Charge Offset Stability in Si Single Electron Devices with Al Gates

We report on the charge offset drift (time stability) in Si single electron devices (SEDs) defined with aluminum (Al) gates. The size of the charge offset drift (0.15 $e$) is intermediate between that of Al/AlO$_x$/Al tunnel junctions (greater than 1 $e$) and Si SEDs defined with Si gates (0.01 $e$). This range of values suggests that defects in the AlO$_x$ are the main cause of the charge offset drift instability

Sex differences in atheroma burden and endothelial function in patients with early coronary atherosclerosis

Aims Women and men have different clinical presentations and outcomes in coronary artery disease (CAD). We tested the hypothesis that sex differences may influence coronary atherosclerotic burden and coronary endothelial function before development of obstructive CAD. Methods and results A total of 142 patients (53 men, 89 women; mean ± SD age, 49.3 ± 11.7 years) with early CAD simultaneously underwent intravascular ultrasonography and coronary endothelial function assessment. Atheroma burden in the left main and proximal left anterior descending (LAD) arteries was significantly greater in men than women (median, 23.0% vs. 14.1%, P = 0.002; median, 40.1% vs. 29.3%, P = 0.001, respectively). Atheroma eccentricity in the proximal LAD artery was significantly higher in men than women (median, 0.89 vs. 0.80, P = 0.04). The length of the coronary segments with endothelial dysfunction was significantly longer in men than women (median, 39.2 vs. 11.1 mm, P = 0.002). In contrast, maximal coronary flow reserve was significantly lower in women than men (2.80 vs. 3.30, P < 0.001). Sex was an independent predictor of atheroma burden in the left main and proximal LAD arteries (both P < 0.05) by multivariate analysis. Conclusion Men have greater atheroma burden, more eccentric atheroma, and more diffuse epicardial endothelial dysfunction than women. These results suggest that men have more severe structural and functional abnormalities in epicardial coronary arteries than women, even in patients with early atherosclerosis, which may result in the higher incidence rates of CAD and ST-segment myocardial infarction in men than wome

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy

Abstract Background Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing continuous renal replacement therapy (CRRT) for severe acute kidney injury. Accordingly, the present study applies machine learning algorithms to improve prediction accuracy for this patient subset. Methods We randomly divided a total of 1571 adult patients who started CRRT for acute kidney injury into training (70%, n = 1094) and test (30%, n = 477) sets. The primary output consisted of the probability of mortality during admission to the intensive care unit (ICU) or hospital. We compared the area under the receiver operating characteristic curves (AUCs) of several machine learning algorithms with that of the APACHE II, SOFA, and the new abbreviated mortality scoring system for acute kidney injury with CRRT (MOSAIC model) results. Results For the ICU mortality, the random forest model showed the highest AUC (0.784 [0.744–0.825]), and the artificial neural network and extreme gradient boost models demonstrated the next best results (0.776 [0.735–0.818]). The AUC of the random forest model was higher than 0.611 (0.583–0.640), 0.677 (0.651–0.703), and 0.722 (0.677–0.767), as achieved by APACHE II, SOFA, and MOSAIC, respectively. The machine learning models also predicted in-hospital mortality better than APACHE II, SOFA, and MOSAIC. Conclusion Machine learning algorithms increase the accuracy of mortality prediction for patients undergoing CRRT for acute kidney injury compared with previous scoring models

Real-time feedback protocols for optimizing fault-tolerant two-qubit gate fidelities in a silicon spin system

Recently, several groups have demonstrated two-qubit gate fidelities in semiconductor spin qubit systems above 99%. Achieving this regime of fault-tolerant compatible high fidelities is nontrivial and requires exquisite stability and precise control over the different qubit parameters over an extended period of time. This can be done by efficiently calibrating qubit control parameters against different sources of micro- and macroscopic noise. Here, we present several single- and two-qubit parameter feedback protocols, optimised for and implemented in state-of-the-art fast FPGA hardware. Furthermore, we use wavelet-based analysis on the collected feedback data to gain insight into the different sources of noise in the system. Scalable feedback is an outstanding challenge and the presented implementation and analysis gives insight into the benefits and drawbacks of qubit parameter feedback, as feedback related overhead increases. This work demonstrates a pathway towards robust qubit parameter feedback and systematic noise analysis, crucial for mitigation strategies towards systematic high-fidelity qubit operation compatible with quantum error correction protocols

Spatio-temporal correlations of noise in MOS spin qubits

In quantum computing, characterising the full noise profile of qubits can aid the efforts towards increasing coherence times and fidelities by creating error mitigating techniques specific to the type of noise in the system, or by completely removing the sources of noise. Spin qubits in MOS quantum dots are exposed to noise originated from the complex glassy behaviour of two-level fluctuators, leading to non-trivial correlations between qubit properties both in space and time. With recent engineering progress, large amounts of data are being collected in typical spin qubit device experiments, and it is beneficiary to explore data analysis options inspired from fields of research that are experienced in managing large data sets, examples include astrophysics, finance and climate science. Here, we propose and demonstrate wavelet-based analysis techniques to decompose signals into both frequency and time components to gain a deeper insight into the sources of noise in our systems. We apply the analysis to a long feedback experiment performed on a state-of-the-art two-qubit system in a pair of SiMOS quantum dots. The observed correlations serve to identify common microscopic causes of noise, as well as to elucidate pathways for multi-qubit operation with a more scalable feedback system.Comment: updated referenc

Entangling gates on degenerate spin qubits dressed by a global field

Coherently dressed spins have shown promising results as building blocks for future quantum computers owing to their resilience to environmental noise and their compatibility with global control fields. This mode of operation allows for more amenable qubit architecture requirements and simplifies signal routing on the chip. However, multi-qubit operations, such as qubit addressability and two-qubit gates, are yet to be demonstrated to establish global control in combination with dressed qubits as a viable path to universal quantum computing. Here we demonstrate simultaneous on-resonance driving of degenerate qubits using a global field while retaining addressability for qubits with equal Larmor frequencies. Furthermore, we implement SWAP oscillations during on-resonance driving, constituting the demonstration of driven two-qubit gates. Significantly, our findings highlight the fragility of entangling gates between superposition states and how dressing can increase the noise robustness. These results represent a crucial milestone towards global control operation with dressed qubits. It also opens a door to interesting spin physics on degenerate spins

Renal ischemia–reperfusion injury causes intercalated cell-specific disruption of occludin in the collecting duct

Renal ischemic events open tight junctions and disrupt epithelial polarity. The purpose of this study was to examine the effects of ischemia–reperfusion (IR) injury on expression and distribution of the tight junction proteins, occludin and ZO-1, in the rat kidney. IR injury was induced by clamping both renal pedicles for 30 min and animals were killed at 6 h after the reperfusion. IR injury decreased blood bicarbonate level, but did not persistently alter pH, Na+, K+, or Cl−. In control kidneys, occludin immunoreactivity was intense in the tight junctions in the thick ascending limb, distal convoluted tubule, and collecting duct, moderate in the thin limbs of the loop of Henle, and was not detected in the proximal tubule, glomerulus, and blood vessels. ZO-1 was expressed in the same sites in which occludin was expressed, and additionally was also expressed in the proximal tubule, glomerulus, and vascular endothelial cells. IR kidneys exhibited damaged renal tubular epithelial cells in both proximal tubule and collecting duct segments in the outer medulla. In the collecting duct, the response of intercalated cells and principal cells differed. Following IR injury, intercalated cells, but not principal cells, lost their normal epithelial polarity and were frequently extruded into the tubule lumen. Occludin, instead of being localized to tight junctions, was localized diffusely in the cytoplasm in intercalated cells of IR kidneys. Principal cells, in contrast, were not detectably affected and neither occludin nor ZO-1 expression were altered in response to IR injury. The normal localization of ZO-1 expression to tight junction sites in both the proximal tubule and collecting duct was altered in response to IR, and, instead, ZO-1 expression was present diffusely in the cytoplasm. IR injury did not alter detectably either occludin or ZO-1 localization to the tight junction of the thick ascending limb cells. The abundance of total occludin protein by immunoblot analysis was not changed with IR injury. These results demonstrate that renal IR injury causes tight junction disruptions in both the proximal tubule and the collecting duct, and that altered distribution of the tight junction protein, occludin, may play a critical role in the collecting duct dysfunction which IR induces

Coronary Computed Tomographic Angiography at 80 kVp and Knowledge-Based Iterative Model Reconstruction Is Non-Inferior to that at 100 kVp with Iterative Reconstruction

The aims of this study were to compare the image noise and quality of coronary computed tomographic angiography (CCTA) at 80 kVp with knowledge-based iterative model reconstruction (IMR) to those of CCTA at 100 kVp with hybrid iterative reconstruction (IR), and to evaluate the feasibility of a low-dose radiation protocol with IMR. Thirty subjects who underwent prospective electrocardiogram-gating CCTA at 80 kVp, 150 mAs, and IMR (Group A), and 30 subjects with 100 kVp, 150 mAs, and hybrid IR (Group B) were retrospectively enrolled after sample-size calculation. A BMI of less than 25 kg/m2 was required for inclusion. The attenuation value and image noise of CCTA were measured and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated at the proximal right coronary artery and left main coronary artery. The image noise was analyzed using a non-inferiority test. The CCTA images were qualitatively evaluated using a four-point scale. The radiation dose was significantly lower in Group A than Group B (0.69 ± 0.08 mSv vs. 1.39 ± 0.15 mSv, p < 0.001). The attenuation values were higher in Group A than Group B (p < 0.001). The SNR and CNR in Group A were higher than those of Group B. The image noise of Group A was non-inferior to that of Group B. Qualitative image quality of Group A was better than that of Group B (3.6 vs. 3.4, p = 0.017). CCTA at 80 kVp with IMR could reduce the radiation dose by about 50%, with non-inferior image noise and image quality than those of CCTA at 100 kVp with hybrid IR