gebhart/patrepeval huggingface dataset:
An Independent Visual Background Reduced Simulator Sickness in a Driving Simulator (2004)

Simulator sickness (SS)-virtual environment (VE) sickness is expected to become increasingly troublesome as VE technology evolves. This paper investigated using an independent visual background (IVB) to reduce SS and VE sickness. The IVB is a visual scene component that provides visual motion and orientation cues that match those from the vestibular receptors. In this study, the IVB was stationary, fixed with respect to inertial space. Two experiments were conducted. The first experiment examined the differences in visual motion-induced postural disturbance as a function of simultaneous exposure to an IVB. Subjects exhibited less balance disturbance when the IVB was presented. An expected statistically significant interaction between IVB presence-absence and visual scene motion oscillation frequency was observed. In the second experiment, subjects reported less SS when the IVB was presented during the VE exposure. We suggest that an IVB may alleviate disturbance when conflicting visual and inertial cues evoke SS.
In-run bias self-calibration for low-cost MEMS vibratory gyroscopes (2014)

We present a method for improving bias instability and Rate Random Walk (RRW) in low-cost MEMS vibratory gyroscopes by periodically reversing polarity of the resonator drive force, yielding a 5 times reduction of RRW noise. The feasibility of the approach was experimentally evaluated using an in-production Analog Devices ADXRS800, a fully integrated MEMS gyroscope with a quadruple mass architecture. The proposed method is to use periods of alternating co-phase and anti-phase drive clock to drive-mode oscillation periods, and sampling the gyroscope sense-mode output during the equal times of co-phase anti-phase drive of the resonator, thereby canceling the drive alignment bias error term. The proposed self-calibration method allows for long and short term stability improvement in low-cost and high performance MEMS vibratory gyroscopes.
Ultrasound Biomicroscopy of Cancer Therapy Effects: Correlation between Light and Electron Microscopy, and a New Non-Invasive Ultrasound Imaging Method for Detecting Apoptosis (2000)

Abstract We have discovered that high-frequency ultrasound imaging, or ultrasound biomicroscopy, can be used to detect apoptosis in a number of experimental systems. We have shown that such detection with 30-40 MHz ultrasound is possible using cells in an in vitro system (AML-3 leukemia cells) made to undergo apoptosis in response to treatment with a variety of cancer killing chemotherapeutic drugs. We have shown that ultrasound biomicroscopy can also detect programmed cell death in tissues made to undergo apoptosis in response to photodynamic therapy, currently an experimental cancer treating regimen. Lastly, we have shown that this ultrasound imaging approach works in vivo, using living animals where apoptosis has been induced similarly using photodynamic therapy. Specifically, apoptotic cells and regions of apoptosis in tissues exhibit up to a 36-fold increase in ultrasound backscatter intensity permitting this type of cell death to be readily discriminated from surrounding viable tissue.
Experiments on resonantly photo-pumped x ray lasers (1992)

We describe our recent effort to identify and study a promising resonantly photopumped x-ray laser scheme. In particular we will describe a scheme which uses the strong emission lines of a nickel-like ion to resonantly photo-pump a neon-like ion and enhance the lasing of the neon-like 3p {yields} 3s transitions.
Experimental Investigation of Heat Transfer in Microchannels (2003)

Heat transport in microchannels is experimentally investigated to explore the validity of classical correlations for conventional-sized rectangular channels in predicting the thermal behavior and the onset of transition in microchannels. The microchannels considered range in width from 194 μm to 534 μm, with the channel depth being nominally five times the width in each case. Ten microchannels were machined into a 2.54 cm by 2.54 cm copper substrate for each test piece. The experiments were conducted with deionized water, with the Reynolds number ranging from approximately 300 to 3500. The results show that the heat transfer in microchannels is satisfactorily predicted with a classical, continuum approach. However, the applicable classical correlations need to be chosen carefully to match the boundary and entrance length conditions imposed in the experiment.
CHARACTERIZATION, CLONING, AND EXPRESSION OF TWO DIAGNOSTIC ANTIGENS FOR TAENIA SOLIUM TAPEWORM INFECTION (2004)

Adult and larval stages of Taenia solium cause 2 diseases in humans, i.e., taeniasis and cysticercosis, respectively. Diagnosis and treatment of taeniasis are the ultimate means to eliminate cysticercosis. A serological taeniasis diagnostic test has been developed for laboratory use. However, recombinant forms of the taeniasis diagnostic proteins are required to overcome the limited supply of native proteins and allow the development of a low-cost and field-applicable test with high sensitivity and specificity. Using 2-dimensional electrophoresis of T. solium excretory and secretory (TSES) products from hamster adult tape-worm in vitro cultures, we have identified 5 T. solium-specific protein spots, with molecular weights of 33 kDa (protein isoelectrofocusing point [pI]: 5.6, 5.3, 5.1) and 38 kDa (pI: 4.6, 4.5). Protein sequencing and molecular cloning of these proteins showed that although endowed with different pls, the proteins with the same molecular weights shared the same protein backbone, named TSES33 and TSES38. Their full-length complementary DNAs encode proteins with 267 and 278 amino acids, respectively. TSES33 and TSES38 were expressed in a baculovirus system. Both recombinant proteins were recognized by a panel of taeniasis, but not cysticercosis patient serum samples, indicating that they can potentially replace the native proteins in the development of a more efficacious taeniasis diagnostic test.
CU-brick cable-driven robot for automated construction of complex brick structures: From simulation to hardware realisation (2018)

Robotic building construction has had significant advances in the recent decades, but also has various limitations. In particular, construction typically requires a robot to operate within a large space for long hours and be able to transport between sites. Cable-driven parallel robots (CDPRs) show strong potentials within the automation of construction due to its desirable characteristics, such as high payload-to-weight ratio, transportability, scalability and reconfigurability. This paper proposes a simulation-based analysis, design and pre-execution verification for a cable-driven brick structure building system (CU-Brick), among which a way to determine the buildable workspace where the construction could be constructed is proposed. Simulations are used to do the workspace analysis, design of the brick structure within the workspace and also verification that the motions can be executed. Using this simulation approach, real demonstrations have been performed to show that indeed the system is able to construct the brick structures safely and consistently.
Coupled phase-shift distributed-feedback semiconductor lasers for narrow linewidth operation (1989)

Mode properties of a coupled phase-shift distributed-feedback (DFB) structure are analyzed and the feasibility of narrow-linewidth emission is shown theoretically. The structure consists of a multiple number of phase-shift DFB laser units which are arranged in tandem and coupled with each other through additional phase shift of corrugation. Optimum structure parameters were determined for two coupled laser units so that the frequency detuning is zero and the mode pattern is the flattest. The mode analysis shows that the intensity distribution is flatter and the normalized coupling constant can be larger than those for the conventional DFB laser with a single phase shift. This indicates that the cavity length can be extended with less influence from the longitudinal spatial hole burning effect.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Evaluation of Anti-PLA2R1 as Measured by a Novel ELISA in Patients With Idiopathic Membranous Nephropathy (2014)

ELISA performs excellently in differentiating idiopathic from secondary MN. Furthermore, ELISA shared high agreement with WB and IIF.
Differentiation of human adipose-derived stem cells into “brite” (brown-in-white) adipocytes (2011)

It is well established now that adult humans possess active brown adipose tissue (BAT) which represents a potential pharmacological target to combat obesity and associated diseases. Moreover thermogenic brown-like adipocytes ("brite adipocytes") appear also in mouse white adipose tissue (WAT) upon β3-adrenergic stimulation. We had previously shown that human multipotent adipose-derived stem cells (hMADS) are able to differentiate into cells which exhibit the key properties of human white adipocytes, and then to convert into functional brown adipocytes upon PPARγ activation. In light of a wealth of data indicating that thermogenic adipocytes from BAT and WAT have a distinct cellular origin, we have characterized at the molecular level UCP1 positive hMADS adipocytes from both sexes as brite adipocytes. Conversion of white to brown hMADS adipocytes is dependent on PPARγ activation with rosiglitazone as the most potent agonist and is inhibited by a PPARγ antagonist. In contrast to mouse cellular models, hMADS cells conversion into brown adipocytes is weakly induced by BMP7 treatment and not modulated by activation of the Hedgehog pathway. So far no primary or clonal precursor cells of human brown adipocytes have been obtained that can be used as a tool to develop therapeutic drugs and to gain further insights into the molecular mechanisms of brown adipogenesis in humans. Thus hMADS cells represent a suitable human cell model to delineate the formation and/or the uncoupling capacity of brown/brite adipocytes that could help to dissipate caloric excess intake among individuals.
Room-temperature near-infrared tunable laser operation of Cr^4+:Ca_2GeO_4 (1996)

Large crystals of highly doped Cr(4+):Ca(2)GeO(4) were grown by a top-seeded solution growth method. Absorption and emission measurements for various crystal orientations have been performed. From the spectroscopic measurements, the only optically active center was identified as tetrahedrally coordinated Cr(4+). Gainswitched, tunable laser operation of Cr(4+):Ca(2)GeO(4) crystal was demonstrated. Pulse energies of 0.4 mJ at 1.4 microm have been generated at a repetition rate of 100 Hz. Tunability over the 1348-1482-nm spectral range has been demonstrated.
Test of SAGD Flow-Distribution-Control Liner System in the Surmont Field, Alberta, Canada (2013)

Summary The Surmont Well Pair 102-06 started steam-assisted-gravity drainage (SAGD) operation in April 2009 with flow-distribution control (FDC) built into the horizontal liners for both the injection and the production wells. After preheat steam circulation, this liner system has allowed operation without a toe tubing string in either completion and has delivered superior steam-chamber development and overall performance. The design also allowed reducing the liner and casing size for the injection well. Future SAGD-well design may benefit by further reduction in liner and casing sizes for both the injector and producer, which could allow longer completions by reducing liner drag and increasing directional-drilling flexibility. Ultimately, these SAGD-well design changes could increase the amount of reservoir developed per well and per well pad, using longer wells and more wells per pad while achieving superior SAGD performance.
Targeted silencing of the Aquaporin 2 gene of Rhipicephalus (Boophilus) microplus reduces tick fitness (2015)

Collectively, considering the gene expression and tick fitness data, we conclude that RmAQP2 is critical for tick blood feeding and may be a suitable candidate target for the development of novel strategies to control R. microplus and tick-borne parasites.
Development of a non-living vaccine against Burkholderia mallei (129.2) (2009)

Abstract Burkholderia mallei is a gram-negative highly pathogenic bacterium, responsible for glanders. B. mallei is considered potential bioterrorism agents, classified as such in list B by the Centers for Disease Control and Prevention. Currently there is no vaccine available against B. mallei. In this study, we aimed to identify the protective proteins of B. mallei. The candidate proteins were selected based on the previous data of proteomics and linear expression library (LEE) whole-genome screens coupled with known structures or functions of the proteins in other bacteria. The selected proteins were BMA-4, BMA-8, BMA-9, BMA-10, BMA-11 and BMA-12. The genes encoding each protein were cloned into pCDNA3.1 and pET28a. The His-tag proteins were then purified. BALB/c mice were vaccinated with DNA encoding each protein and then boosted 3 weeks later with the recombinant proteins. Two weeks after boosting, mice were infected with B. mallei ATCC23344. The result showed that, 19 days after infection, there was 100% survival in the BMA2821 and BMAA0768 groups, however only 78% survival in the control group. The study needs to be repeated and the result will be discussed.
Direct Growth of High-Power InGaN/GaN Quantum-Disks-in-Nanowires Red Light-Emitting Diodes on Polycrystalline Molybdenum Substrates (2016)

The first high-power InGaN/GaN quantum-disks-in-nanowires red (λ=705 nm) light-emitting diodes on metal substrates was demonstrated. The low turn-on voltage and high power were achieved through the direct growth of high-quality nanowires on TiN/Ti/Mo stack.
Secondary markets for mobile data: Feasibility and benefits of traded data plans (2015)

The growing volume of mobile data traffic has led many Internet service providers (ISPs) to cap their users' monthly data usage, with overage fees for exceeding their caps. In this work, we examine a secondary data market in which users can buy and sell leftover data caps from each other. China Mobile Hong Kong recently introduced such a market. While similar to an auction in that users submit bids to buy and sell data, it differs from traditional double auctions in that the ISP serves as the middleman between buyers and sellers. We derive the optimal prices and amount of data that different buyers and sellers are willing to bid in this market and then propose an algorithm for ISPs to match buyers and sellers. We compare the optimal matching for different ISP objectives and derive conditions under which an ISP can obtain higher revenue with the secondary market: while the ISP loses revenue from overage fees, it can assess administration fees and take the differences between the buyer and seller prices. Finally, we use one year of usage data from 100 U.S. mobile users to illustrate that the conditions for a revenue increase can hold in practice.
Power-Efficient RAM Mapping Algorithms for FPGA Embedded Memory Blocks (2007)

Contemporary field-programmable gate array (FPGA) design requires a spectrum of available physical resources. As FPGA logic capacity has grown, locally accessed FPGA embedded memory blocks have increased in importance. When targeting FPGAs, application designers often specify high-level memory functions, which exhibit a range of sizes and control structures. These logical memories must be mapped to FPGA embedded memory resources such that physical design objectives are met. In this paper, a set of power-efficient logical-to-physical RAM mapping algorithms is described, which converts user-defined memory specifications to on-chip FPGA memory block resources. These algorithms minimize RAM dynamic power by evaluating a range of possible embedded memory block mappings and selecting the most power-efficient choice. Our automated approach has been validated with both simulation of power dissipation and measurements of power dissipation on FPGA hardware. A comparison of measured power reductions to values determined via simulation confirms the accuracy of our simulation approach. Our power-aware RAM mapping algorithms have been integrated into a commercial FPGA compiler and tested with 34 large FPGA benchmarks. Through experimentation, we show that, on average, embedded memory dynamic power can be reduced by 26% and overall core dynamic power can be reduced by 6% with a minimal loss (1%) in design performance. In addition, it is shown that the availability of multiple embedded memory block sizes in an FPGA reduces embedded memory dynamic power by an additional 9.6% by giving more choices to the computer-aided design algorithms
Automatic generation of mobile app signatures from traffic observations (2015)

There are network management, traffic engineering, and security practices adopted in today's networking that rely on the knowledge about what applications' traffic is passing through the networks. These practices might fail with mobile apps whose identity remains hidden in generic HTTP traffic. The main reason is that unlike traditional applications, most mobile apps do not use specific protocols or IP ports with distinctive features. Many enterprises and service providers are in a great need of regaining control over their networks that increasingly carry mobile traffic. In this paper we propose FLOWR, a system that automatically identifies mobile apps by continually learning the apps' distinguishing features via traffic analysis. FLOWR focuses solely on key-value pairs in HTTP headers and intelligently identifies the pairs suitable for app signatures. Our system employs a custom supervised learning approach that leverages a very limited knowledge of app-signature seeds and autonomously grows its capacity for app identification. The approach is motivated by a simple but effective hypothesis that unknown app-identifying features should co-occur with the known signatures. Our experimental results show a significant growth in flow identification coverage provided by FLOWR. Specifically, we show that FLOWR can achieve identification of 86-95% of flows related to their generating apps.
High purity germanium crystal growth at the University of South Dakota (2015)

High-purity germanium crystal growth is challenging work, requiring the control of individual crystal properties such as the impurity distribution, the dislocation density, and the crystalline structure. Currently, we grow high-purity germanium crystals by the Czochralski method in our laboratory in order to understand the details of the growing process, especially for large diameter crystals. In this paper, we report the progress of detector-grade germanium crystal growth at the University of South Dakota.
Indexing highly dynamic hierarchical data (2015)

Maintaining and querying hierarchical data in a relational database system is an important task in many business applications. This task is especially challenging when considering dynamic use cases with a high rate of complex, possibly skewed structural updates. Labeling schemes are widely considered the indexing technique of choice for hierarchical data, and many different schemes have been proposed. However, they cannot handle dynamic use cases well due to various problems which we investigate in this paper. We therefore propose our dynamic Order Indexes , which offer competitive query performance, unprecedented update efficiency, and robustness for highly dynamic workloads.
Periodic activation functions in memristor-based analog neural networks (2013)

This work explores the use of periodic activation functions in memristor-based analog neural networks. We propose a hardware neuron based on a folding amplifier that produces a periodic output voltage. Furthermore, the amplifier's fold factor be adjusted to change the number of low-to-high or high-to-low output voltage transitions. We also propose a memristor-based synapse circuit and training circuitry for realizing the Perceptron learning rule. Behavioral models of our circuits were developed for simulating a single-layer, single-output feedforward neural network. The network was trained to detect the edges of a grayscale image. Our results show that neurons with a single fold-with an activation function similar to a sigmoidal activation function-perform the worst for this application, since they are unable to learn functions with multiple decision boundaries. Conversely, the 4-fold neuron performs the best (up to ≈65% better than the 1-fold neuron), as its activation function is periodic, and it is able to learn functions with four decision boundaries.
Phantom: a serializing compiler for multitasking embedded software (2006)

In an era of powerful general-purpose embedded compute platforms, the migration of system functionality from application specific integrated circuits (ASICs) to software has become a promising trend toward addressing the system complexity and shrinking time-to-market window challenges. Hence, in modern embedded systems, software development plays an increasingly vital role. On the other hand, the real-time concurrent programming model provides the high level abstractions necessary to effectively design complex software. Support for real-time concurrent programming is typically provided by a realtime operating system. We propose an alternate solution, the Phantom serializing compiler, to support the real-time concurrent programming model. The Phantom serializing compiler generates a single-threaded monolithic executable, from the multi-threaded application software, capable of directly executing on the underlying embedded compute platform. Further, the generated executable is tuned for maximum performance and efficiency, yielding an application-specific solution. In this paper, we give an overview of the Phantom serializing compiler and demonstrate its feasibility with some experimental results
KL-divergence kernel regression for non-Gaussian fingerprint based localization (2011)

Various methods have been developed for indoor localization using WLAN signals. Algorithms that fingerprint the Received Signal Strength Indication (RSSI) of WiFi for different locations can achieve tracking accuracies of the order of a few meters. RSSI fingerprinting suffers though from two main limitations: first, as the signal environment changes, so does the fingerprint database, which requires regular updates; second, it has been reported that, in practice, certain devices record more complex (e.g bimodal) distributions of WiFi signals, precluding algorithms based on the mean RSSI. In this article, we propose a simple methodology that takes into account the full distribution for computing similarities among fingerprints using Kullback-Leibler divergence, and that performs localization through kernel regression. Our method provides a natural way of smoothing over time and trajectories. Moreover, we propose unsupervised KL-divergence-based recalibration of the training fingerprints. Finally, we apply our method to work with histograms of WiFi connections to access points, ignoring RSSI distributions, and thus removing the need for recalibration. We demonstrate that our results outperform nearest neighbors or Kalman and Particle Filters, achieving up to 1m accuracy in office environments. We also show that our method generalizes to non-Gaussian RSSI distributions.
Pulsed laser triggered high speed microfluidic fluorescence activated cell sorter (2012)

We report a high speed and high purity pulsed laser triggered fluorescence activated cell sorter (PLACS) with a sorting throughput up to 20,000 mammalian cells/s with 37% sorting purity, 90% cell viability in enrichment mode, and >90% purity in high purity mode at 1,500 cells/s or 3,000 beads/s. Fast switching (30 μs) and a small perturbation volume (∼90 pL) is realized by a unique sorting mechanism in which explosive vapor bubbles are generated using focused laser pulses in a single layer microfluidic PDMS channel.