Research on Spatial and Dynamic Planning Methods for Settlement Buildings Based on Data Mining

Traditional settlements are widely concerned by academic circles for their unique settlement patterns, exquisite residential buildings, and rich historical and cultural connotations, and their protection and development is an important proposition for rural revitalization. Therefore, from the perspective of big data mining (BDM), this paper explores its application in architectural space and settlement protection of traditional settlements in Hainan and provides new ideas for the protection and renewal of traditional settlements in Hainan. The attribute elements of spatial data of settlement groups are analyzed by the decision tree classification mining method. In order to avoid the multivalued tendency of ID3 algorithm and improve the efficiency of decision tree generation by ID3 algorithm, an improved ID3 algorithm is proposed by introducing user interest and simplifying the calculation process of the algorithm. At the same time, the graph theory recognition method of grid pattern is proposed. Aiming at the intersection graph and direction relation graph of straight line pattern, grid pattern recognition is realized by solving the connectivity, intersection, and subsequent construction of the maximum complete subgraph. Experiments show that the improved ID3 algorithm has better running efficiency than the parallel algorithm based on cooccurrence matrix. The analysis of the architectural space of traditional settlements in Hainan will help us better grasp social activities and provide direction for the protection and renewal of traditional settlements from the perspective of tourists and residents.

Toroidal topology of population activity in grid cells

The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment1. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations2, and are organized in modules3 that collectively form a population code for the animal’s allocentric position1. The invariance of the correlation structure of this population code across environments4,5 and behavioural states6,7, independent of specific sensory inputs, has pointed to intrinsic, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern1,8–11. However, whether grid cell networks show continuous attractor dynamics, and how they interface with inputs from the environment, has remained unclear owing to the small samples of cells obtained so far. Here, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold, as expected in a two-dimensional CAN. Positions on the torus correspond to positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep, as predicted by CAN models for grid cells but not by alternative feedforward models12. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.

Investigation On Mechanism of Ultrasonic Welding AZ31B / 5052 Joint With Laser Texturing On Mental Surface

The ultrasonic welding was carried out to improve the quality of dissimilar Al/Mg alloys joint. The effects of laser texturing on the microstructure and mechanism of AZ31B/5052 joint connected by ultrasonic welding were also investigated. A series of laser texturing experiments on Al alloy (5052) and Mg alloy (AZ31B) were performed to determine the process parameters and their ef-fect on ultrasonic weld quality, especially on weld strength. Little effect was attained by opti-mizing welding parameters in improving mechanical properties. Both welding parameters and different texture pattern were investigated to obtain good weld quality. The connection mecha-nisms of joints were discussed based on the analysis of weld interface morphology, microstruc-ture evolution. Mechanical analysis of particle and movement of material atoms were analyzed in the study to explain the connect mechanism. The results show that the better lock-interface and lager lap shear strength were attained by laser texture addition and optimal welding parameters. Compared with the untextured joint, swirling bonding interface was obtained after the laser tex-ture. The laser texture with grid pattern was found to raise the strength up to 26% higher maxi-mum tensile-shear load than the joints obtained with the untextured surface.

A Cerebral Organoid Connectivity Apparatus to Model Neuronal Tract Circuitry

Mental disorders have high prevalence, but the efficacy of existing therapeutics is limited, in part, because the pathogenic mechanisms remain enigmatic. Current models of neural circuitry include animal models and post-mortem brain tissue, which have allowed enormous progress in understanding the pathophysiology of mental disorders. However, these models limit the ability to assess the functional alterations in short-range and long-range network connectivity between brain regions that are implicated in many mental disorders, e.g., schizophrenia and autism spectrum disorders. This work addresses these limitations by developing an in vitro model of the human brain that models the in vivo cerebral tract environment. In this study, microfabrication and stem cell differentiation techniques were combined to develop an in vitro cerebral tract model that anchors human induced pluripotent stem cell-derived cerebral organoids (COs) and provides a scaffold to promote the formation of a functional connecting neuronal tract. Two designs of a Cerebral Organoid Connectivity Apparatus (COCA) were fabricated using SU-8 photoresist. The first design contains a series of spikes which anchor the CO to the COCA (spiked design), whereas the second design contains flat supporting structures with open holes in a grid pattern to anchor the organoids (grid design); both designs allow effective media exchange. Morphological and functional analyses reveal the expression of key neuronal markers as well as functional activity and signal propagation along cerebral tracts connecting CO pairs. The reported in vitro models enable the investigation of critical neural circuitry involved in neurodevelopmental processes and has the potential to help devise personalized and targeted therapeutic strategies.

Knowledge Based Prediction of Standard Penetration Resistance of Soil Using Geotechnical Database

The current study aimed at predicting standard penetration resistance (N) of soil using particle sizes and Atterberg's limits. The geotechnical database was created subsequent to the field and laboratory testing. The sample collection points were distributed in a mesh grid pattern to have uniform sampling consistency. Artificial Neural Networks (ANN) were trained on the database to build a knowledge-based understanding of the interrelation of the given soil parameters. To check the efficacy of the model, the validation was carried out by predicting standard penetration resistance (N) for another 30 samples which were not included in the training data (444 samples). The trained ANN model has been found to predict N values in close agreement with the N values measured in the field. The novelty of the research work is the standard penetration prediction employing basic physical properties of soil. This proves the efficacy of the proposed model for the target civil engineering application. Doi: 10.28991/CEJ-SP2021-07-01 Full Text: PDF

Effect of reward on electrophysiological signatures of grid cell population activity in human spatial navigation

The regular equilateral triangular periodic firing pattern of grid cells in the entorhinal cortex is considered a regular metric for the spatial world, and the grid-like representation correlates with hexadirectional modulation of theta (4–8 Hz) power in the entorhinal cortex relative to the moving direction. However, researchers have not clearly determined whether grid cells provide only simple spatial measures in human behavior-related navigation strategies or include other factors such as goal rewards to encode information in multiple patterns. By analysing the hexadirectional modulation of EEG signals in the theta band in the entorhinal cortex of patients with epilepsy performing spatial target navigation tasks, we found that this modulation presents a grid pattern that carries target-related reward information. This grid-like representation is influenced by explicit goals and is related to the local characteristics of the environment. This study provides evidence that human grid cell population activity is influenced by reward information at the level of neural oscillations.

Effect of Infill Pattern and Lattice Structure on the Mechanical Properties of 3D Printed Metal Polylactide Filament

The purpose of this given research is to study the mechanical properties of the printed metal polylactide filament due to the recent growth of 3D printing technology. It had been widely used in many industries, but some consequences influence the material properties of printed parts and cause anisotropy. The consequences mentioned are based on parameters that have been involved in causing changes in the mechanical properties of the printed specimen such as the infill pattern, infill density, printing temperature, surrounding temperature, printing orientation, and printing speed. This paper will emphasize more on the infill patterns and choosing the better infill pattern for a printed material using copper metal polylactide (PLA) filament in terms of better strength. The strength of the printed material can be analysed using the tensile test method according to ASTM D68-10 standards. so that Young’s Modulus can be evaluated based on stress and strain data collected from each specimen that has been tested. This experiment is conducted twice using PLA and copper metal PLA whereby the PLA is used as a comparison towards copper metal PLA. Based on previous studies shows honeycomb has the strongest infill pattern but after running through the certain test it is found out that grid pattern has the qualities for FDM processes which will be discussed further.

Effects of infill pattern and density on wear performance of FDM-printed acrylonitrile-butadiene-styrene parts

Acrylonitrile-butadiene-styrene test specimens were additively manufactured by fused deposition method to investigate the effects of infill pattern and density on wear rate, coefficient of friction, wear mechanisms, and microscopic wear characterization. The surface morphology of specimens was characterized using a scanning electron microscope. Under constant parameters of applied load, sliding speed, and sliding time, wear tests were carried out at room temperature. The study revealed that a grid pattern of high infill density and a honeycomb pattern of low infill density showed the lowest wear rate and lowest coefficient of friction compared to the rectilinear pattern. Infill pattern and density affected the wear rate behavior of specimens directly. Moreover, adhesion between additively manufactured layers along with surface texture affects the wear behavior and wear rate. Increasing infill density allowed poor cooling of previously built layers. Longer process time results in rough surfaces.