gebhart/patrepeval huggingface dataset:
A Continuum-Microscopic Algorithm for Modeling Fibrous, Heterogeneous Media with Dynamic Microstructures (2021)

Many materials undergo reconfiguration of microscopic structure in response to applied stress. Computing the mechanical behavior of such materials at the continuum level requires a locally valid stress-strain relation. Due to the dynamic microstructure reconfiguration, such relations are difficult to obtain analytically. Numerical simulation of the microscopic dynamics is an alternative, albeit one that is computationally expensive. Continuum-microscopic (CM) interaction algorithms seek to reduce computational cost by microscopic simulation over some small fraction of the continuum time step of interest, enough to determine the locally valid stress-strain relationship, assumed to hold over the entire continuum time step. One difficulty with this approach is the problem of recreating a valid microscopic configuration at the start of the next continuum time step. In most previous CM algorithms, the microscopic structure at the beginning of a new continuum time step is assumed to obey some predefined statistical distribution. This paper extends current CM methods by applying a probability distribution function (PDF) estimation procedure to describe local microscopic states within each continuum computational cell. The estimated PDFs are extrapolated forward over a continuum time step to recreate new microscopic configurations. This procedure captures local variability in the microscopic structure. The algorithm is applied to a generic fibrous material with randomly oriented, cross-linked fibers. Numerical results show that the procedure furnishes continuum stress and strain values to within 5-10% of those obtained from averaging a full microscopic simulation. The computational time is reduced by a factor of two in serial computation and by an order of magnitude when the PDF estimation procedures are computed in parallel.
Preliminary evidence for anticipation in genetic E200K Creutzfeldt-Jakob disease (1999)

Creutzfeldt-Jakob disease (CJD) linked to the E200K mutation of the prion protein (PrP) gene presents within a wide range of phenotypic heterogeneity, including the age at disease onset. We report an earlier disease onset for mutation carriers of the offspring generation when compared with that of their parents, suggesting the possibility of anticipation. A still unidentified environmental or genetic element may affect the age at onset in mutation carriers of different generations.
Rydberg excitons in synthetic cuprous oxide Cu2O (2021)

High-lying Rydberg states of Mott-Wannier excitons are receiving considerable interest due to the possibility of adding long-range interactions to the physics of excitons. Here, we study Rydberg excitation in bulk synthetic cuprous oxide grown by the optical float zone technique and compare the result with natural samples. X-ray characterization confirms both materials are mostly single crystal, and midinfrared transmission spectroscopy revealed little difference between synthetic and natural material. The synthetic samples show principal quantum numbers up to $n=10$, exhibit additional absorption lines, plus enhanced spatial broadening and spatial inhomogeneity. Room temperature and cryogenic photoluminescence measurements reveal a significant quantity of copper vacancies in the synthetic material. These measurements provide a route towards achieving high-$n$ excitons in synthetic crystals, opening a route to scalable quantum devices.
Optical Signal Processing Promoted by Optical Data Form Conversion (2007)

This talk reviews opportunities of optical signal processing promoted by optical data form conversion for the next generation of photonics. The current physical advancements surrounding optical technology are summed up that ultra-short pulse and diffractive optics overlap each other in terms of spatial dimensions. It suggests that ultra-fast photonics and nanotechnology could go well together and it comes to be easier to deal with a temporal waveform in spatial domain, as well as spectral one. And conventional optical elements would be reborn again. One of the indispensable match-maker between them would be time-space conversion. In this talk, time-space conversion is described as a typical example of optical data form conversion with especially focusing on our works based on 2 dimensional time-space conversion with mainly focusing on our works based on 2 dimensional time-space conversion.
Agreement among three examiners of colour Doppler imaging retrobulbar blood flow velocity measurements (2011)

Expert training and execution of a specific protocol for CDI of ocular blood flow velocity measurements provide highly reproducible results in healthy volunteers. This is important for long-term studies assessing ocular hemodynamics, where multiple examiners may be involved.
Uncovering social spammers (2010)

Web-based social systems enable new community-based opportunities for participants to engage, share, and interact. This community value and related services like search and advertising are threatened by spammers, content polluters, and malware disseminators. In an effort to preserve community value and ensure longterm success, we propose and evaluate a honeypot-based approach for uncovering social spammers in online social systems. Two of the key components of the proposed approach are: (1) The deployment of social honeypots for harvesting deceptive spam profiles from social networking communities; and (2) Statistical analysis of the properties of these spam profiles for creating spam classifiers to actively filter out existing and new spammers. We describe the conceptual framework and design considerations of the proposed approach, and we present concrete observations from the deployment of social honeypots in MySpace and Twitter. We find that the deployed social honeypots identify social spammers with low false positive rates and that the harvested spam data contains signals that are strongly correlated with observable profile features (e.g., content, friend information, posting patterns, etc.). Based on these profile features, we develop machine learning based classifiers for identifying previously unknown spammers with high precision and a low rate of false positives.
Crystallographic and spectroscopic characterization of a mixed actinide–lanthanide carbide cluster stabilized inside anIh(7)-C80fullerene cage (2020)

A mixed actinide-lanthanide cluster fullerene, Sc<sub>2</sub>UC@I<sub>h</sub>(7)-C<sub>80</sub>, was isolated and fully characterized. For the first time, the single crystal X-ray crystallographic analysis confirms a novel actinide-lanthanide cluster Sc<sub>2</sub>UC stabilized inside an I<sub>h</sub>(7)-C<sub>80</sub> cage. Moreover, the U[double bond, length as m-dash]C double bond distance is 2.01 Å, the shortest U[double bond, length as m-dash]C bond confirmed by crystallography so far.
Graph of virtual actors (GOVA): A Big Data analytics architecture for IoT (2017)

With the emergence of cloud computing and sensor technologies, Big Data analytics for the Internet of Things (IoT) has become the main force behind many innovative solutions for our society's problems. This paper provides practical explanations for the question “why is the number of Big Data applications that succeed and have an effect on our daily life so limited, compared with all of the solutions proposed and tested in the literature?”, with examples taken from Smart Grids. We argue that “noninvariants” are the most challenging issues in IoT applications, which can be easily revealed if we use the term “invariant” to replace the more common terms such as “information”, “knowledge”, or “insight” in any Big Data for IoT research. From our experience with developing Smart Grid applications, we produced a list of “noninvariants”, which we believe to be the main causes of the gaps between Big Data in a laboratory and in practice in IoT applications. This paper also proposes Graph of Virtual Actors (GOVA) as a Big Data analytics architecture for IoT applications, which not only can solve the noninvariants issues, but can also quickly scale horizontally in terms of computation, data storage, caching requirements, and programmability of the system.
Environmental Fate of Chiral Pollutants &ndash the Necessity of Considering Stereochemistry (1997)

Many organic compounds regulated by environmental laws are chiral and are released into the environment as racemates. 3-Phenylbutanoic acid and mecoprop, two chiral pollutants, were enantioselectively degraded by pure cultures of microorganisms. This indicates the importance of assessing the environmental impact of stereoisomers separately, because selective enrichment of one of the enantiomers may occur in the environment. Field studies on the fate of highly polar, chiral compounds, like sulfophenylcarboxylates, are hampered by the lack of appropriate analytical methods for the separation of the enantiomers. Therefore, a method based on capillary electrophoresis with ?-cyclodextrin as chiral selector was developed to separate the enantiomers of such compounds. In a field study at a Swiss waste disposal site, the fate of the chiral herbicide mecoprop was investigated. The enantiomeric ratio of (R)-mecoprop to (S)-mecoprop altered during groundwater passage of landfill leachate. This is a strong indication for in situ biodegradation. Our data imply that not only the enantiomers of a chiral drug or pesticide may exert different effects on the biological targets, but also their biodegradation and environmental fate may differ.
Supplementary Figure from Phase II Clinical Trial of Eribulin–Gemcitabine Combination Therapy in Previously Treated Patients With Advanced Liposarcoma or Leiomyosarcoma (2023)

Supplementary Figure from Phase II Clinical Trial of Eribulin–Gemcitabine Combination Therapy in Previously Treated Patients With Advanced Liposarcoma or Leiomyosarcoma
Potential for Layered Double Hydroxides-Based, Innovative Drug Delivery Systems (2014)

Layered Double Hydroxides (LDHs)-based drug delivery systems have, for many years, shown great promises for the delivery of chemical therapeutics and bioactive molecules to mammalian cells in vitro and in vivo. This system offers high efficiency and drug loading density, as well as excellent protection of loaded molecules from undesired degradation. Toxicological studies have also found LDHs to be biocompatible compared with other widely used nanoparticles, such as iron oxide, silica, and single-walled carbon nanotubes. A plethora of bio-molecules have been reported to either attach to the surface of or intercalate into LDH materials through co-precipitation or anion-exchange reaction, including amino acid and peptides, ATPs, vitamins, and even polysaccharides. Recently, LDHs have been used for gene delivery of small molecular nucleic acids, such as antisense, oligonucleotides, PCR fragments, siRNA molecules or sheared genomic DNA. These nano-medicines have been applied to target cells or organs in gene therapeutic approaches. This review summarizes current progress of the development of LDHs nanoparticle drug carriers for nucleotides, anti-inflammatory, anti-cancer drugs and recent LDH application in medical research. Ground breaking studies will be highlighted and an outlook of the possible future progress proposed. It is hoped that the layered inorganic material will open up new frontier of research, leading to new nano-drugs in clinical applications.
Adaptive evolution of Esherichia coli towards a predicted phenotype (2002)

With abundant genomic data now available, methods must be formulated to utilize this pool of data to yield meaningful biological information. Using a constraints-based approach, a genome-scale whole cell model has been constructed for Escherichia coli that can be used to predict behavioral characteristics of the K-12 MG1655 wild-type strain. In particular, phenotype phase-plane analysis can be used to distinguish different operating states of E. coli with particular interest in defining a line of optimal growth. A hypothesis was formulated that E. coli will naturally optimize its growth and exhibit a phenotype corresponding to the predicted line of optimality. Evolution experiments were carried out for 500 to 1000 generations where E. coli were allowed to naturally accumulate mutations. Various carbon sources with different entry points into central metabolism were used to test the robustness of the model. The experimental results showed that over the course of evolution, E. coli evolved towards the line of optimality and remained along the line of optimality while increasing its substrate uptake rate, oxygen uptake rate, and specific growth rate. Thus, the constraints-based model of E. coli serves as an accurate predictive tool in determining the growth behavior of E. coli under the parameters tested.
Incorporating blood pressure load into an elastomechanical ventricular mod (2005)

Elastomechanical modeling constitutes an essential step for realistic computer simulations of the cardiac system. The deformation of tissue effects e.g. cellular electrophysiology, which is commonly neglected in electrophysiological simulations due to the lack of efficient mechanical models. This work focuses on extending a mechanical deformation model by including blood pressure as endocardial boundary condition. Four phases are distinguished in a normal heart cycle: isovolumic contraction, isotonic contraction, isometric relaxation, and isotonic relaxation. The first three phases were modeled. The methods modeling intraventricular pressure corresponding to contraction phases are illustrated, applied, and discussed. Simulation results show that the mechanical model is capable of incorporating a pressure load leading to a more realistic contraction behavior. Furthermore, the ejection curve resembles in closer detail measured data
cis–trans Equilibrium in meta-chlorophenyl aldehydes, ethers, ketones, and carboxylic esters from dipole moment studies (1971)

Comparison of dipole moments of meta-chloro-, para-chloro-, and 3,5-dichloro-substituted compounds with parents enable the calculation of group dipole directions, of interaction moments, and of cis–trans conformational equilibria in the meta-substituted derivatives.
New Optimal Common-Mode Modulation for Three-Phase Inverters with DC-Link Referenced Output Filter (2017)

A two-level inverter followed by a DC-link referenced output filter is a promising solution for high-speed low-voltage drive systems. A limitation of this power electronics topology, however lies in the high current ripple and hence additional losses occurring within the filter inductors. This shortcoming can be addressed by means of an appropriate modulation technique. This paper details two new modulation strategies, tailored to the specific characteristics of three-phase inverters with DC-link referenced output filter, utilizing the instantaneous common-mode (CM) voltage as a degree of freedom, in order to decrease the output inductor's current ripple. It is deduced that a constant (DC) CM injection modulation (DCCMM) or an AC CM injection modulation (ACCMM) with arbitrarily large amplitude yields the best performance depending on the operating point. The CM pattern that minimizes the inductor current ripple envelope results from the combination of the two schemes and constitutes the optimal CM injection modulation (OCMM). Furthermore, the proposed modulation schemes are tested on a 300 W hardware demonstrator driving a 300 krpm custom designed motor, where a reduction of the total inverter losses of up to 11% is observed.
Assessing the impact of novel polymers and thermal management in a power electronics module using machine learning approaches (2021)

We highlight the predictive utility of machine learning (ML) techniques in estimating thermal performance benefits in power electronics modules, resulting from the use of high thermal conductivity polymers and thermal management techniques. The thermal performance of a commercial 1.2kV/444A SiC half-bridge module is quantified via high fidelity numerical simulations. Parametric simulations are conducted by considering the thermal conductivity of i) encapsulant (anisotropic), ii) baseplate and iii) heat sink as variable parameters, along with the coolant temperature and convection heat transfer coefficient. These simulations generate a data set of more than 2500 data points, which is used to train and evaluate the performance of machine learning algorithms to estimate the maximum junction temperature (Tj) of the package. Parameters are varied to represent a broad spectrum of possibilities ranging from high thermal conductivity polymer-based heat sinks to copper heat sinks; and air to two-phase liquid cooling technologies. The performance of three different statistical machine learning models is evaluated: polynomial regression, random forest, and support vector machines in predicting Tj. While polynomial regression does not predict Tj with a reasonable accuracy, random forest and support vector machines demonstrate excellent prediction accuracies w ith overall R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 99.6 and 99.98%, respectively. To estimate the relative contribution of the underlying thermal parameters, we use SHAP (Shapley Additive exPlanations) dependence plots in combination with random forest algorithm to identify parameters which strongly influence Tj. We observe that the thermal conductivity of heat sink material and heat transfer coefficient have the maximum impact on Tj reduction, whereas the thermal conductivity of the polymeric encapsulant has the least influence on Tj. The presently used approach of simulations-based training of ML algorithms can be adapted for the thermal design and parameter optimization in other electronics packages.
Learning Transformations (1985)

A low-rank transformation learning framework for subspace clustering and classification is here proposed. Many high-dimensional data, such as face images and motion sequences, approximately lie in a union of low-dimensional subspaces. The corresponding subspace clustering problem has been extensively studied in the literature, partitioning such high-dimensional data into clusters corresponding to their underlying low-dimensional subspaces. However, low-dimensional intrinsic structures are often violated for real-world observations, as they can be corrupted by errors or deviate from ideal models. We propose to address this by learning a linear transformation on subspaces using matrix rank, via its convex surrogate nuclear norm, as the optimization criteria. The learned linear transformation restores a low-rank structure for data from the same subspace, and, at the same time, forces a high-rank structure for data from different subspaces. In this way, we reduce variations within the subspaces, and increase separation between the subspaces for improved subspace clustering and classification.
Frontispiece: Continuous Synthesis of Nanominerals in Supercritical Water (2019)

By the use of supercritical water, it is now possible to obtain a synthetic talc phyllomineral and two synthetic inominerals such as synthetic xonotlite and synthetic tobermorite in only few seconds and with the ability to be transferable at an industrial scale. This article highlights the awareness attained from the synthesis of minerals which contributes to a greater insight of the geological genesis processes of natural minerals. For more information, see the Concept article by C. Aymonier et al. on page 5814 ff.
Quantum-Noise in Multi-Mode Parametric Amplifiers—Noiseless Amplification in Bulk QPM LiNbO3 (1996)

Noiseless optical amplification–a non-classical process in which a weak optical signal may be amplified without any degradation in the signal to noise ratio (SNR)–is generating interest in the telecommunications community. Although successfully demonstrated in bulk KTP crystals 1 , practical applications are severely hampered by the enormous pump-field strength required to obtain a sizeable gain. Efforts to reduce this requirement are centred on the search for better non-linear materials and stronger confinement of the interacting fields. In this article a noiseless optical parametric amplifier (OPA) is demonstrated with tightly-focused incident fields in quasi-phase-matched (QPM) lithium niobate (LiNbO 3 ), for the first time. The quantum noise properties are analysed within a quantised field framework which reveals a strong similarity between guided and free wave interactions.
Role of Gene Regulation during Vestibular Compensation (2001)

Identification of the role of gene regulation in vestibular compensation is one aspect of a larger issue: the identification of molecular bases for plasticity in multiple vestibulo-ocular, vestibulo-spinal, vestibulo-collic, and vestibulo-autonomic responses. To achieve this goal, it is incumbent on investigators to examine molecular events within the contexts of the single neuron, the location of the neuron in pathways, and the timing of the molecular events relative to behavioral compensation. Hence, the goal of identifying molecular bases for a particular compensatory response (e.g., the disappearance of spontaneous nystagmus in the light or the disappearance of static head tilt) requires careful attention to the time course of physiologic compensation and the location of the effects within central pathways that have the potential to affect the responses. The effects of impeding these site-specific and time-specific changes can then be tested to determine their role in the compensatory process. A consideration of the recent literature on molecular events related to the resolution of spontaneous nystagmus in the light indicates that a meaningful approach to these issues requires a broadening of our conceptual approach. Specifically, one must consider the roles of transcriptional, translational, and posttranslational events on the turnover of critical signaling substrates for vestibular compensation.
Studies on the mechanism of action of 5‐aziridinyl‐2,4‐dinitrobenzamide (CB 1954), a selective inhibitor of the walker tumour (1971)

Abstract CB 1954, a monofunctional alkylating agent, has exceptional activity against the Walker carcinoma yet is inactive against a large number of other animal tumours. A line of the Walker tumour with acquired resistance to CB 1954 was cross‐resistant to Melphalan, implying a common mechanism of action, although other tumours highly sensitive to Melphalan were not affected by CB 1954. CB 1954 was also similar to Melphalan in its effects on DNA and RNA synthesis. No correlation was observed between binding of CB 1954 to the DNA of tumour cells and their sensitivity to it. Differences in response of the Walker tumour when incubated with Melphalan and CB 1954 suggest that the latter agent may have some features of an anti‐metabolite. In preliminary experiments, its selective anti‐tumour effect against the Walker carcinoma has been completely reversed by an intermediate in purine biosynthesis.
Cleaved-coupled-cavity lasers with large cavity length ratios for enhanced stability (1984)

The fabrication and operation of the first cleaved-coupled-cavity (C3) semiconductor lasers with large cavity length ratios are described. The internal cleaved facet is precisely positioned by photochemically etching a groove through most of the wafer. Single longitudinal mode operation is obtained over a temperature range of 21 °C and over a current range of threshold to greater than four times threshold. Sidemode suppression of 100:1 was measured when the laser was modulated at 350 MHz with an extinction ratio greater than 10:1. These results are experimentally and theoretically compared to approximately equal length C3 lasers.