Accurate exchange-correlation energies for the warm dense electron gas

Density matrix quantum Monte Carlo (DMQMC) is used to sample exact-on-average $N$-body density matrices for uniform electron gas systems of up to 10$^{124}$ matrix elements via a stochastic solution of the Bloch equation. The results of these calculations resolve a current debate over the accuracy of the data used to parametrize finite-temperature density functionals. Exchange-correlation energies calculated using the real-space restricted path-integral formalism and the $k$-space configuration path-integral formalism disagree by up to $\sim$$10$\% at certain reduced temperatures $T/T_F \le 0.5$ and densities $r_s \le 1$. Our calculations confirm the accuracy of the configuration path-integral Monte Carlo results available at high density and bridge the gap to lower densities, providing trustworthy data in the regime typical of planetary interiors and solids subject to laser irradiation. We demonstrate that DMQMC can calculate free energies directly and present exact free energies for $T/T_F \ge 1$ and $r_s \le 2$.Comment: Accepted version: added free energy data and restructured text. Now includes supplementary materia

Ultrasound in the diagnosis of a median neuropathy in the forearm: case report

<p>Abstract</p> <p>Background</p> <p>Electrodiagnostic studies are traditionally used in the diagnosis of focal neuropathies, however they lack anatomical information regarding the nerve and its surrounding structures. The purpose of this case is to show that high-resolution ultrasound used as an adjunct to electrodiagnostic studies may complement this lack of information and give insight to the cause.</p> <p>Case presentation</p> <p>A 60-year-old male patient sustained a forearm traction injury resulting in progressive weakness and functional loss in the first three digits of the right hand. High-resolution ultrasound showed the presence of an enlarged nerve and a homogenous soft-tissue structure appearing to engulf the nerve. The contralateral side was normal. Surgery revealed fibrotic bands emanating from the flexor digitorum profundus muscle compressing the median nerve thus confirming the ultrasound findings.</p> <p>Conclusion</p> <p>A diagnostically challenging case of median neuropathy in the forearm is presented in which high-resolution ultrasound was valuable in establishing an anatomic etiology and directing appropriate management.</p

Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients

Quantification of myocardial perfusion has the potential to improve detection of regional and global flow reduction. Significant effort has been made to automate the workflow, where one essential step is the arterial input function (AIF) extraction. Since failure here invalidates quantification, high accuracy is required. For this purpose, this study presents a robust AIF detection method using the convolutional neural net (CNN) model. CNN models were trained by assembling 25,027 scans (N=12,984 patients) from three hospitals, seven scanners. A test set of 5,721 scans (N=2,805 patients) evaluated model performance. The 2D+T AIF time series was inputted into CNN. Two variations were investigated: a) Two Classes (2CS) for background and foreground (LV mask); b) Three Classes (3CS) for background, foreground LV and RV. Final model was deployed on MR scanners via the Gadgetron InlineAI. Model loading time on MR scanner was ~340ms and applying it took ~180ms. The 3CS model successfully detect LV for 99.98% of all test cases (1 failed out of 5,721 cases). The mean Dice ratio for 3CS was 0.87+/-0.08 with 92.0% of all test cases having Dice ratio >0.75, while the 2CS model gave lower Dice of 0.82+/-0.22 (P<1e-5). Extracted AIF signals using CNN were further compared to manual ground-truth for foot-time, peak-time, first-pass duration, peak value and area-under-curve. No significant differences were found for all features (P>0.2). This study proposed, validated, and deployed a robust CNN solution to detect the LV for the extraction of the AIF signal used in fully automated perfusion flow mapping. A very large data cohort was assembled and resulting models were deployed to MR scanners for fully inline AI in clinical hospitals.Comment: Accepted by Magnetic Resonance in Medicine on March 30, 202

Age-stratified heritability estimation in the Framingham Heart Study families

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31–49 years, 50–60 years, and 61–79 years), reflecting the longitudinal nature of the data, for four quantitative traits. Age-adjusted heritability estimates were obtained at a single common time point for the same four quantitative traits. The importance of these groups is that they consist of the same individuals. The highest age-stratified heritability estimate (h(2 )= 0.88 (± 0.06)) was for height in the model adjusting for gender over all three age groups. SBP gave the lowest heritability estimate (h(2 )= 0.15 (± 0.11)) for the 70 age group in the model adjusting for gender, height, BMI, smoker, and drinker. BMI had slightly higher estimates (h(2 )= 0.64 (± 0.11)) in the 40 age group than previously published. The highest age-adjusted heritability estimate (h(2 )= 0.90 (± 0.06)) was for height in the model adjusting for gender. SBP gave the lowest heritability estimate (h(2 )= 0.38 (± 0.09)) for unadjusted model. These results indicate that some common, complex traits may vary little in their genetic architecture over time and suggest that a common set of genes may be contributing to observed variation for these longitudinally collected phenotypes

Determination of the Thermal Noise Limit of Graphene Biotransistors

To determine the thermal noise limit of graphene biotransistors, we have measured the complex impedance between the basal plane of single-layer graphene and an aqueous electrolyte. The impedance is dominated by an imaginary component but has a finite real component. Invoking the fluctuation–dissipation theorem, we determine the power spectral density of thermally driven voltage fluctuations at the graphene/electrolyte interface. The fluctuations have 1/f[superscript p] dependence, with p = 0.75–0.85, and the magnitude of fluctuations scales inversely with area. Our results explain noise spectra previously measured in liquid-gated suspended graphene devices and provide realistic targets for future device performance.Keywords: Noise, Liquid gate, Graphene field-effect transistor, 1/f noise, Biosenso

Measurement of high carrier mobility in graphene in an aqueous electrolyte environment

Graphene is a promising material for applications in aqueous electrolyte environments. To explore the impact of such environments on graphene's electrical properties, we performed Hall bar measurements on electrolyte-gated graphene. Assuming a Drude model, we find that the room temperature carrier mobility in water-gated, SiO₂-supported graphene reaches 7000 cm²/Vs, comparable to the best dry SiO₂-supported graphene devices. Our results show that the electrical performance of graphene is robust, even in the presence of dissolved ions that introduce an additional mechanism for Coulomb scattering

Electrical Monitoring of sp³ Defect Formation in Individual Carbon Nanotubes

Many carbon nanotube (CNT) applications require precisely controlled chemical functionalization that is minimally disruptive to electrical performance. A promising approach is the generation of sp³ hybridized carbon atoms in the sp²-bonded lattice. We have investigated the possibility of using a carboxylic acid functionalized diazonium reagent to introduce a defined number of sp³ defects into electrically-contacted CNTs. Having performed real-time measurements on individually-contacted CNTs, we show that the formation of an individual defect is accompanied by an upward jump in resistance of approximately 6 kΩ. Additionally, we observe downward jumps in resistance of the same size, indicating that some defects are unstable. Our results are explained by a two-step reaction mechanism. Isolated aryl groups, formed in the first step, are unstable and dissociate on the minute timescale. Stable defect generation requires a second step, the coupling of a second aryl group adjacent to the first. Additional mechanistic understanding is provided by a systematic investigation of the gate voltage dependence of the reaction, showing that defect formation can be turned on and off. In summary, we demonstrate an unprecedented level of control over sp³ defect formation in electrically-contacted CNTs, and prove that sp³ defects are minimally disruptive to the electrical performance of CNTs

Cardiovascular Outcomes in Acute Coronary Syndrome and Malnutrition: A Meta-Analysis of Nutritional Assessment Tools

Background: There is emerging evidence that malnutrition is associated with poor prognosis among patients with acute coronary syndrome (ACS). // Objectives: This study seeks to elucidate the prognostic impact of malnutrition in patients with ACS and provide a quantitative review of most commonly used nutritional assessment tools. // Methods: Medline and Embase were searched for studies reporting outcomes in patients with malnutrition and ACS. Nutritional screening tools of interest included the Prognostic Nutrition Index, Geriatric Nutritional Risk Index, and Controlling Nutritional Status. A comparative meta-analysis was used to estimate the risk of all-cause mortality and cardiovascular events based on the presence of malnutrition and stratified according to ACS type, ACS intervention, ethnicity, and income. // Results: Thirty studies comprising 37,303 patients with ACS were included, of whom 33.5% had malnutrition. In the population with malnutrition, the pooled mortality rate was 20.59% (95% CI: 14.95%-27.67%). Malnutrition was significantly associated with all-cause mortality risk after adjusting for confounders including age and left ventricular ejection fraction (adjusted HR: 2.66, 95% CI: 1.78-3.96, P = 0.004). There was excess mortality in the group with malnutrition regardless of ACS type (P = 0.132), ethnicity (P = 0.245), and income status (P = 0.058). Subgroup analysis demonstrated no statistically significant difference in mortality risk between individuals with and without malnutrition (P = 0.499) when using Controlling Nutritional Status (OR: 7.80, 95% CI: 2.17-28.07, P = 0.011), Geriatric Nutritional Risk Index (OR: 4.30, 95% CI: 2.78-6.66, P < 0.001), and Prognostic Nutrition Index (OR: 4.67, 95% CI: 2.38-9.17, P = 0.023). // Conclusions: Malnutrition was significantly associated with all-cause mortality risk following ACS, regardless of ACS type, ethnicity, and income status, underscoring the importance of screening and interventional strategies for patients with malnutrition

Making Sense of Blockchain Applications:A Typology for HCI

Blockchain is an emerging infrastructural technology that is proposed to fundamentally transform the ways in which people transact, trust, collaborate, organize and identify themselves. In this paper, we construct a typology of emerging blockchain applications, consider the domains in which they are applied, and identify distinguishing features of this new technology. We argue that there is a unique role for the HCI community in linking the design and application of blockchain technology towards lived experience and the articulation of human values. In particular, we note how the accounting of transactions, a trust in immutable code and algorithms, and the leveraging of distributed crowds and publics around vast interoperable databases all relate to longstanding issues of importance for the field. We conclude by highlighting core conceptual and methodological challenges for HCI researchers beginning to work with blockchain and distributed ledger technologies