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Publications - 6383

A bibliometric investigation of chatbot applications in business and management

Publication Name: Discover Applied Sciences

Publication Date: 2025-10-01

Volume: 7

Issue: 10

Page Range: Unknown

Description:

Chatbots have become a pivotal technology in business and management. Despite their growing adoption, existing research on chatbots is diverse and fragmented, lacking a cohesive overview of the field’s development and emerging trends. This study aims to answer the core research question: “What are the major research patterns, influential contributors, and emerging themes in chatbot-related literature within business and management between 2018 and 2024?” To address this, a structured four-step bibliometric methodology was applied to systematically collect, screen, and analyze relevant literature. A total of 331 peer-reviewed journal articles published between 2018 and 2024 were retrieved from the Web of Science database. Bibliometric and metadata analyses were conducted using CiteSpace software, including keyword co-occurrence, co-citation, and collaboration network visualizations. The findings show a steady rise in chatbot publications, with the highest output in 2023 (88 articles) and 2024 (85 articles). Prolific authors include Mou Jian, Lova Rajaobelina, and Xueming Luo, while top institutions are the University System of Ohio and the Indian Institute of Management. Core themes include AI, customer service, trust, and consumer experience, with emerging topics such as large language models and service quality. Influential cited works focus on anthropomorphism, technology acceptance, and generative AI. This study provides quantitative insights into the evolution of chatbot research, highlights key contributors and trends, and offers practical implications for improving chatbot design and adoption in business contexts.

Open Access: Yes

DOI: 10.1007/s42452-025-07770-z

A fully symbolic design and modeling of nonlinear glucose control with Control System Professional Suite (CSPS) of Mathematica

Publication Name: Acta Physiologica Hungarica

Publication Date: 2004-09-09

Volume: 91

Issue: 2

Page Range: 147-156

Description:

In this case study a fully symbolic design and modeling method are presented for blood glucose control of diabetic patients under intensive care using Mathematica. The analysis is based on a modified two-compartment model proposed by Bergman et al. (2). The applied feedback control law decoupling even the nonlinear model leads to a fully symbolic solution of the closed loop equations. The effectivity of the applied symbolic procedures being mostly built-in the new version of Control System Professional Suite (CSPS) Application of Mathematica have been demonstrated for controller design in case of a glucose control for treatment of diabetes mellitus and also presented for a numerical situation described in Juhász (8). The results are in good agreement with the earlier presented symbolic-numeric analysis by Benyó et al. (1).

Open Access: Yes

DOI: 10.1556/APhysiol.91.2004.2.6

Safe and secure implementation of the global platform conform infrastructure supporting the customer centric model based ecosystem

Publication Name: Ines 2016 20th Jubilee IEEE International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2016-08-26

Volume: Unknown

Issue: Unknown

Page Range: 131-140

Description:

Global Platform (GP) as a cross industry, nonprofit association develops and publishes specifications promoting secure deployment and management of multi-Application environments of smart card technology based applications and ensuring their interoperability. The GP specifications define the business and technological processes and the associated security requirements. This publication introduces the design and development of a fully functioning smart card application management infrastructure implementing all the related GP processes and corresponding security requirements. The infrastructure supports all the phases of the application life cycle and all the partners in the ecosystem. The system is tested by several trials and certified by independent security assessment.

Open Access: Yes

DOI: 10.1109/INES.2016.7555107

Uncovering key factors in differentiating fermented milk by feeding type and probiotic potential with E-nose and NIRS techniques

Publication Name: Food Control

Publication Date: 2025-10-01

Volume: 176

Issue: Unknown

Page Range: Unknown

Description:

1: This study evaluates the capabilities of near-infrared spectroscopy (NIRS) and electronic nose (E-nose) in characterizing fermented milk, focusing on the impact of feeding type and probiotic potential. Three separate trials were conducted to compare the effects of Total Mixed Ration (TMR) cow feeds enriched with polyunsaturated fatty acids against control feeds. Milk samples, collected from the feeding trials, were fermented with three Lactobacillus strains categorized based on their probiotic potential: moderate (M), non-probiotic (N), and probiotic (P). The probiotic (P) strain exhibited distinct biochemical changes that were easily identifiable by both technologies. The NIRS and E-nose datasets were analysed separately to highlight the individual strengths and unique contributions of each technique in discriminating sample attributes. Specific NIRS wavelengths (1600–1800 nm), associated with unsaturated fatty acids like oleic and linoleic acids, acted as reliable markers for distinguishing milk samples based on the feeding type, while the 1300–1600 nm range helped differentiate strains. E-nose analysis identified volatile compounds such as hexanal and 1-hexen-3-one, formed from the oxidative degradation of unsaturated fatty acids, highlighting the impact of bacterial strains and milk composition on aroma and flavor. The fatty acid profile, particularly the unsaturated fatty acids and their derivatives, played a crucial role in strain and diet selection, offering valuable insights into the development of fermented milk products with specific probiotic characteristics.

Open Access: Yes

DOI: 10.1016/j.foodcont.2025.111376

Myrsinane, Premyrsinane, and Cyclomyrsinane Diterpenes from Euphorbia falcata as Potassium Ion Channel Inhibitors with Selective G Protein-Activated Inwardly Rectifying Ion Channel (GIRK) Blocking Effects

Publication Name: Journal of Natural Products

Publication Date: 2016-08-26

Volume: 79

Issue: 8

Page Range: 1990-2004

Description:

GIRK channels are activated by a large number of G protein-coupled receptors and regulate the electrical activity of neurons, cardiac atrial myocytes, and β-pancreatic cells. Abnormalities in GIRK channel function have been implicated in the pathophysiology of neuropathic pain, drug addiction, and cardiac arrhythmias. In the heart, GIRK channels are selectively expressed in the atrium, and their activation inhibits pacemaker activity, thereby slowing the heart rate. In the present study, 19 new diterpenes, falcatins A-S (1-19), and the known euphorprolitherin D (20) were isolated from Euphorbia falcata. The compounds were assayed on stable transfected HEK-hERG (Kv11.1) and HEK-GIRK1/4 (Kir3.1 and Kir3.4) cells. Blocking activity on GIRK channels was exerted by 13 compounds (61-83% at 10 μM), and, among them, five possessed low potency on the hERG channel (4-20% at 10 μM). These selective activities suggest that myrsinane-related diterpenes are potential lead compounds for the treatment of atrial fibrillation.

Open Access: Yes

DOI: 10.1021/acs.jnatprod.6b00260

Beyond Learning-by-Hiring: Conceptualizing the Micro-Foundations of Knowledge-Centric Recruitment

Publication Name: Systems

Publication Date: 2026-05-01

Volume: 14

Issue: 5

Page Range: Unknown

Description:

This conceptual article introduces knowledge-centric recruitment (KCR) as a distinct dynamic capability that reframes recruitment and post-hire socialization as strategic knowledge-development activities. (1) Background: Unlike conventional vacancy-driven approaches, KCR is a proactive process through which firms deliberately access and import external organizational capabilities embodied in senior professionals—termed knowledge-hires—from rival organizations. These knowledge-hires embody tacit, socio-cognitive building blocks of capabilities developed through involvement in their prior employers’ routines and practices. (2) Methods: This article develops a micro-foundational model of KCR comprising four interrelated processes: external capability scanning and prioritization, identification of target capabilities and knowledge-hires, evaluation through the novel lens of contextual capability fit, and expectations of adaptation during onboarding. (3) Results: Contextual capability fit integrates complementary and supplementary quality with knowledge distance to enable firms to forecast both the strategic value of inbound capabilities and the hire’s expected socialization difficulty. (4) Conclusions: The primary theoretical contribution lies in advancing the learning-by-hiring literature by shifting the focus from passive knowledge diffusion to deliberate, calculative capability acquisition. By integrating insights from the knowledge-based view, person–organization fit, absorptive capacity, and strategic recruitment, the KCR model offers a coherent micro-foundational framework for transforming employee mobility into a source of sustained competitive advantage.

Open Access: Yes

DOI: 10.3390/systems14050560

Multi-Physics thermal analysis of permanent magnets motors with exterior rotor

Publication Name: Civil Comp Proceedings

Publication Date: 2015-01-01

Volume: 108

Issue: Unknown

Page Range: Unknown

Description:

This paper presents a magneto-thermal analysis of an external-rotor permanent magnet synchronous machine based on finite element method. The model developed can be used to predict the temperature distribution inside the motor during the rated operation. Electromagnetic computation is carried out with the aid of two twodimensional finite-element simulations of the cross-section of the permanent magnet motor [1]. In addition, the magnetic core losses of the stator and rotor are modelled based on the results from the electromagnetic analysis and a post-processing formula based on the loss-separation principle. To analyse the process of heat transfer in an electrical machine, empirical correlations are used to describe the convective heat transfer from the different surfaces of the permanent magnet motor. The heat transfer coefficients are determined using dimensionless numbers and the Nusselt number [2]. After the loss calculation, the temperatures of the machine are calculated using a three-dimensional finite element method. The results obtained from the model are compared with the experimental results from testing the prototype electric motor.

Open Access: Yes

DOI: DOI not available

Visualization and art in the mathematics classroom

Publication Name: Zdm International Journal on Mathematics Education

Publication Date: 2003-12-01

Volume: 35

Issue: 1

Page Range: 24-29

Description:

In this paper we summarize our concepts and practice on computer-aided mathematical experimentation, and illustrate them by Mathematica projects that we have developed for our research and the courses "Computer-aided mathematical modelling" and "Computer Algebra I-II" held for students of life sciences at University of Szeged and computational engineering at TFH Berlin, University of Applied Sciences.

Open Access: Yes

DOI: DOI not available

Climate Risk Management and Sustainable Finance: The Role of Financial Institutions in the European Context

Publication Name: Journal of Risk and Financial Management

Publication Date: 2026-05-01

Volume: 19

Issue: 5

Page Range: Unknown

Description:

Climate-related financial risks have become a central concern for financial institutions and regulators, particularly within the European financial system. This paper examines how climate-related risks are integrated into governance, risk assessment, and regulatory practices in European financial institutions. Using a structured narrative literature review of academic and institutional sources published between 2015 and 2026, the study synthesizes evidence on physical, transition, and liability risks, as well as the frameworks and tools used to assess them, including climate stress testing, scenario analysis, and climate value-at-risk models. The findings indicate that climate considerations are increasingly embedded within governance structures and supervisory frameworks; however, implementation remains fragmented due to inconsistent data, methodological limitations, and institutional barriers. The review further highlights that existing risk models often struggle to capture the long-term and non-linear nature of climate-related uncertainty. This paper contributes to the literature by linking financial stability theory and institutional theory to explain the persistent gap between regulatory ambition and institutional practice within the European context. The study concludes by discussing implications for supervisory policy, disclosure standardization, and climate-risk integration in financial decision-making.

Open Access: Yes

DOI: 10.3390/jrfm19050373