Electro-spinning/netting: A strategy for the fabrication of three-dimensional polymer nano-fiber/nets.

Since 2006, a rapid development has been achieved in a subject area, so called electro-spinning/netting (ESN), which comprises the conventional electrospinning process and a unique electro-netting process. Electro-netting overcomes the bottleneck problem of electrospinning technique and provides a versatile method for generating spider-web-like nano-nets with ultrafine fiber diameter less than 20 nm. Nano-nets, supported by the conventional electrospun nanofibers in the nano-fiber/nets (NFN) membranes, exhibit numerious attractive characteristics such as extremely small diameter, high porosity, and Steiner tree network geometry, which make NFN membranes optimal candidates for many significant applications. The progress made during the last few years in the field of ESN is highlighted in this review, with particular emphasis on results obtained in the author's research units. After a brief description of the development of the electrospinning and ESN techniques, several fundamental properties of NFN nanomaterials are addressed. Subsequently, the used polymers and the state-of-the-art strategies for the controllable fabrication of NFN membranes are highlighted in terms of the ESN process. Additionally, we highlight some potential applications associated with the remarkable features of NFN nanostructure. Our discussion is concluded with some personal perspectives on the future development in which this wonderful technique could be pursued

Efficient Closed Pattern Mining in the Presence of Tough Block Constraints

In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbased constraints that better capture the underlying application requirements and characteristics. In this paper we introduce a new class of block constraints that determine the significance of an itemset pattern by considering the dense block that is formed by the pattern's items and its associated set of transactions. Block constraints provide a natural framework by which a number of important problems can be specified and make it possible to solve numerous problems on binary and real-valued datasets. However, developing computationally e#cient algorithms to find these block constraints poses a number of challenges as unlike the di#erent itemset-based constraints studied earlier, these block constraints are tough as they are neither anti-monotone, monotone, nor convertible. To overcome this problem, we introduce a new class of pruning methods that can be used to significantly reduce the overall search space and make it possible to develop computationally e#cient block constraint mining algorithms. We present an algorithm called CBMiner that takes advantage of these pruning methods to develop an algorithm for finding the closed itemsets that satisfy the block constraints. Our extensive performance study shows that CBMiner generates more concise result set and can be order(s) of magnitude faster than the traditional frequent closed itemset mining algorithms

The evaluation of ammonia tolerance in introduced and local Pacific white shrimp, Litopenaeus vannamei, populations in China

The white shrimp, Litopenaeus vannamei, is one of the most valuable commodities in the global seafood trade. Affected by high-density farming environments, ammonia accumulates in shrimp cultures and has a strong toxic effect, resulting in poor shrimp survival and poor immune function and metabolism. We selected six different populations of L. vannamei from Xing Hai No.1 (A and B), CHAI, Sy Aqua, PRIMO, and a second-generation Sy Aqua-PRIMO hybrid population (SP). The shrimps (3.24 ± 0.71 cm body length) were exposed to ammonia (24 h, 48 h), followed by recovery (R48 h, R96 h) to assess the tolerance of different populations. The survival rate (SR), immune-related enzymes (superoxide dismutase SOD, catalase CAT, and Glutathione peroxidase GSH-PX), Malondialdehyde (MDA), and metabolism (glutamate dehydrogenase GDH, glutamine synthetase GS, and aspartic acid transaminase GOT) and were measured at different populations under acute ammonia stress. Multiple comparisons of the ammonia resistance index from six populations showed that the expression of these indicators varied among the populations. The degree of lipid peroxidation in the Sy Aqua and PRIMO was significantly higher than in the other populations (P < 0.05), and the ammonia metabolism index was poor. The GDH and GOT genes for the Xing Hai No.1 (A) were higher than for the other populations. Mortality and physiological indicators recovered to varying degrees for all experimental populations following 96 h of ammonia relief, whereas the Sy Aqua and PRIMO showed a noticeable lag. These results indicated that the immunity and metabolic capacity of Xing Hai No.1 (A) might be higher than those of Sy Aqua and PRIMO. These data could have value in developing future scientific breeding schemes and in the sustainability of shrimp farming