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RATIONALE: Early life social rearing has profound consequences on offspring behavior and resilience. Yet, most studies examining early life development in rodents use species whose young are born immobile and do not produce complex social behavior until later in development. Furthermore, models of rearing under increased social complexity, rather than deprivation, are needed to provide alternative insight into the development of social neural circuitry. OBJECTIVES: To understand precocial offspring social development, we manipulated early life social complexity in the communal spiny mouse Acomys cahirinus and assessed long-term consequences on offspring social behavior, exploration, and neural responses to novel social stimuli. METHODS: Spiny mouse pups were raised in the presence or absence of a non-kin breeding group. Upon adulthood, subjects underwent social interaction tests, an open field test, and a novel object test. Subjects were then exposed to a novel conspecific and novel group and neural responses were quantified via immunohistochemical staining in brain regions associated with social behavior. RESULTS: Early life social experience did not influence behavior in the test battery, but it did influence social processing. In animals exposed to non-kin during development, adult lateral septal neural responses toward a novel conspecific were weaker and hypothalamic neural responses toward a mixed-sex group were stronger. CONCLUSIONS: Communal species may exhibit robust behavioral resilience to the early life social environment. But the early life environment can affect how novel social information is processed in the brain during adulthood, with long-term consequences that are likely to shape their behavioral trajectory.
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In this study, a low-cost space mapping (SM) modeling method with mesh deformation is proposed for microwave components. In this approach, the coarse-mesh model with mesh deformation is developed as the coarse model, and the fine-mesh model is simulated as the fine model. The SM technique establishes the mapping relationship between the coarse-mesh model and the fine-mesh model. This approach enables us to combine the computational efficiency of the coarse model with the accuracy of the fine model. The automatic mesh deformation technology is embedded in the coarse model to avoid the discontinuous change in the electromagnetic response. The proposed model consisting of the coarse model and two mapping modules can represent the features of the fine model more accurately, and predict the electromagnetic response of microwave components quickly. The proposed mesh SM modeling technique is applied to the four-pole waveguide filter. The value for the training and test errors in the proposed model is less than 1%, which is lower than that for the ANN models and the existing SM models trained with the same data. Compared with HFSS software, the proposed model can save about 70% CPU time in predicting a set of 100 data. The results show that the proposed method achieves a good modeling accuracy and efficiency with few training data and a low computational cost.
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The accelerated evolution of communication platforms including Internet of Things (IoT) and the fifth generation (5G) wireless communication network makes it possible to build intelligent gas sensor networks for real-time monitoring chemical safety and personal health. However, this application scenario requires a challenging combination of characteristics of gas sensors including small formfactor, low cost, ultralow power consumption, superior sensitivity, and high intelligence. Herein, self-powered integrated nanostructured-gas-sensor (SINGOR) systems and a wirelessly connected SINGOR network are demonstrated here. The room-temperature operated SINGOR system can be self-driven by indoor light with a Si solar cell, and it features ultrahigh sensitivity to H2, formaldehyde, toluene, and acetone with the record low limits of detection (LOD) of 10, 2, 1, and 1 ppb, respectively. Each SINGOR consisting of an array of nanostructured sensors has the capability of gas pattern recognition and classification. Furthermore, multiple SINGOR systems are wirelessly connected as a sensor network, which has successfully demonstrated flammable gas leakage detection and alarm function. They can also achieve gas leakage localization with satisfactory precision when deployed in one single room. These successes promote the development of using nanostructured-gas-sensor network for wide range applications including smart home/building and future smart city.
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Bioinspired superhydrophobic surfaces are an artificial functional surface that mainly extracts morphological designs from natural organisms. In both laboratory research and industry, there is a need to develop ways of giving large-area surfaces water repellence. Currently, surface modification methods are subject to many challenging requirements such as a need for chemical-free treatment or high surface roughness. Laser micro-nanofabrications are a potential way of addressing these challenges, as they involve non-contact processing and outstanding patterning ability. This review briefly discusses multiple laser patterning methods, which could be used for surface structuring toward creating superhydrophobic surfaces.
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We propose UV-IR femtosecond laser hybrid lithography for the efficient printing of complex on-chip waveguides, which offers good performance in terms of processing efficiency and accuracy. With this three-dimensional printing technology, waveguides with complex cross-section shapes, such as owls and kittens, can be easily fabricated with an efficiency increased by 1500% (for ${6}\;\unicode{x00B5} {\rm m}\; \times \;{6}\;\unicode{x00B5} {\rm m}$6µm×6µm). In addition, a circular cross-section waveguide with an extremely low birefringence and complex ${8} \times {8}$8×8 random walk networks were quickly customized, which implies that in the design and preparation of the large-scale optical chips, the proposed maskless method allows for the preparation of highly customized devices.
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Periodical structures induced by pulsed lasers are a unique phenomenon when pulsed lasers irradiate on some material surfaces. These periodical structures with a subwavelength-scale period hold potential in integrated-optics and biomimetic micro-nanodevices for their direct shaping by laser pulses. However, the blurred nature of the laser-induced structuring hinders its further exploration in these application scopes. In this review, the plasmon-mediated structuring targeted on various materials, both organic and inorganic, will be discussed profoundly.