Predit: A temporal predictive framework for scheduling systems

Scheduling can be formalized as a Constraint Satisfaction Problem (CSP). Within this framework activities belonging to a plan are interconnected via temporal constraints that account for slack among them. Temporal representation must include methods for constraints propagation and provide a logic for symbolic and numerical deductions. In this paper we describe a support framework for opportunistic reasoning in constraint directed scheduling. In order to focus the attention of an incremental scheduler on critical problem aspects, some discrete temporal indexes are presented. They are also useful for the prediction of the degree of resources contention. The predictive method expressed through our indexes can be seen as a Knowledge Source for an opportunistic scheduler with a blackboard architecture

Conserved Amino Acids in Each Subunit of the Heteroligomeric tRNA m\u3csup\u3e1\u3c/sup\u3eA58 Mtase from \u3cem\u3eSaccharomyces cerevisiae\u3c/em\u3e Contribute to tRNA Binding

In Saccharomyces cerevisiae, a two-subunit methyltransferase (Mtase) encoded by the essential genes TRM6 and TRM61 is responsible for the formation of 1-methyladenosine, a modified nucleoside found at position 58 in tRNA that is critical for the stability of . The crystal structure of the homotetrameric m1A58 tRNA Mtase from Mycobacterium tuberculosis, TrmI, has been solved and was used as a template to build a model of the yeast m1A58 tRNA Mtase heterotetramer. We altered amino acids in TRM6 and TRM61 that were predicted to be important for the stability of the heteroligomer based on this model. Yeast strains expressing trm6 and trm61 mutants exhibited growth phenotypes indicative of reduced m1A formation. In addition, recombinant mutant enzymes had reduced in vitro Mtase activity. We demonstrate that the mutations introduced do not prevent heteroligomer formation and do not disrupt binding of the cofactor S-adenosyl-l-methionine. Instead, amino acid substitutions in either Trm6p or Trm61p destroy the ability of the yeast m1A58 tRNA Mtase to bind , indicating that each subunit contributes to tRNA binding and suggesting a structural alteration of the substrate-binding pocket occurs when these mutations are present

Pengaruh Kualitas Layanan, Promosi Dan Kepuasan Terhadap Loyalitas Nasabah Pada PT. Pegadaian Cabang Manado Timur

Persaingan bisnis yang semakin ketat menuntut para pelaku bisnis khususnya di bidang jasa gadai dimana salah satunya adalah PT. Pegadaian untuk memaksimalkan kinerjanya. Penelitian ini bertujuan untuk mengetahui dan menganalisa pengaruh Kualitas Layanan, Promosi dan Kepuasan terhadap Loyalitas Nasabah Gadai KCA pada PT. Pegadaian (Persero) Cabang Manado Timur. Kuesioner dirancang dengan menggunakan Likert Scale. Populasi dalam penelitian ini adalah seluruh nasabah Kredit Cepat Aman (KCA) yang berjumlah 1.330 orang dengan jumlah responden sebanyak 100 orang. Analisa data menggunakan Regresi Linear Berganda. Hasil penelitian secara simultan menunjukkan bahwa Kualitas Layanan, Promosi danKepuasan berpengaruh signifikan positif terhadap Loyalitas Nasabah. Secara parsial Promosi paling dominan berpengaruh signifikan positif terhadap Loyalitas Nasabah sebesar 51,80% sedangkan Kualitas Layanan berpengaruh signifikan positif terhadap Loyalitas Nasabah sebesar 37,10%. Kepuasan berpengaruh tidak signifikan terhadap Loyalitas Nasabah. Walaupun Kepuasan Nasabah tidak berpengaruh signifikan positif tetapi tetap harus menjadi perhatian mengingat persaingan bisnis jasa keuangan saat ini yang sangat kompetitif maka harus ada upaya-upaya untuk meningkakan kepuasan nasabah

Protein Expression, Characterization and Activity Comparisons of Wild Type and Mutant DUSP5 Proteins

Background The mitogen-activated protein kinases (MAPKs) pathway is critical for cellular signaling, and proteins such as phosphatases that regulate this pathway are important for normal tissue development. Based on our previous work on dual specificity phosphatase-5 (DUSP5), and its role in embryonic vascular development and disease, we hypothesized that mutations in DUSP5 will affect its function. Results In this study, we tested this hypothesis by generating full-length glutathione-S-transferase-tagged DUSP5 and serine 147 proline mutant (S147P) proteins from bacteria. Light scattering analysis, circular dichroism, enzymatic assays and molecular modeling approaches have been performed to extensively characterize the protein form and function. We demonstrate that both proteins are active and, interestingly, the S147P protein is hypoactive as compared to the DUSP5 WT protein in two distinct biochemical substrate assays. Furthermore, due to the novel positioning of the S147P mutation, we utilize computational modeling to reconstruct full-length DUSP5 and S147P to predict a possible mechanism for the reduced activity of S147P. Conclusion Taken together, this is the first evidence of the generation and characterization of an active, full-length, mutant DUSP5 protein which will facilitate future structure-function and drug development-based studies

Morobe Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra

Madang Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra