Multi-morbidities are Not a Driving Factor for an Increase of COPD-Related 30-Day Readmission Risk

Background and Objective: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States. COPD is expensive to treat, whereas the quality of care is difficult to evaluate due to the high prevalence of multi-morbidity among COPD patients. In the US, the Hospital Readmissions Reduction Program (HRRP) was initiated by the Centers for Medicare and Medicaid Services to penalize hospitals for excessive 30-day readmission rates for six diseases, including COPD. This study examines the difference in 30-day readmission risk between COPD patients with and without comorbidities.Methods: In this retrospective cohort study, we used Cox regression to estimate the hazard ratio of 30-day readmission rates for COPD patients who had no comorbidity and those who had one, two or three, or four or more comorbidities. We controlled for individual, hospital and geographic factors. Data came from three sources: Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID), Area Health Resources Files (AHRF) and the American Hospital Association’s (AHA’s) annual survey database for the year of 2013.Results: COPD patients with comorbidities were less likely to be readmitted within 30 days relative to patients without comorbidities (aHR from 0.84 to 0.87, p \u3c 0.05). In a stratified analysis, female patients with one comorbidity had a lower risk of 30-day readmission compared to female patients without comorbidity (aHR = 0.80, p \u3c 0.05). Patients with public insurance who had comorbidities were less likely to be readmitted within 30 days in comparison with those who had no comorbidity (aHR from 0.79 to 0.84, p \u3c 0.05).Conclusion: COPD patients with comorbidities had a lower risk of 30-day readmission compared with patients without comorbidity. Future research could use a different study design to identify the effectiveness of the HRRP

Traffic-aware techniques to reduce 3G/LTE wireless energy consumption

The 3G/LTE wireless interface is a significant contributor to battery drain on mobile devices. A large portion of the energy is consumed by unnecessarily keeping the mobile device's radio in its "Active" mode even when there is no traffic. This paper describes the design of methods to reduce this portion of energy consumption by learning the traffic patterns and predicting when a burst of traffic will start or end. We develop a technique to determine when to change the radio's state from Active to Idle, and another to change the radio's state from Idle to Active. In evaluating the methods on real usage data from 9 users over 28 total days on four different carriers, we find that the energy savings range between 51% and 66% across the carriers for 3G, and is 67% on the Verizon LTE network. When allowing for delays of a few seconds (acceptable for background applications), the energy savings increase to between 62% and 75% for 3G, and 71% for LTE. The increased delays reduce the number of state switches to be the same as in current networks with existing inactivity timers.National Science Foundation (U.S.) (Grant CNS-0931550

Best point detour query in road networks

A point detour is a temporary deviation from a user preferred path P (not necessarily a shortest network path) for visiting a data point such as a supermarket or McDonald's. The goodness of a point detour can be measured by the additional traveling introduced, called point detour cost or simply detour cost. Given a preferred path to be traveling on, Best Point Detour (BPD) query aims to identify the point detour with the minimum detour cost. This problem can be frequently found in our daily life but is less studied. In this work, the efficient processing of BPD query is investigated with support of devised optimization techniques. Furthermore, we investigate continuous-BPD query with target at the scenario where the path to be traveling on continuously changes when a user is moving to the destination along the preferred path. The challenge of continuous-BPD query lies in finding a set of update locations which split P into partitions. In the same partition, the user has the same BPD. We process continuous-BPD query by running BPD queries in a deliberately planned strategy. The efficiency study reveals that the number of BPD queries executed is optimal. The efficiency of BPD query and continuous-BPD query processing has been verified by extensive experiments

A Plan for Optimizing Network-Intensive Cloud Applications

A significant and growing number of applications deployed on cloud infrastructures are network-intensive. These applications are frequently bottlenecked by the speed of network connections between the machines on which they are deployed. Due to the complexity and size of cloud networks, such applications often run slowly or have unpredictable completion times and/or throughput, both of which can result in increased cost to the customer. In this paper, we argue that cloud customers should be able to express the demands and objectives of their applications. We outline an architecture that allows for this type of expression, and distributes applications within the cloud network such that the application's objectives are met. We discuss some of the key questions that need to be addressed to implement the architecture, as well as the interactions between optimizations done by clients and by cloud providers. We also present preliminary results that indicate that these types of systems are feasible and improve performance

Delphi: A Software Controller for Mobile Network Selection

This paper presents Delphi, a mobile software controller that helps applications select the best network among available choices for their data transfers. Delphi optimizes a specified objective such as transfer completion time, or energy per byte transferred, or the monetary cost of a transfer. It has four components: a performance predictor that uses features gathered by a network monitor, and a traffic profiler to estimate transfer sizes near the start of a transfer, all fed into a network selector that uses the prediction and transfer size estimate to optimize an objective.For each transfer, Delphi either recommends the best single network to use, or recommends Multi-Path TCP (MPTCP), but crucially selects the network for MPTCP s primary subflow . The choice of primary subflow has a strong impact onthe transfer completion time, especially for short transfers.We designed and implemented Delphi in Linux. It requires no application modifications. Our evaluation shows that Delphi reduces application network transfer time by 46% for Web browsing and by 49% for video streaming, comparedwith Android s default policy of always using Wi-Fi when it is available. Delphi can also be configured to achieve high throughput while being battery-efficient: in this configuration, it achieves 1.9x the throughput of Android s default policy while only consuming 6% more energy

Bilayer graphene nanoribbons junction with aligned holes exhibiting high ZT values

We investigate the thermoelectric performance of armchair graphene nanoribbon (AGNR), bilayer GNRs junction (BGNRJ) and BGNRJ with holes (BGNRJ-H) by the first principles calculation with non-equilibrium Green function. It is found that the BGNRJ-H exhibits high ZT values of 9.65 and 5.55 at 300K. The reason of these significantly larger ZT values than previously observed has been calculated due to reduced thermal conductivity and enhanced electrical conductivity. The low thermal conductance comes from the van der Waals (vdW) interaction between two graphene layers. The increased electrical conductivity can be attributed to the coupling effect of aligned holes in both layers. It is found from analysis results that the electron transmission of the BGNRJ-H is much stronger than a normal BGNRJ, which gives rise to the higher electrical conductance and outstanding ZT values

A NOVEL ROLE OF GELSOLIN IN AUTOPHAGY AND CANCER CELL SURVIVIAL

Ph.DDOCTOR OF PHILOSOPH