A different approach to the analysis of pure ventricular parasystole

Until recently, it had not been recognized that predictions regarding the number of sinus beats interposed between two consecutive parasystolic beats could be made. In a case of perfect, pure parasystole resulting from unintentional fixed rate ventricular pacing, the following was observed: there were consistently three different values (0,2,3) for the number of interposed sinus beats; only one of these values was odd, and the sum of the two smaller values was one less than the larger value. Our findings, which are in keeping with those obtained in an mathematical model, may be of additional help in the diagnosis of this elusive arrhythmia.     

Regular Random k-SAT: Properties of Balanced Formulas

We consider a model for generating random k-SAT formulas, in which each literal occurs approximately the same number of times in the formula clauses (regular random and k-SAT). Our experimental results show that such regular random k-SAT instances are much harder than the usual uniform random k-SAT problems. This is in agreement with other results that show that more balanced instances of random combinatorial problems are often much more difficult to solve than uniformly random instances, even at phase transition boundaries. There are almost no formal results known for such problem distributions. The balancing constraints add a dependency between variables that complicates a standard analysis. Regular random 3-SAT exhibits a phase transition as a function of the ratio α of clauses to variables. The transition takes place at approximately α = 3.5. We show that for α > 3.78 with high probability (w.h.p.) random regular 3-SAT formulas are unsatisfiable. Specifically, the events hold with high probability if Pr when n → ∞. We also show that the analysis of a greedy algorithm proposed by Kaporis et al. for the uniform 3-SAT model can be adapted for regular random 3-SAT. In particular, we show that for formulas with ratio α < 2.46, a greedy algorithm finds a satisfying assignment with positive probability.     

A decision support system for fraud detection in public procurement

Over the past few years, investigators in Brazil have been uncovering numerous corruption and money laundering schemes at all levels of government and in the country's largest corporations. It is estimated that between 2% and 5% of the global GDP is lost annually because of such practices, not only directly impacting public services and private sector development but also strengthening organized crime. However, most law enforcement agencies do not have the capability to carry out systematic corruption risk assessment leveraging on the availability of data related to public procurement. The currently prevailing approach employed by Brazilian law enforcement agencies to detect companies involved in potential cases of fraud consists in receiving circumstantial evidence or complaints from whistleblowers. As a result, a large number of companies involved in fraud remain undetected and unprosecuted. The decision support system (DSS) described in this work addresses these existing limitations by providing a tool for systematic analysis of public procurement. It allows the law enforcement agencies to establish priorities concerning the companies to be investigated. This DSS incorporates data mining algorithms for quantifying dozens of corruption risk patterns for all public contractors inside a specific jurisdiction, leading to improvements in the quality of public spending and to the identification of more cases of fraud. These algorithms combine operations research tools such as graph theory, clusterization, and regression analysis with advanced data science methods to allow the identification of the main risk patterns, such as collusion between bidders, conflicts of interest (e.g., a politician who owns a company contracted by the same government body where he or she was elected), and companies owned by a potentially straw person used for disguising its real owner (e.g., beneficiaries of cash conditional transfer programs). The DSS has already led to a detailed analysis of large public procurement datasets, which add up to more than 50 billion dollars. Moreover, the DSS provided strategic inputs to investigations conducted by federal and state agencies.     

Catching a viral video

The sharing and re-sharing of videos on social sites, blogs e-mail, and other means has given rise to the phenomenon of viral videos—videos that become popular through internet sharing. In this paper we seek to better understand viral videos on YouTube by analyzing sharing and its relationship to video popularity using millions of YouTube videos. The socialness of a video is quantified by classifying the referrer sources for video views as social (e.g. an emailed link, Facebook referral) or non-social (e.g. a link from related videos). We find that viewership patterns of highly social videos are very different from less social videos. For example, the highly social videos rise to, and fall from, their peak popularity more quickly than less social videos. We also find that not all highly social videos become popular, and not all popular videos are highly social. By using our insights on viral videos we are able develop a method for ranking blogs and websites on their ability to spread viral videos.     

A GRASP heuristic using path‐relinking and restarts for the Steiner traveling salesman problem

The traveling salesman problem (TSP) is one of the most studied problems in combinatorial optimization. Given a set of nodes and the distances between them, it consists in finding the shortest route that visits each node exactly once and returns to the first. Nevertheless, more flexible and applicable formulations of this problem exist and can be considered. The Steiner TSP (STSP) is a variant of the TSP that assumes that only a given subset of nodes must be visited by the shortest route, eventually visiting some nodes and edges more than once. In this paper, we adapt some classical TSP constructive heuristics and neighborhood structures to the STSP variant. In particular, we propose a reduced 2‐opt neighborhood and we show that it leads to better results in smaller computation times. Computational results with an implementation of a GRASP heuristic using path‐relinking and restarts are reported. In addition, ten large test instances are generated. All instances and their best‐known solutions are made available for download and benchmarking purposes.     

The integration of CBT, multicultural and feminist psychotherapies with Latinas.

Socorro was a 35-year-old Venezuelan woman who attempted suicide by overdose. The psychotherapeutic approach relied on identifying the social context, constructs, and working within Socorro's cultural framework. Cultural issues related to immigration, acculturation, and culturally based gender issues were identified. The integration of cognitive–behavioral, feminist, and multicultural approaches helped to identify how migratory stressors oppressed her sense of self. Tenets of multiracial feminism were incorporated to better understand how her social context affected her perception of relationships, how she made choices and interpreted them. Future work with Latinas should address the development of models for treatment that fuse these perspectives. (PsycINFO Database Record (c) 2010 APA, all rights reserved)