gebhart/patrepeval huggingface dataset:
Melatonin exerts by an autocrine loop antiproliferative effects in cholangiocarcinoma; its synthesis is reduced favoring cholangiocarcinoma growth (2011)

Cholangiocarcinoma (CCA) is a devastating biliary cancer. Melatonin is synthesized in the pineal gland and peripheral organs from serotonin by two enzymes, serotonin N-acetyltransferase (AANAT) and acetylserotonin O-methyltransferase (ASMT). Cholangiocytes secrete neuroendocrine factors, including serotonin-regulating CCA growth by autocrine mechanisms. Melatonin exerts its effects by interaction with melatonin receptor type 1A/1B (MT1/MT2) receptors. We propose that 1) in CCA, there is decreased expression of AANAT and ASMT and secretion of melatonin, changes that stimulate CCA growth; and 2) in vitro overexpression of AANAT decreases CCA growth. We evaluated the 1) expression of AANAT, ASMT, melatonin, and MT1/MT2 in human nonmalignant and CCA lines and control and CCA biopsy samples; 2) melatonin levels in nonmalignant and CCA lines, and bile and serum from controls and patients with intrahepatic CCA; 3) effect of melatonin on the growth and expression of AANAT/ASMT and MT1/MT2 in CCA lines implanted into nude mice; and 4) effect of AANAT overexpression on the proliferation, apoptosis, and expression of MT1/MT2 in Mz-ChA-1 cells. The expression of AANAT, ASMT, and melatonin decreased, whereas MT1/MT2 expression increased in CCA lines and biopsy samples. Melatonin secretion decreased in the supernatant of CCA lines and bile of CCA patients. Melatonin decreased xenograft CCA tumor growth in nude mice by increased AANAT/ASMT and melatonin, along with reduced MT1/MT2 expression. Overexpression of AANAT in Mz-ChA-1 cells inhibited proliferation and MT1/MT2 expression and increased apoptosis. There is dysregulation of the AANAT/ASMT/melatonin → melatonin receptor axis in CCA, which inhibited melatonin secretion and subsequently enhanced CCA growth.
Optical architectures for an adaptive associative processing module (1985)

There has been a recent resurgence of interest in associative-processing/neural-network architectures as a model for parallel processing, particularly in such difficult problem domains as image understanding and artificial intelligence. Optics offers unique capabilities for implementing the massive parallel interconnection between successive 1-D and/or 2-D information arrays required by these architectures. Furthermore, these systems are often low-precision (e.g., binary) and hence are compatible with the limited dynamic-range capabilities of optics. We are developing optical architectures consisting of multiple adaptive, associative modules 1 interconnected and cascaded in particular configurations, according to a variety of organizational principles. The experimental performance of actual optical implementations of the individual adaptive associative modules will be discussed. These optical modules adapt as they are exposed to associated information pattern vectors ( u,v ), so that subsequent presentation of one pattern, u, results in recall of the other, v . The set of associations is dynamically learned in real time and stored as an electron charge distribution on an electrooptic crystal in a spatial light modulator. These architectures include feedback, which makes them self-correcting to a variety of optical system aberrations, and they have the capacity to store N associated pairs of N -element vectors, where N of a few hundred appear feasible.
Resampling approach for anomalous change detection (2007)

We investigate the problem of identifying pixels in pairs of co-registered images that correspond to real changes on the ground. Changes that are due to environmental differences (illumination, atmospheric distortion, etc.) or sensor differences (focus, contrast, etc.) will be widespread throughout the image, and the aim is to avoid these changes in favor of changes that occur in only one or a few pixels. Formal outlier detection schemes (such as the one-class support vector machine) can identify rare occurrences, but will be confounded by pixels that are "equally rare" in both images: they may be anomalous, but they are not changes. We describe a resampling scheme we have developed that formally addresses both of these issues, and reduces the problem to a binary classification, a problem for which a large variety of machine learning tools have been developed. In principle, the effects of misregistration will manifest themselves as pervasive changes, and our method will be robust against them - but in practice, misregistration remains a serious issue.
Demystifying model transformations (2009)

Model-driven development (MDD) is widely used to develop modern business applications. MDD involves creating models at different levels of abstractions. Starting with models of domain concepts, these abstractions are successively refined, using transforms, to design-level models and, eventually, code-level artifacts. Although many tools exist that support transform creation and verification, tools that help users in understanding and using transforms are rare. In this paper, we present an approach for assisting users in understanding model transformations and debugging their input models. We use automated program-analysis techniques to analyze the transform code and compute constraints under which a transformation may fail or be incomplete. These code-level constraints are mapped to the input model elements to generate model-level rules. The rules can be used to validate whether an input model violates transform constraints, and to support general user queries about a transformation. We have implemented the analysis in a tool called XYLEM. We present empirical results, which indicate that (1) our approach can be effective in inferring useful rules, and (2) the rules let users efficiently diagnose a failing transformation without examining the transform source code.
A Signal Processing Approach for Detection of Hemodynamic Instability before Decompensation (2016)

Advanced hemodynamic monitoring is a critical component of treatment in clinical situations where aggressive yet guided hemodynamic interventions are required in order to stabilize the patient and optimize outcomes. While there are many tools at a physician's disposal to monitor patients in a hospital setting, the reality is that none of these tools allow hi-fidelity assessment or continuous monitoring towards early detection of hemodynamic instability. We present an advanced automated analytical system which would act as a continuous monitoring and early warning mechanism that can indicate pending decompensation before traditional metrics can identify any clinical abnormality. This system computes novel features or bio-markers from both heart rate variability (HRV) as well as the morphology of the electrocardiogram (ECG). To compare their effectiveness, these features are compared with the standard HRV based bio-markers which are commonly used for hemodynamic assessment. This study utilized a unique database containing ECG waveforms from healthy volunteer subjects who underwent simulated hypovolemia under controlled experimental settings. A support vector machine was utilized to develop a model which predicts the stability or instability of the subjects. Results showed that the proposed novel set of features outperforms the traditional HRV features in predicting hemodynamic instability.
Enhancing Training Collections for Image Annotation: An Instance-Weighted Mixture Modeling Approach (2013)

Tagged Web images provide an abundance of labeled training examples for visual concept learning. However, the performance of automatic training data selection is susceptible to highly inaccurate tags and atypical images. Consequently, manually curated training data sets are still a preferred choice for many image annotation systems. This paper introduces ARTEMIS - a scheme to enhance automatic selection of training images using an instance-weighted mixture modeling framework. An optimization algorithm is derived to learn instance-weights in addition to mixture parameter estimation, essentially adapting to the noise associated with each example. The mechanism of hypothetical local mapping is evoked so that data in diverse mathematical forms or modalities can be cohesively treated as the system maintains tractability in optimization. Finally, training examples are selected from top-ranked images of a likelihood-based image ranking. Experiments indicate that ARTEMIS exhibits higher resilience to noise than several baselines for large training data collection. The performance of ARTEMIS-trained image annotation system is comparable with usage of manually curated data sets.
Sharp Infrared Eyes: The Journey of QWIPs from Concept to Large Inexpensive Sensitive Arrays in Hand-Held Infrared Cameras (1996)

One of the simplest device realizations of the classic particle-in-a-box problem of basic quantum mechanics is the Quantum Well Infrared Photodetector (QWIP). Optimization of the detector design and material growth and processing has culminated in the realization of a camera with a large (256x256 pixel) focal plane array of QWIPs which can see at 8.5 mu m, holding forth great promise for a variety of applications in the 6-25 mu m wavelength range.
A streamlined model for use in clinical breast cancer risk assessment maintains predictive power and is further improved with inclusion of a polygenic risk score (2021)

Five-year absolute breast cancer risk prediction models are required to comply with national guidelines regarding risk reduction regimens. Models including the Gail model are under-utilized in the general population for various reasons, including difficulty in accurately completing some clinical fields. The purpose of this study was to determine if a streamlined risk model could be designed without substantial loss in performance. Only the clinical risk factors that were easily answered by women will be retained and combined with an objective validated polygenic risk score (PRS) to ultimately improve overall compliance with professional recommendations. We first undertook a review of a series of 2,339 Caucasian, African American and Hispanic women from the USA who underwent clinical testing. We first used deidentified test request forms to identify the clinical risk factors that were best answered by women in a clinical setting and then compared the 5-year risks for the full model and the streamlined model in this clinical series. We used OPERA analysis on previously published case-control data from 11,924 Gail model samples to determine clinical risk factors to include in a streamlined model: first degree family history and age that could then be combined with the PRS. Next, to ensure that the addition of PRS to the streamlined model was indeed beneficial, we compared risk stratification using the Streamlined model with and without PRS for the existing case-control datasets comprising 1,313 cases and 10,611 controls of African-American (n = 7421), Caucasian (n = 1155) and Hispanic (n = 3348) women, using the area under the curve to determine model performance. The improvement in risk discrimination from adding the PRS risk score to the Streamlined model was 52%, 46% and 62% for African-American, Caucasian and Hispanic women, respectively, based on changes in log OPERA. There was no statistically significant difference in mean risk scores between the Gail model plus risk PRS compared to the Streamlined model plus PRS. This study demonstrates that validated PRS can be used to streamline a clinical test for primary care practice without diminishing test performance. Importantly, by eliminating risk factors that women find hard to recall or that require obtaining medical records, this model may facilitate increased clinical adoption of 5-year risk breast cancer risk prediction test in keeping with national standards and guidelines for breast cancer risk reduction.
Nanostructure of Er3+ doped silicates (2005)

We demonstrate nanostructural evolution resulting in highly increased photoluminescence in silicates doped with Er3+ ions. High-resolution transmission electron microscopy (HRTEM) imaging, nano-energy dispersed X-ray (NEDX) spectroscopy, X-ray diffraction (XRD) and photoluminescence analysis confirm the local composition and structure changes of the Er3+ ions upon thermal annealing. We studied two types of amorphous nanopowder: the first is of the composition SiO2/18Al2O3/2Er2O3 (SAE), synthesized by combustion flame-chemical vapor condensation, and the second is with a composition of SiO2/8Y2O3/2Er2O3 (SYE), synthesized by sol-gel synthesis (composition in mol%). Electron diffraction and HRTEM imaging clearly show the formation of nanocrystallites with an average diameter of approximately 8 nm in SAE samples annealed at 1000 degrees C and SYE samples annealed at 1200 degrees C. The volume fraction of the nanocrystalline phase increased with each heat treatment, eventually leading to complete devitrification at 1400 degrees C. Further XRD and NEDX analysis indicates that the nanocrystalline phase has the pyrochlore structure with the formula Er(x)Al(2-x)Si2O7 or Er(x)Y(2-x)Si2O7 and a surrounding silica matrix.
Proposed three-dimensional structure for the cellular prion protein. (1994)

Prion diseases are a group of neurodegenerative disorders in humans and animals that seem to result from a conformational change in the prion protein (PrP). Utilizing data obtained by circular dichroism and infrared spectroscopy, computational studies predicted the three-dimensional structure of the cellular form of PrP (PrPc). A heuristic approach consisting of the prediction of secondary structures and of an evaluation of the packing of secondary elements was used to search for plausible tertiary structures. After a series of experimental and theoretical constraints were applied, four structural models of four-helix bundles emerged. A group of amino acids within the four predicted helices were identified as important for tertiary interactions between helices. These amino acids could be essential for maintaining a stable tertiary structure of PrPc. Among four plausible structural models for PrPc, the X-bundle model seemed to correlate best with 5 of 11 known point mutations that segregate with the inherited prion diseases. These 5 mutations cluster around a central hydrophobic core in the X-bundle structure. Furthermore, these mutations occur at or near those amino acids which are predicted to be important for helix-helix interactions. The three-dimensional structure of PrPc proposed here may not only provide a basis for rationalizing mutations of the PrP gene in the inherited prion diseases but also guide design of genetically engineered PrP molecules for further experimental studies.
Functional organic cations in low-dimensional hybrid organic-inorganic perovskites: charge transfer processes (2022)

Hybrid organic-inorganic perovskites (HOIPs) have received a lot of research attention over the past decade, related to the rapid increase in the power conversion efficiency of perovskite solar cells. The materials used for solar cells are mainly three-dimensional (3D) HOIPs, with a general formula of ABX3 with A being a small monovalent organic cation, B a divalent metal ion, and X a halide anion. More recently, the related material class of 2D HOIPs, with a general formula of (A*)2BX4, is receiving increased attention by combining a generally enhanced material stability compared to 3D HOIPs with a much higher degree of compositional flexibility. 2D HOIPs can accommodate bulkier organic cations (A*) with a conjugated organic core. Depending on the relative alignment between the frontier energy levels of the organic core and the inorganic framework, energy/charge transfer between the components of the hybrid is possible. We built in a carbazole derivative as the organic cation into a 2D HOIP. Through electron paramagnetic resonance experiments combined with computational calculations, we show that excitons generated in the inorganic layer undergo charge transfer at the organic−inorganic interface, resulting in a positive polaron delocalized over several carbazole moieties. In another material system, we incorporate an organic charge-transfer complex (CTC) with a pyrene derivative as the donor and TCNQ as the acceptor into the organic layer of a 2D HOIP. Based on time-resolved spectroscopy, we show that holes are transferred to the inorganic layer upon excitation of the CTC while electrons stay localized on TCNQ acceptor molecules.
Observations on the Hydration Behaviour of a Selection of Bed and Fly Ashes From FBC Installations (2005)

The behaviour of FBC ash/water systems is complex and the hydration behaviour of FBC ashes attracts attention both for environmental reasons and because hydration could be used to reactivate the ashes for further use in SO2 capture. In a recent study, hydration of 16 FBC bed and fly ashes from industrial installations firing high-ash coal and mine wastes was studied. Saturated steam at ∼165°C was employed; samples were analyzed chemically and investigated by X-ray diffraction (XRD) and thermal analysis (TGA). One of the more important results was that in some of the ashes there was no unreacted CaO and no Ca(OH)2 after hydration, and they could even consume CaO added to them before hydration. XRD evidence was also obtained to show that a hydrated calcium silico-aluminate (katoite) was formed during the hydration of ashes high in excess, unreacted CaO. The same ashes were used in the present study. The methods used were the same, but the bed ashes were divided into three size fractions and hydration by saturated steam at 100°C was employed. The results generally confirmed the earlier findings. Differences were small but could be significant. First, no katoite could be detected after hydration, so its formation (and possibly that of other compounds of that type) may require more drastic hydration conditions. Second, small quantities of Ca(OH)2 were detected in most hydrated samples. Third, systematic differences between bed ash size fractions were found. In particular, the proportion of anhydrite and the degree of CaO to CaSO4 conversion steadily increased with decreasing particle size fraction, but in the corresponding fly ash was lower and for lime-rich ashes, much lower.
Enhanced nanometer-scale infrared spectroscopy with a contact mode microcantilever having an internal resonator paddle (2010)

Infrared (IR) spectroscopy is one of the most widely used analytical techniques to measure the chemical composition of organic materials. IR spectra can lead to identification of specific chemical species, but the diffraction limit prohibits IR spectroscopy from probing regions smaller than about 5 ¿m. This paper demonstrates IR spectroscopy with 100 nm spatial resolution using a tunable IR laser and a vibrating atomic force microscope cantilever. Novel microcantilevers transduce thermomechanical pulses from the laser, with a factor of 6 signal-to-noise improvement over conventional microcantilevers. We show 100 nm IR spectroscopy for chemical identification of ethylene acrylic acid (EAA) and Nylon.
Toughened YBa sub 2 Cu sub 3 O sub x /ZrO sub 2 composites (1990)

Tetragonal ZrO{sub 2} particles have been added to YBa{sub 2}Cu{sub 3}O{sub x} to improve the fracture toughness of the superconductor. For some processing procedures, toughness was increased from 1 to 3 MPa(m){sup 0.5}, but in some cases ZrO{sub 2} reacted with YBa{sub 2}Cu{sub 3}O{sub x} and destroyed its superconductivity. Coating the ZrO{sub 2} with Y{sub 2}BaCuO{sub 5} is being explored to minimize the reaction between ZrO{sub 2} and YBa{sub 2}Cu{sub 3}O{sub x}. 25 refs., 5 figs.
A physical catalyst for the electrolysis of nitrogen to ammonia (2018)

Ammonia synthesis consumes 3 to 5% of the world's natural gas, making it a significant contributor to greenhouse gas emissions. Strategies for synthesizing ammonia that are not dependent on the energy-intensive and methane-based Haber-Bosch process are critically important for reducing global energy consumption and minimizing climate change. Motivated by a need to investigate novel nitrogen fixation mechanisms, we herein describe a highly textured physical catalyst, composed of N-doped carbon nanospikes, that electrochemically reduces dissolved N<sub>2</sub> gas to ammonia in an aqueous electrolyte under ambient conditions. The Faradaic efficiency (FE) achieves 11.56 ± 0.85% at -1.19 V versus the reversible hydrogen electrode, and the maximum production rate is 97.18 ± 7.13 μg hour<sup>-1</sup> cm<sup>-2</sup>. The catalyst contains no noble or rare metals but rather has a surface composed of sharp spikes, which concentrates the electric field at the tips, thereby promoting the electroreduction of dissolved N<sub>2</sub> molecules near the electrode. The choice of electrolyte is also critically important because the reaction rate is dependent on the counterion type, suggesting a role in enhancing the electric field at the sharp spikes and increasing N<sub>2</sub> concentration within the Stern layer. The energy efficiency of the reaction is estimated to be 5.25% at the current FE of 11.56%.
Multicomponent Intraocular Lens (1996)

The multicomponent intraocular lens concept is a major departure from conventional IOL technology because it allows enhancement, or fine tuning, of an already fairly accurate refractive procedure, IOL surgery.
Two Phase Write Scheme to Improve Low Voltage Write-ability in Medium-Density SRAMs (2015)

State-of-art SRAM designs use either the negative bit line or the overdrive word line write assist circuits to improve the write-ability in a low voltage VDDMIN environment. But at the higher voltage operations, these write assist circuits will have an adverse effect on the SRAM bit cell's pass gate oxide tox reliability like hot carrier injection and time-dependent dielectric breakdown (TDDB). In this paper, we propose a novel two phase write scheme to improve the write-ability in a VDDMIN environment. We achieved improved write-ability by driving the word line voltage level to the power supply rail, in conjunction with the medium-sized SRAM bit cell. Simulation results at VDDMIN voltage of 0.52V in 16nm TSMC Fin FET technology, demonstrate that the worst 5σ bit cell write margin is improved by 85mV. Our two phase write scheme with the word line voltage level restricted to the power supply rail, does not risk the bit cell's pass gate tox reliability at the higher voltage operations. We also present the two phase write scheme macro implementation for a column multiplexed SRAM architecture.
Therapeutic efficacy of cerium oxide nanoparticles against sepsis induced acute lung injury (2015)

Sepsis induced acute lung injury (ALI) is one of the leading causes of mortality in the intensive care unit. The development of ALI is primarily driven by the systemic inflammatory response syndrome and the increased cellular ROS subsequent to immune system over activation. Cerium oxide nanoparticles (CeO 2 ) nanoparticles have been shown to scavenge reactive oxygen species both in vitro and in vivo under various experimental settings while others have suggested that they may also exhibit the ability to protect lungs from hypoxia induced oxidative stress. In the present study we investigated the protective effects of cerium oxide nanoparticles against sepsis induced ALI. Administration of a single dose of CeO 2 nanoparticles (0.5mg/kg) to septic animals attenuated alveolar congestion. Treatment associated decreases in alveolar congestion were associated with reduced infiltration of inflammatory cells, diminished myeloperoxidase activity, and decreased p38‐MAPK / STAT3 phosphorylation. Additional experiments to explore the potential efficacy of using CeO 2 nanoparticles for the treatment of sepsis induced ALI may be warranted.