On the geometry of parallel impedances

A geometrical construction for the equivalent (sinusoidal) impedance of two impedances connected in parallel is presented. The special case of two resistors connected in parallel is reviewed     

A New Level-Set Model for the Representation of Non-Smooth Geometries

In Starinshak et al. (J Comput Phys 262(1):1–16, 2014), we proposed a new level-set model for representing multimaterial flows in multiple space dimensions. Rather than associating each level-set function with the boundary of a material, the new model associates each level-set function with a pair of materials and the interface that separates them. In this paper, we extend the model to represent geometries with non-smooth boundaries. The model uses multiple level-set functions to describe the shape boundary, typically with one level-set function per smooth boundary segment. Sign information is collected from all level-set functions and a voting algorithm is used to determine the interior/exterior of the geometric shape. The model is well suited for representing boundaries with singularities; it offers significant improvement over standard level-set approaches, both in shape preservation and area conservation; and it eliminates the need for costly redistancing of the level-set function. Numerical examples illustrate the superior performance of the proposed model.     

A Multiple-Criteria Approach to Ranking Computer Operating Systems

To select an operating system, an organization must consider several essential characteristics during its initial evaluation process. The analytic hierarchy process (AHP) offers an appropriate solution; the author illustrates it with a realistic case study in which an organization evaluates and ranks Windows XP, Linux, and Mac OS X 10.4.     

Labeling Schemes for Tree Representation

This paper deals with compact label-based representations for trees. Consider an n-node undirected connected graph G with a predefined numbering on the ports of each node. The all-ports tree labeling ℒ _all gives each node v of G a label containing the port numbers of all the tree edges incident to v. The upward tree labeling ℒ _up labels each node v by the number of the port leading from v to its parent in the tree. Our measure of interest is the worst case and total length of the labels used by the scheme, denoted M _up (T) and S _up (T) for ℒ _up and M _all (T) and S _all (T) for ℒ _all . The problem studied in this paper is the following: Given a graph G and a predefined port labeling for it, with the ports of each node v numbered by 0,…,deg (v)−1, select a rooted spanning tree for G minimizing (one of) these measures. We show that the problem is polynomial for M _up (T), S _up (T) and S _all (T) but NP-hard for M _all (T) (even for 3-regular planar graphs). We show that for every graph G and port labeling there exists a spanning tree T for which S _up (T)=O(nlog log n). We give a tight bound of O(n) in the cases of complete graphs with arbitrary labeling and arbitrary graphs with symmetric port labeling. We conclude by discussing some applications for our tree representation schemes. A preliminary version of this paper has appeared in the proceedings of the 7th International Workshop on Distributed Computing (IWDC), Kharagpur, India, December 27–30, 2005, as part of Cohen, R. et al.: Labeling schemes for tree representation. In: Proceedings of 7th International Workshop on Distributed Computing (IWDC), Lecture Notes of Computer Science, vol. 3741, pp. 13–24 (2005). R. Cohen supported by the Pacific Theaters Foundation. P. Fraigniaud and D. Ilcinkas supported by the project “PairAPair” of the ACI Masses de Données, the project “Fragile” of the ACI Sécurité et Informatique, and by the project “Grand Large” of INRIA. A. Korman supported in part by an Aly Kaufman fellowship. D. Peleg supported in part by a grant from the Israel Science Foundation.     

Velocity-Guided Tracking of Deformable Contours in Three Dimensional Space

This paper presents a 3D active contour model for boundary detection and tracking of non-rigid objects, which applies stereo vision and motion analysis to the class of energy-minimizing deformable contour models, known as snakes. The proposed contour evolves in three-dimensional space in reaction to a 3D potential function, which is derived by projecting the contour onto the 2D stereo images. The potential function is augmented by a kinetic term, which is related to the velocity field along the contour. This term is used to guide the inter-image contour displacement. The incorporation of inter-frame velocity estimates in the tracking algorithm is especially important for contours which evolve in 3D space, where the added freedom of motion can easily result in loss of tracking. The proposed scheme incorporates local velocity information seamlessly in the snake model, with little computational overhead, and does not require exogenous computation of the optical flow or related quantities in each image. The resulting algorithm is shown to provide good tracking performance with only one iteration per frame, which provides a considerable advantage for real time operation.     

Exosome Secretion and Epithelial-Mesenchymal Transition in Ovarian Cancer Are Regulated by Phospholipase D

Phospholipase D (PLD) isoenzymes participate in a variety of cellular functions that are mostly attributed to phosphatidic acid (PA) synthesis. Dysregulation of PLD regulates tumor progression and metastasis, yet little is known about the underlying mechanism. We previously reported on the expression and clinical role of the PLD isoenzymes PLD1 and PLD2 in tubo-ovarian high-grade serous carcinoma (HGSC). In the present study, we investigated the biological function of PLD1 and PLD2 using the OVCAR-3 and OVCAR-8 HGSC cell lines. KO cell lines for both PLDs were generated using CRISPR/CAS9 technology and assayed for exosome secretion, spheroid formation, migration, invasion and expression of molecules involved in epithelial-mesenchymal transition (EMT) and intracellular signaling. Significant differences between PLD1 and PLD2 KO cells and controls were observed for all the above parameters, supporting an important role for PLD in regulating migration, invasion, metastasis and EMT.     

A knowledge based system for the integrated design and manufacture of round broach tools

A complete knowledge based procedure for the design and manufacture of a round hole broach tool is described. The knowledge based design system (KBDS) produces a tool specification from user inputs describing the task to be performed. These design results are then used by the knowledge base to generate a geometric CAD/CAM representation, which can be utilized directly to display a drawing of the tool or to generate a CNC program for producing it. The process of formulating a knowledge-based design system demonstrates: the integration of expertise from experts, handbooks and theory; the awareness of restrictions on the scope of design that can be handled by a given system: the use of failure handling mechanisms to detect design failures and either adjust the emerging design or indicate infeasibility.     

Hyaluronan Synthase and Hyaluronidase Expression in Serous Ovarian Carcinoma is Related to Anatomic Site and Chemotherapy Exposure

The present study investigated the expression and clinical role of hyaluronan synthases (HAS1-3) and hyaluronidases (Hyal1-3) in serous ovarian carcinoma. HAS and HYAL mRNA expression was analyzed in 97 tumors (61 effusions, 27 primary carcinomas, 9 solid metastases) using PCR and further studied for association with clinicopathologic parameters, including survival. HAS1 mRNA was overexpressed in effusions compared to primary carcinomas and solid metastases (p < 0.001), and an alternatively spliced HAS1 was expressed only in effusions. HAS2 mRNA was overexpressed in solid metastases and primary carcinomas compared to effusions (p = 0.043), and HAS3 mRNA was overexpressed in primary carcinomas and effusions compared to solid metastases (p = 0.008). HYAL1 mRNA was absent in all specimens, whereas HYAL2 was expressed as two splice variants, of which HYAL2-var2 was overexpressed in solid metastases compared to effusions and primary carcinomas (p < 0.001). HYAL3 mRNA was expressed as wild-type and variant 1–3 form, the latter more highly in primary carcinomas and effusions compared to solid metastases (p = 0.006). HAS1 mRNA was overexpressed in pre- compared to post-chemotherapy effusions (p < 0.001), with opposite finding for HYAL2-var1 and HYAL3-WT (p = 0.016 and p = 0.024, respectively). Higher HYAL2-var1 and HAS1 splice variant mRNA expression in effusions was associated with longer (p = 0.033) and shorter (p = 0.047) overall survival, respectively. These data are the first to document a role for HAS and Hyal members in tumor progression in ovarian carcinoma, as evidenced by their differential expression as function of anatomic site and chemotherapy exposure, with a possible prognostic role for patients with malignant effusions.     

Discrete-time complementary models and smoothing

The fact that the smoothing error is a (wide sense) Markov process is somehow surprising since smoothed estimates depend upon both past and future data. In this paper we first give a simple and general proof of this fact. Then we use the so-called complementary models introduced by Weinert and Desai to derive forwards and backwards markovian models for the smoothing error in state-space models. By exploring the structure of the complementary models we show that, under certain restrictions, only two simple structured models exist, one that runs forwards in time and the other that runs backwards in time. The forwards complementary model leads to the forward Rauch-Tung-Striebel (RTS) smoothing formula and to a backwards markovian model for the error, whereas the backwards model leads to the backward RTS formula and to a forwards error model. The two models for the smoothing error can be derived one from the other by a forward-backward transformation that preserves the sample paths. Finally, by using a combination of the two complementary models we give yet another proof for the two-filter smoothing formula.