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Now showing 1 - 10 of 130
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    Time‐Dependent Cation Selectivity of Titanium Carbide MXene in Aqueous Solution
    (Weinheim : Wiley-VCH, 2022) Wang, Lei; Torkamanzadeh, Mohammad; Majed, Ahmad; Zhang, Yuan; Wang, Qingsong; Breitung, Ben; Feng, Guang; Naguib, Michael; Presser, Volker
    Electrochemical ion separation is a promising technology to recover valuable ionic species from water. Pseudocapacitive materials, especially 2D materials, are up-and-coming electrodes for electrochemical ion separation. For implementation, it is essential to understand the interplay of the intrinsic preference of a specific ion (by charge/size), kinetic ion preference (by mobility), and crystal structure changes. Ti3C2Tz MXene is chosen here to investigate its selective behavior toward alkali and alkaline earth cations. Utilizing an online inductively coupled plasma system, it is found that Ti3C2Tz shows a time-dependent selectivity feature. In the early stage of charging (up to about 50 min), K+ is preferred, while ultimately Ca2+ and Mg2+ uptake dominate; this unique phenomenon is related to dehydration energy barriers and the ion exchange effect between divalent and monovalent cations. Given the wide variety of MXenes, this work opens the door to a new avenue where selective ion-separation with MXene can be further engineered and optimized.
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    BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data
    (Sofia : Pensoft Publishers, 2021) Chamanara, Javad; Gaikwad, Jitendra; Gerlach, Roman; Algergawy, Alsayed; Ostrowski, Andreas; König-Ries, Birgitta
    Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research.
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    Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests
    (Katlenburg-Lindau : European Geosciences Union, 2021) Sakschewski, Boris; Bloh, Werner von; Drüke, Markus; Sörensson, Anna Amelia; Ruscica, Romina; Langerwisch, Fanny; Billing, Maik; Bereswill, Sarah; Hirota, Marina; Oliveira, Rafael Silva; Heinke, Jens; Thonicke, Kirsten
    A variety of modelling studies have suggested tree rooting depth as a key variable to explain evapotranspiration rates, productivity and the geographical distribution of evergreen forests in tropical South America. However, none of those studies have acknowledged resource investment, timing and physical constraints of tree rooting depth within a competitive environment, undermining the ecological realism of their results. Here, we present an approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 (Lund-Potsdam-Jena managed Land) dynamic global vegetation model (DGVM) and apply it to tropical and sub-tropical South America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulation of intra-annual productivity and evapotranspiration and consequently of forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and below-ground biomass across the study region. Our findings support the hypothesis that the ability of evergreen trees to adjust their rooting systems to seasonally dry climates is crucial to explaining the current dominance, productivity and evapotranspiration of evergreen forests in tropical South America.
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    Surface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients
    (Basel : MDPI, 2021) Osei, Eric Boateng; Paniushkina, Liliia; Wilhelm, Konrad; Popp, Jürgen; Nazarenko, Irina; Krafft, Christoph
    Extracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.
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    Denoising for Improved Parametric MRI of the Kidney: Protocol for Nonlocal Means Filtering
    (Totowa, NJ : Humana Press, 2021) Starke, Ludger; Tabelow, Karsten; Niendorf, Thoralf; Pohlmann, Andreas; Pohlmann, Andreas; Niendorf, Thoralf
    In order to tackle the challenges caused by the variability in estimated MRI parameters (e.g., T2* and T2) due to low SNR a number of strategies can be followed. One approach is postprocessing of the acquired data with a filter. The basic idea is that MR images possess a local spatial structure that is characterized by equal, or at least similar, noise-free signal values in vicinities of a location. Then, local averaging of the signal reduces the noise component of the signal. In contrast, nonlocal means filtering defines the weights for averaging not only within the local vicinity, bur it compares the image intensities between all voxels to define “nonlocal” weights. Furthermore, it generally compares not only single-voxel intensities but small spatial patches of the data to better account for extended similar patterns. Here we describe how to use an open source NLM filter tool to denoise 2D MR image series of the kidney used for parametric mapping of the relaxation times T2* and T2. This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
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    Effect of Fans’ Placement on the Indoor Thermal Environment of Typical Tunnel-Ventilated Multi-Floor Pig Buildings Using Numerical Simulation
    (Basel : MDPI AG, 2022) Wang, Xiaoshuai; Cao, Mengbing; Hu, Feiyue; Yi, Qianying; Amon, Thomas; Janke, David; Xie, Tian; Zhang, Guoqiang; Wang, Kaiying
    An increasing number of large pig farms are being built in multi-floor pig buildings (MFPBs) in China. Currently, the ventilation system of MFPB varies greatly and lacks common standards. This work aims to compare the ventilation performance of three popular MFPB types with different placement of fans using the Computational Fluid Dynamics (CFD) technique. After being validated with field-measured data, the CFD models were extended to simulate the air velocity, air temperature, humidity, and effective temperature of the three MFPBs. The simulation results showed that the ventilation rate of the building with outflowing openings in the endwall and fans installed on the top of the shaft was approximately 25% less than the two buildings with fans installed on each floor. The ventilation rate of each floor increased from the first to the top floor for both buildings with a shaft, while no significant difference was observed in the building without a shaft. Increasing the shaft’s width could mitigate the variation in the ventilation rate of each floor. The effective temperature distribution at the animal level was consistent with the air velocity distribution. Therefore, in terms of the indoor environmental condition, the fans were recommended to be installed separately on each floor.
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    Impact of Camera Viewing Angle for Estimating Leaf Parameters of Wheat Plants from 3D Point Clouds
    (Basel : MDPI, 2021) Li, Minhui; Shamshiri, Redmond R.; Schirrmann, Michael; Weltzien, Cornelia
    Estimation of plant canopy using low-altitude imagery can help monitor the normal growth status of crops and is highly beneficial for various digital farming applications such as precision crop protection. However, extracting 3D canopy information from raw images requires studying the effect of sensor viewing angle by taking into accounts the limitations of the mobile platform routes inside the field. The main objective of this research was to estimate wheat (Triticum aestivum L.) leaf parameters, including leaf length and width, from the 3D model representation of the plants. For this purpose, experiments with different camera viewing angles were conducted to find the optimum setup of a mono-camera system that would result in the best 3D point clouds. The angle-control analytical study was conducted on a four-row wheat plot with a row spacing of 0.17 m and with two seeding densities and growth stages as factors. Nadir and six oblique view image datasets were acquired from the plot with 88% overlapping and were then reconstructed to point clouds using Structure from Motion (SfM) and Multi-View Stereo (MVS) methods. Point clouds were first categorized into three classes as wheat canopy, soil background, and experimental plot. The wheat canopy class was then used to extract leaf parameters, which were then compared with those values from manual measurements. The comparison between results showed that (i) multiple-view dataset provided the best estimation for leaf length and leaf width, (ii) among the single-view dataset, canopy, and leaf parameters were best modeled with angles vertically at -45⸰_ and horizontally at 0⸰_ (VA -45, HA 0), while (iii) in nadir view, fewer underlying 3D points were obtained with a missing leaf rate of 70%. It was concluded that oblique imagery is a promising approach to effectively estimate wheat canopy 3D representation with SfM-MVS using a single camera platform for crop monitoring. This study contributes to the improvement of the proximal sensing platform for crop health assessment. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    The Effect of Diet and Farm Management on N2O Emissions from Dairy Farms Estimated from Farm Data
    (Basel : MDPI, 2021) Menardo, Simona; Lanza, Giacomo; Berg, Werner
    The N2O emissions of 21 dairy farms in Germany were evaluated to determine the feasi-bility of an estimation of emissions from farm data and the effects of the farm management, along with possible mitigation strategies. Emissions due to the application of different fertilisers, manure storage and grazing were calculated based on equations from the IPCC (Intergovernmental Panel of Climate Change) and German emission inventory. The dependence of the N2O emissions on fertiliser type and quantity, cultivated crops and diet composition was assessed via correlation analysis and linear regression. The N2O emissions ranged between 0.11 and 0.29 kg CO2eq per kilogram energy-corrected milk, with on average 60% resulting from fertilisation and less than 30% from fertiliser storage and field applications. The total emissions had a high dependence on the diet composition; in particular, on the grass/maize ratio and the protein content of the animal diet, as well as from the manure management. A linear model for the prediction of the N2O emissions based on the diet composition and the fertilisation reached a predictive power of R2 = 0.89. As a possible mitigation strategy, the substitution of slurry for solid manure would reduce N2O emissions by 40%. Feeding cows maize-based diets instead of grass-based diets could reduce them by 14%. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    Self-Adhesive Silicone Microstructures for the Treatment of Tympanic Membrane Perforations
    (Weinheim : Wiley-VCH, 2021) Lana, Gabriela Moreira; Sorg, Katharina; Wenzel, Gentiana Ioana; Hecker, Dietmar; Hensel, René; Schick, Bernhard; Kruttwig, Klaus; Arzt, Eduard
    Inspired by the gecko foot, polymeric microstructures have demonstrated reliable dry adhesion to both stiff objects and sensitive surfaces such as skin. Microstructured silicone patches are proposed, herein, for the treatment of tympanic membrane perforations with the aim of serving as an alternative for current surgical procedures that require anesthesia and ear canal packing. Sylgard 184 PDMS micropillars of 20 μm in diameter and 60 μm in length are topped by a Soft Skin Adhesive (SSA) MG7-1010 terminal layer, of about 25 μm thickness. The adhesion is evaluated by specially designed tack tests against explanted murine eardrums and, for comparison, against a rigid substrate. Functional effects are evaluated using auditory brainstem responses (ABRs) and distortion product otoacoustic emissions (DPOAE). The adhesion strength of the microstructure and unstructured controls to explanted murine tympanic membranes is comparable (typically 12 kPa), but the microstructured patches are easier to handle by the surgeon. For the first time, partial recovery of hearing performance is measured immediately after patch application. The novel patches adhere without the need for further fixation, removing the need for ear canal packing. The proposed material design holds great promise for improving clinical treatments of tympanic membrane perforations.
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    Curvature model for nanoparticle size effects on peptide fibril stability and molecular dynamics simulation data
    (Amsterdam [u.a.] : Elsevier, 2022) John, Torsten; Martin, Lisandra L.; Risselada, Herre Jelger; Abel, Bernd
    Nanostructured surfaces are widespread in nature and are being further developed in materials science. This makes them highly relevant for biomolecules, such as peptides. In this data article, we present a curvature model and molecular dynamics (MD) simulation data on the influence of nanoparticle size on the stability of amyloid peptide fibrils related to our research article entitled “Mechanistic insights into the size-dependent effects of nanoparticles on inhibiting and accelerating amyloid fibril formation” (John et al., 2022) [1]. We provide the code to perform MD simulations in GROMACS 4.5.7 software of arbitrarily chosen biomolecule oligomers adsorbed on a curved surface of chosen nanoparticle size. We also provide the simulation parameters and data for peptide oligomers of Aß40, NNFGAIL, GNNQQNY, and VQIYVK. The data provided allows researchers to further analyze our MD simulations and the curvature model allows for a better understanding of oligomeric structures on surfaces.