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Introduction: Antimicrobial resistance (AMR) has emerged as one of the leading threats to public health. AMR possesses a multidimensional challenge that has social, economic, and environmental dimensions that encompass the food production system, influencing human and animal health. The One Health approach highlights the inextricable linkage and interdependence between the health of people, animals, agriculture, and the environment. Antibiotic use in any of these One Health areas can potentially impact the health of other areas. There is a dearth of evidence on AMR from the natural environment, such as the plant-based agriculture sector. Antibiotics, antibiotic-resistant bacteria (ARB), and related AMR genes (ARGs) are assumed to present in the natural environment and disseminate resistance to fresh produce/vegetables and thus to human health upon consumption. Therefore, this study aims to investigate the role of vegetables in the spread of AMR through an agroecosystem exploration from a One Health perspective in Ahmedabad, India.
Protocol: The present study will be executed in Ahmedabad, located in Gujarat state in the Western part of India, by adopting a mixed-method approach. First, a systematic review will be conducted to document the prevalence of ARB and ARGs on fresh produce in South Asia. Second, agriculture farmland surveys will be used to collect the general farming practices and the data on common vegetables consumed raw by the households in Ahmedabad. Third, vegetable and soil samples will be collected from the selected agriculture farms and analyzed for the presence or absence of ARB and ARGs using standard microbiological and molecular methods.
Discussion: The analysis will help to understand the spread of ARB/ARGs through the agroecosystem. This is anticipated to provide an insight into the current state of ARB/ARGs contamination of fresh produce/vegetables and will assist in identifying the relevant strategies for effectively controlling and preventing the spread of AMR.
Jahresbericht 2022
(2023)
Voraussehen heißt, Visionen für die Zukunft zu entwickeln und verantwortungsvoll mitzugestalten und dies im engen Austausch zwischen angewandter Wissenschaft, Gesellschaft und Wirtschaft. Das ist der Hochschule Bonn-Rhein-Sieg ein wichtiges Anliegen. Die H-BRS hat in Lehre, Forschung und Transfer neue Wege beschritten und Akzente gesetzt – zum Beispiel auf den Gebieten Nachhaltigkeit, Energiewende oder Cybersecurity. Der Jahresbericht 2022/23 bietet einen Überblick über die wichtigsten Themen aus den Gebieten Forschung, Lehre, Studium und Kooperation.
Dieses Buch wurde im Rahmen eines Wirtschaftsinformatik-Projektes an der Hochschule Bonn-Rhein-Sieg unter Aufsicht von Prof. Dr. Alexandra Kees geschrieben. Ziel des Projektes war die Erstellung eines Funktionsreferenzmodells für Enterprise Resource Planning (ERP-) Software, welches in Form eines Buches veröffentlicht werden sollte. Die Studierenden haben für das Projekt jeweils verschiedene Teilbereiche, die in einem ERP-System gewöhnlich Anwendung finden, zugeteilt bekommen. In diesem Teil wird der Bereich Lagerverwaltung näher betrachtet.
Although climate-induced liquidity risks can cause significant disruptions and instabilities in the financial sector, they are frequently overlooked in current debates and policy discussions. This paper proposes a macro-financial agent-based integrated assessment model to investigate the transmission channels of climate risks to financial instability and study the emergence of liquidity crises through interbank market dynamics. Our simulations show that the financial system could experience serious funding and market liquidity shortages due to climate-induced liquidity crises. Our investigation contributes to our understanding of the impact - and possible solutions - to climate-induced liquidity crises, besides the issue of asset stranding related to transition risks usually considered in the existing studies.
A PM2.5 concentration prediction framework with vehicle tracking system: From cause to effect
(2023)
Representing 3D surfaces as level sets of continuous functions over R3 is the common denominator of neural implicit representations, which recently enabled remarkable progress in geometric deep learning and computer vision tasks. In order to represent 3D motion within this framework, it is often assumed (either explicitly or implicitly) that the transformations which a surface may undergo are homeomorphic: this is not necessarily true, for instance, in the case of fluid dynamics. In order to represent more general classes of deformations, we propose to apply this theoretical framework as regularizers for the optimization of simple 4D implicit functions (such as signed distance fields). We show that our representation is capable of capturing both homeomorphic and topology-changing deformations, while also defining correspondences over the continuously-reconstructed surfaces.
Spektroskopische Qualifizierung und Quantifizierung von Hyaluronsäure in Nahrungsergänzungsmitteln
(2023)
The paper investigates the nature of Kenya's entrepreneurship education ecosystem (EEE) through a comparative analysis of three entrepreneurship education programs and an examination of how the institutions foster a favourable entrepreneurial environment. This study looks at the entrepreneurship education ecosystem through the lens of universities, NGO's and private institutes in Kenya.
A systemic analysis of EEE is provided by utilizing the Actiotope Model as a conceptual framework. The exploratory research adopts a pragmatic mixed-method methodological approach best suited to understand the research problem.
The results reveal that entrepreneurship education at higher education institutions was primarily theoretical and relied on traditional forms of entrepreneurship education. Recurring rigid patterns show minimal personalization of content and learning styles within the University, with more personalization reported in the Mully Model of education and the more specialized entrepreneurship program of the Identity Projects.
The adaptation of the Actiotope Model provided a new and unique approach to analyzing entrepreneurship ecosystems. The person-centred approach of the model provides valuable insights to learners and to entrepreneurship education institutions and researchers.
Enhanced collaboration between the different entrepreneurial education stakeholders could be a more effective short to medium-term solution to addressing the gaps in entrepreneurial education at tertiary institutions.
In the long term, the study recommends adopting practical-based and goal-oriented entrepreneurship teaching models.
Social businesses have a great positive impact on communities and are a sustainable way to do business today and in the future. This impact can be amplified through the means of digitalization. In the past, traditional for-profit business models have been used to understand the structures of business operations. However, the underlying business model of digital social businesses has not yet been explored. This study presents a building block analysis of business models and a subsequent typology. Digital and social business models are identified via a literature review. The building block analysis encompasses an assessment of the individual business activities contained in the business models. The typology is developed from existing literature utilizing a matrix for the evaluation of digital social businesses. Additionally, five semi-structured expert interviews are conducted to inform, extend, or content the findings of this study. To this end, an inductive coding procedure is applied to the transcribed interviews for the detection of themes within the text. This study contributes to social business model research by providing a first insight into the unique building blocks of digital social business models. It also creates a typology tool based on two parameters, which enables the comparison of digital social businesses.
Mobile technologies have evolved into the means of gaining access to information for learning. Its application in higher education is still a novel concept, particularly in underdeveloped countries. This study is aimed at exploring the views of doctoral students regarding their learning experiences with mobile technologies. Student focus group interviews of 24 doctoral students from 3 different academic institutions were interviewed. The participants’ responses were recorded, transcribed, and analyzed to make conclusions. According to the findings of this study, mobile devices play an important part in the learning experiences of doctoral students. The participating students engaged in collaborative learning using mobile technologies. Given the benefits of adopting mobile technologies for learning activities, academic institutions should focus on teaching faculty members to use this to involve students in their learning process. The implications of this study call for the continued advancement of mobile technologies to facilitate effective learning experience for the multitude of mobile learners in developing countries. Another implication is that academic institutions with collaboration with libraries should see the need to develop user friendly mobile app that is linked to the library management system. Such an application would allow the students to optimally use their smartphones and tablets to search the library’s resources from their mobile devices. Training should be offered to the teaching faculty members to come to terms with the benefits of mobile technologies for learning activities.
TREE Jahresbericht 2021/2022
(2023)
Das Institut TREE freut sich, ihnen den Jahresbericht der Jahre 2021 und 2022 präsentieren zu können. Blicken sie mit uns zurück auf zwei herausfordernde Jahre.
Unser neuer Doppel-Jahresbericht 2021/2022 enthält viele, interessante, Beiträgen unserer spannenden, interdisziplinären Forschungprojekte der Bereiche Energie, Modellbildung Simulation, Drohnenforschung, Materialien und Prozesse und Technikkommunikation.
The UN Declaration on the Right to Development (UNDRTD) adopted in 1986 and the 2030 Agenda for Sustainable Development adopted in 2015 share a universal concept of development that refers both to individual and collective dimensions of prosperity and thus includes the rights of future generations.2 They thus offer a definition of the relationship between development and human rights that is very relevant for the 21st century. The core norm of the UNDRTD has been defined later as “the right of peoples and individuals to the constant improvement of their wellbeing and to a national and global enabling environment conducive to just, equitable, participatory and human-centred development respectful of all human rights”3.
The continuously increasing number of biomedical scholarly publications makes it challenging to construct document recommendation algorithms that can efficiently navigate through literature. Such algorithms would help researchers in finding similar, relevant, and related publications that align with their research interests. Natural Language Processing offers various alternatives to compare publications, ranging from entity recognition to document embeddings. In this paper, we present the results of a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. We aim to determine the best approach that resembles relevance without the need for further training. Specifically, we employ five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition, and state-of-the-art models based on BERT. To evaluate the document similarity obtained by these approaches, we utilize different evaluation metrics that account for relevance judgment, relevance search, and re-ranking of the relevance search. Our results demonstrate that the most promising approach is an in-house version of document embeddings, starting with word embeddings and using centroids to aggregate them by document.
The continuous increase of biomedical scholarly publications makes it challenging to construct document recommendation algorithms to navigate through literature, an important feature for researchers to keep up with relevant publications. Understanding semantic relatedness and similarity between two documents could improve document recommendations. The objective of this study is performing a comparative analysis of vector-based approaches to assess document similarity in the RELISH corpus. Here we present our approach to compare five different techniques to generate vectors representing the text in the documents. These techniques employ a combination of various Natural Language Processing frameworks such as Word2Vec, Doc2Vec, dictionary-based Named Entity Recognition as well as state-of-the-art models based on BERT.
Tourism in Rwanda is challenging. Since the country is small and hilly, it is difficult to tap the potential. As the country is blessed with diverse nature, the Rwandan government decided to combine ecotourism with high-end tourism, to exploit the full potential. This study aims to assess the extent to which these two types of tourism fit together, as well as if sustainability is a decisive argument in this upscale segment. In this context, ecotourism is characterized by its 3 core criteria: education, nature and sustainability. To evaluate the main question: to what extent can ecotourism projects help to promote the perception of Rwanda as a high-end tourist destination on the German market? As well as if sustainability is a decisive argument, interviews with stakeholder from the Rwandan tourism industry as well as German tour operators were conducted, to gain an understanding of both sites and then evaluate them according to the 3 ecotourism core criteria and the demands of high-end tourists. The results showed that there is a difference in the perception of the needs of high-end tourists. While the 3 core criteria seem to be too relevant while they are in booking decision with the tour operator. The high-end lodges in Rwanda state an interest in these three criteria. It is evident from the results that there is a limited active demand for sustainable tourist products, while nature and education are more relevant, but not yet fully exploited. However, all interviewees indicated that ecotourism, and in particular sustainability, is experiencing an increase in demand and will continue to grow in importance in the future. Accordingly, the results suggest the driving markets approach is relevant to further drive demand in that segment.