gebhart/patrepeval huggingface dataset:
Wireless big data are our wireless edge networks ready? (2014)

The wireless industry has served the world for more than a century. More recently over the last 30 years, the evolution of the cellular industry and wireless mobility has radically changed the very nature and socialization of human communications globally, now reaching almost every human being on the planet. But with its success, cellular communications is also reaching a nexus point, a point of change that raises questions as to its long term sustainability in its current form. The radio spectrum used for cellular communications today is both fragmented and limited in channel size, and in aggregation provides only a Gigahertz worth of spectrum worldwide - a condition making it ill-suited for the emergence of wireless “big data” transport. To utilize this very limited spectrum capacity for the evolving role of cellular communications, service providers are deploying enhanced technologies, network topologies and increasingly complex modulation methods to extract the remaining network capacity from this spectrum band. Going forward and in light of the remarkable and ongoing growth in wireless data, will these network enhancements and reliance on existing cellular and Wi-Fi spectrum alone be enough to sustain voice and data cellular infrastructure and network capacity well into the future? Or alternatively, and in addition to existing infrastructure, will new high capacity spectrum, new spectrum policies, non-traditional technologies and network topologies be required to meet emerging cellular and wireless data challenges.
Turbulence forecasting via Neural ODE (2019)

Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that are non-local in scale-space. As such the computational demands associated with explicitly resolving the full set of scales and their interactions, as in the Direct Numerical Simulation (DNS) of the Navier-Stokes equations, in most problems of practical interest are so high that reduced modeling of scales and interactions is required before further progress can be made. While popular reduced models are typically based on phenomenological modeling of relevant turbulent processes, recent advances in machine learning techniques have energized efforts to further improve the accuracy of such reduced models. In contrast to such efforts that seek to improve an existing turbulence model, we propose a machine learning(ML) methodology that captures, de novo, underlying turbulence phenomenology without a pre-specified model form. To illustrate the approach, we consider transient modeling of the dissipation of turbulent kinetic energy, a fundamental turbulent process that is central to a wide range of turbulence models using a Neural ODE approach. After presenting details of the methodology, we show that this approach outperforms state-of-the-art approaches.
Polarization Control for MEMS-VCSEL Using Simple Metal Slit (2019)

We developed a micromechanically tunable vertical cavity surface emitting laser in which the polarization is controlled by metal slit. The slit was fabricated on a mirror in a microcavity, with the width of the slit being approximately the same as the beam width. We calculated the effect of the slit on the polarization using the finite difference time domain method with a 3D model. The results showed that the polarization perpendicular to the slit decayed faster than that parallel to the slit, implying that the structure is polarization-selective. This effect was confirmed when the slit was incorporated into actual devices.
Tumor-specific usage of alternative transcription start sites in colorectal cancer identified by genome-wide exon array analysis (2011)

Alternative TSS usage in colorectal adenoma and cancer samples has been shown for nine genes, and OSBPL1A and TRAK1 were found to be regulated in vitro by Wnt signaling. TCF12 protein expression was upregulated in cancer samples and correlated with progression free survival.
Direct Derivation of the Gradient Method for Network Utility Maximization in Broadcast Channels and Its Application (2011)

In broadcast channels, network utility maximization formulates a scheduling problem in order to maximize a sum of given utility functions. It is known that the network utility maximization is achieved if a gradient method is used. In this paper, however, we show that the network utility maximization is achieved only if a gradient method is used. That proves the equivalence between a problem formulated by the network utility maximization and a problem with a gradient method. The gradient method simplifies the object function of a scheduling problem by modifying utility functions to a gradient form, so that it makes easy to deal with the problem. We apply the gradient method to a problem with utility functions given by generalized proportional fairness. It is revealed that using the gradient method for the generalized proportional fairness is equivalent to applying a binomial approximation. Simulation results are presented with various scheduling parameters.
Drop mass transfer in a microfluidic chip compared to a centrifugal contactor (2014)

A model system was developed for enabling a multiscale understanding of centrifugal‐contactor liquid–liquid extraction. The system consisted of Nd(III) + xylenol orange in the aqueous phase buffered to pH = 5.5 by KHP, and dodecane + thenoyltrifluroroacetone (HTTA) + tributyphosphate (TBP) in the organic phase. Diffusion constants were measured for neodymium in both the organic and aqueous phases, and the Nd(III) partition coefficients were measured at various HTTA and TBP concentrations. A microfluidic channel was used as a high‐shear model environment to observe mass transfer on a droplet scale with xylenol orange as the aqueous‐phase metal indicator; mass‐transfer rates were measured quantitatively in both diffusion and reaction limited regimes on the droplet scale. The microfluidic results were comparable to observations made for the same system in a laboratory scale liquid–liquid centrifugal contactor, indicating that single drop microfluidic experiments can provide information on mass transfer in complicated flows and geometries. © 2014 American Institute of Chemical Engineers AIChE J , 60: 3071–3078, 2014
Advances in Computers and Information in Engineering Research, Volume 1 (2014)

This book series aims to capture advances in computers and information in engineering research, especially by researchers and members of ASME's Computers &amp; Information in Engineering (CIE) Division. The books will be published in both traditional and eBook formats. The series is focusing on advances in computational methods, algorithms, tools, and processes on the cutting edge of research and development as they have evolved and/or have been reported during the last three to five annual CIE conferences. The series will provide a resource for enhancing engineering practice by enabling the understanding and the application of evolving and emerging technologies that impact critical engineering issues related to the topics and themes under CIE's technical committees areas of interest, but not limited to: Advanced Modeling and Simulation; Computer-Aided Product and Process Development; Systems Engineering, Information and Knowledge Management; Virtual Environments and Systems
How does Oracle Database In-Memory Scale out? (2015)

The Oracle RDBMS In-memory Option (DBIM), introduced in 2014, is an industry-first distributed dual format in-memory RDBMS that allows a database object to be stored in columnar format purely in-memory, simultaneously maintaining transactional consistency with the corresponding row-major format persisted in storage and accessed through in-memory database buffer cache. The in-memory columnar format is highly optimized to break performance barriers in analytic query workloads while the row format is most suitable for OLTP workloads. In this paper, we present the distributed architecture of the Oracle Database In-memory Option that enables the in-memory RDBMS to transparently scale out across a set of Oracle database server instances in an Oracle RAC cluster, both in terms of memory capacity and query processing throughput. The architecture allows complete application-transparent, extremely scalable and automated in-memory distribution of Oracle RDBMS objects across multiple instances in a cluster. It seamlessly provides distribution awareness to the Oracle SQL execution framework, ensuring completely local memory scans through affinitized fault-tolerant parallel execution within and across servers without explicit optimizer plan changes or query rewrites.
Alkali Assisted Reduction of Open‐Circuit Voltage Deficit in CZTSe Solar Cells (2017)

Pure selenide Cu2ZnSnSe4 solar cells were fabricated with a maximum achieved open-circuit voltage (V-OC) of 454 mV, which is on par with the highest known V-OC for this technology (Bourdais et al., Adv. Energ. Mater. 2016, 6). A simple, non-vacuum, spin coating technique was developed for the introduction of alkali ions (Li+, K+, Rb+) before two annealing steps. The presence of Rb and Li ions in particular, was observed to reduce recombination in the bulk and increase minority charge carrier decay time. This resulted in the reduction of the redshift in the photoluminescence peak from the bandgap and the V-OC deficit. Bandgap variations and electrostatic potential fluctuations in conduction and valence bands were investigated as aspects likely affected by alkali ions.
Interpretation and evolution of open-circuit voltage, recombination, ideality factor and subgap defect states during reversible light-soaking and irreversible degradation of perovskite solar cells (2017)

Insights into the interplay of different recombination mechanisms and their origins (bulk, surface) are provided comparing fresh, light-soaked and aged devices.
Secrecy sum-rate for orthogonal random beamforming with opportunistic scheduling (2013)

We employ orthogonal random beamforming (ORBF) for the worst-case multi-user downlink scenario where each user is wiretapped by one eavesdropper. Two opportunistic scheduling techniques that ensure confidentiality by exploiting multi-user diversity are investigated; the first technique (optimal) requires limited feedback of the effective signal-to-interference ratio (SIR) from all the users and the eavesdroppers while the second technique (suboptimal) incorporates SIR knowledge from only the legitimate users. By using extreme value theory, we derive the achievable SIR-based secrecy sum-rate and the associated scaling laws for both scheduling techniques.
Ultra High Resolution Linear Ion Trap Orbitrap Mass Spectrometer (Orbitrap Elite) Facilitates Top Down LC MS/MS and Versatile Peptide Fragmentation Modes (2011)

Although only a few years old, the combination of a linear ion trap with an Orbitrap analyzer has become one of the standard mass spectrometers to characterize proteins and proteomes. Here we describe a novel version of this instrument family, the Orbitrap Elite, which is improved in three main areas. The ion transfer optics has an ion path that blocks the line of sight to achieve more robust operation. The tandem MS acquisition speed of the dual cell linear ion trap now exceeds 12 Hz. Most importantly, the resolving power of the Orbitrap analyzer has been increased twofold for the same transient length by employing a compact, high-field Orbitrap analyzer that almost doubles the observed frequencies. An enhanced Fourier Transform algorithm-incorporating phase information-further doubles the resolving power to 240,000 at m/z 400 for a 768 ms transient. For top-down experiments, we combine a survey scan with a selected ion monitoring scan of the charge state of the protein to be fragmented and with several HCD microscans. Despite the 120,000 resolving power for SIM and HCD scans, the total cycle time is within several seconds and therefore suitable for liquid chromatography tandem MS. For bottom-up proteomics, we combined survey scans at 240,000 resolving power with data-dependent collision-induced dissociation of the 20 most abundant precursors in a total cycle time of 2.5 s-increasing protein identifications in complex mixtures by about 30%. The speed of the Orbitrap Elite furthermore allows scan modes in which complementary dissociation mechanisms are routinely obtained of all fragmented peptides.
Polymers for Reversible Hydrogen Storage Inspired by Electrode-active Materials in Organic Batteries (2022)

Redox-active polymers with electrochemical reversibility and rapid electrode reaction rates are employed to develop organic electrode-active materials employed in organic batteries, based on their selfexchange reactions in polymer layers. Negative charging of the electroneutral redox polymers results in a significant increase in basicity to allow protonation of each redox-active site in the polymer. Since most of the hydrogenated products are no longer redox-active, aprotic battery electrolytes are employed to avoid the hydrogenation in organic batteries. On the other hand, organic compounds that undergo reversible hydrogenation, such as toluene to yield methylcyclohexane, have been studied as hydrogen storage materials. However, the hydrogenation with hydrogen gas usually proceeds via a highly energy consuming process. We anticipated that electrolytic hydrogenation of the redox-active molecules would provide a much simpler process. We have found that ketone-containing polymers stored hydrogen via the electrolytic process in the presence of water at room temperature. The resulting alcohol polymer evolved hydrogen gas by warming under mild conditions with an iridium catalyst. The hydrogenation/dehydrogenation cycle was accomplished throughout the polymer layer, meaning that all of the ketone groups in the polymer were equilibrated with the hydrogen gas according to > C = O + H2 ⇄ > CH-OH in the presence of the iridium catalyst. The reversible hydrogenation/dehydrogenation was extended to various types of organic groups in the polymer, providing many types of the hydrogen carrier polymers as a new class of energy-related functional polymers. The easy handling and moldable nature of the organic polymers indicate the feasibility of applying them as pocketable hydrogen carriers.
Bi-level Score Matching for Learning Energy-based Latent Variable Models (2020)

Score matching (SM) provides a compelling approach to learn energy-based models (EBMs) by avoiding the calculation of partition function. However, it remains largely open to learn energy-based latent variable models (EBLVMs), except some special cases. This paper presents a bi-level score matching (BiSM) method to learn EBLVMs with general structures by reformulating SM as a bi-level optimization problem. The higher level introduces a variational posterior of the latent variables and optimizes a modified SM objective, and the lower level optimizes the variational posterior to fit the true posterior. To solve BiSM efficiently, we develop a stochastic optimization algorithm with gradient unrolling. Theoretically, we analyze the consistency of BiSM and the convergence of the stochastic algorithm. Empirically, we show the promise of BiSM in Gaussian restricted Boltzmann machines and highly nonstructural EBLVMs parameterized by deep convolutional neural networks. BiSM is comparable to the widely adopted contrastive divergence and SM methods when they are applicable; and can learn complex EBLVMs with intractable posteriors to generate natural images.
Rack-Scale In-Memory Join Processing using RDMA (2015)

Database systems running on a cluster of machines, i.e. rack-scale databases, are a common architecture for many large databases and data appliances. As the data movement across machines is often a significant bottleneck, these systems typically use a low-latency, high-throughput network such as InfiniBand. To achieve the necessary performance, parallel join algorithms must take advantage of the primitives provided by the network to speed up data transfer.
EPE Joint Wind Energy and T&D Chapters Seminar. The Utzon Centre & Aalborg University, Aalborg, Denmark. Thursday-Friday 28th-29thJune 2012. (2011)

(2011). EPE Joint Wind Energy and T&D Chapters Seminar. The Utzon Centre & Aalborg University, Aalborg, Denmark. Thursday-Friday 28th-29th June 2012. EPE Journal: Vol. 21, No. 4, pp. 4-4.
Models of Multilayer Antenna Radomes with Anisotropic Materials (2006)

A modified Paris' model (Paris, 1970) for computed-aided radome analysis is presented, which takes into account the dielectric material anisotropy of the radome layers. The analytical model is combined with a practically realized two-resonator method for characterization of the normal and parallel to the surface dielectric parameters of the radome layers. Finally, several examples are given, which illustrate the steps for introduction of appropriate radome models of reinforced and composite radome structures with anisotropy, which accurate represent all the layers formed in the practical radome construction - cores, skins, irregular epoxy glue fillets, protective coatings, etc.
Daily cone-beam computed tomography used to determine tumour shrinkage and localisation in lung cancer patients (2010)

One third of all patients with lung cancer undergoing chemo-RT achieved significant tumour shrinkage from planning CT until the end of the radiotherapy. Differences in GTV-t and GTV-n motion was observed and matching using the ITV including both GTV-t and GTV-n is therefore preferable.
Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks (2020)

The unstoppable adoption of the Internet of Things (IoT) is driven by the deployment of new services that require continuous capture of information from huge populations of sensors, or actuating over a myriad of "smart" objects. Accordingly, next generation networks are being designed to support such massive numbers of devices and connections. For example, the 3rd Generation Partnership Project (3GPP) is designing the different 5G releases specifically with IoT in mind. Nevertheless, from a security perspective this scenario is a potential nightmare: the attack surface becomes wider and many IoT nodes do not have enough resources to support advanced security protocols. In fact, security is rarely a priority in their design. Thus, including network-level mechanisms for preventing attacks from malware-infected IoT devices is mandatory to avert further damage. In this paper, we propose a novel Software-Defined Networking (SDN)-based architecture to identify suspicious nodes in 4G or 5G networks and redirect their traffic to a secondary network slice where traffic is analyzed in depth before allowing it reaching its destination. The architecture can be easily integrated in any existing deployment due to its interoperability. By following this approach, we can detect potential threats at an early stage and limit the damage by Distributed Denial of Service (DDoS) attacks originated in IoT devices.
Structure-based Discovery of Phenyl (3-Phenylpyrrolidin-3-yl)sulfones as Selective, Orally Active RORγt Inverse Agonists (2019)

A new phenyl (3-phenylpyrrolidin-3-yl)sulfone series of RORγt inverse agonists was discovered utilizing the binding conformation of previously reported bicyclic sulfonamide <b>1</b>. Through a combination of structure-based design and structure-activity relationship studies, a polar set of amides at <i>N</i>1-position of the pyrrolidine ring and perfluoroisopropyl group at <i>para</i>-position of the 3-phenyl group were identified as critical structural elements to achieve high selectivity against PXR, LXRα, and LXRβ. Further optimization led to the discovery of (1<i>R</i>,4r)-4-((<i>R</i>)-3-((4-fluorophenyl)sulfonyl)-3-(4-(perfluoropropan-2-yl)phenyl)pyrrolidine-1-carbonyl)cyclohexane-1-carboxylic acid (<b>26</b>), which displayed excellent selectivity, desirable liability and pharmacokinetic properties <i>in vitro</i>, and a good pharmacokinetic profile in mouse. Oral administration of <b>26</b> demonstrated dose-dependent inhibition of IL-17 production in a mouse IL-2/IL-23-induced pharmacodynamic model and biologic-like efficacy in an IL-23-induced mouse acanthosis model.
Lithium/Sodium‐Ion Batteries: In Situ, Atomic‐Resolution Observation of Lithiation and Sodiation of WS2 Nanoflakes: Implications for Lithium‐Ion and Sodium‐Ion Batteries (Small 24/2021) (2021)

In article number 2100637, Vinayak P. Dravid, Jinsong Wu, and co-workers perform a systematic study of WS2 nanoflakes as the anode for lithium-ion and sodium-ion batteries. It is found that compared to LIBs, SIBs exhibit a higher reversible sodium storage capacity and superior cyclability. The results show a direct correlation between the reaction dynamics of lithiated/sodiated WS2 nanoflakes and their electrochemical performance.
Natural Rubber-Toughened Polystyrene: Effects of Mixing Procedure and Maleic Anhydride Content on Impact Property and Phase Morphology (2013)

The toughening of polystyrene (PS) by melt blending with natural rubber (NR) was prepared in a brabender plasticorder. Two kinds of processing had been used: (a) one-step mixing in which the three components of PS (60 wt%), NR (40 wt%) and maleic anhydride (MA) were simultaneously introduced in the mixer; (b) two-step mixing in which NR and MA were separately premixed before the final mixing with PS. The effect of MA loading (3 and 5 phr) on gel content, impact energy and morphology of PS-NR-MA blend were further investigated. The results showed that the incorporation of NR into PS increased the impact energy of the blend. The results also showed a significant effect of the different mixing procedures on the properties of PS-NR-MA blend. High contents of unreacted MA and gel were found in the blend obtained by the one-step mixing, whereas the blend prepared by the two-step mixing showed lower values in both unreacted MA and gel content. On the other hand, the impact energy of the blend prepared by one-step mixing was slightly higher than that of the blend prepared by two-step mixing. This is due to the decreased molecular weight of NR in the formerly prepared MNR of the two-step mixing. For the effect of MA loading, the decrease of unreacted MA content, gel content and rubber particle size were found at low concentration of MA.
Solid phase synthesis of complex natural products and libraries thereof (2001)

Natural products have served as an important source of medicinal compounds and pharmaceutical leads over the last century. Within the last 10 years, significant interest has developed in applying combinatorial chemistry techniques to the study of natural products and their biological activities. In this review, we examine several representative efforts wherein natural product skeletons have been constructed or immobilized on solid support and subsequently derivatized, giving rise to analog libraries useful in understanding the structure-activity relationships of the parent natural product. Issues such as target selection, library design, linker development, automation, and library characterization are addressed.
Assessment of clinical practice guideline methodology for the treatment of knee osteoarthritis with intra-articular hyaluronic acid (2015)

There is a need for a standard "appropriate methodology" that is agreed upon for osteoarthritis clinical practice guidelines in order to prevent the development of conflicting recommendations for intra-articular hyaluronic acid treatment for knee osteoarthritis, and to assure that treating physicians who are utilizing these guidelines are making their clinical decisions on the best available evidence. At present, the inconsistent recommendations provided for intra-articular hyaluronic acid treatment make it difficult for clinical professionals to determine its appropriateness when treating patients with knee osteoarthritis.