Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementing Efficient, Portable Computations for Machine Learning

Author(s): Moskewicz, Matthew W. | Advisor(s): Keutzer, Kurt W | Abstract: Computers are powerful tools which perform fast, accurate calculations over huge sets of data. However, many layers of abstraction are required to use computers for any given task. Recent advances in machine learning employ compute-intensive operations embedded in complex overall flows. Further, deployment of these systems must balance many concerns: accuracy, speed, energy, portability, and cost. Currently, for each target, a good implementation of the needed software layers requires many programmer-years of effort. To address this, we explore new tools and methods to amplify programmer effort for machine learning applications. In particular, we focus on portability and speed for machine learning operations, algorithms, and flows. Additionally, we wish to maintain accuracy and carefully control the complexity of the overall software system. First, we motivate our approach with a case study in developing libHOG, which provides high-speed primitives for calculating image gradient histograms, where we achieve a 3.6X speedup over the state of the art. Next, in DenseNet, we enable previously prohibitively slow multiscale sliding window object detection using dense convolutional neural network features. Finally, we propose our Boda framework for implementing artificial neural network computations, based on metaprogramming, specialization, and autotuning. In Boda, we explore in depth the development of efficient convolution operations across various types of hardware. With only a few months of effort, we achieve speed within 2X of the highly-tuned vendor library on NVIDIA Graphics Processing Units (GPUs). Further, in only a few weeks, we achieve up to 30\% efficiency on Qualcomm mobile GPUs, where no vendor library exists.
Implementing a knowledge medium in a multi-centered clinical trial

The health care industry is essentially knowledge-based. Despite of this fact, knowledge management and processing techniques are mainly used in form of isolated systems for very specific domains. The basic processes of knowledge generation, distribution and consumption across domains and locations are not supported by integrated computer systems. Under the growing pressure on quality assurance and cost reduction, concepts and technologies to support the management of knowledge are increasingly gaining the interest of stakeholders. Such a concept-the knowledge medium-is introduced in this paper, and its applicability to the health care domain is demonstrated on the example of a multicentered clinical trial, i.e. the Swiss HIV Cohort Study. We define a knowledge medium as a platform for the exchange and management of knowledge within a specific community of agents. It comprises the following components. Information objects, i.e. interactive carriers containing externalized knowledge; agents who form a community with common interests and goals, a logical system, which defines the common syntax and semantics of the knowledge managed by the medium. We conclude that there great opportunities for knowledge media in the health care domain, and that the development of a knowledge medium must evolve such as to take into account both the processes of knowledge management and the technological convergence.
The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential

Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen–deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.
Application of Artificial Neural Network to Nondestructive Testing of Internal Wood Defects Based on the Intrinsic Frequencies

The location and size of internal wood defects are nondestructively determined using experimental modal analysis and artificial neural network in this study. The different defect sizes and locations were simulated by removing mass from intact wood specimens. At room temperature in the laboratory, free vibration testing was conducted to generate the frequency response functions (FRF) of intact and defective Korean Pine (Pinus koraiensis) wood specimens using fast Fourier transform analysis system. The first three orders intrinsic frequencies were captured by picking up the location of each order peak of FRF curves. Then, two identification indexes developed by previous research were constructed based on these intrinsic frequencies, and they were used as input parameters to build the networks for localization and size determination of wood defects respectively. These two artificial neural networks were trained and tested for wood defects recognition. The research results showed that: (1) the intrinsic frequencies of defective wood were lower than those of intact wood; and (2) the constructed two identification indexes were capable to effectively detect the location and size of wood defects, which were more sensitive to large size defects than small size defects.
Inhibition of thioredoxin reductase (E.C. 1.6.4.5.) by antitumor quinones.

Thioredoxin reductase (TR) is a widely distributed flavoenzyme that provides reduced thioredoxin, a dithiol hydrogen donor for protein disulfide reduction and for the reduction of ribonucleotides to deoxyribonucleotides, the first unique step of DNA synthesis. Antitumor quinones were found to exhibit time- and concentration-dependent inhibition of purified rat liver TR that requires the presence of NADPH. Diaziquone initially shows competitive inhibition of the enzyme with 5,5'-dithiobis 2-nitrobenzoic acid as substrate with a Ki of 7.5 microM, which becomes non-competitive after 1 hour incubation with NADPH with a Ki of 0.5 microM. Doxorubicin shows non-competitive inhibition both initially and after 1 hr incubation with NADPH, with Ki values of 10 microM and 0.5 microM, respectively. Electron spin resonance spectroscopy showed the formation of semiquinone free radicals by TR incubated under anaerobic conditions with doxorubicin or diaziquone and NADPH. Redox cycling and formation of oxygen radicals does not play a major role in the inhibition of TR by antitumor quinones as shown by the minor effect on inhibition of removing O2, and the lack of effect of superoxide dismutase and catalase. Diaziquone causes time- and concentration-dependent inhibition of TR activity in intact A204 human rhabdomyosarcoma cells that is associated with growth inhibition. The results suggest that inhibition of TR by antitumor quinones could contribute to their growth inhibitory properties.
Hyperbola tracing algorithm based on particle filter approach within a half-quadrant space for signal source localization

Signal source localization has become an interesting research problem due to its wide applications. Time Difference of Arrival is one of the popular models to estimate the location of signal source using multiple sensors. Closed-form and exact-solution algorithms are commonly utilized to solve non-linear distance equations in the model through linearization process. As an alternative, hyperbola-tracing algorithm to find intersection point between two hyperbolas is proposed in this paper. This algorithm starts with reduction of possible solution space into half of a quadrant in 2D problem. It is carried out through comparison of time of signal arrival at each sensor. Two pairs of sensors are then selected to build two hyperbolas. The second step consists of particle-filter-based approach to seek the intersection of these two non-linear functions. A simulation is presented to show the performance of this algorithm.
Long interspersed nuclear elements (LINEs) show tissue-specific, mosaic genome and methylation-unrestricted, widespread expression of noncoding RNAs in somatic tissues of the rat

We report strong somatic and germ line expression of LINE RNAs in eight different tissues of rat by using a novel ~2.8 kb genomic PstI-LINE DNA (P1-LINE) isolated from the rat brain. P1-LINE is present in a 93 kb LINE-SINE-cluster in sub-telomeric region of chromosome 12 (12p12) and as multiple truncated copies interspersed in all rat chromosomes. P1-LINEs occur as inverted repeats at multiple genomic loci in tissue-specific and mosaic patterns. P1-LINE RNAs are strongly expressed in brain, liver, lungs, heart, kidney, testes, spleen and thymus into large to small heterogeneous RNAs (~5.0 to 0.2 kb) in tissue-specific and dynamic patterns in individual rats. P1-LINE DNA is strongly methylated at CpG-dinucleotides in most genomic copies in all the tissues and weakly hypomethylated in few copies in some tissues. Small (700–75 nt) P1-LINE RNAs expressed in all tissues may be possible precursors for small regulatory RNAs (PIWI-interacting/piRNAs) bioinformatically derived from P1-LINE. The strong and dynamic expression of LINE RNAs from multiple chromosomal loci and the putative piRNAs in somatic tissues of rat under normal physiological conditions may define functional chromosomal domains marked by LINE RNAs as long noncoding RNAs (lncRNAs) unrestricted by DNA methylation. The tissue-specific, dynamic RNA expression and mosaic genomic distribution of LINEs representing a steady-state genomic flux of retrotransposon RNAs suggest for biological role of LINE RNAs as long ncRNAs and small piRNAs in mammalian tissues independent of their cellular fate for translation, reverse-transcription and retrotransposition. This may provide evolutionary advantages to LINEs and mammalian genomes.
Comparison of plasma extraction techniques in preparation of samples for endotoxin testing by the Limulus amoebocyte lysate test

Due to the presence of inhibitory and possible mimicking substances in plasma difficulties have occurred in the use of the Limulus amoebocyte lysate test. Currently, there are a variety of extraction techniques discussed in the literature which are used to remove these interfering substances, but there is little information comparing these techniques. Five such procedures were compared in their ability to provide an extracted plasma sample in which low levels of endotoxin could be detected by the Limulus amoebocyte lysate test. Results indicated that some procedures adversely affected endotoxin detection. The dilution + heating extraction method was found to be as effective as the widely used chloroform extraction method. Comparison of Limulus amoebocyte lysate test results from healthy human plasma samples extracted by these two methods indicated that lysate type and not extraction procedure was associated with previously reported questionable positive tests. Thus, ambiguities associated with Limulus amoebocyte lysate tests of plasma samples may be due not only to extraction method but also the lysate type employed.
Low complexity LID using pruned pattern tables of LZW

We present two discriminative language modelling techniques for Lempel-Ziv-Welch (LZW) based LID system. The previous approach to LID using LZW algorithm was to directly use the LZW pattern tables forlanguage modelling. But, since the patterns in a language pattern table are shared by other language pattern tables, confusability prevailed in the LID task. For overcoming this, we present two pruning techniques (i) Language Specific (LS-LZW)-in which patterns common to more than one pattern table are removed. (ii) Length-Frequency product based (LF-LZW)-in which patterns having their length-frequency product below a threshold are removed. These approaches reduce the classification score (Compression Ratio [LZW-CR] or the weighted discriminant score [LZW-WDS]) for non native languages and increases the LID performance considerably. Also the memory and computational requirements of these techniques are much less compared to basic LZW techniques.
Impact Monitoring of Smart Composite Laminates Using Neural Network and Wavelet Analysis

Low-velocity impact damage is a major concern in the design of structures made of advanced laminated composites, because such damage is mostly hidden inside the laminates and cannot be detected by visual inspection. It is necessary to develop the impact monitoring techniques providing on-line diagnostics of smart composite structures susceptible to impacts. In this paper, we discuss the process for impact location detection in which the generated acoustic signals are detected by PZT using the improved neural network paradigms. To improve the accuracy and reliability of a neural network based impact identification method, the Levenberg-Marquardt algorithm and the generalization methods were applied. This study concentrates not only on the determination of the location of impacts from sensor data, but also the implementation of time-frequency analysis such as the Wavelet Transform (WT) to measure the characteristic frequencies of acoustic emission waves for the determination of the occurrence and the estimation of impact damage.
Management of Anomia

Abstract Anomia is a complex, commonly occurring symptom of aphasia with different underlying causes. A number of behavioral approaches to rehabilitation of anomia have been described. Some are restitutive in nature and attempt to reactivate lexical-semantic or phonological representations to improve word retrieval. Others are intended to reorganize language functions by engaging alternative cognitive systems to mediate word retrieval or by exploiting residual abilities to circumvent the impairment. A better appreciation of the characteristics of an individual’s naming deficit may assist the clinician in selecting appropriate interventions for restitution or substitution of function in the management of this disorder.
Intraspecific competition affects the strength of individual specialization : an optimal diet theory method

Question: Why would individuals that inhabit the same environment choose to feed on different subsets of the available resources? Mathematical method: We outline a flexible model that combines phenotypic variation with optimal diet theory and population dynamics. We then apply this model to investigate the role of different types of trade-offs, phenotype diversity and level of competition in determining the degree of individual specialization. Key assumptions: The foragers in the model are omniscient and maximize energy intake per time unit. Conclusion: Numerical simulations match empirical observations that changes in population density can alter the degree of individual specialization. Forager density and phenotypic variation affected prey densities, which in turn affected forager diet breadth and fitness (energy income). We propose that this feedback can explain the empirical relationship between forager density and the degree of individual specialization in the forager population.
Biocompatibility of MG-63 Cells on Collagen, Poly-L-Lactic Acid, Hydroxyapatite Scaffolds with Different Parameters

Purpose In this study, osteoblast-like MG-63 cells were cultured on 3 different scaffold types composed of (a) collagen + poly-L-lactic acid (PLLA), (b) collagen + hydroxyapatite (HA; 30°C) or (c) collagen + hydroxyapatite (HA; 37°C) and produced with different porosities. Methods Biomechanical properties of the scaffolds were characterized by tensile strength measurements. Properties of the cell-seeded scaffolds were evaluated with scanning electron microscopy (SEM). Cell adhesion and proliferation capacities were evaluated. Alkaline phosphatase (ALP) levels in media were measured. Transmission electron microscopy (TEM) and histological analyses were used to assess morphological characteristics. Results Our results showed that collagen-based PLLA and HA scaffolds have good cell biocompatibility. MTT test showed that the scaffolds exhibited no cytotoxicity. According to the force and displacement data, collagen + HA at 37°C showed the highest mechanical strength and displacement. Conclusion The results suggest that collagen-based PLLA and HA scaffolds might improve osteoblastic growth in vitro and have biomaterial integration potential in possible therapeutic approaches for future clinical studies.
A reduced surface-wave twin arc-slot antenna for millimeter-wave applications

A simple, uniplanar, reduced surface-wave twin arc-slot antenna element for millimeter-wave (mm-wave) integrated circuit antenna systems is presented. This design allows for almost complete surface-wave cancellation and resonance to be achieved simultaneously. Measured far-field radiation patterns on an electrically thick substrate are in very good agreement with theory and show little evidence of surface-wave propagation.
Role of the Steroid Receptor Coactivator SRC-3 in Cell Growth

ABSTRACT Steroid receptor coactivator 3 (SRC-3/p/CIP/AIB1/ACTR/RAC3/TRAM-1) is a member of the p160 family of nuclear receptor coactivators, which includes SRC-1 (NCoA-1) and SRC-2 (TIF2/GRIP1/NCoA2). Previous studies indicate that SRC-3 is required for normal animal growth and is often amplified or overexpressed in many cancers, including breast and prostate cancers. However, the mechanisms of SRC-3-mediated growth regulation remain unclear. In this study, we show that overexpression of SRC-3 stimulates cell growth to increase cell size in prostate cancer cell lines. Furthermore, our results indicate that overexpression of SRC-3 can modulate the AKT signaling pathway in a steroid-independent manner, which results in the activation of AKT/mTOR signaling concomitant with an increase in cell size. In contrast, down-regulation of SRC-3 expression in cells by small interfering RNA decreases cell growth, leading to a smaller cell size. Similarly, in SRC-3 null mutant mice, AKT signaling is down-regulated in normally SRC-3-expressing tissues. Taken together, these results suggest that SRC-3 is an important modulator for mammalian cell growth.
Cocoa (Theobroma cacao) Polyphenol-rich Extract Increases the Chronological Lifespan of Saccharomyces cerevisiae.

BACKGROUND Saccharomyces cerevisiae is a model organism with conserved aging pathways. Yeast chronological lifespan experiments mimic the processes involved in human non-dividing tissues, such as the nervous system or skeletal muscle, and can speed up the search for biomolecules with potential anti-aging effects before proceeding to animal studies. OBJECTIVE To test the effectiveness of a cocoa polyphenol-rich extract (CPE) in expanding the S. cerevisiae chronological lifespan in two conditions: in the stationary phase reached after glucose depletion and under severe caloric restriction. MEASUREMENTS Using a high-throughput method, wild-type S. cerevisiae and its mitochondrial manganese-dependent superoxide dismutase null mutant (sod2Δ) were cultured in synthetic complete dextrose medium. After 2 days, 0, 5 and 20 mg/ml of CPE were added, and viability was measured throughout the stationary phase. The effects of the major components of CPE were also evaluated. To determine yeast lifespan under severe caloric restriction conditions, cultures were washed with water 24 h after the addition of 0 and 20 mg/ml of CPE, and viability was followed over time. RESULTS CPE increased the chronological lifespan of S. cerevisiae during the stationary phase in a dose-dependent manner. A similar increase was also observed in (sod2Δ). None of the major CPE components (theobromine, caffeine, maltodextrin, (-)-epicatechin, (+)-catechin and procyanidin B2) was able to increase the yeast lifespan. CPE further increased the yeast lifespan under severe caloric restriction. CONCLUSION CPE increases the chronological lifespan of S. cerevisiae through a SOD2-independent mechanism. The extract also extends yeast lifespan under severe caloric restriction conditions. The high-throughput assay used makes it possible to simply and rapidly test the efficacy of a large number of compounds on yeast aging, requiring only small amounts, and is thus a convenient screening assay to accelerate the search for biomolecules with potential anti-aging effects.
Integrating content and semantic representations for music recommendation

Music recommender systems are used by millions of people every day to discover new and exciting music. Central to making recommendations is the representation of each track, which may be used to calculate similarity. Content representations capture the musical and texture facets of each track, and semantic representations describe social and cultural information provided by listeners. This thesis is motivated by an analysis of the strengths and weaknesses of both content and semantic representations. Content representations can be available for all tracks in a collection, but provide poor recommendation quality. Semantic representations suffer from the cold-start problem and are not available for all tracks, but provide good recommendation quality when a strong representation is available. These observations highlight the need to integrate both content and semantic representations, and use the strengths of each to improve music recommendation quality and discovery. A bridge of the gap between content and semantic representations is achieved in this thesis through hybrid representation. Content texture representations are examined, and a new music-inspired texture representation is defined. This content is integrated with semantic tags directly, and through a mid-level pseudo-tag representation. The effect of these approaches is to increase the high quality discovery of tracks, and to allow users to uncover interesting novel recommendations. The challenge of evaluating music recommendations when many tracks are undertagged is addressed. Implicit and explicit feedback provided by users is exploited to define a new ground truth similarity measure, which accurately reflects how different recommendation methods perform. A user study is conducted to evaluate both this measure, and the performance of integrated representations for recommending strong novel recommendations.