The PHQ-9 performs well and has acceptable psychometric properties for screening of patients with late-life depression in Chinese primary care settings.

Purpose The purpose of this paper is to empirically investigate the effect of rural finance on industrial integration of rural primary, secondary and tertiary industries. Design/methodology/approach Using household-level data collected by Third National Agricultural Census and the provincial-level data collected from Wind database, the authors estimated the impacts of rural finance on rural industrial integration using Logit and Probit regression models. Further, the authors examined how the effect of rural finance varies with the age and education of householders, and with household and provincial characteristics by investigating the moderating effect. Findings The findings show that rural finance has a significant and positive effect on promoting farmers’ participation in new agricultural management organizations. This effect is more obvious in families whose householders are 40–50 years old, or families that have more educated members. This is because the middle-aged or educated people are more willing to accept and take part in industrial integration. The results further indicate that rural finance has a greater effect on industrial integration in provinces with a high degree of marketization, and in provinces with the high output value of industries and services in agricultural intermediate input. Originality/value The authors investigated the impact of rural finance on rural industrial integration empirically, and this topic is rarely covered before. The findings of this study also enrich the literature on financial development and economic growth as well as provide policy suggestions on how to promote rural industrial integration.

The growth of vehicle ownership not only brings opportunity for the economy, but also brings environment and transport problems, which is not good for sustainable transportation. It is of great significance to build supporting infrastructure and other services based on accurate forecasts of vehicle ownership in various provinces because of the variance of economic development stages, the carrying capacity of resources, and different degrees of transport planning in each province. We used the Gompertz model in order to predict China’s provincial vehicle ownership from 2018 to 2050. Considering the impact of the population structure, we summed up the growth rate of GDP per labor, the growth rate of population and the growth rate of employment rate to get the growth rate of GDP and then the GDP per capita of each province. We found that the vehicle ownership in each province will grow rapidly in the next 30 years; however, the change in the ranking of vehicle ownership among provinces varies. The ranking of some provinces with high or middle ranking now will decline in the following years, especially Beijing, Tianjin, Shanghai and Xinjiang. While the ranking of some provinces that locates in the middle and low ranking now will increase, such as Chongqing, Hubei, Anhui, Sichuan, Heilongjiang, Jiangxi, Hunan and Guangxi. We also investigate the reasons that affect the trend in each province and we find that the suitable vehicle growth pattern of each province, the stage of economic development and government policy, which are related to the growth rate of GDP per labor, employment rate, and GDP per capita, can affect vehicle ownership in the future.

C 54H44Cl2Cu2N2P2,m onoclinic, C12/c1(no. 15 Source of materialThe title compound was obtained by the reaction of CuCl and PPh 3 (molar ratio 1:1) in the presence of isoquinoline (1 ml) in the mixed solution of CH 3OH (5 ml) and CH2Cl2 (5 ml) for 4hours at ambient temperature. The insoluble residues were removed by filtration, and the filtrate was evaporated slowly at room temperature for about one week to yield yellow crystals. Crystals suitable for single crystal X-ray diffraction investigation were extracted directly from the sample as prepared.

C 45 H 37 BrCuNP 2 ,monoclinic, P2 1 /n (no. 14), a =10.019(1) Å, b =36.487(3) Å, c =11.294(2) Å, b =114.653(1)°, V =3752.3 Å 3 , Z =4,Rgt(F) =0.058, wRref (F 2 ) =0.125, T =298 K. Source of materialSynthesis of the title compound was carried out by stirring the solution of the CuBr (0.0215 g, 0.15 mmol), triphenylphosphine (PPh 3 ,0 .0787 g, 0.3 mmol), and isoquinoline (1 ml) in the CH 3 OH (5 ml) and CH 2 Cl 2 (5 ml) for 4hours at room temperature. The filtrate was allowed to stand at the room temperature. Slow evaporation of the solvent yielded yellow crystals. DiscussionThe d 10 metal copper(I) and Ag(I) complexes containing mixed ligands such as PPh 3 (triphenylphosphine) and nitrogen ligands have been noticed for along time because of their various interesting structures [1][2][3]. Quinoline and isoquinoline are good nitrogen dorners because they contain pyridine ring, the strong Lewis base group. It is difficult to synthesize copper(I) complexes because of their low solubility in the organic solvents and their instability. We succeeded in synthesizing as eries of copper(I) complexes with nitrogen heterocycle complexes, halogen and triphenylphosphine as ligands. [CuBr(PPh 3)(C9H7N]2 (1), [CuI(PPh 3)(C9H7N)]2 (2)and [CuCl(PPh3)(i-C9H7N)]2 (3) [4][5][6]. The crystal structure of the title complex shows that the copper(I) atom is coordinated by two phosphorus atoms from PPh 3 groups, one nitrogen atom from isoquinoline and one bromide anion. The structure shows differences among the title complex and (1), (2) and (3)