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10 pages, 2692 KiB  
Proceeding Paper
Calculating the Effectiveness of COVID-19 Non-Pharmaceutical Interventions with Interrupted Time Series Analysis via Clustering-Based Counterfactual Country
by Fatemeh Navazi, Yufei Yuan and Norm Archer
Eng. Proc. 2023, 39(1), 51; https://doi.org/10.3390/engproc2023039051 - 5 Jul 2023
Cited by 2 | Viewed by 1074
Abstract
During the first year of the COVID-19 pandemic, governments only had access to non-pharmaceutical interventions (NPIs) to mitigate the spread of the disease. Various methods have been discussed in the literature for calculating the effectiveness of NPIs. Among these methods, the interrupted time [...] Read more.
During the first year of the COVID-19 pandemic, governments only had access to non-pharmaceutical interventions (NPIs) to mitigate the spread of the disease. Various methods have been discussed in the literature for calculating the effectiveness of NPIs. Among these methods, the interrupted time series analysis method is the area of our interest. To study the second wave, we clustered countries based on levels of implemented NPIs, except for the target NPI (X) whose effectiveness wanted to be evaluated. To do so, the COVID-19 Policy Response Tracker data-set gathered by the “Our World in Data” team of Oxford University, and COVID-19 statistical data gathered by the John Hopkins Hospital were used. After clustering, we selected a counterfactual country from the countries that were in the same cluster as the target country, and implemented NPI (X) at its lowest level. Thus, the target country and the counterfactual country were similar in implementation level of other NPIs and only differed in the implementation level of the target NPI (X). Therefore, we can calculate the effectiveness of NPI (X) without being concerned about the impurity of the effectiveness values that might be caused by other NPIs. This allowed us to calculate the effectiveness of NPI (X) using the interrupted time series analysis with the control group. Interrupted time series analysis assesses the effect of different policy-implementation levels by evaluating interruptions caused by policies in trend and level after the policy-implementation date. Before the NPI-implementation date, the implementation levels of NPIs were similar in both selected countries. After this date, the counterfactual country could be treated as a baseline for calculating changes in the trends and levels of COVID-19 cases in the target country. To demonstrate this approach, we used the generalized least square (GLS) method to estimate interrupted time series parameters related to the effectiveness of school closure (the target NPI) in Spain (the target country). The results show that increasing the implementation level of school closure caused a 34% decrease in COVID-19 prevalence in Spain after only 10 days compared to the counterfactual country. Full article
(This article belongs to the Proceedings of The 9th International Conference on Time Series and Forecasting)
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<p>Developed hybrid methodology.</p>
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<p>Data frame transformation for time series clustering.</p>
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<p>Determining the number of clusters by Silhouette score.</p>
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<p>Clustering (K = 2) results for the second wave of COVID-19.</p>
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<p>ACF and PACF plot of OLS model residuals.</p>
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<p>COVID-19 prevalence in target and control countries with and without school closure level increase.</p>
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13 pages, 1684 KiB  
Article
Which Wastepaper Should Not Be Processed?
by Edyta Małachowska, Aneta Lipkiewicz, Marcin Dubowik and Piotr Przybysz
Sustainability 2023, 15(4), 2850; https://doi.org/10.3390/su15042850 - 4 Feb 2023
Cited by 5 | Viewed by 2025
Abstract
In the 21st century, numerous economic and environmental initiatives have significantly increased paper recycling, which continues to expand due to environmental awareness. With increasing recycling rate, low-quality paper fractions may be included in the process, leading to the overproduction of very low-value papers [...] Read more.
In the 21st century, numerous economic and environmental initiatives have significantly increased paper recycling, which continues to expand due to environmental awareness. With increasing recycling rate, low-quality paper fractions may be included in the process, leading to the overproduction of very low-value papers that cannot be reprocessed. Moreover, the production of paper from poor-quality wastepaper can result in the introduction of chemicals from the recycled paper into the recycling loop and unintended spread of chemical substances. Therefore, reliable and conscious selection of recycled pulp is imperative. To this end, the present study verified the properties of recycled pulp critical for the assessment of its papermaking ability for the production of high-quality sanitary paper. Following an examination of samples, it was found that the key parameters that influence the papermaking ability of wastepaper include presence of impurities, content of extractive substances, freeness, and length of fiber. On this basis, types of wastepaper that, at the very beginning, did not portend well for obtaining paper products with high potential for utility were eliminated. Full article
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<p>Microscopic images of wastepaper surfaces.</p>
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<p>Microscopic images of wastepaper surfaces.</p>
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<p>Light reflection curve of white wastepaper.</p>
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<p>Light reflection curve of mixed wastepaper.</p>
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9 pages, 581 KiB  
Perspective
The Potential Antiviral Effects of Selenium Nanoparticles and Coated Surfaces
by Jonathan Kopel, Joe Fralick and Ted W. Reid
Antibiotics 2022, 11(12), 1683; https://doi.org/10.3390/antibiotics11121683 - 23 Nov 2022
Cited by 8 | Viewed by 1929
Abstract
Modern epidemics quickly spread across borders and continents with devastating effects on both human health and the world economy. This issue is made worse by the various ways that infections are spread, including through aerosol, droplets, and fomites. The antibacterial qualities of various [...] Read more.
Modern epidemics quickly spread across borders and continents with devastating effects on both human health and the world economy. This issue is made worse by the various ways that infections are spread, including through aerosol, droplets, and fomites. The antibacterial qualities of various surface materials and coatings have been the subject of much research. However, the antiviral activity of metal coatings can be heavily influenced by imbalances in metal distribution and the presence of other metal impurities. As such, there is interest in developing novel surface coatings that can reduce the transmission of active viral particles in healthcare facilities. In recent years, the non-metals, such as selenium and nanoparticles, have acquired greater interest from the medical and scientific community for their antiviral surface activity. In this review, we will discuss the cellular and physiological functions of selenium in mammalian cells and against viral infections. We then discuss the mechanism behind selenium coated surfaces and their efficacy against bacterial infections. Lastly, we examine the antiviral activity of selenium, and the potential antiviral activity of selenium nanoparticles and coatings. Full article
(This article belongs to the Section Mechanisms and Structural Biology of Antibiotic Action)
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<p>Confocal laser scanning microscopy of biofilm formed by <span class="html-italic">E. coli</span> GFP (<b>A</b>) and <span class="html-italic">S. aureus</span> GFP AH133 (<b>B</b>) on control tubing (left) and selenium compound polymerized tubing (right). Images were acquired at 2 µm intervals through the biofilms using a Nikon A1+/AIR+ Confocal Microscope.</p>
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14 pages, 3559 KiB  
Article
A Detection-Service-Mobile Three-Terminal Software Platform for Point-of-Care Infectious Disease Detection System
by Xiangyi Su, Yile Fang, Haoran Liu, Yue Wang, Minjie Ji, Zhu Chen, Hui Chen, Song Li, Yan Deng, Lian Jin, Yuanying Zhang, Murugan Ramalingam and Nongyue He
Biosensors 2022, 12(9), 684; https://doi.org/10.3390/bios12090684 - 25 Aug 2022
Cited by 1 | Viewed by 2042
Abstract
The traditional infectious disease detection process is cumbersome, and there is only a single application scenario. In recent years, with the development of the medical industry and the impact of the epidemic situation, the number of infectious disease detection instruments based on nursing [...] Read more.
The traditional infectious disease detection process is cumbersome, and there is only a single application scenario. In recent years, with the development of the medical industry and the impact of the epidemic situation, the number of infectious disease detection instruments based on nursing point detection has been increasing. Due to this trend, many detection instruments and massive detection data urgently need to be managed. In addition, the experiment failed due to the abnormal fluorescence curve generated by a human operator or sample impurities. Finally, the geographic information system has also played an active role in spreading and preventing infectious diseases; this paper designs a “detection-service-mobile” three-terminal system to realize the control of diagnostic instruments and the comprehensive management of data. Machine learning is used to classify the enlarged curve and calculate the cycle threshold of the positive curve; combined with a geographic information system, the detection results are marked on the mobile terminal map to realize the visual display of the positive results of nucleic acid amplification detection and the early warning of infectious diseases. In the research, applying this system to portable field pathogen detection is feasible and practical. Full article
(This article belongs to the Special Issue Biomedical Signal Processing in Healthcare and Disease Diagnosis)
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<p>The overall architecture of the three-terminal software. The detection terminal can be used in different scenarios, and the data can be synchronized to the server so that the mobile terminal can view the data and address the location of the instrument anytime and anywhere and display this visually.</p>
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<p>Workflow of three-terminal software. Describes the workflow when the user uses the software to realize the automatic control of the experiment. First, the detection terminal obtains data by controlling the automatic experiment of the lower computer and then synchronizes the data to the server. Finally, the mobile terminal accesses the database and displays the results on the map.</p>
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<p>Flow chart of fluorescence curve analysis. It is divided into four parts: send data, curve classification, Ct value calculation, and receive data.</p>
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<p>The steps of classifier selection and training. It includes data collection, feature selection and normalization, classifier selection, and performance evaluation.</p>
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<p>Six types of curves are input to the classifier. Different curve types are distinguished by the color of dot. Positive curve, negative curve and abnormal curve use red dot, blue dot and purple dot respectively (<b>a</b>) The curve was s-shaped, with an obvious exponential phase and plateau phase. (<b>b</b>) The rising rate was slow at the peak stage of the amplification phase and fast at the later stage of the amplification phase. (<b>c</b>) Straight line parallel to the X axis. (<b>d</b>) Jump at the end of the curve. (<b>e</b>) The curve showed a trend of rising first and then declining. (<b>f</b>) Upward drift line or approximate upward drift line.</p>
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<p>Principal component analysis diagram of six curves.</p>
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<p>The main interface of the detection software. (<b>a</b>) The main page, (<b>b</b>) the configuration page of nucleic acid extraction parameters, (<b>c</b>) the qPCR parameter configuration page, (<b>d</b>) the page for selecting card boxes and channels, (<b>e</b>) the page for nucleic acid extraction, and (<b>f</b>) the page for qPCR.</p>
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<p>The main interface of the mobile software. (<b>a</b>) Home page of the mobile software. (<b>b</b>,<b>c</b>) Map visualization.</p>
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<p>Confusion matrix of SVC in the form of the heat map. The larger the value, the darker the color, which can help us clearly see the prediction effect of each category.</p>
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<p>Curve fitting diagram of original data. The original data and fitted curves of HBV samples at three different concentrations are displayed in a graph, and the amplification area is enlarged. In the figure, the positions of inflection points calculated by StepOnePlus<sup>TM</sup> and the self-developed algorithm are marked, respectively. The abscissa of the inflection point is the Ct value. The specific values are shown in <a href="#biosensors-12-00684-t004" class="html-table">Table 4</a>.</p>
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31 pages, 7690 KiB  
Article
Silicates from Lherzolites in the South-Eastern Part of the Kempirsay Massif as the Source for Giant Chromitite Deposits (the Southern Urals, Kazakhstan)
by Dmitri E. Saveliev, Darkhan K. Makatov, Ildar R. Rakhimov, Ruslan A. Gataullin and Vladimir V. Shilovskikh
Minerals 2022, 12(8), 1061; https://doi.org/10.3390/min12081061 - 22 Aug 2022
Cited by 5 | Viewed by 2194
Abstract
We provide results of a comprehensive mineralogical and microstructural study of relict lherzolites of the main ore field and fresh rocks from a deep structural borehole drilled in the south-eastern part of the Kempirsay massif. Olivine and orthopyroxene from lherzolites contain numerous pieces [...] Read more.
We provide results of a comprehensive mineralogical and microstructural study of relict lherzolites of the main ore field and fresh rocks from a deep structural borehole drilled in the south-eastern part of the Kempirsay massif. Olivine and orthopyroxene from lherzolites contain numerous pieces of evidence of material redistribution at different scales caused mainly by solid-state processes, such as plastic flow of mantle, syntectonic recrystallization, and annealing. The results of deformation-induced processes at the submicron scale are recorded by optical and electronic microscopy. In olivine, the plastic deformation caused segregation of impurities at structural defects. As a result, abundant tiny rods of newly formed Cr-spinels occurred inside its grains. Moreover, in enstatite, deformation caused partial or complete chemical decomposition with exsolution of diopside, pargasite and spinel lamellae up to the formation of a “fibrous” structure. In other cases, it provided partial or complete recrystallization to form new phases of enstatite-2, forsterite, diopside, pargasite, and spinel. Petrographic observations are validated by geochemical data, i.e., regularly decreasing concentrations of minor elements in neoblasts compared to large grains (porphyroclasts). Further redistribution of spinel grains with the formation of chromitite bodies is witnessed by their permanent association with the most mobile phase of the upper mantle, i.e., olivine, which is the only mineral that remains stable under the intense plastic flow. An increased concentration of Cr-spinel grains during formation of massive chromitites could appear under conditions close to pressure sintering, as evidenced by stressed textures of ores and an increased grain size compared to disseminated chromitites. The formation of unique chromitite deposits is associated with integration of numerous disparate podiform bodies into “ore bunches” due to the tectonic impact in the shear-compression regime. This was most likely associated with transition of the rifting (spreading) regime to that of the upper mantle of the fore-arc basin. Full article
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<p>(<b>a</b>) Position of the Kempirsay ophiolite massif within Uralian fold belt (after [<a href="#B32-minerals-12-01061" class="html-bibr">32</a>]) and its schematic geological map (after [<a href="#B15-minerals-12-01061" class="html-bibr">15</a>,<a href="#B24-minerals-12-01061" class="html-bibr">24</a>]) (<b>b</b>): 1–6—Stratified rocks: 1—Yuzhnomugodzhary zone (basalts (S-D<sub>1</sub>, D<sub>2</sub>), flyschoids and olistostromes (D<sub>3</sub>-C<sub>1</sub>); 2—Ebeta zone (basalt-andesite-rhyodacite units, carbonaceous-silicite and greywacke formations (V?PZ<sub>1–2</sub>); 3–6—Sakmara zone: 3—basalt-andesite-dacite units, greywacke phthanite and carbonate formations (PZ<sub>1–2</sub>), 4—pillow lavas and pyroclastics of basalt-andesite-rhyodacite units with members of phtanites and clay-siliceous shales (PZ<sub>1–2</sub>), 5—phtanites and carbonaceous shales (O<sub>2</sub>), 6—tholeiite pillow basalts with phtanite lenses (O<sub>2</sub>), 7–10—Kempirsay massif: 7—swarms of parallel diabase dykes and isotropic hornblende gabbro, 8—Kyzylkain unit of pyroxenite-gabbro rocks, 9—Kokpekta unit of olivine gabbro and troctolite, 10—upper mantle harzburgite, lherzolite and dunite, 11—chromitites (a—unique and large deposits; b—ordinary deposits and occurrences; icon size correlates with ore reserves), 12—numbers of holes from which samples were studied: 766 (samples 7087, 8156), 820 (sample 820/300), 809 (sample 809/347), 012 (sample 012/300.9), 046 (sample 046/359.5), 016 (samples 016/925 and 016/1108.5), 079 (sample 079/90.7), 005 (sample 005/263.6), 094 (sample 094/238.7), 947 (sample 947/540).</p>
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<p>Petrographic features of peridotites from Kempirsay massif: (<b>a</b>)—Protogranular structure in predominantly olivine aggregate of lherzolite with secondary mesh serpentine (sample 820/300); (<b>b</b>)—Porphyroclastic structure on the area with predominant enstatite grains in lherzolite (sample 809/347); (<b>c</b>)—Undulose extinction of olivine grain reflecting a subgrain structure development that induced by plastic deformation (sample 8156); (<b>d</b>)—Parallel-alternating extinction in plastically deformed olivine grains which surrounded by recrystallized neoblasts in fresh lherzolite (sample 8156); (<b>e</b>)—Polygonal-grained olivine aggregates (sample 7087); (<b>f</b>)—Anhedral olivine grain separated by subgrain boundaries in polygonal-grained aggregate (sample 7087). Arrows note subgrain boundaries. Ol—olivine, Opx—orthopyroxene, Spl—Cr-spinel.</p>
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<p>Structural and morphological features of pyroxene grains in lherzolites from Kempirsay massif: (<b>a</b>,<b>b</b>)—Deformation of Opx porphyroclast according with impregnation along shear zones olivine and diopside, and a deformation-indused formation of lamellae and neoblasts of diopside and pargasite (<b>a</b>—sample 7087, <b>b</b>—sample 016/1108.5); (<b>c</b>)—Deformed Opx porphyroclast with abundant lamellae (L) of diopside, pargasite, spinel, and a neoblast cluster (N) along shear zones (arrows) (sample 820/300); (<b>d</b>)—Initial stage of neoblast formation along blocks boundary and close to grain edges in deformed Opx grain (sample 809/347). Cpx—clinopyroxene.</p>
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<p>Morphological features of accessory spinel grains from ultramafic rocks of Kempirsay massif: (<b>a</b>,<b>b</b>)—Anhedral Cr-spinel grains (holly leaf) with silicate inclusions, as well as units of ol-spl and opx-spl “symplectites” close to them (<b>a</b>—sample 809/347, <b>b</b>—sample 8156); (<b>c</b>)—Unequally-grained Cr-spinels in lherzolite: fine-grained euhedral and subhedral grains, and large anhedral grain with branches (sample 7087); (<b>d</b>)—Large anhedral Cr-spinel grain containing inclusions and occupying silicate fragments in lherzolite (sample 7087); (<b>e</b>)—Subhedral and elongated Cr-spinel grains in fresh spinel peridotite (sample 7087); (<b>f</b>)—Subhedral Cr-spinel grain in serpentinized harzburgite (sample 012/300.9); (<b>g</b>)—Isometric smooth Cr-spinel grains in dunitic serpentinite (sample 947/540); (<b>h</b>)—Subhedral and euhedral Cr-spinel grains in serpentinized dunite (sample 046/359.5). bs—bastite, srp—serpentine.</p>
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<p>Evolution of chromitite structure in deposits of Kempirsay ophiolite massif: (<b>a</b>)—Sparsely disseminated fine-grained chromitite consisting of small smooth chromite grains (sample 079/90.7); (<b>b</b>)—Moderately disseminated chromitite: grains containing pargasite and olivine inclusions (sample 079/90.7); (<b>c</b>,<b>d</b>)—Amphibole inclusions in chromite grains (sample 005/263.6); (<b>e</b>)—Densely disseminated chromitite formed by impingement, compaction and coarsening of grains (sample 005/263.6); (<b>f</b>)—Massive coarse-grained chromitite with joints formed by compaction (sample 094/238.7); (<b>g</b>)—Squeezing of weak silicate matrix from between the chromite grains in massive ore and compaction by “pressure sintering” leading to disappearance of boundaries (sample 016/925); (<b>h</b>)—Already homogeneous massive chromitite with rare thin and straight joints as result of “pressure sintering” (sample 016/925). Width of images <b>a</b>,<b>b</b>,<b>e</b>–<b>h</b> is 2 mm. Amp—amphibole, Chr—chromite.</p>
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<p>(<b>a</b>)—Normative mineral compositions of peridotites inferred from chemical composition; (<b>b</b>)—OSMA diagram for coexisting Ol and Cr-spl grains; here, percent notes partial melting degree in experiment after [<a href="#B40-minerals-12-01061" class="html-bibr">40</a>], that corresponds to Ol-Spl compositions in restite; gray points are Ol-Spl compositions in lherzolite-type massifs of South Urals after [<a href="#B41-minerals-12-01061" class="html-bibr">41</a>]; Lz-Hb-766—peridotite of well 766; Lz-Hb-AZ—peridotite from Almaz-Zhemchuzhina deposit area; Hb—harzburgite, D—dunite; (<b>c</b>)—Compositions of Opx and Cpx on the triangular diagram En–Wo–Fs.</p>
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<p>(<b>a</b>)—Al–Cr–Fe diagram for three-valent cations of Cr-spinel; (<b>b</b>)—#Cr = Cr/(Cr + Al) vs. #Mg = Mg/(Mg + Fe) diagram for Cr-spinel grains; (<b>c</b>)—#Cr vs. <tt>Δ</tt>log(fO<sub>2</sub>) diagram; fields: 1–3, peridotite xenoliths: 1, primitive; 2, slightly metasomatized; 3, strongly metasomatized; 4, 5, abyssal peridotites with spinel (4) and plagioclase (5), after [<a href="#B42-minerals-12-01061" class="html-bibr">42</a>]; KrNrMn—lherzolite-type massifs of South Urals (Kraka, Nurali, Mindyak); Lc-Hb-766—peridotites of well 766; Lz-Hb-AZ—peridotite from Almaz-Zhemchuzhina deposit area; Hb—harzburgite, D—dunite; (<b>d</b>)—Diagram of PT formation conditions of mineral assemblages using pyroxene geothermometers and geobarometers [<a href="#B43-minerals-12-01061" class="html-bibr">43</a>,<a href="#B44-minerals-12-01061" class="html-bibr">44</a>]; gray points are samples of lherzolite-type massifs of South Urals.</p>
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<p>Olivine and orthopyroxene fabric in fresh lherzolites from well 766 of Kempirsay massif. Pole figures of the crystallographic orientation of olivine (Ol) and orthopyroxene (Opx) are presented in the upper hemisphere using an equal area projection. The color coding refers to the density of data points. S—foliation, L—lineation.</p>
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<p>Cr-spinel tiny precipitates in olivine and enstatite grains: (<b>a</b>)—Opx porphyroclast with numerous diopside, pargasite and spinel lamellae; (<b>b</b>)—Detailed images of the grain: we can see growing holly-leaf Cr-spinel grain oriented parallel to lamellae; (<b>c</b>)—Tiny spinel precipitates in olivine grain, as well as spinel and diopside lamellae in adjacent enstatite grain; (<b>d</b>)—Tiny spinel precipitates in olivine grain close to boundary with enstatite grain, as well as larger spinel precipitates in olivine at a distance. All images—sample 820/300.</p>
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<p>Formation and coalescence of precipitates in deformed orthopyroxene grain: (<b>a</b>)—General view of orthopyroxene porphyroclast with parallel zones containing by tiny crystals of diopside, spinel and pargasite (arrows noted bends induced by plastic deformation); (<b>b</b>)—Detail of the same grain (<b>a</b>,<b>c</b>)—Boundary in Opx grain: on the right, grain have fibrous structure caused by numerous sub-micrometer precipitates of spl and cpx; on the left, grain contains rare isometric inclusions of cpx and spl, similar spinel inclusions are observed in adjacent olivine grain; (<b>d</b>)—Detail of structure of “fibrous” Opx with numerous precipitates of pargasite, diopside and spinel; (<b>e</b>)—Enstatite neoblast (Opx<sub>n</sub>) in deformed porphyroclast of the same mineral (Opx<sub>p</sub>): in Opx porphyroclast, we can see abundant spinel and diopside lamellae but Opx neoblast associate with larger isometric grains of the same minerals; (<b>f</b>) –Detail of internal building of Opx porphyroclast: moment was fixed when spinel lamella are re-organizing into isometric grain. Images (<b>a</b>–<b>d</b>)—sample 809/347, (<b>e</b>–<b>f</b>)—sample 820/300.</p>
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<p>General model of Kempirsay chromitite deposits formation: (<b>a</b>)—initial stage of dunite formation, (<b>b</b>)—stage of disseminated chromitite formation, (<b>c</b>)—stage of massive podiform chromitite formation, (<b>d</b>)—terminal stage of large chromitite deposits formation.</p>
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11 pages, 4060 KiB  
Article
A Novel Method of Si and Si3N4 Powder Resources Recycling: Cold Bonding Briquettes
by Yuandong Xiong, Ying Li, Huiting Chen, Dejin Qiu, Shiyu Wei, Henrik Saxén and Yaowei Yu
Materials 2022, 15(16), 5496; https://doi.org/10.3390/ma15165496 - 10 Aug 2022
Cited by 1 | Viewed by 1537
Abstract
Silicon nitride (Si3N4) and silicon powder (Si) are two kinds of harmful solid waste in industrial production. As an environmental and low-consumption method, the cold-bonding technique is a novel method to utilize the problem of powder resource cycling. In [...] Read more.
Silicon nitride (Si3N4) and silicon powder (Si) are two kinds of harmful solid waste in industrial production. As an environmental and low-consumption method, the cold-bonding technique is a novel method to utilize the problem of powder resource cycling. In this experiment, mechanical and high-temperature properties of Si and Si3N4 briquettes were studied after cold bonding. The results are as follows: (1) The compressive strength of the Si and Si3N4 briquettes increased with the improvement of molding pressure. With the same binder (1 wt.%) and water (10 wt.%) addition, the compressive strength of the Si3N4 briquette arrived at 12,023.53 N under 40 Mpa molding pressure, which is much higher than that of the Si briquette (942.40 N). The Si particles are uneven and irregular, which leads to an intense arch bridge effect in the Si briquette and the compressive strength decrease. Compared with Si powder, the particle size and shape of Si3N4 is small, uniform, and regular. The influence of the arch bridge effect is smaller than that in the Si briquette. (2) After being treated at 1473 K for 1 h, the compressive strength of the Si briquette increased to 5049.83 N, and the compressive strength of the Si3N4 briquette had a slight change. The surface of the briquettes was contacted with oxygen and reacted to form an outer shell which mainly contains SiO2 in the high-temperature treatment. FT-IR results have shown there were no extra impurities in cold-bonded briquettes when using the organic binder. (3) The microstructure of the cross section of the Si and Si3N4 briquettes after high-temperature treatment presented that oxygen entered the briquette through the pores and continued to react with the Si and Si3N4. The outer shell of the Si briquette grew and thickened continuously with the oxygen spreading in the Si briquette. However, because of the smaller particle size and regular shape, little oxygen diffused in the Si3N4 briquette. The outer shell of the Si3N4 briquette is fairly thin, so the compressive strength did not change too much. Full article
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<p>Schematic of the process for making cold-bonded briquettes.</p>
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<p>Microstructure of (<b>a</b>) Si particles and (<b>b</b>) Si<sub>3</sub>N<sub>4</sub> particles.</p>
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<p>Compressive-displacement curves of the briquettes under various pressures (<b>a</b>) Si, (<b>b</b>) Si<sub>3</sub>N<sub>4</sub>.</p>
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<p>Cross-sectional photographs of (<b>a</b>) Si briquette; (<b>b</b>) Si briquette after being treated at 1473 K for 1 h; (<b>c</b>) Si<sub>3</sub>N<sub>4</sub> briquette; (<b>d</b>) Si<sub>3</sub>N<sub>4</sub> briquette after being treated at 1473 K for 1 h.</p>
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<p>Variation of compressive-displacement curves after being treated at 1473 K for 1 h: (<b>a</b>) Si briquette, (<b>b</b>) Si<sub>3</sub>N<sub>4</sub> briquette.</p>
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<p>XRD patterns of briquette and outer shell: (<b>a</b>) Si; (<b>b</b>) Si<sub>3</sub>N<sub>4</sub>.</p>
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<p>Formation of SiO<sub>2</sub> layer on the surface of briquettes after heating under an oxygen atmosphere.</p>
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<p>FTIR spectra of powder, briquette, and outer shell (<b>a</b>) Si and (<b>b</b>) Si<sub>3</sub>N<sub>4</sub>.</p>
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<p>SEM of the cross section of Si and Si<sub>3</sub>N<sub>4</sub> briquette: (<b>a</b>) Si briquette, (<b>b</b>) Si<sub>3</sub>N<sub>4</sub> briquette; EDS image of outer shell: (<b>c</b>) Si briquette, (<b>d</b>) Si<sub>3</sub>N<sub>4</sub> briquette.</p>
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18 pages, 6478 KiB  
Article
Modeling the Chemical Pollution of the Area by the Random-Addition Method
by Roman Ekhlakov, Ekaterina Romanova, Elena Dogadina, Sergey Korchagin, Sergey Gataullin, Józef Mosiej, Timur Gataullin and Petr Nikitin
Fractal Fract. 2022, 6(4), 193; https://doi.org/10.3390/fractalfract6040193 - 31 Mar 2022
Cited by 3 | Viewed by 6892
Abstract
Currently, a significant group of industrial facilities can be classified as chemically hazardous facilities (CHFs). To predict the spread of harmful impurities in the programs being developed, Gaussian and Lagrangian models are actively used, on the basis of which the complexes used both [...] Read more.
Currently, a significant group of industrial facilities can be classified as chemically hazardous facilities (CHFs). To predict the spread of harmful impurities in the programs being developed, Gaussian and Lagrangian models are actively used, on the basis of which the complexes used both in the EMERCOM of Russia and in research organizations are being implemented. These complexes require the introduction of a large amount of information, including the characteristics of the wind field in the distribution of an emergency chemically hazardous substance, which limits their use. In systems, the formation of which is influenced by a large number of different random factors, spatial scaling (similarity) is often found, and one or another parameter can be described using the methods of fractal geometry, which in the past few decades has been actively and successfully applied to the description of various physical objects. The purpose of this study is to analyze the possibility of using the random-addition method for early prediction of the distribution of harmful impurities in the surface air layer during the short-term release of a substance on the surface as a result of an emergency. Full article
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<p>Appearance of maps of the area: (<b>a</b>) the density of chemical pollution; (<b>b</b>) altitude above sea level; (<b>c</b>) precipitation zones.</p>
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<p>Stages of risk analysis and forecasting.</p>
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<p>Prediction causal diagram.</p>
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<p>Qualitative change over time of the zone with the threshold concentration.</p>
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<p>Change in the distribution zone of a substance with a threshold concentration over time.</p>
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<p>A set of surface-level lines.</p>
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<p>Determination of the similarity dimension for the wind field of the atmosphere in the surface layer.</p>
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<p>Example of isohypsum.</p>
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<p>Projections of the intervals of conditional heights.</p>
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<p>Conditional values of inhalation doses in the absence of a directed wind and the presence of random turbulent movements of the environment.</p>
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<p>Density of pollution in relative units (work surfaces). Hurst index <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>; scale factor <math display="inline"><semantics> <mrow> <mi>r</mi> <mo>=</mo> <mn>1.41</mn> </mrow> </semantics></math>.</p>
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<p>Approximating dependences for each wind speed, where the OX axis is the equivalent amount of PPS, and OY is the depth of the contamination zone.</p>
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<p>Approximating dependences for each wind speed, where the OX axis is the equivalent amount of PPS, and OY is the depth of the contamination zone.</p>
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<p>Analysis of the dependence of the area of infection on the wind speed at the corresponding depths of hazardous chemicals according to the existing method (blue) and by the method of random addition (green).</p>
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28 pages, 9781 KiB  
Article
Origin of Steam Contaminants and Degradation of Solid-Oxide Electrolysis Stacks
by Dominik Schäfer, Larissa Queda, Volker Nischwitz, Qingping Fang and Ludger Blum
Processes 2022, 10(3), 598; https://doi.org/10.3390/pr10030598 - 19 Mar 2022
Cited by 5 | Viewed by 3143
Abstract
Two once-through steam generators and a combination of a steam generator and a gas preheater for supplying feed gases to solid-oxide electrolysis stacks were evaluated for their carryover characteristics of contaminants from the feed-water into the steam phase. The concentrations of various trace [...] Read more.
Two once-through steam generators and a combination of a steam generator and a gas preheater for supplying feed gases to solid-oxide electrolysis stacks were evaluated for their carryover characteristics of contaminants from the feed-water into the steam phase. The concentrations of various trace impurities in the steam were determined by sampling the steam condensates and screening them with inductively coupled plasma–mass spectrometry for 19 elements and liquid ion chromatography and continuous flow analysis for chloride and ammonium. Steam-soluble species such as boric acid undergo complete volatilization and transfer into the steam phase. During unstable evaporation in the steam generators an extensive physical carryover of alloying metal species was observed. At realistic operation conditions for steam electrolysis, the gas preheater caused a considerable release of silicon into the steam phase. Two stack experiments were performed with common preheater temperatures and showed largely increased cell voltage degradation at higher operation temperatures. The post-test chemical analysis of cell samples revealed significant concentrations of silicon in the samples that are regarded as primary cause for increased degradation. These findings could partially explain the wide spread of degradation rates reported for solid-oxide steam electrolysis experiments. Full article
(This article belongs to the Section Energy Systems)
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<p>Sodium concentrations in condensates in dependence of operation temperature for the AG-SG: (<b>a</b>) Background levels for clean feed-waters; (<b>b</b>) Concentrations for spiked feed-water solutions containing sodium.</p>
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<p>Sodium concentrations in condensates in dependence of operation temperature for the two SB-SG: (<b>a</b>) Background levels for clean feed-waters; (<b>b</b>) Concentrations for spiked feed-water solutions containing sodium.</p>
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<p>Ammonium and chloride concentrations in condensates for the AG-SG. Dashed lines indicate the concentrations in the feed-water solutions.</p>
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<p>Background concentrations of quantifiable species in condensates of the AG-SG (group A) in dependence of operation temperature.</p>
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<p>Background concentrations of quantifiable species in condensates of the SB-SG (group A) in dependence of operation temperature.</p>
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<p>Background concentrations of quantifiable species in condensates of the AG-SG (group B) in dependence of operation temperature.</p>
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<p>Background concentrations of quantifiable species in condensates of the SB-SG (group B) in dependence of operation temperature.</p>
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<p>Concentrations of quantifiable species in condensates of the AG-SG obtained with spiked feed-water (group A) in dependence of operation temperature.</p>
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<p>Concentrations of quantifiable species in condensates of the SB-SG obtained with spiked feed-water (group A) in dependence of operation temperature (no concentrations above limit of detection for Bi and Co).</p>
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<p>Concentrations of quantifiable species in condensates of the AG-SG obtained with spiked feed-water (group B) in dependence of operation temperature. Dashed lines indicate feed-water concentrations.</p>
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<p>Concentrations of quantifiable species in condensates of the SB-SG obtained with spiked feed-water (group B) in dependence of operation temperature. Dashed lines indicate feed-water concentrations (no concentrations above limit of detection for Ca).</p>
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<p>Concentrations of silicon, arsenic, and molybdenum in steam condensates obtained after the fuel gas preheater in dependence of the preheater operation temperature.</p>
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<p>Concentrations of (<b>a</b>) boron and (<b>b</b>) antimony in steam condensates obtained after the fuel gas preheater in dependence of the preheater operation temperature.</p>
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<p>Time traces showing layer voltages, current densities, stack temperatures, and preheater operation temperatures for stack A.</p>
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<p>Time traces showing layer voltages, current densities, stack temperatures, and preheater operation temperatures for stack B.</p>
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<p>Concentrations of silicon, boron, molybdenum, and chromium found in cell samples of the stacks A and B after operation.</p>
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<p>Sodium concentrations in steam condensates (includes clean and spiked feed-waters): (<b>a</b>) for the AG-SG; (<b>b</b>) for the two SB-SGs.</p>
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14 pages, 4031 KiB  
Article
Structural, Optical, Electrical and Antibacterial Properties of Fe-Doped CeO2 Nanoparticles
by Shalendra Kumar, Suliman Yousef AlOmar, Kavita Kumari, Fadwa Albalawi, Rajesh Kumar, Faheem Ahmed, Naushad Ahmad, Sourabh Dwivedi and Parvez Ahmad Alvi
Crystals 2021, 11(12), 1594; https://doi.org/10.3390/cryst11121594 - 20 Dec 2021
Cited by 13 | Viewed by 3171
Abstract
This paper reports the structural, optical and antimicrobial study of Ce1−xFexO2−δ (0 x 20) nanoparticles (NPs) synthesized using a microwave-assisted hydrothermal method. The XRD pattern analysed using Rietveld refinement method clearly infers that all [...] Read more.
This paper reports the structural, optical and antimicrobial study of Ce1−xFexO2−δ (0 x 20) nanoparticles (NPs) synthesized using a microwave-assisted hydrothermal method. The XRD pattern analysed using Rietveld refinement method clearly infers that all the samples exhibit single phase nature and exclude the possibility of an impurity phase. The lattice parameters and unit cell volume were found to decrease with an increase in Fe-doping content in CeO2 nanoparticles. The crystalline size determined using XRD pattern and TEM micrographs was found to decrease with Fe doping in CeO2. Selective area electron diffraction (SAED) pattern also demonstrated the crystalline nature of the Fe-CeO2 nanoparticles. Optical properties studied using UV–vis spectroscopy indicated that band gap decreased with an increase in Fe doping. The electrical properties have been investigated via dielectric constant, dielectric loss and AC conductivity. The dielectric constant was found to increase in the Fe-doped CeO2 nanoparticles, while AC conductivity was found to be reduced, which shows good dielectric behaviour of the Fe-doped CeO2 nanoparticles. The antibacterial activity of the synthesized NPs was achieved under ambient conditions with different bacteria, and the results showed that the properties were different for both bacteria. The antimicrobial activity reflects the possibility to develop Fe-doped CeO2 NPs as antibacterial agents against extensive microorganisms to control and prevent the spread and persistence of bacterial infections. Full article
(This article belongs to the Section Inorganic Crystalline Materials)
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<p>(<b>a</b>) Rietveld refinement of the XRD patterns of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs, (<b>b</b>) Representation of unit cell structure of Ce<sub>0.80</sub>Fe<sub>0.20</sub>O<sub>2−δ</sub> nanoparticles.</p>
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<p>Variation of lattice parameter, volume and particle size with the doping concentration of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs.</p>
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<p>TEM micrographs of (<b>a</b>) CeO<sub>2</sub>, (b) Ce<sub>0.95</sub>Fe<sub>0.05</sub>O<sub>2</sub>, (<b>c</b>) Ce<sub>0.90</sub>Fe<sub>0.10</sub>O<sub>2</sub>, (<b>d</b>) Ce<sub>0.80</sub>Fe<sub>0.20</sub>O<sub>2</sub> NPs. SAED patterns of (<b>e</b>) CeO<sub>2</sub>, (<b>f</b>) Ce<sub>0.95</sub>Fe<sub>0.05</sub>O<sub>2</sub>, (<b>g</b>) Ce<sub>0.80</sub>Fe<sub>0.20</sub>O<sub>2</sub> NPs.</p>
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<p>(<b>a</b>) Absorption curves and (<b>b</b>) (αhν)<sup>2</sup> vs (hν) plots of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs.</p>
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<p>Dielectric constant vs. frequency of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs at room temperature.</p>
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<p>Loss tangent (tan δ) vs. frequency of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs at room temperature.</p>
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<p>(<b>a</b>). AC conductivity vs. frequency of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs at room temperature. (<b>b</b>). Fitted ln(AC conductivity) vs. ln(ω) of Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs at room temperature.</p>
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<p>Bacterial growth inhibition using Ce<sub>1−x</sub>Fe<sub>x</sub>O<sub>2−δ</sub>, (0 ≤ x ≤ 20) NPs.</p>
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<p>Antibiofilm activity of (<b>a</b>) CeO<sub>2</sub>, (<b>b</b>) Ce<sub>0.95</sub>Fe<sub>0.05</sub>O<sub>2</sub>, (<b>c</b>) Ce<sub>0.90</sub>Fe<sub>0.10</sub>O<sub>2</sub>, (<b>d</b>) Ce<sub>0.80</sub>Fe<sub>0.20</sub>O<sub>2</sub> NPs.</p>
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17 pages, 4529 KiB  
Article
Production of High Purity Biosurfactants Using Heavy Oil Residues as Carbon Source
by Athina Mandalenaki, Nicolas Kalogerakis and Eleftheria Antoniou
Energies 2021, 14(12), 3557; https://doi.org/10.3390/en14123557 - 15 Jun 2021
Cited by 11 | Viewed by 2503
Abstract
Typically, oil pollution cleanup procedures following first response actions include dispersion. Crude oil is biodegradable, and its bioavailability can be increased when dispersed into very fine droplets by means of chemical surfactants. Although their use is widely spread in many applications, the latter [...] Read more.
Typically, oil pollution cleanup procedures following first response actions include dispersion. Crude oil is biodegradable, and its bioavailability can be increased when dispersed into very fine droplets by means of chemical surfactants. Although their use is widely spread in many applications, the latter may prove toxic, depending on the extent of use. The use of biological means, such as bioremediation and biosurfactants, has emerged over the past years as a very promising ‘green’ alternative technology. Biosurfactants (BSs) are amphiphilic molecules produced by microorganisms during biodegradation, thus increasing the bioavailability of the organic pollutants. It is their biodegradability and low toxicity that render BSs as a very promising alternative to the synthetic ones. Alcanivorax borkumensis SK2 strain ability to produce BSs, without any impurities from the substrate, was investigated. The biosurfactant production was scaled up by means of a sequencing batch reactor (SBR) and a heavy oil residue substrate as the carbon source. The product is free from substrate impurities, and its efficiency is tested on oil bioremediation in the marine environment. The product’s dispersion efficiency was determined by the baffled flask test. The production method proposed can have a significant impact to the market, given the ever-increasing demand for ecologically friendly, reliable, commercially viable and economically competitive environmental cleanup techniques. Full article
(This article belongs to the Special Issue Marine Biotechnology: Applications and Challenges)
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<p>Growth curve of <span class="html-italic">Alcanivorax borkumensis SK2</span> in ONR7a with HOF-2 and N and P nutrients. Optical Density (OD) vs. Time.</p>
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<p>(<b>a</b>) Biosurfactant production by <span class="html-italic">A. borkumensis SK2</span> in ONR7a with HOF-1 as carbon source and N and P nutrients (filled dots <span style="color:#0070C0">●</span>); 52.5 mg/L is the maximum amount of BS reached without impurities in the product; after that, the product is contaminated by the carbon source (empty dots <b><span style="color:#F3850D">o</span></b>). (<b>b</b>) Biosurfactant production by <span class="html-italic">A. borkumensis SK2</span> in ONR7a with HOF-2 as the carbon source and N and P nutrients.</p>
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<p>Biosurfactant concentration cycle in sequencing batch reactor. Time zero is after a 10-day batch operation period. Max BS represents the BS concentration just before removing 60% of the cultures volume (rhombus). Min BS represents the BS concentration just after adding new ONR7a and nutrients to fill up the bioreactor (square). Black circles represent sampling points in between the min and max values.</p>
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<p>BFT efficiency test of BS-in-SOY agent with BS produced by <span class="html-italic">Alcanivorax borkumensis SK2</span>. The concentration of BS diluted in soybean oil where 0%, 5%, 7.5% and 15% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test results. Saturated hydrocarbons concentration after 28 days of bioremediation (Cx are the saturated hydrocarbons, x is the number of carbons in the molecule, Pr: pristane and Ph: phytane). (a) SW_CO: Sea water with crude oil. (b) SW_CO_NP: Sea water, crude oil and N and P nutrients. (c) SW_CO_NP_BS: Sea water, crude oil, N and P nutrients and BS-in-dH<sub>2</sub>O 0.4% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test results. Saturated hydrocarbons concentration after 28 days of bioremediation (Cx are the saturated hydrocarbons, x is the number of carbons in the molecule, Pr: pristane and Ph: phytane). (a) SW_CO: Sea water with crude oil. (b) SW_CO_SOY: Sea water, crude oil and soybean oil (c). SW_CO_NP: Sea water, crude oil and N and P nutrients. (d) SW_CO_NP_SOY: Sea water, crude oil, N and P nutrients and soybean oil. (e) SW_CO_NP_15% BS.IN.SOY: Sea water, crude oil, N and P nutrients and BS-in-SOY agent 15% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test. Comparing percentages of reduction of Saturated Hydrocarbons after 28 days of bioremediation (Cx are the saturated hydrocarbons, x is the number of carbons in the molecule, Pr: pristane and Ph: phytane). Comparing results of cultivations with sea water from Agios Onoufrios and crude oil plus BS-in-dH<sub>2</sub>O agent (0.4% <span class="html-italic">w</span>/<span class="html-italic">v</span>) and BS-in-SOY agent (15% <span class="html-italic">w</span>/<span class="html-italic">v</span>).</p>
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<p>Calibration curve of dissolved crude oil in saline water.</p>
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<p>Bioremediation test results. Saturated hydrocarbons concentration after 7 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_NP: Sea water, crude oil and N and P nutrients. (c) SW_CO_NP_BS: Sea water, crude oil, N and P nutrients and BS-in-dH<sub>2</sub>O 0.4% <span class="html-italic">w</span>/<span class="html-italic">v</span>. (Cx are the saturated hydrocarbons, x is the number of carbons in the molecule, Pr: pristane and Ph: phytane).</p>
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<p>Bioremediation test results. Saturated hydrocarbons concentration after 7 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_SOY: Sea water, crude oil and soybean oil. (c) SW_CO_NP: Sea water, crude oil and N and P nutrients. (d) SW_CO_NP_SOY: Sea water, crude oil, N and P nutrients and soybean oil. (e) SW_CO_NP_15%BS.IN.SOY: Sea water, crude oil, N and P nutrients and BS-in-SOY agent 15% <span class="html-italic">w</span>/<span class="html-italic">v</span>. (Cx are the saturated hydrocarbons, x is the number of carbons in the molecule, Pr: pristane and Ph: phytane).</p>
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<p>Bioremediation test results. Aromatic hydrocarbons concentration after 7 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_NP: Sea water, crude oil and N and P nutrients. (c) SW_CO_NP_BS: Sea water, crude oil, N and P nutrients and BS-in-dH<sub>2</sub>O 0.4% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test results. Aromatic hydrocarbons concentration after 28 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_NP: Sea water, crude oil and N and P nutrients. (c) SW_CO_NP_BS: Sea water, crude oil, N and P nutrients and BS-in-dH<sub>2</sub>O 0.4% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test results. Aromatic hydrocarbons concentration after 7 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_SOY: Sea water, crude oil and soybean oil. (c) SW_CO_NP: Sea water, crude oil and N and P nutrients (d) SW_CO_NP_SOY: Sea water, crude oil, N and P nutrients and soybean oil. (e) SW_CO_NP_15%BS.IN.SOY: Sea water, crude oil, N and P nutrients and BS-in-SOY agent 15% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Bioremediation test results. Aromatic hydrocarbons concentration after 28 days of bioremediation. (a) SW_CO: Sea water with crude oil. (b) SW_CO_SOY: Sea water, crude oil and soybean oil. (c) SW_CO_NP: Sea water, crude oil and N and P nutrients. (d) SW_CO_NP_SOY: Sea water, crude oil, N and P nutrients and soybean oil. (e) SW_CO_NP_15%BS.IN.SOY: Sea water, crude oil, N and P nutrients and BS-in-SOY agent 15% <span class="html-italic">w</span>/<span class="html-italic">v</span>.</p>
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<p>Production scheme of rhamnolipids using a sequencing batch reactor.</p>
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15 pages, 474 KiB  
Article
Mathematical Description of the Groundwater Flow and that of the Impurity Spread, which Use Temporal Caputo or Riemann–Liouville Fractional Partial Derivatives, Is Non-Objective
by Agneta M. Balint and Stefan Balint
Fractal Fract. 2020, 4(3), 36; https://doi.org/10.3390/fractalfract4030036 - 21 Jul 2020
Cited by 13 | Viewed by 2969
Abstract
In this paper, it is shown that the mathematical description of the bulk fluid flow and that of content impurity spread, which uses temporal Caputo or temporal Riemann–Liouville fractional order partial derivatives, having integral representation on a finite interval, in the case of [...] Read more.
In this paper, it is shown that the mathematical description of the bulk fluid flow and that of content impurity spread, which uses temporal Caputo or temporal Riemann–Liouville fractional order partial derivatives, having integral representation on a finite interval, in the case of a horizontal unconfined aquifer is non-objective. The basic idea is that different observers using this type of description obtain different results which cannot be reconciled, in other words, transformed into each other using only formulas that link the numbers representing a moment in time for two different choices from the origin of time measurement. This is not an academic curiosity; it is rather a problem to find which one of the obtained results is correct. Full article
(This article belongs to the Special Issue Fractional Behavior in Nature 2019)
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<p>Aquifers and wells.</p>
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2 pages, 168 KiB  
Abstract
A Center for the Rapid Analysis of Clinical-Grade Biologics: The Biophysical Characterization of HIV-1 Env Protein
by José A. Lasalde-Dominicci, Abel Baerga-Ortiz, Pearl Akamine, José A. González-Feliciano, Coral Capó-Vélez and Manuel Delgado-Vélez
Proceedings 2020, 50(1), 130; https://doi.org/10.3390/proceedings2020050130 - 15 Jul 2020
Cited by 1 | Viewed by 1276
Abstract
The development of a prophylactic vaccine against the human immunodeficiency virus (HIV) is of paramount importance in the global drive to halt the spread of the virus. Even after the successful discovery and initial testing of a vaccine candidate, there are hurdles associated [...] Read more.
The development of a prophylactic vaccine against the human immunodeficiency virus (HIV) is of paramount importance in the global drive to halt the spread of the virus. Even after the successful discovery and initial testing of a vaccine candidate, there are hurdles associated with production yield, purification strategy, and in vitro stability that may hinder its development as a biological product. The goal of the Clinical Bioreagent Center (CBC) is to streamline the vaccine development pipeline from a promising lead to the clinic, in part by developing state-of-the-art analytical tools to characterize and to quickly monitor the quality of the HIV-1 Env protein, a new vaccine candidate. A method was developed to determine the purity of the HIV-1 Env glycoprotein by capillary electrophoresis that provides higher sensitivity of detection of impurities and better resolution as compared to regular gel electrophoresis. Using an Octet QKe system, host cell protein content was confirmed using a kit that has greater precision and linear range than available kits based on enzyme-linked immunosorbent assay (ELISA). Imaged capillary isoelectric focusing results highlight the charge heterogeneity of the recombinant HIV-1 Env protein. The binding affinity of the broadly neutralizing antibody, 4E10, to the HIV-1 Env protein was determined by biolayer interferometry. The glycan profile obtained by matrix-assisted laser desorption/ionization (MALDI) spectrometry showed that the recombinant HIV-1 Env protein glycans are distinct from SF162 gp140. These analytical tools can be implemented to ensure that the protein expression and purification conditions do not change the integrity, bioactivity, and therapeutic properties of the vaccine. The methods developed here can be qualified with current good manufacturing practices to facilitate their transfer to a biomanufacturing facility. Our experimental tools were developed to monitor the quality of the HIV-1 Env protein, with the goal of boosting production yields to expedite its success onto clinical trials. Full article
(This article belongs to the Proceedings of Viruses 2020—Novel Concepts in Virology)
8 pages, 1943 KiB  
Article
Using a Multi-Layer Stacked AlGaN/GaN Structure to Improve the Current Spreading Performance of Ultraviolet Light-Emitting Diodes
by Yanli Wang, Peixian Li, Xinyu Zhang, Shengrui Xu, Xiaowei Zhou, Jinxing Wu, Wenkai Yue and Yue Hao
Materials 2020, 13(2), 454; https://doi.org/10.3390/ma13020454 - 17 Jan 2020
Cited by 6 | Viewed by 2612
Abstract
To obtain excellent current spreading performance of ultraviolet light-emitting diodes (UVLEDs), a 60-period stacked Si modulation-doped n-AlGaN/u-GaN structure is proposed to replace the traditional n-AlGaN structure. The high-resolution X-ray diffraction ω-scan rocking curves show that the periodic growth of AlGaN and GaN layers [...] Read more.
To obtain excellent current spreading performance of ultraviolet light-emitting diodes (UVLEDs), a 60-period stacked Si modulation-doped n-AlGaN/u-GaN structure is proposed to replace the traditional n-AlGaN structure. The high-resolution X-ray diffraction ω-scan rocking curves show that the periodic growth of AlGaN and GaN layers plays a positive role in reducing dislocation density. Compared with the conventional UV light-emitting diodes (LEDs), light emission micrographs of devices with a multi-layer stacked n-AlGaN/u-GaN structure reveal higher brightness and a more uniform distribution. In addition, the output power and external quantum efficiency under a 20-mA injection current are increased by 22% and 26.5%, respectively. Experimental and simulation results indicate that a multi-layer stacking structure can alleviate the current crowding effect in four ways: (1) a reduction in dislocation density; (2) replacement of quasi-two-dimensional electron transport with electronic bulk transport to enhance electron mobility; (3) an increase in electron concentration without improving the impurity concentration; and (4) a weakening of the electron scattering effect by reducing the impurity concentration. Full article
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<p>Schematic structures of the (<b>a</b>) conventional Sample A and (<b>b</b>) Sample B with a multi-layer stacking structure.</p>
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<p>High-resolution XRD (HRXRD) ω-scans of the (<b>a</b>) (002) reflection and (<b>b</b>) (102) reflection for both samples.</p>
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<p>Raman spectra of both samples (the inset is a partially enlarged view of the spectra).</p>
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<p>Micrographs of light emission for (<b>a</b>) Sample A and (<b>b</b>) Sample B.</p>
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<p>(<b>a</b>,<b>b</b>) are the calculated partial conduction band energy and electron concentration diagrams of both samples in the AlGaN/GaN structure; (<b>c</b>) is the hole concentration diagram along the x direction of both samples in the first quantum well.</p>
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<p>(<b>a</b>) The measured I–V characteristics of both samples (the inset shows the PL (Photoluminescence) spectrum at room temperature); (<b>b</b>) the optical output power and external quantum efficiency of both samples.</p>
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17 pages, 6345 KiB  
Article
Pedunculate and Sessile Mixed Oak Forest Regeneration Process in Lithuania
by Girmantė Jurkšienė and Virgilijus Baliuckas
Forests 2018, 9(8), 459; https://doi.org/10.3390/f9080459 - 27 Jul 2018
Cited by 2 | Viewed by 2797
Abstract
Pedunculate and sessile oak species are sympatric. These oaks hybridize with one another, and this process influences the development of undergrowth. The purpose of this study was to determine how different oak species influence the forest regeneration process. For this purpose, the forest [...] Read more.
Pedunculate and sessile oak species are sympatric. These oaks hybridize with one another, and this process influences the development of undergrowth. The purpose of this study was to determine how different oak species influence the forest regeneration process. For this purpose, the forest was divided into eight transects of 300 m and 100 m widths, distinguished into temporary plots of 10 m in diameter covering the whole territory of the forest. The distribution of oak undergrowth was calculated by four oak height groups, determining the composition of the first storey, covering of underbrush and herbaceous plant, and forest site. We determined that the spread of oak differed depending on the first storey tree species and underbrush. Grass cover was the biggest influence on the sessile oak. The impurity of sessile oak in oak stands had a positive impact on the development of undergrowth, since the entire undergrowth develops faster than separate components of the undergrowth. Full article
(This article belongs to the Section Forest Ecology and Management)
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Figure 1

Figure 1
<p>Trakas Forest in Alytus district, Veisiejai Forest Enterprise, Seirijai Forest District in Lithuania (54°14′11″ N, 23°45′30″ E, 190 m a.s.l.): (<b>a</b>) circles—locations of the sampling sites of the undergrowth; squares—the location of sampling sites of the first storey of the stand in Trakas Forest; numbers and lines indicate forest blocks; (<b>b</b>) rectangular area shows the location of Trakas Forest in Lithuania and smaller black circles indicate the nearest natural sessile oak stands in Poland.</p>
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<p>Oak undergrowth distribution by height groups and species. Brightest colour indicates an area where there is no oak undergrowth. Different colours indicate differing numbers of oaks in the plots. The plot area is 78.5 m<sup>2</sup>. The largest number of oak undergrowth in the group up to 0.5 m height was: for <span class="html-italic">Q. robur</span>, 26; hybrids, 15; <span class="html-italic">Q. petraea</span>, 17. Respectively, in the group with height 0.5–1.5 m: 13, 13, 3; in the group of 1.5–3.0 m height: 10, 2, 0; and in the group with height over 3.0 m: 10, 3, 4.</p>
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<p>The first stand storey (larger circles) and undergrowth (smaller circles) distribution by species in four study plots of 0.5 ha each. The letters of legend indicate: P—pedunculate oak, H—hybrid oak, S—sessile oak.</p>
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<p>Abundance of oak undergrowth (P—pedunculate oak, H—hybrid oak, S—sessile oak) in different forest sites: Ne—eutrophic soils of normal moisture, Nm—mesoeutrophic soils of normal moisture, Se—eutrophic soils of normal moisture on slopes (&gt;15°), Sm—mesoeutrophic soils of normal moisture on slopes (&gt;15°), Tm—mesoeutrophic gleyic soils of temporary overmoisture, Pm—mesoeutrophic gley soils of permanent overmoisture.</p>
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<p>The abundance of oak undergrowth depending on the first storey prevailing species: P—pedunculate oak, H—hybrid oak, S—sessile oak. In the x array: O—oak sp., Sp—Norway spruce, T—the total oak undergrowth, Pi—silver pine, A—black alder, L—small-lived lime, B—common birch, Ho—common hornbeam.</p>
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<p>The abundance of oak undergrowth depending on the first storey prevailing species: P—pedunculate oak, H—hybrid oak, S—sessile oak. In the x array: O—oak sp., Sp—Norway spruce, T—the total oak undergrowth, Pi—silver pine, A—black alder, L—small-lived lime, B—common birch, Ho—common hornbeam.</p>
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<p>The vector distribution between two axes (RDA): pedunculate oak (<b>top</b>), sessile oak (<b>lower</b>) and their hybrid (<b>middle</b>) in four undergrowth (Ug) height classes (y) and their dependence from site density (D) and covering of underbrush (UbC) and herbaceous plant (HC) (x).</p>
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<p>The vector distribution between two axes (RDA): pedunculate oak (<b>top</b>), sessile oak (<b>lower</b>) and their hybrid (<b>middle</b>) in four undergrowth (Ug) height classes (y) and their dependence from site density (D) and covering of underbrush (UbC) and herbaceous plant (HC) (x).</p>
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<p>The dependence of the relative density (<span class="html-italic">A<sub>V</sub></span>/<span class="html-italic">A<sub>V</sub></span><sub>,0</sub>) on the total oak undergrowth in the formation period: 1—data of observations, 2—Gomperz curve, 3—exponent curve.</p>
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<p>Relative amount of exponential dependence on the age of the pedunculate oak undergrowth compared with other authors’ observation data in different oak stands: 1—exponential curve to Δ<span class="html-italic">t</span> = 3 year, 2—exponential curve to Δ<span class="html-italic">t</span> = 5 year, 3—an exponential curve to Δ<span class="html-italic">t</span> = 7 years. Points—data of observations [<a href="#B6-forests-09-00459" class="html-bibr">6</a>].</p>
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23 pages, 8122 KiB  
Article
Three-D Mineralogical Mapping of the Kovdor Phoscorite-Carbonatite Complex, NW Russia: III. Pyrochlore Supergroup Minerals
by Gregory Yu. Ivanyuk, Nataly G. Konopleva, Victor N. Yakovenchuk, Yakov A. Pakhomovsky, Taras L. Panikorovskii, Andrey O. Kalashnikov, Vladimir N. Bocharov, Ayya A. Bazai, Julia A. Mikhailova and Pavel M. Goryainov
Minerals 2018, 8(7), 277; https://doi.org/10.3390/min8070277 - 28 Jun 2018
Cited by 14 | Viewed by 3773
Abstract
The pyrochlore supergroup minerals (PSM) are typical secondary phases that replace (with zirconolite–laachite) earlier Sc-Nb-rich baddeleyite under the influence of F-bearing hydrothermal solutions, and form individual well-shaped crystals in surrounding carbonatites. Like primary Sc-Nb-rich baddeleyite, the PSM are concentrated in the axial carbonate-rich [...] Read more.
The pyrochlore supergroup minerals (PSM) are typical secondary phases that replace (with zirconolite–laachite) earlier Sc-Nb-rich baddeleyite under the influence of F-bearing hydrothermal solutions, and form individual well-shaped crystals in surrounding carbonatites. Like primary Sc-Nb-rich baddeleyite, the PSM are concentrated in the axial carbonate-rich zone of the phoscorite-carbonatite complex, so their content, grain size and chemical diversity increase from the pipe margins to axis. There are 12 members of the PSM in the phoscorite-carbonatite complex. Fluorine- and oxygen-dominant phases are spread in host silicate rocks and marginal carbonate-poor phoscorite, while hydroxide-dominant PSM occur mainly in the axial carbonate-rich zone of the ore-pipe. Ti-rich PSM (up to oxycalciobetafite) occur in host silicate rocks and calcite carbonatite veins, and Ta-rich phases (up to microlites) are spread in intermediate and axial magnetite-rich phoscorite. In marginal (apatite)-forsterite phoscorite, there are only Ca-dominant PSM, and the rest of the rocks include Ca-, Na- and vacancy-dominant phases. The crystal structures of oxycalciopyrochlore and hydroxynatropyrochlore were refined in the Fd3¯m space group with R1 values of 0.032 and 0.054 respectively. The total difference in scattering parameters of B sites are in agreement with substitution scheme BTi4+ + YOH = BNb5+ + YO2‒. The perspective process flow diagram for rare-metal “anomalous ore” processing includes sulfur-acidic cleaning of baddeleyite concentrate from PSM and zirconolite–laachite impurities followed by deep metal recovery from baddeleyite concentrate and Nb-Ta-Zr-U-Th-rich sulfatic product from its cleaning. Full article
(This article belongs to the Special Issue Arctic Mineral Resources: Science and Technology)
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Graphical abstract

Graphical abstract
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<p>Distributions of Nb in baddeleyite (<b>a</b>), PSM-bearing rocks (<b>b</b>) and average size of PSM grains in a sample (<b>c</b>) within the Kovdor phoscorite-carbonatite complex.</p>
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<p>Typical PSM morphology: (<b>а</b>) irregularly shaped grain of hydroxycalciopyrochlore in forsterite-magnetite phoscorite 987/2.1; (<b>b</b>) drop-like grains of oxycalciopyrochlore in calcite-magnetite-apatite-forsterite phoscorite 987/99.6; (<b>c</b>) cubic crystal of hydroxykenopyrochlore in vein calcite carbonatite 963/61.3; (<b>d</b>) truncated octahedral crystals of hydroxynatropyrochlore in dolomite carbonatite K-017-4; (<b>e</b>) poikilitic metacrystal of oxycalciopyrochlore from calcite-magnetite-forsterite phoscorite 917/318.5; (<b>f</b>) skeletal crystal of oxycalciobetafite-hydroxycalciopyrochlore in magnetite-dolomite-serpentine rock 987/198.0; (<b>g</b>) veinlets of hydroxykenopyrochlore in vein calcite carbonatite 989/57.8; (<b>h</b>) hydroxycalciopyrochlore crystal with baddeleyite relics in calcite-magnetite-apatite-forsterite phoscorite 986/49.6; (<b>i</b>) epitaxial overgrowth of hydroxykenopyrochlore on baddeleyite in calcite-apatite-forsterite phoscorite 1009/186.6. Macrophoto (<b>d</b>) and back-scattered electron (BSE) images of thin polished sections (the rest). Mineral abbreviations are in <a href="#sec2-minerals-08-00277" class="html-sec">Section 2</a>.</p>
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<p>Typical products of hydroxykenopyrochlore low-temperature alteration: <b>a</b>—replacement of baddeleyite and hydroxykenopyrochlore by zirconolite in dolomite carbonatite 964/148.2; <b>b</b>—relic of hydroxykenopyrochlore within pyrite grain in phlogopitite 948/31.4; <b>c</b>—radiated aggregate vallereite around hydroxykenopyrochlore grain in vein calcite carbonatite 943/54.7; <b>d</b>—hydroxykenopyrochlore grain rimmed by strontianite in phoscorite-related calcite carbonatite 974/115.6. BSE-images of polished thin sections. Mineral abbreviations are in <a href="#sec2-minerals-08-00277" class="html-sec">Section 2</a>.</p>
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<p>The Kovdor PSM classification diagram [<a href="#B11-minerals-08-00277" class="html-bibr">11</a>] and relations between Nb, Ta and Ti contents.</p>
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<p>Nb, Ti, Ca and U content vs. fluorine amount in PSM.</p>
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<p>Relations between cations and vacancies in the <span class="html-italic">A</span>-site of the Kovdor PSM (<b>a</b>—all samples, <b>b</b>—kenopyrochlores, <b>c</b>—kenopyrochlores enriched in high-charge cations).</p>
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<p>Changes of mean factor scores reflected PSM composition (see <a href="#minerals-08-00277-t005" class="html-table">Table 5</a>) in natural sequence of the Kovdor rocks.</p>
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<p>Distribution of the PSM basic constituents in the Kovdor phoscorite-carbonatite complex.</p>
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<p>Zonal crystals of pyrochlore: (<b>a</b>) primary zonation of hydroxycalciopyrochlore–fluorcalciopyrochlore crystal from magnetite-forsterite phoscorite 1010/243.7; (<b>b</b>) secondary zonation in grain of oxycalciopyrochlore–U-rich hydroxykenopyrochlore from magnetite-forsterite phoscorite 987/2.1. BSE-images of thin polished sections with indicated fluorine contents. Mineral abbreviations are in <a href="#sec2-minerals-08-00277" class="html-sec">Section 2</a>.</p>
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<p>General view of hydroxynatropyrochlore K-017-4 crystal structure (<b>a</b>) and geometry of the coordination polyhedra in the crystal structures of hydroxynatropyrochlore K-017-4 (<b>b</b>) and oxycalciopyrochlore 917/318.5 (<b>c</b>). <span class="html-italic">A</span>O<sub>8</sub> polyhedra are green, <span class="html-italic">B</span>O<sub>6</sub> octahedra are blue, oxygen sites are represented by red circles, <span class="html-italic">Y</span>1 sites are shown as pink circles.</p>
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<p>Initial (<b>a</b>) and re-calculated (<b>b</b>) Raman spectra of pyrochlore supergroup minerals. HNP is hydroxynatropyrochlore, HKP is hydroxykenopyrochlore.</p>
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<p>PSM composition vs. position of typical absorption bands in the corresponding Raman spectra.</p>
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<p>Particles of baddeleyite within exsolution inclusions of spinel and ilmenite in magnetite from calcite-magnetite-apatite phoscorite 956/138.9 (<b>a</b>) and magnetite-forsterite phoscorite 987/2.1 (<b>b</b>). Mineral abbreviations are in <a href="#sec2-minerals-08-00277" class="html-sec">Section 2</a>.</p>
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<p>Process flow diagrams of the PSM-bearing baddeleyite concentrate acidic cleaning (<b>a</b>, after [<a href="#B49-minerals-08-00277" class="html-bibr">49</a>]) and deep processing (<b>b</b>, after [<a href="#B50-minerals-08-00277" class="html-bibr">50</a>,<a href="#B51-minerals-08-00277" class="html-bibr">51</a>]). Gray rectangles show final products.</p>
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