Automated design of self-stabilization

Self-stabilization is a property of a distributed system such that, regardless of the legitimacy of its current state, the system behavior shall eventually reach a legitimate state and shall remain legitimate thereafter. The elegance of self-stabilization stems from the fact that it distinguishes distributed systems by a strong fault tolerance property against arbitrary state perturbations. The difficulty of designing and reasoning about self-stabilization has been witnessed by many researchers; most of the existing techniques for the verification and design of self-stabilization are either brute-force, or adopt manual approaches non-amenable to automation. In this dissertation, we first investigate the possibility of automatically designing self-stabilization through global state space exploration. In particular, we develop a set of heuristics for automating the addition of recovery actions to distributed protocols on various network topologies. Our heuristics equally exploit the computational power of a single workstation and the available parallelism on computer clusters. We obtain existing and new stabilizing solutions for classical protocols like maximal matching, ring coloring, mutual exclusion, leader election and agreement. Second, we consider a foundation for local reasoning about self-stabilization; i.e., study the global behavior of the distributed system by exploring the state space of just one of its components. It turns out that local reasoning about deadlocks and livelocks is possible for an interesting class of protocols whose proof of stabilization is otherwise complex. In particular, we provide necessary and sufficient conditions – verifiable in the local state space of every process – for global deadlock- and livelock-freedom of protocols on ring topologies. Local reasoning potentially circumvents two fundamental problems that complicate the automated design and verification of distributed protocols: (1) state explosion and (2) partial state information. Moreover, local proofs of convergence are independent of the number of processes in the network, thereby enabling our assertions about deadlocks and livelocks to apply on rings of arbitrary sizes without worrying about state explosion.

Evolution of the Southern Kenya Rift from Miocene to present with a focus on the Magadi area

The Kenya (a.k.a., Gregory) Rift is a geologically active area located within the eastern branch of the larger East African Rift System (EARS). The study area is located in the southern Kenya Rift between 1° South and the Kenya-Tanzania border (covering approximately 1.5 square degrees, semi-centered on Lake Magadi) and is predominantly filled with extrusive igneous rocks (mostly basalts, phonolites and trachytes) of Miocene age or younger. Sediments are thin, less than 1.5Ma, and are confined to small grabens. The EARS can serve both as an analogue for ancient continental rifting and as a modern laboratory to observe the geologic processes responsible for rifting. This study demonstrates that vintage (as in older, quality maps published by the Kenya Geological Survey, that may be outdated based on newer findings) quarter-degree maps can be successfully combined with recently published data, and used to interpret satellite (mainly Landsat 7) images to produce versatile, updated digital maps. The study area has been remapped using this procedure and although it covers a large area, the mapping retains a quadrangle level of detail. Additionally, all geologic mapping elements (formations, faults, etc.) have been correlated across older map boundaries so that geologic units don't end artificially at degree boundaries within the study area. These elements have also been saved as individual digital files to facilitate future analysis. A series of maps showing the evolution of the southern Kenya rift from the Miocene to the present was created by combining the updated geologic map with age dates for geologic formations and fault displacements. Over 200 age dates covering the entire length of the Kenya Rift have been compiled for this study, and 6 paleo-maps were constructed to demonstrate the evolution of the area, starting with the eruption of the Kishalduga and Lisudwa melanephelinites onto the metamorphic basement around 15Ma. These eruptions occurred before the initial rift faulting and were followed by a massive eruption of phonolites between 13-10 Ma that covered most of the Kenya dome. This was followed by a period of relative quiescence, until the initial faulting defined the western boundary of the rift around 7Ma. The resulting graben was asymmetrical until corresponding faults to the east developed around 3Ma. The rift valley was flooded by basalts and trachytes between 3Ma and 700ka, after which the volcanic activity slowed to a near halt. Since 700ka most of the deposition has been comprised of sediments, mainly from lakes occupying the various basins in the area. The main results of this study are, in addition to a detailed interpretation of the rift development, a new geologic map that correlates dozens of formations across old map boundaries and a compilation of over 300 age dates. Specific products include paleomaps, tables of fault timing and displacement, and volume estimates of volcanic formations. The study concludes with a generalization of the present environment at Magadi including discussions of lagoon chemistry, mantle gases in relation to the trona deposit, and biology of the hot springs. Several biologic samples were collected during the 2006 field season in an attempt to characterize the organisms that are commonly seen in the present Lake Magadi environment. Samples were selected to represent the different, distinctive forms that are found in the hotsprings. Each sample had it own distinctive growth habit, and analysis showed that each was formed by a different cyanobacterial. Actual algae was rare in the collected samples, and represented by a few scattered diatoms.

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

ROLE OF MICRORNA LET-7 IN PANCREATIC BETA CELLS

MicroRNAs (miRNAs) are small non-coding RNAs that inhibit gene expression at transcriptional or post-transcriptional level. Let-7 family is among the first identified human miRNAs and regulates multiple cellular processes including glucose metabolism in multiple organs. It has been reported that overexpression of let-7 resulted in insulin resistance and impaired glucose tolerance through repressing insulin signaling pathway in both muscle and liver. However, the role and mechanism underlying let-7 function in pancreatic beta-cells have yet to be elucidated. Let-7 family contains nine members, which poses a significant challenge in complete deletion of this miRNA family. To study the function of let-7 and to overcome the functional redundancies of various let-7 members in pancreatic beta-cells, the highly expressed let-7a and let-7b were blocked simultaneously using short tandem target mimic (STTM) approach developed in our laboratory. Introducing STTM-let7 into beta-cells markedly increased the expression of Caspase 3, a direct target of let-7, confirming a sufficient functional knockdown of let-7a/b by STTM-let7. STTM-let7 enhanced apoptotic cell death induced by cytokine, indicating that let-7a/b is able to protect from apoptosis through attenuating Caspase 3 expression in pancreatic beta-cells. In contrast to the previous observation that let-7 silencing increases insulin signaling in muscle and liver, inhibition of let-7 with STTM-let7 significantly repressed glucose-stimulated insulin signaling in pancreatic beta-cells, leading to impaired insulin secretion and reduced beta-cell proliferation. Taken together, an appropriate level of let-7 is essential in maintaining beta-cell function and viability. Dysregulation of let-7 may contribute to the pathogenesis of type 2 diabetes.

FAULT MORPHOLOGY WITHIN THE SOUTHERN KENYAN PORTION OF THE EAST AFRICAN RIFT VALLEY

Faults form quickly, geologically speaking, with sharp, crisp step-like profiles. Logic dictates that erosion wears away this "sharpness" or angularity creating more rounded features. As erosion occurs, debris accumulates at the base of the scarp slope. The stable end point of this process is when the scarp slope approaches an ideal sigmoid shape. This theory of fault end process, in combination with a new method developed in this report for fault profile delineation, has the potential to enable observation and categorization of fault profiles over large, diverse swaths of fault formation-- in remote areas such as the Southern Kenyan Rift Valley. This up-to date method uses remote sensing data and the digitizer tool in Global Mapper to create shape files of fault segments. This method can provide further evidence to support the notion that sigmoidal- shaped profiles represent a natural endpoint of the erosional process of fault scarps. Over time, faults of many different ages would exist in this similar shape over a wide region. However, keeping in mind that other processes can be at work on scarps-- most notably drainage patterns, when anomalies in profiles are observed, reactivation in some form possibly has occurred.