Asymptotically Double Lacunary Equivalent Sequences in Topological Groups

In this paper we study the concept of asymptotically double lacunary statistical convergent sequences in topological groups and prove some inclusion theorems

The generalized difference gai sequences of fuzzy numbers defined by Orlicz functions

abstract: In this paper we introduce the classes of gai sequences of fuzzy numbers using generalized difference operator ∆ m (m fixed positive integer) and the Orlicz functions. We study its different properties and also we obtain some inclusion results of these classes

Lymph node metastasis in grossly apparent clinical stage Ia epithelial ovarian cancer: Hacettepe experience and review of literature

Background Lymphadenectomy is an integral part of the staging system of epithelial ovarian cancer. However, the extent of lymphadenectomy in the early stages of ovarian cancer is controversial. The objective of this study was to identify the lymph node involvement in unilateral epithelial ovarian cancer apparently confined to the one ovary (clinical stage Ia). Methods A prospective study of clinical stage I ovarian cancer patients is presented. Patient's characteristics and tumor histopathology were the variables evaluated. Results Thirty three ovarian cancer patients with intact ovarian capsule were evaluated. Intraoperatively, neither of the patients had surface involvement, adhesions, ascites or palpable lymph nodes (supposed to be clinical stage Ia). The mean age of the study group was 55.3 ± 11.8. All patients were surgically staged and have undergone a systematic pelvic and paraaortic lymphadenectomy. Final surgicopathologic reports revealed capsular involvement in seven patients (21.2%), contralateral ovarian involvement in two (6%) and omental metastasis in one (3%) patient. There were two patients (6%) with lymph node involvement. One of the two lymph node metastasis was solely in paraaortic node and the other metastasis was in ipsilateral pelvic lymph node. Ovarian capsule was intact in all of the patients with lymph node involvement and the tumor was grade 3. Conclusion In clinical stage Ia ovarian cancer patients, there may be a risk of paraaortic and pelvic lymph node metastasis. Further studies with larger sample size are needed for an exact conclusion.PubMedWoSScopu

High binding yet accelerated guest rotation within a cucurbit[7]uril complex. Toward paramagnetic gyroscopes and rolling nanomachines †

International audienceThe (15-oxo-3,7,11-triazadispiro[5.1.5.3]hexadec-7-yl)oxidanyl, a bis-spiropiperidinium nitroxide derived from TEMPONE, can be included in cucurbit[7]uril to form a strong (K a ∼ 2 × 10 5 M −1) CB[7]@bPTO complex. EPR and MS spectra, DFT calculations, and unparalleled increased resistance (a factor of ∼10 3) toward ascorbic acid reduction show evidence of deep inclusion of bPTO inside CB[7]. The unusual shape of the CB[7]@bPTO EPR spectrum can be explained by an anisotropic Brownian rotational diffusion, the global tumbling of the complex being slower than rotation of bPTO around its " long molecular axis " inside CB[7]. The CB[7] (stator) with the encapsulated bPTO (rotator) behaves as a supramolecular para-magnetic rotor with increased rotational speed of the rotator that has great potential for advanced nano-scale machines requiring wheels such as cucurbiturils with virtually no friction between the wheel and the axle for optimum wheel rotation (i.e. nanopulleys and nanocars)

Non-instantaneous polarization dynamics in dielectric media

Third-order optical nonlinearities play a vital role for generation1,2 and characterization 3-5 of some of the shortest optical pulses to date, for optical switching applications6,7, and for spectroscopy8,9. In many cases, nonlinear optical effects are used far off resonance, and then an instantaneous temporal response is expected. Here, we show for the first time resonant frequency-resolved optical gating measurements1012 that indicate substantial nonlinear polarization relaxation times up to 6.5 fs in dielectric media, i.e., significantly beyond the shortest pulses directly available from commercial lasers. These effects are among the fastest effects observed in ultrafast spectroscopy. Numerical solutions of the time-dependent Schrödinger equation13,14 are in excellent agreement with experimental observations. The simulations indicate that pulse generation and characterization in the ultraviolet may be severely affected by this previously unreported effect. Moreover, our approach opens an avenue for application of frequency-resolved optical gating as a highly selective spectroscopic probe in high-field physics

A foundation model for generalizable disease detection from retinal images

Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders 1. However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications 2. Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging.</p

A foundation model for generalizable disease detection from retinal images

Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders1. However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications2. Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging