gebhart/patrepeval huggingface dataset:
NXG05-5: Shared-Memory Combined Input-Crosspoint Buffered Packet Switch for Differentiated Services (2006)

Combined input-crosspoint buffered (CICB) packet switches with dedicated crosspoint buffers require a minimum amount of memory in the buffered crossbar of N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ldr k ldr L bytes, where N is the number of ports and k is the crosspoint buffer size, which is defined by the distance between the line cards and the buffered crossbar, and L is the cell (packet) size in bytes, to avoid buffer underflow under high-speed data flows. To support P traffic classes with different priorities, CICB switches requires N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ldrkldrLldrP bytes to avoid blocking of high priority cells. In this paper, we study a shared-memory crosspoint buffered packet switch that uses small crosspoint buffers and no speedup to support differentiated services and long distances between the line cards and the buffered crossbar in practical implementations. The proposed switch requires 1/m of memory amount in a CICB switch to achieve similar throughput performance.
ConceptLearner: Discovering visual concepts from weakly labeled image collections (2015)

Discovering visual knowledge from weakly labeled data is crucial to scale up computer vision recognition systems, since it is expensive to obtain fully labeled data for a large number of concept categories. In this paper, we propose ConceptLearner, which is a scalable approach to discover visual concepts from weakly labeled image collections. Thousands of visual concept detectors are learned automatically, without human in the loop for additional annotation. We show that these learned detectors could be applied to recognize concepts at image-level and to detect concepts at image region-level accurately. Under domain-specific supervision, we further evaluate the learned concepts for scene recognition on SUN database and for object detection on Pascal VOC 2007. ConceptLearner shows promising performance compared to fully supervised and weakly supervised methods.
Gate-tunable Epsilon-Near-Zero Nanophotonics (2018)

We present our recent development on the use of tunable transparent conducting oxides to demonstrate electrically tunable epsilon-near-zero (ENZ) optical devices and to excite ENZ resonance in nanostructured optical fiber.
Characterization of Defects in SiC Substrates and Epilayers (2014)

A review is presented of recent monochromatic and white beam synchrotron topography based studies of defects in SiC substrates and epilayers. The methodologies used in applying these techniques to gain understanding of the origins and evolution of the defect structures in PVT grown boules and CVD grown epilayers will be elucidated. In particular, criteria used in distinguishing grown-in defects from deformation induced defects will be discussed. Contrast observed from the various dislocations present in the crystals will be explained, and it will be shown how contrast simulation can be used to identify the detailed characteristics of the dislocations (for example, both Burgers vector sign and magnitude). Application of the various techniques to the complete analysis of the distribution, character and origins of grown-in c-axis screw dislocations (both hollow and closed-core), deformation induced basal plane dislocations, and grown-in threading edge dislocations will be discussed.
Dynamic Neural Accelerator for Reconfigurable & Energy-efficient Neural Network Inference (2021)

Unique Challenges for AI Inference Hardware at the Edge • Peak TOPS or TOPS/Watt are not ideal measures of performance at the edge. Cannot prioritize performance over power efficiency (throughput/watt) • Many AI Hardware rely on batching to improve utilization. Unsuitable for streaming data (batch size 1) use-case at the edge • AI hardware architectures that fully cache network parameters using large on-chip SRAM cannot be scaled down easily to sizes applicable for edge workloads. • Need adaptability to new workloads and the ability to deploy multiple AI models • AI-specific accelerator needs to operate within heterogenous compute environments • Need for efficient compiler & scheduling to maximize compute utilization • Need for high software robustness and usability
Solution of the Perturbation Equation in Optical Tomography Using Weight Functions as a Transform Basis (1998)

This paper describes a new inverse solver for optical tomography. As with prior studies, we employ an iterative perturbation approach, which at each iteration requires the solution of a forward problem and an inverse problem. The inverse problem involves the solution of a linear perturbation equation, which is often severely underdetermined. To overcome this problem, we propose to represent the unknown image of optical properties by a set of linearly independent basis functions, with the number of basis functions being equal to or less than the number of independent detector readings. The accuracy of the solution depends on the choice of the basis. We have explored the use of the weight functions associated with different source and detector pairs (i.e. the rows in the weight matrix of the perturbation equation) as the basis functions. By choosing those source and detector pairs which have uncorrelated weight functions, the inverse problem is transformed into a well-posed, uniquely determined problem. The system matrix in the transformed representation has a dimension significantly smaller than the original matrix, so that it is feasible to perform the inversion using singular value decomposition (SVD). This new method has been integrated with a previously reported forward solver, and applied to data generated from numerical simulations using diffusion approximation. Compared to the Conjugate Gradient Descent (CGD) method used in previously reported studies, the new method takes substantially less computation time, while providing equal, if not better, image reconstmction quality at similar noise levels.
Amorphous Boron Nitride: A Universal, Ultrathin Dielectric for 2D Nanoelectronics (Postprint) (2015)

Abstract : Next-generation nanoelectronics based on 2D materials ideally will require reliable, flexible, transparent, and versatile dielectrics for transistor gate barriers, environmental passivation layers, capacitor spacers, and other device elements. Ultrathin amorphous boron nitride of thicknesses from 2 to 17 nm, described in this work, may offer these attributes, as the material is demonstrated to be universal in structure and stoichiometric chemistry on numerous substrates including flexible polydimethylsiloxane, amorphous silicon dioxide, crystalline Al2O3, other 2D materials including graphene, 2D MoS2, and conducting metals and metal foils. The versatile, large area pulsed laser deposition growth technique is performed at temperatures less than 200 C and without modifying processing conditions, allowing for seamless integration into 2D device architectures.
Stable immobilized amine sorbents for heavy metal and REE removal from industrial wastewaters (2020)

Stable and immobilized amine sorbents can simultaneously remove/recover cationic and oxyanionic toxic metals plus valuable rare earth elements from industrial and mining effluents prior to discharging into environmental water systems.
DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates (2021)

We propose DeepMetaHandles, a 3D conditional generative model based on mesh deformation. Given a collection of 3D meshes of a category and their deformation handles (control points), our method learns a set of meta-handles for each shape, which are represented as combinations of the given handles. The disentangled meta-handles factorize all the plausible deformations of the shape, while each of them corresponds to an intuitive deformation. A new deformation can then be generated by sampling the co-efficients of the meta-handles in a specific range. We employ biharmonic coordinates as the deformation function, which can smoothly propagate the control points’ translations to the entire mesh. To avoid learning zero deformaion as meta-handles, we incorporate a target-fitting module which deforms the input mesh to match a random target. To enhance deformations’ plausibility, we employ a soft-rasterizer-based discriminator that projects the meshes to a 2D space. Our experiments demonstrate the superiority of the generated deformations as well as the interpretability and consistency of the learned meta-handles. The code is available at https://github.com/Colin97/DeepMetaHandles.
Improving the Scalability of Parallel Jobs by adding Parallel Awareness to the Operating System (2003)

A parallel application benefits from scheduling policies that include a global perspective of the application's process working set. As the interactions among cooperating processes increase, mechanisms to ameliorate waiting within one or more of the processes become more important. In particular, collective operations such as barriers and reductions are extremely sensitive to even usually harmless events such as context switches among members of the process working set. For the last 18 months, we have been researching the impact of random short-lived interruptions such as timer-decrement processing and periodic daemon activity, and developing strategies to minimize their impact on large processor-count SPMD bulk-synchronous programming styles. We present a novel co-scheduling scheme for improving performance of fine-grain collective activities such as barriers and reductions, describe an implementation consisting of operating system kernel modifications and run-time system, and present a set of empirical results comparing the technique with traditional operating system scheduling. Our results indicate a speedup of over 300% on synchronizing collectives.
<title>Subpicosecond Proximity-Focused Visible Streak Camera Evaluation And Application</title> (1977)

Several years ago a new era in streak, cameras began with the introduction of an x-ray sensitive proximity mfocused streak tube. This device displayed. better than 3 ps resolution and a large dynamic range, making it a fundamental laser-fusion. diagnostic. The new tube is based upon parallel-photoelectron trajectories, rather than cross-over or pinhole electron optics used in virtually all other streak tubes. This eliminates a most of problems due to space charge buildup effects at the electron pinhole such as low dynamic resolution, limited dynamic range and unpredictable instrumental field distortion. In the old, tube instrumental errors are relate to distribution of photocathode illumination. in picosecond temporal application. Recently a visible variant of the proximity-focused tube design has been constructed. This camera displays all the advantages of its predecessor including high sensitivity, large dynamic range and a flat format making it ideal for digital readout. In addition, picosecond streaks of high statistical quality indicate the design limit has yet to be reached. TLe. new camera has already uncovered laser oscillator problems proving its utility as a basic laser diagnostic. Using this new "photon micrometer", a myriad. of new optical techniques such as high-accuracy three dimensional imaging are now possible.
Predicted sequence of the host‐protective immunogen of infectious bursal disease virus (1986)

The genome of Australian strain 002-73 of infectious bursal disease virus (IBDV) has been cloned as cDNA fragments into an expression library based on pUR plasmid vectors. Recombinant colonies were selected with a monoclonal antibody specific for the 32-kDa host-protective immunogen of IBDV and fully characterized by nucleotide sequence analysis. The amino acid sequence of several tryptic peptides derived from the native 32-kDa structural protein has confirmed the coding region assignment and nucleotide sequence data. We believe this to be the first published sequence of a birnavirus-encoded protein and these data may provide the basis for an effective subunit vaccine against IBDV.
Synergistic Effects of Inexpensive Mixed Metal Oxides for Catalytic Hydrothermal Liquefaction of Food Wastes (2020)

Industrial wastes and natural mixed oxide materials were evaluated as inexpensive heterogeneous catalysts for catalytic hydrothermal liquefaction (CHTL) of food wastes. Red mud and red clay achieved biocrude carbon yields of 47.0 and 39.5% with higher heating values (HHVs) of 40.2 and 37.7 MJ kg–1, respectively, which were much greater than those without the catalyst (biocrude carbon yield of 19.7% and HHV of 36.1 MJ kg–1). Biocrude characterization revealed that similar families of molecules were formed in the presence and absence of catalysts, implying that the main role of the catalyst is to promote rates of thermal reactions, leading to biocrude production without opening new pathways. The crystalline structures of inexpensive mixed oxides were stable under hydrothermal conditions, with modest calcium leaching (7.5%) and trace leaching of other metals. Using red clay or red mud resulted in >40% recovery of the energy in food waste as biocrude, greater than that obtained under noncatalytic conditions (18%) or from any individual constituent oxide (19–27%). The improved CHTL performance of the mixed metal oxides compared with single-metal oxides was attributed to the synergistic effects of base and acid sites present on catalyst surfaces; mixed oxides presented balanced densities of acids and bases, whereas the constituent oxides were either primarily acidic or primarily basic. The percent of energy recovered as biocrude oil was strongly correlated with the base-to-acid site density ratio, providing an important performance predictor for CHTL conversion of food waste to bioenergy.
Advanced packaging automation for opto-electronic systems (2005)

In this paper, we present a learning control algorithm used in our research of advanced opto-electronic automation, which yields high performance, low cost optoelectronic alignment and packaging through the use of intelligent control theory and system-level modeling. The learning loop technique is activated at a lower sampling frequency for specific and appropriate tasks, to improve the knowledge based control model. Our automation technique is based on constructing an a priori knowledge based model, specific to the assembled package's optical power propagation characteristics. From this model, a piece-wise linear inverse model is created and used in the "feed-forward" loop. This model can be updated for increased accuracy through the learning loop.
Incorporating Demand Resources into Optimal Dispatch (2008)

This paper presents a methodology for integrating demand response into optimal dispatch algorithms for electric power systems. Current methods to dispatch demand do not typically account for the impact of load shifting to later time periods. A critical component to properly dispatch demand resources is the inclusion of the rebound effect. Since the time scales for many demand response implementations are on the order of hours, once a demand resource has been dispatched, it is likely unavailable for re-dispatch during the same day. It is also likely that dispatched demand will increase in subsequent time periods. Incorporating the limited number of daily dispatches and the rebound effect into the optimal dispatch of demand resources is therefore necessary. This paper first provides a framework for incorporating demand resources into optimal dispatch and then presents a numeric example that compares optimal demand dispatch programs with and without the rebound effect. This comparison demonstrates the inefficiencies associated with a large-scale demand response program that does not take the rebound effect into account.
Regulation and genetic enhancement of beta-amylase production in Clostridium thermosulfurogenes (1985)

We studied the general mechanism for regulation of beta-amylase synthesis in Clostridium thermosulfurogenes. beta-Amylase was expressed at high levels only when the organism was grown on maltose or other carbohydrates containing maltose units. Three kinds of mutants altered in beta-amylase production were isolated by using nitrosoguanidine treatment, enrichment on 2-deoxyglucose, and selection of colonies with large clear zones on iodine-stained starch-glucose agar plates. beta-Amylase was produced only when maltose was added to cells growing on sucrose in wild-type and catabolite repression-resistant mutant strains, but the differential rate of enzyme synthesis in constitutive mutants was constant regardless of the presence of maltose. In carbon-limited chemostats of wild-type and catabolite repression-resistant mutant stains, beta-amylase was expressed on maltose but not on glucose or sucrose. beta-Amylase synthesis was immediately repressed by the addition of glucose. Therefore, we concluded that beta-amylase synthesis in C. thermosulfurogenes was inducible and subject to catabolite repression. The addition of cAMP did not eliminate the repressive effect of glucose. The mutants were generally characterized in terms of beta-amylase production, growth properties, fermentation product formation, and alterations in glucose isomerase and glucoamylase activities. A hyperproductive mutant produced eightfold more beta-amylase on starch medium than the wild type and more rapidly fermented starch to ethanol.
Clinical outcome of recurrent giant cell tumor of the extremity in the era before molecular target therapy: the Japanese Musculoskeletal Oncology Group study (2016)

We concluded that repetitive, thorough curettage with surgical adjuvant treatment resulted in a favorable rate of adjacent joint preservation (76.6 %), but recurettage inferred a risk of repetitive recurrences. Although the treatment strategy against the recurrent GCTB is being updated with denosumab, we believe that our data will be useful for future comparisons with the long-term clinical benefit of denosumab.
Fully self-aligned tri-layer a-Si:H TFT with ultra-thin active layer (2002)

To the best of our knowledge, the simple processing method described is the first fully self-aligned trilayer TFT with deposited n/sup +/ contacts. This process requires one less mask than our standard tri-layer process, with one additional unmasked backside exposure. In addition, these fully self-aligned TFTs have an ultra-thin a-Si:H layer that results in improved performance.
A scalable architecture for modular multiplication based on montgomery's algorithm (2003)

This paper presents a scalable architecture for the computation of modular multiplication, based on the Montgomery multiplication (MM) algorithm. A word-based version of MM is presented and used to explain the main concepts in the hardware design. The proposed multiplier is able to work with any precision of the input operands, limited only by memory or control constraints. Its architecture gives enough freedom to select the word size and the degree of parallelism to be used, according to the available area and/or desired performance. Design trade offs are analyzed in order to identify adequate hardware configurations for a given area or bandwidth requirement.
Acoustic Signal Processing for Anomaly Detection in Machine Room Environments (2016)

We present a system that uses acoustic signals to monitor equipment in commercial buildings, such as in machine rooms with HVAC system components. The system uses an ensemble of machine learning classifiers to effectively label signals as either "normal" or "abnormal". We collect audio clips from mobile devices in a machine room and an elevator shaft in the main building of IBM Research. We use these to learn the spectrum of normal sound signatures and identify abnormal sounds that fall outside this range. Abnormal sounds detected by the system are presented to the end user for anomaly confirmation. We also integrate a work-order system to automatically issue a repair work-order if the sound is abnormal.
<title>Use of localized performance-based functions for the specification and correction of hybrid imaging systems</title> (1992)

Localized wavefront performance analysis (LWPA) is a system that allows the full utilization of the system optical transfer function (OTF) for the specification and acceptance of hybrid imaging systems. We show that LWPA dictates the correction of wavefront errors with the greatest impact on critical imaging spatial frequencies. This is accomplished by the generation of an imaging performance map-analogous to a map of the optic pupil error-using a local OTF. The resulting performance map a function of transfer function spatial frequency is directly relatable to the primary viewing condition of the end-user. In addition to optimizing quality for the viewer it will be seen that the system has the potential for an improved matching of the optical and electronic bandpass of the imager and for the development of more realistic acceptance specifications. 1. LOCAL WAVEFRONT PERFORMANCE ANALYSIS The LWPA system generates a local optical quality factor (LOQF) in the form of a map analogous to that used for the presentation and evaluation of wavefront errors. In conjunction with the local phase transfer function (LPTF) it can be used for maximally efficient specification and correction of imaging system pupil errors. The LOQF and LPTF are respectively equivalent to the global modulation transfer function (MTF) and phase transfer function (PTF) parts of the OTF. The LPTF is related to difference of the average of the errors in separated regions of the pupil. Figure
SO/sub 2/ removal (1983)

Improved methods are provided for the efficient and economic removal of sulfur dioxide from gases, which comprise contacting the gas with neutralizing values obtained from type S hydrated lime, i.e. Calcined dolomite, slaked with water under elevated temperature and pressure. The type S hydrated dolomitic lime may be used in conjunction with a wet scrubber to provide base and neutralizing magnesium values, in a spray dryer or dry scrubber, or directly introduced into the boiler. The use of type S hydrated dolomitic lime greatly enhances the efficiency of sulfur dioxide removal, providing for enhanced utilization of base values and more rapid rate of reaction.
Extra-high oxygen addition as a new strengthening strategy to overcome strength/ductility trade-off in fully biocompatible hexagonal titanium alloys (2020)

A new titanium alloy family was developed aiming at creating a fully biocompatible alternative to titanium alloys currently on the dental implants market. Despite their hexagonal closepacked (HCP) single-phase structure, these Ti-Zr-O materials display an extremely interesting combination of properties. Zirconium is shown to be involved through a double contribution: on the one hand, a moderate but noticeable solid solution strengthening effect and on the other hand, a strong grain refinement. Therefore, the combination of both effects results in a beneficial strengthening of Ti-Zr-O alloys. However, the main remarkable aspect remains the outstanding hardening generated by extra high oxygen addition, occurring without any drop of ductility. The evolution of the dislocation network according to the oxygen content has been investigated to understand the underlying mechanisms in these Ti-Zr-O alloys, allowing to overcome the classical strength/ductility trade-off in commercial titanium alloys. Finally, the different perspectives of these findings in the field of biomedical and more generally in the field of titanium alloys are discussed.