Nonlinear Langevin model with product stochasticity for biological networks: The case of the Schnakenberg model

Langevin equation is widely used to study the stochastic effects in molecular networks, as it often approximates well the underlying chemical master equation. However, frequently it is not clear when such an approximation is applicable and when it breaks down. This paper studies the simple Schnakenberg model consisting of three reversible reactions and two molecular species whose concentrations vary. To reduce the residual errors from the conventional formulation of the Langevin equation, the authors propose to explicitly model the effective coupling between macroscopic concentrations of different molecular species. The results show that this formulation is effective in correcting residual errors from the original uncoupled Langevin equation and can approximate the underlying chemical master equation very accurately.     

Application of artificial neural networks in global climate change and ecological research: An overview

Fields that employ artificial neural networks (ANNs) have developed and expanded continuously in recent years with the ongoing development of computer technology and artificial intelligence. ANN has been adopted widely and put into practice by researchers in light of increasing concerns over ecological issues such as global warming, frequent El Niño-Southern Oscillation (ENSO) events, and atmospheric circulation anomalies. Limitations exist and there is a potential risk for misuse in that ANN model parameters require typically higher overall sensitivity, and the chosen network structure is generally more dependent upon individual experience. ANNs, however, are relatively accurate when used for short-term predictions; despite global climate change research favoring the effects of interactions as the basis of study and the preference for long-term experimental research. ANNs remain a better choice than many traditional methods when dealing with nonlinear problems, and possesses great potential for the study of global climate change and ecological issues. ANNs can resolve problems that other methods cannot. This is especially true for situations in which measurements are difficult to conduct or when only incomplete data are available. It is anticipated that ANNs will be widely adopted and then further developed for global climate change and ecological research.     

Density and structure of undercooled liquid titanium

For liquid Ti, it is difficult to achieve high undercooling because of its chemical reactivity; as a result, there is little information available on its properties and structure in the undercooled state. In this study, we investigate the density and structure, using molecular dynamics method, for the undercooling and superheating ranges 0-743 K and 0-457 K. The density increases quadratically for undercooling. At the melting temperature, the density is 4.14 g/cm3, and first and second temperature coefficients are obtained. The pair correlation functions and coordination numbers indicate that the short range degree of order becomes increasingly significant with increasing undercooling.     

Generalized variation iteration solution of an atmosphere-ocean oscillator model for global climate

A box model of the interhemispheric thermohaline circulation (THC) in atmosphere-ocean for global climate is considered. By using the generalized variational iteration method, the approximate solution of a simplified nonlinear model is studied. The generalized variational iteration method is an analytic method, and the obtained analytic solution can be operated sequentially. The authors also diversify qualitative and quantitative behaviors for corresponding physical quantities.     

Temperature-induced fractionation of oxygen isotopes of diatom frustules and growth water in Lake Sihailongwan in Northeast China

Diatom oxygen isotopes have been widely applied in quantitative reconstruction of the paleoclimate and paleoenvironment, but have rarely been reported in China. In the present study, Lake Sihailongwan in Northeast China was selected for detailed investigation of oxygen isotopic fractionation between diatom frustules and lake water induced by growth temperature. This study involved a 2-year period of field monitoring of the lake water temperature at multiple depths and biweekly collections of traps for both sediment and water at shallow and bottom depths (7 and 49 m below the lake surface, respectively), diatom separation and purification of the trap sediments, and oxygen isotope measurement for diatom silica and lake water samples. The conditioned experiment conducted herein demonstrated that the laboratory device, methods and techniques used in this study were capable of generating reliable data for the typical oxygen isotope composition of diatom frustules. The data obtained revealed a prominent linear relationship between the oxygen isotope composition of the modern diatom and lake temperature during growth. The fractionation coefficient was about −0.185‰/°C−0.238‰/°C in the temperature range of 3.6–24°C, which is consistent with the observations from various aquatic environments and laboratory culture with different diatom taxa. These findings provide strong support for the dominant control of the growth temperature on the oxygen isotope fractionation between the diatom frustules and ambient water. A notable difference in the fractionation coefficient was observed between the surface and bottom diatom oxygen isotopes, suggesting that various depositional processes and taphonomic effects influenced the surface and bottom trap samples. Another factor leading to this difference may be that enrichment by evaporation and dilution by rainfall have a stronger influence on the surface. Overall, the results presented here demonstrate significant progress in evaluation of diatom oxygen isotopes in China and draw attention to the differences between surface and bottom diatom oxygen isotope compositions.     

Application of surface plasmon resonance in screening adsorbents and explaining adsorption phenomena using model polymers

A surface plasmon resonance (SPR) technique was developed as an online screening method to identify effective adsorbents for the peptide NH₂-Cys-Thr-Trp-Trp-COOH (CW-4). To validate the SPR technique, several linear polymers containing amino acid residues were synthesized as models of their corresponding adsorbents. SPR screening of all the linear polymers demonstrated that the linear polymer containing phenylalanine residues (PPhe) exhibited the highest affinity for CW-4 among the polymers tested. In accordance with the screening results from SPR, the adsorbent containing phenylalanine (APhe) exhibited the highest adsorption capacity for CW-4. An interesting observation was that the amounts of CW-4 adsorbed on 3 adsorbents were quite small, even though both SPR and isothermal titration calorimetry (ITC) experiments indicated the presence of interactions between CW-4 and the three polymers. A kinetic analysis performed using SPR technology suggested such a phenomenon was ascribed to the poor stability of the CW-4/polymer complexes; that is, CW-4 associates with the polymers quickly, but it also dissociated quickly. The combined results suggested that SPR was a promising tool to identify the optimal adsorbent for peptides, analyze the interactions contributing to adsorption and explain adsorption phenomena using polymer models.     

刚性柱双π墙金属有机框架:单晶到单晶结构转换,碘富集与缓释,协同导电性研究

本文在溶剂热条件下利用刚性柱型金属手性配位链(Zn-lactate),辅助于三角架桥联配体(pybz)构筑了目前第一例高稳定性、双π墙的纳米孔道配位聚合物Zn3(pybz)2(lac)2·2.5DMF(1).化合物1具有孔径为1.12 nm×1.02 nm的一维纳米通道,其孔洞率Vvoid为43.5％,Langmuir比表面积为918.5m2·g-1,热稳定性高达400℃.化合物1通过晶态转换的方式得到去客体化合物Zn3 (pybz)2 (lac)2(1′).1′在碘的环己烷溶液中展现出对碘分子前所未有的超级富集与控释效果,单位碘负载量达到1 g I2/g 1 ′,同时载碘单晶在乙醇溶液中可实现碘的可控释放.由于客体I2分子与主体双壁π电子两者间交替的电荷转移,导致载碘单晶的导电性能比碘单质剧增440倍.上述研究,在国际上首次发现了绝缘性客体与绝缘性配位聚合物主体协同有序电荷转移进而导电性剧增的特殊现象.     

粉煤灰性能与其最优掺量的灰色关联分析

为研究粉煤灰品质对混凝土开裂性能的影响,利用改进的平板法分析粉煤灰的品质和掺量对混凝土的开裂性能的影响.同时,采用灰色关联分析方法研究粉煤灰粒径分布与化学成分对其最优掺量的影响.研究结果表明:粒径小于20.4μm的粉煤灰颗粒与其最优掺量是正关联;适当提高粉煤灰中MgO,K2O,CaO与SO3的质量分数和降低烧失量可以提高其最优掺量.     

定向井环空内岩屑运移机理的研究

运用实验观察方法,对定向井环空内岩屑的运移情况进行了研究和分析。从宏观上看,斜井环空内岩屑的运移状况有四种不同的流动物理模型,即:均称悬浮流动、非均称悬浮流动、移动床流动和固定床流动。在不同斜度的井眼中分别存在一个对应的临界流速.从微观上分析,岩屑床床面的岩屑颗粒承受液流的拖曳力和上举力、粒间离散力、重力和浮力的作用。对于极细的岩屑颗粒,还承受粒间粘结力。研究结果表明,环空倾角对岩屑运移有一定的影响。倾角越大,越不利于岩屑的运移。液流流速越大,岩屑的运移越快。     

大斜度井中岩屑床厚度模式的研究

岩屑床是大斜度钻井中的重要影响因素,为了控制岩屑床的形成厚度,保证安全钻进,建立了岩屑床厚度的理论计算模式和半经验模式,分析了影响岩屑床形成的各种因素。运用所建立的计算模式对油田丛式井斜度较大的6口井进行了计算。计算结果表明,半经验模式计算结果与理论模式计算结果基本相符。由计算结果推出了安全钻进时岩屑床的厚度极值为1.9cm.