Dynamic scaling in the 2D Ising spin glass with Gaussian couplings

We carry out simulated annealing and employ a generalized Kibble-Zurek scaling hypothesis to study the 2D Ising spin glass with normal-distributed couplings. The system has an equilibrium glass transition at temperature $T=0$. From a scaling analysis when $T\rightarrow 0$ at different annealing velocities, we extract the dynamic critical exponent $z$, i.e., the exponent relating the relaxation time $\tau$ to the system length $L$; $\tau\sim L^z$. We find $z=13.6 \pm 0.4$ for both the Edwards-Anderson spin-glass order parameter and the excess energy. This is different from a previous study of the system with bimodal couplings [S. J. Rubin, N. Xu, and A. W. Sandvik, Phys. Rev. E {\bf 95}, 052133 (2017)] where the dynamics is faster and the above two quantities relax with different exponents (and that of the energy is larger). We here argue that the different behaviors arise as a consequence of the different low-energy landscapes---for normal-distributed couplings the ground state is unique (up to a spin reflection) while the system with bimodal couplings is massively degenerate. Our results reinforce the conclusion of anomalous entropy-driven relaxation behavior in the bimodal Ising glass. In the case of a continuous coupling distribution, our results presented here indicate that, although Kibble-Zurek scaling holds, the perturbative behavior normally applying in the slow limit breaks down, likely due to quasi-degenerate states, and the scaling function takes a different form.Comment: 10 pages, 5 figure

Investigation on the changes of corneal curvature after non-phacoemulsification in small-incision cataract surgery with intraocular lens implantation

AIM: To investigate the changes of corneal curvature after non-phacoemulsification in small-incision cataract surgery with intraocular lens implantation and discuss the essence of iatrogenic astigmatism. <p>METHODS: In this study, the horizontal corneal curvature(HCC)and vertical corneal curvature(VCC)of 99 patients(116 eyes)were documented before and after cataract surgery,with the postoperative follow-up of 3d; 1, 2wk; 1, 3, 6mo; 1, 2, 3a. The difference value of the HCC and the VCC between preoperation and postoperation were calculated and statistically analyzed. <p>RESULTS: The VCC was deceased by 2.01D, while the HCC was increased by 1.62D on the 3d after surgery; the difference value of the HCC and VCC were both decreased acutely in the 3mo postoperationly(the difference value of the VCC was -0.52D and HCC was 0.46D); the difference value of the HCC and VCC both were decreased mildly after 3mo of postoperation, There was no significant difference between the difference value of HCC(0.29D)and VCC(-0.29D)at 6mo(<i>P</i>=0.801); VCC was still smaller than that of preoperation(-0.26D), and HCC was larger than that of preoperation(0.25D)at the 3a. Paired <i>t</i> test was performed in these curvature differences, which both decreased apparently from 3d to 6mo after surgery(<i>P</i><0.001), while they stayed still from 6mo to 3a postoperatively(VCC: <i>P</i>=0.284; HCC:<i>P</i>=1.000). <p>CONCLUSION: It remains astigmatism for a short time after small-incision cataract surgery and the treatment requires improvement so as to minimize the astigmatism as much as possible

The Evolution of Telepractice Use during the COVID-19 Pandemic: Perspectives of Pediatric Speech-Language Pathologists

The study investigated how pediatric speech-language pathologists (SLPs) applied telepractice to compensate for the loss of in-person services and the dynamics of telepractice use during the COVID-19 pandemic in a rural state. We conducted interviews with 10 SLPs and then a statewide survey in which 51 SLPs participated. The qualitative interviews revealed themes including changes in service environment due to the pandemic (e.g., transition to telepractice, losing clients), challenges in the transition to telepractice (e.g., limited training, difficulty engaging clients), worsening wellbeing of clinicians and clients, and SLPs’ perspectives and suggestions towards telepractice in the future. Survey results showed service disruptions and transition dynamics during the pandemic. SLPs’ weekly caseloads reduced from an average of 42.3 clients prior to the pandemic to 25.9 and 23.4 from March to May and from June to September 2020, respectively, and then recovered to 37.2 clients from October to December 2020. In contrast, the number of telepractice caseloads sharply increased from 0.2 clients per week prior to the pandemic to 14.8 from March to May 2020. The weekly telepractice caseloads then declined to 5.5 clients from June to September and 7.9 clients from October to December 2020. In the months right after the pandemic outbreak (i.e., March to May), client children struggled with treatment gains and behavioral wellbeing. However, their outcomes gradually improved by October to December and approached pre-pandemic levels. About one-third of the SLPs reported that they would be more likely or much more likely to use telepractice in the future regardless of the pandemic. However, only about a quarter perceived telepractice as comparable to in-person services. We concluded that the transition from in-person services to telepractice substantially mitigated service disruptions right after the pandemic outbreak and that telepractice’s substitute role evolved over time

What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives

Intelligent Mesh Generation (IMG) represents a novel and promising field of research, utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG has significantly broadened the adaptability and practicality of mesh generation techniques, delivering numerous breakthroughs and unveiling potential future pathways. However, a noticeable void exists in the contemporary literature concerning comprehensive surveys of IMG methods. This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape. With a focus on 113 preliminary IMG methods, we undertake a meticulous analysis from various angles, encompassing core algorithm techniques and their application scope, agent learning objectives, data types, targeted challenges, as well as advantages and limitations. We have curated and categorized the literature, proposing three unique taxonomies based on key techniques, output mesh unit elements, and relevant input data types. This paper also underscores several promising future research directions and challenges in IMG. To augment reader accessibility, a dedicated IMG project page is available at \url{https://github.com/xzb030/IMG_Survey}