gebhart/patrepeval huggingface dataset:
Radiometal-Dependent Biological Profile of the Radiolabeled Gastrin-Releasing Peptide Receptor Antagonist SB3 in Cancer Theranostics: Metabolic and Biodistribution Patterns Defined by Neprilysin (2018)

Recent advances in oncology involve the use of diagnostic/therapeutic radionuclide-carrier pairs that target cancer cells, offering exciting opportunities for personalized patient treatment. Theranostic gastrin-releasing peptide receptor (GRPR)-directed radiopeptides have been proposed for the management of GRPR-expressing prostate and breast cancers. We have recently introduced the PET tracer <sup>68</sup>Ga-SB3 (SB3, DOTA- p-aminomethylaniline-diglycolic acid-DPhe-Gln-Trp-Ala-Val-Gly-His-Leu-NHEt), a receptor-radioantagonist that enables the visualization of GRPR-positive lesions in humans. Aiming to fully assess the theranostic potential of SB3, we herein report on the impact of switching <sup>68</sup>Ga to <sup>111</sup>In/<sup>177</sup>Lu-label on the biological properties of resulting radiopeptides. Notably, the bioavailability of <sup>111</sup>In/<sup>177</sup>Lu-SB3 in mice drastically deteriorated compared with metabolically robust <sup>68</sup>Ga-SB3, and as a result led to poorer <sup>111</sup>In/<sup>177</sup>Lu-SB3 uptake in GRPR-positive PC-3 xenografts. The peptide cleavage sites were identified by chromatographic comparison of blood samples from mice intravenously receiving <sup>111</sup>In/<sup>177</sup>Lu-SB3 with each of newly synthesized <sup>111</sup>In/<sup>177</sup>Lu-SB3-fragments. Coinjection of the radioconjugates with the neprilysin (NEP)-inhibitor phosphoramidon led to full stabilization of <sup>111</sup>In/<sup>177</sup>Lu-SB3 in peripheral mouse blood and resulted in markedly enhanced radiolabel uptake in the PC-3 tumors. In conclusion, in situ NEP-inhibition led to indistinguishable <sup>68</sup>Ga/<sup>111</sup>In/<sup>177</sup>Lu-SB3 profiles in mice emphasizing the theranostic prospects of SB3 for clinical use.
Inductively coupled plasma mass spectrometry signal fluctuations due to individual aerosol droplets and vaporizing particles (1992)

ICPMS signal fluctuations, in some cases larger than 1 order of magnitude, are observed on a tens of microsecond time scale. The analyte ICPMS signal fluctuations are larger than those characteristic of analyte ion emission intensities observed from the side of the plasma. The analyte, solvent and plasma gas ICPMS signal fluctuations correlate with atom and ion emission intensities monitored 1.3 mm in front of the sampling cone. Analyte and O+ ICPMS signals are depressed near incompletely desolvated droplets and enhanced near vaporizing analyte particles. ICPMS molecular ion signals including ArH+, O2+, H2O+, and H3O+ are enhanced near both incompletely desolvated droplets and vaporizing particles. In contrast to other species, Ar+ ICPMS signals are depressed near a vaporizing particle. The nature of the ICPMS signal fluctuations (spikes or dips) observed at a fixed sampling position (sampling depth) is critically dependent on the center (nebulizer) gas flow rate.
A study on performance evaluation of conventional cache replacement algorithms: A review (2016)

Cache Replacement Policies play a significant and contributory role in the context of determining the effectiveness of cache memory cells. It has also become one of the major key features for efficient memory management from the technological aspect. Hence, owing to the existing critical computing systems, it has become too essential to attain faster processing of executable instructions under any adverse situations. In the current scenario, the state of art processors such as Intel multi-core processors for application specific integrated circuits, usually employ various cache replacement policies such as Least Recently Used (LRU) and Pseudo LRU (pLRU), Round Robin, etc. However, fewer amounts of existing research works are found till date to utter about explicit performance issues associated with the conventional cache replacement algorithms. Therefore, the proposed study intended to carry out a performance evaluation to explore the design space of conventional cache replacement policies under SPEC CPU2000 benchmark suite. It initiates and configures the experimental Simple Scalar toolbox prototype on a wide range of cache sizes. The experimental outcomes obtained from the benchmark suite show that PLRU outperforms the conventional LRU concerning computational complexity and a variety of cache blocks organization.
Molecular Genetics of Childhood Leukemias (1998)

Although clinical features are important prognostic indicators, genetic alterations of leukemic blasts may be better predictors of outcome for acute leukemia patients. We therefore favor risk-adapted therapy based on classification schemes that incorporate both genetic and clinical features.
Neural Network Approaches Versus Statistical Methods in Classification of Multisource Remote Sensing Data (2005)

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.
Planar lightwave circuit dispersion equalizer (1996)

The authors report an integrated-optic dispersion equalizer fabricated on a planar lightwave circuit (PLC). This PLC dispersion equalizer is composed of several asymmetrical Mach-Zehnder interferometers cascaded in series. The dispersion equalizer has a high degree of design flexibility and can compensate for both normal and anomalous fiber dispersions at any center wavelength. Moreover, the equalizer can be applied to WDM transmission systems. This equalizer employing five asymmetrical interferometers is fabricated and its measured dispersion values are +834 and -1006 ps/nm. The effectiveness of the equalizer is demonstrated in a 2.5 Gb/s transmission experiment with a 1.3 /spl mu/m zero-dispersion fiber at 1.55 /spl mu/m. Also, its performance is evaluated theoretically.
Public-key cryptosystem design based on factoring and discrete logarithms (1994)

Most existing cryptosystem designs incorporate just one cryptographic assumption, such as factoring or discrete logarithms. These assumptions appear secure today; but, it is possible that efficient algorithms will be developed in the future to break one or more of these assumptions. It is very unlikely that multiple cryptographic assumptions would simultaneously become easy to solve. Enhancing security is the major objective for cryptosystems based on multiple assumptions. K.S. McCurley (1990) proposed the first key distribution system based on two dissimilar assumptions, both of which appear to be hard. In his design, the sizes of the security parameters for these two assumptions are quite different. The modulus to satisfy the proper security requirement for one assumption is too large for the other assumption. The side effects are (1) the public key size is larger than the original Diffie-Hellman key distribution scheme; and (2) more computation time is required. The authors propose a cryptographic system design based on the two popular assumptions: factoring and discrete logarithms. Breaking this system is computationally infeasible because it requires (1) solving the Diffie-Hellman discrete logarithm problem in a subgroup of Zp*, where p=2p'*q'+1 and p', q' are two large primes, and (2) factoring (p-1)/2 into two large primes, p' and q'. Thus, in the proposed system it is possible to choose the same size of security parameter for these two assumptions and, therefore, to maintain the efficiency of the implementation.
Cell-Based Potassium Ion Channel Screening Using the FluxOR™ Assay (2010)

FluxOR technology is a cell-based assay used for high-throughput screening measurements of potassium channel activity. Using thallium influx as a surrogate indicator of potassium ion channel activity, the FluxOR Potassium Ion Channel Assay is based on the activation of a novel fluorescent dye. This indicator reports channel activity with a large fluorogenic response and is proportional to the number of open potassium channels on the cell, making it extremely useful for studying K(+) channel targets. In contrast to BTC-AM ester, FluxOR dye is roughly 10-fold more thallium sensitive, requiring much lower thallium for a larger signal window. This also means that the assay is carried out in a physiological, normal-chloride saline. In this article, the authors describe how they used BacMam gene delivery to express Kv7.2 and 7.3 (KCNQ), Kir2.1, or Kv11.1 (hERG) potassium ion channels in U2-OS cells. Using these cells, they ran the FluxOR assay to identify and characterize channel-specific inhibitory compounds discovered within the library (Tocriscreen Mini 1200 and Sigma Sodium/Potassium Modulators Ligand set). The FluxOR assay was able to identify several known specific inhibitors of Kv7.2/7.3 or hERG, highlighting its potential to identify novel and more efficacious small-molecule modulators.
EvoAE -- A New Evolutionary Method for Training Autoencoders for Deep Learning Networks (2015)

Although deep learning has achieved outstanding performances on several difficult machine learning applications, there are multiple issues that make its application on new problems difficult: speed of training, local minima, and manual selection of hyper-parameters. To overcome these problems, this paper proposes a new evolutionary method, EvoAE, to train auto encoders for deep learning networks. By evolving a population of auto encoders, EvoAE learns multiple features in each auto encoder in the form of hidden nodes, evaluates the auto encoders based on their reconstruction quality, and generates new auto encoders using crossover and mutation with chromosomes made up of hidden nodes and associated connections and weights. EvoAE optimizes network weights and structures of auto encoders simultaneously and employs a mini-batch variant, called Evo-batch, to speed up auto encoder search on large datasets. Furthermore, EvoAE supports different training methods in data partitioning and selection, requires little manual intervention, and reduces overall training time drastically over traditional methods on large datasets.
Nonadhesive Stationary Organ Culture of Human Bronchial Mucosa (1996)

Abstract The supply of fresh bronchial tissue from human donors for in vitro culture is limited. Routine fiberoptic bronchoscopy offers a safe and easy procedure for obtaining minor biopsies and we wanted to see if the material provided could be used for organ culture by using a simple liquid overlay technique. Bronchial biopsies were cut into fragments 400-500 microns and kept immersed in a standard serum-supplemented medium for 40 days. An agar base prevented adhesion of the tissue. By light and electron microscopy it was shown that the tissue fragments had a differentiated epithelium at their surface throughout the culture period. An outgrowth of epithelial cells on the scaffold of the exposed stroma, covering the surface of the whole fragment, occurred within the first 5 days of culture. This epithelium was partly ciliated, 2-4 cell layers thick with squamous and cuboidal cells and expressed epithelial markers (cytokeratin and Ber-Ep4). The amount of cilia increased during the first 15 days of culture. The epithelium rested on a neosynthesized basement membrane as visualized by electron microscopy and immunohistochemistry with antibodies directed against collagen IV, laminin, and fibronectin. The central stroma consisted of loose connective tissue with fibroblasts. This simple tissue culture model combines maintenance and neoformation of bronchial epithelium on top of a living natural substrate, thus enabling direct biological studies on clinical biopsy material under perfectly viable conditions.
Frugivory by Brown Marmorated Stink Bug (Hemiptera: Pentatomidae) Alters Blueberry Fruit Chemistry and Preference by Conspecifics (2016)

The brown marmorated stink bug, Halyomorpha halys (Stål), is an invasive pest from Asia that feeds on many agricultural crops in the United States, including blueberries. Yet, the effects of H. halys feeding on fruit chemistry and induced resistance to insects remain unknown. Here we hypothesized that frugivory by H. halys changes fruit chemical composition, which in turn affects insect feeding behavior. In field experiments, blueberry fruit was either mechanically injured or injured by 0 (control), 2, 5, or 10 H. halys Total soluble solids (°Brix) and anthocyanin and phenolic content in injured and uninjured fruits, as well as their effects on feeding behavior by conspecifics, were measured subsequently in the laboratory. Results showed lower °Brix values in injured fruit as compared with uninjured fruit. Fruit injured by 2 and 5 H. halys also had 32 and 20% higher total phenolics, respectively, than the uninjured controls. The proportions of the anthocyanins derived from delphinidin, cyanidin, and petunidin increased, whereas those from malvidin decreased, in fruit after mechanical wounding and frugivory by H. halys In dual-choice tests, H. halys fed more often on uninjured fruit than those previously injured by conspecifics. These results show that frugivory by H. halys reduces the amounts of soluble solids, alters anthocyanin ratios, and increases levels of phenolics, and, as a result, injured fruits were a less preferred food source for conspecifics. To our knowledge, this is the first study to investigate the effects of frugivory on fruit chemistry and induced fruit resistance against a fruit-eating herbivore.
Iterative near-term ecological forecasting: Needs, opportunities, and challenges (2018)

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.
Leveraging mainstream design and analysis tools for MEMS (2004)

Mainstream CAD/CAE tools are used to rapidly design and commercialize a broad product line of rugged MEMS-based devices for applications including RF/wireless, telecom, oil and gas production, process monitoring, medical diagnostics and scientific discovery. These tools deliver the robust capabilities previously available only with specialized, often expensive, MEMS-focused options. This paper illustrates some of the considerations in choosing a MEMS CAD/CAE tool, and provides examples of mainstream tools successfully used in MEMS design and analysis.
Dnsmos P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressors (2022)

Human subjective evaluation is the "gold standard" to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. We have recently developed a non-intrusive speech quality metric called Deep Noise Suppression Mean Opinion Score (DNSMOS) using the scores from ITU-T Rec. P.808 [1] subjective evaluation. The P.808 scores reflect the overall quality of the audio clip. ITU-T Rec. P.835 [2] subjective evaluation framework gives the standalone quality scores of speech and background noise in addition to the overall quality. In this work, we train an objective metric based on P.835 human ratings that output 3 scores: i) speech quality (SIG), ii) background noise quality (BAK), and iii) the overall quality (OVRL) of the audio. The developed metric is highly correlated with human ratings, with a Pearson’s Correlation Co-efficient (PCC)=0.94 for SIG and PCC=0.98 for BAK and OVRL. This is the first non-intrusive P.835 predictor we are aware of. DNSMOS P.835 is made publicly available as an Azure service.
Discovery of eight novel divergent homologs expressed in cattle placenta (2006)

Ten divergent homologs were identified using a subtractive bioinformatic analysis of 12,614 cattle placenta expressed sequence tags followed by comparative, evolutionary, and gene expression studies. Among the 10 divergent homologs, 8 have not been identified previously. These were named as follows: cattle cerebrum and skeletal muscle-specific transcript 1 ( CSSMST1), cattle intestine-specific transcript 1 ( CIST1), hepatitis A virus cellular receptor 1 amino-terminal domain-containing protein ( HAVCRNDP), prolactin-related proteins 8, 9, and 11 ( PRP8, PRP9, and PRP11, respectively) and secreted and transmembrane protein 1A and 1B ( SECTM1A and SECTM1B, respectively). In addition, two previously known divergent genes were identified, trophoblast Kunitz domain protein 1 ( TKDP1) and a new splice variant of TKDP4. Nucleotide substitution analysis provided evidence for positive selection in members of the PRP gene family, SECTM1A and SECTM1B. Gene expression profiles, motif predictions, and annotations of homologous sequences indicate immunological and reproductive functions of the divergent homologs. The genes identified in this study are thus of evolutionary and physiological importance and may have a role in placental adaptations.
Molecular Characterization and Phylogenetic Analysis of Two Novel Regio-specific Flavonoid Prenyltransferases from Morus alba and Cudrania tricuspidata (2014)

Prenylated flavonoids are attractive specialized metabolites with a wide range of biological activities and are distributed in several plant families. The prenylation catalyzed by prenyltransferases represents a Friedel-Crafts alkylation of the flavonoid skeleton in the biosynthesis of natural prenylated flavonoids and contributes to the structural diversity and biological activities of these compounds. To date, all identified plant flavonoid prenyltransferases (FPTs) have been identified in Leguminosae. In the present study two new FPTs, Morus alba isoliquiritigenin 3'-dimethylallyltransferase (MaIDT) and Cudrania tricuspidata isoliquiritigenin 3'-dimethylallyltransferase (CtIDT), were identified from moraceous plants M. alba and C. tricuspidata, respectively. MaIDT and CtIDT shared low levels of homology with the leguminous FPTs. MaIDT and CtIDT are predicted to be membrane-bound proteins with predicted transit peptides, seven transmembrane regions, and conserved functional domains that are similar to other homogentisate prenyltransferases. Recombinant MaIDT and CtIDT were able to regioselectively introduce dimethylallyl diphosphate into the A ring of three flavonoids with different skeleton types (chalcones, isoflavones, and flavones). Phylogenetic analysis revealed that MaIDT and CtIDT are distantly related to their homologs in Leguminosae, which suggests that FPTs in Moraceae and Leguminosae might have evolved independently. MaIDT and CtIDT represent the first two non-Leguminosae FPTs to be identified in plants and could thus lead to the identification of additional evolutionarily varied FPTs in other non-Leguminosae plants and could elucidate the biosyntheses of prenylated flavonoids in various plants. Furthermore, MaIDT and CtIDT might be used for regiospecific prenylation of flavonoids to produce bioactive compounds for potential therapeutic applications due to their high efficiency and catalytic promiscuity.
Toward Neutral Principles of Stare Decisions in Tort Law (2006)

for sharing his thoughts and experience in addressing stare decisis as ajustice onl the Michigan Supreme Court, federal Judge .lackB. Weinstein of the Eastern District of
Closed-Form 2D Angle Estimation With Rectangular Arrays Via DFT Beamspace ESPRIT+ (1995)

UCA- ESPRITis a recently developed closed form algorithm for use in conjunction with a uniform circular array (UCA) that provides automatically paired source azimuth and elevation angle estimates. 2D DFT Beamspace ESPRIT is presented as an algorithm providing the same capabilities for a uniform rectangular array (URA). In the final stage of the algorithm, the real and imaginary parts of the i-th eigenvalue of a matrix yield the respective direction cosines of the i-th source relative to the two array axes. In addition to the reduction in computational complexity facilitated by operation in a reduced dimension beamspace, 20 DFT Beamspace ESPRIT is efficiently formulated in terms of real-valued computation throughout. Simulation results are presented verifying the efficacy of the method.
An Optimized FPGA-Based Real-Time NDT for 3D-LiDAR Localization in Smart Vehicles (2021)

Light detection and ranging (LiDAR) based normal distribution transform (NDT) is a popular localization algorithm in smart vehicles for its robustness and accuracy. To meet the requirement of higher speed of smart vehicles, LiDAR point clouds become increasingly large due to the increase of not only the number of laser channels but also their frame rates. However, previous NDT implementations fail to achieve real-time performance when handling large point clouds because they require an enormous number of search operations and perform intensive computations per search operation. To address this issue, we propose an optimized NDT algorithm and its FPGA implementation. First, we effectively speed up each search operation by proposing a new non-recursive and memory-efficient data structure, called occupation-aware-voxel-structure (OAVS). Second, we significantly reduce the number of search operations by removing redundant searches with an optimized semantic-assisted OAVS-based NDT algorithm (SEO-NDT). Third, we further improve the real-time and energy efficiency by proposing a streaming FPGA accelerator architecture for SEO-NDT. Compared with the state-of-the-art embedded CPU and GPU implementations, our FPGA implementation achieves up to 35.85x and 2.44x execution time speed up, respectively.