Evaluation of resultant pellet quality and low temperature closed-cycle grain drying system

Along with the increasing population, the lack of food and energy have become major global issues in 21 century. Bioethanol is now one of the most popular renewable energy sources and is mostly produced by corn in the US. The corn-based ethanol production has grown rapidly over the past two decades. The increasing of corn ethanol production also created a huge amount of by-product like DDGS, which commonly used as animal feed and make the whole industry even more profitable. However, the low bulk density and poor flowability inhibit the value of DDGS. The DDGS low bulk density and low flowability could be improved by pelleting process. Pellet quality is the key aspect of this project. To obtain a high yield of corn ethanol and high quality DDGS the quality of the ingredients is very important. There are many things can affect the overall corn quality from planting to storage. The drying process is a vital step to maintaining corn quality and extent the corn storage life. Our study was conducted to analysis the resultant DDGS pellet quality and evaluate a prototype low-temperature grain drying system. The pelleting studies in this thesis were focused on analysis the resultant pellet quality by using 100% corn-based DDGS. The pelleting process was operated with three different DDGS moisture content and three different dies. The results showed that by using pilot-scale pellet mill, the bulk density can be increased and the flowability of DDGS could be improved by pelleting process. The grain drying project talks about an experiment of measure the power consumption and moisture removal efficiency of a prototype low temperature grain drying system. The data were collected through two replications of the drying process. The drying results indicated that the system had high efficiency and had no negative effect on germination performance. The TEA and LCA study were conducted to understand both environmental and economic impacts of an on-farm low-temperature grain drying system. Three scales of this drying system were analyzed in this study. The result showed that the unit drying cost decreased as the drying capacity expanded and the lowest unit drying cost was 0.46 USD per bushel of corn. In conclusion, the pelleting process could be a valid way to improve the low bulk density and poor flowability of DDGS. The low temperature closed-cycle grain drying system was more efficient than other commonly used high temperature grain dryer and maintain the grain quality

Sugar metabolism and accumulation in the fruit of transgenic apple trees with decreased sorbitol synthesis.

Both sorbitol and sucrose are synthesized in source leaves and transported to fruit for supporting fruit growth in tree fruit species of the Rosaceae family. In apple (Malus domestica), antisense suppression of aldose-6-phosphate reductase, the key enzyme for sorbitol synthesis, significantly decreased the sorbitol concentration but increased the sucrose concentration in leaves, leading to a lower sorbitol but a higher sucrose supply to fruit in these plants. In response to this altered carbon supply, the transgenic fruit had lower concentration of sorbitol and much higher concentration of glucose but similar levels of fructose, sucrose, and starch throughout fruit development relative to the untransformed control. Activities of sorbitol dehydrogenase, fructokinase, and sucrose phosphate synthase were lower, whereas activities of neutral invertase, sucrose synthase, and hexokinase were higher in the transgenic fruit during fruit development. Transcript levels of MdSOT1, MdSDHs, MdFK2, and MdSPS3/6 were downregulated, whereas transcript levels of MdSUC1/4, MdSUSY1-3, MdNIV1/3, MdHKs, and MdTMT1 were upregulated in the transgenic fruit. These findings suggest that the Sucrose cycle and the sugar transport system are very effective in maintaining the level of fructose and provide insights into the roles of sorbitol and sucrose in regulating sugar metabolism and accumulation in sorbitol-synthesizing species

CEIL: A General Classification-Enhanced Iterative Learning Framework for Text Clustering

Text clustering, as one of the most fundamental challenges in unsupervised learning, aims at grouping semantically similar text segments without relying on human annotations. With the rapid development of deep learning, deep clustering has achieved significant advantages over traditional clustering methods. Despite the effectiveness, most existing deep text clustering methods rely heavily on representations pre-trained in general domains, which may not be the most suitable solution for clustering in specific target domains. To address this issue, we propose CEIL, a novel Classification-Enhanced Iterative Learning framework for short text clustering, which aims at generally promoting the clustering performance by introducing a classification objective to iteratively improve feature representations. In each iteration, we first adopt a language model to retrieve the initial text representations, from which the clustering results are collected using our proposed Category Disentangled Contrastive Clustering (CDCC) algorithm. After strict data filtering and aggregation processes, samples with clean category labels are retrieved, which serve as supervision information to update the language model with the classification objective via a prompt learning approach. Finally, the updated language model with improved representation ability is used to enhance clustering in the next iteration. Extensive experiments demonstrate that the CEIL framework significantly improves the clustering performance over iterations, and is generally effective on various clustering algorithms. Moreover, by incorporating CEIL on CDCC, we achieve the state-of-the-art clustering performance on a wide range of short text clustering benchmarks outperforming other strong baseline methods.Comment: The Web Conference 202

Nanocomposites of Carbon Nanotube (CNTs)/CuO with High Sensitivity to Organic Volatiles at Room Temperature

AbstractIn order to enhance the sensitivity of carbon nanotube based chemical sensors at room temperature operation, CNTs/CuO nanocomposite was prepared under hydrothermal reaction condition. The resulted-product was characterized with TEM (transmission electron microscopy), XRD (X-ray diffraction) and so on. A chemical prototype sensor was constructed based on CNTs/CuO nanocomposite and an interdigital electrode on flexible polymer substrate. The gas-sensing behavior of the sensor to some typical organic volatiles was investigated at room temperature operation. The results indicated that the carbon nanotube was dispersed well in CuO matrix, the CuO was uniformly coated on the surface of carbon nanotube, and the tubular structure of carbon nanotube was clearly observed. From morphology of TEM images, it can also be observed that a good interfacial adhesion between CNT and CuO matrix was formed, which maybe due to the results of strong interaction between CNTs with carboxyl groups and CuO containing some hydroxy groups. The CNTs/CuO nanocomposite showed dramatically enhanced sensitivity to some typical organic volatiles. This study would provide a simple, low-cost and general approach to functionalize the carbon nanotube. It is also in favor of developing chemical sensors with high sensitivity or catalysts with high activity to organic volatiles at low temperature

GlyphDraw: Learning to Draw Chinese Characters in Image Synthesis Models Coherently

Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user instructions. Although the synthesis performance is fascinating, one significant limitation of current image generation models is their insufficient ability to generate coherent text within images, particularly for complex glyph structures like Chinese characters. To address this problem, we introduce GlyphDraw, a general learning framework aiming at endowing image generation models with the capacity to generate images embedded with coherent text. To the best of our knowledge, this is the first work in the field of image synthesis to address the generation of Chinese characters. % we first adopt the OCR technique to collect images with Chinese characters as training samples, and extract the text and locations as auxiliary information. We first sophisticatedly design the image-text dataset's construction strategy, then build our model specifically on a diffusion-based image generator and carefully modify the network structure to allow the model to learn drawing Chinese characters with the help of glyph and position information. Furthermore, we maintain the model's open-domain image synthesis capability by preventing catastrophic forgetting by using a variety of training techniques. Extensive qualitative and quantitative experiments demonstrate that our method not only produces accurate Chinese characters as in prompts, but also naturally blends the generated text into the background. Please refer to https://1073521013.github.io/glyph-draw.github.ioComment: 24 pages, 5 figure

A Metal-Ion-Incorporated Mussel-Inspired Poly(Vinyl Alcohol)-Based Polymer Coating Offers Improved Antibacterial Activity and Cellular Mechanoresponse Manipulation

Cobalt (CoII) ions have been an attractive candidate for the biomedical modification of orthopedic implants for decades. However, limited research has been performed into how immobilized CoII ions affect the physical properties of implant devices and how these changes regulate cellular behavior. In this study we modified biocompatible poly(vinyl alcohol) with terpyridine and catechol groups (PVA-TP-CA) to create a stable surface coating in which bioactive metal ions could be anchored, endowing the coating with improved broad-spectrum antibacterial activity against Escherichia coli and Staphylococcus aureus, as well as enhanced surface stiffness and cellular mechanoresponse manipulation. Strengthened by the addition of these metal ions, the coating elicited enhanced mechanosensing from adjacent cells, facilitating cell adhesion, spreading, proliferation, and osteogenic differentiation on the surface coating. This dual-functional PVA-TP-CA/Co surface coating offers a promising approach for improving clinical implantation outcomes