gebhart/patrepeval huggingface dataset:
Deep Reinforcement Learning for Economic Dispatch of Virtual Power Plant in Internet of Energy (2020)

With the high penetration of large-scale distributed renewable energy generation, the power system is facing enormous challenges in terms of the inherent uncertainty of power generation of renewable energy resources. In this regard, virtual power plants (VPPs) can play a crucial role in integrating a large number of distributed generation units (DGs) more effectively to improve the stability of the power systems. Due to the uncertainty and nonlinear characteristics of DGs, reliable economic dispatch in VPPs requires timely and reliable communication between DGs, and between the generation side and the load side. The online economic dispatch optimizes the cost of VPPs. In this article, we propose a deep reinforcement learning (DRL) algorithm for the optimal online economic dispatch strategy in VPPs. By utilizing DRL, our proposed algorithm reduced the computational complexity while also incorporating large and continuous state space due to the stochastic characteristics of distributed power generation. We further design an edge computing framework to handle the stochastic and large-state space characteristics of VPPs. The DRL-based real-time economic dispatch algorithm is executed online. We utilize real meteorological and load data to analyze and validate the performance of our proposed algorithm. The experimental results show that our proposed DRL-based algorithm can successfully learn the characteristics of DGs and industrial user demands. It can learn to choose actions to minimize the cost of VPPs. Compared with the deterministic policy gradient algorithm and DDPG, our proposed method has lower time complexity.
Bio-inspired controller for a dexterous prosthetic hand based on principal components analysis (2009)

Controlling a dexterous myoelectric prosthetic hand with many degrees of freedom (DoFs) could be a very demanding task, which requires the amputee for high concentration and ability in modulating many different muscular contraction signals. In this work a new approach to multi-DoF control is proposed, which makes use of Principal Component Analysis (PCA) to reduce the DoFs space dimensionality and allow to drive a 15 DoFs hand by means of a 2 DoFs signal. This approach has been tested and properly adapted to work onto the underactuated robotic hand named CyberHand, using mouse cursor coordinates as input signals and a principal components (PCs) matrix taken from the literature. First trials show the feasibility of performing grasps using this method. Further tests with real EMG signals are foreseen.
A planar array capacitive imaging system for detecting damage in composite structures: a numerical study (2018)

Fiber-reinforced polymer (FRP) composites are widely used in the aerospace industry, but they are also susceptible to different types of damage. In particular, impact is a serious concern, since they can cause subsurface damage that can be hidden from visual inspection and jeopardize structural safety and performance. In addition, the complex geometries of FRP components can limit the use of current nondestructive inspection techniques. Thus, the objective of this study is to develop a portable, noncontact, surface scanning tool for technicians to rapidly detect, characterize, and localize subsurface structural features and damage in structural components. The technique is centered around the theory of electrical capacitance tomography (ECT). Unlike conventional ECT, an array of noncontact electrodes is arranged in a planar fashion. Electric field is propagated between electrodes to interrogate the sensing region, which is defined as the region of space underneath the plane of electrodes. Meanwhile, the corresponding mutual capacitance between excitation and other electrodes are measured. The recorded datasets are then used as inputs to solve the ECT inverse problem in which the electrical permittivity of the 3D sensing region can be reconstructed. In this work, numerical modeling was employed to demonstrate the sensing performance of the planar array capacitive imaging system. First, several composite components with different types of damage were simulated using finite element modeling. Damage was introduced by selectively changing the electrical permittivity at different regions. Second, the planar capacitive electrode array, which was placed near the composite component, was also modeled. Electric field was propagated between different electrodes while the corresponding mutual capacitance of other electrodes were determined. The simulated data was then used as inputs to solve the ECT inverse problem. The numerical simulation results showed that the planar array capacitive imaging system was able to detect, quantify, and locate damage-induced changes in electrical permittivity distributions in composite structures, thereby demonstrating its potential for use as a nondestructive inspection tool.
Unmatched Multiblock Grids for Simulation of Geometrically Complex Reservoirs (2004)

B001 UNMATCHED MULTIBLOCK GRIDS FOR SIMULATION OF GEOMETRICALLY COMPLEX RESERVOIRS Abstract C. WOLFSTEINER 1 S.H.LEE 1 H. A. TCHELEPI 2 P. JENNY 3 and W. H. CHEN 1 (1) ChevronTexaco Energy Technology Co. (2) Stanford U. (3) ETH Zürich A simulator with hexahedral multiblock grids has been developed to simulate flow in reservoirs with geometrically complex features (i.e. faults and wells). A reservoir model can always be gridded with multiblock grids with matching grid lines between blocks. However this matching requirement may introduce many small cells that have little impact on the simulation results as well as unnecessarily increase the
Suppression of harmonic current for IPMSM using generalized repetitive control (2010)

Interior Permanent Magnet Synchronous Motors (IPMSM) are generally driven by the current control based on the vector control system. However, there exist harmonic components in the current control loop. For the harmonic current, suppression control methods using a repetitive control have been proposed. In the conventional repetitive control, the amount of memory for implementation has not been considered explicitly. Furthermore, the control parameters determined in our earlier works does not ensure an optimality. In this paper, we propose a new control method of suppressing the harmonic current using the generalized repetitive control. Compared with the conventional method, the proposed method achieves better control performance while considering the amount of memory. The effectiveness of the proposed method is verified through simulations and experiments.
Depolarization versus repolarization abnormality underlying inferolateral J-wave syndromes: New concepts in sudden cardiac death with apparently normal hearts (2018)

Early repolarization indicates a distinct electrocardiographic phenotype affecting the junction between the QRS complex and the ST segment in inferolateral leads (inferolateral J-wave syndromes). It has been considered a benign electrocardiographic variant for decades, but recent clinical studies have demonstrated its arrhythmogenicity in a small subset, supported by experimental studies showing transmural dispersion of repolarization. Here we review the current knowledge and the issues of risk stratification that limit clinical management. In addition, we report on new mapping data of patients refractory to pharmacologic treatment using high-density electrogram mapping at the time of inscription of J wave. These data demonstrate that distinct substrates, delayed depolarization, and abnormal early repolarization underlie inferolateral J-wave syndromes, with significant implications. Finally, based on these data, we propose a new simplified mechanistic classification of sudden cardiac deaths without apparent structural heart disease.
Inverted p-down pin photodiode exceeding 70-GHz bandwidth featuring low operating bias voltage of 2 V (2020)

We present a vertical-illumination pin photodiode (PD) with an inverted p-down structure, which is advantageous in fabrication, optical coupling, and dark-current suppression. The PD is designed to maximize bandwidth at low bias, resulting in 70.1-GHz bandwidth at 2 V with 0.61-A/W responsivity.
Supplementary methods, legends and Table S1 from Molecular Insights of Pathways Resulting from Two Common PIK3CA Mutations in Breast Cancer (2023)

&lt;p&gt;Additional methods, supplementary figure legend and Table S1&lt;/p&gt;
Model Distribution in Decentralized Multi-Sensor Data Fusion (1991)

This paper considers the problem of data fusion in a decentralized and distributed network of multi-sensor processing nodes. A decentralized and distributed Kalman filter is formulated. This filter needs no central processor; globally optimum estimates are obtained at each mode by requiring an underlying centrality of the state space rather than a centralized topology. Model distribution reduces the computational burden at each node by allowing each node a local model that is most appropriate to the dynamics of its observations. The combination of model distribution and decentralization yields a robust and efficient parallel processing network. The problem of communicating and assimilating relevant estimates directly between nodes with different models and state subspaces is solved using internodal transformations. The same intermodal transformations are used to relate models directly between nodes. Ralationships between the transformations and network configuration considerations are discussed.
Highly compressible fluorescent particles for pressure sensing in liquids (2017)

Pressure sensing in liquids is important for engineering applications ranging from industrial processing to naval architecture. Here, we propose a pressure sensor based on highly compressible polydimethylsiloxane foam particles embedding fluorescent Nile Red molecules. The particles display pressure sensitivities as low as 0.0018 kPa–1, which are on the same order of magnitude of sensitivities reported in commercial pressure-sensitive paints for air flows. We envision the application of the proposed sensor in particle image velocimetry toward an improved understanding of flow kinetics in liquids.
Phosphite-mediated in situ carboxyvinylation: a new general acrylic acid synthesis (1981)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTPhosphite-mediated in situ carboxyvinylation: a new general acrylic acid synthesisDavid R. BrittelliCite this: J. Org. Chem. 1981, 46, 12, 2514–2520Publication Date (Print):June 1, 1981Publication History Published online1 May 2002Published inissue 1 June 1981https://pubs.acs.org/doi/10.1021/jo00325a016https://doi.org/10.1021/jo00325a016research-articleACS PublicationsRequest reuse permissionsArticle Views983Altmetric-Citations52LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Studies towards streptonigrinoids: formal synthesis of lavendamycin methyl ester (1993)

M. A. Ciufolini and M. J. Bishop, J. Chem. Soc., Chem. Commun., 1993, 1463 DOI: 10.1039/C39930001463
In Situ Time-Resolved SAXS Study of the Formation of Mesostructured Organically Modified Silica through Modeling of Micelles Evolution during Surfactant-Templated Self-Assembly (2012)

The mechanisms of formation of organically modified (phenyl, vinyl, and methyl) silica materials with cubic Pm3n and hexagonal p6m periodic mesostructures obtained in one step in the presence of the cetyltrimethylammonium bromide (CTA(+)B) surfactant are reported in this study. Understanding the way these complex materials form is difficult but undoubtedly necessary for controlling the material structure and its properties because of the combined presence of surface organic groups and large surface areas. Here, the mechanism of formation is clarified on the basis of the modeling of time-resolved in situ small angle X-ray scattering (SAXS) experiments, with a specific focus on the micelle evolution during material formation. Their fast self-assembly is followed for the first time with a quick temporal resolution of a few seconds using a third-generation synchrotron radiation source. To better understand the behavior of the complex organic-containing mesostructure, we perform a comparative study with the corresponding organo-free, isostructural materials obtained from three different surfactants (CTA(+), CTEA(+), and CTPA(+)) having a constant chain length (C(16)) and an increasing polar head volume (met-, et-, and prop-). Numerical modeling of SAXS data was crucial to highlighting a systematic sphere-to-rod micellar transition, otherwise undetected, before the formation of the 2D hexagonal phase in both organo-free and organo-containing systems. Then, two different pathways were found in the formation of the cubic Pm3n mesostructure: either an ordering transition from concentrated flocs of spherical micelles (from CTEA(+) or CTPA(+)) for pure TEOS systems or a structural transformation from an intermediate 2D hexagonal mesophase in organosilane systems (from CTA(+)). Combining the comparison between organo-free and organo-containing systems with numerical modeling, we find that the hexagonal-to-cubic phase transition in the organically modified materials seems to be strongly influenced not only by the obvious presence of the organic group but also by the quicker and more massive condensation kinetics of silicate oligomers on the CTA(+) micellar surface. Finally, quite unexpectedly, we find a wormlike-to-sphere micellar transition in the CTPA(+) system.
Interpretable machine learning-accelerated seed treatment by nanomaterials for environmental stress alleviation (2023)

Crops are constantly challenged by different environmental conditions. Seed treatment by nanomaterials is a cost-effective and environmentally-friendly solution for environmental stress mitigation in crop plants. Here, 56 seed nanopriming treatments are used to alleviate environmental stresses in maize. Seven selected nanopriming treatments significantly increase the stress resistance index (SRI) by 13.9% and 12.6% under salinity stress and combined heat-drought stress, respectively. Metabolomics data reveals that ZnO nanopriming treatment, with the highest SRI value, mainly regulates the pathways of amino acid metabolism, secondary metabolite synthesis, carbohydrate metabolism, and translation. Understanding the mechanism of seed nanopriming is still difficult due to the variety of nanomaterials and the complexity of interactions between nanomaterials and plants. Using the nanopriming data, we present an interpretable structure-activity relationship (ISAR) approach based on interpretable machine learning for predicting and understanding its stress mitigation effects. The post hoc and model-based interpretation approaches of machine learning are combined to provide complementary benefits and give researchers or policymakers more illuminating or trustworthy results. The concentration, size, and zeta potential of nanoparticles are identified as dominant factors for correlating root dry weight under salinity stress, and their effects and interactions are explained. Additionally, a web-based interactive tool is developed for offering prediction-level interpretation and gathering more details about specific nanopriming treatments. This work offers a promising framework for accelerating the agricultural applications of nanomaterials and may profoundly contribute to nanosafety assessment.
Ionic‐Liquid‐Based Acidic Aqueous Biphasic Systems for Simultaneous Leaching and Extraction of Metallic Ions (2017)

Abstract The first instance of an acidic aqueous biphasic system (AcABS) based on tributyltetradecyl phosphonium chloride ([P 44414 ][Cl]) and an acid is here reported. This AcABS exhibits pronounced thermomorphic behavior and is shown to be applicable to the extraction of metal ions from concentrated acidic solutions. Metal ions such as cobalt(II), iron(III), platinum(IV) and nickel(II) are found to partition preferentially to one of the phases of the acidic aqueous biphasic system and it is here shown that it successfully allows the difficult separation of Co II from Ni II , here studied at 24 and 50 °C.
Synthesis and Anti‐<scp>HIV</scp> Activity of 4‐(Naphthalen‐1‐yl)‐1,2,5‐thiadiazol‐3‐hydroxyl Derivatives (2014)

A series of 4-(naphthalen-1-yl)-1,2,5-thiadiazol-3-hydroxyl derivatives (Ia-Im and IIa-IIe) designed as novel HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) was synthesized via an expeditious route and evaluated for their anti-HIV activities in MT-4 cell cultures. All the synthesized compounds were structurally confirmed by spectral analyses. Biological results showed that three analogues displayed moderate inhibitory activity against wild-type (wt) HIV-1 replication with EC(50) values ranging from 16 to 22 μm. Molecular docking of compound Ih with wt HIV-1 RT was performed to understand the binding mode between these inhibitors and the wt HIV-1 RT and to rationalize some SARs.
Inflammatory/haematopoietic cytokine production by human bone marrow adipocytes (2000)

International audience
Application of Grassmann—Cayley Algebra to Geometrical Interpretation of Parallel Robot Singularities (2009)

The aim of this paper is two—fold: first, it provides an overview of the implementation of Grassmann—Cayley algebra to the study of singularities of parallel robots1 and, second, this algebra is utilized to solve the singularity of a general class of Gough—Stewart platforms (GSPs). The Grassmann—Cayley algebra has an intuitive way of representing geometric entities and writing them and their incidence algebraically. The singularity analysis is performed using the bracket representation of the Jacobian matrix determinant associated with this algebra. This representation is a coordinate-free one, and for all cases treated and addressed in this paper, it enables the translation of the algebraic expression into a geometrically meaningful statement. The class of GSPs having two pairs of collocated joints, whose singularity is treated in this paper, is one of the more general classes. Their singularity analysis and geometrical interpretation, is presented here, to the best of our knowledge, for the first time.
Chronic neutropenia: possible association with Sjögren's syndrome. (1982)

Three white males, ages 42-59, with chronic neutropenia are described. All 3 patients had splenomegaly, positive tests for rheumatoid factor, elevated erythrocyte sedimentation rates, hypergammaglobulinemia and bone marrow examinations which showed normal to increased cellularity. Two of the 3 patients had recurring arthralgias and positive tests for antinuclear antibodies. All 3 patients had evidence for decreased tearing suggestive of Sjogren's syndrome, but in only 1 patient was a positive lip biopsy obtained. One patient had repeated cutaneous infections which ceased after splenectomy resulted in an increased neutrophil count. Serum IgG neutrophil-binding and in vivo neutrophil kinetic studies on 1 patient were consistent with a humoral immune mechanism for his neutropenia.
Clinical Analysis of Combined Hypopharyngeal Cancer and Esophageal Cancer with Esophageal Reconstruction. (1999)

Head and neck cancer has been reported to be frequently associated with cancer of the esophagus and the stomach. Esophago-gastric endoscopy combined with esophageal iodine staining was performed in a total of 181 patients with head and neck cancer, and esophageal cancer was detected in 19 cases and gastric cancer in 16 cases. In 30 cases of hypopharyngeal cancer, esophageal cancer was detected in 9 cases and dysplasia of the esophagus in 6 cases. Twelve of 30 cases underwent total esophagectomy with reconstruction of the stomach or colon. All cases of hypopharyngeal cancer associated with esophageal cancer or dysplasia were of the piriform sinus type or the postcricoid type. On the other hand, no cancerous or dysplastic changes were detected in the esophagus in the posterior type of hypopharyngeal cancer. Therefore, total esophagectomy was necessary for treatment of the piriform sinus type and postcricoid type of hypopharyngeal cancer to improve prognosis.
DNA Encoded Biotechnologies for Informative Cancer Diagnostics (2009)

This thesis describes the development of DNA-encoded, multi-parametric, sensing platforms for informative cancer diagnostics. In the first part of this thesis, I will present a technology called “DNA-encoded antibody library (DEAL).” In this approach, computationally derived, orthogonal ssDNA sequences are conjugated to antibodies specific for protein targets and cell surface markers. The resulting collection of conjugates is applied to a biological sample of interest, binds to their cognate antigens, and is detected after the complexes are hybridized to a glass substrate printed with spatially distinct complementary DNA sequences. By using DNA assembly, the DEAL platform enables the simultaneous detection of the major classes of biological molecules, namely nucleic acids, proteins and cells. The second part of this thesis focuses on the development of a cell sorting platform that can detect antigen-specific T cells called “Nucleic Acid Cell Sorting (NACS).” In NACS, ssDNA encoding is used to assemble peptide major histocompatability complexes (p/MHC) on glass substrates by hybridization to cDNA microarrays. These assembled peptide/MHC microarrays are then used to sort mixed populations of antigen-specific T cells. This spatially encoded scheme addresses the widespread desire for methods that allow the multiplexed detection of antigen-specific T cells. The sensitivity and selectivity of NACS is similar to flow cytometry, demonstrated in key experiments with T cells derived from multiple sources, including endogenous and TCR-engineered T cells collected from cancer patients. Finally, this platform is used to monitor the persistence of cancer-specific T cells in peripheral blood collected from a patient undergoing T cellular immunotherapy. Lastly, a scheme for the detection of cell surface markers is presented. In this approach, DEAL and NACS conjugates prepared with UV labile ssDNA oligonucleotides are allowed to bind to target cell samples in solution. The ssDNA tags are released in solution by UV-induced photocleavage. The presence and expression of the cognate antigen is determined by collecting the pool of reporter ssDNA tags followed by exponential amplification by PCR. A DEAL conjugate specific for the oncogene EGFR was used to determine the expression level of EGFR in a low-passage brain tumor primary cell line. The feasibility of using ssDNA-p/MHC complexes for detecting unique TCRs was also demonstrated. Finally an experimental flow is described for integration with second generational high-throughput sequencing platforms for global and quantitative surface-ome profiling.