COLLATERAL BENEFITS OF DIABETES SELF-MANAGEMENT ASSOCIATED WITH SELF-ADMINISTERED OUTPATIENT PARENTERAL ANTIMICROBIAL THERAPY

Self-administered outpatient parenteral antimicrobial therapy (S-OPAT) is a self-care treatment modality in which patients requiring extended courses of intravenous antibiotics are trained to safely self-administer treatment via an indwelling catheter in their home. Many patients seen in the S-OPAT program have a diagnosis of diabetes and present with infections associated with poor glycemic control, including skin and soft-tissue infections and osteomyelitis. Given the degree of patient activation required to successfully complete the S-OPAT process, we hypothesized that participation in this self-care program may benefit patients in self-management of other chronic health conditions, such as diabetes. The study team included Anisha Ganguly (MPH candidate), Larry Brown (biostatistician), David Watkins, Dr. Kristin Alvarez, Dr. Deepak Agrawal, and Dr. Kavita Bhavan, founder and director of the Parkland S-OPAT clinic. We conducted a before-after retrospective analysis of diabetic patients receiving S-OPAT. HgbA1c, diabetes medication refill rates, and changes to diabetes medication regimen were compared in 6-month intervals prior to and following initiation of S-OPAT. A total number of 348 diabetic patients were identified, and 206 diabetic patients were included in the analysis. The mean HgbA1c decreased by 1.82 from the time period 6 months prior to and 6 months after initiation of S-OPAT (p \u3c 0.001). Subgroup analysis showed an additional significant reduction in HgbA1c among insulin users (p = 0.002). There were no differences in refill rates of diabetes medications or changes in medication regimen pre- and post-initiation of S-OPAT (p \u3e 0.05). Initiation of S-OPAT was associated with a significant reduction in HgbA1c among diabetic patients with similar findings among insulin users, a group requiring a higher level of self-care. The degree of patient engagement obtained through the S-OPAT model may have collateral benefits in improved self-management of other chronic diseases such as diabetes

Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations

To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Topics, Top 5 Hotels in Paris or 10 Most Viewed News Stories), which rely on crowdsourced popularity signals to select the items. However, different sections of a crowd may have different preferences, and there is a large silent majority who do not explicitly express their opinion. Also, the crowd often consists of actors like bots, spammers, or people running orchestrated campaigns. Recommendation algorithms today largely do not consider such nuances, hence are vulnerable to strategic manipulation by small but hyper-active user groups. To fairly aggregate the preferences of all users while recommending top-K items, we borrow ideas from prior research on social choice theory, and identify a voting mechanism called Single Transferable Vote (STV) as having many of the fairness properties we desire in top-K item (s)elections. We develop an innovative mechanism to attribute preferences of silent majority which also make STV completely operational. We show the generalizability of our approach by implementing it on two different real-world datasets. Through extensive experimentation and comparison with state-of-the-art techniques, we show that our proposed approach provides maximum user satisfaction, and cuts down drastically on items disliked by most but hyper-actively promoted by a few users.Comment: In the proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). Please cite the conference versio

Soliton Lattice and Single Soliton Solutions of the Associated Lam\'e and Lam\'e Potentials

We obtain the exact nontopological soliton lattice solutions of the Associated Lam\'e equation in different parameter regimes and compute the corresponding energy for each of these solutions. We show that in specific limits these solutions give rise to nontopological (pulse-like) single solitons, as well as to different types of topological (kink-like) single soliton solutions of the Associated Lam\'e equation. Following Manton, we also compute, as an illustration, the asymptotic interaction energy between these soliton solutions in one particular case. Finally, in specific limits, we deduce the soliton lattices, as well as the topological single soliton solutions of the Lam\'e equation, and also the sine-Gordon soliton solution.Comment: 23 pages, 5 figures. Submitted to J. Math. Phy

Infrared spectroscopic studies of the oxide-​hydroxides of nickel, cobalt, and manganese

Metal oxide-​hydroxides of the general formula MO(OH) (M = Ni3+, Co3+ and Mn3+) are actually bronzes of the corresponding quadrivalent metal oxides and should be represented as HxMO2 (x = 1)​. IR spectroscopic studies show that these compds. do not exhibit any OH stretch. The protons seem to be delocalized between slabs of MO2

Deep Neural Network Cloud-Type Classification (DeepCTC) model and its application in evaluating PERSIANN-CCS

Satellite remote sensing plays a pivotal role in characterizing hydrometeorological components including cloud types and their associated precipitation. The Cloud Profiling Radar (CPR) on the Polar Orbiting CloudSat satellite has provided a unique dataset to characterize cloud types. However, data from this nadir-looking radar offers limited capability for estimating precipitation because of the narrow satellite swath coverage and low temporal frequency. We use these high-quality observations to build a Deep Neural Network Cloud-Type Classification (DeepCTC) model to estimate cloud types from multispectral data from the Advanced Baseline Imager (ABI) onboard the GOES-16 platform. The DeepCTC model is trained and tested using coincident data from both CloudSat and ABI over the CONUS region. Evaluations of DeepCTC indicate that the model performs well for a variety of cloud types including Altostratus, Altocumulus, Cumulus, Nimbostratus, Deep Convective and High clouds. However, capturing low-level clouds remains a challenge for the model. Results from simulated GOES-16 ABI imageries of the Hurricane Harvey event show a large-scale perspective of the rapid and consistent cloud-type monitoring is possible using the DeepCTC model. Additionally, assessments using half-hourly Multi-Radar/Multi-Sensor (MRMS) precipitation rate data (for Hurricane Harvey as a case study) show the ability of DeepCTC in identifying rainy clouds, including Deep Convective and Nimbostratus and their precipitation potential. We also use DeepCTC to evaluate the performance of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) product over different cloud types with respect to MRMS referenced at a half-hourly time scale for July 2018. Our analysis suggests that DeepCTC provides supplementary insights into the variability of cloud types to diagnose the weakness and strength of near real-time GEO-based precipitation retrievals. With additional training and testing, we believe DeepCTC has the potential to augment the widely used PERSIANN-CCS algorithm for estimating precipitation

Time lower bounds for nonadaptive turnstile streaming algorithms

We say a turnstile streaming algorithm is "non-adaptive" if, during updates, the memory cells written and read depend only on the index being updated and random coins tossed at the beginning of the stream (and not on the memory contents of the algorithm). Memory cells read during queries may be decided upon adaptively. All known turnstile streaming algorithms in the literature are non-adaptive. We prove the first non-trivial update time lower bounds for both randomized and deterministic turnstile streaming algorithms, which hold when the algorithms are non-adaptive. While there has been abundant success in proving space lower bounds, there have been no non-trivial update time lower bounds in the turnstile model. Our lower bounds hold against classically studied problems such as heavy hitters, point query, entropy estimation, and moment estimation. In some cases of deterministic algorithms, our lower bounds nearly match known upper bounds

Structure, bonding and magnetism in cobalt clusters

The structural, electronic and magnetic properties of Co$_n$ clusters ($n=2-$20) have been investigated using density functional theory within the pseudopotential plane wave method. An unusual hexagonal growth pattern has been observed in the intermediate size range, $n=15-$20. The cobalt atoms are ferromagnetically ordered and the calculated magnetic moments are found to be higher than that of corresponding hcp bulk value, which are in good agreement with the recent Stern-Gerlach experiments. The average coordination number is found to dominate over the average bond length to determine the effective hybridization and consequently the cluster magnetic moment.Comment: 12 pages and 9 figure

The Advantage of Increased Resolution in the Study of Quasar Absorption Systems

We compare a new R = 120,000 spectrum of PG1634+706 (z_QSO = 1.337,m_V = 14.9) obtained with the HDS instrument on Subaru to a R = 45, 000 spectrum obtained previously with HIRES/Keck. In the strong MgII system at z = 0.9902 and the multiple cloud, weak MgII system at z = 1.0414, we find that at the higher resolution, additional components are resolved in a blended profile. We find that two single-cloud weak MgII absorbers were already resolved at R = 45,000, to have b = 2 - 4 km/s. The narrowest line that we measure in the R = 120, 000 spectrum is a component of the Galactic NaI absorption, with b = 0.90+/-0.20 km/s. We discuss expectations of similarly narrow lines in various applications, including studies of DLAs, the MgI phases of strong MgII absorbers, and high velocity clouds. By applying Voigt profile fitting to synthetic lines, we compare the consistency with which line profile parameters can be accurately recovered at R = 45,000 and R = 120,000. We estimate the improvement gained from superhigh resolution in resolving narrowly separated velocity components in absorption profiles. We also explore the influence of isotope line shifts and hyperfine splitting in measurements of line profile parameters, and the spectral resolution needed to identify these effects. Super high resolution spectra of quasars, which will be routinely possible with 20-meter class telescopes, will lead to greater sensitivity for absorption line surveys, and to determination of more accurate physical conditions for cold phases of gas in various environments.Comment: To appear in AJ. Paper with better resolution images available at http://www.astro.psu.edu/users/anand/superhigh.AJ.pd