Abstract. We explore problems related to computing graph distances in the data-stream model. The goal is to design algorithms that can process the edges of a graph in an arbitrary order given only a limited amount of working memory. We are motivated by both the practical challenge of processing massive graphs such as the web graph and the desire for a better theoretical understanding of the datastream model. In particular, we are interested in the trade-offs between model parameters such as perdata-item processing time, total space, and the number of passes that may be taken over the stream. These trade-offs are more apparent when considering graph problems than they were in previous streaming work that solved problems of a statistical nature. Our results include the following: (1) Spanner construction: There exists a single-pass,Õ(tn 1+1/t )-space,Õ(t 2 n 1/t )-time-per-edge algorithm that constructs a (2t + 1)-spanner. For t = Ω(log n/log log n), the algorithm satisfies the semistreaming space restriction of O(n polylog n) and has per-edge processing time O(polylog n).This resolves an open question from [J. Feigenbaum et al., Theoret. Comput. Sci., 348 (2005), pp. 207-216]. (2) Breadth-first-search (BFS) trees: For any even constant k, we show that any algorithm that computes the first k layers of a BFS tree from a prescribed node with probability at least 2/3 requires either greater than k/2 passes orΩ(n 1+1/k ) space. Since constructing BFS trees is an important subroutine in many traditional graph algorithms, this demonstrates the need for new algorithmic techniques when processing graphs in the data-stream model. (3) Graph-distance lower bounds: Any t-approximation of the distance between two nodes requires Ω(n 1+1/t ) space. We also prove lower bounds for determining the length of the shortest cycle and other graph properties. (4) Techniques for decreasing per-edge processing: We discuss two general techniques for speeding up the per-edge computation time of streaming algorithms while increasing the space by only a small factor.

3DGN and MOF-derived metal oxide composites as free-standing electrodes for supercapacitors have been reported for the first time which exhibit a high specific capacitance, good rate capability and excellent long cycle stability.

No abstract

No abstract

No abstract

Bioavailability of phytosterols is very low due to their crystalline structure and poor water solubility, limiting their potential health benefits. In this study, a novel approach to forming low crystallinity phytosterol nanoparticles is developed using nanoporous starch aerogels, namely wheat starch aerogels (WSAs) and corn starch aerogels (CSA), in combination with supercritical carbon dioxide (SC‐CO2) to improve the bioaccessibility and in turn bioavailability of phytosterols. Starch aerogels with outstanding properties (WSA with a surface area of 62 m2 g−1 and pore size of 19 nm; CSA with a surface area of 221 m2 g−1 and pore size of 7 nm) were used as a mold to form phytosterol nanoparticles. The highest phytosterol impregnation capacity is obtained with CSA monolith (195 mg phytosterols/g CSA). Impregnation into powder or monolithic forms of the aerogels resulted in different phytosterol morphology where the monolithic form prevented formation of large plate‐like phytosterol crystals. Impregnation into WSA monolith (WSA‐M) generated low crystallinity phytosterol nanoparticles (70 nm). Bioaccessibility of the phytosterols increased by 20‐fold when impregnated into WSA‐M. The hydrolysis of CSA (30–39%) was lower than that of WSA (55–59%) during simulated digestion, which negatively affected the release of phytosterols. Practical applications: Practical applications include: i) a novel process that can decrease the size and crystallinity of phytosterols and thus improve their bioavailability; ii) a blueprint to apply to other water insoluble food bioactives; and iii) the transfer of green technology to food manufacturers. Longer‐term, this novel approach will (i) improve the health benefits of water‐insoluble bioactives; ii) enable food manufacturers to add water‐insoluble bioactives into low‐ and high‐fat foods to produce health‐promoting foods; iii) improve public health through diet; iv) enhance the cost‐benefit ratio of water insoluble bioactives; v) avert toxic chemicals and environmental pollution; and vi) lower the costs of handling, storage, and transportation of bioactives. Bioavailability of phytosterols is very low due to their crystalline structure and poor water solubility, limiting their potential health benefits. Our novel approach to forming first‐of‐its‐kind low‐crystallinity phytosterol nanoparticles are developed using nanoporous starch aerogels in combination with supercritical carbon dioxide to improve the bioaccessibility and in turn bioavailability of phytosterols. The novel low‐crystallinity phytosterol nanoparticles are 20‐folds more bioaccessible compared to the crude phytosterols after simulated digestion.

No abstract

This paper presents a generic Monte Carlo-based approach for bivariate extreme response prediction for fixed offshore structures, particularly jacket type. The bivariate analysis of extremes is often poorly understood and generally not adequately considered in most practical measurements/situations; that is why it is important to utilize the recently developed bivariate average conditional exceedance rate (ACER) method. According to the current literature study, there is not yet a direct application of the bivariate ACER method to coupled offshore jacket stresses. This study aims at being first to apply bivariate ACER method to jacket critical stresses, aiming at contributing to safety and reliability studies for a wide class of fixed offshore structures. An operating jacket located in the Bohai bay was taken as an example to demonstrate the proposed methodology. Satellite measured global wave statistics was used to obtain realistic wave scatter diagram in the jacket location area. Second-order wave load effects were taken into account, while simulating jacket structural response. An accurate finite element ANSYS model was used to model jacket response dynamics, subject to nonlinear hydrodynamic wave and sea current loads. Offshore structure design values are often based on univariate statistical analysis, while actually multivariate statistics is more appropriate for modeling the whole structure. This paper studies extreme stresses that are simultaneously measured/simulated at two different jacket locations. Due to less than full correlation between stresses in different critical jacket locations, application of the multivariate (or at least bivariate) extreme value theory is of practical engineering interest.