Yunnan University

In this study, an adsorbent (LCB) with rich honeycomb structure was prepared from cork waste generated from furniture factories for efficient adsorption of excess phosphorus (P) from wastewater. This adsorbent was successfully prepared in only one step, in situ precipitation method, which greatly simplified the synthesis process. Kinetic studies showed that when the initial concentration (C 0 ) of wastewater was 10 mg P L ⁻¹ , the P in the water could be completely adsorbed within 20 min. The adsorption efficiency of phosphorus was significantly improved compared to previous studies. When the C 0 of pollutant and the dosage of LCB were 20 mg P L ⁻¹ and 0.5 g L ⁻¹ , respectively, the removal rate of P exceeded 99% in the pH range of 3–10, which indicates the wide applicability of LCB. In addition, the P adsorption capacity of LCB was 82.4% of its initial value after nine adsorption–desorption cycles, indicating that LCB has a high stability and can be widely used in different water environments. Therefore, LCB is a promising material for the treatment of P-containing wastewater. Graphical Abstract

A typical Tesla thermomagnetic engine employs a solid magnetic wheel to convert thermal energy into mechanical energy, while thermomagnetic convection in ferrofluid is still challenging to observe because it is a volume convection that occurs in an enclosed space. Using a water‐based ferrofluid, we demonstrate a liquid Tesla thermomagnetic engine and report the observation of thermomagnetic convection on a free surface. Both types of fluid motions are driven by light and observed by simply placing ferrofluid on a cylindrical magnet. The surface thermomagnetic convection on the free surface is made possible by eliminating the Marangoni effect, while the spinning of the liquid wheel is achieved through the solid‐like behavior of the ferrofluid under a strong magnetic field. Increasing the magnetic field reveals a transition from simple thermomagnetic convection to a combination of the central spin of the spiky wheel surrounded by thermomagnetic convection in the outer region of the ferrofluid. We further demonstrate the coupling between multiple ferrofluid wheels through a fluid bridge. These demonstrations not only unveil the unique properties of ferrofluid but also provide a new platform for studying complex fluid dynamics and thermomagnetic convection, opening up exciting opportunities for light‐controlled fluid actuation and soft robotics. This article is protected by copyright. All rights reserved

Plant lateral organs are often elaborated through repetitive formation of developmental units, which progress robustly in predetermined patterns along their axes. Leaflets in compound leaves provide an example of such units that are generated sequentially along the longitudinal axis, in species-specific patterns. In this context, we explored the molecular mechanisms underlying an acropetal mode of leaflet initiation in chickpea pinnate compound leaf patterning. By analyzing naturally occurring mutants multi-pinnate leaf1 (mpl1) that develop higher-ordered pinnate leaves with more than forty leaflets, we show that MPL1 encoding a C2H2-zinc finger protein sculpts a morphogenetic gradient along the proximodistal axis of the early leaf primordium, thereby conferring the acropetal leaflet formation. This is achieved by defining the spatiotemporal expression pattern of CaLEAFY, a key regulator of leaflet initiation, and also perhaps by modulating the auxin signaling pathway. Our work provides novel molecular insights into the sequential progression of leaflet formation.

Anaerobic digestion can help mitigate tobacco waste (TW) pollution. Both the mono-digestion of sludge and the co-digestion of TW and sludge were considered in this study. Additionally, the effects of nano-Al2O3 and multi-walled carbon nanotubes (MWCNTs) on these two digestion systems were investigated through a 35 day digestion experiment. The microbial communities in the control reactors and the nano-Al2O3 reactors were also examined. Kinetic analysis revealed that the Rm values for the mono- and co-digestion nano-Al2O3 reactors increased by 8.88% and 13.5% compared with that of the MWCNTs reactor, respectively. Furthermore, the co-digestion system exhibited a 34.8% higher Rm than the mono-digestion system when nano-Al2O3 was added to both systems. Nano-Al2O3 was found to shorten the lag phase, while MWCNTs prolonged the lag phase time. Furthermore, 16S RNA amplicon sequencing results indicated that microbial species such as Methanobacterium sp., Hydrogenispora sp., Lutispora sp., and Ruminiclostridium sp. were more abundant in the nano-Al2O3 reactor. These results demonstrated that biogas production in co-digestion systems was improved. Moreover, nano-Al2O3 addition enhanced biogas production.

Ovarian cancer is the leading cause of death from gynecologic illnesses worldwide. High-grade serous ovarian cancer (HGSOC) is a gynecological tumor that accounts for roughly 70% of ovarian cancer deaths in women. Runt-related transcription factor 1(RUNX1) proteins were identified with overexpression in the HGSOC. However, the roles of RUNX1 in the development of HGSOC are poorly understood. In this study, combined with whole-transcriptome analysis and multiple research methods, RUNX1 was identified as vital in developing HGSOC. RUNX1 knockdown inhibits the physiological function of ovarian cancer cells and regulates apoptosis through the FOXO1-Bcl2 axis. Down-regulated RUNX1 impairs EMT function through the EGFR-AKT-STAT3 axis signaling. In addition, RUNX1 knockdown can significantly increase the sensitivity to clinical drug therapy for ovarian cancer. It is strongly suggested that RUNX1 work as a potential diagnostic and therapeutic target for HGSOC patients with better prognoses and treatment options. It is possible to generate novel potential targeted therapy strategies and translational applications for serous ovarian carcinoma patients with better clinical outcomes.

A 1,6-conjugate addition reaction of β,β-disubstituted N-tert-butanesulfinyl metalloenamines, generated via stereospecific α-deprotonation of enantioenriched α,α-disubstituted ketimines or deprotonation of NH in geometry-defined enesulfinamides, with isatin-derived para-quinone methides was developed to build vicinal quaternary stereocenters with high stereocontrol. The resulting 3,3-disubstituted oxindoles contain a less-accessible acyclic quaternary stereogenic carbon substituted with two sterically and electronically similar groups at the α-position of the imino group. This protocol constitutes a rare example of the stereoselective construction of vicinal quaternary stereocenters via the conjugate addition of acyclic enolates/aza-enolates bearing two similar β-substituents.

The development of environmentally sustainable and highly efficient technologies for ammonia production is crucial for the future advancement of carbon‐neutral energy systems. The nitrite reduction reaction (NO 2 RR) for generating NH 3 is a promising alternative to the low‐efficiency nitrogen reduction reaction (NRR), owing to the low N=O bond energy and high solubility of nitrite. In this study, we designed a highly efficient dual‐atom catalyst with Fe‐Cu atomic pair sites (termed FeCu DAC), and the as‐developed FeCu DAC was able to afford a remarkable NH 3 yield of 24,526 μg h ⁻¹ mg cat. ⁻¹ at −0.6 V, with a Faradaic Efficiency (FE) for NH 3 production of 99.88 %. The FeCu DAC also exhibited exceptional catalytic activity and selectivity in a Zn‐NO 2 battery, achieving a record‐breaking power density of 23.6 mW cm ⁻² and maximum NH 3 FE of 92.23 % at 20 mA cm ⁻² . Theoretical simulation demonstrated that the incorporation of the Cu atom changed the energy of the Fe 3d orbital and lowered the energy barrier, thereby accelerating the NO 2 RR. This study not only demonstrates the potential of galvanic nitrite‐based cells for expanding the field of Zn‐based batteries, but also provides fundamental interpretation for the synergistic effect in highly dispersed dual‐atom catalysts.

Lithium‐sulfur (Li‐S) batteries stand out for their high theoretical specific capacity, cost‐effectiveness. However, the practical implementation of Li‐S batteries is hindered by issues such as the shuttle effect, tardy redox kinetics, and dendrite growth. Herein, an appealingly designed covalent organic framework (COF) with bi‐functional active sites of cyanide groups and polysulfide chains (COF‐CN‐S) is developed as cooperative functional promoters to simultaneously address dendrites and shuttle effect issues. Combining in‐situ techniques and theoretical calculations, it can be demonstrated that the unique chemical architecture of COF‐CN‐S is capable of performing the following functions: (1) The COF‐CN‐S delivers significantly enhanced Li ⁺ transport capability due to abundant ion‐hopping sites (cyano‐groups); (2) it functions as a selective ion sieve by regulating the dynamic behavior of polysulfide anions and Li ⁺ , thus inhibiting shuttle effect and dendrite growth; (3) by acting as a redox mediator, the COF‐CN‐S can effectively control the electrochemical behavior of polysulfides and enhance their conversion kinetics. Based on the above advantages, the COF‐CN‐S endows Li‐S batteries with excellent performance. This study highlights the significance of interface modification and offers novel insights into the rational design of organic materials in Li‐S realm. This article is protected by copyright. All rights reserved

The combination of biochar and bacteria is a promising strategy for the remediation of Cd-polluted soils. However, the synergistic mechanisms of biochar and bacteria for Cd immobilization remain unclear. In this study, the experiments were conducted to evaluate the effects of the combination of biochar and Pseudomonas sp. AN-B15, on Cd immobilization, soil enzyme activity, and soil microbiome. The results showed that biochar could directly reduce the motility of Cd through adsorption and formation of CdCO3 precipitates, thereby protecting bacteria from Cd toxicity in the solution. In addition, bacterial growth further induces the formation of CdCO3 and CdS and enhances Cd adsorption by bacterial cells, resulting in a higher Cd removal rate. Thus, bacterial inoculation significantly enhances Cd removal in the presence of biochar in the solution. Moreover, soil incubation experiments showed that bacteria-loaded biochar significantly reduced soil exchangeable Cd in comparison with other treatments by impacting soil microbiome. In particular, bacteria-loaded biochar increased the relative abundance of Bacillus, Lysobacter, and Pontibacter, causing an increase in pH, urease, and arylsulfatase, thereby passivating soil exchangeable Cd and improving soil environmental quality in the natural alkaline Cd-contaminated soil. Overall, this study provides a systematic understanding of the synergistic mechanisms of biochar and bacteria for Cd immobilization in soil and new insights into the selection of functional strain for the efficient remediation of the contaminated environments by bacterial biochar composite.

Background: Estimating tobacco leaf yield is a crucial task. The number of leaves is directly related to yield. Therefore, it is important to achieve intelligent and rapid high-throughput statistical counting of field tobacco leaves. Unfortunately, the current method of counting the number of tobacco leaves is expensive, imprecise, and inefficient. It heavily relies on manual labor and also faces challenges of mutual shading among the field tobacco plants during their growth and maturity stage, as well as complex environmental background information. This study proposes an efficient method for counting the number of tobacco leaves in a large field based on unmanned aerial vehicle (UAV) image data. First, a UAV is used to obtain high-throughput vertical orthoimages of field tobacco plants to count the leaves of the tobacco plants. The tobacco plant recognition model is then used for plant detection and segmentation to create a dataset of images of individual tobacco plants. Finally, the improved algorithm YOLOv8 with Squeeze-and-Excitation (SE) and bidirectional feature pyramid network (BiFPN) and GhostNet (YOSBG) algorithm is used to detect and count tobacco leaves on individual tobacco plants. Results: Experimental results show YOSBG achieved an average precision (AP) value of 93.6% for the individual tobacco plant dataset with a model parameter (Param) size of only 2.5 million (M). Compared to the YOLOv8n algorithm, the F1 (F1-score) of the improved algorithm increased by 1.7% and the AP value increased by 2%, while the model Param size was reduced by 16.7%. In practical application discovery, the occurrence of false detections and missed detections is almost minimal. In addition, the effectiveness and superiority of this method compared to other popular object detection algorithms have been confirmed. Conclusions: This article presents a novel method for high-throughput counting of tobacco leaves based on UAV image data for the first time, which has a significant reference value. It solves the problem of missing data in individual tobacco datasets, significantly reduces labor costs, and has a great impact on the advancement of modern smart tobacco agriculture.

In this article, the long-time behaviors of weak solutions for the 2D non-autonomous magneto-viscoelastic flows are considered. Unlike the results established by Liu and Liu (Politeh Univ Buchar Sci Bull Ser A Appl Math Phys 81(4):155–166, 2019), utilizing the method of \(\ell \)-trajectories introduced by Málek and Pražák (J Differ Equ 181(2):243–279, 2002), we first justify the existence of finite-dimensional pullback attractors for the process \(\{L(t,\tau )\}_{t\ge \tau }\) in the \(\ell \)-trajectories space \(X_{\ell }\). Then we obtain the corresponding finite-dimensional pullback attractors for the process \(\{U(t,\tau )\}_{t\ge \tau }\) in the original phase space \(\mathbb {H}\).

In potato, stolon swelling is a complex and highly regulated process, and much more work is needed to fully understand the underlying mechanisms. We identified a novel tuber‐specific basic helix–loop–helix (bHLH) transcription factor, StbHLH93 , based on the high‐resolution transcriptome of potato tuber development. StbHLH93 is predominantly expressed in the subapical and perimedullary region of the stolon and developing tubers. Knockdown of StbHLH93 significantly decreased tuber number and size, resulting from suppression of stolon swelling. Furthermore, we found that StbHLH93 directly binds to the plastid protein import system gene TIC56 promoter, activates its expression, and is involved in proplastid‐to‐amyloplast development during the stolon‐to‐tuber transition. Knockdown of the target TIC56 gene resulted in similarly problematic amyloplast biogenesis and tuberization. Taken together, StbHLH93 functions in the differentiation of proplastids to regulate stolon swelling. This study highlights the critical role of proplastid‐to‐amyloplast interconversion during potato tuberization.

Assessing river health by combining different biological taxa can provide more reliable results. However, there is still a lack of in-depth research on how different taxa respond to river health and what kind of supplementary ecological data might be provided. In this study, we set up 31 survey sections in the main streams and major tributaries of the Babian River to investigate the conditions of river habitat, macroinvertebrates, phytoplankton, water quality, riparian zone, and societal value. Indexes of biotic integrity of macroinvertebrates and phytoplankton (B-IBI and P-IBI) were constructed, and assessments of biotic integrity, water quality, riparian zone, and societal value were conducted. The responses of macroinvertebrates and phytoplankton to river health were analyzed across the Babian River basin, as well as those in rivers with-various substrates, river widths, elevations, and flow velocities. The results showed that 1) both B-IBI and P-IBI could distinguish between reference and impaired sites, and could be used to assess the target watershed, but their assessment results were both sub-healthy. 2) Both B-IBI and P-IBI accurately reflected the overall water quality (comprehensive pollution index, CPI) and TN condition, and partially reflected the status of the riparian zone, but neither one was able to reflect the results of the societal value survey. 3) The applicability and assessment effectiveness of B-IBI and P-IBI in different habitats revealed obvious differences: phytoplankton more comprehensively reflected the river health than macroinvertebrates in pebble and sediment-dominated rivers, wider and narrower rivers, high-elevation rivers, and low-velocity rivers. However, phytoplankton were not able to indicate NH3-N and CODMn conditions across the whole watershed or in different habitats. In contrast, macroinvertebrates responded better to CPI, NH3-N, and CODMn throughout the entire watershed, as well as in rivers that were narrower, pebble-dominated, at low-elevation, and with high-velocity. In summary, macroinvertebrates could effectively supplement the insufficiency of phytoplankton in the assessment of organic pollution and oxygen-consuming pollutants due to their sensitivity to NH3-N and CODMn. The findings will provide data and theoretical support for selecting biological taxa and constructing multimetric indices in river health assessment.

Several new uniqueness conditions of the stationary probability matrix of transition probability tensors arising from higher-order multivariate Markov chains are given by using contract mapping principle, the technique of inequality scaling and parameter method. It is proved that the new results are better than the one provided by Li et al. [Comput. Math. Appl., 2019, 78(3): 1008–1025]. As applications, a new convergence condition and an error bound for the power method to calculate the stationary probability matrix are given. Meanwhile, a perturbation bound for stationary probability matrix is obtained.

Unmanned Aerial Vehicles (UAVs)-assisted Multi-access Edge Computing (MEC) has emerged as a promising solution in B5G/6G networks. The high flexibility and seamless connectivity of UAVs make them well-suited for providing enhanced communications coverage and efficient computing support. Particularly in situations where ground facilities may be compromised or communication is unreliable. In this paper, we study joint dynamic service switching and resource allocation for multiple UAVs in MEC network. We consider the heterogeneity of tasks and UAVs and model the dynamic service process of UAVs as a sequential decision problem based on the Markovian decision process. To enable dynamic and intelligent UAV service, we first propose a centralized dynamic service algorithm DDBC based on deep reinforcement learning. However, given the training difficulties of the centralized algorithm, we propose a more promising distributed learning algorithm FLBF, which combines federated learning. We conduct extensive simulations to evaluate the effectiveness and advantages of the proposed algorithms. Our results show that both DDBC and FLBF can improve the model convergence speed by 50%, and reduce the system cost by 12.30% to 35.72% compared to comparative algorithms. Furthermore, simulations indicate that FLBF is well-suited for training models in UAV-assisted MEC networks.

Identifying key spreaders in a network is one of the fundamental problems in the field of complex network research, and accurately identifying influential propagators in a network holds significant practical implications. In recent years, numerous effective methods have been proposed and widely applied. However, many of these methods still have certain limitations. For instance, some methods rely solely on the global position information of nodes to assess their propagation influence, disregarding local node information. Additionally, certain methods do not consider clustering coefficients, which are essential attributes of nodes. Inspired by the quality formula, this paper introduces a method called SNC (Structure-based Node Centrality) that takes into account the neighborhood information of nodes. SNC measures the propagation power of nodes based on first and second-order neighborhood degrees, local clustering coefficients, structural hole constraints, and other information, resulting in higher accuracy. A series of pertinent experiments conducted on twelve real-world datasets demonstrate that, in terms of accuracy, SNC outperforms methods like CycleRatio and KSGC. Additionally, SNC demonstrates heightened monotonicity, enabling it to distinguish subtle differences between nodes. Furthermore, when it comes to identifying the most influential Top-k nodes, SNC also displays superior capabilities compared to the aforementioned methods. Finally, we conduct a detailed analysis of SNC and discuss its advantages and limitations.

Humans have long been fascinated by the mysteries surrounding fish migrations, and addressing these complex behaviors often requires large data sets. Biogeochemical tags, including trace elements and stable isotopes, are the most accessible biomarkers for tracking fish migrations. However, access to standardized biogeochemical tag data is rarely available for migratory fish, which limits our understanding of the evolutionary origins, drivers, timing, and corridors of migration. This precludes the development of conservation strategies and the implementation of management actions. Here, we present MFishBT, a global, open-access database of Migratory Fish's Biogeochemical Tags. As of April 2023, the MFishBT contains biogeochemical records from 1305 studies, of which 53% used element-to-calcium (E/Ca) ratios, 34% used isotopic ratios, and 13% used both. The database covers 17,413 field sampling locations (inland 47% vs. marine 53%) around the globe, comprising 490 migratory fish species of four classes, 44 orders/suborders, and 137 families. Seventy-seven trace elements and 11 isotope systems were measured across various fish biological archives, including otoliths, scales, eye lenses, and vertebrae. E/Ca ratios were examined more frequently than isotopic ratios, led by Sr/Ca, Mg/Ca, Ba/Ca, and 87Sr/86Sr, δ13C, and δ18O, respectively. The MFishBT compiles 27,030, 16,222, and 2,481,714 records with biogeochemical data detected in the core, edge, and core-to-edge transects for biological archives of migratory fish, respectively. This is the most globally comprehensive open-access database on biogeochemical tags in migratory fish to date, which can serve a variety of needs in scientific research, conservation, and management. We encourage researchers to add more data sets to this database in the future. This database is released for non-commercial use only. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.