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Recent real-time networking developments have enabled ultra reliability, very low latency and high data rates in wired networks. Wireless networking developments have also shown that they can achieve very high data rates with consistency, but they still lack in providing ultra reliability and extremely low latency. Time Sensitive Networking (TSN) developments have brought these capabilities in Industry automation and Automotive industry too. Although TSN is standardized for wired networks for a long time, for wireless networks it will be standardized within the IEEE 802.11be standard for Wi-Fi and 3GPP Release 17 for 5G in the near future. This paper provides an overview of TSN in wired and wireless networks with the aim of comparing different simulators and presenting their offered functionality and shortcomings. These tools can be used to make oneself familiar with TSN algorithms, standards, and for the development and testing of time sensitive networks. Afterwards, the paper discusses open research questions for using TSN over wireless networks.
Water retention properties of wood fiber based growing media and their impact on irrigation strategy
(2024)
Distribution of water and air in growing media during ebb-and-flow irrigation depends on water storage properties (water retention curve) and water transport properties (hydraulic conductivity) of the materials. Growing media with their high number of coarse pores are known to exhibit strong hysteresis, i.e., differences in the water retention properties during drying and wetting cycles. To account for potential ecological disadvantages of peat, wood fibers are commonly used as substitutes for peat in growing media. However, the wood fibers generally have higher air capacities and hydraulic conductivities and lower water capacities compared to peat which may results in necessary adaptions of the irrigation strategy. Tools to optimize irrigation systems are physically based water transport models, such as HYDRUS-1D, which is commonly used to describe water transport in soils, but not often for growing media. In this study, white peat and pure wood fibers were used to describe differences in their water retention behavior. Water retention curves (drying cycles) and hydraulic conductivities were measured with standard analytical procedures. Hysteresis of the water retention curves was analytically determined based on their capillary rise properties. The results were used with a modified HYDRUS-1D model to test model quality against measured water contents during ebb-and-flow irrigation cycles and to optimize the irrigation strategy for the different materials. The results showed that the model quality was sufficiently good only if the strong hysteresis of the water retention curves was considered during the simulation process. Different strategies were tested to modify ebb-and-flow irrigation (irrigation frequency, irrigation duration and irrigation height) in that way that the water suction in the root zone was similar to that of the peat material. Simulation results showed that significant improvements could only be reached by increasing the flooding depth in ebb-and-flow systems to ensure an optimum water supply of plants in the wood fiber based growing media.
Wood fibers can contribute to replacing peat in growing media and thus help to protect peatlands. As domestic, renewable raw materials, they represent a sustainable option for this purpose. To date, however, wood fibers are usually used as a peat substitute at a maxi-mum of 30% (v/v). A main reason for this limitation is the insufficient microbial stability of wood fibers, which favors nitrogen immobilization and can thus impair nitrogen supply of plants. To address this drawback, in this study wood fibers were subjected to different thermal or thermal-hydrolytic treatments. Seedling tests with napa cabbage were conducted to determine whether treated wood fibers were free of phytotoxic substances. Mixtures with 50% (v/v) wood fiber and white peat each were used. In addition, three wood fiber varieties were evaluated in the cultivation of petunia. Two wood fiber proportions (30 and 60% v/v) and two nitrogen fertilization rates (common and increased supply) were included in each case. In the seedling trial with napa cabbage, no phytotoxic effects were detectable in any of the wood fiber variants investigated. However, when cultivating petunias, both shoot mass growth and number of flowers decreased with increasing wood fiber content. In substrates with a wood fiber content of 60% (v/v), plant development was inhibited so severely that the petunias no longer achieved marketable quality. Increased nitrogen fertilization was able to compensate for this negative effect only in few cases. This suggests that other factors than nitrogen limited plant growth in wood fiber-rich substrates. Among others, physical proper-ties such as the lower water capacity of wood fibers may be a cause. More in-depth investigations are still required in this regard.
Enhancing the nutritional value of pears through agronomic biofortification with iodine (Abstract)
(2024)
Response of petunia to wood fibre amended peat substrate under ebb-and-flow irrigation (Abstract)
(2024)
Compliance of agricultural AI systems : app-based legal verification throughout the development
(2024)
Significant advances in artificial intelligence (AI) have been achieved; however, practical implementation in agriculture remains limited. Compliance with emerging regulations, such as the EU AI Act and GDPR, is now vital, even for non-critical AI systems. Developers need tools to assess legal compliance, which is complex, often requiring full legal advice. To address this issue, we are developing a support app that simplifies the legal aspects of AI system development, covering the entire lifecycle, from conception to distribution. The current app, which covers the key legal area of copyright and will soon include GDPR and the AI Act, aims to bridge the gap between AI research and agriculture. An evaluation of our app by experts from both the legal and the IT domains shows that the app assists the developers so that they make legally correct statements. Consequently, it promotes legal compliance and awareness among developers, contributing to the seamless integration of AI into agriculture. The need for compliant AI systems in various industries, including agriculture, will only increase as regulations evolve.
Artificial intelligence (AI) promises transformative impacts on society, industry, and agriculture, while being heavily reliant on diverse, quality data. The resource-intensive "data
problem" has initialized a shift to synthetic data. One downside of synthetic data is known as the "reality gap", a lack of realism. Hybrid data, combining synthetic and real data, addresses this. The paper examines terminological inconsistencies and proposes a unified taxonomy for real, synthetic, augmented, and hybrid data. It aims to enhance AI training datasets in smart agriculture, addressing the challenges in the agricultural data landscape. Utilizing hybrid data in AI models offers improved prediction performance and adaptability.
Artificial intelligence (AI) and human-machine interaction (HMI) are two keywords that usually do not fit embedded applications. Within the steps needed before applying AI to solve a specific task, HMI is usually missing during the AI architecture design and the training of an AI model. The human-in-the-loop concept is prevalent in all other steps of developing AI, from data analysis via data selection and cleaning to performance evaluation. During AI architecture design, HMI can immediately highlight unproductive layers of the architecture so that lightweight network architecture for embedded applications can be created easily. We show that by using this HMI, users can instantly distinguish which AI architecture should be trained and evaluated first since a high accuracy on the task could be expected. This approach reduces the resources needed for AI development by avoiding training and evaluating AI architectures with unproductive layers and leads to lightweight AI architectures. These resulting lightweight AI architectures will enable HMI while running the AI on an edge device. By enabling HMI during an AI uses inference, we will introduce the AI-in-the-loop concept that combines AI's and humans' strengths. In our AI-in-the-loop approach, the AI remains the working horse and primarily solves the task. If the AI is unsure whether its inference solves the task correctly, it asks the user to use an appropriate HMI. Consequently, AI will become available in many applications soon since HMI will make AI more reliable and explainable.
Bamboo is an environmentally friendly alternative to conventional materials in mechanical engineering such as steel or aluminium. Bamboo is the fastest growing plant in the world. Instead of releasing CO2 during the manufacturing process, bamboo absorbs CO2 as it grows.
In addition to the sustainability aspect, bamboo tubes also offer excellent properties as a lightweight construction material, which have been optimised through evolution. Bamboo tubes have high strength and stiffness at low weight when used as tension-compression bars or bending beams. Bamboo has strong, high-density fibres at the boundary area, where bending stresses are greatest. Towards the inside, where the stresses are lower, the bamboo becomes porous to optimise weight. This, together with knots arranged in regular intervals, counteracts buckling.
In mobile applications such as cars and bicycles, lightweight construction is sought for energy efficiency reasons. Because of its excellent lightweight properties, the project investigated whether bamboo could be used in mobile, automotive or agricultural engineering. For example, a bamboo bicycle frame has been developed with the aim to be as light as possible. There are bamboo bicycles on the market, but they can only be made one at a time by hand. The bamboo tubes are joined together and functional elements such as the bottom bracket and headset are integrated by wrapping them in resin-impregnated natural or carbon fibres. This makes the joints very heavy. A different approach is taken here: the bamboo tubes are drilled out slightly to achieve a defined internal diameter, and then short aluminium tubes are glued into the bamboo canes from the inside. To prevent the cane from breaking in the circumferential direction, i.e. perpendicular to the fibre direction, the bamboo tubes are wrapped in a thin layer of natural or carbon fibre impregnated with synthetic resin. The aluminium tubes and functional elements are welded or soldered together beforehand.
The design of the bicycle frame, i.e. the dimensioning of the bamboo tubes and joints, was based on extensive bending and tensile tests to determine the strength properties of the natural material bamboo. The bonding between the bamboo cane and the aluminium tube was also investigated experimentally. Finally, several prototype bicycle frames were made and tested for durability according to DIN-EN-14764. The frames passed the tests.
The result is a bamboo bicycle that is manufactured with standardised connectors and joints. The assembly concept developed allows both fully automated and semi-automated series production of bamboo bicycles.
Biomechanical analyses are capable of capturing and evaluating human motions. In addition to the major biomechanical fields of kinetics and kinematics, electromyography (EMG) provides a reliable way to analyse neuromuscular activities, e.g. inter- and intramuscular coordination or fatigue behavior. Based on these parameters it is possible to conclude to clinically relevant parameters such as motor control, muscular coordination or compensation strategies with different loads. In addition to this, EMG can be used in treatment itself, e.g. biofeedback-training with an EMG is an effective and evidenced based tool to improve neuromuscular control. The purpose of this workshop is to show the advantages of implementing EMG in performing artists´ health and to demonstrate additional therapy and diagnostic options.
This workshop briefly introduces the theoretical principles of EMG and the clinical applications in the context of performing artists´ health. It explains why EMG provides an additional value in the clinical reasoning process and supports the therapist, but decision making in the clinical reasoning process should never be based on EMG solely.
In the further course of the workshop the use of EMG in diagnostics and therapy (biofeedback) with performing artists is practically demonstrated and discussed with the participants.
Approach of Presentation:
1. Short presentation: introduction and understanding of EMG (educational objective 1)
2. Short case presentation of a performing artist to introduce EMG in the field of performing artists´ health and clinical reasoning (educational objective 2)
3. Interactive practical demonstration (diagnosis and biofeedback-training) as the central part of the workshop. Questions and comments will be discussed directly throughout the group (educational objective 3)
Clinical Significance:
EMG based functional neuromuscular diagnostics and biofeedback-training provides both the therapist as well as the performing artist with additional value in their clinical work.
Educational Objectives:
At the end of the workshop, the participants will be able to…
1. understand and describe the basic principles of EMG
2. understand and describe the importance of EMG in the context of performing artists´ health, physical therapy and clinical reasoning
3. use EMG on performing artists in the performance process
Nostalgia is a construct that, even when rooted in lived experiences, serves the ultimate purpose of creating a desired sense of world. Fundamental cognitive competencies, including memory and imagination, are utilized by the nostalgic subject to fulfill a need for narrative coherence. A temporal or spatial distance is necessary for the occurrence of a nostalgic episode, which can be conceptualized as a “had been” state of being, as direct access to the experience is often impossible. Nostalgia may thus be viewed as a tool for sense-making rather than solely as a yearning for the past. The nostalgic narrative form is a construct that permits human subjects to comprehend their existence in the world while drawing upon their roots. These tools for sense-making serve as bridges between past experiences and current conditions. Ultimately, nostalgic identity is not just about longing for the past but also about utilizing the past as a resource for navigating the labyrinths of the present. Analyses are conducted to examine the medium of music video at three levels - auditory, visual, and linguistic - in order to investigate the strategies and techniques employed by the Iranian diaspora to create nostalgic narratives. Samples of original pieces and renditions are contrasted in order to identify elements of nostalgic narrativity. Drawing on empirical research, it is argued that the unity of a music video arises from the integration of separate layers of sensory and conceptual inputs that have been composed towards an affective resonance and narrative coherence.
Background: Multilingual children with suspected SLCN are often overlooked or their needs not accurately differentiated regarding the necessity of language support or therapy. The purpose of the study was to conceptualize, carry out and evaluate a local language support (LS) project within linguistically and culturally diverse (LCD) families and its effects on all collaborating participants.
Methods: Eight SLT students and one lecturer took part in the LS-project, alongside equivalent numbers of family liaison personnel. Students visited more than 10 young children aged between 2-6 years, and for each child 10 weekly home visits were carried out. Language enhancement was documented, several case studies with children and interviews with five liaison personnel conducted.
Results: All SLT students perceived changes in the behaviour and communication of participating children. Children in the case studies developed from pre-verbal to verbal means of communication and family liaison personnel reported positive changes alongside parental wishes to continue the support.
Conclusion: Local language support projects with LCD families can lead to positive differences regarding their children's communication development and better inclusion in mainstream society. SLT students benefit from working with LCD families and their collaborative support together with family liaison personnel, and vice versa.
Learning Outcomes: To differentiate the influence of language enhancement vs. formalized SLT therapy. To enhance the relationship with LCD clientele and collaboration with liaison personnel in SLCN settings. To incorporate life-long learning and intercultural sensitization.
Purpose
Sedentary behaviour (SED) and low level of physical activity (PA) might be associated with the development or worsening of pain. Still, studies assessing physical behaviours by accelerometry in individuals with orofacial pain are limited. This study aims to assess whether women with temporomandibular disorders (TMD) present different patterns of physical behaviours in days with (DWP) or without pain (DWoP).
Methods
Twenty-nine out of forty-four women (mean age 29.21 sd 7.96) were diagnosed with TMD and monitored over seven days using a thigh-worn accelerometer. DWP was determined when subjects presented pain in one of the craniocervical regions (head, jaw and neck) with intensity of at least 3 in the numerical rating scale. To be considered a DWoP, the individual presented less than 3 points in the three regions. Daily time-use compositions were described in terms of SED in short (<30 min) and long (≥30 min) bouts, light PA (LPA), moderate-to-vigorous PA (MVPA), and time-in-bed. Isometric log-ratios (ilr) were calculated to express the ratio of time-in-bed to time spent awake, SED relative to LPA and MVPA, SED in short relative to long bouts, and LPA relative to MVPA. Differences between DWP and DWoP were examined using MANOVA, followed by univariate post-hoc tests of pairwise differences.
Results
During DWP, women with TMD spent more time in SED in short (239 min) and long bouts (419 min), less time in LPA (245 min), MVPA (68 min), and in bed (468 min) compared with DWoP (235, 378, 263, 70 and 493 min, respectively). The MANOVA showed that all sets of ilrs did not differ statistically (ηp2 = 0.19, p = 0.25). Still, the post-hoc tests showed a trend that time spent SED relative to LPA and MVPA was larger in DWP than in DWoP (Cohen’s d = 0.36, p = 0.05).
Conclusions
Women with TMD did not show different patterns of physical behaviours in DWP or DWoP. However, there is a trend of more sedentary behaviour and less physical activity in DWP compared to DWoP. Future studies should consider other pain intensity cut-offs, isolated pain locations, and larger sample sizes to confirm these results.
The aim of this European interprofessional Health Informatics (HI) Summer School was (i) to make advanced healthcare students familiar with what HI can offer in terms of knowledge development for patient care and (ii) to give them an idea about the underlying technical and legal mechanisms. According to the students’ evaluation, interprofessional education was very well received, problem-based learning focussing on cases was rated positively and the learning goals were met. However, it was criticised that the online material provided was rather detailed and comprehensive and could have been a bit overcharging for beginners. These drawbacks were obviously compensated by the positive experience of working in international and interprofessional groups and a generally welcoming environment.
Background and Aims
Early identification of nerve lesions and associated neuropathic pain in spine-related pain disorders is important for tailored treatment. Management may consist of surgical intervention for compressive neural lesions.
With a growing waitlist for public surgical outpatient clinics in Western Australia and wait times exceeding the recommended wait time for initial assessment (Category 1 – assessment within 1 months, Category 2 within 3 months, category 3 within 12 months), a call to support new models of care has been made1, including the evaluation and expansion of workforce models supporting advanced skills in allied health.1
An Advanced Scope Physiotherapy (ASP) led Neurosurgery Spinal Clinic operates at Sir Charles Gairdner Hospital in Western Australia. The ASPs (2FTE) examine patients from the neurosurgery waitlist for their suitability for spinal surgery. Recommendation of either further investigation and possible assessment by a neurosurgeon or appropriate non-surgical management of the patients’ pain condition is suggested. Patient assessment is conducted either ‘in person’ at the hospital or via telehealth due to the remoteness of some rural patients. Patient cases are discussed with a neurosurgery consultant on a weekly basis. The aim of this project is to evaluate the ASP service in the year 2022.
Method
A retrospective descriptive analysis of patient data captured in 2022 was performed.
Results
In 2022, 1337 new patient referrals were managed plus 267 follow-ups from the previous year. Category 1 patients (n=81) waited on average 31 days for their first appointment, Category 2 patients (n=394) waited 76 days and Category 3 patients (n=854) waited 376 days.
287 (18%) referrals were discharged without physical assessment of the patient (DNA, cancellations, declined). Of the 1317 patients physically assessed by the ASPs (57%) were discharged directly after assessment, for 290 patients (22%) their outcome was still pending at time of analysis (March 2023) and 281 (22%) patients were referred for review with a neurosurgeon. Of the 229 patients assessed by a neurosurgeon (including patients from 2022), 103 patients (45%) were offered surgery, 52 (23%) were not offered surgery, 46 ( 20%) patients had to be reviewed, and for the remaining (n=18) their outcome was unknown.
Conclusion
Of the 1604 patients managed in the Neurosurgery Spinal Clinic, only 17% needed to see a neurosurgeon. The conversion rate to surgery of 45% is higher compared to an estimated 5%-10% in a non-triaged clinic.
The ASP model of care has proved invaluable to (i) provide access of patient care within the recommended wait times (ii) optimize neurosurgeons’ time, (iii) educate patients and, in case of non-suitability for surgery, advise and refer them for alternative appropriate management.
Relevance for Patient Care
The Advanced Scope Physiotherapy model of care at the Neurosurgery Spinal Clinic allows timely assessment of patients with spine-related disorders and supports targeted management of their condition.
Ethical Permissions
This project is registered as a Quality Improvement Project at Sir Charles Gairdner Hospital (QI35728) and as per the National Statement on Ethical Conduct in Human Research was exempt from review by the Sir Charles Gairdner Hospital Human Research and Ethics Committee
References
1Sustainable Health Review (2019). Sustainable Health Review: Final report to the Western Australian Government of Health, Western Australia
Workshop: “‘Sciatica’: neuropathic or not and does it matter? Outcomes from a NeuPSIG working group”
(2023)
The identification of neuropathic pain in persons with spine-related leg pain is important as this information guides treatment and management, including self-management. The NeuPSIG neuropathic pain grading system was developed to assist clinicians and researchers in determining whether patients have neuropathic pain and the level of confidence associated with that decision. Based on clinical and laboratory examination findings, patients are classified as having no neuropathic pain, possible, probable or definite neuropathic pain. Whereas this grading system works nicely in people with systemic neuropathies where sensory findings and diagnostic tests are mostly present, its application in patients with spine-related leg pain, particular in radicular pain, can be challenging. For example, in the absence of sensory changes and MRI findings, patients with radicular pain would at best reach a classification of possible neuropathic pain according to the current neuropathic pain grading system.
In this presentation I will explain the adaptations to the neuropathic pain grading system for spine-related leg pain recommended by the NeuPSIG working group. I will demonstrate its application in clinical practice using case studies and provide clarity for how the system can be incorporated in clinical trials. This will be an interactive session with audience participation.
Methods: Systematic review of randomized controlled trials (RCT). Searches were conducted in five electronic databases. Studies were selected if they included patients with NP over 18 years old treated with aerobic exercise (AE) (e.g., cycling, running, hiking, and walking). The main outcome of interest was pain intensity. Qualitative and quantitative data were extracted. The risk of bias (RoB) was determined using the Cochrane RoB Tool-2 and the overall certainty of the evidence with the GRADE recommendations.
Results: Out of 21,585 initial records screened, a total of six individual studies published in ten manuscripts were included. There was a great heterogeneity between protocols, comparisons, and studies’ results (different magnitudes and directions). When looking at the effect of aerobic exercise versus control groups or other interventions on pain intensity measured with the VAS, not statistically (nor clinical) significant differences between aerobic exercise and control groups (MD [95%CI] 5.16 mm [-6.38, 16.70]) were identified. The combined effect of AE plus other interventions seems to be effective. Strength exercise obtained better effects than aerobic exercises (MD [95%CI]: -11.34 mm [-21.6, -1.09]).
Conclusions: Aerobic exercise presented positive results to reduce pain intensity, and improving disability, and physical and emotional functioning. However, the evidence is restricted, low quality, and heterogeneous.
Methods: The searches were conducted on five electronic databases. RCTs or CTs with patients over 18 years old of both sexes with OFP diagnoses were targeted. The intervention of interest was AE (i.e., walking, cycling, and running), compared to any other conservative and non-conservative therapy. The primary outcome was pain intensity. Risk of bias (RoB) was done with the Cochrane RoB tool (RoB 2). The overall certainty of the evidence was evaluated with GRADE.
Results: Out of 21,585 initial records found in the initial database search, only one study (reported on three manuscripts) was included. The diagnosis of interest was headache plus temporomandibular disorders (TMD). Three treatment groups (strengthening (Str) exercise + manual therapy (MT) (G1); AE + MT + Str exercises (G2); AE (G3)) were compared. The main outcome was pain; the secondary outcomes included disability, strength, anxiety, and quality of life. The combined treatment (AE+MT+Str exercises) had the strongest effect to decrease pain and headache intensity in patients with OFP (SMD: 9.99 [95%CI: 7.19, 12.80].
Conclusions: a multimodal treatment strategy achieved the greatest positive effects on pain and other outcomes in the short/medium term. AE seems to be an important component of this strategy. However, the scientific evidence supporting AE’s isolated effect is limited, indicating a research gap in this scientific field.
The excitement sparked by the emergence of AI open platforms has encountered significant scrutiny from educators and educational planners, who have raised valid concerns about issues such as plagiarism, testing protocols, and the authenticity of content submitted by students. While these concerns are timely and crucial, it's essential not to overlook other pressing issues that often go unnoticed in the lived educational experience of learners, particularly within the field of social sciences. This paper aims to advocate for a humanistic approach with a focus on education in the generative AI Era.
Iron deficiency is a global issue and can lead to a variety of clinical pictures. The biofor-tification of vegetables with iron could complement the existing portfolio of iron-rich products, thus improving iron supply in the long term. In order to determine whether the iron-biofortified vegetables could meet this demand and would address appropriate target groups, a quantitative online survey was conducted in Germany. Based on 1000 consumer responses, a cluster analysis was performed. The results showed a four-cluster solution. The first cluster was holistically engaged, the second was fitness-affine but health unconcerned, the third cluster consists frugal eaters with a focus on medical prevention, and the fourth cluster are hedonists. No cluster focused its consumption on iron-enriched products, but instead all developed an individual mix of the three product groups.
The energy transition involves various challenges. One key aspect is the decentralization of power generation, which requires new actors. In order to integrate these into the system in the best possible way, there are various approaches e.g. in cooperation in citizens' initiatives or cooperatives (Dorniok, 2016).
Cooperation in general can enable the implementation of certain business models or can increase profitability by the exploitation of economies of scale (Skovsgaard & Jacobsen, 2017; Theurl, 2010). Synergy effects result from the utilization of know-how, different technologies or resources of the partners involved to complement the own competencies and services (Eggers & Engelbrecht, 2005; Sander, 2009). Cooperation exists in various industries and enable the participating companies to compensate their size-related resource deficits (Glaister & Buckley, 1996; Todeva & Knoke, 2005). This creates the opportunity to develop innovations, open up new markets, exploit newly created economies of scale and share costs and risks (Franco & Haase, 2015). In agriculture, cooperation in the form of cooperatives have been of essential importance for a long time, especially with the aim of exploiting synergy effects (Bareille et al., 2017). In the field of renewable energy development, cooperation in form of citizen cooperatives make a significant contribution to the participation of citizens in political, social and financial aspects of the energy transition (Huybrechts & Mertens, 2014). Energy cooperatives are frequently discussed as a potential actor in the energy transition and are increasingly being established to advance the common interests of stakeholders. For example, the joint operation of decentralized power generation plants can involve new actors in the energy transition through regional cooperation (Walk, 2014).
Existing biogas plants in Germany need new business models after the 20-year Renewable Energy Sources Act feed-in tariff expires. For continued operation, a business model innovation is needed, which can be realized based on the different technical utilization pathways. Cooperation can have a significant impact on the profitability of the different business models, especially by exploiting synergy effects (Karlsson et al., 2019). In addition, cooperation can help to ensure that existing plants continue to operate at all.
Currently, the most widespread use of biogas in Germany is in the coupled generation of electricity and heat. Additionally, there is the possibility of upgrading biogas to biomethane or biogenic hydrogen path (Mertins & Wawer, 2022).
Different options for cooperative business models that exist in the biogas utilization pathways are presented. The focus is on explaining the advantages of a joint approach compared to single-farm business models and identifying the relevant actors. Subsequently, drivers and barriers for the different cooperative business models are identified and classified based on 20 semi-structured interviews with plant operators in the administrative district of Osnabrück. The aim is to identify drivers and barriers for cooperative post-EEG operation. As a result, political instruments are to be found that make it possible to involve relevant actors and thus stimulate the best possible continued operation from the point of view of the energy system. The results are structured according to the PESTEL analysis. This assigns drivers and barriers to the categories political, economic, sociocultural, technological, ecological and legal (Kaufmann, 2021). The analysis of the interviews is supplemented and validated by a literature review.
Drivers and barriers for cooperative business models are manifold and can vary mainly depending on the plant and the operator.
Drivers
• Political
o Promotion of renewable energies: reduce dependence on fossil (Russian) fuels
• Economic
o Expectation of synergies (information sharing, shared risk, economies of scale)
o Planning security (fixed supply or purchase contracts)
o Access to new markets (not accessible by single-farm business models)
o Cost savings by sharing infrastructure, technology
o Positive return expectation
• Sociocultural
o Motivating, innovative environment
o Lowers barriers to participation in new markets
o Target-oriented partnerships
o Better use of capacities and strengths
o Strengthening regional value creation
• Technological
o Economies of scale (efficiency)
o Available, mature technology
o Storable, transportable gas
o Well-developed infrastructure
• Ecological
o Increase in plant efficiency
o Reduction of greenhouse gas emissions
o Promotion of the circular economy by utilization of organic waste and agricultural residues
o Improving soil quality (fermentation residues as fertilizer)
Barriers
• Political
o Competition to other renewable energies
• Economic
o Uncertainty about future development of energy markets
o Disagreements between the cooperation partners
o Lack of flexibility due to longer-term contractual obligations
o Allocation of profits
• Sociocultural
o Cooperation with current competitor
o Cultural differences and lack of trust
o Acceptance by the general public (e.g. overproduction of maize)
• Technological
o Different technology that is difficult to combine
o Data protection
• Ecological
o Competition for agricultural land
o Use of monocultures
o Emissions from plant
o Pollution from transport
• Legal
o Legal requirements and regulations
o Unfavorable regulatory environment, e.g. long permitting process
One finding is that uncertainty is a major barrier for plant operators. This includes uncertainty about regulatory frameworks and political requirements, as well as about the general development of the energy markets. In addition, social factors such as lack of reliability and disagreement about revenue sharing are a potential barrier. A key driver for the implementation of cooperative business models is the expectation of synergy effects. In addition, operators are driven by a positive expectation of returns and the responsibility for securing the energy supply in times of crisis.
The drivers identified can now be used to develop strategies to advance cooperative business models. In particular, synergy effects should be exploited so that operators can benefit from cooperation. The advantages can also be highlighted and communicated to increase acceptance among the general public. Another important step is to reduce the barriers discussed above. In order to reduce social barriers in particular, it may be advisable to include an external partner in the cooperation, such as a municipal utility that operates an upgrading plant and concludes purchase agreements with the individual partners. In addition, it would be politically expedient to provide the operators with a clear framework for the future in order to reduce uncertainties. As a further aspect, knowledge transfer on new technologies and markets should take place.
SimBO is a flexible framework for optimizing discrete event-driven simulations (DES) using sequential optimization algorithms. While specifically designed for Bayesian Optimization (BO) in the context of DES, SimBO can be applied to any black-box problem with other optimization algorithms. The framework consists of four encapsulated components - the black-box problem, the sequential optimization algorithm, a database for experiment configuration and results, and a web-based graphical user interface - that communicate via well-defined interfaces. Each component can be run in different environments, allowing for cooperation between different hardware- and software configurations. In our research context, SimBO’s architecture enabled BO algorithms to be run on a high-performance cluster with GPU support, while the simulation is executed on a local Windows machine using the Simio simulation software. The framework’s flexibility also makes it suitable for evolving from a research-focused tool to a production-ready, cloud-based optimization tool for modern algorithms.
Diet can influence healthy aging through anti- or proinflammatory effects, partly by modulating the gut microbiome composition. This study investigated the relationships between the Dietary Inflammatory Index (DII), the gut microbiome, and nutritional status in elderly individuals. Methods: This cross-sectional analysis included 114 home-dwelling individuals aged over 70 years. The Energy-adjusted DII (E-DII) was calculated from 3-day food diaries, and blood samples were taken to measure micronutrient status, glucose, and lipid metabolism. Body composition was assessed using bioimpedance, and fecal gut microbiome composition was analyzed through 16S rRNA gene sequencing. The participants were categorized into maintaining an anti-inflammatory diet (AD) and a pro-inflammatory diet (PD) based on the median E-DII score. The associations of E-DII groups with blood markers and microbial diversity and composition were examined using the analysis of covariance, permutational analysis of variance, and multivariate linear models. Results: The AD (n = 57, 76 ± 3.83 years) and PD (n = 57, 75 ± 5.21 years) groups were similar in age but differed in sex distribution, with a higher proportion of females in the AD group (p = 0.02). When compared to the PD group and adjusted for sex, the AD group had a lower body mass index, fat mass, fasting insulin level, HOMA-IR (Homeostasis Model Assessment of Insulin Resistance), fasting triglycerides, and serum uric acid concentration (all p < 0.05), with higher concentrations of high-density lipoprotein, red-blood-cell folate (RBC), and Omega-3 index (all p < 0.05). While the microbial diversity and composition did not differ between the DII groups, folate concentrations were negatively associated with Agathobacter and positively associated with Bacteroides abundance (both q = 0.23). Lower uric acid concentrations were associated with a higher abundance of Bifidobacterium (q = 0.09) and lower abundance of Phocaeicola (q = 0.11). Discussion: The study suggests that following an anti-inflammatory diet is associated with improved nutritional status in the elderly. Dietary blood markers, rather than E-DII, were found to be associated with the gut microbiome, suggesting a potential link between the microbiome and changes in nutritional markers independent of diet. Further studies are needed to explore the causal relationship between dietary inflammatory potential, gut microbiome, and healthy aging.
Knowledge of the maximum friction coefficient µmax between tire and road is necessary for implementing autonomous driving. As this coefficient cannot be measured via existing serial vehicle sensors, µmax estimation is a challenging field in modern automotive research. In particular, model-based approaches are applied, which are limited in the estimation accuracy by the physical vehicle model. Therefore, this paper presents a data-based µmax estimation using serial vehicle sensors. For this purpose, recurrent artificial neural networks are trained, validated, and tested based on driving maneuvers carried out with a test vehicle showing improved results compared to the model-based algorithm from previous works.
Within the consortium “Experimentation Field Agro-Nordwest”, a practical concept for knowledge and technology transfer of digital competence in agriculture was created. For this purpose, the web-based e-learning system “SensX” was set up, consisting of videos, presentations and instructions. In addition, the classical e-learning concept was extended by data sets, student experiments and sensor data of plants acquired by a remote phenotyping robot. This resulted in a massive open online course (MOOC), which was tested with agricultural and biotechnology students in higher education at the University of Applied Sciences Osnabrück over two years. The evaluation process of “SensX” included an empirical survey, qualitative interviews of the participating students by an external institution and an evaluation of the concept by the lecturers.
Computer-image processing becomes more and more important in the analysis of data in biological and agricultural research and practice. However, robust image processing is highly de pendent on the histogram analysis algorithms used and the quality of the data being processed. The algorithm presented here aims to improve the accuracy of the classification of image data generated under complex boundary situations and inconsistent lighting conditions. Using the example of the determination of nitrogen content of tomato leaves and the qualitative determination of starch con tent of apples on the basis of color image processing, we showed that the developed algorithm is able to perform a robust classification and represents an improvement to simple histogram analysis.
The Internet of Things (IoT) is the enabler for new innovations in several domains. It allows the connection of digital services with physical entities in the real world. These entities are devices of different categories and sizes range from large machinery to tiny sensors. In the latter case, devices are typically characterized by limited resources in terms of computational power, available memory and sometimes limited power supply. As a consequence, the use of security algorithms requires of them to work within the limited resources. This means to find a suitable implementation and configuration for a security algorithm, that performs properly on the device, which may become a challenging task. On the other side, there is the desire to protect valuable assets as strong as possible. Usually, security goals are recorded in security policies, but they do not consider resource availability on the involved device and its power consumption while executing security algorithms. This paper presents an IoT security configuration tool that helps the designer of an IoT environment to experiment with the trade-off between maximizing security and extending the lifetime of a resource constrained IoT device. The tool is controlled with high-level description of security goals in the form of policies. It allows the designer to validate various (security) configurations for a single IoT device up to a large sensor network.