Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem

Population policies, programmes and the environment

Human consumption is depleting the Earth's natural resources and impairing the capacity of life-supporting ecosystems. Humans have changed ecosystems more rapidly and extensively over the past 50 years than during any other period, primarily to meet increasing demands for food, fresh water, timber, fibre and fuel. Such consumption, together with world population increasing from 2.6 billion in 1950 to 6.8 billion in 2009, are major contributors to environmental damage. Strengthening family-planning services is crucial to slowing population growth, now 78 million annually, and limiting population size to 9.2 billion by 2050. Otherwise, birth rates could remain unchanged, and world population would grow to 11 billion. Of particular concern are the 80 million annual pregnancies (38% of all pregnancies) that are unintended. More than 200 million women in developing countries prefer to delay their pregnancy, or stop bearing children altogether, but rely on traditional, less-effective methods of contraception or use no method because they lack access or face other barriers to using contraception. Family-planning programmes have a successful track record of reducing unintended pregnancies, thereby slowing population growth. An estimated $15 billion per year is needed for family-planning programmes in developing countries and donors should provide at least$5 billion of the total, however, current donor assistance is less than a quarter of this funding target

Creating an Instrument to Measure Student Response to Instructional Practices

BackgroundCalls for the reform of education in science, technology, engineering, and mathematics (STEM) have inspired many instructional innovations, some research based. Yet adoption of such instruction has been slow. Research has suggested that students’ response may significantly affect an instructor’s willingness to adopt different types of instruction.PurposeWe created the Student Response to Instructional Practices (StRIP) instrument to measure the effects of several variables on student response to instructional practices. We discuss the step‐by‐step process for creating this instrument.Design/MethodThe development process had six steps: item generation and construct development, validity testing, implementation, exploratory factor analysis, confirmatory factor analysis, and instrument modification and replication. We discuss pilot testing of the initial instrument, construct development, and validation using exploratory and confirmatory factor analyses.ResultsThis process produced 47 items measuring three parts of our framework. Types of instruction separated into four factors (interactive, constructive, active, and passive); strategies for using in‐class activities into two factors (explanation and facilitation); and student responses to instruction into five factors (value, positivity, participation, distraction, and evaluation).ConclusionsWe describe the design process and final results for our instrument, a useful tool for understanding the relationship between type of instruction and students’ response.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136692/1/jee20162_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136692/2/jee20162.pd