gebhart/patrepeval huggingface dataset:
Behaviour modelling of wideband RF transmitters using Hammerstein–Wiener models (2010)

The authors concern the application and use of a class of block-oriented systems, known as Hammerstein–Wiener, to model the dynamic non-linear behaviour of radio frequency (RF) transmitters. This class of system models is found to better mimic strong dynamic non-linear systems, as compared to simpler individual Hammerstein and Wiener models. The identification, which may look complicated at first glance, is skillfully tackled in an iterative two-stage identification approach by applying a class of global pattern search techniques along with the Narendra–Gallman method. The number of parameters processed at each iteration is therefore reduced, which considerably facilitates the progress and convergence of the identification algorithm. The model is identified and validated for two classes of power amplifiers. The validation results are obtained for various orders and are compared to the results of memory polynomial models. The Hammerstein–Wiener model achieves comparable results with a much lower level of complexity, in terms of the number of parameters associated with the model.
Study of Impact of Access Resistance on High-Frequency Performance of AlGaN/GaN HEMTs by Measurements at Low Temperatures (2006)

This letter studies the effect of access resistance on the high-frequency performance of AlGaN/GaN high-electron-mobility transistors. To systematically reduce the sheet access resistance, the transistors were measured at different temperatures. The increase of mobility at lower temperatures allowed more than four-fold reduction in the sheet access resistances. Both the current- and power-gain cutoff frequencies are observed to increase at low temperatures. Also, the intrinsic effective velocity has been estimated in these devices, as well as the parasitic delays involved in the final performance. Channel charging delay, which was expected to be most sensitive to parasitics, is observed to decrease at low temperatures. However, the drain delay, intrinsic delay, and effective electron velocity remain unaffected by temperature
ChemInform Abstract: ADSORPTION AND DECOMPOSITION OF DIMETHYL METHYLPHOSPHONATE ON AN ALUMINUM OXIDE SURFACE (1985)

Abstract Die Adsorption von Me‐PO(OMe)2 (MPDM) an einen A1‐ Oxid‐Film (Oberflächen‐Temp.
Hydroalumination of 1,4-Diazabut-1-enes and 4-Lithio-1,4-diazabut-1-enes: Synthesis of Amidoaluminum Hydride, Lithium Aluminum Hydride, and Lithium Diamidoaluminum Hydride Complexes (1995)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTHydroalumination of 1,4-Diazabut-1-enes and 4-Lithio-1,4-diazabut-1-enes: Synthesis of Amidoaluminum Hydride, Lithium Aluminum Hydride, and Lithium Diamidoaluminum Hydride ComplexesMichael G. Gardiner, Stacey M. Lawrence, and Colin L. RastonCite this: Inorg. Chem. 1995, 34, 18, 4652–4659Publication Date (Print):August 1, 1995Publication History Published online1 May 2002Published inissue 1 August 1995https://pubs.acs.org/doi/10.1021/ic00122a023https://doi.org/10.1021/ic00122a023research-articleACS PublicationsRequest reuse permissionsArticle Views174Altmetric-Citations29LEARN 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-AlertscloseSupporting Info (2)»Supporting Information Supporting Information Get e-Alerts
D-SPTF (2004)

Distributed Shortest-Positioning Time First (D-SPTF) is a request distribution protocol for decentralized systems of storage servers. D-SPTF exploits high-speed interconnects to dynamically select which server, among those with a replica, should service each read request. In doing so, it simultaneously balances load, exploits the aggregate cache capacity, and reduces positioning times for cache misses. For network latencies expected in storage clusters (e.g., 10--200μs), D-SPTF performs as well as would a hypothetical centralized system with the same collection of CPU, cache, and disk resources. Compared to popular decentralized approaches, D-SPTF achieves up to 65% higher throughput and adapts more cleanly to heterogenous server capabilities.
Data from Transcriptomic Profiling of Sequential Tumors from Breast Cancer Patients Provides a Global View of Metastatic Expression Changes Following Endocrine Therapy (2023)

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; Disease recurrence is a common problem in breast cancer and yet the mechanisms enabling tumor cells to evade therapy and colonize distant organs remain unclear. We sought to characterize global expression changes occurring with metastatic disease progression in the endocrine-resistant setting.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; Here, for the first time, RNAsequencing has been performed on matched primary, nodal, and liver metastatic tumors from tamoxifen-treated patients following disease progression. Expression of genes commonly elevated in the metastases of sequenced patients was subsequently examined in an extended matched patient cohort with metastatic disease from multiple sites. The impact of tamoxifen treatment on endocrine-resistant tumors &lt;i&gt;in vivo&lt;/i&gt; was investigated in a xenograft model.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; The extent of patient heterogeneity at the gene level was striking. Less than 3% of the genes differentially expressed between sequential tumors were common to all patients. Larger divergence was observed between primary and liver tumors than between primary and nodal tumors, reflecting both the latency to disease progression and the genetic impact of intervening therapy. Furthermore, an endocrine-resistant &lt;i&gt;in vivo&lt;/i&gt; mouse model demonstrated that tamoxifen treatment has the potential to drive disease progression and establish distant metastatic disease. Common functional pathways altered during metastatic, endocrine-resistant progression included extracellular matrix receptor interactions and focal adhesions.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; This novel global analysis highlights the influence of primary tumor biology in determining the transcriptomic profile of metastatic tumors, as well as the need for adaptations in cell–cell communications to facilitate successful tumor cell colonization of distant host organs. &lt;i&gt;Clin Cancer Res; 21(23); 5371–9. ©2015 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;
Optimal Energy Management for a Hybrid Vehicle Using Neuro-Dynamic Programming to Consider Transient Engine Operation (2011)

This paper proposes a self-learning approach to develop optimal power management with multiple objectives, e.g. to minimize fuel consumption and transient engine-out NOx and particulate matter emission for a series hydraulic hybrid vehicle. Addressing multiple objectives is particularly relevant in the case of a diesel powered hydraulic hybrid since it has been shown that managing engine transients can significantly reduce real-world emissions. The problem is formulated as an infinite time horizon stochastic sequential decision making/markovian problem. The problem is computationally intractable by conventional Dynamic programming due to large number of states and complex modeling issues. Therefore, the paper proposes an online self-learning neural controller based on the fundamental principles of Neuro-Dynamic Programming (NDP) and reinforcement learning. The controller learns from its interactions with the environment and improves its performance over time. The controller tries to minimize multiple objectives and continues to evolve until a global solution is achieved. The control law is a stationary full state feedback based on 5 states and can be directly implemented. The controller performance is then evaluated in the Engine-in-the-Loop (EIL) facility.
Catalytic, Enantioselective, Copper–Boryl Additions to Alkenes (2019)

Enantiomerically enriched organoboron compounds are of considerable utility in organic synthesis. Unlike other organometallic reagents (e.g., RM, M = Li, Al, Mg, or Zn), boron‐containing hydrocarbons possess a number of desirable properties that include air, moisture, and configurational stability in addition to ease of preparation and exceptional functional group tolerance. Multicomponent, CB bond forming reactions, catalyzed by readily accessible, copper‐based complexes, have recently emerged as an attractive option for efficient, chemo‐, regio‐, diastereo‐ and enantioselective generation of multifunctional organoboron compounds. These processes typically begin with the addition of a copper–boryl complex to an alkenyl site, generating a copper–alkyl intermediate that then reacts with an electrophile. The focus of this chapter will be these transformations. A brief analysis of the key mechanistic nuances that impact the observed selectivity will be followed by an overview of the scope and limitations of the various strategies and their applications to the synthesis of bioactive molecules.
An Experimental Simulation of a Design Three-Port DC-DC Converter (2014)

Traditional DC-DC converter topologies interface two power terminals: a source and a load. The construction of diverse and flexible power management and distribution (PMAD) systems with such topologies is governed by a tight compromise between converter count, efficiency, and control complexity. The broader impact of the current research activity is the development of enhanced power converter systems suitable for a wide range of applications. Potential users of this technology include the designers of portable and stand-alone systems such as laptops, hand-held electronics, and communication repeater stations. High power topology options support the evolution of clean power technologies such as hybrid-electric vehicles (HEV’s) and solar vehicles. DC-DC converter is considered as an advanced environmental issue since it is a greenhouse emission eliminator. By utilizing the advancement of these renewable energy sources, we minimize the use of fossil fuel. Thus, we will have a cleaner and pollution free environment. In this paper, a three-port DC-DC converter is designed and discussed. The converter was built and tested at the energy research laboratory at Taibah University, Al Madinah, KSA.
Ultra-thin multiple-channel LWIR imaging systems (2006)

Infrared camera systems may be made dramatically smaller by simultaneously collecting several low-resolution images with multiple narrow aperture lenses rather than collecting a single high-resolution image with one wide aperture lens. Conventional imaging systems consist of one or more optical elements that image a scene on the focal plane. The resolution depends on the wavelength of operation and the f-number of the lens system, assuming a diffraction limited operation. An image of comparable resolution may be obtained by using a multi-channel camera that collects multiple low-resolution measurements of the scene and then reconstructing a high-resolution image. The proposed infrared sensing system uses a three-by-three lenslet array with an effective focal length of 1.9mm and overall system length of 2.3mm, and we achieve image resolution comparable to a conventional single lens system having a focal length of 5.7mm and overall system length of 26mm. The high-resolution final image generated by this system is reconstructed from the noisy low-resolution images corresponding to each lenslet; this is accomplished using a computational process known as superresolution reconstruction. The novelty of our approach to the superresolution problem is the use of wavelets and related multiresolution method within a Expectation-Maximization framework to improve the accuracy and visual quality of the reconstructed image. The wavelet-based regularization reduces the appearance of artifacts while preserving key features such as edges and singularities. The processing method is very fast, making the integrated sensing and processing viable for both time-sensitive applications and massive collections of sensor outputs.
14-OR: Harmine and Exenatide Combination Increases Human ß-Cell Survival (2022)

GLP1R agonists such as Exendin-4 (E) together with DYRK1A inhibitors such as Harmine (H) significantly increase human β-cell replication in vitro and in vivo. Importantly, 3-month treatment with H+E combination markedly increases human beta cell mass (∼7-fold) in islets transplanted in immunosuppressed mice, beyond the increase induced by proliferation. Therefore, we addressed whether H+E also enhances β-cell survival and that contributes to the increased human β-cell mass expansion in vivo. Treatment with H+E significantly decreased β-cell apoptosis in dispersed primary human islet cells treated in vitro with either thapsigargin (ER stress) , cytokines (inflammation) and H2O2 (ROS) , while the drugs alone or vehicle (V) did not induce such effect. Importantly, H+E treatment for 7 days significantly reduced β-cell apoptosis in human islet grafts transplanted in immunosuppressed mice assessed by insulin and TUNEL staining. Human β-cell mass analysis of these grafts by iDISCO+ revealed a significant ∼50% increase in H+E-treated mice compared with mice treated with drugs alone or V. Human α-cell mass was unchanged. To address the signaling pathways modulated by H+E after 7-day treatment, we performed RNA-seq analysis of these human islet grafts. We identified 29 differentially expressed human genes (&amp;gt; 2-fold, p&amp;lt;0.05) in H+E-treated human islet grafts. GSEA analysis revealed cell adhesion, survival, vascularization and secretion as the main pathways induced by H+E. Among the upregulated genes, VGF (VGF Nerve Growth Factor Inducible) is known to regulate insulin secretion and β-cell survival. We found that H+E treatment of human islets in vitro increases 2-to-3-fold VGF mRNA and secretion. We are now determining VGF involvement in H+E-induced human β-cell survival. In conclusion, we have uncovered a novel prosurvival function of H+E in human β-cells with the potential implication of VGF in these effects. These studies can lead to the discovery of future β-cell protection and regeneration therapies for diabetes. Disclosure C.Rosselot: None. A.F.Stewart: None. A.Garcia-ocana: Consultant; Sun Pharmaceutical Industries Ltd. Y.Li: None. D.Guevara: None. K.A.Beliard: None. R.Kang: None. P.Wang: None. K.Thakkar: None. G.Lu: None. R.J.Devita: None. Funding DYRK Inhibitors for Human Beta Cell Expansion RDK105015
Structure-Dependent Doppler Broadening Using a Generalized Thermal Scattering Law (2021)

The thermal scattering law (TSL), i.e., S(α,β), represents the momentum and energy exchange phase space for a material. The incoherent and coherent components of the TSL correlate an atom’s trajectory with itself and/or with other atoms in the lattice structure. This structural information is especially important for low energies where the wavelength of neutrons is on the order of the lattice interatomic spacing. Both thermal neutron scattering as well as low energy resonance broadening involve processes where incoming neutron responses are lattice dependent. Traditionally, Doppler broadening for absorption resonances approximates these interactions by assuming a Maxwell–Boltzmann distribution for the neutron velocity. For high energies and high temperatures, this approximation is reasonable. However, for low temperatures or low energies, the lattice structure binding effects will influence the velocity distribution. Using the TSL to determine the Doppler broadening directly introduces the material structure into the calculation to most accurately capture the momentum and energy space. Typically, the TSL is derived assuming cubic lattice symmetry. This approximation collapses the directional lattice information, including the polarization vectors and associated energies, into an energy-dependent function called the density of states. The cubic approximation, while valid for highly symmetric and uniformly bonded materials, is insufficient to capture the true structure. In this work, generalized formulation for the exact, lattice-dependent TSL is implemented within the Full Law Analysis Scattering System Hub (FLASSH) using polarization vectors and associated energies as fundamental input. These capabilities are utilized to perform the generalized structure Doppler broadening analysis for UO2.
Laser cooling of strontium atoms towards the quantum degenerate regime (2005)

Summary form only given. All-optical production of quantum degenerate atomic gases has been one of the long-standing targets in laser cooling. We report a novel approach towards this direction based on a narrow-line laser cooling for strontium atoms. By employing two transitions with markedly different dipole moments, i.e., the allowed /sup 1/S/sub 0/-/sup 1/P/sub 1/ (/spl lambda/=461 nm, /spl gamma/=2/spl pi//spl times/32 MHz) and the spin-forbidden /sup 1/S/sub 0/-/sup 3/P/sub 1/ (/spl lambda/=689 nm, /spl gamma/=2/spl pi//spl times/7.6 kHz) transition, thermal strontium atoms were Doppler-cooled down to 400 nK or the photon recoil temperature, in a magneto-optical trap (MOT). Presents the corresponding energy levels for cooling and trapping. The use of a narrow spin-forbidden transition successfully reduced the radiation trapping effects at a high atom density over 10/sup 12//cm/sup 3/, thus enabling us to attain the hitherto high phase space density of 0.01 in a MOT.
Structure-Guided Discovery of a Novel Aminoglycoside Conjugate Targeting HIV-1 RNA Viral Genome (2013)

The dimerization initiation site (DIS) of the HIV-1 genomic RNA is a conserved stem-loop that promotes viral genome dimerization by forming a loop-loop complex. The DIS constitutes a potentially interesting target because it is crucial for several key steps of the viral replication. In this work we describe the synthesis of a rationally designed aminoglycoside conjugate that binds the HIV-1 DIS viral RNA with high specificity, as shown by an extensive in vitro binding characterization. We propose a three-dimensional model of the drug-RNA interaction that perfectly fits with binding data. Our results show the feasibility of targeting the HIV DIS viral RNA dimer and open the way to the rationale design of a new class of antiviral drugs. In addition, due to similarities between the HIV-1 DIS RNA and the bacterial aminoacyl decoding site (A site) RNA, we show that this novel aminoglycoside conjugate also binds the bacterial A site with a similar affinity as natural aminoglycoside antibiotics.
Correction for Colussi et al., HDAC2 blockade by nitric oxide and histone deacetylase inhibitors reveals a common target in Duchenne muscular dystrophy treatment (2009)

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.
HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance Scaling (2023)

Dynamic neural networks (DyNNs) have become viable techniques to enable intelligence on resource-constrained edge devices while maintaining computational efficiency. In many cases, the implementation of DyNNs can be sub-optimal due to its underlying backbone architecture being developed at the design stage independent of both: (i) potential support for dynamic computing, e.g. early exiting, and (ii) resource efficiency features of the underlying hardware, e.g., dynamic voltage and frequency scaling (DVFS). Addressing this, we present HADAS, a novel Hardware-Aware Dynamic Neural Architecture Search framework that realizes DyNN architectures whose backbone, early exiting features, and DVFS settings have been jointly optimized to maximize performance and resource efficiency. Our experiments using the CIFAR-100 dataset and a diverse set of edge computing platforms have shown that HADAS can elevate dynamic models' energy efficiency by up to 57% for the same level of accuracy scores. Our code is available at https://github.com/HalimaBouzidi/HADAS
Molecular characterization of three enteroviral strains isolated in Kuwait from young children with serious conditions (2017)

The results provided a better understanding of the genetic variations, evolution and adaptation of enteroviruses in Kuwait.
Research data supporting "Investigation of the Thermoelectric Response in Conducting Polymers Doped by Solid-State Diffusion" (2019)

Research data supporting the journal publication "Investigation of the Thermoelectric Response in Conducting Polymers Doped by Solid-State Diffusion" is provided, sorted by the figures displaying the underlying data. See the associated README file for further information about this dataset.
Development of Industrial SFF System Using a New Selective Dual-Laser Sintering Process (2006)

This DOI is not currently attached to any metadata records. DOIs can’t actually ever be deleted (they’re persistent), but sometimes our members create DOIs in error. We do have a process to approximate deletion which we follow only in rare cases where the DOI has been genuinely created in error, and most crucially, if the DOI has never been published anywhere online or in print and never otherwise distributed to or communicated with anyone (authors, readers, reviewers, etc.
A Novel Method for lind Frequency ffset Correction in an OFD (1998)

Orthogonal Frequency Division Multiplexing (OFDM) is believed to be an important technique for future wireline and wireless communications. One of the major disadvantages of such a multi-carrier modulation is the sensitivity of the performance to a frequency offset. The frequency offset can result from a Doppler shift due to mobile movement as well as from a carrier frequency synchronization error. Such a frequency offset causes a loss of the carriers’ orthogonality, and hence Inter Carrier Interference (ICI). A previously proposed method to estimate and correct the frequency offset uses the retransmission of a data symbol, thus reducing the bandwidth efficiency. Another method, which merely reduces the effects of the IC1 instead of completely correcting for effects of the frequency offset is based on repetition coding in the frequency domain, hence also reducing the throughput. In this paper, we propose a blind method using the correlation of the samples at the output of the Discrete Fourier Transform (DFT) to estimate the frequency offset. As no training sequence or symbol retransmission is required there is no loss in bandwidth efficiency. Additionally, we develop an adaptive algorithm for the frequency offset correction. The derived algorithm is basically a stochastic gradient algorithm which minimizes the mean squared frequency offset error.
A lightweight thermally insulating and moisture-stable composite made of hollow silica particles (2022)

Thermal insulation materials are highly desirable for several applications ranging from building envelopes to thermal energy storage systems. A new type of low-cost insulation material called hollow silica particles (HSPs) was recently reported. The present work presents an HSP-based stand-alone composite that has very low thermal conductivity and is highly stable to moisture.