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The objective of this review is a global assessment of the economics of second‐generation biorefineries, with a focus on the use of food waste and agricultural residues for chemical production by applying biotechnological processes. Analyses are conducted on feedstock and product distribution, applied economic models, and profitability figures for the period 2013–2018. In a study of 163 articles on different biorefinery systems, the production of chemicals is identified as the second major product class, after bioenergy. Bagasse and straw are frequently analyzed second‐generation feedstocks. Based on the evaluation of 22 articles, second‐generation biorefineries producing chemicals by applying biotechnological processes proves to be economically feasible. On average, both the internal rate of return (IRR) and the return on investment (ROI) are 20% and the payback period (PP) is 6 years. The cost share of feedstock in biorefineries is between 0–50%. The price of the end product and the fermentation yields have the most impact on profitability. The processing of food waste that has industrial and municipal origins appears more economical than the processing of agricultural residues. Scientists, policy makers and entrepreneurs with an appropriate risk tolerance are advised to pay particular attention to municipal food waste and the potential economic production of carboxylic acids. For various economic issues related to biorefineries, dynamic‐deterministic models are recommended, which can be extended by a stochastic model. This review provides an initial overview of the economic feasibility of second‐generation biorefineries. Further techno‐economic analyses are required to produce statistically significant statements on key profitability figures. © 2020 The Authors. Biofuels, Bioproducts, and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.
Hintergrund Die physiotherapeutische Dokumentation spielt im Therapieprozess eine wichtige Rolle, erfolgt jedoch auf unterschiedlichste Weise. Es existieren derzeit eine Vielzahl von Softwarelösungen für die physiotherapeutische Dokumentation, welche sich jedoch in ihren Funktionalitäten stark unterscheiden. Ziel Mithilfe einer Befragung soll ein Konsens von Expertenaus der Physiotherapie im Themengebiet der softwarebasierten Dokumentation ermittelt werden. Anhand der Ergebnisse wird ein Anforderungskatalog für die Entwicklung einer neuartigen und benutzerorientierten Dokumentationssoftware erstellt. Methode Online-Delphi-Befragung mit neun Experten über drei Befragungswellen.
Ergebnisse Hinsichtlich der Anforderungen an die Anamnese konnte ein Konsens erzielt werden. Bei der Gliederung des Befundes kam es zu keiner Übereinstimmung der Experten. Das Ergebnis lässt sich durch unterschiedliche manualtherapeutische Konzepte erklären, die für die Befunderhebung verwendet wurden. Schlussfolgerung Eine softwarebasierte Dokumentation sollte standardisierter als bisher erfolgen, um den ClinicalReasoning-Prozess zu unterstützten. Gleichzeitig ist dabei eine gewisse Flexibilität geboten. Die gesammelten Anforderungen können für die Entwicklung einer neuartigen und benutzerorientierten mobilen Anwendung zur Effizienzsteigerung in der physiotherapeutischen Dokumentation verwendet werden.
Der nachfolgende Projektbericht, welcher im Rahmen des Masterprojektes und des Moduls „Bildgebende Sensortechnik“ erarbeitet wurde, ist wie folgt den beiden Fächern zuzuordnen.
Die Kapitel, welche sich mit der Inbetriebnahme und den Umgang des SICK RMS320 Radarsensors beschäftigen, sind Teil des Masterprojektes. Dies betrifft die Kapitel 2.2, 4.1, 4.3 und in Teilen das Kapitel 4.5.
Dem Modul „Bildgebende Sensortechnik“ sind hingegen die Messung des Einflusses von Kleidung auf die Erkennungsfähigkeit eines Menschen sowie die Radarmessungen der verschiedene Prüfkörper zuzuordnen. Dies wird in den Kapiteln 2.3, 3, 4.2, 4.4 und 4.5 behandelt.
Die „Grundlagen der Radartechnik“ sind für beide Teile gleichbedeutend wichtig.
Analysis of methods for prioritizing critical data transmissions in agricultural vehicular networks
(2020)
Applying wireless communication technologies to agricultural vehicular networks often results in high end-to-end delays and loss of packets due to intermittent or broken connectivity. This paper analyses the methods for the successful delivery of the vehicular data within acceptable delay times. Different kinds of data that are generated and transmitted in agricultural networks are considered in this paper, followed by the data prioritization methods which allow critical data to be prioritized against other data. In this regard, Enhanced Distributed Channel Access, Differentiated Services, and application-based data rate variation are discussed in conjunction with the Simple Network Management Protocol. These techniques are simulated or tested separately and then together and the results show that even in poor network conditions, high-prioritized data is not lost or delayed.
Process modeling languages help to define and execute processes and workflows. The Business Process Model and Notation (BPMN) 2.0 is used for business processes in commercial areas such as banks, shops, production and supply industry. Due to its flexible notation, BPMN is increasingly being used in non-traditional business process domains like Internet of Things (IoT) and agriculture. However, BPMN does not fit well to scenarios taking place in environments featuring limited, delayed, intermittent or broken connectivity. Communication just exists for BPMN - characteristics of message transfers, their priorities and connectivity parameters are not part of the model. No backup mechanism for communication issues exists, resulting in error-prone and failing processes. This paper introduces resilient BPMN (rBPMN), a valid BPMN extension for process modeling in unreliable communication environments. The meta model addition of opportunistic message flows with Quality of Service (QoS) parameters and connectivity characteristics allows to verify and enhance process robustness at design time. Modeling of explicit or implicit, decision-based alternatives ensures optimal process operation even when connectivity issues occur. In case of no connectivity, locally moved functionality guarantees stable process operation. Evaluation using an agricultural slurry application showed significant robustness enhancements and prevented process failures due to communication issues.
Optimised Nutrient Recovery from Biogas Digestate by Solid/Liquid Separation and Membrane Treatment
(2019)
Anaerobic digestion products of agricultural biogas plants are characterised by high nitrogen, phosphorus, and potassium content. In three scale-up steps, a membrane based digestate treatment process of solid-liquid-separation, ultrafiltration, and reverse osmosis for nutrient recovery was investigated. Lab-scale trials delivered a very good understanding of fluid properties and subsequent ultrafiltration performance, which is the limiting process step in terms of energy demand and operation costs. In semi-technical experiments, optimisation, and design parameters were developed, which were subsequently applied to pilot-scale tests at two full-scale biogas plants. The process optimisation resulted in 50 % energy reduction of the ultrafiltration step. About 36 % of the sludge volume was recovered as dischargeable water, 20 % as solid N/P-fertiliser, and 44 % as liquid N/K-fertiliser.
We describe an automated approach, to easily track patients regaining their walking ability while recovering from neurological diseases like e.g. stroke. Based on captured gait data and objective measures derived out of it the rehabilitation process can be optimized and thus steered. In order to apply such system in clinical practice two key requirements have to be fulfilled: (i) the system needs to be applicable in terms of ease of use and performance; (ii) the derived measures need to be accurate.
The usage of high-level synthesis (HLS) tools for FPGAs has increased significantly over the last years since they matured and allow software programmers to take advantage of reconfigurable hardware technology.
Most HLS tools employ methods to optimize for loops, e. g. by unrolling or pipelining them. But there is hardly any work on the optimization of while loops. This comes at no surprise since most while loops have loop-carried dependences involving the loop condition which result in large recurrence cycles in the dataflow graphs. Therefore typical while loops cannot be parallelized or pipelined.
We propose a novel transformation which allows to optimize while loops nested within a for loop. By interchanging the two loops, it is possible to pipeline (and thereby parallelize) the inner loop, resulting in a reduced execution time. We present two case studies on different hardware platforms and show the speedup factors - compared to a host processor and to an unoptimized hardware implementation - achieved by our while loop optimization method.
A recently published study of high temperature nitridation of iron chromium aluminum alloys (FeCrAl) at 900°C in N2–H2 has redundantly shown the formation of locally confined corrosion pockets reaching several microns into the alloy. These nitrided pockets form underneath chromia islands laterally surrounded by the otherwise protective alumina scale. Chromia renders a nitrogen‐permeable defect under the given conditions and the presence of aluminum in the alloy. In light of these findings on FeCrAl, a focused ion beam–scanning electron microscope tomography study has been undertaken on an equally nitrided FeNiCrAl sample to characterize its nitridation corrosion features chemically and morphologically. The alloy is strengthened by a high number of chromium carbide precipitates, which are also preferential chromia formation sites. Besides the confirmation of the complete encapsulation of the corrosion pocket from the alloy by a closed and dense aluminum nitride rim, very large voids have been found in the said pockets. Furthermore, metallic particles comprising nickel and iron are deposited on top of the outer oxide scale above such void regions.