Stentz, D. A., Vita, Engineer's Council for Professional Development

NPS 1959 Professors in Engineer's Council for Professional DevelopmentNPS 1959 Professors in Engineer's Council for Professional Developmen

Fertility and Childbearing Among American Female Physicians

Background: Female physicians may experience unique challenges regarding fertility and family planning. We sought to determine childbearing patterns and decision-making among American female physicians. Materials and Methods: In 2012?2013, we surveyed a random sample of 600 female physicians who graduated medical school between 1995 and 2000. Primary outcome measures included fertility and childbearing history, reflections regarding decision-making, perceptions of workplace support, and estimations of childbearing potential. Results: Response rate was 54.5% (327/600). A majority (82.0%) of the sample were parents, 77.4% had biological children with an average of 2.3 children. Average age at medical school graduation was 27.5 years, at completion of training (completion of medical school, residency, and/or fellowship) was 31.6 years, and at first pregnancy was 30.4 years. Nearly one quarter (24.1%) of respondents who had attempted conception were diagnosed with infertility, with an average age at diagnosis of 33.7 years. Among those with infertility, 29.3% reported diminished ovarian reserve. When asked what they would do differently in retrospect, most respondents (56.8%) would do nothing differently regarding fertility/conception/childbearing, 28.6% would have attempted conception earlier, 17.1% would have gone into a different specialty, and 7.0% would have used cryopreservation to extend fertility. Fewer of those whose first pregnancy was in medical school perceived substantial workplace support (68.2%) than those whose first pregnancies followed training (88.6%). Conclusions: A substantial proportion of female physicians have faced infertility or have regrets about family planning decisions and career decision-making. Combining a medical career with motherhood continues to pose challenges, meriting further investigation and targeted support.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140144/1/jwh.2015.5638.pd

Experiencing Extreme Height for The First Time: The Influence of Height, Self-Judgment of Fear and a Moving Structural Beam on the Heart Rate and Postural Sway During the Quiet Stance

Falling from elevated surfaces is the main cause of death and injury at construction sites. Based on the Bureau of Labor Statistics (BLS) reports, an average of nearly three workers per day suffer fatal injuries from falling. Studies show that postural instability is the foremost cause of this disproportional falling rate. To study what affects the postural stability of construction workers, we conducted a series of experiments in the virtual reality (VR). Twelve healthy adults—all students at the University of Nebraska-Lincoln—were recruited for this study. During each trial, participants’ heart rates and postural sways were measured as the dependent factors. The independent factors included a moving structural beam (MB) coming directly at the participants, the presence of VR, height, the participants’ self-judgment of fear, and their level of acrophobia. The former was designed in an attempt to simulate some part of the steel erection procedure, which is one of the key tasks of ironworkers. The results of this study indicate that height increase the postural sway. Self-judged fear significantly was found to decrease postural sway, more specifically the normalized total excursion of the center of pressure (TE), both in the presence and absence of height. Also, participants’ heart rates significantly increase once they are confronted by a moving beam in the virtual environment (VE), even though they are informed that the beam will not ‘hit’ them. The findings of this study can be useful for training novice ironworkers that will be subjected to height and/or steel erection for the first time

Expecting the Unexpected : Measuring Uncertainties in Mobile Robot Path Planning in Dynamic Envionments

Unexpected obstacles pose significant challenges to mobile robot navigation. In this paper we investigate how, based on the assumption that unexpected obstacles really follow patterns that can be exploited, a mobile robot can learn the locations within an environment that are likely to contain obstacles, and so plan optimal paths by avoiding these locations in subsequent navigation tasks. We propose the DUNC (Dynamically Updating Navigational Confidence) method to do this. We evaluate the performance of the DUNC method by comparing it with existing methods in a large number of randomly generated simulated test environments. our evaluations show that, by learning the likely locations of unexpected obstacles, the DUNC method can plan more efficient paths than existing approaches to this problem

In Silico Analysis of the Small Molecule Content of Outer Membrane Vesicles Produced by Bacteroides thetaiotaomicron Indicates an Extensive Metabolic Link between Microbe and Host

The interactions between the gut microbiota and its host are of central importance to the health of the host. Outer membrane vesicles (OMVs) are produced ubiquitously by Gram-negative bacteria including the gut commensal Bacteroides thetaiotaomicron. These vesicles can interact with the host in various ways but until now their complement of small molecules has not been investigated in this context. Using an untargeted high-coverage metabolomic approach we have measured the small molecule content of these vesicles in contrasting in vitro conditions to establish what role these metabolites could perform when packed into these vesicles. B. thetaiotaomicron packs OMVs with a highly conserved core set of small molecules which are strikingly enriched with mouse-digestible metabolites and with metabolites previously shown to be associated with colonization of the murine GIT. By use of an expanded genome-scale metabolic model of B. thetaiotaomicron and a potential host (the mouse) we have established many possible metabolic pathways between the two organisms that were previously unknown, and have found several putative novel metabolic functions for mouse that are supported by gene annotations, but that do not currently appear in existing mouse metabolic networks. The lipidome of these OMVs bears no relation to the mouse lipidome, so the purpose of this particular composition of lipids remains unclear. We conclude from this analysis that through intimate symbiotic evolution OMVs produced by B. thetaiotaomicron are likely to have been adopted as a conduit for small molecules bound for the mammalian host in vivo

Sampling-based Algorithms for Optimal Motion Planning

During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics Researc

Use of bioengineered human commensal gut bacteria-derived microvesicles for mucosal plague vaccine delivery and immunization

Plague caused by the Gram-negative bacterium, Yersinia pestis, is still endemic in parts of the world today. Protection against pneumonic plague is essential to prevent the development and spread of epidemics. Despite this, there are currently no licensed plague vaccines in the western world. Here we describe the means of delivering biologically active plague vaccine antigens directly to mucosal sites of plague infection using highly stable microvesicles (outer membrane vesicles; OMVs) that are naturally produced by the abundant and harmless human commensal gut bacterium Bacteroides thetaiotaomicron (Bt). Bt was engineered to express major plague protective antigens in its OMVs, specifically Fraction 1 (F1) in the outer membrane and LcrV (V antigen) in the lumen, for targeted delivery to the gastrointestinal (GI) and respiratory tracts in a non-human primate (NHP) host. Our key findings were that Bt OMVs stably expresses F1 and V plague antigens, particularly the V antigen, in the correct, immunogenic form. When delivered intranasally V-OMVs elicited substantive and specific immune and antibody responses, both in the serum [immunoglobulin (Ig)G] and in the upper and lower respiratory tract (IgA); this included the generation of serum antibodies able to kill plague bacteria. Our results also showed that Bt OMV-based vaccines had many desirable characteristics, including: biosafety and an absence of any adverse effects, pathology or gross alteration of resident microbial communities (microbiotas); high stability and thermo-tolerance; needle-free delivery; intrinsic adjuvanticity; the ability to stimulate both humoral and cell-mediated immune responses; and targeting of primary sites of plague infection

Coupling 3D Geomechanics to Classical Petroleum System Simulation

Geomechanical models of classical petroleum system simulators are limited to 1D phenomenological laws relating porosity to vertical effective stress. In order to overcome this limitation, a 3D poromechanical model is integrated in the sedimentary basin simulation by applying an iterative coupling scheme between a conventional basin code and a mechanical finite element code. This paper presents the porous material constitutive law specifically devised to deal with basin modeling, together with essential aspects of the mechanical code implementation and explicit coupling workflow. The numerical procedure is first verified according to a semi-analytical solution and then compared to an implicit academic code. Finally, a 3D synthetic case demonstrates the importance of incorporating 3D geomechanics to basin simulation. The results show that tectonic compression may significantly contribute to overpressure development and natural fracturing of seal rocks, contrary to the standard procedures of petroleum system simulation which are unable to capture such effect

Is a Priming Dose of Insulin Necessary in a Low-Dose Insulin Protocol for the Treatment of Diabetic Ketoacidosis?

OBJECTIVE—The purpose of this study was to assess the efficacy of an insulin priming dose with a continuous insulin infusion versus two continuous infusions without a priming dose