Social investors: new patrons of community development

Investors who want to make money while sticking to personal values are growing in number. Social investors have typically used screens and shareholder advocacy in their approach. Now, many are learning about and investing in community economic development.Economic development ; Investments

Is housing next in company benefits?

The call for employers to offer housing benefits has been made in Greater Boston - but to little avail so far. Looser labor markets and lack of familiarity with a new concept are some reasons why employers are hesitant. What are the prospects for employer assisted housing and what is being done to spark enthusiasm?Housing - Prices ; Housing - Massachusetts

Moving into new territory: Internet banks make defining community difficult

Community Reinvestment Act of 1977 ; Internet

Mind the gap: grandparents raising grandchildren

The population of grandparents raising their grandchildren is rising. These families face unique pressures, such as finding appropriate and affordable housing. In Boston, one housing community meets their needs. Others around the country may be on the way.Child care ; Housing - Boston

Natural data structure extracted from neighborhood-similarity graphs

'Big' high-dimensional data are commonly analyzed in low-dimensions, after performing a dimensionality-reduction step that inherently distorts the data structure. For the same purpose, clustering methods are also often used. These methods also introduce a bias, either by starting from the assumption of a particular geometric form of the clusters, or by using iterative schemes to enhance cluster contours, with uncontrollable consequences. The goal of data analysis should, however, be to encode and detect structural data features at all scales and densities simultaneously, without assuming a parametric form of data point distances, or modifying them. We propose a novel approach that directly encodes data point neighborhood similarities as a sparse graph. Our non-iterative framework permits a transparent interpretation of data, without altering the original data dimension and metric. Several natural and synthetic data applications demonstrate the efficacy of our novel approach

Building communities: making a difference

One of the most vexing economic problems facing the United States has been the persistence of pockets of poverty in the midst of prosperity. The reasons for this are many and complex. Prominent among them are economic isolation in the case of rural areas, and language and cultural barriers in the case of many inner-city communities. Discrimination has played a role, but so too has simple ignorance. Resources and opportunities exist in these communities, but getting the recognition from market sources necessary to leverage these assets is difficult. For whatever reason, human and physical resources in these neighborhoods may not be fully utilized. Perhaps even worse, exclusion from the economic mainstream perpetuates and reinforces itself. Lacking jobs, capital, and examples of success, many of these communities have remained mired in poverty.Community development corporations ; Poverty

Neural avalanches at the edge-of-chaos?

Does the brain operate at criticality, to optimize neural computation? Literature uses different fingerprints of criticality in neural networks, leaving the relationship between them mostly unclear. Here, we compare two specific signatures of criticality, and ask whether they refer to observables at the same critical point, or to two differing phase transitions. Using a recurrent spiking neural network, we demonstrate that avalanche criticality does not necessarily lie at edge-of-chaos

Novel insights into cochlear information processing

Already Helmholtz profoundly addressed the question how the nonlinearity of the human hearing sensor, the cochlea, might shape human sound perception. At his time, research was, however, obstructed by the lack of experimental data regarding the amplification properties of the inner ear. In the meantime, accurate measuring methods have permitted the comparison of models of the hearing sensor with empirical data, leading to a strong revival of the interest into Helmholtz’s original research questions. In our paper, we describe some recent theoretical and modeling advances in the understanding of the nature of human pitch perception. We reveal a number of to date unexplained human auditory percept effects to be direct consequences of the nonlinear properties of the mammalian hearing sensor. Our insights also demonstrate, as a by-note, the limitations of the present reverse engineering approach towards cochlear implants