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Zur Förderung einer freien und offenen Wissenschaft fördert und unterstützt die Hochschule Bonn-Rhein-Sieg den ungehinderten Zugang zu wissenschaftlicher Arbeit. Um die wissenschaftlichen Ergebnisse der Forschenden an der H-BRS einer breiten Öffentlichkeit zugänglich zu machen, wird die Möglichkeit gefördert, wissenschaftliche Arbeiten Open Access zu publizieren. Dadurch lassen sich diese ohne Zugriffsbeschränkungen nutzen und sind international sichtbar.
Die soziale Netzwerkanalyse versucht menschliche Interaktion in einen analytischen und auswertbaren Zusammenhang zu bringen. Sie hat sich als Methode in den letzten Jahrzehnten über die Sozialwissenschaften hinaus in die Geschichtswissenschaften, Archäologie und Religionswissenschaften verbreitet. Dabei fanden verschiedene Paradigmenwechsel statt, zum Beispiel vom statischen Netzwerken mit dem Schwerpunkt auf quantitativ-struktureller Analyse hin zu heterogenen Handlungsnetzwerken wie zum Beispiel in der der Actor Network Theory (ANT) gewandelt. Der Fokus liegt aktuell eher auf der Frage des Informationsaustauschs und der Dynamik nicht statischer Netzwerke.
Jahresbericht 2020
(2021)
It has been well proved that deep networks are efficient at extracting features from a given (source) labeled dataset. However, it is not always the case that they can generalize well to other (target) datasets which very often have a different underlying distribution. In this report, we evaluate four different domain adaptation techniques for image classification tasks: DeepCORAL, DeepDomainConfusion, CDAN and CDAN+E. These techniques are unsupervised given that the target dataset dopes not carry any labels during training phase. We evaluate model performance on the office-31 dataset. A link to the github repository of this report can be found here: https://github.com/agrija9/Deep-Unsupervised-Domain-Adaptation.
Kundenloyalität stellt als langfristig wirkende Metrik eine erstrebenswerte Erfolgsgröße vieler Unternehmen dar. Im Rahmen einer Strukturgleichungsmodellierung wurden die Beziehungen und Auswirkungen der wahrgenommenen Kundenzentrierung, des Markenvertrauens (kognitiv und affektiv) und der Preis-Wahrnehmung auf die Kundenloyalität (Wiederkaufintention und Empfehlungsbereitschaft) bei physischen high-Involvement-Produkten untersucht. (Verlagsangaben)
This paper gives an overview of how we can benefit from using container technology in our academic work. It aims to be a starting point for fellow researchers which also think about applying these technologies. Hence, we focus on decribing our own experiences and motivations instead of proving hard scientific facts.
Open-Source Software spielt sowohl zur Ausgestaltung von Lehr- und Lernszenarien (bspw. Organisation mit Editoren und Groupware, Kollaboration und Kommunikation via Chats und Webblogs), als auch für die Umsetzung von Forschunsprojekten (zum Beispiel Auswertung großer Datenbestände, Erprobung realer Situationen in vituellen Laboren, Evaluation neuer Oberflächenentwicklungen) eine wichtige Rolle. Um eine bestmögliche Passung der Software herzustellen, erfolgt Softwareentwicklung im Hochschulbereich entweder forschungsprojektbezogen oder Disziplin- und Einrichtungsübergreifend.
Ice accumulation in the blades of wind turbines can cause them to describe anomalous rotations or no rotations at all, thus affecting the generation of electricity and power output. In this work, we investigate the problem of ice accumulation in wind turbines by framing it as anomaly detection of multi-variate time series. Our approach focuses on two main parts: first, learning low-dimensional representations of time series using a Variational Recurrent Autoencoder (VRAE), and second, using unsupervised clustering algorithms to classify the learned representations as normal (no ice accumulated) or abnormal (ice accumulated). We have evaluated our approach on a custom wind turbine time series dataset, for the two-classes problem (one normal versus one abnormal class), we obtained a classification accuracy of up to 96$\%$ on test data. For the multiple-class problem (one normal versus multiple abnormal classes), we present a qualitative analysis of the low-dimensional learned latent space, providing insights into the capacities of our approach to tackle such problem. The code to reproduce this work can be found here https://github.com/agrija9/Wind-Turbines-VRAE-Paper.
Das Kernanliegen des Datenschutzes ist es, natürliche Personen vor nachteiligen Effekten der Speicherung und Verarbeitung der sie betreffenden Daten zu schützen. Aber viele Personen scheinen gar nicht geschützt werden zu wollen. Im Gegenteil, viele Endanwender willigen “freiwillig“ – bewusst oder unbewusst – in eine umfassende Verarbeitung ihrer personenbezogenen Daten ein. Warum tun Menschen dies? Es werden verschiedene Ursachen diskutiert (beispielsweise in [79]), hierzu gehören Uninformiertheit, mangelnde Sensibilität, das Gefühl der Hilflosigkeit, mangelnde Zahlungsbereitschaft und mangelnde Alternativen. Auch wenn dies in Einzelfällen zutrifft, so gibt es oft sehr wohl datenschutzfreundliche Alternativen. Beispielsweise existiert zu WhatsApp (als Instant Messaging App) die Alternative Threema. Threema gilt als EU-DS-GVO-konform und funktional durchaus mit WhatsApp vergleichbar [62]. Allerdings ist inzwischen die aktuelle Netzwerkgröße ein entscheidendes Auswahlkriterium: Im Januar 2018 hatte Threema 4,5 Millionen Nutzer [172], WhatsApp dagegen 1,5 Milliarden [171]. Dies ist ein Indiz dafür, dass WhatsApp sich quasi zum De-facto-Standard entwickelt hat und es für die einzelne Person nur schwer möglich ist, viele andere “zum Wechsel auf ein anderes Produkt zu bewegen. [. . . ] Bei Diensten mit Nutzerzahlen im Milliardenbereich kann von ’Freiwilligkeit’ nur noch bedingt gesprochen werden.“ [9]
Experience made with free and open source software (FOSS) in the public research is shared with the community. The motivation for using and publishing FOSS is to increase visibility, transparancy and feedback quality while at the same time lowering software licensing costs. Also, the idea of giving back and returning a value plays a role. The most frequently given counter arguments are discussed. In the end, it’s important to embed FOSS publishing into the company’s strategy for the exploitation of scientific research results. To help with this, a checklist of criteria to indicate FOSS publishing is suggested. On the backround of wireless sensor networks, some case studies of FOSS contribution are detailed. The emphasis is on checking the original motivation and the spirit of FOSS back with the reality. Finally, further potential of publishing FOSS in the context of scientific research is identified.
Cancer is one of the leading causes of death worldwide [183], with lung tumors being the most frequent cause of cancer deaths in men as well as one of the most common cancers diagnosed in woman [40]. As symptoms often arise in advanced stages, an early diagnosis is especially important to ensure the best and earliest possible treatment. In order to achieve this, Computed Tomography (CT) scans are frequently used for tumor detection and diagnosis. We will present examples of publicly available CT image data of lung cancer patients and discuss possible methods to realize an automatic system for automated cancer diagnosis. We will also look at the recent SPIE-AAPM Lung CT Challenge [10] data set in detail and describe possible methods and challenges for image segmentation and classification based on this data set.
Zwischen Gut und Böse
(2021)
Neurodevelopmental disorder with dysmorphic facies and distal limb anomalies (NEDDFL), defined primarily by developmental delay/intellectual disability, speech delay, postnatal microcephaly, and dysmorphic features, is a syndrome resulting from heterozygous variants in the dosage-sensitive bromodomain PHD finger chromatin remodeler transcription factor BPTF gene. To date, only 11 individuals with NEDDFL due to de novo BPTF variants have been described. To expand the NEDDFL phenotypic spectrum, we describe the clinical features in 25 novel individuals with 20 distinct, clinically relevant variants in BPTF, including four individuals with inherited changes in BPTF. In addition to the previously described features, individuals in this cohort exhibited mild brain abnormalities, seizures, scoliosis, and a variety of ophthalmologic complications. These results further support the broad and multi-faceted complications due to haploinsufficiency of BPTF.
BACKGROUND
Biallelic loss-of-function variants in NCF1 lead to reactive oxygen species deficiency and chronic granulomatous disease (CGD). Heterozygosity for the p.Arg90His variant in NCF1 has been associated with susceptibility to systemic lupus erythematosus, rheumatoid arthritis, and Sjögren's syndrome in adult patients. This study demonstrates the association of the homozygous p.Arg90His variant with interferonopathy with features of autoinflammation and autoimmunity in a pediatric patient.
CASE PRESENTATION
A 5-year old female of Indian ancestry with early-onset recurrent fever and headache, and persistently elevated antinuclear, anti-Ro, and anti-La antibodies was found to carry the homozygous p.Arg90His variant in NCF1 through exome sequencing. Her unaffected parents and three other siblings were carriers for the mutant allele. Because the presence of two NCF1 pseudogenes, this variant was confirmed by independent genotyping methods. Her intracellular neutrophil oxidative burst and NCF1 expression levels were normal, and no clinical features of CGD were apparent. Gene expression analysis in peripheral blood detected an interferon gene expression signature, which was further supported by cytokine analyses of supernatants of cultured patient's cells. These findings suggested that her inflammatory disease is at least in part mediated by type I interferons. While her fever episodes responded well to systemic steroids, treatment with the JAK inhibitor tofacitinib resulted in decreased serum ferritin levels and reduced frequency of fevers.
CONCLUSION
Homozygosity for p.Arg90His in NCF1 should be considered contributory in young patients with an atypical systemic inflammatory antecedent phenotype that may evolve into autoimmunity later in life. The complex genomic organization of NCF1 poses a difficulty for high-throughput genotyping techniques and variants in this gene should be carefully evaluated when using the next generation and Sanger sequencing technologies. The p.Arg90His variant is found at a variable allele frequency in different populations, and is higher in people of South East Asian ancestry. In complex genetic diseases such as SLE, other rare and common susceptibility alleles might be necessary for the full disease expressivity.
Somatic Mutations in UBA1 Define a Distinct Subset of Relapsing Polychondritis Patients With VEXAS
(2021)
Kinder – unsere Zukunft!
(2021)
Die Analytik ist zwar ein grundlegendes Thema innerhalb der Chemie, hat es aber ganz schön in sich. Aber keine Sorge, Ulf Ritgen erklärt Ihnen in diesem Buch was Sie zur Analytischen Chemie Wissen sollten. Wie erhält man eigentlich analytische Infos? Welche Standards gibt es? Und wie sollte man überhaupt mit den Stoffgemischen umgehen? All diese Grundlagen werden ausführlich erläutert. Aber auch die Anwendungsgebiete und Methoden kommen keinesfalls zu kurz. Egal ob Gravimetrie, Titration, Fällung oder Konduktometrie, endlich wird alles verständlich erklärt. Jetzt können Prüfung und Praktikum kommen! (Verlagsangaben)
The deficiency of adenosine deaminase 2 (DADA2) is an autosomal recessively inherited disease that has undergone extensive phenotypic expansion since being first described in patients with fevers, recurrent strokes, livedo racemosa, and polyarteritis nodosa in 2014. It is now recognized that patients may develop multisystem disease that spans multiple medical subspecialties. Here, we describe the findings from a large single center longitudinal cohort of 60 patients, the broad phenotypic presentation, as well as highlight the cohort's experience with hematopoietic cell transplantation and COVID-19. Disease manifestations could be separated into three major phenotypes: inflammatory/vascular, immune dysregulatory, and hematologic, however, most patients presented with significant overlap between these three phenotype groups. The cardinal features of the inflammatory/vascular group included cutaneous manifestations and stroke. Evidence of immune dysregulation was commonly observed, including hypogammaglobulinemia, absent to low class-switched memory B cells, and inadequate response to vaccination. Despite these findings, infectious complications were exceedingly rare in this cohort. Hematologic findings including pure red cell aplasia (PRCA), immune-mediated neutropenia, and pancytopenia were observed in half of patients. We significantly extended our experience using anti-TNF agents, with no strokes observed in 2026 patient months on TNF inhibitors. Meanwhile, hematologic and immune features had a more varied response to anti-TNF therapy. Six patients received a total of 10 allogeneic hematopoietic cell transplant (HCT) procedures, with secondary graft failure necessitating repeat HCTs in three patients, as well as unplanned donor cell infusions to avoid graft rejection. All transplanted patients had been on anti-TNF agents prior to HCT and received varying degrees of reduced-intensity or non-myeloablative conditioning. All transplanted patients are still alive and have discontinued anti-TNF therapy. The long-term follow up afforded by this large single-center study underscores the clinical heterogeneity of DADA2 and the potential for phenotypes to evolve in any individual patient.
TREE Jahresbericht 2019/2020
(2021)
Der Jahresbericht soll in seiner Breite als auch in seiner Tiefe die Stärken unserer gemeinschaftlichen Anstrengungen im Forschungsfeld der nachhaltigen Technologien aufzeigen: interdisziplinär, forschungsstark, nachwuchsfördernd und gesellschaftszugewandt.
Im vergangenen Jahr war die Pandemie auch für das Insitut TREE eine Herausforderung. Wie die Mitglieder mit der Umstellung auf eine hauptsächlich online stattfindende Kommunikation umgegangen sind und wie das Hochschulleben sich dadurch verändert hat, wurde im Jahresbericht unter "See you online" festgehalten. Auch der Wechsel im Direktorium des Instituts ist Thema des diesjährigen Jahresberichts. Unter den Hauptthemen "Wissenschaftstransfer", "TREE und Wirtschaft" und "Transfer Öffentlichkeit" können sie die wichtigsten Ereignisse für das Institut in den Jahren 2019 und 2020 nachlesen.
One of the biggest challenges faced by many tech start-ups from developed markets is to have validated market-fit products/services and to see their solutions implemented. In several sectors, stringent regulations, and the law of handicap of head start at home can be hurdles that limit the development and even the survival potential of theses start-ups. Tech start-ups seeking implementation, learning, and legitimacy may have a solution in expanding into emerging markets. Emerging markets offer both business opportunities in sectors in need of new technologies as they are “fertile grounds” for developing and testing internationalisation business models. We present here a process designed to help tech start-ups to identify, access, shape and seize these opportunities and to overcome their own specificities and emerging markets specificities. The three phases of the proposed process cover entry node concept, partnership, and business, operating and revenue joint models’ development. DesignScience Research Paradigm is used for the design and evaluation of the process. To show the relevance of this process, a case study on the expansion in Morocco of a Dutch start-up active in e-health is used. The study shows the importance of the process for the embeddedness in a local relevant value network with a relevant adopter’s system, a key enabler to achieve time and cost-effective expansion in that specific business and institutional contexts. A pilot to assess the proposed models and evidence of benefits is under development. To boost their chances of growth tech start-ups from developed markets should consider expansion into emerging markets in their strategy. It would be beneficial that policy makers adopt a strategy by which to assist tech start-ups in accessing value networks in emerging markets. It is also important for policy makers from emerging markets to consider developing schemes to attract tech start-ups from developed markets.
Research on entrepreneurial eco-systems is evolving with exhortations for empirical studies at regional and local levels to augment national surveys. The study, therefore, sought to explore the entrepreneurial eco-system of the Central Region, which is relatively well-endowed with natural resources but lags behind in economic advancement in Ghana. Through descriptive research design, quantitative data were collected using self-administered questionnaires from a convenience sample of 44 entrepreneurs under the presidential business support programme in the Central Region of Ghana, in 2019. Data were analysed, by conducting descriptive analysis such as means (M) and percentages and by exploratory factor analysis, with the IBM SPSS Version 25. Descriptive results of 37 valid responses showed that the respondents were satisfied, in varying degrees (M = 4.19-5.65), with 11 factors within the eco-system; the top three factors were demand, security and availability of raw materials. Respondents were, however, not satisfied with access to business development services, access to finance, rent charges and access to repairers of equipment and thus, pose as challenges to their entrepreneurial pursuits. Principal component analysis revealed inter-connectedness among the factors in the eco-system with strong loadings of measures of institutions and resource endowment under the two components of the solution. Based on the findings, it is concluded that the entrepreneurs surveyed were satisfied with more factors in the EES of the Central Region while they were dissatisfied with relatively few but critical factors in the EES, thereby posing as major challenges to their entrepreneurial activities. As an exploratory study, the findings suggest that the entrepreneurial eco-system of the Central Region of Ghana is, to some extent, supportive of entrepreneurial activities but has key challenges. To achieve maximum outcomes, policy interventions should collectively address, at a time, factors that interact strongly to influence entrepreneurship within the system.
Developing the Circular Economy in Uganda: Prospects for Academia-Public-Private-Partnerships
(2021)
Issues: Circular economy is a production system that optimizes the reusability of by-products/waste as raw materials. As the global population threatens to reach 9 billion by 2050, consumption levels grow proportionally, raising food, material, and energy demands. In Uganda, soil nutrient depletion and energy poverty are key challenges faced by urban and rural communities. Rampart depletion of natural resources calls for transit from the linear economic models towards sustainable production/consumption technologies. This study investigated prospects for APPP to optimize the reusability of by-products/waste as raw materials. Approach: Quantitative and qualitative tools were used to collect data via document analysis, interviews, and participant observations. The tools were administered to municipal authorities, private waste-collecting agencies in cities and municipalities; officials in Ministries of energy and Agriculture; officials in universities research units and entrepreneurs that deal in agricultural and energy products; officials from civil society organizations. Findings: there are a number of sustainability projects being undertaken by Universities and High schools, Government agencies, companies, and civil society organization isolation. Singlehandedly, individual agencies lack the requisite capacity to develop closed-loop production/consumption models. Analysis of a few successful RRR projects suggests that APPP is positioned to promote CE. Transiting towards a circular economy requires joint ventures to optimize human, technological, and financial resources and develop policy and institutional frameworks. In Uganda, recycling biotic by-products can promote environmental sustainability; reduce stress on natural resources; enable cost savings; promote green entrepreneurship, and create jobs/livelihoods. Conclusion: working jointly, CE could be enhanced via technical and business models by the academia, private capital investment by companies, community engagement by CSOs, and development of supportive policy and institutional frameworks to facilitate decision-making processes. The APPPs are positioned to use interactive platforms for creating awareness and promote sensitization about green values through education and multimedia communication platforms.
This study sought to apply the Structure Conduct Performance paradigm to Africa´s air transport landscape in general. To do that, it examines the past, present, and future expectations of four of Sub-Saharan Africa’s biggest aviation economies, namely South Africa, Kenya, Ethiopia, and Nigeria. Secondary data containing historical passenger traffic was analysed, and predictions for growth in the next ten years were proposed. The findings suggest that the experience of the existing liberalization initiatives, such as the Yamoussoukro Declaration (YD), has produced less than expected benefits. However, the future of aviation in Africa is somewhat positive, with a growth trajectory expected to follow a linear and gradual path supported by various initiatives, including the Single African Air Transport Market (SAATM) and the African Continental Free Trade Area (AFCTA). The study’s contribution is to illuminate the current discourse on the aviation sector in Africa through the Structure-Conduct-Performance theory paradigm and suggests a conceptual model that could be applied to future studies relating to aviation in Africa.
Personal values and electronic waste disposal behaviours among households in Cape Coast Metropolis
(2021)
The study examined social values that accounted for electronic waste recycling and reuse behaviours. Via a crosscommunity survey of 193 of households in the Cape Coast Metropolis, a correlational design was employed in the study. Partial Least Squares-Structural equation modelling was used to analyse the data. Results from the analysis showed the influence of altruistic values (β = 0.275, p < 0.05) on reuse behaviour. Similarly, environmental awareness (β = 0.213, p<0.05) also showed significant influence on participation in recycling, whereas psychological ownership significantly influenced both reuse (β = 0.319, p < 0.05), and participation in recycling (β = 0.339, p < 0.05), The joint significance of altruistic values, environmental awareness and psychological ownership to explaining recycling participation was 21.3% (R2 = 0.213, p < 0.05) and that of reuse was 24.6% (R2 = 0.246, p < 0.05). The results of the study showed that individuals who are knowledgeable about the state of their environment were more likely to participate in recycling. On the other hand, individuals with altruistic values preferred giving unwanted electronic equipment to others for reuse. Altruistic values are particularly true of collectivist cultural orientation. Psychological ownership was significant in predicting both behaviours, however, the effect size on reuse was moderate. Psychological ownership due to waste aversion and frugality lead consumers to keep, and subsequently give to close relatives in their social network. It was recommended that individuals should be encouraged to patronize formal recycling services. as a way to show concern for the well-being of others by reducing pollution due to improper waste treatment. Again, like in developed economies, second-hand collection systems for unwanted electronic products can be developed, and made convenient for individuals with reusable items, who may be willing to donate or even resell.
There is severe clinical vitamin A deficiency (VAD) prevalence among Ghanaians and many African countries. Foodbased diets has been suggested as a more sustainable approach to solving the VAD situation in Africa. In this study, A participatory action research between orange flesh sweet potato farmers, gari processors within central region and academia was adopted to develop gari containing provitamin A beta-carotene. Gari is a major staple for Ghanaians and people in the West African subregion due to its affordability and swelling capacity. It is mainly eaten raw with water, sugar, groundnut and milk as gari-soakings or with hot water to prepare gelatinized food called gari-kai in Ghana or “eba” among Nigerians. However, gari is limited in provitamin A carotenoids. Orange fleshed sweet potato (OFSP) is known to contain large amount of vitamin A precursor. Therefore, addition of OFSP to gari would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa. To develop this, different proportions of orange fleshed sweet potatoes (OFSP) was used to substitute cassava mash and fermented spontaneously to produce composite gari - a gritty-crispy ready-to-eat food product. Both the amount of OFSP and the fermentation duration caused significant increases in the β-carotene content of the composite gari. OFSP addition reduced the luminance while roasting made the composite gari yellower when compared with the cake used. Addition of OFSP negatively affected the swelling capacity of the gari although not significant. The taste, texture, flavour and the overall preferences for the composite gari decreased due to the addition of the OFSP but fermentation duration (FD) improved them. The sample with 10% OFSP and FD of 1.81 days was found to produce the optimal gari. One-portion of the optimal gari would contribute to 34.75, 23.2, 23.2, 27, 17 and 16% of vitamin A requirements amongst children, adolescent, adult males, adult females, pregnant women and lactating mothers respectively. The study demonstrated that partial substitution of cassava with OFSP for gari production would have the potential to fight the high prevalence rate of vitamin A deficiency amongst less developed regions of Africa while involvement of farmers and processors prior to the design of research phase enhanced the adoption of intervention strategies.
In times of climatic or political grievances that affect not only human life worldwide, but also the environment and the economic situation of a country, a change in the way of thinking about tourism is beginning and the sector of ecotourism is also becoming increasingly important in Germany. The applicability of this form of tourism in the East African destination Kenya in the form of a travel package that is both partly unique and can be designed individually describes the subject matter of this elaboration and is illustrated using the example of the charitable organization Mully Children's Family and the related registered tourism company, MCF Africa Safaris. The underlying research aims to determine how to transform the organisation's own tree planting initiative into a niche tourist market and how this must be geared to gain the interest of the German eco-tourist. Based on the evaluation of the research results, there is high potential, which is dedicated to the implementation of a form of travel consisting of the active support of the named charity and its initiative as well as individually selectable holiday activities in the target market Kenya. As a result, there are basic prerequisites, the consideration of which is essential for the successful integration of the so-called niche market tree planting and the branch-specific nature of ecotourism in the Kenyan travel market.
Most economies across the globe rely on entrepreneurship for growth. There is evidence to suggest that entrepreneurship creates job opportunities and spurs economic growth and development (Pacheco, Dean, & Payne, 2010; Mojica, Gebremedhin, & Schaeffer, 2010, and Solomon, 2007). Even though entrepreneurship is one of the fastest growing education disciplines globally, researchers are still divided on what should be taught and how it should be taught in institutions of higher learning. Entrepreneurial decision-making is laced with uncertainty and drawbacks. Hence, entrepreneurship learners must be taught using practical and conceptual methodologies to equip them with the requisite knowledge and skill that will enable them to confront such challenges in their entrepreneurial activities. This calls for entrepreneurship teachers to be innovative and to also encourage their learners to be innovative as entrepreneurship involves the generation of new business ideas. This paper sought to examine teaching methodologies for entrepreneurship education in institutions of higher learning in Kenya. A mixed-method approach that involved triangulation as the main data collection technique was used. Interviews were administered with teachers and learners of entrepreneurial education in Kenya, with a view to identifying the most commonly used teaching methodologies of entrepreneurial education and their shortcomings. Course outlines and curricula borrowed from twenty (20) institutions of higher learning in Kenya were reviewed. Results indicate that entrepreneurial education in Kenya is largely theoretical and does not meet the needs of the modern entrepreneur. The paper therefore recommends innovative teaching methodologies of entrepreneurial education that can be utilised by the teacher to prepare students adequately to generate entrepreneurial ideas and to identify entrepreneurial opportunities. For this reason, the paper recommends the use of such methodologies as business plan generation, idea generation, innovation, creativity, networking, opportunity recognition, expecting and embracing failure, and adapting to change.
Rural Social Entrepreneurship (RSE) is considered an essential factor for achieving Sustainable Rural Development (SRD) and improving rural people's socio-economic status through increasing production, productivity, reducing unemployment, and accelerating the progress in achieving SDGs. The paper aims at examining the role of social entrepreneurship in achieving (SRD) in Sudan with reference to Wad Balal Project for investment and rural development in Gezira State, which established in 2005 in small villages in Gezira State through mobilizing of local savings and resources for creating job opportunities, sponsoring poor households, improving the infrastructures, and reducing poverty. The study depends on cross-sectional data collected through a questionnaire and focus group discussion from 100 head of households in the village under research. A questionnaire is internally consistent, and its questions are stable. Frequencies and percentages have been used for describing the basic characteristics of the respondents. Statistical t-test was adopted to test the opinions of respondents about the role of the project based on the Likert scale. The results revealed that the project has significantly increased the opportunities of job and training as well as household income, the results also confirmed that the project has improved the status of education and health services in the village. The project has extended and established many branches; the project also diversified its investment to cover more kinds of investments, the project reinvested 50% of its profits and directed the rest to charity, and social services in the village, many lessons can be learned from the project story. The research recommended that a similar social entrepreneurship project can be generalized to more villages in Sudan and other developing countries to accelerate sustainable rural development. Local communities have to support similar initiatives for developing their villages.
A school leader’s achievement is not what they study in learning institutions but the way they organize themselves into problem solving and realistic decision making. While this includes some taught hard skills, the bulk of school activities rely on soft skills. Soft skills, however, are frequently neglected, although they play an important role in school principals’ daily operations as an instructional supervisor. This study aimed to examine the relationship between soft skills training and Principals' performance. The study adopted a cross-sectional mixed survey design. Using Yamane formulae, the sample comprised of 167 principals from 286 public secondary schools in Kiambu County. These were spread proportionally across all the 12 sub-counties in the County. The principal research instrument was primarily a questionnaire. The reliability of the instrument using the Cronbach Alpha coefficient was deemed reasonable at.73. The findings showed that a substantial relationship exists between the training of the principal on soft skills and their good performance of the duties. The study suggests routine in-service training should be undertaken in the county to improve the development of soft skills. It is also advisable that undergraduate, postgraduate, or in-service training include soft skills as a unit, to build knowledge of the value of soft skills.
Studies in entrepreneurship education in hospitality and tourism has indicated that further attention could be given toward helping students to develop creativity and critical thinking skills, engage in deeper self-discovery experiences, and understand tourism more fully to help prepare them for entrepreneurial roles. This study aims at evaluating Hospitality entrepreneurial modules offered in Tourism programs in Ghanaian institutions. The curriculum of Tourism in two tertiary institutions in Ghana offering Tourism is studied. The research highlights on the need to integrate hospitality technical skills into Tourism education to create a culture that will enhance the growth of entrepreneurial hospitality into Tourism as culinary Tourism is becoming common. Some of the challenges faced by tourism students and entrepreneurship educators are highlighted. Structured interview technique was used to collect data from 20 purposive sampled students of the selected institutions. The results revealed that the level of importance and attention given to hospitality skills in tourism and the perception of students on acquisition of the required competencies is minimal. It is therefore recommended that more skills and competences in hospitality operation, food and beverage production and service be introduced in tourism education in a more holistic manner with emphasis on skill acquisition in order to make the tourism graduate more creative and critical thinker in today’s global competitive environment.
Datenschutz und informationelle Selbstbestimmung sind Bestandteile aktueller Leitbilder einer Digitalen Bildung in der Schule. Im Kontext der Schulschließungen und der vorrangigen Nutzung digitaler Medien zeigte sich jedoch, dass Datenschutz weder als Thema noch als Gestaltungsprinzip digitaler Lernumgebungen in der bildungsadministrativen und pädagogisch-praktischen Schulwirklichkeit systematisch verankert ist. Die Diskrepanz zwischen aktuellen Leitbildern einer digitalen Bildung und der sichtbar problematischen Praxis des digitalen Notfalldistanzunterrichts markiert den Ausgangspunkt des Beitrages, der sich der übergeordneten Frage widmet, welche Herausforderungen sich bei der Realisierung von Datenschutz in der Schul- und Unterrichtswirklichkeit in einer digital geprägten Welt stellen. Im Sinne einer Problemfeldanalyse werden prototypische Handlungsprobleme der Schule herausgearbeitet. Fokussiert betrachtet werden exemplarische Herausforderungen und Anforderungen an Technologien und Akteur:innen der inneren und äußeren Schulentwicklung auf den Ebenen der Unterrichtsentwicklung, der Personalentwicklung, der Technologieentwicklung und der Organisationsentwicklung.
Machine learning and neural networks are now ubiquitous in sonar perception, but it lags behind the computer vision field due to the lack of data and pre-trained models specifically for sonar images. In this paper we present the Marine Debris Turntable dataset and produce pre-trained neural networks trained on this dataset, meant to fill the gap of missing pre-trained models for sonar images. We train Resnet 20, MobileNets, DenseNet121, SqueezeNet, MiniXception, and an Autoencoder, over several input image sizes, from 32 x 32 to 96 x 96, on the Marine Debris turntable dataset. We evaluate these models using transfer learning for low-shot classification in the Marine Debris Watertank and another dataset captured using a Gemini 720i sonar. Our results show that in both datasets the pre-trained models produce good features that allow good classification accuracy with low samples (10-30 samples per class). The Gemini dataset validates that the features transfer to other kinds of sonar sensors. We expect that the community benefits from the public release of our pre-trained models and the turntable dataset.
The role of tourism entrepreneurship in rural development continues to be a subject of interest and debate among academia and practitioners. Theoretically, it is anticipated that tourism entrepreneurship will lead to livelihood diversification, enhancement and ultimately a revitalization of the rural economy. While tourism is posited as an accessible entrepreneurship pathway, there is a dearth of information regarding rural dwellers’ actual experiences with it, especially within the Ghanaian context. Using a case study approach and qualitative data from Wli; a rural tourism destination in Ghana, this paper delves into the opportunities and concerns associated with tourism entrepreneurship in rural areas. Data was obtained between November and December 2016 from 27 persons who were either tourism enterprise owners or employees. Findings from the study showed that entrepreneurial activities centred on the provision of accommodation, food and beverage, souvenir and guiding services. The nature of the activities enabled easy transfer of existing skills and knowledge. Further, entry into tourism entrepreneurship was perceived to be easy by the majority of study participants. These findings confirm the potential for tourism to be employed in boosting entrepreneurial activities in rural areas. Nevertheless, there were concerns regarding access to credit, institutional support, unhealthy competitions, low incomes, unguaranteed pensions, and seasonality and skewness of demand. These concerns threatened the growth and sustainability of tourism entrepreneurship within the community. From a policy perspective, there is a need for institutional recognition and support for tourism entrepreneurial intentions and activities in rural areas. Practice-wise, credit facilities need to be designed specifically for tourism-related rural enterprises. Further, periodic skills and knowledge augmentation programmes must be initiated to help expand the skill sets for the rural entrepreneurs. Finally, there is a need for the formation of traderelated networks to provide a platform for knowledge and experience sharing among the entrepreneurs.
Kenya as a touristic destination is well known as an exotic country offering many different landscapes as well as the diversity of wildlife; this is typical for several African countries. To ensure a sustainable tourism development, different forms of tourism have to be considered. One of these forms could be eco-mountain bike cycling tours, as these tours are gaining in popularity, for example in Germany. The aim of this study was to obtain results regarding the market potential for mountain bike eco-tourism in Kenya. The up-and-coming tourism branch of mountain biking was examined in connection with the increasing demand for long-distance travel. The results of this study showed that mountain biking in exotic countries like Kenya has market potential in principle. However, it was also found that mountain biking alone is not a sufficient pull factor for tourists. The combination with other activities turned out to be promising. It was found that tourist packages that include mountain biking as an activity are perceived as attractive. Moreover, it was obtained that not only tourists who ride a mountain bike regularly are addressed as a target group. Even "regular" tourists find mountain biking an attractive (touristic) activity, especially in combination with game drives. Experts also assess the market potential for eco-mountain bike tourism as positive and find existing routes and accommodation attractive. The findings are giving indications for the possibilities to develop eco-mountain bike tourism as a touristic alternative and addition to existing touristic products.
Object-Based Trace Model for Automatic Indicator Computation in the Human Learning Environments
(2021)
This paper proposes a traces model in the form of an object or class model (in the UML sense) which allows the automatic calculation of indicators of various kinds and independently of the computer environment for human learning (CEHL). The model is based on the establishment of a trace-based system that encompasses all the logic of traces collecting and indicators calculation. It is im-plemented in the form of a trace database. It is an important contribution in the field of the exploitation of the traces of apprenticeship in a CEHL because it pro-vides a general formalism for modeling the traces and allowing the calculation of several indicators at the same time. Also, with the inclusion of calculated indica-tors as potential learning traces, our model provides a formalism for classifying the various indicators in the form of inheritance relationships, which promotes the reuse of indicators already calculated. Economically, the model can allow organi-zations with different learning platforms to invest only in one traces Management System. At the social level, it can allow a better sharing of trace databases be-tween the various research institutions in the field of CEHL.
Hinreichende Datensouveränität gestaltet sich für Verbraucher:innen in der Praxis als äußerst schwierig. Die Europäische Datenschutzgrundverordnung garantiert umfassende Betroffenenrechte, die von verwantwortlichen Stellen durch technisch-organisatorische Maßnahmen umzusetzen sind. Traditionelle Vorgehensweisen wie die Bereitstellung länglicher Datenschutzerklärungen oder der ohne weitere Hilfestellungen angebotene Download von personenbezogenen Rohdaten werden dem Anspruch der informationellen Selbstbestimmung nicht gerecht. Die im Folgenden aufgezeigten neuen technischen Ansätze insbesondere KI-basierter Transparenz- und Auskunftsmodalitäten zeigen die Praktikabilität wirksamer und vielseitiger Mechanismen. Hierzu werden die relevanten Transparenzangaben teilautomatisiert extrahiert, maschinenlesbar repräsentiert und anschließend über diverse Kanäle wie virtuelle Assistenten oder die Anreicherung von Suchergebnissen ausgespielt. Ergänzt werden außerdem automatisierte und leicht zugängliche Methoden für Auskunftsersuchen und deren Aufbereitung nach Art. 15 DSGVO. Abschließend werden konkrete Regulierungsimplikationen diskutiert.
The universal basic income grant (UBIG): A comparative review of the characteristics and impact
(2021)
In recent years, public debates, pilot projects and academic research have internationally boosted the prominence of the universal basic income grant (UBIG) as a policy option. Despite this prominence, the arguments and evidence of the UBIG discussion have not been systematically put forward and discussed in light of the different UBIG conceptual understandings and applications. This paper adds value to the debate by systematic presenting the social, economical and political arguments in support of and against a UBIG. It furthermore discusses the UBIG dimensions/characteristics and variations, and also pose questions about whether all the UBIG experiments can really be classified as a UBIG. Antagonist of a UBIG often raise concerns about the negative effect of the lack of conditions and targeting in a UBIG. Since evidence on the impact of UBIG is limited, this paper turns to the evidence base on unconditional cash transfers and conditional cash transfers. The results show that it is the cash transfer rather than the conditionality and targeting that produce positive outcomes in areas of personal wellbeing.
Nudging stellt eine Methode zur positiven Verhaltensbeeinflussung unserer Mitmenschen dar. Mit diesem Instrument kann das Sicherheits- und Gesundheitsverhalten von Arbeitnehmern gestärkt werden. Allerdings findet sie trotz intensiver Forschung bislang wenig Anwendung im betrieblichen Kontext. Daher lautet die Forschungsfrage dieser Arbeit: „Wie lässt sich Nudging seitens der Unternehmen als Präventionsmaßnahme während der Corona-Pandemie einsetzen?“. Mit der Übertragung von Nudging in der Arbeitswelt auf die derzeitigen Herausforderungen der aktuellen Corona-Pandemie leistet diese Arbeit einen wichtigen Beitrag zur Entwicklung neuer Präventionsmaßnahmen in Unternehmen. In der Arbeit konnte festgestellt werden, dass die Entwicklung von Nudges im Unternehmen unter Einbeziehung der Mitarbeiter in einem proaktiven und partizipativen Prozess stattfinden sollte. Mithilfe eines solchen Prozesses werden Gründe für das mögliche Fehlverhalten der Arbeitnehmer analysiert. Anschließend sollten Nudging-Techniken eingesetzt werden, die genau an diesen Punkten anknüpfen – am Fehlverhalten der Menschen. Über den partizipativen Nudging-Prozess wird die Akzeptanz der Arbeitnehmer im Hinblick auf etwaige Maßnahmen gefördert. Es wird am reflektierten Entscheidungssystem der Arbeitnehmer angesetzt. Unter Berücksichtigung der Corona-Pandemie sollte im betrieblichen Kontext zur Förderung des Sicherheitsverhaltens besonders auf den Wirkmechanismus „Norms“ gesetzt werden. Im Home-Office eignen sich aufgrund der Distanz zu den Arbeitnehmern Nudges mit technischer Natur, wie z.B. automatisierte Anmeldungen zu Maßnahmen des Gesundheitsmanagements. Hier greift der Wirkmechanismus „Defaults“. Diese Bachelorarbeit wurde als theoretische Arbeit auf Grundlage einer Literaturrecherche verfasst.
This study investigated the application potential of Black Soldier Fly Larva Hermetia illucens Stratiomyidae: Diptera (L.1758) for wastewater treatment and the removal potential of chemical oxygen demand, ammonia, and phosphorus of and liquid manure residue and municipal waste water containing 1% solids content. Black Soldier Fly Larva were found to reduce the concentration of chemical oxygen demand, but unfortunately, increase the concentration of ammonia and phosphorus. The ability of Black Soldier Fly Larva to feed on organic waste of Liquid manure residue showed that Black Soldier Fly Larva increase their weight by 365% in a solution with 12% solids content and by 595% in a solution having 6% solids content. The study also showed that Black Soldier Fly Larva have the ability to survive in a solution of 1% solids content and have the ability to reduce chemical oxygen demand by up to 86.4% for liquid manure residue and 46.9% for municipal wastewater after 24 hours. Generally, ammonia increased by 43.9% for Liquid manure residue and 98.6% for municipal wastewater. Total phosphorus showed an increase of 11.0% and 88.6% increase for liquid manure residue and municipal wastewater respectively over the 8-day study. Transparent environments tend to reduce the COD content more than the dark environment, both for the liquid manure residue (55.8% and 65.4%) and municipal wastewater (71.5% and 66.4%).
The idea of a basic income grant (BIG) is not new and there are ongoing debates internationally as well as nationally in low- and middle-income countries just like in high-income countries of a BIG as a social protection policy option. The challenge is that there are different conceptualisations, which conflates and muddles the understanding. In the context of social assistance provision, a universal basic income grant (UBIG) is often compared and contrasted against targeted cash transfers (CTs). This case study systematically presents the arguments for targeted CTs and UBIGs. The value of the case study is that it systematically brings together these arguments, highlighting the variations in UBIG applications, including the evidence and actual impact of UBIG experiments. The structure of the case study is as follows: Section 2 simultaneously contrasts and compares the arguments for targeted CTs and UBIG. Section 3 discusses UBIG experiments, as well as presenting the evidence on the application of the UBIG idea, and Section 4 concludes.
The Global Compact for Safe, Orderly and Regular Migration defines Global Skill Partnerships (GSP) as an innovative means of strengthen skills development among origin countries and countries of destination in mutually beneficial manner. However, GSPs are very limited in number and scope, and empirical analyses of them are, to date, relatively rare. This study helps fill this gap in data by presenting and examining existing GSPs or GSP-like approaches (e.g., transnational training partnerships). The aim of the study is to take stock of the various conceptual discourses on and practical experience with transnational skill partnerships. Using Kosovo as a case study, the study details the structure of such partnerships and the processes they entail. It documents the experience of those involved and catalogues the factors contributing to success. On this basis, the authors propose a means of categorizing the various practices that will help structure the empirical diversity of such approaches and render them conceptually feasible: Transnational Skills and Mobility Partnerships (TSMP).
Robot Action Diagnosis and Experience Correction by Falsifying Parameterised Execution Models
(2021)
When faced with an execution failure, an intelligent robot should be able to identify the likely reasons for the failure and adapt its execution policy accordingly. This paper addresses the question of how to utilise knowledge about the execution process, expressed in terms of learned constraints, in order to direct the diagnosis and experience acquisition process. In particular, we present two methods for creating a synergy between failure diagnosis and execution model learning. We first propose a method for diagnosing execution failures of parameterised action execution models, which searches for action parameters that violate a learned precondition model. We then develop a strategy that uses the results of the diagnosis process for generating synthetic data that are more likely to lead to successful execution, thereby increasing the set of available experiences to learn from. The diagnosis and experience correction methods are evaluated for the problem of handle grasping, such that we experimentally demonstrate the effectiveness of the diagnosis algorithm and show that corrected failed experiences can contribute towards improving the execution success of a robot.
The majority of biomedical knowledge is stored in structured databases or as unstructured text in scientific publications. This vast amount of information has led to numerous machine learning-based biological applications using either text through natural language processing (NLP) or structured data through knowledge graph embedding models (KGEMs). However, representations based on a single modality are inherently limited. To generate better representations of biological knowledge, we propose STonKGs, a Sophisticated Transformer trained on biomedical text and Knowledge Graphs. This multimodal Transformer uses combined input sequences of structured information from KGs and unstructured text data from biomedical literature to learn joint representations. First, we pre-trained STonKGs on a knowledge base assembled by the Integrated Network and Dynamical Reasoning Assembler (INDRA) consisting of millions of text-triple pairs extracted from biomedical literature by multiple NLP systems. Then, we benchmarked STonKGs against two baseline models trained on either one of the modalities (i.e., text or KG) across eight different classification tasks, each corresponding to a different biological application. Our results demonstrate that STonKGs outperforms both baselines, especially on the more challenging tasks with respect to the number of classes, improving upon the F1-score of the best baseline by up to 0.083. Additionally, our pre-trained model as well as the model architecture can be adapted to various other transfer learning applications. Finally, the source code and pre-trained STonKGs models are available at https://github.com/stonkgs/stonkgs and https://huggingface.co/stonkgs/stonkgs-150k.
A qualitative study of Machine Learning practices and engineering challenges in Earth Observation
(2021)
Machine Learning (ML) is ubiquitously on the advance. Like many domains, Earth Observation (EO) also increasingly relies on ML applications, where ML methods are applied to process vast amounts of heterogeneous and continuous data streams to answer socially and environmentally relevant questions. However, developing such ML- based EO systems remains challenging: Development processes and employed workflows are often barely structured and poorly reported. The application of ML methods and techniques is considered to be opaque and the lack of transparency is contradictory to the responsible development of ML-based EO applications. To improve this situation a better understanding of the current practices and engineering-related challenges in developing ML-based EO applications is required. In this paper, we report observations from an exploratory study where five experts shared their view on ML engineering in semi-structured interviews. We analysed these interviews with coding techniques as often applied in the domain of empirical software engineering. The interviews provide informative insights into the practical development of ML applications and reveal several engineering challenges. In addition, interviewees participated in a novel workflow sketching task, which provided a tangible reflection of implicit processes. Overall, the results confirm a gap between theoretical conceptions and real practices in ML development even though workflows were sketched abstractly as textbook-like. The results pave the way for a large-scale investigation on requirements for ML engineering in EO.
When an autonomous robot learns how to execute actions, it is of interest to know if and when the execution policy can be generalised to variations of the learning scenarios. This can inform the robot about the necessity of additional learning, as using incomplete or unsuitable policies can lead to execution failures. Generalisation is particularly relevant when a robot has to deal with a large variety of objects and in different contexts. In this paper, we propose and analyse a strategy for generalising parameterised execution models of manipulation actions over different objects based on an object ontology. In particular, a robot transfers a known execution model to objects of related classes according to the ontology, but only if there is no other evidence that the model may be unsuitable. This allows using ontological knowledge as prior information that is then refined by the robot’s own experiences. We verify our algorithm for two actions – grasping and stowing everyday objects – such that we show that the robot can deduce cases in which an existing policy can generalise to other objects and when additional execution knowledge has to be acquired.
Spätestens seit der Belegausgabepflicht in Deutschland ist der digitale Kassenbon in aller Munde. Neben der Reduzierung umweltschädlichen Thermopapiers ergeben sich mit dieser Technologie auch neue Schnittstellen zwischen Kunde:in und Handel. Diese können für eine stärkere Digitalisierung und ein gesteigertes Kund:innen-Erlebnis genutzt werden.
Vor diesem Hintergrund betrachtet dieses Whitepaper die Perspektiven der verschiedenen Stakeholder, Architekturen sowie mögliche Mehrwertdienste zur Steigerung des Kund:innen-Erlebnis, aber auch zur Optimierung der Handelsprozesse.
Target meaning representations for semantic parsing tasks are often based on programming or query languages, such as SQL, and can be formalized by a context-free grammar. Assuming a priori knowledge of the target domain, such grammars can be exploited to enforce syntactical constraints when predicting logical forms. To that end, we assess how syntactical parsers can be integrated into modern encoder-decoder frameworks. Specifically, we implement an attentional SEQ2SEQ model that uses an LR parser to maintain syntactically valid sequences throughout the decoding procedure. Compared to other approaches to grammar-guided decoding that modify the underlying neural network architecture or attempt to derive full parse trees, our approach is conceptually simpler, adds less computational overhead during inference and integrates seamlessly with current SEQ2SEQ frameworks. We present preliminary evaluation results against a recurrent SEQ2SEQ baseline on GEOQUERY and ATIS and demonstrate improved performance while enforcing grammatical constraints.
Simultaneous determination of selected catechins and pyrogallol in deer intoxications by HPLC-MS/MS
(2021)
Aim: To understand how transcriptional factors Pdr1 and Pdr3, belonging to the pleiotropic drug resistance system, are activated, and regulated after introducing chemical toxins to the cell in the model organism Saccharomyces cerevisiae.
Methods: Series of molecular methods were applied using different strains of S. cerevisiae over-expressing proteins of interest as a eukaryotic cell model. The chemical stress introduced to the cell is represented by menadione. Results were obtained performing protein detection and analysis. Additionally, the regulation of the DNA binding of the transcriptional activators after stimulation is quantified using chromatin immunoprecipitation, employing epitope-tagged factors and real-time qPCR.
Results: Our results indicated higher expression levels of the Pdr1 transcriptional factor, compared to its homologous Pdr3 after treatment with menadione. The yeast-cell defence system was tested against various organic solvents to exclude the possibility of their presence potentially affecting the results. The results indicate that Pdr1 is most abundant after 30 minutes from the beginning of the treatment, compared with 240 minutes after the treatment when the function of the transcription factor is faded. It appears that Pdr1 binding to the PDR5 and SNQ2 promoters, which are both activated by Pdr1, peaks around the same time, or more precisely after 40 minutes from the start of the treatment.
Conclusion: The tendency of Pdr1 reduction after its activation by menadione is detected. One possibility is that Pdr1, after recognizing the xenobiotic menadione, is removed by a degradation mechanism. Given the fact that Pdr1 directly binds the xenobiotic molecule, its destruction might help the cells to remove toxic levels of menadione. It is possible that overexpressing the part of Pdr1 which recognizes menadione alone was sufficient to detoxify and hence produce a tolerance towards menadione.
Our study shows ZP2 to be a new biomarker for diagnosis, best used in combination with other low abundant genes in colon cancer. Furthermore, ZP2 promotes cell proliferation via the ERK1/2-cyclinD1-signaling pathway. We demonstrate that ZP2 mRNA is expressed in a low-abundant manner with high specificity in subsets of cancer cell lines representing different cancer subtypes and also in a significant proportion of primary colon cancers. The potential benefit of ZP2 as a biomarker is discussed. In the second part of our study, the function of ZP2 in cancerogenesis has been analyzed. Since ZP2 shows an enhanced transcript level in colon cancer cells, siRNA experiments have been performed to verify the potential role of ZP2 in cell proliferation. Based on these data, ZP2 might serve as a new target molecule for cancer diagnosis and treatment in respective cancer types such as colon cancer.
In thyroid carcinoma cells, the soluble βgalactosidespecific lectin, galectin3, is extra and intracellularly expressed and plays a significant role in thyroid cancer diagnosis. The functional relevance of this molecule, particularly in its extracellular environment however, warrants further elucidation. To gain insight into this topic, the present study characterized principal functional properties of galectin3 in 3 commonly used thyroid carcinoma cell lines (BCPAP, Cal62 and FTC133) that express the molecule intra and extracellulary. Cellintrinsic galectin3 harbors a functional carbohydrate recognition domain as determined by affinity purification. Moreover, cell surface expressed galectin3 can be partially removed by treatment with lactose or asialofetuin, but not with sucrose. Thyroid carcinoma cells adhere to substratebound galectin3 in a βgalactosidespecific manner, whereby only cell adhesion, but not cell migration is promoted. Thus, thyroid tumor cells harbor functional active galectin3 that, inter alia, specifically interacts with cell surfaceexpressed molecular ligands in a βgalactosidedependent manner, whereby the molecule can at least interfere with cell adhesion. The modulation of galectin3 expression level or its ligands in such tumor cells could be of therapeutic interest and needs further experimental clarification.
Background: Staurosporine-dependent single and collective cell migration patterns of breast carcinoma cells MDA-MB-231, MCF-7, and SK-BR-3 were analysed to characterise the presence of drug-dependent migration promoting and inhibiting yin-yang effects. Methods: Migration patterns of various breast cancer cells after staurosporine treatment were investigated using Western blot, cell toxicity assays, single and collective cell migration assays, and video time-lapse. Statistical analyses were performed with Kruskal–Wallis and Fligner–Killeen tests. Results: Application of staurosporine induced the migration of single MCF-7 cells but inhibited collective cell migration. With the exception of low-density SK-BR-3 cells, staurosporine induced the generation of immobile flattened giant cells. Video time-lapse analysis revealed that within the borderline of cell collectives, staurosporine reduced the velocity of individual MDA-MB-231 and SK-BR-3, but not of MCF-7 cells. In individual MCF-7 cells, mainly the directionality of migration became disturbed, which led to an increased migration rate parallel to the borderline, and hereby to an inhibition of the migration of the cell collective as a total. Moreover, the application of staurosporine led to a transient activation of ERK1/2 in all cell lines. Conclusion: Dependent on the context (single versus collective cells), a drug may induce opposite effects in the same cell line.
In recent years, the basic income grant (BIG) discourse has gained attention worldwide as a potential policy option in social protection as testified by recent public debates, ongoing pilot projects, campaigning efforts,1 policy measures during Covid-19 and the surge in academic research. A BIG refers to regular cash transfers paid to all members of society irrespective of their socio-economic status, their capacity or willingness to participate in the labour market or having to meet pre-determined conditions (Offe 2008; Van Parijs 1995, 2003; Wright 2004, 2006). Despite the recent hype around BIG, Iran is the only country worldwide with a scaled-up BIG (Tabatabai 2011, 2012). Other programmes have never gone beyond pilot programmes. This raises the question why this is the case.
Most people use disaster apps infrequently, primarily only in situations of turmoil, when they are physically or emotionally vulnerable. Personal data may be necessary to help them, data protections may be waived. In some circumstances, free movement and liberties may be curtailed for public protection, as was seen in the current COVID pandemic. Consuming and producing disaster data can deepen problems arising at the confluence of surveillance and disaster capitalism, where data has become a tool for solutionist instrumentarian power (Zuboff 2019, Klein 2008) and part of a destructive mode of one world worlding (Law 2015, Escobar 2020). The special use of disaster apps prompts us to ask what role consumer protection could play in safeguarding democratic liberties. Within this work, a set of current approaches are briefly reviewed and two case studies are presented of what we call appropriation or design against datafication. These combine document analysis and literature research with several months of online and field ethnographic observation. The first case study examines disaster app use in response to the 2010 Haiti earthquake, the second explores COVID Contact Tracing in Taiwan in 2020/21. Against this backdrop we ask, ‘how could and how should consumer protection respond to problems of surveillance disaster capitalism?’ Drawing on our work with the is IT ethical? Exchange, a co-designed community platform and knowledge exchange for disaster information sharing, and a Societal Readiness Assessment Framework that we are developing alongside it, we explore how co-design methodologies could help define answers.
Künstliche Intelligenz im autonomen Fahrzeug verarbeitet enorme Mengen an Daten. Beim Betrieb eines solchen Fahrzeugs basiert jede Bewegung auf einer datenbasierten, automatisierten und adaptiven Entscheidungsfindung. Aber auch, um Regeln zur Erkennung und Entscheidung in komplexen Situationen wie den hochindividuellen Verkehrsszenarien entwickeln zu können (KI-Training), sind bereits beachtliche Datenmengen von Fahrzeugen im Realverkehr erforderlich – zum Beispiel Videosequenzen aus Kamerafahrten. Für das Training Künstlicher Intelligenz ist es aus Sicht der Fahrzeugentwicklung attraktiv, auf den Datenschatz zuzugreifen, den die Gesamtheit der Fahrzeuge im realen Anwendungskontext erzeugen kann. Als Nutzer:innen und Insassen sind Verbraucher:innen so Teil einer groß angelegten Testdatenerhebung durch Fahrzeughersteller und Anbieter. Das wirft Datenschutzfragen auf. Ziel des vorliegenden Beitrags ist es herauszuarbeiten, inwiefern sich hierdurch Implikationen für die Rechte und Freiheiten von Verbraucher:innen ergeben und welche Mechanismen das geltende Recht sowie aktuelle legislative Entwicklungen bereithalten, den „Datenhunger“ der KI mit den Interessen an Datensouveränität und informationeller Selbstbestimmung in Einklang und Ausgleich zu bringen. Im Fokus steht dabei insbesondere, wie Anforderungen schon im Produktdesign „mitgedacht“ werden und damit für Verbraucher:innen rechts- und vertrauensfördernd wirken können.
Sprachassistenten wie Alexa oder Google Assistant sind aus dem Alltag vieler VerbraucherInnen nicht mehr wegzudenken. Sie überzeugen insbesondere durch die sprachbasierte und somit freihändige Steuerung und mitunter auch den unterhaltsamen Charakter. Als häuslicher Lebensmittelpunkt sind die häufigsten Aufstellungsorte das Wohnzimmer und die Küche, da sich Haushaltsmitglieder dort die meiste Zeit aufhalten und das alltägliche Leben abspielt. Dies bedeutet allerdings ebenso, dass an diesen Orten potenziell viele Daten erfasst und gesammelt werden können, die nicht für den Sprachassistenten bestimmt sind. Demzufolge ist nicht auszuschließen, dass der Sprachassistent – wenn auch versehentlich – durch Gespräche oder Geräusche aktiviert wird und Aufnahmen speichert, selbst wenn eine Aktivierung unbewusst von Anwesenden bzw. von anderen Geräten (z. B. Fernseher) erfolgt oder aus anderen Räumen kommt. Im Rahmen eines Forschungsprojekts haben wir dazu NutzerInnen über Ihre Nutzungs- und Aufstellungspraktiken der Sprachassistenten befragt und zudem einen Prototyp getestet, der die gespeicherten Interaktionen mit dem Sprachassistenten sichtbar macht. Dieser Beitrag präsentiert basierend auf den Erkenntnissen aus den Interviews und abgeleiteten Leitfäden aus den darauffolgenden Nutzungstests des Prototyps eine Anwendung zur Beantragung und Visualisierung der Interaktionsdaten mit dem Sprachassistenten. Diese ermöglicht es, Interaktionen und die damit zusammenhängende Situation darzustellen, indem sie zu jeder Interaktion die Zeit, das verwendete Gerät sowie den Befehl wiedergibt und unerwartete Verhaltensweisen wie die versehentliche oder falsche Aktivierung sichtbar macht. Dadurch möchten wir VerbraucherInnen für die Fehleranfälligkeit dieser Geräte sensibilisieren und einen selbstbestimmteren und sichereren Umgang ermöglichen.
Der Hochschulentwicklungsplan (HEP) 3 der Hochschule Bonn-Rhein-Sieg beschreibt die strategischen Schwerpunkte der Hochschulentwicklung für die Jahre 2021 bis 2025. Er steht insbesondere unter den Leitbegriffen "Nachhaltigkeit und gesellschaftliche Verantwortung, Digitalisierung, Internationalisierung und Diversität".
Sie sind im Bereich Qualitätsmanagement tätig und haben die Aufgabe bekommen, ein Problem systematisch zu untersuchen und methodisch zu lösen? Sie haben zu viele Aufgaben und wissen nicht, wie Sie diese priorisieren sollen? Oder haben Sie zu begrenzte Ressourcen, um alle Reklamationen gleichzeitig bearbeiten zu können? Oder wissen nicht, wie Sie einen bestimmten Prozess in seinen Grenzen zielführend verbessern können?
Policy analysis is the cornerstone of evidence-based policy making.1 It identifies the problems, informs programme design, supports the monitoring of policy implementation and is needed to evaluate programme impacts (Scott 2005). Rigorous and credible policy evidence is necessary to ensure the transparency and accountability of policy decisions, to secure political and public support and, hence, the allocation of financial resources. Sound policy analysis helps design effective and efficient programmes, thereby maximizing programme impact.
The future of work
(2021)
Driven by the exponential increase in the computational power of machines, data digitalization and scientific advancement in robotics and automation, the current wave of technological change is seemingly unprecedented in speed and scale. It transforms manufacturing and businesses making them more flexible, decentralized and efficient (Lasi et al. 2014). Even though technological change is nothing new, some argue that it is different this time. The new technologies have not only the potential to substitute labor (Nomaler and Verspagen 2018), they also change the way people work. The trend towards new forms of employment is no longer a marginal phenomenon.
Application of underwater robots are on the rise, most of them are dependent on sonar for underwater vision, but the lack of strong perception capabilities limits them in this task. An important issue in sonar perception is matching image patches, which can enable other techniques like localization, change detection, and mapping. There is a rich literature for this problem in color images, but for acoustic images, it is lacking, due to the physics that produce these images. In this paper we improve on our previous results for this problem (Valdenegro-Toro et al, 2017), instead of modeling features manually, a Convolutional Neural Network (CNN) learns a similarity function and predicts if two input sonar images are similar or not. With the objective of improving the sonar image matching problem further, three state of the art CNN architectures are evaluated on the Marine Debris dataset, namely DenseNet, and VGG, with a siamese or two-channel architecture, and contrastive loss. To ensure a fair evaluation of each network, thorough hyper-parameter optimization is executed. We find that the best performing models are DenseNet Two-Channel network with 0.955 AUC, VGG-Siamese with contrastive loss at 0.949 AUC and DenseNet Siamese with 0.921 AUC. By ensembling the top performing DenseNet two-channel and DenseNet-Siamese models overall highest prediction accuracy obtained is 0.978 AUC, showing a large improvement over the 0.91 AUC in the state of the art.
The dataset contains the following data from successful and failed executions of the Toyota HSR robot placing a book on a shelf.
RGB images from the robot's head camera
Depth images from the robot's head camera
Rendered images of the robot's 3D model from the point of view of the robot's head camera
Force-torque readings from a wrist-mounted force-torque sensor
Joint efforts, velocities and positions
extrinsic and intrinsic camera calibration parameters
frame-level anomaly annotations
The anomalies that occur during execution include:
the manipulated book falling down
books on the shelf being disturbed significantly
camera occlusions
robot being disturbed by an external collision
The dataset is split into a train, validation and test set with the following number of trials:
Train: 48 successful trials
Validation: 6 successful trials
Test: 60 anomalous trials and 7 successful trials
Property-Based Testing in Simulation for Verifying Robot Action Execution in Tabletop Manipulation
(2021)
An important prerequisite for the reliability and robustness of a service robot is ensuring the robot’s correct behavior when it performs various tasks of interest. Extensive testing is one established approach for ensuring behavioural correctness; this becomes even more important with the integration of learning-based methods into robot software architectures, as there are often no theoretical guarantees about the performance of such methods in varying scenarios. In this paper, we aim towards evaluating the correctness of robot behaviors in tabletop manipulation through automatic generation of simulated test scenarios in which a robot assesses its performance using property-based testing. In particular, key properties of interest for various robot actions are encoded in an action ontology and are then verified and validated within a simulated environment. We evaluate our framework with a Toyota Human Support Robot (HSR) which is tested in a Gazebo simulation. We show that our framework can correctly and consistently identify various failed actions in a variety of randomised tabletop manipulation scenarios, in addition to providing deeper insights into the type and location of failures for each designed property.
Execution monitoring is essential for robots to detect and respond to failures. Since it is impossible to enumerate all failures for a given task, we learn from successful executions of the task to detect visual anomalies during runtime. Our method learns to predict the motions that occur during the nominal execution of a task, including camera and robot body motion. A probabilistic U-Net architecture is used to learn to predict optical flow, and the robot's kinematics and 3D model are used to model camera and body motion. The errors between the observed and predicted motion are used to calculate an anomaly score. We evaluate our method on a dataset of a robot placing a book on a shelf, which includes anomalies such as falling books, camera occlusions, and robot disturbances. We find that modeling camera and body motion, in addition to the learning-based optical flow prediction, results in an improvement of the area under the receiver operating characteristic curve from 0.752 to 0.804, and the area under the precision-recall curve from 0.467 to 0.549.
Short summary
Accompanying dataset for our paper
A. Mitrevski, P. G. Plöger, and G. Lakemeyer, "Robot Action Diagnosis and Experience Correction by Falsifying Parameterised Execution Models," in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2021.
Contents
The dataset includes a single zip archive, containing data from the experiment described in the paper (conducted with a Toyota HSR). The zip archive contains three subdirectories:
handle_grasping_failure_database: A dump of a MongoDB database containing data from the handle grasping experiment, including ground-truth grasping failure annotations
pre_arm_motion_images: Images collected from the robot's hand camera before moving the robot's hand towards the handle
pregrasp_images: Images collected from the robot's hand camera just before closing the gripper for grasping
The image names include the time stamp at which the images were taken; this allows matching each image with the execution data in the database.
Database usage
After unzipping the archive, the database can be restored with the command
mongorestore handle_grasping_failure_database
This will create a MongoDB database with the name drawer_handle_grasping_failures.
Code for processing the data and failure analysis can be found in our <a href="https://github.com/alex-mitrevski/explainable-robot-execution-models">GitHub repository.
Contents
There are two zip archives included (grasping.zip and throwing.zip), corresponding to two experiments (grasping objects and throwing them in a drawer), both performed with a Toyota HSR. Each archive contains two directories - learning and generalisation - with object-specific learning and generalisation data. For each object, we provide a dump of a MongoDB database, which contains data sufficient for learning the models used in our experiments.
Usage
After unzipping the archives, each database can be restored with the command
mongorestore [data_directory_name]
This will create a MongoDB database with the name of the directory. Code for processing the data and model learning can be found in our <a href="https://github.com/alex-mitrevski/explainable-robot-execution-models">GitHub repository.
The solvent exchange as one of the most important steps during the manufacturing process of organic aerogels was investigated. This step is crucial as a preparatory step for the supercritical drying, since the pore solvent must be soluble in supercritical carbon dioxide to enable solvent extraction. The development and subsequent optimization of a suitable system with a peristaltic pump for automatic solvent exchange proved to be a suitable approach. In addition, the influence of zeolites on the acceleration of the process was found to be beneficial. To investigate the process, the water content in acetone was determined at different times using Karl Fischer titration. The shrinkage, densities, as well as the surface areas of the aerogels were analyzed. Based on these, the influence of various process parameters on the final structure of the obtained aerogels was investigated and evaluated. Modeling on diffusion in porous materials completes this study.
Dieses Dokument präsentiert eine Zusammenfassung der Dissertation der Autorin. In dieser Dissertation [Ha20] wurde ein neuartiger und hybrider Ansatz für die Scha ̈tzung der Intensität von Gesichtsmuskelbewegungen (Action Unit (AU)) vorgeschlagen und validiert. Dieser Ansatz basiert auf einer Gauß’schen Zustandsschätzung und kombiniert ein verformbares, AU-basiertes Gesichtsformmodell, ein viskoelastisches Modell der Gesichtsmuskelbewegung, mehrere erscheinungsbasierten AU-Klassifikatoren und eine Methode zur Erkennung von Gesichtspunkten. Es wurden mehrere Erweiterungen vorgeschlagen und in das Zustandsschätzungs-Framework integriert, um mit den personenspezifischen Eigenschaften sowie technischen und praktischen Herausforderungen umzugehen.Die mit der vorgeschlagenen Methode erzeugten AU-Intensitätsschätzungen wurden für die automatische Erkennung von Schmerzen und für die Analyse von Fahrerablenkung eingesetzt.
Over the last decades, different kinds of design guides have been created to maintain consistency and usability in interactive system development. However, in the case of spatial applications, practitioners from research and industry either have difficulty finding them or perceive such guides as lacking relevance, practicability, and applicability. This paper presents the current state of scientific research and industry practice by investigating currently used design recommendations for mixed reality (MR) system development. We analyzed and compared 875 design recommendations for MR applications elicited from 89 scientific papers and documentation from six industry practitioners in a literature review. In doing so, we identified differences regarding four key topics: Focus on unique MR design challenges, abstraction regarding devices and ecosystems, level of detail and abstraction of content, and covered topics. Based on that,we contribute to the MR design research by providing three factors for perceived irrelevance and six main implications for design recommendations that are applicable in scientific and industry practice.