A Mossbauer resonance study of FeC12 monolayers deposited on oriented basal planes of graphite (Grafoil) is reported. Samples with fractional monolayer coverages between 0.2 and 0.9 were studied between 300 and 80'K. The spectra show two distinct quadrupole doublets; one with a room-temperature splitting of -2 mm/sec {designated L) and the other -0.8 mm/sec (8), which is identical to the splitting of bulk FeC1, and has the same shift. There is a marked difference between the intensities of the two lines of each doublet: For each sample, the ratio I+/I depends on the orientation of the planes of the Grafoil sheets relative to k". The intensity ratio for k"normal to the plane of the foilsprogresses from I+/I p 1 to I+!I & 1 with reduction of coverage. The total intensity of the 3 doublet relative to L is reduced with decreasing coverage. The velocity shift of L and the temperature dependence of the intensity of both L and B doublets differ markedly from those of bulk FeC1~and other known Fe++ compounds. The results suggest the existence of at least two distinct phases of FeC12 in the film samples, and that the FeC12-graphite samples involve monolayer surface states rather than bulk FeCl, aggregates. A calculation of the adsorption binding energy from the temperature dependence of the Debye-%'aller factor yields about 80 kcal/mole for 8 and about 60 kcal/mole for the L phase; both values are larger than the heats of fusion (10 kcal/mole) and evaporation (30 kcal/mole) of bulk FeCl"and are comparable with the heat of formation {80kcal/mole). Possible models for surface arrangements of ferrous chloride molecules are discussed. 1876
Social media is used nowadays for various location-based applications and services, aspiring to use the vast and timely potential of user-generated content. To evaluate the correctness, reliability and potential of these applications and services, they are mostly evaluated in terms of optimization or compared to existing authoritative data sources and services. With respect to route planning, criterion optimization is mostly implemented to evaluate the service effectiveness, in terms of, e.g., length, time or visited places. These evaluations are mostly limited in their effectiveness at presenting the complete experience of the route, since they are limited to a predefined criterion and are mostly implemented in two-dimensional space. In this research, we propose a comprehensive evaluation process, in which a tourism walking route is analyzed with respect to three-dimensional visibility that measures the attractiveness of the route relating to the user perception. To present our development, we showcase the use of Flickr, a social media photo-sharing online website that is popular among travelers that share their tourism experiences. We use Flickr photos to generate tourism walking routes and evaluate them in terms of the visible space. We show that the 3D visibility analysis identifies the various visible urban elements in the vicinity of the tourism routes, which are more attractive, scenery and include many tourism attractions. Since urban attractivity is often reflected in the photo-trails of Flickr photographers, we argue that using 3D visibility analysis that measures urban attractiveness and scenery should be considered for the purpose of analysis and evaluation of location-based services.
Abstract. It is always a tourism challenge – and aspiration – to discover scenery routes and tourism attractions in unfamiliar areas. Tourism information is getting more extensive, comprehensive and complex, so first-time tourists have to manage and mine large volumes of data to better plan their trip. Nowadays, geotagged photos are uploaded by users to social media photo-sharing online websites, which become more popular and commonly used by travelers to share their tourism experiences. Handling, mining and interpreting these user-generated ‘digital footprints’ can be used to reconstruct travel trajectories of users to recover their activity and knowledge. In this research, we showcase Flickr geotagged crowdsource photo database as a source for mining users’ trajectories to effectively compute walking tourism routes. Our methodology mines tourism context by conceptualizing a set of adaptive spatiotemporal descriptors to identify photographers that show tourism activity of first-time visitors. By implementing spatial clustering, we find popular locations that are traversed by these tourism-oriented photographers’ trajectories. To analyze our approach, we develop a greedy route computation algorithm that seeks the most popular traversed locations between origin and destination points defined by the user. Results for two cities are presented, proving the robust mining and retrieving of valuable tourism context and information from social media photos. We evaluate and validate our results by comparing the computed walking routes to recognized tourism information. The computed walking routes are scenery and pass through the main popular tourism sights and landmarks in the city, including additional attractive places that are frequently visited by tourism-photographers.
Abstract. Since many tourists share the photos they take on social media channels, large collections of tourist attraction photos are easily accessible online. Recent research has dealt with identifying popular places from these photos, as well as computing city tourism routes based on these photo collections. Although current approaches show great potential, many tourism attractions suffer from being overrun by tourists, not least because many tourists are aware of only a few tourism hot spots that are trending. In the worst case, automatic city route recommendations based on social media photos will intensify this issue and disappoint tourists who seek individual experiences. In the best case, however, if individual preferences are appropriately incorporated into the route planning algorithm, more personalized route recommendations will be achieved. In this paper, we suggest distinguishing two different types of photo contributors, namely: first-time visitors who are usually tourists who "follow the crowd" (e.g., to visit the top tourist attractions), and repeated visitors who are usually locals who "don’t follow the crowd" (e.g., to visit photogenic yet less well-known places). This categorization allows the user to decide how to trade the one objective off against the other. We present a novel method based on a classification of photographers into locals and tourists, and show how to incorporate this information into an algorithmic routing framework based on the Orienteering Problem approach. In detailed experiments we analyze how choosing the parameter that models the trade-off between both objectives influences the optimal route found by the algorithm, designed to serve the user’s travel objective and preferences in terms of visited attraction types.
(Abstracted from J Ultrasound Med 2022;41:917–923)As cesarean delivery (CD) rates have exponentially increased worldwide during the last 2 decades, the development of a “niche,” or a CD scar defect (also called isthmocele), has arisen as a key factor associated with secondary gynecological and obstetrical complications. In terms of subsequent pregnancies, these defects have been indirectly associated with increased rates of placenta accreta, iatrogenic obstetric complications, and preterm birth.
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