19 research outputs found
Knot invariants in lens spaces
In this survey we summarize results regarding the Kauffman bracket, HOMFLYPT,
Kauffman 2-variable and Dubrovnik skein modules, and the Alexander polynomial
of links in lens spaces, which we represent as mixed link diagrams. These
invariants generalize the corresponding knot polynomials in the classical case.
We compare the invariants by means of the ability to distinguish between some
difficult cases of knots with certain symmetries
A model of early evolution of karst conduits affected by subterranean CO2 sources
In investigating early karstification of one-dimensional conduits by computer models, so far one has assumed that the CO2 content of the calcite aggressive water stems entirely from the surface. Subterranean sources of CO2, however, can rejuvenate the solutional power of water already close to equilibrium with respect to calcite, and boost dissolution rates. In a first scenario we have investigated the influence of a punctual source of CO2 as the most simple case of release of CO2 into a karstifiable fracture at some position KL from its entrance of the widening joint with length L, (K\u3c1). The results show that only a small increase of the p CO2 in the solution to about 0.01 atm is sufficient to reduce the breakthrough times to about 0.3 with respect to the case, where no CO2 is delivered. Other sources of CO2 are due to the metabolic activity of microorganisms. The existence of such diverse subterraneous microbial life in karst systems is demonstrated. Whether situated on the fissure surfaces or free floating in the karst water, one basic product of their metabolism is CO2. This contributes over the whole flow path to the p CO2 of the karst water. Therefore in a second scenario we assumed a constant rate of CO2-input along parts of the fracture, as could be delivered by the activity of aerobic bacteria dwelling at its walls. Such a scenario also applies to an extended diffuse CO2 migration from volcanic activity deep underground. In this case drastic reductions of the breakthrough time by about one order of magnitude are observed. These reductions are enhanced when the fracture aperture width of the initial fracture decreases. The physicochemical mechanisms of enhancement of karstification are discussed in detail by considering the evolution of the fracture aperture width and of the dissolution rates in space and time
Karst show caves : How DTN technology as used in space assists automatic environmental monitoring and tourist protection - experiment in Postojna cave
The paper presents an experiment demonstrating a novel and successful application of delay- and disruption-tolerant networking (DTN) technology for automatic data transfer in a karst cave early warning and measuring system. The experiment took place inside the Postojna Cave in Slovenia, which is open to tourists. Several automatic meteorological measuring stations are set up inside the cave, as an adjunct to the surveillance infrastructure; the regular data transfer provided by the DTN technology allows the surveillance system to take on the role of an early warning system (EWS). One of the stations is set up alongside the railway tracks, which allows the tourist to travel inside the cave by train. The experiment was carried out by placing a DTN "data mule" (a DTN-enabled computer with WiFi connection) on the train and by upgrading the meteorological station with a DTN-enabled WiFi transmission system. When the data mule is in the wireless drive-by mode, it collects measurement data from the station over a period of several seconds as the train without stopping passes the stationary equipment, and delivers data at the final train station by the cave entrance. This paper describes an overview of the experimental equipment and organization allowing the use of a DTN system for data collection and an EWS inside karst caves where there is regular traffic of tourists and researchers.Validerad; 2014; 20140210 (maud)</p
Stance and influence of Twitter users regarding the Brexit referendum
Abstract Social media are an important source of information about the political issues, reflecting, as well as influencing, public mood. We present an analysis of Twitter data, collected over 6 weeks before the Brexit referendum, held in the UK in June 2016. We address two questions: what is the relation between the Twitter mood and the referendum outcome, and who were the most influential Twitter users in the pro- and contra-Brexit camps? First, we construct a stance classification model by machine learning methods, and are then able to predict the stance of about one million UK-based Twitter users. The demography of Twitter users is, however, very different from the demography of the voters. By applying a simple age-adjusted mapping to the overall Twitter stance, the results show the prevalence of the pro-Brexit voters, something unexpected by most of the opinion polls. Second, we apply the Hirsch index to estimate the influence, and rank the Twitter users from both camps. We find that the most productive Twitter users are not the most influential, that the pro-Brexit camp was four times more influential, and had considerably larger impact on the campaign than the opponents. Third, we find that the top pro-Brexit communities are considerably more polarized than the contra-Brexit camp. These results show that social media provide a rich resource of data to be exploited, but accumulated knowledge and lessons learned from the opinion polls have to be adapted to the new data sources