bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accelerating randomized image secret sharing with GPU: contrast enhancement and secure reconstruction using progressive and convolutional approaches
Authors: M Raviraja Holla , D Suma , Pais Alwyn R. 
Published: March 2024

AbstractImage Secret Sharing (ISS) is a cryptographic technique used to distribute secret images among multiple users. However, current Visual Secret Sharing (VSS) schemes produce a halftone image with only 50% contrast when reconstructing the original image. To overcome this limitation, the Randomized Image Secret Sharing (RISS) scheme was introduced. RISS achieves a higher contrast of 70% when extracting the secret image but comes with a high computational cost. This research paper presents a novel approach called Graphics Processing Unit (GPU)-based Randomized Image Secret Sharing (GRISS), which utilizes data parallelism within the RISS pipeline. The proposed technique also incorporates an Autoencoder-based Single Image Super-Resolution (ASISR) to enhance the contrast of the recovered image. The performance of GRISS is evaluated against RISS, and the contrast of the ASISR images is compared to current benchmark models. The results demonstrate that GRISS outperforms state-of-the-art models in both efficiency and effectiveness.
Workflow-Induced Uncertainty in Data-Driven Mineral Prospectivity Mapping
Authors: Zhang Steven E. , Lawley Christopher J. M. , Bourdeau Julie E. , Nwaila Glen T. , Ghorbani Yousef 
Published: March 2024

AbstractThe primary goal of mineral prospectivity mapping (MPM) is to narrow the search for mineral resources by producing spatially selective maps. However, in the data-driven domain, MPM products vary depending on the workflow implemented. Although the data science framework is popular to guide the implementation of data-driven MPM tasks, and is intended to create objective and replicable workflows, this does not necessarily mean that maps derived from data science workflows are optimal in a spatial sense. In this study, we explore interactions between key components of a geodata science-based MPM workflow on the geospatial outcome, within the modeling stage by modulating: (1) feature space dimensionality, (2) the choice of machine learning algorithms, and (3) performance metrics that guide hyperparameter tuning. We specifically relate these variations in the data science workflow to the spatial selectivity of resulting maps using uncertainty propagation. Results demonstrate that typical geodata science-based MPM workflows contain substantial local minima, as it is highly probable for an arbitrary combination of workflow choices to produce highly discriminating models. In addition, variable domain metrics, which are key to guide the iterative implementation of the data science framework, exhibit inconsistent relationships with spatial selectivity. We refer to this class of uncertainty as workflow-induced uncertainty. Consequently, we propose that the canonical concept of scientific consensus from the greater experimental science framework should be adhered to, in order to quantify and mitigate against workflow-induced uncertainty as part of data-driven experimentation. Scientific consensus stipulates that the degree of consensus of experimental outcomes is the determinant in the reliability of findings. Indeed, we demonstrate that consensus through purposeful modulations of components of a data-driven MPM workflow is an effective method to understand and quantify workflow-induced uncertainty on MPM products. In other words, enlarging the search space for workflow design and experimenting with workflow components can result in more meaningful reductions in the physical search space for mineral resources.
Stability of Fractional Reaction-Diffusion Memristive Neural Networks Via Event-Based Hybrid Impulsive Controller
Authors: Wang Huiyu , Liu Shutang , Wu Xiang , Sun Jie , Qiao Wei 
Published: March 2024

AbstractThis article explores the asymptotic stability of fractional delayed memristive neural networks with reaction-diffusion terms. A novel hybrid impulsive controller triggered by a specific event is proposed to stabilize the network, thereby replacing the conventional approach of modifying network parameters. The proposed controller is proven to prevent Zeno behavior. Sufficient conditions for the asymptotic stability of fractional delayed memristive neural networks with reaction-diffusion terms are established through Lyapunov direct method, inequality techniques, Green’s theorem and impulse analysis. Furthermore, the proposed controller is theoretically shown to be more resource-efficient than the conventional one, and our work extends existing research to make it more suitable for practical application such as pattern recognition, image processing and so on. Finally, an example is provided to illustrate the validity of the findings.
Measuring vulnerability to assess households resilience to flood risks in Karonga district, Malawi
Authors: Mwalwimba Isaac Kadono , Manda Mtafu , Ngongondo Cosmo 
Published: March 2024

AbstractMany parts of Malawi are prone to natural hazards with varying degrees of risk and vulnerability. This study aimed at obtaining baseline data for quantifying vulnerability of the households to flood risks in Karonga District in northern Malawi, specifically in Group Village Headman Matani Mwakasangila of Traditional Authority Kilupula. The study used cross-sectional survey, and data were collected using a structured questionnaire. This study applied Flood Vulnerability Index and statistical methods to quantify and analyse vulnerability of households in the aspects of exposure, susceptibility and resilience characteristics. Proportional Odds Model also known as Ordered Logistic Regression was used to identify factors that determine vulnerability of households to flood risks. The results show that households headed by females and elders of age (at least 61 years) were the most vulnerable to floods because of their limited social and livelihood capacities, resulting from being uneconomically active group. Households with houses built of mud, thatched and very old with no protective account for high vulnerability due to the fact that most of them are constructed using substandard materials. The level of vulnerability was increasing with an increase in the number of households exposed and susceptible to floods. With an increase in resilience to floods, vulnerability level was decreasing. The results further revealed a predictive margins of vulnerability levels which were not significantly different among the villages. However, villages with more exposed, susceptible and not resilience households were most vulnerable to floods. This study recommends that vulnerability assessment should be included in Disaster Risk Reduction planning and implementation in order to make DRR more efficient and realistic. This would further strengthen the disaster risk management to be more proactive as well as increase resilience of households to flood risks.
Exploring the role of big data analytics and dynamic capabilities in ESG programs within pharmaceuticals
Authors: Pesqueira Antonio , Sousa Maria José 
Published: March 2024

AbstractAchieving the United Nations’ Sustainable Development Goals (SDGs) requires environmental, social, and governance (ESG) programs in the pharmaceutical industry. Using the Millennium Development Goals, the 2030 agenda aims to transform European Union companies toward sustainability. In pharmaceuticals, in particular, ESG programs come with complexities such as employee skills, corporate goals, and management expectations. Managing these programs effectively requires advanced technologies such as big data analytics (BDA) and dynamic capabilities (DC). In this study, DC theory is used to develop an architecture for managing ESG criteria, focusing on provenance, traceability, and availability. BDA’s role in ESG programs is explored, along with its use cases and benefits, and how DC drives success in ESG implementation. The study examined five pharmaceutical companies in Germany, Portugal, and Switzerland, all consulting the same firm for BDA systems, to identify the characteristics of effective BDA implementation. The research explores how BDA and DC jointly enhance ESG efforts, the essential skills needed, and how DC aids in real-time decision-making in BDA projects aligned with ESG standards. It highlights the BDA system’s accuracy and effectiveness in managing ESG programs, with DC as a pivotal facilitator. Findings reveal BDA’s value in operational efficiency and aligning business models with ESG goals, underscoring the need for diverse skills in BDA implementation and DC’s importance in integrating various managerial capacities into effective strategies. The study promotes a dynamic, data-driven approach in the pharmaceutical industry for managing complex ESG initiatives. It stresses continuous learning, adaptation, and integrating technological advances with ethical business practices. The research concludes by emphasizing BDA and DC’s vital roles in advocating ethical, socially responsible, and environmentally sustainable practices in the pharmaceutical sector, marrying technology with ethical business strategies.
Detection of malicious URLs using machine learning
Authors: Reyes-Dorta Nuria , Caballero-Gil Pino , Rosa-Remedios Carlos 
Published: March 2024

AbstractThe detection of fraudulent URLs that lead to malicious websites using addresses similar to those of legitimate websites is a key form of defense against phishing attacks. Currently, in the case of Internet of Things devices is especially relevant, because they usually have access to the Internet, although in many cases they are vulnerable to these phishing attacks. This paper offers an overview of the most relevant techniques for the accurate detection of fraudulent URLs, from the most widely used machine learning and deep learning algorithms, to the application, as a proof of concept, of classification models based on quantum machine learning. Starting from an essential data preparation phase, special attention is paid to the initial comparison of several traditional machine learning models, evaluating them with different datasets and obtaining interesting results that achieve true positive rates greater than 90%. After that first approach, the study moves on to the application of quantum machine learning, analysing the specificities of this recent field and assessing the possibilities it offers for the detection of malicious URLs. Given the limited available literature specifically on the detection of malicious URLs and other cybersecurity issues through quantum machine learning, the research presented here represents a relevant novelty on the combination of both concepts in the form of quantum machine learning algorithms for cybersecurity. Indeed, after the analysis of several algorithms, encouraging results have been obtained that open the door to further research on the application of quantum computing in the field of cybersecurity.
Autohydrolysis treatment of bamboo and potassium oxalate (K2C2O4) activation of bamboo product for CO2 capture utilization
Authors: Viet Dang Duc , Thao Doan Thi , Anh Khuong Duy , Tsubota Toshiki 
Published: March 2024

AbstractTypically, the hydroxide agents, such as sodium hydroxide and potassium hydroxide, which have corrosive properties, are used in the carbon activation process. In this study, potassium oxalate (K2C2O4), a less toxic and non-corrosive activating reagent, was used to synthesize activated carbon from the solid residue after autohydrolysis treatment. The effect of the autohydrolysis treatment and the ratio of the K2C2O4/solid residue are presented in this study. Moreover, the comparison between the activated carbon from bamboo and biochar from the solid residue are also reported. The resulting activated carbon from the solid residue exhibited a high surface area of up to 1432 m2·g−1and a total pore volume of up to 0.88 cm3·g−1. The autohydrolysis treatment enhanced the microporosity properties compared to those without pretreatment of the activated carbon. The microporosity of the activated carbon from the solid residue was dominated by the pore width at 0.7 nm, which is excellent for CO2storage. At 25 °C and 1.013 × 105Pa, the CO2captured reached up to 4.1 mmol·g−1. On the other hand, the ratio between K2C2O4and the solid residue has not played a critical role in determining the porosity properties. The ratio of the K2C2O4/solid residue of 2 could help the carbon material reach a highly microporous textural property that produces a high carbon capture capacity. Our finding proved the benefit of using the solid residue from the autohydrolysis treatment as a precursor material and offering a more friendly and sustainable activation carbon process.
How Not to Diversify Philosophy of Religion: A Critique from the Twenty-First Century
Authors: Stepien Rafal K. 
Published: March 2024

AbstractPhilosophy of religion has been the object of penetrating critiques concerning its continued near-complete blindness to all but a single religion. The need for philosophy of religion to open up so as to include more than merely occasional and tokenistic treatments of ‘Other’ religions is clearly evident from the slew of recently published titles concerned with diversifying the field. In this light, a book such as Victoria Harrison’s Eastern Philosophy of Religion should surely come as a welcome addition. And yet, unfortunately, this book turns out to be a case study in how not to diversify philosophy of religion in the twenty-first century.
Evolution and trends of the metaverse in business and management: A bibliometric analysis
Authors: Piñeiro-Chousa Juan , López-Cabarcos M. Ángeles , VittoriRomero Valentín , Pérez-Pérez Aurora 
Published: March 2024

Abstract
The Metaverse is an immersive digital environment that enables users, through avatars, to create worlds, objects, and interact with each other for various purposes. Furthermore, its significance in Business and Management is increasingly evident. The objective of this research is to examine the evolution, trends, and research approaches related to the Metaverse in the field of Business and Management. This study presents a comprehensive contextualization and bibliometric analysis of the existing literature in this area. In the contextualization phase, publications per year, citations received per year, most cited publications, and languages used in publications were examined. These analyses provided an overview of the temporal evolution of research, influential publications, and language diversity in the field of Business and Management. Subsequently, a bibliometric analysis was conducted using Co-citation, Bibliographic coupling, and Co-occurrence of author keywords. These analyses helped identify relationships between scientific works, thematic connections, and collaborations among researchers in the studied field. The use of the Web of Science database ensured the quality and comprehensiveness of the collected data, while the Vosviewer tool facilitated efficient visualization and analysis of the results. The findings of this study provide a detailed understanding of the research landscape in Business and Management, revealing key areas of focus, significant contributions, and existing collaboration networks. These insights can be valuable for researchers, professionals, and regulators in the field of Business and Management.
HMGA1 regulates the mitochondrial apoptosis pathway in sepsis-induced cardiomyopathy
Authors: Xu Jing , Li Xinwei , Lu Qianqian , Li Xiaohua , Shan Hongying 
Published: March 2024

AbstractHigh mobility group protein AT-hook 1 (HMGA1), an architectural transcription factor, has previously been reportedto play an essential role in architectural remodeling processes. However, its effects on cardiovascular diseases, particularly sepsis-induced cardiomyopathy, have remained unclear. The study aimed to investigate the role of HMGA1 in lipopolysaccharide-induced cardiomyopathy. Mice subjected to lipopolysaccharide for 12 h resulted in cardiac dysfunction. We used an adeno-associated virus 9 delivery system to achieve cardiac-specific expression of the HMGA1 gene in the mice. H9c2 cardiomyocytes were infected with Ad-HMGA1 to overexpress HMGA1 or transfected with si-HMGA1 to knock down HMGA1. Echocardiography was applied to measure cardiac function. RT-PCR was used to detect the transcriptional level of inflammatory cytokines. CD45 and CD68 immunohistochemical staining were used to detect inflammatory cell infiltration and TUNEL staining to evaluate the cardiomyocyte apoptosis, MitoSox was used to detect mitochondrial reactive oxygen species, JC-1 was used todetect Mitochondrial membrane potential. Our findings revealed that the overexpression of HMGA1 exacerbated myocardial inflammation and apoptosis in response to lipopolysaccharide treatment. Additionally, we also observed that H9c2 cardiomyocytes with HMGA1 overexpression exhibited enhanced inflammation and apoptosis upon stimulation with lipopolysaccharide for 12 h. Conversely, HMGA1 knockdown in H9c2 cardiomyocytes attenuated lipopolysaccharide-induced cardiomyocyte inflammation and apoptosis. Further investigations into the molecular mechanisms underlying these effects showed that HMGA1 promoted lipopolysaccharide-induced mitochondrial-dependent cardiomyocyte apoptosis. The study reveals that HMGA1 worsens myocardial inflammation and apoptosis in response to lipopolysaccharide treatment. Mechanically, HMGA1 exerts its effects by regulating the mitochondria-dependent apoptotic pathway.
Comments on Sociology in a New Key by Helmut Staubmann
Authors: Lidz Victor 
Published: March 2024

AbstractHelmut Staubmann argues in his new book that sociological theory should acknowledge its overemphasis on the normative regulation of social relationships and institutions and provide appropriate attention to the expressive and aesthetic aspects of social life. With many illustrations, he demonstrates that the expressive aspect is present in almost all interaction and, moreover, important institutions, such as museums and concert venuses, operate to give popular access to highly salient aesthetic experiences. Staubmann also provides an unparalleled overview of past literature addressing the expressive/aesthetic aspect of social life. The present comments add suggestions about how, given the complexity of the problem, the expressive/aesthetic elements of interaction.
$$L^p_{loc}$$ Positivity Preservation and Liouville-Type Theorems
Authors: Bisterzo Andrea , Farina Alberto , Pigola Stefano 
Published: March 2024

AbstractOn a complete Riemannian manifold (M, g), we consider$$L^{p}_{loc}$$Llocpdistributional solutions of the differential inequality$$-\Delta u + \lambda u \ge 0$$-Δu+λu≥0with$$\lambda >0$$λ>0a locally bounded function that may decay to 0 at infinity. Under suitable growth conditions on the$$L^{p}$$Lpnorm ofuover geodesic balls, we obtain that any such solution must be nonnegative. This is a kind of generalized$$L^{p}$$Lp-preservation property that can be read as a Liouville-type property for nonnegative subsolutiuons of the equation$$\Delta u \ge \lambda u$$Δu≥λu. An application of the analytic results to$$L^{p}$$Lpgrowth estimates of the extrinsic distance of complete minimal submanifolds is also given.
Backdraft in Self-Compassion: An Overlooked Yet Vital Research Focus
Authors: Cai Ru Ying 
Published: March 2024

AbstractSelf-compassion involves treating oneself with the same kindness, understanding, and forgiveness that one would typically offer a friend in times of suffering or adversity. While self-compassion has shown consistent benefits in research and therapy, including psychological and physical health benefits, some individuals practicing it may initially encounter adverse reactions known as “backdraft.” Backdraft has been theorized to be an inevitable part of healing and recovery from past hurts and trauma. However, empirical studies specifically examining backdraft experiences in the context of self-compassion are lacking. This commentary argues that integrating broader literature outside of self-compassion is crucial for advancing our understanding of the causes of backdraft and identifying practices to alleviate it. Specifically, ideas drawn from traditional Buddhist practices and phenomena conceptually similar to backdraft, such as fear of self-compassion from compassion-focused therapy and adverse effects of meditation practices used in mindfulness-based interventions, should be considered. This commentary concludes that there is an urgent need to establish a clear definition of backdraft. This may promote empirical investigations of the backdraft experiences arising from self-compassion interventions. Only through empirical research can we better understand this backdraft phenomenon, with the ultimate goal of reducing short- and long-term harm and improving the efficacy of self-compassion programs.
Clinical experience of consolidative radiotherapy for localized metastatic non-small cell lung cancer who showed favorable tumor response after systemic treatment
Authors: Kim Hakyoung , Kim Sun Myung , Hwang Jeongeun , Yang Dae Sik 
Published: March 2024

Abstract
Background
Our study has aimed to assess the effects of consolidative high-dose radiotherapy on clinical outcomes in patients with localized metastatic non-small cell lung cancer (NSCLC) who showed favorable tumor response after systemic treatment.

Methods
We retrospectively reviewed the medical records of 83 patients with localized metastatic NSCLC, who received systemic therapy followed by consolidative local radiotherapy at the Korea University Guro Hospital between March 2017 and June 2022. In the current study, we defined localized metastatic disease as the presence of one to three metastatic sites at the time of diagnosis. And patients who showed favorable tumor response after systemic treatment, including oligo-progressive disease at the thoracic site which was amenable to curative high-dose local radiotherapy, were included. The planned total dose and fraction size mainly depended on the location of lesions.

Results
The median follow-up time after consolidative radiotherapy was 16 months (range: 5–52 months). The overall 2-year progression-free survival rates were 81.4%. Of 83 patients, only four (4.3%), treated with intensity-modulated radiation therapy, showed an in-field local recurrence. Interestingly, only one patient experienced a local failure among the 20 patients who showed an oligo-progressive disease at the thoracic site on the tumor response evaluation after systemic treatment. Regarding treatment-related pulmonary toxicity, three patients with grade-3 and one patient with grade-4 radiation pneumonitis were presented.

Conclusions
If the disease is sufficiently controlled and localized by systemic therapy, local consolidative radiotherapy is thought to improves local control rates with acceptable treatment-related toxicities in patients with localized metastatic NSCLC, especially those with oligo-progressive disease.