A genome-wide association study for celiac disease identifies risk variants in the region harboring IL2 and IL21

We tested 310,605 SNPs for association in 778 individuals with celiac disease and 1,422 controls. Outside the HLA region, the most significant finding (rs13119723; P = 2.0 x 10(-7)) was in the KIAA1109-TENR-IL2-IL21 linkage disequilibrium block. We independently confirmed association in two further collections (strongest association at rs6822844, 24 kb 5' of IL21; meta-analysis P = 1.3 x 10(-14), odds ratio = 0.63), suggesting that genetic variation in this region predisposes to celiac disease.     

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.     

Optimal maintenance and replacement of extraction machinery

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

From Researching Regions at a Distance to Participatory Network Building: Integrating Action Research and Economic Geography

This paper describes the change in a researcher's practices from one of studying regional industrial development at a distance to one of working closely with a network of agri-food managers. This is accompanied by a discussion of the methodological and theoretical possibilities for an action research inspired economic geography. Some of the core characteristics of a pragmatic conceptualization of action research are revised. It is argued that theoretical developments within economic geography make possible a dialogue between researchers and local actors and that economic geography is challenged to accept that knowledge is generated through such a dialogue. Attempts to create a dialogue between action research and economic geography in a specific Norwegian industrial and geographical context are described. These attempts indicate that the researcher's methodological approach has been transformed from a narrow one relying solely on conventional social science methods to a broader one including participatory action research.