非对称碰撞约束下形状记忆合金梁的随机响应与分岔

形状记忆合金(SMA)是二十一世纪具有形状记忆效应的新型智能材料.针对具有非对称约束的SMA梁,本文构造了碰撞振动系统.在无碰撞和有碰撞两种情况下,利用随机平均法给出了近似解析结果.数值模拟作为验证解析结果的工具.结果表明,系统能量的概率响应曲线具有非光滑特性.当约束位置发生变化时,系统会出现随机P分岔和D分岔.     

An Absence of Non-specific Immune Response towards para-Sulphonato-calix[n]arenes

The effects of para-Sulphonato-calix[4]arene, para-Sulphonato-calix[6]arene and para-Sulphonato-calix[8]arene on the activation of NADPH oxidase in neutrophils has been studied. All three molecules do not induce NADPH oxidase activation, and hence do not stimulate neutrophils. Measurement of cell viability demonstrates that these three water-soluble calix[n]arene derivatives are not cytotoxic.     

SHAPE MEMORY EFFECT OF PU IONOMERS WITH IONIC GROUPS ON HARD-SEGMENTS

SMPU （shape memory polyurethane） non-ionomers and ionomers, synthesized with poly（c-caprolactone） （PCL）, 4, 4＇-diphenylmethane diisocyanate （MDI）, 1,4-butanediol （BDO）, dimethylolpropionic acid （DMPA） were measured with cyclic tensile test and strain recovery test. The relations between the structure and shape memory effect of these two series were studied with respect to the ionic group content and the effect of neutralization. The resulting data indicate that, with the introduction of asymmetrical extender, the stress at 100% elongation is decreased for PU non-ionomer and ionomer series, especially lowered sharply for non-ionomer series; the fixation ratio of ionomer series is not affected obviously by the ionic group content; the total recovery ratio of ionomer series is decreased greatly. After sufficient relaxation time for samples stretched beforehand, the switching temperature is raised slightly, whereas the recovery ratio measured with strain recovery test method is lowered with increased DMPA content. The characterization with FT-IR, DSC, DMA elucidated that, the ordered hard domain of the two series is disrupted with the introduction of DMPA which causes more hard segments to dissolve in soft phase; ionic groups on hard segment enhance the cohesion between hard segments especially at high ionic group content and significantly facilitate the phase separation compared with the corresponding non-ionomer at moderate ionic group content.     

STUDIES ON PREPARATION OF INACTIVATED VACCINES FROM CELL CULTURES OF MINK ENTERITIS VIRUS (MEV) AND THEIR IMMUNITY

In this paper, superhigh reproductive rate strains of MEV with titre more than HA8192* or TCID50 log9.7 10 have been achieved both by cultivation in cell lines with different susceptibility to MEV and by isolating and identifying in field by the author. The systematic tests proved that S18 and L12 strains of MEV are the best strains for vaccine preparation. In this study, the best means for the tissue cultivation of MEV and the most advanced technological process for the production and detection of serum-free cell-cultured MEV fluids with super-high HA titre in batches in large quantities have been established for the first time. Optimum conditions for MEV inactivation were determined, and safe and effective inactivated vaccines with mineral oil or A1(OH)3 gel adjuvant were successfully prepared with serum-free cell-cultured MEV fluids. Both vaccines with different adjuvants can be manufactured in batches in large quantities and have been widely used all over China since 1986. The change laws of the imm     

POLYMER NETWORK-POLY(ETHYLENE GLYCOL)COMPLEXES WITH SHAPE MEMORY EFFECT

The complexes of poly(methacrylic acid-co-methyl methacrylate) network with poly(ethylene glycol) stabilized byhydrogen bonds were prepared. By introducing the poly(ethylene glycol), a large difference in storage modulus below andabove the glass transition temperature occurred and the complexes exhibited shape memory behaviors. The morphology ofcomplexes was studied by using DSC, WAXD, and DMA. The results indicate that the fixed phase of this kind of novelshape memory materials is the network, and the reversible phase is the amorphous state of PEG:PMAA complex phase. Theshape recoverability almost reaches 100%. This type of complexes can be regarded as a novel shape memory network.     

Rigorous bounds on the storage capacity of the dilute Hopfield model

We study a neural network model consisting ofN neurons where a dendritic connection between each pair of neurons exists with probabilityp and is absent with probability 1-p. For the Hopfield Hamiltonian on such a network, we prove that ifp c[(lnN)/N]^1/2, the model can store at leastm= _cpN patterns, where _c 0.027 ifc 3 and decreases proportional to 1/(–lnc) forc small. This generalizes the results of Newman for the standard Hopfield model.     

Is Bitcoin’s Carbon Footprint Persistent? Multifractal Evidence and Policy Implications

The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that the persistence of high levels of energy consumption of Bitcoin could have permanent policy implications, we examine the presence of long memory in the daily data of the Bitcoin Energy Consumption Index (BECI) (BECI upper bound, BECI lower bound, and BECI average) covering the period 25 February 2017 to 25 January 2022. Employing fractionally integrated GARCH (FIGARCH) and multifractal detrended fluctuation analysis (MFDFA) models to estimate the order of fractional integrating parameter and compute the Hurst exponent, which measures long memory, this study shows that distant series observations are strongly autocorrelated and long memory exists in most cases, although mean-reversion is observed at the first difference of the data series. Such evidence for the profound presence of long memory suggests the suitability of applying permanent policies regarding the use of alternate energy for mining; otherwise, transitory policy would quickly become obsolete. We also suggest the replacement of ‘proof-of-work’ with ‘proof-of-space’ or ‘proof-of-stake’, although with a trade-off (possible security breach) to reduce the carbon footprint, the implementation of direct tax on mining volume, or the mandatory use of carbon credits to restrict the environmental damage.     

Effect of Poly(methacrylic acid) on the Cytokine Level in an In Vivo Tumor Model

Cancer is a leading cause of mortality globally. Despite remarkable improvements in cancer-treatment approaches, disease recurrence and progression remain major obstacles to therapy. While chemotherapy is still a first-line treatment for a variety of cancers, the focus has shifted to the development and application of new approaches to therapy. Nevertheless, the relationship between immune response, neoplastic diseases and treatment efficiency is not fully understood. Therefore, the aim of the study was to investigate the immunopharmacological effects of methacrylic acid homopolymer in an in vivo tumor model. Materials and methods: Monomeric methacrylic acid was used to synthesize polymers. Methacrylic acid was polymerized in dioxane in the presence of 4-Cyano-4-[(dodecylsulfanylthiocarbonyl)sulfanyl]pentanoic acid. To study the molecular weight characteristics of PMAA by GPC, carboxyl groups were preliminarily methylated with diazomethane. An experimental cancer model was obtained by grafting RMK1 breast cancer cells. The serum levels of IL-6, IL-10, IL-17, transforming growth factor β1 (TGF-β1), and tumor necrosis factor α (TNF-α) were measured by ELISA. Results: The effect of PMAA on the serum concentrations of several cytokines was studied upon its single administration to laboratory animals in early neoplastic process. The IL-6, IL-17 and TGF-β1 concentrations were found to change significantly and reach the level observed in intact rats. The IL-10 concentration tended to normalize. Conclusion: The positive results obtained are the basis for further studies on the effect of methacrylic-acid polymers with different molecular-weight characteristics on the neoplastic process.     

免疫算法在双闭环直流调速系统中的应用

文中对双闭环直流调速系统控制器的选择进行了分析,并借鉴免疫算法强大的寻优能力,提出了基于免疫算法的调速系统控制器参数整定方法.为了分析比较,实际应用中采用了三种控制器参数整定方法,比较结果说明,免疫算法在调速系统控制器参数整定中的应用是更加有效的.通过在单晶炉拉晶过程的应用,证明该方法可行性和正确性.     

Alpha-Beta Hybrid Quantum Associative Memory Using Hamming Distance

This work presents a quantum associative memory (Alpha-Beta HQAM) that uses the Hamming distance for pattern recovery. The proposal combines the Alpha-Beta associative memory, which reduces the dimensionality of patterns, with a quantum subroutine to calculate the Hamming distance in the recovery phase. Furthermore, patterns are initially stored in the memory as a quantum superposition in order to take advantage of its properties. Experiments testing the memory’s viability and performance were implemented using IBM’s Qiskit library.