gebhart/patrepeval huggingface dataset:
Selective Genotyping for Marker Assisted Selection Strategies for Soybean Yield Improvement (2015)

Using molecular markers in soybean [Glycine max (L.) Merr.] has lead to the identification of major loci controlling quantitative and qualitative traits that include: disease resistance, insect resistance and tolerance to abiotic stresses. Yield has been considered as one of the most important quantitative traits in soybean breeding. Unfortunately, yield is a very complex trait and most yield quantitative trait loci (QTL) that have been identified have had only limited success for marker assisted selection (MAS). The objective of this study was to identify QTL associated with soybean seed yield in preliminary yield trials grown in different environments and to evaluate their effective use for MAS using a yield prediction model (YPM), which included epistasis. To achieve this objective, 875 F5:9 recombinant inbred lines (RIL) from a population developed from a cross between two prominent ancestors of the North American soybean (Essex and Williams 82) were used. The 875 RIL and check cultivars were divided into four groups based on maturity and each group was grown in Knoxville, TN and one other location that had an environment in which the maturity group (MG) was adapted to be grown. Each RIL was genotyped with &gt;50,000 single nucleotide polymorphic markers (SNPs) of which 17,232 were polymorphic across the population. Yield QTL were detected using a single factor (SF) analysis of variance (ANOVA) and composite interval mapping (CIM). Based on CIM, 23 yield QTL were identified. Twenty-one additional QTL were detected using SF ANOVA. Individually, these QTL explained from 4.5% to 11.9% of the phenotypic variation for yield. QTL were identified on all 20 chromosomes and five of the 46 QTL have not been previously reported. This study provides new information concerning yield QTL in soybean and may offer important insights into MAS strategies for soybean.
Impact of the Proline Residue on Ligand Binding of Neurotensin Receptor 2 (NTS2)‐Selective Peptide–Peptoid Hybrids (2013)

To investigate the binding mode and structure-activity relationships (SARs) of selective neurotensin receptor 2 (NTS2) ligands, novel peptide-peptoid hybrids that simulate the function of the endogenous ligand were developed. Starting from our recently described NTS2 ligands of type 1, structural variants of type 2 and the metabolically stable analogues 3 a,b were developed. Replacement of the proline unit by a collection of structural surrogates and evaluation of the respective molecular probes for NTS2 affinity and selectivity indicated similar SARs as described for NT(8-13) derivatives bound to the subtype NTS1. Peptide-peptoid hybrids 2 d, 3 a,b showed substantial NTS2 binding affinity (Ki =8.1-16 nM) and 2400-8600-fold selectivity over NTS1. The thiazolidine derivative 3 b showed metabolic stability over 32 h in a serum degradation assay. In an inositol phosphate accumulation assay, the neurotensin mimetics 3 a and 3 b displayed an inhibition of constitutive activity exceeding 1.7-2.0 times the activity of NT(8-13). The fluorinated derivative 3 a could afford attractive opportunities to detect NTS2 by (19) F magnetic resonance imaging.
Performance prediction of a tidal in-stream current energy converter and site assessment next to Jindo, South Korea (2015)

The magnitude of energy, which can be extracted by tidal energy converter devices, has a significant impact on the commercial viability of a project. Therefore, a quantitative characterization of the tidal current at the location of interest and subsequently a reliable prediction of the productivity of a tidal energy converter prior to installation is of high interest. This paper presents the successful deployment of a unique and novel fully symmetric tidal in-stream current energy converter HyTide 110-5.3 in Jindo, South Korea, and a methodology to predict the productivity of a single device based on simulation. The simulation combines a 2D shallow water equation model with turbine performance curves and is validated using real performance data from the prototype under real conditions. In addition, the predicted productivity is compared with actual field measurements during the operation of the Voith demonstrator using two Acoustic Doppler Current Profilers according to the IEC specifications for the performance assessment of Tidal Energy Converters, which is novel at that time. The simulation results show that the productivity of a single device can be predicted accurately and furthermore serves as a proof of concept for the symmetrical turbine layout. The 2D shallow water equation solver based on OpenFOAM® (tidalFoam) captures the rough conditions at the turbine site accurately, where the turbine is facing flood tides with a mean inclined inflow angle of 30°. In addition, the zero-equation turbulence model is shown to successfully capture the influence of a Kármán Vortex street on the turbine unit. High-resolution data of bathymetry, shorelines, and tidal elevations are used to set up the open boundaries of the unstructured mesh used in the model. The sea ground friction as an additional source term in the model is used to calibrate the simulation against Acoustic Doppler Current Profiler measurements on site. The simulation results are shown to be reliable, yielding highly accurate productivity predictions of a single tidal turbine. This is an important step towards a robust commercial evaluation of tidal energy projects prior to installation. Based on the single turbine model, simulations of three tidal current turbine farms as well as the available theoretical and technical power output of the region around Jindo during an entire moon cycle were performed. Possible impacts on average volumetric flow rate changes for neighbouring channels are presented.
Location of the Synaptosome-Binding Regions on Botulinum Neurotoxin B (2011)

The regions of botulinum neurotoxin B (BoNT/B) involved in binding to mouse brain synaptosomes (snps) were localized. Sixty 19-residue overlapping peptides (peptide C31 consisted of 24 residues) encompassing BoNT/B H chain (residues 442-1291) were synthesized and used to inhibit binding of (125)I-labeled BoNT/B to snps. Synaptosome-binding regions were noncompeting and existed on both H(N) and H(C) domains of neurotoxin. At 37 °C, inhibitory activities on H(N) resided, in decreasing order, in peptides 638-656 (26.7%), 596-614 (18.2%), 512-530 (13.9%), 778-796 (13.8%), and 526-544 (11.6%). On H(C), activity resided in decreasing order in peptides 1170-1188 (44.6%), 1128-1146 (21.6%), 1184-1202 (18.6%), 1156-1174 (13.0%), 946-964 (11.8%), 1114-1132 (11.2%), 1100-1118 (6.2%), 876-894 (6.1%), 1268-1291 (4.6%), and 1226-1244 (4.3%). The 45 remaining H(N) and H(C) peptides had no activity. At 4 °C, peptide C24 (1170-1188) remained quite active (inhibiting, 31.2%), while activities of peptides N15, C21, and C25 were little under 10%. The snp-binding regions contained sites that bind synaptotagmin II and gangliosides. Despite the low degree of sequence homology, BoNT/B and BoNT/A display significant structural homology and appeared to bind in part to the same snp-binding regions. Binding of each labeled toxin to snps was inhibited ~50% by the other toxin, 70-72% by its correlate H(C), and by the H(C) of the other toxin [29% (BoNT/A by H(C) of B) or 32% (BoNT/B by H(C) of A)]. In the three-dimensional structure of BoNT/B, the greater part of H(C), one H(N) face, and part of the belt on the same side interact with snps. Thus, BoNT/B binds to snps through the H(C) head and employs regions on one H(N) face and the belt, reserving flexibility for the belt's unbound part to release the light chain. Most snp-binding regions coincide or overlap with blocking antibody (Ab)-binding regions explaining how such Abs prevent BoNT/B toxicity.
A 400-BPS Vocoder using Line Spectral Frequencies and Frame Repeat Coding (1986)

A 400-bps vocoder utilizing frame repeat vector quantization is described that is designed to be used with fixed data rate systems. It combines several improvements over existing 400-bps systems. Line spectrum frequency parameters are vector quantized using a perceptually meaningful distortion metric. Frames to be repeated are determined from a buffer's length of data, which determines the coding delay. Excitation parameters are trellis coded using a variable lookahead approach to minimize throughput delay.
Platform Agnostic Streaming Data Application Performance Models (2021)

The mapping of computational needs onto execution resources is, by and large, a manual task, and users are frequently guided simply by intuition and past experiences. We present a queueing theory based performance model for streaming data applications that takes steps towards a better understanding of resource mapping decisions, thereby assisting application developers to make good mapping choices. The performance model (and associated cost model) are agnostic to the specific properties of the compute resource and application, simply characterizing them by their achievable data throughput. We illustrate the model with a pair of applications, one chosen from the field of computational biology and the second is a classic machine learning problem.
Compact holographic optical neural network system for real‐time pattern recognition (1996)

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with onedimensional electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high-resolution volume holographic materials and is capable of performing massive 3-D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation-shift-scaleinvariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.
RNA interference-based functional knockdown of the voltage-gated potassium channel Kv7.2 in dorsal root ganglion neurons after in vitro and in vivo gene transfer by adeno-associated virus vectors (2017)

Activation of the neuronal potassium channel Kv7.2 encoded by the KCNQ2 gene has recently been shown to be an attractive mechanism to inhibit nociceptive transmission. However, potent, selective, and clinically proven activators of Kv7.2/Kv7.3 currents with analgesic properties are still lacking. An important prerequisite for the development of new drugs is a model to test the selectivity of novel agonists by abrogating Kv7.2/Kv7.3 function. Since constitutive knockout mice are not viable, we developed a model based on RNA interference-mediated silencing of KCNQ2. By delivery of a KCNQ2-specific short hairpin RNA with adeno-associated virus vectors, we completely abolished the activity of the specific Kv7.2/Kv7.3-opener ICA-27243 in rat sensory neurons. Results obtained in the silencing experiments were consistent between freshly prepared and cryopreserved dorsal root ganglion neurons, as well as in dorsal root ganglion neurons dissociated and cultured after in vivo administration of the silencing vector by intrathecal injections into rats. Interestingly, the tested associated virus serotypes substantially differed with respect to their transduction capability in cultured neuronal cell lines and primary dorsal root ganglion neurons and the in vivo transfer of transgenes by intrathecal injection of associated virus vectors. However, our study provides the proof-of-concept that RNA interference-mediated silencing of KCNQ2 is a suitable approach to create an ex vivo model for testing the specificity of novel Kv7.2/Kv7.3 agonists.
Applications of signal-flow graph theory to epicyclic gear trains (1968)

The purpose of this correspondence is to illustrate the use of signal-flow graph theory in obtaining a topological representation of the linear relationship that exists between the inputs and outputs of an epicyclic gear train [1]. Additional applications of signal-flow graph theory are also suggested.
Relaxed Gaussian Belief Propagation (2012)

The Gaussian Belief Propagation (GaBP) algorithm executed on Gaussian Markov Random Fields can take a large number of iterations to converge if the inverse covariance matrix of the underlying Gaussian distribution is ill-conditioned and weakly diagonally dominant. Such matrices can arise from many practical problem domains. In this study, we propose a relaxed GaBP algorithm that results in a significant reduction in the number of GaBP iterations (of up to 12.7 times). We also propose a second relaxed GaBP algorithm that avoids the need of determining the relaxation factor a priori which can also achieve comparable reductions in iterations by only setting two basic heuristic measures. We show that the new algorithms can be implemented without any significant increase, over the original GaBP, in both the computational complexity and the memory requirements. We also present detailed experimental results of the new algorithms and demonstrate their effectiveness in achieving significant reductions in the iteration count.
LedgerGuard: Improving Blockchain Ledger Dependability (2018)

The rise of crypto-currencies has spawned great interest in their underlying technology, namely, Blockchain. The central component in a Blockchain is a shared distributed ledger. A ledger comprises series of blocks, which in turns contains a series of transactions. An identical copy of the ledger is stored on all nodes in a blockchain network. Maintaining ledger integrity and security is one of the crucial design aspects of any blockchain platform. Thus, there are typically built-in validation mechanisms leveraging cryptography to ensure the validity of incoming blocks before committing them into the ledger. However, a blockchain node may run over an extended period of time, during which the blocks on the disk can may become corrupted due to software or hardware failures, or due to malicious activity. This paper proposes LedgerGuard, a tool to maintain ledger integrity by detecting corrupted blocks and recovering these blocks by synchronizing with rest of the network. The experimental implementation of LedgerGuard is based on Hyperledger Fabric, which is a popular open source permissioned blockchain platform.
A new form of hydroxyaluminum phthalocyanine by acid treatment. Characterization and photoactivity (1988)

A new polymorph of hydroxyaluminum phthalocyanine (PcAlOH) was obtained when PcAlOH thin film was exposed to aqueous acid solutions. The new polymorph, which is characterized by infrared, near-infrared, and visible absorption spectrometry and X-ray diffractometry, shows enhanced photoactivity in a photoelectrochemical solar cell device.
Robust background subtraction to global illumination changes via multiple features-based online robust principal components analysis with Markov random field (2015)

Background subtraction is an important task for various computer vision applications. The task becomes more critical when the background scene contains more variations, such as swaying trees and abruptly changing lighting conditions. Recently, robust principal component analysis (RPCA) has been shown to be a very efficient framework for moving-object detection. However, due to its batch optimization process, high-dimensional data need to be processed. As a result, computational complexity, lack of features, weak performance, real-time processing, and memory issues arise in traditional RPCA-based approaches. To handle these, a background subtraction algorithm robust against global illumination changes via online robust PCA (OR-PCA) using multiple features together with continuous constraints, such as Markov random field (MRF), is presented. OR-PCA with automatic parameter estimation using multiple features improves the background subtraction accuracy and computation time, making it attractive for real-time systems. Moreover, the application of MRF to the foreground mask exploits structural information to improve the segmentation results. In addition, global illumination changes in scenes are tackled by using sum of the difference of similarity measure among features, followed by a parameter update process using a low-rank, multiple features model. Evaluation using challenging datasets demonstrated that the proposed scheme is a top performer for a wide range of complex background scenes.
High-power laser transmitters for LADAR applications (2016)

We review architectures for high-power LADAR transmitters relying on fiber and hybrid fiber/bulk waveguide lasers. Multi-mJ/MW pulse energies/peak-powers are demonstrated in combination with good spatial/spectral beam quality and average output powers &gt; 100 W.
Surface Curvature and Shape Reconstruction from Unknown Multiple Illumination and Integrability (1997)

We present a multiple illumination technique that directly recovers the viewer-centered curvature matrix, up to a scalar factor, at each mutually illuminated point on a smooth object surface. This technique is completely independent of knowledge of incident illumination orientation, local surface orientation, or diffuse surface albedo. The cornerstore of this technique is the use of theintegrability constraintwhich is a fundamental mathematical property of smooth surfaces. The integrability constraint allows the derivation of an equation at each object point, which is linear in terms of quantities involving the initially unknown parameters of incident illumination orientation. These quantities, which we call thegradient ratio constants, can be simultaneously solved for five or more equations arising from the same number of object points. We show that deriving these gradient ratio constants provides just enough calibration information about incident illumination geometry to compute the viewer-centered curvature matrix at each object point, up to a scalar multiple. We demonstrate three important applications of this technique: (i) segmentation of the object surface by sign of Gaussian curvature, (ii) further segmentation of nonnegative Gaussian curvature into convexity and concavity, and (iii) reconstruction of the surface height, independent of knowledge of incident illumination orientation and diffuse surface albedo.
Development of Highly Potent and Selective Steroidal Inhibitors and Degraders of CDK8 (2018)

Cortistatin A is a natural product isolated from the marine sponge Corticium simplex and was found to be a potent and selective inhibitor of CDK8. Many synthetic groups have reported total syntheses of Cortistatin A; however, these syntheses require between 16 and 30 steps and report between 0.012-2% overall yields, which is not amenable to large-scale production. Owing to similarities between the complex core of Cortistatin A and the simple steroid core, we initiated a campaign to design simple, more easily prepared CDK8 inhibitors based on a steroid scaffold that would be more convenient for large-scale synthesis. Herein, we report the discovery and optimization of JH-VIII-49, a potent and selective inhibitor of CDK8 with a simple steroid core that has an eight-step synthesis with a 33% overall yield, making it suitable for large-scale preparation. Using this scaffold, we then developed a bivalent small molecule degrader, JH-XI-10-02, that can recruit the E3 ligase CRL4<sup>Cereblon</sup> to promote the ubiquitination and proteosomal degradation of CDK8.
Allelic loss on chromosome 3p21.3 and promoter hypermethylation of semaphorin 3B in non-small cell lung cancer. (2003)

The aim of this study was to evaluate the promoter methylation status and loss of heterozygosity (LOH) of the SEMA3B in non-small cell lung cancers (NSCLCs). We analyzed the methylation status of semaphorin 3B (SEMA3B) promoter and LOH at 3p21.3 in eight NSCLC cell lines and 27 primary tumors. Hypermethylation of SEMA3B was found in 50% of the cell lines and 41% of the primary tumors studied. The presence of hypermethylation was statistically associated with loss of SEMA3B expression in both cell lines (P = 0.02) and primary tumors (P < 0.01). There was no correlation between SEMA3B and tumor stage. On the other hand, the correlation between SEMA3B methylation status and LOH at 3p21.3 was significant (P = 0.02). Notably, 7 of 8 tumors with both hypermethylation and LOH of SEMA3B showed the absence of the expression. Treatment with 5-AZAC restored SEMA3B expression in NSCLC cell line. These results indicate that SEMA3B gene alterations may play a important role in the malignant transformation of NSCLC via a two-hit mechanism, including epigenetic changes and allelic loss, for tumor suppressor gene inactivation.
The novel Rho-GTPase activating gene MEGAP / srGAP3 has a putative role in severe mental retardation (2002)

In the last few years, several genes involved in X-specific mental retardation (MR) have been identified by using genetic analysis. Although it is likely that additional genes responsible for idiopathic MR are also localized on the autosomes, cloning and characterization of such genes have been elusive so far. Here, we report the isolation of a previously uncharacterized gene, MEGAP, which is disrupted and functionally inactivated by a translocation breakpoint in a patient who shares some characteristic clinical features, such as hypotonia and severe MR, with the 3p(-) syndrome. By fluorescence in situ hybridization and loss of heterozygosity analysis, we demonstrated that this gene resides on chromosome 3p25 and is deleted in 3p(-) patients that present MR. MEGAP/srGAP3 mRNA is predominantly and highly expressed in fetal and adult brain, specifically in the neurons of the hippocampus and cortex, structures known to play a pivotal role in higher cognitive function, learning, and memory. We describe several MEGAP/srGAP3 transcript isoforms and show that MEGAP/srGAP3a and -b represent functional GTPase-activating proteins (GAP) by an in vitro GAP assay. MEGAP/srGAP3 has recently been shown to be part of the Slit-Robo pathway regulating neuronal migration and axonal branching, highlighting the important role of MEGAP/srGAP3 in mental development. We propose that haploinsufficiency of MEGAP/srGAP3 leads to the abnormal development of neuronal structures that are important for normal cognitive function.
Pilot-Assisted Adaptive Channel Estimation for Coded MC-CDMA with ICI Cancellation (2009)

One of the promising wireless access techniques for the next generation mobile communications systems is multi-carrier code division multiple access (MC-CDMA). MC-CDMA can provide good transmission performance owing to the frequency diversity effect in a severe frequency-selective fading channel. However, the bit error rate (BER) performance of coded MC-CDMA is inferior to that of orthogonal frequency division multiplexing (OFDM) due to the residual inter-code interference (ICI) after frequency-domain equalization (FDE). Recently, we proposed a frequency-domain soft interference cancellation (FDSIC) to reduce the residual ICI and confirmed by computer simulation that the MC-CDMA with FDSIC provides better BER performance than OFDM. However, ideal channel estimation was assumed. In this paper, we propose adaptive decision-feedback channel estimation (ADFCE) and evaluate by computer simulation the average BER and throughput performances of turbo-coded MC-CDMA with FDSIC. We show that even if a practical channel estimation is used, MC-CDMA with FDSIC can still provide better performance than OFDM.
Figure S5 from α<sub>v</sub>β<sub>3</sub> Integrin Mediates Radioresistance of Prostate Cancer Cells through Regulation of Survivin (2023)

&lt;p&gt;siRNA doses&lt;/p&gt;