Service Quality Evaluation Model of Public Living Facilities in a Community

Accurate evaluating the service quality of public living facilities in a community by quantitative method is significant to urban planning. However, the performances of existing methods are usually limited for service quality evaluation due to single data source or single index. To solve the above problems, we propose a service quality evaluation model of public living facilities in a community. Firstly, POI data and subjective residents\u27 satisfaction evaluation data was pre-processed for data preparation. Then, the four evaluation indicators included in the model were established, namely, accessibility, diversity, selectivity, and satisfaction. Finally, after the completion of the calculation of the four indexes, standardized processing of the calculation results was performed, and the entropy method was used to assign different weights to the indexes, thereby achieving the quantitative evaluation of the service quality of community public living facilities. We chose the central urban area of Chengdu, China, as a case study for modeling analysis, and the case study successfully estimated the service quality and spatial difference of community living facilities. The results of this model can provide a reliable basis for future urban planning and the location of commercial facilities

Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment

Large Language Models (LLMs) can acquire extensive world knowledge through pre-training on large corpora. However, due to exposure to low-quality data, LLMs may exhibit harmful behavior without aligning with human values. The dominant approach for steering LLMs towards beneficial behavior involves Reinforcement Learning with Human Feedback (RLHF), with Proximal Policy Optimization (PPO) serving as the default RL optimizer. Despite its effectiveness, PPO has limitations when optimizing rewards trained from comparison-based loss. Primarily, PPO is not invariant to equivalent reward functions containing identical preference information due to the need to calibrate the reward scale. Additionally, PPO's necessity for token-wise updates introduces complexity in both function approximation and algorithm design compared to trajectory-wise optimization. This paper proposes a new framework, reinforcement learning with relative feedback, and a novel trajectory-wise policy gradient algorithm, Pairwise Proximal Policy Optimization (P3O) that operates directly on comparative rewards. We show theoretically that P3O is invariant to equivalent rewards and avoids the complexity of PPO. Empirical evaluations demonstrate that P3O outperforms PPO in the KL-Reward trade-off and can align with human preferences as well as or better than prior methods. In summary, this work introduces a simpler yet effective approach for aligning LLMs to human preferences through relative feedback.Comment: 19 pages, 5 figure

Local and global convolutional transformer-based motor imagery EEG classification

Transformer, a deep learning model with the self-attention mechanism, combined with the convolution neural network (CNN) has been successfully applied for decoding electroencephalogram (EEG) signals in Motor Imagery (MI) Brain-Computer Interface (BCI). However, the extremely non-linear, nonstationary characteristics of the EEG signals limits the effectiveness and efficiency of the deep learning methods. In addition, the variety of subjects and the experimental sessions impact the model adaptability. In this study, we propose a local and global convolutional transformer-based approach for MI-EEG classification. The local transformer encoder is combined to dynamically extract temporal features and make up for the shortcomings of the CNN model. The spatial features from all channels and the difference in hemispheres are obtained to improve the robustness of the model. To acquire adequate temporal-spatial feature representations, we combine the global transformer encoder and Densely Connected Network to improve the information flow and reuse. To validate the performance of the proposed model, three scenarios including within-session, cross-session and two-session are designed. In the experiments, the proposed method achieves up to 1.46%, 7.49% and 7.46% accuracy improvement respectively in the three scenarios for the public Korean dataset compared with current state-of-the-art models. For the BCI competition IV 2a dataset, the proposed model also achieves a 2.12% and 2.21% improvement for the cross-session and two-session scenarios respectively. The results confirm that the proposed approach can effectively extract much richer set of MI features from the EEG signals and improve the performance in the BCI applications

Mechanical model of deformation-seepage-erosion for Karst collapse column water inrush and its application

With the extension of coal mining in China, fault water inrush has become one of major disasters threatening the safety of coal mine production. Based on the research results related to the mining-induced fault water inrush, this paper proposes a conceptual model of water inrush caused by the erosion synergy of mining-induced rock mass damage rupture and fractured rock mass (fault), derives the permeability evolution equation of the two media, and systematically constructs the cooperative disaster causing mechanism model between mining failure and particle erosion inside faults. The numerical simulation is conducted to study the deformation and failure of rock mass, the particle transport in faults and the evolution characteristics of seepage channel, and systematically explain the temporal and spatial evolution mechanism of seepage catastrophe caused by mining-induced fault inrush. The results show that: ① With the continuous advancement of working face, the damage field of mine floor rock mass is connected with the fault erosion fracture, forming a seepage path of aquifer-fault-mining fracture-working face, and with the increase of erosion time, it finally develops into several dominant water diversion channels, resulting in a sharp increase in water inflow at the working face and a lagging water inrush. ② With the increase of seepage time, the water inflow and fracture opening degree inside faults all show three stages: slow change, sudden increase and stable, and the erosion particle concentration shows a trend of first increasing and then decreasing. ③ Under the geological conditions of the mining area studied in this paper, in order to prevent the occurrence of fault water inrush, the methods such as advanced grouting or leaving water prevention coal pillars can be adopted, and the advance grouting time should be before the bottom plate fracture zone connects faults, if grouting is not applied, the width of the reasonable water prevention coal pillar should not be less than 20 m

Screening and fermentation medium optimization of a strain favorable to Rice–fish Coculture

Rice–fish coculture (RF) is a small ecosystem in which microorganisms are widely distributed in the fish, water environment, soil, and plants. In order to study the positive effects of microorganisms on common carp and rice in the RF ecosystem, a total of 18 strains with growth-promoting ability were screened from common carp (Cyprinus carpio) gut contents, among which three strains had the ability to produce both DDP-IV inhibitors and IAA. The strain with the strongest combined ability, FYN-22, was identified physiologically, biochemically, and by 16S rRNA, and it was initially identified as Bacillus licheniformis. As the number of metabolites secreted by the strain under natural conditions is not sufficient for production, the FYN-22 fermentation medium formulation was optimized by means of one-factor-at-a-time (OFAT) experiments and response surface methodology (RSM). The results showed that, under the conditions of a soluble starch concentration of 10.961 g/l, yeast concentration of 2.366 g/l, NH4Cl concentration of 1.881 g/l, and FeCl3 concentration of 0.850 g/l, the actual measured number of FYN-22 spores in the fermentation broth was 1.913 × 109 CFU/ml, which was 2.575-fold improvement over the pre-optimization value. The optimized fermentation solution was used for the immersion operation of rice seeds, and, after 14 days of incubation in hydroponic boxes, the FYN-22 strain was found to have a highly significant enhancement of 48.31% (p < 0.01) on the above-ground part of rice, and different degrees of effect on root length, fresh weight, and dry weight (16.73, 17.80, and 21.97%, respectively; p < 0.05). This study may provide new insights into the fermentation process of Bacillus licheniformis FYN-22 and its further utilization in RF systems

Solid-Gas Flow Characteristics of Drilling Bit-Rod Integral Structure

Sampling based on negative pressure pneumatic conveying method is an important theory in determining coal bed methane (CBM) content. The coal-gas two-phase flow path is an integrated structure composed of polycrystalline diamond compact (PDC) bit and drilling rod. In this work, CFD-DEM coupling numerical simulation was adopted to study the solid-gas flow characteristics of an integrated structure having PDC bit and gas velocity pipe under different gas velocity and solid mass flow rates. The results showed that the gas phase had a reverse velocity zone at the PDC bit. The reverse velocity zone gradually decreased with increase of gas velocity. In addition, a high-velocity band in drill pipe became apparent for the particle phase; there was an obvious bottom flow characteristic at the PDC bit and an area of the highest layer thickness in the drill pipe. Under the same gas velocity, the location of the area of the highest layer thickness shifted from the drill bit with the increase of solid mass flow rate. Increase in the gas velocity resulted in a rapid increase of the velocity of coal particles, while the bottom flow characteristics of coal particles weakened and the suspension flow gradually appeared. The results of this study are of great significance for optimizing the gas velocity based on negative pressure pneumatic conveying technique

HGF Spatial–Spectral Fusion Method for Hyperspectral Images

Quantitative studies on surface elements require satellite hyperspectral images with high spatial resolution. The identification of different surface elements requires different characteristic bands and their corresponding optimal spatial–spectral fusion methods. To address these problems, the harmonic analysis (HA), guided filtering, and Gram–Schmidt (GS) algorithms were integrated to propose a spatial–spectral fusion method called HGF. The fusion experiment and validation of the hyperspectral images of GaoFen-5 (GF-5) and ZY1-02D were conducted separately using the HGF method, and the fusion effect was evaluated in three band intervals according to the spectral response of the ground class. First, HGF was used to fuse the GF-5 and GaoFen-1 (GF-1) images, and the fusion effect was evaluated both qualitatively and quantitatively. Second, the optimal fusion method was selected for the corresponding characteristic bands of the different surface elements. Finally, the hyperspectral image obtained by ZY1-02D and multispectral image of Sentinel-2B were used for validation to improve the accuracy and efficiency of satellite hyperspectral images in quantitative studies. The results show that for further studies on soil, vegetation, and water bodies, the best fusion methods in the 390–730, 730–1400, and 1400–2260 nm intervals are the GS, HGF, and HGF algorithms, respectively. Further analysis showed that the HGF or GS methods can be selected for quantitative studies on vegetation and water bodies and that the HGF method exhibits outstanding advantages for quantitative analysis of each soil element

A numerical solution to the effects of surface roughness on water–coal contact angle

Abstract Coal dust is a great threat to coal mine workers' health and safety in coal mine production. Wet dust removal is one of the effective dust removal methods. As a solid, coal has different rough surfaces, which have a certain effect on the wetting effect of coal. In this paper, three coal samples with different surface wettability are used as the research objects. Phase-field interface tracking method is used to simulate the wetting of droplets on rough surfaces. From the simulation results, it can be concluded that the influence of the rough interface on the contact angle of the droplets is in accordance with the change rule described in the Wenzel model. As the roughness increases, the contact angle of the hydrophilic lignite surface gradually decreases. As the roughness increases, the contact angle of hydrophobic coking coal gradually increases. The change trend of the contact on the surface of weakly hydrophilic anthracite coal is the same as that of lignite. Due to the local and global differences, the contact angles obtained from the numerical model are slightly different from the values calculated from the Wenzel model

Evolution Mechanism of Water-Conducting Channel of Collapse Column in Karst Mining Area of Southwest China

There are many karst collapse columns in coal seam roof in the southern coal field in China, which are different from those in coal seam floor in the northern coal field, due to the stratum characteristics. The karst collapse column in coal seam roof tends to reactivate and conduct water and induce the serious water inrush disaster, when the karst collapse column communicates with the overlying aquifer. In order to reveal the evolution mechanism of water-conducting channel of collapse column in karst mining area of southwest China, the aquifers and water inflow rule in 1908 working face in Qianjin coal mine are analyzed. Besides, the particle size distribution and mineral component of collapse column are researched by the X-ray diffraction test and the screening method, which are the basis for researching the water inrush mechanism in karst collapse column. On this basis, the water inrush of roof collapse column under the influence of mining is researched by establishing the numerical calculation model with the UDEC numerical software. The results show that the water flowing into the 1908 working face comes from the Changxing formation aquifer and Yulongshan formation aquifer above the coal seam, and the proportion of coarse particles and fine particles in collapse column is 89.86% and 10.14%, respectively. With the advance of working face, the water-conducting channel connected the working face with the aquifer, or the surface is formed by collapse pits, karst caves, and collapse column. The research results can be treated as an important basis for the water-preserved mining in southern coal field in China