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  1. Free, publicly-accessible full text available January 23, 2025
  2. A D-band (110‒170 GHz) SiC substrate-integrated waveguide (SIW) is characterized on-wafer by two different vector network analyzers (VNAs): a 220-GHz single-sweep VNA and an 110-GHz VNA with WR8 (90‒140 GHz) and WR5 (140‒220 GHz) frequency extenders. To facilitate probing, the SIW input and output are transitioned to grounded coplanar waveguides (GCPWs). Two-tier calibration is used to de-embed the SIW-GCPW transitions as well as to extract the intrinsic SIW characteristics. In general, the two VNAs are in agreement and both result in an ultra-low insertion loss of approximately 0.2 dB/mm for the same SIW, despite stitching errors at band edges. 
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  3. Abstract Aim The microbial metabolic quotient (MMQ; mg CO 2 ‐C/mg MBC/h), defined as the amount of microbial CO 2 respired (MR; mg CO 2 ‐C/kg soil/h) per unit of microbial biomass C (MBC; mg C/kg soil), is a key parameter for understanding the microbial regulation of the carbon (C) cycle, including soil C sequestration. Here, we experimentally tested hypotheses about the individual and interactive effects of multiple nutrient addition (nitrogen + phosphorus + potassium + micronutrients) and herbivore exclusion on MR, MBC and MMQ across 23 sites (five continents). Our sites encompassed a wide range of edaphoclimatic conditions; thus, we assessed which edaphoclimatic variables affected MMQ the most and how they interacted with our treatments. Location Australia, Asia, Europe, North/South America. Time period 2015–2016. Major taxa Soil microbes. Methods Soils were collected from plots with established experimental treatments. MR was assessed in a 5‐week laboratory incubation without glucose addition, MBC via substrate‐induced respiration. MMQ was calculated as MR/MBC and corrected for soil temperatures (MMQsoil). Using linear mixed effects models (LMMs) and structural equation models (SEMs), we analysed how edaphoclimatic characteristics and treatments interactively affected MMQsoil. Results MMQsoil was higher in locations with higher mean annual temperature, lower water holding capacity and lower soil organic C concentration, but did not respond to our treatments across sites as neither MR nor MBC changed. We attributed this relative homeostasis to our treatments to the modulating influence of edaphoclimatic variables. For example, herbivore exclusion, regardless of fertilization, led to greater MMQsoil only at sites with lower soil organic C (< 1.7%). Main conclusions Our results pinpoint the main variables related to MMQsoil across grasslands and emphasize the importance of the local edaphoclimatic conditions in controlling the response of the C cycle to anthropogenic stressors. By testing hypotheses about MMQsoil across global edaphoclimatic gradients, this work also helps to align the conflicting results of prior studies. 
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