Public Passenger Transport Logistics in the Context of Digital Transformation of Transportation Services Organisation Systems

Transport route specification models are used to analyse the need for combined passenger transportation on popular routes in a large urban agglomeration. The problem of managing the travel chains of passengers using public transport (PT) is revealed with the focus on the complexity of applying the principle of multimodality on the route network used by population due to the mismatch of the schemes of transport and users’ routes.The study of the logistics of passenger transportation with PT introduces the concept of «public transport user (PTU)» which has a variable status relative to the flows of people, pedestrians, passengers, and transport vehicles. The description of the registers of the main parameters of the routes under study serves to create their digital twins.To manage the travel chains of PTUs, identify related sections of transport routes, it is proposed to highlight within the passenger flow the currents of the same profile which include PTUs that have common transport behaviour.Models and algorithms of network proximity to transport infrastructure objects, visualisation of digital traces of PTUs and the results of comparing the used and the best route options according to the modelled parameters allow to identify behavioural profiles of PTUs, as well as regulators managing the travel chains.

What Moves Physicians to Work in Rural Areas? An In-Depth Examination of Physician Practice Location Decisions

This study contributes to the current understanding of what drives physicians to practice in rural areas by analyzing new, comprehensive survey data of practicing physicians in the United States. This research confirmed that rural origin is a powerful and reliable predictor for rural practice and revealed that new and experienced physicians have different priorities regarding location choice. Physicians choosing rural practice locations are more likely to be motivated by compensation, the resemblance of the environment to the one they grew up in, patient needs, and prenegotiated service obligations or visa/immigration status. They are less likely to attribute their location choice to social network proximity. These findings have important implications for salary incentives and policy initiatives aimed at increasing the rural physician workforce. The results of this study will help decrypt the difficulties rural areas face in attracting and retaining medical and other professionals and inform policy development.

Structural characteristics and proximity comparison of China’s urban innovation cooperation network

How to promote and improve the level of urban innovation cooperation is a major issue in China’s current high-quality economic development. Thus, enhancing innovation ability is essential to achieving high-quality economic growth under the "new normal". Based on the data of Chinese invention patents from 1985 to 2017, this paper analyzes the characteristics of China’s urban innovation cooperation network and the different roles of proximity by using social network analysis and exploratory spatial data analysis methods. The analysis results show that: (1) On the whole, the development of China’s urban innovation cooperation network is characterized by stages (initial development stage, rapid development stage, and gradual decline stage); The urban innovation cooperation network has strong connectivity and centripetal concentration but its imbalance needs to be further improved; The degree of urban participation has gradually increased, consolidating the stability of the network structure. (2) The centrality of urban innovation cooperation network has obvious characteristics of administrative center orientation, coastal areas orientation, and ‘strong east and weak west’; Beijing is the center and bridge of the network, and the network flattening characteristics are obvious; A hierarchical ‘core-edge’ structure is gradually formed for the urban innovation cooperation network, and the pyramid structure with Beijing standing at the top is being consolidated. (3) The geographical proximity presents a significant global spatial positive correlation, while the network proximity and pure network proximity have a more significant global spatial negative correlation; The local spatial autocorrelation of China’s urban innovation cooperation system based on network proximity is more obvious and identifiable than that based on the geographical proximity, which better reflects the new development model of "relationship economy".

RWNE: A Scalable Random-Walk based Network Embedding Framework with Personalized Higher-order Proximity Preserved

Higher-order proximity preserved network embedding has attracted increasing attention. In particular, due to the superior scalability, random-walk-based network embedding has also been well developed, which could efficiently explore higher-order neighborhoods via multi-hop random walks. However, despite the success of current random-walk-based methods, most of them are usually not expressive enough to preserve the personalized higher-order proximity and lack a straightforward objective to theoretically articulate what and how network proximity is preserved. In this paper, to address the above issues, we present a general scalable random-walk-based network embedding framework, in which random walk is explicitly incorporated into a sound objective designed theoretically to preserve arbitrary higher-order proximity. Further, we introduce the random walk with restart process into the framework to naturally and effectively achieve personalized-weighted preservation of proximities of different orders. We conduct extensive experiments on several real-world networks and demonstrate that our proposed method consistently and substantially outperforms the state-of-the-art network embedding methods.

Network medicine framework for identifying drug-repurposing opportunities for COVID-19

The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically approved compounds for their potential effectiveness for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. To test the predictions, we used as ground truth 918 drugs experimentally screened in VeroE6 cells, as well as the list of drugs in clinical trials that capture the medical community’s assessment of drugs with potential COVID-19 efficacy. We find that no single predictive algorithm offers consistently reliable outcomes across all datasets and metrics. This outcome prompted us to develop a multimodal technology that fuses the predictions of all algorithms, finding that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We screened in human cells the top-ranked drugs, obtaining a 62% success rate, in contrast to the 0.8% hit rate of nonguided screenings. Of the six drugs that reduced viral infection, four could be directly repurposed to treat COVID-19, proposing novel treatments for COVID-19. We also found that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these network drugs rely on network-based mechanisms that cannot be identified using docking-based strategies. These advances offer a methodological pathway to identify repurposable drugs for future pathogens and neglected diseases underserved by the costs and extended timeline of de novo drug development.

Knowledge networks and strong tie creation: the role of relative network position

The proximity literature usually treats proximity in terms of common attributes shared by agents, disregarding the relative position of an actor inside the network. This paper discusses the importance of such dimension of proximity, labelled as in-network proximity, and proposes an empirical measurement for it, assessing its impact (jointly with other dimensions of proximity) on the creation of strong knowledge network ties in ICT in the region of Trentino. The findings show that actors with higher in-network proximity are more attractive for both other central actors and peripheral ones, which is further strengthening their position within the network. In detail, the centrally positioned actors repeat collaboration with other central actors in the network, as central actors gather more ‘reputation’, signalling that they will possess the needed knowledge resources. Relatively peripheral actors, either new or not so active inside the network, seek for collaboration with relatively central actors in order to tap on knowledge resources they do not acquire.

On Location-based Services Build on the Close Patial Position of Mobile Devices

This article focuses on architectural models of location-based services. The paper discusses the model of spatial network proximity, within which the classical architecture of services using location information, based on the use of geo-coordinates data provided by users, is replaced by some distributed cyber-physical system. Within the network proximity model, geo-computation is replaced by the direct proximity definitions. And this very proximity measurement is based on determining the availability (visibility) of the signals of the wireless network nodes. This article discusses how to build new service models using location information.

Similarity in functional brain connectivity at rest predicts interpersonal closeness in the social network of an entire village

People often have the intuition that they are similar to their friends, yet evidence for homophily (being friends with similar others) based on self-reported personality is inconsistent. Functional connectomes—patterns of spontaneous synchronization across the brain—are stable within individuals and predict how people tend to think and behave. Thus, they may capture interindividual variability in latent traits that are particularly similar among friends but that might elude self-report. Here, we examined interpersonal similarity in functional connectivity at rest—that is, in the absence of external stimuli—and tested if functional connectome similarity is associated with proximity in a real-world social network. The social network of a remote village was reconstructed; a subset of residents underwent functional magnetic resonance imaging. Similarity in functional connectomes was positively related to social network proximity, particularly in the default mode network. Controlling for similarities in demographic and personality data (the Big Five personality traits) yielded similar results. Thus, functional connectomes may capture latent interpersonal similarities between friends that are not fully captured by commonly used demographic or personality measures. The localization of these results suggests how friends may be particularly similar to one another. Additionally, geographic proximity moderated the relationship between neural similarity and social network proximity, suggesting that such associations are particularly strong among people who live particularly close to one another. These findings suggest that social connectivity is reflected in signatures of brain functional connectivity, consistent with the common intuition that friends share similarities that go beyond, for example, demographic similarities.