SOLVING RESOURCE—CONSTRAINED PROJECT SCHEDULING PROBLEMS WITH BI—CRITERIA HEURISTIC SEARCH TECHNIQUES

In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm forsolving multiple resource-constrained project scheduling problems. The heuristic solves problems intwo phases. In the pre-processing phase, the algorithm estimates distance between a state and the goalstate and measures complexity of problem instances. In the search phase, the algorithm uses estimatesof the pre-processing phase to further estimate distances to the goal state. The search continues in astepwise generation of a series of intermediate states through search path evaluation process withbacktracking. Developments of intermediate states are exclusively based on a bi-criteria new stateselection technique where we consider resource utilization and duration estimate to the goal state. Wealso propose a variable weighting technique based on initial problem complexity measures.Introducing this technique allows the algorithm to efficiently solve complex project schedulingproblems. A numerical example illustra     

A Proposed Gravitodynamic Theory

1.IntRODUCTIONInarecentreviewPaper,Norton[11hasshownthattheprincipleofgeneralcovariancehasbeendisputedasphysicallyvacuous.ThedebateoverthisprinciplePersiststoday.Ingeneralrelativity,spaCe-timecoordinatescanbearbitrarilychosen[2,3]andgravitationalPOtentialsarerepresentedbythemetrictensof,gp.inthefouredimensional(4ro)lineelement:wheregpvhastenindependentcomPOnents,andGreekletterspandvrunfrom0tO3.InEq.(l),d/isan'invariantunderspace--timecoordinatetransformation.However,inordertogetunique…     

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation＇s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit （RTU） system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.     

Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci

Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with complex etiology but strong clustering in families (lambda(S) = approximately 30). We performed a genome-wide association scan using 317,501 SNPs in 720 women of European ancestry with SLE and in 2,337 controls, and we genotyped consistently associated SNPs in two additional independent sample sets totaling 1,846 affected women and 1,825 controls. Aside from the expected strong association between SLE and the HLA region on chromosome 6p21 and the previously confirmed non-HLA locus IRF5 on chromosome 7q32, we found evidence of association with replication (1.1 x 10(-7) < P(overall) < 1.6 x 10(-23); odds ratio = 0.82-1.62) in four regions: 16p11.2 (ITGAM), 11p15.5 (KIAA1542), 3p14.3 (PXK) and 1q25.1 (rs10798269). We also found evidence for association (P < 1 x 10(-5)) at FCGR2A, PTPN22 and STAT4, regions previously associated with SLE and other autoimmune diseases, as well as at > or =9 other loci (P < 2 x 10(-7)). Our results show that numerous genes, some with known immune-related functions, predispose to SLE.     

Zebrafish rgs4 is essential for motility and axonogenesis mediated by Akt signaling

The schizophrenia susceptibility gene, Rgs4, is one of the most intensively studied regulators of G-protein signaling members, well known to be fundamental in regulating neurotransmission. However, little is known about its role in the developing nervous system. We have isolated zebrafish rgs4 and shown that it is transcribed in the developing nervous system. Rgs4 knockdown did not affect neuron number and patterning but resulted in locomotion defects and aberrant development of axons. This was confirmed using a selective Rgs4 inhibitor, CCG-4986. Rgs4 knockdown also attenuated the level of phosphorylated-Akt1, and injection of constitutively-activated AKT1 rescued the motility defects and axonal phenotypes in the spinal cord but not in the hindbrain and trigeminal neurons. Our in vivo analysis reveals a novel role for Rgs4 in regulating axonogenesis during embryogenesis, which is mediated by another schizophrenia-associated gene, Akt1, in a region-specific manner.     

Deletion of Pten in mouse brain causes seizures, ataxia and defects in soma size resembling Lhermitte-Duclos disease.

Initially identified in high-grade gliomas, mutations in the PTEN tumor-suppressor are also found in many sporadic cancers and a few related autosomal dominant hamartoma syndromes. PTEN is a 3'-specific phosphatidylinositol-3,4,5-trisphosphate (PI(3,4,5)P3) phosphatase and functions as a negative regulator of PI3K signaling. We generated a tissue-specific deletion of the mouse homolog Pten to address its role in brain function. Mice homozygous for this deletion (PtenloxP/loxP;Gfap-cre), developed seizures and ataxia by 9 wk and died by 29 wk. Histological analysis showed brain enlargement in PtenloxP/loxP;Gfap-cre mice as a consequence of primary granule-cell dysplasia in the cerebellum and dentate gyrus. Pten mutant cells showed a cell-autonomous increase in soma size and elevated phosphorylation of Akt. These data represent the first evidence for the role of Pten and Akt in cell size regulation in mammals and provide an animal model for a human phakomatosis condition, Lhermitte-Duclos disease (LDD).     

被子植物雌雄配子及其表膜特异蛋白研究进展

近年来．被子植物雌雄配子的细胞学与生物化学研究取得了一系列重要进展．包括精卵细胞分离纯化、活力保持与检测技术的建立、形态的构观察、生化特性分析及人工体外融合成功，等等．这些进展为创建体外受精操作系统及探讨受精识别机理提供了可能性．被子植物双受精过程存在多位点识别．有关配子水平识别的研究刚刚起步，主要是通过不同途径寻找雌雄配子表膜特异蛋白．其中质膜的纯度与数量问题亟待解决．     

Functional cloning of TUG as a regulator of GLUT4 glucose transporter trafficking

Insulin stimulates glucose uptake in fat and muscle by mobilizing the GLUT4 glucose transporter. GLUT4 is sequestered intracellularly in the absence of insulin, and is redistributed to the plasma membrane within minutes of insulin stimulation. But the trafficking mechanisms that control GLUT4 sequestration have remained elusive. Here we describe a functional screen to identify proteins that modulate GLUT4 distribution, and identify TUG as a putative tether, containing a UBX domain, for GLUT4. In truncated form, TUG acts in a dominant-negative manner to inhibit insulin-stimulated GLUT4 redistribution in Chinese hamster ovary cells and 3T3-L1 adipocytes. Full-length TUG forms a complex specifically with GLUT4; in 3T3-L1 adipocytes, this complex is present in unstimulated cells and is largely disassembled by insulin. Endogenous TUG is localized with the insulin-mobilizable pool of GLUT4 in unstimulated 3T3-L1 adipocytes, and is not mobilized to the plasma membrane by insulin. Distinct regions of TUG are required to bind GLUT4 and to retain GLUT4 intracellularly in transfected, non-adipose cells. Our data suggest that TUG traps endocytosed GLUT4 and tethers it intracellularly, and that insulin mobilizes this pool of retained GLUT4 by releasing this tether.     

On estimation and prediction procedures for ar(1) models with power transformation

The power transformation of Box and Cox (1964) has been shown to be quite useful in short-term forecasting for the linear regression model with AR(1) dependence structure (see, for example, Lee and Lu, 1987, 1989). It is crucial to have good estimates of the power transformation and serial. correlation parameters, because they form the basis for estimating other parameters and predicting future observations. The prediction of future observations is the main focus of this paper. We propose to estimate these two parameters by minimizing the mean squared prediction errors. These estimates and the corresponding predictions compare favourably, via revs and simulated data, with those obtained by the maximum likelihood method. Similar results are also demonstrated in the repeated measurements setting.