No description available.

yes / Background The roles of diffusely-adherent Escherichia coli (DAEC) and enteroaggregative E. coli (EAEC) in disease are not well understood, in part because of the limitations of diagnostic tests for each of these categories of diarrhoea-causing E. coli. A HEp-2 adherence assay is the Gold Standard for detecting both EAEC and DAEC but DNA probes with limited sensitivity are also employed. Results We demonstrate that the daaC probe, conventionally used to detect DAEC, cross-reacts with a subset of strains belonging to the EAEC category. The cross hybridization is due to 84% identity, at the nucleotide level, between the daaC locus and the aggregative adherence fimbriae II cluster gene, aafC, present in some EAEC strains. Because aaf-positive EAEC show a better association with diarrhoea than other EAEC, this specific cross-hybridization may have contributed to an over-estimation of the association of daaC with disease in some studies. We have developed a discriminatory PCR-RFLP protocol to delineate EAEC strains detected by the daaC probe in molecular epidemiological studies. Conclusions A PCR-RFLP protocol described herein can be used to identify aaf-positive EAEC and daaC-positive DAEC and to delineate these two types of diarrhoeagenic E. coli, which both react with the daaC probe. This should help to improve current understanding and future investigations of DAEC and EAEC epidemiology. / Food Standards Agency

No description available.

Test and Diagnosis are critical areas in semiconductor manufacturing. Every chip manufactured using a new or premature technology or process needs to be tested for manufacturing defects to ensure defective chips are not sold to the customer. Conventionally, test is done by mounting the chip on an Automated Test Equipment (ATE) and applying test patterns to test for different faults. With shrinking feature sizes, the complexity of the circuits on chip is increasing, which in turn increases the number of test patterns needed to test the chip comprehensively. This increases the test application time which further increases the cost of test, ultimately leading to increase in the cost per device. Furthermore, chips that fail during test need to be diagnosed to determine the cause of the failure so that the manufacturing process can be improved to increase the yield. With increase in the size and complexity of the circuits, diagnosis is becoming an even more challenging and time consuming process. Fast diagnosis of failing chips can help in reducing the ramp-up to the high volume manufacturing stage and thus reduce the time to market. To reduce the time needed for diagnosis, efficient diagnostic patterns have to be generated that can distinguish between several faults. However, in order to reduce the test application time, the total number of patterns should be minimized. We propose a technique for generating diagnostic patterns that are inherently compact. Experimental results show up to 73% reduction in the number of diagnostic patterns needed to distinguish all faults. Logic Built-in Self-Test (LBIST) is an alternative methodology for testing, wherein all components needed to test the chip are on the chip itself. This eliminates the need of expensive ATEs and allows for at-speed testing of chips. However, there is hardware overhead incurred in storing deterministic test patterns on chip and failing chips are hard to diagnose in this LBIST architecture due to limited observability. We propose a technique to reduce the number of patterns needed to be stored on chip and thus reduce the hardware overhead. We also propose a new LBIST architecture which increases the diagnosability in LBIST with a minimal hardware overhead. These two techniques overcome the disadvantages of LBIST and can make LBIST more popular solution for testing of chips. Modern designs may contain a large number of small embedded memories. Memory Built-in Self-Test (MBIST) is the conventional technique of testing memories, but it incurs hardware overhead. Using MBIST for small embedded memories is impractical as the hardware overhead would be significantly high. Test generation for such circuits is difficult because the fault effect needs to be propagated through the memory. We propose a new technique for testing of circuits with embedded memories. By using SMT solver, we model memory at a high level of abstraction using theory of array, while keeping the surrounding logic at gate level. This effectively converts the test generation problem into a combinational test generation problem and make test generation easier than the conventional techniques. / Ph. D.

The adjacent box beam bridges (ABBB) are considered as an ideal solution for short to medium span bridges and for routes with low to medium traffic volumes. The ABBB system has been utilized and is popular in several states in the United States. However, this bridge system has long term durability issues caused by shear key failure and reflective cracking in the topping. The means and methods to alleviate the problems in connections between members of the ABBB were researched and the development of new connection details was pursued. Diagnostic tests to study the in-service behavior of ABBBs was performed. Two bridges with varying magnitude of joint deterioration were investigated. Both bridges were instrumented extensively and were subjected to known loads in the form of tandem trucks. The response of these bridges was studied and conclusions were made about the state of the bridges and the behavior after shear key failure. A finite element (FE) model of one of the tested bridges was developed to study the response of an ABBB with sound joints. The results of the finite element analysis (FEA) were compared with the results of the bridge diagnostic test. Conclusions about the FE model were made on the basis of this comparison. Another FE model, referred as the full scale bridge (FSB) was developed. The FSB model was used to simulate the behavior of an ABBB with the proposed connection details. This FSB model was subjected to design truck loads and the response was studied. The behavior of FSB model was replicated through a three beam sub-assembly that was supported on elastic supports. The stiffness of the elastic supports was calibrated such that the state of stress in the joints and the relative displacements between adjacent box beams in the sub-assemblage matched those in the FSB. The three beam sub-assembly was constructed with the proposed connection details. Two new connection details were proposed in this research. A Kevlar and epoxy connection and a spliced connection with fiber reinforced self-consolidating concrete are proposed. A total of six specimens, with different connection details, were constructed and tested for strength and durability in the laboratory. The behavior of the proposed connections and the connection materials were studied in detail. Additional FEA was performed to study the effect of shrinkage and temperature on the proposed connection details. / Ph. D.

Chocolate is a food that is craved by many in the world and healthy chocolates have become a current topic in the healthy eating trend. The healthiness of a chocolate depends mainly on the polyphenol, fat and sugar contents. Although the literature serves several interventions to reduce the fat content and total calorie content of chocolates, it does not provide many interventions that consider both improving the polyphenol and reducing the fat content simultaneously. Considering this gap in the literature, this research project sought to develop a chocolate that is both low in fat and high in polyphenol content, without sacrificing the taste that consumers would expect in a good dark chocolate. The research resulted in three chocolate formulas that consists of 60% cocoa and 30% fat (formula A, formula B and formula C). They differed from each other in the polyphenol content due to the changes in the cocoa powder type and the presence or absence of freeze-dried blueberry powder. Formula A and formula B mainly differed in the percentage of each type of cocoa powder, both alkalized and non- alkalized. Formula C differed from the other two formulas because there was no freeze-dried blueberry powder. The resulted chocolates were evaluated for the sensory characteristics using paired preference tests and consumer-oriented attribute diagnostic tests (color, flavor, melting properties, overall preference, likelihood to buy). They were analyzed for polyphenol content using Folin-Ciocalteu assay. The chocolates were compared with a well-established commercial chocolate (formula D) of a 60% cocoa. Sensory evaluation tests revealed that formula C was superior and comparable to the commercial chocolate D in all the tested attributes except for color. Polyphenol analysis confirmed that all three developed formulas had a higher polyphenol estimate than formula D. Consumers preferred to buy each chocolate type regardless of the differences in their preference for the other attributes, if the chocolates were known to be healthier. Formula C was found to be the best prototype formula among the developed formulas and it can further be developed to enhance the color and other attributes in future work.

Empirical likelihood, which was pioneered by Thomas and Grunkemeier (1975) and Owen (1988), is a powerful nonparametric method of statistical inference that has been widely used in the statistical literature. In this thesis, we investigate the merits of empirical likelihood for various problems arising in ratio estimation. First, motivated by the smooth empirical likelihood (SEL) approach proposed by Zhou & Jing (2003), we develop empirical likelihood estimators for diagnostic test likelihood ratios (DLRs), and derive the asymptotic distributions for suitable likelihood ratio statistics under certain regularity conditions. To skirt the bandwidth selection problem that arises in smooth estimation, we propose an empirical likelihood estimator for the same DLRs that is based on non-smooth estimating equations (NEL). Via simulation studies, we compare the statistical properties of these empirical likelihood estimators (SEL, NEL) to certain natural competitors, and identify situations in which SEL and NEL provide superior estimation capabilities. Next, we focus on deriving an empirical likelihood estimator of a baseline cumulative hazard ratio with respect to covariate adjustments under two nonproportional hazard model assumptions. Under typical regularity conditions, we show that suitable empirical likelihood ratio statistics each converge in distribution to a 2 random variable. Through simulation studies, we investigate the advantages of this empirical likelihood approach compared to use of the usual normal approximation. Two examples from previously published clinical studies illustrate the use of the empirical likelihood methods we have described. Empirical likelihood has obvious appeal in deriving point and interval estimators for time-to-event data. However, when we use this method and its asymptotic critical value to construct simultaneous confidence bands for survival or cumulative hazard functions, it typically necessitates very large sample sizes to achieve reliable coverage accuracy. We propose using a bootstrap method to recalibrate the critical value of the sampling distribution of the sample log-likelihood ratios. Via simulation studies, we compare our EL-based bootstrap estimator for the survival function with EL-HW and EL-EP bands proposed by Hollander et al. (1997) and apply this method to obtain a simultaneous confidence band for the cumulative hazard ratios in the two clinical studies that we mentioned above. While copulas have been a popular statistical tool for modeling dependent data in recent years, selecting a parametric copula is a nontrivial task that may lead to model misspecification because different copula families involve different correlation structures. This observation motivates us to use empirical likelihood to estimate a copula nonparametrically. With this EL-based estimator of a copula, we derive a goodness-of-fit test for assessing a specific parametric copula model. By means of simulations, we demonstrate the merits of our EL-based testing procedure. We demonstrate this method using the data from Wieand et al. (1989). In the final chapter of the thesis, we provide a brief introduction to several areas for future research involving the empirical likelihood approach.

The purpose of this study was to investigate the effect of gender and reasoning ability on the 8th grade students&rsquo / understanding of ecological concepts and attitude toward science. All 8th grade students from public elementary school in Tosya participated in the study. Students&rsquo / understanding, attitude toward science and reasoning ability were also measured by means of the Test of Ecology Concept (TEC), the Attitude Scale toward Science (ASTS) and the Test of Logical Thinking (TOLT) respectively. In order to investigate students&rsquo / understanding deeply, interview was conducted. Results of the TEC and interview show that students have many misconceptions concerning ecosystem, population, community, decomposers, food chain, food web, energy pyramid and energy flow. Students&rsquo / understanding for the first tier (M= 55.8), combination of first two tiers (M= 27) and combination of all three tiers (M= 21.2) were calculated according to TEC results. Multivariate Analysis of Covariance (MANCOVA) conducted to determine the effect of gender on students&rsquo / understanding of ecological concepts and attitude towards science when reasoning ability was controlled. The results indicated that there was significant gender difference in favor of girls with respect to students&rsquo / understanding of ecological concepts and attitude towards science when reasoning ability was controlled (Wilks&rsquo / Lambda=0.97 / p=.00).

Introduction: Ensuring universal access to primary health care (PHC) is a key component of the Ethiopian nationalhealth policy. The policy also emphasises promoting and enhancing national self-reliance in health development bymobilizing and efficiently utilizing resources including community participation. To this end, the government introducedthe accelerated expansion of the PHC strategy through a comprehensive health extension programme (HEP). HEP is afamily and community-based health care delivery system institutionalised at health post level which combines carefullyselected high impact promotive, preventive and basic curative interventions. All HEP interventions are promotive and preventive except the malaria intervention which, in addition, incorporates a curative service. In the country, malaria is a leading disease. Unlike most Sub-Saharan African countries where P. falciparum accounts for almost all malaria infections, in Ethiopia both P. falciparum and P. vivax are co-dominant. Considering this peculiar epidemiological nature, the national guideline recommends alternative diagnosis and treatment strategies. Rationale: The lack of adequate resources and the efficiency with which available resources are being utilised are the main challenges in any health care setting. Therefore, if the HEP which consumes consideral amount of resource desires to reach its intended goal, monitoring and improving its efficiency is of great public heath importance. HEP has been successful in improving access to PHC including the malaria diagnosis and treatment service. Though this is a crucial measure, its quality ought to be considered. For the malaria curative service, studying the cost-effectiveness of the available strategy and patients’ adherence to the treatment regimen can be considered as proxy measures of quality for which local evidence is lacking. However, none of the existing studies in this field of research has addressed the Ethiopian malaria epidemiological context and its diagnosis and treatment guideline. In Tigray, for more than two decades, access to malaria early diagnosis and prompt treatment was facilitated by volunteer community healthworkers (CHWs). However, with the introduction of artemether-lumefantrine (AL) the service was compromised mainly for reasons of cost, safety and logistic. Therefore, it was important to explore the feasibility and the impact of community deployment of AL with rapid diagnostic tests (RDTs). The aim: to explore the overall performance of HEP and particularly the access to and quality of malaria early diagnosis and prompt treatment in the Tigray region of Ethiopia. Methods: Different study designs and populations were used for each of the four specific objectives. Data envelop analysis (DEA) was applied to assess the HEP efficiency. For this, register data for the output variables and primary data for the input and the environmental factors were collected. A health provider perspective cost-effectiveness analysis was used to determine which among the currently available diagnostic and treatment strategies is best for the country. Effectiveness data were generated from a stratified cross-sectional survey and secondary data were used to calculate the cost. For measuring adherence to the six-dose AL regimen, an assessment questionnaire and pill count was employed at patients´ home. To determine whether deploying AL with RDT at community level was feasible and effective, a number of designs were used: longitudinal follow-up, cross-sectional surveys, cost analysis, verbal autopsyquestionnaires and focal group discussions. Main findings: More than three-quarters of the health posts were found to be technically inefficient with an average score of 42%, which implies potentially they could improve their efficiency by 58%. Scale of operation was not a cause of inefficiency. None of the considered environmental factors was associated with efficiency. The Parascreen-based strategy (multispecies RDT-BS) was found to be the most cost-effective strategy, which allowed treating correctly an additional 65% of patients with less cost than the paracheck-BS. Presumptive-BS was highly dominated. Among P.falciparum positive patients to whom AL was prescribed, more than a quarter did not finish their treatment. The main reasons for interrupting the dose were ‘too many tablets’ and ‘felt better before finishing the dose’. The ownership of aradio, the belief that malaria cannot be treated traditionally and a delay of more than one day in seeking treatment after the onset of fever were significantly associated with being adherent. Deploying AL with RDT at community level was demonstrated to be effective and feasible. In the intervention district, almost 60% of suspected cases were managed by CHWs. Malaria transmission was lower at least threefold and malaria mortality risk by around 40% compared to the control district. The use of RDTs reduced cost and possibly the risk of drug resistance development. Conclusion: Though improving access to health care is important, it should be considered a means, not an end. Themore accessible a system is the more people could utilise it to improve their health. Thus, ensuring the access obtainedthrough HEP is maintained, its quality is improved and efficiently utilised to its optimal productivity level is a necessarytask. The DEA study revealed a high level of inefficiency where majority of the health posts needed improvement.This thesis also found parascreen-BS to be the most cost-effective strategy and that there is no epidemiological andeconomical contextual justification to keep both, the presumptive-BS and the RDT-BS specific only to P.falciparum.The high poor adherence levels raises great concern as it leads to recurrent malaria attacks of the patient, speed upthe development and spread of drug resistance strains and reduces the effect of the drug on the transmission. Therefore,providing effective drug alone is not sufficient; assessing and monitoring adherence to the treatment is by faressential. Deployment of AL with RDT through a community-based service has shown an enormous impact in termsof cost, transmission, morbidity and mortality. However, it is worth noting that this results came from an area wherea community-based service has been involved in the PHC system for more than three decades.

Empirical likelihood, which was pioneered by Thomas and Grunkemeier (1975) and Owen (1988), is a powerful nonparametric method of statistical inference that has been widely used in the statistical literature. In this thesis, we investigate the merits of empirical likelihood for various problems arising in ratio estimation. First, motivated by the smooth empirical likelihood (SEL) approach proposed by Zhou & Jing (2003), we develop empirical likelihood estimators for diagnostic test likelihood ratios (DLRs), and derive the asymptotic distributions for suitable likelihood ratio statistics under certain regularity conditions. To skirt the bandwidth selection problem that arises in smooth estimation, we propose an empirical likelihood estimator for the same DLRs that is based on non-smooth estimating equations (NEL). Via simulation studies, we compare the statistical properties of these empirical likelihood estimators (SEL, NEL) to certain natural competitors, and identify situations in which SEL and NEL provide superior estimation capabilities. Next, we focus on deriving an empirical likelihood estimator of a baseline cumulative hazard ratio with respect to covariate adjustments under two nonproportional hazard model assumptions. Under typical regularity conditions, we show that suitable empirical likelihood ratio statistics each converge in distribution to a 2 random variable. Through simulation studies, we investigate the advantages of this empirical likelihood approach compared to use of the usual normal approximation. Two examples from previously published clinical studies illustrate the use of the empirical likelihood methods we have described. Empirical likelihood has obvious appeal in deriving point and interval estimators for time-to-event data. However, when we use this method and its asymptotic critical value to construct simultaneous confidence bands for survival or cumulative hazard functions, it typically necessitates very large sample sizes to achieve reliable coverage accuracy. We propose using a bootstrap method to recalibrate the critical value of the sampling distribution of the sample log-likelihood ratios. Via simulation studies, we compare our EL-based bootstrap estimator for the survival function with EL-HW and EL-EP bands proposed by Hollander et al. (1997) and apply this method to obtain a simultaneous confidence band for the cumulative hazard ratios in the two clinical studies that we mentioned above. While copulas have been a popular statistical tool for modeling dependent data in recent years, selecting a parametric copula is a nontrivial task that may lead to model misspecification because different copula families involve different correlation structures. This observation motivates us to use empirical likelihood to estimate a copula nonparametrically. With this EL-based estimator of a copula, we derive a goodness-of-fit test for assessing a specific parametric copula model. By means of simulations, we demonstrate the merits of our EL-based testing procedure. We demonstrate this method using the data from Wieand et al. (1989). In the final chapter of the thesis, we provide a brief introduction to several areas for future research involving the empirical likelihood approach.