FB Umweltplanung/-technik (UCB)
Filtern
Erscheinungsjahr
Dokumenttyp
Volltext vorhanden
- ja (44)
Gehört zur Bibliographie
- nein (44)
Schlagworte
- Elektrofahrzeug (5)
- Biodiversität (4)
- CO2-Bilanz (4)
- Elektromobilität (4)
- Fermentation (4)
- Maschinelles Lernen (4)
- Biomonitoring (3)
- Insekten (3)
- Klimaänderung (3)
- Rapid Prototyping <Fertigung> (3)
- additive manufacturing (3)
- 3D printing (2)
- 3D-Druck (2)
- Alkoholmissbrauch (2)
- Anomalie <Medizin> (2)
- Anomalieerkennung (2)
- Bioreaktor (2)
- CO2 (2)
- Convolutional Neural Network (2)
- Deutschland (2)
- Intervention <Medizin> (2)
- Jugend (2)
- Künstliche Intelligenz (2)
- LCA (2)
- LTER (2)
- Magnetisches Trennverfahren (2)
- Personenkraftwagen (2)
- Umweltbilanz (2)
- Universität (2)
- alcohol (2)
- anomaly detection (2)
- biodiversity (2)
- carbon footprint (2)
- carbon footprinting (2)
- climate policy (2)
- efficiency trade-offs (2)
- electric cars (2)
- fermentation (2)
- global warming potential (2)
- greenhouse gas emissions (2)
- high-gradient magnetic separation (2)
- insect monitoring (2)
- internet (2)
- life cycle assessment (2)
- mRNA-Impfstoff (2)
- machine learning (2)
- magnetic beads (2)
- modeling (2)
- optimization (2)
- renewable energy (2)
- university carbon footprint (2)
- university sustainability (2)
- young people (2)
- zero emission university (2)
- ALAN (1)
- ATR-Technik (1)
- Agent <Künstliche Intelligenz> (1)
- Agglomerieren (1)
- Algorithmus (1)
- Apoptosis (1)
- App <Programm> (1)
- Art (1)
- BASF Ultrafuse (1)
- BEV (1)
- BEV (battery electric vehicle) (1)
- BPA (1)
- Bartak (1)
- Batterie (1)
- Batteriefahrzeug (1)
- Bestäuber (1)
- Bewertung (1)
- Bild (1)
- Bilderkennung (1)
- Bildung für nachhaltige Entwicklung (1)
- Bildverarbeitung (1)
- Biofilm (1)
- Bioklima (1)
- Biomasse (1)
- Bioverfahrenstechnik (1)
- Bisphenol A (1)
- Boden (1)
- Bodenorganismus (1)
- Bodentemperatur (1)
- Branch-and-Bound-Methode (1)
- CNN (1)
- CO2 emissions (1)
- Charpy impact energy (1)
- China (1)
- Computerfigur (1)
- Cyanobakterien (1)
- DNN (1)
- Deep learning (1)
- Demontage (1)
- Dieselkraftstoff (1)
- Diskriminanzanalyse (1)
- Diuron (1)
- E-Learning (1)
- E. coli (1)
- EBV (1)
- EHR (1)
- ESD (1)
- Elektronische Patientenakte (1)
- Emissionsverringerung (1)
- Energie (1)
- Energiemodell (1)
- Environmental Campus Birkenfeld (1)
- Escherichia coli (1)
- Europa (1)
- Europe (1)
- European diesel car boom (1)
- European perch (1)
- FT-IR-Spektroskopie (1)
- Falle (1)
- Fed-batch-Verfahren (1)
- Festigkeit (1)
- Flussbarsch (1)
- Forschung (1)
- Frequenzumsetzung (1)
- Frequenzverdopplung (1)
- Fused Deposition Modeling (1)
- Fuzzy-Logik (1)
- GA-ANFIS (1)
- GA-FUZZY (1)
- GA-GA-FUZZY (1)
- GHG (1)
- GHG accounting and reporting (1)
- GWP (1)
- Genetischer Algorithmus (1)
- Gesundheitsökonomie (1)
- Handy (1)
- Herzmuskelkrankheit (1)
- Hydrothermale Karbonisierung (1)
- Höheres Bildungswesen (1)
- ICU (1)
- Industrieroboter (1)
- Integriertes Lernen (1)
- Intensivpflege (1)
- Intensivstation (1)
- Internet (1)
- K2Al2B2O7 (1)
- KABO (1)
- Klassifikation (1)
- Klimaschutz (1)
- Kohlendioxidemission (1)
- Konturfindung (1)
- Kraftfahrzeugindustrie (1)
- Kraftwagen (1)
- Kristall (1)
- Kunststoff (1)
- Künstliche Beatmung (1)
- Laborparameter (1)
- Lasertechnologie (1)
- Leistung (1)
- Lernsoftware (1)
- Lichtverschmutzung (1)
- Lufttemperatur (1)
- Malaise trap (1)
- Markforged (1)
- Materialermüdung (1)
- Medizinische Informatik (1)
- Messung (1)
- Metaanalyse (1)
- Meteorologische Station (1)
- Methanol-Analytik (1)
- Methode der kleinsten Quadrate (1)
- Methylotrophe Organismen (1)
- Mikroklima (1)
- Modell (1)
- NLO crystals (1)
- NLO-Kristall (1)
- Nachhaltigkeit (1)
- Nahrungskette (1)
- Nanyang Technological University (1)
- Naturschutz (1)
- Neuro-Fuzzy-System (1)
- Neuronales Netz (1)
- Nichtlineare Diffusion (1)
- Nichtlineare Optik (1)
- Nullemission (1)
- PETG (1)
- Parasit (1)
- Pellet (1)
- Penicillium (1)
- Penicillium sp. (1)
- Perca fluviatilis (1)
- Petri nets (1)
- Pflanzenkohle (1)
- Photoreaktor (1)
- Physik (1)
- Physikunterricht (1)
- Pichia pastoris (1)
- Plug-in-Hybrid (1)
- Proteaseinhibitor (1)
- Prozessanalytik (1)
- Prozessmanagement (1)
- Prozessmesstechnik (1)
- Raucherentwöhnung (1)
- Recycling (1)
- Rekursives neuronales Netz (1)
- Robotertechnik (1)
- Rotationsdispersion (1)
- Ruß (1)
- Selbstorganisierende Karte (1)
- Selektives Laserschmelzen (1)
- Sepsis (1)
- Singapur (1)
- Soziale Norm (1)
- Sporenbildung (1)
- Statistik (1)
- Student (1)
- Studiengang (1)
- Suchverfahren (1)
- Süßwasser (1)
- Teer (1)
- Townes (1)
- Umwelt-Campus Birkenfeld (1)
- Umweltdaten (1)
- Unterstützungssystem <Informatik> (1)
- VentAI (1)
- Vergleich (1)
- Verteilung (1)
- Virtuelles Laboratorium (1)
- Wassertiere (1)
- Wellenlänge (1)
- Windturbine (1)
- YAB (1)
- YAl3(BO3)4 (1)
- Zigarettenrauch (1)
- Zulaufsatzkultur-Fermentationen (1)
- active learning (1)
- adaptive neuro fuzzy system (1)
- adsorption mechanism (1)
- agglomeration (1)
- alternating least squares (1)
- apoptosis (1)
- aquatic subsidies (1)
- artificial intelligence (1)
- bachelor degree programs in business administration and mechanical engineering (1)
- battery (1)
- battery electric vehicle (1)
- battery electric vehicles (1)
- battery production (1)
- battery second use (1)
- battery size (1)
- biocarriers (1)
- bioclimatic variables (1)
- biofilm (1)
- bioprocess engineering (1)
- bioreactor internals (1)
- black carbon (1)
- blended learning (1)
- branch and bound search algorithm (1)
- break-even mileages (1)
- break-even production (1)
- building emissions (1)
- carbon mass balance constraint (1)
- carbon offsetting (1)
- classification (1)
- climate change (1)
- climate change impact (1)
- climate change mitigation (1)
- conservation (1)
- convolutional neural networks (1)
- critical care (1)
- critically-ill patient (1)
- cross-ecosystem (1)
- data-oriented business process (1)
- de-agglomeration (1)
- deep learning (1)
- diesel (1)
- diesel emissions (1)
- diet specialization (1)
- disassembly plan (1)
- disassembly process (1)
- diuron (1)
- e-bikes (1)
- e-boards (1)
- ecological gradients (1)
- ecological niche models (1)
- edge detection (1)
- educational software (1)
- electric bus (1)
- electric conversion (1)
- electric kick scooters (1)
- electric light commercial vehicles (1)
- electric motorcycles (1)
- electric three- and four-wheelers (1)
- electric trucks (1)
- electric vehicles (1)
- electricity (1)
- embodied emissions (1)
- embodied impacts (1)
- emissions mitigation costs (1)
- energy (1)
- energy impacts (1)
- energy modeling (1)
- energy system (1)
- energy system modeling (1)
- energy use (1)
- environmental effect (1)
- environmental impact (1)
- eye fluke (1)
- fatigue properties (1)
- fed-batch (1)
- fed-batch fermentations (1)
- food web (1)
- frequency conversion (1)
- fuel cell vehicles (1)
- fungal growth (1)
- fungal pellets (1)
- fuzzy logic (1)
- genetic algorithm (1)
- global maps (1)
- health impact (1)
- heat (1)
- higher education for a sustainable development (1)
- higher education institutions (1)
- human-robot-collaboration (1)
- hybrid modelling (1)
- hydrochar (1)
- hydrothermal carbonization (1)
- image processing (1)
- image recognition (1)
- impact categories (1)
- indicator system (1)
- inferencing (1)
- informed software agent (1)
- insect communities (1)
- insects (1)
- intelligent robot assistant (1)
- intensive care (1)
- internal combustion engine vehicle (1)
- inversion twin (1)
- knowledge-intensive process (1)
- lab values (1)
- land cover (1)
- learning rates (1)
- light pollution (1)
- lightGBM (1)
- linear discriminant analysis (LDA) (1)
- local biodiversity (1)
- long‐term ecosystem research (1)
- mRNA-based vaccines (1)
- mRNA-vaccines (1)
- malaise trap (1)
- maximal function (1)
- mechanical testing (1)
- medical consumables (1)
- medical economics (1)
- medical informatics (1)
- meta-analysis (1)
- methanol analytics (1)
- methylotrophic organisms (1)
- microclimate (1)
- mobile phone (1)
- mobility impacts (1)
- model evaluation (1)
- monitoring (1)
- multimedia learning (1)
- multivariate curve resolution (1)
- near-surface temperatures (1)
- necroptosis (1)
- nonlinear diffusion (1)
- ontology (1)
- optical activity (1)
- optical rotatory dispersion (1)
- parasite (1)
- passenger cars (1)
- passenger kilometers travelled (1)
- pedagogical agent (1)
- pellets (1)
- per capita carbon footprint (1)
- photobioreactor (1)
- physics (1)
- pichia pastoris (1)
- plastics recycling (1)
- plug-in hybrid cars (1)
- plug-in hybrid electric vehicle (1)
- pollinator (1)
- power curve anomalies (1)
- power curve health value (1)
- predator-prey (1)
- problem drinking (1)
- process analytics (1)
- product model (1)
- protease inhibitor (1)
- radiative forcing (1)
- real-world driving (1)
- real-world emissions (1)
- real-world life-cycle inventory (1)
- reinforcement learning algorithm (1)
- repeated-batch fermentation (1)
- research infrastructure (1)
- robot system (1)
- second harmonic generation (1)
- self organizing maps (SOM) (1)
- septic cardiomyopathy (1)
- sharp function (1)
- single-use application (1)
- single‐use bioreactor (1)
- site networks (1)
- small data (1)
- smoking cessation (1)
- social norms (1)
- soft constraints (1)
- soil temperature (1)
- soil-dwelling organisms (1)
- sporulation conditions (1)
- stable isotope analysis (1)
- strategy (1)
- students (1)
- sustainability education (1)
- sustainable mobility (1)
- sustainable road transport (1)
- tar (1)
- temperature offset (1)
- tensile strength (1)
- terrestrial cyanobacteria (1)
- text messaging (1)
- thermal performance (1)
- time series classification (1)
- time trend (1)
- tobacco (1)
- toxic emissions (1)
- traffic emissions (1)
- traffic modes (1)
- transport (1)
- trap selectivity (1)
- uncertainty (1)
- urban mobility (1)
- vehicle mass (1)
- vehicle power (1)
- vehicle size effect (1)
- ventilation (1)
- virtual physics lab (1)
- weather stations (1)
- web (1)
- well-to-wheels (1)
- wind turbine (1)
- Ökologie (1)
- π–π interaction (1)
Institut
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.
Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.
Hydrochar derived from Argan nut shell (ANS) was synthesized and applied to remove bisphenol A (BPA) and diuron. The results indicated that the hydrochar prepared at 200 °C (HTC@ANS-200) possessed a higher specific surface area (42 m2/g) than hydrochar (HTC@ANS-180) prepared at 180 °C (17 m2/g). The hydrochars exhibited spherical particles, which are rich in functional groups. The HTC@ANS-200 exhibited high adsorption efficiency, of about 92% of the BPA removal and 95% of diuron removal. The maximum Langmuir adsorption capacities of HTC@ANS-200 at room temperature were 1162.79 mg/for Bisphenol A and 833.33 mg/g for diuron (higher than most reported adsorbents). The adsorption process was spontaneous (− ΔG°) and exothermic (− ΔH°). Excellent reusability was reclaimed after five cycles, the removal efficiency showed a weak decrease of 4% for BPA and 1% for diuron. The analysis of Fourier transforms infrared spectrometry demonstrated that the aromatic C=C and OH played major roles in the adsorption mechanisms of BPA and diuron in this study. The high adsorption capacity was attributed to the beneficial porosity (The pore size of HTC@ANS-200 bigger than the size of BPA and diuron molecule) and surface functional groups. BPA and diuron adsorption occurred also via multiple adsorption mechanisms, including pore filling, π–π interactions, and hydrogen bonding interactions on HTC@ANS-200.
Since operational managers often monitor large numbers of wind turbines (WTs), they depend on a toolset to provide them with highly condensed information to identify and prioritize low performing WTs or schedule preventive maintenance measures. Power curves are a frequently used tool to assess the performance of WTs. The power curve health value (HV) used in this work is supposed to detect power curve anomalies since small deviations in the power curve are not easy to identify. It evaluates deviations in the linear region of power curves by performing a principal component analysis. To calculate the HV, the standard deviation in direction of the second principal component of a reference data set is compared to the standard deviation of a combined data set consisting of the reference data and data of the evaluated period. This article examines the applicability of this HV for different purposes as well as its sensitivities and provides a modified HV approach to make it more robust and suitable for heterogeneous data sets. The modified HV was tested based on ENGIE's open data wind farm and data of on- and offshore WTs from the WInD-Pool. It proved to detect anomalies in the linear region of the power curve in a reliable and sensitive manner and was also eligible to detect long term power curve degradation. Also, about 7 % of all corrective maintenance measures were preceded by high HVs with a median alarm horizon of three days. Overall, the HV proved to be a promising tool for various applications.
This paper presents a feasibility study for the production of recycled glycol modified polyethylene terephthalate (PETG) material for additive manufacturing. Past studies showed a variety of results for the recycling of 3D-printing material, therefore the precise effect on the material properties is not completely clear. For this work, PETG waste of the same grade was recycled once and further processed into 3D printing filament. The study compares three blend ratios between purchased plastic pellets and recycled pellets to determine the degradation effect of one recycling cycle and possible blend ratios to counter these effects. Furthermore, the results include a commercially available filament. The comparison uses the filament diameter, the dimensional accuracy of the printed test specimen and mechanical properties as quality criteria. The study shows that the recycled material has a minor decrease concerning the tensile strength and Young’s modulus.
Productive biofilms are gaining growing interest in research due to their potential of producing valuable compounds and bioactive substances such as antibiotics. This is supported by recent developments in biofilm photobioreactors that established the controlled phototrophic cultivation of algae and cyanobacteria. Cultivation of biofilms can be challenging due to the need of surfaces for biofilm adhesion. The total production of biomass, and thus production of e.g. bioactive substances, within the bioreactor volume highly depends on the available cultivation surface. To achieve an enlargement of surface area for biofilm photobioreactors, biocarriers can be implemented in the cultivation. Thereby, material properties and design of the biocarriers are important for initial biofilm formation and growth of cyanobacteria. In this study, special biocarriers were designed and additively manufactured to investigate different polymeric materials and surface designs regarding biofilm adhesion of the terrestrial cyanobacterium Nostoc flagelliforme (CCAP 1453/33). Properties of 3D-printed materials were characterized by determination of wettability, surface roughness, and density. To evaluate the influence of wettability on biofilm formation, material properties were specifically modified by gas-phase fluorination and biofilm formation was analyzed on biocarriers with basic and optimized geometry in shaking flask cultivation. We found that different polymeric materials revealed no significant differences in wettability and with identical surface design no significant effect on biomass adhesion was observed. However, materials treated with fluorination as well as optimized biocarrier design showed improved wettability and an increase in biomass adhesion per biocarrier surface.
We present the concrete realization of a virtual laboratory equipped with a pedagogical agent. Its functionality and media didactics takes into account the results of an usability test on a prototype system, and the students' demand on such an automated assistance as obtained from a preliminary survey. The pedagogical agent mediates between the content and the learner by activating him or her. To provide information about the learner's skills, we propose a pragmatic and simplified competence model that is based on fundamental representations in physics (experiment, figure, text and equation). Moreover, an automated feedback relates the student's self-assessment with the submitted answer to the correctness of the respective task. In consequence, the pedagogical agent enables mental reflection for a crucial review of the own learning process. Interestingly, learning pathways can be envisioned, thus, giving valuable insight into individual strengths and weaknesses.
Passenger cars in Europe have become both heavier and more powerful over the past decades. This trend has increased vehicle utility but it might have also offset technical improvements in powertrain efficiency. Here, we analyze efficiency trade-offs and CO2 emissions for three popular compact cars in Germany. We find that mass, power, and front area of model variants has increased by 66%, 147%, and 22%, respectively between 1980 and 2018. In the same period, fuel consumption decreased 14% for gasoline models but it increased 9% for diesel models. However, if vehicle mass, power, and front area had remained at 1980 levels, technical efficiency improvements would have decreased the fuel consumption of gasoline and diesel models by 23% and 24%, respectively. The related efficiency trade-offs amount to 24 g CO2/km or 13% of the current fuel consumption for gasoline models and 40 g CO2/km or 25% of the current fuel consumption for diesel models. These findings suggest that about half of the technical efficiency improvements in gasoline models and all of the technical efficiency improvements in diesel models are offset through other vehicle attributes. By accounting for the observed efficiency trade-offs, climate policy could become more effective.
Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15–91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.
The current work investigates the capability of a tailored multivariate curve resolution–alternating least squares (MCR-ALS) algorithm to analyse glucose, phosphate, ammonium and acetate dynamics simultaneously in an E. coli BL21 fed-batch fermentation. The high-cell-density (HCDC) process is monitored by ex situ online attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy and several in situ online process sensors. This approach efficiently utilises automatically generated process data to reduce the time and cost consuming reference measurement effort for multivariate calibration. To determine metabolite concentrations with accuracies between ±0.19 and ±0.96·gL−l, the presented utilisation needs primarily — besides online sensor measurements — single FTIR measurements for each of the components of interest. The ambiguities in alternating least squares solutions for concentration estimation are reduced by the insertion of analytical process knowledge primarily in the form of elementary carbon mass balances. Thus, in this way, the established idea of mass balance constraints in MCR combines with the consistency check of measured data by carbon balances, as commonly applied in bioprocess engineering. The constraints are calculated based on online process data and theoretical assumptions. This increased calculation effort is able to replace, to a large extent, the need for manually conducted quantitative chemical analysis, leads to good estimations of concentration profiles and a better process understanding.
This study introduced an automated long-term fermentation process for fungals grown in pellet form. The goal was to reduce the overgrowth of bioreactor internals and sensors while better rheological properties in the fermentation broth, such as oxygen transfer and mixing time, can be achieved. Because this could not be accomplished with continuous culture and fed-batch fermentation, repeated-batch fermentation was implemented with the help of additional bioreactor internals (“sporulation supports”). This should capture some biomass during fermentation. After harvesting the suspended biomass, intermediate cleaning was performed using a cleaning device. The biomass retained on the sporulation support went through the sporulation phase. The spores were subsequently used as inocula for the next batch. The reason for this approach was that the retained pellets could otherwise cause problems (e.g., overgrowth on sensors) in subsequent batches because the fungus would then show undesirable hyphal growth. Various sporulation supports were tested for sufficient biomass fixation to start the next batch. A reproducible spore concentration within the range of the requirements could be achieved by adjusting the sporulation support (design and construction material), and an intermediate cleaning adapted to this.
Background: In recent years, the volume of medical knowledge and health data has increased rapidly. For example, the increased availability of electronic health records (EHRs) provides accurate, up-to-date, and complete information about patients at the point of care and enables medical staff to have quick access to patient records for more coordinated and efficient care. With this increase in knowledge, the complexity of accurate, evidence-based medicine tends to grow all the time. Health care workers must deal with an increasing amount of data and documentation. Meanwhile, relevant patient data are frequently overshadowed by a layer of less relevant data, causing medical staff to often miss important values or abnormal trends and their importance to the progression of the patient’s case.
Objective: The goal of this work is to analyze the current laboratory results for patients in the intensive care unit (ICU) and classify which of these lab values could be abnormal the next time the test is done. Detecting near-future abnormalities can be useful to support clinicians in their decision-making process in the ICU by drawing their attention to the important values and focus on future lab testing, saving them both time and money. Additionally, it will give doctors more time to spend with patients, rather than skimming through a long list of lab values.
Methods: We used Structured Query Language to extract 25 lab values for mechanically ventilated patients in the ICU from the MIMIC-III and eICU data sets. Additionally, we applied time-windowed sampling and holding, and a support vector machine to fill in the missing values in the sparse time series, as well as the Tukey range to detect and delete anomalies. Then, we used the data to train 4 deep learning models for time series classification, as well as a gradient boosting–based algorithm and compared their performance on both data sets.
Results: The models tested in this work (deep neural networks and gradient boosting), combined with the preprocessing pipeline, achieved an accuracy of at least 80% on the multilabel classification task. Moreover, the model based on the multiple convolutional neural network outperformed the other algorithms on both data sets, with the accuracy exceeding 89%.
Conclusions: In this work, we show that using machine learning and deep neural networks to predict near-future abnormalities in lab values can achieve satisfactory results. Our system was trained, validated, and tested on 2 well-known data sets to ensure that our system bridged the reality gap as much as possible. Finally, the model can be used in combination with our preprocessing pipeline on real-life EHRs to improve patients’ diagnosis and treatment.
Species distribution models (SDMs) are key tools in biodiversity and conservation, but assessing their reliability in unsampled locations is difficult, especially where there are sampling biases. We present a spatially-explicit sensitivity analysis for SDMs – SDM profiling – which assesses the leverage that unsampled locations have on the overall model by exploring the interaction between the effect on the variable response curves and the prevalence of the affected environmental conditions. The method adds a ‘pseudo-presence’ and ‘pseudo-absence’ to unsampled locations, re-running the SDM for each, and measuring the difference between the probability surfaces of the original and new SDMs. When the standardised difference values are plotted against each other (a ‘profile plot’), each point's location can be summarized by four leverage measures, calculated as the distances to each corner. We explore several applications: visualization of model certainty; identification of optimal new sampling locations and redundant existing locations; and flagging potentially erroneous occurrence records.
This study compares the environmental impacts of petrol, diesel, natural gas, and electric vehicles using a process-based attributional life cycle assessment (LCA) and the ReCiPe characterization method that captures 18 impact categories and the single score endpoints. Unlike common practice, we derive the cradle-to-grave inventories from an originally combustion engine VW Caddy that was disassembled and electrified in our laboratory, and its energy consumption was measured on the road. Ecoivent 2.2 and 3.0 emission inventories were contrasted exhibiting basically insignificant impact deviations. Ecoinvent 3.0 emission inventory for the diesel car was additionally updated with recent real-world close emission values and revealed strong increases over four midpoint impact categories, when matched with the standard Ecoinvent 3.0 emission inventory. Producing batteries with photovoltaic electricity instead of Chinese coal-based electricity decreases climate impacts of battery production by 69%. Break-even mileages for the electric VW Caddy to pass the combustion engine models under various conditions in terms of climate change impact ranged from 17,000 to 310,000 km. Break-even mileages, when contrasting the VW Caddy and a mini car (SMART), which was as well electrified, did not show systematic differences. Also, CO2-eq emissions in terms of passenger kilometers travelled (54–158 g CO2-eq/PKT) are fairly similar based on 1 person travelling in the mini car and 1.57 persons in the mid-sized car (VW Caddy). Additionally, under optimized conditions (battery production and use phase utilizing renewable electricity), the two electric cars can compete well in terms of CO2-eq emissions per passenger kilometer with other traffic modes (diesel bus, coach, trains) over lifetime. Only electric buses were found to have lower life cycle carbon emissions (27–52 g CO2-eq/PKT) than the two electric passenger cars.
Ahmad et al. in their paper for the first time proposed to apply sharp function for classification of images. In continuation of their work, in this paper we investigate the use of sharp function as an edge detector through well known diffusion models. Further, we discuss the formulation of weak solution of nonlinear diffusion equation and prove uniqueness of weak solution of nonlinear problem. The anisotropic generalization of sharp operator based diffusion has also been implemented and tested on various types of images.
The number of additive manufacturing methods and materials is growing rapidly, leaving gaps in the knowledge of specific material properties. A relatively recent addition is the metal-filled filament to be printed similarly to the fused filament fabrication (FFF) technology used for plastic materials, but with additional debinding and sintering steps. While tensile, bending, and shear properties of metals manufactured this way have been studied thoroughly, their fatigue properties remain unexplored. Thus, the paper aims to determine the tensile, fatigue, and impact strengths of Markforged 17-4 PH and BASF Ultrafuse 316L stainless steel to answer whether the metal FFF can be used for structural parts safely with the current state of technology. They are compared to two 316L variants manufactured via selective laser melting (SLM) and literature results. For extrusion-based additive manufacturing methods, a significant decrease in tensile and fatigue strength is observed compared to specimens manufactured via SLM. Defects created during the extrusion and by the pathing scheme, causing a rough surface and internal voids to act as local stress risers, handle the strength decrease. The findings cast doubt on whether the metal FFF technique can be safely used for structural components; therefore, further developments are needed to reduce internal material defects.
A new comprehensive evaluation system presented here allows to compare and to quantify education for a sustainable development (ESD) in degree programs. The evaluation is based on a criteria system working with three hierarchic levels. The highest level considers a list of 35 indicator terms. Primarily, the two most popular undergraduate (bachelor’s) degree programs in Germany (mechanical engineering, ME, and business administration, BA) have been reviewed for ESD contents based on the new evaluation scheme. Additionally we reviewed and quantified ESD subjects and their temporal changes in the entire bandwidth of degree programs of a university (Umwelt-Campus Birkenfeld, University of Applied Sciences Trier), back to 1999. Moreover, a spot check on international ME and BA bachelor’s degree programs was performed. Through our reviews, we found a high number of elective classes dedicated to ESD particularly in BA bachelor programs. However, the percentage of compulsory classes related to ESD is relatively low with 5-6 % in both ME and BA programs, respectively. The spot check on degree programs outside Germany revealed similar results. Analysing the time trend at Umwelt-Campus Birkenfeld, a considerable share of ESD that was part of the original diploma degrees was moved to what are now master’s degrees.
1. Among the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators, pest control agents, and as a food source. Few insect monitoring programmes cover the large spatial scales required to provide more generalizable estimates of insect responses to global change drivers.
2. We ask how climate and surrounding habitat affect flying insect biomass using data from the first year of a new monitoring network at 84 locations across Germany comprising a spatial gradient of land cover types from protected to urban and crop areas.
3. Flying insect biomass increased linearly with temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages.
4. Land cover explained little variation in insect biomass, but biomass was lowest in forests. Grasslands, pastures, and orchards harboured the highest insect biomass. The date of peak biomass was primarily driven by surrounding land cover, with grasslands especially having earlier insect biomass phenologies.
5. Standardised, large-scale monitoring provides key insights into the underlying processes of insect decline and is pivotal for the development of climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the positive effects of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. Our results highlight the importance of local adaptation in climate change-driven impacts on insect communities.
Global change effects on biodiversity and human wellbeing call for improved long-term environmental data as a basis for science, policy and decision making, including increased interoperability, multifunctionality, and harmonization. Based on the example of two global initiatives, the International Long-Term Ecological Research (ILTER) network and the Group on Earth Observations Biodiversity Observation Network (GEO BON), we propose merging the frameworks behind these initiatives, namely ecosystem integrity and essential biodiversity variables, to serve as an improved guideline for future site-based long-term research and monitoring in terrestrial, freshwater and coastal ecosystems. We derive a list of specific recommendations of what and how to measure at a monitoring site and call for an integration of sites into co-located site networks across individual monitoring initiatives, and centered on ecosystems. This facilitates the generation of linked comprehensive ecosystem monitoring data, supports synergies in the use of costly infrastructures, fosters cross-initiative research and provides a template for collaboration beyond the ILTER and GEO BON communities.
Many borate crystals feature nonlinear optical properties that allow for efficient frequency conversion of common lasers down into the ultraviolet spectrum. Twinning may degrade crystal quality and affect nonlinear optical properties, in particular if crystals are composed of twin domains with opposing polarities. Here, we use measurements of optical activity to demonstrate the existence of inversion twins within single crystals of YAl3(BO3)4 (YAB) and K2Al2B2O7 (KABO). We determine the optical rotatory dispersion of YAB and KABO throughout the visible spectrum using a spectrophotometer with rotatable polarizers. Space-resolved measurements of the optical rotation can be related to the twin structure and give estimates on the extent of twinning. The reported dispersion relations for the rotatory power of YAB and KABO may be used to assess crystal quality and to select twin-free specimens.