Miracle-dz/UniFAR-FTUs huggingface dataset:
A STABLE MODELING OF LARGE PLANT ECOSYSTEMS

The focus of this paper is finding a balance of the plant density and the plant spatial distribution in visual models of large plant ecosystems. This is achieved by simulating plant competitions for resources that is sensitive to many constants and initial conditions, and can easily become unstable causing some individuals to die and the others to grow exponentially. We have found that a negative feedback can provide stability able to resolve catastrophes and unstable states. The replication and seeding cause plants of the same species to grow in clusters that guarantees visual plausibility of the resulting models.
Improvements in the survival of children and adolescents with acute lymphoblastic leukemia

Over the past 50 years, the treatment of young patients with acute lymphoblastic leukemia (ALL) has significantly improved, and is one of the success stories of cancer treatment. This success is measured by the improved survival of childhood ALL patients from less than 10% in the 1960s to more than
Alternative ways of verification and validation of computational models: A case of replication in the innovation networks.

Conventional practice in modelling requires checking that the model implementation is correct with respect to its conceptualisation (verification) and that corresponds to and explains the real world phenomenon modelled (validation). Agent-based models (ABM) have been applied in many scientific fields, but only recently researchers have started to realise that the lack of verification and validation protocols/approaches is one of the main challenges and criticisms in fully adopting the models. Verification and validation assure the external and operational validity of a model and when data for estimation is not readily available, the behaviour of the computational model cannot be operationally validated and thus, the results are ‘questionable’. Alternative approaches have recently gained increasing attention. Docking or replication of the models is one of them, based on the reflection that if different implementations of a conceptual model produce similar findings, that lends support to the models in mimicking the real world phenomenon. This paper reports on the docking experience (using fuzzy logic) and other approaches to validate an agent-based model (ABM) in the context of innovation in business networks. Using two modelling paradigms and software programs, we modelled in 18 months’ interval a network of three categories of agents (R&D organisations, venture capitalists VCs, and manufacturing companies M). The two models were developed for exploring innovation creation and change of resources in business networks. Agent-based and fuzzy logic approaches capture inter-relations between heterogeneous organisations/agents and between organisations and their environment, and cumulative network effects explain changes in the system. The organisations are autonomous and they exchange resources in a decentralised manner, the result in the system as a whole being dependent on the degree of interdependence of agents in the network.
Malarial positive image retrieval using Content Based Retrieval Systems

CBIR Systems retrieve the relevant images by using various perceptions and mathematical calculations for example size, shape and other features of various objects in the image. These systems are being largely used in various fields. Here we use them for Retrieval of malarial positive images. In this paper retrieval could be done by using image or text as a query. To achieve best performance in order to help doctors we have proposed a methodology that does annotation of images by use of ontology. Further, more the number of objects in image larger is the need to do annotation. This methodology focuses on decrease in semantic gap by use of ontology and hence leading to increase in recall and precision. The results obtained are compared with previously defined algorithms and are found to be better than them.
1 2 N ov 2 00 5 Replacing Pfaffians and applications

We present some Pfaffian identities, which are completely different from the Plücker relations. As consequences we obtain a quadratic identity for the number of perfect matchings of plane graphs, which has a simpler form than the formula by Yan et al (Graphical condensation of plane graphs: a combinatorial approach, Theoret. Comput. Sci., to appear), and we also obtain some new determinant identities.
Determinants of Economic and Accounting Components of Residual Income: An Application to the Pharmaceutical Industry

This study investigates determinants of the present value of future residual income for firms operating in the pharmaceutical industry. It is well known that residual income has both economic and accounting components. We exploit the industrial organization and competitive strategy literatures to identify general features of economic context that are likely to be related to the generation of economic profit. Applying this framework to the pharmaceutical industry, we identify product innovation, product promotion, strategic success, and operating efficiency as four determinants of the economic component of residual income and select ten accounting variables to proxy for these determinants. We then draw on prior accounting research to specify when we expect accounting rules to create period-by-period timing differences between economic profit and residual income. In the pharmaceutical industry, research and development and advertising are important activities and the accounting rules for these items are likely to systematically bias residual income relative to economic profit. We combine our analysis of economic and accounting determinants of residual income to develop industry-wide hypotheses relating the ten accounting variables to the prediction of the present value of future residual income. The results of our empirical analyses are generally consistent with these hypotheses and the explanatory power of the model is quite high. Most firms in the pharmaceutical industry offer a mix of products that span three product segments with differing economic and accounting contexts. We exploit this richness of the pharmaceutical industry to develop hypotheses for industry segment related differences in the magnitudes of the multipliers on the ten accounting variables. The results are generally consistent with our predictions that the magnitudes of these multipliers are conditioned on the firm? s product mix and that the impact of accounting bias introduced by certain accounting rules varies as predicted. We supplement the analysis of the present value of residual income with a direct examination of the explanatory power of the ten accounting variables for equity value. The explanatory power of our model is again quite high and is considerably higher than that of comparison models taken from the prior literature. Overall, our approach for considering economic and accounting contexts in the pharmaceutical industry is successful in identifying value relevant accounting data beyond earnings and beyond a simple decomposition of earnings. Key Words: Economic context; Accounting Context; Value relevance; Residual income; Abnormal earnings; Structure; conduct; Performance; Pharmaceutical industry; Industry segments; Non-financial data
Intelligence arms race: delayed reward increases complexity of agent strategies

Social brain theory hypothesizes that the human brain becomes larger through evolution mainly because of reading others' intentions in society. Reading opponents' intentions and cooperating with them or outsmarting them results in an intelligence arms race. The author discusses the evolution of such an arms race, represented as finite state automatons, under three distinct payoff schemes and the implications of these results, which suggest that agents increase complexity of their strategies.
Forward-weighted CADIS method for global variance reduction

Recent applications’ needs/desires have motivated efforts to develop approaches for optimizing Monte Carlo calculations for global distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as response at multiple localized detectors and spectra. Recent efforts at Oak Ridge National Laboratory (ORNL) have led to the development of a variation on the Consistent Adjoint Driven Importance Sampling (CADIS) method for effective global variance reduction. This method, referred to as Forward-Weighted CADIS (FW-CADIS), and an example of its application are presented in this paper. To the authors’ knowledge, this is a new method and novel use of the adjoint methodology for biasing Monte Carlo simulations. It has long been recognized that the adjoint function (i.e., the solution to the adjoint form of the Boltzmann transport equation) has physical significance [1] as a measure of the importance of a particle to some objective function (e.g., the response of a detector) and that this physical interpretation makes the adjoint function well suited for biasing Monte Carlo simulations. Accordingly, recent trends in Monte Carlo code development have reflected a recognition of the benefits of using deterministic adjoint (importance) functions for Monte Carlo variance reduction. [2] The CADIS methodology [2,3], which has been incorporated into codes such as ADVANTG [4] (based on MCNP) and the MAVRIC [5] sequence of SCALE, is being routinely used at ORNL for three-dimensional (3-D) Monte Carlo simulations of real applications. Although the CADIS methodology has proven to be very effective for automated optimization of localized quantities, until very recently, efforts to optimize global distributions have not been nearly as successful. A number of heuristic approaches, such as specification of the adjoint source (response function) throughout the problem phase space, have been tested and found to be ineffective. Specification of the adjoint source at the outer boundaries of a problem in an attempt to encourage particles to move outward through the entire system was found to be reasonably effective. Previous work by Cooper and Larsen, which used the inverted forward flux as the importance function (no adjoint calculation) in an attempt to distribute particles uniformly throughout the system has demonstrated some benefit [6]. While this approach does encourage particles toward regions of lower flux and discourage particles from moving toward regions of higher flux, the forward flux does not represent the expected contribution to the desired response, which is uniform particle density (or response) throughout the system. When applied to a large realistic application, this method was not found to be effective. Hence, a need has remained for an effective method for global variance reduction of Monte Carlo simulations.
Taxonomy of Satellite Image and Validation Using Statistical Inference

Classification of Land Use Land Cover (LULC) data from satellite images is extremely remarkable to design the thematic maps for analysis of natural resources like Forest, Agriculture, Water bodies, urban areas etc. The process of Satellite Image Classification involves grouping the pixel values into significant categories and estimating areas by counting each category pixels. Manual classification by visual interpretation technique is accurate but time consuming and requires field experts. To overcome these difficulties, the present research work investigated efficient and effective automation of satellite image classification. Automated classification approaches are broadly classified in to i) Supervised Classification ii) Unsupervised Classification iii) Object Based Classification. This paper presents classification capabilities of K-Means, Parallel Pipe and Maximum Likelihood classifiers to classify multispectral spatial data. Using statistical inference, classified results are validated with reference data collected from field experts. Among three, Maximum Likelihood classifier (MLC) inflate a extensive credit with Overall accuracy and Kappa Factor.
The Cost of Unsold Output , the Elasticity of Demand , and Prices

Abstract: When a firm must choose price and output before observing demand and therefore risks unsold output, the standard mark-up rule applies with the elasticity being the elasticity of the average quantity sold with respect to price and marginal cost being the marginal cost of an expected unit sold, computed as the marginal cost of a unit produced divided by the expected fraction of the marginal unit produced that the firm sells. The rule resolves the longstanding puzzle of why increased demand uncertainty causes output to increase with additive uncertainty and decrease with multiplicative uncertainty.
A generalized local ansatz and its effect on halo bias

Motivated by the properties of early universe scenarios that produce observationally large local non-Gaussianity, we perform N-body simulations with non-Gaussian initial conditions from a generalized local ansatz. The bispectra are schematically of the local shape, but with scale-dependent amplitude. We find that in such cases the size of the non-Gaussian correction to the bias of small and large mass objects depends on the amplitude of non-Gaussianity roughly on the scale of the object. In addition, some forms of the generalized bispectrum alter the scale dependence of the non-Gaussian term in the bias by a fractional power of k. These features may allow significant observational constraints on the particle physics origin of any observed local non-Gaussianity, distinguishing between scenarios where a single field or multiple fields contribute to the curvature fluctuations. While analytic predictions for the non-Gaussian bias agree qualitatively with the simulations, we find numerically a stronger observational signal than expected. This suggests that a more precise understanding of halo formation is needed to fully explain the consequences of primordial non-Gaussianity.
MIMO Radar with Colocated Antennas

We have provided a review of some recent results on the emerging technology of MIMO radar with colocated antennas. We have shown that the waveform diversity offered by such a MIMO radar system enables significant superiority over its phased-array counterpart, including much improved parameter identifiability, direct applicability of adaptive techniques for parameter estimation, as well as superior flexibility of transmit beampattern designs. We hope that this overview of our recent results on the MIMO radar, along with the related results obtained by our colleagues, will stimulate the interest deserved by this topic in both academia and government agencies as well as industry.
The Educational Attainment of Turkey's Labor Force: A Comparison Across Provinces and Overtime

This paper presents regional and provincial data on the educational composition of Turkey's labor force over time as well as estimates of the human capital stock measured as the average years of formal education received by the work force. The data set is comprised of the estimated human capital stock for the set of 67 provinces over the census years from 1970 to 1990. Although regional disparities have persisted, the data shows significant improvements in the educational attainment of the labor force during the past two decades.
Relativistic Accretion

A brief summary of the properties of astrophysical black holes is presented. Various modes of accretion are distinguished, corresponding to accretion at rates from well below to well above the Eddington rate. The importance of mass loss is emphasized when the accreting gas cannot radiate and it is asserted that a strong wind is likely to be necessary to carry oﬀ mass, angular momentum and energy from the accreting gas. The possible importance of the black hole spin in the formation of jets and in dictating the relative importance of non-thermal emission over thermal radiation is discussed.
Innovation, work Organisation and Systems of Social Protection

Much of the core research on the determinants of innovation traditionally has focused on the role of formal processes of R&D and on the importance of the skills and expertise of scientists and engineers with third-level education. In research on national innovation systems there has been a parallel tendency to focus on the institutions and organisations responsible for the production and diffusion of formal scientific and technical knowledge. At the level of measurement these emphases are reflected in the classic definition of innovation developed in the Oslo Manual as technical product and process innovation (TPP), and at the level of innovation policies they can be seen in the continuing importance attached to increasing national R&D intensity. More recently there have been notable efforts to widen the scope of innovation research so as to more fully take into account the role of work processes, systems of labour market protection and more generally the impact of welfare state institutions. This chapter focuses on these changes in scope and seeks to identify key challenges for researchers in innovation studies. The chapter begins by examining how work organisation has been analysed in the developing field of innovation studies including the factors that account for the growing interest in the 2000s in measuring and analysing processes of organisational innovation. It is argued that a key challenge still facing researchers in innovation studies is developing an adequate understanding of the interdependencies between work organisation and processes of technical change and innovation. The chapter then turns to the analysis of national systems, arguing that there is a need for developing more robust typologies of innovation systems that integrate the role of labour market and welfare state institutions. A related challenge is developing multi-level governance frameworks that serve to clarify the interconnections between these social institutions at the levels of nations and regions. The chapter concludes by discussing the obstacles to putting work organisation and organisational innovation more firmly on the EU policy agenda.
Sectoral Structure and Economic Growth

The main goal of the present work is to reveal the advantages of introducing the socalled structural coefficient (SC) into economic analysis. SC is defined as an indicator of the similarity between a given sectoral structure and another, which is admitted as a referential. Consequently, the paper is organized as follows. The first chapter is consecrated to computational formulas applicable to the estimation of such a measure. Ten possible algorithms are examined and five are retained as adequate for empirical investigations. The second chapter discusses, by using WB Statistics for the World Economy, two important questions concerning the structural coefficient (SC): “Is SC an authentic “numeraire”? and “Can SC be rather considered as an “attractor”? ”. The paper inclines towards the second supposition. In the third chapter, on the famous binomial “sectoral structure-economic growth”, comments based on analytical valences of the structural coefficient (SC) are provided. With this aim, the Toda–Yamamoto version of Granger causality test is applied. Several conclusions and further research lines end the paper. The necessary statistical appendices and references are included.
Extracting the comparative relations for mobile reviews

This paper devotes the research on the comparative reviews in the field of mobiles. For the comparative reviews, the study builds a comparative feature lexicon and a superlative feature lexicon, and then classifies the words in the comparative feature lexicon according to their polarities. During the extracting, an identifying method based on the naming characteristics is proposed for the comparative entities. For the comparative results, the study constructs 6 extracting patterns to apply to the comparative reviews. Finally, a formula is given to calculate the comparative result. The experimental results demonstrate the feasibility of this method.
Spatiotemporal filtering for ultrasound images

The lesion detectability by using ultrasound images is reduced by a factor of eight due to the presence of noise hampering the perception and extraction of fine details. Speckle noise occurrence is often undesirable, since it affects the tasks of human interpretation and diagnosis. The speckle is a random multiplicative noise caused by signals with different phase relations received from many sub-scatterers. It is a random mottling of the image with bright and dark spots, which obscures fine details. Speckle filtering is thus a critical pre-processing step in medical ultrasound imagery, provided that the features of interest for diagnosis are not lost. A new speckle reduction method is proposed for medical ultrasound imaging. It is based on temporal and spatial image filtering by a combination of two methods, Wavelet and diffusion transform. The method has two steps: the first one uses Wavelet transform in order to enhance the image contrast. The second step is based on nonlinear model-anisotropic complex diffusion filtering, because the human visual perception mechanism has nonlinear characteristics. As real images, the thyroid ultrasound images obtained by using a 5 MHz linear transducer were investigated. The diffusion coefficient was evaluated from the local pixel values, and wavelet shrinkage denoising used soft thresholding. Both subjective and objective evaluations of the experimental results show better performance of the proposed method in improving the signal to noise ratio compared to the conventional filtering methods.
Weak Larval Competition between the Invasive Mosquito Aedes Japonicus Japonicus (Diptera: Culicidae) and Three Resident Container-Inhabiting Mosquitoes in the Laboratory

ABSTRACT The spread of exotic mosquito species into new environments can introduce shifts in mosquito populations and potentially alter public health risks to mosquito-borne diseases. The successful establishment of exotic species may occur due to their competitive advantage over other cohabitating species. We hypothesized that the recently introduced exotic mosquito Aedes japonicus japonicus (Theobald) would be a more effective competitor than Aedes atropalpus (Coquillett) and Aedes triseriatus (Say), and an equal competitor to Culex pipiens (L.) based on larval abundance data within tire habitats. Impacts of competition were measured using the larval developmental rate and survival of larvae, adult mortality, wing length, and sex ratio. We found that intraspecific competition acted strongest against Ae. japonicus versus the other three resident mosquito species by delaying larval development and increasing adult mortality. Interspecific competition was generally weak and significant main effects were only detected for species and density. Overall, our results show that larval competition between Ae. japonicus and the three resident species was weak when present, indicating that other ecological or behavioral factors may be influencing the invasion success for Ae. japonicus in North America.