July 2009 Sample Clauses

July 2009. The redundancy pay out for a person employed at Council after 1 July 2009, whose position becomes redundant, will be entitled to: i Three (3) weeks ordinary pay per year of continuous service but not to exceed a maximum 12 month payment;
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July 2009. The redundancy pay out for a person employed at Council prior to 1 July 2009, whose position has become redundant, will be maintained on a present occupant only basis as:
July 2009. The individual installing or using this software represents and warrants that he or she has authority to enter into this Agreement with Balsamiq on behalf of the Licensee, that he or she has read the terms and conditions set out herein and that the Licensee accepts and agrees to be bound by this Agreement. If the Licensee does not agree with the terms and conditions, the Licensee must not use or permit the use of the Product.
July 2009. Effective July 1, 2009, the pay rates on the July 1, 2008 pay schedules shall be increased by three percent (3 %) as shown in Sections A.1., 2., and 3.
July 2009. 30 June 2010 An officer shall be paid a District Allowance at the standard rate prescribed in column II of Schedule D – District Allowance Rates as at 1 July 2009, for the region in which the officer’s headquarters are located. Provided that where the officer’s headquarters is situated in a town or placed specified in column III of Schedule D – District Allowance Rates as at 1 July 2009, the officer shall be paid a District Allowance at the rate appropriate to that town or place as prescribed in column IV of said schedule.
July 2009. The comparison is applied to the urbanized (URB) and reference (CTRL) simulations vs. the observations. The simulation performance is assessed using the Xxxxxxx linear correlation coefficient (Xxxxx 1995; Xxxxxxx et al., 2006; Xxxxxxx, 2004). It assesses the linear relationship between the simulations and the observations but fails to account for bias (Xxxxxxx et al., 2006). For a better characterisation the mean error (ME) is also computed, giving the bias of the simulations. Accuracy is assessed based on the mean square error (MSE), where high values of MSE indicate a high level of discrepancy between the simulations and the observations. The root square of MSE (RMSE) represents the typical magnitude of the simulation error and it has the same dimension as the original variable. According to Xxxxxx (2002) and Xxxxxxx et al. (2006) the parameter RMSEub evaluate the skill of a simulation, which represents the unbiased root MSE after a mean deviation is removed. A simulation has skill if the following conditions are met: (1) σobs~σsim, (2) RMSE<σobs, (3) RMSEub<σobs, where σobs is the standard deviation of observations and σsim is the standard deviation of the simulations. Data R Summer MEAN Sigma RMSE RMSEub R Winter MEAN Sigma RMSE RMSEub a) TEMPERATURE Urban OBS 20.51 2.47 9.15 2.83 CTRL 0.81 18.78 2.97 2.46 3.66 0.86 8.56 2.95 1.64 1.53 URB 0.82 19.01 2.98 2.28 4.37 0.88 8.48 2.97 1.61 1.46 Coastal OBS 19.75 1.95 9.25 2.61 CTRL 0.72 18.34 1.5 1.94 1.81 0.92 9.06 2.51 1.04 1.32 URB 0.76 18.26 1.63 1.95 1.61 0.94 9.03 2.54 1.02 1.61 Inland OBS 20.66 3.11 8.1 3.55 CTRL 0.82 18.24 3.52 3.17 4.18 0.81 7.79 2.97 2.14 2.98 URB 0.82 18.32 3.53 3.12 4.24 0.81 7.61 3.05 2.17 2.8 Rural OBS 19.64 3.4 4.9 3.35 CTRL 0.9 18.13 3.76 2.28 2.95 0.5 7.53 2.9 4.3 5.35 URB 0.9 18.12 3.77 2.28 2.91 0.5 7.22 3.03 4.15 5.15 b) RELATIVE HUMIDITY Urban OBS 0.01 0.0017 0.00578 0.0012 CTRL 0.78 0.009 0.0013 0.002 0.00000164 0.92 0.00465 0.00108 0.0014 0.00047 URB 0.75 0.009 0.0012 0.002 0.00000196 0.91 0.00469 0.00101 0.001 0.00052 Coastal OBS 0.011 0.0016 0.00558 0.00123 CTRL 0.89 0.0095 0.0013 0.0016 0.000000578 0.91 0.00501 0.00118 0.001 0.00106 URB 0.85 0.0095 0.0013 0.0017 0.000000777 0.91 0.00505 0.00115 0.001 0.0011 Inland OBS 0.0123 0.0019 0.00606 0.00137 CTRL 0.77 0.009 0.0013 0.0034 0.00000148 0.91 0.00469 0.00108 0.0014 0.002 URB 0.73 0.0091 0.0013 0.0034 0.00000173 0.92 0.00475 0.001 0.0014 0.00197 Rural OBS 0.0103 0.0015 0.0043 0.00107 CTRL 0.82 0.0091 0.0012 0.0015 0...
July 2009. Figure 11. Difference plots for the (a) air temperature at 2 m and (b) wind speed at 10 m between the outputs of the urbanized (BEP + AHF) and control runs of the Enviro- HIRLAM model on 5th of July 2009 at 6 UTC. During the daytime hours (from 7 to 14 UTC) the wind at the coastal station is increased due to the peak flows of the sea breeze circulation, while the difference in the wind shows a decreased at the urban and at the sub-urban hinterland station. Following the influence of the sea and up-valley breeze circulation, it causes a positive relative humidity anomaly during the afternoon. The UHI during the day hours appears to be negligible at urban and coastal sites but a negative effect occurs at the sub-urban hinterland site (-1.3 ºC at 15 UTC). This fact could be explained by the fact that this area is located in the upper side of the valley in the center of the two mountain ranges. Additionally, while the type of districts is that of “high density buildings”, the rest of the city is characterized as industrial-residential-centre and is located in the open side of the valley towards the sea. These characteristics provoke “cold spots” where the shadows and the lesser heating of the building materials produce a lower temperature during the day. The gradient between the slopes of the surrounded mountains and the area is larger and the anabatic plus up-valley winds increase (the difference of the wind in the simulations is 1 ms-1 in the hinterland and negative in the city centre and in the coast). From the late afternoon towards the night-time (15 to 23 UTC) the process of the development of the UHI starts again when the land breeze regime moves out from the city to the sea. While the wind speed at the sub-urban areas commences to decrease, it increases at the urban areas. The temperature anomaly (urban minus control simulations) reach 0.4 ºC at 23 UTC at the urban site while in the sub-urban areas still negligible but increasing.
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July 2009. August 10, 2007 ... September 28, 2007. September 28, 2007. December 17, 2007. March 31, 2008 .... June 20, 2008 ...... October 17, 2007 January, 2008 ....... October 31, 2007 PPAA Blueprints .................. Minutes of Panelists reviews and ratings. Study findings ......................
July 2009. June–July 2009 .... July 2009 .............. Xxxxxx, PPT presentation, attendee’s list and scoring rule. Scoring results and reports. Statistical analysis and re- ports. Xxxxxx, PPT, attendee’s list, standard setting tech- nical report. Xxxxxx, PPT, attendee’s list, performance level descriptors and cut scores and standard setting tech- nical report. Reports. Stakeholder roster, attendee’s list and sug- gestions. Test Forms. Test form approval. Office of the Undersecretary for Academic Affairs As- sessment Division. Evaluation and Planning Unit. Office of the Assistant Sec- retary for Academic Serv- ices. Office of the Associate Sec- retary for Special Edu- cation. Action steps Completion date Documentation Responsible office Estimated budget
July 2009. 39.08307699 January 2014...... 20.47517506 February 2005..... 52.23355203 August 2009....... 38.91816237 February 2014..... 20.09599005 March 2005........ 51.
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