Electrochemical Characterization of Nonaqueous Systems for Secondary Battery Application Quarterly Report, May - Jul. 1968

Electrochemical characterization of nonaqueous systems for secondary battery applicatio

Electrochemical characterization of nonaqueous systems for secondary battery application Quarterly report, Aug. - Oct. 1967

Multisweep cyclic voltammograms for electrochemical characterization of nonaqueous systems for secondary battery application

Electrochemical characterization of nonaqueous systems for secondary battery application

Electrochemical evaluation of electrode organic electrolyte combinations for rechargeable battery system

Electrochemical characterization of nonaqueous systems for secondary battery application Quarterly report, Nov. 1967 - Jan. 1968

Multisweep cyclic voltammograms for electrochemical characterization of nonaqueous systems for secondary battery application

Electrochemical characterization of nonaqueous systems for secondary battery application Quarterly report, Feb. - Apr. 1968

Electrochemical characterization of nonaqueous battery systems to determine solubility and reactivity effects on electrode compatibilit

Representaci?nes de estructuras ordenadas

71 p. Recurso Electr?nic

Diarréia associada a astrovírus em crianças de ambulatório em Hospital Público de Córdoba, Argentina

Human astroviruses have been increasingly identified as important agents of diarrheal disease in children. However, the disease burden of astrovirus infection is still incompletely assessed. This paper reports results on the epidemiological and clinical characteristics of astrovirus-associated diarrhea, as well as the impact of astrovirus infection on the ambulatory setting at a Public Hospital in Córdoba city, Argentina. From February 2001 through January 2002, 97 randomly selected outpatient visits for diarrhea among children ; 0.05). According to our estimation about one out of seventy-four children in this cohort would be assisted annually for an astroviral-diarrheal episode in the Public Hospital and one out of eight diarrheal cases could be attributed to astrovirus infection. Astrovirus is a common symptomatic infection in pediatric outpatient visits in the public hospital in the study area, contributing 12.37% of the overall morbidity from diarrhea.Os astrovírus humanos têm sido identificados como importantes agentes de diarréias em crianças embora o impacto da sua infecção não tenha sido esclarecido. Este estudo não só mostra os resultados das características epidemiológicas e clínicas, mas também o impacto da infecção por astrovírus em pacientes ambulatoriais de um Hospital Público da cidade de Córdoba na Argentina. Escolheram-se randomicamente 97 pacientes ambulatoriais com menos de 36 meses, entre fevereiro de 2001 e janeiro de 2002, que consultaram por diarréia. Pesquisou-se antígeno de astrovírus por ensaio imuno-enzimático em uma única amostra de fezes por paciente estudado. Determinou-se a presença de astrovírus em 12,37% dos casos de diarréia. Todos os casos positivos foram em crianças de 4 a 18 meses, mas o índice mais elevado se apresentou em crianças de 4 a 6 meses (23,80%). Os sintomas de diarréia associada a astrovírus foram febre 41,66%; vômitos 25,00% e desidratação 8,33%; ou seja, 16,66% dos pacientes precisaram hospitalização. A presença de astrovírus foi anual sem se observar comportamento sazonal, semestre frio 15,21% versus semestre quente 9,80% p >; 0,05. Em nossa pesquisa, uma de cada 74 crianças seria atendida anualmente por apresentar um episódio de diarréia associada a astrovírus no hospital público e um de cada 8 casos de diarréia poderia atribuir-se à infecção por astrovírus. Astrovírus é uma infecção sintomática em pacientes pediátricos ambulatoriais, representando 12,37% da morbidade por diarréia

Simulation of nonlinear random vibrations using artificial neural networks

The simulation of mechanical system random vibrations is important in structural dynamics, but it is particularly difficult when the system under consideration is nonlinear. Artificial neural networks provide a useful tool for the modeling of nonlinear systems, however, such modeling may be inefficient or insufficiently accurate when the system under consideration is complex. This paper shows that there are several transformations that can be used to uncouple and simplify the components of motion of a complex nonlinear system, thereby making its modeling and random vibration simulation, via component modeling with artificial neural networks, a much simpler problem. A numerical example is presented

Preoperative serum CD26 levels: diagnostic efficiency and predictive value for colorectal cancer

CD26 is an ectoenzyme with dipeptidyl peptidase IV activity expressed on a variety of cell types. Although the function of the high concentration of serum-soluble CD26 (sCD26) is unknown, it may be related to the cleavage of biologically active polypeptides. As CD26 or enzymatic activity levels were previously associated with cancer, we examined the potential diagnostic and prognostic value of preoperative sCD26 measurements by ELISA in colorectal carcinoma patients. We found a highly significant difference between sCD26 levels in healthy donors (mean 559.7 ± 125.5 μg l–1) and cancer patients (mean 261.7 ± 138.1 μg l–1) (P < 0.001). A cut-off at 410 μg l–1 gave 90% sensitivity with 90% specificity which means that the diagnostic efficiency of sCD26 is higher than that shown by other markers, particularly in patients at early stages. Moreover, sCD26 as a variable is not related with Dukes’ stage classification, age, gender, tumour location or degree of differentiation. With a follow-up of 2 years until recurrence, preliminary data show that sCD26 can be managed as a prognostic variable of early carcinoma patients. In addition, the origin of sCD26 is discussed. © 2000 Cancer Research Campaig

Use of artificial neural networks for analysis of complex physical systems

Mathematical models of physical systems are used, among other purposes, to improve our understanding of the behavior of physical systems, predict physical system response, and control the responses of systems. Phenomenological models are frequently used to simulate system behavior, but an alternative is available - the artificial neural network (ANN). The ANN is an inductive, or data-based model for the simulation of input/output mappings. The ANN can be used in numerous frameworks to simulate physical system behavior. ANNs require training data to learn patterns of input/output behavior, and once trained, they can be used to simulate system behavior within the space where they were trained.They do this by interpolating specified inputs among the training inputs to yield outputs that are interpolations of =Ming outputs. The reason for using ANNs for the simulation of system response is that they provide accurate approximations of system behavior and are typically much more efficient than phenomenological models. This efficiency is very important in situations where multiple response computations are required, as in, for example, Monte Carlo analysis of probabilistic system response. This paper describes two frameworks in which we have used ANNs to good advantage in the approximate simulation of the behavior of physical system response. These frameworks are the non-recurrent and recurrent frameworks. It is assumed in these applications that physical experiments have been performed to obtain data characterizing the behavior of a system, or that an accurate finite element model has been run to establish system response. The paper provides brief discussions on the operation of ANNs, the operation of two different types of mechanical systems, and approaches to the solution of some special problems that occur in connection with ANN simulation of physical system response. Numerical examples are presented to demonstrate system simulation with ANNs