Uterine leiomyosarcomas (LMS) are difficult to distinguish from benign leiomyomas without surgery. In this study we performed transcervical needle biopsy on 475 patients, 8 LMS patients and 467 patients with non-sarcomas (non-LMS) in a high-risk group for LMS, and evaluated whether examinations performed with Ki-67 and CD34 immunohistochemical analyses in addition to the standard hematoxylin-eo...

In a distributed network environment, the diffusion-least mean squares (LMS) algorithm gives faster convergence than the original LMS algorithm. It has also been observed that, the diffusion-LMS generally outperforms other distributed LMS algorithms like spatial LMS and incremental LMS. However, both the original LMS and diffusion-LMS are not applicable in non-linear environments where data may...

This review paper presents the analysis about features of Learning Management System (LMS) and ways to include parental participation into LMS. A list 20 popular LMs given. The main LMS discussed. importance including parents Leaning Systems also

Metastasectomy represents the standard treatment for improving survival in patients with lung metastases (LMs) from bone (BS) or soft-tissue sarcoma (STS). Recently, radiofrequency ablation (RFA) of the LMs has been proved to be a useful option which can promise the similar effect to metastasectomy. The aim of this study was to determine prognostic factors, including tumor volume doubling time ...

Leiomyosarcoma (LMS) is a malignant neoplasm with smooth muscle differentiation. Little is known about its molecular heterogeneity and no targeted therapy currently exists for LMS. We performed expression profiling on 99 cases of LMS with 3'end RNA sequencing (3SEQ) and demonstrated the existence of 3 molecular subtypes in this cohort. We consequently showed that these molecular subtypes are re...

This paper proposes a cascaded RLS-LMS predictor for lossless audio coding. In this proposed predictor, a high-order LMS predictor is employed to model the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. To solve the slow convergence problem of the LMS algorithm with colored inputs, a low-order RLS predictor is cascaded prior to the LMS predictor...

The sparsity-aware zero attractor least mean square (ZA-LMS) algorithm manifests much lower misadjustment in strongly sparse environment than its sparsity-agnostic counterpart, the least mean square (LMS), but is shown to perform worse than the LMS when sparsity of the impulse response decreases. The reweighted variant of the ZA-LMS, namely RZALMS shows robustness against this variation in spar...

This paper introduces a new variable step-size LMS (NVSS LMS) algorithm in an adaptive channel equalizer. This variant of VSS LMS algorithm is based on the weighting coefficinets bias/varance trade-off. We will show here that the adaptive equalizer with the NVSS LMS algorithm has favorable performance. Simulation results are provided to support the proposed implementation of the NVSS LMS.