Brain connectivity Patterns Dissociate action of specific Acupressure Treatments in Fatigued Breast cancer survivors

Funding This work was supported by grants R01 CA151445 and 2UL1 TR000433-06 from the National Institutes of Health. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. We thank the expert assistance by Dr. Bradley Foerster in acquisition of 1H-MRS and fMRI data.Peer reviewedPublisher PD

Exploring More-Coherent Quantum Annealing

In the quest to reboot computing, quantum annealing (QA) is an interesting candidate for a new capability. While it has not demonstrated an advantage over classical computing on a real-world application, many important regions of the QA design space have yet to be explored. In IARPA's Quantum Enhanced Optimization (QEO) program, we have opened some new lines of inquiry to get to the heart of QA, and are designing testbed superconducting circuits and conducting key experiments. In this paper, we discuss recent experimental progress related to one of the key design dimensions: qubit coherence. Using MIT Lincoln Laboratory's qubit fabrication process and extending recent progress in flux qubits, we are implementing and measuring QA-capable flux qubits. Achieving high coherence in a QA context presents significant new engineering challenges. We report on techniques and preliminary measurement results addressing two of the challenges: crosstalk calibration and qubit readout. This groundwork enables exploration of other promising features and provides a path to understanding the physics and the viability of quantum annealing as a computing resource.Comment: 7 pages, 3 figures. Accepted by the 2018 IEEE International Conference on Rebooting Computing (ICRC

Physically-Adaptive Computing via Introspection and Self-Optimization in Reconfigurable Systems.

Digital electronic systems typically must compute precise and deterministic results, but in principle have flexibility in how they compute. Despite the potential flexibility, the overriding paradigm for more than 50 years has been based on fixed, non-adaptive inte-grated circuits. This one-size-fits-all approach is rapidly losing effectiveness now that technology is advancing into the nanoscale. Physical variation and uncertainty in com-ponent behavior are emerging as fundamental constraints and leading to increasingly sub-optimal fault rates, power consumption, chip costs, and lifetimes. This dissertation pro-poses methods of physically-adaptive computing (PAC), in which reconfigurable elec-tronic systems sense and learn their own physical parameters and adapt with fine granu-larity in the field, leading to higher reliability and efficiency. We formulate the PAC problem and provide a conceptual framework built around two major themes: introspection and self-optimization. We investigate how systems can efficiently acquire useful information about their physical state and related parameters, and how systems can feasibly re-implement their designs on-the-fly using the information learned. We study the role not only of self-adaptation—where the above two tasks are performed by an adaptive system itself—but also of assisted adaptation using a remote server or peer. We introduce low-cost methods for sensing regional variations in a system, including a flexible, ultra-compact sensor that can be embedded in an application and implemented on field-programmable gate arrays (FPGAs). An array of such sensors, with only 1% to-tal overhead, can be employed to gain useful information about circuit delays, voltage noise, and even leakage variations. We present complementary methods of regional self-optimization, such as finding a design alternative that best fits a given system region. We propose a novel approach to characterizing local, uncorrelated variations. Through in-system emulation of noise, previously hidden variations in transient fault sus-ceptibility are uncovered. Correspondingly, we demonstrate practical methods of self-optimization, such as local re-placement, informed by the introspection data. Forms of physically-adaptive computing are strongly needed in areas such as com-munications infrastructure, data centers, and space systems. This dissertation contributes practical methods for improving PAC costs and benefits, and promotes a vision of re-sourceful, dependable digital systems at unimaginably-fine physical scales.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78922/1/kzick_1.pd

Trial of Essiac to Ascertain Its Effect in Women with Breast Cancer (TEA-BC)

Background: Breast cancer is a major cause of morbidity, mortality, and medical expenditures among women in Canada. Essiac (Resperin™ Canada Limited, Waterloo, Ontario, Canada), a blend of at least four herbs (burdock root [Arctium lappa], Indian rhubarb [Rheum palmatum], sheep sorrel [Rumex acetosella], and the inner bark of slippery elm [Ulmus fulva or U. rubra]), has become one of the more popular herbal remedies for breast-cancer treatment, secondary prevention, improving quality of life, and controlling negative side-effects of conventional breast-cancer treatment. Objectives: Our primary objective was to determine the difference in health-related quality of life (HR-QOL), as assessed by the Functional Assessment of Cancer Therapy Breast Cancer Version, between women who are new Essiac users (since breast cancer diagnosis) and those who have never used Essiac. Secondary endpoints included differences in depression, anxiety, fatigue, rate of adverse events, and prevalence of complications or benefits associated with Essiac during standard breast-cancer treatment. Additionally, we described the pattern of use of Essiac in this cohort of women. Methods: We performed a retrospective cohort study in 510 women, randomly chosen from the Ontario Cancer Tumour Registry, with a diagnosis of primary breast cancer in 2003. Results: With the exception changes in a Physical well-being subscale and a relationship with doctor subscale, Essiac did not have a significant effect on HR-QOL or mood states. Even for Physical well-being and relationship with doctor, Essiac seemed to have a negative effect, with Essiac users doing worse than the non-Essiac users. This might be attributed to the fact that the group of users comprised younger women with more advanced stages of breast cancer, and both of these subgroups of patients have been shown to be at a significantly increased risk for negative mood states and/or a decreased sense of well-being. The women were taking low doses (total daily dose 43.6 ± 30.8 mL) of Essiac that corresponded to the label directions found on most Essiac products. Friends were the most common source of information, and most women were taking Essiac to boost their immune systems or increase their chances of survival. Only 2 women reported minor adverse events, whereas numerous women reported beneficial effects of Essiac. Conclusions: Essiac does not appear to improve HR-QOL or mood states. Future studies are needed to determine whether other clinical outcomes, such as cancer reoccurrence, are affected by Essiac.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63199/1/acm.2006.12.971.pd

A Numerical Model for Brownian Particles Fluctuating in Incompressible Fluids

We present a numerical method that consistently implements thermal fluctuations and hydrodynamic interactions to the motion of Brownian particles dispersed in incompressible host fluids. In this method, the thermal fluctuations are introduced as random forces acting on the Brownian particles. The hydrodynamic interactions are introduced by directly resolving the fluid motions with the particle motion as a boundary condition to be satisfied. The validity of the method has been examined carefully by comparing the present numerical results with the fluctuation-dissipation theorem whose analytical form is known for dispersions of a single spherical particle. Simulations are then performed for more complicated systems, such as a dispersion composed of many spherical particles and a single polymeric chain in a solvent.Comment: 6 pages, 8 figure

Relaxation Acupressure Reduces Persistent Cancer-Related Fatigue

Persistent cancer-related fatigue (PCRF) is a symptom experienced by many cancer survivors. Acupressure offers a potential treatment for PCRF. We investigated if acupressure treatments with opposing actions would result in differential effects on fatigue and examined the effect of different “doses” of acupressure on fatigue. We performed a trial of acupressure in cancer survivors experiencing moderate to severe PCRF. Participants were randomized to one of three treatment groups: relaxation acupressure (RA), high-dose stimulatory acupressure (HIS), and low-dose stimulatory acupressure (LIS). Participants performed acupressure for 12-weeks. Change in fatigue as measured by the Brief Fatigue Inventory (BFI) was our primary outcome. Secondary outcomes were assessment of blinding and compliance to treatment. Fatigue was significantly reduced across all treatment groups (mean ± SD reduction in BFI: RA 4.0 ± 1.5, HIS 2.2 ± 1.6, LIS 2.7 ± 2.2), with significantly greater reductions in the RA group. In an adjusted analysis, RA resulted in significantly less fatigue after controlling for age, cancer type, cancer stage, and cancer treatments. Self-administered RA caused greater reductions in fatigue compared to either HIS or LIS. The magnitude of the reduction in fatigue was clinically relevant and could represent a viable alternative for cancer survivors with PCRF

Anneal-path correction in flux qubits

Quantum annealers require accurate control and optimized operation schemes to reduce noise levels, in order to eventually demonstrate a computational advantage over classical algorithms. We study a high coherence four-junction capacitively shunted flux qubit (CSFQ), using dispersive measurements to extract system parameters and model the device. Josephson junction asymmetry inherent to the device causes a deleterious nonlinear cross-talk when annealing the qubit. We implement a nonlinear annealing path to correct the asymmetry in-situ, resulting in a substantial increase in the probability of the qubit being in the correct state given an applied flux bias. We also confirm the multi-level structure of our CSFQ circuit model by annealing it through small spectral gaps and observing quantum signatures of energy level crossings. Our results demonstrate an anneal-path correction scheme designed and implemented to improve control accuracy for high-coherence and high-control quantum annealers, which leads to an enhancement of success probability in annealing protocols.Comment: v2 published versio

The MOSDEF survey: a stellar mass-SFR-metallicity relation exists at z∼2.3z\sim2.3

We investigate the nature of the relation among stellar mass, star-formation rate, and gas-phase metallicity (the M$_*$-SFR-Z relation) at high redshifts using a sample of 260 star-forming galaxies at $z\sim2.3$ from the MOSDEF survey. We present an analysis of the high-redshift M$_*$-SFR-Z relation based on several emission-line ratios for the first time. We show that a M$_*$-SFR-Z relation clearly exists at $z\sim2.3$. The strength of this relation is similar to predictions from cosmological hydrodynamical simulations. By performing a direct comparison of stacks of $z\sim0$ and $z\sim2.3$ galaxies, we find that $z\sim2.3$ galaxies have $\sim0.1$ dex lower metallicity at fixed M$_*$ and SFR. In the context of chemical evolution models, this evolution of the M$_*$-SFR-Z relation suggests an increase with redshift of the mass-loading factor at fixed M$_*$, as well as a decrease in the metallicity of infalling gas that is likely due to a lower importance of gas recycling relative to accretion from the intergalactic medium at high redshifts. Performing this analysis simultaneously with multiple metallicity-sensitive line ratios allows us to rule out the evolution in physical conditions (e.g., N/O ratio, ionization parameter, and hardness of the ionizing spectrum) at fixed metallicity as the source of the observed trends with redshift and with SFR at fixed M$_*$ at $z\sim2.3$. While this study highlights the promise of performing high-order tests of chemical evolution models at high redshifts, detailed quantitative comparisons ultimately await a full understanding of the evolution of metallicity calibrations with redshift.Comment: 19 pages, 8 figures, accepted to Ap

The MOSDEF Survey: Kinematic and Structural Evolution of Star-Forming Galaxies at 1.4≤z≤3.81.4\leq z\leq 3.8

We present ionized gas kinematics for 681 galaxies at $z\sim 1.4-3.8$ from the MOSFIRE Deep Evolution Field survey, measured using models which account for random galaxy-slit misalignments together with structural parameters derived from CANDELS Hubble Space Telescope (HST) imaging. Kinematics and sizes are used to derive dynamical masses. Baryonic masses are estimated from stellar masses and inferred gas masses from dust-corrected star formation rates (SFRs) and the Kennicutt-Schmidt relation. We measure resolved rotation for 105 galaxies. For the remaining 576 galaxies we use models based on HST imaging structural parameters together with integrated velocity dispersions and baryonic masses to statistically constrain the median ratio of intrinsic ordered to disordered motion, $V/\sigma_{V,0}$. We find that $V/\sigma_{V,0}$ increases with increasing stellar mass and decreasing specific SFR (sSFR). These trends may reflect marginal disk stability, where systems with higher gas fractions have thicker disks. For galaxies with detected rotation we assess trends between their kinematics and mass, sSFR, and baryon surface density ($\Sigma_{\mathrm{bar},e}$). Intrinsic dispersion correlates most with $\Sigma_{\mathrm{bar},e}$ and velocity correlates most with mass. By comparing dynamical and baryonic masses, we find that galaxies at $z\sim 1.4-3.8$ are baryon dominated within their effective radii ($R_E$), with Mdyn/Mbaryon increasing over time. The inferred baryon fractions within $R_E$, $f_{\mathrm{bar}}$, decrease over time, even at fixed mass, size, or surface density. At fixed redshift, $f_{\mathrm{bar}}$ does not appear to vary with stellar mass but increases with decreasing $R_E$ and increasing $\Sigma_{\mathrm{bar},e}$. For galaxies at $z\geq2$, the median inferred baryon fractions generally exceed 100%. We discuss possible explanations and future avenues to resolve this tension.Comment: Accepted to ApJ. Added Figure 9, corrected sample size (main results unchanged). 28 pages, 13 figure