Metacomputing across intercontinental networks

An intercontinental network of supercomputers spanning more than 10 000 miles and running challenging scientific applications was realized at the Supercomputing ’99 (SC99) conference in Portland, OR using PACX-MPI and ATM PVCs. In this paper, we describe how we constructed the heterogeneous cluster of supercomputers, the problems we confronted in terms of multi-architecture and the way several applications handled the specific requirements of a metacomputer.     

The Braun-Falco-Marghescu syndrome, contribution to congenital poikiloderma

Braun-Falco together with Marghescu described 1965 for the first time the clinical picture of bullous congenital poikilodermia. In reviewing 15 cases of the literature and one own case this disease is discussed here as an own nosological entity within the congenital poikilodermias and it is suggested to use the designation "Braun-Falco-Marghescu-Syndrome" according to the first describers.     

The interplay of memory and judgment processes in effects of aging on hindsight bias.

Hindsight bias is the phenomenon that after people are presented with the correct answer to a question, their judgment regarding their own past answer to this question is biased toward the correct answer. In three experiments, younger and older adults gave numerical responses to general-knowledge questions and later attempted to recall their responses. For some questions, the correct answer was provided during recall (Experiment 1) or before recall (Experiments 2 and 3). Multinomial model-based analyses show age differences in both recollection bias and reconstruction bias when the correct judgment was in working memory during the recall phase. The authors discuss implications for theories of cognitive aging and theories of hindsight bias. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Material Control System for the Manufactured Housing Industry

A manufactured home is a factory-built house constructed in a controlled factory environment according to federal standards known as the Department of Housing and Urban Development (HUD) code. The manufactured home shares approximately 20% of the total housing units in the United States and plays an important role in providing affordable housing. However, in terms of material engineering, advanced techniques are scarcely used in the manufactured housing (MH) industry. The current material flow and control systems are characterized as independent demand systems that are based on the personal experience of the material managers. Although independent inventory control systems are widely used in many manufacturing industries, these systems lead to a large amount of inventory and have many drawbacks for the MH industry. On the other hand, dependent inventory systems can reduce unfavorable inventory levels using new techniques and present substantial benefits for the MH industry. This paper applies lean inventory control systems and supply chain management techniques to the current systems of the MH industry and proposes a new framework of material control systems as one of the system management tools.     

Towards Efficient Execution of MPI Applications on the Grid: Porting and Optimization Issues

The message passing interface (MPI) is a standard used by many parallel scientific applications. It offers the advantage of a smoother migration path for porting applications from high performance computing systems to the Grid. In this paper Grid-enabled tools and libraries for developing MPI applications are presented. The first is MARMOT, a tool that checks the adherence of an application to the MPI standard. The second is PACX-MPI, an implementation of the MPI standard optimized for Grid environments. Besides the efficient development of the program, an optimal execution is of paramount importance for most scientific applications. We therefore discuss not only performance on the level of the MPI library, but also several application specific optimizations, e.g., for a sparse, parallel equation solver and an RNA folding code, like latency hiding, prefetching, caching and topology-aware algorithms.     

Probabilistic proximity search: Fighting the curse of dimensionality in metric spaces

Proximity searches become very difficult on “high dimensional” metric spaces, that is, those whose histogram of distances has a large mean and/or a small variance. This so-called “curse of dimensionality”, well known in vector spaces, is also observed in metric spaces. The search complexity grows sharply with the dimension and with the search radius. We present a general probabilistic framework applicable to any search algorithm and whose net effect is to reduce the search radius. The higher the dimension, the more effective the technique. We illustrate empirically its practical performance on a particular class of algorithms, where large improvements in the search time are obtained at the cost of a very small error probability.     

Decentralized adaptive recurrent neural control structure

This paper presents a novel decentralized variable structure neural control approach for large-scale uncertain systems, which is developed using recurrent high-order neural networks (RHONN). It is assumed that each subsystem belongs to a class of block-controllable nonlinear systems whose vector fields includes interconnection terms, which are bounded by nonlinear functions. A decentralized RHONN structure and the respective learning law are proposed in order to approximate online the dynamical behavior of each nonlinear subsystem. The control law, which is able to regulate and to track the desired reference signals, is designed using the well-known variable structure theory. The stability of the whole system is analyzed via the Lyapunov methodology. The applicability of the proposed decentralized identification and control algorithm is illustrated via simulations as applied to an interconnected double inverted pendulum.     

A Time-Domain Digital-Intensive Built-In Tester for Analog Circuits

To solve test challenges in nanometer CMOS technologies, a time-domain digital-intensive built-in tester for analog circuits is proposed. The compact tester allows characterizations of AC response and DC gain for various analog circuits which have a low-pass frequency characteristic. By applying ramp signals to stimulate the circuit under test and measuring slopes and time delays of its responses, the testing can be simple and robust over process-voltage-temperature variations. Also, it is well suited for nanometer technologies because of its digital-intensive implementation. The tester was fabricated in 65 nm standard CMOS process and occupies 0.026 mm².     

Binary ant colony optimization applied to variable screening in the Mahalanobis–Taguchi System

This work presents the application of the Mahalanobis–Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.     

Theophylline: Old Drug in a New Light,Application in COVID-19 through Computational Studies

Theophylline (3-methyxanthine) is a historically prominent drug used to treat respiratory diseases, alone or in combination with other drugs. The rapid onset of the COVID-19 pandemic urged the development of effective pharmacological treatments to directly attack the development of new variants of the SARS-CoV-2 virus and possess a therapeutical battery of compounds that could improve the current management of the disease worldwide. In this context, theophylline, through bronchodilatory, immunomodulatory, and potentially antiviral mechanisms, is an interesting proposal as an adjuvant in the treatment of COVID-19 patients. Nevertheless, it is essential to understand how this compound could behave against such a disease, not only at a pharmacodynamic but also at a pharmacokinetic level. In this sense, the quickest approach in drug discovery is through different computational methods, either from network pharmacology or from quantitative systems pharmacology approaches. In the present review, we explore the possibility of using theophylline in the treatment of COVID-19 patients since it seems to be a relevant candidate by aiming at several immunological targets involved in the pathophysiology of the disease. Theophylline down-regulates the inflammatory processes activated by SARS-CoV-2 through various mechanisms, and herein, they are discussed by reviewing computational simulation studies and their different applications and effects.