Location, colors and mineral composition in the fine fractions in sandstones from Hatira crater, Ramon crater, and Manara cliff in Israel.
\r\n\tDiagnosis and management of complications while on ECMO therapy and weaning to recovery or advanced therapies will be also discussed.
\r\n\r\n\tChapters focusing on specific patient populations, such as cardiogenic shock, thoracic organ transplantation, trauma, and neonates, Covid-19 syndrome, will provide insight into the particular challenges in dealing with the unusual problems of these very diverse groups.
\r\n\r\n\tThe goal of this book is to provide, thanks to the thorough contributions by known experts in the field, a framework for successful program development. Hopefully, this text will also inspire others to further advance this delicate field.
",isbn:"978-1-80356-549-1",printIsbn:"978-1-80356-548-4",pdfIsbn:"978-1-80356-550-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"254c18981115aeda50bdf71829902141",bookSignature:"Dr. Antonio Loforte",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11718.jpg",keywords:"Heart Failure, Cardiogenic Shock, Respiratory Failure, Circulatory Failure, End-Organ Dysfunction, VA-ECMO, VV ECMO, Central ECMO, ECMO Running, Weaning off ECMO, Adverse Events While on ECMO, Survival on ECMO",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 10th 2022",dateEndSecondStepPublish:"April 7th 2022",dateEndThirdStepPublish:"June 6th 2022",dateEndFourthStepPublish:"August 25th 2022",dateEndFifthStepPublish:"October 24th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Loforte is a dedicated and pioneering researcher in the surgical treatment of advanced heart failure in terms of LVAD, BVAD, ECLS, and TAH adoption in different clinical scenarios. He is a member of several professional organizations including the prestigious STS, ISHLT, ASAIO, EACTS, RHICS, SICCH, SITO, ELSO, and ESOT among others. His bibliography lists over 150 peer-reviewed original articles, 250 abstracts (communications) for international meetings, 20 book chapters, and 8 manuals.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"42172",title:"Dr.",name:"Antonio",middleName:null,surname:"Loforte",slug:"antonio-loforte",fullName:"Antonio Loforte",profilePictureURL:"https://mts.intechopen.com/storage/users/42172/images/system/42172.jpg",biography:"Dr. Loforte is currently staff surgeon and chair of the Mechanical Circulatory Support (MCS) program at the Department of Cardiothoracic, Transplantation and Vascular Surgery, S. Orsola Hospital, ALMA Mater Studiorum University of Bologna, IRCCS Bologna, Italy. 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The sandstones are quartz (SiO2) arenite with rounded quartz grains, clay minerals and siltstones. Lower Chemical weathering of the Pan-African continental basement favored silicate weathering, particularly a warm and humid climate, low relief and low sedimentation rates which prevailed over large tracts of Gondwana in the aftermath of the Pan-African orogeny [4]. Cretaceous sandstone originates from Paleozoic sandstones, the first-cycle quartz-rich sandstones [5]. The stratigraphic cycles showed progradational – retrogradational trends due to small global sea-level rises which inundated the continent for short periods and fossils were found [6]. In Lebanon similar sandstones were deposited during the Lower Cretaceous [7]. The composition of the sandstones was 85–95% quartz indicating well-sorted sandstone. Sedimentological observations suggest that the Chouf Formation deposited in fluvial, coastal plain and deltaic environments. The origin of the sandstone is from recycling of Paleozoic sandstones. Sandstones of the Lower Cretaceous were deposited and covered by sediments that were deposited after the Thetis Ocean covered the area during the Upper Cretaceous, hence, hard carbonate stones, limestones, dolomites and marls precipitated, overlying the sandstones. At the end of the Mesozoic era, closure of the Thetis Sea yielded formation of the Syrian arc with monoclines of the Hatira and Ramon areas. After regression of the Thetis Sea during the Oligocene, an erosion surface truncated the hard carbonate rocks of the fold’s crest and exposed the underlying friable Lower Cretaceous sandstone. For crater (Makhtesh) Hatira, such an erosion base level formed locally and for a limited period in the Early Miocene. The opening of the Ramon crater started in the Early Pliocene, when the Syrian Arc Fold Belt was uplifted and arched and the Dead Sea Rift was established as a deep intercontinental erosion base in the east [8]. In the northern part of Israel, the Lower Cretaceous sandstones were exposed close to the Dead Sea transform fault and uplift of the Manara cliff and formation of Hula valley.
Composition and morphology of the nano-crystals that coat quartz grain reflect the environmental conditions in which they were formed as primary or secondary forms [9].
In this paper, we present Transmission Electron Microscopic (TEM) observation of the nano-sized minerals from Lower Cretaceous sandstones exposed in the Hatira and Ramon craters in southern Israel, and in the Manara cliff in the northern part of Israel (Figure 1).
a. Geomorphological map of Israel. In the northern part is Manara cliff and in the southern part Hatira and Ramon craters. b. Sandstones exposed in the Hatira crater and a sample of red and yellow layers. c. Sandstones exposed in the Ramon crater and a sample with dark violet, red and yellow-red thin layer. d. Sandstones in the Manara cliff.
The main motivation of this research is to identify nano-crystals in sandstone that cause the variability in their colors. By using TEM detrital or authigenic phases can be identified.
The samples that were collected were separated according to their colors: dark violet, violet, dark red, red and yellow (Table 1). Sand stone were put for few minutes into an ultrasonic bath, then the fine fraction was separated from the quartz grains and freeze-dried. Each sample was suspended in distilled water and placed on Cu supported holey carbon film and dried. Nano-sized (5–200 nm) particles were checked with Transmission Electron Microscopy (TEM) using a JEOL JEM-2100F analytical TEM operated at 200 kV, equipped with a JED-2300 T Energy Dispersive Spectrometer (EDS) for microprobe elemental analyses. All chemical analyses were obtained by point analyses with a beam width of 1 nm and are presented as atomic ratios. JEOL Analytical Station software, based on the Cliff-Lorimer ratio technique, with an accuracy of ~5%, was used for the calculations. The CuKa line was used to calibrate the spectrometer. Energy-filtered TEM (EFTEM) experiments were performed using a Gatan image filter. The titanium L-edge (456 eV), silicon L-edge (99 eV) and iron L-edge (708 eV) were used for elemental mapping using the three-window method.
No. | Sample | Color | Location | Minerals identified with HRTEM |
---|---|---|---|---|
1 | GNH4 YR | Yellow-red | Hatira crater, east | Kaolinite, illite, hematite, goethite |
2 | GNH4 DR | Dark red | Hatira crater, east | Quartz, clays, jarosite, anatase, goethite, calcite, ilmenite |
3 | GNH6 R | Red | Hatira crater, east | Kaolinite, ilmenite, hematite, quartz |
4 | GNR1 V | Violet | Ramon crater northern cliff highway 40 | Anatase, kaolinite illite, smectite, goethite, magnetite, maghemite |
5 | GNR1 Y | Yellow | Ramon crater northern cliff highway 40 | Hematite, illite, rutile, quartz |
6 | GNR2 DV | Dark violet | Ramon crater northern cliff highway 40 | Hematite, goethite, kaolinite alunite, apatite |
7 | GNR2 R | Red | Ramon crater northern cliff highway 40 | Goethite, hematite, anatase, illite, kaolinite |
8 | GNR2 VR | Violet, red | Ramon crater northern cliff highway 40 | Hematite, goethite, kaolinite anatase |
9 | GNR3 R | Red | Ramon crater northern cliff highway 40 | Goethite, hematite, kaolinite, illite |
10 | GNR5 R | Red | Ramon crater northern cliff highway 40 | Goethite hematite, anatase, kaolinite, illite, smectite |
11 | GNKS1 | Red | Manara cliff near Kiriat Shmona | Kaolinite, ilmenite, apatite, goethite, quartz |
Location, colors and mineral composition in the fine fractions in sandstones from Hatira crater, Ramon crater, and Manara cliff in Israel.
Crystalline phases were identified, using Selected Area Electron Diffraction (SAED) in the TEM. With this method, a very high-energy electron beam (200 kV) transmits through the sample and the d-values obtained enabled their identification. The accuracy of the d-values determination was better than 0.005 nm. The smallest area of SAED was 100 nm. If a good lattice image was obtained in very small particles by High Resolution Transmission Electron microscopy, the use of Fast Fourier Transformation (FFT) enabled the identification of the minerals, using the program Digital Micrograph (Gatan).
Samples from the Hatira crater were collected at the eastern side of the crater. The colors of the sandstones vary, with thin layers of red sandstone or dark red close to clay layers. Usually the yellow layers are thicker.
In the sample: yellow-red (GNH4 YR), from the Hatira crater (Figure 2), a cluster of goethite (FeOOH) with clay minerals, mainly kaolinite (Al4Si4O20(OH)8), was observed, and a cluster of hematite (Fe2O3) shows the previous morphology of goethite, indicating that hematite was formed by recrystallization of goethite preserving the acicular morphology of goethite. Crystal size of hematite is around 15 nm. Small crystals (25-50 nm) with Ti impurity might reflect ilmenite (FeTiO3) disintegration. The dominance of goethite crystals contributes to the yellow color and hematite contributes to the red color. The recrystallization of goethite into hematite might have happened due to thermal transformation, as the sandstones were covered by younger layers.
GNH4 YR images of yellow-red sandstone from the Hatira crater with electron diffractions. Minerals observed were: a. cluster of clay minerals (illite (K0.65Al2.0[Al0.65Si3.35O10](OH)2) and kaolinite, with goethite; electron diffractions of goethite 0.42–0.43 nm in the inner circle. b. Cluster of hematite; electron diffractions of hematite 0.36–0.37 0.268–0.269 nm. c. Tiny crystal of hematite high resolution of hematite formed by recrystallization of goethite preserving the initial phase of goethite. Small crystals had Ti/Fe ratios 0.07 and 0.45. Electron diffractions were 0.36 and 0.27 nm.
Sample GNH4 DR (Figure 3) had a dark red color and the minerals identified were clay minerals, small crystals of calcite (CaCO3), jarosite (KFe3(SO4)2(OH)6), goethite, ilmenite, and anatase (TiO2). The image obtained by TEM shows clay minerals with clusters of anatase and goethite. Jarosite appears with euhedral or sub-hedral morphology, indicating that it was formed in the sandstone. The crystal size of jarosite is 100-200 nm. Ilmenite crystal had Fe/Ti 0.85 and the crystal’s size is ≈200 nm.
GNH4 DR dark red sandstone from the Hatira crater. Minerals observed were clay minerals, jarosite goethite, anatase and ilmenite. a. Jarosite with point analyses (%atom) in the lower left side yielded Al-27.28, S-46.69 K-13.91 and Fe-12.12; in the upper part Al-24.38, S-52.13, K-9.32 and Fe-14.17. Electron diffractions at the left side were 0.59 nm, 0.57 nm and 0.28 nm at the central part the electron diffractions were 0.506 nm, 0.3108 nm and 0.3012 nm. b. Minerals observed were clay minerals, jarosite, goethite, anatase with atomic ratio Fe/Ti 0.85. Electron diffractions at the upper part of the images yielded for goethite 0.42 nm and for anatase 0.35. c. Minerals observed were quartz, and ilmenite with electron diffraction of 0.36 nm.
Sample GNH6 R (Figure 4) was collected from a thin red layer and vein within a clay layer in the sandstone. Ilmenite was found as a cluster of small particles surrounded by clay minerals. The ilmenite point analysis had Fe/Ti 0.38, indicating that a larger crystal disintegrated and was preserved within the clay layer. EFTEM RGB color shows disintegration of the ilmenite mineral. Usually ilmenite is resistant to weathering processes and it probably arrived at the area along with the quartz grains. At the lower part of the image hematite formed a layer, causing the red color of the sandstone. Recrystalliztion of ilmenite into hematite was found also in sands along the Mediterranean coast. The precursor and the recrystallized tiny hematite crystals remain close to each other since they are all kept within clay minerals [10].
GNH6 R red sandstone from the Hatira crater: a. cluster of ilmenite with Fe/Ti 0.38 in a kaolinite layer covering hematite layer. The upper gray layer is part of a quartz grain. b. Composition of phases observed on the left side. c. High resolution image of hematite with FFT.
Sandstones are exposed at the northern cliff of the Ramon crater close to highway 40. Volcanic eruption occurred in the area during the Lower Cretaceous, forming basanite flows and paleosol between the volcanic flows [11]. The samples presented were collected above the basanitic flows. Lower cretaceous sandstones in the Ramon crater have various colors: dark violet, violet, dark red, red and yellow (Figure 1c).
The violet sample GNR1V (Figure 5) had kaolinite clusters, euhedral crystals of anatase (50-100 nm), magnetite (Fe3O4) and maghemite (Fe3O4) that was probably formed by magnetite oxidation. Kaolinite crystals had euhedral morphology, indicating that they crystallized in the area. Similar euhedral morphology of some of the anatase and rutile (TiO2) crystals indicates that they might also have been formed in the sandstone by recrystallization of other phases. Another option is that the euhedral morphology of the Ti-oxides results from their resistance to weathering. In sample GNR1 V, anatase crystals reached a size of 90 nm and Fe/Ti atomic ratios were 0.04–0.26.
GNR1 V violet sandstone from Ramon crater. Minerals observed: a, b, c: Anatase with electron diffraction at 0.36 nm and kaolinite. d: Magnetite (Fe3O4) and maghemite (Fe3O4) on a quartz (SiO2) grain, kaolinite at the right side.
Sample GNR1Y (Figure 6) presents additional phases of a yellow sandstone. Quartz grain was observed surrounded by a cluster of illite (K0.65Al2.0[Al0.65Si3.35O10](OH)2), hematite and a euhedral rutile crystal (250 nm) with Fe/Ti 0.03 atomic ratio. Hematite tiny crystals <100 nm were also observed close to the quartz grain and on the clays.
GNR1 Y. image of yellow sandstone from Ramon crater with electron diffractions. The minerals observed were rutile, hematite illite and kaolinite. Quartz (SiO2) grain is on the right side.
In sample GNR2 DV dark violet sandstone from the Ramon crater (Figure 7), the main clay mineral is kaolinite forming clusters with hematite and alunite (KAl3(SO4)2(OH)6). The largest crystal size of hematite is around 300 nm, contributing to the violet color of the sandstone. Point analysis in % atom of alunite yielded: Al 6.00–6.37, S 2.04–2.34, K 0.29–0.32 and Fe 0.01. Alunite was probably precipitated from acid rain or evaporation of sea water that might have entered the area during the Lower Cretaceous. Tiny crystals of goethite formed clusters with clays.
GNR2 DV image of dark violet sandstone from Ramon crater. Minerals observed were: a. kaolinite and hematite; b. kaolinite, hematite with electron diffraction at 0.37 nm and at the lower part alunite with electron diffraction at 0.5 nm; c. small crystal of Ti-oxide, cluster of goethite with electron diffraction 0.42 nm and alunite crystal on the right side.
Sample GNR2 R from red sandstone in the Ramon crater (Figure 8) had clay minerals, illite and kaolinite with anatase, goethite and hematite. Anatase (~50 nm) had euhedral morphology, indicating that it might have crystallized in the sandstone. The goethite crystals had acicular morphology (~150 nm); some of the goethite partially recrystallized into hematite preserving the initial acicular goethite morphology. Tiny crystals of hematite were also observed on goethite crystals. A high resolution image was taken from a cluster of hematite preserving outer goethite morphology.
GNR2 R red sandstone from Ramon crater. Minerals observed: a. goethite and hematite on illite and kaolinite; b. hematite and anatase; c. goethite and tiny crystal of hematite; d. high resolution of goethite and hematite.
Sample GNR2 VR (Figure 9) is from violet-red sandstone from the Ramon crater. The minerals identified were kaolinite, goethite, hematite and anatase. High resolution of the sample yielded morphology of euhedral acicular crystals that were the initial stage of goethite, and the inner morphology was of small crystals of hematite. Goethite has been transformed into hematite preserving the acicular morphology. The cluster of hematite includes the clay mineral, kaolinite. Euhedral anatase crystal (~60 nm) was observed close to clay minerals with impurity of Fe/Ti 0.027 atomic ratio.
GNR2 VR violet-red sandstone from Ramon crater. Minerals observed: a. a cluster of hematite with electron diffraction 0.367–0.374 nm; b. hematite electron diffraction 0.367–0.377 nm and goethite electron diffraction 0.42 nm; c. high resolution of hematite preserving initial crystals of goethite electron diffractions 0.365–0.375 nm; d. anatase (TiO2) with iron impurity and clays.
Sample GNR3 R (Figure 10) red sandstone from the Ramon crater had clusters of goethite with kaolinite, illite and smectite. Small crystals (<50 nm) that were observed on the clays had impurity of Ti with the atomic ratio of Ti/Fe 0.027. These crystals might result from disintegration of ilmenite.
GNR3 R red sandstone from Ramon crater: a. Kaolinite, smectite and illite with electron diffractions of 0.45nm and goethite. b. Lay minerals and goethite electron diffraction 0.41 nm.
Sample GNR5 R (Figure 11) red sandstone from the Ramon crater had clay minerals, goethite crystals and anatase (TiO2). The size of the goethite crystals reached 800 nm.The size of euhedral anatase crystal was 200 nm and impurity of iron was Fe/Ti 0.04 atomic ratio. From a dark field image obtained, tiny crystals of anatase are located in the upper part of the image.
GNR5 R red sandstone from Ramon crater. a. Minerals observed with electron diffraction were: anatase and goethite surrounded by clays. b. Dark field image showing larger anatase crystal and small crystals of anatase in the area.
Sandstones of Lower Cretaceous were exposed in the northern part of Israel due to uplift along the Dead Sea transform fault. The main phases identified in the fine fraction were clay minerals, mainly kaolinite, ilmenite and hematite (Figure 12). The size of ilmenite crystals varies between 1000 nm and 50 nm. Most of the ilmenite crystals disintegrate into small crystals and Fe/Ti ratios decrease. The tiny ilmenite crystals are preserved in clays covering a quartz grain. Hematite tiny crystals that result from disintegration of ilmenite and recrystallize into hematite are preserved within clay minerals.
GNKS1 sandstones exposed in Manara cliff. Minerals observed: a. clays and ilmenite; b. ilmenite electron diffraction 0.255 nm; c. cluster of hematite with electron diffraction of 0.37–0.38 nm and clays over a small quartz (SiO2) grain on the upper left side quartz grain and clays.
The Lower Cretaceous sandstones are mainly quartz arenite with rounded quartz grains that were separated from the fine fraction. These sandstones originated from Paleozoic sandstones that were the first-cycle quartz-rich sandstones and resulted from widespread chemical weathering of the Pan-African continental basement [4]. The composition of the sandstones changes from the arkose at the lower layers to sub-arkose and the younger layers are mainly mature quartz arenite [12, 13]. The fine fraction includes minerals that were formed by disintegration of the initial phases or result from dust storms.
Clay minerals usually cover the quartz grains. In the samples studied the dominant clay mineral is mainly kaolinite, small amounts of illite and some smectite. Kaolinite is usually crystallized at permeable bedrock in warm, moist regions forming as a residual weathering product. Illite might result from weathering of muscovite or K-feldspar [14], and smectite was formed from weathering of other minerals like biotite or amphibole that were in the Paleozoic sandstones from the first cycle. The crystal size of kaolinite is around 200-500 nm. Quartz-arenite stones from the Lower Miocene Moghra in Egypt were studied showing similar results with smectite, illite and kaolinite as clay minerals and hematite as the iron oxide [15].
Iron oxides were goethite, hematite, and some magnetite and maghemite. The iron oxides are responsible for the colors of the sandstones. Similar results were found in sands on the Atlantic coastal plain as iron oxides coat sand grains [16]. Goethite is usually yellow but impurities might change its color. Crystal’s size might also affect the color. Goethite crystal sizes of 300 nm–1000 nm cause a yellow color; with smaller crystals it becomes darker. Hematite is usually yellow-red but larger crystals cause the appearance of a purple color. Formation of the iron oxides depends on the environment in which they were crystalized. Goethite usually crystallizes at fast oxidation at lower pH [17]. Hematite results from recrystallization of goethite close to a clay layer that adsorbs the OH of goethite, and hematite crystallizes (Figure 2a). Hematite and ilmenite (FeTiO3) form a solid solution. Disintegration of ilmenite formed hematite crystals with Ti impurity and the leftover of the ilmenite was enriched with Ti forming Fe/Ti < 1 ratios.
Rutile (TiO2) and anatase (TiO2) had euhedral morphology, indicating that they might have crystallized in the area or, due to their hardness, they preserved their initial morphology. Rutile was found in the Paleozoic sandstone along with tourmaline [18]. Fe impurity in Ti-oxides might indicate that they were formed by in the area as ilmenite disintegrated and they were preserved within the surrounding clay minerals. It is also possible that rutile and anatase recrystallized from biotite from the magmatic and metamorphic rocks from the basement [19].
Jarosite (KFe3(SO4)2(OH)6) and alunite (KAl3(SO4)2(OH)6) were observed in dark violet or dark red sandstones. Jarosite was found in younger marl layers of Taqiya formation in the southern part of Israel, as a result of alteration of pyrite [20]. It was also found in Jurassic sandstone in the Ramon crater, and two possible formation processes were suggested: acid rain or from transgression, for a short period, of the sea [21]. Usually jarosite and alunite form a solid solution and they crystalize in saline lakes or acid sulphate soils [22]. In Utah (USA) they form cement in Jurassic sandstones and they precipitated in marginal marine to coastal dune [23]. Jarosite usually formed at low pH conditions and it requires an arid environment to prevent its decomposition into ferric oxyhydroxides [24]. It is possible that both jarosite and alunite were crystallized due to short transgression episodes of the Thetis Sea.
Quartz arenite sandstones were formed during Lower Cretaceous in the southern and northern parts of Israel. The fine fraction observed by TEM includes clay minerals mainly kaolinite and small amounts of illite and smectite. Additional minerals that contribute to the colors of the sandstones are iron oxides, goethite and hematite. The initial phase of iron oxides that coat quartz grains or form clusters was goethite, and hematite crystals preserved the initial acicular goethite structure. Ilmenite preserved within clay minerals disintegrate into small crystals enriched with iron. The tiny euhedral crystals of Ti oxides were probably formed in the sand. Jarosite and alunite observed in Ramon and Hatira craters were crystallized in the sandstones due to short transgression of the Thetis Sea.
The project was sponsored by Ilse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva, Israel 8410501.
The Republic of South Africa (RSA) is known to be among one of the world’s most active mining countries. RSA hosts several deposits such as gold deposits in the Witwatersrand basin, diamond deposits in Kimberly, Platinum group elements (PGE) in the Bushveld Complex and Manganese deposits in the Griqualand West Basin, all to which, to some extent they control the economy of the country [1]. The Namaqua- Natal Metamorphic Province, particularly the Namaqua Sector has proven to be the remarkable mineralised sector in the country hosting Copperton deposit, which according to [2], and [3] is one of the world’s giant Volcanic Hosted Massive Sulphide (VHMS) deposit.
The Namaqua-Natal Metamorphic Province (NNMP) is a tectonostratigraphic province that stretches 1400 km across South Africa, it extensively outcrops in the Northern Cape Province and Kwa-Zulu Natal Province and referred as Namaqua and Natal Sectors respectively and in Namibia. NNMP embrace igneous and metamorphic rocks formed or metamorphosed during the Namaqua Orogeny at 1200 Ma–1000 Ma. It is 400 km wide and has borders with the Kaapvaal Craton to the north and Pan-African (Gariep and Saldania) belts in the west and south [4, 5].
The Namaqua Sector of the Namaqua-Natal Province is subdivided into a number of distinct, discontinuity-bounded domains: Richtersveld Subprovince, Bushmanland Terrane, Gordonia Terrane, and Kaaien Terrane (Figure 1; [6]). The Location of the study area is in western degree of the 2922 Prieska sheet, Northern Cape Province, South Africa (Figure 1).
Map of Southern Africa showing Pan-African orogenic belts, NNP, Kheis Province and Kaapvaal craton [
The small portion of Kaapvaal Craton is part of the study area (Figure 1). The preserved basin on the Kaapvaal Craton, which is the part of the study area of this research, is Griqualand-West basin. The westernmost of Griqualand West basin exposures at the eastern edge of the Kheis Belt, thrust and fold belt that post-dates younger Olifantshoek red beds. In its extreme, south the Griqualand-West strata are truncated by later dextral shearing on the Brakbosch and Brulpan faults [6].
Geochemical data combined with mineralogical and other additional data sets such as geologic maps, mineral distribution, geophysical methods, among others, provides a foundation for classifying and evaluating mineral resource endowment and natural hazards. A mineral resource produces diagnostic textural, geologic, geophysical, and geochemical signatures when exposed at or near the surface of the earth. Geochemical exploration is based on outlining such dispersion halos and in the present study that will be done by chemical analyses of stream-drainage sediments.
There is different between regional and detailed surveys in terms objective, size of area being surveyed, sampling density, type and of material sampled. Ginsburg [7] recognised three scales of geochemical mapping and surveys depending on purpose and objective, namely, reconnaissance, prospecting and detailed. Regional survey can be conveniently discussed based on the number of stream sediment samples taken per square kilometres [8].
Regional geochemical mapping has been part of the core mapping function of the Council for Geoscience (CGS) since the 1970s. The Regional geochemical mapping program follow a systematic approach focussed on providing high quality- and high density datasets that will contribute to resolving issues relevant to modern South African geological society, namely, exploration, geological mapping, groundwater, environmental studies, and geological modelling. The principal objective of this geochemical orientation survey is to define the patterns of primary and secondary dispersion occurring in the study area particularly those of economically and environmentally interesting elements.
The stream sediments composition of the research are is poorly understood. Mobility of the different elements varies considerably because of factors such as adsorption and Eh-pH conditions. Stream sediments programs worldwide had discovered numerous deposits.
The geochemical patterns obtained from this study will enable to link elements deficiencies and abundances with the underlying geology, structures and known mineral occurrences and mines. This will assist in tracing the source of anomalies encountered on stream sediments and delineate targets for follow-up studies within the Orange River catchment area.
The primary aim of this study is to map the VMS mineralisation potential of the Prieska area using the stream sediment data, determine geochemistry of stream sediments within the Orange River catchment area. This will enable the recognition of anomalies within the catchment area and trace their sources.
The following specific objectives need to be met:
To determine the solid geochemistry of the sediments from Orange River catchment
To determine heavy metals content of the sediments
Locate the source of anomalies and delineate targets for follow-up studies.
Geochemical and mineralogical anomalies of the sediments in the Orange River can be determined
Metal content of stream Orange River sediments was introduced in solution
Sources of resulted anomalies within the Orange River catchment can be traced.
Large areas may be successfully explored using stream sediments geochemistry for indications of individual mineral deposits, groups of occurrences, or favourable geological environments. Sampling density ranges from one sample per 1 km2 to one per 25 km2 depending upon the type of target and drainage characteristics, and inherent in the reconnaissance concept is the need for more detailed sampling to determine the significance of regional anomalies [9, 10]. The government agencies, Council for Geological Survey and mining companies are mostly responsible to carry out Regional stream sediments surveys. Successful stream sediments surveys conducted around the globe.
The Geological Survey of Zambia in Africa employed regional and provincial scale geochemical mapping in systematic geological mapping. Analyses were for 20 elements by semi quantitative XRF. The Institute of Mining Research at the University of Zimbabwe (formerly known as Rhodesia) had been active in regional geochemical research projects since 1976. Some of the studies done by the institute include a regional stream sediment reconnaissance of 1350 km2 of the Sabi Tribal Trust Land at a density of one sample per km2 [11], and a survey of 1664 km2 near West Nicholson, Zimbabwe, at same density [12] employing multi-element in both cases. In southern Africa, most mining companies devote a greater effort to regional soil sampling than to drainage reconnaissance and it had been estimated that more than 95% of samples collected by the major companies in 1973 were taken from soil grids [13].
In Australia, during 1976, there was a low level of activity as only 4250 stream sediments were collected; the number was expected to decline in 1977. Nevertheless, in the more favourable humid zones most mineral exploration companies make fixed use of regional stream sediment sampling since stream sediments are of limited use in the more arid regions because of low density of drainage and dilution by the wind-blown material. Two size fractions approach may be employed in arid regions, minus-120 mesh and minus-4-plus −16 mesh with coarser fraction containing gossan fragments and multiple grains cemented by metal-rich iron hydroxides [10].
In southern British Columbia portion and Yukon during 1976, Stream sediments sampling took place over an area of 75,000 km2 (Cameroon, 1976). According to Meyer et al. [10], Smee and Ballantyne [14] reported that the British Columbia portion of the program covered 46,800 km2 at a mean density of one sample per 13 km2 and in the Yukon 2200 stations were sampled over an area of 28,490 km2, giving the same degree of coverage. More than 90% of stream sediment activities of the Geological Survey of Canada and Federal-Provincial Uranium Reconnaissance Program that commenced in 1975 are related. Rose and Keith [15] concluded that stream sediments were preferable to water for reconnaissance drainage surveys for uranium for eastern Pennsylvania.
Several techniques including geological mapping and stream sediments geochemistry were used to investigate stream sediments geochemical patterns of the Orange River catchment prospecting area in order to accomplish the goals and objectives set out for this study. A descriptive methodology is summarised in the below flow chart (Figure 2). The steps followed in order to achieve the objectives of this study are desktop study, reconnaissance survey, fieldwork, laboratory work, data analysis and interpretation, discussion, conclusions and recommendations.
Flow chart indicating methods and procedures applied during the study.
In order to acquire first-hand information about the study area. Prior to field visit, the information from previous work on geology, nature of mineralisation and previous exploration conducted in the Orange River catchment prospect is studied. Information is sources from Books, unpublished technical reports, geological reports, topographical maps, journals and internet sources.
A reconnaissance survey was undertaken prior to detailed or actual fieldwork. During this, a snap survey of geology, vegetation, and accessibility of the study area was undertaken. The aim is to locate the ground, target areas indicated by outcrops of different lithologies. The general attitudes of lithologies at the prospects, rock outcrops, and quantity of samples and duration of fieldwork were established. Additionally, a thorough study of topography, vegetation, pedology, drainage patterns and characteristics of rocks was also to gather as much information as possible in the study area. Stream distribution was also assessed which drain into the Orange River catchment prospect.
Field observations were transferred to a base map before being digitised using ArcGIS 10.3.1. The observations were transferred to a field base map; using diverse colours to discriminate the streams distribution mapped in the area. The spatial extent of each lithology and lithology contacts as well as stream distribution were trace on the map. Field notes includes describing the coordinates and nature of contact with other rock types and soil colour where there is limited outcrops.
The sample analysis was conducted by the Council for Geoscience (CGS) laboratory in Pretoria. Sieve shaker, drying oven, atomic absorption spectrometry (Perkin Elmer Analyst 400, AAS), PANanalytical-Axios XRF were used for sample preparation and analysis.
This section describes the methods used to prepare stream sediments samples collected from the Orange River catchment prospect for laboratory analysis.
Samples are oven dried at 105–110 °C. Once completely dry, samples were first sieved through a 2 mm sieve to remove gravels and organic materials and subsequently sieved through a − 125 μm fraction size and milled to 85% -75 μm. The milled samples were placed in labelled sample bags ready for analysis.
The prime requirement for mineral exploration survey is the availability of analytical procedures capable of high precision, low detection limit and acceptable accuracy.
The PANanalytical-Axios XRF was used for geochemical analysis of stream sediments. The milled samples roasted at 1000 °C for at least three hours in order to oxidise Fe2+ and S and to determine loss of ignition (LOI). Glass disks for XRF analysis were prepared by fusing 1 g sample and 8 g of flux (35% LiBO2 and 64.71% Li2B4O7) at 1050 °C for major element analysis. Major element oxides (SiO2, TiO2, Al2O3, Fe2O3t, MnO, MgO, CaO, Na2O, K2O, P2O5 and Cr2O3) and trace element (Ni, Cu, Co, As, Zn, Pb, Cr, Ba, Sc, Sr., V, Th, U, Y, Zr) were analysed.
Trace element analysis was achieved by mixing 12 g milled sample and a 3 g Hoechst wax and then pressing into a powder briquette by a hydraulic press with the applied pressure at 25 ton. The glass disks and wax pellets were analysed by PANalytical-Axios XRF. XRF has the advantage of being non-destructive, multi-elemental, fast and cost effective compared to other competitive techniques such as Atomic Absorption Spectrometry (ASS) or Inductively Coupled Plasma Spectrometry (ICP OES).
X-rays are produced by irradiating a sample with high energy photons produced by primary X-ray tube. When a high energy primary X-ray collides with an atom, an electron can be ejected from a low energy level creating an electron vacancy. When an electron from a higher energy level fills the vacancy, a secondary X-ray is created characteristic of that element. XRF analysis devices can be largely categorised into wavelength-dispersive X-ray spectrometry (WDX) and energy-dispersive X-ray spectrometry (EDX). WDX disperses the fluorescent X-ray generated in the sample using dispersion crystal and measures it using a goniometer, resulting in a large size. The detector in EDX on the other hand, has a superior energy resolution and requires no dispersion system, which enable downsizing of the device. Interaction of X-rays with sample creates secondary diffracted beams of X-rays related to inter-planner spacing in the crystalline powder according Bragg’s Law:
Where: n is an integer, λ is the wavelength of X-rays; d is the inter-planar spacing generating the diffraction and is the
The XRF was calibrated by identification of optimum conditions of several variable factors for each element, like identifying correct elemental peak and background, pulse height, collimator mask, counting time, dead time, followed by matrix and inter-element interference corrections. This was achieved by repeated analysis of certified reference material and correcting the variables to yield elemental concentration close to known values. This included 12/76 (amphibolite standard).
The weighted inverse distance interpolation (IDW) method was used to convert point XRF data into continuous geochemical maps using ArcGIS, the IDW parameters used were: power = 2, maximum neighbours = 15, minimum neighbours = 10, cell Size = Maximum of Inputs.
It is vitally important that an analysis is precise but the accuracy is not generally so crucial, although some indication of accuracy is needed for most purposes in mineral exploration [16]. Quality assurance program should aim to assess the quality and accuracy at all stages of measurement process, from site selection and sampling through sample handling, preparation and analysis. Subsequently, a quality control/quality assurance See Table 1 for the results of the reference material and lower limit of detection for each element. The glass disk R422 was analysed firstly with the calibration standards and then every 12 hours during analysis of the sample. The three sediment reference material GSD-9, GSD-11 and GSD-14 were repeatedly analysed every 30 samples to evaluate the precision of the analysis, Table 1 summaries the results of the reference material and each lower detection limit of each element.
GSD-9 | GSD-11 | GSD-14 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Oxide (wt %) | Lower level of determination | N = 391 | N = 525 | N = 435 | |||||||||
Element (ppm) | Certified | Average | Standard | %RMS | Certified | Average | Standard | %RMS | Certified | Average | Standard | %RMS | |
SiO2 | 0.01 | 64.89 | 68.20 | 3.20 | 4.70 | 76.25 | 77.29 | 3.17 | 4.10 | 57.25 | 53.43 | 2.51 | 4.69 |
TiO2 | 0.01 | 0.92 | 0.94 | 0.01 | 1.34 | 0.35 | 0.35 | 0.00 | 1.02 | 2.40 | 2.29 | 0.04 | 1.84 |
Al2O3 | 0.01 | 10.58 | 11.30 | 0.72 | 6.40 | 10.37 | 10.41 | 0.56 | 5.39 | 13.39 | 11.75 | 0.77 | 6.56 |
Fe2O3 | 0.01 | 4.86 | 4.82 | 0.13 | 2.63 | 4.39 | 4.15 | 0.08 | 1.96 | 9.50 | 9.75 | 0.17 | 1.77 |
MnO | 0.00 | 0.08 | 0.08 | 0.00 | 2.91 | 0.32 | 0.31 | 0.01 | 3.10 | 0.16 | 0.17 | 0.00 | 2.52 |
MgO | 0.01 | 2.39 | 2.57 | 0.15 | 5.64 | 0.62 | 0.64 | 0.06 | 8.68 | 3.40 | 3.27 | 0.17 | 5.10 |
CaO | 0.01 | 5.35 | 5.99 | 0.26 | 4.31 | 0.47 | 0.45 | 0.02 | 4.70 | 3.50 | 3.17 | 0.15 | 4.60 |
Na2O | 0.01 | 1.44 | 1.68 | 0.17 | 10.15 | 0.46 | 0.52 | 0.06 | 11.73 | 2.00 | 2.03 | 0.17 | 8.21 |
K2O | 0.01 | 1.99 | 2.18 | 0.03 | 1.29 | 3.28 | 3.43 | 0.05 | 1.43 | 2.30 | 2.28 | 0.04 | 1.60 |
P2O5 | 0.00 | 0.15 | 0.17 | 0.01 | 4.56 | 0.06 | 0.07 | 0.01 | 8.32 | 0.23 | 0.22 | 0.01 | 5.86 |
Ag | 4.00 | 5.00 | 1.00 | 19.20 | |||||||||
As | 4.00 | 8.40 | 13.00 | 4.90 | 38.00 | 188.00 | 195.00 | 3.00 | 1.60 | 18.00 | 11.00 | 8.00 | 71.40 |
Ba | 5.00 | 430.00 | 430.00 | 9.70 | 2.30 | 260.00 | 258.00 | 7.40 | 2.90 | 760.00 | 810.00 | 18.10 | 2.20 |
Ce | 10.00 | 78.00 | 79.00 | 12.20 | 15.40 | 58.00 | 59.00 | 8.70 | 14.70 | 10.00 | 107.00 | 11.50 | 10.80 |
Co | 4.00 | 14.40 | 13.00 | 0.20 | 1.90 | 8.50 | 8.00 | 0.50 | 6.70 | 28.00 | 28.00 | 0.60 | 2.30 |
Cr | 4.00 | 85.00 | 89.00 | 2.60 | 2.90 | 40.00 | 36.00 | 2.70 | 7.50 | 243.00 | 244.00 | 7.50 | 3.10 |
Cu | 2.00 | 32.10 | 33.00 | 1.40 | 4.10 | 78.60 | 78.00 | 2.00 | 2.60 | 66.00 | 72.00 | 2.50 | 3.50 |
Ga | 2.00 | 14.00 | 18.00 | 3.00 | 16.90 | 18.50 | 19.00 | 3.40 | 17.20 | 25.00 | 30.00 | 4.00 | 13.70 |
Hf | 5.00 | 9.70 | 11.00 | 0.70 | 6.90 | 5.40 | 6.00 | 0.80 | 14.70 | 13.00 | 15.00 | 1.20 | 8.00 |
Mo | 2.00 | 0.64 | 5.90 | 7.00 | 0.50 | 7.70 | 2.70 | 4.00 | 0.50 | 13.90 | |||
Nb | 3.00 | 17.70 | 22.00 | 2.90 | 13.20 | 25.00 | 29.00 | 2.80 | 9.70 | 72.00 | 86.00 | 4.90 | 5.70 |
Nd | 3.00 | 34.00 | 37.00 | 7.80 | 20.09 | 27.00 | 23.00 | 6.40 | 27.80 | 45.00 | 51.00 | 10.10 | 19.70 |
Ni | 2.00 | 32.30 | 34.00 | 1.00 | 2.80 | 14.40 | 18.00 | 1.20 | 7.10 | 87.00 | 100.00 | 3.70 | 3.70 |
Pb | 2.00 | 23.00 | 23.00 | 0.90 | 8.10 | 636.00 | 627.00 | 14.70 | 2.30 | 66.00 | 68.00 | 3.20 | 4.70 |
Rb | 2.00 | 80.00 | 84.00 | 2.20 | 2.60 | 408.00 | 417.00 | 10.50 | 2.50 | 87.00 | 92.00 | 3.40 | 3.70 |
S | 3.00 | 150.00 | 217.00 | 6.70 | 3.10 | 170.00 | 178.00 | 14.50 | 8.10 | 175.00 | 16.10 | 9.20 | |
Sb | 3.00 | 0.80 | 14.90 | 11.00 | 1.30 | 11.60 | 2.70 | 4.00 | 0.70 | 18.70 | |||
Sc | 3.00 | 11.10 | 16.00 | 4.30 | 26.90 | 7.40 | 8.00 | 3.80 | 45.20 | 18.00 | 21.00 | 4.30 | 20.50 |
Sn | 3.00 | 2.60 | 5.00 | 2.10 | 42.30 | 370.00 | 400.00 | 7.90 | 2.00 | 9.50 | 8.00 | 3.90 | 47.70 |
Sr | 2.00 | 166.00 | 168.00 | 1.90 | 1.10 | 29.00 | 34.00 | 1.10 | 3.30 | 216.00 | 327.00 | 5.40 | 230 |
Ta | 3.00 | 1.30 | 5.70 | 5.00 | 1.40 | 24.80 | 5.00 | 4.00 | 0.80 | 19.60 | |||
Ih | 3.00 | 12.40 | 11.00 | 1.90 | 17.00 | 23.30 | 48.00 | 2.10 | 4.30 | 12.40 | 12.00 | 2.20 | 17.40 |
U | 3.00 | 2.60 | 4.00 | 0.80 | 20.60 | 9.10 | 8.00 | 1.20 | 15.20 | 3.00 | 4.00 | 1.50 | 37.20 |
V | 4.00 | 97.00 | 105.00 | 5.40 | 2.50 | 46.80 | 39.00 | 3.60 | 9.20 | 190.00 | 230.00 | 20.30 | 8.80 |
W | 3.00 | 1.76 | 126.00 | 97.00 | 3.80 | 3.90 | 5.60 | 5.00 | 0.90 | 18.10 | |||
Y | 3.00 | 26.50 | 25.00 | 0.60 | 2.30 | 42.70 | 37.00 | 2.00 | 5.50 | 3.40 | 34.00 | 1.50 | 5.30 |
Zn | 3.00 | 78.00 | 72.00 | 0.60 | 0.90 | 373.00 | 368.00 | 9.50 | 2.60 | 165.00 | 183.00 | 5.20 | 2.80 |
Zr | 3.00 | 370.00 | 391.00 | 9.00 | 2.30 | 152.00 | 156.00 | 5.60 | 3.60 | 524.00 | 560.00 | 17.40 | 3.10 |
The Lower limit of detection (LLD) of each element and the reference material obtained results.
The statistical tests of standard samples repeatability can be based on replicate assays of a certified standard in one laboratory or, conversely, inter laboratory analyses. Blank samples for materials that have very low grade of a metal of interest are usually inserted in a batch of samples being processed. The main purpose of using blanks is to monitor laboratory for a possible contamination of samples, which are mainly caused by poor housekeeping, and insufficient thorough cleaning of equipment.
Analytical data processing aims, firstly, at reducing random and/or systematic errors resulting from field survey and/or laboratory analysis, and secondly, at identifying whether the data contain some useful information indicating the source, pathway and trap of coal concentrations in the study area. The careful analysis of such data, using standard computer software packages, is an important and affordable way of adding value to an exploration programme.
Statistical methods have been widely applied to interpret analytical data sets and define anomalies. However, such methods need to be used cautiously since the data are typically and spatially dependent on each sample site and a range of different processes that may have influenced the element abundance measured. The data are also imprecise because of unavoidable variability in sampling methods and media and the level of analytical precision.
Moon [16] indicated that the aim of mineral exploration is to define significant anomalies. Anomalies are defined by statistically grouping data and comparing these with geology and sampling information. Strong anomalies detected may be for instance due to a combination of factors such as sampling and analytical errors, or contaminations which do not represent mineralisation. The absence of anomaly on the other hand may not necessarily mean the absence of mineralisation in the area of study. Such absence may be due to low rate of weathering in the area, buried or blind mineralisation, or dilution between source and sample site [17].
The use of descriptive statistics helps us to simplify large amounts of data into a simpler summary. Numerical and graphical methods are the two commonly used methods. Numerical method enables one to compute statistics such as mean and standard deviation while, graphical methods are better suited than numerical for identifying patterns in the data sets. The numerical and graphical methods complement each other and it is therefore wise to use both. Consequently, histograms, and summary statistical information were used in this study to identify patterns in data sets. According to Riemann et al. [18], a graphical inspection of analytical data is necessary as the first step in data analysis. The best means of statistical grouping data is graphical examination using histograms and box plots [19, 20].
The geology map retrieved from the CGS database, was compiled on ArcGIS software (Figure 3). The area is comprised of the Transvaal Sequence, Olifantshoek Supergroup, Kaaien Terrane, Areachap Group and Karoo Supergroup. The Transvaal Sequence is confined to the north-central part of the Kaapvaal Craton [21]. It overlies the Witwatersrand foreland basin (Supergroup) and is overlain by Bushveld Complex [21]. The three basins – the Transvaal basin, and Griqualand West basin, in South Africa, and the Kanye basin in Botswana basins are preserved on the Kaapvaal Craton [21].
The Geology of the Prieska map.
The geochemical data was transformed into a raster data with a cell size of 1 km using weighted inverse distance interpolation method. A maximum of four points were used to calculate a value for each cell location. First, the raster maps of the uni-elements were visualised in ArcGIS and compared to the underlying geology and known base metal occurrences. Univariate statistical methods was used to extract information from a data set of values for a single element, frequency histograms are created using GIS geostastical analyst tool, to examine the frequency distribution and identify the type of distribution, the all elements Histograms are on none transformation.
The only elements that correlates (Table 2) importantly with the known base metals occurrence in Prieska area as discussed in this section. The copper, lead, zinc, gold and silver minerals are associated with Volcanogenic Massive Sulphide (VMS) deposits. Prieska area is underlain by the Areachap Terrane, known to host VMS and Sedimentary exhalative deposit (SEDEX) deposits, including the mined out Copperton deposit, approximately 10 km southwest of the Prieska town. The Areachap terrane is overlain by up to 100 m of Karoo sediments that limited historical exploration.
Ag | As_ | Ba | Ce | Co | Cc | Cu | Ga | Hf | Mo | Nb | Nd | Ni | Pb | Rb | S | Sb | Sc | Sn | Sc | Ta | Th | U | V | W | Y | Zn | Zr | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Af | 10,000 | |||||||||||||||||||||||||||
As_ | 0,1552 | 10,000 | ||||||||||||||||||||||||||
Ba | 0,0520 | −0,0555 | 10,000 | |||||||||||||||||||||||||
Ce | 0,0956 | 0,5085 | −0,0218 | 10,000 | ||||||||||||||||||||||||
Co | 0,1271 | 0,0562 | 0,0767 | 0,0064 | 10,000 | |||||||||||||||||||||||
Cr | 0,1998 | 0,4000 | −0,0958 | 0,2664 | 0,5850 | 10,000 | ||||||||||||||||||||||
Cu | 0,0738 | −0,0106 | 0,5897 | −0,0222 | 0,2059 | 0,0606 | 10,000 | |||||||||||||||||||||
Ga | 0,1201 | 0,1445 | 0,3487 | −0,0953 | 0,1985 | 0,0926 | 0,1297 | 10,000 | ||||||||||||||||||||
Hf | 0,1611 | 0,0188 | −0,0435 | 0,6219 | 0,0443 | 0,4811 | −0,0134 | 0,1140 | 10,000 | |||||||||||||||||||
Mo | 0,1508 | 0,4587 | 0,1155 | 0,4859 | 0,1453 | 0,3451 | 0,2328 | −0,0075 | 0,4829 | 10,000 | ||||||||||||||||||
Nb | 0,4435 | 0,6413 | 0,1369 | 0,4409 | 0,0939 | 0,4380 | 0,0356 | 0,3268 | 0,3157 | 0,4147 | 10,000 | |||||||||||||||||
Nd | 0,1358 | 0,5690 | −0,0068 | 0,3967 | −0,0168 | 0,3239 | −0,0245 | −0,0169 | 0,7506 | 0,3212 | 0,5731 | 10,000 | ||||||||||||||||
Ni | 0,1609 | −0,0154 | 0,0303 | −0,0828 | 0,7213 | 0,5889 | 0,1484 | 0,2066 | 0,0004 | 0,0565 | 0,0926 | −0,0727 | 10,000 | |||||||||||||||
Pb | 0,2079 | 0,0909 | 0,5272 | 0,1199 | 0,0348 | 0,0140 | 0,3975 | 0,3629 | 0,1723 | 0,1611 | 0,3920 | 0,1846 | 0,0470 | 10,000 | ||||||||||||||
Rb | 0,0999 | 0,0098 | 0,4749 | 0,0740 | −0,1606 | −0,2758 | 0,0678 | 0,5134 | 0,0385 | −0,0054 | 0,2702 | 0,0929 | −0,0889 | 0,4933 | 10,000 | |||||||||||||
S | −0,0072 | −0,0354 | 0,2343 | 0,0001 | −0,0166 | −0,0475 | 0,1906 | −0,0291 | −0,0377 | 0,0375 | −0,0501 | −0,0048 | −0,0014 | 0,0529 | −0,0482 | 10,000 | ||||||||||||
Sb | −0,0034 | 0,0161 | 0,0213 | 0,0036 | −0,0242 | −0,0089 | 0,0064 | 0,0041 | −0,0144 | −0,0094 | −0,0080 | 0,0031 | −0,0122 | −0,0098 | 0,0575 | −0,0063 | 10,000 | |||||||||||
Sc | 0,2047 | −0,0250 | 0,0318 | −0,1328 | 0,4429 | 0,2516 | 0,0639 | 0,2282 | −0,0301 | 0,0183 | 0,1180 | −0,1172 | 0,2640 | 0,0207 | 0,0119 | −0,0715 | 0,0271 | 10,000 | ||||||||||
Sn | 0,0304 | 0,0776 | 0,0155 | 0,0503 | 0,0261 | 0,0482 | 0,0054 | 0,0062 | 0,0402 | 0,0568 | 0,0500 | 0,0601 | 0,0250 | 0,5404 | 0,0168 | −0,0106 | 0,0187 | −0,0079 | 10,000 | |||||||||
Sr | 0,0695 | −0,0067 | 0,1634 | 0,0728 | 0,1555 | 0,1554 | 0,0720 | 0,1295 | −0,0078 | 0,0549 | 0,0924 | 0,0699 | 0,0793 | 0,0682 | −0,0083 | 0,2750 | 0,0156 | 0,0796 | −0,0029 | 10,000 | ||||||||
Ta | 0,1460 | 0,6796 | −0,0043 | 0,3454 | 0,0778 | 0,3385 | 0,0015 | 0,2528 | 0,6254 | 0,3035 | 0,5409 | 0,4318 | 0,0610 | 0,1471 | 0,0602 | −0,0345 | −0,0151 | −0,0390 | 0,0562 | 0,0001 | 10,000 | |||||||
Th | 0,2442 | 0,6040 | 0,1355 | 0,4527 | 0,0881 | 0,3830 | 0,0042 | 0,3247 | 0,7713 | 0,3685 | 0,3119 | 0,5952 | 0,0532 | 0,3880 | 0,3286 | −0,0708 | −0,0072 | 0,0508 | 0,0870 | 0,0994 | 0,5251 | 10,000 | ||||||
U | 0,4857 | 0,6433 | 0,0206 | 0,4750 | 0,1511 | 0,4374 | 0,0340 | 0,0623 | 0,7311 | 0,4912 | 0,7532 | 0,5298 | 0,0777 | 0,2401 | 0,1082 | −0,0399 | −0,0052 | 0,1456 | 0,0738 | 0,0748 | 0,4471 | 0,7055 | 10,000 | |||||
V | 0,2149 | 0,4729 | 0,1704 | 0,3644 | 0,4582 | 0,6379 | 0,1149 | 0,4151 | 0,6194 | 0,2823 | 0,6647 | 0,5072 | 0,3049 | 0,2850 | 0,1388 | −0,0441 | 0,0091 | 0,2151 | 0,0459 | 0,2889 | 0,4409 | 0,7084 | 0,5656 | 10,000 | ||||
W | 0,1762 | 0,7146 | −0,0475 | 0,4144 | 0,0653 | 0,3628 | 0,0655 | 0,2838 | 0,6472 | 0,3569 | 0,5250 | 0,4742 | 0,1001 | 0,1219 | −0,0574 | 0,0089 | −0,0233 | −0,1385 | 0,0592 | −0,0880 | 0,6536 | 0,4426 | 0,3475 | 0,3731 | 10,000 | |||
Y | 0,0760 | 0,6310 | 0,1944 | 0,4462 | 0,0596 | 0,2291 | 0,0368 | 0,1847 | 0,6366 | 0,3524 | 0,6057 | 0,4921 | −0,0679 | 0,2747 | 0,3773 | −0,0808 | 0,0349 | 0,1034 | 0,0384 | 0,1085 | 0,3644 | 0,6741 | 0,6577 | 0,5464 | 0,0729 | 10,000 | ||
Zn | 0,0507 | −0,0406 | 0,6355 | −0,0231 | 0,1166 | 0,0117 | −0,9213 | 0,1624 | −0,0329 | 0,2150 | 0,0267 | −0,0194 | 0,0852 | 0,4360 | 0,1348 | 0,1933 | 0,0016 | 0,0126 | −0,0011 | 0,0920 | −0,0125 | 0,0093 | 0,0037 | 0,1061 | 0,0443 | 0,0403 | 10,000 | |
Zr | 0,1553 | 0,3292 | −0,0691 | 0,6256 | 0,0378 | 0,4734 | −0,0244 | 0,0292 | 09565 | 0,5239 | 0,7904 | 0,7295 | −0,0231 | 0,1445 | 0,0038 | −0,0438 | −0,0143 | −0,0294 | 0,0488 | −0,0256 | 0,6015 | 0,7495 | 0,7594 | 0,5776 | 0,5925 | 0,6669 | −0,0501 | 10,000 |
Very Strong Correlation | ||||||||||||||||||||||||||||
Moderate to strong correlation | ||||||||||||||||||||||||||||
Moderate Correlation |
The summary statistics of all the analysed elements.
The elemental distribution maps are plotted using the Jenks natural classification system. The elemental population is classified into five break points;
The first break is minimum to mean value, and
Second break is from mean to (mean plus standard deviation) value, the first two break are regarded as a background value, values above the threshold calculates Table 3 are anomalous,
From the threshold to mean + 3*standard deviation value is highly anomalous and
The fifth break is the value from mean + 3*standard deviation value to maximum value.
Element | Count | Minimum | Maximum | Mean | Standard Deviation | Skewness | &$$$; | Quantile1 | Median | Quantile3 | Threshold values | Mean + 3*SD | Coefficient Variation |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SiO2 (%) | 9312 | 18.993 | 80.991 | 47.074 | 4.408 | −0.535 | 6.054 | 44.797 | 47.382 | 49.804 | 55.891 | 60.299 | 0.093651 |
TiO2 (%) | 9312 | 0.238 | 7.230 | 1.161 | 0.342 | 3.891 | 32.579 | 0.988 | 1.095 | 1.224 | 1.845 | 2.188 | 0.294575 |
Al2O3 (%) | 9312 | 2.592 | 19.816 | 9.756 | 1.748 | −0.076 | 3.303 | 8.562 | 9.753 | 10.980 | 13.251 | 14.999 | 0.179152 |
Fe2O3 (%) | 9312 | 2.766 | 26.504 | 7.607 | 1.659 | 1.579 | 9.573 | 6.685 | 7.328 | 8.271 | 10.925 | 12.584 | 0.218062 |
MnO (%) | 9312 | 0.036 | 2.281 | 0.133 | 0.082 | 6.192 | 87.683 | 0.094 | 0.114 | 0.141 | 0.297 | 0.379 | 0.617984 |
MgO (%) | 9312 | 0.000 | 7.909 | 1.315 | 0.761 | 2.045 | 10.105 | 0.830 | 1.092 | 1.593 | 2.838 | 3.599 | 0.578966 |
CaO (%) | 9312 | 0.189 | 31.877 | 1.737 | 1.737 | 5.547 | 51.711 | 1.012 | 1.240 | 1.705 | 5.211 | 6.948 | 0.999938 |
Na2O (%) | 9312 | 0.000 | 6.769 | 0.566 | 0.168 | 6.231 | 206.536 | 0.471 | 0.555 | 0.637 | 0.902 | 1.070 | 0.29633 |
K2O (%) | 9312 | 0.535 | 3.266 | 2.067 | 0.311 | −0.249 | 3.443 | 1.890 | 2.059 | 2.282 | 2.688 | 2.999 | 0.150348 |
P2O5 (%) | 9312 | 0.029 | 1.052 | 0.139 | 0.051 | 3.117 | 35.630 | 0.107 | 0.135 | 0.162 | 0.240 | 0.290 | 0.364042 |
As (ppm) | 9312 | 4.000 | 120.910 | 15.802 | 13.874 | 2.235 | 9.991 | 6.145 | 11.450 | 20.240 | 43.551 | 57.425 | 0.878017 |
Ag (ppm) | 9312 | 4.000 | 25.270 | 5.392 | 2.452 | 3.519 | 19.435 | 4.000 | 4.240 | 6.050 | 10.296 | 12.748 | 0.454685 |
Ba (ppm) | 9312 | 91.180 | 4187.720 | 410.752 | 76.653 | 24.597 | 1080.028 | 382.565 | 409.805 | 439.865 | 564.058 | 640.711 | 0.186616 |
Ce (ppm) | 9312 | 10.000 | 864.010 | 78.027 | 55.741 | 4.665 | 36.596 | 53.200 | 64.390 | 79.425 | 189.510 | 245.251 | 0.714379 |
Co (ppm) | 9312 | 4.000 | 56.420 | 14.733 | 4.017 | 1.149 | 6.949 | 12.050 | 14.140 | 16.790 | 22.766 | 26.783 | 0.272629 |
Cx (ppm) | 9312 | 49.790 | 1052.880 | 141.762 | 40.500 | 4.198 | 49.516 | 119.470 | 131.680 | 151.535 | 222. 762 | 263.262 | 0.285688 |
Cn (ppm) | 9312 | 7.370 | 2357.040 | 34.465 | 31.879 | 53.683 | 3534.044 | 28.510 | 32.780 | 37.740 | 98.223 | 130.102 | 0.924974 |
Ga (ppm) | 9312 | 6.250 | 46.420 | 19.769 | 4.425 | 0.143 | 2.650 | 16.040 | 19.890 | 23.160 | 28.618 | 33.043 | 0.223816 |
Hf (ppm) | 9312 | 5.000 | 245.440 | 23.292 | 14.397 | 3.954 | 30.123 | 15.850 | 19.820 | 25.720 | 52.085 | 66.482 | 0.618101 |
Mo (ppm) | 9312 | 2.000 | 13.550 | 2.143 | 0.568 | 7.505 | 84.540 | 2.000 | 2.000 | 2.000 | 3.279 | 3.846 | 0.264826 |
Nb (ppm) | 9312 | 3.000 | 112.200 | 25.264 | 8.482 | 2.075 | 13.720 | 20.650 | 24.060 | 28.115 | 42.229 | 50.711 | 0.335735 |
Nd (ppm) | 9312 | 3.000 | 459.830 | 40.511 | 27.490 | 4.003 | 31.632 | 26.270 | 34.815 | 44.850 | 95.490 | 122.980 | 0.678578 |
Ni (ppm) | 9312 | 11.360 | 460.500 | 39.559 | 12.345 | 7.908 | 192.598 | 33.180 | 37.620 | 43.905 | 64.250 | 76.595 | 0.31207 |
Pb (ppm) | 9312 | 2.000 | 167.110 | 18.776 | 5.030 | 7.963 | 192.132 | 16.420 | 18.745 | 20.950 | 28.836 | 33.866 | 0.267912 |
Kb (ppm) | 9312 | 21.170 | 142.690 | 86.942 | 13.467 | −0.688 | 4.017 | 80.355 | 88.400 | 95.525 | 133.876 | 127.343 | 0.154898 |
Sb (ppm) | 9312 | 3.000 | 4.300 | 3.001 | 0.026 | 36.635 | 1554.275 | 3.000 | 3.000 | 3.000 | 3.052 | 3.077 | 0.008499 |
S (ppm) | 9312 | 54.920 | 32965.370 | 233.027 | 471.570 | 49.696 | 3037.767 | 146.985 | 195.115 | 257.120 | 1176.166 | 1647.735 | 2.023673 |
Sa (ppm) | 9312 | 3.000 | 230.040 | 3.611 | 3.976 | 31.589 | 1458.505 | 3.000 | 3.000 | 3.000 | 11.562 | 15.538 | 1.100919 |
Se (ppm) | 9312 | 3.000 | 50.180 | 18.183 | 5.077 | 0.135 | 3.687 | 14.930 | 17.930 | 21.355 | 28.337 | 33.413 | 0.279187 |
Sr (ppm) | 9312 | 18.170 | 975.050 | 113.523 | 28.744 | 8.948 | 201.199 | 100.590 | 133.045 | 123.810 | 171.010 | 199.754 | 0.253195 |
Ta (ppm) | 9312 | 3.000 | 61.570 | 7.556 | 6.478 | 2.620 | 12.424 | 3.000 | 5.285 | 9.130 | 20.513 | 26.992 | 0.857349 |
Th (ppm) | 9312 | 3.000 | 132.240 | 13.868 | 6.750 | 4.161 | 40.510 | 10.270 | 12.970 | 15.890 | 27.367 | 34.116 | 0.486706 |
U (ppm) | 9312 | 3.000 | 25.760 | 4.041 | 1.842 | 3.467 | 22.295 | 3.000 | 3.075 | 4.450 | 7.726 | 9.568 | 0.455809 |
V (ppm) | 9312 | 16.180 | 836.190 | 126.384 | 33.836 | 3.657 | 41.490 | 108.250 | 123.520 | 137.885 | 194.057 | 227.893 | 0.267726 |
W (ppm) | 9312 | 3.000 | 51.750 | 6.318 | 5.147 | 2.546 | 12.203 | 3.000 | 3.980 | 7.850 | 16.612 | 21.759 | 0.814664 |
Y (ppm) | 9312 | 3.960 | 112.390 | 27.021 | 7.211 | 2.420 | 18.762 | 23.030 | 26.635 | 29.860 | 41.443 | 48.654 | 0.266869 |
Zn (ppm) | 9312 | 11.990 | 5347.830 | 66.145 | 68.394 | 58.378 | 4155.871 | 53.120 | 62.850 | 74.285 | 202.933 | 271.327 | 1.034011 |
Zx (ppm) | 9312 | 111.870 | 9242.850 | 1023.432 | 671.759 | 3.605 | 24.477 | 669.530 | 855.425 | 1144.235 | 2366.950 | 3038.709 | 0.656379 |
Correlation Matrix.
The primary aim of the exploration target generation is twofold; to generate new areas for exploration activity where favourable geology and no mineral occurrences are coincident, and secondly a rethink in areas of known mineralisation on the possibilities of other styles or models of mineralisation. The geology of Prieska area and the geochemistry was joined using the Analysis tool spatial joint; the aim is to calculate the mean values of Uni-element of the lithostratigraphic unit. Table 4 below refers to the lithostratigraphic unit with their associated elements. Based on [22] the five Fuzzy operators are useful for combining exploration datasets, Fuzzy AND, OR, Algebraic product, algebraic sum and γ-operator. In this study Fuzzy OR operation was applied to combine maps of relevant indicator elements associated with the geology (Table 4).
Geology (Ilthostratigraphy) | Elements |
---|---|
Zeekobraat | W, Fe |
Spioenkop | Cu, Ga, Rb, Zn |
Uitdraai | V |
Waterkop | Ba |
Ongeluk lava Formation | Co, Ni |
Prieskaspoort | Cr, S, Sr., Mg |
Koegas Group | Nd, Pb, Th |
Jacomyns Pan | Ag |
Kalahari Group | Sn |
Builsand | Hf, Mo, Nb, Sc, Ta, U |
Boegoeberg Dam | Zr, As |
Asbestos Hill | Ce |
Relevant indicator elements associated with the geology.
The elements of the highest mean averages associated with the Spioenkop Formation is the Cu, Ga, Zn and Rb (Figure 4). Cu and Zn correlates very strong at the correlation coefficient of 0.97. The distribution of the two elements strongly correlated with the known VMS Copperton deposit. Figures 5–7 displays a Fuzzy OR overlap multi-element map of Cu, Ga, Zn and Rb. The map index poorly delineate Spioenkop Formation, the second dispersion occur in Uitdraai Formation, Jacomyns pan Formation, Globershoop, and Spioenkop Formation. The observed mineralisation potential areas are M1 and M2. The M1 anomaly is associated with the known mine area named Copperton Deposit, Prieska mine, the M1 anomaly is overlaying the Kalahari and Dwyka Group The Prieska Cu_Zn is known as the VMS deposit, the most common commodities or minerals exploited in this area are the Zinc, Copper and Sphalerite. The Mine known as a medium scale abandoned mine. The M2 anomaly is in close vicinity to the Orange River catchment, the anomaly is overlaying the Campbellrand subgroup. Campbell Rand Subgroup belongs to the Ghaap Group. The base mineralisation have been recorded in Ghaap Group is Pering deposit far northeast about 150 km from the study area. The Host rocks to Zn–Pb mineralisation on the Ghaap Plateau are stromatolitic dolomites, with minor oolitic dolomites, chert and carbonaceous shale beds of the Campbell Rand Subgroup (Gutzmer, 2006). The occurrence of the M2 potential mineralisation zones requires follow-up studies.
Fuzzy OR overlay multi-element map index of Cu, Ga, Zn, and Rb.
There is a very strong correlation between the Co and Ni, and moderate to strong correlation between Co and Cr indicator elements. The correlations of Co-Ni-Cr are the indicator of mafic- ultramafic geological index. The strong correlation between Co and Ni can also indicate the base metal mineraization. The Ni-Co covers the sulphides and oxides of interest (Co-Ni-Cr) in ultramafic rocks. Co-Ni is a pathfinder of Ni-Cu.
The anomaly M3 – M7 (Figure 8) are Co-Ni high values. The M3 potential mineralisation area to the west of Prieska town covers the Dwyka Group, this mineralisation is at the very close vicinity to the Orange River catchment (primary stream) dominant mostly to the south of the catchment. The Co-Ni anomaly (M3) to the north of the Catchment is similar to the Cu-Ga-Zn-Rb anomaly M2, these anomalies cover the Campbellrand Subgroup at the same area, and therefore this outline the new potential of base metal mineralisation The M4 anomaly overlay the Dwyka Group, Asbestos Hills and the Skalkseput Granite. The M4 anomaly trends to the north-west following the Skalkseput Granite lithology, at the M7 the Co-Ni anomaly covers the Skalkseput Granite and is associated with the known occurring Uranium commodity.
The Fuzzy OR overlay map for Cu_Zn index.
The M5 Co-Ni anomaly is in close vicinity with the known small Copper occurrence. The anomaly is evident in and around the Orange River Catchment. This will require follow up study to confirm the parent source of the anomaly, because of its close vicinity with the known Cu occurrence the Co-Ni correlation may possibly indicate the Base (Cu_Zn) mineralisation. Unlike the M7 anomaly associated with Spioenkop Formation and Ongeluk lava Formation. The M6 anomaly overlay the Ongeluk Lava Formation, and Asbestos Hill.
The elements of the highest mean averages associated with the Brulsand are the Hf, Mo, Nb, Sc, Ta, and U. The Hf, Sc, Mo, Nb, and Ta are transition elements and most of are typically treated as being immobile during metamorphic processes and therefore can be useful in understanding the effects of metamorphism. U strongly correlates with Hf, Ta and Nb, and moderately correlates with Mo. The M8 potential mineralisation (Figure 9) consist of isolated cluster of potential mineralisation zones overlying the Asbestos Hills Subgroup, Koegas Group, Kalahari group, Olifantshoek Supergroup. M9 is associated with known metals occurrences; Cu and U, the isolated cluster of anomalies towards the know Prieska Copperton mine. The M9 potential mineralisation zones on the west of Orange River catchment overlies the Draghoender granite/gneiss, Skalkseput granite, Uitdraai Formation and Zeekoebaart Formation. Granitic rocks rich in pyrochlore, euxenite, brannerite, thorite yield soils rich in Nb, Ta, Ti, rare earths, Sc and Zr, are enriched in dark heavy minerals. The radioactive species originally contained in the parent rocks form a major fraction [23]. The Sc, U, Nb, and Ta are indicators of uranium-bearing minerals in granitic, syenitic, magmatitic, pegmatitic and aplitic bodies and complexes. Strauss and Elsenbroek (2006) found in a study on South African alkali and carbonatite complexes that Nb is by far the strongest and most common indicator for these complexes in soils followed by Zr.
The Fuzzy OR overlay map for Ni, Co and Cr index.
The following geochemical indices are potential target generators for the Prieska area based on the predominant geology in the area coupled with the single element distribution patterns. The Cu_Zn for VMS Zn_Cu deposit, Ni_Co_Cr ultramafic Ni_Cr (±Cu) deposit and Zr_Nb_U_Th_Hf_Ta for the heavy mineral placer deposits. First, new raster files for each index element is created by using of the inverse distance weighted interpolation (IDW). Then the indices were calculated using the fuzzy overlay OR function from ARCGIS, the advantage of using fuzzy OR overlay is generally provides a better result in cases where the indicator elements are not always associated and is better suited for the secondary dispersion where associated elements in the primary environment are likely to be separated.
The anomaly (Figure 5) delineates the known Copperton mine in Prieska area, the Copperton ore body occurs in a series of quartz-feldspar rocks quartz-biotite gneisses and quartz- plagioclase–amphibole gneisses as Copperton Volcanic Pile.
The Fuzzy OR overlay of Zr_Nb_U_Th_Hf_Ta.
The anomaly M12 associated with Koegas Group, Ongeluk lava Formation and Asbestos Hill Subgroup (Figure 6) is a preferred potential target for ultramafic Ni_ Cr (±Cu) deposit. The anomaly overlies the banded Iron Formation of the Asbestos Hill Subgroup; the Asbestos Hill Subgroup is Fe-rich. The anomaly M14 is associated with the known Cu occurrence straddles the Campbell Rand Subgroup, and Zeekoebaart Formation is the secondary target. Anomaly M13 is also identified as the secondary potential target for ultramafic Ni_Cr (±Cu) associated with Dwyka Group.
The Fuzzy OR overlay multi-element map index of Co and Ni.
Zr_Nb_U_Th_Hf_Ta are high field strength elements associated with the carbonatites deposits and alkaline magmatic complexes, however the carbonatites deposits are unknown to occur around the Prieska geology area. The high field strength elements are primary indicators of the REE deposit. These elements are associated as incompatible ions, within alkaline igneous melts, which by their emplacement is controlled by the failed rift zone or deep-seated suture.
The anomalies of the Zr_Nb_U_Th_Hf_Ta (Figure 7) may be due to thorium in waste rock or sediment; dust from mining activities in the surrounding, and possible water contamination from spillage or leakage of chemical solutions used to leach and process ore. Asbestiform amphiboles that are present in waste dumps. The correlation of the Cu-Pb-Zn anomaly with alkali elements (Nb, Zr, Th, and U) and REEs suggests there is a possibility that the M26 –M29 anomaly are alkali-granitic genetic origin. The anomaly could therefore indicate the presence of Cu, Pb, Zn and As sulphides associated with alkali elements and REEs, which makes it a very promising target however the map (Figure 7) display a batch effect specifically anomaly M26 and 27, and therefore it is not suitable for interpretation.
The Fuzzy OR overlay of Mo, Nb, Sc, Ta, and U.
Prieska study area generally forms part of the Namaqua Metamorphic Province and the Griqualand-West Basin. The Kalahari Aeolian sand covers the geology on the area around Prieska Cu-Zn mine. The host sequence in the Copperton district is, from the base: Smouspan Gneiss Member, Prieska Copper Mines Member, and Vogelstruisbult Member. The aeolian sand extensively covers the research area. The secondary dispersion patterns of the elements in the stream sediments may also destroy the primary association of elements. To overcome this difficulty, a Fuzzy OR overlay of indicator applied. Fuzzy OR generally provides a better result in cases where the indicator elements are not always associated and is better suited for the secondary dispersion where associated elements in the primary environment are likely to be separated.
The descriptive statistics (Table 3) results shows that the Ag, Co, Ga, Mo, Nb, Pb, Sb, Sn, Sc, Ta, Th, U, and W concentrations exhibited generally low standard deviation and coefficient of variation values, suggesting a homogenous spatial distribution. In contrast As, Ba, Ce, Cr, Cu, Hf, Nd, Ni, Rb, Sr., S, V, Zr and Zn contents showed a heterogeneous spatial distribution, reflected by high coefficient of variation and large standard deviation. The difference between the median and mean values of high coefficient of variation of the As, Ba, Ce, Cr, Cu, Hf, Nd, Ni, Rb, Sr., S, V, Zr and Zn may be attributed to the extremely high values of these trace elements.
The Fuzzy OR maps give a summary of the potential targets for mineralisation within the study area. Anomaly M1 and M2 associated with Spioenkop Formation though the anomaly does not delineate the Spioenkop Formation but Dwyka Group Sediments, Kalahari Group and Campbell Rand Subgroup. These anomaly signatures are characterised by the one or more of these elements Cu, Ga, Zn, Rb, Pb, Mo, and Ba. Barium is a powerful indicator tool of gossan and be used as an indicator for Zn–Pb deposit. The dataset shows a significant relationship between the Ba and Zn. The relationship between these elements therefore delineate M1 and M2 as potential target for VMS deposit.
The anomaly M2 in close vicinity to the Orange River Catchment, a follow-up study is therefore recommended. The Cu and Zn are generally interpreted as pollution related or may be as a result of metal dispersion from the mine waste. The Zn and Cu high concentrations are not distributed across the Prieska area, the Fuzzy OR overlay of these elements are only elevated in the known Copperton mine area and on the M2 potential VMS mineralisation target area. The anomaly M2 associated with Campbell Rand Subgroup may be as a result of metal dispersion or sourced from the parent underlying rocks.
The Pb and S are also elevated on the known Copperton mine, these elements strongly correlates with the Zn. The Pb and S are likely to be associated with the generic anthropogenic source including sewage discharge, agricultural practises and various kinds of industrial activities. M11 is definitely a VMS mineralisation target, the anomaly overlies the Copperton mine. The high Cu, Zn and Pb are derived from the ore minerals related VMS deposits. The Fe elevated concentration are derived from both primary minerals which are not directly related to the VMS or Co_Ni (±Cu) (illustrated in Figures 4 and 8) mineralisation within the study area or from ore related minerals of deposits hosted in Banded Iron formation of the Asbestos Hills Subgroup.
The Cr, Ni reflect ultramafic fraction of the stream sediments. The Ni and Cr originate from direct ophiolitic sequences erosion and the recycling of the rocks enriched in ultramafic debris. The M13 and M14 anomaly are traced along the Orange river Catchment, on the Ghaap group which occurs NW to SE of the study area and north of the Orange River Catchment. Ghaap Group consists of shale, sandstone, andesite, and dolomite, and comprised of the magnesium, carbonate-rich Formation such as Vryburg Formation. M13 and M24 potential mineralisation are possibly sourced from ultramafic debris transported from the Ghaap Group by the Orange River Catchment, however this potential target will require follow-up studies for verification. There is a very high Cu-Zn correlation coefficient calculated for samples near the Copperton deposit.
Indicator elements in stream sediments sample represents either mineralisation or post- mineralisation processes. The processes that affect the indicator elements distribution patterns, these process includes weathering, erosion of ore bodies and adjacent mineralised rock, contamination of pollutants, regolith, topographic gradient vegetation density and/or climate. In this study integration of mineral exploration methods such as remote sensing, geophysics and petrography are recommended, this follow-up studies will assist in determining the extent of the anomaly.
The airborne geophysics studies must be conducted over the research area. Low level airborne electromagnetic (EM) surveys over the target area (M1-M29) especially the M2 and M3 which delineate the possibility of the base metal mineralisation is recommended. The high density stream sediments sampling on the grid and a depth of at least 50 meters to minimise the effect of Aeolian sand cover must be conducted. Petrography is another important tool, to understand the mineralogy of the study area underlying rocks. The detailed analysis of minerals by optical microscopy in thin section and micro-texture and structure is recommended in order to understand the origin and history of the rock.
Remote sensing will also be advantageous in conducting geological traverses of the study area in which anomalies of one or more of the above mentioned elements occur to establish the significance of the anomalies. Remote sensing imagery will also provide information on rock composition or rock alteration which is associated with the indicative of the presence of mineral deposits. Ore deposits are localised along regional and local fracture patterns, the Landsat and radar images are used to map these fracture pattern. Using multiple tools of exploration such as geology, structures, geochemistry, and drainage pattern are recommended for use in ArcGIS as thematic layers to generate the potential mineralisation targets.
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This system consists of a rotor, a shaft, a cover, and a base. The author derives a meaningful electromagnetic force by using the singular value decomposition. The author develops a control system using the proportional‐integral‐derivative controller to control the position of the rotor and regulate the two gimbal angles of the rotor. The author gives the numerical simulation and experimental results on the control of the electromagnetic levitation system.",book:{id:"5523",slug:"bearing-technology",title:"Bearing Technology",fullTitle:"Bearing Technology"},signatures:"Yonmook Park",authors:[{id:"2861",title:"Dr.",name:"Yonmook",middleName:null,surname:"Park",slug:"yonmook-park",fullName:"Yonmook Park"}]},{id:"55312",doi:"10.5772/67144",title:"Design Aspects of the Bearing Supports",slug:"design-aspects-of-the-bearing-supports",totalDownloads:1650,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter examines different types of bearing supports. Technical parameters of different types of bearing supports are presented. The effectiveness of some types of bearings is determined. General approach for the calculation of bearing overall dimensions is considered.",book:{id:"5523",slug:"bearing-technology",title:"Bearing Technology",fullTitle:"Bearing Technology"},signatures:"Ismagilov Flur Rashitovich, Vavilov Vyacheslav Evgenievich and D.V.\nGusakov",authors:[{id:"192044",title:"Dr.",name:"Viacheslav",middleName:null,surname:"Vavilov",slug:"viacheslav-vavilov",fullName:"Viacheslav Vavilov"},{id:"192050",title:"Prof.",name:"Flur",middleName:null,surname:"Ismagilov",slug:"flur-ismagilov",fullName:"Flur Ismagilov"},{id:"197037",title:"Ph.D.",name:"Denis",middleName:null,surname:"Gusakov",slug:"denis-gusakov",fullName:"Denis Gusakov"}]}],mostDownloadedChaptersLast30Days:[{id:"53926",title:"Condition Monitoring and Fault Diagnosis of Roller Element Bearing",slug:"condition-monitoring-and-fault-diagnosis-of-roller-element-bearing",totalDownloads:2661,totalCrossrefCites:6,totalDimensionsCites:7,abstract:"Rolling element bearings play a crucial role in determining the overall health condition of a rotating machine. 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Technical parameters of different types of bearing supports are presented. The effectiveness of some types of bearings is determined. 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His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. 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Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. 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He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a Principal Investigator and Scientist at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via machine-learning-based analyses of exosomal signatures. Dr. Paul has published in more than fifty peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"333824",title:"Dr.",name:"Ahmad Farouk",middleName:null,surname:"Musa",slug:"ahmad-farouk-musa",fullName:"Ahmad Farouk Musa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333824/images/22684_n.jpg",biography:"Dato’ Dr Ahmad Farouk Musa\nMD, MMED (Surgery) (Mal), Fellowship in Cardiothoracic Surgery (Monash Health, Aust), Graduate Certificate in Higher Education (Aust), Academy of Medicine (Mal)\n\n\n\nDato’ Dr Ahmad Farouk Musa obtained his Doctor of Medicine from USM in 1992. He then obtained his Master of Medicine in Surgery from the same university in the year 2000 before subspecialising in Cardiothoracic Surgery at Institut Jantung Negara (IJN), Kuala Lumpur from 2002 until 2005. He then completed his Fellowship in Cardiothoracic Surgery at Monash Health, Melbourne, Australia in 2008. He has served in the Malaysian army as a Medical Officer with the rank of Captain upon completing his Internship before joining USM as a trainee lecturer. He is now serving as an academic and researcher at Monash University Malaysia. He is a life-member of the Malaysian Association of Thoracic & Cardiovascular Surgery (MATCVS) and a committee member of the MATCVS Database. He is also a life-member of the College of Surgeons, Academy of Medicine of Malaysia; a life-member of Malaysian Medical Association (MMA), and a life-member of Islamic Medical Association of Malaysia (IMAM). Recently he was appointed as an Interim Chairperson of Examination & Assessment Subcommittee of the UiTM-IJN Cardiothoracic Surgery Postgraduate Program. As an academic, he has published numerous research papers and book chapters. He has also been appointed to review many scientific manuscripts by established journals such as the British Medical Journal (BMJ). He has presented his research works at numerous local and international conferences such as the European Association for Cardiothoracic Surgery (EACTS) and the European Society of Cardiovascular Surgery (ESCVS), to name a few. He has also won many awards for his research presentations at meetings and conferences like the prestigious International Invention, Innovation & Technology Exhibition (ITEX); Design, Research and Innovation Exhibition, the National Conference on Medical Sciences and the Annual Scientific Meetings of the Malaysian Association for Thoracic and Cardiovascular Surgery. He was awarded the Darjah Setia Pangkuan Negeri (DSPN) by the Governor of Penang in July, 2015.",institutionString:null,institution:{name:"Monash University Malaysia",country:{name:"Malaysia"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}}]}},subseries:{item:{id:"23",type:"subseries",title:"Computational Neuroscience",keywords:"Single-Neuron Modeling, Sensory Processing, Motor Control, Memory and Synaptic Pasticity, Attention, Identification, Categorization, Discrimination, Learning, Development, Axonal Patterning and Guidance, Neural Architecture, Behaviours and Dynamics of Networks, Cognition and the Neuroscientific Basis of Consciousness",scope:"Computational neuroscience focuses on biologically realistic abstractions and models validated and solved through computational simulations to understand principles for the development, structure, physiology, and ability of the nervous system. This topic is dedicated to biologically plausible descriptions and computational models - at various abstraction levels - of neurons and neural systems. This includes, but is not limited to: single-neuron modeling, sensory processing, motor control, memory, and synaptic plasticity, attention, identification, categorization, discrimination, learning, development, axonal patterning, guidance, neural architecture, behaviors, and dynamics of networks, cognition and the neuroscientific basis of consciousness. 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