zilongwang/ReadingBank huggingface dataset:
Fig. S5 PLE and PL spectra of micrometer-sized Ag+-exchanged zeolite nanoparticles exposed to X-ray radiation for different durations. λex=305 nm, λem=524 nm. Fig. S6 Change in PL quantum efficiency (QE) of micrometer-sized Ag+-exchanged zeolite with X-ray irradiation duration. λex=305 nm. Fig. S7 ESR spectra of quartz glass tube (a) and Ag+-exchanged zeolite nanoparticle powders (b,c). Before (b) and after (c) X-ray irradiation for 40 min.
illness or injury? Did you experience sustained bullying or rejection by schoolmates? Bullying/peer rejection Were you physically abused? Physical abuse Were you sexually abused? Sexual abuse Were you emotionally abused? Emotional abuse Did you experience extreme poverty or neglect? Neglect/poverty Did you witness a natural disaster such as earthquake, flood or fire? Disaster Was your house destroyed by fire or other means? Home destroyed Did you witness warfare? Warfare Did your parents divorce or separate? Parental divorce/separation Were you separated for a long period from a parent, brother or sister? Sibling separation Was there sustained conflict within your family? Sustained conflict Did one of your parents, a brother or sister die? Death in family Did one of your parents, a brother or sister experience a life-threatening illness? Family health trauma Did you witness domestic violence within your family? DV
Table S1: Operating conditions of several large-scale desalination plants equipped with porous membranes Location Type – mode of filtration (manufacturer) Production flow rate (m3.j−1) Permeate flux (L.h−1.m−2) References UF/MF RO Yu-Huan – China UF – SUB 76,800 34,500 30–50 [21, 22] Perth – Australia UF – PO/I (Memcor) 360,000 144,000 - [23, 24] Moni – Cyprus UF – PO/I (Dow) - 20,000 60 [25] Algeria UF – PO/I (Hyflux) 450,000 - 50–70 [24] California – USA MF – PO/I (Pall) 75,000 - - [26] Kindasa – Saudi Arabia UF – PI/O (Hydranautics) - 90,000 75–100 [21, 27] Hamriyah – United Arab Emirates UF – PI/O (Hydranautics) 114,000 91,000 - [28] Torrevaldaliga – Italy UF – PI/O (Inge) - 8700 - [29] Dalian – China UF – PI/O (Inge) - 36,500 [30] Palm Jumeirah – United Arab Emirates UF – PI/O (Pentair) 184,000 64,000 60–80 [21, 31] Colakoglu – Turkey UF – PI/O (Pentair) - 67,000 50–60 [21, 32] UF: ultrafiltration; MF: microfiltration; RO: reverse osmosis; PO/I: filtration under pressure from the outside to the inside of fiber; PI/O: filtration under pressure from the inside to the outside of fiber; SUB: submerged membrane filtration; GWI: Global Water Intelligence.
Table S2: Characteristics of different seawater sampled in the global maritime exchange zones Location TSS (mg.L−1) Turbidity (NTU) Chlorophyll a (µg.L−1) TOC (mg.L−1) DOC (mg.L−1) Conductivity (mS.cm−1) pH SiO2 (mg.L−1) SDI References Mediterranean - 0.1–2.9 - - - - 7.8–8.2 - 14–40* [33] Mediterranean - 0.1–1.3 0.9–1.3 1–1.5 - - - - [34] Mediterranean – France 10–20 0.5–4.0 - - 2.7–6.1 50.0–57.3 8.0–8.1 - 6.1–6.4° [35] Mediterranean – France - - - - 1.5–1.8 - 8.1 - - [36] Mediterranean – Gibraltar - 0.7 - 2.1 0.3 48.7 8.1 - 13–24.6† [37] Red Sea – Saudi Arabia - 4.5 - - - 34.9 - - - [38] Atlantic Ocean – Canary Islands - <0.2–0.6 - 0.5–0.7 - 46.7–49.6 7.4–8.1 - - [39] Mediterranean - 1–10 - - - - - - - [38] Red Sea – Saudi Arabia - 0.05–20 - - - - - - - [27] Red Sea – Israel - 0.2–1.1 - - - - - - - [38] Oman Gulf - 0.12–0.56 - <5.0 - 54.2–56.5 7.9–8.5 - 3.6–20° [40]
Table S2. Analytical methods used for the laboratory analysis of the physico-chemical characterization of sediments. Adapted from Johnston et al. (2014) and Skilton et al. (2015). Analyte Method number Method description Detection Organic content (AFDW) APHA 2540 G 22nd ed. 2012. Ignition in muffle furnace 550 °C, 6 hr, gravimetric. 0.04 g/100 g dry wt 0.010 metals, trace As,Cd,Cr,Cu,Ni,Pb,Zn,Hg PSP 2002 mod./APHA metals by Dried sample, <2 mm fraction. Nitric/Hydrochloric acid digestion, ICP-MS, trace level 0.010 - 0.4 mg/kg dry w Total Recoverable Barium PSP 2002 mod./APHA metals by Dried sample, sieved as specified (if required). 1, 5, 9 Nitric/Hydrochloric acid digestion, ICP-MS, trace level. US EPA 200.2. 0.02 mg/kg dry wt 40 Total Recoverable Iron Total PSP 2002 mod./APHA metals by Dried sample, sieved as specified (if required). 1, 5, 9 Nitric/Hydrochloric acid digestion, ICP-MS, screen level. USEPA 200.2 40 mg/kg dry wt 1.0 Total Recoverable Manganese PSP 2002 mod./APHA metals by Dried sample, sieved as specified (if required). 1, 5, 9 Nitric/Hydrochloric acid digestion, ICP-MS, screen level. USEPA 200.2 1.0 mg/kg dry wt Polycyclic Aromatic Hydrocarbons ESEPA 8270C Sonication extraction, SPE (solid phase extraction) cleanup, GC-MS SIM (gas chromatography-mass spectroscopy selective ion monitoring) analysis. 0.002 - 0.010 mg/kg dry wt Total Petroleum Hydrocarbons US EPA 8015B/MfE Petroleum Industry Guidelines. Sonication extraction, Silica cleanup, GC-FID (flame ionising detection) analysis . 8 - 70 mg/kg dry wt
SI-Table 4 Conflicts matrix Land Use Conservation Archaeology Recreation defence/ Coastal Protection Ports Infrastructure Industry Agriculture Extraction residential Tourism Ecosystem Ecosystem Good/ Service Sub Land Use protected subtidal protected intertidal areas heritage on land heritage in estuary Footpath sailing/ boating Bird Watching Flood bank Managed realignment Navigation Capital dredging Maintenance dredging Vessels Reclamation disturbance adjacent to the system disturbance in the system Import pipelines bridges piers/ jetty seawall cables Water Abstraction Discharge Activity adjacent to system run-off Water Abstraction commercial recreational wildfowling Discharge disturbance adjacent to system drinking water abstraction beaches Estuary Water body Fish Vegetation water supply navigation climate carbon sequestration maintain biodiversity nutrient cycling recreation future uses visual amenity tourism education/ research landscape use Estuary- Mudflats Fish carbon sequestration water purification air purification maintain biodiversity nutrient cycling sediment formation and stability shoreline protection recreation future uses visual amenity tourism education/ research landscape use Estuary - Sand Dunes Vegetation water supply climate carbon sequestration water purification air purification maintain biodiversity nutrient cycling sediment formation and stability shoreline protection recreation future uses visual amenity tourism education/ research landscape use Managed realignment Sites Fish Vegetation water supply climate carbon sequestration purification air purification maintain biodiversity nutrient cycling
Vermont 13.1 62.9 31.3 59.5 41.3 41.6 Virginia 79.5 32.9 30.4 43.2 60.0 49.2 Washington 56.7 31.3 28.9 30.1 45.8 38.6 West Virginia 21.1 37.2 24.5 44.8 53.4 36.2 Wisconsin 65.0 97.9 64.1 74.7 73.0 74.9 Wyoming 45.5 22.8 31.2 32.4 46.2 35.6
SUPPLEMENTAL TABLES Supplemental table 1 IP1 Receptor Agonist pEC50 (EC50 μM) Base (%) N mGlu3 WT Glutamate - 38,76 ± 3,00 3 mGlu2 WT 4,79 ± 0,07 (16,22) 100,00 ± 0,00 3 VFT2/TMD3 4,56 ± 0,08 (27,54) 148,47 ± 12,48 3 VFT3/TMD2 - 41,69 ± 4,57 3 TR-FRET sensor Receptor Agonist pEC50 (EC50 μM) Base (%) N mGlu3 WT Glutamate 5,30 ± 0,14 (5,01) 15,22 ± 3,01 3 mGlu2 WT 4,99 ± 0,13 (10,23) 100,00 ± 0,00 3 VFT2/TMD3 4,71 ± 0,16 (19,50) 111,27 ± 1,19 3 VFT3/TMD2 6,06 ± 0,08 (0,87) 7,84 ± 2,22 3 Supplemental table 1: Concentration-response curves parameters of mGlu2-mGlu3 chimeras.
Table S1. Calculation of theoretical integrations from relative abundance determined by GPC and theoretical molar masses. Molar Mass (g/mol) Relative Abundance (wt. %) Mole Fraction Theoretical # of carbonyl C’s per chain Theoretical # of terminal methoxy C’s per Contribution to integration of carbonyl C's per chain Contribution to integration of terminal methoxy C's per chain Monomer 1314.5 43.37 0.667 1.75 1.75 1.17 1.17 Dimer 2538.9 24.78 0.197 2.75 1.75 0.54 0.34 Trimer 3763.5 5.38 0.029 3.75 1.75 0.11 0.05 Tetramer 4988.0 26.47 0.107 4.75 1.75 0.51 0.19 Sum -- 100 1 -- -- 2.33 1.75 Figure S3. Representative DSC Thermograms of PFPEE10-DMC and PFPED10-DMC, illustrating the greater change in glass transition temperature upon salt loading in the E10 series. Traces are vertically offset from each other for ease of visualization. Figure S4. Thermogravimetric Analysis curves of dimethyl carbonate and PFPE polymers.
modulus (G) and tensile modulus (E) as shown in the (eq. 2).1 The bulk modulus and shear modulus can be calculated from Molar Elastic Wave Function, U; it is independent of temperature or polymeric phase state and can be calculated from additive group contribution as can be seen from (eq. 3) - (eq. 4). So the tensile modulus or Young’s modulus (E) can be estimated from (eq. 2 ) - (eq. 5). K = ρ (UR/V)6 (eq. 3) G = ρ (UH/V)6 (eq. 4) G/K = (UH/UR)6 (eq. 5) The modulus of each polyester were calculated from group contribution parameters in Table S3 considering each repeating unit structure. As shown in the Table S4, the modulus increase in the order PET, P12PT, P23BT and these trends supported that the substituted methyl group made the polymer chain stiffer. Table S3. Group contributions to the Rao and Hartmann-functions Group URa UHa -CH2- 880 675 -CH(CH3)- 1,875 1,650 1,225 900 4,100 3,300 a UR = Rao-function, UH = Hartmann function, which are experted from Table 14.4 in Ref. 1.
Supporting Information for Biopolymeric nanogel derived from functionalized glycogen towards targeted delivery of 5-fluorouracil Priyapratim Patra a, Venkata Sundeep Seesala b, Dipankar Das a, Asit Baran Panda c, Santanu Dhara b, * and Sagar Pal a, * a Polymer Chemistry Laboratory, Department of Applied Chemistry, Indian Institute of Technology (ISM), Dhanbad 826004, India. b Biomaterials and Tissue Engineering Laboratory, School of Medical Science and Technology, Indian Institute of Technology, Kharagpur 721302, c Discipline of Inorganic Materials and Catalysis, Central Salt and Marine Chemicals Research Institute (CSIR), Bhavnagar 364002, Gujarat, India. a*Corresponding Author: E-mail: ; Tel: +91-326-2235769 b*Corresponding Author: E-mail: Tel: +91-3222-282306.
Glycogen 137.14 139.82 pHEMA 171.89 173.92 Second zone of n-Gly/pHEMA nanogel 179.70 180.53 zone of n-Gly/pHEMA nanogel 231.38 231.83 Table S2. Yield stress and gel strength Polymer Applied frequency (Hz) Yield stress (Pa) Gel strength (G'/G'') 1 110 1.10 5 302 1.32
Table S3. % loading and % encapsulation of 5-FU Drug Weight of (mg) Weight of drug (mg) Time of loading (h) % of loading % of encapsulation 5-FU 20 5 24 5 19 48 15 60 Table S4: Release mechanism data
ITO/ZnO/polymer:ITIC(1:1, w/w)/MoO3/Ag device structure, measured under AM 1.5G illumination (100 mW cm-2) Donor Wt. ratio (D:A) Annealing Temp. Voc (V) Jsc (mA cm-2) FF (%) PCE (%) Ran-TT ITIC 1 : 1 RT 0.79 12.7 52.5 5.32 100 oC 0.81 12.6 55.3 5.65 120 oC 0.76 12.5 55.6 5.28 1 : 2 100 oC 0.81 5.67 55.8 2.57 1 : 1.5 0.81 6.34 53.9 3.02 1 : 1 0.81 12.6 55.3 5.65 1.5 : 1 0.82 7.49 50.5 3.10 Fig. S5. J-V characteristics of PSCs based on Ran-TT:ITIC as-cast films prepared with different solvents. Table S3. Photovoltaic properties of PSCs fabricated with the use of an additive with ITO/ZnO/polymer:ITIC (1:1, w/w)/MoO3/Ag device structure, measured under AM 1.5G illumination (100 mW cm-2) Donor Acceptor solvent Voc (V) Jsc (mA cm-2) FF (%) PCE (%) Ran-TT ITIC CB + CN 1% (v/v) 0.82 6.13 55.3 2.72 CB 0.79 11.2 54.2 4.89 CB : CF = 1 : 4 0.82 9.63 57.8 4.57
Fig S6. J-V characteristics of PSCs based on Polymer : PC71BM with and without 3% DIO additive. Table S4. Photovoltaic properties of PSCs made from chloroform solution with a ITO/PEDOT:PSS/polymer:ITIC (1:1, w/w)/LiF/Al device structure measured under AM 1.5G illumination (100 mW cm-2); Acceptor Donor Voc (V) Jsc (mA cm-2) FF (%) PCE (%) PC71BM Ran-BT 0.73 (0.63a) 2.64 (4.97a) 63.3 (60.5a) 1.22 (1.89a) Reg-BT 0.66 (0.58a) 1.46 (3.42a) 50.0 (56.2a) 0.48 (1.12a) Ran-TT 0.74 (0.64a) 1.93 (4.22a) 55.3 (64.0a) 0.79 (1.73a) Reg-TT 0.66 (0.57a) 1.44 (3.11a) 48.8 (51.2a) 0.47 (0.90a) a With 3% DIO Properties of HOD and EOD
Supplemental Table S3: Significant results of the a priori sensitivity analysis by the systematic removal of each one by onea Removal of MD 95% CI I² Comment Triglycerides (mmol/L) Jenkins et al 2011 - routine -0.36 [-0.46, <0.0001 0% 0.71 Heterogeneity was explained after removal Systolic blood pressure (mmHg) Jenkins et al. 2011 - intensive -1.17 [-3.02, 0.68] 0.22 0% 0.84 MD no longer significant removal Diastolic blood pressure (mmHg) Jenkins et al 2011 - routine -1.17 [-2.57, 0.22] 0.10 12% 0.34 MD no longer significant after trial removal Jenkins et al. 2011 - intensive -0.96 [-2.16, 0.25] 0.12 0% 0.48 CRP (mg/L) Jenkins et al. 2003b -0.53 [-1.07, 0.02] 0.06 44% 0.12 MD no longer significant after removal Jenkins et al. 2003a -0.50 [-1.00, 0.00] 0.05 40% 0.14 Jenkins et. al. 2010 - High MUFA -0.44 [-0.91, 0.02] 0.06 23% 0.26 10-year CHD Risk, % Jenkins et al. 2003a -0.81 [-1.36, 0.004 0% 0.67 Heterogeneity was explained trial removal a Sensitivity analysis included the removal of a single from the meta-analyses one at a time and the summary effect was recalculated. An influential comparison was considered a comparison whose removal changed the significance, direction or magnitude (by >10%) of the pooled estimate or changed the significance of the heterogeneity estimate. Only influential comparisons are presented in this table.
LDL-C (mmol/L) -0.50 [-0.61, -0.40] 0.00001 0% 0.81 MD changed by >10% and heterogeneity was explained -11% Total-C (mmol/L) -0.61 [-0.74, -0.48] 0% 0.84 MD changed by >10% and heterogeneity was explained -9% Triglycerides (mmol/L) -0.28 [-0.61, 0.05] 0.10 92% 0.0004 MD changed by >10% and significance lost -18% HDL-C (mmol/L) -0.03 [-0.08, 0.02] 0.27 4% 0.31 MD changed by >10% removal of trials -2% non-HDL-C (mmol/L) -0.58 [-0.72, -0.45] <0.00001 0% 0.85 MD changed by >10% and heterogeneity was explained -11% ApoB (g/L) -0.14 [-0.16, -0.11] 0% 0.72 MD changed by >10% and heterogeneity was explained -12% Systolic blood pressure (mmHg) -2.00 [-3.82, -0.19] 0.03 0% 0.36 no changes -2% Diastolic blood pressure (mmHg) -1.75 [-2.90, -0.59] 0.003 0% 0.55 no changes -2% CRP (mg/L) -0.73 [-1.73, 0.28] 0.15 0% 0.70 MD changed by >10% and significance lost -40%
Table S1 Weighted estimates (percentages) of fluoride exposure and other dental health related indicators in Calgary and Edmonton, 2013/14 Variable and categories Calgary (n=2,778) Percentage (95% CI) Edmonton (n=1,907) Percentage (95% CI) Dental health variables General health of child’s mouth: Percent excellent/very good (vs. good / fair / poor)* 55% (53%, 58%) 50% (48%, 53%) Brush twice/day: Percent yes (vs no)* 68% (66%, 70%) 59% (56%, 62%) Floss once/day: Percent yes (vs no) 18% (17%, 20%) 17% (15%, 19%) Dental care variables Visit dentist “only for emergencies or never”: Percent yes (vs. about once/year or more for treatment or prevention)* 10% (8%, 11%) 14% (12%, 16%) Last time dentist: Percent within the last year (vs. more than one year ago)* 84% (82%, 85%) 78% (75%, 80%) Dental insurance: Percent no (vs yes) 15% (14%, 17%) 17% (15%, 19%) Dietary variables Fruits & vegetables at least once/day: Percent yes* 45% (42%, 48%) 39% (36%, 42%) Sugary drinks (i.e., fruit drink, sports drink, pop) at least once/day: Percent yes* 10% (8%, 12%) 14% (12%, 16%) Fluoride exposure variables Fluoride supplements at home: Percent yes [ever] (vs no)^ 6% (5%, 7%) 4% (4%, 6%)
Minimum Elevation Tall S. alterniflora -0.67 0.55 -0.46 -1.46 Medium S. alterniflora 0.24 1.46 0.45 -0.55 Short S. alterniflora 0.59 1.81 0.79 -0.20 Intertidal Mud 0.52 1.74 0.73 -0.27 S. virginica 0.75 1.97 0.96 -0.04 D. spicata 0.78 2.00 0.98 -0.02 B. maritima 0.84 2.06 1.04 0.05 Salt pan 0.87 2.09 1.08 0.08 J. roemerianus 0.67 1.88 0.87 -0.13 B. frutescens 0.94 2.16 1.15 0.15 Maximum Elevation Tall S. alterniflora 0.85 2.07 1.05 0.05 Medium S. alterniflora 1.09 2.31 1.30 0.30 Short S. alterniflora 1.14 2.35 1.34 0.34 Intertidal Mud 1.09 2.31 1.30 0.30 S. virginica 1.28 2.50 1.49 0.49 D. spicata 1.10 2.31 1.30 0.30 B. maritima 1.29 2.51 1.50 0.50 Salt pan 1.16 2.38 1.36 0.36 J. roemerianus 1.46 2.68 1.66 0.67 B. frutescens 1.49 2.71 1.70 0.70
Table S3. Maximum likelihood classification (MLC) error matrix for the initial hyperspectral classification in this study prior to application of the decision tree. Columns represent reference data (what the pixel actually is based on validation data) and rows represent image data (what the pixel was classified as). Percentages are rounded to the nearest decimal place and may not sum to 100% for each cover class. Class Tall S. alterniflora Medium S. alterniflora S. alterniflora Intertidal Mud S. virginica B. maritima Salt Pan J. B. Unclassified 0 0 0 0 0 0 0 0 0 Tall S. alterniflora 93.30 2.93 0 1.76 0.16 0 0 2.26 0 Medium S. alterniflora 5.76 86.77 13.24 0.00 6.06 0 0 2.02 2.04 Short S. alterniflora 0 7.99 85.44 10.56 0.98 0 0 0 0 Intertidal Mud 0.2 0 0.54 86.80 0 0 0 0 0 S. virginica 0 1.19 0.68 0 82.49 3.64 2.38 0 0 B. maritima 0 0 0 0 5.73 89.27 0 0.97 2.66 Salt Pan 0 0 0 1 4.58 0 97.62 0 0 J. roemerianus 0 1.12 0.1 0 0 0 0 94.35 0 B. frutescens 0.74 0 0 0 0 7.09 0 0 95.30 Total 100 100 100 100 100 100 100 100 100
Sequence type Primer name Primer sequence Amplified sequence length References Sequencing platform Bacteria 16S rRNA 338F 5'- ACTCCTACGGGAGGCAGCA-3' 468bp Fan et al., 2014 PE300 platform 806R 5'- GGACTACHVGGGTWTCTAAT-3' Fungi 18S rRNA ITS1F 5'-CTTGGTCATTTAGAGGAAGTAA-3' About 300bp Rousk et al., 2010 platform 2043R 5'-GCTGCGTTCTTCATCGATGC-3' Table in Supplementary methods: information of selected primers and Miseq platform.
Table S1. Key functional in N-cycling pathway and primers used for quantification of gene copy numbers. Target gene PCR primers Primer sequence (5’→3’) Reference Bacterial amoA amoA-1F GGGGTTTCTACTGGTGGT (Rotthauwe et al., 1997) amoA-2R CCCCTCKGSAAAGCCTTCTTC Archaeal amoA CrenamoA23f ATGGTCTGGCTWAGACG (Nicol et al., 2008) CrenamoA616r GCCATCCATCTGTATGTCCA nirK nirK876 ATYGGCGGVCAYGGCGA (Henry et al., 2004) nirK1040 GCCTCGATCAGRTTRTGGTT nirS nirSCd3aF AACGYSAAGGARACSGG (Kandeler et al., 2006) nirSR3cd GASTTCGGRTGSGTCTTSAYGAA nosZ nosZ1F WCSYTGTTCMTCGACAGCCAG et al., 2006) nosZ1R ATGTCGATCARCTGVKCRTTYTC
Simazine 6.70 0.1 202.0854 Atrazine D5 Tebuconazole 15.73 0.5 308.1524 Tebuconazole D6 Terbuthylazine 11.30 0.1 230.1155 Atrazine D5 Thiodicarb 8.12 0.1 355.0551 Pirimicarb D6
Fig. S7. Structures of 2,4-D and analogues: BA, 2,4,5-T and 2,4-D-OBu. References [1] J.T. Lai, D. Filla, R. Shea, Functional polymers from novel carboxyl-terminated trithiocarbonates as highly efficient RAFT agents, Macromolecules 35 (2002) [2] J. Liu, Z. Sun, Y. Deng, Y. Zou, C. Li, X. Guo, L. Xiong, Y. Gao, F. Li, D. Zhao, Highly water-dispersible biocompatible magnetite particles with low cytotoxicity stabilized by citrate groups, Angew. Chem.-Int. Edit. 48 (2009) 5875-9. [3] D. Liu, Y. Li, J. Deng, W. Yang, Synthesis and characterization of magnetic Fe 3 O 4-silica-poly (γ-benzyl-l-glutamate) composite microspheres, React. Funct. Polym. 71 (2011) 1040-1044. [4] Y. He, Y. Huang, Y. Jin, X. Liu, G. Liu, R. Zhao, Well-defined nanostructured surface-imprinted polymers for highly selective magnetic separation of fluoroquinolones in human urine, ACS Appl. Mater. Interfaces 6 (2014) 9634-42. [5] G. Scatchard, The attractions of proteins for molecules and ions, Ann. N.Y. Acad. Sci. 51 (1949) 660-672. [6] A.K. Bordbar, A.A. Saboury, A.A. Moosavi-Movahedi, The shapes of Scatchard plots for systems with two sets of binding sites, Biochemical Education 24 (1996) 172-175.
[37] Photolithography Whatman chromatography paper no 1 CB pH 1.8, 9 µM TBPB, 1:1 (vol) 0.5 µL each Artificial urine 6 – 12 min N/A <20 µM [9] Photolithography Chromatography paper 250 mM CB, pH 1.8; 3.3 mM TBPB in 95% EtOH; 1:1 (vol) 0.3 µL each Prepared solutions 10-11 minutes 0.38 µM (observed) 0 – 75 µM (tested) CB: Citrate buffer, TBPB: Tetrabromophenol blue
Fig. S2. FTIR spectra of the intermediates MSN-NH2 (blank line), (red AF-MSN-QDs (blue line). Element Wt% At% CK 21.17 36.76 NK 07.05 10.50 OK 19.90 25.95 SiK 25.15 18.68 SK 00.88 00.58 CdL 03.85 00.72 TeL 01.24 00.20 ZnK 20.75 06.62 Fig. S3. EDX spectra of AF-MSN-QD@ZIF-8 samples; presents the corresponding elemental ratio calculated by the EDX software.
4. Perdew, J. P.; Burke, K.;, Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865. 5. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. J. Chem. Phys. 2010, 132, 154104. 6. Becke, A. D.; Johnson, E. R. J. Chem. Phys. 2005, 122, 154104. 7. Grimme, S.; Ehrlich, S.; Goerigk, L. J. Comput. Chem. 2011, 32, 1456-1465. 8. Johnson, E. R.; Keinan, S.; Mori-Sanchez, P. J. Am. Chem. Soc. 2010, 132, 6498-6506. 9. Contreras-García, J.; Johnson, E. R.; Keinan, S.; Chaudret, R.; Piquemal, J. P.; Beratan, D. N.; et al. J. Chem. Theory. Comput. 2011, 7, 625-632. 10. Contreras-García, J.; Boto, R. A.; Izquierdo-Ruiz, F.; Reva, I.; Woller, T.; et al. Chem. Acc. 2016, 135, 242. 11. Venkataramanan, N. S. J. Mol. Model. 2016, 22, 1-11. 12. Safin, D. A.; Babashkina, M. G.; Robeyns, K.; Mitoraj, M. P.; Kubisiak, P.; Garcia, Y. Chem. Eur. J. 2015, 21, 16679-16687.
Supporting Information for Preparation and reactions of iodobutoxy pinacolborate. Synthesis of substituted alkyl and arylpinacolboronates via iodobutoxy pinacolborate utilizing tetrahydrofuran as the leaving group Chris L. Murphy, Aaron Hall, Emily J. Roberts, Matthew D. Ryan, Jacob W. Clary, and Bakthan Singaram* Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California, 95064 Table of Contents 2-(4-Iodobutoxy)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1) 1H, 13C, and 11B-NMR spectrum of Boronates (Table 1) 2-Octyl-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1a) 2-(3-Chlorophenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1b) 2-(4-Chlorophenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1c) 2-(3,4-Dichlorophenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1d) 2-(3,5-Dichlorophenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1e) 2-(4-Ethylphenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1f) 4,4,5,5-tetramethyl-2-o-tolyl-1,3,2-dioxaborolane (1g) 4,4,5,5-tetramethyl-2-m-tolyl-1,3,2-dioxaborolane (1h) Page S3 S6 S9 S12 S15 S18 S21 S24 S27
2-(5-Chloro-2-thienyl)- 4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1i) 2-(2-Biphenyl-2-yl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1j) 2-(4-Methoxy-2-methylphenyl)-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1k) 2-Isopropyl-4,4,5,5-tetramethyl-1,3,2-dioxaborolane (1l) 2-(Tert-butyl)-4,4,5,5-tetramthyl-1,3,2-dioxaborolane (1m 1H and 13C spectrum of Isolated MgBr2/THF Solid (Scheme 2) 1H NMR of Isolated Solid 13C NMR of Isolated Solid S30 S33 S36 S39 S42 S45 S46
C8H9Cl (Mr = 140.61); Reaction conditions: 0.5 mmol 1-phenylethanol (60 μl) 0.55 mmol TMSCl (69.8 μl), rt, stirring 400, 4 h – SFRC; Purification: CC (SiO2, CH2Cl2/hexane 1:1); Yield: 55.1 mg (79%), colourless liquid; 1H NMR (300 MHz, CDCl3): δ = 7.45 – 7.21 (m, 5H), 5.08 (q, J = 6.8 Hz, 1H), 1.84 (d, J = 6.8 Hz, 3H). 13C NMR (76 MHz, CDCl3): δ = 142.9, 128.8, 128.4, 126.6, 58.9, 26.7. 1-(1-Chloroethyl)-4-methylbenzene (2d)6 C9H11Cl (Mr = 154.64); Reaction conditions: 0.5 mmol (68.9 μl), 0.55 mmol TMSCl (69.8 μl), rt, stirring 400, 4 h – SFRC; Purification: CC (SiO2, CH2Cl2/hexane 1:1); Yield: 66.4 mg (86%), colourless oil; 1H NMR (300 MHz, CDCl3): δ = 7.29 (d, J = 8.1 Hz, 2H), 7.14 (d, J = 7.9 Hz, 2H), 5.06 (q, J = 6.8 Hz, 1H), 2.33 (s, 3H), 1.82 (d, J = 6.8 Hz, 3H). 13C NMR (76 MHz, CDCl3): δ = 140.0, 138.2, 129.4, 126.5, 58.9, 26.6, 21.2. 1-(1-Chloroethyl)-4-fluorobenzene (2e)7
IR (neat): 3356, 3036, 2884, 2795, 1608, 1518, 1350, 1230, 1164, 1019, 943, 809, 753, 702 and 559 cm-1 TLC: Rf = 0.4 (4:1; hexane: EtOAc) References: , , , , , J. Org. Chem., 2015, 80 , 8122–8133. X. Xu, G. Liu, A. Azuma, E. Tokunaga, N. Shibata, Org. Lett., 2011, 13, 4854-4857. W. Sheih, S. Dell, A. Bach, O. Repic, T. J. Blacklock, J. Org. Chem., 2003, 68, T. W. Greulich, C. G. Daniliuc, A. Studer; Org. Lett., 2014, 17, 254-257. R. J. Rafferty, R. M. Williams, Tetrahedron Lett.,, 2011, 52, 2037-2040. K. Chanda, S. Rej, S. Liu, M. H. Huang, Chem. Cat. Chem., 2015, 7, 1813-1817. T. H. Babu, G. S. Paramasivan, T. Perumal, Tetrahedron Lett., 2009, 50, 2881-2884 Gondon W. Gribble, Charles F. Nutaitis; Synthesis, 1987, 8, 709-711. , , Org. Lett., 2009, 11, 5214–5217. , , , Org. Lett., 2011, 13, 5124–5127.
NMR (400 MHz, DMSO-d6): δ 9.68 (s, 1H), 7.68 (d, J = 9.0 Hz, 1H), 7.65 (d, J = 8.6 Hz, 2H), 7.30 (d, J = 2.35 Hz, 1H), 6.89 (dd, J = 9.0, 2.35 Hz, 1H), 6.63 (d, J = 8.6 Hz, 2H), 5.78 (s, 1H). 13C APT (100.7 MHz, DMSO-d6): δ 165.0, 155.3, 151.9, 147.8, 135.5, 128.6, 122.8, 121.0, 115.9, 114.1, 107.1. REFERENCES R. V.; Patel, P. K.; Kumari, P.; Rajani, D. P.; Chikhalia, K. H., Eur. J. Med. Chem. 2012, 53, 41. L. A.; Noveron J. C.; Olmstead M. M.; Mascharak P. K. Inorg. Chem. 2000, 39, 357. Jean M.; Renault J.; Weghe P.; Asao N. Tetrahedron Lett. 2010, 51, 378. Kamal, A.; Ahmed, S. K.; Reddy, K. S.; Khan, M. N. A.; Shetty, R. V.C.R.N.C.; Siddhardha, B.; Murty, U. S. N.; China, A.; Nagaraja, V. Lett. Drug Des. Discov. 2007, 4, 550. Mathis, C. A.; Wang, Y. M.; Holt, D. P.; Huang, G. F.; Debnath, M. L.; Klunk, W. E. J. Med. Chem. 2003, 46, 2740. 1H NMR (400 MHz, DMSO-d6) 13C APT (100.7 MHz, DMSO-d6)
stage to another and is related to developmental tasks, such as career, acquiring job competencies, improving job performance, etc. Often, however, adults perceive employer-provided training as employer-required training. Then, agree to make the most out of training nevertheless. On the other hand, be aware that for those who want to be in the class, training is important and they must walk away with something. Adults are task-oriented. Education is subject-centered, but adult training should be task-centered. For example, a child in a school composition class learns grammar, and then sentence and paragraph construction. An adult in a composition training program learns how to write a business letter, a marketing plan, etc. Organize content around tasks, not subjects. See Learning”, by Malcolm S. Knowles, The ASTD Training & Development Handbook: A Guide to Human Resource Development, Robert L. Craig, editor, 1996.
5. References [1] (a) Q. Wang and X. Li, Org. Lett., 2016, 18, 2102; (b) B. Priewisch and K. J. Org. Chem., 2005, 70, 2350; (c) D. Zhao, M. Johansson and J. -E. Bäckvall, Eur. J. Org. Chem., 2007, 4431. [2] S. Bellotto, R. Reuter, C. Heinis and H. A. Wegner, J. Org. Chem., 2011, 76, 9826. [3] B. Nguyen, E. J. Emmett, and M. C. Willis, J. Am. Chem. Soc., 2010, 132, [4] N. K. Mishra, Y. Oh, M. Jeon, S. Han, S. Sharma, S. H. Han, S. H. Um and I. S. Kim, Eur. J. Org. Chem., 2016, 4976. [5] T. Kaiya, T. Fujiwara and K. Kohda, Chem. Res. Toxicol., 2000, 13, 993.
6. Copies of the 1H NMR, 13C NMR Spectra N-Phenyl-1H-benzo[d]imidazol-1-amine (3a) 6-fluoro-N-Phenyl-1H-benzo[d]imidazol-1-amine (3b) 6-chloro-N-Phenyl-1H-benzo[d]imidazol-1-amine (3c) (3d) N-(p-tolyl)-1H-benzo[d]imidazol-1-amine (3e) N-(4-(tert-butyl)phenyl)-1H-benzo[d]imidazol-1-amine (3f)
N-(4-chlorophenyl)-1H-benzo[d]imidazol-1-amine (3g) N-([1,1'-biphenyl]-4-yl)-1H-benzo[d]imidazol-1-amine (3h) N-(4-bromophenyl)-1H-benzo[d]imidazol-1-amine (3i) 6-chloro-N-(4-chlorophenyl)-1H-benzo[d]imidazol-1-amine (3j) (3k) N-(3-bromophenyl)-1H-benzo[d]imidazol-1-amine (3l)
N-(3-chlorophenyl)-1H-benzo[d]imidazol-1-amine (3m) N-(3-chlorophenyl)-7-methyl-1H-benzo[d]imidazol-1-amine (3n) N-(3,5-dimethylphenyl)-1H-benzo[d]imidazol-1-amine (3o) N-(3-methylphenyl)-1H-benzo[d]imidazol-1-amine (3p) N-(o-tolyl)-1H-benzo[d]imidazol-1-amine (3q) N-(2-(tert-butyl)phenyl)-1H-benzo[d]imidazol-1-amine (3r)
(5) Chowrasia, R.; Katla, R.; Darbem, M. P.; Branquinho, T. A., Oliveira, A. R.; Manjari, P. S.; Domingues, N. Tetrahedron Lett. 2016, 57, 1656. (6) Schilt, A.A.; Wu, J. F. Talanta. 1976, 23, 543. (7) Wu, K.; Zhang, T.; Zhan, L.; Zhong, C.; Gong, S.; Jiang, N.; Lu, Z.-H.; Yang, C. Chem. Eur. J. 2016, 22, 10860. (8) Mastalir, M.; Glatz, M.; Pittenauer, Ernst.; Allmaier, G.; Kirchner, Karl. J. Am. Chem. Soc. 2016, 138, 15543. 7. Copies of the 1H NMR, 13C NMR Spectra 2,4,6-triphenylpyrimidine (4a): 2-(4-fluorophenyl)-4,6-diphenylpyrimidine (4b):
mT). Spectrum on right shows reaction between acetone oxime and PTAD with two new signals. ESI of PTAD + acetone reaction (removed from NMR tube and quickly diluted to 1 ng/uL in 50:50 water:acetonitrile 0.1% formic acid and injected into ESI-MS). Other products have begun to form as the nitroso decomposes. References to Supporting Information Ghorbani-Choghamarani, A.; Chenani, Z.; Mallakpour, S. Syn. Comm. 2009, 39, 4264-4270. Hall, J. H.; Bigard, W. E.; Fargher, J. M.; Jones, M. L. J. Org. Chem. 1982, 47, 1459-1462. Zolfigol, M. A.; Ghorbani-Vaghei, R.; Mallakpour, S.; Chehardoli, G.; A.; Yazdi, A. H. Synthesis 2006, 1631-1634.
Supplementary Information Table S-1: Summary of quality control data of six analytical batches of urine samples Method Detection Limits (MDLs) Method Reporting Limits (MRLs) Standard Reference Material (SRM) NIST 1640a Laboratory Fortified Blank (BS) mean SD mean SD % % % % % % % Rec. SD % Rec. SD 0.22 0.27 0.49 6.71 − − 0.05 1.01 0.01 − 100.33 7.81 0.32 0.43 2.51 3.67 − 100.00 10.41
0.20 0.11 1.18 0.01 − 83.50 0.71 0.13 0.04 1.05 0.01 − 102.17 8.86 0.14 0.05 1.04 0.02 − − 92.50 15.07 SD: Standard deviation; % Rec: Expected percent recovery: 75-125% , % RPD: Expected relative percent difference: <25% Minimum limits of detection; tAs (0.01 µg L-1), As+5 (0.10 µg L-1), As+3 (0.10 µg L-1), MMA (0.12 µg L-1), DMA (0.10 µg L-1), AsB (0.10 µg L-1)
Supplementary Table 1: HPV type-specific longitudinal prevalence HIV negative HIV positive Visit 1 HPV Prevalence n/N (%) Visit 2 HPV Prevalence n/N (%) Visit 1 HPV Prevalence n/N (%) Visit 2 HPV Prevalence n/N (%) High-risk HPV types HPV-16 1/72 (1.4) 3/38 (7.9) 10/93 (10.8) 5/47 (10.6) HPV-18 0/72 (0) 1/38 (2.6) 6/93 (6.5) 2/47 (4.3) HPV-26 0/72 (0) 0/38 (0) 0/93 (0) 0/47 (0) HPV-31 0/72 (0) 0/38 (0) 4/93 (4.3) 1/47 (2.1) HPV-33 1/72(1.4) 0/38 (0) 1/93 (1.1) 1/47 (2.1) HPV-35 1/72 (1.4) 2/38 (5.3) 6/93 (6.5) 2/47 (4.3) HPV-39 1/72 (1.4) 2/38 (5.3) 5/93 (5.4) 3/47 (6.4) HPV-45 3/72 (4.2) 1/38 (2.6) 8/93 (8.6) 7/47 (14.9) HPV-51 0/72 (0) 0/38 (0) 4/93 (4.3) 2/47 (4.3) HPV-52 2/72 (2.8) 0/38 (0) 11/93 (11.8) 9/47 (19.1) HPV-53 1/72 (1.4) 1/38 (2.6) 5/93 (5.4) 4/47 (8.5)
where Ai, Pi and hi are the geometrical surface area, the perimeter and the thickness of particles i, respectively; and mn is the weight of n particles. The equivalent particle diameter (dp) can be given by the following expression: (2)
lines; and AGW, PFAA-AGW, and permanganate-PFAA-AGW were carried through the dotted lines. Adapted from McKenzie et al. (2015). 1.2. Materials The compositions of artificial ground (AGW; made per Guelfo and Higgins (2013)), AGW amended with nominal 2 µg/L PFAA (PFAA-AGW), and AGW amended with an oxidant and nominal 2 µg/L PFAA (oxidant-PFAA-AGW) are shown in Table S1. Table S1 - Composition of source waters (adapted from McKenzie et al., 2015) Source water Components Influent pH Ionic strength Salinity (‰) Fe (mM) Artificial groundwater (AGW) Millipore water + 0.01 mM MnSO4 + 1.27 mM Na2SO4 + 1.93 mM NaCl + 0.48 mM NaHCO3 7.5 0.0056 0.33 0.0 PFAA-AGW AGW + 2 μg/L each PFAA 7.5 0.0056 0.33 0.0 Persulfate PFAA-AGW + 52.1 mM Na2S2O8 + 26.0 mM + 5.2 mM C6H8O7 1.9 0.2633 17.03 26.0 Permanganate PFAA-AGW + 8.4 mM 7.8 0.0140 1.66 0.0 Catalyzed hydrogen peroxide PFAA-AGW + 14.7 mM H2O2 + 0.5 mM 3.4 0.0076 0.91 0.5
Table S1a Comparison of time required for zero cell count for batch mode cell-killing Amount of Ag-AC (mg/ml) Velocity (cm/min) of E.coli in cell suspension Time required for reaching zero cell count (min) 2 1500 35 4 1500 25 6 1500 25 8 1500 25 intracellular reaction (step d) is the rate limiting step, whenever a minimum amount of Ag-NP (2 mg/ml) is assured. The minimum required time of 25 min. is indicative of the intracellular reaction step. This numerical value may increase when transport limitations are there. Table S1b Comparison of time required for zero cell count for continuous mode cell-killing Column diameter for continuous mode cell-killing Amount of Ag-AC (mg/ml) Velocity (cm/min) of E.coli cell suspension Time required for reaching zero cell count (min) 1 cm 737 1.15 20 5 cm 764 1.12 22 8 cm 793 1.07 23
Table S2 Comparison of different parameters with previous works for batch mode silver release experiments System description State of nanoparticle Coating agent Initial silver loading (mg/L) Sotiriou et al. (2012, Langmuir) Ag-SiO2 dispersed in deionized water Ag-NP attached on SiO2 No coating agent 40 Kittler et al. (2010, Chem. Mater.) Ag-NP dispersed in ultrapure water and placed inside a dialysis bag Free Ag-NP Sodium citrate 140 Peretyazhko et al. (Environ. Sci. Technol., 2014) Ag-NP dispersed in Milli-Q water Free Ag-NP Methoxyl polyethylene glycol (PEGSH) 8 Present work Ag-AC dispersed in Milli-Q water Ag-NP adsorbed AC Tri-sodium citrate 16 Sotiriou et al. (2012) did not have any coating agent (Table S2) to prevent silver release from the NP, which causes the Ag concentration to bulid-up at the fastest rate amongst these four reports. Absence of coating agent also accelerates the steady state value in this case. Finally,
PMS-methanol 0.0292 0.0106 BDD-tert-butanol 0.0123 0.0095 PDS-tert-butanol 0.0174 0.0102 PMS- tert-butanol 0.0235 0.0115 Table S4. Estimation of the relative contribution of involved reactive species in electrochemical activation of PDS process. Process Reactive species Apparent degradation rate of CBZ (min-1) Contribution BDD DET + HO• 0.0578 PDS DET + HO• + nonradical + PDS 0.1135 100% BDD-methanol DET 0.0135 11.89% PDS-methanol DET + nonradical + PDS 0.0201 nonradical 0.0040 3.52% HO• 0.0934 82.21% PDS 0.0027 2.38% Table S5. Estimation of the relative contribution of involved reactive species in electrochemical activation of PMS process. Process Reactive species Apparent degradation rate of CBZ (min-1) Contribution BDD DET + HO• 0.0578 PMS DET + HO• + nonradical + PMS 0.3129 100% BDD-methanol DET 0.0135 4.31% PMS-methanol DET + nonradical + PMS 0.0292 nonradical 0.0122 3.90%
REFERENCES Carr, S. A., Liu, J., Tesoro, A. G., 2016. Transport and fate of microplastic particles in wastewater treatment plants. Water Research 91, 174-182. Mintenig, S. M., Int-Veen, I., Löder, M. G. J., Primpke, S., Gerdts, G., 2017. Identification of microplastic in effluents of waste water treatment plants using focal plane array-based infrared imaging. Water Research 108, 365-372. Qiu, Q., Tan, Z., Wang, J., Peng, J., Li, M., Zhan, Z., 2016. Extraction, enumeration and identification methods for monitoring microplastics in the environment. Estuarine Coastal and Shelf Science 176, 102-109. Underwood, A. J., Chapman, M. G., Browne, M. A., 2017. Some problems and practicalities in design and interpretation of samples of microplastic Analytical Methods 9, 1332-1345.
IS_Atrazine-13C3 219.100 177.000 106 23 8 219.100 69.900 106 47 8 IS_Benzotriazole-D4 124.086 69.000 106 31 8 124.086 41.100 106 49 10 IS_BisphenolA-13C12 239.000 224.000 -85 -24 -11 239.000 223.000 -85 -40 -11 IS_Caffeine-D3 198.135 138.000 36 27 18 198.135 110.000 36 31 14 IS_Cotinine-D3 180.095 80.000 56 29 10 180.095 101.000 56 31 18 IS_DEET-D7 199.192 126.000 121 23 6 199.192 98.000 121 41 10 IS_Diazinon-D10 314.926 170.000 131 29 26 314.926 154.000 131 29 20 IS_Diclofenac-D4 297.775 253.900 -15 -16 -23 297.775 216.900 -15 -30 -13 IS_Imidacloprid-D4 259.989 213.000 36 21 12 259.989 179.100 36 27 10 IS_IsoproturonD3 210.131 74.900 91 21 8 210.131 49.000 91 31 12 IS_Mecoprop-D3 215.900 143.900 -25 -18 -7 217.900 145.900 -25 -18 -7 IS_Metolachlor-D6 290.166 258.100 56 19 12 290.166 182.100 56 35 10 IS_Mono-isobutyl-phthalate-D4 224.993 81.000 -30 -22 -9 224.993 181.100 -30 -14 -11 IS_Nitrophenol-D4 141.927 112.000 -50 -24 -7 141.927 95.900 -50 -32 -11
IS_Sulfamethoxazole-D4 258.106 95.900 111 35 10 258.106 111.900 111 31 14 IS_Tebuconazole-D9 317.046 70.000 51 61 18 317.046 124.900 51 57 14 IS_Triclosan-D3 290.000 35.000 -35 -40 -15 292.000 35.000 -35 -40 -15 IS_Tri-n-butylphosphate-D27 294.303 101.900 66 25 26 294.303 82.900 130 44 10
Rainbow Trout Growth 1900 U.S. Environmental Protection Agency Pesticide Ecotoxicity Database (Formerly: Environmental Effects Database (EEDB)) Environmental Fate and Effects Division, U.S.EPA, Washington, D.C.: 1992 Daphnia Reproduction 1050 U.S. Environmental Protection Agency Pesticide Ecotoxicity Database (Formerly: Environmental Effects Database (EEDB)) Environmental Fate and Effects Division, U.S.EPA, Washington, D.C.: 1992 Tramadol Daphnia magna Reproduction 8500 Le,T.H., E.S. Lim, S.K. Lee, J.S. Park, Y.H. Kim, and J. Min Toxicity Evaluation of Verapamil and Tramadol Based on Toxicity Assay and Expression Patterns of Dhb, Vtg, Arnt, CYP4, and CYP314 in Daphnia magna Environ. Toxicol.26(5): 515-523 2011 Trimethoprim rerio Reproduction 157 Madureira,T.V., M.J. C. Cruzeiro, M.H. Galante, R.A.F. Monteiro, and E. Rocha The Toxicity Potential of Pharmaceuticals Found in the Douro River Estuary (Portugal): Assessing Impacts on Gonadal Maturation with a Histopathological and Stereological Study of Zebrafish Ovary and Testis After Sub-Acu Aquat. Toxicol.105(3/4): 292-299 2011 Daphnia magna Reproduction 6250 De Liguoro,M., V. Di Leva, M. Dalla Bona, R. Merlanti, G. Caporale, and G. Radaelli Sublethal Effects of Trimethoprim on Four Freshwater Organisms Ecotoxicol. Environ. 2012 Algae Population 40000 Yang,L.H., G.G. Ying, H.C. Su, J.L. Stauber, M.S. Adams, and M.T. Binet Growth-Inhibiting Effects of 12 Antibacterial Agents and Their Mixtures on the Freshwater Microalga Pseudokirchneriella subcapitata Environ. Toxicol. Chem.27(5): 1201-1208 2008
Fig. 13C NMR (100 MHz) spectrum of 3-(5-chlorothiophen-2-yl)-5-(4-fluorophenyl)-1-phenyl-4,5-dihydro-1H-pyrazole 5b. Fig. 13C NMR (100 MHz) spectrum of 5g. Fig. 13C NMR (100 MHz) spectrum of 1-(5-chlorothiophen-2-yl)-3-(4-methylphenyl)prop-2-en-1-one, 3d. Fig. 13C NMR (100 MHz) spectrum of 1-(5-chlorothiophen-2-yl)-3-(4-methoxyphenyl)prop-2-en-1-one, 3e.
Substance Na-percarbonate avlogEC50 0.969 Number of species 2 Trophic levels covered 2 Reliability Species Trophic level Duration EC50 (mg/L) Type Source 1 Daphnia pulex Invertebrate 48 h 4.9 Acute ECHA (1989) 2 Pimephales promelas Fish 96 h 70.7 Acute ECHA (1989) Substance TAED avlogEC50 3.000 Number of species 1 Trophic levels covered 1 Reliability Species Trophic level Duration EC50 (mg/L) Type Source 1 Daphnia magna Invertebrate 21d 1000 Chronic ECHA (2008) Substance STP avlogEC50 1.988 Number of species 5 Trophic levels covered 3 Reliability Species Trophic level Duration EC50 (mg/L) Type Source 2 rerio Fish 96 h 10 Chronic ECHA (Sinha and Kanamadi,2000) 4 Cladoceran dubia Invertebrate 48 h 276.61 Acute ECHA (Warne and Schifko, 1999) 3 Ceriodaphnia Invertebrate 24 h 290.2 Acute ECHA (2004) 3 Daphnia magna Invertebrate 50h 1089 Acute IUCLID (Huber, 1987) 2 Desmodesmus subspicatus Algae 96 h 160 Acute ECHA (1985) Substance PEG avlogEC50 3.048 Number of species 2 Trophic levels covered 1 Reliability Species Trophic level Duration EC50 (mg/L) Type Source unknown Carassius auratus Fish 24 h 5000 Acute PAN (Bridie et al., 1979) unknown Salmo salar Fish 96 h 1000 Acute PAN (Wildish, 1974) Substance Na-silicate avlogEC50 2.249 Number of species 7 Trophic levels covered 3 Reliability Species Trophic level Duration EC50 (mg/L) Type Source
2 Oncorhynchus mykiss Fish 96 h 285 Acute ECHA (Maruyama et al., 1989) 1 Danio rerio Fish 96 h 1108 ECHA (1988) 2 Danio rerio Fish 96 h 210 Acute OECD SIDS (Richterich and Mühlberg, 2001) 4 Lepomis macrochirus Fish 96 h 389.5 Acute ECHA (1991) 2 Daphnia magna Invertebrate 48 h 1700 Acute ECHA (1997) 4 Daphnia Invertebrate 96 h 231.5 ECHA (Dowden and Bennett, 1965) 2 Lymnaea sp. eggs Invertebrate 96 h 632 Acute ECHA (Dowden and Bennett, 1965) 2 Hyallela sp. Invertebrate 96 h 160 Acute ECHA (Dowden and Bennett, 1965) 2 Desmodesmus subspicatus Algae 72 h 207 Acute ECHA (1995) Substance Na-carbonate avlogEC50 2.265 Number of species 8 Trophic levels covered 3 Reliability Species Trophic Duration EC50 (mg/L) Type Source 2 Lepomis macrochirus Fish 96 h 300 Acute ECHA (Cairns and Scheier, 1959) 2 Gambusia affinis Fish 96 h 740 Acute ECHA (Wallen et al., 1957) 4 Mollienesia latipinna Fish 96 h 297 Acute ECHA (Dowden and Bennett, 1965) 4 Lepomis macrochirus Fish 96 h 385 Acute ECHA (Dowden and Bennett, 1965) 2 Ceriodaphnia sp. Invertebrate 48 h 213.5 Acute ECHA (Warne and Schifko, 1999) 4 Daphnia magna Invertebrate 48 h 265 Acute ECHA (Dowden and Bennett, 1965) 4 Dugesia sp. Invertebrate 48 h 360 Acute ECHA (Dowden and Bennett, 1965) 4 sp. Invertebrate 48 h 600 Acute ECHA (Dowden and Bennett, 1965) 4 Nitzschia sp. Algae 120 h 242 Chronic IUCLID (Patrick et al., 1968)
Table S2 Blocks, GPs and villages of Patna in Bihar surveyed and the number of samples analyzed from each village along with samples having As >10 µg/l and >50 µg/l in this study Sl No Block GP Village Number of samples Number of samples having As >10 µg/l Number of samples having As >50 µg/l 1 Maner Kitta chawhatar(paschim) Badal Tola 69 69 67 2 Maner Chawhatar(paschim) Benikarai tola 16 16 14 3 Maner Chawhatar purba Chhihantar 33 24 0 4 Maner Hatitola Dhajawa tola 45 38 36 5 Maner Chawhatar purba Dubhaila 53 53 44 6 Maner Kitta chawhatar(paschim) Harijan tola 29 28 25 7 Maner Hatitola Hati tola 28 28 23 8 Maner Hatitola Islamganj 36 36 5 9 Maner Chhihantar Mahabir tola 19 19 18 10 Hatitola Muji tola 15 15 11 11 Maner Kitta chawhatar(paschim) New tola (haldichhapara) 41 41 41 12 Maner Kitta chawhatar(paschim) Purantola (haldichhapara) 54 54 53 13 Maner Kitta chawhatar(paschim) Ramnagar 20 20 17 14 Maner Magarpal Ratan tola 73 70 65 15 Maner Kitta chawhatar(paschim) Sa anna (haldichhapara) 20 20 15 16 Maner chawhatar(paschim) Siwdihal raiketola 16 16 16 17 Maner Sadikpur Srinagar 18 1 1 18 Danapur Kasim chak Bara kashim chak 14 8 1 19 Danapur Danapur municipal Chhitnawan 29 0 0 20 Danapur Kasimchak Chhoteka kasim chak 14 14 12 21 Danapur Danapur municipal Daudpur 47 1 0 22 Danapur Kasimchak Firangi bhagatka tola 14 11 3
Table S3 The statistics of the experimentally derived Abraham parameters. Compound Parameter Estimate Standard error N SD Adjusted R2 P value RDX S 2.249 0.394 5 0.421 0.995 0.003 A 0.491 0.177 B 0.637 0.163 HMX S 2.774 1.013 5 1.082 0.986 0.009 A 0.684 0.455 B 1.136 0.419 DNX S 2.287 0.330 5 0.353 0.996 0.002 A 0.447 0.148 B 0.567 0.137 MNX S 2.266 0.615 4 0.523 0.993 0.055 A 0.480 0.220 B 0.593 0.230 TNX S 2.093 0.365 5 0.390 0.995 0.003 A 0.330 0.164 B 0.602 0.151 TNT S 1.809 0.571 5 0.610 0.982 0.011 A 0.012 0.257 B 0.683 0.236 TNB S 1.664 0.730 5 0.780 0.971 0.017 A 0.061 0.328 B 0.708 0.302 4NAN S 1.292 0.030 5 0.033 1.000 0.000 A 0.030 0.014 B 0.398 0.013
Table S5 List of pp-LFERs used for model validation. System pp-LFER equation Reference Air-water log K= -0.994+0.577E+2.549S+3.813A+4.841B-0.869V 1 Organic carbon-water log K = 0.67+1.075E-0.277S-0.363A-1.697B+1.468V 8 Water solubility log K = 0.368-0.711E+0.407S+1.73A+3.383B-3.493V-1.036AB-0.005 (mp-25) where mp = melting point (°C) 9 Table S6 Physical-chemical properties of experimental measurements and model predictions. Property Compound Exp-APa Observed Organic (log Koc, L∙kg-1) RDX 2.09 -0.31 1.8010 2.0012 HMX 2.06 -0.68 TNT 2.53 2.85 2.7212 TNB 2.28 2.60 1.8814 Water-air (log Kwa, Lair/Lwater) RDX 9.43 15.18 9.1015 HMX 13.76 20.31 12.9715 TNT 6.56 6.56 6.3515 Water solubility RDX -2.24 2.34 -3.7216 -3.7213
Table S1 Information of the study area and the sampling sites along the Hailuogou Glacier foreland Altitude (m a.s.l.) Dominant plants 2940 Salix rehderiana, Astragalus adsurgens Pall., Hippophae rhamnoides L. 2920 Populus purdomii Rehder (half-mature) 2910 Betula albosinensis Burk, Abies fabri (Mast.) Craib (half-mature) 2890 Abies fabri (Mast.), Craib Picea brachytyla (Franch.) E.Pritz. 2850 Picea brachytyla (Franch.) E.Pritz., Abies fabri (Mast.) Craib The date represents the soil exposure time since the glacier retreat (Zhong et al., 1999).
qt = k2qe2t/(1+k2qet) (S2) where qt and qe (mg g-1) correspond to the adsorbed amount at time t (min) and at the equilibrium time, respectively, and the constant k2 [g (mg min)-1] is the pseudo-second order rate coefficient (Gupta and Bhattacharyya, 2011;Simonin et al., 2016). Table S1 Parameters of the non-linear modeling using the pseudo-first and pseudo-second order kinetic for adsorption of As(V) on Mg-Fe LDH. pH 5.5 pH 8.5 Pseudo-first order qe(exp) (mg g-1) 7.79 7.18 qe (mg g-1) 7.69 6.69 k1 (min-1) 0.46 0.25 R2 0.97 0.93 Pseudo-second order qe (mg g-1) 8.07 7.22 k2 [g (mg min)-1] 0.10 0.05 R2 0.99 0.99 Fig. S2. pHPZC of Mg-Fe LDH determined by the immersion technique. Equilibrium adsorption experiments The non-linear form of the Langmuir equation is given by: qe =qmaxKLce/(1+KLce) (S3) where ce and qe correspond to the equilibrium concentration in the solution (mg L-1) and the adsorbed amount at equilibrium (mg g-1), respectively. The parameters qmax and KL are the maximum adsorption capacity (mg g-1) and the Langmuir constant related to the affinity to
SM-15. OCPs in and sediments sampled in Mexico since 2000. Ranges, arithmetic means ± s.d., geometric means (GM) (ng g-1 d.w.)a SM-15. OCPs in soils and sediments sampled in Mexico since 2000. Ranges, arithmetic means ± s.d., geometric means (GM) (ng g-1 d.w.)a a) Summed residues consist of one or more of the following compounds (see individual for details): ΣDDT = p,p’- and o,p’- isomers of DDE, DDD, DDT; ΣHCH = α-HCH + β-HCH + γ-HCH + δ-HCH; ΣCHL = TC + CC + HEPT + HEPX. b) Ranges of means or geometric means indicate separate compilations for different regions or communities. c) Abbreviations of Mexican states: BAJ – Baja, CAM – Campeche, CHH – Chihuahua, CHP – Chiapas, MEX – Mexico, MOR – Morelos, NUE – Nuevo Leon, PUE – Puebla, VER – Veracruz, SIN – Sinaloa, SON – Sonora; ROO – Quintana Roo; TAB – Tabasco. d) Concentrations in the original paper were mistakenly reported as μg g-1, corrected to ng g-1 by correspondence. e) Blank in this space means sampling date not given. f) number: means for upper 3.4 cm sediment layer in two cores; lower number: means for downcore sediments (to 95 cm in one core and 145 cm in the other).
Zr 0.048 ± 0.004 0.253 ± 0.012 0.273 ± 0.015 1.313 ± 0.166 11.343 ± 3.558 34.347 ± 3.686 2.807 ± 0.922 0.070 ± 0.010 0.110 ± 0.026 0.123 ± 0.012
S3 Physiochemical characteristics of four filtered water samples (site 1, 15, 17, and 21) collected from April 2016 and November 2016 (mean value with standard deviation in parenthesis). Sampling date pH K+ Na+ Ca2+ Mg2+ SO42- Cl- HCO3- CO32- mg L-1 April 2016 impoundment) 8.31 (0.26) 6.06 (0.59) 48.4 (1.68) 30.0 (1.88) 19.7 (1.46) 31.1 (3.66) 37.5 (5.14) 107 (9.45) 5.07 (1.07) November 2016 (late impoundment) 8.19 (0.34) 7.64 (0.42) 42.2 (2.37) 21.0 (3.47) 16.4 (1.28) 37.5 (2.89) 41.8 (5.78) 93 (8.79) 3.69 (0.79)
Table S2 Charge density of atoms in N-rGO and rGO model N and C atoms N-rGO rGO Pyridinic N and the adjacent C atoms α -0.21 - C1 0.08 1.03 C2 -0.22 -0.41 Pyrrolic N and the adjacent C atoms β1 -0.21 - C3 -0.08 0.79 C4 -0.24 0.79 β2 -0.21 - C5 -0.16 0.79 C6 -0.03 0.79 Graphitic N and the adjacent C γ1 0.10 - C7 0.39 0.004 C8 0.20 0.004 C9 0.19 0.11 γ2 -0.02 - C10 0.06 0.004 C11 0.15 -0.36 C12 0.98 0.60