A Fixed-Parameter Algorithm for the Max-Cut Problem on Embedded 1-Planar Graphs

We propose a fixed-parameter tractable algorithm for the \textsc{Max-Cut} problem on embedded 1-planar graphs parameterized by the crossing number $k$ of the given embedding. A graph is called 1-planar if it can be drawn in the plane with at most one crossing per edge. Our algorithm recursively reduces a 1-planar graph to at most $3^k$ planar graphs, using edge removal and node contraction. The \textsc{Max-Cut} problem is then solved on the planar graphs using established polynomial-time algorithms. We show that a maximum cut in the given 1-planar graph can be derived from the solutions for the planar graphs. Our algorithm computes a maximum cut in an embedded 1-planar graph with $n$ nodes and $k$ edge crossings in time $\mathcal{O}(3^k \cdot n^{3/2} \log n)$.Comment: conference version from IWOCA 201

Rhabdomyolysis due to the additive effect of statin therapy and hypothyroidism: a case report

We describe a patient with previously undiagnosed hypothyroidism who developed rhabdomyolysis while taking a statin. He had no other precipitating factors. The statin was stopped, intravenous fluids were started immediately and L-thyroxin was given after confirming the diagnosis of hypothyroidism. His symptoms improved over a few days. Because rhabdomyolysis is a rare but potentially life threatening disorder when complicated by acute tubular necrosis and renal failure, physicians must pay special attention when starting statins in patients with hyperlipidemia

Network 'small-world-ness': a quantitative method for determining canonical network equivalence

Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing

Ventilatory Chaos Is Impaired in Carotid Atherosclerosis

Ventilatory chaos is strongly linked to the activity of central pattern generators, alone or influenced by respiratory or cardiovascular afferents. We hypothesized that carotid atherosclerosis should alter ventilatory chaos through baroreflex and autonomic nervous system dysfunctions. Chaotic dynamics of inspiratory flow was prospectively evaluated in 75 subjects undergoing carotid ultrasonography: 27 with severe carotid stenosis (>70%), 23 with moderate stenosis (<70%), and 25 controls. Chaos was characterized by the noise titration method, the correlation dimension and the largest Lyapunov exponent. Baroreflex sensitivity was estimated in the frequency domain. In the control group, 92% of the time series exhibit nonlinear deterministic chaos with positive noise limit, whereas only 68% had a positive noise limit value in the stenoses groups. Ventilatory chaos was impaired in the groups with carotid stenoses, with significant parallel decrease in the noise limit value, correlation dimension and largest Lyapunov exponent, as compared to controls. In multiple regression models, the percentage of carotid stenosis was the best in predicting the correlation dimension (p<0.001, adjusted R2: 0.35) and largest Lyapunov exponent (p<0.001, adjusted R2: 0.6). Baroreflex sensitivity also predicted the correlation dimension values (p = 0.05), and the LLE (p = 0.08). Plaque removal after carotid surgery reversed the loss of ventilatory complexity. To conclude, ventilatory chaos is impaired in carotid atherosclerosis. These findings depend on the severity of the stenosis, its localization, plaque surface and morphology features, and is independently associated with baroreflex sensitivity reduction. These findings should help to understand the determinants of ventilatory complexity and breathing control in pathological conditions

Use of antipsychotic drugs. A multicentric study of inpatients with acute psychotic disorders

Com o objectivo de caracterizar o padrão e os determinantes de utilização de fármacos antipsicóticos por via intra-muscular em indivíduos hospitalizados por perturbação psicótica aguda, efectuou-se um estudo retrospectivo de 244 indivíduos, admitidos em sete unidades hospitalares de internamento psiquiátrico. Foram seleccionados dois grupos, IM (Intra Muscular) e PO (Via Oral), que nos primeiros três dias de internamento receberam respectivamente medicação antipsicótica por via intramuscular ou por via oral, tendo-se explorado as eventuais diferenças nas áreas demográfica, clínica e terapêutica (com revisão dos casos aos 6 e 12 meses após a alta hospitalar). Os dois grupos foram homogéneos quanto à idade, raça, sexo, idade do início da doença e diagnóstico, tendo-se verificado um número maior de internamentos compulsivos no grupo IM. As perturbações psicóticas mais prevalentes em ambos os grupos foram a esquizofrenia e a perturbação bipolar, não se tendo encontrado qualquer associação entre os diagnósticos iniciais e a via de administração dos fármacos. O tempo de hospitalização foi igual entre grupos, embora nos doentes do grupo IM tivesse sido necessário tomar medidas de precaução especiais com maior frequência. A medicação ansiolítica foi superior no grupo PO nos dias um e dois de hospitalização e igual nos dois grupos no dia três e no dia de alta. A terapêutica anticolinérgica foi semelhante entre os dois grupos. O número de novas hospitalizações, bem como a percentagem de doentes a utilizar medicação antipsicótica, ansiolítica e anticolinérgica, foi semelhante nos dois grupos após 6 e 12 meses de seguimento. Neste estudo, a presença de agitação psicomotora e de comportamentos agressivo/destrutivo na fase inicial do internamento no grupo IM (incluindo o primeiro contacto, maioritariamente feito no serviço de urgência) foram os elementos estatisticamente determinantes da utilização da via intramuscular para a administração dos fármacos antipsicóticos. With the objective of determining the pattern and decision making process in using antipsychotic drugs in patients admitted to hospital for acute psychotic disorder we have made a retrospective analysis in 244 in-patients in 7 hospitals for mental disorders. We have selected two groups, IM and PO, that in the first three days of internment have received either intravenous antipsychotic medication or oral medication; the demographical, clinical and therapeutical differences have been considered (with a review of the cases at 6 and 12 months after discharge from hospital). Homogeneity was considered regarding age, race, gender, age at the onset of the disease and diagnosis; in the IM group there were a larger number of compulsive admissions. The most prevalent psychotic disorders in both groups were schizophrenia and bipolar disorder; with no association being made between the initial diagnosis and drug administration. The hospitalization period was the same for both groups, although in the patients in the IM group the need for special precautions was more frequent. Medication with anxiolytics was higher in the PO group on day 1 and 2 of the hospitalization and the same for the two groups on day 3 and on discharge. The number of new admissions, as well as the percentage of patients taking antipsychotic, anxiolytic and anticholinergic medication was similar in both groups after a period of 6 and 12 months follow-up. In this study, agitation and aggressive/destructive behaviours in the initial phase of hospitalization in the IM group (including the first contact, most of the times on admission at the ER) were statistically significant factors for the use of intramuscular administration of antipsychotic drugs.publishersversionpublishe

A survey on independence-based Markov networks learning

This work reports the most relevant technical aspects in the problem of learning the \emph{Markov network structure} from data. Such problem has become increasingly important in machine learning, and many other application fields of machine learning. Markov networks, together with Bayesian networks, are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. Learning graphical models from data have been extensively applied for the case of Bayesian networks, but for Markov networks learning it is not tractable in practice. However, this situation is changing with time, given the exponential growth of computers capacity, the plethora of available digital data, and the researching on new learning technologies. This work stresses on a technology called independence-based learning, which allows the learning of the independence structure of those networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sampling of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms for learning Markov networks structure, discussing its current limitations, and proposing a series of open problems where future works may produce some advances in the area in terms of quality and efficiency. The paper concludes by opening a discussion about how to develop a general formalism for improving the quality of the structures learned, when data is scarce.Comment: 35 pages, 1 figur

Repurposed floxacins targeting RSK4 prevent chemoresistance and metastasis in lung and bladder cancer

Lung and bladder cancers are mostly incurable because of the early development of drug resistance and metastatic dissemination. Hence, improved therapies that tackle these two processes are urgently needed to improve clinical outcome. We have identified RSK4 as a promoter of drug resistance and metastasis in lung and bladder cancer cells. Silencing this kinase, through either RNA interference or CRISPR, sensitized tumor cells to chemotherapy and hindered metastasis in vitro and in vivo in a tail vein injection model. Drug screening revealed several floxacin antibiotics as potent RSK4 activation inhibitors, and trovafloxacin reproduced all effects of RSK4 silencing in vitro and in/ex vivo using lung cancer xenograft and genetically engineered mouse models and bladder tumor explants. Through x-ray structure determination and Markov transient and Deuterium exchange analyses, we identified the allosteric binding site and revealed how this compound blocks RSK4 kinase activation through binding to an allosteric site and mimicking a kinase autoinhibitory mechanism involving the RSK4’s hydrophobic motif. Last, we show that patients undergoing chemotherapy and adhering to prophylactic levofloxacin in the large placebo-controlled randomized phase 3 SIGNIFICANT trial had significantly increased (P = 0.048) long-term overall survival times. Hence, we suggest that RSK4 inhibition may represent an effective therapeutic strategy for treating lung and bladder cancer

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject