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Macroporous metal–organic frameworks (MOFs) exhibit immense promise as carriers for immobilizing macromolecules, notably lipases. Nevertheless, their minute particle dimensions pose challenges in the recycling process, thereby significantly constraining their widespread practical utilization. To address this limitation, this study explores the potential of incorporating magnetic substances during the carbonization process, especially focusing on the use of magnetically carbonized Macro-MIL-88A for lipase immobilization and biodiesel production. The effects of different carbonation temperatures on macroporous MIL-88A and microporous MIL-88A were investigated. Our findings revealed that the carbonization temperature influenced the preservation of the 3D structure and the generation of magnetite. Carbonized Macro-MIL-88A (Macro-Fe3O4-C) at 500 °C exhibited superior specific activity and enhanced activity recovery. Lipase immobilized on Macro-Fe3O4-C (Macro-Fe3O4-C-TLL) demonstrated higher methanol tolerance during the biodiesel production process compared to Micro-Fe3O4-C. The reduced reusability of Macro-Fe3O4-C-TLL was attributed to the adsorption of the by-product glycerol. We further investigated pre- and posthydrophobic modifications on Macro-Fe3O4-C and found that post-PDMS modification maintained both high enzyme loading and good reusability of the immobilized lipase during biodiesel production. This study presents a promising method to enhance the reusability of immobilized large molecules by incorporating magnetite via a straightforward carbonization process. [ABSTRACT FROM AUTHOR]

In the era of GeoAI, Geospatial Intelligent Question Answering (GeoIQA) represents the ultimate pursuit for everyone. Even generative AI systems like ChatGPT-4 struggle to handle complex GeoIQA. GeoIQA is domain complex IQA, which aims at understanding and answering questions accurately. The core of IQA is the Question Classification (QC), which mainly contains four types: content-based, template-based, calculation-based and method-based classification. These IQA_QC frameworks, however, struggle to be compatible and integrate with each other, which may be the bottleneck restricting the substantial improvement of IQA performance. To address this problem, this paper reviewed recent advances on IQA with the focus on solving question classification and proposed a comprehensive IQA_QC framework for understanding user query intention more accurately. By introducing the basic idea of the IQA mechanism, a three-level question classification framework consisting of essence, form and implementation is put forward which could cover the complexity and diversity of geographical questions. In addition, the proposed IQA_QC framework revealed that there are still significant deficiencies in the IQA evaluation metrics in the aspect of broader dimensions, which led to low answer performance, functional performance and systematic performance. Through the comparisons, we find that the proposed IQA_QC framework can fully integrate and surpass the existing classification. Although our proposed classification can be further expanded and improved, we firmly believe that this comprehensive IQA_QC framework can effectively help researchers in both semantic parsing and question querying processes. Furthermore, the IQA_QC framework can also provide a systematic question-and-answer pair/library categorization system for AIGCs, such as GPT-4. In conclusion, whether it is explicit GeoAI or implicit GeoAI, the IQA_QC can play a pioneering role in providing question-and-answer types in the future. [ABSTRACT FROM AUTHOR]

Extremely large magnetoresistance (EXMR) and high mobility are always desired for use in spintronic devices. Herein, we report the observation of EXMR and very large hole mobility reaching ∼ 2 × 104% (30 T) and ∼2 × 104 cm2 V−1 s−1, respectively, at 2 K in an unfilled skutterudite CoP3 crystal. The magnetotransport measurements unveil remarkable Shubnikov–de Haas quantum oscillations hosting nontrivial Berry phase induced by strong Zeeman splitting. First-principles calculations suggest band inversion between Co-dxy/yz and P-pz orbitals, which forms fourfold quadratic contact point at the Γ point above the Fermi level of ∼0.146 eV. The angle-resolved photoelectron spectroscopy measurements verify the calculated surface state. The results provide a quadratic contact point semimetal, which has potential applications in topological devices. [ABSTRACT FROM AUTHOR]

Kaolinite is one of the principal rare earth element (REE) ion-adsorption clays that hosts a wide range of elements, including Dy(III) as a representative example. Ammonium sulfate is a typical salt used to leach REEs. Due to the carbon dioxide emissions which occur during ammonia production, it is urgently necessary to develop low environmental pollution leaching agents that can replace (NH4)2SO4. MgSO4 is regarded as the most promising eco-friendly leaching agent. Herein, the first-principles plane-wave pseudopotential method based on the density functional theory (DFT) was used to investigate the stable adsorption structures of Dy(III) and its hydrated ions, MgSO4 leaching agent ions and the corresponding hydrated ions on the surface of kaolinite, which revealed the adsorption mechanism of Dy(III), Mg(II), and SO42− on the silico–oxygen plane and the aluminum–hydroxyl plane of kaolinite. Based on the research results of the steric hindrance effect of Dy(III) on the silico–oxygen plane and the aluminum–hydroxyl plane of kaolinite, the adsorption of Dy(H2O)103+ was more stable on the silico–oxygen plane. It was easier to leach out Dy(III) with MgSO4, while SO42− tended to interact with the rare earth ions in an aqueous solution. The results provide theoretical guidance for efficient rare earth extraction and obtaining novel efficient leaching agents. [ABSTRACT FROM AUTHOR]

Rich nontrivial topological phases rooted in the interplay between magnetism and topology in the layered antiferromagnet EuCd2As2 have captured vast attention, especially the ideal Weyl semimetal state realized in the spin‐polarized ferromagnetic (FM) structure driven by a moderate external magnetic field. In this work, combining magnetization, magneto‐transport, and structure measurements under high pressure and first principles calculations, this study finds that the pressure can drive the in‐plane antiferromagnetic structure of EuCd2As2 across an intermediate in‐plane FM structure then into the out‐of‐plane FM structure. This study also finds butterfly‐shaped MR and anomalous Hall effect under large pressure, which may support the pressure‐driven FM state. High‐pressure angle‐dispersive X‐ray diffraction and X‐ray absorption near‐edge spectroscopy measurements exclude structure transition and/or change of Eu2+ valence state as sources for the magnetic phase transitions. Alternatively, apparently reduced axial ratio (c/a) and compressed Eu‐layer space distance should play important roles. Interestingly, the calculations unveil that the out‐of‐plane FM structure hosts only one pair of Weyl nodes around the Fermi level, suggesting that pressure can be an alternative way to realize the ideal Weyl semimetal state in EuCd2As2 and will be useful for exploring exotic topological properties in such layered magnetic topological phase with strongly competing magnetic exchanges. [ABSTRACT FROM AUTHOR]

Alterations in intestinal function play a crucial role in the pathogenesis of sepsis, and the repair of the intestinal barrier is a potential strategy for the treatment of sepsis. Sestrin2 (SESN2), a highly conserved stress-responsive protein, can be induced in response to stress. This paper aimed to explore the role and mechanism of SESN2 in septic intestinal dysfunction. Blood samples were collected from patients with septic intestinal dysfunction, and Caco-2 cells were subjected to lipopolysaccharide (LPS) to construct in vitro models. The expression level of SESN2 was determined in the blood samples and cells. The impacts of SESN2 overexpression on cell inflammation, oxidative stress, barrier integrity, and MAPK/Nrf2 signaling were evaluated. To determine the mediated role of MAPK signaling and ferroptosis, AMPK inhibitor (Compound C) and ferroptosis inducer (erastin) were separately used to treat cells, and the influences on the above aspects in cells were assessed. The expression level of SESN2 was down-regulated in patients with septic intestinal dysfunction and LPS-induced cells. SESN2 overexpression was found to suppress cell inflammation and oxidative stress, maintain barrier integrity, and activate AMPK/Nrf2 signaling. Following the AMPK signaling was inhibited or the ferroptosis was triggered, the effects of SESN2 overexpression on the cells were both reversed. Reduced SESN2 contributed to inflammatory response and barrier dysfunction in septic intestinal dysfunction by promoting ferroptosis via activating the AMPK/Nrf2 signaling pathway. [ABSTRACT FROM AUTHOR]

We propose a Multimodal Machine Learning method for estimating the Photometric Redshifts of quasars (PhotoRedshift-MML for short), which has long been the subject of many investigations. Our method includes two main models, i.e. the feature transformation model by multimodal representation learning, and the photometric redshift estimation model by multimodal transfer learning. The prediction accuracy of the photometric redshift was significantly improved owing to the large amount of information offered by the generated spectral features learned from photometric data via the MML. A total of 415 930 quasars from Sloan Digital Sky Survey (SDSS) Data Release 17, with redshifts between 1 and 5, were screened for our experiments. We used |Δ z | = |(z phot − z spec)/(1 + z spec)| to evaluate the redshift prediction and demonstrated a |$4.04{{\ \rm per\ cent}}$| increase in accuracy. With the help of the generated spectral features, the proportion of data with |Δ z | < 0.1 can reach |$84.45{{\ \rm per\ cent}}$| of the total test samples, whereas it reaches |$80.41{{\ \rm per\ cent}}$| for single-modal photometric data. Moreover, the Root Mean Square (RMS) of |Δ z | is shown to decrease from 0.1332 to 0.1235. Our method has the potential to be generalized to other astronomical data analyses such as galaxy classification and redshift prediction. [ABSTRACT FROM AUTHOR]

Location-based social networks (LBSN) allow users to socialize with friends by sharing their daily life experiences online. In particular, a large amount of check-ins data generated by LBSNs capture the visit locations of users and open a new line of research of spatio-temporal big data, i.e., the next point-of-interest (POI) recommendation. At present, while some advanced methods have been proposed for POI recommendation, existing work only leverages the temporal information of two consecutive LBSN check-ins. Specifically, these methods only focus on adjacent visit sequences but ignore non-contiguous visits, while these visits can be important in understanding the spatio-temporal correlation within the trajectory. In order to fully mine this non-contiguous visit information, we propose a multi-layer Spatio-Temporal deep learning attention model for POI recommendation, Spatio-Temporal Transformer Recommender (STTF-Recommender). To incorporate the spatio-temporal patterns, we encode the information in the user's trajectory as latent representations into their embeddings before feeding them. To mine the spatio-temporal relationship between any two visited locations, we utilize the Transformer aggregation layer. To match the most plausible candidates from all locations, we develop on an attention matcher based on the attention mechanism. The STTF-Recommender was evaluated with two real-world datasets, and the findings showed that STTF improves at least 13.75% in the mean value of the Recall index at different scales compared with the state-of-the-art models. [ABSTRACT FROM AUTHOR]

In the context of debates on the rise of China in the West, China's seaport investment projects in the Mediterranean region have aroused concerns in the US and the EU given that they regard China as an emerging strategic and economic challenge. The EU has strategic doubts about the security, political, and economic implications of China's seaport investments. The EU is concerned that Beijing's investment has geopolitical and military purposes, which might undermine internal solidarity in the EU and subvert the existing shipping structure in Europe. This study attempts to discuss how does the EU perceives China's seaport investment and reveal whether China is a status-quo competitor or a partner for the EU in the Mediterranean. The major finding indicates that the EU had the attitude of hedging China and the US influence plays a significant role on this issue. This study put forth a clear answer on China's seaport investments' 'Dilemma'. [ABSTRACT FROM AUTHOR]