gebhart/patrepeval huggingface dataset:
Stiffness Estimation in Single Degree of Freedom Mechanisms using Regression (2021)

This paper leverages machine learning principles in combination with an exploratory procedure to estimate the unknown stiffness of a grasped object in a single degree of freedom gripper mechanism. The object stiffness is estimated using regression; sensor measurements of actuator position and actuator current are the regressor inputs, and object stiffness is the regressor output. The proposed approach reduces overall system complexity and cost compared to systems that use tactile sensors to estimate object stiffness. Several datasets are generated using a physics-based simulation model of the system. Regressors are trained on data produced by the simulation model, and their performance is analyzed under variations on simulation model parameters including stick-slip friction parameters; the influence of the actuation command signal used to direct the exploratory procedure is also considered. These regressors are then experimentally evaluated on a representative single degree of freedom mechanism, demonstrating worst-case stiffness estimation errors (based on datasheet spring stiffness values) of 3.4%.
Coordinated multipoint transmission/reception techniques for LTE-advanced [Coordinated and Distributed MIMO (2010)

This article presents an elaborate coordination technique among multiple cell sites called coordinated multipoint transmission and reception in the Third Generation Partnership Project for LTE-Advanced. After addressing major radio access techniques in the LTE Release 8 specifications, system requirements and applied radio access techniques that satisfy the requirements for LTE-Advanced are described including CoMP transmission and reception. Then CoMP transmission and reception schemes and the related radio interface, which were agreed upon or are currently being discussed in the 3GPP, are presented. Finally, system-level simulation evaluations show that the CoMP transmission and reception schemes have a significant effect in terms of improving the cell edge user throughput based on LTE-Advanced simulation conditions.
570 Blockade of the inhibitory collagen receptor LAIR-1, PD-L1, and TGF-β promotes anti-tumor activity through T cell activation and myeloid cell polarization (2021)

<h3>Background</h3> Leukocyte-associated immunoglobulin-like receptor 1 (LAIR-1) is an immune inhibitory receptor that binds collagen-like domains commonly found in extracellular matrix (ECM) collagens and complement component C1q. LAIR-1 is expressed on several immune cell types including activated T cells, B cells, NK cells, dendritic cells, and macrophages. Numerous cancer types including gastric, colon, ovarian, bladder, and others, upregulate collagens which enhances tumor growth, metastases, and invasion while actively suppressing antitumor immunity. While a soluble decoy, LAIR-2, is expressed in humans and competes with LAIR-1 for binding of collagen domains, excess LAIR ligands in the tumor often result in an immune suppressive environment. <h3>Methods</h3> Here, we report on a novel immunotherapy approach combining NC410, a novel fusion protein consisting of two LAIR-2 molecules grafted on to an IgG1 antibody backbone, capable of targeting the tumor ECM and blocking LAIR-1 signaling; and bintrafusp alfa, a first-in-class bifunctional fusion protein composed of the extracellular domain of the human transforming growth factor β receptor II (TGF-βRII or TGF-β ”trap”) fused via a flexible linker to the C-terminus of each heavy chain of an IgG1 antibody blocking programmed death ligand 1 (anti–PD-L1). <h3>Results</h3> We have demonstrated that the combination of NC410 and bintrafusp alfa more effectively controls in vivo tumor growth of the collagen rich MC38 colon and EMT6 mammary carcinomas compared to either monotherapy. We demonstrate that this potent anti-tumor immune response is propagated through the synergy of activated tumor infiltrating lymphocytes and a repolarization of myeloid cells in the tumor microenvironment. MC38 tumors treated with the combination of NC410 plus bintrafusp alfa contained higher numbers of infiltrating T cells, NK cells, and M1 polarized macrophages. <h3>Conclusions</h3> This study highlights the synergy of reshaping the large suppressive myeloid cell populations often present in tumors with activation of adaptive T-cell immune responses dampened by checkpoint inhibition. The results also provide the rationale for the future evaluation of this combination therapy in the clinic.
Activation of Human NK Cells by Staphylococci and Lactobacilli Requires Cell Contact-Dependent Costimulation by Autologous Monocytes (2002)

NK cells are instrumental in innate immune responses, in particular for the early production of gamma interferon (IFN-gamma) and other cytokines necessary to control certain bacterial, parasitic, and viral infections. NK cell-mediated effector functions are controlled by a fine balance between distinct receptors mediating activating and inhibitory signals; however, little is known about activating receptors on NK cells and their corresponding ligands. Several studies have shown that commensal lactobacilli isolated from the human gastrointestinal tract activate human mononuclear cells and are potent inducers of IFN-gamma and monocyte-derived interleukin 12 (IL-12). NK cell activation was shown for Lactobacillus johnsonii La1. In this study the cellular mechanisms of in vitro NK cell activation by gram-positive bacteria were analyzed. Staphylococcus aureus- and L. johnsonii La1-mediated activation of CD3(-) CD16(+) CD56(+) human peripheral blood NK cells, including expression of the activation antigen CD69 and secretion of IFN-gamma, required cell contact-dependent costimulation by autologous monocytes. S. aureus- and L. johnsonii-preactivated monocytes retained their capacity to induce NK cell activation. In contrast, cytokine-primed monocytes completely failed to induce NK cell activation unless bacteria were present. This suggests that phagocytosis of bacteria provided additional coactivation signals on accessory cells that may differ from those induced by tumor necrosis factor and IFN-gamma. Blocking of costimulatory molecules by B7.1, B7.2, and IL-12 but not CD14 monoclonal antibodies inhibited S. aureus- and L. johnsonii-induced effector function of NK cells. Our data suggest an important role for accessory cell-derived signals in the process of NK cell activation by gram-positive bacteria.
A comprehensive study on identification of risk factors for fatal pedestrian crashes at urban intersections in a developing country (2020)

Pedestrian safety is a major and growing problem in Indian cities. The current investigation examines crash data (2011–2016) obtained from the Kolkata Police and identifies high-risk intersections for fatal pedestrian crashes in Kolkata City, India. To recognize the significant risk of fatal pedestrian crashes, a set of safety performance functions (SPFs) is developed. These SPFs are an attempt to analyze a host of risk factors ranging from road infrastructure to land use, traffic volume and operational parameters, pedestrian attributes, and the spatial characteristics of an intersection. The study findings show that high speed by approaching vehicles, high levels of pedestrian–vehicular interaction, road width, on-street parking, the absence or encroachment of a footpath, pedestrians’ perceived difficulty of crossing, distractions, signal violations, post-encroachment time, and a number of spatial features such as slum population, share of working population, and population density significantly affect the frequency of fatal crashes involving pedestrians.
Development of a synthetic single crystal diamond dosimeter for dose measurement of clinical proton beams (2017)

The scope of this work was to develop a synthetic single crystal diamond dosimeter (SCDD-Pro) for accurate relative dose measurements of clinical proton beams in water. Monte Carlo simulations were carried out based on the MCNPX code in order to investigate and reduce the dose curve perturbation caused by the SCDD-Pro. In particular, various diamond thicknesses were simulated to evaluate the influence of the active volume thickness (e <sub>AV</sub>) as well as the influence of the addition of a front silver resin (250 µm in thickness in front of the diamond crystal) on depth-dose curves. The simulations indicated that the diamond crystal alone, with a small e <sub>AV</sub> of just 5 µm, already affects the dose at Bragg peak position (Bragg peak dose) by more than 2% with respect to the Bragg peak dose deposited in water. The optimal design that resulted from the Monte Carlo simulations consists of a diamond crystal of 1 mm in width and 150 µm in thickness with the front silver resin, enclosed by a water-equivalent packaging. This design leads to a deviation between the Bragg peak dose from the full detector modeling and the Bragg peak dose deposited in water of less than 1.2%. Based on those optimizations, an SCDD-Pro prototype was built and evaluated in broad passive scattering proton beams. The experimental evaluation led to probed SCDD-Pro repeatability, dose rate dependence and linearity, that were better than 0.2%, 0.4% (in the 1.0-5.5 Gy min<sup>-1</sup> range) and 0.4% (for dose higher than 0.05 Gy), respectively. The depth-dose curves in the 90-160 MeV energy range, measured with the SCDD-Pro without applying any correction, were in good agreement with those measured using a commercial IBA PPC05 plane-parallel ionization chamber, differing by less than 1.6%. The experimental results confirmed that this SCDD-Pro is suitable for measurements with standard electrometers and that the depth-dose curve perturbation is negligible, with no energy dependence and no significant dose rate dependence.
A platform for predicting real-time service-level metrics from device statistics (2015)

Predicting performance metrics for cloud services is critical for real-time service assurance. We demonstrate a platform for estimating real-time service-level metrics. Statistical learning methods on device statistics are used to predict metrics for services running on these devices.
Applying Machine Learning for High‐Performance Named‐Entity Extraction (2000)

This paper describes a machine learning approach to building an efficient and accurate name spotting system. Finding names in free text is an important task in many text‐based applications. Most previous approaches were based on hand‐crafted modules encoding language and genre‐specific knowledge. These approaches had at least two shortcomings: They required large amounts of time and expertise to develop and were not easily portable to new languages and genres. This paper describes an extensible system that automatically combines weak evidence from different, easily available sources: parts‐of‐speech tags, dictionaries, and surface‐level syntactic information such as capitalization and punctuation. Individually, each piece of evidence is insufficient for robust name detection. However, the combination of evidence, through standard machine learning techniques, yields a system that achieves performance equivalent to the best existing hand‐crafted approaches.
Machine Learning for Integrated Quantum Photonics (2020)

Realization of integrated quantum photonics is a key step toward scalable quantum applications such as quantum computing, sensing, information processing, and quantum material metrology. To enable practical quantum photonic systems, several challenges should be addressed, including (i) the realization of deterministic, bright, and stable single-photon emission operating at THz rates and at room temperatures, (ii) on-chip integration of efficient single-photon sources, and (iii) the development of deterministic and scalable nanoassembly of quantum circuitry elements. In this Perspective, we focus on the emerging field of physics-informed machine learning (ML) quantum photonics that is envisioned to play a decisive role in addressing the above challenges. Specifically, three directions of ML-assisted quantum research are discussed: (i) rapid preselection of single single-photon sources via ML-assisted quantum measurements, (ii) hybrid ML-optimization approach for developing efficient quantum circuits elements, and (iii) ML-based frameworks for developing novel deterministic assembly of on-chip quantum emitters.
A modified constant-Q transform for audio signals (2004)

The paper proposes a new transform for musical audio signals. The new transform, so-called modified constant-Q fast filter bank (mCQFFB), yields a log-like description in the frequency domain with improved frequency response when compared to the standard DFT. The improved frequency response of the mCQFFB is achieved by interpreting the sliding-DFT (sDFT) as a multi-stage filter bank, and substituting the sDFT basic filter in this description by a higher-order filter with improved characteristics. The logarithmic spectral scale of the mCQFFB is achieved by the adequate resampling of a chosen channel filter. We also discuss implementation issues related to the mCQFFB and exemplify its application to the analysis of musical signals.
Signal Detection Scheme for MB-OFDM through Fractional Sampling (2008)

Currently, detect and avoid (DAA) techniques of UWB have been paid large attention because it has been regulated in Japan and Europe. In this paper, a novel signal detection scheme for coexistence of UWB and the 4th generation mobile communication systems is proposed. The proposed scheme makes use of multipath through fractional sampling. The probabilities of false detection and false alarm with fractional sampling in a MB-OFDM receiver are investigated. The numerical results show that the proposed scheme with fractional sampling improves the probability of false detection by about 10 times as compared to conventional schemes. The numerical results also prove that the DFT size can be reduced without increasing the probability of false detection.
Treating Uncertainties to Generate a Robust Design of Gas Turbine Disk Using L Moments and Scarce Samples Including Outliers (2018)

Uncertainties in the input variables are inevitable in any design process. As a consequence, the output responses are also uncertain. Robust design is one of the sought after approach to treat such uncertainties for controlling the variation in the output responses, while maximizing the mean performance. Variation is modeled by a measure of data spread. Often, the details of the uncertainties in the input space are not available readily and they are usually characterized from scarce sample realizations. In addition, there could also be outliers in the realizations. These will increase the error in the measure of spread of the output response. Hence, it is desirable that an approach that is insensitive to outliers but can characterize the spread of data is developed for robust design. In this work we propose using L moments to model the spread of data. The classical robust design formulation is reformulated using the second L moment (l2). The proposed approach is demonstrated on a turbine disk design with 17 design and random variables. The details of the uncertainties are not known. A DoE of 200 samples is used and at each DoE point, we propagate the uncertainties using scarce samples, which include outliers. Robust design is performed and it is shown that the proposed approach works better than the classical robust design formulation.
Sum rate approximation of zero-forcing beamforming with semi-orthogonal user selection (2010)

In this paper, we present a closed-form approximation of the average sum rate of zero-forcing (ZF) beamforming (BF) with semi-orthogonal user selection (SUS). We first derive the survival probability associated with the SUS that absolute square of the channel correlation between two users is less than the orthogo-nalization level threshold (OLT). With this result, each distribution for the number of surviving users at each iteration of the SUS and the number of streams for transmission is calculated. Secondly, the received signal power of ZF-BF is represented as a function of the elements of the upper triangular matrix from QR decomposition of the channel matrix. Thirdly, we approximate the received signal power of ZF-BF with the SUS as the maximum of scaled chi-square random variables where the scaling factor is approximated as a function of both OLT and the number of users in the system. Putting all the above derivations and order statistics together, the approximated ergodic sum rate of ZF-BF with the SUS is shown in a closed form. The simulation results verify that the approximation tightly matches with the sample average for any OLT and even for a small number of users.
Cross-Layer Optimization of Fast Video Delivery in Cache-Enabled Relaying Networks (2015)

This paper investigates the cross-layer optimization of fast video delivery and caching for minimization of the overall video delivery time in a two-hop relaying network. The half-duplex relay nodes are equipped with both a cache and a buffer which facilitate joint scheduling of fetching and delivery to exploit the channel diversity for improving the overall delivery performance. The fast delivery control is formulated as a two-stage functional non-convex optimization problem. By exploiting the underlying convex and quasi-convex structures, the problem can be solved exactly and efficiently by the developed algorithm. Simulation results show that significant caching and buffering gains can be achieved with the proposed framework, which translates into a reduction of the overall video delivery time. Besides, a trade-off between caching and buffering gains is unveiled.
Engraftment and proliferation potential of embryonic lung tissue cells in irradiated mice with emphysema (2019)

Recently, there has been increasing interest in stem cell transplantation therapy, to treat chronic respiratory diseases, using lung epithelial cells or alveolospheres derived from endogenous lung progenitor cells. However, optimal transplantation strategy of these cells has not been addressed. To gain insight into the optimization of stem cell transplantation therapy, we investigated whether lung cell engraftment potential differ among different developmental stages. After preconditioning with irradiation and elastase to induce lung damage, we infused embryonic day 15.5 (E15.5) CAG-EGFP whole lung cells, and confirmed the engraftment of epithelial cells, endothelial cells, and mesenchymal cells. The number of EGFP-positive epithelial cells increased from day 7 to 28 after infusion. Among epithelial cells derived from E13.5, E15.5, E18.5, P7, P14, and P56 mice, E15.5 cells demonstrated the most efficient engraftment. In vitro, E15.5 epithelial cells showed high proliferation potential. Transcriptome analyses of sorted epithelial cells from E13.5, E15.5, E18.5, P14, and P56 mice revealed that cell cycle and cell-cell adhesion genes were highly enriched in E15.5 epithelial cells. Our findings suggest that cell therapy for lung diseases might be most effective when epithelial cells with transcriptional traits similar to those of E15.5 epithelial cells are used.
Online expansion of large-scale data warehouses (2011)

Modern data warehouses store exceedingly large amounts of data, generally considered the crown jewels of an enterprise. The amount of data maintained in such data warehouses increases significantly over time---often at a continuous pace, e.g., by gathering additional data or retaining data for longer periods to derive additional business value, but occasionally also precipitously, e.g., when consolidating disparate data warehouses and Data Marts into a single database. Having to expand a data warehouse with 100's of TB of data by a substantial portion, e.g., 100% or more is a complex and disruptive maintenance operation as it typically involves some sort of dumping and reloading of data which requires substantial downtime. In this paper we describe the methodology and mechanisms we developed in Greenplum Database to expand large-scale data warehouses in an online fashion, i.e., without noticeable downtime. At the core of our approach is a set of robust and transactionally consistent primitives that enable efficient data movement. Special emphasis was put on usability and control that lets an administrator tailor the expansion process to specific operational characteristics via priorities and schedules. We present a number of experiments to quantify the impact of an on-going expansion on query workloads.
A prochelator peptide designed to use heterometallic cooperativity to enhance metal ion affinity (2015)

A peptide has been designed so that its chelating affinity for one type of metal ion regulates its affinity for a second, different type of metal ion. The prochelator peptide (PCP), which is a fusion of motifs evocative of calcium loops and zinc fingers, forms a 1 : 2 Zn : peptide complex at pH 7.4 that increases its affinity for Zn<sup>2+</sup> ∼3-fold in the presence of Tb<sup>3+</sup> (log <i>β</i><sub>2</sub> from 13.8 to 14.3), while the 1 : 1 luminescent complex with Tb<sup>3+</sup> is brighter, longer lived, and 20-fold tighter in the presence of Zn<sup>2+</sup> (log <i>K</i> from 6.2 to 7.5). This unique example of cooperative, heterometallic allostery in a biologically compatible construct suggests the possibility of designing conditionally active metal-binding agents that could respond to dynamic changes in cellular metal status.
Combined OCT and Fluorescence Imaging for Cancer Detection and Therapeutic Monitoring (2011)

We developed a co-registered optical coherence tomography (OCT) and fluorescence molecular imaging (FMI) system for simultaneous morphological and molecular imaging. This system enables real-time imaging of fluorescence-labeled gold nanoparticles and monitoring photothermal therapy.
Detailed immunophenotypic characterization of different major and minor subsets of peripheral blood cells in patients with paroxysmal nocturnal hemoglobinuria (2008)

The best combination of markers for the diagnostic screening of PNH would include evaluation of CD14 on monocytes and of CD16 on neutrophils, although further analysis of CD55 and CD59 expression may contain additional clinically useful information. Clear association between the genetic changes detected in the PIG-A gene in 5 of 13 cases analyzed, and the phenotypic profile of PNH cells has not been found. Additionally, an abnormally higher expression of several GPI-APs among normal residual cells from PNH patients in comparison to healthy donors was observed, suggesting that factors other than the PIG-A mutation could determine the phenotypic profile of PB cells in PNH.