gebhart/patrepeval huggingface dataset:
Joint Manifold Learning Based Distributed Sensor Fusion of Image and Radio-Frequency Data (2019)

This paper presents a joint manifold learning based distributed sensor fusion approach for image and radio frequency (RF) data. A typical scenario includes several objects (with RF emitters), which are observed by a network of platforms with Medium Wavelength Infrared (MWIR) cameras and/or RF Doppler sensors. Based on a joint manifold learning (JML) sensor fusion approach, we propose to design and implement a distributed heterogeneous data fusion approach for improved Detection, Classification, and Identification (DCI) of targets and entities in dynamic environments with constrained communications. We design and implement distributed JML using diffusion and consensus approaches. In our distributed mechanism, we first partition the JML matrices into submatrices for each platform. For every platform, these submatrices represent the mapping from the sensor data to its contribution in the final fused result. Each node processes the local measurements using submatrices and shares the results with a limited number of neighbors. A prototype is constructed from drones, onboard processing capabilities (Intel Next Unit of Computing, NUC), cameras, and radars to demonstrate the proposed distributed data fusion approach. Supportive results are achieved from field tests and compared with centralized JML framework.
Intercomputer communication architecture for a mixed redundancy distributed system (1989)

The triply redundant intercomputer network for the Advanced Information Processing System (AIPS), an architecture developed to serve as the core avionics system for a broad range of aerospace vehicles, is discussed. The AIPS intercomputer network provides a high-speed, Byzantine-fault-resilient communication service between processing sites, even in the presence of arbitrary failures of simplex and duplex processing sites on the IC network. The IC network contention poll has evolved from the Laning Poll. An analysis of the failure modes and effects and a simulation of the AIPS contention poll, demonstrate the robustness of the system.
O6.05 * ERBB2/HER2-SPECIFIC NATURAL KILLER CELLS FOR ADOPTIVE IMMUNOTHERAPY OF GLIOBLASTOMA (2014)

BACKGROUND: While EGFRvIII appears a logical target for immunotherapy, only a subpopulation of tumor cells express EGFRvIII and immune escape has been demonstrated. ErbB2 is overexpressed in a substantial proportion of glioblastomas and has been successfully utilized in immunotherapies. Natural killer (NK) cells are the first line of defense against viral infections and malignant cells. The continuously growing cytotoxic cell line NK-92 holds promise for cancer immunotherapy. Safety of infusion of high doses of NK-92 was established in previous phase I clinical trials utilizing irradiated cells to prevent permanent engraftment. METHODS: To provide NK-92 cells with pre-determined tumor-cell specificity, we generated a lentiviral second generation chimeric antigen receptor (CAR) construct (5.28.z) employing the ErbB2 (HER2)-specific scFv(FRP5) antibody fragment for target cell recognition, and human CD28-CD3 ζ as a composite signaling moiety. An ErbB2-specific single cell clone (NK-92/5.28.z) was isolated, which showed high and selective cytotoxicity towards ErbB2-expressing tumor cells of various origins in vitro. We evaluated the cytotoxicity of NK-92/5.28.z cells against a panel of glioblastoma cell lines and primary glioblastoma cultures with different levels of Erb2 expression in vitro and in vivo. RESULTS: 13 out of a total of 15 established glioblastoma cell lines and 5 out of 5 primary glioblastoma cell lines were specifically lysed by NK-92/5.28.z cells, although to varying degrees. ErbB2 expression was necessary for cytotoxicity of NK-92/5.28.z cells towards glioblastoma cells, and ectopic overexpression of ErbB2 enhanced their cytotoxicity. In subcutaneous glioblastoma xenograft models, injections of NK-92/5.28.z induced prolonged regression in NOD-scid/gamma (NSG) mice with grafts of LN-319 cells and retarded the growth of LNT-229 grafts. In an orthotopic intracranial model utilizing LN-319 cells, tumor size in mice intratumorally injected with NK-92/5.28.z cells weekly was substantially smaller compared to controls as assessed by MR imaging. Injections of NK-92/5.28.z cells also conferred an impressive advantage in symptom free survival in two independent experiments (median 73 days in controls versus 140 days in NK-92/5.28.z treated animals in experiment A, p < 0,05, and median 77 days in controls versus 163 days in NK-92/5.28.z treated animals in experiment B, p < 0,01). In preparation of a phase I trial, GMP-compliant protocols for expansion of the NK-92/5.28.z line were established. CONCLUSIONS: Adoptive immunotherapy with application of ErbB2-specific NK-92/5.28.z cells may be a promising new immunotherapy approach for ErB2 positive glioblastoma. A phase I trial for glioblastoma patients with local injections of NK-92/5.28.z cells is in preparation.
Fault tolerance properties of a double phase encoding encryption technique (1997)

We investigate the robustness of an image encryption technique that uses random phase encoding in both the input plane and the Fourier plane when the encrypted image has been distorted. The distortions include different types of noise, loss of encrypted data, and the binarization of the encrypted image. It is shown that decryption transforms the noise added to the encrypted image to a wide-sense stationary additive white noise. Consequently, regardless of the type of the noise added to the encrypted image, the quality of the recovered image can be improved by processing techniques designed for filtering out additive white noise. The double-phase encryption technique distributes the input image over the entire output plane, which provides robustness to the distortions due to loss of encrypted data. Regarding the binarization, it enables easy implementation and data compression while recovering images of good quality may be possible.
Visual Font Pairing (2019)

This paper introduces the problem of automatic font pairing. Font pairing is an important design task that is difficult for novices. Given a font selection for one part of a document (e.g., header), our goal is to recommend a font to be used in another part (e.g., body) such that the two fonts used together look visually pleasing. There are three main challenges in font pairing. First, this is a fine-grained problem, in which the subtle distinctions between fonts may be important. Second, rules and conventions of font pairing given by human experts are difficult to formalize. Third, font pairing is an asymmetric problem in that the roles played by header and body fonts are not interchangeable. To address these challenges, we propose automatic font pairing through learning visual relationships from large-scale human-generated font pairs. We introduce a new database for font pairing constructed from millions of PDF documents available on the Internet. We propose two font pairing algorithms: dual-space k-NN and asymmetric similarity metric learning (ASML). These two methods automatically learn fine-grained relationships from large-scale data. We also investigate several baseline methods based on the rules from professional designers. Experiments and user studies demonstrate the effectiveness of our proposed dataset and methods.
Optical Stimulation of the Central Nervous System In Vitro (2008)

Optical stimulation in the central nervous system could potentially provide less invasive techniques for procedures involving stimulation of neurons in Neurosurgery. Optical stimulation of the thalamocortical brain slice model indicated a frequency and wavelength dependence.
Design and simulation of advanced surface micromachined micromirror devices for telescope adaptive optics applictions (1998)

This paper describes the design, fabrication, modeling, surface characterization, and simulation of advanced surface micromachined micromirror devices that are optimized for adaptive optics applications. Design considerations and fabrication capabilities are presented. Simulation of adaptive optics performance of unique Flexure-Beam and Axial-Rotation Micromirror devices is performed for many common aberrations. These devices are fabricated in the state-of-the-art four-level planarized polysilicon process available at Sandia National Laboratories known as the Sandia Ultra-planar Multi-level planarized MEMS Technology. This enabling process permits the development of micromirror devices with near-ideal characteristics that have previously been unrealizable in standard three-layer polysilicon processes. This paper describes such characteristics as elevated address electrodes, array wiring techniques, planarized mirror surfaces using chemical mechanical polishing, unique post-process metallization, and the best active surface area to date.
Chromate-free corrosion resistant conversion coatings for aluminum alloys (1995)

Inorganic polycrystalline hydrotalcite, Li{sub 2}[Al{sub 2}(OH){sub 6}]{sub 2}{center_dot}CO{sub 3}{center_dot}3H{sub 2}O, coatings can be formed on aluminum and aluminum alloys by exposure to alkaline lithium carbonate solutions. This process is conducted using methods similar to traditional chromate conversion coating procedures, but does not use or produce toxic chemicals. The coating provides anodic protection and delays the onset of pitting during anodic polarization. Cathodic reactions are also inhibited which may also contribute to corrosion protection. Recent studies have shown that corrosion resistance can be increased by sealing hydrotalcite coated surfaces to transition metal salt solutions including Ce(NO{sub 3}){sub 3}, KMnO{sub 4} and Na{sub 2}MoO{sub 4}. Results from these studies are also reported.
Coordinated Look-Ahead Scheduling for Real-Time Traffic Signal Control (Extended Abstract) (2012)

We take an agent-based approach to real-time trac signal control based on coordinated look-ahead scheduling. At each decision point, each agent constructs a schedule that optimizes movement of the currently approaching trac through its intersection. For strengthening its local view, each agent queries the scheduled outows from its direct upstream neighbors to obtain an optimistic observation, which is capable of incorporating non-local impacts from indirect neighbors. We summarize results on a road network of tightly-coupled intersections that demonstrate the ability of our approach. 1
Duplication, divergence and persistence in the Phytochrome photoreceptor gene family of cottons (Gossypium spp.) (2010)

Detailed sequence analysis suggests that phytochrome genes retained after duplication by segmental duplication and allopolyploidy appear to be evolving independently under a birth-and-death-process with strong purifying selection. Our study provides a preliminary phytochrome gene inventory that is necessary and sufficient for further characterization of the biological functions of each of the cotton phytochrome genes, and for the development of 'candidate gene' markers that are potentially useful for cotton improvement via modern marker-assisted selection strategies.
Panel Packaging Approach to Micro Thin-film Battery Sealing for Healthcare and Internet of Things (IoT) Applications (2020)

In this work, a panel packaging approach based on programmable laser milling, injection molded soldering (IMS), and temporary handling technologies has been proposed and demonstrated for micro thin-film-battery (TFB) cells. Micro TFB cells in the dimensions of 2.5mm × 2.5mm × 0.1mm have been successfully packaged and sealed with overmolding solder.
Nonlinear Hebbian Learning for noise-independent vehicle sound recognition (2008)

In this paper we propose using a new approach, a nonlinear Hebbian learning, to implement acoustic signature recognition of running vehicles. The proposed learning rule processes both time and frequency components of input data. The spectral analysis is realized using auditory gammatone filterbanks. The gammatone-filtered feature vectors are then assembled over multiple temporal frames to establish a high-dimensional spectro-temporal representation (STR). With the exact acoustic signature of running vehicles being unknown, a nonlinear Hebbian learning (NHL) rule is employed to extract representative independent features from the spectro-temporal ones and to reduce the dimensionality of the feature space. During learning, synaptic weights between input and output neurons are adaptively learned. Motivated by neurobiological synaptic transmission in the brain, one specific nonlinear activation function, which can represent multiple independent neural signaling pathways, is proposed to process nonlinear Hebbian learning. It is shown that this function satisfies the requirements of the activation function in nonlinear neural learning, and that its derivative matches the implicit distribution of vehicle sounds, thus leading to a statistically optimal learning. Simulation results show that both STR and NHL can accurately extract critical features from original input data. The proposed model achieves better performance under noisy environments than its counterparts. For additive white Gaussian noise and common colored noise, the proposed model demonstrates excellent robustness. It can decrease the error rate to 3% with improvement 21 ~ 34% at signal-to-noise ratio (SNR)= 0 dB, and can function efficiently with error rate 7 ~ 8% at low SNR=-6 dB when its counterparts cannot work properly at this situation. To summarize, this study not only provides an efficient way to capture important features from high-dimensional input signals but also offers robustness against severe background noise.
Context-aware unified communication (2004)

Enabling people-to-people interaction across heterogeneous communication end-points enhances user experience and fosters people collaboration. This paper presents the design and implementation of a unified communication system, dubbed Mercury, that allows a user to interact with others using the most convenient device at the time. Mercury supports both two-way conversation and one-way messaging. It leverages the Session Initiation Protocol to manage communication sessions and exploits dynamic user context to proactively route and migrate calls. It allows for subscription to other users' unified reachability status and provides a soft ring feature via universal notification. Mercury has an extensible architecture that allows new device types to be easily incorporated into the system. Our prototype implementation integrates a variety of devices: telephones, Sametime instant messaging clients, email, and pagers.
Types for safe locking (2006)

This article presents a static race-detection analysis for multithreaded shared-memory programs, focusing on the Java programming language. The analysis is based on a type system that captures many common synchronization patterns. It supports classes with internal synchronization, classes that require client-side synchronization, and thread-local classes. In order to demonstrate the effectiveness of the type system, we have implemented it in a checker and applied it to over 40,000 lines of hand-annotated Java code. We found a number of race conditions in the standard Java libraries and other test programs. The checker required fewer than 20 additional type annotations per 1,000 lines of code. This article also describes two improvements that facilitate checking much larger programs: an algorithm for annotation inference and a user interface that clarifies warnings generated by the checker. These extensions have enabled us to use the checker for identifying race conditions in large-scale software systems with up to 500,000 lines of code.
A Wave‐Based Approach to Adaptively Control Self‐Excited Vibrations in Drill‐Strings (2010)

Abstract Due to their small diameter‐to‐length‐ratio, drill‐strings are vulnerable to torsional vibrations. Moreover, the string is exposed to unknown or uncertain time‐variant and nonlinear loads (e.g. friction with falling friction characteristics, contact with the borehole, differential sticking), which can result in severe torsional vibrations and stick‐slip. The control law for the boundary controller at the top drive of the string needs to adapt to those unknown loads in order to stabilize the vibrations. The torsional vibrations of a drill‐string are governed by the wave equation. Analytical solutions and control laws are often based on a separation of the dynamics into a time‐ and a space‐dependent part (modal representation). Here, we decompose the vibrations into two traveling waves according to the D'Alembert solution, using only few measurements along the string. The wave which travels up the string is then compensated by the actuator at the top drive. With this compensation, the upward‐traveling wave is no longer reflected back into the string and vibration energy is absorbed, thus stabilizing the torsional vibrations. (© 2010 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Nonredundant Single-Gimbaled Control Moment Gyroscopes (2012)

Abstract : Two objectives dominate consideration of control moment gyroscopes for spacecraft maneuvers: high torque (equivalently momentum) and singularity-free operations. This paper adds to the significant body of research toward these two goals using a minimal three-control-moment-gyroscope array to provide significant singularity-free momentum performance increase spherically (in all directions) by modification of control-moment-gyroscope skew angles, compared with the ubiquitous pyramid geometry skewed at 54.73 deg. Spherical 1H (one control moment gyroscope s worth momentum) singularity-free momentum is established with bidirectional 1H and 2H in the third direction in a baseline configuration. Next, momentum space reshaping is shown via mixed skew angles permitting orientation of maximum singularity-free angular momentum into the desired direction of maneuver (yaw in this study). Finally, a decoupled gimbal angle calculation technique is shown to avoid loss of attitude control associated with singular matrix inversion. This technique permits 3H (maximal) yaw maneuvers without loss of attitude control despite passing through singularity. These claims are demonstrated analytically, then heuristically, and finally validated experimentally.
<title>Wide area mobile communication networks with multiple routing mode options</title> (1995)

A wide area mobile communication network with multiple modes of transmission routing is described. This is achieved through the integration of multiple, independent wide area networks at both the fixed base station and the mobile device. Through this network, mobile communication devices have access to multiple rf transmission paths with varying characteristics of signal strength, coverage, data rates and cost. Thereby, a composite network is synthesized, combining the best features of each subnetwork.
Plasmonic PHOLEDs: increasing OLED stability (2022)

A novel organic light emitting device intentionally couples emitter energy to the plasmon mode for increased device stability and converts plasmons to photons to improve device efficiency.
Recent advances in organic thermally activated delayed fluorescence materials (2017)

Organic materials that exhibit thermally activated delayed fluorescence (TADF) are an attractive class of functional materials that have witnessed a booming development in recent years. Since Adachi et al. reported high-performance TADF-OLED devices in 2012, there have been many reports regarding the design and synthesis of new TADF luminogens, which have various molecular structures and are used for different applications. In this review, we summarize and discuss the latest progress concerning this rapidly developing research field, in which the majority of the reported TADF systems are discussed, along with their derived structure-property relationships, TADF mechanisms and applications. We hope that such a review provides a clear outlook of these novel functional materials for a broad range of scientists within different disciplinary areas and attracts more researchers to devote themselves to this interesting research field.
Insights for data reduction in primary storage (2012)

There has been increasing interest in deploying data reduction techniques in primary storage systems. This paper analyzes large datasets in four typical enterprise data environments to find patterns that can suggest good design choices for such systems. The overall data reduction opportunity is evaluated for deduplication and compression, separately and combined, then in-depth analysis is presented focusing on frequency, clustering and other patterns in the collected data. The results suggest ways to enhance performance and reduce resource requirements and system cost while maintaining data reduction effectiveness. These techniques include deciding which files to compress based on file type and size, using duplication affinity to guide deployment decisions, and optimizing the detection and mapping of duplicate content adaptively when large segments account for most of the opportunity.
VO2-based ultra-reconfigurable intelligent reflective surface for 5G applications (2022)

As demand for higher capacity wireless communications increases, new approaches are needed to improve capacity. The lack of configurable radio platforms and power consumed to create new signals are some of the limitations preventing further advancements. To address these limitations, we propose an Ultra-Reconfigurable Intelligent Surface (URIS) platform based on the metal-to-insulator transition property of VO<sub>2</sub>. A VO<sub>2</sub> layer is placed on a high-density micro-heater matrix consisting of pixels that can be electronically switched on. With this manner of control, heat can be transferred to selected areas of the VO<sub>2</sub> layer and convert it to highly conductive metallic phase. This technique allows dynamically changing the shape of the reflection surface with high speed. We numerically investigated the heat activated switching and RF reflection characteristics of a reflectarray designed for potential 5G applications operating at 32 GHz. It consists of heating pixels with the size of 40 × 40 μm which can generate metallic VO<sub>2</sub> patches or arbitrary shapes with ~ 100 × 100 μm spatial resolution. Our analyses resulted in large phase range of ~ 300° and approximate losses of -2 dB. The proposed device can serve as a novel platform for ultra-reconfigurable reflectarrays, other IRSs, and various wide spectral range RF applications.
Notice of Retraction: Eliminating RSARP Reporting Errors in the RTS Method for MIMO OTA Test (2017)

Retracted.
Curcumin for the Treatment of Glioblastoma. (2015)

Glioblastoma multiforme is a highly aggressive primary cancer of the brain associated with a poor prognosis. Modest increases in survival can sometimes be achieved with the use of temozolomide and radiation therapy after surgery, but second-line therapy after recurrence has a limited efficacy. Curcumin has demonstrated promising results against this form of cancer in experimental models. The reported activity of curcumin against cancer stem cells, a major cause of glioblastoma resistance to therapy, and its ability to augment the apoptotic effects of ceramides, suggest it would have a synergistic effect with cytotoxic chemotherapy agents currently used in second-line therapy, such as lomustine.