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Although many investors are mindful of mutual funds and ETFs as investment instruments for indexing strategy, few are familiar with direct indexing strategies designed to replicate any stock market index using a separately managed account (SMA) format. Historically, the SMA format required significant computations as each client account required individual management. Recent advancements in computational power, however, allow for the growth of direct indexing, providing clients with customizability, not only to take the benefit of tax-loss harvesting but also to implement other tailored investment objectives. The results provided in this article suggest that there exist benefits associated with tax-loss harvesting even though tax-loss harvesting defers but does not discharge tax obligations. Furthermore, the article also reveals that maintaining a reasonable ex-post tracking error to achieve the indexing goal while obtaining a positive tax-loss benefit is feasible. [ABSTRACT FROM AUTHOR]

The increasing level of harmonics in the power grid, driven by a substantial presence of coupled inverter-based energy resources (IBRs), poses a new challenge to power grid transient stability. This paper presents the findings from experiments and analytical studies on the impact of the topological configuration of coupled IBRs on the level of power flow harmonics in a distribution grid: (i) our findings report that the impact of grid topology on harmonics is nonlinear, which is in contrast to the common perception that the power grid operates as a large linear low-pass filter for harmonics; (ii) importantly, this study highlights that the influence of the topological configuration of inverters on the reduction of system-level harmonics is more substantial than the effect of line impedance, emphasizing the significance of grid topological configuration; (iii) furthermore, the observed reduction in harmonics is attributed to a harmonic cancellation effect achieved through self-compensation by all the coupled inverters without affecting the active power flow in the power grid. These findings propose a new approach to limit the penetration of complex IBR harmonics in the power grid from a system-wide perspective. This approach significantly differs from the component-level or localized solutions used today, such as inverter control, power filtering, and transformer tap changes. [ABSTRACT FROM AUTHOR]

Convertible bonds are fixed-income securities that have embedded options to convert into equities. This optionality offers investors better risk-adjusted returns than traditional bonds or equities. However, due to limited liquidity, investing in convertible bonds is challenging for many investors. In this article, the authors propose a convertible-bond index replication strategy using stocks and a high-yield exchange-traded fund (ETF). Their back-test shows that a replication portfolio consisting of stocks and a high-yield ETF reasonably tracks the risk-adjusted return characteristics of a convertible bond index. [ABSTRACT FROM AUTHOR]

The complexity of modern power grids, caused by integrating renewable energy sources, especially inverter-based resources, presents a significant challenge to grid operation and planning, since linear models are unable to capture the complex nonlinear dynamics of power systems with coupled muti-scale dynamics, and it necessitate an alternative approach utilizing more advanced and data-driven algorithms to improve modeling accuracy and system optimization. This study employs the sparse identification of nonlinear dynamics method by leveraging compressed sensing and sparse modeling principles, offering robustness and the potential for generalization, allowing for identifying key dynamical features with relatively few measurements, and providing deeper theoretical understanding in the field of power system analysis. Taking advantage of the this method in recognizing the active terms (first and high order) in the system's governing equation, this paper also introduces the novel Volterra-based nonlinearity index to characterize system-level nonlinearity. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise is adopted to clearly show the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to inverter-based resources, revealing system-level (second-order) nonlinearity compared to module-level (first order) nonlinearity in conventional synchronous generators. The proposed index quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the profile of the proposed index. [ABSTRACT FROM AUTHOR]

Real‐time estimating harmonic distortion levels near the Point of Interconnections of grid‐connected inverter‐based resources (IBRs) is critical for maintaining the operational reliability and security of the power grid, particularly during transients when IBRs generate excessive harmonics. Traditional methods like Total Harmonic Distortion (THD) are unsuitable for time‐varying waveforms as they suffer from aliasing, spectral leakage, and picket‐fence effects. This paper proposes a novel approach that utilizes convolution‐based measures for estimating harmonic distortion, which offers a more suitable way for ongoing real‐time applications. The first measure uses a 60 Hz sinusoidal function as the convolution kernel, while an enhanced measure employs the Gaussian function as the kernel. Two convolution‐based measures are proposed and compared with THD. The comparison criteria are based on the two significant features describing the variation of harmonics: min/max values and variation curvature of harmonics showing the accurate performance of proposed measures. Moreover, short‐term estimations of harmonic distortion are used to validate the effectiveness of the proposed measures, while long‐term estimations are used to determine the ability of the proposed measures to determine harmonic distortion contributions among power network components. The proposed technique's intrinsic characteristics provide a sampling window with low sensitivity to deviations in the fundamental frequency and signal's stationary condition to prevent aliasing and spectral leakage and rule out the impact of the picket‐fence effect on the harmonic distortion level estimation. [ABSTRACT FROM AUTHOR]

Two photon microscopy and optical coherence tomography (OCT) are two standard methods for measuring flow speeds of red blood cells in microvessels, particularly in animal models. However, traditional two photon microscopy lacks the depth of field to adequately capture the full volumetric complexity of the cerebral microvasculature and OCT lacks the specificity offered by fluorescent labeling. In addition, the traditional raster scanning technique utilized in both modalities requires a balance of image frame rate and field of view, which severely limits the study of RBC velocities in the microvascular network. Here, we overcome this by using a custom two photon system with an axicon based Bessel beam to obtain volumetric images of the microvascular network with fluorescent specificity. We combine this with a novel scan pattern that generates pairs of frames with short time delay sufficient for tracking red blood cell flow in capillaries. We track RBC flow speeds in 10 or more capillaries simultaneously at 1 Hz in a 237 µm × 237 µm × 120 µm volume and quantified both their spatial and temporal variability in speed. We also demonstrate the ability to track flow speed changes around stalls in capillary flow and measure to 300 µm in depth. [ABSTRACT FROM AUTHOR]

Introduction Patients with suspected thoracic pathology frequently get imaging with conventional radiography or chest x-rays (CXR) and computed tomography (CT). CXR include one or two planar views, compared to the three-dimensional images generated by chest CT. CXR imaging has the advantage of lower costs and lower radiation exposure at the expense of lower diagnostic accuracy, especially in patients with large body habitus. Objectives To determine whether CXR imaging could achieve acceptable diagnostic accuracy in patients with a low body mass index (BMI). Methods This retrospective study evaluated 50 patients with age of 63 ± 12 years old, 92% male, BMI 31.7 ± 7.9, presenting with acute, nontraumatic cardiopulmonary complaints who underwent CXR followed by CT within 1 day. Diagnostic accuracy was determined by comparing scan interpretation with the final clinical diagnosis of the referring clinician. Results CT results were significantly correlated with CXR results (r = 0.284, p = 0.046). Correcting for BMI did not improve this correlation (r = 0.285, p = 0.047). Correcting for BMI and age also did not improve the correlation (r = 0.283, p = 0.052), nor did correcting for BMI, age, and sex (r = 0.270, p = 0.067). Correcting for height alone slightly improved the correlation (r = 0.290, p = 0.043), as did correcting for weight alone (r = 0.288, p = 0.045). CT accuracy was 92% (SE = 0.039) vs. 60% for CXR (SE = 0.070, p < 0.01). Conclusion Accounting for patient body habitus as determined by either BMI, height, or weight did not improve the correlation between CXR accuracy and chest CT accuracy. CXR is significantly less accurate than CT even in patients with a low BMI. [ABSTRACT FROM AUTHOR]

The cerebral cortex is organized in cortical layers that differ in their cellular density, composition, and wiring. Cortical laminar architecture is also readily revealed by staining for cytochrome oxidase—the last enzyme in the respiratory electron transport chain located in the inner mitochondrial membrane. It has been hypothesized that a high-density band of cytochrome oxidase in cortical layer IV reflects higher oxygen consumption under baseline (unstimulated) conditions. Here, we tested the above hypothesis using direct measurements of the partial pressure of O2 (pO2) in cortical tissue by means of 2-photon phosphorescence lifetime microscopy (2PLM). We revisited our previously developed method for extraction of the cerebral metabolic rate of O2 (CMRO2) based on 2-photon pO2 measurements around diving arterioles and applied this method to estimate baseline CMRO2 in awake mice across cortical layers. To our surprise, our results revealed a decrease in baseline CMRO2 from layer I to layer IV. This decrease of CMRO2 with cortical depth was paralleled by an increase in tissue oxygenation. Higher baseline oxygenation and cytochrome density in layer IV may serve as an O2 reserve during surges of neuronal activity or certain metabolically active brain states rather than reflecting baseline energy needs. Our study provides to our knowledge the first quantification of microscopically resolved CMRO2 across cortical layers as a step towards better understanding of brain energy metabolism. The high density of cytochrome oxidase in cortical layer IV has been hypothesized to reflect higher basal oxygen consumption, but is this true? This study uses two-photon oxygen imaging technology and modeling to measure basal oxygen metabolism across cortical layers in awake mice; surprisingly, basal oxygen consumption decreases from layer I to layer IV. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Functional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole‐body fat‐referenced magnetic resonance imaging (MRI) for use in multisite clinical trials. Methods: Subjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0–5), were enrolled at six sites and imaged twice 4–12 weeks apart with T1‐weighted two‐point Dixon MRI covering the torso and upper and lower extremities. Thirty‐six muscles were volumetrically segmented using semi‐automatic multi‐atlas‐based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat‐referenced quantification. Results: Seventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within‐patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%. Discussion: We developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders. [ABSTRACT FROM AUTHOR]

The growing penetration of renewable resources such as wind and solar into the electric power grid through power electronic inverters is challenging grid protection. Due to the advanced inverter control algorithms, the inverter-based resources present fault responses different from conventional generators, which can fundamentally affect the way that the power grid is protected. This paper studied solar inverter dynamics focused on negative-sequence quantities during the restoration period following a grid disturbance by using a real-time digital simulator. It was found that solar inverters can act as negative-sequence sources to inject negative-sequence currents into the grid during the restoration period. The negative-sequence current can be affected by different operating conditions such as the number of inverters in service, grid strength, and grid fault types. Such negative-sequence responses can adversely impact the performance of protection schemes based on negative-sequence components and potentially cause relay maloperations during the grid restoration period, thus making system protection less secure and reliable. [ABSTRACT FROM AUTHOR]

We examined the benefit of incorporating ESG factors over a more recent period to acknowledge the ongoing investment trend toward ESG. A review of academic literature suggests lack of consensus on the benefit of incorporating ESG factors. We find no evidence that suggests incorporating ESG criteria results in a performance headwind or subordinate return. Furthermore, we find strong evidence of idiosyncratic risk reduction as one moves from firms that are least ESG compliant toward firms that are most ESG compliant. Finally, we conclude that the source of ESG rating can alter the performance of ESG factors. [ABSTRACT FROM AUTHOR]

There are two types of supervised machine learning (SML): regression and classification. In this study, the authors propose classification-based machine learning algorithms for factor investing with artificial neural networks in which the cross section of stock returns is grouped into five categories: strong buy, buy, neutral, sell, and strong sell. Their empirical out-of-sample results demonstrate some advantages of classification-based machine learning relative to regression-based learning in which the actual stock returns denote the response variable. The classification-based models also deliver slight outperformance relative to the ordinary least squares model, although the outperformance is not statistically significant. Furthermore, the out-of-sample results show that "deep" learning with multilayers of neuron layers cannot outperform a less sophisticated "shallow" learning for both classification-based and regression-based SML algorithms. Their findings suggest that market noise, common in the financial markets, during the training process overwhelms the nonlinear association uncovered in the machine learning process; and the classification of the cross section of stock returns may have reduced some of the noise. [ABSTRACT FROM AUTHOR]