Evolutionary multi-stage financial scenario tree generation

Multi-stage financial decision optimization under uncertainty depends on a careful numerical approximation of the underlying stochastic process, which describes the future returns of the selected assets or asset categories. Various approaches towards an optimal generation of discrete-time, discrete-state approximations (represented as scenario trees) have been suggested in the literature. In this paper, a new evolutionary algorithm to create scenario trees for multi-stage financial optimization models will be presented. Numerical results and implementation details conclude the paper

Four-quark flux distribution and binding in lattice SU(2)

The full spatial distribution of the color fields of two and four static quarks is measured in lattice SU(2) field theory at separations up to 1 fm at beta=2.4. The four-quark case is equivalent to a qbar q qbar q system in SU(2) and is relevant to meson-meson interactions. By subtracting two-body flux tubes from the four-quark distribution we isolate the flux contribution connected with the four-body binding energy. This contribution is further studied using a model for the binding energies. Lattice sum rules for two and four quarks are used to verify the results.Comment: 46 pages including 71 eps figures. 3D color figures are available at www.physics.helsinki.fi/~ppennane/pics

Existence of solutions in non-convex dynamic programming and optimal investment

We establish the existence of minimizers in a rather general setting of dynamic stochastic optimization in finite discrete time without assuming either convexity or coercivity of the objective function. We apply this to prove the existence of optimal investment strategies for non-concave utility maximization problems in financial market models with frictions, a first result of its kind. The proofs are based on the dynamic programming principle whose validity is established under quite general assumptions. © 2016 Springer-Verlag Berlin Heidelber

Diversity of actin architecture in human osteoclasts: Network of curved and branched actin supporting cell shape and intercellular micrometer level tubes

Osteoclasts are multinucleated bone-resorbing cells with a dynamic actin cytoskeleton. Osteoclasts are derived from circulating mononuclear precursors. Confocal and stimulated emission depletion (STED) super-resolution microscopy was used to investigate peripheral blood-derived human osteoclasts cultured on glass surfaces. STED and confocal microscopy demonstrated that the actin was curved and branched, for instance, in the vicinity of membrane ruffles. The overall architecture of the curved actin network extended from the podosomes to the top of the cell. The other novel finding was that a micrometer-level tube containing actin bridged the osteoclasts well above the level of the culture glass. The actin filaments of the tubes originated from the network of curved actin often surrounding a group of nuclei. Furthermore, nuclei were occasionally located inside the tubes. Our findings demonstrated the accumulation of c-Src, cortactin, cofilin, and actin around nuclei suggesting their role in nuclear processes such as the locomotion of nuclei. ARP2/3 labeling was abundant at the substratum level of osteoclasts and in the branched actin network, where it localized to the branching points. We speculate that the actin-containing tubes of osteoclasts may provide a means of transportation of nuclei, e.g., during the fusion of osteoclasts. These novel findings can pave the way for future studies aiming at the elucidation of the differentiation of multinucleated osteoclasts.</p

In vitro model of bone to facilitate measurement of adhesion forces and super-resolution imaging of osteoclasts

To elucidate processes in the osteoclastic bone resorption, visualise resorption and related actin reorganisation, a combination of imaging technologies and an applicable in vitro model is needed. Nanosized bone powder from matching species is deposited on any biocompatible surface in order to form a thin, translucent, smooth and elastic representation of injured bone. Osteoclasts cultured on the layer expressed matching morphology to ones cultured on sawed cortical bone slices. Resorption pits were easily identified by reflectance microscopy. The coating allowed actin structures on the bone interface to be visualised with super-resolution microscopy along with a detailed interlinked actin networks and actin branching in conjunction with V-ATPase, dynamin and Arp2/3 at actin patches. Furthermore, we measured the timescale of an adaptive osteoclast adhesion to bone by force spectroscopy experiments on live osteoclasts with bone-coated AFM cantilevers. Utilising the in vitro model and the advanced imaging technologies we localised immunofluorescence signals in respect to bone with high precision and detected resorption at its early stages. Put together, our data supports a cyclic model for resorption in human osteoclasts.</p

Tadpole-improved SU(2) lattice gauge theory

A comprehensive analysis of tadpole-improved SU(2) lattice gauge theory is made. Simulations are done on isotropic and anisotropic lattices, with and without improvement. Two tadpole renormalization schemes are employed, one using average plaquettes, the other using mean links in Landau gauge. Simulations are done with spatial lattice spacings $a_s$ in the range of about 0.1--0.4 fm. Results are presented for the static quark potential, the renormalized lattice anisotropy $a_t/a_s$ (where $a_t$ is the ``temporal'' lattice spacing), and for the scalar and tensor glueball masses. Tadpole improvement significantly reduces discretization errors in the static quark potential and in the scalar glueball mass, and results in very little renormalization of the bare anisotropy that is input to the action. We also find that tadpole improvement using mean links in Landau gauge results in smaller discretization errors in the scalar glueball mass (as well as in the static quark potential), compared to when average plaquettes are used. The possibility is also raised that further improvement in the scalar glueball mass may result when the coefficients of the operators which correct for discretization errors in the action are computed beyond tree level.Comment: 14 pages, 7 figures (minor changes to overall scales in Fig.1; typos removed from Eqs. (3),(4),(15); some rewording of Introduction

Set optimization - a rather short introduction

Recent developments in set optimization are surveyed and extended including various set relations as well as fundamental constructions of a convex analysis for set- and vector-valued functions, and duality for set optimization problems. Extensive sections with bibliographical comments summarize the state of the art. Applications to vector optimization and financial risk measures are discussed along with algorithmic approaches to set optimization problems

Tau-Mediated Nuclear Depletion and Cytoplasmic Accumulation of SFPQ in Alzheimer's and Pick's Disease

Tau dysfunction characterizes neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Here, we performed an unbiased SAGE (serial analysis of gene expression) of differentially expressed mRNAs in the amygdala of transgenic pR5 mice that express human tau carrying the P301L mutation previously identified in familial cases of FTLD. SAGE identified 29 deregulated transcripts including Sfpq that encodes a nuclear factor implicated in the splicing and regulation of gene expression. To assess the relevance for human disease we analyzed brains from AD, Pick's disease (PiD, a form of FTLD), and control cases. Strikingly, in AD and PiD, both dementias with a tau pathology, affected brain areas showed a virtually complete nuclear depletion of SFPQ in both neurons and astrocytes, along with cytoplasmic accumulation. Accordingly, neurons harboring either AD tangles or Pick bodies were also depleted of SFPQ. Immunoblot analysis of human entorhinal cortex samples revealed reduced SFPQ levels with advanced Braak stages suggesting that the SFPQ pathology may progress together with the tau pathology in AD. To determine a causal role for tau, we stably expressed both wild-type and P301L human tau in human SH-SY5Y neuroblastoma cells, an established cell culture model of tau pathology. The cells were differentiated by two independent methods, mitomycin C-mediated cell cycle arrest or neuronal differentiation with retinoic acid. Confocal microscopy revealed that SFPQ was confined to nuclei in non-transfected wild-type cells, whereas in wild-type and P301L tau over-expressing cells, irrespective of the differentiation method, it formed aggregates in the cytoplasm, suggesting that pathogenic tau drives SFPQ pathology in post-mitotic cells. Our findings add SFPQ to a growing list of transcription factors with an altered nucleo-cytoplasmic distribution under neurodegenerative conditions

Genome sequencing and population genomic analyses provide insights into the adaptive landscape of silver birch

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Scenario trees and policy selection for multistage stochastic programming using machine learning

We propose a hybrid algorithmic strategy for complex stochastic optimization problems, which combines the use of scenario trees from multistage stochastic programming with machine learning techniques for learning a policy in the form of a statistical model, in the context of constrained vector-valued decisions. Such a policy allows one to run out-of-sample simulations over a large number of independent scenarios, and obtain a signal on the quality of the approximation scheme used to solve the multistage stochastic program. We propose to apply this fast simulation technique to choose the best tree from a set of scenario trees. A solution scheme is introduced, where several scenario trees with random branching structure are solved in parallel, and where the tree from which the best policy for the true problem could be learned is ultimately retained. Numerical tests show that excellent trade-offs can be achieved between run times and solution quality