654 resultados para Multiple-line insurance


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Baby Boomers are a generation of life long association joiners, but following generations prefer spontaneous and episodic volunteering. This trend is apparent not only during natural disasters, but in most other spheres of volunteering. Legal liability for such volunteers is a growing concern, which unresolved, may dampen civic participation. We critically examine the current treatment of these liabilities through legislation, insurance and risk management.

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This study aimed to investigate the effects of arsenic trioxide (As2O3) on the mitochondrial DNA (mtDNA) of acute promyelocytic leukemia (APL) cells. The NB4 cell line was treated with 2.0 μmol/L As2O3in vitro, and the primary APL cells were treated with 2.0 μmol/L As2O3in vitro and 0.16 mg kg-1 d-1 As2O3in vivo. The mitochondrial DNA of all the cells above was amplified by PCR, directly sequenced and analyzed by Sequence Navigatore and Factura software. The apoptosis rates were assayed by flow cytometry. Mitochondrial DNA mutation in the D-loop region was found in NB4 and APL cells before As2O3 use, but the mutation spots were remarkably increased after As2O3 treatment, which was positively correlated to the rates of cellular apoptosis, the correlation coefficient: rNB4-As2O3=0.973818, and rAPL-As2O3=0.934703. The mutation types include transition, transversion, codon insertion or deletion, and the mutation spots in all samples were not constant and regular. It is revealed that As2O3 aggravates mtDNA mutation in the D-loop region of acute promyelocytic leukemia cells both in vitro and in vivo. Mitochondrial DNA might be one of the targets of As2O3 in APL treatment.

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The National Road Safety Partnership Program (NRSPP) is an industry-led collaborative network which aims to support Australian businesses in developing a positive road safety culture. It aims to help businesses to protect their employees and the public, not only during work hours, but also when their staff are ‘off-duty’. How do we engage and help an organisation minimise work-related vehicle crashes and their consequences both internally, and within the broader community? The first step is helping an organisation to understand the true cost of its road incidents. Larger organisations often wear the costs without knowing the true impact to their bottom line. All they perceive is the change in insurance or vehicle repairs. Understanding the true cost should help mobilise a business’s leadership to do more. The next step is ensuring the business undertakes an informed, structured, evidence-based pathway which will guide them around the costly pitfalls. A pathway based around the safe system approach with buy-in at the top which brings the workforce along. The final step, benchmarking, allows the organisation to measure and track its change. This symposium will explore the pathway steps for organisations using NRSPP resources to become engaged in road safety. The 'Total Cost of Risk' calculator has been developed by Zurich, tested in Europe by Nestle and modified by NRSPP for Australia. This provides the first crucial step. The next step is a structured approach through the Workplace Road Safety Guide using experts and industry to discuss the preferred safe system approach which can then link into the national Benchmarking Project. The outputs from the symposium can help frame a pathway for organisations to follow through the NRSPP website.

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Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

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The extended recruitment season for short-lived species such as prawns biases the estimation of growth parameters from length-frequency data when conventional methods are used. We propose a simple method for overcoming this bias given a time series of length-frequency data. The difficulties arising from extended recruitment are eliminated by predicting the growth of the succeeding samples and the length increments of the recruits in previous samples. This method requires that some maximum size at recruitment can be specified. The advantages of this multiple length-frequency method are: it is simple to use; it requires only three parameters; no specific distributions need to be assumed; and the actual seasonal recruitment pattern does not have to be specified. We illustrate the new method with length-frequency data on the tiger prawn Penaeus esculentus from the north-western Gulf of Carpentaria, Australia.

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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L-infinity. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

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Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

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The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

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A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

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The oncogene MDM4, also known as MDMX or HDMX, contributes to cancer susceptibility and progression through its capacity to negatively regulate a range of genes with tumour-suppressive functions. As part of a recent genome-wide association study it was determined that the A-allele of the rs4245739 SNP (A>C), located in the 3'-UTR of MDM4, is associated with an increased risk of prostate cancer. Computational predictions revealed that the rs4245739 SNP is located within a predicted binding site for three microRNAs (miRNAs): miR-191-5p, miR-887 and miR-3669. Herein, we show using reporter gene assays and endogenous MDM4 expression analyses that miR-191-5p and miR-887 have a specific affinity for the rs4245739 SNP C-allele in prostate cancer. These miRNAs do not affect MDM4 mRNA levels, rather they inhibit its translation in C-allele-containing PC3 cells but not in LNCaP cells homozygous for the A-allele. By analysing gene expression datasets from patient cohorts, we found that MDM4 is associated with metastasis and prostate cancer progression and that targeting this gene with miR-191-5p or miR-887 decreases in PC3 cell viability. This study is the first, to our knowledge, to demonstrate regulation of the MDM4 rs4245739 SNP C-allele by two miRNAs in prostate cancer, and thereby to identify a mechanism by which the MDM4 rs4245739 SNP A-allele may be associated with an increased risk for prostate cancer.

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This article develops a method for analysis of growth data with multiple recaptures when the initial ages for all individuals are unknown. The existing approaches either impute the initial ages or model them as random effects. Assumptions about the initial age are not verifiable because all the initial ages are unknown. We present an alternative approach that treats all the lengths including the length at first capture as correlated repeated measures for each individual. Optimal estimating equations are developed using the generalized estimating equations approach that only requires the first two moment assumptions. Explicit expressions for estimation of both mean growth parameters and variance components are given to minimize the computational complexity. Simulation studies indicate that the proposed method works well. Two real data sets are analyzed for illustration, one from whelks (Dicathais aegaota) and the other from southern rock lobster (Jasus edwardsii) in South Australia.

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The work is a report of research on using multiple inverters of Battery Energy Storage Systems with angle droop controllers to share real power in an isolated micro grid system consisting of inertia based Distributed Generation units and variable load. The proposed angle droop control method helps to balance the supply and demand in the micro grid autonomous mode through charging and discharging of the Battery Energy Storage Systems while ensuring that the state of charge of the storage devices is within safe operating conditions. The proposed method is also studied for its effectiveness for frequency control. The proposed control system is verified and its performance validated with simulation software MATLAB/SIMULINK.

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Objectives: Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumour type which necessitates multiple invitro models to attain an appreciation of its multiple subtypes. The phenomenon of epithelial-mesenchymal transition (EMT) isimportant to the development of a metastatic cancer cell phenotype being relevant to the ability of cancer cells to intravasate intovasculature and to invade tissues. The role of EMT in human papilloma virus (HPV) positive HNSCC is not well understood. Thispaper aims to characterize seven HNSCC cell lines (FaDu, SCC-25, SCC-15, CAL27, RPMI2650) including two new HPV-16positive HNSCC cell lines (UD-SCC2, 93-VU-147T) for their epithelial and mesenchymal properties. Materials and methods: A panel of HNSCC cell lines from multiple head and neck anatomical sites were profiled for basalexpression of epithelial and mesenchymal characteristics at mRNA, protein and functional levels (proliferative, migratory andinvasive properties). Furthermore, 3D spheroid forming capabilities were investigated. Results: We found that the HPV-16 positive cell line, in particular UD-SCC2 demonstrated a more invasive and mesenchymalphenotype at the molecular and functional levels suggesting HPV infection may mediate some of these cellular properties.Moreover, HPV-negative cell lines were not strictly epithelial presenting with a dynamic range of expression. Conclusions: This study presents the molecular and phenotypic diversity of HNSCC cell lines. It highlights the need formore studies in this field and a scoring system where HNSCC cell lines are ranked according to their respective epithelial andmesenchymal nature. This data will be useful to anyone modelling HNSCC behaviour, providing a molecular context which willenable them to decipher cell phenotypes and to develop therapies which block EMT progression.

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This paper addresses the following predictive business process monitoring problem: Given the execution trace of an ongoing case,and given a set of traces of historical (completed) cases, predict the most likely outcome of the ongoing case. In this context, a trace refers to a sequence of events with corresponding payloads, where a payload consists of a set of attribute-value pairs. Meanwhile, an outcome refers to a label associated to completed cases, like, for example, a label indicating that a given case completed “on time” (with respect to a given desired duration) or “late”, or a label indicating that a given case led to a customer complaint or not. The paper tackles this problem via a two-phased approach. In the first phase, prefixes of historical cases are encoded using complex symbolic sequences and clustered. In the second phase, a classifier is built for each of the clusters. To predict the outcome of an ongoing case at runtime given its (uncompleted) trace, we select the closest cluster(s) to the trace in question and apply the respective classifier(s), taking into account the Euclidean distance of the trace from the center of the clusters. We consider two families of clustering algorithms – hierarchical clustering and k-medoids – and use random forests for classification. The approach was evaluated on four real-life datasets.

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Rule 478 of the Uniform Civil Procedure Rules 1999 (Qld)(view by court) is silent as to the manner in which a court might be expected to exercise the discretion to order an inspection or demonstration under the rule and also as to the use which may be made of any inspection or demonstration ordered. The decision in Matton Developments Pty Ltd v CGU Insurance Limited [2014] QSC 256 provides guidance on both matters. This case provides some guidance on the circumstances in which a court may exercise its discretion to order a view or demonstration