Phase-Sensitive Vibrational Sum and Difference Frequency-Generation Spectroscopy Enabling Nanometer-Depth Profiling at Interfaces

The unique physical and chemical properties of interfaces are governed by a finite depth that describes the transition from the topmost atomic layer to the properties of the bulk material. Thus, understanding the physical nature of interfaces requires detailed insight into the different structures, chemical compositions, and physical processes that form this interfacial region. Such insight has traditionally been difficult to obtain from experiments, as it requires a combination of structural and chemical sensitivity with spatial depth resolution on the nanometer scale. In this contribution, we present a vibrational spectroscopic approach that can overcome these limitations. By combining phase-sensitive sum and difference frequency-generation (SFG and DFG, respectively) spectroscopy and by selectively determining different nonlinear interaction pathways, we can extract precise depth information and correlate these to specific vibrationally resonant modes of interfacial species. We detail the mathematical framework behind this approach and demonstrate the performance of this technique in two sets of experiments on selected model samples. An analysis of the results shows an almost perfect match between experiment and theory, confirming the practicability of the proposed concept under realistic experimental conditions. Furthermore, in measurements with self-assembled monolayers of different chain lengths, we analyze the spatial accuracy of the technique and find that the precision can even reach the sub-nanometer regime. We also discuss the implications and the information content of such depth-sensitive measurements and show that the concept is very general and goes beyond the analysis of the depth profiles. The presented SFG/DFG technique offers new perspectives for spectroscopic investigations of interfaces in various material systems by providing access to fundamental observables that have so far been inaccessible by experiments. Here, we set the theoretical and experimental basis for such future investigations

The Dual Role of Outflows in Quenching Satellites of Low-Mass Hosts: NGC 3109

While dwarf galaxies observed in the field are overwhelmingly star-forming, dwarf galaxies in environments as dense or denser than the Milky Way are overwhelmingly quenched. In this paper, we explore quenching in the lower density environment of the Small-Magellanic-Cloud-mass galaxy NGC 3109 ($\text{M}_* \sim 10^8 \, \text{M}_\odot$), which hosts two known dwarf satellite galaxies (Antlia and Antlia B), both of which are HI deficient compared to similar galaxies in the field and have recently stopped forming stars. Using a new semi-analytic model in concert with the measured star formation histories and gas masses of the two dwarf satellite galaxies, we show that they could not have been quenched solely by direct ram pressure stripping of their interstellar media, as is common in denser environments. Instead, we find that separation of the satellites from pristine gas inflows, coupled with stellar-feedback-driven outflows from the satellites (jointly referred to as the starvation quenching model), can quench the satellites on timescales consistent with their likely infall times into NGC 3109's halo. It is currently believed that starvation is caused by "weak" ram pressure that prevents low-density, weakly-bound gas from being accreted onto the dwarf satellite, but cannot directly remove the denser interstellar medium. This suggests that star-formation-driven outflows serve two purposes in quenching satellites in low-mass environments: outflows from the host form a low-density circumgalactic medium that cannot directly strip the interstellar media from its satellites, but is sufficient to remove loosely-bound gaseous outflows from the dwarf satellites driven by their own star formation.Comment: 20 pages and 2 appendices. To be submitted to MNRAS. Comments welcome

No differences in in vivo kinematics between six different types of knee prostheses

Purpose: The aim of this study was to compare a broad range of total knee prostheses with different design parameters to determine whether in vivo kinematics was consistently related to design. The hypothesis was that there are no clear recognizable differences in in vivo kinematics between different design parameters or prostheses. Methods: At two sites, data were collected by a single observer on 52 knees (49 subjects with rheumatoid arthritis or osteoarthritis). Six different total knee prostheses were used: multi-radius, single-radius, fixed-bearing, mobilebearing, posterior-stabilized, cruciate retaining and cruciate sacrificing. Knee kinematics was recorded using fluoroscopy as the patients performed a step-up motion. Results: There was a significant effect of prosthetic design on all outcome parameters; however, post hoc tests showed that the NexGen group was responsible for 80% of the significant values. The range of knee flexion was much smaller in this group, resulting in smaller anterior-posterior translations and rotations. Conclusion: Despite kinematics being generally consistent with the kinematics intended by their design, there were no clear recognizable differences in in vivo kinematics between different design parameters or prostheses. Hence, the differences in design parameters or prostheses are not distinct enough to have an effect on clinical outcome of patients.Biomechanical EngineeringMechanical, Maritime and Materials Engineerin

Low-density star cluster formation: Discovery of a young faint fuzzy on the outskirts of the low-mass spiral galaxy NGC 247

The classical globular clusters found in all galaxy types have half-light radii of rh ~2-4 pc, which have been tied to formation in the dense cores of giant molecular clouds. Some old star clusters have larger sizes, and it is unclear if these represent a fundamentally different mode of low-density star cluster formation. We report the discovery of a rare, young \u27faint fuzzy\u27 star cluster, NGC 247-SC1, on the outskirts of the low-mass spiral galaxy NGC 247 in the nearby Sculptor group, and measure its radial velocity using Keck spectroscopy. We use Hubble Space Telescope imaging to measure the cluster half-light radius of rh ≃ 12 pc and a luminosity of LV ≃ 4 × 105Lθ. We produce a colour-magnitude diagram of cluster stars and compare to theoretical isochrones, finding an age of ≃300 Myr, a metallicity of [Z/H] ~-0.6 and an inferred mass of M∗ ≃ 9 × 104Mθ. The narrow width of blue-loop star magnitudes implies an age spread of ≲50 Myr, while no old red-giant branch stars are found, so SC1 is consistent with hosting a single stellar population, modulo several unexplained bright \u27red straggler\u27 stars. SC1 appears to be surrounded by tidal debris, at the end of an ∼2 kpc long stellar filament that also hosts two low-mass, low-density clusters of a similar age. We explore a link between the formation of these unusual clusters and an external perturbation of their host galaxy, illuminating a possible channel by which some clusters are born with large sizes

How much time do nurses have for patients? a longitudinal study quantifying hospital nurses' patterns of task time distribution and interactions with health professionals

<p>Abstract</p> <p>Background</p> <p>Time nurses spend with patients is associated with improved patient outcomes, reduced errors, and patient and nurse satisfaction. Few studies have measured how nurses distribute their time across tasks. We aimed to quantify how nurses distribute their time across tasks, with patients, in individual tasks, and engagement with other health care providers; and how work patterns changed over a two year period.</p> <p>Methods</p> <p>Prospective observational study of 57 nurses for 191.3 hours (109.8 hours in 2005/2006 and 81.5 in 2008), on two wards in a teaching hospital in Australia. The validated Work Observation Method by Activity Timing (WOMBAT) method was applied. Proportions of time in 10 categories of work, average time per task, time with patients and others, information tools used, and rates of interruptions and multi-tasking were calculated.</p> <p>Results</p> <p>Nurses spent 37.0%[95%CI: 34.5, 39.3] of their time with patients, which did not change in year 3 [35.7%; 95%CI: 33.3, 38.0]. Direct care, indirect care, medication tasks and professional communication together consumed 76.4% of nurses' time in year 1 and 81.0% in year 3. Time on direct and indirect care increased significantly (respectively 20.4% to 24.8%, P < 0.01;13.0% to 16.1%, P < 0.01). Proportion of time on medication tasks (19.0%) did not change. Time in professional communication declined (24.0% to 19.2%, P < 0.05). Nurses completed an average of 72.3 tasks per hour, with a mean task length of 55 seconds. Interruptions arose at an average rate of two per hour, but medication tasks incurred 27% of all interruptions. In 25% of medication tasks nurses multi-tasked. Between years 1 and 3 nurses spent more time alone, from 27.5%[95%CI 24.5, 30.6] to 39.4%[34.9, 43.9]. Time with health professionals other than nurses was low and did not change.</p> <p>Conclusions</p> <p>Nurses spent around 37% of their time with patients which did not change. Work patterns were increasingly fragmented with rapid changes between tasks of short length. Interruptions were modest but their substantial over-representation among medication tasks raises potential safety concerns. There was no evidence of an increase in team-based, multi-disciplinary care. Over time nurses spent significantly less time talking with colleagues and more time alone.</p

Latent variables and route choice behavior

In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior by proposing and estimating a hybrid model that integrates latent variable and route choice models. Data contain information about latent variable indicators and chosen routes of travelers driving regularly from home to work in an urban network. Choice sets include alternative routes generated with a branch and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers' observable characteristics to latent variables and explanatory variables to utilities. Estimation results illustrate that considering latent variables (i.e., memory, habit, familiarity, spatial ability, time saving skills) alongside traditional variables (e.g., travel time, distance, congestion level) enriches the comprehension of route choice behavior