gebhart/patrepeval huggingface dataset:
On interacting encoders and decoders in multiuser settings (2004)

In multiuser communication systems the exchange of some number of rate-limited messages both between encoders, and between decoders, can enlarge the achievable rate region. We consider interaction between a pair of Slepian-Wolf encoders, and a pair of deterministic broadcast channel decoders. For these systems, a single one-way message is sufficient. More generally, we make connections to relay channels and consider how to quantize data for relaying.
Flexible All-Fiber Generation of Ultra-Wideband Signals via Pulse Compression and Differential Detection (2009)

A flexible and simple scheme for generating ultra-wideband waveforms is proposed, using pulse compression in highly nonlinear fiber and differential detection. Center frequencies of 25 GHz, as well as FCC mask compliant waveforms, are demonstrated.
Acousto-optic correlation techniques (1990)

A description is given of the theory of operation of acousto-optic (AO) devices and correlators in general. Two different applications of twin Bragg cell space-integrating correlator/convolvers are then discussed. In the first a heterodyning technique is employed in which light at different optical frequencies is mixed to give the convolution of the signals applied to the two AO cells. The system is configured to implement the first two stages of the multiply-convolve-multiply algorithm so that the power spectrum of the input-signal is obtained. The second system is a novel nonheterodyning correlator/convolver. It is shown that by amplitude modulating the signals on to the Bragg cell carrier frequency using double sideband large carrier modulation, the full correlation function including amplitude and phase information, may be extracted by measuring only the intensity of light at the output of the system.
Feedforward excitation of the hippocampus by afferents from the entorhinal cortex: redefinition of the role of the trisynaptic pathway. (1990)

For the past 3 decades, functional characterizations of the hippocampus have emphasized its intrinsic trisynaptic circuitry, which consists of successive excitatory projections from the entorhinal cortex to the dentate gyrus, from granule cells of the dentate to the CA3/4 pyramidal cell region, and from CA3/4 to the CA1/2 pyramidal cell region. Despite unequivocal anatomical evidence for a monosynaptic projection from entorhinal to CA3 and CA1/2, few in vivo electrophysiological studies of the direct pathway have been reported. In the experiments presented here, we stimulated axons of entorhinal cortical neurons in vivo and recorded evoked single unit and population spike responses in the dentate, CA3, and CA1 of hippocampus, to determine if pyramidal cells are driven primarily via the monosynaptic or trisynaptic pathways. Our results show that neurons within the three subfields of the hippocampus discharge simultaneously in response to input from a given subpopulation of entorhinal cortical neurons and that the initial monosynaptic excitation of pyramidal cells then is followed by weaker excitatory volleys transmitted through the trisynaptic pathway. In addition, we found that responses of CA3 pyramidal cells often precede those of dentate granule cells and that excitation of CA3 and CA1 pyramidal cells can occur in the absence of granule cell excitation. In total, these results argue for a different conceptualization of the functional organization of the hippocampus with respect to the propagation of activity through its intrinsic pathways: input from the entorhinal cortex initiates a two-phase feedforward excitation of pyramidal cells, with the dentate gyrus providing feedforward excitation of CA3, and with both the dentate and CA3 providing feedforward excitation of CA1.
A packetized direct load control mechanism for demand side management (2012)

Electricity peaks can be harmful to grid stability and result in additional generation costs to balance supply with demand. By developing a network of smart appliances together with a quasi-decentralized control protocol, direct load control (DLC) provides an opportunity to reduce peak consumption by directly controlling the on/off switch of the networked appliances. This paper proposes a packetized DLC (PDLC) solution that is illustrated by an application to air conditioning temperature control. Here the term packetized refers to a fixed time energy usage authorization. The consumers in each room choose their preferred set point, and then an operator of the local appliance pool will determine the comfort band around the set point. We use a thermal dynamic model to investigate the duty cycle of thermostatic appliances. Three theorems are proposed in this paper. The first two theorems evaluate the performance of the PDLC in both transient and steady state operation. The first theorem proves that the average room temperature would converge to the average room set point with fixed number of packets applied in each discrete interval. The second theorem proves that the PDLC solution guarantees to control the temperature of all the rooms within their individual comfort bands. The third theorem proposes an allocation method to link the results in theorem 1 and assumptions in theorem 2 such that the overall PDLC solution works. The direct result of the theorems is that we can reduce the consumption oscillation that occurs when no control is applied. Simulation is provided to verify theoretical results.
Attempto - From Specifications in Controlled Natural Language towards Executable Specifications (1996)

Deriving formal specifications from informal requirements is difficult since one has to take into account the disparate conceptual worlds of the application domain and of software development. To bridge the conceptual gap we propose controlled natural language as a textual view on formal specifications in logic. The specification language Attempto Controlled English (ACE) is a subset of natural language that can be accurately and efficiently processed by a computer, but is expressive enough to allow natural usage. The Attempto system translates specifications in ACE into discourse representation structures and into Prolog. The resulting knowledge base can be queried in ACE for verification, and it can be executed for simulation, prototyping and validation of the specification.
HEAT TRANSFER AND FLUID FLOW IN A NONISOTHERMAL CONSTRAINED VAPOR BUBBLE (2000)

A Constrained Vapor Bubble (CVB) with a relatively large Bond number formed by partially underfilling liquid in an evacuated cavity is capable of high thermal conductance. Il operates on the principle of closed loop phase-change along with capillarity to circulate the working fluid. Analytical investigations were conducted to compare with existing experimental data. A steady-state fluid flow model combined with a two-dimensional heat transfer model was developed and solved to yield key operating parameters ( i.e., temperature and liquid meniscus curvature) of the CVB. The modeling results of the outside wall temperature in the evaporator were found to agree well with the measured experimental data. An area average heat transfer coefficient was used to characterize the heat transfer on the inside wall of the evaporator. The value of this heat transfer coefficient was found to increase with the heat flow rate. The fluid flow model with the heat transfer model in the evaporator to provide the energy balance was used successfully to fit the experimental curvature data. The mass flow rate in the bottom corners of the CVB was found to be higher than that in the top corners due to the gravitational body force.
Demonstration of Synaptic Behaviors and Resistive Switching Characterizations by Proton Exchange Reactions in Silicon Oxide (2016)

We realize a device with biological synaptic behaviors by integrating silicon oxide (SiO(x)) resistive switching memory with Si diodes. Minimal synaptic power consumption due to sneak-path current is achieved and the capability for spike-induced synaptic behaviors is demonstrated, representing critical milestones for the use of SiO2-based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation (LTP), long-term depression (LTD) and spike-timing dependent plasticity (STDP) are demonstrated systematically using a comprehensive analysis of spike-induced waveforms, and represent interesting potential applications for SiO(x)-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from (SiH)2 to generate the hydrogen bridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with large-scale CMOS manufacturing technology.
Neutralizing activity of antibodies against the major herpes simplex virus type 1 glycoproteins (1989)

Abstract The specificity and neutralizing activity of antibodies against the major herpes simplex virus type 1 (HSV‐1) glycoproteins were tested in serum samples of patients with a history of HSV‐1 infection. By preabsorption of sera to preparations of native and denatured HSV‐1 proteins, followed by immunoblotting and microneutralization, it was shown that the majority of neutralizing antibodies are directed against denaturation‐sensitive epitopes. Furthermore, preabsorption of sera to proteins of viral ts and deletion mutants revealed that antibodies specific for gB, gC, and gE had a low neutralizing activity. These results suggest a major role of anti‐gD in neutralization of viral infectivity. In addition, it was shown that antibodies directed against the gB monomer were distinct from antibodies against the gB homodimers. The latter, however, did not reveal any measurable neutralizing activity.
Distored-wave Born calculations of V–V energy transfer (1978)

The temperature dependence of the cross section for intermolecular vibration–vibration (V–V) energy transfer processes is calculated in the distorted-wave Born approximation with a thermal average over relative velocities. The molecular elastic scattering is assumed to be dominated by a hard core from which the distorted wave functions are calculated. Different forms of the potential (Vin) responsible for the V–V energy transfer have been used in the calculation. For near resonance a positive temperature dependence of the V–V cross section is found regardless of whether Vin is an exponential function (’’short range’’) or an inverse power function 1/r5 (’’long range’’). It is demonstrated numerically that the temperature dependence is very sensitive to the magnitude of energy defect ΔE. In general, the positive temperature dependence becomes negative when ΔE becomes sufficiently large. The accuracy of various numerical approximations used in the literature is also investigated.
Biomembrane-Modified Field Effect Transistors for Sensitive and Quantitative Detection of Biological Toxins and Pathogens (2019)

The efforts of detecting bioactive targets with complex, dynamic, and unknown molecular profiles have inspired the development of various biosensor platforms. Herein, we report a cell-membrane-modified field effect transistor (FET) as a function-based nanosensor for the detection and quantitative measurement of numerous toxins and biological samples. By coating carbon nanotube FETs with natural red blood cell membranes, the resulting biomimetic nanosensor can selectively interact with and absorb broad-spectrum hemolytic toxins regardless of their molecular structures. Toxin-biomembrane interactions alter the local charge distribution at the FET surface in an ultrasensitive and concentration-dependent manner, resulting in a detection limit down to the femtomolar (fM) range. Accurate and quantitative measurements are enabled via a built-in calibration mechanism of the sensor, which overcomes batch-to-batch fabrication variations, and are demonstrated using three distinct toxins and various complex bacterial supernatants. The measured signals of bacterium-secreted proteins correlate linearly with the actual bacterial numbers, making the biosensor a nontraditional approach to rapidly detecting bacterial concentrations without a need to count bacterial colonies.
Strategic Capacity Rationing when Customers Learn (2010)

Consider a firm that sells products over repeated seasons, each of which includes a full-price period and a markdown period. The firm may deliberately understock products in the markdown period to induce high-value customers to purchase early at full price. Customers cannot perfectly anticipate availability. Instead, they use observed past capacities to form capacity expectations according to a heuristic smoothing rule. Based on their expectations of capacity, customers decide to buy either in the full-price period or in the markdown period. We embed this customer learning process in a dynamic program of the firm's capacity choices over time. One main result demonstrates the existence of a monotone optimal path of customers' expectations, which converges to either a rationing equilibrium or a low-price-only equilibrium. Further, there exists a critical value of capacity expectation such that the market converges to a rationing equilibrium if customers' initial expectations are less than that critical value; otherwise, a low-price-only equilibrium is the limiting outcome. These results show how firms can be stuck with unprofitable selling strategies from incumbent customer expectations. We also examine numerically how this critical value is affected by the firm's discount factor and customers' learning speed and risk aversion. Last, we show that the equilibrium under adaptive learning converges to that under rational expectations as the firm's discount factor approaches one.
Sketch-Based Retrieval of Document Illustrations and Regions of Interest (2013)

In this paper we present a novel approach towards retrieval of documents with pictorial data. Many prior works focused on word-spotting and text-based retrieval, but none of these techniques handled the retrieval of pictorial part of documents. In this paper, we present a new method that allows users to retrieve any visual data from documents, based on a sketch example. It mainly emphasizes all three main aspects of a visual retrieval system: feature representation, indexing and retrieval. Especially we focus on the design of salient descriptors, capable of capturing unique mapping from sketched images to document illustrations. We evaluate several approaches towards feature representation and indexing, with the aim to maximize the performance of our method. Our proposed technique is highly useful to complement word-spotting technique, when the indexed documents are composed of mixture of visual and textual data. This technique has shown promising results, both on pictorial data automatically extracted from documents as well for those selected by users as regions of interest.
A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings (2023)

Cortical function emerges from the interactions of multi-scale networks that may be studied at a high level using neural mass models (NMM) that represent the mean activity of large numbers of neurons. Here, we provide first a new framework called laminar NMM, or LaNMM for short, where we combine conduction physics with NMMs to simulate electrophysiological measurements. Then, we employ this framework to infer the location of oscillatory generators from laminar-resolved data collected from the prefrontal cortex in the macaque monkey. We define a minimal model capable of generating coupled slow and fast oscillations, and we optimize LaNMM-specific parameters to fit multi-contact recordings. We rank the candidate models using an optimization function that evaluates the match between the functional connectivity (FC) of the model and data, where FC is defined by the covariance between bipolar voltage measurements at different cortical depths. The family of best solutions reproduces the FC of the observed electrophysiology by selecting locations of pyramidal cells and their synapses that result in the generation of fast activity at superficial layers and slow activity across most depths, in line with recent literature proposals. In closing, we discuss how this hybrid modeling framework can be more generally used to infer cortical circuitry.
LES of Flow Processes in an SI Engine Using Two Approaches: OpenFoam and PsiPhi (2014)

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;In this study two different simulation approaches to large eddy simulation of spark-ignition engines are compared. Additionally, some of the simulation results are compared to experimentally obtained in-cylinder velocity measurements. The first approach applies unstructured grids with an automated meshing procedure, using OpenFoam and Lib-ICE with a mapping approach. The second approach applies the efficient in-house code PsiPhi on equidistant, Cartesian grids, representing walls by immersed boundaries, where the moving piston and valves are described as topologically connected groups of Lagrangian particles. In the experiments, two-dimensional two-component particle image velocimetry is applied in the central tumble plane of the cylinder of an optically accessible engine. Good agreement between numerical results and experiment are obtained by both approaches.&lt;/div&gt;&lt;/div&gt;
T‐0901317, a synthetic liver X receptor ligand, inhibits development of atherosclerosis in LDL receptor‐deficient mice (2002)

Liver X receptors (LXR alpha and LXR beta) are nuclear receptors, which are important regulators of cholesterol and lipid metabolism. LXRs control genes involved in cholesterol efflux in macrophages, bile acid synthesis in liver and intestinal cholesterol absorption. LXRs also regulate genes participating in lipogenesis. To determine whether the activation of LXR promotes or inhibits development of atherosclerosis, T-0901317, a synthetic LXR ligand, was administered to low density lipoprotein receptor (LDLR)(-/-) mice. T-0901317 significantly reduced the atherosclerotic lesions in LDLR(-/-) mice without affecting plasma total cholesterol levels. This anti-atherogenic effect correlated with the plasma concentration of T-0901317, but not with high density lipoprotein cholesterol, which was increased by T-0901317. In addition, we observed that T-0901317 increased expression of ATP binding cassette A1 in the lesions in LDLR(-/-) mice as well as in mouse peritoneal macrophages. T-0901317 also significantly induced cholesterol efflux activity in peritoneal macrophages. These results suggest that LXR ligands may be useful therapeutic agents for the treatment of atherosclerosis.
Fumonisin B2production byAspergillus nigerin Thai coffee beans (2009)

During 2006 and 2007, a total of 64 Thai dried coffee bean samples (Coffea arabica) from two growing sites in Chiangmai Province and 32 Thai dried coffee bean samples (Coffea canephora) from two growing sites in Chumporn Province, Thailand, were collected and assessed for fumonisin contamination by black Aspergilli. No Fusarium species known to produce fumonisin were detected, but black Aspergilli had high incidences on both Arabica and Robusta Thai coffee beans. Liquid chromatography (LC) with high-resolution mass spectrometric (HRMS) detection showed that 67% of Aspergillus niger isolates from coffee beans were capable of producing fumonisins B(2) (FB(2)) and B(4) when grown on Czapek Yeast Agar with 5% NaCl. Small amounts (1-9.7 ng g(-1)) of FB(2) were detected in seven of 12 selected coffee samples after ion-exchange purification and LC-MS/MS detection. Two samples also contained FB(4). This is the first record of freshly isolated A. niger strains producing fumonisins and the first report on the natural occurrence of FB(2) and FB(4) in coffee.
Non-metric affinity propagation for unsupervised image categorization (2007)

Unsupervised categorization of images or image parts is often needed for image and video summarization or as a preprocessing step in supervised methods for classification, tracking and segmentation. While many metric-based techniques have been applied to this problem in the vision community, often, the most natural measures of similarity (e.g., number of matching SIFT features) between pairs of images or image parts is non-metric. Unsupervised categorization by identifying a subset of representative exemplars can be efficiently performed with the recently-proposed 'affinity propagation' algorithm. In contrast to k-centers clustering, which iteratively refines an initial randomly-chosen set of exemplars, affinity propagation simultaneously considers all data points as potential exemplars and iteratively exchanges messages between data points until a good solution emerges. When applied to the Olivetti face data set using a translation-invariant non-metric similarity, affinity propagation achieves a much lower reconstruction error and nearly halves the classification error rate, compared to state-of-the-art techniques. For the more challenging problem of unsupervised categorization of images from the CaltechlOl data set, we derived non-metric similarities between pairs of images by matching SIFT features. Affinity propagation successfully identifies meaningful categories, which provide a natural summarization of the training images and can be used to classify new input images.
Wind power forecasting considering wind turbine condition (2015)

In recent years, rapid growth of the wind power all around the world highlights the requirement of developing accurate wind power forecasting method. Since the wind power generation mainly relies on wind speed and wind turbine condition, a novel wind power forecasting strategy considering wind turbine condition is proposed in this paper. The proposed strategy which can predict several-hours-ahead wind power is based on wavelet method and Support Vector Machine method. Real-world dataset is adopted to evaluate the efficiency of the proposed method. Simulation results show that the proposed method can improve wind power forecasting accuracy compared with traditional forecasting strategy.
Endochitinase, a mannan-associated enzyme from Saccharomyces cerevisiae. (1982)

A chitinase was extracted with digitonin from intact yeast cells and purified by adsorption-digestion on chitin. The purified enzyme liberates oligosaccharides of various sizes from chitin, thus behaving as an endochitinase. As found with other chitinases, the yeast enzyme is much more active on nascent chitin, i.e. the chitin formed in the same reaction mixture by the corresponding synthetase, than on preformed polysaccharide. The enzyme has a very low pH optimum, about pH 2.5, and is quite stable at pH 3. Polyacrylamide gel electrophoresis of different preparations of purified chitinase revealed a variable number of protein bands, whose pattern often changed after storage of the enzyme. The distribution of activity in the gel matched that of the stainable material. Association of the chitinase with mannan is indicated by the following results: (a) coincidence in Coomassie blue-staining and periodate-Schiff-staining bands after disc gel electrophoresis; (b) adsorption of the activity on concanavalin A-Sepharose and elution with alpha-methylmanoside; (c) precipitation of the chitinase with appropriate antimannan sera. A carbohydrate content of approximately 18% was found in a trichloroacetic acid-precipitated sample of purified enzyme. Protein and mannan were not dissociated by boiling with sodium dodecyl sulfate, urea, and beta-mercaptoethanol. It could not, however, be conclusively established whether protein and carbohydrate are covalently linked, because the chitinase is resistant to endo-beta-N-acetyl-glucosaminidase.