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  • 1
    Online Resource
    Online Resource
    MDPI AG ; 2023
    In:  Water Vol. 15, No. 3 ( 2023-02-03), p. 604-
    In: Water, MDPI AG, Vol. 15, No. 3 ( 2023-02-03), p. 604-
    Abstract: Flooding is a recurring natural disaster worldwide; developing countries are particularly affected due to poor mitigation and management strategies. Often discharge is used to inform the flood forecast. The discharge is usually inferred from the water level via the rating curve because the latter is relatively easy to measure compared to the former. This research focuses on Cambodia, where data scarcity is prevalent, as in many developing countries. Thus, the rating curve has not been updated, making it difficult to effectively evaluate the performance of the global streamflow services, such as the Global Flood Awareness System (GloFAS) and Streamflow Prediction Tool (SPT), whose longer lead time can benefit the country in taking early action. In this study, we used time series of water level and discharge data to understand the changes in the flood plain to generate a data-derived rating curve for fifteen stations in Cambodia. We deployed several statistical and data-driven techniques to derive a generalized, scalable, and region-agnostic method. We further validated the process by applying it to ten stations in the US and found similar performance. In Cambodia, we obtained an average Kling Gupta Efficiency (KGE) of ∼99% & an average Relative Root Mean Squared Error (RRMSE) of 12% with an average Mean Absolute Error (MAE) of 200 m3/s. In the US, overall KGE was 97%, with an average RRMSE of 17% and an average MAE of 32 m3/s. The results indicated that the distribution of the dataset was key in deriving a good rating curve and that the stations with a low flow stations generally had higher errors than the high flow stations. The time series approach was shown to have more probability in capturing the high-end and low-end events compared to traditional method, where usually fewer data points are used. The study demonstrates that time series of data has valuable information to update the rating curve, especially in a data-scarce country.
    Type of Medium: Online Resource
    ISSN: 2073-4441
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2521238-2
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  • 2
    In: Remote Sensing, MDPI AG, Vol. 12, No. 15 ( 2020-08-01), p. 2469-
    Abstract: Satellite remote sensing plays an important role in the monitoring of surface water for historical analysis and near real-time applications. Due to its cloud penetrating capability, many studies have focused on providing efficient and high quality methods for surface water mapping using Synthetic Aperture Radar (SAR). However, few studies have explored the effects of SAR pre-processing steps used and the subsequent results as inputs into surface water mapping algorithms. This study leverages the Google Earth Engine to compare two unsupervised histogram-based thresholding surface water mapping algorithms utilizing two distinct pre-processed Sentinel-1 SAR datasets, specifically one with and one without terrain correction. The resulting surface water maps from the four different collections were validated with user-interpreted samples from high-resolution Planet Scope data. It was found that the overall accuracy from the four collections ranged from 92% to 95% with Cohen’s Kappa coefficients ranging from 0.7999 to 0.8427. The thresholding algorithm that samples a histogram based on water edge information performed best with a maximum accuracy of 95%. While the accuracies varied between methods it was found that there is no statistical significant difference between the errors of the different collections. Furthermore, the surface water maps generated from the terrain corrected data resulted in a intersection over union metrics of 95.8%–96.4%, showing greater spatial agreement, as compared to 92.3%–93.1% intersection over union using the non-terrain corrected data. Overall, it was found that algorithms using terrain correction yield higher overall accuracy and yielded a greater spatial agreement between methods. However, differences between the approaches presented in this paper were not found to be significant suggesting both methods are valid for generating accurate surface water maps. High accuracy surface water maps are critical to disaster planning and response efforts, thus results from this study can help inform SAR data users on the pre-processing steps needed and its effects as inputs on algorithms for surface water mapping applications.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 3
    In: Cancers, MDPI AG, Vol. 14, No. 3 ( 2022-02-01), p. 762-
    Abstract: Cancer is the leading cause of death by disease in children, and over 15% of pediatric cancer-related mortalities are due to neuroblastoma. Current treatment options for neuroblastoma remain suboptimal as they often have significant toxicities, are associated with long-term side effects, and result in disease relapse in over half of children with high-risk disease. There is a dire need for new therapies, and oncolytic viruses may represent an effective solution. Oncolytic viruses attack tumor cells in two ways: direct infection of tumor cells leading to cytolysis, and production of a debris field that stimulates an anti-tumor immune response. Our group has previously shown that M002, an oncolytic herpes simplex virus (oHSV), genetically engineered to express murine interleukin-12 (mIL-12), was effective at targeting and killing long term passage tumor cell lines. In the current study, we investigated M002 in three neuroblastoma patient-derived xenografts (PDXs). PDXs better recapitulate the human condition, and these studies were designed to gather robust data for translation to a clinical trial. We found that all three PDXs expressed viral entry receptors, and that the virus actively replicated in the cells. M002 caused significant tumor cell death in 2D culture and 3D bioprinted tumor models. Finally, the PDXs displayed variable susceptibility to M002, with a more profound effect on high-risk neuroblastoma PDXs compared to low-risk PDX. These findings validate the importance of incorporating PDXs for preclinical testing of oncolytic viral therapeutics and showcase a novel technique, 3D bioprinting, to test therapies in PDXs. Collectively, our data indicate that oHSVs effectively target high-risk neuroblastoma, and support the advancement of this therapy to the clinical setting.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 4
    In: Metals, MDPI AG, Vol. 7, No. 12 ( 2017-12-10), p. 556-
    Type of Medium: Online Resource
    ISSN: 2075-4701
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2662252-X
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  • 5
    Online Resource
    Online Resource
    MDPI AG ; 2018
    In:  Metals Vol. 8, No. 9 ( 2018-08-29), p. 679-
    In: Metals, MDPI AG, Vol. 8, No. 9 ( 2018-08-29), p. 679-
    Abstract: The focus of the present work is to develop a deep understanding of deformation of stacked metal sheets with a series of different sequences by using shock wave loading. Here, experimental and numerical investigations of deformation of a single metal sheet of 1.5-mm and the stack of three metal sheets of 0.5-mm thickness of aluminum (Al), copper (Cu) and brass (Br) material were carried out. In the shock wave experiments, helium was used as the driving gas to produce a strong shock wave. Finite elements method (FEM) simulations on 3D-computational models were performed with explicit dynamic analysis, and Johnson-Cook material model was used. The obtained results from experiments of the outer diameter, thickness distribution, and dome height were analyzed and compared with the numerical simulations, and both the results are in excellent agreement. Moreover, for the same pressure load, due to lower inter-metallic friction in the stacked sheets compared to a cohesive property of the single sheet, an excellent deformation of stacked metallic sheets was observed. The results of this work indicated that the shock wave-forming process is a feasible technique for mass production of stacked metallic sheets as well as fabricating a hierarchical composite structure, which provides higher formability and smooth thickness distribution compared to a single material.
    Type of Medium: Online Resource
    ISSN: 2075-4701
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2662252-X
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  • 6
    Online Resource
    Online Resource
    MDPI AG ; 2018
    In:  Metabolites Vol. 8, No. 1 ( 2018-02-07), p. 12-
    In: Metabolites, MDPI AG, Vol. 8, No. 1 ( 2018-02-07), p. 12-
    Type of Medium: Online Resource
    ISSN: 2218-1989
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2662251-8
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  • 7
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  International Journal of Molecular Sciences Vol. 22, No. 23 ( 2021-12-05), p. 13149-
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 22, No. 23 ( 2021-12-05), p. 13149-
    Abstract: The transport of drugs across the placenta is a point of great importance in pharmacotherapy during pregnancy. However, the knowledge of drug transport in pregnancy is mostly based on experimental clinical data, and the underlying biological mechanisms are not fully understood. In this review, we summarize the current knowledge of drug transporters in the human placenta. We only refer to human data since the placenta demonstrates great diversity among species. In addition, we describe the experimental models that have been used in human placental transport studies and discuss their availability. A better understanding of placental drug transporters will be beneficial for the health of pregnant women who need drug treatment and their fetuses.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 8
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 2 ( 2022-01-07), p. 581-
    In: Applied Sciences, MDPI AG, Vol. 12, No. 2 ( 2022-01-07), p. 581-
    Abstract: The evaluation of structural response constitutes a fundamental task in the design of ground-excited structures. In this context, the Monte Carlo simulation is a powerful tool to estimate the response statistics of nonlinear systems, which cannot be represented analytically. Unfortunately, the number of samples which is required for estimations with high confidence increases disproportionally to obtain a reliable estimation of low-probability events. As a consequence, the Monte Carlo simulation becomes a non-realizable task from a computational perspective. We show that the application of machine learning algorithms significantly lowers the computational burden of the Monte Carlo method. We use artificial neural networks to predict structural response behavior using supervised learning. However, one shortcoming of supervised learning is the inability of a sufficiently accurate prediction when extrapolating to data the neural network has not seen yet. In this paper, neural networks predict the response of structures subjected to non-stationary ground excitations. In doing so, we propose a novel selection process for the training data to provide the required samples to reliably predict rare events. We, finally, prove that the new strategy results in a significant improvement of the prediction of the response statistics in the tail end of the distribution.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 9
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  Journal of Marine Science and Engineering Vol. 10, No. 7 ( 2022-07-01), p. 914-
    In: Journal of Marine Science and Engineering, MDPI AG, Vol. 10, No. 7 ( 2022-07-01), p. 914-
    Abstract: Geotechnical data are increasingly utilized to aid investigations of coastal erosion and the development of coastal morphological models; however, measurement techniques are still challenged by environmental conditions and accessibility in coastal areas, and particularly, by nearshore conditions. These challenges are exacerbated for Arctic coastal environments. This article reviews existing and emerging data collection methods in the context of geotechnical investigations of Arctic coastal erosion and nearshore change. Specifically, the use of cone penetration testing (CPT), which can provide key data for the mapping of soil and ice layers as well as for the assessment of slope and block failures, and the use of free-fall penetrometers (FFPs) for rapid mapping of seabed surface conditions, are discussed. Because of limitations in the spatial coverage and number of available in situ point measurements by penetrometers, data fusion with geophysical and remotely sensed data is considered. Offshore and nearshore, the combination of acoustic surveying with geotechnical testing can optimize large-scale seabed characterization, while onshore most recent developments in satellite-based and unmanned-aerial-vehicle-based data collection offer new opportunities to enhance spatial coverage and collect information on bathymetry and topography, amongst others. Emphasis is given to easily deployable and rugged techniques and strategies that can offer near-term opportunities to fill current gaps in data availability. This review suggests that data fusion of geotechnical in situ testing, using CPT to provide soil information at deeper depths and even in the presence of ice and using FFPs to offer rapid and large-coverage geotechnical testing of surface sediments (i.e., in the upper tens of centimeters to meters of sediment depth), combined with acoustic seabed surveying and emerging remote sensing tools, has the potential to provide essential data to improve the prediction of Arctic coastal erosion, particularly where climate-driven changes in soil conditions may bias the use of historic observations of erosion for future prediction.
    Type of Medium: Online Resource
    ISSN: 2077-1312
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2738390-8
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  • 10
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 20, No. 1 ( 2019-01-07), p. 194-
    Abstract: N-glycosylation has been shown to affect the pharmacokinetic properties of several classes of biologics, including monoclonal antibodies, blood factors, and lysosomal enzymes. In the last two decades, N-glycan engineering has been employed to achieve a N-glycosylation profile that is either more consistent or aligned with a specific improved activity (i.e., effector function or serum half-life). In particular, attention has focused on engineering processes in vivo or in vitro to alter the structure of the N-glycosylation of the Fc region of anti-cancer monoclonal antibodies in order to increase antibody-dependent cell-mediated cytotoxicity (ADCC). Here, we applied the mannosidase I inhibitor kifunensine to the Nicotiana benthamiana transient expression platform to produce an afucosylated anti-CD20 antibody (rituximab). We determined the optimal concentration of kifunensine used in the infiltration solution, 0.375 µM, which was sufficient to produce exclusively oligomannose glycoforms, at a concentration 14 times lower than previously published levels. The resulting afucosylated rituximab revealed a 14-fold increase in ADCC activity targeting the lymphoma cell line Wil2-S when compared with rituximab produced in the absence of kifunensine. When applied to the cost-effective and scalable N. benthamiana transient expression platform, the use of kifunensine allows simple in-process glycan engineering without the need for transgenic hosts.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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