Botho University

BackgroundThe therapeutic potential of non-invasive transcranial electric stimulation (tES) is growing, but challenges in tailoring treatments to individual patients persist. We demonstrated that personalized montages, informed by biophysical modeling, can reduce dose variability and improve target engagement. However, traditional setups are prone to electrode placement errors, leading to inconsistent dosage, localization and potential off-target engagement.MethodsWe developed a pipeline for creating patient-specific 3D-printed caps based on individual MRI scans to allow custom placement of up to 34 electrodes. Hybrid brush electrodes were incorporated to facilitate the use on with-hair regions of the head. The patient-specific caps are integrated within a Neurostimulator/EEG device, enabling precise electrode placement for recording of neural activity and optimized, personalised tES therapies based on individual biophysical brain models.ResultsA proof-of-concept in-silico study highlighted the importance of positional accuracy in electrode placement, particularly in minimizing off-target stimulation in case of the personalized montage configuration. To mitigate positional displacement, we introduced the pipeline for generating patient-specific 3D-printed caps, ensuring precise anatomical fit. The flexible design of these caps supports high-density electrode arrays tailored to various therapeutic montages. Integrated brush electrodes function in both dry and wet modes and are powered by electronics embedded in a neckpiece, enabling multi-step tES and EEG recording with minimal setup for at-home use. Electrical and mechanical evaluations confirmed the system’s feasibility, and a clinical trial with eight healthy subjects showed improved comfort and increased willingness for home use.ConclusionThis customized cap-electrode system provides a practical solution for self-administered, repeatable personalized tES and EEG session at home.Trial registration: The study is registered on the Swiss National Clinical Trials Portal (SNCTP), (SNCTP000005598) and Clinicaltrials.gov (NCT05999916). The study was approved by the Independent Competent Ethics Committee (Ethikkommission Nordwest-und Zentralschweiz (EKNZ)) at the 14 August 2023 and the Competent Regulatory Authority Swissmedic at the 20 December 2023.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12984-025-01769-8.

The fusion of Generative AI with collaborative robots (cobots) represents a new frontier in Agriculture 6.0, by allowing intelligent decisions, adaptive learning, and increased automation. This chapter provides a thorough technical overview of the architectures, methodologies, and implementation approaches of integrating generative AI models (GANs, Transformers, and diffusion models) with cobots for agricultural applications. The focus of this chapter is on real time adaptability, data efficient learning, and multi-modal sensor fusion for cobots and AI generation techniques. The chapter discusses hardware-software co-design, model deployment on edge processing hardware, interoperability issues, and use cases in the field. The information presented is designed to benefit researchers, technologists, and practitioners working to build sustainable, intelligent, and collaborative agricultural environments.

The concept of IoV, known as the Internet of Vehicles, can revolutionize urban mobility within a future time frame toward creating smart cities through seamless communication between various elements such as vehicles themselves, infrastructure, and external networks. The IoV applies communication like Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), or Vehicle-to-Everything (V2X), which helps optimize traffic movement, congestion reduction, and improvement in road safety. Major enabling technologies concerned with IoV are 5G, AI, IoT, and Blockchain that play facilitating roles in enabling the real-time exchange of data and secure decision-making. IoV support has been very positive towards sustainability by ensuring reduced fuel consumption and emissions and the presence of electric or autonomous vehicles in a future date. Challenges such as privacy issues regarding data, indicatives of infrastructure limitations, and standardization problems still exist in the same.

BEVEZETÉS: Vizsgálatunk arra irányul, hogy az irritábilis bél szindrómás (IBS) betegek táplálkozási szokásairól minél többet megtudjunk és ezen szokásokat összehasonítva következtetéseket vonjunk le, melyek a táplálkozási tanácsadást végző szakemberek számára is hasznosak. MÓDSZERTAN: A magyar lakosság körében, félig strukturált kérdőíves formában kérdeztünk meg 39 önbevallásos IBS-es beteget 2024-ben. Logisztikus regressziót és Fisher-féle egzakt próbát végeztünk az eredmények feldolgozására továbbá Shapiro-Wilk tesztet alkalmaztunk a folytonos változók normalitásának vizsgálatához. A vizsgálati személyeket két csoportra osztottuk a fizikai állapot alapján. A két csoportot összehasonlítottuk a következő kérdésekre adott válaszok mentén: mennyi vizet isznak, mennyi idő alatt fogyasztják el a főételt, mely ételeket eszik gyakrabban és melyeket ritkábban, mely ételeket emésztik könnyebben és melyeket nehezebben. EREDMÉNYEK: Az eredmények alapján megállapítható, hogy vannak olyan élelmiszerek, amelyeket ritkábban kellene fogyasztaniuk vagy egyenesen mellőzniük kellene a fizikai jóllétükre tekintettel, mert nehezen emészthetők és erős tüneteket okoznak. A két csoport között szignifikáns eltérést találtunk az emésztésben és bizonyos ételek fogyasztásának gyakoriságában. Akik azt jelezték, hogy jobban vannak, kevesebb élelmiszert emésztenek nehezen vagy nagyon nehezen, és többet jól vagy nagyon jól. A vízfogyasztást illetően nem találtunk szignifikáns különbséget a két csoport között. Akik fizikailag jobban érzik magukat ritkábban fogyasztanak finomított növényi olajokat, friss és konzerv száraz hüvelyeseket a másik csoporthoz képest. Várakozásunkkal ellentétesen, nem volt szignifikáns eltérés a főétel elfogyasztásának idejében a két csoport között. KÖVETKEZTETÉSEK: Jelen kutatás segítséget nyújt azon szakemberek számára, akik táplálkozással kapcsolatos tanácsot adnak IBS-es betegeknek. A kutatás korlátjaként elmondható, hogy érdemes lenne nagyobb elemszámmal is elvégezni a vizsgálatot, figyelembe véve az IBS magyarországi prevalenciáját. Célszerű lesz az emésztésbeli különbségeket tovább vizsgálni, okokat keresni rá, akár betegség-történettel vagy pszichés módszereket vizsgálva, vagy akár organikus okokat keresve a két csoport szervezetében.

Haptics has disrupted human interactions with machinery by incorporating multiple senses of touch in applications such as AR, robotics, and healthcare. Another implication lies in the emergence of Generative AI in bringing forth new frontiers in design and development of next-gen haptic technologies. This chapter presents the role of generative AI in making the use of haptics both more realistic and more adaptable while aiding in better designed systems that are made less problematic by the functionalities in existing haptic hardware. GANs, VAEs, deep neural networks, and other likely generative models will be reviewed, focusing on improving user experience. Certain applications will focus on the impact that AI has on the future of haptic innovation using immersive virtual environments, robotic control systems, or medical rehabilitation. Finally, the chapter provides some valuable insights on emerging trends, issues, and ethical concerns applied to the noteworthy interfacing strategies intended for more intuitive and lifelike touch-based interactions in the future.

Microservices architecture has revolutionized software development by enabling scalability, resilience, and agility. However, its distributed and decentralized nature introduces unique security challenges. This paper explores the implications of adopting microservices, emphasizing the expanded attack surface, inter-service communication vulnerabilities, and distributed data management risks. Key areas covered include robust authentication mechanisms (OAuth 2.0, JWT), secure inter-service communication via mutual TLS, and the role of service meshes like Istio in enhancing security. Emerging trends, such as the integration of AI/ML for anomaly detection and blockchain for transaction integrity, are discussed alongside future developments in API security standards. By addressing vulnerabilities and implementing proactive security measures, this paper aims to guide organizations in achieving a secure and efficient microservices environment.

Purpose of the study: This study aimed to establish the determinants and consequences of customer delight in Botswana's banking industry. Design/methodology/approach: Data were secured from 332 customers in Botswana's retail banking industry. Convenience and purposive sampling were used to select the final respondents for analysis. The first part of the instrument had a consent statement and screening questions to ensure the relevance and suitability of targeted respondents. The second part of the instrument explicated demographic metrics, while the third part elucidated respondents' patronage behaviour regarding identification and choice of commercial banks where respondents held respective bank accounts. The fourth part of the instrument focused on the scale items of the various subconstructs for the study using a seven-point Likert-type scale. Scale metrics were adapted from measures in extant literature. Data were collected through the observation of COVID-19 expectations. Hypothetical relationships between delight and perceived employee service delivery skills, service quality, joy, surprise, and behavioural intentions were analysed using structural equation modelling with Amos 27.0. Findings: Results showed that perceived employee service delivery skills had a positive and significant influence on delight. Service quality, joy, and surprise were found to have an insignificant effect on delight. Delight was found to have a significant positive effect on behavioural intentions. Recommendations/value: Managers need to communicate with customers to increase personalisation and familiarity with banking service metrics with a view to experiencing delight and behavioural intentions. Managerial implications: The study provides practical insight into cognitive and emotional dynamics concerning service delivery in the service industry for managers, marketers, policymakers, and customers.

This study presents a comprehensive comparative analysis of Random Forest and Neural Networks for grade classification using a dataset of 2,392 high school students. The research involves meticulous data collection and pre-processing, including scaling of numerical features and encoding of categorical variables, to optimize model training. Both models were implemented and rigorously evaluated using standard performance metrics, such as accuracy, precision, recall, and F1-score, with particular attention to their ability to correctly classify students into various grade categories. The results indicate that while the Random Forest model achieved a slightly higher baseline accuracy and benefits from enhanced interpretability, the Neural Networks model demonstrated competitive performance following hyperparameter tuning. The findings underscore the trade-offs between model interpretability and the capacity to capture complex nonlinear relationships, offering valuable insights for practitioners seeking to deploy effective classification strategies in educational settings. Future work may explore ensemble approaches and advanced feature engineering techniques to further improve classification performance.

Real-time monitoring, diagnostics, and personalized care through mHealth devices are important for medical IoT, but the challenge of energy consumption persists. The most important thing in this respect is efficient energy usage to increase the lifespan of the devices, reduce maintenance costs, and improve patient care. The present chapter will cover hardware optimization, energy-saving algorithms, advanced power management, and energy harvesting technologies like solar and kinetic energy for medical IoT devices. It also discusses low-power communication protocols in the context of AI and 5G to further enhance efficiency. Practical case studies, regulatory issues, and future innovations will be discussed to highlight the path toward more sustainable, energy-efficient mHealth solutions, supporting a greener and more effective healthcare system.

to provide the epidemiological framework of those affected by rare diseases resident in the Campania Region (Southern Italy), using the data entered in the Campania Region Rare Disease Registry, acquiring information potentially useful for regional planning. observational retrospective cohort study on patients with rare diseases included in the Regione Campania Rare Disease Registry from 01.01.2022 to 31.12.2022. population included in the Rare Disease Registry and resident in the Campania Region as at 31.12.2022. using the data entered in the Regione Campania Rare Disease Registry, the cumulative incidence (I) of patients with rare diseases resident in Campania was calculated, stratified by age group and rare disease group with the respective 95% confidence intervals (IC95%). Standardised cumulative provincial incidences were also calculated. These are reported using a multiplication factor of 100,000. the incidence of patients with rare diseases in the Campania Region is 50.0 (IC95% 49.4-50.6) per 100,000 inhabitants in the year 2022. Furthermore, the rare disease groups with the highest incidence per 100,000 inhabitants are diseases of the central and peripheral nervous system (I: 8.32 per 100,000 inhabitants) and congenital malformations, chromosomopathies and genetic syndromes (I: 8.52 per 100,000 inhabitants). Moreover, the age groups in which the incidence is highest are in the paediatric age group. an epidemiological framework of the Campania Region on rare diseases such as this one for the year 2022 is fundamental for national and regional planning in order to improve the care and quality of life of people affected by rare diseases, who often feel neglected by society. Sharing this type of information also draws attention to the need for faster diagnosis and the specialisation of new centres.