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Image semantic segmentation using deep learning algorithms plays a vital role in identifying different rock-forming minerals. In this paper, we employ the U-net model for its architecture that guarantees precise localization and efficient data utilization. We implement this deep learning model across two distinct datasets: (1) the first dataset from the ALEX Streckeisen website, and (2) the second dataset from the Gabal Nikeiba area, South Eastern Desert of Egypt. Our model exhibits excellent performance in both datasets, with an average accuracy of precision at 0.89 and 0.83, recall at 0.80 and 0.78, and F1 score at 0.82 and 0.79, respectively, helping in identifying and detecting rock-forming minerals in thin-section images. The model's most exceptional performance is clearly in eleven different basement rock-forming minerals with precision up to 0.89, recall at 0.80, and F1 score at 0.82 on average. This study is significant as it represents the key to identifying and detecting minerals in the thin sections of rock samples in Egypt and the Arabian–Nubian Shield as a whole. By significantly reducing analysis time and improving accuracy compared to manual methods, it revolutionizes geological research and resource exploration in the region. [ABSTRACT FROM AUTHOR]

Coprolites are relatively common trace fossils in Quaternary sites and are used to obtain a variety of information that goes from environment reconstruction to dating sites or recovering DNA among others. However, little attention is given to taphonomic processes undergone by the coprolites that might compromise their validity as sources of information. In this paper, we present the study of the Middle Pleistocene coprolites of Villanueva-1 from a taphonomic point of view and discuss the results of the analyses performed and how the taphonomic alterations identified have an effect on palaeoecological interpretations based on these fossils. Modifications prior to burial may be determined by direct observation of shape, colour, fractures and inclusions. Some diagenetic alterations can also be inferred from colour differences, but mostly require destructive analyses in order to identify the degree of chemical and structural changes that might interfere with content preservation, such as pollen, DNA, or organic carbon for dating purposes. [ABSTRACT FROM AUTHOR]

Sedimentary material sampled in the southwestern Kara Sea both directly in ice scours and on background surfaces undisturbed by ice scouring has been studied. Based on studies of the physical properties and lithomineralogical features of bottom sediments in the ice scours, the boundary of ice scouring impact (exaration contact) was identified. Based on the X-ray diffraction analysis of <0.001-mm fraction, the chlorite structure is sensitive to temperature in samples taken below this contact, in contrast to the overlying samples. Together with the results of microscopic studies of thin sections, this fact indicates the neoformation of chlorite. The presence of secondary chlorite in near-surface conditions can suggest the glaciodynamic impact (pressure) of iceberg keels on bottom sediments. Microstructures of the ice scour sediments differ both in different test sites of the study area and within the same scour, depending on the location of sampling point on the transverse profile of morphosculpture. [ABSTRACT FROM AUTHOR]

This study presents an in-depth archaeometric investigation of Iron Age ceramic assemblage dating from 950 to 750 BCE from the sanctuary at Polizzello Mountain, Sicily. The site, a key sanctuary utilized by indigenous communities for ritual activities, is examined for its strategic location, structural developments, pottery assemblages, and evidence of communal activities. The study employs petrographic analysis on thin sections, integrated with other analytical methods, to explore the technology behind pottery production. It investigates whether such production reflects a common technological knowledge shared by a broader community or if they represent a blend of different manufacturing traditions. The findings highlight that the pottery from Polizzello Mountain aligns with the well-established Sicilian tradition of combining calcareous components and grog, indicating a local tradition of pottery production with no significant compositional differences suggesting specialized production at the workshop level.

Abstract More than 60% of the world’s sedimentary rocks are mudrocks (Potter et al., 1980; Schieber, 1998; Potter, 2003; the term mudrock is favored here over mudstone because the latter term was used to characterize a limestone texture; Dunham, 1962). From a palaeontological perspective these are, compared to sandstones and limestones, heavily undersampled. The main reason for this is that mudrocks decay in surface exposures to small chips, which develop with sun/heat and rain into an awkward pulp. The decay of the mudstone concomitantly destroys all macrofossils which are not durable. This comprises fossils with an aragonitic or delicate calcitic shell unless they are preserved as pyritic or internal calcitic molds or preserved within calcareous concretions. Therefore, most of the fossils are not recorded in surface exposures. In addition, sedimentologic investigations of mudrocks are hampered because (i) compaction makes sedimentary structures hardly recognizableand (ii) good thin sections of mudrocks are exceedingly difficult to manufacture. For micropalaeontological investigations, mudrocks rich in organic material are especially difficult to process. Standard treatments with boiling water, sodium carbonate solution, or peroxide H2O2 generally fail to dissolve much of the sediment so that the fine fraction (and in mudrocks we usually need the 63μm-fraction) largely consists of clay particle aggregates. Yet there are methods to dissolve these aggregates. Otherwise, picking the microfossils would become extremely laborious. In this paper, some guidelines for successful palaeontological work in mudrocks are outlined. These are based on the author’s personal experience. Examples from Jurassic mudrocks of Switzerland/Europe show that such excavations can be very rewarding.

More than 60% of the world's sedimentary rocks are mudrocks (Potter et al., 1980; Schieber, 1998; Potter, 2003; the term mudrock is favored here over mudstone because the latter term was used to characterize a limestone texture; Dunham, 1962). From a palaeontological perspective these are, compared to sandstones and limestones, heavily undersampled. The main reason for this is that mudrocks decay in surface exposures to small chips, which develop with sun/heat and rain into an awkward pulp. The decay of the mudstone concomitantly destroys all macrofossils which are not durable. This comprises fossils with an aragonitic or delicate calcitic shell unless they are preserved as pyritic or internal calcitic molds or preserved within calcareous concretions. Therefore, most of the fossils are not recorded in surface exposures. In addition, sedimentologic investigations of mudrocks are hampered because (i) compaction makes sedimentary structures hardly recognizableand (ii) good thin sections of mudrocks are exceedingly difficult to manufacture. For micropalaeontological investigations, mudrocks rich in organic material are especially difficult to process. Standard treatments with boiling water, sodium carbonate solution, or peroxide H2O2 generally fail to dissolve much of the sediment so that the fine fraction (and in mudrocks we usually need the 63μm-fraction) largely consists of clay particle aggregates. Yet there are methods to dissolve these aggregates. Otherwise, picking the microfossils would become extremely laborious. In this paper, some guidelines for successful palaeontological work in mudrocks are outlined. These are based on the author's personal experience. Examples from Jurassic mudrocks of Switzerland/Europe show that such excavations can be very rewarding. [ABSTRACT FROM AUTHOR]

Image semantic segmentation using deep learning algorithms plays a vital role in identifying different rock-forming minerals. In this paper, we employ the U-net model for its architecture that guarantees precise localization and efficient data utilization. We implement this deep learning model across two distinct datasets: (1) the first dataset from the ALEX Streckeisen website, and (2) the second dataset from the Gabal Nikeiba area, South Eastern Desert of Egypt. Our model exhibits excellent performance in both datasets, with an average accuracy of precision at 0.89 and 0.83, recall at 0.80 and 0.78, and F1 score at 0.82 and 0.79, respectively, helping in identifying and detecting rock-forming minerals in thin-section images. The model’s most exceptional performance is clearly in eleven different basement rock-forming minerals with precision up to 0.89, recall at 0.80, and F1 score at 0.82 on average. This study is significant as it represents the key to identifying and detecting minerals in the thin sections of rock samples in Egypt and the Arabian–Nubian Shield as a whole. By significantly reducing analysis time and improving accuracy compared to manual methods, it revolutionizes geological research and resource exploration in the region.

Digital rock physics (DRP) has undergone significant advancements in the use of various imaging techniques to acquire three-dimensional volumes and images of rock samples for the computation of petrophysical properties. This study focuses on developing a DRP workflow using high-resolution thin section scans for computing porosity and permeability in cuttings samples. The workflow was tested on quarry sandstone plug samples and artificially generated pseudo-cuttings before applying it to real cuttings from oil and gas wells. The results show that the porosity and permeability values obtained through the DRP workflow are statistically equivalent to those obtained through conventional routine core analysis (RCAL). The workflow was also able to handle the presence of various lithologies in real cuttings samples. The study demonstrates the feasibility of obtaining porosity and permeability values in cutting samples using the DRP approach, offering a fast and cost-effective methodology that provides additional data and allows linking petrophysical properties to image data from the cuttings. [ABSTRACT FROM AUTHOR]

A thorough petrographic evaluation of aggregates from igneous rocks in terms of their alkali–silica reaction (ASR) potential is crucial in ensuring the durability and long-term performance of concrete structures, especially those where access to additional alkalis is possible, such as from de-icing agents. The aim of the research was to assess the potential reactivity of aggregates from igneous rocks, as only such aggregates are used for concrete airport pavements in Poland. Petrographic analysis was conducted to identify the reactive minerals in the aggregate, and it was extended by quantitative image analysis. The strained, microcrystalline and cryptocrystalline quartz were found to be reactive components but significantly differed in content. It was found that aggregates from igneous rocks were characterized by different susceptibility to ASR and that methods to mitigate the occurrence of ASR should be considered to be used in airfield concrete. A relationship between the content of analyzed reactive minerals and the expansion of mortar bars in AMBT, as well as of the concrete prism in the CPT method, was revealed. [ABSTRACT FROM AUTHOR]

The analysis of thin sections for lithology identification is a staple technique in geology. Although recent strides in deep learning have catalyzed the development of models for thin section recognition leveraging varied deep neural networks, there remains a substantial gap in the identification of ultra-fine-grained thin section types. Visual Transformer models, superior to convolutional neural networks (CNN) in fine-grained classification tasks, are underexploited, especially when dealing with limited, highly similar sample sets. To address this, we incorporated a dynamic sparse attention mechanism and tailored the structure of the Swin Transformer network. We initially applied a region-to-region (R2R) approach to conserving key regions in coarse-grained areas, which minimized the global information loss instigated by the original model's local window mechanism and bolstered training efficiency with scarce samples. This was then fused with deep convolution, and a token-to-token (T2T) attention mechanism was introduced to extract local features from these regions, facilitating fine-grained classification. In comparison experiments, our approach surpassed various sophisticated models, showcasing superior accuracy, precision, recall, and F1-score. Furthermore, our method demonstrated impressive generalizability in experiments external to the original dataset. Notwithstanding our significant progress, several unresolved issues warrant further exploration. An in-depth investigation of the adaptability of different rock types, along with their distribution under fluctuating sample sizes, is advisable. This line of inquiry is anticipated to yield more potent tools for future geological studies, thereby widening the scope and impact of our research. [ABSTRACT FROM AUTHOR]

Study of ground sections is the most used and, in some respects, still irreplaceable method for examination the microstructure of paleontological and many other hard and friable objects. At the same time, paleontological samples are relatively difficult for preparations of high-quality thin sections. Many techniques and means, particularly embedding media, have been proposed, but they are often hardly accessible, imperfect or insufficiently studied. A promising and easily accessible non-specialized medium, UV-curable acrylic adhesive (glue for glass) was tested for embedding and mounting of objects with diverse mechanical and optical properties. It shows notably good results, in particular durability, reliable adhesion, ease of use and lack of significant birefringence, which makes it especially valuable for polarized light microscopy. Properties of such adhesives are reviewed and compared with properties of epoxy resins and a number of other media. Disadvantages of the adhesives and ways to deal with them are also elucidated. In addition, broadly accessible tools and methods of sawing, embedding, grinding, mounting and other stages of the work are discussed. Efficiency of a number of grinding agents is measured. On the basis of all these results, a technique of making ground sections using easily accessible means was developed and described step by step. The technique was designed for fossil bones, but is applicable to diverse dry samples, including paleontological, neontological and geological ones.

Recent studies have demonstrated the potential of machine learning methods for fast and accurate mineral classification based on microscope thin sections. Such methods can be extremely useful to support geoscientists during the phases of operational geology, especially when mineralogical and petrological data are fully integrated with other geological and geophysical information. In order to be effective, these methods require robust machine learning models trained on pre-labeled data. Furthermore, it is mandatory to optimize the hyper-parameters of the machine learning techniques in order to guarantee optimal classification accuracy and reliability. Nowadays, deep learning algorithms are widely applied for image analysis and automatic classification in a large range of Earth disciplines, including mineralogy, petrography, paleontology, well-log analysis, geophysical imaging, and so forth. The main reason for the recognized effectiveness of deep learning algorithms for image analysis is that they are able to quickly learn complex representations of images and patterns within them. Differently from traditional image-processing techniques based on handcrafted features, deep learning models automatically learn and extract features from the data, capturing, in almost real-time, complex relationships and patterns that are difficult to manually define. Many different types of deep learning models can be used for image analysis and classification, including fully connected deep neural networks (FCNNs), convolutional neural networks (CNNs or ConvNet), and residual networks (ResNets). In this paper, we compare some of these techniques and verify their effectiveness on the same dataset of mineralogical thin sections. We show that the different deep learning methods are all effective techniques in recognizing and classifying mineral images directly in the field, with ResNets outperforming the other techniques in terms of accuracy and precision. In addition, we compare the performance of deep learning techniques with different machine learning algorithms, including random forest, naive Bayes, adaptive boosting, support vector machine, and decision tree. Using quantitative performance indexes as well as confusion matrixes, we demonstrate that deep neural networks show generally better classification performances than the other approaches. Furthermore, we briefly discuss how to expand the same workflow to other types of images and geo-data, showing how this deep learning approach can be generalized to a multiscale/multipurpose methodology addressed to the analysis and automatic classification of multidisciplinary information. This article has tutorial purposes, too. For that reason, we will explain, with a didactical level of detail, all the key steps of the workflow. [ABSTRACT FROM AUTHOR]

Abstract The grain‐size distribution of sediment particles is an important aspect of the architecture of submarine fans and lobes. It governs depositional sand quality and reflects distribution of particulate organic carbon and pollutants. Documenting the grain‐size distribution of these deep‐marine sedimentary bodies can also offer us an insight into the flows that deposited them. Submarine lobes are commonly assumed to linearly fine from an apex, meaning there should be a proportional relationship between grain size and distance from the lobe apex. However, not much detailed quantitative work has been done to test this hypothesis. Exposure of a 5 km long dip‐section of basin‐floor lobes in Clinoform 12, Battfjellet Formation, Spitsbergen, enable the study of basinward grain‐size evolution in lobe deposits. Furthermore, the dataset allows testing if there are any documentable grain‐size differences between lobe sub‐environments. For this purpose, the palaeogeography of Clinoform 12 was reconstructed and the youngest lobe, which was exposed in all collected logs, chosen to be evaluated for its grain‐size trends. Photographed thin sections of 66 rock samples were analysed to obtain quantitative grain‐size distributions. The results show that fining of lobe deposits occurs predominantly in the most proximal and most distal parts of the lobe, while the intermediate lobe, which is dominated by lobe off‐axis deposits, is characterised by a relatively consistent grain‐size range. Lobe sub‐environments show statistically distinct grain‐size distributions from lobe axis to lobe fringe. An explanation for these trends is the interplay of capacity and competence‐driven deposition with the grain‐size stratification of the flows. The outcomes of this study help to better understand the proximal to distal evolution of turbidity currents and their depositional patterns. They also provide important insights in reservoir potential of basin‐floor fans at lobe scale.

The authors present the first results of an archaeometric research project set up by the Rovereto Civic Museum Foundation in collaboration with MUSE–Trento Science Museum, aiming at analysing and comparing Roman plasters from different sites in order to highlight similarities and differences related to the preparation and realization of Roman wall renderings. The data concern the characterization of plaster samples from the Roman Villa of Isera and Ventotene (northern and central Italy) by means of a thin-section mineropetrographic examination under an optical microscope and a scanning electron microscope (SEM). [ABSTRACT FROM AUTHOR]

This study focuses on copper green glazes on the front and reverse schemes of a seventeenth-century harpsichord lid painting. The aim was to investigate the materials and techniques of the copper-based green paints and their brown discolouration, a phenomenon commonly encountered in glazes made with the pigment verdigris (basic and neutral copper acetate). The study summarises the historical materials and recipes for copper green glazes, and includes a review of hypotheses that have been proposed for discolouration, focusing on findings from investigations that have been conducted in laboratory environments into the chemical interactions between verdigris and linseed oil. Analyses, using optical microscopy, SEM-EDX, XRD, THM-Py-GC-MS and ATR-FTIR, were conducted on paint samples from the browned copper green glazes from the front and reverse of the painted lid. To link the laboratory studies with the information known from historical texts and technical analysis of the object, analysis was also conducted in tandem on reconstructions, comprising neutral copper acetate in linseed oil. These were made and previously studied as part of the MOLART project (1995–2000), based on historical paint recipes. The analysis of the MOLART reconstructions supports the idea of a correlation between pigment-medium interaction and oxidation. Results from analysis of the painted lid support the idea that artists used a range of copper-based pigments for green glazes besides copper acetate, and illustrate different techniques for the glazes used within the interior and exterior painted schemes. [ABSTRACT FROM AUTHOR]

Mineral segmentation in ceramic thin sections containing different minerals, in which there are no evident and close boundaries, is a rather complex process. The results of such a process are used in archaeology for analyzing the origin and manufacturing techniques of ancient ceramics. In this paper we present a methodology for the segmentation and analysis of thin sections of material segments and reaching some conclusions in a fully automatic way. We employ machine learning and computer vision techniques to analyze a video of the thin section sample, acquired under an optical microscope. When examined under polarized light, the color of segments may vary during sample rotation. This variation is due to the optical properties of the materials and it provides valuable information about the material inclusions in the sample. Using the video as our input, we perform an entire-video segmentation. To accomplish this task, we developed a hierarchical categorical mean-shift-based algorithm. Using the entire-video segmentation we examine the detected segments and gather statistical information about their sizes, shapes and colors and present an overall report about the sample. We tested the algorithm on nine specimens of ancient ceramics, taken from three different Mediterranean sites. The results show clear differences between the sites in the amounts, sizes and shapes of the segments present in the specimens. [ABSTRACT FROM AUTHOR]

Digital rock physics (DRP) has undergone significant advancements in the use of various imaging techniques to acquire three-dimensional volumes and images of rock samples for the computation of petrophysical properties. This study focuses on developing a DRP workflow using high-resolution thin section scans for computing porosity and permeability in cuttings samples. The workflow was tested on quarry sandstone plug samples and artificially generated pseudo-cuttings before applying it to real cuttings from oil and gas wells. The results show that the porosity and permeability values obtained through the DRP workflow are statistically equivalent to those obtained through conventional routine core analysis (RCAL). The workflow was also able to handle the presence of various lithologies in real cuttings samples. The study demonstrates the feasibility of obtaining porosity and permeability values in cutting samples using the DRP approach, offering a fast and cost-effective methodology that provides additional data and allows linking petrophysical properties to image data from the cuttings.

A thorough petrographic evaluation of aggregates from igneous rocks in terms of their alkali–silica reaction (ASR) potential is crucial in ensuring the durability and long-term performance of concrete structures, especially those where access to additional alkalis is possible, such as from de-icing agents. The aim of the research was to assess the potential reactivity of aggregates from igneous rocks, as only such aggregates are used for concrete airport pavements in Poland. Petrographic analysis was conducted to identify the reactive minerals in the aggregate, and it was extended by quantitative image analysis. The strained, microcrystalline and cryptocrystalline quartz were found to be reactive components but significantly differed in content. It was found that aggregates from igneous rocks were characterized by different susceptibility to ASR and that methods to mitigate the occurrence of ASR should be considered to be used in airfield concrete. A relationship between the content of analyzed reactive minerals and the expansion of mortar bars in AMBT, as well as of the concrete prism in the CPT method, was revealed.

The analysis of thin sections for lithology identification is a staple technique in geology. Although recent strides in deep learning have catalyzed the development of models for thin section recognition leveraging varied deep neural networks, there remains a substantial gap in the identification of ultra-fine-grained thin section types. Visual Transformer models, superior to convolutional neural networks (CNN) in fine-grained classification tasks, are underexploited, especially when dealing with limited, highly similar sample sets. To address this, we incorporated a dynamic sparse attention mechanism and tailored the structure of the Swin Transformer network. We initially applied a region-to-region (R2R) approach to conserving key regions in coarse-grained areas, which minimized the global information loss instigated by the original model’s local window mechanism and bolstered training efficiency with scarce samples. This was then fused with deep convolution, and a token-to-token (T2T) attention mechanism was introduced to extract local features from these regions, facilitating fine-grained classification. In comparison experiments, our approach surpassed various sophisticated models, showcasing superior accuracy, precision, recall, and F1-score. Furthermore, our method demonstrated impressive generalizability in experiments external to the original dataset. Notwithstanding our significant progress, several unresolved issues warrant further exploration. An in-depth investigation of the adaptability of different rock types, along with their distribution under fluctuating sample sizes, is advisable. This line of inquiry is anticipated to yield more potent tools for future geological studies, thereby widening the scope and impact of our research.

The grain‐size distribution of sediment particles is an important aspect of the architecture of submarine fans and lobes. It governs depositional sand quality and reflects distribution of particulate organic carbon and pollutants. Documenting the grain‐size distribution of these deep‐marine sedimentary bodies can also offer us an insight into the flows that deposited them. Submarine lobes are commonly assumed to linearly fine from an apex, meaning there should be a proportional relationship between grain size and distance from the lobe apex. However, not much detailed quantitative work has been done to test this hypothesis. Exposure of a 5 km long dip‐section of basin‐floor lobes in Clinoform 12, Battfjellet Formation, Spitsbergen, enable the study of basinward grain‐size evolution in lobe deposits. Furthermore, the dataset allows testing if there are any documentable grain‐size differences between lobe sub‐environments. For this purpose, the palaeogeography of Clinoform 12 was reconstructed and the youngest lobe, which was exposed in all collected logs, chosen to be evaluated for its grain‐size trends. Photographed thin sections of 66 rock samples were analysed to obtain quantitative grain‐size distributions. The results show that fining of lobe deposits occurs predominantly in the most proximal and most distal parts of the lobe, while the intermediate lobe, which is dominated by lobe off‐axis deposits, is characterised by a relatively consistent grain‐size range. Lobe sub‐environments show statistically distinct grain‐size distributions from lobe axis to lobe fringe. An explanation for these trends is the interplay of capacity and competence‐driven deposition with the grain‐size stratification of the flows. The outcomes of this study help to better understand the proximal to distal evolution of turbidity currents and their depositional patterns. They also provide important insights in reservoir potential of basin‐floor fans at lobe scale. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated the potential of machine learning methods for fast and accurate mineral classification based on microscope thin sections. Such methods can be extremely useful to support geoscientists during the phases of operational geology, especially when mineralogical and petrological data are fully integrated with other geological and geophysical information. In order to be effective, these methods require robust machine learning models trained on pre-labeled data. Furthermore, it is mandatory to optimize the hyper-parameters of the machine learning techniques in order to guarantee optimal classification accuracy and reliability. Nowadays, deep learning algorithms are widely applied for image analysis and automatic classification in a large range of Earth disciplines, including mineralogy, petrography, paleontology, well-log analysis, geophysical imaging, and so forth. The main reason for the recognized effectiveness of deep learning algorithms for image analysis is that they are able to quickly learn complex representations of images and patterns within them. Differently from traditional image-processing techniques based on handcrafted features, deep learning models automatically learn and extract features from the data, capturing, in almost real-time, complex relationships and patterns that are difficult to manually define. Many different types of deep learning models can be used for image analysis and classification, including fully connected deep neural networks (FCNNs), convolutional neural networks (CNNs or ConvNet), and residual networks (ResNets). In this paper, we compare some of these techniques and verify their effectiveness on the same dataset of mineralogical thin sections. We show that the different deep learning methods are all effective techniques in recognizing and classifying mineral images directly in the field, with ResNets outperforming the other techniques in terms of accuracy and precision. In addition, we compare the performance of deep learning techniques with different machine learning algorithms, including random forest, naive Bayes, adaptive boosting, support vector machine, and decision tree. Using quantitative performance indexes as well as confusion matrixes, we demonstrate that deep neural networks show generally better classification performances than the other approaches. Furthermore, we briefly discuss how to expand the same workflow to other types of images and geo-data, showing how this deep learning approach can be generalized to a multiscale/multipurpose methodology addressed to the analysis and automatic classification of multidisciplinary information. This article has tutorial purposes, too. For that reason, we will explain, with a didactical level of detail, all the key steps of the workflow.

In the late 1950s to mid-1960s publications regarding the Upper Palaeolithic and Epipalaeolithic sites from the Middle and Lower Bistrița Valley (Northeastern Romania) several raw material categories were acknowledged: Audia black schist and silicified glauconitic sandstone from the Audia Beds (Lower Cretaceous) opened on Hangu Valley; menilite from the Lower Oligocene deposits found between Bicaz and Piatra Neamț (Bisericani area); good quality flint of various colours from the Middle Prut Valley (Prut flint). This raw materials classification endured the changes faced after 1990 by the Romanian Palaeolithic research and remained in use until today. The current contribution tackles the reassessment of this classification by re-examining the thin section collection intended to back the initial raw material categories from Ceahlău Basin. Also, the bulletins of petrographic analysis for the legacy thin section collection and the associated archive documents were reviewed. This reassessment confirmed most of the raw materials recognised in the initial classification, highlighting the existence of at least 14 raw material categories and the absence of the Oligocene menilite. Through the way it has been presented here, the reassessment was directly linked to the Romanian Palaeolithic research history and impacted a well-established archaeological classification of lithic raw materials. [ABSTRACT FROM AUTHOR]

Abstract Microfractures in the coal matrix have complex spatial structure because of the joint effects of coalification and tectonism. The accurate modeling and characterization of microfractures directly affect mechanism analysis of coal rock fracturing and mining. In this study, taking the high‐rank coal in the north of Qinshui Basin, structural characteristics of microfracture in intact and tectonic coals were analyzed systematically using 2D thin section, 3D micro‐CT modeling and mercury intrusion based on digital image analysis and fractal theory. The result indicates that the response sensitivity of fractal parameters obtained from different methods to microfractures from two types of coal structures is different greatly. Single fractal dimension (Df) in tectonic coal is higher than that of intact coal. Specially, for 2D thin sections, the indicative effect on the Df of manually corrected images is better than that of automatically extracted and linear ones. Df has a positive correlation with the pixel‐based microfracture porosity, as well as generalized fractal parameters. Moreover, microfracture permeability based on the Cubic‐Law increases with the increase of Df. For 3D micro‐CT modeling, the classical Watershed algorithm cannot segment the spatial microfracture network, which, however, can be segmented and characterized by the self‐developed FracSC3D program. Spatial microstructural parameters including volume, surface and length at three‐axis directions meet bifractal characteristics. Specially, for 2D micro‐CT slices, with the increase of porosity, the multifractal spectrum width Δα also increased. Besides, the fractal parameter based on Menger model from mercury intrusion experiment can act as a good indicator for identifying microfractures, flow pores and diffusion pores.

Microfractures in the coal matrix have complex spatial structure because of the joint effects of coalification and tectonism. The accurate modeling and characterization of microfractures directly affect mechanism analysis of coal rock fracturing and mining. In this study, taking the high‐rank coal in the north of Qinshui Basin, structural characteristics of microfracture in intact and tectonic coals were analyzed systematically using 2D thin section, 3D micro‐CT modeling and mercury intrusion based on digital image analysis and fractal theory. The result indicates that the response sensitivity of fractal parameters obtained from different methods to microfractures from two types of coal structures is different greatly. Single fractal dimension (Df) in tectonic coal is higher than that of intact coal. Specially, for 2D thin sections, the indicative effect on the Df of manually corrected images is better than that of automatically extracted and linear ones. Df has a positive correlation with the pixel‐based microfracture porosity, as well as generalized fractal parameters. Moreover, microfracture permeability based on the Cubic‐Law increases with the increase of Df. For 3D micro‐CT modeling, the classical Watershed algorithm cannot segment the spatial microfracture network, which, however, can be segmented and characterized by the self‐developed FracSC3D program. Spatial microstructural parameters including volume, surface and length at three‐axis directions meet bifractal characteristics. Specially, for 2D micro‐CT slices, with the increase of porosity, the multifractal spectrum width Δα also increased. Besides, the fractal parameter based on Menger model from mercury intrusion experiment can act as a good indicator for identifying microfractures, flow pores and diffusion pores. Key Points: 3D microfracture network is segmented and characterized by the developed algorithm FracSC3DClassical watershed algorithm used to segment pore bodies in porous media cannot be used to segment 3D fracture surfaces in fractured media3D microfracture characteristic parameters and mercury intrusion porosimetry meet the dual fractal scaling rather than single fractal law [ABSTRACT FROM AUTHOR]

• The reactivity of sandstone and limestone to hydrogen is investigated. • The degree of mineral dissolution and precipitation induced by H 2 treatment is limited. • Minor changes are observed in the surface morphology and pore properties. • Insignificant alterations in helium gas and NMR porosities are reported. • Sandstone and carbonate rocks are expected to demonstrate high geochemical stability in the presence of H 2. Depleted oil and gas reservoirs have been widely studied for gas storage purposes such as carbon dioxide and methane, however, there are still some uncertainties when it comes to hydrogen operations. Understanding the geochemical interactions of hydrogen-rock-brine is a key factor for safe sub-surface hydrogen containment, due to the associated risks of altering the rock pore properties. Despite the recent interest in evaluating H 2 -rock interactions, there is limited knowledge on the reactivity of sandstone and carbonate rocks to hydrogen and the potential implications on pore structure. In this work, we experimentally treated sandstone and limestone samples with hydrogen at 75 °C and 1400 psi for an extended duration of 6 months. Analytical methods including optical microscope for thin sections, Nuclear magnetic resonance (NMR), and helium gas porosity analysis were conducted before and after the hydrogen treatment. The results confirm the occurrence of geochemical reactions between rock minerals and hydrogen, however, the level of mineral dissolution and precipitation is minimal, and only minor changes were observed on the surface morphology. Consequently, insignificant changes occurred in the pore properties of the samples; the weight of the samples did not exhibit significant changes (an average increase of 0.61 %), while the average reduction in porosity and pore volume of the samples did not exceed 6 %. NMR results show no notable changes in T 2 distribution times curves, the average increase in porosity values for all the samples (sandstone and limestone) did not exceed 5 % after 6 months of H 2 treatment, suggesting that no significant alterations occurred in the pore structure or rock geometry. We conclude that the geochemical reactions of the hydrogen-rock-brine system are very limited even after 6 months of hydrogen treatment, thus the suitability of sandstone and limestone rocks for hydrogen storage is promising. [ABSTRACT FROM AUTHOR]

Age and growth studies provide critical data for clam fishery management. Three aging techniques, thin sections and acetate peel replicas – which involve shell sectioning – and surface growth rings were used to estimate the age and growth of Chamelea gallina populations in the mid-western Adriatic Sea. Their results were compared to identify the most reliable and least time-consuming approach. There were no significant differences between the two shell sectioning techniques (χ2 = 4.66, df = 3, p = 0.198), which were described by the same von Bertalanffy (VBF) growth curve parameters (L8 = 43.9, k = 0.26, t0 = −0.84), whereas significantly different L8 and k values were found between the two shell sectioning techniques and surface growth rings (L8: χ2 = 13.62, df = 1, p < 0.001; k: χ2 = 9.18, df = 1, p < 0.002; these statistics refer to the comparison between acetate peels and surface growth rings). The latter approach proved unreliable and error-prone, as it underestimated age and overestimated the growth rate (L8 = 26.4, k = 1.91, t0 = −0.11). Although the thin sections and acetate peel techniques both provide reliable age and growth estimates, the former approach was less time-consuming. Our analyses demonstrated that shell growth is slower in the cold season and in older specimens and that it has slowed down over the past few decades.

Abstract Objective Our immediate objective is to test the data-suggested possibility that in-agarose gel bacterial propagation causes gel fiber dislocation and alteration of cell distribution. We also test the further effect of lowering water activity. We perform these tests with both Gram-negative and Gram-positive bacteria. Data are obtained via electron microscopy of thin sections, which provides the first images of both bacteria and gel fibers in gel-supported bacterial lawns. The long-term objective is analysis of the effects of in-gel propagation on the DNA packaging of phages. Results We find that agarose gel-supported cells in lawns of Escherichia coli and Lysinibacillus (1) are primarily in clusters that increase in size with time and are surrounded by gel fibers, and (2) sometimes undergo gel-induced, post-duplication rotation and translation. Bacterial growth-induced dislocation of gel fibers is observed. One reason for clustering is that clustering promotes growth by increasing the growth-derived force applied to the gel fibers. Reactive force exerted by gel on cells explains cell movement. Finally, addition to growth medium of 0.94 M sucrose causes cluster-associated E. coli cells to become more densely packed and polymorphic. Shape is determined, in part, by neighboring cells, a novel observation to our knowledge.

Ban Chiang () is an extensively studied archeological site in Northeast Thailand, Udon Thani Province, which became a UNESCO world heritage in 1992. Depending on their production period ceramic artefacts show characteristic patterns at the surface which may be interpreted as iconographic motifs for the site. Two ceramic samples, excavated in 2003, from different periods were re-investigated, previously studied by Tanthanuch W., Pattanasiriwisawa W., Somphon W., Srilomsak S. Synchrotron studies of Ban Chiang ancient pottery. Suranaree J. Sci Technol. 2011, 18, 15–28 who focussed on thermal firing and redox-conditions. Shards selected for this study were sample 5412-S6E15 dated from Bronze Age (ca. 1000–300 BC) with yellow-brown, paint-free surface and a younger sample 8027 from Iron Age (ca. 300 BC–200 AD) with red painted design carrying pictorial patterns typical for the Ban Chiang ceramics. The surface material and colour of both shards was studied in detail using optical reflectance, FTIR spectroscopy and X-ray powder diffraction. Thin sections were used to determine the thickness of the red paint and the elemental composition of the surface using an electron microprobe. Chemical composition of sample 5412-S6E15 consists as oxides of elements mainly of SiO2 and Al2O3 (representing ca. 59 and 20 wt. %) and that of the red colour of the youngest sample 8027 consists mainly of SiO2, Al2O3 and Fe2O3 (representing ca. 52, 13 and 13 wt. %), the average composition adjacent to the red painted area has ca. 72 wt. % SiO2, ca. 10 wt. % Al2O3 and only 2 wt. % Fe2O3. X-ray powder diffraction, FTIR spectroscopy and optical reflectance measurements confirm hematite in the mineralogical composition of the red pigment of shard 8027. [ABSTRACT FROM AUTHOR]

Alder dieback remains a major problem in European alder stands and its spread continues to threaten their existence. The causal agent of this disease is the so-called alder Phytophthora species complex, which includes the hybrid Phytophthora ×alni and its parental species P. uniformis and P. ×multiformis. Little is known about the survival of these Phytophthora species in alder. The aim of our investigations was to find out whether, and if so where, the pathogen survives. The subject of these studies was alder roots. Therefore, artificial infection studies and histological studies with P. ×alni and P. uniformis were carried out on seedlings of black alder (Alnus glutinosa). These histological studies revealed oogonia and oospores of P. ×alni and P. uniformis in different parts of the root tissue.

Digital image analysis has recently emerged as a powerful tool for the analysis of the ceramic thin sections. By producing quantitative data, it increases the usefulness of ceramic petrography to address archeological questions. Despite several works considering digital image analysis to study archeological ceramic materials, so far, no work has been proposed to evaluate the possibilities of optical microscopy (OM) image analysis for classification and modal analysis, knowing its advantages and drawbacks, as compared to scanning electron microscopy (SEM) image processing. In this work, we propose an algorithm to count the mineral inclusions correctly classified by OM image analysis with respect to SEM images. The proposed algorithm is based on a matching mechanism applied to the regions of interest (ROIs) detected in the OM images according to the corresponding ROIs as detected in the SEM images. Moreover, a comparison with point counting on the same OM images is also provided to evaluate the pros and cons of each method. Two Late Acacus (Mesolithic) potsherds (8900–4200 BP) are considered as case study for modal analysis to identify and classify quartz, feldspars, and carbonate aggregates as mineral inclusions. [ABSTRACT FROM AUTHOR]

Abstract Grain Size Distribution is one of the basic measurements for sediment classification. The conventional methods for grain size distribution include the sieve method, the laser diffraction method, and the point-count method. We aimed to develop a robust computer code that simulates these conventional methods. The code can measure grain size distribution on 2-D and 3-D binary images using a watershed algorithm to extract out individual grains, and using principal component algorithms to find the principal axes. The outputs include grain radius for different principal axes, grain volume, grain surface area, principal axes inclinations and azimuths, and the number of contacts for each grain. The calculated distribution can be volume-based, frequency-based, or grid-based. Digital microstructures used in this study include (1) identical sphere packs including a simple cubic pack and a Finney pack, and (2) natural rock geometry such as Berea sandstone, Castlegate sandstone, and Fontainebleau sandstone. Furthermore, we employed this code to provide additional value of information from μXCT images by using μXCT to create 2-D to 3-D model of the grain size distribution, solving what is commonly known as Wicksell's corpuscle problem. We showed that our workflow successfully models a generalized 2-D to 3-D grain size distribution for a particular set of natural rocks that we include in our study. We hope to be able to obtain more μXCT images in the future in order to create a universal model covering most types of natural rocks. Highlights • Robust codes to measure grain size distribution from thin-sections or μXCT images. • Distribution based on sieve method, laser diffraction method, and point-count method. • Model a generalized 2-D to 3-D grain size distributions. [ABSTRACT FROM AUTHOR]

Highlights • General single-sided laser peening cannot enhance thin sections without distortion. • Single-sided laser peening with suitable small spots can cause no distortion. • Single-sided laser peening can generate compressive residual stress on both sides. • The effect of spot size on distortion behaviors in laser peening has been revealed. Abstract Thin sections are widely used in industry and need surface hardening to improve their anti-fatigue properties. This study proposes an improved single-sided LP as an effective way for the surface hardening of thin sections with self-occlusion on one side to overcome the difficulty in double-sided LP. Controlled experiments are conducted on a few specimens with thin sections to investigate the distortion behavior after LP treatment with different process parameters. Finite element method is used to analyze the generation of geometry distortion and explain the difference between LP treatment with several process parameters. The results show that both laser intensity and spot size are of great concern in the geometry distortion after single-sided LP, generating different distortion directions. Single-sided LP with a suitable process parameter set of laser intensity and spot size can enhance specimens without distortion. Numerical model shows the generation of different distortion behaviors is highly related to the bending moment, which is calculated from plastic strain field. Besides, part of plastic strain produced by local deformation varies after LP treatment with different spot sizes, which generates different distortion profiles with the same laser intensity. Furthermore, compressive residual stress is induced on both sides of thin sections by single-sided LP treatment, which ensures the effectivity for the treatment of thin sections. [ABSTRACT FROM AUTHOR]

Amara West, built around 1300 BC, was an administrative centre for the pharaonic colony of Upper Nubia. In addition to producing hand- and wheel-made pottery, respectively, in Nubian and Egyptian style, Amara West also imported a wide range of ceramics from Egypt and the eastern Mediterranean. A scientific study of 18 Mycenaean-style ceramics was undertaken to study provenance and aspects of production technology. Neutron activation analysis (NAA) results show that the pots were imported from several workshops in Greece and Cyprus. Thin-section petrography and scanning electron microscopy, used with energy-dispersive spectroscopy (SEM-EDX), show that different recipes were used to make the fabrics and paints of Mycenaean ceramics, reflecting both technological choices and the range of raw materials used in the different workshops. The petrographic and SEM-EDX results support the NAA provenance attributions. [ABSTRACT FROM AUTHOR]

Acromyrmex fracticornis grass-cutting ants construct conspicuous chimney-shaped nest turrets made of intermeshed grass fragments. We asked whether turrets are constructed by merely piling up nearby materials around the entrance, or whether ants incorporate different materials as the turret develops. By removing the original nest turrets and following their rebuilding process over three consecutive days, age-dependent changes in wall morphology and inner lining fabrics were characterized. Micromorphological descriptions based on thin sections of turret walls revealed the building behaviors involved. Ants started by collecting nearby twigs and dry grass fragments that are piled up around the nest entrance. Several large fragments held the structure like beams. As a net-like structure grew, soil pellets were placed in between the intermeshed plant fragments from the turret base to the top, reinforcing the structure. Concomitantly, the turret inner wall was lined with soil pellets, starting from the base. Therefore, the consolidation of the turret occurred both over time and from its base upwards. It is argued that nest turrets do not simply arise by the arbitrary deposition of nearby materials, and that workers selectively incorporate large materials at the beginning, and respond to the developing structure by reinforcing the intermeshed plant fragments over time.

Increased knowledge of virus assembly-generated particles is needed for understanding both virus assembly and host responses to virus infection. Here, we use a phage T3 model and perform electron microscopy (EM) of thin sections (EM-TS) of gel-supported T3 plaques formed at 30 °C. After uranyl acetate/lead staining, we observe intracellular black particles, some with a difficult-to-see capsid. Some black particles (called LBPs) are larger than phage particles. The LBP frequency is increased by including proflavine, a DNA packaging inhibitor, in the growth medium and increasing plaque-forming temperature to 37 °C. Acidic phosphotungstate-precipitate (A-PTA) staining causes LBP substitution by black rings (BRs) that have the size and shape expected of hyper-expanded capsid containers for LBP DNA. BRs are less frequent in liquid cultures, suggesting that hyper-expanded capsids evolved primarily for in-gel (e.g., in-biofilm) propagation. BR-specific A-PTA staining and other observations are explained by α-sheet intense structure of the major subunit of hyper-expanded capsids. We hypothesize that herpes virus triggering of neurodegenerative disease occurs via in-gel propagation-promoted (1) generation of α-sheet intense viral capsids and, in response, (2) host production of α-sheet intense, capsid-interactive, innate immunity amyloid protein that becomes toxic. We propose developing viruses that are therapeutic via detoxifying interaction with this innate immunity protein.

The article defines the features and principles of researches of soilforming processes in the reference’s and destructive edaphotopes. It is concluded that particularly significant and important ecological role of soil-forming processes in the steppe of edafotop providing the needs of agriculture, forestry, water, utilities and other industries. The important soil-forming processes highlits in the era of growing human pressure on natural ecosystems.

The present work aims to characterize the reservoir properties of the upper Khuff Formation using integrated core plugs, petro-fabrics and Mercury injection analyses. A thirty four rock samples are picked up from the exposure of the upper Khuff Formation (Khuff A Member) at Al-Qassim province. These samples are subjected to a verity of laboratory measurements including core plugs, thin sections and mercury injection as matched with well log and crude oil analyses. Good porosity and permeability ranges (4–18% and 5–20 mD) are indicated, especially at the lower part with a uni-modal pore size distribution. The lithology is mainly dolomitic with minor limestone. Some fractures, cemented pores and dissolution process are indicated at the middle and upper parts of the section, respectively. Autopore-based mercury injection is performed to determine the volume of intrusion, touristy, pore size distribution and diameter. Total intrusion volumes of 0.352, 0.137 and 0.036 ml, threshold pressures of 127.44, 146.04 and 216.00 psi and tortuosities of 40.01, 75.19 and 60.26 are indicated for the analyzed samples, respectively. The results of the logging analyses are matched with the laboratory ones. Good hydrocarbons content is recognized in the middle part of the section. The analysis of crude oil sample indicates medium oil with high carbon content of 81.29 wt% and average specific gravity of 0.886 gm/cc. In conclusion, this integrated study indicates that the lower part of the Khuff A Member attains the best reservoir properties among the studied section. [ABSTRACT FROM AUTHOR]

Environmental conditions, such as temperature and relative humidity, impact the rate of evaporation, mechanical properties and durability of concrete. Thus, they have a direct effect on the development of transport properties. The purpose of this study is to investigate the effect of controlled environmental conditions on moisture retention, dielectric constant (DC), compressive strength, shrinkage, water sorptivity index, rapid chloride migration test (RCMT), microscopical analysis (thin sections) and electrical resistivity. The mortar specimens were prepared using Ordinary Portland Cement with two water-to-cement ratios of 0.42 and 0.52. The specimens cured in the controlled environments of 25, 46 and 65 °C for temperature, and 30% and 90% for relative humidity. The results showed that curing under higher temperature cause reduction in compressive strength and increase in the sorptivity index. Moreover, a great correlation between DC measurements and sorptivity, the RCMT and electrical resistivity was found. Higher relative humidity helped the performance of samples, considering the durability and mechanical properties. [ABSTRACT FROM AUTHOR]

The knowledge of the lithic sources makes it possible to approach the circulation of goods and populations on a regional scale. Recent research in the Andean and circum-andean lake basins of Santa Cruz province (Argentina) were aimed to characterize more specifically the regional lithic resources base (Espinosa et al. 2016). The results of these investigations in the Cardiel lake basin are presented here. Through prospecting and transects, four sectors were recorded with the availability of different lithic resources (basalts, tuffs, silica rocks). This new information allows us to broaden our knowledge of this basin and to re-evaluate proposals regarding land use. [ABSTRACT FROM AUTHOR]

This work is among the few studies conducted in Musawa sheet 56 NE, which is part of the basement complex rocks of TudunWulli - Kankia area. The study area lies between Latitude 12° 19' 00" to 12° 23' 00"N and longitude 7° 42' 00" to 7° 46' 00"N. Due to the continuous play of geologic processes on the earth, there is the need to continuously update the geology of the Nigeria basement complex as this has a very important economic implication especially in areas like mineral and groundwater exploration. Equally, less attention has been given to this sheet unlike other sheets within the zone. The study done in this area has revealed the various rock types and their geological characteristics: fieldrelation, macroscopic andmicroscopic features as well as structural elements. Results from the study shows that the area consists of granite, migmatitegneissandquartzite whichalldisplaya varietyofcolors, texturesandmineralogy. Carefulanalysis of the distinctive mineralogy, textures, optical and structural characteristics led to the nomenclature of the rocks. The migmatite-gneiss display two petrographic varieties base on their foliation: one with linear foliation of alternating light and dark color minerals, and the other with wave like foliation. While granite is generally fine to medium grained in texture. The dominant structural trend of joints and faults in the study area are NNE-SSW and NW-SE. All these trends are consistent with the general trends of the Nigeria basement rocks. A study of thin sections of the rocks under a petrological microscope reveals optical properties peculiar to each rock type. The type and nature of structural elements associated with the rocks together with their geometry reveal that the rocks have undergone more than one deformational event. The occurrence of numerous brittle and ductile structures shows that the area has a great potential for groundwater and mineralization. But the area still experience shortage of water for domestic purposes. [ABSTRACT FROM AUTHOR]