bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bifidobacterium bifidum CCFM1163 Alleviates Cathartic Colon Through the Acetate/Propionate‐GPR41‐Gβγ Pathway
Authors: Huang Yin , Tang Nan , Xue Yifan , Li Jiazhen , Liu WenXu , Zhu Shengnan , Wang Linlin , Wang Gang , Chen Wei , Zhao Jianxin 
Published: November 2024

ABSTRACTCathartic colon, a form of slow‐transit constipation, arises from prolonged stimulant laxative use and is associated with intestinal barrier impairment and enteric nervous system damage. We identified Bifidobacterium bifidum CCFM1163 as an effective agent for alleviating cathartic colon; however, the underlying mechanisms remain unclear. This study first administered live, dead, and supernatant forms of CCFM1163 to cathartic colon mice, finding that only live bacteria were effective. Non‐targeted and targeted metabolomics analyses of mouse fecal metabolites highlighted short‐chain fatty acids (SCFAs) as key players. Animal experiments comparing the effects of major SCFAs revealed that acetic acid (AA) and propionic acid (PA) ameliorated cathartic colon (reduces intestinal transit time, p < 0.0001; increases fecal water content, p < 0.05). Inhibition studies using SCFAs receptor inhibitors and downstream inhibitors demonstrated that both HAS (a G protein‐coupled receptor 41 [GPR41] inhibitor) and Gallein (Gi protein βγ subunit [Gβγ] inhibitor) negated the reparative effects of CCFM1163 on the enteric nerves and intestinal barrier in cathartic colon mice. CCFM1163 was shown to modulate the intestinal flora, notably increasing Faecalibaculum, Candidatus Saccharimonas, and Prevotellaceae UCG‐001 (p < 0.05) and decreasing Escherichia, Clostridioides (p < 0.0001), while elevating AA and PA levels (p < 0.05). AAs act on the GPR41 receptor, activating the Gβγ, thus enhancing the intestinal barrier and reducing tissue inflammation. PA primarily repairs enteric nerves via GPR41‐Gβγ, promoting peristalsis. This study elucidates B. bifidum CCFM1163's potential mechanisms in cathartic colon relief and provides a theoretical basis for probiotic treatment.
Combining Volatility Forecasts of Duration‐Dependent Markov‐Switching Models
Authors: Turatti Douglas Eduardo , Mendes Fernando Henrique de Paula e Silva , Mazzeu João H. G. 
Published: November 2024

ABSTRACTDuration‐dependent Markov‐switching (DDMS) models require a user‐specified duration hyperparameter, for which there is currently no established procedure for estimation or testing. As a result, an ad‐hoc duration choice must be heuristically justified. This paper proposes a methodology for handling duration selection in DDMS models, with a focus on volatility forecasting. The main novelty lies in generating forecasts through model combination techniques. The idea is that the combined forecasts will be more robust to misspecification in selecting the duration structure, thus yielding more accurate forecasts. Additionally, the paper contributes to the literature by evaluating the out‐of‐sample volatility forecasting performance of DDMS models compared to benchmark conditional volatility models. Empirical analysis involves returns from three distinct asset classes: a cryptocurrency, a stock market index, and a foreign currency exchange rate. Various volatility proxies and robust loss functions are incorporated into our analysis. The results indicate that combined forecasts outperform individual models and, in some cases, are more accurate than GARCH and MS‐GARCH models. Furthermore, models with fixed duration typically underperform relative to the simple GARCH model, often resulting in test rejections.
Forest 5.0: Internet of Things‐Based Transformation of Forests
Authors: B Ravi Chandra , Roy Ajay , Vinay Phaninder , Kaur Navdeep , Jha Sudan , Pradhan Nihar Ranjan 
Published: November 2024

ABSTRACTThe phrase “Modernization of forests” highlights the long‐term integration of modern technologies into forest management, aiming to enhance ecosystem observation, data collection, and analysis for exploration and improvement. Technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSN), Artificial Intelligence (AI), and the IoT of Trees are key enablers of this shift. This research explores various technological interventions that could significantly benefit forest ecology, focusing on smart sensing, tracking, and analysis systems for detecting wildfires, illegal logging, and poaching. Simplified structures for tasks like vegetation analysis and forest fire predictions are proposed for future use without altering existing forest management systems. Additionally, the study addresses techniques to improve tribal livelihoods, promote small‐scale forest product marketing, and enhance wildlife monitoring. Key recommendations include establishing reliable wireless communication networks, continuous real‐time monitoring systems, and energy harvesting methods for effective digital forest management.
Internet of Things Integrated Deep‐Learning Algorithms Monitoring and Predicting Abnormalities in Agriculture Land
Authors: Selvam Prabu , Krishnamoorthy N. , Kumar S. Praveen , Lokeshwaran K. , Lokesh Madineni , Syamala Maganti , Vidhya R. G. 
Published: November 2024

ABSTRACTThe Internet of Things (IoT) plays an essential role in the majority of the recent real‐time applications to speed up the process of immediate actions against abnormal behavior. Surveillance monitoring systems using CCTV and web cameras were used in earlier applications; nevertheless, they could only monitor and generate videos. The data transmission rate in the surveillance monitoring systems was poor due to the less‐performance internet technologies used in the earlier systems. Since they were restricted in data transmission speed, data size carried, communication distance, and sensing range. This paper integrates the fifth‐generation Internet technology (5G) IoT devices and sensors and deep‐learning algorithms to improve the efficiency of agriculture surveillance monitoring systems. It helps monitor, generate, and analyze the IoT data that can be processed immediately and predict the abnormal activities happening in agriculture. Landowners can take immediate action to save and recover the crops and their domestic animals concerning abnormal actions. This paper implements a Convolution Neural Network (CNN) algorithm for analyzing the IoT data and predicting abnormal activities. The experiment result is verified and compared with the other state‐of‐the‐art methods to evaluate the performance of the proposed CNN.
Enhanced 6G MIMO Signal Detection With Dynamic Sparse Region‐Based Convolutional Neural Network With White Shark Optimization
Authors: Solomon Arockiadass Sahaaya Arul Mary , Thangavel Nandhini , Prakash A John Felix , Raja Vinoth , Dhaigude Rahul 
Published: November 2024

ABSTRACTMultiple‐input multiple‐output (MIMO) technology is emerging as a promising choice for upcoming sixth‐generation (6G) and beyond‐fifth‐generation (B5G) networks due to the advancements in AI. However, the complexity of MIMO systems, which involve numerous antennas, results in a challenging detection process with high computational demands. To address the interference challenges inherent in large‐scale MIMO technology, this research proposes a 6G massive MIMO signal identification algorithm that integrates a Dynamic Sparse Region‐based Convolutional Neural Network (DSR‐CNN) with White Shark Optimization (WSO) into conventional MIMO receivers. The DSR‐CNN dynamically refines proposal boxes and features, enhancing detection accuracy by effectively handling complex signal patterns. The WSO optimizes the weight parameters within the R‐CNN, improving the algorithm's convergence toward optimal solutions. This hybrid methodology significantly reduces bit error rates (BER) and enhances detection performance, making it ideally suited to the advanced requirements of 6G networks. The proposed approach, DSR‐CNN‐WSO, not only improves accuracy and efficiency but also seamlessly integrates with existing MIMO systems, offering a robust solution for future wireless communication technologies. The proposed method achieves significantly lower BER (0.01) and Mean Square Error (MSE) (0.1), indicating more reliable bit detection and more accurate signal detection.
Surface performance characteristics of carpet‐mat stabilized cool‐season sod over drainage cells for temporary stadium installation
Authors: Bearss Ryan , Guevara Jackie Lyn , Kilby Jake , Rogers Evan , Rogers John N. , Fielder Rhys , Burbrink Conlan , Navarette Ivan , Williams Taylor , Dickson Kyley , Sorochan John 
Published: November 2024

AbstractCarpet‐mat systems are a diverse group of hybrid stabilizing systems that are installed during sod establishment. In this experiment, eight hybrid, carpet‐mat systems (Flexgrass, Hatko Turfgrass XL BIO 40/34/10 [Turfgrass BIO], Hatko Hybridgrass 40 DS 10 XL [Hybridgrass 40 XL], Hatko Hybridgrass 53 DS 10 XL [Hybridgrass 53 XL], HG Turf Group HERO 127.127 [HERO 127], HG Turf Group HERO 169.169 [HERO 169], Tarkett Sports PlayMaster, POWERgrass™ SP/T [POWERgrass]) were screened for their suitability as a playing surface option for FIFA tournaments. Research was conducted at Michigan State University (MSU) and the University of Tennessee (UT). In fall 2023, carpets were seeded with perennial ryegrass (Lolium perenne L.) and established over plastic. Carpets were infilled with a graded, 90:10 (sand:peat) root zone to each carpet manufacturers prescribed depth. In spring 2024 (<12 months after seeding), established sod was harvested and transplanted to a cellular drainage testing block over asphalt. Treatments were evaluated for surface hardness, rotational resistance, and soccer ball rebound. At UT, treatments had no effect on surface hardness; however, both HERO treatments registered higher rotational resistance than all other carpets. At MSU, all carpet‐mats, but HERO 169, generated a harder playing surface than the non‐stabilized control but had no effect on rotational resistance. Ball rebound was unaffected by any treatment at either location. Based on current FIFA thresholds for an excellent quality pitch, all carpet‐mat systems we evaluated following initial establishment could be considered a suitable hybrid option as a playing surface for a FIFA tournament venue.
Festschrift for Mike Jackson: Applying critical systems thinking through phronetic pluralism: Learning from human learning systems and the adaptive learning pathway
Authors: Hesselgreaves Hannah , Hobbs Catherine , French Max , Wilson Rob , Lowe Toby 
Published: November 2024

AbstractContemporary governance challenges require both systemic leadership and adaptive learning to navigate effectively. Yet systems theory and systems thinking remain on the relative margins of management praxis, subject to accusations of theoretical remoteness or impracticality. In this paper, we explore how concepts central to Critical Systems Theory (CST) can be impactfully carried into practice. We discuss the genesis and operation of Human Learning Systems (HLS), a recent complexity‐informed development in public service reform, and the Adaptive Learning Pathway (ALP) for systemic leadership, as two such exemplars. Through these two illustrative cases, we highlight the significance of pragmatism and pluralism in applying CST in practitioner‐orientated and policy contexts and consider the implications for knowledge production and academic relevance. We describe how a spirit of ‘phronetic pluralism’ may act as an appropriate translational device for integrating systems theory in practice and help realise practical improvements in the public policy and management landscape.
Experimental study on the axial compressive performance of prefabricated steel reinforcement cage‐cast‐in‐situ concrete column with an innovative sleeve
Authors: Zhang Zhongwei , Bai Guoliang , Luo Fajiang , Xu Guangxing , Shao Tiantian , Ren Leping , Tian Yong 
Published: November 2024

AbstractBased on the ribbed rebar with direct rolling thread and hot‐forged double‐lock nut mechanical sleeve connection technology, a construction method for prefabricated reinforcement cage‐cast‐in‐situ concrete (PRC‐CISC) column using this connection is proposed. This method contributes to improving the construction efficiency and engineering quality of reinforced concrete columns. Four PRC‐CISC columns and four control specimens were designed with rebar strength, rebar ratio, and rebar connection method as analysis parameters. A comparative study was conducted on their failure modes, axial compression performance, and rebar connector (coupler) working mechanisms. The results show that compared to the control specimens, the crack morphology of PRC‐CISC columns has no significant difference. However, the apparent yielding position of the reinforcement cage may occur on the cross‐sections where the rebar is located on both sides of the sleeve. The partial carrying capacity of the specimens may increase or decrease (≤4.08%), and the maximum deviation of the displacement ductility coefficient is 0.14, indicating that its strength and deformation differences are relatively small. Furthermore, the study reveals the random migration behavior of the control section of PRC‐CISC columns. When the specimens fail, the strain of the sleeve is significantly smaller than the rebar strain in the control specimens, while the concrete strain shows no significant difference. This is because the increase in the effective area of the sleeve shares the vertical load it bears. Finally, based on the test results, sleeve constitutive relationship, and random migration behavior of the control section, the compressive load capacity range of the positive section of PRC‐CISC columns is proposed. This method can effectively estimate their actual carrying capacity and is consistent with the force characteristics.
A Guided Tour in Qualitative Research
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractThis chapter provides a foundational understanding of qualitative research, delineating its essential characteristics and the place of NVivo in the analytic process. The chapter shows the flexibility inherent in qualitative methods and their adaptability across various academic disciplines. The chapter defines qualitative inquiry as a type of research that has the ability to accommodate complex social phenomena by focusing on naturalistic settings, where researchers seek to interpret phenomena through the meanings that people assign to them. Additionally, the chapter touches upon the contested role of software in qualitative research, discussing both the advantages and potential pitfalls of digital tools in qualitative methodologies.
Exploring Coded Data
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractThis chapter presents three unrelated tools that all assist a researcher with interpreting their results after their data is coded (or from the moment a substantial part of the data is coded). The first tool is the Explore Diagram. The Explore Diagram is a dynamic diagram that allows the researcher to virtually “walk around” through their data. The diagram shows a project item (e.g. an interview, a code, a case) in the middle of the diagram and visually shows all the other project items this item is connected to. From that first diagram, each element can be chosen as the core element of a new diagram, changing the insights in the coded data (over and over again). Second, the Comparison Diagram is discussed. The Comparison diagram shows one project item and its connectedness to another project item. It allows for comparing the connectedness of these two project items, either files, codes, or cases. Lastly, the Framework Matrix is demonstrated. This matrix consists of an intersection of cases (in the rows) and codes (in the columns). In the cells, summaries can be made of the data and easily prepared with the auto summarise function.
Organising Your Project: Secondary Data Management
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractIn this chapter, data management techniques are introduced for projects in a more advanced stage. Project items can be linked with relationships and see-also-links when most data files are imported and coded. These tools allow the researcher to make internal linkages of data fragments visible in the analysis. The chapter also introduces the different Sets a user can create. In addition to grouping project items with folders, NVivo allows (virtual) data to be grouped using static or dynamic sets. Static sets are groups with a fixed group of project items. In contrast, dynamic sets have a query on the data underlying the grouping, allowing the set to be updated as new files are imported or new data is coded.
Using NVivo in Focus Group Research
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractThis chapter addresses the application of NVivo in analysing focus group data. It discusses transcription, coding, and querying group interviews, offering strategies to handle the dynamic and multifaceted data that focus groups generate. The chapter emphasises the double-layered analytical level in focus groups and shows ways to deal with this multilevel structure of individuals clustered in groups. With an interview, the analytical level is the interviewee, implying that the file level coincides with the analytical level. In focus groups, the analytical level of the group coincides with the file level, but within the file (either a transcript or a multimedia file), there is the analytical level of the participant, which does not coincide with the file level. For classifications, this implies that (case) classifications need to be made on both the group and the individual level. After discussing these specific preparations, the chapter shows how queries, and most particularly the Matrix Coding Query, can be used with this double analytical level.
Using Multimedia Material (Photos, Sound and Videos)
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractExpanding NVivo’s utility to multimedia materials, this chapter explores methods for coding and analysing photos, sound, and video files. The chapter details how NVivo supports integrating multimedia data into qualitative research, enhancing a textual analysis with visual and auditory dimensions. The chapter shows the similarities between textual analysis and media-type analysis and how similar but also different tools aid visual and auditory material in NVivo. Both coding principles and query possibilities are illustrated.
Using NVivo in Team Projects
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractThis chapter focuses on teams collaborating with the stand-alone version of NVivo. As the server version Collaboration Cloud is unavailable to many users, the chapter shows how collaborative work in teams can be organised within the framework of the standalone version. Two situations are discussed. First, the chapter shows a single researcher actively working in NVivo and another researcher (e.g. the supervisor) involved in the project but not as an NVivo user. In this situation, the chapter shows how the active researcher can share information about the project with the second team member by either exchanging protected projects or exchanging reports. A second situation exemplified in the chapter is a research team with multiple researchers working together on a project and needing to collaborate on the same NVivo project. Here, the team needs to create a core project that is shared and continuously integrated and shared again.
Setting Up Your Project: Primary Data Management
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractThis chapter shows how new projects are created and prepared for data import. Emphasis is put on the backup function and the possibility of repairing NVivo projects when the project files get damaged. Next, the chapter shows how to set up a logical folder structure and import various data types into an NVivo project. Lastly, it shows how media files (audio or video) can be transcribed from within NVivo.
Thematic Coding
Authors: Mortelmans Dimitri 
Published: November 2024

AbstractData coding is one of the most important steps in a qualitative research project. The researcher can only arrive at reliable results in later analysis phases with adequately coded data. Coding means that the researcher labels all information that says something about the same subject and brings similar pieces of information together under the umbrella of a code. This chapter details every possible step in coding data within an NVivo project. It starts with defining codes and references (fragments to be coded) and strategies to gain depth in coding. Next, both deductive and inductive approaches to coding are explained. The chapter ends with a range of coding tips to make coding in NVivo more efficient: drag-and-drop coding methods, renaming codes, making hierarchical codebooks, using visualisation with coding stripes and highlighting and using the aggregation function in the codebook.
Landwirtschaft und Ernährung als komplexe Problemstellung einer nachhaltigen Entwicklung: eine didaktische Intervention
Authors: Jansen Annegret 
Published: November 2024

ZusammenfassungDie Lerneinheit, die als didaktische Intervention für die vorliegende Studie entwickelt wurde, verfolgt das Ziel, politische Urteilsbildung angesichts komplexer Problemstellungen einer nachhaltigen Entwicklung zu fördern. Sie wurde für Schulklassen des 11. Jahrgangs der gymnasialen Oberstufe konzipiert und erstreckt sich über einen Zeitraum von sieben Wochen. Die Konzeption basiert auf Ansatzpunkten einer politischen Nachhaltigkeitsbildung.
Conclusions
Authors: Autero Anniina , de Moraes Batista Simão Marcela , Karppi Ilari , Korvela Paul-Erik 
Published: November 2024

AbstractIn conclusion, the pervasive nature of security extends across diverse disciplines, with its roots deeply embedded in the fabric of international relations. From the foundational works of Machiavelli and Hobbes to Foucault and contemporary conceptual explorations, the discourse surrounding security has evolved significantly. This book contributes to this discourse by delving into the expansive realm of security, transcending conventional interpretations, and incorporating emerging technologies and multifaceted perspectives.