gebhart/patrepeval huggingface dataset:
Metasurface-based multi-harmonic free-electron light source (2018)

Metasurfaces are subwavelength spatial variations in geometry and material where the structures are of negligible thickness compared to the wavelength of light and are optimized for far-field applications, such as controlling the wavefronts of electromagnetic waves. Here, we investigate the potential of the metasurface near-field profile, generated by an incident few-cycle pulse laser, to facilitate the generation of high-frequency light from free electrons. In particular, the metasurface near-field contains higher-order spatial harmonics that can be leveraged to generate multiple higher-harmonic X-ray frequency peaks. We show that the X-ray spectral profile can be arbitrarily shaped by controlling the metasurface geometry, the electron energy, and the incidence angle of the laser input. Using ab initio simulations, we predict bright and monoenergetic X-rays, achieving energies of 30 keV (with harmonics spaced by 3 keV) from 5-MeV electrons using 3.4-eV plasmon polaritons on a metasurface with a period of 85 nm. As an example, we present the design of a four-color X-ray source, a potential candidate for tabletop multicolor hard X-ray spectroscopy. Our developments could help pave the way for compact multi-harmonic sources of high-energy photons, which have potential applications in industry, medicine, and the fundamental sciences.
Two-Timescale Voltage Regulation in Distribution Grids Using Deep Reinforcement Learning (2019)

Frequent and sizeable voltage fluctuations become more pronounced with the increasing penetration of distributed renewable generation, and they considerably challenge distribution grids. Voltage regulation schemes so far have relied on either utility-owned devices (e.g., voltage transformers, and shunt capacitors), or more recently, smart power inverters that come with contemporary distributed generation units (e.g., photovoltaic systems, and wind turbines). Nonetheless, due to the distinct response times of those devices, as well as the discrete on-off commitment of capacitor units, joint control of both types of assets is challenging. In this context, a novel two-timescale voltage regulation scheme is developed here by coupling optimization with reinforcement learning advances. Shunt capacitors are configured on a slow timescale (e.g., daily basis) leveraging a deep reinforcement learning algorithm, while optimal setpoints of the power inverters are computed using a linearized distribution flow model on a fast timescale (e.g., every few seconds or minutes). Numerical experiments using a real-world 47-bus distribution feeder showcase the remarkable performance of the novel scheme.
Real-time data acquisition and telemetry based irrigation control system (2023)

A data acquisition and telemetry based control system for use in facilitating substantially real time management of an agricultural irrigation system. The soil moisture sensor includes a reader and a plurality of probes. The probes each include an electronic circuit having a moisture sensing capacitor in operative communication with the soil whose moisture is to be measured. Each probe also includes a receive/transmit antenna and the reader includes a transmit/receive antenna, so that as the reader passes near the probe, the reader transmits a digital excitation signal to the electronic circuit of the biodegradable probe via an inductive couple formed between the transmit/receive antenna of the reader and the receive/transmit coil of the probe. The electronic circuit uses an energy component of the excitation signal to generate a digital data signal which indicates the moisture content of the soil adjacent to the moisture sensing capacitor. The probe sends the data signal to the reader which then uses the data signal to develop a corresponding set of watering instructions which are then transmitted to a control module in communication with the irrigation system. The control module sends corresponding control signals to nozzles of the irrigation system causing the irrigation system to disperse water in a manner consistent with the moisture content data transmitted by the probes to the reader. Because the irrigation system moves continuously through the field to be irrigated, the moisture content data acquisition and resultant water dispersal by the irrigation system occur substantially in real time.
Enhanced Susceptibility inLNiO3Perovskites (L=La,Pr,Nd,Nd0.5Sm0.5) (2000)

The temperature dependence of the resistivity rho(T) and of the dc magnetic susceptibility chi(T) were measured on high-quality LNiO3 (L = La,Pr,Nd,Nd0.5Sm0.5) samples synthesized under high oxygen pressure. Subtraction of the rare-earth contribution to chi(T) allows the presentation of the evolution of the susceptibility of the NiO3 array from Pauli to Curie-Weiss paramagnetism with decreasing bandwidth. A metal-insulator transition occurring at a temperature T(t) = T(N) is first order for L = Pr and Nd; it becomes second order and produces no anomaly in chi(-1)(T) at a T(t)>T(N) for L = Nd0.5Sm0.5. In the antiferromagnetic domain T<T(N), the chi(T) curve for the NiO3 array resembles that of a paramagnet.
Diffraction-based overlay metrology using angular-multiplexed acquisition of dark-field digital holograms (2020)

In semiconductor device manufacturing, optical overlay metrology measures pattern placement between two layers in a chip with sub-nm precision. Continuous improvements in overlay metrology are needed to keep up with shrinking device dimensions in modern chips. We present first overlay metrology results using a novel off-axis dark-field digital holographic microscopy concept that acquires multiple holograms in parallel by angular multiplexing. We show that this concept reduces the impact of source intensity fluctuations on the noise in the measured overlay. With our setup we achieved an overlay reproducibility of 0.13 nm and measurements on overlay targets with known programmed overlay values showed good linearity of R<sup>2</sup>= 0.9993. Our data show potential for significant improvement and that digital holographic microscopy is a promising technique for future overlay metrology tools.
ChemInform Abstract: Phthalimide Resin Reagent for Efficient Mitsunobu Amino‐Dehydroxylation (1998)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Sparse, Quantized, Full Frame CNN for Low Power Embedded Devices (2017)

This paper presents methods to reduce the complexity of convolutional neural networks (CNN). These include: (1) A method to quickly and easily sparsify a given network. (2) Fine tune the sparse network to obtain the lost accuracy back (3) Quantize the network to be able to implement it using 8-bit fixed point multiplications efficiently. (4) We then show how an inference engine can be designed to take advantage of the sparsity. These techniques were applied to full frame semantic segmentation and the degradation due to the sparsity and quantization is found to be negligible. We show by analysis that the complexity reduction achieved is significant. Results of implementation on Texas Instruments TDA2x SoC [17] are presented. We have modified Caffe CNN framework to do the sparse, quantized training described in this paper. The source code for the training is made available at https://github.com/tidsp/caffe-jacinto.
NM 283, AN EFFICIENT PRODRUG OF THE POTENT ANTI-HCV AGENT 2′-C-METHYLCYTIDINE (2005)

In order to improve the oral bioavailability of 2-C-methylcytidine, a potent anti-HCV agent, the corresponding 3'-O-L-valinyl ester derivative (NM 283) has been synthesized Based on its ease of synthesis and its physicochemical properties, NM 283 has emerged as a promising antiviral drug for treatment of chronic HCV infection.
Hydrolysis of GTP by Sec4 protein plays an important role in vesicular transport and is stimulated by a GTPase-activating protein in Saccharomyces cerevisiae. (1992)

Sec4, a GTP-binding protein of the ras superfamily, is required for exocytosis in the budding yeast Saccharomyces cerevisiae. To test the role of GTP hydrolysis in Sec4 function, we constructed a mutation, Q-79----L, analogous to the oncogenic mutation of Q-61----L in Ras, in a region of Sec4 predicted to interact with the phosphoryl group of GTP. The sec4-leu79 mutation lowers the intrinsic hydrolysis rate to unmeasurable levels. A component of a yeast lysate specifically stimulates the hydrolysis of GTP by Sec4, while the rate of hydrolysis of GTP by Sec4-Leu79 can be stimulated by this GAP activity to only 30% of the stimulated hydrolysis rate of the wild-type protein. The decreased rate of hydrolysis results in the accumulation of the Sec4-Leu79 protein in its GTP-bound form in an overproducing yeast strain. The sec4-leu79 allele can function as the sole copy of sec4 in yeast cells. However, it causes recessive, cold-sensitive growth, a slowing of invertase secretion, and accumulation of secretory vesicles and displays synthetic lethality with a subset of other secretory mutants, indicative of a partial loss of Sec4 function. While the level of Ras function reflects the absolute level of GTP-bound protein, our results suggest that the ability of Sec4 to cycle between its GTP and GDP bound forms is important for its function in vesicular transport, supporting a mechanism for Sec4 function which is distinct from that of the Ras protein.
Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses (2021)

How related are the representations learned by neural language models, translation models, and language tagging tasks? We answer this question by adapting an encoder-decoder transfer learning method from computer vision to investigate the structure among 100 different feature spaces extracted from hidden representations of various networks trained on language tasks. This method reveals a low-dimensional structure where language models and translation models smoothly interpolate between word embeddings, syntactic and semantic tasks, and future word embeddings. We call this low-dimensional structure a language representation embedding because it encodes the relationships between representations needed to process language for a variety of NLP tasks. We find that this representation embedding can predict how well each individual feature space maps to human brain responses to natural language stimuli recorded using fMRI. Additionally, we find that the principal dimension of this structure can be used to create a metric which highlights the brain's natural language processing hierarchy. This suggests that the embedding captures some part of the brain's natural language representation structure.
Patient Demographics Are Associated with Differences in Prehospital Pain Management among Trauma Patients (2022)

Among patients with isolated traumatic injuries treated in a single, urban EMS system, African American and female patients were less likely to receive analgesia than White or male patients. Analgesics were given to a small percentage of patients who were eligible for treatment by protocol, and intravenous opioids were used in the vast majority patients who received treatment.
Chip-level microarchitecture trends (2004)

One year ago, in introducing IEEE Micro’s Hot Chips 14 special issue, I pointed out that features such as low power, reliability, security, and fault tolerance delivered to the customer at affordable cost might well serve as differentiating indices to the multidimensional entity called “system performance.” A year later, I cannot but overemphasize the emerging reality of that expectation. If anything, the focus on power dissipation as a primary design constraint has sharpened, with especially intense concerns about the static (leakage) component of power in future technologies. The basic uncertainty and variance of technology-related device and interconnect parameters (both across and within individually fabricated chips) that experts envisage are causing a major rethinking of the design stack (from high-level microarchitecture to physical design and layout). In addition, there are major implications in terms of design tool support for future, technology-aware microprocessor development. This year, the Hot Chips 15 special issue is guest edited by Michael Flynn and Pradeep Dubey. Their guest editors’ introduction covers the articles selected for publication in IEEE Micro. One of the trends in high-performance microprocessor chips is the increased level of on-chip integration that the technology has made available. IBM’s Power4 had previously started the trend of multicore designs with a dual-core chip multiprocessor offering. This issue of IEEE Micro includes an article on the follow-on chip called Power5, still a dual-core solution, but with each core supporting two independent program threads for a total of four concurrently executing threads per chip. Recent announcements by other vendors depict a similar trend, with an increasing emphasis on enhancing chip-level throughput through multiple cores and threads. In these future designs, each core or thread may not necessarily aim at delivering the highest frequency or performance that is achievable for the given technology. The power “wall” is definitely a factor that could accelerate this trend, since single-core frequencies might not scale up to meet prior trends. On the other hand, the chip-level power and area budgets (especially pertaining to leakage) place a natural limit on the number of cores for a given level of core complexity. This leads to some interesting power-performance tradeoffs that would balance single-thread performance against targets for chip-level throughput, working within a given power and cost budget. Yield and reliability aspects of the design equation (in an era of technological uncertainties) make the future space of design choices even more interesting! Of course, in some markets, singlethread performance might remain the primary driver of chip-level microarchitecture design. Here, to meet performance targets at affordable cost, cooling and packaging technologies must improve sufficiently to meet the challenge. I hope you enjoy reading the leadingedge articles in this special issue. They capture some of the latest advances, trends, and challenges in microprocessor design.
Power Amplifiers' Model Assessment and Memory Effects Intensity Quantification Using Memoryless Post-Compensation Technique (2008)

A novel approach for power amplifiers static nonlinearity characterization in the presence of memory effects is presented. A subsampling technique is used to reduce the bandwidth of the test signal without changing the waveform characteristics. This cancels the memory effects of the amplifier without affecting its static behavior. Memoryless AM/AM and AM/PM characteristics are measured as a function of the carrier frequency. This points out the contribution of the frequency dependency of the amplifier's static nonlinearity to its behavior under wideband signal drive. A memoryless post-compensation technique is then introduced to accurately assess the performance of several behavioral models. In fact, it is demonstrated that direct comparison of the measured output of the device-under-test with the estimated output does not provide reliable assessment of the model performance. Conversely, memoryless post-compensation efficiently differentiates the performance of these models. To provide a comprehensive approach for model validation and prototype performance evaluation, memory effects intensity metrics are introduced. These metrics are applied to evaluate the memory effects present in a 300-W peak power Doherty amplifier driven by various multicarrier wideband code division multiple access signals.
A study of the MVDR filter for acoustic echo suppression (2013)

This paper studies an echo suppression approach to reducing the undesired echoes that result from the acoustic coupling between a loudspeaker and a microphone in duplex voice communication. The approach consists of four basic steps. First, both the loudspeaker and microphone signals are partitioned into small overlapping frames. Second, each frame is transformed into the short-time Fourier transform (STFT) domain. Third, a minimum variance distortionless response (MVDR) filter is designed in each subband by explicitly using the interframe signal correlation. This MVDR filter is then used to estimate the echo signal and the obtained estimate is subsequently subtracted from the microphone signal. Finally, the time-domain processed signal is constructed using the overlap-add technique with the inverse STFT. Experiments are performed and the results demonstrate that this proposed method can achieve significant amount of echo suppression in practical room environments.
Lymphocytes mediate TNF-alpha-induced endothelial cell adhesion molecule expression: studies on SCID and RAG-1 mutant mice (1997)

TNF-alpha is known to elicit a rapid increase in the expression of specific endothelial cell adhesion molecules (ECAMs) within different vascular beds. The aim of this study was to determine whether lymphocytes contribute to the increased ECAM expression elicited by TNF-alpha. A dual radiolabeled mAb technique was used to quantify constitutive and TNF-alpha-induced expression of ICAM-1, VCAM-1, E-selectin, and P-selectin in different vascular beds (lung, heart, stomach, mesentery, small intestine, large intestine, and muscle) in wild-type and SCID mice. In reconstitution experiments, either whole splenocytes, T cell-enriched splenocytes, or B cell-enriched splenocytes were injected into SCID mice 48 h before TNF-alpha administration. Although the constitutive expression of ECAMs differed only slightly between wild-type and SCID mice, TNF-alpha-induced ECAM expression was markedly blunted in SCID mice compared with wild-type mice. This blunted response to TNF-alpha was also demonstrated for VCAM-1 in recombination activating gene (RAG)-1 mutant mice. Reconstitution studies revealed that administration of 50 x 10(6) splenocytes in SCID mice at 48 h before cytokine treatment restored the TNF-alpha-induced expression of VCAM-1 to levels normally observed in wild-type mice. Reconstitution with T cell- but not B cell-enriched splenocytes, also restored the TNF-alpha-induced expression of VCAM-1 in SCID mice to wild-type levels. These results implicate circulating T lymphocytes as modulators of the increased ECAM expression elicited by TNF-alpha.
The Microstructure of Poly(Isobutylene-co-p-Methylstyrene) by NMR Spectroscopy (1995)

Abstract The microstructure of isobutylene-para-methylstyrene (IB-pMeSt) copolymers was studied by NMR spectroscopy. 1H- and 13C-NMR spectra were used to obtain overall copolymer compositions. 13C-NMR signals were assigned in terms of triad monomer sequences, and triad distributions were obtained over a wide copolymer composition range. According to statistical tests, the IB-pMeSt copolymerization cannot be described by zero- (Bernoullian) or first-order Markov models because reactivity ratios r IB and r pMeSt were found to change with the monomer feed composition. Additional insight into the microstructure of IB-pMeSt copolymers was gained by calculating sequence numbers, run numbers, and sequence lengths from triad distributions. Further, the Kelen-Tüdös plot showed a distinct curvature indicating that the Kelen-Tüdös method, applied over the entire monomer feed composition range, cannot give meaningful reactivity ratios for this monomer pair. Evidently the simple two-parameter Mayo-Lewis model is inadequate to describe the IB-pMeSt copolymerization system.
A Revolution: Belief Propagation in Graphs with Cycles (1997)

Until recently, artificial intelligence researchers have frowned upon the application of probability propagation in Bayesian belief networks that have cycles. The probability propagation algorithm is only exact in networks that are cycle-free. However, it has recently been discovered that the two best error-correcting decoding algorithms are actually performing probability propagation in belief networks with cycles.
CCR1 and CC Chemokine Ligand 5 Interactions Exacerbate Innate Immune Responses during Sepsis (2004)

CCR1 has previously been shown to play important roles in leukocyte trafficking, pathogen clearance, and the type 1/type 2 cytokine balance, although very little is known about its role in the host response during sepsis. In a cecal ligation and puncture model of septic peritonitis, CCR1-deficient (CCR1(-/-)) mice were significantly protected from the lethal effects of sepsis when compared with wild-type (WT) controls. The peritoneal and systemic cytokine profile in CCR1(-/-) mice was characterized by a robust, but short-lived and regulated antibacterial response. CCR1 expression was not required for leukocyte recruitment, suggesting critical differences extant in the activation of WT and CCR1(-/-) resident or recruited peritoneal cells during sepsis. Peritoneal macrophages isolated from naive CCR1(-/-) mice clearly demonstrated enhanced cytokine/chemokine generation and antibacterial responses compared with similarly treated WT macrophages. CCR1 and CCL5 interactions markedly altered the inflammatory response in vivo and in vitro. Administration of CCL5 increased sepsis-induced lethality in WT mice, whereas neutralization of CCL5 improved survival. CCL5 acted in a CCR1-dependent manner to augment production of IFN-gamma and MIP-2 to damaging levels. These data illustrate that the interaction between CCR1 and CCL5 modulates the innate immune response during sepsis, and both represent potential targets for therapeutic intervention.
Modeling of HVAC system in data center with super-multipoint temperature sensing technology (2014)

In this paper, we consider a server cooling system in a data center with fans and a super-multipoint temperature sensing technology using optimal time-domain reflectometry of optical fiber. The sensing system was developed to visualize the temperature distribution of the room in real time, and it can also be a key technology to control the distribution in order to reduce total power consumption in data centers. In this paper, we first present a concept of the fan control system. The objective of the system is to uniformize the rack air inlet temperature distribution in the presence of heat from each server. Since the control scheme requires a dynamical model of the temperature variations in the room, this paper mainly addresses the modeling. The challenge of the modeling stems from a large volume of data provided by the sensing system. It is computationally hard to directly apply standard identification techniques to the data. We thus present a two-stage reduction scheme of the output dimension using the concept of so-called mutual information. The effectiveness of the proposed scheme is finally demonstrated using real data.