Table 16. Main effects calculated from number of Cycles. Columns 3-5 (titled 1-3) are intermediate calculations used by the Xxxxx' algorithm. Factor # Cycles 1 2 3 Effects Mean 875 1575 2155 2845 356 T 700 580 690 -985 -246 RH 500 390 -595 -0000 -000 X*XX 00 000 -000 -000 -64 j 290 -175 -995 -1465 -366 T*j 100 -420 -90 205 51 RH*j 250 -190 -245 905 226 T*RH*j 50 -200 -10 235 59 The main effects of T, RH and j are show negative impact on test duration. From the parallel experiments FS02 and FS12, it was found a standard deviation of 106 cycles. Although limited, this gives some indication of significance levels. A large, positive interaction is found for RH and j. This effect can be interpreted at half the difference between the average effect of RH at high and low j. This is illustrated in Figure 19. Figure 19. Influence of the RH*j interaction on the number of cycles before cell failure. Corner values (black) indicate averaged responses at given levels. Red numbers indicate averaged effects. Interaction effect is found from half the difference of opposite red numbers. From the figure it can be seen that the average effect for RH is -45 at high j whereas it is -497 at low j. By analogy, the average effect of j is -140 at high RH and -592 at low RH. Half the difference is in both cases 226 cycles. The effect does not easily translate into a phenomenon of PEMFC degradation nature. The large interaction of RH and j suggest that the main effects of RH and j are not additive. The isolated effects of RH and j cannot therefore be evaluated without taking the magnitude of the interaction into account.
Table 16. Performance Management Roles and Responsibilities Performance Management Roles and Responsibilities ACS Symetra
Table 16. The household income ranges between the two legal status groups were different, with undocumented immigrants reporting lower income ranges than their documented counterparts. Male respondents also skewed towards slightly higher incomes than females, regardless of legal status (Table 17). Over two-thirds of undocumented immigrants reported incomes in the range of $501 to $3,500 a month, with a modal income of $1,501-2,000/month. Documented immigrants on the other hand, reported income ranges that were higher, with a mode of $2,501- 3,500. A higher frequency of undocumented immigrant females reported making under $1,500/month (n=21), less than their documented counterparts. A similar pattern was seen with undocumented immigrant men with n=13 of them reporting making less than $1,500/month, while only one documented male reported making under $1,500/month. It is important to note that the survey population was not a random sample and that the 3:1 proportion of undocumented to documented survey respondents may have contributed to the income distributions. Table 17 Health Insurance and Medical Expenditures Undocumented immigrants rarely reported having health insurance coverage, while just over half of documented immigrants reported having health insurance (Table 18). A mere 6.8 percent (n=5) of undocumented immigrant females and 12.0 percent (n=9) of undocumented males reported having some type of health insurance, much lower than documented females (51.6 percent; n=16) and males (56.5 percent; n=13). Of the 43 respondents with health insurance, there does not seem to be much of a difference in health insurance satisfaction between legal status groups; though a higher frequency of documented immigrants reported having health coverage that “Always” met their medical and health needs (Table 19). The most common types of health insurances reported in households were Medicaid, Private Insurance, and Peachcare (Table 20). Table 20 clearly suggests that Medicaid is an important resource for undocumented respondents; 87.5 percent of those who have someone in their home with Medicaid were undocumented respondents. Table 18 Table 19 Table 20 Undocumented immigrants reported going longer without having visited a medical or health professional than documented respondents (Table 21). The most reported time period without seeing a medical or health professional was more than 1 year (n=88); undocumented immigrants accounted for 86.4 percent of this group and were younger. A...
Table 16. Species (and their abundances) that best explain dissimilarities between the estuary groups defined by the LINKTREE analysis. Cont: contribution of each species to the dissimilarity between groups. Cum: Cumulative contributions. Dissimilarity Species Average abundance Cont. Cum. Xxx Xxxxxxxx Group 3 Group 4 (%) (%) Palaemon longirostris 1.78 0.00 - - 7.4 7.4 Pachygrapsus marmoratus 1.54 0.00 - - 6.4 13.7 Macropodia rostrata 0.00 1.25 - - 5.2 18.9 Xxx-Xxxxxxxx 73.32 Palaemon elegans 1.21 0.00 - - 5.0 23.9 Pisidia longicornis 0.00 0.90 - - 3.7 27.6 Palaemon serratus 0.00 0.76 - - 3.1 30.8 Liocarcinus navigator 0.00 0.76 - - 3.1 33.9 Palaemonetes sp. 0.00 0.71 - - 2.9 36.8 Crangon crangon 0.86 - 1.87 - 5.3 5.3 Macropodia rostrata 0.00 - 0.97 - 5.3 10.6 Solea solea 0.00 - 0.92 - 5.0 15.6 Lea-Group 3 53.21 Palaemon serratus 0.00 - 0.80 - 4.4 20.0 Carcinus maenas 1.33 - 2.06 - 4.0 24.0 Diplodus sargus 0.00 - 0.75 - 3.9 27.9 Anguilla anguilla 0.69 - 0.00 - 3.8 31.6 Hippocampus hippocampus 0.00 - 0.67 - 3.7 35.3 Palaemon elegans 1.21 - - 0.48 7.5 7.5 Solea solea 0.00 - - 0.87 7.3 14.8 Lea-Group 4 49.08 Platichthys flesus 0.00 - - 0.78 6.5 21.2 Palaemon longirostris 1.78 - - 1.08 6.3 27.5 Macropodia rostrata 0.00 - - 0.70 6.0 33.5 Pilumnus hirtellus 0.69 - - 0.00 5.8 39.3 Syngnathus typhle 0.69 - - 0.07 5.2 44.5 Pachygrapsus marmoratus - 0.00 1.41 - 5.3 5.3 Palaemon longirostris - 0.00 1.25 - 4.7 10.0 Palaemon elegans - 0.00 0.93 - 3.5 13.5 Crangon crangon - 1.00 1.87 - 3.2 16.6 Oiartzun-Group 3 60.10 Carcinus maenas - 1.27 2.06 - 3.0 19.6 Liocarcinus navigator - 0.76 0.00 - 2.9 22.5 Diplodus sargus - 0.00 0.75 - 2.7 25.2 Palaemonetes sp. - 0.71 0.00 - 2.7 27.9 Arnoglossus laterna - 0.71 0.00 - 2.7 30.6 Arnoglossus thori - 0.71 0.00 - 2.7 33.2 Hippocampus hippocampus - 0.00 0.67 - 2.5 35.8 Palaemon longirostris - 0.00 - 1.08 4.7 4.7 Pachygrapsus marmoratus - 0.00 - 1.04 4.7 9.4 Platichthys flesus - 0.00 - 0.78 3.4 12.9 Liocarcinus navigator - 0.76 - 0.00 3.4 16.2 Oiartzun-Group 4 66.07 Palaemonetes sp. - 0.71 - 0.00 3.2 19.4 Arnoglossus laterna - 0.71 - 0.00 3.2 22.5 Arnoglossus thori - 0.71 - 0.00 3.2 25.7 Xxxxxxx nitescens - 0.64 - 0.00 2.9 28.5 Thoralus cranchii - 0.64 - 0.00 2.9 31.4 Buglossidium luteum - 0.64 - 0.00 2.9 34.2 Scorpaena porcus - 0.64 - 0.00 2.9 37.1 Diplodus sargus - - 0.75 0.48 5.0 5.0 Crangon crangon - - 1.87 1.46 4.8 9.8 Palaemon elegans - - 0.93 0.48 4.5 14.3 Group 3-4 44.23 Hippocampus hippocampus - - 0.67 0.00 4.3 18.6 Buglossidium luteum ...
Table 16. Delivery plan for older people Performance Framework NB Partners to revise and complete the delivery plans by mid-May 2013. This will include checking against the menu of local outcome indicators and data availability Long Term Outcomes Intermediate/Short Term Outcomes Inputs/Resources Partners TBI Indicators & Baseline info Improvement/ Targets People are healthy and have a good quality of life People live longer healthier lives The health & social care spend on older people approx. £204m per annum. This figure excludes some costs that cannot be disaggregated (eg some aspects of prescribing). Still to add anything from partners Increased healthy life expectancy (Indicator definition? Years?) Measuring quality of life? Increase From and to? Inequalities in health are reduced Reduce life expectancy gap between most and least deprived areas Detail to be discussed Perhaps an indicator re increase in % of those entitled to claim benefits doing so? TBA People know how to stay as healthy & fit as possible Create a single point of access to services to be available in every District People’s perceptions of their levels of health Number of Anticipatory Care Plans tba People’s health needs are met at the earliest and Provide targeted re- ablement services through Integrated District Teams % of people receiving reablement interventions who do not require ongoing care interventions after Increase from baseline of 40% Long Term Outcomes Intermediate/Short Term Outcomes Inputs/Resources Partners TBI Indicators & Baseline info Improvement/ Targets most local level possible with initial 6 weeks Increase the number of community-based health and social care activities in each area of Highland and the number of community-based activities in each area. 40% of people receiving re- ablement interventions not requiring on-going care interventions after initial 6 weeks. Implement a local pilot area to examine the options for developing an integrated transport solution in relation to health and social care and community wellbeing People’s health needs are anticipated and planned for Develop strategic and operational commissioning of services for adults within the Lead Agency Model Improve service delivery through service review and redesign The age of admission of older people to long-term residential and nursing care Reduce the rate of emergency inpatient bed days for people aged 75 and over per 1,000 population Co-production tba? tba Tele-health tab? Reduce the number of younge...
Table 16. “Reduced risk” irrigation target values over the growing season for midday stem water potential (bars). Period Month March April May June July August September Early- -6 -8 -9 -10 -12 -13 -14 Mid- -7 -8 -9 -11 -12 -13 -15 Late- -7 -9 -10 -11 -12 -14 -15 Results: Initially only five sites were able to have a comparison between “conventional” irrigation management and “reduced risk” irrigation management. At four of the sites, (Aguair, CSUC, Giacolini, and Xxxxxxx), benefits of the “reduced risk” program in terms of reduced water use was realized (see Figure 11). Although the actual quantity of water savings was beyond the scope of this project, some of these sites saved applied water as compared to the “conventional” program in terms of SWP (examples: CSUC, Giacolini, Xxxxxxx) While others mostly copied the “reduced risk” schedule in their “conventional “ orchard sites (examples: Aguair and Xxxx). Although measuring energy and economic savings from reduced irrigations was beyond the scope of this project it was observed with some growers who scheduled fewer irrigations than in previous years. Scheduling and applying fewer irrigations had no impact on fruit production (only measured in the first year) or on fruit quality at season’s end (see Tables 17 and 18). In the last four years all cooperating growers scheduled irrigations in all projects sites based on pressure chamber readings and following the “reduced risk” recommendation of irrigation scheduling. Monitored sites generally observed a good match between the observed and the target SWP. An example of these comparisons can be seen if Figure 12. Figure 11. Midday stem water potential in comparison orchards -0.6 -0.8 -1.0 -1.2 -1.4 treatment Conventional Reduced Risk Target Xxxxxx APR MAY JUN JUL AUG SEP 0 -1 -2 -3 CSUC -0.6 -0.8 -1.0 -1.4 APR MAY JUN JUL AUG SEP Giacolini APR MAY JUN JUL AUG SEP -0.5 -0.7 -0.9 -1.1 -1.3 -1.5 -1.7 -1.9 Xxxx APR MAY -0.6 -0.8 -1.0 -1.2 -1.4 JUN JUL AUG SEP Xxxxxxx APR MAY JUN JUL AUG SEP -0.6 -0.4 -0.8 -0.8 -1.0 -1.2 -1.2 -1.4 -1.6 -1.6 Xxx X -2.0 Xxxxxxx Xx APR MAY JUN JUL AUG SEP APR MAY JUN JUL AUG SEP -0.5 -0.5 -1.0 -1.0 -1.5 Xxxxxxx -1.5 Xxxxx J APR MAY JUN JUL AUG SEP APR MAY JUN JUL AUG SEP -0.5 TARGET -0.9 OBSERVED -1.3 -1.7 Willow G APR MAY JUN JUL AUG SEP
Table 16. Number (N) of measured and modelled pairs for each area and selected day. 53 Table 17. Deviations of simulated versus observed climate variables for 2010/08/07 and 2010/08/08 in Casco Viejo. 61 Table 18. Difference between measured and modelled cClimate variables for 2010/08/06 and 2010/08/08 in Miribilla. 65 Table 19. Description of PET values derived from measured climate variables data for each area and selected day. 69 Table 20. PET correlation coefficients between measured and modelled values for each area and selected day, as well as for all data available. 71 Table 21. Values of adjusted R squared from the seven regression analysis of measured PET with the independent variables involved. 72 Table 22. Values of standardized regression coefficients (Beta) from the seven regression analysis of measured PET. 72 Table 23. Values of adjusted R squared from the seven regression analysis of ΔPET (PETmeasured - PETmodelled) with the independent variables involved. 73 Table 24. Values of standardized regression coefficients (Beta) from the seven regression analysis of ΔPET (PETmeasured - PETmodelled). 73 Table 25. Values of ΔPET, ΔPETa, ΔPETb values for each area and selected day. 74 Table 26. Values of adjusted R-squared from the three regression analysis of ΔPET, ΔPETa, ΔPETb with the independent variables involved. 74 Table 27. Values of standardized regression coefficients (Beta) from the three regression analysis of ΔPET, ΔPETa, ΔPETb. 74 List of Abbreviations CMIP5 coupled model intercomparison project phase 5 CORDEX coordinated regional climate downscaling experiment CPU central processing unit (computer processor) ECMWF European centre for medium-range weather forecasting ENVI-met microscale urban climate model Enviro-HIRLAM environment – high resolution limited area model GCM global climate model IPCC integovernmental panel on climate change (of the UN) SW, XX Xxxxx- and Longwave (radiation) Tmrt mean radiant temperature UHI urban heat island UrbClim urban boundary layer climate model WS, WD wind speed and direction 1 Executive Summary Within RAMSES, use is made of numerical models to generate urban climate projections. This is a useful and even necessary exercise as only such computer models can provide quantitative information regarding the impact of climate change on local urban climate. Indeed, since cities strongly shape their own climate, when assessing climate change impacts it is insufficient to simply take output, such as temperature or prec...
Table 16. 1 My School Leader Contributes to a Positive School Environment My school leader contributes to a positive school environment. Participant Years at APEG Position Agree Sometimes Disagree 2 16 Curriculum Coach X 3 4 Teacher X 4 23 Teacher X 5 1.5 Teacher X 6 4 Teacher X \ 7 * Curriculum Coach X X 8 5 Curriculum Coach X *Choose not to state Table 16. 2
Table 16. 8.1(d)-2 Consideration for the License under Section 16.8.1(b) (Termination by Biogen for Convenience of an Initial Licensed Program) [***]
Table 16. Volvo CE raw data The information in the table above is confidential and must not be used in any publications unless granted by Volvo CE
