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Subways, underground logistics systems and underground parking, as the primary facilities types of underground, contribute significantly to the achievement of carbon–neutral cities by moving surface transportation to underground, thereby releasing surface space for the creation of more urban blue-green space for carbon sink. Therefore, in-depth studies on carbon neutrality strategies as well as reliable layout optimization solutions of these three types of underground facilities are required. This study proposes a spatial layout optimization strategy for carbon neutrality using underground hydrogen storage and geothermal energy for these three types of underground facilities employing a multi-agent system model. First, three spatial layout relationships, competition, coordination, and followership, between five underground facilities that contribute to emission reduction were investigated. Second, the implementation steps for optimizing the spatial layout of underground facilities were determined by defining the behavioral guidelines for spatial environment, underground facility, and synergistic agent. Finally, using the Tianfu New District in Chengdu City, China, as a case study, layouts of underground facilities under three different underground space development scenarios were simulated to verify the model. The findings of this study address the gap in the research on underground spatial facilities and their layout optimization in response to emission reduction. This study provided a significant reference for the study of underground space and underground resources at the planning level to aid in achieving carbon–neutral cities.

As an energy-saving device for energy transduction, a steam ejector has been crucial in energy saving and emission reduction, energy consumption reduction, and energy reuse. An optimization method of full geometric parameters and a preferred method of working conditions were considered to rise the entrainment ratio of a steam ejector and improve its entrainment capacity. The related models of the ejector were established and numerically simulated. The influence of geometric parameters on the entrainment capacity of the ejector researched by adopting the control variable method and the 11-factor 5-level orthogonal test. The effect of working conditions on the entrainment ratio for the optimized ejector discussed, and the preferred method of working conditions of the ejector proposed. The results show that the entrainment ratio of the optimized ejector by the control variable method rises by 30.8 % to that of the original ejector, and the entrainment ratio of the new ejector by orthogonal test rises by 78 %. The constant cross-section diameter is a critical parameter affecting the entrainment capacity of the ejector. Contrasted with the original ejector, the maximum entrainment ratio under preferred working conditions rises by 242%–471 % via using the preferred method of working conditions. Considering the optimization of full geometric parameters and working conditions, the influence of the optimized process on the entrainment capacity of ejectors is evident, which provides an effective way and reference for the optimization research and development of other types of ejectors.

With the expansion of cities and the emergence of various urban problems, urban underground space has been developed as a solution. In China’s urban transition context, there is a need for the development of underground space in urban built-up areas. In this case-study of the central city of Nanjing, we used spatial analysis and statistical methods to characterize the underground space use of urban built-up areas from a dynamic spatiotemporal perspective. We first analyzed the relationship between the population distribution and the underground space use of the central city of Nanjing based on a Baidu heat map, which can reflect the real-time population distribution, and then, we explored the spatiotemporal characteristics and spatial structure of the underground space use in urban built-up areas. The analysis results provide a reference for planning to improve and optimize the layout of underground space in the central city of Nanjing and, more generally, for the stock-type planning of underground space in urban built-up areas.

The growth simulation of urban underground space (UUS) under the consideration of ecological constraints can effectively reveal the characteristics and trends of UUS changes, and provide a basis for planning the construction of sustainable and livable ecological cities. Therefore, this study considers urban ecological space as a constraint mechanism for UUS development and conducts a simulation study of the dynamic and complex UUS growth process, with a view toward guiding UUS planning under a long-term overall vision. In this study, a patch-based cellular automaton (CA) model is constructed to simulate the dynamic and complex growth process of UUS, subject to the ecological constraints generated by the agent-based land allocation optimization model. The spatial drivers of UUS growth simulation are determined based on the Random Forest (RF) algorithm. The results of the research case in Tianfu New District, Chengdu City, demonstrate that UUS expansion with ecological constraints exhibits sustainable characteristics. However, the growth rate of the UUS development scale is significantly lower when ecological constraints are present compared to when they are not. This study’s results contribute to urban management by finding a balance between UUS development and ecological space conservation, and providing theoretical support for rational UUS planning and decision making in the construction of low-carbon cities.

Rational use of urban underground space (UUS) and public transportation transfer underground can solve urban traffic problems. Accurate short-term prediction of passenger flow can ensure the efficient, safe, and comfortable operation of subway stations. However, complex and nonlinear interdependencies between time steps and time series complicate such predictions. This study considered temporal patterns across multiple time steps and selected relevant information on short-term passenger flow for prediction. A hybrid model based on the temporal pattern attention (TPA) mechanism and the long short-term memory (LSTM) network was developed (i.e., TPA-LSTM) for predicting the future number of passengers in subway stations. The TPA mechanism focuses on the hidden layer output values of different time steps in history and of the current time as well as correlates these output values to improve the accuracy of the model. The card swiping data from the Hangzhou Metro automatic fare collection system in China were used for verification and analysis. This model was compared with a convolutional neural network (CNN), LSTM, and CNN-LSTM. The results showed that the TPA-LSTM outperformed the other models with good applicability and accuracy. This study provides a theoretical basis for the pre-allocation of subway resources to avoid subway station crowding and stampede accidents.

Convective heat transfer on the exterior surface of the building envelope is an important component for building energy consumption. The calculation of energy consumption depends on the convective heat transfer coefficient (CHTC) of the exterior surface of the envelope. The existing research does not fully consider the effects of the airflow field around the building on the CHTC of different envelope exterior surfaces. In this paper, the relationships between the CHTC and influence factors were investigated for the isolated building. Response surface methodology (RSM) and support vector machine (SVM) algorithms were integrated with the single building simulation to build the fitting formulas. Then, the fitting correlation between CHTC and different influencing factors was validated by the heating building simulation. The results showed that the CHTC of the building exterior surface was related to the wind velocity, wind direction and temperature difference. Additionally, the fitting formulas had good accuracy in calculating the CHTC under different conditions. The SVM algorithm (averaged error: 3.34%) performed slightly better than the RSM algorithm (averaged error: 4.84%).

Abstract Astrocytes have been implicated in epileptogenesis and seizure-induced brain injury. Pathological studies reveal a variety of structural abnormalities in astrocytes, such as vacuolization and astrogliosis. While in vivo imaging methods have demonstrated rapid changes in astrocytes under a variety of physiological and pathological conditions, the acute effects of seizures on astrocyte morphology in vivo and corresponding mechanisms of seizure-induced astrocytic injury have not been documented. In this study, we utilized in vivo two-photon imaging to directly monitor the acute structural effects of kainate-induced seizures on cortical astrocytes. Kainate seizures cause an immediate, but transient, vacuolization of astrocytes, followed over several days by astrogliosis. These effects are prevented by pre- or post-treatment with rapamycin, indicating the mTOR pathway is involved in mediating seizure-induced astrocyte injury. These finding have clinical implications for mechanisms of seizure-induced astrocyte injury and potential therapeutic applications with mTOR inhibitors.

Tuberous sclerosis complex (TSC) is a genetic disease related to hyperactivation of the mechanistic target of rapamycin (mTOR) pathway and manifested by neurological symptoms, such as epilepsy and sleep disorders. The pathophysiology of sleep dysfunction is poorly understood and is likely multifactorial, but may involve intrinsic biological regulators in the brain. Here, we characterized a mouse model of sleep disorders in TSC and investigated mechanisms of sleep dysfunction in this conditional knockout model involving inactivation of the Tsc1 gene in neurons and astrocytes (Tsc1GFAPCKO mice). Sleep studies utilizing EEG, EMG, and behavioral analysis found that Tsc1GFAPCKO mice have decreased REM sleep and impaired sleep-wake differentiation between light and dark phases. mTOR activity and orexin expression were increased in hypothalamic sections and cultured hypothalamic neurons from Tsc1GFAPCKO mice. Both the sleep abnormalities and increased orexin expression in Tsc1GFAPCKO mice were reversed by rapamycin treatment, indicating their dependence on mTOR activation. An orexin antagonist, suvorexant, also restored normal REM levels in Tsc1GFAPCKO mice. These results identify a novel mechanistic link between mTOR and orexin in the hypothalamus related to sleep dysfunction and suggest a targeted therapeutic approach to sleep disorders in TSC.

Astrocytes play important roles in normal brain function and neurological diseases. In vivo two-photon excitation laser scanning microscopy has the potential to reveal rapid, dynamic structural changes in cells in a variety of physiological and pathological conditions. The type of in vivo imaging method has been shown to affect the plasticity of dendritic spines of neurons, but the optimal in vivo imaging methods of astrocytes have not been established. We compared open-skull and thinned-skull imaging methods for two-photon laser microscopy of live astrocytes in neocortex of GFAP-GFP transgenic mice. The thinned-skull method provided stable image intensity and morphological features of astrocytes in vivo over at least one week, with no evidence of astrogliosis. In contrast, the open-skull method resulted in significant changes in image intensity and induced astrogliosis. The thinned-skull method is the preferred approach for in vivo imaging of astrocytes under most conditions involving gross astrocyte modulation or causing astrogliosis.

Seizures may directly cause brain injury by disrupting the structure and function of synapses. Previous studies using in vivo time-lapse imaging have demonstrated an acute beading of dendrites and loss of dendritic spines immediately following status epilepticus, but the effects of brief seizures and the long-term evolution of this dendritic injury are unknown. Here, we examined the effects of seizures of varying durations on dendritic structure over several weeks using in vivo multiphoton imaging with kainate-induced seizures in mice. The degree of dendritic injury was directly dependent on the duration of the seizures, with seizures lasting more than 30 min (status epilepticus) resulting in a greater than 75% spine loss. However, even brief seizures (

Posttraumatic epilepsy is a major source of disability following traumatic brain injury (TBI) and a common cause of medically-intractable epilepsy. Previous attempts to prevent the development of posttraumatic epilepsy with treatments administered immediately following TBI have failed. Recently, the mammalian target of rapamycin complex 1 (mTORC1) pathway has been implicated in mechanisms of epileptogenesis and the mTORC1 inhibitor, rapamycin, has been proposed to have antiepileptogenic effects in preventing some types of epilepsy. In this study, we have tested the hypothesis that rapamycin has antiepileptogenic actions in preventing the development of posttraumatic epilepsy in an animal model of TBI. A detailed characterization of posttraumatic epilepsy in the mouse controlled cortical impact model was first performed using continuous video-EEG monitoring for 16 weeks following TBI. Controlled cortical impact injury caused immediate hyperactivation of the mTORC1 pathway lasting at least one week, which was reversed by rapamycin treatment. Rapamycin decreased neuronal degeneration and mossy fiber sprouting, although the effect on mossy fiber sprouting was reversible after stopping rapamycin and did not directly correlate with inhibition of epileptogenesis. Most posttraumatic seizures occurred greater than 10 weeks after TBI, and rapamycin treatment for one month after TBI decreased the seizure frequency and rate of developing posttraumatic epilepsy during the entire 16 week monitoring session. These results suggest that rapamycin may represent a rational treatment for preventing posttraumatic epilepsy in patients with TBI.