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Twinning structures and their interfacial segregation play a key role in strengthening of magnesium alloys. Micro-steps are frequently existed in the incoherent twin boundaries, while the effect of them on interface and interfacial segregation is still not clear. In this work, we performed an atomic-scale microstructure analysis using high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) to explore the effect of micro-steps on twin and its interfacial segregation in Mg-Ag alloy. Diffraction pattern of the incoherent {10 1 ¯ 1} twin shows that the misorientation has a slight tilt of 5° from its theoretical angle of 125° due to the accumulated effects of the micro-steps and their misfit dislocations in twin boundaries. Most of the micro-steps in {10 1 ¯ 1} twin boundary are in the height of 2 d ( 10 1 ¯ 1 ) and 4 d ( 10 1 ¯ 1 ) , respectively, and both of them have two types according to whether there are dislocations on the micro-steps. The twin boundary is interrupted by many micro-steps, which leads to a step-line distributed interfacial segregation. Moreover, the Ag tends to segregate to dislocation cores, which results in the interruption of interfacial segregation at the micro-steps with dislocations.

[Purpose/Significance] Open science is shaping a new academic innovation ecology, aiming to promote open exchange and use of knowledge, emphasize open and cooperative research methods, and thus accelerate scientific innovation. Open innovation emphasizes the flow of knowledge across organizational boundaries. Both of them have obvious internal consistency and regard the free flow of knowledge as the driving factor of innovation. However, there are few studies on the relationship between open science and open innovation at present. They are often studied separately in the scientific research environment and the enterprise environment, ignoring the common role and integration of the two in the open innovation ecology. This paper aims to analyze the consistency of the connotation of open science and open innovation, study the mechanism of open science for innovation ecology, and provide reference for building an open science innovation ecology integrating open science and open innovation, as well as for developing open science governance for scientific and technological innovation. [Method/Process] First, based on the existing connotation of open science, this paper established the connotation analysis framework of "resource-process-subject-behavior" of open science, and put forward four key elements and principles of open science: "openness of scientific knowledge resources - transparency of research process - inclusiveness of participants - collaboration of research behavior". Then it de-constructed open innovation according to the connotation analysis framework of open science, and put forward four key elements of innovation knowledge resources, innovation process, innovation subject and innovation activities, as well as the principle of transparent and open innovation knowledge resources and innovation process, and value of co-creation based on the inclusiveness of innovation subject. Finally, according to the four principles of open science, the "Open Science Spectrum" was established to clarify the consistency and synergy of both sides from the perspective of openness. Besides, in order to understand the joint action mechanism of open science and open innovation in the innovation ecology, this paper analyzes the open science innovation mechanism in different innovation stages from the perspective of innovation process, including the open science mechanism in the open science research stage, the mechanism in the technology research and development stage, the citizen science mechanism in the social inclusion stage, and the responsible innovation mechanism covering the whole process of innovation. [Results/Conclusions] The innovation ecology of open science has come into being. Open science and open innovation have consistency in connotation and synergy in openness. Under the open science innovation ecology, open science plays a role in different stages of innovation. Explicit knowledge and tacit knowledge are open and flowing in different stages of innovation, accelerating open science innovation, open innovation, public innovation and responsible innovation. The inadequacy of this paper is that the relevant research is still at the theoretical level. For example, the spectrum of open science needs to be refined to an assessable and operable granularity, and the mechanism of open science for innovation ecology also needs more cases to verify. At the same time, based on this research, we need to further explore the governance mechanism of open science under the innovation system and the linkage strategy of science, industry, society and policy under the open innovation ecology.

We present a study of the detached eclipsing binary TV Mon using spectra from the LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) medium-resolution survey, ASAS-SN (All Sky Automated Survey for SuperNovae), and CoRoT (Convection, Rotation and planetary Transits) photometry. We apply multiple-epochs spectral fitting to derive radial velocities and spectral parameters. The analysis of eclipses in CoRoT data shows the relative sizes of the stellar components and almost edge-on circular orbit. Combining the spectral and photometrical solutions we estimate masses and radii of the components: |$M_{\rm A,B}=2.063\pm 0.033({\rm stat.})\pm 0.095({\rm syst.}), \ 0.218\pm 0.004({\rm stat.})\pm 0.018({\rm syst.}) \, \mathrm{ M}_\odot$|⁠ , |$R_{\rm A,B}=2.394\pm 0.014, \ 2.860\pm 0.016 \, \mathrm{ R}_\odot$|⁠. Spectral energy distribution analysis and Gaia parallax allow us to get an estimation of temperatures |${T_{\rm eff}}_{\rm A,B}=7624^{+194}_{-174}, \ 5184^{+130}_{-123} \, \mathrm{ K}$| and distance |$d=907\pm 11 \, \mathrm{ pc}$|⁠. We identify three |$\delta$|  Scuti-type pulsation frequencies in the primary component, while we also suspect TV Mon having a spot activity in the secondary component. This system experienced intensive mass transfer and mass ratio reversal in the past, but currently shows no signs of mass transfer in the spectra. The low-mass component will lose its outer envelope and shrink to the helium white dwarf, the mass and orbital period of which are in good agreement with evolutionary model predictions. [ABSTRACT FROM AUTHOR]

Ciboria shiraiana is a necrotrophic fungus that causes mulberry sclerotinia disease resulting in huge economic losses in agriculture. During infection, the fungus uses immunity elicitors to induce plant tissue necrosis that could facilitate its colonization on plants. However, the key elicitors and immune mechanisms remain unclear in C. shiraiana. Herein, a novel elicitor Cs08297 secreted by C. shiraiana was identified, and it was found to target the apoplast in plants to induce cell death. Cs08297 is a cysteine‐rich protein unique to C. shiraiana, and cysteine residues in Cs08297 were crucial for its ability to induce cell death. Cs08297 induced a series of defence responses in Nicotiana benthamiana, including the burst of reactive oxygen species (ROS), callose deposition, and activation of defence‐related genes. Cs08297 induced‐cell death was mediated by leucine‐rich repeat (LRR) receptor‐like kinases BAK1 and SOBIR1. Purified His‐tagged Cs08297‐thioredoxin fusion protein triggered cell death in different plants and enhanced plant resistance to diseases. Cs08297 was necessary for sclerotial development, oxidative‐stress adaptation, and cell wall integrity but negatively regulated virulence of C. shiraiana. In conclusion, our results revealed that Cs08297 is a novel fungal elicitor in fungi inducing plant immunity. Furthermore, its potential to enhance plant resistance provides a new target to control agricultural diseases biologically. [ABSTRACT FROM AUTHOR]

This study presents the development of predictive models for concrete performance, specifically targeting the compressive strength and slump value, utilizing the quantities of individual raw materials in the concrete mix design as input variables. Three distinct machine learning approaches—Backpropagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF)—were employed to establish the prediction models independently. In the model construction process, the Particle Swarm Optimization (PSO) algorithm was integrated with cross-validation to fine-tune the hyperparameters of each model, ensuring optimal performance. Following the completion of training and modeling, a comprehensive comparison of the predictive accuracy among the three models was conducted, with the aim of selecting the most suitable model for incorporation into an optimized objective function. The findings reveal that among the chosen machine learning techniques, BPNN exhibited superior predictive capabilities for the compressive strength of concrete. Specifically, in the validation set, BPNN achieved a high correlation coefficient (R) of 0.9531 between the predicted and actual outputs, accompanied by a low Root Mean Square Error (RMSE) of 4.2568 and a Mean Absolute Error (MAE) of 2.6627, indicating a precise and reliable prediction. Conversely, for the prediction of the concrete slump value, RF outperformed the other two models, demonstrating a correlation coefficient (R) of 0.8986, an RMSE of 9.4906, and an MAE of 5.5034 in the validation set. This underscores the effectiveness of RF in capturing the complexity and variability inherent in slump behavior. Overall, this research highlights the potential of integrating advanced machine learning algorithms with optimization techniques for enhancing the accuracy and efficiency of concrete performance predictions. The identified optimal models, BPNN for compressive strength and RF for slump, can serve as valuable tools for engineers and researchers in the field of construction materials, facilitating the design of concrete mixes tailored to specific performance requirements. [ABSTRACT FROM AUTHOR]

This study presents an exhaustive exploration into the development and rigorous evaluation of nano-TiO2-modified recycled aggregates (NT@RAs) as an environmentally sustainable substitute for natural aggregates in concrete applications. A methodical framework was devised for the synthesis and thorough characterization of NT@RAs, emphasizing the optimization of nano-TiO2 loading onto the RA surface and within its intricate porous structure. The investigation encompassed three distinct types of recycled aggregates: recycled glass sands (RGSs), recycled clay brick sands (RCBSs), and recycled concrete sands (RCSs). Of particular interest, NT@RGS, with its properties of an inherently smooth surface texture and low water absorption, was found to exert a favorable influence on the rheological behavior of concrete, manifested in reduced yield stress, thereby underscoring the potential for fine-tuning mix designs to enhance workability. As the substitution levels of NT@RGS and NT@RCBS escalated, an initial decrement in compressive strength was discernible, which subsequently reversed to strength restoration at optimized substitution ratios. This phenomenon is attributed to the synergistic interplay among NT@RA components. Remarkably, NT@RA-incorporated concrete demonstrated unparalleled self-cleaning abilities, surpassing the performance of concrete with direct nano-TiO2 powder incorporation. This comprehensive research contributes significantly to the advancement in sustainable, high-performance photocatalytic construction materials within the realm of concrete technology. It underscores the potential for enhancing not only the rheological and mechanical properties but also the environmental responsiveness of concrete through the innovative utilization of NT@RAs. [ABSTRACT FROM AUTHOR]

Carbonate‐associated sulfate (CAS) δ34S values (δ34SCAS) are generally assumed to reflect S isotopic composition of paleo‐seawater and have been extensively used to reconstruct secular variations in seawater sulfate concentrations during the geological past. However, it has often been documented that δ34SCAS records are incompatible with seawater sulfur isotopes (20.9 ± 0.1%, 2σ) determined from other archives, such as sulfate evaporites and barite (both of which may also display inconsistencies). A possible explanation for this discrepancy is that δ34SCAS values can be easily altered by atmospheric sulfate and sulfide re‐oxidation. However, the specific influence of biological factors (vital effects, common in biogenic carbonates) on CAS S isotopic composition remains unresolved, particularly at microscale levels. To elucidate these effects on δ34SCAS, S isotopic profiles were analyzed across two skeletal transects of two modern deep‐sea corals (gorgonia) using a novel secondary‐ion mass spectrometry method. Strong S isotopic fractionation was observed in calcitic skeletons from the most 34S‐depleted center (δ34S = ∼19‰), increasing outward to a relatively constant 22.5‰ in gorgonia sp. coral and 21.6‰ in bamboo coral, suggesting that vital effects are much larger than previous estimated (∼±1‰ fractionation from seawater). Oxygen isotopic and Mg, S, O elemental compositions, and Raman spectral and crystal morphological features indicate that processes such as pH control, Rayleigh fractionation, and organic effects are precluded as causes of such fractionation. Instead, vital effects associated with kinetic processes related to surface entrapment seem plausible as controls on S isotopic fractionations in the coral. This novel method is significant for gaining insights into vital effects, assessing the reliability of biogenic carbonates as high‐resolution environmental archives of S isotopes, and understanding the fundamental mechanisms governing biomineralization. Plain Language Summary: The δ34S values of carbonate‐associated sulfate (CAS) serve as crucial indicators of past environmental conditions, providing insights into historical variations in seawater sulfate and atmospheric oxygen levels. It is commonly assumed that δ34SCAS closely reflects seawater sulfate, except for severely altered samples. However, analysis of S isotopic profiles across two skeletal transects of modern calcitic deep‐sea corals (gorgonia sp. coral and bamboo coral) using a newly developed in situ method based on secondary‐ion mass spectrometry, reveals significant isotopic fractionation. The most 34S‐depleted center (δ34S = ∼19‰) increases outward to a relatively constant value of 22.5‰ for gorgonia sp. coral and 21.6‰ for bamboo coral. These findings suggest that vital effects play a notable role in δ34SCAS fractionation, challenging the previous consensus of ∼±1‰. Further investigation, incorporating multiple indices and skeletal δ18O, indicates that vital effects associated with kinetic processes related to surface entrapment contribute to this fractionation. These insights shed light on the processes driving S–O isotopic fractionation in biogenic carbonates, bolstering their utility in reconstructing paleo‐oceanographic conditions. Key Points: Development of in situ carbonate S isotopic analysis using secondary‐ion mass spectrometryCommonly observed anomalous low δ34S and δ18O values in the axial skeleton of deep‐sea gorgonia coralsContribution of kinetic‐associated vital effects to significant Carbonate‐associated sulfate sulfur isotopic fractionation, supported by multiple geochemical indices [ABSTRACT FROM AUTHOR]

This research introduces a novel approach to reconstruct sea surface temperature (SST) by developing a universal coral thermometer using machine learning (ML) algorithms on monthly resolved Porites coral proxies and SST data. A total of 1,202 data sets from 19 corals, covering SSTs ranging from 21.5 to 31.5°C, with proxies including Sr/Ca, Mg/Ca, Li/Mg, U/Ca, and B/Ca ratios were analyzed. The data were divided into four sub‐datasets by regional and taxon constraints. An exhaustive analysis was conducted, training 1,612 models using various proxy combinations and ML strategies to assess the impact of the non‐SST effect on the universality of ML models. The results indicated that the non‐SST effect is more significantly attributed to regional variations than to taxon differences, underscoring the importance of regional factors in Porites coral proxy‐based SST reconstructions. Sr/Ca and Li/Mg proxies were identified as the most indicative of SST, showing clearer relationships with temperature than other proxies. Non‐linear approaches achieved a Root Mean Square Error (RMSE) of less than 0.90°C, which further decreased to 0.72°C upon incorporating specific regional and taxon constraints. In an independent test set focusing exclusively on Li/Mg and Sr/Ca proxies, the tree‐based algorithms particularly excelled, achieving an average RMSE improvement of at least 0.52°C over the Universal Multi‐Trace Element Calibration Scheme and the Li/Mg empirical equation. This research underscores the potential of applying ML to coral‐based SST reconstructions, especially highlighting the effectiveness of tree‐based algorithms and the suitability of Sr/Ca and Li/Mg proxies for accurate temperature estimations. Key Points: A universal coral thermometer was developed using machine learning (ML) on Porites coral proxies, enhancing paleo sea surface temperature (SST) reconstruction accuracyLi/Mg and Sr/Ca proxies were identified as the most effective for SST reconstructions, showcasing clearer relationships with SSTTree‐based ML models outperformed others in predicting SST, advocating their use when Sr/Ca and Li/Mg proxies are available [ABSTRACT FROM AUTHOR]

Complex concentrated solutions of multiple principal elements are being widely investigated as high- or medium-entropy alloys (HEAs or MEAs).sup.1-11, often assuming that these materials have the high configurational entropy of an ideal solution. However, enthalpic interactions among constituent elements are also expected at normal temperatures, resulting in various degrees of local chemical order.sup.12-22. Of the local chemical orders that can develop, chemical short-range order (CSRO) is arguably the most difficult to decipher and firm evidence of CSRO in these materials has been missing thus far.sup.16,22. Here we discover that, using an appropriate zone axis, micro/nanobeam diffraction, together with atomic-resolution imaging and chemical mapping via transmission electron microscopy, can explicitly reveal CSRO in a face-centred-cubic VCoNi concentrated solution. Our complementary suite of tools provides concrete information about the degree/extent of CSRO, atomic packing configuration and preferential occupancy of neighbouring lattice planes/sites by chemical species. Modelling of the CSRO order parameters and pair correlations over the nearest atomic shells indicates that the CSRO originates from the nearest-neighbour preference towards unlike (V-Co and V-Ni) pairs and avoidance of V-V pairs. Our findings offer a way of identifying CSRO in concentrated solution alloys. We also use atomic strain mapping to demonstrate the dislocation interactions enhanced by the CSROs, clarifying the effects of these CSROs on plasticity mechanisms and mechanical properties upon deformation. Direct experimental evidence of chemical short-range atomic-scale ordering (CSRO) in a VCoNi medium-entropy alloy is provided via diffraction and electron microscopy, analysed from specific crystallographic directions., Author(s): Xuefei Chen [sup.1] [sup.2] , Qi Wang [sup.3] , Zhiying Cheng [sup.4] , Mingliu Zhu [sup.1] , Hao Zhou [sup.5] , Ping Jiang [sup.1] , Lingling Zhou [sup.1] [sup.2] [...]

Understanding the mineralization of coral is significant for the formation of coral reefs and paleoclimatic reconstructions. However, the fundamental mechanisms involved in biomineralization are poorly understood. A combination of Raman spectral and cross-polarized reflected light microscopy imaging was used to examine the three-dimensional spatial distribution of the skeletal ultrastructures and their associated mineral, organic, and water chemistry in coral, which enable insight into the spatial growth features of the ultrastructures and possible formation processes. A possible mechanism is proposed that controls the formation of skeletal ultrastructures, which likely involves compartmentalized calcifying cells and their related cellular activities. This could clarify the association between coral skeletal mineralization and biology, and it may be beneficial to better protection and application of coral reefs. [ABSTRACT FROM AUTHOR]