Generation Function Research Articles

Investigating Artificial Cells’ Spatial Proliferation with a Gene Regulatory Network

This paper discusses the combination of a Gene Regulatory Network (GRN) with a Genetic Algorithm (GA) in the context of spatial proliferation of artificial and dynamical cells. It gives the first steps in constructing and investigating simple ways of self-adaptation to furnish lifelike behaving cells. We are thus interested in growing an adaptive cells population in respect to environmental conditions. From a single cell, evolving on some nutriment field, we obtain relatively complex shapes, and functions, acquired with a GA. In a previous work, the artificial cells have been implemented with physical primitives for motion (in order to move correctly in space by convection and diffusion dynamics). The main goal of this current work is therefore to implement, for these physically moving cells, an embedded mechanism providing them with decisions capacities when it comes to choose the suitable “biological” routines (mitosis, apoptosis, migration…) depending on nutriment conjuncture. To that end, we use a “protein-based” GRN, "easily" evolvable to achieve adequate behavior in response to environment inputs. In order to build such a GRN, we start from random GRNs, train them using a GA with a generic nutriment field and different fitness functions, and finally we run the obtained evolved GRN in different nutriment fields to test the robustness of our self-adaption structure.

On the characterisation of a generic hardening model beyond the onset of necking

Abstract Finite element model updating is an inverse method which enables to arrive at a complete solution for the diffuse necking of a thick tensile specimen. The method relies on the characterization of a phenomenological strain hardening model. Therefore, the method’s accuracy is limited due to the predefined character of the analytical function. Consequently, identifying a generic strain hardening model is proposed in this work. First, different possible generic functions to characterize the actual strain hardening behaviour of a material have been scrutinized. Next, the optimal identification procedure has been examined whereof finally, the flexibility of the model has been probed.

複合システムにおける基本機能の数理的基礎付け

複合システムにおける基本機能の数理的基礎付け

MsBP: An R Package to Perform Bayesian Nonparametric Inference Using Multiscale Bernstein Polynomials Mixtures

msBP is an R package that implements a new method to perform Bayesian multiscale nonparametric inference introduced by Canale and Dunson (2016). The method, based on mixtures of multiscale beta dictionary densities, overcomes the drawbacks of Pólya trees and inherits many of the advantages of Dirichlet process mixture models. The key idea is that an infinitely-deep binary tree is introduced, with a beta dictionary density assigned to each node of the tree. Using a multiscale stick-breaking characterization, stochastically decreasing weights are assigned to each node. The result is an infinite mixture model. The package msBP implements a series of basic functions to deal with this family of priors such as random densities and numbers generation, creation and manipulation of binary tree objects, and generic functions to plot and print the results. In addition, it implements the Gibbs samplers for posterior computation to perform multiscale density estimation and multiscale testing of group differences described in Canale and Dunson (2016).

Single-supplier single-manufacturer multi-retailer consignment policy for retailers’ generalized demand distributions

Most existing publications regarding the supply chain (SC) have concentrated on two-tier models that include the vendor and the buyer. In reality, SC systems are more multifaceted and consist of at least three parties: supplier, manufacturer, and retailer. This study presents a manufacturer managed consignment policy (CP) model for a three-tier supply chain involving a single supplier, a single manufacturer, and multiple retailers. We also present a traditional policy (TP) model considering similar circumstances for a comparative study. In these models, we consider that retailers’ demands are random variables following generic probability density functions. The manufacturer collects raw materials from the supplier to produce finished goods, and then delivers the finished items to the retailers depending upon the retailers’ demand. These are profit maximizing models. We present techniques for solving these problems. We demonstrate the potential significance of the proposed models using comparative studies based on three numerical example problems. We found that all SC members earned increased profits under CP when compared with TP, and that the three-tier consignment is better than the two-tier consignment. We also analyzed the retail price markdown.

III–V-on-Si Photonic Crystal Nanocavity Laser Technology for Optical Static Random Access Memories

Heterogeneous integration of III-V semiconductors on silicon has gained considerable momentum fueled by the need to implement fully functional photonic devices and circuits in a CMOS compatible platform. In this communication, we report on a III-V photonic crystal (PhC) nanocavity, heterogeneously integrated on a silicon-on-insulator platform, to form a PhC nanocavity laser capable of exhibiting two elementary static random access memory (SRAM) cell functions individually, namely switching and latching operations under a high-speed, bit-level regime. As such, the PhC nanocavity laser is examined as a generic logic functions building block, suitable toward multiGb/s energy-efficient, optical SRAM cells with minimal device footprint. The proposed device occupies a total area of only 6.2 μm2 , rendering in this way the demonstrated memory element the smallest among the integrated optical memories presented so far. Bit-level SRAM cell operation requires two elementary functions: the access gate (AG) switching function and set-reset flip-flop (SR-FF) latching function. At first, AG switching operation is evaluated through successful wavelength conversion at 10 Gb/s, revealing a power penalty of 1 dB at 10–9 BER and a switching energy of only 4.8 fJ/bit. Then, fully functional SR-FF memory operation is successfully demonstrated, exhibiting error-free operation with negative power penalty at 5 Gb/s and switching energies of 6.4 fJ/bit. FF operation at higher speeds of 10 Gb/s with reduced switching energy levels of 3.2 fJ/bit is also experimentally investigated. Both logic operations were demonstrated separately with the same PhC nanocavity laser device exhibiting <50 ps switching times and evaluated under real-type data traffic patterns, raising expectations for beyond 20 Gb/s capabilities toward implementing energy-efficient, ultracompact and high-speed true optical SRAM setups for Datacom applications.

The CptnHook Profiler - A tool to investigate usage patterns of mathematical functions.

Transcendental mathematical functions are one of the main hot-spots of scientific applications. The usage of highly optimised, general purpose mathematical libraries can mitigate this issue. On the other hand, a more comprehensive solution is represented by the replacement of the generic mathematical functions by specific implementations targeting particular subdomains only.CptnHook is a tool that helps achieving this goal allowing to monitor the input values of mathematical functions used in a given application, categorised according to the stacktraces leading to their invocations. In this contribution we describe the design of CptnHook, the data format of its profile and how it is possible to perform measurements without instrumenting the users code and imposing the need of recompilation.We demonstrate that this approach scales on production workflows of LHC experiments and characterise a set of real life measurements, showing where opportunities for improvement lie and how the tool can be used for advanced debugging. We also illustrate how elegant summaries of the measurements can be produced and how ROOT based analysis of the profiles can be performed.

Individualization of head-related transfer functions by the principle component analysis based on anthropometric measurements

A binaural reproduction either uses individual or generic head-related functions (HRTFs). The assessment of individual spatial high-resolution HRTF datasets is very time-consuming and requires a special measurement setup. On the other hand, a generic HRTF dataset from a dummy head can lead to localization errors such as front-back confusions and in-head localizations. In the present work, the generation of individualized HRTF datasets using the principle component analysis and multiple regression analysis from a generic HRTF dataset is discussed. The individualized HRTFs reduce the localization errors by taking individual anthropometric dimensions of the head and pinna into account. The method is applied to 48 individual HRTF datasets to determine the principal components and their weights. The anthropometric dimensions are obtained from the 3D magnetic resonance imaging scans of the 48 subjects. The focus of the work is on the number of necessary principle components with respect to the measurement grid and redundancy of anthropometric dimensions.

Sound has size: Stages of concert halls

Sabine characterized whole concert halls by ratio of volume to absorption, which devolves into a “reverberation time” of logarithmic decay of intensity of sound. These times, on the order of seconds, are generic but indeterminate functions of architecture. The critical time for human perception, the aural integration period, where perception of time (intervals) passes over to inverse time (frequencies), is two orders of magnitude shorter, and can be used to scale and define the “orchestral region” of a hall. In 25 ms sound travels 8.5 m, and 8.5 m is the wavelength of 40 Hz, near low E, the lowest orchestral note. If, by analogy with optics, 8.5 m is thought of as a “coherence length,” it affects the time domain by promoting ensemble and the frequency domain by enhancing bass tones through proximity effects. A primary property of human hearing so scales the stages of concert halls.

On the Hausdorff Distance Between the Shifted Heaviside Function and Some Generic Growth Functions

On the Hausdorff Distance Between the Shifted Heaviside Function and Some Generic Growth Functions

The Costs of Indeterminacy: How to Determine Them?

Indeterminate classifiers are cautious models able to predict more than one class in case of high uncertainty. A problem that arises when using such classifiers is how to evaluate their performances. This problem has already been considered in the case where all prediction errors have equivalent costs (that we will refer as the "0/1 costs" or accuracy setting). The purpose of this paper is to study the case of generic cost functions. We provide some properties that the costs of indeterminate predictions could or should follow, and review existing proposals in the light of those properties. This allows us to propose a general formula fitting our properties that can be used to produce and evaluate indeterminate predictions. Some experiments on the cost-sensitive problem of ordinal regression illustrate the behavior of the proposed evaluation criterion.

Mixed Wavelet Leaders Multifractal Formalism for Baire Generic Functions in a Product of Intersections of Hölder Spaces with Non-Continuous Besov Spaces

In Ben Slimane (Mediterr J Math, 13(4):1513–1533 (2016)), the second author proved that, generically in the Baire category sense, pairs of functions in \({B_{t_{1}}^{s_{1},\infty}(\mathbb{R}^m) \times B_{t_{2}}^{s_{2},\infty}(\mathbb{R}^m) }\), for \({s_{1} > \frac{m}{t_{1}}}\) and \({s_{2} > \frac{m}{t_{2}}}\), satisfy a mixed multifractal formalism based on wavelet leaders. In this paper, we extend this validity on \({(B_{t_{1}}^{s_{1},\infty}(\mathbb{R}^m) \cap C^{\gamma_{1}}(\mathbb{R}^m)) \times (B_{t_{2}}^{s_{2},\infty}(\mathbb{R}^m) \cap C^{\gamma_{2}}(\mathbb{R}^m)}\), for \({0 < \gamma_{1} < s_{1} < \frac{m}{t_{1}}}\) and \({0 < \gamma_{2} < s_{2} < \frac{m}{t_{2}}}\). The main change is that the wavelet coefficients of the saturating function which generates the residual \({G_\delta}\) set are not everywhere large enough and do not coincide everywhere with the wavelet leaders. Nevertheless, the computation of the wavelet leaders is done everywhere and allows to deduce both mixed spectra and mixed scaling function.

Evaluating Top-N queries in n-dimensional normed spaces

For the problem of processing top-N queries, the threshold algorithm (TA) is an important method in many scenarios. The model of top-N queries with TA has three characteristics: (1) the ranking function is monotone, (2) the query point is fixed, and (3) TA scans the sorted index lists unidirectionally. In many database applications, however, there are opportunities for evaluating top-N queries with arbitrary query points and generic (not necessarily monotone) ranking functions. In this paper, we propose an approach for evaluating top-N queries in n-dimensional normed spaces. Given a query point Q = (q1,…, qn) in the real vector space ℜn and a generic norm distance d as ranking function, our method employs the norm equivalence theorem in Functional Analysis so that the candidate tuples of top-N query Q with d can be obtained using the Maximum distance d∞. This method projects each qi on its corresponding axis and constructs an interval centered at qi, and then enlarges each interval bidirectionally until the n-dimensional hyperrectangle contains enough candidate tuples so that the top-N tuples are retrieved according to the given norm distance d. Extensive experiments are conducted to measure the performance of our approach for both low-dimensional and high-dimensional data.

River Basin Information System: Open Environmental Data Management for Research and Decision Making

An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project databases often refer to only one research project and are limited to specific purposes. Once implemented, those systems are often not further maintained and updated, rendering the stored information useless once the system stops operating. The River Basin Information System (RBIS) presented here is designed to fit not only the requirements of one research project, but focuses on generic functions, extensibility and standards compliance typically found in interdisciplinary environmental research. Developed throughout more than 10 years of research cooperation worldwide, RBIS is designed to manage different types of environmental data with and without spatial context together with a rich set of metadata. Beside data management and storage, RBIS provides functions for the visualization, linking, analysis and processing of different types of data to support research, decision making, result dissemination and information discovery for all kinds of users. The focus of this paper is on the description of the technical implementation and the presentation of functions. This will be complemented by an overview of example applications and experiences during RBIS development and operation.

Big Bang Bifurcation Analysis and Allee Effect in Generic Growth Functions

The main purpose of this work is to study the dynamics and bifurcation properties of generic growth functions, which are defined by the population size functions of the generic growth equation. This family of unimodal maps naturally incorporates a principal focus of ecological and biological research: the Allee effect. The analysis of this kind of extinction phenomenon allows to identify a class of Allee’s functions and characterize the corresponding Allee’s effect region and Allee’s bifurcation curve. The bifurcation analysis is founded on the performance of fold and flip bifurcations. The dynamical behavior is rich with abundant complex bifurcation structures, the big bang bifurcations of the so-called “box-within-a-box” fractal type being the most outstanding. Moreover, these bifurcation cascades converge to different big bang bifurcation curves with distinct kinds of boxes, where for the corresponding parameter values several attractors are associated. To the best of our knowledge, these results represent an original contribution to clarify the big bang bifurcation analysis of continuous 1D maps.

Λ scattering equations

The CHY representation of scattering amplitudes is based on integrals over the moduli space of a punctured sphere. We replace the punctured sphere by a double-cover version. The resulting scattering equations depend on a parameter $\Lambda$ controlling the opening of a branch cut. The new representation of scattering amplitudes possesses an enhanced redundancy which can be used to fix, modulo branches, the location of four punctures while promoting $\Lambda$ to a variable. Via residue theorems we show how CHY formulas break up into sums of products of smaller (off-shell) ones times a propagator. This leads to a powerful way of evaluating CHY integrals of generic rational functions, which we call the $\Lambda$ algorithm.

‘Quality television’ as a critical obstacle: explanation and aesthetics in television studies

The category of ‘quality television’ is familiar in its generic and evaluative functions. Less frequently examined are its implications as a framework for explaining the emergence of particular forms and instances of television fiction. This essay highlights and analyzes this aspect of ‘quality television’ discourse. It situates this discourse within television studies’ widespread tendency to account for the development and status of particular television fictions through appeal to industrial determinants and taste formations. This tendency is shown to present an obstacle to the kind of interpretive attention and response that television fictions call for, and that is needed if we are to understand why particular fictions take the precise form that they do. The essay thus stakes a claim for television studies to accord greater importance to the practice of interpretive, expressive criticism.

Adtpp: lightweight efficient safe polymorphic algebraic data types for C

SummaryAdtpp is an open‐source tool that adds support for algebraic data types (ADTs) to the C programming language. ADTs allow more precise description of program types and more robust handling of data structures than are directly supported by C. ADT definitions and other declarations are put in a file that is preprocessed by adtpp to produce a C header (‘.h’) file that can be included in C source files. The generated header file contains C type definitions, macros, and inline functions that support type‐safe construction, deconstruction, and pattern matching of ADT values while avoiding unsafe operations such as casts, and avoiding the risk of errors such as dereferencing NULL pointers and accessing inappropriate fields of unions. Values are represented efficiently, using techniques from the implementation of declarative languages. For many simple data types, the memory representation is identical to a direct implementation in C, with no loss of efficiency. For more complex types, the adtpp representation is more efficient than common C representations while preserving type safety and convenience. As an example, we present a new variation of 234‐trees that is very compact. Adtpp also supports parametric polymorphism such as defining a type ‘list of t’, where t can be any ADT, and generic functions such as length. However, polymorphic code is somewhat more verbose than for typical declarative languages, due to our reliance on the limited type checking available in C. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Soil moisture sensor calibration for organic soil surface layers

Abstract. This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the here-proposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.

Unified Approach to Thermodynamic Optimization of Generic Objective Functions in the Linear Response Regime

While many efforts have been devoted to optimizing the power output for a finite-time thermodynamic process, thermodynamic optimization under realistic situations is not necessarily concerned with power alone; rather, it may be of great relevance to optimize generic objective functions that are combinations of power, entropy production, and/or efficiency. One can optimize the objective function for a given model; generally the obtained results are strongly model dependent. However, if the thermodynamic process in question is operated in the linear response regime, then we show in this work that it is possible to adopt a unified approach to optimizing the objective function, thanks to Onsager’s theory of linear irreversible thermodynamics. A dissipation bound is derived, and based on it, the efficiency associated with the optimization problem, which is universal in the linear response regime and irrespective of model details, can be obtained in a unified way. Our results are in good agreement with previous findings. Moreover, we unveil that the ratio between the stopping time of a finite-time process and the optimized duration time plays a pivotal role in determining the corresponding efficiency in the case of linear response.