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This research examines the potential outputs, outcomes, and impacts of the German Act on Corporate Due Diligence Obligations in Supply Chains (LkSG) on the smallholder cocoa farmers in West Africa. The study primarily relies on a literature review and an impact pathway to conduct a systematic analysis to identify the potential effects of the LkSG on smallholder cocoa farmers. The findings indicate that some, but not all of the risks addressed by the LkSG align with those faced by smallholder cocoa farmers and their families. Additionally, the research also reveals weaknesses, particularly in managing environmental risks, which the LkSG does not adequately cover. Our findings show that in the short- and medium-term, the LkSG has no potential effects on smallholder cocoa farmers. Furthermore, the potential positive impacts of the law on smallholder cocoa farmers will take a long time to realize, as the LkSG considers primarily tier-1 suppliers. Companies in Germany might reassess their supply chains to strive for an LkSG-risk-free supply chain, which could in the long term have sustained impacts on smallholder cocoa farmers. However, we recommend a comprehensive risk analysis of the cocoa supply chain to enhance the human rights of cocoa farmers.
Environmental pollution by plastics is a global issue of increasing concern. However, microplastic analysis in complex environmental matrices, such as soil samples, remains an analytical challenge. Destructive mass-based methods for microplastic analysis do not determine plastics’ shape and size, which are essential parameters for reliable ecological risk assessment. By contrast, nondestructive particle-based methods produce such data but require elaborate, time-consuming sample preparation. Thus, time-efficient and reliable methods for microplastic analysis are needed. The present study explored the potential of frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) for rapidly and reliably identifying as well as differentiating plastics and natural materials from terrestrial environments. We investigated the fluorescence spectra of ten natural materials from terrestrial environments, tire wear particles, and eleven different transparent plastic granulates <5 mm to determine the optimal excitation wavelength for identification and differentiation via FD-FLIM under laboratory conditions. Our comparison of different excitation wavelengths showed that 445 nm excitation exhibited the highest fluorescence intensities. 445 nm excitation was also superior for identifying plastic types and distinguishing them from natural materials from terrestrial environments with a high probability using FD-FLIM. We could demonstrate that FD-FLIM analysis has the potential to contribute to a streamlined and time-efficient direct analysis of microplastic contamination. However, further investigations on size-, shape-, color-, and material-type detection limitations are necessary to evaluate if the direct identification of terrestrial environmental samples of relatively low complexity, such as a surface inspection soil, is possible.
Microplastic pollution of the environment has been extensively studied, with recent studies focusing on the prevalence of microplastics in the environment and their effects on various organisms. Identification methods that simplify the extraction and analysis process to the point where the extraction can be omitted are being investigated, thus enabling the direct identification of microplastic particles. Currently, microplastic samples from environmental matrices can only be identified using time-consuming extraction, sample processing, and analytical methods. Various spectroscopic methods are currently employed, such as micro Fourier-transform infrared, attenuated total reflectance, and micro Raman spectroscopy. However, microplastics in environmental matrices cannot be directly identified using these spectroscopic methods. Investigations using frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) to identify and differentiate plastics from environmental materials have yielded promising results for directly identifying microplastics in an environmental matrix. Herein, two artificially prepared environmental matrices that included natural soil, grass, wood, and high-density polyethylene were investigated using FD-FLIM. Our first results showed that we successfully identified one plastic type in the two artificially prepared matrices using FD-FLIM. However, further research must be conducted to improve the FD-FLIM method and explore its limitations for directly identifying microplastics in environmental samples.
Previous research on identifying plastic types and differentiating plastics from environmental material is promising by utilizing the specific fluorescence lifetime, but the evaluation still has to be automated. Therefore, an automated Gaussian analysis is developed for evaluating frequency-domain fluorescence lifetime images of plastics and environmental materials. Furthermore, we applied a “Multilayer Perceptron” and “Random Forest Classifier” to the data resulting from the Gaussian analysis of the frequency domain fluorescence lifetime imaging microscopy data. The classification results show high F1-scores, whereby the best “Multilayer Perceptron” and “Random Forest Classifier” achieved an F1-score of 90%. Thus, identifying and differentiating plastics and environmental materials is possible by applying a “Multilayer Perceptron” or “Random Forest Classifier” to the Gaussian-analyzed imaged fluorescence lifetime data.
Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix.
Existing plastic analysis techniques such as Fourier transform infrared spectroscopy and Raman spectroscopy are problematic because samples must be anhydrous and identification can be hindered by additives. This article describes a new approach that has been successfully demonstrated in which plastics can be classified by neural networks that are trained, validated, and tested by frequency domain fluorescence lifetime imaging microscopy measurements.
The FD-FLIM technique has a high potential for automated post-consumer wood sorting. A problem of analysing post-consumer wood fluorescence properties is the uncertainty of the post-consumer wood category as the origin of the samples are unknown. In this study, the fluorescence properties of actual post-consumer wood is compared with prepared wood samples. The post-consumer wood samples display slightly different fluorescence intensities and lifetimes due to environmental influences and a higher sample diversity. For improved training of evaluation algorithms for post-consumer wood sorting, the prepared sample set should be extended or the post-consumer wood should be additionally analysed in the laboratory.
Development of a Neural Network for Automatic Classification of Post-Consumer Wood Using Rapid-FLIM
(2023)
The economic use of wood is a growing sector, not only because of the significant advantage of wood to retain CO 2 . It is crucial to increase the material recycling of wood in several lifecycles, but currently, there is no reliable post-consumer wood sorting technique in line. This research measures 365 post-consumer wood samples of classes A1-4 four times with the frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) subset method rapid fluorescence lifetime imaging microscopy (Rapid-FLIM). The data is analyzed on their statistical features. Four neural networks based on Multilayer perceptron are then trained and tested with twelve statistical features extracted from the Rapid-FLIM images. The best model for this application contains the optimizer RMSprop, the activation function SELU and the loss function binary crossentropy. The best model of this structure could achieve a false positive ratio of 4.79 % over the ten folds.
The fast classification and identification of plastics presents a significant challenge. The study assesses the suitability of a Multilayer Perceptron to classify and identify commonly found plastic types using Rapid-FLIM, achieving an accuracy of 88.33%. @inproceedingsSchwarz:23, Increasing demand for wood products requires methods to determine its harvest origin and ensure sustainable and legal sourcing. In 15 out of 21 cases, the origin of Quercus robur was differentiable in FD-FLIM studies.
Investigation of tool wear of the trimming unit and resulting quality in the edgebanding process
(2023)
The edgebanding process, i.e. the covering of the raw edge of the laminated particleboard by means of decorative plastic or real wood veneer bands, is an important process step in the manufacture of furniture components. The quality of the final product is significantly influenced by this production step. The manufacturing process step within the edgebanding machine begins with the milling of the raw edge. The quality of the edgebanding process is determined by a large number of process input variables, such as the tool used and the cutting geometry, the type of laminate used for the wood-based material, adhesives, etc. The quality of the edgebanding process is also determined by the type of material processed. Particularly with regard to the materials, the increased use of recycled wood in the particleboard sector and different types of adhesives (with reduced formaldehyde emissions) results in increased demands on the milling process. Due to this developments, most of the earlier investigations (in the years 1990 - 2000) are not comparable with today’s general conditions. The mechanical and optical properties of the edge applied to the end product are decisively influenced by the quality of this joint. The milling technology used, as well as the tool used for this purpose and its condition, is a decisive influencing factor in the formation of quality. Tests on the indication of various influencing variables in the edgebanding process at the Rosenheim Technical University of Applied Sciences showed that in the case of chipboard milling, a decrease in the electrical power required for the cutting process can take place with increasing tool wear. It was also demonstrated that previous process steps in furniture production, such as panel dividing by means of sawing or milling/nesting, generally have a significantly different influence on the subsequent joining process during edge banding process. Furthermore, a direct correlation was determined between the mechanical properties of the end product and the condition of the tool used, which can be used as a measurable indicator. In addition to the effect of the tool condition on the mechanical properties of the edge banding, this also has an impact on the optical quality characteristics. Accordingly, it could be demonstrated here that an increase in the size and number of chippings takes place in the laminate of the board material to be processed.
The machining of furniture components requires a complete geometrical specification of dimensions with associated tolerances to define in the first step appropriate manufacturing processes and to carry out the design and setup. Furthermore, a verification of the defined specification after production is a next step to check the quality and related to the production equipment, to calculate process capability and effectiveness.
In 2011, the system of Geometrical Product Specification (GPS) has been published completely. The system is built for a distinct range of geometrical quality characteristics and consists of chains of standards referring to each other. With three elements of these chains, the product can be specified. With three additional elements, the verification of the product and the measuring system is possible. It does not contain the verification of the production processes, the process qualification.
The German standard DIN 68100 provides a frame for dimensioning and tolerancing lengths and also angles, parallelism and straightness for furniture components. It includes a method to consider swelling and shrinking of wood and wood-based materials. Apart from its benefit of specifying products in a supply chain, it is rarely used in the branch nowadays. DIN 68100 is currently far away from GPS.
To gain all benefits arising from GPS the branch needs a consolidated action. New symbols for drafts and an updated method for tolerancing with moisture consideration have to be developed as well as measuring dimensions of flexible work pieces, like most parts in the furniture industry. In GPS, the link between product verification and process specification is not that consistent. In other branches SPC and methods of process qualifications are established. At the moment the kitchen industry is establishing SPC or similar procedures. An action towards GPS can also accompany these efforts.
Due to a shift in the tolerance principles, the GPS system is hardly directly applicable to the furniture industry, e.g. DIN 68100. But there is a real threat that the system is called up accidentally and out of ignorance.
This paper sketches a comprehensive system of product specification, verification for furniture components and process qualification. It will share experience gained in the kitchen furniture industry and will add a theoretical analysis of a possible application of GPS-chains for important examples of quality characteristics. The activities are part of a process (VDI 3415-2) carried out in the working group 102 of the Society of German Engineers (VDI).
Due to the increasing customer demands, companies face the challenge of adapting their manufacturing facilities to produce batch size one parts. In this context, each component comes with specific customer requirements, significantly increasing the complexity of its manufacturing process. Traditional process planning done by employees is no longer feasible in the face of the growing complexity and diversity of batch size one parts. Therefore, there is a need for novel computer-aided process planning methods capable of autonomously learning and identifying the necessary machining features of these parts. We propose a configurable automated feature recognition framework tailored to batch size one parts to address this need. This framework comprises two main components. First, a customizable data generator is developed to create a dataset of computer-aided design models incorporating user-specific machining features. Second, a graph neural network is employed to learn these user-specific machining features by leveraging the graph structure represented by the vertices and edges in each computer-aided design model. We evaluate the effectiveness of our framework using a real-world example from the furniture industry. Specifically, we construct a dataset comprising over 7000 computer-aided design models of wooden boards using our framework's data generator. Each wooden board contains up to 30 randomly placed machining features for the application of connectors and fittings, randomly selected from 14 standard machining features commonly used in the furniture industry. An optimization algorithm adapts a graph neural network for classifying these specific machining features. The results demonstrate that our framework addresses the automated feature recognition problem without requiring data conversions, such as pixels or voxels, as other approaches often do. By introducing this configurable automated feature recognition framework, we solve the challenges posed by batch size one manufacturing. The framework's effectiveness and accuracy are demonstrated through extensive testing on the example of the furniture industry, showcasing its potential for enhancing manufacturing processes in various domains
In the whole field of woodworking, from carpentry to industry, new products are created and designed every day and manufacturers wonder if similar workpieces have already been produced in the company and if corresponding drawings, information, tools, jigs, etc. can be reused. Under certain circumstances, considerable duplication of work can be avoided and a more efficient production is possible. In order to find similar workpieces, it must be clarified what exactly is meant by similarity. The different fields of knowledge do not provide a clear definition. However, similarities are always used to compare objects. In woodworking, objects can be a wide variety of components and products, such as carcase sides, furniture fronts, fittings, tools or profile strips. The search for similar profiled elements – related to the potential, data structure and algorithms – is the focus of this paper. There is a wide range of different profiled elements, which are used constructively as well as decoratively, e.g. for baseboards, door frames, window frames or decorative moulding profiles. These profiles are manufactured in a multi-stage production process in which the workpieces are first machined with profiled tools before surface finishing takes place. Along this production chain, tools, machine settings and, in some cases, fixtures are used that are adapted to the respective profile and can be reused for the same or similar jobs. Inheritance of information offers the greatest potential of similarity search. Inheritance means that existing knowledge in the form of drawings, CNC programs, process parameters and setup specifications, etc., is transferred from existing profiles to a new profile. By inheriting existing information, for example, the effort required for process setting can be reduced by adopting spindle positions, positions of guides and stops, or feed and cutting speeds. However, this can only be done if the process knowledge and other technological information concerning a profile are sufficiently documented. This is the only way how all information is made available for the similarity search and inheritance, and also for setting the processes when the profile is manufactured once again. The profile data must therefore be stored in a meaningful structure without loss of information. Therefore, a holistic product data model was developed that combines the geometrical with the technological profile data. The developed model allows a combined search for geometrically and e.g. materially similar products – also with a weighted evaluation of the individual criteria. The research has shown that data modelling is the essential foundation for the implementation of modern AI algorithms to enable similarity search. In conclusion, the use of a search system for geometrically and technologically similar profiles represents a real innovation for wood processing companies. This paper presents a holistic approach for geometrical and technological similarity search presenting different algorithms
This research examines the potential outputs, outcomes, and impacts of the German Act on Corporate Due Diligence Obligations in Supply Chains (LkSG) on the smallholder cocoa farmers in West Africa. The study primarily relies on a literature review and an impact pathway to conduct a systematic analysis to identify the potential effects of the LkSG on smallholder cocoa farmers. The findings indicate that some, but not all of the risks addressed by the LkSG align with those faced by smallholder cocoa farmers and their families. Additionally, the research also reveals weaknesses, particularly in managing environmental risks, which the LkSG does not adequately cover. Our findings show that in the short- and medium-term, the LkSG has no potential effects on smallholder cocoa farmers. Furthermore, the potential positive impacts of the law on smallholder cocoa farmers will take a long time to realize, as the LkSG considers primarily tier-1 suppliers. Companies in Germany might reassess their supply chains to strive for an LkSG-risk-free supply chain, which could in the long term have sustained impacts on smallholder cocoa farmers. However, we recommend a comprehensive risk analysis of the cocoa supply chain to enhance the human rights of cocoa farmers.
Teachers should be able to balance content knowledge, pedagogical knowledge and technological knowledge (TPACK) in their various activities on curriculum, instruction, and assessment. Our Germany-wide study focused on measuring intrapreneurship competence. To ensure a valid and reliable assessment, we followed the three-step assessment triangle: cognition, observation and interpretation. We modeled the intended IP competence as an interdisciplinary and interprofessional team, designed a technology-based performance assessment tool that uses authentic work tasks, and analyzed apprentices’ behavior via a model-based IRT (Rasch model) approach. Our results identify the distribution of the IP competence of apprentices on four proficiency levels. Since these results are generalizable, single IP tasks can be used by teachers to support and guide apprentices individually with regard to these proficiency levels. Our approach is a blueprint for evidence-based teaching that tackles all areas of TPACK.
Stirring is used for mass and heat transfer, particle suspending or similar processes. It is commonly conducted in a steady operation mode. This paper targets on performing the stirring process dynamically by reversing the rotation direction to introduce additional turbulences and hence accelerating the dispersing processes. The power introduced into the fluid as well as mixing kinetics performing dynamic mixing were studied based on the rotational acceleration, blade pitch angle, liquid volume and duration of the rotational speed direction interval for a vessel equipped with a turbine agitator with and without baffles. Experiments show that baffles are not necessary if reverse mixing is performed at a specific frequency.
Stable isotope data from hypogene (i.e., below the line of weathering) iron oxides and gangue minerals from BIF-hosted iron ore deposits in Australia, South Africa, and Brazil have significantly assisted in constraining different hydrothermal fluid sources and fluid flow models during the upgrade of BIF to iron ore. The δ18O values on iron oxides from BIF and different paragenetic stages of enrichment display a consistent decrease from unenriched BIF (4–9‰) to as low as −10‰ for high-grade iron ore. This large shift in oxygen isotope values is interpreted as evidence for enormous incursion of ‘ancient’ meteoric water into fault and fracture zones at the time of iron enrichment during the Archean and Paleoproterozoic time. The δ18Ofluid values of paragenetically early iron oxides of > 4‰ suggest the involvement of magmatic fluids in greenstone belt-hosted Carajás-type iron ore deposits, and basinal brines in basin-hosted Hamersley-type deposits. In contrast, the paragenetically late stage iron oxides in the metamorphosed, basin hosted iron ore deposits of the Quadrilátero Ferrífero display δ18Ofluid values > 6‰. This reflects the renewed deep crustal, hypogene (metamorphic or magmatic) fluid influx. Carbon and oxygen isotope data on carbonates in BIF and hydrothermally altered iron ore indicate that carbon in the latter is not derived from BIF units, but represents either magmatic carbon in the case of the Carajás-type deposits or carbon within the underlying basin stratigraphy as in the case of the Hamersley-type iron deposits. The systematic decrease of δ18O values in iron oxides from the early to late paragenetic stages and from the distal to proximal alteration zone, including the ore zone, may be used as a geochemical vector. In this case, oxygen isotope analyses on iron oxides provide a potential exploration tool, particularly for targeting the extension of iron ore bodies or entirely concealed high-grade iron ore deposits, in which hematite/magnetite are frequently the only mineral that can be readily analysed.
Large-scale, hypogene iron mineralization systems developed recurrently in the São Francisco craton in association with two orogenies. During the ca. 2.1–2.0 Ga Trans-Amazonian orogeny, low-temperature and low-to-moderate-salinity metamorphic fluids resulted in carbonatization-related iron enrichment of the early Paleoproterozoic Cauê Iron Formation (IF) of the Minas Supergroup (MSG) as well as short-distance iron mobilization. Monazite from the iron-oxide veins yielded a SHRIMP 232Th/208Pb date corresponding to fluid circulation coeval with the migmatization of the Archean tonalite-trondhjemite-granodiorite crust. During the Ediacaran to Cambrian Brasiliano orogeny, when the São Francisco craton was consolidated in its present configuration, hydrothermal fluids repeatedly mineralized the Cauê IF and the younger IFs of the lower Espinhaço Supergroup. Far-field hydrothermal alteration associated with distinct Fe mineralization episodes widely affected Meso- to Neoproterozoic sequences as well as Archean to Paleoproterozoic terranes of the cratonic core. Circulation of hydrothermal fluids during the Brasiliano orogeny caused desilicification, iron mobilization, and widespread alteration of the rocks. The alteration events are dated with monazite and xenotime intergrown with hematite, anatase, and recrystallized rims of detrital zircons from interlayered quartzites and of igneous zircons from pegmatites, granites, acidic volcanic rocks, and orthogneisses, yielding U-Pb dates between 542 and 493 Ma. U-Pb dates point to five Cambrian hydrothermal events from the waning stages to the aftermath of the Brasiliano orogeny. These hydrothermal fluid circulation events correspond to the emplacement ages of four granite suites and pegmatites that lasted from the final stages of the collision to the collapse of the Araçuaí-West Congo orogen. Episodic circulation of fluids continued for approximately 2 billion years after IF deposition on the eastern São Francisco craton with the formation of high-grade iron ore deposits and resetting of the IF trace-element inventory.
This study investigates for the first time how public charging infrastructure usage differs under the presence of diverse pricing models. About 3 million charging events from different European countries were classified according to five different pricing models (cost-free, flat-rate, time-based, energy-based, and mixed) and evaluated using various performance indicators such as connection duration; transferred energy volumes; average power; achievable revenue; and the share of charging and idle time for AC, DC, and HPC charging infrastructure. The study results show that the performance indicators differed for the classified pricing models. In addition to the quantitative comparison of the performance indicators, a Kruskal–Wallis one-way analysis of variance and a pairwise comparison using the Mann–Whitney-U test were used to show that the data distributions of the defined pricing models were statistically significantly different. The results are discussed from various perspectives on the efficient design of public charging infrastructure. The results show that time-based pricing models can improve the availability of public charging infrastructure, as the connection duration per charging event can be roughly halved compared to other pricing models. Flat-rate pricing models and AC charging infrastructure can support the temporal shift of charging events, such as shifting demand peaks, as charging events usually have several hours of idle time per charging process. By quantifying various performance indicators for different charging technologies and pricing models, the study is relevant for stakeholders involved in the development and operation of public charging infrastructure.
In any dimension d≥2, there is no known example of a low-discrepancy sequence which possesses Poisssonian pair correlations. This is in some sense rather surprising, because low-discrepancy sequences always have β-Poissonian pair correlations for all 0<β<1/d and are therefore arbitrarily close to having Poissonian pair correlations (which corresponds to the case β=1/d). In this paper, we further elaborate on the closeness of the two notions. We show that d-dimensional Kronecker sequences for badly approximable vectors α→ with an arbitrary small uniformly distributed stochastic error term generically have β=1/d-Poissonian pair correlations.
Organizational mining, a sub-discipline of process mining, introduced social networks based on business processes. However, process mining has only half-heartedly pursued this line of development. In particular, the well-founded results of interdisciplinary social network analysis have hardly been taken up.
This article shows how the explanation and design of the phenomenon "organization" can benefit from the further development of this network view of business processes. To this end, the basic idea of social process networks is presented and the current state of research is outlined. Furthermore, social networks are presented as a new component of organization design. An interesting, far-reaching new field of research is expected.
This paper presents three novel findings that could be the starting point for further research, but can also be used in practice today.
The variation of the contact impedance of adhesive conductive EMI shielding tapes under high temperature storage (HTS) of 110degC is investigated. The adhesive tapes under test are implemented as signal return paths in microstrip lines. Changes in the ground plane impedance by adhesive deterioration are analyzed by S-parameter measurements from 1MHz to 3GHz. A circuit model for contact impedance degradation is proposed and applied in simulation of board level shielding. Contact resistance and contact capacitance are found to increase significantly after 2400h, causing a declined magnetic field shielding effectiveness by 30 dB below 500 MHz.
Previous work has indicated that testing can enhance memory for subsequently studied new information by reducing proactive interference from previously studied information. Here, we examined this forward testing effect in children’s spatial memory. Kindergartners (5–6 years) and younger (7–8 years) and older (9–10 years) elementary school children studied four successively presented 3 x 3 arrays, each composed of the same 9 objects. The children were asked to memorize the locations of the objects that differed across the four arrays. Following presentation of each of the first three arrays, memory for the object locations of the respective array was tested (testing condition) or the array was re-presented for additional study (restudy condition). Results
revealed that testing Arrays 1 to 3 enhanced children’s object location memory for Array 4 relative to restudying. Moreover, children in the testing condition were less likely to confuse Array 4 locations with previous locations, suggesting that testing reduces the buildup of proactive interference. Both effects were found regardless of age. Thus, the current findings indicate that testing is an effective means to resolve proactive interference and, in this way, to enhance children’s learning and remembering of spatial information even before the time of school entry.
This article examines interweaving collective histories in different formerly colonized regions of the world: 1. Migratory movements from the territory of the former Ottoman Empire to the Americas, specifically to Brazil, and 2. transregional migration between different regions within China. On the basis of empirical data, we discuss sociological biographical research as an approach to analyzing migration and social mobility as transgenerational processes. In the case of Syrians in Brazil who have fled from the civil war, these processes are reflected in transnational family structures, transgenerational mandates, and knowledge transmission. In the case of domestic migration within China, the “mission” that families give their children is social advancement through education (e.g., Crabb 2010; Fong 2004). In the context of anti-Western discourses in China, it can be demonstrated that postcolonial discourses are functional in the effort to regain former international strength and national prosperity, and that discourses on “becoming a modern citizen” pervade family aspirations. The article is intended as a plea for i) taking a closer look at historical and contemporary South-South relations, and ii) situating current migration movements historically. It ties into global historical and sociological debates on “shared/common histories” and “intertwined histories."
Enhanced inductive power transmission (IPT) between coaxially arranged circular coils is introduced by time-modulation of the mutual inductance. This modulation is accomplished by coherent switching of the short circuit current induced in a third loop. An analytical circuit model supporting the design for future time-modulated IPT systems is derived. We demonstrate an increase in load rms-voltage by 13% (28% gain in power) compared to an unmodulated transfer on an experimental system operating at fundamental frequencies ranging from 40kHz to 500kHz.
BACKGROUND
Vertigo, dizziness or balance disorders (VDB) affect the mobility and participation of many older people and are also one of the most frequent reasons for visiting the general practitioner's (GP) practice due to multifactorial causes. Physiotherapy (PT) can be crucial for the complex care of people with VDB but is rarely prescribed by GPs. So we developed an evidence-based, multidisciplinary care pathway as a complex intervention following the UK Medical Research Council guideline, which was piloted and is now being evaluated for effectiveness, accompanied by a process evaluation.
METHOD
The care pathway of the multicentre cluster-RCT (MobilE-PHY2) included decision aids and training for PTs and GPs in the intervention group and optimised standard care in the control group. A mixed-methods process evaluation following Grant’s framework for designing process evaluations examined barriers, facilitating factors and mechanisms of impact in recruiting and reaching participants, implementing the intervention and the response of all participants. Therefore, a logic model was developed illustrating the relationship between the planned work to implement the intervention, the expected mechanism of impact (based on the behaviour change wheel as a change theory), the intended results (output, outcome and impact), and categories of possible influencing factors. The underlying assumption is that a behavioural change in PT and GP is a prerequisite for a change in patient behaviour, which can lead to improved mobility and participation (outcome of MobilE-PHY2). Guided interviews were conducted with patients before the intervention and after six months and with PTs and GPs after six months. Additionally, the training evaluations, completed decision aids and structural questionnaires will be analysed from June 2023.
RESULTS AND CONCLUSION
At one study site, a total of 37 patients, 17 PTs and nine GPs were included. Interviews were conducted with 16 patients, six PTs and GPs. In the intervention group, 12 PTs and 18 GPs completed decision aids, 13 PTs and two GPs completed evaluation forms, and eight PTs and four GPs completed structural data. The preliminary results of the process evaluation will be reported at the Congress. The results are intended to give indications for a broad implementation of the care pathway, including and promoting physiotherapy and therefore contributing to improved evidence-based healthcare for older people with VDB.
A Planar Magneto-Inductive Device with Modulated Mutual Inductance for Wireless Power Transmission
(2023)
A Magneto-Inductive Wave (MIW) structure for wireless power transfer (WPT) is proposed with switchable mutual inductance between neighbored coupling coils. Orthogonally placed switchable short circuit loops are added in order to modulate the wave propagation properties of the MIW structure without changing the resonance frequency. We derive an analytical model based on lumped circuit analysis for the MIW waveguide and successfully evaluate the theoretical findings by circuit modeling and field simulation. We demonstrate switchable, i.e. addressable, guided wireless power transfer along an experimental MIW structure at a resonance frequency of 20.5 MHz.
Many experts project generative AI will impact the types of competencies that are valued among working professionals. This is the first known academic study to explore the views of business practitioners about the impacts of generative AI on skill sets. This survey of 692 business practitioners showed that business practitioners widely use generative AI, with the most common uses involving research and ideation, drafting of business messages and reports, and summarizing and revising text. Business practitioners report that character-based traits such as integrity and soft skills will become more important. Implications for teaching business communication are discussed.
The bond between polymer fibers and the surrounding cementitious matrix is essential for the development of concrete reinforcement. The single fiber pull-out test (SFPT) is the standard characterization technique for testing the bond strength. However, the different phases of debonding cannot be distinguished by the SFPT. This study investigates the debonding of different polymer fibers from the surrounding cementitious matrix with a modified SFPT and proposes methods to change the SFPT setup to generate more valuable information on the debonding mechanism. The SFPT was equipped with linear variable differential transformers (LVDT), digital image correlation (DIC) and acoustic emission (AE) analysis. The results demonstrate that the modified SFPT allows a better understanding of the different phases of debonding during fiber pull-out. Furthermore, bond strength values calculated by different methods reveal that the chemical bond of the investigated polymers is not different as reported by previous studies. Deformation measurements performed using LVDTs and DIC are suitable measuring techniques to characterize the debonding mechanism in SFPT. A correlation between recorded AE and debonding phases was not found.
The necessity for resource-efficient manufacturing technologies requires new developments within the field of plastic processing. Lightweight design using wood fibers as sustainable reinforcement for thermoplastics might be one solution. The processing of wood fibers requires special attention to the applied thermal load. Even at low processing temperatures, the influence of the dwell time, temperature and shear force is critical to ensure the structural integrity of fibers. Therefore, this article compares different compounding rates for polypropylene with wood fibers and highlights their effects on the olfactory, visual and mechanical properties of the injection-molded part. The study compares one-step processing, using an injection-molding compounder (IMC), with two-step processing, using a twin-scew-extruder (TSE), a heating/cooling mixer (HCM) and an internal mixer (IM) with subsequent injection molding. Although the highest fiber length was achieved by using the IMC, the best mechanical properties were achieved by the HCM and IM. The measured oxidation induction time and volatile organic compound content indicate that the lowest amount of thermal damage occurred when using the HCM and IM. The advantage of one-time melting was evened out by the dwell time. The reinforcement of thermoplastics by wood fibers depends more strongly on the structural integrity of the fibers compared to their length and homogeneity
The study at hand presents a methodology to determine the utilization of public charging infrastructure by the proportion of effective charging time and idle time. The results of the study can be used by decision makers to better understand the usage behavior of public charging infrastructure and to align the provision of charging infrastructure with the behavior of users. The user behavior is analyzed using charging areas and scenario-based analysis of charging sessions. More than 300,000 charging sessions at AC and DC charging stations in the urban area of Munich in 2020 were recorded as the data basis for the study. The methodology takes the available vehicle models in the study area as well as the characteristic charging behavior of plug-in electric vehicles (PEV) with a decreasing charging power at high states of charge of the battery into account. The results show a high proportion of idle time at AC charging stations. The outcome of a correlation analysis additionally indicates a correlation between the share of idle time and the proportion of high-density urban living in the survey area.
This study presents an approach to collect and classify usage data of public charging infrastructure in order to predict usage based on socio-demographic data within a city. The approach comprises data acquisition and a two-step machine learning approach, classifying and predicting usage behavior. Data is acquired by gathering information on charging points from publicly available sources. The first machine learning step identifies four relevant usage patterns from the gathered data using an agglomerative clustering approach. The second step utilizes a Random Forest Classification to predict usage patterns from socio-demographic factors in a spatial context. This approach allows to predict usage behavior at locations for potential new charging points. Applying the presented approach to Munich, a large city in Germany, results confirm the adaptability in complex urban environments. Visualizing the spatial distribution of the predicted usage patterns shows the prevalence of different patterns throughout the city. The presented approach helps municipalities and charging infrastructure operators to identify areas with certain usage patterns and, hence different technical requirements, to optimize the charging infrastructure in order to help meeting the increasing demand of electric mobility.
Virtual team meetings are increasingly supported with advanced technology. This study investigates the extent to which Al-enabled speech technology can be useful for global virtual teams (GVT). A survey was conducted in GVTs in 2020 and 2021, when people's lives were primarily dominated by the pandemic. A transcription software was used to support the collaboration. A total of 530 survey responses were analyzed using a structured approach- qualitative content analysis. The data was structured using the SWOT framework that aimed at comprehensively answering the research question "To what extent is the use of Al-supported speech technology in GVTs useful?". Al-generated transcripts are helping to overcome language and time zone barriers in GVT. Yet, they also cause misunderstandings and impact openness of communication. Further results and implications for GVT are discussed.
Corrosion of steel reinforcements in concrete constructions is a big topic for the building industry. Polymeric materials are a possible alternative due to their ability to withstand corrosion. To replace steel reinforcements, fibers with high mechanical properties and a good bonding ability between fiber and concrete are needed. Today different approaches for concrete reinforcement by polymer fibers have been investigated. The bonding ability of the fibers can be increased by mechanical anchoring, e.g. crimped or embossed fibers, as well as by a chemical bonding between concrete and fiber surface. To realize the requirements of high mechanical properties and a good bonding behavior, a fiber that is drawn from a co-extruded filament shall be produced and tested. The filament owns an innovative core-shell-structure. The core maintains the fiber-stiffness and the tensile strength while the shell allows using another material to affect the bonding behavior of the fiber. This study shows the usage of fibers with differing shell materials to examine their influence on the mechanical properties of the fiber in total and the adhesion abilities to concrete. As core material, an unfilled polypropylene (PP) is used. The shell materials are varied using different polymers e.g. polypropylene or ethylene acrylic acid copolymer, as well as two PP based compounds filled with wood particles and calcium carbonate blended with a maleic anhydride based coupling agent. The mechanical properties of the fibers are tested by fiber tensile tests to compare the younǵs modulus and the tensile strength. The influence of the shell phase on the bonding ability to concrete is evaluated by the interfacial shear strength calculated from single fiber pull-out tests. Microscopy is used to interpret changes before and after pull-out. The results depict incredible positive effects and allow new insights in possible materials for fiber reinforced concrete constructions.
Generalized Ng–Kundu–Chan model of adaptive progressive Type-II censoring and related inference
(2024)
The model of adaptive progressive Type-II censoring introduced by Ng et al. (2009) (referred to as Ng–Kundu–Chan model) is extended to allow switching from a given initial censoring plan to any arbitrary given plan of the same length. In this generalized model, the joint distribution of the failure times and the corresponding likelihood function is derived. It is illustrated that the computation of maximum likelihood and Bayesian estimates are along the same lines as for standard progressive Type-II censoring. However, the distributional properties of the estimators will usually be different since the censoring plan actually applied in the (generalized) Ng–Kundu–Chan model is random. As already mentioned in Cramer and Iliopoulos (2010), we directly show that the normalized spacings are independent and identically exponentially distributed. However, it turns out that the spacings themselves are generally dependent with mixtures of exponential distributions as marginals. These results are used to study linear estimators. Finally, we propose an algorithm for generating random numbers in the generalized Ng–Kundu–Chan model and present some simulation results. The results obtained also provide new findings in the original Ng–Kundu–Chan model; the corresponding implications are highlighted.
We introduce a quick and accurate quasi-static magnetic field scanning technique by employing a progressive sampling method in an unconfined input space. The proposed
machine learning algorithm is tested against uniform sampling on a printed circuit board test structure. We prove allocation of multiple, separated regions with predefined tangential field strengths at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling detects contours of given field limits in less than 3% of the reference measurement time.
Driving forest machines on wet soils causes irreversible soil compaction, often associated with intensive rut formation and inaccessibility of wheeled forest machines for future forest operations. The German forestry equipment manufacturer FHS, Forsttechnik Handel & Service GmbH, engineered a forwarder, the Trac 81/11, equipped with conventional, well-proved bogie-axles embraced by a closed rubber track. At the center of the bogie-axle, four additional supportive rollers are placed to increase the load-carrying section between the tires of the bogie-axle. The study aimed to characterize the principle concept and the trafficability of the forwarder by analyzing the footprint area, the contact pressure, the rut formation on forest sites and the slippage during driving. Therefore, the effective contact area was measured on steel plates and rut formation was analyzed on a case study basis. Results showed that the supportive rollers increase the contact surface area by about 1/3. By this, a decrease of peak loads below the wheels and a more homogenous load distribution were observed. However, the contact surface area is still clearly divided into three parts; the area between the supportive rollers and the wheels does not take any load. Results of the rut formation were diverse: After 20 passes with 26,700 kg total mass, rut depth varied between 12.6 and 212.5 mm. Overall, the new undercarriage concept of FHS demonstrated a generally positive performance. The engineered forwarder contributes to reduce the environmental impact associated with log extraction.
Background Personalized mRNA vaccines are promising new therapeutic options for patients with cancer. Because mRNA vaccines are not yet approved for first-line therapy, the vaccines are presently applied to individuals that received prior therapies that can have immunocompromising effects. There is a need to address how prior treatments impact mRNA vaccine outcomes.
Method Therefore, we analyzed the response to BioNTech/Pfizer’s anti-SARS-CoV-2 mRNA vaccine in 237 oncology outpatients, which cover a broad spectrum of hematologic malignancies and solid tumors and a variety of treatments. Patients were stratified by the time interval between the last treatment and first vaccination and by the presence or absence of florid tumors and IgG titers and T cell responses were analyzed 14 days after the second vaccination.
Results Regardless of the last treatment time point, our data indicate that vaccination responses in patients with checkpoint inhibition were comparable to healthy controls. In contrast, patients after chemotherapy or cortisone therapy did not develop an immune response until 6 months after the last systemic therapy and patients after Cht-immune checkpoint inhibitor and tyrosine kinase inhibitor therapy only after 12 months.
Conclusion Accordingly, our data support that timing of mRNA-based therapy is critical and we suggest that at least a 6-months or 12-months waiting interval should be observed before mRNA vaccination in systemically treated patients.
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialised robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question, but also one of technology acceptance.
In this paper we analyse the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appear-ance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an im-portant factor that is not included in existing technology acceptance models. Finally, the discovery of a significant dis-crepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stake holder mapping is a valid tool to analyze the inter-dependences for acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further ana-lyze these issues.
In this research, we discuss the past and current trends in defining poverty to look at the topic from different perspectives and to provide an outline of future work that we aim to complete the picture on the qualitative and quantitative side. For this purpose, our focus here is to evaluate the diversity of definitions and to emphasize how important it is to combine subjective and objective approaches for practical policy analysis. As a first step of our future work, we also present the pilot study results to assess the results comparatively in the EU states and Türkiye.
Virtual meeting recordings have become a common part of virtual and hybrid workplace environments. Meeting recordings offer potential benefits (speedy transcript production, expedited information sharing, searchable information, inclusion of visual and tonal expressions) and drawbacks (difficulty discussing sensitive issues, employee privacy, limited off-the-record capabilities, and employee concerns over sharing recordings). Given this variance, policies for virtual meetings are a necessity. Managers can successfully implement a policy by co-creating policy preferences with employees in open-ended and nonjudgmental conversations that openly discuss potential benefits, drawbacks, and employee concerns. Topics such as when to record, when not to record, how to gain consent, and who will have administrative and sharing rights should be covered. Accessibility concerns, use or rejection of software features, for how long and where meeting recordings should be stored, and emerging issues such as use of virtual reality meetings and AI tools are areas of less urgency that may be part of the conversations. Managers should deliver policy preferences to a group of representatives from Human Resources, Information Technology, and the executive team to compose the policy, request a legal review, then introduce and implement it in the organization.
This study investigates the impact of generative AI systems like ChatGPT on semi-structured decision-making, specifically in evaluating undergraduate dissertations. We propose using Davis’ technology acceptance model (TAM) and Schulz von Thun’s four-sides communication model to understand human–AI interaction and necessary adaptations for acceptance in dissertation grading. Utilizing an inductive research design, we conducted ten interviews with respondents having varying levels of AI and management expertise, employing four escalating-consequence scenarios mirroring higher education dissertation grading. In all scenarios, the AI functioned as a sender, based on the four-sides model. Findings reveal that technology acceptance for human–AI interaction is adaptive but requires modifications, particularly regarding AI’s transparency. Testing the four-sides model showed support for three sides, with the appeal side receiving negative feedback for AI acceptance as a sender. Respondents struggled to accept the idea of AI, suggesting a grading decision through an appeal. Consequently, transparency about AI’s role emerged as vital. When AI supports instructors transparently, acceptance levels are higher. These results encourage further research on AI as a receiver and the impartiality of AI decision-making without instructor influence. This study emphasizes communication modes in learning-ecosystems, especially in semi-structured decision-making situations with AI as a sender, while highlighting the potential to enhance AI-based decision-making acceptance.
Exploring stakeholder perspectives: Enhancing robot acceptance for sustainable healthcare solutions
(2023)
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialized robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question but also one of technology acceptance. The answer to this question supports entrepreneurial opportunities to develop sustainable healthcare solutions.
In this paper, we analyze the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appearance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an important factor that is not included in existing technology acceptance models. Finally, the discovery of a significant discrepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved in caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stakeholder mapping is a valid tool to analyze the interdependencies for the acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further analyze these issues.
One major problem of a continuous process like plastic extrusion is their incapability to deal with non-local gas pressure. This is an inherent problem because a continuous process has an open end in the feeding port where pressure can escape. In this study a novel feeding system was developed to enable granulate feeding into gas pressurized processes inside a single- or twin-screw extruder. With this apparatus gas pressure can be applied inside the extrusion process. The apparatus separates the pressurized extruder from the dosing equipment that feeds the extruder. It keeps the pressure inside the system while continuously feeding new material into the process. A small-scale prototype was designed for proof-of concept. The small size of the prototype was able to handle small amounts of granulates of around 100 - 200 g/h. An applied gas pressure of 8 bar was achieved. In future optimizations, throughput can be increased and maximum applied gas pressure towards 15-20 bar.
Recently, the SQL standardization Committee published a specification for support of the concept called Row Pattern Recognition in SQL. That way, the focus for the members of the Committee turned back to a kernel issue of the language, after standardizing the storage and manipulation of data formats, such as XML and JSON. In this paper we discuss the specified features using several examples and show to what extent different relational database systems as well as Data Analytics tools have integrated them. At the end of the paper, we describe the main inaccuracies of the proposal and the ways how to solve them. From our point of view, the following should be modified in one of the future proposals of the standard in relation to this concept: (a) Naming of several pattern navigation operations is inappropriate and should be changed; (b) The concept of implicit definition for row pattern variables in DEFINE should be changed to explicit; (c) The set of existing functions should be extended.
The automotive industry is pushing power electronic packaging to higher operating and heatsink temperatures while still requiring very high power densities due to limited space. Currently, the power electronics that is implemented within the engine compartment of the vehicle must operate with heatsink temperatures of approximately 85/spl deg/C and this temperature can be expected to increase to 125/spl deg/C in the near future. The high temperature operation of the power electronic structure is fundamentally limited by the employed materials maximum temperatures. A packaging concept is introduced that describes a structure realisation that enables the materials to operate at high ambient temperatures without exceeding their individual maximum temperatures. This in turn allows the complete power electronic structure to operate at a higher system temperature. In this paper, the packaging concept that can be used to meet these difficult requirements of high temperature and high power-density is introduced, discussed and implemented. Two case studies are considered and implemented to illustrate the packaging concept.
For sustainable handling of wood and high material utilization, post-consumer wood has to be sorted by post-consumer wood categories in Germany. The non-destructive FD-FLIM method could improve the wood recycling process by automatic classification of waste wood into post-consumer wood classes. Thus, the phase-dependent fluorescence decay time of treated wood is analysed in this study to obtain the impact of the treatment on the fluorescence decay time. It is shown that treated and untreated wood can be differentiated using the fluorescence decay time, although the state-of-the-art theoretical fluorescence decay time differs from the experimentally determined fluorescence decay time.
We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling identifies contours of given field limits in less than 3% of the reference measurement time.
Reliability analysis of power MOSFET’s with the help of compact models and circuit simulation
(2002)