Performance and Power Characterization of Cellular Networks and Mobile Application Optimizations.

Smartphones with cellular data access have become increasingly popular with the wide variety of mobile applications. However, the performance and power footprint of these mobile applications are not well-understood, and due to the unawareness of the cellular specific characteristics, many of these applications are causing inefficient radio resource and device energy usage. In this dissertation, we aim at providing a suite of systematic methodology and tools to better understand the performance and power characteristics of cellular networks (3G and the new LTE 4G networks) and the mobile applications relying upon, and to optimize the mobile application design based on this understanding. We have built the MobiPerf tool to understand the characteristics of cellular networks. With this knowledge, we make detailed analysis on smartphone application performance via controlled experiments and via a large-scale data set from one major U.S. cellular carrier. To understand the power footprint of mobile applications, we have derived comprehensive power models for different network types and characterize radio energy usage of various smartphone applications via both controlled experiments and 7-month-long traces collected from 20 real users. Specifically, we characterize the radio and energy impact of the network traffic generated when the phone screen is off and propose the screen-aware traffic optimization. In addition to shedding light to the mobile application design throughout our characterization analysis, we further design and implement a real optimization system RadioProphet, which uses historical traffic features to make predictions and intelligently deallocate radio resource for improved radio and energy efficiency.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99905/1/hjx_1.pd

Efficient Correlated Topic Modeling with Topic Embedding

Correlated topic modeling has been limited to small model and problem sizes due to their high computational cost and poor scaling. In this paper, we propose a new model which learns compact topic embeddings and captures topic correlations through the closeness between the topic vectors. Our method enables efficient inference in the low-dimensional embedding space, reducing previous cubic or quadratic time complexity to linear w.r.t the topic size. We further speedup variational inference with a fast sampler to exploit sparsity of topic occurrence. Extensive experiments show that our approach is capable of handling model and data scales which are several orders of magnitude larger than existing correlation results, without sacrificing modeling quality by providing competitive or superior performance in document classification and retrieval.Comment: KDD 2017 oral. The first two authors contributed equall

Saikosaponins induced hepatotoxicity in mice via lipid metabolism dysregulation and oxidative stress: a proteomic study

Background Radix Bupleuri (RB) has been popularly used for treating many liver diseases such as chronic hepatic inflammation and viral Hepatitis in China. Increasing clinical and experimental evidence indicates the potential hepatotoxicity of RB or prescriptions containing RB. Recently, Saikosaponins (SS) have been identified as major bioactive compounds isolated from RB, which may be also responsible for RB-induced liver injury. Methods Serum AST, ALT and LDH levels were determined to evaluate SS-induced liver injury in mice. Serum and liver total triglyceride and cholesterol were used to indicate lipid metabolism homeostasis. Liver ROS, GSH, MDA and iNOS were used to examine the oxidative stress level after SS administration. Western blot was used to detect CYP2E1 expression. A 8-Plex iTRAQ Labeling Coupled with 2D LC - MS/MS technique was applied to analyze the protein expression profiles in livers of mice administered with different doses of SS for different time periods. Gene ontology analysis, cluster and enrichment analysis were employed to elucidate potential mechanism involved. HepG2 cells were used to identify our findings in vitro. Results SS dose- and time-dependently induced liver injury in mice, indicated by increased serum AST, ALT and LDH levels. According to proteomic analysis, 487 differentially expressed proteins were identified in mice administrated with different dose of SS for different time periods. Altered proteins were enriched in pathways such as lipid metabolism, protein metabolism, macro molecular transportation, cytoskeleton structure and response to stress. SS enhanced CYP2E1 expression in a time and dose dependent manner, and induced oxidative stress both in vivo and in vitro. Conclusion Our results identified hepatotoxicity and established dose-time course-liver toxicity relationship in mice model of SS administration and suggested potential mechanisms, including impaired lipid and protein metabolism and oxidative stress. The current study provides experimental evidence for clinical safe use of RB, and also new insights into understanding the mechanism by which SS and RB induced liver injury

Soil–Plant Indices Help Explain Legume Response to Crop Rotation in a Semiarid Environment

Crop productivity is typically affected by various soil–plant factors systematically as they influence plant photosynthesis, soil fertility, and root systems. However, little is known about how the productivity of legumes is related to crop rotation systems. The objectives of this study were to determine the effect of rotation systems on legume productivity and the relationships among legume productivity and soil–plant factors. Three annual legumes – chickpea (Cicer arietinum L.), pea (Pisum sativum L.), and lentil (Lens culinaris Medikus), were included in various diversified rotation systems and compared with legume monoculture in the 8-year rotation study. Soil N and water conditions, and canopy and root systems were evaluated at the end of 8-year rotation in the semiarid Canadian prairies. Results showed that diversified rotation systems improved leaf greenness by 4%, shoot biomass by 25%, nodule biomass by 44%, and seed yield by 95% for chickpea and pea, but such effects were not found for lentil. Pea monocultures increased root rot severity by threefold compared with diversified rotations, and chickpea monoculture increased shoot rot severity by 23%, root rot severity by 96% and nodule damage by 219%. However, all the legume monocultures improved soil N accumulation by an average 38% compared to diversified systems. Pea and chickpea displayed considerable sensitivity to plant biotic stresses, whereas lentil productivity had a larger dependence on initial soil N content. The 8-year study concludes that the rotational effect on legume productivity varies with legume species, the frequency of a legume appearing in the rotation, and the integration of relevant soil and plant indices

RadioProphet: Intelligent Radio Resource Deallocation for Cellular Networks

Abstract. Traditionally, radio resources are released in cellular networks by statically configured inactivity timers, causing substantial resource inefficiencies. We propose a novel system RadioProphet (RP), which dynamically and intelligently determines in real time when to deallocate radio resources by predicting the network idle time based on traffic history. We evaluate RP using 7-month-long real-world cellular traces. Properly configured, RP correctly predicts 85.9 % of idle time instances and achieves radio energy savings of 59.1 % at the cost of 91.0 % of signaling overhead, outperforming existing proposals. We also implement and evaluate RP on real Android devices, demonstrating its negligible runtime overhead.

CLASH: Extreme Emission Line Galaxies and Their Implication on Selection of High-Redshift Galaxies

We utilize the CLASH (Cluster Lensing And Supernova survey with Hubble) observations of 25 clusters to search for extreme emission-line galaxies (EELGs). The selections are carried out in two central bands: F105W (Y105) and F125W (J125), as the flux of the central bands could be enhanced by the presence of [O III] 4959, 5007 at redshift of about 0.93-1.14 and 1.57-1.79, respectively. The multi-band observations help to constrain the equivalent widths of emission lines. Thanks to cluster lensing, we are able to identify 52 candidates down to an intrinsic limiting magnitude of 28.5 and to a rest-frame [O III] 4959,5007 equivalent width of about 3737 angstrom. Our samples include a number of EELGs at lower luminosities that are missed in other surveys, and the extremely high equivalent width can be only found in such faint galaxies. These EELGs can mimic the dropout feature similar to that of high redshift galaxies and contaminate the color-color selection of high redshift galaxies when the S/N ratio is limited or the band coverage is incomplete. We predict that the fraction of EELGs in the future high redshift galaxy selections cannot be neglected.Comment: 17 pages, 9 figures, 2 tables, Accepted for publication in AP

Novel TLR7/8 agonists promote activation of HIV-1 latent reservoirs and human T and NK cells

Antiretroviral therapy can successfully suppress HIV-1 replication to undetectable levels but fails to eliminate latent and persistent HIV-1 reservoirs. Recent studies have focused on the immunomodulatory agents such as Toll-like receptor 7 and 8 (TLR7 and TLR8) capable of activating, thereby rendering the reservoir susceptible to antiretroviral inhibition and immune recognition and elimination. In this context, this study focused on generating a diverse repertoire of TLR7/8 agonists to identify more potent candidates for activating latent HIV-1 and immune cells’ response. Through combinational strategies of computer-aided design and biological characterization, 159 pyrido [3,2-d] pyrimidine and pyridine-2-amine-based derivatives were synthesized. Of which, two TLR7/8 dual and one TLR8-specific agonists with exceptionally high potency in activating HIV-1 latent reservoirs in cell lines and PBMCs of patients with persistent and durable virologic controls were identified. Particularly, these agonists appeared to enhance NK and T cells activity, which were correlated with the degree of surface activation markers. The outcome of this study highlights the remarkable potential of TLR7/8 agonists in simultaneously activating HIV-1 from the latently infected cells and augmenting immune effector cells

Simulation of a floating solar farm in waves with a novel sun-tracking system

12th International Workshop on Ship and Marine Hydrodynamics (IWSH-2023) 28/08/2023 - 01/09/2023 Aalto University, Espoo, FinlandThe awareness of the energy and climate crisis has accelerated the development of renewable energy sources. Photovoltaic (PV) solar power plants harvest clean solar energy and convert it to electricity, which will be one of the most promising alternatives to the power industry in the context of a low-carbon society. Due to its low power density, the traditional deployment of PV systems on land or inland rivers requires much space. Therefore, industries are increasingly interested in expanding offshore Floating PhotoVoltaics (FPV) to oceans, where FPV has less influence on the marine environment and does not occupy precious space for land resources and human activities. This study performs a hydrodynamics-based structural response analysis for a novel FPV system in OpenFOAM. The wave-proof FPV platform is newly designed for this work, which integrated breakwater technologies to sustain the system's survivability in harsh ocean-wave environments. Firstly, the rational mooring types for FPVs installed close to the island are studied considering seabed effects. Subsequently, extensive parametric studies have been conducted to determine a rational design strategy for the mitigation of wave impact. Several potential effects of the proposed platforms on the hydrodynamics in a coastal sea are evaluated for the first time.Innovate UK: 1004818