A New Conjugate Gradient Algorithm with Sufficient Descent Property for Unconstrained Optimization

A new nonlinear conjugate gradient formula, which satisfies the sufficient descent condition, for solving unconstrained optimization problem is proposed. The global convergence of the algorithm is established under weak Wolfe line search. Some numerical experiments show that this new WWPNPRP+ algorithm is competitive to the SWPPRP+ algorithm, the SWPHS+ algorithm, and the WWPDYHS+ algorithm

Integrated network analysis and metabolomics reveal the molecular mechanism of Yinchen Sini decoction in CCl4-induced acute liver injury

Objective: Yinchen Sini decoction (YCSND), a traditional Chinese medicine (TCM) formula, plays a crucial role in the treatment of liver disease. However, the bioactive constituents and pharmacological mechanisms of action remain unclear. The present study aimed to reveal the molecular mechanism of YCSND in the treatment of acute liver injury (ALI) using integrated network analysis and metabolomics.Methods: Ultra-high-performance liquid chromatography coupled with Q-Exactive focus mass spectrum (UHPLC-QE-MS) was utilized to identify metabolites in YCSND, and high-performance liquid chromatography (HPLC) was applied to evaluate the quality of four botanical drugs in YCSND. Cell damage and ALI models in mice were established using CCl4. 1H-NMR metabolomics approach, along with histopathological observation using hematoxylin and eosin (H&E), biochemical measurements, and reverse transcription quantitative real-time PCR (RT-qPCR), was applied to evaluate the effect of YCSND on CCl4- induced ALI. Network analysis was conducted to predict the potential targets of YCSND in ALI.Result: Our results showed that 89 metabolites in YCSND were identified using UHPLC-QE-MS. YCSND protected against ALI by reducing the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and malondialdehyde (MDA) contents and increasing those of superoxide dismutase (SOD), and glutathione (GSH) both in vivo and in vitro. The 1H-NMRmetabolic pattern revealed that YCSND reversed CCl4-induced metabolic abnormalities in the liver. Additionally, the Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis identified five pathways related to liver injury, including the PI3K-AKT, MAPK, HIF-1, apoptosis, and TNF signaling pathways. Moreover, RT-qPCR showed YCSND regulated the inflammatory response (Tlr4, Il6, Tnfα, Nfκb1, Ptgs2, and Mmp9) and apoptosis (Bcl2, Caspase3, Bax, and Mapk3), and inhibited PI3K-AKT signaling pathway (Pi3k and Akt1). Combined network analysis and metabolomics showed a link between the key targets (Tlr4, Ptgs2, and Mmp9) and vital metabolites (choline, xanthine, lactate, and 3-hydroxybutyric acid) of YCSND in ALI.Conclusion: Overall, the results contribute to the understanding of the therapeutic effects of YCSND on ALI, and indicate that the integrated network analysis and metabolomics could be a powerful strategy to reveal the pharmacological effects of TCM

Immunization of Mice with Recombinant Protein CobB or AsnC Confers Protection against Brucella abortus Infection

Due to drawbacks of live attenuated vaccines, much more attention has been focused on screening of Brucella protective antigens as subunit vaccine candidates. Brucella is a facultative intracellular bacterium and cell mediated immunity plays essential roles for protection against Brucella infection. Identification of Brucella antigens that present T-cell epitopes to the host could enable development of such vaccines. In this study, 45 proven or putative pathogenesis-associated factors of Brucella were selected according to currently available data. After expressed and purified, 35 proteins were qualified for analysis of their abilities to stimulate T-cell responses in vitro. Then, an in vitro gamma interferon (IFN-γ) assay was used to identify potential T-cell antigens from B. abortus. In total, 7 individual proteins that stimulated strong IFN-γ responses in splenocytes from mice immunized with B. abortus live vaccine S19 were identified. The protective efficiencies of these 7 recombinant proteins were further evaluated. Mice given BAB1_1316 (CobB) or BAB1_1688 (AsnC) plus adjuvant could provide protection against virulent B. abortus infection, similarly with the known protective antigen Cu-Zn SOD and the license vaccine S19. In addition, CobB and AsnC could induce strong antibodies responses in BALB/c mice. Altogether, the present study showed that CobB or AsnC protein could be useful antigen candidates for the development of subunit vaccines against brucellosis with adequate immunogenicity and protection efficacy

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes

Classifying historical remotely sensed imagery using a tempo-spatial feature evolution (T-SFE) model

Large and growing archives of orbital imagery of the earth\u27s surface collected over the past 40 years provide an important resource for documenting past and current land cover and environmental changes. However uses of these data are limited by the lack of coincident ground information with which either to establish discrete land cover classes or to assess the accuracy of their identification. Herein is proposed an easy-to-use model, the Tempo-Spatial Feature Evolution (T-SFE) model, designed to improve land cover classification using historical remotely sensed data and ground cover maps obtained at later times. This model intersects (1) a map of spectral classes (S-classes) of an initial time derived from the standard unsupervised ISODATA classifier with (2) a reference map of ground cover types (G-types) of a subsequent time to generate (3) a target map of overlaid patches of S-classes and G-types. This model employs the rules of Count Majority Evaluation, and Subtotal Area Evaluation that are formulated on the basis of spatial feature evolution over time to quantify spatial evolutions between the S-classes and G-types on the target map. This model then applies these quantities to assign G-types to S-classes to classify the historical images. The model is illustrated with the classification of grassland vegetation types for a basin in Inner Mongolia using 1985 Landsat TM data and 2004 vegetation map. The classification accuracy was assessed through two tests: a small set of ground sampling data in 1985, and an extracted vegetation map from the national vegetation cover data (NVCD) over the study area in 1988. Our results show that a 1985 image classification was achieved using this method with an overall accuracy of 80.6%. However, the classification accuracy depends on a proper calibration of several parameters used in the model. (C) 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved

The Impact of Jobs Outside One's Hometown and Left-Behind Family Members on the Return Intentions of Migrant Workers: A Multi-Dimensional Comparative Analysis

In the process of leaving one's hometown for work, migrant workers face the problem of family separation, resulting in a large number of left-behind children, women, and elderly. The separation between the "jobs" and "family" of migrant workers makes them consider not only their "jobs" but also their "family" when making mobility choices. However, few existing studies have conducted in-depth multi-dimensional comparative analyses on return intentions from the perspectives of "jobs" and "family" at the same time. Drawing on data from the 2014 and 2016 "Migrants' Dynamic Monitoring Survey" and case interview data, using a mixed research method of quantitative and qualitative research, starting from Neoclassical Economics (NE) and the New Economics of Labor Migration (NELM), and based on multi-dimensional comparative analysis, this study discusses the impact of jobs outside one's hometown and left-behind family members on the return intentions of migrant workers. Results indicate that such jobs decrease migrants' intentions to return, while left-behind family members increase their return intentions. The former has a greater influence than the latter. The impact of left-behind family members on return intentions was weakened in the following order: left-behind children, left-behind spouses, and left-behind parents. From a generational perspective, the impact of jobs outside one's hometown on the new generation of migrant workers is greater than on the old generation, and the impact of left-behind children on the younger generation of migrant workers is greater than on the old generation, while the impact of left-behind spouses shows an opposite trend. From the perspective of social change, the impact of jobs outside one's hometown strengthen, and that of left-behind children increase. The opposite is true for left-behind spouses and left-behind parents. The results show that: (1) NE is more suitable than NELM for explaining the impact of jobs outside one's hometown on the return intentions of migrant workers in China; (2) NELM is more suitable than NE to explain the impact of left-behind family members on the return intentions of migrant workers in China; (3) When analyzing the influence mechanism of left-behind family members on the return intentions of migrant workers in China, we should not only focus on one dimension of economy but also explain the phenomenon from the perspective of family culture and family responsibility. This study contributes to the literature by expanding and supplementing the views of NE and NELM and developing and deepening the empirical study of migrant workers' return intentions through a multi-dimensional comparative analysis in combination with China's context. This study suggests that the relevant government departments should take measures to promote the realization of the dream of having both "jobs" and "family" at the same time for migrant workers as well as to promote their family construction

Ecological Analysis of an Emerging Urban Landscape Pattern–Desakota: A case study in Suzhou, China

Recent scholarly efforts to investigate the conventional wisdom of urban transition and conceptualize the distinct patterns of urbanization emerging in China, simply referred to as desakota , have not yielded any conclusive validation. The possible existence of desakota is significant for landscape ecology and regional science research in that it challenges long cherished Western notions concerning the separation of urban processes from rural processes and the spatial uniqueness of the respective landscapes. This paper examines physical evidence of desakota from land use changes and tempo-spatial dynamics of desakota development in the lower Yangtze River Delta-one of the most populous and rapidly growing economic regions in China. The paper uses satellite data in 1990, 1995 and 2000 to spectrally disaggregate such rural landscape patterns as urban construction expanding from existing commercial and industrial centers, rural non-agricultural construction, special large infrastructure construction, and crop cultivation. The paper inspects one transect (60 km long and 12 km wide) cutting across Suzhou City in south and Changshu City in north. The transect is divided into four segments to investigate quantitative changes of land types between the two cities over time. The paper applies landscape ecological metrics to analyze tempo-spatial patterns of desakota changes in terms of counts, densities, shapes, compositions, spatial relationships and diversities. The paper concludes: (1) desakota occurred in Suzhou area before 1990 and witnessed two phases of development, dramatic expansion between 1990 and 1995 and consolidation during 19952000; (2) desakota dynamics show distinct spatial patterns, new growth of large and specialized urban districts dominant in the vicinity of large cities (Suzhou) and incremental expansion of existing urban places in small cities and rural areas; and (3) landscape metrics are very informative in discerning dynamics and patterns of land use and land cover changes and different metrics vary in descriptive power and sensitivity