摘要：Molecular constructs define the elementary units in porous materials for efficient CO_(2)*** design of appro-priate interpore and intermolecular space is crucial to stabilize CO_(2)molecules and maximize the *** the molecular construct usually has a fixed dimension,whether its inter-molecular space could be self-adjustable during CO_(2)capture and release,behaving as a balloon,has captured *** we report a flexible intermolecular space of the double chain structure of self-assembled 1,4-pheny-lene diisocyanide(PDI)molecules on Ag(110)surface,which dynamically broadens and recovers during the CO_(2)capture and *** incipient PDI double chains organize along the[001]direction of Ag(110),in which individual PDI molecules stand up in a zigzag order with the interchain width defined by twice the Ag lattice distance along_([110])direction(2α_([110])).When CO_(2)molecules are introduced,they assemble to occupy the interchain spaces,expanding the interchain width to 3α_([110]),4α_([110])and 5α_([110]):Warming up the sample leads to the thermally-driven CO_(2)desorption that recovers the original interchain ***-resolution scanning tunneling microscopy(STM)jointly with density functional theory(DFT)calculations determine the structural and electronic interactions of CO_(2)molecules with the dynamical PDI structures,providing a molecular-level perspective for the design of a self-adjustable metal-organic construct for reversible gas capture and release.

摘要：Accurate detection of multiple small end-metabolic biomarkers is more sensitive than large biomoleculesto provide real-time feedbacks of physiological/pathologicalstate, but is more challenging due to lack of specific identifyinggroups. Current optical platforms suffer from unsatisfactoryresolutions to differentiate each target because they producesimilar output to different targets using a single excitation,and inevitably involve non-functional components that increase chances of interacting with non-target ***, by taking full advantage of each building unit’sfunctionality to integrate multivariate recognition elements inone interface, a dual-excitation-driven full-component-responsive metal-organic framework (MOF)-based luminescentprobe, namely CeTMA-TMA-Eu, is successfully custom-tailored for detecting both pseudouridine (Ψ) and N-acetylaspartate (NAA), the diagnostic hallmarks of cancer andneurodegenerative disorder. Remarkably, Ψ interacts withMOF’s organic building unit (trimesic acid, TMA) and filtersout its absorptions of 262 nm-light to reduce its energytransferred to Eu^(3+), while NAA induces the valence transitionof Ce^(4+)/Ce^(3+) nodes to improve the cooperative energy transferefficacy from TMA and Ce^(3+) to Eu^(3+). As a result, this platformexhibits completely reverse photoresponses towards Ψ(“switch-off” at 262 nm excitation) and NAA (“switch-on”upon 296 nm excitation), and demonstrates excellent selectivity and sensitivity in complex biofluids, with low detection limits of 0.16 and 0.15 μM, and wide linear ranges of0–180 and 0–100 μM, respectively. Such full-componentresponsive probe with dual-excitation-mediated reverse responses for multi-small targets intrinsically minimizes its interaction with non-target molecules and amplifies resolutionto discriminate each target, providing a new strategy for improving assay accuracy of multi-small biomarkers in diagnostics.

摘要：Machine learning (ML) has been widely used todesign and develop new materials owing to its low computational cost and powerful predictive capabilities. In recentyears, the shortcomings of ML in materials science have gradually emerged, with a primary concern being the scarcity ofdata. It is challenging to build reliable and accurate ML modelsusing limited data. Moreover, the small sample size problemwill remain long-standing in materials science because of theslow accumulation of material data. Therefore, it is importantto review and categorize strategies for small-sample learningfor the development of ML in materials science. This reviewsystematically sorts the research progress of small-samplelearning strategies in materials science, including ensemblelearning, unsupervised learning, active learning, and transferlearning. The directions for future research are proposed, including few-shot learning, and virtual sample *** importantly, we emphasize the significance of embedding material domain knowledge into ML and elaborate on thebasic idea for implementing this strategy.

摘要：Zero-dimensional perovskite materials,characterized by broadband emission caused by self-trapped excitons,are promising materials for stimuli-responsive and photo-writeable ***,existing research is focused on the effects of structural phase transitions on photophysical properties,and lacks in-depth understanding of the mechanisms of self-trapped excitons ***,we demonstrate that the dehydration reaction in zero-dimensional antimony halide clusters significantly enhances the self-trapped excitons emission without inducing structural phase transition,resulting in a substantial increase in photoluminescence(PL)quantum yield from 3.5%to 91.4%.In-situ X-ray diffraction and PL techniques were employed to shed light on the relationship between the crystal structure and radiative recombination,demonstrating the introduction of rich lattice distortion during the dehydration ***-dependent PL spectra and transient absorption spectra suggest that the lattice distortion causes the moderate electron-phonon coupling strength and high exciton binding energy,facilitating self-trapped excitons to relax from the non-radiative recombination singlet state to the radiative recombination triplet state,corresponding to the enhanced emission *** a proof of concept,several switchable PL applications have been established in scenarios such as anti-counterfeiting,rewritable luminescent paper,and humidity *** finding elucidates the emission mechanism of self-trapped excitons and provides a novel avenue for designing switchable luminescent materials.

摘要：In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing（OFDM） Multiple-Input Multiple-Output（MIMO） radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design（AWD） based on a constrained Multi-Objective Optimization（MOO）. The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.

摘要：The mechanical properties dependence on the microstructure was reviewed and analyzed,and the ultrafine grained duplex microstructure of BCC matrix and large fractioned austenite was given as one of the optimum structures to develop the third generation steel with high strength and high *** medium-Mn steels with different carbon contents processed by austenite reverted transformation(ART-annealing) were studied thoroughly to fabricate the ultrafine duplex steels with large fractioned *** lamellar typed ultrafine structure,the granular typed ultrafine duplex structure and the corresponding mechanical properties of the medium-Mn steels processed by ART-annealing were demonstrated in this *** was revealed that the duplex structure with large fraction of austenite and ultrafine grain structure is capable of producing steels with excellent combination of strength and ductility,i.e.,Rm A about 30-50 GPa%,which is about two times of that of the conventional automobile steels and close to that of the TWIP *** was concluded that the ART-annealing of the medium-Mn steels would be at least one of the promising ways to fabricate the third generation automobile steels in the near future.

摘要：In this paper,we propose a homogenization theory for designing graded viscoelastic sonic crystals（VSCs） which consist of periodic arrays of elastic scatterers embedded in a viscoelastic host *** extend an elastic homogenization theory to VSC by using the elastic-viscoelastic correspondence principle and propose an analytical effective loss factor of *** results of VSC and the equivalent structure calculated by using the finite element method are in good *** to the relation of the effective loss factor to the filling fraction,a graded VSC plate is easily and quickly ***,the graded VSC may have potential applications in the vibration absorption and noise reduction fields.

摘要：The eukaryotic genome is packaged into a complex nucleoprotein structure named chromatin, balancing the compactness of genome and the accessibility of regulatory proteins and RNA polymerases to DNA. The mechanisms of the regulation of chromatin dynamics include the post-translational modification of histones, alteration of nucleosome positions by chromatin remodelers, replacement of canonical histones by histone variants with the aid of histone chaperones, and dynamic organization of the three-dimensional genome in the small nucleus. Histone variants are different from canonical histones by substitution of several amino acid residues or changes in amino acid sequence. Histone variants perform specialized functions such as altering nucleosome stability, dynamics, structure, as well as playing critical roles in a range of biological processes like transcriptional regulation, DNA repair and recombination, development and immune responses. Here we discuss how histone variants, their modification and specific loading to chromatin are involved in transcriptional regulation, DNA repair and plant development.

摘要：Developing efficient walking gaits for quadruped robots has intrigued investigators for years. Trot gait, as a fast locomotion gait, has been widely used in robot control. This paper follows the idea of the six determinants of gait and designs a trot gait for a parallel-leg quadruped robot, Baby Elephant. The walking period and step length are set as constants to maintain a relatively fast speed while changing different foot trajectories to test walking quality. Experiments show that kicking leg back improves body stability. Then, a steady and smooth trot gait is designed. Furthermore, inspired by Central Pattern Generators （CPG）, a series CPG model is proposed to achieve robust and dynamic trot gait. It is generally believed that CPG is capable of producing rhythmic movements, such as swimming, walking, and flying, even when isolated from brain and sensory inputs. The proposed CPG model, inspired by the series concept, can automatically learn the previous well-designed trot gait and reproduce it, and has the ability to change its walking frequency online as well. Experiments are done in real world to verify this method.

摘要：Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.