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Generally, there is a seismogenic process before rockbursts occurrence, accompanied by formation of a great amount of micro-cracks and release of micro-seismic energy (micro-seismic precursor). The micro-seismic precursory information can be captured by micro-seismic monitoring equipment. As the micro-seismic activities are of temporal priority and spatial consistency with rockbursts events, the rockburst-prone zone can be predicted accurately. Firstly, Based on the great number of rockbursts events recorded during construction of the headrace tunnels of Jinping II Hydropower Station, the characteristics and mechanism of rockbursts and the role of geological structures are summarized in this essay. And a method was presented that the micro-seismic monitoring technology was employed in rockburst monitoring and early warning during construction of the deep-buried headrace tunnels. Full-time continuous monitoring of micro-seismic activities was realized. Comparison analysis was conducted between the rockbursts and microseismic monitoring results according to the site condition. The relationship between the spatial and temporal evolution of microseismic activities and rockbursts was revealed. The rockbursts analysis, monitoring and early warning practices indicate that: In deep-buried rock tunnels, the tempo-spatial distribution of rockbursts and rockburst intensity follow a certain law. A certain correlation exists between the occurrence of rockbursts and the influencing factors, such as the geological structure, construction method, and excavation disturbance, among which the geological structure plays a crucial role. The engineering practices in this study have proven that application of the microseismic monitoring technology in rockburst monitoring and early warning for deep-buried rock tunnels is feasible and the results are reasonably accurate, which changes the traditional viewpoint that the rockburst is unpredictable. The study in this essay provides a new research idea in rockburst prediction and safe construction for tunnels.

A consistently diamagnetic persistent current (PC) of period halving ( Φ 0 /2-current) observed in mesoscopic rings is in apparent contradiction with the theoretical prediction of barely exclusively paramagnetism . By developing a super-cell method, we analytically and numerically study the magnetic response mechanics of non-interacting mesoscopic rings in both the absence and presence of random disorder. A maximal paramagnetic and/or diamagnetic PC is obtained in primary Φ 0 - and/or Φ 0 /2-period, exhibiting a remarkable quantum size effect. It is shown that for lower free energy, an electron circling the ring accumulates an additional phase on each inter-channel transition induced by magnetic flux, leading to the period halving and the paramagnetic–diamagnetic transition. Our results can well mediate the disputes between the experiments and theory.

To improve the knowledge of nematode communities in the Liaohe estuary, the spatiotemporal variations of free-living nematode communities (density, diversity and trophic structure) in the protected zone (PZ) and the development zone (DZ) were seasonally studied. Soil nematode communities were analysed at the depths of 0–10 and 10–20 cm. The results showed that bacterial feeder nematodes were the most abundant trophic groups in both depths and at both sites. Nematode abundance and plant-parasitic nematodes maturity index/maturity index in the DZ were higher than that in the PZ ( p p

Anencephaly is one of the most serious forms of neural tube defects (NTDs), a group of congenital central nervous system (CNS) malformations. MicroRNAs (miRNAs) are involved in diverse biological processes via the post-transcriptional regulation of target mRNAs. Although miRNAs play important roles in the development of mammalian CNS, their function in human NTDs remains unknown. Using a miRNA microarray, we identified a unique expression profile in fetal anencephalic brain tissues, characterized by 70 upregulated miRNAs (ratio ≥ 2) and 7 downregulated miRNAs (ratio ≤ 0.5) compared with healthy human samples. Ten miRNAs with altered expression were selected from the microarray findings for validation with real-time quantitative reverse transcription-polymerase chain reaction. We found that in anencephalic tissues, miR-22, miR-23a, miR-34a, miR-103, miR-125a, miR-132, miR-134, miR-138, and miR-185 were significantly upregulated, while miR-149 was significantly downregulated. Furthermore, 459 potential target genes within the validated miRNAs were revealed using combined four target prediction algorithms in the human genome, and subsequently analyzed with the Molecule Annotation System 3.0. A total of 119 target genes were ultimately identified, including those involved in 22 singular annotations (i.e., transcription, signal transduction, and cell cycle) and 55 functional pathways [i.e., mitogen-activated protein kinase (MAPK) signaling pathway, and actin cytoskeleton regulation]. Six target genes (HNRPU, JAG1, FMR1, EGR3, RUNX1T1, and NDEL1) were chosen as candidate genes and associated with congenital birth abnormalities of the brain structure. Our results, therefore, suggest that miRNA maladjustment mainly contributes to the etiopathogenesis of anencephaly via the MAPK signaling pathway.

The recent development of silicon-based microreactors requires conventional catalyst carriers to be trimmed down to the sub-micrometer regime while keeping their complex geometrical shapes unchanged. In this work, we use a “top-down” etching approach to fabricate Al 2 O 3 nano-trilobe carriers from the inter-channel parts of pseudo-hexagonally arranged one-dimensional channels of anodic alumina membranes. With a dilute NaOH (0.04 M) etchant and prolonged etching time (1.5 h), highly regulated Al 2 O 3 nanocarriers have been prepared into two major forms: well-aligned (bundles) and freestanding trilobes. It has been found that the Al 2 O 3 nano-trilobes are generated only on the upward facing of the membranes owing to the support provided by less etched membrane underneath and a less vibrant region in fluid exchange. The etching process can be described as a nucleophilic reaction that involves an attachment of hydroxyl ions to Lewis acid sites of aluminum cations. The amorphous as-prepared nano-trilobes can be further heat-treated to any crystallographic phases. For example, phase pure polycrystalline θ-Al 2 O 3 nano-trilobes have been prepared at 1000 °C in laboratory air. Future applications of these nanocarriers have also been discussed.

Double-C 60 -end-capped poly(ethylene oxide) (FPEOF) was reinforced with acid-treated multi-walled carbon nanotubes (MWNTs). The storage modulus of FPEOF was significantly enhanced, whereas the crystallization behavior was not significantly affected upon the incorporation of MWNTs. Fourier transform infrared spectroscopy showed the existence of hydrogen-bonding interactions between the ether oxygen atoms on FPEOF and proton-donating functionalities on the MWNTs, leading to a strong matrix-filler interfacial adhesion. The low-temperature storage modulus of a FPEOF/MWNT composite (6.0 GPa) is more than twice that of a poly(ethylene oxide)/fluorinated single-walled carbon nanotube composite (2.5 GPa) with the same nanotube loading of 4 wt%. The thermal stability of FPEOF is also improved by the addition of MWNTs.

In situ functionalized multi-walled carbon nanotube (MWNT)/Phenoxy composites were prepared by melt mixing Phenoxy with MWNT and 1-(aminopropyl)imidazole (NIm). Composites with 4.8 wt% or more of in situ functionalized MWNT show higher storage modulus than Phenoxy, provided a sufficient amount of NIm was used to aid in the dispersion of the hydrophobic MWNTs in the hydrophilic Phenoxy matrix.

A simple and reliable method has been developed for the controlled growth of well-aligned carbon nanotubes patterns with different sizes and shapes on a silicon substrate. A patterned film of sputtered cobalt on the silicon was prepared by a lift-off process, and the carbon nanotubes were grown via chemical vapor deposition using ethylenediamine as a precursor. The carbon nanotubes are vertically aligned with high density within the micro patterns. The diameter of carbon nanotubes is determined by the thickness of cobalt film while the length of the nanotubes can be controlled by varying the reaction time. The bamboo-like multi-walled carbon nanotubes have been observed by high-resolution transmission electron microscopy. The micro-Raman spectrum further confirmed the graphitic structure of the nanotubes. The potential application of the carbon nanotubes to flat-panel displays is demonstrated by the ability to provide stable high field-emission current densities.

A simple method has been developed for growth of well-aligned carbon nanotubes (CNTs) on nickel-film quartz plates by chemical vapor deposition (CVD) with organic ethylenediamine as a precursor. High-density carbon nanotubes were vertically aligned on a large area of the quartz plates. The height of the nanotube array could be controlled by varying the CVD time. High-resolution transmission electron microscopy analysis revealed that the multiwalled CNTs were composed of crystalline graphitic sheets with a bamboo structure.

Many aspects of high temperature electrolysis cell operation have been studied experimentally in recent years, including the freezing and melting of electrolyte, the dissolution of added solute material, replacement of anodes and the degradation of the cell's top crust. The present paper reviews this work for the specific case of aluminium electrolysis cells and describes a mathematical model for the cell enthalpy balance which allows the combined effect of all the process kinetics to be observed over time. Comparison of model predictions with dynamic industrial cell measurements is performed where possible, and this demonstrates the importance of interfacial heat transfer from the electrolyte to the cell walls and to feed materials—alumina and anode carbon. The model is then applied to the analysis of generic energy imbalances in a modern industrial electrolysis cell. The causes of these energy imbalances are identified and the consequences for cell performance are predicted using the model. Key issues in the modelling of electrolysis cells identified from these applications, include the importance of different time-scales in mathematically stiff systems, and the unusual behaviour of electrolyte superheat under certain energy imbalance conditions.

The paper compares the performances of multilayer perceptrons (MLPs) and radial basis function (RBF) networks in detecting clouds in NOAA/AVHRR images. The main results show that the RBF networks are able to handle complex atmospheric and oceanographic phenomena while conventional rule-based systems and MLPs cannot. In particular, the experimental evaluations show that the RBF networks can converge to global minima while the MLPs can only achieve this occasionally, and that classification errors made by the RBF networks decrease dramatically when the number of basis functions increases. In addition, these errors are almost identical when the number of basis functions reaches a threshold. Only on a few rare occasions does the backpropagation algorithm attain an optimal solution and the classification errors made by the MLPs are comparable to (but still larger than) the ones made by the RBF networks. However, the results show that achieving such optimal solutions is difficult. It is, therefore, concluded that the RBF networks are better than the MLPs for cloud detection.

In speaker verification, the cohort and world models have been separately used for scoring normalization. The authors embed the two models in elliptical basis function networks and propose a two-stage decision procedure for improving verification performance. The procedure begins with normalization of an utterance by a world model. If the difference between the resulting score and a world threshold is sufficiently large, the claimant is accepted or rejected immediately. Otherwise, the score will be normalized by a cohort model, and the resulting score will be compared with a cohort threshold to make a final accept/reject decision. Experimental evaluations based on the YOHO corpus suggest that the two-stage method achieves a lower error rate as compared to the case where only one background model is used.

This paper investigates the application of a particular type of probabilistic neural networks, namely radial basis function (RBF) networks, to detecting cloud in NOAA/AVHRR images. Based on the images collected from the East China Sea, the paper compares the performance of RBF networks with that of traditional multi-layer perceptrons (MLPs). The main results show that RBF networks are able to handle complex atmospheric and oceanographic phenomena while MLPs could not. The internal representation of the RBF networks and MLPs are also detailed in this paper.

The cohort and world models are commonly used for scoring normalization in speaker verification. As these models represent different regions of the feature space, a better solution could be obtained by integrating them into a single framework. In this paper, we embed the two models in elliptical basis function networks and propose a two-stage decision procedure for improving verification performance. In the first stage, the score of an unknown utterance is normalized by a world model. If the difference between the resulting normalized score and a world threshold is sufficiently large, the claimant is accepted or rejected immediately. Otherwise, the score will be normalized by a cohort model and compared with a cohort threshold to make a final accept/reject decision. Experimental evaluations based on the YOHO corpus suggest that the two-stage method achieves a lower error rate as compared to the case where only one background model is used.