Improved Formula for Predicting Hemodialyzability of Intravenous and Oral Drugs

2021 ◽  
pp. 1-11
Author(s):  
Marina Murakami ◽  
Yuki Narita ◽  
Motoki Urata ◽  
Misato Ichigi ◽  
Sakura Nakatani ◽  
...  
Keyword(s):  
Test Data ◽  
Removal Rate ◽  
Training Data ◽  
Physical Parameters ◽  
Regression Analyses ◽  
Oral Drugs ◽  
Removal Rates ◽  
Binding Rate ◽  
Drug Removal ◽  
Data Group

Background: The rate of drug removal by hemodialysis needs to be considered when designing drug dosage regimens for patients on hemodialysis. We previously developed a simplified equation to predict the removal rates of intravenously administered drugs by hemodialysis. Here, we addressed shortcomings of this equation and developed a more accurate equation that can also predict the removal rates of orally administered drugs. Methods: A total of 70 drugs with known pharmacokinetic and physical parameters and drug removal rates that were measured during hemodialysis in clinical cases were randomly assigned at a 4:1 ratio to a training data group or a test data group. A prediction equation was developed by performing stepwise multiple regression analyses using the training data (i.e., the removal rate by hemodialysis) as the objective variable and pharmacokinetic parameters as the explanatory variables. The equation was validated using the test data. Results: Multiple regression analyses revealed that molecular weight (MW), protein binding rate, and fraction excreted unchanged in urine relative to the volume of distribution (Vd) were independently correlated with the drug clearance rate (adjusted coefficient of determination, 0.83; p = 2.2e−16). The following equation was obtained: drug removal rate by hemodialysis (%) = −17.32 × [log (MW)] – 0.39 × [protein binding rate (%)] + 0.06 × [fraction excreted unchanged in urine (%)/Vd (L/kg)] + 83.34. Validation of the equation using the test data showed a very high correlation between predicted and measured reduction rate (R = 0.93, p = 1.87e−6). Mean error was −3.34 (95% confidence interval: −10.03, 3.35), mean absolute error was 9.59, and root mean square error was 16.48. Conclusion: The modified equation derived in this study using pharmacokinetic and physical parameters as variables precisely predicted the removal rates of both intravenous and oral drugs by hemodialysis.

Analysis of organic removal rates in the aerated submerged fixed film process

1998 ◽  
Vol 38 (8-9) ◽  
pp. 213-221 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain
Keyword(s):  
Pilot Plant ◽  
Removal Rate ◽  
Domestic Wastewater ◽  
Removal Rates ◽  
Hydraulic Loading ◽  
Organic Removal ◽  
Wide Range ◽  
Fixed Film ◽  
Cod Removal Rate ◽  
And Performance

Performance data from a pilot-plant employing the four-stage aerated submerged fixed film (ASFF) process treating domestic wastewater were analyzed to examine the organic removal rates. The process has shown high BOD removal efficiencies (> 90%) over a wide range of hydraulic loading rates (0.04 to 0.68 m3/m2·d). It could also cope with high hydraulic and organic loadings with minimal loss in efficiency due to the large amount of immobilized biomass attained. The organic (BOD and COD) removal rate was influenced by the hydraulic loadings applied, but organic removal rates of up to 104 kg BOD/ m2·d were obtained at a hydraulic loading rate of 0.68 m3/m2·d. A Semi-empirical model for the bio-oxidation of organics in the ASFF process has been formulated and rate constants were calculated based on statistical analysis of pilot-plant data. The relationships obtained are very useful for analyzing the design and performance of the ASFF process and a variety of attached growth processes.

The comparison of trichloroethylene removal rates by methane- and aromatic-utilizing microorganisms

1998 ◽  
Vol 38 (7) ◽  
pp. 19-24 ◽  
Author(s):  
C.-J. Lu ◽  
C. M. Lee ◽  
M.-S. Chung
Keyword(s):  
Cell Concentration ◽  
Removal Rate ◽  
Carbon Sources ◽  
Batch Reactors ◽  
Initial Cell Concentration ◽  
Removal Rates ◽  
Initial Cell ◽  
Toluene Concentration ◽  
Cell Source ◽  
Removal Efficiencies

The comparison of TCE cometabolic removal by methane, toluene, and phenol utilizers was conducted with a series of batch reactors. Methane, toluene, or phenol enriched microorganisms were used as cell source. The initial cell concentration was about 107 cfu/mL. Methane, toluene, and phenol could be readily biodegraded resulting in the cometabolic removal of TCE. Among the three primary carbon sources studied, the presence of phenol provided the best cometabolic removal of TCE. When the concentration of carbon source was 3 mg-C/L, the initial TCE removal rates initiated by methane, toluene, and phenol utilizers were 1.5, 30, and 100 μg/L-hr, respectively. During the incubation period of 80 hours, TCE removal efficiencies were 26% and 96% with the presence of methane and toluene, respectively. However, it was 100% within 20 hours with the presence of phenol. For phenol utilizers, the initial TCE removal rates were about the same, when the phenol concentrations were 1.35, 2.7, and 4.5 mg/L. However, TCE removal was not proportional to the concentrations of phenol. TCE removal was hindered when the phenol concentration was higher than 4.5 mg/L because of the rapid depletion of dissolved oxygen. The presence of toluene also initiated cometabolic removal of TCE. The presence of toluene at 3 and 5 mg/L resulted in similar TCE removal. The initial TCE removal rate was about 95 μg/L-hr at toluene concentrations of 3 and 5 mg/L compared to 20 μg/L-hr at toluene concentration of 1 mg/L.

Relations between carbon removal rates, biofilm size and density of a novel anaerobic reactor: the inverse turbulent bed

2000 ◽  
Vol 41 (4-5) ◽  
pp. 253-260 ◽  
Author(s):  
P. Buffière ◽  
R. Moletta
Keyword(s):  
Removal Rate ◽  
Removal Rates ◽  
Carbon Removal ◽  
Biofilm Growth ◽  
Loading Rates ◽  
Biomass Activity ◽  
High Turbulence ◽  
The One ◽  
High Level ◽  
Very High

An anaerobic inverse turbulent bed, in which the biogas only ensures fluidisation of floating carrier particles, was investigated for carbon removal kinetics and for biofilm growth and detachment. The range of operation of the reactor was kept within 5 and 30 kgCOD· m−3· d−1, with Hydraulic Retention Times between 0.28 and 1 day. The carbon removal efficiency remained between 70 and 85%. Biofilm size were rather low (between 5 and 30 μm) while biofilm density reached very high values (over 80 kgVS· m−3). The biofilm size and density varied with increasing carbon removal rates with opposite trends; as biofilm size increases, its density decreases. On the one hand, biomass activity within the reactor was kept at a high level, (between 0.23 and 0.75 kgTOC· kgVS· d−1, i.e. between 0.6 and 1.85 kgCOD·kgVS · d−1).This result indicates that high turbulence and shear may favour growth of thin, dense and active biofilms. It is thus an interesting tool for biomass control. On the other hand, volatile solid detachment increases quasi linearly with carbon removal rate and the total amount of solid in the reactor levels off at high OLR. This means that detachment could be a limit of the process at higher organic loading rates.

scholarly journals Analysis of the Physical Properties of Seeds of Selected Viburnum Species for the Needs of Seed Sorting Operations

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 711
Author(s):  
Zdzisław Kaliniewicz ◽  
Dariusz J. Choszcz
Keyword(s):  
Physical Properties ◽  
Ornamental Plants ◽  
Seed Mass ◽  
Terminal Velocity ◽  
Landscape Design ◽  
Physical Parameters ◽  
Regression Analyses ◽  
Uniform Size ◽  
Size Fractions ◽  
Physical Attributes

Viburnum is a genus of colorful and ornamental plants popular in landscape design on account of their high esthetic appeal. The physical properties of viburnum seeds have not been investigated in the literature to date. Therefore, the aim of this study was to characterize the seeds of selected Viburnum species and to search for potential relationships between their physical attributes for the needs of seed sorting operations. The basic physical parameters of the seeds of six Viburnum species were measured, and the relationships between these attributes were determined in correlation and regression analyses. The average values of the evaluated parameters were determined in the following range: terminal velocity—from 5.6 to 7.9 m s−1, thickness—from 1.39 to 1.87 mm, width—from 3.59 to 6.33 mm, length—from 5.58 to 7.44 mm, angle of external friction—from 36.7 to 43.8°, mass—from 16.7 to 35.0 mg. The seeds of V. dasyanthum, V. lentago and V. sargentii should be sorted in air separators, and the seeds of V. lantana and V. opulus should be processed with the use of mesh screens with round apertures to obtain uniform size fractions. The seeds of V. rhytodophyllum cannot be effectively sorted into batches with uniform seed mass, but they can be separated into groups with similar dimensions.

scholarly journals New polyp image classification technique using transfer learning of network-in-network structure in endoscopic images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Young Jae Kim ◽  
Jang Pyo Bae ◽  
Jun-Won Chung ◽  
Dong Kyun Park ◽  
Kwang Gi Kim ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Transfer Learning ◽  
Test Data ◽  
State Of The Art ◽  
Early Stage ◽  
Statistical Significance ◽  
Recall Rate ◽  
Training Data ◽  
Fine Tuning ◽  
Accuracy Evaluation

AbstractWhile colorectal cancer is known to occur in the gastrointestinal tract. It is the third most common form of cancer of 27 major types of cancer in South Korea and worldwide. Colorectal polyps are known to increase the potential of developing colorectal cancer. Detected polyps need to be resected to reduce the risk of developing cancer. This research improved the performance of polyp classification through the fine-tuning of Network-in-Network (NIN) after applying a pre-trained model of the ImageNet database. Random shuffling is performed 20 times on 1000 colonoscopy images. Each set of data are divided into 800 images of training data and 200 images of test data. An accuracy evaluation is performed on 200 images of test data in 20 experiments. Three compared methods were constructed from AlexNet by transferring the weights trained by three different state-of-the-art databases. A normal AlexNet based method without transfer learning was also compared. The accuracy of the proposed method was higher in statistical significance than the accuracy of four other state-of-the-art methods, and showed an 18.9% improvement over the normal AlexNet based method. The area under the curve was approximately 0.930 ± 0.020, and the recall rate was 0.929 ± 0.029. An automatic algorithm can assist endoscopists in identifying polyps that are adenomatous by considering a high recall rate and accuracy. This system can enable the timely resection of polyps at an early stage.

scholarly journals Enhanced Wastewater Treatment by Immobilized Enzymes

2021 ◽  
Author(s):  
Jakub Zdarta ◽  
Katarzyna Jankowska ◽  
Karolina Bachosz ◽  
Oliwia Degórska ◽  
Karolina Kaźmierczak ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Process Optimization ◽  
Organic Pollutants ◽  
Large Scale ◽  
Removal Rate ◽  
Immobilized Enzymes ◽  
Future Research ◽  
Process Conditions ◽  
Removal Rates ◽  
Catalytic Cycles

Abstract Purpose of Review In the presented review, we have summarized recent achievements on the use of immobilized oxidoreductases for biodegradation of hazardous organic pollutants including mainly dyes, pharmaceuticals, phenols, and bisphenols. In order to facilitate process optimization and achievement of high removal rates, effect of various process conditions on biodegradation has been highlighted and discussed. Recent Findings Current reports clearly show that immobilized oxidoreductases are capable of efficient conversion of organic pollutants, usually reaching over 90% of removal rate. Further, immobilized enzymes showed great recyclability potential, allowing their reuse in numerous of catalytic cycles. Summary Collected data clearly indicates immobilized oxidoreductases as an efficient biocatalytic tools for removal of hazardous phenolic compounds, making them a promising option for future water purification. Data shows, however, that both immobilization and biodegradation conditions affect conversion efficiency; therefore, process optimization is required to achieve high removal rates. Nevertheless, we have demonstrated future trends and highlighted several issues that have to be solved in the near-future research, to facilitate large-scale application of the immobilized oxidoreductases in wastewater treatment.

Lubricant Removal, Degradation, and Recovery on Particulate Magnetic Recording Media

1992 ◽  
Vol 114 (1) ◽  
pp. 61-67 ◽  
Author(s):  
V. J. Novotny ◽  
T. E. Karis ◽  
N. W. Johnson
Keyword(s):  
Bulk Viscosity ◽  
Magnetic Recording ◽  
Photoelectron Spectroscopy ◽  
Removal Rate ◽  
Lateral Diffusion ◽  
Recording Media ◽  
Magnetic Recording Media ◽  
Removal Rates ◽  
Linear Chains ◽  
Mechanical Durability

Lubrication of particulate magnetic recording media improves their mechanical durability in sliding and flying by several orders of magnitude compared with unlubricated media. Lubricant removal, degradation, and recovery were studied using microslit scanning Fourier transform infrared spectroscopy and microspot scanning X-ray photoelectron spectroscopy. These techniques measure the total and surface lubricant amounts in the porous film, respectively. Lubricant dynamics were compared for two physisorbed polyperfluoroalkylether lubricants of similar molecular weight but different molecular structure—Y with a CF3 side group and Z with linear chains. The bulk viscosity of Y was about ten times higher than the viscosity of Z. In sliding, the lubricant removal rate of Y was significantly higher than that of Z while in flying the removal rates were reversed. Removal rates in sliding were orders of magnitude higher than those in flying. Effective lateral diffusion coefficients estimated from the rate of lubricant reflow back to the depleted tracks were close to inversely proportional to the bulk viscosity. During sliding and flying both lubricants degraded as evidenced by chemically altered lubricant detected on the surfaces after dissolution of undegraded lubricant.

Mechanisms of High Efficiency and Stabilization of Baffled Constructed Wetland in Treatment of Domestic Sewage

2013 ◽  
Vol 295-298 ◽  
pp. 1057-1061 ◽  
Author(s):  
Chang Bing Ye ◽  
Zhi Ming Zhou ◽  
Ke Zhao ◽  
Qin Liu
Keyword(s):  
Constructed Wetland ◽  
Removal Rate ◽  
Short Circuit ◽  
Domestic Sewage ◽  
Wetland Plants ◽  
Stable Operation ◽  
Removal Rates ◽  
Operational Life ◽  
High Efficient ◽  
Hydraulic Load

To solve the problem of short-circuit of individual current constructed wetland, a baffled constructed wetland was designed and applied to treat domestic sewage by our research group. The wetland plants were composed of Eichhormia crassipes, Oenanthe javanica, Cyperusalternifolius, Phragmites communis and Aquatic. The results of 18 month indicated that the optimal hydraulic load of baffled constructed wetland was 2.0~2.2 m3/(m2•d). At the hydraulic load of 2.0m3/(m2•d), the COD, TN and TP removal rates of baffled constructed wetland could be over 76.40%, 76.12%, 65.37%, respectively, at 24°C. When the temperature decreased to 12°C, the COD, TN, TP removal rates of system decreased to 67.56%、62.75% and 61.33%, respectively; The SS removal rate of the first 6 compartments was about 79.5% and that of system could maintain 87.18% during the operation of system. Based on the results of trial, the mechanisms of extending the baffled constructed wetland's operational life was owed to high efficient SS removal rate of the first 6 compartments which was used as constructed wetland and anaerobic baffled reactor (ABR). As a result, the long-term stable operation of system in treatment of domestic sewage was explained with extending about 5 times service life than that of individual current constructed wetland. The mechanisms of higher efficiency of baffled constructed wetland in treatment of domestic sewage were owed to the longer flow line of system and the up-down flow of domestic sewage makes pollutant more intimate contact with roots of wetland plants.

Updating Finite Element Model of Combined Structures on the Basis of Dynamic Test Results

1996 ◽  
Author(s):  
Chen Xin ◽  
Qin Ye ◽  
Yuan Xiguang ◽  
Zhang Ping ◽  
Sun Jian
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Test Data ◽  
Dynamic Test ◽  
Element Model ◽  
Physical Parameters ◽  
Structural Joint ◽  
Combined Structure ◽  
Joint Parameters ◽  
Two Stages

Abstract According to the real situation, a new method of updating the finite element model (FEM) of a combined structure step by step is proposed in this paper. It is assumed that there are two types of error when establishing the FEMs. One of them results from the simplifications, in fact, it is severe for complicated structures, which usually assume many simplifications; the other is from the process of identifying structural joint parameters. For this reason, it is recommended that the FEM should be established in two stages. At the first stage, the local physical parameters relating with the simplifications are corrected by using the dynamic test data of the corresponding substructures. Then, the structural joint parameters that link the substructures are corrected by the dynamic test data of the combined structure as a whole. The updating formula is presented and proved, and its algorithm is also described. And the experimental results show that the efficiency and accuracy of the proposed method are quite satisfactory.

Improved Training for Machine Learning: The Additional Potential of Innovative Algorithmic Approaches.

2021 ◽  
Author(s):  
Octavian Dumitru ◽  
Gottfried Schwarz ◽  
Mihai Datcu ◽  
Dongyang Ao ◽  
Zhongling Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Test Data ◽  
Satellite Images ◽  
Training Data ◽  
Data Selection ◽  
Generative Adversarial Networks ◽  
Radar Images ◽  
Basic Work ◽  
Selection Of

<p>During the last years, much progress has been reached with machine learning algorithms. Among the typical application fields of machine learning are many technical and commercial applications as well as Earth science analyses, where most often indirect and distorted detector data have to be converted to well-calibrated scientific data that are a prerequisite for a correct understanding of the desired physical quantities and their relationships.</p><p>However, the provision of sufficient calibrated data is not enough for the testing, training, and routine processing of most machine learning applications. In principle, one also needs a clear strategy for the selection of necessary and useful training data and an easily understandable quality control of the finally desired parameters.</p><p>At a first glance, one could guess that this problem could be solved by a careful selection of representative test data covering many typical cases as well as some counterexamples. Then these test data can be used for the training of the internal parameters of a machine learning application. At a second glance, however, many researchers found out that a simple stacking up of plain examples is not the best choice for many scientific applications.</p><p>To get improved machine learning results, we concentrated on the analysis of satellite images depicting the Earth’s surface under various conditions such as the selected instrument type, spectral bands, and spatial resolution. In our case, such data are routinely provided by the freely accessible European Sentinel satellite products (e.g., Sentinel-1, and Sentinel-2). Our basic work then included investigations of how some additional processing steps – to be linked with the selected training data – can provide better machine learning results.</p><p>To this end, we analysed and compared three different approaches to find out machine learning strategies for the joint selection and processing of training data for our Earth observation images:</p><ul><li>One can optimize the training data selection by adapting the data selection to the specific instrument, target, and application characteristics [1].</li> <li>As an alternative, one can dynamically generate new training parameters by Generative Adversarial Networks. This is comparable to the role of a sparring partner in boxing [2].</li> <li>One can also use a hybrid semi-supervised approach for Synthetic Aperture Radar images with limited labelled data. The method is split in: polarimetric scattering classification, topic modelling for scattering labels, unsupervised constraint learning, and supervised label prediction with constraints [3].</li> </ul><p>We applied these strategies in the ExtremeEarth sea-ice monitoring project (http://earthanalytics.eu/). As a result, we can demonstrate for which application cases these three strategies will provide a promising alternative to a simple conventional selection of available training data.</p><p>[1] C.O. Dumitru et. al, “Understanding Satellite Images: A Data Mining Module for Sentinel Images”, Big Earth Data, 2020, 4(4), pp. 367-408.</p><p>[2] D. Ao et. al., “Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X”, Remote Sensing, 2018, 10(10), pp. 1-23.</p><p>[3] Z. Huang, et. al., "HDEC-TFA: An Unsupervised Learning Approach for Discovering Physical Scattering Properties of Single-Polarized SAR Images", IEEE Transactions on Geoscience and Remote Sensing, 2020, pp.1-18.</p>

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