529 research outputs found
Route Planning in Transportation Networks
We survey recent advances in algorithms for route planning in transportation
networks. For road networks, we show that one can compute driving directions in
milliseconds or less even at continental scale. A variety of techniques provide
different trade-offs between preprocessing effort, space requirements, and
query time. Some algorithms can answer queries in a fraction of a microsecond,
while others can deal efficiently with real-time traffic. Journey planning on
public transportation systems, although conceptually similar, is a
significantly harder problem due to its inherent time-dependent and
multicriteria nature. Although exact algorithms are fast enough for interactive
queries on metropolitan transit systems, dealing with continent-sized instances
requires simplifications or heavy preprocessing. The multimodal route planning
problem, which seeks journeys combining schedule-based transportation (buses,
trains) with unrestricted modes (walking, driving), is even harder, relying on
approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4,
previously published by Microsoft Research. This work was mostly done while
the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at
Microsoft Research Silicon Valle
Structural and thermodynamic characterization of the adrenodoxin-like domain of the electron-transfer protein Etp1 from Schizosaccharomyces pombe
The protein Etp1 of Schizosaccharomyces pombe consists of an amino-terminal COX15-like domain and a carboxy-terminal ferredoxin-like domain, Etp1(fd), which is cleaved off after mitochondrial import. The physiological function of Etp1(fd) is supposed to lie in the participation in the assembly of iron-sulfur clusters and the synthesis of heme A. In addition, the protein was shown to be the first microbial ferredoxin being able to support electron transfer in mitochondrial steroid hydroxylating cytochrome P450 systems in vivo and in vitro, replacing thereby the native redox partner, adrenodoxin. Despite a sequence similarity of 39% and the fact that fission yeast is a mesophilic organism, thermodynamic studies revealed that Etp1(fd) has a melting temperature more than 20°C higher than adrenodoxin. The three-dimensional structure of Etp1(fd) has been determined by crystallography. To the best of our knowledge it represents the first three-dimensional structure of a yeast ferredoxin. The structure-based sequence alignment of Etp1(fd) with adrenodoxin yields a rational explanation for their observed mutual exchangeability in the cytochrome P450 system. Analysis of the electron exchange with the S. pombe redox partner Arh1 revealed differences between Etp1(fd) and adrenodoxin, which might be linked to their different physiological functions in the mitochondria of mammals and yeast
Colored Non-Crossing Euclidean Steiner Forest
Given a set of -colored points in the plane, we consider the problem of
finding trees such that each tree connects all points of one color class,
no two trees cross, and the total edge length of the trees is minimized. For
, this is the well-known Euclidean Steiner tree problem. For general ,
a -approximation algorithm is known, where is the
Steiner ratio.
We present a PTAS for , a -approximation algorithm
for , and two approximation algorithms for general~, with ratios
and
Mental Health Service Utilization before and after Receipt of a Service‐Connected Disability Award for PTSD: Findings from a National Sample
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/1/hesr12859.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/2/hesr12859-sup-0001-AppendixSA1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/3/hesr12859_am.pd
The role of asymmetric dimethylarginine (ADMA) in COVID-19: association with respiratory failure and predictive role for outcome
We aimed to assess the potential role of Asymmetric dimethylarginine (ADMA) in conditioning respiratory function and pulmonary vasoregulation during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) infection. Within 72 h from admission, samples from 90 COVID-19 patients were assessed for ADMA, SDMA, L-arginine concentrations. In addition to classical statistics, patients were also clustered by a machine learning approach according to similar features. Multivariable analysis showed that C-reactive protein (OR 1.012), serum ADMA (OR 4.652), white blood cells (OR = 1.118) and SOFA (OR = 1.495) were significantly associated with negative outcomes. Machine learning-based clustering showed three distinct clusters: (1) patients with low severity not requiring invasive mechanical ventilation (IMV), (2) patients with moderate severity and respiratory failure whilst not requiring IMV, and (3) patients with highest severity requiring IMV. Serum ADMA concentration was significantly associated with disease severity and need for IMV although less pulmonary vasodilation was observed by CT scan. High serum levels of ADMA are indicative of high disease severity and requirement of mechanical ventilation. Serum ADMA at the time of hospital admission may therefore help to identify COVID-19 patients at high risk of deterioration and negative outcome
Quantum gates using electronic and nuclear spins of Yb in a magnetic field gradient
An efficient scheme is proposed to carry out gate operations on an array of
trapped Yb ions, based on a previous proposal using both electronic and
nuclear degrees of freedom in a magnetic field gradient. For this purpose we
consider the Paschen-Back regime (strong magnetic field) and employ a
high-field approximation in this treatment. We show the possibility to suppress
the unwanted coupling between the electron spins by appropriately swapping
states between electronic and nuclear spins. The feasibility of generating the
required high magnetic field is discussed
Quantum Gates and Memory using Microwave Dressed States
Trapped atomic ions have been successfully used for demonstrating basic
elements of universal quantum information processing (QIP). Nevertheless,
scaling up of these methods and techniques to achieve large scale universal
QIP, or more specialized quantum simulations remains challenging. The use of
easily controllable and stable microwave sources instead of complex laser
systems on the other hand promises to remove obstacles to scalability.
Important remaining drawbacks in this approach are the use of magnetic field
sensitive states, which shorten coherence times considerably, and the
requirement to create large stable magnetic field gradients. Here, we present
theoretically a novel approach based on dressing magnetic field sensitive
states with microwave fields which addresses both issues and permits fast
quantum logic. We experimentally demonstrate basic building blocks of this
scheme to show that these dressed states are long-lived and coherence times are
increased by more than two orders of magnitude compared to bare magnetic field
sensitive states. This changes decisively the prospect of microwave-driven ion
trap QIP and offers a new route to extend coherence times for all systems that
suffer from magnetic noise such as neutral atoms, NV-centres, quantum dots, or
circuit-QED systems.Comment: 9 pages, 4 figure
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