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Imaging methods by the means of optical sensors are applied in diverse scientific areas such as medical research and diagnostics, aerodynamics, environmental analysis, or marine research. After a general introduction to the field, this review is focused on works published between 2012 and 2022. The covered topics include planar sensors (optrodes), nanoprobes, and sensitive coatings. Advanced sensor materials combined with imaging technologies enable the visualization of parameters which exhibit no intrinsic color or fluorescence, such as oxygen, pH, CO2, H2O2, Ca2+, or temperature. The progress on the development of multiple sensors and methods for referenced signal read out is also highlighted, as is the recent progress in device design and application formats using model systems in the lab or methods for measurements’ in the field.
The Lightweight Directory Access Protocol (LDAP) is the standard technology to query information stored in directories. These directories can contain sensitive personal data such as usernames, email addresses, and passwords. LDAP is also used as a central, organization-wide storage of configuration data for other services. Hence, it is important to the security posture of many organizations, not least because it is also at the core of Microsoft’s Active Directory, and other identity management and authentication services.
We report on a large-scale security analysis of deployed LDAP servers on the Internet. We developed LanDscAPe, a scanning tool that analyzes security-relevant misconfigurations of LDAP servers and the security of their TLS configurations. Our Internet-wide analysis revealed more than 10k servers that appear susceptible to a range of threats, including insecure configurations, deprecated software with known vulnerabilities, and insecure TLS setups. 4.9k LDAP servers host personal data, and 1.8k even leak passwords. We document, classify, and discuss these and briefly describe our notification campaign to address these concerning issues.
This study investigates the impact of Large Language Model (LLM) parameters, specifically
temperature and top P, on Supply Chain Risk Detection (SCRD). With a heightened focus
on Supply Chain Risk Management (SCRM) using AI, the research employs a Design of
Experiments (DoE) approach. The results reveal optimal temperature values for valid
assessments in SCRD applications. The study emphasizes the importance of tailored LLM
parameter settings, contributing insights for future research and practical applications in
enhancing supply chain resilience. Suggestions for incorporating Response Surface
Methodology (RSM) and refining the process are proposed for further investigation.
What constitutes social work is a central question in theory building. If social work wants to be more than a model idea, we cannot answer this question without looking at social work practice.
The article presents ‘doing social work’ as an approach to theorising social work through
ethnographic research. In addition to the basic theoretical and methodological characteristics of the approach, we present four modes of doing social work, which have been developed based on a comparison of different ethnographic studies in different fields: deciding in uncertainty; playing with ambiguity; using categories of difference; and disciplining the everyday. In the following, the mode of playing with ambiguity will be singled out and presented in detail, as it has an important impact on doing relationship while doing social work. In the article, we will use ethnographic data and examples to show how actors actively deal with different roles without making this explicit.
This review paper provides an initial overview of the
state of the art of common corrosion protection methods
for offshore wind turbines. The functions of the
individual corrosion protection methods and their
interaction are explained. In addition, the specific corrosion
protection of different zones and components
of an offshore wind turbine will be discussed. Finally,
some information is given on current and possible
future developments in this subject area.
Objective:
We examined whether autonomic flexibility to experimentally presented stressors is reduced in somatic symptom disorder (SSD) as this would point to reduced vagal control as a proposed indicator of emotion regulation deficits.
Method:
In this experimental study, the influence of health-related and social stressors on subjective and physiological reactivity was investigated in 29 subjects with SSD without any medical condition SSD(mc−), 33 subjects with SSD with medical condition SSD(mc+) and 32 healthy controls at the age from 18 to 70 years. Self-report and physiological variables were measured before and after/during stressor exposure, using state ratings of symptom intensity, disability, tension and mood, heart rate (HR), and heart rate variability (HRV).
Results:
Overall, the tension increased and the mood worsened after exposure to stressors compared to pre-exposure. Compared to HC, the two SSD groups showed higher symptom intensity, disability, tension and worse mood. The SSD(mc−) group revealed higher HR than HC (p = .012, d = −0.77). Compared to pre-exposure, symptom impairment increased after social stressor exposure in SSD(mc−) (p < .001, d = 1.36). HRV-root mean square of successive differences (RMSSD) only decreased in HC during exposure (p = .003, d = −1.09), not in the SSD groups. The two SSD groups did not differ in their reactivity to stressors.
Conclusion:
HRV in SSD, seems to respond less flexibly to stressors, potentially reflecting overall physiological disturbance through reduced parasympathetic influence on HR. Stress reactivity in SSD(mc−) and SSD(mc+) do not seem to differ.
The construction and operation of hydropower plants
for energy generation is a major issue in sustainable
energy production. Nevertheless, hydropower plants
have a negative impact on fish populations. It is crucial
to understand the causes and consequences of fish
mortality in hydropower plants in order to find sustainable
solutions that reconcile the need for energy
with the conservation of aquatic ecosystems. This
article examines the fish protection measures that can
be implemented to reduce fish mortality and maintain
ecological balance. Based on the main literature reviewed,
this article mainly refers to Germany in terms
of studies carried out and hydropower plants.
Wind energy plays a major role among renewable
energies. Its expansion is therefore important in order
to achieve the climate targets. Repowering is an
important element in the expansion of wind energy.
On the one hand, it offers a solution for many wind
turbines in Germany that are no longer subsidised due
to their age. On the other hand, modern turbines are
significantly more powerful and enable more efficient
land utilisation. This article provides an overview of
the most important aspects of onshore repowering.
There is a lot to consider when repowering wind turbines.
The legal situation for repowering aims to
be improved through simplified authorisation procedures.
Even though efforts are being made by the
government, there is still room for improvement. The
repowering potential is also dependent on the various
distance regulations to residential buildings in
the federal states. These regulations might also be
improved in the future. Another aspect is the remuneration,
which is now closer to market developments
due to the market premium model. It is also subject
to greater competition as a result of the tendering
process. At the same time, interest rates and turbine
prices have risen, which creates economic challenges
for the operators of future wind farms. Last but not
least, repowering also depends on public acceptance.
This is also to be regulated by law in the future.
As Germany aims to increase its utilization of wind
power, the potential threat to bird populations due
to this expansion is a controversial issue. This paper
aims to collect data on the magnitude of bird strikes
on wind turbines, review existing protective measures
and explore innovative solutions. After a thorough
examination of the literature, it was concluded that
although the impact on bird populations is significant,
it may be overemphasized in popular debates. This
statement is not final as further research is necessary
to assess the impact of bird strikes and explore new
solutions. Comprehensive studies on this specific topic
in Germany are limited, which makes a thorough evaluation
challenging. While there are measures in place
to protect species that may be negatively impacted, it
is possible that these measures will not be adequate
for all of them. While several innovative methods
are under examination, progress in testing and implementation
is slow. Lastly, an information problem
was identified. Since the topic is highly politicized
and polarizing, it is crucial to provide the public with
accessible and reliable information on the discussed
themes. This is currently not the case due to a lack
of data and missing information campaigns.
This document presents a comparative analysis of
horizontal and vertical small wind turbines for urban
areas in three power classes up to 10 kW in different
categories. The main objective was to conduct a market
analysis to assess the marketability of these wind
energy systems. The aim was to make it easier for
potential customers to make a decision. However, due
to the limited availability of data, the project encountered
considerable difficulties. As a result, the study
became a comparative assessment, which led to results
that may not be readily transferable to urban environments,
slightly missing the original objective of the
study. The results underline the difficulties associated
with conducting a comprehensive market analysis in
this sector and highlight the need for an independent
series of tests under specific conditions. The paper
concludes with a plea for future research efforts to
adapt data collection methods to urban conditions in
order to improve the relevance and applicability of
such studies in practice.
This paper outlines the three main areas relevant
to dismantling: the rotor blades, hub and nacelle,
the tower and the foundation. The paper discusses
the dismantling procedures, including the removal of
the top structure, the tower and the foundation, and
evaluates various methods of dismantling the tower,
such as modular dismantling, collapse blasting, folding
blasting, wrecking ball demolition and hydraulic
ram demolition. The assessment of these methods
in practice and the potential challenges and considerations
for future dismantling, particularly as wind
turbine heights increase, are also addressed.
The upscaling of wind turbines has been increasing in
recent years and will continue to play a significant role
in the future, as it allows for the reduction of electricity
generation costs. Various challenges arise when it
comes to upscaling. This article summarizes the technical
challenges associated with upscaling wind turbines
and presenting their problem-solving approaches
and research trends based on other reviews. It was
found that the most frequently cited challenges are
related to individual components, such as rotor blades,
drive train, generator, tower, and noise impact.
For rotor blades, the challenges are increased flexibility,
more aeroelastic vibrations, increased wear,
interferences with radar and transportation difficulties.
Proposed solutions include the use of carbon-fiber
blades, prebending, novel paints, and for transportation,
segmented rotor blades and on-site manufacturing.
In the gearbox, torque increases, leading to
higher weight and susceptibility to errors. As a result,
the trend is moving towards gearless systems with
permanent magnet synchronous generators. Transportation
is the major issue with towers, which can
be resolved with on-site manufacturing. In terms of
noise emission, reducing aerodynamic noise plays the
most significant role.
The pursuit of Offshore Wind Energy (OWE), integral
to the German government’s ambitious renewable
energy goals raises concerns about the environmental
impact of noise emissions on marine life. This paper
delves into the theoretical background of Offshore
Wind Turbine (OWT) noise, exploring its various
phases from the survey to decommission. It examines
the types and causes of noise emissions, their effects
on marine wildlife and potential mitigation measures.
Highlighting the regulatory framework in Germany,
the paper emphasises the need for nuanced approaches
to balance renewable energy objectives with marine
ecosystem preservation.
The urge for personalisation and the rise of technological advancements
in the 21st century is pushing for more innovative marketing strategies. As such, this dissertation examines the impact of personality-tailored
campaigns (PTC) and how it affects purchasing decisions among
Generation Z, focusing on theoretical and practical implications.
A conceptual framework for the process of personality-tailored marketing has been developed to provide tangible value for businesses of
various industries in particular the fragrance, smartphone, and food
industry.
Toward a notation for modeling value driver trees: Classification development and research agenda
(2024)
This study investigates the role of individual differences in channel choice and switching behavior in a multichannel environment using latent class analysis on data from 1512 customers. Psychographic variables from five domains (risk attitudes, cognitive ability, motivation, personality, and decision-making style) serve as covariates for multichannel customer behavior. We identify six segments that differ significantly on six psychographic variables (readiness to take risks, need for cognition, autotelic and instrumental need for touch, and rational and intuitive decision-making styles). The results advance the theory-building of multichannel customer behavior and present insights for proactively managing customer journeys of distinct segments.
Consequences of the consistent exact solution of Einstein{Cartan equation on the time dependence of Hubble parameter are discussed. The torsion leads to a space and time-dependent expansion parameter which results into nontrivial windows of Hubble parameter between diverging behavior.
Only one window shows a period of decreasing followed by increasing time dependence. Provided a known cosmological constant and the present values of Hubble and deceleration parameter this changing time can be given in the past as well as the ending time of the windows or universe. The comparison with the present experimental data allows to determine all parameters of the model.
Large-scale spatial periodic structures appear. From the metric with torsion outside matter, it is seen that torsion can feign dark matter.
This study identifies supply options for sustainable urban energy systems, which are robust to external system changes. A multi-criteria optimization model is used to minimize greenhouse gas (GHG) emissions and financial costs of a reference system. Sensitivity analyses examine the impact of changing boundary conditions related to GHG emissions, energy prices, energy demands, and population density. Options that align with both financial and emission reduction and are robust to system changes are called “no-regret” options. Options sensitive to system changes are labeled as “potential-risk” options.
There is a conflict between minimizing GHG emissions and financial costs. In the reference case, the emission-optimized scenario enables a reduction of GHG emissions (-93%), but involves higher costs (+160%) compared to the financially-optimized scenario.
No-regret options include photovoltaic systems, decentralized heat pumps, thermal storages, electricity exchange between sub-systems and with higher-level systems, and reducing energy demands through building insulation, behavioral changes, or the decrease of living space per inhabitant. Potential-risk options include solar thermal systems, natural gas technologies, high-capacity battery storages, and hydrogen for building energy supply.
When energy prices rise, financially-optimized systems approach the least-emission system design. The maximum profitability of natural gas technologies was already reached before the 2022 European energy crisis.
Wind turbine structures take a major role in the
modern conversion to renewable energy sources and
contribute to the creation of a greener world. In recent
years, the development and installation of wind
turbines have seen rapid growth. However, with the
increasing capacity and size of wind farms worldwide,
there are growing concerns about the safety and reliability
of these installations. Therefore, structural
health monitoring and the detection of damage to
wind turbines have gained considerable importance in
research. Wind turbine blades are particularly susceptible
to various types of damage due to environmental
influences. This article provides an overview of signal
responses, sensors used and non-destructive testing
techniques in the field of damage detection on wind
turbine blades. The intention of the article is to give
an insight into the possibilities of structural health
monitoring and at the same time to point out unsolved
problems in this field.
Meanwhile, renewable energy sources such as hydropower, solar and wind energy and biomass are increasingly being used to reduce dependence on fossil fuels and thus counteract the ongoing global warming. However, these are also associated with environmental impacts. To that effect, this article takes a closer look at tidal power plants, which are classified as hydroelectric power plants, by conducting a systematic literature review. The results show that the strength and form of the environmental impact depends on the specific location and type of plant. Tidal power plants have an impact on the habitats of marine animals and thus influence their behavior and population. In addition, the operation of tidal power plants changes the sediment distribution, causes a reduction in current velocities and a change in current direction in the surrounding area and leads to a change in wave height. The construction of the power plants is associated with noise, which primarily causes changes in the behavior of some species. Furthermore, the electromagnetic fields generated can also affect marine life. In order to assess the environmental impact of tidal power plants in comparison to other renewable energies, further studies should focus on the environmental impact of the different technologies in relation to the energy yield.
The preservation of water bodies continuity is fundamental
for aquatic communities, particularly for fish
populations. Various structures impede watercourse
continuity, impacting fish migration and habitat distribution.
Conventional fish passages often fall short
in diverse scenarios, prompting the development of
specialized solutions. This article proposes a criteria
catalog for these special fish passage solutions based
on DWA leaflet DWA-A 509. It discusses the need
for these solutions, presents a selection of specialized
options, and outlines criteria from DWA-M 509, construction
guidelines, and economic perspectives. It
scrutinizes criteria ranging from target fish species to
cost considerations. Three examples, including the
Runserau fish lift, the bristle ramp fish lock, and the
Fishcon sluice, illustrate these specialized solutions,
their functionalities, advantages, and drawbacks. Additionally,
the article compiles criteria from industry
standards and guidelines into a comprehensive evaluation
catalog. The criteria, when applied, assist in the
selection of suitable fish passage solutions based on
specific site conditions and fish species requirements.
This holistic approach aims to optimize fishway selection,
fostering the ecological sustainability of watercourses.
However, this catalog remains dynamic
and open to expansion with evolving research and
practical application, urging further exploration and
validation of these criteria through diverse case studies
and technological advancements in the field.
This article discusses the use of artificial intelligence
in the wind energy industry, particularly in addressing
challenges and optimizing the expansion of renewable
energies in Germany. It highlights the application
of artificial intelligence in wind forecasts and yield
predictions, bird detection, wind turbine and farm
design, condition monitoring, and predictive maintenance.
Additionally, it introduces the “WindGISKI”
research project, which aims to use artificial intelligence
to identify new areas for wind turbines. The
project utilizes a neural network to analyze and predict
flight routes, potentially reducing bird mortality.
The document also emphasizes the potential broader
applications of “WindGISKI” in other fields of activity,
such as land use planning and city development.
Overall, it underscores the significant role of artificial
intelligence in addressing challenges in wind energy
and outlines the potential for artificial intelligence
to drive the expansion of renewable energies while
addressing key obstacles.
The Educational Journal of Renewable Energy Short Reviews (EduJRESR, formally published as ‘EGU Journal of Renewable Energy Short Reviews’) is a teaching project rather than a regular scientific journal.
To publish in this journal, it is a premise to take part in the master course wind power, hydro power and biomass usage at the department of Energy, Building Services and Environmental Engineering of the Münster University of Applied Sciences.
Students receive an equivalent of 2.5 credit points (European Credit Transfer and Accumulation System – ECTS) for their engagement in the course and for publishing a short review article of at most 3 000 words in this periodical. The publication process closely mimics the typical publication procedure of a regular journal.
The peer-review process, however, is conducted within the group of course-participants.
Although being just an exercise, we think that publishing the outcome of this course in a citable manner is not only promoting the motivation of our students, but may also be a helpful source of introductory information for researchers and practitioners in the field of renewable energies. We encourage students to write their articles in English, but this is not mandatory. The reader will thus find a few articles in German language.
To further encourage students practicing English writing, perfect grammar is not part of the assessment.
We especially thank our students for working with LATEX on Overleaf, although LATEX is new to some of them. In this way, the editorial workload was reduced to a minimum. We also thank our students for sharing their work under the creative commons attribution licence (CC-BY). We appreciate their contribution to scientific information, being available to every person of the world, almost without barriers. We also thank the corresponding authors and publishers of the cited work, for granting permission.
The annual wastewater flow that is treated by public
wastewater treatment plants in Germany amounts
to approx. 10 ∗ 10^9 m3/a and forms an ”artificial” hydropower
potential that can be used for energy generation
or recovery. In the context of this paper, energy
recovery in the outlet of wastewater treatment plants
is examined using the specific example of the water
wheel at the Warendorf central wastewater treatment
plant. The ”artificial” hydropower potential can be
roughly estimated at up to 20 to 105 GWh/a , whereby
this is largely dependent on the hydraulic gradient.
The strong variance results, among other things, from
the findings of the water wheel operation in Warendorf.
The decisive aspect here is the differential factor,
which describes the deviation between the theoretical
and actual energy yield of the water wheel. The
factor includes maintenance work, downtimes and insufficient
inflows, which are associated with a loss of
output. In the case study, the annual energy recovery
amounts to approx. 2 % of the annual electricity consumption
of the wastewater treatment plant and can
be estimated to 23,500 kWh (2022). In the context
of the economic analysis, it can be seen that despite
the ”low” yield, economic operation is possible if the
system is viewed as a long-term investment - payback
period of the example is approx. 14,5 years. The
27-year operation (1996 - 2023) of the water wheel
at the Warendorf central wastewater treatment plant
confirms this and important findings on successful
practical operation can be shown in the context of
this paper.
Potential and risks of water reuse in Brandenburg (Germany) – an interdisciplinary case study
(2024)
For Brandenburg, a region in Germany with increasing water shortage and drought events, water reuse can counteract competition scenarios between drinking water supply, agricultural irrigation, and industrial use. Centralized and decentralized sources for reclaimed water are found to potentially substitute 245 or 28% of irrigation water, respectively, in agriculture production in Brandenburg. For such a reuse scenario, the
fate of organic micropollutants is examined for diatrizoate (DZA) and carbamazepine (CBZ). Retention in local sandy soil and transfer into roots and leaves of arugula are analyzed in lysimeter studies and greenhouse pot experiments. Vertical transport was found for DZA and accumulation in or on arugula roots with a root concentration factor of 1,925+34% but a low bioconcentration factor due to intrinsic molecule properties. CBZ was not found to be mobile in the sandy soil but accumulates in arugula roots and leaves by factors of 70+7% and 155+12%, respectively. Further research on potential plant uptake and groundwater enrichment for more substances is highly recommended as well as tertiary wastewater treatment prior to water reuse.
Wastewater generation model to predict impacts of urine separation on wastewater treatment plants
(2024)
Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series.
Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.
Family firm performance through transformational CEO leadership and familiness-related team forces
(2024)
Purpose. The purpose of this study is to test the role of familiness-related team forces induced by the CEO of family firms. In particular, we report on the effects of the transformational leadership style of CEOs on their respective top-management team (TMT) and firm performance when viewed through a familiness lens.
Design/methodology/approach. Survey measures were taken from a snowballed
sample of 72 CEOs of German family firms as well as from 245 members of their TMTs. We tested the aggregated firm-level data with objective performance indicators of the firms they led.
Findings. Support was obtained for the three hypothesized team-force mediations and the four-path mediation model. The relationship between CEO’s transformational style and
high family-firm performance is found to be serially mediated by TMT cohesion, behavioral integration and efficacy. Together, these three types of collective forces are assumed to be the
familiness effect of a family-member CEO with a transformational leadership style.
Originality. With our model we quantitatively tested familiness-type forces vis-à-vis firm performance. Theoretical and practical implications of these findings are discussed.
An important, often overlooked group of workers that HR managers have trouble reaching are those intentionally disconnected from personal digital devices. That is, workers in manufacturing facilities, distribution centers, secure areas, or locations where employers ban workers from bringing their own devices. We explore the engagement problem for these intentionally disconnected workers. We outline a disruptive HR strategy in these work contexts. We then focus on implementation, testing a simple digital platform prototype that can serve as an entry for existing, disruptive HR management engagement tools (e.g. chatbots, HR analytics) in these settings. Our exploratory findings suggest engagement is a problem for these workers and these simple tools can be an effective strategy to help HR managers improve engagement. We conclude that simple digital solutions aimed at engaging this underserved segment of the workforce can have disruptive yet positive effects for workers, HR managers and shareholders.
Supply chains often match the supply of labour to uncertain demand by using precarious workprecarious workers. This increases flexibility and lowers costs for the supply chain by shifting risk to the workers and costs to society. Supply chains are maximizing profits, often literally, on the backs of their workers by creating serious negative externalities for society. We address this issue using a powerpower perspective because powerpower is asymmetrically oriented against workers in many supply chain contexts. This allows us to identify examples of how to reverse this trend and shift powerpower back to workers. The goal is to get to where stakeholders understand the costs and limited benefits of precarity, where we can separate the notion of flexibility from low costs, and where through a combination of incentives, policy, social norms of ethical behaviour, and consumer action, we can get to a better place than where we are now.
When simulating and optimizing urban energy systems, the focus is usually on minimizing financial costs or greenhouse gas (GHG) emissions. As energy systems transition towards a growing share of renewable energy sources and technological complexity, environmental impacts that affect more than just GHG emissions, such as resource extractions, water and land use impacts or impacts on human health, are becoming increasingly relevant.
To address this gap, this thesis introduces an automated coupling procedure for energy system modeling (ESM) and life cycle assessment (LCA). The implementation includes general recommendations and a practical coupling of the Open Energy Modelling Framework (oemof) based Spreadsheet Energy System Model Generator (SESMG) with a suitable LCA software.
The LCA procedure involves goal and scope definition, inventory analysis, impact assessment, and interpretation. To adapt these steps to different energy system models, the LCA should be attributional, process-based and territorial. Further, the openLCA software by Green-Delta serves as a suitable soft-linking tool. The main challenge of the coupling procedure is the inventory analysis. Data collection faces limitations, reasoned by the commercialization and high maintenance efforts in open-source databases. After evaluating free databases, the Prozessorientierte Basisdaten für Umweltmanagement-Instrumente (ProBas) database of the Umweltbundesamt emerged as the most suitable choice for the coupling. However, also this database lacks traceability of datasets or compatibility with a comprehensive impact assessment.
A generalized framework for the LCA application of energy systems was developed. The framework is based on an ex-post LCA assessment that considers the combination of the two approaches within every step of the procedure. Main considerations of this framework include automatic calculations of the inventory analysis and the impact assessment for different energy technologies, as well as calculations summed up for all technologies of energy system scenarios. Further, technology mapping and data harmonization are essential considerations for the automatic coupling and double counting of impacts needs to be avoided.
Subsequently, the framework is realized with the adaption of the SESMG. Its database-independent realization allows compatibility with different databases in openLCA. For the selected ProBas database, the tool can be used with different available energy technologies. The use of unit processes is encouraged for data harmonization. Result interpretation of the LCA (in general or with the SESMG) should not solely focus on the absolute values of the impact categories, but rather on the comparative strengths among scenarios and technologies.
The successful application to a reference single-family building using the ProBas database revealed varied environmental impacts, in relation with a higher reduction in GHG emissions, with an increase of 11 % in terrestrial acidification impacts in the emission-optimized scenario. These findings emphasize a more comprehensive perspective on environmental impacts and provide a valuable validation of the developed methodology.
Future research should include the improvement of data harmonization, the inclusion of more datasets for a more customized analysis of energy systems and more applications. The coupled approach offers a promising avenue for gaining deeper insights into optimizing urban energy systems.
This study presents a comprehensive evaluation of force sensors manufactured through conventional CNC machining, laser powder bed fusion (LPBF), and material extrusion (MEX) 3D printing methods. The study utilized a combination of finite element method (FEM) simulations, functional testing, durability assessments, and ultimate strength testing in order to assess the viability of additive manufacturing for sensing technology applications. The FEM simulations provided a preliminary framework for predictive analysis, closely aligning with experimental outcomes for LPBF and conventionally manufactured sensors. Nevertheless, discrepancies were observed in the performance of MEX-printed sensors during ultimate strength testing, necessitating the implementation of more comprehensive modeling approaches that take into account the distinctive material characteristics and failure mechanisms. Functional testing confirmed the operational capability of all sensors, thereby demonstrating their suitability for the intended application. Moreover, all sensors exhibited resilience during 50,000 cycles of cyclic testing, indicating reliability, durability, and satisfactory fatigue life performance. Notably, sensors produced via LPBF exhibited a significant increase in strength, nearly three times that of conventionally manufactured sensors. These findings suggest the potential for innovative sensor design and the expansion of their use into higher-loaded applications. Overall, while both LPBF and conventional methods demonstrated reliability and closely matched simulation predictions, further research is necessary to refine modeling approaches for MEX-printed sensors and fully unlock their potential in sensing technology applications. These findings indicate that additive manufacturing of metals may be a viable alternative for the fabrication of biomedical sensors.
AI-based chatbots as enabler for efficient external knowledge management in public administration
(2024)
This study addresses the pressing issue of staff shortages in German public administrations through the lens of digitalization, focusing on the potential of AI-based chatbots to solve this problem by replacing human labour. Employing a Design Science Research Process (DSRP) methodology, the research synthesizes theoretical foundations and regulatory frameworks to develop a robust chatbot concept. The artifact presented is a comprehensive architectural framework integrating user-centric design, linguistic processing, and regulatory compliance. The proposed artifact navigates complex federal structures and diverse IT infrastructures, promoting accessibility and inclusivity. Implications suggest enhanced efficiency and accessibility in public service delivery for potentially increasing citizen satisfaction and decreasing employee workload. The study underscores the importance of legal compliance and the evolving regulatory landscape in AI deployment. Future research will involve prototyping and evaluating the artifact's performance and applicability throughout the course of the DSRP, thus contributing to the advancement of digital transformation in public administrations.
Oxidative stress plays a critical role in the pathogenesis of chronic diseases. Therefore, improvement of oxidative stress status through lifestyle intervention can play a vital role in preventing and treating chronic diseases. This systematic review aims to provide an overview of articles published in the last decade examining the association between lifestyle intervention and oxidative stress biomarkers in the context of non-communicable diseases. The electronic databases PubMed and Web of Science were searched for relevant studies, following the PRISMA (Preferred Reporting of Systematic Reviews and Meta-Analyses) guidelines. This systematic review focused on the four important oxidative stress biomarkers; glutathione (GSH), superoxide dismutase (SOD), catalase, and malondialdehyde. 671 articles were identified, of which nine met the inclusion criteria. A trend emerged, showing that lifestyle modifications that focus on diet and physical health can improve oxidative stress in the form of an increase in superoxide dismutase and CAT levels and a decrease in Malondialdehyde levels in participants with non-communicable diseases (NCDs), GSH levels were not affected. However, the results are difficult to compare because of the heterogeneity of the methods of the biomarkers studied. Our review indicates that oxidative stress can be influenced by lifestyle modifications and may be an effective tool for the prevention and management of non-communicable diseases. This review also elucidated the importance of analyzing multiple oxidative stress biomarkers to evaluate oxidative stress, it further highlights the need to conduct long-term lifestyle intervention studies on oxidative stress biomarkers to understand the connection between oxidative stress biomarkers, NCDs and Lifestyle intervention.
In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces “customer journey mining”. Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.
Against the setting of an increasing need for innovation and low margins, companies in the logistics
sector are facing highly competitive pressure. One field with high potential for optimization lies within
damage quotas. The use of big data analytics or data mining represents a promising approach to face
this challenge. However, within supply chain management, data mining is hardly being researched on
regarding damage quotas and thus not being utilized to its full possible extend. At the current time it
seems to predominantly be used for route and utilization optimization while the analysis of delivery
damages is hardly considered.
The aim of this research is therefore to showcase an initial approach for data mining in logistics to predict
delivery damage probabilities and to validate this by means of a multiple case study research. To create
a sound basis for evaluation, the groundwork is laid out based on CRISP-DM by the analysis of reference
data (German road-cargo market).
As a central result it is noted that data mining can systematically be used to help reducing the damages
by forecasting the probabilities of damages occurring during transport in dependence of different factors.
The approach can be utilized across different markets as long as sufficient data tracking delivery
damages is being collected within a company. Challenges arise in the field of air- and sea-freight.
Wastewater Generation Model to Predict Impacts of Urine Separation on Wastewater Treatment Plants
(2023)
Wastewater treatment plants are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. Separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central wastewater treatment plant. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study introduces a modelling framework which allows to determine the influence of targeted urine separation on the operation and emissions of central wastewater treatment plants. The framework includes an adapted stochastic wastewater generation model, the Stormwater Management Model, and Activated Sludge Model No. 3 with Bio-P module (SIMBA#). The entire application is embedded in the R programming language. The model is validated by an extensive sampling and measurement campaign. Preliminary results based on observed and simulated wastewater generation and transport for a catchment area of 436 residents indicate the suitability of the model for wastewater generation and transport modelling, but also show further need for calibration.
A novel approach for ventilation systems is a periodically varying supply air flow rate, the so-called unsteady mode of operation. So far, useful effects of this unsteady operating mode have been observed, but the effect mechanisms are still unknown. In this manuscript, simulations using the recently proposed k-ω-ζ - f model implemented in a sensitized RANS computational framework for a cuboid room with swirl diffusers are compared and validated with PIV measurements.
The use of computational modeling and simulation (CMS) as a tool for gaining insight into the technical performance and safety of medical devices has emerged continuously over the past years. However, to rely on information and decisions derived from model predictions, it is essential to establish model credibility for the specific context of use. Limited regulatory requirements and lack of consensus on the level of verification and validation activities required result in rare use of CMS as a source of evidence in the medical device approval process. The American Society of Mechanical Engineers (ASME) developed a risk-informed framework to establish appropriate credibility requirements of a computational model: the ASME V&V 40?2018 standard. This paper aims to outline the concepts of this standard and to demonstrate its application using an example from the orthotics field. The necessary steps to establish model credibility for a custom?made 3D printed wrist hand orthosis (WHO) are presented. It is shown that the credibility requirements of each verification and validation activity depend on model risk by applying two different contexts of use to the same computational model.
A communication over an Internet Protocol (IP) based network fails if an endpoint sends packets that are too big to reach their destination and if the sender is unable to detect that. The node on the path that drops these packets should respond with a Packet Too Big (PTB) message. However, multiple scenarios exist in which the sender will not receive a PTB message. Even if it does, it refrains from using the information in case it suspects that a potential attacker forged the message. In particular, we are not aware of any implementation of the secure transport protocol QUIC (e.g., used by HTTP/3) that processes PTB messages. In this paper, we present a novel parameterizable PTB detection algorithm for reliable transport protocols that does not depend on PTB messages. We further describe how to integrate our algorithm into QUIC, present results from an evaluation using the algorithm within a QUIC simulation model and, based on these results, suggest concrete parameter values.
The paper describes the design, facilitation and outcomes of a series of workshops with faculty, staff and students from a teacher education program specialized in vocational education and training (VET). We analyze and reflect upon the facilitation techniques, discussion and participation results, and evaluation of the workshop series. Practitioners and researchers alike will find this article a valuable source for contemplating the effectiveness of design thinking, making and serious play in teacher education. While our case study is situated in the particular context of preparing future vocational teachers within the German VET system, the resulting concepts are applicable to other teacher education programs
Numerical investigation of a transonic dense gas flow over an idealized blade vane configuration
(2023)
This review paper presents a short overview of current power system modelling tools especially used for analysing energy and electricity systems for the supply and demand sector. The main focus of this review lies on open source tools and models which are written and used in the programming language “Python”. The modelling tools are represented in a comprehensive table with key information. Five modelling tools with an open source license can be filtered out. The modelling tool PyPSA can be considered as a high performing tool especially as the gap between power system analysis tool (PSAT) and energy system modelling tool.
Background
Chronic low-grade inflammation is associated with an increased risk of chronic disease and mortality. The objective of the study was to test the effect of a healthy lifestyle intervention on biomarkers of inflammation (among other risk markers).
Methods
We conducted a non-randomized controlled trial with mostly middle-aged and elderly participants from the general population in rural northwest Germany (intervention: n = 114; control: n = 87). The intervention consisted of a 1-year lifestyle programme focusing on diet (largely plant-based; strongest emphasis), physical activity, stress management, and social support. High-sensitivity C-reactive protein (hs-CRP) was assessed at baseline, 10 weeks, 6 months, and 1 year. Homocysteine (Hcy) was assessed at baseline, 10 weeks, and 1 year. Adiponectin (Apn) was assessed at baseline and 10 weeks. An exploratory analysis of these inflammatory markers assessing the between-group differences with ANCOVA was conducted.
Results
The 1-year trajectory of hs-CRP was significantly lower in the intervention group compared to control (between-group difference: -0.8 (95% CI -1.2, -0.3) mg/l; p = 0.001; adjusted for baseline). The 1-year trajectory of Hcy was non-significantly higher in the intervention compared to control (between-group difference: 0.2 (95% CI -0.3, 0.7) µmol/l; p = 0.439; adjusted for baseline). From baseline to 10 weeks, Apn decreased significantly more in the intervention group compared to control (between-group difference: -1.6 (95% CI -2.7, -0.5) µg/ml; p = 0.004; adjusted for baseline).
Conclusions
Our study shows that healthy lifestyle changes can lower hs-CRP and Apn levels and are unlikely to significantly affect Hcy levels within 1 year.
Trial registration
German Clinical Trials Register (DRKS; reference: DRKS00018775, registered 12 Sept 2019; retrospectively registered; www.drks.de).
Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in nano- or micro-diamonds is a promising technology for precise magnetic-field sensors. Here, we propose a new, low-cost and stand-alone sensor setup that employs machine learning on an embedded device, so-called edge machine learning. We train an artificial neural network with data acquired from a continuous-wave ODMR setup and subsequently use this pre-trained network on the sensor device to deduce the magnitude of the magnetic field from recorded ODMR spectra. In our proposed sensor setup, a low-cost and low-power ESP32 microcontroller development board is employed to control data recording and perform inference of the network. In a proof-of-concept study, we show that the setup is capable of measuring magnetic fields with high precision and has the potential to enable robust and accessible sensor applications with a wide measuring range.
Introduction
Hip and knee osteoarthritis are associated with functional limitations, pain and restrictions in quality of life and the ability to work. Furthermore, with growing prevalence, osteoarthritis is increasingly causing (in)direct costs. Guidelines recommend exercise therapy and education as primary treatment strategies. Available options for treatment based on physical activity promotion and lifestyle change are often insufficiently provided and used. In addition, the quality of current exercise programmes often does not meet the changing care needs of older people with comorbidities and exercise adherence is a challenge beyond personal physiotherapy. The main objective of this study is to investigate the short- and long-term (cost-)effectiveness of the SmArt-E programme in people with hip and/or knee osteoarthritis in terms of pain and physical functioning compared to usual care.
Methods
This study is designed as a multicentre randomized controlled trial with a target sample size of 330 patients. The intervention is based on the e-Exercise intervention from the Netherlands, consists of a training and education programme and is conducted as a blended care intervention over 12 months. We use an app to support independent training and the development of self-management skills. The primary and secondary hypotheses are that participants in the SmArt-E intervention will have less pain (numerical rating scale) and better physical functioning (Hip Disability and Osteoarthritis Outcome Score, Knee Injury and Osteoarthritis Outcome Score) compared to participants in the usual care group after 12 and 3 months. Other secondary outcomes are based on domains of the Osteoarthritis Research Society International (OARSI). The study will be accompanied by a process evaluation.
Discussion
After a positive evaluation, SmArt-E can be offered in usual care, flexibly addressing different care situations. The desired sustainability and the support of the participants’ behavioural change are initiated via the app through audio-visual contact with their physiotherapists. Furthermore, the app supports the repetition and consolidation of learned training and educational content. For people with osteoarthritis, the new form of care with proven effectiveness can lead to a reduction in underuse and misuse of care as well as contribute to a reduction in (in)direct costs.
Trial registration
German Clinical Trials Register, DRKS00028477. Registered on August 10, 2022.
Pathological Skin Picking (PSP) is an excessive behavior which characterizes Skin Picking Disorder. Individuals repeatedly pick their skin and cause skin lesions, but are unable to control the behavior, which can cause severe distress. Visible self-inflicted skin lesions can additionally affect individuals with PSP due to emerging appearance-related concerns. However, these concerns and their role in PSP have hardly been studied, especially not in comparison with individuals with dermatological conditions and skin-healthy controls.
The present cross-sectional study (n=453, 83.9% female, 15.9% male, 0.2% diverse) aimed at analyzing appearance-related concerns and mental health outcomes between four groups: Individuals with PSP and dermatological conditions (SP/DC; n=83), PSP without dermatological conditions (SP; n=56), dermatological conditions without PSP (DC; n=176) and skin-healthy controls (SH, n=138). We compared questionnaire data on dysmorphic concerns, appearance-based rejection sensitivity, and body dysmorphic symptoms, as well as PSP-symptoms and mental health outcomes (depression, anxiety, and self-esteem) between groups.
The analyses showed a significant multivariate group effect in the appearance-related variables, F(6, 896)=19.92, Wilks’ Λ=0.78, p<.001, and mental health outcomes, F(6, 896)=16.24, Wilks’ Λ=0.81, p<.001. The SP/DC group had the strongest appearance-related concerns and mental health impairments, followed by the SP group, the DC group and the SH group. The SP/DC group and SP group only differed significantly with regard to dysmorphic concerns, but not in other variables. The DC group was less affected but still showed higher dysmorphic concerns and mental health impairments than skin-healthy controls. In contrast to the PSP groups, the other two groups did not exceed clinically relevant cut-off scores.
The present study shows that individuals with PSP exhibit strong appearance-related concerns, regardless of the presence or absence of underlying or comorbid dermatological conditions. These findings shed new light on the importance of appearance-related concerns in skin picking disorder and the role of PSP as a potentially overlooked risk factor in dermatological patients. Therefore, appearance-related concerns should be explicitly addressed in dermatological and psychotherapeutic settings. Future studies should also include longitudinal and experimental analyses to more clearly classify the role of appearance-related concerns in the etiology of PSP and skin picking disorder.
Local and regional energy systems are becoming increasingly entangled. Therefore, models for optimizing these energy systems are becoming more and more complex and the required computing resources (run-time and random access memory usage) are increasing rapidly. The computational requirements can basically be reduced solver-based (mathematical optimization of the solving process) or model-based (simplification of the real-world problem in the model). This paper deals with identifying how the required computational requirements for solving optimization models of multi-energy systems with high spatial resolution change with increasing model complexity and which model-based approaches enable to reduce the requirements with the lowest possible model deviations. A total of 12 temporal model reductions (reduction of the number of modeled time steps), nine techno-spatial model reductions (reduction of possible solutions), and five combined reduction schemes were theoretically analyzed and practically applied to a test case. The improvement in reducing the usage of computational resources and the impact on the quality of the results were quantified by comparing the results with a non-simplified reference case. The results show, that the run-time to solve a model increases quadratically and memory usage increases linearly with increasing model complexity. The application of various model adaption methods have enabled a reduction of the run-time by over 99% and the memory usage by up to 88%. At the same time, however, some of the methods led to significant deviations of the model results. Other methods require a profound prior knowledge and understanding of the investigated energy systems to be applied. In order to reduce the run-time and memory requirements for investment optimization, while maintaining good quality results, we recommend the application of (1) a pre-model that is used to (1a) perform technological pre-selection and (1b) define reasonable technological boundaries, (2) spatial sub-modeling along network nodes, and 3) temporal simplification by only modeling every nth day (temporal slicing), where at least 20% of the original time steps are modeled. Further simplifications such as spatial clustering or larger temporal simplification can further reduce the computational effort, but also result in significant model deviations.
This article explores educational media pedagogies that are predominantly non-digital, but nonetheless timely and influential. Design Thinking, Making, and Serious Play are three distinct yet interrelated approaches to problem-solving, resilience and innovation that have gained increased traction in education over the past decade. We explore the similarities and differences between these playful, experiental pedagogies and provide an overview of how these approaches can be integrated effectively into education settings. Finally, we provide transferable examples, including evaluation results, from a weeklong workshop series at Muenster University of Applied Sciences conducted in Spring 2022. The article serves as a theoretically informed practical guide for educators and practitioners seeking to select, implement and evaluate playful pedagogies. It contributes to the understanding of underlying principles, characteristics, potential impact and limitations.
This research case study presents a novel way to study the development and growth of a multi-sided disruptive platform built on digital technologies. The corresponding business model unfolds industry-changing dynamics eventually changing competition logic in established markets. Despite the appeal of those models, developing and managing such a multi-sided disruptive platform is challenging because multiple platform sides need to be strategically aligned to develop along a disruptive path. Hence, scholars and practitioners are increasingly debating about the dynamics arising in the development and growth of such platforms. The focal case study discusses a research project which contributes to those debates:
This case study discusses how we used topic modeling and qualitative content analysis to make sense of a large amount of historical data from and about multiple platform sides to understand the strategic management and alignment mechanisms that unfolded over time. We discuss how we studied an entrant that was spun off from an established catalog retailer and is steering a multi-sided disruptive platform in the German fashion retail industry. We present how we faced the challenges of collecting data from multiple platform sides and how we used topic modeling to overcome data asphyxiation (i.e. difficulties in making sense of an overwhelming amount of qualitative data). Readers of this case study are equipped with practical insights about a) studying the development of multi-sided platforms over time, and b) using topic modeling and qualitative content analysis as complementing methodological approaches.