Pork quality is an important issue for the whole meat chain, from producers, abattoirs, retailers through to costumers and is affected by a web of multi-factorial actions that occur throughout the pork production chain. A vast amount of information is available on how these diverse factors influence different pork quality traits. However, results derived from individual studies often vary and are in some cases even contradictory due to different experimental designs or different pork quality assessment techniques or protocols. Also, individual influencing factors are often studied in isolation, ignoring interacting effects. A suitable method is therefore required to account for a range of interacting factors, to combine the results from different experiments and to derive generic response-laws. The aim of this thesis was to use meta-analyses to produce quantitative, predictive models that describe how diverse factors affect pork quality over a range of experimental conditions.

Background: Multiple sclerosis (MS) is the most common cause of disability in young people and yet there are no interventions available which reliably alter disease progression. This is despite several decades of research using the most common animal model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE). There is now emerging evidence across the neurosciences to suggest that limited internal validity (measures to reduce bias) and external validity (e.g. using a clinically relevant animal model) may influence the translational success. Aim and objectives: To provide an unbiased summary of the scope of the literature on candidate drugs for MS tested in EAE to identify potential reasons for the failures to translate efficacy to clinical trials. My objectives were, across all of the identified publications, to: (1) describe the reporting of measures to reduce bias and to assess their impact on measures of drug efficacy; (2) assess the relationship between treatment related effects measured using different outcome measures; (3) assess the prevalence and impact of any publication bias; (4) compare findings from the above with another disease with limited translational success (Parkinson’s disease; PD). Methods: I used systematic searches of three online databases to identify relevant publications. Estimates of efficacy were extracted for neurobehavioural scores, inflammation, demyelination and axon loss. For PD experiments, we searched for dopamine agonists tested in animal models of PD with outcome assessed as change in neurobehavioural scores. I calculated normalised mean difference or standardised mean difference effect sizes and combined these in a meta-analysis using a random effects model. I used stratified meta-analysis or meta-regression to assess the extent to which different study design characteristics explained differences in reported efficacies. These characteristics included: measures to reduce bias (random allocation to group and blinded assessment of outcome), the animal species, sex, time of drug administration, route of drug administration and the number of animals per group. Publication bias was assessed using funnel plotting, Egger regression and “trim and fill”. Results: I identified 1464 publications reporting drugs tested in EAE. Reported study quality was poor: 11% reported random allocation to group, 17% reported blinded assessment of neurobehavioural outcomes, 28% reported blinded assessment of histological outcomes, and < 1% reported a sample size calculation. Estimates of efficacy measured as the reduction in inflammation were substantially higher in unblinded studies (47.1% reduction (95% CI 41.8-52.4)) versus blinded studies (33.1% (25.8-40.4). Moreover, the same finding was identified for 121 publications on dopamine agonists tested in experimental PD models where efficacy was measured as change in neurobehavioural outcomes. For EAE studies we were unable to include data from 631 publications describing original research. Usually this was because the publication did not include basic details such as the number of animals in each group (115 publications), the observed variance (592) or suitable control data (49). For each category of outcome I found evidence of a substantial publication bias. Interventions were most commonly administered on or before the induction of EAE with shorter times to treatment associated with higher estimates of efficacy for the reduction in mean severity scores (a neurobehavioural outcome). Treatment related effects were found to vary across different outcome measures with the largest effect being for the reduction in axon loss. Where neurobehavioural scores and axon loss were measured in the same cohort of animals, the concordance between efficacies in these increased with later times to treatment. Conclusions: In this, the largest systematic review and meta-analysis of animal studies in any domain, I have found that a large number of publications present incomplete data. In addition, measures to reduce bias are seldom reported, the lack of which is associated with overstatements of efficacy for both a measure of drug efficacy in EAE and experimental PD studies. Translational success may have also been affected by the majority of studies administering drugs on or before EAE induction which is of limited relevance in the clinical setting where patients do not present at that stage of disease. Moreover, my analysis of the relationship between outcome measures provides empirical evidence from systematically identified studies to suggest that targeting axon loss as later time points is most strongly associated with improvements in neurobehavioural scores. Therefore drugs which are successfully able to target axon loss at these time points may offer substantial hope for clinical success. Overall, improvements in the conduct and reporting of preclinical studies are likely to improve their utility, and the prospects for translational success. While my findings relate predominately to the animal modelling of MS and PD it is likely that they also hold for other animal research.

O crescente uso dos Sistemas de Informações Geográficas exige a reflexão sobre a qualidade dos dados georreferenciados, que é crucial para a qualidade do produto final destes sistemas. A qualidade destes dados é muitas vezes desconhecida ou simplesmente ignorada. Conhecendo-a, o usuário adquire subsídios para aceitá-los ou rejeitá-los em seus projetos. O objetivo deste trabalho é avaliar a qualidade de dados georreferenciados, através da análise de discrepância entre estes no meio digital e os obtidos a partir da tecnologia GPS. Efetuando-se estas análises, verifica-se a existência de erros sistemáticos na obtenção destes dados e analisa-se a precisão dos mesmos em relação aos padrões adotados, obtendo-se assim, um perfil que permite a avaliação qualitativa e quantitativa dos mesmos. / The crescent use of the Geographic Information System asks for a reflection about the quality of the georeferenced data, which is important for the quality of the final product of these systems. The quality of these data is many times unknown or simply ignored. Knowing this quality, the user acquires subsidies to accept or reject them in their projects. The aim of this work is to evaluate the quality of georeferenced data, through the analysis of discrepancy among these in the digital mean and those obtained from the GPS Technology. Performing these analysis it is verified the existence of systematical errors in the obtainment of these data and it is analyzed the precision of those in relation to the adopted standards, obtaining in this way, a feature that allows the qualitative and quantitative evaluation of these.

O crescente uso dos Sistemas de Informações Geográficas exige a reflexão sobre a qualidade dos dados georreferenciados, que é crucial para a qualidade do produto final destes sistemas. A qualidade destes dados é muitas vezes desconhecida ou simplesmente ignorada. Conhecendo-a, o usuário adquire subsídios para aceitá-los ou rejeitá-los em seus projetos. O objetivo deste trabalho é avaliar a qualidade de dados georreferenciados, através da análise de discrepância entre estes no meio digital e os obtidos a partir da tecnologia GPS. Efetuando-se estas análises, verifica-se a existência de erros sistemáticos na obtenção destes dados e analisa-se a precisão dos mesmos em relação aos padrões adotados, obtendo-se assim, um perfil que permite a avaliação qualitativa e quantitativa dos mesmos. / The crescent use of the Geographic Information System asks for a reflection about the quality of the georeferenced data, which is important for the quality of the final product of these systems. The quality of these data is many times unknown or simply ignored. Knowing this quality, the user acquires subsidies to accept or reject them in their projects. The aim of this work is to evaluate the quality of georeferenced data, through the analysis of discrepancy among these in the digital mean and those obtained from the GPS Technology. Performing these analysis it is verified the existence of systematical errors in the obtainment of these data and it is analyzed the precision of those in relation to the adopted standards, obtaining in this way, a feature that allows the qualitative and quantitative evaluation of these.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2003. / Härtill 4 uppsatser.

Thesis (M.S.)--Ohio University, August, 2009. / Title from PDF t.p. Includes bibliographical references.

The aim of this thesis is to propose a model that explains the relationship between customer satisfaction, retention and loyalty based on service quality attributes. The three elements of satisfaction, retention and loyalty towards products represent ongoing challenges for the corporate financial performance. Customer behaviour analysis (known as business intelligence or customer relationship management or customer experience management) has become a major factor in the corporate decision making and strategic planning processes. Prevailing logic dictates that by improving service attributes one should expect better customer satisfaction levels. Consequently, improved satisfaction levels should increase the probability of customer retention and degree of loyalty. Substantial research work has been dedicated to explain the importance of customer behaviour measurement for industry. However, there is little evidence that there has been an overall integrating empirical research that relates the three elements of satisfaction, retention and loyalty with respect to service quality attributes. Empirical data collected from the UK mobile telecommunication for this research shows that such an objective model that is capable of capturing this three dimensional relationship will contribute towards more robust decision making and better strategic planning. The proposed thesis extracts the data about key service attributes from a combination of literature review, surveys, and interviews from the UK mobile telecommunication industry. Responses were analysed using multiple regression, regression analysis with dummy variables, logistic regression, logistic regression with dummy variables and structural equation modelling (SEM) to test variables and their interrelationships. This study makes a step forward and contributes to the body of knowledge as it: (a) highlights the role of service attribute performance towards customer satisfaction, consequently identifies attributes that affect satisfaction and dissatisfaction of customers, (b) maps the relationship between attribute importance and attribute performance, (c) optimise resource allocation process using importance-performance analysis (IPA), (d) classifies customers with respect to the role and length of relationship they have with the company (switching probability), and (e) describes the interrelationship between customer satisfaction, retention and loyalty. The novelty of the research lies in: (a) establishment of a framework that links service attribute performance to customer satisfaction and then to customer future intentions (customer retention and customer loyalty), and (b) provision of a model that could assist key decision makers in prudent usage of resources for maximum profitability. This dissertation presents a novel approach methodology and modelling construct for customer behaviour analysis. For proof of concept it presents a case study in the mobile telecommunication industry. It is worth noting that in this research work Customer Retention is interpreted as probability of switching between service providers. Customer Loyalty is interpreted as referral (word-of-mouth) activity by existing customers.

The InfiniBand Architecture (IBA) network has been proposed as a new industrial standard with high-bandwidth and low-latency suitable for constructing high-performance interconnected cluster computing systems. This architecture replaces the traditional bus-based interconnection with a switch-based network for the server Input-Output (I/O) and inter-processor communications. The efficient Quality-of-Service (QoS) mechanism is fundamental to ensure the import at QoS metrics, such as maximum throughput and minimum latency, leaving aside other aspects like guarantee to reduce the delay, blocking probability, and mean queue length, etc. Performance modelling and analysis has been and continues to be of great theoretical and practical importance in the design and development of communication networks. This thesis aims to investigate efficient and cost-effective QoS mechanisms for performance analysis and improvement of InfiniBand networks in cluster-based computing systems. Firstly, a rate-based source-response link-by-link admission and congestion control function with improved Explicit Congestion Notification (ECN) packet marking scheme is developed. This function adopts the rate control to reduce congestion of multiple-class traffic. Secondly, a credit-based flow control scheme is presented to reduce the mean queue length, throughput and response time of the system. In order to evaluate the performance of this scheme, a new queueing network model is developed. Theoretical analysis and simulation experiments show that these two schemes are quite effective and suitable for InfiniBand networks. Finally, to obtain a thorough and deep understanding of the performance attributes of InfiniBand Architecture network, two efficient threshold function flow control mechanisms are proposed to enhance the QoS of InfiniBand networks; one is Entry Threshold that sets the threshold for each entry in the arbitration table, and other is Arrival Job Threshold that sets the threshold based on the number of jobs in each Virtual Lane. Furthermore, the principle of Maximum Entropy is adopted to analyse these two new mechanisms with the Generalized Exponential (GE)-Type distribution for modelling the inter-arrival times and service times of the input traffic. Extensive simulation experiments are conducted to validate the accuracy of the analytical models.

Pagrindinis geriamojo vandens šaltinis Lietuvoje – požeminis vanduo. Geros kokybės geriamasis vanduo yra svarbus veiksnys kiekvieno žmogaus gyvenime. Šio darbo tikslas – išanalizuoti Kelmės rajono vandenviečių tiekiamo geriamojo vandens kokybę ir jo tinkamumą vartoti 2004–2010 metais. Šiame darbe nagrinėjami Kelmės rajono vandenviečių tiekiamo geriamojo vandens toksiniai (cheminiai) (fluoridai, nitratai, nitritai), indikatoriniai (bendroji geležis, manganas, permanganato indeksas) ir mikrobiologiniai (kolonijas sudarantys vienetai, žarniniai enterokokai, žarninės lazdelės (E. coli)) kokybės rodikliai 2004–2010 m. laikotarpiu. Kai kurių analizuojamų vandenviečių vandens kokybė neatitinka normų dėl per didelio fluoridų bei bendrosios geležies kiekio. Nustatyta fluoridų koncentracija 2004–2010 metais DLK (DLK=1,5 mg/l) viršijo Gailių, Kelmės, Kukečių, Šedbarų ir Verpenos vandenvietėse. Bendrosios geležies koncentracija DLK (DLK=0,2) viršijo Budraičių, Gailių, Kukečių, Liolių, Maironių, Pagryžuvio, Šedbarų, Tytuvėnų vandenviečių vandenyje. Mangano koncentracija DLK (DLK=0,05 mg/l) viršijo tik Gailių vandenvietės vandenyje. Nitratų ir nitritų vidutinė koncentracija analizuojamu laikotarpiu DLK neviršija nei vienoje vandenvietėje. Analizuojamu 2004–2010 metų laikotarpiu vidutinės permanganato indekso vertės Kelmės rajono vandenvietėse DLK neviršijo (DLK=5 mg/l). Vandens kokybė Pagal mikrobiologinius rodiklius analizuojamose Kelmės rajono neatitiko reikalavimų pagal KSV... [toliau žr. visą tekstą] / The main source of drinking water in Lithuania is the groundwater. Quality of drinking water and harmful substances in drinking water is an important factor in everyone‘s life. The aim of this Diploma paper – to analyze quality of drinking water in watering–places in Kelmė district and its suitability for consumption in 2004–2010. In many watering–places of Kelmė district in drinking water was found to much fluoride and iron. Average concentration of fluoride in 2004–2010 exceeded MAC (Maximum Acceptable Concentration) in Gailiai, Kelmė, Kukečiai, Šedbarai and Verpena watering–places. Average concentration of iron exceeded MAC in Budraičiai, Gailiai, Kukečiai, Lioliai, Maironiai, Pagryžuvys, Šedbarai, Tytuvėnai watering–places. Average concentration of manganese in 2004 – 2010 exceeded MAC in Gailiai watering–place. Average concentration of organic matter (permanganate index), nitrate and nitrite did not exceeded MAC. In some watering–places was found temporary microbiological pollution. In water found colony–forming units. The survey in Kelmė district towns showed that most respondents water quality regarded as good. However, information about the quality of drinking water and its changes is inadequate. Sediments are the worst characteristic of drinking water in Kelmė district watering–places. Concentration of nitrate in Kelmė district wells in most cases exceeded MAC. In many wells of Kelmė district water was very hard (°d–>21) and hard (°d–>14).

Fermentation processes play an integral role in the manufacture of pharmaceutical products. The Quality by Design initiative, combined with Process Analytical Technologies, aims to facilitate the consistent production of high quality products in the most efficient and economical way. The ability to estimate and control product quality from these processes is essential in achieving this aim. Large historical datasets are commonplace in the pharmaceutical industry and multivariate methods based on PCA and PLS have been successfully used in a wide range of applications to extract useful information from such datasets. This thesis has focused on the development and application of novel multivariate methods to the estimation and control of product quality from a number of processes. The document is divided into four main categories. Firstly, the related literature and inherent mathematical techniques are summarised. Following this, the three main technical areas of work are presented. The first of these relates to the development of a novel method for estimating the quality of products from a proprietary process using PCA. The ability to estimate product quality is useful for identifying production steps that are potentially problematic and also increases process efficiency by ensuring that any defective products are detected before they undergo any further processing. The proposed method is simple and robust and has been applied to two separate case studies, the results of which demonstrate the efficacy of the technique. The second area of work concentrates on the development of a novel method of identifying the operational phases of batch fermentation processes and is based on PCA and associated statistics. Knowledge of the operational phases of a process can be beneficial from a monitoring and control perspective and allows a process to be divided into phases that can be approximated by a linear model. The devised methodology is applied to two separate fermentation processes and results show the capability of the proposed method. The third area of work focuses on undertaking a performance evaluation of two multivariate algorithms, PLS and EPLS, in controlling the end-point product yield of fermentation processes. Control of end-point product quality is of crucial importance in many manufacturing industries, such as the pharmaceutical industry. Developing a controller based on historical and identification process data is attractive due to the simplicity of modelling and the increasing availability of process data. The methodology is applied to two case studies and performance evaluated. From both a prediction and control perspective, it is seen that EPLS outperforms PLS, which is important if modelling data is limited.