gebhart/patrepeval huggingface dataset:
Plasmonic computing of spatial differentiation (2017)

Optical analog computing offers high-throughput low-power-consumption operation for specialized computational tasks. Traditionally, optical analog computing in the spatial domain uses a bulky system of lenses and filters. Recent developments in metamaterials enable the miniaturization of such computing elements down to a subwavelength scale. However, the required metamaterial consists of a complex array of meta-atoms, and direct demonstration of image processing is challenging. Here, we show that the interference effects associated with surface plasmon excitations at a single metal-dielectric interface can perform spatial differentiation. And we experimentally demonstrate edge detection of an image without any Fourier lens. This work points to a simple yet powerful mechanism for optical analog computing at the nanoscale.
Statistical screening of system dynamics models (2005)

Abstract This paper describes a pragmatic method of searching for the key inputs to a system dynamics model. This analysis is known as screening. The goal is to learn which of the many uncertain inputs stand out as most influential. The method is implemented with readily available software and relies on the simple correlation coefficient to indicate the relative importance of model inputs at different times in the simulation. The screening is demonstrated with two examples with step‐by‐step instructions. The paper recommends that screening analysis be used in an iterative process of screening and model expansion to arrive at tolerance intervals on model results. The appendices compare screening analysis with analytical methods to identify the key inputs to system dynamics models. Copyright © 2005 John Wiley & Sons, Ltd.
MASS ESTIMATE TECHNIQUES OF MOLECULAR CLOUDS (1994)

We have reviewed three different techniques to estimate molecular cloud mass, and discussed the uncertainties involved. We found that determination of the most important parameter, the abundance, is not very sensitive to the real LTE conditions, and that any possible error in deriving LTE column density may not introduce an error in the total gas column density, as far as the visual extinction is established for the object cloud. The virial technique always endows the largest mass estimate as there are several uncertainties, even if the cloud is in virial equilibrium. The strong indicator of the cloud perturbation is the centroid velocity dispersion. The mass using CO luminosity is based on the empirical law, but weakly dependent on the virial assumption, thus it still gives a larger mass estimate. The mass discrepancy is likely to be inevitable, and a factor of two or three difference between mass estimates could easily be attributed to the uncertainties mentioned above. The LTE mass estimate may be the most reliable one if we use the relation visual extinction and column density of the object cloud, and the intercept is included.
Oxidation of D-glucose by coenzyme PQQ: 1,2-enediolates as substrates for PQQ oxidation (1987)

S. Itoh, M. Mure and Y. Ohshiro, J. Chem. Soc., Chem. Commun., 1987, 1580 DOI: 10.1039/C39870001580
Text Counterfactuals via Latent Optimization and Shapley-Guided Search (2021)

We study the problem of generating counterfactual text for a classifier as a means for understanding and debugging classification. Given a textual input and a classification model, we aim to minimally alter the text to change the model's prediction. White-box approaches have been successfully applied to similar problems in vision where one can directly optimize the continuous input. Optimization-based approaches become difficult in the language domain due to the discrete nature of text. We bypass this issue by directly optimizing in the latent space and leveraging a language model to generate candidate modifications from optimized latent representations. We additionally use Shapley values to estimate the combinatoric effect of multiple changes. We then use these estimates to guide a beam search for the final counterfactual text. We achieve favorable performance compared to recent whitebox and black-box baselines using human and automatic evaluations. Ablation studies show that both latent optimization and the use of Shapley values improve success rate and the quality of the generated counterfactuals.
Dendritic Cells and CD8 T Cell Immunity in Tumor Microenvironment (2018)

Dendritic cells (DCs) play a central role in the regulation of the balance between CD8 T cell immunity versus tolerance to tumor antigens. Cross-priming, a process which DCs activate CD8 T cells by cross-presenting exogenous antigens, plays a critical role in generating anti-tumor CD8 T cell immunity. However, there are compelling evidences now that the tumor microenvironment (TME)-mediated suppression and modulation of tumor-associated DCs (TIDCs) impair their function in initiating potent anti-tumor immunity and even promote tumor progression. Thus, DC-mediated cross-presentation of tumor antigens in tumor-bearing hosts often induces T cell tolerance instead of immunity. As tumor-induced immunosuppression remains one of the major hurdles for cancer immunotherapy, understanding how DCs regulate anti-tumor CD8 T cell immunity in particular within TME has been under intensive investigation. Recent reports on the Batf3-dependent type 1 conventional DCs (cDC1s) in anti-tumor immunity have greatly advanced our understanding on the interplay of DCs and CD8 T cells in the TME, highlighted by the critical role of CD103+ cDC1s in the cross-priming of tumor antigen-specific CD8 T cells. In this review, we will discuss recent advances in anti-tumor CD8 T cell cross-priming by CD103+ cDC1s in TME, and share perspective on future directions including therapeutic applications and memory CD8 T cell responses.
Terahertz Micromachined On-Wafer Probes: Repeatability and Reliability (2012)

An improved micromachined on-wafer probe covering frequencies 500-750 GHz is demonstrated in this paper to address sub-millimeter-wave integrated-circuit testing. Measurements of a prototype WR-1.5 micromachined on-wafer probe exhibit a return loss better than 12 dB and a mean insertion loss of 6.5 dB from 500 to 750 GHz. The repeatability of on-wafer measurements with the micromachined probe is investigated. Monte Carlo simulations are used to identify the dominant error source of on-wafer measurement and to estimate the measurement accuracy. The dominant error source is positioning error, which results in phase uncertainty. Reliability tests show the probe is robust and can sustain over 20 000 contacts.
Synthesis of 8-, 9-, 12-, and 13-mono-<sup>13</sup>C-retinal (1985)

The 8-, 9-, 12-, and 13-mono- 13 C-retinals were synthesized with > 98% chemical purity and 93% 13 C incorporation from 13 C-labelled acetonitrile. Their 13 C– 13 C and 13 C– 1 H nmr coupling constants were determined.
Aerobic exercise for adult patients with major depressive disorder in mental health services: A systematic review and meta-analysis (2018)

Although exercise is associated with depression relief, the effects of aerobic exercise (AE) interventions on clinically depressed adult patients have not been clearly supported. The purpose of this meta-analysis was to examine the antidepressant effects of AE versus nonexercise comparators exclusively for depressed adults (18-65 years) recruited through mental health services with a referral or clinical diagnosis of major depression. Eleven e-databases and bibliographies of 19 systematic reviews were searched for relevant randomized controlled clinical trials. A random effects meta-analysis (Hedges' g criterion) was employed for pooling postintervention scores of depression. Heterogeneity and publication bias were examined. Studies were coded considering characteristics of participants and interventions, outcomes and comparisons made, and study design; accordingly, sensitivity and subgroup analyses were calculated. Across 11 eligible trials (13 comparisons) involving 455 patients, AE was delivered on average for 45 min, at moderate intensity, three times/week, for 9.2 weeks and showed a significantly large overall antidepressant effect (g = -0.79, 95% confidence interval = -1.01, -0.57, P < 0.00) with low and nonstatistically significant heterogeneity (I<sup>2</sup> = 21%). No publication bias was found. Sensitivity analyses revealed large or moderate to large antidepressant effects for AE (I<sup>2</sup> ≤ 30%) among trials with lower risk of bias, trials with short-term interventions (up to 4 weeks), and trials involving individual preferences for exercise. Subgroup analyses revealed comparable effects for AE across various settings and delivery formats, and in both outpatients and inpatients regardless symptom severity. Notwithstanding the small number of trials reviewed, AE emerged as an effective antidepressant intervention.
Engineering structured MOF at nano and macroscales for catalysis and separation (2011)

Here, we present for the first time the combination of the postfunctionalization of a MOF with its shaping as structured bodies. This study deals with the porous zinc carboxylimidazolate material known as SIM-1. A great advantage of this method is that the aldehyde moieties present on the structure walls allow organic modifications in the solid state, such as imine synthesis by condensation with primary amines to give the corresponding imino-functionalized SIM-2. We show that this postfunctionalization can be carried out on shaped SIM-1 bodies and films. The parent SIM-1 structured materials are prepared by direct in situ synthesis on a variety of supports for catalysis such as alumina beads and cordierite monoliths, and for separation applications using supports such as alumina tubes, fibers and anodic alumina disks. The hydrophobic SIM-2(C12) prepared on alumina beads is found to be an active catalyst for the Knoevenagel condensation, while its analogous supported membrane on alumina tube is efficient for CO2/N2 separation under humid conditions.
Maturation of nonadrenergic noncholinergic inhibitory system in normal and allergen-sensitized rabbits (1994)

We investigated the functional existence of the nonadrenergic noncholinergic inhibitory (NANCi) system in developing rabbit airways in vitro. Furthermore, we evaluated the effect of parenteral exposure to a specific allergen (ragweed) on the maturation of this neural pathway. NANCi responses were studied on tracheal smooth muscle (TSM) segments obtained from normal and ragweed-sensitized New Zealand White rabbits at 1, 2, 4, and 12 wk of age. The TSM segments were removed and placed in tissue baths containing modified Krebs-Henseleit solution, atropine (1 x 10(-5) M), and propranolol (5 x 10(-6) M). After contraction with neurokinin A (1 x 10(-5) M), electrical field stimulation was applied at stimulation frequencies ranging from 5 to 30 Hz to determine the frequency that produced maximal relaxation. The NANCi response to EFS was measured and expressed as the mean (+/- SE) percent relaxation at 20 Hz, because this stimulation frequency gave the maximal NANCi response at each age studied. TSM segments obtained from control rabbits at 1 wk of age did not demonstrate a NANCi response at the frequencies of stimulation used. By contrast, a reproducible NANC relaxation was demonstrated in TSM from 2-, 4-, and 12-wk-old rabbits. The magnitude of this response was 27 +/- 4.7 (n = 10), 29 +/- 4.8 (n = 9), and 37 +/- 4% (n = 18), respectively. The same experiments performed on TSM segments obtained from ragweed-sensitized animals gave significantly decreased values of NANCi response. In 2-, 4-, and 12-wk-old rabbits, the NANCi responses were 11.5 +/- 3.4 (n = 9), 11 +/- 2 (n = 13), and 16 +/- 4.2% (n = 14).(ABSTRACT TRUNCATED AT 250 WORDS)
Efficient Privacy-Preserving Machine Learning in Hierarchical Distributed System (2018)

With the dramatic growth of data in both amount and scale, distributed machine learning has become an important tool for the massive data to finish the tasks as prediction, classification, etc. However, due to the practical physical constraints and the potention privacy leakage of data, it is infeasible to aggregate raw data from all data owners for the learning purpose. To tackle this problem, the distributed privacy-preserving learning approaches are introduced to learn over all distributed data without exposing the real information. However, existing approaches have limits on the complicated distributed system. On the one hand, traditional privacy-preserving learning approaches rely on heavy cryptographic primitives on training data, in which the learning speed is dramatically slowed down due to the computation overheads. On the other hand, the complicated system architecture becomes a barrier in the practical distributed system. In this paper, we propose an efficient privacy-preserving machine learning scheme for hierarchical distributed systems. We modify and improve the collaborative learning algorithm. The proposed scheme not only reduces the overhead for the learning process but also provides the comprehensive protection for each layer of the hierarchical distributed system. In addition, based on the analysis of the collaborative convergency in different learning groups, we also propose an asynchronous strategy to further improve the learning efficiency of hierarchical distributed system. At the last, extensive experiments on real-world data are implemented to evaluate the privacy, efficacy, and efficiency of our proposed schemes.
Transductive malware label propagation: Find your lineage from your neighbors (2014)

The numerous malware variants existing in the cyberspace have posed severe threats to its security. Supervised learning techniques have been applied to automate the process of classifying malware variants. Supervised learning, however, suffers in situations where we have only scarce labeled malware samples. In this work, we propose a transductive malware classification framework, which propagates label information from labeled instances to unlabeled ones. We improve the existing Harmonic function approach based on the maximum confidence principle. We apply this framework on the structural information collected from malware programs, and propose a PageRank-like algorithm to evaluate the distance between two malware programs. We evaluate the performance of our method against the standard Harmonic function method as well as two popular supervised learning techniques. Experimental results suggest that our method outperforms these existing approaches in classifying malware variants when only a small number of labeled samples are available.
Characterization of cyclosporin A transport in cultured rabbit corneal epithelial cells: P-glycoprotein transport activity and binding to cyclophilin. (1999)

These results suggest that in RCEC the tear-side-facing membrane has a P-gp-mediated drug efflux pump. In addition, there is suggestive evidence for the presence of the cytosolic protein, cyclophilin. The presence of P-gp in these cells could help protect them from being damaged by the uptake of toxic substances.
Cellular, Molecular Consequences of Peroxisome Proliferator- Activated Receptor-δ Activation in Ovarian Cancer Cells (2006)

Peroxisome proliferator-activated receptor-gamma (PPAR-gamma) is a ligand-activated transcription factor. In addition to its canonical role in lipid and glucose metabolism, PPAR-gamma controls cell proliferation, death, and differentiation in several tissues. Here we have examined the expression of PPAR-gamma in ovarian tumors and the cellular and molecular consequences of its activation in ovarian cancer cells. PPAR-gamma was expressed in a large number of epithelial ovarian tumors and cell lines. The PPAR-gamma ligand ciglitazone inhibited the growth and clonogenic survival of ovarian cancer cells, inducing cell cycle arrest and cell death. Growth inhibition by ciglitazone was reversed by the PPAR-gamma antagonist GW9662, indicating the involvement of PPAR-gamma-dependent mechanisms. Microarray-based gene profiling revealed complex changes in the transcriptional program of ovarian cancer cells on treatment with ciglitazone and identified multiple pathways that may contribute to PPAR-gamma ligands' antitumor activity. Genes upregulated by ciglitazone were predominantly associated with metabolic, differentiation, and tumor-suppressor pathways, whereas downregulated genes were involved in cell proliferation, cell cycle, cell organization, and steroid biosynthesis. Collectively, our data indicate that PPAR-gamma activation by selective agonists is a valid strategy for ovarian cancer therapy and prevention, and should be tested alone and in combination with other anticancer drugs.
[Synthesis of chrysin derivatives and their interaction with DNA]. (2007)

Using chrysin as a leading compound, intermediate 5, 7-dihydroxy-6, 8-bis (hydroxymethyl) flavone (1) was synthesized by hydroxymethylation. The intermediate reacted with different alcohols to afford 5, 7-dihydroxy-6, 8-bis ( methoxymethyl) flavone (2), 6, 8-bis (ethoxymethyl) -5, 7dihydroxyflavone (3), 6, 8-bis-(butoxymethyl)-5, 7-dihydroxyflavone (4), 6, 8-bis (pentyloxymethyl) -5,7-dihydroxy flavone (5) and 6, 8-bis-(ethoxymethyl) -5-hydroxy-7-methoxyflavone (6). These compounds were characterized by IR, 1H NMR, 13C NMR and element analysis. The crystal structure of 6 was determined by X-ray crystal diffraction. The interaction of the derivatives with CT-DNA was studied by fluorescent spectroscopy. According to the Stern-Volmer equation, the quenching constants of the compounds 1 - 4 were measured, separately, they were K(q1) = 9.71 x 10(3) L x mol(-1), K(q2) = 2.25 x 10(4) L x mol(-1), K(q3) = 1.03 x 10(4) L x mol(-1) and K(q4) = 7.96 x 10(3) L x mol(-1). Compounds 1-4 showed higher binding affinity with DNA than chrysin did. The results provided the experimental basis for developing a more effective flavonoid and worthing further thoroughly study.
Joint Autoregressive and Hierarchical Priors for Learned Image Compression (2018)

Recent models for learned image compression are based on autoencoders, learning approximately invertible mappings from pixels to a quantized latent representation. These are combined with an entropy model, a prior on the latent representation that can be used with standard arithmetic coding algorithms to yield a compressed bitstream. Recently, hierarchical entropy models have been introduced as a way to exploit more structure in the latents than simple fully factorized priors, improving compression performance while maintaining end-to-end optimization. Inspired by the success of autoregressive priors in probabilistic generative models, we examine autoregressive, hierarchical, as well as combined priors as alternatives, weighing their costs and benefits in the context of image compression. While it is well known that autoregressive models come with a significant computational penalty, we find that in terms of compression performance, autoregressive and hierarchical priors are complementary and, together, exploit the probabilistic structure in the latents better than all previous learned models. The combined model yields state-of-the-art rate--distortion performance, providing a 15.8% average reduction in file size over the previous state-of-the-art method based on deep learning, which corresponds to a 59.8% size reduction over JPEG, more than 35% reduction compared to WebP and JPEG2000, and bitstreams 8.4% smaller than BPG, the current state-of-the-art image codec. To the best of our knowledge, our model is the first learning-based method to outperform BPG on both PSNR and MS-SSIM distortion metrics.
Memetic multilevel hypergraph partitioning (2018)

Hypergraph partitioning has a wide range of applications such as VLSI design or scientific computing. With focus on solution quality we develop the first multilevel memetic algorithm to tackle the problem. Key components of our contribution are new effective multilevel recombination and mutation operations that provide a large amount of diversity. We perform a wide range of experiments on a benchmark set containing instances from application areas such VLSI, SAT solving, social networks, and scientific computing. Compared to the state-of-the-art hypergraph partitioning tools hMetis, PaToH, and KaHyPar, our new algorithm computes the best results on almost all instances of the benchmark set.
Information theory applied to the sparse gene ontology annotation network to predict novel gene function (2007)

Supplementary data are available at Bioinformatics online.
Identification of a recent recombination event within the human beta-globin gene cluster. (1984)

In a detailed study of inheritance of DNA sequence polymorphism in a large reference pedigree, an individual was identified with an apparent genetic recombination event within the human beta-globin gene cluster. Analysis of the haplotypes of relevant individuals within this pedigree suggested that the meiotic crossing-over event is likely to have occurred within a 19.8-kilobase-pair region of the beta-globin gene cluster. Analysis of other DNA markers closely linked to the beta-globin gene cluster--segment 12 of chromosome 11 (D11S12) and loci for insulin, the cellular oncogene c-Ha-ras, and preproparathyroid hormone--confirmed that a crossover event must have occurred within the region of chromosome 11 between D11S12 and the beta-globin gene cluster. It is suggested that the event observed has occurred within a DNA region compatible with recombinational "hot spots" suggested by population studies.
Thermally Assisted Magnetization Reversal in Submicron-Sized Magnetic Thin Films (2000)

We have measured the rate of thermally assisted magnetization reversal of submicron-sized magnetic thin films. For fields H just less than the zero-temperature switching field H(C), the probability of reversal, P(exp)(s)(t), increases for short times t, achieves a maximum value, and then decreases exponentially. Micromagnetic simulations exhibit the same behavior and show that the reversal proceeds through the annihilation of two domain walls that move from opposite sides of the sample. The behavior of P(exp)(s)(t) can be understood through a simple "energy-ladder" model of thermal activation.
Active Matrix Electronic Skin Strain Sensor Based on Piezopotential‐Powered Graphene Transistors (2015)

A piezopotential-powered active matrix strain sensor array based on a piezopotential-gated graphene transistor (GT) is demonstrated using a piezoelectric polymer. The strain sensor based on the piezopotential-gated GT exhibits excellent performance, including ultrahigh sensitivity (gauge factor = 389) and good durability (>3000 bending and releasing cycles) with a minimum detectable strain at 0.008%.
Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer (2016)

Mutation analysis of acetylation and ubiquitination PTM sites reveals their importance in cancer. As PTM networks are increasingly mapped and related enzymes are often druggable, deeper investigation of specific associated mutations may lead to the discovery of treatment-relevant cellular mechanisms.
Intelligent Data Analysis (2005)

Intelligent Data Analysis (IDA) is an interdisciplinary study concerned with the effective analysis of data. IDA draws the techniques from diverse fields, including artificial intelligence, databases, high-performance computing, pattern recognition, and statistics. These fields often complement each other (e.g., many statistical methods, particularly those for large data sets, rely on computation, but brute computing power is no substitute for statistical knowledge) (Berthold & Hand 2003; Liu, 1999).