Estimation of land production and its response to cultivated land conversion in North China Plain

Major State Basic Research Development Program of China 2010CB950904;National Natural Science Foundation of China 70503025 40801231;Chinese Academy of Sciences KZCX2-YW-305-2Food safety and its related influencing factors in China are the hot research topics currently, and cultivated land conversion is one of the significant factors influencing food safety in China. Taking the North China Plain as the study area, this paper examines the changes of cultivated land area using satellite images, estimates land productivity from 1985 to 2005 using the model of Estimation System for Land Productivity (ESLP), and analyzes the impact of cultivated land conversion on the land production. Compared with the grain yield data from statistical yearbooks, the results indicate that ESLP model is an effective tool for estimating land productivity. Land productivity in the North China Plain showed a slight decreasing trend from 1985 to 2005, spatially, increased from the north to the south gradually, and the net changes varied in different areas. Cultivated land area recorded a marginal decrease of 8.0 x 10(5) ha, mainly converted to other land uses. Cultivated land conversion had more significant negative impacts on land production than land productivity did. Land production decreased by about 6.48 x 10(6) t caused by cultivated land conversion between 1985 and 2005, accounting for 91.9% of the total land production reduction. Although the land productivity increased in Anhui and Jiangsu provinces, it can not offset the overall adverse effects caused by cultivated land conversion. Therefore, there are significant meanings to control the cultivated land conversion and improve the land productivity for ensuring the land production in the North China Plain

Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.

Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.This research is supported by the Center forDynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant no. MOST103-2911-I-008-001). Also, it is supported by National Chung-Shan Institute of Science & Technology in Taiwan (Grant nos. CSIST-095-V301 and CSIST-095-V302)

Predicting Bus Travel Time with Hybrid Incomplete Data – A Deep Learning Approach

The application of predicting bus travel time with real-time information, including Global Positioning System (GPS) and Electronic Smart Card (ESC) data is effective to advance the level of service by reducing wait time and improving schedule adherence. However, missing information in the data stream is inevitable for various reasons, which may seriously affect prediction accuracy. To address this problem, this research proposes a Long Short-Term Memory (LSTM) model to predict bus travel time, considering incomplete data. To improve the model performance in terms of accuracy and efficiency, a Genetic Algorithm (GA) is developed and applied to optimise hyperparameters of the LSTM model. The model performance is assessed by simulation and real-world data. The results suggest that the proposed approach with hybrid data outperforms the approaches with ESC and GPS data individually. With GA, the proposed model outperforms the traditional one in terms of lower Root Mean Square Error (RMSE). The prediction accuracy with various combinations of ESC and GPS data is assessed. The results can serve as a guideline for transit agencies to deploy GPS devices in a bus fleet considering the market penetration of ESC

Detecting rare functional variants using a wavelet-based test on quantitative and qualitative traits

We conducted a genome-wide association study on the Genetic Analysis Workshop 17 simulated unrelated individuals data using a multilocus score test based on wavelet transformation that we proposed recently. Wavelet transformation is an advanced smoothing technique, whereas the currently popular collapsing methods are the simplest way to smooth multilocus genotypes. The wavelet-based test suppresses noise from the data more effectively, which results in lower type I error rates. We chose a level-dependent threshold for the wavelet-based test to suppress the optimal amount of noise according to the data. We propose several remedies to reduce the inflated type I error rate: using a window of fixed size rather than a gene; using the Bonferroni correction rather than comparing to the maxima of test values for multiple testing corrections; and removing the influence of other factors by using residuals for the association test. A wavelet-based test can detect multiple rare functional variants. Type I error rates can be controlled using the wavelet-based test combined with the mentioned remedies

The ‘credibility paradox’ in China’s science communication: Views from scientific practitioners

In contrast to increasing debates on China’s rising status as a global scientific power, issues of China’s science communication remain under-explored. Based on 21 in-depth interviews in three cities, this article examines Chinese scientists’ accounts of the entangled web of influence which conditions the process of how scientific knowledge achieves (or fails to achieve) its civic authority. A main finding of this study is a ‘credibility paradox’ as a result of the over-politicisation of science and science communication in China. Respondents report that an absence of visible institutional endorsements renders them more public credibility and better communication outcomes. Thus, instead of exploiting formal channels of science communication, scientists interviewed were more keen to act as ‘informal risk communicators’ in grassroots and private events. Chinese scientists’ perspectives on how to earn public support of their research sheds light on the nature and impact of a ‘civic epistemology’ in an authoritarian state

Fumarate Analogs Act as Allosteric Inhibitors of the Human Mitochondrial NAD(P)+-Dependent Malic Enzyme

Human mitochondrial NAD(P)+-dependent malic enzyme (m-NAD(P)-ME) is allosterically activated by the four-carbon trans dicarboxylic acid, fumarate. Previous studies have suggested that the dicarboxylic acid in a trans conformation around the carbon-carbon double bond is required for the allosteric activation of the enzyme. In this paper, the allosteric effects of fumarate analogs on m-NAD(P)-ME are investigated. Two fumarate-insensitive mutants, m-NAD(P)-ME_R67A/R91A and m-NAD(P)-ME_K57S/E59N/K73E/D102S, as well as c-NADP-ME, were used as the negative controls. Among these analogs, mesaconate, trans-aconitate, monomethyl fumarate and monoethyl fumarate were allosteric activators of the enzyme, while oxaloacetate, diethyl oxalacetate, and dimethyl fumarate were found to be allosteric inhibitors of human m-NAD(P)-ME. The IC50 value for diethyl oxalacetate was approximately 2.5 mM. This paper suggests that the allosteric inhibitors may impede the conformational change from open form to closed form and therefore inhibit m-NAD(P)-ME enzyme activity

Molecular Valves for Controlling Gas Phase Transport Made from Discrete Angstrom-Sized Pores in Graphene

An ability to precisely regulate the quantity and location of molecular flux is of value in applications such as nanoscale 3D printing, catalysis, and sensor design. Barrier materials containing pores with molecular dimensions have previously been used to manipulate molecular compositions in the gas phase, but have so far been unable to offer controlled gas transport through individual pores. Here, we show that gas flux through discrete angstrom-sized pores in monolayer graphene can be detected and then controlled using nanometer-sized gold clusters, which are formed on the surface of the graphene and can migrate and partially block a pore. In samples without gold clusters, we observe stochastic switching of the magnitude of the gas permeance, which we attribute to molecular rearrangements of the pore. Our molecular valves could be used, for example, to develop unique approaches to molecular synthesis that are based on the controllable switching of a molecular gas flux, reminiscent of ion channels in biological cell membranes and solid state nanopores.Comment: to appear in Nature Nanotechnolog

Generalized Painleve-Gullstrand descriptions of Kerr-Newman black holes

Generalized Painleve-Gullstrand metrics are explicitly constructed for the Kerr-Newman family of charged rotating black holes. These descriptions are free of all coordinate singularities; moreover, unlike the Doran and other proposed metrics, an extra tunable function is introduced to ensure all variables in the metrics remain real for all values of the mass M, charge Q, angular momentum aM, and cosmological constant \Lambda > - 3/(a^2). To describe fermions in Kerr-Newman spacetimes, the stronger requirement of non-singular vierbein one-forms at the horizon(s) is imposed and coordinate singularities are eliminated by local Lorentz boosts. Other known vierbein fields of Kerr-Newman black holes are analysed and discussed; and it is revealed that some of these descriptions are actually not related by physical Lorentz transformations to the original Kerr-Newman expression in Boyer-Lindquist coordinates - which is the reason complex components appear (for certain ranges of the radial coordinate) in these metrics. As an application of our constructions the correct effective Hawking temperature for Kerr black holes is derived with the method of Parikh and Wilczek.Comment: 5 pages; extended to include application to derivation of Hawking radiation for Kerr black holes with Parikh-Wilczek metho

Developing Fatigue Pre-crack Procedure to Evaluate Fracture Toughness of Pipeline Steels Using Spiral Notch Torsion Test

The spiral notch torsion test (SNTT) has been utilized to investigate the crack growth behavior of X52 steel base and welded materials used for hydrogen infrastructures. The X52 steel materials are received from a welded pipe using friction stir welding techniques. Finite element models were established to study the crack growth behavior of steel SNTT steel samples, which were assumed to be isotropic material. A series SNTT models were set up to cover various crack penetration cases, of which the ratios between crack depth to diameter (a/D ratio) ranging from 0.10 to 0.45. The evolution of compliance and energy release rates in the SNTT method have been investigated with different cases, including different geometries and materials. Indices of characteristic compliance and energy release rates have been proposed. Good agreement has been achieved between predictions from different cases in the same trend. These work shed lights on a successful protocol for SNTT application in wide range of structural materials. The further effort needed for compliance function development is to extend the current developed compliance function to the deep crack penetration arena, in the range of 0.55 to 0.85 to effectively determine fracture toughness for extremely tough materials

Stem cell differentiation increases membrane-actin adhesion regulating cell blebability, migration and mechanics

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/K. S. is funded by an EPSRC PhD studentship. S.T. is funded by an EU Marie Curie Intra European Fellowship (GENOMICDIFF)