scholarly journals Optimization of tannin extraction stage from oriental spruce and oak bark

Author(s):  
Oktay GÖNÜLTAŞ ◽  
Mualla BALABAN UÇAR
Marine Drugs ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. 437
Author(s):  
Milena Álvarez-Viñas ◽  
Sandra Souto ◽  
Noelia Flórez-Fernández ◽  
Maria Dolores Torres ◽  
Isabel Bandín ◽  
...  

Carrageenan and carrageenan oligosaccharides are red seaweed sulfated carbohydrates with well-known antiviral properties, mainly through the blocking of the viral attachment stage. They also exhibit other interesting biological properties and can be used to prepare different drug delivery systems for controlled administration. The most active forms are λ-, ι-, and κ-carrageenans, the degree and sulfation position being determined in their properties. They can be obtained from sustainable worldwide available resources and the influence of manufacturing on composition, structure, and antiviral properties should be considered. This review presents a survey of the antiviral properties of carrageenan in relation to the processing conditions, particularly those assisted by intensification technologies during the extraction stage, and discusses the possibility of further chemical modifications.


2020 ◽  
Vol 13 (1) ◽  
pp. 71
Author(s):  
Zhiyong Xu ◽  
Weicun Zhang ◽  
Tianxiang Zhang ◽  
Jiangyun Li

Semantic segmentation is a significant method in remote sensing image (RSIs) processing and has been widely used in various applications. Conventional convolutional neural network (CNN)-based semantic segmentation methods are likely to lose the spatial information in the feature extraction stage and usually pay little attention to global context information. Moreover, the imbalance of category scale and uncertain boundary information meanwhile exists in RSIs, which also brings a challenging problem to the semantic segmentation task. To overcome these problems, a high-resolution context extraction network (HRCNet) based on a high-resolution network (HRNet) is proposed in this paper. In this approach, the HRNet structure is adopted to keep the spatial information. Moreover, the light-weight dual attention (LDA) module is designed to obtain global context information in the feature extraction stage and the feature enhancement feature pyramid (FEFP) structure is promoted and employed to fuse the contextual information of different scales. In addition, to achieve the boundary information, we design the boundary aware (BA) module combined with the boundary aware loss (BAloss) function. The experimental results evaluated on Potsdam and Vaihingen datasets show that the proposed approach can significantly improve the boundary and segmentation performance up to 92.0% and 92.3% on overall accuracy scores, respectively. As a consequence, it is envisaged that the proposed HRCNet model will be an advantage in remote sensing images segmentation.


2021 ◽  
Author(s):  
Silvana Cecilia Tourn ◽  
Alfredo Sequeira ◽  
Eliana Paola Dagnino ◽  
Walter Gustavo Morales ◽  
Ester Chamorro

Author(s):  
Elsye Gunawan ◽  
Enrick Kharo Etmond ◽  
Linus Yhani Chrystomo

Papua has a diversity of flora species, one of which is the Papuan Grape (Sararanga sinuosa Hemsley). It is commonly used by the Depapre community, Jayapura, as a stamina booster. This research aims to identify the secondary metabolite compounds, to test the cytotoxic activity of Papuan Grape (Sararanga sinuosa Hemsley) extract, and to determine the best concentration that inhabits the growth of Artemia salina larvae using the BSLT method. This study was conducted with the extraction stage using the maceration method by making use of 96% ethanol solvent. Subsequently, the concentration series 0, 50, 100, 150, 200, 250, 300 ppm of Papuan Grape (Sararanga sinuosa Hemsley) extract were made to test the cytotoxic activity on the mortality of Artemia salina shrimp larvae. The results showed that Alkaloids, Flavonoids, Saponins, and Tannins were compounded as secondary metabolite. An antioxidant research that had been carried out previously had LC50 of green-white fruit (12,49 ± 0,35 mg/ml), orange-red fruit (17,62 ± 3,49 mg/ml) and red fruit (12,23 ± 0,46 mg/ml). The community process one stalk of it into juice and used or consumed it two times a day. An inappropriate dose of traditional medicine usage can affect the organ system and had adverse effects in the future The result of cytotoxic research obtained the value of LC50 in ethanol extract of Papuan Grape was 140,863 ppm, and concentration of 250 ppm was the best concentration to inhibit the growth of shrimp larvae (Artemia salina L). The conclusion of this study was the ethanol extract of Papuan Grape (Sararanga sinuosa Hemsley) showed the highest cytotoxic activity and potentially become an anti-cancer agent.


TAPPI Journal ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 139-147
Author(s):  
MARKKU KUOSA ◽  
ANTTI HEIKKINEN ◽  
TAPIO TIRRI ◽  
LASSE PULKKINEN

A pilot-size screw reactor (extraction unit) was used for tannin extraction of spruce. Yield of the same magnitude or better was obtained when comparing a screw reactor with batch reactors. A longer presoaking time in water seemed to be better than a short one for obtaining higher yield. A higher yield is obtained with lower dry-water ratio, which suggests that the internal diffusion in bark does not determine mass transfer as much as is the case without presoaking of bark. The higher dry-water ratio decreased the yield. The prior soaking of the bark also minimized the mechanical reactor feeding problems (clogging). The benefits of a screw reactor likely are that run time changes for different process conditions are flexible; it simplifies design and construction of an industrial unit for tannin production; and it saves space because of the need for fewer and smaller intermediate storage tanks.


2014 ◽  
Vol 608 ◽  
pp. 62-67
Author(s):  
Karin Kandananond

Although the manufacturing businesses have played an important role in generating the highest GDP for Thailand, they also emit more greenhouse gas (GHG) than other sectors. Due to the cap and trade scheme by European Union (EU), the carbon footprint is the GHG emitted by products, organization or persons and it has to be tracked and recorded. Since the ceramic production process also has a major contribution on the emission, its carbon footprint is a piece of product information which cannot be ignored. In this research, the carbon footprint for the whole life cycle of a local ceramic product was recorded and calculated. It is interesting to note that the resource extraction stage has contributed to the highest emission followed by the product use, manufacturing, disposal and distribution. The results from this research are useful for local ceramic manufacturers who want to export their products to the EU countries and it is also important for the customers who are concerned about the environment.


Author(s):  
A. Z. Qamhiyah ◽  
R. D. Venter ◽  
B. Benhabib

Abstract Feature-extraction techniques address the primary limitation of feature-recognition approaches, namely their lack of generalization. This paper presents a boundary-based procedure for the classification and sequential extraction of form features from the CAD models of objects with planar surfaces. Form features are first classified based on their effect on the boundary elements of a basic shape. Geometric reasoning is then used to obtain generalized properties of the form-features’ classes. Finally, form-features’ classes are sequentially extracted based on the recognized properties. At the onset of each extraction stage, the object is viewed as an initial basic shape that has been iteratively altered through the introduction of form features.


2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Tzung-Han Jeng ◽  
Yi-Ming Chen ◽  
Chien-Chih Chen ◽  
Chuan-Chiang Huang

Despite the efforts of information security experts, cybercrimes are still emerging at an alarming rate. Among the tools used by cybercriminals, malicious domains are indispensable and harm from the Internet has become a global problem. Malicious domains play an important role from SPAM and Cross-Site Scripting (XSS) threats to Botnet and Advanced Persistent Threat (APT) attacks at large scales. To ensure there is not a single point of failure or to prevent their detection and blocking, malware authors have employed domain generation algorithms (DGAs) and domain-flux techniques to generate a large number of domain names for malicious servers. As a result, malicious servers are difficult to detect and remove. Furthermore, the clues of cybercrime are stored in network traffic logs, but analyzing long-term big network traffic data is a challenge. To adapt the technology of cybercrimes and automatically detect unknown malicious threats, we previously proposed a system called MD-Miner. To improve its efficiency and accuracy, we propose the MD-MinerP here, which generates more features with identification capabilities in the feature extraction stage. Moreover, MD-MinerP adapts interaction profiling bipartite graphs instead of annotated bipartite graphs. The experimental results show that MD-MinerP has better area under curve (AUC) results and found new malicious domains that could not be recognized by other threat intelligence systems. The MD-MinerP exhibits both scalability and applicability, which has been experimentally validated on actual enterprise network traffic.


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