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Hyperhydricity (HH) is one of the most important physiological disorders that negatively affects various plant tissue culture techniques. The objective of this study was to characterize optical features to allow an automated detection of HH. For this purpose, HH was induced in two plant species, apple and Arabidopsis thaliana, and the severity was quantified based on visual scoring and determination of apoplastic liquid volume. The comparison between the HH score and the apoplastic liquid volume revealed a significant correlation, but different response dynamics. Corresponding leaf reflectance spectra were collected and different approaches of spectral analyses were evaluated for their ability to identify HH-specific wavelengths. Statistical analysis of raw spectra showed significantly lower reflection of hyperhydric leaves in the VIS, NIR and SWIR region. Application of the continuum removal hull method to raw spectra identified HH-specific absorption features over time and major absorption peaks at 980 nm, 1150 nm, 1400 nm, 1520 nm, 1780 nm and 1930 nm for the various conducted experiments. Machine learning (ML) model spot checking specified the support vector machine to be most suited for classification of hyperhydric explants, with a test accuracy of 85% outperforming traditional classification via vegetation index with 63% test accuracy and the other ML models tested. Investigations on the predictor importance revealed 1950 nm, 1445 nm in SWIR region and 415 nm in the VIS region to be most important for classification. The validity of the developed spectral classifier was tested on an available hyperspectral image acquisition in the SWIR-region.
Recording of Low-Oxygen Stress Response Using Chlorophyll Fluorescence Kinetics in Apple Fruit
(2023)
Long-term storage of apples (Malus x domestica, Borkh.) is increasingly taking place under Dynamic Controlled Atmosphere (DCA). The oxygen level is lowered to ≤ 1 kPa O2 and the apples are stored just above the Lower Oxygen Limit (LOL). Low oxygen stress during controlled atmosphere storage can lead to fermentation in apples if oxygen levels are too low. Chlorophyll fluorescence can be used to detect low-oxygen stress at an early stage during storage. The currently available non-imaging fluorescence systems often use the minimal fluorescence (Fo) parameter. In contrast, the use of chlorophyll fluorescence kinetics is insufficiently described. Therefore, this study aimed to gain more knowledge about the response of chlorophyll fluorescence kinetics to low oxygen stress in apples using a fluorescence imaging system. The results show that the kinetic fluorescence curves differ under aerobic and fermentation conditions. The fermentative conditions initiated a decrease in fluorescence intensity upon application of the saturation pulses during exposure to actinic light. This result was made at 18 °C and 2 °C ambient temperatures. Interestingly, the kinetic curve changed at 2 °C before fermentation products accumulated in the apples. Non-photochemical quenching (NPQ) decreased under fermentation conditions in the dark phase after relaxation. Upon entering the dark relaxation phase after Kautsky induction, ɸPSII began to increase. Under atmospheric oxygen conditions, ɸPSII reached values of 0.81 to 0.76, while under fermentation, ɸPSII values ranged from 0.57 to 0.44.
Background
The current development of sensor technologies towards ever more cost-effective and powerful systems is steadily increasing the application of low-cost sensors in different horticultural sectors. In plant in vitro culture, as a fundamental technique for plant breeding and plant propagation, the majority of evaluation methods to describe the performance of these cultures are based on destructive approaches, limiting data to unique endpoint measurements. Therefore, a non-destructive phenotyping system capable of automated, continuous and objective quantification of in vitro plant traits is desirable.
Results
An automated low-cost multi-sensor system acquiring phenotypic data of plant in vitro cultures was developed and evaluated. Unique hardware and software components were selected to construct a xyz-scanning system with an adequate accuracy for consistent data acquisition. Relevant plant growth predictors, such as projected area of explants and average canopy height were determined employing multi-sensory imaging and various developmental processes could be monitored and documented. The validation of the RGB image segmentation pipeline using a random forest classifier revealed very strong correlation with manual pixel annotation. Depth imaging by a laser distance sensor of plant in vitro cultures enabled the description of the dynamic behavior of the average canopy height, the maximum plant height, but also the culture media height and volume. Projected plant area in depth data by RANSAC (random sample consensus) segmentation approach well matched the projected plant area by RGB image processing pipeline. In addition, a successful proof of concept for in situ spectral fluorescence monitoring was achieved and challenges of thermal imaging were documented. Potential use cases for the digital quantification of key performance parameters in research and commercial application are discussed.
Conclusion
The technical realization of “Phenomenon” allows phenotyping of plant in vitro cultures under highly challenging conditions and enables multi-sensory monitoring through closed vessels, ensuring the aseptic status of the cultures. Automated sensor application in plant tissue culture promises great potential for a non-destructive growth analysis enhancing commercial propagation as well as enabling research with novel digital parameters recorded over time.
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.
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.
Einleitung
Die Prävalenz der über 80-jährigen bei Ulcus cruris venosum (VLU) beträgt 4-5 %, obwohl diese Altersgruppe nur 1 % der Gesamtbevölkerung ausmacht. Zusätzlich wird bei VLU-Patienten häufig eine Mangelernährung beobachtet. Insbesondere geriatrische Patienten leiden darunter. Dabei ist bekannt, dass Mangelernährung Einfluss auf die Wundheilung und somit auf die Lebensqualität der Patienten hat. Diverse Studien beschreiben erste erfolgreiche ernährungstherapeutische Ansätze für einen beschleunigten Wundheilungsprozess. Allerdings ist die Ernährungstherapie bei VLU-Patienten wenig erforscht. Ziel dieser Arbeit ist es einen Überblick über den ernährungsphysiologischen Einfluss zur VLU zu schaffen, um mögliche Ernährungsinterventionen für geriatrische Patienten zu erhalten.
Grasslands are ubiquitous globally, and their conservation and restoration are critical to combat both the biodiversity and climate crises. There is increasing interest in implementing effective multifunctional grassland restoration to restore biodiversity concomitant with above- and belowground carbon sequestration, delivery of carbon credits and/or integration with land dedicated to solar panels. Other common multifunctional restoration considerations include improved forage value, erosion control, water management, pollinator services, and wildlife habitat provisioning. In addition, many grasslands are global biodiversity hotspots. Nonetheless, relative to their impact, and as compared to forests, the importance of preservation, conservation, and restoration of grasslands has been widely overlooked due to their subtle physiognomy and underappreciated contributions to human and planetary well-being. Ultimately, the global success of carbon sequestration will depend on more complete and effective grassland ecosystem restoration. In this review, supported by examples from across the Western world, we call for more strenuous and unified development of best practices for grassland restoration in three areas of concern: initial site conditions and site preparation; implementation of restoration measures and management; and social context and sustainability. For each area, we identify the primary challenges to grassland restoration and highlight case studies with proven results to derive successful and generalizable solutions.
Geometrie und Funktionen
(2024)
Im Band 2 werden die Themen aus dem "Core Curriculum" der Europäischen Gesellschaft für Ingenieurausbildung (SEFI) fortgesetzt, in dem die wesentlichen Inhalte und Ziele der Mathematikausbildung für Ingenieure berücksichtigt werden:
- Differentialrechnung,
- Integralrechnung,
- Differentialgleichungen,
- Geometrie und Trigonometrie,
- Diskrete Mathematik,
- Vektoren,
- Wahrscheinlichkeitsrechnung und Statistik.
Jedes Kapitel führt in das Thema kurz ein, die verwendeten Begriffe werden definiert. Viele einfache Abbildungen tragen zur Veranschaulichung bei. Ausformulierte Lernziele, die jeweils mit "Ich kann ..." beginnen, helfen, sich die benötigte Mathematik zu erschließen. Das Arbeiten mit Kann-Listen macht den eigenen Lernerfolg für Studierende sichtbar: einfach Abhaken! Darüber hinaus verbindet es das zu Lernende mit der Meta-Ebene des Stoffs, was für nachhaltiges Erinnern entscheidend ist. Der innovative didaktische Ansatz hat sich in der Praxis bewährt.
Jedes Kapitel bietet zusätzlich eine Vielzahl an Aufgaben und schließlich ausführlichen Lösungen. Zu jeder Aufgabe gibt es eine Zeitangabe, die den Studierenden bei der Auswahl zum Anfang hilft. Die Aufgaben selbst sind unterschiedlich, teils auf Anwendung bezogen, teils zum Rechnen, teils zur Klärung der Begrifflichkeiten.
Semi-natural grasslands (SNGs) are an essential part of European cultural landscapes. They are an important habitat for many animal and plant species and offer a variety of ecological functions. Diverse plant communities have evolved over time depending on environmental and management factors in grasslands. These different plant communities offer multiple ecosystem services and also have an effect on the forage value of fodder for domestic livestock. However, with increasing intensification in agriculture and the loss of SNGs, the biodiversity of grasslands continues to decline. In this paper, we present a method to spatially classify plant communities in grasslands in order to identify and map plant communities and weed species that occur in a semi-natural meadow. For this, high-resolution multispectral remote sensing data were captured by an unmanned aerial vehicle (UAV) in regular intervals and classified by a convolutional neural network (CNN). As the study area, a heterogeneous semi-natural hay meadow with first- and second-growth vegetation was chosen. Botanical relevés of fixed plots were used as ground truth and independent test data. Accuracies up to 88% on these independent test data were achieved, showing the great potential of the usage of CNNs for plant community mapping in high-resolution UAV data for ecological and agricultural applications.
Farmland bird populations are in a deep crisis across Europe. Agri-environment schemes (AES) were implemented by the European Union to stop and reverse the general decline of biodiversity in agricultural landscapes. In Germany, flower strips are one of the most common AES. Establishing high-quality perennial wildflower strips (WFS) with species-rich native forb mixtures from regional seed propagation is a recent approach, for which the effectiveness for birds has not yet been sufficiently studied. We surveyed breeding birds and vegetation on 40 arable fields with WFS (20 with single and 20 with aggregated WFS) and 20 arable fields lacking WFS as controls across Saxony-Anhalt (Germany). Additionally, vegetation composition, WFS quantity and landscape structure (e.g. distance to nearest woody element) were considered in our analyses. All WFS were established with species-rich native seed mixtures (30 forbs) in agricultural practice as AES. Arable fields with WFS had a higher species richness and territory density of birds than controls, confirming the effectiveness of this AES. A forb-rich vegetation was the main driver promoting birds. Flower strip quantity at the landscape level had positive effects only on bird densities, but also single WFS achieved benefits. A short distance from WFS to woody elements increased total bird species richness. However, the density of farmland birds, which are target species of these AES, were negatively affected by the proximity and proportion of woody elements in the vicinity. The effect of the proportion of non-intensively used open habitats and overall habitat richness was unexpectedly low in the otherwise intensively farmed landscape. Species-rich perennial WFS significantly promoted breeding birds. Successful establishment of WFS, resulting in high-quality habitats, a high flower strip quantity as well as implementation in open landscapes were shown to maximise the effectiveness for restoring declining and AES target farmland birds.
Green roofs can mitigate negative environmental effects of urban densifcation to some extent, but they are often covered by species-poor Sedum mixtures with a low value for biodiversity. By combining a habitat template and a seedprovenance approach, we review the suitability of plant species from regionally occurring dry sandy grasslands (Koelerio-Corynophoretea) for extensive roof greening in northwestern Germany. Since 2015, we have studied the effects of species introduction on vegetation dynamics on experimental mini-roofs. Treatments included sowing seeds of regional native origin in two densities (1 g and 2 g/m2) and the transfer of raked material from an ancient dry grassland area classifed as Natura 2000 site. The applied raked material contained diaspores of 27 vascular plant species (including seven threatened species) and vegetative fragments of grasslandspecifc mosses and lichens. Since 2018, we have tested more species-rich seed mixtures in a large-scale experiment on a roof of 500 m2 with different engineered green-roof substrates and layering. In 2019, a green roof of 10,200 m2 was established in cooperation with a local enterprise to support regional native biodiversity.
In this chapter, we summarise the most important results of our studies and discuss how to support regional native biodiversity on green roofs.
Urban greenspace has gained considerable attention during the last decades because of its relevance to wildlife conservation, human welfare, and climate change adaptation. Biodiversity loss and ecosystem degradation worldwide require the formation of new concepts of ecological restoration and rehabilitation aimed at improving ecosystem functions, services, and biodiversity conservation in cities. Although relict sites of natural and semi-natural ecosystems can be found in urban areas, environmental conditions and species composition of most urban ecosystems are highly modified, inducing the development of novel and hybrid ecosystems. A consequence of this ecological novelty is the lack of (semi-) natural reference systems available for defining restoration targets and assessing restoration success in urban areas. This hampers the implementation of ecological restoration in cities. In consideration of these challenges, we present a new conceptual framework that provides guidance and support for urban ecological restoration and rehabilitation by formulating restoration targets for different levels of ecological novelty (i.e., historic, hybrid, and novel ecosystems). To facilitate the restoration and rehabilitation of novel urban ecosystems, we recommend using established species-rich and well-functioning urban ecosystems as reference. Such urban reference systems are likely to be present in many cities. Highlighting their value in comparison to degraded ecosystems can stimulate and guide restoration initiatives. As urban restoration approaches must consider local history and site conditions, as well as citizens’ needs, it may also be advisable to focus the restoration of strongly altered urban ecosystems on selected ecosystem functions, services and/or biodiversity values. Ecosystem restoration and rehabilitation in cities can be either relatively inexpensive or costly, but even expensive measures can pay off when they effectively improve ecosystem services such as climate change mitigation or recreation. Successful re‐shaping and re-thinking of urban greenspace by involving citizens and other stakeholders will help to make our cities more sustainable in the future.
Die vorliegende Abschlussarbeit befasst sich mit der Arbeitsweise des Building Information Modeling (BIM) in der Landschaftsarchitektur und der Untersuchung von Modellierungsop-tionen für Vegetationsobjekte. Wenngleich Vegetation einen wesentlichen Bestandteil der Planung von Außenanlagen darstellt, gibt es für den allgemeinen Umgang mit Bepflanzung in BIM bisher noch keine ausgereiften Konzepte. Insbesondere die Planung von Stauden-flächen wird in digitalen Modellen bisher kaum thematisiert. Es fehlen darüber hinaus allge-meine Workflows, um die Bepflanzungsplanung in den Prozess des Building Information Modeling zu integrieren. Das vorrangige Ziel dieser Arbeit ist daher die Entwicklung von exemplarischen Arbeitsab-läufen für das Aufgabenfeld der Bepflanzungsplanung innerhalb der 3D-Modellierungssoft-ware Autodesk Revit. Um die Potentiale des Programms bestmöglich zu nutzen, werden zudem die visuellen Programmierwerkzeuge des Softwaremoduls Dynamo verwendet. Die in Dynamo entwickelten benutzerdefinierten Tools ergänzen die Standardfunktionen von Revit und können für spezifische Modellierungsaufgaben wiederholt zum Einsatz kommen. Zum einen basiert die Modellierung in Revit auf den BIM-Grundlagen der Fertigstellungsgrade und Anwendungsfälle. Zum anderen soll durch das Modell ein automatisiertes Ableiten von Bepflanzungsplänen ermöglicht werden. Eine Analyse spezialisierter Softwareprodukte für die ‚Grüne Branche‘ gibt Aufschluss über die möglichen Funktionen der zu erstellenden Skripte in Dynamo. Der Workflow in Revit wird an einem Beispielprojekt veranschaulicht. Anhand eines Entwurfes für die Außenanlagen des Wohnkomplexes ‚Charlie Living‘ in Berlin wird somit ein vereinfachtes Modell angefertigt. Das Vegetationsmodell wird sukzessive für die Fertigstellungsgrade 100 bis 300 detailliert und enthält Bepflanzungselemente für Bäume, Hecken, Stauden und Pflanzflächen. Die Vegetationselemente werden mit zusätzlichen alphanumerischen Daten versehen und abschließend in einem Bepflanzungsplan dargestellt. Der Modellierungsprozess wird insgesamt mit zehn verschiedenen benutzerdefinierten Dynamo-Tools unterstützt und automatisiert. Anhand des Modellierungserfolges konnte eine generelle Eignung der BIM-Software Revit für die Anforderungen der Bepflanzungsplanung festgestellt werden. Die dargelegten Workflows in dieser Abschlussarbeit könnten demnach auch für das Modellieren von Vegetationsobjekten in anderen BIM-Projekten mit vergleichbarer Software Anwendung finden.
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.