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Achieving urban water security is a major challenge for many countries. While several studies have assessed water security at a regional level, many studies have also emphasized the lack of assessment of water security and application of measures to achieve it at the urban level.
Recent studies that have focused on measuring urban water security are not holistic, and there is still no agreed-upon understanding of how to operationalize and identify an assessment framework to measure the current state and dynamics of water security. At present, there is also no clearly defined and widely endorsed definition of urban water security. To address this challenge, this study provides a systematic approach to better understand urban water security, with a working definition and an assessment framework to be applied in peri-urban and urban areas. The proposed working definition of urban water security is based on the United Nations (UN) sustainable development goal on water and sanitation and the human rights on water and sanitation. It captures issues of urban-level technical, environmental, and socio-economic indicators that emphasize credibility, legitimacy, and salience.
The assessment framework depends on four main dimensions to achieve urban water security: Drinking water and human beings, ecosystem, climate change and water-related hazards, and socio-economic factors (DECS). The framework further enables the analysis of relationships and trade-off between urbanization and water security, as well as between DECS indicators. Applying this framework will help governments, policy-makers, and water stakeholders to target scant resources more eff ectively and sustainably. The study reveals that achieving urban water security requires a holistic and integrated approach with collaborative stakeholders to provide a meaningful way to improve understanding and managing urban water security.
Stable recombinant mammalian cells are of growing importance in pharmaceutical biotechnology production scenarios for biologics such as monoclonal antibodies, growth and blood factors, cytokines and subunit vaccines. However, the establishment of recombinant producer cells using classical stable transfection of plasmid DNA is hampered by low stable gene transfer efficiencies. Consequently, subsequent selection of transgenic cells and the screening of clonal cell populations are time- and thus cost-intensive. To overcome these limitations, expression cassettes were embedded into transposon-derived donor vectors. Upon the co-transfection with transposase-encoding constructs, elevated vector copy numbers stably integrated into the genomes of the host cells are readily achieved facilitating under stringent selection pressure the establishment of cell pools characterized by sustained and high-yield recombinant protein production. Here, we discuss some aspects of transposon vector technologies, which render these vectors promising candidates for their further utilization in the production of biologics.
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.
Despite intensive research over the last three decades, it has not yet been possible to bring an effective vaccine against human immunodeficiency virus (HIV) and the resulting acquired immunodeficiency syndrome (AIDS) to market. Virus-like particles (VLP) are a promising approach for efficient and effective vaccination and could play an important role in the fight against HIV. For example, HEK293 (human embryo kidney) cells can be used to produce virus-like particles. In this context, given the quality-by-design (QbD) concept for manufacturing, a digital twin is of great importance for the production of HIV-Gag-formed VLPs. In this work, a dynamic metabolic model for the production of HIV-Gag VLPs was developed and validated. The model can represent the VLP production as well as the consumption or formation of all important substrates and metabolites. Thus, in combination with already described process analytical technology (PAT) methods, the final step towards the implementation of a digital twin for process development and design, as well as process automation, was completed.
Abstract
Due to their pronounced bioactivity and limited availability from natural resources, metabolites of the soft coral Pseudopterogorgia elisabethae, such as erogorgiaene and the pseudopterosines, represent important target molecules for chemical synthesis. We have now developed a particularly short and efficient route towards these marine diterpenes exploiting an operationally convenient enantioselective cobalt‐catalyzed hydrovinylation as the chirogenic step. Other noteworthy C−C bond forming transformations include diastereoselective Lewis acid‐mediated cyclizations, a Suzuki coupling and a carbonyl ene reaction. Starting from 4‐methyl‐styrene the anti‐tubercular agent (+)‐erogorgiaene (>98 % ee) was prepared in only 7 steps with 46 % overall yield. In addition, the synthesis of the pseudopterosin A aglycone was achieved in 12 steps with 30 % overall yield and, surprisingly, was found to exhibit a similar anti‐inflammatory activity (inhibition of LPS‐induced NF‐κB activation) as a natural mixture of pseudopterosins A−D or iso‐pseudopterosin A, prepared by β‐D‐xylosylation of the synthetic aglycone.
Thioredoxin (Trx) overexpression is known to be a cause of chemotherapy resistance in various tumor entities. However, Trx effects on resistance are complex and depend strictly on tissue type. In the present study, we analyzed the impact of the Trx system on intrinsic chemoresistance of human glioblastoma multiforme (GBM) cells to cytostatic drugs. Resistance of GBM cell lines and primary cells to drugs and signaling inhibitors was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. Impact of Trx inhibition on apoptosis was investigated by proteome profiling of a subset of proteins and annexin V apoptosis assays. Trx-interacting protein (TXNIP) was overexpressed by transfection and protein expression was determined by immunoblotting. Pharmacological inhibition of Trx by 1-methyl-2-imidazolyl-disulfide (PX-12) reduced viability of three GBM cell lines, induced expression of active caspase-3, and reduced phosphorylation of AKT-kinase and expression of β-catenin. Sensitivity to cisplatin could be restored by both PX-12 and recombinant expression of the upstream Trx inhibitor TXNIP, respectively.
In addition, PX-12 also sensitized primary human GBM cells to temozolomide. Combined inhibition of Trx and the phosphatidylinositide 3-kinase (PI3K) pathway resulted in massive cell death. We conclude that the Trx system and the PI3K pathway act as a sequential cascade and could potentially present a new drug target.
AbstractThis paper discusses the comparison of two methods to achieve thermal comfort utilising air conditioning (AC) system in a small indoor space – adaptive control and fuzzy control. Thermal comfort indoors is performed to provide comfortability individually or for a group of people. Due to the small indoor space which usually a bit cramped, crowded and less airy, the ambience can be very uncomfortable either for doing sedentary or active work, thus the AC system can be very useful to provide thermal comfort. Both methods can be utilised depending on how thermal comfort is viewed and how the level of thermal comfort is decided. Every method has its own advantage and limitations, and will be covered in this paper as well.
This paper documents the design, implementation and evaluation of the Unfolding Space Glove—an open source sensory substitution device. It transmits the relative position and distance of nearby objects as vibratory stimuli to the back of the hand and thus enables blind people to haptically explore the depth of their surrounding space, assisting with navigation tasks such as object recognition and wayfinding. The prototype requires no external hardware, is highly portable, operates in all lighting conditions, and provides continuous and immediate feedback—all while being visually unobtrusive. Both blind (n = 8) and blindfolded sighted participants (n = 6) completed structured training and obstacle courses with both the prototype and a white long cane to allow performance comparisons to be drawn between them. The subjects quickly learned how to use the glove and successfully completed all of the trials, though still being slower with it than with the cane. Qualitative interviews revealed a high level of usability and user experience. Overall, the results indicate the general processability of spatial information through sensory substitution using haptic, vibrotactile interfaces. Further research would be required to evaluate the prototype’s capabilities after extensive training and to derive a fully functional navigation aid from its features.
We examine the impact of the existence on an explicit deposit insurance (DI) scheme and its design features on bilateral cross‐border deposits (CBD) in a gravity model setting. We find that both the absolute quality of a country's DI and its relative quality vis‐à‐vis other countries' DI generally affect depositor behavior. However, during systemic banking crises, cross‐border depositors primarily seek countries with the best DI schemes. Similarly, during the 2008–2009 great financial crisis, the emergency actions taken by the governments, which supply and maintain these safe havens, have led to substantial relocations of CBD. (JEL F34, G18)
This study aimed to simulate the sector-coupled energy system of Germany in 2030 with the restriction on CO2 emission levels and to observe how the system evolves with decreasing emissions. Moreover, the study presented an analysis of the interconnection between electricity, heat and hydrogen and how technologies providing flexibility will react when restricting CO2 emissions levels. This investigation has not yet been carried out with the technologies under consideration in this study. It shows how the energy system behaves under different set boundaries of CO2 emissions and how the costs and technologies change with different emission levels. The study results show that the installed capacities of renewable technologies constantly increase with higher limitations on emissions. However, their usage rates decreases with low CO2 emission levels in response to higher curtailed energy. The sector-coupled technologies behave differently in this regard. Heat pumps show similar behaviour, while the electrolysers usage rate increases with more renewable energy penetration. The system flexibility is not primarily driven by the hydrogen sector, but in low CO2 emission level scenarios, the flexibility shifts towards the heating sector and electrical batteries.
The Production of Isophorone
(2023)
Isophorone is a technically important compound used as a high-boiling-point solvent for coatings, adhesives, etc., and it is used as a starting material for various valuable compounds, including isophorone diisocyanate, a precursor for polyurethanes. For over 80 years, isophorone has been synthesized via base-catalyzed self-condensation of acetone. This reaction has a complex reaction mechanism with numerous possible reaction steps including the formation of isophorone, triacetone dialcohol, and ketonic resins. This review provides an overview of the different production processes of isophorone in liquid- and vapor-phase and reviews the literature-reported selectivity toward isophorone achieved using different reaction parameters and catalysts.
In this work, supported cellulose acetate (CA) mixed matrix membranes (MMMs) were prepared and studied concerning their gas separation behaviors. The dispersion of carbon nanotube fillers were studied as a factor of polymer and filler concentrations using the mixing methods of the rotor–stator system (RS) and the three-roll-mill system (TRM). Compared to the dispersion quality achieved by RS, samples prepared using the TRM seem to have slightly bigger, but fewer and more homogenously distributed, agglomerates. The green γ-butyrolactone (GBL) was chosen as a polyimide (PI) polymer-solvent, whereas diacetone alcohol (DAA) was used for preparing the CA solutions. The coating of the thin CA separation layer was applied using a spin coater. For coating on the PP carriers, a short parameter study was conducted regarding the plasma treatment to affect the wettability, the coating speed, and the volume of dispersion that was applied to the carrier. As predicted by the parameter study, the amount of dispersion that remained on the carriers decreased with an increasing rotational speed during the spin coating process. The dry separation layer thickness was varied between about 1.4 and 4.7 μm. Electrically conductive additives in a non-conductive matrix showed a steeply increasing electrical conductivity after passing the so-called percolation threshold. This was used to evaluate the agglomeration behavior in suspension and in the applied layer. Gas permeation tests were performed using a constant volume apparatus at feed pressures of 5, 10, and 15 bar. The highest calculated CO2/N2 selectivity (ideal), 21, was achieved for the CA membrane and corresponded to a CO2 permeability of 49.6 Barrer.
In water electrolyzers, polymer electrolyte membranes (PEMs) such as Nafion can accumulate cations stemming from salt impurities in the water supply, which leads to severe cell voltage increases. This combined experimental and computational study discusses the influence of sodium ion poisoning on the ionic conductivity of Nafion membranes and the ion transport in a thereon based water electrolysis cell. Conductivities of Nafion and aqueous solutions with the same amount of dissolved cations are measured with impedance spectroscopy and compared with respect to Nafion’s microstructure. The dynamic behavior of the voltage of a water electrolysis cell is characterized as a function of the sodium ion content and current density, showing the differences of the ion transport at alternating and direct currents. These experimental results are elucidated with a physical ion transport model for sodium ion poisoned Nafion membranes, which describes a proton depletion and sodium ion accumulation at the cathode. During proton depletion, the cathodic hydrogen evolution is maintained by the water reduction that forms hydroxide ions. Together with sodium ions from the membrane, the formed hydroxide ions can diffuse pairwise into the water supply, so that the membrane’s sodium ions can be at least partly be replaced with anodically formed protons.
This study explores the potential of robust, strongly basic type I ion exchange resins—specifically, Amberlyst® A26 OH and Lewatit® K 6465—as catalysts for the aldol condensation of citral and acetone, yielding pseudoionone. Emphasis is placed on their long-term stability and commendable performance in continuous operational settings. The aldol reaction, which traditionally is carried out using aqueous sodium hydroxide as the catalyst, holds the potential for enhanced sustainability and reduced waste production through the use of basic ion exchange resins in heterogeneous catalysis. Density Functional Theory (DFT) calculations are employed to investigate catalyst deactivation mechanisms. The result of these calculations indicates that the active sites of Amberlyst® A26 OH are cleaved more easily than the active sites of Lewatit® K 6465. However, the experimental data show a gradual decline in catalytic activity for both resins. Batch experiments reveal Amberlyst® A26 OH’s active sites diminishing, while Lewatit® K 6465 maintains relative consistency. This points to distinct deactivation processes for each catalyst. The constant count of basic sites in Lewatit® K 6465 during the reaction suggests additional factors due to its unique polymer structure. This intriguing observation also highlights an exceptional temperature stability for Lewatit® K 6465 compared to Amberlyst® A26 OH, effectively surmounting one of the prominent challenges associated with the utilization of ion exchange resins in catalytic applications.
The teaching of civil engineering consists of different didactic approaches, such as lectures, group work or research-based teaching, depending on the respective courses. Currently, the metaverse is gaining importance in teaching and offers the possibility of a new teaching approach for civil engineering and especially for the teaching of courses from the areas of “Digital Design and Construction”. Although the advantages of teaching in the metaverse, such as location and time independence or a higher learning outcome, are mentioned in the literature, there are also challenges that must be considered when teaching in the metaverse. Against this background, this paper examines the implications of using the metaverse as a teaching tool in teaching “Digital Design and Construction”. The impact of teaching BIM in the metaverse is evaluated by (1) a literature review and workshops to evaluate use cases and demands for extended reality (XR) and the metaverse, (2) integrating XR and the metaverse in the courses and valuation by quantitative evaluations and (3) analyzing student papers of the courses and outcomes of a World Café. Due to these steps, this paper presents a novel approach by reflecting the students’ perspective. Furthermore, this paper presents a validated approach for integrating BIM and the metaverse in teaching.
Table Tennis Tutor: Forehand Strokes Classification Based on Multimodal Data and Neural Networks
(2021)
Beginner table-tennis players require constant real-time feedback while learning the fundamental techniques. However, due to various constraints such as the mentor’s inability to be around all the time, expensive sensors and equipment for sports training, beginners are unable to get the immediate real-time feedback they need during training. Sensors have been widely used to train beginners and novices for various skills development, including psychomotor skills. Sensors enable the collection of multimodal data which can be utilised with machine learning to classify training mistakes, give feedback, and further improve the learning outcomes. In this paper, we introduce the Table Tennis Tutor (T3), a multi-sensor system consisting of a smartphone device with its built-in sensors for collecting motion data and a Microsoft Kinect for tracking body position. We focused on the forehand stroke mistake detection. We collected a dataset recording an experienced table tennis player performing 260 short forehand strokes (correct) and mimicking 250 long forehand strokes (mistake). We analysed and annotated the multimodal data for training a recurrent neural network that classifies correct and incorrect strokes. To investigate the accuracy level of the aforementioned sensors, three combinations were validated in this study: smartphone sensors only, the Kinect only, and both devices combined. The results of the study show that smartphone sensors alone perform sub-par than the Kinect, but similar with better precision together with the Kinect. To further strengthen T3’s potential for training, an expert interview session was held virtually with a table tennis coach to investigate the coach’s perception of having a real-time feedback system to assist beginners during training sessions. The outcome of the interview shows positive expectations and provided more inputs that can be beneficial for the future implementations of the T3.
Emergency management services, such as firefighting, rescue teams and ambulances,are all heavily reliant on road networks. However, even for highly industrialised countries such asGermany, and even for large cities, spatial planning tools are lacking for road network interruptionsof emergency services. Moreover, dependencies of emergency management expand not only onroads but on many other systemic interrelations, such as blockages of bridges. The first challenge thispaper addresses is the development of a novel assessment that captures systemic interrelations ofcritical services and their dependencies explicitly designed to the needs of the emergency services.This aligns with a second challenge: capturing system nodes and areas around road networksand their geographical interrelation. System nodes, road links and city areas are integrated into aspatial grid of tessellated hexagons (also referred to as tiles) with geographical information systems.The hexagonal grid is designed to provide a simple map visualisation for emergency planners andfire brigades. Travel time planning is then optimised for accessing city areas in need by weighingimpaired areas of past events based on operational incidents. The model is developed and testedwith official incident data for the city of Cologne, Germany, and will help emergency managers tobetter device planning of resources based on this novel identification method of critical areas.
Linoleic acid hydroperoxides are versatile intermediates for the production of green note aroma compounds and bifunctional ω-oxo-acids. An enzyme cascade consisting of lipoxygenase, lipase and catalase was developed for one-pot synthesis of 13-hydroperoxyoctadecadienoic acid starting from safflower oil. Reaction conditions were optimized for hydroperoxidation using lipoxygenase 1 from Glycine max (LOX-1) in a solvent-free system. The addition of green surfactant Triton CG-110 improved the reaction more than two-fold and yields of >50% were obtained at linoleic acid concentrations up to 100 mM. To combine hydroperoxidation and oil hydrolysis, 12 lipases were screened for safflower oil hydrolysis under the reaction conditions optimized for LOX-1. Lipases from Candida rugosa and Pseudomonas fluorescens were able to hydrolyze safflower oil to >75% within 5 h at a pH of 8.0. In contrast to C. rugosa lipase, the enzyme from P. fluorescens did not exhibit a lag phase. Combination of P. fluorescens lipase and LOX-1 worked well upon LOX-1 dosage and a synergistic effect was observed leading to >80% of hydroperoxides. Catalase from Micrococcus lysodeikticus was used for in-situ oxygen production with continuous H2O2 dosage in the LOX-1/lipase reaction system. Foam generation was significantly reduced in the 3-enzyme cascade in comparison to the aerated reaction system. Safflower oil concentration was increased up to 300 mM linoleic acid equivalent and 13-hydroperoxides could be produced in a yield of 70 g/L and a regioselectivity of 90% within 7 h.
Abstract
(−)‐Menthol is one of the most popular aroma compounds worldwide. While in the past mostly extracted from mint plants, today (−)‐menthol synthesis from other raw materials is becoming more relevant. Common starting materials for menthol synthesis are m‐cresol, citral and myrcene, but also substrates like menthone, mono‐ and bicyclic terpenes and terpenoids have been used for this purpose in the past. As for many applications (−)‐menthol of high purity is required, asymmetric syntheses and enantiomeric resolution of obtained raw products are applied for menthol production. This review gives an overview on the most important synthetic menthol production processes of the companies Symrise, Takasago and BASF and relevant literature in the field of menthol synthesis with a focus on the last 20 years.
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.