a one-covariate-at-a-time multiple testing (OCMT) approach to choose significant variables in high-dimensional nonparametric additive regression models. Similarly to Chudik, Kapetanios and Pesaran (2018), we consider the statistical significance of individual nonparametric additive components one at a time and take into account the multiple testing nature of the problem. One-stage and multiple-stage procedures are both considered. The former works well in terms of the true positive rate only if the marginal effects of all signals are strong enough; the latter helps to pick up hidden signals that have weak marginal effects. Simulations demonstrate the good finite sample performance of the proposed procedures. As an empirical application, we use the OCMT procedure on a dataset we extracted from the Longitudinal Survey on Rural Urban Migration in China. We find that our procedure works well in terms of the out-of-sample forecast root mean square errors, compared with competing methods.

Supplemental material, sj-doc-1-acr-10.1177_02841851211054191 for Predictors of sentinel lymph node metastasis in Chinese women with clinical T1-T2 N0 breast cancer and a normal axillary ultrasound by Fenfen Fu, Yonghui Zhang, Jie Sun, Chun Zhang, Dongjie Zhang, Lingduo Xie, Futao Chu, Xue Yu and Yuntao Xie in Acta Radiologica

Three new acetylenic aromatic compounds, sterehirsutynes A–C (1–3), along with three known congeners, frustulosinol (4), vibrayne (5), and sterehirsutinol (6), were isolated from the culture broth of Stereum hirsutum. Their structures were determined by detailed analyses of NMR and high-resolution mass. Chiral column analysis showed that compounds 2 and 3 were racemic mixtures. These new compounds were evaluated for porcine pancreatic lipase (PPL) inhibitory activities, and compounds 1 and (±) 3 showed moderate inhibitory activity against PPL, with IC50 values of 23.2 ± 1.04 and 21.8 ± 2.15 μM, respectively.

Vehicle video terminal devices have weak computing and storage ability. A simple, reliable, and effective data sampling and compression algorithm is urgently needed in the mobile environment with the harsh environment. According to compressive sensing (CS) theory, when image data had highly sparse representation, image data would have a highly compressive rate after sampling using a measurement matrix. Image data sampling and compression can be completed simultaneously. Meanwhile, the image that is divided to blocks can improve to process speed. Therefore, in this paper, an improved block-based CS (BCS) is used for vehicle video residual compression. Each vehicle video frame is divided into blocks and residual is sparse in the spatial domain, but we observed residual images have a large amount of redundant data because of illumination and bumps during vehicle motion, and two blocks of adjacent frames have similar texture structure. In order to expand the range of sparse representation of the residual spatial domain, we propose MIBCS method that uses residual energy and mutual information (MI) to judge and process texture structure for two adjacent non-key frames’ blocks. Finally, we use SPL to reconstruct residual in the spatial domain. MIBCS has been tested in a bus video. The experimental results show this method can reduce the residual data volume by nearly half without significantly reducing the video quality. This method is strong and robust because reconstruction quality is weakly affected by block size.

The endophytic fungus Periconia sp. TJ403-rc01 (Dematiaceae) isolated from the leaves of Rosa chinensis Jacq. (Rosaceae) was cultivated on rice medium and chemically investigated, affording two new lanostane-type triterpenoids, namely pericinones A and B (1 and 2). Their structures were determined mainly by 1 D and 2 D NMR and HRESIMS data. Notably, it is the first report of lanostane-type triterpenoids from species of Periconia. Compounds 1 and 2 showed moderate anti-inflammatory activity against the NO production with IC50 values of 24.12 ± 0.73 and 11.38 ± 1.56 μM, respectively.

With its lightweight structure and acceptable accuracy loss, MobileNet-SSD has been widely used in embedded system. The defect of multi-scale detection structure in the original SSD algorithm makes it insufficient in detecting small targets. In this paper, SKBlock structure is used to adaptively expand the receptive field of SSD shallow feature map to improve its detection ability for small targets. Experiments show that it can effectively improve the target detection ability, and does not increase the computational burden.

Kinsenoside (KD) exhibits anti-inflammatory and immunosuppressive effects. Dendritic cells (DCs) are critical regulators of the pathologic inflammatory milieu in liver fibrosis (LF). Herein, we explored whether and how KD repressed development of LF via DC regulation and verified the pathway involved in the process. Given our analysis, both KD and adoptive transfer of KD-conditioned DCs conspicuously reduced hepatic histopathological damage, proinflammatory cytokine release and extracellular matrix deposition in CCl4-induced LF mice. Of note, KD restrained the LF-driven rise in CD86, MHC-II, and CCR7 levels and, simultaneously, upregulated PD-L1 expression on DCs specifically, which blocked CD8+T cell activation. Additionally, KD reduced DC glycolysis, maintained DCs immature, accompanied by IL-12 decrease in DCs. Inhibiting DC function by KD disturbed the communication of DCs and HSCs with the expression or secretion of α-SMA and Col-I declined in the liver. Mechanistically, KD suppressed the phosphorylation of PI3K-AKT driven by LF or PI3K agonist, followed by enhanced nuclear transport of FoxO1 and upregulated interaction of FoxO1 with the PD-L1 promoter in DCs. PI3K inhibitor or si-IL-12 acting on DC could relieve LF, HSC activation and diminish the effect of KD. In conclusion, KD suppressed DC maturation with promoted PD-L1 expression via PI3K-AKT-FoxO1 and decreased IL-12 secretion, which blocked activation of CD8+T cells and HSCs, thereby alleviating liver injury and fibro-inflammation in LF., Graphical Abstract ga1

In this paper, a mobile camera positioning method based on forward and inverse kinematics of robot is proposed, which can realize far point positioning of imaging position and attitude tracking in large scene enhancement. Orbit precision motion through the framework overhead cameras and combining with the ground system of sensor array object such as mobile robot platform of various sensors, realize the good 3 d image registration, solve any artifacts that is mobile robot in the large space position initialization problem, effectively implement the large space no marks augmented reality, human-computer interaction, and information summary. Finally, the feasibility and effectiveness of the method are verified by experiments.

background: Osteoporosis is an important cause of bone fractures and even a cause of threaten to the lives of elderly people. Mind-body exercises are beneficial interventions for improving flexibility, controlling body balance, and reducing pain. To assess the effect of mind-body exercise on osteoporosis in aging people, we will perform this systematic review. Methods: Randomized controlled trials (RCTs) which carried out about mind-body exercise for osteoporosis will be included. Web of Science, PubMed, Science Direct, Medline, Cochrane Library, China National Knowledge Infrastructure, and Wanfang will be searched from inception to January 2020. The outcomes will include bone mineral density (BMD), bone mineral content (BMC), body balance, function of lower extremity, pain, fearing level, and quality of life. Trial reporting quality will be assessed by 2 reviewers independently and Review Manager 5.3 software will be used for meta-analysis. Trial registration is under PROSPERO (CRD42020165385). Results: Based on the current evidence, the potential rank of the efficacy and safety of mind-body exercises for BMD, BMC, body balance, function of lower extremity, pain, fearing level and quality of life will be assessed, and a prioritization regimen will be summarized. Conclusions: Evidence from this systematic review could be useful for patients, clinical practitioners, and guideline-makers to select an optimum proposal of mild-body exercises for older adults with osteoporosis.

Ensuring the students in good physical levels is imperative for their future health. In recent years, the continually growing concentration of Particulate Matter (PM) has done increasingly serious harm to student health. Hence, it is highly required to prevent and control PM concentrations in the campus. As the source of PM prevention and control, developing a good model for PM monitoring is extremely urgent and has posed a big challenge. It has been found in prior works that photobased methods are available for PM monitoring. To verify the effectiveness of existing PM monitoring methods in the campus, we establish a new dataset which includes 1,500 photos collected in the Beijing University of Technology. Experiments show that stated-of-the-art methods are far from ideal for PM monitoring in the campus.

Two new phenolic glucosides, including a new O-glycoside (1) and a new C-glycoside (2), were isolated from a marine-derived fungus Aspergillus sp. The structures of new compounds were elucidated through interpretations of spectroscopic evidence and high-resolution electrospray ionization mass spectrometry. The hexose unit of 1 was identified as β-D-glucose by comparison with an authentic sample via HPLC after acid hydrolysis and derivatization. All compounds were evaluated for their ability to inhibit LPS-induced NO production in RAW264.7 macrophages, but none of them displayed significant activity.

Nowadays, Internet of Things (IoT) gives rise to a huge amount of data. IoT nodes equipped with smart sensors can immediately extract meaningful knowledge from the data through machine learning technologies. Deep learning (DL) is constantly contributing significant progress in smart sensing due to its dramatic superiorities over traditional machine learning. The promising prospect of wide-range applications puts forwards demands on the ubiquitous deployment of DL under various contexts. As a result, performing DL on mobile or embedded platforms is becoming a common requirement. Nevertheless, a typical DL application can easily exhaust an embedded or mobile device owing to a large amount of multiply and accumulate (MAC) operations and memory access operations. Consequently, it is a challenging task to bridge the gap between deep learning and resource-limited platforms. We summarize typical applications of resource-limited deep learning and point out that deep learning is an indispensable impetus of pervasive computing. Subsequently, we explore the underlying reasons for the high computational overhead of DL through reviewing the fundamental concepts including capacity, generalization, and backpropagation of a neural network. Guided by these concepts, we investigate on principles of representative research works, as well as three types of solutions: algorithmic design, computational optimization, and hardware revolution. In pursuant to these solutions, we identify challenges to be addressed.

Since Particulate Matters (PMs) are closely related to people's living and health, it has become one of the most important indicator of air quality monitoring around the world. But the existing sensor-based methods for PM monitoring have remarkable disadvantages, such as low-density monitoring stations and high-requirement monitoring conditions. It is highly desired to devise a method that can obtain the PM concentration at any location for the following air quality control in time. The prior works indicate that the PM concentration can be monitored by using ubiquitous photos. To further investigate such issue, we gathered 1,500 photos in big cities to establish a new AQPDCITY dataset. Experiments conducted to check nine state-of-the-art methods on this dataset show that the performance of those above methods perform poorly in the AQPDCITY dataset.

Recently, Ag/AgCl composites with different structures have been widely studied and used as photocatalysts to degrade dye pollutants, due to their high separation efficiency of electron–hole pairs under visible light irradiation. Herein, we adopted a nucleation, precipitation, growth and photoreduction method to prepare Ag and AgCl co-doped ZIF-8 hybrid photocatalysts and explored the influence of Ag content on their physical and chemical properties. All as-prepared samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) measurements, energy dispersive spectroscopy (EDS), UV-vis diffuse reflectance and X-ray photoelectron spectroscopy (XPS). XRD indicated that ZIF-8 and AgCl were formed and some of the AgCl was reduced into Ag0 after 30 min of UV light irradiation. SEM and TEM images verified that Ag/AgCl nanoparticles were inlaid in the body of ZIF-8 and Ag ions could hinder the growth of the ZIF-8 crystal. BET data indicated that Ag/AgCl nanoparticles did not alter the pore size of ZIF-8. The UV-vis diffuse reflectance spectra showed that Ag/AgCl@ZIF-8 has excellent ability to absorb visible light, indicating the high efficiency of the electron–hole pair separation of Ag/AgCl@ZIF-8. Finally, the photocatalytic activities of all of the as-synthesized samples were evaluated by degradation of RhB under visible light irradiation. Ag and AgCl co-doped ZIF-8 hybrid photocatalysts exhibited high photocatalytic activity due to the synergistic effect of ZIF-8, AgCl and Ag. After 60 min of visible light irradiation, Ag/AgCl(15)@ZIF-8 exhibited the best photocatalytic activity and could degrade 99.12% RhB, which was higher than Ag/AgCl (94.24%) and ZIF-8 (5.17%). Additionally, a photocatalytic mechanism for dye pollutant degradation over the Ag and AgCl co-doped ZIF-8 hybrid photocatalysts was proposed.

The acoustic emission (AE) characteristics of the damage evolution of surrounding rock during tunnel-boring machine (TBM) excavation were studied using AE monitoring and ultrasonic testing. The res...

In order to ensure the safety of driving, this paper studies the vehicle detection algorithm based on convolutional neural network which integrates color and depth images. This paper mainly discusses the subject through convolutional network multi-scale forward looking depth imaging positioning model, forward looking variable scale vehicle detection pre-positioning algorithm, and typical model identification algorithm based on transfer learning, and verifies the algorithm performance and model identification algorithm accuracy by combining with simulation test. The results show that the accuracy of the algorithm is 96.89% under different weather conditions, indicating its effectiveness in application. Compared with previous vehicle detection algorithms, the detection accuracy of this algorithm is effectively improved by 3.96%, indicating that this algorithm has innovative significance.

Aiming at the problem that the existing SRCNN algorithm has too long training time, poor reconstruction performance and slow running speed, a new image super-resolution reconstruction algorithm based on convolutional neural network is proposed. The algorithm uses low-resolution images as the network input, the higher-order representation of the image is learned using the convolution operation, the high-resolution image is up-sampling by the deconvolution operation, and the residual structure is added to the network, so that the entire network can converge better. Experimental results on Set5, Set14, and BSD200 test sets show that compared with Bicubic, SRCNN and other methods, the method proposed in this paper is more efficient on super-resolution reconstruction of images and the convergence speed of the network is faster.

LiCoO2 is still the potential first choice of cathode for lithium ion batteries due to the superior tap density of 4.1 g cm−3 and high theoretical specific capacity of 274 mAh g−1. However, the reversible capacity and cycle performance are restricted due to structural instability at high voltage (≥4.5 V). In this work, the problem will be improved by multiple synergistic effect of nano-Ag. The flake-like LiCoO2/Ag cathodes are firstly synthesized by solid state reaction and the following calcination. The structural characteristics reveal that Ag nanoparticles with ca. 10 nm are uniformly embedded into LiCoO2 particles. The initial discharge specific capacity of LiCoO2 is increased by 12% by introducing nano-Ag at 100 mA g−1 (∼0.7C) between 3.0–4.5 V, and after 100 cycles, the discharge specific capacity is enhanced by 52%. Furthermore, when the current density is increased to 2000 mA g−1, the specific capacity retention of LiCoO2/Ag researches to 62%, higher than 52% of LiCoO2. The results clearly indicate that LiCoO2/Ag cathode exhibits excellent specific capacities, enhanced cycle stability and rate performances enabled by nano-Ag through enhancing Li ions diffusion, electron transport and improving structural stability.

Asperterpenes A and B, two BACE1 inhibitors with unprecedented carbon skeletons isolated from Aspergillus terreus, exhibit potent anti-Alzheimer's disease activity., Asperterpenes A (1) and B (2), two 3,5-dimethylorsellinic acid-based meroterpenoids that contain a unique β-oriented Me-21 with an unprecedented 1,2,5-trimethyl-4,9-dioxobicyclo[3.3.1]non-2-ene-3-carboxylic acid moiety, were obtained from Aspergillus terreus in very limited amounts of 3.6 mg and 1.8 mg, respectively. The absolute structure of 1 was determined using X-ray diffraction. Because of the low yield of 1, a comprehensive characterization of the BACE1 inhibitory activities of 1 was completed via molecular biological, cell and animal studies guided by in silico target confirmation (ISTC). ISTC assays suggested that compounds 1 and 2 might be BACE1 inhibitors. In cell-based tests, asperterpenes A and B, as natural products, exhibited promising inhibitory activities against BACE1, with IC50 values of 78 and 59 nM, respectively. LY2811376 (the positive control), one of the most potent clinical BACE1 inhibitors, has shown an IC50 value of 260 nM. In vivo, compound 1 exhibited activity similar to that of LY2811376 against Alzheimer's disease (AD) in 3xTg AD mice. Taken together, these findings demonstrate that asperterpene A, which contains a novel carbon skeleton, is the first terpenoid to exhibit effective BACE1 inhibitory activity. Moreover, 1 represents a potential lead compound and a versatile scaffold for the development of drugs for the treatment of AD.

Sobel edge detection algorithm is an important research method in image processing and computer vision, but for most edge detection is obtained through PC-side processing, it can not be directly detected locally. This paper proposes that FPGA(Field Programmable Gate Array) can implement modular and local detection of the algorithm. First, the principle and advantages of multidirectional Sobel algorithm are described. Secondly, the FPGA implementation of the algorithm is studied and the preliminary experimental results are obtained. Finally, The detection images obtained by using the eight-direction Sobel algorithm and FPGA are compared with those obtained by matlab, It is found that the hardware can realize the edge detection of local real-time processing while ensuring the image detection effect.

Regular manual sampling and fixed node on-line detection are main methods of water quality monitoring in waters at present. Sampling nodes are subj ect to great restrictions. This paper presents an autonomous cruise unmanned ship for water quality monitoring and sampling, which can be achieved in the waters of any designated location for water quality sampling, achieves the real-time on-line monitoring of the whole water environment by means of the combination of dynamic nodes and static monitoring nodes. This paper introduces the control unit system, the ground station control unit system and the water quality sampling and the monitoring unit system of the unmanned ship and carries out the actual test. The unmanned ship designed in this paper has successfully achieved autonomous cruise, designated water quality sampling and dynamic online real-time water quality monitoring, which provides a new means for water quality monitoring in waters.

Polyacrylate/nano-TiO2 composite latex was prepared via double in-situ polymerization using acrylamide (AM), vinyl acetate (VAc), butyl acrylate (BA) and methyl methacrylate (MMA) as monomers, tetrabutyl titanate (Ti(OBu)4) as precursor of TiO2. The morphology, structure and distribution of composite latex were characterized by Transmission Electron Microscope (TEM), Fourier Transform Infrared Spectroscopy (FTIR), Dynamic Light Scattering (DLS) and X-Ray Diffraction (XRD). The thermal stability, anti-yellowing and antibacterial properties of composite latex were also investigated. The results showed that nano-TiO2 consisted in polyacrylate latex and it was located on the surface of latex particles. The average particle size of polyacrylate/nano-TiO2 composite latex was 156.6 nm, which was bigger than that of pure polyacrylate (125.1 nm). The introduction of nano-TiO2 improved the thermal stability, anti-yellowing and antibacterial properties of the latex film. At last, the polyacrylate/nano-TiO2 composite latex was applied in leather finishing. Compared with polyacrylate latex, the properties of the leather finished by polyacrylate/nano-TiO2 composite latex were enhanced: water vapor permeability increased by 58% and water uptake decreased by 3.52%.

Large-scale one-dimensional (1-D) ZnO nanoarrays (NAs) with controllable density and diameter have been successfully fabricated on silver plated aluminium through a simple, low-temperature, two-step strategy. Besides, the silver trap structures constructed based on the prepared 1-D ZnO NAs as the building blocks and their performance in the secondary electron yield suppression were discussed. X-ray diffraction and energy dispersive spectrometry morphologies of the NAs characterized by scanning electron microscopy clarified that, for the 1-D ZnO NAs as-obtained, the density increased and the vertical alignment improved with the concentration of reactants in the aqueous solution. The average diameter of the individual ZnO nanorod varied based both on the density of the NAs and the concentration of the reactants. Increasing the dip-coating times was an effective way to get higher density ZnO NAs with better vertical alignment under the same conditions. Meanwhile, uniform and dense 1-D ZnO NAs with good alignment have been successfully fabricated on PET cloth and stainless steel mesh utilizing this strategy. As for the silver trap structures, there were no obvious differences in the NAs' density before and after the silver trap construction. However, when it came to the individual nanorods, the hexagonal surface disappeared while cylindrical ones with roughened morphology were obtained. Secondary electron yield measurements showed that the silver trap structures exhibited a 30.8% reduction in the secondary electron yield relative to the bare silver plate aluminium, which provided a promising application for this strategy to fabricate desired 1-D ZnO NAs as the building blocks.

We report a novel three-terminal device fabricated on MgZnO/ZnO/MgZnO triple-layer architecture. Because of the combined barrier modulation effect by both gate and drain biases, the device shows an unconventional I–V characteristics compared to a common field effect transistor. The photoresponse behavior of this unique device was also investigated and applied in constructing a new type ultraviolet (UV) photodetector, which may be potentially used as an active element in a UV imaging array. More significantly, the proper gate bias-control offers a new pathway to overcome the common persistent photoconductivity (PPC) effect problem. Additionally, the MgZnO:F as a channel layer was chosen to optimize the photoresponse properties and the spectrum indicated a gate bias-dependent wavelength-selectable feature for different response peaks, which suggests the possibility to build a unique dual-band UV photodetector with this new architecture.

My dissertation consists of three essays on labor supply responses, along the extensive margin (participation into the labor force) and along the intensive margin (intensity of work on the job). The first two essays focus on the labor supply responsiveness of single women with children to taxation and welfare programs. The third essay investigates the effects of marriage, the wage rate, and the associated tax rate on men's labor supply. In the first essay, to avoid bias from the fact that labor supply outcomes are being driven by self-selection, I build a dynamic stochastic discrete choice model to investigate the long run effects of the earned income tax credit and welfare policies on single mothers' labor supply. Simulated method of moments is used to estimate parameters of this dynamic model, based on March CPS data files from 1964 to 2013. I compare the performance of the dynamic stochastic discrete choice model, a static model, and a reduced-form model. My analysis concludes that the dynamic stochastic discrete choice model captures the simultaneous impact of the state variables on the predicted employment decision. My study provides evidence of the long-run positive effect of public policy on low income families in a life-cycle setting. This essay also emphasizes the importance of education in increasing single mothers' labor supply. The second essay is designed to identify factors that help single mothers leave TANF within a short span of time. I find strong evidence for the importance of child support assistance to single mothers' success in exiting TANF with a job. I uncover evidence that work-related activities do not induce TANF participants to leave within a short span of time. My analysis also suggests that health issues significantly limit the ability of single mothers to exit TANF. In the third essay, the main research question is how marital status affects the elasticity of the labor supply of males with respect to wages and taxes, in a life-cycle setting. A dynamic panel data model, which extends the literature on dynamic labor supply, indicates that the elasticity of men's labor supply with respect to wages and taxes is affected by marital status. The empirical results using the Panel Study of Income Dynamics (PSID) data show that men who are continuously married to the same wife have a lower average Frisch elasticity than others. Ph. D.

Influenza A(H7N9) virus emerged in eastern China in February 2013 and continues to circulate in this region, but its ecology is poorly understood. In April 2013, the Guangdong Provincial Center for Disease Control and Prevention (CDC) implemented environmental and human syndromic surveillance for the virus. Environmental samples from poultry markets in 21 city CDCs (n=8,942) and respiratory samples from persons with influenza-like illness or pneumonia (n=32,342) were tested; viruses isolated from 6 environmental samples and 16 patients were sequenced. Sequence analysis showed co-circulation of 4 influenza A(H7N9) virus strains that evolved by reassortment with avian influenza A(H9N2) viruses circulating in this region. In addition, an increase in human cases starting in late 2013 coincided with an increase in influenza A H7 virus isolates detected by environmental surveillance. Co-circulation of multiple avian influenza viruses that can infect humans highlights the need for increased surveillance of poultry and potential environmental sources.

Steer-by-wire (SBW) system in electric vehicle replaces the mechanical connection between steering wheel and front wheels with cable in the traditional steering system, which overcomes the limitations of the traditional steering system for the drivers. It is a hot research topic in the field of new energy vehicles in the future. The proposed new structure of SBW in electric vehicle is introduced; its integrated control strategy consists of three modules. A coordinated control determines the body forces/moment required to achieve electric vehicle motion objectives. The body forces/moment are allocated to braking and steering subsystems based on phase plane notion. The coordination of these actuators is achieved through the controller of the feedback gains with respect to electric vehicle speed. The gain scheduled steering controller provides the desired yaw rate damping while keeping the yaw-lateral motion decoupled. The simulation test results show the effectiveness of the proposed architecture and steering control system when the SBW in electric vehicle is subject to critical driving situations. Our work provided a reference for further research of SBW system.

The retention of plasma low-density lipoprotein (LDL) particles in subendothelial space following transcytosis across the endothelium is the initial step of atherosclerosis. Whether or not C-reactive protein (CRP) can directly affect the transcytosis of LDL is not clear. Here we have examined the effect of CRP on transcytosis of LDL across endothelial cells and have explored the underlying mechanisms.Effects of CRP on transcytosis of FITC-labelled LDL were examined with human umbilical vein endothelial cells and venous rings in vitro and, in vivo, ApoE(-/-) mice. Laser scanning confocal microscopy, immunohistochemistry and Oil Red O staining were used to assay LDL.CRP increased transcytosis of LDL. An NADPH oxidase inhibitor, diphenylene iodonium, and the reducing agent, dithiothreitol partly or completely blocked CRP-stimulated increase of LDL transcytosis. The PKC inhibitor, bisindolylmaleimide I and the Src kinase inhibitor, PP2, blocked the trafficking of the molecules responsible for transcytosis. Confocal imaging analysis revealed that CRP stimulated LDL uptake by endothelial cells and vessel walls. In ApoE(-/-) mice, CRP significantly promoted early changes of atherosclerosis, which were blocked by inhibitors of transcytosis.CRP promoted atherosclerosis by directly increasing the transcytosis of LDL across endothelial cells and increasing LDL retention in vascular walls. These actions of CRP were associated with generation of reactive oxygen species, activation of PKC and Src, and translocation of caveolar or soluble forms of the N-ethylmaleimide-sensitive factor attachment protein.

* Dan Zhao, Zhongjie Li and Yonghui Zhang contributed equally * Correspondence: Weizhong Yang: ywz126@vip.sina.com; Wenbiao Hu: w.hu@sph.uq.edu.au Background Dengue fever (DF) has been recognised a...

Porous and single crystalline ZnO nanosheets, which were synthesized by annealing hydrozincite Zn(5)(CO(3))(2)(OH)(6) nanoplates produced with a water/ethylene glycol solvothermal method, are used as building blocks to construct functional Pd-ZnO nanoarchitectures together with Pd nanoparticles based on a self-assembly approach. Chemical sensing performances of the ZnO nanosheets were investigated carefully before and after their surface modification with Pd nanoparticles. It was found that the chemical sensors made with porous ZnO nanosheets exhibit high selectivity and quick response for detecting acetone, because of the 2D ZnO nanocrystals exposed in (100) facets at high percentage. The performances of the acetone sensors can be further improved dramatically, after the surfaces of ZnO nanosheets are modified with Pd nanoparticles. Novel acetone sensors with enhanced response, selectivity and stability have been fabricated successfully by using nanoarchitectures consisting of ZnO nanosheets and Pd nanoparticles.

Background This study was conducted to identify epidemiological characteristics of the first documented CHIK fever outbreak in China and evaluate the effect of the preventive measures taken. Methodology/principal findings From September 1 to October 29, 2010, China's first documented outbreak of CHIK fever occurred in the Xincun community of Wanjiang District of Dongguan city, Guangdong province; 253 case-patients were recorded, of which 129 were laboratory confirmed, with an attack rate of 1%. Before September 18(th) the number of CHIK fever cases remained relatively low in the Xincun community; from September 19(th) onwards, the number of cases increased drastically, with an outbreak peak on October 4(th). Cases were distributed across nine small village groups in the Xincun community, with an attack rate of 0-12% at the village level. The household attack rates ranged between 20% and 100%. No significant difference was found in the attack rate between males and females. There was a significant difference in the attack rate in different age groups (chi-square=18.35, p=0.005); highest in patients aged 60 years or older and the lowest in patients aged under 10. The major clinical characteristics of patients are fever (100%), joint pain (79%) and rash (54%). Phylogenetic analysis of the E1 gene on the five earliest confirmed cases showed that the strains of CHIKV isolated from their sera were highly homologous (up to 99%) with isogeneic strains isolated in Thailand in 2009. After control measures were taken, including killing adult mosquitoes and cleaning breeding habitats of Aedes mosquitoes, the Breteau index and Mosq-ovitrap index decreased rapidly, and the outbreak ended on October 29. Conclusion/significance The infection source of the outbreak was imported. Cases showed obvious temporal, spatial, and population aggregation during the outbreak. Comprehensive control measures based on reducing the density of Aedes mosquitoes were effective in controlling the epidemic.

Based on the theory of all-phase spectrum, this paper analyses frequency and harmonics of power. All-phase time-shifting phase difference correcting spectrum analysis is used to correct the measurements of parameters of power quality. All-phase FFT based spectrum analysis and correction has better performance than traditional methods by considering all complexions of the input data. By analyzing the power signal sampling data, it concludes that All-phase FFT based spectrum analysis is more precise on detecting higher harmonics and analyzing power quality than classic FFT.

When the Three-phase power signal containing multiple harmonics signal, there is a clear error that FFT algorithm is used directly to measure the phase. Even with the various correction methods such as ratio method, center of energy gravity method etc., precision is severely constrained by harmonic signal. To solve these problems, a modified FFT algorithm, which is all-phase FFT, is used to measure the phase difference of three-phase power. The algorithm makes phase measurement accuracy significantly improve. More importantly, this method is almost immune to harmonic noise, and easily implements in hardware to meet real-time measurement of power system requirements.

Customer Lifetime Value (CLV) is a problem in urgent need of recognization by telecom operators at present. The existing researches generally consider CLV as the operators’ discounted value of the full value from customers, and the computational methods are listed at the conceptual level. Besides reviewing and analyzing these concepts, the thesis put forward the opinion that since measuring methods of CLV are always lack of operability, it cannot be applied in practical sales. Based on this, the thesis considers CLV as customer value after the evaluation time from the application perspective. Moreover, CLV is broken down according to previous researches and corresponding computational methods of every index are listed, making CLV measurement operable.

When the Three-phase power signal containing multiple harmonics signal, there is a clear error that FFT algorithm is used directly to measure the phase, even with the various correction methods such as ratio method, center of energy gravity method etc. precision is severely constrained by harmonic signal. To solve these problems, a modified FFT algorithm, which is all-phase FFT, is used to measure the phase difference of three-phase power. The algorithm makes phase measurement accuracy significantly improve. More importantly, the way is almost free from harmonic noise, and easily implements in hardware to meet real-time measurement of power system requirements.

This paper based on the theory of all-phase spectrum, analysis the power harmonic signal. All-phase spectrum uses time shifting and phase retardation correction method to correct the frequency and amplitude of harmonic signal, all-phase FFT spectrum analysis and correcting has better performance by considering all complexions of the input data It's accurately measured the harmonic's frequency and amplitude by the theory of all-phase FFT. The accuracy of detect high harmonics is four times magnitude higher than the FFT method on the non-interference situation.

The production of aluminum powder nitrogen atomizing and classifying is a process with strong nonlinear, coupling, large lag, and uncertainty. It is difficult to achieve global optimal control for atomizing process by using single intelligent or conventional method. In this paper, research work to the techniques features and control demands of the aluminum powder nitrogen atomizing process is done. Using the integrated optimal control technology, a distributed control system is presented to effectively control the aluminum powder nitrogen atomizing process and optimize it. As a result, the temperature of atomizing furnace is stabilizing for melted aluminum atomizing; the concentration of oxygen, pressure and temperature of the recycle nitrogen are all controlled very well; the aluminum powder nitrogen atomization process model based on RBF neural networks is presented and enhanced GA based aluminum powder nitrogen atomizing process integrated optimal control is implemented to improve the atomizing effect of aluminum powder and promote the percentage of super-tiny aluminum powder greatly.

An optically transparent electrode, indium tin oxide (ITO) film is fabricated by vacuum E-beam evaporation. The thermal annealing effects on the ITO/GaP contact have been investigated by means of the transmission line model method. Under 435 °C, with rapid thermal annealing for 40 s in N2 ambient, the ITO contact resistance reaches the minimized value of 4.3 × 10−3 Ω · cm2. The results from Hall testing and Auger spectra analysis indicate that the main reasons for the change of the contact resistance are the difference in the concentration of carriers and the diffusion of In, Ga, O. Furthermore, the reliability of AlGaInP LEDs with a 300-nm thickness transparent conducting ITO film is studied. The increase of LED chip voltage results from the degradation of ITO film. Moreover the difference between the thermal expansion coefficient of GaP and ITO results in the invalidation of the LED chip.