A Bayesian incentive compatible mechanism for decentralized supply chain formation

In this paper we consider a decentralized supply chain formation problem for linear multi-echelon supply chains when the managers of the individual echelons are autonomous, rational, and intelligent. At each echelon, there is a choice of service providers and the specific problem we solve is that of determining a cost-optimal mix of service providers so as to achieve a desired level of end-to-end delivery performance. The problem can be broken up into two sub-problems following a mechanism design approach: (1) Design of an incentive compatible mechanism to elicit the true cost functions from the echelon managers; (2) Formulation and solution of an appropriate optimization problem using the true cost information. In this paper we propose a novel Bayesian incentive compatible mechanism for eliciting the true cost functions. This improves upon existing solutions in the literature which are all based on the classical Vickrey-Clarke-Groves mechanisms, requiring significant incentives to be paid to the echelon managers for achieving dominant strategy incentive compatibility. The proposed solution, which we call SCF-BIC (Supply Chain Formation with Bayesian Incentive Compatibility), significantly reduces the cost of supply chain formation. We illustrate the efficacy of the proposed methodology using the example of a three echelon manufacturing supply chain.

Broadcast in Ad hoc Wireless Networks with Selfish Nodes: A Bayesian Incentive Compatibility Approach

We consider the incentive compatible broadcast (ICB) problem in ad hoc wireless networks with selfish nodes. We design a Bayesian incentive compatible Broadcast (BIC-B) protocol to address this problem. VCG mechanism based schemes have been popularly used in the literature to design dominant strategy incentive compatible (DSIC) protocols for ad hoe wireless networks. VCG based mechanisms have two critical limitations: (i) the network is required to he bi-connected, (ii) the resulting protocol is not budget balanced. Our proposed BIC-B protocol overcomes these difficulties. We also prove the optimality of the proposed scheme.

Probing the existing magnetic phases in Pr0.5Ca0.5MnO3 (PCMO) nanowires and nanoparticles: magnetization and magneto-transport investigations

We show from conventional magnetization measurements that the charge order (CO) is completely suppressed in 10 nm Pr0.5Ca0.5MnO3 (PCMO 10) nanoparticles. Novel magnetization measurements, designed by a special high field measurement protocol, show that the dominant ground state magnetic phase is ferromagnetic-metallic (FM-M), which is an equilibrium phase, which coexists with the residual charge ordered anti-ferromagnetic phase (CO AFM) (an arrested phase) and exhibits the characteristic features of a `magnetic glassy state' at low temperatures. It is observed that there is a drastic reduction in the field required to induce the AFM to FM transition (similar to 5-6 T) compared to their bulk counterpart(similar to 27 T); this phase transition is of first order in nature, broad, irreversible and the coexisting phases are tunable with the cooling field. Temperature-dependent magneto-transport data indicate the occurrence of a size-induced insulator-metal transition (TM-I) and anomalous resistive hysteresis (R-H) loops, pointing out the presence of a mixture of the FM-M phase and AFM-I phase.

GMM based Bayesian approach to speech enhancement in signal transform domain

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator. The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Probing the aging effect in metallic polypyrrole by terahertz time-domain spectroscopy

Terahertz time-domain spectroscopy has been carried out on a metallic film of polypyrrole (PPy doped by PF6). The sample was exposed to air to investigate how the conductivity of the film varies as a function of time. The absorption and dispersion of the film decrease during initial days, and then tend to saturate. The conductivity of unaged sample follows the Drude model, and upon aging the data fit to the localization-modified Drude model. The fitting parameters show that the number of charge carriers decreases during the aging process. The initial rapid decrease in conductivity suggests that some of the delocalized carriers are localized due to aging. (C) 2007 American Institute of Physics.

Accelerator Mass Spectrometry and Bayesian Data Analysis

Accelerator mass spectrometry (AMS) is an ultrasensitive technique for measuring the concentration of a single isotope. The electric and magnetic fields of an electrostatic accelerator system are used to filter out other isotopes from the ion beam. The high velocity means that molecules can be destroyed and removed from the measurement background. As a result, concentrations down to one atom in 10^16 atoms are measurable. This thesis describes the construction of the new AMS system in the Accelerator Laboratory of the University of Helsinki. The system is described in detail along with the relevant ion optics. System performance and some of the 14C measurements done with the system are described. In a second part of the thesis, a novel statistical model for the analysis of AMS data is presented. Bayesian methods are used in order to make the best use of the available information. In the new model, instrumental drift is modelled with a continuous first-order autoregressive process. This enables rigorous normalization to standards measured at different times. The Poisson statistical nature of a 14C measurement is also taken into account properly, so that uncertainty estimates are much more stable. It is shown that, overall, the new model improves both the accuracy and the precision of AMS measurements. In particular, the results can be improved for samples with very low 14C concentrations or measured only a few times.

Communicative and Anticipatory Decision-making Supported by Bayesian Networks

The purpose of this research is to draw up a clear construction of an anticipatory communicative decision-making process and a successful implementation of a Bayesian application that can be used as an anticipatory communicative decision-making support system. This study is a decision-oriented and constructive research project, and it includes examples of simulated situations. As a basis for further methodological discussion about different approaches to management research, in this research, a decision-oriented approach is used, which is based on mathematics and logic, and it is intended to develop problem solving methods. The approach is theoretical and characteristic of normative management science research. Also, the approach of this study is constructive. An essential part of the constructive approach is to tie the problem to its solution with theoretical knowledge. Firstly, the basic definitions and behaviours of an anticipatory management and managerial communication are provided. These descriptions include discussions of the research environment and formed management processes. These issues define and explain the background to further research. Secondly, it is processed to managerial communication and anticipatory decision-making based on preparation, problem solution, and solution search, which are also related to risk management analysis. After that, a solution to the decision-making support application is formed, using four different Bayesian methods, as follows: the Bayesian network, the influence diagram, the qualitative probabilistic network, and the time critical dynamic network. The purpose of the discussion is not to discuss different theories but to explain the theories which are being implemented. Finally, an application of Bayesian networks to the research problem is presented. The usefulness of the prepared model in examining a problem and the represented results of research is shown. The theoretical contribution includes definitions and a model of anticipatory decision-making. The main theoretical contribution of this study has been to develop a process for anticipatory decision-making that includes management with communication, problem-solving, and the improvement of knowledge. The practical contribution includes a Bayesian Decision Support Model, which is based on Bayesian influenced diagrams. The main contributions of this research are two developed processes, one for anticipatory decision-making, and the other to produce a model of a Bayesian network for anticipatory decision-making. In summary, this research contributes to decision-making support by being one of the few publicly available academic descriptions of the anticipatory decision support system, by representing a Bayesian model that is grounded on firm theoretical discussion, by publishing algorithms suitable for decision-making support, and by defining the idea of anticipatory decision-making for a parallel version. Finally, according to the results of research, an analysis of anticipatory management for planned decision-making is presented, which is based on observation of environment, analysis of weak signals, and alternatives to creative problem solving and communication.

Probing top-gated field effect transistor of reduced graphene oxide monolayer made by dielectrophoresis

We demonstrate a top-gated field effect transistor made of a reduced graphene oxide (RGO) monolayer (graphene) by dielectrophoresis. The Raman spectrum of RGO flakes of typical size of 5 mu m x 5 mu m shows a single 2D band at 2687 cm(-1), characteristic of single-layer graphene.The two-probe current-voltage measurements of RGO flakes, deposited in between the patterned electrodes with a gap of 2.5 mu m using ac dielectrophoresis, show ohmic behavior with a resistance of similar to 37 k Omega. The temperature dependence of the resistance (R) of RGO measured between 305 K and 393 K yields a temperature coefficient of resistance [dR/dT]/R similar to -9.5 x 10(-4)/K, the same as that of mechanically exfoliated single-layer graphene. The field-effect transistor action was obtained by electrochemical top-gating using a solid polymer electrolyte (PEO + LiClO4) and Pt wire. The ambipolar nature of graphene flakes is observed up to a doping level of similar to 6 x 10(12)/cm(2) and carrier mobility of similar to 50 cm(2)/V s. The source-drain current characteristics show a tendency of current saturation at high source-drain voltage which is analyzed quantitatively by a diffusive transport model. (C) 2010 Elsevier Ltd. All rights reserved.

Probing Fluorine Interactions in a Polyhydroxylated Environment: Conservation of a C-F center dot center dot center dot H-C Recognition Motif in Presence of O-H center dot center dot center dot O Hydrogen Bonds

Three conformationally locked fluorinated polycyclitols have been specially crafted on a rigid trans-decalin backbone, employing a surprisingly facile pyridine-poly(hydrogen fluoride)-mediated stereospecific epoxide ring opening as the key reaction. Molecula design of the three fluorinated probes under study focused on providing an efficient platform for (a) evaluating the ability of covalently bonded fluorine, vis-a-vis the isosteric hydroxy group, to act as a H-bond acceptor and (b) examining the possibility for an organic fluorine moiety, placed suitably in a spatially invariant position, to engage an 1,3-diaxial OH functionality in a purported intramolecular O-H center dot center dot center dot F hydrogen bond. The present endeavour reveals that C(sp(3))-F center dot center dot center dot H-C(sp(3)) hydrogen bonds, though weak and lesser investigated, can indeed be observed and supramolecular recognition motifs, involving such interactions, can be conserved even in crystal structures laden with stronger O-H center dot center dot center dot O hydrogen bonds.

Bayesian Analysis of a Superimposed Renewal Process

Stochastic behavior of an aero-engine failure/repair process has been analyzed from a Bayesian perspective. Number of failures/repairs in the component-sockets of this multi-component system are assumed to follow independent renewal processes with Weibull inter-arrival times. Based on the field failure/repair data of a large number of such engines and independent Gamma priors on the scale parameters and log-concave priors on the shape parameters, an exact method of sampling from the resulting posterior distributions of the parameters has been proposed. These generated parameter values are next utilised in obtaining the posteriors of the expected number of system repairs, system failure rate, and the conditional intensity function, which are computed using a recursive formula.

Probing the role of the C-H center dot center dot center dot O hydrogen bond stabilized polypeptide chain reversal at the C-terminus of designed peptide helices. Structural characterization of three decapeptides

The structural characterization in crystals of three designed decapeptides containing a double D-segment at the C-terminus is described. The crystal structures of the peptides Boc-Leu-Aib-Val-Xxx-Leu-Aib-Val- (D)Ala-(D)Leu-Aib-OMe, (Xxx = Gly 2, (D)Ala 3, Aib 4) have been determined and compared with those reported earlier for peptide 1 (Xxx = Ala) and the all L analogue Boc-Leu-Aib-Val-Ala-Leu-Aib-Val-Ala-Leu-Aib-OMe, which yielded a perfect right-handed a-helical structure. Peptides 1 and 2 reveal a right-handed helical segment spanning residues 1 to 7, ending in a Schellman motif with Ala(8) functioning as the terminating residue. Polypeptide chain reversal occurs at residue 9, a novel feature that appears to be the consequence of a C-(HO)-O-... hydrogen bond between residue 4 (CH)-H-alpha and residue 9 CO groups. The structures of peptides 3 and 4, which lack the pro R hydrogen at the C-alpha atom of residue 4, are dramatically different. Peptide 3 adopts a right-handed helical conformation over the 1 to 7 segment. Residues 8 and 9 adopt at conformations forming a C-terminus type I' beta-turn, corresponding to an incipient left-handed twist of the polypeptide chain. In peptide 4, helix termination occurs at Aib(6), with residues 6 to 9 forming a left-handed helix, resulting in a structure that accommodates direct fusion of two helical segments of opposite twist. Peptides 3 and 4 provide examples of chiral residues occurring in the less favored sense of helical twist; (D)Ala(4) in peptide 3 adopts an alpha(R) conformation, while (L)Val(7) in 4 adopts an alpha(L) conformation. The structural comparison of the decapeptides reported here provides evidence for the role of specific C-(HO)-O-... hydrogen bonds in stabilizing chain reversals at helix termini, which may be relevant in aligning contiguous helical and strand segments in polypeptide structures.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Probing disorder in cubic pyrochlore Bi-1 Zn-5(1) Nb-0(1) O-5(7) (BZN) thin films

The dielectric response of pulsed laser ablated Bi-1 Zn-5(1) Nb-0(1) O-5(7) (BZN) thin films are investigated within the temperature range of 300-660 K and frequency range of 100 Hz-100 kHz Thin film exhibited a strong dielectric relaxation behavior A sharp rise in dielectric constant of BZN thin film at high temperatures is related to disorder in canon and anion lattices Observed dielectric relaxation implies a redistribution of charges within the unit cell This phenomenon suggests that the large change in dielectric constant is due to a dynamical rise of dipolar fluctuations in the unit cell XPS spectra of BZN (A(2)B(2)O(6)O') cubic pyrochlore confirm that the relaxation corresponds to the ionic hopping among the A and O' positions of several local potential minima Barrier height for hopping is distributed between 0 and 0 94 eV The O is spectrum confirms presence of two types of oxygen in BZN thin film The disorder in charge neutralized thin film is correlated with XPS spectra (C) 2010 Elsevier Ltd All rights reserved

Probing of unusual DNA structures in topologically constrained form V DNA: use of restriction enzymes as structural probe

The ability of DNA sequences to adopt unusual structures under the superhelical torsional stress has been studied. Sequences that are forced to adopt unusual conformation in topologically constrained pBR322 form V DNA (Lk=0) were mapped using restriction enzymes as probes. Restriction enzymes such as BamHI, Pstl, Aval and HindIII could not cleave their recognition sequences. The removal of topological constraint relieved this inhibition. The influence of neighbouring sequences on the ability of a given sequence to adopt unusual DNA structure, presumably left handed Z conformation, was studied through single hit analysis. Using multiple cut restriction enzymes such as Narl and Fspl, it could be shown that under identical topological strain, the extent of structural alteration is greatly influenced by the neighbouring sequences. In the light of the variety of sequences and locations that could be mapped to adopt non-6 conformation in pBR322 form V DNA, restriction enzymes appear as potential structural probes for natural DNA sequences.