Frequency Tracking and Parameter Estimation for Robust Quantum State-Estimation

In this paper we consider the problem of tracking the state of a quantum system via a continuous measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small error in the assumed Hamiltonian can render this approach useless. The natural answer to this problem is to include the parameters of the Hamiltonian as part of the estimation problem, and the full Bayesian solution to this task provides a state-estimate that is robust against uncertainties. However, this approach requires considerable computational overhead. Here we consider a single qubit in which the Hamiltonian contains a single unknown parameter. We show that classical frequency estimation techniques greatly reduce the computational overhead associated with Bayesian estimation and provide accurate estimates for the qubit frequencyComment: 6 figures, 13 page

GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions

BACKGROUND: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficult resource for investigators to utilize effectively. Software tools have been recently developed to use the distribution of gene ontology (GO) terms associated with the genes in an EP to identify specific biological functions or processes that are over- or under-represented in that EP relative to other EPs. Additionally, it is possible to use the distribution of GO terms inherent to each EP to relate that EP as a whole to other EPs. Because GO term annotation is organized in a tree-like cascade of variable granularity, this approach allows the user to relate (e.g., by hierarchical clustering) EPs of varying length and from different platforms (e.g., GeneChip, SAGE, EST library). RESULTS: Here we present GOurmet, a software package that calculates the distribution of GO terms represented by the genes in an individual expression profile (EP), clusters multiple EPs based on these integrated GO term distributions, and provides users several tools to visualize and compare EPs. GOurmet is particularly useful in meta-analysis to examine EPs of specified cell types (e.g., tissue-specific stem cells) that are obtained through different experimental procedures. GOurmet also introduces a new tool, the Targetoid plot, which allows users to dynamically render the multi-dimensional relationships among individual elements in any clustering analysis. The Targetoid plotting tool allows users to select any element as the center of the plot, and the program will then represent all other elements in the cluster as a function of similarity to the selected central element. CONCLUSION: GOurmet is a user-friendly, GUI-based software package that greatly facilitates analysis of results generated by multiple EPs. The clustering analysis features a dynamic targetoid plot that is generalizable for use with any clustering application

An Analysis of Expressed Cheating Behaviors in Video Games

A series of 50 responses regarding reasons for cheating behavior in video games were provided by undergraduate students. These responses were sorted into a series of 13 categories by raters to investigate the most common reasons provided for cheating. An analysis of inter-rater agreement as well as frequency of category representation is provided. The most common outcomes were that players cheat to progress in a game as well as to gain advantage over others. The discussion compared this study’s results to an existing cheating taxonomy

Ethical Perceptions and Actions in Gaming

The present study explored how individuals perceive actions in gaming that contain ethical components, whether they have ever engaged in those behaviors and how judgments of ethical actions in gaming relate to participant personality. Participants completed a 16-item survey, which measured their perception of the ethics of gaming behaviors, such as buying a hack or lying to another player. Participants were also asked to indicate for each item whether or not they had ever engaged in that behavior. Results indicated that participants were able to judge the ethical level of different gaming behaviors with lying to other players and unauthorized access to servers being rated as most unethical. Furthermore, self-reports of engagement in unethical activities were fairly low. When ethical rating and action scores were correlated with personality characteristics using the Cattell 16PF1, the only correlation to reach significance showed that participants higher in rule consciousness rated the ethical gaming questions as more unethical overall than their less rule-conscious peers. Given the extent and popularity of gaming in today’s world, it is important to understand how individuals perceive the gaming culture. One aspect of this culture that merits further examination is ethical behavior in gaming

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Modeling Human Gaming Playing Behavior and Reward/Penalty Mechanism using Discrete Event Simulation (DES)

Humans are remarkably complex and unpredictable; however, while predicting human behavior can be problematic, there are methods such as modeling and simulation that can be used to predict probable futures of human decisions. The present study analyzes the possibility of replacing human subjects with data resulting from pure models. Decisions made by college students in a multi-level mystery-solving game under 3 different gaming conditions are compared with the data collected from a predictive sequential Markov-Decision Process model. In addition, differences in participants’ data influenced by the three different conditions (additive, subtractive, control) were analyzed. The test results strongly suggest that the data gathered from the model can possibly represent the ones gathered from the human participants in a practical experiment

Response and resistance to BET bromodomain inhibitors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy. BET bromodomain inhibitors, which have shown efficacy in several models of cancer have not been evaluated in TNBC. These inhibitors displace BET bromodomain proteins such as BRD4 from chromatin by competing with their acetyl-lysine recognition modules, leading to inhibition of oncogenic transcriptional programs. Here we report the preferential sensitivity of TNBCs to BET bromodomain inhibition in vitro and in vivo, establishing a rationale for clinical investigation and further motivation to understand mechanisms of resistance. In paired cell lines selected for acquired resistance to BET inhibition from previously sensitive TNBCs, we failed to identify gatekeeper mutations, new driver events or drug pump activation. BET-resistant TNBC cells remain dependent on wild-type BRD4, which supports transcription and cell proliferation in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify strong association with MED1 and hyper-phosphorylation of BRD4 attributable to decreased activity of PP2A, identified here as a principal BRD4 serine phosphatase. Together, these studies provide a rationale for BET inhibition in TNBC and present mechanism-based combination strategies to anticipate clinical drug resistance

Using a smartphone application to promote healthy dietary behaviours and local food consumption

Smartphone “apps” are a powerful tool for public health promotion, but unidimensional interventions have been ineffective at sustaining behavioural change. Various logistical issues exist in successful app development for health intervention programs and for sustaining behavioural change. This study reports on a smartphone application and messaging service, called “SmartAPPetite,” which uses validated behaviour change techniques and a behavioural economic approach to “nudge” users into healthy dietary behaviours. To help gauge participation in and influence of the program, data were collected using an upfront food survey, message uptake tracking, experience sampling interviews, and a follow-up survey. Logistical and content-based issues in the deployment of the messaging service were subsequently addressed to strengthen the effectiveness of the app in changing dietary behaviours. Challenges included creating relevant food goal categories for participants, providing messaging appropriate to self-reported food literacy and ensuring continued participation in the program. SmartAPPetite was effective at creating a sense of improved awareness and consumption of healthy foods, as well as drawing people to local food vendors with greater frequency. This work serves as a storehouse of methods and best practices for multidimensional local food-based smartphone interventions aimed at improving the “triple bottom line” of health, economy, and environment

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Naturalistic driving measures of route selection associate with resting state networks in older adults

Our objective was to identify functional brain changes that associate with driving behaviors in older adults. Within a cohort of 64 cognitively normal adults (age 60+), we compared naturalistic driving behavior with resting state functional connectivity using machine learning. Functional networks associated with the ability to interpret and respond to external sensory stimuli and the ability to multi-task were associated with measures of route selection. Maintenance of these networks may be important for continued preservation of driving abilities