Browsing by Author "Wang, Yu"

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    Biochemical Characterization of a Dihydroneopterin Aldolase Used for Methanopterin Biosynthesis in Methanogens
    Wang, Yu; Xu, Huimin; Grochowski, Laura L.; White, Robert H. (American Society for Microbiology, 2014-06-30)
    The gene encoding 7,8-dihydroneopterin aldolase (DHNA) was recently identified in archaea through comparative genomics as being involved in methanopterin biosynthesis (V. Crecy-Lagard, G. Phillips, L. L. Grochowski, B. El Yacoubi, F. Jenney, M. W. Adams, A. G. Murzin, and R. H. White, ACS Chem. Biol. 7:1807-1816, 2012, doi:10.1021/cb300342u). Archaeal DHNA shows a unique secondary and quaternary structure compared with bacterial and plant DHNAs. Here, we report a detailed biochemical examination of DHNA from the methanogen Methanocaldococcus jannaschii. Kinetic studies show that M. jannaschii DHNA possesses a catalytic capability with a k(cat)/K-m above 10(5) M-1 s(-1) at 70 degrees C, and at room temperature it exhibits a turnover number (0.07 s(-1)) comparable to bacterial DHNAs. We also found that this enzyme follows an acid-base catalytic mechanism similar to the bacterial DHNAs, except when using alternative catalytic residues. We propose that in the absence of lysine, which is considered to be the general base in bacterial DHNAs, an invariant water molecule likely functions as the catalytic base, and the strictly conserved His35 and Gln61 residues serve as the hydrogen bond partners to adjust the basicity of the water molecule. Indeed, substitution of either His35 or Gln61 causes a 20-fold decrease in k(cat). An invariant Tyr78 is also shown to be important for catalysis, likely functioning as a general acid. Glu25 plays an important role in substrate binding, since replacing Glu25 by Gln caused a >= 25-fold increase in K-m. These results provide important insights into the catalytic mechanism of archaeal DHNAs.
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    CS5604 Information Storage and Retrieval Fall 2017 Solr Report
    Kumar, Abhinav; Bangad, Anand; Robertson, Jeff; Garg, Mohit; Ramesh, Shreyas; Mi, Siyu; Wang, Xinyue; Wang, Yu (Virginia Tech, 2018-01-15)
    The Digital Library Research Laboratory (DLRL) has collected over 1.5 billion tweets and millions of webpages for the Integrated Digital Event Archiving and Library (IDEAL) and Global Event Trend Archive Research (GETAR) projects. We are using a 21 node Cloudera Hadoop cluster to store and retrieve this information. One goal of this project is to expand the data collection to include more web archives and geospatial data beyond what previously had been collected. Another important part in this project is optimizing the current system to analyze and allow access to the new data. To accomplish these goals, this project is separated into 6 parts with corresponding teams: Classification (CLA), Collection Management Tweets (CMT), Collection Management Webpages (CMW), Clustering and Topic Analysis (CTA), Front-end (FE), and SOLR. The report describes the work completed by the SOLR team which improves the current searching and storage system. We include the general architecture and an overview of the current system. We present the part that Solr plays within the whole system with more detail. We talk about our goals, procedures, and conclusions on the improvements we made to the current Solr system. This report also describes how we coordinate with other teams to accomplish the project at a higher level. Additionally, we provide manuals for future readers who might need to replicate our experiments. The main components within the Cloudera Hadoop cluster that the SOLR team interacts with include: Solr searching engine, HBase database, Lily indexer, Hive database, HDFS file system, Solr recommendation plugin, and Mahout. Our work focuses on HBase design, data quality control, search recommendations, and result ranking. Overall, throughout the semester, we have processed 12,564 web pages and 5.9 million tweets. In order to cooperate with Geo Blacklight, we make major changes on the Solr schema. We also function as a data quality control gateway for the Front End team and deliver the finalized data for them. As to search recommendation, we provide search recommendation such as the MoreLikeThis plugin within Solr for recommending related records from search results, and a custom recommendation system based on user behavior to provide user based search recommendations. After the fine tuning over the final weeks of semester, we successfully allowed effective connection of results from data provided by other teams, and delivered them to the front end through a Solr core.
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    A Deep Learning Based Pipeline for Image Grading of Diabetic Retinopathy
    Wang, Yu (Virginia Tech, 2018-06-21)
    Diabetic Retinopathy (DR) is one of the principal sources of blindness due to diabetes mellitus. It can be identified by lesions of the retina, namely microaneurysms, hemorrhages, and exudates. DR can be effectively prevented or delayed if discovered early enough and well-managed. Prior studies on diabetic retinopathy typically extract features manually but are time-consuming and not accurate. In this research, we propose a research framework using advanced retina image processing, deep learning, and a boosting algorithm for high-performance DR grading. First, we preprocess the retina image datasets to highlight signs of DR, then follow by a convolutional neural network to extract features of retina images, and finally apply a boosting tree algorithm to make a prediction based on extracted features. Experimental results show that our pipeline has excellent performance when grading diabetic retinopathy images, as evidenced by scores for both the Kaggle dataset and the IDRiD dataset.
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    Hippocampal Subregions Express Distinct Dendritic Transcriptomes that Reveal Differences in Mitochondrial Function in CA2
    Farris, Shannon; Ward, James M.; Carstens, Kelly E.; Samadi, Mahsa; Wang, Yu; Dudek, Serena M. (CellPress, 2019-10-08)
    RNA localization is one mechanism neurons use to spatially and temporally regulate gene expression at synapses. Here, we test the hypothesis that cells exhibiting distinct forms of synaptic plasticity will have differences in dendritically localized RNAs. Indeed, we discover that each major subregion of the adult mouse hippocampus expresses a unique complement of dendritic RNAs. Specifically, we describe more than 1,000 differentially expressed dendritic RNAs, suggesting that RNA localization and local translation are regulated in a cell typespecific manner. Furthermore, by focusing Gene Ontology analyses on the plasticity-resistant CA2, we identify an enrichment of mitochondria-associated pathways in CA2 cell bodies and dendrites, and we provide functional evidence that these pathways differentially influence plasticity and mitochondrial respiration in CA2. These data indicate that differences in dendritic transcriptomes may regulate cell type-specific properties important for learning and memory and may influence region-specific differences in disease pathology.
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    Identification of the Final Two Genes Functioning in Methanofuran Biosynthesis in Methanocaldococcus jannaschii
    Wang, Yu; Xu, Huimin; Jones, Michael K.; White, Robert H. (American Society for Microbiology, 2015-06-22)
    All methanofuran structural variants contain a basic core structure of 4-[N-(gamma -L-glutamyl)-p-(beta-aminoethyl) phenoxymethyl]( aminomethyl) furan (APMF-Glu) but have different side chains depending on the source organism. Recently, we identified four genes (MfnA, MfnB, MfnC, and MfnD) that are responsible for the biosynthesis of the methanofuran precursor gamma-glutamyltyramine and 5-(aminomethyl)-3-furanmethanol-phosphate (F1-P) from tyrosine, glutamate, glyceraldehyde-3-P, and alanine in Methanocaldococcus jannaschii. How gamma-glutamyltyramine and F1-P couple together to form the core structure of methanofuran was previously unknown. Here, we report the identification of two enzymes encoded by the genes mj0458 and mj0840 that catalyze the formation of F1-PP from ATP and F1-P and the condensation of F1-PP with gamma-glutamyltyramine, respectively, to form APMF-Glu. We have annotated these enzymes as MfnE and MfnF, respectively, representing the fifth and sixth enzymes in the methanofuran biosynthetic pathway to be identified. Although MfnE was previously reported as an archaeal adenylate kinase, our present results show that MfnE is a promiscuous enzyme and that its possible physiological role is to produce F1-PP. Unlike other enzymes catalyzing coupling reactions involving pyrophosphate as the leaving group, MfnF exhibits a distinctive alpha/beta two-layer sandwich structure. By comparing MfnF with thiamine synthase and dihydropteroate synthase, a substitution nucleophilic unimolecular (S-N-1) reaction mechanism is proposed for MfnF. With the identification of MfnE and MfnF, the biosynthetic pathway for the methanofuran core structure APMF-Glu is complete. IMPORTANCE This work describes the identification of the final two enzymes responsible for catalyzing the biosynthesis of the core structure of methanofuran. The gene products of mj0458 and mj0840 catalyze the formation of F1-PP and the coupling of F1-PP with gamma-glutamyltyramine, respectively, to form APMF-Glu. Although the chemistry of such a coupling reaction is widespread in biochemistry, we provide here the first evidence that such a mechanism is used in methanofuran biosynthesis. MfnF belongs to the hydantoinase A family (PF01968) and exhibits a unique alpha/beta two-layer sandwich structure that is different from the enzymes catalyzing similar reactions. Our results show that MfnF catalyzes the formation of an ether bond during methanofuran biosynthesis. Therefore, this work further expands the functionality of this enzyme family.
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    The influence of the Environmental Quality Incentives Program on local water quality
    Liu, Pengfei; Wang, Yu; Zhang, Wei (AAEA/Wiley, 2022-04-27)
    The Environmental Quality Incentives Program (EQIP) is the primary conservation program on working agricultural land. The United States Department of Agriculture obligated over $15 billion through EQIP cost-sharing contracts during the fiscal years 2009–2019. The voluntary nature of the program and the lack of performance assessment have led to speculations regarding the effectiveness of the program in delivering environmental benefits, in particular for improving water quality. This study provides quantitative estimates of the influence of EQIP payments on local water quality at a national scale. We link monitoring station level water quality readings with EQIP contract data and exploit the direction of river flow for identification. The estimated effects of EQIP vary across water quality measures. Estimates indicate that EQIP payments have significantly reduced biochemical oxygen demand and nitrogen, indicating improvements in water quality, but increased total suspended solids, fecal coliform, and phosphorus, suggesting that the implementation of certain conservation practices might have increased soil erosion and pathogen transfer, especially in watersheds with more agricultural production.
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    Information Freshness Optimization in Real-time Network Applications
    Liu, Zhongdong (Virginia Tech, 2024-06-12)
    In recent years, the remarkable development in ubiquitous communication networks and smart portable devices spawned a wide variety of real-time applications that require timely information updates (e.g., autonomous vehicular systems, industrial automation systems, and live streaming services). These real-time applications all have one thing in common: they desire their knowledge of the information source to be as fresh as possible. In order to measure the freshness of information, a new metric, called the Age-of-Information (AoI) is proposed. AoI is defined as the time elapsed since the generation time of the freshest delivered update. This metric is influenced by both the inter-arrival time and the delay of the updates. As a result of these dependencies, the AoI metric exhibits distinct characteristics compared to traditional delay and throughput metrics. In this dissertation, our goal is to optimize AoI under various real-time network applications. Firstly, we investigate a fundamental problem of how exactly various scheduling policies impact AoI performance. Though there is a large body of work studying the AoI performance under different scheduling policies, the use of the update-size information and its combinations with other information (such as arrival-time information and service preemption) to reduce AoI has still not been explored yet. Secondly, as a recently introduced measure of freshness, the relationship between AoI and other performance metrics remains largely ambiguous. We analyze the tradeoffs between AoI and additional performance metrics, including service performance and update cost, within real-world applications. This dissertation is organized into three parts. In the first part, we realize that scheduling policies leveraging the update-size information can substantially reduce the delay, one of the key components of AoI. However, it remains largely unknown how exactly scheduling policies (especially those making use of update-size information) impact the AoI performance. To this end, we conduct a systematic and comparative study to investigate the impact of scheduling policies on the AoI performance in single-server queues and provide useful guidelines for the design of AoI-efficient scheduling policies. In the second part, we analyze the tradeoffs between AoI and other performance metrics in real-world systems. Specifically, we focus on the following two important tradeoffs. (i) The tradeoff between service performance and AoI that arises in the data-driven real-time applications (e.g., Google Maps and stock trading applications). In these applications, the computing resource is often shared for processing both updates from information sources and queries from end users. Hence there is a natural tradeoff between service performance (e.g., response time to queries) and AoI (i.e., the freshness of data in response to user queries). To address this tradeoff, we begin by introducing a simple single-server two-queue model that captures the coupled scheduling between updates and queries. Subsequently, we design threshold-based scheduling policies to prioritize either updates or queries. Finally, we conduct a rigorous analysis of the performance of these threshold-based scheduling policies. (ii) The tradeoff between update cost and AoI that appear in the crowdsensing-based applications (e.g., Google Waze and GasBuddy). On the one hand, users are not satisfied if the responses to their requests are stale; on the other side, there is a cost for the applications to update their information regarding certain points of interest since they typically need to make monetary payments to incentivize users. To capture this tradeoff, we first formulate an optimization problem with the objective of minimizing the sum of the staleness cost (which is a function of the AoI) and the update cost, then we obtain a closed-form optimal threshold-based policy by reformulating the problem as a Markov decision process (MDP). In the third part, we study the minimization of data freshness and transmission costs (e.g., energy cost) under an (arbitrary) time-varying wireless channel without and with machine learning (ML) advice. We consider a discrete-time system where a resource-constrained source transmits time-sensitive data to a destination over a time-varying wireless channel. Each transmission incurs a fixed cost, while not transmitting results in a staleness cost measured by the AoI. The source needs to balance the tradeoff between these transmission and staleness costs. To tackle this challenge, we develop a robust online algorithm aimed at minimizing the sum of transmission and staleness costs, ensuring a worst-case performance guarantee. While online algorithms are robust, they tend to be overly conservative and may perform poorly on average in typical scenarios. In contrast, ML algorithms, which leverage historical data and prediction models, generally perform well on average but lack worst-case performance guarantees. To harness the advantages of both approaches, we design a learning-augmented online algorithm that achieves two key properties: (i) consistency: closely approximating the optimal offline algorithm when the ML prediction is accurate and trusted; (ii) robustness: providing a worst-case performance guarantee even when ML predictions are inaccurate.
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    An Investigation of the Structural and Magnetic Transitions in Ni-Fe-Ga Ferromagnetic Shape Memory Alloys
    Heil, Todd M. (Virginia Tech, 2005-12-12)
    The martensite and magnetic transformations in Ni-Fe-Ga ferromagnetic shape memory alloys are very sensitive to both alloy chemistry and thermal history. A series of Ni-Fe-Ga alloys near the prototype Heusler composition (X2YZ) were fabricated and homogenized at 1423 °K, and a Ni₅₃Fe₁₉Ga₂₈ alloy was subsequently annealed at various temperatures below and above the B2/L21 ordering temperature. Calorimetry and magnetometry were employed to measure the martensite transformation temperatures and Curie temperatures. Compositional variations of only a few atomic percent result in martensite start temperatures and Curie temperatures that differ by about 230 °K degrees and 35 °K degrees, respectively. Various one-hour anneals of the Ni₅₃Fe₁₉Ga₂₈ alloy shift the martensite start temperature and the Curie temperature by almost 70 °K degrees. Transmission electron microscopy investigations were conducted on the annealed Ni₅₃Fe₁₉Ga₂₈ alloy. The considerable variations in the martensite and magnetic transformations in these alloys are discussed in terms of microstructural differences resulting from alloy chemistry and heat treatments. The phase-field method has been successfully employed during the past ten years to simulate a wide variety of microstructural evolution in materials. Phase-field computational models describe the microstructure of a material by using a set of field variables whose evolution is governed by thermodynamic functionals and kinetic continuum equations. A two dimensional phase-field model that demonstrates the ferromagnetic shape memory effect in Ni2MnGa is presented. Free energy functionals are based on the phase-field microelasticity and micromagnetic theories; they account for energy contributions from martensite variant boundaries, elastic strain, applied stress, magnetocrystalline anisotropy, magnetic domain walls, magnetostatic potential, and applied magnetic fields. The time-dependent Ginzburg-Landau and Landau-Lifshitz kinetic continuum equations are employed to track the microstructural and magnetic responses in ferromagnetic shape memory alloys to applied stress and magnetic fields. The model results show expected microstructural responses to these applied fields and could be potentially utilized to generate quantitative predictions of the ferromagnetic shape memory effect in these alloys.
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    Magnetic and Elastic Interactions at Cracks and Interfaces in Ferromagnetic Materials
    Harutyunyan, Satenik (Virginia Tech, 2008-09-11)
    In addition to being useful for some nondestructive evaluation techniques, interactions between magnetic fields and defects in solids may also alter material properties. To explore this possibility, Maxwell's equations were coupled with a continuum mechanics model for elastic strain to formulate analytical expressions for the interaction of a magnetic field with several crack geometries. The influence of crack velocity and a realistic (nonlinear) magnetic susceptibility were included into a model of this type for the first time and shown to introduce unexpected trends in the magneto-elastic stress intensity. Singularities magneto-elastic stresses appear at different combinations of magnetic field strength and crack velocity, and the stresses at the crack tip switch sign. In a related study, the interaction of an alternating magnetic field with elastic stress through was explored through a coupling effect known as magneto-acoustic resonance. A model for the phenomena, in which magnetic waves excite elastic waves and vice versa, was formulated and used to explore the spin (magnon) and anti-plane elastic (phonon) interactions in piecewise homogeneous ferromagnetic spaces with two different sets of properties. The model suggests some combinations of magnetic field and frequency can produce a new kind of wave to appear. These new waves, which we call Accompanying Surface Magnetoelastic (ASM) waves, are localized at the interface between the two ferromagnetic media and they accompany reflection and transmission waves. It is shown that the amplitudes of the reflected, transmitted, and ASM waves depend strongly on magnetic field strength, frequency, and the angle of the incident wave, as well as on the physical properties of ferromagnetic media.
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    Magneto-Elastic Interactions in a Cracked Ferromagnetic Body
    Harutyunyan, Satenik (Virginia Tech, 2006-11-30)
    The stress-strain state of ferromagnetic plane with a moving crack has been investigated in this study. The model considers a soft magnetic ferroelastic body and incorporates a realistic (nonlinear) susceptibility. A moving crack is present in the body and is propagating in a direction perpendicular to the magnetic field. Assuming that the processes in the moving coordinates are stationary, a Fourier transform method is used to reduce the mixed boundary value problem to the solutions of a pair of dual integral equations yielding to a closed form solution. As a result of this investigation, the magnetoelastic stress intensity factor is obtained and its dependency upon the crack velocity, material constants and nonlinear law of magnetization are highlighted. It has been shown that stress result around the crack essentially depend on external magnetic field, speed of the moving crack, nonlinear law of magnetization, and other physical parameters. The results presented in this work show that when cracked ferromagnetic structure is under the influence of magnetic field it is necessary to take into account the interaction effects between deformation of the body and magnetic field and that such interaction can bring to a new conditions for strengthening the materials. Closed form solutions for the stress-strain state are obtained, graphical representations are supplied and conclusions and prospects for further developments are outlined.
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    Magnetoelectric Device and the Measurement Unit
    Xing, Zengping (Virginia Tech, 2009-04-10)
    Magnetic sensors are widely used in the field of mineral, navigational, automotive, medical, industrial, military, and consumer electronics. Many magnetic sensors have been developed that are generated by specific laws or phenomena: such as search-coil, fluxgate, Hall Effect, anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), magnetoelectric (ME), magnetodiode, magnetotransictor, fiber-optic, optical pump, superconducting quantum interference device (SQUID), etc. Each of these magnetic field sensors has their merits and application areas. For low power consumption (<10uW), quasi-static frequency (<10Hz) and high sensitivity (ME is the most important parameter. To enhance resonant gain in αME, I have developed a three phase laminate concept, which is based on increasing the effective mechanical factor Q while reducing the resonant frequency. A ME voltage coefficient of αME ~40V/cm.Oe has been achieved at resonance, which is about 2x higher than that of a conventional bending mode. Investigations of detection circuit optimization were also performed. Component selection strategies and a new charge topology were considered. Proper component values were required to optimize the charge detection scheme. It was also found, under some specific conditions to satisfy the circuit stability, that if the lowest required measurement frequency of the charge source was f1, then that it was not necessary to make the high corner frequency fp of the charge amplifier lower than f₁: as doing so would decrease the system's signal-to-noise ratio (SNR). A high pass, high order filter placed behind the charge amplifier was found to increase the charge sensitivity, as it narrows the intrinsic noise bandwidth and decreases the output noise contribution, while only slightly affecting the signal's output amplitude. Prototype ME unit were also constructed, and their noise level simulated by Pspice. Experimental results showed that prototypes ME unit can reach their detection limit. In addition, a new magneto-electric coupling mechanism was also found, which had a giant ME effect.
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    Magnetoelectric laminated composites and devices
    Zhai, Junyi (Virginia Tech, 2009-02-10)
    Since the turn of the millennium, giant magnetoelectric (ME) effects have been found in laminated composites of piezoelectric and magnetostrictive layers. Compared to ME single phase and two phase particulate composites, laminated composites have much higher ME coefficients and are also readily fabricated. In this thesis, I have investigated ME effect in laminated composites including materials, structures, fundamental properties and devices. Giant permeability Metglas was incorporated in ME laminates. The piezomagnetic coefficient of the Metglas is larger than that of widely used magnetostrictive materials, such as Terfenol-D or nickel ferrite. The experimental results show that Metglas based ME laminates have giant ME voltage coefficients and small required DC magnetic biases. Besides, the laminates have a good directional dependence of the magnetic field: it can only sense the magnetic field along its longitudinal direction. Symmetric bimorph and differential mode magnetoelectric laminates have been designed to reject (decrease) thermal and vibration noise sources, respectively. The mechanism for the noise cancellation capability is that the laminate operates in a bending (or longitudinal) mode, whereas the noise is contained in the other mode. The ME susceptibility (αme) is the fundamental property that describes the coupling between the polarization and magnetization of a ME media. It is a complex quantity ( ). I discuss the relationship of the ME susceptibility between the magnetic permeability, dielectric permittivity of the materials, and the widely used ME voltage coefficient. The shape of the magnetic layer has a large impact on the giant permeability due to shape demagnetization effects. A long, thin and narrow shape increases the ME voltage coefficient and decreases the required optimum DC bias. The resonance frequency of Terfenol-D/PZT laminates can be continuously tuned by magnetic field over a wide range. This large tunability is due to the large magnetostriction of Terfenol-D. It results in a dramatic increase in the bandwidth over which devices might take advantage of the resonance enhanced ME coefficient. Four device applications have also been studied based on the giant ME effect of laminate composites. (i) ME laminates offer much potential for low-frequency (10⁻² to 10³ Hz) detection of minute magnetic fields (10-12Tesla or below) in a passive mode of operation. With a wrapped active coil, the Metglas/PZT laminates are also capable of detecting changes of 0.8 nano-Tesla in DC magnetic fields without an applied DC bias. (ii) A geomagnetic field sensor is shown to have high sensitivity to variations in Earth's field of HDC=0.8nano-Tesla. It could offer potential applications in global positioning. (iii) Under electro-mechanical resonance drive conditions, ME laminates have been shown to have a high gyration effect. These findings indicate the potential existence of a fifth fundamental network element. (iv) A multimodal system has been developed for simultaneously harvesting mechanical vibration and magnetic energies.
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    A modest 0.5-m rise in sea level will double the tsunami hazard in Macau
    Li, Linlin; Switzer, Adam D.; Wang, Yu; Chan, Chung-Han; Qiu, Qiang; Weiss, Robert (AAAS, 2018-08-15)
    Rising sea levels will have overwhelmingly negative impacts on coastal communities globally. With previous research focused on how sea-level rise (SLR) affects storm-induced flooding, we show that SLR will also increase both the frequency and the intensity of tsunami-induced flooding, another significant coastal hazard associated with sea-level extremes. We developed probabilistic tsunami inundation maps for Macau, a densely populated coastal city located in the South China Sea, under current sea-level, 0.5-m SLR, and 1-m SLR conditions, using an extensive Monte Carlo tsunami inundation simulation. Our results indicate that conservative amounts of SLR of 0.5 m (by 2060) and 1 m (by 2100) would dramatically increase the frequency of tsunami-induced flooding incidences by a factor of 1.2 to 2.4 and 1.5 to 4.7, respectively.
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    Nanogrowth twins and abnormal magnetic behavior in CoFe2O4 epitaxial thin films
    Yan, Li; Wang, Yu; Li, Jiefang; Pyatakov, Alexander P.; Viehland, Dwight D. (American Institute of Physics, 2008-12-15)
    Nanogrowth twins (GTs) have been observed in CoFe2O4 (CFO) epitaxial thin films deposited on (111) oriented SrTiO3 substrates by pulsed laser deposition. The GTs form during nucleation and growth and consist of CFO growth regions that have a mirror relationship with respect to each other. We show that the films with GTs (i) are better crystallized than the ones without them and (ii) have higher saturation magnetizations due to the presence of twin boundaries.
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    Online Learning for Resource Allocation in Wireless Networks: Fairness, Communication Efficiency, and Data Privacy
    Li, Fengjiao (Virginia Tech, 2022-12-13)
    As the Next-Generation (NextG, 5G and beyond) wireless network supports a wider range of services, optimization of resource allocation plays a crucial role in ensuring efficient use of the (limited) available network resources. Note that resource allocation may require knowledge of network parameters (e.g., channel state information and available power level) for package schedule. However, wireless networks operate in an uncertain environment where, in many practical scenarios, these parameters are unknown before decisions are made. In the absence of network parameters, a network controller, who performs resource allocation, may have to make decisions (aimed at optimizing network performance and satisfying users' QoS requirements) while emph{learning}. To that end, this dissertation studies two novel online learning problems that are motivated by autonomous resource management in NextG. Key contributions of the dissertation are two-fold. First, we study reward maximization under uncertainty with fairness constraints, which is motivated by wireless scheduling with Quality of Service constraints (e.g., minimum delivery ratio requirement) under uncertainty. We formulate a framework of combinatorial bandits with fairness constraints and develop a fair learning algorithm that successfully addresses the tradeoff between reward maximization and fairness constraints. This framework can also be applied to several other real-world applications, such as online advertising and crowdsourcing. Second, we consider global reward maximization under uncertainty with distributed biased feedback, which is motivated by the problem of cellular network configuration for optimizing network-level performance (e.g., average user-perceived Quality of Experience). We study both the linear-parameterized and non-parametric global reward functions, which are modeled as distributed linear bandits and kernelized bandits, respectively. For each model, we propose a learning algorithmic framework that can be integrated with different differential privacy models. We show that the proposed algorithms can achieve a near-optimal regret in a communication-efficient manner while protecting users' data privacy ``for free''. Our findings reveal that our developed algorithms outperform the state-of-the-art solutions in terms of the tradeoff among the regret, communication efficiency, and computation complexity. In addition, our proposed models and online learning algorithms can also be applied to several other real-world applications, e.g., dynamic pricing and public policy making, which may be of independent interest to a broader research community.
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    Optimized Method for Robust Transcriptome Profiling of Minute Tissues Using Laser Capture Microdissection and Low-Input RNA-Seq
    Farris, Shannon; Wang, Yu; Ward, James M.; Dudek, Serena M. (Frontiers, 2017-06-17)
    Obtaining high quality RNA from complex biological tissues, such as the brain, is needed for establishing high-fidelity cell-type specific transcriptomes. Although combining genetic labeling techniques with laser capture microdissection (LCM) is generally sufficient, concerns over RNA degradation and limited yields call into question results of many sequencing studies. Here we set out to address both of these issues by: (1) developing a fluorescence-assisted LCM protocol that yields high quality RNA from fresh-frozen tissues; and (2) determining a suitable RNA-Seq library generation method for limited amounts of RNA (1–5 ng total RNA). The latter focused on comparing commercially available kits able to produce libraries of sufficient concentration and complexity while limiting PCR amplification biases. We find that high quality RNA (RNA integrity number, RIN, >9) of sufficient concentration can be isolated from lasercaptured material from thinly-sectioned tissues when digestion time and temperature are minimized. Furthermore, we found that library generation approaches that retain ribosomal RNA (rRNA) through cDNA library generation required fewer cycles of PCR, minimizing bias in the resulting libraries. Lastly, end stage depletion of rRNA prior to sequencing enriches for target RNAs, thereby increasing read depth and level of gene detection while decreasing sequencing costs. Here we describe our protocol for generating robust RNA-Seq libraries from laser-captured tissue and demonstrate that with this method, we obtain samples with RNA quality superior to the current standard in the LCM field, and show that low-input RNA-Seq kits that minimize PCR bias produce high fidelity sequencing metrics with less variability compared to current practices.
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    Phase transformations in highly electrostrictive and magnetostrictive crystals: structural heterogeneity and history dependent phase stability
    Cao, Hu (Virginia Tech, 2008-05-08)
    Ferroelectric and ferromagnetic materials have been extensively studied for potential applications in sensors, actuators and transducers. Highly electrostrictive (1-x)Pb(Mg1/3Nb2/3)-xPbTiO₃ (PMN-xPT) and highly magnetostrictive Fe-xat.%Ga are two such novel materials. Both materials systems have chemical disorders and structural inhomogeneity on a microscale, giving rise to an interesting diversity of crystal structures and novel macroscopic physical properties, which are dependent on thermal and electrical histories of the crystals. In this thesis, I have to investigated phase transformations in these two systems under thermal and field (electric/magnetic) histories, using x-ray and neutron scattering techniques. In PMN-xPT crystals, x-ray and neutron diffractions were performed along the different crystallographic orientations and for different thermal and electrical histories. Various intermediate monoclinic (M) phases that structurally “bridge” the rhombohedral (R) and tetragonal (T) ones across a morphtropic phase boundary (MPB) have been observed. Systematic investigations of (001) and (110) electric (E) field-temperature phase diagrams of PMN-xPT crystals have demonstrated that the phase stability of PMN-xPT crystals is quite fragile: depending not only on modest changes in E (≤ 0.5kV/cm), but also on the direction along which E is applied. Structurally bridging monoclinic Mc or orthorhombic (O) phases were found to be associated with the T phase, whereas the monoclinic Ma or Mb phases bridged the Cubic (C) and R ones. In addition, neutron inelastic scattering was performed on PMN-0.32PT to study the dynamic origin of the MPB. Data were obtained between 100 and 600 K under various E applied along the cubic [001] direction. The lowest frequency zone-center, transverse optic phonon was strongly damped and softened over a wide temperature range, but started to recover on cooling into the T phase at the Curie temperature (TC). Comparisons of my findings with prior ones for PMN and PMN-0.60PT suggest that the temperature dependence and energy scales of the soft mode dynamics in PMN-xPT are independent of PT concentration below the MPB, and that the MPB may be defined in composition space x when TC matches the temperature at which the soft mode frequency begins to recover. High-resolution x-ray studies then showed that the C–T phase boundary shifted to higher temperatures under E by an expected amount within the MPB region: suggesting an unusual instability within the apparently cubic phase at the MPB. In Fe-xat.%Ga alloys, the addition of Ga atoms into the b.c.c. α-Fe phase also results in diversity of crystal structures and structural inhomogeneity, which are likely the source of its unusual magneto-elastic properties. I have carefully investigated decomposition of Fe-xat.%Ga alloys subjected to different thermal treatments by x-ray and neutron diffraction for 12 < x < 25. Quenching was found to suppress the formation of a DO₃ structure in favor of a high-temperature disordered bcc (A2) one. By contrast, annealing produced a two-phase mixture of A2 + DO₃ for 14 < x < 20 and a fully DO₃ phase for x = 25. A splitting of the (2 0 0) and (0 0 2) Bragg peaks observed along the respective transverse directions indicated that Fe-xat.%Ga –crystals' are composed of several crystal grain orientations (or texture structures), which are slightly tilted with respect to each other. In order to investigate the local structural distortions and heterogeneities, neutron diffuse scattering was performed on Fe-x%Ga alloys for different thermal conditions. Diffuse scattering around a (100) superlattice reflection was found for 14 < x < 22 in the furnace-cooled condition, indicative of short-range ordered DO₃ nanoprecipitates in an A2 matrix. This diffuse intensity had an asymmetric radial contour and an off-centering. Analysis (x=19) revealed two broad peaks with c/a–1.2: indicating that the DO₃-like nanoprecipitates are not cubic, but rather of lower symmetry with a large elastic strain. The strongest diffuse scattering was observed for x=19, which correspondingly had maximum magnetostriction: indicating a structural origin for enhanced magnetostriction.
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    Stability of Nanoporous Metals
    Crowson, Douglas A. (Virginia Tech, 2006-06-14)
    A study of the stability of bicontinuous nanoporous metals is presented. Atomic scale simulations are used to probe the dominant mechanisms of geometric relaxation in these materials. A method is presented for generating model bicontinuous metal / void structures for use in atomistic simulations of bicontinuous nanoporous solids. The structures are generated with periodic boundary conditions using a phase-field model to simulate the spinodal decomposition of an ideal system. One phase in the model is then associated with the pore volume while the other phase is associated with the metal ligaments. Small angle neutron scattering was used to quantitatively compare experimental samples to those generated by the phase field method. EAM results using model structures with experimentally accessible length scales are presented which demonstrate the potential of such simulations in understanding the behavior of nanoporous metals. Simulated relaxations of these structures, as well as the relaxation of model spherical clusters, indicate that the surface relaxation effect dominates the overall dimensional relaxation of np-metals post processing. Capillary effects play a secondary role in the overall relaxation. The simulation results presented also identify a maximum surface area to volume ratio necessary to maintain mechanical stability beyond which the pore structure collapses.
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    Studies on the structure and the magnetic properties of high-entropy spinel oxide (MgMnFeCoNi)Al2O4
    Krysko, Evan; Min, Lujin; Wang, Yu; Zhang, Na; Barber, John P.; Niculescu, Gabriela E.; Wright, Joshua T.; Li, Fankang; Burrage, Kaleb; Matsuda, Masaaki; Robinson, Robert A.; Zhang, Qiang; Katzbaer, Rowan; Schaak, Raymond; Terrones, Mauricio; Rost, Christina M.; Mao, Zhiqiang (AIP Publishing, 2023-10-20)
    The study of high-entropy materials has attracted enormous interest since they could show new functional properties that are not observed in their related parent phases. Here, we report single crystal growth, structure, thermal transport, and magnetic property studies on a novel high-entropy oxide with the spinel structure (MgMnFeCoNi)Al2O4. We have successfully grown high-quality single crystals of this high-entropy oxide using the optical floating zone growth technique for the first time. The sample was confirmed to be a phase pure high-entropy oxide using x-ray diffraction and energy-dispersive spectroscopy. Through magnetization measurements, we found (MgMnFeCoNi)Al2O4 exhibits a cluster spin glass state, though the parent phases show either antiferromagnetic ordering or spin glass states. Furthermore, we also found that (MgMnFeCoNi)Al2O4 has much greater thermal expansion than its CoAl2O4 parent compound using high resolution neutron Larmor diffraction. We further investigated the structure of this high-entropy material via Raman spectroscopy and extended x-ray absorption fine structure spectroscopy (EXAFS) measurements. From Raman spectroscopy measurements, we observed (MgMnFeCoNi)Al2O4 to display a combination of the active Raman modes in its parent compounds with the modes shifted and significantly broadened. This result, together with the varying bond lengths probed by EXAFS, reveals severe local lattice distortions in this high-entropy phase. Additionally, we found a substantial decrease in thermal conductivity and suppression of the low temperature thermal conductivity peak in (MgMnFeCoNi)Al2O4, consistent with the increased lattice defects and strain. These findings advance the understanding of the dependence of thermal expansion and transport on the lattice distortions in high-entropy materials.
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    Study of Nanowires Using Molecular Dynamics Simulations
    Monk, Joshua D. (Virginia Tech, 2007-11-01)
    In this dissertation I present computational studies that focus on the unique characteristics of metallic nanowires. We generated virtual nanowires of nanocrystalline nickel (nc-Ni) and single crystalline silver (Ag) in order to investigate particular nanoscale effects. Three-dimensional atomistic molecular dynamics studies were performed for each sample using the super computer System X located at Virginia Tech. Thermal grain growth simulations were performed on 4 nm grain size nc-Ni by observing grain sizes over time for temperatures from 800K to 1450K and we discovered grain growth to be linearly time-dependant, contrary to coarse grained materials with square root dependence. Strain induced grain growth studies consisted of straining the nanostructures in tension at a strain rate of 3.3 x 10^8 s⁻¹. Grain boundary movement was recorded to quantify grain boundary velocities and grain growth. It was shown that during deformation, there is interplay between dislocation-mediated plasticity and grain boundary accommodation of plasticity through grain boundary sliding. To further understand the effect of stress on nanocrystalline materials we performed tensile tests at different strain rates, varying from 2.22 x 10⁷ s⁻¹ to 1.33 x 10⁹ s⁻¹ for a 5 nm grain size nc-Ni nanowire with a 5 nm radius. The activation volume was given as ~2b³, where b is the Burger's vector and is consistent with a grain boundary dominate deformation mechanism. We expanded our research to 10 nm grain size nc-Ni nanowires with radii from 5 nm to 18 nm. Each wire was deformed 15% in tension or compression at a strain rate of 3.3 x 10⁸ s⁻¹. Asymmetry was observed for all radii, in which larger radii produced higher flow stresses for compression and small radii yielded higher flow stresses in tension. A cross over in the tension-compression asymmetry is found to occur at a radius of ~9 nm. A change in the dominate deformation mechanism in combination with the ease of grain boundary sliding contributes to the phenomena of the asymmetry. In the final chapter we focus on the energetic stability of multi-twinned Ag nanorods at the nanoscale. We used a combination of molecular statics and dynamics to find the local minimum energies for the multi-twinned nanorods and the non-twinned "bulk" materials and concluded that the stability of multi-twinned nanorods is highly influenced by the size of the sample and the existence of the ends. Using an analytical model we found the excess energy of the nanorods with ends and determined the critical aspect ratio below which five-twinned nanorods are stable.