This study examined the prevalence of psychiatric disorders and assessed factors that are assumed to be related to recognition of this morbidity among clinical patients. A total of 794 patients aged 18 years or older participated in the study. Using an Arabic-translated version of the General Health Questionnaire (GHQ-28), the prevalence of psychiatric morbidity was found to be 61%. The highest prevalence rates of psychiatric disorders were found in the 40 years and older age group, in female subjects, in uneducated and highly educated groups, in unemployed individuals, and in patients who were perceived to have 'fair' or 'poor' physical health. Multiple logistic regression analysis revealed that unemployment and perceived severity of physical illness were positively correlated with psychiatric disorders, but no significant correlation was found with sex, age or level of education. The physicians in the present study were able to detect morbidity in only 24% of the patients. Among patients with psychiatric disorders, recognition of this morbidity was significantly greater in women, in patients who had consulted with their family doctors, in patients previously known to their physicians, and in patients with mild physical illness than in their counterparts. The most common lines of psychiatric management used in this study were referral to psychiatrists (47%) and psychotropic medication (16%).

Locating the critical slip surface and the associated minimum factor of safety are two complementary parts in a slope stability analysis. A large number of computer programs exist to solve slope stability problems. Most of these programs, however, have used inefficient and unreliable search procedures to locate the global minimum factor of safety. This paper presents an efficient and reliable method to determine the global minimum factor of safety coupled with a modified version of the Monte Carlo technique. Examples are presented to illustrate the reliability of the proposed method.Key words: factor of safety, method of search, critical slip surface, circular, global, Monte Carlo.

No abstract

Based on both field data collected from engineering literature and measurements made using model piles, a correlation for the residual pressure at the pile tip point is presented. The resulting correlation suggested that pile flexibility is a key parameter controlling the magnitude of the residual point pressure, qres. The calculated residual point pressure values for the database piles using the developed correlation were compared with the measured values and with those calculated using Briaud and Tucker's (1984) method. The comparison indicated that predictions made using the proposed method were closer to the measurements than those obtained using Briaud and Tucker's (1984) method. In the present study, the residual load distribution along the lower portion of the pile (the bottom 10m) was modeled as a parabola. In the upper portion of the pile, and upon the removal of the driving force, it is assumed that the upward movement of the pile is enough to reverse the direction of the unit shaft resistance from an upward direction during driving to a downward direction, with a magnitude controlled by pile flexibility as well as the available shaft friction along the upper portion of the pile. As a consequence of this approach of modeling residual load distribution, the results indicate that residual load distribution peaks at a distance (less than 0.3L) above the pile tip point. This distance (measured from the pile tip) decreases with increasing pile flexibility, and for flexible pile, residual shear stresses may act in the downward direction all the way down to the pile tip. Also, the method of analysis adopted in this paper indicates that in some cases the magnitude of the peak residual load may exceed 50% of the measured ultimate uplift load. This magnitude is significant and leads to the prudent conclusion that any design method for an axially loaded pile in sand using pile load test data as a database should consider the existence of residual loads when pile load test data are interpreted.

No abstract