Cost models for engineering services

This thesis describes the procedure and results from four years research undertaken through the IHD (Interdisciplinary Higher Degrees) Scheme at Aston University in Birmingham, sponsored by the SERC (Science and Engineering Research Council) and Monk Dunstone Associates, Chartered Quantity Surveyors. A stochastic networking technique VERT (Venture Evaluation and Review Technique) was used to model the pre-tender costs of public health, heating ventilating, air-conditioning, fire protection, lifts and electrical installations within office developments. The model enabled the quantity surveyor to analyse, manipulate and explore complex scenarios which previously had defied ready mathematical analysis. The process involved the examination of historical material costs, labour factors and design performance data. Components and installation types were defined and formatted. Data was updated and adjusted using mechanical and electrical pre-tender cost indices and location, selection of contractor, contract sum, height and site condition factors. Ranges of cost, time and performance data were represented by probability density functions and defined by constant, uniform, normal and beta distributions. These variables and a network of the interrelationships between services components provided the framework for analysis. The VERT program, in this particular study, relied upon Monte Carlo simulation to model the uncertainties associated with pre-tender estimates of all possible installations. The computer generated output in the form of relative and cumulative frequency distributions of current element and total services costs, critical path analyses and details of statistical parameters. From this data alternative design solutions were compared, the degree of risk associated with estimates was determined, heuristics were tested and redeveloped, and cost significant items were isolated for closer examination. The resultant models successfully combined cost, time and performance factors and provided the quantity surveyor with an appreciation of the cost ranges associated with the various engineering services design options.

Purification and characterisation of two cancer cachexia factors

Cachexia is a wasting phenomenon that often accompanies malignant disease. Its manifestation is associated with shortened survival and reduced responsiveness to anti-tumour therapy and as yet there is no established, effective amelioratory treatment. The MAC 16 model of cancer cachexia has been shown by many studies to closely mirror the human condition. Thus, cachexia is mediated by the presence of a small, slow-growing solid tumour that is mainly resistant to chemotherapy. In addition, the condition is largely attributable to aberrations in metabolic processes, while weight loss due to anorexia is negligible. Cachexia induced by the MAC 16 tumour, has been shown to be mediated by the production of tumour-derived circulatory catabolic factors, and the further elucidation of the structure of these molecules contributes towards the main content of this report. Thus, a factor with in vitro lipid-mobilising activity has been purified from the MAC 16 tumour, and has been found to have similarities to tumour-derived lipolytic factors published to date. Further work demonstrated that this factor was also purifiable from the urine of a patient with pancreatic cancer, and that it was capable of inducing weight loss in non tumour-bearing mice. Sequence analysis of the homogeneous material revealed an identity to Zn-α-2-glycoprotein, the significance of which is discussed. An additional factor, first detected as a result of its specific reactivity with a monoclonal antibody produced by fusion of splenocytes from MAC 16 tumour-bearing mice with mouse BALB/c myeloma cells, was identified as a co-purificant during studies to isolate the lipolytic factor. Subsequent purification of this material to homogeneity resulted in the determination of 18 of the N-terminal amino acids and revealed the highly glycosylated nature of its structure. Thus, this material (P24) was found to have an apparent molecular mass of 24kD of which 2kD was due to protein, while the remainder (92%) was due to the presence of carbohydrate groups. Sequence analysis of the protein core of P24 revealed an identity with Streptococcal pre-absorbing antigen (PA-Ag) in 11 of the amino acids, and the significance of this is discussed. P24 was shown to induce muscle protein breakdown in vitro and to induce cachexia in vivo, as measured by the depletion of fat (29%) and muscle (14%) tissue in the absence of a reduction of food and water intake. Further studies revealed that the same material was purifiable from the urine of patients with pancreatic cancer and was found to be detectable in the urine of cancer patients with weight loss greater than l.Skg/month. Thus, cachexia induced by the MAC 16 tumour in mice and by malignant disease in humans may be induced by similar mediators. Attempts to isolate the gene for P24 using information provided by the N-terminal protein sequence were unsuccessful. This was probably due to the low abundance o[ the material, as determined by protein purification studies; and the nature of the amino acids of the N-terminal sequence, which conferred a high degree o[ degeneracy to the oligonucleotides designed for the polymerase chain reaction.

Looking under the bonnet:factors affecting student adoption of e-learning systems in Jordan

The primary questions addressed in this paper are the following: what are the factors that affect students’ adoption of an e-learning system and what are the relationships among these factors? This paper investigates and identifies some of the major factors affecting students’ adoption of an e-learning system in a university in Jordan. E-learning adoption is approached from the information systems acceptance point of view. This suggests that a prior condition for learning effectively using e-learning systems is that students must actually use them. Thus, a greater knowledge of the factors that affect IT adoption and their interrelationships is a pre-cursor to a better understanding of student acceptance of e-learning systems. In turn, this will help and guide those who develop, implement, and deliver e-learning systems. In this study, an extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The TAM was populated using data gathered from a survey of 486 undergraduate students using the Moodle based e-learning system at the Arab Open University. The model was estimated using Structural Equation Modelling (SEM). A path model was developed to analyze the relationships between the factors to explain students’ adoption of the e-learning system. Whilst findings support existing literature about prior experience affecting perceptions, they also point to surprising group effects, which may merit future exploration.

Factors associated with high anticholinergic burden in aging adults with intellectual disabilities:a cross-sectional study

Background: Anticholinergic (AC) medications are associated with cognitive and functional decline in older people, with risk of adverse outcomes increasing with increasing AC exposure. Older people with intellectual disabilities are at increased risk of high AC exposure owing to higher prevalence of multimorbidity, particularly psychiatric morbidities. Objectives: The aims of this study were to determine individual’s AC exposure using the AC cognitive burden (ACB) scale, identify therapeutic classes contributing to burden and determine clinical and demographic factors associated with two levels of AC exposure (ACB score 1–4, ACB 5+). Methods: Cross-sectional (self-report/proxy report)medication data were drawn from Wave 1 of the Intellectual Disability Supplement to the Irish Longitudinal Study on Ageing, a study on ageing of 753nationally representative people with ID aged over40 randomly selected from the National Intellectual Disability Database. Medication data were available for 736 (98%). Each individual’s cumulative AC exposure was calculated using the ACB. Multinomiallogistic regression was performed identifying clinical and demographic factors associated with ACB score1–4, and ACB 5+. Results: In the eligible population of 736 participants(mean (±SD) age 54.1 (±8.8) years,55% female), 522(70.9%) were exposed to an ACB medicine (ACB 1+); 214 (29%) had an ACB score of 5+; mean total ACB score= 4.5 (±3.0). Antipsychotics accounted for35.6% of the cumulative ACB score. Age over 65yearswas associated with increased likelihood of both levels of AC exposure (ACB 1–4—adjusted OR 3.28; 95%CI 1.49–7.25, ACB 5+—adjusted OR 3.08; 95%CI1.21–7.63) and having a mental health condition(ACB 1–4—adjusted OR 9.79; 95%CI 5.63–17.02, ACB 5+—adjusted OR 23.74; 95%CI 12.29–45.83). Conclusions: Using a simple cumulative measure proved an effective means to capture total burden and established that AC exposure was high and associated with older age and mental health morbidity. This highlights need for comprehensive medication reviews for older people with intellectual disabilities.