zilongwang/ReadingBank huggingface dataset:
LC-12 <5 <5 < <50 <20 <200 <10 <200 <20 <20 < 55 < 65 < 825 < < 420 < 25 < 50 < < 20 LC-13 <5 <5 < <50 <20 <200 <10 <200 <20 <20 < 55 < 65 < 825 < < 420 < 25 < 50 < < 20 S2. (continued) Code Ʃ syn-DP anti-DP 4- BP 24- DBP 26- DBP TBBPS Cheese (CHC) and dairy products (DC) DC-01 <20 <20 < 55 < 65 < 825 < 420 < < < < DC-C-01 < <20 <20 < 55 373 < 825 < 420 < < < < DC-C-02 < <20 <20 < 55 < 65 < 825 < < 420 < < < < CHC-01 <20 <20 < 770 < 100 < 2 ng/g < 800 < < < 5 < CHC-02 <20 <20 < 770 < 100 < 2 ng/g < 800 < < < 5 < CHC-03 < <20 <20 < 770 < 100 < 2 ng/g < < 800 < < < < CHC-04 <20 <20 < 770 < 100 < 2 ng/g < < 800 < < < < CHC-05 6 <20 <20 < 770 < 100 < 2 ng/g < < 800 < < < < 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
6 6 58 FC-16 1350 <20 <20 569 < 15 < 500 < 210 < 6 < < 7 < FC-17 349 <20 <20 933 < 45 < 585 < 4 < 500 < 4 < < FC-18 14 <20 <20 164 < 45 < 585 9 < 500 < 4 < < < FC-19 39 <20 <20 490 < 15 < 500 < 6 < 210 < 6 < < 7 < FC-20 187 <20 <20 < 250 28 < 500 < 210 < 6 < 7 < FC-21 83 <20 <20 < 250 < 15 < 500 < 210 < 6 < < 7 < FC-23 431 <20 <20 1038 < 75 < 950 < 210 < < 7 < FC-25 2630 <20 <20 913 83 < 500 < 210 < 6 < < 7 < FC-26 91 <20 <20 < 200 2960 < 1600 < 5 < 210 < < < < FC-28 2542 <20 <20 4019 < 15 < 500 < 210 < 6 < < 7 < FC-32 595 <20 <20 < 200 < 120 < 1600 < 5 < 210 < < < < FC-33 12 <20 <20 < 75 < 45 < 585 < 500 < 4 < < < FC-34 160 <20 <20 < 200 < 120 < 1600 < < 210 < < < FC-35 < LOQ <20 <20 < 75 < 45 < 585 < < 500 < < < <
Code Ʃ syn-DP anti-DP 4- BP 26- DBP Meat (MEC) MEC-01 < LOQ <10 <20 <20 < 215 < < 825 < < < < < < MEC-02 422 <10 <20 <20 < 215 < < 825 < < < < < < MEC-03 <10 <20 <20 < 215 < < 825 < < < < MEC-04 9171 <10 <20 <20 < 215 < < 825 < < < < < MEC-05 9 9 <10 <20 <20 < 215 < < 825 < < < < < < MEC-06 6 6 <10 <20 <20 < 215 < < 825 < < < < < < MEC-07 900 <10 <20 <20 < 215 < < 825 < < < < < MEC-08 23 <10 <20 <20 < 215 < < 825 < < < < < < MEC-09 948 <10 <20 <20 387 < < 825 < < < < < MEC-10 347 <10 <20 <20 < 215 < < 825 < < < < < < MEC-11 < LOQ <10 <20 <20 710 < < 825 < < < < < < MEC-12 501 <10 <20 <20 < 215 < < 825 < < < < < MEC-13 90 <10 <20 <20 < 215 < < 825 < < < < < <
≥400 ng/ml (n = 40) 5 2 <400 ng/ml (n = 101) 7 9 Differentiation <0.001 0.352 Well (n = 27) 0 0 Moderately (n = 109) 4 10 Poorly (n = 26) 12 2 vp/im 0.001 0.352 + (n = 92) 15 9 – (n = 70) 1 3 Etiology NA NA Alcoholic (n = 5) 0 0 HBV (n = 42) 9 4 HCV (n = 69) 6 6 NASH (n = 6) 0 0 Others (n = 40) 1 2 METAVIR score 0.528 0.252 0–2 (n = 93) 8 5 3–4 (n = 69) 8 7 Ki67 index <0.001 a 0.602 ≥30% (n = 14) 11 0 <30% (n = 148) 5 12 Mitotic counts <0.001 1.000 ≥10/10 HPF (n = 5) 5 0 <10/10 HPF (n = 157) 11 12 Pearson’s chi-squared test and a Fisher’s exact test. NA, not assessed. Supplementary Table 4. Association of clinicopathological features with p53-only-positive cases and all-negative cases the in –/– group. All-negative cases p53-only-positive cases n p value n p value AFP <0.001 0.354 a ≥400 ng/ml (n = 21) 3 2 <400 ng/ml (n = 133) 78 7 PIVKA-II 0.456 0.273 a ≥400 ng/ml (n = 40) 21 4 <400 ng/ml (n = 101) 45 5 Differentiation <0.001 0.401 a Well (n = 27) 25 0 Moderately (n = 109) 57 7 Poorly (n = 26) 5 2 vp/im <0.001 0.733 a + (n = 92) 38 6 – (n = 70) 49 3 Etiology NA NA Alcoholic (n = 5) 2 0 HBV (n = 42) 18 4 HCV (n = 69) 34 3 NASH (n = 6) 4 1
S3 Recoveries of 13C10-labeled standards for PCNs Surrogate standard Recovery of surrogate standard Mean 13C10-CN-27 60.8-121% 93.7% 13C10-CN-42 56.1-131% 90.5% 13C10-CN-52 44.2-118% 72.0% 37.2-98.8% 55.5% 13C10-CN-73 48.2-125% 82.1% 13C10-CN-75 36.0-129% 67.1%
tri-CNs 0.234 0.682** tetra-CNs -0.119 0.271 0.572** penta-CNs -0.037 0.461* 0.539** 0.746** hexa-CNs -0.251 0.232 0.198 0.569** 0.764** hepta-CNs -0.062 0.130 0.002 0.282 0.416* 0.598** octa-CN -0.006 0.114 0.088 0.204 0.430* 0.399* 0.392* PCNs 0.383* 0.839** 0.840** 0.549** 0.658** 0.446* 0.355 0.273 TOC -0.508** -0.286 -0.257 0.051 0.105 0.087 -0.060 0.117 -0.343 Serving populationa 0.006 0.163 0.382 -0.057 -0.231 -0.242 -0.329 -0.615** 0.153 Treatment volume of industrial effluent b 0.135 0.307 0.284 0.291 0.204 0.131 0.169 -0.124 0.432 * P < 0.05; ** P < 0.01. an=24. b treatment volume of industrial effluent = % ind effluent × Treatment volume, n=21.
Table S2 – Operational characteristics of the electrospray ionization Ion Trap-Mass Spectrometer (ESI-IT-MSn). Mode Tune Source Trap MS/MS Automatic Mass Mode Std/Normal Trap Drive 46.8 Scan Begin 50 m/z Precursor Ions AutoMS(2) 4 Ion Polarity Positive Octopole RF Amplitude 266.7 Vpp Scan End 300 m/z Precursor Ions AutoMS(>2) 1 Ion Source Type ESI Lens 2 -58.0 V Averages 4 Spectra MS(n) Averages 5 Spectra Capillary Exit 108.3 V Accumulation Time 200000 s Depth AutoMS(>2) 3 Dry Temp. 350 °C (Smart) ICC Target 40000 Auto MS/MS On Nebulizer 30.00 psi ICC On Group Length 5 Dry Gas 12.00 L/min abs. Threshold Auto MS(2) 10000 HV Capillary 4080 V rel. Threshold Auto MS(2) 5.0% HV End Plate Offset 500 V abs. Threshold Auto MS(>2) 1000 Skimmer 33.4 V rel. Threshold Auto MS(>2) 5.0% octopole one 10.71 V octopole two 2.24 V
Table S3 – Operational characteristics of the heated electrospray ionization High resolution Orbitrap Mass Spectrometer (H-ESI-HRMS/MS). Tune File Values Negative polarity Scan Event Details Source Type HESI Source Voltage (kV) 3.00 1: FTMS - c norm res=30000 50.0-300.0 Capillary Temp (C) 300.00 Source Current (A) 100.00 Activation Type CID APCI Vaporizer Temp (C) 200.00 Capillary Voltage (V) -9.50 Min. Signal Required 5.0 Sheath Gas Flow 50.00 Tube Lens (V) -35.00 Isolation Width 2.00 Aux Gas Flow 5.00 Multipole RF Amplifier (Vp-p) 770.00 Normalized Coll. Energy 20.0 Ion Trap Zoom AGC Target 1000.00 Multipole 00 Offset (V) 4.00 Default Charge State 1 Ion Trap Full AGC Target Lens 0 Voltage (V) 4.20 Activation Q 0.500 Ion Trap SIM AGC Target 5000.00 Multipole 0 Offset (V) 4.50 Activation Time 30.000 Ion Trap MSn AGC Target 5000.00 Lens 1 Voltage (V) 15.00 FTMS Full AGC Target 200000.00 Gate Lens Offset (V) 35.00 FTMS SIM AGC Target 10000.00 Multipole 1 Offset (V) 8.00 FTMS MSn AGC Target 100000.00 Lens (V) 5.25
Fig. S7 – Consumption of ferric and ferrous ions during the UV/Fe2+/H2O2. Fig. S8 Fig. S8 – Consumption of H2O2 during the photo-Fenton treatment Fig. S9 Fig. S9 – Effect of catalyst loading on the mineralization rates of 5-Fluorouracil. (Concentration of 5-FU 20 mg/L), n = 3
Table S1. Predictors used in Cubist models; see Viscarra Rossel et al. (2015) for source references. Theme Name of surrogate variable Description Environmental factor Source Soil and parent material Kaolinite, Illite, Smectite Clay mineral abundances soil, lithology, relief, climate Viscarra Rossel (2011) PC1, PC2, PC3 First three principal components of vis--NIR spectra representing soil organic and mineral composition: PC1 represents soil with abundant haematite PC2 represents soil rich in organic matter PC3 represents soil with abundant smectite, illite and goethite soil, relief, climate Viscarra Rossel and Chen (2011) dose, K, U and Th Gamma radiometrics dose and concentrations in % and mg kg-1, respectively soil, lithology Minty et al. (2009) Magnetics Magnetic anomalies in nanoTesla (nT) units soil, lithology Milligan et al. (2004) Gravity Bouguer gravity anomaly, Gal soil, lithology GA (2009) Climate Rainfall Average annual rainfall, mm climate, relief, biota, soil Xu and Hutchinson (2011) Minimum temperature Average annual minimum temperature / climate, relief, biota, soil Maximum temperature Average annual maximum temperature/ climate, relief, biota, soil Potential evapotranspiration Mean annual evapotranspiration/mm climate, relief, biota, soil Solar radiation Mean annual solar radiation in J m-2 year-1 climate, biota, relief, soil Prescott Prescott index climate, relief, soil, biota Prescott (1950)
Table N: This table details the criteria we used in our judgemental parameter assessment. A spectrum of information types are listed and the factors controlling their reliability are scored out of three. Information type Assessment indicator Physical law Score Controlled experiments Uncontrolled experiments Statistical information Predictive models Expert/stakeholder knowledge Modeller intuition A Transferability of location N/A 3 Within area Within area Within study area model Specialises in study area Specialises in study area 2 Comparable environment Comparable environment Comparable environment Regional model Specialises in comparable environments Specialises in comparable environments 1 Poorly comparable environment Poorly comparable environment Poorly comparable environment Global Specialises in the field only Specialises in the only B Transferability of spatial scale N/A 3 Study scale scale Study scale Study scale N/A N/A 2 Similar Similar scale Similar scale Similar scale 1 Incomparable scale Incomparable scale Incomparable scale Incomparable scale C Quantity of evidence/studies N/A 3 High number of experiments High number of experiments High number of surveys High number of models Comprehensive sample N/A 2 Multiple experiments Multiple experiments Multiple surveys Multiple models Representative sample frame 1 Single experiment Single experiment Single survey Single model Selective sample frame D Statistical confidence N/A 3 P < 0.001 P < 0.001 P < 0.001 P < 0.001 N/A N/A 2 P < 0.05 P < 0.05 P < 0.05 P < 0.05 1 P-value not provided P-value not provided P-value not provided P-value not provided
S8 ds Released 50 0 37 13 21 14 23 7 18 9 12 7 Recaptured 7 (14) n.a. 7 (18.9) 2 (15.3) 4 (19) 3 (21.4) 5 (21.7) 1 (14.2) 4 (22.2) 2 (22.2) 2 (16.6) 1 (14.2) S8 us Released 131 6 98 6 79 12 20 4 13 7 7 6 Recaptured 28 (21.3) 1 (16.6) 19 (19.3) 1 (16.6) 16 (20.2) 2 (16.6) 4 (20) 1 (25) 3 (23) 1 (14.2) 1 (14.2) 1 (16.6) Supplementary table 4: Numbers of VIE tagged brown trout (bt) and bullhead (bh) released per date and recaptured at least once (with recapture percentages in parentheses) per site (immediately downstream (ds) and upstream (us) of each structure). Data of the final survey in each CMR year is not listed, because no new fish were tagged in that survey.
Supplemental 1. Chromium, copper, manganese, nickel, antimony and vanadium leached per 250 mL serving based on a two-hour simulated cooking extraction with 4% acetic acid. (Note: Repeated boil tests are numbered 1-3) Country of origin Item Boil Cr µg/serving Cu µg/serving Mn µg/serving Ni µg/serving Sb µg/serving V µg/serving Bangladesh A 1 1 11 18 37 ND 2 B 1 111 35 543 12 10 20 2 155 180 789 9 14 31 3 114 41 549 11 10 23 C 1 88 66 499 21 11 15 2 68 55 381 17 7 13 3 90 86 491 23 10 20 D 1 63 31 507 33 7.3 15 2 59 56 491 12 7.0 16 3 74 44 615 18 8.4 20 Guatemala A 1 128 125 486 37 14 24 B 1 107 225 347 22 9 16 C 1 69 31 363 7 13 13 D 1 77 112 310 31 9 14 India A 1 1 2 5 1 3 2 B 1 7 2 371 1 ND 8 C 1 18 5 43 3 4 4 Indonesia A 1 3 4 13 21 ND 14 B 1 59 20 998 14 14 18 2 45 21 806 42 12 14 3 74 119 276 8 10 15 C 1 35 4 331 2 7 16 Ivory Coast A 1 44 28 208 7 11 6 2 46 38 194 9 6 7 3 102 548 652 44 15 32 B 1 14 15 565 5 9 6 2 23 89 878 11 3 11 3 26 83 915 11 6 14 C 1 1 11 314 2 7 6 D 1 13 6 89 2 17 6 Kenya A 1 21 ND 74 5 8 8 B 1 6 2 22 2 4 5 C 1 1 1 16 0.4 4 4 D 1 30 88 384 12 6 12
Country of origin Item Boil Cr µg/serving Cu µg/serving Mn µg/serving Ni µg/serving Sb µg/serving V µg/serving Nepal A 1 6 3 56 3 4 6 B 1 6 2 36 2 5 7 C 1 7 21 28 2 5 5 D 1 5 5 43 1 ND 6 2 6 9 57 3 2 4 3 7 16 88 3 3 4 E 1 48 17 79 3 7 5 Philippines A 1 56 8 317 8 13 13 2 107 1267 724 68 21 31 3 1 8 7 2 4 2 B 1 42 49 132 6 8 14 C 1 174 80 179 13 15 20 D 1 72 499 299 18 4 24 2 74 511 330 22 9 21 3 117 458 388 20 12 26 E 1 99 263 338 8 ND 23 2 106 218 359 20 9 20 3 40 35 721 44 13 14 4 142 429 481 13 10 31 5 147 1032 485 12 14 34 Tanzania A 1 4 4 65 2 3 3 2 6 13 85 4 ND 3 3 73 670 318 27 13 25 B 1 12 7 84 2 5 3 2 21 6 157 3 3 4 3 21 7 153 3 2 3 C 1 8 5 55 1 5 5 Viet Nam A 1 ND ND ND ND ND ND B 1 22 4 197 2 3 9 C 1 5 6 29 65 ND 1 2 9 ND 297 14 3 5 3 11 8 446 6 4 6 D 1 4 13 111 46 4 5 2 44 17 1017 9 8 21 3 58 8 1420 13 11 27 E 1 14 1 175 3 5 12 2 15 7 430 4 3 6 3 20 26 564 4 4 9 F 1 6 2 181 1 3 4 G 1 16 7 339 2 5 9 ND = Not detected; below ICP detection limit. MQLs were 1.0, 2.0, 1.0, 1.0, 9.0 and 3.0 µg/L for Cr, Cu, Mn, Ni, Sb and V respectively.
Table S1 Questionnaire of household coal consumption ____Province, _____City, _____county/district __________________village/street Date information of Household ______person(s) area ______m2 area ______ m2 of Coal stove ______ ①Honeycomb briquette stove ②other briquette stove ③Anthracite raw coal stove ④Bituminous raw coal stove ⑤Other of purchase coal ______ ①go to mine individual dealer ③POS of government ④Other period yy__mm__dd information Longitude____________ Latitude____________ of building floor and amount of coal consumption Types: ①Honeycomb briquette coal ②Other briquette coal ③Anthracite raw coal ④Bituminous raw coal ⑤Semi-coke 1. Purpose 2.Type of 3.Annual 4.Changes in the past five Cooking Heating Other Table S2 Summary of air pollutants emission factors for different types of
Table 9S Incremental lifetime cancer risks (ILR) at five fire stations (Vimioso (VMS), Macedo de Cavaleiros (MCC), Izeda (IZD), Vila Flor (VFR), Alfândega da Fé (AFF)) Corporation Nap B[a]A Chry B[b]F B[k]F B[a]P D[a,h]A InP VMS 8.7×10–8 1.49×10–9 9.49×10–11 1.72×10–8 1.60×10–9 3.54×10–8 3.56×10–8 1.21×10–9 MCC 4.84×10–9 3.13×10–10 2.98×10–11 1.29×10–9 2.04×10–10 4.22×10–9 8.30×10–9 2.82×10–10 IZD 2.25×10–8 8.53×10–10 1.70×10–10 3.45×10–9 5.81×10–10 1.04×10–8 2.05×10–8 6.98×10–10 VFR 1.38×10–8 3.86×10–10 4.48×10–11 5.81×10–9 7.98×10–10 3.21×10–8 1.16×10–7 4.29×10–9 AFF 2.44×10–8 1.27×10–9 3.74×10–10 6.41×10–9 1.12×10–9 3.45×10–8 6.37×10–8 1.68×10–9 Note: naphthalene – Nap; benz[a]anthracene – B[a]A; chrysene – Chry; benzo[b]fluoranthene –B[b]F; benzo[k]fluoranthene – B[k]F; benzo[a]pyrene – B[a]P; dibenz[a,h]anthracene – D[a,h]A; indeno[1,2,3–cd]pyrene – InP;
Where X is the net growth of biomass (gCODX) and S is the amount of removed substrate (gCODS) during the biological test. S is by the mass balance between time 0 and the final time, as follows: S = Sfed - Stub -Spol -Seff - Sbio where the following symbols indicate the amount of DMP fed to the bioreactor during the biological test (Sfed); in the liquid inside the tubing at the end of the testStub); sorbed by the polymer, measured by solvent extraction at the end of the test (Spol); in the effluent collected by the tubing from the beginning to the end of the test (Seff); in the liquid phase of the bioreactor at the end of the test (Sbio). while X has been calculated as follows X = Vr [Xf – X0] -Vr ∙b ∙t ∙ Xa where: Vr is the reactor volume; Xf is the final biomass concentration; X0 is the final biomass concentration; Xa is the average concentration of biomass referred to t; b is the endogenous coefficient; t is the test duration time.
Table S1: Socio-demographic characteristics of studied populations Location Carrasqueira VNMF p-value n % n % Sex 102 100 0.049 Male 57.8 44.0 Female 42.2 56.0 Age group (years) 102 100 0.267 ≤17 14.7 14.0 18- 44 29.4 26.0 45-64 40.2 33.0 65- 74 9.8 12.0 ≥75 5.9 15.0 Education level 99 94 <0.001 No formal education 14.1 11.7 Primary and lower secondary education 69.7 42.6 secondary education 10.1 21.3 Post - secondary or higher education 6.1 24.5 Labour status 98 94 <0.001 Self employed 38.8 11.7 Employee 23.5 34.0 Fulfilling domestic tasks 5.1 5.3 Retired 14.3 25.5 Unemployed 4.1 11.7 Student 14.3 11.7 Table S2. Occupational exposure: distribution of both participants by route of exposure (direct, indirect, another via or without relevant exhibition) related to the main occupation. Location Carrasqueira (exposed) VNMF (unexposed) p-value n % n % Direct exposure 80 48.8 84 1.2 <0.001 Indirect exposure 80 30 84 11.9 0.004
Table A.2. The range and median values of OR for each of 16 global biomes. The area of each biome is given to 4 significant figures. 1 = Hockaday et al. (); 2 = Masiello et al. (); 3 = Kuz’menio & Pavlova (); 4 = Baldock et al. (); 5 = Clay and Worrall (); 6 = Clay and Worrall (); 7 = Worrall et al. (); and 8 = this study. Global biome Study Number of samples Range of OR Area (km2) Evergreen forest 1,2,5 4 1.03 – 1.08 18 710 000 Deciduous forest 46 1.03 – 1.11 5 690 000 Croplands 26 1.00 – 1.10 13 790 000 Woody savanna 2,6 6 1.04 – 1.11 7 564 000 Grasslands 142 0.93 – 1.10 11 230 000 Mixed forest 20 1.05 – 1.12 7 256 000 Cropland/Natural mosaic 4 5 1.02 – 1.08 14 620 000 Closed shrublands 5 12 1.04 – 1.13 23 150 000 Open shrublands 8 10 1.08 – 1.15 19 490 000 Savannas 6 2 1.06 – 1.12 9 168 000 Permanent wetlands 5,8 48 0.96 – 1.14 1 331 000 Urban 269 000 Snow/ice 16 570 000 Barren 17 730 000 Unclassified 78 740 Total 321
CANNABINOIDS JWH-018 JWH-01817 C24H23NO 341.44552 (A) 341.177964 (M) 209414-07-3 6.51 --- Tetrahidrocannabinol C21H30O2 314.4617 (A) 314.224580204 (M) 1972-08-3 5.65 10.6 THC-d3 C21H27D3O2 11-Nor-9-carboxy-Δ9-tetrahidrocannabinol THC-COOH18 C21H28O4 344.44462 (A) 344.198759 (M) 104874-50-2 5.14 9.3 THC-COOH-d3 C21H25D3O4
Topological indices TIE E-state topological parameter Drug-like indices LLS_02 modified lead-like from Monge et al. (8 rules) 4S. Correlation matrix for the best QSAR model established. Eq. 1 1 0.154 0.243 0.034 0.413 1 0.101 0.389 0.184 1 0.514 0.122 1 0.027 1
= 50 (data from UKWIR 2014). 4 Propanolol atenolol Blood pressure lowering Low removal, CIP1 PNEC applied = 0.1 µg/L (astrazeneca.com and et al. (2011). PNEC applied = 148 µg/L (astrazeneca.com and et al. (2011). 5 amoxicillin Penicillin-like (β lactam) antibiotic expected to be unstable - considered but NOT forward 6 erythromycin, norerythromycin azithromycin - low usage clarithromycin - higher usage “Macrolide”antibiotics Low removal noted in CIP1 PNEC applied = 0.2 µg/L (JRC 2016). Low usage high toxicity PNEC applied = 0.09 µg/L (JRC 2016). Higher usage moderate toxicity PNEC applied = 0.13 µg/L (JRC 2016). 7 ciprofloxacin Antibiotic High usage
PNEC applied = 0.089 µg/L (JRC 2016). 8 metformin Anti diabetic Very high usage PNEC applied = 13.45 µg/L; Daphnia acute EC50 of 1345 µg/L / AF = 100 (data from UKWIR 2014). 9 ranitidine Anti indigestion proton pump inhibitor Over counter, high usage PNEC applied = 0.31 µg/L; Daphnia acute EC50 of 310 µg/L / AF = 1000 (data from UKWIR 2014). 10 carbamazepine 10,11- epoxycarbamazepine Mood stabilising anticonvulsant Established EU concern PNEC applied = 2.5 µg/L; Daphnia chronic EC10 of 25 µg/L / AF = 10 (data from 2014). 11 sertraline / norsertraline SSRI antidepressant Sludge risk PNEC applied = 0.121 µg/L; Algal acute EC50 of 12.1 µg/L / AF = 100 (data from UKWIR 2014). 12 fluoxetine Antidepressant Low removal Established concern in CIP1 PNEC applied = 0.047 µg/L; Snail chronic NOEC of 0.47
Interest on fixed capital (without property) 3,530,477.50 0.07 247,133.43 € Appendix D.2: Economic (Impact) Analysis input for a planned aquaculture with blue mussel in Germany. Details specified as followed: 1 Investment on equipment (per cage/trestle/longline); 2 Other investments (excl. Equipment, land facilities and properties); 3 Investment on land facilities; 4 Investment on properties; 5 Market value culture species per ton; 6 Average no. of days at sea/culture site; 7 Average fuel costs Euro/km; 8 Annual expenditure on wages/salaries; 9 Intermediate costs variable (e.g. juveniles/seeds/food); 10 Other costs (variable); 11 Annual rate on capital resources (%); 12 Intermediate costs fixed (e.g. insurance/maintenance and repair ship); 13 Other costs (fixed). Aquaculture-specific information modified from Ebeling (2016). Interest rates for Germany taken from IMF (2017). Description Unit Quantity Price/Unit Total value Production cycle 1 Production density tons/m³ or ha 0.005 Cage size/area m³/ha 1675 Production quantity tons 40000 Distance (example) km 31.484 Number quantity 4777 Investment cages/longlines1 Euro 6,947.9 33,190,118.3 € Other investments2 Euro 4,000,000 4,000,000 € Costs/land facilities3 Euro 1,500,000 1,500,000 € Costs/property4 Euro 200,000 200,000 € Fuel (0.55 Euro/litre; 4.58 Euro/km)6,7 days at sea/y 85 24,513.44 24,513.44 € fuel costs Euro/km 4.58 Wages8 Euro 199,980 199,980 € Intermediate costs (e.g. juveniles/seeds/food)9 Euro/ton 0 0 € Other costs (variable)10 Euro 119,271 119,271 € Interest on operating capital (in %)11 % 343,764.44 0.07 24,063.51 €
Intermediate costs (e.g. insurance/maintenance and repair ship)12 Euro 78,257 78,257 € Other costs (fixed)13 Euro 7,964,971.99 7,964,971.99 € Interest on property 200,000 0.07 14,000 € Interest on fixed capital (without property) 8,043,228.99 0.07 563,026.03 €
A meeting of the Trust Board of Directors – Part 1 To be held on Tuesday, 19th December 2017 at 9.00 am – 1.00 pm in the Main Boardroom at Diana Princess of Wales Hospital Walkabout - 1.00 pm – 1.30 pm For the purpose of transacting the business set out below Board Briefing – Health & Safety Update – Bill Parkinson 1.45pm – 2.30pm 1 Business Items 1.1 Chair’s Opening Remarks & Star of the Month Award Anne Shaw, Verbal 1.2 Apologies for Absence Anne Shaw, Chair Verbal 1.3 Declarations of Interest Anne Shaw, Chair Verbal 1.4 To approve the minutes of the previous public meeting held on 28 November 2017 Anne Shaw, Chair NLG(17)475 1.5 Matters Arising Anne Shaw, Chair 1.5.1 Update on BAF Wendy Booth, Director of Governance & Assurance & Trust Secretary 1.5.2 Confirmation of the Maternity Improvement Director Tara Filby, Chief Nurse Verbal Verbal Verbal 40 mins 1.6 Trust Board Action Log – Public Anne Shaw, Chair NLG(17)476 1.7 Freedom to Speak Up Guardian’s Quarterly Report Dr Makani Hemadri NLG(17)477 1.8 Proposed changes to meeting structure NLG(17)479 Wendy Booth, Director of Governance & Assurance & Trust Secretary 1.9 NED Roles:Attachment to Divisions Verbal Anne Shaw, Trust Chair & Wendy Booth, Director of Governance & Assurance & Trust Secretary 1.10 Chief Executive’s Briefing Reading, Chief Executive NLG(17)481 10 mins 2 Quality & Safety 2.1 Patient’s Story & Reflection Jo Loughborough 2.2 Patient Experience Moving Forward Jo Loughborough Verbal A - NLG(17)482 10 mins 5 mins 2.3 Quality Special Measures Progress Report: 2.3.1 Integrated Performance Report – Quality & Safety NLG(17)483
Table B: EC50 values of ACP treated water effluents for acute daphnia toxicity test Treatment sample ACP treatment time (min) Period of exposure (h) EC50 (% v/v) Meat effluent 5 24 9.78 48 7.58 10 24 6.06 48 5.10 Dairy effluent 5 24 9.81 48 9.50 10 24 5.26 48 5.26
Table S1 Additional information on the four watersheds studied (). Adapted from Cho et al., 2014. River Length of main stream (km) Number of tributaries Total stream length (km) Watershed area (km2) population Daily discharge of wastewater (kg/day) Nakdong 470.0 1,185 9,637.6 31,785.0 14,431,507 1,363,452.72 Yeongsan 117.7 576 3,540.4 12,833.4 3,800,240 235,607.66 Geum 393.1 876 6,134.9 17,537.0 5,721,207 692,017.98 Han 560.0 912 8,567.7 41,957.0 23,404,251 1,089,801.92 Table S2 Geographic coordinates and brief notes on some qualitative characteristics of the 16 study sites. River basins Sites Abb. GPS locations Characteristics Nakdong Ayang1 N1 N 35°53′20″ E 128°381′18.4″ had a bad smell with high amount of suspended matters which mainly come from the sewage treatment plant that is located in close proximity. Study area
heavy and leather industries with large inputs of urban wastes. Yeongsan PD-1 Y1 N 35° 07' 54.3'' E 126° 44' 70.9'' The collected water was found to be turbid with red clay. PD-2 Y2 N 35° 07' 54.3'' E 126° 44' 70.9'' The collected water was found to be turbid with red clay. Gwangju-1 Y3 N 35° 09' 86.1'' E 126° 49' 25.4'' Water flow rate was very slow at this site due to the presence of a dam. This site was contaminated with organic compounds in the water and sediment fractions. Gw.gong dam Y4 N 35° 09' 33.8'' E 126° 50' 14.7'' The water at this site had high turbidity but did not have
a bad smell. The sediments were found to be contaminated with organic compounds. Restoration actions were undertaken at this site. Gwangju Y5 N 35° 09' 33.8'' E 126° 50' 14.7'' The water at this site had high turbidity but did not have a bad smell. The sediments were found to be contaminated with organic compounds. Restoration actions were undertaken at this site. GJ-2 Y6 N 35° 10' 11.5'' E 126° 51' 74.4'' Visually, the water and sediment appearance
Inpatient days 2.3 4.1 4.1 3.3 2.1 2.9 4.1 Sick leave days 126.6 126.2 126.3 121.3 116.1 114.6 108.5 92.9 All cohorts (n) 830 857 885 917 949 974 991 1008 Specialist physician visits 6.5 7.1 7.5 7.0 6.1 6.4 6.1 6.0 Inpatient days 3.3 3.2 3.2 3.5 3.4 3.6 3.1 Sick leave days, all Sick days,<66 years (n) 129.8 148.4 (726) 127.9 147.0 (746) 126.5 146.9 (762) 123.0 144.8 (779) 116.4 139.1 (794) 114.0 139.1 (798) 107.3 133.6 (796) 95.1 123.3 (777) a For 2003 the number of inpatient days was not complete
Other mineral supplements (A12C) 10 4.3 2.35 (1.12-4.32) Iron preparations (B03A) 85 34 2.48 (1.98-3.07) Anti-inflammatory and anti-rheumatic products (M01) 254 203 1.25 (1.10-1.42) Anti-inflammatory and anti-rheumatic products, NSAIDS (M01A) 254 203 1.25 (1.10-1.42) Acetic acid and derivatives and related substances (M01AB) 127 112 1.13 (0.95-1.35) Diclofenac (M01AB05) 124 105 1.18 (0.98-1.41) Propionic acid derivatives (M01AE) 94 75 1.25 (1.01-1.53) Ibuprofen (M01AE01) 30 31 0.98 (0.66-1.40) Naproxen (M01AE02) 46 33 1.40 (1.03-1.87) Ketoprofen (M01AE03) 14 10 1.36 (0.74-2.29) Coxibs (M01AH) 18 11 1.58 (0.94-2.50) Etoricoxib (M01AH05) 14 8.2 1.71 (0.93-2.87) Other anti-inflammatory and anti-rheumatic agents, (M01AX) 46 28 1.65 (1.21-2.20) Glucosamine (M01AX05) 37 23 1.57 (1.11-2.17) Topical products for joint and muscular pain (M02) 35 23 1.55 (1.08-2.15) Topical products for joint and muscular pain (M02A) 35 23 1.55 (1.08-2.15) Anti-inflammatory preparations, non-steroids for topical use (M02AA) 35 23 1.55 (1.08-2.15)
A meeting of the Board of Directors, in Public – Part B To be held on Tuesday, 25 July 2017 at 2.00pm in the Boardroom at the Scunthorpe General Hospital For the purpose of transacting the business set out below Business Items 1. Chairs Opening Remarks Apologies for Absence Anne Shaw Verbal 2 mins 2. Declarations of Interest Anne Shaw Verbal 1 min 3. Patient’s Story and Reflection Jo Loughborough Verbal 10 mins 4. To approve the minutes of the previous Public Meeting held on 30th May 2017 Anne Shaw A - NLG(17)303 3 mins 5. Trust Board Action Log - Public Anne Shaw A - NLG(17)304 3 mins 6. Chief Executives Briefing to include Improving Clinical Engagement Paper Richard Sunley NLG(17)305 NLG(17)306 5 mins 3 mins 7. Quality, Safety & Performance 7.1 Board Assurance Framework 7.1a Risk Register Quarterly Report 7.2 Improving Together Update 7.3 Integrated Performance Report 7.3.1 Performance & Access 7.3.2 Quality & Safety including:- 7.3.2.1 Monthly Capacity & Capability on our Wards 7.3.2.2 Quality Matron Environment Report – Q1 7.3.3 Finance Report Q1 7.3.4 Workforce 7.3.4.1 Listening into Action Wendy Booth Wendy Booth Wendy Booth Pam Clipson Claire Phillips Tara Filby Tara Filby Tara Filby Marcus Hassall Jayne Adamson Kar Farquaharson NLG(17)307 NLG(17)308 NLG(17)309 A - NLG(17)310 A - NLG(17)311 A - NLG(17)312 Presentation 15 mins 5 mins 5 mins 5 mins 5 mins 5 mins 5 mins 5 mins 10 mins 8. Trust Board Sub-Committee Highlight Report & Board Challenge 8.1 Workforce Sustainability & Transformation 8.2 Finance, Information & Performance 8.3 QSPEC Highlight Report 8.4 MACIC Highlight Report, July 2017 Sandra Hills Tony Bramley Tony Bramley Sue Cousland Verbal NLG(17)316 NLG(17)317 NLG(17)318 5 mins 5 mins 5 mins 5 mins
Available trials are often small or underpowered, and recruitment is challenging Leverage collaborations between existing national CKD trial networks to facilitate multinational trials Partner with to conduct a multinational investigator-initiated clinical trial on common interventions such as bicarbonate, uric acid reduction, ACEi/ARB or phosphate binder therapies Clinical Trials (ISN- ACT), ASN Kidney Health Initiative, French CKD clinical trials network and others Little is known about how to manage symptoms of CKD G4+, which is a key treatment objective for patients Do more studies of symptom management Create a toolbox of validated instruments for common CKD G4+ symptoms that can be used in trials or in supporting studies KDIGO* * Although KDIGO could act as a catalyst to establish these initiatives, they will likely require the creation of a dedicated organization or structure to ensure sustainability. ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; CKD, chronic kidney disease; KDIGO, Kidney Disease: Improving Global Outcomes; ISN, International Society of Nephrology, ASN, American Society of Nephrology.
Battle of the List B Title Author Picture The Polar Bear’s Home: A Story About Global Warming Lara Berger My Senator and Me Edward Kennedy Magic School Bus: At the Waterworks Joanna Cole Bear Alert David Biedrzycki Young Cam Jansen and the Lost Tooth David Adler Ivy & Bean Annie Barrows Chocolate Fever Robert Kimmel Smith Ganesha’s Sweet Tooth Emily Haynes Second Grade Rules, Amber Brown Paula Danzinger Nate the Great and the Mushy Valentine Marjorie Sharmat Aliens are Coming! The True Account of the 1938 War of the World Radio Broadcast Meghan McCarthy Knuffle Bunny Free Mo Williams Clara and the Book Wagon Nancy Levinson Each Kindness Jacqueline Woodson
Baseball Us Ken Mochizuki Frog and Toad are Friends Arnold Lobel Mercy Watson Comes to the Rescue Kate DiCamillo Freddy: Don’t Sit on My Lunch Abby Klein Magic Tree House: Polar Bears Past Bedtime Mary Pope Osborne Stink! The Incredible Shrinking Kid Megan McDonald
focuses on the importance of the blolo bla and bian and how they contribute to Baule society. To the person, the spirit life is their connection to the outer world. It helps them in love and with the bearing of children but can also behave poorly if neglected by its earthly spouse. If a person is having relationship or fertility issues, a diviner would be called in to help the person with their blolo spouse and its creation. The look of each spirit spouse is unique and is specific to the person that it is created for. These statues become an integral part of Baule society and life. They are even given their own day of the week in which the earthly spouse spends dinner with them and sleeps besides them. They are always in the house of the spouse and always on their minds. However, no matter the type of sculpture the Baule hold them with great regard. Works Cited Arneson Richard, "Egalitarianism", The Stanford Encyclopedia of Philosophy (2002.) Web:
TOTAL Student’s Name_______________________________ Phone Number______________________________ To order please send this form with Check made payable to Bucks County Karate School To: Jennefer Pursell 20 Pineside Drive Perkasie, Pa 18944 All T- shirt orders must be received by October 19, 2017. Additional T-shirts will be for sale at event for $20.
Match Oxfordshire Captains H’cap Result Cambridgeshire Captains H’cap NO.1 1st Tee Pete Walton – Captain Kirtlington Golf Club 11 L Akers – Captain Barkway Park GC 19 1.00pm Theo Ziffo Badgemore Park Golf Club 20 5 & 4 Dave Woods Ely City GC 12 NO.2 1st Tee Ray Shaw Tadmarton Heath Golf Club 8 L John Johnson Barkway Park GC 16 1.08pm Jim Weir Drayton Park Golf Club 15 4 & 2 Malcolm Knoble-Forbes Heydon Grange GC 12 NO.3 1st Tee Terry Killick Badgemore Park Golf Club 9 L Gordon Hannam Oxfordshire sub 1.16pm David Palmer Drayton Park Golf Club 17 4 & 3 Alan Rogerson Barkway Park GC 18 NO.4 1st Tee Pete Steele Burford Golf Club 9 W Gordon Lamb Gog Magog GC 10 1.24pm Bill White Hadden Hill Golf Club 17 2 & 1 John Papworth Ely City GC 17 NO.5 1st Tee Danny Fois Badgemore Park Golf Club 8 L David Steer GC 15 1.32pm Brian Maddison – Match Manager Drayton Park Golf Club 17 5 & 4 John Cardwell Brampton Park GC 18 NO.6 10th Tee Dave Briggs Bicester Golf Club 12 L John Fuller – Vice Captain Girton GC 16 1.00pm Stuart Dobbs Hadden Hill Golf Club 16 2 & 1 Tony Leigh Heydon Grange GC 19 NO.7 10th Tee Ken Arlett Badgemore Park Golf Club 16 L David Francis Barkway Park GC 16 1.08pm Tom Campbell Henley Golf Club 16 7 & 6 Phil Black Heydon Grange GC 16 NO.8 10th Tee Keith Bowker Drayton Park Golf Club 16 W Steve Kane Barkway Park GC 16 1.16pm John Edwards The Springs Golf Club 22 2 & 1 Harry Jeffrey Links – Newmarket GC 24
Rule 3. Drafting 1. The text of the policy must be prepared in a form that meets the drafting conventions of the Planning Policy Framework. Rule 4. Document references 1. Documents required to make or inform a planning decision, which meet Rule 1, may be included under “Guidelines for decision makers.” 2. Documents which do not meet Rule 1, but which form useful background as to why a policy has been drafted in a particular way, may be included as “Background Documents”. Defined language Strategies The following matrix of strategy verbs presents the Committee’s approach to the use of verbs in strategies based on the policy approach to be taken and the type of action to which the policy is directed. It identifies whether the strategy has a focus of facilitation, regulation, further planning work or identifying matters for consideration. Matrix of strategy verbs APPROACH TO BE TAKEN Make it happen Support it happening Control what happens (facilitate support) (should must) ACTION THEMES Build new Facilitate Provide Support Create Require Repair Upgrade Improve Restore Reinforce Maintain Conserve Protect Reinforce Preserve Reduce (the adverse impact) Minimise (the adverse impact) Avoid (the adverse impact) Decide Recognise Balance Plan Prepare (a specific type of plan) Plan/design Use (a specific technique or approach) Particular provisions Particular provisions relevant to the policy matter have been listed to aid the decision maker. Guidelines for decision makers These include: 1. Relevant matters to be considered 2. Information to be supplied with permit applications 3. Standards that should be met in planning decisions. Documents to be considered as relevant hold weight in decision making, at the discretion of the decision maker. Strategic planning guidelines The strategic planning guidelines are intended to indicate desirable further strategic work within a framework of continuous improvement. a) Monitor, consider
BAWSC Membership Renewal Process Log into the site by entering in your email address assoicated with your previous year membership and passord. Note: if you forgot your password click on the “forgot passord” link and the system will send you an email with a link to reset your password. Once you are logged in click on the “View Profile” button found in the upper right hand corner of the screen under your name. You should then see the “My Profile” screen as in the example below Click on the “Renew until 01/01/2014” button to begin the renewal process. You should then see the “Membership Renewal” screen as seen below. Validate/update all the fields on the screen including clicking on and accepting the “Membership Waiver” If you have dependents 18 and under associated with your account please make sure you update the Dependents section to reflect the correct age and names of your dependents. See the Membership Application Help Video for example how Brady Bunch would register with the club. Once you have updated the form click on “Update and Next” Note: If you don’t see the “Renew until 01/01/2014” button it is most likely because you are a bundle member (co-member) and need the bundle administrator (primary member) to execute the renewal process. As a bundle member (co-member) you can still update your profile and accept the club waiver.
0-10 10-30 30-40 40-1 1-110 110-130 130-140 140-2 2-210 210-230 230-240 240-3 3-310 310-330 330-340 340-4 4-5 5-520 520-530 530-550 550-6 6-620 620-630 630-650 650-7 7-720 720-730 730-750 750-8 8-820 820-830 830-850 850-950 950-1010 1010-1020 1020-1040 1040-1050 1050-1110 1110-1120 1120-1140 1140-1150 1150-1210 1210-1220 1220-1240 1240-1250 1250-1310 1310-1320 1320-1340 1340-1440 1440-15 15-1510 1510-1530 1530-1540 1540-16 16-1610 1610-1630 1630-1640 1640-17 17-1710 1710-1730 1730-1740 1740-18 18-1810 1810-1830 Go All Out for 20 Seconds (Battle rope waves or any battle rope variation at nowloss.com/battle)
The interaction between GA3 and soaking time was significant on Cuscuta germination only on day 6 of Trial I (Table 7). The interaction result showed that, 250 ppm and 36 hours soaking time had significantly the highest germination of C. campestris seeds compared to the rest of the interaction effects, although it was comparable with 100 and 150 ppm with 36 hours. soaking time treatments (Table 8). DISCUSSIONS Effect of Wet Heat on Germination of Cuscuta campestris Dormancy in seeds is usually associated with the factors of protective covering such as the hard seed coat or enclosed embryo. In this study dipping C. campestris seeds for 5 seconds in wet heat were effective in breaking the seed dormancy compared with the control which recorded less germination for the period of the experiment. Wet heat might have weakening effect on the cuticle or lignin of the seed coat of C. campestris thereby permitting the absorbsion of more water that might probably leach out germination inhibitors present either in the seed coat or in the embryo. Ekhator et al. (2008) have also used hot water treatment to enhance the germination of Mimosa invisa Mart where 71% germination was observed when seeds were immersed in boiling water for 2 minutes. Similarly, Aliero (2004) reported that, treatment of Parkia biglobosa seed for 4 seconds in hot water gave the highest germination of 42.4% when compared with the control, 1, 2, 3 and 5 seconds hot water treatments. Effect of Mechanical Scarification on Germination of Cuscuta campestris Mechanically scarified seed with sandpaper continuously gave higher germination percentage of the combined mean followed by gravel and the least from the unscarified seeds (control) though not significant. Probably, this showed that C. campestris seeds were more scarified with sandpaper than the rest of the mechanical treatments which have less potential of breaking the dormancy of the seed. Similarly, Hutchison and Ashton (1979) reported that mature dodder seeds were induced to germinate by mechanical scarification with sandpaper. Aliero (2004) also reported that, total germination of Parkia biglobosa seeds mechanically scratched in gravels was 21.4% and no germination from the unscarified seeds (control).
BI 7961 HDI biuret DMP 2,250 410 70 coil and electrostatic BI 7963 HDI biuret DEM 4,500 477 70 PM low temp curing or higher reactivity BI 7981 HDI trimer e Cap 450 476 65 PMA coil coating BI 7982 HDI trimer DMP 600 410 70 PM automotive and coil coating BI 7984 HDI trimer MEKO 3,000 373 75 automotive and coil coating Hybrid Aliphatic Blocked Isocyanates* BI 7990 IPDI trimer DMP/ DEM 5,000 538 65 PM/ PMA automotive and coil coatings BI 7991 HDI biuret DMP/ DEM 1,000 456 70 PM/ PMA automotive and coil coatings BI 7992 HDI trimer DMP/ DEM 1,500 456 70 PM/ PMA automotive and coil coatings *Hybrid blocking agents reduces tendency of DEM blocked isocyanates from crystallizing upoin standing, and improves the compatibility with OH functional resins. Blocked Isocyanate Prepolymers Blocked aromatic prepolynmers are also available for use as epoxy flexibilizers. These systems are designed for use with ambient temperature processed, amine cured, two pack epoxy systems. Replacing some the the epoxy resin in the formulation with these products gives increased elongation, impact resistance and flexibility without compromising the chemical resistance of the epoxy. Trixene Iso Type Polymer Type Viscosity @ 25C (cps) Isocyanate Eq. Wt. BI 7770 TDI Branched 68,000 1860 BI 7771 TDI Branched 80,000 1750 BI 7772 TDI Linear 35,000 2100 BI 7774 TDI Branched 40,000 1945 BI 7779* TDI Branched 30,000 2170 *contains 10% dioctyl phthalate Please contact your Tri-iso Technical Sales Representative if you would like additional information or visit our website, . Alternatively, send an email .
Homebridge John Afshar | Sr. Account Executive (Direct) | (eFax) jafshar@homebridge.com Lender Paid Compensation: 1.75% Minimum: $3,000. Maximum: $15,000. Interbank Wholesale Dino Biorac-Account Executive dbiorac C-714-232-6498 P-530-210-7323 F-530-852-0894 Lender Paid Compensation: 1.75% Early loan payoff: 150 days JMAC Lending – Broker ID# 10600 Anne Nguyen – Account Executive P: 949-390-2688 x2614 Lender Paid Compensation: 1.375% Minimum Commission: $3,000 Maximum Commission: $20,000 Note: Please go to website for rate sheets. password: feb14 (1st three letters of the month we are in/ last two digits of the year we are in) This password changes at the beginning of every month.
Home ph: 07 543 2118 Work ph: 07 572 4000 Mobile ph: 027 427 3601 Rotorua General Thurston 19 Moncur Drive Rotorua 3015 Home ph: 07 348 6768 Mobile ph: 0274 966 499 Rotorua General Neil Oppatt 11 Steep Street RD 5 Lake Ōkāreka Rotorua 3076 Mobile ph: 021 708 052 Home ph: 07 362 8424 Eastern Bay of Plenty General Colin Holmes 4465 Galatea Road RD 1 Murupara 3079
This section seeks information about implementation of the performance criteria contained in 9VAC25-830-130 of the Chesapeake Bay Preservation Act Designation and Management Regulations (Regulations). In the past year, how many notices have been sent to on-site septic system owners regarding the pump-out and inspection requirement? In the past year, how many on-site septic tanks have been determined to meet Bay Act regulations by being pumped, inspected or fitted with plastic effluent filters? Pumped: Inspected: Plastic Effluent Filters: Total number of septic systems that have been pumped out, inspected or fitted with plastic effluent filters within the past five years. Total number of septic systems located in local Chesapeake Bay Preservation Areas Total number of Soil and Water Conservation Assessments completed in the past year . Number of new agricultural BMPs installed (based on a SWCA) during the past year that were not funded through a cost share program PART III - CBPA DELINEATIONS AND MAPPING Total land area in CBPA: Total land area included in the RPA: How were these figures determined? If the RPA number above was determined from local mapping resources (GIS, etc.), are the updates of the CBPA map based on completed perennial flow and/or wetlands determinations? If so, how frequently is the CBPA map updated? If the CBPA map is updated, how much Resource Protection Area was added (or subtracted) as a result of Perennial Flow Determinations? (Please indicate unit of measurement: acres, square feet, linear stream miles, etc.) PART IV - VIOLATIONS IN RESOURCE PROTECTION number of RPA violations identified: Vegetation removal only: All other RPA violations: If there are additional aspects of the Bay Act program (education and outreach programs, innovative enhancements, etc.) that should be reported, please list those items on a separate page. PART IV – COMPREHENSIVE PLAN UPDATES Have been any updates to the Bay Act elements of the comprehensive plan? What is the status of any implementation measures in the Bay Act elements of the comprehensive plan?
The patient- and family-centered care concept benefits both MPMHC and the patient/family members. The ability to address old problems with new ideas can make a significant difference to patient care and safety. Jargon 101 Below is a list of some of the acronyms or terms you may hear while participating in this program. If you are in a situation where you hear an acronym or term you do not understand, please do not hesitate to ask the person using the phrase for clarification. Terms: ACP – Advance Care Planning ARNP – Advance Registered Practitioner EMR – Electronic Medical Record HIPAA – Health Insurance Portability and Accountability Act HIM – Health Information Management IT – Information Technology MSW – Masters in Social Work NEP – New Established Patient OP – Occupational Therapy PCL- RN Patient Care Leader PCT– Patient Care Technician PHR – Personal Health Record PFAC – Patient and Family Advisory Council PSR – Patient Service Representative PT – Physical Therapy Rad Tech – Imaging Technician RD – Registered Dietitian RN – Registered Nurse
Q: What are motor proteins? A: Existing just beneath the cell's surface, motor proteins carry to the nucleus nutrients that have been processed by endosomes. Q: What do ribosomes do? A: Normally, ribosomes convert our DNA blueprints into ________________ that are important to the cell. But when fed with viral instructions, they can start building the raw materials for a virus "_____________." Q: What happens to a cell when its DNA becomes paralyzed by a virus? A: The cell falls into ___________________; its only activity is that of the ________________. Q: What keeps a virus from spreading? A: White blood cells usually ____________________ the virus, even engulfing nearby cells that may be vulnerable to infection. (Some surrounding cells even destroy themselves to stop the virus from spreading.)
Intercept 58.87 15.33 3.84 0.00 28.59 89.15 of X -1.64 0.85 -1.93 0.06 -3.31 0.04 Income (‘000s) 1.11 0.24 4.64 0.00 0.63 1.56 3-1 . Only the coefficients for the Intercept and Income are statistically significant at the 5 percent level or better. The R-square is quite low, indicating that the model explains only 14 percent of the total variation in demand for X. The adjusted R-square is only marginally lower (13 percent), suggesting that the R-square is not the result of an excessive number of estimated coefficients relative to the sample size. The F-statistic, however, suggests that the overall regression is statistically significant at better than the 5 percent level. The approximate 95 percent confidence interval for a is . Thus, you can be 95 percent confident that a is within the range of 17 and 27. The approximate 95 percent confidence interval for b is . Thus, you can be 95 percent confident that b is within the range of –3.2 and –0.4. The t statistics are as follows: ; ; and . the coefficient estimate, , is not statistically different from zero. Since, the coefficient estimate, , is statistically different from zero. Finally, since the coefficient estimate, , is not statistically different from zero. The R-square tells us that 35 percent of the variability in the dependent variable is explained by price and income. The own-price elasticity of demand is -2.18, so demand is elastic. The income elasticity of demand is 0.34, so X is a normal good. The result is not surprising. Given the available information, the own price elasticity of demand for major cellular telephone manufacturer is . Since this number is greater than one in absolute value, demand is elastic. By the total revenue test, this means that a reduction in price will increase revenues. The regression output is as follows: Table 3-2
Let (given , or conditioning on) be i.i.d. where the variance is known. The sample mean is the sufficient statistic for , such that Then so the posterior distribution is The same as previous examples, we are setting the posterior distribution as where Therefore as know from the general theorem, the posterior distribution using the sufficient statistic yields the same result as the one using the entire likelihood in example 2. 4. Frequentist Properties of Bayesian Estimators. Given a random sample from a Normal population with mean and variance 4. Please (a) Derive a sufficient statistic for. (b) Derive the maximum likelihood estimator (MLE) of. (c) Assuming the prior ofDerive the the Bayes estimator of. (d) Which of the two estimators (the Bayes estimator and the MLE) are better? Why?