Figures of personhood

Conceptualizing Linguistic Difference: Perspectives from Linguistic Anthropolog

Marketing Approaches to Human Resources Management In the Hospitality Industry

Now that baby boomers are older and pursuing more career-oriented jobs, managers of the hospitality industry are experiencing the effects of the pre- sent labor crisis; they now know that those vacant hourly jobs are going to be tough to fill with quality personnel. The companies able to attract quality personnel by offering employees what they need and want will be the successful ones in the next decade. The authors explain how the labor crisis is currently affecting the hospitality industry and make suggestions about how firms may survive the labor crash” of the 1990s with the application of marketing technology to human resource management

Substructure of high-p_T Jets at the LHC

We study high-pt jets from QCD and from highly-boosted massive particles such as tops, W, Z and Higgs, and argue that infrared-safe observables can help reduce QCD backgrounds. Jets from QCD are characterized by different patterns of energy flow compared to the products of highly-boosted heavy particle decays, and we employ a variety of jet shapes, observables restricted to energy flow within a jet, to explore this difference. Results from Monte Carlo generators and arguments based on perturbation theory support the discriminating power of the shapes we refer to as planar flow and angularities. We emphasize that for massive jets, these and other observables can be analyzed perturbatively.Comment: 5 pages and 4 figure

A heparin-mimicking polymer conjugate stabilizes basic fibroblast growth factor.

Basic fibroblast growth factor (bFGF) is a protein that plays a crucial role in diverse cellular functions, from wound healing to bone regeneration. However, a major obstacle to the widespread application of bFGF is its inherent instability during storage and delivery. Here, we describe the stabilization of bFGF by covalent conjugation with a heparin-mimicking polymer, a copolymer consisting of styrene sulfonate units and methyl methacrylate units bearing poly(ethylene glycol) side chains. The bFGF conjugate of this polymer retained bioactivity after synthesis and was stable to a variety of environmentally and therapeutically relevant stressors--such as heat, mild and harsh acidic conditions, storage and proteolytic degradation--unlike native bFGF. Following the application of stress, the conjugate was also significantly more active than the control conjugate system in which the styrene sulfonate units were omitted from the polymer structure. This research has important implications for the clinical use of bFGF and for the stabilization of heparin-binding growth factors in general

Prevention of cisplatin-induced hearing loss in children: Informing the design of future clinical trials.

Cisplatin is an essential chemotherapeutic agent in the treatment of many pediatric cancers. Unfortunately, cisplatin-induced hearing loss (CIHL) is a common, clinically significant side effect with life-long ramifications, particularly for young children. ACCL05C1 and ACCL0431 are two recently completed Childrens Oncology Group studies focused on the measurement and prevention of CIHL. The purpose of this paper was to gain insights from ACCL05C1 and ACCL0431, the first published cooperative group studies dedicated solely to CIHL, to inform the design of future pediatric otoprotection trials. Use of otoprotective agents is an attractive strategy for preventing CIHL, but their successful development must overcome a unique constellation of methodological challenges related to translating preclinical research into clinical trials that are feasible, evaluate practical interventions, and limit risk. Issues particularly important for children include use of appropriate methods for hearing assessment and CIHL severity grading, and use of trial designs that are well-informed by preclinical models and suitable for relatively small sample sizes. Increasing interest has made available new funding opportunities for expanding this urgently needed research

A Magnetic and Moessbauer Spectral Study of Core/Shell Structured Fe/Au Nanoparticles

Fe/Au nanoparticles have been chemically synthesized through a reverse micelle reaction and investigated by both conventional and synchrotron based x-ray diffraction and by magnetic and Moessbauer spectral studies. The powder x-ray diffraction patterns reveal both the presence of crystalline alpha-iron and gold and the absence of any crystalline iron oxides or other crystalline products. First-order reversal curves, along with the major hysteresis loops of the Fe/Au nanoparticles have been measured as a function of time in order to investigate the evolution of their magnetic properties. The iron-57 Moessbauer spectra of both uncoated iron nanoparticles and the Fe/Au nanoparticles have been measured at 78 and 295 K and indicate that two major iron containing components are present, namely the expected alpha-iron and the unexpected amorphous Fe1-xBx alloy; several poorly crystallized ordered iron(III) oxide components as well as paramagnetic iron(II) and iron(III) components are also observed. These results indicate that the Fe-core/Au-shell nanoparticles synthesized through reverse micelles are far more complex that had been believed.Comment: 31 pages, 1 table, 8 figures, to appear in Chemistry of Material

An efficient surrogate model for emulation and physics extraction of large eddy simulations

In the quest for advanced propulsion and power-generation systems, high-fidelity simulations are too computationally expensive to survey the desired design space, and a new design methodology is needed that combines engineering physics, computer simulations and statistical modeling. In this paper, we propose a new surrogate model that provides efficient prediction and uncertainty quantification of turbulent flows in swirl injectors with varying geometries, devices commonly used in many engineering applications. The novelty of the proposed method lies in the incorporation of known physical properties of the fluid flow as {simplifying assumptions} for the statistical model. In view of the massive simulation data at hand, which is on the order of hundreds of gigabytes, these assumptions allow for accurate flow predictions in around an hour of computation time. To contrast, existing flow emulators which forgo such simplications may require more computation time for training and prediction than is needed for conducting the simulation itself. Moreover, by accounting for coupling mechanisms between flow variables, the proposed model can jointly reduce prediction uncertainty and extract useful flow physics, which can then be used to guide further investigations.Comment: Submitted to JASA A&C

Appearance and Geometry Assisted Visual Navigation in Urban Areas

Navigation is a fundamental task for mobile robots in applications such as exploration, surveillance, and search and rescue. The task involves solving the simultaneous localization and mapping (SLAM) problem, where a map of the environment is constructed. In order for this map to be useful for a given application, a suitable scene representation needs to be defined that allows spatial information sharing between robots and also between humans and robots. High-level scene representations have the benefit of being more robust and having higher exchangeability for interpretation. With the aim of higher level scene representation, in this work we explore high-level landmarks and their usage using geometric and appearance information to assist mobile robot navigation in urban areas. In visual SLAM, image registration is a key problem. While feature-based methods such as scale-invariant feature transform (SIFT) matching are popular, they do not utilize appearance information as a whole and will suffer from low-resolution images. We study appearance-based methods and propose a scale-space integrated Lucas-Kanade’s method that can estimate geometric transformations and also take into account image appearance with different resolutions. We compare our method against state-of-the-art methods and show that our method can register images efficiently with high accuracy. In urban areas, planar building facades (PBFs) are basic components of the quasirectilinear environment. Hence, segmentation and mapping of PBFs can increase a robot’s abilities of scene understanding and localization. We propose a vision-based PBF segmentation and mapping technique that combines both appearance and geometric constraints to segment out planar regions. Then, geometric constraints such as reprojection errors, orientation constraints, and coplanarity constraints are used in an optimization process to improve the mapping of PBFs. A major issue in monocular visual SLAM is scale drift. While depth sensors, such as lidar, are free from scale drift, this type of sensors are usually more expensive compared to cameras. To enable low-cost mobile robots equipped with monocular cameras to obtain accurate position information, we use a 2D lidar map to rectify imprecise visual SLAM results using planar structures. We propose a two-step optimization approach assisted by a penalty function to improve on low-quality local minima results. Robot paths for navigation can be either automatically generated by a motion planning algorithm or provided by a human. In both cases, a scene representation of the environment, i.e., a map, is useful to specify meaningful tasks for the robot. However, SLAM results usually produce a sparse scene representation that consists of low-level landmarks, such as point clouds, which are neither convenient nor intuitive to use for task specification. We present a system that allows users to program mobile robots using high-level landmarks from appearance data