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[Display omitted] • A novel solvent extraction technique was developed for PVC plasticizers. • Subcritical fluid dimethyl ether (DME) effectively eliminated all plasticizer. • Compatibility was evaluated using hansen solubility parameters. • DME extraction does not cause DEHP plasticizer or PVC degradation. Poly(vinyl chloride) (PVC) is one of the most widely used plastics. However, a major challenge in recycling PVC is that there is no economical method to separate and remove its toxic phthalate plasticizers. This research made a breakthrough by extracting PVC with liquefied dimethyl ether (DME) and successfully separating the plasticizer components. Nearly all (97.1 %) of the di(2-ethylhexyl) phthalate plasticizer was extracted within 30 min by passing liquefied DME (285 g) through PVC at 25 °C. The compatibility of PVC with organic solvents, including liquefied DME, was derived theoretically from their Hansen solubility parameters (HSP), and actual dissolution experiments were conducted to determine the optimal PVC solvents. A liquefied DME mixture was used to dissolve PVC, and the extract was diluted with ethanol to precipitate the dissolved PVC. We demonstrated that liquefied DME is a promising method for producing high quality recycled products and that the process retains the fundamental properties of plasticizers and PVC without inducing degradation or depolymerization. Because of its low boiling point, DME can be easily separated from the solute after extraction, allowing for efficient reuse of the solvent, extracted plasticizer, and PVC. DME does not require heat and produces little harmful wastewater, which significantly reduces the energy consumption of the plasticizer additive separation process. [ABSTRACT FROM AUTHOR]

Nowadays, the interest of the world toward nanocellulose materials has been incredibly increased for the development of high value products owing to the unique and potentially convenient structures of nanocellulose. There is advanced enhancement of the nanocellulose application with strongly increasing interest for the high demand of sustainability requirements in the global market. Nanocellulose materials are sourced from different plant fibers, algae, tunicate and bacteria. They have been synthesized through different extraction techniques like acid hydrolysis, and mechanical refining methods with increasing advancements. Nanocellulose products have potential application areas of reinforcements in nanocomposites, paper and packaging industries, biodegradable films, barriers in packaging and membrane industries, additives in food and medical applications, and medical devices, wound healing, bioactive implants and self-healing applications. This review realizes the current understandings of nanocellulose materials with source materials, isolation techniques from their sources, extraction methods and end use applications. [ABSTRACT FROM AUTHOR]

Honey bee venom (HBV) is a valuable bee product famous for its therapeutic efficacy. HBV has a complex matrix containing several compounds, of which melittin is identified as the major component and can be considered an indicator compound. According to the numerous pharmacological effects of HBV, it can be a great candidate as an efficient active pharmaceutical ingredient (API). Despite the widespread analysis of crude HBV, not enough evaluations have been conducted on HBV pharmaceutical products, which is crucial in quality control procedures. Following the importance of APIs assay, we aimed to develop a feasible and valid HBV extraction method from cosmeceutical creams using precipitation techniques, and an analysis method was developed and validated based on high‐performance liquid chromatography. The analysis was well performed with a high separation capability. The method was repeatable and accurate and exhibited a linear behavior in melittin's 0.1–1.4 mg/mL concentration range. Accordingly, the extraction method revealed a notable recovery between 86% and 104%, and a 0.007 mg/mL detection limit and 0.022 mg/mL limit of quantification were estimated, respectively. Consequently, both extraction and analysis methods were considered valid and feasible, which may influence the quality control tests of HBV pharmaceutical and cosmetic products. [ABSTRACT FROM AUTHOR]

In the current study, the effect of different new extraction methods including supercritical carbon dioxide extraction (SC -CO2), microwave - assisted extraction (MAE), and also conventional Soxhlet extraction (CSE) were investigated on bioactive compounds recovery from Silybum marianum seed. The crude extraction yield (22.40± 0.15%) was obtained using CSE, while the efficiency of SC -CO2 and MAE were about 89 and 50% of those obtained using CSE. The highest free radical scavenging activity in terms of DPPH and HO radicals was obtained in an extract obtained using SC -CO2. From the TPC analysis, the highest and lowest value was determined in extracts obtained using SC -CO2 (102.93± 0.14 mg GAE/g) and CSE (14.50± 0.18 mg GAE/g), respectively. Fatty acid composition was analyzed using Gas Chromatography –Mass Spectrometry. Linoleic and oleic acids were determined as the main fatty acids. Finally, it can be concluded that S. marianum seed is a potential source of bioactive compounds and new extraction techniques of SC - CO2 and MAE could be suggested as promising methods to substitute conventional method for successful recovery of bioactive compounds. [ABSTRACT FROM AUTHOR]

The study aims to characterize the structural features of Jordanian tar sand using analytical techniques including (FTIR, ultimate and proximate analysis, TGA, XRD, and XRF). The tar sand shows a low content of volatile matter (bitumen) with significant nitrogen content. The bitumen contains a high proportion of aliphatic hydrocarbons of which high content of it attached to oxygen atom. The minerals were mainly quartz and low concentration of carbonate with noticeable content of sulfite and potassium oxide from XRF. The recovery of bitumen was evaluated using three different extraction techniques: solvent extraction methods (ultrasound-assisted extraction, non-aqueous extraction) and thermal pyrolysis using the Fischer assay apparatus. The non-aqueous solvent extraction method gave the highest bitumen recovery using toluene as a solvent; however, the high-temperature Fischer assay method provided a low recovery. The extracted bitumen under the optimum condition was characterized using NMR, elemental analysis, and GC-MS analysis. The oil products from tar sand showed a high concentration of oxygen and noticeable concentration of sulfur atoms. The 1H-NMR revealed a high content of aliphatic hydrocarbons in good agreement with raw tar sand characteristics. The identified compounds in the GC-MS where mainly substituted with oxygen atom in the form of alcohols and ethers. [ABSTRACT FROM AUTHOR]

Black soybean hulls have been reported to contain abundant anthocyanin pigments, which can be used as a colorant in food as well as non-food industries. In this study, anthocyanins were extracted from black soybean hulls using different extraction techniques such as aqueous extraction (solid to solvent ratio 1:20 g/mL, temperature of 40 °C for 65 min), microwave treatment (solid to solvent ratio 1:22 g/mL, microwave power of 240 W for 91s), ultrasound treatment (solid to solvent ratio of 1:26 g/mL, ultrasound power of 200 W for 50 min, and ethanol 90% v/v), and enzyme treatment (60% ethanol, solid to solvent ratio of 1:20 g/mL at 37 °C for 90 min). The results of this investigation showed that the enzyme-assisted extraction method showed the presence of the highest number of phytochemical compounds compared to other methods investigated in this study. Additionally, hull extracts displayed the presence of various important compounds that can be used in different industries, including as a pigment in the food industry which enhances the nutritional value, develops functional food, upgrades food quality, and is also beneficial in the pharmaceutical industry. [ABSTRACT FROM AUTHOR]

For irrigation in agriculture, water is a natural resource. Recycling water use is vital for the sustainable development of ecological environment and for resource conservation. Different substances that are thought to be pollutants and contribute to the deterioration of water quality are present in the wastewater from daily life and industrial activity. This research propose novel method in agricultural water management using feature extraction as well as classification based on DL methods. Inputs are collected as agriculture field water management as well as processed for noise removal, normalization and smoothening. Processed input data features are extracted utilizing kernel convolutional component analysis network. The extracted features has been classified using Quadratic reinforcement NN. Experimental analysis are carried out in terms of accuracy, precision, recall, positive predictive value, RMSE and mAP. Proposed technique attained accuracy of 92%, precision of 86%, recall of 65%, positive predictive value of 71%, RMSE of 55%, MAP of 51%. [ABSTRACT FROM AUTHOR]

Extensive use of α-pinene in cosmetics, and medicine, especially for its antioxidant/antibacterial, and anti-cancer properties, and also as a flavoring agent, has made it a versatile product. α-Pinene (one of the two pinene isomers) is the most abundant terpene in nature. When extracting α-pinene from plants and, to a lesser extent, fruits, given that its purity is essential, purification methods should also be used as described in this study. Also, an attempt has been made to describe the extraction techniques of α-pinene, carried out by conventional and novel methods. Some disadvantages of conventional methods (such as hydrodistillation or solvent extraction) are being time consuming, low capacity per batch and being labor intensive and the requirement of trained operators. Most novel methods, such as supercritical fluid extraction and microwave-assisted extraction, can reduce the extraction time, cost, and energy compared to conventional methods, and, in fact, the extraction and preservation efficiency of α-pinene in these methods is higher than conventional methods. Although the above-mentioned extraction methods are effective, they still require rather long extraction times. In fact, advanced methods such as green and solvent-free ultrasonic-microwave-assisted extraction are much more efficient than microwave-assisted extraction and ultrasound-assisted extraction because the extraction efficiency and separation of α-pinene in these methods are higher; furthermore, no solvent consumption and maximum extraction efficiency are some crucial advantages of these techniques. However, the application of some novel methods, such as ultrasound-assisted extraction, in industry scale is still problematic because of their intricate design data. [ABSTRACT FROM AUTHOR]

Background: Phytophthora sojae, a soil-borne oomycete pathogen, has been a yield limiting factor for more than 60 years on soybean. The resurgence of P. sojae (Phytophthora sojae) is primarily ascribed to the durable oospores found in soil and remnants of the disease. P. sojae is capable of infesting at any growth periods of the soybean, and the succeed infestation of P. sojae is predominantly attributed to long-lived oospores present in soil. Comprehending the molecular mechanisms that drive oospores formation and their significance in infestation is the key for effective management of the disease. However, the existing challenges in isolating and extracting significant quantities of oospores pose limitations in investigating the sexual reproductive stages of P. sojae. Results: The study focused on optimizing and refining the culture conditions and extraction process of P. sojae, resulting in establishment of an efficient and the dependable method for extraction. Novel optimized approach was yielded greater quantities of high-purity P. sojae oospores than traditional methods. The novel approach exceeds the traditional approaches with respect to viability, survival ability, germination rates of new oospores and the pathogenicity of oospores in potting experiments. Conclusion: The proposed method for extracting P. sojae oospores efficiently yielded a substantial quantity of highly pure, viable, and pathogenic oospores. The enhancements in oospores extraction techniques will promote the research on the sexual reproductive mechanisms of P. sojae and lead to the creation of innovative and effective approaches for managing oomycete diseases. [ABSTRACT FROM AUTHOR]

Mulberry is a rapidly growing plant that thrives in diverse climatic, topographical, and soil types, spanning temperature and temperate countries. Mulberry plants are valued as functional foods for their abundant chemical composition, serving as a significant reservoir of bioactive compounds like proteins, polysaccharides, phenolics, and flavonoids. Moreover, these compounds displayed potent antioxidant activity by scavenging free radicals, inhibiting reactive oxygen species generation, and restoring elevated nitric oxide production induced by LPS stimulation through the downregulation of inducible NO synthase expression. Active components like oxyresveratrol found in Morus demonstrated anti-inflammatory effects by inhibiting leukocyte migration through the MEK/ERK signaling pathway. Gallic and chlorogenic acids in mulberry leaves (ML) powder-modulated TNF, IL-6, and IRS1 proteins, improving various inflammatory conditions by immune system modulation. As we delve deeper into understanding its anti-inflammatory potential and how it works therapeutically, it is crucial to refine the extraction process to enhance the effectiveness of its bioactive elements. Recent advancements in extraction techniques, such as solid–liquid extraction, pressurized liquid extraction, superficial fluid extraction, microwave-assisted extraction, and ultrasonic-assisted extraction, are being explored. Among the extraction methods tested, including Soxhlet extraction, maceration, and ultrasound-assisted extraction (UAE), UAE demonstrated superior efficiency in extracting bioactive compounds from mulberry leaves. Overall, this comprehensive review sheds light on the potential of mulberry as a natural immunomodulatory agent and provides insights into its mechanisms of action for future research and therapeutic applications. [ABSTRACT FROM AUTHOR]

Taxus, as a globally prevalent evergreen tree, contains a wealth of bioactive components that play a crucial role in the pharmaceutical field. Taxus extracts, defined as a collection of one or more bioactive compounds extracted from the genus Taxus spp., have become a significant focus of modern cancer treatment research. This review article aims to delve into the scientific background of Taxus extracts and their considerable value in pharmaceutical research. It meticulously sifts through and compares various advanced extraction techniques such as supercritical extraction, ultrasound extraction, microwave-assisted extraction, solid-phase extraction, high-pressure pulsed electric field extraction, and enzymatic extraction, assessing each technology's advantages and limitations across dimensions such as extraction efficiency, extraction purity, economic cost, operational time, and environmental impact, with comprehensive analysis results presented in table form. In the area of drug formulation design, this paper systematically discusses the development strategies for solid, liquid, and semi-solid dosage forms based on the unique physicochemical properties of Taxus extracts, their intended medical uses, and specific release characteristics, delving deeply into the selection of excipients and the critical technical issues in the drug preparation process. Moreover, the article looks forward to the potential directions of Taxus extracts in future research and medical applications, emphasizing the urgency and importance of continuously optimizing extraction methods and formulation design to enhance treatment efficacy, reduce production costs, and decrease environmental burdens. It provides a comprehensive set of preparation techniques and formulation optimization schemes for researchers in cancer treatment and other medical fields, promoting the application and development of Taxus extracts in pharmaceutical sciences. [ABSTRACT FROM AUTHOR]

Labdanum resin or "gum" can be obtained from Cistus ladanifer L. by two different extraction methods: the Zamorean and the Andalusian processes. Although its main use is in the fragrance and perfumery sectors, ethnobotanical reports describe its use for medicinal purposes in managing hyperglycemia and mental illnesses. However, data concerning the bioactivities and pharmacological applications are scarce. In this work, it was found that the yield of labdanum resin extracted by the Andalusian process was 25-fold higher than the Zamorean one. Both resins were purified as absolutes, and the Andalusian absolute was purified into diterpenoid and flavonoid fractions. GC-EI-MS analysis confirmed the presence of phenylpropanoids, labdane-type diterpenoids, and methylated flavonoids, which are already described in the literature, but revealed other compounds, and showed that the different extracts presented distinct chemical profile. The potential antidiabetic activity, by inhibition of α-amylase and α-glucosidase, and the potential neuroprotective activity, by inhibition of acetylcholinesterase, were investigated. Diterpenoid fraction produced the higher α-amylase inhibitory effect (~30% and ~40% at 0.5 and 1 mg/mL, respectively). Zamorean absolute showed the highest α-glucosidase inhibitory effect (~14% and ~24%, at 0.5 and 1 mg/mL, respectively). Andalusian absolute showed the highest acetylcholinesterase inhibitory effect (~70% and ~75%, at 0.5 and 1 mg/mL, respectively). Using Caco-2 and HepG2 cell lines, Andalusian absolute and its purified fractions showed moderate cytotoxic/anti-proliferative activity at 24 h exposure (IC50 = 45–70 µg/mL, for Caco-2; IC50 = 60–80 µg/mL, for HepG2), whereas Zamorean absolute did not produce cytotoxicity (IC50 ≥ 200.00 µg/mL). Here we show, for the first time, that labdanum resin obtained by the Andalusian process, and its fractions, are composed of phytochemicals with anti-diabetic, neuroprotective and anti-proliferative potential, which are worth investigating for the pharmaceutical industry. However, toxic side-effects must also be addressed when using these products by ingestion, as done traditionally. [ABSTRACT FROM AUTHOR]

Proanthocyanidins, natural polyphenolic compounds abundantly present in plants, exhibit diverse bioactivities, including antioxidative, anti-inflammatory, and antibacterial effects. These bioactivities are intricately linked to the degree of polymerization of these compounds. Through a comprehensive analysis of recent domestic and international research, this article synthesizes the latest advancements in the extraction process, degradation methods, as well as the biological activities and underlying mechanisms of proanthocyanidins. Furthermore, future research endeavors should prioritize the refinement of extraction techniques, the elucidation of bioactive mechanisms, and the development of formulations with enhanced potency. This will maximize the utilization of proanthocyanidins across diverse applications. [ABSTRACT FROM AUTHOR]

Simple Summary: Cheek teeth extractions are a laborious procedure. A minimally invasive transbucal screw extraction technique has been described. This technique requires several mallet strikes to disrupt the periodontal ligament to loosen the affected tooth. The objective of this study is to provide evidence that the use of a corkscrew-like mechanism is effective in completing cheek tooth extraction in standing sedated horses without the use of a mallet. The instruments and methodology described here can help equine practitioners to improve dental screw extractions. Further studies are needed to refine the instruments and procedures as well as evaluate both intraoperative and postoperative complications. Several tooth extraction techniques are described in equine literature, and oral extraction techniques in standing sedated horses are popular among equine practitioners. The objectives of this study were to develop the corkscrew technique for cheek tooth extraction (CSET) in equine cadaver heads and evaluate this technique in clinical cases. We hypothesized that the CSET could be performed safely to extract cheek teeth in standing sedated horses. First, the CSET was attempted and developed in eight equine cadaver heads. Second, the CSET was performed in clinical cases between 2016 and 2020, and the following information was recorded: diagnosis, affected tooth, procedure duration, intraoperative difficulties, tooth size, postoperative complications, medication, hospitalization time, and 1-year follow-up. Sixteen CSET procedures were performed in eight equine skulls with a 75% success rate. In 24 clinical cases, 25 CSET procedures were attempted to extract 22 superior and 3 inferior cheek teeth. CSET was successful in 76% of procedures. Fractures of the tooth and stripping of screw threads were the major complications that led to the failure of CSET. CSET is a viable and safe technique to extract cheek teeth in standing sedated horses. Longitudinal drilling is a must for this technique to be successful. [ABSTRACT FROM AUTHOR]

Polysaccharides from non‐conventional sources, such as fruits, have gained significant attention recently. Aegle marmelos (Bael), a non‐conventional fruit, is an excellent source of biologically active components with potential indigenous therapeutic and food applications. Apart from polyphenolic components, this is an excellent source of mucilaginous polysaccharides. Polysaccharides are one the major components of bael fruit, having a high amount of galactose and glucuronic acid, which contributes to its potential therapeutic properties. Therefore, this review emphasizes the conventional and emerging techniques of polysaccharide extraction from bael fruit. Insight into the attributes of polysaccharide components, their techno‐functional properties, characterization of bael fruit polysaccharide, emulsifying properties, binding properties, reduction of hazardous dyes, application of polysaccharides in film formation, application of polysaccharide as a nanocomposite, and biological activities of bael fruit polysaccharides are discussed. This review also systematically overviews the relationship between extraction techniques, structural characteristics, and biological activities. Additionally, recommendations, future perspectives, and new valuable insight towards better utilization of bael fruit polysaccharide have been given importance, which can be promoted in the long term. [ABSTRACT FROM AUTHOR]

Tea is the most consumed beverage worldwide and has many health effects. Although there are many different types of tea, black tea and green tea comprise 98% of total tea production in the world. Tea waste production consists of withering, crushing, fermentation, drying and finally packaging processes. All of the waste generated during this production line is called tea waste. Tea production results in a significant amount of waste that cannot be effectively used for value creation. This waste contains many different components including protein, fiber, caffeine, and polyphenols. Due to its rich composition, it can be revalorized for different purposes. In this study, the general composition and bioactive compounds of tea waste were reviewed. Despite the fact that there have been few studies on the bioactivity of tea waste, those studies have also been discussed. The extraction techniques that are used to separate the compounds in the waste are also covered. It has been indicated that these valuable compounds, which can be separated from tea wastes by extraction methods, have the potential to be used for different purposes, such as biogas production, functional foods, food additives, silages, soluble packaging materials, and adsorbents. Although there are some studies on the revalorization of tea waste, new studies on the extraction of bioactive compounds are necessary to improve its utilization potential. [ABSTRACT FROM AUTHOR]

Text classification has critical applications, including healthcare, where it can assist patients in locating specialized clinics based on their symptom descriptions. This can enhance healthcare services by reducing misdiagnoses and efficiently guiding patients to appropriate specialists. This research focuses on building a model for multi-class text classification in Arabic healthcare. Two evaluation schemes were employed using health data from the Altibbi dataset. Various feature extraction techniques were employed, including term frequency-inverse document frequency (TF-IDF) and word-to-vector (Word2Vec). Classical machine learning models such as Logistic Regression (LR), Random Forest (RF), Multinomial Naïve Bayes (MNB), Stochastic Gradient Descent, and Support Vector Machine (SVM), along with ensemble classifications, were implemented. Evaluation measures were used to compare model performance, including precision, recall, and F1-score. Results indicated that TF-IDF generally outperformed Word2Vec regarding the F1-score across most classes. LR and RF consistently demonstrated strong performance, while MNB exhibited lower precision. Ensemble methods like stacking and bagging showed promise, with LR and RF performing well across multiple classes. The SVM model displayed lower precision in certain classes. Preliminary experiments with the transformer-based models for Arabic language AraBERT and MarBERT as feature extraction and classification models demonstrated impressive precision, recall, and F1 scores across various classes. The findings show the effectiveness of ensemble models using TF-IDF and Arabic transformer models in accurately classifying Arabic health texts. However, challenges related to standardization, semantic variations, data availability, and resources should be considered. [ABSTRACT FROM AUTHOR]

Morinda officinalis How oligosaccharide (MOO) stands as one of the principal active constituents of M. officinalis How, widely employed in traditional Chinese medicine. The methods for MOO extraction predominantly encompass hot water extraction, ethanol extraction, ultrasonic-assisted extraction, and microwave-assisted extraction. Distinct extraction techniques yield varying MOO quantities. MOO encompasses a diversity of oligosaccharides, including bajijiasu, sucrose, 1-kestose, nystose, mannose, 1F-fructofuranosylnystose, 1,1,1,1-kestohexose, fructoheptasaccharide, inulin-type hexasaccharide, inulin-type heptasaccharide, inulotriose, inulotetraose, inulopentaose, and mannose. MOO exhibits a wide spectrum of biological activities, exerting specific effects on the nervous system, cardiovascular system, motor system, reproductive system, and immune system. It demonstrates antidepressant properties, offers potential in mitigating Alzheimer's disease, stimulates angiogenesis, and possesses anti-osteoporotic and other pharmacological effects. Clinically, when combined with various antidepressants, MOO exhibits specific therapeutic efficacy across multiple forms of depression. As a naturally occurring plant oligosaccharide, MOO holds diverse pharmaceutical applications. This article conducts a review of the latest extraction and purification methodologies, structural characterization analysis, biological activity assessment, and clinical applications of MOO. Such a comprehensive analysis yields innovative insights for advancing the research and application of MOO in the future. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) anatomical extraction techniques could help the forensic anthropologist in a precise and inclusive assessment of biological phenotypes for the development of facial reconstruction methods. In this research, the nose morphology and the underlying hard tissue of two South African populations were studied. To this end, a 3D computer-assisted approach based on an automated landmarking workflow was used to generate relevant 3D anatomical components, and shape discrepancies were investigated using a data set of 200 cone-beam computer tomography (CBCT) scans. The anatomical landmarks were placed on the external nose and the mid-facial skeleton (the nasal bones, the anterior nasal aperture, the zygoma, and the maxilla). Shape differences related to population affinity, sex, age, and size were statistically evaluated and visualised using geometric morphometric methods. Population affinity, sexual dimorphism, age, and size affect the nasal complex morphology. Shape variation in the mid-facial region was significantly influenced by population affinity, emphasising that shape variability was specific to the two population groups, along with the expression of sexual dimorphism and the effect of ageing. In addition, nasal complex shape and correlations vary greatly between white and black South Africans, highlighting a need for reliable population-specific 3D statistical nose prediction algorithms. Significance: • 3D anatomical structures were acquired and extracted from 200 CBCT scans of modern South Africans. • Geometric morphometric methods were applied. • Soft- and hard-tissue nasal complex morphology vary across South African groups. [ABSTRACT FROM AUTHOR]

In this study, microwave extraction (ME) of pectic polysaccharides (M‐CPPs) from cantaloupe peels (CPs) is optimized using response surface methodology (RSM) with a Box–Behnken design (BBD). The optimum ME parameters are liquid–solid ratio 26.04 mL g−1, microwave power 543.04 W, irradiation time 6.38 min, and pH 1.5. Compared heat reflux extraction polysaccharides (H‐CPPs), the yield, the contents of neutral sugars (TSC), uronic acids (UAC), total flavonoids (TFC), total phenolics (TPC), sulfate groups (SGC) of M‐CPPs increased by 156.06%, 15.33%, 7.27%, 1019.05%, 1.75%, and 57.89%, but the molecular weight (Mw) and degree of esterification (DE) reduced by 29.08% and 24.81%, respectively. M‐CPPs exhibit superior antioxidant and hypoglycemic activities than H‐CPPs, which may be attributed to its higher UAC, TFC and SGC, lower Mw, and DE. There is almost no change in the monosaccharide types of isolated polysaccharides, only a change in molar ratio. Results proved that ME is an efficient technique for the extraction and modification of pectic polysaccharides (CPPs) from CPs with high yield, strong antioxidant, and hypoglycemic activities for applications in medical and food industries. [ABSTRACT FROM AUTHOR]

This article presents an innovative approach to analyzing and extracting electrocardiogram (ECG) signals from the abdomen and thorax of pregnant women, with the primary goal of isolating fetal ECG (fECG) and maternal ECG (mECG) signals. To resolve the difficulties related to the low amplitude of the fECG, various noise sources during signal acquisition, and the overlapping of R waves, we developed a new method for extracting ECG signals using blind source separation techniques. This method is based on independent component analysis algorithms to detect and accurately extract fECG and mECG signals from abdomen and thorax data. To validate our approach, we carried out experiments using a real and reliable database for the evaluation of fECG extraction algorithms. Moreover, to demonstrate real-time applicability, we implemented our method in an embedded card linked to electronic modules that measure blood oxygen saturation (SpO2) and body temperature, as well as the transmission of data to a web server. This enables us to present all information related to the fetus and its mother in a mobile application to assist doctors in diagnosing the fetus's condition. Our results demonstrate the effectiveness of our approach in isolating fECG and mECG signals under difficult conditions and also calculating different heart rates (fBPM and mBPM), which offers promising prospects for improving fetal monitoring and maternal healthcare during pregnancy. [ABSTRACT FROM AUTHOR]

Background Ponceau 4R (E124) and carmoisine (CMS; E122) are frequently utilized azo synthetic dyes in the food industry owing to their aesthetically pleasing coloration and broad consumer acceptability. It is imperative to prioritize environmentally favorable technologies for quantifying these dyes, as excessive consumption of these poses significant health risks. Objective The primary objective of this research was to establish a reversed-phase (RP)-HPLC method that could simultaneously detect Ponceau 4R and CMS, implementing green analytical chemistry (GAC) and analytical quality by design (AQbD), using an ultrasound-assisted extraction (UAE) technique in commercial food samples. Methods An Agilent Eclipse Plus column (C18, 250 × 4.6 mm id, 5 µm) was utilized for effective separation with a mobile phase of ethanol-acetate buffer pH 5 (60:40, v/v), flow rate of 1 mL/min, and detection wavelength of 515 nm. Critical variables selected for method optimization were ethanol percentage and flow rate, determined using central composite design (CCD). In order to adhere to the 12 principles of green chemistry, hazardous solvents were substituted with ethanol, which is distinguished by its ease of use, effectiveness, and ecological sustainability. The greenness assessment was conducted utilizing the green analytical procedure index (GAPI), analytical eco-scale (AES), and analytical greenness metrics (AGREE). Results The respective retention times for Ponceau 4R and CMS were 2.276 and 3.450 min. The recovery rate of Ponceau 4R and CMS fluctuated between 70% and 102% and 80% and 102%, respectively, across various marketed food samples. The procedure passed validation in accordance with the International Conference on Harmonization Q14 guidelines. Conclusion The devised method demonstrates that the validation parameters like linearity, precision, sensitivity, and reproducibility are within the specified limits of ICH guidelines. The greenness assesment tools GAPI, AES, and AGREE produced the most favorable results. Highlights In future, environmentally sustainable, solvent-based, robust AQbD methodologies for assessing varieties of food colorants may be adopted and improved commercially. [ABSTRACT FROM AUTHOR]

In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic information extraction techniques to compress their large-sized data before transmitting them to a multi-antenna base station (BS). Our model represents large-sized data through substantial knowledge graphs, utilizing shared probability graphs between the users and the BS for efficient semantic compression. The resource allocation problem is formulated as an optimization problem with the objective of maximizing the sum of the equivalent rate of all users, considering the total power budget and semantic resource limit constraints. The computation load considered in the PSC network is formulated as a non-smooth piecewise function with respect to the semantic compression ratio. To tackle this non-convex non-smooth optimization challenge, a three-stage algorithm is proposed, where the solutions for the received beamforming matrix of the BS, the transmit power of each user, and the semantic compression ratio of each user are obtained stage by stage. The numerical results validate the effectiveness of our proposed scheme. [ABSTRACT FROM AUTHOR]

Cistus ladanifer L., Acacia dealbata L., and Aloysia citrodora Paláu were subject to an optimization procedure for two extraction techniques (heat-assisted extraction (HAE) and ultrasound-assisted extraction (UAE)). The extracts were then analyzed by HPLC-DAD-ESI/MS for their phenolic profile (cistus—15 compounds, acacia—21 compounds, and lemon verbena—9 compounds). The response surface methodology was applied, considering four varying factors: ethanol percentage; extraction time; temperature/power; and S/L ratio, generating two responses (the major phenolic compound, or family of compounds, and the extraction yield). For cistus, both techniques optimized the extraction yield of punicalagins, with UAE proving to be the most efficient extraction method (3.22% ethanol, 22 min, 171 W, and 35 g/L). For acacia, HAE maximized the extraction of procyanidin (74% ethanol, 86 min, 24 °C, and 50 g/L), and UAE maximized the content of myricetin (65% ethanol, 8 min, 50 W, and 50 g/L). For lemon verbena, HAE favored the extraction of martynoside (13% ethanol, 96 min, 49 °C and 17 g/L) and forsythiaside UAE (94% ethanol, 25 min, 399 W, and 29 g/L). The optimal conditions for the extraction of compounds with high added value and potential for use in pharmaceuticals and nutraceuticals were defined. [ABSTRACT FROM AUTHOR]

Measurements of the clumped isotope anomalies (Δ13CDH3 and Δ12CD2H2) of methane have shown potential for constraining methane sources and sinks. At Utrecht University, we use the Thermo Scientific Ultra high-resolution isotope-ratio mass spectrometer to measure the clumped isotopic composition of methane emitted from various sources and directly from the atmosphere. We have developed an extraction system with three sections for extracting and purifying methane from high (> 1 %), medium (0.1 % to 1 %), and low-concentration (< 0.1 %) samples, including atmospheric air (∼ 2 ppm = 0.0002 %). Depending on the methane concentration, a quantity of sample gas is processed that delivers 3 ± 1 mL of pure methane, which is the quantity typically needed for one clumped isotope measurement. For atmospheric air with a methane mole fraction of 2 ppm, we currently process up to 1100 L of air. The analysis is performed on pure methane, using a dual-inlet setup. The complete measurement time for all isotope signatures is about 20 h for one sample. The mean internal precision values of sample measurements are 0.3 ± 0.1 ‰ for Δ13CDH3 and 2.4 ± 0.8 ‰ for Δ12CD2H2. The long-term reproducibility, obtained from repeated measurements of a constant target gas, over almost 3 years, is around 0.15 ‰ for Δ13CDH3 and 1.2 ‰ for Δ12CD2H2. The measured clumping anomalies are calibrated via the Δ13CDH3 and Δ12CD2H2 values of the reference CH4 used for the dual-inlet measurements. These were determined through isotope equilibration experiments at temperatures between 50 and 450 °C. We describe in detail the optimized sampling, extraction, purification, and measurement technique followed in our laboratory to measure the clumping anomalies of methane precisely and accurately. This paper highlights the extraction and one of the first global measurements of the clumping anomalies of atmospheric methane. [ABSTRACT FROM AUTHOR]

Maturity of the coconut is judged manually based on the shape, color, weight, shaking sound, timeframe, etc. Currently, there is not much research being done to find solutions involving the latest techniques including fuzzy, machine learning and deep learning techniques for identifying maturity of the coconuts without human intervention. These techniques have significant challenges in detecting the multiple classes in coconut maturity due to difference in size and shape of the coconuts and the complex nature of their backgrounds as each coconut tree and each coconut bunch are unique. In this research work, we propose an integrated fuzzy and deep learning model (IFDM) to identify the maturity classes of coconut. Deep learning-based Mask R-CNN is used to classify and segment the coconut images. The combined fuzzy system (CFS) extracts the color, shape and scratch features with a fuzzy extraction technique for each feature. A probability-based fuzzy integration (PFI) method integrates the output from each fuzzy extraction to classify the coconuts. Decision-making probability (DMP) model combines the class probability of the probability-based fuzzy integration method and Mask R-CNN model to obtain the final coconut maturity class. The dataset with 10,000 images is used for training. Two test datasets, the first one containing 1754 real-time coconut images and the second containing 1000 cropped coconut images from the background, are used for testing. Using the proposed learning model in real time, an accuracy of 86.3% is obtained in classifying the maturity classes of coconuts. While integrating the models like Yolo v3, Yolo v5, Faster R-CNN, random forest and KNN with combined fuzzy system, Mask R-CNN performed better in terms of accuracy. [ABSTRACT FROM AUTHOR]

Fatty acids (FAs) have attracted many interests for their pivotal roles in many biological processes. Imbalance of FAs is related to a variety of diseases, which makes the measurement of them important in biological samples. Over the past two decades, mass spectrometry (MS) has become an indispensable technique for the analysis of FAs owing to its high sensitivity and precision. Due to complex matrix effect of biological samples and inherent poor ionization efficiency of FAs in MS, sample preparation including extraction and chemical derivatization prior to analysis are often employed. Here, we describe an updated overview of FA extraction techniques, as well as representative derivatization methods utilized in different MS platforms including gas chromatography-MS, liquid chromatography-MS, and mass spectrometry imaging based on different chain lengths of FAs. Derivatization strategies for the identification of double bond location in unsaturated FAs are also summarized and highlighted. The advantages, disadvantages, and prospects of these methods are compared and discussed. This review provides the development and valuable information for sample pretreatment approaches and qualitative and quantitative analysis of interested FAs using different MS-based platforms in complex biological matrices. Finally, the challenges of FA analysis are summarized and the future perspectives are prospected. [ABSTRACT FROM AUTHOR]

The superior seeds are indicated by clean, good germination rate, pest and disease-free. One of the problems in providing superior tomato seeds is the presence of pulp attached to the tomato seeds, leading to less clean of seed. To remove the muscus on tomato seeds, the seeds have to be extracted. Other than seeds extraction, seeds exposure also could optimize seeds growth by increasing the metabolism of the tomato. The aim of this research is to determine the best extraction technique and magnetic field exposure for obtaining high tomato seeds germination. The complete random design used in this research consist of two factors, seeds extraction and magnetic field with three time replications. The result showed that seeds extraction for 24 hours is the best treatment for improving the maximum germination percentage, growth potential, growth rate, speed growth, uniformity index than others. Magnetic exposure at 6mT is the best treatment to improve seeds maximum growth and seeds speed growth. [ABSTRACT FROM AUTHOR]

Along with power transmission lines' efficiency, another crucial factor in electrical power transmission networks is reliability, which guarantees power transmission stability. One of the crucial and essential tasks for maintaining the continuity and stability of power transmission in transmission networks Capacity without any significant failures is identifying errors and malfunctions in power transmission lines as soon as possible. The goal of this article is to develop and apply ANN technology to overcome the obstacles faced by the electrical power transmission network. In order for the ANN to learn useful patterns and features from raw current measurements, pre-processing and feature extraction techniques are used during the training process. Real-time applications can benefit from the ANN's architecture, which is optimized for high accuracy, quick response times, and scalability. To validate the performance of the ANN-based fault detection system, extensive simulations are conducted using data from different transmission line scenarios, including various fault types that short-circuit. The results demonstrate the capability of the ANN model to accurately detect and classify faults, as well as disconnect the power grid after detect any fault. The results showed the accuracy and high speed of the proposed method using a neural network compared to traditional methods. [ABSTRACT FROM AUTHOR]

Technological improvements in dietary supplements and nutraceuticals have highlighted the significance of bioactive molecules in a healthy lifestyle. Eicosapentaenoic acid and Cervonic acid (DHA), omega-3 polyunsaturated fatty acids seem to be famed for their ability to prevent diverse physiological abnormalities. Selection of appropriate pretreatments and extraction techniques for extraction of lipids from robust microalgae cell wall are very important to retain their stability and bioactivity. Therefore, extraction techniques with optimized extraction parameters offer an excellent approach for obtaining quality oil with a high yield. Oils enriched in omega-3 are particularly imperiled to oxidation which ultimately affects customer acceptance. Bio active encapsulation could be one of the effective approaches to overcome this dilemma. This review paper aims to give insight into the cultivation methods, and downstream processes, various lipid extraction approaches, techniques for retaining oxidative stability, bioavailability and food applications based on extracted or encapsulated omega-3. [ABSTRACT FROM AUTHOR]

Nowadays, kinship verification is an attractive research area within computer vision. It significantly affects applications in the real world, such as finding missing individuals and forensics. Despite the importance of this research topic, it still faces many challenges, such as low accuracy and illumination variations. Due to the existence of different classes of feature extraction techniques, different types of information can be extracted from the input data. Moreover, the fusion power produces complementary information that can address kinship verification problems. Therefore, this paper proposes a new approach for verifying kinship by fusing features from different perspectives, including color-texture and color features in different color spaces. Besides using promising methods in the field, such as local binary pattern (LBP) and scale-invariant feature transform (SIFT), the paper utilizes other feature extraction methods, which are heterogeneous auto-similarities of characteristics (HASC), color correlogram (CC), and dense color histogram (DCH). As far as we know, these features haven't been employed before in this research area. Accordingly, the proposed approach goes into six stages: preprocessing, feature extraction, feature normalization, feature fusion, feature representation, and kinship verification. The proposed approach was evaluated on the KinFaceW-I and KinFaceW-II field standard datasets, achieving maximum accuracy of 79.54% and 90.65%, respectively. Compared with many state-of-the-art approaches, the results of the proposed approach reflect the promising achievements and encourage the authors to plan for future enhancement. [ABSTRACT FROM AUTHOR]

Kiwifruit is widely consumed in many parts of the world. They contain a variety of bioactive substances that make them a valuable functional food source. For instance, kiwifruit contains vitamin C, polysaccharides, polyphenols (catechin, anthocyanin, chlorogenic acid, gallic acid), alkaloids (aconitine, safranin, actinidine), and terpenoids (ursolic acid, oleanolic acid), which are claimed to exhibit antioxidant, anti-inflammatory, and anticancer effects, as well as protecting against cardiovascular and cerebrovascular diseases. However, the potentially beneficial effects of most of these bioactive substances have still not been confirmed by clinical trials. This article reviews recent research on the type and physiological functions of the main bioactive components in kiwifruit. The techniques required to extract and characterize these components are discussed, as well as current challenges in kiwifruit processing. Several innovative extraction techniques have been utilized to extract bioactive substances from kiwifruits, including ultrasound- and microwave-assisted methods. Moreover, several non-thermal processing methods (such as ultrasound, high-pressure, and pulsed electric field processing) are being used to reduce the losses and increase the activity of bioactive substances, preserve the sensory qualities of the fruit, and reduce the allergenicity of kiwifruit. [ABSTRACT FROM AUTHOR]

The battle between malware analysts and malware authors is a never-ending challenge with the advent of complex malware such as polymorphic, metamorphic, and packed malware. A malware packer uses various techniques combined with file encryption to harden against reverse engineering of the program and hinder the analysis of program behaviors. In any case, substantial elements have emerged after more than a decade of continuous research in malware packer detection, such as multi-packing. Newly modified packers have this persistent problem, which demands new concepts and techniques. This study aims to provide a systematic and comprehensive review of run-time packers' mitigation techniques. We provide different types of packers and propose a malware packer handling life cycle for AV engines. Furthermore, we deliver a modern malware packers classification features set by examining the feature engineering in the packing handling life-cycle, such as feature extraction techniques in machine learning approaches. Also, we present extensive related works and discuss each work's benefits and weaknesses to address this problem, with a particular emphasis on packers identification techniques, to aid in unpacking malware. Finally, we identify the current gaps in knowledge and provide ideas about future work. [ABSTRACT FROM AUTHOR]

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features. [ABSTRACT FROM AUTHOR]

Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar symptoms, complicating their diagnosis and the development of specific treatment strategies. Our study evaluated multiple feature extraction techniques for identifying AD and FTD biomarkers from electroencephalographic (EEG) signals. We developed an optimised machine learning architecture that integrates sliding windowing, feature extraction, and supervised learning to distinguish between AD and FTD patients, as well as from healthy controls (HCs). Our model, with a 90% overlap for sliding windowing, SVD entropy for feature extraction, and K-Nearest Neighbors (KNN) for supervised learning, achieved a mean F1-score and accuracy of 93% and 91%, 92.5% and 93%, and 91.5% and 91% for discriminating AD and HC, FTD and HC, and AD and FTD, respectively. The feature importance array, an explainable AI feature, highlighted the brain lobes that contributed to identifying and distinguishing AD and FTD biomarkers. This research introduces a novel framework for detecting and discriminating AD and FTD using EEG signals, addressing the need for accurate early-stage diagnostics. Furthermore, a comparative evaluation of sliding windowing, multiple feature extraction, and machine learning methods on AD/FTD detection and discrimination is documented. [ABSTRACT FROM AUTHOR]

Theobroma cacao L. seeds, commonly known as cocoa beans, are the foundation for cocoa and chocolate production. Following harvest, these beans undergo a multi-step processing chain including fermentation, drying, roasting, and grinding. This process yields cocoa solids, cocoa butter, and cocoa powder—all fundamental ingredients in the food and beverage industry. Beyond its sensory appeal (flavor, aroma, and texture), cocoa has garnered significant interest for its potential health benefits attributed to a rich profile of bioactive compounds. Cocoa is a well-documented source of polyphenolics, specifically flavanols, alongside methylxanthines, phytosterols, and dietary fibers. These constituents have been associated with a diverse range of bioactivities, including antioxidant, anti-carcinogenic, anti-diabetic, anti-inflammatory, anti-obesity, and anti-allergenic properties, potentially contributing to overall health maintenance. Efficient extraction techniques are crucial for maximizing the recovery of these valuable bioactive components from cocoa plant material. Modern methods are continuously being explored to optimize this process. This review focuses on the established health benefits associated with the bioactive compounds present in cocoa. Additionally, it will explore and discuss contemporary approaches for the extraction of these bioactive compounds from this plant source. [ABSTRACT FROM AUTHOR]

Rationale: Himalayan marmot oil (SPO) has been used for pharmaceutical purposes for centuries, but its composition is still unclear. The bioactivity of SPO highly depends on the techniques used for its processing. This study focused on the comprehensive lipidomics of SPO, especially on the ones derived from dry rendering, wet rendering, cold pressing, and ultrasound‐assisted solvent extraction. Methods: We performed lipid profiling of SPO acquired by different extraction methods using ultrahigh‐performance liquid chromatography Q‐Exactive Orbitrap mass spectrometry, and 17 classes of lipids (2 BMPs, 12 LysoPCs, 9 LysoPEs, 41 PCs, 24 PEs, 23 Plasmenyl‐PCs, 10 Plasmenyl‐PEs, 10 MGs, 63 DGs, 187 TGs, 2 MGDGs, 3 Cer[NDS]s, 22 Cer[NS]s, 2 GlcCer[NS]s, 14 SMs, 14 CEs, and 6 AcylCarnitines) were characterized. Results: Fifty‐five lipids were differentially altered (VIP > 1.5, p < 0.05) between the extraction techniques, which can be used as potential biomarkers to differentiate SPO extracted by various methods. Additionally, the contents of oleic acid and arachidic acid were abundant in all samples that may suggest their medicinal values and are conducive to in‐depth research. Conclusions: These findings reveal the alterations of lipid profile and free fatty acid composition in SPO obtained with different extraction methods, providing a theoretical foundation for investigating its important components as functional factors in medicines and cosmetics. [ABSTRACT FROM AUTHOR]

The Cycolcarya paliurus (C. paliurus) has a long history of medicinal use as a traditional Chinese medicine to deal with diabetic, hyperlipidemic, inflammatory, and cancer, and triterpenes are one of its main active substances. Current studies on triterpenoids from C. paliurus have shown that different combinations of extraction methods and techniques have been used to isolate triterpenes from the leaves of the tree. The structures of the isolated triterpenoids from C. paliurus have also been elucidated to analyze their biological activities and conformational relationships. This paper presents a comprehensive evaluation of the triterpenes in C. paliurus in terms of extraction and purification methods, chemical structure, active functions and utilization, in order to provide a reference for the further development and utilization of triterpenoids in C. paliurus. [ABSTRACT FROM AUTHOR]

A rapid and efficient analytical method was established to quantify indoxyl sulfate (IS) in plasma through extraction technique with a deep eutectic solvent (DES) and spectrofluorimetric method. DES (choline chloride: urea) was mixed with plasma samples for the extraction of IS, followed by the addition of dipotassium hydrogen phosphate (K2HPO4) solution to form an aqueous two-phase system. The fluorescence intensity of IS which was first extracted to the DES-rich-phase and then back-extracted into the salt-rich-phase, was measured by spectrofluorimetric method. Some key factors such as pH, centrifugation speed and time, the volume ratio of DES/salt, and salt concentration were optimized. Under the optimized conditions, the suggested method had a dynamic range between 20 and 160 µg/mL with a coefficient of determination (R2) of 0.99. Precision (relative standard deviation) was less than 15% and accuracy (% relative recovery) was ± 15% at the nominal concentration level. In addition, results showed that IS levels in real samples were higher than 40 µg/mL which was compatible with reported IS levels in end-stage renal disease (ESRD) patients. Overall, all the results reflect the fact that the presented analytical method can potentially be used for the determination of IS in real plasma samples. [ABSTRACT FROM AUTHOR]

The corrosion product deposit (crud) found on the surface of the fuel rod of the pressurized water reactors (PWRs) chiefly made up of nickel ferrite. Fe, Co, Ni and Cr are the major elements exist in PWR crud. Ascribable to the simplicity in execution, handling, and option for recyclability, solvent extraction technique has been broadly used in nuclear energy sector. In the present investigation, the recovery of iron, cobalt, and nickel has been studied from simulated crud solution in nitrate medium using a novel hydrophobic menthol‐decanoic acid‐based deep eutectic solvent. Process parameters such as pH, DES concentration and shaking time were considered as input variables, and concentration of Fe, Co, and Ni as response variables for the design of experiments. Response surface methodology via Box‐Behnken design using polynomial quadratic model was selected for optimization of solvent extraction experiments. A total of 17 runs were conducted and the results were used for optimization purpose. Complete separation of Co/Fe and Co/Ni is achievable under various extraction conditions. As per the BBD analysis, the optimization conditions obtained were pH=1.9, [DES]=2.99 mol/L and shaking duration=18.27 min. Under these conditions,the amount of Fe, Co and Ni extracted were found as 32.29 g/L, 0.2111 g/L, and 19.83 g/L, respectively. [ABSTRACT FROM AUTHOR]

BACKGROUND: Three different organic sunflower seed cakes, produced from seeds differing in the content of their hulls, were extracted by two different extraction methods – conventional extraction (CE) and ultrasound‐assisted extraction (UAE). The total phenolic compound (TPC) content of the extracts was evaluated using Folin–Ciocâlteu reagent (FCR) and high‐performance liquid chromatography (HPLC). The antioxidant capacity of extracts was evaluated with the Trolox equivalent antioxidant capacity (TEAC) and 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) assays. RESULTS: The results showed that both extracts displayed high TPC content and antioxidant capacity. The UAE method showed significantly higher TPC content and antioxidant capacity values than CE. Individual phenolic compounds such as chlorogenic acid (CGA) isomers (3‐, 4‐ and 5‐O‐caffeoylquinic acids), di‐CGA isomers, and feruloylquinic and coumaroylquinic acids were identified according to their exact masses by HPLC coupled to time‐of‐flight mass spectrometry. CONCLUSION: The results revealed that the UAE method could be used effectively to facilitate the extraction of phenolic compounds from sunflower seed cake. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Highly accurate data on urban and rural settlement (URS) are essential for urban planning and decision-making in response to climate and environmental changes. This study developed an optimal random forest classification model for URSs based on spectral–topographic–radar polarization features using Landsat 8, NASA DEM, and Sentinel-1 SAR as the remote-sensing data sources. An optimal urban and rural settlement boundary (URSB) extraction technique based on morphological and pixel-level statistical methods was established to link discontinuous URSs and improve the accuracy of URSB extraction. An optimal random forest classification model for URSs was developed, as well as a technique to optimize URSB, using the Google Earth Engine (GEE) platform. The URSB of Xining, China, in 2020 was then extracted at a spatial resolution of 30 m, achieving an overall accuracy and Kappa coefficient of 96.21% and 0.92, respectively. Compared to using a single spectral feature, these corresponding metrics improved by 16.21% and 0.35, respectively. This research also demonstrated that the newly constructed Blue Roof Index (BRI), with enhanced blue roof features, is highly indicative of URSs and that the URSB was best extracted when the window size of the structural elements was 13 × 13. These results can be used to provide technical support for obtaining highly accurate information on URSs. [ABSTRACT FROM AUTHOR]