Development and use of a multiplex real-time quantitative polymerase chain reaction assay for detection and differentiation of Porcine circovirus-2 genotypes 2a and 2b in an epidemiological survey.

By the end of 2004, the Canadian swine population had experienced a severe 2 increase in the incidence of Porcine circovirus-associated disease (PCVAD), a problem that was 3 associated with the emergence of a new Porcine circovirus-2 genotype (PCV-2b), previously 4 unrecovered in North America. Thus it became important to develop a diagnostic tool that could 5 differentiate between the old and new circulating genotypes (PCV-2a and -2b, respectively). 6 Consequently, a multiplex real-time quantitative polymerase chain reaction (mrtqPCR) assay that 7 could sensitively and specifically identify and differentiate PCV-2 genotypes was developed. A 8 retrospective epidemiological survey that used the mrtqPCR assay was performed to determine if 9 cofactors could affect the risk of PCVAD. From 121 PCV-2–positive cases gathered for this 10 study, 4.13%, 92.56% and 3.31% were positive for PCV-2a, PCV-2b, and both genotypes, 11 respectively. In a data analysis using univariate logistic regressions, PCVAD compatible 12 (PCVAD/c) score was significantly associated with the presence of Porcine reproductive and 13 respiratory syndrome virus (PRRSV), PRRSV viral load, PCV-2 viral load, and PCV-2 14 immunohistochemistry (IHC) results. Polytomous logistic regression analysis revealed that 15 PCVAD/c score was affected by PCV-2 viral load (P = 0.0161) and IHC (P = 0.0128), but not by 16 the PRRSV variables (P > 0.9); suggesting that mrtqPCR in tissue is a reliable alternative to IHC. 17 Logistic regression analyses revealed that PCV-2 increased the odds ratio of isolating 2 major 18 swine pathogens of the respiratory tract, Actinobacillus pleuropneumoniae and Streptococcus 19 suis serotypes 1/2, 1, 2, 3, 4, and 7, which are serotypes commonly associated with clinical 20 diseases.

SUPPLY CHAIN MANAGEMENT IN INDIAN PETROLEUM REFINING INDUSTRY

Model development for selection of location for refinery in India and identification of characteristics to be looked into when configuring it and to develop models for integrated supply chain planning for a refinery. Locating and removing inbound, internal and outbound logistic problems in an existing refinery and overall design of a logistic information system for a refinery are the main objectives of the study. A brief description of supply chain management (SCM), elements of SCM and their significance, logistics cost in petroleum industry and its impacts, and dynamics of petroleum its logistic practices are also to be presented. Scope of application of SCM in petroleum refinery will also be discussed. A review of the investigations carried out by earlier researches in the area of supply chain management in general and with specific reference to petroleum refining.

How could construction supply chain benefit from RFID/GPS integration: a knowledge management perspective

Construction materials and equipment are essential building blocks of every construction project and may account for 50-60 per cent of the total cost of construction. The rate of their utilization, on the other hand, is the element that most directly relates to a project progress. A growing concern in the industry that inadequate efficiency hinders its success could thus be accommodated by turning construction into a logistic process. Although mostly limited, recent attempts and studies show that Radio Frequency IDentification (RFID) applications have significant potentials in construction. However, the aim of this research is to show that the technology itself should not only be used for automation and tracking to overcome the supply chain complexity but also as a tool to generate, record and exchange process-related knowledge among the supply chain stakeholders. This would enable all involved parties to identify and understand consequences of any forthcoming difficulties and react accordingly before they cause major disruptions in the construction process. In order to achieve this aim the study focuses on a number of methods. First of all it develops a generic understanding of how RFID technology has been used in logistic processes in industrial supply chain management. Secondly, it investigates recent applications of RFID as an information and communication technology support facility in construction logistics for the management of construction supply chain. Based on these the study develops an improved concept of a construction logistics architecture that explicitly relies on integrating RFID with the Global Positioning System (GPS). The developed conceptual model architecture shows that categorisation provided through RFID and traceability as a result of RFID/GPS integration could be used as a tool to identify, record and share potential problems and thus vastly improve knowledge management processes within the entire supply chain. The findings thus clearly show a need for future research in this area.

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

Assessment of long chain n-3 polyunsaturated fatty acid status and clinical outcome in adults receiving home parenteral nutrition

Background & aims: Long term parenteral nutrition rarely supplies the long chain n-3 polyunsaturated fatty acids (PUFA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA). The aim of this study was to assess long chain n-3 PUFA status in patients receiving home parenteral. nutrition (HPN). Methods: Plasma phospholipid fatty acids were measured in 64 adult HPN patients and compared with 54 age, sex and BMI matched controls. Logistic regression analysis was used to identify factors related to plasma fatty acid fractions in the HPN patients, and to identify factors associated with the risk of clinical. complications. Results: Plasma phospholipid fractions of EPA, DPA and DHA were significantly tower in patients receiving HPN. Factors independently associated with tow fractions included high parenteral energy provision, tow parenteral lipid intake, tow BMI and prolonged duration of HPN. Long chain n-3 PUFA fractions were not associated with incidence of either central venous catheter associated infection or central venous thrombosis. However, the fraction of EPA were inversely associated with plasma alkaline phosphatase concentrations. Conclusions: This study demonstrates abnormal long chain n-3 PUFA profiles in patients receiving HPN. Reduced fatty acid intake may be partly responsible. Fatty acid metabolism may also be altered. (C) 2008 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered.

Applying supply chain management models in the banking industry: a brazilian case analysis

The study presents the results and recommendations deriving from the application of two supply chain management analysis models as proposed by the Supply Chain Council (SCOR, version 10.0) and by Lambert (1997, Framework for Supply Chain Management) on the logistics of cash transfers in Brazil. Cash transfers consist of the transportation of notes to and from each node of the complex network formed by the bank branches, ATMs, armored transportation providers, the government custodian, Brazilian Central Bank and financial institutions. Although the logistic to sustain these operations is so wide-ranged (country-size), complex and subject to a lot of financial regulations and security procedures, it has been detected that it was probably not fully integrated. Through the use of a primary and a secondary data research and analysis, using the above mentioned models, the study ends up with propositions to strongly improve the operations efficiency

Análise pelo Supply Chain Management da cadeia produtiva da castanha de caju no Rio Grande do Norte

This work presents the cashew nuts chain in the State of Rio Grande do Norte between 1960 and 2009. The main purpose of this research was to find the reason of the low productivity of the cashew nut in this state, identifying in the cashew's chain production the struggling points which were limiting the commerce of this product through the distribution network. Therefore, the Supply Chain Management was used as a logistic analysis methodology, focusing on relationships management between the nodes of this chain, from the producer until the final customer. Many problems were found: first, the precarious production conditions of the small producer don't lead to reach the demanded productivity by the market. The distance, the lack of communication of the small producers among themselves and an archaic way of dealing with their businesses, may be an explanatory reason for this problem, considering that those factors are the main elements which contribute for the weakening of the small producer placed in the productive chain. Another spotted point was that the business-oriented relationship between the producer and the local trader does not allow the small producer's economical development, which interferes in any technological investment to reach a good quality production that fulfills the market demand. And also, the fact that there is a tendency of the final costumer to require lower prices day-byday, forcing a pressure on the nodes transferring to the other and successively until arriving at the producer who inevitably is suffering the biggest impacts from this mentioned pressure.

Green supply chain management: Mapping the territory

The objective of this paper is to identify the main definitions, related practices and to point out future directions in green supply chain management (GSCM). After a literature review and systematisation of the published articles in this field, it was possible to identify: a) the main research objectives of analysed papers; b) the research methods adopted; c) the predominantly analysed industrial sectors; d) the GSCM practices considered by the researchers. Results are presented in each of these analytical perspectives. The main findings are: 1) there are various classifications, nomenclatures and types of GSCM practices, but the most commonly used by studies in GSCM are cleaner production, product design, reverse logistic and green purchasing; 2) from the highlighted definitions, the tonic is to adapt operating activities and incorporate the supply chain management philosophy (integration/ collaboration) to environmental concerns (impact reduction) in relations between links in the chain. These results can be useful for those interested in environmental management as well as supply chain management, considering the growing interest in GSCM. We also propose a research agenda on this subject. This is one of the most recent literature review and systematisation on green supply chain management. © 2013 Inderscience Enterprises Ltd.

Application and Development Trend of Integrated Supply Chain in China

Importing integrated supply chains have changed Chinese logistic from simplex freight to the process of product of production、circulation and consumption of logistic system. Different modal of integrated supply chain apply in the different companies, bring activity and efficiency integrated supply chain in China. The trend of Chinese integrated supply chain in the future will stress on e-commerce and customer service, and combined Chinese own logistic system to enlarge Chinese logistic, which will more international and world wild.

Logistic regression with Markov chains as covariates

The tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is an obvious carcinogen for lung cancer. Since CBMN (Cytokinesis-blocked micronucleus) has been found to be extremely sensitive to NNK-induced genetic damage, it is a potential important factor to predict the lung cancer risk. However, the association between lung cancer and NNK-induced genetic damage measured by CBMN assay has not been rigorously examined. ^ This research develops a methodology to model the chromosomal changes under NNK-induced genetic damage in a logistic regression framework in order to predict the occurrence of lung cancer. Since these chromosomal changes were usually not observed very long due to laboratory cost and time, a resampling technique was applied to generate the Markov chain of the normal and the damaged cell for each individual. A joint likelihood between the resampled Markov chains and the logistic regression model including transition probabilities of this chain as covariates was established. The Maximum likelihood estimation was applied to carry on the statistical test for comparison. The ability of this approach to increase discriminating power to predict lung cancer was compared to a baseline "non-genetic" model. ^ Our method offered an option to understand the association between the dynamic cell information and lung cancer. Our study indicated the extent of DNA damage/non-damage using the CBMN assay provides critical information that impacts public health studies of lung cancer risk. This novel statistical method could simultaneously estimate the process of DNA damage/non-damage and its relationship with lung cancer for each individual.^

A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Innovation across the food chain – the Hungarian case

The small and medium sized enterprises (SMEs) in the Hungarian agri-food sector play determining role. The innovation capacity (efforts, activities and results) however of the individual SMEs is very limited. Food production (including SMEs) has to fulfil food safety requirements in a rapidly increasing extent, which implies a continuous innovation and development process from all market players. In Hungary the agri-food chain had to face a suddenly increased competition especially after the EU enlargement. Based on survey data this paper examines the efforts, activities and results in knowledge acquisition, utilisation, coordination and transfer in the Central Hungarian food SMEs. We have found (using ordered logistic regression) that R&D expenditures, achieved innovations, export/import orientation as well as the networking activity of the SMEs play significant role in market development.

Analytics and Methods for Logistic System Design and Operations Management

Analytics is the technology working with the manipulation of data to produce information able to change the world we live every day. Analytics have been largely used within the last decade to cluster people’s behaviour to predict their preferences of items to buy, music to listen, movies to watch and even electoral preference. The most advanced companies succeded in controlling people’s behaviour using analytics. Despite the evidence of the super-power of analytics, they are rarely applied to the big data collected within supply chain systems (i.e. distribution network, storage systems and production plants). This PhD thesis explores the fourth research paradigm (i.e. the generation of knowledge from data) applied to supply chain system design and operations management. An ontology defining the entities and the metrics of supply chain systems is used to design data structures for data collection in supply chain systems. The consistency of this data is provided by mathematical demonstrations inspired by the factory physics theory. The availability, quantity and quality of the data within these data structures define different decision patterns. Ten decision patterns are identified, and validated on-field, to address ten different class of design and control problems in the field of supply chain systems research.

Quantitative Proteomic Analysis Reveals Metabolic Alterations, Calcium Dysregulation, And Increased Expression Of Extracellular Matrix Proteins In Laminin α2 Chain-deficient Muscle.

Congenital muscular dystrophy with laminin α2 chain deficiency (MDC1A) is one of the most severe forms of muscular disease and is characterized by severe muscle weakness and delayed motor milestones. The genetic basis of MDC1A is well known, yet the secondary mechanisms ultimately leading to muscle degeneration and subsequent connective tissue infiltration are not fully understood. In order to obtain new insights into the molecular mechanisms underlying MDC1A, we performed a comparative proteomic analysis of affected muscles (diaphragm and gastrocnemius) from laminin α2 chain-deficient dy(3K)/dy(3K) mice, using multidimensional protein identification technology combined with tandem mass tags. Out of the approximately 700 identified proteins, 113 and 101 proteins, respectively, were differentially expressed in the diseased gastrocnemius and diaphragm muscles compared with normal muscles. A large portion of these proteins are involved in different metabolic processes, bind calcium, or are expressed in the extracellular matrix. Our findings suggest that metabolic alterations and calcium dysregulation could be novel mechanisms that underlie MDC1A and might be targets that should be explored for therapy. Also, detailed knowledge of the composition of fibrotic tissue, rich in extracellular matrix proteins, in laminin α2 chain-deficient muscle might help in the design of future anti-fibrotic treatments. All MS data have been deposited in the ProteomeXchange with identifier PXD000978 (http://proteomecentral.proteomexchange.org/dataset/PXD000978).