带复杂数据结构的模型检测工具

模型检测是近二十几年来最成功的自动验证技术之一,而模型检测工具的开发是将模型检测和实际相结合的关键.为了有效地对涉及到复杂数据类型的并发传值系统进行模型检测,总结了以扩展的带赋值符号迁移图和模态图分别作为并发系统和逻辑公式的语义模型来实现模型检测工具的工作,特别是将复杂数据结构引入传值进程定义语言和带赋值符号迁移图.同时结合实际例子说明模型检测工具的有效性.

'Explain in plain English' questions revisited : data structures problems

Recent studies have linked the ability of novice (CS1) programmers to read and explain code with their ability to write code. This study extends earlier work by asking CS2 students to explain object-oriented data structures problems that involve recursion. Results show a strong correlation between ability to explain code at an abstract level and performance on code writing and code reading test problems for these object-oriented data structures problems. The authors postulate that there is a common set of skills concerned with reasoning about programs that explains the correlation between writing code and explaining code. The authors suggest that an overly exclusive emphasis on code writing may be detrimental to learning to program. Non-code writing learning activities (e.g., reading and explaining code) are likely to improve student ability to reason about code and, by extension, improve student ability to write code. A judicious mix of code-writing and code-reading activities is recommended.

A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Model updating of the non-linear vibrating structures through Volterra series and proper orthogonal decomposition

Classical procedures for model updating in non-linear mechanical systems based on vibration data can fail because the common linear metrics are not sensitive for non-linear behavior caused by gaps, backlash, bolts, joints, materials, etc. Several strategies were proposed in the literature in order to allow a correct representative model of non-linear structures. The present paper evaluates the performance of two approaches based on different objective functions. The first one is a time domain methodology based on the proper orthogonal decomposition constructed from the output time histories. The second approach uses objective functions with multiples convolutions described by the first and second order discrete-time Volterra kernels. In order to discuss the results, a benchmark of a clamped-clamped beam with an pre-applied static load is simulated and updated using proper orthogonal decomposition and Volterra Series. The comparisons and discussions of the results show the practical applicability and drawbacks of both approaches.

A Petrov-Galerkin method for a singularly perturbed ordinary differential equation with non-smooth data

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Secondary attribute retrieval using tree data structures

Several techniques are known for searching an ordered collection of data. The techniques and analyses of retrieval methods based on primary attributes are straightforward. Retrieval using secondary attributes depends on several factors. For secondary attribute retrieval, the linear structures—inverted lists, multilists, doubly linked lists—and the recently proposed nonlinear tree structures—multiple attribute tree (MAT), K-d tree (kdT)—have their individual merits. It is shown in this paper that, of the two tree structures, MAT possesses several features of a systematic data structure for external file organisation which make it superior to kdT. Analytic estimates for the complexity of node searchers, in MAT and kdT for several types of queries, are developed and compared.

Food and Indoor Air Isolated Bacillus Non-Protein Toxins: : Structures, Physico-Chemical Properties and Mechanisms of Effects on Eukaryotic Cells

We report here the structures and properties of heat-stable, non-protein, and mammalian cell-toxic compounds produced by spore-forming bacilli isolated from indoor air of buildings and from food. Little information is available on the effects and occurrence of heat-stable non-protein toxins produced by bacilli in moisture-damaged buildings. Bacilli emit spores that move in the air and can serve as the carriers of toxins, in a manner similar to that of the spores of toxic fungi found in contaminated indoor air. Bacillus spores in food cause problems because they tolerate the temperatures applied in food manufacture and the spores later initiate growth when food storage conditions are more favorable. Detection of the toxic compounds in Bacillus is based on using the change in mobility of boar spermatozoa as an indicator of toxic exposure. GC, LC, MS, and nuclear magnetic resonance NMR spectroscopy were used for purification, detection, quantitation, and analysis of the properties and structures of the compounds. Toxicity and the mechanisms of toxicity of the compounds were studied using boar spermatozoa, feline lung cells, human neural cells, and mitochondria isolated from rat liver. The ionophoric properties were studied using the BLM (black-lipid membrane) method. One novel toxin, forming ion channels permeant to K+ > Na+ > Ca2+, was found and named amylosin. It is produced by B. amyloliquefaciens isolated from indoor air of moisture-damaged buildings. Amylosin was purified with an RP-HPLC and a monoisotopic mass of 1197 Da was determined with ESI-IT-MS. Furthermore, acid hydrolysis of amylosin followed by analysis of the amino acids with the GS-MS showed that it was a peptide. The presence of a chromophoric polyene group was found using a NMR spectroscopy. The quantification method developed for amylosin based on RP-HPLC-UV, using the macrolactone polyene, amphotericin B (MW 924), as a reference compound. The B. licheniformis strains isolated from a food poisoning case produced a lipopeptide, lichenysin A, that ruptured mammalian cell membranes and was purified with a LC. Lichenysin A was identified by its protonated molecules and sodium- and potassium- cationized molecules with MALDI-TOF-MS. Its protonated forms were observed at m/z 1007, 1021 and 1035. The amino acids of lichenysin A were analyzed with ESI-TQ-MS/MS and, after acid hydrolysis, the stereoisomeric forms of the amino acids with RP-HPLC. The indoor air isolates of the strain of B. amyloliquefaciens produced not only amylosin but also lipopeptides: the cell membrane-damaging surfactin and the fungicidal fengycin. They were identified with ESI-IT-MS observing their protonated molecules, the sodium- and potassium-cationized molecules and analysing the MS/MS spectra. The protonated molecules of surfactin and fengycin showed m/z values of 1009, 1023, and 1037 and 1450, 1463, 1493, and 1506, respectively. Cereulide (MW 1152) was purified with RP-HPLC from a food poisoning strain of B. cereus. Cereulide was identified with ESI-TQ-MS according to the protonated molecule observed at m/z 1154 and the ammonium-, sodium- and potassium-cationized molecules observed at m/z 1171, 1176, and 1192, respectively. The fragment ions of the MS/MS spectrum obtained from the protonated molecule of cereulide at m/z 1154 were also interpreted. We developed a quantification method for cereulide, using RP-HPLC-UV and valinomycin (MW 1110, which structurally resembles cereulide) as the reference compound. Furthermore, we showed empirically, using the BLM method, that the emetic toxin cereulide is a specific and effective potassium ionophore of whose toxicity target is especially the mitochondria.

Ion pairs in non-redundant protein structures

Ion pairs contribute to several functions including the activity of catalytic triads, fusion of viral membranes, stability in thermophilic proteins and solvent-protein interactions. Furthermore, they have the ability to affect the stability of protein structures and are also a part of the forces that act to hold monomers together. This paper deals with the possible ion pair combinations and networks in 25% and 90% non-redundant protein chains. Different types of ion pairs present in various secondary structural elements are analysed. The ion pairs existing between different subunits of multisubunit protein structures are also computed and the results of various analyses are presented in detail. The protein structures used in the analysis are solved using X-ray crystallography, whose resolution is better than or equal to 1.5 angstrom and R-factor better than or equal to 20%. This study can, therefore, be useful for analyses of many protein functions. It also provides insights into the better understanding of the architecture of protein structure.

Interaction of water molecules in non-identical protein structures

The interaction of the protein atoms with the surrounding water oxygen atoms has been computed for 392 protein chains from 369 protein structures belonging to 90% non-homologous high resolution (<= 1.5 angstrom) protein Structures with a crystallographic R-factor <= 20%. The percentage composition of the polar atoms is found to be 36.3%. An average of 82.55% of water oxygen atoms are found to be in the primary hydration shell and 15.12% in the secondary hydration shell. The average Percentage of interactions of water oxygen atoms with the polar atoms of the main chain and side chain are 54% and 46%. respectively. The interaction of the acidic residues, aspartate and glutamate, with the water oxygen atoms is more when compared to that of the other residues.