Rhabdomyosarcoma of the uterus in an adult patient with osteopetrosis: a case report

Background Uterine sarcoma accounts for 3–7% of uterine malignant neoplasms. It is more aggressive than epithelial neoplasms, and patients have a poor prognosis. Rhabdomyosarcoma is classified as a heterologous uterine sarcoma. It is the most common soft tissue malignancy in children while rare in adults. In young patients, the majority of genital tract rhabdomyosarcomas occur in vagina; however, the most common site of gynecologic rhabdomyosarcoma is cervix followed by uterine corpus, in adults. Uterine corpus rhabdomyosarcoma is rare in adults. Diagnosis of pure rhabdomyosarcoma in uterus involves widespread and perfect sampling as well as precise histopathological evaluation to uncover any epithelial component. Case presentation Here we report a case of pure rhabdomyosarcoma of uterine corpus in a 60-year-old Iranian postmenopausal female who had osteopetrosis, presenting with 8-month heavy vaginal bleeding and a protruding cervical mass. She is alive on 18-month follow-up after treatment. Conclusions Rhabdomyosarcoma of uterine corpus is rare in adults. Diagnosis of pure rhabdomyosarcoma in uterus involves widespread and perfect sampling as well as precise histopathological evaluation to uncover any epithelial component. Treatment options in adult gynecological rhabdomyosarcoma are based on studies in younger patients, and more studies may help us choose the best approach for improving outcome.

Perfect Sampling of Hawkes Processes and Queues with Hawkes Arrivals

In this paper we develop to our best knowledge the first perfect sampling algorithm for queues with Hawkes input (i.e., single-server queues with Hawkes arrivals and independent and identically distributed service times of general distribution). In addition to the stability condition, we also assume the excitation function of the Hawkes process has a light tail and the service time has finite moment-generating function in the neighborhood of the origin. In this procedure, we also propose a new perfect sampling algorithm for Hawkes processes with improved computational efficiency compared with the existing algorithm. Theoretical analysis and numerical tests on the algorithms’ correctness and efficiency are also included.

Rejection- and importance-sampling-based perfect simulation for Gibbs hard-sphere models

Coupling-from-the-past (CFTP) methods have been used to generate perfect samples from finite Gibbs hard-sphere models, an important class of spatial point processes consisting of a set of spheres with the centers on a bounded region that are distributed as a homogeneous Poisson point process (PPP) conditioned so that spheres do not overlap with each other. We propose an alternative importance-sampling-based rejection methodology for the perfect sampling of these models. We analyze the asymptotic expected running time complexity of the proposed method when the intensity of the reference PPP increases to infinity while the (expected) sphere radius decreases to zero at varying rates. We further compare the performance of the proposed method analytically and numerically with that of a naive rejection algorithm and of popular dominated CFTP algorithms. Our analysis relies upon identifying large deviations decay rates of the non-overlapping probability of spheres whose centers are distributed as a homogeneous PPP.

Sensitivity Analysis and Simulation of a Multiserver Queueing System with Mixed Service Time Distribution

The motivation of mixing distributions in communication/queueing systems modeling is that some input data (e.g., service time in queueing models) may follow several distinct distributions in a single input flow. In this paper, we study the sensitivity of performance measures on proximity of the service time distributions of a multiserver system model with two-component Pareto mixture distribution of service times. The theoretical results are illustrated by numerical simulation of the M/G/c systems while using the perfect sampling approach.