On the Frequency of Potential Venus Analogs from Kepler Data

The field of exoplanetary science has seen a dramatic improvement in sensitivity to terrestrial planets over recent years. Such discoveries have been a key feature of results from the {\it Kepler} mission which utilizes the transit method to determine the size of the planet. These discoveries have resulted in a corresponding interest in the topic of the Habitable Zone (HZ) and the search for potential Earth analogs. Within the Solar System, there is a clear dichotomy between Venus and Earth in terms of atmospheric evolution, likely the result of the large difference ($\sim$ factor of two) in incident flux from the Sun. Since Venus is 95\% of the Earth's radius in size, it is impossible to distinguish between these two planets based only on size. In this paper we discuss planetary insolation in the context of atmospheric erosion and runaway greenhouse limits for planets similar to Venus. We define a ``Venus Zone'' (VZ) in which the planet is more likely to be a Venus analog rather than an Earth analog. We identify 43 potential Venus analogs with an occurrence rate (\eta_{\venus}) of $0.32^{+0.05}_{-0.07}$ and $0.45^{+0.06}_{-0.09}$ for M dwarfs and GK dwarfs respectively.Comment: 6 pages, 3 figures, 2 tables. Accepted for publication in the Astrophysical Journal Letters. More information and graphics can be found at the Habitable Zone Gallery (http://hzgallery.org

Using the Daily Missions Gamification Strategy To Promote Incremental Progress on Programming Assignments

Automatic assessment tools are increasingly utilized in undergraduate programming courses to evaluate software solutions, streamlining the grading process for both students and professors. In spite of their benefits of speed and convenience, such online systems for providing instant feedback have the tendency to draw attention to performance-based outcomes while failing to reliably recognize the effort and hard work a student puts into a solution. For the many struggling students who are new to programming, this type of objective feedback can be discouraging and may decrease their motivation to stay engaged towards success. To address this issue, this paper explores strategies for more effectively recognizing student progress on programming assignments and identifying small tasks for students to complete that will steer them in the right direction. Further, this paper presents the design of a Daily Missions gamification strategy that was added to an automated program grading system. A pilot study shows feasibility of the approach and suitability of the design, indicating a statistically significant increase in the rate of completing tasks assigned as daily missions, and that students believe daily missions reinforce good practices while giving them better ideas on how to improve their work. An evaluation of experiences from using the strategy in the classroom is presented, along with student perceptions from using the system

Debating How to Measure Media Exposure in Surveys

To answer many of the most pressing questions in the social sciences, researchers need reliable and valid measures of media exposure that can be implemented in surveys. Despite considerable effort, however, substantial disagreement remains about how best to measure this key concept. This chapter critically reviews the debate surrounding traditional frequency measures of exposure to “news” and contemporary list-based measures of political media exposure. It also evaluates the related debate over how best to capture the effects of media exposure with different observational research designs. Overall, the chapter finds that although substantial progress has been made in measurement and research design, both issues require more attention if scholars are to understand the many and varied effects of media exposure

Positive regulation of meiotic DNA double-strand break formation by activation of the DNA damage checkpoint kinase Mec1(ATR)

During meiosis, formation and repair of programmed DNA double-strand breaks (DSBs) create genetic exchange between homologous chromosomes-a process that is critical for reductional meiotic chromosome segregation and the production of genetically diverse sexually reproducing populations. Meiotic DSB formation is a complex process, requiring numerous proteins, of which Spo11 is the evolutionarily conserved catalytic subunit. Precisely how Spo11 and its accessory proteins function or are regulated is unclear. Here, we use Saccharomyces cerevisiae to reveal that meiotic DSB formation is modulated by the Mec1(ATR) branch of the DNA damage signalling cascade, promoting DSB formation when Spo11-mediated catalysis is compromised. Activation of the positive feedback pathway correlates with the formation of single-stranded DNA (ssDNA) recombination intermediates and activation of the downstream kinase, Mek1. We show that the requirement for checkpoint activation can be rescued by prolonging meiotic prophase by deleting the NDT80 transcription factor, and that even transient prophase arrest caused by Ndt80 depletion is sufficient to restore meiotic spore viability in checkpoint mutants. Our observations are unexpected given recent reports that the complementary kinase pathway Tel1(ATM) acts to inhibit DSB formation. We propose that such antagonistic regulation of DSB formation by Mec1 and Tel1 creates a regulatory mechanism, where the absolute frequency of DSBs is maintained at a level optimal for genetic exchange and efficient chromosome segregation

Learning from Examples with Unspecified Attribute Values

We introduce the UAV learning model in which some of the attributes in the examples are unspecified. In our model, an example x is classified positive (resp., negative) if all possible assignments for the unspecified attributes result in a positive (resp., negative) classification. Otherwise the classificatoin given to x is ? (for unknown). Given an example x in which some attributes are unspecified, the oracle UAV-MQ responds with the classification of x. Given a hypothesis h, the oracle UAV-EQ returns an example x (that could have unspecified attributes) for which h(x) is incorrect. We show that any class learnable in the exact model using the MQ and EQ oracles is also learnable in the UAV model using the MQ and UAV-EQ oracles as long as the counterexamples provided by the UAV-EQ oracle have a logarithmic number of unspecified attributes. We also show that any class learnable in the exact model using the MQ and EQ oracles is also learnable in the UAV model using the UAV-MQ and UAV-EQ oracles as well as an oracle to evaluate a given boolean formula on an example with unspecified attributes. (For some hypothesis classes such as decision trees and unate formulas the evaluation can be done in polynomial time without an oracle.) We also study the learnability of a universal class of decision trees under the UAV model and of DNF formulas under a representation-dependent variation of the UAV model

Agnostic Learning of Geometric Patterns

Goldberg, Goldman, and Scott demonstrated how the problem of recognizing a landmark from a one-dimensional visual image can be mapped to that of learning a one-dimensional geometric pattern and gave a PAC algorithm to learn that class. In this paper, we present an efficient on-line agnostic learning algorithm for learning the class of constant-dimension geometric patterns. Our algorithm can tolerate both classification and attribute noise. By working in higher dimensional spaces we can represent more features from the visual image in the geometric pattern. Our mapping of the data to a geometric pattern, and hence our learning algorithm, is applicable to any data representable as a constant-dimensional array of values, e.g. sonar data, temporal difference information, or amplitudes of a waveform. To our knowledge, these classes of patterns are more complex than any class of geometric patterns previously studied. Also, our results are easily adapted to learn the union of fixed-dimensional boxes from multiple-instance examples. Finally, our algorithms are tolerant of concept shift

Restoring Trust in Corporate Directors: The Disney Standard and the ‘New’ Good Faith

The purpose of this Article is to explore the parameters and potential impact of the good faith standard articulated in Disney V and clarified in Stone. Part I begins with a brief review of the historical impact of the tension between entrepreneurial freedom and managerial accountability, and Part II explains why the Disney standard differs significantly from the traditional understanding of good faith as the absence of subjective bad faith. Part III points out that the court\u27s use of the language of bad faith to articulate the new good faith may undercut the effectiveness of the standard. It urges further clarification of the difference between the absence of good faith and the presence of bad faith to ensure that the Disney standard will not be reduced to a mere semantic variation on the traditional duty of loyalty applicable only in the presence of improper-i.e., subjectively bad -motivation. Finally, Part IV examines the Disney standard\u27s potential to serve as a vehicle for restoring trust in corporate directors and argues that the new good faith has the capacity to serve this important function, but only if the courts utilize the doctrine to require corporate directors to engage actively in oversight of the business and affairs of the entities entrusted to them