The Golden Mean, the Arab Spring and a 10-step analysis of American economic history

The Long-Wave theories of Nikolai Kondratiev and others claim to find mathematic waves in economic and other social data which are at present in dispute. Currently the theory is considered outside the scope of mainstream economics under several rationales. Despite the lack of mainstream acceptance, we make a strong case for the existence of long waves in the Real GNP of the United States with a 56 year cycle. Our analysis bypasses many of the issues cited by Long-Wave theory critics and in fact clarifies the mathematical structure of the theory.Real GNP; Golden Mean; Fibonacci Series; Arab Spring; Phi; Long Wave; Long Cycle; Kondratiev Wave; Economic Forecasting; Economic Model; Global Financial Crisis; Constitutional Law; American Economic History; Revolution; Consolidation; GNP Spiral; Okun's Law; “The Great Moderation”

Profitable Scheduling on Multiple Speed-Scalable Processors

We present a new online algorithm for profit-oriented scheduling on multiple speed-scalable processors. Moreover, we provide a tight analysis of the algorithm's competitiveness. Our results generalize and improve upon work by \textcite{Chan:2010}, which considers a single speed-scalable processor. Using significantly different techniques, we can not only extend their model to multiprocessors but also prove an enhanced and tight competitive ratio for our algorithm. In our scheduling problem, jobs arrive over time and are preemptable. They have different workloads, values, and deadlines. The scheduler may decide not to finish a job but instead to suffer a loss equaling the job's value. However, to process a job's workload until its deadline the scheduler must invest a certain amount of energy. The cost of a schedule is the sum of lost values and invested energy. In order to finish a job the scheduler has to determine which processors to use and set their speeds accordingly. A processor's energy consumption is power \Power{s} integrated over time, where \Power{s}=s^{\alpha} is the power consumption when running at speed $s$. Since we consider the online variant of the problem, the scheduler has no knowledge about future jobs. This problem was introduced by \textcite{Chan:2010} for the case of a single processor. They presented an online algorithm which is $\alpha^{\alpha}+2e\alpha$-competitive. We provide an online algorithm for the case of multiple processors with an improved competitive ratio of $\alpha^{\alpha}$.Comment: Extended abstract submitted to STACS 201

Identification of a system required for the functional surface localization of sugar binding proteins with class III signal peptides in Sulfolobus solfataricus

The hyperthermophilic archaeon Sulfolobus solfataricus contains an unusual large number of sugar binding proteins that are synthesized as precursors with a class III signal peptide. Such signal peptides are commonly used to direct archaeal flagellin subunits or bacterial (pseudo)pilins into extracellular macromolecular surface appendages. Likewise, S. solfataricus binding proteins have been suggested to assemble in higher ordered surface structures as well, tentatively termed the bindosome. Here we show that S. solfataricus contains a specific system that is needed for the functional surface localization of sugar binding proteins. This system, encoded by the bas (bindosome assembly system) operon, is composed of five proteins: basABC, three homologues of so-called bacterial (pseudo)pilins; BasE, a cytoplasmic ATPase; and BasF, an integral membrane protein. Deletion of either the three (pseudo)pilin genes or the basEF genes resulted in a severe defect of the cells to grow on substrates which are transported by sugar binding proteins containing class III signal peptides, while growth on glucose and maltose was restored when the corresponding genes were reintroduced in these cells. Concomitantly, ΔbasABC and ΔbasEF cells were severely impaired in glucose uptake even though the sugar binding proteins were normally secreted across the cytoplasmic membrane. These data underline the hypothesis that the bas operon is involved in the functional localization of sugar binding proteins at the cell surface of S. solfataricus. In contrast to surface structure assembly systems of Gram-negative bacteria, the bas operon seems to resemble an ancestral simplified form of these machineries.

Application of boundary integral equations to elastoplastic problems

The application of boundary integral equations to elastoplastic problems is reviewed. Details of the analysis as applied to torsion problems and to plane problems is discussed. Results are presented for the elastoplastic torsion of a square cross section bar and for the plane problem of notched beams. A comparison of different formulations as well as comparisons with experimental results are presented

Computer program for calculating laminar, transitional, and turbulent boundary layers for a compressible axisymmetric flow

Finite-difference computer program calculates viscous compressible boundary layer flow over either planar or axisymmetric surfaces. Flow may be initially laminar and progress through transitional zone to fully turbulent flow, or it may remain laminar, depending on imposed boundary conditions, laws of viscosity, and numerical solution of momentum and energy equations

Sound radiation from a high speed axial flow fan due to the inlet turbulence quadrupole interaction

A formula is obtained for the total acoustic power spectra radiated out the front of the fan as a function of frequency. The formula involves the design parameters of the fan as well as the statistical properties of the incident turbulence. Numerical results are calculated for values of the parameters in the range of interest for quiet fans tested at the Lewis Research Center. As in the dipole analysis, when the turbulence correlation lengths become equal to the interblade spacing, the predicted spectra exhibit peaks around the blade passing frequency and its harmonics. There has recently been considerable conjecture about whether the stretching of turbulent eddies as they enter a stationary fan could result in the inlet turbulence being the dominant source of pure tones from nontranslating fans. The results of the current analysis show that, unless the turbulent eddies become quite elongated, this noise source contributes predominantly to the broadband spectrum

Spatial bias correction for sporadic meteors photographed in New Mexico

Spatial bias correction for sporadic meteors photographed in New Mexic

The Parameter Houlihan: a solution to high-throughput identifiability indeterminacy for brutally ill-posed problems

One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions have an advantage of being useful with particularly sparse, non-stationary clinical data. However, physiological models are often nonlinear and can have many parameters, leading to potential problems with parameter identifiability, or the ability to find a unique set of parameters that minimize forecasting error. The identifiability problems can be minimized or eliminated by reducing the number of parameters estimated, but reducing the number of estimated parameters also reduces the flexibility of the model and hence increases forecasting error. We propose a method, the parameter Houlihan, that combines traditional machine learning techniques with data assimilation, to select the right set of model parameters to minimize forecasting error while reducing identifiability problems. The method worked well: the data assimilation-based glucose forecasts and estimates for our cohort using the Houlihan-selected parameter sets generally also minimize forecasting errors compared to other parameter selection methods such as by-hand parameter selection. Nevertheless, the forecast with the lowest forecast error does not always accurately represent physiology, but further advancements of the algorithm provide a path for improving physiologic fidelity as well. Our hope is that this methodology represents a first step toward combining machine learning with data assimilation and provides a lower-threshold entry point for using data assimilation with clinical data by helping select the right parameters to estimate

Spatial Endogenous Fire Risk and Efficient Fuel Management and Timber Harvest

This paper integrates a spatial fire behavior model and a stochastic dynamic optimization model to determine the optimal spatial pattern of fuel management and timber harvest. Each years fire season causes the loss of forest values and lives in the western US. This paper uses a multi-plot analysis and incorporates uncertainty about fire ignition locations and weather conditions to inform policy by examining the role of spatial endogenous risk - where management actions on one stand affect fire risk in that and adjacent stands. The results support two current strategies, but question two other strategies, for managing forests with fire risk.Resource /Energy Economics and Policy,