BGI Cross-Scale Coupling Space Connecting Regional Greenway and Community

At present, China is advancing its territory spatial planning, implementing the requirements of the Paris Agreement and the Convention on Biological Diversity through the construction of the GI, reducing the impact of urban development on climate change, improving ecosystem services, and maintaining sustainable urban development. Regional territory spatial planning provides a planning method for urban and regional green infrastructure. However, there is a lack of research on the green infrastructure construction mode connecting the boundary space of these two scales of greenway networks. Greenway systems must be highly connected to maintain basic ecological functions (Forman 1995, Urban 2001, Coulon 2004). In this paper, the concept of Boundary Green Infrastructure (BGI) is proposed, that is, the ecological space where the urban green infrastructure (UGI) network and regional green infrastructure (RGI) network intersect at the boundary of urban areas. BGI has the capability of connecting two levels of the greenway network. This paper selects greenway systems in six European cities as case studies. By calculating the patch landscape stability, the best BGI distance threshold range was determined, and the BGI range was determined by comparing the differences between patch importance indexes. This paper analyzes the spatial pattern of BGI and summarizes the BGI planning strategy suitable for the sustainable development of Chinese cities, which also provides a reference for the GI system in Europe. It has been proved that BGI can strengthen the connection between urban and regional greenway networks, improve ecological functions, and connect cross-scale greenway networks. Based on the above methods, this paper analyzes the current BGI indicators of Harbin (the capital of Heilongjiang Province, China) and optimizes the BGI of Harbin\u27s cross-scale greenway network. Thus, the landscape connectivity of the optimized greenway system can be improved, the ecological core area can be increased, and the ecological function can be advanced, which proves the feasibility of connecting the multi-scale greenway network with the BGI model

CD-CNN: A Partially Supervised Cross-Domain Deep Learning Model for Urban Resident Recognition

Driven by the wave of urbanization in recent decades, the research topic about migrant behavior analysis draws great attention from both academia and the government. Nevertheless, subject to the cost of data collection and the lack of modeling methods, most of existing studies use only questionnaire surveys with sparse samples and non-individual level statistical data to achieve coarse-grained studies of migrant behaviors. In this paper, a partially supervised cross-domain deep learning model named CD-CNN is proposed for migrant/native recognition using mobile phone signaling data as behavioral features and questionnaire survey data as incomplete labels. Specifically, CD-CNN features in decomposing the mobile data into location domain and communication domain, and adopts a joint learning framework that combines two convolutional neural networks with a feature balancing scheme. Moreover, CD-CNN employs a three-step algorithm for training, in which the co-training step is of great value to partially supervised cross-domain learning. Comparative experiments on the city Wuxi demonstrate the high predictive power of CD-CNN. Two interesting applications further highlight the ability of CD-CNN for in-depth migrant behavioral analysis.Comment: 8 pages, 5 figures, conferenc

Model and Algorithm for Linkage Disequilibrium Analysis in a Non-Equilibrium Population

The multilocus analysis of polymorphisms has emerged as a vital ingredient of population genetics and evolutionary biology. A fundamental assumption used for existing multilocus analysis approaches is Hardy–Weinberg equilibrium at which maternally- and paternally-derived gametes unite randomly during fertilization. Given the fact that natural populations are rarely panmictic, these approaches will have a significant limitation for practical use. We present a robust model for multilocus linkage disequilibrium analysis which does not rely on the assumption of random mating. This new disequilibrium model capitalizes on Weir’s definition of zygotic disequilibria and is based on an open-pollinated design in which multiple maternal individuals and their half-sib families are sampled from a natural population. This design captures two levels of associations: one is at the upper level that describes the pattern of cosegregation between different loci in the parental population and the other is at the lower level that specifies the extent of co-transmission of non-alleles at different loci from parents to their offspring. An MCMC method was implemented to estimate genetic parameters that define these associations. Simulation studies were used to validate the statistical behavior of the new model

Multi-Granularity Whole-Brain Segmentation Based Functional Network Analysis Using Resting-State fMRI

In this work, we systematically analyzed the effects of various nodal definitions, as determined by a multi-granularity whole-brain segmentation scheme, upon the topological architecture of the human brain functional network using the resting-state functional magnetic resonance imaging data of 19 healthy, young subjects. A number of functional networks were created with their nodes defined according to two types of anatomical definitions (Type I and Type II) each of which consists of five granularity levels of whole brain segmentations with each level linked through ontology-based, hierarchical, structural relationships. Topological properties were computed for each network and then compared across levels within the same segmentation type as well as between Type I and Type II. Certain network architecture patterns were observed in our study: (1) As the granularity changes, the absolute values of each node's nodal degree and nodal betweenness change accordingly but the relative values within a single network do not change considerably; (2) The average nodal degree is generally affected by the sparsity level of the network whereas the other topological properties are more specifically affected by the nodal definitions; (3) Within the same ontology relationship type, as the granularity decreases, the network becomes more efficient at information propagation; (4) The small-worldness that we observe is an intrinsic property of the brain's resting-state functional network, independent of the ontology type and the granularity level. Furthermore, we validated the aforementioned conclusions and measured the reproducibility of this multi-granularity network analysis pipeline using another dataset of 49 healthy young subjects that had been scanned twice

Thermoacoustic heat pump utilizing medium/low-grade heat sources for domestic building heating

Thermoacoustic heat pumps are a promising heating technology that utilizes medium/low-grade heat to reduce reliance on electricity. This study proposes a single direct-coupled configuration for a thermoacoustic heat pump, aimed at minimizing system complexity and making it suitable for domestic applications. Numerical investigations were conducted under typical household heating conditions, including performance analysis, exergy loss evaluation, and axial distribution of key parameters. Results show that the proposed thermoacoustic heat pump achieves a heating capacity of 5.7 kW and a coefficient of performance of 1.4, with a heating temperature of 300 °C and a heat-sink temperature of 55 °C. A comparison with existing absorption heat pumps reveals favorable adaptability for large temperature lift applications. A case study conducted in Finland over an annual cycle analyzes the economic and environmental performance of the system, identifying two distinct modes based on the driving heat source: medium temperature (≥250 °C) and low temperature (<250 °C), both of which exhibit favorable heating performance. When the thermoacoustic heat pump is driven by waste heat, energy savings of 20.1 MWh/year, emission reductions of 4143 kgCO$_2$/year, and total environmental cost savings of 1629 €/year are obtained. These results demonstrate the potential of the proposed thermoacoustic heat pump as a cost-effective and environmentally friendly option for domestic building heating using medium/low-grade heat sources

Measurement of solid–liquid mixing quality by using a uniform design method based on image analysis

Solid–liquid mixing has been a common industrial process operation. The measurement of solid–liquid mixing quality can help improve the efficiency of related industrial processes, but there is still a lack of an intuitive, accurate, and simple measurement method. As an important indicator to evaluate the solid–liquid mixing quality, the degree of solid suspension and the uniformity of solid distribution are directly related to mass transfer and reaction efficiency. Therefore, it is necessary to study the solid suspension and distribution in a solid–liquid system. In this work, the solid suspension and distribution of a solid–liquid system composed of glass beads–water stirred by the impeller are studied experimentally via digital image processing combined with statistical analysis. Specifically, images of solid–liquid mixing are first obtained using a camera and digitally processed. The area ratio of the solid in the image is proposed to reflect the degree of solid suspension, and the modified L2-star discrepancy (MD) is then used to quantify the uniformity of the solid distribution. Then, the solid–liquid mixing quality can be characterized by combining the area ratio and solid distribution. The feasibility of this method was proved by qualitative analysis of the solid–liquid mixing state and comparison with known studies. In addition, the effects of various stirring factors on the solid distribution were studied and discussed by using the proposed method. The results show that the method proposed in this paper can measure the quality of the solid–liquid mixing state more directly and is effective and accurate. Furthermore, it was used to find the best experimental parameters in this work. This method is also simpler and cheaper than many other methods. It is of great significance to improve the efficiency of chemical and metallurgical and other industrial processes