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ObjectiveTo establish a culture-dependent rapid detection method for gas-producing spoilage bacteria in vinegar.MethodsOne kind of medium was screened out from six candidate media and modified. Then its specificity， accuracy， and sensitivity were determined， on which a detection method was proposed. This method was subsequently applied to assess heat sterilization conditions and preservative concentrations for vinegar products and to verify the detection effectiveness of vinegar products.ResultsA modified MRS medium that could specifically detect gas-producing spoilage bacteria in vinegar samples was proposed， with which negative results were obtained targeting at other 12 spoilage bacteria isolated from vinegar. The established method was adopted to examine 75 unknown vinegar samples and plastic bottle incubation method was used as control. Consistent results were obtained using both methods， however the detection rate of established method was 3-5 times faster than control， with a detection limit （initial bacterial count） ranging from 1 CFU to 10 CFU. The larger bacterial load is， the shorter detection time would be. And it will take only 1-2 d for high-contamination vinegar samples. Results also showed that sterilization at 75-85 ℃ for 5-15 min could effectively kill the gas-producing spoilage bacteria that is recalcitrant to common preservatives within their maximum allowable concentrations. The verification was in agreement with the actual situation.ConclusionThe constructed method features fast， specific， accurate， and sensitive. This study sheds light on detection and comprehensive control of gas-producing spoilage bacteria for vinegar enterprises.

A better understanding of the spatiotemporal dynamics of species composition and biodiversity provides significant insights into the distribution patterns of biodiversity and the prediction of biodiversity fate in a global change context. However, how species and phylogenetic diversity change along elevational gradient with temporal scale in mountain ecosystems is still unknown. In this study, we used census data (2004, 2008 and 2013) of an elevational transect (elevational range 960 - 2 878 m) covering eastern and western slopes of Gaoligong Mountains, SW China, to investigate the spatiotemporal dynamics of forest arbor layer (DBH≥5 cm) species composition, species diversity and phylogenetic diversity. The results were as follows: (1) Species diversity was hump-shaped along the elevational gradient, while the phylogenetic diversity increased with increasing elevation. Clustering phylogenetic structure was observed at low elevations, and over dispersed or random structure was detected at high elevations. (2) Overall, temporal species and phylogenetic beta diversity analysis showed no significant difference among these three investigation time points. However, we found a higher clustering of phylogenetic structure along the temporal scale. (3) Spatial beta diversity showed that there was a significant loss of species at low elevations (960 - 1 381 m) on the eastern slope, where the vegetation had been disturbed or completely converted into farmland. The main lost species including Terminalia chebula, Quercus acutissima, Pistacia weinmanniifolia, Hovenia acerba and Ilex wattii. In contrast, the change in the western slope was mild at low elevations, only observing species abundance increasing, which including Cyclobalanopsis oxyodon, Symplocos chinensis, and Taiwania cryptomerioides. Therefore, we speculated that the dynamic changes in species and phylogenetic diversity of the arbor layer of subtropical evergreen broadleaf forest might be related to communities succession process and climatic change in middle and high elevations, while the communities at low elevations were seriously impacted by human activities in Gaoligong Mountains. The results deepen the understanding of the mechanisms of plant community dynamics in Gaoligong Mountains, and provide new insights to guide precise conservation strategies in the region.

Paring seawater electrolyte with zinc metal electrode has emerged as one of the most sustainable alternative solutions for offshore stationary energy storages owing to the intrinsic safety, extremely low cost, and unlimited water source. However, it remains a substantial challenge to stabilize zinc metal negative electrode in seawater electrolyte, given the presence of chloride ions and complex cations in seawater. Here, we reveal that chloride pitting initiates negative electrode corrosion and aggravates dendritic deposition, causing rapid battery failure. We then report a charge gradient negative electrode interface design that eliminates chloride-induced corrosion and enables a sustainable zinc plating/stripping performance beyond 1300 h in natural seawater electrolyte at 1 mA cm-2/1 mAh cm-2. The gradually strengthened negative charges formed via diffusion-controlled electrostatic complexation of biomass-derived polysaccharides serve to repel the unfavorable accumulation of chloride ions while simultaneously accelerating the diffusion of zinc ions. The seawater-based Zn | |NaV3O8·7H2O cell delivers an initial areal discharge capacity of 5 mAh cm-2 and operates over 500 cycles at 500 mA g-1. Seawater electrolytes provide a sustainable option for aqueous zinc batteries but challenge the stability of zinc metal electrodes. Here, authors elucidate the zinc electrode failure mechanisms and propose a charge gradient interface strategy to stabilize the zinc electrode in seawater electrolytes. [ABSTRACT FROM AUTHOR]

Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose. However, the standard NMF approach, fundamentally based on the bag-of-words model, fails to utilize the contextual information of documents and may result in a significant loss of semantics. To address this issue, we propose a new NMF scheme incorporating a regularization term based on the Wasserstein metric, which quantifies an approximation of a word-context matrix to leverage semantic information. Since the word-context matrix is typically symmetric and positive definite (SPD), the Wasserstein metric used in the regularization is related to a natural SPD manifold structure. We then build upon this manifold structure to integrate an explicit expression of the Wasserstein metric into the NMF framework. Additionally, we introduce modifications to the gradient computation to adapt three fundamental classes of numerical algorithms from ordinary NMF to tackle the Wasserstein-regularized NMF (NMF-WR) problem. To demonstrate the effectiveness of the NMF-WR model and the proposed algorithms, we conduct experiments on popular datasets, focusing on topic modeling and document clustering. The results indicate that the NMF-WR model exhibits superior performance compared to other conventional NMF models in processing text embeddings. These findings suggest that this novel NMF-WR framework not only enhances semantic representation but also underscores a commitment to the model's reliability and interpretability. [ABSTRACT FROM AUTHOR]