Extraction Process Research Articles

Comparison of Different Extraction and Purification Methods of Lime Peel Pectin and Evaluation of Physiochemical, Rheological, and Textural Properties

Background:: Pectin production has recently attracted considerable research interest due to its various applications arising from its unique characteristics. Lime peel, as a by-product of juice factories, has a promising potential for pectin extraction. Methods:: Lime peel pectin samples were extracted by three extraction processes: a) 90°C of heating for 120 min, b) 90°C of heating for 90 min and then 32 min of sonication, and c) 80°C of heating for 60 min and then 22 min of sonication. Then, they were purified either by ethanol or sodium caseinate (SC) and characterized. Results:: SC purification did not enhance the pectin yield; rather, it diminished the level of nonpectin components and resulted in purer pectin (i.e., lower sugar content). The samples purified with SC showed much lower viscosity in solution and storage modulus than the samples purified with ethanol, which could be attributed to their lower sugar content and higher pH (~ 4.6 vs. 2). However, pectin samples purified with SC had a relatively high sugar gel consistency, maybe due to protein retention in their structure as well as the preferential hydration effect of added sucrose. Conclusion:: The compact and extended conformations of the pectin sample, which was extracted by “(c) extraction method” and purified with ethanol, resulted in its high viscosity and storage modulus in solution and the highest gel consistency (16.91 Kg.s) compared to the other samples. Regardless of the conditions of extraction procedures, the purification method had a considerable impact on the pectin samples’ characteristics and potential applications.

Implementation of pumped hydro/photovoltaic systems in mining-degraded areas: a case study in Quadrilátero Ferrífero, Minas Gerais, Brazil

This work presents a proposal for the transformation of mining-degraded areas into renewable energy installations, converting deactivated mine pits, in the Quadrilátero Ferrífero (QF) region in state of Minas Gerais (MG), Brazil, into reservoirs for Pumped Storage Hydropower (PSH). Additionally, it proposes the alteration of adjacent areas impacted by mining extraction process, through their conversion into Photovoltaic Power Plants (PV). This measure has the potential to turn mining liabilities into sources of energy with lower environmental impact and sustainability for society. This process allows energy to be stored in the form of hydraulic batteries, which can mitigate the effects of intermittency of photovoltaic generation in the electrical grid. The presented methodology involves mapping deactivated mines, calculating the energy potential of the coupled PSH and PV systems, and conducting an economic feasibility study for PSH implementation. The work includes a case study discussing potential local environmental impacts and the energy potentials of this solution. The case study resulted in identifying a suitable pair of mine pits for a PSH in the QF, capable of supplying the electrical grid with approximately 234.3 MW, with the generated energy cost ranging between U$112.26/MWh to U$167.22/MWh. It is concluded that utilizing inactive mines as PSH reservoirs and installing PV in adjacent mining-degraded areas are innovative and technologically feasible strategies. Economically, their implementation will depend on the market price of energy.

Recovery of Vanadium from Carbonated Solution by Extraction with Transformed Aliquat 336 and Stripping-Precipitation

ABSTRACT The leaching solution from the direct reduction-sodium smelting process of ultra-poor vanadium-bearing titanomagnetite contained sodium, vanadium, and impurities. It was carbonated to ensure sodium recovery, and the recovery of vanadium proved challenging. This study proposed and optimized a novel process of extracting vanadium from this alkaline carbonated solution using the transformed organic phase of 20 vol% (0.44 mol/L) Aliquat 336, 8 vol% 2-octanol, and 72 vol% sulfonated kerosene. To achieve superior vanadium extraction, Aliquat 336 in the organic phase was transformed into carbonate type by successively washing with NaHCO3 and NaOH solutions. The single-stage extraction efficiency of vanadium exceeded 85% at a pH of 8.0‒9.0 and an organic-to-aqueous phase ratio of 1:1. The thermodynamics of the vanadium extraction process was examined, confirming that the extraction process is an exothermic reaction (ΔH 0 = −9.56 kJ/mol). Furthermore, using a solution of 4 mol/L NH4Cl and 1 mol/L NH4OH with a pH of 8.8 as the effective stripping reagent to realize one-step stripping and precipitation of vanadium, the single-stage stripping efficiency of vanadium was 99.8%, and the precipitation efficiency was about 95%. Through this stripping-precipitation process, solid ammonium metavanadate with a purity of 98.14% was obtained in one step. The mechanisms of transformation, extraction, and stripping were studied via infrared spectra of the organic phases.

Innovative Application of Juniperus Communis Wood Oil in Acne Skincare:

This review study explores the potential of Juniperus communis wood oil in cosmetics, namely its efficacy in treating acne diseases and its antibacterial qualities. Acne is a common skin ailment characterized by inflammation and the presence of several forms of acne lesions. Traditional acne treatments sometimes involve medications that may have possible side effects, which has sparked a growing interest in natural alternatives with antibacterial properties. Juniperus communis, commonly referred to as juniper, is extensively utilized in traditional medicine for its firmly established therapeutic advantages. This article consolidates the current scientific literature on the use of Juniperus communis wood oil for acne treatment, encompassing its mechanisms of action and its capacity to attack acne-causing bacteria by means of its antimicrobial properties. The review analyzes the anti-inflammatory, antioxidant, sebum-regulating, and anti-comedogenic properties of Juniperus communis wood oil. The paper also evaluates the efficacy of the treatment by analyzing its influence on many indicators, such as the decrease in the number of lesions, inflammation, and sebum production, as evidenced in clinical investigations. The text explores several aspects related to safety factors and formulation considerations, including extraction processes, synergistic effects, and appropriate administration systems. The paper presents a comprehensive analysis of the potential benefits of utilizing Juniperus communis wood oil as a treatment for acne, its potential implications for future acne therapies, and the need for further research in this area.

Probing the interaction mechanism of choline chloride-based deep eutectic solvents with flavonoid and polyphenol systems

Choline chloride-based deep eutectic solvents (DES) have been demonstrated as promising green solvents for the extraction of flavonoids and polyphenols. This study investigates the interaction between six different hydrogen bond donors (HBD) choline chloride-based DES and three types of polyphenolic flavonoid substrates. Density functional theory (DFT) and molecular dynamics (MD) simulations suggest that Cl− dominates the interaction primarily through electrostatic forces. The extraction effect of alcohol DES on rutin was optimized obviously, and the maximum interaction could reach 737.6 kJ/mol. Acid DES has a better extraction effect on anthocyanins, with a maximum interaction of 376.4 kJ/mol. With the increase of the carbon chain of HBA and the increase of the number of functional groups, the interaction between DES and the active substance decreases. As HBD, ethanolamine with both hydroxyl and amino groups showed the best effect in the extraction process of DES, forming the maximum interaction energy of 1575.8 kJ/mol. Additionally, multivariate analysis is employed to establish the relationship between different variables and interaction energy. This study provides micro-theoretical support for the extraction of flavonoids and polyphenols.

Single-step extraction/pre-formulation process for B-phycoerythrin using glycerol-based eutectic solvents: A step toward more sustainable production of phycobiliproteins

B-Phycoerythrin (B-PE) is a protein pigment of significant interest to the food and cosmetic industries. B-PE is obtained from algal or microalgal biomass, such as Porphyridium cruentum, after complex pre-treatment, extraction, and pre-formulation schemes. This work investigated the use of a single step process for the extraction and pre-formulation of B-PE from P. cruentum without complex biomass pretreatment. Five hydrophilic NaDES based on glycerol with varying water contents (20–40%) were implemented by ultrasound-assisted extraction using a one-step extraction procedure. The yields obtained were satisfaying, ranging from 5 to 15 mg of B-PE per gram of dry matter. Additionally, a purity index suitable for use in cosmetics and food products was achieved, with an average of >1.5. Furthermore, the extracts obtained in a eutectic medium demonstrated enhanced stability for B-PE, with an average loss of 10% after accelerated aging, allowing storage at room temperature without loss of quality. In particular, NaDES based on glycerol and glucose and/or betaine appeared to be the most effective in preserving the integrity and antioxidant activity of B-PE, with a range of 15–30% quenched DPPH. The ComplexGAPI tool demonstrated that our single-step NaDES process is more environmentally friendly than conventional extraction processes, thanks to lower energy consumption, reduced unitary operations, and less waste production. These results provide a solid foundation for sustainable management of the valorization of P-BE for cosmetic or food industries.

The transformation of the rotational energy of a Kerr black hole

This paper analyzes the feedback of the rotational energy extraction from a Kerr black hole (BH) by the ‘ballistic method’, i.e. the test particle decay in the BH ergosphere pioneered by Roger Penrose. The focus is on the negative energy counterrotating particles (which can be massive or massless) going in towards the horizon, and the feedback on the BH irreducible mass is assessed. Generally, the change in irreducible mass is a function of the conserved quantities of the particle. For an extreme Kerr BH and in the limit μ1/M→0 , all the reduced transformable energy goes into the irreducible mass (i.e. ΔMirr/|E1|→∞ ), resulting in high irreversibility. The amount of extracted energy from the BH using test particles is much lower than the change of transformable energy. For non-extreme Kerr BHs, the effective potential of particle motion on the equatorial plane in Kerr spacetime is analyzed, and it is demonstrated that the Penrose process can only be undergone by BHs with a dimensionless spin a^>1/2 if the decay point coincides with the turning point. Based on that, the lower limit of the change in irreducible mass is provided as a function of the dimensionless spin of the BH. The significance of the increase in the irreducible mass of the BH during the energy extraction process is generally and concisely illustrated by introducing the concept of transformable energy of the BH. The feedback from the Penrose process on the irreducible mass demonstrates the irreversibility of energy extraction and highlights that the total amount of energy that can be extracted from a BH is less than previously anticipated.

Femur bone volumetric estimation for osteoporosis classification based on deep learning with tuna jellyfish optimization using X-ray images

Osteoporosis is a disorder, that leads to fractures and fatal problems in bones. It is believed that more than 200 million individuals are affected globally. Furthermore, osteoporosis is caused by micro-architectural degeneration of bone tissues, which increases the risk of bone fragility and fractures. Moreover, the osteoporosis categorization is essential for the medical industry, which classifies the skeleton problems of individuals caused by ageing. This work presented the prediction of femur bone volume for osteoporosis classification. Moreover, the femur bone X-ray image is utilized for the classification. The preprocessing phase is employed to neglect the noise contained in input bone images through a non-local means filter. In the image segmentation process, the SegNet is utilized to isolate the specific portion. Moreover, the template search approach based on femoral geometric estimation is carried out and the feature extraction phase is essential for a significant feature extraction process. The proposed tuna jellyfish optimization based deep batch-normalized eLU AlexNet (DbneAlexNet) is utilized in the osteoporosis classification process. Furthermore, accuracy, Positive Predictive Value (PPV), Negative Predictive Value (NPV), True Positive Rate (TPR) and True Negative Rate (TNR) are the metrics to validate the model and the superior values 0.913, 0.906, 0.896, 0.923 and 0.932 are achieved.

Prediction model of early recurrence of multimodal hepatocellular carcinoma with tensor fusion

Objective. In oncology, clinical decision-making relies on a multitude of data modalities, including histopathological, radiological, and clinical factors. Despite the emergence of computer-aided multimodal decision-making systems for predicting hepatocellular carcinoma (HCC) recurrence post-hepatectomy, existing models often employ simplistic feature-level concatenation, leading to redundancy and suboptimal performance. Moreover, these models frequently lack effective integration with clinically relevant data and encounter challenges in integrating diverse scales and dimensions, as well as incorporating the liver background, which holds clinical significance but has been previously overlooked. Approach. To address these limitations, we propose two approaches. Firstly, we introduce the tensor fusion method to our model, which offers distinct advantages in handling multi-scale and multi-dimensional data fusion, potentially enhancing overall performance. Secondly, we pioneer the consideration of the liver background’s impact, integrating it into the feature extraction process using a deep learning segmentation-based algorithm. This innovative inclusion aligns the model more closely with real-world clinical scenarios, as the liver background may contain crucial information related to postoperative recurrence. Main results. We collected radiomics (MRI) and histopathological images from 176 cases diagnosed by experienced clinicians across two independent centers. Our proposed network underwent training and 5-fold cross-validation on this dataset before validation on an external test dataset comprising 40 cases. Ultimately, our model demonstrated outstanding performance in predicting early recurrence of HCC postoperatively, achieving an AUC of 0.883. Significance. These findings signify significant progress in addressing challenges related to multimodal data fusion and hold promise for more accurate clinical outcome predictions. In this study, we exploited global 3D liver background into modelling which is crucial to to the prognosis assessment and analyzed the whole liver background in addition to the tumor region. Both MRI images and histopathological images of HCC were fused at high-dimensional feature space using tensor techniques to solve cross-scale data integration issue.

Influence of the Extraction Process on the Mechanical and Morphological Properties of Technical Fibers from Typha domingensis

ABSTRACT Typha is a fast-growing and invasive plant that spreads in the humid areas. Its proliferation has a negative impact on the local ecosystems. This study aims at the valorization of the by-products of this plant as biocomposites’ reinforcements. A mechanical extraction technique and retting in distilled water and sea water processes were developed to extract fibers from the leaves and stems of the Typha plants. SEM, FTIR analyses and monotonic tensile tests have been carried out to assess fibers’ properties. Morphological observations revealed that fibers extracted from the leaves were on average 48% finer than those from the stems. This fineness was more significant for the fibers retted in distilled water, that presented a smoother surface. The leaf fibers tensile properties (502, 247 and 372 MPa for the strength, 20.5, 14.2 and 12.8 GPa for the Young’s modulus and 2.47, 1.68 and 2.73% for maximum strain, respectively for the mechanical, distilled water and sea water retting processes) were on average 50% higher than for stem fibers, regardless of the extraction method. The results showed that the fibers elaborated had promising properties for biocomposite reinforcement. The extraction methods developed are low cost and without the use and generation of polluting chemicals

Adaptive RAO ensembled dichotomy technique for the accurate parameters extraction of solar PV system

The parameter extraction process for PV models poses a complex nonlinear and multi-model optimization challenge. Accurately estimating these parameters is crucial for optimizing the efficiency of PV systems. To address this, the paper introduces the Adaptive Rao Dichotomy Method (ARDM) which leverages the adaptive characteristics of the Rao algorithm and the Dichotomy Technique. ARDM is compared with the several recent optimization techniques, including the tuna swarm optimizer, African vulture’s optimizer, and teaching–learning-based optimizer. Statistical analyses and experimental results demonstrate the ARDM's superior performance in the parameter extraction for the various PV models, such as RTC France and PWP 201 polycrystalline, utilizing manufacturer-provided datasheets. Comparisons with competing techniques further underscore ARDM dominance. Simulation results highlight ARDM quick processing time, steady convergence, and consistently high accuracy in delivering optimal solutions.

RSM- and ANN-Based Multifrequency Ultrasonic Extraction of Polyphenol-Rich Sargassum horneri Extracts Exerting Antioxidative Activity via the Regulation of MAPK/Nrf2/HO-1 Machinery.

Sargassum horneri (SH) is widely consumed as a healthy seaweed food in the Asia-Pacific region. However, the bioactive components contributing to its biological activity remain unknown. Herein, we optimized multifrequency ultrasonic-assisted extraction conditions to achieve higher antioxidant activity using a response surface methodology and an artificial neural network. High-resolution mass spectrometry (HRMS; negative mode) was used to tentatively identify the secondary metabolites in the optimized SH extract, which were further tested against oxidative stress in RAW264.7 cells. Additionally, the identified compounds were analyzed in silico to determine their binding energies with the Keap1 protein (4L7B). We identified 89 compounds using HRMS, among which 19 metabolites (8 polyphenolics, 2 flavonoids, 2 lignans, 2 terpenes, 2 tannins, 2 sulfolipids, and 1 phospholipid) were putatively reported for the first time in SH. The in vitro results revealed that optimized SH extract inhibited oxidative stress via the Nrf2/MAPKs/HO-1 pathway in a dose-dependent manner. This result was validated by performing in silico simulation, indicating that sargaquinoic acid and glycitein-7-O-glucuronide had the highest binding energies (-9.20 and -9.52 Kcal/mol, respectively) toward Keap1 (4L7B). This study offers a unique approach for the scientific community to identify potential bioactive compounds by optimizing the multivariant extraction processing conditions, which could be used to develop functional and nutraceutical foods.

Solar‐Driven Lithium Extraction by a Floating Felt

AbstractOceans/brine offers a massive supply of lithium sources that can support the renewable energy storage system. However, the current lithium extraction processes from seawater are complicated for scalable production. Here, a high‐performance solar‐driven, direct lithium‐extraction felt (DEF) is developed. DEF consists of a reasonable addition of Li1.6Mn1.6O4 particles on polypropylene/polyethylene core‐sheath fibers, which are dark‐colored and can float on top of bodies of water. Compared with the conventional method, DEF shows improved Li‐ion adsorption rate and capacity by solar‐driven. Meanwhile, the fibers’ hydrophilicity promotes spontaneous upward transport of water/ions, avoiding concentration polarization. Even for the test using simulated seawater (≈100 kg) with low Li‐ion concentration outdoors, DEF demonstrates high efficiency under natural sunlight. DEF shows good salt‐rejection performance in outdoor real‐time evaporation experiments to ensure working stability. In addition, this method saves the steps of liquid storage, liquid transportation, and pump drive. This work provides an easy, highly efficient, and low‐cost strategy to extract lithium directly from seawater/brine with the assistance of solar energy.

SD-YOLOv8: An Accurate Seriola dumerili Detection Model Based on Improved YOLOv8.

Accurate identification of Seriola dumerili (SD) offers crucial technical support for aquaculture practices and behavioral research of this species. However, the task of discerning S. dumerili from complex underwater settings, fluctuating light conditions, and schools of fish presents a challenge. This paper proposes an intelligent recognition model based on the YOLOv8 network called SD-YOLOv8. By adding a small object detection layer and head, our model has a positive impact on the recognition capabilities for both close and distant instances of S. dumerili, significantly improving them. We construct a convenient S. dumerili dataset and introduce the deformable convolution network v2 (DCNv2) to enhance the information extraction process. Additionally, we employ the bottleneck attention module (BAM) and redesign the spatial pyramid pooling fusion (SPPF) for multidimensional feature extraction and fusion. The Inner-MPDIoU bounding box regression function adjusts the scale factor and evaluates geometric ratios to improve box positioning accuracy. The experimental results show that our SD-YOLOv8 model achieves higher accuracy and average precision, increasing from 89.2% to 93.2% and from 92.2% to 95.7%, respectively. Overall, our model enhances detection accuracy, providing a reliable foundation for the accurate detection of fishes.

Quantification of Methane Emissions from Cold Heavy Oil Production with Sand Extraction in Alberta and Saskatchewan, Canada.

Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.

Date pomace polysaccharide: ultrasonic-assisted deep eutectic solvent extraction, physicochemical properties, biological activities, gut microbiota modulation, and rheological properties

BackgroundThis study utilized ultrasonication-assisted green extraction techniques to explore the physicochemical, rheological, biological, and prebiotic properties, alongside gut modulation abilities of novel polysaccharides extracted from date pomace. The extraction aimed at enhancing the utilization of date pomace, a by-product of date fruit processing, by investigating its potential as a functional food ingredient. The research focused on optimizing the extraction process, understanding the complex structure of the polysaccharides, and assessing their various health-related functionalities.ResultsThe ultrasonically extracted polysaccharides (UPS) were identified as a mixture of significant bioactive compounds including galacturonic acid, galactose, glucose, arabinose, and fructose, showcasing a high molecular weight of 537.7 kDa. The study found that UPS exhibited outstanding antioxidant activities, with scavenging abilities ranging from 59 to 82% at a concentration of 1000 mg/L. Additionally, UPS demonstrated potent inhibitory effects on α-amylase (83%), α-glucosidase (81%), and ACE-inhibition (45%), alongside strong antiproliferative activities against Caco-2 and MCF-7 cancer cell lines and broad-spectrum antimicrobial properties. Remarkably, UPS also enhanced the abundance of beneficial gut microbiota, including Actinobacteria, Firmicutes, and Proteobacteria, during in vitro fermentations and positively modulated gut metabolic pathways, promoting the production of major short-chain fatty acids. UPS had higher abundance in pathways related to cofactors, vitamins, electron carriers, and prosthetic groups biosynthesis compared to blank.ConclusionsThe findings affirm the potential of UPS extracted from date pomace as an innovative and promising functional food ingredient. Its high molecular weight, complex sugar composition, significant antioxidant, antimicrobial, antiproliferative activities, and prebiotic properties make it a valuable resource for promoting health and managing diseases. This study paves the way for further research on the bioavailability and physiological effects of UPS in vivo, highlighting the importance of sustainable utilization of agricultural by-products in developing functional foods that support human health.Graphical

Single-frame double-grating interferometry with two inherent-phase-shifted interferograms

In this work, we introduce a novel self-referencing, common-path, double-grating interferometry method for studying slowly varying phase samples. Two plane wave diffraction orders of the gratings, namely (0,+1) and (+1,0), with a certain phase difference, interfere with each other in a single frame. When a phase sample is applied in the middle of the impinging beam, two simultaneous inherent phase-shifted interferograms are generated on either side of the interference pattern. In one interferogram, the sample phase is added to (0,+1), while in the second one, the sample phase is added to (+1,0). Consequently, the phase of the first interferogram increases by the amount of the sample phase, while in the second interferogram, it decreases by the same amount. Without a phase sample, both interferograms have uniform intensity and value since the two interfering beams have the same phase difference in both patterns. We observe that the intensity changes in the two interferograms due to the phase sample, depending on the initial phase difference between the two interfering beams, can be equal or unequal, and in certain circumstances, they can be even complementary. We introduce a specific phase difference between the interfering orders by precisely controlling the separation between two diffraction gratings. This allows us to extract the sample's phase information from the resulting pair of interferograms. This setup enables us to obtain the sample phase without applying an additional phase shift(s) between the interfering beams. The method was applied to a thermal lens induced in a nonlinear liquid sample containing absorbent nanoparticles. The proposed method is characterized by its simplicity, accuracy, and insensitivity to vibrations, making it well-suited for analyzing dynamic samples with millimeter scales, such as nearly transparent organisms. The theory, simulations, and experimental results presented in this paper are found to be consistent. Unlike conventional methods, our approach does not necessarily require a reference interferogram. Additionally, when the absolute value of phase changes over the sample area and time is less than π, the raw phase pattern precisely matches the reconstructed phase pattern of the sample, eliminating the need for a phase-reconstructing algorithm. The phase pattern can be accurately calculated from the interferograms using an arcsine function without needing a fast Fourier transform. Compared to Fourier-based methods, the phase extraction process for each frame in our approach is 60 times faster. As a result, this technique operates in real-time for |φ(x, y;t) | < π.

Evaluation of a Novel Fungicidal Extract from Blue Spruce, Picea pungens

Aqueous extracts from 22 species of evergreen plants and 32 accessions of spruce ( Picea A. Dietr.) were screened using an in vitro assay to determine their antifungal activity against Calonectria henricotiae, one of the causal agents of boxwood blight. Most of the evergreen species and all the spruce accessions showed significant antifungal activity ( P < 0.05); in particular, the extract from one accession of Picea pungens Engelm. had significant effective fungistatic and fungicidal activity ( P < 0.05), both in vitro and when tested on detached boxwood leaves and whole boxwood plants. The extraction process was simple, consisting of autoclaving fresh leaves in water, and, once extracted, the active compound was stable in aqueous solution and when lyophilized and reconstituted. Further investigations will focus on the potential of this extract as an alternative to traditional fungicides for use in a wide range of crops and in diverse applications, from controlling fungal infections in the landscape to preventing postharvest losses in fruit and vegetable crops.

Temporal Attention for Few-Shot Concept Drift Detection in Streaming Data

Concept drift describes unforeseeable changes in the underlying distribution of streaming data over time. Concept drift is a phenomenon in which the statistical properties of a target domain change over time in an arbitrary way. These changes might be caused by changes in hidden variables that cannot be measured directly. With the onset of the big data era, domains such as social networks, meteorology, and finance are generating copious amounts of streaming data. Embedded within these data, the issue of concept drift can affect the attributes of streaming data in various ways, leading to a decline in the accuracy and performance of models. There is a pressing need for new models to re-adapt to the changes in streaming data. Traditional concept drift detection algorithms struggle to effectively capture and utilize the key feature points of concept drift within complex time series, thereby failing to maintain the accuracy and efficiency of the models. In light of these challenges, this study introduces a novel concept drift detection method that incorporates a temporal attention mechanism within a prototypical network. By integrating a temporal attention mechanism during the feature extraction process, our approach enhances the capability to process complex time series data, preserves temporal locality, strengthens the learning of key features, and reduces the amount of labeled data required. This method significantly improves the detection accuracy and efficiency of small sample streaming data by better capturing the local features of the data. Experiments conducted across multiple datasets demonstrate that this method exhibits comprehensive leading performance in terms of accuracy and F1-score, with excellent recall and precision, thereby validating its effectiveness in enhancing concept drift detection in streaming data.

Extraction and Purification of Squalene from Virgin Olive Oil via Catalytic Transesterification and Molecular Distillation

Squalene, a highly valuable compound abundant in various natural sources, shows great potential in pharmaceutical, cosmetic, and nutraceutical applications. This research article outlines a comprehensive methodology for extracting and purifying squalene from virgin olive oil, a rich source of the compound. The extraction process begins with degumming, which involves heating the olive oil to 60-70°C to reduce viscosity, followed by the addition of 2-3% warm water to hydrate phospholipids. Food-grade phosphoric acid is then added to react with the phospholipids, forming precipitates. The mixture is stirred for 20-30 minutes and allowed to rest for an additional 20-30 minutes, enabling impurities to settle. The upper layer of degummed oil is separated via decantation or centrifugation and washed with warm water for pH adjustment. Next, transesterification is performed by mixing 100 ml of virgin olive oil with 25% methanol (w/w) and a catalyst (0.5% sodium methoxide or PTSA), and heating the mixture to 80-90°C under reflux for 1-2 hours. Following transesterification, the solvent and acetone are distilled out, and acetone precipitation is repeated 2-3 times to remove unsaponified matter, which is then filtered and evaporated. The concentrated oil undergoes molecular distillation at 180°C and 0.0033 bar pressure for 1 hour, yielding the distillate and residue for further analysis. Qualitative analysis using Thin Layer Chromatography (TLC) involves Merck TLC plates with silica gel 60 F254 and a hexane: chloroform (9:1) mobile phase. Spots are developed with a 10% HCl solution, confirming the presence of squalene with an RF value of 0.93. Quantitative analysis via High-Performance Thin-Layer Chromatography (HPTLC) employs Merck TLC plates with cyclohexane as the mobile phase and CAMAG at 254 nm and 366 nm wavelengths, revealing a squalene purity of 67% and a recovery rate of 69.8%. The initial purification through transesterification facilitated the conversion of ester groups, yielding squalene-rich fractions, while acetone precipitation effectively removed saponified matter. Molecular distillation further enhanced squalene purity. TLC analysis confirmed the qualitative presence of squalene, and HPTLC provided precise quantitative measurements. The obtained squalene purity of 67% significantly enriches the initial content in virgin olive oil, though further optimization could enhance purity and yield. Complementary techniques like GC-MS or HPLC could validate the purification process. This study presents an efficient, replicable procedure for extracting and purifying squalene from virgin olive oil, with significant implications for pharmaceutical, cosmetic, and nutraceutical industries. The findings support a sustainable and ethical shift towards vegetable-derived squalene, meeting market demands while ensuring high-quality production.