Multiple grain-size fraction analysis of heavy minerals and the provenance identification of sediments from the abandoned Huanghe River,eastern China

The quantitative analysis of sediment sources in a sink is an important scientific topic and challenge in provenance research.The characteristics of heavy minerals,combined with the geochemical constituents of detrital grains,provide a reliable provenance-tracing approach.We developed a mineral identification method to analyze the multiple grain-size fraction of sediments,from which the elemental geochemistry of hornblende was used to compare the characteristics of sediments from the Huaihe River and Huanghe(Yellow)River in eastern China.Elements that were statistically identified as being able to discriminate sediment provenance were employed to perform a quantitative analysis of the sources of sediments of the abandoned Huanghe River.Results reveal that the Huaihe River is characterized by a high amphibole content of>60%and that the Huanghe and abandoned Huanghe rivers have greater abundances of limonite and carbonate minerals compared with those of the Huaihe River.The contents of trace elements and rare earth elements in hornblende show that the sediments of the abandoned Huanghe River are similar to those of the Huanghe River but different from those of the Huaihe River.Furthermore,chemical mass balance was used to calculate the relative contributions of different provenances of sediment from the abandoned Huanghe River,and nine trace elements of hornblende were identified as discriminators of provenance.Approximately 2%of the hornblende in the abandoned Huanghe River is derived from the Huaihe River and 98%from the Huanghe River.Considering the proportion of hornblende in the total sediment,it is inferred that the contribution of Huaihe River sediment to the abandoned Huanghe River is approximately 0.5%.This study shows that mineral analysis using multiple grain-size fractions(within the wide range of 1Φto 6Φ)with assessment in elemental geochemistry of hornblende can characterize the provenance of fluvial material in coastal zones.

Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

Genetic Variability and Phenotypic Correlations Study among Grain Quality Traits and Mineral Elements Concentrations in Colored and Non-Colored Rice (Oryza sativa L.)

Twenty-four rice genotypes were examined to assess genetic variability,heritability,and correlations for seven-grain quality traits,eight nutritional elements,and protein.ANOVA revealed significant differences for the quality traits studied.For every trait under study,the phenotypic coefficient of variation was higher than the correspon-dence genotypic coefficient of variation.Heritability in a broad sense varied from 29.75%for grain length to 98.31%for the elongation trait.Hulling percentage recovery had a highly significant positive correlation with milling and head rice percentage.Consequently,milling percentage had a highly positive correlation with head rice percentage.In amylose percentage,all the genotypes belonged to low amylose except the Hassawi-1 variety,which had intermediate amylose content.Mineral nutrition contents of magnesium(Mg),sodium(Na),potas-sium(K),calcium(Ca),copper(Cu),manganese(Mn),zinc(Zn),iron(Fe),or protein percentage gave different variations for 24 rice genotypes under all the nutritional elements.Among the 24 genotypes,ten rice genotypes–HighNutrient-1,HighNutrient-2,HighNutrient-9,HighNutrient-8,HighNutrient-3,Hassawi-2,HighNutrient-7,HighNutrient-6,Hassawi-1,and HighNutrient-4–had the highest heist value for all nutritional and protein con-tents,and could be used as a donor to improving new varieties.There was a positive and significant correlation between magnesium Mg,K,Zn and Fe.Consequently,K had a positive correlation with zinc Zn,Fe,and protein percentage.Clustering analysis was divided into two groups:thefirst group included all genotypes rich in nutri-ents,while the remaining genotypes with low nutritional content were included in the second group.

Use of high-resolution X-ray computed tomography and 3D image analysis to quantify mineral dissemination and pore space in oxide copper ore particles

Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.

MINERALIZATION AGES OF GOLD-HYDROTHERMAL DEPOSITS IN NORTHERN ZONE OF EASTERN KUNLUN MOUNTAINS BASED ON FISSION TRACK ANALYSIS

The age of mineralization in a mining area is a primary factor in various researches related to ore\|forming process. It is that the uncertainty of mineralization ages of gold ore deposits in northern zone of eastern Kunlun Mountains, Qinghai Province, restrains to probe the relationship of the deposits to the regional tectonic evolution. This paper documents the fission track method used to determine the ages of gold ore deposits in eastern Kunlun Mountains and considers the implication for the origin of the deposits.Eastern Kunlun Mountains is the northern part of the Qinghai—Tibet Plateau and is of three deep\|seated fault belts in about EW extension. This work mainly includes three gold ore districts. All of them, in the north of Mid\|Kunlun fault belt, belong to northern part of eastern Kunlun Mountains. The Yanjingou district, with geographical coordinate 96°00’E and 36°10’N, is located 60 km north of Hongqigou district . Both of them are large, typical tectonoalteration gold deposits and were formed in similar geological setting. Hongshuihe ore district is located 50 km east of Yanjingou district and includes tectonoalteration and magmatic cryptoexplosive gold deposits. Outcroped strata are dominantly Jinshuikou Group metamorphic rocks of Lower Proterozoic erathem. The occurrence area of igneous rocks, especially granitoid, accounts for about 90% in first two districts and become less in Hongshuihe district. The gold deposits occur in NW\|striking fault belts. The Rb\|Sr isochron age and K\|Ar isotopic age of Moyite relevant to the gold mineralization are respectively 228 25Ma and 207 1Ma. Rb\|Sr dating of diorite porphyrite is 209 09Ma. Sericite selected from Yanjingou orebody has 252 9Ma K\|Ar age. The ore in Hongqigou district has 197Ma K\|Ar age and 210Ma model age of Pb isotope of galena.

A New Method for Clay Mineral Analysis and Its Application in Geology

X-ray diffraction (XRD) peaks in a low-angle diffraction section of clayminerals, especially those of authigenic origin, have broadening and tailing features in shape.Using the five basic parameters, peak position, peak height, width, shape coefficient and asymmetry,to describe an XRD peak is more accurate, comprehensive and integrated than using only 3 of them,position, height and width. Following the concept of the five basic parameters of an XRD peak, theprogram Decoform proposed in this study provides more information in mineralogical analyses byfitting actual XRD profiles. In combination with the HW-IR plot, Decoform can he systematically andaccurately used in the comprehensive analyses of crystallinity, domain size, lattice strain andquantitative phase. It is also of value for the geological investigations of diagenesis,metamorphism, basin maturity, structural stress field and so on.

Metallic Mineral Resources Assessment and Analysis System Design

This paper presents the aim and the design structure of the metallic mineral resources assessment and analysis system. This system adopts an integrated technique of data warehouse composed of affairs processing layer and analysis application layer. The affairs processing layer includes multiform databases (such as geological database, geophysical database, geochemical database), while the analysis application layer includes data warehouse, online analysis processing and data mining. This paper also presents in detail the data warehouse of the present system and the appropriate spatial analysis methods and models. Finally, this paper presents the prospect of the system.

Data-Driven Discovery in Mineralogy: Recent Advances in Data Resources, Analysis, and Visualization

Large and growing data resources on the diversity, distribution, and properties of minerals are ushering in a new era of data-driven discovery in mineralogy. The most comprehensive international mineral database is the IMA database, which includes information on more than 5400 approved mineral species and their properties, and the mindat.org data source, which contains more than 1 million species/locality data on minerals found at more than 300 000 localities. Analysis and visualization of these data with diverse techniques—including chord diagrams, cluster diagrams, Klee diagrams, skyline diagrams, and varied methods of network analysis—are leading to a greater understanding of the co-evolving geosphere and biosphere. New data-driven approaches include mineral evolution, mineral ecology, and mineral network analysis—methods that collectively consider the distribution and diversity of minerals through space and time. These strategies are fostering a deeper understanding of mineral co-occurrences and, for the first time, facilitating predictions of mineral species that occur on Earth but have yet to be discovered and described.

Mineralogical characterization of copper sulfide tailings using automated mineral liberation analysis: A case study of the Chambishi Copper Mine tailings

As ore grades constantly decline,more copper tailings,which still contain a considerable amount of unrecovered copper,are expected to be produced as a byproduct of froth flotation.This research reveals the occurrence mechanism of copper minerals in typical copper sulfide tailings using quantitative mineral liberation analysis(MLA)integrated with scanning electron microscopy–energy dispersive spectroscopy(SEM–EDS).A comprehensive mineralogical characterization was carried out,and the results showed that almost all copper minerals were highly disseminated within coarse gangue particles,except for 9.2wt%chalcopyrite that occurred in the 160–180μm size fraction.The predominant copper-bearing mineral was chalcopyrite,which was closely intergrown with orthoclase and muscovite rather than quartz.The flotation tailings sample still contained 3.28wt%liberated chalcopyrite and 3.13wt%liberated bornite because of their extremely fine granularity.The SEM–EDS analysis further demonstrated that copper minerals mainly occurred as fine dispersed and fully enclosed structures in gangue minerals.The information obtained from this research could offer useful references for recovering residual copper from flotation tailings.

Use of Mineral Liberation Analysis (MLA) in the Characterization of Lithium-Bearing Micas

The capabilities and opportunities of the application of automated mineralogy for the characterization of lithium-bearing zinnwaldite-micas are critically assessed. Samples of a crushed greisen-type ore comprising mostly of quartz, topaz and zinnwaldite (Li-rich mica) were exposed to further comminution by cone crusher and high voltage pulse power fragmentation. Product properties were analyzed by using a Mineral Liberation Analyser (MLA) and the obtained mineralogical and mineral processing relevant parameters were carefully evaluated with special focus on the characteristics of zinnwaldite. The results illustrate that both samples contain a significant quantity of very fine particles that are products of comminution. The modal mineralogy in the different sieve fractions is characterized by the accumulation of minerals of low hardness in the finest fraction and the enrichment of topaz, having a high hardness, in the somewhat larger fractions. Based on the results of mineral association data for zinnwaldite, a displacement of the muscovite-quartz ratio, in comparison to the results of modal mineralogy, was observed by indicating good quartz-zinnwaldite boundary breakage and weak muscovite-zinnwaldite breakage. Liberation as well as mineral grade recovery curves indicate that fraction 1000 to +500 μm is most suitable for beneficiation. The results of this study demonstrate that SEM-based image analysis, such as MLA, can effectively be used to investigate and evaluate phyllosilicate minerals in a fast and precise way. It is shown that the results of MLA investigations, such as modal mineralogy, are in good agreement with other analytical methods such as quantitative X-ray powder diffraction.

Near-Infrared Spectroscopy Combined with Partial Least Squares Discriminant Analysis Applied to Identification of Liquor Brands

The identification of liquor brands is very important for food safety. Most of the fake liquors are usually made into the products with the same flavor and alcohol content as regular brand, so the identification for the liquor brands with the same flavor and the same alcohol content is essential. However, it is also difficult because the components of such liquor samples are very similar. Near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was applied to identification of liquor brands with the same flavor and alcohol content. A total of 160 samples of Luzhou Laojiao liquor and 200 samples of non-Luzhou Laojiao liquor with the same flavor and alcohol content were used for identification. Samples of each type were randomly divided into the modeling and validation sets. The modeling samples were further divided into calibration and prediction sets using the Kennard-Stone algorithm to achieve uniformity and representativeness. In the modeling and validation processes based on PLS-DA method, the recognition rates of samples achieved 99.1% and 98.7%, respectively. The results show high prediction performance for the identification of liquor brands, and were obviously better than those obtained from the principal component linear discriminant analysis method. NIR spectroscopy combined with the PLS-DA method provides a quick and effective means of the discriminant analysis of liquor brands, and is also a promising tool for large-scale inspection of liquor food safety.

Application of near-infrared spectroscopy for the rapid analysis of Lonicerae Japonicae Flos solution extracted by water

A rapid quantitative analytical method for three components of Lonicerae Japornicae Flos solution(Lonicera Japonica Thumb.)extracted by water was developed using near-infrared(NIR)spectroscopy and the partial least-squares(PLS)method.The NIR spectra of 81 samples collected from a production line were obtained.The concentrations of secologanic acid,chlorogenicacid and galuteolin were detemmined by using high-performance liquid chromatography-diodearray detection as the reference method.Several pretreatment methods for the NIR spectra wereusedi during PLS calibration.The most appropriate latent variable number of the PLS factor wasselected based on the standard error of cross-validation(SECV).The performance of the finalPLS models was evaluated according to SECV,standard error of predliction(SEP)and deter-mination coeficient(R^(2)).The compounds secologanic acid,chlorogenic acid and galuteolin hadSEP values of 0.030,0.061 and 1.668μg/mL,respectively and R^(2) values over 0.85.This workshows that NIR spectroscopy is a rapid and convenient method for the analysis of LoniceraeJaponicae Flos solution extracted by water.The proposed method can help in the application ofprocs analytical technology in the pha maceutical industry,particularly in tra ditional Chinesemedicine injections.

Discriminant Analysis of Liquor Brands Based on Moving-Window Waveband Screening Using Near-Infrared Spectroscopy

Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.

Visible and Near-Infrared Spectroscopy with Multi-Parameters Optimization of Savitzky-Golay Smoothing Applied to Rapid Analysis of Soil Cr Content of Pearl River Delta

Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters d, p, m and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEPV), relative root mean square error (R-SEPV) and correlation coefficients (RP, V) of prediction were 11.66 mg·kg-1, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.

Global Optimization of Norris Derivative Filtering with Application for Near-Infrared Analysis of Serum Urea Nitrogen

Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stability. A large-scale parameter cyclic and global optimization platform for Norris derivative filter (NDF) of three parameters (the derivative order: d, the number of smoothing points: s and the number of differential gaps: g) was developed with PLS regression. Meantime, the parameters’ adaptive analysis of NDF algorithm was also given, and achieved a significantly better modeling effect than one without spectral pre-processing. After eliminating the interference wavebands of saturated absorption, the modeling performance was further improved. In validation, the root mean square error (SEP), correlation coefficient (RP) for prediction and the ratio of performance to deviation (RPD) were 1.66 mmol?L-1, 0.966 and 4.7, respectively. The results showed that the high-precision analysis of SUN was feasibility based on NIR spectroscopy and Norris-PLS. The global optimization method of NDF is also expected to be applied to other analysis objects.

Analysis on Uranium Mineralization Potential of Late Yanshanian Granites in Sichuan of Sanjiang Area

The Sanjiang area is an important granite distribution area in China,except for South China,in which granites is complex and complete.Based on fully collecting date about it,this paper explores the significance of uranium

Near-Infrared Spectroscopy Combined with Absorbance Upper Optimization Partial Least Squares Applied to Rapid Analysis of Polysaccharide for Proprietary Chinese Medicine Oral Solution

Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L-1 and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.

Priority-sequence of mineral resources' development and utilization based on grey relational analysis method

Generally, the sequence decision of the development and utilization of Chinese mineral resources is based on national and provincial overall plan of the mineral resources. Such plan usually cannot reflect the relative size of the suitability of the development and utilization of mineral resources. To solve the problem, the paper has selected the gift condition, the market condition, the technological condition,socio-economic condition and environmental condition as the starting-points to analyze the influential factors of the priority-sequence of mineral resources' development and utilization. The above 5 conditions are further specified into 9 evaluative indicators to establish an evaluation indicator system. At last,we propose a decision model of the priority sequence based on grey relational analysis method, and figure out the observation objects by the suitability index of development. Finally, the mineral resources of a certain province in China were analyzed as an example. The calculation results indicate that silver(2.0057), coal(1.9955), zinc(1.9442), cement limestone(1.9077), solvent limestone(1.5624) and other minerals in the province are suitable for development and utilization.

Automated Mineral Liberation Analysis on a Multipurpose SEM

Ore grades are currently declining and mines are increasingly required to operate more efficiently in order to save costs and conserve resources. As a result, automated procedures to control and measure process efficiency have become popular: The demand for sustainable mining and metals processing is globally increasing. Mineral Liberation Analysis is a well established technique to analyse and optimize mining processes and its significance to process mineralogy studies and mineral & metallurgical processing has been widely reported. Dedicated systems consisting of an optimized scanning electron microscopes (SEM) and usually several X-ray detectors are an established solution. With the advent of large area SDDs (Silicon drift detector) and progress in stage automation on conventional SEMs, the speed of X-Ray acquisition is no longer a limiting factor. However, until now, the particle analysis packages on commercially available systems do not lend themselves to Mineral Liberation Analysis without significant modification. INCAMineral is a new solution for mineral liberation analysis which runs on conventional SEMs equipped with large area SDDs.