The Potential Of Kohonen Method For Classifying Rivers Focused On Regional Environmental Flow Determination With ELOHA

This article highlights the potential benefits that the Kohonen method has for the classification of rivers with similar characteristics by determining regional ecological flows using the ELOHA (Ecological Limits of Hydrologic Alteration) methodology. Currently, there are many methodologies for the classification of rivers, however none of them include the characteristics found in Kohonen method such as (i) providing the number of groups that actually underlie the information presented, (ii) used to make variable importance analysis, (iii) which in any case can display two-dimensional classification process, and (iv) that regardless of the parameters used in the model the clustering structure remains. In order to evaluate the potential benefits of the Kohonen method, 174 flow stations distributed along the great river basin “Magdalena-Cauca” (Colombia) were analyzed. 73 variables were obtained for the classification process in each case. Six trials were done using different combinations of variables and the results were validated against reference classification obtained by Ingfocol in 2010, whose results were also framed using ELOHA guidelines. In the process of validation it was found that two of the tested models reproduced a level higher than 80% of the reference classification with the first trial, meaning that more than 80% of the flow stations analyzed in both models formed invariant groups of streams.

Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Self-Organizing Maps as a New Tool for Classification of Plants at Lower Hierarchical Levels

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural studies of AgPO3-MoO3 glasses using solid state NMR and vibrational spectroscopies

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of processing on the structure of zein/oleic acid films investigated by X-ray diffraction

Zein films plasticized with oleic acid were formed by solution casting, by the stretching of moldable resins, and by blown film extrusion. The effects of the forming process on film structure were investigated by X-ray diffraction. Wide-angle X-ray scattering (WAXS) patterns showed d-spacings at 4.5 and 10 angstrom, which were attributed to the zein alpha-helix backbone and inter-helix packing, respectively. The 4.5.angstrom d-spacing remained stable under processing while the 10 angstrom d-spacing varied with processing treatment. Small-angle X-ray scattering (SAXS) detected a long-range periodicity for the formed films but not for unprocessed zein, which suggests that the forming process-promoted film structure development is possibly aided by oleic acid. The SAXS d-spacing varied among the samples (130-238 angstrom) according to zein origin and film-forming method. X-ray scattering data suggest that the zein molecular structure resists processing but the zein supramolecular arrangements in the formed films are dependent on processing methods.

Classification of petroleum well drilling operations using Support Vector Machine (SVM)

During the petroleum well drilling operation many mechanical and hydraulic parameters are monitored by an instrumentation system installed in the rig called a mud-logging system. These sensors, distributed in the rig, monitor different operation parameters such as weight on the hook and drillstring rotation. These measurements are known as mud-logging records and allow the online following of all the drilling process with well monitoring purposes. However, in most of the cases, these data are stored without taking advantage of all their potential. On the other hand, to make use of the mud-logging data, an analysis and interpretationt is required. That is not an easy task because of the large volume of information involved. This paper presents a Support Vector Machine (SVM) used to automatically classify the drilling operation stages through the analysis of some mud-logging parameters. In order to validate the results of SVM technique, it was compared to a classification elaborated by a Petroleum Engineering expert. © 2006 IEEE.

Geoestística e sensoriamento remoto na classificação de imagens em áreas cultivadas com citros

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach.

This paper proposes the optimization relaxation approach based on the analogue Hopfield Neural Network (HNN) for cluster refinement of pre-classified Polarimetric Synthetic Aperture Radar (PolSAR) image data. We consider the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution, which is then supplied to the HNN optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The classification improvement is verified by computing a cluster separability coefficient and a measure of homogeneity within the clusters. During the HNN optimization process, for each iteration and for each pixel, two consistency coefficients are computed, taking into account two types of relations between the pixel under consideration and its corresponding neighbors. Based on these coefficients and on the information coming from the pixel itself, the pixel under study is re-classified. Different experiments are carried out to verify that the proposed approach outperforms other strategies, achieving the best results in terms of separability and a trade-off with the homogeneity preserving relevant structures in the image. The performance is also measured in terms of computational central processing unit (CPU) times.

Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements

We present a new method to accurately locate persons indoors by fusing inertial navigation system (INS) techniques with active RFID technology. A foot-mounted inertial measuring units (IMUs)-based position estimation method, is aided by the received signal strengths (RSSs) obtained from several active RFID tags placed at known locations in a building. In contrast to other authors that integrate IMUs and RSS with a loose Kalman filter (KF)-based coupling (by using the residuals of inertial- and RSS-calculated positions), we present a tight KF-based INS/RFID integration, using the residuals between the INS-predicted reader-to-tag ranges and the ranges derived from a generic RSS path-loss model. Our approach also includes other drift reduction methods such as zero velocity updates (ZUPTs) at foot stance detections, zero angular-rate updates (ZARUs) when the user is motionless, and heading corrections using magnetometers. A complementary extended Kalman filter (EKF), throughout its 15-element error state vector, compensates the position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backward walk, at different speeds), and does not require an offline calibration for the user gait. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total traveled distance), resulting in typical positioning errors along the walking path (no matter its length) of approximately 1.5 m.

Laminar-turbulent transition induced by a discrete roughness element in a supersonic boundary layer

The linear instability and breakdown to turbulence induced by an isolated roughness element in a boundary layer at Mach 2:5, over an isothermal flat plate with laminar adiabatic wall temperature, have been analysed by means of direct numerical simulations, aided by spatial BiGlobal and three-dimensional parabolized (PSE-3D) stability analyses. It is important to understand transition in this flow regime since the process can be slower than in incompressible flow and is crucial to prediction of local heat loads on next-generation flight vehicles. The results show that the roughness element, with a height of the order of the boundary layer displacement thickness, generates a highly unstable wake, which is composed of a low-velocity streak surrounded by a three-dimensional high-shear layer and is able to sustain the rapid growth of a number of instability modes. The most unstable of these modes are associated with varicose or sinuous deformations of the low-velocity streak; they are a consequence of the instability developing in the three-dimensional shear layer as a whole (the varicose mode) or in the lateral shear layers (the sinuous mode). The most unstable wake mode is of the varicose type and grows on average 17% faster tan the most unstable sinuous mode and 30 times faster than the most unstable boundary layer mode occurring in the absence of a roughness element. Due to the high growthrates registered in the presence of the roughness element, an amplification factor of N D 9 is reached within 50 roughness heights from the roughness trailing edge. The independently performed Navier–Stokes, spatial BiGlobal and PSE-3D stability results are in excellent agreement with each other, validating the use of simplified theories for roughness-induced transition involving wake instabilities. Following the linear stages of the laminar–turbulent transition process, the roll-up of the three-dimensional shear layer leads to the formation of a wedge of turbulence, which spreads laterally at a rate similar to that observed in the case of compressible turbulent spots for the same Mach number.

Control of pre-mRNA accumulation by the essential yeast protein Nrd1 requires high-affinity transcript binding and a domain implicated in RNA polymerase II association

Nrd1 is an essential yeast protein of unknown function that has an RNA recognition motif (RRM) in its carboxyl half and a putative RNA polymerase II-binding domain, the CTD-binding motif, at its amino terminus. Nrd1 mediates a severe reduction in pre-mRNA production from a reporter gene bearing an exogenous sequence element in its intron. The effect of the inserted element is highly sequence-specific and is accompanied by the appearance of 3′-truncated transcripts. We have proposed that Nrd1 binds to the exogenous sequence element in the nascent pre-mRNA during transcription, aided by the CTD-binding motif, and directs 3′-end formation a short distance downstream. Here we show that highly purified Nrd1 carboxyl half binds tightly to the RNA element in vitro with sequence specificity that correlates with the efficiency of cis-element-directed down-regulation in vivo. A large deletion in the CTD-binding motif blocks down-regulation but does not affect the essential function of Nrd1. Furthermore, a nonsense mutant allele that produces truncated Nrd1 protein lacking the RRM has a dominant-negative effect on down-regulation but not on cell growth. Viability of this and several other nonsense alleles of Nrd1 appears to require translational readthrough, which in one case is extremely efficient. Thus the CTD-binding motif of Nrd1 is important for pre-mRNA down-regulation but is not required for the essential function of Nrd1. In contrast, the RNA-binding activity of Nrd1 appears to be required both for down-regulation and for its essential function.

Molecular basis of intramolecular electron transfer in sulfite-oxidizing enzymes is revealed by high resolution structure of a heterodimeric complex of the catalytic molybdopterin subunit and a c-type cytochrome subunit

Sulfite-oxidizing molybdoenzymes convert the highly reactive and therefore toxic sulfite to sulfate and have been identified in insects, animals, plants, and bacteria. Although the well studied enzymes from higher animals serve to detoxify sulfite that arises from the catabolism of sulfur-containing amino acids, the bacterial enzymes have a central role in converting sulfite formed during dissimilatory oxidation of reduced sulfur compounds. Here we describe the structure of the Starkeya novella sulfite dehydrogenase, a heterodimeric complex of the catalytic molybdopterin subunit and a c-type cytochrome subunit, that reveals the molecular mechanism of intramolecular electron transfer in sulfite-oxidizing enzymes. The close approach of the two redox centers in the protein complex (Mo-Fe distance 16.6 angstrom) allows for rapid electron transfer via tunnelling or aided by the protein environment. The high resolution structure of the complex has allowed the identification of potential through-bond pathways for electron transfer including a direct link via Arg-55A and/or an aromatic-mediated pathway. A potential site of electron transfer to an external acceptor cytochrome c was also identified on the SorB subunit on the opposite side to the interaction with the catalytic SorA subunit.

Marketing performance assessment systems and the business context

Purpose ‐ This study provides empirical evidence for the contextuality of marketing performance assessment (MPA) systems. It aims to introduce a taxonomical classification of MPA profiles based on the relative emphasis placed on different dimensions of marketing performance in different companies and business contexts. Design/methodology/approach ‐ The data used in this study (n=1,157) were collected using a web-based questionnaire, targeted to top managers in Finnish companies. Two multivariate data analysis techniques were used to address the research questions. First, dimensions of marketing performance underlying the current MPA systems were identified through factor analysis. Second, a taxonomy of different profiles of marketing performance measurement was created by clustering respondents based on the relative emphasis placed on the dimensions and characterizing them vis-á-vis contextual factors. Findings ‐ The study identifies nine broad dimensions of marketing performance that underlie the MPA systems in use and five MPA profiles typical of companies of varying sizes in varying industries, market life cycle stages, and competitive positions associated with varying levels of market orientation and business performance. The findings support the previously conceptual notion of contextuality in MPA and provide empirical evidence for the factors that affect MPA systems in practice. Originality/value ‐ The paper presents the first field study of current MPA systems focusing on combinations of metrics in use. The findings of the study provide empirical support for the contextuality of MPA and form a classification of existing contextual systems suitable for benchmarking purposes. Limited evidence for performance differences between MPA profiles is also provided.

Current range characteristics of Swiss stone pine (Pinus cembra L.) along the Carpathians revealed by chloroplast SSR markers.

We investigated the diversity pattern of nine Swiss stone pine (Pinus cembra L.) populations along the Carpathian range including the High Tatras, by using six chloroplast DNA microsatellites (cpSSR). Our aim was to detect genetically distinct regions by clustering of populations, and to tackle possible historical colonization routes. Our analysis referred to an investigated geographical range with the two most distant populations situated at about 500 air km. We found that the most diverse populations are situated at the two edges of the investigated part, in the Retezat Mts. (South Carpathians) and the High Tatras, and diversity decreases towards the populations of the Eastern Carpathians. Hierarchical clustering and NMDS revealed that the populations of the South Carpathians with the Tatras form a distinct cluster, significantly separated from those of the Eastern Carpathians. Moreover, based on the most variable chloroplast microsatellites, the four populations of the two range edges are not significantly different. Our results, supported also by palynological and late glacial macrofossil evidences, indicate refugial territories within the Retezat Mts. that conserved rich haplotype composition. From this refugial territory Pinus cembra might have colonized the Eastern Carpathians, and this was accompanied by a gradual decrease in population diversity. Populations of the High Tatras might have had the same role in the colonizing events of the Carpathians, as positive correlation was detected among populations lying from each other at a distance of 280 km, the maximum distance between neighbouring populations.

Liquidity, governance and adverse selection in asset pricing

A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. ^ In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company's shares. Hence, we jointly examine both the factors, namely, governance and liquidity - in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll's (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.^