Unified Near-field and Far-field Localization with Holographic MIMO

Localization which uses holographic multiple input multiple output surface such as reconfigurable intelligent surface (RIS) has gained increasing attention due to its ability to accurately localize users in non-line-of-sight conditions. However, existing RIS-enabled localization methods assume the users at either the near-field (NF) or the far-field (FF) region, which results in high complexity or low localization accuracy, respectively, when they are applied in the whole area. In this paper, a unified NF and FF localization method is proposed for the RIS-enabled localization system to overcome the above issue. Specifically, the NF and FF regions are both divided into grids. The RIS reflects the signals from the user to the base station~(BS), and then the BS uses the received signals to determine the grid where the user is located. Compared with existing NF- or FF-only schemes, the design of the location estimation method and the RIS phase shift optimization algorithm is more challenging because they are based on a hybrid NF and FF model. To tackle these challenges, we formulate the optimization problems for location estimation and RIS phase shifts, and design two algorithms to effectively solve the formulated problems, respectively. The effectiveness of the proposed method is verified through simulations

On the microstructure and mechanical properties of silver-bearing antibacterial CD4MCu duplex stainless steels:Solid solution temperature

The Ag-bearing antibacterial stainless steel has attracted substantial attention in the field of bacterial proliferation prevention. In this study, a Cu-Ag alloy was incorporated into a CD4MCu duplex stainless steel (DSS) to produce a good antibacterial property. The Ag-bearing CD4MCu duplex stainless steel samples were conducted solid solution treatment at various temperatures. The effects of the solid solution temperature on the microstructure, mechanical and corrosion properties, as well as silver ion release characteristics and antibacterial properties were investigated. Results show that apart from the original alpha, gamma phases, Ag-bearing phases were formed in all samples after solid solution at different temperatures. The volume fraction of gamma and Ag-bearing phases decrease with increasing solution temperature. The tensile strength, hardness, elongation, and corrosion resistance first decrease and then increase along with the increase in the solid solution temperature. The heat treatment conducted at 1150 degrees C increases the strength, the hardness, the pitting corrosion resistance, and the antimicrobial capability simultaneously. The antibacterial rates of all the Ag-bearing CD4MCu duplex stainless steel samples after solid solution treatment are above 99%, indicating their good anti-bacterial capabilities

Effect of Quench Polish Quench Nitriding Temperature on the Microstructure and Wear Resistance of SAF2906 Duplex Stainless Steel

The effect of quench polish quench (QPQ) nitriding temperature on the microstructure and wear resistance of SAF2906 duplex stainless steel was investigated. Results showed the surface of the nitrided samples was composed of an oxidized layer, a loose compound layer, a compact compound layer, and a diffusion layer. The oxidized layer was composed of Fe3O4. The main phases of the loose compound layer were CrN, alpha(N), Fe2-3N, and Fe3O4. The compact compound layer was composed of CrN, alpha(N), and Fe2-3N. In the diffusion layer, CrN and expanded austenite (S) were the main phases. The nitrided layer thickness increased from 20 to 41 mu m with an increasing temperature of 570 to 610 degrees C. When the nitriding temperature was above 590 degrees C, the precipitates in the diffusion layer became coarsened, and their morphologies gradually changed from spherical particulate to rod-like and flocculent-like. Tribotests showed the cumulative mass loss of QPQ-treated samples was much lower than that of the substrate. The cumulative mass loss of the samples nitrided at 610 degrees C was higher than that at 570 degrees C during the first 29 h. When the test time was over 29 h, the former was lower than the latter

Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method

The stochastic shortest path problem is of crucial importance for the development of sustainable transportation systems. Existing methods based on the probability tail model seek for the path that maximizes the probability of arriving at the destination before a deadline. However, they suffer from low accuracy and/or high computational cost. We design a novel Q-learning method where the converged Q-values have the practical meaning as the actual probabilities of arriving on time so as to improve accuracy. By further adopting dynamic neural networks to learn the value function, our method can scale well to large road networks with arbitrary deadlines. Experimental results on real road networks demonstrate the significant advantages of our method over other counterparts

Self-identity matters: an extended theory of planned behavior to decode tourists’ waste sorting intentions

Waste sorting is a practical way of handling the garbage and an effective strategy for facilitating sustainable waste management. This research extended the theory of planned behavior (TPB) with self-identity and moral norms to predict waste sorting intentions in a heritage context of tourism. A total of 403 valid self administrated questionnaires were achieved at a heritage destination in China. The results indicated that: (1) TPB variables (i.e., attitudes toward the behavior, subjective norms, and perceived behavioral control), self-identity, and moral norms were all directly and positively linked to tourists’ waste sorting intentions, respectively; (2) self-identity indirectly influenced tourists’ waste sorting intentions through the mediation of moral norms; and (3) the integrated model exhibited better predictive utility than any single model. This research contributes to the literature on waste management in the context of tourism by extending TPB with identity and personal normative constructs. It also provides practical implications for destination managers to leverage tourists’ self-identity and moral norms for sustainable management

MicroRNA-519a promotes proliferation and inhibits apoptosis of hepatocellular carcinoma cells by targeting FOXF2

AbstractRecent studies report that microRNA-519a (miR-519a) is a novel oncomir, which facilitates the onset and progression of human cancers. However, the clinical significance of miR-519a and its functional role and underlying mechanisms in hepatocellular carcinoma (HCC) are poorly investigated. In the present study, elevated expression of miR-519a was observed in HCC tissues compared with adjacent non-tumor tissues. The increased level of miR-519a expression was significantly correlated with adverse clinical features of HCC including hepatitis B virus (HBV) infection, large tumor size, cirrhosis and advanced tumor-node-metastasis tumor stage. Furthermore, high expression of miR-519a was prominently associated with a poorer 5-year overall survival and recurrence-free survival of HCC patients. Gain- and loss-of function experiments showed that miR-519a overexpression enhanced proliferation and reduced apoptosis of Huh7 cells. By contrast, miR-519a knockdown inhibited SMMC-7721 cell proliferation and induced apoptosis. Importantly, up-regulation of miR-519a reduced the expression of FOXF2 mRNA and protein in Huh7 cells, while down-regulation of miR-519a resulted in increased expression of FOXF2 in SMMC-7721 cells. An inverse correlation between mRNA levels of miR-519a and FOXF2 was observed in HCC tissues. Thus, Forkhead box F2 (FOXF2) was identified as a downstream target of miR-519a in HCC. Mechanistically, the effects of miR-519a knockdown on SMMC-7721 cells were abrogated by FOXF2 repression. In conclusion, miR-519a is a novel prognostic predictor for HCC patients and it may potentiate proliferation and inhibits apoptosis of HCC cells by targeting FOXF2

Efficient Neural Neighborhood Search for Pickup and Delivery Problems

We present an efficient Neural Neighborhood Search (N2S) approach for pickup and delivery problems (PDPs). In specific, we design a powerful Synthesis Attention that allows the vanilla self-attention to synthesize various types of features regarding a route solution. We also exploit two customized decoders that automatically learn to perform removal and reinsertion of a pickup-delivery node pair to tackle the precedence constraint. Additionally, a diversity enhancement scheme is leveraged to further ameliorate the performance. Our N2S is generic, and extensive experiments on two canonical PDP variants show that it can produce state-of-the-art results among existing neural methods. Moreover, it even outstrips the well-known LKH3 solver on the more constrained PDP variant. Our implementation for N2S is available online.Comment: Accepted at IJCAI 2022 (short oral

The role of social capital in predicting tourists’ waste sorting intentions in rural destinations: extending the theory of planned behavior

Improper waste disposal of tourists has detrimental impacts on the environment, economy, and people in rural destinations. Separating at the source is an effective means to mitigate these adverse impacts on rural destinations. Hence, identifying factors influencing tourists’ waste sorting intentions in rural destinations is critical to the sustainability of rural tourism and rural land. However, few studies focus on tourists’ waste sorting intentions. Drawing on the theory of planned behavior (TPB) and social capital, this research examined the determinants of tourists’ waste sorting intentions in rural destinations. A total of 395 valid questionnaires were collected from a rural destination in Huzhou, China. The results indicated that: (1) all TPB variables, i.e., attitude toward the behavior, subjective norms, and perceived behavioral control, positively and directly affect tourists’ waste sorting intentions; (2) interpersonal trust directly and positively influences tourists’ waste sorting intentions; (3) subjective norms, perceived behavioral control, interpersonal trust, and emotional bonding indirectly influence tourists’ waste sorting intentions through the mediation of attitude toward the behavior; (4) emotional bonding does not directly affect tourists’ waste sorting intentions, but the link is established through the mediation of attitude toward the behavior. This research expands the body of knowledge by integrating individuals’ psychological elements with their social contexts. The findings offer some theoretical and managerial implications for understanding how tourists’ social contexts facilitate tourists’ waste sorting intentions

The effect of pro-environmental destination image on resident environmental citizenship behavior: the mediating roles of satisfaction and pride

Despite the lengthy history of the research on destination image from various perspectives, how pro-environmental destination image promotes resident environmental citizenship behavior remains underexplored. Grounded in the cognition–affect–behavior (CAB) model, this research investigated the translation of pro-environmental destination image into resident environmental citizenship behavior via satisfaction and pride. Data were collected using an intercept survey approach from a tourism village recognized as one of the best in the world by UNWTO. The results indicated that a pro-environmental destination image has a positive impact on resident environmental citizenship behavior in the private and public domains. Furthermore, resident satisfaction and pride serve as mediators between pro-environmental destination image and resident environmental citizenship behavior. This research contributes to the literature on resident environmental citizenship behavior by considering the role of pro-environmental destination image. The findings provide practical implications for fostering environmental citizenship behavior through the presentation of pro-environmental images to residents and eliciting their positive emotions