Table_1_Logistics strategies of food delivery O2O supply chain with anti-food waste regulation.pdf

With the ever-growing popularity of food deliver, more and more consumers are embracing this convenience as part of their lifestyle. However, the issue of food waste created by the food deliver industry has become a pressing concern in society. This paper aims to examine the link between food waste and food delivery services, and investigate the effects of anti-food waste regulations on the generation of food waste and the choice of logistics strategies in an Online-to-Offline (O2O) supply chain. Using game-theoretical approach, we focus on two prominent logistics strategies—the restaurant-free self-logistics strategy (RF strategy) and the platform-charge logistics strategy (PC strategy). Our research results show that anti-food waste regulation can effectively reduce food waste in food delivery service under the PC logistics strategy. The choice of logistics strategy is constrained by the online market potential, the relative logistics costs of platform logistics, and anti-food waste regulations. If the anti-food waste regulation is strict, as long as the size of the food delivery market and the relative logistics costs of platform logistics are not simultaneously small, the RF strategy will be the equilibrium strategy, whereas the supply chain members should choose the PC strategy. The study thus offers useful inferences for theory and practice.</p

Application of Molecular Simulation Methods in Food Science: Status and Prospects

Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods

Concentration-Dependent Enrichment Identifies Primary Protein Targets of Multitarget Bioactive Molecules

Multitarget bioactive molecules (MBMs) are of increasing importance in drug discovery as they could produce high efficacy and a low chance of resistance. Several advanced approaches of quantitative proteomics were developed to accurately identify the protein targets of MBMs, but little study has been carried out in a sequential manner to identify primary protein targets (PPTs) of MBMs. This set of proteins will first interact with MBMs in the temporal order and play an important role in the mode of action of MBMs, especially when MBMs are at low concentrations. Herein, we describe a valuable observation that the result of the enrichment process is highly dependent on concentrations of the probe and the proteome. Interestingly, high concentrations of probe and low concentrations of incubated proteome will readily miss the hyper-reactive protein targets and thereby increase the probability of rendering PPTs with false-negative results, while low concentrations of probe and high concentrations of incubated proteome more than likely will capture the PPTs. Based on this enlightening observation, we developed a proof-of-concept approach to identify the PPTs of iodoacetamide, a thiol-reactive MBM. This study will deepen our understanding of the enrichment process and improve the accuracy of pull-down-guided target identification

High-Performance Biomass-Based Flexible Solid-State Supercapacitor Constructed of Pressure-Sensitive Lignin-Based and Cellulose Hydrogels

Employing renewable, earth-abundant, environmentally friendly, low-cost natural materials to design flexible supercapacitors (FSCs) as energy storage devices in wearable/portable electronics represents the global perspective to build sustainable and green society. Chemically stable and flexible cellulose and electroactive lignin have been employed to construct a biomass-based FSC for the first time. The FSC was assembled using lignosulfonate/single-walled carbon nanotube_HNO₃ (Lig/SWCNT_HNO₃) pressure-sensitive hydrogels as electrodes and cellulose hydrogels as an electrolyte separator. The assembled biomass-based FSC shows high specific capacitance (292 F g^–1 at a current density of 0.5 A g^–1), excellent rate capability, and an outstanding energy density of 17.1 W h kg^–1 at a power density of 324 W kg^–1. Remarkably, the FSC presents outstanding electrochemical stability even suffering 1000 bending cycles. Such excellent flexibility, stability, and electrochemical performance enable the designed biomass-based FSCs as prominent candidates in applications of wearable electronic devices

Concentration-Dependent Enrichment Identifies Primary Protein Targets of Multitarget Bioactive Molecules

Multitarget bioactive molecules (MBMs) are of increasing importance in drug discovery as they could produce high efficacy and a low chance of resistance. Several advanced approaches of quantitative proteomics were developed to accurately identify the protein targets of MBMs, but little study has been carried out in a sequential manner to identify primary protein targets (PPTs) of MBMs. This set of proteins will first interact with MBMs in the temporal order and play an important role in the mode of action of MBMs, especially when MBMs are at low concentrations. Herein, we describe a valuable observation that the result of the enrichment process is highly dependent on concentrations of the probe and the proteome. Interestingly, high concentrations of probe and low concentrations of incubated proteome will readily miss the hyper-reactive protein targets and thereby increase the probability of rendering PPTs with false-negative results, while low concentrations of probe and high concentrations of incubated proteome more than likely will capture the PPTs. Based on this enlightening observation, we developed a proof-of-concept approach to identify the PPTs of iodoacetamide, a thiol-reactive MBM. This study will deepen our understanding of the enrichment process and improve the accuracy of pull-down-guided target identification

Bacterial diversity and functional characteristics of natural rainwater lakes in Saihanba artificial forest farm as revealed by 16S rRNA sequencing

The Saihanba Mechanical Forest is an artificial national forest park with a forest-steppe landscape. The flora and fauna have been extensively studied, but a comprehensive understanding of the bacterial community composition and structure of the natural rainwater lakes present in the area has rarely been reported. In this study, the structure and functional characteristics of bacterial communities in lake sediments and water samples in the Saihanba artificial forest were investigated using 16s rRNA high-throughput sequencing. Microbial diversity analyses revealed that Proteobacteria, Acidobacteria, Bacteroidota and Verrucomicrobiota microbiota dominated. The abundance of Proteobacteria and Actinobacteriota was significantly higher (p < .05) in water samples compared to sediment samples. PICRUSt2 functional analysis predicted genes associated with the degradation of xenobiotics and the execution of essential metabolic processes. Here, we report differences in the composition of native bacterial communities in sediments and water under the Saihanba artificial forest and make functional gene predictions. This study provides a reference for further exploring the structure and functional characteristics of microbial communities in water samples and sediment environments of lakes under planted forests.</p

Physical and Antimicrobial Properties of Peppermint Oil Nanoemulsions

The mixture of peppermint oil (PO) with medium-chain triacylglycerol was emulsified in water and stabilized with a food-grade biopolymer, modified starch, to form PO nanoemulsions. The effects of emulsifying conditions including homogenization pressure, the number of processing cycles, and oil loading on the mean diameters and viscosities of nanoemulsions were characterized by dynamic light scattering, optical microscopy, and rheological measurements. The formulated PO nanoemulsions with mean diameters normally <200 nm showed high stability over at least 30 days of storage time. Their antimicrobial properties related to those of PO have also been evaluated by two assays, the minimum inhibitory concentration (MIC) and time-kill dynamic processes, against two Gram-positive bacterial strains of Listeria monocytogenes Scott A and Staphylococcus aureus ATCC 25923. Compared with bulk PO, the PO nanoemulsions showed prolonged antibacterial activities. The results suggest that the nanoemulsion technology can provide novel applications of essential oils in extending the shelf life of aqueous food products

Supplementary document for Long-term monitoring chlorophyll-a concentration using HJ-1 A/B imagery and machine learning algorithms in typical lakes, a cold semi-arid region - 6943993.pdf

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