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Wang, Yi, and Tao Li. "Improving semi-supervised co-forest algorithm in evolving data streams." Applied Intelligence 48, no. 10 (February 20, 2018): 3248–62. http://dx.doi.org/10.1007/s10489-018-1149-7.
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Praczyk, Tomasz. "Evolving Co-Adapted Subcomponents in Assembler Encoding." International Journal of Applied Mathematics and Computer Science 17, no. 4 (December 1, 2007): 549–63. http://dx.doi.org/10.2478/v10006-007-0045-9.
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Evolving Co-Adapted Subcomponents in Assembler EncodingThe paper presents a new Artificial Neural Network (ANN) encoding method called Assembler Encoding (AE). It assumes that the ANN is encoded in the form of a program (Assembler Encoding Program, AEP) of a linear organization and of a structure similar to the structure of a simple assembler program. The task of the AEP is to create a Connectivity Matrix (CM) which can be transformed into the ANN of any architecture. To create AEPs, and in consequence ANNs, genetic algorithms (GAs) are used. In addition to the outline of AE, the paper also presents a new AEP encoding method, i.e., the method used to represent the AEP in the form of a chromosome or a set of chromosomes. The proposed method assumes the evolution of individual components of AEPs, i.e., operations and data, in separate populations. To test the method, experiments in two areas were carried out, i.e., in optimization and in a predator-prey problem. In the first case, the task of AE was to create matrices which constituted a solution to the optimization problem. In the second case, AE was responsible for constructing neural controllers used to control artificial predators whose task was to capture a fast-moving prey.
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Deng, Jinliang, Xiusi Chen, Zipei Fan, Renhe Jiang, Xuan Song, and Ivor W. Tsang. "The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting." ACM Transactions on Knowledge Discovery from Data 15, no. 6 (May 19, 2021): 1–25. http://dx.doi.org/10.1145/3450528.
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Transportation demand forecasting is a topic of large practical value. However, the model that fits the demand of one transportation by only considering the historical data of its own could be vulnerable since random fluctuations could easily impact the modeling. On the other hand, common factors like time and region attribute, drive the evolution demand of different transportation, leading to a co-evolving intrinsic property between different kinds of transportation. In this work, we focus on exploring the co-evolution between different modes of transport, e.g., taxi demand and shared-bike demand. Two significant challenges impede the discovery of the co-evolving pattern: (1) diversity of the co-evolving correlation, which varies from region to region and time to time. (2) Multi-modal data fusion. Taxi demand and shared-bike demand are time-series data, which have different representations with the external factors. Moreover, the distribution of taxi demand and bike demand are not identical. To overcome these challenges, we propose a novel method, known as co-evolving spatial temporal neural network (CEST). CEST learns a multi-view demand representation for each mode of transport, extracts the co-evolving pattern, then predicts the demand for the target transportation based on multi-scale representation, which includes fine-scale demand information and coarse-scale pattern information. We conduct extensive experiments to validate the superiority of our model over the state-of-art models.
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Hengpraprohm, Supoj, Kairung Hengpraprohm, Dech Thammasiri, and Suvimol Mukviboonchai. "Co-Evolving Ensemble of Genetic Algorithm Classifier for Cancer Microarray Data Classification." Advanced Science Letters 24, no. 2 (February 1, 2018): 1330–33. http://dx.doi.org/10.1166/asl.2018.10743.
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Yuan, Yinyin. "Abstract IA006: Co-evolving artificial intelligence and pathology." Cancer Prevention Research 15, no. 12_Supplement_1 (December 1, 2022): IA006. http://dx.doi.org/10.1158/1940-6215.dcis22-ia006.
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Abstract A fundamental question in cancer biology is how cancers evolve heterogeneity and treatment resistance. The evolution trajectory of cancer is dictated by selective pressures from treatments and the tumor ecosystem. Artificial intelligence (AI) enables us to directly study geographical patterns of the microenvironment in pathological samples, to infer cancer habitats and niches. Significant challenges and open questions remain: how to establish multidisciplinary platforms, develop reproducible AI tools, and how to leverage pathology, genetic, molecular, and clinical data to improve personalized oncology. Charles Darwin described how the intimate coexistence between flowering plants and insects leads to reciprocal evolutionary changes; this is now known as coevolution. Today, through the demolition of disciplinary barriers, AI and pathology can co-evolve to create evolutionary changes and new paradigms. I will discuss our latest progress on combining AI and experimental technologies for spatial histology and omics data analysis. We aim to understand how cancer evolves within diverse environmental conditions. Our work has revealed a high level of geospatial variation in the tumor microenvironment, with profound implications for early diagnosis, biomarker development, and cancer therapeutics. Citation Format: Yinyin Yuan. Co-evolving artificial intelligence and pathology [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA006.
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Khouri, Selma, and Ladjel Bellatreche. "LOD for Data Warehouses: Managing the Ecosystem Co-Evolution." Information 9, no. 7 (July 17, 2018): 174. http://dx.doi.org/10.3390/info9070174.
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For more than 30 years, data warehouses (DWs) have attracted particular interest both in practice and in research. This success is explained by their ability to adapt to their evolving environment. One of the last challenges for DWs is their ability to open their frontiers to external data sources in addition to internal sources. The development of linked open data (LOD) as external sources is an excellent opportunity to create added value and enrich the analytical capabilities of DWs. However, the incorporation of LOD in the DW must be accompanied by careful management. In this paper, we are interested in managing the evolution of DW systems integrating internal and external LOD datasets. The particularity of LOD is that they contribute to evolving the DW at several levels: (i) source level, (ii) DW schema level, and (iii) DW design-cycle constructs. In this context, we have to ensure this co-evolution, as conventional evolution approaches are adapted neither to this new kind of source nor to semantic constructs underlying LOD sources. One way of tackling this co-evolution issue is to ensure the traceability of DW constructs for the whole design cycle. Our approach is tested using: the LUBM (Lehigh University BenchMark), different LOD datasets (DBepedia, YAGO, etc.), and Oracle 12c database management system (DBMS) used for the DW deployment.
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Clayson, Amanda, Lucy Webb, and Nigel Cox. "When two worlds collide: critical reflection on co-production." Drugs and Alcohol Today 18, no. 1 (March 5, 2018): 51–60. http://dx.doi.org/10.1108/dat-08-2017-0040.
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Purpose The purpose of this paper is to report the findings from reflexive data collection on the evolving co-production research relationship between the two “worlds” of community and academia: people with lived experience and their community intermediaries and academic researchers. It reports analysis of reflections on experience as the different partners explore and evaluate their own experiences of co-productive research within the context of substance use recovery co-production research. Design/methodology/approach The research uses reflexive data from perspectives of an intermediary community partner, academic partners, and community researchers on experiences of a series of co-productive research projects. The aim is to identify thematic features of the co-productive experiences from different positions and through the process of adaptation to a co-productive relationship. Findings This paper outlines what has been learnt from the experience of co-production and what has “worked” for community and academic partners; around the nature of co-production, barriers to performance, and its value to participants and the wider recovery research agenda. Originality/value This paper reports a unique perspective on a developing methodology in health and social care, contributing to a growing body of knowledge pertaining to experiences of co-production research.
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Mohd Amran Mohd Daril, Fozia Fatima, Samar Raza Talpur, and Alhamzah F. Abbas. "Unveiling the Landscape of Big Data Analytics in Healthcare: A Comprehensive Bibliometric Analysis." International Journal of Online and Biomedical Engineering (iJOE) 20, no. 06 (April 12, 2024): 4–24. http://dx.doi.org/10.3991/ijoe.v20i06.48085.
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In the rapidly evolving landscape of healthcare, the digital transformation marked by healthcare 4.0 has spurred a surge in data generation, giving rise to ‘big data’. Big data analytics has become an effective tool in the healthcare industry, revolutionising medical research, patient care, and healthcare management. This study undertakes a meticulous bibliometric analysis, drawing upon a dataset of 2212 articles from the Scopus database spanning 2014 to 2023, to unravel the trajectory of big data analytics in healthcare. The research explores diverse dimensions, from the distribution of studies across years to the productivity rankings of journals, countries, and institutions, elucidating the evolving trends and key contributors. Co-authorship networks and keyword co-occurrence analysis reveal thematic clusters and intellectual structures, contributing to a nuanced understanding of the field. The results underscore the escalating global interest in the fusion of big data and healthcare, illuminating collaborations, and identifying influential players. Additionally, the study identifies pressing challenges, including security concerns and skill shortages, emphasizing the imperative of overcoming these barriers for effective big data applications in healthcare. Serving as a valuable resource for researchers, practitioners, and policymakers, this research not only captures the current landscape but also provides insights for future exploration, contributing to strategic planning in this dynamic domain.
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Judijanto, Loso, Adi Suroso, and Andriya Risdwiyanto. "Bibliometric Assessment of Data-Driven Marketing Research Trends in the Last Two Decades." West Science Business and Management 2, no. 03 (September 30, 2024): 987–1001. http://dx.doi.org/10.58812/wsbm.v2i03.1278.
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This study presents a bibliometric analysis of data-driven marketing research trends over the last two decades, with a focus on its intersection with innovation, decision-making, and related topics. Using VOSviewer for network visualization, we analyze co-authorship, keyword co-occurrence, publication frequency, and country collaboration to uncover key themes and research developments. The findings indicate a significant rise in data-driven marketing research, particularly from 2015 onwards, driven by advancements in big data, machine learning, and artificial intelligence. Co-authorship networks reveal strong interdisciplinary collaboration, while keyword co-occurrence maps highlight the growing role of innovation, decision-making, and machine learning in data-driven marketing. Additionally, country collaboration networks show the United States, China, the United Kingdom, and India as central contributors to global research. The keyword density heatmap emphasizes the increasing focus on data-driven innovation and product development. These insights offer valuable implications for academics and practitioners seeking to understand and apply data-driven marketing in a rapidly evolving digital landscape.
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Yasaka, Noriaki. "Data mining in anti-money laundering field." Journal of Money Laundering Control 20, no. 3 (July 3, 2017): 301–10. http://dx.doi.org/10.1108/jmlc-09-2015-0041.
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Purpose This report aims to focus on how suspicious transaction report is created with data mining methods and used from the point of view of knowledge management. Design/methodology/approach This paper considers data mining versus knowledge management in the anti-money laundering (AML) field. Findings In the AML field, the information and knowledge gained are not necessarily used for or shared with the related shareholders. Creating and co-evolving the network of “knowledge professionals” is the impending assignment in this industry. The first and most important task is knowledge management in the global AML field. Originality/value The report considers the creation with data mining methods and utilization from the point of view of knowledge management.
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Lee, Eun Mi. "Navigating ePolicy Cycle: Big Data, Citizen, and Government." Crisis and Emergency Management: Theory and Praxis 13, no. 9 (September 30, 2023): 39–47. http://dx.doi.org/10.14251/jscm.2023.9.39.
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This study explores the ePolicy cycle, with a specific focus on the intricate relationship between big data, citizen engagement, and government decision-making. The primary objective is to shed light on the complexities, opportunities, and challenges inherent in this dynamic interplay. The study aims to equip policymakers, government officials, data analysts, and engaged citizens with the knowledge and insights needed to effectively navigate this evolving landscape. This research examines the key components of ePolicy within the context of data-driven governance, emphasizing the principles of data privacy, security, and transparency. Furthermore, it explores the innovative ways in employed by governments to leverage the potential of big data analytics for making more informed and responsive policy decisions, as well as the growing role of citizens in co-creating public policies through digital channels. As it navigates this multifaceted terrain, the aim is to foster a deeper understanding of the ePolicy cycle and its implications for modern governance. This study seeks to empower stakeholders at all levels to responsibly leverage big data, engage citizens effectively, and ultimately forge a more collaborative, data-informed, and participatory future for government policy-making.
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Helbing, Dirk, Farzam Fanitabasi, Fosca Giannotti, Regula Hänggli, Carina I. Hausladen, Jeroen van den Hoven, Sachit Mahajan, Dino Pedreschi, and Evangelos Pournaras. "Ethics of Smart Cities: Towards Value-Sensitive Design and Co-Evolving City Life." Sustainability 13, no. 20 (October 9, 2021): 11162. http://dx.doi.org/10.3390/su132011162.
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The digital revolution has brought about many societal changes such as the creation of “smart cities”. The smart city concept has changed the urban ecosystem by embedding digital technologies in the city fabric to enhance the quality of life of its inhabitants. However, it has also led to some pressing issues and challenges related to data, privacy, ethics inclusion, and fairness. While the initial concept of smart cities was largely technology- and data-driven, focused on the automation of traffic, logistics and processes, this concept is currently being replaced by technology-enabled, human-centred solutions. However, this is not the end of the development, as there is now a big trend towards “design for values”. In this paper, we point out how a value-sensitive design approach could promote a more sustainable pathway of cities that better serves people and nature. Such “value-sensitive design” will have to take ethics, law and culture on board. We discuss how organising the digital world in a participatory way, as well as leveraging the concepts of self-organisation, self-regulation, and self-control, would foster synergy effects and thereby help to leverage a sustainable technological revolution on a global scale. Furthermore, a “democracy by design” approach could also promote resilience.
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Md Abdul Ahad Maraj, Mahmudul Hasan, Md Mostafizur Rahman, Md Shakawat Hossain. "ADVANCING DATA SECURITY IN GLOBAL BANKING: INNOVATIVE BIG DATA MANAGEMENT TECHNIQUES." GLOBAL MAINSTREAM JOURNAL 1, no. 2 (May 1, 2024): 26–37. http://dx.doi.org/10.62304/ijmisds.v1i2.133.
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In the context of the rapidly evolving digital landscape, the banking sector faces unprecedented challenges in data security due to the massive volumes of sensitive information they manage. This paper examines the implementation and efficacy of innovative big data management techniques within global banking institutions to enhance data security. It discusses the integration of predictive analytics, the impact of regulatory changes, and the adoption of emerging technologies like blockchain and advanced encryption, which collectively redefine data security strategies. The study utilises a qualitative case study approach focusing on three central banks—JPMorgan Chase & Co., HSBC Holdings plc, and the Industrial and Commercial Bank of China—highlighting how each bank utilises big data techniques to address specific security challenges, comply with regulations, and enhance customer trust. The findings underscore the crucial role of innovative data management strategies in mitigating risks and safeguarding data against cyber threats, suggesting that these technologies fulfil security needs and offer competitive advantages in customer trust and regulatory compliance. The paper concludes with strategic recommendations for banks to enhance their data security measures and suggests directions for future research in data security within the banking industry.
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Chen, Lianfu, Simon T. Segar, Bhanumas Chantarasuwan, Da-Mien Wong, Rong Wang, Xiaoyong Chen, and Hui Yu. "Adaptation of Fig Wasps (Agaodinae) to Their Host Revealed by Large-Scale Transcriptomic Data." Insects 12, no. 9 (September 11, 2021): 815. http://dx.doi.org/10.3390/insects12090815.
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Figs and fig wasps are highly species-specific and comprise a model system for studying co-evolution and co-speciation. The evolutionary relationships and molecular adaptations of fig wasps to their fig hosts are poorly understood, and this is in part due to limited sequence data. Here, we present large-scale transcriptomic datasets of 25 fig wasp species with the aim of uncovering the genetic basis for host specificity. Our phylogenetic results support the monophyly of all genera associated with dioecious figs, and two genera associated with monoecious figs, Eupristina and Platyscapa, were revealed to be close relatives. We identified gene loss and gain, potentially rapidly evolving genes, and genes under positive selection. Potentially functional changes were documented and we hypothesize as to how these may determine host specificity. Overall, our study provides new insights into the evolutionary diversification of fig wasps and contributes to our understanding of adaptation in this group.
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Latorraca, Tássia, Ana Sofia Guimarães, and Bárbara Rangel. "Bibliometric Analysis of Personalized 3D-Printed Concrete-Based Modules for Construction: Leveraging the Ordinatio Method." Buildings 14, no. 3 (March 15, 2024): 802. http://dx.doi.org/10.3390/buildings14030802.
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The research landscape of personalized 3D-printed concrete-based modules for construction and their impact on thermal performance through generative design methods is explored through a bibliometric analysis. Comprehensive analysis techniques, including bibliographic data and visualization with VoSviewer, are employed to unveil collaborative networks, influential articles, research trends, and emerging themes within this domain. Global contributions are showcased, with citations predominantly from the UK and USA, while Denmark and Australia demonstrate a significant impact relative to publication numbers. Prominent authors like Buswell, Mechtcherine, and Zhang are highlighted through co-authorship analysis, revealing evolving collaborative patterns over time. Seminal works and influential authors are identified through co-citation analysis, providing insights into intellectual networks. Source citation analysis emphasizes the importance of sustainability and advanced manufacturing methods through key journals in the field. Keyword co-occurrence analysis identifies the core themes, including 3D concrete printing, additive manufacturing, and sustainability. Emerging trends indicate a growing focus on sustainability and adopting advanced manufacturing technologies. These insights have implications for future research, guiding impactful contributions in this evolving field.
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Mishra, Deepa, Zongwei Luo, Shan Jiang, Thanos Papadopoulos, and Rameshwar Dubey. "A bibliographic study on big data: concepts, trends and challenges." Business Process Management Journal 23, no. 3 (June 5, 2017): 555–73. http://dx.doi.org/10.1108/bpmj-10-2015-0149.
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Purpose The purpose of paper is twofold. First, it provides a consolidated overview of the existing literature on “big data” and second, it presents the current trends and opens up various future directions for researchers who wish to explore and contribute in this rapidly evolving field. Design/methodology/approach To achieve the objective of this study, the bibliographic and network techniques of citation and co-citation analysis was adopted. This analysis involved an assessment of 57 articles published over a period of five years (2011-2015) in ten selected journals. Findings The findings reveal that the number of articles devoted to the study of “big data” has increased rapidly in recent years. Moreover, the study identifies some of the most influential articles of this area. Finally, the paper highlights the new trends and discusses the challenges associated with big data. Research limitations/implications This study focusses only on big data concepts, trends, and challenges and excludes research on its analytics. Thus, researchers may explore and extend this area of research. Originality/value To the knowledge of the authors, this is the first study to review the literature on big data by using citation and co-citation analysis.
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Nur Fajari, Sihabudin, and Isti Raafaldini Mirzanti. "Capturing Consumer Preferences to Develop the New Product Development of Ordinary Kids Through The Co-Creation Process." European Journal of Business and Management Research 7, no. 6 (November 3, 2022): 43–50. http://dx.doi.org/10.24018/ejbmr.2022.7.6.1665.
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The e-commerce fashion industry is rapidly evolving. As the seasons change, consumer preferences shift according to context. As recorded during the COVID-19 outbreak, many significant changes in style, behavior, and habits are either for adults or children. Hence, to capture this change, businesses must collaborate with their customers in developing products to avoid failure and meet positive perceptions. A qualitative methodology was used as an approach. Primary data come from interviews, documentation, and question boxes with purposive sampling. Secondary data includes articles, books, journals, and technical documents. The analysis for this study finds the main results for the next new product development by co-creation process. First, there are main preferences that must be put on children's clothing such as soft fabric, adorable, fashionable, and fit size; second, the author developed an integrative collaboration involving external and internal participation, and engagement as requisites for five co-creation processes (co-ideation, co-evaluation, co-design, co-test, and co-launch) in product development; third, participant in this study give a positive response to the product in accordance with ideation proposal and inputs.
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Fosci, Paolo, and Giuseppe Psaila. "Towards Flexible Retrieval, Integration and Analysis of JSON Data Sets through Fuzzy Sets: A Case Study." Information 12, no. 7 (June 22, 2021): 258. http://dx.doi.org/10.3390/info12070258.
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How to exploit the incredible variety of JSON data sets currently available on the Internet, for example, on Open Data portals? The traditional approach would require getting them from the portals, then storing them into some JSON document store and integrating them within the document store. However, once data are integrated, the lack of a query language that provides flexible querying capabilities could prevent analysts from successfully completing their analysis. In this paper, we show how the J-CO Framework, a novel framework that we developed at the University of Bergamo (Italy) to manage large collections of JSON documents, is a unique and innovative tool that provides analysts with querying capabilities based on fuzzy sets over JSON data sets. Its query language, called J-CO-QL, is continuously evolving to increase potential applications; the most recent extensions give analysts the capability to retrieve data sets directly from web portals as well as constructs to apply fuzzy set theory to JSON documents and to provide analysts with the capability to perform imprecise queries on documents by means of flexible soft conditions. This paper presents a practical case study in which real data sets are retrieved, integrated and analyzed to effectively show the unique and innovative capabilities of the J-CO Framework.
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Brodsky, Casey N., Ryan G. Hadt, Dugan Hayes, Benjamin J. Reinhart, Nancy Li, Lin X. Chen, and Daniel G. Nocera. "In situ characterization of cofacial Co(IV) centers in Co4O4 cubane: Modeling the high-valent active site in oxygen-evolving catalysts." Proceedings of the National Academy of Sciences 114, no. 15 (March 27, 2017): 3855–60. http://dx.doi.org/10.1073/pnas.1701816114.
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The Co4O4 cubane is a representative structural model of oxidic cobalt oxygen-evolving catalysts (Co-OECs). The Co-OECs are active when residing at two oxidation levels above an all-Co(III) resting state. This doubly oxidized Co(IV)2 state may be captured in a Co(III)2(IV)2 cubane. We demonstrate that the Co(III)2(IV)2 cubane may be electrochemically generated and the electronic properties of this unique high-valent state may be probed by in situ spectroscopy. Intervalence charge-transfer (IVCT) bands in the near-IR are observed for the Co(III)2(IV)2 cubane, and spectroscopic analysis together with electrochemical kinetics measurements reveal a larger reorganization energy and a smaller electron transfer rate constant for the doubly versus singly oxidized cubane. Spectroelectrochemical X-ray absorption data further reveal systematic spectral changes with successive oxidations from the cubane resting state. Electronic structure calculations correlated to experimental data suggest that this state is best represented as a localized, antiferromagnetically coupled Co(IV)2 dimer. The exchange coupling in the cofacial Co(IV)2 site allows for parallels to be drawn between the electronic structure of the Co4O4 cubane model system and the high-valent active site of the Co-OEC, with specific emphasis on the manifestation of a doubly oxidized Co(IV)2 center on O–O bond formation.
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Ferreira, Manuel Portugal, Christian Daniel Falaster, Cláudia Sofia Frias Pinto, and Renata Canela. "Publishing in co-authorship: A comparison of the motivations between more and less prolific Management scholars in Brazil." Administração: Ensino e Pesquisa 21, no. 2 (May 1, 2020): 56–88. http://dx.doi.org/10.13058/raep.2020.v21n2.1576.
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In this study, we investigate what more and less prolific scholars – that publish more or less scientific articles – search for in their co-authorship ties. Specifically, we seek to understand if and how there are differences in the motivations presiding to co-authorship between more and less prolific researchers. Research on co-authorship is of interest to the academia, since the majority of the articles are published in co-authorship and co-authorships may have an important impact in the scholars’ career. We have collected survey data with 171 Brazilian management faculty, about their motivations, pressures, and choices for co-authorship. We identify significant differences on the perceived pressures to publish, source of pressure, motivations to work in co-authorship and the contributions warranting co-authorship across more and less prolific researchers. We contribute to the debate on the development of scholars and the formation of co-authorship ties, suggesting that co-authorship may be strategically managed and evolving along the professional path of the researchers, and leaving the possibility that scholars’ networks of co-authorship evolve strategically as they seek different goals.
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Luo, Shishi, and Alan S. Perelson. "The challenges of modelling antibody repertoire dynamics in HIV infection." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1676 (September 5, 2015): 20140247. http://dx.doi.org/10.1098/rstb.2014.0247.
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Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. We describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.
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Lazrak, Youssra, Amina El Idrissi Tissafi, and Rachid Boukharrazi. "Exploring value co-creation strategies to improve e-reputation in the hotel industry: insights from Fez, Morocco." Innovative Marketing 20, no. 4 (November 15, 2024): 112–20. http://dx.doi.org/10.21511/im.20(4).2024.10.
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In the context of a rapidly evolving digital landscape, the co-creation of value with customers has gained importance in both academic and business realms, particularly within the hospitality sector. This study aims to analyze the integration of value co-creation strategies to enhance the online reputation of hotels, with a focus on active customer involvement. Using a qualitative research strategy, the study involved semi-structured, in-person interviews with twenty hotel managers from various hotels in Fez, Morocco. Thematic analysis of the interview data, conducted using NVivo 14 software, highlighted the critical role of value co-creation, customer experience, and e-reputation in enhancing hotels’ online reputation. Key sub-themes identified under value co-creation include active collaboration, innovation based on customer needs, and taking into account online comments. Regular online surveys were also significant for gathering customer proposals. In terms of customer experience, themes such as engagement, satisfaction, and perception were prominent. E-reputation management emerged as crucial, with sub-themes including real-time monitoring and response, integrating feedback into improvement processes, adopting advanced tools, and adapting online reputation strategies based on continuous feedback. The results underscore the interconnectedness of customer engagement, experience, and e-reputation. Integrating strategies that consider online comments and adopt advanced tools significantly improves the online reputation of hotels. Conclusions advocate for a cohesive approach prioritizing customer experience and continuous improvement, through innovative technologies and strategic adjustments to meet evolving customer needs, fostering a positive and enduring hotel online presence.
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Bujak, Jonathan, and Alexandra Bujak. "Origin and Evolution of the Azolla Superorganism." Plants 13, no. 15 (July 29, 2024): 2106. http://dx.doi.org/10.3390/plants13152106.
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Azolla is the only plant with a co-evolving nitrogen-fixing (diazotrophic) cyanobacterial symbiont (cyanobiont), Nostoc azollae, resulting from whole-genome duplication (WGD) 80 million years ago in Azolla’s ancestor. Additional genes from the WGD resulted in genetic, biochemical, and morphological changes in the plant that enabled the transmission of the cyanobiont to successive generations via its megaspores. The resulting permanent symbiosis and co-evolution led to the loss, downregulation, or conversion of non-essential genes to pseudogenes in the cyanobiont, changing it from a free-living organism to an obligate symbiont. The upregulation of other genes in the cyanobiont increased its atmospheric dinitrogen fixation and the provision of nitrogen-based products to the plant. As a result, Azolla can double its biomass in less than two days free-floating on fresh water and sequester large amounts of atmospheric CO2, giving it the potential to mitigate anthropogenic climate change through carbon capture and storage. Azolla’s biomass can also provide local, low-cost food, biofertiliser, feed, and biofuel that are urgently needed as our population increases by a billion every twelve years. This paper integrates data from biology, genetics, geology, and palaeontology to identify the location, timing and mechanism for the acquisition of a co-evolving diazotrophic cyanobiont by Azolla’s ancestor in the Late Cretaceous (Campanian) of North America.
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Aryatwijuka, Dr Wilbroad, Joan Shina Arimpa, Assoc Prof Henry Mutebi, Assoc Prof Benjamin Tukamuhabwa, and Prof Moses Muhwezi. "Co-evolution and Sustainable Procurement in Humanitarian Organizations: The Mediating effect of Self-organization." American Journal of Supply Chain Management 9, no. 3 (September 27, 2024): 26–44. http://dx.doi.org/10.47672/ajscm.2454.
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Purpose: The study examined the role of self-organization in facilitating co-evolution and sustainable procurement in Humanitarian Organisations (HOs). Materials and Methods: Using simple random sampling, data were collected from 79 Hos with respondents purposively selected following a quantitative cross-sectional design, which was analyzed through partial least structural equation modelling (PLS-SEM) using SmartPLS version 4.0.9.0. Findings: Co-evolution and self-organization play a significant role in the attainment of sustainable procurement, and the relationship between co-evolution and sustainable Procurement is partially mediated by self-organization. Implications: Co-evolutionary and self-organizing approach are introduced to allow humanitarian agencies procure sustainably during relief operations. HO procurement functions can interact with other partners in their procurement activities by continuously engaging each other and sharing resources. By confirming mediation, the mediation role of self-organization in the relationship between co-evolution and sustainable procurement among HOs, the study provides critical insights in the evolving literature. Implications to Theory, Practice and Policy: The study shows that co-evolution connects with self-organization and sustainable procurement. Furthermore, it explains how self-organization mediates the relationship between co-evolution and sustainable procurement.
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Kuazaqui, Edmir. "Marketing, Digital Environment and Big Data: A Preliminary Discussion about the Influences within A Company." Journal of Business Theory and Practice 8, no. 4 (December 4, 2020): p72. http://dx.doi.org/10.22158/jbtp.v8n4p72.
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This article discusses how Big Data influences Brazilian enterprises from the view point of marketing, once there is a deepening in the use of Information Technology (IT) in the business environment and is a differentiated competitive factor, as well as for the consumer. The bibliographical research involved subjects such as the evolution of digital marketing, digital inclusion, co-creation, social media, and Big Data, to have a theoretical vision. Through in-depth qualitative research, using the Focus Group method, the impressions of professionals with academic backgrounds were collected regarding knowledge, abilities and necessary competences for these enterprises to have full results, the need for curve experience, adaptability to the exponential world, as well as the opportunities and challenges stemming from this reality. One of the highlighted points of this research was the need to be dealing in still evolving digital atmospheres and that of ethical behavior, both in the collection, dissemination, and application of digital marketing strategies, as well as in information security.
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Castro, Cyndi V., and Hanadi S. Rifai. "Development and Assessment of a Web-Based National Spatial Data Infrastructure for Nature-Based Solutions and Their Social, Hydrological, Ecological, and Environmental Co-Benefits." Sustainability 13, no. 19 (October 4, 2021): 11018. http://dx.doi.org/10.3390/su131911018.
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Comprehensive datasets for nature-based solutions (NBS), and their diverse relationships have not yet been accumulated into a deployable format. This research describes the development of a novel National Spatial Data Infrastructure (NSDI) system for NBS co-benefits throughout the contiguous United States. Here, we gather and integrate robust geospatial datasets from the social, ecological, environmental, and hydrologic domains using seamless, cloud-based data services to facilitate the trans-disciplinary assessment of NBSs as a function of society and Earth. This research enhances practical decision making and research by assimilating web-based datasets and describing the missing links between national policy and robust adoption of NBSs as a sustainability solution. This NSDI serves to foster participatory planning capabilities and integrate local sustainability goals into decision–support frameworks. Such a platform strengthens the knowledge base necessary for addressing multiple, co-evolving issues of societal relevance, an essential component of fully espousing NBSs within the realm of socio-technological systems and improving policies and implementation regarding sustainable solutions. The efficacy of the proposed platform to serve as a holistic data information system is assessed by exploring important characteristics associated with geospatial NSDI tools, namely, openness, spatial functionality, scalability, and standardization. By placing GIS strengths and weaknesses in the context of transdisciplinary NBSs, we reveal strategic directions toward further co-production of such NSDIs. We conclude with recommendations for facilitating a shared vision of transdisciplinary technologies to strengthen the amalgamation of broad co-benefits and multi-disciplinary influences in sustainability planning.
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Jayesh Jayaram, Dr Binoy Thomas,. "Assessing the Effectiveness of In-Store Promotions for Private Label Brands in Retail Stores." European Economic Letters (EEL) 13, no. 5 (January 12, 2024): 1851–60. http://dx.doi.org/10.52783/eel.v13i5.997.
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In an era marked by intense market competition and evolving consumer preferences, the pivotal role of In-Store Promotions (ISPs) in shaping the success of Private Label Brands (PLBs) is of crucial importance. This research paper delves deeply into the dynamic landscape of ISPs and their profound impact on the market performance of PLBs within the contemporary retail environment. Using a descriptive research design, the study aims to assess the effectiveness of ISPs for PLBs and explore their influence on Consumer Observation (CO), Consumer Interest (CI), and Purchase Behaviour (PB). Primary data were collected from 206 customers of various supermarkets using a purposive sampling method. A structured questionnaire was disseminated using Google Forms to gather data. The data underwent statistical analysis, including Correlation, Regression, and Mediation analysis, utilising the SPSS 24.0 software package. The findings of this study reveal a positive relationship of CO and CI with PB, underscoring the substantial significance of ISPs for PLBs. Additionally, the analysis unveiled the mediating role of CI in the CO - PB relationship. These research findings offer valuable insights that can enhance ISPs and deepen our understanding of consumer preferences within the dynamic retail industry landscape.
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Cho, Yoon-Sik, Greg Steeg, and Aram Galstyan. "Co-Evolution of Selection and Influence in Social Networks." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (August 4, 2011): 779–84. http://dx.doi.org/10.1609/aaai.v25i1.7952.
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Many networks are complex dynamical systems, where both attributes of nodes and topology of the network (link structure) can change with time. We propose a model of co-evolving networks where both node attributes and network structure evolve under mutual influence. Specifically, we consider a mixed membership stochastic blockmodel, where the probability of observing a link between two nodes depends on their current membership vectors, while those membership vectors themselves evolve in the presence of a link between the nodes. Thus, the network is shaped by the interaction of stochastic processes describing the nodes, while the processes themselves are influenced by the changing network structure. We derive an efficient variational inference procedure for our model, and validate the model on both synthetic and real-world data.
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Börner, Katy, Olga Scrivner, Leonard E. Cross, Michael Gallant, Shutian Ma, Adam S. Martin, Lisel Record, Haici Yang, and Jonathan M. Dilger. "Mapping the co-evolution of artificial intelligence, robotics, and the internet of things over 20 years (1998-2017)." PLOS ONE 15, no. 12 (December 2, 2020): e0242984. http://dx.doi.org/10.1371/journal.pone.0242984.
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Understanding the emergence, co-evolution, and convergence of science and technology (S&T) areas offers competitive intelligence for researchers, managers, policy makers, and others. This paper presents new funding, publication, and scholarly network metrics and visualizations that were validated via expert surveys. The metrics and visualizations exemplify the emergence and convergence of three areas of strategic interest: artificial intelligence (AI), robotics, and internet of things (IoT) over the last 20 years (1998-2017). For 32,716 publications and 4,497 NSF awards, we identify their topical coverage (using the UCSD map of science), evolving co-author networks, and increasing convergence. The results support data-driven decision making when setting proper research and development (R&D) priorities; developing future S&T investment strategies; or performing effective research program assessment.
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Mohd Said, Mohd Azrin. "Design and Develop Low-Cost Device on Monitoring Environmental Indoor Air Quality in Factory." Journal of Engineering and Science Research 4, no. 4 (October 30, 2020): 6–11. http://dx.doi.org/10.26666/rmp.jesr.2020.4.2.
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Environmental indoor air quality is one of the major concerns in occupational safety and health issues related to workers. Nowadays, the evolving of Internet of Things (IoT), the monitoring of the surrounding environmental desired parameters is more fascinating with the use of various sensors. Real time data now can be monitored with the Wi-Fi connection where the data being transfer across the network cloud with different platform service. This research focus is on the environmental monitoring for indoor air quality in terms of carbon monoxide (CO) in selected palm oil mill factory. This project aims to benefit the workers in a way where air quality is monitored. This low-cost device air quality monitoring (LCDAQM) used an ESPduino-32 to collect and process sensed data to the ThingSpeak platform service that can be monitored through web based or apps. The level of the carbon monoxide (CO) will light up the red LED when reach more than 50ppm which was set by OSHA. Result shows that level of CO in factory is unhealthy and need future engineering control action. The validation between LCDAQM and RS CO meter show the percentage error of 14.41%. Therefore, this study will help workers and factory to monitor and reduce the occupational safety and health (OSH) related problems to indoor air quality in factory.
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Suwarsi, Sri, Nizar Fauzan, and Nabilla Anasty Fahzaria. "Amplifying Brand Advocacy Through an Evolving Trend in The Future Research: Bibliometric Analysis." Revista de Gestão Social e Ambiental 18, no. 2 (February 27, 2024): e04893. http://dx.doi.org/10.24857/rgsa.v18n2-074.
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Objective: The purpose of this article is to investigate brand advocacy reviews and conduct a systematic analysis utilizing bibliometric analysis to investigate the evolving research in the marketing sector, specifically consumer behavior. Method: Based on a bibliometric examination of 736 research publications from the Scopus data-based index from 2010 to 2023, this study employed citation, co-citation, and co-occurrence of authors' keyword analysis. Results and conclusion: This current study elucidates the development of brand advocacy research during the past decade. The research on brand loyalty for service marketing among young clients reveals three areas of particular significance. In addition to studies on brand advocacy and the potential future direction of this research subject, no other topics are covered. Implications of the research: This study is limited by its reliance on a single database and its inability to provide contextual information regarding the citation structure of the publications discovered throughout the review process. Originality/value: This study aims to identify the philosophical framework of brand advocacy literature and to trace the sector's historical development.
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Shukla, Umesh, Nita Radhakrishnan, Bhanu Kiran Bhakhri, Ravi Shankar, Sohini Ghosh, Vikas Jain, Dharmendra K. Singh, and Devendra K. Gupta. "Children, comorbidities and COVID-19 - What tilts the balance?" Asian Journal of Medical Sciences 12, no. 3 (March 1, 2021): 10–13. http://dx.doi.org/10.3126/ajms.v12i3.32738.
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Background: Data on the outcome of children with SARS-COV-2 infection (COVID-19) is still evolving as the pandemic unfolds.
Aims and Objective: The present study aims at describing the clinical severity, course and outcome of COVID-19 in children who had underlying illnesses or co-infections.
Materials and Methods: Retrospective, single center, observational study, conducted in a pediatric tertiary care center at Noida (National Capital Region, India).
Results: We analyzed the data of 15 children with co-morbidities associated with COVID-19. Cancer (n=4, 26.6%), co-infections (n=5, 33.3%), Thalassemia major (n=2, 13.3%) and one child each with celiac disease, cholelithiasis, Duchenne muscular dystrophy and multiple rib fractures were diagnosed with COVID-19. None were asymptomatic. 9 children (60%) had mild symptoms and 4 had moderate symptoms (26.6%) with respiratory distress. 2 children had severe respiratory distress requiring high flow oxygen. Convalescent plasma, IVIG, Oseltamivir, Azithromycin, Hydroxychloroquine were given as treatment in varying combinations. All children recovered from COVID-19.
Conclusion: Active malignancy, hypogammaglobinemia, underlying lung disease were associated with moderate to severe symptoms in this series of patients. Convalescent plasma helped in both children with severe hypoxia.
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Saunders, Lucy, Harriott Nowell, Lynne Thomas, Paul Raithby, and Chick Wilson. "Single crystal synchrotron X-ray diffraction for imaging hydrogen bond evolution." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C559. http://dx.doi.org/10.1107/s2053273314094406.
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Hydrogen bonding is a valuable intermolecular interaction in "engineering" solid-state materials. This is because of the directionality and relative strength (1) of these bonds. Hydrogen bonds enable charge and energy transfer, via H-bond evolution, in a range of biological and chemical systems (2). Recent work has demonstrated that single crystal X-ray diffraction can be used to image the evolution of hydrogen bonds, including variable temperature proton migration and proton disorder processes. In particular, in a recent study of the temperature dependent proton disorder in hydrogen bonded 3,5-dinitrobenzoic acid (3,5-DNBA) dimers, the proton disorder deduced from data collected on an X-ray laboratory source is in agreement with that found from neutron data (3). This work focuses on variable temperature single crystal synchrotron X-ray diffraction, for the imaging of evolving hydrogen bonds. The development of appropriate methodology is important here, particularly as previous studies have involved laboratory X-ray sources only. Results will be presented from variable temperature data collections on I19, at the Diamond Light Source, and on beamline 11.3.1, at the Advanced Light Source (ALS), on systems such as 3,5-DNBA and co-crystals of benzimidazole, both exhibiting proton disorder across hydrogen bonding interactions. Synchrotron X-ray diffraction measurements have also been used to follow the change in the position of a proton within an intramolecular [N–H···N]+ hydrogen bond across a range of proton-sponge molecular complexes. Importantly, it has been possible to visualise the evolving hydrogen atom position in Fourier difference electron density maps generated from the synchrotron data. In particular, for the 35-DNBA study, the clearest picture of the evolving hydrogen atom position is observed in those generated from data collected at the ALS; even clearer than that observed in X-ray laboratory and neutron measurements on the same system.
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Al-Rousan, Thamer, and Hassan Abualese. "E-Learning Impact on Higher Education Institutions during COVID-19 Pandemic: A Bibliometric Analysis." International Journal of Education and Information Technologies 18 (October 11, 2024): 98–104. http://dx.doi.org/10.46300/9109.2024.18.10.
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The COVID-19 pandemic forced a rapid shift to online learning in higher education. To understand this evolving field better, this study employed a powerful technique called bibliometrics. Researchers analyzed scholarly publications between 2020 and 2023 in Web of Science, focusing on keywords related to e-learning, universities, and the pandemic's impact. This data-driven approach provided a more comprehensive picture than traditional reviews, revealing connections between research topics, researchers, and specific studies. Furthermore, the VOSviewer tool was employed to identify frequently co-occurring keywords, thus uncovering the major themes within the research. This analysis of keyword co-occurrence allowed the study to pinpoint key trends and areas of focus in e-learning for higher education institutions. Ultimately, this research offers valuable insights for researchers, educators, and policymakers navigating the changing educational landscape and the future of e-learning in higher education.
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PRATHIBA, GEETHA, MENDE MANEESHA, G.SHARANYA, and K.SONYSANDHYA. "REPRESENTING FINE GRINED CO-OCCURANCES FOR BEHAVIOR BASED FRAUD DETECTION IN ONLINE SYSTEM." Journal of Engineering Sciences 15, no. 10 (2024): 64–70. http://dx.doi.org/10.36893/jes.2024.v15i10.09.
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The vigorous development of e-commerce breeds cybercrime. Online payment fraud detection, a challenge faced by online service, plays an important role in rapidly evolving e-commerce. Behavior-based methods are recognized as a promising method for online payment fraud detection. However, it is a big challenge to build highresolution behavioral models by using low-quality behavioral data. In this work, we mainly address this problem from data enhancement for behavioral modeling. We extract fine-grained co-occurrence relationships of transactional attributes by using a knowledge graph. Furthermore, we adopt the heterogeneous network embedding to learn and improve representing comprehensive relationships. Particularly, we explore customized network embedding schemes for different types of behavioral models, such as the population-level models, individual-level models, and generalized-agentbased models. The performance gain of our method is validated by the experiments over the real dataset from a commercial bank. It can help representative behavioral models improve significantly the performance of online banking payment fraud detection. To the best of our knowledge, this is the first work to realize data enhancement for diversified behavior models by implementing network embedding algorithms on attribute-level co-occurrence relationships.
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Eddy, Brian, and Andrea Dort. "Integrating Socio-Economic Data for Integrated Land Management (ILM): Examples from the Humber River Basin, Western Newfoundland." GEOMATICA 65, no. 3 (September 2011): 283–91. http://dx.doi.org/10.5623/cig2011-044.
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The application of geomatics for Integrated Land Management (ILM) often focuses on analysis and modelling of bio-physical dimensions of a study area. However, data about human dimensions, such as socioeconomic conditions of communities within a region, are equally important to consider as key drivers behind various ILM scenarios. Incorporating socio-economic conditions of communities in a spatially-explicit manner presents a number of challenges due to differences in spatial frameworks associated with human and biophysical data. This paper presents an approach for integrating socio-economic data for ILM analysis that allows better geospatial alignment and integration of human and biophysical dimensions, and further allows for a more local, contextual analysis of the relationships and dependencies particular communities have with the surrounding landscape and its resources. It does this using a concept of communities as ‘human habitats’ whereby each community in a region can be analyzed in terms of how it is co-evolving and adapting with other communities in the region and with natural changes in the bio-physical landscape.
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Cambra-Fierro, Jesus, Iguacel Melero-Polo, and F. Javier Sese. "Customer value co-creation over the relationship life cycle." Journal of Service Theory and Practice 28, no. 3 (May 14, 2018): 336–55. http://dx.doi.org/10.1108/jstp-01-2017-0009.
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PurposeDrawing from the theory of relationship dynamics, the purpose of this paper is to investigate how the relationship life cycle moderates the link between relationship quality and customer value co-creation. As customer-firm relationships pass through different stages (exploration, buildup, maturity, and decline) characterized by distinct customer behaviors, this study proposes a dynamic conceptual framework.Design/methodology/approachA questionnaire was administered in financial services firms. The final valid sample comprised 2,000 individuals. Subjective customer information from the questionnaire was combined with objective data that the financial entity provided.FindingsThe results demonstrate that the relationship life cycle plays a key moderating role, revealing that, in the buildup and maturity stages, the influence of relationship quality on customer value co-creation is stronger than in the decline stage. However, for customers in the exploration stage, relationship quality does not lead to customer value co-creation behaviors.Practical implicationsAs customer relationship stages are constantly evolving, this study provides companies with additional interesting tools to personalize business strategies and to adapt marketing investments to the specific situation of customers.Originality/valueTo the authors’ knowledge, this is the first study to consider how the relationship life cycle influences the strength with which relationship quality promotes customer value co-creation.
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Richard, Brendan. "Hotel chains: survival strategies for a dynamic future." Journal of Tourism Futures 3, no. 1 (April 3, 2017): 56–65. http://dx.doi.org/10.1108/jtf-06-2016-0018.
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Purpose The purpose of this paper is to better understand the future of hotel chains by exploring the evolving expectations of guests, potential innovations, emerging opportunities, and likely future scenarios. Design/methodology/approach A literature review consisting of current events, industry reports, and recent trends is utilized to summarize and categorize the challenges and opportunities facing hotel chains. Findings The future of hotel chains will be driven by the convergence of an increasingly competitive landscape, along with a diverse evolving customer base seeking out unique and individualized experiences. In order to survive in the future hotel chains will have to: listen to and learn from guests incorporating big data insights, go beyond segments to provide personalized services, continuously develop the brand through signature experiences, utilize collaboration and open innovation to maintain an edge in technology and service, and through total revenue management generate ancillary revenues and maximize guest spend. Originality/value This paper provides a comprehensive set of recommendations to hotel chains highlighting opportunities related to: financing, revenue generation, personalization, and co-creation.
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Nikitkov, Alexei N., Dan N. Stone, and Timothy C. Miller. "Internal Controls, Routine Activity Theory (RAT), and Sustained Online Auction Deception: A Longitudinal Analysis." Journal of Information Systems 28, no. 1 (January 1, 2014): 311–37. http://dx.doi.org/10.2308/isys-50708.
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ABSTRACT This paper adapts and extends routine activity theory (RAT) to investigate the co-evolution of eBay's controls with mundane crime in the rapidly growing auction market of 1997–2005. A suspected deceptive seller's eight-year account history indicates the presence of the three market characteristics that RAT identifies as essential for deception: (1) a motivated offender, (2) suitable targets, and (3) an absence of capable guardians (i.e., regulation and eBay controls). The results document the co-evolution of a deceptive seller's tactics with eBay's controls. The investigation introduces (1) a new market, i.e., the early online auctions, (2) a new theory, i.e., RAT, and (3) new data, i.e., of a long-term deceptive seller, to the accounting controls literature. Contributions include tracing the evolving eBay control system, considering eBay's feedback system as an emergent form of continuous monitoring, and investigating the potential of RAT as an alternative theory for understanding control violations and informing accounting control analysis and design. Data Availability: The archival data are available from public sources. The primary data are available to scholars willing to sign agreements that protect the confidentiality of the sources.
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George, Jason T., Herbert Levine, Jeffrey J. Molldrem, and Haven Garber. "Stochastic cancer-immune coevolution: Implications for cancer incidence and immunotherapeutic efficacy." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e14023-e14023. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e14023.
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e14023 Background: Despite recent progress, robust treatment strategies that lead to durable remission are still lacking for many cancer types. This disease is difficult to treat owing in part to the complexity introduced by a heterogeneous population of cancer cells capable of evolving mechanisms of resistance to traditional therapy. Nonetheless, the discovery and continued optimization of T-cell immunotherapy has revolutionized the treatment of many cancers. This treatment strategy stands out from other approaches in its unique ability to co-evolve alongside an evading tumor. While promising, such therapies are also complex. For example, allogeneic stem cell transplantation leverages a donor-derived T-cell repertoire to treat patients with refractory hematologic malignancies and relies upon a delicate balance between desirable anti-tumor effects and potentially life-threatening graft-versus-host-disease. Currently, the decision to utilize this therapy and others like it is largely influenced by prior empirical evidence. Thus, there is great need for quantitative models of the cancer-immune interaction to generate testable predictions of treatment outcome, which could then be validated prior to T-cell immunotherapy administration. Methods: We develop a foundational mathematical model to investigate the properties of stochastic tumor-immune co-evolution using applied stochastic process theory and probabilistic analysis. We use this model to predict the effects of reduced immunity, T-cell diversity, and thymic turnover rates on cancer incidence, and compare model simulations to cancer evolutionary data. Results: We predict that changes in T-cell diversity, and to a lesser degree thymic turnover, increase the chance of tumor progression. When applied to experimental data, we demonstrate that the observations are consistent with co-evolution between an indolent cancer population and the adaptive immune system prior to clinical disease. Conclusions: Our results provide a fundamental framework for analyzing the interaction dynamics of an evolving threat like cancer and the adaptive immune system in order to better understand and predict immunotherapeutic efficacy.
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Md Tuhin Mia, Mst Zannatun Ferdus, Md Abdur Rakib Rahat, Nishat Anjum, Ummay Siddiqua, and Md Azad Hossain Raju. "A Comprehensive Review of Text Mining Approaches for Predicting Human Behavior using Deep Learning Method." Journal of Computer Science and Technology Studies 6, no. 1 (February 12, 2024): 170–78. http://dx.doi.org/10.32996/jcsts.2024.6.1.18.
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This article presents a systematic review of research on predicting human behavior through unstructured textual data, employing a comprehensive selection process illustrated in a flow diagram. The review categorizes 82 selected papers into three primary behavioral domains: emotional, social, and cognitive. Each paper undergoes meticulous examination, identifying objectives, algorithms, computational models, and applications. Natural language processing (NLP) emerges as a dominant text mining approach, utilized in over half of the literature, followed by data extraction, report arrangement, and clusterization. The study further employs VOSviewer to visualize the co-occurrence of the term "text mining," revealing prevalent associations and emphasizing the challenges in analyzing unstructured data efficiently. The article contributes to understanding the evolving landscape of behavior analysis through text mining, addressing the need for automated methods in evaluating individuals' attitudes, emotions, or performance.
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Tsui, Amy B. M., Carol K. K. Chan, Gary Harfitt, and Promail Leung. "Crisis and opportunity in teacher preparation in the pandemic: exploring the “adjacent possible”." Journal of Professional Capital and Community 5, no. 3/4 (July 13, 2020): 237–45. http://dx.doi.org/10.1108/jpcc-07-2020-0061.
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PurposeThis paper draws on Kauffman's theory of the “adjacent possible” to make sense of the practices which have emerged in response to school and university closures in Hong Kong and reflects on what opportunities exist in this current global crisis.Design/methodology/approachThis paper drew on qualitative data from two emergent practices – the e-practicum and co-teaching on an online platform – in a teacher preparation program at the University of Hong Kong. The data set included online teaching resources produced by student teachers (STs), reflections from STs, feedback from mentors and university tutors, interactions on an online platform and interviews with co-teaching team members.FindingsThe authors found “emergent practices” were developed in response to the pandemic by pushing the boundaries of existing practices and exploring the opportunities hovering at the edges of the possible. These practices were still evolving, but they contained elements that can morph into innovative practices in teacher preparation.Originality/valueThis paper provides a perspective on where opportunity in a crisis can be found and what innovation means in an educational context.
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Vafaei-Najafabadi, N., L. D. Amorim, E. Adli, W. An, C. I. Clarke, C. E. Clayton, S. Corde, et al. "Producing multi-coloured bunches through beam-induced ionization injection in plasma wakefield accelerator." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2151 (June 24, 2019): 20180184. http://dx.doi.org/10.1098/rsta.2018.0184.
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This paper discusses the properties of electron beams formed in plasma wakefield accelerators through ionization injection. In particular, the potential for generating a beam composed of co-located multi-colour beamlets is demonstrated in the case where the ionization is initiated by the evolving charge field of the drive beam itself. The physics of the processes of ionization and injection are explored through OSIRIS simulations. Experimental evidence showing similar features are presented from the data obtained in the E217 experiment at the FACET facility of the SLAC National Laboratory. This article is part of the Theo Murphy meeting issue ‘Directions in particle beam-driven plasma wakefield acceleration’.
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Li, Wei, Haozhou Zhou, Zhenyuan Lu, and Sagar Kamarthi. "Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis." Sensors 24, no. 4 (February 12, 2024): 1202. http://dx.doi.org/10.3390/s24041202.
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Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study reveals that research on digital twins is rapidly diversifying, with focused themes such as predictive and decision-making functions. Additionally, there is an emphasis on real-time data and point cloud technologies. The advent of federated learning and edge computing also highlights a shift toward distributed computation, prioritizing data privacy. This study confirms that digital twins have evolved into complex systems that can conduct predictive operations through advanced sensing technologies. The discussion also identifies challenges in sensor selection and empirical knowledge integration.
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Saxena, Dr Richa, Aahan Shah, Aditya Ranjan, Akhil Khandelwal, Aman Bapu, and Anish Nair. "A BIBLIOMETRIC REVIEW OF SUSTAINABLE SUPPLY CHAIN MANAGEMENT: AN OR PERSPECTIVE." International Journal of Business Management and Economic Review 07, no. 05 (2024): 01–17. http://dx.doi.org/10.35409/ijbmer.2024.3606.
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This bibliometric analysis offers a comprehensive overview of the evolving landscape of Sustainable Supply Chain Management (SSCM) research from an Operations Research (OR) perspective. This review systematically extracted and analysed 232 articles published between 2005 and 2023. The findings reveal significant trends and insights in SSCM literature. The study finds that SSCM research has experienced exponential growth since 2011. The co-authorship analysis highlights both collaboration and individual contributions, indicating room for increased scholarly interaction. The co-word analysis uncovered thematic clusters, such as sustainability reporting, supply chain resilience, and the use of Big Data. The findings suggest emerging areas for research, including the impact of the COVID-19 pandemic on supply chains and the growing interest in carbon taxes and Internet of Things (IoT) applications. These insights offer valuable guidance for both researchers and industry professionals seeking to align with current SSCM trends and collaboration between academia and industry holds promise for enhancing sustainable and efficient supply chain practices.
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Edwing, Richard, Chung-Chu Teng, and Robert Heitsenrether. "Technology Developments in NOAA's Real-Time Coastal Observing Systems." Marine Technology Society Journal 49, no. 2 (March 1, 2015): 122–37. http://dx.doi.org/10.4031/mtsj.49.2.15.
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AbstractThe critical need for real-time coastal oceanographic and meteorological measurements to support maritime forecasters, emergency managers, pilots, vessel operators, port authorities, coastal planners, and many other decision makers has rapidly grown, along with the variety of scientific research applications that rely on resulting long-term data records. To support the needs for such observations, the National Ocean Service Center for Operational Oceanographic Products and Services (CO-OPS) continues to maintain and develop the National Water Level Observation Network (NWLON) and Physical Oceanographic Real-Time Systems (PORTS®). Together, these networks consist of over 300 long-term, real-time observatories distributed across the nation's coasts. In situ data measured and disseminated in real time from NWLON and PORTS stations include water levels, ocean currents, waves, water temperature, conductivity, bridge clearance, visibility, and several meteorological parameters. CO-OPS invests heavily in analysis of emerging technologies to identify potential improvements in data quality and operating efficiency and to ensure that the evolving needs of its diverse user community are continuously met. Recent enhancements to the CO-OPS network include the transition to microwave radar water level sensors to increase accuracy and simplify installation and maintenance requirements; development and testing of nearshore wave measurement systems; development of standalone, bottom-mounted water level gauges for applications in remote Arctic areas; and expanding data communication capabilities to improve usage of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellites and to broaden use of the Iridium satellite system. An overview of the latest design features of typical CO-OPS real-time stations is presented, along with highlights of recent system developments and enhancements.
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Almeida, Cícero, Artur Fonsêca, Karla Galvão Bezerra dos Santos, Magdalena Mosiolek, and Andrea Pedrosa-Harand. "Contrasting evolution of a satellite DNA and its ancestral IGS rDNA in Phaseolus (Fabaceae)." Genome 55, no. 09 (September 2012): 683–89. http://dx.doi.org/10.1139/g2012-059.
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CC4 is a satellite DNA from common bean ( Phaseolus vulgaris L.) that is similar to its intergenic spacer (IGS) rDNA. CC4 was originally hypothesized to be an old, fast evolving satellite family that has invaded common bean rDNA. To test this hypothesis and contribute to the understanding of IGS-like satellite DNA evolution, we have investigated its distribution in the genus Phaseolus and related species. CC4 was cloned and used as probe for Southern blot and FISH experiments. CC4 was observed as an independent satellite in common bean, forming two to three major and a few minor pericentromeric clusters. In Phaseolus coccineus , CC4 was present in four major clusters, also not co-localized with the 45S rDNA sites. Remarkably, in the less related species of the genus, signals were detected co-localized with the 45S rDNA sites, but co-localization was not observed in the species where CC4 is present as an independent satellite. No signal was detected in species from related genera. Altogether, the data suggest that CC4 has originated from the IGS rDNA in the P. vulgaris – P. coccineus lineage and has evolved slower than the IGS rDNA from this lineage.
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Safar, Leos, Jakub Sopko, and Matus Panko. "Assessing business readiness for Industry 4.0: A bibliometric analysis of research trends." Acta Tecnología 10, no. 01 (March 31, 2024): 11–21. http://dx.doi.org/10.22306/atec.v10i1.191.
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This research provides a comprehensive analysis of the state of readiness assessment for enterprises in the context of Industry 4.0. It examines the most influential authors, countries, and journals in this field, identifies key research themes, and explores the evolving landscape of Industry 4.0. By bibliometric analysis, this study uncovers the intricate network of co-authorship and co-citation among researchers, journals, and countries. The analysis underscores the dominance of China in terms of both publication volume and citation impact, driven by its strategic "Made in China 2025" plan. The United States and India also make substantial contributions, reflecting the global nature of Industry 4.0 research. The key themes in this area include digital transformation, IT innovations, production, and supply chain management. This study pinpoints three distinct clusters of journals, demonstrating the multidisciplinary nature of Industry 4.0. In addition, a co-occurrence analysis of keywords highlights the most prevalent themes, including Industry 4.0, frameworks, big data, and performance. This research offers valuable insights into the research landscape, informing scholars and industry stakeholders of key players, trends, and emerging areas in assessing enterprise readiness for Industry 4.0.
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Vedeld, Trond. "The Co-creation Paradox: Small Towns and the Promise and Limits of Collaborative Governance for Low-Carbon, Sustainable Futures." Scandinavian Journal of Public Administration 26, no. 3 (September 1, 2022): 45–70. http://dx.doi.org/10.58235/sjpa.v26i3.7006.
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Co-creation is considered a ‘near perfect strategy’ for resolving complex and unruly public problems, such as climate change. Based on data collected among small Scandinavian towns, this article investigates the role of co-creation in the urban governance of climate- and sustainability responses by looking at their vertical and horizontal integration in the wider polycentric governance framework. The article has a two-fold aim. First, it develops an analytical framework for investigating how small towns and municipalities navigate in a range of governance contexts based on two strains of theories on collaborative governance and urban climate governance. Second, it applies this framework to a comparative study of small towns to analyse how co-creation plays a strategic role across types and scales of governance in relation to an evolving climate agenda. The article finds that new forms of public leadership in each of the three municipalities and towns is a main factor in the ‘remaking’ of collaborative planning arenas, triple helix partnerships, business alliances, city networks and collaborative pilot projects, much in a similar manner as observed in global cities. Co-creation is extensively employed as a proactive policy- and leadership instrument. However, the nature of response is uneven across the cases compared. A co-creation paradox is suggested: limited municipal politico-administrative leadership and capacity correspond to a low level of ability to engage in co-creation of solutions. This implies that those organisations with the most need for co-creation may have the least capacity to do so.
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Norman, Utku, and A. Ercument Cicek. "ST-Steiner: a spatio-temporal gene discovery algorithm." Bioinformatics 35, no. 18 (February 13, 2019): 3433–40. http://dx.doi.org/10.1093/bioinformatics/btz110.
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AbstractMotivationWhole exome sequencing (WES) studies for autism spectrum disorder (ASD) could identify only around six dozen risk genes to date because the genetic architecture of the disorder is highly complex. To speed the gene discovery process up, a few network-based ASD gene discovery algorithms were proposed. Although these methods use static gene interaction networks, functional clustering of genes is bound to evolve during neurodevelopment and disruptions are likely to have a cascading effect on the future associations. Thus, approaches that disregard the dynamic nature of neurodevelopment are limited.ResultsHere, we present a spatio-temporal gene discovery algorithm, which leverages information from evolving gene co-expression networks of neurodevelopment. The algorithm solves a prize-collecting Steiner forest-based problem on co-expression networks, adapted to model neurodevelopment and transfer information from precursor neurodevelopmental windows. The decisions made by the algorithm can be traced back, adding interpretability to the results. We apply the algorithm on ASD WES data of 3871 samples and identify risk clusters using BrainSpan co-expression networks of early- and mid-fetal periods. On an independent dataset, we show that incorporation of the temporal dimension increases the predictive power: predicted clusters are hit more and show higher enrichment in ASD-related functions compared with the state-of-the-art.Availability and implementationThe code is available at http://ciceklab.cs.bilkent.edu.tr/st-steiner.Supplementary informationSupplementary data are available at Bioinformatics online.