29 research outputs found
Quick survey of graph-based fraud detection methods
In general, anomaly detection is the problem of distinguishing between normal
data samples with well defined patterns or signatures and those that do not
conform to the expected profiles. Financial transactions, customer reviews,
social media posts are all characterized by relational information. In these
networks, fraudulent behaviour may appear as a distinctive graph edge, such as
spam message, a node or a larger subgraph structure, such as when a group of
clients engage in money laundering schemes. Most commonly, these networks are
represented as attributed graphs, with numerical features complementing
relational information. We present a survey on anomaly detection techniques
used for fraud detection that exploit both the graph structure underlying the
data and the contextual information contained in the attributes
Community-Level Anomaly Detection for Anti-Money Laundering
Anomaly detection in networks often boils down to identifying an underlying
graph structure on which the abnormal occurrence rests on. Financial fraud
schemes are one such example, where more or less intricate schemes are employed
in order to elude transaction security protocols. We investigate the problem of
learning graph structure representations using adaptations of dictionary
learning aimed at encoding connectivity patterns. In particular, we adapt
dictionary learning strategies to the specificity of network topologies and
propose new methods that impose Laplacian structure on the dictionaries
themselves. In one adaption we focus on classifying topologies by working
directly on the graph Laplacian and cast the learning problem to accommodate
its 2D structure. We tackle the same problem by learning dictionaries which
consist of vectorized atomic Laplacians, and provide a block coordinate descent
scheme to solve the new dictionary learning formulation. Imposing Laplacian
structure on the dictionaries is also proposed in an adaptation of the Single
Block Orthogonal learning method. Results on synthetic graph datasets
comprising different graph topologies confirm the potential of dictionaries to
directly represent graph structure information
Minimally invasive treatments for disk hernia
Interventional Radiology Department, University Hospital, Bucharest, Romania, “Carol Davila” University, Neurosurgery Clinic, University Hospital, Bucharest, Romania, Neurosurgery Clinic, University Hospital, Bucharest, Romania, “Carol Davila” University, Radiology and Medical Imaging Clinic, University Hospital, Bucharest, Romania, Al VIII-lea Congres Naţional de Ortopedie și Traumatologie cu participare internaţională 12-14 octombrie 2016Background and purpose: Low back pain (LBP) is one of the common reasons for people to seek treatment from a physician,
especially in modern society. We present the indications, technique, complications, etc. of the different minimally invasive
interventions.
Methods: A multitude of therapies are available to treat disc herniation, ranging from conserva-tive methods (medication
and physical therapy) to minimally invasive (chemonucleolysis, O₂-O₃ therapy, mechanical nucleoplasty, intradiscal
electrothermal therapy, etc) and surgery.
Results: We present our experience of 10 years in minimally invasive interventions with common indications, results,
complications, tips and tricks, etc.
Conclusions: Percutaneous disk interventions are an alternative therapy situated between medical treatment and spinal
surgery. Patients selection is very important and lead to the successful of the intervention
Prognostic impact of acute pulmonary triggers in patients with Takotsubo syndrome : new insights from the International Takotsubo Registry
© 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License.Aims: Acute pulmonary disorders are known physical triggers of takotsubo syndrome (TTS). This study aimed to investigate prevalence of acute pulmonary triggers in patients with TTS and their impact on outcomes.
Methods and results: Patients with TTS were enrolled from the International Takotsubo Registry and screened for triggering factors and comorbidities. Patients were categorized into three groups (acute pulmonary trigger, chronic lung disease, and no lung disease) to compare clinical characteristics and outcomes. Of the 1670 included patients with TTS, 123 (7%) were identified with an acute pulmonary trigger, and 194 (12%) had a known history of chronic lung disease. The incidence of cardiogenic shock was highest in patients with an acute pulmonary trigger compared with those with chronic lung disease or without lung disease (17% vs. 10% vs. 9%, P = 0.017). In-hospital mortality was also higher in patients with an acute pulmonary trigger than in the other two groups, although not significantly (5.7% vs. 1.5% vs. 4.2%, P = 0.13). Survival analysis demonstrated that patients with an acute pulmonary trigger had the worst long-term outcome (P = 0.002). The presence of an acute pulmonary trigger was independently associated with worse long-term mortality (hazard ratio 2.12, 95% confidence interval 1.33-3.38; P = 0.002).
Conclusions: The present study demonstrates that TTS is related to acute pulmonary triggers in 7% of all TTS patients, which accounts for 21% of patients with physical triggers. The presence of acute pulmonary trigger is associated with a severe in-hospital course and a worse long-term outcome.C. T. has been supported by the H.H. Sheikh Khalifa binHamad Al-Thani Research Programme and the Swiss HeartFoundation. The InterTAK Registry is supported by the BissDavies Charitable Trust. L. S. M. has been supported by EUHORIZON 2020(SILICOFCM ID777204)info:eu-repo/semantics/publishedVersio
Enhanced hydrogen production from thermochemical processes
To alleviate the pressing problem of greenhouse gas emissions, the development and deployment of sustainable energy technologies is necessary. One potentially viable approach for replacing fossil fuels is the development of a H2 economy. Not only can H2 be used to produce heat and electricity, it is also utilised in ammonia synthesis and hydrocracking. H2 is traditionally generated from thermochemical processes such as steam reforming of hydrocarbons and the water-gas-shift (WGS) reaction. However, these processes suffer from low H2 yields owing to their reversible nature. Removing H2 with membranes and/or extracting CO2 with solid sorbents in situ can overcome these issues by shifting the component equilibrium towards enhanced H2 production via Le Chatelier's principle. This can potentially result in reduced energy consumption, smaller reactor sizes and, therefore, lower capital costs. In light of this, a significant amount of work has been conducted over the past few decades to refine these processes through the development of novel materials and complex models. Here, we critically review the most recent developments in these studies, identify possible research gaps, and offer recommendations for future research
Optimal campaigns in end-to-end continuous pharmaceuticals manufacturing. Part 2: Dynamic optimization
© 2018 Elsevier B.V. We investigate theoretical optimal campaigns in a continuous process of pharmaceuticals production. The simulated process, inspired by a pilot plant previously tested at MIT, includes several reaction and separation steps to produce final tablets. This paper, demonstrates the use of nonsmooth differential-algebraic equations (DAEs) framework for such optimal campaigns design. We embed the model developed in the first part of this series in a dynamic optimization problem formulated as a hybrid discrete/continuous and nonsmooth problem. We enforce the quality constraints only on an interior epoch (on-spec) and optimize its duration. We then use a gradient-based optimization tool (IPOPT) to solve the problem. We consider the on-specification productivity over the entire campaign. Various control valves are chosen as decision variables, as well as the timings of the control switchings. The yield and the productivity of the process are considered as objectives under a constant (short) time horizon. Pareto curves of optimal yield and productivity for various campaign durations are calculated. The results show a significant improvement over a “nominal” operating procedure that only considers steady-state operation. This methodology can be used to guide decision makers, in both the design stage of new plants and the operation of existing configurations
Nonsmooth differential-algebraic equations in chemical engineering
This article advocates a nonsmooth differential-algebraic equations (DAEs) modeling paradigm for dynamic simulation and optimization of process operations. A variety of systems encountered in chemical engineering are traditionally viewed as exhibiting hybrid continuous and discrete behavior. In many cases such discrete behavior is nonsmooth (i.e. continuous but nondifferentiable) rather than discontinuous, and is appropriately modeled by nonsmooth DAEs. A computationally relevant theory of nonsmooth DAEs (i.e. well-posedness and sensitivity analysis) has recently been established (Stechlinski and Barton, 2016a, 2017) which is suitable for numerical implementations that scale efficiently for large-scale dynamic optimization problems. Challenges posed by competing hybrid modeling approaches for process operations (e.g. hybrid automata) are highlighted as motivation for the nonsmooth DAEs approach. Several examples of process operations modeled as nonsmooth DAEs are given to illustrate their wide applicability before presenting the appropriate mathematical theory.Natural Sciences and Engineering Research Council of Canad
Lipopolysaccharide-mediated interferon regulatory factor activation involves TBK1-IKKepsilon-dependent Lys(63)-linked polyubiquitination and phosphorylation of TANK/I-TRAF.
Type I interferon gene induction relies on IKK-related kinase TBK1 and IKKepsilon-mediated phosphorylations of IRF3/7 through the Toll-like receptor-dependent signaling pathways. The scaffold proteins that assemble these kinase complexes are poorly characterized. We show here that TANK/ITRAF is required for the TBK1- and IKKepsilon-mediated IRF3/7 phosphorylations through some Toll-like receptor-dependent pathways and is part of a TRAF3-containing complex. Moreover, TANK is dispensable for the early phase of double-stranded RNA-mediated IRF3 phosphorylation. Interestingly, TANK is heavily phosphorylated by TBK1-IKKepsilon upon lipopolysaccharide stimulation and is also subject to lipopolysaccharide- and TBK1-IKKepsilon-mediated Lys(63)-linked polyubiquitination, a mechanism that does not require TBK1-IKKepsilon kinase activity. Thus, we have identified TANK as a scaffold protein that assembles some but not all IRF3/7-phosphorylating TBK1-IKKepsilon complexes and demonstrated that these kinases possess two functions, namely the phosphorylation of both IRF3/7 and TANK as well as the recruitment of an E3 ligase for Lys(63)-linked polyubiquitination of their scaffold protein, TANK.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe