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Dinoflagellates and heterotrophic bacteria are two major micro-organism groups within marine ecosystems. Their coexistence has led to a co-evolutionary relationship characterized by intricate interactions that not only alter their individual behaviors but also exert a significant influence on the broader biogeochemical cycles. Our review commenced with an analysis of bacterial populations, both free-living and adherent to dinoflagellate surfaces. Members of Alphaproteobacteria, Gammaproteobacteria, and the Cytophaga-Flavobacterium-Bacteroides group are repeatedly found to be associated with dinoflagellates, with representation by relatively few genera, such as Methylophaga , Marinobacter , and Alteromonas . These bacterial taxa engage with dinoflagellates in a limited capacity, involving nutrient exchange, the secretion of pathogenic substances, or participation in chemical production. Furthermore, the genomic evolution of dinoflagellates has been profoundly impacted by the horizontal gene transfer from bacteria. The integration of bacterial genes into dinoflagellates has been instrumental in defining their biological characteristics and nutritional strategies. This review aims to elucidate the nuanced interactions between dinoflagellates and their associated bacteria, offering a detailed perspective on their complex relationship.

In recent years, small molecular acceptors (SMAs) have extensively promoted the progress of organic solar cells (OSCs). The facile tuning of chemical structures affords SMAs excellent tunability of their absorption and energy levels, and it gives SMA-based OSCs slight energy loss, enabling OSCs to achieve high power conversion efficiencies (e.g., >18%). However, SMAs always suffer complicated chemical structures requiring multiple-step synthesis and cumbersome purification, which is unfavorable to the large-scale production of SMAs and OSC devices for industrialization. Direct arylation coupling reaction via aromatic C-H bonds activation allows for the synthesis of SMAs under mild conditions, and it simultaneously reduces synthetic steps, synthetic difficulty, and toxic by-products. This review provides an overview of the progress of SMA synthesis through direct arylation and summarizes the typical reaction conditions to highlight the field's challenges. Significantly, the impacts of direct arylation conditions on reaction activity and reaction yield of the different reactants' structures are discussed and highlighted. This review gives a comprehensive view of preparing SMAs by direct arylation reactions to cause attention to the facile and low-cost synthesis of photovoltaic materials for OSCs.

Owing to their unique chemical properties, α-alkylidene succinimides generally act as versatile synthons in organic synthesis. Compared with well-established annulations, nucleophilic alkylations of α-alkylidene succinimides are very limited. Accordingly, an organocatalytic allylic alkylation of α-benzylidene succinimides with Morita-Baylis-Hillman (MBH) carbonates was established. In the presence of a chiral phosphine catalyst, α-benzylidene succinimides reacted smoothly with MBH carbonates under mild conditions to furnish a series of optical active succinimides in high yields and enantioselectivities. Different from the reported results, the organocatalytic enantioselective construction of pyrrolidine-2,5-dione frameworks bearing contiguous chiral tertiary carbon centers was achieved via this synthetic strategy. Scaling up the reaction indicated that it is a practical strategy for the organocatalytic enantioselective alkylation of α-alkylidene succinimides. A possible reaction mechanism was also proposed.

Extreme disasters, defined as low-probability-high-consequences events, are often due to cascading effects combined to amplifying environmental factors. While such a risk complexity is commonly addressed by the modeling of site-specific multi-risk scenarios, there exists no harmonized approach that considers the full space of possibilities, based on the general relationships between the environment and the perils that populate it. In this article, I define the concept of a digital template for multi-risk R&D and prototyping in the Generic Multi-Risk (GenMR) framework. This digital template consists of a virtual natural environment where different perils may occur. They are geological (earthquakes, landslides, volcanic eruptions), hydrological (river floods, storm surges), meteorological (windstorms, heavy rains), and extraterrestrial (asteroid impacts). Both geological and hydrological perils depend on the characteristics of the natural environment, here defined by two environmental layers : topography and soil. Environmental objects , which alter the layers, are also defined. They are here geomorphic structures linked to some peril source characteristics. Hazard intensity footprints are then generated for primary, secondary, and tertiary perils. The role of the natural environment on intensity footprints and event cascading is emphasized, one example being the generation of a "quake lake". Future developments, à la SimCity , are finally discussed.

The literature on probabilistic hazard and risk assessment shows a rich and wide variety of modeling strategies tailored to specific perils. On one hand, catastrophe (CAT) modeling, a recent professional and scientific discipline, provides a general structure for the quantification of natural (e.g., geological, hydrological, meteorological) and man-made (e.g., terrorist, cyber) catastrophes. On the other hand, peril characteristics and related processes have yet to be categorized and harmonized to enable adequate comparison, limit silo effects, and simplify the implementation of emerging risks. We reviewed the literature for more than 20 perils from the natural, technological, and socio-economic systems to categorize them by following the CAT modeling hazard pipeline: (1) event source → (2) size distribution → (3) intensity footprint. We defined the following categorizations, which are applicable to any type of peril, specifically: (1) point/line/area/track/diffuse source, (2) discrete event/continuous flow, and (3) spatial diffusion (static)/threshold (passive)/sustained propagation (dynamic). We then harmonized the various hazard processes using energy as the common metric, noting that the hazard pipeline's underlying physical process consists of some energy being transferred from an energy stock (the source), via an event, to the environment (the footprint).

Natural phosphate (NP) and synthetic fluorapatite phosphate (SFAP) were proposed as stable, inexpensive, readily available and recyclable catalysts for the condensation of 1,2-diamines with 1,2-dicarbonyls in methanol to afford quinoxaline at room temperature. NP provided as high as 92-99% yield for quinoxalines in short reaction times (i.e., 1-45 min), while SFAP created quinoxalines with 87-97% yield in 60-120 min. From the chemical analyses, X-ray fluoresecency, X-ray diffraction, energy dispersive X-ray and Fourier-transform infrared spectroscopy methods, two main phases (CaO, P 2 O 5 ) appeared in NP together with other low content phases (SiO 2 , Fe 2 O 3 ). Compared to other phases, apatite (CaO and P 2 O 5 as Ca10(PO 4 ) 6 ) played a major role in the catalytic activity of NP. SFAP with similar Ca/P atomic ratio showed a relatively lower catalytic activity than NP for the condensation of 1,2-diamine with 1,2-dicarbonyl in methanol at ambient temperature. To investigate the recyclability of catalysts, the surface properties of NP and 6-recycled NP were investigated using scanning electron microscopy, energy dispersive X-ray and Brunauer-Emmett-Teller and Barrett-Joyner-Halenda methods. Some differences were observed in NP and 6-recycled NP's particle size, surface area, the volume and size of pores, and the content of elements; nevertheless, the use-reuse process did not noticeably change the catalytic property of NP.

The prediction of human mobility can facilitate resolving many kinds of urban problems, such as reducing traffic congestion, and promote commercial activities, such as targeted advertising. However, the requisite personal GPS data face privacy issues. Related organizations can only collect limited data and they experience difficulties in sharing them. These data are in "isolated islands" and cannot collectively contribute to improving the performance of applications. Thus, the method of federated learning (FL) can be adopted, in which multiple entities collaborate to train a collective model with their raw data stored locally and, therefore, not exchanged or transferred. However, to predict long-term human mobility, the performance and practicality would be impaired if only some models were simply combined with FL, due to the irregularity and complexity of long-term mobility data. Therefore, we explored the optimized construction method based on the high-efficient gradient-boosting decision tree (GBDT) model with FL and propose the novel federated voting (FedVoting) mechanism, which aggregates the ensemble of differential privacy (DP)-protected GBDTs by the multiple training, cross-validation and voting processes to generate the optimal model and can achieve both good performance and privacy protection. The experiments show the great accuracy in long-term predictions of special event attendance and point-of-interest visits. Compared with training the model independently for each silo (organization) and state-of-art baselines, the FedVoting method achieves a significant accuracy improvement, almost comparable to the centralized training, at a negligible expense of privacy exposure.

Lead detection for biological environments, aqueous resources, and medicinal compounds, rely mainly on either utilizing bulky lab equipment such as ICP-OES or ready-made sensors, which are based on colorimetry with some limitations including selectivity and low interference. Remote, rapid and efficient detection of heavy metals in aqueous solutions at ppm and sub-ppm levels have faced significant challenges that requires novel compounds with such ability. Here, a UiO-66(Zr) metal-organic framework (MOF) functionalized with SO3H group (SO3H-UiO-66(Zr)) is deposited on the end-face of an optical fiber to detect lead cations (Pb2+) in water at 25.2, 43.5 and 64.0 ppm levels. The SO3H-UiO-66(Zr) system provides a Fabry-Perot sensor by which the lead ions are detected rapidly (milliseconds) at 25.2 ppm aqueous solution reflecting in the wavelength shifts in interference spectrum. The proposed removal mechanism is based on the adsorption of [Pb(OH2)6]2+ in water on SO3H-UiO-66(Zr) due to a strong affinity between functionalized MOF and lead. This is the first work that advances a multi-purpose optical fiber-coated functional MOF as an on-site remote chemical sensor for rapid detection of lead cations at extremely low concentrations in an aqueous system.

Leaf senescence is the final stage of leaf development. It is accompanied by the remobilization of nutrients from senescent leaves to developing organs. The occurrence of senescence is the consequence of integrating intrinsic and environmental signals. DNA damage triggered by stresses has been regarded as one of the reasons for senescence. To prevent DNA damage, cells have evolved elaborate DNA repair machinery. The ataxia telangiectasia mutated (ATM) functions as the chief transducer of the double-strand breaks (DSBs) signal. Our previous study suggests that ATM functions in lifespan regulation in Arabidopsis . However, ATM regulatory mechanism on plant longevity remains unclear. Here, we performed chemical mutagenesis to identify the components involved in ATM-mediated longevity and obtained three dominant mutants satmf1~3 , suppressor of atm in fertility , displaying delayed senescence and restored fertility in comparison with atm mutant. Molecular cloning and functional analysis of SATMF (suppressor of atm in fertility) will help to understand the underlying regulatory mechanism of ATM in plants, and shed light on developing new treatments for the disease Ataxia-telangiectasia.

A vast literature investigating behavioural underpinnings of financial bubbles and crashes relies on laboratory experiments. However, it is not yet clear how findings generated in a highly artificial environment relate to the human behaviour in the wild. It is of concern that the laboratory setting may create a confound variable that impacts the experimental results. To explore the similarities and differences between human behaviour in the laboratory environment and in a realistic natural setting, with the same type of participants, we translate a field study conducted by reference (Sornette, D.; et al. Econ. E-J. 2020 , 1-53) with trading rounds each lasting six full days to a laboratory experiment lasting two hours. The laboratory experiment replicates the key findings from the field study but we observe substantial differences in the market dynamics between the two settings. The replication of the results in the two distinct settings indicates that relaxing some of the laboratory control does not corrupt the main findings, while at the same time it offers several advantages such as the possibility to increase the number of participants interacting with each other at the same time and the number of traded securities. These findings pose important insights for future experiments investigating human behaviour in complex systems.14 , 1-53) with trading rounds each lasting six full days to a laboratory experiment lasting two hours. The laboratory experiment replicates the key findings from the field study but we observe substantial differences in the market dynamics between the two settings. The replication of the results in the two distinct settings indicates that relaxing some of the laboratory control does not corrupt the main findings, while at the same time it offers several advantages such as the possibility to increase the number of participants interacting with each other at the same time and the number of traded securities. These findings pose important insights for future experiments investigating human behaviour in complex systems.

Some of the most devastating natural events on Earth, such as earthquakes and tropical cyclones, are prone to trigger other natural events, critical infrastructure failures, and socioeconomic disruptions. Man-made disasters may have similar effects, although to a lesser degree. We investigate the space of possible interactions between 19 types of loss-generating events, first by encoding possible one-to-one interactions into an adjacency matrix A, and second by calculating the interaction matrix M of emergent chains-of-events. We first present the impact of 24 topologies of A on M to illustrate the non-trivial patterns of cascading processes, in terms of the space of possibilities covered and of interaction amplification by feedback loops. We then encode A from 29 historical cases of cascading disasters and compute the matching matrix M. We observe, subject to data incompleteness, emergent cascading behaviors in the technological and socioeconomic systems, across all possible triggers (natural or man-made); disease is also a systematic emergent phenomenon. We find interactions being mostly amplified via two events: network failure and business interruption, the two events with the highest in-degree and betweenness centralities. This analysis demonstrates how cascading disasters grow in and cross over natural, technological, and socioeconomic systems., Competing Interests: The author declares no conflict of interest.

The Einstein-Podolsky-Rosen (EPR) steering is a subtle intermediate correlation between entanglement and Bell nonlocality. It not only theoretically completes the whole picture of non-local effects but also practically inspires novel quantum protocols in specific scenarios. However, a verification of EPR steering is still challenging due to difficulties in bounding unsteerable correlations. In this survey, the basic framework to study the bipartite EPR steering is discussed, and general techniques to certify EPR steering correlations are reviewed.

Brassinosteroids (BRs) are steroid hormones essential for different biological processes, ranging from growth to environmental adaptation in plants. The plant brassinosteroid-signaling kinase (BSK) proteins belong to a family of receptor-like cytoplasmic kinases, which have been reported to play an important role in BR signal transduction. However, the knowledge of BSK genes in plants is still quite limited. In the present study, a total of 143 BSK proteins were identified by a genome-wide search in 17 plant species. A phylogenetic analysis showed that the BSK gene originated in embryophytes, with no BSK found in green algae, and these BSK genes were divided into six groups by comparison with orthologs/paralogs. A further study using comparative analyses of gene structure, expression patterns and alternative splicing of BSK genes in Arabidopsis revealed that all BSK proteins shared similar protein structure with some exception and post-translation modifications including sumolyation and ubiquitination. An expression profile analysis showed that most Arabidopsis BSK genes were constitutively expressed in different tissues; of these, several BSK genes were significantly expressed in response to some hormones or abiotic stresses. Furthermore, reverse transcription-polymerase chain reaction (RT-PCR) assays showed that BSK5 , BSK7 , and BSK9 underwent alternative splicing in specific stress induced and tissue-dependent patterns. Collectively, these results lay the foundation for further functional analyses of these genes in plants.