We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Intrinsically disordered proteins (IDP) are a class of proteins that lack a three-dimensional structure and their prevalence and diverse functions in the cell have only been discovered relatively recently. The intermediate chain (IC) subunit of the microtubule motor protein complex dynein contains an N-terminal disordered region, N-IC, which is central...
Designing spectral efficient, high-speed wireless links that offer high quality-
of-service and range capability has been a critical research and engineering challenge. In this thesis, we mainly address the complexity and performance issues of
channel estimation and data detection in multiple-input multiple-output (MIMO)
orthogonal frequency division multiplexing (OFDM) systems over...
Multiple-input multiple-output (MIMO) antenna technology is promising
for high-speed wireless communications without increasing the transmission band-
width. Space time coding (STC) is a scheme that employs multiple antennas to
increase transmission rate or to improve transmission quality. STC is used widely
in mobile cellular networks, wireless local area networks (WLAN)...
RNAs play important roles in the central dogma of molecular biology, and are involved in multiple biology processes such as chromatin modification, transcriptional interference and translation initiation. The functions of RNAs, especially non-coding RNAs, are highly related to its secondary structures, therefore computational methods for RNA structure prediction are of...
Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language.
In this dissertation, we will first introduce several deep models...
We present an experimental investigation of the effect of kinetic energy on the ion doping efficiency of superfluid helium droplets using cesium cations from a thermionic emission source. The kinetic energy of Cs⁺ is controlled by the bias voltage of a collection grid collinearly arranged with the droplet beam. Efficient...
The isotopic composition of water vapour provides integrated perspectives on the hydrological histories of air masses and has been widely used for tracing physical processes in hydrological and climatic studies. Over the last two decades, the infrared laser spectroscopy technique has been used to measure the isotopic composition of water...
We propose the Breathing Earth System Simulator (BESS), an upscaling approach to quantify global gross primary productivity and evapotranspiration using MODIS with a spatial resolution of 1-5 km and a temporal resolution of 8 days. This effort is novel because it is the first system that harmonizes and utilizes MODIS...
BACKGROUND: Chronic exposure to arsenic is associated with skin lesions. However, it is not known whether reducing arsenic exposure will improve skin lesions.
OBJECTIVE: We evaluated the association between reduced arsenic exposures and skin lesion recovery over time.
METHODS: A follow-up study of 550 individuals was conducted in 2009-2011 on...
Vitamin E (VitE) is necessary for vertebrate embryonic development. VitE prevents lipid peroxidation (LPO), which requires detoxification by cellular antioxidant systems subsequently involving reducing power derived from energy metabolism. Thus, VitE protects metabolic networks in the developing embryo and the integrated gene expression networks compensating for and impaired by LPO-induced...
In this dissertation, I present experimental observations of multiply charged atomic ions (MCAI) generated from interactions of atomic/molecular clusters with moderately intense nanosecond laser pulses. This process is also known as Coulomb explosion (CE) and it has been extensively studied in intense laser fields using ultrashort pulses. Several prevailing theories...
Chemistry of preparing dense film from solution deposition is explored with several cases in this thesis. Surface dense structure, conversion at melting point, and ion exchange in aqueous solution are the main topics covered here for the thin films of aluminum oxide phosphate and tin dioxide. Thin film density, optical...
Recent advances in computing, communication, and artificial intelligence (AI) technologies have made our world more interconnected and data-rich than ever with the proliferation of smart devices and sensors. As a result, we are increasingly dependent on electronic devices and sensors to automate away life’s mundane parts. For example, in business...
The need for less toxic quantum dots (QDs) has led to a significant number of investigations related to copper indium sulfide (CIS) QDs. Lower toxicity and broad band absorbance width makes CIS QDs appealing for light emitting diodes (LEDs), lasers, sensors, bio-imaging, solar cells, and computing. The optical and electronic...
DNA has a well-defined structural transition-the denaturation of its double-stranded form into two single strands-that strongly affects its thermal transport properties. We show that, according to a widely implemented model for DNA denaturation, one can engineer DNA 'heattronic' devices that have a rapidly increasing thermal conductance over a narrow temperature...
Melanoma is the deadliest form of skin cancer, arising from malignant transformation of pigment-producing melanocytes. The primary risk factor for melanoma and other skin cancers is DNA damage resulting from unprotected solar ultraviolet radiation (UVR). If incorrectly repaired, this damage can result in incorporation of mutations that cause aberrant cell...
Gender relations as well as the social situation of Manchu women have long been ignored in studies of the cultural evolution of the Manchu. By setting the discussion of Manchu women in the context of cultural adaptation, this study reintroduces gender and women's problems into the research on the Manchu...
The demand for the development of sustainable energy is an all time high as we burn through limited fossil fuel reserves and as environmental concerns rise every year. Renewable energy sources such as wind and solar power have limitations due to inconsistent power supply that cannot meet the regular needs...
This dissertation proposes the use of advanced time-varying approaches for modeling the dynamics of the multipath channel in wireless communication networks. These advanced time-varying approaches include linear Kalman innovation models in observable block companion form, and neural network-based models. The e˙ectiveness of these type of models is evaluated through three...
The variety of natural disasters provide different sets of characteristics and properties with unique challenges. One significant difference between hazard types is prewarning lead time, the amount of time individuals have from a potential warning to the disaster occurring. Rapid onset disasters may not provide an official warning about a...
Dynamic bipedal locomotion is among the most difficult and yet relevant problems in modern robotics. While a multitude of classical control methods for bipedal locomotion exist, they are often brittle or limited in capability. In recent years, work in applying reinforcement learning to robotics has lead to superior performance across...
Copper antimony sulfide (CAS) is a ternary material that is of research interest for thin film photovoltaic applications due to its high absorption coefficient and tunable bandgap. The material is also ideal for sustainable manufacturing due the constituent elements being earth-abundant and less toxic than solar cell absorbers like gallium...
This thesis studies cooperative techniques that rely on femtocell user diversity to improve the downlink communication quality of macrocell users. We analytically analyze and evaluate the achievable performance of these techniques in the downlink of Rayleigh fading channels. We provide an approximation of both the bit-error rate (BER) and the...
The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
In this dissertation, I describe the experimental investigation in electron diffraction of molecules in superfluid helium droplets. The project is part of an overall scheme called ‘single molecule serial electron diffraction imaging’ (SS-EDI), with the ultimate goal of building an apparatus to determine atomic structures from oriented macromolecules. In SS-EDI,...
Laser Powder Bed Fusion (LPBF) is a process commonly used to create additively manufactured metal parts. The flexibility and complexity allowed by the LPBF process provides opportunity for significant advancement in multiple industries as parts can be customized in shape and function for specific needs. These benefits can be compounded...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Back pain is the leading cause of disability worldwide, entailing a significant socioeconomic impact. A primary source of back pain can be attributed to intervertebral disc (IVD) degeneration allowing nerve ingrowth, facet joint arthritis, disc bulging, and osteophyte formations that press on nearby nerve roots or the spinal cord. While...
Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them.
Further, there have been concerns about the possibility of bias and discrimination in predictive applications.
In order to address these issues, we propose an...
Today nano scale materials are being used for wide range of applications. One promising topic in nano scale materials is using them for reinforcement of different polymeric materials to reach desirable stiffness properties. The stiffness of these materials is mostly found experimentally because the nanocomposite community lacks a decent analytical...
This dissertation addresses the problem of semantic labeling of image pixels. In the course of our work, we considered different types of semantic labels, including object classes (e.g., car, person), 3D depth values (in the range 0 to 80 meters), and affordance classes (e.g., walkable, sittable). Semantic pixel labeling is...
Herbs have been used for many centuries in diverse civilizations for the treatment of heart disease. Only a few natural supplements claim to have direct cardiovascular actions including hawthorn (Crataegus spp.) and berberine derived from the Berberidaceae family. Several different studies indicate important cardiovascular effects of hawthorn and berberine. For...
We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
Wheat (Triticum aestivum L.) is one of the most important crops in the world. It has been and continues to be one of the main sources of food for humans and animals. Although traditional wheat breeding has contributed greatly to the improvement of wheat both in productivity and biotic/abiotic stress...
Emerging data showing the presence of atmospheric microplastics (MPs) has recently raised awareness surrounding the potential of human nanoplastics (NPs) exposure. Due to factors such as weathering, UV exposure, and other biodegradation processes, plastic pollution in the environment breaks down over time into micro (<5 micrometers) and nanoscale (<1000nm) particles....
Cyanobacterial harmful algae blooms (cyanoHABs) are a growing concern worldwide due to damage of ecosystems and threats to human health. Previous research indicates that plant humics from aquatic and wetland vascular plants are effective inhibitors of cyanobacterial metabolism and growth and may be useful as control agents for mitigating cyanoHABs....
Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
The utility of high-throughput, computational screening has become an invaluable asset to the field of materials science. In the hierarchy of computational methods, the most accurate methods are often the most computationally expensive. However, as both the efficiency and fidelity of numerical techniques advance, high-quality screening of large materials datasets...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
The Va nationality, despite its small population compared
to other nationalities in China, has preserved most of its
traditions largely due to limits placed by historical
circumstances and geographical isolation. To non-Chinese
anthropologists, the Va people still remain unknown, as there
is little or no information about them in English...
Coniferous trees are a major North American crop that has been intensively managed for its commercial value, while also serving as critical habitat for abundant wildlife and as carbon sinks. Having diverse functions, North American temperate coniferous forests have become a research hotspot for numerous scientific studies aiming to integrate...
In this dissertation, I describe the experimental investigation of catching ions in superfluid helium droplets. The ultimate goal of our project is to build a coherent electron diffraction apparatus for atomic structure determination from oriented single macromolecules. This involves generating protein ions from electrospray ionization (ESI) and doping them in...
This thesis studies the problem of structured prediction (SP), where the agent needs to predict a structured output for a given structured input (e.g., Part-of-Speech tagging sequence for an input sentence). Many important applications including machine translation in natural language processing (NLP) and image interpretation in computer vision can be...
Intrinsically disordered proteins (IDPs), protein regions (IDRs), and protein complexes continue to emerge at the forefront of protein science. Proteins and protein regions lacking specific structure are found in all organisms, and often have vital roles in numerous biological processes. Breaking the well-known structure-function paradigm, the understanding of disorder-based functionality...
As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
In recent years, many studies have focused on the molecular and biochemical mechanisms regulating the development of wine grapes. The course of grape berry development is directed by genetic design and is mediated by phytohormones, which regulate grape berry growth and development by orchestrating a complex network of interacting genes,...