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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.
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.
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.
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.
Response of petunia to wood fibre amended peat substrate under ebb-and-flow irrigation (Abstract)
(2024)
The objective of this article is to prepare for the initial certification according to IFS Global Markets Food V3 at the Landshuter Brauhaus AG private brewery at the Ellermühle site, which is expected in August 2025, and to create the basis for a potential follow-up certification according to IFS Food. The IFS Global Markets Food Program V3 is a standardized, voluntary and non-accredited assessment program for food companies, both for retail and manufacturer brand products (IFS 2023, p. 10 f.). It is based on the specifications of the Global Markets Program developed in 2008 (GFSI 2023a; VDOE 2020, p. 620).
The methodology of the target/actual analysis was used to work on the topic in order to be able to carry out a conformity check with regard to the requirements of IFS Global Markets Food V3 (see Appendix 3; IFS 2023). Observations, document analyses and employee surveys were carried out to obtain the most meaningful information possible. These have been recorded and evaluated within the target-performance analysis. A total of 65 deviations (equivalent to 53.7%) were identified at the basic level, and 60 deviations (equivalent to 82.2%) at the intermediate level. These were either processed as directly implemented corrective actions or formulated as recommendations for continuous improvement in the form of an action plan (see Appendix 15). The presentation of the action plan shows the deviations, the resulting measures, the associated responsibilities, the time period with the starting point and end point of the measures, and the current status. In addition a subdivision into "Basic" and "+Intermediate" was made for a better overview in the subsequent processing by the brewery.
A review as well as assessment of relevant requirements with regard to processes and significant violations after completion of the new building and commissioning at the Ellermühle site with regard to correlation with a potential "major" rating is recommended on the part of the operations manager or brewmaster (IFS 2023, p. 30).
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.
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.