Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy ...coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.
The energy efficiency of neural signal transmission is thought to be an important constraint in the nervous system. It is generally measured as the energy consumed per unit of information. Most of ...the previous studies have demonstrated this efficiency by focusing on single action potentials. However, neural information is more likely to be encoded by a spike train rather than by a single spike. To date, how the energy efficiency is dependent on patterns of spike trains is still unclear. In this study, we examined the energy efficiency of various firing patterns simulated by the Chay neuron model, including relatively high-frequency activities with massive spikes, medium-frequency activities with a moderate number of spikes, and low-frequency activities with rare spikes. Our results indicate that medium-frequency patterns are more energy efficient than both the high-frequency and low-frequency patterns. The most efficient medium-frequency pattern is a sparse burst firing (SBF) pattern because it consumes minimal energy and transmits an amount of neural information comparable to that of high-frequency patterns which consume much more energy. SBF patterns minimize energy consumption not only by producing fewer spikes than high-frequency patterns, but more importantly, also by consuming available energy sources, namely the potential energy stored in ionic concentration gradients, in a balanced way. Furthermore, with fewer spikes, the irregular spike trains of SBF patterns with short bursts and single spikes maximize the neural information that they carry, leading to higher energy efficiency. Thus, the sensory system may give priority to limiting energy costs over maximizing information to achieve greater energy efficiency.
Low-carbon steel pipelines are frequently used as transport pipelines for various media. As the pipeline transport industry continues to develop in extreme directions, such as high efficiency, long ...life, and large pipe diameters, the issue of pipeline reliability is becoming increasingly prominent. This study selected Q235 steel, a typical material for low-carbon steel pipelines, as the research object. In accordance with the pipeline service environment and the accelerated corrosion environment test spectrum, cyclic salt spray accelerated corrosion tests that simulated the effects of the marine atmosphere were designed and implemented. Corrosion properties, such as corrosion weight loss, morphology, and product composition of samples with different cycles, were characterized through appearance inspection, scanning electron microscopy analysis, and energy spectrum analysis. The corrosion behavior and mechanism of Q235 low-carbon steel in the enhanced corrosion environment were studied, and the corrosion weight loss kinetics of Q235 steel was verified to conform to the power function law. During the corrosion process, the passivation film on the surface of the low-carbon steel and the dense and stable α-FeOOH layer formed after the passivation film was peeled off played a role in corrosion resistance. The passivation effect, service life, and service limit of Q235 steel were studied and determined, and an evaluation model for quick evaluation of the corrosion life of Q235 low-carbon steel was established. This work provides technical support to improve the life and reliability of low-carbon steel pipelines. It also offers a theoretical basis for further research on the similitude and relevance of cyclic salt spray accelerated corrosion testing.
Brief bursts of high-frequency spikes are a common firing pattern of neurons. The cellular mechanisms of bursting and its biological significance remain a matter of debate. Focusing on the energy ...aspect, this paper proposes a neural energy calculation method based on the Chay model of bursting. The flow of ions across the membrane of the bursting neuron with or without current stimulation and its power which contributes to the change of the transmembrane electrical potential energy are analyzed here in detail. We find that during the depolarization of spikes in bursting this power becomes negative, which was also discovered in previous research with another energy model. We also find that the neuron’s energy consumption during bursting is minimal. Especially in the spontaneous state without stimulation, the total energy consumption (2.152 × 10
−7
J) during 30 s of bursting is very similar to the biological energy consumption (2.468 × 10
−7
J) during the generation of a single action potential, as shown in Wang et al. (Neural Plast 2017,
2017a
). Our results suggest that this property of low energy consumption could simply be the consequence of the biophysics of generating bursts, which is consistent with the principle of energy minimization. Our results also imply that neural energy plays a critical role in neural coding, which opens a new avenue for research of a central challenge facing neuroscience today.
Cancer is one of the leading causes of death across the world, and the prevalence and mortality rates of cancer will continue to grow. Chemotherapeutics play a critical role in cancer therapy, but ...drug resistance and side effects are major hurdles to effective treatment, evoking an immediate need for the discovery of new anticancer agents. Triazines including 1,2,3‐, 1,2,4‐, and 1,3,5‐triazine have occupied a propitious place in drug design and development due to their excellent pharmacological profiles. Mechanistically, triazine derivatives could interfere with various signaling pathways to induce cancer cell death. Hence, triazine derivatives possess potential in vitro and in vivo efficacy against diverse cancers. In particular, triazine hybrids are able to overcome drug resistance and reduce side effects. Moreover, several triazine hybrids such as brivanib (indole‐containing pyrrolo2,1‐f1,2,4triazine), gedatolisib (1,3,5‐triazine‐urea hybrid), and enasidenib (1,3,5‐triazine‐pyridine hybrid) have already been available in the market. Accordingly, triazine hybrids are useful scaffolds for the discovery of novel anticancer chemotherapeutics. This review focuses on the anticancer activity of 1,2,3‐, 1,2,4‐, and 1,3,5‐triazine hybrids, together with the structure–activity relationships and mechanisms of action developed from 2017 to the present. The enriched structure–activity relationships may be useful for further rational drug development of triazine hybrids as potential clinical candidates.
This review provides the recent developments (2017–present) in triazine hybrids with anticancer potential. The structure–activity relationships as well as mechanisms of action are also discussed to facilitate the further rational design of more effective candidates.
Pipe cleaning is currently the most effective method to improve the cleanliness and corrosion resistance of pipes. In this paper, a new method of pipe cleaning is proposed, combining mechanical and ...chemical cleaning, offline tank cleaning and online cycle cleaning. Through experiments and characterization of the morphology changes, the mechanism of pickling and passivation of Q235 steel was explored, and the entire process of microstructure and morphology changes on the pipe wall’s surface was analyzed to verify the feasibility of this technology. The cleaning process was optimised using response surface analysis to determine the optimum cleaning conditions. This study is of great relevance to the effective operation of continuous-casting equipment over a long period of time.
Summary
High‐quality genome of rosemary (Salvia rosmarinus) represents a valuable resource and tool for understanding genome evolution and environmental adaptation as well as its genetic improvement. ...However, the existing rosemary genome did not provide insights into the relationship between antioxidant components and environmental adaptability. In this study, by employing Nanopore sequencing and Hi‐C technologies, a total of 1.17 Gb (97.96%) genome sequences were mapped to 12 chromosomes with 46 121 protein‐coding genes and 1265 non‐coding RNA genes. Comparative genome analysis reveals that rosemary had a closely genetic relationship with Salvia splendens and Salvia miltiorrhiza, and it diverged from them approximately 33.7 million years ago (MYA), and one whole‐genome duplication occurred around 28.3 MYA in rosemary genome. Among all identified rosemary genes, 1918 gene families were expanded, 35 of which are involved in the biosynthesis of antioxidant components. These expanded gene families enhance the ability of rosemary adaptation to adverse environments. Multi‐omics (integrated transcriptome and metabolome) analysis showed the tissue‐specific distribution of antioxidant components related to environmental adaptation. During the drought, heat and salt stress treatments, 36 genes in the biosynthesis pathways of carnosic acid, rosmarinic acid and flavonoids were up‐regulated, illustrating the important role of these antioxidant components in responding to abiotic stresses by adjusting ROS homeostasis. Moreover, cooperating with the photosynthesis, substance and energy metabolism, protein and ion balance, the collaborative system maintained cell stability and improved the ability of rosemary against harsh environment. This study provides a genomic data platform for gene discovery and precision breeding in rosemary. Our results also provide new insights into the adaptive evolution of rosemary and the contribution of antioxidant components in resistance to harsh environments.
Hydrostatic guideways are used as an alternative to contact bearings due to high stiffness and high damping in heavy machine tools. To improve the dynamic characteristic of bearing structure, the ...dynamic modeling of the hydrostatic guidway should be accurately known. This paper presents a “mass-spring-Maxwell” model considering the effects of inertia, squeeze, compressibility and static bearing. To determine the dynamic model coefficients, numerical simulation of different cases between displacement and dynamic force of oil film are performed with fluent code. Simulation results show that hydrostatic guidway can be taken as a linear system when it is subjected to a small oscillation amplitude. Based on a dynamic model and numerical simulation, every dynamic model’s parameters are calculated by the Levenberg-Marquardt algorithm. Identification results show that “mass-spring-damper” model is the most appropriate dynamic model of the hydrostatic guidway. This paper provides a reference and preparation for the analysis of the dynamic model of the similar hydrostatic bearings.
In this paper, the Lingban entry to the third 'CHiME' speech separation and recognition challenge is presented. A time-frequency masking based speech enhancement front-end is proposed to suppress the ...environmental noise utilizing multi-channel coherence and spatial cues. The state-of-the-art speech recognition techniques, namely recurrent neural network based acoustic and language modeling, state space minimum Bayes risk based discriminative acoustic modeling, and i-vector based acoustic condition modeling, are carefully integrated into the speech recognition back-end. To further improve the system performance by fully exploiting the advantages of different technologies, the final recognition results are obtained by lattice combination and rescoring. Evaluations carried out on the official dataset prove the effectiveness of the proposed systems. Comparing with the best baseline result, the proposed system obtains consistent improvements with over 57% relative word error rate reduction on the real-data test set.
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