Computation of solutions to linear difference and differential equations with a prescribed asymptotic behavior

Linear differential equations usually arise from mathematical modeling of physical experiments and real-world problems. In most applications these equations are linked to initial or boundary conditions. But sometimes the solution under consideration is characterized by its asymptotic behavior, which leads to the question how to infer from the asymptotic growth of a solution to its initial values. In this paper we show that under some mild conditions the initial values of the desired solution can be computed by means of a continuous-time analogue of a modified matrix continued fraction. For numerical applications we develop forward and backward algorithms which behave well in most situations. The topic is closely related to the theory of special functions and its extension to higher-dimensional problems. Our investigations result in a powerful tool for solving some classical mathematical problems. To demonstrate the efficiency of our method we apply it to Poincaré type and Kneser’s differential equation

Structured modeling and analysis of stochastic epidemics with immigration and demographic effects

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity

Situationally Aware In-Car Information Presentation Using Incremental Speech Generation: Safer, and More Effective

Kousidis S, Kennington C, Baumann T, Buschmeier H, Kopp S, Schlangen D. Situationally Aware In-Car Information Presentation Using Incremental Speech Generation: Safer, and More Effective. In: Proceedings of the EACL 2014 Workshop on Dialogue in Motion. Gothenburg, Sweden; 2014: 68-72.Holding non-co-located conversations while driving is dangerous (Horrey and Wickens, 2006; Strayer et al., 2006), much more so than conversations with physically present, “situated” interlocutors (Drews et al., 2004). In-car dialogue systems typically resemble non-co-located conversations more, and share their negative impact (Strayer et al., 2013). We implemented and tested a simple strategy for making in-car dialogue systems aware of the driving situation, by giving them the capability to interrupt themselves when a dangerous situation is detected, and resume when over. We show that this improves both driving performance and recall of system-presented information, compared to a non-adaptive strategy

A Multimodal In-Car Dialogue System That Tracks The Driver's Attention

Kousidis S, Kennington C, Baumann T, Buschmeier H, Kopp S, Schlangen D. A Multimodal In-Car Dialogue System That Tracks The Driver's Attention. In: Proceedings of the 16th International Conference on Multimodal Interfaces. Istanbul, Turkey; 2014: 26-33.When a passenger speaks to a driver, he or she is co-located with the driver, is generally aware of the situation, and can stop speaking to allow the driver to focus on the driving task. In-car dialogue systems ignore these important aspects, making them more distracting than even cell-phone conversations. We developed and tested a ``situationally-aware'' dialogue system that can interrupt its speech when a situation which requires more attention from the driver is detected, and can resume when driving conditions return to normal. Furthermore, our system allows driver-controlled resumption of interrupted speech via verbal or visual cues (head nods). Over two experiments, we found that the situationally-aware spoken dialogue system improves driving performance and attention to the speech content, while driver-controlled speech resumption does not hinder performance in either of these two tasks

Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation

Kennington C, Kousidis S, Baumann T, Buschmeier H, Kopp S, Schlangen D. Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation. In: AutomotiveUI 2014: Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. Seattle, Washington, USA; 2014: 7:1-7:7.It is established that driver distraction is the result of sharing cognitive resources between the primary task (driving) and any other secondary task. In the case of holding conversations, a human passenger who is aware of the driving conditions can choose to interrupt his speech in situations potentially requiring more attention from the driver, but in-car information systems typically do not exhibit such sensitivity. We have designed and tested such a system in a driving simulation environment. Unlike other systems, our system delivers infor- mation via speech (calendar entries with scheduled meetings) but is able to react to signals from the environment to interrupt when the driver needs to be fully attentive to the driving task and subsequently resume its delivery. Distraction is measured by a secondary short-term memory task. In both tasks, drivers perform significantly worse when the system does not adapt its speech, while they perform equally well to control conditions (no concurrent task) when the system intelligently interrupts and resumes

Be smart against cancer! A school-based program covering cancer-related risk behavior

Background: Several studies suggest that most school-age children are poorly informed about cancer risk factors. This study examines the effectiveness of the ‘Be smart against cancer’ (BSAC) program in promoting cancer awareness and intentions to engage in health-promoting behavior. Methods: 235 seventh-grade students were randomized to either the intervention (N = 152) or the wait-control group (N = 83). The intervention included the modules: “What is cancer?,” “Sun protection,” “Non smoking,” and “Physical activity, Healthy nutrition, and Limited alcohol consumption.” Outcomes measured at baseline and at the end of the one week BSAC program included knowledge of cancer and its behavioral risk factors, health-promoting intentions, and reported risk behavior. Results: BSAC was effective in increasing knowledge about cancer and risk factors for cancer (p < .001), as well as in increasing intentions to engage in health-promoting behavior (p < .001), independent of a student’s risk profile. Knowledge did not serve as a mediator for intention building. Conclusions: The BSAC is an effective school-based program for raising awareness of cancer, associated risk factors and intentions to engage in cancer-preventive behavior. The results indicate that the effectiveness of BSAC is independent of a student’s risk profile. Therefore, it holds considerable promise as a broadly applicable program to raise cancer awareness and promote healthy behavior intentions

Intramolecular Modulation of Serine Protease Inhibitor Activity in a Marine Cyanobacterium with Antifeedant Properties

Extracts of the Floridian marine cyanobacterium Lyngbya cf. confervoides were found to deter feeding by reef fish and sea urchins (Diadema antillarum). This antifeedant activity may be a reflection of the secondary metabolite content, known to be comprised of many serine protease inhibitors. Further chemical and NMR spectroscopic investigation led us to isolate and structurally characterize a new serine protease inhibitor 1 that is formally derived from an intramolecular condensation of largamide D (2). The cyclization resulted in diminished activity, but to different extents against two serine proteases tested. This finding suggests that cyanobacteria can endogenously modulate the activity of their protease inhibitors

SS18 Together with Animal-Specific Factors Defines Human BAF-Type SWI/SNF Complexes

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