gebhart/patrepeval huggingface dataset:
Low size, weight and power quantum key distribution system for small form unmanned aerial vehicles (2019)

The security of sensitive information exchange has become a major topic in recent years. Quantum Key Distribution (QKD) provides a highly secure approach to share random encryption keys between two communication terminals. In contrast with traditional public cryptography methods, QKD security relies on the foundations of quantum mechanics and not on computational capabilities. This makes QKD unconditionally secure (if properly implemented) and it is envisaged as a main component in the next–generation cryptographic technology. QKD has already been successfully demonstrated in different contexts such as fibre-to- fibre, and free-space ground-toground as well as ground-to-air communications. However, Size, Weight and Power (SWaP) constraints have prevented previous implementations to be demonstrated on small form airborne platforms such as Unmanned Aircraft Systems (UAS) and High Altitude Pseudo-Satellites (HAPS). Project Q-DOS aims to deliver a QKD module using compact, cutting-edge photonic waveguide technology, which will allow low-SWaP aerospace requirements to be met. This module uses 1550 nm single photons to implement a BB84 protocol, and will enable the demonstration of a secure, high-speed optical communication data link (~0.5 Gbps) between a drone and a ground station. The targeted link range is 1 km. The airborne communications module, including the QKD terminal, tracking modules, traditional communications systems, optics and control electronics, must not exceed a mass of 5 kg and a power consumption of 20 W.
Enabling Mobility in LTE-Compatible Mobile-edge Computing with Programmable Switches (2019)

Network softwarization triggered a new wave of innovation in modern network design. The next generation of mobile networks embraces this trend. Mobile-edge computing (MEC) is a key part of emerging mobile networks that enables ultra-low latency mission-critical application such as vehicle-to vehicle communication. MEC aims at bringing delay-sensitive applications closer to the radio access network to enable ultra-low latency for users and decrease the back-haul pressure on mobile service providers. However, there are no practical solutions to enable mobility at MEC where connections are no longer anchored to the core network and serving applications are supposed to move as their users move. We propose the mobile-edge gateway (MEGW) to address this gap. MEGW enables mobility for MEC applications transparently and without requiring any modifications to existing protocols and applications. MEGW supports mobility by reconstructing mobile users' location via listening to LTE control plane in addition to using two-stage location-dependent traffic steering for edge connections. Networks can incrementally upgrade to support MEC by upgrading some IP router to programmable switches that run MEGW. We have implemented MEGW using P4 language and verified its compatibility with existing LTE networks in a testbed running reference LTE protocol stack. Furthermore, using packet-level simulations we show that the two-stage traffic steering algorithm reduces the number of application migrations and simplifies service provisioning.
Direct Synthesis of Carbon Nanofibers on Cement Particles (2010)

Carbon nanotubes (CNTs) and nanofibers (CNFs) are promising candidates for the next generation of high-performance structural and multifunctional composite materials. One of the largest obstacles to creating strong, electrically or thermally conductive CNT–CNF composites is the difficulty of getting a good dispersion of the carbon nanomaterials in a matrix. Typically, time-consuming steps are required in purifying and functionalizing the carbon nanomaterial. A new approach under which CNTs–CNFs are grown directly on the surface of matrix and matrix precursor particles is proposed. Cement was selected as the precursor matrix, since it is the most important construction material. A novel cement hybrid material (CHM) was synthesized in which CNTs and CNFs are attached to the cement particles by two different methods: screw feeder and fluidized bed reactors. CHM has been proved to increase the compressive strength by two times and the electrical conductivity of the hardened paste by 40 times.
N,P-Doped Carbon Nanodots for Food-Matrix Decontamination, Anticancer Potential, and Cellular Bio-Imaging Applications (2020)

We report a facile one-step thermal treatment method for the synthesis of biocompatible, fluorescent nitrogen-phosphorus-doped carbon nanodots (NPCDs) as multifunctional agents for the food matrix decontamination, cancer targeting, and cellular bio-imaging. NPCDs exhibit high toxicity towards <i>L. monocytogenes</i>, as illustrated by fluorescent live-dead cell counting, disruption of membrane permeability/potential, changes in the levels of cellular ions, genetic materials, and proteins, as well as intracellular production of reactive oxygen species. The tryptophan and protein peaks released in NPCDs treated cells contributed to indole ring breathing and correlated with induced cell death. NPCDs significantly inhibited bacterial biofilm formation on a solid substrate. NPCDs-coated low-density polyethylene (LDPE) film crosslinked with 1% aminopropyltriethoxy silane (APTES) via silane-hydroxyl linking as a food-grade wrap significantly reduced bacterial counts in a raw chicken food model. Furthermore, NPCDs induced apoptosis in HeLa cervical cancer cells, as confirmed by the distorted cell morphology, fluorescence microscopic analysis, presence of fragmented nuclei and the qPCR results of mRNA expression levels of apoptotic markers. Moreover, NPCDs were also applicable in utilized for the cellular bio-imaging of KM12-C colon cancer cells under confocal microscopy owing to their excellent luminescence properties. Overall, NPCDs represent a promising platform to reduce the environmental health risks associated with hazardous pathogens, anticancer targeting, and their application in cellular bio-imaging as multifunctional targets/nanocarriers.
Desorption Electrospray Mass Spectrometry (2014)

This chapter encompasses applications, fundamentals, instrumentation and future perspectives of desorption electrospray ionization (DESI) mass spectrometry (MS). Since it was first reported in 2004, DESI has paved the way for the development of ambient ionization MS with a wide variety of applications ranging from the analysis of pharmaceutical and illicit drugs to biological lipids and fatty acids. DESI-MS imaging has proven to be one of the most important applications of DESI, yielding comparable data to nonambient MS imaging techniques for tumor classification, virtual fingerprint chemical mapping and many other imaging applications. The development of DESI-MS for such a wide variety of applications has been aided by fundamental studies, which have established a mechanism in which primary DESI droplets first cause analyte dissolution followed by splashing from the surface to produce secondary, sample-containing droplets. A major area that has evolved directly from increased mechanistic understanding is the development of reactive DESI-MS, where reagents are added so as to react with analyte in the secondary droplets to yield better specificity and/or ionization efficiency. In addition to enhancing analytical performance, reactivity in these small secondary droplets often occurs at rates many orders of magnitude faster than bulk-phase reactions. Another developing area of DESI-MS application is its use as an intrasurgical tool to obtain tissue diagnosis including tumor margin assessment. The implementation of DESI-MS for novel applications like these as well as its use in conjunction with a portable mass spectrometer is covered.
Hybrid clean approach for post-copper CMP defect reduction (2013)

A “hybrid” post-Cu CMP cleaning process that combines acidic and basic cleans in sequence is developed and implemented. The new process demonstrates the advantages of both acidic and basic cleans and achieves a more than 60% reduction in CMP defects, such as polish residues, foreign materials, slurry abrasives, scratches, and hollow metal, relative to an all-basic brush clean process. It also eliminates the circular ring defects that occur intermittently during roller brush clean. TXRF scans confirm the reduction of AlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> defects when using the hybrid clean process. XPS spectra show similar Cu surface oxidation states between the basic and hybrid clean processes. Both short and open yields can be improved by using the new clean process. The underlying mechanism of the huge defect reduction benefits is discussed.
A new modified HF-last cleaning process for high-performance gate dielectrics (2003)

A cleaning mixture which consists of HF with minute amounts of IPA added is discussed. This solution prevents the deposition of particles on the Si surface during HF-dipping and subsequent deionized-water rinsing and does not change the chemical state of the surface significantly. The characteristics of a thin gate oxide grown after this treatment show a markedly improved performance over the standard HF-last or RCA-cleaned samples. The addition of IPA to the HF mixture gives electrical breakdown results which are comparable to or better than the best results for HF-last samples. This demonstrates that the physisorbed IPA poses no problem for the gate oxide growth. It was observed that the contact angle directly correlates with the gate oxide yield. It is, therefore, a very powerful and fast technique for characterizing the Si surface after various treatments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
A frequency based sighting blurring algorithm for use with location based services on the internet (2008)

In this paper we describe a sighting blurring algorithm for use by a trusted middleware infrastructure, which is part of an architecture that supports the operation of Location Based Services (LBSs) over the Internet. This infrastructure can only obtain sightings for the users who are directly involved in a current invocation of an LBS. Therefore, our sighting blurring algorithm is designed to be dependent on only the sightings of these users. Our sighting blurring algorithm offers these users increased privacy by performing spatial blurring on the location components of their sightings. It does not perform temporal blurring, because we believe that this reduces an LBS's ability to offer a useful service. Instead, our sighting blurring algorithm introduces a new parameter that specifies the frequency with which sightings are released by the infrastructure for a particular user. This frequency parameter is a function of the size of the location component.
Early Onset of SARS-COV-2 Antibodies after First Dose of BNT162b2: Correlation with Age, Gender and BMI (2021)

Our study demonstrates that a single dose of BNT162b2 activates the immune response, and being young and normal-weight correlate positively with this response. Larger specifically designed clinical trials are needed to validate these results.
LED-based CO2 Sensor for Balloon Deployment (2011)

We are developing a sensor for monitoring ambient CO2 from unmanned aircraft and balloons. The sensor consists of a mid-IR LED coupled with a high dynamic range gated integrator. The measurement precision is 0.4 ppmv at 30 seconds.
Preparation and Characterization of Low Dispersity Anionic Multiresponsive Core–Shell Polymer Nanoparticles (2012)

We prepared anionic multistimuli responsive core-shell polymer nanoparticles with very low size dispersity. By using either acrylic acid (AA) or methacrylic acid (MA) as a comonomer in the poly(N-isopropyl acrylamide) (PNIPAM) shell, we are able to change the distribution of negative charges in the nanoparticle shell. The particle size, volume phase transition temperature, and aggregation state can be modulated using temperature, pH, or ionic strength, providing a very versatile platform for applications in sensors, medical diagnostics, environmental remediation, etc. The nanoparticles have a glassy poly(methyl methacrylate) (PMMA) core of ca. 40 nm radius and a cross-linked PNIPAM anionic shell with either AA or MA comonomers. The particles, p(N-AA) and p(MA-N), respectively, have the same total charge but different charge distributions. While the p(MA-N) particles have the negative charges preferentially distributed toward the inner shell, in the case of the p(N-AA) particles the charge extends more to the particle outer shell. The volume phase transition temperature (T(VPT)) of the particles is affected by the charge distribution and can be fine-tuned by controlling the electrostatic repulsion on the particle shell (using pH and ionic strength). By suppressing the particle charge we can also induce temperature-driven particle aggregation.
An algorithmic framework for the decoding problem in statistical machine translation (2004)

The decoding problem in Statistical Machine Translation (SMT) is a computationally hard combinatorial optimization problem. In this paper, we propose a new algorithmic framework for solving the decoding problem and demonstrate its utility. In the new algorithmic framework, the decoding problem can be solved both exactly and approximately. The key idea behind the framework is the modeling of the decoding problem as one that involves alternating maximization of two relatively simpler subproblems. We show how the subproblems can be solved efficiently and how their solutions can be combined to arrive at a solution for the decoding problem. A family of provably fast decoding algorithms can be derived from the basic techniques underlying the framework and we present a few illustrations. Our first algorithm is a provably linear time search algorithm. We use this algorithm as a subroutine in the other algorithms. We believe that decoding algorithms derived from our framework can be of practical significance.
Table S2 from Phase I Dose-Escalation and -Expansion Study of Telisotuzumab (ABT-700), an Anti–c-Met Antibody, in Patients with Advanced Solid Tumors (2023)

&lt;p&gt;Additional details for MET-amplified patients with one or more postbaseline tumor assessment (n=9).&lt;/p&gt;
Tumor-induced T cell tolerance in a prostate cancer model (2007)

C269 Prostate cancer is the most prevalent malignancy among American men, leading to significant mortality each year. This is in part due to a lack of effective treatments for advanced prostate cancer, highlighting the critical need for novel therapies to treat this disease. The prostate is considered an ideal organ for cancer immunotherapy, because of its non-essential nature, and because of the presence of several prostate-specific antigens that could serve as targets for an immune response. However, such therapy is limited by tolerization of CD8+ T cells in the tumor local environment, essentially abrogating an anti-tumor response. The objective of this work is to understand the interactions between CD8+ T cells and tumor cells that lead to tolerance, and to design therapies to reinvigorate the immune response. A spontaneous prostate cancer model, the TRansgenic Adenocarcinoma of the Mouse Prostate (TRAMP) model1, has been used to develop an in vivo system to explore tolerance. Tumor-induced tolerance has been characterized using TRAMP mice engineered to express the antigen SIY in their prostate tissue, TRAMP-SIY mice, coupled with T cells that recognize Kb-SIY, 2C T cells. We have demonstrated that 2C T cells are tolerized in the tumor local environment of TRAMP-SIY mice through both their inability to produce IFN-γ and their impaired cytotoxic killing functions. In vivo screens have also been used to define critical mechanisms of tolerance in this model, most notably tolerance mediated by cross-presentation. We have shown that systemic α-CD40 administration can initially overcome tolerizing mechanisms in TRAMP-SIY mice and can restore function to 2C T cells. Based on these findings, novel localized α-CD40 therapies are being rationally designed to break tolerance, while minimizing the autoimmune complications observed with systemic treatments.  1. Greenberg, N.,; DeMayo, F.; Finegold, M.; Medina, D.; Tilley, W.; Aspinall, J.; Cunha, G.; Donjacour, A.; Matusik, R.; Rosen, J.; Proc. Natl. Acad. Sci., 92, 3439-3443, 1995.
Supplementary Data from Efficient <i>In vivo</i> Priming by Vaccination with Recombinant NY-ESO-1 Protein and CpG in Antigen Naïve Prostate Cancer Patients (2023)

&lt;p&gt;Supplementary Figure S1; Supplementary Table S1.&lt;/p&gt;
Fluid-Elastic Lock-in of a Cavity Shear Layer Instability With the Modes of a Submerged Cantilevered Beam (2019)

Abstract Lock-in flow tones can occur for many different types of flow instabilities and structural-acoustic resonators at low Mach number. This paper examines the interaction between a shear layer instability generated by flow over a shallow cavity and the modes of an elastic cantilevered beam containing the cavity. A describing function model indicates that a cavity shear layer instability capable of producing lock-in with acoustic pipe resonances cannot achieve lock-in with equivalent structural beam resonances, particularly resonances of submerged structures. Fluid-elastic cavity lock-in is unlikely to occur due to the high level of damping that exists for a submerged structure, the high fluid-loaded modal mass, and the relatively weak source strength a cavity generates. Limited experimentation using pressure, acceleration, and particle image velocimetry (PIV) measurements has been performed which are consistent with the describing function model. A stronger source produced by a larger scale flow instability—separated flow over a bluff body—was able to lock-in with modes of the same submerged structure, further demonstrating that the concern for lock-in from a cavity shear layer instability is isolated to systems capable of stronger coupling or those dominated by fluid-acoustic resonances.
An optical-carry, look-ahead adder based on a content-addressable memory (1990)

We will discuss a new optical parallel- arithmetic processing scheme that uses a nonholographic optoelectronic content-addressable memory (CAM). To increase the processing speed, a carry look-ahead addition (CLA) scheme can be used. We will also present the design of a 4-bit CAM-based optical-carry look-ahead adder, as well as our experimental results.
Preparation and Characterization of PLGA Scaffold Impregnated Keratin for Tissue Engineering Application (2008)

Keratin is the major structural fibrous protein providing outer covering such as wool, hair, and nail. Keratin is useful as natural protein. We developed the keratin loaded poly(L-lactide-co-glycolide) (PLGA) scaffolds (keratin/PLGA) for the possibility of the application of the tissue engineering using bone marrow mesenchymal (BMSCs). Keratin/PLGA (contents 0%, 10%, 20% and 50% of PLGA weight) scaffolds were prepared by solvent casting/salt leaching method. We characterized porosity, wettability, and water uptake ability, DSC of keratin/PLGA scaffold. We seeded BMSCs isolated from the femurs of rat into the inner core of the hybrid scaffold. Celluar viability were assayed by 3- (4,5-dimethylthiazol-2-yl) -2,5-diphenyl-tetrazolium bromide (MTT) test. We confirmed that keratin/PLGA scaffold is hydrophilic by wettability, and water uptake ability measurement results. In MTT assay results, cell viability in scaffolds impregnated 10 and 20 wt% of keratin were higher than other scaffolds. In conclusion, we suggest that keratin/PLGA scaffold may be useful to tissue engineering using BMSCs.
MicroRNA-Based Classification of Hepatocellular Carcinoma and Oncogenic Role of miR-517a (2011)

We propose miRNA-based classification of 3 subclasses of HCC. Among the proliferation class, miR-517a is an oncogenic miRNA that promotes tumor progression. There is rationale for developing therapies that target miR-517a for patients with HCC.
Efficient lattice rescoring using recurrent neural network language models (2014)

Recurrent neural network language models (RNNLM) have become an increasingly popular choice for state-of-the-art speech recognition systems due to their inherently strong generalization performance. As these models use a vector representation of complete history contexts, RNNLMs are normally used to rescore N-best lists. Motivated by their intrinsic characteristics, two novel lattice rescoring methods for RNNLMs are investigated in this paper. The first uses an n-gram style clustering of history contexts. The second approach directly exploits the distance measure between hidden history vectors. Both methods produced 1-best performance comparable with a 10k-best rescoring baseline RNNLM system on a large vocabulary conversational telephone speech recognition task. Significant lattice size compression of over 70% and consistent improvements after confusion network (CN) decoding were also obtained over the N-best rescoring approach.
Morphology and grafting in polybutylacrylate‐polystyrene core‐shell emulsion polymerization (1983)

Abstract The morphology of polybutylacrylate–polystyrene (PBA–PS) core‐shell latex particles prepared by seeded emulsion polymerization was investigated as a function of the addition method of styrene (St). The thin layer chromatography/flame ionization detector (TLC–FID) technique was used to characterize the morphology of the core‐shell latexes. It was found that grafting PS to the PBA core occurs during seeded emulsion polymerization. The percentage of grafting depended on the method of addition of St, being greatest for the batch reaction, less for the preswollen batch reaction, and least for the semibatch reaction. Upon aging the PBA core‐polymer migrated out of the latex particles with a low degree of grafting to form dumbellshaped particles, whereas the PBA–PS core‐shell particles with a high degree of grafting remained spherical because of the emulsifying ability of graft copolymer.
Deposition of the MoSe<inf>2</inf> ethanol dispersions on tapered fiber (2016)

The method of Ethanol catalytic deposition (ECD) had been proposed and demonstrated in the deposition of MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> on the tapered fiber. ECD method can significantly improve the velocity and the efficiency of deposition. In our work, we used the ECD method to deposit the two-dimensional (2D) MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> materials to prove that the ECD method can be applied to many similar 2D materials. Also, we compared the ECD method to the conventional optical driven deposition using water and organic solvent and verified the effectiveness of ECD method. One of the influential factors, i.e., injected optical power was also discussed.
Active Learning with Unsupervised Ensembles of Classifiers (2020)

The present work introduces a simple scheme for active classification of data using unsupervised ensembles of classifiers. Uncertainty sampling, with different uncertainty measures, is evaluated for data selection, while an online expectation maximization algorithm is derived to estimate model parameters on-the-fly. Preliminary tests on real data showcase the potential of the novel approach.