gebhart/patrepeval huggingface dataset:
Dynamics of polymer ejection from capsid (2014)

Polymer ejection from a capsid through a nanoscale pore is an important biological process with relevance to modern biotechnology. Here, we study generic capsid ejection using Langevin dynamics. We show that even when the ejection takes place within the drift-dominated region there is a very high probability for the ejection process not to be completed. Introducing a small aligning force at the pore entrance enhances ejection dramatically. Such a pore asymmetry is a candidate for a mechanism by which viral ejection is completed. By detailed high-resolution simulations we show that such capsid ejection is an out-of-equilibrium process that shares many common features with the much studied driven polymer translocation through a pore in a wall or a membrane. We find that the ejection times scale with polymer length, τ ∼ N(α). We show that for the pore without the asymmetry the previous predictions corroborated by Monte Carlo simulations do not hold. For the pore with the asymmetry the scaling exponent varies with the initial monomer density (monomers per capsid volume) ρ inside the capsid. For very low densities ρ ≤ 0.002 the polymer is only weakly confined by the capsid, and we measure α = 1.33, which is close to α=1.4 obtained for polymer translocation. At intermediate densities the scaling exponents α = 1.25 and 1.21 for ρ = 0.01 and 0.02, respectively. These scalings are in accord with a crude derivation for the lower limit α = 1.2. For the asymmetrical pore precise scaling breaks down, when the density exceeds the value for complete confinement by the capsid, ρ ⪆ 0.25. The high-resolution data show that the capsid ejection for both pores, analogously to polymer translocation, can be characterized as a multiplicative stochastic process that is dominated by small-scale transitions.
CTX2: SCR, ECG, respiration, and startle eyeblink EMG measurements in a contextual fear conditioning task under VR with acquisition and recall test after one week (2022)

This dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, electromygram (EMG) for 23 healthy unmedicated participants (15 females and 8 males aged 24 +/- 4.0) participating in a Pavlovian differential contextual fear conditioning experiment under virtual reality with 2 sessions. The two contexts (CTX+, CTX-) were designed as living rooms with the same furniture in different arrangement. A neutral corridor connected the two rooms and served as inter-trial interval (ITI). Participants were continuously passively guided through the spaces based on a predefined path, but were free to move and rotate their heads for observation. US was a train of 25 square electric pulses with 0.2 ms duration with a duty cycle of 0.91%, delivered with a constant current stimulator on participants' dominant forearm through a pin-cathod/ring-anode configuration. US was delivered randomly during 6-8 s and/or 21-24 s after room entry. No US was delivered in ITI. Participants underwent the conditioning task with CTXs (CTX+ 100% reinforced) and US delivery in session 1, and were tested in a retention/extinction task one week later in session 2, with CTXs and auditory startle probe (ST) delivered during 6-8 s and/or 21-24 s after room entry. One ST was delivered during 5-10 s after entry of ITI. No US was delivered during session 2. Participants travelled 10 times through each CTX room for around 31 s, and 20 times through the ITI corridor for around 15 s. From the corridor, participants would be guided into the other room (six trials) or back to the same room (four trials) in pseudo-random order.
Automatic P-wave Arrival Time Picking Method for Seismic and Microseismic Data (2011)

Summary P-wave arrival time picking is very significant in the processing of seismic and microseismic data. The method presented here is based on the standard deviation in a moving time window that produces reasonably accurate results when tested on real microseismic dataset comprising of eight receivers with good and poor signal to noise ratio.
Periodic assembly of nanoparticle arrays in disclinations of cholesteric liquid crystals (2017)

An important goal of the modern soft matter science is to discover new self-assembly modalities to precisely control the placement of small particles in space. Spatial inhomogeneity of liquid crystals offers the capability to organize colloids in certain regions such as the cores of the topological defects. Here we report two self-assembly modes of nanoparticles in linear defects-disclinations in a lyotropic colloidal cholesteric liquid crystal: a continuous helicoidal thread and a periodic array of discrete beads. The beads form one-dimensional arrays with a periodicity that matches half a pitch of the cholesteric phase. The periodic assembly is governed by the anisotropic surface tension and elasticity at the interface of beads with the liquid crystal. This mode of self-assembly of nanoparticles in disclinations expands our ability to use topological defects in liquid crystals as templates for the organization of nanocolloids.
Considering User Agreement in Learning to Predict the Aesthetic Quality (2022)

How to robustly rank the aesthetic quality of given images has been a long-standing ill-posed topic. Such challenge stems mainly from the diverse subjective opinions of different observers about the varied types of content. There is a growing interest in estimating the user agreement by considering the standard deviation (σ) of the scores, instead of only predicting the mean aesthetic opinion score (µ). Nevertheless, when comparing a pair of contents, few studies consider how confident are we regarding the difference in the aesthetic scores. In this paper, we thus propose (1) a re-adapted multi-task attention network to predict both the mean opinion score and the standard deviation in an end-to-end manner; (2) a brand-new confidence interval ranking loss that encourages the model to focus on image-pairs that are less certain about the difference of their aesthetic scores. With such loss, the model is encouraged to learn the uncertainty of the content that is relevant to the diversity of observers’ opinions, i.e., user disagreement. Extensive experiments have demonstrated that the proposed multi-task aesthetic model achieves state-of-the-art performance on two different types of aesthetic datasets, i.e., AVA and TMGA.
Direct self-condensation of bio-alcohols in the aqueous phase (2014)

Recyclable iridium catalysts have been developed rationally for the direct self-condensation of ethanol and butanol in water and air.
065 Blockade of Rage with Lentiviral Gene Therapy Accelerates Healing in Diabetic Wounds Over Time (2008)

The diabetic wound is characterized by abnormal, prolonged inflammatory activity and impaired healing. Enhanced interaction between the receptor for advanced glycation end products (RAGE) and its ligands in the diabetic tissue environment has been shown to increase proinflammatory cytokines and tissue-degradative matrix metalloproteinases, resulting in decreased collagen generation. Blockade of RAGE with multiple topical applications of soluble RAGE (sRAGE) on diabetic wounds has been shown to accelerate diabetic wound closure. We investigated the potential efficacy of gene therapy as a method for enhancing sRAGE expression in the diabetic wound. Full thickness 2 × 2 cm2 excisional wounds were created on the dorsae of genetically diabetic db/db mice. Lentiviral vector (1 × 105 PFU in 1 ml saline) carrying the gene for soluble receptor for advanced glycation end products (lenti-sRAGE) was injected into the wound margins and base. Mice were sacrificed at 14-, 21-, and 35-day intervals. Measurement of the residual epithelial gap showed increased healing of lenti-sRAGE-treated wounds compared to wounds treated with saline injection alone. Lenti-sRAGE-treated wounds were significantly smaller (epithelial gap ± SD) than saline-treated wounds at both 21 days (0.77 ± 0.24 cm, compared to 1.13 ± 0.30 cm; P < 0.05) and 35 days (0.51 ± 0.42 cm, compared to 0.86 ± 0.35 cm; P < 0.05). Picrosirius red staining showed that lenti-sRAGE-treated wounds had 2.23 ± 0.35 and 13.26 ± 6.25-fold increases in collagen content relative to saline-treated wounds at 21 and 35 days, respectively (P < 0.05). Preliminary CD31 staining of 21-day wounds demonstrated a twofold increase in neovascularization in lenti-sRAGE-treated wounds versus saline-treated wounds. Lentiviral gene therapy with sRAGE can accelerate diabetic wound healing over time, and genetic modification of the diabetic tissue environment to restore normal inflammatory activity could have a central role in the clinical setting. Supported by a grant from the American Diabetes Association
A photodetector array for acousto-optic signal processors (1989)

Acousto-optic (AO) signal processors are of interest for processing wide bandwidth signals in real-time. Unfortunately the performance of practical systems is often limited by the photodetector array, which must satisfy conflicting requirements concerning sensitivity, dynamic range, and response/readout time. A recently developed photodetector structure has important potential advantages for this application. It uses the exponential current to voltage relationship obtainable with a profile channel metal oxide semiconductor field-effect transistor to provide a steady state logarithmic relationship between incident light intensity and output voltage and a dynamic range exceeding 70 dB. This paper discusses the design considerations associated with the use of the new photodetector structure in the context of a 128 element photodetector array being developed for realtime processing of wide bandwidth signals. This design uses a series-parallel architecture to provide a minimum exposure time of 1 μs. The photodetector and readout electronics are optimized to provide high sensitivity and response speed for transient signals. Simulation results for the time response to pulse signals and the crosstalk performance are presented. These suggest that the dynamic range exceeds 50 dB for pulses less than 1 μs in duration.
On Cluster Validity Indexes in Fuzzy and Hard Clustering Algorithms for Image Segmentation (2007)

This paper addresses the issue of assessing the quality of the clusters found by fuzzy and hard clustering algorithms. In particular, it seeks an answer to the question on how well cluster validity indexes can automatically determine the appropriate number of clusters that represent the data. The paper surveys several key existing solutions for cluster validity in the domain of image segmentation. In addition, it suggests two new indexes. The first one is based on Akaike's information criterion (AIC). While AIC was devoted to other domains such as statistical estimation of model fitting, it is implemented here for the first time as a validation index. The second index is developed from the well-established idea of cross-validation. The existing and new indexes are evaluated and compared on several synthetic images corrupted with noise of varying levels and volumetric MR data.
The In Vivo Survival of Coombs Positive Autologous Erythrocytes Produced by Agglomeration (1966)

Coombs positive erythrocytes were observed following the preservation of autologous, human erythrocytes using glycerol, slow freezing, and agglomeration. In 22 of 48 autotransfusions, the preserved erythrocytes were Coombs positive when tested with an anti‐gamma + non‐gamma globulin serum. In ten of these 22 units, the erythrocytes were tested with both an anti‐7S gamma globulin serum and an anti‐β 1 C globulin serum. All of the erythrocytes in these ten units reacted positively with the anti‐β 1 C globulin serum, and only one unit reacted equivocally with the anti‐7S gamma globulin serum. The reduction in ionic strength during glycerolization allowed for the uptake of the complement fraction β 1 C by the erythrocytes. There was a significant correlation between the Coombs test and the per cent of initial ionic strength of the erythrocyte resuspension medium after glycerolization. There was no significant correlation between the Coombs test and the 24‐hour and seven‐day chromium survivals.
Selection of Metastatic Breast Cancer Cell-Specific Aptamers for the Capture of CTCs with a Metastatic Phenotype by Cell-SELEX (2018)

Circulating tumor cells (CTCs) have the potential to predict metastasis, and the capture of CTCs based on their surface markers is mostly applied for CTC detection. Considering that the CTCs with a metastatic phenotype preferably form a metastatic focus and that aptamers have the ability to bind targets with high specificity and affinity, we selected aptamers directed toward metastatic cells by subtractive Cell-SELEX technology using highly metastatic MDA-MB-231 cells as the target cell and low-metastatic MCF-7 cells as the negative cell for the capture of metastatic CTCs. Affinity and selectivity assays showed that aptamer M3 had the highest affinity, with a K<sub>D</sub> of 45.6 ± 1.2 nM, and had good specificity against several other types of metastatic cancer cells. Based on these findings, we developed an M3-based capture system for CTC enrichment, which has the capability to specifically capture the metastatic cells MDA-MB-231 mixed with non-metastatic MCF-7 cells and CTCs derived from the peripheral blood from metastatic breast cancer patients. A further comparative analysis with the anti-EpCAM probe showed that M3 probe captured epithelial feature-deletion metastatic cells. We developed an aptamer-based CTC capture system through the selection of aptamers by taking whole metastatic cells, not known molecules, as targets, which provided a new insight into CTC capture and Cell-SELEX application.
A semiparametric estimator of survival for doubly truncated data (2010)

Doubly truncated data are often encountered in the analysis of survival times, when the sample reduces to those individuals with terminating event falling on a given observational window. In this paper we assume that some information about the bivariate distribution function (df) of the truncation times is available. More specifically, we represent this information by means of a parametric model for the joint df of the truncation times. Under this assumption, a new semiparametric estimator of the lifetime df is derived. We obtain asymptotic results for the new estimator, and we show in simulations that it may be more efficient than the Efron-Petrosian nonparametric maximum likelihood estimator. Data on the age at diagnosis of childhood cancer in North Portugal are analyzed with the new method.
Deep neural networks for energy load forecasting (2017)

Smartgrids of the future promise unprecedented flexibility in energy management. Therefore, accurate predictions/forecasts of energy demands (loads) at individual site and aggregate level of the grid is crucial. Despite extensive research, load forecasting remains to be a difficult problem. This paper presents a load forecasting methodology based on deep learning. Specifically, the work presented in this paper investigates the effectiveness of using Convolutional Neural Networks (CNN) for performing energy load forecasting at individual building level. The presented methodology uses convolutions on historical loads. The output from the convolutional operation is fed to fully connected layers together with other pertinent information. The presented methodology was implemented on a benchmark data set of electricity consumption for a single residential customer. Results obtained from the CNN were compared against results obtained by Long Short Term Memories LSTM sequence-to-sequence (LSTM S2S), Factored Restricted Boltzmann Machines (FCRBM), “shallow” Artificial Neural Networks (ANN) and Support Vector Machines (SVM) for the same dataset. Experimental results showed that the CNN outperformed SVR while producing comparable results to the ANN and deep learning methodologies. Further testing is required to compare the performances of different deep learning architectures in load forecasting.
Design Multilayer Antireflection Coatings for Terrestrial Solar Cells (2014)

In order to analyze the influence of methods to design antireflection coatings (ARCs) on reflectivity of broadband solar cells, we provide detailed analyses about the ARC coupled with a window layer and the refractive index dispersion effect of each layer. By multidimensional matrix data simulation, two methods were employed to measure the composite reflection of a SiO2/ZnS double-layer ARC within the spectral ranges of 300-870 nm (dual junction) and 300-1850 nm (triple junction) under AM1.5 solar radiation. A comparison study, between the results obtained from the commonly used weighted average reflectance method (WAR) and that from the introduced effective average reflectance method (EAR), shows that the optimization of ARC by EAR method is convenient and feasible.
Indole Alkaloids of Ailanthus altissima (1980)

From the root bark of Ailanthus altis-sima four simple indole alkaloids have been isolated: Cathin-6-one (I), 1-medio xycathin-6-one (II), Methyl 6-methoxy-ß-carboline-1 -carboxylate (III) and an unidentified alkaloid.
Anthropomorphic Remote Manipulator (1991)

Two-armed telerobot undergoing development manipulates objects with dexterity approaching that of human. Designed to be remotely operated by human. Operator wears harness with exoskeletonlike sleeves and gloves; remote manipulator follows operator's arm, hand, and finger movements and feeds back position and force information so operator has sense of manipulating object held by telerobot. Developed for use in outer space. Suited for such terrestrial uses as handling materials and maintaining equipment in hazardous environments where mechanical dexterity and nearly instantaneous feedback of sensory information needed.
Reliable Memristor-based Neuromorphic Design Using Variation- and Defect-Aware Training (2021)

The memristor crossbar provides a unique opportunity to develop a neuromorphic computing system (NCS) with high scalability and energy efficiency. However, the reliability issues that arise from the immature fabrication process and physical device limitations, i.e., variations and stuck-at-faults (SAF), dramatically prevent its wide application in practice. Specifically, variations make the programmed weights deviate from their expected values. On the other hand, defective mem-ristors cannot even represent the weights effectively. In this work, we propose a variation- and defect-aware framework to improve the reliability of memristor-based NCS while minimizing the inference performance loss. We propose to develop analytical weight models to characterize the non-ideal effects of variations and SAFs, which can then be incorporated into a Bayesian neural network as priori and constraint. We then convert the reliability improvement to the neural network training for optimal weights that can accommodate variations and defects across the chips, which does not require computation-intensive retraining or cost-expensive testing. Extensive experimental results with the proposed framework confirm its effective capability of improving the reliability of NCS, while significantly mitigating the inference accuracy degradation under even severe variations and SAFs.
2F26 Fundamental study on data acquisition and processing by catheter tactile sensor composed of organic ferroelectrics (2016)

In this study, we fabricated a prototype catheter type tactile sensor composed of two polyvinylidene fluoride (PVDF) films and evaluated the data acquisition and processing by the sensor to detect the diseased part in a blood vessel. The PVDF films, which have stress (strain) rate dependent output, are located in a silicon rubber cylinder whose outer diameter is 5 [mm]. We inserted the prototype sensor into a blood vessel model whose inner shape was partially changed assuming that these changes occur by a disease. The vessel model consists of a tube whose inner diameter is 8 [mm]. The sensor can detect the position of the projections in the tube. Moreover, peak-to-peak value of the sensor output voltage increases according to the insertion speed. In addition, we can evaluate the surface roughness inside the tube by fourier transform of the sensor output. In the future, we hope to evaluate the sensor with a more practical prototype.
Rapid Ultrasonic Bath Processing for Electron Microscopy (1991)

A new rapid method for the processing of biopsy specimens for electron microscopy is described. The method uses standard reagents and media and employs ultrasonic cleaning bath agitation to accelerate fluid exchange. The procedure takes approximately 2.5 h from specimen excision to polymerized block and gives excellent results.
Prime colors and color imaging (1998)

In modeling color vision, certain visiblewavelengths have special significance. A growing body of scientific work shows that the wavelengths around 450nm, 540nm and 605nm, the so called prime-color (PC) wavelengths, are fundamental to color vision. Perhaps unsurprisingly, these same wavelengths are often discussed in the color imaging literature. Monitors that can display a large gamut of colors and are visually efficient have phosphor-primary peaks at the PC wavelengths. Color cameras that have peak sensitivities at the PC wavelengths have favorable color-balancing properties. Why are the PC wavelengths so important? This paper provides a start toward a mathematical theory to answer this question.
Possible scheme of synthesis-assembling of fullerenes (2001)

A new scheme of fullerene formation is proposed on the basis of the similarity between the experimentally detected carbon structures. According to experimental data, the microclusters of C2 and C10 are synthesized first and then either an intermediate nucleus cluster or an obtainable lower fullerene is assembled from them. A high-symmetry fullerene can be assembled with a high probability from a nucleus cluster with a “good” symmetry. The atomic and electronic structures of molecules such as C36, C60, C70, and C76 are analyzed. For C36, the NMR spectra are calculated and compared with the experimental data.
Trends in aluminum resistance spot welding for the auto industry (2005)

Recent advances in resistance welding technology, alloys, and NDE techniques have helped to reduce manufacturing costs for aluminum sheet structures.
Microarray Analysis of p53-Mediated Transcription: Mutli-Thousand Piece Puzzle or Invitation to Collective Thinking? (2003)

Commentary to Global Genechip Profiling to Identify Genes Responsive to p53-Induced Growth Arrest and Apoptosis in Human Lung Carcinoma Cells. Robinson P, et al. Cancer Biol Ther 2(4):406-415; Microarray Expression Profiling of p53-Dependent Transcriptional Changes in an Immortalized Mouse Embryo Fibroblast Cell Line. Sax JK, et al. Cancer Biol Ther 2(4):416-430; and Microarray Analysis of p53 Target Gene Expression Patterns in the Spleen and Thymus in Response to Ionizing Radiation. Burns TF, et al. Cancer Biol Ther 2(4):431-443.
Enzymatically degradable oxidized dextran–chitosan hydrogels with an anisotropic aligned porous structure (2013)

Enzyme-degradable hydrogels with aligned pores were prepared via unidirectional freezing of a mixed solution of oxidized dextran (oxDex) and chitosan (CHI) followed by cryo-gelation. At the frozen state, imine bonds as the crosslinking points of the hydrogels were formed as a result of the reaction between the aldehyde groups on the oxDex and the amino groups on the CHI. The morphologies of the obtained hydrogels were studied by confocal laser scanning microscopy (CLSM). Microtubular pores aligned along the freezing direction were obtained in the swollen state of the hydrogels. The pore size was adjustable ranging from 20 to 100 μm by controlling the freezing temperature in the unidirectional freezing step. Upon exposure of the hydrogels to chitosanase solution, chitosan can be hydrolyzed into short oligosaccharide fragments leading to collapse and degradation of the gel network. The degradation rate can be tuned by adjusting the gel composition and enzyme concentration.