Although the indications of minimally invasive treatments for pediatric urolithiasis are similar to those in adults, it is still crucial to make the right treatment decision due to the special ...considerations of children. This review aims to evaluate the efficacy and safety of extracorporeal shockwave lithotripsy (SWL), percutaneous nephrolithotomy (PCNL), and retrograde intrarenal surgery (RIRS) in the management of pediatric upper urinary tract stones.
EMBASE, PubMed, and the Cochrane Library were searched from their first available date to March 2018. The studies that meet the inclusive criteria were included. The efficacy and safety of the treatments were assessed by means of meta-analysis of the stone free rate (SFR), complication rate, effectiveness quotient (EQ) and secondary outcome indicators.
A total of 13 comparative studies were identified for data analysis. PCNL presented a significantly higher SFR compared with SWL. Similarly, the single-session SFR of RIRS was significantly higher than SWL. However, no significant difference was found between RIRS and SWL in the overall SFR. There was no significant difference between PCNL and RIRS in the SFR. Furthermore, no significant differences in complication rates were found among the three therapies. Compared with the other two treatments, PCNL had a longer operative time, fluoroscopy time and hospital stay. SWL had a shorter hospital stay, higher retreatment rate and auxiliary rate in comparison with the other two treatments. The present data also showed that PCNL presented a higher EQ than the other two treatments, and RIRS had a lower efficiency than SWL and PCNL. In the subgroup analysis of pediatric patients with stone ≤20 mm, the comparative results were similar to those described above, except for the higher complication rate of PCNL than SWL.
Although SWL as an outpatient procedure provides shorter hospital stay and reduces operative time, it has a lower SFR and higher retreatment rate than the other two treatments. PCNL exhibits a higher SFR and EQ than SWL; nevertheless, it has a longer operative time and fluoroscopy time than the other two procedures. RIRS offers a similar SFR as PCNL but a lower efficiency than PCNL.
In
various subdisciplines of optics and photonics, Mie theory has
been serving as a fundamental language and playing indispensable roles
widely. Conventional studies related to Mie scattering largely ...focus
on local properties such as differential cross sections and angular
polarization distributions. Though spatially integrated features of
total cross sections in terms of both scattering and absorption are
routine for investigations, they are intrinsically dependent on the
specific morphologies of both the scattering bodies and the incident
waves, consequently manifesting no sign of global invariance. Here,
we propose a global Mie scattering theory to explore topological invariants
for the characterization of scatterings by any obstacles of arbitrarily
structured or polarized coherent light. It is revealed that, independent
of distributions and interactions among the scattering bodies of arbitrary
geometric and optical parameters, in the far field, inevitably, there
are directions where the scatterings are either zero or circularly
polarized. Furthermore, for each such singular direction, we can assign
a half-integer index and the index sum of all those directions are
bounded to be a global topological invariant of 2. The global Mie
theory we propose, which is mathematically simple but conceptually
penetrating, can render new perspectives for light scattering and
topological photonics in both linear and nonlinear regimes and would
potentially shed new light on the scattering of acoustic and matter
waves of various forms.
Organic chemistry is undergoing a major paradigm shift, moving from a labor-intensive approach to a new era dominated by automation and artificial intelligence (AI). This transformative shift is ...being driven by technological advances, the ever-increasing demand for greater research efficiency and accuracy, and the burgeoning growth of interdisciplinary research. AI models, supported by computational power and algorithms, are drastically reshaping synthetic planning and introducing groundbreaking ways to tackle complex molecular synthesis. In addition, autonomous robotic systems are rapidly accelerating the pace of discovery by performing tedious tasks with unprecedented speed and precision. This article examines the multiple opportunities and challenges presented by this paradigm shift and explores its far-reaching implications. It provides valuable insights into the future trajectory of organic chemistry research, which is increasingly defined by the synergistic interaction of automation and AI.
In this paper, we develop an efficient and accurate procedure of electromagnetic multipole decomposition by using the Lebedev and Gaussian quadrature methods to perform the numerical integration. ...Firstly, we briefly review the principles of multipole decomposition, highlighting two numerical projection methods including surface and volume integration. Secondly, we discuss the Lebedev and Gaussian quadrature methods, provide a detailed recipe to select the quadrature points and the corresponding weighting factor, and illustrate the integration accuracy and numerical efficiency (that is, with very few sampling points) using a unit sphere surface and regular tetrahedron. In the demonstrations of an isotropic dielectric nanosphere, a symmetric scatterer, and an anisotropic nanosphere, we perform multipole decomposition and validate our numerical projection procedure. The obtained results from our procedure are all consistent with those from Mie theory, symmetry constraints, and finite element simulations.
Graphical Abstract
Scattering activities are generally manifest through different optical responses of scattering bodies to circularly polarized light of opposite handedness. Similar to the ubiquitous roles played by ...scattering theory across different branches of photonics, scattering activities can serve as a fundamental concept to clarify underlying mechanisms of various chiroptical effects, both within and beyond scattering systems. In this work, we investigate scattering activities for reciprocal systems that exhibit various geometric symmetries but are intrinsically achiral. We reveal how scattering activities are generally bounded by reciprocity and parity conservation, demonstrating that though extinction activity is usually excluded by symmetry, scattering activities in forms of distinct absorptions, scatterings or angular scattering patterns can more widely emerge. Since our analyses are solely based on fundamental laws of reciprocity and parity conservation, regardless of geometric and optical parameters of the scattering systems, the principles revealed are generically applicable. The intuitive and pictorial framework we have established is beyond any specific coupling models, able to reveal hidden connections between seemingly unrelated chiral manifestations, and thus more accessible for a unified understanding of various chiroptical effects.
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The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations ...remain, however, that impede the pace of understanding the networks, especially the extraction of understandable semantic space. In this work, the framework of semantic explainable artificial intelligence (S‐XAI) is introduced, which utilizes a sample compression method based on the distinctive row‐centered principal component analysis (PCA) that is different from the conventional column‐centered PCA to obtain common traits of samples from the convolutional neural network (CNN), and extracts understandable semantic spaces on the basis of discovered semantically sensitive neurons and visualization techniques. Statistical interpretation of the semantic space is also provided, and the concept of semantic probability is proposed. The experimental results demonstrate that S‐XAI is effective in providing a semantic interpretation for the CNN, and offers broad usage, including trustworthiness assessment and semantic sample searching.
The semantic explainable artificial intelligence (S‐XAI) proposed in this work can extract common traits via the row‐centered sample compression method and obtain semantically sensitive neurons for visualizing the semantic space. The S‐XAI is effective in providing a semantic interpretation for the convolutional neural network, and offers broad usage, including trustworthiness assessment and semantic sample searching.
•Supervised learning based on indirect labels is proposed.•New method of introducing physical mechanism based on projection matrix is developed.•Indirect physics-constrained loss is performed with ...projection matrix normalization and prediction covariance analysis.
This study proposes a supervised learning method that does not rely on labels. We use variables associated with the label as indirect labels, and construct an indirect physics-constrained loss based on the physical mechanism to train the model. In the training process, the model prediction is mapped to the space of value that conforms to the physical mechanism through the projection matrix, and then the model is trained based on the indirect labels. The final prediction result of the model conforms to the physical mechanism between indirect label and label, and also meets the constraints of the indirect label. The present study also develops projection matrix normalization and prediction covariance analysis to ensure that the model can be fully trained. Finally, the effect of the physics-constrained indirect supervised learning is verified based on a well log generation problem.
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