Heat stress affects tassel development and reduces the kernel number of summer maize

Maize grain yield is drastically reduced by heat stress (HTS) during anthesis and early grain filling. However, the mechanism of HTS in reproductive organs and kernel numbers remains poorly understood. From 2018 to 2020, two maize varieties (ND372, heat tolerant; and XY335, heat sensitive) and two temperature regimens (HTS, heat stress; and CK, natural control) were evaluated, resulting in four treatments (372CK, 372HTS, 335CK, and 335HTS). HTS was applied from the nine-leaf stage (V9) to the anthesis stage. Various morphological traits and physiological activities of the tassels, anthers, and pollen from the two varieties were evaluated to determine their correlation with kernel count. The results showed that HTS reduced the number of florets, tassel volume, and tassel length, but increased the number of tassel branches. HTS accelerates tassel degradation and reduces pollen weight, quantity, and viability. Deformation and reduction in length and volume due to HTS were observed in both the Nongda 372 (ND372) and Xianyu 335 (XY335) varieties, with the average reductions being 22.9% and 35.2%, respectively. The morphology of the anthers changed more conspicuously in XY335 maize. The number of kernels per spike was reduced in the HTS group compared with the CK group, with the ND372 and XY335 varieties showing reductions of 47.3% and 59.3%, respectively. The main factors underlying the decrease in yield caused by HTS were reductions in pollen quantity and weight, tassel rachis, and branch length. HTS had a greater effect on the anther shape, pollen viability, and phenotype of XY335 than on those of ND372. HTS had a greater impact on anther morphology, pollen viability, and the phenotype of XY335 but had no influence on the appearance or dissemination of pollen from tassel

Imprint of the stochastic nature of photon emission by electrons on the proton energy spectra in the laser-plasma interaction

The impact of stochasticity effects (SEs) in photon emissions on the proton energy spectra during laser-plasma interaction is theoretically investigated in the quantum radiation-dominated regime, which may facilitate SEs experimental observation. We calculate the photon emissions quantum mechanically and the plasma dynamics semiclassically via two-dimensional particle-in-cell simulations. An ultrarelativistic plasma generated and driven by an ultraintense laser pulse head-on collides with another strong laser pulse, which decelerates the electrons due to radiation-reaction effect and results in a significant compression of the proton energy spectra because of the charge separation force. In the considered regime the SEs are demonstrated in the shift of the mean energy of the protons up to hundreds of MeV. This effect is robust with respect to the laser and target parameters and measurable in soon available strong laser facilities

Artificial Intelligence-Enabled ECG Algorithm Based on Improved Residual Network for Wearable ECG

Heart disease is the leading cause of death for men and women globally. The residual network (ResNet) evolution of electrocardiogram (ECG) technology has contributed to our understanding of cardiac physiology. We propose an artificial intelligence-enabled ECG algorithm based on an improved ResNet for a wearable ECG. The system hardware consists of a wearable ECG with conductive fabric electrodes, a wireless ECG acquisition module, a mobile terminal App, and a cloud diagnostic platform. The algorithm adopted in this study is based on an improved ResNet for the rapid classification of different types of arrhythmia. First, we visualize ECG data and convert one-dimensional ECG signals into two-dimensional images using Gramian angular fields. Then, we improve the ResNet-50 network model, add multistage shortcut branches to the network, and optimize the residual block. The ReLu activation function is replaced by a scaled exponential linear units (SELUs) activation function to improve the expression ability of the model. Finally, the images are input into the improved ResNet network for classification. The average recognition rate of this classification algorithm against seven types of arrhythmia signals (atrial fibrillation, atrial premature beat, ventricular premature beat, normal beat, ventricular tachycardia, atrial tachycardia, and sinus bradycardia) is 98.3%

Genetics of Resistance to Common Root Rot (Spot Blotch), Fusarium Crown Rot, and Sharp Eyespot in Wheat

Due to soil changes, high density planting, and the use of straw-returning methods, wheat common root rot (spot blotch), Fusarium crown rot (FCR), and sharp eyespot (sheath blight) have become severe threats to global wheat production. Only a few wheat genotypes show moderate resistance to these root and crown rot fungal diseases, and the genetic determinants of wheat resistance to these devastating diseases are poorly understood. This review summarizes recent results of genetic studies of wheat resistance to common root rot, Fusarium crown rot, and sharp eyespot. Wheat germplasm with relatively higher resistance are highlighted and genetic loci controlling the resistance to each disease are summarized

An improved extraction method reveals varied DNA content in different parts of the shells of Pacific oysters

The DNA in the shell of Crassostrea gigas could have important roles in the shell biomineralization. However, limited by the low efficiency of existing extraction methods, studies investigating the DNA in shells are lacking. In this study, the shell DNA of C. gigas was extracted using the organic solvent extraction (OSE) and guanidine lysis buffer (GLB) methods; the efficiency and quality of these two methods were compared. The sequences of a mitochondrial gene (cytochrome c oxidase subunit I, COI) and a nuclear gene (28S rRNA) of C. gigas were analyzed to verify the origin of the extracted shell DNA. Finally, the DNA contents of the ventral edge, middle part, and dorsal edge of C. gigas shells were compared. The results showed that OSE had a higher DNA extraction efficiency than GLB; the oyster shell DNA was homologous to the oyster genome; the DNA content was higher in the ventral edge than in the middle part or in the dorsal edge of the C. gigas shell. This study not only reports an improved extraction method for the mollusk shell DNA, but also revealed that the DNA in the oyster shell originates from the oyster body and that the DNA content in different parts of the C. gigas shell showed obvious variance. These results provide supporting evidence for the hypothesis that oyster cells participate in shell formation, and also afford a nondestructive method for oyster genetic identification, which can promote the application of molecular biology technology in oyster breeding. In addition, a shell growth pattern of ‘Under Old & Exceeding Old’ was also proposed

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort (n= 92) and evaluated on a testing cohort (n= 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.</p

DESIGN AND RESEARCH ARM OF THE CONVERTER SLIDE

A hydraulic mechanical arm is designed,which realizes the installation and disassembly of the converter and the mechanical and automation of the transport. In order to verify the rationality of the design,through the Pro/Engineer,ADAMS,ANSYS structural co-simulation platform,a key part of the mounting arm coupled to the flexible member is rigid virtual prototype model. According to the practical application of the mechanical arm,telescopic hydraulic cylinders to determine the scope,and its validation,ensuring that meet the requirements. By ADAMS kinematics and dynamics simulation analysis,mounting arm motion displacement curve and the mounting process load lifting arm high dynamic stress areas. Based on ANSYS software provides mounting arm modal constraints analysis,identify the natural frequency and vibration mode of mounting arm,optimize its structural strength and resistance to impact and improve the ability of vibration reference

Variation in Potential Evapotranspiration and Its Sensitivity Coefficients to Climatic Factors in the Huang-Huai-Hai Plain

peer reviewedPotential evapotranspiration (ET0) is generally accepted to be an important element of the hydrological cycle, and changes in sensitivity coefficients of ET0 are of great significance for agricultural water use planning, irrigation system design and management. Potential evapotranspiration and their sensitivity coefficients in four seasons and entire year were calculated by the Penman-Monteith methods and partial derivative equation across six agricultural sub-zones of the Huang-Huai-Hai plain (3H plain) from a data set of daily climate variables in 40 meteorological stations during the period from 1961 to 2013. The highest value of ET0 was found in summer, while in autumn and winter in the fourth zone. A decreasing trend for ET0 was detected in summer in these six sub-zones in recent 53 years and maximum amplitude was found in fifth zone. However, an increasing trend for ET0 was detected in second and sixth zone during spring and in second zone during winter. Relative humidity was considered to be the most sensitive variable for ET0 in spring, autumn, winter and whole year and solar radiation was the most sensitive variable for ET0 in summer. Moreover, the positive and negative values of sensitivity coefficients were recognized as solar radiation and relative humidity respectively for ET0 with a decreasing trend, similarly for wind speed and air temperature with an increasing trend. Moreover, the high value of sensitivity coefficients to relative humidity and wind speed was found in the first zone of study area, while the high value of sensitivity coefficients to solar radiation and air temperature was in fourth zone of south region. The findings from this research provide important information for crop planting adjustment, ecological engineering planning and water-soil resource management in 3H plain in an attempt to improving the healthy development of agriculture and ecological environmen