Application of polyuronides for removing heavy metals from vegetable oils. III. Application of alginic acid, pectic and pectinic acids for demetalization of hydrogenated sunflower oil.

Laboratory experiments have been carried out for the removal of heavy metals from hydrogenated vegetable oils using hydrated polyuronides (degree of swelling from 4 to 12.8 ml/g) such as alginic acid, pectic and pectinic acids. The effect of the type of polyuronide, degree of esterification and oil treatment on the degree of demetalization has been studied. It has been shown that with increase in the degree of esterification of the polyuronide the efficiency of demetalization decreases. The second and third treatment of the hydrogenated oil with pectinic acid resulted in a high degree of heavy metal removal. The possibility of efficient demetalization of hydrogenated oils by treatment with water solutions of pectinic acids has also been demonstrated. The degree of metal ion removal increases with decreasing concentration of pectinic acids in the water solution.     

A fast compound algorithm for mining generators,closed itemsets,and computing links between equivalence classes

In pattern mining and association rule mining, there is a variety of algorithms for mining frequent closed itemsets (FCIs) and frequent generators (FGs), whereas a smaller part further involves the precedence relation between FCIs. The interplay of these three constructs and their joint computation have been studied within the formal concept analysis (FCA) field yet none of the proposed algorithms is scalable. In frequent pattern mining, at least one suite of efficient algorithms has been designed that exploits basically the same ideas and follows the same overall computational schema. Based on an in-depth analysis of the aforementioned interplay that is rooted in a fundamental duality from hypergraph theory, we propose a new schema that should enable for a more parsimonious computation. We exemplify the new schema in the design of Snow-Touch, a concrete FCI/FG/precedence miner that reuses an existing algorithm, Charm, for mining FCIs, and completes it with two original methods for mining FGs and precedence, respectively. The performance of Snow-Touch and of its closest competitor, Charm-L, were experimentally compared using a large variety of datasets. The outcome of the experimental study suggests that our method outperforms Charm-L on dense data while on sparse one the trend is reversed. Furthermore, we demonstrate the usefulness of our method and the new schema through an application to the analysis of a genome dataset. The initial results reported here confirm the capacity of the method to focus on significant associations.     

Generating Rare Association Rules Using the Minimal Rare Itemsets Family

Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support. We also propose an efficient solution for finding the set of minimal rare itemsets. This set serves as a basis for generating rare association rules.     

The SHARC framework for data quality in Web archiving

Web archives preserve the history of born-digital content and offer great potential for sociologists, business analysts, and legal experts on intellectual property and compliance issues. Data quality is crucial for these purposes. Ideally, crawlers should gather coherent captures of entire Web sites, but the politeness etiquette and completeness requirement mandate very slow, long-duration crawling while Web sites undergo changes. This paper presents the SHARC framework for assessing the data quality in Web archives and for tuning capturing strategies toward better quality with given resources. We define data quality measures, characterize their properties, and develop a suite of quality-conscious scheduling strategies for archive crawling. Our framework includes single-visit and visit?Crevisit crawls. Single-visit crawls download every page of a site exactly once in an order that aims to minimize the ??blur?? in capturing the site. Visit?Crevisit strategies revisit pages after their initial downloads to check for intermediate changes. The revisiting order aims to maximize the ??coherence?? of the site capture(number pages that did not change during the capture). The quality notions of blur and coherence are formalized in the paper. Blur is a stochastic notion that reflects the expected number of page changes that a time-travel access to a site capture would accidentally see, instead of the ideal view of a instantaneously captured, ??sharp?? site. Coherence is a deterministic quality measure that counts the number of unchanged and thus coherently captured pages in a site snapshot. Strategies that aim to either minimize blur or maximize coherence are based on prior knowledge of or predictions for the change rates of individual pages. Our framework includes fairly accurate classifiers for change predictions. All strategies are fully implemented in a testbed and shown to be effective by experiments with both synthetically generated sites and a periodic crawl series for different Web sites.     

A Declarative Approach to Network Device Configuration Correctness

Configuration Logic (CL) is a formal language that allows a network engineer to express constraints in terms of the actual parameters found in the configuration of network devices. We present an efficient algorithm that can automatically check a pool of devices for conformance to a set of CL constraints; moreover, this algorithm can point to the part of the configuration responsible for the error when a constraint is violated. Contrary to other validation approaches that require dumping the configuration of the whole network to a central location in order to be verified, we also present an algorithm that analyzes the correct formulas and greatly helps reduce the amount of data that need to be transferred to that central location, pushing as much of the evaluation of the formula locally on each device. The procedure is also backwards-compatible, in such a way that a device that does not (or only partially) supports a local evaluation may simply return a subset or all of its configuration. These capabilities have been integrated into a network management tool called ValidMaker.     

Interleaved Ultrawideband Antenna Arrays Based on Optimized Polyfractal Tree Structures

There is considerable interest in interleaving multiple phased array antennas into a single common aperture system. Current phased array antenna technology is limited to narrowband operation, leading to the appearance of grating lobes and strong mutual coupling effects when they are incorporated into the design of a common aperture system. To overcome this obstacle, a new class of arrays, called polyfractal arrays, has been introduced that possess natural wideband properties well suited for large-scale genetic algorithm optimizations. These arrays also possess recursive beamforming properties and an autopolyploidy-based chromosome expansion that can dramatically accelerate the convergence of a genetic algorithm. In addition, a robust Pareto optimization can be applied to reduce the peak sidelobe levels at several frequencies throughout the intended operating band, leading to ultrawideband antenna array designs. Because of their lack of grating lobes, these polyfractal arrays are ideal building blocks for interleaved antenna array systems. This paper develops these concepts, first creating ultrawideband array designs based on polyfractal geometries and then interleaving these designs into a common aperture system. Several examples of interleaved systems are discussed, with one two-array system possessing a peak sidelobe level of nearly -18 dB with no grating lobes over a 20:1 bandwidth with either of the component array mainbeams steered independently up to 60deg from broadside.     

Thick lead-free ferroelectric films with high Curie temperatures through nanocomposite-induced strain

Ferroelectric materials are used in applications ranging from energy harvesting to high-power electronic transducers. However, industry-standard ferroelectric materials contain lead, which is toxic and environmentally unfriendly. The preferred alternative, BaTiO(3), is non-toxic and has excellent ferroelectric properties, but its Curie temperature of ～130 °C is too low to be practical. Strain has been used to enhance the Curie temperature of BaTiO(3) (ref. 4) and SrTiO(3) (ref. 5) films, but only for thicknesses of tens of nanometres, which is not thick enough for many device applications. Here, we increase the Curie temperature of micrometre-thick films of BaTiO(3) to at least 330 °C, and the tetragonal-to-cubic structural transition temperature to beyond 800 °C, by interspersing stiff, self-assembled vertical columns of Sm(2)O(3) throughout the film thickness. The columns, which are 10 nm in diameter, strain the BaTiO(3) matrix by 2.35%, forcing it to maintain its tetragonal structure and resulting in the highest BaTiO(3) transition temperatures so far.