extraction process
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2022 ◽  
Vol 13 (1) ◽  
pp. 1-11
Shih-Chia Huang ◽  
Quoc-Viet Hoang ◽  
Da-Wei Jaw

Despite the recent improvement of object detection techniques, many of them fail to detect objects in low-luminance images. The blurry and dimmed nature of low-luminance images results in the extraction of vague features and failure to detect objects. In addition, many existing object detection methods are based on models trained on both sufficient- and low-luminance images, which also negatively affect the feature extraction process and detection results. In this article, we propose a framework called Self-adaptive Feature Transformation Network (SFT-Net) to effectively detect objects in low-luminance conditions. The proposed SFT-Net consists of the following three modules: (1) feature transformation module, (2) self-adaptive module, and (3) object detection module. The purpose of the feature transformation module is to enhance the extracted feature through unsupervisely learning a feature domain projection procedure. The self-adaptive module is utilized as a probabilistic module producing appropriate features either from the transformed or the original features to further boost the performance and generalization ability of the proposed framework. Finally, the object detection module is designed to accurately detect objects in both low- and sufficient- luminance images by using the appropriate features produced by the self-adaptive module. The experimental results demonstrate that the proposed SFT-Net framework significantly outperforms the state-of-the-art object detection techniques, achieving an average precision (AP) of up to 6.35 and 11.89 higher on the sufficient- and low- luminance domain, respectively.

Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 506
Jie Lu ◽  
Zhiqiang Huang ◽  
Yusheng Liu ◽  
Huimin Wang ◽  
Min Qiu ◽  

Flavonoids have important biological activities, such as anti-inflammatory, antibacterial, antioxidant and whitening, which is a potential functional food raw material. However, the biological activity of Fengdan peony flavonoid is not particularly clear. Therefore, in this study, the peony flavonoid was extracted from Fengdan peony seed meal, and the antioxidant, antibacterial and whitening activities of the peony flavonoid were explored. The optimal extraction conditions were methanol concentration of 90%, solid-to-liquid ratio of 1:35 g:mL, temperature of 55 °C and time of 80 min; under these conditions, the yield of Fengdan peony flavonoid could reach 1.205 ± 0.019% (the ratio of the dry mass of rutin to the dry mass of peony seed meal). The clearance of Fengdan peony total flavonoids to 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical, hydroxyl radical and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical could reach 75%, 70% and 97%, respectively. Fengdan peony flavonoid could inhibit the growth of the Gram-positive bacteria. The minimal inhibitory concentrations (MICs) of Fengdan peony flavonoid on S. aureus, B. anthracis, B. subtilis and C. perfringens were 0.0293 mg/mL, 0.1172 mg/mL, 0.2344 mg/mL and 7.500 mg/mL, respectively. The inhibition rate of Fengdan peony flavonoid on tyrosinase was 8.53–81.08%. This study intensely illustrated that the antioxidant, whitening and antibacterial activity of Fengdan peony total flavonoids were significant. Fengdan peony total flavonoids have a great possibility of being used as functional food materials.

2022 ◽  
Vol 16 (1) ◽  
pp. 54
Imam Husni Al amin ◽  
Awan Aprilino

Currently, vehicle number plate detection systems in general still use the manual method. This will take a lot of time and human effort. Thus, an automatic vehicle number plate detection system is needed because the number of vehicles that continues to increase will burden human labor. In addition, the methods used for vehicle number plate detection still have low accuracy because they depend on the characteristics of the object being used. This study develops a YOLO-based automatic vehicle number plate detection system. The dataset used is a pretrained YOLOv3 model of 700 data. Then proceed with the number plate text extraction process using the Tesseract Optical Character Recognition (OCR) library and the results obtained will be stored in the database. This system is web-based and API so that it can be used online and on the cross-platform. The test results show that the automatic number plate detection system reaches 100% accuracy with sufficient lighting and a threshold of 0.5 and for the results using the Tesseract library, the detection results are 92.32% where the system is successful in recognizing all characters on the license plates of cars and motorcycles. in the form of Alphanumeric characters of 7-8 characters.

Membranes ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 90
Salar Bahrami ◽  
Leila Dolatyari ◽  
Hassan Shayani-Jam ◽  
Mohammad Reza Yaftian ◽  
Spas D. Kolev

A polymer inclusion membrane (PIM) composed of 50 wt% base polymer poly(vinylidenefluoride-co-hexafluoropropylene), 40 wt% extractant Aliquat® 336, and 10 wt% dibutyl phthalate as plasticizer/modifier provided the efficient extraction of vanadium(V) (initial concentration 50 mg L−1) from 0.1 M sulfate solutions (pH 2.5). The average mass and thickness of the PIMs (diameter 3.5 cm) were 0.057 g and 46 μm, respectively. It was suggested that V(V) was extracted as VO2SO4− via an anion exchange mechanism. The maximum PIM capacity was estimated to be ~56 mg of V(V)/g for the PIM. Quantitative back-extraction was achieved with a 50 mL solution of 6 M H2SO4/1 v/v% of H2O2. It was assumed that the back-extraction process involved the oxidation of VO2+ to VO(O2)+ by H2O2. The newly developed PIM, with the optimized composition mentioned above, exhibited an excellent selectivity for V(V) in the presence of metallic species present in digests of spent alumina hydrodesulfurization catalysts. Co-extraction of Mo(VI) with V(V) was eliminated by its selective extraction at pH 1.1. Characterization of the optimized PIM was performed by contact angle measurements, atomic-force microscopy, energy dispersive X-ray spectroscopy, thermogravimetric analysis/derivatives thermogravimetric analysis and stress–strain measurements. Replacement of dibutyl phthalate with 2-nitrophenyloctyl ether improved the stability of the studied PIMs.

2022 ◽  
Vol 12 (2) ◽  
pp. 831
Hamida Akli ◽  
Spyros Grigorakis ◽  
Abdessamie Kellil ◽  
Sofia Loupassaki ◽  
Dimitris P. Makris ◽  

The extraction of phenolic compounds from olive leaves was optimized using three glycerol-based deep eutectic solvents (DESs) with lysine, proline, and arginine. A three-level Box–Behnken design was used to examine the influence of the liquid/solid ratio, concentration of DESs, and extraction temperature on the yield of the extraction process. A second-order polynomial model was used for predicting the polyphenol extraction yield. The optimal predicted conditions were used for extractions and they provided the highest total phenol yields with the glycerol–lysine exhibiting the best performance. Quantification of tyrosol, hydroxytyrosol, oleuropein, luteolin-7-O-glucoside, and rutin in the extracts showed high content in tyrosol in all DESs, particularly with glycerol–lysine and relatively similar contents with other studies for the other phenolic compounds. Finally, a linear relationship between tyrosol content and the total phenolic content of the extracts was observed.

BMC Chemistry ◽  
2022 ◽  
Vol 16 (1) ◽  
Sanae Tarhouchi ◽  
Rkia Louafy ◽  
El Houssine El Atmani ◽  
Miloudi Hlaïbi

Abstract Background Paracetamol compound remains the most used pharmaceutical as an analgesic and antipyretic for pain and fever, often identified in aquatic environments. The elimination of this compound from wastewater is one of the critical operations carried out by advanced industries. Our work objective was to assess studies based on membrane processes by using two membranes, polymer inclusion membrane and grafted polymer membrane containing gluconic acid as an extractive agent for extracting and recovering paracetamol compound from aqueous solutions. Result The elaborated membrane characterizations were assessed using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Kinetic and thermodynamic models have been applied to determine the values of macroscopic (P and J0), microscopic (D* and Kass), activation and thermodynamic parameters (Ea, ΔH#, ΔS#, ΔH#diss, and ΔH#th). All results showed that the PVA–GA was more performant than its counterpart GPM–GA, with apparent diffusion coefficient values (107D*) of 41.807 and 31.211 cm2 s−1 respectively, at T = 308 K. In addition, the extraction process for these membranes was more efficient at pH = 1. The relatively low values of activation energy (Ea), activation association enthalpy (ΔH≠ass), and activation dissociation enthalpy (ΔH≠diss) have indicated a kinetic control for the oriented processes studied across the adopted membranes much more than the energetic counterpart. Conclusion The results presented for the quantification of oriented membrane process ensured clean, sustainable, and environmentally friendly methods for the extraction and recovery of paracetamol molecule as a high-value substance.

Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 177
Gianfranco Gagliardi ◽  
Antonio Igor Maria Cosma ◽  
Francesco Marasco

The high demand of information and communication technology (ICT) in agriculture applications has led to the introduction of the concept of smart farming. In this respect, moving from the main features of the Fourth Industrial Revolution (Industry 4.0) promoted by the European Community, new approaches have been suggested and adopted in agriculture, giving rise to the so-called Agriculture 4.0. Improvements in automation, advanced information systems and Internet technologies allow for farmers to increase the productivity and to allocate the resources reasonably. For these reasons, agricultural decision support systems (DSS) for Agriculture 4.0 have become a very interesting research topic. DSS are interactive tools that enable users to make informed decisions about unstructured problems, and can be either fully computerized, human or a combination of both. In general, a DSS analyzes and synthesizes large amounts of data to assist in decision making. This paper presents an innovative decision support system solution to address the issues faced by coconut oil producers in making strategic decisions, particularly in the comparison of different methods of oil extraction. In more detail, the adopted methodology describes how to address the problems of coconut oil extraction in order to minimize the processing time and processing cost and to obtain energy savings. To this end, the coconut oil extraction process of the Leão São Tomé and Principe Company is presented as a case study: a DSS instance that analyzes the problem of the optimal selection between two different oil coconut extraction methods (fermentation-based and standard extraction processes) is developed as a meta-heuristics with a mixed integer linear programming problem. The obtained results show that there is clearly a trade-off between the increase in cost and reliability that the decision-maker may be willing to evaluate. In this respect, the proposed model provides a tool to support the decision-maker in choosing the best combination between the two different coconut oil extraction methods. The proposed DSS has been tested in a real application context through an experimental campaign.

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