Focus on the future of clinical care

2006 Annual report of Thomas Jefferson Universit

Orchestrating the future of clinical care

2005 Annual report of Thomas Jefferson University

Redefining healthcare education: Perspectives and accomplishments

2007 Annual report of Thomas Jefferson University

Electromagnetic Propagation Velocities in an Inhomogeneous or Random Atmosphere

This thesis is concerned primarily with determination of statistics for the velocities of propagation of an electromagnetic wave in a dispersive medium. The velocities of propagation are discussed in terms of a plane travelling wave solution of Maxwell\u27s equations obtained using the multiple Laplace transformation and complex inversion integrals. The types of dispersion discussed correspond to a magneto-ionic, electron displacement and polar resonances of the ionosphere and troposphere. The physical nature of the randomness of the dispersive index of refraction is derived from considerations of statistical turbulence theory. Expressions are then obtained for determining the mean, mean square and variance of the signal, group and phase velocity of an electromagnetic wave. It is proposed by S. M. Harris (IRE Trans. Vol. AP-9, No. 2, pp. 207-210, Mar., 1961) that the group velocity and phase velocity of an electromagnetic wave propagated in the ionosphere may be averaged to obtain a velocity estimate free of refraction to within second order refractive effects. The basis for this procedure is that for an operating frequency considerably above the critical frequencies of the ionospheric medium, the group velocity is slightly less than the velocity of light

CATHEDRAL: A Fast and Effective Algorithm to Predict Folds and Domain Boundaries from Multidomain Protein Structures

We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure–based method (using graph theory) to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these domains are already classified in CATH, CATHEDRAL will considerably facilitate the automation of protein structure classification

Illicit Activity Detection in Large-Scale Dark and Opaque Web Social Networks

Many online chat applications live in a grey area between the legitimate web and the dark net. The Telegram network in particular can aid criminal activities. Telegram hosts “chats” which consist of varied conversations and advertisements. These chats take place among automated “bots” and human users. Classifying legitimate activity from illegitimate activity can aid law enforcement in finding criminals. Social network analysis of Telegram chats presents a difficult problem. Users can change their username or create new accounts. Users involved in criminal activity often do this to obscure their identity. This makes establishing the unique identity behind a given username challenging. Thus we explored classifying users from their language usage in their chat messages.The volume and velocity of Telegram chat data place it well within the domain of big data. Machine learning and natural language processing (NLP) tools are necessary to classify this chat data. We developed NLP tools for classifying users and the chat group to which their messages belong. We found that legitimate and illegitimate chat groups could be classified with high accuracy. We also were able to classify bots, humans, and advertisements within conversations

Report of the panel on geopotential fields: Magnetic field, section 9

The objective of the NASA Geodynamics program for magnetic field measurements is to study the physical state, processes and evolution of the Earth and its environment via interpretation of measurements of the near Earth magnetic field in conjunction with other geophysical data. The fields measured derive from sources in the core, the lithosphere, the ionosphere, and the magnetosphere. Panel recommendations include initiation of multi-decade long continuous scalar and vector measurements of the Earth's magnetic field by launching a five year satellite mission to measure the field to about 1 nT accuracy, improvement of our resolution of the lithographic component of the field by developing a low altitude satellite mission, and support of theoretical studies and continuing analysis of data to better understand the source physics and improve the modeling capabilities for different source regions

Treatment Orientation and Associated Characteristics of North American Academic Psychiatrists

We present data showing the degree to which a “biological-psychotherapeutic” division persists in American psychiatry, and how psychiatrists' treatment orientation is associated with personal and professional characteristics. Almost two thirds of academic psychiatrists who responded to our survey (N = 435) could be classified as either biological (27%) or psychotherapeutic (37%) in orientation, according to the proportion of their caseload to which they provided psychotherapy (25% vs. ≥75%). There appears to have been an increase over the last 35 years in the proportion of psychiatrists who can be classified as biologically oriented and a decrease in the proportion who can be classified as psychotherapeutically oriented, as well as the emergence of a large class of intermediate or “eclectic” practitioners (36%). Several personal and professional attributes were distributed differentially according to treatment orientation. Psychotherapeutically oriented respondents more frequently reported personal histories of psychiatric disorders than did biologically oriented respondents (64% vs. 39%) as well as greater satisfaction with clinical work (81% vs. 53% “very satisfied”). Differences were also found in age, gender, history of personal psychotherapy, family history of psychiatric disorder, history of marijuana use, degrees of involvement in research, teaching and clinical care of patients, and overall work satisfaction, as well as other characteristics

Sexual orientation and associated characteristics among north american academic psychiatrists

We mailed questionnaires inquiring about a range of personal and professional attributes to 972 North American psychiatrists at five leading medical schools in the United States and Canada. Of these, 49% (435 psychiatrists) responded. Of the respondents, 90.9% reported being exclusively heterosexual, 3.5% predominantly heterosexual, and 5.6% bisexual/homosexual. Analyses were performed to assess the relationship between sexual orientation and other variables. We found that exclusive heterosexuals were more likely than other psychiatrists to be Jewish (p = .002), to have first‐degree relatives with psychiatric illness (p =.015), and to have conducted research after residency training (p = .034). Exclusively heterosexual psychiatrists were less likely to have used recreational drugs (p = .025), or to prescribe psychotropic medications to none of their patients (p = .017). Sexual orientation was not correlated with a variety of other personal and professional characteristics. The findings suggest that gay men and lesbians are represented within psychiatry at rates comparable to their estimated representation in society. Moreover, the data invite several hypotheses—for example, that medical students may be drawn to psychiatry for specific reasons such as feeling marginalized due to being gay or bisexual