Expression of Lineage Transcription Factors Identifies Differences in Transition States of Induced Human Oligodendrocyte Differentiation

Oligodendrocytes (OLs) are critical for myelination and are implicated in several brain disorders. Directed differentiation of human-induced OLs (iOLs) from pluripotent stem cells can be achieved by forced expression of different combinations of the transcription factors SOX10 (S), OLIG2 (O), and NKX6.2 (N). Here, we applied quantitative image analysis and single-cell transcriptomics to compare different transcription factor (TF) combinations for their efficacy towards robust OL lineage conversion. Compared with S alone, the combination of SON increases the number of iOLs and generates iOLs with a more complex morphology and higher expression levels of myelin-marker genes. RNA velocity analysis of individual cells reveals that S generates a population of oligodendrocyte-precursor cells (OPCs) that appear to be more immature than those generated by SON and to display distinct molecular properties. Our work highlights that TFs for generating iOPCs or iOLs should be chosen depending on the intended application or research question, and that SON might be beneficial to study more mature iOLs while S might be better suited to investigate iOPC biology.

Estimating Visible Band Albedo from Aerial Orthophotographs in Urban Areas

Albedo is an important parameter in many environmental and renewable energy models. Satellite sensors can be used to derive broadband or narrowband albedos. However, the spatial resolution of such data can be insufficient in urban areas with complex morphology and land cover diversity. In this study, we propose the use of widely available aerial orthophotographs to derive visible band albedo in urban surfaces that can be effectively used in high-resolution applications. The solution is based on the estimation of the reflected irradiance captured by an RGB sensor and approximated by the brightness component in the hue-saturation-brightness (HSB) color model and incident solar irradiance modelled by the r.sun module in GRASS GIS. The visible band albedo values are calibrated by published reference values for selected land cover classes or, alternatively, by a spectroradiometer. The method is applied to the central part of Košice and compared to visible band albedo derived from the Landsat 8 OLI and Sentinel 2A sensors and previously published typical albedo values for various land cover classes, resulting in reasonable agreement. The proposed methodology is implemented using standard GIS tools that are easily applicable to any high-resolution urban data.

Swin–UNet++: A Nested Swin Transformer Architecture for Location Identification and Morphology Segmentation of Dimples on 2.25Cr1Mo0.25V Fractured Surface

The precise identification of micro-features on 2.25Cr1Mo0.25V steel is of great significance for understanding the mechanism of hydrogen embrittlement (HE) and evaluating the alloy’s properties of HE resistance. Presently, the convolution neural network (CNN) of deep learning is widely applied in the micro-features identification of alloy. However, with the development of the transformer in image recognition, the transformer-based neural network performs better on the learning of global and long-range semantic information than CNN and achieves higher prediction accuracy. In this work, a new transformer-based neural network model Swin–UNet++ was proposed. Specifically, the architecture of the decoder was redesigned to more precisely detect and identify the micro-feature with complex morphology (i.e., dimples) of 2.25Cr1Mo0.25V steel fracture surface. Swin–UNet++ and other segmentation models performed state-of-the-art (SOTA) were compared on the dimple dataset constructed in this work, which consists of 830 dimple scanning electron microscopy (SEM) images on 2.25Cr1Mo0.25V steel fracture surface. The segmentation results show Swin–UNet++ not only realizes the accurate identification of dimples but displays a much higher prediction accuracy and stronger robustness than Swin–Unet and UNet. Moreover, efforts from this work will also provide an important reference value to the identification of other micro-features with complex morphologies.

Many ways to decline a noun: elicitation of children’s novel noun inflection in Estonian

abstract Aims This study investigated three- to five-year-olds’ ability to generalise knowledge of case inflection to novel nouns in Estonian, which has complex morphology and lacks a default declension pattern. We explored whether Estonian-speaking children use similar strategies to adults, and whether they default to a preferred pattern or use analogy to phonological neighbours. Method We taught children novel nouns in nominative or allative case and elicited partitive and genitive case forms based on pictures of unfamiliar creatures. Participants included 66 children (3;0–6;0) and 21 adults. Because of multiple grammatical inflection patterns, children’s responses were compared with those of adults for variability, accuracy, and morphological neighbourhood density. Errors were analysed to reveal how children differed from adults. Conclusions Young children make use of varied available patterns, but find generalisation difficult. Children’s responses showed much variability, yet even three-year-olds used the same general declension patterns as adults. Accuracy increased with age but responses were not fully adult-like by age five. Neighbourhood density of responses increased with age, indicating that analogy over a larger store of examples underlies proficiency with productive noun inflection. Children did not default to the more transparent, affixal patterns available, preferring instead to use the more frequent, stem-changing patterns.

ECG and Pacing Criteria for Differentiating Conduction System Pacing from Myocardial Pacing

During His-Purkinje conduction system (HPS) pacing, it is crucial to confirm capture of the His bundle or left bundle branch versus myocardialonly capture. For this, several methods and criteria for differentiation between non-selective (ns) capture – capture of the HPS and the adjacent myocardium – and myocardial-only capture were developed. HPS capture results in faster and more homogenous depolarisation of the left ventricle than right ventricular septal (RVS) myocardial-only capture. Specifically, the depolarisation of the left ventricle (LV) does not require slow cell-to-cell spread of activation from the right side to the left side of the interventricular septum but begins simultaneously with QRS onset as in native depolarisation. These phenomena greatly influence QRS complex morphology and form the basis of electrocardiographic differentiation between HPS and myocardial paced QRS. Moreover, the HPS and the working myocardium are different tissues within the heart muscle that vary not only in conduction velocities but also in refractoriness and capture thresholds. These last two differences can be exploited for the diagnosis of HPS capture using dynamic pacing manoeuvres, namely differential output pacing, programmed stimulation and burst pacing. This review summarises current knowledge of this subject.

A novel signal-adaptive multi-feature extraction algorithm for arrhythmia detection

Background The significant features like an amplitude and intervals of electrocardiograph or P-QRS-T wave represent the functionality of the heart. Accurate extraction of these features helps in capturing characteristics of the signal helpful for the detection of cardiac abnormalities. In this paper, a novel signal folding-based algorithm is proposed to obtain detailed information about the complex morphology of signal. It explores the denoising and feature extraction of the specific ECG signals. Results The experimental study conducted using MIT-BIH Arrhythmia database ECG records with known conditions of left bundle branch block, right bundle branch block, Wolff-Parkinson-White syndrome beats has been considered. Heart rate values for selected ECG records from MIT-BIH dataset and synthetic signals from ECG simulator yielded the same values and thus validate our approach. Conclusion The proposed algorithm determines the heart rate, percentage leakage around the peak and is capable of folding a signal very efficiently based on detected R peaks and period-dependent gate(window).