Further Development of the Sextupole and Decapole Spool Corrector Magnets for the LHC

In the Large Hadron Collider (LHC) the main dipoles will be equipped with sextupole (MCS) and decapole (MCD) spool correctors to meet the very high demands of field quality required for the satisfactory operation of the machine. Each decapole corrector will in addition have an octupole insert (MCO) and the assembly of the two is designated MCDO. These correctors are needed in relatively large quantities, i.e. 2464 MCS Sextupoles and 1232 MCDO Decapole-Octupole assemblies. Half the number of the required spool correctors will be made in India through a collaboration between CERN and CAT (Centre for Advanced Technology, Indore, India), the other half will be built by European industry. The paper describes final choices concerning design, materials, production techniques, and testing so as to assure economic magnet manufacture but while maintaining a homogenous magnetic quality that results in a robust product

Electronic depiction of magnetic origin in undoped and Fe doped TiO2-d epitaxial thin films

We have investigated the electronic and magnetic properties of the pulsed laser deposited epitaxial thin films of undoped and Fe doped (4 at. %) anatase TiO2-d by photoemission, magnetization measurements, and ab-initio band structure calculations. These films show room temperature magnetic ordering. It is observed that Fe ions hybridize with the oxygen vacancy induced Ti3+ defect states. Our study reveals the formation of local magnetic moment at Ti and Fe sites to be responsible for magnetic ordering. A finite density of states at the Fermi level in both undoped and Fe doped films is also observed, suggesting their degenerate semiconducting nature. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3640212]991

Magnetic stray fields in nanoscale magnetic tunnel junctions

The magnetic stray field is an unavoidable consequence of ferromagnetic devices and sensors leading to a natural asymmetry in magnetic properties. Such asymmetry is particularly undesirable for magnetic random access memory applications where the free layer can exhibit bias. Using atomistic dipole-dipole calculations we numerically simulate the stray magnetic field emanating from the magnetic layers of a magnetic memory device with different geometries. We find that edge effects dominate the overall stray magnetic field in patterned devices and that a conventional synthetic antiferromagnet structure is only partially able to compensate the field at the free layer position. A granular reference layer is seen to provide near-field flux closure while additional patterning defects add significant complexity to the stray field in nanoscale devices. Finally we find that the stray field from a nanoscale antiferromagnet is surprisingly non-zero arising from the imperfect cancellation of magnetic sublattices due to edge defects. Our findings provide an outline of the role of different layer structures and defects in the effective stray magnetic field in nanoscale magnetic random access memory devices and atomistic calculations provide a useful tools to study the stray field effects arising from a wide range of defects

Cooperative Sentry Vehicles And Differential GPS Leapfrog

As part of a project for the Defense Advanced Research Projects Agency, Sandia National Laboratories Intelligent Systems and Robotics Center is developing and testing the feasibility of using a cooperative team of robotic sentry vehicles to guard a perimeter, perform a surround task, and travel extended distances. This paper describes the authors most recent activities. In particular, this paper highlights the development of a Differential Global Positioning System (DGPS) leapfrog capability that allows two or more vehicles to alternate sending DGPS corrections. Using this leapfrog technique, this paper shows that a group of autonomous vehicles can travel 22.68 kilometers with a root mean square positioning error of only 5 meters

AudioPaLM: A Large Language Model That Can Speak and Listen

We introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt. We release examples of our method at https://google-research.github.io/seanet/audiopalm/examplesComment: Technical repor

Angiopoietin-1 promotes functional neovascularization that relieves ischemia by improving regional reperfusion in a swine chronic myocardial ischemia model

10.1007/s11373-006-9082-xJournal of Biomedical Science134579-59

Control of frequency chirp in nanosecond-pulsed laser spectroscopy. 2. A long-pulse optical parametric oscillator for narrow optical bandwidth

Richard T. White, Yabai He, Brian J. Orr, Mitsuhiko Kono, and K. G. H. Baldwinhttp://www.opticsinfobase.org/josab/issue.cfm?volume=21&issue=

Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex socio-technical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating them requires research methods that scale beyond the traditional areas of inquiry of Information Systems (IS) “individuals, organizations, and markets” and that deliver solutions in addition to insights. We describe an approach to address these challenges through Competitive Benchmarking (CB), a novel research method that helps interdisciplinary research communities to tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS-based solutions