Reconstructed springtime (March–June) precipitation tracked by tree rings dating back to 1760 CE in the Qinling-Bashan mountainous area

In recent decades, considerable advances have been made in dendroclimatic reconstruction in the eastern monsoon region of China. However, understanding of long-term hydroclimatic changes has not been comprehensive due to the complexity of the regional geography in China's north-south transitional zone. Growth-climate response analysis indicated that springtime precipitation is the main factor limiting the radial growth of pine trees in the Qinling-Bashan mountainous area. Based on the three tree ring chronologies distributed in the southeast of Shaanxi Province, we developed a March–June precipitation reconstruction spanning 1760–2020 CE for the Qinling-Bashan mountainous area. Precipitation reconstruction accounts for 40.6% of the total precipitation variance during the instrumental period 1955–2016. Spatial correlation analysis indicated that the precipitation reconstruction recorded similar common precipitation signals for the eastern Qinling Mountains and the Yangtze-Huai River Basin. The results of the superposed epoch analysis (SEA) revealed that low precipitation was one of the main causes of severe drought and locust plague events. The preliminary synoptic climatology analysis showed that our reconstructed precipitation is closely linked to the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) variability.Fil: Wang, Shijie. Yunnan University; ChinaFil: Man, Wenmin. Chinese Academy of Sciences; República de ChinaFil: Chen, Feng. Yunnan University; China. China Meteorological Administration; ChinaFil: Chen, Youping. Yunnan University; ChinaFil: Yu, Shulong. China Meteorological Administration; ChinaFil: Cao, Honghua. Yunnan University; ChinaFil: Hu, Mao. Yunnan University; ChinaFil: Hou, Tiyuan. Yunnan University; ChinaFil: Hadad, Martín Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Centro de Investigaciones de la Geosfera y Biosfera. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones de la Geosfera y Biosfera; ArgentinaFil: Roig Junent, Fidel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina. Universidad Mayor; Chil

Fertility Cost, Intergenerational Labor Division, and Female Employment

China has set to increase the minimum retirement age, to ease the pressure from pension expenditure and the falling labor supply caused by the aging population. However, policy debates have so far neglected the crucial fact that families in China largely rely on retired grandparents for childcare. Using novel and high-quality survey data, we demonstrate that intrafamily downward labor transfer towards childcare significantly increases young females’ labor force participation rate and their labor income, and such effects do not exist for males. Furthermore, we show that the positive effects from grandparental childcare are higher for better-educated, urban females with younger children. This paper thus reveals a large, hidden cost in the new retirement policy — the reduced feasibility of grandparental support, due to postponed retirements, may crowd out productive labor of young females, — and rationalizes a series of social protection policies to accompany the phase-in of the new retirement scheme

Who cares: Deciphering China's female employment paradox

Female post-childbirth labor market participation and labor intensity are extraordinarily high in China, given that public childcare subsidies are limited and supportive policies for childbearing female employees are largely absent. Establishing a panel dataset that tracks female employment and childbirth, we find that such a paradox is well-explained by the intra-family childcare support provided by grandparents. Correcting the selection bias that stems from women's fertility choices using the propensity score matching difference-in-difference model, we find that women without grandparental support suffer a substantial drop in post-childbirth employment, while women with grandparental support even experience a rise in employment after childbirth. It takes women without grandparental support twice as long to recover their employment after childbirth. Finally, we find that childbirth does not decrease women's labor intensity due to a lack of labor market flexibility, and that women face a stay-or-quit dilemma when grandparental childcare support is absent

Fertility Cost, Intergenerational Labor Division, and Female Employment

China has set to increase the minimum retirement age, to ease the pressure from pension expenditure and the falling labor supply caused by the aging population. However, policy debates have so far neglected the crucial fact that families in China largely rely on retired grandparents for childcare. Using novel and high-quality survey data, we demonstrate that intrafamily downward labor transfer towards childcare significantly increases young females’ labor force participation rate and their labor income, and such effects do not exist for males. Furthermore, we show that the positive effects from grandparental childcare are higher for better-educated, urban females with younger children. This paper thus reveals a large, hidden cost in the new retirement policy — the reduced feasibility of grandparental support, due to postponed retirements, may crowd out productive labor of young females, — and rationalizes a series of social protection policies to accompany the phase-in of the new retirement scheme.publishedVersio

Effects of Fe3P Addition on Sintering Behaviors and Magnetic Properties of Fe-P Alloys Sintered at Low Temperatures

In this paper, we demonstrate that trace amounts of P addition can activate the sintering of carbonyl powder and influence the magnetic properties of the sintered materials. Fe-x P (x = 0, 0.6, 0.8, 1.0, 1.2, 1.4, and 1.6 wt.%) samples were fabricated by doping carbonyl powder with different amounts of Fe3P. They were sintered at 1000 °C in argon for 2 h. The sintering of the Fe-0 wt.% P sample was interrupted by the ferrite-austenite transformation at 912 °C due to the low diffusion rate of the austenite. The addition of P can stabilize the ferrite, and suppress the ferrite-austenite transformation. Therefore, all the P-containing samples shrank continuously throughout the whole sintering process, which showed improved sintering densities compared to the P-free sample. However, the sintering density did not increase monotonously with increasing P content. The Fe-1.4 wt.% P and Fe-1.6wt.% P samples easily got oxidized during sintering, and the densification process was thus influenced by the P-containing oxide particles. As a result, the Fe-1.2 wt.% P sample exhibited the highest sintering density (7.664 g/cm3) and the best magnetic properties (coercive force 172 A/m)

Understanding the Representativeness of Tree Rings and Their Carbon Isotopes in Characterizing the Climate Signal of Tajikistan

The juniper tree forest is a critical component of the carbon, water, and energy cycles of Tajikistan. However, to date, long-term information about tree-ring isotopes is limited in this region. Here, we developed tree-ring width (TRW) and tree-ring 13C chronologies for juniper trees (Juniperus seravschanica (Juniperus excelsa subsp.polycarpos (K. Koch) Takht.) and Juniperus turkestanica (Juniperus pseudosabina Fisch. & C. A. Mey)) and investigated their dendroclimatic signals in the northwest of the Pamir-Alay (NWPA) mountains in Tajikistan. Tree-ring ∆13C and TRW of juniper presented different sensitivities to monthly precipitation. Moreover, ∆13C in juniper showed consistently significant relationships with climatic factors in larger seasonal windows than TRW did. Dendroclimatological analysis demonstrates that precipitation has significant effects on tree growth and isotope enrichment. Late summer to early winter temperature is one limiting factor for the TRW chronologies, but previous spring, summer, and autumn temperature and precipitation from the previous July to the current May were the dominant climatic factors accounting for inter-annual variations in the ∆13C chronologies. This verified that the multi tree-ring parameters of juniper in Tajikistan are a promising tool for investigating inter-annual climate variations. Furthermore, the stable carbon isotopes of tree rings have proven to be powerful evidence of climatic signals. The moisture-sensitive tree-ring isotope provides opportunities for complex investigations of changes in atmospheric circulation patterns and timing of seasonal rainfall. Our results highlight the need for more detailed studies of tree growth responses to changing climate and tree-ring isotopes to understand source water variations (especially baseflow) of the juniper tree forest

Design and Implementation of a Hardware-in-the-Loop Simulation System for a Tilt Trirotor UAV

The tilt trirotor unmanned aerial vehicle (UAV) is a novel aircraft that has broad application prospects in transportation. However, the development progress of the aircraft is slow due to the complicated control system and the high cost of the flight experiment. This work attempts to overcome the problem by developing a hardware-in-the-loop (HIL) simulation system based on a heavily developed and commercially available flight simulator X-Plane. First, the tilt trirotor UAV configuration and dynamic model are presented, and the parameters are obtained by conducting identification experiments. Second, taking the configuration of the aircraft into account, a control scheme composed of the mode transition strategy, hierarchical controller, and control allocation is proposed. Third, a full-scale flight model of the prototype is designed in X-Plane, and an interface program is completed for connecting the autopilot and X-Plane. Then, the HIL simulation system that consists of the autopilot, ground control station, and X-Plane is developed. Finally, the results of the HIL simulation and flight experiments are presented and compared. The results show that the HIL simulation system can be an efficient tool for verifying the performance of the proposed control scheme for the tilt trirotor UAV. The work contributes to narrowing the gap between theory and practice and provides an alternative verification method for the tilt trirotor UAV

City commercial banks and credit allocation: Firm-level evidence

This paper investigates how government-led banking liberalization affects credit allocation by banks using as a quasi-natural experiment the establishment of city commercial banks (CCBs) in China. Based on more than three million corporate financial statements spanning over 16 years, we find that the establishment of CCBs led to a 6-14 % drop in debt funding for private firms, as well as a 1-2 % rise in their funding costs. At the same time, private infrastructure firms enjoyed a nearly 6 % increase in debt funding and more than 100-basis-point drop in interest costs despite their inferior credit quality. The debt financing of private firm appears most severely affected in municipalities where officials face high promotional pressures or fiscal constraints

An Identification Method of Feature Interpretation for Melanoma Using Machine Learning

Melanoma is a fatal skin cancer that can be treated efficiently with early detection. There is a pressing need for dependable computer-aided diagnosis (CAD) systems to address this concern effectively. In this work, a melanoma identification method with feature interpretation was designed. The method included preprocessing, feature extraction, feature ranking, and classification. Initially, image quality was improved through preprocessing and k-means segmentation was used to identify the lesion area. The texture, color, and shape features of this region were then extracted. These features were further refined through feature recursive elimination (RFE) to optimize them for the classifiers. The classifiers, including support vector machine (SVM) with four kernels, logistic regression (LR), and Gaussian naive Bayes (GaussianNB) were applied. Additionally, cross-validation and 100 randomized experiments were designed to guarantee the generalization of the model. The experiments generated explainable feature importance rankings, and importantly, the model demonstrated robust performance across diverse datasets