Spigelian hernia

Spigelian hernia is very rare. Together with the direct inguinal hernia which emerges between the inferior epigastric artery and the edge of the rectus muscle, it is more frequent. Congenital openings in the aponeurosis of the transverse muscle permit the hernia either above or under the inferior epigastric artery. Due to neglect of this type of hernia and absence of herniation, the diagnosis can be difficult. Complaints are often uncharacteristic. Surgical intervention is indicated.     

Sterilization of the operating microscope

Sterilization of the operating microscope and its equipment with formaldehyde (10 g for 10 hours) in a specially developed container provides sterility and ideal storage, and secures immediate availability in daily operating theatre practice.     

Differences in tissue fatty acids and cholesterol of swine from different genetic backgrounds

A review of 1,000 consecutive coronary angiograms, most of them performed for evaluation of angina pectoris, yielded 9 examples of congenital anomalies of the coronary arteries. In 2 cases the angina may have been due to malposition of the left coronary artery or one of its branches. There were 2 cases of aberrant origin of the circumflex artery from the right coronary artery, 2 cases of aberrant left anterior descending artery, 3 cases in which all three major coronary branches arose from the right aortic sinus, and 2 cases of coronary artery fistulas. Malposition of the coronary artery should be considered as a possible cause of angina.     

Measurement of Spectral Properties for a Non-Gaussian Process Model of EEG

Abstract

The electrical activity of the brain produces a signal which in general is a non-stationary process. Nevertheless stationary Gaussian models are used successfully to characterize the signal in short sections without obvious non-stationarities. However, it has been observed that the characterization of the signal differs more between separate sections than may be explained using a stationary Gaussian model. In this paper a stationary but non-Gaussian process model of EEG is developed and analyzed. It is shown that for a given measurement time estimates of the autocorrelation function and the power spectrum are less accurate for this process than for the corresponding process in a Gaussian model. Upper limits for the increase in the variance of the estimates are given.

The process has been simulated on a digital computer and the experimental results verify the theoretical properties.     

Systems Identification by Quasilinearization and by Evolutionary Programming

Abstract

Two new methods for obtaining the values of the coefficients in the differential equations describing the dynamics of a system are developed. The first method is based on a quasilinearization procedure and is applicable in parameter identification problems where the plant is modeled by a system of linear differential equations, and noisy measurements of state and control variables are available. Computationally, this method is equivalent to a modification of the classical Newton-Raphson method. The second, a “directed random search” method, is based on a concept called evolutionary programming, and is also applicable for nonlinear problems.

Using recorded flight test data of an experimental aircraft, the two methods are compared for accuracy and computational efficiency.     

Organizations as self-organizing and sustaining systems: a complex and autopoietic systems perspective

Many alternative theories about organization exist. Despite this, or perhaps because of it, adequate explanation of the relationship between macro and micro processes of organization, and organizational dynamics remains elusive. In the recent past there has been growing interest in two areas of systems science that offer a different basis for understanding the generative and dynamic qualities of organizations. These are autopoietic theory and complex adaptive systems theory. In this paper, we outline a theory of organization built on a synthesis of these two theoretical strands. It is argued that the approach provides an improved framework for understanding the nature and dynamics of organizational phenomena, and as such a more rigorous basis upon which to base future organizational research.