Stanford Aerospace Research Laboratory research overview

Over the last ten years, the Stanford Aerospace Robotics Laboratory (ARL) has developed a hardware facility in which a number of space robotics issues have been, and continue to be, addressed. This paper reviews two of the current ARL research areas: navigation and control of free flying space robots, and modelling and control of extremely flexible space structures. The ARL has designed and built several semi-autonomous free-flying robots that perform numerous tasks in a zero-gravity, drag-free, two-dimensional environment. It is envisioned that future generations of these robots will be part of a human-robot team, in which the robots will operate under the task-level commands of astronauts. To make this possible, the ARL has developed a graphical user interface (GUI) with an intuitive object-level motion-direction capability. Using this interface, the ARL has demonstrated autonomous navigation, intercept and capture of moving and spinning objects, object transport, multiple-robot cooperative manipulation, and simple assemblies from both free-flying and fixed bases. The ARL has also built a number of experimental test beds on which the modelling and control of flexible manipulators has been studied. Early ARL experiments in this arena demonstrated for the first time the capability to control the end-point position of both single-link and multi-link flexible manipulators using end-point sensing. Building on these accomplishments, the ARL has been able to control payloads with unknown dynamics at the end of a flexible manipulator, and to achieve high-performance control of a multi-link flexible manipulator

Mixed-mode oscillations and interspike interval statistics in the stochastic FitzHugh-Nagumo model

We study the stochastic FitzHugh-Nagumo equations, modelling the dynamics of neuronal action potentials, in parameter regimes characterised by mixed-mode oscillations. The interspike time interval is related to the random number of small-amplitude oscillations separating consecutive spikes. We prove that this number has an asymptotically geometric distribution, whose parameter is related to the principal eigenvalue of a substochastic Markov chain. We provide rigorous bounds on this eigenvalue in the small-noise regime, and derive an approximation of its dependence on the system's parameters for a large range of noise intensities. This yields a precise description of the probability distribution of observed mixed-mode patterns and interspike intervals.Comment: 36 page

Bipartite entangled stabilizer mutually unbiased bases as maximum cliques of Cayley graphs

We examine the existence and structure of particular sets of mutually unbiased bases (MUBs) in bipartite qudit systems. In contrast to well-known power-of-prime MUB constructions, we restrict ourselves to using maximally entangled stabilizer states as MUB vectors. Consequently, these bipartite entangled stabilizer MUBs (BES MUBs) provide no local information, but are sufficient and minimal for decomposing a wide variety of interesting operators including (mixtures of) Jamiolkowski states, entanglement witnesses and more. The problem of finding such BES MUBs can be mapped, in a natural way, to that of finding maximum cliques in a family of Cayley graphs. Some relationships with known power-of-prime MUB constructions are discussed, and observables for BES MUBs are given explicitly in terms of Pauli operators.Comment: 8 pages, 1 figur

Technique for Specifying the Fatty Acid at the SN2 Position of Acylglycerol Lipids

A method for specifying a fatty acid at the sn2 position of acylglycerol lipids including (a) transfecting a vector including the SLC1 gene or a variant thereof into embryonic biological material, and (b) allowing the SLC1 gene to specify the type of fatty acid at the sn2 position of acylglycerol lipids. Also provided for is an isolated SLC1 gene and a probe for its detection

Maximally symmetric stabilizer MUBs in even prime-power dimensions

One way to construct a maximal set of mutually unbiased bases (MUBs) in a prime-power dimensional Hilbert space is by means of finite phase-space methods. MUBs obtained in this way are covariant with respect to some subgroup of the group of all affine symplectic phase-space transformations. However, this construction is not canonical: as a consequence, many different choices of covariance sugroups are possible. In particular, when the Hilbert space is $2^n$ dimensional, it is known that covariance with respect to the full group of affine symplectic phase-space transformations can never be achieved. Here we show that in this case there exist two essentially different choices of maximal subgroups admitting covariant MUBs. For both of them, we explicitly construct a family of $2^n$ covariant MUBs. We thus prove that, contrary to the odd dimensional case, maximally covariant MUBs are very far from being unique.Comment: 22 page

MUBs inequivalence and affine planes

There are fairly large families of unitarily inequivalent complete sets of N+1 mutually unbiased bases (MUBs) in C^N for various prime powers N. The number of such sets is not bounded above by any polynomial as a function of N. While it is standard that there is a superficial similarity between complete sets of MUBs and finite affine planes, there is an intimate relationship between these large families and affine planes. This note briefly summarizes "old" results that do not appear to be well-known concerning known families of complete sets of MUBs and their associated planes.Comment: This is the version of this paper appearing in J. Mathematical Physics 53, 032204 (2012) except for format changes due to the journal's style policie

Systematic Identification of Coordination Gaps in Pediatric Care

In the United States, the status of coordination among pediatric care services is not well understood. Through the use of quality improvement (QI) techniques, coordination gaps were systematically identified in the interagency network of pediatric services in Kalamazoo MI. Gaps were found in transportation resources, follow-up procedures, awareness of services, interagency communication, insurance limitations, population behaviors, and resource utilization. This preliminary study reveals the need for (1) protocols for intra- and inter-agency communication, (2) mechanisms for easy and fast retrieval of pediatric resources, and (3) health information exchange

Toward a consensus nomenclature for ghrelin, its non-acylated form, liver expressed antimicrobial peptide 2 and growth hormone secretagogue receptor

The stomach-derived octanoylated peptide ghrelin was discovered in 1999 and recognized as an endogenous agonist of the growth hormone secretagogue receptor (GHSR). Subsequently, ghrelin has been shown to play key roles in controlling not only growth hormone secretion, but also a variety of other physiological functions including, but not limited to, food intake, reward-related behaviors, glucose homeostasis and gastrointestinal tract motility. Importantly, a non-acylated form of ghrelin, desacyl-ghrelin, can also be detected in biological samples. Desacyl-ghrelin, however, does not bind to GHSR at physiological levels, and its physiological role has remained less well-characterized than that of ghrelin. Ghrelin and desacyl-ghrelin are currently referred to in the literature using many different terms, highlighting the need for a consistent nomenclature. The variability of terms used to designate ghrelin can lead not only to confusion, but also to miscommunication, especially for those who are less familiar with the ghrelin literature. Thus, we conducted a survey among experts who have contributed to the ghrelin literature aiming to identify whether a consensus may be reached. Based on the results of this consensus, we propose using the terms “ghrelin” and “desacyl-ghrelin” to refer to the hormone itself and its non-acylated form, respectively. Based on the results of this consensus, we further propose using the terms “GHSR” for the receptor, and “LEAP2” for liver-expressed antimicrobial peptide 2, a recently recognized endogenous GHSR antagonist/inverse agonist.Fil: Perello, Mario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Dickson, Suzanne L.. The Sahlgrenska Academy at the University of Gothenburg; SueciaFil: Zigman, Jeffrey M.. UT Southwestern Medical Center; Estados UnidosFil: Leggio, Lorenzo. National Institutes of Health; Estados Unido