Water Saving Technology in Chinese Rice Production - Evidence from Survey Data

Whereas water is an important input in rice production, China faces severe problems with increasing demand for water and limited water resources. In conventional paddy production, one of the most important irrigated crops, a significant amount of irrigation water is lost due to percolation and evaporation. Therefore, it exist a vivid research in water saving rice technologies. This paper analyzes the adoption of one of these water-saving rice production technologies, the so-called Ground Cover Rice Production System (GCRPS), in the Hubei province. Based on farm survey data several factors which affect the adoption decision could be identified. The adoption decision is treated as a binary choice problem and therefore a probit model is used for the econometric analysis. The main determinants of the adoption decision are the number of previous adoptions, the membership in an extension service and the income of the household. Additionally, soil characteristics show a significant impact on the probability of adoption.China, technology adoption, water, GCRPS, probit, Crop Production/Industries, O30, Q16,

Observation of Infrared and Radio Lines of Molecules toward GL2591 and Comparison to Physical and Chemical Models

We have observed rovibrational transitions of acetylene and HCN near 13 microns in absorption toward GL2591. We also observed rotational lines of CS, HCN, H2CO, and HCO+. The combined data are analyzed in terms of models with a cloud envelope with density gradients and discrete regions of hot, dense gas, probably near the infrared source. The abundance of HCN is enhanced by a factor of 400 in the gas producing the infrared absorption, in agreement with chemical models which involve depletion of molecules onto grains and subsequent sublimation when temperatures are raised.Comment: 34 pages, postscript with 14 postscript figure files, uuencoded compressed and tar'ed; unpacks self with csh. In case of problems, contact [email protected]

Intrinsic and Extrinsic Performance Limits of Graphene Devices on SiO2

The linear dispersion relation in graphene[1,2] gives rise to a surprising prediction: the resistivity due to isotropic scatterers (e.g. white-noise disorder[3] or phonons[4-8]) is independent of carrier density n. Here we show that acoustic phonon scattering[4-6] is indeed independent of n, and places an intrinsic limit on the resistivity in graphene of only 30 Ohm at room temperature (RT). At a technologically-relevant carrier density of 10^12 cm^-2, the mean free path for electron-acoustic phonon scattering is >2 microns, and the intrinsic mobility limit is 2x10^5 cm^2/Vs, exceeding the highest known inorganic semiconductor (InSb, ~7.7x10^4 cm^2/Vs[9]) and semiconducting carbon nanotubes (~1x10^5 cm^2/Vs[10]). We also show that extrinsic scattering by surface phonons of the SiO2 substrate[11,12] adds a strong temperature dependent resistivity above ~200 K[8], limiting the RT mobility to ~4x10^4 cm^2/Vs, pointing out the importance of substrate choice for graphene devices[13].Comment: 16 pages, 3 figure

The Economic and Social Impact of GMOs in China

The use of modern biotechnology to create genetically modified organisms (GMOs) is allowing our main food agricultural crops to be altered in ways that were not believed possible even by specialists who took part in the green revolution only decades ago. Agriculture and food production are going through another revolution, the current technology of moving individual genes through biotechnology—genetic engineering. Plants and animals have been modified to resist pests and diseases. Even though..

The Economic and Social Impact of GMOs in China

The use of modern biotechnology to create genetically modified organisms (GMOs) is allowing our main food agricultural crops to be altered in ways that were not believed possible even by specialists who took part in the green revolution only decades ago. Agriculture and food production are going through another revolution, the current technology of moving individual genes through biotechnology—genetic engineering. Plants and animals have been modified to resist pests and diseases. Even though..

Experimental measurements of bulk modulus for two types of hydraulic oil at pressures to 140MPa and temperatures to 180°C

Bulk modulus of hydraulic oil represents the resistance of hydraulic oil to compression and is the reciprocal of compressibility. The bulk modulus is a basic thermodynamic property of hydraulic oil that has a very important influence on work efficiency and dynamic characteristics of hydraulic systems, especially for the hydraulic systems at ultra-high pressure or ultra-high temperature. In this study, a bulk modulus experimental equipment for hydraulic oil was designed and manufactured, two types of hydraulic oil were selected and its isothermal secant bulk modulus were measured at pressures to 140MPa and temperatures of 20~180°C. Compared the experimental results with the calculated results from the prediction equations of liquid bulk modulus that proposed by Klaus, Hayward, and Song, it is found that the experimental results are not completely identical with the calculated results

Lower Difficulty and Better Robustness: A Bregman Divergence Perspective for Adversarial Training

In this paper, we investigate on improving the adversarial robustness obtained in adversarial training (AT) via reducing the difficulty of optimization. To better study this problem, we build a novel Bregman divergence perspective for AT, in which AT can be viewed as the sliding process of the training data points on the negative entropy curve. Based on this perspective, we analyze the learning objectives of two typical AT methods, i.e., PGD-AT and TRADES, and we find that the optimization process of TRADES is easier than PGD-AT for that TRADES separates PGD-AT. In addition, we discuss the function of entropy in TRADES, and we find that models with high entropy can be better robustness learners. Inspired by the above findings, we propose two methods, i.e., FAIT and MER, which can both not only reduce the difficulty of optimization under the 10-step PGD adversaries, but also provide better robustness. Our work suggests that reducing the difficulty of optimization under the 10-step PGD adversaries is a promising approach for enhancing the adversarial robustness in AT

Characteristic abnormal expression of galectin-3 in serrated colon lesions and its pathological significance

Serrated lesions are precursors of some colon cancers. The expression of galectin-3 has been reported to be involved in BRAF and KRAS mutations (the key pathogenic drivers of serrated lesions). This study aimed to investigate the expression intensity and subcellular localization of galectin-3 in serrated colon lesions by immunohistochemistry. The results demonstrated that, regarding expression intensity, galectin-3 expression in serrated colon lesions was significantly upregulated; regarding subcellular localization, the membrane expression of hyperplastic polyps/ sessile serrated lesions (HP/SSL) was weakened, the structure was disorganized and that of traditional serrated adenoma (TSA) was significantly weakened or disappeared, and the nuclear expression of both was positive; in the dysplasia of SSL (SSL-D) and TSA (TSA-HD), galectin-3 expression intensity remained high, and was weakened or disappeared in some nuclei, the expression disorder of the SSL-D cell membrane was reduced, the polarity of the cell was restored, weak expression appeared in the local cell membrane of TSA-HD, and the "serrated" structure of both was reduced or disappeared and seemed to revert more to that seen in common adenomas. In summary, abnormal galectin-3 expression occurs in the early stages of serrated lesions, its expression is characteristic, the dynamic changes in galectin-3 expression are closely related to the histopathological changes and progression of serrated lesions, and further accumulated molecular alterations contribute to this process

PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning

Classical federated learning (FL) enables training machine learning models without sharing data for privacy preservation, but heterogeneous data characteristic degrades the performance of the localized model. Personalized FL (PFL) addresses this by synthesizing personalized models from a global model via training on local data. Such a global model may overlook the specific information that the clients have been sampled. In this paper, we propose a novel scheme to inject personalized prior knowledge into the global model in each client, which attempts to mitigate the introduced incomplete information problem in PFL. At the heart of our proposed approach is a framework, the PFL with Bregman Divergence (pFedBreD), decoupling the personalized prior from the local objective function regularized by Bregman divergence for greater adaptability in personalized scenarios. We also relax the mirror descent (RMD) to extract the prior explicitly to provide optional strategies. Additionally, our pFedBreD is backed up by a convergence analysis. Sufficient experiments demonstrate that our method reaches the state-of-the-art performances on 5 datasets and outperforms other methods by up to 3.5% across 8 benchmarks. Extensive analyses verify the robustness and necessity of proposed designs.Comment: Accepted by NeurIPS 202