The problem of negatives in input-output analysis: a review of the solutions

The main models to construct technical coefficients are the industry technology model and the commodity technology model. The former yields nonnegative coefficients and the latter fulfills nice theoretical properties, such as price invariance. Although the models are very different, this paper presents a flexible formula that encompasses both of them. Various solutions to the problem of negatives of the commodity technology model-including replacements by industry technology based coefficients-are reviewed in our framework.Input-output analysis; technical coefficients; use and make matrices

Better predictions when models are wrong or underspecified

Many statistical methods rely on models of reality in order to learn from data and to make predictions about future data. By necessity, these models usually do not match reality exactly, but are either wrong (none of the hypotheses in the model provides an accurate description of reality) or underspecified (the hypotheses in the model describe only part of the data). In this thesis, we discuss three scenarios involving models that are wrong or underspecified. In each case, we find that standard statistical methods may fail, sometimes dramatically, and present different methods that continue to perform well even if the models are wrong or underspecified. The first two of these scenarios involve regression problems and investigate AIC (Akaike's Information Criterion) and Bayesian statistics. The third scenario has the famous Monty Hall problem as a special case, and considers the question how we can update our belief about an unknown outcome given new evidence when the precise relation between outcome and evidence is unknown.UBL - phd migration 201

Adapting AIC to conditional model selection

In statistical settings such as regression and time series, we can condition on observed information when predicting the data of interest. For example, a regression model explains the dependent variables $y_1, \ldots, y_n$ in terms of the independent variables $x_1, \ldots, x_n$. When we ask such a model to predict the value of $y_{n+1}$ corresponding to some given value of $x_{n+1}$, that prediction's accuracy will vary with $x_{n+1}$. Existing methods for model selection do not take this variability into account, which often causes them to select inferior models. One widely used method for model selection is AIC (Akaike's Information Criterion \cite{Akaike}), which is based on estimates of the KL divergence from the true distribution to each model. We propose an adaptation of AIC that takes the observed information into account when estimating the KL divergence, thereby getting rid of a bias in AIC's estimate

Extraordinary behavioral entrainment following circadian rhythm bifurcation in mice.

The mammalian circadian timing system uses light to synchronize endogenously generated rhythms with the environmental day. Entrainment to schedules that deviate significantly from 24 h (T24) has been viewed as unlikely because the circadian pacemaker appears capable only of small, incremental responses to brief light exposures. Challenging this view, we demonstrate that simple manipulations of light alone induce extreme plasticity in the circadian system of mice. Firstly, exposure to dim nocturnal illumination (<0.1 lux), rather than completely dark nights, permits expression of an altered circadian waveform wherein mice in light/dark/light/dark (LDLD) cycles "bifurcate" their rhythms into two rest and activity intervals per 24 h. Secondly, this bifurcated state enables mice to adopt stable activity rhythms under 15 or 30 h days (LDLD T15/T30), well beyond conventional limits of entrainment. Continuation of dim light is unnecessary for T15/30 behavioral entrainment following bifurcation. Finally, neither dim light alone nor a shortened night is sufficient for the extraordinary entrainment observed under bifurcation. Thus, we demonstrate in a non-pharmacological, non-genetic manipulation that the circadian system is far more flexible than previously thought. These findings challenge the current conception of entrainment and its underlying principles, and reveal new potential targets for circadian interventions

Mapping Applications to an FPFA Tile

This paper introduces a transformational design method which can be used to map code written in a high level source language, like C, to a coarse grain reconfigurable architecture. The source code is first translated into a control data flow graph (CDFG), which is minimized using a set of behaviour preserving transformations, such as dependency analysis, common subexpression elimination, etc. After applying graph clustering, scheduling and allocation transformations on this minimized graph, it can be mapped onto the target architecture

Exploring Patterns of Activities of Daily Living in the Home Environment

Background: Senior citizens tend to live longer and longer independently. Judging whether a senior person is still capable of living on his own is often based on the occurrence of incidents, with all consequences thereof. In the specific case of early dementia, the symptoms are not immediately apparent and the occurrence and severity of incidents progress gradually over time. In this case, the children or grandchildren are burdened by the question whether or not the elderly adult can still live safely and independently in his or her own home. This decision is only based on input obtained through incidental visits. We believe that the capability of independent living can only be objectively judged, by a health professional, if long term objective information on the elderly person's daily activities of living (ADL) is available