Interior-Point Methods with Decomposition for Solving Large-Scale Linear Programs

This paper deals with an algorithm incorporating the interior-point method into the Dantzig–Wolfe decomposition technique for solving large-scale linear programming problems. The algorithm decomposes a linear program into a main problem and a subproblem. The subproblem is solved approximately. Hence, inexact Newton directions are used in solving the main problem. We show that the algorithm is globally linearly convergent and has polynomial-time complexity.     

POPMUSIC for the travelling salesman problem

POPMUSIC— Partial OPtimization Metaheuristic Under Special Intensification Conditions — is a template for tackling large problem instances. This metaheuristic has been shown to be very efficient for various hard combinatorial problems such as p-median, sum of squares clustering, vehicle routing, map labelling and location routing. A key point for treating large Travelling Salesman Problem (TSP) instances is to consider only a subset of edges connecting the cities. The main goal of this article is to present how to build a list of good candidate edges with a complexity lower than quadratic in the context of TSP instances given by a general function. The candidate edges are found with a technique exploiting tour merging and the POPMUSIC metaheuristic. When these candidate edges are provided to a good local search engine, high quality solutions can be found quite efficiently. The method is tested on TSP instances of up to several million cities with different structures (Euclidean uniform, clustered, 2D to 5D, grids, toroidal distances). Numerical results show that solutions of excellent quality can be obtained with an empirical complexity lower than quadratic without exploiting the geometrical properties of the instances.     

大型滑坡发生的时间分布与固体潮的关系

为研究大型滑坡在发生时间呈现的规律,本文对我国近年来发生的大型滑坡在时间分布和诱导因素上进行了统计。从统计结果可以看出,自然边坡往往在一定的诱导因素下发生失稳破坏,而大型滑坡的失稳破坏在时间分布上则表现出望日或者朔日前后易于发生,并且滑坡在一天中发生的具体时刻则呈现出正态分布的特点。因此,根据固体潮的理论,以及固体潮在一天之中引潮力的变化与滑坡发生时刻的对应关系,本文认为固体潮是诱导大型边坡失稳的因素之一。同时由于组成边坡物质的蠕变特性不同,造成了大型滑坡的发生往往有超前或滞后现象,以上结果为滑坡的预报或预防工作提供了一定的理论支持。     

Interpretation of simple and cloud-resolving simulations of moist convection–radiation interaction with a mock-Walker circulation

An idealized two-dimensional mock-Walker circulation in the tropical atmosphere forced by prescribed horizontal gradients in sea-surface temperature (SST) is discussed. This model problem includes feedbacks between cumulus convection and tropical large-scale circulations that have proved challenging for global climate models to predict accurately. Three-dimensional cloud-resolving model (CRM) simulations that explicitly simulate turbulent circulations within individual cloud systems across 4,096 and 1,024 km-wide Walker circulations are compared with a simple theoretical model, the Simplified Quasiequilibrium Tropical Circulation Model (SQTCM). This theoretical model combines the weak-temperature-gradient approximation with a unimodal truncation of tropospheric vertical structure coupled to highly simplified formulations of moist precipitating cumulus convection and its cloud-radiative feedbacks. The rainfall, cloud and humidity distribution, circulation strength, energy fluxes and scaling properties are compared between the models. The CRM-simulated horizontal distribution of rainfall and energy fluxes are adequately predicted by the SQTCM. However, the humidity distribution (drier subsidence regions and high-humidity boundary layers in the CRM), vertical structure and domain-size scaling of the circulation differ significantly between the models. For the SQTCM, the concept of gross moist stability – related to advection of moist static energy (MSE) out of tropospheric columns by the mean divergent circulation – is used to explain the width and intensity of the rainy region. Column MSE budgets averaged across the ascent branch of the simulated Walker circulation provide similar insight into the cloud-resolving simulations after consideration of the more complex horizontal and vertical circulation structure and the role of transient eddies. A nondimensional ascent-region moist stability ratio α, analogous to the SQTCM gross moist stability, is developed. One term of α is related to the vertical profiles of ascent-region mean vertical motion and ascent-region edge MSE; a second term is proportional to eddy export from the ascent region. Smaller α induces a narrower, rainier ascent region. The sensitivity of the SQTCM and CRM to a uniform 2 K increase in SST is compared, and the rainy upward branch of the circulation narrows in both models. MSE budget arguments are used to explain this behavior. In the simple model, the gross moist stability is a decreasing function of tropospheric temperature. Hence gross moist stability reduces and the ascent region narrows as the SST increases. In the CRM, increased atmospheric radiative cooling due to the warmer and moister troposphere destabilizes the MSE profile and decreases α, inducing a narrower ascent region. In the CRM, and to a lesser extent in the SQTCM, intensified shortwave cloud forcing in the warmer climate causes a negative radiative feedback on the SST change.Funding for this work from NSF grant DMS-0139794 is gratefully appreciated     

Efficiently predicting large-scale protein-protein interactions using MapReduce

With a rapid development of high-throughput genomic technologies, a vast amount of protein-protein interactions (PPIs) data has been generated for difference species. However, such set of PPIs is rather small when compared with all possible PPIs. Hence, there is a necessity to specifically develop computational algorithms for large-scale PPI prediction. In response to this need, we propose a parallel algorithm, namely pVLASPD, to perform the prediction task in a distributed manner. In particular, pVLASPD was modified based on the VLASPD algorithm for the purpose of improving the efficiency of VLASPD while maintaining a comparable effectiveness. To do so, we first analyzed VLASPD step by step to identify the places that caused the bottlenecks of efficiency. After that, pVLASPD was developed by parallelizing those inefficient places with the framework of MapReduce. The extensive experimental results demonstrate the promising performance of pVLASPD when applied to prediction of large-scale PPIs.     

以大型仪器为依托构建本科生科研素质培养的新模式

本文以江汉大学高分子材料与工程专业本科教学为例,提出以大型仪器为依托构建本科生科研素质培养的新模式。借助于大型仪器在本科生科研素质培养中的优势作用,采用建立在线资料库、大型仪器模拟仿真、大型仪器操作实训、组建学生科研团队和建立多元化考核评价体系等措施,进一步激发学生的学习兴趣,培养学生的自主学习能力、独立思考能力、团队协作能力和创新能力。通过转变学习方式和方法,提升学生的学习和科学研究等方面的综合能力,为高素质、有特色的应用型技术人才的培养提供一定的参考。     

New simple and recyclable O-acylation serine derivatives as highly enantioselective catalysts for the large-scale asymmetric direct aldol reactions in the presence of water

New classes of O-acylation serine derived organocatalysts have been synthesized one-step by rational combination of serine with acyl chlorides at room temperature in trifluoroacetic acid. No protecting groups or chromatographic techniques are involved in any of the procedures, and certain combined serine-surfactant organocatalysts mediate the direct aldol reactions of ketones with a series of aromatic aldehydes to provide the aldol products in high yields (up to 99%) and enantioselectivities (up to 99% ee). The catalyst 1b can be easily recovered and reused, and without significant decrease of enantioselectivity was observed for five cycles. This novel catalyst can be efficiently used in large-scale reactions with the enantioselectivities being maintained at the same level, which offers a great possibility for application in industry.     

Computation of the analysis error covariance in variational data assimilation problems with nonlinear dynamics

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function. The data contain errors (observation and background errors), hence there will be errors in the optimal solution. For mildly nonlinear dynamics, the covariance matrix of the optimal solution error can often be approximated by the inverse Hessian of the cost functional. Here we focus on highly nonlinear dynamics, in which case this approximation may not be valid. The equation relating the optimal solution error and the errors of the input data is used to construct an approximation of the optimal solution error covariance. Two new methods for computing this covariance are presented: the fully nonlinear ensemble method with sampling error compensation and the ‘effective inverse Hessian’ method. The second method relies on the efficient computation of the inverse Hessian by the quasi-Newton BFGS method with preconditioning. Numerical examples are presented for the model governed by Burgers equation with a nonlinear viscous term.