Using Mobile Apps to Improve Medication Adherence in Patients with Hypertension

BACKGROUND: Medication non-adherence (MNA) is one of modern medicine\u27s most prominent challenges, directly contributing to increased healthcare expenditures, poorer health outcomes, and higher mortality rates. Patients diagnosed with hypertension (HTN) are often disproportionally impacted by MNA. In recent years, mobile medication applications (MMAs) have emerged as a promising intervention to address MNA, offering medication reminders, patient-specific education, and adherence tracking data. LOCAL PROBLEM: This project was hosted by a primary care office in Johnson City, TN, which, before this project, had no standard practice for addressing MNA. The AIM of this project was to assess if MMAs could decrease the rate of MNA among the hypertensive patient population in a local primary care clinic by at least 10%. METHODS: The project was directed by the Johns Hopkins Nursing Evidence-Based Practice Model. Outcomes were measured by verbally obtaining a baseline Hill-Bone Medication Adherence Score (HB-MAS), then repeating the process via phone call 90 days post-intervention. After the project was completed, patients were assessed on their opinion of the application and utilization of the application. INTERVENTIONS: During implementation, patients were assisted with downloading the Medisafe MMA, entering medications, and setting dose reminders. RESULTS: When all participants were considered (N=11), there was a statistically significant improvement in MA (P=0.013). However, participants who utilized the app (N=7) showed a greater statistical improvement in medication adherence (P=0.006). A positive correlation was identified between how often the application was used and how much the participant’s HB-MAS score improved. CONCLUSIONS: MMAs are a low-cost, easy-to-use intervention for improving MNA. For this project, using MMAs led to a statistically significant improvement in MA, making them a promising intervention for MNA

DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack

Deep Neural Networks (DNNs) are extremely computationally demanding, which presents a large barrier to their deployment on resource-constrained devices. Since such devices are where many emerging deep learning applications lie (e.g., drones, vision-based medical technology), significant bodies of work from both the machine learning and systems communities have attempted to provide optimizations to accelerate DNNs. To help unify these two perspectives, in this paper we combine machine learning and systems techniques within the Deep Learning Acceleration Stack (DLAS), and demonstrate how these layers can be tightly dependent on each other with an across-stack perturbation study. We evaluate the impact on accuracy and inference time when varying different parameters of DLAS across two datasets, seven popular DNN architectures, four DNN compression techniques, three algorithmic primitives with sparse and dense variants, untuned and auto-scheduled code generation, and four hardware platforms. Our evaluation highlights how perturbations across DLAS parameters can cause significant variation and across-stack interactions. The highest level observation from our evaluation is that the model size, accuracy, and inference time are not guaranteed to be correlated. Overall we make 13 key observations, including that speedups provided by compression techniques are very hardware dependent, and that compiler auto-tuning can significantly alter what the best algorithm to use for a given configuration is. With DLAS, we aim to provide a reference framework to aid machine learning and systems practitioners in reasoning about the context in which their respective DNN acceleration solutions exist in. With our evaluation strongly motivating the need for co-design, we believe that DLAS can be a valuable concept for exploring the next generation of co-designed accelerated deep learning solutions

The SMC5/6 Complex Represses the Replicative Program of High-Risk Human Papillomavirus Type 31

The multi-subunit structural maintenance of chromosomes (SMC) 5/6 complex includes SMC6 and non-SMC element (NSE)3. SMC5/6 is essential for homologous recombination DNA repair and functions as an antiviral factor during hepatitis B (HBV) and herpes simplex-1 (HSV-1) viral infections. Intriguingly, SMC5/6 has been found to associate with high-risk human papillomavirus (HPV) E2 regulatory proteins, but the functions of this interaction and its role during HPV infection remain unclear. Here, we further characterize SMC5/6 interactions with HPV-31 E2 and its role in the HPV life cycle. Co-immunoprecipitation (co-IP) revealed that SMC6 interactions with HPV-31 E2 require the E2 transactivation domain, implying that SMC5/6 interacts with full-length E2. Using chromatin immunoprecipitation, we found that SMC6 is present on HPV-31 episomes at E2 binding sites. The depletion of SMC6 and NSE3 increased viral replication and transcription in keratinocytes maintaining episomal HPV-31, indicating that SMC5/6 restricts the viral replicative program. SMC6 interactions with E2 were reduced in the presence of HPV-31 E1, suggesting that SMC6 and E1 compete for E2 binding. Our findings demonstrate SMC5/6 functions as a repressor of the viral replicative program and this may involve inhibiting the initiation of viral replication

Optimizing Grouped Convolutions on Edge Devices

When deploying a deep neural network on constrained hardware, it is possible to replace the network's standard convolutions with grouped convolutions. This allows for substantial memory savings with minimal loss of accuracy. However, current implementations of grouped convolutions in modern deep learning frameworks are far from performing optimally in terms of speed. In this paper we propose Grouped Spatial Pack Convolutions (GSPC), a new implementation of grouped convolutions that outperforms existing solutions. We implement GSPC in TVM, which provides state-of-the-art performance on edge devices. We analyze a set of networks utilizing different types of grouped convolutions and evaluate their performance in terms of inference time on several edge devices. We observe that our new implementation scales well with the number of groups and provides the best inference times in all settings, improving the existing implementations of grouped convolutions in TVM, PyTorch and TensorFlow Lite by 3.4x, 8x and 4x on average respectively. Code is available at https://github.com/gecLAB/tvm-GSPC/Comment: Camera ready version to be published at ASAP 2020 - The 31st IEEE International Conference on Application-specific Systems, Architectures and Processors. 8 pages, 6 figure

1998 Fine Art Graduation Exhibition Catalogue

Fine Art ProgramFanshawe College McIntosh GalleryUniversity of Western Ontario April 16th to May 3rd., 1998 Guest Speaker: Michael P. Gibson Director: Michael Gibson Galleryhttps://first.fanshawec.ca/famd_design_fineart_gradcatalogues/1009/thumbnail.jp

Lack of Transit Timing Variations of OGLE-TR-111b: A re-analysis with six new epochs

We present six new transits of the exoplanet OGLE-TR-111b observed with the Magellan Telescopes in Chile between April 2008 and March 2009. We combine these new transits with five previously published transit epochs for this planet between 2005 and 2006 to extend the analysis of transit timing variations reported for this system. We derive a new planetary radius value of 1.019 +/- 0.026 R_J, which is intermediate to the previously reported radii of 1.067 +/- 0.054 R_J (Winn et al. 2007) and 0.922 +/- 0.057 R_J (Diaz et al. 2008). We also examine the transit timing variation and duration change claims of Diaz et al. (2008). Our analysis of all eleven transit epochs does not reveal any points with deviations larger than 2 sigma, and most points are well within 1 sigma. Although the transit duration nominally decreases over the four year span of the data, systematic errors in the photometry can account for this result. Therefore, there is no compelling evidence for either a timing or a duration variation in this system. Numerical integrations place an upper limit of about 1 M_E on the mass of a potential second planet in a 2:1 mean-motion resonance with OGLE-TR-111b.Comment: 28 pages, 7 tables, 6 figures. Accepted by Ap

Optimization of human papillomavirus-based pseudovirus techniques for efficient gene transfer

Human papillomavirus (HPV) L1 and L2 capsid proteins self-assemble into virions capable of efficiently packaging either its 8 kilobase genome or non-viral DNA. The ability of HPV capsids to package non-viral DNA makes these a useful tool for delivering plasmids to study proteins of interest in a variety of cell types. We describe optimization of current methods and present new protocols for using HPV capsids to deliver non-viral DNA thereby providing an alternative to DNA transfection. Using keratinocyte generated extracellular matrices can enhance infection efficiency in keratinocytes, hepatocytes and neuronal cells. Furthermore, we describe a suspension-based efficient technique for infecting different cell types

Re-examining the decline in the US saving rate: The impact of mortgage equity withdrawal

In this paper we examine the role of mortgage equity withdrawal in explaining the decline of the US saving rate, since when house prices rise and mortgage rates are low, homeowners have an incentive to withdraw housing equity and this may affect the saving rate. We estimate a Vector Error Correction (VEC) model including the sav- ing rate, asset prices, equity withdrawal and interest rates and find that indeed mortgage equity withdrawal is a key determinant of the observed saving pattern

Engaging "seldom heard" groups in research and intervention development: Offender mental health.

BACKGROUND: People subject to the criminal justice system often have substantially different life-experiences from the general population. Patient and public involvement (PPI) of "seldom heard" groups provides valuable experiential knowledge, enhancing research. OBJECTIVE: To share our jointly developed techniques to ensure the meaningful engagement and contribution of people with lived experience of the criminal justice system (PWLECJS) in research, trial science, intervention theory development and dissemination. METHODS: Commitment to adequate financial resources, appropriate staff skills and adequate time were combined with previous learning. PWLECJS were approached through local community organizations. A group was established and met fortnightly for ten months in an unthreatening environment and had a rolling membership. Ongoing engagement was promoted by the group taking responsibility for the rules, interactive and accessible activities, feeding back tangible impacts, ongoing contact, building a work ethic, joint celebrations, sessions with individual academic researchers and pro-actively managed endings. RESULTS: The Peer Researchers contributed to study documents, training academic researchers, research data collection and analysis, intervention delivery and theory development and trial science. The Peer Researchers gained in confidence and an improved sense of self-worth. The Academic Researchers gained skills, knowledge and an increased openness to being challenged. DISCUSSION AND CONCLUSIONS: PWLECJS can be meaningful included in health research and intervention development. The key elements required are listed. Challenges included differences in priorities for timescales and dissemination, resource limitations and the use of Peer Researchers' names. Further research is required to understand what might be of relevance for other "seldom heard" groups

Orthopedic Surgeon's Awareness Can Improve Osteoporosis Treatment Following Hip Fracture: A Prospective Cohort Study

Through retrospective Jeju-cohort study at 2005, we found low rates of detection of osteoporosis (20.1%) and medication for osteoporosis (15.5%) in those who experienced hip fracture. This study was to determine the orthopedic surgeons' awareness could increase the osteoporosis treatment rate after a hip fracture and the patient barriers to osteoporosis management. We prospectively followed 208 patients older than 50 yr who were enrolled for hip fractures during 2007 in Jeju-cohort. Thirty four fractures in men and 174 in women were treated at the eight hospitals. During the study period, orthopedic surgeons who worked at these hospitals attended two education sessions and were provided with posters and brochures. Patients were interviewed 6 months after discharge using an evaluation questionnaire regarding their perceptions of barriers to osteoporosis treatment. The patients were followed for a minimum of one year. Ninety-four patients (45.2%) underwent detection of osteoporosis by dual energy x-ray absorptiometry and 67 (32.2%) were prescribed medication for osteoporosis at the time of discharge. According to the questionnaire, the most common barrier to treatment for osteoporosis after a hip fracture was patients reluctance. The detection and medication rate for osteoporosis after hip fracture increased twofold after orthopedic surgeons had attended the intervention program. Nevertheless, the osteoporosis treatment rate remains inadequate