Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.

The condensation and ordering of models of empty liquids

We consider a simple model consisting of particles with four bonding sites ("patches"), two of type A and two of type B, on the square lattice, and investigate its global phase behavior by simulations and theory. We set the interaction between B patches to zero and calculate the phase diagram as the ratio between the AB and the AA interactions, epsilon(AB)*, varies. In line with previous work, on three-dimensional off-lattice models, we show that the liquid-vapor phase diagram exhibits a re-entrant or "pinched" shape for the same range of epsilon(AB)*, suggesting that the ratio of the energy scales - and the corresponding empty fluid regime - is independent of the dimensionality of the system and of the lattice structure. In addition, the model exhibits an order-disorder transition that is ferromagnetic in the re-entrant regime. The use of low-dimensional lattice models allows the simulation of sufficiently large systems to establish the nature of the liquid-vapor critical points and to describe the structure of the liquid phase in the empty fluid regime, where the size of the "voids" increases as the temperature decreases. We have found that the liquid-vapor critical point is in the 2D Ising universality class, with a scaling region that decreases rapidly as the temperature decreases. The results of simulations and theoretical analysis suggest that the line of order-disorder transitions intersects the condensation line at a multi-critical point at zero temperature and density, for patchy particle models with a re-entrant, empty fluid, regime. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3657406]

Study of the one dimensional and transient bioheat transfer equation: Multi-layer solution development and applications

: In this work we derive an analytical solution given by Bessel series to the transient and one-dimensional (1D) bioheat transfer equation in a multi-layer region with spatially dependent heat sources. Each region represents an independent biological tissue characterized by temperature-invariant physiological parameters and a linearly temperature dependent metabolic heat generation. Moreover, 1D Cartesian, cylindrical or spherical coordinates are used to define the geometry and temperature boundary conditions of first, second and third kinds are assumed at the inner and outer surfaces. We present two examples of clinical applications for the developed solution. In the first one, we investigate two different heat source terms to simulate the heating in a tumor and its surrounding tissue, induced during a magnetic fluid hyperthermia technique used for cancer treatment. To obtain an accurate analytical solution, we determine the error associated with the truncated Bessel series that defines the transient solution. In the second application, we explore the potential of this model to study the effect of different environmental conditions in a multi-layered human head model (brain, bone and scalp). The convective heat transfer effect of a large blood vessel located inside the brain is also investigated. The results are further compared with a numerical solution obtained by the Finite Element Method and computed with COMSOL Multi-physics v4.1 (c). (c) 2013 Elsevier Ltd. All rights reserved.

How patchy can one get and still condense? The role of dissimilar patches in the interactions of colloidal particles

We investigate the influence of strong directional, or bonding, interactions on the phase diagram of complex fluids, and in particular on the liquid-vapour critical point. To this end we revisit a simple model and theory for associating fluids which consist of spherical particles having a hard-core repulsion, complemented by three short-ranged attractive sites on the surface (sticky spots). Two of the spots are of type A and one is of type B; the interactions between each pair of spots have strengths [image omitted], [image omitted] and [image omitted]. The theory is applied over the whole range of bonding strengths and results are interpreted in terms of the equilibrium cluster structures of the coexisting phases. In systems where unlike sites do not interact (i.e. where [image omitted]), the critical point exists all the way to [image omitted]. By contrast, when [image omitted], there is no critical point below a certain finite value of [image omitted]. These somewhat surprising results are rationalised in terms of the different network structures of the two systems: two long AA chains are linked by one BB bond (X-junction) in the former case, and by one AB bond (Y-junction) in the latter. The vapour-liquid transition may then be viewed as the condensation of these junctions and we find that X-junctions condense for any attractive [image omitted] (i.e. for any fraction of BB bonds), whereas condensation of the Y-junctions requires that [image omitted] be above a finite threshold (i.e. there must be a finite fraction of AB bonds).

Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions

The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

PRETERM BIRTH AND FETAL GROWTH RESTRICTION IN HIV-INFECTED BRAZILIAN PREGNANT WOMEN

Introduction: Maternal HIV infection and related co-morbidities may have two outstanding consequences to fetal health: mother-to-child transmission (MTCT) and adverse perinatal outcomes. After Brazilian success in reducing MTCT, the attention must now be diverted to the potentially increased risk for preterm birth (PTB) and intrauterine fetal growth restriction (IUGR). Objective: To determine the prevalence of PTB and IUGR in low income, antiretroviral users, publicly assisted, HIV-infected women and to verify its relation to the HIV infection stage. Patients and Methods: Out of 250 deliveries from HIV-infected mothers that delivered at a tertiary public university hospital in the city of Vitória, state of Espírito Santo, Southeastern Brazil, from November 2001 to May 2012, 74 single pregnancies were selected for study, with ultrasound validated gestational age (GA) and data on birth dimensions: fetal weight (FW), birth length (BL), head and abdominal circumferences (HC, AC). The data were extracted from clinical and pathological records, and the outcomes summarized as proportions of preterm birth (PTB, < 37 weeks), low birth weight (LBW, < 2500g) and small (SGA), adequate (AGA) and large (LGA) for GA, defined as having a value below, between or beyond the ±1.28 z/GA score, the usual clinical cut-off to demarcate the 10th and 90th percentiles. Results: PTB was observed in 17.5%, LBW in 20.2% and SGA FW, BL, HC and AC in 16.2%, 19.1%, 13.8%, and 17.4% respectively. The proportions in HIV-only and AIDS cases were: PTB: 5.9 versus 27.5%, LBW: 14.7% versus 25.0%, SGA BW: 17.6% versus 15.0%, BL: 6.0% versus 30.0%, HC: 9.0% versus 17.9%, and AC: 13.3% versus 21.2%; only SGA BL attained a significant difference. Out of 15 cases of LBW, eight (53.3%) were preterm only, four (26.7%) were SGA only, and three (20.0%) were both PTB and SGA cases. A concomitant presence of, at least, two SGA dimensions in the same fetus was frequent. Conclusions: The proportions of preterm birth and low birth weight were higher than the local and Brazilian prevalence and a trend was observed for higher proportions of SGA fetal dimensions than the expected population distribution in this small casuistry of newborn from the HIV-infected, low income, antiretroviral users, and publicly assisted pregnant women. A trend for higher prevalence of PTB, LBW and SGA fetal dimensions was also observed in infants born to mothers with AIDS compared to HIV-infected mothers without AIDS.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Financial depth, stock markets and economic growth in the EU-15 countries

The aim of this paper is to assess the impact of financial depth on economic growth in the EU-15 countries from 1970 until 2012, using the two-step System GMM estimator. Even though it might be expected a positive impact, the results show it is negative and sometimes even negative and statistically significant. Among the reasons presented for this, the existence of banking crises seems to better explain these results. In tranquil periods, financial deepening appears to have a positive impact, whereas in banking crises it is persistently negative and statistically significant. Also, after an assessment of the impact of stock markets on economic growth, it appears that more developed countries in the EU-15 have an economy more reliant on this segment of the financial system rather than in bank intermediation.

Research policy and endogenous growth

This paper studies the effects of different types of research policy on economic growth. We find that while tax incentives to private research, public funding of private projects, and basic research performed at public institutions have unambiguously positive effects on economic growth, performing applied research at public institutions could have negative growth effects. This is due to the large crowding out of private research caused by public R\&D when it competes with private firms in the "patent race". Concerning the effects of these policies on welfare, it is found that research policy can either improve or reduce consumer welfare depending on the characteristics of the policy and that an excessively high research subsidy will reduce it.

Nuclear factor I-C links platelet-derived growth factor and transforming growth factor beta1 signaling to skin wound healing progression.

Transforming growth factor beta (TGF-beta) and platelet-derived growth factor A (PDGFAlpha) play a central role in tissue morphogenesis and repair, but their interplay remain poorly understood. The nuclear factor I C (NFI-C) transcription factor has been implicated in TGF-beta signaling, extracellular matrix deposition, and skin appendage pathologies, but a potential role in skin morphogenesis or healing had not been assessed. To evaluate this possibility, we performed a global gene expression analysis in NFI-C(-/-) and wild-type embryonic primary murine fibroblasts. This indicated that NFI-C acts mostly to repress gene expression in response to TGF-beta1. Misregulated genes were prominently overrepresented by regulators of connective tissue inflammation and repair. In vivo skin healing revealed a faster inflammatory stage and wound closure in NFI-C(-/-) mice. Expression of PDGFA and PDGF-receptor alpha were increased in wounds of NFI-C(-/-) mice, explaining the early recruitment of macrophages and fibroblasts. Differentiation of fibroblasts to contractile myofibroblasts was also elevated, providing a rationale for faster wound closure. Taken together with the role of TGF-beta in myofibroblast differentiation, our results imply a central role of NFI-C in the interplay of the two signaling pathways and in regulation of the progression of tissue regeneration.

Factor Proportions and the Growth of World Trade

Most of the expansion of global trade during the last three decades has been of the North-South kind - between capital-abundant developed and labour-abundant developing countries. Based on this observation, I argue that the recent growth of world trade is best understood from a factor-proportions perspective. I present novel evidence documenting that differences in capital-labour ratios across countries have increased in the wake of two shocks to the global economy: i) the opening up of China and ii) financial globalisation and the resulting upstream capital flows towards capital-abundant regions. I analyse their impact on specialisation and the volume of trade in a dynamic model which combines factor-proportions trade in goods with international trade in financial assets. Calibrating this model, I find that it can account for 60% of world trade growth between 1980 and 2007. It is also capable of predicting international investment patterns which are consistent with the data

An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

Coactivated platelet-derived growth factor receptor {alpha} and epidermal growth factor receptor are potential therapeutic targets in intimal sarcoma.

Intimal sarcoma (IS) is a rare, malignant, and aggressive tumor that shows a relentless course with a concomitant low survival rate and for which no effective treatment is available. In this study, 21 cases of large arterial blood vessel IS were analyzed by immunohistochemistry and fluorescence in situ hybridization and selectively by karyotyping, array comparative genomic hybridization, sequencing, phospho-kinase antibody arrays, and Western immunoblotting in search for novel diagnostic markers and potential molecular therapeutic targets. Ex vivo immunoassays were applied to test the sensitivity of IS primary tumor cells to the receptor tyrosine kinase (RTK) inhibitors imatinib and dasatinib. We showed that amplification of platelet-derived growth factor receptor α (PDGFRA) is a common finding in IS, which should be considered as a molecular hallmark of this entity. This amplification is consistently associated with PDGFRA activation. Furthermore, the tumors reveal persistent activation of the epidermal growth factor receptor (EGFR), concurrent to PDGFRA activation. Activated PDGFRA and EGFR frequently coexist with amplification and overexpression of the MDM2 oncogene. Ex vivo immunoassays on primary IS cells from one case showed the potency of dasatinib to inhibit PDGFRA and downstream signaling pathways. Our findings provide a rationale for investigating therapies that target PDGFRA, EGFR, or MDM2 in IS. Given the clonal heterogeneity of this tumor type and the potential cross-talk between the PDGFRA and EGFR signaling pathways, targeting multiple RTKs and aberrant downstream effectors might be required to improve the therapeutic outcome for patients with this disease.