Minimal model fusion rules from 2-groups

The fusion rules for the $(p,q)$-minimal model representations of the Virasoro algebra are shown to come from the group G = \boZ_2^{p+q-5} in the following manner. There is a partition $G = P_1 \cup ...\cup P_N$ into disjoint subsets and a bijection between $\{P_1,...,P_N\}$ and the sectors $\{S_1,...,S_N\}$ of the $(p,q)$-minimal model such that the fusion rules $S_i * S_j = \sum_k D(S_i,S_j,S_k) S_k$ correspond to $P_i * P_j = \sum_{k\in T(i,j)} P_k$ where $T(i,j) = \{k|\exists a\in P_i,\exists b\in P_j, a+b\in P_k\}$.Comment: 8 pages, amstex, v2.1, uses fonts msam, msbm, no figures, tables constructed using macros: cellular and related files are included. This paper will be submitted to Communications in Math. Physics. A compressed dvi file is available at ftp://math.binghamton.edu/pub/alex/fusionrules.dvi.Z , and compressed postscript at ftp://math.binghamton.edu/pub/alex/fusionrules.ps.

Micromechanical origin of plasticity and hysteresis in nest-like packings

Disordered packings of unbonded, semiflexible fibers represent a class of materials spanning contexts and scales. From twig-based bird nests to unwoven textiles, bulk mechanics of disparate systems emerge from the bending of constituent slender elements about impermanent contacts. In experimental and computational packings of wooden sticks, we identify prominent features of their response to cyclic oedometric compression: non-linear stiffness, transient plasticity, and eventually repeatable velocity-independent hysteresis. We trace these features to their micromechanic origins, identified in characteristic appearance, disappearance, and displacement of internal contacts

Beliefs around luck : confirming the empirical conceptualization of beliefs around luck and the development of the Darke and Freedman beliefs around luck scale

The current study developed a multi-dimensional measure of beliefs around luck. Two studies introduced the Darke and Freedman beliefs around luck scale where the scale showed a consistent 4 component model (beliefs in luck, rejection of luck, being lucky, and being unlucky) across two samples (n = 250; n = 145). The scales also show adequate reliability statistics and validity by ways of comparison with other measures of beliefs around luck, peer and family ratings and expected associations with measures of personality, individual difference and well-being variables

2000-2001 Master Class - Michael Sachs (Trumpet)

https://spiral.lynn.edu/conservatory_masterclasses/1187/thumbnail.jp

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales

Edge Node: A Multi-User Rendezvous and Proximity Operations On-Orbit Testbed

Edge Node is a multi-small satellite free-flying, collaborative testbed for formation flight and rendezvous and proximity operations (RPO) under development by The Aerospace Corporation that is planned for launch in 2026- 2027. Edge Node will develop and advance local space situational awareness sensors for CubeSat-scale platforms and facilitate the development and qualification of autonomous on-board RPO software for CubeSats. Edge Node is intended to serve as a multi-user on-orbit facility through which technologies and algorithms can be tested and validated in the authentic operational low Earth orbital environment. Edge Node leverages recent advances in miniature sensor and computing hardware for terrestrial applications (e.g., NVIDIA Jetson TX2 NX, automotive lidar and radar sensors, microbolometer LWIR camera, and polarization image sensors, among others). The mission will enable close-in observations including pose estimation, feature identification, and dynamic motion model characterization. Edge Node is specifically designed to test the limits of autonomous decision-making to support future missions where control with a ground operator in the loop is not possible. Edge Node builds on the prior success of RPO test facilities (e.g., SPHERES and AstroBee) that were confined to operate within the International Space Station (ISS). By operating independently in low-Earth orbit, experimenters will face realistic lighting, complex background scenes, and orbital dynamics that cannot be accurately replicated via terrestrial testbeds or within the confines of the ISS. The Edge Node mission’s computing platform, consisting of a cluster of NVIDIA Jetson TX2 NX modules, builds on a foundation of three prior qualification missions in low Earth orbit in addition to proton 50 MeV radiation testing of the target hardware. A radiation-tolerant 32-bit ARM Cortex-M7 processor oversees the TX2 NX cluster and interfaces with the rest of the spacecraft avionics. Dual terabyte NVMe drives running a ZFS filesystem provide enhanced reliability on top of radiation screened industrial NAND Flash storage drives. Edge Node will utilize a custom Linux environment utilizing Docker to containerize workloads and provide access to hardware including 256 NVIDIA CUDA GPU cores per TX2 NX for acceleration of workloads. The Robot Operating System (ROS2) will be utilized as an infrastructure layer for both intra-satellite and inter-satellite Remote Procedure Calls and data transport, offering useful communication patterns and will be the primary API for hosted applications from experimenters. An on-board autonomy watchdog ensures safety of flight while enabling advanced algorithm demonstrations (e.g., artificial intelligence / machine learning (AI/ML)). An earlier risk reduction payload, Edge Node Lite, comprising a subset of the sensing and computing hardware will launch as a hosted payload in early 2025. This risk reduction demonstration mission includes multiple advanced image-processing and machine-learning algorithm demonstrations provided by multiple mission partners

Ionized Gas in the Smith Cloud

We present WHAM observations of Halpha, [N II], and [S II] in the Smith Cloud. A map of Halpha emission from the cloud shows ionized gas coincident with the brightest H I emission, but nearly-as-bright Halpha in some regions with faint H I. The ionized mass of the cloud is at least as large as the neutral mass, > 10^6 M_sun. Ionized gas in the core of the Smith Cloud has an electron temperature 6000 K < T < 16000 K. The observed ratio [N II] / Halpha = 0.39 \pm 0.09 shows that the cloud has a non-primordial nitrogen abundance, 0.1 - 1 times solar.Comment: 4 pages, 2 figures. To appear in the proceedings of "The Role of Disk-Halo Interaction in Galaxy Evolution: Outflow vs Infall?", EAS Publication Serie