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Triadica sebifera is an important landscaping tree species because of its colorful autumn leaves. In recent years, some cultivars have been bred and licensed, but it can be difficult to identify them from their morphological traits due to their similar phenotypes. To explore the genetic relationships and construct a fingerprint of the cultivars, the licensed T. sebifera cultivars were analyzed using SSR markers. A total of 179 alleles were identified among the 21 cultivars at 16 SSR loci, and these alleles exhibited a high level of genetic diversity (He = 0.86). The genetic variations mainly occurred among cultivars based on an analysis of molecular variance (AMOVA). According to phylogenetic analysis, principal coordinate analysis (PCoA), and Bayesian clustering analysis, the genetic relationships were independent of geographic distances, which may be mainly due to transplantations between regions. Some cultivars with different leaf colors showed obvious genetic differentiation and may be preliminary candidates for cross-breeding. Finally, the fingerprint for the licensed cultivars was constructed with two SSR markers. The results of this study can provide technical support for the application and legal protection of licensed Triadica sebifera cultivars. [ABSTRACT FROM AUTHOR]

Conductive‐bridge random access memory (CBRAM) emerges as a promising candidate for next‐generation memory and storage device. However, CBRAMs are prone to degenerate and fail during electrochemical metallization processes. To address this issue, herein we propose a self‐repairability strategy for CBRAMs. Amorphous NbSe2 was designed as the resistive switching layer, with Cu and Au as the top and bottom electrodes, respectively. The NbSe2 CBRAMs demonstrate exceptional cycle‐to‐cycle and device‐to‐device uniformity, with forming‐free and compliance current‐free resistive switching characteristics, low‐operation voltage, and competitive endurance and retention performance. Most importantly, the self‐repairable behavior is discovered for the first time in CBRAM. The device after failure can recover its performance to the initially normal state by operating with a slightly large reset voltage. The existence of Cu conductive filament and excellent controllability of Cu migration in the NbSe2 switching layer has been revealed by a designed broken‐down point approach, which is responsible for the self‐repairable behavior of NbSe2 CBRAMs. Our self‐repairable and high‐uniform amorphous NbSe2 CBRAM may open the door to the development of memory and storage devices in the future. [ABSTRACT FROM AUTHOR]

Artificial synapse devices are dedicated to overcoming the von Neumann bottleneck. Adopting light signals in visual information processing and computing is vital for developing next‐generation artificial neuromorphic systems. A strategy to construct all‐optically controlled artificial synaptic devices based on full oxides with amorphous ZnAlSnO/SnO heterojunction in a two‐terminal planar configuration is proposed. All synaptic behaviors are operated in the visible optical pathway, with excitatory synapse under red (635 nm) light and inhibitory synapse under green (532 nm) and blue (405 nm) lights. Based on the different inhibitory effects, two modes of long‐term depression (LTD) and RESET processes can be implemented through green and blue lights, respectively. The energy consumption of an event can be as low as 0.75 pJ. A three‐layer perceptron model is designed to classify 28 × 28‐pixel handwritten digital images and performed supervised learning using a backpropagation algorithm, demonstrating the bio‐visually inspired neuromorphic computing with a training accuracy of 92.74%. The all‐optically controlled artificial synapses with write/erasure behaviors in visible RGB region and rational microelectronic process, as presented in this work, are essential in developing future artificial neuromorphic systems and highlight the huge potential of next‐generation computer systems. [ABSTRACT FROM AUTHOR]

Vision sensors are becoming increasingly ubiquitous, and they continuously collect, store, communicate, and process vast amount of sensitive data that are vulnerable to being stolen and misused. Existing cryptosystems based on complex cipher algorithms generally require extensive computational resources, making them difficult to use in vision sensors that have limited processing capabilities. Here, we propose and experimentally demonstrate a novel in situ image cryptography scheme based on a neuromorphic vision sensor comprising all-optically controlled (AOC) memristors. Due to the unique light wavelength and irradiation history-dependent bidirectional persistent photoconductivity of AOC memristors, a visual image can be stored, encrypted, decrypted, denoised, and destroyed within a vision sensor. A decrypted image can be encoded in situ and then accurately recognized through a memristive neural network. Encrypted and destroyed images are capable of withstanding hacking attacks even with trained neural networks. Our cryptography scheme enables complete cryptographic operations entirely on a sensor and, therefore, effectively safeguards visual information. This work provides a simple yet efficient solution to the security challenges faced by vision sensors. [ABSTRACT FROM AUTHOR]

Cherries (Prunus Subgenus Cerasus) have economic value and ecological significance, yet their phylogeny, geographic origin, timing, and dispersal patterns remain challenging to understand. To fill this gap, we conducted a comprehensive analysis of the complete chloroplast genomes of 54 subg. Cerasus individuals, along with 36 additional genomes from the NCBI database, resulting in a total of 90 genomes for comparative analysis. The chloroplast genomes of subg. Cerasus exhibited varying sizes and consisted of 129 genes, including protein-coding, transfer RNA, and ribosomIal RNA genes. Genomic variation was investigated through InDels and SNPs, showcasing distribution patterns and impact levels. A comparative analysis of chloroplast genome boundaries highlighted variations in inverted repeat (IR) regions among Cerasus and other Prunus species. Phylogeny based on whole-chloroplast genome sequences supported the division of Prunus into three subgenera, I subg. Padus, II subg. Prunus and III subg. Cerasus. The subg. Cerasus was subdivided into seven lineages (IIIa to IIIg), which matched roughly to taxonomic sections. The subg. Padus first diverged 51.42 Mya, followed by the separation of subg. Cerasus from subg. Prunus 39.27 Mya. The subg. Cerasus started diversification at 15.01 Mya, coinciding with geological and climatic changes, including the uplift of the Qinghai–Tibet Plateau and global cooling. The Himalayans were the refuge of cherries, from which a few species reached Europe through westward migration and another species reached North America through northeastward migration. The mainstage of cherry evolution was on the Qing–Tibet Plateau and later East China and Japan as well. These findings strengthen our understanding of the evolution of cherry and provide valuable insights into the conservation and sustainable utilization of cherry's genetic resources. [ABSTRACT FROM AUTHOR]

Amorphous oxide-based memristors are significant candidates for the realization of neuromorphic systems. However, barely attributing memristive performance to oxygen vacancy is insufficient and oversimplified. In this work, the amorphous structure stability, surface morphology and chemical state of amorphous ZnTiSnO films with different oxygen vacancy contents are comprehensively characterized. The memristive performance of Au/ZnTiSnO/Au crossbar devices is sensitive to the oxygen vacancy content affected by the oxygen pressure during functional layer deposition. The device prepared under 4.4 Pa oxygen pressure achieved far more pinched hysteresis loops than that fabricated at 4.5 Pa oxygen pressure. In contrast, no memristive behavior could be observed for devices prepared at 1.8 Pa and 0 Pa. Notably, the content of OII components representing oxygen vacancies differs by less than 10% between samples. An initial low resistance state is observed owing to the Fermi level above the conduction band. For the 4.4 Pa device, there is a narrow difference between the conduction band minimum and the Fermi level, accompanied by high Schottky barriers. These findings provide new inspiration for the design of valence change mechanism memristors. [ABSTRACT FROM AUTHOR]

A simple low-temperature (< 100 °C) hot-water treatment was used to synthesize Fe–N co-doped anatase nanocrystals which were uniformly dispersed in micro–mesoporous SiO2 host film for the first time. The Fe–N co-doped TiO2–SiO2 (FNTS) film exhibited stable photocatalytic activities. A NO removal efficiency of 56.1% was achieved under simulated solar light irradiation without any obvious inactivation in 30 min. The transient photocurrent response of FNTS film is approximately six times higher than that of non-doped TiO2–SiO2 film, indicating the superior charge separation of photo-generated electron–hole pairs. Electron spin resonance analysis showed that the ·OH and ·O2− radicals were key species to remove NO. Combined with quantitative reaction intermediates, the possible photocatalytic degradation mechanism of NO over FNTS film was proposed. In addition, the FNTS thin films exhibited intrinsic super-hydrophilicity and durable self-cleaning property even after 6 months of storage in the dark. This work provides a facile method to load the catalyst on thermal labile substrates, such as soda–lime glass and organic polymer for more practical applications. A simple low-temperature (< 100 °C) hot-water treatment was used to synthesize micro–mesoporous TiO2–SiO2 composite film, which shows good self-cleaning ability and superior photodegradation activity for NO removal under solar light. [ABSTRACT FROM AUTHOR]

Neuromorphic computing (NC) is a new generation of artificial intelligence. Memristors are promising candidates for NC owing to the feasibility of their ultrahigh‐density 3D integration and their ultralow energy consumption. Compared to traditional electrical memristors, the emerging optoelectronic memristors are more attractive owing to their ability to combine the advantages of both photonics and electronics. However, the inability to reversibly tune the memconductance with light has severely restricted the development of optoelectronic NC. Here, an all‐optically controlled (AOC) analog memristor is realized, with memconductance that is reversibly tunable over a continuous range by varying only the wavelength of the controlling light. The device is based on the relatively mature semiconductor material InGaZnO and a memconductance tuning mechanism of light‐induced electron trapping and detrapping. It is found that the light‐induced multiple memconductance states are nonvolatile. Furthermore, spike‐timing‐dependent plasticity learning can be mimicked in this AOC memristor, indicating its potential applications in AOC spiking neural networks for highly efficient optoelectronic NC. [ABSTRACT FROM AUTHOR]