An Adaptive POI Recommendation Algorithm by Integrating User's Temporal and Spatial Features in LBSNs

In location-based social networks (LBSNs), exploit several key features of points-of-interest (POIs) and users on precise POI recommendation be significant. In this work, a novel POI recommendation pipeline based on the convolutional neural network named RecPOID is proposed, which can recommend an accurate sequence of top-k POIs and considers only the effect of the most similar pattern friendship rather than all user’s friendship. We use the fuzzy c-mean clustering method to find the similarity. Temporal and spatial features of similar friends are fed to our Deep CNN model. The 10-layer convolutional neural network can predict longitude and latitude and the Id of the next proper locations; after that, based on the shortest time distance from a similar pattern’s friendship, select the smallest distance locations. The proposed structure uses six features, including user’s ID, month, day, hour, minute, and second of visiting time by each user as inputs. RecPOID based on two accessible LBSNs datasets is evaluated. Experimental outcomes illustrate considering most similar friendship could improve the accuracy of recommendations and the proposed RecPOID for POI recommendation outperforms state-of-the-art approaches.

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The role of action effects in motor sequence planning and execution: exploring the influence of temporal and spatial effect anticipation

Psychological Research ◽

10.1007/s00426-021-01525-2 ◽

2021 ◽

Author(s):

Rachel M. Brown ◽

Erik Friedgen ◽

Iring Koch

Keyword(s):

Action Planning ◽

Spatial Effects ◽

Motor Sequence ◽

Action Sequence ◽

Sequential Action ◽

Spatial Features ◽

Temporal Features ◽

Action Sequences ◽

Temporal And Spatial ◽

Anticipation Effect

AbstractActions we perform every day generate perceivable outcomes with both spatial and temporal features. According to the ideomotor principle, we plan our actions by anticipating the outcomes, but this principle does not directly address how sequential movements are influenced by different outcomes. We examined how sequential action planning is influenced by the anticipation of temporal and spatial features of action outcomes. We further explored the influence of action sequence switching. Participants performed cued sequences of button presses that generated visual effects which were either spatially compatible or incompatible with the sequences, and the spatial effects appeared after a short or long delay. The sequence cues switched or repeated across trials, and the predictability of action sequence switches was varied across groups. The results showed a delay-anticipation effect for sequential action, whereby a shorter anticipated delay between action sequences and their outcomes speeded initiation and execution of the cued action sequences. Delay anticipation was increased by predictable action switching, but it was not strongly modified by the spatial compatibility of the action outcomes. The results extend previous demonstrations of delay anticipation to the context of sequential action. The temporal delay between actions and their outcomes appears to be retrieved for sequential planning and influences both the initiation and the execution of actions.

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G-DAN-SNR: An improved Personalized POI recommendation algorithm based on gating and attention mechanism

10.1109/iccsnt53786.2021.9615459 ◽

2021 ◽

Author(s):

Ming Huang ◽

Yijie Fu ◽

Xuan Jiao

Keyword(s):

Attention Mechanism ◽

Recommendation Algorithm ◽

Poi Recommendation

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Dynamic response of microglia/macrophage polarization following demyelination in mice

Journal of Neuroinflammation ◽

10.1186/s12974-019-1586-1 ◽

2019 ◽

Vol 16 (1) ◽

Cited By ~ 6

Author(s):

Tianci Chu ◽

Yi Ping Zhang ◽

Zhisen Tian ◽

Chuyuan Ye ◽

Mingming Zhu ◽

...

Keyword(s):

Diffusion Tensor ◽

Macrophage Polarization ◽

Functional Decline ◽

Oligodendrocyte Progenitor Cells ◽

Spatial Features ◽

Lesion Pattern ◽

Temporal Features ◽

Temporal And Spatial ◽

Highly Correlated ◽

Focal Demyelination

Abstract Background The glial response in multiple sclerosis (MS), especially for recruitment and differentiation of oligodendrocyte progenitor cells (OPCs), predicts the success of remyelination of MS plaques and return of function. As a central player in neuroinflammation, activation and polarization of microglia/macrophages (M/M) that modulate the inflammatory niche and cytokine components in demyelination lesions may impact the OPC response and progression of demyelination and remyelination. However, the dynamic behaviors of M/M and OPCs during demyelination and spontaneous remyelination are poorly understood, and the complex role of neuroinflammation in the demyelination-remyelination process is not well known. In this study, we utilized two focal demyelination models with different dynamic patterns of M/M to investigate the correlation between M/M polarization and the demyelination-remyelination process. Methods The temporal and spatial features of M/M activation/polarization and OPC response in two focal demyelination models induced by lysolecithin (LPC) and lipopolysaccharide (LPS) were examined in mice. Detailed discrimination of morphology, sensorimotor function, diffusion tensor imaging (DTI), inflammation-relevant cytokines, and glial responses between these two models were analyzed at different phases. Results The results show that LPC and LPS induced distinctive temporal and spatial lesion patterns. LPS produced diffuse demyelination lesions, with a delayed peak of demyelination and functional decline compared to LPC. Oligodendrocytes, astrocytes, and M/M were scattered throughout the LPS-induced demyelination lesions but were distributed in a layer-like pattern throughout the LPC-induced lesion. The specific M/M polarization was tightly correlated to the lesion pattern associated with balance beam function. Conclusions This study elaborated on the spatial and temporal features of neuroinflammation mediators and glial response during the demyelination-remyelination processes in two focal demyelination models. Specific M/M polarization is highly correlated to the demyelination-remyelination process probably via modulations of the inflammatory niche, cytokine components, and OPC response. These findings not only provide a basis for understanding the complex and dynamic glial phenotypes and behaviors but also reveal potential targets to promote/inhibit certain M/M phenotypes at the appropriate time for efficient remyelination.

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Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates

Remote Sensing ◽

10.3390/rs12010171 ◽

2020 ◽

Vol 12 (1) ◽

pp. 171

Author(s):

Maria Lanfredi ◽

Rosa Coluzzi ◽

Vito Imbrenda ◽

Maria Macchiato ◽

Tiziana Simoniello

Keyword(s):

Annual Cycle ◽

Progressive Deformation ◽

Precipitation Regime ◽

Equilibrium Conditions ◽

Spatial Properties ◽

Spatial Features ◽

Precipitation Seasonality ◽

Temporal And Spatial ◽

Average Annual Precipitation ◽

Simulated Scenario

Seasonality is a fundamental feature of environmental systems which critically depend on the climate annual cycle. The regularity of the precipitation regime, in particular, is a basic factor to sustain equilibrium conditions. An incomplete or biased understanding of precipitation seasonality, in terms of temporal and spatial properties, could severely limit our ability to respond to climate risk, especially in areas with limited water resources or fragile ecosystems. Here, we analyze precipitation data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) at 0.050 resolution to study the spatial features of the precipitation seasonality across different climate zones in Central-Southern Europe during the period 1981–2018. A cluster analysis of the average annual precipitation cycle shows that seasonality under the current climate can be synthesized in the form of a progressive deformation process of the annual cycle, which starts from the northernmost areas with maximum values in summer and ends in the south, where maximum values are recorded in winter. Our analysis is useful to detect local season-dependent changes, enhancing our understanding of the geography of climate change. As an example of application to this issue, we discuss the seasonality analysis in a simulated scenario based on IPCC projections.

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