gebhart/patrepeval huggingface dataset:
Avalanche criticalities and elastic and calorimetric anomalies of the transition from cubic Cu-Al-Ni to a mixture of18Rand2Hstructures (2016)

We studied the two-step martensitic transition of a Cu-Al-Ni shape-memory alloy by calorimetry, acoustic emission (AE), and resonant ultrasound spectroscopy (RUS) measurements. The transition occurs under cooling from the cubic $(\ensuremath{\beta}, Fm3m)$ parent phase near 242 K to a mixture of orthorhombic $2H$ and monoclinic $18R$ phases. Heating leads first to the back transformation of small $18R$ domains to $\ensuremath{\beta}$ and/or $2H$ near 255 K, and then to the transformation $2H$ to $\ensuremath{\beta}$ near 280 K. The total transformation enthalpy is $\mathrm{\ensuremath{\Delta}}{H}_{T}=328\ifmmode\pm\else\textpm\fi{}10$ J/mol and is observed as one large latent heat peak under cooling. The back-transformation entropy under heating breaks down into a large component $18R$ to $\ensuremath{\beta}$ at 255 K and a smaller, smeared component of the transformation $2H$ to $\ensuremath{\beta}$ near 280 K. The proportions inside the phase mixture depend on the thermal history of the sample. The elastic response of the sample is dominated by large elastic softening during cooling. The weakening of the elastic shear modulus shows a peak at 242 K, which is typical for the formation of complex microstructures. Cooling the sample further leads to additional changes of the microstructure and domain wall freezing, which is seen by gradual elastic hardening and increasing damping of the RUS signal. Heating from 220 K to room temperature leads to elastic anomalies due to the initial transformation, which is now shifted to high temperatures. The transition is smeared over a wider temperature interval and shows strong elastic damping. The shear modulus of the cubic phase is recovered at 280 K. The phase transformation leads to avalanches, which were recorded by AE and by time-resolved calorimetry. The cooling transition shows very extended avalanche signals in calorimetry with power-law distributions. Cooling and heating runs show AE signals over a large temperature interval above 260 K. Splitting the transformation into two martensite phases leads to power-law exponents $\ensuremath{\varepsilon}\ensuremath{\sim}2$ $(\ensuremath{\beta}\ensuremath{\leftrightarrow} 18R)$ and $\ensuremath{\varepsilon}\ensuremath{\sim}1.5$ $(\ensuremath{\beta}\ensuremath{\leftrightarrow} 2H)$ while the phase mixture shows an effective AE exponent of 1.7.
LEAD microscopy performing at 100’s kHz frames per second for nonlinear imaging and 3D-imaging flow cytometry (Conference Presentation) (2023)

I will present a new fluorescence imaging method called LEAD (line excitation array detection) microscopy, capable of providing 0.8 million frames per second. This method performs line-scanning of excitation laser beam using a chirped signal-driven longitudinal acousto-optic deflector to create a virtual light-sheet, and images the field-of-view with a linear photomultiplier tube array to generate a 66×14 pixel frame each scan cycle. I will present an implementation of the LEAD microscopy as a blur-free 3D imaging flow cytometer with 3.5-micron resolution and signal-to-background ratios >200. I will also present its conceptual implementation as an ultrafast two-photon LEAD microscopy (2p-LEAD).
Machine learning algorithms for predicting occupants' behaviour in the manual control of windows for cross-ventilation in homes (2020)

The manual control of windows is one of the common adaptive behaviours for occupants to adjust their indoor environment in homes. The cross-ventilation by the window opening provides a useful tool to control the thermal comfort and indoor air quality in homes. The objective of this study was to develop a modelling methodology for predicting individual occupant's behaviour relating to the manual control of windows by using machine learning algorithms. The proposed six machine learning algorithms were trained by the field monitoring data of 23 sample homes. The predictive performance of the machine learning algorithms was analysed. The algorithms predicted the occupant's behaviour more precisely compared with the logistic model. Among the algorithms, K-Nearest Neighbours (KNN) shows the best fitness with the monitored data set. The driving parameters of the manual control of windows in each sample home can be clearly drawn by the algorithms. The proposed machine learning algorithms can help to understand the influence of the occupant's behaviour on the indoor environment in buildings.
SDP-quality bounds via convex quadratic relaxations for global\n optimization of mixed-integer quadratic programs (2021)

We consider the global optimization of nonconvex mixed-integer quadratic\nprograms with linear equality constraints. In particular, we present a new\nclass of convex quadratic relaxations which are derived via quadratic cuts. To\nconstruct these quadratic cuts, we solve a separation problem involving a\nlinear matrix inequality with a special structure that allows the use of\nspecialized solution algorithms. Our quadratic cuts are nonconvex, but define a\nconvex feasible set when intersected with the equality constraints. We show\nthat our relaxations are an outer-approximation of a semi-infinite convex\nprogram which under certain conditions is equivalent to a well-known\nsemidefinite program relaxation. The new relaxations are implemented in the\nglobal optimization solver BARON, and tested by conducting numerical\nexperiments on a large collection of problems. Results demonstrate that, for\nour test problems, these relaxations lead to a significant improvement in the\nperformance of BARON.\n
A neural network model to configure maps for a satellite communication network (2002)

A self-configurable satellite communication network that can be dynamically configured to different maps, to best meet the network requirements, by means of a modified Kohonen self-organization procedure is described. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is an analysis of the discrepancy between the chosen exemplar map and the state of the network, and adaptively modifies the chosen exemplar map to conform closely to the network requirement (input data pattern) by Kohonen's self-organization procedure. On the basis of certain performance criteria, it is decided in the third stage whether a new map is generated to replace the original map. Experimental results are presented to demonstrate that the self-organization model can dynamically configure maps for a satellite communication network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Environmental applications of membrane introduction mass spectrometry (2002)

The purpose of this review is to highlight the versatility of membrane introduction mass spectrometry (MIMS) in environmental applications, summarize the measurements of environmental volatile organic compounds (VOCs) accomplished using MIMS, present developments in the detection of semi-volatile organic compounds (SVOCs) and forecast possible future directions of MIMS in environmental applications.
Diamonds are a Chemist's Best Friend: Diamondoid Chemistry Beyond Adamantane (2007)

Marilyn Monroe knew that "diamonds are a girl's best friend" but, in the meantime, many chemists have realized that they are also extremely attractive objects in contemporary chemistry. The chemist's diamonds are usually quite small (herein: nanometer-sized "diamondoids") and as a result of their unique structure are unusual chemical building blocks. Since lower diamondoids (up to triamantane) have recently become available in large amounts from petroleum and higher diamondoids (starting from tetramantane) are now also accessible from crude oil new research involving them has begun to emerge. Having well-defined structures makes these cage compounds so special compared to other nanometer-scale diamonds. Selective and high-yielding synthetic approaches to the functionalization of diamondoids gives derivatives that can find applications in, for example, polymers, coating materials, drugs, and molecular electronics.
Novel CMOS Schmitt trigger with controllable hysteresis (1992)

A novel CMOS Schmitt trigger with controllable hysteresis based on the standard CMOS circuit with three transistor pairs is proposed. With the addition of only one transistor pair a Schmitt trigger with two selectable hysteresis characteristics can be achieved. Simulation results are compared with theory and a possible application is presented.
A Mutation Causing Imidazolinone Resistance Maps to the Csr1 Locus of Arabidopsis thaliana (1990)

A mutant of Arabidopsis thaliana, two hundred times more resistant to the imidazolinone herbicide imazapyr than wild-type plants, was isolated by direct selection of seedlings from a mutagenized population. Genetic analysis showed that resistance is due to a single dominant nuclear mutation that could not be separated by recombination from a mutation in the CSR1 gene encoding acetohydroxy acid synthase. Acetohydroxy acid synthase activity in extracts isolated from the mutant was 1000-fold more resistant to inhibition by imazapyr than that of the wild type. The resistant enzyme activity cosegregated with whole plant resistance. These data strongly suggest that the mutation is an allele of CSR1 encoding an imazapyr-resistant AHAS.
Vanadium‐cyclohexanone–initiated graft copolymerization of methyl methacrylate onto jute fibers (1986)

Abstract Graft copolymerization of methyl methacrylate (MMA) was carried out on jute fibers using a V 5+ ‐cyclohexanone redox initiator system. The effect of the concentration of acid, monomer, and V 5+ on graft yield have been studied. In order to obtain optimum conditions of grafting, the effects of temperature, acid, reaction medium, solvent, and some inorganic salts on graft yield have been investigated. The most remarkable features of the investigation include the proposition of a mechanism and derivation of rate expression for the grafting process. More than 100% grafting could be achieved with the present system.
An Endoplasmic Reticulum-Specific Cyclophilin (1991)

Cyclophilin is a ubiquitously expressed cytosolic peptidyl-prolyl cis-trans isomerase that is inhibited by the immunosuppressive drug cyclosporin A. A degenerate oligonucleotide based on a conserved cyclophilin sequence was used to isolate cDNA clones representing a ubiquitously expressed mRNA from mice and humans. This mRNA encodes a novel 20-kDa protein, CPH2, that shares 64% sequence identity with cyclophilin. Bacterially expressed CPH2 binds cyclosporin A and is a cyclosporin A-inhibitable peptidyl-prolyl cis-trans isomerase. Cell fractionation of rat liver followed by Western blot (immunoblot) analysis indicated that CPH2 is not cytosolic but rather is located exclusively in the endoplasmic reticulum. These results suggest that cyclosporin A mediates its effect on cells through more than one cyclophilin and that cyclosporin A-induced misfolding of T-cell membrane proteins normally mediated by CPH2 plays a role in immunosuppression.
E.S.R. spectrum of BH3-· in gamma-irradiated tetramethylammonium borohydride (1971)

(1971). E.S.R. spectrum of BH3 -· in gamma-irradiated tetramethylammonium borohydride. Molecular Physics: Vol. 20, No. 2, pp. 375-378.
Degradation of splicing factor SRSF3 contributes to progressive liver disease (2019)

Serine rich splicing factor 3 (SRSF3) plays a critical role in liver function and its loss promotes chronic liver damage and regeneration. As a consequence, genetic deletion of SRSF3 in hepatocytes caused progressive liver disease and ultimately led to hepatocellular carcinoma. Here we show that SRSF3 is decreased in human liver samples with non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), or cirrhosis that was associated with alterations in RNA splicing of known SRSF3 target genes. Hepatic SRSF3 expression was similarly decreased and RNA splicing dysregulated in mouse models of NAFLD and NASH. We showed that palmitic acid-induced oxidative stress caused conjugation of the ubiquitin like NEDD8 protein to SRSF3 and proteasome mediated degradation. SRSF3 was selectively neddylated at lysine11 and mutation of this residue (SRSF3-K11R) was sufficient to prevent both SRSF3 degradation and alterations in RNA splicing. Finally prevention of SRSF3 degradation in vivo partially protected mice from hepatic steatosis, fibrosis and inflammation. These results highlight a neddylation-dependent mechanism regulating gene expression in the liver that is disrupted in early metabolic liver disease and may contribute to the progression to NASH, cirrhosis and ultimately hepatocellular carcinoma.
Resiliency of automotive object detection networks on GPU architectures (2019)

Safety is the most important aspect of an autonomous driving platform. Deep neural networks (DNNs) play an increasingly critical role in localization, perception, and control in these systems. The object detection and classification inference are of particular importance to construct a precise picture of a vehicle's surrounding objects. Graphics Processing Units (GPU) are well-suited to accelerate such DNN-based inference applications since they leverage data and thread-level parallelism in GPU architectures. Understanding the vulnerability of such DNNs to random hardware faults (including transient and permanent faults) in GPU-based systems is essential to meet the safety requirements of auto safety standards such as the ISO 26262, as well as to influence the design of hardware and software-based safety features in current and future generations of GPU architectures and GPU-based automotive platforms. In this paper, we assess the vulnerability of object detection and classification DNNs to permanent and transient faults using fault injection experiments and accelerated neutron beam testing respectively. We also evaluate the effectiveness of chip-level safety mechanisms in GPU architectures, such as ECC and parity, in detecting these random hardware faults. Our studies demonstrate that such object detection networks tend to be vulnerable to random hardware faults, which cause incorrect or mispredicted object detection outcomes. The neutron beam experiments show that existing chip-level protections successfully mitigate all silent data corruption events caused by transient faults. For permanent faults, while ECC and parity are effective in some cases, our results suggest the need for exploring other complementary detection methods, such as periodic online and offline diagnostic testing.
A VC-dimension-based outer bound on the zero-error capacity of the binary adder channel (2015)

The binary adder is a two-user multiple access channel whose inputs are binary and whose output is the real sum of the inputs. While the Shannon capacity region of this channel is well known, little is known regarding its zero-error capacity region, and a large gap remains between the best inner and outer bounds. In this paper, we provide an improved outer bound for this problem. To that end, we introduce a soft variation of the Saur-Perles-Shelah Lemma, that is then used in conjunction with an outer bound for the Shannon capacity region with an additional common message.
Characterization of Carbapenem-Resistant Enterobacteriaceae Cultured From Retail Meat Products, Patients, and Porcine Excrement in China (2021)

The emergence and dissemination of carbapenem-resistant Enterobacteriaceae (CRE) is a growing concern to animal and public health. However, little is known about the spread of CRE in food and livestock and its potential transmission to humans. To identify CRE strains from different origins and sources, 53 isolates were cultured from 760 samples including retail meat products, patients, and porcine excrement. Antimicrobial susceptibility testing was carried out, followed by phylogenetic typing, whole-genome sequencing, broth mating assays, and plasmids analyses. Forty-three <i>Escherichia coli</i>, nine <i>Klebsiella pneumoniae</i>, and one <i>Enterobacter cloacae</i> isolates were identified, each exhibiting multidrug-resistant phenotypes. Genetically, the main sequence types (STs) of <i>E. coli</i> were ST156 (<i>n</i> = 7), ST354 (<i>n</i> = 7), and ST48 (<i>n</i> = 7), and the dominant ST of <i>K. pneumoniae</i> is ST11 (<i>n</i> = 5). <i>bla</i> <sub>NDM-5</sub> (<i>n</i> = 40) of <i>E. coli</i> and <i>bla</i> <sub>KPC-2</sub> (<i>n</i> = 5) were the key genes that conferred carbapenem resistance phenotypes in these CRE strains. Additionally, the <i>mcr-1</i> gene was identified in 17 <i>bla</i> <sub>NDM</sub>-producing isolates. The <i>bla</i> <sub>NDM-5</sub> gene from eight strains could be transferred to the recipients <i>via</i> conjugation assays. Two <i>mcr-1</i> genes in the <i>E. coli</i> isolates could be co-transferred along with the <i>bla</i> <sub>NDM-5</sub> genes. IncF and IncX3 plasmids have been found to be predominantly associated with <i>bla</i> <sub>NDM</sub> gene in these strains. Strains isolated in our study from different sources and regions tend to be concordant and overlap. CRE strains from retail meat products are a reservoir for transition of CRE strains between animals and humans. These data also provide evidence of the dissemination of CRE strains and carbapenem-resistant genes between animal and human sources.
A Scalable High-Throughput Isoelectric Fractionation Platform for Extracellular Nanocarriers: Comprehensive and Bias-Free Isolation of Ribonucleoproteins from Plasma, Urine, and Saliva (2023)

Extracellular nanocarriers (extracellular vesicles (EVs), lipoproteins, and ribonucleoproteins) of protein and nucleic acids mediate intercellular communication and are clinically adaptable as distinct circulating biomarkers. However, the overlapping size and density of the nanocarriers have so far prevented their efficient physical fractionation, thus impeding independent downstream molecular assays. Here, we report a bias-free high-throughput and high-yield continuous isoelectric fractionation nanocarrier fractionation technique based on their distinct isoelectric points. This nanocarrier fractionation platform is enabled by a robust and tunable linear pH profile provided by water-splitting at a bipolar membrane and stabilized by flow without ampholytes. The linear pH profile that allows easy tuning is a result of rapid equilibration of the water dissociation reaction and stabilization by flow. The platform is automated with a machine learning procedure to allow recalibration for different physiological fluids and nanocarriers. The optimized technique has a resolution of 0.3 ΔpI, sufficient to separate all nanocarriers and even subclasses of nanocarriers. Its performance is then evaluated with several biofluids, including plasma, urine, and saliva samples. Comprehensive, high-purity (plasma: >93%, urine: >95% and saliva: >97%), high-yield (plasma: >78%, urine: >87% and saliva: >96%), and probe-free isolation of ribonucleoproteins in 0.75 mL samples of various biofluids in 30 min is demonstrated, significantly outperforming affinity-based and highly biased gold standards having low yield and day-long protocols. Binary fractionation of EVs and different lipoproteins is also achieved with similar performance.
NEUTRON PHYSICS EXPERIMENTS AT THE SACLAY 28-Mev ELECTRON LINEAR ACCELERATOR (1962)

The time-of-flight method for neutron cross section measurements is described, and its principal limitations (experimental resolution and thermal perturbation in the nuclei in the sample) are given. Some examples of the measurements made and the results obtained for total and fission cross sections and capture gamma rays are discussed. (auth)
Data Stream Algorithms (2005)

How does one deal with massive data sets that is available for analyses? We will describe the classical data stream model in which we make one pass over the data and with sublinear resources perform much of the data analyses we care about, such as frequent items, summaries, compressed sensing, clustering and others. We will present the basic algorithmic techniques used to build the sophisticated analyses above. In addition, we will present extensions to other problems (graph, matrix, statistics) and to other models (probabilistic models, parallel models such as Google’s MapReduce). One of the reasons this area of research thrives is its immediate application to a number of scenarios, which we will describe.
Intelligent control of cupola furnaces (2003)

The objective of this research is to improve the efficiency of the cupola operation in the presence of desired output changes. This is achieved by developing an automatic controller for the cupola furnace. A controller was previously developed that provided tight control over the output parameters of the cupola under little or no desired change. The controller considers physical and practical limitations on the possible inputs. Previous research described optimal pairing of cupola outputs and inputs. This is exploited in a fuzzy controller that pairs oxygen enrichment and blast rate to the outputs of metal temperature and melt rate, respectively. The controller is modified to determine action when problems in production require a slow down or shut down of the melting process. A model is developed using a combination of experimental data and data obtained from the AFS cupola model. The model is a first order multivariable dynamical system. Due to the nonlinearities of the cupola, the model is only accurate for a narrow operating band. By varying the model parameters, simulations show the control to be robust. Simulations in the presence of input disturbances and output sensor noise show the controller efficiently rejects the common noise of a cupola furnace environment.
An Air‐ and Water‐Stable Hydrogen‐Bond‐Donor Catalyst for the Enantioselective Generation of Quaternary Carbon Stereocenters by Additions of Substituted Cyanoacetate Esters to Acetylenic Esters (2020)

The chiral enantiopure cobalt(III) complex Δ-[Co((S,S)-dpen)<sub>3</sub> ]<sup>3+</sup> 2Cl<sup>-</sup> B(C<sub>6</sub> F<sub>5</sub> )<sub>4</sub> <sup>-</sup> (Δ-(S,S)-2<sup>3+</sup> 2Cl<sup>-</sup> B(C<sub>6</sub> F<sub>5</sub> )<sub>4</sub> <sup>-</sup> ; dpen=1,2-diphenylethylenediamine) is an effective catalyst, together with pyridine (10 mol % each), for enantioselective additions of substituted cyanoacetate esters NCCH(R)CO<sub>2</sub> R' to acetylenic esters R''C≡CCO<sub>2</sub> R'''. In the resulting adducts NC(R'O<sub>2</sub> C)C(R)CR''C=CHCO<sub>2</sub> R''', C=C isomers in which the CO<sub>2</sub> R''' moiety is trans to the new carbon-carbon bond dominate (avg. ratio 98:2). These are obtained in 70-98 % ee (avg. 86 %; data for optimum R' and R'''), as determined by <sup>1</sup> H NMR with the chiral solvating agent Λ-(S,S)-2<sup>3+</sup> 2I<sup>-</sup> B(3,5-C<sub>6</sub> H<sub>3</sub> (CF<sub>3</sub> )<sub>2</sub> )<sub>4</sub> <sup>-</sup> . NMR experiments show that the cyanoacetate and acetylenic esters and pyridine can hydrogen bond to certain NH groups of the catalyst. Rates are zero order in the cyanoacetate and acetylenic esters as well as the catalyst, and implications are discussed.