Table 5. Allowances Rates from the first full pay period on or after 1 July 2022 and 1 July 2023. Item Allowance Clause From the Operative Date of the Agreement $ 1 July 2022 $ 1 July 2023 $ 1 Uniform Allowance when uniform is not supplied Per shift 22.3(b) 1.49 1.49 1.49 Per week 22.3(b) 7.56 7.56 7.56 2 Laundry Allowance (excluding Nursing Classifications) Per shift or part thereof 22.3(c) 0.39 0.39 0.39 Per week 22.3(c) 1.81 1.81 1.81 3 Laundry Allowance (Nursing Classifications Only) Per week 22.3(c) 5.45 5.45 5.45 Meal Allowance when no meal is provided* 4 When required to work more than one hour beyond usual finishing time 22.4(a) 13.83 14.11 14.39 5 Further payment when overtime exceeds 4 hours (Aged Care, Health Professionals and Nursing Classifications only) 22.4(a)(ii) 12.47 12.72 12.97 6 Further payment when overtime exceeds 4 hours (Home Care Classifications only) 22.4(a)(ii) 13.83 14.11 14.39 On Call Allowance (Nursing classifications only)* 7 Between rostered shifts Monday to Friday 22.5(a)(i) 23.03 23.49 23.96 8 Between rostered shifts or on a Saturday 22.5(a)(ii) 34.70 35.39 36.10 9 Between rostered shifts or ordinary hours on a Sunday, public holiday or a day when not rostered to work 22.5(a)(iii) 45.09 45.99 46.91 On Call Allowance (Home care classifications only)* 10 Finishing duty on Monday to finishing duty on Friday 22.6(a) 20.63 21.04 21.46 11 Any other period or public holiday 22.6(b) 40.84 41.66 42.49 12 Mileage Allowance 22.7(a) & (c) 0.92 0.92 0.92 Continuing Education Allowance (Nursing Classifications Only) 13 RN - post grad certificate in clinical field 22.8(g) 20.39 20.39 20.39 14 RN - post grad diploma or degree in clinical field 22.8(h) 34.01 34.01 34.01 15 RN - relevant master's degree or doctorate in clinical field 22.8(i) 40.78 40.78 40.78 16 EN - certificate IV qualification in a clinical field 22.8(j) 13.58 13.58 13.58 In-Charge Allowance (Nursing Classifications only) 17 RN – in charge of facility of less than 100 beds on day, evening or night 22.9(a) 24.30 24.30 24.30 18 RN – in charge of facility of more than 100 beds on day, evening or night 22.9(a) 39.16 39.16 39.16 19 RN in charge of a shift in a section of a facility 22.9(b) 24.29 24.29 24.29 Leading Hand Allowance (Aged Care Classifications only)* 20 - in charge of 2 - 5 Employees 22.10(b) 26.17 26.69 27.22 21 - in charge of 6 - 10 Employees 37.34 38.09 38.85 22 - in charge of 11 - 15 Employees 47.14 48.08 49.04 23 - in charge of 16-19 Employees 57.63 58.78 59.96 24 Sle...
Table 5. Panel logistic regression models of the annual moving propensity of couples between t and t+1 Variable (observed at wave t) Model 1 Model 2 Model 3 Model 4 Model 5 Coeff. S.E. Coeff. S.E. Coeff. S.E. Coeff. S.E. Coeff. S.E. Housing satisfaction (ref=both satisfied) Man dissatisfied 0.977*** 0.081 0.690*** 0.079 0.226** 0.092 Woman dissatisfied 1.033*** 0.074 0.790*** 0.073 0.308*** 0.085 Both dissatisfied 1.751*** 0.078 1.100*** 0.077 0.130 0.091 Dislike neighbourhood (ref=both like) Man dislikes 0.460*** 0.120 0.410*** 0.117 -0.122 0.135 Woman dislikes 0.649*** 0.111 0.620*** 0.106 0.068 0.124 Both dislike 0.953*** 0.115 0.968*** 0.109 -0.081 0.127 Desire to move (ref=neither desire) Man desires 0.756*** 0.098 0.646*** 0.098 0.629*** 0.100 Woman desires 0.475*** 0.104 0.386*** 0.105 0.322** 0.108 Both desire 0.969*** 0.077 0.879*** 0.077 0.825*** 0.083 Expect to move (ref=neither expect) Man expects 1.817*** 0.125 1.417*** 0.127 1.414*** 0.128 Woman expects 2.120*** 0.115 1.738*** 0.116 1.720*** 0.117 Both expect 3.735*** 0.085 3.200*** 0.084 3.197*** 0.084 Highest age -0.033*** 0.003 -0.024*** 0.003 -0.024*** 0.003 Cohabit (ref=married) -0.022 0.067 -0.179** 0.078 -0.181** 0.078 Couple type (ref=couple, no children) Preschool chldren -0.231** 0.084 -0.111 0.099 -0.121 0.099 School age children -0.753*** 0.081 -0.499*** 0.091 -0.513*** 0.091 Children of both ages -0.657*** 0.110 -0.261** 0.125 -0.266** 0.125 Non-dependent children -0.634*** 0.115 -0.360** 0.125 -0.361** 0.125 Other 0.336** 0.169 -0.146 0.201 -0.158 0.202 Change in n children (ref=no change) Increased at t+1 0.170 0.096 -0.046 0.114 -0.049 0.115 Decreased at t+1 -0.080 0.143 0.010 0.162 0.009 0.162 Unknown at t+1 2.075*** 0.204 1.975*** 0.231 1.987*** 0.231 Highest education level (ref=very low) Low 0.206 0.122 0.089 0.132 0.085 0.132 Medium 0.131 0.117 -0.088 0.126 -0.098 0.126 High 0.378** 0.128 -0.081 0.140 -0.090 0.140 Employment status (ref=no earner) Dual earner -0.344*** 0.098 -0.372*** 0.110 -0.375*** 0.110 Single earner -0.190** 0.095 -0.312** 0.107 -0.310** 0.107 Change in n employed (ref=no change) Increased at t+1 -0.007 0.112 0.002 0.129 -0.005 0.129 Decreased at t+1 0.459*** 0.093 0.448*** 0.107 0.450*** 0.107 Unknown at t+1 -0.052 0.184 -0.030 0.207 -0.033 0.207 Real household income/10,000 0.043*** 0.011 0.034** 0.011 0.035** 0.011 Housing tenure (ref=homeowner) Social renter -0.256** 0.087 -0.164 0.097 -0.170 0.099 Private renter 1.303*** 0.081 0.983*** 0.093 0.962*** 0.09...
Table 5. A 8-round linear trail for Friet-PC in the form of masks at the output of ξ in the 8 successive rounds. round δa δb δc weight 0 ...............................1 2 1 ...............................1 ...............................1 ...............................1 2 2 ................8............... ................................ ...............................1 2 3 ................8...8..........1 ................8............... ................8..1............ 6 4 ................4..18...8......1 ....................8..........1 .......1........8...8..........1 10 5 ....4..1........4..14...8...8... ................4..1....8....... ....8...........4..18...8..1...1 14 6 8...c..14.......2...c......18..1 ....4..1............4.......8... ....4..18......14...4.......8. 22 7 8.......c......16...a...8..1...1 8...8...4.......2...8......1...1 8..18..14.......2...c......1...1 22 5.6 Combined Resistance Against 1st Order DPA and SIFA A straightforward Friet-P implementation is vulnerable to SIFA [17] and SIFA- like attacks [28]. A realistic attack scenario would be the following. An adversary has access to the outer part of the state at a given time and can inject a fault during the computation of the permutation in order to recover some information on the inner part of the state. Provided that she can redo the attack multiple times on the same initial state, She could then try to inject a fault in the first round to modify one of the inputs of the AND operation in ξ. A bitflip in an input of a binary AND only propagates to its output if the other input is 1 and hence is only effective in that case. It can hence be simply be derived from the behavior of the fault-detection mechanism. Simulating probabilistic or less precise fault models such as, e.g., the random-AND fault model or a byte-based fault model would also yield exploitable results, although the adversary might need to profile the fault behavior of the device in advance with fault templates [28].
Table 5. 1: Employment outcomes of full-time first degree students (%) 2002/03 03/04 04/05 Employment 62.9% 62.7% 62.8% Employment and further study 7.9% 8.6% 8.1% Further study only 14.8% 15.0% 14.9% Assumed unemployed 7.0% 6.4% 6.5% Not available for employment 5.2% 5.0% 4.9% Other 1.0% 1.0% 1.1% Question not answered 1.2% 1.4% 1.8% Source: HESA, 2005 The potential of the lifelong learning sector to generate benefits for the UK economy should therefore not be underestimated. In addition, in Autumn 2006, the Financial Times newspaper ran a series of comprehensive reports on the state of the nation. One key conclusion was that investment in people, through better schooling and in infrastructure, and where the social benefit outweighed the cost, offered more permanent solutions than public spending on health and housing in poorer regions. Hence, policy interventions and other responses to economic, social and demographic changes could help to bring about enhanced participation in lifelong learning and increase attainment rates, which, in turn, could improve economic productivity considerably in the coming decades.
Table 5. 2 shows how different methods of in-situ preservation mitigate against specific threats. For example, geotextiles may be used in different ways: as a layer placed between the sediment and the archaeological objects, or as a barrier method, wrapping objects or a structure. These different uses mean it may be effective in different scenarios. The rubber sheeting method that was used on the Stora Sofia in Sweden represents various methods that cover a site, but which do not actively capture sand. These kinds of methods should be used in combination with, for example, additional sand deposits. 125 See, for example, the devastating effect of the Teredo navalis on the wrecks in the Oostvoornsemeer. xxxx://xxx.xxxxxxxxxxxxxxxxx.xx/magazine/MP03/ MP03_05.1.htm (accessed 30-01-2017). 126 On the Xxxxxxx Xxxxx, the Stirling Castle (wrecked 1703), and in the Southern Delta, the Roompot (wrecked 1853). Both are wrecks that have begun protruding from the seabed due to sand shifts. They belonged to the best preserved sites in northwestern Europe, but have been deteriorating rapidly over the last couple of years. Another wreck that is well preserved, with the boards still standing at least 3 metres is the OVM 14. This wreck, which lies at 30 metres depth in the Oostvoornsemeer, is now under threat of being destroyed by the Teredo navalis, which has been reintroduced into the lake due to the salinization of the water. 127 See Chapter 3. 128 See, for example, the natural conditions around the well-preserved shipwrecks in the Baltic Sea such as the Ghost Wreck or those in the Black Sea. 129 See Chapter 3 on mitigation against multiple threats.
Table 5. Postoperative complications.** RT+TME TME n=695 n=719 n % n % Infectious wound infection 43 6 45 6 abscess 31 5 20 3 haematoma 7 1 2 <1 sepsis/fever 63 9 50 7 other 2 <1 2 <1 Any infectious complication 120 17 105 15 General cardiac 36 5 22 3 # multi-organ failure 11 2 10 1 pulmonary 53 8 57 8 thrombo-embolism 11 2 12 2 line-sepsis 9 1 9 1 neurological 10 1 12 2 psychological disorders 28 4 10 1 * renal 4 1 6 1 other 25 4 23 3 Any general complication 000 00 00 00 # Surgical leakage (LAR) 49 11 56 12 perforation 8 1 7 1 intestinal necrosis 6 1 7 1 fistula 8 1 14 2 stoma complications 14 2 12 2 bleeding 23 3 29 4 abdominal dehiscence 16 2 25 4 perineal complications (APR) 61 29 39 18 diarrhoea 11 2 2 <1 # ileus 37 5 48 7 other 22 3 10 1 # Any surgical complication 209 30 191 27 Any complication 336 48 297 41 * # P<0.05 * P<0.01 ** The numbers and percentages of the separate complications do not summate "any complication" since some patients had more than one complication. They were registered for each separate complication, but for "any complication" they were counted as one.
Table 5. Ablation studies of the gradual sparsity increase schedule. The number of training epochs are 3, 5 and 5 for MNLI, QQP and FEVER respectively. The subnetworks are at 90% sparsity. The numbers in the subscripts are standard deviations. gradual soft MNLI HANS QQP PAWSqqp PAWSqqp FEVER Symm1 Symm2 fixed hard 72.090.92 72.630.31 52.560.92 52.820.47 fixed hard 71.641.85 77.080.66 55.701.92 46.483.55 49.591.84 49.380.98 fixed hard 49.565.09 72.800.95 27.452.94 46.670.73 29.754.40 52.330.75 0.2∼0.9 73.610.28 75.060.31 53.900.87 54.991.28 0.2∼0.9 75.790.39 77.540.47 51.570.69 50.920.97 47.940.98 48.860.89 0.2∼0.9 73.531.36 77.01 . 46.471.66 49.87 . 52.421.39 56.57 . 0.5∼0.9 gradual soft 0.5∼0.9 gradual soft 0.5∼0.9 0 43 0 95 0 22 0.7∼0.9 76.840.46 56.720.75 0.7∼0.9 79.490.58 46.591.81 51.150.73 0.7∼0.9 79.010.68 51.740.71 58.170.33 ∼ Table 6: Results of XxXXXXx-base and XXXX-large on the NLI task. We conduct mask training with XxX loss on the standard fine-tuned PLMs. “0.5 0.7" denotes gradual sparsity increase. The numbers in the subscripts are standard deviations. XxXXXXx-base MNLI XXXX full model std 87.140.21 68.330.88 xxx 86.560.18 76.151.35 0.5 85.400.14 75.170.55 XXXX-large MNLI HANS full model std 86.840.13 69.442.39 xxx 86.250.17 76.271.55 0.5 85.470.28 75.400.64 mask train 0.7 83.480.29 68.631.33 mask train 0.7 77.546.10 60.197.56 0.5∼0.7 84.410.15 71.951.23 0.5∼0.7 84.830.26 70.182.24
Table 5. Adjusteda Odds Ratios and 95% Confidence Intervals of Reported Non-typhoidal Salmonella Cases Hospitalized, 2014 – 2016, by test type Gender Male aOR (95% CI) Female aOR (95% CI) Test Type CIDT Culture CIDT Culture Age group (years) Less than 5 0.19 (0.14-0.25)c ref 0.31 (0.23-0.42)c ref 5-17b - - - 18-44 0.59 (0.34-1.02) ref 0.98 (0.55-1.72) ref 45-64 0.60 (0.31-1.14) ref 0.98 (0.53-1.81) ref 65 and above 0.31 (0.14-0.70)c ref 0.52 (0.23-1.17) ref a Multivariate logistic regression, adjusting for age groups listed in table and gender b No significant interaction or confounding effects observed in the age category 5-17 years. c Significant result in χ2-testing (p-value <0.05). Figures 2500 2234 2105 2153 2000 CIDT Culture 1500 1000 275 500 392 186 0 2014 2015 Year 2016 # of Salmonella Cases Figure 1. Number of Reported SendSS Salmonellosis Cases, by Year and Test Type, 2014 – 2016 1200 1030 1002 1014 1000 800 600 400 200 0 2014 2015 Year 2016 # of Hospitalized Salmonella Patients Figure 2. Number of Hospitalized SendSS Salmonella Patients, by Year an Test Type, 2014 – 2016 CIDT Culture 10 43 108 1200 1087 1025 1058 1000 CIDT Culture 800 600 400 270 200 159 31 0 2014 2015 Year 2016 # Salmonella Tests Figure 3. Number of Reported SendSS Salmonella Cases within Seven Days, by Year and Test Type, 2014 – 2016 Appendix A List of Counties in Metropolitan Statistical Area (MSA) Barrow, Bartow, Butts, Carroll, Cherokee, Clayton, Cobb, Coweta, Xxxxxx, Dekalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Haralson, Heard, Henry, Jasper, Lamar, Meriwether, Morgan, Newton, Paulding, Pickens, Pike, Rockdale, Xxxxxxxx, Xxxxxx Appendix B IRB Letters Emory GDPH Chapter III: Summary, Public Health Implications, Future Directions Methods used to detect enteric disease in the United States are changing at a rapid pace as technological advances create faster, cheaper, and more efficient diagnostic tests. Since 2011, Culture-independent diagnostic testing (CIDT) methods have become this new generation of tests and continue to increasingly be used to diagnose non-typhoidal Salmonella in Georgia. For our study we used FoodNet data from 2014 to 2016 to look for any demographic differences by and to assess the relationships of hospitalizations and timely reporting with testing methodology used to diagnose non-typhoidal Salmonella in Georgia. This study found that the number of positive CIDTs used to identify Salmonella nearly doubled from 2014 to 2016, while the number of cultures p...
Table 5. 1 Summary of pharmacy CI claims 2012 – 2016 Claim year No of pharmacies with claims Value of claims Volume of CIs received by patients Average claim amount per CI Average claim per participating pharmacy 2012 4,905 $26,204,044 2,013,377 $13.01 $5,342 2013 5,018 $12,426,350 3,764,365 $3.30 $2,476 2014 5,931 $20,003,906 3,514,910 $5.69 $3,373 2015 5,088 $19,640,278 4,477,088 $4.39 $3,860 2016 4,780 $4,926,953 1,449,043 $3.40 $1,031 Total 7,816 $83,201,530 15,218,783 $5.47 $10,645 Source: Claims payment data supplied in PPI Total Data Compilation_Copy.xls Table 5.1 shows that the volume of patient CIs received by patients has increased 122.4% from 2.0 million in 2012 to 4.5 million in 2015, matched to corresponding increase of 3.7% in the number of participating pharmacies, indicating that participating pharmacies have substantially increased their volumes. Note that the 2012 average claim rates are higher due to the inclusion of an introductory base rate of $150 in the claim formula in the first year. Between 2013 and 2015 Table 5.1 shows that the average amount earned by pharmacies per patient CI has increased by 33.0%, going from $3.30 in 2013 to $4.39 in 2015, the average total annual amount claimed by participating pharmacies has also increased from $2,476 to $3,860 (55.9% increase), which has been driven primarily by proportionally higher volumes. Table 5.2 deconstructs the same data by ABS remoteness. Pharmacies classified as Very Remote Australia have received disproportionately greater claims payments per patient CI than all of the other remoteness classifications (with an average of $5.97 in 2015). Remote Australia received the least per patient CI service supplied (with an average of $3.48). These variations are primarily a result of the inverse relationship between unit cost and the relative service volumes between regions. Table 5.2 Summary of pharmacy CI claims 2012 – 2016 by ABS Remoteness ABF Remoteness Claim year No of pharmacies with claims Value of claims Volume of CIs received by patients Average claim amount per CI Average claim per participating pharmacy Inner Regional Australia 2012 999 $5,044,504 349,065 $14.45 $5,050 2013 988 $2,200,353 551,757 $3.99 $2,227 2014 1,218 $4,016,831 606,589 $6.62 $3,298 2015 978 $4,017,911 772,869 $5.20 $4,108 2016 924 $1,007,312 243,443 $4.14 $1,090 Total 1,634 $16,286,912 2,523,723 $6.45 $9,968 Major Cities of Australia 2012 3,334 $18,567,671 1,480,857 $12.54 $5,569 9 Pharmacies are counted according to...
Table 5. Objective 2: To ensure that any use of waterbirds in the Agreement area is sustainable Progress Target Indicator Summary and reference 2.1: The use of lead shot for hunting in wetlands is phased out in all CPs All CPs have adopted national legislation prohibiting the use of lead shot (in wetlands) No authenticated report of continued use of lead shot for hunting in wetlands in the Agreement area is received by the Secretariat 24% of the Contracting Parties have fully phased out the use of lead shot with an additional 7% having introduced partial ban. Change since MOP5: Slightly negative. Although the proportion of CPs with full ban has been retained, only 7% report partial ban as opposed to 16% at MOP5. Reference: Analysis of AEWA National Reports for the triennium 2012- 2014 (document AEWA/MOP 6.13) 2.2: Internationally coordinated collection of harvest data is developed and implemented Internationally coordinated harvest data collection in place involving at least 25% of the CPs 41% of the Contracting Parties (CPs) have confirmed harvest data collection systems in place and for 13% of the CPs these systems cover all AEWA species, the whole territory of the country and all harvesting activities. However, the international coordination and synchronization of these national schemes is still lacking. Change since MOP5: Negative. 9% less countries confirmed harvest data collection systems in place and 18% CPs less countries reported comprehensive systems covering all species, the whole territory and all harvesting activities. Reference: Analysis of AEWA National Reports for the triennium 20012- 2014 (document AEWA/MOP 6.14) Progress Target Indicator Summary and reference 2.3: Measures to reduce, and as far as possible eliminate, illegal taking of waterbirds, the use of poison baits and non- selective methods of taking are developed and implemented All CPs have pertinent legislation in place which is being fully enforced 52% of the Contracting Parties (CPs) confirmed that measures are in place to reduce/eliminate illegal taking of waterbirds within their country, while only 20% of the CPs consider the effectiveness of these measures to be high. Only 34% of the CPs have indicated that all non-selective methods of taking, as listed in the AEWA Action Plan, including poison baits, have been prohibited. Change since MOP5: Negative (lowered category of progress – from good progress to limited progress). With sliding down proportions of CPs with pertinent and effect...
