Electronically Switchable Sham Transcranial Magnetic Stimulation (TMS) System

Transcranial magnetic stimulation (TMS) is increasingly being used to demonstrate the causal links between brain and behavior in humans. Further, extensive clinical trials are being conducted to investigate the therapeutic role of TMS in disorders such as depression. Because TMS causes strong peripheral effects such as auditory clicks and muscle twitches, experimental artifacts such as subject bias and placebo effect are clear concerns. Several sham TMS methods have been developed, but none of the techniques allows one to intermix real and sham TMS on a trial-by-trial basis in a double-blind manner. We have developed an attachment that allows fast, automated switching between Standard TMS and two types of control TMS (Sham and Reverse) without movement of the coil or reconfiguration of the setup. We validate the setup by performing mathematical modeling, search-coil and physiological measurements. To see if the stimulus conditions can be blinded, we conduct perceptual discrimination and sensory perception studies. We verify that the physical properties of the stimulus are appropriate, and that successive stimuli do not contaminate each other. We find that the threshold for motor activation is significantly higher for Reversed than for Standard stimulation, and that Sham stimulation entirely fails to activate muscle potentials. Subjects and experimenters perform poorly at discriminating between Sham and Standard TMS with a figure-of-eight coil, and between Reverse and Standard TMS with a circular coil. Our results raise the possibility of utilizing this technique for a wide range of applications

Model-based machine learning to identify clinical relevance in a high-resolution simulation of sepsis and trauma

Introduction: Sepsis is a devastating, costly, and complicated disease. It represents the summation of varied host immune responses in a clinical and physiological diagnosis. Despite extensive research, there is no current mediator-directed therapy, nor a biomarker panel able to categorize disease severity or reliably predict outcome. Although still distant from direct clinical translation, dynamic computational and mathematical models of acute systemic inflammation and sepsis are being developed. Although computationally intensive to run and calibrate, agent-based models (ABMs) are one type of model well suited for this. New analytical methods to efficiently extract knowledge from ABMs are needed. Specifically, machine-learning techniques are a promising option to augment the model development process such that parameterization and calibration are performed intelligently and efficiently. Methods: We used the Keras framework to train an Artificial Neural Network (ANN) for the purpose of identifying critical biological tipping points at which an in silico patient would heal naturally or require intervention in the Innate Immune Response Agent-Based Model (IIRABM). This ANN, determines simulated patient “survival” from cytokine state based on their overall resilience and the pathogenicity of any active infections experienced by the patient, defined by microbial invasiveness, toxigenesis, and environmental toxicity. These tipping points were gathered from previously generated datasets of simulated sweeps of the 4 IIRABM initializing parameters. Results: Using mean squared error as our loss function, we report an accuracy of greater than 85% with inclusion of 20% of the training set. This accuracy was independently validated on withheld runs. We note that there is some amount of error that is inherent to this process as the determination of the tipping points is a computation which converges monotonically to the true value as a function of the number of stochastic replicates used to determine the point. Conclusion: Our method of regression of these critical points represents an alternative to traditional parameter-sweeping or sensitivity analysis techniques. Essentially, the ANN computes the boundaries of the clinically relevant space as a function of the model’s parameterization, eliminating the need for a brute-force exploration of model parameter space. In doing so, we demonstrate the successful development of this ANN which will allows for an efficient exploration of model parameter space

Telescope Alignment From Sparsely Sampled Wavefront Measurements Over Pupil Subapertures

Alignment of two-element telescopes is a classic problem. During recent integration and test of the Space Interferometry Mission s (SIM s) Astrometric Beam Combiner (ABC), the innovators were faced with aligning two such telescope subsystems in the presence of a further complication: only two small subapertures in each telescope s pupil were accessible for measuring the wavefront with a Fizeau interferometer. This meant that the familiar aberrations that might be interpreted to infer system misalignments could be viewed only over small sub-regions of the pupil, making them hard to recognize. Further, there was no contiguous surface of the pupil connecting these two subapertures, so relative phase piston information was lost; the underlying full-aperture aberrations therefore had an additional degree of ambiguity. The solution presented here is to recognize that, in the absence of phase piston, the Zygo measurements primarily provide phase tilt in the subaperture windows of interest. Because these windows are small and situated far from the center of the (inaccessible) unobscured full aperture, any aberrations that are higher-order than tilt will be extremely high-order on the full aperture, and so not necessary or helpful to the alignment. Knowledge of the telescope s optical prescription allows straightforward evaluation of sensitivities (subap mode strength per unit full-aperture aberration), and these can be used in a predictive matrix approach to move with assurance to an aligned state. The technique is novel in every operational way compared to the standard approach of alignment based on full-aperture aberrations or searching for best rms wavefront. This approach is closely grounded in the observable quantities most appropriate to the problem. It is also more intuitive than inverting full phase maps (or subaperture Zernike spectra) with a ray-tracing program, which must certainly work in principle, but in practice met with limited success. Even if such classical alignment techniques became practical, the techniques reported here form a reassuringly transparent and intuitive check on the course of the alignment with very little computational effort

Infrared and microwaves at 5.8 GHz in a catalytic reactor

An improved micro-reactor cell for IR spectroscopic studies of heterogeneous catalysis was built around a 5.8 GHz microwave cavity. The reactor can operate at 20 bars and with conventional heating up to 720 K, with reactant gas flows velocities (GHSV) from 25 000 to 50 000 h−1. The temperature of the sample under microwave irradiation was measured by time resolved IR emission spectroscopy. The first experiment performed was the IR monitoring of the desorption of carbonates induced by irradiating an alumina sample by microwaves at 5.8 GHz

A design specification for Critical Illness Digital Twins to cure sepsis: responding to the National Academies of Sciences, Engineering and Medicine Report: Foundational Research Gaps and Future Directions for Digital Twins

On December 15, 2023, The National Academies of Sciences, Engineering and Medicine (NASEM) released a report entitled: Foundational Research Gaps and Future Directions for Digital Twins. The ostensible purpose of this report was to bring some structure to the burgeoning field of digital twins by providing a working definition and a series of research challenges that need to be addressed to allow this technology to fulfill its full potential. In the work presented herein we focus on five specific findings from the NASEM Report: 1) definition of a Digital Twin, 2) using fit-for-purpose guidance, 3) developing novel approaches to Verification, Validation and Uncertainty Quantification (VVUQ) of Digital Twins, 4) incorporating control as an explicit purpose for a Digital Twin and 5) using a Digital Twin to guide data collection and sensor development, and describe how these findings are addressed through the design specifications for a Critical Illness Digital Twin (CIDT) aimed at curing sepsis.Comment: 31 pages, 13 Figures, 1 Tabl

Children's Medicines in Tanzania: A National Survey of Administration Practices and Preferences.

The dearth of age-appropriate formulations of many medicines for children poses a major challenge to pediatric therapeutic practice, adherence, and health care delivery worldwide. We provide information on current administration practices of pediatric medicines and describe key stakeholder preferences for new formulation characteristics. We surveyed children aged 6-12 years, parents/caregivers over age 18 with children under age 12, and healthcare workers in 10 regions of Tanzania to determine current pediatric medicine prescription and administration practices as well as preferences for new formulations. Analyses were stratified by setting, pediatric age group, parent/caregiver education, and healthcare worker cadre. Complete data were available for 206 children, 202 parents/caregivers, and 202 healthcare workers. Swallowing oral solid dosage forms whole or crushing/dissolving them and mixing with water were the two most frequently reported methods of administration. Children frequently reported disliking medication taste, and many had vomited doses. Healthcare workers reported medicine availability most significantly influences prescribing practices. Most parents/caregivers and children prefer sweet-tasting medicine. Parents/caregivers and healthcare workers prefer oral liquid dosage forms for young children, and had similar thresholds for the maximum number of oral solid dosage forms children at different ages can take. There are many impediments to acceptable and accurate administration of medicines to children. Current practices are associated with poor tolerability and the potential for under- or over-dosing. Children, parents/caregivers, and healthcare workers in Tanzania have clear preferences for tastes and formulations, which should inform the development, manufacturing, and marketing of pediatric medications for resource-limited settings

The mass and anisotropy profiles of galaxy clusters from the projected phase space density: testing the method on simulated data

We present a new method of constraining the mass and velocity anisotropy profiles of galaxy clusters from kinematic data. The method is based on a model of the phase space density which allows the anisotropy to vary with radius between two asymptotic values. The characteristic scale of transition between these asymptotes is fixed and tuned to a typical anisotropy profile resulting from cosmological simulations. The model is parametrized by two values of anisotropy, at the centre of the cluster and at infinity, and two parameters of the NFW density profile, the scale radius and the scale mass. In order to test the performance of the method in reconstructing the true cluster parameters we analyze mock kinematic data for 20 relaxed galaxy clusters generated from a cosmological simulation of the standard LCDM model. We use Bayesian methods of inference and the analysis is carried out following the Markov Chain Monte Carlo approach. The parameters of the mass profile are reproduced quite well, but we note that the mass is typically underestimated by 15 percent, probably due to the presence of small velocity substructures. The constraints on the anisotropy profile for a single cluster are in general barely conclusive. Although the central asymptotic value is determined accurately, the outer one is subject to significant systematic errors caused by substructures at large clustercentric distance. The anisotropy profile is much better constrained if one performs joint analysis of at least a few clusters. In this case it is possible to reproduce the radial variation of the anisotropy over two decades in radius inside the virial sphere.Comment: 11 pages, 10 figures, accepted for publication in MNRA

Physical properties underlying observed kinematics of satellite galaxies

We study the kinematics of satellites around isolated galaxies selected from the Sloan Digital Sky Survey (SDSS) spectroscopic catalog. Using a model of the phase-space density previously measured for the halos of LCDM dark matter cosmological simulations, we determine the properties of the halo mass distribution and the orbital anisotropy of the satellites as a function of the colour-based morphological type and the stellar mass of the central host galaxy. We place constraints on the halo mass and the concentration parameter of dark matter and the satellite number density profiles. We obtain a concentration-mass relation for galactic dark matter haloes that is consistent with predictions of a standard LCDM cosmological model. At given halo or stellar mass, red galaxies have more concentrated halos than their blue counterparts. The fraction of dark matter within a few effective radii is minimal for 11.25<log M_star<11.5. The number density profile of the satellites appears to be shallower than of dark matter, with the scale radius typically 60 per cent larger than of dark matter. The orbital anisotropy around red hosts exhibits a mild excess of radial motions, in agreement with the typical anisotropy profiles found in cosmological simulations, whereas blue galaxies are found to be consistent with an isotropic velocity distribution. Our new constraints on the halo masses of galaxies are used to provide analytic approximations of the halo-to-stellar mass relation for red and blue galaxies.Comment: 12 pages, 11 figures; accepted for publication in MNRAS (updated references

Atmospheric Heating and Wind Acceleration: Results for Cool Evolved Stars based on Proposed Processes

A chromosphere is a universal attribute of stars of spectral type later than ~F5. Evolved (K and M) giants and supergiants (including the zeta Aurigae binaries) show extended and highly turbulent chromospheres, which develop into slow massive winds. The associated continuous mass loss has a significant impact on stellar evolution, and thence on the chemical evolution of galaxies. Yet despite the fundamental importance of those winds in astrophysics, the question of their origin(s) remains unsolved. What sources heat a chromosphere? What is the role of the chromosphere in the formation of stellar winds? This chapter provides a review of the observational requirements and theoretical approaches for modeling chromospheric heating and the acceleration of winds in single cool, evolved stars and in eclipsing binary stars, including physical models that have recently been proposed. It describes the successes that have been achieved so far by invoking acoustic and MHD waves to provide a physical description of plasma heating and wind acceleration, and discusses the challenges that still remain.Comment: 46 pages, 9 figures, 1 table; modified and unedited manuscript; accepted version to appear in: Giants of Eclipse, eds. E. Griffin and T. Ake (Berlin: Springer