ABSTRACT
Common wastewater treatment strategies in the food industry do not include efficient remediation strategies for nitrogen, phosphorous and organic carbon. Incorporating microalgae in water treatment plants is rising in popularity because of their high nutrient and trace element uptake driven by light. In this study, four different side streams from an Austrian potato processing company have been screened for their applicability of microalgal cultivation. The side streams were assessed for Chlorella vulgaris growth and their requirement of any additional pretreatment or media supplementation. One side stream specifically, called blanching water II, a stream generated by boiling the potatoes for ease of peeling, turned out very useful to cultivate Chlorella vulgaris and concomitantly remedy the wastewater. Compared to a state-of-the-art cultivation in BG11, cultivating Chlorella vulgaris in blanching water II led to a 45 % increase in specific growth rate of 1.29 day-1 and a 48% increase in biomass productivity to 294.6 mg/L/day, while all nitrogen and phosphate present in the side stream were metabolized. Overall, the results demonstrate that the water remediation process for blanching water II shows vast potential in regard to water purification and waste to value approaches.
ABSTRACT
Polymeric composite materials are gaining importance due to their universal applicability and easy adaptability for their intended use. For the comprehensive characterization of these materials, the concurrent determination of the organic and the elemental constituents is necessary, which cannot be provided by classical analysis methods. In this work, we present a novel approach for advanced polymer analysis. The proposed approach is based on firing a focused laser beam onto a solid sample placed in an ablation cell. The generated gaseous and particular ablation products are measured online parallelly by EI-MS and ICP-OES. This bimodal approach allows direct characterization of the main organic and inorganic constituents of solid polymer samples. The LA-EI-MS data showed excellent agreement with the literature EI-MS data allowing not only the identification of pure polymers but also of copolymers, as demonstrated with acrylonitrile butadiene styrene (ABS) as the sample. The concurrent collection of ICP-OES elemental data is vital for classification, provenance determination, or authentication studies. The applicability of the proposed procedure has been demonstrated by analysis of various polymer samples from everyday use.
ABSTRACT
Background and objectives: An expert's subjective assessment is still the most reliable evaluation of adnexal pathology, thus raising the need for methods less dependent on the examiner's experience. The aim of this study was to evaluate the performance of standardized methods when applied by examiners with different levels of experience and to suggest the most suitable method for less-experienced gynecologists. Materials and methods: This single-center retrospective study included 50 cases of histologically proven first-time benign or malignant adnexal pathology. Three examiners evaluated the same transvaginal ultrasound images: an expert (level III), a 4th year resident in gynecology (level I), and a final year medical student after basic training (labeled as level 0). The assessment methods included subjective evaluation, Simple Rules (SR) with and without algorithm, ADNEX and Gynecologic Imaging Reporting and Data System (GI-RADS) models. Sensitivity, specificity, accuracy, positive and negative predictive values with 95% confidence interval were calculated. Results: Out of 50 cases, 33 (66%) were benign and 17 (34%) were malignant adnexal masses. Using only SR, level III could classify 48 (96%), level I-41 (82%) and level 0-40 (80%) adnexal lesions. Using SR and algorithm, the performance improved the most for all levels and yielded sensitivity and specificity of 100% for level III, 100% and 97% for level I, 94.4% and 100% for level 0, respectively. Compared to subjective assessment, ADNEX lowered the accuracy of level III evaluation from 97.9% to 88% and GI-RADS had no impact. ADNEX and GI-RADS improved the sensitivity up to 100% for the less experienced; however, the specificity and accuracy were notably decreased. Conclusions: SR and SR+ algorithm have the most potential to improve not only sensitivity, but also specificity and accuracy, irrespective of the experience level. ADNEX and GI-RADS can yield sensitivity of 100%; however, the accuracy is decreased.
