Hotspots and social background of urban traffic crashes: A case study in Cluj-Napoca (Romania)

Mobility practices have changed dramatically in Romanian towns over the last 25 years, following the collapse of socialist mobility restrictions. Urban areas like Cluj-Napoca are facing both increasing immigration and car mobility, and therefore increasing levels of road traffic crashes.The analysis of traffic crashes is one of the most important elements for improving the road safety policy. This paper is divided in two parts. In the first one, the authors focus on identifying the traffic crash hotspots along the street network, while in the second part they discuss the social background of road traffic crash occurrence.The first step in analyzing traffic crashes is to determine crash hotspots. A four-year record (2010–2013) provided by the Traffic Department of the General Inspectorate of Romanian Police (GIRPTD) was used. As a method of hotspot determination, the Kernel Density Estimation tool was employed, in the frame of the spatial analysis along network (SANET). The outcome was the hotspot map of traffic crashes in Cluj-Napoca. The results have revealed 4 categories of street segments: not-dangerous, low-dangerous, medium-dangerous and high-dangerous. Based on this classification, at least 4 dangerous areas were identified, located at the city entrances-exits (in the West, North-West and East) and the city center (the most dangerous zone).The second part of the paper focuses on social groups involved in car crashes. The following are considered: age, gender and blood alcohol concentration of the person (driver or pedestrian) found guilty for every individual crash.     

Assessing the Effect of Global Travel and Contact Restrictions on Mitigating the COVID-19 Pandemic

Travel restrictions and physical distancing have been implemented across the world to mitigate the coronavirus disease 2019 (COVID-19) pandemic, but studies are needed to understand their effectiveness across regions and time. Based on the population mobility metrics derived from mobile phone geolocation data across 135 countries or territories during the first wave of the pandemic in 2020, we built a metapopulation epidemiological model to measure the effect of travel and contact restrictions on containing COVID-19 outbreaks across regions. We found that if these interventions had not been deployed, the cumulative number of cases could have shown a 97-fold (interquartile range 79–116) increase, as of May 31, 2020. However, their effectiveness depended upon the timing, duration, and intensity of the interventions, with variations in case severity seen across populations, regions, and seasons. Additionally, before effective vaccines are widely available and herd immunity is achieved, our results emphasize that a certain degree of physical distancing at the relaxation of the intervention stage will likely be needed to avoid rapid resurgences and subsequent lockdowns.     

Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading

To date, the only effective means to respond to the spreading of the COVID-19 pandemic are non-pharmaceutical interventions (NPIs), which entail policies to reduce social activity and mobility restrictions. Quantifying their effect is difficult, but it is key to reducing their social and economic consequences. Here, we introduce a meta-population model based on temporal networks, calibrated on the COVID-19 outbreak data in Italy and applied to evaluate the outcomes of these two types of NPIs. Our approach combines the advantages of granular spatial modelling of meta-population models with the ability to realistically describe social contacts via activity-driven networks. We focus on disentangling the impact of these two different types of NPIs: those aiming at reducing individuals’ social activity, for instance through lockdowns, and those that enforce mobility restrictions. We provide a valuable framework to assess the effectiveness of different NPIs, varying with respect to their timing and severity. Results suggest that the effects of mobility restrictions largely depend on the possibility of implementing timely NPIs in the early phases of the outbreak, whereas activity reduction policies should be prioritized afterwards.     

Trade-offs between mobility restrictions and transmission of SARS-CoV-2

In their response to the COVID-19 outbreak, governments face the dilemma to balance public health and economy. Mobility plays a central role in this dilemma because the movement of people enables both economic activity and virus spread. We use mobility data in the form of counts of travellers between regions, to extend the often-used SEIR models to include mobility between regions. We quantify the trade-off between mobility and infection spread in terms of a single parameter, to be chosen by policy makers, and propose strategies for restricting mobility so that the restrictions are minimal while the infection spread is effectively limited. We consider restrictions where the country is divided into regions, and study scenarios where mobility is allowed within these regions, and disallowed between them. We propose heuristic methods to approximate optimal choices for these regions. We evaluate the obtained restrictions based on our trade-off. The results show that our methods are especially effective when the infections are highly concentrated, e.g. around a few municipalities, as resulting from superspreading events that play an important role in the spread of COVID-19. We demonstrate our method in the example of the Netherlands. The results apply more broadly when mobility data are available.     

Interventions to maintain mobility: What works?

Mobility, in broad terms, includes everything from the ability to move within your immediate environment (e.g., get out of bed) to the ability to drive across the country. Mobility is essential to maintaining independence and wellbeing, particularly for older adults. This is highlighted by the large number of interventions developed for older adults with the goal of maintaining such mobility. The current paper reviews the state of the science with respect to mobility interventions. Inclusion criteria for the review were: (1) articles must have been peer-reviewed; (2) interventions were evaluated in a randomized controlled trial (RCT); (3) studies included a mobility outcome such as lifespace, driving, or walking ability; (4) studies included a sample of healthy community-dwelling older adults (e.g., not investigations of disease conditions); and (5) studies must have reported enough empirical data and detail such that results could potentially be replicated. Three main types of interventions were identified: cognitive training, educational interventions, and exercise interventions. A detailed summary and evaluation of each type of intervention, and the current evidence regarding its effectiveness in maintaining mobility, are discussed. Several interventions show clear evidence of effectiveness, and thus are prime areas for translation of results to the older population. Needs and issues for future intervention research are also detailed.     

Effective thermoelastic properties of composites with temperature-dependent constituents

Effective thermoelastic properties—elasticities, thermal expansions, heat capacities—of composites with temperature-dependent constituents are derived all at the same time using a unified thermodynamic treatment within Kovalenko’s thermoelasticity theory, which assumes the strain to be small but places no restrictions on temperature variations. Known results on elasticities and thermal expansions are rederived in a new way and new results on thermal expansions and heat capacities are obtained. In addition, the temperature-independent framework is revisited and expressions for the effective properties are obtained that are free of the restrictions placed on temperature variations within linear thermoelasticity.     

Computing the mobility of grain boundaries

As current experimental and simulation methods cannot determine the mobility of flat boundaries across the large misorientation phase space, we have developed a computational method for imposing an artificial driving force on boundaries. In a molecular dynamics simulation, this allows us to go beyond the inherent timescale restrictions of the technique and induce non-negligible motion in flat boundaries of arbitrary misorientation. For different series of symmetric boundaries, we find both expected and unexpected results. In general, mobility increases as the grain boundary plane deviates from (111), but high-coincidence and low-angle boundaries represent special cases. These results agree with and enrich experimental observations.     

Analysis and Interpretation of the Structural Failures of the Orthostate in the Northern Wall of the Athens Parthenon

Abstract:  An investigation into the typology of the failures recorded on the first row (orthostate) of the Parthenon northern wall and analysis of their causes was undertaken. Systematic marble detachment was observed at the areas of the connectors. Failures were categorised and five failure modes were defined. The understanding of the structural history of the building and the design of new interventions requires the analysis of the factors that produced the observed failures, namely mechanical action or rust. The analysis undertaken was based on the simultaneous consideration of: (a) the kinematic restrictions of each block separately; (b) the applied system of deformations/displacements on each structural member; and (c) the applied system of deformations/displacements on the wall itself. Moreover, a numerical analysis was also undertaken, and some preliminary results are also reported. The effect of the marble orthotropy (mainly the position of the marble soft plane inside the block) was also studied. The main conclusion of the study is that the mechanical action of the connectors could explain the observed structural pathology, whereas rust is not a necessary condition for the structural failures to occur.     

Restricted randomization and multiple responses in industrial experiments

Two issues regarding designed experiments are discussed; restrictions on randomization and multiple responses. The former is typically related to hard‐to‐vary factors and factors appearing in separate stages of a process experiment. Randomization restrictions should be taken into account in the construction of the design as well as in the statistical modelling. In the paper, a case study of sausage production is discussed, having a split‐plot model with correlated multiple responses. Multiple responses are handled in two ways, by principal component analysis (PCA) followed by ANOVA of the principal components, and by a newly developed alternative, the ‘50–50 MANOVA’. Multiple tests of correlated response variables are also described. Practical aspects of the planning, performing, response measurements, and statistical analysis are emphasized throughout. Hence, the paper aims to extend the utility of statistical methods in industry by linking design of experiments to multivariate analysis of the responses. Copyright © 2007 John Wiley & Sons, Ltd.     

Parking Availability Prediction with Coarse-Grained Human Mobility Data

Nowadays, the anticipation of parking-space demand is an instrumental service in order to reduce traffic congestion levels in urban spaces. The purpose of our work is to study, design and develop a parking-availability predictor that extracts the knowledge from human mobility data, based on the anonymized human displacements of an urban area, and also from weather conditions. Most of the existing solutions for this prediction take as contextual data the current road-traffic state defined at very high temporal or spatial resolution. However, access to this type of fine-grained location data is usually quite limited due to several economic or privacy-related restrictions. To overcome this limitation, our proposal uses urban areas that are defined at very low spatial and temporal resolution. We conducted several experiments using three Artificial Neural Networks: Multilayer Perceptron, Gated Recurrent Units and bidirectional Long Short Term Memory networks and we tested their suitability using different combinations of inputs. Several metrics are provided for the sake of comparison within our study and between other studies. The solution has been evaluated in a real-world testbed in the city of Murcia (Spain) integrating an open human-mobility dataset showing high accuracy. A MAPE between 4% and 10% was reported in horizons of 1 to 3 h.     

An empirical examination of response time,product variety and firm performance

Response time and product variety are both important strategies that firms utilize to cope with fast changing demand and stiff competition. However, the empirical link between the two areas is not clear. The purpose of this study is to explore the link between response time, product variety and firm performance under build-to-order scenario. A multi-method approach (mainly including OTD time mapping, document examinations, interviews and plant tours) was used to collect the data at the Chinese vehicle manufacturers. Based on the objective data statistically analyzed, this study makes the contribution in three aspects: First, this study provides an empirical examination into the order-to-delivery time structure. The research results reveal that order processing time is independent from producing time. Second, this study provides the first empirical exploration into the association between product variety and response time in the automotive industry. The results show that more model variations may significantly increase order processing time while more type variations do not significantly impact on producing time. Third, the results of this study demonstrate the impacts of both product variety and response time on firm's performance. Fast response time helps increase sales in a short term while more product variety benefits higher growth rate.     

Sustainability of smart rural mobility and tourism: A key performance indicators-based approach

The concept of smart mobility and tourism has evolved from a technology-driven approach to one that focuses on sustainable solutions to address economic, social, and environmental issues. The United Nations (UN) sustainable development goals (SDGs) provide a framework for measuring and tracking progress toward sustainability goals. Key performance indicators (KPIs) are a useful tool for measuring and tracking progress towards these goals, allowing for continuous monitoring and evaluation of progress, identification of areas for improvement, and directing targeted interventions. This research aims to develop an indicators-based framework to evaluate the sustainability of smart and sustainable mobility and tourism in rural areas. Rural areas have often been neglected, or at least less prioritized, in the sustainability development of the mobility sector. The study also seeks to identify the overlap of KPIs between rural tourism and mobility, and how improved green mobility services can enhance sustainable rural tourism. Smart mobility and tourism indicators have a strong mutual relationship in rural communities, driving economic development, improving the quality of life for residents and visitors, and creating more sustainable and livable communities. Smart mobility and tourism indicators also play a crucial role in supporting the UN SDGs by providing data and insights that can inform policy and decision-making. The results of this research conclude how the target and performance setting of projects on sustainable mobility and tourism in rural communities support each other, and how they support achieving SDGs.     

Coupling human mobility and social ties

Studies using massive, passively collected data from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion and organizational dynamics. More recently, these data have come tagged with geographical information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns among social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals'' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user''s ego network in terms of the type of contacts they keep is correlated with mobility behaviour. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare its ability to reproduce empirical measurements with two additional models of mobility.     

The spatial dissemination of COVID-19 and associated socio-economic consequences

The ongoing coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc worldwide with millions of lives claimed, human travel restricted and economic development halted. Leveraging city-level mobility and case data, our analysis shows that the spatial dissemination of COVID-19 can be well explained by a local diffusion process in the mobility network rather than a global diffusion process, indicating the effectiveness of the implemented disease prevention and control measures. Based on the constructed case prediction model, it is estimated that there could be distinct social consequences if the COVID-19 outbreak happened in different areas. During the epidemic control period, human mobility experienced substantial reductions and the mobility network underwent remarkable local and global structural changes toward containing the spread of COVID-19. Our work has important implications for the mitigation of disease and the evaluation of the socio-economic consequences of COVID-19 on society.     

COVID-19 policy analysis: labour structure dictates lockdown mobility behaviour

Countries and cities around the world have resorted to unprecedented mobility restrictions to combat COVID-19 transmission. Here we exploit a natural experiment whereby Colombian cities implemented varied lockdown policies based on ID number and gender to analyse the impact of these policies on urban mobility. Using mobile phone data, we find that the restrictiveness of cities’ mobility quotas (the share of residents allowed out daily according to policy advice) does not correlate with mobility reduction. Instead, we find that larger, wealthier cities with more formalized and complex industrial structure experienced greater reductions in mobility. Within cities, wealthier residents are more likely to reduce mobility, and commuters are especially more likely to stay at home when their work is located in wealthy or commercially/industrially formalized neighbourhoods. Hence, our results indicate that cities’ employment characteristics and work-from-home capabilities are the primary determinants of mobility reduction. This finding underscores the need for mitigations aimed at lower income/informal workers, and sheds light on critical dependencies between socio-economic classes in Latin American cities.     

Flow-level performance and user mobility in wireless data networks

Channel conditions in wireless networks exhibit huge variations across space and time, giving rise to vast fluctuations in the transmission rates. Channel-aware scheduling strategies provide an effective mechanism for improving throughput performance by exploiting such rate variations, and these have been extensively examined at the packet level for a static user configuration. In this paper, we discuss the performance implications at the flow level for a dynamic user population, taking into account variations on a slower time scale and wide-range user mobility as well. First of all, we present simple necessary conditions for flow-level stability and prove that these are in fact (near) sufficient for a wide family of utility-based scheduling strategies. It is further shown how the flow-level performance of the proportional fair scheduling strategy may be evaluated by means of a processor-sharing model with a state-dependent service rate. In addition, we examine the impact of variations on a slower time scale, and establish that the so-called fluid and quasi-stationary regimes yield explicit, insensitive performance bounds. Finally, we turn our attention to a network of several base stations (BSs) with handoffs of active sessions governed by wide-range user mobility. It is demonstrated that mobility increases the capacity, not only in the case of globally optimal scheduling but also when each of the BSs adheres to a local fair-sharing discipline.     

Critical excitation for elastic–plastic structures via statistical equivalent linearization

Since earthquake ground motions and their effects on structural responses are very uncertain even with the present knowledge, it is desirable to develop a robust structural design method taking into account these uncertainties. Critical excitation approaches are promising and a new random critical excitation method for single-degree-of-freedom (SDOF) elastic–plastic structures is proposed. The power (area of power spectral density (PSD) function) and the intensity (magnitude of PSD function) are fixed and the critical excitation is found under these restrictions. In contrast to linear elastic structures, transfer functions and related simple expressions for response evaluation cannot be defined in elastic–plastic structures and difficulties arise in describing the peak responses except elastic–plastic time-history response analysis. Statistical equivalent linearization is utilized to estimate the elastic–plastic stochastic peak responses approximately. The critical excitations are obtained for two examples and compared with the corresponding recorded earthquake ground motions.     

国际城区再生模式对沈阳市同泽北街旧城区域的改造启示

目的 "城区再生"是近年来许多发达国家中步入后工业化社会的城区在面对城市发展的困境时,为了提升区域活力,恢复城区在社会经济发展中的引导作用而提出来的。城区再生通常被理解为对城区中濒临消失的历史遗迹以及建筑进行保留或修复的措施。而城区持续再生强调的是在把握发展趋势的基础上,更新城市功能,改善人居环境,恢复或维持许多城区已经失去或正在失去的"区域发展牵引力"的功能。"城区再生"不同于"城市更新",它主要是强调了在原有的基础上进行修缮和进化,属于"有机更新理论"范畴之内,并非是进行"大拆大建"。通过对城区再生模式的研究,为沈阳旧城区同泽北街街道的改造项目提供具有启示价值的方法。方法主要采用的研究方法为对比研究方法,通过对比国内外成功的城市再生案例,如:韩国釜山甘川文化村和中国上海新天地,总结其再生模式的成功之处,探讨其再生模式"移植"的可行性,并通过这两处成功的再生模式对沈阳旧城同泽北街街道进行改造可行性研究。结论最终总结出通过视觉艺术的手段对城市中旧城区风貌进行视觉修葺是城市区域再生中较为简单有效的方法。     

金属填充碳纳米管的制备研究进展

金属填充的碳纳米管在高密度数据存储、生物医用领域和电磁波吸收与屏蔽等许多方面都有极好的应用前景,因而成为当前研究的一个热点领域.按照纳米管的制备与填充过程是否同步完成,可将目前为止制备金属填充碳纳米管的诸多方法分为两大类:两步法和一步法.两步法主要包括毛细填充法和溶液化学法两种;一步法主要包括电弧放电法、熔盐电解法、模板法和热解金属有机物法等四种.本文对按照此分类的制备方法进行了综述,并对今后该领域的研究方向进行了初步的展望.     

Using a Single Transducer Ultrasonic Imaging Method to Eliminate the Effect of Thickness Variation in the Images of Ceramic and Composite Plates

This article describes a single transducer ultrasonic imaging method based on ultrasonic velocity measurement that eliminates the effect of thickness variation in the images of ceramic and composite plate samples. The method is based on using a reflector located behind the sample and acquiring echoes off the sample and reflector surfaces in two scans. As a result of being thickness-independent, the method isolates ultrasonic variations due to material microstructure. Its use can result in significant cost savings because the ultrasonic image can be interpreted correctly without the need for precision thickness machining during nondestructive evaluation stages of material development. Velocity images obtained using the thickness-independent methodology are compared with apparent velocity maps and c-scan echo peak amplitude images for monolithic ceramic (silicon nitride), metal matrix composite and polymer matrix composite materials having thickness and microstructural variations. It was found that the thickness-independent ultrasonic images reveal and quantify correctly areas of global microstructural (pore and fiber volume fraction) variation due to the elimination of thickness effects. A major goal achieved in this study was to move the thickness-independent imaging technology out of the lab prototype environment and into the commercial arena so that it would be available to users worldwide. The method has been implemented on commercially-available ultra-sonic can systems manufactured by Sonix, Inc. via a formal technology transfer agreement between NASA and Sonix.