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Differentiating morphologically similar cerambycid beetle species by molecular and chemical analyses
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01The student, Anupama Udayakumar, accepted the attached license on 2025-07-18 at 18:37.The student, Anupama Udayakumar, submitted this Thesis for approval on 2025-07-18 at 18:51.This Thesis was approved for publication on 2025-07-21 at 10:44.DSpace SAF Submission Ingestion Package generated from Vireo submission #22664 on 2025-10-25 at 15:54:23The Cerambycidae, the longhorn beetles, is among the largest insect families with at least 35,000 described species. In their native ranges, cerambycids may provide important ecosystem services by initiating the breakdown of dying and dead tissues of woody plants, recycling the nutrients into forest ecosystems. However, some species are also pests due to their ability to damage wood or transmit plant diseases. As larvae of most cerambycid species are long-lived and can develop within lumber, palettes, dunnage, and other wooden products, they are also readily transported to new countries by international commerce, making them high-risk exotic species. A problem in managing some cerambycid pests is the difficulty discriminating between morphologically similar congeners. This study tests the hypothesis that cuticular hydrocarbon profiling provides an accurate means of identification. The study species were the morphologically similar congeners Graphisurus despectus (LeConte) and G. fasciatus (Degeer) (subfamily Lamiinae: tribe Acanthocinini) that are native to the eastern US. Forty-five adult beetles were collected from field sites in east-central Illinois, their hydrocarbons were extracted, and profiles were characterized and compared to identify consistent and diagnostic components. The beetles also were subjected to DNA sequencing to confirm the species status of the specimens. This study supported the hypothesis that hydrocarbon profiling is an efficient, cost-effective alternative to molecular methods for distinguishing between morphologically similar species of cerambycids, with potential applications in monitoring endangered species and managing pest species
Design space exploration of binary algebraic hard decision decoders for data center connectivity
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01The student, Gene Lee, accepted the attached license on 2025-07-24 at 12:17.The student, Gene Lee, submitted this Thesis for approval on 2025-07-24 at 12:25.This Thesis was approved for publication on 2025-07-24 at 13:09.DSpace SAF Submission Ingestion Package generated from Vireo submission #22679 on 2025-10-25 at 15:54:24The recent adoption of large artificial intelligence models with trillions of parameters has introduced the need for new connectivity solutions. These complex models are trained within data centers, involving coordinated execution across thousands of compute nodes, which requires the connectivity between these compute sockets to support higher data rates with lower latency and energy costs. This justifies a need to re-evaluate current communication systems and design connectivity links capable of supporting the rapidly growing compute and energy consumption of these future workloads. Forward error correction is a key component in enabling high-throughput, low-latency, and energy-efficient communication links, reducing the need for costly protocol-level retransmission and relaxing the signal-to-noise ratio requirements on the channel and analog front-end circuits. However, the design space of forward error correction implementations is vast, spanning across diverse families of codes, each with their corresponding decoding algorithms and very large-scale integration architectures. In this thesis, we explore the design space of binary algebraic hard decision decoders for connectivity. We first analyze and derive specifications on FEC for short-reach connectivity. These stringent requirements indicate that published works and implementations from communication standards do not meet these requirements. Therefore, we hypothesize that algebraic hard decision decoders, under a modern process node, are suitable baselines for connectivity due to their efficient decoding algorithms and high-speed architectures. We justify this both information-theoretically and experimentally, using a design space exploration methodology with place-and-routed circuit data points in a 28 nm process. From this exploration, we find that these algebraic decoders meet the connectivity specifications quite comfortably, which validates our hypothesis and provides a strong baseline to design decoders for future workloads
Global coal ball stable isotope analysis to define permineralizing environments
No full textSubmission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01The student, Hannah Beddow, accepted the attached license on 2025-07-24 at 12:08.The student, Hannah Beddow, submitted this Thesis for approval on 2025-07-24 at 12:18.This Thesis was approved for publication on 2025-07-25 at 10:36.DSpace SAF Submission Ingestion Package generated from Vireo submission #22729 on 2025-10-25 at 15:54:39Coal balls are permineralized calcareous remains of plant material from peat swamps of the late Carboniferous and early Permian, formed under conditions unique to the time period by processes that are still not fully understood. While multiple pathways have been proposed for the formation of coal balls, there is currently no consensus. Geochemical, petrological, and cyclostratigraphic results from previous studies have provided conflicting evidence suggesting that meteoric water or marine water is the source of the calcium carbonate ions responsible for permineralizing areas of the peat swamp. Similarly, there is a lack of consensus regarding the specific triggering mechanism by which calcite begins to precipitate within the peat. We aimed to establish a comprehensive global geochemical dataset of stable isotope values, with the goal of characterizing the environments and conditions necessary for the formation of coal balls. Our δ13C, δ18O, and 87Sr/86Sr measurements were within the range of a meteoric water source with a small number of outliers that suggested a marine water source. We interpret these results as indicating that coal balls formed in a predominantly meteoric water environment, with occasional inputs of marine water into the peat swamp
Sequential Change Point Detection via Denoising Score Matching
Get PDFSequential change-point detection plays a critical role in numerous real-world applications, where timely identification of distributional shifts can greatly mitigate adverse outcomes. Classical methods often assume that the pre- and post-change distributions are either fully known or belong to a parametric family with unknown parameters, limiting their effectiveness for high-dimensional and complex data streams. In this paper, we propose a score-based CUSUM-type detection procedure applicable when the pre- and post-change distributions are unknown and not restricted to parametric families. We begin by estimating their score functions through noise injection and denoising score matching. The online detection statistic is then constructed by accumulating the differences between the pre- and post-change Hyvarinen score functions, and a change is declared once this statistic exceeds a pre-specified threshold. We consider both offline and online versions of score estimation. Through theoretical analysis, we demonstrate that denoising score matching can enhance detection power by effectively controlling the injected noise scale. Finally, we validate the practical efficacy of our method through numerical experiments on two synthetic datasets and a real-world earthquake precursor detection task, demonstrating its effectiveness in real applications
An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources
Get PDFThis paper studies a biometric identification system model with two distinct biometric sources, extending beyond the existing model that assumes all biometric sequences are drawn from a common source. We consider a scenario involving two user groups, where the biometric sequences in each group are generated from separate sources and stored in two corresponding databases. To identify an unknown user, the decoder first performs hypothesis testing to determine which database the observed sequence is correlated with, followed by user identification. The main contribution of this work is the derivation of an achievable rate region for the optimal trade-off between identification rates and error exponent of the type-II error probability under negligible type-I error probability, called the capacity region. When testing against independence, the capacity region is obtained and coincides with previous results in several special cases
Leaky Multi-Message Private Information Retrieval with Differential Privacy Guarantees
Get PDFThe Private Information Retrieval (PIR) problem aims to enable users to privately access data stored on remote servers. Recently, there has been a growing interest in leaky PIR schemes, which enable users to trade off higher rates for a controlled leakage of information about the identities of the downloaded messages. Motivated by applications that require the simultaneous retrieval of multiple data items, we focus on the ϵ-differential privacy framework for Leaky Multi-message PIR (LMPIR). Our paper complements the existing work on multi-message PIR, which has so far focused on perfect privacy. Our main contribution is the construction of an LMPIR scheme based on a randomized query and answer generation mechanism that carefully balances the tradeoff between privacy and efficiency, and is tailored to maximize the retrieval rate under the given privacy parameter ϵ. Our scheme requires a small degree of subpacketization L, which grows at most linearly with the number of servers. We also outline an information-theoretic upper bound on the maximum achievable rate for LMPIR. Our numerical results indicate that our scheme achieves a better privacy-efficiency tradeoff compared to alternatives, such as repeated application of leaky single-message PIR schemes
Improved Achievable Rate for Single-Server SPIR over Binary Erasure Channels
Get PDFIn 1-out-of-D Symmetric Private Information Retrieval (SPIR) protocols, the client privately selects and retrieves one of the D files stored on a server, learns nothing about the remaining D − 1 files, and keeps its choice hidden from the server. We propose an achievable rate scheme for 1-out-of- D SPIR in a single-server setting over a binary erasure channel (BEC) with parameter ϵ, where the server controls the BEC input and the client observes the output. Existing 1-out-of-D SPIR protocols over BEC that build on repeated 1-out-of-2 primitives define the achievable rate as the number of bits transmitted per channel use. We propose a 1-out-of-D SPIR scheme over the BEC by repeating a novel 1-out-of-M SPIR scheme where [Editor’s note: see paper for mathematical equation]. Our derived achievable rate surpasses existing rates for ϵ ∈ [1/2, 1], and achieves the SPIR capacity for D = 2, and for D > 2 when [Editor’s note: see paper for mathematical equation]
Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
Get PDFWe present an architecture for scaling digital beamforming for wideband massive MIMO radar. Conventional spatial processing becomes computationally prohibitive as array size grows; for example, the computational complexity of MVDR beamforming scales as O(N3) for an N-element array. In this paper, we show that energy concentration in beamspace provides the basis for drastic complexity reduction, with array scaling governed by the O(N log N) complexity of the spatial FFT used for beamspace transformation. Specifically, we propose an architecture for windowed beamspace MVDR beamforming, parallelized across targets and subbands, and evaluate its efficacy for beamforming and interference suppression for government-supplied wideband radar data from the DARPA SOAP (Scalable On-Array Processing) program. We demonstrate that our approach achieves detection performance comparable to full-dimensional benchmarks while significantly reducing computational and training overhead, and provide insight into tradeoffs between beamspace window size and FFT resolution in balancing complexity, detection accuracy, and interference suppression
How Do We Measure Intelligence?
No full textIntelligence is something that scientists have studied for centuries. From a neuropsychological standpoint, intelligence can be defined as one's abilities to adapt and change according to different environments and learn from one's experiences (Sternberg, 2012). This somewhat vague definition has led to multiple ways to measure it over the years, with each one prioritizing and measuring different aspects of cognitive function