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Water security is a major concern for water-scarce cities that face dynamic water challenges due to limited water supply, climate change and increasing water demand. Framing urban water security is challenging due to the complexity and uncertainties of the definitions and assessment frameworks concerning urban water security. Several studies have assessed water security by granting priority indicators equal weight without considering or adapting to the local conditions. This study develops a new urban water security assessment framework with application to the water-scarce city
of Madaba, Jordan. The study applies the new assessment framework on the study area and measures urban water security using the integrated urban water security index (IUWSI) and the analytic hierarchy process (AHP) as a decision management tool to prioritise and distinguish indicators that affect the four dimensions of urban water security: drinking water, ecosystems, climate change and water-related hazards, and socioeconomic aspects (DECS). The integrated urban water security index (IUWSI) highlights the state of water security and intervention strategies in Madaba. The study reveals that urban water security in Madaba is satisfactory to meet basic needs, with shortcomings in some aspects of the DECS. However, Madaba faces poor security in terms of managing climate- and water-related risks. The IUWSI framework assists with a rational and evidence-based decision-making process, which is important for enhancing water resources management in water-scarce cities.
The paper presents results of the modelling of heat transfer at film boiling of a liquid in a porous medium on a vertical heated wall bordering with the porous medium. Such processes are observed at cooling of high-temperature surfaces of heat pipes, microstructural radiators etc. Heating conditions at the wall were the constant wall temperature or heat flux. The outer boundary of the vapor film was in contact with moving or stationary liquid inside the porous medium. An analytical solution was obtained for the problem of fluid flow and heat transfer using the porous medium model in the Darcy–Brinkman and Darcy–Brinkman–Forchheimer approximation. It was shown that heat transfer at film boiling in a porous medium was less intensive than in the absence of a porous medium (free fluid flow) and further decreased with the decreasing permeability of the porous medium. Significant differences were observed in frames of both models: 20% for small Darcy numbers at Da < 2 for the Darcy–Brinkman model, and 80% for the Darcy–Brinkman–Forchheimer model. In the Darcy–Brinkman model, depending on the interaction conditions at the vapor–liquid interface (no mechanical interaction or stationary fluid), a sharp decrease in heat transfer was observed for the Darcy numbers lower than five. The analytical predictions of heat transfer coefficients qualitatively agreed with the data of Cheng and Verma (Int J Heat Mass Transf 24:1151–1160, 1981) though demonstrated lower values of heat transfer coefficients for the conditions of the constant wall temperature and constant wall heat flux.
This investigation attempts to understand the eco‐hydrology of, and accordingly suggest an option to manage floodwater for agriculture in, the understudied and data‐sparse ephemeral Baraka River Basin within the hyper‐arid region of Sudan. Reference is made to the major feature of the basin, that is, the Toker Delta spate irrigation scheme. A point‐to‐pixel comparison of gridded and ground‐based data sets is performed to enhance the estimates of rainfall. Analysis of remotely sensed land use/cover data is performed. The results show a significant reduction of the grassland and barren areas explained by a significant expansion of the cropland and open shrubland (invasive mesquite trees) areas in the delta. The cotton sown area is highly dependent on the flooded area and the discharge volume in the delta. However, the area of this major crop has declined since the early 1990s in favour of cultivation of more profitable food crops. Expansion of mesquite in the delta is problematic, taking hold under increased floodwater, and can only be manged by clearance to provide crop cultivation area. There is a great potential for floodwater harvesting during the rainfall season (June to September). A total seasonal runoff volume of around 4.6 and 10.8 billion cubic metres is estimated at 90 and 50% probabilities of exceedance (reliabilities), respectively. Rather than leaving the runoff generated from rainfall events to pass to the Red Sea or be consumed by mesquite trees, a location for runoff harvesting structure in a highly suitable area is proposed. Such a structure will support any policy shifts towards planning and managing the basin water resources for use in irrigating the agricultural scheme.
One-step preparation of bilayered films from kraft lignin and cellulose acetate to mimic tree bark
(2020)
This contribution presents the development of a dry-cast method for the one-step preparation of bio-based films from wood polymers that mimic the bilayered structure of tree bark, the natural protective layer of the tree. In a simplified view, natural bark can be considered as the superposition of an external homogeneous and non-porous layer (outer bark) and a porous substructure layer (inner bark). This work is a first step for the future development of bio-based biomimetic wood coatings. The film had a bark-like appearance and its total density, bulk density and porosity were similar to values measured in natural bark. Furthermore, the structural characteristics of the studied film, namely specific surface area (BET) and pore size distribution, as well as the performance of the water adsorption ability were investigated and discussed.
We consider a risk model in discrete time with dividends and capital injections. The goal is to maximise the value of a dividend strategy. We show that the optimal strategy is of barrier type. That is, all capital above a certain threshold is paid as dividend. A second problem adds tax to the dividends but an injection leads to an exemption from tax. We show that the value function fulfils a Bellman equation. As a special case, we consider the case of premia of size one. In this case we show that the optimal strategy is a two barrier strategy. That is, there is a barrier if a next dividend of size one can be paid without tax and a barrier if the next dividend of size one will be taxed. In both models, we illustrate the findings by de Finetti’s example.
Pelleted biomass has a low, uniform moisture content and can be handled and stored cheaply and safely. Pellets can be made of industrial waste, food waste, agricultural residues, energy crops, and virgin lumber. Despite their many desirable attributes, they cannot compete with fossil fuel sources because the process of densifying the biomass and the price of the raw materials make pellet production costly.
Leaves collected from street sweeping are generally discarded in landfills, but they can potentially be valorized as a biofuel if they are pelleted. However, the lignin content in leaves is not high enough to ensure the physical stability of the pellets, so they break easily during storage and transportation. In this study, the use of eucalyptus kraft lignin as an additive in tree-leaf pellet production was studied. Results showed that when 2% lignin is added the abrasion resistance can be increased to an acceptable value. Pellets with added lignin fulfilled all requirements of European standards for certification except for ash content. However, as the raw material has no cost, this method can add value or contribute to financing continued sweeping and is an example of a circular economy scenario.
How Digital Strategy and Management Games Can Facilitate the Practice of Dynamic Decision-Making
(2020)
This paper examines how digital strategy and management games that have been initially designed for entertainment can facilitate the practice of dynamic decision-making. Based on a comparative qualitative analysis of 17 games—organized into categories derived from a conceptual model of decision-making design—this article illustrates two ways in which these games may be useful in supporting the learning of dynamic decision-making in educational practice:
(1) Players must take over the role of a decider and solve situations in which players must pursue different conflicting goals by making a continuous series of decisions on a variety of actions and measures; (2) three of the features of the games are considered to structure players’ practice of decision-making and foster processes of learning through the curation of possible decisions, the offering of lucid feedback and the modification of time. This article also highlights the games’ shortcomings, from an educational perspective, as players’ decisions are restricted by the numbers of choices they can make within the game, and certain choices are rewarded more than others. An educational application of the games must, therefore, entail a critical reflection of players’ limited choices inside a necessarily biased system.
This bachelor thesis addresses the issue of how school resilience can be measured and assessed quantitatively. Schools as social infrastructures have a significant value for society. Yet, on a global scale, they, and therefore the respective community as well, are continuously endangered by a variety of threats such as natural disasters or violence and mental abuse affecting students, parents and school staff. However, these threats differ greatly depending on climatic and geographical conditions as well as on the socio-cultural context of the corresponding community. To strengthen school resilience against potential threats and to ensure education continuity despite the occurrence of these disruptions, a methodology is developed to measure and assess school resilience in conjunction with its specific circumstances. Initially, qualitative and quantitative (composite) indicators are identified and categorised with the help of a Systematic Literature Review and Mayring's Qualitative Content Analysis. These are subsequently developed into a Comprehensive Index for School Resilience (CISR). Building on this, a pre-existing assessment methodology, which uses Likert-Scales arranged in questionnaires to assign quantitative values to the composite indicators, is adapted to operationalise the CISR and by an exemplary application at Europaschule Troisdorf, the methodology is adapted to the socio-cultural conditions in Germany using an expert’s operational and contextual knowledge. The results obtained show that the methodologies and techniques described in current international research can, after an appropriate adaptation, successfully be applied to schools in Germany as well. Nevertheless, by identifying research limitations and errors as well as potential improvements, it is evident that further research and development is needed to provide stakeholders with a decision-making tool to strengthen the resilience of schools in the future, such as an exhaustive supplement to the CISR or the integration of more precise quantification methodologies and techniques.
With Google’s Flutter framework continuing to grow in popularity for companies and developers alike, the need for an understanding of how to utilize the framework in a large-scale context has become more relevant than ever. The purpose of this thesis is to document the crucial steps most development teams using Flutter in a large-scale application will face. Additionally, a fully documented, large-scale reference application was generated so that other developers may use it as an aid when creating their own Flutter projects on a similar scale. Multiple steps were taken to ensure that optimal solutions were chosen for each aspect of the development process. For each of those aspects, a wide range of possible solutions were explored, compared and analysed. Finally, one of the possible solutions was chosen based on a wide range of scientific papers and community-generated sources. Additionally, an interview with an expert in the field was conducted to further validate those decisions. After the application was fully implemented, ten crucial aspects of the development process were identified. Those ten aspects are now explained in detail in this thesis. Ultimately, the knowledge provided by this thesis can act as a map for peers using Flutter in a large-scale context and help them overcome the crossroads they will most likely come to face.
At the case study of the city of Cologne and the neighbouring Rhein‐Erft‐Kreis (a county), selected resilience aspects of critical infrastructure (CI) and cascading effects are analysed concerning major river floods. Using a Geographic Information System, the applicability of the approach is demonstrated using open source software and data, augmented by manual entries. This study demonstrates the feasibility and limitations of analysing lifeline features of interest for disaster risk and emergency management such as roads, bridges and electricity supply. By highlighting interdependencies of emergency services with CI such as roads, cascading effects of interconnected paths are shown. The findings indicate that in an extreme event flood scenario over 2,000 km of roads and eight bridges will be exposed to floods in the area of the rivers Rhine and Erft. This places huge demands on disaster and emergency management institutions and people affected and limits their resiliency.
The Enhancement of standard dense phase carbon dioxide (DPCD) pasteurization by additional mechanical effects wasassessed in this work. These effects were induced during pasteurization by the sudden depressurization in a narrow mini-tube. The high flow velocities, moderate pressures (40–80 bar) and low temperatures (25–45°C) lead to intense degasifica-tion and shear stress. The inactivation of the test microorganismEscherichia coliDH5a(E. coliDH5a) was determinedbefore and after depressurization in the minitube, representing entirely chemical DPCD via dissolved CO2and total inacti-vation comprising the effects of dissolved CO2and mechanical effects, respectively. Compared to conventional DPCDpasteurization, which is mostly attributed to chemical effects, the additional mechanical effects increased the inactivationefficiency considerably.
This article explores the relationship between digital transformation and disaster risk.Vulnerability studies aim at differentiating impacts and losses by using fine-grained information fromdemographic, social, and personal characteristics of humans. With ongoing digital development,these characteristics will transform and result in new traits, which need to be identified andintegrated. Digital transformations will produce new social groups, partly human, semi-human,or non-human—some of which already exist, and some which can be foreseen by extrapolating fromrecent developments in the field of brain wearables, robotics, and software engineering. Thoughinvolved in the process of digital transformation, many researchers and practitioners in the field ofDisaster Risk Reduction or Climate Change Adaptation are not yet aware of the repercussions fordisaster and vulnerability assessments. Emerging vulnerabilities are due to a growing dependency ondigital services and tools in the case of a severe emergency or crisis. This article depicts the differentimplications for future theoretical frameworks when identifying novel semi-human groups and theirvulnerabilities to disaster risks. Findings include assumed changes within common indicators of socialvulnerability, new indicators, a typology of humans, and human interrelations with digital extensionsand two different perspectives on these groups and their dependencies with critical infrastructure.
This paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implementation effort for the usage of artificial intelligence algorithms. The core of the CAAI is a cognitive module that processes the user’s declarative goals, selects suitable models and algorithms, and creates a configuration for the execution of a processing pipeline on a big data platform. Constant observation and evaluation against performance criteria assess the performance of pipelines for many and different use cases. Based on these evaluations, the pipelines are automatically adapted if necessary. The modular design with well-defined interfaces enables the reusability and extensibility of pipeline components. A big data platform implements this modular design supported by technologies such as Docker, Kubernetes, and Kafka for virtualization and orchestration of the individual components and their communication. The implementation of the architecture is evaluated using a real-world use case. The prototypic implementation is accessible on GitHub and contains a demonstration.
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
As Digital Twins gain more traction and their adoption in industry increases, there is a need to integrate such technology with machine learning features to enhance functionality and enable decision making tasks. This has lead to the emergence of a concept known as Digital Triplet; an enhancement of Digital Twin technology through the addition of an ’intelligent activity layer’. This is a relatively new technology in Industrie 4.0 and research efforts are geared towards exploring its applicability, development and testing of means for implementation and quick adoption. This paper presents the design and implementation of a Digital Triplet for a three-floor elevator system. It demonstrates the integration of a machine learning (ML) object detection model and the system Digital Twin. This was done to introduce an additional security feature that enabled the system to make a decision, based on objects detected and take preliminary security measures. The virtual model was designed in Siemens NX and programmed via Total Integrated Automation (TIA) portal software. The corresponding physical model was fabricated and controlled using a Programmable Logic Controller (PLC) S7 1200. A control program was developed to mimic the general operations of a typical elevator system used in a commercial building setting. Communication, between the physical and virtual models, was enabled using the OPC-Unified Architecture (OPC-UA) protocol. Object recognition using “You only look once” (YOLOV3) based machine learning algorithm was incorporated. The Digital Triplet’s functionality was tested, ensuring the virtual system duplicated actual operations of the physical counterpart through the use of sensor data. Performance testing was done to determine the impact of the ML module on the real-time functionality aspect of the system. Experiment results showed the object recognition contributed an average of 1.083s to an overall signal travel time of 1.338 s.
Digital competences are describing a set of skills, which are necessary to use digital devices and tools with an adequate degree of self-determination. With the ubiquitous digitization of our lives and our society it is important for every citizen to have digital competences. Therefor, it is necessary to educate those competences in schools. As one cannot assume teachers to have enough digital competences to well educate the children of todays classes, this master thesis tries to find out: How to shape the process of teaching digital competences to adolescents in German schools, focusing on including multiple parties from diverse backgrounds into the process? At first, the current situation of teaching digital competences in German schools is analyzed by means of a literature review. After the identification of the challenges within the German system, international best practices are examined. Therefor, four countries, which have reached high scores in the International Computer and Information Literacy Study are selected. Australia, the Czech Republic, Denmark and the Republic of Korea are compared and possible chances for Germany identified. As the next step, expert interviews with divers parties, which have direct or indirect relation to the German education system, are held. The goal of the interviews is to generate ideas on how to support the education system by external help. At the end of the thesis the recommended approach of Motivating External People is presented. Several measures, such as teaching or mentoring students in a guest lecturer model; providing IT support for the hard- and software of the schools or creating Open Educational Resources as education material for the teachers are presented and possible third parties are named. As it is not possible to support the education system from the outside without education system internal persons, it is presented, what needs to change within the system to get the approach working. Therefor, not a complex and system changing approach is presented, but a combined top-down and bottom-up process to motivate external people to support.
To realize a reliable and cost-effective application of high-temperature superconductive (HTS) equipment at high-voltage (HV) levels, the influence of thermally induced gas bubbles on the dielectric strength of different solid insulating materials in liquid nitrogen (LN2) was investigated. A heatable copper tape electrode arrangement was developed simulating HTS tapes with insulation in between. AC breakdown measurements were performed without and with forced boiling on insulating papers, polypropylene laminated paper (PPLP) and polyimide (PI) films. Under nucleate boiling the influence of bubbles on the dielectric strength of all materials was not significant. However under film boiling the dielectric strength of the insulating papers decreased to a level comparable to their dielectric strength in air, demonstrating the insufficient impregnation of porous materials under film boiling. For PI there was no degradation at all. PPLP retained about 70% of its basic dielectric strength in LN2.
Chagas disease is a parasitic infection endemic to America, caused by the protozoan Trypanosoma cruzi and mainly transmitted to humans by contact with insect species of the Triatominae subfamily (Hemiptera). The disease is known to affect disproportionally rural impoverished human communities where it is known to cause premature death and is considered a social and economic burden. The Mexican government has made important progress into the detection, surveillance, treatment, and prevention of the disease in the last decades, however, Chagas disease has also been reported in areas where it had not been previously reported, and there are still barriers for access to treatment. In the state of San Luis Potosi, the disease is more studied in the east, nevertheless, it has been estimated that the reported cases of the entire state have been underestimated. New approaches to detect Chagas risk areas could help prioritize locations for Chagas disease education and prevention programs, detect cases of the disease in a timely manner, and provide access to the necessary treatments. The objective of this study was to identify risk areas for the transmission of Chagas disease in San Luis Potosí using species distribution modelling to estimate vectors and reservoirs’ distributions. To do this, firstly, important vectors and one reservoir species of T. cruzi were identified by reviewing their reported infection rates in literature and the number of times reported in Mexico. Next, species distribution models were calculated for the chosen vector and reservoir species present in the state. The models were done using the Maxent algorithm. Lastly, the resulting distribution models were combined into a risk map by thresholding the model outputs to produce binary predictions and then performing an overlap spatial analysis. Vector species were found to have suitable areas in 36.08% of the state’s territory while areas suitable for both vectors and reservoir were 7.4% of the state’s total area. While this figure may look small at first glance, the analysis suggests that 30% of the rural population and 52% of the urban population of the state are living in an area suitable for vectors and reservoir and therefore at risk. Species distribution modelling can be a powerful tool for identifying human populations at risk of contracting Chagas disease. In the future, including different species of reservoirs into the analysis could help to discover new risk areas in the state.
Enhancing DPCD in Liquid Products by Mechanical Inactivation Effects: Assessment of Feasibility
(2020)
The enhancement of standard dense phase carbon dioxide (DPCD) pasteurization by additional mechanical effects was assessed in this work. These effects were induced during pasteurization by the sudden depressurization in a narrow minitube. The high flow velocities, moderate pressures (40–80 bar) and low temperatures (25–45 °C) lead to intense degasification and shear stress. The inactivation of the test microorganism Escherichia coli DH5α (E. coli DH5α) was determined before and after depressurization in the minitube, representing entirely chemical DPCD via dissolved CO2 and total inactivation comprising the effects of dissolved CO2 and mechanical effects, respectively. Compared to conventional DPCD pasteurization, which is mostly attributed to chemical effects, the additional mechanical effects increased the inactivation efficiency considerably.
Water risk assessment is becoming an essential part of any decision-making process in the business sector. In the world where freshwater resources are becoming scarcer, water risks are growing and causing high costs to businesses. Therefore, numerous frameworks, guidelines, methodologies, tools, and other approaches were developed during the last century. Various scholars have appeared to give an economic value or price for environment goods in order to understand trade-offs better. Nowadays, the corporate world tends to use different approaches to convert sustainability management data to the financial language of decision-makers. This study explores the possible ways for a company to measure the costs of water related risks. It examines how to convert water risks to financial risks using a Peruvian agricultural company. The results show, that from all today’s available frameworks, guidelines or tools there is no one commonly accepted and recognised as the best for water risk assessment and monetising. It was learned, that available tools could provide just a simple overview of possible water related risks and calculate their costs in a very general way. The work also highlights the importance of regular and appropriate data collection on the company level in order to be able to assess water risk related costs for the business.