New methods for measuring CSA tensors : applications to nucleotides and nucleosides

A novel version of the CSA (Chemical Shift Anisotropy) amplification experiment which results in large amplification factors is introduced. Large xa (up to 48) are achieved by sequences which are efficient in terms of the number of π pulses and total duration compared to a modification due to Orr et al. (2005), and greater flexibility in terms of the choice of amplification factor is possible than in our most recent version. Furthermore, the incorporation of XiX decoupling ensures the overall sensitivity of the experiment is optimal. This advantage has been proved by extracting the CSA tensors for a novel vinylphosphonate-linked nucleotide. The application of CSA amplification experiment to six nucleosides is also discussed. The measured principal tensor values are compared with those calculated using the recently developed first-principles methods. Throughout this work, the NMR parameters of all nucleosides are presented. Finally, high-resolution multi-nuclear solid-state NMR experiments are used to study some novel vinyl phosphonate-linked oligo-nucleotides

Genetic Characterization of Cynodon Accessions by Morphology, Flow Cytometry and Dna Profiling

Crop Scienc

The dynamical second-order transport coefficients of smeared Dp-brane

The smeared Dp-brane is constructed by having the black Dp-brane uniformly smeared over several transverse directions. After integrating the spherical directions and the smeared directions, the smeared Dp-brane turns out to be a Chamblin-Reall model with one background scalar field. Within the framework of the fluid/gravity correspondence, we not only prove the equivalence between the smeared Dp-brane and the compactified Dp-brane by explicitly calculating the 7 dynamical second-order transport coefficients of their dual relativistic fluids, but also revisit the Correlated Stability Conjecture for the smeared Dp-brane via the fluid/gravity correspondence.Comment: 25pages, 2 table

New methods for measuring CSA tensors : applications to nucleotides and nucleosides

A novel version of the CSA (Chemical Shift Anisotropy) amplification experiment which results in large amplification factors is introduced. Large xa (up to 48) are achieved by sequences which are efficient in terms of the number of π pulses and total duration compared to a modification due to Orr et al. (2005), and greater flexibility in terms of the choice of amplification factor is possible than in our most recent version. Furthermore, the incorporation of XiX decoupling ensures the overall sensitivity of the experiment is optimal. This advantage has been proved by extracting the CSA tensors for a novel vinylphosphonate-linked nucleotide. The application of CSA amplification experiment to six nucleosides is also discussed. The measured principal tensor values are compared with those calculated using the recently developed first-principles methods. Throughout this work, the NMR parameters of all nucleosides are presented. Finally, high-resolution multi-nuclear solid-state NMR experiments are used to study some novel vinyl phosphonate-linked oligo-nucleotides

Comparative analysis reveals chromosome number reductions in the evolution of African bermudagrass (Cynodon transvaalensis Burtt-Davy)

African bermudagrass (Cynodon transvaalensis Burtt-Davy) (2n = 2x = 18) belongs to the genus Cynodon, tribe Cynodonteae, subfamily Chloridoideae in the grass family Poaceae. The species is frequently crossed with common bermudagrass (Cynodon dactylon Pers.) in developing high-quality hybrid turf cultivars. Molecular resources for C. transvaalensis are scarce; thus, its genomic evolution is unknown. Recently, a linkage map consisting of 1278 markers provided a powerful tool for African bermudagrass genomic research. The objective of this study was to investigate chromosome number reduction events that resulted in the nine haploid chromosomes in this species. Tag sequences of mapped single nucleotide polymorphism markers in C. transvaalensis were compared against genome sequences of Oropetium thomaeum (L.f.) Trin. (2n = 2x = 20), a genomic model in the Cynodonteae tribe. The comparative genomic analyses revealed broad collinearity between the genomes of these two species. The analyses further revealed that two major interchromosomal rearrangements of the paleochromosome ρ12 (ρ1– ρ12–ρ1 and ρ6–ρ12–ρ6) resulted in nine chromosomes in the genome of C. transvaalensis. The findings provide novel information regarding the formation of the initial diploid species in the Cynodon genus.Horticulture and Landscape ArchitecturePlant and Soil Science

Development of a genome-wide multiple duplex-SSR protocol and its applications for the identification of selfed progeny in switchgrass

Background: Switchgrass (Panicum virgatum) is a herbaceous crop for the cellulosic biofuel feedstock development in the USA and Europe. As switchgrass is a naturally outcrossing species, accurate identification of selfed progeny is important to producing inbreds, which can be used in the production of heterotic hybrids. Development of a technically reliable, time-saving and easily used marker system is needed to quantify and characterize breeding origin of progeny plants of targeted parents.Results: Genome-wide screening of 915 mapped microsatellite (simple sequence repeat, SSR) markers was conducted, and 842 (92.0%) produced clear and scorable bands on a pooled DNA sample of eight switchgrass varieties. A total of 166 primer pairs were selected on the basis of their relatively even distribution in switchgrass genome and PCR amplification quality on 16 tetraploid genotypes. Mean polymorphic information content value for the 166 markers was 0.810 ranging from 0.116 to 0.959. From them, a core set of 48 loci, which had been mapped on 17 linkage groups, was further tested and optimized to develop 24 sets of duplex markers. Most of (up to 87.5%) targeted, but non-allelic amplicons within each duplex were separated by more than 10-bp. Using the established duplex PCR protocol, selfing ratio (i.e., selfed/all progeny x100%) was identified as 0% for a randomly selected open-pollinated 'Kanlow' genotype grown in the field, 15.4% for 22 field-grown plants of bagged inflorescences, and 77.3% for a selected plant grown in a growth chamber.Conclusions: The study developed a duplex SSR-based PCR protocol consisting of 48 markers, providing ample choices of non-tightly-linked loci in switchgrass whole genome, and representing a powerful, time-saving and easily used method for the identification of selfed progeny in switchgrass. The protocol should be a valuable tool in switchgrass breeding efforts.Peer reviewedPlant and Soil Science

Complexity analysis of weakly noisy quantum states via quantum machine learning

Quantum computers capable of fault-tolerant operation are expected to provide provable advantages over classical computational models. However, the question of whether quantum advantages exist in the noisy intermediate-scale quantum era remains a fundamental and challenging problem. The root of this challenge lies in the difficulty of exploring and quantifying the power of noisy quantum states. In this work, we focus on the complexity of weakly noisy states, which we define as the size of the shortest quantum circuit required to prepare the noisy state. To analyze the complexity, we propose a quantum machine learning (QML) algorithm that exploits the intrinsic-connection property of structured quantum neural networks. The proposed QML algorithm enables efficiently predicting the complexity of weakly noisy states from measurement results, representing a paradigm shift in our ability to characterize the power of noisy quantum computation

Winter Survival of Experimental Bermudagrasses in the Upper Transition Zone

A winter with very cold temperatures in 2017–2018 allowed for good separation of standard and experimental bermudagrasses for freezing tolerance. When evaluated in May 2018, survival of commonly used cultivars was: Tifway, 0%; Latitude 36, 20%; Northbridge, 25%. Some experimental progeny had up to 98% winter survival on the same rating date

Trainability Analysis of Quantum Optimization Algorithms from a Bayesian Lens

The Quantum Approximate Optimization Algorithm (QAOA) is an extensively studied variational quantum algorithm utilized for solving optimization problems on near-term quantum devices. A significant focus is placed on determining the effectiveness of training the $n$-qubit QAOA circuit, i.e., whether the optimization error can converge to a constant level as the number of optimization iterations scales polynomially with the number of qubits. In realistic scenarios, the landscape of the corresponding QAOA objective function is generally non-convex and contains numerous local optima. In this work, motivated by the favorable performance of Bayesian optimization in handling non-convex functions, we theoretically investigate the trainability of the QAOA circuit through the lens of the Bayesian approach. This lens considers the corresponding QAOA objective function as a sample drawn from a specific Gaussian process. Specifically, we focus on two scenarios: the noiseless QAOA circuit and the noisy QAOA circuit subjected to local Pauli channels. Our first result demonstrates that the noiseless QAOA circuit with a depth of $\tilde{\mathcal{O}}\left(\sqrt{\log n}\right)$ can be trained efficiently, based on the widely accepted assumption that either the left or right slice of each block in the circuit forms a local 1-design. Furthermore, we show that if each quantum gate is affected by a $q$-strength local Pauli channel with the noise strength range of $1/{\rm poly} (n)$ to 0.1, the noisy QAOA circuit with a depth of $\mathcal{O}\left(\log n/\log(1/q)\right)$ can also be trained efficiently. Our results offer valuable insights into the theoretical performance of quantum optimization algorithms in the noisy intermediate-scale quantum era

GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence

Conditional story generation is significant in human-machine interaction, particularly in producing stories with complex plots. While Large language models (LLMs) perform well on multiple NLP tasks, including story generation, it is challenging to generate stories with both complex and creative plots. Existing methods often rely on detailed prompts to guide LLMs to meet target conditions, which inadvertently restrict the creative potential of the generated stories. We argue that leveraging information from exemplary human-written stories facilitates generating more diverse plotlines. Delving deeper into story details helps build complex and credible plots. In this paper, we propose a retrieval-au\textbf{G}mented sto\textbf{R}y generation framework with a f\textbf{O}rest of e\textbf{V}id\textbf{E}nce (GROVE) to enhance stories' complexity. We build a retrieval repository for target conditions to produce few-shot examples to prompt LLMs. Additionally, we design an ``asking-why'' prompting scheme that extracts a forest of evidence, providing compensation for the ambiguities that may occur in the generated story. This iterative process uncovers underlying story backgrounds. Finally, we select the most fitting chains of evidence from the evidence forest and integrate them into the generated story, thereby enhancing the narrative's complexity and credibility. Experimental results and numerous examples verify the effectiveness of our method.Comment: Findings of EMNLP 202