Aqueous biphasic systems developed with deep eutectic solvents and polymer for the efficient extraction of pigments from beverages.

Novel aqueous biphasic systems (ABSs) developed with benzyl-based quaternary ammonium salts-deep eutectic solvents (DESs) and polypropylene glycol (PPG) were herein proposed. The liquid-liquid equilibrium and the partitioning behavior of pigments in the systems were addressed. The results suggested that the shorter the carbon chain length of the DES, the easier to form two phases. The analysis of mixed samples showed that the selective separation was achieved in the ABSs, including 99.47% of tartrazine in the DES-rich phase and 98.47% of sudan III in the PPG-rich phase. Additionally, the systems were successfully applied to the extraction of pigments from the actual beverage samples with recoveries ranging from 93.43% to 102.15%. Furthermore, the study on the separation mechanism indicated that the hydrogen bonding played a significant role in the separation process. All the above results highlight the proposed DES/polymer-based ABSs have great advantages in selective and high-performance separation of pigments from beverages.

[Influence of Denitrification on Cyanobacterial Blooms Trends in Lake Taihu, China].

Denitrification is a major process in aquatic ecosystems, and it competes with cyanobacterial growth for nitrogen. However, the effect of denitrification on cyanobacterial blooms under the background of climate change remains unclear. This study explored the interaction between lake denitrification and formation of cyanobacterial blooms, using the historical water quality monitoring data of North Lake Taihu over five years from 2017 to 2021 and via incubation experiments of cyanobacteria and sediment denitrification. The monitoring data showed that algal biomass (Chla as a proxy) primarily peaked during summer and autumn. The seasonal variations in total N concentration showed a completely opposite trend than that of algal biomass, which peaked in winter and spring. Nitrate was the major component of dissolved inorganic nitrogen, and the nitrate concentration was approximately zero in summer and autumn. The total phosphorus concentration varied in the same way as the Chla concentration. The experimental results showed that Cyanobacteria did not grow when the temperature was below 20℃. In comparison, denitrification showed a significant linear relationship with temperatures between 10-25℃ (R2=0.99) and reached the maximum value of (62.98±21.36) µmol·(kg·h)-1 in Lake Taihu at 25℃. Additionally, the nitrate concentration threshold at the maximum denitrification rate was 4 mg·L-1. Cyanobacteria assimilate nitrate for growth, thereby reducing the concentration of nitrate required for denitrification. This study indicated that the advance in lake temperature warming due to climate change may result in earlier growth of cyanobacteria, thereby leading to large amounts of N being assimilated by algae before denitrification, further affecting the dynamics of cyanobacterial blooms. The present results are scientifically important for explaining the mechanism of cyanobacterial bloom rebound in Lake Taihu under the background of recent climate changes.

Mixture of personality improved spiking actor network for efficient multi-agent cooperation.

Adaptive multi-agent cooperation with especially unseen partners is becoming more challenging in multi-agent reinforcement learning (MARL) research, whereby conventional deep-learning-based algorithms suffer from the poor new-player-generalization problem, possibly caused by not considering theory-of-mind theory (ToM). Inspired by the ToM personality in cognitive psychology, where a human can easily resolve this problem by predicting others' intuitive personality first before complex actions, we propose a biologically-plausible algorithm named the mixture of personality (MoP) improved spiking actor network (SAN). The MoP module contains a determinantal point process to simulate the formation and integration of different personality types, and the SAN module contains spiking neurons for efficient reinforcement learning. The experimental results on the benchmark cooperative overcooked task showed that the proposed MoP-SAN algorithm could achieve higher performance for the paradigms with (learning) and without (generalization) unseen partners. Furthermore, ablation experiments highlighted the contribution of MoP in SAN learning, and some visualization analysis explained why the proposed algorithm is superior to some counterpart deep actor networks.

Spatial Differences and Influential Factors of Urban Carbon Emissions in China under the Target of Carbon Neutrality.

Cities are areas featuring a concentrated population and economy and are major sources of carbon emissions (CEs). The spatial differences and influential factors of urban carbon emissions (UCEs) need to be examined to reduce CEs and achieve the target of carbon neutrality. This paper selected 264 cities at the prefecture level in China from 2008 to 2018 as research objects. Their UCEs were calculated by the CE coefficient, and the spatial differences in them were analyzed using exploratory spatial data analysis (ESDA). The influential factors of UCEs were studied with Geodetector. The results are as follows: (1) The UCEs were increasing gradually. Cities with the highest CEs over the study period were located in the urban agglomerations of Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing. (2) The UCEs exhibited certain global and local spatial autocorrelations. (3) The industrial structure was the dominant factor influencing UCEs.

Outcomes of Transscleral Two-Point Fixation Versus Closed Continuous-Loop Four-Point Fixation of Intraocular Lens in Subluxated Lens Secondary to Marfan Syndrome.

INTRODUCTION: To compare the outcome of two different transscleral fixation approaches for posterior chamber intraocular lens (IOL) implantation, a two-point fixation of the Sensar (Allergan) or CZ70BD (Alcon) IOL and a four-point fixation of the Akreos Adapt (Bausch & Lomb) foldable IOL, for treatment of subluxated lenses in Marfan syndrome (MFS). METHODS: Fifty-three eyes of 33 consecutive patients with subluxated lenses secondary to MFS were studied. Eighteen patients with MFS (30 eyes) received two-point fixation of the Sensar (16 patients, 26 eyes) or CZ70BD (2 patients, 4 eyes) IOL, and 15 patients with MFS (23 eyes) received four-point fixation of the Akreos Adapt IOL. Preoperative and postoperative ophthalmologic examinations were performed. A primary outcome measure of postoperative complication was studied. RESULTS: The mean preoperative best corrected visual acuity (BCVA) in the two-point group was 0.68 ± 0.38 logarithm of the minimum angle of resolution (logMAR), and it improved to 0.30 ± 0.32 logMAR at the final follow-up (p < 0.05). The mean preoperative BCVA in the four-point group was 0.68 ± 0.45 logMAR, and it improved to 0.28 ± 0.28 logMAR at the final follow-up (p < 0.05). The BCVA results did not differ significantly between groups. The intraocular pressure was increased at the final follow-up in the two-point group (p < 0.05). Transscleral two-point fixation of IOL has relatively high incidences of pupillary capture of the IOL. CONCLUSION: The closed continuous-loop transscleral four-point fixation of the Akreos Adapt foldable IOL is more suitable than two-point fixation of a two-haptic IOL in treating subluxated lenses due to MFS.

Improving Cross-State and Cross-Subject Visual ERP-Based BCI With Temporal Modeling and Adversarial Training.

Brain-computer interface (BCI) is a useful device for people without relying on peripheral nerves and muscles. However, the performance of the event-related potential (ERP)-based BCI declines when applying it to real environments, especially in cross-state and cross-subject conditions. Here we employ temporal modeling and adversarial training to improve the visual ERP-based BCI under different mental workload states and to alleviate the problems above. The rationality of our method is that the ERP-based BCI is based on electroencephalography (EEG) signals recorded from the scalp's surface, continuously changing with time and somewhat stochastic. In this paper, we propose a hierarchical recurrent network to encode all ERP signals in each repetition at the same time and model them with a temporal manner to predict which visual event elicited an ERP. The hierarchical architecture is a simple yet effective method for organizing recurrent layers in a deep structure to model long sequence signals. Taking a cue from recent advances in adversarial training, we further applied dynamic adversarial perturbations to create adversarial examples to enhance the model performance. We conduct our experiments on one published visual ERP-based BCI task with 15 subjects and 3 different auditory workload states. The results indicate that our hierarchical method can effectively model the long sequence EEG raw data, outperform the baselines on most conditions, including cross-state and cross-subject conditions. Finally, we show how deep learning-based methods with limited EEG data can improve ERP-based BCI with adversarial training. Our code is available at https://github.com/aispeech-lab/VisBCI.

Root Endophytic Fungal Community and Carbon and Nitrogen Stable Isotope Patterns Differ among Bletilla Species (Orchidaceae).

Orchids of the genus Bletilla are well-known ornamental plants and sources of traditional medicine in Asia that rely on the symbiotic relationship with root endophytic fungi throughout their whole life cycle. However, little is known about their fungal partners, infection pattern, and pathways of carbon gain. We investigated carbon and nitrogen stable isotope patterns in different organs of three Bletilla species, identified the root endophytic fungal community composition, and determined mycorrhizal colonization rates. The three Bletilla species were comprised by a polyphyletic group which belongs to different trophic modes, such as saprotroph, pathotroph, and symbiotroph; however, the dominant species and their abundances varied among Bletilla spp. Mycorrhizal infection rates also varied among Bletilla species, with B. striata (65% ± 25%) being significantly higher than those of B. formosana (35% ± 16%) and B. ochracea (22% ± 13%). Compared with surrounding autotrophic plants, all Bletilla spp. were significantly enriched in 13C with B. striata to a significantly higher level than other two Bletilla species. Among different organs, stems had higher δ13C values, while leaves and flowers had higher δ15N and total N content values across all three species. Our results indicate that the symbiotic relationship of Bletilla and its root endophytic fungi is not strictly specific. Although mycorrhizal infection rates were highly variable, the three Bletilla species had the same infection pattern with hyphae penetrating the cortex cell by the pathway cell. Different Bletilla species have different strategies for C allocation among plant organs. These findings provide new insights into the ecological adaptation of orchids and will contribute to Bletilla germplasm conservation and sustainable utilization.

Temporal Variation in Community Composition of Root Associated Endophytic Fungi and Carbon and Nitrogen Stable Isotope Abundance in Two Bletilla Species (Orchidaceae).

Mycorrhizae are an important energy source for orchids that may replace or supplement photosynthesis. Most mature orchids rely on mycorrhizae throughout their life cycles. However, little is known about temporal variation in root endophytic fungal diversity and their trophic functions throughout whole growth periods of the orchids. In this study, the community composition of root endophytic fungi and trophic relationships between root endophytic fungi and orchids were investigated in Bletilla striata and B. ochracea at different phenological stages using stable isotope natural abundance analysis combined with molecular identification analysis. We identified 467 OTUs assigned to root-associated fungal endophytes, which belonged to 25 orders in 10 phyla. Most of these OTUs were assigned to saprotroph (143 OTUs), pathotroph-saprotroph (63 OTUs) and pathotroph-saprotroph-symbiotroph (18 OTUs) using FunGuild database. Among these OTUs, about 54 OTUs could be considered as putative species of orchid mycorrhizal fungi (OMF). For both Bletilla species, significant temporal variation was observed in the diversity of root endophytic fungi. The florescence and emergence periods had higher fungal community richness of total species and endemic species than did other periods. Both Bletilla species were dominated by Agaricomycetes and Basidiomycota fungi throughout the whole year; however, their abundances varied between two Bletilla species and among phenological stages. Meanwhile, the ranges of 13C and 15N natural abundance were also highly dynamic across all growth stages of Bletilla species. Compared with the surrounding autotrophic plants, significant 13C enrichments (ε13C) were found across all phenological stages, while significant 15N enrichment in the florescence period and strong 15N depletion during the fruiting period were found for both Bletilla species. We can deduce that both Bletilla species obtained carbon from root endophytic fungi during the whole year. Additionally, the temporal varying tendency of root endophytic fungal diversity was consistent with 13C enrichments, which was also accord with the nutritional requirement of plant.

Chloroplast Genome Analysis of Two Medicinal Coelogyne spp. (Orchidaceae) Shed Light on the Genetic Information, Comparative Genomics, and Species Identification.

Although the medicinal properties of Coelogyne spp. have been previously studied, there is little genomic information providing a valuable tool for the plant taxonomy, conservation, and utilization of this genus. This study used the next-generation MiSeq sequencing platform to characterize the chloroplast (cp) genomes of Coelogyne fimbriata and Coelogyne ovalis. The Maximum Likelihood (ML) and Bayesian (BI) methods were employed to confirm the phylogenetic position of two Coelogyne species based on the whole chloroplast genome sequences. Additionally, we developed eight new primers based on the two cp genomes' medium variable regions and evaluated the transferability to another 16 Coelogyne species. We constructed phylogenetic trees including 18 Coelogyne species and four outgroup species using the chloroplast fragments with the ML method. Our results showed that the cp genomes of C. fimbriata and C. ovalis contained a small single-copy region (18,839 and 18,851 bp, respectively) and a large single-copy region (87,606 and 87,759 bp, respectively), separated by two same-length inverted-repeat regions (26,675 bp in C. fimbriata and 26,715 bp C. ovalis, respectively). They all contained 86 protein-coding genes, 38 tRNA genes, and eight rRNA genes, revealing strong structure and gene content similarities. The phylogenetic analysis indicated a close relationship between the genera Coelogyne and Pleione. The newly developed primers revealed good transferability among the Coelogyne taxa and provided enough variable sites to distinguish C. fimbriata and C. ovalis. The two complete cp genomes and the eight new primers of Coelogyne provide new genomic data for further studies on phylogenomics, population genetics, and evolutionary history of Coelogyne taxa.