Test and Analysis of TIG-MIG Hybrid Welding Are

A high-speed camera is used to observe the arc starting and arc stabilization process of the TIG-MIG hybrid welding system. Paschen’s law is used to analyze the path of TIG welding arc breakdown under the condition of the conductive channel provided by the MIG welding arc, and the arc starting process of the double arc hybrid welding is determined. The study found that when the electrode spacing is less than 8.5 mm, two molten pools can form a common molten pool after arc initiation of MIG welding; when the spacing is 10 mm, the two molten pools after arc initiation form a “8” shape; When the distance is 12 mm, there is a low temperature zone between the two arcs, which is separated.

Stabilization of Long-Pitch Supertwisted Nematic Structures

Stabilized reverse twisted nematic liquid crystal devices (RTN-LCDs) were fabricated using formation of a polymer matrix under UV irradiation with an applied voltage (sustain voltage) in the vicinity of the alignment layers. In the absence of an applied voltage, the non-stabilized RTN structure gradually returns to a splay twist structure. The sustain voltage was decreased with an increase in temperature. A stabilized long-pitch supertwisted nematic (LPSTN) structure could also be formed during the RTN structure stabilization process with a much lower sustain voltage at a temperature near the clearing point. The chiral pitch for the LPSTN structure is longer than that for a typical STN structure. LPSTN-LCDs similar to RTN-LCDs show a large reduction in both the threshold and saturation voltage compared with those for TN-LCDs consisted of the same LC materials. Furthermore, a notable feature of LPSTN-LCDs is a change to a TN structure when a high voltage is applied. A black state can be realized due to the change from the LPSTN structure to the RTN structure unlike the typical STN mode under the crossed nicols condition. In contrast STN-LCDs retain their color due to the retardation because the RTN and LPSTN states are considered topologically equivalent.

Application Analysis of Radial Basis Function Neural Network Algorithm of Genetic Algorithm for Environmental Restoration and Treatment Effect Evaluation of Decommissioned Uranium Tailings Ponds

A new analysis method for the environmental stability of uranium tailing ponds is established in this paper, and the stability intervals and environmental stability rates of indicators are defined in precise mathematical language and analyzed with examples. The results show that the overall environmental stability of this uranium tailings pond is still in a poor state after the first phase of decommissioning treatment, and special decommissioning treatment should be carried out for factors such as pH and radionuclides Po and Pb. Using the powerful nonlinear mapping function of the artificial neural network, a radial basis function neural network algorithm was constructed to predict the environmental stability of the uranium tailing pond. It provides a new feasible method for the comprehensive evaluation technology of uranium tailings ponds. Accuracy in DOA Estimation. The research work in this paper mainly analyzed the environmental stabilization process and stability of decommissioned uranium tailings ponds, proposed a new concept of environmental stability with ecological and environmental protection concepts and gave it a new connotation, established an environmental stability evaluation index system for decommissioned uranium tailings ponds through index screening by using rough set theory, comprehensively considered the influence of environmental factors such as external wastewater and exhaust gas, and realized the multifactor. The system of evaluation indexes for the stability of decommissioned uranium tailings ponds was established by combining multiple factors, and the long-term monitoring and modeling of the environmental stabilization process of decommissioned uranium tailings ponds was carried out by using mathematical methods. The results show that the RBFNN-GA algorithm can reduce the training error of the random radial basis function neural network, improve the generalization ability of the network, and make it capable of handling large data sets.

NON-LINEAR SUSCEPTIBILITY TO INTERFERENCES IN DECLARATIVE MEMORY FORMATION

After encoding, memories go through a labile state followed by a stabilization process known as consolidation. Once consolidated they can enter a new labile state after the presentation of a reminder of the original memory, followed by a period of re-stabilization (reconsolidation). During these periods of lability the memory traces can be modified. Currently, there are studies that show a rapid stabilization after 30 min, while others show that stabilization occurs after longer periods (e.g. 6 h). Here we investigate the effect of an interference treatment on declarative memory consolidation, comparing distinct time intervals after acquisition. On day 1, participants learned a list of non- syllable pairs (List 1). Immediately after, 30 min, 3 h or 8 h later, they received an interference list (List 2) that acted as an amnesic agent. On day 2 (48 h after training) participants had to recall List 1 first, followed by List 2. We found that the List 1 memory was susceptible to interference when the List 2 was administered immediately or 3 h after learning; however, shortly after acquisition (e.g. 30 min) the List 1 memory becomes transiently protected against interference. We propose the possibility that this rapid memory protection could be induced by a fast and transient neocortical integration (where the memory is transiently protected) becoming partially independent from the hippocampus followed by a hippocampal re-engagement where the memory becomes susceptible to interferences again. Our results open a discussion about the contribution of molecular and systemic aspects to memory consolidation.

Effect of Polyacrylonitrile Precursor Orientation on the Structures and Properties of Thermally Stabilized Carbon Fiber

The thermal stabilization process of polyacrylonitrile (PAN) precursor fiber was the key step to prepare high-performance carbon fiber. During the thermal stabilization process, the aggregation structure and the reactivity of molecular chains have significant effects on the microstructures and mechanical properties of carbon fiber. In the present paper, the effects of the orientation structure of PAN precursor fiber on the thermal stabilization reaction and the mechanical properties of carbon fiber were experimentally studied. Using multi-dimensional structural and mechanical properties tests, such as XRD, DSC, 13C NMR and Instron machine testing, the crystalline and skeleton structure, exothermic behavior, and tensile properties of PAN precursor fiber with different orientations in the process of thermal stabilization were characterized to reveal the relationship between microstructure evolution and tensile properties. The results showed that the orientation structure of PAN precursor fiber had an obvious effect on the thermal stabilization process and the tensile stress–strain characteristic. When the heat treatment temperature was lower than 200 °C, the crystallinity and crystallite size of PAN fibers with higher orientation degrees increased significantly. After sufficient thermal stabilization, the original PAN precursor fiber with a higher orientation degree could form more aromatic lamellar structures and showed better regularity. Furthermore, the yield strength and initial modulus of the fibers with a higher orientation degree increased due to the formation of more aromatic rings. The maximum increase in the percentages of yield strength and tensile modulus of the PAN fibers were achieved when the heat-treated temperature was 200 °C, and the percentage values were 138.4% and 158.7% compared to the precursor without heat-treatment. In addition, the elongation at break of the fibers with a higher orientation degree was also relatively larger.