Fast computation of minimal elementary decompositions of metabolic flux vectors

The concept of elementary flux vector is valuable in a number of applications of metabolic engineering. For instance, in metabolic flux analysis, each admissible flux vector can be expressed as a non-negative linear combination of a small number of elementary flux vectors. However a critical issue concerns the total number of elementary flux vectors which may be huge because it combinatorially increases with the size of the metabolic network. In this paper we present a fast algorithm that randomly computes a decomposition of admissible flux vectors in a minimal number of elementary flux vectors without explicitly enumerating all of them.     

The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.     

Distributed data clustering in sensor networks

Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., a local sensor read, and a concise picture of the global system state needs to be obtained. In resource-constrained environments like sensor networks, this needs to be done without collecting all the data at any location, i.e., in a distributed manner. To this end, we address the distributed clustering problem, in which numerous interconnected nodes compute a clustering of their data, i.e., partition these values into multiple clusters, and describe each cluster concisely. We present a generic algorithm that solves the distributed clustering problem and may be implemented in various topologies, using different clustering types. For example, the generic algorithm can be instantiated to cluster values according to distance, targeting the same problem as the famous k-means clustering algorithm. However, the distance criterion is often not sufficient to provide good clustering results. We present an instantiation of the generic algorithm that describes the values as a Gaussian Mixture (a set of weighted normal distributions), and uses machine learning tools for clustering decisions. Simulations show the robustness, speed and scalability of this algorithm. We prove that any implementation of the generic algorithm converges over any connected topology, clustering criterion and cluster representation, in fully asynchronous settings.     

Good programming in transactional memory : Game theory meets multicore architecture

In a multicore transactional memory (TM) system, concurrent execution threads interact and interfere with each other through shared memory. The less interference a thread provokes the better for the system. However, as a programmer is primarily interested in optimizing her individual code’s performance rather than the system’s overall performance, she does not have a natural incentive to provoke as little interference as possible. Hence, a TM system must be designed compatible with good programming incentives (GPI), i.e., writing efficient code for the overall system should coincide with writing code that optimizes an individual thread’s performance. We show that with most contention managers (CM) proposed in the literature so far, TM systems are not GPI compatible. We provide a generic framework for CMs that base their decisions on priorities and explain how to modify Timestamp-like CMs so as to feature GPI compatibility. In general, however, priority-based conflict resolution policies are prone to be exploited by selfish programmers. In contrast, a simple non-priority-based manager that resolves conflicts at random is GPI compatible.     

Pancreatic xanthomatous neuropathy associated with hyperlipidemia: a cause of abdominal pain mimicking chronic pancreatitis

"Hyperlipidemic crisis" is a term used to describe episodic abdominal pain in patients with hyperlipidemia. The morphologic correlates of this phenomenon have not been investigated and the etiology of the disorder is uncertain. We report a unique histologic finding in the pancreas of a 34-year-old woman with a 17-year history of episodic abdominal pain, sometimes accompanied by hyperamylasemia. At the age of 18 years, grossly elevated cholesterol and triglyceride levels were documented and type V hyperlipidemia was diagnosed. At the age of 34 years, subtotal pancreatectomy was performed for intractable abdominal pain. Histologic examination identified an increased number of enlarged pancreatic nerves that were infiltrated by foamy macrophages and encircled by fibrous tissue; endoneurial infiltration with macrophages occasionally split nerves into individual fascicles. Otherwise, the pancreas had only minimal fibrosis, nesidioblastosis, mucinous metaplasia of some pancreatic ducts, and scattered small collections of chronic inflammatory cells, subtle features suggesting very mild chronic pancreatitis. We propose that this novel xanthomatous neuropathy mimicked pancreatitis and was one of the underlying pathophysiologic mechanisms of abdominal pain in this patient. Further studies are necessary to document the prevalence of this new entity in patients with hyperlipidemia and to correlate its occurrence with "hyperlipidemic crisis" in those individuals.     

Complications after extracorporeal shock wave lithotripsy (ESWL) and methods of management of such cases

The authors presented the complications which occurred in patients after extracorporeal shock wave lithotripsy (ESWL), and discussed the methods of management of such patients. It was found that the most common complications were: renal colic, fever, "calculus route", and, less frequently, subcapsular and perirenal haematomas. In most patients conservative treatment was adequate. Some of these patients required admission to hospital and proper specialized management.     

Constraint Lingo: towards high‐level constraint programming

Logic programming requires that the programmer convert a problem into a set of constraints based on predicates. Choosing the predicates and introducing appropriate constraints can be intricate and error prone. If the problem domain is structured enough, we can let the programmer express the problem in terms of more abstract, higher‐level constraints. A compiler can then convert the higher‐level program into a logic‐programming formalism. The compiler writer can experiment with alternative low‐level representations of the higher‐level constraints in order to achieve a high‐quality translation. The programmer can then take advantage of both a reduction in complexity and an improvement in runtime speed for all problems within the domain. We apply this analysis to the domain of tabular constraint‐satisfaction problems. Examples of such problems include logic puzzles solvable on a hatch grid and combinatorial problems such as graph coloring and independent sets. The proper abstractions for these problems are rows, columns, entries, and their interactions. We present a higher‐level language, Constraint Lingo, dedicated to problems in this domain. We also describe how we translate programs from Constraint Lingo into lower‐level logic formalisms such as the logic of propositional schemata. These translations require that we choose among competing lower‐level representations in order to produce efficient results. The overall effectiveness of our approach depends on the appropriateness of Constraint Lingo, our ability to translate Constraint Lingo programs into high‐quality representations in logic formalisms, and the efficiency with which logic engines can compute answer sets. We comment on our computational experience with these tools in solving both graph problems and logic puzzles. Copyright © 2004 John Wiley & Sons, Ltd.     

Impossible differential cryptanalysis of 7-round Advanced Encryption Standard (AES)

In 2000, Biham and Keller [Cryptanalysis of reduced variants of Rijndael, 3rd AES Conference, in press] presented an impossible differential cryptanalysis of the Advanced Encryption Standard (AES) up to 5 rounds. This was later improved in 2001 by Cheon et al. [Improved impossible differential cryptanalysis of Rijndael and Crypton, in: Lecture Notes in Comput. Sci., vol.  2288, Springer-Verlag, Berlin, 2001, pp. 39-49] to apply to 6 rounds of the AES. In this paper, we extend on previous results to present an attack on the AES up to 7 rounds. This is the best-known impossible differential attack on the AES, and works by exploiting weaknesses in the AES key schedule.     

Innovative hydrogen release from sodium borohydride hydrolysis using biocatalyst-like Fe2O3 nanoparticles impregnated on Bacillus simplex bacteria

For the first time in this innovative study, microorganisms such as Bacillus simplex bacteria, mostly used in biological activity studies, are used as a bio-supporter agent of iron to release hydrogen from sodium borohydride hydrolysis at 25.0 ± 0.1 °C. The goal is to investigate thoroughly sodium borohydride hydrolysis catalyzed by Fe₂O₃ nanoparticles impregnated on microorganism such as Bacillus simplex (BS) bacteria (Fe₂O₃@BS NPs) known with strong antibacterial properties, which makes innovative them a candidate for hydrolysis reaction. This study was focused on the preparation, identification, and catalytic use of biocatalyst-like Fe₂O₃@BS NPs for hydrogen release from the sodium borohydride hydrolysis at 25.0 ± 0.1 °C. The characterization results made after and before hydrolysis reaction using by SEM/SEM-EDX, FT-IR, XRD, UV–vis, XPS, DLS, ELS Zeta potential, ESR, and TEM techniques reveal the formation of highly active, stable, durable, and long-lived biocatalysts-like Fe₂O₃@BS NPs.