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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.
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.
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.
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)
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.
Response of petunia to wood fibre amended peat substrate under ebb-and-flow irrigation (Abstract)
(2024)
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
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.
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.