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In this work, we propose a novel data-driven approach to recover missing or corrupted motion capture data, either in the form of 3D skeleton joints or 3D marker trajectories. We construct a knowledge-base that contains prior existing knowledge, which helps us to make it possible to infer missing or corrupted information of the motion capture data. We then build a kd-tree in parallel fashion on the GPU for fast search and retrieval of this already available knowledge in the form of nearest neighbors from the knowledge-base efficiently. We exploit the concept of histograms to organize the data and use an off-the-shelf radix sort algorithm to sort the keys within a single processor of GPU. We query the motion missing joints or markers, and as a result, we fetch a fixed number of nearest neighbors for the given input query motion. We employ an objective function with multiple error terms that substantially recover 3D joints or marker trajectories in parallel on the GPU. We perform comprehensive experiments to evaluate our approach quantitatively and qualitatively on publicly available motion capture datasets, namely CMU and HDM05. From the results, it is observed that the recovery of boxing, jumptwist, run, martial arts, salsa, and acrobatic motion sequences works best, while the recovery of motion sequences of kicking and jumping results in slightly larger errors. However, on average, our approach executes outstanding results. Generally, our approach outperforms all the competing state-of-the-art methods in the most test cases with different action sequences and executes reliable results with minimal errors and without any user interaction.
Austria is committed to the net-zero climate goal along with the European Union. This requires all sectors to be decarbonized. Hereby, hydrogen plays a vital role as stated in the national hydrogen strategy. A report commissioned by the Austrian government predicts a minimum hydrogen demand of 16 TWh per year in Austria in 2040. Besides hydrogen imports, domestic production can ensure supply. Hence, this study analyses the levelized cost of hydrogen for an off-grid production plant including a proton exchange membrane electrolyzer, wind power and solar photovoltaics in Austria. In the first step, the capacity factors of the renewable electricity sources are determined by conducting a geographic information system analysis. Secondly, the levelized cost of electricity for wind power and solarphotovoltaics plants in Austria is calculated. Thirdly, the most cost-efficient portfolio of wind power and solar photovoltaics plants is determined using electricity generation profiles with a 10-min granularity. The modelled system variants differ among location, capacity factors of the renewable electricity sources and the full load hours of the electrolyzer. Finally, selected variables are tested for their sensitivities. With the applied model, the hydrogen production cost for decentralized production plants can be calculated for any specific location. The levelized cost of hydrogen estimates range from 3.08 EUR/kg to 13.12 EUR/kg of hydrogen, whereas it was found that the costs are most sensitive to the capacity factors of the renewable electricity sources and the full load hours of the electrolyzer. The novelty of the paper stems from the model applied that calculates the levelized cost of renewable hydrogen in an off-grid hydrogen production system. The model finds a cost-efficient portfolio of directly coupled wind power and solar photovoltaics systems for 80 different variants in an Austria-specific context.
Abstract
Even though researchers are increasingly acknowledging the dark side of customer participation (i.e., behavioral customer engagement), particularly in professional services with high cognitive demands that cause customer participation stress (i.e., negative psychological state resulting from the customer's overextension by required customer participation efforts), insights on how firms can effectively mitigate customer participation stress remains limited. Building on transactional stress theory, we investigate whether customers can effectively cope with the expected cognitive demands of professional services. Moreover, by introducing an adapted coping construct (i.e., coping support), we examine whether employees can provide coping support to help decrease customer participation stress. The findings of a time‐lagged field study with customers of a large German bank (N = 117) suggest that customer coping before the encounter cannot mitigate the effect of anticipated cognitive demands on customer participation stress. Instead, the results of both the field study and a follow‐up experimental study (N = 218) show that a certain set of employee coping support during service encounters is crucial. While focusing on action coping support is not ideal in situations with high cognitive demands, firms should advise their professional service employees to offer emotional coping support to attenuate the unfavorable effect of cognitive demands on customer participation stress.
As the population ages, the demand for care for older adults is increasing. To maintain their independence and autonomy, even with declining health, assistive technologies such as connected medical devices or social robots can be useful. In previous work, we introduced a novel health monitoring system that combines commercially available products with apps designed specifically for older adults. The system is intended for the long-term collection of subjective and objective health data. In this work, we present an exploratory user experience (UX) and usability study we conducted with older adults as the target group of the system and with younger expert users who tested our msystem. All participants interacted with a social robot conducting a health assessment and tested sensing devices and an app for data visualization. The UX and usability of the individual components of the system were rated highly in questionnaires in all sessions. All participants also said they would use such a system in their everyday lives, demonstrating the potential of these systems for self-managing users’ health. Finally, we found factors such as previous experience with social robots and technological expertise to have an influence on the reported UX of the users.
To date, the establishment of high-titer stable viral packaging cells (VPCs) at large scale for gene therapeutic applications is very time- and cost-intensive. Here we report the establishment of three human suspension 293-F-derived ecotropic MLV-based VPCs. The classic stable transfection of an EGFP-expressing transfer vector resulted in a polyclonal VPC pool that facilitated cultivation in shake flasks of 100 mL volumes and yielded high functional titers of more than 1 × 106 transducing units/mL (TU/mL). When the transfer vector was flanked by transposon terminal inverted repeats (TIRs) and upon co-transfection of a plasmid encoding for the transposase, productivities could be slightly elevated to more than 3 × 106 TU/mL. In contrast and using mRNA encoding for the transposase, as a proof of concept, productivities were drastically improved by more than ten-fold exceeding 5 × 107 TU/mL. In addition, these VPC pools were generated within only 3 weeks. The production volume was successfully scaled up to 500 mL employing a stirred-tank bioreactor (STR). We anticipate that the stable transposition of transfer vectors employing transposase transcripts will be of utility for the future establishment of high-yield VPCs producing pseudotype vector particles with a broader host tropism on a large scale.
Porous polymer membranes substantially contribute to an acceleration of sustainability transformation based on the energy efficient separation of liquid and gaseous mixtures. This rapid shift toward sustainable industrial processes leads to an increased demand for specifically tailored membranes. In order to predict membrane performance factors like permeability, selectivity and durability, the membrane formation process by film casting and phase inversion needs to be understood further. In recent years, computational models of the membrane formation process have been studied intensely. Their high spatial and temporal resolution allows a detailed quantitative description of phase inversion phenomena. New experimental techniques complement this development, as they provide quantitative data, e.g., on compositional changes of the polymer solution during membrane formation as well as the kinetic progression of the phase separation process. This state-of-the-art review compiles computational and experimental approaches that characterize the phase inversion process. We discuss how this methodological pluralism is necessary for improving the tailoring of membrane parameters, but that it is unlikely to be the way to the ultimate goal of a complete description of the evolution of the membrane structure from the initial demixing to the final solidification. Alternatively, we formulate an approach that includes a database of standardized and harmonized membrane performance data based on previously publicized data, as well as the application of artificial neural networks as a new powerful tool to link membrane production parameters to membrane performance.
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.
Agents with antifungal activity play a vital role as therapeutics in health care, as do fungicides in agriculture. Effectiveness, toxicological profile, and eco-friendliness are among the properties used to select suitable substances. Furthermore, a steady supply of new agents with different modes of action is required to counter the well-known potential of human and phyto-pathogenic fungi to develop resistance against established antifungals. Here, we use an in vitro growth assay to investigate the activity of the calcineurin inhibitor tacrolimus in combination with the commercial fungicides cyproconazole and hymexazol, as well as with two earlier reported novel {2-(3-R-1H-1,2,4-triazol-5-yl)phenyl}amines, against the fungi Aspergillus niger, Colletotrichum higginsianum, Fusarium oxysporum and the oomycete Phytophthora infestans, which are notoriously harmful in agriculture. When tacrolimus was added in a concentration range from 0.25 to 25 mg/L to the tested antifungals (at a fixed concentration of 25 or 50 mg/L), the inhibitory activities were distinctly enhanced. Molecular docking calculations revealed triazole derivative 5, (2-(3-adamantan-1-yl)-1H-1,2,4-triazol-5-yl)-4-chloroaniline), as a potent inhibitor of chitin deacetylases (CDA) of Aspergillus nidulans and A. niger (AnCDA and AngCDA, respectively), which was stronger than the previously reported polyoxorin D, J075-4187, and chitotriose. The results are discussed in the context of potential synergism and molecular mode of action.
During spaceflight, humans experience a variety of physiological changes due to deviations from familiar earth conditions. Specifically, the lack of gravity is responsible for many effects observed in returning astronauts. These impairments can include structural as well as functional changes of the brain and a decline in cognitive performance. However, the underlying physiological mechanisms remain elusive. Alterations in neuronal activity play a central role in mental disorders and altered neuronal transmission may also lead to diminished human performance in space. Thus, understanding the influence of altered gravity at the cellular and network level is of high importance. Previous electrophysiological experiments using patch clamp techniques and calcium indicators have shown that neuronal activity is influenced by altered gravity. By using multi-electrode array (MEA) technology, we advanced the electrophysiological investigation covering single-cell to network level responses during exposure to decreased (micro-) or increased (hyper-) gravity conditions. We continuously recorded in real-time the spontaneous activity of human induced pluripotent stem cell (hiPSC)-derived neural networks in vitro. The MEA device was integrated into a custom-built environmental chamber to expose the system with neuronal cultures to up to 6 g of hypergravity on the Short-Arm Human Centrifuge at the DLR Cologne, Germany. The flexibility of the experimental hardware set-up facilitated additional MEA electrophysiology experiments under 4.7 s of high-quality microgravity (10–6 to 10–5 g) in the Bremen drop tower, Germany. Hypergravity led to significant changes in activity. During the microgravity phase, the mean action potential frequency across the neural networks was significantly enhanced, whereas different subgroups of neurons showed distinct behaviors, such as increased or decreased firing activity. Our data clearly demonstrate that gravity as an environmental stimulus triggers changes in neuronal activity. Neuronal networks especially reacted to acute changes in mechanical loading (hypergravity) or de-loading (microgravity). The current study clearly shows the gravity-dependent response of neuronal networks endorsing the importance of further investigations of neuronal activity and its adaptive responses to micro- and hypergravity. Our approach provided the basis for the identification of responsible mechanisms and the development of countermeasures with potential implications on manned space missions.
The European heating sector is currently heavily dominated by fossil fuels. Composting is a naturally occurring process in which heat is liberated from the composting substrate at a higher rate than the process needs to support itself. This difference could be harnessed for low-heat applications such as residential consumption, alleviating some of the impacts fossil fuel emissions represent. In this study, the composting heat recovery reported in the literature was compared to the energy demand for space and water heating in four European countries. A review of potential heat production from the waste representative of the residential sector was performed. We found that the theoretically recoverable composting heat does not significantly reduce the need for district heating. However, it can significantly reduce the energy demand for water heating, being able to supply countries such as Greece with between 36% and 100% of the yearly hot water demand, or 12% to 53% of the yearly hot water of countries such as Switzerland, depending on the efficiency of heat recovery.
The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.
Hydroxybenzene, commonly known as phenol, is one of the most important organic commodity chemicals. To produce phenol, the cumene process is the most used process worldwide. A crucial step in this process is the Hock rearrangement, which has a major impact on the overall cumene consumption rate and determines the safety level of the process. The most used catalyst for the cleavage of cumene hydroperoxide (CHP) is sulfuric acid. Besides its strong corrosive property, which increases plant investment costs, it also requires neutralization after the decomposition step to prevent side reactions. In this study, we show that high-temperature-treated Linde Type X (LTX) zeolites exhibit a high activity for the peroxide cleavage step. In addition, the structure–activity relationship responsible for this good performance in the reaction system of the HOCK rearrangement was investigated. XRPD analyses revealed the formation of a new phase after temperature treatment above 900 °C. The Si/Al ratio determined by EDX suggested the formation of extra-framework aluminum, which was confirmed by solid-state NMR analysis. The newly formed extra-framework aluminum was found to be responsible for the high catalytic activity. BET analyses showed that the surface area drops at higher calcination temperatures. This leads to a lower catalytic activity for most known reactions. However, for this study, no decrease in activity has been observed. The newfound material shows extraordinarily high activity as a catalyst in the HOCK cleavage and has the potential to be a heterogeneous alternative to sulfuric acid for this reaction.
The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque deep reinforcement learning (DRL) agents. We investigate three algorithms for generating training data for axis-parallel and oblique DTs with the help of DRL agents (“oracles”) and evaluate these methods on classic control problems from OpenAI Gym. The results show that one of our newly developed algorithms, the iterative training, outperforms traditional sampling algorithms, resulting in well-performing DTs that often even surpass the oracle from which they were trained. Even higher dimensional problems can be solved with surprisingly shallow DTs. We discuss the advantages and disadvantages of different sampling methods and insights into the decision-making process made possible by the transparent nature of DTs. Our work contributes to the development of not only powerful but also explainable RL agents and highlights the potential of DTs as a simple and effective alternative to complex DRL models.
Multifocal intraocular lenses incorporate a variety of design considerations, including dimensioning of the base monofocal shape and the diffraction grating. While studying three different lens models, we present a practical approach for mathematical modelling and evaluation of these geometries. Contrary to typical lens measurement methods, non-contact measurements were performed on the Alcon SN6AD1, HumanOptics MS 612 DAY and the AMO ZMA00 lenses using a confocal microscope. Subsequent data processing includes centering, tilting correction, filtering and an algorithmic decomposition into a conic and polynomial part and the diffraction grating. Lastly, evaluation of fitting parameters and grating shape is done to allow for inferences about further optical properties. Results and analysis show the confocal microscope to be a suitable imaging method for lens measurements. The processing of this data enables the reconstruction of the annular diffraction grating over the complete lens diameter. Apodization, near addition and diffraction efficiency characteristics are found utilizing the grating shape. Additionally, near-optical axis curvature, asphericity and higher order polynomials are identified qualitatively from the reconstruction of the monofocal base form. Derived properties also include the lens optical base and addition power. By making use of the surface geometries, as well as the lens’ material and thickness, a full lens model can be created for further studies. In summary, our analytical approach enables the insight to various intraocular lens design decisions. Furthermore, this procedure is suitable for lens model creation for research and simulation.
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.
A novel approach to manufacture components with integrated conductor paths involves embedding and sintering an isotropic conductive adhesive (ICA) during fused filament fabrication (FFF). However, the molten plastic is deposited directly onto the adhesive path which causes an inhomogeneous displacement of the uncured ICA. This paper presents a 3D printing strategy to achieve a homogeneous cross-section of the conductor path. The approach involves embedding the ICA into a printed groove and sealing it with a wide extruded plastic strand. Three parameter studies are conducted to obtain a consistent cavity for uniform formation of the ICA path. Specimens made of polylactic acid (PLA) with embedded ICA paths are printed and evaluated. The optimal parameters include a groove printed with a layer height of 0.1 mm, depth of 0.4 mm, and sealed with a PLA strand of 700 µm diameter. This resulted in a conductor path with a homogeneous cross-section, measuring 660 µm ± 22 µm in width (relative standard deviation: 3.3%) and a cross-sectional area of 0.108 mm2 ± 0.008 mm2 (relative standard deviation 7.2%). This is the first study to demonstrate the successful implementation of a printing strategy for embedding conductive traces with a homogeneous cross-sectional area in FFF 3D printing.
To date, the establishment of high-titer stable viral packaging cells (VPCs) at large scale for gene therapeutic applications is very time- and cost-intensive. Here we report the establishment of three human suspension 293-F-derived ecotropic MLV-based VPCs. The classic stable transfection of an EGFP-expressing transfer vector resulted in a polyclonal VPC pool that facilitated cultivation in shake flasks of 100 mL volumes and yielded high functional titers of more than 1 × 106 transducing units/mL (TU/mL). When the transfer vector was flanked by transposon terminal inverted repeats (TIRs) and upon co-transfection of a plasmid encoding for the transposase, productivities could be slightly elevated to more than 3 × 106 TU/mL. In contrast and using mRNA encoding for the transposase, as a proof of concept, productivities were drastically improved by more than ten-fold exceeding 5 × 107 TU/mL. In addition, these VPC pools were generated within only 3 weeks. The production volume was successfully scaled up to 500 mL employing a stirred-tank bioreactor (STR). We anticipate that the stable transposition of transfer vectors employing transposase transcripts will be of utility for the future establishment of high-yield VPCs producing pseudotype vector particles with a broader host tropism on a large scale.
Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data
(2023)
The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control.
Positive Impact of Red Soil on Albedo and the Annual Yield of Bifacial Photovoltaic Systems in Ghana
(2023)
The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.
Ground tire rubber (GTR) is a product obtained by grinding worn tire treads before retreading them or via the cryogenic or ambient temperature milling of end-of-life tires (ELTs). The aim of this study is to evaluate if calcium carbonate can be substituted by GTR and, if so, to what extent. Different types of ground tire rubber are incorporated in an EPDM (ethylene–propylene–diene–rubber) model compound as partial or complete substitutes of calcium carbonate. The raw compounds and the vulcanizates are characterized to identify the limits. In general, it is apparent that increasing amounts of GTR and larger particles degrade the mechanical properties. The GTR also influences the vulcanization kinetics by reducing the scorch time up to 50% and vulcanization time up to nearly 80%. This is significant for production processes. The compounds with one-third substitution with the smaller-particle-size GTR show mostly similar or even better properties than the reference.
Steer-by-wire systems represent a key technology for highly automated and autonomous driving. In this context, robust steering control is a fundamental precondition for automated vehicle lateral control. However, there is a need for improvement due to degrees of freedom, signal delays, and nonlinear characteristics of the plant which are unconsidered in the design models for the design of current steering controls. To be able to design an extremely robust steering control, suitable optimal models of a steer-by-wire system are required. Therefore, this paper presents an innovative nonlinear detail model of a steer-by-wire system. The detail model represents all characteristics of a real steer-by-wire system. In the context of a dominance analysis of the detail model, all dominant characteristics of a steer-by-wire system, including parameter dependencies, are identified. Through model reduction, a reduced model of the steer-by-wire system is then developed that can be used for a subsequent robust control design. Furthermore, this paper compares the steer-by-wire system with a conventional electromechanical power steering and shows similarities as well as differences.
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.
Ten years after the journal’s first publication, we are taking a closer look at the knowledge flows of the output of the journal Publications. We analyzed the papers, topics, their authors and countries to assess the development of scholarly communication within Publications. Our bibliometric analyses show the research journal’s community, where the knowledge of this community is coming from, where it is going, and how diverse the community is based on its internationality and multidisciplinarity. We compare these findings with the scopes and topical goals the journal specifies. We aim at informing the editors and editorial board about the journal’s development to advance the journal’s role in scholarly communication. The results show that regarding topical diversity and internationality, the journal has remarkably developed. Moreover, the journal tends towards the field of library and information science, but strengthens its multidisciplinary status via its topics and author backgrounds.
Feasibility Study of Wheel Torque Prediction with a Recurrent Neural Network Using Vehicle Data
(2023)
In this paper, we present a feasibility study on predicting the torque signal of a passenger car with the help of a neural network. In addition, we analyze the possibility of using the proposed model structure for temperature prediction. This was carried out with a neural network, specifically a three-layer long short-term memory (LSTM) network. The data used were real road load data from a Jaguar Land Rover Evoque with a Twinster gearbox from GKN. The torque prediction generated good results with an accuracy of 55% and a root mean squared error (RMSE) of 49 Nm, considering that the data were not generated under laboratory conditions. However, the performance of predicting the temperature signal was not satisfying with a coefficient of determination (R2) score of −1.396 and an RMSE score of 69.4 °C. The prediction of the torque signal with the three-layer LSTM network was successful but the transferability of the network to another signal (temperature) was not proven. The knowledge gained from this investigation can be of importance for the development of virtual sensor technology.
Reducing the carbon emissions from hotels on non-interconnected islands (NII) is essential in the context of a low carbon future for the Mediterranean region. Maritime tourism is the major source of income for Greece and many other countries in the region, as well as hot-temperate and tropical regions worldwide. Like many NIIs, Rhodes attracts a high influx of tourists every summer, doubling the island’s energy demand and, given the high proportion of fossil fuels in the Rhodian energy supply, increasing carbon emissions. Using the theoretical framework ‘FINE’, this paper presents the optimisation of a medium-sized hotel’s energy system with the aim of reducing both cost and carbon emissions. By introducing a Photovoltaic (PV) net metering system, it was found that the carbon emissions associated with an NII hotel’s energy system could be reduced by 31% at an optimised cost. It is suggested that large-scale deployment of PV or alternative renewable energy sources (RES) in NII hotels could significantly reduce carbon emissions associated with the accommodation sector in Greece and help mitigate climate change.
Decisions on irrigation water management are usually made at different levels, including farms, water user associations (WUAs), and regional water planning agencies. The latter generally have good access to information and decision tools regarding water resources management. However, these remain out of reach to the final water users, namely the farmers. The study, conducted in the irrigated district of Cherfech, north Tunisia, had the main objective of investigating farmer’s perceptions of, and acceptance for, the use of an irrigation advisory service (IAS) to be implemented by their WUA. The suggested IAS provides the following information: (1) reference evapotranspiration (ETo) and rainfall; (2) crop water requirement (CWR) of the most cultivated crops; (3) irrigation water requirement (IWR) of the farmer’s crop; and (4) crop monitoring and real-time estimation of IWR of crops settled, using soil moisture sensors. Such services and information would be available at the WUA level and provided in a timely manner to farmers for more effective decision making at the plot level. Prior to the acceptance study, we launched a technical study to determine the required tools and equipment required for the implementation of the IAS, followed by a farmer survey to assess their respective perceptions and acceptance towards this IAS. Results showed that only 54% of the farmers are satisfied by WUAs work, but that 77% of them accepted using the suggested IAS. Farmers are also willing to pay for most of the IAS packages suggested. The financial profitability of investing in the IAS at the WUA level shows the venture is financially viable, with a benefit cost ratio (BCR) of 1.018. The project will be even more profitable if we add the social benefits, which may result in water savings at the WUA level.
Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems. Still, it is difficult for practitioners to get an overview that explains their advantages in comparison to a large number of available methods in the scope of optimization. Available taxonomies lack the embedding of current approaches in the larger context of this broad field. This article presents a taxonomy of the field, which explores and matches algorithm strategies by extracting similarities and differences in their search strategies. A particular focus lies on algorithms using surrogates, nature-inspired designs, and those created by automatic algorithm generation. The extracted features of algorithms, their main concepts, and search operators, allow us to create a set of classification indicators to distinguish between a small number of classes. The features allow a deeper understanding of components of the search strategies and further indicate the close connections between the different algorithm designs. We present intuitive analogies to explain the basic principles of the search algorithms, particularly useful for novices in this research field. Furthermore, this taxonomy allows recommendations for the applicability of the corresponding algorithms.
Conventional individual head-related transfer function (HRTF) measurements are demanding in terms of measurement time and equipment. For more flexibility, free body movement (FBM) measurement systems provide an easy-to-use way to measure full-spherical HRTF datasets with less effort. However, having no fixed measurement installation implies that the HRTFs are not sampled on a predefined regular grid but rely on the individual movements of the subject. Furthermore, depending on the measurement effort, a rather small number of measurements can be expected, ranging, for example, from 50 to 150 sampling points. Spherical harmonics (SH) interpolation has been extensively studied recently as one method to obtain full-spherical datasets from such sparse measurements, but previous studies primarily focused on regular full-spherical sampling grids. For irregular grids, it remains unclear up to which spatial order meaningful SH coefficients can be calculated and how the resulting interpolation error compares to regular grids. This study investigates SH interpolation of selected irregular grids obtained from HRTF measurements with an FBM system. Intending to derive general constraints for SH interpolation of irregular grids, the study analyzes how the variation of the SH order affects the interpolation results. Moreover, the study demonstrates the importance of Tikhonov regularization for SH interpolation, which is popular for solving ill-posed numerical problems associated with such irregular grids. As a key result, the study shows that the optimal SH order that minimizes the interpolation error depends mainly on the grid and the regularization strength but is almost independent of the selected HRTF set. Based on these results, the study proposes to determine the optimal SH order by minimizing the interpolation error of a reference HRTF set sampled on the sparse and irregular FBM grid. Finally, the study verifies the proposed method for estimating the optimal SH order by comparing interpolation results of irregular and equivalent regular grids, showing that the differences are small when the SH interpolation is optimally parameterized.
Changing our unsustainable linear water management pattern is necessary to face growing global water challenges. This article proposes an integrated framework to analyse and understand the role of different contextual conditions in the possible transition towards water circularity. Our framework combines a systematic multi-level perspective to explore the water system and the institutional work theory for technology legitimation. The framework consists of the following stages: (1) describing and understanding the water context, (2) assessment of the selected technologies’ circularity level, (3) assessment of the alternative circular technologies’ legitimacy, and (4) identification of the legitimation actions to support the upscale of alternative circular technologies. The practical applicability of the integrated assessment framework and its four assessment stages was demonstrated in the exploration of circular water technologies for the horticulture sector in Westland, the Netherlands. The results revealed the conditions that hinder or enable the legitimation of the circular water technologies, such as political environmentalism, trust in water governing authorities, and technical, financial, and knowledge capabilities.
Electroplating generates high volumes of rinse water that is contaminated with heavy metals. This study presents an approach for direct metal recovery and recycling from simulated rinse water, made up of an electroplating electrolyte used in industry, using reverse osmosis (RO). To simulate the real industrial application, the process was examined at various permeate fluxes, ranging from 3.75 to 30 L·m−2·h−1 and hydraulic pressures up to 80 bar. Although permeance decreased significantly with increasing water recovery, rejections of up to 93.8% for boric acid, >99.9% for chromium and 99.6% for sulfate were observed. The final RO retentate contained 8.40 g/L chromium and was directly used in Hull cell electroplating tests. It was possible to deposit cold-hued chromium layers under a wide range of relevant current densities, demonstrating the reusability of the concentrate of the rinsing water obtained by RO.
Resilience in the urban context can be described as a continuum of absorptive, adaptive, and transformative capacities. The need to move toward a sustainable future and bounce forward after any disruption has led recent urban resilience initiatives to engage with the concept of transformative resilience when and where conventional and top-down resilience initiatives are less likely to deliver effective strategies, plans, and implementable actions. Transformative resilience pathways emphasize the importance of reflexive governance, inclusive co-creation of knowledge, innovative and collaborative learning, and self-organizing processes. To support these transformative pathways, considering techno-social co-evolution and digital transformation, using new data sources such as Volunteered Geographic Information (VGI) and crowdsourcing are being promoted. However, a literature review on VGI and transformative resilience reveals that a comprehensive understanding of the complexities and capacities of utilizing VGI for transformative resilience is lacking. Therefore, based on a qualitative content analysis of available resources, this paper explores the key aspects of using VGI for transformative resilience and proposes a comprehensive framework structured around the identified legal, institutional, social, economic, and technical aspects to formalize the process of adopting VGI in transformative resilience initiatives.
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.
Due to the COVID-19 pandemic, university students worldwide have experienced drastic changes in their academic and social lives, with the rapid shift to online courses and contact restrictions being reported among the major stressors. In the present study, we aimed at examining students’ perceived stress over the course of the pandemic as well as individual psychological and social coping resources within the theoretical framework of the Transactional Model of Stress and Coping in the specific group of STEM students. In four cross-sectional studies with a total of 496 computer science students in Germany, we found that students reported significantly higher levels of perceived stress at both measurement time points in the second pandemic semester (October/November 2020; January/February 2021) as compared to the beginning of the first (April/May 2020), indicating that students rather became sensitized to the constant pandemic-related stress exposure than habituating to the “new normal”. Regarding students’ coping resources in the higher education context, we found that both high (a) academic self-efficacy and (b) academic online self-efficacy as well as low (c) perceived social and academic exclusion among fellow students significantly predicted lower levels of students’ (d) belonging uncertainty to their study program, which, in turn, predicted lower perceived stress at the beginning of the first pandemic semester. At the beginning of the second pandemic semester, we found that belonging uncertainty still significantly mediated the relationship between students’ academic self-efficacy and perceived stress. Students’ academic online self-efficacy, however, no longer predicted their uncertainty about belonging, but instead had a direct buffering effect on their perceived stress. Students’ perceived social and academic exclusion among fellow students only marginally predicted their belonging uncertainty and no longer predicted their perceived stress 6 months into the pandemic. We discuss the need and importance of assessing and monitoring students’ stress levels as well as faculty interventions to strengthen students’ individual psychological and social coping resources in light of the still ongoing pandemic.
A bifacial Photovoltaic (PV) simulation model is created by combining the optical View Factor matrix with electrical output simulation in python to analyse the energy density of bifacial systems. A discretization of the rear side of the bifacial modules allows a further investigation of mismatching and losses due to inhomogeneous radiation distribution. The model is validated, showing a deviation of -1.25 % to previous simulation models and giving hourly resolvedoutput data with a higher accuracy than existing software for bifacial PV systems.
3d printing is capable of providing dose individualization for pediatric medicines and translating the precision medicine approach into practical application. In pediatrics, dose individualization and preparation of small dosage forms is a requirement for successful therapy, which is frequently not possible due to the lack of suitable dosage forms. For precision medicine, individual characteristics of patients are considered for the selection of the best possible API in the most suitable dose with the most effective release profile to improve therapeutic outcome. 3d printing is inherently suitable for manufacturing of individualized medicines with varying dosages, sizes, release profiles and drug combinations in small batch sizes, which cannot be manufactured with traditional technologies. However, understanding of critical quality attributes and process parameters still needs to be significantly improved for this new technology. To ensure health and safety of patients, cleaning and process validation needs to be established. Additionally, adequate analytical methods for the in-process control of intermediates, regarding their printability as well as control of the final 3d printed tablets considering any risk of this new technology will be required. The PolyPrint consortium is actively working on developing novel polymers for fused deposition modeling (FDM) 3d printing, filament formulation and manufacturing development as well as optimization of the printing process, and the design of a GMP-capable FDM 3d printer. In this manuscript, the consortium shares its views on quality aspects and measures for 3d printing from drug-loaded filaments, including formulation development, the printing process, and the printed dosage forms. Additionally, engineering approaches for quality assurance during the printing process and for the final dosage form will be presented together with considerations for a GMP-capable printer design.
The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.
Different mechanisms mediate the toxicity of RNA. Genomic retroviral mRNA hijacks infected host cell factors to enable virus replication. The viral genomic RNA of the human immunodeficiency virus (HIV) encompasses nine genes encoding in less than 10 kb all proteins needed for replication in susceptible host cells. To do so, the genomic RNA undergoes complex alternative splicing to facilitate the synthesis of the structural, accessory, and regulatory proteins. However, HIV strongly relies on the host cell machinery recruiting cellular factors to complete its replication cycle. Antiretroviral therapy (ART) targets different steps in the cycle, preventing disease progression to the acquired immunodeficiency syndrome (AIDS). The comprehension of the host immune system interaction with the virus has fostered the development of a variety of vaccine platforms. Despite encouraging provisional results in vaccine trials, no effective vaccine has been developed, yet. However, novel promising vaccine platforms are currently under investigation.
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.
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.
Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.
Despite great efforts to develop a vaccine against human immunodeficiency virus (HIV), which causes AIDS if untreated, no approved HIV vaccine is available to date. A promising class of vaccines are virus-like particles (VLPs), which were shown to be very effective for the prevention of other diseases. In this study, production of HI-VLPs using different 293F cell lines, followed by a three-step purification of HI-VLPs, was conducted. The quality-by-design-based process development was supported by process analytical technology (PAT). The HI-VLP concentration increased 12.5-fold while >80% purity was achieved. This article reports on the first general process development and optimization up to purification. Further research will focus on process development for polishing and formulation up to lyophilization. In addition, process analytical technology and process modeling for process automation and optimization by digital twins in the context of quality-by-design framework will be developed.
Climate change includes the change of the long-term average values and the change of the tails of probability density functions, where the extreme events are located. However, obtaining average values are more straightforward than the high temporal resolution information necessary to catch the extreme events on those tails. Such information is difficult to get in areas lacking sufficient rain stations. Thanks to the development of Satellite Precipitation Estimates with a daily resolution, this problem has been overcome, so Extreme Precipitation Indices (EPI) can be calculated for the entire Colombian territory. However, Colombia is strongly affected by the ENSO (El Niño—Southern Oscillation) phenomenon. Therefore, it is pertinent to ask if the EPI’s long-term change due to climate change is more critical than the anomalies due to climate variability induced by the warm and cold phases of ENSO (El Niño and La Niña, respectively). In this work, we built EPI annual time series at each grid-point of the selected Satellite Precipitation Estimate (CHIRPSv2) over Colombia to answer the previous question. Then, the Mann-Whitney-Wilcoxon test was used to compare the samples drawn in each case (i.e., change tests due to both long-term and climatic variability). After performing the analyses, we realized that the importance of the change depends on the region analyzed and the considered EPI. However, some general conclusions became evident: during El Niño years (La Niña), EPI’s anomaly follows the general trend of reduction -drier conditions- (increase; -wetter conditions-) observed in Colombian annual precipitation amount, but only on the Pacific, the Caribbean, and the Andean region. In the Eastern plains of Colombia (Orinoquía and Amazonian region), EPI show a certain insensitivity to change due to climatic variability. On the other hand, EPI’s long-term changes in the Pacific, the Caribbean, and the Andean region are spatially scattered. Still, long-term changes in the eastern plains have a moderate spatial consistency with statistical significance.
The management of the liquid fraction of digestate produced from the anaerobic digestion of biodegradable municipal solid waste is a difficult affair, as its land application is limited due to high ammonium concentrations and the municipal waste that water treatment plants struggle to treat due to high pollutant loads. The amount of leachate and the pollutant load in the leachate produced by landfills usually decreases with the time, which increases the capacity of landfill leachate treatment plants (LLTPs) to treat additional wastewater. In order to solve the above two challenges, the co-treatment of landfill leachate and the liquid fraction of anaerobic digestate in an industrial-scale LLTP was investigated along with the long-term impacts of the liquid fraction of anaerobic digestate on biocoenosis and its impact on LLTP operational expenses. The co-treatment of landfill leachate and liquid fraction of anaerobic digestate was compared to conventional leachate treatment in an industrial-scale LLTP, which included the use of two parallel lanes (Lane-1 and Lane-2). The average nitrogen removal efficiencies in Lane-1 (co-treatment) were 93.4%, 95%, and 92%, respectively, for C/N ratios of 8.7, 8.9, and 9.4. The average nitrogen removal efficiency in Lane-2 (conventional landfill leachate treatment), meanwhile, was 88%, with a C/N ratio of 6.5. The LLTP’s average chemical oxygen demand (COD) removal efficiencies were 63.5%, 81%, and 78% during phases one, two, and three, respectively. As the volume ratios of the liquid fraction of anaerobic digestate increased, selective oxygen uptake rate experiments demonstrated the dominance of heterotrophic bacteria over ammonium and nitrite-oxidising organisms. The inclusion of the liquid fraction of anaerobic digestate during co-treatment did not cause a significant increase in operational resources, i.e., oxygen, the external carbon source, activated carbon, and energy.
Microphone arrays consisting of sensors mounted on the surface of a rigid, spherical scatterer are popular tools for the capture and binaural reproduction of spatial sound scenes. However, microphone arrays with a perfectly spherical body and uniformly distributed microphones are often impractical for the consumer sector, in which microphone arrays are generally mounted on mobile and wearable devices of arbitrary geometries. Therefore, the binaural reproduction of sound fields captured with arbitrarily shaped microphone arrays has become an important field of research. In this work, we present a comparison of methods for the binaural reproduction of sound fields captured with non-spherical microphone arrays. First, we evaluated equatorial microphone arrays (EMAs), where the microphones are distributed on an equatorial contour of a rigid, spherical 1.
Second, we evaluated a microphone array with six microphones mounted on a pair of glasses. Using these two arrays, we conducted two listening experiments comparing four rendering methods based on acoustic scenes captured in different rooms2. The evaluation includes a microphone-based stereo approach (sAB stereo), a beamforming-based stereo approach (sXY stereo), beamforming-based binaural reproduction (BFBR), and BFBR with binaural signal matching (BSM). Additionally, the perceptual evaluation included binaural Ambisonics renderings, which were based on measurements with spherical microphone arrays. In the EMA experiment we included a fourth-order Ambisonics rendering, while in the glasses array experiment we included a second-order Ambisonics rendering. In both listening experiments in which participants compared all approaches with a dummy head recording we applied non-head-tracked binaural synthesis, with sound sources only in the horizontal plane. The perceived differences were rated separately for the attributes timbre and spaciousness. Results suggest that most approaches perform similarly to the Ambisonics rendering. Overall, BSM, and microphone-based stereo were rated the best for EMAs, and BFBR and microphone-based stereo for the glasses array.
Abstract
Two types (with and without a hydrolysis stabilizer) of polyamide 6.6 (PA6.6) reinforced with 30% w/w glass fibres were examined against the influence of automotive cooling fluids, e.g. ethylene glycol aqueous solutions. The overall goal was to find a methodology to compare the performance of PA6.6 materials against the impacts of the hydrolysis environment. The stabilizer effect on the hydrolytic resistance of the materials was assessed using tensile tests according to ISO 527, and their strain‐at‐break values were evaluated in more detail. The degradation mechanism of both PA types was monitored by infrared spectroscopy and SEM. The material lifetime was described by the Arrhenius equation. The results show that the hydrolysis stabilizer operates effectively at low temperature but exhibits weak performance above 130 °C, which is explained by faster consumption of the stabilizing agent. © 2021 The Authors. Polymer International published by John Wiley & Sons Ltd on behalf of Society of Industrial Chemistry.
The importance of lithium as a raw material is steadily increasing, especially in the growing markets of grid energy and e-mobility. Today, brines are the most important lithium sources. The rising lithium demand raises concerns over the expandability and the environmental impact of common mining techniques, which are mainly based on the evaporation of brine solutions (Salars) in arid and semiarid areas. In this case, much of the water contained in the brine is lost. Purification processes lead to further water losses of the ecosystems. This calls for new and improved processes for lithium production; one of them is electrodialysis (ED). Electrodialysis offers great potential in accessing lithium from brines in a more environmentally friendly way; furthermore, for the recovery of lithium from spent lithium-ion batteries (LIB), electrodialysis may become a vital technology. The following study focused on investigating the effect of varying brine compositions, different ED operation modes, and limiting factors on the use of ED for concentrating lithium-containing brine solutions. Synthetic lithium salt solutions (LiCl, LiOH) were concentrated using conventional ED in batch-wise operation. While the diluate solution was exchanged once a defined minimum concentration was reached, the concentrate solution was concentrated to the respective maximum. The experiments were conducted using a lab-scale ED-plant (BED1-3 from PCCell GmbH, Germany). The ion-exchange membranes used were PCSK and PCSA. The treated solutions varied in concentration and composition. Parameters such as current density, current efficiency, and energy requirements were evaluated. ED proved highly effective in the concentration of lithium salt solutions. Lithium chloride solutions were concentrated up to approximately 18-fold of the initial concentration. Current efficiencies and current densities depended on voltage, concentration, and the composition of the brine. Overall, the current efficiencies reached maximum values of around 70%. Furthermore, the experiments revealed a water transport of about 0.05 to 0.075% per gram of LiCl transferred from the diluate solution to the concentrate solution.
Pressure injuries remain a serious health complication for patients and nursing staff. Evidence from the past decade has not been analysed through narrative synthesis yet. PubMed, Embase, CINAHL Complete, Web of Science, Cochrane Library, and other reviews/sources were screened. Risk of bias was evaluated using a slightly modified QUIPS tool. Risk factor domains were used to assign (non)statistically independent risk factors. Hence, 67 studies with 679,660 patients were included. In low to moderate risk of bias studies, non-blanchable erythema reliably predicted pressure injury stage 2. Factors influencing mechanical boundary conditions, e.g., higher interface pressure or BMI < 18.5, as well as factors affecting interindividual susceptibility (male sex, older age, anemia, hypoalbuminemia, diabetes, hypotension, low physical activity, existing pressure injuries) and treatment-related aspects, such as length of stay in intensive care units, were identified as possible risk factors for pressure injury development. Health care professionals’ evidence-based knowledge of above-mentioned risk factors is vital to ensure optimal prevention and/or treatment. Openly accessible risk factors, e.g., sex, age, BMI, pre-existing diabetes, and non-blanchable erythema, can serve as yellow flags for pressure injury development. Close communication concerning further risk factors, e.g., anemia, hypoalbuminemia, or low physical activity, may optimize prevention and/or treatment. Further high-quality evidence is warranted.
The oxidation of cumene and following cleavage of cumene hydroperoxide (CHP) with sulfuric acid (Hock rearrangement) is still, by far, the dominant synthetic route to produce phenol. In 2020, the global phenol market reached a value of 23.3 billion US$ with a projected compound annual growth rate of 3.4% for 2020–2025. From ecological and economical viewpoints, the key step of this process is the cleavage of CHP. One sought-after way to likewise reduce energy consumption and waste production of the process is to substitute sulfuric acid with heterogeneous catalysts. Different types of zeolites, silicon-based clays, heteropoly acids, and ion exchange resins have been investigated and tested in various studies. For every type of these solid acid catalysts, several materials were found that show high yield and selectivity to phenol. In this mini-review, first a brief introduction and overview on the Hock process is given. Next, the mechanism, kinetics, and safety aspects are summarized and discussed. Following, the different types of heterogeneous catalysts and their performance as catalyst in the Hock process are illustrated. Finally, the different approaches to substitute sulfuric acid in the synthetic route to produce phenol are briefly concluded and a short outlook is given.
AbstractThe Ganges-Brahmaputra (GB) delta is one of the most disaster-prone areas in the world due to a combination of high population density and exposure to tropical cyclones, floods, salinity intrusion and other hazards. Due to the complexity of natural deltaic processes and human influence on these processes, structural solutions like embankments are inadequate on their own for effective hazard mitigation. This article examines nature-based solutions (NbSs) as a complementary or alternative approach to managing hazards in the GB delta. We investigate the potential of NbS as a complementary and sustainable method for mitigating the impacts of coastal disaster risks, mainly cyclones and flooding. Using the emerging framework of NbS principles, we evaluate three existing approaches: tidal river management, mangrove afforestation, and oyster reef cultivation, all of which are actively being used to help reduce the impacts of coastal hazards. We also identify major challenges (socioeconomic, biophysical, governance and policy) that need to be overcome to allow broader application of the existing approaches by incorporating the NbS principles. In addition to addressing GB delta-specific challenges, our findings provide more widely applicable insights into the challenges of implementing NbS in deltaic environments globally.