Analisa Pengaruh Kualitas Aset, Likuiditas, Efensiensi Usaha dan Profitabilitas terhadap Rasio Kecukupan Modal pada Umum Syariah Periode 2012-2015

The aim of this study is to examine the influence of effect of Asset Quality (NPF), Liquidity Level (FDR), Operating Efficiency (BOPO) and Return On Asset (ROA) on the Capital Adequacy Level by Capital Adequacy (CAR) on the general Islamic Bank listed on the Indonesian Bank in period 2012-2015. There are 11 samples in this research that is sharia BCA Bank, Muamalat Bank, Bukopin Bank, BRI Bank, Mega Bank, BNI Bank, BJB Bank, Mandiri Bank, Victoria Bank, Panin Bank and Maybank Bank. Hypotheses test used is panel data regression by carry out F Test and T test with value significant 5%. The result of F test, shows that simultaneously the NPF, FDR, BOPO and ROA have a influence on Capital Adequacy Ratio (CAR). The result of t-test,shows that ROA, FDR and BOPO are have negative influence on Capital Adequacy (CAR) and NPF have no effect towards Capital Adequacy (CAR) at Sharia Bank period 2010-2015

Multi-dimensional parameter estimation of heavy-tailed moving averages

In this paper we present a parametric estimation method for certain multi-parameter heavy-tailed L\'evy-driven moving averages. The theory relies on recent multivariate central limit theorems obtained in [3] via Malliavin calculus on Poisson spaces. Our minimal contrast approach is related to the papers [14, 15], which propose to use the marginal empirical characteristic function to estimate the one-dimensional parameter of the kernel function and the stability index of the driving L\'evy motion. We extend their work to allow for a multi-parametric framework that in particular includes the important examples of the linear fractional stable motion, the stable Ornstein-Uhlenbeck process, certain CARMA(2, 1) models and Ornstein-Uhlenbeck processes with a periodic component among other models. We present both the consistency and the associated central limit theorem of the minimal contrast estimator. Furthermore, we demonstrate numerical analysis to uncover the finite sample performance of our method

Spherical collapse of dark energy with an arbitrary sound speed

We consider a generic type of dark energy fluid, characterised by a constant equation of state parameter w and sound speed c_s, and investigate the impact of dark energy clustering on cosmic structure formation using the spherical collapse model. Along the way, we also discuss in detail the evolution of dark energy perturbations in the linear regime. We find that the introduction of a finite sound speed into the picture necessarily induces a scale-dependence in the dark energy clustering, which in turn affects the dynamics of the spherical collapse in a scale-dependent way. As with other, more conventional fluids, we can define a Jeans scale for the dark energy clustering, and hence a Jeans mass M_J for the dark matter which feels the effect of dark energy clustering via gravitational interactions. For bound objects (halos) with masses M >> M_J, the effect of dark energy clustering is maximal. For those with M << M_J, the dark energy component is effectively homogeneous, and its role in the formation of these structures is reduced to its effects on the Hubble expansion rate. To compute quantitatively the virial density and the linearly extrapolated threshold density, we use a quasi-linear approach which is expected to be valid up to around the Jeans mass. We find an interesting dependence of these quantities on the halo mass M, given some w and c_s. The dependence is the strongest for masses lying in the vicinity of M ~ M_J. Observing this M-dependence will be a tell-tale sign that dark energy is dynamic, and a great leap towards pinning down its clustering properties.Comment: 25 pages, 6 figures, matches version published in JCA

Modelling radiation-induced cell cycle delays

Ionizing radiation is known to delay the cell cycle progression. In particular after particle exposure significant delays have been observed and it has been shown that the extent of delay affects the expression of damage such as chromosome aberrations. Thus, to predict how cells respond to ionizing radiation and to derive reliable estimates of radiation risks, information about radiation-induced cell cycle perturbations is required. In the present study we describe and apply a method for retrieval of information about the time-course of all cell cycle phases from experimental data on the mitotic index only. We study the progression of mammalian cells through the cell cycle after exposure. The analysis reveals a prolonged block of damaged cells in the G2 phase. Furthermore, by performing an error analysis on simulated data valuable information for the design of experimental studies has been obtained. The analysis showed that the number of cells analyzed in an experimental sample should be at least 100 to obtain a relative error less than 20%.Comment: 19 pages, 11 figures, accepted for publication in Radiation and Environmental Biophysic

Merkel cell polyomavirus large T antigen disrupts lysosome clustering by translocating human Vam6p from the cytoplasm to the nucleus

Merkel cell polyomavirus (MCV) has been recently described as the cause for most human Merkel cell carcinomas. MCV is similar to simian virus 40 (SV40) and encodes a nuclear large T (LT) oncoprotein that is usually mutated to eliminate viral replication among tumor-derived MCV. We identified the hVam6p cytoplasmic protein involved in lysosomal processing as a novel interactor with MCV LT but not SV40 LT. hVam6p binds through its clathrin heavy chain homology domain to a unique region of MCV LT adjacent to the retinoblastoma binding site. MCV LT translocates hVam6p to the nucleus, sequestering it from involvement in lysosomal trafficking. A naturally occurring, tumor-derived mutant LT (MCV350) lacking a nuclear localization signal binds hVam6p but fails to inhibit hVam6p-induced lysosomal clustering. MCV has evolved a novel mechanism to target hVam6p that may contribute to viral uncoating or egress through lysosomal processing during virus replication

Cell cycle times of short-term cultures of brain cancers as predictors of survival

Tumour cytokinetics estimated in vivo as potential doubling times (Tpot values) have been found to range in a variety of human cancers from 2 days to several weeks and are often related to clinical outcome. We have previously developed a method to estimate culture cycle times of short-term cultures of surgical material for several tumour types and found, surprisingly, that their range was similar to that reported for Tpot values. As Tpot is recognised as important prognostic variable in cancer, we wished to determine whether culture cycle times had clinical significance. Brain tumour material obtained at surgery from 70 patients with glioblastoma, medulloblastoma, astrocytoma, oligodendroglioma and metastatic melanoma was cultured for 7 days on 96-well plates, coated with agarose to prevent proliferation of fibroblasts. Culture cycle times were estimated from relative 3H-thymidine incorporation in the presence and absence of cell division. Patients were divided into two groups on the basis of culture cycle times of ⩽10 days and >10 days and patient survival was compared. For patients with brain cancers of all types, median survival for the ⩽10-day and >10-day groups were 5.1 and 12.5 months, respectively (P=0.0009). For 42 patients with glioblastoma, the corresponding values were 6.5 and 9.0 months, respectively (P=0.03). Lower grade gliomas had longer median culture cycle times (16 days) than those of medulloblastomas (9.9 days), glioblastomas (9.8 days) or melanomas (6.7 days). We conclude that culture cycle times determined using short-term cultures of surgical material from brain tumours correlate with patient survival. Tumour cells thus appear to preserve important cytokinetic characteristics when transferred to culture