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This article explores the ways in which physical scientists, especially in the geosciences, are responding to calls to decolonise university curricula in current conjunctural conditions. It asserts that it is crucial not to strip decolonisation of its radical political potential and reduce it to an instrumental Equity, Diversion and Inclusion (EDI) initiative. Geoscientists in higher education who wish to decolonise their curricula must also pay attention to epistemological pluralism, politics, and colonial violence and free themselves from Eurocentric legacies of positivism, universality and objectivity. They must also make the turn to social theory, in ways that address the politics of geologic matter and the modes of violence that geoscientific practice and knowledge reproduce. Engaging with curricular decolonisation has potential not only to arrest the decline being experienced by the geosciences, but to make the forced neoliberal mergers between geography and geology less painful and more intellectually productive. This article explores the ways in which physical scientists, especially in the geosciences, are responding to calls to decolonise university curricula in current conjunctural conditions. It asserts that geoscientists who wish to decolonise their curricula must pay attention to epistemological pluralism, politics, and colonial violence and free themselves from Eurocentric legacies of positivism, universality and objectivity. Engaging with curricular decolonisation has potential not only to arrest the decline being experienced by the geosciences, but to make the forced neoliberal mergers between geography and geology less painful and more intellectually productive. [ABSTRACT FROM AUTHOR]

Interpretation of vertical electrical sounding (VES) data is inherently difficult due to its ambiguity and non-linear characteristics. Conventional least square-based methods rely on a well-defined apriori model, constrained by ground information (available borehole logs and field observations of exposed lithological sections) for meaningful interpretations. In this work, a back-propagation neural network-based model was developed to estimate layer resistivities and thickness from given apparent resistivities. The model was trained and validated on noise-infused synthetic datasets. Since the effectiveness and generalisation of any model depend on its hyperparameter settings, we investigated effective methods for estimating hyperparameters such as learning rate, momentum, model architecture and learning rate scheduling parameters. It is well known that the optimal values of hyperparameters are not entirely independent of each other. Thus, any change in one hyperparameter changes the optimal range of all other hyperparameters, and thus, tuning any hyperparameter individually is futile. This warrants a joint hyperparameter tuning along with network architecture, which was carried out using a modified version of meta-heuristic black hole algorithm. The modifications include randomly flipping one or more coordinates of the population stars (solutions) whose cost function was above a threshold value decided by a mutation rate parameter. This helped in boosting the exploration capability of the algorithm and prune trajectories with higher cost functions. It is demonstrated that with a finely tuned neural network model, reasonable resistivity model parameters which interpret the ground conditions fairly well could be obtained. The model was tested on resistivity-sounding data with associated borehole lithologs and was found to be giving reasonable results. The same model was used to estimate the overburden thickness consisting of topsoil and deposited silts in Bhadradri–Kothagudem district, India. The layer thickness was consistent with those seen in cutbanks in the area. The methods of optimal hyperparameter set estimation are not exclusive to this model and can be used to train models accomplishing other geophysical tasks. [ABSTRACT FROM AUTHOR]

We examined data from the American Geophysical Union (AGU), the world's largest earth and space science society, to characterize demographics of multiple milestones in a biogeoscientists' career. Geoscientists of color and White women make up a smaller proportion of those participating in activities critical to transitioning from student to professional (submitting manuscripts, getting published, and receiving review invitations) in comparison to White men. Gender parity for biogeoscientists appears within reach at earlier career stages, with 37% of AGU Biogeosciences members and 41% of Biogeosciences attendees at the Fall Meeting identifying as women in 2020. The demographics of those successfully completing activities required for career advancement, that is, publishing and reviewing with Journal of Geophysical Research and Global Biogeochemical Cycles, two biogeoscience journals, illustrate more progress is needed. A large majority of manuscripts were submitted by men (73%), many of which have no co‐authors that identify as women or non‐binary geoscientists. Further, our communities' bias of who we suggest as reviewers, results in 85% of the reviewer invites going to White geoscientists and 63% going to men. Thus, while representation of diverse communities has improved in some areas, barriers to publishing result in authorship not reflective of society: only 25% of accepted manuscripts were led by self‐identified geoscientists of color and fewer than 5% were led by women geoscientists of color. It is critical that efforts to diversify move beyond gender, to ensure that scientists of color are also afforded the access and opportunity needed to thrive as biogeoscientists. Plain Language Summary: The geosciences remain one of the least diverse STEM fields. We use data from the American Geophysical Union (AGU), the largest scientific society for earth and space scientists, to characterize the demographics of scientists participating in scientific publication and conference activities. We used information provided on biogeoscientists' gender, race and/or ethnicity, and age to illustrate representation trends reached early in one's career (attending a scientific meeting), at career development transitions points (publishing), and in the later more established phase of one's career (invitation to peer review). We found that while the gender gap between people that identify as men and those that identify as women is closing at early career milestones, like that of AGU membership and conference attendance, we do not see this same progress at more advanced career milestones, such as publishing and reviewing. Biogeoscientists of color continue to be overlooked at all career stages; however we were limited in our ability to draw conclusions about race and ethnicity given a scarcity of representation from ethnically or racially diverse groups within the data provided. Key Points: Women make up a larger fraction of American Geophysical Union (AGU) Biogeosciences members and meeting attendees as compared to AGU and the Fall Meeting overallBiogeosciences manuscript submissions (73%) and invited reviewers (69%) are dominated by geoscientists identifying as menWhite geoscientists enjoy higher acceptance rates (66%) and received the majority (85%) of reviewer invites [ABSTRACT FROM AUTHOR]

This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences①.

This is a systematic literature review of the application of machine learning (ML) algorithms in geosciences, with a focus on environmental monitoring applications. ML algorithms, with their ability to analyze vast quantities of data, decipher complex relationships, and predict future events, and they offer promising capabilities to implement technologies based on more precise and reliable data processing. This review considers several vulnerable and particularly at-risk themes as landfills, mining activities, the protection of coastal dunes, illegal discharges into water bodies, and the pollution and degradation of soil and water matrices in large industrial complexes. These case studies about environmental monitoring provide an opportunity to better examine the impact of human activities on the environment, with a specific focus on water and soil matrices. The recent literature underscores the increasing importance of ML in these contexts, highlighting a preference for adapted classic models: random forest (RF) (the most widely used), decision trees (DTs), support vector machines (SVMs), artificial neural networks (ANNs), convolutional neural networks (CNNs), principal component analysis (PCA), and much more. In the field of environmental management, the following methodologies offer invaluable insights that can steer strategic planning and decision-making based on more accurate image classification, prediction models, object detection and recognition, map classification, data classification, and environmental variable predictions.

The sedimentary sequence of the Ninama Basin is associated with the latest phase of the continental Deccan volcanism of the Indian peninsula. It occurs as inter-, intratrappeans with a 39-m thick sequence comprising Sukhbhadar Formation and Ninama Limestone. The investigation aims to reconstruct its depositional setting based on the lithofacies and inorganic geochemistry to understand the influence of paleosalinity, paleoredox, paleodepth, provenance and paleoclimate on the sedimentation pattern. It is characterized by clastic and chemically formed rocks, including shale, mudstone, siltstone, sandstone and limestone. Facies analysis has revealed seven lithofacies, amongst which four are clastic facies, shale (SH), calcareous shale (CSH), silty mudstone (SM) and lithic greywacke (LGW), and three are carbonate facies, namely, grey-black limestone (GBL), cherty limestone (CL) and marlite (ML). Using geochemical analysis of major oxides and trace elements, ratios of Ca/(Ca+Fe), Sr/Ba, V/(V+Ni), V/Cr, Fe/(Ca+Mg), Ti/Al, Na/K, K/(Fe+Mg), CIA-K and MAP were determined and used to interpret and note the changes in the depositional system. The combined results of the lithofacies and geochemistry indicate that the deposition occurred in three phases. Phase 1 is characterized by high energy conditions in the shallow to moderate depth brackish-saline lake with oxic to dysoxic conditions; Phase 2 is characterized by anoxic deep fresh to the brackish water basin; and Phase 3 is characterized by semiarid conditions, saline, anoxic waters, high evaporation leading to shallowing of the lake, and low to moderate terrestrial input. This lacustrine basin in the paleotopographic low of the Deccan Volcanic Province is characterized by distinct lithology governed by various depositional parameters. A composite depositional model is constructed for the Ninama Basin, reflecting three phases of evolution that are dominantly controlled by the paleoenvironment. Research highlights: The present study focuses on lithofacies and inorganic geochemical analysis of Ninama paleolake sediments, Saurashtra intertrappeans, to interpret their paleosalinity, paleoredox, water depth, provenance, detrital influx, and paleoclimate. Phase 1 deposition was initiated in paleotopographic low of Deccan Traps, in an oxic–dysoxic, high-energy turbulent brackish water environment, in humid conditions. Phase 2 characterizes fine-grained clastic facies deposited in anoxic, fresh-brackish, deep lake waters in humid conditions. Phase 3 marks the shallowing, evident by carbonate facies with low-moderate terrestrial input deposited in saline and anoxic paleolake in semiarid conditions with high evaporation and low-moderate precipitation. The Deccan Traps have influenced the paleolake intertrappean sequence. [ABSTRACT FROM AUTHOR]

This is a systematic literature review of the application of machine learning (ML) algorithms in geosciences, with a focus on environmental monitoring applications. ML algorithms, with their ability to analyze vast quantities of data, decipher complex relationships, and predict future events, and they offer promising capabilities to implement technologies based on more precise and reliable data processing. This review considers several vulnerable and particularly at-risk themes as landfills, mining activities, the protection of coastal dunes, illegal discharges into water bodies, and the pollution and degradation of soil and water matrices in large industrial complexes. These case studies about environmental monitoring provide an opportunity to better examine the impact of human activities on the environment, with a specific focus on water and soil matrices. The recent literature underscores the increasing importance of ML in these contexts, highlighting a preference for adapted classic models: random forest (RF) (the most widely used), decision trees (DTs), support vector machines (SVMs), artificial neural networks (ANNs), convolutional neural networks (CNNs), principal component analysis (PCA), and much more. In the field of environmental management, the following methodologies offer invaluable insights that can steer strategic planning and decision-making based on more accurate image classification, prediction models, object detection and recognition, map classification, data classification, and environmental variable predictions. [ABSTRACT FROM AUTHOR]

Human existence and progress hinge on sustainability and resilience, especially in the Anthropocene Era, where the diversity of nature plays a critical role. Central to this endeavor is the realm of geoethics, which not only reshapes the role of geosciences but also fosters the development of ethical behavior and practices in our interaction with the Earth. This paper presents a conceptual framework that integrates the seemingly disparate domains of geoethics, geoenvironmental education, and the sense of place. By conducting a systematic review using the keywords "Geoethics AND Education" and "Geoethics AND place" across global databases, including Scopus, Web of Science, ProQuest, and JSTOR, up to October 2023, we seek to uncover evidence illuminating the potential connections between these concepts. Out of n = 98 records identified, n = 22 met the eligibility criteria for inclusion in our review. Our findings reveal a growing scientific interest in the spectrum of geoethics over the last decade, with diverse perspectives related to concerns about geoeducation. We propose that future research should focus on expanding the scope of geoethics across various disciplines, emphasizing the importance of human ethos, socio-eco responsibility, and ethical considerations in geological heritage and geoconservation management. Geoenvironmental education emerges as a crucial avenue for advancing geoethics, while the multifaceted outcome of the sense of place offers a promising pathway for standardizing and correlating these fields effectively. [ABSTRACT FROM AUTHOR]

This study aims to analyze sinkholes by applying QGIS, mapping and comparing the occurrences with existing natural patterns to observe the cause of the occurrence and the solution. Sinkholes are topographic depressions that appear when the underlying bedrock weathers down, commonly found in sedimentary bedrock. They typically form due to drastic changes in groundwater levels. In urban areas, sediments may also be flushed out due to leaks in underground water pipes, increasing sinkhole formation. This study collected data on 41 sinkhole incidents in South Korea. The latitude and longitude of each incident were manually obtained and cross-checked. The locations were also classified by region to indicate whether they were considered rural or urban. The data was put into a spreadsheet and mapped using QGIS, and waterways were imported from OpenStreetMap (OSM) data and refined. The resulting map provides spatial insights into the distribution of sinkhole incidents in relation to waterways and sedimentary rocks. Whereas rural sinkholes tend to occur in areas with sedimentary rock as its bedrock material during summer when precipitation levels are high, sinkholes around urban areas are related to many human disturbances. By identifying patterns of sinkhole occurrences, the aim is to predict the formation of sinkholes to prevent catastrophic losses. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Correlative light and electron microscopy (CLEM) is an advanced imaging approach that faces critical challenges in the analysis of both materials and biological specimens. CLEM integrates the strengths of both light and electron microscopy, in a hardware and software correlative environment, to produce a composite image that combines the high resolution of the electron microscope with the large field of view of the light microscope. It enables a more comprehensive understanding of a sample's microstructure, texture, morphology, and elemental distribution, thereby facilitating the interpretation of its properties and characteristics. CLEM has diverse applications in the geoscience field, including mineralogy, petrography, and geochemistry. Despite its many advantages, CLEM has some limitations that need to be considered. One of its major limitations is the complexity of the imaging process. CLEM requires specialized equipment and expertise, and it can be challenging to obtain high-quality images that are suitable for analysis. In this study, we present a CLEM workflow based on an innovative sample holder design specially dedicated to the examination of thin sections and three-dimensional samples, with a particular emphasis on geosciences. [ABSTRACT FROM AUTHOR]

Achieving a successful energy transition requires society to deploy as many technologies as possible, rather than relying on one single technology to be the ‘magic bullet’. However, there are characteristics that make this transition more challenging than previous transitions in terms of its scope. These challenges include the wide range of sustainable technologies involved and the time constraints. For this research the importance of carbon capture and storage (CCS) and hydrogen technologies for the decarbonization process was analysed, including the main challenges that their large-scale implementation is facing from a subsurface perspective. The ongoing role that fossil fuels play, as well as how the hydrocarbon industry can facilitate the current transition, must also be considered. The common denominator in the analysis is the critical position of Earth sciences in discovering, characterizing, and sustainably utilizing subsurface resources. Geoscientists are essential for providing communication and cooperation between scientists and stakeholders who use, manage and preserve the subsurface. The success of CO2 and hydrogen storage, as part of the climate change mitigation strategies, and the eventual phase-out of fossil fuels ultimately depends on the sustainable development of the subsurface.

The importance of empirical versus theoretical laws is a controversial issue in many scientific fields, the latter being generally accepted and the relevance of which is not discussed here. As in other areas, there are well-known theoretical and empirical formulas in geosciences that do not adequately represent the reality of a given phenomenon. Quantitative comparison of geophysical and petrophysical results with data from the other multiple fields that comprise the geosciences compels a high exigency to avoid discontinuities in existing relationships. However, the proposal of new empirical laws that more accurately reflect a given phenomenon is often considered insufficient to contradict existing formulas. The aim of this work is to defend the development of new empirical laws by showing that they constitute a true model of analysed behaviour if certain criteria are followed. This defence is especially needed when non-linearisable functions are required to fit the empirical data. To achieve this aim, this study shows the established algebraic function as a function of a single variable, whose main advantage is its application to phenomena of a geological nature that show two differentiated behaviours as the variable x is increased. A series of five examples of different phenomena related to geosciences is selected to demonstrate the level of accuracy that new empirical laws can reach in contrast to the widely accepted historical relationships. [ABSTRACT FROM AUTHOR]

In 2019, GeoScienceWorld was actively planning to bring a large content and data repository, that includes a significant proportion of highly valued Grey Literature, into our existing collection of 50+ peer-reviewed journals and over 2300 books in the geosciences. Due to various external situations, including the impacts of the COVID-19 pandemic, and an absence of communityaccepted standards for Grey Literature publishing, this project has stalled. GeoScienceWorld continues to investigate opportunities to bring original datasets, as well as other collections of Grey Literature, predominantly in the form of partner societies' conference proceedings and related conference materials, into our traditional research platform. We are also in the early stages of planning for a new research tool that will be truly content agnostic in bringing research and valuable insights to our primary end-user stakeholders, researchers, whether in academia or industry. As an organization, GeoScienceWorld is further implementing an Agile mindset and development philosophy to bring increasingly useful, and timely, resources to our stakeholder groups. A key ceremony of all truly Agile development processes is the Retrospective. In this paper, I review the initial aims of the project to incorporate a large grey dataset into our traditional scholarly literature platform and provide reflections on how both GeoScienceWorld and the wider Grey Literature community can move forward to bring such valuable datasets to audiences that both want and need, such content to advance their research. For each element of the initial project, I ask the following Agile Retrospective questions:  What did we do well?  What could we have done better?  What have we learned?  What are we still puzzled by? As a result of applying these questions to the initial project, I will present recommendations that both inform GeoScienceWorld's future integration and presentation of Grey Literature, as well as offer a clearer path toward greater Grey Literature acceptance within traditional scholarly platforms such as ours. [ABSTRACT FROM AUTHOR]

Efforts to diversify STEM fields have not completely eliminated higher rates of women leaving certain science, technology, engineering, and mathematics (STEM) disciplines, such as geosciences. A diverse mentorship network is linked to persistence in STEM among college students, but little is known about how it leads to persistence. In particular, does a student's sense of belonging mediate the relationship between the diversity of one's mentor network and persistence in a field? This longitudinal study investigated whether students' university sense of belonging mediates the relationship between the diversity of mentor networks and interest in geoscience. 253 college women in STEM majors from nine U.S. universities reported on the diversity of their mentor networks, university belongingness, and interest in geoscience from Spring 2018 to Spring 2019. Consistent with our hypotheses, mediation analysis revealed a statistically and practically significant indirect effect of the diversity of mentor networks on interest development through university belonging. [ABSTRACT FROM AUTHOR]

Abstract: Climate models calibrated exclusively with observations from the 19th through 21st centuries are unsuitable for assessing many important hypotheses about the future. Many systems in the modern climate are expected to cross dynamic thresholds in the near future, requiring more than the instrumental record for adequate calibration. In this paper I argue that paleoclimate analogues from earth’s past can mitigate this threshold problem, even if the modern climate exhibits features that make it historically unique. While this requires that paleoclimatologists be increasingly discriminate in the past systems they target for modern analogues, the upshot is a practice of climate model construction that improves the reliability of future projections. All of this is achieved by integrating features of past climate systems discovered by the study of earth deep in the past. My analysis synthesizes important empirical work done by climate modelers and paleoclimatologists with relevant philosophical work on analogical reasoning in science. [ABSTRACT FROM AUTHOR]

As an important branch of computed tomography (CT), industrial CT is used widely in many fields, such as aerospace, military industry, and geological analysis fields, because of its advantages of high resolution, repeatability, and wide detection range. On the basis of thorough investigation and study, this paper summarizes three typical industrial CT technologies (i.e., seismic wave CT, resistivity CT, and electromagnetic wave CT) as well as the comprehensive geophysical exploration methods used in the geosciences. The current applications of industrial CT in pore structure studies, gas hydrate studies, digital core construction, and geological utilization and storage of carbon dioxide are introduced. The development trend of industrial CT in the geosciences is also discussed.

As a result of the continuous growth in the amount of geological data, machine learning (ML) offers an opportunity to contribute to solving problems in geosciences. However, digital geology applications introduce new challenges for machine learning due to the unique geoscience properties encountered in each problem, requiring novel research in ML. This paper proposes a novel machine learning method, entitled "Partial Decision Tree Forest (PART Forest)", to overcome these challenges introduced by geoscience problems and offers potential advancements in both machine learning and geoscience disciplines. The effectiveness of the proposed PART Forest method was illustrated in mineral classification. This study aims to build an intelligent ML model that automatically classifies the minerals in terms of their crystal structures (triclinic, monoclinic, orthorhombic, tetragonal, hexagonal, and trigonal) by taking into account their chemical compositions and their physical and optical properties. In the experiments, the proposed PART Forest method demonstrated its superiority over one of the well-known ensemble learning methods, random forest, in terms of accuracy, precision, recall, f-score, and AUC (area under the curve) metrics. [ABSTRACT FROM AUTHOR]

Reconstruction of geological images using partial measurement is one of the most important topics in geosciences. In many methods, this is done using training images and very complex models, which increase the computational complexity. In the first part of the article, a simple method based on spatial domain filters, such as median and mean filters is presented in order to reconstruct geological images. One of the most significant characteristics of this method is that it does not need the training image; moreover, its computational complexity is less than the other advanced methods. Via this method, it is easy to reconstruct binary, continuous, and three-dimensional images. The results show that the reconstruction accuracy of the proposed method is also acceptable. In the second part of the article, in order to introduce quantum computing to geosciences and encourage researchers to work on this issue, a quantum median filter is proposed to reconstruct geological images. According to the results, this method has much less computational complexity than classical methods, such as DS. Also, its results are acceptable in terms of reconstruction rate. Due to the high speed of quantum algorithms and the widespread use of quantum computers in the near future, it is necessary for researchers in this field to become more familiar with quantum computing. [ABSTRACT FROM AUTHOR]

This paper explores the concept of geoethics and its application in the professional practice of geosciences. Geoethics involves research and reflection on the values and principles that underpin appropriate behaviours wherever human actions interact with the earth system. It advocates for solutions to the problems of human-Earth interaction and contributes to protecting humanity and citizens in the professional field and everyday life. After evaluating the common geoethical problem in Latin America, provide examples from three South American countries: Peru, Chile and Brazil. The synergistic action of the geoscientific community in promoting a geoethical framework is discussed. The need for transparent, quantitative, rational and repeatable analyses is highlighted to ensure high professionalism in conducting studies. The importance of providing role models for young and beginning geoscientists and correctly disseminating geoscientific information to the public is further emphasized. The ability to communicate effectively is a fundamental requirement to train engineers, geologists and geoscientists capable of addressing global issues such as environmental management, geological hazards, and energy transition. Additionally, the implementation of geoethics in geological engineering and geoscience careers is proposed to promote social and environmental responsibility among young graduates and scientists starting their careers to prevent unethical professional practices and improve the visibility of geosciences and its benefits to society. The article concludes by calling for the involvement of geoscientists in public policies for the protection of geological heritage and the promotion of geoethical values, as well as the creation of a professional group to develop and promote geoscience didactics to improve educational quality in the field. [ABSTRACT FROM AUTHOR]

The conducted review presents the possibility of using artificial neural networks in sectors related to environmental protection, agriculture, forestry, land uses, groundwater and bathymetric. Today there is a lot of research in these areas with different research methodologies. The result is the improvement of decision-making processes, design, and prediction of certain events that, with appropriate intervention, can prevent severe consequences for society. The review shows the capabilities to optimize and automate the processes of modeling urban and land dynamics. It examines the forecasts of assessment of the damage caused by natural phenomena. Detection of environmental changes via the analysis of certain time intervals and classification of objects on the basis of different images is presented. The practical aspects of this work include the ability to choose the correct artificial neural network model depending on the complexity of the problem. This factor is a novel element since previously reviewed articles did not encounter a study of the correlation between the chosen model or algorithm, depending on the use case or area of the problem. This article seeks to outline the reason for the interest in artificial intelligence. Its purpose is to find answers to the following questions: How can artificial neural networks be used for spatial analysis? What does the implementation of detailed algorithms depend on? It is proved that an artificial intelligence approach can be an effective and powerful tool in various domains where spatial aspects are important. [ABSTRACT FROM AUTHOR]

With the rapid expansion in big data and artificial intelligence (AI), Earth sciences are undergoing unprecedented advances in data processing and interpretation techniques, as well as in facilitating data-driven discoveries of complex Earth systems. This special collection explores scientific research related to data-driven discoveries in geosciences and provides a timely presentation of progress in developments and/or applications of AI and big data approaches to multiple aspects of geosciences. These include geohazards monitoring, mineral resource exploration, and environmental assessments. We hope this collection will inspire researchers and will transform the work undertaken in the field of data-driven Earth science. While many challenges remain, including the formidable tasks of transforming the deluge of geoscience data into useable information and furthering knowledge via cutting-edge AI techniques, we envision that data-driven discovery will revolutionize conventional methods of observation, analysis, modeling, and prediction in geosciences, and will further advance scientific understanding of our complex Earth system. [ABSTRACT FROM AUTHOR]

In a period in which climate change is significantly varying rainfall regimes and their intensity all over the world, river-flow prediction is a major concern of geosciences. In recent years there has been an increase in the use of deep-learning models for river-flow prediction. However, in this field we can observe two main issues: i) many case studies use similar (or the same) strategies without sharing the codes, and ii) the application of these techniques requires good computer knowledge. This work proposes to employ a Google Colab notebook called CleverRiver, which allows the application of deep-learning for river-flow predictions. CleverRiver is a dynamic software that can be upgraded and modified not only by the authors but also by the users. The main advantages of CleverRiver are the following: the software is not limited by the client hardware, operating systems, etc.; the code is open-source; the toolkit is integrated with user-friendly interfaces; updated releases with new architectures, data management, and model parameters will be progressively uploaded. The software consists of three sections: the first one enables to train the models by means of some architectures, parameters, and data; the second section allows to create predictions by using the trained models; the third section allows to send feedback and to share experiences with the authors, providing a flux of precious information able to improve scientific research. [ABSTRACT FROM AUTHOR]

UNESCO Global Geoparks (UGGps) stand out as territories of excellence for the development of educational activities in the international arena. Their didactic potential, their multidisciplinarity and their importance for the development of non-formal and informal teaching activities have drawn the attention of institutions, organizations and governments of many countries. This, to such an extent, that the number of UGGps continues to increase year after year, having currently reached 177 territories spread over 46 countries. All of them work every day developing different activities and educational proposals aimed at the creation of the so-called "Quality Education", the fourth objective of the SDGs of the 2030 Agenda. The diversity of didactic plans, their adaptability and their accessibility mean that each UGGp is unique and different from the rest, maintaining the key values that make up this group of territories. This study describes the different educational proposals and activities that the Spanish and Portuguese UGGps show on their official websites, with the aim of analyzing their level of visibility before visiting the territories and highlighting their relevance in the education development framework. [ABSTRACT FROM AUTHOR]

This article presents applications of metagenomics and metabolomics in geosciences. It emphasizes the significance of biomolecular proxies in palaeoclimatology, the evolution of life, the genesis of hydrocarbons and the role of biological processes in metallogeny. Several examples of breakthroughs with respect using these methods in earth sciences exist, such as the estimating resilience time of landscapes against invasive species. It is unfortunate that scientific programmes using bioproxies have not yet taken root in Indian institutions. Now is the appropriate time to delineate the critical role of biology in geology and establish it as a thrust area of research in India. A molecular geobiology programme would deal with the understanding of varied issues such as microbial heat production and its role in soil processes, the role of biology in mineralization, the use of biomarkers (metabolites) and ancient DNA studies in understanding feedbacks in climate change, evolution of life, etc. This article focuses on the use of metagenomics and metabolomics in palaeo-sciences and the potential intellectual dividends they could provide. [ABSTRACT FROM AUTHOR]

In past years, we have followed, in Brazil and in the world, major disasters that have demanded a better response capacity. This fact has already been pointed out even at the United Nations Conferences on Disaster Risk Reduction. The contribution and responsibility that the geoscientist has in the identification and assessment of hazards and in the classification of risk areas - actions common to Risk Management - are relatively better known and discussed, both in the academic and technical areas, however, what it is not yet so explored is the role, and consequently the institutional and operational protocols, of the geosciences professional in the stages of preparation and response to the incident, that is, in Disaster Management. This study aims to address some emergency and contingency plans, at the state level, in use in Brazil, especially analyzing the insertion and contribution of geosciences to disasters associated with mass movements. It is certainly understood that preventing disasters is the priority, but knowing how to respond to them effectively, quickly, safely, and efficiently is also very important and for that it is necessary to consider if the existing documents and protocols adequately and sufficiently comply with the existing demands. [ABSTRACT FROM AUTHOR]

In this paper I introduce the thesis of cultural readiness about science found in the historical analysis of the Alvarez impact hypothesis of the end-Cretaceous mass extinction. Cultural readiness posits that in some scientific domains, there are scientifically apt questions, methodologies or theories that are only developed, considered, and adopted by a scientific community once some combination of empirical and cultural factors obtains within and without that domain. I demonstrate that 21st century philosophy of the historical sciences has been motivated by a commitment to legitimization and has prioritized epistemic ingenuity and has not addressed cultural readiness. I then argue that one vehicle for cultural readiness in the historical sciences is their use of narrative explanatory forms. Narratives offer an arena to blend cultural and empirical phenomena by their characteristic elicitation of familiarity and emotionality. [ABSTRACT FROM AUTHOR]

Copyright of Arte & Ensaio is the property of Arte & Ensaio and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Water is life. It is a familiar phrase, frequently spoken today. Even so, little thought goes into what this simple phrase means. We exist in water throughout our lives, dependent on it from conception, surrounded in water in our mother’s womb, until our last water vapor breath. Water is so common, we are so accustomed to our submergence in it that we fail to notice how vital it is and fail to recognize our dependence on it, taking for granted the water vapor-laden environment we exist in every moment of every day...

At the end of July 2022, some 150 individuals from across the country gathered at the University of Minnesota Twin Cities for “Data Science in Indian Country,” the Fifth Geoscience Alliance Conference since 2010. Founded by Dr. Nievita Bueno Watts of California State Polytechnic University, Humboldt (Cal Poly Humboldt), Prof. Anthony Berthelote of Salish Kootenai College, and Dr. Diana Dalbotten of the University of Minnesota’s St. Anthony Falls Laboratory, the Geoscience Alliance (GA) is a coalition of students, educators and staff, Indigenous community members, and others committed to broadening the participation of Native Americans, Alaska Natives, and people of Native Hawai’ian ancestry in the geosciences...

Abstract Introduced in 2016, the FAIR Guiding Principles endeavour to significantly improve the process of today's data‐driven research. The Principles present a concise set of fundamental concepts that can facilitate the findability, accessibility, interoperability and reuse (FAIR) of digital research objects by both machines and human beings. The emergence of FAIR has initiated a flurry of activity within the broader data publication community, yet the principles are still not fully understood by many community stakeholders. This has led to challenges such as misinterpretation and co‐opted use, along with persistent gaps in current data publication culture, practices and infrastructure that need to be addressed to achieve a FAIR data end‐state. This paper presents an overview of the practices and perspectives related to the FAIR Principles within the Geosciences and offers discussion on the value of the principles in the larger context of what they are trying to achieve. The authors of this article recommend using the principles as a tool to bring awareness to the types of actions that can improve the practice of data publication to meet the needs of all data consumers. FAIR Guiding Principles should be interpreted as an aspirational guide to focus behaviours that lead towards a more FAIR data environment. The intentional discussions and incremental changes that bring us closer to these aspirations provide the best value to our community as we build the capacity that will support and facilitate new discovery of earth systems.