gebhart/patrepeval huggingface dataset:
A Realization of Multilateral Force Feedback Control for Cooperative Motion (2007)

This paper proposes a novel control design for multilateral system considering different degrees of freedom (DOF) and structure. The conventional coordinate transformation with respect to the Cartesian coordinate system is not always suitable for bilateral and/or multilateral control for dexterous tasks, including grasping motion. This paper introduces spatial mode transformation, which is corresponding to human's tasks. The spatial modes are abstracted by using mode quarry matrices. The order of the mode quarry matrices means the task DOF, and the decoupled modes correspond to ldquotranslational task,rdquo ldquorotating task,rdquo ldquograsping task,rdquo and so on. Thus, the problems for motion integration of different DOF and structure are solved to design a multilateral controller in the spatial mode coordinate systems. Furthermore, the proposed multilateral control is designed based on acceleration control to realize both the force servoing and the position regulator for action-reaction law in remote environment simultaneously. The proposed multilateral control is applied for a multimaster/single-slave system, where the DOF is different from each other. As a result, a complicated task for the slave system is easily realized by two master systems with vivid force feedback based on modal control design of the multilateral system. The experimental results show viability of the proposed method.
Activin A expression regulates multipotency of mesenchymal progenitor cells (2010)

This comparative analysis of MPCs from different tissue sources also identifies bone marrow-derived MPCs as the most potent MPCs in terms of multilineage differentiation and immunosuppression, two key requirements in cell-based regenerative medicine. In addition, this study implicates the significance of activin A as a functional marker of MPC identity.
Inverse halftoning by decision tree learning (2004)

Inverse halftoning is the process to retrieve a (gray) continuous-tone image from a halftone. Recently, machine-learning-based inverse halftoning techniques have been proposed. Decision-tree learning has been applied with success to various machine-learning applications for quite some time. In this paper, we propose to use decision-tree learning to solve the inverse halftoning problem. This allows us to reuse a number of algorithms already developed. Especially, the maximization of entropy gain is a powerful idea that makes the learning algorithm to automatically select the ideal window as the decision-tree is constructed. The new technique has generated gray images with PSNR numbers, which are several dB above those previously reported in the literature. Moreover, it possesses very fast implementation, lending itself useful for real time applications.
Phase Noise Estimation in OFDM: Utilizing Its Associated Spectral Geometry (2015)

In this paper, we develop frequency-domain phase noise estimation schemes for an orthogonal frequency division multiplexing (OFDM) system that utilize the geometrical structure associated with the spectral components of the complex exponential of the phase noise process. This geometry can be expressed as a set of non-convex quadratic equality constraints that involve permutation matrices. Since the oscillator power spectral density is typically a low-pass process, we can reduce the dimensionality of the phase noise spectral vector. In particular, we propose a new dimensionality reduction model that preserves the phase noise spectral geometry when moving from smaller to larger dimensional spaces. Using this new model and building upon existing works, the phase noise estimation problem is posed as an optimization problem. We show, using the S-procedure, that the optimization problem has an optimal solution that is attained and can be solved using semidefinite programming. In order to reduce the computational complexity of the aforementioned optimization problem, we consider sub-optimal schemes that provide an estimate satisfying this geometry. Through numerical simulations, we demonstrate superior bit-error-rate performance when the proposed model used in conjunction with the phase noise spectral geometry is incorporated in the estimation process.
Biosilicification of loricate choanoflagellate: organic composition of the nanotubular siliceous costal strips of Stephanoeca diplocostata (2010)

Loricate choanoflagellates (unicellular, eukaryotic flagellates; phylum Choanozoa) synthesize a basket-like siliceous lorica reinforced by costal strips (diameter of approximately 100 nm and length of 3 μm). In the present study, the composition of these siliceous costal strips is described, using Stephanoeca diplocostata as a model. Analyses by energy-dispersive X-ray spectroscopy (EDX), coupled with transmission electron microscopy (TEM), indicate that the costal strips comprise inorganic and organic components. The organic, proteinaceous scaffold contained one major polypeptide of mass 14 kDa that reacted with wheat germ agglutinin. Polyclonal antibodies were raised that allowed mapping of the proteinaceous scaffold, the (glyco)proteins, within the costal strips. Subsequent in vitro studies revealed that the organic scaffold of the costal strips stimulates polycondensation of ortho-silicic acid in a concentration- and pH-dependent way. Taken together, the data gathered indicate that the siliceous costal strips are formed around a proteinaceous scaffold that supports and maintains biosilicification. A scheme is given that outlines that the organic template guides both the axial and the lateral growth of the strips.
Sodium bicarbonate cotransporter NBCe2 gene variants increase sodium and bicarbonate transport in human renal proximal tubule cells (2018)

NBCe2 activity is stimulated by an increase in intracellular sodium and is hyper-responsive in hRPTCs carrying HV SLC4A5 rs7571842 through an aberrant HNF4A-mediated mechanism.
The implementation of novel idea of translation matrix to maintain QoS for a roaming user between heterogeneous 4G wireless networks (2012)

The heterogeneous mixture of 4G wireless networks brings together many different interconnecting wireless IP domains, each following different QoS models thus complicating the overall end-to-end QoS process. The target of end-to-end QoS provisioning in wireless Internet has become even more challenging because of the combination of different types of end-user traffic requiring different QoS performance characteristics. Further, we can witness these days that mobile terminals are having the capability to access many of these wireless network types at the same time. The networks are very different in terms of delay, jitter and data rate. As terminals move between different access networks it becomes an important issue how to map resource reservations between different networks in order to maintain QoS behavior. In this paper, we present a novel mechanism for achieving service continuity through a Translation Matrix, which maps QoS parameters between different access networks. Each network maintains matrices corresponding to the traffic behavior of the different available traffic classes. The matrices are then used to compare existing flow parameters to possible new reservation classes as the terminal changes network access. In addition to presenting the mechanism, in this paper we detail the steps to construct the matrices. The construction of matrices are based on modeling the behavior of multiple classes of 4G traffic passing through different kinds of wireless IP domains implemented with different queuing and scheduling combinations.
Enzymatic properties of Staphylococcus aureus adenosine synthase (AdsA) (2011)

Collectively, these results provide insight into the unique ability of AdsA to produce adenosine through the consecutive hydrolysis of ATP, ADP and AMP, thereby endowing S. aureus with the ability to modulate host immune responses.
A Hard Look at Cardiac Safety with Dopamine Agonists in Endocrinology (2021)

peer reviewed
Identification of Hydroxybenzoic Acids as Selective Lactate Receptor (GPR81) Agonists with Antilipolytic Effects (2012)

Following the characterization of the lactate receptor (GPR81), a focused screening effort afforded 3-hydroxybenzoic acid 1 as a weak agonist of both GPR81 and GPR109a (niacin receptor). An examination of structurally similar arylhydroxy acids led to the identification of 3-chloro-5-hydroxybenzoic acid 2, a selective GPR81 agonist that exhibited favorable in vivo effects on lipolysis in a mouse model of obesity.
Robust adaptive control of the mold level in the continuous casting process using multiple models (2010)

In the continuous casting of steel, mold level control is fundamental for obtaining high productivity and high quality. Using conventional methods, it is difficult to achieve both stability and performance robustness because of different classes of disturbances and parameters uncertainties in the process. This paper presents a multi-model adaptive control architecture based on the so-called RMMAC methodology. With the help of precise definition of robust performance requirements, the number of models, estimators and controllers are merely derived. More importantly, the combination of robust non-adaptive mixed-μ synthesis and stochastic hypothesis testing concepts enables controller performances prediction as well as online monitoring process parameters which could be used by operators to take corrective actions. The generated signals are likewise useful for understanding the physical phenomena in the process.
Improvement of Thermal Conductivity of Poly(dimethyl siloxane) Composites Filled with Boron Nitride and Carbon Nanotubes (2013)

Poly(dimethyl siloxane)(PDMS, 실리콘 고무)의 열전도도 향상을 위하여 보론 나이트라이드과 탄소나노튜브를 열전도성 충전제로 사용하였다. 보론 나이트라이드의 함량은 0에서 100 phr로 증가시켰으며, 탄소나노튜브의 함량은 보론 나이트라이드의 함량을 100 phr로 고정시킨 상태에서 0에서 4 phr로 증가시켰다. 실리콘 고무 복합재료의 열전도도는 보론 나이트라이드 함량의 증가에 따라 증가하였으나, 탄소나노튜브를 추가로 첨가하더라도 열전도도 향상에 대한 효과는 미미하였다. 100 phr 함량의 보론 나이트라이드 함량에 탄소나노튜브를 충전 시 복합재료의 열분해가 가속화되는 예상치 못한 결과를 얻었다. 이를 해석하기 위하여 Horowitz-Metzger 방법을 이용하여 열분해 활성화 에너지를 계산하였다. 또한 보론 나이트라이드/탄소나노튜브가 충전된 실리콘 고무 복합재료의 경화거동, 전기저항 및 기계적 물성을 연구하였다. In order to enhance the thermal conductivity of poly(dimethyl siloxane) (PDMS), boron nitride (BN) and carbon nanotubes (CNTs) were incorporated as the thermally conductive fillers. The amount of BN was increased from 0 to 100 phr (parts per hundred rubber) and the amount of CNTs was increased from 0 to 4 phr at a fixed amount of the boron nitride (100 phr). The thermal conductivity of the composites increased with an increasing concentration of BN, but the incorporation of CNTs had only a slight effect on the enhancement of thermal conductivity. Unexpectedly, the thermal degradation of the composites was accelerated by the addition of CNTs in 100 phr BN filled PDMS. Activation energy for thermal decomposition of the composites was calculated using the Horowitz-Metzger method. The curing behavior, electrical resistivity, and mechanical properties of PDMS filled with BN and CNTs were investigated.
ASSESSMENT OF FLUORESCEIN ANGIOGRAPHY NONPERFUSION IN EYES WITH DIABETIC RETINOPATHY USING ULTRAWIDE FIELD RETINAL IMAGING (2022)

Approximately, 70% of NP in diabetic eyes is located outside the posterior pole. Increased NP is associated with the presence of FA-PPL, suggesting UWF-FA may better predict future DR worsening than UWF-color alone.
An analysis of robust cost functions for CNN in computer-aided diagnosis (2016)

Deep convolutional neural networks (CNNs) have proven to be powerful and flexible tools that advance the state-of-the-art in many fields, e.g. speech recognition, computer vision and medical imaging. Usually deep CNN models employ the logistic (soft-max) loss function in the training process of classification tasks. Recent evidence on a computer vision benchmark data-set indicates that the hinge (SVM) loss might give smaller misclassification errors on the test set compared to the logistic loss (i.e. offer better generality). In this paper, we study and compare four different loss functions for deep CNNs in the context of computer-aided abdominal and mediastinal lymph node detection and diagnosis (CAD) using CT images. Besides the logistic loss, we compare three other CNN losses that have not been previously studied for CAD problems. The experiments confirm that the logistic loss performs the worst among the four losses, and an additional 3% increase in detection rate at 3 false positives/volume can be obtained by just replacing it with Lorenz loss. The free-receiver operating characteristic curves of two of the three loss functions consistently outperform the logistic loss in testing.
Segmented channel routing (2002)

Routing channels in a field-programmable gate array contain predefined wiring segments of various lengths. These may be connected to the pins of the gates or joined end-to-end to form longer segments by programmable switches. The segmented channel routing problem is formulated, and polynomial time algorithms are given for certain special cases. The general problem is NP-complete, but it can be adequately solved in practice. Experiments indicate that a segmented channel with judiciously chosen segment lengths may near the efficiency of a conventional channel.
Cholesky decomposition using fused datapath synthesis (2009)

In this paper we present an implementation of a Cholesky decomposition core, with IEEE754 single precision arithmetic. The datapaths are generated using fused datapath synthesis, created with an experimental floating point compiler tool, capable of fitting hundreds of floating point operators into a single device. We present a scalable architecture for both real and complex matrixes, on which we will report results for up to 128x128 real matrices. The concepts of fused datapath synthesis for FPGA floating point designs will be reviewed, and the application to the Cholesky algorithm detailed. Experimental results will be given to show that the accuracy of this method is superior to those expected from a traditional IEEE754 core based design flow.
N-to-SRGB Mapping for Single-Sensor Multispectral Imaging (2015)

Visualization of a multispectral image in a standard color space, typically the sRGB space, is an important task for human color perception. When we reproduce the sRGB image from the multispectral image with N spectral bands, an N-to-sRGB mapping is required. The challenge of the N-to-sRGB mapping in single-sensor multispectral imaging with a multispectral filter array (MSFA) is to reduce demosaicking error amplification and propagation across different spectral bands, which are not trivial because of very sparse sampling of multiple spectral bands in a single image sensor. In this paper, we propose a novel N-to-sRGB mapping pipeline for effectively suppressing the demosaicking error amplification and propagation. Our idea is to apply guided filtering in the mapped sRGB space using one of input N band images before the amplification and propagation as a guide image. Experimental results demonstrate that our proposed pipeline improves the mapping accuracy for various MSFA types.
Organosulfonates aid argentophilic forces in the crystal engineering of [2+2] photodimerisations: reactivity involving 3-pyridyl groups (2013)

AbstractPhotoreactive Ag(I) organosulfonate complexes involving (E)-methyl-3-(pyridin-3-yl)prop-2-enoate (3-PAMe) are reported. Argentophilic interactions stack 3-PAMe to undergo a head-to-head intermolecular [2+2] photodimerisation to generate (rctt)-dimethyl-3,4-bis(pyridine-3-yl)cyclobutane-1,2-dicarboxylate (3,3′-MeBPCD) in the solid state regioselectively and in quantitative yield. The organosulfonate participates in C–H…O interactions with the coordinated 3-pyridyl groups to effectively aid in crystal engineering of the reactivity.Keywords:: supramolecular chemistry[2+2] photodimerisationcrystal engineering Additional informationFundingWe are grateful to the National Science Foundation (L.R.M., DMR-1104650) for funding.
Poor neutralization and rapid decay of antibodies to SARS-CoV-2 variants in vaccinated dialysis patients (2022)

Patients on dialysis are at risk of severe course of SARS-CoV-2 infection. Understanding the neutralizing activity and coverage of SARS-CoV-2 variants of vaccine-elicited antibodies is required to guide prophylactic and therapeutic COVID-19 interventions in this frail population. By analyzing plasma samples from 130 hemodialysis and 13 peritoneal dialysis patients after two doses of BNT162b2 or mRNA-1273 vaccines, we found that 35% of the patients had low-level or undetectable IgG antibodies to SARS-CoV-2 Spike (S). Neutralizing antibodies against the vaccine-matched SARS-CoV-2 and Delta variant were low or undetectable in 49% and 77% of patients, respectively, and were further reduced against other emerging variants. The fraction of non-responding patients was higher in SARS-CoV-2-naïve hemodialysis patients immunized with BNT162b2 (66%) than those immunized with mRNA-1273 (23%). The reduced neutralizing activity correlated with low antibody avidity. Patients followed up to 7 months after vaccination showed a rapid decay of the antibody response with an average 21- and 10-fold reduction of neutralizing antibodies to vaccine-matched SARS-CoV-2 and Delta variant, which increased the fraction of non-responders to 84% and 90%, respectively. These data indicate that dialysis patients should be prioritized for additional vaccination boosts. Nevertheless, their antibody response to SARS-CoV-2 must be continuously monitored to adopt the best prophylactic and therapeutic strategy.
Textured Beta-Sialon:Eu<sup>2+</sup> Phosphor Deposits Fabricated by Electrophoretic Deposition (EPD) Process within a Strong Magnetic Field: Preparation Process and Photoluminescence (PL) Properties Depending on Orientation (2015)

Beta-sialon:Eu 2+ phosphor deposits were fabricated by electrophoretic deposition (EPD) process within a strong magnetic field (12 T). The direction of the magnetic field was adjusted to be parallel or perpendicular to that of the electric field, that is, vertical-or horizontal setup. The oriented deposits were fabricated by aligning the β-sialon:Eu 2+ particles along the higher magnetic-susceptibility c -crystal axis ( a, b -crystal plane). For the case of vertically-setup magnetic field, the oriented deposit aligned along the c -axis possessed higher relative deposit density than the randomly fabricated deposit, as a result, varying the intensity ratio of emission and transmitted excitation, and therefore, presenting different chromaticity coordinates; for the case of horizontally-setup magnetic field, photoluminescence (PL) intensities of the deposits oriented along c -axis were significantly improved by comparing with those of the randomly-oriented ones.
Consortium-Based Science: The NIEHS’s Multipronged, Collaborative Approach to Assessing the Health Effects of Bisphenol A (2012)

NIEHS/NTP BPA research investments made over the past 4 years include extramural research grants, establishment of a BPA Grantee Consortium, intramural research activities on BPA's mechanisms of action, the launch of two clinical studies and an occupational study, development of a round-robin experiment to validate BPA measurements in human serum, and, in collaboration with the Food and Drug Administration (FDA), formation of a consortium to design and execute a chronic toxicity study of BPA in rats. The NIEHS's new consortium-based approach has led to more integrated, collaborative efforts and should improve our ability to resolve controversies over the potential human health effects of exposures to low levels of endocrine-active agents.
FGFR3-TACC3 fusion proteins act as naturally occurring drivers of tumor resistance by functionally substituting for EGFR/ERK signaling (2016)

The epidermal growth factor receptor (EGFR) is a clinically validated target in head and neck squamous cell carcinoma (HNSCC), where EGFR-blocking antibodies are approved for first-line treatment. However, as with other targeted therapies, intrinsic/acquired resistance mechanisms limit efficacy. In the FaDu HNSCC xenograft model, we show that combined blockade of EGFR and ERBB3 promotes rapid tumor regression, followed by the eventual outgrowth of resistant cells. RNA sequencing revealed that resistant cells express FGFR3-TACC3 fusion proteins, which were validated as drivers of the resistant phenotype by several approaches, including CRISPR-mediated inactivation of FGFR3-TACC3 fusion genes. Interestingly, analysis of signaling in resistant cell lines demonstrated that FGFR3-TACC3 fusion proteins promote resistance by preferentially substituting for EGFR/RAS/ERK signaling rather than ERBB3/PI3K/AKT signaling. Furthermore, although FGFR3-TACC3 fusion proteins promote resistance of additional EGFR-dependent HNSCC and lung cancer cell lines to EGFR blockade, they are unable to compensate for inhibition of PI3K signaling in PIK3CA-mutant HNSCC cell lines. Validation of FGFR3-TACC3 fusion proteins as endogenous drivers of resistance in our screen provides strong evidence that these fusions are capable of substituting for EGFR signaling. Thus, FGFR3-TACC3 fusion proteins may represent a novel mechanism of acquired resistance in EGFR-dependent cancers of multiple cell lineages.
High output power 1540 nm vertical cavity semiconductor optical amplifiers (2004)

Vertical cavity semiconductor optical amplifiers operating at 1540 nm are presented. The use of AlInGaAs multiple quantum well active regions resulted in record-high saturation output power of +0.5 dBm and 16 dB of fibre-to-fibre gain. These results were achieved in reflection mode operation using optical pumping by a 980 nm semiconductor laser.
Estimation of turbulence closure coefficients for data centers using machine learning algorithms (2012)

CFD models of data centers often use two equation turbulence models such as the k-ε model. These models are based on closure coefficients or turbulence model constants determined from a combination of scaling/dimensional analysis and experimental measurements of flows in simple configurations. The simple configurations used to derive the turbulence model constants are often two dimensional and do not have many of the complex flow characteristics found in engineering flows. Such models perform poorly, especially in flows with large pressure gradients, swirl and strong three dimensionality, as in the case of data centers. This study attempts to use machine learning algorithms to optimize the model constants of the k-ε turbulence model for a data center by comparing simulated data with experimentally measured temperature values. For a given set of turbulence constants, we determine the Root Mean Square `error' in the model, defined as the difference between experimentally measured temperature from a data center test cell and CFD calculations using the k-ε model. An artificial neural network (ANN) based method for parameter identification is then used to find the optimal values for turbulence constants such that the error is minimized. The optimum turbulence model constants obtained by our study results in lowering the RMS error by 25% and absolute average error by 35% compared to the error obtained by using standard k-ε model constants.