How do land use regulations influence industrial land prices? Evidence from China

Due to low industrial land prices and inefficiently used industrial land, China’s central government has reformed land regulations in order to promote more market-oriented industrial land. Considering the differences in land management between developed and developing countries, this study aims to investigate the impact of land use regulations on industrial land prices in China and the effect of market-oriented reforms of industrial land policy. Measures that capture multiple dimensions of land use regulation tools are incorporated into OLS models based on a micro dataset from 1999 to 2016 that covers Jiaxing City in Eastern China. The results show that (1) The land policy implemented in 2006 to promote industrial land marketization has had a very limited effect; (2) The impact of land supply on industrial land prices was decreased for land transferred through listings after 2006, which implies an immature marketization; (3) Zoning instruments has obvious effects on industrial land prices; (4) The results imply that the effect of land use regulations varies with firm ownership and development zones. The findings in this paper clearly show that the industrial land market should be more open and competitive and combined with a rational land supply to promote the market-oriented price mechanism. First published online 28 December 202

BTH Treatment Delays the Senescence of Postharvest Pitaya Fruit in Relation to Enhancing Antioxidant System and Phenylpropanoid Pathway

The plant resistance elicitor Benzo (1,2,3)-thiadiazole-7-carbothioic acid S-methyl ester (BTH) can enhance disease resistance of harvested fruit. Nonetheless, it is still unknown whether BTH plays a role in regulating fruit senescence. In this study, exogenous BTH treatment efficiently delayed the senescence of postharvest pitaya fruit with lower lipid peroxidation level. Furthermore, BTH-treated fruit exhibited lower hydrogen peroxide (H2O2) content, higher contents of reduced ascorbic acid (AsA) and reduced glutathione (GSH) levels and higher ratios of reduced to oxidized glutathione (GSH/GSSG) and ascorbic acid (AsA/DHA), as well as higher activities of ROS scavenging enzymes, including superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), peroxidase (POD) and glutathione reductase (GR) in comparison with control fruit. Moreover, BTH treatment enhanced the activities of phenylpropanoid pathway-related enzymes, including cinnamate-4-hydroxylase (C4H), phenylalanine ammonia-lyase (PAL) and 4-coumarate/coenzyme A ligase (4CL) and the levels of phenolics, flavonoids and lignin. In addition, BTH treatment upregulated the expression of HuSOD1/3/4, HuCAT2, HuAPX1/2 and HuPOD1/2/4 genes. These results suggested that application of BTH delayed the senescence of harvested pitaya fruit in relation to enhanced antioxidant system and phenylpropanoid pathway

The interaction of CpEBF1 with CpMADSs is involved in cell wall degradation during papaya fruit ripening

Papaya: Anti-ripening treatment prevents degradation of cell wall Long-term treatment with an anti-ripening agent inhibits the expression of regulatory genes that normally break down the cell wall of the papaya fruit. A team from Guangzhou’s South China Agricultural University led by Xueping Li and Weixin Chen applied a hormone inhibitor to papayas at the breaker stage of fruit ripening. 1 h of treatment delayed ripening, whereas 16 h of treatment caused the fruit to become rubbery, with significantly higher levels of cellulose and lignin, both structural components of the cell wall. The researchers identified two genes with reduced expression following extended hormone-blocking treatment. Both normally encode proteins that aid in degrading the cell wall to promote fruit ripening. The findings thus offer a molecular explanation for why misuse of anti-ripening agents on papaya fruits can lead to undesirable characteristics

THOR, Trace-based Hardware-driven Layer-Oriented Natural Gradient Descent Computation

It is well-known that second-order optimizer can accelerate the training of deep neural networks, however, the huge computation cost of second-order optimization makes it impractical to apply in real practice. In order to reduce the cost, many methods have been proposed to approximate a second-order matrix. Inspired by KFAC, we propose a novel Trace-based Hardware-driven layer-ORiented Natural Gradient Descent Computation method, called THOR, to make the second-order optimization applicable in the real application models. Specifically, we gradually increase the update interval and use the matrix trace to determine which blocks of Fisher Information Matrix (FIM) need to be updated. Moreover, by resorting the power of hardware, we have designed a Hardware-driven approximation method for computing FIM to achieve better performance. To demonstrate the effectiveness of THOR, we have conducted extensive experiments. The results show that training ResNet-50 on ImageNet with THOR only takes 66.7 minutes to achieve a top-1 accuracy of 75.9 % under an 8 Ascend 910 environment with MindSpore, a new deep learning computing framework. Moreover, with more computational resources, THOR can only takes 2.7 minutes to 75.9 % with 256 Ascend 910