This experiment explored the effects of single application of seven types of slow- and controlled-release fertilizers on rice yield and various population characteristics. Based on a study of the ...nitrogen (N) release characteristics of these fertilizers, pot experiments were conducted in 2018 and 2019 with split fertilization (CK, urea applied split equally at basal and panicle initiation stages, respectively) as control, which assessed the effects on SPAD value, yield and yield components, dynamic changes of rice tillers and dry matter accumulation. The results showed that the N release characteristics of different types of slow- and controlled-release fertilizers were significantly different. Polymer-coated urea (PCU) showed a controlled-release mode and provided sustained release throughout the whole growth stages. Sulfur-coated urea (SCU) exhibited a slow-release mode, providing insufficient release at the middle and late stages. Urease inhibitor urea (AHA) and urea-formaldehyde (UF) yielded a rapid-release mode, with an explosive N release at the early stage and no release at the middle and late stages. These results showed that PCU delayed the peak seedling stage. Compared with CK, dry matter accumulation and SPAD showed no significant differences, and due to the continuous release of N throughout the growth stages, rice yield, spikelets per panicle, seed setting rate, and 1 000-grain weight were all increased. Owing to the lack of N supply at the late stage and the low number of spikelets, SCU led to a reduction of rice yield, which is nevertheless not statistically significant. AHA and UF were susceptible to environmental factors and had varying effects on rice yield. The results of this experiment indicated that given a fixed amount of N applied in a pot, the stronger the N supply capacity and the longer the effective duration time of the fertilizer, the higher the dry matter accumulation at the late growth stage, and the higher the rice yield.
AGRP (agouti-related neuropeptide) expressing inhibitory neurons sense caloric needs of an animal to coordinate homeostatic feeding. Recent evidence suggests that AGRP neurons also suppress competing ...actions and motivations to mediate adaptive behavioral selection during starvation. Here, in adult mice of both sexes we show that AGRP neurons form inhibitory synapses onto ∼30% neurons in the medial preoptic area (mPOA), a region critical for maternal care. Remarkably, optogenetically stimulating AGRP neurons decreases maternal nest-building while minimally affecting pup retrieval, partly recapitulating suppression of maternal behaviors during food restriction. In parallel, optogenetically stimulating AGRP projections to the mPOA or to the paraventricular nucleus of hypothalamus but not to the LHA (lateral hypothalamus area) similarly decreases maternal nest-building. Chemogenetic inhibition of mPOA neurons that express Vgat (vesicular GABA transporter), the population targeted by AGRP terminals, also decreases maternal nest-building. In comparison, chemogenetic inhibition of neurons in the LHA that express vesicular glutamate transporter 2, another hypothalamic neuronal population critical for feeding and innate drives, is ineffective. Importantly, nest-building during low temperature thermal challenge is not affected by optogenetic stimulation of AGRP→mPOA projections. Finally, via optogenetic activation and inhibition we show that distinctive subsets of mPOA Vgat+ neurons likely underlie pup retrieval and maternal nest-building. Together, these results show that AGRP neurons can modulate maternal nest-building, in part through direct projections to the mPOA. This study corroborates other recent discoveries and underscores the broad functions that AGRP neurons play in antagonizing rivalry motivations to modulate behavioral outputs during hunger.
In order for animals to initiate ethologically appropriate behaviors, they must typically decide between behavioral repertoires driven by multiple and often conflicting internal states. How neural pathways underlying individual behaviors interact to coherently modulate behavioral outputs, in particular to achieve a proper balance between behaviors that serve immediate individual needs versus those that benefit the propagation of the species, remains poorly understood. Here, by investigating projections from a neuronal population known to drive hunger behaviors to a brain region critical for maternal care, we show that activation of AGRP→mPOA projections in females dramatically inhibits maternal nest-building while leaving mostly intact pup retrieval behavior. Our findings shed new light on neural organization of behaviors and neural mechanisms that coordinate behavioral selection.
We elucidate here the impact of aging temperature on microstructural evolution and strengthening behavior on low lattice misfit cobalt-free maraging steel. The best combination of high-strength ...(1850 MPa) and high-toughness (125.4 MJ m−3) was obtained at the optimal aging temperature of 520 °C, without sacrificing ductility. Electron back scattered diffraction studies suggested that preferred orientations of {101}, fraction of high-angle grain boundary (HAGB) and total length of grain boundary per unit area (μm/μm2) were increased with increase of aging temperature, which was beneficial to both strengthening and toughening of maraging steel. The strengthening contribution from the precipitates was transformed from shearing mechanism to bypass mechanism when the aging temperature is greater than 520 °C. The aging tempered steel of 520 °C provided maximum strengthening increment of 1463 MPa through shearing mechanism, while granular reverted austenite at this temperature contributed to high toughness.
With the advances of Software-Defined Networks (SDN) and Network Function Virtualization (NFV), Service Function Chain (SFC) has been becoming a popular paradigm to carry and complete network ...services. Such new computing and networking paradigm enables Virtual Network Functions (VNFs) to be placed in software entities/virtual machines over a network of physical equipments in elastic and flexible way with low capital and operation expenses. VNFs are chained together to steer traffic as needed. However, most of the existing traffic steering and routing path computation algorithms for SFC are complex, unscalable, and low time-efficiency. In this paper, we study the VNF Selection and Chaining Problem (VNF-SCP) in SDN/NFV-enabled networks. We formulate VNF-SCP as a Binary Integer Programming (BIP) model in order to compute routing path for each SFC Request (SFCR) with the minimum end-to-end delay. Then, a novel Deep Learning-based Two-Phase Algorithm (DL-TPA) is introduced, where VNF selection network and VNF chaining network are designed to achieve intelligent and efficient VNF selection and chaining for SFCRs. Performance evaluation shows that DL-TPA can achieve high prediction accuracy and time efficiency of routing path computation, and the overall network performance can be improved significantly.
Predatory hunting plays a fundamental role in animal survival. Little is known about the neural circuits that convert sensory cues into neural signals to drive this behavior. Here we identified an ...excitatory subcortical neural circuit from the superior colliculus to the zona incerta that triggers predatory hunting. The superior colliculus neurons that form this pathway integrate motion-related visual and vibrissal somatosensory cues of prey. During hunting, these neurons send out neural signals that are temporally correlated with predatory attacks, but not with feeding after prey capture. Synaptic inactivation of this pathway selectively blocks hunting for prey without impairing other sensory-triggered behaviors. These data reveal a subcortical neural circuit that is specifically engaged in translating sensory cues into neural signals to provoke predatory hunting.
With the aim of gathering temporal trends on bacterial epidemiology and resistance from multiple laboratories in China, the CHINET surveillance system was organized in 2005. Antimicrobial ...susceptibility testing was carried out according to a unified protocol using the Kirby-Bauer method or automated systems. Results were analyzed according to Clinical and Laboratory Standards Institute (CLSI) 2014 definitions. Between 2005 and 2014, the number of bacterial isolates ranged between 22 774 and 84 572 annually. Rates of extended-spectrum β-lactamase production among Escherichia coli isolates were stable, between 51.7 and 55.8%. Resistance of E. coli and Klebsiella pneumoniae to amikacin, ciprofloxacin, piperacillin/tazobactam and cefoperazone/sulbactam decreased with time. Carbapenem resistance among K. pneumoniae isolates increased from 2.4 to 13.4%. Resistance of Pseudomonas aeruginosa strains against all of antimicrobial agents tested including imipenem and meropenem decreased with time. On the contrary, resistance of Acinetobacter baumannii strains to carbapenems increased from 31 to 66.7%. A marked decrease of methicillin resistance from 69% in 2005 to 44.6% in 2014 was observed for Staphylococcus aureus. Carbapenem resistance rates in K. pneumoniae and A. baumannii in China are high. Our results indicate the importance of bacterial surveillance studies.
Understanding the heterosis in multiple environments between different heterotic groups is of fundamental importance in successful maize breeding. A total of 737 hybrids derived from 41 maize inbreds ...were evaluated over two years, with the aim of assessing the genetic diversity and their performance between heterotic groups under drought-stressed (DS) and well-watered (WW) treatments. A total of 38 737 SNPs were employed to assess the genetic diversity. The genetic distance (GD) between the parents ranged from 0.05 to 0.74, and the 41 inbreds were classified into five heterotic groups. According to the hybrid performance (high yield and early maturity between heterotic groups), the heterosis and heterotic patterns of Iowa Stiff Stalk Synthetic (BSSS)×Non-Stiff Stalk (NSS), NSS×Sipingtou (SPT) and BSSS×SPT were identified to be useful options in China's maize breeding. The relative importance of general and specific combining abilities (GCA and SCA) suggests the importance of the additive genetic effects for grain yield traits under the WW treatment, but the non-additive effects under the DS treatment. At least one of the parental lines with drought tolerance and a high GCA effect would be required to achieve the ideal hybrid performance under drought conditions. GD showed a positive correlation with yield and yield heterosis in within-group hybrids over a certain range of GD. The present investigation suggests that the heterosis is due to the combined accumulation of superior genes/alleles in parents and the optimal genetic distance between parents, and that yield heterosis under DS treatment was mainly determined by the non-additive effects.
Biocompatible magnetite nanocrystals (see Figure) are prepared by thermal decomposition of ferric triacetylacetonate in 2‐pyrrolidone in the presence of monocarboxyl‐terminated poly(ethylene glycol) ...(MPEG‐COOH). The results reveal that MPEG is covalently bound to the nanocrystal surface by COOH groups. Magnetic resonance imaging (MRI) experiments indicate that the coated nanocrystals are potential MRI contrast agents due to their excellent water solubility and biocompatibility.
Abstract High-frequency gravitational wave (HFGW) detection is a great challenge, as its signal is significantly weak compared with the relevant background noise in the same frequency bands. ...Therefore, besides designing and running the feasible installation for the experimental weak-signal detection, developing various effective approaches to process the big detected data for extracting the information about the GWs is also particularly important. In this paper, we focus on the simulated time-domain detected data of the electromagnetic response of the GWs in high-frequency band, typically such as Gigahertz. Specifically, we develop an effective deep learning method to implement the classification of the simulated detection data, which includes the strong electromagnetic background noise in the same frequency band, for the parameter estimations of the HFGWs. The simulatively detected data is generated by the transverse first-order electromagnetic responses of the HFGWs passing through a high stationary magnetic field biased by a high-frequency Gaussian beam. We propose a convolutional neural network model to implement the classification of the simulated detection data, whose accuracy can reach more than 90%. With these data being served as the positive sample datasets, the physical parameters of the simulatively detected HFGWs can be effectively estimated by matching the sample datasets with the noise-free template library one by one. The confidence levels of these extracted parameters can reach 95% in the corresponding confidence interval. Through the multiple data experiments, the effectiveness and reliability of the proposed data processing method are verified. The proposed method could be generalized to big data processing for the detection of experimental HFGWs in the future.
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