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Data on innovation financing in Colombia present a paradox: Manufacturing companies prefer to finance their innovation projects with their own capital, with bank loans in second place, and cheaper public funding last. Extant financial theories cannot explain such a paradox (reversed pecking order), making a different approach necessary. Hence, a new perspective is presented on the basis of Sierra’s (2014, 2020) proposal. A fixed effects panel estimation is carried out that includes three new variables: A Knowledge Incorporation and Consolidation System, interaction among companies and funders, a particular type of investor (Dedicated). The results support the alternative explanation. Additionally, research possibilities, designs and applications of public and organisational policy aimed to overcome some of the problems mentioned are proposed. [ABSTRACT FROM AUTHOR]

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Forecasted increases in flood risk from future changes in precipitation patterns and sea level rise and storm surge events prompted the city of Cambridge to start a pilot program to assess feasible mitigation and resilience measures in the Alewife Brook area within the city. Because the potential magnitude of these inundation events extends well beyond the city's boundaries and are likely to be caused by factors mostly at the watershed or regional scale, the city has decided to build a fully integrated model of the Mystic River watershed. The Alewife Brook is one of the tributaries to the Mystic River. The integrated model includes the hydrology and riverine geometry of the entire watershed and has been greatly refined within Cambridge's boundaries to include the city's sewer system model. The sewer system model has been seamlessly integrated with the riverine model and now allows for modeling of the highly dynamic and interdependent interactions between both environments. Additionally, in the integrated platform, the floodplain within Cambridge was represented with a high-resolution, two-dimensional grid also seamlessly coupled with the riverine and sewer platforms. The integrated model of the Mystic River watershed was successfully calibrated and validated using two large historical storms known to have caused flooding in some areas within Cambridge. Calibration was performed using three different river gauges as well as photographic evidence provided by the city and others. The calibrated model is now ready for evaluating the relative benefit of proposed mitigation measures, individually or in combination, and to quantify potential impacts these measures may have on the rest of the watershed communities. This tool is now readily available to kick-start collaboration among stakeholders confronting a problem that poses a great risk moving forward. [ABSTRACT FROM AUTHOR]

A natural river system is organized as a nested hierarchy of interconnected habitats with specific environmental conditions to which the biological community has adapted. Due to this hierarchical structure, identifying the role of different stressors on the biological community is a formidable task. Efforts trying to link stressors to biological integrity have always been bound to the geographic scale of the selected study area, leading to scale-specific results. In this research, an attempt is made to lift this limitation and develop a hierarchical, scale-sensitive methodology that can identify the significant environmental stressors to the biological community at different scales. Sites with similar background environmental conditions are clustered using self-organizing maps (SOM). This is used to identify stressors which affect the biological community throughout the area of study – called environmental gradients or large-scale stressors. Subsequently, these clusters of similar observations (sampling sites) are progressively sub-divided using environmental variables with a significant but localized effect on the biological community – called small-scale stressors. A parent group of sites is split only when the resulting sub-groups have significantly different biological responses. At the end of this recursive sites decomposition procedure, the original set of observations is organized as a tree of environmentally homogeneous groups of observations characterized by unique biological responses to multiple stressors with different geographic extents. The developed hierarchical analysis methodology has been validated using a large-size dataset of environmental observations from the State of Ohio. Our results show that habitat degradation and increased nutrient loading are the large-scale stressors with a widespread impact in Ohio. Other stressors, such as heavy metals, pH or nitrate concentrations have significant albeit localized effects on biological integrity. [Copyright &y& Elsevier]

Our empirical analysis on the determinants of self-declared happiness on more than 100 000 individuals from representative samples in 82 world countries does not reject the hypothesis that the time spent for relationships has a significant and positive impact on happiness. This basic nexus helps to understand new unexplored paths in the so-called 'happiness-income paradox'. To illustrate them we show that personal income has two main effects on happiness. The first is a positive effect which depends on individual's ranking within domestic income quintiles. The second is determined by the relationship between income and relational goods. In principle, more productive individuals may substitute (if the income effect prevails over the substitution effect) worked hours with the nonworking time made free for enjoying relationships, when they have strong preferences for them. The problem is that these individuals tend to have ties with their income class peers who share with them a high opportunity cost for the time spent for relationships. Hence, a coordination failure may reduce the joint investment in relational goods (local public goods which need to be co-produced in order to be enjoyed together) and, through this effect, individuals in the highest income quintiles may end up with poorer relational goods. The indirect impact of personal income on happiness through this channel is therefore expected to be negative. [ABSTRACT FROM AUTHOR]

Two different methods to predict biotic integrity were tested and compared in the present paper. The first one tries to predict the fish indices of biotic integrity (IBI) at the state or regional scale based on the most similar observations to a specific target site of interest using the simple to implement k-nearest neighbors (or kNN) method. Two different distance functions were considered to find the k-nearest neighbors: the Euclidean and the Mahalanobis. The second method was applied on the same datasets and consisted of a step-wise multiple regression. The two modeling approaches yielded similar results but kNN proved to be more time-efficient and very fast computationally for the given dataset sizes, which allowed applying a leave-one-out cross validation. In an attempt to reveal the importance of scale in the prediction of IBI, regression models were constructed at the state (or regional) scale and at the more refined cluster of sampling sites scale. Clusters of sites were extracted using Kohonen's self-organizing maps (SOM) followed by k-means clustering of the SOM neurons. Cluster-level regression models, constructed after site patterning, performed better in IBI prediction than global regression models constructed without any previous site patterning. The importance of identifying groups of sites with similar environmental characteristics affecting the IBI was revealed. The combined use of site patterning and regression modeling for IBI prediction also helped identifying important variables acting at the local scale which remain latent at the global scale. [Copyright &y& Elsevier]

Advanced computerized methods and models of retrieving knowledge from large multiparameter data bases were used to analyze data on fish and macroinvertebrate composition (metrics), habitat, land use and water quality. The research focused on the north central and northeastern United States and involved thousands of sites monitored by the state agencies. The techniques and methodologies included supervised and unsupervised Artificial Neural Networks (ANN) modeling, Principal Component Analysis, Canonical Component Analysis (both linear and nonlinear), Multiple Regression Analyses, and analyses of variance by ANOVA. The research resulted in defining a concept of clusters of sites based on their biotic (fish) community composition, identified cluster dominating factors, and developed meaningful models for predicting fish composition based on environmental and in-stream habitat stresses. [ABSTRACT FROM AUTHOR]

Over the past 20 years, the city of Cambridge has taken a rigorous approach to combined sewer and stormwater management. In tandem with sewer separation, it is constructing drainage systems to relieve broad community flooding problems, address long-term operations and maintenance, and enhance water quality in local receiving waters. As a result, rivers are becoming cleaner, and in areas where stormwater management improvements have occurred, flooding has diminished measurably. In achieving this, Cambridge has met the Massachusetts Water Resources Authority's (MWRA) court-ordered start dates for the sewer separation work in the Alewife watershed area, exceeded the Massachusetts Department of Environmental Protection's (MassDEP's) expectations for removing illicit connections and common manholes, and become a regional leader in stormwater management. The city believes it has done this in a manner that, while at times unavoidably and extraordinarily disruptive, has been genuinely sensitive to and considerate of community needs. [ABSTRACT FROM AUTHOR]