Effects of Geometrical Symmetry on the Vortex Nucleation and Penetration in Mesoscopic Superconductors

We investigate how the geometrical symmetry affects the penetration and arrangement of vortices in mesoscopic superconductors using self-consistent Bogoliubov-de Gennes equations. We find that the entrance of the vortex happens when the current density at the hot spots reaches the depairing current density. Through determining the spatial distribution of hot spots, the geometrical symmetry of the superconducting sample influences the nucleation and entrance of vortices. Our results propose one possible experimental approach to control and manipulate the quantum states of mesoscopic superconductors with their topological geometries, and they can be easily generalized to the confined superfluids and Bose-Einstein condensates

2013 (Hemiptera: Fulgoromorpha: Kinnaridae)

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Experimental study on configuration optimization of floating breakwaters

In this paper, four types of floating breakwaters (FB) are proposed: cylindrical floating breakwater (CFB), porous floating breakwater (PFB), mesh cage floating breakwater type-I (MCFB-I) and mesh cage floating breakwater type-II (MCFB-II). The hydrodynamic performance of each type has been tested to identify the most effective configuration for wave attenuation. The experiment was conducted in a wave flume in which regular waves were produced. The incident and transmitted waves, the tensions in the mooring lines and the motion responses of all of the four types of floating breakwaters were measured. It is shown that all proposed types of floating breakwaters can effectively reduce transmitted wave amplitude. Among them the MCFB-I is seen to yield the most attenuating effect on incident wave amplitude

Experimental study of a new type of floating breakwater

A new type of floating breakwater (FB) is proposed in this paper. Its hydrodynamic performance has been tested. The structure of the new breakwater named cylindrical floating breakwater (CFB) consists of two parts: a main body of rigid cylinders, and a flexible mesh cage containing a number of suspending balls that are intended to absorb the wave energy into their mechanical energy. A series of experiments were carried out on the new floating breakwater and traditional double pontoons and box floating breakwaters to compare their performances. A two-dimensional wave flume was used in the experiment; the incident and transmitted waves, the tensions on the mooring lines and the motion responses of the floating breakwaters were measured. Results showed that the new floating breakwater had a better performance than the traditional double pontoons and the box floating breakwaters: wave transmission was significantly reduced by the mesh cage with the balls, especially for long waves

Knowledge-Based Tweet Classification for Disease Sentiment Monitoring

Disease monitoring and tracking is of tremendous value, not only for containing the spread of contagious diseases but also for avoiding unnecessary public concerns and even panic. In this chapter, we present a near real-time sentiment analysis service of public health-related tweets. Traditionally, it is impossible for humans to effectively measure the degree of public health concerns due to limited resources and significant time delays. To solve this problem, we have developed a computational intelligence approach for Epidemic Sentiment Monitoring System (ESMOS) to automatically analyze the disease sentiments and gauge the Measure of Concern (MOC) expressed by Twitter users. More specifically, we present a knowledge-based approach that employs a disease ontology to detect the outbreak of diseases and to analyze the linguistic expressions that convey subjective expressions and sentiment polarity of emotions, feelings, opinions, personal attitudes, etc. with a sentiment classifier. The two-step sentiment classification method utilizes the subjective vocabulary corpus (MPQA), sentiment strength corpus (AFINN), as well as emoticons and profanity words that are often used in social media postings. It first automatically classifies the tweets into personal and non-personal classes, eliminating many tweets such as non-personal “retweets” of news articles from further consideration. In the second stage, the personal tweets are classified into Negative and non-Negative sentiments. In addition, we present a model to quantify the public’s Measure of Concern (MOC) about a disease, based on sentiment classification results. The trends of the public MOC are visualized on a timeline. Correlation analyses between MOC timeline and disease-related sentiment category timelines show that the peaks of the MOC are weakly correlated with the peaks of the News timeline without any appreciable time delay or lead. Our sentiment analysis method and the MOC trend analyses can be generalized to other topical domains, such as mental health monitoring and crisis management. We present the ESMOS prototype for public health-related disease monitoring, for public concern trending and for mapping analyses

1-(Benzyl­ideneamino)pyridinum iodide

In the title compound, C12H11N2 +·I−, the aromatic rings are oriented at a dihedral angle of 73.40 (3)°. In the crystal structure, π–π contacts between the pyridine rings and the benzene and pyridine rings [centroid–centroid distances = 3.548 (3) and 4.211 (3) Å] may stabilize the structure

(2S,3R)-2-[(4-Ethyl-2,3-dioxopiperazin-1-yl)carbonyl­amino]-3-hydroxy­butyric acid monohydrate

In the title compound, C11H17N3O6·H2O, an important building block of the medicine cefbuperazone sodium, the piperazine ring adopts a screw-boat conformation. Inter­molecular O—H⋯O and intra­molecular N—H⋯O hydrogen bonds are observed. The water mol­ecule participates as both donor and acceptor in this framework