gebhart/patrepeval huggingface dataset:
Distributed Interference Alignment for Mobile MIMO Systems Based on Local CSI (2014)

The requirement for global channel state information (CSI) throughout the network is a significant hurdle to overcome in interference alignment (IA) technologies for mobile applications. In this letter, a distributed IA algorithm is proposed that uses local CSI at the receivers to determine desirable precoding matrices for all interfering transmitters. These matrices are fed back to the transmitters where they are combined, using scalar weighting, to determine the next set of transmit precoding matrices. Results herein show that, with equivalent feedback limitations, the proposed algorithm provides better SINR performance than an IA algorithm requiring full CSI-based feedback, due to the smaller dimensions of the precoding matrices.
Reversible switches between male–male and male–female mating behaviour by male damselflies (2005)

For many animal groups, both sexes have been reported to attempt to mate with members of their own sex. Such behaviour challenges theories of sexual selection, which predict optimization of reproductive success. We tested male mate choice between opposite- and same-sex members in the damselfly Ischnura elegans. Binary choice experiments were conducted following exposure periods in insectaries with only males or with both sexes present. We show that switches in choice between the opposite sex and the same sex can be induced and reversed again by changing the social context. We argue that the observed reversibility in male-male- and male-female-directed mating behaviour is maladaptive and a consequence of strong selection on a male's ability to alter choice between different female colour morphs.
Biotemplated Morpho Butterfly Wings for Tunable Structurally Colored Photocatalysts (2018)

Morpho sulkowskyi butterfly wings contain naturally occurring hierarchical nanostructures that produce structural coloration. The high aspect ratio and surface area of these wings make them attractive nanostructured templates for applications in solar energy and photocatalysis. However, biomimetic approaches to replicate their complex structural features and integrate functional materials into their three-dimensional framework are highly limited in precision and scalability. Herein, a biotemplating approach is presented that precisely replicates Morpho nanostructures by depositing nanocrystalline ZnO coatings onto wings via low-temperature atomic layer deposition (ALD). This study demonstrates the ability to precisely tune the natural structural coloration while also integrating multifunctionality by imparting photocatalytic activity onto fully intact Morpho wings. Optical spectroscopy and finite-difference time-domain numerical modeling demonstrate that ALD ZnO coatings can rationally tune the structural coloration across the visible spectrum. These structurally colored photocatalysts exhibit an optimal coating thickness to maximize photocatalytic activity, which is attributed to trade-offs between light absorption and catalytic quantum yield with increasing coating thickness. These multifunctional photocatalysts present a new approach to integrating solar energy harvesting into visually attractive surfaces that can be integrated into building facades or other macroscopic structures to impart aesthetic appeal.
Modulating the Filamentary-Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers (2022)

The resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.
Quasi- (that is, Sub-) Random Numbers (1989)

ometimes we want to pick sample points in an ndimensional space that are spread out as uniformly as possible.The most obvious case is where we want to integrate a function over n-dimensional space by a Monte Carlo method.The desired integral is, in essence, the average of the function value at a bunch of randomly sampled points, multiplied by the volume of n space that is uniformly sampled (For more detail, see Sec. 7.6.in Refs. 1 or 2.) As the number of sampled points N is increased, the accuracy of the integral gets better.But how fast?In the familiar case of un correlated points, e.g., those generated by a good pseudorandom number generator, the fractional error of the estimated integral will decrease by the equally familiar 1I,[Nlaw.In essence, each new point sampled adds linearly to an accumulated sum that will become the function average, and also linearly to an accumulated sum of squares that will become the variance.The estimated error comes from the square root of this variance, hence the powerJust because this square root convergence is familiar does not, however, mean that it is inevitable.A simple counterexample is to choose sample points that lie on a Cartesian grid, and to sample each grid point exactly once (in whatever order).The Monte Carlo method thus becomes a deterministic quadrature scheme-albeit a simple one-whose fractional error decreases at least as fast as N -I (even faster if the function goes to zero smoothly at the boundaries of the sampled region, or is periodic in the region).The trouble with a grid is that one has to decide in ad- vance how fine it should be.One is then committed to completing all of its sample points.With a grid, it is not convenient to "sample until" some convergence or termination criterion is met.Is there a better way?A similar question arises for tasks other than Monte Carlo integration.We might want to search an n- dimensional space for a point where some (locally computable) condition holds.Of course, for the task to be computationally meaningful, there had better be continuity so that the desired condition will hold in some finite ndimensional neighborhood.We may not know a priori how large that neighborhood is, however.We want to "sample until" the desired point is found, moving smoothly to finer scales with increasing samples.Is there any way to do this that is better than uncorrelated, random samples?The answer to the above questions is "yes."Sequences of n-tuples that fill n space more uniformly than
High-Sensitivity Detection of Carbohydrate Antigen 15-3 Using a Gold/Zinc Oxide Thin Film Surface Plasmon Resonance-Based Biosensor (2010)

We report that gold/zinc oxide (Au/ZnO) nanocomposite films were effectively employed to enhance the performance of surface plasmon resonance (SPR) for the detection of tumor markers. Carbohydrate antigen 15.3 (CA15-3), a tumor marker for breast cancer, was chosen as a model analyte. We analyzed intensity response to the samples at various concentrations (0.0125 U/mL to 160 U/mL) in pleural fluid to evaluate the detection capability of the SPR biosensor based on Au/ZnO thin films. The linear range extended from 1 to 40 U/mL with a correlation coefficient of R(2) = 0.991 and a limit of detection reaching 0.025 U/mL at a signal-to-noise ratio of 3:1. Compared with the degree of the shift in SPR intensity induced by the specific binding event between antibody and antigen, the change of intensity on the Au/ZnO layers was increased by at least 2 fold over that on the gold/chromium (Au/Cr) layers. In addition, we determined that the Au/ZnO layers allowed for a detection limit 4 times lower than the Au/Cr layers, which are in widespread use as the sensing interfaces in current SPR-based detectors. In conclusion, the use of Au/ZnO films greatly enhanced the SPR signal yield for this bimolecular interaction and showed high sensitivity.
A gallic acid based metal organic framework derived NiS/C anode for sodium ion batteries (2021)

A NiS/C sodium-ion battery anode is synthesized from a MOF based on naturally occurring, non-toxic gallic acid.
Friction-Inclusive Modeling of Sliding Contact Transmission Systems in Robotics (2021)

This article presents a unified mathematical approach for modeling, identifying, and solving the friction-inclusive dynamics of robotic mechanisms driven by sliding contact transmission systems. This approach is applied to the most common industrial screw-based drives: 1) the worm drive, 2) the simple lead screw drive, and 3) the antibacklash lead screw drive. The resulting dynamics, handily transferable to single and multiple degree of freedom (DoF) manipulators, are complemented with an algorithm for the solution of the forward dynamics problem as well as a framework for friction identification based on nonlinear optimization. The presented theory is experimentally tested on single-DoF screw-based drives for a variety of payloads and at different operation speeds. Simulation and parameter identification results using the classical Coulomb model, the Coulomb model with Stribeck friction, and the Armstrong model with Stribeck friction, rising static friction, and frictional memory are compared with experimental data, showcasing the effectiveness of the presented approach toward framing the concepts of friction and motion transmission into a robotics setting.
Endogenously produced nitric oxide inhibits endothelial cell growth as demonstrated using novel antisense cell lines (2000)

Proliferation of endothelial cells is a vital component of vascular repair and angiogenesis. The endothelial cell mediator, nitric oxide (NO) has been reported both to inhibit and to promote endothelial cell proliferation. In this study we have generated cell lines which constitutively express antisense RNA to a region of inducible nitric oxide synthase (iNOS) from a murine endothelial cell line, sEnd-1. In response to stimulation with lipopolysaccharide (LPS) and interferon-gamma (IFN-gamma) these antisense cells had no detectable RNA for endogenous iNOS, barely detectable iNOS protein and produced 82% less NO than did the control transfected line. Stimulation of the control transfected line caused significant NO production and inhibition of cell growth whereas for the antisense line, producing little NO in response to stimulation, proliferation remained the same as for unstimulated cells. No differences in cell death were observed between unstimulated and LPS/IFN-gamma stimulated cells. The data presented in this study directly demonstrate that NO derived endogenously from iNOS inhibits proliferation of endothelial cells. This approach overcomes problems in other studies where NO donors or non-isoform specific inhibitors of NO synthase have been used.
PENETRATION HEIGHT CORRELATIONS FOR OIL-IN-WATER UNSTEADY EMULSIONS OF A LIQUID JET IN CROSS FLOW AT GAS TURBINE CONDITIONS (2011)

A series of combustion rig tests were analyzed to determine liquid jet penetration heights of oil-in-water unsteady emulsions in a gaseous cross flow. Data was taken ranging the water to fuel ratio at several engine loads. The goal of this study is to develop a transfer function to model penetration heights over the engine load range and compare with emissions requirements to predict emission compliant water to fuel ratios without risk of combustion liner wetting and coating spallation. In this study correlations were developed at lower and upper range engine loads while the mid range shows an unclear transition pattern that needs to be addressed in further research.
Relative Glucose Metabolic Rate Higher in White Matter in Patients With Schizophrenia (2007)

In comparisons of unmedicated schizophrenia patients with normal volunteers, relative metabolic increases are apparent in white matter in patients with schizophrenia as well as decreases in gray matter. Inefficiency in brain circuitry, defects in white matter leading to enhanced energy need, white matter damage, and alterations in axon packing density are among the possible explanations for these schizophrenia-related findings of relatively increased metabolism in white matter.
THE “CLINICALLY RECONSTRUCTED” INFANT IN THE DEVELOPMENT OF PSYCHOANALYTIC THEORY (2010)

Infant research observations and hypotheses have raised serious questions about previous mainstream psychoanalytic theories of earliest childhood development. In Jungian Psychotherapy and Contemporary Infant Research, Mario Jacoby looks at how these observations are relevant to psychotherapeutic and Jungian analytical practice. Using recent findings in infant research, along with practical examples from therapeutic practice, he shows how early emotional exchange processes, though becoming superimposed in adult life by rational control and various defenses, remain operative and become reactivated in situations of intimacy. Jungian Psychotherapy and Contemporary Infant Research will be of interest to both professionals and students involved in analytical psychology and psychotherapy.
Compressive Sensing Based Classification in the Presence of Intra-and Inter-Signal Correlation (2018)

In this letter, we investigate the problem of classification with high-dimensional data using low-dimensional random projections in the presence of inter- and intra-signal correlations. Each sensor is assumed to compress its high-dimensional (Gaussian) signal vector using random projections in a multisensor setting. In order to quantify the classification performance with compressed data, we consider the Bhattacharya distance as the performance metric. In the presence of intra-signal correlation at a given sensor, the degradation in the Bhattacharya distance with compressed data is shown to be nonlinear with the compression ratio in contrast to the case when there is no intra-signal correlation. In the presence of inter-signal correlation, the degradation in the Bhattacharya distance with compressed data depends on whether or not an identical projection matrix is used to compress data at multiple sensors.
Synthesis of 1-BODIPY-labeled 2-amino-2-deoxy-d-glucose, substrate for acetyl-CoA:glucosaminide N-acetyltransferase (2015)

A new fluorescent substrate for acetyl-CoA: glucosaminide N-acetyltransferase, namely, 2-amino-2-deoxy-d-glucose BODIPY-labeled by the 1-position, was synthesized in five steps from 2-azido-2-deoxy-d-glucose.
Rücktitelbild: Synthesis of Polyampholyte Janus‐like Microgels by Coacervation of Reactive Precursors in Precipitation Polymerization (Angew. Chem. 3/2020) (2019)

Die Synthese Stimuli-responsiver, Janus-artiger Polyampholyt-Mikrogele in einer templatfreien, wasserbasierten, einfach skalierbaren Technik wird von A. Pich et al. in ihrem Forschungsartikel auf S. 1264 vorgestellt. Sie basiert auf der kontrollierten Selbstassemblierung und Koazervierung von wachsenden Polyelektrolyt-Mikrogel-Vorläufern während einer Fällungspolymerisation. Die Mischzeit der zwei Lösungen wachsender Mikrogel-Vorläufer bestimmt die Morphologie der Polyampholyt-Mikrogele.
Source Wavelet Amplitude Spectrum Estimation Using Marchenko Focusing Functions (2017)

Summary Marchenko focusing enables the redatuming of seismic surface data to an arbitrary new datum level in the subsurface. One requirement for an accurate redatuming is the correct deconvolution of the source signature from the acquired surface reflection response. Using an erroneous source wavelet for deconvolution leads to inaccurate redatuming and, thus, to artefacts in the redatumed data. However, the true amplitude spectrum of the source wavelet is often unknown. We propose a novel approach to invert for the amplitude spectrum of the source wavelet using focusing functions obtained by the Marchenko redatuming process. Deconvolving the data with an incorrect source wavelet generates undesired coda events in the focusing function. We identify such coda events by the analysis of an ensemble of focusing functions, where differently scaled source wavelets are used for deconvolution prior to redatuming. The amplitude spectrum of the identified coda is strongly related to an error in the source wavelet. Thus, we can iteratively invert for the correct scaling of the source wavelet by analyzing the amplitude spectrum of coda events in the focusing function. This approach yields the correct scaling of the amplitude spectrum of the source wavelet and enables accurate Marchenko redatuming.
Solution Self-Assembly of Poly(ferrocenylphenylphosphine)-block-polydimethylsiloxane: Formation of Spherical Micelles with an Organometallic Poly(ferrocenylphenylphosphine) Core (2001)

The novel organometallic-inorganic diblock copolymer, poly(ferrocenylphenylphosphine)-block-polydimethylsiloxane (PFP-b-PDMS), with narrow molecular weight distribution has been synthesized by living anionic polymerization through sequential monomer addition. These block copolymers self-assemble into “star-like” spherical micelles in hexane with a dense organometallic PFP core surrounded by a swollen corona of the PDMS chains. Transmission electron microscopy (TEM) and dynamic light scattering (DLS) were used to characterize these micellar aggregates. It was found that the block copolymer micelles have a relatively narrow core size distribution, but an overall broader distribution of hydrodynamic size in hexane. Significantly, the preparation method of the micelle solution was also found to have an influence on the size and size distribution of the resulting micellar structures.
The Alaska Sar Processor (2005)

The Alaska SAR processor was designed to process over 200 100 km x 100 km (Seasat like) frames per day from the raw SAR data, at a ground resolution of 30 m x 30 m from ERS-1, J-ERS-1, and Radarsat. The near real time processor is a set of custom hardware modules operating in a pipelined architecture, controlled by a general purpose computer. Input to the processor is provided from a high density digital cassette recording of the raw data stream as received by the ground station. A two pass processing is performed. During the first pass clutter-lock and auto-focus measurements are made. The second pass uses the results to accomplish final image formation which is recorded on a high density digital cassette. The processing algorithm uses fast correlation techniques for range and azimuth compression. Radiometric compensation, interpolation and deskewing is also performed by the processor. The standard product of the ASP is a high resolution four-look image, with a low resolution (100 to 200 m) many look image provided simultaneously.
Edinburgh's Syntax-Based Machine Translation Systems (2013)

We present the syntax-based string-totree statistical machine translation systems built for the WMT 2013 shared translation task. Systems were developed for four language pairs. We report on adapting parameters, targeted reduction of the tuning set, and post-evaluation experiments on rule binarization and preventing dropping of verbs. 1
Statistical Reconstruction of Material Decomposed Data in Spectral CT (2013)

Photon-counting detector technology has enabled the first experimental investigations of energy-resolved computed tomography (CT) imaging and the potential use for K-edge imaging. However, limitations in regards to detecter technology have been imposing a limit to effective count rates. As a consequence, this has resulted in high noise levels in the obtained images given scan time limitations in CT imaging applications. It has been well recognized in the area of low-dose imaging with conventional CT that iterative image reconstruction provides a superior signal to noise ratio compared to traditional filtered backprojection techniques. Furthermore, iterative reconstruction methods also allow for incorporation of a roughness penalty function in order to make a trade-off between noise and spatial resolution in the reconstructed images. In this work, we investigate statistically-principled iterative image reconstruction from material-decomposed sinograms in spectral CT. The proposed reconstruction algorithm seeks to minimize a penalized likelihood-based cost functional, where the parameters of the likelihood function are estimated by computing the Fisher information matrix associated with the material decomposition step. The performance of the proposed reconstruction method is quantitatively investigated by use of computer-simulated and experimental phantom data. The potential for improved K-edge imaging is also demonstrated in an animal experiment.
XConveryer: Guarantee Hadoop Throughput via Lightweight OS-Level Virtualization (2009)

Large-scale data parallel applications such as web indexing, data mining demand plenty of computing and storage resources. As a widely adopted solution, hadoop partitions and distributes the large datasets into chunks across multiple nodes in clusters to process in parallel. For a single cluster node, typically there are several concurrently running applications, sharing and competing system CPU, memory, disk and network bandwidth. The competition will cause unfairness for some jobs and extend their response time. Particularly, some jobs have to be cancelled and rescheduled because of resource starvation. In this paper, we present a solution to reduce resource challenge. The XConveyer, as one of key component, is designed based on kernel-level virtualization facilities, to isolate Hadoop jobs and to guarantee their resource share. Built on XConveyer, Hadoop can enforce scheduling polities down to Operating System, that more fine-granular control can be achieved. The evaluation shows the XConveyer can encapsulate Hadoop jobs executed in isolated containers and guarantee strict control their system resources usages.
Multimodal Relational Tensor Network for Sentiment and Emotion Classification (2018)

Understanding Affect from video segments has brought researchers from the language, audio and video domains together. Most of the current multimodal research in this area deals with various techniques to fuse the modalities, and mostly treat the segments of a video independently. Motivated by the work of We also generate rich representations of text and audio modalities by leveraging richer audio and linguistic context alongwith fusing fine-grained knowledge based polarity scores from text. We present the results of our model on CMU-MOSEI dataset and show that our model outperforms many baselines and state of the art methods for sentiment classification and emotion recognition.