Gossip vs. Markov Chains, and Randomness-Efficient Rumor Spreading

We study gossip algorithms for the rumor spreading problem which asks one node to deliver a rumor to all nodes in an unknown network. We present the first protocol for any expander graph $G$ with $n$ nodes such that, the protocol informs every node in $O(\log n)$ rounds with high probability, and uses $\tilde{O}(\log n)$ random bits in total. The runtime of our protocol is tight, and the randomness requirement of $\tilde{O}(\log n)$ random bits almost matches the lower bound of $\Omega(\log n)$ random bits for dense graphs. We further show that, for many graph families, polylogarithmic number of random bits in total suffice to spread the rumor in $O(\mathrm{poly}\log n)$ rounds. These results together give us an almost complete understanding of the randomness requirement of this fundamental gossip process. Our analysis relies on unexpectedly tight connections among gossip processes, Markov chains, and branching programs. First, we establish a connection between rumor spreading processes and Markov chains, which is used to approximate the rumor spreading time by the mixing time of Markov chains. Second, we show a reduction from rumor spreading processes to branching programs, and this reduction provides a general framework to derandomize gossip processes. In addition to designing rumor spreading protocols, these novel techniques may have applications in studying parallel and multiple random walks, and randomness complexity of distributed algorithms.Comment: 41 pages, 1 figure. arXiv admin note: substantial text overlap with arXiv:1304.135

Physics-Based Electromigration Modeling and Analysis and Optimization

Long-term reliability is a major concern in modern VLSI design. Literature has shown that reliability gets worse as technology advances. It is expected that the future VLSI systems would have shorter reliability-induced lifetime comparing with previous generations. Being one of the most serious reliability effects, electromigration (EM) is a physical phenomenon of the migration of metal atoms due to the momentum exchange between atoms and the conducting electrons. It can cause wire resistance change or open circuit and result in functional failure of the circuit. Power-ground networks are the most vulnerable part to EM effect among all the interconnect wires since the current flow on this part is the largest on the chip. With new generation oftechnology node and aggressive design strategies, more accurate and efficient EM models are required. However, traditional EM approaches are very conservative and cannot meet current aggressive design strategies. Besides circuit level, EM also need to be thoroughly studied in system level due to limited power and temperature budgets among cores on chip. This research focuses on developing physical level EM model for VLSI circuits and system level EM optimization for multi-core systems in order to overcome the aforementioned problems. Specifically, for physical level, we develop two EM immortality check methods and a power grid EM check method. Firstly, a voltage based EM immortality analysis has been developed. Immortality condition in nucleation phase can be determined fast and accurately for multi-segment interconnect wires. Secondly, a saturation volume based incubation phase immortality check method has been proposed. This method can further reduce the redundancy in VLSI circuit design by immortality check in multiphase. Furthermore, both immortality check methods are integrated into a new power grid EM check methodology (EMspice) as filter for EM analysis. These filters can accelerate the simulation by filtering out immortal trees so that we only need to do simulation on fewer trees that are mortal. Coupled EM simulation considering both hydrostatic stress and electronic current/voltage in the power grid network will be applied to these mortal trees. This tool can work seamlessly with commercial synthesis flow. Besides physical level reliability models, system level reliability optimization is also discussed in this research. A deep reinforcement learning based EM optimization has been proposed for multi-core system. Both long term reliability effect (hard error) and transient soft error are considered. Energy can be optimized with all the reliability and other constraints fast and accurately compared to existing reliability management techniques. Last but not least, a scheduling based reliability optimization method for multi-core systems has been proposed. NBTI, HCI and EM are considered jointly. Lifetime of the system can be improved significantly compared to traditional methods which mainly focus on utilization

Investigation of molecular effects of the soy-derived phytoestrogen genistein on cardiomyocytes by proteomic analysis

2011 Fall.Includes bibliographical references.The soy-derived phytoestrogen genistein (GEN) has received attention for its potential to benefit the cardiovascular system by providing protection to cardiomyocytes against pathophysiological stresses. Although GEN is a well-known estrogen receptor (ER) agonist and a non-specific tyrosine kinase inhibitor, current understanding of the complex cellular and molecular effects of GEN in cardiomyocytes is still incomplete. The overall goal of this dissertation is to use high throughput proteomics methodologies to better understand the molecular action of GEN in cardiomyocytes and to identify proteins and pathways that respond to GEN treatment. The first study of this project focused on the concentration-dependent proteome changes in cultured HL-1 cardiomyocytes due to GEN treatments. Proteins from HL-1 cardiomyocytes treated with 1 μM and 50 μM GEN were prefractionated into hydrophilic and hydrophobic protein fractions and were analyzed by two-dimensional electrophoresis followed by protein identification using tandem mass spectrometry (MS). In total, 25 and 62 differential expressed proteins were identified in response to 1 μM and 50 μM of GEN treatment, respectively. These results suggest that 1 μM GEN enhanced the expression of heat shock proteins and anti-apoptotic proteins, while 50 μM GEN down-regulated glycolytic and antioxidant enzymes, potentially making cardiomyocytes more susceptible to energy depletion and apoptosis. The second study, employing a two-dimensional liquid chromatography and tandem MS shotgun proteomics workflow, was carried out to dissect the cellular functions changed in cardiomyocytes by ER-dependent or ER-independent actions of GEN. In this study, primary cardiomyocytes isolated from male adult SD rats were treated with 10 μM GEN without or with 10 μM ER antagonist ICI 182,780 (ERA) before proteomics comparison. A total of 14 and 15 proteins were found differentially expressed in response to the GEN, and the GEN+ERA treatment, respectively. Cellular functions such as glucose and fatty acid metabolism and cardioprotection were found to be modulated by GEN in an ER-dependent fashion, while proteins involved with steroidogenesis and estrogen signaling were identified as novel effectors of GEN via ER-independent actions. In this study, a consensus-iterative searching strategy was also developed to enhance the sensitivity of the shotgun proteomic approach. In the last study, an attempt to explore the response to a GEN stimulus in the signaling pathways, we developed a phosphopeptide enrichment method to assist the detection of protein phosphorylation in a complex peptide mixture. The quantitative performance of a sequential immobilized metal affinity chromatography (SIMAC) protocol was evaluated. We further conducted a preliminary application of this protocol in a large-scale, quantitative, label-free phosphoproteomics study to explore the alterations of protein phosphorylation patterns due to ER-independent GEN action in the SD rat cardiomyocytes. This project demonstrates the usefulness of proteomics methodologies to screen novel molecular targets influenced by GEN in cardiomyocytes. This is also the first investigation of the complex cellular impact of this soy-derived phytoestrogen in cardiomyocytes via a systems biology perspective

Gossip vs. Markov Chains, and Randomness-Efficient Rumor Spreading

We study gossip algorithms for the rumor spreading problem which asks one node to deliver a rumor to all nodes in an unknown network, and every node is only allowed to call one neighbor in each round. In this work we introduce two fundamentally new techniques in studying the rumor spreading problem: First, we establish a new connection between the rumor spreading process in an arbitrary graph and certain Markov chains. While most previous work analyzed the rumor spreading time in general graphs by studying the rate of the number of (un-)informed nodes after every round, we show that the mixing time of a certain Markov chain suffices to bound the rumor spreading time in an arbitrary graph. Second, we construct a reduction from rumor spreading processes to branching programs. This reduction gives us a general framework to derandomize the rumor spreading and other gossip processes. In particular, we show that, for any n-vertex expander graph, there is a protocol which informs every node in O(log n) rounds with high probability, and uses O (log n · log log n) random bits in total. The runtime of our protocol is tight, and the randomness requirement of O (log n· log log n) random bits almost matches the lower bound of Ω(log n) random bits. We further show that, for many graph families (defined with respect to the expansion and the degree), O (poly log n) random bits in total suffice for fast rumor spreading. These results give us an almost complete understanding of the role of randomness in the rumor spreading process, which was extensively studied over the past years

MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY

Ph.DDOCTOR OF PHILOSOPH

Norm of Reciprocity, Reciprocal Benefits, and Reciprocal Relationships: A Revisit of the Role of Reciprocity in Knowledge Sharing

Reciprocity has been considered one of the most important constructs in knowledge sharing literature. However, prior studies have defined and measured this construct in different ways, leading to mixed research findings about its role. To solve the controversy, based on prior reciprocity literature, we differentiate three relevant concepts namely norm of reciprocity, reciprocal benefits, and reciprocal relationships and propose the causal relationships between these constructs according to the norm internalization theory. A field survey with 386 employees in a Chinese organization is conducted to test the proposed hypotheses. The results show that reciprocal benefits and reciprocal relationships fully mediate the impacts of norm of reciprocity on knowledge sharing intention. These findings suggest that the internalization mechanism (e.g., indirect effect) works better than the compliance mechanism (e.g., direct effect) under the voluntary knowledge sharing context. This study enriches the knowledge sharing literature and provides suggestions on organizational knowledge sharing practices

Establishment of gender- and age-specific reference intervals for serum liver function tests among the elderly population in northeast China: a retrospective study

Reference intervals (RIs) for younger population may not apply to the elderly population. The aim of this study was to establish gender- and age-specific RIs for serum liver function tests among the elderly population and to compare with younger population RIs currently used in China and other countries. This was a retrospective study, and subjects (≥ 18 year-old) were recruited from the laboratory information system (LIS) at the First Hospital of Jilin University between April 2020 and April 2021. The following parameters were collected: aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), alkaline phosphatase (ALP), total protein (TP), albumin (ALB), total bilirubin (TBIL), and direct bilirubin (DBIL). The Tukey method was used to eliminate outliers. Reference intervals were established by the nonparametric method. A total of 23,597 healthy individuals were enrolled in the study. From all parameters AST, ALT, TP and ALB required no gender partition, while ALT, GGT, TP, ALB and DBIL required different partitions for age. Activities and concentrations of ALT, ALB, and TP showed a downward trend in the elderly aged 60-89. In contrast, DBIL showed a gradual upward trend. The RIs for liver function tests among healthy elderly population were different from those among young population in China. There were apparent gender and age differences in the RIs of liver function for elderly and significant differences compared with national standards and RIs in other countries. Therefore, it is necessary to establish gender- and age-specific RIs for serum liver function tests among the elderly population