On A* Graph Search Algorithm Heuristics Implementation Towards Efficient Path Planning in the Presence of Obstacles

Nowadays it has become more and more important to reach a destination in a short time, in the shortest path between all the options and possibilities. This need is addressed by different search engines like google maps for example and it is common sense that the user is expecting the result in the least amount of time. The scope of this publication, is to help the reader understand the mechanism behind pathfinding algorithms integrated with heuristics and on how to choose between them in a given case study. Moreover, this paper aims at illustrating, after pathfinding algorithm selection, how to tweak and improve it in order to better fit the given setup scenario. With this respect, it will be shown how the A* algorithm computationally performs in a graph theoretic grid setup, initially in a small one and then, in a graph grid with a 10-fold increase of the initial setup dimensions. This experimental study compares two different heuristics in A* implementation, the Euclidean distance heuristic and the Chebyshev heuristic. Computational time results are compared with respect to the time taken to produce a final result in each case. Moreover, the total number of nodes involved in the path as well as the total cost estimated are considered per each case. These results are further compared with the ones derived when obstacles are introduced in the graph grid setup and how the algorithm will handle such scenarios is illustrated. This paper aims at providing information to researchers so that to understand what analysis needs to be done when selecting heuristics associated with pathfinding algorithms heuristics, and at providing relevant performance metrics regarding shortest path planning estimation between two predefined nodes in a graph grid setup. Moreover, aims at providing information on how the heuristics define the decision-making process in the A* algorithm and on how to weight the time/cost factors importance based on specific use cases

TRANSFORMERS: Robust spatial joins on non-uniform data distributions

Spatial joins are becoming increasingly ubiquitous in many applications, particularly in the scientific domain. While several approaches have been proposed for joining spatial datasets, each of them has a strength for a particular type of density ratio among the joined datasets. More generally, no single proposed method can efficiently join two spatial datasets in a robust manner with respect to their data distributions. Some approaches do well for datasets with contrasting densities while others do better with similar densities. None of them does well when the datasets have locally divergent data distributions. In this paper we develop TRANSFORMERS, an efficient and robust spatial join approach that is indifferent to such variations of distribution among the joined data. TRANSFORMERS achieves this feat by departing from the state-of-the-art through adapting the join strategy and data layout to local density variations among the joined data. It employs a join method based on data-oriented partitioning when joining areas of substantially different local densities, whereas it uses big partitions (as in space-oriented partitioning) when the densities are similar, while seamlessly switching among these two strategies at runtime. We experimentally demonstrate that TRANSFORMERS outperforms state-of-the-art approaches by a factor of between 2 and 8

Transcription factor signal transducer and activator of transcription 5 promotes growth of human prostate cancer cells in vivo

Purpose: Stat5a/b is the key mediator of prolactin (Prl) effects in prostate cancer cells via activation of Jak2. Prl is locally produced growth factor in human prostate cancer. Prl protein expression and constitutive activation of Stat5a/b are associated with high histological grade of clinical prostate cancer. Moreover, activation of Stat5a/b in primary prostate cancer predicts early disease recurrence. Here, we inhibited Stat5a/b by several different methodological approaches. Our goal was to establish a proof-of-principle that Stat5a/b is critical for prostate cancer cell viability in vitro and for prostate tumor growth in vivo. Experimental Design: We inhibited Stat5a/b protein expression by antisense oligonucleotides or RNA interference and transcriptional activity of Stat5a/b by adenoviral expression of a dominant-negative mutant of Stat5a/b in prostate cancer cells in culture. Moreover, Stat5a/b activity was suppressed in human prostate cancer xenograft tumors in nude mice. Stat5a/b regulation of BclXL and Cyclin-D1 protein levels was demonstrated by antisense suppression of Stat5a/b protein expression followed by Western blotting. Results and Conclusions: We show here that inhibition of Stat5a/b by antisense oligonuleotides, RNA interference, or adenoviral expression of DNStat5a/b all effectively kill prostate cancer cells. Moreover, we demonstrate that Stat5a/b is critical for human prostate cancer xenograft growth in nude mice. Stat5a/b effects on the viability of on prostate cancer cells involve Stat5a/b-regulation of BclXL and Cyclin-D1 protein levels, but not the expression or activation of Stat3. This work establishes Stat5a/b as a therapeutic target protein for prostate cancer. Pharmacological inhibition of Stat5a/b in prostate cancer can be achieved by small-molecule inhibitors of transactivation, dimerization or DNA-binding of Stat5a/b

Supporting Shared Understanding in Asynchronous Communication Contexts

[Context and motivation] The success of software projects depends on developing a system that satisfies the stakeholders’ wishes and needs according to their mental models of the intended system. However, stakeholders may have different or misaligned mental models of the same system, resulting in conflicting requirements. For this reason, aligned mental models and thus a shared understanding of the project vision is essential for the success of software projects. [Question/problem] While it is already challenging to achieve shared understanding in synchronous contexts, such as meetings, it is even more challenging when only asynchronous contexts, like messaging services, are possible. When multiple stakeholders are involved from different locations and time zones, primarily asynchronous communication occurs. Despite the frequent use of software tools, like Confluence, to support asynchronous contexts, their use for the development of a shared understanding has hardly been analyzed. [Principal ideas/results] In this paper, we propose five concepts to help stakeholders develop a shared understanding in asynchronous communication contexts. We assess the adaptability of three existing software tools to our concepts, adapt these software tools accordingly, and develop our own prototype that implements all five concepts. In an experiment with 30 participants, we evaluate these four software tools and compare them to a control group that had no support in developing a shared understanding. [Contribution] Our results show the suitability of our concepts, as the participants using our concepts were able to achieve a higher level of shared understanding compared to the control group

PAH under XUV excitation: an ultrafast XUV- photochemistry experiment for astrophysics

International audienceUnderstanding processes induced by XUV excitation of Polycyclic Aromatic Hydrocarbons (PAHs) is at the heart of molecular astrophysics, which aims at understanding molecular evolution in interstellar media. We used ultrashort XUV pulses to produce highly excited PAHs cations. The photo-induced dynamics is probed using a pump-probe XUV-IR spectroscopy. By studying PAH from small (naphthalene) to large (hexabenzocoronene) PAHs, we show that the dynamic is governed by the large density of states, in which many-body quantum effects are dominant