Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Spatial and seasonal trends of a natural population of Biomphalaria occidentalis in northeastern Argentina

This study aims to analyze the age of a population of Biomphalaria occidentalis on a pound of Riachuelo river basin, wich is one of the three most important Middle Paraná river affluents in Corrientes province. Samples were drawn from three stations, were spatial and temporal numerical variations of the snail, as well as its relation with different environmental parameters, mainly temperature, rainfall, pH and conductivity, were analyzed. Snail abundance is given in number of individuals/hour. The differences between the three sampling stations, estimated by nonparametric tests, was nonsignificant. A relative scale to the greatest shell diameter was employed to build the age pyramids. Temporal fluctuations of snail abundance correlated negatively with the highest monthly accumulated temperatures (P < 0.05). Although different floristic compositions were observed at the three stations, no significant numerical variations were detected in B. occidentalis spatial distribution. Reproductive activity took place between March-April and November with overlapping cohort system. During summer (December-Febuary) mortality increased along with temperature and reproductive activity was not evident.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

The Accessibility City. When Transport Infrastructure Matters in Urban Spatial Structure

Suburbanization is changing the urban spatial structure and less monocentric metropolitan regions are becoming the new urban reality. Focused only on centers, most works have studied these spatial changes neglecting the role of transport infrastructure and its related location model, the “accessibility city”, in which employment and population concentrate in low-density settlements and close to transport infrastructure. For the case of Barcelona, we consider this location model and study the population spatial structure between 1991 and 2006. The results reveal a mix between polycentricity and the accessibility city, with movements away from the main centers, but close to the transport infrastructure.

Distinct expression pattern of microtubule-associated protein-2 in human oligodendrogliomas and glial precursor cells.

Microtubule-associated protein 2 (MAP2), a protein linked to the neuronal cytoskeleton in the mature central nervous system (CNS), has recently been identified in glial precursors indicating a potential role during glial development. In the present study, we systematically analyzed the expression of MAP2 in a series of 237 human neuroepithelial tumors including paraffin-embedded specimens and tumor tissue microarrays from oligodendrogliomas, mixed gliomas, astrocytomas, glioblastomas, ependymomas, as well as dysembryoplastic neuroepithelial tumors (DNT), and central neurocytomas. In addition, MAP2-immunoreactive precursor cells were studied in the developing human brain. Three monoclonal antibodies generated against MAP2A-B or MAP2A-D isoforms were used. Variable immunoreactivity for MAP2 could be observed in all gliomas with the exception of ependymomas. Oligodendrogliomas exhibited a consistently strong and distinct pattern of expression characterized by perinuclear cytoplasmic staining without significant process labeling. Tumor cells with immunoreactive bi- or multi-polar processes were mostly encountered in astroglial neoplasms, whereas the small cell component in neurocytomas and DNT was not labeled. These features render MAP2 immunoreactivity a helpful diagnostic tool for the distinction of oligodendrogliomas and other neuroepithelial neoplasms. RT-PCR, Western blot analysis, and in situ hybridization confirmed the expression of MAP2A-C (including the novel MAP2+ 13 transcript) in both oligodendrogliomas and astrocytomas. Double fluorescent laser scanning microscopy showed that GFAP and MAP2 labeled different tumor cell populations. In embryonic human brains, MAP2-immunoreactive glial precursor cells were identified within the subventricular or intermediate zones. These precursors exhibit morphology closely resembling the immunolabeled neoplastic cells observed in glial tumors. Our findings demonstrate MAP2 expression in astrocytic and oligodendroglial neoplasms. The distinct pattern of immunoreactivity in oligodendrogliomas may be useful as a diagnostic tool. Since MAP2 expression occurs transiently in migrating immature glial cells, our findings are in line with an assumed origin of diffuse gliomas from glial precursors.

Assessing the quality of alternative energy sources: Energy Return On the Investment (EROI), the metabolic pattern of societies and energy statistics

This paper presents an initial challenge to tackle the every so "tricky" points encountered when dealing with energy accounting, and thereafter illustrates how such a system of accounting can be used when assessing for the metabolic changes in societies. The paper is divided in four main sections. The first three, present a general discussion on the main issues encountered when conducting energy analyses. The last section, subsequently, combines this heuristic approach to the actual formalization of it, in quantitative terms, for the analysis of possible energy scenarios. Section one covers the broader issue of how to account for the relevant categories used when accounting for Joules of energy; emphasizing on the clear distinction between Primary Energy Sources (PES) (which are the physical exploited entities that are used to derive useable energy forms (energy carriers)) and Energy Carriers (EC) (the actual useful energy that is transmitted for the appropriate end uses within a society). Section two sheds light on the concept of Energy Return on Investment (EROI). Here, it is emphasized that, there must already be a certain amount of energy carriers available to be able to extract/exploit Primary Energy Sources to thereafter generate a net supply of energy carriers. It is pointed out that this current trend of intense energy supply has only been possible to the great use and dependence on fossil energy. Section three follows up on the discussion of EROI, indicating that a single numeric indicator such as an output/input ratio is not sufficient in assessing for the performance of energetic systems. Rather an integrated approach that incorporates (i) how big the net supply of Joules of EC can be, given an amount of extracted PES (the external constraints); (ii) how much EC needs to be invested to extract an amount of PES; and (iii) the power level that it takes for both processes to succeed, is underlined. Section four, ultimately, puts the theoretical concepts at play, assessing for how the metabolic performances of societies can be accounted for within this analytical framework.

Post-traumatic mutism in children: clinical characteristics, pattern of recovery and clinicopathological correlations.

Among the numerous clinical syndromes observed after severe traumatic head injury, post-traumatic mutism is a disorder rarely reported in adults and not studied in any detail in children. We report seven children between the ages of 3 1/2 and 14 years who sustained severe head injury and developed post-traumatic mutism. We aim to give a precise clinical characterization of this disorder, discuss differential diagnosis and correlations with brain imaging and suggest its probable neurological substrate. After a coma lasting from 5 to 25 days, the seven patients who suffered from post-traumatic mutism went through a period of total absence of verbal production lasting from 5 to 94 days, associated with the recovery of non-verbal communication skills and emotional vocalization. During the first days after the recovery of speech, all patients were able to produce correct small sentences with a hypophonic and monotonous voice, moderate dysarthria, word finding difficulties but no signs of aphasia, and preserved oral comprehension. The neurological signs in the acute phase (III nerve paresis in three of seven patients, signs of autonomic dysfunctions in five of seven patients), the results of the brain imaging and the experimental animal data all suggest the involvement of mesencephalic structures as playing a key role in the aetiology of post-traumatic mutism.

Impaired early visual response modulations to spatial information in chronic schizophrenia.

Early visual processing stages have been demonstrated to be impaired in schizophrenia patients and their first-degree relatives. The amplitude and topography of the P1 component of the visual evoked potential (VEP) are both affected; the latter of which indicates alterations in active brain networks between populations. At least two issues remain unresolved. First, the specificity of this deficit (and suitability as an endophenotype) has yet to be established, with evidence for impaired P1 responses in other clinical populations. Second, it remains unknown whether schizophrenia patients exhibit intact functional modulation of the P1 VEP component; an aspect that may assist in distinguishing effects specific to schizophrenia. We applied electrical neuroimaging analyses to VEPs from chronic schizophrenia patients and healthy controls in response to variation in the parafoveal spatial extent of stimuli. Healthy controls demonstrated robust modulation of the VEP strength and topography as a function of the spatial extent of stimuli during the P1 component. By contrast, no such modulations were evident at early latencies in the responses from patients with schizophrenia. Source estimations localized these deficits to the left precuneus and medial inferior parietal cortex. These findings provide insights on potential underlying low-level impairments in schizophrenia.

Iceberg transport technologies in spatial competition. Hotelling reborn

Transport costs in address models of differentiation are usually modeled as separable of the consumption commodity and with a parametric price. However, there are many sectors in an economy where such modeling is not satisfactory either because transportation is supplied under oligopolistic conditions or because there is a difference (loss) between the amount delivered at the point of production and the amount received at the point of consumption. This paper is a first attempt to tackle these issues proposing to study competition in spatial models using an iceberg-like transport cost technology allowing for concave and convex melting functions.

Spatial and temporal distribution of anopheline larvae in two malarious areas in Sucre State, Venezuela

The spatial and temporal distribution of anopheline larvae was studied in two coastal malarious areas of Sucre, State, Venezuela. Seven habitat types were sampled in the village of Guayana and eight species of Anopheles were collected. Anopheles aquasalis was the predominant species collected and was most abundant in the brackish marsh habitat (71 larvae per 100 samples). It was most abundant during the rainy season. At the second location, Santa F e, six habitat types were sampled and four anopheline species were collected. Habitats where An. aquasalis was most abundant were temporary freshwater ponds (34 larvae per 100 samples) and mangroves (10.5 larvae per 100 samples). At this location it was also most abundant in the rainy season. During the dry season it was collected in small numbers in river pools (1.3 larvae per 100 samples) along with large numbers of An. pseudopunctipennis (479 larvae per 100 samples). Larval control could be an important component of the malaria control program because major habitats could be defined and presence and abundance of larvae was limited to specific times of year.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Discharge properties of single neurons in the dorsal nucleus of the lateral lemniscus of the rat.

The aim of the present study was to characterize the discharge properties of single neurons in the dorsal nucleus of the lateral lemniscus (DNLL) of the rat. In the absence of acoustic stimulation, two types of spontaneous discharge patterns were observed: units tended to fire in a bursting or in a nonbursting mode. The distribution of units in the DNLL based on spontaneous firing rate followed a rostrocaudal gradient: units with high spontaneous rates were most commonly located in the rostral part of the DNLL, whereas in the caudal part units had lower spontaneous discharge rates. The most common response pattern of DNLL units to 200 ms binaural noise bursts contained a prominent onset response followed by a lower but steady-state response and an inhibitory response in the early-off period. Thresholds of response to noise bursts were on average higher for DNLL units than for units recorded in the inferior colliculus under the same experimental conditions. The DNLL units were arranged according to a mediolateral sensitivity gradient with the lowest threshold units in the most lateral part of the nucleus. In the rat, as in other mammals, the most common DNLL binaural input type was an excitatory response to contralateral ear stimulation and inhibitory response to ipsilateral ear stimulation (EI type). Pure tone bursts were in general a more effective stimulus compared to noise bursts. Best frequency (BF) was established for 97 DNLL units and plotted according to their spatial location. The DNLL exhibits a loose tonotopic organization, where there is a concentric pattern with high BF units located in the most dorsal and ventral parts of the DNLL and lower BF units in the middle part of the nucleus.