Context-aware personal route recognition

Personal route recognition is an important element of intelligent transportation systems. The results may be used for providing personal information about location-specific events, services, emergency or disaster situations, for location-specific advertising and more. Existing real-time route recognition systems often compare the current driving trajectory against the trajectories observed in past and select the most similar route as the most likely. The problem is that such systems are inaccurate in the beginning of a trip, as typically several different routes start at the same departure point (e.g. home). In such situations the beginnings of trajectories overlap and the trajectory alone is insufficient to recognize the route. This drawback limits the utilization of route prediction systems, since accurate predictions are needed as early as possible, not at the end of the trip. To solve this problem we incorporate external contextual information (e.g. time of the day) into route recognition from trajectory. We develop a technique to determine from the historical data how the probability of a route depends on contextual features and adjust (post-correct) the route recognition output accordingly. We evaluate the proposed context-aware route recognition approach using the data on driving behavior of twenty persons residing in Aalborg, Denmark, monitored over two months. The results confirm that utilizing contextual information in the proposed way improves the accuracy of route recognition, especially in cases when the historical routes highly overlap

Metals and trace elements in tissues of Common Eiders (Somateria mollissima) from the Finnish archipelago

We sampled Common Eiders (Somateria mollissima) at five locations near coastal Finland in 1997 and 1998 for evidence of exposure to arsenic, cadmium, chromium, copper, iron, mercury, magnesium, manganese, molybdenum, lead, selenium, and zinc. Livers and kidneys were collected from adult males and females found dead and hunter-killed males, and livers were collected from ducklings. Two adult females, one of which had an ingested lead shot in its gizzard, were poisoned by lead . The concentrations of metals and trace elements that we found in tissues of eiders, other than the two lead poisoned birds, were not high enough to have independently caused mortality

"Tell me more" : Finding related items from user provided feedback

The results returned by a search, datamining or database engine often contains an overload of potentially interesting information. A daunting and challenging problem for a user is to pick out the useful information. In this paper we propose an interactive framework to efficiently explore and (re)rank the objects retrieved by such an engine, according to feedback provided on part of the initially retrieved objects. In particular, given a set of objects, a similarity measure applicable to the objects and an initial set of objects that are of interest to the user, our algorithm computes the k most similar objects. This problem, previously coined as ’cluster on demand’ [10], is solved by transforming the data into a weighted graph. On this weighted graph we compute a relevance score between the initial set of nodes and the remaining nodes based upon random walks with restart in graphs. We apply our algorithm "Tell Me More" (TMM) on text, numerical and zero/one data. The results show that TMM for almost every experiment significantly outperforms a k-nearest neighbor approach

New use of an old drug: Inhibition of breast cancer stem cells by benztropine mesylate

Cancer stem cells (CSCs) play major roles in cancer initiation, metastasis, recurrence and therapeutic resistance. Targeting CSCs represents a promising strategy for cancer treatment. The purpose of this study was to identify selective inhibitors of breast CSCs (BCSCs). We carried out a cell-based phenotypic screening with cell viability as a primary endpoint, using a collection of 2,546 FDA-approved drugs and drug-like molecules in spheres formed by malignant human breast gland-derived cells (HMLER-shEcad cells, representing BCSCs) and control immortalized non-tumorigenic human mammary cells (HMLE cells, representing normal stem cells). 19 compounds were identified from screening. The chemically related molecules benztropine mesylate and deptropine citrate were selected for further validation and both potently inhibited sphere formation and self-renewal of BCSCs in vitro. Benztropine mesylate treatment decreased cell subpopulations with high ALDH activity and with a CD44+/CD24- phenotype. In vivo, benztropine mesylate inhibited tumor-initiating potential in a 4T1 mouse model. Functional studies indicated that benztropine mesylate inhibits functions of CSCs via the acetylcholine receptors, dopamine transporters/receptors, and/or histamine receptors. In summary, our findings identify benztropine mesylate as an inhibitor of BCSCs in vitro and in vivo. This study also provides a screening platform for identification of additional anti-CSC agents.ISSN:1949-255