The Modulation of Multiple Phases Leading to the Modified KdV Equation

This paper seeks to derive the modified KdV (mKdV) equation using a novel approach from systems generated from abstract Lagrangians that possess a two-parameter symmetry group. The method to do uses a modified modulation approach, which results in the mKdV emerging with coefficients related to the conservation laws possessed by the original Lagrangian system. Alongside this, an adaptation of the method of Kuramoto is developed, providing a simpler mechanism to determine the coefficients of the nonlinear term. The theory is illustrated using two examples of physical interest, one in stratified hydrodynamics and another using a coupled Nonlinear Schr\"odinger model, to illustrate how the criterion for the mKdV equation to emerge may be assessed and its coefficients generated.Comment: 35 pages, 5 figure

Low thrust orbit determination program

Logical flow and guidelines are provided for the construction of a low thrust orbit determination computer program. The program, tentatively called FRACAS (filter response analysis for continuously accelerating spacecraft), is capable of generating a reference low thrust trajectory, performing a linear covariance analysis of guidance and navigation processes, and analyzing trajectory nonlinearities in Monte Carlo fashion. The choice of trajectory, guidance and navigation models has been made after extensive literature surveys and investigation of previous software. A key part of program design relied upon experience gained in developing and using Martin Marietta Aerospace programs: TOPSEP (Targeting/Optimization for Solar Electric Propulsion), GODSEP (Guidance and Orbit Determination for SEP) and SIMSEP (Simulation of SEP)

Hemorrhage into an Occult Spinal Ependymoma after Epidural Anesthesia

Summary of Background Data: Five cases of hemorrhage into a spinal neoplasm after spinal or epidural anesthesia are reported in the literature. Presentation ranges from severe low back pain to acute cauda equina syndrome. Methods: A case study of a patient who hemorrhaged into an intradural, extramedullary spinal cord mass was performed. A detailed literature review is also provided. Results: A 27 year old female underwent epidural anesthesia for Cesarean section delivery. She presented with a 3 week history of increasing low back pain with bilateral radiculopathy. Imaging studies revealed a large hemorrhagic intradural mass compressing the lower conus medullaris and cauda equina, which operatively was confirmed to be a myxopapillary ependymoma. Conclusions: We report a case of hemorrhage into a previously unrecognized ependymoma after epidural anesthesia. Underlying tumors may rarely complicate regional anesthesia in the lumbar spine

Case Report: Hemorrhage into an Occult Spinal Ependymoma after Epidural Anesthesia

Epidural anesthesia is a procedure which is well tolerated and has a low incidence of adverse events. In performing caesarean sections, regional anesthesia (spinal or epidural) is the preferred modality for anesthetic delivery. Although rare with continuous epidural anesthesia, epidural hematomas have been reported to occur with an incidence between 1:150,000 and 1:190,00010. An underlying bleeding diathesis has been implicated as a causative factor. We present the sixth reported case of hemorrhage into an occult intradural neoplasm after spinal or epidural anesthesia. Similar lesions have not been reported in the recent spine literature

Most vital segment barriers

We study continuous analogues of "vitality" for discrete network flows/paths, and consider problems related to placing segment barriers that have highest impact on a flow/path in a polygonal domain. This extends the graph-theoretic notion of "most vital arcs" for flows/paths to geometric environments. We give hardness results and efficient algorithms for various versions of the problem, (almost) completely separating hard and polynomially-solvable cases

Creating massive entanglement of Bose condensed atoms

We propose a direct, coherent coupling scheme that can create massively entangled states of Bose-Einstein condensed atoms. Our idea is based on an effective interaction between two atoms from coherent Raman processes through a (two atom) molecular intermediate state. We compare our scheme with other recent proposals for generation of massive entanglement of Bose condensed atoms.Comment: 5 pages, 3 figures; Updated figure 3(a), original was "noisy

Plk1 Phosphorylation of Orc2 and Hbo1 Contributes to Gemcitabine Resistance in Pancreatic Cancer

Although gemcitabine is the standard chemotherapeutic drug for treatment of pancreatic cancer, almost all patients eventually develop resistance to this agent. Previous studies identified Polo-like kinase 1 (Plk1) as the mediator of gemcitabine resistance, but the molecular mechanism remains unknown. In this study, we show that Plk1 phosphorylation of Orc2 and Hbo1 mediates the resistance to gemcitabine. We show that the level of Plk1 expression positively correlates with gemcitabine resistance, both in pancreatic cancer cells and xenograft tumors. Overexpression of Plk1 increases gemcitabine resistance, while inhibition of Plk1 sensitizes pancreatic cancer cells to gemcitabine treatment. To validate our findings, we show that inhibition of Plk1 sensitizes tumors to gemcitabine treatment in a mouse xenograft study. Mechanistically, we find that Plk1 phosphorylation of Orc2 maintains DNA replication on gemcitabine treatment. Furthermore, Plk1 phosphorylation of Hbo1 transcriptionally increases cFos expression and consequently elevates its target multidrug resistance 1 (MDR1), which was previously reported to confer chemotherapeutic drug resistance. Knockdown of cFos or MDR1 sensitizes gemcitabine-resistant cells to gemcitabine treatment. Finally, pancreatic cancer cells expressing Plk1-unphosphorylatable mutants of Orc2 or Hbo1 are more sensitive to gemcitabine than cells expressing wild-type Orc2 or Hbo1. In short, our study provides a mechanism for Plk1-mediated gemcitabine resistance, suggesting that Plk1 is a promising target for treatment of gemcitabine-resistant pancreatic cancer

2003 Manifesto on the California Electricity Crisis

The authors, an ad-hocgroup of professionals with experience in regulatory and energy economics, share a common concern with the continuing turmoil facing the electricity industry ("the industry") in California. Most ofthe authorsendorsed the first California Electricity Manifesto issued on January 25, 2001. Almost two years have passed since that first Manifesto. While wholesale electric prices have moderated and California no longer faces the risk of blackouts, in many ways the industry is in worse shape now than it was at the start of 2001. As a result, the group of signatories continues to have a deep concern with the conflicting policy directions being pursued for the industry at both the State and Federal levels of government and the impact the uncertainties associated with these conflicting policies will have, long term, on the economy of California. Theauthorshave once again convened under the auspices of the Institute of Management, Innovation and Organization at the University of California, Berkeley, to put forward ourtheir ideas on a basic set of necessary policies to move the industry forward for the benefit of all Californians and the nation. The authors point out that theydo not pretend to be "representative." They do bring, however, a very diverse range of backgrounds and expertise.Technology and Industry, Regulatory Reform

Ground Delay Program Analytics with Behavioral Cloning and Inverse Reinforcement Learning

We used historical data to build two types of model that predict Ground Delay Program implementation decisions and also produce insights into how and why those decisions are made. More specifically, we built behavioral cloning and inverse reinforcement learning models that predict hourly Ground Delay Program implementation at Newark Liberty International and San Francisco International airports. Data available to the models include actual and scheduled air traffic metrics and observed and forecasted weather conditions. We found that the random forest behavioral cloning models we developed are substantially better at predicting hourly Ground Delay Program implementation for these airports than the inverse reinforcement learning models we developed. However, all of the models struggle to predict the initialization and cancellation of Ground Delay Programs. We also investigated the structure of the models in order to gain insights into Ground Delay Program implementation decision making. Notably, characteristics of both types of model suggest that GDP implementation decisions are more tactical than strategic: they are made primarily based on conditions now or conditions anticipated in only the next couple of hours

Fast, scalable, Bayesian spike identification for multi-electrode arrays

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate