Explore the vast range of titles available.

In the technological revolution of the 21st century, autonomous driving technology is rapidly changing transportation modes, and path planning, as a key component, relies heavily on advanced algorithm optimization. The Multi-Arm Bandit (MAB) algorithm may become an efficient decision optimization tool in autonomous driving path planning. Because it can continuously experiment, learn, and quickly determine the optimal strategy to maximize profits under resource constraints. When applied to autonomous driving, the MAB algorithm may be able to demonstrate its advantages. In complex traffic environments, it dynamically adjusts strategies to adapt to constantly changing road conditions, plans safe and efficient driving paths, and quickly responds to unexpected situations to ensure driving safety. Compared with other algorithms, the learning and adaptability of MAB algorithm makes it particularly suitable for the dynamics and unpredictability of real-world driving scenarios. However, the practical application of MAB algorithm in autonomous driving faces challenges, including accurately evaluating path efficiency, efficiently processing large amounts of traffic data, and ensuring the stability and reliability of the algorithm. Further in-depth research and exploration are crucial for fully utilizing the advantages of MAB algorithm in path planning and promoting the sustainable development and enhancement of autonomous driving technology.

China’s Singles Day Shopping Festivals (SDSFs) have continuously attracted consumers in recent years. As large-scale online sales events, their atmospherics have not yet been systematically analyzed. The present study aims to develop a measurement scale named “shopping festival atmospherics” (SFA) to capture the major dimensions of the atmospherics created by SDSFs. Following a rigorous procedure, both qualitative and quantitative approaches are employed to develop the measurement scale. Finally, three dimensions (cultural cues, social cues, and online cues) that contain eighteen attributes are extracted. The present study also identifies several novel shopping atmospheric cues that have not been mentioned in the literature. The happily crowded environment (“ Renao ” in the Chinese language) is a positive atmospheric cue for Chinese participants. A fair shopping environment is also a positive atmospherics cue as participants worry about price scams. Finally, the limitations and suggestions for future research are presented at the end of the paper.

Cellular micronucleus detection plays an important role in pathological toxicology detection and early cancer diagnosis. To address the challenges of tiny targets, high inter-class similarity, limited sample data and class imbalance in the field of cellular micronucleus image detection, this paper proposes a lightweight network called MobileViT-MN (Micronucleus), which integrates a multilayer perceptual attention mechanism. Considering that limited data and class imbalance may lead to overfitting of the model, we employ data augmentation to mitigate this problem. Additionally, based on domain adaptation, we innovatively introduce transfer learning. Furthermore, a novel Deep Separation-Decentralization module is designed to implement the reconstruction of the network, which employs attention mechanisms and an alternative strategy of deep separable convolution. Numerous ablation experiments are performed to validate the effectiveness of our method. The experimental results show that MobileViT-MN obtains outstanding performance on the augmented cellular micronucleus dataset. Avg_Acc reaches 0.933, F1 scores 0.971, and ROC scores 0.965. Compared with other classical algorithms, MobileViT-MN is more superior in classification performance.

It is of great significance to clarify the ranges and states of subsurface coalfield spontaneous combustion areas for coal mining and disaster management. Since the spontaneous combustion of coal seams produces highly magnetic burnt rocks and high temperatures, magnetic and infrared remote sensing measurements are commonly used for detection. To infer the accurate ranges of highly magnetic burnt rocks, we propose a three-dimensional constrained magnetization vector inversion method based on coal seam information, which considers highly magnetic burnt rocks to be produced via the combustion of a coal seam and to have thermal remanence, and this method can more accurately obtain the ranges of magnetic source for deducing coalfield spontaneous combustion areas. Combined with infrared remote sensing temperature measurement data, we analyze the range, state, and future spread direction of coalfield spontaneous combustion areas in Liaoning Province, China, according to the relative positions of high-temperature areas and highly magnetic burnt rocks. Based on the inversion results, we divided the survey area into nine blocks and obtained corresponding interpretation results. The accuracy of the interpretation was verified through drilling. This provides comprehensive spontaneous combustion area information for coal mining and disaster management.

A disastrous form of pedestrian behavior is a stampede occurring in an event involving a large crowd in a panic situation. To deal with such stampedes, the possibility to increase the outflow by suitably placing a pillar or some other shaped obstacles in front of the exit has been demonstrated. We present a social force based genetic algorithm to optimize the best design of architectural entities to deal with large crowds. Unlike existing literature, our simulation results indicate that appropriately placing two pillars on both sides but not in front of the door can maximize the escape efficiency. Human experiments using 80 participants correspond well with the simulations. We observed a peculiar property named tangential momentum, the escape speed and the tangential momentum are found to be negatively correlated. The idea to reduce the tangential momentum has practical implications in crowd architectural design.

As an important supporting technology for carbon neutrality strategy, the combination of an integrated energy system and hydrogen storage is expected to become a key research direction. To address the insufficient flexibility of multi-energy coupling in the integrated energy system and the overall strategic demand of low-carbon development, a multi-storage integrated energy system architecture that includes electric storage, heat storage and hydrogen storage is established. Then, according to the system status factors, such as energy cost, response characteristics and energy storage status, a hierarchical energy supply control strategy focusing on the energy supply priority of energy storage units is proposed. NSGA-II-MOABC is created as the optimization algorithm to meet the demand of multi-energy coupling energy supply in the integrated energy system. Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. Based on the simulation example, the scheduling results of the multi-storage combined system are obtained, through comparative analysis, the addition of hydrogen storage can effectively improve the flexibility of system scheduling. Then, taking several scenarios as simulation examples, the hierarchical energy supply strategy can effectively reduce the system operation cost and carbon emission cost, and it also has a certain role in realizing the local consumption of renewable energy.

Climate change is significantly and enduringly impacting global agricultural supply chains (ASCs), underscoring the urgent need to enhance their climate resilience. This study aims to identify key strategies for building agricultural supply chain resilience (ASCRes) in the context of climate change and their interrelationships. Through a comprehensive literature review and expert consultations, a framework of 12 strategies was developed. Using survey data from 312 Chinese ASC companies, BP-DEMATEL-ISM and PLS-SEM methods were employed to conduct causal analysis and factor level evaluation. The results indicate that “diversification of agricultural products and supply chain (SC) networks,” “Agriculture 4.0 and digital transformation,” and “taking proactive climate action” are critical strategies to enhance ASCRes in the context of climate change. These findings can provide theoretical basis for farmers, ASC companies, and governments to cope with the impact of climate change, so as to build more robust ASC systems.

We have developed CRISPR-assisted RNA–protein interaction detection method (CARPID), which leverages CRISPR–CasRx-based RNA targeting and proximity labeling to identify binding proteins of specific long non-coding RNAs (lncRNAs) in the native cellular context. We applied CARPID to the nuclear lncRNA XIST, and it captured a list of known interacting proteins and multiple previously uncharacterized binding proteins. We generalized CARPID to explore binders of the lncRNAs DANCR and MALAT1, revealing the method’s wide applicability in identifying RNA-binding proteins. CARPID uses CRISPR technology to navigate biotin ligase to specific lncRNAs, which allows proximal labeling and thus the querying of RNA–protein interactions in living cells.

With the growing demand for contactless human–computer interaction in the smart home field, gesture recognition technology shows great market potential. In this paper, a sparse millimeter wave point cloud-based gesture recognition system, RaGeoSense, is proposed, which is designed for smart home scenarios. RaGeoSense effectively improves the recognition performance and system robustness by combining multiple advanced signal processing and deep learning methods. Firstly, the system adopts three methods, namely K-mean clustering straight-through filtering, frame difference filtering and median filtering, to reduce the noise of the raw millimeter wave data, which significantly improves the quality of the point cloud data. Subsequently, the generated point cloud data are processed with sliding sequence sampling and point cloud tiling to extract the spatio-temporal features of the action. To further improve the classification performance, the system proposes an integrated model architecture that combines GBDT and XGBoost for efficient extraction of nonlinear features, and utilizes LSTM gated loop units to classify the gesture sequences, thus realizing the accurate recognition of eight different one-arm gestures. The experimental results show that RaGeoSense performs well at different distances, angles and movement speeds, with an average recognition rate of 95.2%, which is almost unaffected by the differences in personnel and has a certain degree of anti-interference ability.

This work is concerned with investigating the effect of substrate hydrophobicity and zeta potential on the dynamics and kinetics of the initial stages of bacterial adhesion. For this purpose, bacterial pathogens Staphylococcus aureus and Escherichia coli O157:H7 were inoculated on the substrates coated with thin thiol layers (i.e., 1-octanethiol, 1-decanethiol, 1-octadecanethiol, 16-mercaptohexadecanoic acid, and 2-aminoethanethiol hydrochloride) with varying hydrophobicity and surface potential. The time-resolved adhesion data revealed a transformation from an exponential dependence to a square root dependence on time upon changing the substrate from hydrophobic or hydrophilic with a negative zeta potential value to hydrophilic with a negative zeta potential for both pathogens. The dewetting of extracellular polymeric substances (EPS) produced by E . coli O157:H7 was more noticeable on hydrophobic substrates, compared to that of S . aureus , which is attributed to the more amphiphilic nature of staphylococcal EPS. The interplay between the timescale of EPS dewetting and the inverse of the adhesion rate constant modulated the distribution of E . coli O157:H7 within microcolonies and the resultant microcolonial morphology on hydrophobic substrates. Observed trends in the formation of bacterial monolayers rather than multilayers and microcolonies rather than isolated and evenly spaced bacterial cells could be explained by a colloidal model considering van der Waals and electrostatic double-layer interactions only after introducing the contribution of elastic energy due to adhesion-induced deformations at intercellular and substrate-cell interfaces. The gained knowledge is significant in the context of identifying surfaces with greater risk of bacterial contamination and guiding the development of novel surfaces and coatings with superior bacterial antifouling characteristics.