Synthesis and Evaluation of Osteogenic Oxysterols as Hedgehog Pathway Activators

Oxysterols (OHCs) are metabolic byproducts of cholesterol that are known to function as agonists of the Hedgehog (Hh) signaling pathway. Previously, we reported 23(S)‐hydroxycholesterol [23(S)‐OHC, 4 ] as a potent activator of Hh signaling with the ability to functionally differentiate mouse embryonic fibroblasts to an osteogenic fate. To obtain 23(S)‐OHC in quantities suitable for in vivo evaluation, we developed a revised synthetic route that decreases the number of steps and chromatographic purifications, and which also enhances the stereoselective nature of the synthesis. This new route also allows access to the C21 methyl group of the OHC scaffold, and several new analogues with varying stereochemistry at this location were evaluated for their ability to up‐regulate the Hh pathway.     

A methodology for predicting and comparing the full‐scale fire performance of similar materials based on small‐scale testing

Reconstructive fire testing is an important tool used by fire investigators to determine the cause, origin, and progression of a particular fire. Accurate reconstruction of the fire requires the laboratory structure to be outfitted with materials that, in terms of contribution to fire growth, perform similarly to the original materials found at the fire scene. Therefore, a procedure was developed to enable fire investigators to select these replacement materials on the basis of a quantitative assessment of their relative fire performance. This procedure consists of gram‐scale and/or milligram‐scale standard testing accompanied by inverse numerical modeling of these tests, which is used to obtain relevant material properties. A numerical model composed of a detailed pyrolysis submodel and empirical flame heat feedback submodels, which were developed in this study, is subsequently employed to simulate the early stages of the Room Corner Test, which was selected to represent full‐scale material performance. The results of these simulations demonstrate that this procedure can successfully differentiate between fire growth propensities of several commercially available medium density fiberboards.     

Identification of channelling and recirculation parameters of agitated pulp stock chests

This paper describes a mechanism for identifying the dynamics of non-ideal mixing processes. The object is to study two of the non-ideal behaviours of agitated pulp stock chests: recirculation and channelling. An initial continuous-time model, which contains physically relevant parameters, is transformed into its discrete-time counterpart. This transformation introduces some challenging identification problems, as the discrete-time parameters become a non-linear combination of the original continuous-time parameters. A system identification methodology that addresses these challenges is developed and demonstrated by means of computer simulation. The analysis of data collected from experiments on a laboratory scale model of an industrial chest shows the potential of the techniques developed in this paper.     

Geometric Approach to Digital Quantum Information

We present geometric methods for uniformly discretizing the continuous N-qubit Hilbert space H_N. When considered as the vertices of a geometrical figure, the resulting states form the equivalent of a Platonic solid. The discretization technique inherently describes a class of /2 rotations that connect neighboring states in the set, i.e., that leave the geometrical figures invariant. These rotations are shown to generate the Clifford group, a general group of discrete transformations on N qubits. Discretizing H_N allows us to define its digital quantum information content, and we show that this information content grows as N². While we believe the discrete sets are interesting because they allow extra-classical behavior—such as quantum entanglement and quantum parallelism—to be explored while circumventing the continuity of Hilbert space, we also show how they may be a useful tool for problems in traditional quantum computation. We describe in detail the discrete sets for one and two qubits.PACS: 03.67.Lx; 03.67.pp; 03.67.-a; 03.67.Mn.PACS: 03.67.Lx; 03.67.pp; 03.67.-a; 03.67.Mn.     

Dynamic effects of self-efficacy on smoking lapse and relapse.

Self-efficacy (SE) is thought to be critical to success in smoking cessation both as an individual difference and as a dynamic process after a quit attempt. In this study, 214 smokers used palm-top computers to record day-to-day variations in SE during 4 weeks after quitting. SE remained at high and stable levels prior to a 1st lapse but decreased and became more variable thereafter. The authors used event history models with time-varying covariates to assess the effect of daily SE on lapse and relapse risk. Daily SE measures predicted an initial lapse on the subsequent day. However, this relationship was accounted for by stable baseline differences in SE (assessed by questionnaire), rather than by day-to-day dynamics in SE. Progression from 1st lapse to relapse was also examined. In this instance, daily SE predicted subsequent relapse risk, even when baseline SE and concurrent smoking were accounted for, suggesting the importance of SE dynamics for this stage of the relapse process. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mechanical principles of dynamic terrestrial self-righting using wings

Terrestrial animals and robots are susceptible to flipping-over during rapid locomotion in complex terrains. However, small robots are less capable of self-righting from an upside-down orientation compared to small animals like insects. Inspired by the winged discoid cockroach, we designed a new robot that opens its wings to self-right by pushing against the ground. We used this robot to systematically test how self-righting performance depends on wing opening magnitude, speed, and asymmetry, and modeled how kinematic and energetic requirements depend on wing shape and body/wing mass distribution. We discovered that the robot self-rights dynamically using kinetic energy to overcome potential energy barriers, that larger and faster symmetric wing opening increases self-righting performance, and that opening wings asymmetrically increases righting probability when wing opening is small. Our results suggested that the discoid cockroach’s winged self-righting is a dynamic maneuver. While the thin, lightweight wings of the discoid cockroach and our robot are energetically sub-optimal for self-righting compared to tall, heavy ones, their ability to open wings saves them substantial energy compared to if they had static shells. Analogous to biological exaptations, our study provided a proof-of-concept for terrestrial robots to use existing morphology in novel ways to overcome new locomotor challenges.     

A longitudinal study of emoticon use in text messaging from smartphones

Our goal in the present study was to understand how emoticons are used in text messaging and, in particular, how genders differed in the frequency and variety of emoticons used via this medium. Previous research has found small and sundry differences in emotive expression online suggesting that technology has closed the gender gap. However, the data collected in these studies were public. In this study, we collected real portions of private communications data from individuals’ smartphones over a 6-month period. SMS messages, in general, were not used very much overall, with only 4% of all messages containing at least one emoticon. Still, differences between genders manifested in the amount and variety of emoticons used. Females sent more messages with emoticons; however, surprisingly, males used a more diverse range of emoticons.     

Personalcasting: Tailored Broadcast News

Broadcast news sources and newspapers provide society with the vast majority of real-time information. Unfortunately, cost efficiencies and real-time pressures demand that producers, editors, and writers select and organize content for stereotypical audiences. In this article we illustrate how content understanding, user modeling, and tailored presentation generation promise personalcasts on demand. Specifically, we report on the design and implementation of a personalized version of a broadcast news understanding system, MITRE’s Broadcast News Navigator (BNN), that tracks and infers user content interests and media preferences. We report on the incorporation of Local Context Analysis to both expand the user’s original query to the most related terms in the corpus, as well as to allow the user to provide interactive feedback to enhance the relevance of selected newsstories. We describe an empirical study of the search for stories on ten topics from a video corpus. By personalizing both the selection of stories and the form in which they are delivered, we provide users with tailored broadcast news. This individual news personalization provides more fine-grained content tailoring than current personalized television program level recommenders and does not rely on externally provided program metadata.     

Interval Set Clustering of Web Users with Rough K-Means

Data collection and analysis in web mining faces certain unique challenges. Due to a variety of reasons inherent in web browsing and web logging, the likelihood of bad or incomplete data is higher than conventional applications. The analytical techniques in web mining need to accommodate such data. Fuzzy and rough sets provide the ability to deal with incomplete and approximate information. Fuzzy set theory has been shown to be useful in three important aspects of web and data mining, namely clustering, association, and sequential analysis. There is increasing interest in research on clustering based on rough set theory. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. For example, the clusters and associations in web mining do not necessarily have crisp boundaries. As a result, researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have used genetic algorithms based on rough set theory for clustering. However, the genetic algorithms based clustering may not be able to handle the large amount of data typical in a web mining application. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents clusters as interval or rough sets. The paper also describes the design of an experiment including data collection and the clustering process. The experiment is used to create interval set representations of clusters of web visitors.