Effects of Grain Morphology on Flow Behavior of Semi-Solid Slurries

The flow behavior of semi-solid slurry determines the quality of the castings produced by the semi-solid forming process. Many studies have done to investigate the flow behavior of slurry under different conditions, and results show that the rheological behavior of slurry with dendritic structure is inappropriate for semi-solid forming. In this study, slurries with varying morphologies of grain for the same alloy with the same fraction solid have tested using a partial filling method. The SEED process was employed, and the pouring temperature adjusted to prepare semi-solid slurries with different grain morphologies. The flow pattern, entrapped air during the filling process, and also microstructure of the samples were examined to characterize the macro and micro flow behavior. The results show that a turbulent macro-flow, leading to entrapped air, and severe segregation appeared in the sample using slurry of Tpour ≥ 660 °C . For the slurry of Tpour < 660 °C, none of the three phenomena found in the sample. This investigation further showed that the detriment of dendrite on the semi-solid forming process, and implied that large size dendrite in semi-solid slurry must avoided.

Experimental Study on Restoration of Deteriorated Timber due to Termites by Resin Filling

There are many valuable wooden buildings in the world, because timber has been used all over the world as a building material for a long time. However, there is an issue that timber deteriorates due to various factors. Therefore, in order to preserve these valuable wooden buildings, it is necessary to appropriately repair or reinforce treatment. One of the treatments is the resin filling method. In this method, filling the resin in order to restore the strength into an internal cavity caused by deterioration. It has become clear that it is possible to recover the strength using this method, however, we are still conducting construction based on the rule of thumb. Therefore, authors examined the resin characteristics in order to inject the resin in stable manner and ensure strength recovery. Authors focused on deteriorated timber due to termites, because Japan has a very high amount of such type of timber. Authors reports the following four aspects of the characteristics of resin filling into timber. 1. The Area velocity is determined by the injection pressure, width of the gap, and viscosity of the resin. 2. The resin spreads concentrically in the gap of wood, but there is no regularity in the random gap like deteriorated timber due to termites. 3. Authors proposed a new coefficient for the application, of a theoretical formula to deteriorated timber due to termites. 4. Authors proposed a flowchart of resin filling method to perform stable construction.

Long-gap Filling Method for the Coastal Monitoring Data

Technique for the long-gap filling that occur frequently in ocean monitoring data is developed. The method estimates the unknown values of the long-gap by the summation of the estimated trend and selected residual components of the given missing intervals. The method was used to impute the data of the long-term missing interval of about 1 month, such as temperature and water temperature of the Ulleungdo ocean buoy data. The imputed data showed differences depending on the monitoring parameters, but it was found that the variation pattern was appropriately reproduced. Although this method causes bias and variance errors due to trend and residual components estimation, it was found that the bias error of statistical measure estimation due to long-term missing is greatly reduced. The mean, and the 90% confidence intervals of the gap-filling model’s RMS errors are 0.93 and 0.35~1.95, respectively.

Spectral Temporal Information for Missing Data Reconstruction (STIMDR) of Landsat Reflectance Time Series

The number of Landsat time-series applications has grown substantially because of its approximately 50-year history and relatively high spatial resolution for observing long term changes in the Earth’s surface. However, missing observations (i.e., gaps) caused by clouds and cloud shadows, orbit and sensing geometry, and sensor issues have broadly limited the development of Landsat time-series applications. Due to the large area and temporal and spatial irregularity of time-series gaps, it is difficult to find an efficient and highly precise method to fill them. The Missing Observation Prediction based on Spectral-Temporal Metrics (MOPSTM) method has been proposed and delivered good performance in filling large-area gaps of single-date Landsat images. However, it can be less practical for a time series longer than one year due to the lack of mechanics that exclude dissimilar data in time series (e.g., different phenology or changes in land cover). To solve this problem, this study proposes a new gap-filling method, Spectral Temporal Information for Missing Data Reconstruction (STIMDR), and examines its performance in Landsat reflectance time series. Two groups of experiments, including 2000 × 2000 pixel Landsat single-date images and Landsat time series acquired from four sites (Kenya, Finland, Germany, and China), were performed to test the new method. We simulated artificial gaps to evaluate predicted pixel values with real observations. Quantitative and qualitative evaluations of gap-filled images through comparisons with other state-of-the-art methods confirmed the more robust and accurate performance of the proposed method. In addition, the proposed method was also able to fill gaps contaminated by extreme cloud cover for a period (e.g., winter in high-latitude areas). A down-stream task of random forest supervised classification through both gap-filled simulated datasets and the original valid datasets verified that STIMDR-generated products are relevant to the user community for land cover applications.

Intelligent Filling Method of Power Grid Working Ticket Based on Historical Ticket Knowledge Base

The traditional power grid ticket filling method has a large workload, low efficiency, and cannot achieve comprehensive and effective reference of historical tickets. This paper proposes a method of intelligent filling in a power grid working ticket based on a historical ticket knowledge base. Firstly, the historical ticket data are preprocessed, then the historical ticket information is mined by the association rule algorithm, and the method of establishing the historical ticket knowledge base is proposed. Based on the improved word bag model, an intelligent grid work ticket filling model is established based on the historical ticket knowledge base, and the correctness of the method is verified by an example. The results show that the accuracy of the proposed method is at least 18% higher than that of the traditional model, and the matching efficiency is 50% higher than the evaluation results of the three models based on semantic expressions. The method enables the identification and extraction of similar and associated work tickets, improves the efficiency of filling work tickets for power grids, and promotes the intelligence of the safety procedures for power grid operations.

A gap-filling algorithm for prediction of metabolic interactions in microbial communities

The study of microbial communities and their interactions has attracted the interest of the scientific community, because of their potential for applications in biotechnology, ecology and medicine. The complexity of interspecies interactions, which are key for the macroscopic behavior of microbial communities, cannot be studied easily experimentally. For this reason, the modeling of microbial communities has begun to leverage the knowledge of established constraint-based methods, which have long been used for studying and analyzing the microbial metabolism of individual species based on genome-scale metabolic reconstructions of microorganisms. A main problem of genome-scale metabolic reconstructions is that they usually contain metabolic gaps due to genome misannotations and unknown enzyme functions. This problem is traditionally solved by using gap-filling algorithms that add biochemical reactions from external databases to the metabolic reconstruction, in order to restore model growth. However, gap-filling algorithms could evolve by taking into account metabolic interactions among species that coexist in microbial communities. In this work, a gap-filling method that resolves metabolic gaps at the community level was developed. The efficacy of the algorithm was tested by analyzing its ability to resolve metabolic gaps on a synthetic community of auxotrophic Escherichia coli strains. Subsequently, the algorithm was applied to resolve metabolic gaps and predict metabolic interactions in a community of Bifidobacterium adolescentis and Faecalibacterium prausnitzii, two species present in the human gut microbiota, and in an experimentally studied community of Dehalobacter and Bacteroidales species of the ACT-3 community. The community gap-filling method can facilitate the improvement of metabolic models and the identification of metabolic interactions that are difficult to identify experimentally in microbial communities.

Comparison of Root Filling Quality of Two Types of Single Cone-Based Canal Filling Methods in Complex Root Canal Anatomies: The Ultrasonic Vibration and Thermo-Hydrodynamic Obturation versus Single-Cone Technique

This study aimed to assess the effectiveness of ultrasonic vibration and thermo-hydrodynamic obturation (VibraTHO) using two types of root canal sealers, in comparison to the single-cone (SC) technique and a calcium silicate-based root canal sealer in complex root canal anatomies. Thirty single-rooted human maxillary premolars with two canals that had a complex root canal anatomy of transverse anastomoses or ramifications were prepared and assigned to the following three experimental groups, according to the filling method: SE group, SC technique with Endoseal TCS; VE group, VibraTHO with Endoseal TCS; and VG group, VibraTHO with GuttaFlow 2. Each tooth was scanned using micro-computed tomography, and the volume percentages of the filling material were calculated. The analysis of variance was used to analyze the statistical differences between the three groups (p < 0.05). The mean volume of the filling material was higher in the VG and VE groups than that in the SE group (p < 0.05) along the apical to middle-to-coronal thirds, and significant differences were observed between each root canal area (p < 0.05), with the only exception being at the apical thirds between the VE and SE groups. The VibraTHO technique using GuttaFlow 2 can be a more effective root canal filling method for anatomically complex root canal systems than the SC technique with Endoseal TCS. On the other hand, the VibraTHO technique using Endoseal TCS has a limited effect on improving the quality of the root filling at the apical portion of anatomically complex root canal systems, compared to the SC technique with Endoseal TCS.