Vanadium(IV) ions extraction in the aqueous two-phase system based on poly(ethylene glycol)

Vanadium has found wide applications in various industries: metallurgy, electronics, batteries, and others. This element, being dispersed, does not form its minerals and, therefore, is mined along the way. An alternative approach of vanadium extraction is to separate it from heavy oil, by flushing the oil with strong acids solutions and further hydrometallurgical processing. The existing methods of oil dehydration solutions processing for the vanadium extraction are not perfect - they do not meet the “green” chemistry principles. Thus, we investigated V(IV) ions extraction in the aqueous two-phase system (ATPS) based on poly(ethylene glycol) 1500 (16.3wt%) – NaNO3 (36wt%) – H2O. The dependences of V(IV) extraction efficiency on phases time contact, and dependences V(IV) distribution coefficients on salt phase acidity have been obtained. This system is shown to be a prospective solution for the vanadium(IV) recovery from acidic waste steams problem as it is possible to extract vanadium with an efficiency of more than 81.6% per one extraction step (the distribution coefficient of vanadium (IV) was 4.84).

COVIDFast: A high-throughput and RNA extraction-free method for SARS-CoV-2 detection in swab (SwabFAST) or saliva (SalivaFAST)

There is an urgent need of having a rapid, high throughput, yet accurate SARS-COV-2 PCR testing to control the COVID19 pandemic. However, the RNA extraction step in conventional PCR creates a major bottle neck in the diagnostic process. In this paper we modified the CDC COVID-19 assay and developed an RNA-extraction free RT-qPCR assay for SARS-CoV-2, i.e. COVIDFast. Depending on sample types, the assay is further divided into SwabFAST, which uses anterior nares nasal swab, and SalivaFAST, which uses saliva. By utilizing the proprietary buffer for either swab or saliva samples, the performance of SwabFAST or SalivaFAST is equivalent to RNA-extraction SARS-CoV-2 RT-qPCR in both contrived and clinical samples. The limit of detection of either assay is 4 copies/uL. We further developed a semi-automatic system, which is easy to adapt by clinical lab for implementation of a high-throughput SARS-CoV-2 test. Working together with the COVIDCheck Colorado, we have tested over 400,000 samples using COVIDFast (83.62% SwabFAST and 16.38% SalivaFAST) in less than a year, resulting in significant clinical contribution in the battle against COVID-19 during the pandemic.

Blended Features Classification of Leaf-Based Cucumber Disease Using Image Processing Techniques

Existing plant leaf disease detection approaches are based on features of extracting algorithms. These algorithms have some limits in feature selection for the diseased portion, but they can be used in conjunction with other image processing methods. Diseases of a plant can be classified from their symptoms. We proposed a cucumber leaf recognition approach, consisting of five steps: preprocessing, normalization, features extraction, features fusion, and classification. Otsu’s thresholding is implemented in preprocessing and Tan–Triggs normalization is applied for normalizing the dataset. During the features extraction step, texture and shape features are extracted. In addition, increasing the instances improves some characteristics. Through a principal component analysis approach, serial feature fusion is employed to provide a feature score. Fused features can be classified through a support vector machine. The accuracy of the Fine KNN is 94.30%, which is higher than the previous work in past papers.

Rapid and Simultaneous Determination of Free Aromatic Carboxylic Acids and Phenols in Commercial Juices by GC-MS after Ethyl Chloroformate Derivatization

Natural phenol and phenolic acids are widely distributed in the plant kingdom and the major dietary sources include fruits and beverages derived therefrom. Over the past decades, these compounds have been widely investigated for their beneficial effects on human health and, at the same time, several analytical methods have been developed for their determination in these matrices. In the present paper, 19 different aromatic carboxylic acids and phenols were characterized by GC-MS using ethyl chloroformate as the derivatizing agent. This procedure occurs quickly at room temperature and takes place in aqueous media simultaneously with the extraction step in the presence of ethanol using pyridine as a catalyst. The analytical method herein developed and validated presents excellent linearity in a wide concentration range (25–3000 ng/mL), low LOQ (in the range 25–100 ng/mL) and LOD (in the range 12.5–50 ng/mL), and good accuracy and precision. As a proof of concept, ethyl chloroformate derivatization was successfully applied to the analysis of a selection of commercial fruit juices (berries, grape, apple, pomegranate) particularly rich in phenolic compounds. Some of these juices are made up of a single fruit, whereas others are blends of several fruits. Our results show that among the juices analyzed, those containing cranberry have a total concentration of the free aromatic carboxylic acids and phenols tested up to 15 times higher than other juices.

Using semantics to scale up evidence-based chemical risk-assessments

Background The manual processes used for risk assessments are not scaling to the amount of data available. Although automated approaches appear promising, they must be transparent in a public policy setting. Objective Our goal is to create an automated approach that moves beyond retrieval to the extraction step of the information synthesis process, where evidence is characterized as supporting, refuting, or neutral with respect to a given outcome. Methods We combine knowledge resources and natural language processing to resolve coordinated ellipses and thus avoid surface level differences between concepts in an ontology and outcomes in an abstract. As with a systematic review, the search criterion, and inclusion and exclusion criterion are explicit. Results The system scales to 482K abstracts on 27 chemicals. Results for three endpoints that are critical for cancer risk assessments show that refuting evidence (where the outcome decreased) was higher for cell proliferation (45.9%), and general cell changes (37.7%) than for cell death (25.0%). Moreover, cell death was the only end point where supporting claims were the majority (61.3%). If the number of abstracts that measure an outcome was used as a proxy for association there would be a stronger association with cell proliferation than cell death (20/27 chemicals). However, if the amount of supporting evidence was used (where the outcome increased) the conclusion would change for 21/27 chemicals (20 from proliferation to death and 1 from death to proliferation). Conclusions We provide decision makers with a visual representation of supporting, neutral, and refuting evidence whilst maintaining the reproducibility and transparency needed for public policy. Our findings show that results from the retrieval step where the number of abstracts that measure an outcome are reported can be misleading if not accompanied with results from the extraction step where the directionality of the outcome is established.

No Need of Data Pre-processing

Device-free context awareness is important to many applications. There are two broadly used approaches for device-free context awareness, i.e., video-based and radio-based. Video-based approaches can deliver good performance, but privacy is a serious concern. Radio-based context awareness applications have drawn researchers' attention instead, because it does not violate privacy and radio signal can penetrate obstacles. The existing works design explicit methods for each radio-based application. Furthermore, they use one additional step to extract features before conducting classification and exploit deep learning as a classification tool. Although this feature extraction step helps explore patterns of raw signals, it generates unnecessary noise and information loss. The use of raw CSI signal without initial data processing was, however, considered as no usable patterns. In this article, we are the first to propose an innovative deep learning–based general framework for both signal processing and classification. The key novelty of this article is that the framework can be generalised for all the radio-based context awareness applications with the use of raw CSI. We also eliminate the extra work to extract features from raw radio signals. We conduct extensive evaluations to show the superior performance of our proposed method and its generalisation.

A novel methodology for direct esterification of olives optimized through design of experiments

A novel methodology was proposed, and optimized using the Design Expert software, aiming to enable characterization of the fatty acid profile of olives whilst abolishing the lipid extraction step. Furthermore, the proposed method was proven more efficient whereas requiring less time, and sample and solvent amounts, consequently improving process yield. Optimum conditions obtained after experimental design were as follows: sonication temperature and time of 60 ºC and 8 minutes, respectively, and concentrations for alkaline and acid reactions of 0.70 and 1.5 mol L-1, respectively. Total fatty acid content for olive sample was 172.0 mg g-1, the predicted value was and is in the coefficient of variation range of 11.52%

Sequential Extraction of Hydroxytyrosol, Mannitol and Triterpenic Acids Using a Green Optimized Procedure Based on Ultrasound

Olive-derived biomasses contain bioactive compounds with health promoting effects as well as antioxidant and sweet-tasting properties. However, their sequential extraction has not been attained. In the present study, firstly antioxidants and mannitol were extracted from exhausted olive pomace (EOP) by an eco-friendly method, ultrasound-assisted water extraction (UAWE). The amplitude (20–80%), extraction time (2–18 min) and solid loading (2–15%, w/v) were evaluated according to a Box–Behnken experimental design. Using the response surface methodology, the optimal conditions for extraction were obtained: 80% amplitude, 11.5% solid loading and 16 min. It enabled the multi-response optimization of the total phenolic content (TPC) (40.04 mg/g EOP), hydroxytyrosol content (6.42 mg/g EOP), mannitol content (50.92 mg/g EOP) and antioxidant activity (ferric reducing power or FRAP, 50.95 mg/g EOP; ABTS, 100.64 mg/g EOP). Moreover, the phenolic profile of the extracts was determined by liquid chromatography-UV and mass spectrometry, identifying hydroxytyrosol as the main phenolic compound and other minor derivatives could be characterized. Scanning electron microscopy was used to analyze the morphological changes produced in the cellular structure of EOP after UAWE. In addition, the chemical composition of the extracted EOP solid was characterized for further valorization. Then, a second extraction step was performed in order to extract bioactive triterpenes from the latter solid. The triterpenes content in the extract was determined and the effect of the previous UAWE step on the triterpenes extraction was evaluated. In this case, the use of ultrasound enhanced the extraction of maslinic acid and oleanolic acid from pelletized EOP with no milling requirement. Overall, UAWE can be applied to obtain antioxidant compounds and mannitol as first extraction step from pelletized EOP while supporting the subsequent recovery of triterpenic acids.

Fast determination of phthalates in mussel samples by micro-matrix solid-phase dispersion (micro-MSPD) coupled with GC–MS/MS

A fast, effective and low cost sample preparation method based on miniaturized matrix solid-phase dispersion (micro-MSPD) combined with gas chromatography coupled to tandem triple-quadrupole-mass spectrometry (GC–MS/MS) has been developed for the determination of six phthalate diesters (DMP, DEP, DBP, BzBP, DEHP and DnOP) in mussel samples. The six target compounds have been included in the list of priority pollutants by United States Environmental Protection Agency. The extraction step was optimized on real spiked mussel coming from Galician Rías by means of a factorial design. The final procedure involved the use of 0.45 g of sample, 0.5 g of dispersant agent (Florisil) and 3 mL of organic solvent (ethyl acetate). The optimized method was validated giving satisfactory analytical performance, low detection limits (0.09 to 6.73 ng g−1 dw) and high recoveries (93 and 114%). The validated method was applied to four real mussel samples coming from Galician Rías.