Mining Heat-Resistant Key Genes of Peony Based on Weighted Gene Co-Expression Network Analysis.

The RNA-Seq and gene expression data of mature leaves under high temperature stress of Paeonia suffruticosa 'Hu Hong' were used to explore the key genes of heat tolerance of peony. The weighted gene co-expression network analysis (WGCNA) method was used to construct the network, and the main modules and core genes of co-expression were screened according to the results of gene expression and module function enrichment analysis. According to the correlation of gene expression, the network was divided into 19 modules. By analyzing the expression patterns of each module gene, Blue, Salmon and Yellow were identified as the key modules of peony heat response related functions. GO and KEGG functional enrichment analysis was performed on the genes in the three modules and a network diagram was constructed. Based on this, two key genes PsWRKY53 (TRINITY_DN60998_c1_g2, TRINITY_DN71537_c0_g1) and PsHsfB2b (TRINITY_DN56794_c0_g1) were excavated, which may play a key role in the heat shock response of peony. The three co-expression modules and two key genes were helpful to further elucidate the heat resistance mechanism of P. suffruticosa 'Hu Hong'.

Piecewise-potential-field-based path planning method for fixed-wing UAV formation.

The multi-UAV path planning method based on artificial potential field (APF) has the advantage of rapid processing speed and the ability to deal with dynamic obstacles, though some problems remain-such as a lack of consideration of the initial heading constraint of the UAVs, making it easy to fall into a local minimum trap, and the path not being sufficiently smooth. Consequently, a fixed-wing UAV formation path planning method based on piecewise potential field (PPF) is proposed, where the problem of UAV formation flight path planning in different states can be solved by suitable design of the PPF function. Firstly, the potential field vector can be used to represent the potential field functions of obstacles and target points to meet the kinematic constraints of the UAV. Secondly, the local minimum region can be detected, the additional potential field vector being set to break away from this region. Finally, the change rules of the potential field vector of a UAV in the formation reconstruction scene can be designed, a smooth formation flight track being assured by adjusting the corresponding speed of each UAV track point. Considering the path planning of a five-UAV formation as an example, we conducted simulation experiments. The results showed that-compared with the existing methods based on APF-the results obtained using the PPF-based method considered the initial heading limits of the UAVs, the planned path being considerably smoother. Moreover, the proposed method could plan multiple UAV tracks, satisfying the known constraints without conflict in complex scenarios.

Healthcare Wearable Sensors Adhesion to Human Fingernails and Toenails.

A novel adhesion method of a sensor to a fingernail is described. Wearable sensors can provide health insights to humans for a wide variety of benefits, such as continuous wellness monitoring and disease monitoring throughout a patient's daily life. While there are many locations to place these wearable sensors on the body, we will focus on the fingertip, one significant way that people interact with the world. Like artificial fingernails used for aesthetics, wearable healthcare sensors can be attached to the fingernail for short or long time periods with minimal irritation and disruption to daily life. In this study the structure and methods of healthcare sensors' attachment and removal have been explored to support (1) the sensor functional requirements, (2) biological and environmentally compatible solutions and (3) ease of attachment and removal for short- and long-term user applications. Initial fingernail sensors were attached using a thin adhesive layer of commonly available cosmetic nail glue. While this approach allowed for easy application and strong adhesion to the nail, the removal could expose the fingernail and finger to a commercially available cosmetic nail removal (acetone-based chemical) for extended times measured in minutes. Therefore, a novel structure and method were developed for rapid healthcare sensor attachment and removal in seconds, which supported both the sensor functional objectives and the biologically and environmentally safe use objectives.

The effects of biogenic amines in Chinese Huangjiu on the behavior of mice and hangover headache-related indices.

Huangjiu (Chinese rice wine) is a popular and traditional alcoholic beverage in China; however, the consumption of Huangjiu readily results in hangover symptoms. The aim of this study was to identify the main components associated with behavioral inhibition, headache, and the relevant mechanisms by using a mice hangover model. The results of an open-field experiment revealed that the key biogenic amine associated with mice behavior was histamine, which inhibited the behavior activity of mice in a dose-dependent manner. Moreover, histamine treatment decreased the levels of serotonin (5-HT) and 5-hydroxyindole acetic acid. In addition, the levels of dopamine and nitric oxide, which are associated with migraine, increased in the brain tissue of mice. In addition, the expression of receptor genes of 5-HT, including Htr1a, Htr1f, and Htr2c, is essential in regulating various behaviors and mental activities. In conclusion, the present study demonstrated that histamine is a key component in Huangjiu, and it is related to hangover symptoms by affecting the level of 5-HT and its receptors.

Construction of Non-Biaryl Atropisomeric Amide Scaffolds Bearing a C-N Axis via Enantioselective Catalysis.

The significant scaffold offered by atropisomeric amides with a C-N chiral axis has been extensively utilized for pharmaceuticals, agricultural science, and organic syntheses. As a result, the field of atropisomer synthesis has attracted considerable interest within chemistry communities. To date, a range of catalytic atroposelective approaches has been reported for the efficient construction of these challenging scaffolds. However, greatly concise and highly useful methodologies for the synthesis of these atropisomeric compounds, focusing on transition-metal, chiral amine, and phosphoric acid catalysis reactions, etc., are still desirable. Hence, it is indispensable to succinctly and systematically present all such reports by means of disclosing the mechanistic analysis and application, as well as the challenges and issues associated with the establishment of these atropisomers. In this review, we summarize the development of catalytic asymmetric synthetic strategies to access non-biaryl atropisomers rotating around a C-N chiral axis, including the reaction methods, mechanism, late-stage transformations, and applications.

Dynamic Parameter Calibration Framework for Opinion Dynamics Models.

In the past decade, various opinion dynamics models have been built to depict the evolutionary mechanism of opinions and use them to predict trends in public opinion. However, model-based predictions alone cannot eliminate the deviation caused by unforeseeable external factors, nor can they reduce the impact of the accumulated random error over time. To solve this problem, we propose a dynamic framework that combines a genetic algorithm and a particle filter algorithm to dynamically calibrate the parameters of the opinion dynamics model. First, we design a fitness function in accordance with public opinion and search for a set of model parameters that best match the initial observation. Second, with successive observations, we tracked the state of the opinion dynamic system by the average distribution of particles. We tested the framework by using several typical opinion dynamics models. The results demonstrate that the proposed method can dynamically calibrate the parameters of the opinion dynamics model to predict public opinion more accurately.

Load balancing for multi-threaded PDES of stochastic reaction-diffusion in neurons.

Stochastic simulation of chemical reactions and diffusion in a neuron helps to provide a realistic view of the molecular dynamics within a neuron. We developed a multi-threaded PDES simulator, Neuron Time Warp-Multi Thread, suitable for the stochastic simulation of reaction and diffusion in a neuron. In this paper we make use of Q-Learning and Simulated Annealing to determine the parameters for a dynamic load balancing algorithm and for dynamic window control. During the simulation, the runtime statistics of each thread are collected and used to determine the execution time of the simulation. Based upon this assessment, workload is migrated from the most overloaded threads to the most under-load ones. As the results for a calcium wave model show, both approaches can improve the execution time for small simulations by up to 31% (Q-Learning) and 19% (SA). The simulated annealing approach is more suitable for larger populations, decreasing execution time by 41%.

Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons.

Cells exhibit stochastic behavior when the number of molecules is small. Hence a stochastic reaction-diffusion simulator capable of working at scale can provide a more accurate view of molecular dynamics within the cell. This paper describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. To the best of our knowledge, this is the first parallel discrete event simulator oriented towards stochastic simulation of chemical reactions in a neuron. The simulator was developed as part of the NEURON project. NTW-MT is optimistic and thread-based, which attempts to capitalize on multi-core architectures used in high performance machines. It makes use of a multi-level queue for the pending event set and a single roll-back message in place of individual anti-messages to disperse contention and decrease the overhead of processing rollbacks. Global Virtual Time is computed asynchronously both within and among processes to get rid of the overhead for synchronizing threads. Memory usage is managed in order to avoid locking and unlocking when allocating and de-allocating memory and to maximize cache locality. We verified our simulator on a calcium buffer model. We examined its performance on a calcium wave model, comparing it to the performance of a process based optimistic simulator and a threaded simulator which uses a single priority queue for each thread. Our multi-threaded simulator is shown to achieve superior performance to these simulators. Finally, we demonstrated the scalability of our simulator on a larger CICR model and a more detailed CICR model.

Reusable component model development approach for parallel and distributed simulation.

Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different simulation platforms and applications. To address the problem, this paper first proposed a reusable component model framework. Based on this framework, then our reusable model development approach is elaborated, which contains two phases: (1) domain experts create simulation computational modules observing three principles to achieve their independence; (2) model developer encapsulates these simulation computational modules with six standard service interfaces to improve their reusability. The case study of a radar model indicates that the model developed using our approach has good reusability and it is easy to be used in different simulation platforms and applications.

Synaptic plasticity and memory functions achieved in a WO3-x-based nanoionics device by using the principle of atomic switch operation.

A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO3-x-based nanoionics device and can be precisely and cumulatively controlled by adjusting the device's resistance state and input pulse parameters such as the amplitude, interval, and number. This control is analogous to biological synaptic plasticity including short-term plasticity, long-term potentiation, transition from short-term memory to long-term memory, forgetting processes for short- and long-term memory, learning speed, and learning history. A compact WO3-x-based nanoionics device with a simple stacked layer structure should thus be a promising candidate for use as an inorganic synapse in artificial neural networks due to its striking resemblance to the biological synapse.

Room temperature multiferroicity in Bi(4.2)K(0.8)Fe(2)O(9+δ).

Magnetoelectric multiferroics are materials that have coupled magnetic and electric dipole orders, which can bring novel physical phenomena and offer possibilities for new device functions. In this report, single-crystalline Bi(4.2)K(0.8)Fe(2)O(9+δ) nanobelts which are isostructural with the high-temperature superconductor Bi(2)Sr(2)CaCu(2)O(8+δ) are successfully grown by a hydrothermal method. The regular stacking of the rock salt slabs and the BiFeO(3)-like perovskite blocks along the c axis of the crystal makes the Bi(4.2)K(0.8)Fe(2)O(9+δ) nanobelts have a natural magnetoelectric-dielectric superlattice structure. The most striking result is that the bulk material made of the Bi(4.2)K(0.8)Fe(2)O(9+δ) nanobelts is of multiferroicity near room temperature accompanied with a structure anomaly. When an external magnetic field is applied, the electric polarization is greatly suppressed, and correspondingly, a large negative magnetocapacitance coefficient is observed around 270 K possibly due to the magnetoelectric coupling effect. Our result provides contributions to the development of single phase multiferroics.

Spatial and seasonal variations of pesticide contamination in agricultural soils and crops sample from an intensive horticulture area of Hohhot, North-West China.

The spatial variability and temporal trend in concentrations of the organochlorine pesticides (OCPs), hexachlorocyclohexane (HCH) and dichlorodiphenyltrichloroethane (DDT), in soils and agricultural corps were investigated on an intensive horticulture area in Hohhot, North-West China, from 2008 to 2011. The most frequently found and abundant pesticides were the metabolites of DDT (p,p'-DDE, p,p'-DDT, o,p'-DDT and p,p'-DDD). Total DDT concentrations ranged from ND (not detectable) to 507.41 ng/g and were higher than the concentration of total HCHs measured for the range of 4.84-281.44 ng/g. There were significantly positive correlations between the ∑DDT and ∑HCH concentrations (r (2)>0.74) in soils, but no significant correlation was found between the concentrations of OCPs in soils and clay content while a relatively strong correlation was found between total OCP concentrations and total organic carbon (TOC). ß-HCH was the main isomer of HCHs, and was detected in all samples; the maximum proportion of ß-HCH compared to ∑HCHs (mean value 54%) was found, suggesting its persistence. The α/γ-HCH ratio was between 0.89 and 5.39, which signified the combined influence of technical HCHs and lindane. Low p,p'-DDE/p,p'-DDT in N1, N3 and N9 were found, reflecting the fresh input of DDTs, while the relatively high o,p'-DDT/p,p'-DDT ratios indicated the agricultural application of dicofol. Ratios of DDT/(DDE+DDD) in soils do not indicate recent inputs of DDT into Hohhot farmland soil environment. Seasonal variations of OCPs featured higher concentrations in autumn and lower concentrations in spring. This was likely associated with their temperature-driven re-volatilization and application of dicofol in late spring.

Dynamic properties of spin cluster glass and the exchange bias effect in BiFeO3 nanocrystals.

A spin cluster glass behavior and a complicated exchange bias effect are observed in high quality BiFeO(3) nanocrystals grown by a hydrothermal method. The dynamic properties of the spin clusters investigated by measuring the frequency dependences of ac susceptibility show that the relaxation process can be described using a power law with the glass transition temperature T(g) = 57 K, relaxation time constant τ(0) = 4.4 × 10(-10) s, and critical exponent zv = 10.3 ± 1.9, consistent with a three-dimensional Ising spin glass. The exchange bias field (H(EB)) varies non-monotonically with temperature and achieves a minimum at T(g). The abnormal shift of hysteresis loops above T(g) may be interpreted in terms of a Malozemoff's random-field model with a framework of antiferromagnetic core/spin-cluster shell structure and a two-dimensional diluted antiferromagnet in a field (2D-DAFF) model, respectively. The exchange anisotropy of the BiFeO(3) nanocrystals will shed light on a possible application for magnetism related nanosized devices.

Abstract Next Subvolume Method: a logical process-based approach for spatial stochastic simulation of chemical reactions.

The spatial stochastic simulation of biochemical systems requires significant calculation efforts. Parallel discrete-event simulation is a promising approach to accelerate the execution of simulation runs. However, achievable speedup depends on the parallelism inherent in the model. One of our goals is to explore this degree of parallelism in the Next Subvolume Method type simulations. Therefore we introduce the Abstract Next Subvolume Method, in which we decouple the model representation from the sequential simulation algorithms, and prove that state trajectories generated by its executions statistically accord with those generated by the Next Subvolume Method. The experimental performance analysis shows that optimistic synchronization algorithms, together with careful controls over the speculative execution, are necessary to achieve considerable speedup and scalability in parallel spatial stochastic simulation of chemical reactions. Our proposed method facilitates a flexible incorporation of different synchronization algorithms, and can be used to select the proper synchronization algorithm to achieve the efficient parallel simulation of chemical reactions.

[Transpiration of Brassica chinensis L. in a plastic greenhouse covered with insect-proof nets in lower reaches of Yangtze River: a simulation study].

With the climate data inside and outside a plastic greenhouse as driving variables, and the greenhouse structure, insect-proof net material, and characteristic breadth and leaf area index of Brassica chinensis L. as parameters; a canopy transpiration model for greenhouse B. chinensis was established, based on Penmam-Monteith transpiration model. This established model was validated by the experimental data of independent samples in a single greenhouse. The results showed that in lower reaches of Yangtze River, the vent discharge coefficient (Cd) of greenhouse covered with 20-, 25-, and 28- mesh insect-proof nets was 0.771, 0.758 and 0.736, and the wind pressure coefficient (Cw) was 0.33, 0.37, and 0.39, respectively. The determination coefficient (R2) between the predicted and measured canopy transpiration rate for the sunny, cloudy, and overcast days in summer was 0.95, 0.91, and 0.94, root mean squared error (RMSE) was 0.018, 0.014, and 0.015 g x m(-2) x s(-1), and relative prediction error (RE) was 14.27%, 18.05%, and 15.80%, respectively, suggesting that this model could better predict the transpiration rate of B. chinensis in the plastic greenhouse covered with insect-proof nets in lower reaches of Yangtze River.

[Characteristics analysis of micro-element contents in western Erdos soil and in Tetraena mongolica plant].

This paper studied why the ex-situ conservation of Tetraena mongolica isn't successful. Through measuring and analyzing the micro-element contents in the soil where Tetraena mongolica is naturally distributed and where Tetraena mongolica is introduced in western Erdos. The results showed that among the areas where Tetraena mongolica is native to and the ex situ protection area, the average contents of 9 micro-elements, except B, are not only obviously higher than the average values in China's soil, but also higher than the values in desert areas. The contents of all micro-elements, except Cu, in the ex situ protection area are higher than desert and the natural distribution areas of Tetraena mongolica. Among the contents of the micro-elements in Tetraena mongolica plant, Fe, Cu, Zn, B, Se and Co are quite higher than that in other plant species on steppes, and Mo is higher than that in other plant species but is only 50% to the desert plants. The correlation coefficient for the contents of micro-elements between soil and plants (including adults and seedlings) are not significant and the contents in Tetraena mongolica plant are much higher than available contents of the counterparts in soil. By comparing the contents of micro-elements in Tetraena mongolica, grassland plants on steppe and desert and the contents in soil, it can be seen that every micro-element was enriched by Tetraena mongolica during its growth. The results do not support the suggestion that the contents of micro-elements in soil is the factor restricting the growth of Tetraena mongolica in the ex situ protection area.