Matching Items (150)
Description
Predatory bacteria are a guild of heterotrophs that feed directly on other living bacteria. They belong to several bacterial lineages that evolved this mode of life independently and occur in many microbiomes and environments. Current knowledge of predatory bacteria is based on culture studies and simple detection in natural systems. The ecological consequences of their activity, unlike those of other populational loss factors like viral infection or grazing by protists, are yet to be assessed. During large-scale cultivation of biological soil crusts intended for arid soil rehabilitation, episodes of catastrophic failure were observed in cyanobacterial growth that could be ascribed to the action of an unknown predatory bacterium using bioassays. This predatory bacterium was also present in natural biocrust communities, where it formed clearings (plaques) up to 9 cm in diameter that were visible to the naked eye. Enrichment cultivation and purification by cell-sorting were used to obtain co-cultures of the predator with its cyanobacterial prey, as well as to identify and characterize it genomically, physiologically and ultrastructurally. A Bacteroidetes bacterium, unrelated to any known isolate at the family level, it is endobiotic, non-motile, obligately predatory, displays a complex life cycle and very unusual ultrastructure. Extracellular propagules are small (0.8-1.0 µm) Gram-negative cocci with internal two-membrane-bound compartmentalization. These gain entry to the prey likely using a suite of hydrolytic enzymes, localizing to the cyanobacterial cytoplasm, where growth begins into non-compartmentalized pseudofilaments that undergo secretion of vesicles and simultaneous multiple division to yield new propagules. I formally describe it as Candidatus Cyanoraptor togatus, hereafter Cyanoraptor. Its prey range is restricted to biocrust-forming, filamentous, non-heterocystous, gliding, bundle-making cyanobacteria. Molecular meta-analyses showed its worldwide distribution in biocrusts. Biogeochemical analyses of Cyanoraptor plaques revealed that it causes a complete loss of primary productivity, and significant decreases in other biocrusts properties such as water-retention and dust-trapping capacity. Extensive field surveys in the US Southwest revealed its ubiquity and its dispersal-limited, aggregated spatial distribution and incidence. Overall, its activity reduces biocrust productivity by 10% at the ecosystem scale. My research points to predatory bacteria as a significant, but overlooked, ecological force in shaping soil microbiomes.
ContributorsBethany Rakes, Julie Ann (Author) / Garcia-Pichel, Ferran (Thesis advisor) / Gile, Gillian (Committee member) / Cao, Huansheng (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2022
Description
A remarkable phenomenon in contemporary physics is quantum scarring in classically chaoticsystems, where the wave functions tend to concentrate on classical periodic orbits. Quantum
scarring has been studied for more than four decades, but the problem of efficiently detecting
quantum scars has remained to be challenging, relying mostly on human visualization of
wave function patterns. This paper develops a machine learning approach to detecting
quantum scars in an automated and highly efficient manner. In particular, this paper exploits Meta
learning. The first step is to construct a few-shot classification algorithm, under the
requirement that the one-shot classification accuracy be larger than 90%. Then propose a
scheme based on a combination of neural networks to improve the accuracy. This paper shows that
the machine learning scheme can find the correct quantum scars from thousands images of
wave functions, without any human intervention, regardless of the symmetry of the underlying
classical system. This will be the first application of Meta learning to quantum systems. Interacting spin networks are fundamental to quantum computing. Data-based tomography oftime-independent spin networks has been achieved, but an open challenge is to ascertain the
structures of time-dependent spin networks using time series measurements taken locally
from a small subset of the spins. Physically, the dynamical evolution of a spin network under
time-dependent driving or perturbation is described by the Heisenberg equation of motion.
Motivated by this basic fact, this paper articulates a physics-enhanced machine learning framework
whose core is Heisenberg neural networks. This paper demonstrates that, from local measurements, not only the local Hamiltonian can be recovered but the Hamiltonian reflecting the interacting structure of the whole system can
also be faithfully reconstructed. Using Heisenberg neural machine on spin networks of a
variety of structures. In the extreme case where measurements are taken from only one spin,
the achieved tomography fidelity values can reach about 90%. The developed machine
learning framework is applicable to any time-dependent systems whose quantum dynamical
evolution is governed by the Heisenberg equation of motion.
ContributorsHan, Chendi (Author) / Lai, Ying-Cheng (Thesis advisor) / Yu, Hongbin (Committee member) / Dasarathy, Gautam (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2022
Description
Few-layer black phosphorous (FLBP) is one of the most important two-dimensional (2D) materials due to its strongly layer-dependent quantized bandstructure, which leads to wavelength-tunable optical and electrical properties. This thesis focuses on the preparation of stable, high-quality FLBP, the characterization of its optical properties, and device applications.Part I presents an approach to preparing high-quality, stable FLBP samples by combining O2 plasma etching, boron nitride (BN) sandwiching, and subsequent rapid thermal annealing (RTA). Such a strategy has successfully produced FLBP samples with a record-long lifetime, with 80% of photoluminescence (PL) intensity remaining after 7 months. The improved material quality of FLBP allows the establishment of a more definitive relationship between the layer number and PL energies.
Part II presents the study of oxygen incorporation in FLBP. The natural oxidation formed in the air environment is dominated by the formation of interstitial oxygen and dangling oxygen. By the real-time PL and Raman spectroscopy, it is found that continuous laser excitation breaks the bonds of interstitial oxygen, and free oxygen atoms can diffuse around or form dangling oxygen under low heat. RTA at 450 °C can turn the interstitial oxygen into dangling oxygen more thoroughly. Such oxygen-containing samples show similar optical properties to the pristine BP samples. The bandgap of such FLBP samples increases with the concentration of the incorporated oxygen.
Part III deals with the investigation of emission natures of the prepared samples. The power- and temperature-dependent measurements demonstrate that PL emissions are dominated by excitons and trions, with a combined percentage larger than 80% at room temperature. Such measurements allow the determination of trion and exciton binding energies of 2-, 3-, and 4-layer BP, with values around 33, 23, 15 meV for trions and 297, 276, 179 meV for excitons at 77K, respectively.
Part IV presents the initial exploration of device applications of such FLBP samples. The coupling between photonic crystal cavity (PCC) modes and FLBP's emission is realized by integrating the prepared sandwich structure onto 2D PCC. Electroluminescence has also been achieved by integrating such materials onto interdigital electrodes driven by alternating electric fields.
ContributorsLi, Dongying (Author) / Ning, Cun-Zheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Lai, Ying-Cheng (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2022
Description
There is an estimated five trillion pieces of plastic in the global ocean, with 4.8 to 12.7 million metric tons entering the ocean annually. Much of the plastic in the ocean is in the form of microplastics, or plastic particles <5mm in size. Microplastics enter the marine environment as primary or secondary microplastics; primary microplastics are pre-manufactured micro-sized particles, such as microbeads used in cosmetics, while secondary microplastics form from the degradation of larger plastic objects, such water bottles. Once in the ocean, plastics are readily colonized by a consortium of prokaryotic and eukaryotic organisms, which form dense biofilms on the plastic; this biofilm is termed the “plastisphere”. Despite growing concerns about the ecological impact of microplastics and their respective plastispheres on the marine environment, there is little consensus about the factors that shape the plastisphere on environmentally relevant secondary microplastics. The goal of my dissertation is to comprehensively analyze the role of plastic polymer type, incubation time, and geographic location on shaping plastisphere communities attached to secondary microplastics. I investigated the plastisphere of six chemically distinct plastic polymer types obtained from common household consumer products that were incubated in the coastal Caribbean (Bocas del Toro, Panama) and coastal Pacific (San Diego, CA) oceans. Genotyping using 16S and 18S rRNA gene amplification and next-generation Illumina sequencing was employed to identify bacterial and eukaryotic communities on the polymer surfaces. Statistical analyses show that there were no polymer-specific assemblages for prokaryotes or eukaryotes, but rather a microbial core community that was shared among plastic types. I also found that rare hydrocarbon degrading bacteria may be specific to certain chemical properties of the microplastics. Statistical comparisons of the communities across both sites showed that prokaryotic plastispheres were shaped primarily by incubation time and geographic location. Finally, I assessed the impact of biofilms on microplastic degradation and deposition and conclude that biofilms enhance microplastic sinking of negatively buoyant particles and reduce microplastic degradation. The results of my dissertation increases understanding of the factors that shape the plastisphere and how these communities ultimately determine the fate of microplastics in the marine environment.
ContributorsDudek, Kassandra Lynn (Author) / Neuer, Susanne (Thesis advisor) / Polidoro, Beth (Committee member) / Garcia-Pichel, Ferran (Committee member) / Cao, Huansheng (Committee member) / Arizona State University (Publisher)
Created2021
Description
With the development and successful landing of the NASA Perseverance rover, there has been growing interest in identifying how evidence of ancient life may be preserved and recognized in the geologic record. Environments that enable fossilization of biological remains are termed, “taphonomic windows”, wherein signatures of past life may be detected. In this dissertation, I have sought to identify taphonomic windows in planetary-analog environments with an eye towards the exploration of Mars. In the first chapter, I describe how evidence of past microbial life may be preserved within serpentinizing systems. Owing to energetic rock-water reactions, these systems are known to host lithotrophic and organotrophic microbial communities. By investigating drill cores from the Samail Ophiolite in Oman, I report morphological and associated chemical biosignatures preserved in these systems as a result of subsurface carbonation. As serpentinites are known to occur on Mars and potentially other planetary bodies, these deposits potentially represent high-priority targets in the exploration for past microbial life. Next, I investigated samples from Atacama Desert, Chile, to understand how evidence of life may be preserved in ancient sediments formed originally in evaporative playa lakes. Here, I describe organic geochemical and morphological evidence of life preserved within sulfate-dominated evaporite rocks from the Jurassic-Cretaceous Tonel Formation and Oligocene San Pedro Formation. Because evaporative lakes are considered to have been potentially widespread on Mars, these deposits may represent additional key targets to search for evidence of past life. In the final chapter, I describe the fossilization potential of surficial carbonates by investigating Crystal Geyser, an active cold spring environment. Here, carbonate minerals precipitate rapidly in the presence of photosynthetic microbial mat communities. I describe how potential biosignatures are initially captured by mineralization, including cell-like structures and microdigitate stromatolites. However, these morphological signatures quickly degrade owing to diagenetic dissolution and recrystallization reactions, as well as textural coarsening that homogenizes the carbonate fabric. Overall, my dissertation underscores the complexity of microbial fossilization and highlights chemically-precipitating environments that may serve as high-priority targets for astrobiological exploration.
ContributorsZaloumis, Jonathan (Author) / Farmer, Jack D (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Trembath-Reichert, Elizabeth (Committee member) / Ruff, Steven W (Committee member) / Shock, Everett L (Committee member) / Arizona State University (Publisher)
Created2021
Description
Animals use diverse signal types (e.g. visual, auditory) to honestly advertise their genotypic and/or phenotypic quality to prospective mates or rivals. Behavioral displays and other dynamically updateable signals (e.g. songs, vibrations) can reliably reveal an individual’s quality in real-time, but it is unclear whether more fixed traits like feather coloration, which is often developed months before breeding, still reveal an individual’s quality at the time of signal use. To address this gap, we investigated if various indices of health and condition – including body condition (residual body mass), poxvirus infection, degree of habitat urbanization, and circulating levels of ketones, glucose, vitamins, and carotenoids – were related to the expression of male plumage coloration at the start of the spring breeding season in wild male house finches (Haemorhous mexicanus), a species in which many studies have demonstrated a link between plumage redness and the health and condition of individuals at the time the feathers are grown in late summer and autumn. We found that, at the time of pair formation, plumage hue was correlated with body condition, such that redder males were in better condition (i.e. higher residual mass). Also, as in previous studies, we found that rural males had redder plumage; however, urban males had more saturated plumage. In sum, these results reveal that feather coloration developed long before breeding still can be indicative to choosy mates of a male’s current condition and suggest that females who prefer to mate with redder males may also gain proximate material benefits (e.g. better incubation provisioning) by mating with these individuals in good current condition.
ContributorsDepinto, Kathryn (Author) / McGraw, Kevin (Thesis director) / Sweazea, Karen (Committee member) / Webb, Emily (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Psychology (Contributor)
Created2021-12
Description
Bioindicators of wildlife health are useful tools for studying the viability of various organisms and populations, and can include a range of phenotypic variables, such as behavior, body size, and physiological parameters, such as circulating hormones and nutrients. Few studies have investigated the utility of total plasma protein as a predictor of environmental or nutritional variation among birds, as well as variation across different seasons and life-history stages. Here I examined relationships between plasma protein and season, urbanization, sex, body condition, molt status, and disease state in house finches (Haemorhous mexicanus). I sampled blood from house finches across three seasons (winter, summer and fall 2021) and measured plasma protein levels using a Bradford assay. I also collected data including condition, sex, and poxvirus infection state at capture, as well as fecal samples to assess gut parasitism (coccidiosis). During the fall season I also estimated molt status, as number of actively growing feathers. I found circulating plasma protein concentration to be lower in the fall during molt than during winter or summer. I also found a significant relationship between circulating protein levels and capture site, as well as novel links to molt state and pox presence, with urban birds, those infected with pox, and those in more intense molt having higher protein levels. My results support the hypotheses that plasma protein concentration can be indicative of a bird’s body molt (which demands considerable protein for feather synthesis) and degree of habitat urbanization, although future work is needed to determine why protein levels were higher in virus-infected birds.
ContributorsDrake, Dean (Author) / McGraw, Kevin (Thesis director) / Sweazea, Karen (Committee member) / Jackson, Daniel (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.
ContributorsBou-Ghazale, Carine (Author) / Lai, Ying-Cheng (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2022-05
Description
Predicting nonlinear dynamical systems has been a long-standing challenge in science. This field is currently witnessing a revolution with the advent of machine learning methods. Concurrently, the analysis of dynamics in various nonlinear complex systems continues to be crucial. Guided by these directions, I conduct the following studies. Predicting critical transitions and transient states in nonlinear dynamics is a complex problem. I developed a solution called parameter-aware reservoir computing, which uses machine learning to track how system dynamics change with a driving parameter. I show that the transition point can be accurately predicted while trained in a sustained functioning regime before the transition. Notably, it can also predict if the system will enter a transient state, the distribution of transient lifetimes, and their average before a final collapse, which are crucial for management. I introduce a machine-learning-based digital twin for monitoring and predicting the evolution of externally driven nonlinear dynamical systems, where reservoir computing is exploited. Extensive tests on various models, encompassing optics, ecology, and climate, verify the approach’s effectiveness. The digital twins can extrapolate unknown system dynamics, continually forecast and monitor under non-stationary external driving, infer hidden variables, adapt to different driving waveforms, and extrapolate bifurcation behaviors across varying system sizes. Integrating engineered gene circuits into host cells poses a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback. I conducted systematic studies on hundreds of circuit structures exhibiting various functionalities, and identified a comprehensive categorization of growth-induced failures. I discerned three dynamical mechanisms behind these circuit failures. Moreover, my comprehensive computations reveal a scaling law between the circuit robustness and the intensity of growth feedback. A class of circuits with optimal robustness is also identified. Chimera states, a phenomenon of symmetry-breaking in oscillator networks, traditionally have transient lifetimes that grow exponentially with system size. However, my research on high-dimensional oscillators leads to the discovery of ’short-lived’ chimera states. Their lifetime increases logarithmically with system size and decreases logarithmically with random perturbations, indicating a unique fragility. To understand these states, I use a transverse stability analysis supported by simulations.
ContributorsKong, Lingwei (Author) / Lai, Ying-Cheng (Thesis advisor) / Tian, Xiaojun (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2023
Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise.
Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state
switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
ContributorsGoetz, Hanah Elizabeth (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2022