New millennium frontiers on precision engineering

The need to establish ultraprecision mechanical fabrication processes to produce 'microfunctional structures' that have microstructures on their surfaces and/or inside and which are capable of performing various functions are inarguably growing increasingly stronger. In industries today, holographic optical elements (OHE), silicon-on-insulator (DOI) substrates and semiconductor devices wafers for ultralarge-scale integrated circuits(ULSI), microlens and microparts/components are good examples of microfunctional structures in the field of optoelectronics and mechatronics. For all these applications, the definition of precision engineering was changed by a few orders of magnitude. Some example of new precision engineering processes will be presented, which will include atomistic level polishing of AlTiC magnetic heads, microspherical lens fabrication and molecular dynamics (MD) simulation of the abrasive processes. Finally, some of the limitations of the precision engineering processes will be pointed out.     

Space–time tradeoffs for parallel 3D reconstruction algorithms for virus‐structure determination

The 3D electron‐density determination of viruses, from experimental data provided by electron microscopy, is a data‐intensive computation that requires the use of clusters of PCs or parallel computers. In this paper we report on three parallel algorithms used for 3D reconstruction of asymmetric objects from their 2D projections. We discuss their computational, communication, I/O, and space requirements and present some performance data. The algorithms are general and can be used for 3D reconstruction of asymmetric objects for applications other than structural biology. Copyright © 2001 John Wiley & Sons, Ltd.     

Agent based scientific simulation and modeling

The simulation and modeling of complex physical systems often involves many components because (i) the physical system itself has components of differing natures, (ii) parallel computing strategies require many (somewhat independent) components, and (iii) existing simulation software applies only to simpler geometrical shapes and physical situations. We discuss how agent based networks are applied to such multi‐component applications. The network agents are used to (a) control the execution of existing solvers on sub‐components, (b) mediate between sub‐components, and (c) coordinate the execution of the ensemble. This paper focuses on partial differential equation (PDE) models as an instance of the approach and describes the implementation of networks using the PELLPACK problem solving environment for PDEs and the Bond system for agent based computing. Copyright © 2000 John Wiley & Sons, Ltd.     

Non-Coding RNAs: Prevention,Diagnosis, and Treatment in Myocardial Ischemia–Reperfusion Injury

Recent knowledge concerning the role of non-coding RNAs (ncRNAs) in myocardial ischemia/reperfusion (I/R) injury provides new insight into their possible roles as specific biomarkers for early diagnosis, prognosis, and treatment. MicroRNAs (miRNAs) have fewer than 200 nucleotides, while long ncRNAs (lncRNAs) have more than 200 nucleotides. The three types of ncRNAs (miRNAs, lncRNAs, and circRNAs) act as signaling molecules strongly involved in cardiovascular disorders (CVD). I/R injury of the heart is the main CVD correlated with acute myocardial infarction (AMI), cardiac surgery, and transplantation. The expression levels of many ncRNAs and miRNAs are highly modified in the plasma of MI patients, and thus they have the potential to diagnose and treat MI. Cardiomyocyte and endothelial cell death is the major trigger for myocardial ischemia–reperfusion syndrome (MIRS). The cardioprotective effect of inflammasome activation in MIRS and the therapeutics targeting the reparative response could prevent progressive post-infarction heart failure. Moreover, the pharmacological and genetic modulation of these ncRNAs has the therapeutic potential to improve clinical outcomes in AMI patients.     

Quantum Error Correction of Time-correlated Errors

The complexity of the error correction circuitry forces us to design quantum error correction codes capable of correcting a single error per error correction cycle. Yet, time-correlated error are common for physical implementations of quantum systems; an error corrected during the previous cycle may reoccur later due to physical processes specific for each physical implementation of the qubits. In this paper, we study quantum error correction for a restricted class of time-correlated errors in a spin-boson model. The algorithm we propose allows the correction of two errors per error correction cycle, provided that one of them is time-correlated. The algorithm can be applied to any stabilizer code when the two logical qubits and are entangled states of 2 ⁿ basis states in .      

Algorithms for Divisible Load Scheduling of Data-intensive Applications

In this paper we introduce the Divisible Load Scheduling (DLS) family of algorithms for data-intensive applications. The polynomial time algorithms partition the input data and generate optimal mappings to collection of autonomous and heterogeneous computational systems. We prove the optimality of the solution and report a simulation study of the algorithms.     

AND/OR Branch-and-Bound search for combinatorial optimization in graphical models

This is the first of two papers presenting and evaluating the power of a new framework for combinatorial optimization in graphical models, based on AND/OR search spaces. We introduce a new generation of depth-first Branch-and-Bound algorithms that explore the AND/OR search tree using static and dynamic variable orderings. The virtue of the AND/OR representation of the search space is that its size may be far smaller than that of a traditional OR representation, which can translate into significant time savings for search algorithms. The focus of this paper is on linear space search which explores the AND/OR search tree. In the second paper we explore memory intensive AND/OR search algorithms. In conjunction with the AND/OR search space we investigate the power of the mini-bucket heuristics in both static and dynamic setups. We focus on two most common optimization problems in graphical models: finding the Most Probable Explanation in Bayesian networks and solving Weighted CSPs. In extensive empirical evaluations we demonstrate that the new AND/OR Branch-and-Bound approach improves considerably over the traditional OR search strategy and show how various variable ordering schemes impact the performance of the AND/OR search scheme.     

Dual Stem Cell Therapy Improves the Myocardial Recovery Post-Infarction through Reciprocal Modulation of Cell Functions

Mesenchymal stromal cells (MSC) are promising candidates for regenerative therapy of the infarcted heart. However, poor cell retention within the transplantation site limits their potential. We hypothesized that MSC benefits could be enhanced through a dual-cell approach using jointly endothelial colony forming cells (ECFC) and MSC. To assess this, we comparatively evaluated the effects of the therapy with MSC and ECFC versus MSC-only in a mouse model of myocardial infarction. Heart function was assessed by echocardiography, and the molecular crosstalk between MSC and ECFC was evaluated in vitro through direct or indirect co-culture systems. We found that dual-cell therapy improved cardiac function in terms of ejection fraction and stroke volume. In vitro experiments showed that ECFC augmented MSC effector properties by increasing Connexin 43 and Integrin alpha-5 and the secretion of healing-associated molecules. Moreover, MSC prompted the organization of ECFC into vascular networks. This indicated a reciprocal modulation in the functionality of MSC and ECFC. In conclusion, the crosstalk between MSC and ECFC augments the therapeutic properties of MSC and enhances the angiogenic properties of ECFC. Our data consolidate the dual-cell therapy as a step forward for the development of effective treatments for patients affected by myocardial infarction.