arXiv subjects

Robert Miller

Publications and source records attributed to Robert Miller.

11 recordsLinked to original sources

arXiv2026

Demonstration of a scalable all-solid-state refrigerator exploiting diffusion geometries and limiting interfacial conductances at temperatures below 1 kelvin

Solid-state refrigerators using Normal-metal/Insulator/Superconductor (NIS) junctions have previously demonstrated excellent electron cooling but limited ability to cool phonons. The energy gap of the superconductor is used as an energy filter to allow higher than average energy electrons to preferentially tunnel from the normal-metal through the insulator into the superconductor where they travel as quasi-particles. Typically, the heat is moved and work is done to deposit hot quasi-particles into a normal-metal quasi-particle trap for rejection to the next refrigeration stage. Realizing that (1) the quasi-particles flow diffusively, driven by a concentration gradient in the electric field-free superconductor, and (2) that the undesirable backwards leaking of heat from the hot-side trap can be reduced by engineering the geometry and materials at the superconductor-to-trap interface, enhanced cooling can be achieved. Fabrication of the refrigerator was accomplished using a tungsten and titanium-tungsten alloy as the cold-side normal-metal, aluminum oxide as the insulator, aluminum as the superconductor, and gold as the trap, with the cold-side NIS portion being attached to the hot-side gold trap by bump bonding. The refrigerator consisted of 1121 junction pairs, each pair being an SINIS unit, all electrically connected in series. Using this we have measured the effective phonon temperature of a 3.9 mm x 3.9 mm x 0.65 mm silicon chip driven down to 70 mK from a bath temperature of 120 mK, and down to 174 mK from a 271 mK rejection temperature (a cooling of -97 mK). This is the first demonstration of the sub 1 K cooling of an entire silicon chip using NIS junctions.

cond-mat.supr-con↗

arXiv2026

Testing three models of cognitive stress effects: A psychopharmacological randomized controlled trial of acute stress and stress hormones across visual perception, response inhibition and cognitive flexibility

Acute stress alters cognitive performance, yet competing models make divergent predictions regarding the mechanisms, scope, and temporal dynamics of these effects. This large-scale randomized controlled trial tested predications from three influential stress-effect models using a broad cognitive task battery embedded within a psychopharmacological stress paradigm. Across 606 testing sessions, 303 healthy male participants completed both the Maastricht Acute Stress Test (MAST) and its non-stress control condition. To independently manipulate acute stress and stress hormone availability, participants were additionally randomized to receive atomoxetine (40 mg; to prolong norepinephrine availability), hydrocortisone (10 mg; to increase cortisol availability), or placebo. Cognitive performance was assessed over 80-minutes (post-stress) using tasks targeting visual perception (rapid serial visual presentation), response inhibition (stop-signal), and cognitive flexibility (dual and switch tasks). MAST exposure selectively impaired response inhibition, reflected in shorter stop-signal delays, lower probabilities of successful stopping and prolonged stop-signal reaction times, particularly during later testing phases (40-80 minutes post-stress). MAST exposure did not affect visual perception or task-switching performance but buffered time-related declines in processing efficiency at the expense of task prioritization in the dual task. Pharmacological manipulation of norepinephrine or cortisol availability was effective but did not moderate cognitive stress effects. Overall, this pattern of task-specific impairment alongside stabilized processing efficiency cannot be fully explained by any tested model, highlighting the need to refine existing models and adopt more integrative approaches to advance our mechanistic understanding of cognitive stress-effects in laboratory and real-world contexts.

q-bio.NC↗

arXiv2021

An Open Natural Language Processing Development Framework for EHR-based Clinical Research: A case demonstration using the National COVID Cohort Collaborative (N3C)

While we pay attention to the latest advances in clinical natural language processing (NLP), we can notice some resistance in the clinical and translational research community to adopt NLP models due to limited transparency, interpretability, and usability. In this study, we proposed an open natural language processing development framework. We evaluated it through the implementation of NLP algorithms for the National COVID Cohort Collaborative (N3C). Based on the interests in information extraction from COVID-19 related clinical notes, our work includes 1) an open data annotation process using COVID-19 signs and symptoms as the use case, 2) a community-driven ruleset composing platform, and 3) a synthetic text data generation workflow to generate texts for information extraction tasks without involving human subjects. The corpora were derived from texts from three different institutions (Mayo Clinic, University of Kentucky, University of Minnesota). The gold standard annotations were tested with a single institution's (Mayo) ruleset. This resulted in performances of 0.876, 0.706, and 0.694 in F-scores for Mayo, Minnesota, and Kentucky test datasets, respectively. The study as a consortium effort of the N3C NLP subgroup demonstrates the feasibility of creating a federated NLP algorithm development and benchmarking platform to enhance multi-institution clinical NLP study and adoption. Although we use COVID-19 as a use case in this effort, our framework is general enough to be applied to other domains of interest in clinical NLP.

cs.CL↗

arXiv2021

Automating LC-MS/MS mass chromatogram quantification. Wavelet transform based peak detection and automated estimation of peak boundaries and signal-to-noise ratio using signal processing methods

While there are many different methods for peak detection, no automatic methods for marking peak boundaries to calculate area under the curve (AUC) and signal-to-noise ratio (SNR) estimation exist. An algorithm for the automation of liquid chromatography tandem mass spectrometry (LC-MS/MS) mass chromatogram quantification was developed and validated. Continuous wavelet transformation and other digital signal processing methods were used in a multi-step procedure to calculate concentrations of six different analytes. To evaluate the performance of the algorithm, the results of the manual quantification of 446 hair samples with 6 different steroid hormones by two experts were compared to the algorithm results. The proposed approach of automating mass chromatogram quantification is reliable and valid. The algorithm returns less nondetectables than human raters. Based on signal to noise ratio, human non-detectables could be correctly classified with a diagnostic performance of AUC = 0.95. The algorithm presented here allows fast, automated, reliable, and valid computational peak detection and quantification in LC- MS/MS.

q-bio.QM↗

arXiv2020

A rapidly updating stratified mix-adjusted median property price index model

Homeowners, first-time buyers, banks, governments and construction companies are highly interested in following the state of the property market. Currently, property price indexes are published several months out of date and hence do not offer the up-to-date information which housing market stakeholders need in order to make informed decisions. In this article, we present an updated version of a central-price tendency based property price index which uses geospatial property data and stratification in order to compare similar houses. The expansion of the algorithm to include additional parameters owing to a new data structure implementation and a richer dataset allows for the construction of a far smoother and more robust index than the original algorithm produced.

stat.AP↗

arXiv2020

GeoTree: a data structure for constant time geospatial search enabling a real-time mix-adjusted median property price index

A common problem appearing across the field of data science is $k$-NN ($k$-nearest neighbours), particularly within the context of Geographic Information Systems. In this article, we present a novel data structure, the GeoTree, which holds a collection of geohashes (string encodings of GPS co-ordinates). This enables a constant $O\left(1\right)$ time search algorithm that returns a set of geohashes surrounding a given geohash in the GeoTree, representing the approximate $k$-nearest neighbours of that geohash. Furthermore, the GeoTree data structure retains $O\left(n\right)$ memory requirement. We apply the data structure to a property price index algorithm focused on price comparison with historical neighbouring sales, demonstrating an enhanced performance. The results show that this data structure allows for the development of a real-time property price index, and can be scaled to larger datasets with ease.

cs.DS↗

arXiv2019

A blockchain-orchestrated Federated Learning architecture for healthcare consortia

We propose a novel architecture for federated learning within healthcare consortia. At the heart of the solution is a unique integration of privacy preserving technologies, built upon native enterprise blockchain components available in the Ethereum ecosystem. We show how the specific characteristics and challenges of healthcare consortia informed our design choices, notably the conception of a new Secure Aggregation protocol assembled with a protected hardware component and an encryption toolkit native to Ethereum. Our architecture also brings in a privacy preserving audit trail that logs events in the network without revealing identities.

cs.CY↗

arXiv2017

How to disentangle psychobiological stress reactivity and recovery: A comparison of model-based and non-compartmental analyses of cortisol concentrations

This article seeks to address the prevailing issue of how to measure specific process components of psychobiological stress responses. Particularly the change of cortisol secretion due to stress exposure has been discussed as an endophenotype of many psychosomatic health outcomes. To assess its process components, a large variety of non-compartmental parameters (i.e., composite measures of substance concentrations at different points in time) like the area under the concentration-time curve (AUC) are utilized. However, a systematic evaluation and validation of these parameters based on a physiologically plausible model of cortisol secretion has not been performed so far. Thus, a population pharmacokinetic (mixed-effects SDE) model was developed and fitted to densely sampled salivary cortisol data of 10 males from Montreal, Canada, and sparsely sampled data of 200 mixed-sex participants from Dresden, Germany, who completed the Trier Social Stress Test (TSST). Besides the two major process components representing (1) stress-related cortisol secretion (reactivity) and (2) cortisol elimination (recovery), the model incorporates two additional, often disregarded components: (3) the secretory delay after stress onset, and (4) deviations from the projected steady-state concentration. The fitted model (R2 = 99%) was thereafter used to investigate the correlation structure of the four individually varying, and readily interpretable model parameters and eleven popular non-compartmental parameters. Based on these analyses, we recommend to use the minimum-maximum cortisol difference and the minimum concentration as proxy measures of reactivity and recovery, respectively. Finally, statistical power analyses of the reactivity-related sex effect illustrate the consequences of using impure non-compartmental measures of the different process components that underlie the cortisol stress response.

q-bio.QM↗

arXiv2017

On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times

Inferring processes or constructs from performance data is a major hallmark of cognitive psychometrics. Particularly, diffusion modeling of response times (RTs) from correct and erroneous responses using the Wiener distribution has become a popular measurement tool because it provides a set of psychologically interpretable parameters. However, an important precondition to identify all of these parameters is a sufficient number of RTs from erroneous responses. In the present article, we show by simulation that the parameters of the Wiener distribution can be recovered from tasks yielding very high or even perfect response accuracies using the shifted Wald distribution. Specifically, we argue that error RTs can be modeled as correct RTs that have undergone censoring by using techniques from parametric survival analysis. We illustrate our reasoning by fitting the Wiener and (censored) shifted Wald distribution to RTs from six participants who completed a Go/No-go task. In accordance with our simulations, diffusion modeling using the Wiener and the shifted Wald distribution yielded identical parameter estimates when the number of erroneous responses was predicted to be low. Moreover, the modeling of error RTs as censored correct RTs substantially improved the recovery of these diffusion parameters when premature trial timeout was introduced to increase the number of omission errors. Thus, the censored shifted Wald distribution provides a suitable means for diffusion modeling in situations when the Wiener distribution cannot be fitted without parametric constraints.

q-bio.NC↗

arXiv2011

Human-powered Sorts and Joins

Crowdsourcing markets like Amazon's Mechanical Turk (MTurk) make it possible to task people with small jobs, such as labeling images or looking up phone numbers, via a programmatic interface. MTurk tasks for processing datasets with humans are currently designed with significant reimplementation of common workflows and ad-hoc selection of parameters such as price to pay per task. We describe how we have integrated crowds into a declarative workflow engine called Qurk to reduce the burden on workflow designers. In this paper, we focus on how to use humans to compare items for sorting and joining data, two of the most common operations in DBMSs. We describe our basic query interface and the user interface of the tasks we post to MTurk. We also propose a number of optimizations, including task batching, replacing pairwise comparisons with numerical ratings, and pre-filtering tables before joining them, which dramatically reduce the overall cost of running sorts and joins on the crowd. In an experiment joining two sets of images, we reduce the overall cost from $67 in a naive implementation to about $3, without substantially affecting accuracy or latency. In an end-to-end experiment, we reduced cost by a factor of 14.5.

cs.DB↗

arXiv2005

Poly-MTO, {(CH_3)_{0.92} Re O_3}_\infty, a Conducting Two-Dimensional Organometallic Oxide

Polymeric methyltrioxorhenium, {(CH_{3})_{0.92}ReO_{3}}_{\infty} (poly-MTO), is the first member of a new class of organometallic hybrids which adopts the structural pattern and physical properties of classical perovskites in two dimensions (2D). We demonstrate how the electronic structure of poly-MTO can be tailored by intercalation of organic donor molecules, such as tetrathiafulvalene (TTF) or bis-(ethylendithio)-tetrathiafulvalene (BEDT-TTF), and by the inorganic acceptor SbF$_3$. Integration of donor molecules leads to a more insulating behavior of poly-MTO, whereas SbF$_3$ insertion does not cause any significant change in the resistivity. The resistivity data of pure poly-MTO is remarkably well described by a two-dimensional electron system. Below 38 K an unusual resistivity behavior, similar to that found in doped cuprates, is observed: The resistivity initially increases approximately as $ρ\sim$ ln$(1/T$) before it changes into a $\sqrt{T}$ dependence below 2 K. As an explanation we suggest a crossover from purely two-dimensional charge-carrier diffusion within the \{ReO$_2$\}$_{\infty}$ planes at high temperatures to three-dimensional diffusion at low temperatures in a disorder-enhanced electron-electron interaction scenario (Altshuler-Aronov correction). Furthermore, a linear positive magnetoresistance was found in the insulating regime, which is caused by spatial localization of itinerant electrons at some of the Re atoms, which formally adopt a $5d^1$ electronic configuration. X-ray diffraction, IR- and ESR-studies, temperature dependent magnetization and specific heat measurements in various magnetic fields suggest that the electronic structure of poly-MTO can safely be approximated by a purely 2D conductor.

cond-mat.mtrl-sci↗