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Crohn's disease (CD) is a complex disorder resulting from the interaction of intestinal microbiota with the host immune system in genetically susceptible individuals. The largest meta-analysis of genome-wide association to date identified 71 CD-susceptibility loci in individuals of European ancestry. An important epidemiological feature of CD is that it is 2-4 times more prevalent among individuals of Ashkenazi Jewish (AJ) descent compared to non-Jewish Europeans (NJ). To explore genetic variation associated with CD in AJs, we conducted a genome-wide association study (GWAS) by combining raw genotype data across 10 AJ cohorts consisting of 907 cases and 2,345 controls in the discovery stage, followed up by a replication study in 971 cases and 2,124 controls. We confirmed genome-wide significant associations of 9 known CD loci in AJs and replicated 3 additional loci with strong signal (p<5×10 -6). Novel signals detected among AJs were mapped to chromosomes 5q21.1 (rs7705924, combined p = 2×10 -8; combined odds ratio OR = 1.48), 2p15 (rs6545946, p = 7×10 -9; OR = 1.16), 8q21.11 (rs12677663, p = 2×10 -8; OR = 1.15), 10q26.3 (rs10734105, p = 3×10 -8; OR = 1.27), and 11q12.1 (rs11229030, p = 8×10 -9; OR = 1.15), implicating biologically plausible candidate genes, including RPL7, CPAMD8, PRG2, and PRG3. In all, the 16 replicated and newly discovered loci, in addition to the three coding NOD2 variants, accounted for 11.2% of the total genetic variance for CD risk in the AJ population. This study demonstrates the complementary value of genetic studies in the Ashkenazim. © 2012 Kenny et al.

Crohn's disease (CD) is a complex disorder resulting from the interaction of intestinal microbiota with the host immune system in genetically susceptible individuals. The largest meta-analysis of genome-wide association to date identified 71 CD-susceptibility loci in individuals of European ancestry. An important epidemiological feature of CD is that it is 2-4 times more prevalent among individuals of Ashkenazi Jewish (AJ) descent compared to non-Jewish Europeans (NJ). To explore genetic variation associated with CD in AJs, we conducted a genome-wide association study (GWAS) by combining raw genotype data across 10 AJ cohorts consisting of 907 cases and 2,345 controls in the discovery stage, followed up by a replication study in 971 cases and 2,124 controls. We confirmed genome-wide significant associations of 9 known CD loci in AJs and replicated 3 additional loci with strong signal (p<5×10 -6). Novel signals detected among AJs were mapped to chromosomes 5q21.1 (rs7705924, combined p = 2×10 -8; combined odds ratio OR = 1.48), 2p15 (rs6545946, p = 7×10 -9; OR = 1.16), 8q21.11 (rs12677663, p = 2×10 -8; OR = 1.15), 10q26.3 (rs10734105, p = 3×10 -8; OR = 1.27), and 11q12.1 (rs11229030, p = 8×10 -9; OR = 1.15), implicating biologically plausible candidate genes, including RPL7, CPAMD8, PRG2, and PRG3. In all, the 16 replicated and newly discovered loci, in addition to the three coding NOD2 variants, accounted for 11.2% of the total genetic variance for CD risk in the AJ population. This study demonstrates the complementary value of genetic studies in the Ashkenazim. © 2012 Kenny et al.

Crohn's disease (CD) is a complex disorder resulting from the interaction of intestinal microbiota with the host immune system in genetically susceptible individuals. The largest meta-analysis of genome-wide association to date identified 71 CD-susceptibility loci in individuals of European ancestry. An important epidemiological feature of CD is that it is 2-4 times more prevalent among individuals of Ashkenazi Jewish (AJ) descent compared to non-Jewish Europeans (NJ). To explore genetic variation associated with CD in AJs, we conducted a genome-wide association study (GWAS) by combining raw genotype data across 10 AJ cohorts consisting of 907 cases and 2,345 controls in the discovery stage, followed up by a replication study in 971 cases and 2,124 controls. We confirmed genome-wide significant associations of 9 known CD loci in AJs and replicated 3 additional loci with strong signal (p<5×10 -6). Novel signals detected among AJs were mapped to chromosomes 5q21.1 (rs7705924, combined p = 2×10 -8; combined odds ratio OR = 1.48), 2p15 (rs6545946, p = 7×10 -9; OR = 1.16), 8q21.11 (rs12677663, p = 2×10 -8; OR = 1.15), 10q26.3 (rs10734105, p = 3×10 -8; OR = 1.27), and 11q12.1 (rs11229030, p = 8×10 -9; OR = 1.15), implicating biologically plausible candidate genes, including RPL7, CPAMD8, PRG2, and PRG3. In all, the 16 replicated and newly discovered loci, in addition to the three coding NOD2 variants, accounted for 11.2% of the total genetic variance for CD risk in the AJ population. This study demonstrates the complementary value of genetic studies in the Ashkenazim. © 2012 Kenny et al.

This article introduces the Strength-focused and Meaning- oriented Approach to Resilience and Transformation (SMART) as a model of crisis intervention, which aims at discovering inner strengths through meaning reconstruction. Limitations of conventional crisis management and current findings in post-traumatic growth research are discussed. Instead of adopting a pathological framework, the SMART approach holds a holistic view of health, employs facilitative strategies, and promotes dynamic coping. Intervention components include Eastern spiritual teachings, physical techniques such as yoga and meditation, and psycho-education that promotes meaning reconstruction. Efficacy of the SMART model is assessed with reference to two pilot studies conducted in Hong Kong at the time when the SARS pandemic caused widespread fear and anxiety in the community. Response to potential criticisms of the SMART model is attempted.

The Body-Mind-Spirit model of health promotion (Chan, Ho&Chow, 2002) guided the construction of a multidimensional inventory for assessing holistic health. Named Body-Mind-Spirit Well-Being Inventory (BMSWBI), it comprises four scales: Physical Distress, Daily Functioning, Affect, and Spirituality (differentiated from religiosity and conceived as ecumenical). Respondents (674 Chinese adults from Hong Kong) completed the BMSWBI via the Internet. Results indicate that all four scales have high reliability, with alpha coefficients ranging from .87 to .92, and concurrent validity. Factor analysis indicates that (a) positive and negative affect form two distinct factors; and (b) spirituality comprises three distinct aspects, tranquility, resistance to disorientation, and resilience. Spirituality is positively associated with mental well-being, positive affect, satisfaction with life, and hope; but negatively associated with negative affect and perceived stress. These results suggest that the inventory may be used to assess different dimensions of health satisfactorily.

A key issue in the design of a cellular manufacturing system is the formation of the machines and parts into groups or production cells. The production cells are designed to minimize the costs of inter-cell part movements and intra-cell processing, while balancing the workload within each cell. Most of the prior research represents the cell formation problem as a binary machine-part incidence matrix. The workload balance within each production cen can be precisely calculated only if the processing times and demand rates are included in the analysis. For this reason, a heuristic-based procedure that uses processing times and demand rates to form the production cells is proposed. The procedure considers the cell imbalance costs as well as the costs associated with the inter-cell part movements and intra-cell processing. The efficiency and effectiveness of the heuristic is compared with other methods, and an industrial application of the proposed heuristic is presented.

Group technology plays an important role in the design of an automated manufacturing system. The ideal situation is to partition the machines into machine cells and the parts into part families so that each machine cell together with the part family for the cell is independent of the rest of the system. We will give a characterization of the independent cells for an arbitrary manufacturing system. An efficient algorithm to identify these independent cells will also be discussed. An effective policy for subcell formation (not necessarily independent) from larger cells will also be discussed. Computational results show that our algorithms always obtain solutions with higher grouping efficiency compared with some of the existing algorithms. We also discuss the effectiveness of grouping efficiency as a measure for group technology.

A key issue in the design of a cellular manufacturing system is the formation of the machines and parts into groups or production cells. The production cells are designed to minimize the costs of inter-cell part movements and intra-cell processing, while balancing the workload within each cell. Most of the prior research represents the cell formation problem as a binary machine-part incidence matrix. The workload balance within each production cen can be precisely calculated only if the processing times and demand rates are included in the analysis. For this reason, a heuristic-based procedure that uses processing times and demand rates to form the production cells is proposed. The procedure considers the cell imbalance costs as well as the costs associated with the inter-cell part movements and intra-cell processing. The efficiency and effectiveness of the heuristic is compared with other methods, and an industrial application of the proposed heuristic is presented.

Group technology plays an important role in the design of an automated manufacturing system. The ideal situation is to partition the machines into machine cells and the parts into part families so that each machine cell together with the part family for the cell is independent of the rest of the system. We will give a characterization of the independent cells for an arbitrary manufacturing system. An efficient algorithm to identify these independent cells will also be discussed. An effective policy for subcell formation (not necessarily independent) from larger cells will also be discussed. Computational results show that our algorithms always obtain solutions with higher grouping efficiency compared with some of the existing algorithms. We also discuss the effectiveness of grouping efficiency as a measure for group technology.

A key issue in the design of a cellular manufacturing system is the formation of the machines and parts into groups or production cells. The production cells are designed to minimize the costs of inter-cell part movements and intra-cell processing, while balancing the workload within each cell. Most of the prior research represents the cell formation problem as a binary machine-part incidence matrix. The workload balance within each production cen can be precisely calculated only if the processing times and demand rates are included in the analysis. For this reason, a heuristic-based procedure that uses processing times and demand rates to form the production cells is proposed. The procedure considers the cell imbalance costs as well as the costs associated with the inter-cell part movements and intra-cell processing. The efficiency and effectiveness of the heuristic is compared with other methods, and an industrial application of the proposed heuristic is presented.

Group technology plays an important role in the design of an automated manufacturing system. The ideal situation is to partition the machines into machine cells and the parts into part families so that each machine cell together with the part family for the cell is independent of the rest of the system. We will give a characterization of the independent cells for an arbitrary manufacturing system. An efficient algorithm to identify these independent cells will also be discussed. An effective policy for subcell formation (not necessarily independent) from larger cells will also be discussed. Computational results show that our algorithms always obtain solutions with higher grouping efficiency compared with some of the existing algorithms. We also discuss the effectiveness of grouping efficiency as a measure for group technology.

Two measures for the efficiency of grouping in cellular manufacturing are discussed in this paper. We first analyze the effectiveness of the first measure, grouping efficiency. A worst case bound is then derived for the minimum spanning tree algorithm with respect to this measure. We then show a newly proposed measure, grouping efficacy, is not suitable from an algorithmic point of view. A weighted grouping efficacy is then proposed and worst case bounds are derived with respect to this new measure. We also propose several policies to improve grouping efficiency and grouping efficacy during the decomposition of larger machine cells. Computational results will also be presented to demonstrate the effectiveness of these measures and the worst case bounds.

Two measures for the efficiency of grouping in cellular manufacturing are discussed in this paper. We first analyze the effectiveness of the first measure, grouping efficiency. A worst case bound is then derived for the minimum spanning tree algorithm with respect to this measure. We then show a newly proposed measure, grouping efficacy, is not suitable from an algorithmic point of view. A weighted grouping efficacy is then proposed and worst case bounds are derived with respect to this new measure. We also propose several policies to improve grouping efficiency and grouping efficacy during the decomposition of larger machine cells. Computational results will also be presented to demonstrate the effectiveness of these measures and the worst case bounds.

Two measures for the efficiency of grouping in cellular manufacturing are discussed in this paper. We first analyze the effectiveness of the first measure, grouping efficiency. A worst case bound is then derived for the minimum spanning tree algorithm with respect to this measure. We then show a newly proposed measure, grouping efficacy, is not suitable from an algorithmic point of view. A weighted grouping efficacy is then proposed and worst case bounds are derived with respect to this new measure. We also propose several policies to improve grouping efficiency and grouping efficacy during the decomposition of larger machine cells. Computational results will also be presented to demonstrate the effectiveness of these measures and the worst case bounds.