A strong approximation of the shortt process

A shortt of a one dimensional probability distribution is defined to be an interval which has at least probability t and minimal length. The length of a shortt, U(t), and its obvious estimator, U_n(t), are significant measures of scale of a probability distribution and the corresponding random sample, respectively. The shortt process is defined to be $\sqrt{n}(U_n(t)-U(t)) / U'(t)$, similarly to the definition of the quantile process. It is known that this process converges weakly, under natural regularity conditions, to a Brownian bridge. In this note a strong approximation of the shortt process by a Kiefer process is established, which yields the weak convergence as a corollary. Applications of the result to the global and local strong limiting behaviour of the shortt process are also presented

Worst-case throughput analysis for parametric rate and parametric actor execution time scenario-aware dataflow graphs

Scenario-aware dataflow (SADF) is a prominent tool for modeling and analysis of dynamic embedded dataflow applications. In SADF the application is represented as a finite collection of synchronous dataflow (SDF) graphs, each of which represents one possible application behaviour or scenario. A finite state machine (FSM) specifies the possible orders of scenario occurrences. The SADF model renders the tightest possible performance guarantees, but is limited by its finiteness. This means that from a practical point of view, it can only handle dynamic dataflow applications that are characterized by a reasonably sized set of possible behaviours or scenarios. In this paper we remove this limitation for a class of SADF graphs by means of SADF model parametrization in terms of graph port rates and actor execution times. First, we formally define the semantics of the model relevant for throughput analysis based on (max,+) linear system theory and (max,+) automata. Second, by generalizing some of the existing results, we give the algorithms for worst-case throughput analysis of parametric rate and parametric actor execution time acyclic SADF graphs with a fully connected, possibly infinite state transition system. Third, we demonstrate our approach on a few realistic applications from digital signal processing (DSP) domain mapped onto an embedded multi-processor architecture

Modeling static-order schedules in synchronous dataflow graphs

Abstract—Synchronous dataflow graphs (SDFGs) are used extensively to model streaming applications. An SDFG can be extended with scheduling decisions, allowing SDFG analysis to obtain properties like throughput or buffer sizes for the scheduled graphs. Analysis times depend strongly on the size of the SDFG. SDFGs can be statically scheduled using static-order schedules. The only generally applicable technique to model a staticorder schedule in an SDFG is to convert it to a homogeneous SDFG (HSDFG). This conversion may lead to an exponential increase in the size of the graph and to sub-optimal analysis results (e.g., for buffer sizes in multi-processors). We present a technique to model periodic static-order schedules directly in an SDFG. Experiments show that our technique produces more compact graphs compared to the technique that relies on a conversion to an HSDFG. This results in reduced analysis times for performance properties and tighter resource requirements

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Selective Induction of Apoptosis in Melanoma Cells by Tyrosinase Promoter-Controlled CD95 Ligand Overexpression

Induction of apoptosis has been demonstrated previously by overexpression of CD95 ligand (CD95L) in cultured human melanoma cells. For in vivo approaches based on CD95L, however, targeted expression is a prerequisite and tyrosinase promoters have been considered for selection. Luciferase reporter gene assays performed for a representative panel of melanoma cell lines characterized by strong (SK-Mel-19), moderate (SK-Mel-13, MeWo), weak (A-375), and missing expression (M-5) of endogenous tyrosinase revealed high tyrosinase promoter activities in SK-Mel-19, SK-Mel-13, and MeWo, but only weak activities in A-375 and M-5 as well as in non-melanoma cell lines. After transfection of a CMV promoter CD95L expression construct, melanoma cells were found highly sensitive, as compared with non-melanoma cells. By applying a tyrosinase promoter CD95L construct, apoptosis was selectively induced in SK-Mel-19, SK-Mel-13, MeWo as well as in A-375, which was characterized by high CD95 surface expression and high sensitivity to agonistic CD95 activation. M5 and non-melanoma cell lines remained uninfluenced. Also, resistance to agonistic CD95 activation seen in MeWo characterized by weak CD95 surface expression was overcome by overexpression of CD95L. Our investigations provide evidence that tyrosinase promoter CD95L constructs may be of value for selective induction of apoptosis in therapeutic strategies for melanoma