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Supporting information for: [https://doi.org/10.1021/acs.jnatprod.8b00390] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/3096]

Supplementary material for: [https://doi.org/10.1007/s00894-017-3570-y] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2103]

Supplementary material for: [https://doi.org/10.1016/j.ejmech.2017.10.045] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2075]

The data provided in these files have been generated/collected during the study on the effect of buffer on the development of electro-active biofilms (EABfs). These data contain measured current density, acetate concentrations, and biofilm development over time. 

Bio-carbonates from Well NK1 were sampled from every chip using a micro-drill. Twenty-four chips were drilled twice and the duplicate samples were used for quality control. Sub-samples of 50 mg were firstly leached with 0.3 N acetic acid and Milli-Q water for 30 min to remove absorbed salt. Rinsed samples were placed in 1.5 ml of 1.0 N acetic acid and sonicated for 2 hrs. Elemental compositions of the carbonate phase were firstly measured on the ICP-MS using 0.5 mL of supernatant. Elemental concentrations and 87Sr/86Sr isotope of insoluble residue from one sample (NK1-Nd-73 at 721.85 m) were measured. Insoluble residue of this sample was digested using a mixture of HNO3 (0.2 ml) and HF (0.8 ml). Following a modified procedure by Deniel and Pin (2001), one-half milliliter of supernatant was loaded to the preconditioned Sr-Spec columns to separate strontium. Strontium-isotope ratios were measured on a Nu Plasma high-resolution (HR) multi-collector ICP-MS at the Radiogenic Isotope Facility, University of Queensland. The standard deviation of triple measurements is 0.000009 on average. During the course of measurements, analyses of NBS SRM987 yield a mean 87Sr/86Sr ratio of 0.710222 ± 20 (2σ). All data are normalized to 86Sr/88Sr = 0.1194 and the 87Sr/86Sr are corrected to SRM987 =0.710249 ± 28 (2σ) to reflect the long-term drift. *Median standard deviations for triple measurements.**Median standard deviation incorporating the external SRM987 errors with measurement errors of samples and the standard.

Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2865] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2858] Supplementary material for: [https://www.sciencedirect.com/science/article/pii/S0277538719301664?via%3Dihub]

Data underlying the article: "Ultrahigh Dynamic Range and Low Noise Figure Programmable Integrated Microwave Photonic Filter". The data set consists of several different measurement results for the modulation transformer, double injection ring resonator, and microwave photonic filter responses as published in the resource article. All data is stored in files using the CSV-format. The set is structered to give the data per figure (subfigure), where each subfigure has a folder containing a README-file describing the data in that folder. Integrated Optics, Microwave Photonics, Si3N4 NWO Vidi grant 15702 NWO Start-up grant 740.018.021

Understanding the scaling between leaf size and leafing intensity (leaf number per stem size) is crucial for comprehending theories about the leaf costs and benefits in the leaf size–twig size spectrum. However, the scaling scope of leaf size vs. leafing intensity changes along the twig leaf size variation in different leaf habit species remains elusive. Here, we hypothesize that the numerical value of scaling exponent for leaf mass versus leafing intensity in twig is governed by the minimum leaf mass versus maximum leaf mass (Mmin vs. Mmax) and constrained to be ≤ -1.0. We tested this hypothesis by analyzing the twigs of 123 species datasets complied in the subtropical mountain forest. The standardized major axis regression (SMA) analyses showed the Mmin scaled as the 1.19 power of Mmax and the -a (-1.19) was not statistically different from the exponents of Mmin vs. leafing intensity in whole data. Across leaf habit groups, the Mmax scaled negatively and isometrically with respect to leafing intensity. The pooled data's scaling exponents ranged from -1.14 to -0.96 for Mmin and Mmax vs. the leafing intensity based on stem volume (LIV). In the case of Mmin and Mmax vs. the leafing intensity based on stem mass (LIM), the scaling exponents ranged from -1.24 to -1.04. Our hypothesis successfully predicts that the scaling relationship between leaf mass and leafing intensity is constrained to be ≤ -1.0. More importantly, the lower limit to scaling of leaf mass and leafing intensity maybe closely correlate with Mmin vs. Mmax. Besides, constrained by the maximum leaf mass expand, the broad scope range between leaf size and number may be insensitive to leaf habit groups in subtropical mountain forest. A total of 68 and 75 species were sampled from the two sites (Table 1). The total number of sampled species was 123 (including 20 overlapping species) belonging to 92 genera of 53 families. In August 2016 and 2017, three to five current-year undamaged, healthy twigs from three individuals of each species were randomly selected. All of the leaves (with petioles) on each twig were removed and counted (NL). Twig diameter (D) and length (L) were measured using a vernier caliper, with an accuracy of 0.1 mm (Milla, 2009). The stem volume of each twig (Vstem, mm3) was estimated using L and D assuming stems are cylindrical. Stems and leaves were brought to the laboratory where they were oven-dried at 75 ºC to determine total leaf mass (Mleaf) and stem mass (Mstem). Each leaf of each twig was subsequently scanned and its area was calculated using the Image J software (Image J 1.2v; National Institutes of Health, USA). Then, we multiplied the area of the largest and smallest leaf per twig by leaf mass per area (LMA, total leaf mass divided by total leaf area) to estimate the maximum and minimum leaf mass per twig, respectively. The volume-based leafing intensity (LIV) is here defined as NL / Vstem; the mass-based leafing intensity (LIM) is here defined as NL / Mstem. This dataset contains the leaf traits of 123 woody species.