Probabilistic methods for distributed information dissemination

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 457-484).The ever-increasing growth of modern networks comes with a paradigm shift in network operation. Networks can no longer be abstracted as deterministic, centrally controlled systems with static topologies but need to be understood as highly distributed, dynamic systems with inherent unreliabilities. This makes many communication, coordination and computation tasks challenging and in many scenarios communication becomes a crucial bottleneck. In this thesis, we develop new algorithms and techniques to address these challenges. In particular we concentrate on broadcast and information dissemination tasks and introduce novel ideas on how randomization can lead to powerful, simple and practical communication primitives suitable for these modern networks. In this endeavor we combine and further develop tools from different disciplines trying to simultaneously addresses the distributed, information theoretic and algorithmic aspects of network communication. The two main probabilistic techniques developed to disseminate information in a network are gossip and random linear network coding. Gossip is an alternative to classical flooding approaches: Instead of nodes repeatedly forwarding information to all their neighbors, gossiping nodes forward information only to a small number of (random) neighbors. We show that, when done right, gossip disperses information almost as quickly as flooding, albeit with a drastically reduced communication overhead. Random linear network coding (RLNC) applies when a large amount of information or many messages are to be disseminated. Instead of routing messages through intermediate nodes, that is, following a classical store-and-forward approach, RLNC mixes messages together by forwarding random linear combinations of messages. The simplicity and topology-obliviousness of this approach makes RLNC particularly interesting for the distributed settings considered in this thesis. Unfortunately the performance of RLNC was not well understood even for the simplest such settings. We introduce a simple yet powerful analysis technique that allows us to prove optimal performance guarantees for all settings considered in the literature and many more that were not analyzable so far. Specifically, we give many new results for RLNC gossip algorithms, RLNC algorithms for dynamic networks, and RLNC with correlated data. We also provide a novel highly efficient distributed implementation of RLNC that achieves these performance guarantees while buffering only a minimal amount of information at intermediate nodes. We then apply our techniques to improve communication primitives in multi-hop radio networks. While radio networks inherently support broadcast communications, e.g., from one node to all surrounding nodes, interference of simultaneous transmissions makes multihop broadcast communication an interesting challenge. We show that, again, randomization holds the key for obtaining simple, efficient and distributed information dissemination protocols. In particular, using random back-off strategies to coordinate access to the shared medium leads to optimal gossip-like communications and applying RLNC achieves the first throughput-optimal multi-message communication primitives. Lastly we apply our probabilistic approach for analyzing simple, distributed propagation protocols in a broader context by studying algorithms for the Lovász Local Lemma. These algorithms find solutions to certain local constraint satisfaction problems by randomly fixing and propagating violations locally. Our two main results show that, firstly, there are also efficient deterministic propagation strategies achieving the same and, secondly, using the random fixing strategy has the advantage of producing not just an arbitrary solution but an approximately uniformly random one. Both results lead to simple, constructions for a many locally consistent structures of interest that were not known to be efficiently constructable before.by Bernhard Haeupler.Ph.D

Medicinal plants use in Nigeria for the management of hypertension and diabetes

Worldwide, people constantly embrace alternative and/or complementary therapies, which include traditional medicinal plants (TMPs), for management of their health conditions. Two non-communicable diseases, hypertension and diabetes, evoke growing concerns over the escalating health threat which they pose to humanity globally. Over the past decade these conditions have become two of the biggest healthcare issues in Africa, rivalling communicable diseases. This study focuses on the use of TMPs for the management of hypertension and diabetes in Nigeria, Africa’s most populous country. The aim is to determine using questionnaire, the extent of the usage of these TMPs. The high prevalence of hypertension and diabetes in Nigeria is a national health problem. The impact of poor management due mainly to unaffordable healthcare costs makes it more burdensome on the patients. These factors, combined with disease complications, exacerbate the financial plight of individual families. Hence the search for alternatives. This study considers the drive behind TMP use. A survey among HTN and DM patients in two South Eastern Nigeria hospitals was run based on a structured/semi-structured questionnaire administered over 600 patients. The results of this study show high prevalence in the use of TMPs for the management of hypertension and diabetes. Approximately, 75% of the participants use TMPs. All of them use TMPs concurrently with their prescription medicines, predisposing them to severe hypotension or hypoglycaemia, possibilities of drug interactions, direct toxicities, as well as adulteration with active pharmaceutical agents. Also, the poor quality of herbal medicines raises safety concerns. Directions for use of these TMPs are scanty or anecdotal. Consequently, fifty (50) plants commonly used by these patients were recorded with known pharmacokinetic parameters. Most of these TMPs have been proven to possess therapeutic properties and pharmacological effects, thus providing a baseline for investigation into their uses by patients. Vernonia amygdalina (bitter leaf), Ocimum gratissimum (sweet basil/scent leaf) and Gongronema latifolium (bush buck) were three of the most commonly used medicinal plants identified from this work. Quantitative statistical cross-analysis was used to make statistical inferences using data from this study. It was ascertained that there were some associations between the use of TMPs by patients, their conditions and demographics. This study is important as it forms the basis of a future study - survey to be conducted on Nigerian doctors – to ascertain their views on alternative medicine and its integration into the national healthcare system. Keywords: Hypertension; Diabetes mellitus; Traditional medicines; Medicinal plants; Nigeria; South Eastern Nigeria; CAM; ethnobotany; ethnopharmacology; Antihypertensive, herbs, herbal remedies; hypertension/diabetes and medicinal plant

Understanding transcriptional regulation through computational analysis of single-cell transcriptomics

Gene expression is tightly regulated by complex transcriptional regulatory mechanisms to achieve specific expression patterns, which are essential to facilitate important biological processes such as embryonic development. Dysregulation of gene expression can lead to diseases such as cancers. A better understanding of the transcriptional regulation will therefore not only advance the understanding of fundamental biological processes, but also provide mechanistic insights into diseases. The earlier versions of high-throughput expression profiling techniques were limited to measuring average gene expression across large pools of cells. In contrast, recent technological improvements have made it possible to perform expression profiling in single cells. Single-cell expression profiling is able to capture heterogeneity among single cells, which is not possible in conventional bulk expression profiling. In my PhD, I focus on developing new algorithms, as well as benchmarking and utilising existing algorithms to study the transcriptomes of various biological systems using single-cell expression data. I have developed two different single-cell specific network inference algorithms, BTR and SPVAR, which are based on two different formalisms, Boolean and autoregression frameworks respectively. BTR was shown to be useful for improving existing Boolean models with single-cell expression data, while SPVAR was shown to be a conservative predictor of gene interactions using pseudotime-ordered single-cell expression data. In addition, I have obtained novel biological insights by analysing single-cell RNAseq data from the epiblast stem cells reprogramming and the leukaemia systems. Three different driver genes, namely Esrrb, Klf2 and GY118F, were shown to drive reprogramming of epiblast stem cells via different reprogramming routes. As for the leukaemia system, FLT3-ITD and IDH1-R132H mutations were shown to interact with each other and potentially predispose some cells for developing acute myeloid leukaemia.Wellcome Trust and Cambridge Trus

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 24th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2021, which was held during March 27 until April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The 28 regular papers presented in this volume were carefully reviewed and selected from 88 submissions. They deal with research on theories and methods to support the analysis, integration, synthesis, transformation, and verification of programs and software systems

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space