gebhart/patrepeval huggingface dataset:
Ectopic Defense Gene Expression Is Associated with Growth Defects in Medicago truncatula Lignin Pathway Mutants (2019)

Lignin provides essential mechanical support for plant cell walls but decreases the digestibility of forage crops and increases the recalcitrance of biofuel crops. Attempts to modify lignin content and/or composition by genetic modification often result in negative growth effects. Although several studies have attempted to address the basis for such effects in individual transgenic lines, no common mechanism linking lignin modification with perturbations in plant growth and development has yet been identified. To address whether a common mechanism exists, we have analyzed transposon insertion mutants resulting in independent loss of function of five enzymes of the monolignol pathway, as well as one double mutant, in the model legume <i>Medicago truncatula</i> These plants exhibit growth phenotypes from essentially wild type to severely retarded. Extensive phenotypic, transcriptomic, and metabolomics analyses, including structural characterization of differentially expressed compounds, revealed diverse phenotypic consequences of lignin pathway perturbation that were perceived early in plant development but were not predicted by lignin content or composition alone. Notable phenotypes among the mutants with severe growth impairment were increased trichome numbers, accumulation of a variety of triterpene saponins, and extensive but differential ectopic expression of defense response genes. No currently proposed model explains the observed phenotypes across all lines. We propose that reallocation of resources into defense pathways is linked to the severity of the final growth phenotype in monolignol pathway mutants of <i>M. truncatula</i>, although it remains unclear whether this is a cause or an effect of the growth impairment.
A Closer Look at Art Mediums: The MAMe Image Classification Dataset (2020)

Art is an expression of human creativity, skill and technology. An exceptionally rich source of visual content. In the context of AI image processing systems, artworks represent one of the most challenging domains conceivable: Properly perceiving art requires attention to detail, a huge generalization capacity, and recognizing both simple and complex visual patterns. To challenge the AI community, this work introduces a novel image classification task focused on museum art mediums, the MAMe dataset. Data is gathered from three different museums, and aggregated by art experts into 29 classes of medium (i.e. materials and techniques). For each class, MAMe provides a minimum of 850 images (700 for training) of high-resolution and variable shape. The combination of volume, resolution and shape allows MAMe to fill a void in current image classification challenges, empowering research in aspects so far overseen by the research community. After reviewing the singularity of MAMe in the context of current image classification tasks, a thorough description of the task is provided, together with dataset statistics. Baseline experiments are conducted using well-known architectures, to highlight both the feasibility and complexity of the task proposed. Finally, these baselines are inspected using explainability methods and expert knowledge, to gain insight on the challenges that remain ahead.
ZrO2/TiO2 Electron Collection Layer for Efficient Meso-Superstructured Hybrid Perovskite Solar Cells (2016)

Since the first reports of efficient organic-inorganic perovskite solar cells in 2012, an explosion of research activity has emerged around the world, which has led to a rise in the power conversion efficiencies (PCEs) to over 20%. Despite the impressive efficiency, a key area of the device which remains suboptimal is the electron extraction layer and its interface with the photoactive perovskite. Here, we implement an electron collection "bilayer" composed of a thin layer of zirconia coated with titania, sitting upon the transparent conductive oxide fluorine-doped tin oxide (FTO). With this double collection layer we have reached up to 17.9% power conversion efficiency, delivering a stabilized power output (SPO) of 17.0%, measured under simulated AM 1.5 sunlight of 100 mW cm<sup>-2</sup> irradiance. Finally, we propose a mechanism of the charge transfer processes within the fabricated architectures in order to explain the obtained performance of the devices.
Responsibility for publication of the school paper in Indiana high schools in cities of less than 18,000 population (1948)

There is no abstract available for this research paper.
Automated Defect Inspection: A Valuable Tool For Proactive Defect Control (1988)

Defect control in a VLSI production facility is a critical activity for establishing stability and improvement in final die yield. A key aspect of any defect control program is visual inspection of product wafers during their manufacture. Traditionally this has been executed by operators. However, a visual inspection program utilizing automated defect detection equipment has been developed and will be described in this paper. The program places emphasis on monitoring and detecting defects as they occur. The bulk of the inspections are done on critical layers (i.e. layers with a high density of printed and etched patterns) as they will be most susceptible to yield loss. A highly controlled classification system along with proper training of operators is used to maintain the integrity of the collected defect data. A flexible data base, in which the defect data is entered, is used to maximize the analysis techniques that can be applied with this inspection program. Finally, examples of successful application of the program will be described.
Quantum BCH Codes (1999)

After a brief introduction to both quantum computation and quantum error correction, we show how to construct quantum error-correcting codes based on classical BCH codes. With these codes, decoding can exploit additional information about the position of errors. This error model - the quantum erasure channel - is discussed. Finally, parameters of quantum BCH codes are provided.
The diversity of fungi in aerobic sewage granules assessed by 18S rRNA gene and ITS sequence analyses (2009)

Aerobic sewage granules are dense, spherical biofilms, regarded as a useful and promising tool in wastewater treatment processes. Recent studies revealed that fungi can be implemented in biofilm formation. This study attempts to uncover the fungal diversity in aerobic granules by sequence analysis of the 18S and 5.8S rRNA genes and the internal transcribed spacer regions. For this purpose, appropriate PCR and sequencing primer sets were selected and an improved DNA isolation protocol was used. The sequences of 41 isolates were assigned to the taxonomic groups Pleosporaceae, Xylariales, Theleobolaceae, Claviceps, Aureobasidium, Candida boleticola, and Tremellomycetes within the fungi. It turned out that the fungal community composition in granules depended on the wastewater type and the phase of granule development.
A cardiac electro-physiological model based approach for filtering high frequency ECG noise (2007)

With an increasing focus on automatic diagnoses of cardiac disease through ECG signals, de-noising techniques that do not introduce artifacts have become necessary. This paper proposes a model based approach for removing high frequency noise from ECG signals. The proposed modeling technique is based on the propagation of the electric waves over the cardiac tissue. The proposed approach models the crucial nodes as a difference between two sigmoid functions. The ECG signal is modeled as the sum of the activity at the SA node, AV node, Bundle branches, Purkenji fibers, and right and left ventricles. The model is adapted to the targeted ECG signal using a nonlinear least squares optimization technique. The proposed filtering approach is applied to randomly selected ECGs from the long-term ST database. A quantitative analysis is performed on simulated ECG signals perturbed with white noise with ST signal to noise ratios ranging from -25 to 5 dB.
Polarization holding in randomly perturbed fibers (1982)

In many applications, single-mode fibers which can transmit a stable well-defined state of polarization are required. This has led to development of several types of highly birefringent fibers which should be able to hold, or propagate, linearly polarized light along the entire fiber length, even when subjected to irregular and time-dependent perturbing birefringences. These polarization-maintaining fibers are usually characterized by the strength of their linear birefringence βi or, equivalently, their beat length Lp = 2π//βi which can be measured quite simply. The more relevant characterization, namely, how well the fibers hold polarization when subjected to perturbations, is not so simple to perform.
Influences of damage and contamination from reactive ion etching on selective tungsten deposition in a low-pressure chemical-vapor-deposition reactor (1996)

Reactive ion etching (RIE) used in contact hole formation can result in damage and contamination of the underlying silicon substrate. In this work, influences of these phenomena on selective tungsten deposition in a low-pressure chemical-vapor-deposition reactor have been studied. The damage was generated because of ion bombardment and radiation-induced bonding changes in silicon lattices. It causes large Si consumption, rough W/Si interface during tungsten deposition, and large leakage current of W/Si Schottky structure. Simultaneously, contamination occurred with two forms of residual layers and impurity permeation layers in fluorocarbon-based RIE chemistries. The CF4/CHF3/O2 RIE of oxide produces the SiFxCyOz complex layers deposited on the sidewall and on the Si surface as well as the embedding of impurities such as F and C in the Si substrate. The creep-up, selectivity loss, lateral encroachment, high W film resistivity, and rough W/Si interface have been observed in the contaminated samples. Accordingly, a post-RIE etching technique used to remove the damage and contaminants before tungsten growth has been developed. A CF4/O2 plasma etching followed with an O2 plasma ashing step exhibits the capability of efficient surface cleaning. The excellent characteristics of W films such as elimination of encroachment and creep-up, low selectivity loss (i.e., 0.25 pcs/cm2), low resistivity of W films, smooth W/Si interface, and very low leakage current of W/Si contacts are thus obtained.
More on Thermoregulatory Thresholds with Halothane (1989)

Resident in Anesthesiology, Assistant Professor of Anesthesiology and Neurosurgery, Departments of Anesthesiology and Neurosurgery University of Florida College of Medicine Gainesville, Florida 32610–0254
2D QSAR Studies on Series of Human Beta-secretase (BACE-1) Inhibitors (2014)

β-secretase (BACE-1) plays a pivotal role in the β-Amyloid plaques formation, which is responsible for progressive cognitive and memory loss commonly found in Alzheimer disease patients. As a consequence, it has been considered as a good target for drug development efforts. Early work focused on the synthesis of peptidomimetics, but poor pharmacokinetics profile prevented advancing lead compounds to clinical trials. As an alternative, aminoimidazoles, aminohydantoins and aminopyridines derivatives that inhibit BACE-1 were designed. Herein we report statistically sound descriptor- based (r(2) = 0.87, q(2) = 0.85, 6 PCs) and fragment-based (r(2) = 0.91, q(2) = 0.84, 6 PCs) QSAR models, that show high predictive ability (r(2)pred = 0.84, averaged r(2)m=0.78) and underscore polar interactions that are important for BACE-1 inhibition.
Imaging of cerebral tryptophan metabolism using 7-[18F]FTrp-PET in a unilateral Parkinsonian rat model (2021)

Degradation products of the essential amino acid tryptophan (Trp) are important signaling molecules in the mammalian brain. Trp is metabolized either through the kynurenine pathway or enters serotonin and melatonin syntheses. The aim of the present work was to examine the potential of the novel PET tracer 7-[<sup>18</sup>F]fluorotryptophan ([<sup>18</sup>F]FTrp) to visualize all three pathways in a unilateral 6-OHDA rat model. [<sup>18</sup>F]FDOPA-PET scans were performed in nine 6-OHDA-injected and six sham-operated rats to assess unilateral dopamine depletion severity four weeks after lesion placement. Afterwards, 7-[<sup>18</sup>F]FTrp-PET scans were conducted at different timepoints up to seven months after 6-OHDA injection. In addition, two 6-OHDA-injected rats were examined for neuroinflammation using [<sup>18</sup>F]DAA1106-PET. 7-[<sup>18</sup>F]FTrp-PET showed significantly increased tracer uptake at the 6-OHDA injection site which was negatively correlated to time after lesion placement. Accumulation of [<sup>18</sup>F]DAA1106 at the injection site was increased as well, suggesting that 7-[<sup>18</sup>F]FTrp uptake in this region may reflect kynurenine pathway activity associated with inflammation. Bilaterally in the dorsal hippocampus, 7-[<sup>18</sup>F]FTrp uptake was significantly decreased and was inversely correlated to dopamine depletion severity, indicating that it reflects reduced serotonin synthesis. Finally, 7-[<sup>18</sup>F]FTrp uptake in the pineal gland was significantly increased in relation with dopamine depletion severity, providing evidence that melatonin synthesis is increased in the 6-OHDA rat model. We conclude that 7-[<sup>18</sup>F]FTrp is able to detect alterations in both serotonin/melatonin and kynurenine metabolic pathways, and can be applied to visualize pathologic changes related to neurodegenerative processes.
A Novel Ultraviolet Irradiation Technique for Shape-Controlled Synthesis of Gold Nanoparticles at Room Temperature (1999)

Shape-controlled gold nanoparticles were synthesized using a novel ultraviolet irradiation technique at room temperature. The very slow ultraviolet irradiation photoreduction process may favor the formation of the shaped gold nanoparticles. It was found that not only the concentration of gold cations and the irradiation time but also the concentration and the species of polymer capping materials play important roles in the morphology control of the gold nanoparticles.
Effect of Fish Bone Bioactive Peptides on Oxidative, Inflammatory and Pigmentation Processes Triggered by UVB Irradiation in Skin Cells (2021)

In the present study, we evaluated for the first time the photoprotective effect of fish bone bioactive peptides (FBBP) preparation isolated from silver carp (<i>Hypophthalmichthys molitrix</i>) discarded tissue using in vitro experimental models of skin cells exposed to ultraviolet B (UVB) irradiation and stressing agents. FBBP preparation was obtained by papain treatment of minced bones and centrifugal ultrafiltration, and the molecular weight (MW) distribution was characterized by size exclusion and reversed-phase high performance liquid chromatography (RP-HPLC). In vitro assessment of the effect of FBBP pretreatment in UVB-irradiated L929 fibroblasts and HaCaT keratinocytes revealed their cytoprotective activity. Their capacity to efficiently reduce reactive oxygen species (ROS) production and lipid peroxidation varied in a dose-dependent manner, and it was greater in fibroblasts. A decrease of proinflammatory cytokines secretion, in particular of tumor necrosis factor alpha (TNF-α), was found after FBBP pretreatment of THP-1-derived inflamed macrophages. Melanin production and tyrosinase activity investigated in UVB-irradiated Mel-Juso cells were lowered in direct relation to FBBP concentrations. FBBP fractions with high radical scavenging activity were separated by ion exchange chromatography, and two collagenic sequences were identified. All these results offer new scientific data on aquaculture fish bone-derived peptides confirming their ability to control the antioxidant, anti-inflammatory and pigmentation processes developed during UV irradiation of skin cells and recommend their use as valuable natural ingredients of photoprotective cosmeceutical products.
Evidence for threshold switching in the set process of NiO-based RRAM and physical modeling for set, reset, retention and disturb prediction (2008)

This work addresses the set and reset mechanisms in NiO-based resistive-switching memory (RRAM) devices, presenting a new physics-based model for RRAM reliability and programming. We show experimental evidence that the set process is initiated by threshold switching, that is a reversible electronic transition to a high conductance state. We develop set/reset models for prediction of programming voltage and time under sweep or pulsed conditions. The speed limitations of RRAMs are then assessed by a detailed study of reset operation in the pulsed regime, showing evidence for over-reset under high-voltage, fast programming conditions (< 1 mus).
Clinical and serological evaluation of a novel CENP-A peptide based ELISA (2010)

Anti-CENP-A antibodies as determined by peptide ELISA represent a sensitive, specific and independent marker for the detection of ACA and are useful biomarkers for the diagnosis of SSc. Our data suggest that anti-CENP-A antibodies are a more specific biomarker for SSc than antibodies to CENP-B. Furthers studies are required to verify these findings.
A dynamic packet reservation multiple access scheme for wireless ATM (2002)

Dynamic packet reservation multiple access (DPRMA) is a medium access control protocol for wireless multimedia applications. It allows the integration of both constant bit rate and variable bit rate traffic through a single access control mechanism that permits users to specify their bandwidth requirements. Users are allowed to repeatedly update this information in order to reflect any changes in their data rates. A base station analyzes the mobiles' requests, determines which can be accommodated, and conveys the resulting bandwidth assignments to the users. The ability of a mobile to initially reserve a portion of the channel capacity and to then dynamically alter this reservation is a primary feature of the system. In DPRMA, an attempt is made to match the capacity assigned to the user with the user generation rate. Furthermore, this capacity can be allocated using fractional or multiple slot assignments. The scheme is shown to provide improved performance over a system with a modified version of the packet reservation multiple access (PRMA) scheme.
Biomethane potential of wine lees from mesophilic anaerobic digestion (2023)

Wine lees (WL) are undervalued residues from the wine-making process. Anaerobic digestion (AD) of WL is highly challenging due to the acidic pH and high content of readily biodegradable compounds. This study investigated the biomethane potential (BMP) of 3 WL samples through mesophilic batch tests fed with 2–3 % total solids. The influence of wood-based biochar (BC), considering 2 different BCs and doses (3 and 10 g L−1), was also assessed. BMP values up to 1.257 Nm3 kgVS−1 and 92–96 % soluble COD removal were recorded. However, the inhibition of methanogenesis was observed due to organic acids accumulation exceeding 21–24 g L−1. BC addition didn’t improve biomethane production in the considered experimental conditions. This study proved that WL is a highly attractive AD substrate, considering its high biodegradability and availability throughout the year, although the process must be carefully operated.
Linear Sketching over $\mathbb F_2$ (2016)

We initiate a systematic study of linear sketching over $\mathbb F_2$. For a given Boolean function $f \colon \{0,1\}^n \to \{0,1\}$ a randomized $\mathbb F_2$-sketch is a distribution $\mathcal M$ over $d \times n$ matrices with elements over $\mathbb F_2$ such that $\mathcal Mx$ suffices for computing $f(x)$ with high probability. We study a connection between $\mathbb F_2$-sketching and a two-player one-way communication game for the corresponding XOR-function. Our results show that this communication game characterizes $\mathbb F_2$-sketching under the uniform distribution (up to dependence on error). Implications of this result include: 1) a composition theorem for $\mathbb F_2$-sketching complexity of a recursive majority function, 2) a tight relationship between $\mathbb F_2$-sketching complexity and Fourier sparsity, 3) lower bounds for a certain subclass of symmetric functions. We also fully resolve a conjecture of Montanaro and Osborne regarding one-way communication complexity of linear threshold functions by designing an $\mathbb F_2$-sketch of optimal size. 
Furthermore, we show that (non-uniform) streaming algorithms that have to process random updates over $\mathbb F_2$ can be constructed as $\mathbb F_2$-sketches for the uniform distribution with only a minor loss. In contrast with the previous work of Li, Nguyen and Woodruff (STOC'14) who show an analogous result for linear sketches over integers in the adversarial setting our result doesn't require the stream length to be triply exponential in $n$ and holds for streams of length $\tilde O(n)$ constructed through uniformly random updates. Finally, we state a conjecture that asks whether optimal one-way communication protocols for XOR-functions can be constructed as $\mathbb F_2$-sketches with only a small loss.
Perspective—Enhancing Active Anode Material Performance for Lithium-Ion Batteries via Manipulation of Interfacial Chemistry (2020)

Over the past decade, conversion-type anodes have been viewed as an attractive frontrunner for use in the next-generation of high-capacity battery materials. However, many technological limitations exist in the stability and long-term reliability of these anodes for the commercialization of these electrodes. This perspective studies how interfacial interactions between different components of the electrode can help elucidate the key physical and chemical properties needed for the development of high-capacity materials for battery applications.
Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome (2020)

State-of-the-art machine learning (ML) artificial intelligence methods are increasingly leveraged in clinical predictive modeling to provide clinical decision support systems to physicians. Modern ML approaches such as artificial neural networks (ANNs) and tree boosting often perform better than more traditional methods like logistic regression. On the other hand, these modern methods yield a limited understanding of the resulting predictions. However, in the medical domain, understanding of applied models is essential, in particular, when informing clinical decision support. Thus, in recent years, interpretability methods for modern ML methods have emerged to potentially allow explainable predictions paired with high performance. To our knowledge, we present in this work the first explainability comparison of two modern ML methods, tree boosting and multilayer perceptrons (MLPs), to traditional logistic regression methods using a stroke outcome prediction paradigm. Here, we used clinical features to predict a dichotomized 90 days post-stroke modified Rankin Scale (mRS) score. For interpretability, we evaluated clinical features' importance with regard to predictions using deep Taylor decomposition for MLP, Shapley values for tree boosting and model coefficients for logistic regression. With regard to performance as measured by Area under the Curve (AUC) values on the test dataset, all models performed comparably: Logistic regression AUCs were 0.83, 0.83, 0.81 for three different regularization schemes; tree boosting AUC was 0.81; MLP AUC was 0.83. Importantly, the interpretability analysis demonstrated consistent results across models by rating age and stroke severity consecutively amongst the most important predictive features. For less important features, some differences were observed between the methods. Our analysis suggests that modern machine learning methods can provide explainability which is compatible with domain knowledge interpretation and traditional method rankings. Future work should focus on replication of these findings in other datasets and further testing of different explainability methods.