Publications

Melatonin has recently been detected in fermented beverages and foods, in which microorganism metabolism is highly important. The existing literature knowledge discusses the direction for future studies in this review. Evidence shows that many species of microorganisms could synthesize melatonin. However, the actual concentrations of melatonin in fermented foods and beverages range from picograms per milliliter to nanograms per milliliter. Different types of microorganisms, different raw materials, different culture environments, the presence or absence of precursors, high or low alcohol content, and different detection methods are all possible reasons for the huge difference of melatonin levels. Thus far, there have been relatively few studies on the melatonin synthesis pathway microorganisms. Thus, referring to the synthetic pathway of plants and animals, the putative melatonin biosynthesis pathway of microorganisms is presented. It will be significant to discuss whether all species of microorganisms have the capacity to synthesize melatonin and what the biological functions of melatonin are in microorganisms. Melatonin plays a lot of important roles in microorganisms, particularly in enhancing the tolerance of environment stress. Also, the loss of melatonin concentration in commercially available fermented foods and beverages is a ubiquitous trend, and how to solve this problem is a new field to be further explored.

Abstract Heavy metals are of particular concern in grape and wine processing, especially copper. The sources of copper are diverse, including vineyard soil, copper‐containing pesticides on the fruit surface, copper wine‐making equipment, and exogenous addition in winemaking. Copper has potential risks to human nerves, metabolism, and others. It can inhibit yeast growth, delay fermentation, and also mediate oxidation reactions, which has a huge impact on the nutritional quality and sensory quality of fresh wine and aged wine. It is therefore crucial to detect, quantify, and remove copper from grapes and wine. However, the copper situations in the wine industries of various countries are complicated and diverse, and the existing forms of copper are quite different, which makes the research challenging. This review summarizes and analyzes the existence and influence of copper in the wine industry by analyzing the sources of, the current situation regarding, and the detection and removal methods for copper in wine. With the study, a better understanding of copper's impact on wine production will be gained, facilitating further control of copper in wine and helping the wine industry grow.

We evaluated the role of syntrophic acetate oxidation coupled with hydrogenotrophic methanogens in three different methanogenic consortia.Three methanogenic hexadecane degrading consortia named Y15, M82 and SK were taken from the same oily sludge of Shengli oil-field and enriched. They were incubated at 15, 35 and 55 °C, respectively. The consortia amended with acetate and inhibitors of NH4Cl or CH3F were further transferred and incubated at corresponding temperatures. The cultures atlate logarithmic phase were collected for terminal restriction fragment length polymorphism (T-RFLP) combined with cloning and phylogenetic analysis of 16S rRNA gene fragments.Gas chromatograph analysis showed that all of the consortia could grow and produce methane, but the lag phase was delayed and the growth rate was retarded in the cultures amended with inhibitor. Combination analysis of T-RFLP and clone library revealed the predominance of obligate aceticlastic Methanosaeta in the acetate cultures of Y15, M82 and SK. Under the mesophilic and thermophilic conditions, after add inginhibitor the relative abundance of aceticlastic methanogen decreased but hydrogenotrophic methanogen increased.Syntrophic acetate oxidation during methanogenic degradation of petroleum hydrocarbons occurs under mesophilic and thermophilic conditions, although the situation at low temperature seems uncertain.

This paper addresses the trade-off between Accuracy and Transparency for deep learning applied to sports analytics. Neural nets achieve great predictive accuracy through deep learning, and are popular in sports analytics. But it is hard to interpret a neural net model and harder still to extract actionable insights from the knowledge implicit in it. Therefore, we built a simple and transparent model that mimics the output of the original deep learning model and represents the learned knowledge in an explicit interpretable way. Our mimic model is a linear model tree, which combines a collection of linear models with a regression-tree structure. The tree version of a neural network achieves high fidelity, explains itself, and produces insights for expert stakeholders such as athletes and coaches. We propose and compare several scalable model tree learning heuristics to address the computational challenge from datasets with millions of data points.

With the increasing penetration of renewable energy in power systems, fluctuation of renewable energy power plants has great influence on stability of the system, and renewable power curtailment is also becoming more and more serious due to the insufficient consumptive ability of local power grid. In order to maximize the utilization of renewable energy, this paper focuses on the generation scheduling optimization for a wind-solar-thermal hybrid system considering that the produced energy will be transmitted over a long distance to satisfy the demands of the receiving end system through ultra-high voltage (UHV) transmission lines. Accordingly, a bilevel optimization based on a non-cooperative game method is proposed to maximize the profit of power plants in the hybrid system. Users in the receiving end system are at the lower level of the bilevel programming, and power plants in the transmitting end system are at the upper level. Competitive behavior among power plants is formulated as a non-cooperative game and the profit of power plant is scheduled by adjusting generation and bidding strategies in both day-ahead markets and intraday markets. In addition, generation cost, wheeling cost, and carbon emissions are all considered in the non-cooperative game model. Moreover, a distributed algorithm is presented to obtain the generalized Nash equilibrium solution, which realizes the optimization in terms of maximizing profit. Finally, several simulations are implemented and analyzed to verify the effectiveness of the proposed optimization method.

Apparent molar volumes (VΦ) of mannitol in aqueous solutions of 1-propanol and 2-propanol were obtained from densities of the ternary solutions, accurately measured with a quartz vibrating-tube den- simeter at 298.15 K. These data have been used to deduce limiting partial molar volumes of mannitol ( Φ V � ) and correspondingly limiting partial molar volumes of transfer ( trs Φ V ∆ � ) from water to different alcohol so- lutions at different concentrations. The results indicated that influence of 1-propanol on the volumetric prop- erty of mannitol in aqueous solution was stronger than that of 2-propanol. The changes of the volumetric properties were discussed in the light of interaction between solute and solvent and the different locations of hydroxyl group in propanol isomers. Keywords limiting partial molar volume; mannitol; 1-propanol; 2-propanol