View Of Landscape Research Articles

Ethics in AI through the practitioner’s view: a grounded theory literature review

The term ethics is widely used, explored, and debated in the context of developing Artificial Intelligence (AI) based software systems. In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of AI technology in our everyday lives. But what do we know about the views and experiences of those who develop these systems – the AI practitioners? We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners’ views on ethics in AI and analysed them to derive five categories: practitioner awareness, perception, need, challenge, and approach. These are underpinned by multiple codes and concepts that we explain with evidence from the included studies. We present a taxonomy of ethics in AI from practitioners’ viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics. The taxonomy provides a landscape view of the key aspects that concern AI practitioners when it comes to ethics in AI. We also share an agenda for future research studies and recommendations for practitioners, managers, and organisations to help in their efforts to better consider and implement ethics in AI.

Navigating the Digital Horizon: The Impact and Future of Communication Technologies in Society

The article delves deeper into the dynamic and rapidly evolving realm of digital communication technologies, highlighting their transformative impact across various dimensions of modern society. It scrutinizes the latest advancements in digital communication tools and platforms, assessing how these innovations are not only altering our fundamental methods of interaction but also redefining the paradigms of information exchange and processing. The study provides an in-depth analysis of five key domainssocial media dynamics, e-commerce evolution, mobile communication progression, online educational methodologies, and telemedicine advancements. Each of these domains is thoroughly examined through three distinct lenses, offering a nuanced perspective on their current state, challenges faced, and the potential trajectories they may follow. The article aims to furnish a holistic view of the digital communication landscape, contemplating its broader implications on social behavior, economic patterns, educational practices, healthcare delivery, and governance mechanisms. This comprehensive exploration is intended to offer readers a multifaceted understanding of how digital communication technologies are not just tools of convenience, but powerful forces shaping the future contours of our global society.

Research on Internal Control of Chinese Commercial Banks Based on Comprehensive Risk Management

The dynamic and complex nature of global financial markets has necessitated the evolution of internal control mechanisms within commercial banks, especially within the context of Chinese financial institutions which operate in a rapidly changing economic environment. This study delves into the intricacies of internal control systems in Chinese commercial banks, scrutinizing their effectiveness through the lens of comprehensive risk management practices. Employing a mixed-methods approach that combines quantitative data analysis with qualitative case studies, this research examines the extent to which these banks have integrated risk management into their internal control frameworks. The analysis focuses on financial, operational, compliance, and strategic risks, providing a holistic view of the internal control landscape. Key findings reveal that while many Chinese commercial banks have made significant strides in embedding risk management principles into their internal controls, there remain notable inconsistencies and gaps, particularly in areas related to emerging financial technologies and regulatory compliance. Moreover, the study highlights the critical role of organizational culture and leadership in fostering an environment conducive to effective risk management. This research contributes to the existing body of knowledge by offering insights into the challenges and opportunities facing internal control systems in Chinese commercial banks. It underscores the necessity of adopting an integrated risk management approach to enhance resilience and competitiveness. Furthermore, the findings have practical implications for policymakers, regulators, and banking professionals, suggesting pathways for strengthening the internal control mechanisms to mitigate risks and capitalize on opportunities in the evolving financial landscape.

Differential contributions of G protein- or arrestin subtype-mediated signalling underlie urocortin 3-induced somatostatin secretion in pancreatic δ cells.

Pancreatic islets are modulated by cross-talk among different cell types and paracrine signalling plays important roles in maintaining glucose homeostasis. Urocortin 3 (UCN3) secreted by pancreatic β cells activates the CRF2 receptor (CRF2R) and downstream pathways mediated by different G protein or arrestin subtypes in δ cells to cause somatostatin (SST) secretion, and constitutes an important feedback circuit for glucose homeostasis. Here, we used Arrb1-/-, Arrb2-/-, Gsfl/fl and Gqfl/fl knockout mice, the G11-shRNA-GFPfl/fl lentivirus, as well as functional assays and pharmacological characterization to study how the coupling of Gs, G11 and β-arrestin1 to CRF2R contributed to UCN3-induced SST secretion in pancreatic δ cells. Our study showed that CRF2R coupled to a panel of G protein and arrestin subtypes in response to UCN3 engagement. While RyR3 phosphorylation by PKA at the S156, S2706 and S4697 sites may underlie the Gs-mediated UCN3- CRF2R axis for SST secretion, the interaction of SYT1 with β-arrestin1 is also essential for efficient SST secretion downstream of CRF2R. The specific expression of the transcription factor Stat6 may contribute to G11 expression in pancreatic δ cells. Furthermore, we found that different UCN3 concentrations may have distinct effects on glucose homeostasis, and these effects may depend on different CRF2R downstream effectors. Collectively, our results provide a landscape view of signalling mediated by different G protein or arrestin subtypes downstream of paracrine UCN3- CRF2R signalling in pancreatic β-δ-cell circuits, which may facilitate the understanding of fine-tuned glucose homeostasis networks.

Abstract 1144: Glioblastoma cells increase expression of neurodevelopmental programs and synaptic connectivity in the tumor periphery

Abstract Glioblastoma remains one of the deadliest brain malignancies. First-line therapy consists of maximal surgical tumor resection, accompanied by concomitant and adjuvant temozolomide chemotherapy and radiotherapy. Malignant cells escape surgical resection by migrating into the brain parenchyma, where they give rise to the recurrent tumor. Based on gene expression, the tumor core can be subtyped into mesenchymal, proneural and classical areas, each being associated with differences in genetic alterations and cellular composition. In contrast, the tumor periphery where migrating tumor cells infiltrate brain parenchyma is less characterized in patients. Using spatial transcriptomics (n = 11), we show that specific malignant states colocalize in tumor core areas with necrosis and microvascular proliferation. Malignant cells within proneural or mesenchymal subtyped cores displayed, as expected, many differences in genetic expression, although such differences disappeared in the tumor periphery. Malignant cells residing in the tumor periphery had increased expression of genes related to neurodevelopmental pathways and synaptic connectivity. Our findings show similarities in cellular states across tumor subtypes with implications for post-operative treatment and provide an updated view of the spatial landscape of glioblastomas. Citation Format: Dylan Harwood, Vilde Pedersen, Nicolai S. Bager, Ane Y. Schmidt, Tobias O. Stannius, Ausrine Areskeviciute, Knud Josefsen, Dorte S. Nørøxe, David Scheie, Hannah E. Rostalski, Ulrik Lassen, Frederik O. Bagger, Joachim Weischenfeldt, Dieter H. Heiland, Kristoffer Vitting-Seerup, Signe R. Michaelsen, Bjarne W. Kristensen. Glioblastoma cells increase expression of neurodevelopmental programs and synaptic connectivity in the tumor periphery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1144.

Sustainable Copolymer Synthesis from Carbon Dioxide and Butadiene.

Carbon dioxide (CO2) has long been recognized as an ideal C1 feedstock comonomer for producing sustainable materials because it is renewable, abundant, and cost-effective. However, activating CO2 presents a significant challenge because it is highly oxidized and stable. A CO2/butadiene-derived δ-valerolactone (EVP), generated via palladium-catalyzed telomerization between CO2 and butadiene, has emerged as an attractive intermediate for producing sustainable copolymers from CO2 and butadiene. Owing to the presence of two active carbon-carbon double bonds and a lactone unit, EVP serves as a versatile intermediate for creating sustainable copolymers with a CO2 content of up to 29 wt % (33 mol %). In this Review, advances in the synthesis of copolymers from CO2 and butadiene with divergent structures through various polymerization protocols have been summarized. Achievements made in homo- and copolymerization of EVP or its derivatives are comprehensively reviewed, while the postmodification of the obtained copolymers to access new polymers are also discussed. Meanwhile, potential applications of the obtained copolymers are also discussed. The literature references were sorted into sections based on polymerization strategies and mechanisms, facilitating readers in gaining a comprehensive view of the present chemistry landscape and inspiring innovative approaches to synthesizing novel CO2-derived copolymers.

Abstract P17: Epigenomic fingerprinting of limited primary immune cells using automated CUT&RUN

Abstract Chromatin structure drives gene expression programs during immune cell development and in cancer, making it central to the advancement of precision medicine. Indeed, the study of chromatin regulation has provided valuable insight on effector cell differentiation and function, anti-tumor immune responses, and therapeutic resistance. Epigenomic features – such as histone post-translational modifications (PTMs) and chromatin-associated proteins – mark distinct genomic compartments (e.g., promoters, enhancers) and regulate chromatin function/gene expression. Mapping the genomic distribution of these may uncover new biomarkers or drug targets and provides a rich context for exploring immunology. Despite widespread interest, integration of epigenomics in large-scale immunotherapy and/or drug research has been hampered by the poor sensitivity, high background, and low throughput of traditional chromatin mapping technologies, most notably ChIP-seq. Instead, efforts to characterize chromatin dynamics have focused on DNA methylation (bisulfite-seq) or chromatin accessibility (ATAC-seq). However, these assays provide an incomplete view of the chromatin landscape, limiting their ability to define cell differentiation pathways or derive mechanistic insight into disease etiology. Here, we present autoCUT&RUN, a high-throughput assay for rapid, ultra-sensitive profiling of epigenomic features from FACS-isolated primary cells or tissues. This workflow generates reliable profiles from ~10,000 cells per reaction, and is supported by a rigorous optimization strategy, high-quality antibodies, and quantitative spike-in controls. As part of a multi-site collaboration with the Immunological Genome Consortium, we used our autoCUT&RUN platform to build a comprehensive epigenomic database of primary mouse immune cells - composed of >1,500 epigenomic profiles from >100 different FACS-isolated immune cell types. These studies set the stage to leverage high-throughput epigenomics in immunotherapy and precision medicine applications. Citation Format: Ellen N. Weinzapfel, Keith E. Maier, Matthew R. Marunde, Vishnu U. Sunitha Kumary, Carolina P. Lin Windham, Danielle N Maryanski, Liz Albertorio-Saez, Dughan J. Ahimovic, Michael J. Bale, Juliana J. Lee, Bryan J. Venters, Michael-Christopher Keogh, Immunological Genome Consortium. Epigenomic fingerprinting of limited primary immune cells using automated CUT&RUN [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P17.

Quantum-based privacy-preserving techniques for secure and trustworthy internet of medical things an extensive analysis

The advent of Quantum Key Distribution (QKD) and quantum-based privacy-preserving techniques has ushered in a new era for securing communication channels within the Internet of Medical Things (IoMT) systems. We examine the fundamentals, uses, and ramifications of quantum cryptography in relation to healthcare data security in this thorough investigation. The journey commences with an in-depth overview of quantum cryptography, unraveling the concepts of superposition, entanglement, and quantum gates that form the bedrock of quantum computing. As we proceed, we investigate the uses of quantum cryptography, highlighting its contribution to resolving the particular issues brought about by the data-intensive and networked character of IoMT systems. The relevance of QKD in ensuring secure communication within IoMT is meticulously dissected, with case studies and experiments demonstrating the practicality and effectiveness of quantum-based privacy-preserving techniques. From telemedicine networks to wearable health devices, each case study offers valuable insights into the application of quantum-safe cryptography, showcasing its ability to fortify data integrity and confidentiality. A meticulous survey of existing research, coupled with an analysis of advancements in quantum cryptography, provides a panoramic view of the current landscape. From hardware limitations to distance constraints, the study navigates through challenges and breakthroughs, offering a roadmap for the future integration of quantum technologies into IoMT systems.Comparing quantum-based approaches with classical cryptography unveils a nuanced landscape of computational complexity, key distribution methodologies, and real-time encryption considerations. This comparative analysis serves as a guide for healthcare practitioners and technologists in making informed decisions regarding the adoption of quantum-based privacy-preserving techniques in IoMT environments. The case studies and experiments collectively paint a picture of the practicality and promise of quantum-based privacy-preserving techniques in IoMT scenarios. Anticipating future advancements, the exploration extends into quantum hardware improvements, standardization efforts, and the integration of quantum technologies with emerging trends like edge computing and blockchain. As the healthcare industry stands on the cusp of a quantum revolution, the comprehensive insights provided herein offer a foundation for understanding, implementing, and shaping the future of secure healthcare communication through the lens of quantum cryptography.

Big data applications in portfolio management: A review of techniques and strategies

In the ever-evolving landscape of finance, the advent of big data has ushered in a paradigm shift, transforming the art and science of portfolio management from its traditional moorings to a future where data reigns supreme. This paper delves into the intricate dance between big data and portfolio management, aiming to demystify the journey from historical practices to the forefront of technological innovation in finance. Through a meticulous examination, the study sets out to map the evolution of portfolio management in the digital age, scrutinize the technological foundations essential for big data analytics, and explore the symbiotic relationship between big data capabilities and investment strategies. Employing a systematic literature review as its methodological backbone, the research navigates through the complexities of integrating big data into portfolio management, offering a panoramic view of the current landscape and the challenges that lie ahead. The findings illuminate the transformative impact of big data analytics, highlighting its potential to enhance decision-making, optimize risk assessment, and unearth new investment opportunities. However, the journey is fraught with challenges, including data privacy concerns, ethical considerations, and the need for continuous technological adaptation. In conclusion, the study advocates for a proactive embrace of big data, urging portfolio managers to cultivate a culture of innovation, ethical vigilance, and lifelong learning. As the financial sector stands on the brink of a data-driven era, this paper calls for a strategic reorientation towards the integration of big data analytics in portfolio management, paving the way for a future where informed decision-making and strategic foresight are paramount.

A landscape view of emerging sustainability responses within VET

ABSTRACT With evidence of global climate change and ongoing ecological degradation, there is an urgent need to give more attention to sustainability within VET to ensure that VET does not remain complicit in reproducing the unjust and unsustainable trajectories of current economic and development pathways. At present, the VET literature does not adequately address these issues, hence the need for this special issue. In response, this paper offers a meta-reflective ‘landscape view’ of the sustainability within the VET ‘field of knowledge’ as it is emerging. Here, we use landscape review as a multi-dimensional, ‘outside-in’ view that provides a basis for understanding the broad context and helps to inform actionable next steps. This analysis we believe helps to highlight the key emerging priorities as well as what paths VET is taking on the journey to sustainability. The analysis shows that while some progress has been made in policy and practice related to the ‘greening’ of VET, much of the current response within VET to the environmental challenge reflects a minimalist reformist approach, characterised by ‘bolt-ons’ to existing institutional structures and curricula whilst leaving the fundamental beliefs in productivism, industrialisation and growth in place. Yet, as argued by researchers working on green economy, these beliefs are often complicit in co-creation of the environmental crisis.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Spike Protein Variants.

The slow experimental acquisition of high-quality atomic structures of the rapidly changing proteins of the COVID-19 virus challenges vaccine and therapeutic drug development efforts. Fortunately, deep learning tools such as AlphaFold2 can quickly generate reliable models of atomic structure at experimental resolution. Current modeling studies have focused solely on definitions of mutant constellations of Variants of Concern (VOCs), leaving out the impact of haplotypes on protein structure. Here, we conduct a thorough comparative structural analysis of S-proteins belonging to major VOCs and corresponding latitude-delimited haplotypes that affect viral seasonal behavior. Our approach identified molecular regions of importance as well as patterns of structural recruitment. The S1 subunit hosted the majority of structural changes, especially those involving the N-terminal domain (NTD) and the receptor-binding domain (RBD). In particular, structural changes in the NTD were much greater than just translations in three-dimensional space, altering the sub-structures to greater extents. We also revealed a notable pattern of structural recruitment with the early VOCs Alpha and Delta behaving antagonistically by suppressing regions of structural change introduced by their corresponding haplotypes, and the current VOC Omicron behaving synergistically by amplifying or collecting structural change. Remarkably, haplotypes altering the galectin-like structure of the NTD were major contributors to seasonal behavior, supporting its putative environmental-sensing role. Our results provide an extensive view of the evolutionary landscape of the S-protein across the COVID-19 pandemic. This view will help predict important regions of structural change in future variants and haplotypes for more efficient vaccine and drug development.

The varied restorative values of campus landscapes to students’ well-being: evidence from a Chinese University

BackgroundThe literature on therapeutic landscapes highlights that the university campus landscape has restorative effects on students. This deserves more scholarly attention since mental health has become an important issue among university students. However, existing empirical studies have revealed mixed evidence with little attention to the heterogeneity across the design and, therefore, the potential therapeutic effects across different landscapes.MethodThis research examined how 13 landscape sites on a university campus might be differentially related to student well-being. These sites were identified from a variety of sources (campus design documents, photos used in the university’s social media posts, and interviews with a small group of students) to represent a comprehensive list of places that students might visit. The data was collected in a large online survey of a Chinese university (n = 2,528). We asked about students’ use of individual landscape sites and the associated motivations for visits, and measured well-being using a perceived stress scale and overall evaluation of the happiness level. Bivariate analysis was used to explore the zero-order associations between landscape use and well-being. OLS (for stress) and logistic regressions (for happiness) were conducted to further evaluate the associations after controlling the student background variables and potential correlations of uses across different landscapes.ResultsAmong 13 landscape sites, four sites had significant positive associations with either or both measures of well-being after controlling for the student characteristics and use of the other landscape sites. There was also an additive benefit of visiting more landscapes. Compared to those who did not frequently visit any of the sites, well-being had a significant stepwise increase among those who frequently visited one or two and more sites. One site that was significantly related to both measures of well-being only offered distant views of landscapes, but it was right next to the study areas.ConclusionsThis study demonstrates the heterogeneity of restorative effects across different landscapes on campus. The findings suggest that effective landscape design that aims to promote student well-being should be placed close to stressors (i.e., where they study), and between where they study and live to offer students opportunities to break from the common routines and to relax. The findings hold greater relevance for universities in China and institutions with similar student campus lifestyles, occupancies, and behavior patterns worldwide.

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers.

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

Single-cell sequencing reveals the immune landscape of breast cancer patients with brain metastasis.

Breast cancer has the highest incidence rate of cancer worldwide, and brain metastases (BrM) are among the most malignant cases. While some patients have benefited from immune checkpoint inhibitors (ICIs), the complex anatomical structure of the brain and the heterogeneity of metastatic tumors have made it difficult to characterize the tumor immune microenvironment (TME) of metastatic tumors. To address this, we used single-cell RNA sequencing (scRNA-seq) to analyze immune cells in the cerebrospinal fluid (CSF) of BrM patients with breast cancer, thereby providing a comprehensive view of the immune microenvironment landscape of BrM. Based on canonical marker genes, we identified nine cell types, and further identified their subtypes through differential expression gene (DEG) analysis. We compared the changes in cells and functions in the immune microenvironment of patients with different prognoses. Our analysis revealed a series of genes that promote tumor immune function (CCR5, LYZ, IGKC, MS4A1, etc.) and inhibit tumor immune function (SCGB2A2, CD24, etc.). The scRNA-seq in CSF provides a noninvasive method to describe the TME of breast cancer patients and guide immunotherapy.

Bibliometric analysis of peer-reviewed literature on perinatal depression in Mexico

Background. Perinatal depression (PND) is a clinical disease developed in any stage during the pregnancy and postpartum period with serious health and economic implications. Objective. The aim of this work was to analyze via bibliometrics indicators Mexico’s production on PND to provide a view of the academic landscape and a comprehensive reference for subsequent research in the country. Method. The Scopus and Web of Science (WoS) databases were used to perform a search for peer reviewed papers related to PND in México. The search was made following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The extracted data were processed with VOS Viewer to examine link strength and clusters associations of diverse bibliometrics variables. Results. A total of 132 records were retrieved and we included 70 studies in the bibliometric analysis after application of the exclusion criteria. The authors with more papers were Navarrete L., and Asunción Lara M. The institutions with more papers were the National Institute of Perinatology, Ramón de la Fuente National Institute of Psychiatry, and National Institute of Public Health of Mexico. A diminution of the research considered in PND is observed in the last two years. Four keyword clusters were identified related to PND: symptoms, prevalence, pregnancy. Discussion and conclusion. The scarce literature concerning PND in Mexico compared with other countries could be due the limited collaboration between the health institutes. An urgent need to increase research on PND in Mexico is evident to be applicable in the management of resources in the healthcare system.

Technological innovations in the LNG sector: A review: Assessing recent advancements and their impact on LNG production, transportation and usage

This paper thoroughly explores the recent technological innovations in the Liquefied Natural Gas (LNG) sector, examining their impact on production, transportation, storage, and usage. The study delves into the evolution of the global LNG market, emphasizing the critical role of technological advancements in shaping the industry's future. The aim is to analyze these innovations, assess their environmental and economic impacts, and explore the influence of geopolitical and market dynamics. By employing a comprehensive literature review, the paper utilizes a multi-criteria decision support framework to select relevant technological innovations and assess their impacts. This methodology integrates environmental, social, policy, and economic dimensions, offering a holistic view of the LNG sector's technological landscape. The findings reveal significant advancements in LNG production technologies, such as green ammonia and biogas, enhancing sustainability and efficiency. Innovations in LNG transportation, including optimized carrier fleets and storage systems, have revolutionized the industry, improving economic viability and safety. The emergence of Floating LNG (FLNG) technologies marks a pivotal development, unlocking new gas monetization possibilities. The study also highlights the environmental benefits of these innovations, including reduced greenhouse gas emissions and their synergy with renewable energy systems. The paper concludes that while technological advancements offer substantial benefits, they also present challenges, including high investment costs and regulatory complexities. It recommends continued innovation, strategic collaborations, and supportive regulatory frameworks to fully exploit the potential of LNG technologies. As the global energy landscape evolves, the LNG sector is poised to play a crucial role in the transition to a more sustainable and efficient energy future.

A STUDY OF COVID-19 EFFECTS ON THE IDENTITY THEFT LANDSCAPE

This research studies the impact of COVID-19 on the identity theft landscape using historical data published by the Federal Trade Commission. The data set included information about the number of identity theft reports for each state per year over a 6-year period, 2017 -2022. The dataset also included the number of reports for each identity theft category, providing a holistic view of the identity theft landscape. The data showed a significant increase in the number of identity thefts across all the states in 2020 compared to 2019; the percentage increase ranged from 45% to 1,801.1%. This coincided with the pandemic, which started in December 2019. The top 5 states that had the highest percent increase in 2020 are Kansas, Rhode Island, Maine, Washington, and Illinois. Moreover, in the year 2020, there was a dramatic increase across all the states in the number of identity theft reports related to government documents or benefits fraud, ranging from 207.7% to 33,236% increase compared to the year 2019. This was due to the sudden increase in available funds to help Americans during the pandemic, including unemployment benefits, stimulus checks, small business loans, etc., along with the expedited process to distribute the funds, which created ideal conditions for cybercriminals, especially identity thieves.

The Evolution of Scottish Enlightenment Publishing

AbstractThis article uses large-scale bibliographic data to extract and analyse the works, authors, and publishers of the Scottish Enlightenment. By doing so, we aim to encompass a wider scope and definition of Scottish Enlightenment publishing, contextualizing both the major and the lesser-known publishers. We reveal two competing models for key Scottish publishers: those working in Scotland, publishing works that were printed later in London; and those working in London, printing Scottish works. We show that the careers of key publishers such as Andrew Millar (1705–68) should be considered in relational terms: that Millar must be understood in the context of his wider network, taking into account a longer view of the publishing landscape both before and after his career. Moreover, we establish the relevance of subsequent editions of existing works for the understanding of eighteenth-century publishing. The article also argues for an agnostic view of the ‘Scottish Enlightenment text’, one which considers the features of individual texts rather than a priori assumptions about canonical works. Consequently, we show that the significance of works of scientific improvement evolves and becomes intertwined with education, literature, philosophy, and history over time; resulting in a convergence of practice, theory, and literary expression.

Review on Modeling and SOC/SOH Estimation of Batteries for Automotive Applications

Lithium-ion batteries have revolutionized the portable and stationary energy industry and are finding widespread application in sectors such as automotive, consumer electronics, renewable energy, and many others. However, their efficiency and longevity are closely tied to accurately measuring their SOC and state of health (SOH). The need for precise algorithms to estimate SOC and SOH has become increasingly critical in light of the widespread adoption of lithium-ion batteries in industrial and automotive applications. While the benefits of lithium-ion batteries are undeniable, the challenges related to their efficient and safe management cannot be overlooked. Accurate estimation of SOC and SOH is crucial for ensuring optimal battery management, maximizing battery lifespan, optimizing performance, and preventing sudden failures. Consequently, research and development of reliable algorithms for estimating SOC and SOH have become an area of growing interest for the scientific and industrial community. This review article aims to provide an in-depth analysis of the state-of-the-art in SOC and SOH estimation algorithms for lithium-ion batteries. The most recent and promising theoretical and practical techniques used to address the challenges of accurate SOC and SOH estimation will be examined and evaluated. Additionally, critical evaluation of different approaches will be highlighted: emphasizing the advantages, limitations, and potential areas for improvement. The goal is to provide a clear view of the current landscape and to identify possible future directions for research and development in this crucial field for technological innovation.

A Landscape View of the Female Genital Tract Microbiome in Healthy Controls and Women With Reproductive Health Conditions Associated With Ectopic Pregnancy.

Disruption of the female genital microbiome is associated with several pregnancy complications, including miscarriage, preterm onset of labour, and tubal pregnancy. Ectopic pregnancy is a known cause of maternal morbidity and mortality, but early diagnosis and treatment of ectopic pregnancy remain a challenge. Despite growing established associations between genital microbiome and female reproductive health, few studies have specifically focused on its link with ectopic pregnancy. Therefore, the current review aims to provide a comprehensive account of the female genital microbiome in healthy and fertile women compared to those in ectopic pregnancy and its associated risk factors. The microbial diversity from various sites of the female genital tract was explored for a reliable proxy of female reproductive health in sequencing-based ectopic pregnancy research. Our report confirmed the predominance of Lactobacillus in the vagina and the cervix among healthy women. The relative abundance decreased in the vaginal and cervical microbiome in the disease state. In contrast, there were inconsistent findings on the uterine microbiome across studies. Additionally, we explore a spectrum of opportunities to enhance our understanding of the female genital tract microbiome and reproductive conditions. In conclusion, this study identifies gaps within the field and emphasises the need for visionary solutions in metagenomic tools for the early detection of ectopic pregnancy and other gynaecological diseases.