Structural change of vortex patterns in anisotropic Bose-Einstein condensates

We study the changes in the spatial distribution of vortices in a rotating Bose-Einstein condensate due to an increasing anisotropy of the trapping potential. Once the rotational symmetry is broken, we find that the vortex system undergoes a rich variety of structural changes, including the formation of zig-zag and linear configurations. These spatial re-arrangements are well signaled by the change in the behavior of the vortex-pattern eigenmodes against the anisotropy parameter. The existence of such structural changes opens up possibilities for the coherent exploitation of effective many-body systems based on vortex patterns.Comment: 5 pages, 4 figure

Alcohol consumption in young adults: the role of multisensory imagery.

Accepted 19.11.2013Little is known about the subjective experience of alcohol desire and craving in young people. Descriptions of alcohol urges continue to be extensively used in the everyday lexicon of young, non-dependent drinkers. Elaborated Intrusion (EI) Theory contends that imagery is central to craving and desires, and predicts that alcohol-related imagery will be associated with greater frequency and amount of drinking. This study involved 1,535 age stratified 18- 25 year olds who completed an alcohol–related survey that included the Imagery scale of the Alcohol Craving Experience (ACE) questionnaire. Imagery items predicted 12-16% of the variance in concurrent alcohol consumption. Higher total Imagery subscale scores were linearly associated with greater drinking frequency and lower self-efficacy for moderate drinking. Interference with alcohol imagery may have promise as a preventive or early intervention target in young people

Polysubstance use in cannabis users referred for treatment: Drug use profiles, psychiatric comorbidity and cannabis-related beliefs

Background: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. Methods: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. Results: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging substance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. Conclusion: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment

Acetic Acid Bacteria: Physiology and Carbon Sources Oxidation

Acetic acid bacteria (AAB) are obligately aerobic bacteria within the family Acetobacteraceae, widespread in sugary, acidic and alcoholic niches. They are known for their ability to partially oxidise a variety of carbohydrates and to release the corresponding metabolites (aldehydes, ketones and organic acids) into the media. Since a long time they are used to perform specific oxidation reactions through processes called “oxidative fermentations”, especially in vinegar production. In the last decades physiology of AAB have been widely studied because of their role in food production, where they act as beneficial or spoiling organisms, and in biotechnological industry, where their oxidation machinery is exploited to produce a number of compounds such as l-ascorbic acid, dihydroxyacetone, gluconic acid and cellulose. The present review aims to provide an overview of AAB physiology focusing carbon sources oxidation and main products of their metabolism

A combinatorial multi-armed bandit approach to correlation clustering

Given a graph whose edges are assigned positive-type and negative-type weights, the problem of correlation clustering aims at grouping the graph vertices so as to minimize (resp. maximize) the sum of negative-type (resp. positive-type) intra-cluster weights plus the sum of positive-type (resp. negative-type) inter-cluster weights. In correlation clustering, it is typically assumed that the weights are readily available. This is a rather strong hypothesis, which is unrealistic in several scenarios. To overcome this limitation, in this work we focus on the setting where edge weights of a correlation-clustering instance are unknown, and they have to be estimated in multiple rounds, while performing the clustering. The clustering solutions produced in the various rounds provide a feedback to properly adjust the weight estimates, and the goal is to maximize the cumulative quality of the clusterings. We tackle this problem by resorting to the reinforcement-learning paradigm, and, specifically, we design for the first time a Combinatorial Multi-Armed Bandit (CMAB) framework for correlation clustering. We provide a variety of contributions, namely (1) formulations of the minimization and maximization variants of correlation clustering in a CMAB setting; (2) adaptation of well-established CMAB algorithms to the correlation-clustering context; (3) regret analyses to theoretically bound the accuracy of these algorithms; (4) design of further (heuristic) algorithms to have the probability constraint satisfied at every round (key condition to soundly adopt efficient yet effective algorithms for correlation clustering as CMAB oracles); (5) extensive experimental comparison among a variety of both CMAB and non-CMAB approaches for correlation clustering

Trade with the People\u27s Republic of China: Current Status and Future Prospects

Since the normalization of diplomatic relations with the People\u27s Republic of China (PRC) in 1979, U.S. trade with China has developed rapidly. In particular, 1980 saw significant developments in the institutional framework of U.S.-China trade relations, with the signing of several new trade-related bilateral agreements and a number of high-level visits in both directions.2 At the same time, China has begun to update its domestic legal system as it plans to integrate more fully into the international economic order.3 The last year has also witnessed the cancellation of certain large development projects, and delay in the implementation of others, as the Chinese readjust their economic plans and priorities. This Perspective will first discuss the current status of U.S.-China trade relations, with an emphasis on the developments of 1980. It will then present our view of the Chinese economy and prospects for the future development of China\u27s foreign trade. Changes in the Chinese legal system will be mentioned only briefly, as those matters are treated in detail elsewhere in this issue

The impact of diabetes mellitus on survival following resection and adjuvant chemotherapy for pancreatic cancer

BACKGROUND: Diabetes mellitus is frequently observed in pancreatic cancer patients and is both a risk factor and an early manifestation of the disease. METHODS: We analysed the prognostic impact of diabetes on the outcome of pancreatic cancer following resection and adjuvant chemotherapy using individual patient data from three European Study Group for Pancreatic Cancer randomised controlled trials. Analyses were carried out to assess the association between clinical characteristics and the presence of preoperative diabetes, as well as the effect of diabetic status on overall survival. RESULTS: In total, 1105 patients were included in the analysis, of whom 257 (23%) had confirmed diabetes and 848 (77%) did not. Median (95% confidence interval (CI)) unadjusted overall survival in non-diabetic patients was 22.3 (20.8–24.1) months compared with 18.8 (16.9–22.1) months for diabetic patients (P=0.24). Diabetic patients were older, had increased weight and more co-morbidities. Following adjustment, multivariable analysis demonstrated that diabetic patients had an increased risk of death (hazard ratio: 1.19 (95% CI 1.01, 1.40), P=0.034). Maximum tumour size of diabetic patients was larger at randomisation (33.6 vs 29.7 mm, P=0.026). CONCLUSIONS: Diabetes mellitus was associated with increased tumour size and reduced survival following pancreatic cancer resection and adjuvant chemotherapy

Correlation Clustering: From Local to Global Constraints

Given a set of data objects, consider that object pairs are assigned two weights expressing the advantage of putting those objects in the same cluster or in separate clusters, respectively. Correlation clustering partitions the input object set so as to minimize the sum of the intra-cluster negative-type weights plus the sum of the inter-cluster positive-type weights. Existing approximation algorithms provide quality guarantees if the weights are bounded in some way. Regardless of the type, the weight bounds that have been so far studied are local bounds, i.e., constraints that are required to hold for every object pair in isolation. In this paper, we discuss global weight bounds in correlation clustering, and in particular, we derive bounds on edge weights' aggregate functions that are sufficient to lead to proved quality guarantees. Our formulation extends the range of applicability of the most prominent existing correlationclustering algorithms thus providing benefits, both theoretical and practical. Also, we showcase our results in a real-world scenario of feature selection for fair clustering