Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparsity Pattern Recovery in Compressed Sensing

Author(s): Reeves, Galen | Advisor(s): Gastpar, Michael | Abstract: The problem of recovering sparse signals from a limited number of measurements is now ubiquitous in signal processing, statistics, and machine learning. A natural question of fundamental interest is that of what can and cannot be recovered in the presence of noise. This thesis provides a sharp characterization for the task of sparsity pattern recovery (also known as support recovery). Using tools from information theory, we find a sharp separation into two problem regimes -- one in which the problem is fundamentally noise-limited, and a more interesting one in which the problem is limited by the behavior of the sparse components themselves. This analysis allows us to identify settings where existing computationally efficient algorithms, such as the LASSO or approximate message passing, are optimal as well as other settings where these algorithms are highly suboptimal. We compare our results to predictions of phase transitions made via the powerful but heuristic replica method, and find that our rigorous bounds confirm some of these predictions.The remainder of the thesis explores extensions of our bounds to various scenarios. We consider specially structured sampling matrices and show how such additional structure can make a key difference, analogous to the role of diversity in wireless communications. Finally, we illustrate how the new bounding techniques introduced in this thesis can be used to establish information-theoretic secrecy results for certain communication channel models that involve eavesdroppers.
Entrainment of Neuronal Oscillations as a Mechanism of Attentional Selection

Whereas gamma-band neuronal oscillations clearly appear integral to visual attention, the role of lower-frequency oscillations is still being debated. Mounting evidence indicates that a key functional property of these oscillations is the rhythmic shifting of excitability in local neuronal ensembles. Here, we show that when attended stimuli are in a rhythmic stream, delta-band oscillations in the primary visual cortex entrain to the rhythm of the stream, resulting in increased response gain for task-relevant events and decreased reaction times. Because of hierarchical cross-frequency coupling, delta phase also determines momentary power in higher-frequency activity. These instrumental functions of low-frequency oscillations support a conceptual framework that integrates numerous earlier findings.
Object-Oriented Templates for Automated Assembly Planning of Complex Products

In the assembly modeling of complex products, it is not unusual facing an explosive growth of assembly relations, or called combination explosion. Through integrating object-oriented methods with the knowledge template based modeling, in this paper, a new methodology is proposed to deal with the complexity of the assemblies of large-scale products. As such, the templates with various assembly relations can be defined for complex products; constitutive parts or subassemblies in a product structure are defined as object classes; their features can be encapsulated, and defined or modified freely via the parameters of object classes to meet the requirements of a specific instance. The new method supports reusing knowledge and simplifying assembly modeling of complex products. In this paper, recent literatures on object-oriented methodologies and knowledge template methods for assembly modeling are reviewed, the rationales of object-oriented templates are discussed, and a method is proposed for creating assembly templates for complex products. In the case study included in this paper, the developed method has been applied to digital modeling of aero-engines, thus, validating its performance.
Persistence of routing tables in Wireless Mesh Networks with duty cycling

Currently, clean energy sources, such as solar and wind power, are more and more used in Wireless Mesh Networks (WMNs). Such power sources, however, are intermittent and require these networks to save energy. Duty cycling is a common approach employed by WMNs to save energy by cyclically turning on and off the wireless radios. When the radios are turned off, the node's routing table eventually expires and, when the radios turn back on, it is necessary to wait for routes to be discovered before sending data. In order to eliminate this need, this work proposes a mechanism to ensure the persistence of the routing tables in wireless mesh networks. PORT (Persistence of Routing Tables) keeps track of routing entries while nodes are in the energy saving mode and thus allows nodes to exchange packets as soon as the radio turns on. Experiments show that PORT increases the route availability and consequently it increases up to 100% the network throughput.
Electrical Resistivities of Monocrystalline and Polycrystalline TiB2

The electrical resistivity of monocrystalline and polycrystalline TiB/sub 2/ was measured under an inert atmosphere by a four-point ac impedance technique over the range 298 to 1373 K. The results are expressed in the form /rho/ - /rho//sub 298/ = m(T - 298). The following values of /rho//sub 298/ (.mu cap omega.Xcm) and m(/eta/.cap omega.XcmXK/sup -1/) were determined: for polycrystalline TiB/sub 2/ (69% dense) 18.2 and 95; for polycrystalline TiB/sub 2/ (99% dense) 7.4 and 42; and for monocrystalline TiB/sub 2/ 6.6 and 34.9.
The applications of PCA in QSAR studies: A case study on CCR5 antagonists

Principal component analysis (PCA), as a well‐known multivariate data analysis and data reduction technique, is an important and useful algebraic tool in drug design and discovery. PCA, in a typical quantitative structure–activity relationship (QSAR) study, analyzes an original data matrix in which molecules are described by several intercorrelated quantitative dependent variables (molecular descriptors). Although extensively applied, there is disparity in the literature with respect to the applications of PCA in the QSAR studies. This study investigates the different applications of PCA in QSAR studies using a dataset including CCR5 inhibitors. The different types of preprocessing are used to compare the PCA performances. The use of PC plots in the exploratory investigation of matrix of descriptors is described. This work is also proved PCA analysis to be a powerful technique for exploring complex datasets in QSAR studies for identification of outliers. This study shows that PCA is able to easily apply to the pool of calculated structural descriptors and also the extracted information can be used to help decide upon an appropriate harder model for further analysis.
The ancestor of extant Japanese fancy mice contributed to the mosaic genomes of classical inbred strains

Commonly used classical inbred mouse strains have mosaic genomes with sequences from different subspecific origins. Their genomes are derived predominantly from the Western European subspecies Mus musculus domesticus, with the remaining sequences derived mostly from the Japanese subspecies Mus musculus molossinus. However, it remains unknown how this intersubspecific genome introgression occurred during the establishment of classical inbred strains. In this study, we resequenced the genomes of two M. m. molossinus–derived inbred strains, MSM/Ms and JF1/Ms. MSM/Ms originated from Japanese wild mice, and the ancestry of JF1/Ms was originally found in Europe and then transferred to Japan. We compared the characteristics of these sequences to those of the C57BL/6J reference sequence and the recent data sets from the resequencing of 17 inbred strains in the Mouse Genome Project (MGP), and the results unequivocally show that genome introgression from M. m. molossinus into M. m. domesticus provided the primary framework for the mosaic genomes of classical inbred strains. Furthermore, the genomes of C57BL/6J and other classical inbred strains have long consecutive segments with extremely high similarity (>99.998%) to the JF1/Ms strain. In the early 20th century, Japanese waltzing mice with a morphological phenotype resembling that of JF1/Ms mice were often crossed with European fancy mice for early studies of “Mendelism,” which suggests that the ancestor of the extant JF1/Ms strain provided the origin of the M. m. molossinus genome in classical inbred strains and largely contributed to its intersubspecific genome diversity.
An introduction to artificial prediction markets for classification

Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learning of conditional probability estimators. The artificial prediction market is a novel method for fusing the prediction information of features or trained classifiers, where the fusion result is the contract price on the possible outcomes. The market can be trained online by updating the participants' budgets using training examples. Inspired by the real prediction markets, the equations that govern the market are derived from simple and reasonable assumptions. Efficient numerical algorithms are presented for solving these equations. The obtained artificial prediction market is shown to be a maximum likelihood estimator. It generalizes linear aggregation, existent in boosting and random forest, as well as logistic regression and some kernel methods. Furthermore, the market mechanism allows the aggregation of specialized classifiers that participate only on specific instances. Experimental comparisons show that the artificial prediction markets often outperform random forest and implicit online learning on synthetic data and real UCI datasets. Moreover, an extensive evaluation for pelvic and abdominal lymph node detection in CT data shows that the prediction market improves adaboost's detection rate from 79.6% to 81.2% at 3 false positives/volume.
When are genetic methods useful for estimating contemporary abundance and detecting population trends?

The utility of microsatellite markers for inferring population size and trend has not been rigorously examined, even though these markers are commonly used to monitor the demography of natural populations. We assessed the ability of a linkage disequilibrium estimator of effective population size (Ne) and a simple capture‐recapture estimator of abundance (N) to quantify the size and trend of stable or declining populations (true N = 100–10,000), using simulated Wright–Fisher populations. Neither method accurately or precisely estimated abundance at sample sizes of S = 30 individuals, regardless of true N. However, if larger samples of S = 60 or 120 individuals were collected, these methods provided useful insights into abundance and trends for populations of N = 100–500. At small population sizes (N = 100 or 250), precision of the Ne estimates was improved slightly more by a doubling of loci sampled than by a doubling of individuals sampled. In general, monitoring Ne proved a more robust means of identifying stable and declining populations than monitoring N over most of the parameter space we explored, and performance of the Ne estimator is further enhanced if the Ne/N ratio is low. However, at the largest population size (N = 10,000), N estimation outperformed Ne. Both methods generally required ≥ 5 generations to pass between sampling events to correctly identify population trend.
Expression of tumor necrosis factor-stimulated gene-6 in the rat ovary in response to an ovulatory dose of gonadotropin.

Current evidence supports the hypothesis that the biochemical events of mammalian ovulation are analogous to an acute inflammatory reaction. This study reveals that tumor necrosis factor-stimulated gene-6 (TSG-6), which encodes a member of the superfamily of hyaluronan-binding proteins that is specifically translated in inflammatory reactions, is expressed in ovarian follicles that have been induced to ovulate. Immature Wistar rats were primed with 10 IU equine CG s.c. ; and 48 h later, the 12-h ovulatory process was initiated by 10 IU human CG (hCG), s.c. Ovarian RNA was extracted at 0, 2, 4, 8, 12, and 24 h after the primed animals were injected with hCG. The RNA extracts were used for RT-PCR differential display of amplified complementary DNAs (cDNAs) that represented gene expression in the stimulated ovarian tissue. Northern analysis of one of the differentially amplified cDNAs confirmed that it was part of a gene that was substantially up-regulated at 4-8 h after the ovaries had been stimulated by hCG. Subcloning and sequence analysis revealed that the cDNA matched the gene for TSG-6. In situ hybridization indicated that the TSG-6 messenger RNA was primarily located in the cumulus mass and the antral granulosa cells of large ovarian follicles. In conclusion, the data show that expression of TSG-6 is an integral part of the cascade of inflammatory-like changes that occur in an ovulatory follicle in response to a trophic hormone that couples with luteinizing hormone/hCG receptors.
Alignment Uncertainty and Genomic Analysis

The statistical methods applied to the analysis of genomic data do not account for uncertainty in the sequence alignment. Indeed, the alignment is treated as an observation, and all of the subsequent inferences depend on the alignment being correct. This may not have been too problematic for many phylogenetic studies, in which the gene is carefully chosen for, among other things, ease of alignment. However, in a comparative genomics study, the same statistical methods are applied repeatedly on thousands of genes, many of which will be difficult to align. Using genomic data from seven yeast species, we show that uncertainty in the alignment can lead to several problems, including different alignment methods resulting in different conclusions.
Trapped Holes Effect on Slow State Generation after Substrate Hole Injection in pMOSFETs

Defects created in p-metal-oxide-semiconductor-field-effect transistors by substrate-hole injection are studied. Both fast and slow interface states are found to be created during the holes injection process. After terminating the stress and applying positive gate bias, fast interface states are found to keep increasing, while slow states reduction and trapped holes annihilation are observed. The build up of fast interface states during and post stress is a consequence of holes injection and annihilation. However, the trapped holes have no influence on the number of slow states present in the oxide. The effect of trapped holes annihilation on both fast and slow states suggests that their formation mechanisms are not the same.
Language guided visual perception

People typically learn through exposure to visual stimuli associated with linguistic descriptions. For instance, teaching visual concepts to children is often accompanied by descriptions in text or speech. This motivates the question of how this learning process could be computationally modeled. In this dissertation we explored three settings, where we showed that combining language and vision is useful for machine perception using images and videos. First, we addressed the question of how to utilize purely textual description of visual classes with no training images, to learn explicit visual classifiers for them. We propose and investigate two baseline formulations, based on regression and domain transfer that predict a classifier. Then, we propose a new constrained optimization formulation that combines a regression function and a knowledge transfer function with additional constraints to predict the classifier parameters for new classes. We also proposed kernelized models, which allow utilizing any kernel functions in the visual space and text space. We applied the models to predict visual classifiers for two fine-grained categorization datasets, and the results indicate successful predictions against several baselines. Second, we modeled searching for events in videos as a language and vision problem, where we proposed a zero-shot event detection method using multi-modal distributional semantic embedding of videos. Our zero-shot event detection model is built on top of distributional semantics and extends it in the following directions: (a) semantic embedding of multimodal information in videos (with focus on the visual modalities), (b) automatically determining relevance of concepts/attributes to a free text query, which could be useful for other applications, and (c) retrieving videos by free text event query based on their content. We validated our method on the TRECVID MED (Multimedia Event Detection) challenge. Using only the event title as a query, our method outperformed the state-of-the-art that uses big descriptions. Third, and motivated by the aforementioned results, we proposed a uniform and scalable setting to learn unbounded number of visual facts. We proposed models that can learn, not only objects, but also their actions, attributes and interactions with other objects, in one unified learning framework and in a never-ending way. The training data comes as structured facts in images, including (1) objects (e.g., <boy>), (2) attributes (e.g.,<boy, tall>), (3) actions (e.g., <boy, playing>, and (4) interactions (e.g., <boy, riding, a horse >). We have worked on the scale of 814,000 images and 202,000 unique visual facts. Our experiments show the advantage of relating facts by the structure in the proposed models compared to four designed baselines on bidirectional fact retrieval. Defense Committee: Prof. Ahmed Elgammal (Chair), Prof. Casimir Kulikowski, Prof. Abdeslam Boularias, Prof. Abhinav Gupta (Carnegie Mellon University)
Telephone-based cognitive behavioral therapy for depression in Parkinson disease

Objective To determine whether, for patients with depression and Parkinson disease (PD), telephone-based cognitive-behavioral treatment (T-CBT) alleviates depressive symptoms significantly more than treatment as usual (TAU), we conducted a randomized controlled trial to evaluate the efficacy of a 10-session T-CBT intervention for depression in PD, compared to TAU. Methods Seventy-two people with PD (PWP) were randomized to T-CBT + TAU or TAU only. T-CBT tailored to PWPs’ unique needs was provided weekly for 3 months, then monthly during 6-month follow-up. CBT targeted negative thoughts (e.g., “I have no control”; “I am helpless”) and behaviors (e.g., social withdrawal, excessive worry). It also trained care partners to help PWP practice healthy habits. Blind raters assessed outcomes at baseline, midtreatment, treatment end, and 1 and 6 months post-treatment. Analyses were intent to treat. Results T-CBT outperformed TAU on all depression, anxiety, and quality of life measures. The primary outcome (Hamilton Depression Rating Scale score) improved significantly in T-CBT compared to TAU by treatment end. Mean improvement from baseline was 6.53 points for T-CBT and −0.27 points for TAU (p < 0.0001); gains persisted over 6-month follow-up (p < 0.0001). Improvements were moderated by a reduction in negative thoughts in the T-CBT group only, reflecting treatment target engagement. Conclusions T-CBT may be an effective depression intervention that addresses a significant unmet PD treatment need and bypasses access barriers to multidisciplinary, evidence-based care. Clinicaltrials.gov identifier NCT02505737. Classification of evidence This study provides Class I evidence that for patients with depression and PD, T-CBT significantly alleviated depressive symptoms compared to usual care.
The adverse impact of the TCP congestion-control mechanism in heterogeneous computing systems

Via experimental study, we illustrate how TCP modulates application traffic in such a way as to adversely affect network performance in a heterogeneous computing system. Even when aggregate application traffic smooths out as more applications' traffic are multiplexed, TCP induces burstiness into the aggregate traffic load, and thus hurts network performance. This burstiness is particularly bad in TCP Reno, and even worse when RED gateways are employed. Based on the results of this experimental study, we then develop a stochastic model for TCP Reno to demonstrate how the burstiness in TCP Reno can be modeled.
A simple algorithm for homeomorphic surface reconstruction

Abstract 1 Introduction The problem of computing a piecewise linear approximation to a surface from a set of sam- ple points on the surface has been a focus of research in solid modeling and graphics due to its many applications. The input to this sur- face reconstruction problem consists of the three dimensional coordinates of the sampled points. The crust algorithm of [1] reconstructs a surface with topological and geometric guarantees using the Voronoi diagram of the input point set. We present new observations that simplify both the algorithm and the proofs for the crust, and we give for the first time a proof that the crust is homeomorphic to the input surface. *Dept. of Computer Science, U. of Texas, Austin TX 78712. e-mail: amenta@cs.utexas. edu tDept, of Computer Science, U. of Texas, Austin, TX 78712. e-mail: sunghee@cs.utexas. edu SDept. of Computer and Information Science, Ohio State U. , Columbus, OH 43210. e-mail: t amaldey¢ci s. ohio-state, edu §Dept. of Computer and Information Science, Ohio State U. , Columbus, OH 43210. e-mail: leekha@cis, ohio-state, edu
Regulation of an Endogenous Locus Using a Panel of Designed Zinc Finger Proteins Targeted to Accessible Chromatin Regions

We have mapped conserved regions of enhanced DNase I accessibility within the endogenous chromosomal locus of vascular endothelial growth factor A (VEGF-A). Synthetic zinc finger protein (ZFP) transcription factors were designed to target DNA sequences contained within the DNase I-hypersensitive regions. These ZFPs, when fused to either VP16 or p65 transcriptional activation domains, were able to activate expression of the VEGF-A gene as assayed by mRNA accumulation and VEGF-A protein secretion through a range exceeding that induced by hypoxic stress. Importantly, multiple splice variants of VEGF-A mRNA with defined physiological functions were induced by a single engineered ZFP transcription factor. We present evidence for an enhanced activation of VEGF-A gene transcription by ZFP transcription factors fused to VP16 and p65 targeted to two distinct chromosomal sites >500 base pairs upstream or downstream of the transcription start site. Our strategy provides a novel approach for dissecting the requirements for gene regulation at a distance without altering the DNA sequence of the endogenous target locus.