Combinatorial Generation of Test Suites

Testgen is a computer program that generates suites of input and configuration vectors for testing other software or software/hardware systems. As systems become ever more complex, often, there is not enough time to test systems against all possible combinations of inputs and configurations, so test engineers need to be selective in formulating test plans. Testgen helps to satisfy this need: In response to a test-suite-requirement-specification model, it generates a minimal set of test vectors that satisfies all the requirements

Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent

This software implements a real-time access control protocol that is intended to make all connected users aware of the presence of other connected users, and which of them is currently in control of the system. Here, "in control" means that a single user is authorized and enabled to issue instructions to the system. The software The software also implements a goal scheduling mechanism that can detect situations where plans for the operation of a target system proposed by different users overlap and interact in conflicting ways. In such situations, the system can either simply report the conflict (rejecting one goal or the entire plan), or reschedule the goals in a way that does not conflict. The access control mechanism (and associated control protocol) is unique. Other access control mechanisms are generally intended to authenticate users, or exclude unauthorized access. This software does neither, and would likely depend on having some other mechanism to support those requirements

Adaptable state based control system

An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment

Real-Time Projection to Verify Plan Success During Execution

The Mission Data System provides a framework for modeling complex systems in terms of system behaviors and goals that express intent. Complex activity plans can be represented as goal networks that express the coordination of goals on different state variables of the system. Real-time projection extends the ability of this system to verify plan achievability (all goals can be satisfied over the entire plan) into the execution domain so that the system is able to continuously re-verify a plan as it is executed, and as the states of the system change in response to goals and the environment. Previous versions were able to detect and respond to goal violations when they actually occur during execution. This new capability enables the prediction of future goal failures; specifically, goals that were previously found to be achievable but are no longer achievable due to unanticipated faults or environmental conditions. Early detection of such situations enables operators or an autonomous fault response capability to deal with the problem at a point that maximizes the available options. For example, this system has been applied to the problem of managing battery energy on a lunar rover as it is used to explore the Moon. Astronauts drive the rover to waypoints and conduct science observations according to a plan that is scheduled and verified to be achievable with the energy resources available. As the astronauts execute this plan, the system uses this new capability to continuously re-verify the plan as energy is consumed to ensure that the battery will never be depleted below safe levels across the entire plan

Relationship between smoking and obesity:a cross-sectional study of 499,504 middle-aged adults in the UK general population

Background: There is a general perception that smoking protects against weight gain and this may influence commencement and continuation of smoking, especially among young women.<p></p> Methods: A cross-sectional study was conducted using baseline data from UK Biobank. Logistic regression analyses were used to explore the association between smoking and obesity; defined as body mass index (BMI) >30kg/m2. Smoking was examined in terms of smoking status, amount smoked, duration of smoking and time since quitting and we adjusted for the potential confounding effects of age, sex, socioeconomic deprivation, physical activity, alcohol consumption, hypertension and diabetes.<p></p> Results: The study comprised 499,504 adults aged 31 to 69 years. Overall, current smokers were less likely to be obese than never smokers (adjusted OR 0.83 95% CI 0.81-0.86). However, there was no significant association in the youngest sub-group (≤40 years). Former smokers were more likely to be obese than both current smokers (adjusted OR 1.33 95% CI 1.30-1.37) and never smokers (adjusted OR 1.14 95% CI 1.12-1.15). Among smokers, the risk of obesity increased with the amount smoked and former heavy smokers were more likely to be obese than former light smokers (adjusted OR 1.60, 95% 1.56-1.64, p<0.001). Risk of obesity fell with time from quitting. After 30 years, former smokers still had higher risk of obesity than current smokers but the same risk as never smokers.<p></p> Conclusion: Beliefs that smoking protects against obesity may be over-simplistic; especially among younger and heavier smokers. Quitting smoking may be associated with temporary weight gain. Therefore, smoking cessation interventions should include weight management support.<p></p&gt

New highlights on stroma–epithelial interactions in breast cancer

Although the stroma in which carcinomas arise has been previously regarded as a bystander to the clonal expansion and acquisition of malignant characteristics of tumor cells, it is now generally acknowledged that stromal changes are required for the establishment of cancer. In the present article, we discuss three recent publications that highlight the complex role the stroma has during the development of cancer and the potential for targeting the stroma by therapeutic approaches

Eclipses During the 2010 Eruption of the Recurrent Nova U Scorpii

The eruption of the recurrent nova U Scorpii on 28 January 2010 is now the all-time best observed nova event. We report 36,776 magnitudes throughout its 67 day eruption, for an average of one measure every 2.6 minutes. This unique and unprecedented coverage is the first time that a nova has any substantial amount of fast photometry. With this, two new phenomena have been discovered: the fast flares in the early light curve seen from days 9-15 (which have no proposed explanation) and the optical dips seen out of eclipse from days 41-61 (likely caused by raised rims of the accretion disk occulting the bright inner regions of the disk as seen over specific orbital phases). The expanding shell and wind cleared enough from days 12-15 so that the inner binary system became visible, resulting in the sudden onset of eclipses and the turn-on of the supersoft X-ray source. On day 15, a strong asymmetry in the out-of-eclipse light points to the existence of the accretion stream. The normal optical flickering restarts on day 24.5. For days 15-26, eclipse mapping shows that the optical source is spherically symmetric with a radius of 4.1 R_sun. For days 26-41, the optical light is coming from a rim-bright disk of radius 3.4 R_sun. For days 41-67, the optical source is a center-bright disk of radius 2.2 R_sun. Throughout the eruption, the colors remain essentially constant. We present 12 eclipse times during eruption plus five just after the eruption.Comment: ApJ in press. 60 pages, 17 figure

Stromal Fibroblasts in Digestive Cancer

The normal gastrointestinal stroma consists of extra-cellular matrix and a community of stromal cells including fibroblasts, myofibroblasts, smooth muscle cells, pericytes, endothelium and inflammatory cells. α-smooth muscle actin (α-SMA) positive stromal fibroblasts, often referred to as myofibroblasts or activated fibroblasts, are critical in the development of digestive cancer and help to create an environment that is permissive of tumor growth, angiogenesis and invasion. This review focusses on the contribution of activated fibroblasts in carcinogenesis and where possible directly applies this to, and draws on examples from, gastrointestinal cancer. In particular, the review expands on the definition, types and origins of activated fibroblasts. It examines the molecular biology of stromal fibroblasts and their contribution to the peritumoral microenvironment and concludes by exploring some of the potential clinical applications of this exciting branch of cancer research. Understanding the origin and biology of activated fibroblasts will help in the development of an integrated epithelial-stromal sequence to cancer that will ultimately inform cancer pathogenesis, natural history and future therapeutics