1,065 research outputs found
IoT Localization and Optimized Topology Extraction Using Eigenvector Synchronization
Internet-of-Things (IoT) devices are low size, weight and power (SWaP), low
complexity and include sensors, meters, wearables and trackers. Transmitting
information with high signal power is exacting on device battery life,
therefore an efficient link and network configuration is absolutely crucial to
avoid signal power enhancement in interference-rich environment and resorting
to battery-life extending strategies. Efficient network configuration can also
ensure fulfilment of network performance metrics like throughput, coding rate
and spectral efficiency. We formulate a novel approach of first localizing the
IoT nodes and then extracting the network topology for information exchange
between the nodes (devices, gateway and sinks), such that overall network
throughput is maximized. The nodes are localized using noisy measurements of a
subset of Euclidean distances between two nodes. Realizable subsets of
neighboring devices agree with their own position within the entire network
graph through eigenvector synchronization. Using communication global
graph-model-based technique, network topology is constructed in terms of
transmit power allocation with the aim of maximizing spatial usage and overall
network throughput. This topology extraction problem is solved using the
concept of linear programming
Tradition and Innovation in Construction Project Management
This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings
Reconstruction of graph colourings
A -deck of a (coloured) graph is a multiset of its induced -vertex
subgraphs. Given a graph , when is it possible to reconstruct with high
probability a uniformly random colouring of its vertices in colours from
its -deck? In this paper, we study this question for grids and random
graphs. Reconstruction of random colourings of -dimensional -grids from
the deck of their -subgrids is one of the most studied colour reconstruction
questions. The 1-dimensional case is motivated by the problem of reconstructing
DNA sequences from their `shotgunned' stretches. It was comprehensively studied
and the above reconstruction question was completely answered in the '90s. In
this paper, we get a very precise answer for higher . For every
and every , we present an almost linear algorithm that reconstructs
with high probability a random -colouring of vertices of a -dimensional
-grid from the deck of all its -subgrids for every and prove that the random -colouring is not
reconstructible with high probability if .
This answers the question of Narayanan and Yap (that was asked for )
on "two-point concentration" of the minimum so that -subgrids determine
the entire colouring. Next, we prove that with high probability a uniformly
random -colouring of vertices of a uniformly random graph is
reconstructible from its full -deck if and is not
reconstructible with high probability if . We further
show that the colour reconstruction algorithm for random graphs can be modified
and used for graph reconstruction: we prove that with high probability
is reconstructible from its full -deck if
while it is not reconstructible with high probability if
Behavior quantification as the missing link between fields: Tools for digital psychiatry and their role in the future of neurobiology
The great behavioral heterogeneity observed between individuals with the same
psychiatric disorder and even within one individual over time complicates both
clinical practice and biomedical research. However, modern technologies are an
exciting opportunity to improve behavioral characterization. Existing
psychiatry methods that are qualitative or unscalable, such as patient surveys
or clinical interviews, can now be collected at a greater capacity and analyzed
to produce new quantitative measures. Furthermore, recent capabilities for
continuous collection of passive sensor streams, such as phone GPS or
smartwatch accelerometer, open avenues of novel questioning that were
previously entirely unrealistic. Their temporally dense nature enables a
cohesive study of real-time neural and behavioral signals.
To develop comprehensive neurobiological models of psychiatric disease, it
will be critical to first develop strong methods for behavioral quantification.
There is huge potential in what can theoretically be captured by current
technologies, but this in itself presents a large computational challenge --
one that will necessitate new data processing tools, new machine learning
techniques, and ultimately a shift in how interdisciplinary work is conducted.
In my thesis, I detail research projects that take different perspectives on
digital psychiatry, subsequently tying ideas together with a concluding
discussion on the future of the field. I also provide software infrastructure
where relevant, with extensive documentation.
Major contributions include scientific arguments and proof of concept results
for daily free-form audio journals as an underappreciated psychiatry research
datatype, as well as novel stability theorems and pilot empirical success for a
proposed multi-area recurrent neural network architecture.Comment: PhD thesis cop
How can genomic data inform biological invasions?
Rates of biological invasions are increasing, with global trade and climate change causing significant damage to biodiversity, human well-being, primary industries, and economies around the world. However, our ability to predict and prevent future invasions is limited by significant gaps in our mechanistic understanding of the invasion process. Advances in next generation sequencing technologies and bioinformatics make it possible to investigate potential genomic factors that drive invasion success with much higher resolution and accuracy than prior research based on a small number of genetic loci. My thesis argues for the value of population genomic data in invasion biology, first examining the uptake of genomics in invasion research and then providing a case study for using genomic data to understand invasion patterns of pink bollworm (Pectinophora gossypiella).
The first analysis (Chapter 2) compares the extent to which population genetic data versus population genomic data, including reference genomes, have been used or are publicly available to study globally invasive species from the International Union for Conservation of Nature (IUCN) ā100 of the Worldās Worst Invasive Alien Speciesā (WAS) list. In this chapter, I demonstrate that āinvasion genomicsā is still in its infancy with respect to research uptake: while 82% of species on the WAS list have been studied using some form of population genetic data, just 32% have been studied using population genomic data. Further, 55% of the WAS list species lack a reference genome, however 18% of these were sequenced in the last three years, indicating a growing investment in genomic resources that looks promising for future invasion genomics research.
The second analysis (Chapter 3) showcases population genomic data being used as a tool to inform a biological invasion. Pink bollworm is one of the most destructive global pests of cotton, costing farmers millions of dollars each year in productivity losses and management efforts. A small population of pink bollworm is currently established in North West Australia, where it poses a significant threat to the expanding cotton industry there. In this chapter, I analysed genomic data in the form of single nucleotide polymorphisms (SNPs) ā obtained through a reduced representation, genotyping-by- sequencing technique (DArTseq) ā for global populations of pink bollworm to elucidate the population structure and connectivity patterns of the pest. My results show that pink bollworm populations in my dataset have low genetic diversity and strong differentiation between populations from different continents. Importantly, the high genetic differentiation between Australia and other continents reduces concerns about gene flow to North West Australia, particularly from populations in India and Pakistan that have evolved resistance to transgenic insecticidal cotton.
As species continue to move globally beyond their natural ranges, understanding how genome-driven processes facilitate invasion is critical. Genomic data can enhance our mechanistic understanding of the invasion process and inform proactive management of invasive species. Yet, despite progress in this space, there remain limitations to the breadth and depth of such studies that are highlighted throughout my thesis. These represent valuable research opportunities. With the cost of generating genomic data constantly decreasing and long-read sequencing bridging the gap for many taxon-specific challenges, genomic data is starting to address many previously intractable research questions and has the potential to improve overall biosecurity outcomes worldwide
Paths and cycles in graphs and hypergraphs
In this thesis we present new results in graph and hypergraph theory all of which feature paths or cycles.
A -uniform tight cycle is a -uniform hypergraph on vertices with a cyclic ordering of its vertices such that the edges are all -sets of consecutive vertices in the ordering.
We consider a generalisation of Lehel's Conjecture, which states that every 2-edge-coloured complete graph can be partitioned into two cycles of distinct colour, to -uniform hypergraphs and prove results in the 4- and 5-uniform case.
For a -uniform hypergraph~, the Ramsey number is the smallest integer such that any 2-edge-colouring of the complete -uniform hypergraph on vertices contains a monochromatic copy of . We determine the Ramsey number for 4-uniform tight cycles asymptotically in the case where the length of the cycle is divisible by 4, by showing that = (5+(1)).
We prove a resilience result for tight Hamiltonicity in random hypergraphs. More precisely, we show that for any >0 and 3 asymptotically almost surely, every subgraph of the binomial random -uniform hypergraph in which all -sets are contained in at least edges has a tight Hamilton cycle.
A random graph model on a host graph is said to be 1-independent if for every pair of vertex-disjoint subsets of , the state of edges (absent or present) in is independent of the state of edges in . We show that = 4 - 2 is the critical probability such that every 1-independent graph model on where each edge is present with probability at least contains an infinite path
SuperCDMS HVeV Run 2 Low-Mass Dark Matter Search, Highly Multiplexed Phonon-Mediated Particle Detector with Kinetic Inductance Detector, and the Blackbody Radiation in Cryogenic Experiments
There is ample evidence of dark matter (DM), a phenomenon responsible for ā 85% of the matter content of the Universe that cannot be explained by the Standard Model (SM). One of the most compelling hypotheses is that DM consists of beyond-SM particle(s) that are nonluminous and nonbaryonic. So far, numerous efforts have been made to search for particle DM, and yet none has yielded an unambiguous observation of DM particles.
We present in Chapter 2 the SuperCDMS HVeV Run 2 experiment, where we search for DM in the mass ranges of 0.5--10ā“ MeV/cĀ² for the electron-recoil DM and 1.2--50 eV/cĀ² for the dark photon and the Axion-like particle (ALP). SuperCDMS utilizes cryogenic crystals as detectors to search for DM interaction with the crystal atoms. The interaction is detected in the form of recoil energy mediated by phonons. In the HVeV project, we look for electron recoil, where we enhance the signal by the Neganov-Trofimov-Luke effect under high-voltage biases. The technique enabled us to detect quantized eā»hāŗ creation at a 3% ionization energy resolution. Our work is the first DM search analysis considering charge trapping and impact ionization effects for solid-state detectors. We report our results as upper limits for the assumed particle models as functions of DM mass. Our results exclude the DM-electron scattering cross section, the dark photon kinetic mixing parameter, and the ALP axioelectric coupling above 8.4 x 10ā»Ā³ā“ cmĀ², 3.3 x 10ā»Ā¹ā“, and 1.0 x 10ā»ā¹, respectively.
Currently every SuperCDMS detector is equipped with a few phonon sensors based on the transition-edge sensor (TES) technology. In order to improve phonon-mediated particle detectors' background rejection performance, we are developing highly multiplexed detectors utilizing kinetic inductance detectors (KIDs) as phonon sensors. This work is detailed in chapter 3 and chapter 4. We have improved our previous KID and readout line designs, which enabled us to produce our first Ćø3" detector with 80 phonon sensors. The detector yielded a frequency placement accuracy of 0.07%, indicating our capability of implementing hundreds of phonon sensors in a typical SuperCDMS-style detector. We detail our fabrication technique for simultaneously employing Al and Nb for the KID circuit. We explain our signal model that includes extracting the RF signal, calibrating the RF signal into pair-breaking energy, and then the pulse detection. We summarize our noise condition and develop models for different noise sources. We combine the signal and the noise models to be an energy resolution model for KID-based phonon-mediated detectors. From this model, we propose strategies to further improve future detectors' energy resolution and introduce our ongoing implementations.
Blackbody (BB) radiation is one of the plausible background sources responsible for the low-energy background currently preventing low-threshold DM experiments to search for lower DM mass ranges. In Chapter 5, we present our study for such background for cryogenic experiments. We have developed physical models and, based on the models, simulation tools for BB radiation propagation as photons or waves. We have also developed a theoretical model for BB photons' interaction with semiconductor impurities, which is one of the possible channels for generating the leakage current background in SuperCDMS-style detectors. We have planned for an experiment to calibrate our simulation and leakage current generation model. For the experiment, we have developed a specialized ``mesh TES'' photon detector inspired by cosmic microwave background experiments. We present its sensitivity model, the radiation source developed for the calibration, and the general plan of the experiment.</p
PLACING THE EVOLUTIONARY HISTORY OF \u3ci\u3eDESMOGNATHUS\u3c/i\u3e SALAMANDERS IN CONTEXT: A PHYLOGEOGRAPHIC APPROACH
Patterns of genetic variation do not arise in a vacuum but are instead shaped by the interplay between evolutionary forces and ecological constraints. Here, I use a phylogeographic approach to examine the role that ecology played in lineage divergence in the Desmognathus quadramaculatus species complex (Family: Plethodontidae), which consists of three nominal species: D. quadramaculatus, D. marmoratus, and D. folkertsi. Previous phylogenetic studies have shown that individuals from these species do not form clades based on phenotype. My approach to reconciling phylogenetic discordance was two-fold, using (1) genome-wide markers to provide insight into the relationships among lineages and (2) geographic and climate data to provide context for patterns of genetic diversity.
First, I obtained genome-wide nuclear markers using double-digest restriction-site associated DNA sequencing (ddRAD) to examine whether two morphologically divergent species, D. marmoratus and D. quadramaculatus, represent independently evolving lineages. Phylogenetic, population structure, and model testing analyses all confirmed that D. marmoratus and D. quadramaculatus do not group based on phenotype. Instead, I found that there were two cryptic genetic lineages (Nantahala and Pisgah) that each contained both phenotypes. Additionally, ecological niche modeling showed that the two genetic lineages primarily occupy geographic areas with significantly different climates, suggesting that climate may have played a role in divergence.
Next, I assembled loci from publicly available sequencing data using a draft transcriptome of Desmognathus fuscus as a reference to assess the three nominal species in the quadramaculatus species complex across their entire range. I used phylogenetic and population structure analyses, alongside haplowebs and conspecificity matrices, to determine if the loci supported the hypothesis that the phenotypes represent multiple independently evolving lineages within the broader genetic clades found in the previous chapter. I found that the loci were not informative enough to determine whether the phenotypes had a genetic basis in Pisgah, but did support genetic divergence between phenotypes in Nantahala.
Finally, I used ecological niche models (ENMs) and resistance modeling to place the genetic results and phenotypic diversity within the context of time and space. I found that though the quadramaculatus and marmoratus phenotypes were nearly indistinguishable in niche space in the present day, they were projected to occupy different geographic areas in the past and future. The southern portion of the study area had areas of high habitat suitability from the Last Glacial Maximum (~22 kya) to the present, which aligns with the higher genetic divergence between groups in Nantahala. Anthropogenic land use changes reduced habitat availability but likely did not drive genetic divergence in the past, and may be of more consequence to genetic diversity than climate change over the next 50 years.
Like many taxa that underwent adaptive radiations, the evolutionary history of Desmognathus has been obfuscated by high rates of within-species phenotypic diversity and shared morphology between distantly related lineages. My findings emphasize the importance of interrogating complex patterns of genetic variation within the context of the dynamic, heterogeneous landscapes in which they arise
Structured data abstractions and interpretable latent representations for single-cell multimodal genomics
Single-cell multimodal genomics involves simultaneous measurement of multiple types of molecular data, such as gene expression, epigenetic marks and protein abundance, in individual cells. This allows for a comprehensive and nuanced understanding of the molecular basis of cellular identity and function. The large volume of data generated by single-cell multimodal genomics experiments requires specialised methods and tools for handling, storing, and analysing it.
This work provides contributions on multiple levels. First, it introduces a single-cell multimodal data standard ā MuData ā designed to facilitate the handling, storage and exchange of multimodal data. MuData provides interfaces that enable transparent access to multimodal annotations as well as data from individual modalities. This data structure has formed the foundation for the multimodal integration framework, which enables complex and composable workflows that can be naturally integrated with existing omics-specific analysis approaches.
Joint analysis of multimodal data can be performed using integration methods. In order to enable integration of single-cell data, an improved multi-omics factor analysis model (MOFA+) has been designed and implemented building on the canonical dimensionality reduction approach for multi-omics integration. Inferring later factors that explain variation across multiple modalities of the data, MOFA+ enables the modelling of latent factors with cell group-specific patterns of activity. MOFA+ model has been implemented as part of the respective multi-omics integration framework, and its utility has been extended by software solutions that facilitate interactive model exploration and interpretation.
The newly improved model for multi-omics integration of single cells has been applied to the study of gene expression signatures upon targeted gene activation. In a dataset featuring targeted activation of candidate regulators of zygotic genome activation (ZGA) ā a crucial transcriptional event in early embryonic development, ā modelling expression of both coding and non-coding loci with MOFA+ allowed to rank genes by their potency to activate a ZGA-like transcriptional response. With identification of Patz1, Dppa2 and Smarca5 as potent inducers of ZGA-like transcription in mouse embryonic stem cells, these findings have contributed to the understanding of molecular mechanisms behind ZGA and laid the foundation for future research of ZGA in vivo.
In summary, this workās contributions include the development of data handling and integration methods as well as new biological insights that arose from applying these methods to studying gene expression regulation in early development. This highlights how single-cell multimodal genomics can aid to generate valuable insights into complex biological systems
On the structure of graphs with forbidden induced substructures
One of the central goals in extremal combinatorics is to understand how the global structure of a combinatorial object, e.g. a graph, hypergraph or set system, is affected by local constraints.
In this thesis we are concerned with structural properties of graphs and hypergraphs which locally do not look like some type of forbidden induced pattern. Patterns can be single subgraphs, families of subgraphs, or in the multicolour version colourings or families of colourings of subgraphs.
ErdÅs and Szekeres\u27s quantitative version of Ramsey\u27s theorem asserts that in every -edge-colouring of the complete graph on vertices there is a monochromatic clique on at least vertices. The famous ErdÅs-Hajnal conjecture asserts that forbidding fixed colourings on subgraphs ensures much larger monochromatic cliques. The conjecture is open in general, though a few partial results are known. The first part of this thesis will be concerned with different variants of this conjecture: A bipartite variant, a multicolour variant, and an order-size variant for hypergraphs.
In the second part of this thesis we focus more on order-size pairs; an order-size pair is the family consisting of all graphs of order and size , i.e. on vertices with edges. We consider order-size pairs in different settings: The graph setting, the bipartite setting and the hypergraph setting. In all these settings we investigate the existence of absolutely avoidable pairs, i.e. fixed pairs that are avoided by all order-size pairs with sufficiently large order, and also forcing densities of order-size pairs , i.e. for approaching infinity, the limit superior of the fraction of all possible sizes , such that the order-size pair does not avoid the pair
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