Ultrafast Dynamics of Carrier Multiplication in Quantum Dots

A quantum-kinetic approach to the ultrafast dynamics of carrier multiplication in semiconductor quantum dots is presented. We investigate the underlying dynamics in the electronic subband occupations and the time-resolved optical emission spectrum, focusing on the interplay between the light-matter and the Coulomb interaction. We find a transition between qualitatively differing behaviors of carrier multiplication, which is controlled by the ratio of the interaction induced time scale and the pulse duration of the exciting light pulse. On short time scales, i.e., before intra-band relaxation, this opens the possibility of detecting carrier multiplication without refering to measurements of (multi-)exciton lifetimes.Comment: 12 pages, 7 figures, submitte

A novel echocardiographic-based classification for the prediction of peri-device leakage following left atrial appendage occluder implantation

(1) Background: The assessment of residual peri-device leakages (PDL) after left atrial appendage occlusion (LAAO) remains crucial for post-procedural management. Our study aimed to verify a novel echocardiographic classification for the prediction of PDL. (2) Methods: Echocardiographic data of 72 patients who underwent percutaneous LAAO were evaluated. All echo images were analyzed by two independent investigators using standard analysis software (Image-Arena IA-4.6.4.44 by TomTec ® , Munich, Germany). A total number of 127 studies was evaluated. Forty-four patients had baseline studies, at 45 days and at 6 months post-implantation. We propose a morphological classification of LAA devices based on the amount of echodensity inside the devices into three types: type A showing complete homogenous thrombosis, type B incompletely thrombosed device with inhomogeneous echo-free space 50% of device in various planes, which we called the “ice-cream cone” sign. Each type was matched to the degree of PDL and clinical outcome parameters. (3) Results: Patients with type C had the highest percentage of PDL at 45 days follow-up (type A: 24%, type B: 31%, type C 100% PDL, p < 0.001) and at 6 months follow-up (type A: 7%, type B: 33%, type C 100% PDL, p < 0.001). Notably, device size in patients with PDL was larger than that in patients without PDL at 6 months follow-up (25.6 ± 3.5 mm vs. 28.7 ± 3.4 mm, p = 0.004). Device size in patients with type C appearance was the largest of the three types (type A: 25.9 ± 3.6 mm, type B: 25.8 ± 3.4 mm, type C 29.8 ± 3.0 mm, type A vs. C; p = 0.019; type B vs. C, p = 0.007). (4) Conclusions: In conclusion, PDL are common post-LAAO, and their frequency is underestimated and under-recognized. PDL are much more common in patients with larger LAA ostial sizes and likely lower longitudinal compression. Type C appearance of the LAAO devices (“ice-cream cone sign”) has a high positive predictive value for PDL. Further studies are needed for better delineation of the clinical importance of this proposed classification

Influence of the carrier reservoir dimensionality on electron-electron scattering in quantum dot materials

We calculated Coulomb scattering rates from quantum dots (QDs) coupled to a 2D carrier reservoir and QDs coupled to a 3D reservoir. For this purpose, we used a microscopic theory in the limit of Born-Markov approximation, in which the numerical evaluation of high dimensional integrals is done via a quasi-Monte Carlo method. Via a comparison of the so determined scattering rates, we investigated the question whether scattering from 2D is generally more efficient than scattering from 3D. In agreement with experimental findings, we did not observe a significant reduction of the scattering efficiency of a QD directly coupled to a 3D reservoir. In turn, we found that 3D scattering benefits from it?s additional degree of freedom in the momentum space

Predicting the need for renal replacement therapy using a vascular occlusion test and tissue oxygen saturation in patients in the early phase of multiorgan dysfunction syndrome

Background: Acute kidney injury (AKI) is associated with an increased mortality in critically ill patients, especially in patients with multiorgan dysfunction syndrome (MODS). In daily clinical practice, the grading of AKI follows the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. In most cases, a relevant delay occurs frequently between the onset of AKI and detectable changes in creatinine levels as well as clinical symptoms. The aim of the present study was to examine whether a near infrared spectroscopy (NIRS)-based, non-invasive ischemia–reperfusion test (vascular occlusion test (VOT)) together with unprovoked (under resting conditions) tissue oxygen saturation (StO 2 ) measurements, contain prognostic information in the early stage of MODS regarding the developing need for renal replacement therapy (RRT). Methods: Within a period of 18 months, patients at the medical intensive care unit of a tertiary university hospital with newly developed MODS (≤24 h after diagnosis, APACHE II score ≥20) were included in our study. The VOT occlusion slope (OS) and recovery slope (RS) were recorded in addition to unprovoked StO 2 . StO 2 was determined non-invasively in the area of the thenar muscles using a bedside NIRS device. The VOT was carried out by inflating a blood pressure cuff on the upper arm. AKI stages were determined by the changes in creatinine levels, urinary output, and/or the need for RRT according to KDIGO. Results: 56 patients with MODS were included in the study (aged 62.5 ± 14.4 years, 40 men and 16 women, APACHE II score 34.5 ± 6.4). Incidences of the different AKI stages were: no AKI, 16.1% ( n = 9); AKI stage I, 19.6% ( n = 11); AKI stage II, 25% ( n = 14); AKI stage III, 39.3% ( n = 22). Thus, 39.3% of the patients ( n = 22) developed the need for renal replacement therapy (AKI stage III). These patients had a significantly higher mortality over 28 days (RRT, 72% ( n = 16/22) vs. no RRT, 44% ( n = 15/34); p = 0.03). The mean unprovoked StO 2 of all patients at baseline was 81.7 ± 11.1%, and did not differ between patients with or without the need for RRT. Patients with RRT showed significantly weaker negative values of the OS (−9.1 ± 3.7 vs. −11.7 ± 4.1%/min, p = 0.01) and lower values for the RS (1.7 ± 0.9 vs. 2.3 ± 1.6%/s, p = 0.02) compared to non-dialysis patients. Consistent with these results, weaker negative values of the OS were found in higher AKI stages (no AKI, −12.7 ± 4.1%/min; AKI stage I, −11.5 ± 3.0%/min; AKI stage II, −11.1 ± 3.3%/min; AKI stage III, −9.1 ± 3.7%/min; p = 0.021). Unprovoked StO 2 did not contain prognostic information regarding the AKI stages. Conclusions: The weaker negative values of the VOT parameter OS are associated with an increased risk of developing AKI and RRT, and increased mortality in the early phase of MODS, while unprovoked StO 2 does not contain prognostic information in that regard

Delayed improvement of depression and anxiety after transcatheter aortic valve implantation (TAVI) in stages of extended extra-valvular cardiac damage

Background: Depression and anxiety are frequently occurring and likely to be linked to the severity of cardiac diseases like aortic stenosis (AS). This seems to be of interest since a staging classification of extra-valvular cardiac damage in AS has been introduced and shown to be of prognostic relevance. Objective: The current study aimed to investigate the frequency of depression and anxiety in association to staging and their dynamics after transcatheter aortic valve implantation (TAVI). Methods: A total number of 224 AS patients undergoing TAVI were classified according to the 2017 staging classification into stage 0 to 4 and further dichotomized into group A (stage 0 to 2) and B (stage 3 and 4). Using the Hospital Anxiety and Depression Scale (HADS-D), patients were assigned to depressive versus non-depressive or anxious versus non-anxious per staging group respectively, and analyzed at baseline, 6 weeks, 6 months and 12 months after TAVI. Results: After dichotomization, 158 patients (70.5%) were assigned to group A and 66 patients (29.5%) to group B. The part showing pathologic values for depression was 25.4% (57/224 patients) in the entire collective, 26.6% (42/158 patients) in group A and 22.7% (15/66 patients) in group B (p = n.s.). The proportion showing pathologic values for anxiety was 26.8% (60/224 patients) in the entire collective and did not differ between group A (24.7%, 39/158 patients) and B (31.8%, 21/66 patients) (p = n.s.). In patients revealing pathologic values for depression or anxiety prior to TAVI, there were significant and stable improvements over time observable already in short-term (6 weeks) follow-up in group A, and likewise, but later, in long-term (6/12 months) follow-up in group B. Conclusions: Although of proven prognostic relevance, higher stages of extra-valvular cardiac damage are not associated with higher rates of pre-existing depression or anxiety. The TAVI procedure resulted in a persisting reduction of depression and anxiety in patients showing pathologic values at baseline. Notably, these improvements are timely delayed in higher stage

Prognostic relevance of mitral and tricuspid regurgitation after transcatheter aortic valve implantation: Impact of follow-up time point for decision-making

Background: In patients with aortic stenosis treated by transcatheter aortic valve implantation (TAVI), mitral and tricuspid regurgitation (MR and TR) at baseline and after TAVI are likely to be of prognostic relevance, and questions such as whether and when treatment further improves prognosis in these patients arise. Aims: Against that background, the purpose of this study was to analyze a variety of clinical characteristics including MR and TR with respect to their potential value as predictors of 2-year mortality after TAVI. Methods: A cohort of 445 typical TAVI patients was available for the study and clinical characteristics were evaluated baseline, 6 to 8 weeks as well as 6 months after TAVI. Results: In 39% of the patients relevant (moderate or severe) MR and in 32% of the patients relevant (moderate or severe) TR could be detected at baseline. The rates were 27% for MR ( p  = 0.001, compared to baseline) and 35% for TR ( p  = n.s., compared to baseline) at the 6- to 8-week follow-up. After 6 months, relevant MR was observable in 28% ( p  = 0.036, compared to baseline) and relevant TR in 34% ( p  = n.s., compared to baseline) of the patients. As predictors of 2-year mortality, a multivariate analysis identified the following parameters for the different time points: sex, age, AS entity, atrial fibrillation, renal function, relevant TR, systolic pulmonary artery pressure (PAPsys), and 6-min walk distance at baseline; clinical frailty scale and PAPsys 6–8 weeks after TAVI and BNP and relevant MR 6 months after TAVI. There was a significantly worse 2-year survival in patients with relevant TR at baseline (68.4% vs. 82.6%, p  < 0.001; whole population, n  = 445) and in patients with relevant MR at 6 months (87.9% vs. 95.2%, p  = 0.042; landmark analysis: n  = 235). Conclusion: This real-life study demonstrated the prognostic relevance of repeated evaluation of MR and TR before and after TAVI. Choosing the right time point for treatment is a remaining clinical challenge, which should be further addressed in randomized trials

Surrogate Modeling Based On Dynamic Numerical Simulation and Measurements for Fast Emulation

Today, in many complex real-world systems, physics-based simulation models often provide sufficient precision but are computationally intensive. Machine learning surrogates, once trained, can achieve simulations by orders of magnitude faster than their original physical model without sacrificing much accuracy. In this paper, we present a surrogate model in form of a neural network that is fitted to a set of different time series. The time series data are generated partly by a physical model and partly by measurement. This is because a physical model is available only for a part of the entire state space that is to be modeled. This method is used to predict the flue gas temperature at the output of the evaporator in the heat recovery steam generator of a combined cycle power plant. For simulation we use a specialized in house tool for transient power plant processes, called 'Dynaplant'. The generated surrogate model is fast and captures the major dynamics. Consequently, the model can be used in applications where fast evaluation is required, e.g., in parallel to operation. One form of such usage is virtual sensors, whereby, physical detectors can be omitted, and thus costs are reduced. With this, we demonstrate a method that beneficially merges physical insight from simulation with reallife data and machine learning. Our findings are of interest to applications where either simulated or measured time series data or both of different operating points are available and a fast simulation model is required