RESUMEN
Alternaria species are commonly found as saprophytes, endophytes and plant pathogens. During a survey of small-spored Alternaria in China, two new species were discovered from Cucurbitaceae plants collected in Hubei and Sichuan provinces. This study identified two new species of Alternaria using seven genes (ITS, GAPDH, TEF1, RPB2, Alt a 1, EndoPG, and OPA10-2) for phylogenetic analyses and morphological characteristics. The two new species A.jingzhouensis and A.momordicae were described and illustrated. Alternariajingzhouensis sp. nov., associated with Citrulluslanatus, is characterized by producing muriform, ellipsoidal, flask-shaped, rostrate, and beaked conidia. It differs from A.koreana, A.ovoidea, and A.baoshanensis by bearing conidia in a simple conidiogenous locus with occasionally longer beaks in a chain, and from A.momordicae sp. nov. by having shorter beaks. Alternariamomordicae sp. nov. from Momordicacharantia was distinct from A.koreana, A.ovoidea, and A.baoshanensis by producing muriform, long ellipsoid or ovoid to obclavate, sometimes inverted club-shaped conidia on a single conidiogenous locus with a wider body and longer beak in a chain, and distinct from A.jingzhouensis sp. nov. by a longer beak conidia. These two species were clearly distinguished from other species in the section Alternaria based on DNA based phylogeny and morphological characteristics. The morphological features were discussed and compared to relevant species in the present paper.
RESUMEN
The rapidly growing requirement for data has put forward Compressed Sensing (CS) to realize low-ratio sampling and to reconstruct complete signals. With the intensive development of Deep Neural Network (DNN) methods, performance in image reconstruction from CS measurements is constantly increasing. Currently, many network structures pay less attention to the relevance of before- and after-stage results and fail to make full use of relevant information in the compressed domain to achieve interblock information fusion and a great receptive field. Additionally, due to multiple resamplings and several forced compressions of information flow, information loss and network structure redundancy inevitably result. Therefore, an Information Enhancement and Fusion Network for CS reconstruction (IEF-CSNET) is proposed in this work, and a Compressed Information Extension (CIE) module is designed to fuse the compressed information in the compressed domain and greatly expand the receptive field. The Error Comprehensive Consideration Enhancement (ECCE) module enhances the error image by incorporating the previous recovered error so that the interlink among the iterations can be utilized for better recovery. In addition, an Iterative Information Flow Enhancement (IIFE) module is further proposed to complete the progressive recovery with loss-less information transmission during the iteration. In summary, the proposed method achieves the best effect, exhibits high robustness at this stage, with the peak signal-to-noise ratio (PSNR) improved by 0.59 dB on average under all test sets and sampling rates, and presents a greatly improved speed compared with the best algorithm.
RESUMEN
The powder process is dynamic at the microscale level. Due to the capillary effect, the viscous attraction of the liquid phase between particles alters the strength and stability of wet granular materials. In this paper, experiments on the rupture behavior of the funicular liquid bridge between three rigid spheres have been presented. The results show that the peak force and rupture distance of the funicular liquid bridges are affected by the size and relative position of the spheres, volume and viscosity of the liquid, and separation rate; the coalescence of the liquid bridges causes a decrease in peak force and an increase in rupture distance, and the rupture distance shows a nonmonotonic functional correlation with the separation rate. Finally, an empirical equation of the correlation between the rupture distance and liquid volume is proposed, whose rationality is verified by comparing it with the results of the existing models.
RESUMEN
Lactic acid enantiomers, normally found in fermented food, are absorbed into the blood and interact with plasma carrier protein human serum albumin (HSA). Unveiling the effect on the function and structure of HSA during chiral interaction can give a better understanding of the different distribution activities of the two enantiomers. Multi-spectroscopic methods and molecular modelling techniques are used to study the interactions between lactic acid enantiomers and HSA. Time-resolved and steady-state fluorescence spectra manifest that the fluorescence quenching mechanism is mainly static in type, due to complex formation. Binding interactions, deduced by thermodynamic calculation, agree with the docking prediction. Docking results and kinetic constants represent chiral-recognizing discriminations consistently. The bindings of lactic acid enantiomers lead to some microenvironmental and slight conformational changes of HSA as shown by circular dichroism (CD), synchronous and three-dimensional fluorescence spectra. This investigation may yield useful information about the possible toxicity risk of lactic acid enantiomers to human health.