Genomic selection (GS) is a promising breeding strategy by which the phenotypes of plant individuals are usually predicted based on genome-wide markers of genotypes. In this study, we present a deep ...learning method, named DeepGS, to predict phenotypes from genotypes. Using a deep convolutional neural network, DeepGS uses hidden variables that jointly represent features in genotypes when making predictions; it also employs convolution, sampling and dropout strategies to reduce the complexity of high-dimensional genotypic data. We used a large GS dataset to train DeepGS and compared its performance with other methods. The experimental results indicate that DeepGS can be used as a complement to the commonly used RR-BLUP in the prediction of phenotypes from genotypes. The complementarity between DeepGS and RR-BLUP can be utilized using an ensemble learning approach for more accurately selecting individuals with high phenotypic values, even for the absence of outlier individuals and subsets of genotypic markers. The source codes of DeepGS and the ensemble learning approach have been packaged into Docker images for facilitating their applications in different GS programs.
A convenient synthetic route has been developed for preparing the novel rigid 4,5-(PR2)2–2,7,9,9-tetramethylacridane-based pincer ligands (acri‑RPNP; R = i Pr and Ph), and the first rare-earth (Ln = ...Y, Lu) alkyl complexes bearing the acri‑RPNP ligands were synthesized by a salt metathesis reaction (for the isopropyl-substituent acri‑iPrPNP complexes, 1-Ln) or direct alkylation (for the phenyl-substituent acri‑PhPNP complexes, 2-Ln). For both 1-Ln and 2-Ln, the NMR spectroscopy and X-ray diffraction study confirmed the successful coordination of the acri‑RPNP ligand to the central metal ion in a tridentate manner via the two phosphine and the nitrogen donors. In contrast to 1-Ln that are solvent-free complexes, the metal centers in 2-Ln are each coordinated with one tetrahydrofuran molecule. Upon activation by Ph3CB(C6F5)4, 1-Y and 2-Lu could catalyze the living polymerization of isoprene and β-myrcene with high catalytic activity and high cis-1,4-selectivity (up to 92.3% for isoprene and 98.5% for β-myrcene). Moreover, the 1-Y/Ph3CB(C6F5)4 catalytic system also could promote the polymerization of butadiene and its copolymerization with isoprene to produce copolymers with high cis-1,4-selectivity and narrow polydispersity.
Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are the main pathogenic microorganisms causing sexually transmitted infections. In this study, a multiplex thermostable recombinase ...polymerase amplification-lateral flow detection (RPA-LFD) assay was established, and the reaction conditions such as the ratio of primer concentration, magnesium ion concentration, amplification time and template DNA concentration in the multiplex RPA reaction were optimized. The optimized multiplex RPA-LFD method was used to detect both CT and NG positive control plasmids, and it was found that the LFD could be used to obtain visible results when the plasmid copy number was only 200. The sensitivity of the multiplex RPA-LFD method used for clinical samples was 85.62 (95% CI at 53.66-97.29) for NG detection and 90.90 (95% CI at 57.12-99.52) for CT detection.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A PNP-pincer ligand provides a versatile ligation framework, which is highly useful in organometallic chemistry and catalytic chemistry. In this work, by a de novo strategy, a simple and efficient ...synthetic pathway, has been developed to prepare the new iminodibenzyl-based PNP pincer proligand imin‑RPNP(Li or H) (R = isopropyl, phenyl). By employing salt metathesis or direct alkyl elimination, we successfully synthesized a series of iminodibenzyl-PNP rare-earth-metal (Ln = Sc, Y, Dy, Ho, Er, Tm, Lu) complexes and characterized them by NMR and X-ray diffraction analyses. Upon addition of a borate and triisobutylaluminum (TIBA), the rare-earth-metal complexes 2-Y, 2-Dy, 2-Ho, 2-Er, and 2-Tm bearing the imin‑PhPNP ligand exhibited unexpectedly high 3,4-selectivity (up to 95%) for the polymerization of 1,3-dienes (isoprene and myrcene); in particular, the chosen yttrium complex 2-Y promoted the 1,3-diene polymerization in a living manner. A computational study suggested that the sterically congested configuration around the metal center imposed by the imin‑RPNP ligand might be the main reason for this unusual selectivity.
MicroRNAs (miRNAs) are a class of short, non-coding RNA that play regulatory roles in a wide variety of biological processes, such as plant growth and abiotic stress responses. Although several ...computational tools have been developed to identify primary miRNAs and precursor miRNAs (pre-miRNAs), very few provide the functionality of locating mature miRNAs within plant pre-miRNAs. This manuscript introduces a novel algorithm for predicting miRNAs named miRLocator, which is based on machine learning techniques and sequence and structural features extracted from miRNA:miRNA* duplexes. To address the class imbalance problem (few real miRNAs and a large number of pseudo miRNAs), the prediction models in miRLocator were optimized by considering critical (and often ignored) factors that can markedly affect the prediction accuracy of mature miRNAs, including the machine learning algorithm and the ratio between training positive and negative samples. Ten-fold cross-validation on 5854 experimentally validated miRNAs from 19 plant species showed that miRLocator performed better than the state-of-art miRNA predictor miRdup in locating mature miRNAs within plant pre-miRNAs. miRLocator will aid researchers interested in discovering miRNAs from model and non-model plant species.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
At the general debate of the 75th session of the United Nations General Assembly, president Xi Jinping proposed to reach ”carbon peak” by 2030 and strive to achieve the ”carbon neutrality” by 2060. ...Research on carbon emission projections is of positive significance to facilitate the effective application of ”double carbon” in China. Therefore, this paper proposes a regional carbon emission projection method. Firstly, based on the regional resource endowment and historical data on energy consumption, this paper forecasts the energy structure of each sector in the region through the Markov model and the energy demand of each sector in the region through the LEAP model. Then, the CO2 emission factor of each energy source is calculated. Finally, the projection of regional CO2 emissions under different policy and technology scenarios is provided by considering the influence of different factors on future regional carbon emissions, and the emission reduction potential is analyzed based on the projection results. To check the effectiveness of the presented method, this paper carries out a case study of regional CO2 emission in a city in China and analyzes the emission decrease effect of each proposed initiative according to the projected results. The results of the case study demonstrate that the presented method can effectively assess the regional CO2 emissions and the reduction potential of different emission reduction measures.
The access of photovoltaics can reduce the carbon emissions of the integrated energy system and can also improve the economics of terminal energy supply, but the uncertainty of photovoltaic output ...also brings greater challenges to the optimal operation of the system. This paper focuses on coordinated optimization for the multiple energy systems in consideration of demand response. Latin hypercube sampling and the K-means algorithm are used to generate acceptable scenarios to deal with the photovoltaic uncertainty. Demand response based on Time-of-Use (TOU) electricity price is employed to realize the peak load shifting, and in consequence to improve the system operation. The optimization objective is to minimize the operational cost, subject to the constraints of electric grids, natural gas grids, and hot water pipeline grids. Due to the nonconvex constraints of these grids, the constraints are relaxed by means of the mixed integer linear programming approach, and the whole problem is established as a mixed integer linear programming model. Case studies show that demand response in each energy system and the coordinated optimization between the multiple energy systems can reduce the operational cost of the whole system. Even though the photovoltaic uncertainty results in a higher operational cost, the system has a more reliable operating point.
Maximum power point tracking (MPPT) plays an important role in increasing the efficiency of a wind energy conversion system (WECS). In this paper, three conventional MPPT methods are reviewed: power ...signal feedback (PSF) control, decreased torque gain (DTG) control, and adaptive torque gain (ATG) control, and their potential challenges are investigated. It is found out that the conventional MPPT method ignores the effect of wind turbine inertia and wind speed fluctuations, which lowers WECS efficiency. Accordingly, an improved adaptive torque gain (IATG) method is proposed, which customizes adaptive torque gains and enhances MPPT performances. Specifically, the IATG control considers wind farm turbulences and works out the relationship between the optimal torque gains and the wind speed characteristics, which has not been reported in the literature. The IATG control is promising, especially under the ongoing trend of building wind farms with large-scale wind turbines and at low and medium wind speed sites.
In 2018, a flash flood occurred in the Zhongdu river, which lies in Yibin, Sichuan province of China. The flood caused many casualties and significant damage to people living nearby. Due to the ...difficulty in predicting where and when flash floods will happen, it is nearly impossible to set up monitors in advance to detect the floods in detail. Field investigations are usually carried out to study the flood propagation and disaster-causing mechanism after the flood’s happening. The field studies take the relic left by the flash flood to deduce the peak level, peak discharge, bed erosion, etc. and further revel the mechanism between water and sediment transport during the flash flood This kind of relic-based study will generate bigger errors in regions with great bed deformation. In this study, we come up with numerical simulations to investigate the flash flood that happened in the Zhongdu river. The simulations are based on two-dimensional shallow water models coupled with sediment transport and bed deformation models. Based on the real water level and discharge profile measured by a hydrometric station nearby, the numerical simulation reproduced the flash flood in the valley. The results show the flood coverage, water level variation, and velocity distribution during the flood. The simulation offers great help in studying the damage-causing process. Furthermore, simulations without considering sediment transport are also carried out to study the impact of bed erosion and sedimentation. The study proved that, without considering bed deformation, the flood may be greatly underestimated, and the sediment lying in the valley has great impact on flood power.
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