gebhart/patrepeval huggingface dataset:
Supplementary Data from A Novel Human Her-2/neu Chimeric Molecule Expressed by <i>Listeria monocytogenes</i> Can Elicit Potent HLA-A2 Restricted CD8-positive T cell Responses and Impact the Growth and Spread of Her-2/neu-positive Breast Tumors (2023)

Supplementary Data from A Novel Human Her-2/neu Chimeric Molecule Expressed by &lt;i&gt;Listeria monocytogenes&lt;/i&gt; Can Elicit Potent HLA-A2 Restricted CD8-positive T cell Responses and Impact the Growth and Spread of Her-2/neu-positive Breast Tumors
Increased particle inspection sensitivity by reduction of background scatter variance (2013)

In dark-field particle inspection, the limiting factor for sensitivity is the amount of background scatter due to substrate roughness. This scatter forms a speckle pattern and shows an intensity distribution with a long tail. To reduce falsepositives to an acceptable level, a high detection threshold should be chosen such that the tail of the background distribution is avoided. We have modeled an optimized illumination mode, that reduces the variance in the background distribution. This illumination mode illuminates the substrate from multiple azimuth angles. We show that the speckle patterns generated by each azimuth angle can be independent from each other. Therefore by combining the angles, the variance of the background signal is reduced. We show that for the parameters of our inspection system the detection threshold can be reduced by a factor three, resulting in a lower detection limit that is 20% smaller in particle size. The change in the background scattering distribution was confirmed by experiments.
Inhibitory activity of marine sponge metabolites on SARS-CoV-2 RNA dependent polymerase: virtual screening and molecular dynamics simulation (2021)

Marine species are known as rich sources of metabolites involved mainly in the pharmaceutical industry. This study aimed to evaluate the effect of biologically active compounds in the marine sponge on the SARS-CoV-2 RNA-dependent-RNA polymerase protein (RdRp) using the <i>in-silico</i> method. A total of 51 marine compounds were checked for their possible interaction with SARS-CoV-2 RdRp using Maestro interface for molecular docking, molecular dynamic (MD) simulation, and MM/GBSA method to estimate compounds binding affinities. Among the 51 compounds screened in this study, two (mycalamide A, and nakinadine B) exhibited the lowest docking energy and best interaction. Among these compounds, mycalamide A was identified as a potent inhibitor of SARS-CoV-2 RdRp that showed the best and stable interaction during molecular dynamic simulation, with residues (Asp760 and Asp761) found in the catalytic domain of RdRp. The analysis through MM/GBSA for molecular dynamic simulation results revealed binding energy -59.7 ± 7.18 for Mycalamide A and -56 ± 10.55 for Nakinadine B. These results elucidate the possible use of mycalamide A for treating coronavirus disease.Communicated by Ramaswamy H. Sarma.
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas (2018)

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN.
Detection of synonyms in specification documents (2012)

Recently, the document information managed in companies becomes complex and various more and more. Specification documents are used for the technical transfer and inheritance of manufactures and services. However, the description and the meaning of the component words in specifications are often inconsistent or multiple, because a specification document is made by the persons in charge of various parts. Then the readers may misunderstand the contents of specifications by its inconsistency. This paper focuses on synonyms, multiple description of words for a meaning or a word, in specification documents and proposes an extraction method of them considering the co-occurrence words of each morpheme in compound words. This paper applies the proposed method to a test data, in which some words in an actual specification document are replaced with words, and studies the effectiveness of the proposed method.
Estimated Cases of Blindness and Visual Impairment from Neovascular Age-Related Macular Degeneration Avoided in Australia by Ranibizumab Treatment (2014)

Intravitreal injections of anti-vascular endothelial growth factor agents, such as ranibizumab, have significantly improved the management of neovascular age-related macular degeneration. This study used patient-level simulation modelling to estimate the number of individuals in Australia who would have been likely to avoid legal blindness or visual impairment due to neovascular age-related macular degeneration over a 2-year period as a result of intravitreal ranibizumab injections. The modelling approach used existing data for the incidence of neovascular age-related macular degeneration in Australia and outcomes from ranibizumab trials. Blindness and visual impairment were defined as visual acuity in the better-seeing eye of worse than 6/60 or 6/12, respectively. In 2010, 14,634 individuals in Australia were estimated to develop neovascular age-related macular degeneration who would be eligible for ranibizumab therapy. Without treatment, 2246 individuals would become legally blind over 2 years. Monthly 0.5 mg intravitreal ranibizumab would reduce incident blindness by 72% (95% simulation interval, 70-74%). Ranibizumab given as needed would reduce incident blindness by 68% (64-71%). Without treatment, 4846 individuals would become visually impaired over 2 years; this proportion would be reduced by 37% (34-39%) with monthly intravitreal ranibizumab, and by 28% (23-33%) with ranibizumab given as needed. These data suggest that intravitreal injections of ranibizumab, given either monthly or as needed, can substantially lower the number of cases of blindness and visual impairment over 2 years after the diagnosis of neovascular age-related macular degeneration.
GATSPI: GPU Accelerated Gate-Level Simulation for Power Improvement (2022)

In this paper, we present GATSPI, a novel GPU accelerated logic gate simulator that enables ultra-fast power estimation for industry sized ASIC designs with millions of gates. GATSPI is written in PyTorch with custom CUDA kernels for ease of coding and maintainability. It achieves simulation kernel speedup of up to 1668X on a single-GPU system and up to 7412X on a multiple-GPU system when compared to a commercial gate-level simulator running on a single CPU core. GATSPI supports a range of simple to complex cell types from an industry standard cell library and SDF conditional delay statements without requiring prior calibration runs and produces industry-standard SAIF files from delay-aware gate-level simulation. Finally, we deploy GATSPI in a glitch-optimization flow, achieving a 1.4% power saving with a 449X speedup in turnaround time compared to a similar flow using a commercial simulator.
SmartDeviceLink as an Open Innovation Platform for Connected Car Features and Mobility Applications (2017)

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;SmartDeviceLink (SDL) is open-source software that connects the vehicle’s infotainment system to mobile applications. SDL includes an open-source software development kit (SDK) that enables a smart-device to connect to the vehicle’s human-machine interface (HMI), read vehicle data, and control vehicle sub-systems such as the audio and climate systems. It is extensible, so other convenience subsystems or brought-in aftermarket modules can be added. Consequently, it provides a platform for cyber-physical systems that can integrate wearables, consumer sensors and cloud data into an intelligent vehicle control system. As an Open Innovation Platform, new features can be rapidly developed and deployed to the market, bypassing the longer vehicle development cycles. This facilitates a channel for rapid prototyping and innovation that is not constrained by the traditional process of automotive parts development, but is rather on the timeline of software development. This allows parties other than the OEM, including third party developers, universities, and startups, to quickly integrate their applications into the car. By digitizing the controls into a programmable application program interface (API), we can incorporate machine learning and ambient intelligence to learn user preferences and needs over time and intelligently pre-set them automatically. This can disrupt the traditional model of the human machine interaction. This is particularly important as transportation moves towards autonomous vehicles. In this paper, we discuss some specific examples using SDL to enhance the transportation experience, including intelligent air quality and climate control, enhanced radio interface, mobility service applications, and innovative intelligent vehicle features.&lt;/div&gt;&lt;/div&gt;
Nanowires-assembled CuO Interpenetrated-leaf Architecture by () Twinning (2012)

High-resolution transmission electron microscopy characterization demonstrates that the petal-like complex three-dimensional (3D) CuO nanomaterial produced by self-assembly in low-temperature wet-chemical synthesis has a unique interpenetrated-leaf structure. The primary leaf consisting of semi-coherent CuO nanocrystallites was formed by bundling, coalescence, and hydrolysis of amorphous Cu (OH)2 nanowires. The petal-like CuO was constructed by growing the secondary leaf on the primary one with a twin relationship ()[010]p//()[]s between them and the twin axis is [101]. The co-axis ⟨010⟩ of leaves is the growth orientation. The 3D complex nanostructure is different from normal low-dimensional nanostructures, e.g. nanorods, nanorings, regarding the formation mechanism and inherent structure.
Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information (2018)

Type 1 diabetes (TID) therapy is based on multiple daily injections of exogenous insulin. The so-called insulin bolus calculators facilitate insulin dose calculation to the patients by implementing a standard formula SF which, besides some patient-related parameters, also considers the current value of blood glucose concentration (BG), normally measured by the patient through a fingerprick device. The recent approval by the U.S. Food and Drug Administration to use the measurements collected by wearable continuous glucose monitoring (CGM) sensors for insulin dosing of fers new perspectives. Indeed, CGM sensors provide real-time information on both glucose concentration and rate of change, currently not considered in the SF. The purpose of this work is to preliminary investigate the possibility of using neural networks (NN)s for the calculation of meal insulin bolus dose exploiting CGM-based information. Using the UVa/Padova TID Simulator, we generated data of 100 subjects in 9-h, single-meal, noise-free scenarios. In particular, for each subject we analyzed different meal conditions in terms of carbohydrate intakes, preprandial BG and glucose rate-of -change. Then, a fully-connected feedforward NN was trained, with the aim of estimating the insulin bolus needed to obtain the best glycemic outcomes according to the blood glucose risk index (BGRI). Preliminary results show that by using the NN to calculate insulin doses lower BGRI values are obtained, on average, compared to the SF. These results encourage further development of the approach and its assessment in more challenging scenarios.
Sea of leads compliant I/O interconnect process integration for the ultimate enabling of chips with low-k interlayer dielectrics (2005)

Sea of leads (SoL) process integration for the series of steps required to transform a fully intact die at the wafer level to a die that is assembled onto a board is described. The primary goal is to address the issues involved in reconciling the fabrication and assembly requirements of compliant leads, such as SoL, with those of standard semiconductor processes and chip assembly techniques. The effort is motivated in-part by the potential failure of the low-k interlayer dielectric in microprocessors as a result of high mechanical stresses due to the coefficient of thermal expansion (CTE) mismatch between the chip and the board. SoL, and other compliant interconnections, mitigate this problem by mechanically decoupling the chip and the board. While compliant leads offer advantages over C4 technology, there is much to consider during the series of steps needed to transform the fully intact dice at the wafer level to dice that are assembled onto the board. The use of an encapsulation film over the leads during wafer sawing is shown to be necessary for slippery leads and other free-standing compliant leads. The use of a suitable flux when the leads are finished with a nickel-oxide nonwettable layer is essential for a successful wafer-level solder reflow. Successful die assembly using thermocompression bonding is demonstrated using two different SoL dice with correspondingly different substrates. The resistance of a chain of 30 cascaded leads is 2.7 /spl Omega/.
Controlled source electromagnetic three‐dimensional grid‐modelling based on a complex resistivity structure of the seafloor: effects of acquisition parameters and geometry of multi‐layered resistors (2009)

ABSTRACT A comprehensive controlled source electromagnetic (CSEM) modelling study, based on complex resistivity structures in a deep marine geological setting, is conducted. The study demonstrates the effects of acquisition parameters and multi‐layered resistors on CSEM responses. Three‐dimensional (3D) finite difference time domain (FDTD) grid‐modelling is used for CSEM sensitivity analysis. Interpolation of normalized CSEM responses provides attributes representing relative sensitivity of the modelled structures. Modelling results show that fine grid, 1 × 1 km receiver spacing, provides good correlations between CSEM responses and the modelled structures, irrespective of source orientation. The resolution of CSEM attributes decreases for receiver spacing &gt;2 × 2 km, when using only in‐line data. Broadside data in the grid geometry increase data density by 100 – approximately 200% by filling in in‐line responses and improve the resolution of CSEM attributes. Optimized source orientation (i.e., oblique to the strike of an elongated resistor) improves the structural definition of the CSEM anomalies for coarse‐grid geometries (receiver spacing ≥3 × 3 km). The study also shows that a multi‐resistor anomaly is not simply the summation but a cumulative response with mutual interference between constituent resistors. The combined response of constituent resistors is approximately 50% higher than the cumulative response of the multi‐resistor for 0.5 Hz at 4000 m offset. A gradual inverse variation of offset and frequency allows differentiation of CSEM anomalies for multi‐layered resistors. Similar frequency‐offset variations for laterally persistent high‐resistivity facies show visual continuity with varying geometric expressions. 3D grid‐modelling is an effective and adequate tool for CSEM survey design and sensitivity analysis.
Sympathetic Activity and Body Mass Index Contribute to Blood Pressure Levels. (2000)

The purpose of this study was to clarify the relationships between obesity (BMI) and BP levels, leptin levels, sympathetic activity, and insulin sensitivity in a Japanese male population. In 912 young, non-diabetic, Japanese men with a wide range of BMI (16.5-33.6 kg/m2), blood pressure (BP), fasting plasma norepinephrine (NE), insulin and leptin levels were measured after an overnight fast. The cohort consisted of 603 normotensive and 309 hypertensive subjects. The study was carried out using a cross-sectional design. When the subjects were subdivided by tertile in relation to BMI, the 101 subjects in the heaviest group (BMI > 27.9 kg/m2) had a significantly higher systolic BP (p< 0.05) and pulse rate (p< 0.05) as well as higher NE (p< 0.01), insulin (p< 0.01), and leptin (p< 0.01) levels than 86 subjects in the leanest group (BMI < 22.2 kg/m2). In the whole cohort, BMI correlated with mean BP (p< 0.01), plasma NE (p< 0.05), insulin (p< 0.001) and leptin (p< 0.001). The mean BP correlated with BMI (p< 0.001), plasma NE (p< 0.01), insulin (p< 0.01) and leptin (p< 0.05). Plasma leptin levels correlated with fasting plasma insulin levels (p < 0.05), but not with plasma NE levels (NS). As analyzed by multiple regression analysis, only plasma NE (p< 0.05) and BMI (p< 0.001), but not plasma insulin levels, were significant, independent predictors of BP levels (r2=0.125, F= 10.51, p=0.0001). These results suggest that obesity (BMI) and heightened sympathetic nervous system activity contribute to BP elevation (hypertension).
Automated Tracking of Arctic Ice Floes in Multitemporal Sar Imagery (2005)

A discussion is presented of two algorithms to perform shape matching on the boundaries of ice floes in SAR (synthetic aperture radar) images in order to produce an ice motion map. The algorithms match a shape descriptor known as the psi-s curve. The first algorithm uses normalized correlation to match the psi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates deformation of the ice floe boundary.
Consensus + innovations distributed inference over networks: cooperation and sensing in networked systems (2013)

This article presents consensus + innovations inference algorithms that intertwine consensus (local averaging among agents) and innovations (sensing and assimilation of new observations). These algorithms are of importance in many scenarios that involve cooperation and interaction among a large number of agents with no centralized coordination. The agents only communicate locally over sparse topologies and sense new observations at the same rate as they communicate. This stands in sharp contrast with other distributed inference approaches, in which interagent communications are assumed to occur at a much faster rate than agents can sense (sample) the environment so that, in between measurements, agents may iterate enough times to reach a decision-consensus before a new measurement is made and assimilated. While optimal design of distributed inference algorithms in stochastic time-varying scenarios is a hard (often intractable) problem, this article emphasizes the design of asymptotically (in time) optimal distributed inference approaches, i.e., distributed algorithms that achieve the asymptotic performance of the corresponding optimal centralized inference approach (with instantaneous access to the entire network sensed information at all times). Consensus + innovations algorithms extend consensus in nontrivial ways to mixed-scale stochastic approximation algorithms, in which the time scales (or weighting) of the consensus potential (the potential for distributed agent collaboration) and of the innovation potential (the potential for local innovations) are suitably traded for optimal performance. This article shows why this is needed and what the implications are, giving the reader pointers to new methodologies that are useful in their own right and in many other contexts.
Behavioral Responses of Nymph and AdultCimex lectularius(Hemiptera: Cimicidae) to Colored Harborages (2016)

Behavioral bioassays were conducted to determine whether bed bug adults and nymphs prefer specific colored harborages. Two-choice and seven-choice behavioral color assays indicate that red (28.5%) and black (23.4%) harborages are optimal harborage choices for bed bugs. Yellow and green harborages appear to repel bed bugs. Harborage color preferences change according to gender, nutritional status, aggregation, and life stage. Female bed bugs prefer harborages with shorter wavelengths (lilac-14.5% and violet-11.5%) compared to males, whereas males prefer harborages with longer wavelengths (red-37.5% and black-32%) compared with females. The preference for orange and violet harborages is stronger when bed bugs are fed as opposed to when they are starved. Lone bed bugs (30%) prefer to be in black harborages while red harborages appear to be the optimum harborage color for bed bugs in more natural mixed aggregations (35.5%). Bed bug nymphs preferred different colored harborages at each stage of development, which is indicative of their developing eye structures and pigments. First instars showed no significant preference for any colored harborage soon after hatching. However, by the fifth instar, 27.5% of nymphs significantly preferred red and black harborages (which was a similar preference to adult bed bugs). The proportion of oviposited eggs was significantly greater under blue, red, and black harborages compared to other colored harborages tested. The use of visual cues such as specific colors offers great potential for improving bed bug monitoring tools by increasing trap captures.
P‐125: Maskless RGB Color Patterning via Dye Diffusion for Vacuum‐Deposited Small Molecule OLED Displays (2015)

A maskless RGB color patterning technique based on dye diffusion is proposed here for vacuum‐deposited small molecule OLED displays. This approach utilizes selective diffusion of dyes through thermal diffusion via physical contact for color patterning. The proposed maskless color patterning technique enables us to overcome challenging issues in the conventional color patterning technique using fine metal shadow masks. The maskless color patterning technique based on dye diffusion has been suggested as a color patterning technique for polymer OLEDs. However, it has not yet been applied to vacuum‐deposited small molecule OLEDs likely due to several expected concerns such as limited diffusion and contact‐induced damage in small molecule films. The purpose of the present study is therefore to test whether the color pattering technique based on dye diffusion can be applied to vacuum‐deposited small molecule OLEDs. In order to investigate that, red, green, and blue OLEDs are fabricated side by side on one substrate by doping dyes into host through thermal diffusion via physical contact. Device performance of the fabricated devices, including electroluminescence spectra and IVL characteristics, is tested to investigate if molecular diffusion is sufficient for obtaining desired color spectrum and investigate effects of the physical contact.