Extraction Process Research Articles

Phytochemical screening of three extraction process of Calotropis gigantea

Abstract Calotropis gigantea is a flowering plant belonging to the genus Calotropis of the family Asclepiadaceae. Many pharmacological activities of this plant show potential in human therapy. In this study, an investigation was conducted on the three extracted process namely n-hexane extract, ethyl acetate extract and ethanolic extract of C. gigantea collected from a coastline at Alue Naga beach, Banda Aceh, Indonesia. Percent yield of C. gigantea leaf extract was mostly produced by ethanol solvent compared to ethyl acetate and n-hexane solvents, with total 8.25 grams (4.12%), 5.62 grams (2.80%), and 4.51 grams (2.25%), respectively. The results of phytochemical screening explained that the ethanol extract of C. gigantea leaves had abundant secondary metabolite compounds, compared to the n-hexane extract, only the steroid compounds were detected. The ethyl acetate extract of C. gigantea leaves showed the presence of flavonoids, triterpenoids, tannins, and phenolic compounds, but no saponins and alkaloids were found. These observations underscore the exciting potential of C. gigantea as a promising reservoir of flora rich in alkaloids, flavonoids, phenolics, tannins, saponins, and steroid compounds, derived from the coast so that it can be used as a drug candidate.

Optimized reversible data hiding technique based on multidirectional prediction error histogram and fluctuation-based adaptation

Optimized reversible data hiding technique based on multidirectional prediction error histogram and fluctuation-based adaptation

From waste to added-value product: A case of efficient separation and recovery of zinc and iron from spent galvanizing acid

Spent galvanizing acid solution contains high concentrations of zinc salts, ferrous salts, and residual acids, exhibiting extremely high value-added recovery potential. However, achieving the efficient extraction and separation of Zn over Fe becomes particularly challenging under elevated Zn ion concentration. Here, the key extraction parameters, such as modifier ratio, Cyanex 923 concentration and ratio of organic phase to aqueous phase (O/A), are investigated. The stripping and regeneration of extractant, extraction mechanism, as well as high-value recovery of Zn and Fe resources are also comprehensively expounded. After the two-stage extraction, the extraction efficiency of Zn and Fe is 98.92 ​% and 2.09 ​%, respectively. Moreover, the stripping efficiency of Zn reaches 92.3 ​% with O/A ratio of 1 : 2, using oxalic acid as stripping agent. The predominant extracted species is confirmed to be ZnCl3−, resulting in the formation of HZnCl3∙R3PO complex. More importantly, the regenerated extractant can be recycled back into the extraction process, and the reproduced HCl, high-value recovered ZnO and Fe2O3 can be used for different industrial fields. These findings lay a solid foundation for the efficient separation and comprehensive recovery of high-concentration spent galvanizing acid solution.

Effect of extraction method on the calcium binding capacity of faba bean globulin fractions at various pH

Faba bean ingredients are rich in proteins and good sources of calcium (Ca), although containing phytic acid (PA) molecules. PA, a polyphosphate compound, can affect the bioavailability of minerals/proteins through complex formation. This study evaluates the impact of two extraction processes, Alkaline Extraction-IsoElectric Precipitation (AE-IEP) and Sequential Extraction (SE), on the ability of faba bean globulin systems to bind added calcium ions. Increasing concentrations of CaCl2 were introduced into 2.5% (w/v) protein dispersions at pHs 4.5, 5.5, 6.5, and 7.5, and free Ca monitored. Near the isoelectric point of globulin (pH ~ 4–5), Ca binding capacity was found to be low. At higher pHs, significant Ca chelation occurred, initially attributed to free PA binding sites, resulting in the formation of insoluble complexes and subsequent protein precipitation. The AE-IEP globulin fraction exhibited a higher Ca binding capacity than the SE globulin, attributed to its higher PA and lower initial Ca concentrations.

Comparative assessment with results from research on hybrid dentures over 4 implants in the mandible

The dental concept of occlusion is defined as functional contact or relationship between the teeth from the upper and the lower jaw. This equilibrium in the masticatory center of occlusion can be interrupted through various processes of tooth destruction or extraction. These alterations disturb the relationship in the occlusion, noticeably in negative direction. The dentist’s main goal is to restore the mastication center and maintain that occlusal balance. There are different options and techniques concerning the way of restoring the occlusal balance. In this article, we will consider them, describing materials and methods used, as well as their positive and negative sides

MixFormer: End-to-End Tracking With Iterative Mixed Attention.

Visual object tracking often employs a multi-stage pipeline of feature extraction, target information integration, and bounding box estimation. To simplify this pipeline and unify the process of feature extraction and target information integration, in this paper, we present a compact tracking framework, termed as MixFormer, built upon transformers. Our core design is to utilize the flexibility of attention operations, and we propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration. This synchronous modeling scheme allows us to extract target-specific discriminative features and perform extensive communication between target and search area. Based on MAM, we build our MixFormer trackers simply by stacking multiple MAMs and placing a localization head on top. Specifically, we instantiate two types of MixFormer trackers, a hierarchical tracker MixCvT, and a non-hierarchical simple tracker MixViT. For these two trackers, we investigate a series of pre-training methods and uncover the different behaviors between supervised pre-training and self-supervised pre-training in our MixFormer trackers. We also extend the masked autoencoder pre-training to our MixFormer trackers and design the new competitive TrackMAE pre-training technique. Finally, to handle multiple target templates during online tracking, we devise an asymmetric attention scheme in MAM to reduce computational cost, and propose an effective score prediction module to select high-quality templates. Our MixFormer trackers set a new state-of-the-art performance on seven tracking benchmarks, including LaSOT, TrackingNet, VOT2020, GOT-10 k, OTB100, TOTB and UAV123. In particular, our MixViT-L achieves AUC scores of 73.3% on LaSOT, 86.1% on TrackingNet and 82.8% on TOTB.

Encapsulation of Arthrospira platensis polyphenolic extract using supercritical emulsion-based process

Arthorospira platensis polyphenolic natural extracts have several benefits for human health. Due to their instability and reduced shelf-life, these extracts are usually encapsulated. This work analyzed the supercritical emulsion extraction (SFEE) processes for the production of polymeric nanoparticles loaded with Arthrospira platensis polyphenols extracts. The objective of this work was to evaluate a powdered encapsulation system to overcome the drawbacks of liquid systems, which are those mainly used for microalgae extract stabilization. An optimization study was performed investigating different process parameters comparing the obtained particles in terms of particle size distribution, morphology, and encapsulation efficiency. The process permitted to produce successfully the loaded polymeric nanoparticles with an encapsulation efficiency up to 74% in the best operating conditions. The SEE process allowed a better control of morphology and particle size distribution of the nanometric particles operating in a continuous mode.

Potential and characteristics of rare-earth metals acid bioleaching from the rare-earth-rich tailings with the enriched functional bacterial consortium: Comparison between one-step and two-step processes

The irreplaceable roles of rare-earth metals (REMs) in modern technologies have renewed interest in the grand challenges of mineral processing and metallurgical engineering—the efficient extraction of REMs. However, traditional methods for extracting REMs are inefficient, costly and harmful to health and the environment. In this study, a method of biological extraction (bioleaching), which has been proved to be effective in the field of mineral processing for extraction of the metals, was employed for REMs bioleaching from Bayan Obo rare-earth-rich tailings (RERT) using the acid functional bacterial consortium, and the optimal culture and leaching conditions were optimized. Under the optimal conditions for 18 days, the total bioleaching rate of the five main REMs of La, Ce, Pr, Nd and Sm was obtained at 82.78 % for one-step process and 83.51 % for two-step process, which has a significant improvement comparing to previous studies. The results demonstrated that REMs could be efficiently bioleached by acid bioleaching functional bacterial consortium, and the difference in leaching efficiency between the one-step and two-step bioleaching process was not significant. In addition, by analyzing the mineral composition of the RERT and leaching residue, the extensively bioleach of REMs in bastnaesite are observed. To sum up, the rare-earth resources of Bayan Obo RERT could be effectively leached by acid bioleaching method.

Improved Extraction of Crocin and Comprehensive Evaluation of its Physicochemical, Biological, and Functional Properties

Crocin, as a valuable metabolite of saffron, encompasses numerous nutritional, pharmacological, and medicinal properties suitable for different applications. This study aimed to effectively extract crocin compounds with high yield and quality from saffron stigma and comprehensively investigate their various physicochemical and functional properties. To this end, the modified solvent extraction method was used for crocin extraction and its different functional and physicochemical properties were investigated using various characterization techniques. The functional and biological properties of the resultant crocins in terms of antioxidant activity, antibacterial potency, anti-tyrosinase property, and cytotoxicity were investigated. According to the results, a high extraction yield and purity for extracted samples (19.6% and 13.4% production yield and 78% and 98.4% purity in the first and second crystallization steps, respectively) were obtained using the green, environmentally friendly, and sustainable crystallization method. The coloring index, bitterness, and aromatic power of the extracted crocin were comparable with the standard crocin. Morphological, structural, and thermal properties of the extracted crocin from different analytical methods confirmed its preserved composition and structure through the solvent extraction process. Moreover, a desired antioxidant activity by the DPPH, superoxide, hydroxyl radical scavenging, and reducing power assays were observed for resultant crocin products. In the antibacterial and cytotoxicity assays, a 5 mg/mL minimum inhibitory concentration (against Gram-positive and Gram-negative bacteria) and more than 95% cell viability (toward the NIH 3T3 cell line) were recorded, respectively. A potent anti-tyrosinase activity (IC50 = 73.93 μg/mL) with a significant reduction in the melanin production of the B16F10 cell line also was noticed for the obtained crocin products.

Enhancing accessibility and discoverability of digital archive images through automated image recognition tool

This research paper presents a comprehensive evaluation of the effectiveness of Imagga and Google cloud vision application programming interface (API) as image recognition tools for generating metadata in digital archive images. The assessment encompasses a diverse range of archive images, including those without text, images with text, and both color and black-and-white images. Through the use of evaluation metrics such as cosine similarity, word overlap similarity, recall, precision, and F1 score, the performance of these tools is quantitatively measured. The findings highlight the strong individual performance of both Imagga and Google cloud vision API, with the combined metadata outputs achieving significantly higher scores across all metrics. This emphasizes the potential benefits of employing a combined approach, leveraging the strengths of multiple tools to enhance the reliability and robustness of the metadata extraction process. The findings contribute to the advancement of metadata management in digital archives and underscore the importance of utilizing multiple tools for improved performance in image metadata generation.

Low-resolution facial emotion recognition on low-cost devices

The low-resolution input image is a crucial challenge for applying facial emotion recognition in real-world scenarios. The critical problem is that valuable object features are relatively lost in the extraction process due to their small size. On the other hand, this vision system is required by a machine to run smoothly on low-cost devices. Facial emotion recognition using a lightweight feature extractor is proposed in this study to effectively capture crucial facial components in a low-resolution image. To compromise the running speed, this work offers an efficient feature convolution to discriminate specific facial features. In addition, the system is embedded with an attentive module to capture important features and correlate them. Our model performance is evaluated on low-resolution public datasets achieving the accuracy of 97.34\%, 81.10\%, and 80.12\% on KDEF, RFDB, and FER-plus, respectively. The practical application demands that the deep learning model can operate fast on inexpensive devices. Consequently, the model achieved a speed of 290 FPS on a CPU device.

Occurrence and mechanism of sulfamethoxazole in alginate-like extracellular polymers from excess sludge

The recovery of biopolymers, particularly alginate-like extracellular polymers, from municipal sludge represents a promising step toward sustainable sludge treatment practices. Originating from wastewater plants in complexly polluted environments, alginate-like extracellular polymers carry potential environmental risks concerning their reuse. This study employs ultrahigh-performance liquid chromatography–tandem mass spectrometry to investigate the distribution coefficients and occurrence of alginate-like extracellular polymers and sulfamethoxazole. Results demonstrate a negative distribution coefficient, suggesting an inhibitory effect on sulfamethoxazole dissolution. The ethanol-extracted alginate-like extracellular polymers exhibits higher sulfamethoxazole levels (approximately 52%) than those obtained via dialysis extraction. Three-dimensional excitation-emission matrix analysis and adsorption studies indicate the absence of tyrosine-like substances in the alginate-like extracellular polymers, unlike in other extracellular polymeric substances. This absence diminishes hydrophobic interactions, highlighting that electrostatic interactions play a more important role. These insights are crucial for understanding the adsorption behavior of alginate-like extracellular polymers and optimizing their large-scale extraction processes.

A short review: fish oil extraction methods obtaining oils with high amounts of unsaturated fatty acids

Abstract Nutrition improvement can be ensured by prioritizing the consumption of animal foods, one of which is fish. Fish consumption generally requires cooking at high temperatures which trigger the protein denaturation, therefore consumption of fish oil is more beneficial for human health. However, extraction of oil from fish is quite challenging, particularly the extraction which produce high amount of unsaturated fatty acid. This short review aims to summarizes and evaluate the best fish oil extraction method by observing temperature, time, solvent ratio, oil yield, and unsaturated fatty acid content. The best quality of fish oil can be obtained through a series of extraction processes, namely the extraction without solvent and using solvent. Each fish oil extraction method takes into account several parameters, such as producing different amounts of oil with unsaturated fatty acid content. Ultrasound-assisted extraction methods provide an excellent oil yield and unsaturated fatty acids with better quality than other extraction methods. It is also underlined that fish oil obtained from the ultrasound-assisted extraction method can be used as a nutritional alternative to improve human health.

Recovery of rare earth elements from sedimentary rare earth ore via sulfuric acid roasting and water leaching

Rare earth elements were extracted using a sulfuric acid roasting-water leaching process. The effect of acid roasting on a new type of low-grade sedimentary rare earth ore found in Guizhou Province, China was analyzed using X-ray diffraction and scanning electron microscopy. A systematic study was conducted on process parameters such as amount of acid, roasting temperature, roasting time, water leaching temperature, and leaching time. The results reveal that the total recovery of rare earth elements reaches 81.37%, which is 3.1 times higher than that achieved through direct acid leaching, under the optimal conditions. In addition, the leaching rate of heavy rare earth elements reaches 72.53%. Rare earth elements and some other valuable metals are transformed into soluble sulfate through the local decomposition of clay minerals under the action of the sulfuric acid attack. The dissolution rates of aluminum, iron, and titanium ions are 34.94%, 17.05%, and 62.77%, respectively. The precipitation rate of Ti reaches 99%, and the loss of rare earth ions in the solution is less than 1%. Meanwhile, the results of a leaching kinetics analysis indicate that the leaching process of rare ions is controlled by diffusion. Precious metal ions such as iron and aluminum in the leaching solution can reduce the adsorption of rare earth ions by kaolinite. This study efficiently recovered rare earth ions under conditions of low calcination temperature and direct water leaching, resulting in reduced energy consumption of the extraction process and acidity of the leaching solution. These findings provide a solid foundation for the further separation and extraction of rare earth ions.

Machine learning approach with a posteriori-based feature to predict service life of a thermal cracking furnace with coking deposition

A thermal cracking furnace is an important equipment in the petrochemical industry that is typically used for breaking long hydrocarbons into short chains and producing coke as a byproduct. Deposition of the generated coke increases the temperature at the outside coil wall, necessitating regular furnace maintenance to prevent coil failure. Therefore, this study proposed a machine learning approach with a posteriori-based feature to predict the service life of the furnace to runtime failure. The proposed approach consists of a two-level machine learning model, which aims to improve prediction accuracy and reduce feature sensitivity. The label is classified as a week-range label, which can be categorized by classification criteria into three classes: weekly, bi-weekly, and quarter-weekly. The first-level model is utilized to extract sensor features into the posterior probability class label score. These scores are then processed and sorted into moving windows to generate features for the second-level model. The results showed that the proposed model could extract process variation and identify service needs, which improved classification accuracy by 23.94 % and 17.67 % for the clean and coke-contaminated datasets compared to the conventional classification model, respectively. Additionally, the most general class range (quarter-weekly) provided the best performance compared to the bi-weekly and weekly classes. Therefore, the model has the potential for the prediction of the furnace service life under pseudo-steady state conditions, where coking evolves gradually over time.

Novel copper-based metal–organic skeleton smart tags that respond to ammonia for real-time visual freshness monitoring of shrimp

In recent years, an amount of attention has been paid to natural pigment-based pH/ammonia-responsive colorimetric smart labels in the field of real-time visual food freshness monitoring. However, the drawbacks of natural pigments, such as complicated extraction processes, poor photostability, and easy inactivation, have severely limited their application in smart packaging. In this research, natural pigments were replaced with copper-based metal–organic frameworks (Cu-MOF) to serve as ammonia-responsive indicators. It attained the benefits of excellent mechanical qualities, high photostability, and greenness. The changes of ΔE values of the smart label composite films of starch/polyvinyl alcohol (PVA)/Cu-MOF were less than 4.8 after being placed in a constant temperature and humidity environment for 40 d, indicating that they have excellent color stability. Within an atmosphere of 0.8 mM ammonia, the composite film can produce a significant color change from teal green to deep blue in 1 min, indicating that the film has ammonia sensitivity. The composite film, in addition, successfully monitored the changes in shrimp freshness at temperatures of 4 °C and 28 °C, effectively prolonging the shelf life of the shrimp. Therefore, starch/ PVA/Cu-MOF composite films have good prospects for smart and active packaging applications.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Probabilistic analysis of seepage and temperature fields in geothermal extraction process based on discrete fracture network (DFN) model

Enhanced geothermal system is currently the most efficient technology of exploiting geothermal energy from high-temperature rock reservior in deep earth. However, due to the uncertainty of geological structural discontinuities, such as natural or artificial fractures, great challenges are encountered in conducting the precise evaluation of heat extraction within enhanced geothermal system. In this paper, a probability analysis is carried out to incorporate the uncertainty of the fracture network into the analysis of the spatial-time evolution on the seepage and temperature fields, based on a discrete fracture network based modeling scheme developed by the authors. The developed finite element model of the fractured reservior exhibits two-phase structure consisting of rock matrix and fractures, which are practically discretized into triangular elements and zero-thickness elements, respectively. The approach demonstrates a favorable comparison with the results obtained from the thereotical and other numerical solution. Monte Carlo simulation technique is then employed to probabilistically analyze the evolution of coupled thermal–hydraulic behavior, which involves 1000 different realizations considering the uncertainty of fracture structure. The results illustrate that the coefficient of variation of the seepage field decreases from 0 to 0.29 at 1 a to 0.06 to 0.15 at 50 a, averaging at 0.07, and the peak coefficient of variation of the temperature field decreases from 0.61 to 0.52, averaging at 0.27. The uncertainty of the temperature field is varying against time and prominent around the proximity to the advancing cold front, upper and lower boundaries, primarily associated with variations in fractures and constraint of boundary conditions. The existence of highly permeable fractures leads to a pronounced heterogeneity in the seepage and temperature fields within enhanced geothermal system. Furthermore, the importance of taking the uncertainty of the fracture structure into account for geothermal reservoir evaluation is highlighted, to enhance the reliability of numerical modeling for geothermal process prediction.

A short review: fish oil extraction methods obtaining oils with high amounts of unsaturated fatty acids

Abstract Nutrition improvement can be ensured by prioritizing the consumption of animal foods, one of which is fish. Fish consumption generally requires cooking at high temperatures which trigger the protein denaturation, therefore consumption of fish oil is more beneficial for human health. However, extraction of oil from fish is quite challenging, particularly the extraction which produce high amount of unsaturated fatty acid. This short review aims to summarizes and evaluate the best fish oil extraction method by observing temperature, time, solvent ratio, oil yield, and unsaturated fatty acid content. The best quality of fish oil can be obtained through a series of extraction processes, namely the extraction without solvent and using solvent. Each fish oil extraction method takes into account several parameters, such as producing different amounts of oil with unsaturated fatty acid content. Ultrasound-assisted extraction methods provide an excellent oil yield and unsaturated fatty acids with better quality than other extraction methods. It is also underlined that fish oil obtained from the ultrasound-assisted extraction method can be used as a nutritional alternative to improve human health.

Comprehensive recovery of valuable elements from vanadium precipitation liquor using selective impurity removal-reduction precipitation process

The vanadium precipitation liquor produced by the vanadium slag extraction process contains various valuable elements, which are not utilized at high value. In this paper, chromium is recovered through aluminum salt impurity removal - chemical reduction precipitation method. Moreover, the ammonia nitrogen and sodium sulfur in the vanadium precipitation liquor are recovered by stripping and crystallization, thereby achieving comprehensive resource recovery and utilization. The aluminum salt slag removal reduction chemical precipitation method is used to separate Cr from Si, Ca and V impurities. As a result, the obtained Cr2O3 product has a purity of 98.20%, the chromium recovery efficiency is 97.58%, and the silicon removal efficiency reaches 99.66%. The ammonia nitrogen was recovered by stripping, which would be reused to the vanadium precipitation process, with an ammonia nitrogen stripping efficiency of 98%. The purity of NH4Cl is 99.13% and meets the 99-level national standard. The Na2SO4 was recovered by evaporation concentration - crystallization method, which would be reused to the vanadium slag roasting process, with a Na2SO4 recovery efficiency of 88.38%. And the purity of Na2SO4 is 98.85%, which meets the industrial standard for Class II Na2SO4 products. The final solution after comprehensive recovery of valuable elements would be reused to the leaching process, thereby achieving water circulation. This process realizes the high-value utilization of chromium, ammonia, nitrogen, sodium and sulfur, and has no wastewater discharge and is an environment-friendly route.