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Crucial to plant development, ambient temperature triggers intricate mechanisms enabling adaptive responses to temperature variations. The precise coordination of chromatin modifications in shaping cell developmental fate under diverse temperatures remains elusive. Our study, integrating comprehensive transcriptome, epigenome profiling, and genetics, demonstrates that lower ambient temperature (16°C) partially restores developmental defects caused by H3K27me3 loss in prc2 mutants by specifically depositing H2A.Zub at ectopically expressed embryonic genes in Arabidopsis, such as ABA INSENSITIVE 3 (ABI3) and LEAFY COTYLEDON 1 (LEC1). This deposition leads to downregulation of these genes and compensates for H3K27me3 depletion. Polycomb-repressive complex 1 (PRC1)-catalyzed H2A.Zub and PRC2-catalyzed H3K27me3 play roles in silencing transcription of embryonic genes for post-germination development. Low-temperature-induced reduction of TOE1 protein level decelerates H2A.Z turnover at specific loci, sustaining repression of embryonic genes and alleviating requirement for PRC2-H3K27me3 at post-germination stage. Our findings offer mechanistic insights into the cooperative epigenetic layers, facilitating plant adaptation to varying environmental temperatures. 

The atomic force microscopy (AFM) technology is a promising method for nanofabrication due to the high tunability of this affordable platform. The quality inspection and control significantly impact the manufacturing effectiveness for realizing the functionality of the achieved nanochannel. Particularly, the surface characteristics of nanochannel sidewalls, which play a significant role in determining the quality of the nanomachined products, can not be accurately captured using conventional surface integrity metrics (e.g., surface roughness). Therefore, it is necessary to propose a method to quantitatively characterize the surface morphology and detect the abnormal parts/regions of the nanochannel sidewall. This paper presents a statistical process control approach derived from the self-affine fractal model to detect the sidewall surface anomalies. It evaluates changes in the self-affine fractal model parameters (standard deviation, correlation length, and roughness exponent), which can be used to signify the changes on the sidewall surface; the statistical distributions of these parameters are derived and used to develop control charts to allow inspection of the sidewall morphology. The approach was tested on the AFM-based nanomachined samples. The results suggest that the presented approach can effectively reflect the abnormal regions on the machined parts, which opens up a new avenue toward guiding the quality control and rework for process improvement for AFM-based nanomachining. 

Atomic force microscope (AFM)-based nanomanufacturing offers an affordable and easily deployable method for fabricating high-resolution nanopatterns. This study employs a comprehensive design of experiment (DOE) approach to investigate the effects of various parameters, such as voltage, speed, and vibration axis, on the width and depth of lithography patterns using electrical field and vibration-assisted lithography on PEDOT: PSS films. The DOE explores the effect of voltage and speed on the process of electrical field and vibration-assisted AFM-based nanopatterning in two vibration trajectories: a circular trajectory employing X and Y axis vibration and a reciprocating trajectory employing Y axis vibration. The results indicate that using circular XY-vibration with a low stiffness contact probe and optimized speed and voltage factors results in higher depth and width of the lithography patterns compared to Y-vibration alone at the same parameters as expected. In both cases, pattern width was dominantly controlled by the voltage. Regarding depth, in XY-vibration, the speed of the tip is the most significant factor, while for Y-vibration, voltage plays the most significant role. It is noteworthy that there is a minimum threshold of speed that can produce a pattern; for example, the high-speed level that produced patterns in the circular trajectory (XY-vibration) did not produce patterns in reciprocating motion (Y-vibration). In conclusion, the study demonstrates the significant impact of voltage, speed, and axis on the width and depth of the lithography patterns. These findings can be instrumental in developing and understanding AFM-based high-resolution nanofabrication techniques. 

Methane (CH4) emissions in Stordalen Mire (northern Sweden), estimated via two different approaches: "Paint by number" (field ch4_modified_prj.tif): CH4 emission across the landscape calculated via “paint-by-number” approach, using 2014 autochamber-based flux measurements (https://doi.org/10.5281/zenodo.14052690) mapped to landcover classifications (https://doi.org/10.5281/zenodo.15042233). DNDC-modeled (Modeled CH4.tif): CH4 emission across the landscape modeled via Wetland-DNDC (https://www.dndc.sr.unh.edu/), driven by remotely sensed landcover classifications (https://doi.org/10.5281/zenodo.15042233), water table depth (https://doi.org/10.5281/zenodo.15092752), climate data (provided by the Abisko Scientific Research Station), and soil parameters (defined as in Deng et al. 2014, 2017). The DNDC model was run on vegetation and water table clusters (determined by k-means clustering), and model output was spatially assigned to each map pixel. Modeled CH4 emissions account for CH4 production from DOC (Randomforest_stack_epsg32634_extent_kmeansclass10_CH4 prod from DOC.tif) and from CO2 (Randomforest_stack_epsg32634_extent_kmeansclass10_CH4 prod from CO2.tif), minus oxidation (Randomforest_stack_epsg32634_extent_kmeansclass10_CH4 oxid.tif). The model also outputs a map of CH4 isotopic composition (δ13C-CH4) of emissions (Randomforest_stack_epsg32634_extent_kmeansclass10_Delta CH4 flux.tif). The difference between these approaches is provided as a difference map (CH4diff.tif), calculated as the "paint-by-number" (PBN) emissions (field ch4_modified_prj.tif) minus the Wetland-DNDC modeled emissions (Modeled CH4.tif). These images are GeoTIFFs with embedded georeferencing information. FUNDING: National Aeronautics and Space Administration, Interdisciplinary Science program: From Archaea to the Atmosphere (award # NNX17AK10G). National Science Foundation, Biology Integration Institutes Program: EMERGE Biology Integration Institute (award # 2022070). United States Department of Energy Office of Biological and Environmental Research, Genomic Science Program: The IsoGenie Project (grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440). National Science Foundation, MacroSystems program (grant # EF-1241037). We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. 

Understanding the kinetics of nanobubbles encapsulated by ultrathin two-dimensional (2D) layered van der Waals crystal membranes on atomically flat substrates is important to the applications of 2D materials and the pursuit of 2D nanobubble technologies. Here, we investigate the controlled motion of monolayer molybdenum disulfide (MoS2)-encapsulated nanobubbles on flat hexagonal boron nitride substrates using atomic force microscopy (AFM). Our study reveals a distinct transition from standstill bubble deformations to stable, stepwise bubble translations on flat substrates. The membrane tension-dominated 2D nanobubble behaves like an elastic soft body in its collision interaction with the AFM tip. This delicate motion-control technique enables neighboring 2D nanobubbles to move closer and eventually coalesce into larger nanobubbles. These findings pave the way for high-precision manipulation of nanobubbles and facilitate the exploration of their emerging applications. 

Vibration-assisted atomic force microscopy (AFM)-based nanomachining is a promising method for the fabrication of nanostructures. During mechanical nanomachining, the geometry of the tooltip and workpiece interface is sensitive to variations in the depth of cut, the material grain size, and system vibrations; understanding the underlying uncertainties is essential to improve the process capability. This paper investigates process uncertainties and their impacts on the achieved surface geometries based on an experimental study of AFM-based nanomachining. The variations and biases of the achieved surface characteristics (compared to the theoretical geometries) are observed and identified as the torsional deflections on the AFM probe. A physical-based model combined with the Kriging method is reported to capture such uncertainties and estimate the surface finish based on different process parameters.