Effects of extreme cooling methods on mechanical properties and shear bond strength of bilayered porcelain/3Y-TZP specimens

Objectives: This study investigated the effect of extreme cooling methods on the flexural strength, reliability and shear bond strength of veneer porcelain for zirconia. Methods: Vita VM9 porcelain was sintered on zirconia bar specimens and cooled by one of the following methods: inside a switched-off furnace (slow), at room temperature (normal) or immediately by compressed air (fast). Three-point flexural strength tests (FS) were performed on specimens with porcelain under tension (PT, n = 30) and zirconia under tension (ZT, n = 30). Shear bond strength tests (SBS, n = 15) were performed on cylindrical blocks of porcelain, which were applied on zirconia plates. Data were submitted to one-way ANOVA and Tukey's post hoc tests (p < 0.05). Weibull analysis was performed on the PT and ZT configurations. Results: One-way ANOVA for the PT configuration was significant, and Tukey's test revealed that fast cooling leads to significantly higher values (p < 0.01) than the other cooling methods. One-way ANOVA for the ZT configuration was not significant (p = 0.06). Weibull analysis showed that normal cooling had slightly higher reliability for both the PT and ZT configurations. Statistical tests showed that slow cooling decreased the SBS value (p < 0.01) and showed less adhesive fracture modes than the other cooling methods. Clinical Significance: Slow cooling seems to affect the veneer resistance and adhesion to the zirconia core; however, the reliability of fast cooling was slightly lower than that of the other methods. © 2013 Elsevier Ltd.

Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns

Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

The Kumaraswamy Gumbel distribution

The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization-referred to as the Kumaraswamy Gumbel distribution-and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

Characterisation of extreme winter precipitation in Mediterranean coastal sites and associated anomalous atmospheric circulation patterns

We present an analysis of daily extreme precipitation events for the extended winter season (October–March) at 20 Mediterranean coastal sites covering the period 1950–2006. The heavy tailed behaviour of precipitation extremes and estimated return levels, including associated uncertainties, are derived applying a procedure based on the Generalized Pareto Distribution, in combination with recently developed methods. Precipitation extremes have an important contribution to make seasonal totals (approximately 60% for all series). Three stations (one in the western Mediterranean and the others in the eastern basin) have a 5-year return level above 100 mm, while the lowest value (estimated for two Italian series) is equal to 58 mm. As for the 50-year return level, an Italian station (Genoa) has the highest value of 264 mm, while the other values range from 82 to 200 mm. Furthermore, six series (from stations located in France, Italy, Greece, and Cyprus) show a significant negative tendency in the probability of observing an extreme event. The relationship between extreme precipitation events and the large scale atmospheric circulation at the upper, mid and low troposphere is investigated by using NCEP/NCAR reanalysis data. A 2-step classification procedure identifies three significant anomaly patterns both for the western-central and eastern part of the Mediterranean basin. In the western Mediterranean, the anomalous southwesterly surface to mid-tropospheric flow is connected with enhanced moisture transport from the Atlantic. During ≥5-year return level events, the subtropical jet stream axis is aligned with the African coastline and interacts with the eddy-driven jet stream. This is connected with enhanced large scale ascending motions, instability and leads to the development of severe precipitation events. For the eastern Mediterranean extreme precipitation events, the identified anomaly patterns suggest warm air advection connected with anomalous ascent motions and an increase of the low- to mid-tropospheric moisture. Furthermore, the jet stream position (during ≥5-year return level events) supports the eastern basin being in a divergence area, where ascent motions are favoured. Our results contribute to an improved understanding of daily precipitation extremes in the cold season and associated large scale atmospheric features.

Periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1(st) and 2(nd) ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

Change of extreme rainfall indexes at Ebro River Basin

The purpose of this work is to provide a description of the heavy rainfall phenomenon on statistical tools from a Spanish region. We want to quantify the effect of the climate change to verify the rapidity of its evolution across the variation of the probability distributions. Our conclusions have special interest for the agrarian insurances, which may make estimates of costs more realistically. In this work, the analysis mainly focuses on: The distribution of consecutive days without rain for each gauge stations and season. We estimate density Kernel functions and Generalized Pareto Distribution (GPD) for a network of station from the Ebro River basin until a threshold value u. We can establish a relation between distributional parameters and regional characteristics. Moreover we analyze especially the tail of the probability distribution. These tails are governed by law of power means that the number of events n can be expressed as the power of another quantity x : n(x) = x? . ? can be estimated as the slope of log-log plot the number of events and the size. The most convenient way to analyze n(x) is using the empirical probability distribution. Pr(X mayor que x) ? x-?. The distribution of rainfall over percentile of order 0.95 from wet days at the seasonal scale and in a yearly scale with the same treatment of tails than in the previous section.

Parametric & nonparametric approaches to event studies: an application to a hotel’s market value

The main objective of this paper is twofold: on the one hand, to analyse the impact that the announcement of the opening of a new hotel has on the performance of its chain by carrying out an event study, and on the other hand, to compare the results of two different approaches to this method: a parametric specification based on the autoregressive conditional heteroskedasticity models to estimate the market model, and a nonparametric approach, which implies employing Theil’s nonparametric regression technique, which in turn, leads to the so-called complete nonparametric approach to event studies. The results that the empirical application arrives at are noteworthy as, on average, the reaction to such news releases is highly positive, both approaches reaching the same level of significance. However, a word of caution must be said when one is not only interested in detecting whether the market reacts, but also in obtaining an exhaustive calculation of the abnormal returns to further examine its determining factors.

New-Generation Hybrid Contact Lens for the Management of Extreme Irregularity in a Thin Cornea After Unsuccessful Excimer Laser Refractive Surgery

Purpose: To report a very successful outcome obtained with the fitting of a new-generation hybrid contact lens of reverse geometry in a thin cornea with extreme irregularity due to the presence of a central island after unsuccessful myopic excimer laser refractive surgery. Methods: A 32-year-old man attended to our clinic complaining of very poor vision in his right eye after bilateral laser in situ keratomileusis (treatment or surgery) for myopia correction and some additional retreatments afterward. After a comprehensive ocular evaluation, contact lens fitting with a reverse geometry hybrid contact lens (SynergEyes PS, SynergEyes, Carlsbad, CA) was proposed as a solution for this case. Visual, refractive, and ocular aberrometric outcomes with the contact lens were evaluated. Results: Distance visual acuity improved from a prefitting uncorrected value of 20/200 to a postfitting corrected value of 20/16. Prefitting manifest refraction was +6.00 sphere and −3.00 cylinder at 70°, with a corrected distance visual acuity of 20/40. Higher order root mean square for a 5-mm pupil changed from a prefitting value of 1.45 to 0.34 µm with the contact lens. The contact lens wearing was reported as comfortable, and the patient was very satisfied with this solution. Conclusions: The SynergEyes PS contact lens seems to be an excellent option for the visual rehabilitation of corneas with extreme irregularity after myopic excimer laser surgery, minimizing the level of higher order aberrations and providing an excellent visual outcome.

Statistical theory of extreme values and some practical applications; a series of lectures.

Bibliography: p. 48-49.

Building up resilience of construction sector SMEs and their supply chains to extreme weather events

Wider scientific community now accept that the threat of climate change as real and thus acknowledge the importance of implementing adaptation measures in a global context. In the UK , the physical effects of climate change are likely to be directly felt in the form of extreme weather events, which are predicted to escalate in number and severity in future under the changing climatic conditions. Construction industry; which consists of supply chains running across various other industries, economies and regions, will also be affected due to these events. Thus, it is important that the construction organisations are well prepared to withstand the effects of extreme weather events not only directly affecting their organisations but also affecting their supply chains which in turn might affect the organisation concerned. Given the fact that more than 99% of construction sector businesses are SMEs, the area can benefit significantly from policy making to improve SME resilience and coping capacity. This paper presents the literature review and synthesis of a doctoral research study undertaken to address the issue of extreme weather resilience of construction sector SMEs and their supply chains. The main contribution of the paper to both academia and practitioners is a synthesis model that conceptualises the factors that enhances resilience of SMEs and their supply chains against extreme weather events. This synthesis model forms the basis of a decision making framework that will enable SMEs to both reduce their vulnerability and enhance their coping capacity against extreme weather. The value of this paper is further extended by the overall research design that is set forth as the way forward.

Extreme events, organizations and the politics of decision making

Purpose – Threats of extreme events, such as terrorist attacks or infrastructure breakdown, are potentially highly disruptive events for all types of organizations. This paper seeks to take a political perspective to power in strategic decision making and how this influences planning for extreme events. Design/methodology/approach – A sample of 160 informants drawn from 135 organizations, which are part of the critical national infrastructure in the UK, forms the empirical basis of the paper. Most of these organizations had publicly placed business continuity and preparedness as a strategic priority. The paper adopts a qualitative approach, coding data from focus groups. Findings – In nearly all cases there is a pre-existing dominant coalition which keeps business continuity decisions off the strategic agenda. The only exceptions to this are a handful of organizations which provide continuous production, such as some utilities, where disruption to business as usual can be readily quantified. The data reveal structural and decisional elements of the exercise of power. Structurally, the dominant coalition centralizes control by ensuring that only a few functional interests participate in decision making. Research limitations/implications – Decisional elements of power emphasize the dominance of calculative rationality where decisions are primarily made on information and arguments which can be quantified. Finally, the paper notes the recursive aspect of power relations whereby agency and structure are mutually constitutive over time. Organizational structures of control are maintained, despite the involvement of managers charged with organizational preparedness and resilience, who remain outside the dominant coalition. Originality/value – The paper constitutes a first attempt to show how planning for emergencies fits within the strategy-making process and how politically controlled this process is.

Extreme weather events and construction SMEs:vulnerability, impacts and responses

Purpose – The UK experienced a number of Extreme Weather Events (EWEs) during recent years and a significant number of businesses were affected as a result. With the intensity and frequency of weather extremes predicted in the future, enhancing the resilience of businesses, especially of Small and Medium-sized Enterprises (SMEs), who are considered as highly vulnerable, has become a necessity. However, little research has been undertaken on how construction SMEs respond to the risk of EWEs. In seeking to help address this dearth of research, this investigation sought to identify how construction SMEs were being affected by EWEs and the coping strategies being used. Design/methodology/approach – A mixed methods research design was adopted to elicit information from construction SMEs, involving a questionnaire survey and case study approach. Findings – Results indicate a lack of coping strategies among the construction SMEs studied. Where the coping strategies have been implemented, these were found to be extensions of their existing risk management strategies rather than radical measures specifically addressing EWEs. Research limitations/implications – The exploratory survey focused on the Greater London area and was limited to a relatively small sample size. This limitation is overcome by conducting detailed case studies utilising two SMEs whose projects were located in EWE prone localities. The mixed method research design adopted benefits the research by presenting more robust findings. Practical implications – A better way of integrating the potential of EWEs into the initial project planning stage is required by the SMEs. This could possibly be achieved through a better risk assessment model supported by better EWE prediction data. Originality/value – The paper provides an original contribution towards the overarching agenda of resilience of SMEs and policy making in the area of EWE risk management. It informs both policy makers and practitioners on issues of planning and preparedness against EWEs.

A conceptual framework for understanding resilience of construction SMEs to extreme weather events

Purpose Small and Medium-sized Enterprises (SMEs), which form a significant portion in many economies, are some of the most vulnerable to the impact of Extreme Weather Events (EWEs). This is of particular importance to the construction industry, as an overarching majority of construction companies are SMEs who account for the majority of employment and income generation within the industry. In the UK, previous research has identified construction SMEs as some of the worst affected by EWEs. Design/methodology/approach Given the recent occurrences of EWEs and predictions suggesting increases in both the intensity and frequency of EWEs in the future, improving the resilience of construction SMEs is vital for achieving a resilient construction industry. A conceptual framework is first developed which is then populated and expanded based on empirical evidence. Positioned within a pragmatic research philosophy, case study research strategy was adopted as the overall research strategy in undertaking this investigation. Findings Based on the findings of two in-depth case studies of construction SMEs, a framework was developed to represent EWE resilience of construction SMEs, where resilience was seen as a collective effect of vulnerability, coping strategies and coping capacities of SMEs, characteristics of the EWE and the wider economic climate. Originality/value The paper provides an original contribution towards the overarching agenda of the resilience of SMEs, and policy making in the area of EWE risk management by presenting a novel conceptual framework depicting the resilience of medium-sized construction companies.

Lexicographic allocations and extreme core payoffs: the case of assignment games

We consider various lexicographic allocation procedures for coalitional games with transferable utility where the payoffs are computed in an externally given order of the players. The common feature of the methods is that if the allocation is in the core, it is an extreme point of the core. We first investigate the general relationship between these allocations and obtain two hierarchies on the class of balanced games. Secondly, we focus on assignment games and sharpen some of these general relationship. Our main result is the coincidence of the sets of lemarals (vectors of lexicographic maxima over the set of dual coalitionally rational payoff vectors), lemacols (vectors of lexicographic maxima over the core) and extreme core points. As byproducts, we show that, similarly to the core and the coalitionally rational payoff set, also the dual coalitionally rational payoff set of an assignment game is determined by the individual and mixed-pair coalitions, and present an efficient and elementary way to compute these basic dual coalitional values. This provides a way to compute the Alexia value (the average of all lemacols) with no need to obtain the whole coalitional function of the dual assignment game.

Wind wave prediction in the Caspian Sea

In this thesis, wind wave prediction and analysis in the Southern Caspian Sea are surveyed. Because of very much importance and application of this matter in reducing vital and financial damages or marine activities, such as monitoring marine pollution, designing marine structure, shipping, fishing, offshore industry, tourism and etc, gave attention by some marine activities. In this study are used the Caspian Sea topography data that are extracted from the Caspian Sea Hydrography map of Iran Armed Forces Geographical Organization and the I 0 meter wind field data that are extracted from the transmitted GTS synoptic data of regional centers to Forecasting Center of Iran Meteorological Organization for wave prediction and is used the 20012 wave are recorded by the oil company's buoy that was located at distance 28 Kilometers from Neka shore for wave analysis. The results of this research are as follows: - Because of disagreement between the prediction results of SMB method in the Caspian sea and wave data of the Anzali and Neka buoys. The SMB method isn't able to Predict wave characteristics in the Southern Caspian Sea. - Because of good relativity agreement between the WAM model output in the Caspian Sea and wave data of the Anzali buoy. The WAM model is able to predict wave characteristics in the southern Caspian Sea with high relativity accuracy. The extreme wave height distribution function for fitting to the Southern Caspian Sea wave data is obtained by determining free parameters of Poisson-Gumbel function through moment method. These parameters are as below: A=2.41, B=0.33. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by above function with the wave data of Neka buoy is about %35. The 100-year return value of the Southern Caspian Sea significant height wave is about 4.97 meter. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by statistical model of peak over threshold with the wave data of Neka buoy is about %2.28. The parametric relation for fitting to the Southern Caspian Sea frequency spectra is obtained by determining free parameters of the Strekalov, Massel and Krylov etal_ multipeak spectra through mathematical method. These parameters are as below: A = 2.9 B=26.26, C=0.0016 m=0.19 and n=3.69. The maximum relative error between calculated free parameters of the Southern Caspian Sea multipeak spectrum with the proposed free parameters of double-peaked spectrum by Massel and Strekalov on the experimental data from the Caspian Sea is about 36.1 % in spectrum energetic part and is about 74M% in spectrum high frequency part. The peak over threshold waverose of the Southern Caspian Sea shows that maximum occurrence probability of wave height is relevant to waves with 2-2.5 meters wave fhe error sources in the statistical analysis are mainly due to: l) the missing wave data in 2 years duration through battery discharge of Neka buoy. 2) the deportation %15 of significant height annual mean in single year than long period average value that is caused by lack of adequate measurement on oceanic waves, and the error sources in the spectral analysis are mainly due to above- mentioned items and low accurate of the proposed free parameters of double-peaked spectrum on the experimental data from the Caspian Sea.