Table 2. Software Subscription Use Case OpenShift Enterprise OpenShift Enterprise Broker Infrastructure OpenShift Enterprise is intended to be used as a platform as a service and will be supported only when used in that capacity. OpenShift Enterprise is not supported on non-server hardware such as desktops or workstations. OpenShift Enterprise is intended for use on a dedicated Physical Node or Virtual Guest; running other applications and/or programs of any type on the Physical Node or Virtual Guest can have a negative impact on the function and/or performance. Red Hat JBoss Enterprise Application Platform for OpenShift and/or Red Hat JBoss EAP for xPaaS will be supported in accordance with the terms of Exhibit 1.B.
Table 2. Determinations Determination Concerning Determiner Bereavement Leave Coordinator Parental Leave (all) Coordinator Sick Leave Coordinator
Table 2. Software Subscription Use Case OpenShift Enterprise OpenShift Enterprise Broker Infrastructure OpenShift Enterprise is intended to be used as a platform as a service and will be supported only when used in that capacity. OpenShift Enterprise is not supported on non-server hardware such as desktops or workstations. OpenShift Enterprise is intended for use on a dedicated Physical Node or Virtual Guest; running other applications and/or programs of any type on the Physical Node or Virtual Guest can have a negative impact on the function and/or performance. Red Hat CloudForms is supported solely for the purpose of managing OpenShift Enterprise Software. Red Hat JBoss Middleware will be supported in accordance with the terms of Exhibit 1.B.
Table 2. Minutes per year with the corresponding probability and the inverse cumulative probability as a function of standard deviation. In the third step, the value rqh, which represents the same range for an allowed normal distribution of the quarter-hourly average frequency deviation, is calculated based on the assumption that the two signals are not correlated: In the fourth step, the ranges which correspond to the probabilities required by SO GL Article 128(3) are calculated taking rqh as basis. The probabilities are calculated as follows: For the calculation of the ranges, the inverse cumulative probabilities of and will be used. SO GL Parameters qh per year Probability inverse cumulative probability value as c σ qh outside level 1 ACE range 5256 0.85 1.0364 σ qh outside level 2 ACE range 876 0.975 1.96 σ Table 3: Values outside the ranges. In the last step, the level 1 and level 2 ranges (L1 and L2) are calculated for each LFC BLOCK. With KSA as K-Factor of the Synchronous Area expressed in MW/Hz, KFCR as the total FCR of the Synchronous Area and KFCR,i as initial FCR obligation of LFC BLOCK i, the targets are given by:
Table 2 the Approved EU Standard Contractual Clauses with optional provisions as set forth in Section 2.2.
Table 2. End-of-Pipe Nutrient Loading Caps for Tar-Pamlico Basin Association Total Nitrogen (lbs/yr) Total Phosphorus (lbs/yr) Phase III Association Cap (15 members) 891,271 (404,274 kg/yr) 161,070 (73,060 kg/yr) Phase IV Association Cap (16 members) a 891,271 (404,274 kg/yr) 161,070 (73,060 kg/yr) aThe City of Creedmoor has expressed interest in constructing a new treatment facility that would discharge up to 1.15 MGD of wastewater in the Tar-Pamlico basin. The City was accepted as a member in 2014 and is included here presuming it applies for and receives an NPDES discharge permit for the discharge. In March 2015 the City of Creedmoor entered into a service agreements with SGWASA that will result in their wastewater continuing to be treated by the facility. Should Creedmoor not apply for on NPDES permit no adjustment will be made to the cap. Final nutrient allocations/ limits will be determined in the course of any permitting process. If loading exceeds either cap in any year of this Agreement, then the Association shall offset that exceedance by funding nonpoint source nutrient controls as described in Section V. Relaxation of these caps in future amendments to this Agreement would only be contemplated if monitoring and modeling results suggest all water quality standards and goals are being met and that assimilative capacity is available to the Association while maintaining a margin of safety, all consistent with the TMDL.
Table 2. The fact that MTT values in our study were less affected than were CBF and CBV values when the dose was low- ered is in concordance with the results of a study by Xxxxxxx et al (21) in which several types of reconstruction algo- rithms were compared when the total CBF 0.911 ,.0001 .094 .118 dose was decreased by one-half. Those CBV 0.906 ,.0001 .025 .089 authors found, however, that the CBV MTT 0.864 ,.0001 .075 .371 values of gray matter actually were un- Gray matter derestimated by 18.6% in all patients, CBF 0.895 ,.0001 .408 .923 and the CBV values of white matter CBV 0.917 ,.0001 .094 .477 were overestimated by 1.5% with fil- the CT perfusion maps, authors of two studies (18,19) reported that clinical decision making is unlikely to change if the overall variability stays within 10%. Dose reduction to less than 2.5 mSv results in overestimation of patient perfusion values, particularly of CBF and CBV values. We hypothesize that increased noise levels lead to increased small-scale gradients on the intensity curves, which are erroneously inter- preted as increased blood flow and vol- ume during the deconvolution process inherent in the perfusion analysis. Ac- cording to the central volume principle (20), MTT is less affected. tered back projection as the recon- struction algorithm, but they gave no explanation for this observation. Our optimal point of dose reduction was lower than the reduction of 33% (from 190 mAs to 125 mAs, no effective dose values were reported) suggested by Ju- luru et al (22). These authors found lit- tle effect of lower dose settings on per- fusion values, although in their study, Xxxxxx et al investigated five dose set- tings with simulated noise, whereas we used real measured noise. To our knowledge, previously pub- lished work is limited primarily because of the difficulty of realistic simulation of patient data at different dose levels. In other studies, this was achieved by simply adding Gaussian noise (22), by reconstructing only a part of the total number of raw projections (21), or by using dual-source CT scanners and let- ting the two tubes operate at different milliampere and kilovolt settings simul- taneously during acquisition (23). An alternative to our approach would be to use dedicated low-dose simulators (24,25). Our approach combined real patient tissue curves with multiple CT scans at a wide range of tube current settings to construct patient-specific digital phantoms. In van den Boom et al (14) these patient-spe...
Table 2. Circumstances where employers are not entitled to replacements as provided in clause 3.1
Table 2. Average Annual Program Activity Levels and Budgets Program Class Average Annual Activity Level Average Annual Budget U-HE Toilet (R/V) SF 1,655 $ 165,500 U-HE Toilet (R/V) MF 618 $ 61,800 HE CW (R/V) SF 3,038 $ 315,638 HE CW Common (R/V) MF 90 $ 33,000 HE CW In-Unit (R/V) MF 374 $ 35,138 Smart Controllers (R/V) SF 1,717 $ 217,800 Smart Controllers (R/V) MF 98 $ 58,350 HE Pop-Up Nozzle (V) SF 119,894 $ 389,656 HE Pop-Up Nozzle (V) MF 52,057 $ 169,185 HE Pop-Up Nozzle (V) CII 189,684 $ 616,473 HE Toilet (R/V) (b) CII 713 $ 100,400 HE CW Coin-Op (R/V) CII 68 $ 27,200 HE Urinals (R/V) CII 223 $ 65,700 Smart Controllers (R/V) CII 200 $ 118,050 Commercial Irrigation Sys (R) CII 146 $ 292,000 Commercial Kitchen (R) CII 10 $ 3,300 Ice Machine (R) CII 5 $ 9,925 Program Class Average Annual Activity Level Average Annual Budget Pre-Rinse Spray Valve (R) CII 10 $ 1,100 Cooling Tower Controller (R/I) Ind 5 $ 5,000 Cooling Tower pH Contr. (R/I) Ind 5 $ 19,050 HE Toilet Direct Install SF 3,040 $ 1,006,240 HE Toilet Direct Install MF 1,189 $ 345,985 Audits and Surveys SF 45 $ 5,760 Audits and Surveys MF 16 $ 15,200 Web-Based Home Survey SF 4,172 $ 62,580 Audits and Surveys CII 6 $ 12,000 Industrial Process Audits (I) Ind 4 $ 5,132 Lrg Landscape Surveys Irr 67 $ 93,800 Lrg Landscape Water Use Rpt Irr 1,373 $ 117,143 Residential Conservation Kit (V) SF 2,399 $ 52,778 Programmatic Total $ 4,420,881 Administration and Research $ 1,186,170 Salary $ 415,081 Benefits $ 303,009 Office Supplies/Travel/Other $ 468,080 Public Information $ 1,127,029 School Education $ 265,677 Total $ 6,999,757 2 The following conditions apply to conservation program activities:
Table 2. 1: Names of folders from the 2018 survey fieldwork data collection Folder name Village Contents Spoken Data_01_aolys_dul_srvy Dulolong oral history, wordlist Spoken Data_02_aolys_alk_srvy Alor Kecil oral history, wordlist Spoken Data_03_aolys_alb_srvy Alor Besar oral history Spoken Data_04_aolys_bya_srvy Buaya oral history, wordlist, speech Spoken Data_05_aolys_ter_srvy Ternate oral history, wordlist, speech Spoken Data_06_aolys_mun_srvy Munaseli oral history Spoken Data_07_aolys_ban_srvy Bana Onong oral history, wordlist Spoken Data_08_aolys_hel_srvy Helangdohi oral history, wordlist Spoken Data_09_aolys_pan_srvy Pandai oral history Spoken Data_10_aolys_war_srvy Wailawar oral history, wordlist, speech Spoken Data_11_aolys_bar_srvy Baranusa oral history, wordlist, speech Spoken Data_12_aolys_beo_srvy Beang Onong oral history, wordlist, speech Spoken Data_13_aolys_kya_srvy Kayang oral history, wordlist, speech Spoken Data_14_aolys_mrs_srvy Xxxxxx oral history All fourteen folders contain oral history interviews and some have recordings of wordlist and natural speech data. The abbreviation aolys represents the Alorese Glottolog code (aol) and my initials ys. The following abbreviations in the folder name stand for the names of the villages where I collected the data (see also list of abbreviations on page xv). The details of the oral history recordings can be found in the introduction to Chapter 3 (cf. §3.1), while the details of the wordlist can be found in the introduction to Chapter 5 (cf. §5.1). From this 2018 survey fieldwork, I also collected written data of stories about village history preserved by the local leaders in the form of scanned PDF files (cf. §3.3.1; Table 3.3). During my fieldwork in 2020, I focused on one dialect spoken in three villages: Pandai (pan), Wailawar (war), and Kabir (kbr). Kabir is an additional location where Alorese speakers of the same dialect as Pandai and Wailawar can be found. All three villages are located close to each other (see Figure 2.1). The list in Table 2.2 below shows the names of the folders in which the recordings of natural speech are stored, together with their transcriptions.
