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While the topic of artificial intelligence (AI) in multinational enterprises has been receiving attention for some time, small and medium enterprises (SMEs) have recently begun to recognize the potential of this new technology. However, the focus of previous research and AI applications has therefore mostly been on large enterprises. This poses a particular issue, as the vastly different starting conditions of various company sizes, such as data availability, play a central role in the context of AI. For this reason, our systematic literature review, based on the PRISMA protocol, consolidates the state of the art of AI with an explicit focus on SMEs and highlights the perceived challenges regarding implementation in this company size. This allowed us to identify various business activities that have been scarcely considered. Simultaneously, it led to the discovery of a total of 27 different challenges perceived by SMEs in the adoption of AI. This enables SMEs to apply the identified challenges to their own AI projects in advance, preventing the oversight of any potential obstacles or risks. The lack of knowledge, costs, and inadequate infrastructure are perceived as the most common barriers to implementation, addressing social, economic, and technological aspects in particular. This illustrates the need for a wide range of support for SMEs regarding an AI introduction, which covers various subject areas, like funding and advice, and differentiates between company sizes.
While recent studies have demonstrated that events are fundamentally climate sensitive, this seems to not be fully considered in event research or corporate event practice. Thus, this study aims to identify the influencing factors that affect the acceptance of climate adaptation measures among decision-makers in the event industry. The analysis was divided into three main parts. First, the existing literature related to climate change in an events context was reviewed. Using 15 semi structured interviews, the findings from this review were then critically discussed with stakeholders in Germany involved in event planning. Finally, explicit climate adaptation measures were proposed and discussed. Based on all findings, there appears to be a low level of awareness of and interest in climate adaptation amongst German event industry players. There is an imminent need for further research on climate adaptation and for decision-makers to better prepare for climate change in order to counteract resulting negative impacts.
Purpose
This study operationalizes risks in stakeholder dialog (SD). It conceptualizes SD as co-produced organizational discourse and examines the capacities of organizers' and stakeholders' practices to create a shared understanding of an organization’s risks to their mutual benefit. The meetings and online forum of a German public service media (PSM) organization were used as a case study.
Design/methodology/approach
The authors applied corpus-driven linguistic discourse analysis (topic modeling) to analyze citizens' (n = 2,452) forum posts (n = 14,744). Conversation analysis was used to examine video-recorded online meetings.
Findings
Organizers suspended actors' reciprocity in meetings. In the forums, topics emerged autonomously. Citizens' articulation of their identities was more diverse than the categories the organizer provided, and organizers did not respond to the autonomous emergence of contextualizations of citizens' perceptions of PSM performance in relation to their identities. The results suggest that risks arise from interactionally achieved occasions that prevent reasoned agreement and from actors' practices, which constituted autonomous discursive formations of topics and identities in the forums.
Originality/value
This study disentangles actors' practices, mutuality orientation and risk enactment during SD. It advances the methodological knowledge of strategic communication research on SD, utilizing social constructivist research methods to examine the contingencies of organization-stakeholder interaction in SD.
The development of base metal electrodes that can act as active and stable oxygen generating electrodes in water electrolysis systems, especially at low pH levels, remains a challenge. The use of suspensions as electrolytes for water splitting has until recently been limited to photoelectrocatalytic approaches. A high current density (j=30 mA/cm2) for water electrolysis has been achieved at a very low oxygen evolution reaction (OER) potential (E=1.36 V vs. RHE) using a SnO2/H2SO4 suspension-based electrolyte in combination with a steel anode. More importantly, the high charge-to-oxygen conversion rate (Faraday efficiency of 88% for OER at j=10 mA/cm2 current density). Since cyclic voltammetry (CV) experiments show that oxygen evolution starts at a low, but not exceptionally low, potential, the reason for the low potential in chronoamperometry (CP) tests is an increase in the active electrode area, which has been confirmed by various experiments. For the first time, the addition of a relatively small amount of solids to a clear electrolyte has been shown to significantly reduce the overpotential of the OER in water electrolysis down to the 100 mV region, resulting in a remarkable reduction in anode wear while maintaining a high current density.
The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option to synchronize either of the networks to the other. The TSN time synchronization over 5G is possible either by using the IEEE 1588 generalized Precision Time Protocol (gPTP) based on UDP/IP multicast or via IEEE 802.1AS based on Ethernet PDUs. The INET and Simu5G simulation frameworks, which are both based on the OMNeT++ discrete event simulator, are widely used for simulating TSN and 5G networks. The INET framework comprises the 802.1AS based time synchronization mechanism, and Simu5G provides the 5G user plane carrying IP PDUs. We modified the 802.1AS-based synchronization model of INET so that it works over UDP/IP. With that, it is possible to synchronize TSN slaves (connected to 5G UEs), across a 5G network, with a TSN master clock, present within a TSN network, that is connected to the 5G core network. Our simulation results show that 500 microseconds of synchronization accuracy can be achieved with the corrected asymmetric propagation delay of uplink and downlink between the gNodeB (gNB) and the User Equipment (UE). Furthermore, the synchronization accuracy can be improved if the delay difference between uplink and downlink is known.
Introduction: Patients undergoing revision total hip surgery (RTHS) have a high prevalence of mild and moderate preoperative anemia, associated with adverse outcomes. The aim of this study was to investigate the association of perioperative allogeneic blood transfusions (ABT) and postoperative complications in preoperatively mild compared to moderate anemic patients undergoing RTHS who did not receive a diagnostic anemia workup and treatment before surgery. Methods: We included 1,765 patients between 2007 and 2019 at a university hospital. Patients were categorized according to their severity of anemia using the WHO criteria of mild, moderate, and severe anemia in the first Hb level of the case. Patients were grouped as having received no ABT, 1–2 units of ABT, or more than 2 units of ABT. Need for intraoperative ABT was assessed in accordance with institutional standards. Primary endpoint was the compound incidence of postoperative complications. Secondary outcomes included major/minor complications and length of hospital and ICU stay. Results: Of the 1,765 patients, 31.0% were anemic of any cause before surgery. Transfusion rates were 81% in anemic patients and 41.2% in nonanemic patients. The adjusted risks for compound postoperative complication were significantly higher in patients with moderate anemia (OR 4.88, 95% CI: 1.54–13.15, p = 0.003) but not for patients with mild anemia (OR 1.93, 95% CI: 0.85–3.94, p < 0.090). Perioperative ABT was associated with significantly higher risks for complications in nonanemic patients and showed an increased risk for complications in all anemic patients. In RTHS, perioperative ABT as a treatment for moderate preoperative anemia of any cause was associated with a negative compound effect on postoperative complications, compared to anemia or ABT alone. Discussion: ABT is associated with adverse outcomes of patients with moderate preoperative anemia before RTHS. For this reason, medical treatment of moderate preoperative anemia may be considered.
Background
Beta-blocker (BB) therapy plays a central role in the treatment of cardiovascular diseases. An increasing number of patients with cardiovascular diseases undergoe noncardiac surgery, where opioids are an integral part of the anesthesiological management. There is evidence to suggest that short-term intravenous BB therapy may influence perioperative opioid requirements due to an assumed cross-talk between G-protein coupled beta-adrenergic and opioid receptors. Whether chronic BB therapy could also have an influence on perioperative opioid requirements is unclear.
Methods
A post hoc analysis of prospectively collected data from a multicenter observational (BioCog) study was performed. Inclusion criteria consisted of elderly patients (≥ 65 years) undergoing elective noncardiac surgery as well as total intravenous general anesthesia without the use of regional anesthesia and duration of anesthesia ≥ 60 min. Two groups were defined: patients with and without BB in their regular preopreative medication. The administered opioids were converted to their respective morphine equivalent doses. Multiple regression analysis was performed using the morphine-index to identify independent predictors.
Results
A total of 747 patients were included in the BioCog study in the study center Berlin. 106 patients fulfilled the inclusion criteria. Of these, 37 were on chronic BB. The latter were preoperatively significantly more likely to have arterial hypertension (94.6%), chronic renal failure (27%) and hyperlipoproteinemia (51.4%) compared to patients without BB. Both groups did not differ in terms of cumulative perioperative morphine equivalent dose (230.9 (BB group) vs. 214.8 mg (Non-BB group)). Predictive factors for increased morphine-index were older age, male sex, longer duration of anesthesia and surgery of the trunk. In a model with logarithmised morphine index, only gender (female) and duration of anesthesia remained predictive factors.
Conclusions
Chronic BB therapy was not associated with a reduced perioperative opioid consumption.
The development of non-precious metal-based electrodes that actively and stably support the oxygen evolution reaction (OER) in water electrolysis systems remains a challenge, especially at low pH levels. The recently published study has conclusively shown that the addition of haematite to H2 SO4 is a highly effective method of significantly reducing oxygen evolution overpotential and extending anode life. The far superior result is achieved by concentrating oxygen evolution centres on the oxide particles rather than on the electrode. However, unsatisfactory Faradaic efficiencies of the OER and hydrogen evolution reaction (HER) parts as well as the required high haematite load impede applicability and upscaling of this process. Here it is shown that the same performance is achieved with three times less metal oxide powder if NiO/H2 SO4 suspensions are used along with stainless steel anodes. The reason for the enormous improvement in OER performance by adding NiO to the electrolyte is the weakening of the intramolecular O─H bond in the water molecules, which is under the direct influence of the nickel oxide suspended in the electrolyte. The manipulation of bonds in water molecules to increase the tendency of the water to split is a ground-breaking development, as shown in this first example.
In modern times, closed-loop control systems (CLCSs) play a prominent role in a wide application range, from production machinery via automated vehicles to robots. CLCSs actively manipulate the actual values of a process to match predetermined setpoints, typically in real time and with remarkable precision. However, the development, modeling, tuning, and optimization of CLCSs barely exploit the potential of artificial intelligence (AI). This paper explores novel opportunities and research directions in CLCS engineering, presenting potential designs and methodologies incorporating AI. Combining these opportunities and directions makes it evident that employing AI in developing and implementing CLCSs is indeed feasible. Integrating AI into CLCS development or AI directly within CLCSs can lead to a significant improvement in stakeholder confidence. Integrating AI in CLCSs raises the question: How can AI in CLCSs be trusted so that its promising capabilities can be used safely? One does not trust AI in CLCSs due to its unknowable nature caused by its extensive set of parameters that defy complete testing. Consequently, developers working on AI-based CLCSs must be able to rate the impact of the trainable parameters on the system accurately. By following this path, this paper highlights two key aspects as essential research directions towards safe AI-based CLCSs: (I) the identification and elimination of unproductive layers in artificial neural networks (ANNs) for reducing the number of trainable parameters without influencing the overall outcome, and (II) the utilization of the solution space of an ANN to define the safety-critical scenarios of an AI-based CLCS.
Hyperhydricity (HH) is one of the most important physiological disorders that negatively affects various plant tissue culture techniques. The objective of this study was to characterize optical features to allow an automated detection of HH. For this purpose, HH was induced in two plant species, apple and Arabidopsis thaliana, and the severity was quantified based on visual scoring and determination of apoplastic liquid volume. The comparison between the HH score and the apoplastic liquid volume revealed a significant correlation, but different response dynamics. Corresponding leaf reflectance spectra were collected and different approaches of spectral analyses were evaluated for their ability to identify HH-specific wavelengths. Statistical analysis of raw spectra showed significantly lower reflection of hyperhydric leaves in the VIS, NIR and SWIR region. Application of the continuum removal hull method to raw spectra identified HH-specific absorption features over time and major absorption peaks at 980 nm, 1150 nm, 1400 nm, 1520 nm, 1780 nm and 1930 nm for the various conducted experiments. Machine learning (ML) model spot checking specified the support vector machine to be most suited for classification of hyperhydric explants, with a test accuracy of 85% outperforming traditional classification via vegetation index with 63% test accuracy and the other ML models tested. Investigations on the predictor importance revealed 1950 nm, 1445 nm in SWIR region and 415 nm in the VIS region to be most important for classification. The validity of the developed spectral classifier was tested on an available hyperspectral image acquisition in the SWIR-region.
Dairy farming has been the subject of public debate on animal welfare for a number of years now. Animal welfare discussions on dairy farming often include the demand for more nature connectedness in this area. This study focuses on the divergent perspectives of consumers and scientists on the importance of more nature connectedness for animal welfare strategies in German dairy farming. Within Europe, Germany is the main producer of cow’s milk and an important industry in many rural areas in Germany is dairy farming. The insights presented are based on qualitative interviews with dairy farming and livestock researchers from Germany and Austria. A key finding of this study is that we need to look more closely at the actual content of nature claims in animal welfare debates. The scientists interviewed tend to see idealized conditions in animal welfare discussions with images of nature which in fact seldom lead to improved conditions in dairy farming and, even then, only to a limited extent. The scientists interviewed rate calls for more nature connectedness in dairy farming from the nonagricultural public as anti-modern, complexity-reducing, and normative. Nevertheless, some of the scientists interviewed did have valuable insights into the nonagricultural public’s criticism of dairy farming practices. These scientists argued, however, that animal welfare needs to differentiate between nature connectedness and the innate needs of cattle when it comes to animal welfare strategies. An important conclusion of the study is that more discussion formats are needed to promote the exchange of ideas between different social groups attempting to understand animal welfare in dairy farming.
Background
The current development of sensor technologies towards ever more cost-effective and powerful systems is steadily increasing the application of low-cost sensors in different horticultural sectors. In plant in vitro culture, as a fundamental technique for plant breeding and plant propagation, the majority of evaluation methods to describe the performance of these cultures are based on destructive approaches, limiting data to unique endpoint measurements. Therefore, a non-destructive phenotyping system capable of automated, continuous and objective quantification of in vitro plant traits is desirable.
Results
An automated low-cost multi-sensor system acquiring phenotypic data of plant in vitro cultures was developed and evaluated. Unique hardware and software components were selected to construct a xyz-scanning system with an adequate accuracy for consistent data acquisition. Relevant plant growth predictors, such as projected area of explants and average canopy height were determined employing multi-sensory imaging and various developmental processes could be monitored and documented. The validation of the RGB image segmentation pipeline using a random forest classifier revealed very strong correlation with manual pixel annotation. Depth imaging by a laser distance sensor of plant in vitro cultures enabled the description of the dynamic behavior of the average canopy height, the maximum plant height, but also the culture media height and volume. Projected plant area in depth data by RANSAC (random sample consensus) segmentation approach well matched the projected plant area by RGB image processing pipeline. In addition, a successful proof of concept for in situ spectral fluorescence monitoring was achieved and challenges of thermal imaging were documented. Potential use cases for the digital quantification of key performance parameters in research and commercial application are discussed.
Conclusion
The technical realization of “Phenomenon” allows phenotyping of plant in vitro cultures under highly challenging conditions and enables multi-sensory monitoring through closed vessels, ensuring the aseptic status of the cultures. Automated sensor application in plant tissue culture promises great potential for a non-destructive growth analysis enhancing commercial propagation as well as enabling research with novel digital parameters recorded over time.
Primary Liver Cancers : Connecting the Dots of Cellular Studies and Epidemiology with Metabolomics
(2023)
Liver cancers are rising worldwide. Between molecular and epidemiological studies, a research gap has emerged which might be amenable to the technique of metabolomics. This review investigates the current understanding of liver cancer’s trends, etiology and its correlates with existing literature for hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA) and hepatoblastoma (HB). Among additional factors, the literature reports dysfunction in the tricarboxylic acid metabolism, primarily for HB and HCC, and point mutations and signaling for CCA. All cases require further investigation of upstream and downstream events. All liver cancers reported dysfunction in the WNT/β-catenin and P13K/AKT/mTOR pathways as well as changes in FGFR. Metabolites of IHD1, IDH2, miRNA, purine, Q10, lipids, phosphatidylcholine, phosphatidylethanolamine, acylcarnitine, 2-HG and propionyl-CoA emerged as crucial and there was an attempt to elucidate the WNT/β-catenin and P13K/AKT/mTOR pathways metabolomically.
Aims and Objectives:
Preventive home visits are a low-threshold counselling and support approach. They have been reported to achieve heterogeneous effects. However, preventive home visits have the potential to reduce the risk of becoming dependent on long-term care. The aim of this study is to investigate the effect of preventive home visits as a nursing intervention on health-related quality of life of older people in a longitudinal survey and to develop recommendations for which target groups preventive home visits have the highest benefit. The sample consisted of 75 people, aged between 65 and 85, who were able to understand and speak German, had not yet been eligible for benefits from the long-term care insurance and lived in the municipality under study.
Methodological Design and Justification:
A quantitative longitudinal study in order to investigate the effects of preventive home visits.
Ethical Issues and Approval:
There were no ethical concerns. Accordingly, ethical approval was granted.
Research Methods, Results and Conclusions:
The health-related quality of life was recorded four times between 01/2017 and 08/2020 with the Short-Form- Health- Survey- 12 and analysed using descriptive statistics. Results reveal that the physical health status cannot be easily influenced over a short period of time. The main effect, however, is that preventive home visits have a significant positive effect on the mental health status. The main topics during the home visits were mobility, nutrition and social participation. Increased knowledge and motivation for preventive behaviour extended the autonomy of older people. Accordingly, preventive home visits can support a self-determined life in a familiar environment. The results of the present study show that preventive home visits as a nursing intervention in rural areas are successful. In Germany, preventive home visits have not yet been implemented on a regular basis. In order to do so, a general definition of the concept is needed. Preventive home visits should be officially included in the regular health care services in Germany.
While developing traffic-based cognitive enhancement technology (CET), such as bike accident prevention systems, it can be challenging to test and evaluate them properly. After all, the real-world scenario could endanger the subjects’ health and safety. Therefore, a simulator is needed, preferably one that is realistic yet low cost. This paper introduces a way to use the video game Grand Theft Auto V (GTA V) and its sophisticated traffic system as a base to create such a simulator, allowing for the safe and realistic testing of dangerous traffic situations involving cyclists, cars, and trucks. The open world of GTA V, which can be explored on foot and via various vehicles, serves as an immersive stand-in for the real world. Custom modification scripts of the game give the researchers control over the experiment scenario and the output data to be evaluated. An off-the-shelf bicycle equipped with three sensors serves as a realistic input device for the subject’s movement direction and speed. The simulator was used to test two early-stage CET concepts enabling cyclists to sense dangerous traffic situations, such as trucks approaching from behind the cyclist. Thus, this paper also presents the user evaluation of the cycling simulator and the CET used by the subjects to sense dangerous traffic situations. With the knowledge of the first iteration of the user-centered design (UCD) process, this paper concludes by naming improvements for the cycling simulator and discussing further research directions for CET that enable users to sense dangerous situations better.
Semi-natural grasslands (SNGs) are an essential part of European cultural landscapes. They are an important habitat for many animal and plant species and offer a variety of ecological functions. Diverse plant communities have evolved over time depending on environmental and management factors in grasslands. These different plant communities offer multiple ecosystem services and also have an effect on the forage value of fodder for domestic livestock. However, with increasing intensification in agriculture and the loss of SNGs, the biodiversity of grasslands continues to decline. In this paper, we present a method to spatially classify plant communities in grasslands in order to identify and map plant communities and weed species that occur in a semi-natural meadow. For this, high-resolution multispectral remote sensing data were captured by an unmanned aerial vehicle (UAV) in regular intervals and classified by a convolutional neural network (CNN). As the study area, a heterogeneous semi-natural hay meadow with first- and second-growth vegetation was chosen. Botanical relevés of fixed plots were used as ground truth and independent test data. Accuracies up to 88% on these independent test data were achieved, showing the great potential of the usage of CNNs for plant community mapping in high-resolution UAV data for ecological and agricultural applications.
Purpose
The purpose of this paper is to distinguish different types of sustainable digital entrepreneurs (SDEs) and explore their approaches toward enhancing organizational resilience.
Design/methodology/approach
Investigation of entrepreneur characteristics using Grounded Theory methodology; 12 semi-structured telephone interviews with (owner-)managers of digital-resilient small and medium-sized enterprises (SMEs) and start-ups in Germany; adaptation of a sustainability-digitalization-matrix for initial clustering; investigation of reoccurring patterns (within and between clusters) through variable-oriented content analysis; application of the capability-based conceptualization of organizational resilience for synthesis and extension.
Findings
First, the authors present a new typology of SDEs, including descriptions of the four main types (Process-Oriented System Thinker, Unconventional Strategist, Dynamic Visionary and Success-Oriented Opportunist). Second, the authors propose a conceptual framework with six success factors of organizational resilience. The framework accentuates the influence of SDEs on organizational culture and the macro-environment.
Practical implications
Digital sustainability and resilience are emerging management principles. The insights gained will allow (future) entrepreneurs to perform a self-assessment and replicate approaches toward enhancing SME resilience; for example, governing the co-creation of an organizational culture with a strong integrative view on sustainability and digitalization.
Originality/value
SMEs are characterized by high vulnerability and a reactive response to the disruptions caused by sustainability crises and digitalization. Blending sustainable and digital entrepreneurship at a micro-level, the authors identified the success factors underpinning organizational resilience that are associated with the characteristics of four types of SDEs.
In recent years, the issue of land consumption or land use has become increasingly important in many areas of our society. Logistics processes in particular take up a lot of space and have a significant impact on the environment. The question is how this use of land can be optimised. Based on a systematic literature review and interviews with experts in the period between May 2021 and July 2021, this paper presents indicators that constitute or influence space-efficient logistics in the context of cooperation. The results show that in addition to the established cooperation characteristics, there are other indicators that are directly related to land use. In the logistics sector, there is strong competitive pressure and, as a result, little trust between companies. It has been shown that with the help of a neutral moderator, the gap between trusting, land-efficient cooperation and one’s own entrepreneurial interests can be narrowed, and cooperation can be profitable for all participants. In addition, digitisation actually does not seem to be sufficient to meet the information needs of a cooperation. The exchange of information not only serves to automate processes, but also makes cooperation more transparent. It shows that legal and municipal requirements need to be developed. It also becomes clear that the indicators have a mutual influence on each other and cannot be considered in isolation when it comes to the actual implementation of a cooperation. By increasing the efficiency of cooperative processes and value creation, it offers the opportunity to make land use more sustainable.
In the race against climate change, small and medium-sized enterprises (SMEs) play a fundamental role. To clarify the contribution of corporate culture to SMEs' emission reduction, three perspectives can be useful: corporate culture as driver and barrier, current and planned corporate culture development actions, and the corporate culture profile as an outcome. As the first application of the extended Belief-Action-Outcome framework, this single case study exemplifies the role of corporate culture in an SME from the steel construction and manufacturing sector in Germany. The investigated SME has achieved emission reduction while increasing its revenue and is an early adopter of sustainable and digital development. The rich insights from an employee survey, semi-structured interviews, observation, and document analysis allowed us to outline an informed approach toward corporate culture development that emphasizes vision development of the desired corporate culture and the role of information systems for promoting emission reduction.
In view of the rapid depletion of natural resources and the associated overloading of the biological ecosystem, the concept of circular business models (CBMs) is increasingly discussed in the literature as well as in business practice. CBMs have the potential to significantly reduce the demand for natural resources. Despite their increasing relevance, the diffusion of CBMs in business practice is largely unexplored. Consequently, this article investigates the extent to which CBMs have already been adopted by large German companies. To answer this question, the annual and sustainability reports of the members of the DAX40 are analyzed for the presence of five specific types of CBMs. Data was gathered for the years 2015 and 2020 in order to describe the development over time. The results show an increasing prevalence of CBMs in the DAX companies. In addition, it is noticeable that CBM types that serve to close material cycles are implemented more frequently than those that decelerate material cycles. In particular Sharing Platforms and Product as a Service stand out due to comparatively low adoption. Potential reasons for these findings are discussed and managerial as well as policy implications suggested.