The Puzzle of the Replacement Ratio in the Context of Renewal Theory

The models Feldstein and Rothschild (1974) and Jorgenson (1974) adopted to highlight the nature of the replacement ratio were identical. Yet, even though the theorems they derived from them were complementary and reinforced each other, the authors reached diametrically opposite conclusions. Digging deeper into the controversy that erupted, it emerges that the staying power of the theorem, according to which replacement is a constant propor-tion of the outstanding capital stock, may be attributed to the following reasons. The discernible shift from realism to instrumentalism in the methodology of economics; Its operational advantages; The data that accumulated, thus facilitating research without having to compute capital stock series from scratch; The inertia of the status quo, which is sustained by the absence of a process to decide when a theorem is in conflict with experience and should be set aside, and lastly the lack of a model leading to a more useful theorem than the one un-der consideration. In this light it is concluded that the time has come for research efforts to be directed towards constructing and testing models in which the useful life of capital is deter-mined endogenously in the presence of embodied technological change.Proportional replacement hypothesis, renewal theory, durability, aggregation

Trading the changes of stock market index composition: evidence from European markets

This paper studies the changes in European stock market indexes composition from 1995 to 2015. It was found that there are mixed price effects producing abnormal returns around the effective replacement of added and deleted stocks. The price pressure hypothesis seems to hold for added stocks in some indexes but not for deleted stocks as there is not a clear inversion of behaviour after the replacement. Finally, the building and back testing of a trading strategy aiming to capture some of those abnormal returns shows it yields a Sharpe Ratio of 1.4 and generates an annualised alpha of 11%

Significance improvement by randomized test in random sampling without replacement

This paper studies one-sided hypothesis testing under random sampling without replacement. That is, when $n+1$ binary random variables $X_1,\ldots, X_{n+1}$ are subject to a permutation invariant distribution and $n$ binary random variables $X_1,\ldots, X_{n}$ are observed, we have proposed randomized tests with a randomization parameter for the upper confidence limit of the expectation of the $(n+1)$th random variable $X_{n+1}$ under a given significance level $\delta>0$. Our proposed randomized test significantly improves over deterministic test unlike random sampling with replacement

TRIBOLOGICAL SYSTEMS FOR THE EVALUATION OF SUPERCRITICAL CARBON DIOXIDE STERILIZED ULTRA-HIGH MOLECULAR WEIGHT POLYETHYLENE

Polymeric biomaterials are especially susceptible to changes in mechanical and surface material properties as a result of sterilization processes that involve heat, moisture and/or irradiation. This is problematic for polymeric materials used in total joint replacement bearings, as these constructs must retain their superior mechanical and tribological properties over their expected 10-20 years of implantation. A younger more active patient population has now exacerbated this longevity issue with service lifetimes of 20+ years now being expected. Supercritical phase carbon dioxide (SC-CO2) is an industrial solvent that has shown great promise as a sterilizing agent in the food industry. Recently, SC-CO2 has adapted for the sterilization of medical grade total joint replacement ultra-high molecular weight polyethylene (UHMWPE), reducing the exposure of the polymer to the detrimental effects of heat, moisture and/or radiation. Further research is needed however to evaluate the effect of SC-CO2 sterilization on the mechanical, surface and tribological properties of UHMWPE over time. This dissertation explores the use of SC- CO2 sterilization for UHMWPE for total joint applications from a tribological perspective. It seeks to investigate and quantify fundamental tribological measures that occur at the bearing contact of total joint replacements, and it formulates and develops new experimental techniques and testing systems to investigate these tribological phenomena. This dissertation explores the hypothesis that SC-CO2 sterilization does not significantly affect the mechanical and/or tribological properties of UHMWPE, making it a \u27material safe\u27 sterilization treatment for this sensitive polymer. To answer this hypothesis, this dissertation develops and employs a series of clinically relevant wear testing methodologies in conjunction with industry standard material and surface characterization techniques to evaluate the efficacy of SC-CO2 for UHMWPE sterilization

Evolutionary history of LINE-1 in the major clades of placental mammals

BACKGROUND: LINE-1 constitutes an important component of mammalian genomes. It has a dynamic evolutionary history characterized by the rise, fall and replacement of subfamilies. Most data concerning LINE-1 biology and evolution are derived from the human and mouse genomes and are often assumed to hold for all placentals. METHODOLOGY: To examine LINE-1 relationships, sequences from the 3′ region of the reverse transcriptase from 21 species (representing 13 orders across Afrotheria, Xenarthra, Supraprimates and Laurasiatheria) were obtained from whole genome sequence assemblies, or by PCR with degenerate primers. These sequences were aligned and analysed. PRINCIPAL FINDINGS: Our analysis reflects accepted placental relationships suggesting mostly lineage-specific LINE-1 families. The data provide clear support for several clades including Glires, Supraprimates, Laurasiatheria, Boreoeutheria, Xenarthra and Afrotheria. Within the afrotherian LINE-1 (AfroLINE) clade, our tree supports Paenungulata, Afroinsectivora and Afroinsectiphillia. Xenarthran LINE-1 (XenaLINE) falls sister to AfroLINE, providing some support for the Atlantogenata (Xenarthra+Afrotheria) hypothesis. SIGNIFICANCE: LINEs and SINEs make up approximately half of all placental genomes, so understanding their dynamics is an essential aspect of comparative genomics. Importantly, a tree of LINE-1 offers a different view of the root, as long edges (branches) such as that to marsupials are shortened and/or broken up. Additionally, a robust phylogeny of diverse LINE-1 is essential in testing that site-specific LINE-1 insertions, often regarded as homoplasy-free phylogenetic markers, are indeed unique and not convergent

Rationale and design of the PRognostic Importance of MIcrovascular Dysfunction in asymptomatic patients with Aortic Stenosis (PRIMID-AS): a multicentre observational study with blinded investigations

Introduction: Aortic stenosis (AS) is the commonest valve disorder in the developed world requiring surgery. Surgery in patients with severe asymptomatic AS remains controversial. Exercise testing can identify asymptomatic patients at increased risk of death and symptom development, but with limited specificity, especially in older adults. Cardiac MRI (CMR), including myocardial perfusion reserve (MPR) may be a novel imaging biomarker in AS. Aims (1) To improve risk stratification in asymptomatic patients with AS and (2) to determine whether MPR is a better predictor of outcome than exercise testing and brain natriuretic peptide (BNP). Method/design Multicentre, prospective observational study in the UK, comparing MPR with exercise testing and BNP (with blinded CMR analysis) for predicting outcome. Population 170 asymptomatic patients with moderate-to-severe AS, who would be considered for aortic valve replacement (AVR). Primary outcome Composite of: typical symptoms necessitating referral for AVR and major adverse cardiovascular events. Follow-up: 12–30 months (minimum 12 months). Primary hypothesis MPR will be a better predictor of outcome than exercise testing and BNP. Ethics/dissemination The study has full ethical approval and is actively recruiting patients. Data collection will be completed in November 2014 and the study results will be submitted for publication within 6 months of completion. ClinicalTrials.gov identifier NCT01658345

Exact testing with random permutations

When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods based on random permutations tend to be seen as approximate. There exists a very limited amount of literature on exact testing with random permutations and only recently a thorough proof of exactness was given. In this paper we provide an alternative proof, viewing the test as a "conditional Monte Carlo test" as it has been called in the literature. We also provide extensions of the result. Importantly, our results can be used to prove properties of various multiple testing procedures based on random permutations

Data Improving in Time Series Using ARX and ANN Models

Anomalous data can negatively impact energy forecasting by causing model parameters to be incorrectly estimated. This paper presents two approaches for the detection and imputation of anomalies in time series data. Autoregressive with exogenous inputs (ARX) and artificial neural network (ANN) models are used to extract the characteristics of time series. Anomalies are detected by performing hypothesis testing on the extrema of the residuals, and the anomalous data points are imputed using the ARX and ANN models. Because the anomalies affect the model coefficients, the data cleaning process is performed iteratively. The models are re-learned on “cleaner” data after an anomaly is imputed. The anomalous data are reimputed to each iteration using the updated ARX and ANN models. The ARX and ANN data cleaning models are evaluated on natural gas time series data. This paper demonstrates that the proposed approaches are able to identify and impute anomalous data points. Forecasting models learned on the unclean data and the cleaned data are tested on an uncleaned out-of-sample dataset. The forecasting model learned on the cleaned data outperforms the model learned on the unclean data with 1.67% improvement in the mean absolute percentage errors and a 32.8% improvement in the root mean squared error. Existing challenges include correctly identifying specific types of anomalies such as negative flows