Buyback Problem - Approximate matroid intersection with cancellation costs

In the buyback problem, an algorithm observes a sequence of bids and must decide whether to accept each bid at the moment it arrives, subject to some constraints on the set of accepted bids. Decisions to reject bids are irrevocable, whereas decisions to accept bids may be canceled at a cost that is a fixed fraction of the bid value. Previous to our work, deterministic and randomized algorithms were known when the constraint is a matroid constraint. We extend this and give a deterministic algorithm for the case when the constraint is an intersection of $k$ matroid constraints. We further prove a matching lower bound on the competitive ratio for this problem and extend our results to arbitrary downward closed set systems. This problem has applications to banner advertisement, semi-streaming, routing, load balancing and other problems where preemption or cancellation of previous allocations is allowed

Packing Returning Secretaries

We study online secretary problems with returns in combinatorial packing domains with $n$ candidates that arrive sequentially over time in random order. The goal is to accept a feasible packing of candidates of maximum total value. In the first variant, each candidate arrives exactly twice. All $2n$ arrivals occur in random order. We propose a simple 0.5-competitive algorithm that can be combined with arbitrary approximation algorithms for the packing domain, even when the total value of candidates is a subadditive function. For bipartite matching, we obtain an algorithm with competitive ratio at least $0.5721 - o(1)$ for growing $n$, and an algorithm with ratio at least $0.5459$ for all $n \ge 1$. We extend all algorithms and ratios to $k \ge 2$ arrivals per candidate. In the second variant, there is a pool of undecided candidates. In each round, a random candidate from the pool arrives. Upon arrival a candidate can be either decided (accept/reject) or postponed (returned into the pool). We mainly focus on minimizing the expected number of postponements when computing an optimal solution. An expected number of $\Theta(n \log n)$ is always sufficient. For matroids, we show that the expected number can be reduced to $O(r \log (n/r))$, where $r \le n/2$ is the minimum of the ranks of matroid and dual matroid. For bipartite matching, we show a bound of $O(r \log n)$, where $r$ is the size of the optimum matching. For general packing, we show a lower bound of $\Omega(n \log \log n)$, even when the size of the optimum is $r = \Theta(\log n)$.Comment: 23 pages, 5 figure

Building data warehouses in the era of big data: an approach for scalable and flexible big data warehouses

During the last few years, the concept of Big Data Warehousing gained significant attention from the scientific community, highlighting the need to make design changes to the traditional Data Warehouse (DW) due to its limitations, in order to achieve new characteristics relevant in Big Data contexts (e.g., scalability on commodity hardware, real-time performance, and flexible storage). The state-of-the-art in Big Data Warehousing reflects the young age of the concept, as well as ambiguity and the lack of common approaches to build Big Data Warehouses (BDWs). Consequently, an approach to design and implement these complex systems is of major relevance to business analytics researchers and practitioners. In this tutorial, the design and implementation of BDWs is targeted, in order to present a general approach that researchers and practitioners can follow in their Big Data Warehousing projects, exploring several demonstration cases focusing on system design and data modelling examples in areas like smart cities, retail, finance, manufacturing, among others

Active Re-identification Attacks on Periodically Released Dynamic Social Graphs

Active re-identification attacks pose a serious threat to privacy-preserving social graph publication. Active attackers create fake accounts to build structural patterns in social graphs which can be used to re-identify legitimate users on published anonymised graphs, even without additional background knowledge. So far, this type of attacks has only been studied in the scenario where the inherently dynamic social graph is published once. In this paper, we present the first active re-identification attack in the more realistic scenario where a dynamic social graph is periodically published. The new attack leverages tempo-structural patterns for strengthening the adversary. Through a comprehensive set of experiments on real-life and synthetic dynamic social graphs, we show that our new attack substantially outperforms the most effective static active attack in the literature by increasing the success probability of re-identification by more than two times and efficiency by almost 10 times. Moreover, unlike the static attack, our new attack is able to remain at the same level of effectiveness and efficiency as the publication process advances. We conduct a study on the factors that may thwart our new attack, which can help design graph anonymising methods with a better balance between privacy and utility

Mediastinitis complicating a percutaneous endoscopic gastrostomy: a case report

BACKGROUND: Since its introduction in the early 1980s, percutaneous endoscopic gastrostomy has become the most popular method for performing a gastrostomy for long-term enteral feeding. It has been associated, however, with a lot of minor and major complications. CASE PRESENTATION: A case of mediastinitis with concominant sepsis caused by a masked esophageal perforation after percutaneous endoscopic gastrostomy in a multi-traumatized, brain-injured patient is presented. Ten – fourteen days after the procedure, the patient became febrile and gradually septic with tenderness of the sternum and upper abdomen. Computerized tomography of the thorax revealed mediastinitis. An urgent left thoracotomy and laparotomy were performed for drainage of the mediastinum, removal of the gastrostomy and insertion of a jejunostomy tube. The patient improved soon after the surgery. He was successfully weaned off the ventilator and was discharged from the Intensive Care Unit. CONCLUSION: Perforating mediastinitis is a rare but potentially lethal complication of percutaneous endoscopic gastrostomy. When diagnosed and properly treated it may have a favourable outcome

Gastric variceal bleeding caused by an intrahepatic arterioportal fistula that formed after liver biopsy: a case report and review of the literature

An intrahepatic arterioportal fistula is a rare cause of portal hypertension and variceal bleeding. We report on a patient with an intrahepatic arterioportal fistula following liver biopsy who was successfully treated by hepatectomy after unsuccessful arterial embolization. We also review the literature on symptomatic intrahepatic arterioportal fistulas after liver biopsy. A 48-year-old male with bleeding gastric varices and hepatitis B virus-associated liver cirrhosis was transferred to our hospital; this patient previously underwent percutaneous liver biopsies 3 and 6 years ago. Abdominal examination revealed a bruit over the liver, tenderness in the right upper quadrant, and splenomegaly. Ultrasonographic examination, computed tomography, and angiography confirmed an arterioportal fistula between the right hepatic artery and the right portal vein with portal hypertension. After admission, the patient suffered a large hematemesis and developed shock. He was treated with emergency transarterial embolization using microcoils. Since some collateral vessels bypassed the obstructive coils and still fed the fistulous area, embolization was performed again. Despite the second embolization, the collateral vessels could not be completely controlled. Radical treatment involving resection of his right hepatic lobe was performed. For nearly 6 years postoperatively, this patient has had no further episodes of variceal bleeding

PROPER: global protein interaction network alignment through percolation matching

Background The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. Results In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. Conclusions We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch

Approximation Algorithms for Network Design and Orienteering

This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning

Awareness during anaesthesia for surgery requiring evoked potential monitoring: A pilot study

Background: Evoked potential monitoring such as somatosensory-evoked potential (SSEP) or motor-evoked potential (MEP) monitoring during surgical procedures in proximity to the spinal cord requires minimising the minimum alveolar concentrations (MACs) below the anaesthetic concentrations normally required (1 MAC) to prevent interference in amplitude and latency of evoked potentials. This could result in awareness. Our primary objective was to determine the incidence of awareness while administering low MAC inhalational anaesthetics for these unique procedures. The secondary objective was to assess the adequacy of our anaesthetic technique from neurophysiologist’s perspective. Methods: In this prospective observational pilot study, 61 American Society of Anesthesiologists 1 and 2 patients undergoing spinal surgery for whom intraoperative evoked potential monitoring was performed were included; during the maintenance phase, 0.7–0.8 MAC of isoflurane was targeted. We evaluated the intraoperative depth of anaesthesia using a bispectral (BIS) index monitor as well as the patients response to surgical stimulus (PRST) scoring system. Post-operatively, a modified Bruce questionnaire was used to verify awareness. The adequacy of evoked potential readings was also assessed. Results: Of the 61 patients, no patient had explicit awareness. Intraoperatively, 19 of 61 patients had a BIS value of above sixty at least once, during surgery. There was no correlation with PRST scoring and BIS during surgery. Fifty-four out of 61 patient’s evoked potential readings were deemed ‘good’ or ‘fair’ for the conduct of electrophysiological monitoring. Conclusions: This pilot study demonstrates that administering low MAC inhalational anaesthetics to facilitate evoked potential monitoring does not result in explicit awareness. However, larger studies are needed to verify this. The conduct of SSEP electrophysiological monitoring was satisfactory with the use of this anaesthetic technique. However, the conduct of MEP monitoring was satisfactory, only in patients with Nurick Grade 1 and 2. The MEP response was poor in patients with Nurick Grade 4 and 5