On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Action observation and robotic agents: learning and anthropomorphism

The ‘action observation network’ (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements.

Does regional infrastructure investment stimulate extra housing and commercial building supply? Long-run evidence across the English regions

This paper uses long-term regional construction data to investigate whether increases infrastructure investment in the English regions leads to subsequent rises in housebuilding and new commercial property, using time series modeling. Both physical (roads and harbours) and social infrastructure (education and health) impacts are investigated across nine regions in England. Significant effects for physical infrastructure are found across most regions and, also, some evidence of a social infrastructure effect. The results are not consistent across regions, which may be due to geographical differences and to network and diversionary effects. However, the results do suggest that infrastructure does have some impact but follows differential lag structures. These results provide a test of the hypothesis of the economic benefits of infrastructure investment in an approach that has not been used before.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

Narratives of grassroots innovations: a comparison of voluntary simplicity and the transition movement in Italy

Grassroots innovations (GI) are promising examples of deliberate transformation of socio-technical systems towards resilience and sustainability. However, evidence is needed on the factors that limit or enable their success. This paper set out to study how GI use narratives to empower innovation in the face of incumbent socio-technical regimes. Institutional documents were comparatively analyzed to assess how the narratives influence the structure, form of action and external interactions of two Italian grassroots networks, Bilanci di Giustizia and Transition Network Italy. The paper finds an internal consistency between narratives and strategies for each of the two networks. The paper also highlights core similarities, but also significant differences in the ethical basis of the two narratives, and in the organizations and strategies. Such differences determine different forms of innovation empowerment and expose the niche to different potentials to transform incumbent regimes, or to the risk of being co-opted by them.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.

Norepinephrine ignites local hot spots of neuronal excitation: how arousal amplifies selectivity in perception and memory

Arousal sometimes enhances and sometimes impairs perception and memory. In our Glutamate Amplifies Noradrenergic Effects (GANE) model, glutamate at active synapses interacts with norepinephrine released by the locus coeruleus to create local ‘hot spots’ of activity that enable the selective effects of arousal. This hot spot mechanism allows local cortical regions to self-regulate norepinephrine release based on current activation levels. In turn, hot spots bias global energetic delivery and functional network connectivity to enhance processing of high priority representations and impair processing of lower priority representations.

Factors affecting dairy farmers' attitudes towards antimicrobial medicine usage in cattle in England and Wales

There has been growing concern about bacterial resistance to antimicrobials in the farmed livestock sector. Attention has turned to sub-optimal use of antimicrobials as a driver of resistance. Recent reviews have identified a lack of data on the pattern of antimicrobial use as an impediment to the design of measures to tackle this growing problem. This paper reports on a study that explored use of antibiotics by dairy farmers and factors influencing their decision-making around this usage. We found that respondents had either recently reduced their use of antibiotics, or planned to do so. Advice from their veterinarian was instrumental in this. Over 70% thought reducing antibiotic usage would be a good thing to do. The most influential source of information used was their own veterinarian. Some 50% were unaware of the available guidelines on use in cattle production. However, 97% thought it important to keep treatment records. The Theory of Planned Behaviour was used to identify dairy farmers’ drivers and barriers to reduce use of antibiotics. Intention to reduce usage was weakly correlated with current and past practice of antibiotic use, whilst the strongest driver was respondents’ belief that their social and advisory network would approve of them doing this. The higher the proportion of income from milk production and the greater the chance of remaining in milk production, the significantly higher the likelihood of farmers exhibiting positive intention to reduce antibiotic usage. Such farmers may be more commercially minded than others and thus more cost-conscious or, perhaps, more aware of possible future restrictions. Strong correlation was found between farmers’ perception of their social referents’ beliefs and farmers’ intent to reduce antibiotic use. Policy makers should target these social referents, especially veterinarians, with information on the benefits from, and the means to, achieving reductions in antibiotic usage. Information on sub-optimal use of antibiotics as a driver of resistance in dairy herds and in humans along with advice on best farm practice to minimise risk of disease and ensure animal welfare, complemented with data on potential cost savings from reduced antibiotic use would help improve poor practice.

Internal nanoparticle structure of temperature-responsive self-assembled PNIPAM-b-PEG-b-PNIPAM triblock copolymers in aqueous solutions: NMR, SANS and light scattering studies

In this study we report detailed information on the internal structure of PNIPAM-b-PEG-b-PNIPAM nanoparticles formed from self-assembly in aqueous solutions upon increase in temperature. NMR spectroscopy, light scattering and small-angle neutron scattering (SANS) were used to monitor different stages of nanoparticle formation as a function of temperature, providing insight into the fundamental processes involved. The presence of PEG in a copolymer structure significantly affects the formation of nanoparticles, making their transition to occur over a broader temperature range. The crucial parameter that controls the transition is the ratio of PEG/PNIPAM. For pure PNIPAM, the transition is sharp; the higher the PEG/PNIPAM ratio results in a broader transition. This behavior is explained by different mechanisms of PNIPAM block incorporation during nanoparticle formation at different PEG/PNIPAM ratios. Contrast variation experiments using SANS show that the structure of nanoparticles above cloud point temperatures for PNIPAM-b-PEG-b-PNIPAM copolymers is drastically different from the structure of PNIPAM mesoglobules. In contrast with pure PNIPAM mesoglobules, where solid-like particles and chain network with a mesh size of 1-3 nm are present; nanoparticles formed from PNIPAM-b-PEG-b-PNIPAM copolymers have non-uniform structure with “frozen” areas interconnected by single chains in Gaussian conformation. SANS data with deuterated “invisible” PEG blocks imply that PEG is uniformly distributed inside of a nanoparticle. It is kinetically flexible PEG blocks which affect the nanoparticle formation by prevention of PNIPAM microphase separation.

SEM and Neurohistological Observations of Nerve Endings in the Middle Region of the Tongue of the Collared Peccary (Tayassu tajacu): A Silver Impregnation Method

The presence of lingual papillae and the nerve endings in the middle region of the tongue mucosa of collared peccary (Tayassu tajacu) were studied using scanning electron microscopy and light microscopy, based upon the silver impregnation method. The middle region of tongue mucosa revealed numerous filiform and fungiform papillae. The thick epithelial layer showed epithelial cells and a dense connective tissue layer containing nerve fibre bundles and capillaries. The sensory nerve endings, intensely stained by silver impregnation, were usually non-encapsulated and extended into the connective tissue of the filiform and fungiform papillae very close to the epithelial cells. In some regions, the sensory nerves fibres formed a dense and complex network of fine fibrils. The presence of these nerve fibrils may characterize the mechanisms of transmission of sensitive impulses to the tongue mucosa.

Early Phase of Allergic Airway Inflammation in Diabetic Rats: Role of Insulin on the Signaling Pathways and Mediators

Background: Allergic lung inflammation is impaired in diabetic rats and is restored by insulin treatment. In the present study we investigated the effect of insulin on the signaling pathways triggered by allergic inflammation in the lung and the release of selected mediators. Methods: Diabetic male Wistar rats (alloxan, 42 mg/kg, i.v., 10 days) and matching controls were sensitized by s.c. injections of ovalbumin (OA) in aluminium hydroxide, 14 days before OA (1 mg/0.4 ml) or saline intratracheal challenge. A group of diabetic rats were treated with neutral protamine Hagedorn insulin (NPH, 4 IU, s.c.), 2 h before the OA challenge. Six hours after the challenge, bronchoalveolar lavage (BAL) was performed for mediator release and lung tissue was homogenized for Western blotting analysis of signaling pathways. Results: Relative to non-diabetic rats, the diabetic rats exhibited a significant reduction in OA-induced phosphorylation of the extracellular signal-regulated kinase (ERK, 59%), p38 (53%), protein kinase B (Akt, 46%), protein kinase C (PKC)-alpha (63%) and PKC-delta (38%) in lung homogenates following the antigen challenge. Activation of the NF-kappa B p65 subunit and phosphorylation of I kappa B alpha were almost suppressed in diabetic rats. Reduced expression of inducible nitric oxide synthase (iNOS, 32%) and cyclooxygenase-2 (COX-2, 46%) in the lung homogenates was also observed. The BAL concentration of prostaglandin (PG)-E(2), nitric oxide (NO) and interleukin (IL)-6 was reduced in diabetic rats (74%, 44% and 65%, respectively), whereas the cytokine-induced neutrophil chemoattractant (CINC)-2 concentration was not different from the control animals. Treatment of diabetic rats with insulin completely or partially restored all of these parameters. This protocol of insulin treatment only partially reduced the blood glucose levels. Conclusion: The data presented show that insulin regulates MAPK, PI3K, PKC and NF-kappa B pathways, the expression of the inducible enzymes iNOS and COX-2, and the levels of NO, PGE(2) and IL-6 in the early phase of allergic lung inflammation in diabetic rats. It is suggested that insulin is required for optimal transduction of the intracellular signals that follow allergic stimulation. Copyright (C) 2010 S. Karger AG, Basel

Borlänge and Falun Brundtland cities

Development of an infrastructure for Brundtland Renewable Energy Network - BREN is a European Commission Alterner Project with Contract no XVII/4. 1030/Z96-032.The project has its origin in the UN-report “Our Common Future”, 1989. A change in and reduction of the use of energy was fundamental in order to reach the goals which the report proposed. Denmark decided on an action plan on how energy consumption could be reduced “Energi 2000 - Handlingsplan för en bäredygtig udvikling”. The ministries of energy in Denmark and Schleswig Holstein both agreed to start an energy saving project in a smaller town. The project was called “Brundtlandby” and the two first were Toftlund in South Jutland and Bredstedt in North Friesland. After a short period a further two German Cities, Rheinsberg and Viernheim, and Rajec in Slovakia joined the group. A network for the exchange of knowledge and experience between the cities was formed. The network, Brundtland City Project, inspired the participating cities in the continuing work with energy saving measures. The Brundtland City Project was presented at an international conference “Cities and Energy” in Trondheim, Norway,in December 1995. Great interest was shown in the project and it was decided that a network should be developed in northern European countries as a pilot project to be enlarged with other European countries later on. A steering committee was formed with representatives from the nordic countries.An application was sent to the European Commission, Alterner Program, and was approved in Juli 1996. The project was subdivided into nine activities. Activity 1, consisted of summarising the experiences of the Brundtland City Project in Toftlund, Denmark and the Brundtland Cities network in Slovakia, Germany and Denmark. The Scandinavian part started with Activity 2, to engage municipalities/cities in Finland, Norway and Sweden in the project. The Solar Energy Research Center, SERC, Högskolan Dalarna was appointed as co-ordinator for the Swedish part. The project was presented at a seminar on the 30th September for representatives from the municipalities of Borlänge and Falun. On the 10th of December 1996 the two municipalities accepted the invitation to join the Northern network. Pelle Helje, Borlänge Energi, has been informant for the municipality of Borlänge and Anders Goop, Department of Urban Planninginformant for the municipality of Falun with Jan Kaans, Estates department providing information to the basis for the Newsletter.Reports on the work in Borlänge and Falun municipalities have been made to Brundtland Center Denmark on three occasions; Activities 2-5, 16-12-1997, Activities 6-7, including parts of activities 8-9, 03-03-1998, and the basis for the Newsletter, 01-07-1998. The Nordic reports have been compiled at the Brundtland Center Denmark for submission to the European Commission. English has been the common language. After the report of activities 2 - 5 the participants wereinvited to a project meeting and a workshop at Brundtland Center the 23rd and 24th March 1998.This was the first occasion the participants in the project met and the network thus took a moreconcrete form. It also was decided that the next meeting should be in Borlänge in August 1998,with Borlänge Energi and Solar Energy Research Center SERC as organisers. As BrundtlandCentre Denmark was wound up for financial reasons, the project meeting in Borlänge wascancelled.Compilation of the Final Report was carried out by Esbensen Consultants in October 1998Future development of the networkIt is intended to continue the work with the Brundtland City Network as an “EU Thermie Bproject”and the network will be enlarged with the addition of four new Brundtland Cities from Austria, Germany, Italy and Great Britain. In addition the village of Putja in Estonia will join the network but this will be financed by the EU-Phare programme.

Selective Coupling between Theta Phase and Neocortical Fast Gamma Oscillations during REM-Sleep in Mice

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

Undersampled Critical Branching Processes on Small-World and Random Networks Fail to Reproduce the Statistics of Spike Avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Uma proposição para o cálculo de mapas de disparidade de imagens estéreo usando um interpolador neural baseado em funções de base radial

This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms