In conclusion, it would also be really nice to see clients start recognise the simple fact there are no absolute guarantees about futureoutcomes. I am really looking forward to seeing the first intelligently prepared tender that asks the organisations submitting a tender to define the probability of them achieving the contract date and the contingency included in their project program to achieve this level of certainty 11 . Any
The RE is an uncertain investment such that it is long-term, costly and depend on a feed-in tariff system. The valuation for RE investment must consider the irreversible and flexibility enjoyed by decision makers (i.e, the option to delay investment) in addition to the uncertainty. A. Dixit et al.  addressed the subject of traditional valuation techniques based on discounted cash flows inferior to real option analysis under these circumstances. Here, we follow the real option approach (ROA) to address the real option valuation (ROV) of an investment in a Solar Energy (SE) projects and the optimal time to invest under a number of different payment settings [12,13]. Fernandes et al.  presented a review of the current state of the art in the application of ROA to investment in non-renewable and RES. Abadie et al.  provides a literature review of the real option valuation for the operating wind farm. According to [14,15], this particular literature in the RE sector is still limited. Therefore, attempts to fill this gap would be welcome.
Less tangible, but equally significant, are political and social trends that directly and indirectly stimulate change within the church. For example, the politically driven shift in thinking in the public services to copy private sector practices and ideologies has also found its way into religious settings. In part this drive to “run a parish like a business” has its roots in the prominent examples of financial mismanagement already mentioned, but equally important is the increasing dominance of a business discourse in society that is difficult for the church to resist. The generally unspoken challenge to church practice is that it would be irresponsible, and therefore un-Christian, to fail in the efficient and effective management of resources. Management control is the art of the known – and such knowledge is powerful and difficult to resist.
Whether or not a water project or some of its components can be postponed for more information depends on the specific circumstances surrounding the project. Delay can be extremely costly in some cases. For example, facing imminent flooding risk, postponing preventive measures such as strengthening levees may lead to devastating results. The cost of delay can be relatively low in other cases, arising mainly from discounting. For instance, without strong demand for irrigation water, building a major irrigation and hydroelectric dam can be delayed for more information. Different components of a major project may also have different costs of delay. If works on levees and other existing flood control facilities provide sufficient protection against flooding in the short run, major components such as building a new flood control dam can be delayed. Finally, the components may have to occur in a certain order, i.e., delaying a certain component may postpone other subsequent components, raising the cost o f delay.
The insurance data, in terms of personal and comer- cial property sewer flood insurance claims and water damage incurred losses, were aggregated at the monthly level for April-September 1992-2002 at each of the se- lected cities (i.e., London, Ottawa, Toronto, Kitchener- Waterloo). Due to the coarse temporal resolution of the monthly insurance data, the data are restricted in their usefulness for studying detailed information on heavy rainfall-related sewer flood insurance claims and water damage incurred losses. In turn, the changes in future heavy rainfall-related water damage insurance claims and incurred losses projected from the monthly-based dataset could possess a greater degree of uncertainty than those that might be was a daily-based dataset available. If the daily insurance data were available, more detailed rela- tionships between daily/hourly rainfall intensity and daily insurance claims and water damage incurred losses could be possibly determined for local climate change impact analysis.
The authors thank Mr Dylan Southard for his kind English editing of the manuscript via Research Affair, Faculty of Medicine, Khon Kaen University, Thailand; the Thailand Research Fund (TRF): IRG 5780016, and the Higher Education Research Promotion National Research University Project of Thailand, Office of the Higher Education Commis- sion through the Health Cluster (SHeP-GMS), Thailand; the Faculty of Medicine, Khon Kaen University grant number TR57201; the TRF Senior Research Scholar Grant, Thailand Research Fund grant number RTA5880001; and grant of Faculty of Medicine, Khon Kaen University, Thailand (Grant Number RG59301).
The remaining questions asked about the current and intended future enrolment of the 1 st , 2 nd and 3 rd year students. We were particularly interested in why students might not continue studying either or both life sciences (Table 7). The most common reason was that students were majoring in another area, and this was often linked to preferring or needing to study other subjects. The responses show that, largely, students do not continue because of prior decisions on course structure; few cited do not enjoy or find studying difficult as their reasons for not continuing.
Khitan, Zeid; Shapiro, Anna P.; Shah, Preeya T.; Sanabria, Juan R.; Santhanam, Prasanna; Sodhi, Komal; Abraham, Nader G.; and Shapiro, Joseph I. (2017) "Predicting Adverse Outcomes in Chronic Kidney Disease Using Machine Learning Methods: Data from the Modification of Diet in Renal Disease," Marshall Journal of Medicine: Vol. 3: Iss. 4, Article 10.
To further evaluate these hypotheses, we perform monthly Fama-MacBeth cross-sectional regressions across subsamples split by the conditioning variables as discussed above. We use the same method and model specifications as in the test of the unconditional IO effect (see Table V). For brevity, we only report the slope on IO estimated from Models 2 to 6 in Table VII. The results also show a sharp contrast in the IO effect across the subsamples even after we control for many well-known return predictors and industry effects. For example, in Panel A, the slope on IO is 0.12%, 0.16%, 0.17%, among younger, more opaque, and high VU index firms, respectively, and are significant at the 1% level. In contrast, their counterparts are only 0.06%, – 0.01%, 0.04%, respectively, and are insignificant or marginally significant. The difference in the IO slopes across the VU index subsamples is also economically and statistically significant (0.13%, t = 3.33). The same pattern exhibits for subsamples split by investor attention and the sensitivity of future profitability to IO (see Panels B and C). Furthermore, the results are also robust to the alternative IO measure as reported in Table IA.X in the Internet Appendix.
Maybe now it is easier to see why we, as an artistic community, need to place more value in a good children’s author/illustrator. Not only does their work create a different kind of challenge, but these books are also starting to be used as learning tools. Teachers in elementary classrooms are using visual art forms more and more as learning aids. Kathy A. Miller-Hewes wrote an article about such learning techniques called “Making the Connection: Children’s Books and the Visual Arts.” In her article she documents a few specific classroom exercises that are performed involving visual art. In one example, a group of children read and observed the contents of three different books involving dragons. The kids soon started to realize that their ‘trained’ idea of what a dragon looked like wasn’t always right. Soon they started talking about what a dragon could look like, as apposed to what it should look like, and that the possibilities were endless. Miller-Hewes says that, “Using children’s books to motivate learning in visual art can be rewarding for the teacher and the student.”
Experimental results indicate that the proposed LP- SVR method gives the smallest error when compared against the other approaches. The LP-SVR shows a mean absolute percent error of 1.58% while the FFNN ap- proach has a 1.61%. Similarly, the FFNN method shows a 330 MWh (Megawatts-hour) mean absolute error, whereas the LP-SVR approach gives a 238 MWh mean absolute error. This is a significant difference in terms of the extra power that would need to be produced if FFNN was used.
The proposed Earthling's mark – E mark stems from my project Gr@y Matter – language of shadows, in which I explored the communication abilities of shadows, expressed as emotions. In the periodic table borrowed from natural sciences, I replaced chemical elements with emotions visualized with images of shadows. These to me denote the DNA of our emotional existence. Parallel to our material existence, presented through chemical elements and molecules, emotions determine our immaterial existence. I decided to rely on emotions and shadows to make Earthling’s mark – E mark because both emotions and shadows are equal to all human beings, regardless of the cultural, social, linguistic, or any other differences. Shadows, when looked at, usually produce an association that is connected to emotions.
This project will utilise all recent developments in the methodology and statistical analysis of systematic reviews. This will include bivariate meta-analysis, a tech- nique which analyses sensitivity and specificity jointly, accounting for the presence of a threshold effect and cor- relation between the two measures. We will also utilise guidelines on the methodology of systematic reviews to assess causation. The results of the review will help pro- duce a set of neonatal tests to predict neonatal, childhood and adult morbidity and mortality, which can be used to inform clinical management of these individuals. The recently recommended GRADE approach to rating the quality of evidence and the strength of the recommenda- tions made on the results will comprehensively explain the findings of our reviews and the rationale behind our recommendations to enable the confident use of our results to influence current practice and recommend fur- ther research.
The initial uncertainty of the unknown proportion is evidently more than initial uncertainty of the certain proportion. Hence, the real sum of probabilities of all foreseeable events (red or black) for the unknown proportion is or (due to the experience of tested people) seems less than that of the certain proportion.
Results: The mean age of the patients was 66.96±9.67 years, the mean AL was 23.29±0.62 mm, the mean K1 was 43.62±1.49D, the mean K2 was 43.69±1.53D, the mean IOL power was 21.066±1.464D, the mean attempted (predicted) SE was -0.178±0.266D, and the mean achieved SE was -0.252±0.562D. The mean PE (difference between predicted and achieved SE) showed a relatively hyperopic shift (mean ± standard deviation: 0.074±0.542D, ranging from -1.855 to 2.170D, P=0.001). A total of 93.87% of eyes were within ±1.00D of the PE and 92.75% of eyes within ±1.00D of achieved postoperative refraction. A total of 39 eyes (7.25%) had a refractive surprise. A total of 32 of 39 eyes were more myopic than -1.00D and 7 of them were more hypermetropic than +1.00D. There was no correlation between the mean PE and IOL type, AL, K1, K2, and IOLp. There were a positive statistically significant correlation between PE and age (r=0.095; P=0.028) and a negative statistically significant correlation between achieved SE and AL (Spearman’s r=-0.125; P=0.04), and age (r=-0.141; P=0.01).
understanding the effects of different disease subtypes, which is key to developing improved diagnostic methods. Gaining an understanding of a system as complex as the respiratory system is difficult if not impossible via experimental methods alone. Computational models offer a complementary method to unravel the structure- function relationships occurring within a multiscale, multiphysics system such as this. Here we review the current state-of-the-art in techniques developed for pulmonary image analysis, development of structural models of the respiratory system and predictions of function within these models. We discuss application of modeling techniques to obstructive lung diseases, namely asthma and emphysema and the use of models to predict response to therapy. Finally we introduce a large European project, AirPROM that is developing multiscale models to investigate structure-function relationships in asthma and COPD.
Modern analysis of the stability of electric power systems is based, as a rule, on the numerical integration of nonlinear models of these systems. In the process of integration, the system trajectories are calculated for different fault scenarios, various operating conditions and different network topologies. Special software packages are used to simulate power systems models in the off-line (not real-time) mode. For example, EUROSTAG and RUSTAB software packages are used by the System Operator of United Power Systems of Russia for planning and managing electrical regimes. However, time-domain methods do not provide stability margins, which would give indication “how far” from instability the system is, which would yield suitable sensitivity analysis tools (Ribbens-Pavella et al., 2000).
This latter property also gives rise to the expected utility representation, i.e., it explains how a utility function over decisions can be uniquely generated from the expectation of a utility function that has domain the set R of possible decision outcomes. Hence, whilst a non-linear map may be applied to determine the utility value of the outcomes within R , property 2 states that linearity is used to determine the utility value of compound or non-degenerate decisions by evaluating a weighted linear sum of the utility for its possible outcomes. In application it is therefore usual to simply assign a, possibly non-linear, utility function over the decision outcome set R (perhaps so as to ensure it is in agreement with some assumed level of risk aversion etc.) and to then use this utility function along with the known distribution over R that corresponds to the given compound decision of interest so as to determine that compound decision’s actual utility value.
In this study, the objective is to develop a fuzzy prob- ability based Markov chain model to predict long term regional electric power demand. The model is coupled with fuzzy probability and discrete interval method to Markov chain in order to deal with the vagueness and uncertainty in system parameters and their interrelation- ships. The model can reflect the different possible of power demand and provide information to a long term power system programming. The model is applied to the case of Beijing. The power load of Beijing is forecasted in different satisfaction degrees.