Auction-based approach to resolve the scheduling problem in the steel making process

Steel production is an extremely complex process and determining coherent schedules for the wide variety of production steps in a dynamic environment, where disturbances frequently occur, is a challenging task. In the steel production process, the blast furnace continuously produces liquid iron, which is transformed into liquid steel in the melt shop. The majority of the molten steel passes through a continuous caster to form large steel slabs, which are rolled into coils in the hot strip mill. The scheduling system of these processes has very different objectives and constraints, and operates in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. The steel making process, which includes steel making followed by continuous casting, is generally the main bottleneck in steel production. Therefore, comprehensive scheduling of this process is critical to improve the quality and productivity of the entire production system. This paper addresses the scheduling problem in the steel making process. The methodology of winner determination using the combinatorial auction process is employed to solve the aforementioned problem. In the combinatorial auction, allowing bidding on a combination of assets offers a way of enhancing the efficiency of allocating the assets. In this paper, the scheduling problem in steel making has been formulated as a linear integer program to determine the scheduling sequence for different charges. Bids are then obtained for sequencing the charges. Next, a heuristic approach is used to evaluate the bids. The computational results show that our algorithm can obtain optimal or near-optimal solutions for combinatorial problems in a reasonable computation time. The proposed algorithm has been verified by a case study

Grassmannian flows and applications to nonlinear partial differential equations

We show how solutions to a large class of partial differential equations with nonlocal Riccati-type nonlinearities can be generated from the corresponding linearized equations, from arbitrary initial data. It is well known that evolutionary matrix Riccati equations can be generated by projecting linear evolutionary flows on a Stiefel manifold onto a coordinate chart of the underlying Grassmann manifold. Our method relies on extending this idea to the infinite dimensional case. The key is an integral equation analogous to the Marchenko equation in integrable systems, that represents the coodinate chart map. We show explicitly how to generate such solutions to scalar partial differential equations of arbitrary order with nonlocal quadratic nonlinearities using our approach. We provide numerical simulations that demonstrate the generation of solutions to Fisher--Kolmogorov--Petrovskii--Piskunov equations with nonlocal nonlinearities. We also indicate how the method might extend to more general classes of nonlinear partial differential systems.Comment: 26 pages, 2 figure

Revealing the footprints of squark gluino production through Higgs search experiments at the Large Hadron Collider at 7 TeV and 14 TeV

The invariant mass distribution of the di-photons from the decay of the lighter scalar Higgs boson(h) to be carefully measured by dedicated h search experiments at the LHC may be distorted by the di-photons associated with the squark-gluino events with much larger cross sections in Gauge Mediated Supersymmetry Breaking (GMSB) models. This distortion if observed by the experiments at the Large Hadron Collider at 7 TeV or 14 TeV, would disfavour not only the standard model but various two Higgs doublet models with comparable h - masses and couplings but without a sector consisting of new heavy particles decaying into photons. The minimal GMSB (mGMSB) model constrained by the mass bound on h from LEP and that on the lightest neutralino from the Tevatron, produce negligible effects. But in the currently popular general GMSB(GGMSB) models the tail of the above distribution may show statistically significant excess of events even in the early stages of the LHC experiments with integrated luminosity insufficient for the discovery of h. We illustrate the above points by introducing several benchmark points in various GMSB models - minimal as well as non-minimal. The same conclusion follows from a detailed parameter scan in a simplified GGMSB model recently employed by the CMS collaboration to interpret their searches in the di-photon + \etslash channel. Other observables like the effective mass distribution of the di-photon + X events may also reveal the presence of new heavy particles beyond the Higgs sector. The contamination of the h mass peak and simple remedies are also discussed.Comment: 23 pages, 7 figures, title and organization of the paper is changed, detailed parameter scan in a simplified GGMSB model is added, conclusions and old numerical results remain unchange

Precision Gauge Unification from Extra Yukawa Couplings

We investigate the impact of extra vector-like GUT multiplets on the predicted value of the strong coupling. We find in particular that Yukawa couplings between such extra multiplets and the MSSM Higgs doublets can resolve the familiar two-loop discrepancy between the SUSY GUT prediction and the measured value of alpha_3. Our analysis highlights the advantages of the holomorphic scheme, where the perturbative running of gauge couplings is saturated at one loop and further corrections are conveniently described in terms of wavefunction renormalization factors. If the gauge couplings as well as the extra Yukawas are of O(1) at the unification scale, the relevant two-loop correction can be obtained analytically. However, the effect persists also in the weakly-coupled domain, where possible non-perturbative corrections at the GUT scale are under better control.Comment: 26 pages, LaTeX. v6: Important early reference adde

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies

Odontogenic tumors and giant cell lesions of jaws - a nine year study

<p>Abstract</p> <p>Objectives</p> <p>A definite geographic variation has been observed in the frequency of odontogenic tumors and giant cell lesions of the jaws reported from different parts of the world. However, there are a few studies on these lesions, especially giant cell lesions, reported from India. Hence, this study was designed to provide a demographic data on the odontogenic tumors and giant cell lesions reported from our institute located in the city of Hyderabad. Hyderabad is the capital city of the southern state of Andhra Pradesh in India. A retrospective analysis of odontogenic tumors and giant cell lesions of jaws reported in our institute between the years 2000 and 2009 was done and this data was compared with previous reports from different parts of the world and India.</p> <p>Methods</p> <p>Biopsies of the lesions received between the years 2000 and 2009 were reviewed and patient's history, clinical, radiological and histopathological characteristics were analyzed.</p> <p>Results</p> <p>A total of 77 biopsies were received during the nine year study period. These lesions were more frequently seen in the males, in a younger age group and showed a predilection for the mandible. Most of them presented as radiolucent, slow growing and painless lesions. Ameloblastomas (71.4%) constituted the majority of odontogenic tumors while central giant cell granulomas (7.8%) constituted the majority of giant cell lesions.</p> <p>Conclusion</p> <p>These lesions showed a definite geographic variation with ameloblastomas being the most common odontogenic tumors and odontomas being relatively rarer lesions in our region.</p

JNK interacting protein 1 (JIP-1) protects LNCaP prostate cancer cells from growth arrest and apoptosis mediated by 12-0-tetradecanoylphorbol-13-acetate (TPA)

12-0-tetradecanoylphorbol-13-acetate (TPA) stimulates protein kinase C (PKC) which mediates apoptosis in androgen-sensitive LNCaP human prostate cancer cells. The downstream signals of PKC that mediate TPA-induced apoptosis in LNCaP cells are unclear. In this study, we found that TPA activates the c-Jun NH2-terminal kinase (JNK)/c-Jun/AP-1 pathway. To explore the possible role that the JNK/c-Jun/AP-1 signal pathway has on TPA-induced apoptosis in LNCaP cells, we stably transfected the scaffold protein, JNK interacting protein 1 (JIP-1), which binds to JNK inhibiting its ability to phosphorylate c-Jun. TPA (10(-9)-10(-7) mol l(-1)) caused phosphorylation of JNK in both wild-type and JIP-1-transfected (LNCaP-JIP-1) cells. It resulted in phosphorylation and upregulation of expression of c-Jun protein in the wild-type LNCaP cells, but not in the JIP-1-transfected LNCaP cells. In addition, upregulation of AP-1 reporter activity by TPA (10(-9) mol l(-1)) occurred in LNCaP cells but was abrogated in LNCaP-JIP-1 cells. Thus, TPA stimulated c-Jun through JNK, and JIP-1 effectively blocked JNK. TPA (10(-12)-10(-8) mol l(-1)) treatment of LNCaP cells caused their growth inhibition, cell cycle arrest, upregulation of p53 and p21waf1, and induction of apoptosis. All of these effects were significantly attenuated when LNCaP-JIP-1 cells were similarly treated with TPA. A previous study showed that c-Jun/AP-1 blocked androgen receptor (AR) signaling by inhibiting AR binding to AR response elements (AREs) of target genes including prostate-specific antigen (PSA). Therefore, we hypothesised that TPA would not be able to disrupt the AR signal pathway in LNCaP-JIP-1 cells. Contrary to expectation, TPA (10(-9)-10(-8) mol l(-1)) inhibited DHT-induced AREs reporter activity and decreased levels of PSA in the LNCaP-JIP-1 cells. Taken together, TPA, probably by stimulation of PKC, phosphorylates JNK, which phosphorylates and increases expression of c-Jun leading to AP-1 activity. Growth control of prostate cancer cells can be mediated through the JNK/c-Jun pathway, but androgen responsiveness of these cells can be independent of this pathway, suggesting that androgen independence in progressive prostate cancer may not occur through activation of this pathway

Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach

Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well