Gap-filling Process Research Articles

Development of Fluxless Micro-Bonding and Narrow Gap Filling Process

Development of Fluxless Micro-Bonding and Narrow Gap Filling Process

A Methodological Approach for Gap Filling of WFV Gaofen-1 Images from Spatial Autocorrelation and Enhanced Weighting

Clouds and cloud shadow cover cause missing data in some images captured by the Gaofen-1 Wide Field of View (GF-1 WFV) cameras, limiting the extraction and analysis of the image information and further applications. Therefore, this study proposes a methodology to fill GF-1 WFV images using the spatial autocorrelation and improved weighting (SAIW) method. Specifically, the search window size is adaptively determined using Getis-Ord Gi* as a metric. The spatial and spectral weights of the pixels are computed using the Chebyshev distance and spectral angle mapper to better filter the suitable similar pixels. Each missing pixel is predicted using linear regression with similar pixels on the reference image and the corresponding similar pixel located in the non-missing region of the cloudy image. Simulation experiments showed that the average correlation coefficient of the proposed method in this study is 0.966 in heterogeneous areas, 0.983 in homogeneous farmland, and 0.948 in complex urban areas. It suggests that SAIW can reduce the spread of errors in the gap-filling process to significantly improve the accuracy of the filling results and can produce satisfactory qualitative and quantitative fill results in a wide range of typical land cover types and has extensive application potential.

Spatial and temporal regeneration patterns within gaps in the primary forests vs. secondary forests of Northeast China

Forest gaps play an important role during forest succession in temperate forest ecosystems. However, the differences in spatial distribution and replacement patterns of woody plants (trees and shrubs) between primary and secondary forests remain unclear during the gap-filling processes, especially for temperate forests in Northeast China. We recorded 45,619 regenerated trees and shrubs in young gaps (<10 years), old gaps (10~20 years), and closed forest stands (i.e., filled gaps) in the primary broadleaved Korean pine (Pinus koraiensis Sieb. Rt Zucc.) forests vs. secondary forests (degraded from primary forests). The gap-filling processes along horizontal (Cartesian coordinate system) and vertical (lower layer: 0~5 m, medium layer: 5~10 m, and upper layer: >10 m) dimensions were quantified by shade tolerance groups of trees and shrubs. We found that gap age, competition between species, and pre-existing regeneration status resulted in different species replacement patterns within gaps in primary vs. secondary forests. Gap formation in both primary and secondary forests increased species richness, with 33, 38, 39, and 41 in the primary closed stands, primary forest gaps, secondary closed stands, and secondary forest gaps, respectively. However, only 35.9% of species in primary forest gaps and 34.1% in secondary forest gaps successfully reached the upper layer. Based on the importance values (IVs) of tree species across different canopy heights, light-demanding trees in the upper layer of the secondary forests were gradually replaced by intermediate and shade-tolerant trees. In the primary forests, Korean pine exhibited intermittent growth patterns at different canopy heights, while it had continuous regeneration along vertical height gradients in the secondary forests. The differences in Korean pine regeneration between the primary and secondary forests existed before gap formation and continued during the gap-filling processes. The interspecific competition among different tree species gradually decreased with increasing vertical height, and compared to the primary forests, the secondary forests showed an earlier occurrence of competition exclusion within gaps. Our findings revealed the species replacement patterns within gaps and provided a further understanding of the competition dynamics among tree species during the gap-filling processes.

Value and limitations of machine learning in high-frequency nutrient data for gap-filling, forecasting, and transport process interpretation

High-frequency monitoring of water quality in catchments brings along the challenge of post-processing large amounts of data. Moreover, monitoring stations are often remote and technical issues resulting in data gaps are common. Machine learning algorithms can be applied to fill these gaps, and to a certain extent, for predictions and interpretation. The objectives of this study were (1) to evaluate six different machine learning models for gap-filling in a high-frequency nitrate and total phosphorus concentration time series, (2) to showcase the potential added value (and limitations) of machine learning to interpret underlying processes, and (3) to study the limits of machine learning algorithms for predictions outside the training period. We used a 4-year high-frequency dataset from a ditch draining one intensive dairy farm in the east of The Netherlands. Continuous time series of precipitation, evapotranspiration, groundwater levels, discharge, turbidity, and nitrate or total phosphorus were used as predictors for total phosphorus and nitrate concentrations respectively. Our results showed that the random forest algorithm had the best performance to fill in data-gaps, with R2 higher than 0.92 and short computation times. The feature importance helped understanding the changes in transport processes linked to water conservation measures and rain variability. Applying the machine learning model outside the training period resulted in a low performance, largely due to system changes (manure surplus and water conservation) which were not included as predictors. This study offers a valuable and novel example of how to use and interpret machine learning models for post-processing high-frequency water quality data.

Using eye-tracking and retrospective verbal reports to explore the cognitive processes of banked gap-filling: a case study featuring methodological triangulation

This study made triangulated use of eye-tracking and retrospective verbal reports (RVRs) to compare the banked gap-filling processes of two same-scorers and those of a top scorer and a bottom scorer. The two same-scorers differed in their cognitive effort on global and local processing, fluency of choice making, and strategy use when completing the task and half of the mutual correct responses. Contrary to findings from previous studies, the top scorer exerted much greater effort on global and local processing than the bottom scorer, in her pursuit of perfection, and she reported much less use of syntax analysis as a strategy. The findings of this study increase our understanding of individual differences in the cognitive processes of English-as-a-foreign-language (EFL) reading and test-taking and prove the value of in-depth, multi-faceted process research. Featuring the use of heatmaps, eye-tracking metrics, choice-making graphs, gaze plots, and RVRs, this study also responds to an emergent concern in language assessment about how the enormous process data can be handled effectively. Implications for testing and learning EFL reading are further developed.

Disentangling regeneration by vertical stratification: A 17-year gap-filling process in a temperate secondary forest

Forest gaps are widely spread in the forest ecosystems and play important roles in driving forest dynamics. However, long-term regeneration during the gap-filling process was less understood, especially species composition and dynamics along vertical gradients over time. We monitored tree regeneration in artificial gaps of a temperate secondary forest for 17 years and analyzed the gap-filling process both as a whole and by stratification (lower layer: 0∼3 m, middle layer: 3∼6 m, and upper layer: >6 m) for three shade-tolerance groups of tree species. We found that the interaction effects of gap size and shade tolerance could result in a growth difference of five to ten years among different regeneration groups, with the most significant effects in the large gaps for the light-demanding species such as Juglans mandshurica and Phellodendron amurense. Regeneration density in the large and small gaps eventually converged, but there were great differences in density dynamics. The regeneration density in the large gaps decreased gradually over time, while it decreased sharply in the small gaps after just one growing season of gap formation and consistently remained at low levels regardless of shade tolerance. Species richness decreased smoothly during the 17-year monitoring, but the richness in the large gaps was consistently higher than that in the small gaps, with all shade-tolerance groups existing, which underlined the importance of gap size in maintaining tree species diversity. Differences in the density, richness, and composition among regeneration layers reduced over time. However, vertical regeneration patterns diverged among shade-tolerance groups during the gap-filling process. Light-demanding species were likely to have only one chance for successful regeneration because almost no new recruitments appeared in the lower or middle layer as dominant stems reached the upper layer. Intermediate and shade-tolerant species, by contrast, were well-distributed in different regeneration layers, indicating a stronger capacity for resistance and resilience during uncertain disturbance events in the long run. Our results revealed the gap-filling strategies of tree species with different shade-tolerance groups, which explained why light-demanding species could not completely occupy a forest gap and highlighted the necessity of repeated gap disturbance for intermediate and shade-tolerant species regeneration.

A Study on the Gap-Fill Process Deposited by the Deposition/Etch/Deposition Method in the Space-Divided PE-ALD System

This study concerns the development of a gap-fill process technology for isolating trench patterns. There are various gap-filling techniques in the case of trench patterns; nevertheless, a processing technology adopting the DED (deposition/etch/deposition) method was developed in this study. After the etch step, an Ar/O2 (1:2) plasma treatment technology reduced the residual amount of F in the films to 0.05%. By improving the etch uniformity, the deposition uniformity after the DED process on a 12-inch flat wafer was secured within <1%, and a high-quality SiO2 thin film with a dielectric constant of 3.97 and a breakdown field of 11.41 MV/cm was fabricated. The DED method can be used for gap-filling even in patterns with a high aspect ratio by changing process parameters, such as RF power and division of etch steps, according to the shape, depth, and CD size of the pattern. This study confirmed that a void-free gap-fill process can be developed in a trench pattern with a maximum aspect ratio of 40:1.

Evaluating homogeneity and trends in extreme daily precipitation indices in a semiarid region of Brazil

A regional investigation of precipitation extremes could help the local authorities to develop strategies against potential climatic disasters, especially in regions of large climate vulnerability. In this context, this study focused on the homogeneity and trend analysis of eleven extreme precipitation indices from a daily rainfall dataset of rain gauges of the state of Ceará, located in the north of Northeast Brazil, from 1974 to 2018 at annual and seasonal time scales. The data were first submitted to gap-filling and quality control processes. Homogeneity, trend, and correlation coefficient were performed subsequently. Homogeneity results showed that most of the precipitation series were classified as “useful.” Significant break years in the series agreed well with moderate and very strong El Niño and La Niña events, suggesting a further investigation of this possible connection. Wet and dry day precipitation indices mainly indicated a decrease in the rainfall regime and an increase in dry days, mainly in the central-eastern, northwestern, and southern regions of the Ceará, especially during the annual time scale and the rainy season. The Locally Weighted Scatterplot Smoothing (LOWESS) curve showed changes in almost all series during the 1980s and 1990s, coinciding with the homogeneity breaks and years of severe droughts that strongly hit the region. Correlation coefficients were strong and significant between rainfall total index and the other precipitation indices.

Buckling-aided gap filling during the extrusion of Acrylonitrile Butadiene Styrene for additive manufacturing

In the fused filament fabrication, a solid polymer filament is extruded through an extruder, to provide extrudates that are needed to print plastic parts. There exists a finite gap between the filament and the inner surface of the extruder. This gap is used to aid in the translation of the filament inside the extruder. In this work, via in-situ observation of the extrusion of a thin Acrylonitrile Butadiene Styrene (ABS) filament through a heated glass tube, we found: (i) the gap was filled along the top–bottom direction, due to local buckling, curved shape, and downward movement of the filament, instead of the polymer melt’s backflow, and (ii) the buckling of the filament creates more contact sites on the tube’s inner wall, increasing the gap-filling rate. These findings provide better understanding of both the gap-filling and extrusion processes.

Active DNA demethylation promotes cell fate specification and the DNA damage response.

Neurons harbor high levels of single-strand DNA breaks (SSBs) that are targeted to neuronal enhancers, but the source of this endogenous damage remains unclear. Using two systems of postmitotic lineage specification-induced pluripotent stem cell-derived neurons and transdifferentiated macrophages-we show that thymidine DNA glycosylase (TDG)-driven excision of methylcytosines oxidized with ten-eleven translocation enzymes (TET) is a source of SSBs. Although macrophage differentiation favors short-patch base excision repair to fill in single-nucleotide gaps, neurons also frequently use the long-patch subpathway. Disrupting this gap-filling process using anti-neoplastic cytosine analogs triggers a DNA damage response and neuronal cell death, which is dependent on TDG. Thus, TET-mediated active DNA demethylation promotes endogenous DNA damage, a process that normally safeguards cell identity but can also provoke neurotoxicity after anticancer treatments.

Bottom-up plasma-enhanced atomic layer deposition of SiO2 by utilizing growth inhibition using NH3 plasma pre-treatment for seamless gap-fill process

The design-rule shrinkage in semiconductor devices is a challenge at every step of the integration process. In the gap-fill process for isolation, the seam and void formation cannot be suppressed by using a deposition process, which even has excellent step coverage. To achieve seamless gap fill in the high-aspect-ratio structure, which has a non-ideal etch profile such as a negative slope, the deposition process should be able to realize the “bottom-up growth” behavior. In this work, the bottom-up growth of a SiO2 plasma-enhanced atomic layer deposition (PE-ALD) process in a trench structure was investigated by using a growth inhibition process employing plasma treatment. N2 and NH3 plasma pre-treatments were employed to suppress the growth of the SiO2 PE-ALD process without any contamination, and the inhibition mechanism was investigated by performing surface chemistry analyses using X-ray photoelectron spectroscopy. Furthermore, the gap-fill characteristics of the SiO2 PE-ALD process were examined, depending on the process conditions of NH3 plasma pre-treatment, by performing cross-sectional field emission scanning electron microscopy measurements. Finally, a seamless gap-fill process in a high-aspect-ratio trench pattern was achieved by the bottom-up growth behavior of SiO2 PE-ALD using NH3 plasma pre-treatment.

Gap-Filling and Missing Information Recovery for Time Series of MODIS Data Using Deep Learning-Based Methods

Sensors onboard satellite platforms with short revisiting periods acquire frequent earth observation data. One limitation to the utility of satellite-based data is missing information in the time series of images due to cloud contamination and sensor malfunction. Most studies on gap-filling and cloud removal process individual images, and existing multi-temporal image restoration methods still have problems in dealing with images that have large areas with frequent cloud contamination. Considering these issues, we proposed a deep learning-based method named content-sequence-texture generation (CSTG) network to generate gap-filled time series of images. The method uses deep neural networks to restore remote sensing images with missing information by accounting for image contents, textures and temporal sequences. We designed a content generation network to preliminarily fill in the missing parts and a sequence-texture generation network to optimize the gap-filling outputs. We used time series of Moderate-resolution Imaging Spectroradiometer (MODIS) data in different regions, which include various surface characteristics in North America, Europe and Asia to train and test the proposed model. Compared to the reference images, the CSTG achieved structural similarity (SSIM) of 0.953 and mean absolute errors (MAE) of 0.016 on average for the restored time series of images in artificial experiments. The developed method could restore time series of images with detailed texture and generally performed better than the other comparative methods, especially with large or overlapped missing areas in time series. Our study provides an available method to gap-fill time series of remote sensing images and highlights the power of the deep learning methods in reconstructing remote sensing images.

In-situ observation of the extrusion processes of Acrylonitrile Butadiene Styrene and Polylactic Acid for material extrusion additive manufacturing

In material extrusion (MatEx) additive manufacturing, solid polymer filaments are fed into extruders to generate extrudates that are needed to build 3D plastic parts. There is a finite gap between the inner surface of an extruder and the edge of a filament, which facilitates the insertion and translation of the filament inside the extruder. It is still not clear how this gap is filled during the extrusion. On the other hand, it is important to know this information, for example, to model the distributions of temperature and pressure during the extrusion. In this work, the gap-filling processes of Acrylonitrile Butadiene Styrene (ABS) and Polylactic Acid (PLA) filaments were directly observed through a heated glass tube. The glass tube functioned as the extruder in our case. A criterion was first developed to determine whether the gap was filled at a specific location of the tube. The gap-filling processes were then observed for different combinations of extrusion temperatures and feed rates. ABS and PLA filaments, which consisted of different colors, were custom-made to aid in the observation. Although ABS and PLA were, respectively, amorphous and semi-crystalline polymers, for both materials, we found: i) the gap inside an extruder was filled through three different steps during the initial stage of extrusion; ii) the gap-filling level depended on extrusion temperature and feed rate; and iii) there was no noticeable difference in the gap-filling level when the extrusion started with an empty tube or resumed after the printing had been paused.

Land Use Modeling Predicts Divergent Patterns of Change Between Upper and Lower Elevations in a Subalpine Watershed of the Alps

The synergic influence of land use and climate change on future forest dynamics is hard to disentangle, especially in human-dominated forest ecosystems. Forest gain in mountain ecosystems often creates different spatial–temporal patterns between upper and lower elevation belts. We analyzed land cover dynamics over the past 50 years and predicted Business as Usual future changes on an inner subalpine watershed by using land cover maps, derived from five aerial images, and several topographic, ecological, and anthropogenic predictors. We analyzed historical landscape patterns through transition matrices and landscape metrics and predicted future forest ecosystem change by integrating multi-layer perceptron and Markov chain models for short-term (2050) and long-term (2100) timespans. Below the maximum timberline elevation of the year 1965, the dominant forest dynamic was a gap-filling process through secondary succession at the expense of open areas leading to an increase of landscape homogeneity. At upper elevations, the main observed dynamic was the colonization of unvegetated soil through primary succession and timberline upward shift, with an increasing speed over the last years. Future predictions suggest a saturation of open areas in the lower part of the watershed and stronger forest gain at upper elevations. Our research suggests an increasing role of climate change over the last years and on future forest dynamics at a landscape scale.

Changes of rock glacier vegetation in 25 years of climate warming in the Italian Alps

Rock glaciers are periglacial landforms sensitive to climate change, and a harsh environment for vegetation colonization due to the potential occurrence of surface instability. Changes of rock glacier vegetation would provide evidence of the importance of climate change impacts, as the limitation provided by physical disturbance could be overcome by plant responses to warming.We assess, through the resurvey of ten rock glaciers (six active, four inactive) in the Italian Central Alps, the vegetation changes in response to 25 years of climate warming. Vegetation was analyzed through the phytosociological method in 1995 and 2020 adopting the same field protocol for both surveys with 1208 relevés. The relation with climate was assessed by multivariate analysis.Air warming occurred in the study area and vegetation changed both in active and inactive rock glaciers, with increases of species richness, cover, changes in floristic composition. After 25 years the differences between active and inactive rock glaciers persisted but with an appreciable decrease mainly due to the larger vegetation changes showed by active rock glaciers. The multivariate analysis confirmed the relation between vegetation changes and air warming. The observed vegetation changes were compatible also with the impact of the decrease of the physical disturbance limitation likely due rock glacier stabilization, in particular for the active rock glaciers located at lower elevations, while the opposite trend could be hypothesized for those at higher elevations. The changes of floristic composition allowed assess that a gap-filling process, instead of species upward migration, produced the vegetation changes, with species persistence coupled to the recruitment of new species from the neighbor communities. Persistence of climate warming in future could lead to vegetation homogenization and biodiversity loss due to the extinction debt of several alpine species.

Gap filling mechanisms during the thin ply Automated Tape Placement process

Automated Tape Placement (ATP) is one of the attractive automated composite manufacturing processes as it reduces labor cost, increases production rate and improves repeatability. In this method, the part is built by consolidating one unidirectional prepreg tape layer at a time with a placement head using a compaction roller. Defects such as gaps between neighboring tapes during lay up are inevitable. This challenge becomes even more critical in the ATP of the thin ply prepreg tapes as the ratio of the gap width to the tape thickness increases. The filling process of such gaps during the process cycle results in resin-rich areas and fiber waviness. In this paper, we present a model to numerically simulate the gap-filling process by coupling the squeeze flow behavior within the tapes to fill the gap with the deformation of the top layers into the hollow space within the gap. First, the experimental results clarify the microstructural physics of the gap-filling process. This is followed by proposing a model to predict the flow front of resin that moves to fill the gap and the gap thickness. The predictions of the model are compared with experimental results and validated by the micrographs of fabricated samples.

Abiotic and biotic determinants of height growth of Picea abies regeneration in small forest gaps in the Swiss Alps

In managed mountain forests, height growth of Norway spruce (Picea abies (L.) Karst) regeneration is a decisive factor for the gap-filling process, especially when the silvicultural goal is to provide continuous protection against natural hazards such as snow avalanches or rockfall. For the planning of management interventions, robust predictions on height growth of regeneration at the scale of forest gaps are thus needed. However, there is a lack of such data for trees of intermediate sizes, and existing studies fail to cover large environmental gradients. The goal of our study is to identify the key factors that influence height growth of Norway spruce regeneration in small gaps of spruce-dominated forests in the Swiss Alps. Furthermore, we assess whether there are site-specific differences of height growth or whether it follows a similar pattern along a large gradient of temperature (i.e., along elevation) and of water and nutrient availability (i.e., among different phytosociological site types) within the upper montane and subalpine vegetation belts. On 124 plots, >2′000 observations of annual height increments of Norway spruce regeneration (10 cm tree height to 12 cm stem diameter) in gaps were collected. Using linear mixed effects models and cross-validation for model selection, we identified the best variable combinations to predict annual height growth. Consistently across the entire gradient, the most important factors were 1) the positive effect of tree size, 2) the negative effect of competition by the surrounding stand, and 3) local topography. We found site-specific differences in height growth patterns such as gap size and therefore direct radiation being the most important competition measure in subalpine sites, as opposed to diffuse radiation in high montane sites. However, the pooled model for the entire environmental gradient allowed for predictions of regeneration height growth with similar explanatory power as the more specific models while containing comparable effect sizes. Furthermore, competition can be equally well expressed by metrics based on basal area measurements as by metrics derived from hemispherical photography. Based on these relatively simple models, accurate and robust predictions of the development of Norway spruce regeneration in gaps of managed mountain forests are possible.

Explicating Epistemic Process in Elementary Students’ Language Use by Practical Epistemology and Discourse Register Analyses

This study provides two exemplars of how grammatical analysis of language use in elementary science classroom discourse enhances the explication of students’ epistemic process in the language use in that discourse. Methodologically, both practical epistemology analysis (PEA) and discourse register analysis (DRA) from systemic functional linguistics were employed as a combinatory approach. The former was used to construe epistemic process of students’ language use and the latter was to articulate grammatical features of the language use. The exemplary analysis was administered for the discourse data collected at two elementary science classes in South Korea. The exemplars showed that ideational metafunction and its semantic relation analyses in DRA facilitated identifying gaps and relations in PEA, and interpersonal and textual metafunction analyses in DRA supported construing the flow of gap-filling or lingering process in PEA. Analysing students’ language use by PEA combined with DRA can help science teachers find the points where the language use in school science gets epistemological productivity, while it is different from the language game in science disciplines.

Development of Gap-filling Impregnation Method of ITER TF Coils

The ITER Toroidal Field (TF) coil is composed of a Winding Pack (WP) and a TF coil case (TFCC). In the manufacturing of a TF coil, the gap between the WP and the TFCC is filled with radiation resistant Triglycidyl-p-aminophenol (TGPAP) resin. Vacuum Pressure Impregnation (VPI) is adopted. The selected resin system displayed two potential problems: high viscosity and cracking after cure. A series of production optimizations have been performed to develop techniques to apply the selected resin for the TF coil production: crack countermeasure, narrow gap injection, and pressure control. For crack countermeasure, the addition of fiberglass tape or sheet layer was found to be effective in preventing fragmentation of cracked resin. Since the cracked resin would not harm the TF coil quality as long as it stays in the original position, addition of confining fiberglass layers solves the problem. In narrow gap qualification tests, resin injection into a 2 mm wide space was observed with proper selection of fiberglass layer addition conditions. The pressure qualification test showed that resin cured without additional pressurization can satisfy the compression strength requirements. From those results, techniques for the TF coil production have been developed, and with the implementation of those techniques the gap-filling of the first TF coil in Japan was successfully completed in 2019. Since then, two more TF coils have completed the gap-filling process with some improvements.

Detecting dynamics and variations of crown asymmetry induced by natural gaps in a temperate secondary forest using terrestrial laser scanning

Gap formation and closure play important roles in forest succession. Most studies focused on regeneration within gaps, but less is known about the growth dynamics of canopy trees surrounding the gaps (i.e., gap border trees), which limits our understanding of the gap-filling process. In this study, terrestrial laser scanning (TLS) was used to quantify the crown asymmetry of six canopy tree species with different wood densities among young gaps (15a), old gaps (32a), and closed forest stands (CK). The size of expanded gaps ranged from 166.8 to 408.1 m2 with an average of 271.5 m2. Each gap border tree was separated into two parts, i.e., one part facing the gap (FG) and the other facing the forest interior (FF). The ratios (FG/FF) of crown length, crown projected area, and crown volume of these two parts were calculated to represent one-, two-, and three-dimensional crown asymmetry, respectively. We found that 90% gap border trees had asymmetric crown toward gaps with an average ratio of 1.58. For trees in the closed forest stands, although crown asymmetry occurred randomly in different directions and had a large variation, the average ratio was close to 1.00. However, the gap age and the location of gap border tree (i.e., north, east, south, and west of the gap) did not show significant influences on the crown asymmetry because differences of crown asymmetry probably disappeared after the long period of gap formation. The crown asymmetry exhibited inter-specific variations and was positively correlated with wood density, which indicated that tree species with a higher wood density such as Acer mono (0.61 g cm−3) could support a more asymmetric crown and have a higher asymmetric crown threshold than others such as Juglans mandshurica (0.45 g cm−3). Crown asymmetry had similar results among different dimensions. Our findings indicated that the general crown asymmetry of gap border trees might increase snapping and uprooting risks during wind and snow disturbances. Although gap-based silviculture is widely applied in forest management, additional practices such as thinning or selective harvesting should be considered to create more space and alleviate an asymmetric crown induced by gap formation.